Online and Distance Learning: Concepts, Methodologies, Tools and Applications [6 vols., 1 ed.] 159904935X, 9781599049359

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Online and Distance Learning:

Concepts, Methodologies, Tools, and Applications Lawrence Tomei Robert Morris University, USA

Volume I

Information Science reference Hershey • New York

Assistant Executive Editor: Acquisitions Editor: Development Editor: Senior Managing Editor: Managing Editor: Typesetter: Cover Design: Printed at:

Meg Stocking Kristin Klinger Kristin Roth Jennifer Neidig Sara Reed Sharon Berger, Jennifer Neidig, Sara Reed, Laurie Ridge, Jamie Snavely, Michael Brehm, Elizabeth Duke, and Diane Huskinson Lisa Tosheff Yurchak Printing Inc.

Published in the United States of America by Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue, Suite 200 Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-pub.com/reference and in the United Kingdom by Information Science Reference (an imprint of IGI Global) 3 Henrietta Street Covent Garden London WC2E 8LU Tel: 44 20 7240 0856 Fax: 44 20 7379 0609 Web site: http://www.eurospanonline.com Copyright © 2008 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Online and distance learning : concepts, methodologies, tools, and applications / Lawrence Tomei, editor. p. cm. Summary: "This comprehensive, six-volume collection addresses all aspects of online and distance learning, including information communication technologies applied to education, virtual classrooms, pedagogical systems, Web-based learning, library information systems, virtual universities, and more. It enables libraries to provide a foundational reference to meet the information needs of researchers, educators, practitioners, administrators, and other stakeholders in online and distance learning"--Provided by publisher. Includes bibliographical references and index. ISBN 978-1-59904-935-9 (hardcover) -- ISBN 978-1-59904-936-6 (ebook) 1. Distance education--United States. I. Tomei, Lawrence A. LC5805.O55 2007 371.350973--dc22 2007023793 British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library.

Associate Editors

Steve Clarke University of Hull, UK San Diego State University, USA Annie Becker Florida Institute of Technology USA Ari-Veikko Anttiroiko University of Tampere, Finland

Editorial Advisory Board

Sherif Kamel American University in Cairo, Egypt In Lee Western Illinois University, USA Jerzy Kisielnicki Warsaw University, Poland Keng Siau University of Nebraska-Lincoln, USA Amar Gupta Arizona University, USA Craig van Slyke University of Central Florida, USA John Wang Montclair State University, USA Vishanth Weerakkody Brunel University, UK

List of Contributors

Aalderink, M.W. (Wijnand) / Windesheim University for Professional Education, The Netherlands ....................................................................................................................................... 2069 Aaron, Bruce / Accenture, USA ....................................................................................................... 3416 Abdel-Hamid, Ayman / Old Dominion University, USA .................................................................. 924 Abdel-Wahab, Hussein / Old Dominion University, USA ................................................................ 924 Abel, Marie-Hélène / University of Technology of Compiègne, France . ....................................... 1794 Abrahamson, Louis / The Better Education Foundation, USA .......................................................... 78 Abresch, John / University of South Florida . ................................................................................. 1714 Adams, Lindsay / Cyber Charter School, USA ................................................................................. 309 Addicott, Kimberly / North Dakota State University, USA ............................................................ 2000 Adkins, Mac / Troy State University Montgomery, USA ................................................................... 257 Aggarwal, A.K. / University of Baltimore, USA .............................................................................. 2784 Agosti, Giorgio / ABB Process, Solutions & Services, Italy .............................................................. 388 Ahuja, Manju / Indiana University, USA........................................................................................... 519 Alexander, Bryan / Middlebury College, USA . .............................................................................. 3549 Allert, Heidrun / University of Hannover, Germany . ..................................................................... 3028 Angeli, Charoula / University of Cyprus, Cyprus ........................................................................... 3251 April, Kurt / University of Cape Town, South Africa ...................................................................... 1178 Armani, Jacopo / Università della Svizzera italiana, Switzerland ................................................... 852 Arthur-Gray, Heather / Griffith University, Australia ................................................................... 2852 Asher, Gregg / St. Cloud State University, USA ................................................................................ 773 Askar, Petek / Hacettepe University, Turkey ......................................................................... 2258, 2610 Aurum, Aybüke / The University of New South Wales, Australia . ................................................. 2234 Aworuwa, Bosede / Texas A&M University-Texarkana, USA ......................................................... 2596 Ball, Dwayne A. / University of Nebraska-Lincoln, USA ................................................................ 2929 Banerji, Ashok / Monisha Electronic Education Trust, Calcutta . .................................................. 2452 Barak, Miri / Massachusetts Institute of Technology, USA ............................................................. 2435 Barbanell, Patricia / Project VIEW, USA . ...................................................................................... 1828 Barker, Sandra / University of South Australia, Australia ............................................................. 2886 Barki, Henri / HEC Montréal, Canada.............................................................................................. 101 Barolli, Leonard / Fukuoka Institute of Technology, Japan ............................................................ 1344 Barrera, Luis / Cesar Vallejo University, Spain .............................................................................. 2602 Barriocanal, Elena García / University of Alcalá, Spain ............................................................... 3401 Bartlett, Andrea / University of Hawaii at Manoa, USA ................................................................ 2049 Barton, Karen / CTB/McGraw-Hill, USA ....................................................................................... 3490

Basu, Saswata / Monisha Electronic Education Trust, India .......................................................... 2452 Batra, Raj / Stanford University, USA ............................................................................................. 2400 Bax, Samantha / Murdoch University, Australia .............................................................................. 201 Beck, Charles E. / University of Colorado at Colorado Springs, USA . ........................................... 716 Becker, Katrin / University of Calgary, Canada . ............................................................................. 357 Becker, Kirk / University of Illinois and Promissor, USA.................................................................. 442 Beedle, Jonathan B. / University of Southern Mississippi and Mississippi State University, USA........................................................................................................................ 1848, 2115 Beers, Maggie / British Columbia Institute of Technology, Canada ............................................... 2702 Behrens, John T. / Cisco Systems, USA .......................................................................................... 2581 Bellavance, François / HEC Montréal, Canada................................................................................. 101 Benrud, Erik / American University, USA ...................................................................................... 3285 Berg, Gary A. / California State University Channel Islands, USA . ............................ 595, 2826, 2976 Berge, Zane L. / University of Maryland, USA ............................................................................... 2979 Bevan, Bronwyn / Exploratorium, USA .......................................................................................... 1259 Bishop, Judith / University of Pretoria, South Africa ..................................................................... 1178 Bjornson, Eric / Stanford University, USA . .................................................................................... 2400 Blandin, Bernard / CESI SAS, France............................................................................................... 475 Bochicchio, Mario / University of Lecce, Italy . .............................................................................. 1402 Bodomo, Adams / The University of Hong Kong, Hong Kong ......................................................... 693 Boechler, Patricia M. / University of Alberta, Canada ......................................................... 1199, 3280 Boettcher, Judith V. / Designing for Learning and the University of Florida, USA . ..................... 1763 Bonk, Curtis J. / Indiana University, USA............................................................. 536, 704, 1004, 3385 Borland, Steve / Temple University Health Systems, USA .............................................................. 2272 Botturi, Luca / Università della Svizzera italiana and University of Lugano, Switzerland . .. 852, 1014 Boyd, Rosangela K. / Temple University, USA . .............................................................................. 1219 Boyd, Gary Mcl. / Concordia University, Canada............................................................................. 174 Bradley, Bryan D. / Brigham Young University, USA . ................................................................... 2356 Braga de Vasconcelos, José / Universidade Fernando Pessoa, Portugal ...................................... 2744 Brandon, Daniel / Christian Brothers University, USA ........................................................ 2042, 2833 Brandt, D. Scott / Purdue University, USA ....................................................................................... 580 Breda, Ana M. / University of Aveiro, Portugal .............................................................................. 1307 Breithaupt, Krista / American Institute for CPAs, USA . ................................................................ 1165 Brescia, William F. / University of Arkansas, USA ......................................................................... 2130 Britto, Marwin / Central Washington University, USA . ................................................................. 1281 Broberg, Anders / Umeå University, Sweden . ................................................................................ 1551 Brooks, Lloyd D. / The University of Memphis, USA ..................................................................... 1537 Buchanan, Elizabeth / University of Wisconsin - Milwaukee, USA ............................................... 1843 Buche, Cédric / CERV/ENIB, France . ............................................................................................ 1137 Burgess, Stephen / Victoria University, Australia ................................................................. 1049, 2918 Burgstahler, Sheryl / University of Washington, USA .................................................................... 1077 Burgsteiner, Harald / Graz University of Applied Sciences, Austria . ............................................ 1744 Burjaw, Rick / University of Western Ontario, Canada..................................................................... 528 Burke, Merilyn / University of South Florida, USA ....................................................................... 3484 Campbell, John / University of Canberra, Australia ...................................................................... 2852 Campbell, Katy / University of Alberta, Canada ............................................................................ 1422

Cantoni, Lorenzo / University of Lugano, Switzerland .................................................................. 1014 Carayon, Pascale / University of Wisconsin-Madison, USA ........................................................... 3224 Carr, Peter / Athabasca University, Canada ................................................................................... 1384 Carroll, John M. / The Pennsylvania State University, USA .......................................................... 2895 Castillo, Gladys / University of Aveiro, Portugal ............................................................................ 1307 Catrysse, Peter / Stanford University, USA ..................................................................................... 2400 Catterick, David / University of Dundee, Scotland . ....................................................................... 3035 Cavanaugh, Cathy / University of North Florida, USA . .................................................................. 686 Cercone, Kathleen / Housatonic Community College, USA ............................................................. 453 Champagne, Matthew V. / IOTA Solutions, USA ........................................................................... 1004 Chan, Hock Chuan / National University of Singapore, Singapore ............................................... 1496 Chang, Yao-Chung / National Dong Hwa University, Taiwan, ROC ............................................. 1661 Chao, Han-Chieh / National Dong Hwa University, Taiwan, ROC . .............................................. 1661 Chavez, Todd / Tampa Library at the University of South Florida-Tampa, USA ........................... 3465 Chen, Charlie / Appalachian State University, USA ....................................................................... 1689 Chen, Irene / University of Houston Downtown, USA ...................................................................... 562 Chen, Jiann-Liang / National Dong Hwa University, Taiwan, ROC............................................... 1661 Chen, Sherry Y. / Brunel University, UK ........................................................................................ 1740 Chen, Weiqin / University of Bergen, Norway ................................................................................ 1105 Cheung, B.S.N. / The University of Hong Kong, Hong Kong ......................................................... 1205 Chevaillier, Piere / CERV/ENIB, France ........................................................................................ 1137 Ching, Hsianghoo Steve / City University of Hong Kong, Hong Kong .......................................... 2215 Chu, Kin Cheong / Hong Kong Institute of Vocational Education, Hong Kong .............................. 943 Cirrincione, Armando / SDA Bocconi School of Management, Italy . ........................................... 1752 Clarebout, Geraldine / University of Leuven, Belgium .................................................................. 3359 Clayton, John F. / Waikato Institute of Technology, New Zealand . ................................................ 1417 Cleveland-Innes, Martha / Athabasca University, Canada ........................................................... 1814 Coffey, John W. / The University of West Florida, USA ................................................................... 971 Cohn, Ellen / University of Pittsburgh, USA ................................................................................... 3020 Collins, Brian P. / Michigan State University, USA ........................................................................ 1903 Collison, Tara A. / Cisco Systems, USA . ......................................................................................... 2581 Connolly, Patrick E. / Purdue University, USA ................................................................................ 252 Corbitt, Brian / RMIT University, Australia ..................................................................................... 905 Correia, Ana Maria R. / Universidade Nova de Lisboa and Instituto Nacional de Engenharia, Technologia e Inovação, Portugal ...................................................................................................... 618 Cristea, Alexandra I. / Eindhoven University of Technology, The Netherlands ............................. 1504 Dan-Gur, Yuval / University of Haifa Mt. Carmel, Israel and University of Saskatchewan, Canada . .................................................................................................................................. 1186, 2435 Daniel, Ben K. / University of Saskatchewan, Canada ................................................................... 1186 Daniels, Lisa M. / North Dakota State University, USA . ................................................................ 2000 Darbyshire, Paul / Victoria University, Australia ................................................................. 1049, 2918 Davis, Donald D. / Old Dominion University, USA . ....................................................................... 3140 Day, John / Ohio University, USA ..................................................................................................... 382 De Loor, Pierre / CERV/ENIB, France ........................................................................................... 1137 Debenham, Margaret / Consultant, UK ......................................................................................... 3241 Dell, Laura A.B. / Public Library of Cincinnati & Hamilton County, USA ...................................... 506

DeLoatch, Sandra J. / Norfolk State University, USA.................................................................... 3140 DeMark, Sarah / Cisco Systems, USA . ........................................................................................... 2581 Dennis, Alan R. / Indiana University, USA ....................................................................................... 101 Depickere, Arnold / Murdoch University, Australia ....................................................................... 1976 DeRosa, Darleen M. / Right Management Consultants, USA ......................................................... 1546 Dewever, Fanuel / IBM, Belgium . ..................................................................................................... 180 Dexter, Sara / University of Virginia, USA .................................................................................. 1, 1939 Diamadis, Efstratios T. / Athens University of Economics and Business, Greece . .......................... 677 Diaz, Veronica / The University of Arizona, USA .............................................................................. 875 Dierking, Lynn D. / Institute for Learning Innovation, USA .......................................................... 2416 Discenza, Richard / University of Colorado at Colorado Springs, USA .............................. 8, 45, 3370 Dixon, Michael / Murdoch University, Australia .................................................................. 2775, 3119 Donnelly, Roisin / Dublin Institute of Technology, Ireland ............................................................... 162 Dooley, Kim E. / Texas A&M University, USA ................................................................................ 3365 Downey, Heather J. / Old Dominion University, USA .................................................................... 3140 Economides, Anastasios A. / University of Macedonia, Greece . ..................................................... 220 Edmundson, Andrea L. / CARF International, USA ...................................................................... 2484 Efendioglu, Alev M. / University of San Francisco, USA ............................................................... 2181 Elbert, Chanda / Texas A&M University, USA ............................................................................... 3365 Elen, Jan / University of Leuven, Belgium . ..................................................................................... 3359 Etter, Stephanie J. / Aloysius College, USA . .................................................................................. 2224 Falco, John / College of Saint Rose, USA . ...................................................................................... 1828 Fan, Jing Ping / Brunel University, UK . ........................................................................................... 278 Fanning, Elizabeth / The University of Virginia, USA .................................................................... 1870 Farag, Waleed / Old Dominion University, USA . ............................................................................. 924 Fernando, Shantha / University of Moratuwa, Sri Lanka .............................................................. 1880 Fiore, Nicola / University of Lecce, Italy ......................................................................................... 1402 Fisher, Allan / iCarnegie, Inc., USA ................................................................................................ 3588 Fodchuk, Katherine M. / Old Dominion University, USA ............................................................. 3140 Fox, Brian F. / Santa Fe Community College, USA ........................................................................ 2061 Frank, Jonathan / Suffolk University, USA ..................................................................................... 2325 Frey, Barbara A. / University of Pittsburgh, USA . ......................................................................... 3020 Fu, Hongguang / Chinese Academy of Sciences, China . ................................................................ 1373 Fujii, Norihiro / Hosei University, Japan . ...................................................................................... 1028 Furtado, Elizabeth / Universidade de Fortaleza, Brazil ................................................................ 1070 Furtado, Vasco / University of Fortaleza, Brazil ............................................................................ 3321 Fustos, Janos / Metropolitan State College of Denver, USA ............................................................... 55 Gadish, David / California State University-Los Angeles, USA . .................................................... 2968 Gallupe, Brent / Queen’s University, Canada ................................................................................... 101 Gama, João / University of Porto, Portugal . .................................................................................. 1307 Gardiner, Adrian / The University of New South Wales, Australia ................................................ 2234 Garland, Virginia E. / The University of New Hampshire, USA .................................................... 1624 Garrison, Randy / University of Calgary, Canada ......................................................................... 1814 Garten, Edward D. / University of Dayton, USA . .......................................................................... 3073 Geller, James / New Jersey Institute of Technology, USA ................................................................. 664 Genone, Sara / Università Cattaneo–LIUC, Italy ........................................................................... 3513

Gerber, R. / University of New England, Australia ......................................................................... 2205 Ghanem, Sahar / Old Dominion University, USA . ........................................................................... 924 Ghaoui, Claude / Liverpool John Moores University, UK ........................................................ 35, 2624 Gibson, David / CurveShift, USA .................................................................................................... 3595 Giles, Lenora / University of Baltimore, USA ................................................................................. 2979 Giorgi, Chiara / Università della Svizzera Italiana (USI), Switzerland . ........................................ 2086 Göbel, Stefan / ZGDV e.V. ­– Computer Graphics Center, Darmstadt, Germany . .......................... 1439 Golann, Bret / University of Maine, USA ........................................................................................ 2902 Goldman, Kathryn Haley / Institute for Learning Innovation, USA . ............................................ 2416 Grackin, Janice A. / State University of New York at Stony Brook, USA . .......................................... 20 Grasso, Floriana / Liverpool University, UK .................................................................................. 2617 Gregory, Vicki L. / University of South Florida, USA .................................................................... 3508 Hagenhoff, Svenja / Georg-August University Goettingen, Germany ............................................ 2871 Hakkarainen, Kai / University of Helsinki, Finland . ..................................................................... 3149 Halıcı, Ugur / Middle East Technical University, Turkey ................................................................ 2258 Haller, Michael / Upper Austria University of Applied Sciences, Austria ...................................... 1600 Handzic, Meliha / The University of New South Wales, Australia .................................................. 2234 Hansen, Eric G. / Educational Testing Service (ETS), Princeton, USA .......................................... 2532 Hanson, Ardis / University of South Florida, USA ......................................................................... 3484 Hantula, Donald A. / Temple University, USA ................................................................................ 1546 Harapnuik, Dwayne / University of Alberta, Canada .................................................................... 3047 Hatzilygeroudis, Ioannis / University of Patras and Research Academic Computer Technology Institute, Greece ................................................................................................................................ 1888 Haughey, Margaret / University of Alberta, Canada ..................................................................... 2344 Hayne, Stephen C. / Colorado State University, USA ...................................................................... 601 Hazari, Sunil / State University of West Georgia, USA ................................................................... 2952 Helin, Heikki / TeliaSonera, Finland . ............................................................................................. 1084 Herring, Susan C. / Indiana University, USA ................................................................................... 519 Herrington, Anthony / University of Wollongong, Australia ............................................................. 68 Herrington, Jan / University of Wollongong, Australia ...................................................................... 68 Hesselink, Lambertus / Stanford University, USA . ........................................................................ 2400 Hewett, Stephenie M. / The Citadel, The Military College of South Carolina, USA . .................... 3200 Hilmer, Kelly McNamara / University of Tampa, USA .................................................................... 101 Hilton, June K. / Jurupa Valley High School, USA ......................................................................... 2385 Hin, Leo Tan Wee / Nanyang Technological University, Singapore ............................................... 2121 Hipsky, Shellie / Robert Morris University, USA .............................................................................. 309 Hoffmann, Anja / ZGDV e.V. ­– Computer Graphics Center, Darmstadt, Germany ....................... 1439 Holt, Dale / Deakin University, Australia .......................................................................................... 905 Holzinger, Andreas / Medical University Graz, Austria ................................................................. 1774 Hoonakker, Peter / University of Wisconsin-Madison, USA . ......................................................... 3224 Horowitz, Harold M. / Socratec, Inc., USA .................................................................................... 2997 Houser, Chris / Kinjo Gakuin University, Japan . ............................................................................. 127 Howard, Caroline / Touro University International and Techknowledge-E Systems, USA .. 8, 45, 3370 Howell, Scott L. / Brigham Young University, USA ...................................................... 300, 2514, 3577 Hricko, Mary / Kent State University—Geauga, USA ...................................................................... 756 Huang, Yi-Ping / University of Maryland, USA .............................................................................. 2163

Huber, Mark / University of Georgia, USA . ..................................................................................... 101 Hui, L.C.K. / The University of Hong Kong, Hong Kong ............................................................... 1205 Hung, Jason C. / Northern Taiwan Institute of Science and Technology, Taiwan . ......................... 3500 Hunter, M. Gordon / The University of Lethbridge, Canada ......................................................... 1384 Hurtado, Ma José Rubio / University of Barcelona, Spain . ............................................................ 589 Inan, Fethi Ahmet / The University of Memphis, USA ..................................................................... 805 Iurgel, Ido / ZGDV e.V. ­– Computer Graphics Center, Darmstadt, Germany . ............................... 1439 Jackson, Nikki L. / Norfolk State University, USA ......................................................................... 3140 Jamison, Jennifer R. / Murdoch University, Australia ................................................................... 2264 Janvier, W.M. / Liverpool John Moores University, UK ..................................................................... 35 Jedrzejowicz, Joanna / University of Gdansk, Poland ................................................................... 1056 Jennings, Morgan M. / Metropolitan State College of Denver, USA ................................................. 55 Johnstone, Douglas B. / Western Governors University, USA ........................................................ 2377 Johnstone, Sally M. / Western Cooperative for Educational Telecommunications, USA ............... 1754 Jones, Nory B. / University of Maine, USA ..................................................................................... 2902 Jorge, J. / Instituto Superior Técnico, Portugal .............................................................................. 2624 Junginger, Markus / University of Missouri-Kansas City, USA ....................................................... 664 Kabene, Stefane M. / University of Western Ontario, Canada ......................................................... 528 Kacsuk, Péter / Hungarian Academy of Sciences, Hungary ........................................................... 1569 Kamel, Sherif / The American University in Cairo, Egypt . ............................................................ 2369 Karoulis, Athanasis / Aristotle University of Thessaloniki, Greece . .............................................. 1782 Karpouzis, Kostas / National Technical University of Athens, Greece . ......................................... 1950 Kayama, Mizue / Senshu University, Japan . .................................................................................... 726 Keppell, Mike / Hong Kong Institute of Education, Hong Kong .................................................... 2568 Khek, Claire / National University of Singapore, Singapore .......................................................... 2497 Kimble, Chris / University of York, UK . ......................................................................................... 2744 Kinsel, Ellen / Odyssey Learning Systems, Canada ........................................................................ 1814 Kinshuk / Massey University, New Zealand .................................................................................... 2520 Kinuthia, Wanjira / Georgia State University, USA ....................................................................... 3234 Klobas, Jane E. / Bocconi University, Italy and the University of Western Australia, Australia . .. 1991 Knust, Michaela / Georg-August University Goettingen, Germany ............................................... 2871 Kock, Ned / Texas A&M International University, USA . ................................................................ 2863 Koike, Nobuhiko / Hosei University, Japan . .................................................................................. 1028 Komathy, K. / Anna University, India ............................................................................................. 1205 Kovačić, Zlatko J. / The Open Polytechnic of New Zealand, New Zealand ..................................... 136 Koyama, Akio / Yamagata University, Japan . ................................................................................ 1344 Kunii, Tosiyasu L. / IT Institute of Kanazawa Institute of Technology, Japan ............................... 1028 Kwok, L. K. / The University of Hong Kong, Hong Kong .............................................................. 1205 Ladyshewsky, Richard / Curtin University of Technology, Australia ............................................ 2958 Lakkala, Minna / University of Helsinki, Finland .......................................................................... 3144 Lammintakanen, Johanna / University of Kuopio, Finland .......................................................... 1252 Lang, Gaye / Houston Independent School District, USA ................................................................. 426 Lateh, Habibah / University of Science, Malaysia, Malaysia . ....................................................... 2636 Laukkanen, Mikko / TeliaSonera, Finland . ................................................................................... 1084 Laws, R. Dwight / Brigham Young University, USA ......................................................................... 300 Leduc, Raymond / University of Western Ontario, Canada ............................................................. 528

Lee, Doris / Pennsylvania State University, USA ............................................................................ 2272 Lee, J. K. W. / University of Hong Kong, Hong Kong .................................................................... 1205 Lee, Jim / CTB/McGraw-Hill, USA ................................................................................................. 3490 Lee, Ji-Yeon / The University of South Carolina, USA . .................................................................... 536 Lee, Seung-hee / Indiana University, USA ...................................................................................... 3385 Lee, Yugyung / University of Missouri-Kansas City, USA ................................................................ 664 Leng, Paul / Liverpool University, UK ............................................................................................ 2617 Lepori, Benedetto / University of Lugano, Switzerland . ................................................................ 1014 Lesht, Faye L. / University of Illinois at Urbana-Champaign, USA ............................................... 2676 Leung, Kenneth / The University of Hong Kong, Hong Kong ........................................................ 1205 Levin, Bruce Lubotsky / University of South Florida, USA . ......................................................... 3484 Levy, Yair / Nova Southeastern University, USA ..................................................................... 265, 2693 Lewis, Marilyn / The University of West Indies, Trinidad and Tobago . ......................................... 2080 Li, Qing / City University of Hong Kong, Hong Kong .................................................................... 3500 Li, Wei / Chinese Academy of Sciences, China . .............................................................................. 1373 Li, Yuan-chao / China University of Petroleum, P.R. China ........................................................... 1724 Lim, Byung-Ro / Kyung Hee University, South Korea . .................................................................. 3309 Lim, John / National University of Singapore, Singapore .............................................................. 2497 Lin, M.T. / National Dong Hwa University, Taiwan, ROC . ............................................................ 1661 Lindberg, J. Ola / Mid Sweden University, Sweden . ...................................................................... 3157 Lindner, James R. / Texas A&M University, USA . ......................................................................... 3365 Lindsay, Nathan K. / University of Michigan, USA . .............................................................. 300, 3577 Liu, Leping / University of Nevada, Reno, USA ................................................................................ 956 Liu, Xiaojing / Indiana University, USA ......................................................................................... 3385 Liyanage, Shantha / The University of Auckland, New Zealand .................................................... 2716 Long, Phil / Information Services and Technology, USA . ............................................................... 3433 Lou, Hao / Ohio University, USA . ..................................................................................................... 382 Love, Kristina / The University of Melbourne, Australia ............................................................... 2461 Lowry, Glenn / United Arab Emirates University, UAE ................................................................. 2791 Lowther, Deborah L. / The University of Memphis, USA . ............................................................... 805 Lowyck, Joost / University of Leuven, Belgium .............................................................................. 3359 Lytras, Miltiadis D. / Athens University of Economics and Business, Greece ............................... 1362 Ma, Xueguang / University of Maryland, USA ................................................................................. 776 MacDonald, Colla J. / University of Ottawa, Canada .................................................................... 1165 MacGregor, Bonnie L. / Bryant & Stratton College, USA ............................................................. 1410 Macredie, Robert D. / Brunel University, UK .................................................................................. 278 Maglogiannis, Ilias / University of the Aegean, Greece .................................................................. 1950 Maindiratta, Y. R. / Datamation Foundation Charitable Trust, India ............................................. 512 Major, Debra A. / Old Dominion University, USA . ........................................................................ 3140 Mallach, Efrem G. / University of Massachusetts Dartmouth, USA ................................................ 329 Maly, Kurt / Old Dominion University, USA .................................................................................... 924 Maresch, Helfrid / Graz University of Applied Sciences, Austria .................................................. 1774 Margolis, Jane / University of California Los Angeles, USA .......................................................... 3588 Mari, Cecilia / Università Cattaneo – LIUC, Italy .......................................................................... 3513 Mari, Luca / Università Cattaneo – LIUC, Italy ............................................................................. 3513 Marold, Kathryn A. / Metropolitan State College of Denver, USA .................................................. 647

Marr, Bernard / University of St. Augustine for Health Services, USA ............................................ 257 Marshall, Kevin / Trinity College, Dublin, Ireland . ....................................................................... 2138 Martz, Jr., Wm. Benjamin / University of Colorado at Colorado Springs, USA ................ 2768, 3272 Maser, Kathryn J. / Booz Allen Hamilton, USA ............................................................................. 3293 Masters, James S. / University of North Carolina at Greensboro and Promissor, USA ................... 442 Masterson-Smith, Julie / Manor Intermediate School, Honeoye Falls-Lima School District, New York, USA .......................................................................................................................................... 1655 Mawhinney, Charles H. / Metropolitan State College of Denver, USA . ............................................ 55 McClean, Phil / North Dakota State University, USA ..................................................................... 2000 McGee, Patricia / The University of Texas at San Antonio, USA ...................................................... 875 McGill, Tanya / Murdoch University, Australia .................................................. 201, 1976, 2775, 3119 McNair, Victor / University of Ulster, Northern Ireland ................................................................. 2138 McNaught, Carmel / The Chinese University of Hong Kong, Hong Kong .................................... 2215 Meert, Shannon K. / Old Dominion University, USA ..................................................................... 3140 Merhout, Jeffrey W. / Miami University, USA . .............................................................................. 2224 Metcalfe, Amy Scott / University of Arizona, USA ......................................................................... 1909 Milanez, Marcos / University of Miami, USA ................................................................................. 2017 Mills, David / ANGEL™ Learning, Inc., USA ................................................................................. 3535 Mislevy, Robert J. / University of Maryland—College Park, USA . ............................................... 2532 Modrák, Vladimír / Technical University of Košice, Slovakia ....................................................... 2760 Molinero, Ashli / University of Pittsburgh, USA ............................................................................. 3020 Montague, Rae-Anne / University of Illinois at Urbana-Champaign, USA ................................... 2676 Morrison, Dirk / University of Saskatchewan, Canada .................................................................. 3346 Moulton, Bonnie / Temple University, USA .................................................................................... 1219 Mulkeen, Aidan / National University of Ireland, Maynooth, Ireland . ............................................ 627 Murphrey, Theresa P. / Texas A&M University, USA . ................................................................... 3365 Murphy, Timothy H. / Texas A&M University, USA ...................................................................... 3365 Murray, L. W. / University of San Francisco, USA ........................................................................ 2181 Muukkonen, Hanni / University of Helsinki, Finland .................................................................... 3149 Naeve, Ambjörn / Royal Institute of Technology (KTH), Stockholm, Sweden ................................ 1362 Naidu, Som / The University of Melbourne, Australia .............................................................. 191, 654 Nantz, Karen S. / Eastern Illinois University, USA . ......................................................................... 293 Nash, John B. / Stanford University, USA ....................................................................................... 3028 Nason, Rodney / Queensland University of Technology, Australia . ................................................. 897 Newell, Christopher / University of Tasmania, Australia ............................................................... 3241 Newman, Dianna L. / University at Albany/SUNY, USA ................................................................ 1828 Nguyen, Lilly / Institute for the Study of Knowledge Management in Education, USA .................. 3475 Niederman, Fred / Saint Louis University, USA ............................................................................. 3340 Notess, Mark / Indiana University, USA ......................................................................................... 1325 O’Brien, David / University of Saskatchewan, Canada .................................................................. 1186 O’Mahony, Christopher / Saint Ignatius’ College, Australia ........................................................ 3559 O’Dea, Michael / University of Hull, UK .......................................................................................... 413 Ogan, Christine / Indiana University, USA ....................................................................................... 519 Okamoto, Toshio / University of Electro- Communications, Japan . ................................................ 726 Olaniran, Bolanle / Texas Tech University, USA . ........................................................................... 3104 Olfman, Lorne / Claremont Graduate University, USA . ................................................................ 1689

Olofsson, Anders D. / Umeå University, Sweden ............................................................................ 3157 Overstreet, C. Michael / Old Dominion University, USA . ............................................................... 924 Owen, Robert S. / Texas A&M University-Texarkana, USA ........................................................... 2596 Page, Vaughn J. / University of Illinois at Urbana-Champaign, USA ............................................ 2676 Pahl, Claus / Dublin City University, Ireland .......................................................................... 733, 3214 Paik, Sandy / Standford University, USA ........................................................................................ 2400 Panton, M. Michelle / Bemidji State University, USA .................................................................... 1461 Parikh, Mihir A. / University of Central Florida, USA .................................................................. 1475 Parolia, Neeraj / University of Central Florida, USA ..................................................................... 1475 Partow-Navid, Parviz / California State University-Los Angeles, USA ......................................... 1481 Passerini, Katia / New Jersey Institute of Technology, USA ............................................................. 822 Payne, Carla R. / Vermont College of Union Institute and University, USA .................................... 153 Paz Dennen, Vanessa / Florida State University, USA ..................................................................... 704 Pelton, Leslee Francis / University of Victoria, Canada . ............................................................... 2333 Pelton, Timothy / University of Victoria, Canada . ......................................................................... 2333 Pendegraft, Norman / University of Idaho, USA ............................................................................ 1531 Petrides, Lisa A. / Institute for the Study of Knowledge Management in Education, USA ............. 3475 Pinsonneault, Alain / McGill University, Canada ............................................................................ 101 Piu, Angela / University of Calabria, Italy ........................................................................................ 346 Plekhanova, Valentina / University of Sunderland, UK ................................................................. 1429 Poda, Ibrahima / Miami University, USA ....................................................................................... 2130 Polyzos, George C. / Athens University of Economics and Business, Greece . ................................. 677 Pombortsis, Andreas / Aristotle University of Thessaloniki, Greece . ............................................ 1782 Poon, Paul W. T. / University Librarian, University of Macau, Macau, China .............................. 2215 Potgieter, Anet / University of Cape Town, South Africa ................................................................ 1178 Pouloudi, Athanasia / Athens University of Economics and Business, Greece .............................. 1362 Pöyry, Päivi / Helsinki University of Technology, Finland . ............................................................ 1676 Prammanee, Noppadol / Burapha University International College, Thaland ............................. 2288 Prentzas, Jim / Technological Educational Institute of Lamia and Research Academic Computer Technical Institute, Greece ............................................................................................................... 1888 Proctor, Deborah W. / Minnesota State Colleges and Universities, USA . ....................................... 237 Puustjärvi, Juha / Helsinki University of Technology, Finland ...................................................... 1676 Querrec, Ronan / CERV/ENIB, France .......................................................................................... 1137 Quesensberry, Jeria L. / The Pennsylvania State University, USA ................................................ 3179 Rada, Roy / University of Maryland, Baltimore County, USA .................................................. 776, 847 Rafaeli, Sheizaf / University of Haifa Mt. Carmel, Israel ............................................................... 2435 Rahman, Hakikur / SDNP, Bangladesh . .............................................................................. 1157, 1706 Ramachandran, V. / Anna University, India ................................................................................... 2660 Ramakrishnan, Cartic / University of Georgia, USA . ..................................................................... 789 Raman, Arumugam / University of Science, Malaysia, Malaysia . ................................................ 2636 Ramchandran, Aparna R. / Michigan State University, USA ........................................................ 1903 Ramim, Michelle M. / Nova Southeastern University, USA ........................................................... 2693 Reddy, Venkateshwar K. / University of Colorado at Colorado Springs, USA ................... 2768, 3272 Rentroia-Bonito, M.A. / Instituto Superior Técnico, Portugal . ..................................................... 2624 Renzi, Stefano / Bocconi University, Italy . ..................................................................................... 1991 Reynolds, Adrienne A. / UAE University, UAE .............................................................................. 2651

Richter, Christoph / University of Hannover, Germany ................................................................. 3028 Rivoltella, Pier Cesare / Catholic University of Milan, Italy . ........................................................ 2318 Rizal, Dharmarus / Stanford University, USA ................................................................................ 2400 Robinson, Jean C. / Indiana University, USA ................................................................................... 519 Robinson, LeAnne K. / Western Washington University, USA ....................................................... 2150 Rogers, P. Clint / Brigham Young University, USA ......................................................................... 2514 Roig, Anna Escofet / University of Barcelona, Spain ....................................................................... 589 Rojas, Maria Delia / Murdoch University, Australia ...................................................................... 1976 Rollier, Bruce / University of Baltimore, USA . ............................................................................... 3340 Roupas, Chrysostomos / University of Macedonia, Greece ............................................................. 220 Ruiz, Jorge G. / University of Miami, USA ..................................................................................... 2017 Russell, Glenn / Monash University, Australia ............................................................................... 3528 Ryan, John / Ryan Management Consulting, Australia .................................................................. 2958 Ryan, Richard / University of Oklahoma, USA . ............................................................................. 2840 Ryan, Terry / Claremont Graduate University, USA . ..................................................................... 1689 Sagawa, Hirohiko / Central Research Laboratory, Hitachi, Ltd., Japan . ...................................... 1637 Saini-Eidukat, Bernhardt / North Dakota State University, USA . ................................................ 2000 Sala, Nicoletta / Università della Svizzera italiana, Switzerland ...................................................... 749 Salmon, Gilly / Open University Business School, UK ................................................................... 2187 Salter, Graeme / University of Western Sydney, Australia .............................................................. 3299 Sanchez-Hucles, Janis V. / Old Dominion University, USA ........................................................... 3140 Sarkar, Asit / University of Saskatchewan, Canada ........................................................................ 1186 Sarmento, Anabela / Instituto Superior de Contabilidade e Administração do Porto, Portugal ..... 618 Savage, Dan / Stanford University, USA .......................................................................................... 2400 Schenk, Karen D. / K.D. Schenk and Associates Consulting, USA . ............................................... 2325 Schifter, Catherine C. / Temple University, USA ............................................................................ 2990 Schmieder, Allen / JDL Technologies, USA .................................................................................... 3069 Schneider, Oliver / ZGDV e.V. ­– Computer Graphics Center, Darmstadt, Germany ..................... 1439 Schniederjans, Marc J. / University of Nebraska-Lincoln, USA .................................................... 2929 Schnipke, Deborah L. / Virtual Psychometrics, LLC, USA .............................................................. 442 Schoepke, Jen / University of Wisconsin-Madison, USA ................................................................ 3224 Schornack, Gary R. / University of Colorado at Denver, USA ........................................................ 716 Schrier, Karen / MIT, USA ................................................................................................................ 988 Schürch, Dieter / Università della Svizzera Italiana (USI), Switzerland ........................................ 2086 Schwert, Donald P. / North Dakota State University, USA ............................................................. 2000 Segrave, Stephen / Deakin University, Australia .............................................................................. 905 Selgrade, Katherine A. / Old Dominion University, USA . ............................................................. 3140 Shaik, Najmuddin / University of Illinois at Urbana-Champaign, USA ........................................ 2676 Shareef, Ali Fawaz / Massey University, New Zealand . ................................................................. 2520 Sharkey, Jennifer / Purdue University, USA . ................................................................................... 580 Sharma, Chetan / Datamation Foundation Charitable Trust, India ................................................ 512 Shaughnessy, Michael / Washington & Jefferson College, USA .................................................... 1292 Sheldrick, Rachael / Accenture, USA .............................................................................................. 3416 Shepherd, Sonya S. / Georgia Southern University, USA ............................................................... 3011 Sheth, Amit / University of Georgia, USA ......................................................................................... 789 Shi, Yuanchun / Tsinghua University, China . ................................................................................. 2026

Shifter, Catherine C. / Temple University, USA . ............................................................................ 2990 Shih, Timothy K. / Tamkang University, Taiwan ............................................................................ 3500 Sicilia, Miguel-Ángel / University of Alcalá, Spain ........................................................................ 3401 Simon, Judith C. / The University of Memphis, USA . .................................................................... 1537 Sipos, Gergely / Hungarian Academy of Sciences, Hungary .......................................................... 1569 Slator, Brian M. / North Dakota State University, USA . ................................................................ 2000 Slusky, Ludwig / California State University-Los Angeles, USA . .................................................. 1481 Smith, C.A.P. / Colorado State University, USA ............................................................................... 601 Smith, Linda C. / University of Illinois at Urbana-Champaign, USA ............................................ 2676 Sorensen, Elsebeth Korsgaard / Aalborg University, Denmark .................................................... 1961 Spadaccini, Jim / Ideum, USA ........................................................................................................... 396 Specht, Marcus / Fraunhofer FIT-ICON, Denmark . ...................................................................... 3183 Spiro, Rand J. / Michigan State University, USA . .......................................................................... 1903 Srivastava, Shirish C. / National University of Singapore, Singapore ........................................... 2941 Stanford, Ronnie / The University of Alabama, USA . .................................................................... 2115 Stern, Mia / IBM Rational Software Lexington, USA ........................................................................ 482 Stevens, Ken / Memorial University of Newfoundland, Canada . ................................................... 2817 Stewart, Craig / University of Nottingham, UK .............................................................................. 1504 Su, Bude / Indiana University, USA . ............................................................................................... 3385 Subramaniam, R. / Nanyang Technological University, Singapore ............................................... 2121 Sweeney, Christine / NCS Pearson, USA ........................................................................................ 3008 Takeuchi, Masaru / Hitachi, Ltd., Japan ........................................................................................ 1637 Takhar, Jatinder / University of Western Ontario, Canada .............................................................. 528 Tan, Bernard C.Y. / National University of Singapore, Singapore . ............................................... 1496 Tan, Wei-Ping / National University of Singapore, Singapore . ...................................................... 1496 Tansey, Frank / Technology Consultant, USA ................................................................................. 3433 Tardini, Stefano / University of Lugano, Switzerland . ................................................................... 1014 Tarnanas, Ioannis / Aristotle University of Thessaloniki, Greece .................................................. 1782 Teo, Thompson S.H. / National University of Singapore, Singapore ............................................. 2941 Terpstra, Jeff / North Dakota State University, USA ...................................................................... 2000 Thomas, Christopher / University of Georgia, USA ........................................................................ 789 Thompson, Tedi / American Public University System, USA . ........................................................ 3073 Thornton, Patricia / Kinjo Gakuin University, Japan ...................................................................... 127 Tiberius, Richard G. / University of Miami, USA .......................................................................... 2017 Tidwell-Scheuring, Sylvia / CTB/McGraw-Hill, USA .................................................................... 3490 Toh, K.A. / Nanyang Technological University, Singapore ............................................................. 2205 Toland, Janet / Victoria University of Wellington, New Zealand .................................................... 2325 Tomei, Lawrence A. / Robert Morris University, USA . ................................................................. xl, 18 Torrisi-Steele, Geraldine / Griffith University, Australia ............................................................... 1354 Treleaven, Lesley / University of Western Sydney, Australia .......................................................... 3449 Turner, Rodney / Victoria University, Australia ............................................................................. 2791 Turoff, Murray / New Jersey Institute of Technology, USA .................................................. 8, 45, 3370 Valanides, Nicos / University of Cyprus, Cyprus . ........................................................................... 3251 Valenzuela, Felix / Yale Law School, USA . ....................................................................................... 117 Van den Ende, Erwin / Institute of Tropical Medicine, Belgium .................................................... 3359 Van den Enden, Jef / Institute of Tropical Medicine, Belgium ....................................................... 3359

Van Slyke, Craig / University of Central Florida, USA .................................................................... 382 van Zuilen, Maria H. / University of Miami, USA . ........................................................................ 2017 Varga, László Zsolt / Hungarian Academy of Sciences, Hungary................................................... 2094 Vasconcelos, Eurico / Integrated Colleges of Ceará (FIC), Brazil . ............................................... 3321 Vat, Kam Hou / University of Macau, Macau . ............................................................................... 1128 Veugelers, H.C.H. (Marij) / Universiteit van Amsterdam, The Netherlands . ................................ 2069 Vivekanandan, P. / Anna University, India ..................................................................................... 2660 Vollmers, Gloria / University of Maine, USA . ................................................................................ 2902 Waddington, Tad / Accenture, USA ................................................................................................ 3416 Wang, Xinchun / California State University, Fresno, USA ........................................................... 3084 Wasson, Barbara / University of Bergen, Norway .......................................................................... 1106 Watson, Katherine / Coast Community College District, USA ...................................................... 3129 Webking, Robert / University of Texas at El Paso, USA .................................................................. 117 White, Alan R. / North Dakota State University, USA .................................................................... 2000 Wild, J. Christian / Old Dominion University, USA ......................................................................... 924 Wilder, Hilary / William Patterson University, USA ....................................................................... 2309 Wilkes, Ronald B. / The University of Memphis, USA . .................................................................. 1537 Williams, Peter B. / Brigham Young University, USA . ................................................................... 3577 Winke, Paula / Georgetown University, USA .................................................................................. 2245 Wisher, Robert A. / U.S. Department of Defense, USA .......................................................... 536, 1004 Wong, Anthony / Stanford University, USA .................................................................................... 2400 Wong, Y.Y. Jessie / Independent Educational Researcher, Canada ................................................ 2205 Wood, Mick / University of Central Lancashire, UK ...................................................................... 1391 Woodruff, Earl / OISE-University of Toronto, Canada..................................................................... 897 Woolf, Beverly / University of Massachusetts, USA . ........................................................................ 482 Wright, Carol / Pennsylvania State University, USA ...................................................................... 1488 Wright, Maurice W. / Temple University, USA ............................................................................... 1923 Wright, Vivian H. / The University of Alabama, USA .......................................................... 1848, 2115 Xiang, Peifeng / Tsinghua University, China . ................................................................................. 2026 Xie, Weikai / Tsinghua University, China ........................................................................................ 2026 Xu, Guangyou / Tsinghua University, China . ................................................................................. 2026 Xu, Zhiwei / Chinese Academy of Sciences, China ......................................................................... 1373 Yang, Chia-chi / University of Missouri-Columbia, USA . .............................................................. 1469 Yee, George / National Research Council Canada, Canada ............................................................. 211 Yiu, S.M. / University of Hong Kong, Hong Kong .......................................................................... 1205 Yukita, Shuichi / Hosei University, Japan ...................................................................................... 1028 Zeng, Guangping / University of Science and Technology of Beijing, China . ............................... 1724 Zhang, Baopeng / Tsinghua University, China . .............................................................................. 2026 Zhang, Dai / Concordia University, Canada ..................................................................................... 174 Zhang, Degan / University of Science and Technology of Beijing, China . ..................................... 1724 Zhang, Huaiyu / Northwest University, China ................................................................................ 1724 Zhang, Xinshang / Jidong Oilfield, P.R. China................................................................................ 1724 Zhenbing, Zeng / Chinese Academy of Sciences, China.................................................................. 1373 Zhong, Yingqin / National University of Singapore, Singapore ..................................................... 2497 Zuckweiler, Kathryn M. / University of Nebraska-Lincoln, USA .................................................. 2929

Contents by Volume

volume 1 Preface........................................................................................................................................ xxxviii Introductory Chapter: Contemporary Research in Distance Learning / Lawrence A. Tomei........... xlii

Section 1: Fundamental Concepts and Theories in Online and Distance Learning This section serves as a foundation for this exhaustive reference tool by addressing crucial theories essential to the understanding of online and distance learning. Chapters within this segment provide an excellent framework in which to position distance learning within the field of information science and technology. With 60 chapters comprising this foundational base of knowledge, the reader can learn and chose from a compendium of expert research on the elemental theories underscoring the online and distance learning discipline. Chapter 1.1. Principles to Guide the Integration and Implementation of Educational Technology / Sara Dexter .........................................................................................................................................1 Chapter 1.2. Technology’s Role in Distance Education / Murray Turoff, Caroline Howard, and Richard Discenza ................................................................................................................................8 Chapter 1.3. The Pillars of Instructional Technology / Lawrence A. Tomei .....................................18 Chapter 1.4. A Psychosocial Framework for IT Education / Janice A. Grackin ..............................28 Chapter 1.5. Interactive E-Learning / Claude Ghaoui and W. Janvier .............................................35 Chapter 1.6. Innovation and Technology for 21st Century Education / Murray Turoff, Caroline Howard, and Richard Discenza .........................................................................................45 Chapter 1.7. Making the Case for Case-Based Learning in Computer Information Systems / Morgan M. Jennings, Charles H. Mawhinney, and Janos Fustos ....................................................55 Chapter 1.8. What is an Authentic Learning Environment? / Anthony Herrington and Jan Herrington . ................................................................................................................................68

Chapter 1.9. A Brief History of Networked Classrooms: Effects, Cases, Pedagogy, and Implications / Louis Abrahamson .....................................................................................................78 Chapter 1.10. Patterns in Electronic Brainstorming / Alan R. Dennis, Alain Pinsonneault, Kelly McNamara Hilmer, Henri Barki, Brent Gallupe, Mark Huber, and François Bellavance ...101 Chapter 1.11. Using Audience Response Systems to Develop Critical Thinking Skills / Robert Webking and Felix Valenzuela ............................................................................................ 117 Chapter 1.12. Mobile Educational Technology / Chris Houser and Patricia Thornton . ...............127 Chapter 1.13. Learning Styles and Adaptive ICT-Based Learning Environment / Zlatko J. Kovačić ............................................................................................................................136 Chapter 1.14. What Do They Learn? / Carla R. Payne ..................................................................153 Chapter 1.15. Online Problem-Based Learning Approach in Higher Education / Roisin Donnelly ..............................................................................................................................162 Chapter 1.16. Re-Enacted Affiliative Meanings and “Branding” in Open and Distance Education / Gary Mcl. Boyd and Dai Zhang .....................................................................................................174 Chapter 1.17. Opportunities for Open Source E-Learning / Fanuel Dewever ...............................180 Chapter 1.18. Researching Distance Education and E-Learning / Som Naidu ...............................191 Chapter 1.19. Learning IT: Where Do Lecturers Fit? / Tanya McGill and Samantha Bax ............201 Chapter 1.20. Security and Privacy in Distance Education / George Yee . ..................................... 211 Chapter 1.21. Evaluation of Computer Adaptive Testing Systems / Anastasios A. Economides and Chrysostomos Roupas . ............................................................................................................220 Chapter 1.22. Accessibility of Technology in Higher Education / Deborah W. Proctor ................237 Chapter 1.23. Virtual Reality and Immersive Technology in Education / Patrick E. Connolly .....252 Chapter 1.24. Student Retention in Online Education / Mac Adkins and Bernard Marr ...............257 Chapter 1.25. Assessing Satisfaction and Academic Locus of Control of Dropout Students in Online Learning Courses / Yair Levy ..............................................................................................265 Chapter 1.26. Gender Differences and Hypermedia Navigation: Principles for Adaptive Hypermedia Learning Systems / Jing Ping Fan and Robert D. Macredie .....................................278

Chapter 1.27. Issues in Delivering Course Material via the Web / Karen S. Nantz . ......................293 Chapter 1.28. Ten Scalability Factors in Distance Education / R. Dwight Laws, Scott L. Howell, and Nathan K. Lindsay ...................................................................................................................300 Chapter 1.29. Strategies for Teaching Students with Exceptional Needs in Cyber Schools / Shellie Hipsky and Lindsay Adams .................................................................................................309 Chapter 1.30. Traditional Education and Distance Learning / Karoulis Athanasis and Andreas Pombortsis ........................................................................................................................321 Chapter 1.31. System Conversion: Teaching vs. Reality / Efrem G. Mallach ...............................329 Chapter 1.32. Distance Education in the Era of Internet / Giorgio Agosti .....................................338 Chapter 1.33. Simulation, Training, and Education Between Theory and Practice / Angela Piu ..346 Chapter 1.34. Pedagogy in Commercial Videos / Katrin Becker ...................................................357 Chapter 1.35. Instructors’ Experiences with Using Groupware to Support Collaborative Project-Based Learning / John Day, Hao Lou, and Craig Van Slyke .............................................382 Chapter 1.36. Real Science: Making Connections to Research and Scientific Data / Jim Spadaccini ................................................................................................................................396 Chapter 1.37. Educational Technology Standards / Michael O’Dea ..............................................413 Chapter 1.38. Administering a Virtual School / Gaye Lang ...........................................................426 Chapter 1.39. Evaluating Content-Management Systems for Online Learning Programs / Deborah L. Schnipke, Kirk Becker, and James S. Masters .............................................................442 Chapter 1.40. Brain-Based Learning / Kathleen Cercone ..............................................................453 Chapter 1.41. Usability Evaluation of Online Learning Programs / Bernard Blandin . .................475 Chapter 1.42. Intelligent and Adaptive Web-Based Instruction / Beverly Woolf and Mia Stern ....482 Chapter 1.43. Connecting K-12 Schools in Higher Education / Laura A.B. Dell ..........................506 Chapter 1.44. Gender and Education in Oral Traditions, Culture, and ICTs / Chetan Sharma and Y. R. Maindiratta . ....................................................................................................................512 Chapter 1.45. Gender and the Culture of Computing in Applied IT Education / Susan C. Herring, Christine Ogan, Manju Ahuja, and Jean C. Robinson ...................................................................519

Chapter 1.46. Medical Education in the 21st Century / Stefane M. Kabene, Jatinder Takhar, Raymond Leduc, and Rick Burjaw . ................................................................................................528 Chapter 1.47. Moderating Learner-Centered E-Learning: Problems and Solutions, Benefits and Implications / Curtis J. Bonk, Robert A. Wisher, and Ji-Yeon Lee . ................................................536 Chapter 1.48. Distance Education Associations / Irene Chen ........................................................562

volume II Chapter 1.49. Integrating Technology Literacy and Information Literacy / Jennifer Sharkey and D. Scott Brandt ...............................................................................................................................580 Chapter 1.50. Gender, Education, and Video Games / Anna Escofet Roig and Ma José Rubio Hurtado ..................................................................................................................589 Chapter 1.51. Educational Technology and Learning Theory / Gary A. Berg ................................595 Chapter 1.52. The Relationship Between E-Collaboration and Cognition / Stephen C. Hayne and C.A.P. Smith .............................................................................................................................601 Chapter 1.53. Adult Learners in Higher Education / Ana Maria R. Correia and Anabela Sarmento . .........................................................................................................................618 Chapter 1.54. ICT in Schools: What is of Educational Value? / Aidan Mulkeen . ..........................627 Chapter 1.55. Delivering Web-Based Education / Kathryn A. Marold . .........................................647 Chapter 1.56. Evaluating Distance Education and E-Learning / Som Naidu .................................654 Chapter 1.57. High Performance Publisher/Subscriber Communication for Adaptive, Collaborative Web-Based Learning / Yugyung Lee, Markus Junginger, and James Geller ...........664 Chapter 1.58. Evaluating Student Learning in Distance Education / Efstratios T. Diamadis and George C. Polyzos ..........................................................................................................................677 Chapter 1.59. Distance Education Success Factors / Cathy Cavanaugh ........................................686 Chapter 1.60. Interactivity in Web-Based Learning / Adams Bodomo ...........................................693 Chapter 1.61. We’ll Leave the Light on for You: Keeping Learners Motivated in Online Courses / Vanessa Paz Dennen and Curtis J. Bonk ........................................................................................704

Section 2: Online and Distance Learning Development and Design Methodologies This section offers in-depth coverage of conceptual architectures and distance learning frameworks to provide the reader with a comprehensive understanding of the emerging technological developments within the field of online distance learning. From basic designs to abstract developments, chapters found in this section serve to expand the reaches of development and design technologies within the online and distance learning community. Included in this section are over 40 contributions from researchers throughout the world on the topic of online development and methodologies in distance learning. Chapter 2.1. Systems Model of Educational Processes / Charles E. Beck and Gary R. Schornack ..........................................................................................................................716 Chapter 2.2. E-Learning Environment / Mizue Kayama and Toshio Okamoto . .............................726 Chapter 2.3. A Conceptual Architecture for the Development of Interactive Educational Media / Claus Pahl ......................................................................................................................................733 Chapter 2.4. Hypermedia Modules for Distance Learning / Nicoletta Sala ...................................749 Chapter 2.5. Understanding Section 508 and Its Implications for Distance Education / Mary Hricko . ..................................................................................................................................756 Chapter 2.6. Inadequate Infrastructure and the Infusion of Technology into K-12 Education / Gregg Asher ....................................................................................................................................773 Chapter 2.7. Web-Based Education Accountability System and Organizational Changes: An Actor-Network Approach / Xueguang Ma and Roy Rada ........................................................776 Chapter 2.8. Semantics for the Semantic Web: The Implicit, the Formal, and the Powerful / Amit Sheth, Cartic Ramakrishnan, and Christopher Thomas ........................................................789 Chapter 2.9. A Comparative Analysis of Computer-Supported Learning Models and Guidelines / Fethi Ahmet Inan and Deborah L. Lowther . ..................................................................................805 Chapter 2.10. Evaluating Learning Management Systems: Leveraging Learned Experiences from Interactive Multimedia / Katia Passerini . .............................................................................822 Chapter 2.11. Online Education and Manufacturing Mode / Roy Rada . ........................................847 Chapter 2.12. Bridging the Gap with MAID: A Method for Adaptive Instructional Design / Jacopo Armani and Luca Botturi . ..................................................................................................852 Chapter 2.13. Distributed Learning Objects: An Open Knowledge Management Model / Veronica Diaz and Patricia McGee ................................................................................................875

Chapter 2.14. Innovations for Online Collaborative Learning in Mathematics / Rodney Nason and Earl Woodruff . .........................................................................................................................897 Chapter 2.15. Strategic Design for Web-Based Teaching and Learning: Making Corporate Technology Systems Work for the Learning Organization / Brian Corbitt, Dale Holt, and Stephen Segrave ..............................................................................................................................905 Chapter 2.16. The Essential Elements of Interactive Multimedia Distance Learning Systems / Kurt Maly, Hussein Abdel-Wahab, C. Michael Overstreet, J. Christian Wild, Ayman Abdel-Hamid, Sahar Ghanem, and Waleed Farag .............................................................924 Chapter 2.17. Using Virtual Instrument to Develop a Real-Time Web-Based Laboratory / Kin Cheong Chu .............................................................................................................................943 Chapter 2.18. Evaluating Online Learning Applications: Development of Quality-Related Models / Leping Liu ........................................................................................................................956 Chapter 2.19. Integrating Visual Representation of Knowledge with Learning Management Systems: Design Priciples for Advanced Computer-Based Learning Support / John W. Coffey . ..971 Chapter 2.20. Reliving History with “Reliving the Revolution”: Designing Augmented Reality Games to Teach the Critical Thinking of History / Karen Schrier . ...................................988 Chapter 2.21. Toward a Comprehensive Model of E-Learning Evaluation: The Components / Curtis J. Bonk, Robert A. Wisher, and Matthew V. Champagne ...................................................1004 Chapter 2.22. Fast Prototyping as a Communication Catalyst for E-Learing Design / Luca Botturi, Lorenzo Cantoni, Benedetto Lepori, and Stefano Tardini ......................................1014 Chapter 2.23. An E-Learning System Based on the Top-Down Method and the Cellular Models / Norihiro Fujii, Shuichi Yukita, Nobuhiko Koike, and Tosiyasu L. Kunii .......................1028 Chapter 2.24. Tertiary Education and the Internet / Paul Darbyshire and Stephen Burgess ........1049 Chapter 2.25. Innovative Approach to Teaching Database Design through WWW: A Case Study and Usability Evaluation / Joanna Jedrzejowicz ...................................................1056 Chapter 2.26. Usability of Online Learning Systems and Course Materials / Elizabeth Furtado .........................................................................................................................1070 Chapter 2.27. Web-Based Distance Learning and the Second Digital Divide / Sheryl Burgstahler ........................................................................................................................1077 Chapter 2.28. Applying Semantic Web in Competence Management / Mikko Laukkanen and Heikki Helin ..................................................................................................................................1084

Chapter 2.29. Intelligent Agents Supporting Distributed Collaborative Learning / Weiqin Chen and Barbara Wasson ............................................................................................... 1105 Chapter 2.30. Conceiving a Learning Organization Model for Online Education / Kam Hou Vat and Raymond Wong . .............................................................................................. 1128 Chapter 2.31. MASCARET: A Pedagogical Multi-Agent System for Virtual Environments for Training / Cédric Buche, Ronan Querrec, Pierre De Loor, and Pierre Chevaillier ............... 1137 Chapter 2.32. Interactive Multimedia Technologies for Distance Education Systems / Hakikur Rahman ........................................................................................................................... 1157 Chapter 2.33. Qualitative Standards for E-Learning: The Demand-Driven Learning Model / Krista Breithaupt and Colla J. MacDonald . ................................................................................ 1165 Chapter 2.34. Complex Adaptive Enterprises / Anet Potgieter, Kurt April, and Judith Bishop . .. 1178

volume III Chapter 2.35. User-Centered Design Principles for Online Learning Communities: A Sociotechnical Approach for the Design of a Distributed Community of Practice / Ben K. Daniel, David O’Brien, and Asit Sarkar . ......................................................................... 1186 Chapter 2.36. Supporting Navigation and Learning in Educational Hypermedia / Patricia M. Boechler . ................................................................................................................... 1199 Chapter 2.37. Content Engineering Agent: A TBL-Based E-Course Development Tool with TQM / B.S.N. Cheung, L.C.K. Hui, S.M. Yiu, J.K.W. Lee, L. K. Kwok, and Kenneth Leung ...1205 Chapter 2.38. Universal Design for Online Education: Access for All / Rosangela K. Boyd and Bonnie Moulton ............................................................................................................................1219 Chapter 2.39. Curriculum Development in Web-Based Education / Johanna Lammintakanen ...1252 Chapter 2.40. Starting with What We Know: A CILS Framework for Moving from Physical to Virtual Science Learning Environments / Bronwyn Bevan . .........................................................1259 Chapter 2.41. Frameworks for CMS Design and Evalution / Marwin Britto ...............................1281 Chapter 2.42. Educational Software Evaluation / Michael Shaughnessy .....................................1292 Chapter 2.43. An Adaptive Predictive Model for Student Modeling / Gladys Castillo, João Gama, and Ana M. Breda ....................................................................................................1307

Chapter 2.44. Applying Contextual Design to Educational Software Development / Mark Notess ..................................................................................................................................1325 Chapter 2.45. A Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones / Akio Koyama and Leonard Barolli . .................................................................1344 Section 3: Online and Distance Learning Tools and Technologies This section presents an extensive coverage of various tools and technologies available in the field of distance learning that practicing educators can utilize to develop different techniques in support of the development of distance learning educational programs. Research within this section enlightens readers about fundamental research on some of the many tools used to facilitate and enhance the distance learning experience. Also explored are some of the recent technologies that have been deployed in support of distance learning course offerings. With more than 35 chapters, this section offers a broad treatment of some of the many tools and technologies within the online and distance learning community. Chapter 3.1. Core Principles of Educational Multimedia / Geraldine Torrisi-Steele ...................1354 Chapter 3.2. Knowledge Management as a Reference Theory for E-Learning: A Conceptual and Technological Perspective / Miltiadis D. Lytras, Ambjörn Naeve, and Athanasia Pouloudi ....1362 Chapter 3.3. Mathematics Education Over the Internet Based on Vega Grid Technology / Zhiwei Xu, Wei Li, Hongguang Fu, and Zhenbing Zeng ..............................................................1373 Chapter 3.4. IT to Facilitate Distance Education / M. Gordon Hunter and Peter Carr . ..............1384 Chapter 3.5. Interactive Response Systems in Higher Education / Mick Wood ............................1391 Chapter 3.6. Hyper Video for Distance Learning / Mario Bochicchio and Nicola Fiore .............1402 Chapter 3.7. Rubrics as an Assessment Tool in Distance Education / Bonnie L. MacGregor ......1410 Chapter 3.8. Education, the Internet, and the World Wide Web / John F. Clayton .......................1417 Chapter 3.9. Learning Portals as New Academic Spaces / Katy Campbell ..................................1422 Chapter 3.10. Learning Systems Engineering / Valentina Plekhanova . .......................................1429 Chapter 3.11. Storytelling-Based Edutainment Applications / Anja Hoffmann, Stefan Göbel, Oliver Schneider, and Ido Iurgel . .................................................................................................1439 Chapter 3.12. Web Conferencing in Distance Education / M. Michelle Panton ...........................1461 Chapter 3.13. Wireless Technologies in Education / Chia-chi Yang .............................................1469

Chapter 3.14. Multiple Internet Technologies in In-Class Education / Mihir A. Parikh and Neeraj Parolia ..............................................................................................................................1475 Chapter 3.15. Change Management and Distance Education / Parviz Partow-Navid and Ludwig Slusky ...............................................................................................................................1481 Chapter 3.16. Distance Education Delivery / Carol Wright ..........................................................1488 Chapter 3.17. One-to-One Video-Conferencing Education / Hock Chuan Chan, Bernard C.Y. Tan, and Wei-Ping Tan ............................................................................................1496 Chapter 3.18. Automatic Authoring of Adaptive Educational Hypermedia / Alexandra I. Cristea and Craig Stewart .......................................................................................1504 Chapter 3.19. Simulation and Gaming in IT Education / Norman Pendegraft .............................1531 Chapter 3.20. Students’ Perceptions of Online Courses / Judith C. Simon, Lloyd D. Brooks, and Ronald B. Wilkes ....................................................................................................................1537 Chapter 3.21. Technology of Formal Education / Donald A. Hantula and Darleen M. DeRosa . ...1546 Chapter 3.22. TEXT-COL: A Tool for Active Reading / Anders Broberg ....................................1551 Chapter 3.23. Grid Technology for Smart Organizations / Gergely Sipos and Péter Kacsuk . .....1569 Chapter 3.24. A Component-Oriented Approach for Mixed Reality Applications / Michael Haller ..............................................................................................................................1600 Chapter 3.25. Digital Literacy and the Use of Wireless Portable Computers, Planners, and Cell Phones for K-12 Education / Virginia E. Garland ................................................................1624 Chapter 3.26. A Sign Language Teaching System Using Sign Language Recognition and Generation Methods / Hirohiko Sagawa and Masaru Takeuchi ...................................................1637 Chapter 3.27. Electronic Reading Programs / Julie Masterson-Smith ..........................................1655 Chapter 3.28. Bluetooth Scatternet Using an Ad Hoc Bridge Node Routing Protocol for Outdoor Distance Education / Yao-Chung Chang, M.T. Lin, Han-Chieh Chao, and Jiann-Liang Chen .........................................................................................................................1661 Chapter 3.29. Information Retrieval in Virtual Universities / Juha Puustjärvi and Päivi Pöyry . ...1676 Chapter 3.30. Online Behavior Modeling: An Effective and Affordable Software Training Method / Charlie Chen, Terry Ryan, and Lorne Olfman ..............................................................1689

Chapter 3.31. Interactive Multimedia Technologies for Distance Education in Developing Countries / Hakikur Rahman ........................................................................................................1706 Chapter 3.32. Geographic Information Systems Research and Data Centers / John Abresch ......1714 Chapter 3.33. Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning / Degan Zhang, Yuan-chao Li, Huaiyu Zhang, Xinshang Zhang, and Guangping Zeng ................1724 Chapter 3.34. Evaluating the Learning Effectiveness of Using Web-Based Instruction: An Individual Differences Approach / Sherry Y. Chen .................................................................1740 Chapter 3.35. Multimedia Technologies in Education / Armando Cirrincione ............................1752 Chapter 3.36. Advancing the Effective Use of Technology in Higher Education / Sally M. Johnstone ........................................................................................................................1759 Chapter 3.37. Design Levels for Distance and Online Learning / Judith V. Boettcher .................1763 Chapter 3.38. Care2x in Medical Informatics Education / Andreas Holzinger, Harald Burgsteiner, and Helfrid Maresch ....................................................................................1774 Chapter 3.39. An Expert-Based Evaluation Concerning Human Factors in ODL Programs: A Preliminary Investigation / Athanasis Karoulis, Ioannis Tarnanas, and Andreas Pombortsis ....1782

volume IV Chapter 3.40. An Organizational Memory Tool for E-Learning / Marie-Hélène Abel .................1794 Section 4: Utilization and Application of Online and Distance Learning This section discusses a variety of applications and opportunities available that can be considered by practicing educators in developing viable and effective distance learning educational programs. This section includes more than 40 chapters which incorporate applications of distance learning into institutions within the educational system as well as application of online learning in the corporate realm. Contributions included in this section also provide excellent coverage of today’s global community and how distance learning technologies and education are impacting the social fabric of our present-day global village. Chapter 4.1. Role Adjustment for Learners in an Online Community of Inquiry: Identifying the Challenges of Incoming Online Learners / Martha Cleveland-Innes, Randy Garrison, and Ellen Kinsel ................................................................................................1814 Chapter 4.2. Videoconferencing Communities: Documenting Online User Interactions / Dianna L. Newman, Patricia Barbanell, and John Falco ............................................................1828

Chapter 4.3. Library Services for Distance Education Students in Higher Education / Elizabeth Buchanan ......................................................................................................................1843 Chapter 4.4. Perspectives from Multiplayer Video Gamers / Jonathan B. Beedle and Vivian H. Wright ...........................................................................................................................1848 Chapter 4.5. Game Mods: Customizable Learning in a K16 Setting / Elizabeth Fanning ...........1870 Chapter 4.6. Issues of E-Learning in Third World Countries / Shantha Fernando . .....................1880 Chapter 4.7. Knowledge Representation in Intelligent Educational Systems / Ioannis Hatzilygeroudis and Jim Prentzas ...................................................................................1888 Chapter 4.8. Modes of Openness and Flexibility in Cognitive Flexibility Hypertext Learning Environments / Rand J. Spiro, Brian P. Collins, and Aparna R. Ramchandran ..........................1903 Chapter 4.9. Overcoming Organizational Barriers to Web Accessibility in Higher Education: A Case Study / Amy Scott Metcalfe ..............................................................................................1909 Chapter 4.10. Creating and Using Multiple Media in an Online Course / Maurice W. Wright ....1923 Chapter 4.11. Educational Theory into Practice Software (ETIPS) / Sara Dexter .......................1939 Chapter 4.12. Combining Synchronous and Asynchronous Distance Learning for Adult Training in Military Environments / Ilias Maglogiannis and Kostas Karpouzis..........................1950 Chapter 4.13. Reflection and Intellectual Amplification in Online Communities of Collaborative Learning / Elsebeth Korsgaard Sorensen .....................................................................................1961 Chapter 4.14. Project Management in Student Information Technology Projects / Maria Delia Rojas, Tanya McGill, and Arnold Depickere ...........................................................1976 Chapter 4.15. Scenarios for Web-Enhanced Learning / Jane E. Klobas and Stefano Renzi .........1991 Chapter 4.16. Effects of Teaching Science Through Immersive Virtual Environments / Lisa M. Daniels, Jeff Terpstra, Kimberly Addicott, Brian M. Slator, Donald P. Schwert, Bernhardt Saini-Eidukat, Phil McClean, and Alan R. White . ......................................................2000 Chapter 4.17. ePortfolios in Graduate Medical Education / Jorge G. Ruiz, Maria H. van Zuilen, Marcos Milanez, and Richard G. Tiberius . ..................................................................................2017 Chapter 4.18. Project Smart Remote Classroom: Providing Novel Real-Time Interactive Distance Learning Technologies / Yuanchun Shi, Weikai Xie, Guangyou Xu, Peifeng Xiang, and Baopeng Zhang ......................................................................................................................2026 Chapter 4.19. The Role of Project Management in Technology Literacy / Daniel Brandon . ......2042

Chapter 4.20. It was Hard Work but It was Worth It: ePortfolios in Teacher Education / Andrea Bartlett . ............................................................................................................................2049 Chapter 4.21. Supporting and Facilitating Academic Integrity in Distance Education Through Student Services / Brian F. Fox ....................................................................................................2061 Chapter 4.22. ePortfolio and Educational Change in Higher Education in The Netherlands / M.W. (Wijnand) Aalderink and H.C.H. (Marij) Veugelers . ..........................................................2069 Chapter 4.23. ICT in Medical Education in Trinidad and Tobago / Marilyn Lewis . ....................2080 Chapter 4.24. ICT, Education, and Regional Development in Swiss Peripheral Areas / Chiara Giorgi and Dieter Schürch ...............................................................................................2086 Chapter 4.25. Applications of Agent-Based Technologies in Smart Organizations / László Zsolt Varga . .......................................................................................................................2094 Chapter 4.26. Enriching and International Program Graduate Offering: A Blended Delivery Model / Vivian H. Wright, Jon Beedle, and Ronnie Stanford ........................................ 2115 Chapter 4.27. Continuing Science Education of the Global Public / Leo Tan Wee Hin and R. Subramaniam ...........................................................................................................................2121 Chapter 4.28. Improving Electronic Information Literacy in West African Higher Education / Ibrahima Poda and William F. Brescia . .......................................................................................2130 Chapter 4.29. How ePortfolios Support Development in Early Teacher Education / Victor McNair and Kevin Marshall ..............................................................................................2138 Chapter 4.30. Examining Perceptual Barriers to Technology: A Study on the Diffusion of Educational Technology and Education Reform / LeAnne K. Robinson ......................................2150 Chapter 4.31. Sustaining ePortfolio: Progress, Challenges, and Dynamics in Teacher Education / Yi-Ping Huang ...........................................................................................................2163 Chapter 4.32. Delivering Management Education via Tutored-Video Instruction / L. W. Murray and Alev M. Efendioglu ..........................................................................................2181 Chapter 4.33. E-Moderating in Higher Education / Gilly Salmon ................................................2187 Chapter 4.34. Diffusion of Web-Based Education in Singapore and Australia / Y.Y. Jessie Wong, R. Gerber, and K.A. Toh . ..................................................................................2205 Chapter 4.35. Effective Technology-Mediated Education for Adult Chinese Learners / Hsianghoo Steve Ching, Carmel McNaught, and Paul W. T. Poon ..............................................2215

Chapter 4.36. Integrating Writing into IT/MIS Courses / Jeffrey W. Merhout and Stephanie J. Etter ..........................................................................................................................2224 Chapter 4.37. Supporting Creativity in Software Development: An Application in IT Education / Aybüke Aurum, Meliha Handzic, and Adrian Gardiner . ..............................................................2234 Chapter 4.38. Online Assessment of Foreign Language Proficiency: Meeting Development, Design and Delivery Challenges / Paula M. Winke . ....................................................................2245 Chapter 4.39. Diffusion of E-Learning as an Educational Innovation / Petek Askar and Ugur Halıcı ...................................................................................................................................2258 Chapter 4.40. Constructing a Clinical Experience in the Classroom / Jennifer R. Jamison .........2264 Chapter 4.41. Implementing Computer-Supported Learning in Corporations / Doris Lee and Steve Borland .........................................................................................................................2272 Chapter 4.42. Understanding Participation in Online Courses: A Case Study of Online Interaction / Noppadol Prammanee ..............................................................................................2288 Chapter 4.43. Using E-Learning to Globalize a Teacher Education Program / Hilary Wilder .....2309 Section 5: Organizational and Social Implications of Online and Distance Learning This section offers a wide range of research regarding the social and organizational impact of online and distance learning technologies around the world. Chapters included in this section epitomize some of the most contested issues within society where access to technology is concerned. One of the most prominent issues discussed in this section is the integration of technology to allow access for all classrooms regardless of socioeconomic status; arguably the most important social and organizational barrier that this field of study has yet to overcome. With over 30 chapters, this discussion offers new insights into the incorporation of distance education within organizations and its impact on the social scheme within our global community. Chapter 5.1. Education and Organization: ICT, Assets, and Values / Pier Cesare Rivoltella . .....2318 Chapter 5.2. E-Mail Usage in South Pacific Distance Education / Jonathan Frank, Janet Toland, and Karen D. Schenk . ............................................................................................2325 Chapter 5.3. Introducing a Computer-Adaptive Testing System to a Small School District / Timothy Pelton and Leslee Francis Pelton ...................................................................................2333 Chapter 5.4. Organizational Models for Faculty Support: The Response of Canadian Universities / Margaret Haughey ........................................................................................................................2344 Chapter 5.5. Legal Implications of Online Assessment: Issues for Educators / Bryan D. Bradley ..........................................................................................................................2356

Chapter 5.6. Virtual Organizations in Post-Graduate Education in Egypt / Sherif Kamel ............2369 Chapter 5.7. Western Governors University and Competency-Based Education / Douglas B. Johnstone ...................................................................................................................2377 Chapter 5.8. Narrowing the Digital Divide: Technology Integration in a High-Poverty School / June K. Hilton ...............................................................................................................................2385

volume V Chapter 5.9. Stanford CyberLab: Internet Assisted Laboratories / Lambertus Hesselink, Dharmarus Rizal, Eric Bjornson, Sandy Paik, Raj Batra, Peter Catrysse, Dan Savage, and Anthony Wong ...............................................................................................................................2400 Chapter 5.10. Free-Choice Learning Research and the Virtual Science Center: Establishing a Research Agenda / Kathryn Haley Goldman and Lynn D. Dierking .........................................2416 Chapter 5.11. Social Recommender Systems: Recommendations in Support of E-Learning / Sheizaf Rafaeli, Yuval Dan-Gur, and Miri Barak .........................................................................2435 Chapter 5.12. ICT Aided Education for People’s Empowerment / Ashok Banerji and Saswata Basu ................................................................................................................................2452 Chapter 5.13. Literacy in K-12 Teacher Education: The Case Study of a Multimedia Resource / Kristina Love ................................................................................................................................2461 Chapter 5.14. The Cross-Cultural Dimensions of Globalized E-Learning / Andrea L. Edmundson ...2484 Chapter 5.15. Facilitating Students with Special Needs in Mainstream Schools: An Exploratory Study of Assistive Learning Technologies (ALT) / Claire Khek, John Lim, and Yingqin Zhong 2497 Chapter 5.16. Distance Education from Religions of the World / P. Clint Rogers and Scott L. Howell . ............................................................................................................................2514 Chapter 5.17. Distance Education in Small Island Nations / Ali Fawaz Shareef and Kinshuk . ...2520 Chapter 5.18. Accessibility of Computer-Based Testing for Individuals with Disablities and English Language Learners within a Validity Framework / Eric G. Hansen and Robert J. Mislevy . .2532 Chapter 5.19. Authentic Cases and Media Triggers for Supporting Problem-Based Learning in Teacher Education / Mike Keppell ............................................................................................2568 Chapter 5.20. The Seven C’s of Comprehensive Online Assessment: Lessons Learned from 36 Million Classroom Assessments in the Cisco Networking Academy Program / John T. Behrens, Tara A. Collison, and Sarah DeMark ...............................................................2581

Chapter 5.21. Programmed Instruction, Programmed Branching, and Learning Outcomes / Robert S. Owen and Bosede Aworuwa . ........................................................................................2596 Chapter 5.22. Distance Education in South America / Luis Barrera ............................................2602 Chapter 5.23. Distance Education in Turkey / Petek Askar ..........................................................2610 Chapter 5.24. Quality Assurance Issues for Online Universities / Floriana Grasso and Paul Leng . . 2617 Chapter 5.25. Motivation to E-Learn Within Organizational Settings: An Exploratory Factor Structure / M.A. Rentroia-Bonito, J. Jorge, and Claude Ghaoui . ...............................................2624 Chapter 5.26. Distance Learning and Educational Technology in Malaysia / Habibah Lateh and Arumugam Raman .................................................................................................................2636 Chapter 5.27. Educational Technology in the Middle East / Adrienne A. R. Reynolds . ...............2651 Chapter 5.28. Secure Soap-Based Web Services for Distance Education / K. Komathy, P. Vivekanandan, and V. Ramachandran .....................................................................................2660 Chapter 5.29. Online Program Assessment: A Case Study of the University of Illinois at Urbana-Champaign Experience / Faye L. Lesht, Rae-Anne Montague, Vaughn J. Page, Najmuddin Shaik, and Linda C. Smith . ........................................................................................2676 Chapter 5.30. Eight Key Elements of Successful Self-Funding E-Learning Programs / Yair Levy and Michelle M. Ramim . ..............................................................................................2693 Chapter 5.31. Using E-Learning to Promote Excellence in Polytechnic Education / Maggie Beers ................................................................................................................................2702 Section 6: Managerial Impact of Online and Distance Learning This section presents contemporary coverage of the social implications of online and distance learning, more specifically related to the corporate and managerial utilization of online learning technologies and applications, and how online learning can be facilitated within these organizations. Core ideas such as training and continuing education of human resources in modern organizations are discussed through these more than 25 chapters. Discussions of strategic planning related to the organizational elements as well as the e-learning program requirements that are necessary to build a framework for the institutionalization and sustainment of e-learning as a core business process are discussed within the chapters found in this section. Equally as crucial, within the educational management system, there is discussion of the virtual classroom which addresses the latest research concerning the management of digital networking via the internet to schools, particularly those in rural communities. Chapter 6.1. Competency Management Systems and Technologies / Shantha Liyanage . ...........2716 Chapter 6.2. An Ontology-Based Competence Management Model to Support Collaborative Working and Organisational Learning / José Braga de Vasconcelos and Chris Kimble ..............2744

Chapter 6.3. Functionalities and Position of Manufacturing Execution Systems / Vladimír Modrák .....2760 Chapter 6.4. Operational Success in Distance Education / Wm. Benjamin Martz, Jr. and Venkateshwar K. Reddy . ...............................................................................................................2768 Chapter 6.5. How Do IT Students Stay Up to Date with Employers’ Skill Requirements? / Tanya McGill and Michael Dixon . ...............................................................................................2775 Chapter 6.6. Stakeholders in Web-Based Education / A.K. Aggarwal ..........................................2784 Chapter 6.7. Information Systems Education for the 21st Century: Aligning Curriculum Content and Delivery with the Professional Workplace / Glenn Lowry and Rodney Turner .......2791 Chapter 6.8. The Management of Virtual Classes in School District Digital Intranets / Ken Stevens ...................................................................................................................................2817 Chapter 6.9. Total Quality Management in Higher Education / Gary A. Berg .............................2826 Chapter 6.10. Project Management and Graduate Education / Daniel Brandon ..........................2833 Chapter 6.11. A Strategy to Expand the University Education Paradigm: Selling Online Class Resources / Richard Ryan ...................................................................................................2840 Chapter 6.12. Education Trends in Thai Businesses Utilizing Information Technology / Heather Arthur-Gray and John Campbell ....................................................................................2852 Chapter 6.13. Bridging the Industry-University Gap through Action Research / Ned Kock ........2863 Chapter 6.14. Education Networks: Expected Market- and Cost-Oriented Benefits / Svenja Hagenhoff and Michaela Knust ........................................................................................2871 Chapter 6.15. Business Students as End-User Developers: Simulating “Real Life” Situations Through Case Study Approach / Sandra Barker ..........................................................................2896 Chapter 6.16. Building Educational Technology Partnerships through Participatory Design / John M. Carroll ............................................................................................................................2895 Chapter 6.17. Using Web-Based Technologies in a Graduate Class to Develop an Entrepreneurship Knowledge Portal / Nory B. Jones, Bret Golann, and Gloria Vollmers . .........2902 Chapter 6.18. A Comparison Between the Use of IT in Business and Education: Applications of the Internet to Tertiary Education / Stephen Burgess and Paul Darbyshire . ...........................2918 Chapter 6.19. Methodologies to Determine Class Sizes for Fair Faculty Work Load in Web Courses / Kathryn M. Zuckweiler, Marc J. Schniederjans, and Dwayne A. Ball .................2929

Chapter 6.20. IT Training as a Strategy for Business Productivity in Developing Countries / Shirish C. Srivastava and Thompson S.H. Teo .............................................................................2941 Chapter 6.21. Using Emerging Technologies for Effective Pedagogy in Management Education / Sunil Hazari ..................................................................................................................................2952 Chapter 6.22. Peer Coaching and Reflective Practice in Authentic Business Contexts: A Strategy to Enhance Competency in Post-Graduate Business Students / Richard Ladyshewsky and John Ryan ..............................................................................................................................2958 Chapter 6.23. Introducing GIS for Business in Higher Education / David Gadish ......................2968 Chapter 6.24. Distance Learning as Commercializing Higher Education / Gary A. Berg ............2976 Chapter 6.25. Implementing and Sustaining E-Learning in the Workplace / Zane L. Berge and Lenora Giles ..........................................................................................................................2979 Chapter 6.26. Faculty Participation in Distance Education Programs / Catherine C. Schifter......2990 Chapter 6.27. ARS Evoltion: Reflections and Recommendations / Harold M. Horowitz . ...........2997

volume VI Section 7: Critical Issues in Online and Distance Learning This section contains 30 chapters addressing issues such as gender barriers, web accessibility, quality assurance and development of e-learning in under-developed countries presenting readers with an in-depth analysis of the most current and relevant issues within this growing field of study. Models for researchers and practitioners are offered as attempts are made to expand the reaches of online and distance learning within the higher education community. The Formation of Frameworks in which to position the issues faced in this growing field is provided by research found in this section while the core psychological paradigms of education are translated into applicable ideas within the exploding realm of online and distance education. Crucial examinations of the cultural biases innate in online and distance learning are presented in this section while simultaneously enticing and inspiring the reader to research further and participate in this increasingly pertinent debate. Chapter 7.1. Critical Barriers to Technolgy in K-12 Education / Christine Sweeney ...................3008 Chapter 7.2. Computer Skills, Technostress, and Gender in Higher Education / Sonya S. Gaither Shepherd ........................................................................................................... 3011 Chapter 7.3. Increasing Web Accessibility and Usability in Higher Education / Barbara A Frey, Ashli Molinero, and Ellen Cohn ........................................................................3020 Chapter 7.4. Evaluating Computer-Supported Learning Initiatives / John B. Nash, Christoph Richter, and Heidrun Allert . ........................................................................................3028

Chapter 7.5. Do the Philosophical Foundations of Online Learning Disadvantage Non-Western Students? / David Catterick ..........................................................................................................3035 Chapter 7.6. Inquisitivism: The Evolution of a Constructivist Approach for Web-Based Instruction / Dwayne Harapnuik . .................................................................................................3047 Chapter 7.7. The Most Dramatic Changes in Education Since Socrates / Allen Schmieder .........3069 Chapter 7.8. Quality Assurance and Online Higher Education / Edward D. Garten and Tedi Thompson ..............................................................................................................................3073 Chapter 7.9. What Factors Promote Sustained Online Discussions and Collaborative Learning in a Web-Based Course? / Xinchun Wang . ...................................................................................3084 Chapter 7.10. Challenges to Implementing E-Learning in Lesser Developed Countries / Bolanle Olaniran ..........................................................................................................................3104 Chapter 7.11. Information Technology Certification: A Student Perspective / Tanya McGill and Michael Dixon . ............................................................................................................................. 3119 Chapter 7.12. Electronic Paralanguage: Interfacing with the International / Katherine Watson ..3129 Chapter 7.13. Enhancing Inclusion in Computer Science Education / Donald D. Davis, Debra A. Major, Janis V. Sanchez-Hucles, Sandra J. DeLoatch, Katherine A. Selgrade, Shannon K. Meert, Nikki L. Jackson, Heather J. Downey, and Katherine M. Fodchuk . .............3140 Chapter 7.14. Technology-Mediated Progressive Inquiry in Higher Education / Hanni Muukkonen, Minna Lakkala, and Kai Hakkarainen . ........................................................3149 Chapter 7.15. Enhancing Phronesis: Bridging Communities Through Technology / Anders D. Olofsson and J. Ola Lindberg . ....................................................................................3157 Chapter 7.16. Female Retention in Post-Secondary IT Education / Jeria L. Quesensberry .........3179 Chapter 7.17. Contextualized Learning: Supporting Learning in Context / Marcus Specht . .......3183 Chapter 7.18. Electronic Portfolios and Education: A Different Way to Assess Academic Success / Stephenie M. Hewett .....................................................................................................3200 Chapter 7.19. Behaviour Analysis for Web-Mediated Active Learning / Claus Pahl . .................3214 Chapter 7.20. Gender Differences in Education and Training in the IT Workforce / Pascale Carayon, Peter Hoonakker, and Jen Schoepke ...............................................................3224 Chapter 7.21. Preparing African Higher Education Faculty in Technology / Wanjira Kinuthia . .3234 Chapter 7.22. Disability, Chronic Illness and Distance Education / Christopher Newell and Margaret Debenham .....................................................................................................................3241

Chapter 7.23. A Socio-Technical Analysis of Factors Affecting the Integration of ICT in Primary and Secondary Education / Charoula Angeli and Nicos Valanides ................................3251 Chapter 7.24. Critical Success Factors for Distance Education Programs / Ben Martz and Venkat Reddy . ...............................................................................................................................3272 Chapter 7.25. Understanding Cognitive Processes in Educational Hypermedia / Patricia M. Boechler . ...................................................................................................................3280 Chapter 7.26. The Online Discussion and Student Success in Web-Based Education / Erik Benrud . .................................................................................................................................3285 Chapter 7.27. The Influences and Responses of Women in IT Education / Kathryn J. Maser .....3293 Chapter 7.28. Factors Affecting the Adoption of Educational Technology / Graeme Salter ........3299 Chapter 7.29. EBS E-Learning and Social Integrity / Byung-Ro Lim . .........................................3309 Chapter 7.30. Educational Geostimulation / Vasco Furtado and Eurico Vasconcelos .................3321 Section 8: Emerging Trends in Online and Distance Learning This concluding section highlights research potential within the field of online and distance learning while exploring uncharted areas of study for the advancement of the discipline. The introductory chapters set the stage for future research directions and topical suggestions for continued debate. Providing a fresh, alternative view of distance education, colleagues from universities all over the world explore the adaptive traits necessary as disseminators of knowledge within this evolving platform of education; a reminder that not only is the role of the learner rapidly evolving, but so too is the role of the facilitator. Educational programs throughout the world have witnessed fundamental changes during the past two decades—changes that are emphasized in the 25 rigorously researched chapters included in this section. With continued technological innovations in information and communication technology and with on-going discovery and research into newer and more innovative techniques and applications, the online and distance learning discipline will continue to witness an explosion of knowledge within this rapidly evolving field. Chapter 8.1. Trends and Perspectives in Online Education / Bruce Rollier and Fred Niederman... 3340 Chapter 8.2. E-Learning in Higher Education: The Need for a New Pedagogy / Dirk Morrison . ..3346 Chapter 8.3. Evaluation of an Open Learning Environment / Geraldine Clarebout, Jan Elen, Joost Lowyck, Jef Van den Enden, and Erwin Van den Ende .......................................................3359 Chapter 8.4. Faculty Perceptions and Participation in Distance Education / James R. Lindner, Kim E. Dooley, Chanda Elbert, Timothy H. Murphy, and Theresa P. Murphrey . ........................3365

Chapter 8.5. How Distance Programs Will Affect Students, Courses, Faculty, and Institutional Futures / Murray Turoff, Richard Discenza, and Caroline Howard .............................................3370 Chapter 8.6. Awareness Design in Online Collaborative Learning: A Pedagogical Perspective / Curtis J. Bonk, Seung-hee Lee, Xiaojing Liu, and Bude Su . ........................................................3385 Chapter 8.7. On the Convergence of Formal Ontologies and Standardized E-Learning / Miguel-Ángel Sicilia and Elena García . ......................................................................................3401 Chapter 8.8. Guerilla Evaluation: Adapting to the Terrain and Situation / Tad Waddington, Bruce Aaron, and Rachael Sheldrick ............................................................................................3416 Chapter 8.9. Standards? What and Why? / Phil Long and Frank Tansey .....................................3433 Chapter 8.10. A New Taxonomy for Evaluation Studies of Online Collaborative Learning / Lesley Treleaven . ..........................................................................................................................3449 Chapter 8.11. Staffing the Transition to the Vitual Academic Library: Competencies, Characteristics, and Change / Todd Chavez ..................................................................................3465 Chapter 8.12. Knowledge Management Trends: Challenges and Opportunities for Educational Institutions / Lisa A. Petrides and Lilly Nguyen ...........................................................................3475 Chapter 8.13. Online Academic Libraries and Distance Learning / Merilyn Burke, Bruce Lubotsky Levin, and Ardis Hanson . ...................................................................................3484 Chapter 8.14. Online Assessment and Instruction Using Learning Maps: A Glimpse into the Future / Jim Lee, Sylvia Tidwell-Scheuring, and Karen Barton ...................................................3490 Chapter 8.15. Future Directions of Multimedia Technologies in E-Learning / Timothy K. Shih, Qing Li, and Jason C. Hung .........................................................................................................3500 Chapter 8.16. The Changing Library Education Curriculum / Vicki L. Gregory ..........................3508 Chapter 8.17. E-Learning and New Teaching Scenarios: The Mediation of Technology Between Methodologies and Teaching Objectives / Cecilia Mari, Sara Genone, and Luca Mari .............3513 Chapter 8.18. Virtual Schools / Glenn Russell ..............................................................................3528 Chapter 8.19. Future Directions of Course Management Systems / David Mills .........................3535 Chapter 8.20. Next Generation: Speculations in New Technologies / Bryan Alexander ..............3549 Chapter 8.21. The Emerging Use of E-Learning Environments in K-12 Education: Implications for School Decision Makers / Christopher O’Mahony . ...............................................................3559

Chapter 8.22. Academic, Economic, and Technological Trends Affecting Distance Education / Nathan K. Lindsay, Peter B. Williams, and Scott L. Howell . .......................................................3577 Chapter 8.23. Social Change Research and the Gender Gap in Computer Science / Jane Margolis and Allan Fisher ...................................................................................................3588 Chapter 8.24. simSchool and the Conceptual Assessment Framework / David Gibson ...............3595

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Preface

Technological advancements of the past two decades have allowed educators to deliver various effective academic programs to knowledge seekers and students around the world free of the traditional dependency on campus based programs. These advancements are formidable technological innovations that have profoundly impacted all realms of society including business, education, health care, and interpersonal and intercultural interfacing. During this period of time numerous researchers and educators have developed a variety of techniques, methodologies, and measurement tools that have allowed them to develop, deliver and at the same time evaluate the effectiveness of several online and distance learning programs. The explosion of these technologies and methodologies in this new field of web-based education and online learning have created an abundance of new, state-of-art literature related to all aspects of this expanding discipline, allowing researchers and practicing educators to learn about the latest discoveries in the filed of distance learning and online teaching. Due to rapid technological changes that are continually taking place, it is a constant challenge for researchers and educators in distance learning to stay abreast of the far-reaching effects of this change, and to be able to develop and deliver more innovative methodologies and techniques utilizing new technological innovation. In order to provide the most comprehensive, in-depth, and recent coverage of all issues related to web-based education and online distance learning, as well as to offer a single reference source on all conceptual, methodological, technical and managerial issues, as well as the opportunities, future challenges and emerging trends related to distance learning, Information Science Reference is pleased to offer a six-volume reference collection on this rapidly growing discipline, in order to empower students, researchers, academicians, and practitioners with a comprehensive understanding of the most critical areas within this field of study. This collection entitled, Online and Distance Learning: Concepts, Methodologies, Tools, and Applications, is organized in eight (8) distinct sections, providing the most wide-ranging coverage of topics such as: (1) Fundamental Concepts and Theories; (2) Development and Design Methodologies; (3) Tools and Technologies; (4) Utilization and Application; (5) Organizational and Social Implications; (6) Managerial Impact; (7) Critical Issues; and (8) Emerging Trends. The following provides a summary of what is covered in each section of this multi volume reference collection: Section 1, Fundamental Concepts and Theories, serves as a foundation for this exhaustive reference tool by addressing crucial theories essential to the understanding of online and distance learning. Chapters such as, Technology’s Role in Distance Education by Caroline Howard, Murray Turoff and Richard Discneza, as well as Distance Education in the Era of the Internet by Giorgio Agosti provide an excellent framework in which to position distance learning within the field of information science and technology. Sara Dexter’s, Principles to Guide the Integration and Implementation of Educational Technology offers excellent insight into the critical incorporation of technology into the classroom for educators and administers alike, while chapters such as, Learning IT: Where Do Lecturers Fit? by Tanya McGill and Samantha Bax address some of the basic, yet crucial stumbling blocks of distance learning. With 60 chapters comprising this foundational section, the reader can learn and chose from a compendium of expert research on the elemental theories underscoring online and distance learning discipline.

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Section 2, Development and Design Methodologies, provides in-depth coverage of conceptual architectures and distance learning frameworks to provide the reader with a comprehensive understanding of the emerging technological developments within the field of online and distance learning. A Conceptual Architecture for the Development of Interactive Educational Media by Claus Pahl offers research fundamentals imperative to the understanding of the design of educational tools. Conversely, Gregg Asher’s, Inadequate Infrastructure and the Infusion of Technology into K-12 Education explores the shortcomings of those schools under-prepared for emersion into the world of online and distance learning. From basic designs to abstract development, chapters such as Systems Model of Educational Processes by Charles E. Beck and Reliving History with ‘Reliving the Revolution’: Designing Augmented Reality Games to Teach the Critical Thinking of History by Karen Schrier serve to expand the reaches of development and design technologies within the online and distance learning community. This section includes over 40 contributions from researchers throughout the world on the topic of online development and methodologies in distance learning. Section 3, Tools and Technologies, presents an extensive coverage of various tools and technologies available in the field of distance learning that practicing educators and researchers alike can utilize to develop different techniques in support of offering distance learning educational programs. Chapters such as Core Principles of Educational Multimedia by Geraldine Torrisi-Steele enlightens readers about the fundamental research on one of the many tools used to facilitate and enhance the distance learning experience whereas chapters like, Hyper Video for Distance Learning by Mario Bochicchio and Nicola Fiore explore the latest technological offerings. It is through these rigorously researched chapters that the reader is provided with countless examples of the upand-coming tools and technologies emerging from the field of online and distance learning. Another contribution entitled Vega Grid Technology, Hyper Video, Learning Portals, Wireless Technologies, Simulation and Gaming and Videoconferencing explores some of the recent technologies that can have been deployed in support of distance learning course offerings. With more than 35 chapters, this section offers a broad treatment of some of the many tools and technologies within the online and distance learning community. Section 4, Utilization and Application, discusses a variety of applications and opportunities available that can be considered by practicing educators in developing viable and effective distance learning educational programs. This section includes more than 40 chapters such as Overcoming Organizational Barriers to Web Accessibility in Higher Education: A Case Study by Amy Scott Metcalfe which incorporates applications of distance learning into the higher education society, while chapters such as Dorris Lee’s, Implementing, discusses the utilization of online learning within the corporate realm. Also considered in this section are the challenges faced when utilizing distance learning as outlined by Martha Cleveland-Innes, Randy Garrison, and Ellen Kinsel’s, Role Adjustment for Learners in an Online Community of Inquiry: Identifying the Challenges of Incoming Online Learners. The adaptability of developing countries is also given consideration in chapters like, Issues of E-Learning in Third World Countries by Shantha Fernando which investigates the major hurdles faced by the socio-economic underprivileged within our global community. Contributions included in this section provide excellent coverage of today’s global community and how distance learning technologies and education are impacting the social fabric of our present-day global village. Section 5, Organizational and Social Implications, includes a wide range of research pertaining to the social and organizational impact of online and distance technologies around the world. Introducing this section is Pier Cesare Rivoltella’s chapter entitled, Education and Organization: ICT, Assets, and Values providing a comprehensive introduction of education and its technological role within organizations as a social construct. Additional chapters included in this section such as Narrowing the Digital Divide: Technology Integration in a High-Poverty School by June K. Hilton epitomize one of the most contested issues within society concerning access to technology—the digital divide. Also introducing a rising concern within the education organization is Bryan D. Bradley’s, Legal Implications of Online Assessment: Issues for Educators which provides an alternative approach to research regarding the legality of online assessment. The discussions presented in this section offer research into the integration of technology to allow access for all classrooms regardless of socioeconomic status; arguably the most important social and organizational barrier that this field of study has yet to overcome. Section 6, Managerial Impact, presents contemporary coverage of the social implications of online and distance learning, more specifically related to the corporate and managerial utilization of online learning technologies and applications, and how online learning can be facilitated within these organizations. Core ideas such as training

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and continuing education of human resources in modern organizations are discussed through these more than 25 chapters. Implementing and Sustaining E-Learning in the Workplace by Zane Berge discusses strategic planning related to the organizational elements and the e-learning program requirements that are necessary to build a framework in order to institutionalize and sustain e-learning as a core business process. Equally as crucial, within the educational management system, chapters such as The Management of Virtual Classes in School District Digital Intranets by Ken Stevens address the latest research concerning the management of digital networking via the internet to schools, particularly those in rural communities. Concluding this section is a chapter by Catherine C. Schifter of Temple University, Faculty Participation in Distance Education Programs. This chapter refocuses the issue of the managerial impact of distance learning to the facilitators by examining the crucial role that faculty members play in the success of a virtual classroom. Section 7, Critical Issues, containing 30 chapters addressing issues such as gender barriers, Web accessibility, quality assurance and development of e-learning in under-developed countries presents readers with an in-depth analysis of the most current and relevant issues within this growing field of study. Barbara A Frey, Ashli Molinero and Ellen Cohn’s, Increasing Web Accessibility and Usability in Higher Education, develops an excellent model for researchers and practitioners as attempts are made to expand the reaches of online and distance learning within the higher education community. Forming a frameworks in which to position the issues faced in this growing field are provided by research found in chapters such as, Inquisitivism: The Evolution of a Constructivist Approach for Web-Based Instruction, by Dwayne Harapnuik—a chapter that takes the core psychological paradigms of education and translates them into applicable ideas within the exploding realm of online and distance education. Crucial examinations such as that presented in David Catterick’s chapter, Do the Philosophical Foundations of Online Learning Disadvantage Non-Western Students? serves to reinforce the ideas presented in this section while simultaneously enticing and inspiring the reader to research further and participate in this increasingly pertinent debate. The concluding section of this authoritative reference tool, Emerging Trends, highlights research potential within the field of online and distance learning while exploring uncharted areas of study for the advancement of the discipline. Introducing this section is Bruce Rollier’s, Trends and Perspectives in Online Education, which sets the stage for future research directions and topical suggestions for continued debate. Providing a fresh, alternative view of distance education is the chapter, Faculty Perceptions and Participation in Distance Education, by James R. Lindner, Kim E. Dooley, Chanda Elbert, Timothy H. Murphy and Theresa P. Murphrey of Texas A&M University. These colleagues explore the adaptive traits necessary as disseminators of knowledge within this evolving platform of education; a reminder that not only is the role of the learner rapidly evolving, but so too is the role of the facilitator. Another a debate which currently finds itself at the forefront of research within this field is presented by David Gibson’s research which centers on simSchool and gaming within online and distance learning as a discipline, whereas Bernhard Ertl, Katrin Winkler, and Heinz Mandl’s, E-Learning: Trends and Future Development, summarizes contemporary trends while projecting future developments. Although the primary organization of the contents in this multi-volume is based on its eight sections, offering a progression of coverage of the important concepts, methodologies, technologies, applications, social issues, and emerging trends, the reader can also identify specific contents by utilizing the extensive indexing system listed at the end of each volume. Furthermore to ensure that the scholar, researcher and educator have access to the entire contents of this multi volume set as well as additional coverage that could not be include in the print version of this publication, the publisher will provide unlimited multi-user electronic access to the online aggregated database of this collection for the life of edition, free of charge when a library purchases a print copy. This aggregated database provides far more contents than what can be included in the print version in addition to continual updates. This unlimited access, coupled with the continuous updates to the database ensures that the most current research is accessible knowledge seekers. Educational programs at the college level have witnessed fundamental changes during the past two decades, moving more toward campus-free approaches and allowing millions of non-traditional as well traditional students around the globe to have access to educational programs which two decades ago, were inaccessible. In addition to this transformation, many traditional educational programs have taken advantage of the technologies offered by distance and online learning in order to expand and augment their existing programs. This has allowed educators to serve their student base more effectively and efficiently in the modern virtual world. With continued technological innovations in information and communication technology and with on-going discovery and research into

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newer and more innovative techniques and applications, the online and distance learning discipline will continue to witness an explosion of knowledge within this rapidly evolving field. This continued trend will also lead to expansion of the literature related to all areas of this discipline. Access to more up-to-date research findings and knowledge of established techniques and lessons to be learned from other researchers and practicing educators will facilitate the discovery and invention of more effective methodologies and applications of online and distance learning technologies. The diverse and comprehensive coverage of online and distance learning in this six-volume authoritative publication will contribute to a better understanding of all topics, research, and discoveries in this developing, significant field of study. Furthermore, the contributions included in this multi-volume collection series will be instrumental in the expansion of the body of knowledge in this enormous field, resulting in a greater understanding of the fundamentals while fueling the research initiatives in emerging fields. We at Information Science Reference, along with the editor of this collection, and the publisher hope that this multi-volume collection will become instrumental in the expansion of the discipline and will promote the continued growth of online and distance learning.

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Introductory Chapter: Contemporary Research in Distance Learning Lawrence Tomei, EdD Robert Morris University, USA

INTRODUCTION Over the last three decades, research and the literature has been building the theoretical foundations for examining contemporary research in distance learning. By 1978, my personal investigations into the fledgling art of instructional technology were interrupted by an opportunity to experience distance learning first-hand. The United States military was one of the first major organizations to recognize the advantages of distance learning. By 1945, they brought distance learning to bear to train a vast cadre of enlisted and officer professional in every imaginable topic, from human relations to information technology. And, they did it via mail-order courses delivered by the U.S. Post Office, pored over in the privacy of one’s home or office, and assessed with the help of a number-two pencil and a balloon answer sheet. The answer sheet was eventually returned in a sealed envelop and evaluated by a team of anonymous reviewers. Distance learning had its beginning as a paper-intensive media that pre-dated the computer. It filled the void caused by a burgeoning population of adult learners in search of a self-paced, individualized, instructional regimen—forming the underpinnings of many of the concepts and principles that guide distance learning today. To be sure, current research has advanced rapidly to fill the lofty demand for proof that distance learning is an effective instructional strategy. Sparked by many constituents, the search for evidence continues unabated and has brought us to this multi-volume offering. Contemporary Research in Distance Learning will argue in support of distance learning as a viable instructional strategy and offer the results of new investigations that bring to light new questions regarding teaching and learning. To structure the discussion, eight dimensions of learning in general and distance learning specifically are posited in this opening chapter. They include: • • • • • •

Fundamental Concepts and Theories of Distance Learning Development and Design Methodologies Tools and Technologies Utilization and Application of Distance Learning Organizational and Social Implications of Distance Learning Managerial Impact of Distance Learning

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• •

Critical Issues in Distance Learning Emerging Trends in Distance Learning

FUNDAMENTAL CONCEPTS AND THEORIES OF DISTANCE LEARNING Most instructional strategies hinge their application to some theoretical basis in concept and theories; distance learning is no exception. Classroom teaching historically clings to one of three prominent schools of educational psychology: behaviorism, cognitivism, or humanism. Behavioral teachers employ the stimulus-response-reinforcement model for the majority of their teaching using a predefined order of instruction (simple to complex, general to specific, etc.) that all learners encounter in a carefully planned and delivered sequence. The cognitivist departs from its behavioral heritage as it shifts its focus from reinforcement of a student behavior to a building block approach that honors not the environment but the nature of knowledge. Humanists are the latest manifestation of learning psychology; products of the 1980’s—the “touchy-feely” generation of affective teachers that place the personalization of information on the forefront of learning. To them, teachers may deliver the content, but learning is solely the purview of the student.

The Educational Psychology of Distance Learning Behaviorism. Distance learning matured from behavioral roots as a text-based content delivery system. Correspondence courses, the earliest expression of carefully sequenced and delivered content, combined with immediate reinforcement to produce observable learning. Using a contemporary example, the eCollege learning management system (or LMS) offers its faculty-client a host of tools that would make B.F. Skinner proud. Week 12 content material follows closely on the heels of Weeks 1-11; assessment tools authenticate learning and provide immediate feedback to the instructor; and, asynchronous tools such as discussion boards, drop boxes, email, and documentsharing extend the behavioral features of the distance learning program. Cognitivism. For cognitive educators, successful learning is an additive process of skills and competencies that develop the personal learning strategies of the individual. As the demand for distance-based education matured along with the work of such notables as Jean Piaget and Carl Rogers, additional technology features were invented to facilitate cognitive teaching. The Blackboard LMS, for instance, epitomizes the cognitive approach to online teaching with its content-based instructional presentation. Instead of introducing weekly schedules of materials, the cognitive educator compartmentalizes instruction by topic, concept, or theme. Blackboard assists in this presentation with its structure based not on sequence but on content. Humanism. Finally, teaching enters the modern educational scene bringing with it a concern for the affective nature of the learner. Personalization of knowledge is the true test of learning for the humanist—a critical concept that serves as a rallying point for advocates of distance learning. The interactive synchronous package called Elluminate combines four regions of the video screen to effectively embrace the learner surrounding the student with an interactive whiteboard, voice and video from the instructor, a polled-response window to communicate with the instructor, and a text-based chat window for posing questions and offering less time-critical comments. For even the most die-hard humanist, technology can no longer be dismissed as a cold, detached media for teaching and learning.

Taxonomies for Teaching and Learning

To build on the previous introduction to educational psychologies and their contributions to the theories of distance learning, we turn our attention now to classification systems. Historically, taxonomies evolved in response to demand from educators to stratify and categorize student thinking and learning outcomes. Arguably the most well-known system for classifying learning objectives is that of Benjamin Bloom and his taxonomy for the cognitive domain. Bloom’s taxonomy has served as the benchmark for countless research projects and innumerable investigations concerning higher-order thinking. Progressing from simple knowledge, the student is quickly confronted

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with the challenges of comprehension, application, analysis, synthesis, and evaluation as the taxonomy forms the framework for advancing learning objectives. Other familiar classification systems include the taxonomy for the affective domain that considers values, feelings, emotions, and the like (Krathwohl, 1984) and the taxonomy for the psychomotor domain that does the same for fine and motor skills (Kibler, 1970). In 2005, the taxonomy for the technology domain was published and, for the first time, defined the six levels of technology for teaching and learning (Tomei, 2005). The technology taxonomy considers how to address distance learning and its various implementations for teaching and learning. Specifically: Literacy. Several of the papers presented herein focus on the literacy of distance learning exploring the basic technologies that support teaching at a distance, teaching online, or teaching with technology. Literacy is defined as the “most modest level of technology-based learning offering the minimum degree of competency with respect to the use of technology as a teaching and learning strategy” (Tomei, 2005). Distance learning literacies offer readers an opportunity to update their knowledge of state-of-the-art delivery media including learning management systems, video conferencing, multimedia, and web-based instruction. Collaboration. Collaboration employs technologies for effective interpersonal communication. Many of the submissions found in Contemporary Research in Distance Learning offer the results of studies that demonstrate the effectiveness of distance learning as a communications-based instructional strategy. Stay alert to those contributions that focus on collaboration and those that move the learner up the taxonomy to even higher levels of technology integration. Decision-making. On the surface, decision-making may not seem an instinctive level of technology implementation with respect to distance learning. Perhaps not on the surface, but not very far beneath it. Several of the papers in this text focus the reader’s attention on decision support systems for instructional delivery. Read carefully those papers that describe how instructors use management systems to track student learning, progress toward specific program/ course goals, and assess student learning outcomes while making distance learning a more effective media. Technology infusion. At the higher levels of the taxonomy, the focus of distance learning shifts to its use in the teaching/ learning equation. Infusion, the fourth level of the taxonomy, is often subtitled “learning with technology” and involves the identification, harvesting, and application of existing technology to unique learning situations (Tomei, 2005). What better description for distance learning? In the realm of distance learning, student learning demands that literacy, collaboration, and decision-making (from the previous three levels) are brought into play to use technology for learning. Contemporary concepts and theories in distance learning offer numerous articles sharing research and scholarship associated with the infusion of technology. Technology integration. Integration is sub-titled “teaching with technology.” At this fifth level of the taxonomy are articles that discuss the successful mixture of video conferencing, synchronous and asynchronous communications tools, online assessment, grade book software, ipods and mp3 players in support of teaching. It is important to note that the title of this text is Contemporary Research in Distance Learning—not “online teaching” or “teaching with technology.” These other terms are often used synonymously with distance learning. For our purposes here, they are simply too restrictive and constraining; whereas, distance learning is more encompassing. The articles found in the Fundamental Concepts and Theories of Distance Learning offer a close-up look at how these applications make a difference in the ways students learn and instructors teach using technology. Tech-ology. Finally, for those already familiar with the higher levels of the taxonomy, no examination of distance learning is complete without a discussion of the many implications of technology. Tech-ology is the study of technology, defined as “the ability to judge the universal impact, shared values, and social implications of technology use and its influence on teaching and learning” (Tomei, 2005). A regard for technology as a discipline in its own right raises many issues that deserve consideration. In sum, the papers presented herein offer an examination of the fundamental concepts and theories that form the foundation of distance learning. To employ distance learning as an effective instructional strategy, consideration of the design and development of distance-based instruction is required. Many methodologies, psychologies, and technologies interact to create well-designed instruction; an introduction into the design and development models seems worthy of our time.

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Figure 1. ADDIE model of instructional design (Smith & Ragan, 1993) Analysis

Implementation

Evaluation

Design

Development

Figure 2. Backward design model (Wiggins & McTighe,1998)

DESIGN AND DEVELOPMENT METHODOLOGIES Regardless of the number of models suggesting a design and development schemata for instructional delivery, certain key elements are typically present. As the articles in this text unfold, it is recommended that the reader consider each paper’s contributions toward research into the design and/or development of distance learning programs.

Design Issues Design issues change over time and vary according to an institution’s involvement in distance learning. For example, recognizing the degree of learner interest in distance learning is a design issue; so is orienting and training faculty in using distance learning resources. For example, should the institution expect faculty to design effective online lessons without dedicated technical (as well as instructional design) assistance? Many online programs offer both instructors and students a proven model for identifying, assigning, and tracking distance learners at established

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levels. Some institutions employ acknowledged models of instructional design; the most popular are the ADDIE model (Figure 1), Kemp Model, and the backward design model (Figure 2).

Development Issues The Engine for the Design of Online Education (Tomei, 2007) identifies some 15 unique developmental demands of the traditional, adult, and distance learner. For our purposes, the more important aspects of the engine are the five focus areas on which educators concentrate to create viable instructional materials. Specifically: • • • • •

Focus on the learner Focus on learning Focus on resources Focus on delivery Focus on outcomes

Focus on the learner. Likely, the most widely-read contributions of the Contemporary Research on Distance Learning would have a recognizable focus on the learner; in this case, the distance learner. Ideally, there will be aspects addressing the learner in every article as no other issue lies more at the heart of effective instruction than consideration of the target audience. The primary responsibility of every educator is to promote (some would say guarantee) student learning. Traditional learners are served by the psychology of pedagogy, normally associated with the teaching of children. But, for many, pedagogy constitutes a wider focus on the study of how learners acquire knowledge. For others, adult learners are their own brand of learner and the discipline is just beginning to appreciate the breadth of their learning demands. In The Modern Practice of Adult Education (1980), Knowles defined andragogy as “an emerging technology for adult learning.” His four andragogical assumptions are that adults (1) move from dependency to self-directedness; (2) draw upon their reservoir of experience for learning; (3) are ready to learn when they assume new roles; and (4) want to solve problems and apply new knowledge immediately. For distance learning, andragogy offers just-in-time learning, infusion of real-world applications into the learning experience, and the incorporation of life experiences into the virtual classroom. Teaching at a distance adds another dimension; one that Priest (2002) coined “allegegory,” or a focus on lifelong learning. In sum, this focus on the learner encompasses traditional, adult, and distance learners across the spectrum of design and development. Many of the articles presented in this text explore how the most effective distance learning applications are designed, developed, and implemented. Focus on learning. Learning is closely aligned to taxonomies that serve as mental organizers of concepts and theories related to distance learning. As we discussed earlier, taxonomies are categorized by domain: cognitive, affective, psychomotor, and technology. As you seek out specific articles in this text, try to label each contribution by one of these classification systems. Distance learning instruction, like the best traditional classroom environments, addresses knowledge acquisition at progressively higher and more complex levels of thinking. Adult education pushes distance learning from knowledge to practical application, mere facts to effective implementation, and delayed learning opportunities to immediate purpose. At the top of the hierarchy are research, practice, and evaluation. It is suggested that the taxonomies be used to categorize various aspects of distance learning and how technology-based instruction moves learning to higher levels of thinking. Focus on resources. Traditional learners have been provided with text-based materials for nearly 600 years, ever since the Gutenberg press, with its wooden and metal movable type printing, brought down the price of printed materials and made these materials available to the masses. Since then, text media has undergone numerous transformations, yet it remains the media of choice in most traditional classrooms. And, why not, it has served us well. Handouts, workbooks, study sheets, and encyclopedias offer a diversity of instructional materials for the traditional learner.

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Adult learners, however, are unrelenting in their search for a broader assortment of learning alternatives including visual graphics, audio reproductions, and CDROM-based digital content. Distance learning commands the widest array of instructional materials. Multimedia affords the distance educator a host of resources divided roughly across print, audio/ video, and digital collections. In addition, an entirely new inventory of learning tools is presented in the next section of this chapter. As distance learning continues to grow, future online instructors should expect to encounter resources heretofore unimagined. Two-way video, desktop conferencing, and pod casting, are just beginning to make their mark in distance learning courses supported by top-notch learning management systems. This focus on resources is the third rung on the design model for distance learning courses development. Once selected (or in the case of distance learning, once infused into online courses), we can turn our attention to the most effective modes for training at a distance. Focus on delivery. Historically, instructors of traditional learners opt for classroom presentations (i.e., lectures or in-class discussions). As learners have grown more sophisticated, so too have the demands for variety in the delivery of instruction. Adults, particularly, have shifted the focus of delivery from traditional classroom formats to newer modes of participative, self-directed instruction that includes such well-known practices as cooperative learning and discovery learning. Delivery for distance learning, however, takes on yet another dimension as instructors to choose delivery modes that include repository (online materials only), hybrid (partially online, partially face-to-face), or immersion (totally online) courses. A typical learning management system offers choices of delivery environments that match not only the best mode for teaching but one that also matches the technological skills and competencies of the instructor and student. Focus on outcomes. Conventional assessments are well-known. They may take many forms and serve multiple masters, but measuring student outcomes is the ultimate goal of any worthwhile evaluation instrument whether it involves traditional, adult, or distance learners. Traditionally, assessment includes both formative and summative evaluations such as true-false, multiple choice, and short-answer responses. Online courses, too, use traditional tools to assess learning, even if somewhat less effectively, because of the physical separation between the instructor and student. Adult learners expect real-world challenges and more practical measures of their knowledge. Discovery learning tasks, project-based exercises, and collaborative group-work are examples of more authentic assessments, many of which are possible with a well-designed and developed online course. Finally, selecting a methodology for assessing distance learning presupposes a virtual learning environment, one that begs the question: how do I know the student on the other end of my connection is really my student? True distance learning encourages more synchronous participation to foster this degree of checks and balances between instructor and student and between student and student. Chat rooms, videoconferencing, threaded discussions, and webcasting involve the student in collaborative discussions that make falsifying attendance and participation more difficult. Integration of a few more innovative tools on the part of the instructor and reasonable assurance of valid assessment is definitely possible. Recap. Designing effective distance learning, then, is a five-step process that focuses the attention of the course designer on the learner, learning, resources, delivery modes, and learning outcomes. The articles subsumed under Contemporary Research in Distance Learning explore various design and development methodologies.

DISTANCE LEARNING TOOLS AND TECHNIQUES Perhaps my personal, all-time favorite portion of the Contemporary Research in Distance Learning is the focus on tools and techniques of distance learning. Using the apparatus of the taxonomy for the technology domain introduced earlier, the reader has a chance to explore Level 4 (Technology for Learning) and Level 5 (Technologies for Teaching) in this section of the text. Technology for learning identifies tools used for acquiring knowledge; specifically, distance learning features that students employ to enhance their own understanding, increase productivity, and promote creativity. Many of the articles presented in these volumes offer insights into such timely topics as knowledge management, interactive response systems, use of hyper media and digital video for learning, change management in a distance learn-

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ing environment, student perception of online learning, electronic reading programs, information retrieval, and evaluation of learning effectiveness. These tools and techniques will help the distance learner identify, select, and evaluate how best to learn in an online class. Technology for teaching advances the view that technology can be a means for creating new tools, content materials, and media for teaching. Incorporating multimedia into an online course, integrating a webinar to deliver content, building an interactive power point presentation, or introducing an electronic portfolio are good examples of technology for teaching. Some other tools common to teaching involve establishing student and/or course portals, engineering advanced learning system, modeling smart learning organizations, and offering database tools for action research. Consider articles contained in this text that discuss modifications to online learning environments that support distance learning; specifically, how some opportunities promote learning online and how technology-enriched research enhances delivery of online programs..

UTILIZATION AND APPLICATION OF DISTANCE LEARNING In simplest terms, distance learning courses take on one of three modalities: repository, hybrid, or online. Many of the papers presented in the Contemporary Research in Distance Learning demonstrate successful applications of distance learning at one or more of these levels. A few papers attempt to compare and contrast similarities and differences among all three levels. Repository courses. A repository course uses the shell of a learning management system to contain instructional materials most often used in traditional, face-to-face courses. A course syllabus, selected readings (usually Webbased or e-books), audio/video clips, and the like are typically loaded into the course shell and offered to students in lieu of (or as supplements to) hard-copy handouts, cumbersome text books, or CDROM-based resources. In addition, a repository course may also use other common learning management system tools such as email, threaded discussions, and chat rooms to promote synchronous and asynchronous course objectives. Hybrid courses. Hybrid implementations of distance learning involve courses that typically contain up to 50% online learning. For example, some semester-long courses may alternate weekly face-to-face sessions on campus with synchronous chat sessions via online. In this case, the course shell also integrates synchronous and asynchronous tools. For the hybrid environment, the scale and scope expands—often geometrically—with respect to the number of users, access time, and time on task. Hybrid course shells offer organizational schemes to the instructor and students often presented as “weeks” or “sessions.” The inherent organization of an LMS also offers materials structured either by topic (i.e., content material) or resource media (text, audio, video, etc.). Instructors who employ a scheme whereby face-to-face sessions alternate with totally online sessions often find adults very receptive to this method of delivery as it often fits better into the busy schedules of student who work full-time. Hybrid courses also support institutional goals when their online programs are just getting off the ground, delayed by wary faculty and/ or a historically in-resident campus. Finally, hybrid courses can be an excellent compromise at universities and colleges as well as corporate training environments not quite ready to move on to the next level of distance learning: totally online instruction. Online courses. Totally online courses integrate the full range of distance learning modalities and most often target geographically-separated students. Courses that employ online features build on the capabilities of both previous levels (repository and hybrid) and extend instructional delivery to student who rarely, if ever, set foot in campus classroom or corporate training facility. Some of the additional distance learning tools often used in a totally online course include the synchronous webinar, voice-over-IP lecture, and webcasting. In addition (and you will notice this in many of the articles), a host of project management, progress tracking, library services, assessment and tutoring tools, and other support features are made available to instructors and students.

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As you peruse the table of contents for this six-volume text, pay particular attention to the articles categorized under Utilization and Application. They will provide insight into how distance learning can be employed effectively for teaching and learning.

ORGANIZATIONAL AND SOCIAL IMPLICATIONS OF DISTANCE LEARNING Organizational implications. Organizationally, the connotations of using a distance learning environment to teach are truly multi-dimensional. Academically, distance learning involves issues of course integrity, transferability, transcripts, student/course evaluation, admission standards, curriculum/course approval, accreditation, online registration/ cancellations/ withdrawals, course/ program/ degree availability, and recruiting/ marketing. Financially, administrators worry about tuition rates for online courses, technology fees, the impact of online courses on enrollment, administrative costs (i.e., IT personnel, technicians, etc.), impact on classroom availability, server space, staffing, and the like. From a faculty perspective, organizational issues associated with distance learning include compensation and workload, development incentives, training, union contracts, class monitoring, faculty support, and course evaluations. A study begun in 2003 and reported in the Journal of Technology and Teacher Education found that enrollment in online courses is often over-subscribed, serving as “cash cows” for many colleges and universities. The study went on to conclude “the ideal traditional class size (based on factors of instructional content, counseling and advisement, and student assessment) was 17 students (for graduate-level courses) while the ideal online class size was 12 students (Tomei, 2006). Also, there are legal aspects of online teaching, many of which must be resolved early in the life of a distance learning program. For instance, intellectual property is a consideration. As courses are developed online, institutions are inevitably confronted with the question of who owns those courses. Unlike traditional environments, distance-based courses are easily downloaded, archived, and distributed. However, it is this same capability that makes theft of intellectual property much more likely. In a similar vein, we now have more issues associated with copyright infringement, academic integrity, and attribution of sources than ever before. Another organizational issue concerns student support services. Once the exclusive domain of the university registrar, distance learning changes the very nature of how we advise students who are not physically present on campus, conduct timely counseling in response to virtual learning difficulties, offer electronic library access, deliver digital content materials (i.e., books, handouts, etc.), provide the necessary entry-level student training in an online environment, proctor tests, and so on all in addition to the “normal” support functions of admissions, registration, and financial aid. Before, concerns over systems reliability, connectivity/access, hardware/software, setup timelines, infrastructure, technical support (staffing), and scheduling remained the domain of the IT department. With distance learning, technical issues, as well as variations in expertise between faculty, staff, students and administrators become critical organizational issues. Finally, issues associated with organizational culture consider the adoption of innovations, acceptance of online/distance teaching, understanding teaching at a distance and what works, and the impact of distance learning on general organizational values within the institution. As important as the impact of distance learning is on an organization, so, too, are the social aspects of teaching at a distance. Social implications. Closely aligned with Bloom’s highest level of the cognitive domain, no discussion of distance learning would be complete without an examination of the organizational implications and the social impact of teaching at a distance. Technology use and its influence on teaching and learning are never more apparent than in distance learning. An adage claims that a learner retains 60% of what they read, 70% of what they hear, 80% of what they see, and 90% of what they do. Over the years, that maxim has expanded. “To truly learn, try teaching.” And, more recently, distance educators and instructional technologists have added, “to really learn, try teaching with technology.” Distance educators lie at the pinnacle of this hierarchy because, in addition to the content knowledge required, they must build their lessons while considering the impact of their technology on learner achievement, student



feedback and assessment, equal access, barriers to learning, individual attitudes, and many other issues largely set aside by the traditional classroom teacher who has the benefit of face-to-face responses. Distance educators have a broader responsibility to consider a myriad of learning styles and characteristics that apply to all students (Grasha, 1996), including independent students who prefer self-paced instruction and working alone (or in very small groups) when tackling course projects. Too, dependent learners often enroll in distance learning courses. They look to teachers for structure and guidance and continue to depend on an authority figure to tell them what to do. Distance educators must adapt their totally online environments to provide this structure while encouraging autonomous learning. Competitive students are found online as well as in the traditional classroom. They seek to perform better than their peers and seek recognition for their academic accomplishments. To do that, distance-based tools must be employed to provide a different view of assessment; one that allows immediate feedback, formative and summative evaluations, and student-teacher and student-student interaction. Synchronous tools such as chat rooms afford both recognition and comparisons crucial to the more academically aggressive student. Collaborative learners attain information by sharing and cooperating. Both teachers and peers provide opportunities for small group discussions and group projects. Distance learning technologies contribute a host of synchronous and asynchronous tools that support the collaborative learner; including, chat rooms, threaded discussions, two-way voice/video, and more. Avoidant learners, who prefer not to attend class at all, can actually be ambivalent with regard to acquiring class content. They are typically uninterested and often overwhelmed by class activities. Distance learning technology can overcome any lackluster presentation associated with the traditional classroom. The rapid rise in the number of adult distance learners is testimony to the excitement that online learning engenders in some students who may have been disengaged by face-to-face learning. Finally, participant learners are excited about the real-world class activities and simulations that distance learning systems extend beyond the traditional classroom. They are eager to engage in the learning process and attempt as many class-assigned tasks as possible. They actively seek out teacher demands and are not satisfied with anything less than meeting those expectations. In a conventional classroom, where students interact with one another both during and outside of class time, social context of learning is important. The Contemporary Research in Distance Learning presents several papers for your consideration that discuss the strategies and concepts important to achieving student learning via distance. Distance learning itself operates within its own social context, concerning itself with how instruction is presented, how students interact with instructors and other students, and evidence of how learning is generated given geographically separated students. Together, the implications discussed above make for an interesting classification schema for the papers offered in this text. As you delve into the various articles, especially those under the heading of Organizational and Social Implications of Distance Learning, consider the author’s focus on organizational issues and social connotations addressed by each article.

MANAGERIAL IMPACT OF DISTANCE LEARNING Distance education increases access to learning opportunities. As we have already discussed, a well-organized distance-based lesson must accommodate multiple learning styles and serve a variety of learners. In many cases, such courses are likely to attract non-traditional students while serving many or more learners per dollar spent. The American Council on Education’s “Guiding Principles for Distance Learning in a Learning Society” (Sullivan and Rocco, 1996) offers an inventory of principles that reflects the tenets and values of an institution, including: • • •

Learning is a lifelong process, important to successful participation in the social, cultural, civic, and economic life of a democratic society. Lifelong learning involves the development of a range of learning skills and behaviors that should reflect explicit outcomes of learning activities. The diversity of learners, learning needs, learning contexts, and modes of learning must be recognized if learning activities are to achieve their goals.

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• • • •

All members of society have the right to access learning opportunities that provide the means for effective participation in society. Participation in a learning society involves both rights and responsibilities for learners, providers, and those charged with the oversight (i.e., management) of learning. Because learning is social and sensitive to context, learning experiences should support interaction and the development of learning communities, whether social, public, or professional. The development of a learning society may require significant changes in the roles, responsibilities, and activities of provider organizations and personnel as well as of the learners themselves.

Distance learning, then, can be said to influence new policies and procedures for any institution addressing principles of instructional practice, the larger social mission of education and the institution, and the philosophy of teaching in a democratic society. Many of the articles in the Contemporary Research in Distance Learning offer sound practical advice on a variety of topics related to the management of distance learning programs. Each offers importance considerations in the area of this text entitled Managerial Impact. Administering distance learning. A distance learning program (including the learning management system that supports it) is hosted either on-site by the educational institution itself or by the vendor supplying the LMS—for additional cost. For those institutions that cannot afford the development, maintenance, and technical staff to host their own system, vendor support is an attractive option. Once the decision of host-site location is resolved, the institution normally assigns a technical coordinator. The coordinator’s responsibilities include: • • • • • • • • • • •

Needs assessment and learner identification Program approval Marketing and promotion Outreach and recruitment Coordination with classroom programs Assessment and enrollment Testing and progress monitoring Learning materials inventory Instructor supervision Managing and using student and program information Program evaluation and improvement

Providing individualized technical assistance is also an issue and varies according to the delivery system used (see Focus on Delivery in our previous discussion of Design and Development Methodologies). Teacher-learner contact is necessary to promote the technical skills and competencies required for the course. Can the student perform the necessary technical tasks to complete the course objectives? Often, a telephone help desk provides 24/7 response to inquiries. Record-keeping. Many higher education schools are required to maintain tracking data on all enrolled learners—and that includes distance learners. Learners enrolled only in online programs are given unique identifiers within many student management systems that provide demographic and programmatic information. Additionally, learner progress information is normally maintained in an individual portfolio or digital file. Such data is invaluable when monitoring the progress of the individual learner. Accountability. Accountability with respect to distance learning programs is a hot topic, primarily because there is so little research that supports the challenge that distance learning is as effective as the traditional classroom—or effective at all in its own right. Accreditation organizations, federal funding units, state certification agencies, and others are all anxious to see an institution’s attempts to quantify and qualify successful learning using technology. Collecting assessment information on each distance learner presents special problems, especially when enrolled in a totally online course versus hybrid or repository-only courses. At the least a valid random sample of learners is useful to limit the data collection burden.

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Table 1. Distance learning task force issues (BGSU, 2006)

Table 2. Critical issues of distance learning Technical Issues

Administrative Issues

Teaching Issues

Learning Issues

Instructional design and training issues

Student support issues

Technical support issues

Human resources

Guidelines for minimum skills and competencies

Instructional strategy issues

Ancillary support issues

Host vs. remote issues

Technical resources

Professional associations and user groups

Instructional resource issues

Residency and accreditation issues

Dedicated vs. shared staff issues

Organizational resources

Copyright assistance and ownership issues

Student service issues

Faculty compensation, load, rewards, tenure/ promotion issues

Student Advisory Committee

Faculty Advisory Committee

Programmatic resources

Technician Advisory Committee

Administrative Advisory Committee

Other Issues

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Many local programs do not effectively use data (even readily-available data) to examine their program performance and make formative or summative adjustments. In the future, it is likely that more standardized learning outcomes or performance-based information will be mandated. It is prudent to become comfortable with these readily available data when reporting to various local stakeholders such as faculty, adult education dean (where many distance learning programs reside in higher education) or other responsible administrators. Other accountability tools include authentic assessment (e.g., internships, practicum, real-world exercises, etc.), portfolios, and anecdotal records of learner progress that augment required data collection. As asynchronous learning is self-paced and individualized, many consider it important to maintain a good record of learner activities and progress that goes beyond mandated record keeping or testing. Experience shows that teachers collect more detailed information on distance learner’s progress than classroom learners. Teachers often have closer, more regular, and more personal student contact with online students and several papers in this text address the issue of distance learning accountability. Monitoring and evaluation. Emphasizing the importance of a learner’s own self-evaluation and reflection is integral to monitoring. Outcome and achievement measures that reflect curriculum mastery cannot be overlooked in spite of the emphasis on standardized testing. Of the research that does exist, investigations have shown that distance learning programs often have more frequent assessment of learner progress than traditional classroom environments. Because many educators and policy-makers remain skeptical about distance learning, there is often a strong emphasis on documenting mastery as well as recording user satisfaction toward student services received. We should also see a number of manuscripts in this text that address the issue of managerial impact. Institutional goals and mission. Managerial concerns are naturally focused around institutional goals and missions and should be mentioned here. Example matters include, but are not limited to, institutional standards of quality, guiding values and principles, distance learning contributions to department goals, policies and procedures already in place, criteria for judging achievements in quality, acceptable evidence necessary to demonstrate achievements, mechanisms do for identifying and correcting poor quality instruction, and an institutional commitment to continuous improvement. Quality assurance. Finally, for managing quality in a distance learning environment, a host of new factors comes into play as institutions attempt to establish an effective quality assurance system. These new factors provide a collection of issues that reflect practice and experience from higher education, fields other than education, and the research literature (Robinson, 1995). Some of the more common aspects, many of which you will find in this text, include: distance learning policies and planning; identification, specification, and satisfaction of standards (technical and discipline-specific); involvement of the learners and the key players (faculty, staff, and administrators) in the delivery of the distance learning program; staff involvement in the development of a distance-based quality assurance program; sound plan for training and staff development; and, a realization that costs (both human and financial) must be considered in light of the anticipated benefits of distance learning.

CRITICAL ISSUES IN DISTANCE LEARNING The issues included in Table 1 were identified by Bowling Green State University to be those most in need of investigation. This list is also supported by the Balancing Quality and Access Project of the Western Interstate Commission for Higher Education (2003), an acknowledged leader in distance learning efforts within higher education. In addition, Table 2 offers another look at grouping distance learning concerns suggested by this author. Both serve as excellent taxonomies for exploring crucial issues in teaching and learning at a distance and allow us to consider these factors by examining them as teaching-related, learning-related, technical, and administrative issues.

Critical Teaching Issues Research and the literature is replete with examples of how distance learning programs have failed as a result of obstacles associated with underestimating the degree of faculty training—both initial and ongoing—required to

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implement successful online programs. Too, faculty are often thrust into teaching online without even a cursory introduction to how technology might impact their own instructional strategies. Regardless of the redesign model chosen, the online format inevitably requires very different kinds of interactions with students when compared to the traditional teaching format. While administrators may overlook the effects of online and hybrid courses on student labs and computer classrooms, instructors quickly come to appreciate the importance of sufficient resources for students, some of whom remain unable to complete assignments because of personal hardware and software shortfalls. Copyright and course ownership issues are growing concerns as more and more faculty develop online courses and plagiarism creeps into our classroom. Finally, issues of faculty compensation, training and course loads, and promotion and tenure have surfaced along with increases in distance learning programs. Faculty have a responsibility to lead the distance learning programs at their institutions and they often do so as members of an academic or university-level advisory committee. These and other important teaching-related issues concerning distance learning delivery are discussed in the following paragraphs. Instructor design and training. Instructors require technical and administrative support; they must learn how to teach at a distance. They may have wrong assumptions concerning the investment of time and preparation required to teach online. One-on-one assistance required for computer-based delivery requires very different considerations from the traditional teaching format. One institution reported how their instructor training program evolved from an initial workshop, to regularly scheduled sessions each semester, to just-in-time training to better assist their distance education faculty (University of Alabama, 2002). In other studies, it was determined that, initially at least, many institutions overestimated the level of faculty preparedness (including graduate teaching assistants) and underestimated the amount of training needed. Many of the teaching assistants had no experience in an online environment and were not prepared to help the students when they asked questions or encountered problems. Although training was held prior to the start of the pilot term, the team discovered that there was a need for ongoing training and stronger continuing support than was initially planned (University of Tennessee, 2002). Instructional strategies. Many online instructors claim that they really grew to know their students—sometimes better than when they taught in person. Others stress that course content was not the issue; rather, students simply wanted to know that their instructor was a real person. Technologies, especially synchronous technologies such as virtual office hours, scheduled chat sessions, and two-way video strengthened the distance-challenged relationships. Other faculty expressed a need to see their students before they could establish a personal relationship necessary for teaching and learning to occur. The desire to teach and learn online using traditional delivery and study methodologies must be overcome by both faculty and students. Once this occurred, many embraced the new system as providing an equally-successful, if not better, learning experience (Drexel University, 2003). Granted, it takes practice and experience to establish an instructor-student relationship at a distance. But it can be done and done very effectively. Instructional resources. Distance educators already know that their students can be literally any where. Many are now only coming to realize that they, too, can be any where. Colleagues serving as online instructors have reported a sense of freedom knowing they can accept invitations to mid-semester conferences, attend to personal and professional crises, or even schedule some time off without negative impact on their teaching schedule. Using a capable learning management system, teaching a session, whether that session is in a hotel room in Cleveland or a faculty office in Pittsburgh, is of little consequence to the student. Institutions are forced to re-define what we mean by distance education in terms of both time and location. Too, distance educators often represent the cadre of faculty known as the “innovators.” Wise administrators encourage innovation by providing these informal leaders with the latest technologies, thus making it easier to implement a successful distance learning program. Copyright assistance and ownership. The debate over ownership of online courses is heating up throughout academia. Faculties at many institutions receive additional compensation for converting their once-traditional courses to a distance-based platform. If so, who, then, owns the rights to the course? Who should have first rights to teach it—given that the author of the course who taught it previously in the traditional format may be an ineffective online instructor? Also, online environments mean integration of digital content; in such circumstances,

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institutions often assist their faculty with the process of securing copyright releases. Their particular expertise with the laws and policies governing ownership of intellectual property are often invaluable. Faculty compensation, load, rewards, tenure/promotion. There are many issues here. For example, as faculty spend more time teaching at a distance, they can become disconnected from their department as well as their students. Efforts must be made to provide professional learning communities for faculty, especially those teaching the same or similar courses. The desire to go back to old ways of doing business must be overcome by both faculty and students. Once this occurs, many instructors embrace online teaching as an acceptable, if not better, learning experience—at least for some of their students (Drexel University, 2003). Also, investigations into the appropriate class size and course load formula have been presented and many have been found to be considerably different than traditional criteria for computing ideal class size and course load. As discussed earlier under Organizational and Social Implications of Distance Learning, one such study found that “the ideal traditional class size (based on factors of instructional content, counseling and advisement, and student assessment) was 17 students (graduate-level courses) while the ideal online class size was 12 students (Tomei, 2006).

Critical Learning Issues Making the change from traditional classroom instruction to new ways of learning involves far more than using a computer. Many students are already set in their ways after a lifetime, albeit brief, of passive instruction. They need preparation in making the transition to a more active learning style. Also, consideration as to how students, as well as the rest of the campus community, are to learn about the redesigned course will help avoid a number of problems that inevitably arise. Here are some of these concerns. Student support issues. Student surveys revealed that a major contributor to pre-course attitudes toward distance learning was the belief that the course would be less personal and lack opportunities for student-student and faculty-student interaction, even though they had never participated in a distance-learning course (University of Dayton, 2002). In addition, many institutions offering quality online programs pre-select their most promising students or, at the very least, pre-identify learners who deserve personalized attention during course delivery. Table 3 offers a few common traits characteristic of successful online learners. Ancillary support. Ancillary issues abound with respect to student-related support. Library and bookstore services, advising and counseling assistance, financial aid and scholarship help, registration and online payment options, tuition and fees (especially online and technology fees) considerations, parking, health services, access to recreation and (more traditional) campus activities, and other similar indicators often determine the long-term success of a distance learning program. How an institution supports online learners is a mark of excellence. Residency and accreditation. Sometimes, state, national, and professional associations pose barriers to distance learning. Most states have embraced online learning, counting credits as though they were taken in a traditional classroom. Still, students should not be expected to accept such stipulations with blind faith. They should take the initiative to confirm such policies during registration. Accreditation, however, is another matter. Since most professional associations accredit programs and not institutions, care must be taken when introducing online components to ensure that teaching at a distance is considered an acceptable format for instructional delivery. Student advisory committee. Most students encounter distance learning in some form or fashion well before they reach higher education. Many high schools are mandating an online experience as part of their graduation requirements. As a constituency of distance learning, students often represent a higher percentage of experienced online learning than even their faculty counterparts. As such, their participation on an academic committee focusing on distance learning makes excellent sense for any institution seeking to enhance its reputation as a tech-savvy institution.

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Critical Technical Issues As critical issues go, access to state-of-the-art technology may be the ultimate determiner of the success or failure of any online program. Most faculty and students alike will tell you that one bad experience entering a username or password, missing a synchronous chat because the software did not download, or losing a paper that was in the document-sharing directory yesterday but gone today will turn any learner sour on future distance learning experiences. Technical support. Technical support is a touchy issue; a blend of cost versus capability if ever there was one. From a student perspective, anything less than 24×7×365 (i.e., 24 hours a day, 7 days a week, every day of the year) access to a dedicated technician able to solve technical, content, and (sometimes) psychological problems, is not responsive. For administrators, such immediate responses are usually not fiscally prudent. Instructors, of course, are stuck in the middle. Teachers must serve as the first-line technical support providing their students with sufficient competencies to complete their assigned projects. Yet, they, too, depend on more technically astute resources to resolve deeper problems.

Table 3. Traits of successful online students: Is online learning for you? (World Wide Learn, 2007) THESE QUESTIONS MAY HELP YOU DECIDE IF ONLINE LEARNING IS FOR YOU: Are you self-directed and motivated? Most of online learning happens on your schedule. You’ll need to be self-directed and motivated to complete activities on schedule and initiate the communication required to be successful. You’ll be responsible for creating the structure to finish each course. Are your technical skills adequate? Along with having access to a computer and not being overwhelmed by typing, online learners should be comfortable with internet browsing and searching, e-mail, sending and reading attachments, word processing, and sometimes downloading and installing software plug-ins (a normally simple but sometimes intimidating task). Do you have strong reading skills? Reading can play a large part in any class, and especially online. The ability to read and comprehend subject matter without it being a chore is critical to your success. Does written communication come easily for you? In most cases writing is the primary method of communication in online classes, so you should be at ease with writing to express your thoughts, share ideas, and ask questions. Will you ask questions when you need to? If you typically don’t hesitate to seek help when you need it you’ll do fine. Since you’ll be in an online environment it’s important to let your instructor and classmates know when you need help. Remember that they won’t be able to see your looks of doubt, confusion, or other body language to tell when things aren’t going well. Will you miss the social interaction? Interaction with instructors and classmates in online learning is often an integral part of the learning experience. Absent is the in-person contact—being able to see facial expressions, hear reactions, and speak. Campus life may be different or nonexistent too. Do you have the discipline to study regularly? Like a traditional school you’ll need to set aside adequate time for study. You may discover that you need to be online frequently to complete assignments or communicate with classmates and instructors. You can plan to spend at least as much time working assignments and studying as you would with a traditional course, and you’ll be setting your own pace in many instances.

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Host vs. remote. Another technical (yet still cost-dependent) decision involves whether or not to host the learning management system on-site or pay to have the vendor provide such service. In the do-it-yourself column are such benefits as rapid response, customization of software and procedures, and unlimited applications. On the other side of the technical support ledger, a vendor-supported learning management system means less staff for the school, more professional (albeit expensive) state-of-the-art customization of software packages, and minimal impact on local resources (such as network bandwidth). And, since most reputable vendors boast uptime rates in excess of 98 percent, this decision is an easy one for many smaller institutions. Dedicated vs. shared staffing. Help desk support, programming, individualized training, etc., stir serious debate when considering online programs. Too, since most organizations maintain their own IT staffs, introducing a distance learning component begs the question whether to add these additional responsibilities to what is probably an already over-burdened IT shop or to create a parallel technical staff that deals solely with online initiatives. A dedicated versus shared technical group raises serious concerns that deserve prior consideration before launching into an online presence. Technician advisory committee. IT services often have their own advisory bodies; usually, they are participants on several campus-wide centers. So, a separate group specifically for distance learning is probably not in the cards. Technical staff, however, can be invaluable on any academic or university-wide technology committee. Select technicians who: can work with people; are familiar with learning management systems and networking; and, perhaps, even taught a course online. A contributing technical advisor can circumvent many user problems that turn off prospective online learners. The interface between the learning management system and student information system is at the top of the list; a well-designed interface transitions the student seamlessly from registration to enrollment to log-in. A well-trained technician can proactively monitor network resources and intervene when response times fall below established parameters, recognize saturation of hardware and plan for the necessary upgrades before they impact student performance, and provide all those tech-related tasks (i.e., archiving and backups, software and platform upgrades, access policies, etc.) that spell the difference between success and failure. Consider how technicians at your institution best serve your critical technology issues.

Critical Administrative Issues Administrators by definition are paid to worry about planning, management, organization, and resources. They are tasked with budgeting, staffing, and implementing. Successful distance learning programs require the best we have to offer in each of these areas. To be successful in this venue, administrators must consider a host of human, technical, organizational, and pragmatic resources. Human resources. Staffing a distance learning program calls for an entirely new suite of human and interpersonal skills, a description of which is still under construction. For most, the process of recruiting a successful online teacher is still an art. Finding an employee who can teach and administer—well, remains a mystery. Good teachers, more often than not, are not good administrators. Good technicians are not always good instructors. So, finding that right blend of person who both appreciates the pedagogical basis of teaching online and who can simultaneously manage a budget, hire staff, and keep students (as well as senior administration) happy is a rare find indeed. Technical resources. Much has already been said about technical resources. To reiterate, the importance of bringing together the proper combination of hardware, software, networking, and human support cannot be underestimated. Timing is critical since the results of every decision made hinges on cost. To further emphasize this point, Table 4 illustrates a cost-profit analysis of two commercially available learning management systems. Considering only the bottom line brings home the impact of cost on any decision to implement a distance learning program. Organizational resources. Marketing departments are affected by any decision to initiate a distance learning program. Financial services (student aid, payroll, and budgeting) are impacted by new online courses as well. Hu-

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man resources will be expected to implement policies never before considered. Even the president’s office must react to the impact that distance learning program impose on strategic planning, the organization’s mission and vision, and the goals of institutional advancement (i.e., fund-raising, capital campaigns, and alumni giving). So, it can be said that distance learning runs the gamut of any organization without question. Administrators, too, are needed on any institutional-level advisory committee; their input is invaluable. Programmatic resources. Quality is everyone’s responsibility, but within the administrator’s scope of authority. The competition must be considered; for example, everyone may be offering distance learning, but not everyone is offering the same quality programs. The evidence of this claim can be found in the growth in recent years of online “diploma mills.” Within another few years as investigations will be completed and reports written to prove this supposition. Programmatic niches will refine online course schedules, marketing decisions will dictate how programs can target these markets, and students and faculty feedback will ensure that institutions abandon any notions they might have entertained to dumb-down the curriculum in order to chase enrollment numbers. Recap. Contemporary Research on Distance Learning offers readers a selection of articles labeled as Critical Issues. Each offers a perspective of many factors experienced by K-12 teachers, college and university faculty, and corporate trainers. However, do not stop with these papers. The very format of the book and the articles presented is one that encourages authors to offer opinions in the form of findings, recommendations, and actions for further study. In each article, critical issues are the criteria by which contributions were accepted for publication. Each paper has something to offer the reader along with a deeper understanding of what maker for an effective distance learning program.

Other Critical Issues Two very important issues seem not to fall intuitively under any of the previous classifications, so they are discussed here.

Table 4. Learning management systems cost-profit analysis

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Table 5. Educational technology standards and performance indicators for all teachers (ISTE, 2002)

I. TECHNOLOGY OPERATIONS AND CONCEPTS. Teachers demonstrate a sound understanding of technology operations and concepts. Teachers: •

Demonstrate introductory knowledge, skills, and understanding of concepts related to technology

•

Demonstrate continual growth in technology knowledge and skills to stay abreast of current and emerging technologies

II. PLANNING AND DESIGNING LEARNING ENVIRONMENTS AND EXPERIENCES. Teachers plan and design effective learning environments and experiences supported by technology. Teachers: •

Design developmentally appropriate learning opportunities that apply technology-enhanced instructional strategies to support the diverse needs of learners

•

Apply current research on teaching and learning with technology when planning learning environments and experiences

•

Identify and locate technology resources and evaluate them for accuracy and suitability

•

Plan for the management of technology resources within the context of learning activities

•

Plan strategies to manage student learning in a technology-enhanced environment

III. TEACHING, LEARNING, AND THE CURRICULUM. Teachers implement curriculum plans that include methods and strategies for applying technology to maximize student learning. Teachers: •

Facilitate technology-enhanced experiences that address content standards and student technology standards

•

Use technology to support learner-centered strategies that address the diverse needs of students

•

Apply technology to develop students’ higher order skills and creativity

•

Manage student learning activities in a technology-enhanced environment

IV. ASSESSMENT AND EVALUATION. Teachers apply technology to facilitate a variety of effective assessment and evaluation strategies. Teachers: •

Apply technology in assessing student learning of subject matter using a variety of assessment techniques

•

Use technology resources to collect and analyze data, interpret results, and communicate findings to improve instructional practice and maximize student learning

•

Apply multiple methods of evaluation to determine students’ appropriate use of technology resources for learning, communication, and productivity

V. PRODUCTIVITY AND PROFESSIONAL PRACTICE. Teachers use technology to enhance their productivity and professional practice. Teachers: •

Use technology resources to engage in ongoing professional development and lifelong learning

•

Continually evaluate and reflect on professional practice to make informed decisions regarding the use of technology in support of student learning

•

Apply technology to increase productivity

•

Use technology to communicate and collaborate with peers, parents, and the larger community in order to nurture student learning

continued on following page

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Table 5. continued VI. SOCIAL, ETHICAL, LEGAL, AND HUMAN ISSUES. Teachers understand the social, ethical, legal, and human issues surrounding the use of technology in PK-12 schools and apply those principles in practice. Teachers: •

Model and teach legal and ethical practice related to technology use

•

Apply technology resources to enable and empower learners with diverse backgrounds, characteristics, and abilities

•

Identify and use technology resources that affirm diversity

•

Facilitate equitable access to technology resources for all students

•

Promote safe and healthy use of technology resources

Skills and competencies. A minimum set of skills and competencies for prospective distance learners seems a reasonable expectation before taking an online course. After all, prerequisites have been around for a long time and, while some students may complain, most understand and accept the fact that they are best served by completing Algebra I before tackling calculus; it should be no different in the distance learning arena. The research offers countless examples of generic technology competencies targeting students, teachers, and administrators. The International Society for Technology in Education (ISTE) goes even further by categorizing skills at various levels of professional teacher development (see Table 5). For example, pre-service teachers (i.e., those still in their undergraduate program) are expected to complete their degree with a limited, albeit rapidly expanding, inventory of personal technology attributes. More experienced teachers are expected to increase their technology tools along with their other instructional strategies. And, an entirely different skill set has been established for students and administrators. However, it should not be too surprising that this list of technological competencies may be a poor indicator of success as a distance learner. It is encouraging to know that many of the articles in this text add to the ISTE skill set new competencies unique to learning online. For example, mastering technology-based communications tools is a basic proficiency for every educator; email is as much an imperative in today’s classroom environment as chalk and blackboards were in years past. For the distance educator, more advanced tools must be mastered including discussion groups, chat rooms, webinars and podcasting. Table 5 offers a recap of technology competencies many of which specifically address distance learning skills. Professional associations. A host of organizations have infused the words “distance” and “online” into their titles. Table 6 illustrates a sampling of the most widely recognized international associations. In addition, many educational and technology-focused organizations have their own branches of distance learning to support its membership interested in online learning. An example of the former is the Open and Distance Learning Association, an international organization with chapters in dozens of countries. The Association for the Advancement of Computing in Education overlaps the categories of education and technology and publishes some of the best (in the author’s opinion) journal articles written on the subject of training at a distance. The surest sign of a quality professional organization is its journal. Without going into great detail here, it would be wise to consider organizations whose publications are listed in the annals of reputable publishing directories such as the Cabell’s Directory of Publishing Opportunities. Look for journals that claim international membership on their editorial review boards, require at least a double-blind review, and are willing to divulge their manuscript acceptance rates. Further, since we are touting distance learning here, the common caution to avoid Web-based-

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only publications falls by the wayside. The United States Distance Learning Association, for example, hosts its popular journal online only. A reputable professional association gives its membership more than a quarterly periodical. Conferences, especially international conferences, are a sure-fire mark of a solid organization. Here again, because the discipline we are discussing is distance learning, perhaps a conference readily augmented by technology (e.g., video conferencing) is not an unreasonable expectation. One good trip to a far-flung venue and a faculty’s annual budget for professional development is quickly depleted. A worthy association captures its proceedings and makes them available to its membership as audio, CDROM, or video media. In addition to conferences, member-sponsored user groups are a highly attractive draw for any professional organization. The most popular learning management system vendors sponsor local or regional user groups, some with memberships that rival the size of other autonomous associations. Training and professional development workshops are well received and a reputable association provides its members with steep discounts and timely topics. The final factor to consider when selecting a professional organization is reputation. Most institutions of higher education limit memberships to organizations only after some formal endorsement by their faculty. Others require the prospective association’s journal to be recognized by the faculty as an “A” list publication before dues are paid. Regardless, professional associations and user groups have indeed emerged as a critical issue in the pursuit of excellence in distance learning. Summary. At the outset of this section of the chapter, two taxonomies were pressed into service as a way to consider the discipline of distance learning. The first classification offered a look at administrators, faculty, and financial parameters as discovered by Bowling Green State University. The second, proposed by this author, classified issues according to teaching, learning, technical, administrative, and other issues. Regardless of which list you prefer, the ideas that follow in this text suggest to the reader a view of distance learning that will serve as a ready reference for the articles presented herein. As you proceed through the sections of the book, keep track of the issues identified by our authors and create your own taxonomies for distance learning.

EMERGING TRENDS IN DISTANCE LEARNING No debate on distance learning is complete without at least a cursory examination of where the discipline might be headed. Distance learning’s rich history, beginning with its correspondence, mail-order platform, has most assuredly provided the foundations necessary for a promising future as we move further into the 21st century. Teaching trends in general and faculty issues specifically are changing daily. Teaching online has become its own “gogy”—with its own unique strengths and weaknesses, advantages and limitations—in much the same light as the art of teaching children (pedagogy) and the art of teaching adults (andragogy) has contributed to our understanding of learning at these levels. Faculty have come to accept the notion that teaching online is its own venue for learning with its own skill set, competencies, and measures of success only now coming under the scrutiny of practitioners and scholars. What the future may hold with respect to teaching at a distance is anyone’s guess. The articles contained in this text under the heading, Educational Trends in Distance Learning, offer considerable opportunities to upland your personal research base on this unique blend of teaching and learning. Search the Web for “online degree programs” and you will find over 39 million links to undergraduate and graduate programs as well as another 2 million doctoral programs. And, these programs are being offered by some of the nation’s (and world’s) most prestigious institutions. Besides formal academic programs, many institutions envision a future including distance-based career certifications, lifelong learning credits, as well as professional credentialing all targeting the non-traditional learner. In truth, there are few sources and even fewer researchers who are not predicting a healthy future for the rapidly expanding inventory of academically strong distance learning programs. Technology trends are up for grabs. Who would have predicted the impact of technology on teaching in 1978 when Apple introduced the first real personal computer? By 1985, computers were commonplace in K-12 schools. Again, a revolution in academic technology was experienced with the advent of the Internet and its separation from the military into its own environment in the 1990s. By 1996, with the announcement of the Pentium pro-

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cessor and multimedia applications, the World Wide Web exploded onto the scene and again changed the face of education. Now, in the new millennium, distance learning seems to be breaking down barriers at unprecedented levels. Many of the papers presented suggest how future trends in the technological base may ultimately impact the future of distance learning. Together, trends in student enrollment, faculty development, academic curriculum, and technology and distance learning advancements suggest a number of emerging tendencies. What follows is a brief description of some of these most important trends.

Student/Enrollment Trends Distance learning program enrollments. Can the current higher education infrastructure accommodate a growing college-aged population or are more distance education programs necessary? The largest high school class in U.S. history is scheduled to graduate in 2009 (Callahan, 2003). In another survey conducted by the U.S. Department of Education, the National Center for Education Statistics predicts that

Table 6. International distance learning and online education associations Professional Association

Web Address

University Continuing Education Association

www.ucea.edu

American Distance Education Consortium 

www.adec.edu

United States Distance Learning Association

www.usdla.org

Association for Ed Communications and Technology 

www.aect.org

International Council for Open and Distance Education

www.col.org

World Association for Online Education (WAOE)

waoe.org

International Association for Distance Learning Texas Distance Learning Association  Maryland Distance Learning Association  Oklahoma Distance Learning Association  Arizona Distance Learning Association  Florida Distance Learning Association  Ethiopian Distance Learning Association

www.iadl.org.uk www.txdla.org www.marylanddla.org www.odla.org www.azdla.org www.fdla.com unicorn.ncat.edu/ ~michael/edla/

Canadian Association for Distance Education (CADE)

www.cade-aced.ca

The Open and Distance Learning Association of Australia

www.odlaa.org

National Association of DE Organisations of South Africa

www.nadeosa.org.za

European Distance Learning and E-Learning Network

www.eden-online.org

European Association of Distance Teaching Universities

www.eadtu.nl

South African Institute for Distance Education

www.saide.org.za

African Distance Learning Association

www.physics.ncat.edu/ ~michael/adla

World Association for Online Education

waoe.org

Association for the Advancement of Computing in Education

aace.org

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college enrollment will grow 16% over the next 10 years (Jones, 2003). With this growth in college-age population and enrollments and the need for more lifelong learning for adults, many institutions acknowledge that within the decade there will be more students than their facilities can accommodate. Online learning is a convenient solution to over-subscribed classrooms. Scalable distance learning models provide the answer to capacity constraints that growing enrollments increasingly place on the current higher education infrastructure. Enrollment shopping. More and more learners are browsing an institution’s online registration system looking not for courses that best fit their academic programs, but for courses that better meet their schedules and circumstances. Why not increase online course inventories and give them both? Today’s busy students require more flexibility in scheduling to accommodate expanding demands from responsibilities such as full-time jobs and families. With these pressures, students are forced to consider courses that accommodate their schedules as well as their learning styles. Organizations such as the Online Consortium of Independent Colleges and Universities (OCICU) are tapping the market by collaborating with schools who offer niche online programs to those without available instructional resources to serve their student populations. “Provider” institutions are opening their online schedules to “member” schools and are doing so in increasingly greater numbers (OCICU, 2007). Students enroll at their host school and their registration is filtered through the OCICU to the institution providing the course. Credits earned at the provider school are quickly transferred at the end of the semester to the institution where the student will earn their degree. Member schools win because they receive tuition monies (minus the US$600 fee charged to both administer the program and deliver the course) that might otherwise go to local competition. OCICU wins to the tune of US$120 per enrollment as they match student to available courses. And, the provider institutions win by filling virtual seats that would otherwise remain empty. Expect to hear more about this truly innovative collaboration in the near future—it’s one of the best examples of a win-win partnership in the current, albeit short, history of distance learning. Profiling the higher education learner. Traditional, adult, and online learners: are the distinctions becoming clearer or blurred? The modern, traditional-age college students are most certainly unlike past generations—just ask any classroom faculty. As we noted early, traditional students are just as likely (some would say even more so) to seek out learning opportunities available from home or tightly wrapped around work, family, and social obligations. For them, multitasking is a way of life, staying connected is considered a right, and there is no tolerance for slow or interrupted access. Adult learners are different from their traditional classroom counterparts. As with all adult learners, they bring to the table real- world experiences; as a result, they tend to be practical problem solvers. These life experiences make them autonomous, self-directed, and goal-oriented users. They need to know the rationale for what they are learning. They are motivated by professional advancement, external expectations, the need to better serve others, social relationships, escape or stimulation, or pure interest in the content of a particular course. Their demands involve time and scheduling, money, and long-term commitment constraints. Many adults are insecure about their abilities with respect to technology. To succeed as a distance learner, they must: (a) receive constant feedback and reassurance; (b) be exposed to instruction that considers their different learning style; and, (c) be exposed to programs that offer sufficient support services. Online students are becoming their own sub-population of higher-education learners. One report notes that distance learners are “generally older, have completed more college credit hours and more degree programs, and have a higher all-college GPA than their traditional counterparts” (Diaz, 2002). The findings go on to report that online students received twice as many A’s as traditional students and half as many D’s and F’s. In sum, as distance learning emerges as its own instructional modality, our prior definitions and presumptions about traditional, adult, online, and lifelong learners must change as well. Consider articles that compare and contrast distance learning targeting these different categories of learners. Adult, female, and minority learners. Adult learners are the fastest-growing population in higher education. While the number of 18-24-year-old students increased only 41% between 1970 and 2000, the number of adult students nearly doubled (Aslanian, 2001; “Lifelong,” 2002). Factors that seem to have influenced this phenomenon

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include the rapid expansion of continuing education programs, a recognition of a new source of profits to be realized from this sector of the educational consumer market, economic necessity to respond to decreasing enrollments in the traditional sector, the rapidly changing job market, changes in the job market that embrace lifelong learning to remain competitive, and the simple aging of student populations. Likewise, the percentage of women and minority learners is increasing. More women (57%) than men now enroll in college, a trend supported by the fact that more women are working outside the home and staying in the job market much longer than before. Among minorities, the proportion of women is even higher with “60 percent of Hispanic women and two-thirds of African-American women as college students” (Cetron, 2003). If enrollments follow population projections, higher education must react with further online programs to serve an even larger share of the adult market. Retention rates. Studies comparing online course retention rates with their traditional counterparts remain inconclusive. Past attempts at assessing technology-driven initiatives in education have nearly always fallen short, even well past the introductory phase of implementation. Research proving that learning has occurred has always been difficult to quantify or qualify statistically; distance learning and online education is no exception. Still, as an emerging trend, the future bodes well. Already, schools and their respective professional organizations are reporting that online programs have as high or higher rates of retention when compared to traditional classroom offerings” (Roach, 2002). Other investigations have demonstrated that distance education attrition is high; some say too high. However, a 2003 benchmark survey at four-year institutions confirmed that 66 percent of their distance learning courses exceed an 8 out of 10 completion rate. It appears that other, more traditionally recognized demands of school, work, and family still take their toll on enrollments.

Faculty Trends Traditional faculty roles. The research has not yet determined the suitability of traditional faculty serving as online instructors. For some, it would seem that online students are better served by more technically competent deliverers. The role of faculty members in distance education requires specialized skills and a broader knowledge of instructional strategies. Distance educators must plan ahead, evidence significant organizational skills, and communicate with their students in a variety of ways. Distance faculty members must possess expert communication skills themselves because of the increased demand for student interaction in an online environment. In an article published in 2006 by the Society of Information Technology and Teacher Education, it was reported that faculty in a traditional classroom spent 30% of their time delivering instructional content, 26% counseling and advising students, and 44% of their time in student assessment. Online instructors, however, had different percentages; specifically, content delivery required 38 percent of their time, counseling another 26%, and assessment the other 36% (Tomei, 2006). Clearly, the role of faculties shifts as they take on distance learning as a new format for instruction. Need for faculty development, support, and training. Understandably, as the amount and quality of online delivery increases, so does the demand for support. Some faculty approach teaching online with a naïve strategy of using their conventional classroom methods in an online forum. Often, they encounter frustration and disappointment when they note a decrease in learning either by poor student performance on tests or by less than sterling course evaluations at the end of the term. Chief academic and information technology officials have rated “helping faculty integrate technology into their instruction” as the single most important IT issue that will confront their campuses over the next two or three years (Green, 2002) while, at the same time, other research has determined that faculty development and support remain outside the top ten uses of an IT shop’s time or resources (Crawford et al., 2003). Faculty and student status. The role of technology as it impacts issues of promotion and tenure are in a state of flux. Administrators are responsible for recruiting distance learning instructors; however, access to technology-ready faculty and contracts adopted before the rise of online teaching negatively affect distance education

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programs. In many institutions, contributions to distance education are considered second-class in terms of moving faculty members toward promotion and tenure and publishing online is hardly appreciated when it comes time to compile one’s vita. As a result, many faculty choose not to participate in distance education efforts and the quality of a school’s online program suffers. It is not uncommon to hear stories from candidates describing the coolness of a hiring committee when the discussion of their resume was readily identifiable as online. While the online reputation of certain schools in the past might be construed as a “less than demanding,” distance learning has certainly become more competitive recently with respect to certain job opportunities. Across the board, the reputation of distance learning remains an emerging issue that is addressed by several articles in this text. Resistance to delivering courses online. Somewhat akin to the previous discussion is the issue that, as long as distance education contributions are not considered as viable fodder in tenure and promotion decisions, many faculty members remain reluctant to develop and deliver online courses. This hesitation takes the form of outright antagonism to department chairs seeking to match a name to a scheduled course section. Too, faculty may place barriers to the growth of online curriculum in union contracts or advisory committee policies and standards. Others complain of the labor-intensive and time-consuming demands required to design and develop online modules as reasons for faculty resistance. Faculty attitudes toward distance education and technology. Despite some resistance, the results of several recent studies show a strong increase in overall faculty support for technology in education. The State University of West Georgia (2003) published its findings of faculty motivation and distance learning. Their study discovered the top seven motivators for faculty who have taught at a distance. They included (in order of importance): • • • • • • •

Ability to reach new audiences that cannot attend class on campus Desire to “keep up” Encouragement from dept. head or dean Personal motivation to use technology Flexible working conditions Intellectual challenge Pressure from administration

For those faculty investigated who had not previously taught online, a few additional factors were uncovered attributing to motivation. They included: monetary support for participation (stipend, overload), opportunity to receive training, course development support, personal motivation to use technology, and credit towards promotion/tenure. On the downside of the issue, faculty who had experience teaching online found the following factors inhibiting or discouraging future application of distance learning: • • • • • • •

Decreased student interaction Lack of time to develop course Preference for traditional setting Concern that students needs on-campus socialization experience Reduced course quality Time away from research and publishing Increased class size

Additionally, a preference for the traditional classroom, appreciation for the on-campus socialization experience, impact on research and scholarship, lack of release time and time to teach courses online, and office equipment were cited as reasons to avoid teaching online. With these, and other, investigations supporting the conclusion that faculty attitudes are evolving, there are reasons to consider many of the articles in this text as guides for moving the faculty even further along the con-

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tinuum toward acceptance of distance learning as a viable teaching venue. Institutions who address the inhibiting factors identified in these studies will find greater successes in launching and maintaining online curriculum. Administrators should seek new ways to introduce faculty to the benefits of the distance format and increase their familiarity with distance education. Perhaps the articles in the Contemporary Research in Distance Learning will provide clues as to how this can be successfully implemented in higher education. Faculty compensation. Faculty are demanding reduced workload and inc r e a s e d c o m p e n s a t i o n f o r d i s t a n c e c o u r s e s . C o m p e n s a t i o n , a s a n e m e rg i n g i s s u e , has surfaced big time, causing institutions to scramble for a solution (ADEC Guiding Principles for Distance Learning, 2002). A chief concern for faculty is how they will be compensated for designing, developing, as well as teaching online courses. Some colleges and universities have unadvisedly supplanted arts and sciences, education, and core curriculum with online courses as their “cash cows” of the institution. While current research suggests that online enrollments should be lower than traditional classrooms (Tomei, 2006), many administrators continue to work under the assumption that teaching 35 students online must be easier than teaching 20 students in a classroom. The National Education Association (2000) found that most faculty members spend more time on their distance courses than they do on traditional courses. Some 84% of online teachers do not receive a reduced workload and 63% receive no extra compensation for their distance courses.

Academic Trends Knowledge and information are growing exponentially. In his book, The Age of Spiritual Machines, Ray Kurzweil (1999) describes how many innovations in the history of the world evolved initially at an arithmetic rate. Even human evolution, according to the author, began slowly and then entered stages of growth at geometric proportions. So too, has been the rate of knowledge and information development. The growth in information will certainly continue to dramatically impact higher education and learning in general. These rapid increases in knowledge have the potential of increasing the available content of higher education courses and serve as catalysts for advancing distance education even further. After all, the articles presented in this text are the best examples of how contemporary thinking and learning are expanding as a direct result of technology. Find those articles that offer some insight into the future of distance learning and how this newest instructional strategy will impact teaching and learning as we continue into the 21st century. The traditional campus vs. distance education. With the recent growth of for-profit institutions, attention has been raised on traditional campuses to remain responsive to the demands for alternative modes of instructional delivery—for several reasons. First, many traditional institutions find themselves “land-locked” with respect to facilities, classrooms, and educational resources. Comparing the indirect costs with delivering content in a classroom and then contrasting both with online instruction and it becomes clear that doing business the traditional way has its vulnerabilities. Projections call for significant changes in higher education over the next 20 years. The number of degree-granting institutions (and their student populations) are predicted to grow at a geometric rate (again, another confirmation of Kurzweil’s theory of evolutionary expansion) while the number of students attending classes on traditional campuses will decline (Dunn, 2000). If traditional institutions intend to remain viable, they cannot ignore the promises (both financially and academically) that online learners bring to the table. The private sector will continue to focus on those areas where profits are most easily made, such as business programs and information technology curriculum, leaving traditional areas to public higher education. By integrating distance learning in areas where traditional campuses have met with past success, they can continue to capture the segment of the market that they typically target anyway. To ignore distance learning as an instructional modality will only encourage these students to seek the flexibility and modality they desire elsewhere – to the further detriment of traditional campuses. Academic accountability. Accreditation and program approvals are fast becoming standard fare at most universities. Certainly, accreditation is one very overt way to validate the veracity of an educational program. More

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and more, professional accreditation is based on observable learning outcomes with a considerable measure of investigation to back up the claims that learning has occurred. Distance educators must accommodate this growing emphasis on accountability if they are to maintain accreditation and meet student demands. In the United States for example, the federal government has stepped in to define the issue at the same time distance learning programs are receiving increased attention from university presidents, administrators, and faculty. The 1998 Reauthorization of the Higher Education Act, appropriately re-titled the Distance Learning and the Higher Education Act, stated as its purpose, “to broaden opportunities for distance learners by expanding eligibility for student aid and encouraging innovative uses of technology by institutions and other education providers, while ensuring the integrity of these courses and programs” (U.S. Dept. of Ed., 2002). According to a 1995 study by the National Center for Education Statistics, 33% of all higher education institutions offered courses using the distance education format to more than 700,000 students. No wonder the discipline is placing renewed interest on testing programs to document learning outcomes. Hopefully, discussions of accountability will be visible throughout the articles offered in this text. Seamless educational opportunities. The number of high school, post-secondary, and lifelong students served by the distance learning modality is on the rise. Several high schools now require an online experience prior to graduation and nearly all post-secondary learners are exposed to an online format sometime during their academic tenure. Further, many institutions are now partnering with nearby colleges and universities to provide high school juniors and seniors with a college-level experience. Some call the experience college-to-high school, dual enrollment, articulation agreements, or advanced placement; most provide such experiences via a distance learning venue. Standardizing reusable learning assets/objects. As a partner in a virtual cyber school, my experiences with learning objectives have convinced me that this technology-based tool holds great promise not only for distance learning but for education in general. Certainly, the concept of learning objects and, specifically, online technologies demands some attention here. The development of learning assets/objects (also known as reusable learning assets/objects) represents a significant evolution in the design, development, and implementation of instruction. Typically, course content is designed around a didactic (i.e., lecture) model. A typical one-hour block of instruction requires 35-55 minutes of instruction. These learning “chunks” (taken from the behavioral concept of chunking information to promote successful learning) form the core of traditional classroom teaching. Learning assets and objects, however, are developed differently. They are usually smaller, self-contained elements focusing on a single concept within the much larger learning module. Consider for a moment the number of articles in this text that mention learning management systems (LMS) and you have some idea of the scope of learning objects as an instructional design strategy. Every LMS is based on the schemata of individualized lessons. The software employed actually makes it possible to reuse objects by tagging them in a systemic way, storing them in a database, and retrieving and combining them with other objects to create new customized learning experiences. In programming, this concept of creating routines is well known; only now is the idea being considered in education.

Distance Learning Trends Ubiquitous nature of technology. Surely, no discussion of emerging issues would be complete without an examination of the most apparent trend affecting distance education: the future of technology. Computers continue to double in speed every 3-5 years while their costs decrease even faster. High-speed network connections continue to expand to provide more bandwidth to more locations including home, office, school, and once-leisure locations thanks to wireless. Included in this expanding technology base are computers, fax machines, cell phones, duplication, e-texts, interactive television, and other personal and education devices. Not only is technology becoming more ubiquitous, it is being used more competently by more people from all nationalities, age groups, and socioeconomic levels with a 59% increase just in the number of children accessing the Internet since 2000 (Murray, 2003). No one can afford to be a computer illiterate.

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Lifelong learning is a competitive necessity. In recent years, it has become even more apparent that lifelong education opportunities are fundamental to one’s competitive edge in a global economy. Distance learning guarantees that school is always in session and everyone has an equal opportunity to participate. It is estimated that 60% of tomorrow’s jobs will require skills that only 20% of today’s workers possess. It is also estimated that the average person leaving college today will change careers 14 times. Without a lifetime of education, training and retraining opportunities, many of the challenges of the 21st century may go unrealized. As new technologies emerge and workers continue to change careers, they will need to learn new skills and apply current skills in new ways. Distance learning provides one solution to attaining new knowledge wherever and whenever the situation demands. Availability of distance education programs. The demand for distance-accessible programs is increasing among currently employed, as well as, aspiring professionals. In 2002, the annual market for distance learning courses was $4.5 billion; by 2005, it had grown to $11 billion. By 2010, the expectations exceed $25 billion. Others have asserted that up one-half of traditional campus programs will be made available, in some form or another (i.e., repository, hybrid, or totally) in an online format.

CONCLUSION Chapter I began with a look at the fundamental concepts and theories of distance learning and introduced the educational psychologies of distance learning and several taxonomies for teaching and learning. A review of design and development methodologies brought into sharper focus several models for designing instruction along with developmental issues associated with learning, learning, resources, delivery formats, and learning outcomes. Distance learning tools and techniques suggested that the readers of this text consider how each of the contributors herein introduced new technologies into their examination of online teaching and learning. Utilization and application of distance learning established the three levels of an online course presence: repository courses that use the shells of a learning management system to hold instructional materials chiefly for a traditional class; hybrid courses that contain up to 50% online learning; and, online courses that employ a total distance environment. Next, the chapter moved from concepts and theory to application with its discussion of the organizational and social implications of distance learning. Closely related was the follow-on consideration of the managerial consequences of distance learning that affect administration, record-keeping, accountability, monitoring and evaluation, institutional goals and mission, and quality assurance. Critical issues in distance learning involved an examination of administrative, and faculty financial matters as well as teaching, learning, and technical concerns. Some of the critical teaching issues examined were instructional strategies and resources, copyright and ownership debates, and faculty remuneration arguments. In the learning issues portion of this chapter a series of questions were posed to help a prospective online learner decide if the distance format was a viable option for learning. Finally, emerging trends inaugurated a host of student, enrollment, higher education, diversity, and retention issues associated with students. From a faculty perspective, the chapter looked at faculty roles, resistance to change, and attitudes about technology in general and distance education specifically. Academic and distance learning trends were also discussed. Chapter I was designed to set the stage for an examination of contemporary research in distance learning. As you proceed through this six-volume register, keep in mind the concepts and theories presented in this first chapter. Good luck on your exploration into this unique brand of teaching and learning

REFERENCES American Distance Education Consortium, DEC Guiding Principles for Distance Learning. Retrieved May 2007 from http://www.adec.edu/admin/papers/distance-learning_principles.html Aslanian, C B. (2001). Adult students today. The College Board: New York.

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California Distance Learning Project Web site. Developed and maintained by the Sacramento County Office of Education, 2005. Retrieved March 2007 from www.cdlponline.org/index.cfm?fuseaction=whatis&pg=6 Callahan, P. M. (2003, March 28-30). UCEA 88th Annual Conference. Chicago. Cetron, M. J., & Daview, O. (2003). 50 trends shaping the future. Special Report Published by the World Future Society. Crawford, G., Rudy, J. A., & the EDUCAUSE Current Issues Committee. (2003, November). Fourth Annual EDUCAUSE survey identifies current IT issues (pp. 12-26). Diaz, D. P. (2002, May/June). Online drop rates revisited. The Technology Source. Retrieved February 2007 from ts.mivu.org/default.asp?show=article&id=981 Distance Learning Task Force Progress Report, Bowling Green State University, dated February 21, 2001. Retrieved March 2007 from ideal.bgsu.edu/deab01.pdf Dunn, S. (2000, March/April). The virtualizing of education. The Futurist, 34(2), 34-38. Faculty Attitudes Toward Distance Education at the State University of West Georgia. Retrieved March 2007 from www.westga.edu/~distance/attitudes.html Grasha, A. F. (1996). Teaching with style. Pittsburgh, PA: Alliance. Green, K. C. (2000). Campus Computing 2002: The 13th national survey of computing and information technology in American higher education. Encino, CA: Campus Computing. International Society for Technology Education (ISTE). Educational Technology Standards and Performance Indicators for All Teachers, 2002. Retrieved March 2007 from cnets.iste.org/teachers/pdf/Appendix_G.pdf Jones, D.R. (2007, January). A recommendation for managing the predicted growth in college enrollment at a time of adverse economic conditions. Online Journal of Distance Learning Administration, 1(6). Retrieved January 2007 from www.westga.edu~distance/ojdla/spring61/jones61.htm Kibler, R.J., Barker, L.L., & Miles, D.T. (1970). Behavioral objectives and instruction. Allyn & Bacon Publishers. Knowles, Malcolm S. (1980). Modern practice of adult education: From pedagogy to andragogy. Chicago: Association Press. Krathwohl, D.L., Bloom, B.S., & Masia, B.B. (1964). Taxonomy of educational objectives. The classifications of educational goals. Handbook II. Krathwohl, D.L., & Bloom, B. S. (1984). Taxonomy of educational objectives. The classifications of educational goals. Handbook I. New York: Addison-Wesley Company/Pearson Publishers. Kurzweil, R. (1999). The age of spiritual machines. New York: Penguin Putnam Publishing. Lifelong learning trends: A profile of continuing higher education (7th ed.). (2002). University Continuing Education Association. MERLOT - Multimedia Educational Resources for Learning and Online Teaching. Retrieved March 2007 from http://www.merlot.org/merlot/viewMaterial.htm?id=242351 Murray, C. (2003). Study reveals shifts in digital divide for students. eSchool News, 36-37. National Education Association (NEA). (2000, June). A survey of traditional and distance learning higher education members. Retrieved March 2007 from www.nea.org/he/abouthe/dlstudy.pdf

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Oblinger, D., & Kidwell, J. (2000). Distance learning: Are we being realistic? Educause, 31-39. Online Consortium of Independent Colleges & Universities (OCICU). Retrieved March 2007 from ocicu.org Priest, S. (2002). Technology think tanks in experiential learning. Unpublished manuscript. Program in Course Redesign, Bowling Green State University. Course Title: The Curriculum (2006). Retrieved March 2007 from www.thencat.org/States/OLN/BGSU_Abstract.htm Program in Course Redesign, Drexel University. Course Title: Computer Programming (October 2003). Retrieved March 2007 from www.thencat.org/PCR/R3/DU/DU_Overview.htm Program in Course Redesign, The University of Alabama. Course Title: Intermediate Algebra (December 2002). Retrieved March 2007 from www.thencat.org/PCR/R2/UA/UA_Overview.htm Program in Course Redesign, University of Tennessee, Knoxville. Course Title: Intermediate Spanish Transition (December 2002). Retrieved March 2007 from www.thencat.org/PCR/R2/UTK/UTK_Overview.htm Roach, R. (2002). Staying connected: Getting retention right is high priority for online degree programs. Black Issues in Higher Education. Robinson, B. (1995, February 20-22). The management of quality in open and distance learning. In Indira Gandhi National Open University, Structure and Management of Open Learning Systems. Proceedings of the Eighth Annual Conference of the Asian Association of Open Universities, New Delhi (Vol. 1, pp. 95-109). Smith, P. L., & Ragan, T. J. (1993). Instructional design. New York: Merrill. State University of West Georgia, Distance Education Center. (2003). Online Journal of Distance Learning Administration, 6(3). Strickland, A.W. ADDIE. Idaho State University College of Education Science, Math & Technology Education. (2006). Retrieved June 2006 from ed.isu.edu/addie/index.html Sullivan E., & Rocco, T. (1996). Guiding principles for distance learning in a learning society. Washington, DC: American Council on Education. Tomei, L. A. (2005). Taxonomy for the technology domain: A classification of educational objectives for the technology domain. Hershey, PA: Idea Group Inc. Tomei, L. A. (2006). Impact of online teaching on faculty load: Computing the ideal class size for online courses. Journal of Technology and Teacher Education, 14(3), 531-542. Tomei, L. A. (2007). Theoretical model for designing online education in support of lifelong learning. In Y. Inoue (Ed.), Online education for lifelong learning (forthcoming). Hershey, PA: IGI Global. U.S. Department of Education, Office of Postsecondary Education. Archives of Information on Priorities of Previous Administration. Washington, DC, 2002. Retrieved March 2007 from www.ed.gov/offices/OPE/PPI/Reauthor/distance.html U.S. Department of Education, Western Interstate Commission For Higher Education: Balancing Quality and Access. Reducing State Policy Barriers to Electronically Delivered Higher Education Programs. Retrieved March 2007 from www.ed.gov/about/offices/list/ope/fipse/lessons4/wiche.html Wiggins, G., & McTighe, J. (1998). Understanding by design. VA: Association for Supervision and Curriculum Development. Wiggins, G., & McTighe, J. (2001). Understanding by design. Prentice Hall. World Wide Learn. Traits of Successful Online Students: Is Online Learning For You? Retrieved March 2007 from www.worldwidelearn.com/about-worldwidelearn

Section 1

Fundamental Concepts and Theories in Online and Distance Learning This section serves as a foundation for this exhaustive reference tool by addressing crucial theories essential to the understanding of online and distance learning. Chapters within this segment provide an excellent framework in which to position distance learning within the field of information science and technology. With 60 chapters comprising this foundational base of knowledge, the reader can learn and chose from a compendium of expert research on the elemental theories underscoring the online and distance learning discipline.



Chapter 1.1

Principles to Guide the Integration and Implementation of Educational Technology Sara Dexter University of Virginia, USA

INTRODUCTION The Educational Technology Integration and Implementation Principles (eTIPs) are six statements that describe the K-12 classroom and school-level conditions under which the use of technology will be most effective. The eTIPs are an example of materials that can aid teachers in designing instruction and participating in creating supportive conditions for technology supported classroom instruction.

BACKGROUND During the last decade, the call for teachers to be better prepared to teach with technology (CEO Forum, 1999, 2000; Office of Technology Assessment, 1995) has been repeated several times. In response, there are now standards in place to which new teachers are being held that explicitly

describe the technology skills all teachers should have to be prepared to teach in a 21st century school. These include the National Education Technology Standards for Teachers (ISTE, 2000), which were adopted by National Council for Accreditation of Teacher Education (NCATE) as a part of its accreditation requirements, and the Interstate New Teacher Assessment and Support Consortium standards (INTASC, 1992) used by many states as licensing requirements. In general, these standards call for teachers to be able to use technology in the classroom to plan and design learning environments and experiences, and support teaching, learning, and the curriculum. These standards, in turn, imply that teachers must make the consideration of technology use a routine part of their instructional decision making. Teachers’ decision making has been defined as the course of action during which teachers gather, organize, and interpret information, generate alternatives, select a specific course of

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Principles to Guide the Integration and Implementation of Educational Technology

action, and, after its implementation, consequently evaluate the effectiveness of the decision (Clark & Yinger, 1977; Lipham, 1974). The research literature emphasizes how critical teachers’ planning and interactive decisions are in determining what they do, or do not do, in the classroom (e.g., Clark & Yinger, 1977; Jackson, 1968; Peterson & Clark, 1978; Shavelson, 1976). Shavelson and Stern (1981) posit that teachers’ decision-making processes are influenced by schemata that are activated from memory.

MAIN THRUST OF CHAPTER The Educational Technology Integration and Implementation Principles (or eTIPs) are one example of a set of statements that could serve as a schema, or the basis of a schema, for a teacher to organize his or her instructional decision making about the integration and implementation of technology. Principles can assist learners in recognizing and connecting ideas and in seeing how new and old ideas relate (Marzano, 2001), which are key tasks in developing the more elaborate schemas that are characteristic of expert teachers (Carter, 1990; Fogarty, Wang, & Creek, 1983; Kagan, 1992). The six eTIPs summarize what research suggests are the conditions that should be present in order for educational technology integration and implementation to be effective (Dexter, 2002), while offering the advantage of brevity over the 23 NETS-T standards and the five technology-specific statements in the INSTASC standards. These eTIPs are organized into two dimensions: classroom and school-wide. The classroom principles expand upon the premise that effective technology integration requires the time and attention of teachers in the role of instructional designers, planning the use of the technology so it will support student learning. They assume that educational technology does not possess inherent



instructional value but that a teacher must design into the instruction any value technology adds to the teaching and learning processes. Thus, the three classroom eTIPS prompt a teacher-designer to consider what he or she is teaching, what added value the technology might bring to the learning environment, and how technology can help to assess student learning.

Classroom-Level eTIPs eTIP 1: Learning Outcomes Drive the Selection of Technology In order for learning outcomes to drive the selection of technology, teachers must first be clear about their lesson or unit’s student-learning outcomes. This is an important first step in determining whether or not the educational technology available can be a support to teaching and learning. It will allow teachers to be more efficient as they search for available, appropriate technologies because they will quickly eliminate those that do not support their learning outcomes. Where technology does seem to support learning outcomes, teachers must also consider the cognitive demands made by the technology and if they are well-suited to the cognitive demands inherent in the learning outcomes. For example, if a learning outcome asks students to analyze or synthesize information, a drill and practice program or reference material on a CD-ROM probably isn’t going to match as well as concept mapping or database software.

eTIP 2: Technology Use Provides Added Value to Teaching and Learning Using technology to add value—meaning to make possible something that otherwise would be impossible or less viable to do—might mean that it helps to individualize instruction or make

Principles to Guide the Integration and Implementation of Educational Technology

it more responsive to a student’s questions and interests or that it provides additional resources of information so instruction is more real-world, authentic, and current. Educational technology can also aid teachers in providing “scaffolds” that support learners as they move from what they already know and can do to what they are learning. Educational technology can also help teachers to create social arrangements that support collaborative as well as independent learning by facilitating communication and interaction patterns. Teachers can also use educational technology to support additional opportunities for learners to practice, get feedback, or allow for revision or reflection; thus, it supports knowledge acquisition and practice, so learners become more fluent in their knowledge. Educational technology can aid students accessing information or representing it in new ways. It can increase access to people, perspectives, or resources and to more current information. Many times, software’s interface design allows learner interaction or presents information in a multisensory format. Hyperlinks can allow learners to easily connect to related information. Built-in indexes and key word searching support learners by easing their search through a large amount of information to find what is relevant. These features all add value by increasing access to data or the users’ control during that access. In terms of processing information, added value might mean that the educational technology supports students learning-by-doing or aids them in constructing mental models, or making meaning, by scaffolding their thinking. For example, a database can allow students to compare, contrast, and categorize information through query features. By asking students to create products with tool software, it requires them to think more deeply about the material in order to represent it with that tool (Jonassen, 2000). Educational technology can also add value to students’ ability to show and articulate to others about what they have learned.

eTIP 3: Technology Assists in the Assessment of the Learning Outcomes At times, teachers will want to collect and return to students formative data, to let them know about their learning progress. Some software or hardware actually collects formative data during its use, and some technologies also provide help in the analysis of the information. Generally, these are software programs designed to assess student learning, such as tutorial or drill and practice software. Some of these programs, through screens or printouts of information, or other feedback mechanisms, support students’ self-assessment of their learning. Teachers will also want to collect summative information about students’ achievement of the learning outcomes. Technology can assist teachers in collecting data that will help them understand how students are meeting or have met the learning outcomes for that lesson or unit. Products students produce through software, whether a database, “mind map,” multimedia or word-processed report, or a Web site, demonstrate what they have learned about both the content of their product, the procedural knowledge required to produce it, and their ability to communicate. The capabilities a product might demonstrate include the skills of editing, analysis, group collaboration, or the operation of the software itself.

School-Level eTIPs Part of what makes teachers’ integration activities feasible or not is the level of technology support at a school. The three school-wide principles elaborate upon the premise that the school environment must support teachers in a role of instructional designer by providing adequate technology support. The presence of high-quality technology support programs are correlated to teachers’ increased uses of educational technology (Dexter,



Principles to Guide the Integration and Implementation of Educational Technology

Anderson & Ronnkvist, 2002). Thinking about the school-level principles while deciding whether or how to integrate technology can help a teacher to take the “technology ecology” of the setting into perspective during instructional design. Together they will help teachers to evaluate the level of access and support available to them in their integration work, which may help to determine whether or not, given their amount of planning time, a particular integration goal is realistic.

eTIP 4: Ready Access to Supported, Managed Hardware/Software Resources is Provided Teachers must have convenient and flexible access to and technical support for appropriate educational technology in order for them to utilize it in their classrooms. Perhaps of all the principles, this one is the most self-evident. Without available and working educational technology, it can hardly be utilized in a classroom. But, the two key words in this principle are ready and supported. Ready access means the technology should be close to where teachers need to use it and that it is scheduled flexibly, so that teachers have an opportunity to sign up for it when it is relevant for classroom work. Here, support specifically refers to technical support like troubleshooting help and scheduled maintenance. The idea of ready access should raise for the teacher questions about whether or not the students could be grouped together to work with the educational technology, if it could be a station through which students rotated, or if all students need to have simultaneous access to the educational technology. Ultimately, the access has to be practical. It must be ready enough that working through the logistics of providing students access to the technology does not outweigh the added value it provides.



eTIP 5: Professional Development is Targeted at Successful Technology Integration Technology professional development is key to teachers learning to integrate technology effectively into the classroom (CEO Forum, 1999). The learning needs can be thought of as being about (1) learning to operate the software and, (2) learning to use software as an integrated, instructional tool. Too often teachers’ learning opportunities are just about the operation of the software. This is necessary, but teachers must also have learning opportunities that address more than these basic skills. Specifically, these learning opportunities should guide teachers in the instructional design I have laid out in the three classroom educational technology integration principles. By having sufficient time to explore educational technology and have their technological imagination sparked by examples of it in use, teachers can identify which materials match their learning outcomes (eTIP #1). Professional development sessions should also provide frameworks or criteria that can aid a teacher in determining whether or not an educational technology resource brings any added value to teaching or learning (eTIP #2). Likewise, through examples and discussion, teachers should have opportunity to consider how educational technology might aid the formative or summative assessment of students’ learning (eTIP #3).

eTIP 6: Professional Community Enhances Technology Integration and Implementation This principle describes a professional collaborative environment for integrating and implementing technology. In such an environment, technology use would be more effective because the school organization would recognize the contribution individuals make to the collective knowledge of the school (Marks & Louis, 1999). And the entire

Principles to Guide the Integration and Implementation of Educational Technology

staff would work toward consensus about the school’s performance, in this case with technology, and how they could improve it (Marks & Louis, 1997). A collaborative professional community would serve as the vehicle for school-wide knowledge processing about technology integration and implementation, increasing the likelihood of reflective dialogue, sharing of instructional practices, and generally increasing collaboration on new practices.

Integration and Implementation Principles (eTIPs) can help teachers recognize and plan for the effective technology use that is represented in the NETS-T and INTASC standards. The eTIPs point out two key aspects of teachers designing effective integrated instruction: the technology use must match and support teaching and learning, and the larger school environment must provide support for the logistical and learning demands technology integration puts on teachers.

FUTURE TRENDS

REFERENCES

As educational technology and Internet access become ubiquitous in classrooms and new teachers headed into the classroom arrive from college already skilled in the operation of technology, it is likely that educational technologists will then be able to shift their research efforts to how best to develop teachers’ instructional decision making about technology integration and implementation. This suggests that further research is needed about the schema of expert technology integrating teachers, and the key cognitive processes involved in designing and implementing effective technology integrated instruction. Future development efforts are needed in the area of developing instructional supports, such as cases and simulationsthat will aid novice integrators in developing the necessary knowledge and skills.

Carter, K. (1990). Teachers’ knowledge and learning to teach. In W. R. Houston (Ed.), Handbook of research on teacher education (pp. 291-310). New York: Macmillan.

CONCLUSION The research literature about teachers’ instructional planning suggests that teacher educators working to develop K-12 educators’ abilities to incorporate educational technology into the classroom should attend to the development of teachers’ schema about technology integration and its implementation. By serving as a schema, or the basis of one, the Educational Technology

CEO Forum on Education and Technology (1999). Professional development: A link to better learning. Retrieved February 16, 2003, from: http:// www.ceoforum.org/reports.cfm?RID=2 CEO Forum on Education and Technology. (2000). Teacher preparation STaR chart: A self-assessment tool for colleges of education. Retrieved February 16, 2003, from: http://www.ceoforum. org/reports.cfm?RID=3 Clark, C. M. & Yinger, R. J. (1977). Research on teacher thinking. Curriculum Inquiry, 7(4), 279- 304. Dexter, S. (2002). eTIPS-educational technology integration and implementation principles. In P. Rodgers (ed.), Designing instruction for technology-enhanced learning (pp.56-70). Hershey, PA: Idea Group Publishing. Dexter, S., Anderson, R. E., & Ronnkvist, A. (2002). Quality technology support: What is it? Who has it? and What difference does it make? Journal of Educational Computing Research, 26 (3), 287-307.



Principles to Guide the Integration and Implementation of Educational Technology

Fogarty, J. L., Wang, M. C., & Creek, R. (1983). A descriptive study of experienced and novice teachers’ interactive instructional thoughts and actions. Journal of Educational Research, 77(1), 22-32. International Society for Technology in Education [ISTE]. (2000). National educational technology standards for teachers. Eugene, OR: International Society for Technology in Education. Interstate New Teacher Assessment and Support Consortium [INTASC]. (1992). Model standards for beginning teacher licensing and development: A resource for state dialogue. Retrieved September 27, 2004 from http://www.ccsso. org/content/pdfs/corestrd.pdf Jackson, P. W. (1968). The way teaching is. Washington, DC: National Education Association. Jonassen, D.H. (2000). Computers as mindtools for schools: Engaging critical thinking (2nd ed.). Columbus, OH: Prentice-Hall. Kagan, D. M. (1992). Professional growth among pre-service and beginning teachers. Review of Educational Research, 62(2), 129-169. Lipham, J. M. (1974). Making effective decisions. In J. A. Culbertson, C. Henson, & G. MorineDeshimer (1978-1979). Planning and classroom reality: An in-depth look. Educational Research Quarterly, 3(4), 83-99. Marks, H, M., & Louis, K.S. (1999). Teacher empowerment and the capacity for organizational learning. Educational Administration Quarterly, 5, 707-750. Marks, H. M., & Louis, K.S. (1997). Does teacher empowerment affect the classroom? The implications of teacher empowerment for instructional practice and student academic performance. Educational Evaluation & Policy Analysis, 3, 245-275.



Marzano, R. J. (2001). Designing a new taxonomy of educational objectives. Thousand Oaks, CA: Corwin Press, Inc. Office of Technology Assessment. (1995, April). Teachers and technology: Making the connection, OTA-EHR-616. Washington, DC: U.S. Government Printing Office. Peterson, P. L., & Clark, C. M. (1978). Teachers’ reports of their cognitive processes during teaching. American Educational Research Journal, 15(4), 555-565. Shavelson, R. J. (1976). Teachers’ decision making. In N. L. Gage (Ed.), Yearbook of the National Society for the Study of Education: The psychology of teaching methods. Chicago: University of Chicago Press. Shavelson, R. J., & Stern, P. (1981). Research on teachers’ pedagogical thoughts, judgments, decisions, and behavior. Review of Educational Research, 51, 455-498. KEY TERMS Added Value: Traditional usage is as an indication that the particular packaging, delivery method, or combination of services in a product brings extra benefits than one would otherwise receive. Applied to educational technology, it communicates that the use of technology brings added value to the teaching or learning processes when it makes possible something that otherwise would be impossible or less viable to do. Principle: Ideas that can assist learners in recognizing and connecting ideas and in seeing how new and old ideas relate. Professional Community: Collaborative activities among a school’s faculty members that focus on meaningful, shared issues in a school and also emphasize how each individual staff member can take responsibility for its achievement.

Principles to Guide the Integration and Implementation of Educational Technology

Professional Development: The National Staff Development Council defines this as the term that educators use to describe the continuing education of teachers, administrators, and other school employees. Schema: Mental constructs that aid learners in categorizing problems or situations and selecting appropriate courses of action for their effective resolution.

Technology Implementation: The putting into place at a system level of a school the conditions that support the integration of technology at the classroom level. Technology Integration: The use of technology in teaching to support learning.

This work was previously published in the Encyclopedia of Information Science and Technology, Vol. 4, edited by Mehdi Khosrow-Pour, pp. 2303-2307, copyright 2005 by Idea Group Reference (an imprint of IGI Global).





Chapter 1.2

Technology’s Role in Distance Education Murray Turoff New Jersey Institute of Technology, USA Caroline Howard Touro University International, USA Richard Discenza University of Colorado at Colorado Springs, USA

Introduction

BACKGROUND

Learning is enhanced by the physical and social technologies typically used in distance education. Students in distance programs typically have access to tools that allow them to repeat lectures and interact with their fellow students and faculty. Students in all classes, including face-to-face and blended courses, benefit from having similar tools and technologies available. This article will review common tools and technologies used in distance education, and demonstrate why they can facilitate learning and expand the educational opportunities for both distant and traditional students.

For many years technologies have been used to facilitate learning. In the early 1980s a group of researchers at the New Jersey Institute of Technology (NJIT) realized the enormous potential of the technology to enhance learning when they used a computer-mediated system to facilitate a regular face-to-face class. The system was introduced to students in a number of computer science and information system courses. Due to the amount of material covered in lectures, there was not much time for dialogue, and only a few students participated when there was a class discussion.

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Technology’s Role in Distance Education

The instructors introduced asynchronous group communication technologies to communicate discussion questions and assigned grade point credits for student participation. One hundred percent of the students participated in these discussions outside of regular classroom hours. The extent and depth of the discussions changed the nature of the classes. Most importantly, student contributions were comprehensive, with more well-thought-out comments, because students had the time to reflect on the ongoing discussion before participating. Also very significant was that students, for whom English was a second language, became equal participants. They could reread the online discussion as many times as needed before replying. The computer-based activity monitoring and transcripts, electronic recordings of the discussions, showed that foreign students spent two to three times more time in a reading mode and reread many discussions, far more than the American students. In addition, professors now have the ability to monitor activities and review the electronic transcripts of student involvement which gives the instructor insights into how students are learning. By reviewing the transcripts of the online discussions, it becomes obvious what and how students are learning. For courses with a high pragmatic content, such as upper-level and graduate courses in topics like the design and management of computer applications, students are required to utilize problem-solving approaches to evaluate the tradeoffs between conflicting objectives. In a traditional classroom environment, especially in large classes, it is very difficult to detect whether students are accurately incorporating the problem-solving mental models that the instructor is attempting to convey. When instructors review the transcripts of class discussions, they give insights into the approaches students are taking to master the material. Unfortunately, in the early 1980s few wanted to hear about a revolution in normal classroom teaching or were willing to expend the effort to dramatically improve classroom

education. It was only the rise of distance education that generated interest in learning about the educational potential of the technology. Hiltz (1994) performed quasi-experimental studies that compared a population of NJIT students (only familiar with face-to-face classroom education) to a population of students taking the same courses in pure face-to-face sections, with pure distance sections using only CMC technology. The students in the matched sections had the same material, the same assignments, the same exams, and the same instructor. They found no significant difference in the amount of learning or the rate of student satisfaction. This finding is much more significant than a determination based on a study that included a population of distance learners already familiar with traditional correspondence classes. Two critical underlying variables driving the success of this approach were identified by Hiltz (1994). First, the role the instructor needed to take was different from the traditional classroom role. The instructor acted more as an active and dedicated facilitator, as well as a consulting expert on the content of the course, rather than traditional teacher. Second, collaborative learning and student teamwork were the educational methodology (Hiltz, 1994) shown in later studies to be a key factor in making distance courses as good as or better than face-to-face courses (Hiltz & Wellman, 1997). These results show that distance courses can be as effective as face-to-face courses when using any of the traditional measures, such as exams and grades. Creative, interactive software programs accompanied by background tutoring can effectively teach students to master the skills currently taught in many undergraduate courses. When these courses are automated, the costs incurred are far below typical college tuition. In the future, colleges and universities will not be able to continue to charge current tuition costs for introductory courses that are largely skill oriented. For example, there are many stand-alone and Web-based soft-



Technology’s Role in Distance Education

ware programs that offer introductory programming courses, as well as skills in many other areas. These courses are comparable to college courses and some are even based upon a textbook used on some college campuses. They are available for a few hundred dollars. The major difference is that they do not carry college credits. The technology allows senior professors or department chairs to effectively evaluate and mentor all instructors of particular courses, whether they are teaching traditional classroom courses or distance courses. The ability to review whole class discussions after the class is over gives senior faculty the ability to evaluate distance instructors hired to teach previously developed courses, as well as to review on-site instructors and junior faculty. Thus, they can improve and extend their mentorship and apprenticing relationships. Today’s technology for distance education allows faculty members to live anywhere they want to. Unique benefits will be available to outstanding teaching faculty. For example, one of the best full-time instructors for NJIT, which is located in beautiful downtown Newark, is a mother with two small children who never has to be on campus. She is teaching other instructors how to teach remotely. Similarly, a University of Colorado accounting professor, on sabbatical in Thailand, is able to teach a course in the Distance MBA program. There have been a few master’s programs where some or all of the instructors are located anywhere in the world. It is technically feasible for those wanting to escape winter cold to teach in places such as Hawaii that we could only dream about. The technology makes it feasible, but various administrative policies, unions, insurance companies, benefit programs, and so forth have not yet caught up to the technology. There is increasing emphasis by accrediting agencies on treating remote instructors the same as faculty are treated. This is likely to bring about a greater degree of equality between instructors and tenured track faculty. The outcome is uncertain, but it may

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mean that the costs for remote and traditional classes will equalize so that the profit margin in online classes will not be quite so high.

Specific functions of technology that facilitate learning Asynchronous Discussions In the online environment, students can take as much time as they need to reflect on a discussion and polish their comments. This improves the quality of the discussion, and changes the psychology and the sociology of communications. Students can address topics in the sequence they choose rather than in a predefined order. This leads to the development of different problem-solving strategies among the individual members of the class. Sometimes courses include synchronous conferences, videoconferencing, and/or video presentations to supplement asynchronous discussions.

Instructor Control of Online Conference and Roles With online course conferences (many per course), instructors control the membership of each, assign roles, and enable other instructors to monitor conferences for joint teaching exercises involving more than one course. Groups within courses are able to set up private online conferences for team and collaborative work group assignments. Joint editing of items facilitates teamwork.

Question-and-Answer Communication Protocol Instructors are able to ask questions during discussions. They can control who views the answer and prevent other students from seeing the

Technology’s Role in Distance Education

answer of the others or engaging in the resulting discussion until they have entered their answer. In studies of group decision support systems, it has been shown that asynchronous groups in an online Delphi mode generate many more ideas than unstructured discussions or face-to-face groups of similar size (Cho, Turoff, & Hiltz, 2003). This area has proven to be a valuable tool in forcing equal participation. Use of question-and answer communication protocol can be used to force each student to think independently through their answer without being influenced by the other students.

Anonymity and Pen Name Signatures When students with work experience are part of a discussion, they can use their real-life experiences to illustrate the concepts the professor is presenting. Such comments from fellow students, rather than the professor, often make the instructor’s message more meaningful to the students. A student confirming the theory presented by a faculty member through real-life examples is more effective in making a point than “dry” data from an instructional article. Furthermore, students can talk about disasters in their companies with respect to decisions in any area, and they can provide detail—including costs—when they are not identified and the anonymity of the company they work for is preserved. Also, the use of pen names allows individuals to develop alternative personas without divulging their real identity and is extremely useful in courses that wish to employ role playing as a collaborative learning method.

Membership Status Lists The monitoring of activities, such as students’ reading and responding to communications, allows the professor to know what each individual has read and how up-to-date they are in the dis-

cussion. This allows the instructor to detect when a student is falling behind. Student collaborative teams can make sure that everyone in the team is up to date. Furthermore, students can easily compare their frequency of contributions relative to other students in the course.

Voting Instant access to group and individual opinions on resolutions and issues are enabled by voting capabilities. This is useful for promoting discussion, and the voting process is continuous so that changes of views can be tracked by everyone. Voting is not used to make decisions. Rather, its function is to explore and discover what are the current agreements and disagreements or uncertainties (polarized vs. flat voting distributions) so that the class can focus the continuing discussion on the latter. Students may change their votes at any time during the discussion.

Special Purpose Scaling Methods These useful methods show true group agreements and minimize ambiguity. Currently we have a system that allows each student at the end of the course to contribute a statement of what they think is the most important thing they have learned in the course; then, everyone votes by rank ordering all the items on the list. The results are reported using Thurstone’s scaling, which translates the rank order by all the individuals to a single group interval scale. In this interval scale, if 50% prefer A to B and 50% prefer B to A, the two items will be at the same point on the scale. It has been surprising what some of the results have been in some courses. For example, in a Management of Information Systems course, the concept of “runaway” software projects was felt to be twice as important as any other topic. The professor was quite surprised by this result, until he began to realize that the students were using this concept

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Technology’s Role in Distance Education

as a mental model in which to integrate many of the other things they had learned.

Information Overload This occurs when enthusiastic discussions by students that are meant to augment the quality of the learning process augment only the quantity of the number of comments, instead leading to the problem of “information overload.” Currently this phenomenon limits the size of the group in a single CMC class. Online discussions allow individuals to enter comments whenever it is convenient for them, without waiting for someone else to finish the point they were trying to make. This makes it physically possible and also very likely that a great deal more discussion will take place and much more information will be exchanged among the group than if only one person can speak at a time, as in the face-to-face classroom environment. Anything that reduces the temptation of some students to “contribute” comments or messages that have nothing to do with the meaningful discussions underway will increase the productivity of the discussion without information overload setting in. Among such functional tools the computer can provide are:

Class Gradebooks This eliminates a tremendous amount of electronic mail traffic that would become very difficult for an individual instructor to manage with a large class.

Selection Lists The instructor can set up lists of unique choices so that each student may choose only one item and others can see who has chosen what. This is very efficient for conveying individualized assignments and reduces a large portion of communications.

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Factor Lists Members of a class or group can add ideas, dimensions, goals, tasks, factors, criteria, and other items to a single, shared list which may then be discussed and modified based upon that discussion and later voted upon.

Notifications Short alerts notify individuals when things occur that they need to know about. For instance, students can be notified that a new set of grades or vote distribution has been posted, eliminating the need for individuals to check for these postings. People can attach notifications to conference comments from a select list that provides alternatives like: I agree, I disagree, I applaud, Boo! Such appendages significantly reduce the need to provide paralinguistic cues of reinforcement as additional separate comments.

Calendars, Agendas, or Schedules Students have access to a space to track the individual and collaborative assignments and their due dates. These are listed in an organized manner that links detailed explanations for each assignment, as well as questions and answers related to the assignments. The authors have seen these technologies facilitate learning beyond what can be assessed using traditional measures. Some of the more subtle intangible benefits of technology that we have observed are: •

Due to social pressures, students tend to be more concerned with how other students view their work quality than how the professor views it. They are significantly more motivated to participate in a meaningful way when their fellow students can view their contributions.

Technology’s Role in Distance Education

•

• •

•

When equality of communications is encouraged, students cannot get away with being passive or lazy. The transcript or electronic recording of the discussions shows who is and is not participating. It is visible to both the instructor and other students that someone is being lazy. (In fact, students seem to be more concerned with what the other students will think of their performance than what the professor will think.) The scope of what the outstanding students learn becomes even more noticeable. The performance of students at the lower end of the distribution is improved. The communications systems permit them to catch up, because they are able to obtain a better understanding of the material with which they are most uncomfortable or have the least background knowledge. The instructor can become more aware of his/her successes or failures with individual students because of the reflective nature of the student contributions to the discussion.

While these dimensions and concepts need confirmation through long-term longitudinal studies of student performances, the marketplace is also providing confirmation of the beliefs held by many experienced in teaching these classes. We are seeing that collaboratively oriented programs offer a solution to the problems, which are inherent in traditional correspondence courses. Students benefit from the ability to electronically store lectures alone or in chunks integrated into other material on the Web. Electronic storage of lectures gives all students the power to choose freely whether they want to attend a face-to-face class or take the same course remotely. Traditional faceto-face students can later hear a lecture missed due to illness or travel. Students with English as a second language can listen to a lecture multiple times. Face-to-face students who have to travel or

fall sick can use the same tapes to catch up and/or review material prior to exams. In our view a student in a face-to-face class that is not augmented by a collaborative learning approach and by asynchronous group communications technology is not getting as good of an education as the distance student who has those benefits. It is the face-to-face student who may be suffering from the segregation of the college system into separate face-to-face and distance courses. These observations about the past and the present lead to some speculations about the future.

The State of the Technology The technology available today includes at least 250 versions of group communication software. However, many of them may not survive the decade. There are a growing number of software packages for course management. The online learning product landscape is changing at a rapid pace as companies are acquiring their competitors to expand functionality. Gray (2002) gives an excellent summary of the popular platforms and the evolving nature of e-learning. There are only a few of these that have wide usage, and they are beginning to raise their prices to capitalize on their popularity. Most of these packages charge a fee per user, which is not the desirable fee structure for the customer. Many of the older conference systems charge on a per-server basis and it does not matter how many students one has. It is far cheaper to spend more on the hardware and a get a more powerful server. Also, the course management systems do not provide many of the useful software features one would like to have for group communications. Given the way prices are going, it might be better to pay some of the undergraduate students to educate some of the faculty on how to create their own Web sites and have their own pages for their

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Technology’s Role in Distance Education

courses that they update and maintain directly. This also has desirable long-term consequences in raising the ability of the faculty in this area. Once you have committed all your content to one vendor’s system, you are a captured customer and will have to pay whatever they want to charge. Right now, software development is undergoing rapid evolution, and no customer should put themselves in the box of only being able to use one vendor. If it is clear that you are using a number of vendors, you may even be able to get some breaks on pricing and will certainly get the top level of service when each of them knows there is an alternative service readily available to the customer. In the coming decade, one can expect major upgrades for these software systems every few years, and the best one today may not be the best one tomorrow.

Course Development and Delivery Unfortunately, many faculty do not know how to use the technology to design a successful distance course. As the historical record shows, it is a mistake when transferring an application to computers to just copy the way it used to be done onto the computer. Utilizing the methodology of collaborative learning is the key to designing courses using group communications technology. Simple systems, which attempt to impose a discussion thread on top of what is electronic mail technology, allow the student or the teacher only to view one comment at a time. This approach does not allow an individual to grasp the totality of any complex discussion. Only by placing the complete discussion thread in a single scrolling page can a person review and understand a long discussion. One can browse the discussion and cognitively comprehend it without having to perform extra operations and lose their cognitive focus. Users of such simple systems cannot generate a large

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complex discussion and have no way of realizing that complex discussion is even possible. When online discussions are successful, they can easily go from enthusiastic wonderful discussions to information overload. Current technology must evolve to fully support collaborative learning.

FUTURE TRENDS To facilitate collaborative learning, critical development directions for the future should include: • • • • • • • •

Tailorability of communication structures by instructor Tailorability of communication protocols by instructor Anonymity and pen name provisions Delphi method tools and the availability of scaling and social judgment (voting methods) Tools for collaborative model building Powerful information retrieval capabilities Tailorability by instructor of applicationoriented icons and graphical components Tools for the analysis of alternative diagrams

Instructors also need to allow students to extend the discourse structure and to vote on the significance of incidents of relationships among factors in the problem domain by using group decision support processes. These systems should allow students not only to develop their own conceptual maps for understanding a problem, but also to detect disagreements about elements of the conceptual map and the meanings of terms. This is valuable preparation for problem solving in their professional life, a process that requires removing inherent ambiguities and individual meanings in the language used to communicate about a problem with others from diverse backgrounds.

Technology’s Role in Distance Education

Routines should be included that are based upon both scaling and social judgment theories, which improve the ability of larger groups to quickly reach mutual understanding. Currently, few tools exist in current systems that support the use of collaborative model building, gaming, and Delphi exercises. The current generation of software does not often include the functions of anonymity and pen names. Course instructors need to have complete control over course communication structures and processes, and should be able to use their recently acquired knowledge for future offerings of the course. Currently, systems lack the needed integration of functions to easily evolve the changes in both the relationships and the content in a given field. A long-term advantage of teaching in the collaborative electronic environment is that the students create useful material for future offerings and can aid the instructor in monitoring the new professional literature. Future technology will allow faculty to organize their material across a whole set of courses into a collaborative knowledge base available to the faculty teaching those courses. This would allow students and faculty to create trails for different objectives and weave the material in that knowledge base to suit a group of students or a set of learning objectives. Individual learning teams would be able to progress through a degree program’s knowledge base at the rate best for them, rather than setting the same timeframe for all learning teams or faculty teams. Faculty, individuals, or teams would take responsibility for a specific domain within the Web of knowledge representing a degree program.

CONCLUSION Collaborative technologies are changing the concept of what constitutes a course. Program material could be an integrated knowledge Web, based largely on semantic hypertext structures. Over

time, the domain experts—the faculty—would continue to develop and evolve their parts of the Web, and wait for learning groups, composed of any mix of distance and regular students sharing the same learning objectives and needs. Current vendor systems focus on the mass market and concentrate on tools to standardize and present course content. Group communication tools are usually just disguised message servers that offer only a discussion thread capability and little more, certainly not the complex capabilities discussed above. Vendors have not yet recognized the primary importance of group communications and how faculty members can guide and facilitate the process and be available for consultation as needed. Based upon the conceptual knowledge maps they design, faculty should be encouraged to develop content structures that are characteristic of their subject matter. In the end, faculty should have the ability to insert group communication activities anywhere in their professional knowledge base (e.g., question/answers, discussion threads, lists, voting, etc.).

NOTE A great deal of recent evaluation studies are beginning to confirm ourearlier findings based upon extensive and large-scale studies at such placesas SUNY, Drexel, Penn State, and others. Some of these may be found inthe Journal of ALN (www. aln.org) and on the ALN EvaluationCommunity Web site (www.alnresearch.org)

REFERENCES Cho, H. K., Turoff, M., & Hiltz, S. R. (2003, January). The impacts of Delphi communication structure on small and medium sized asynchronous groups. In HICSS Proceedings, Hawaii. Piscataway, NJ: IEEE Press.

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Discenza, R., Howard, C., & Schenk, K. (Eds.). (2002). The design and management of effective distance learning programs. Hershey, PA: Idea Group Publishing.

McIntyre, S., & Howard, C. (1994, November). Beyond lecture-test: Expanding focus of control in the classroom. Journal of Education for Management Information Systems.

Gray, S. (2003). Moving—e-learning vendors take aim in the changing environment. Syllabus, 16(1), 28-31.

Nelson, T. H. (1965). A file structure for the complex, the changing and the indeterminate. ACM 20th National Conference Proceedings (pp. 84-99).

Harasim, L., Hiltz, R., Teles, L., & Turoff, M. (1995). Learning networks: A field guide to teaching and learning online. Boston: MIT Press. Hiltz, S. R. (1993). Correlates of learning in a virtual classroom. International Journal of ManMachine Studies, 39, 71-98. Hiltz, S. R. (1994). The virtual classroom: Learning without limits via computer networks. Human Computer Interaction Series. London: Intellect Press. Hiltz, S. R., & Turoff, M. (1993). The network nation: Human communication via computer. Boston: MIT Press (original edition 1978). Hiltz, S. R., & Turoff, M. (2002, April). What makes learning networks effective? Communications of the ACM, 56-59. Hiltz, S. R., & Wellman, B. (1997). Asynchronous learning networks as a virtual classroom. Communications of the ACM, 40(9), 44-49. Howard, C., & Discenza, R. (1996, October). A typology for distance learning: Moving from a batch to an on-line educational delivery system. In Proceedings of the Information Systems Educational Conference (ISECON), St. Louis, MO. Howard, C., & Discenza, R. (2001). The emergence of distance learning in higher education: A revised group decision support system typology with empirical results. In L. Lau (Ed.), Distance education: Emerging trends and issues. Hershey, PA: Idea Group Publishing.

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Turoff, M. (1995, April). A marketplace approach to the information highway. Boardwatch Magazine. Turoff, M. (1996). Costs for the development of a virtual university. Journal of Asynchronous Learning Networks, 1(1). Turoff, M. (1997). Virtuality. Communications of the ACM, 40(9), 38-43. Turoff, M. (1998). Alternative futures for distance learning: The force and the dark side. Online Journal of Distance Learning Administration, 1(1). Turoff, M. (1999). Education, commerce, & communications: The era of competition. WebNet Journal: Internet Technologies, Applications & Issues, 1(1), 22-31. Turoff, M. & Hiltz, R.S. (1986). Remote learning: Technologies and opportunities. In Proceedings of the World Conference on Continuing Engineering Education. Turoff, M. & Hiltz, R.S. (1995). Software design and the future of the virtual classroom. Journal of Information Technology for Teacher Education, 4(2), 197-215. Turoff, M & Discenza, R. (forthcoming). Distance learning: Really a better education? In C. Howard, K. Schenk, & R. Discenza (Eds.), Distance learning and university effectiveness: Changing educational paradigms for online learning. Hershey, PA: Information Science Publishing.

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Turoff, M., Hiltz, R., Bieber, M., Rana, A. & Fjermestad, J. (1999). Collaborative discourse structures in computer mediated group communications. Reprinted in Journal of Computer Mediated Communications on Persistent Conversation, 4(4).

KEY TERMS Asynchronous Group Communication Technologies: Allow participants to send and respond to messages without being online simultaneously. Distance Education: Consists of learning situations in which the students and instructor are located in different localities at least for a portion of the class. Distributed Learning: Consists of learning situations in which the students and instructor

are located in different localities. A bit broader than distance education as it can be used to refer to both education and training. E-Learning: Using technology to assist in the educational process. It is often used to refer to learning situations (both education and training) in which the students and instructor are located in different localities . However, the instructor and teacher can be in close proximity. E-Learning Technologies: The technologies used for e-learning. Pen Name Signatures: Names participants choose for online participation which may or may not allow other participants to identify them. Synchronous Group Communication Technologies: Allow real-time, interactive communications and require participants to be online simultaneously.

This work was previously published in the Encyclopedia of Information Science and Technology, Vol. 5, edited by Mehdi Khosrow-Pour, pp. 2777-2783, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 1.3

The Pillars of Instructional Technology Lawrence A. Tomei Robert Morris University, USA

Abstract

Introduction

This chapter provides an overview of the foundational components of teaching and learning with technology. The pillars of instructional technology include the philosophy of technology (What are we teaching about IT?), the psychology of technology (How are we teaching with IT?), the sociology of technology (Who are we teaching with IT?), the history of technology, and technology leadership. Each “pillar” offers a venue for creating a program of instructional technology at the higher education level. In addition, a new model for implementing an instructional technology program is introduced: the K-A-RPE model of instructional technology provides the infrastructure for any institution of higher learning to infuse technology into its undergraduate, graduate, and post-graduate teacher curriculum.

Philosophy, psychology, sociology, history, and leadership are the pillars of teaching and learning—whether in the classroom or by way of distance-based tools. As such, instructional technology is supported by the following five foundations: 1. Philosophy, that answers the question “What are we teaching about instructional technology?” 2. Psychology, that addresses “How do we teach with instructional technology?” 3. Sociology, involving the “Who are we teaching with instructional technology?” 4. History, encompassing the “When (in the history of education) are we teaching with technology?” 5. And, Leadership, focusing on “Whom (sic) is responsible for using technology to teach?”

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The Pillars of Instructional Technology

Figure 1. Philosophy Psychology Sociology History Leadership

The Philosophy of Instructional Technology What are We Teaching About Instructional Technology? Technology has played a significant role in education and in most successful educational reform movements of the past four decades: charter schools and home schooling; standards, testing, and accountability; best practice; outcome-based learning; professional teacher qualifications, and so forth. It remains a catalyst for changing what we teach—the essence of a personal philosophy of technology. The International Society for Technology in Education (ISTE) provides technology standards for students and divides them into six broad categories. Standards are meant to be integrated into K-12 curriculum at the introduction, reinforcement, or mastery levels. At the state level, 49 of the 51 states have adopted, adapted, aligned with, or otherwise referenced at least one set of standards in their state technology plans, certification, licensure, curriculum plans, assessment plans, or other official state documents (ISTE, 2004). With respect to the philosophy of instructional technology, teachers have these standards and profiles as guidelines for planning technology-

based activities in which lesson-based learning outcomes are focused. Table 1 displays the current technology standards for students. For technologists, NETS*S represents much of “What are we teaching about technology?” Technology fosters better communication, removing barriers that, in the past, have stymied learning. Yet, technology is not a magic potion for resolving all the woes of education. Technology, in and of itself, does not create better teachers, learners, or administrators. However, when technology is used side by side with other school improvement efforts, it can be a very effective vehicle for progress. Learning is a process that happens when teacher and student share a common experience. When students gather and process information (and as a result, form new knowledge, attitudes, or change their behavior), learning occurs. One popular philosophy of teaching and learning offers that “the teacher does not deliver education, the student constructs it.” Technology plays a significant role in changing the instructional environment by promoting the role of the teacher as a guide in educational discovery, serving as a resource to the student-as-information-gatherer. In other words, the effective teacher serves “not as the sage-on-the-stage but rather as the guideby-the-side.”

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The Pillars of Instructional Technology

Table 1. Technology foundation standards for students (Source: NETS*S, 2004) 1.

2.

3.

4.

5.

6.

Basic operations and concepts • Students demonstrate a sound understanding of the nature and operation of technology systems. • Students are proficient in the use of technology. Social, ethical, and human issues • Students understand the ethical, cultural, and societal issues related to technology. • Students practice responsible use of technology systems, information, and software. • Students develop positive attitudes toward technology uses that support lifelong learning, collaboration, personal pursuits, and productivity. Technology productivity tools • Students use technology tools to enhance learning, increase productivity, and promote creativity. • Students use productivity tools to collaborate in constructing technology-enhanced models, prepare publications, and produce other creative works. Technology communications tools • Students use telecommunications to collaborate, publish, and interact with peers, experts, and other audiences. • Students use a variety of media and formats to communicate information and ideas effectively to multiple audiences. Technology research tools • Students use technology to locate, evaluate, and collect information from a variety of sources. • Students use technology tools to process data and report results. • Students evaluate and select new information resources and technological innovations based on the appropriateness for specific tasks. Technology problem-solving and decision-making tools • Students use technology resources for solving problems and making informed decisions • Students employ technology in the development of strategies for solving problems in the real world.

Barriers to learning that once prevented students from participating fully in the educational experience are being methodically erased with the integration of technology. The “what are we teaching” question now includes assistive technologies that help special needs students experience opportunities heretofore unavailable in the traditional classroom. Computers and other technologies are powerful tools supporting students with disabilities. Auditory output devices, print magnification equipment, graphic organizing software, and voice recognition systems all offer students with disabilities equal opportunities to more fully participate in the teaching-learning process (Lengyel, 2003). Technology has become an increasingly integral part of the educational process. But, what is

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its true value as a teaching-learning strategy? Is technology just a tool for improving how we teach and learn? Or, is it also a content area equal in importance to science, mathematics, social studies, and languages? The Philosophy of Instructional Technology answers the question, “What are we teaching about instructional technology?”

The Psychology of Instructional Technology How do We Teach with Instructional Technology? The literature is replete with historically accepted schools of educational psychology. Be-

The Pillars of Instructional Technology

haviorists believe that the best way to learn is through repetition, a principle of learning that has dominated educational thinking since the time of Ivan Pavlov and his experiments with animals. The environment is the key to teaching and learning, viewed in terms of stimuli and response and the reinforcement that links them to changed behavior. Technology is appreciated as an instructional strategy because it offers a media for organization and presentation of information in a designed sequence. Cognitive psychologists focus on the learner as an active participant in the teaching-learning process. Those who adhere to this psychology of learning believe that instructional technology is more effective when tied to prior student knowledge, and linked to information processed and stored in an individual’s memory. Technology offers the schemata for presenting knowledge as a series of building blocks that the teacher places one on top of the other to build upon a student’s understanding. It was actually the information processing model, the principle upon which instructional technology is grounded, that first contributed the archetype of input, process, and retrieval of information used by today’s cognitivists supporting technology for the classroom. Humanism as a psychology is the relative newcomer on the educational scene. Technological applications of humanistic thought are even more recent. The affective elements (feelings, emotions, etc.) of learning have expressed themselves in the latest innovation for teaching and learning—the Internet. For the humanistic teacher, technology creates an educational environment that fosters self-development, cooperation, positive communications, and personalization of information (Tomei, 1998). Taxonomy for the Technology Domain, introduced in 2001, offers a view for using technology to enhance student learning (Tomei, 2001). Research shows that teachers who use a classification scheme when teaching with instructional

technology prepare instructional learning objectives that tend to produce more successful student learning outcomes (Kibler, Barker, & Miles, 1970; Krathwohl & Bloom, 1984). The classification system proposed for the Technology Domain includes Literacy, Collaboration, Decision Making, Infusion, Integration, and Tech-ology (see Table 2 for more detailed definitions). Each classification offers a progressive level of complexity, and success at each level depends on mastery of the previous step. Many educators accept teaching with technology as perhaps the most important instructional strategy to impact the classroom since the textbook. The pillar of psychology examines the key foundations of teaching and learning as applied to instructional technology. Included are issues such as faculty and student attitudes towards instructional technology, professional portfolios for educators, learning theories, instructional technology learning theories (pedagogy and androgogy), and the taxonomy for the technology domain.

The Sociology of Instructional Technology Who are We Teaching with Instructional Technology? Sociology addresses issues affecting the developers of educational systems and the educators who implement, administrators who manage, and learners who take delivery of such systems. This pillar of instructional technology examines the perspectives of each community and its relation to one another. Educators use technology to enhance individual learning as well as to disseminate knowledge within a society. They expect technology to blend with their individual approach to instruction. However, most are not fully aware of the potential

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The Pillars of Instructional Technology

Table 2. The taxonomy for the technology domain (Source: Tomei, 2001) Taxonomy Classification Literacy

Understanding Technology Collaboration

Defining the Level of the Technology Taxonomy Level 1.0—The minimum degree of competency expected of teachers and students with respect to technology, computers, educational programs, office productivity software, the Internet, and their synergistic effectiveness as a learning strategy.

Level 2.0—The ability to employ technology for effective interpersonal interaction.

Sharing Ideas Decision Making

Level 3.0—Ability to use technology in new and concrete situations to analyze, assess, and judge.

Solving Problems Infusion

Level 4.0—Identification, harvesting, and application of existing technology to unique learning situations.

Learning with Technology Integration

Level 5.0—The creation of new technology-based materials, combining otherwise disparate technologies to teach.

Teaching with Technology Tech-ology

Level 6.0—The ability to judge the universal impact, shared values, and social implications of technology use and its influence on teaching and learning.

The Study of Technology

applications of technology in the classroom or corporate training room, or how these technologies might mitigate (or perhaps eliminate entirely) the various barriers to learning from a rapidly expanding, vastly heterogeneous body of learners. Administrators experience a widening continuum of challenges with respect to instructional technology. For example, evaluating educational

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technology programs can be a formidable endeavor, particularly if the administrator has opted to remain unschooled in the applications of technology for learning. As more and more states, districts, schools, and training companies develop technology plans to ensure its effective use to benefit learning and achievement, the need to understand technology’s impact on improving

The Pillars of Instructional Technology

that achievement has become even greater. Furthermore, funding issues necessary to implement components of technology plans often require sound fiscal, as well as pedagogical, evaluation. The question thus becomes, how do you evaluate educational technology programs that impact the types of learners served, the curriculum areas in which technology is used, and the type of technology itself? Learners are demanding more technology—a simple, but understated reality of education in the twenty-first century. Just a few of the technologies found in classrooms and corporate training rooms include: computer-mediated communications, distance-based learning environments, distributed learning environments, educational multimedia, human-computer interface, hypermedia applications, intelligent learning/tutoring environments, interactive learning environments, network-based learning environments, online education, simulations for learning, and Webbased instruction/training. The sociology of contemporary technology-based learning involves an understanding of organizations, groups and classes, and even social movements in an effort

to address the question, “Who are we teaching with instructional technology?”

The History of Instructional Technology When (in the History of Education) Are We Teaching with Technology? More than any of the pillars of instructional technology, history plays an integral role in the successful introduction, implementation, and evaluation of technology for teaching and learning. The historical perspective epitomizes how technology matured by succumbing to the well-known adage, “Necessity is the mother of invention.” A short timeline of key historical instructional technology events is provided in Figure 2. Since the advent of text-based programmed instruction in the 1940s, historical events have impacted the development of the field of instructional technology. WWII surfaced the need for mass training and caused educators to seek more

Figure 2. Timeline of critical events in the history of instructional technology

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The Pillars of Instructional Technology

scientific methods and research to provide effective training materials and systematic training efforts. In 1954, Russia launched the Sputnik satellite, and the space race was on. The United States began to take seriously the effectiveness (or lack thereof) of academic curriculum and pursue with vigor the steps necessary to address learning shortfalls. Another historical event of importance to instructional technology occurred in 1958 when B.F. Skinner built his now infamous drill and practice teaching machine that permanently established the potential of technology in the classroom. The Information Age began in 1978 with the marketing of the first personal microcomputer. Further development of communications schemata grew to a shared resource environment and eventually produced the Internet and the World Wide Web. By all accounts, technology has matured past its first-generation tubes and circuit boards, beyond the second-generation transistors and programming languages, onwards past third-generation integrated circuits and desktop applications, to globalization in which the world communicates, shares information, and learns digitally. Lifelong learners travel and telecommute quickly and effectively without regard to national boundaries, literally changing forever the rules of how education serves its learner client and answering the question, “When (in the history of education) are we teaching with technology?”

Leadership in Instructional Technology Whom (sic) is Responsible for Using Technology to Teach? Leaders in technology, whether academic or corporate, face an “information revolution.” The Aspen Institute Communications and Society

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Program (NSBA, 2003) offered the following ways new information technologies are spurring complex patterns of change. They include dichotomies of centralization versus fragmentation, holistic perspective versus specialized knowledge, too much information versus too little information, leadership versus fellowship, worker isolation and alienation versus community connections, sharing versus withholding access to information, and public intervention versus private decision making. Learning in the 21st century demands a greater dependence on new communication and computing technologies supporting greater learner activity and investigation. It advances the role of educators as mentors, researchers, publishers, technology users, knowledge producers, risk takers, and lifelong learners. Technology will open doors for participation by adult learners and parents to play a more interactive role in their own education and that of their children. Leadership in technology demands a partnership with local businesses and community organizations that have such a deep interdependency on the human yield of education. Think about how future leadership roles will change as we build the schools of the future. Just a few of the consequences future schools must necessarily consider involve how they intend to become more open and flexible to the scheduling demands of their clients; how communications will promote collaboration and higher level learning; how educators will be supported in their use of technologies for learning, professional development, and their own collaboration; how future learners will use technology to achieve new levels of success and better prepare for academic or vocational future; how educational managers will use technology as a tool to direct their learning communities; and how technology will remove barriers caused by geographic separation, a variety of learning styles, and inequitable access to technology.

The Pillars of Instructional Technology

From a non-technical leadership perspective, some of the key issues facing school and corporate leaders with respect to technology include: authentic assessment tasks supported by technology; project-based, cooperative learning skills; available access to technical assistance; support for innovations from the district, state, and federal levels (or the local, regional, or national/international corporate levels); and implementation of technology in a safe (and professionally nonthreatening) environment. Together, these issues guide the implementation of technology for educators so they can once again become learners and share their ideas about teaching and learning and address the question, “Whom (sic) is responsible for using technology to teach?” Grasping each of the pillars already defined will not ensure success without considering the necessary distinction among instructional technology programs at the undergraduate, graduate, and post-graduate levels, and the degree of mastery and technical competency required at each level. Enter the K-A-RPE model.

The K-A-RPE Model Bringing the Pillars to Life The knowledge, application, and research, practice, and evaluation (K-A-RPE) model offers the necessary distinction among instructional technology programs. Assumed at each level of the model is mastery and competency at previous levels. At the Knowledge Level of the model, candidates are introduced to technologies as personal learning tools. Examine the following learning objective found in an undergraduate IT course: Given a lecture/demonstration on the basic features of electronic spreadsheets, the (undergraduate) teacher-candidate will be able to create a 10 cell x 10 cell worksheet to capture semester quiz grades and correctly compute an average (mean) score.

Figure 2. The K-A-RPE model

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The Pillars of Instructional Technology

Graduate candidates, on the other hand, seek to master technology for the advancement of their students. As practicing classroom teachers, instructional technology is presented to foster infusion into the classroom curriculum. At the Application Level, candidates seek to master technology-based skills that are immediately functional in everyday classroom instruction. An example of such a graduate-level IT learning objective follows: Using an instructional system design model of their choosing, candidates will design, develop, and publish a minimum eight-page, text-based, student workbook containing all the essential elements of a workbook appropriate for their selected classroom lesson. At the highest level of the K-A-RPE model lie research, practice, and evaluation. Doctoral candidates, too, must learn new technologies. But they do so with a rich research base to support their implementations of technology as a teaching and learning tool. They are charged with changing the way technology is experienced (i.e., practiced) in the classroom. And they do so with an eye on achievement—“technology for technology’s sake” is an empty philosophy. With a focus on the Research Level of the model, the doctoral candidate is asked to conduct the necessary investigation to determine whether the number of computers located in a particular school affects student achievement scores as evidenced in standardized tests. Here is an example: Using Internet-based data from the state department of education, candidates will seek to determine a correlation between student achievement scores received by a selected school district and the ratio of students-to-computers found in those schools. Research focus.

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Instructional technology changes at this highest level of the model by improving the Practice Level of teaching and learning wherever and whenever possible. Examine this doctoral program learning objective: Candidates will develop a visual presentation suitable for school directors and technology coordinators that provides an overview of instructional technology and its potential impact on district decision making to include: administration (planning and budgets); faculty (professional development, curriculum, and teaching load); and staffing. Practice focus. Finally, at the Evaluation Level, using technology implies assessment of student achievement; an examination of how technology succeeds (or fails) as a tool for learning. In every respect, it presupposes a firm grasp of the pillars of instructional technology education and merits co-equal status in the K-A-RPE model. A learning objective evidencing evaluation follows: Candidates will assess at least three educational software packages in each of the core academic areas of mathematics, social studies, language arts, and science. The assessment must include an appraisal of content coverage, effective use of technology, and impact on student learning outcomes. Evaluation focus. The K-A-RPE model distinguishes among instructional technology programs throughout higher education. With little argument, technology has become an increasingly integral component of the educational process. It is a catalyst for changing what we teach—the essence of the pillars of instructional technology.

The Pillars of Instructional Technology

Conclusion This chapter focuses on the five Pillars of Instructional Technology; specifically, the what, how, who, when, and whom of technology for teaching and learning. Philosophy aids in understanding the elements of instructional technology important enough to be worthy of our attention. Psychology considers the applications of technology for teaching and learning, and involves an examination of all aspects of faculty and students as well as instructional strategies and learning theories. Sociology defines the target population of our technology efforts and specifically characterizes learners who will participate in our programs. History sets technology-based instruction within the context of time and space, and reminds us that instructional technology, while not a new educational reform, remains to be mastered. Leadership places technology in the milieu of budgets, attitudes, standards, and expectations all playing an integral role in any successful technology program. The chapter concludes by introducing the K-A-RPE model for implementing the pillars in instructional technology education. Knowledge,

application, and research, practice, and evaluation focus curriculum for pre-service, in-service, and professional teacher development, and establish varying levels of technical competency expected by educators throughout their academic careers.

References Lengyel, L. (2003). Technologies for students with disabilities. Challenges of teaching with technology across the curriculum: Issues and solutions. Hershey PA: Idea Group Inc. National School Board Association. (2002). Education leadership toolkit. Retrieved from www. nsba.org/sbot/toolkit/ Tomei, L.A. (1998). Learning theories—A primer exercise: An examination of behaviorism, cognitivism, and humanism. Retrieved from www. duq.edu/~tomei/ed711psy/1lngtheo.htm Tomei, L.A. (2001). Teaching digitally: A guide for integrating technology into the classroom. Norwood MA: Christopher-Gordon Publishers.

This work was previously published in Technology Literacy Applications in Learning Environments, edited D.D. Carbonara, pp. 1-13, copyright 2005 by Information Science Publishing (an imprint of IGI Global).

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Chapter 1.4

A Psychosocial Framework for IT Education Janice A. Grackin State University of New York at Stony Brook, USA

INTRODUCTION The most recent U.S. national statistics available indicate that among those earning degrees in engineering in 2000-2001, women made up only 18% of bachelor’s degrees, 21% of master’s degrees, and 17% of doctorates (NCES, 2003). A similar pattern emerges among those earning degrees in computer and information sciences, with women awarded only 28% of bachelor’s degrees, 34% of master’s degrees, and 18% of doctorates in those areas in 2000-2001 (NCES, 2003). These and related statistics suggest a continuing gender imbalance in engineering and computer and information science education, academic pathways that lead to careers which are among those traditionally accorded higher prestige and greater financial reward than traditionally “female” occupations (Kennelly, Misra, & Karides, 1999). The situation is particularly dire in computer and information science education. According to testimony at a recent congressional hearing, although the proportion of computer

science graduates who were women increased steadily from 14% in 1972 to 37% in 1984, from 1984 to 2000 those numbers began to steadily decline again and are currently at less than 28% (Borrego, 2002). If computer and information technology education draws only from the 49% of the population which is male, the resulting gender imbalance is bound to translate into a shortage of trained IT personnel to fill existing positions. The aging IT workforce means that employers will need to fill not only new positions but those vacated by retiring personnel over the next twenty years (Jackson, 2004). The sheer number of technical professional positions to be filled now and in the foreseeable future makes it imperative that we tap the entire pool of young talent through early implementation of formal and informal strategies that encourage girls and young women to develop technical interests and skills and to enter technical training and post-secondary computer and information science education programs.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

A Psychosocial Framework for IT Education

BACKGROUND Although the factors associated with educational and career choices are complex, the relatively small numbers of young women choosing to pursue education and careers in technology and engineering may be directly related to psychosocial factors, such as a lack of professional role models (Smith, 2000). In simplest terms, a role model is someone who shares substantial characteristics of the observer and by extension is doing something the observer could do. The presence or absence of same-sex role models may transmit to individuals a powerful message regarding the gender congruity of various pursuits, including education and careers. The absence of female role models in computer and information science therefore limits the number of young women entering these education pathways, resulting in a situation where neither the academic presence nor the corporate representation of women increases. As mentioned in the previous section, the number of women in computer and information science fields is not increasing and has, in fact, decreased over the last twenty years (Women Yield High-Tech Field, 1998). Insufficient numbers of women IT academics and field practitioners means that newcomer access to senior women who can provide psychosocial and career mentoring (Johnston, 2002) is adversely impacted. Of course, young women coming into the IT education and career pathways can and do find mentors among academics and field practitioners of both sexes. However, in light of the minority status of women as a group in computer and information science, female mentors may be better equipped to guide new female entrants through the social and professional vagaries of the educational and career process (Smith, 2000). Senior women who have successfully weathered the process may be able to impart specialized knowledge regarding coping and adapting, especially important for newcomers. Minimal presence of female mentors may be one cause of the previous decade’s

female exodus from computer and information science fields.

Gender Identity, Cultural Expectations, and Cognitive Schemas That there are proportionately fewer women currently working in or choosing to enter computer and information science fields may be due in large part to gendered cultural expectations (Smith, 2000) and the gender schemas associated with them. Kohlberg’s (1966) theory of development describes the acquisition of gender constancy as a process not completed before children reach the age of five or six. It is at this point in psychosocial development that children understand that being male or female is immutable, just as they begin to integrate the gendered cultural expectations that have swirled around them since before birth and to internalize a gender identity, that is, a strong sense of what it is to be male or female. From these pervasive expectations, culturally derived cognitive schemas are built. At this point, children begin to categorize their world in more constrained ways, using schemas or frameworks into which information can be sorted automatically in order to efficiently organize and process the huge amount of incoming information about the world. Gender schemas are comprised of experienced and culturally defined elements of human “femaleness” and “maleness,” including aptitudes and behaviors, for comparison to anything that might be defined as or characteristic of female or male. Perceptions of gender roles are culturally driven (although there is a fair amount of crosscultural correspondence) and so the resulting gender schemas for “maleness” and “femaleness” are generally shared by members of the same culture. In the case of a particular educational or career path, a culture defines the skills required

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A Psychosocial Framework for IT Education

for associated pursuits, and these skills are often associated with aptitudes believed to be inherently and dispositionally “male” or “female.” In this way, certain careers come to be perceived within a culture as traditionally appropriate for women (e.g., “nurse”) or for men (e.g., “engineer”). These culturally defined gender role schemas are internalized by individuals over the course of their development, reinforced along the way by the popular media and by the attitudes and behaviors of parents, teachers and peers (Smith, Jussim, & Eccles, 1999). The cultural expectations regarding various groups can rise to the level of stereotypes, setting the stage for individual members of that group to experience what is known as stereotype threat (Steele, 1995, 1997). In performance situations where individuals are aware that a negative group stereotype exists, the anxiety produced can adversely affect performance for a variety of reasons unrelated to ability (Steele, 1995, 1997; Threats Within, 2004). Girls and young women find themselves in a stereotype threat situation any time they are performing with technology in general and computers in particular (Cooper & Weaver, 2003). The anxiety produced may negatively affect cognition and performance, resulting in performance that does not truly reflect abilities. Girls may come to doubt their own abilities and out of a need to preserve their own self-esteem they may then dissociate from technology, embracing the prevailing gender schemas that inform us that this is a male domain and that technology competence is unimportant for females.

Impact of Gender Role Schemas on Educational Choices Given the strength and pervasiveness of cultural expectations, it comes as no surprise that genderrelated schemas become quite rigid over time. Such appears to be the case with computer and information science. In western cultures particularly, skills and aptitudes associated with these

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educational and career paths have come to be perceived as traditionally male, and as a result, girls and young women may not consider computer and information science appropriate pursuits for females (Colley, Gale, & Harris, 1994). The very “culture” of computers has become associated with male values (AAUW, 2000), forcing girls to choose between technology pursuits and their basic gender identity or “femininity.” While young people can and do choose “nontraditional” education and career paths, it is clear that cultural expectations drive and constrain such choices. It can be extraordinarily difficult to successfully travel a path that defies the culture’s expectations regarding gender appropriateness. Some “non-traditional” education and career paths may be retained as viable options for males and females through high school and even beyond college entry. A student’s prior lack of interest does not substantially preclude becoming a biologist or chemist. However, the choice of post-secondary computer and information science education may be largely contingent on long-term interest and skills development, which familiarize the individual with IT culture and make these pathways recognized and viable options. Unlike traditional sciences such as biology and chemistry, computer and information science courses, even basic ones, are not offered in all high schools; in schools that offer such classes students are not required to take them. Given that these courses are often elective, the students who choose them are more likely to be those who have had a longstanding interest in computers and technology. As noted above, gendered expectations around education and careers virtually guarantee that high school students with a history of interest in computers are overwhelmingly male and white. Male students are more likely than female students to have a computer in their room at home, and to have participated in pre-high school and pre-college extracurricular computer activities such as camps, clubs and competitions (Clarke & Teague, 1996). As a result of gender differences

A Psychosocial Framework for IT Education

in early technology-related experiences outside of school those taking basic and advanced placement computer and information science courses in high school are overwhelmingly male (Bitten by the Tech Bug, 2000; Clarke & Teague, 1996; Cooper & Weaver, 2003; NCES, 2004). The gender discrepancy persists after high school graduation, with many fewer women than men enrolling in computer and information science courses when they reach college (Cooper & Weaver, 2003).

Early Intervention in IT Education The psychosocial framework as outlined in the previous sections, including gender role expectations and gender differences in early technology experiences, makes it desirable that interventions to increase the presence of women in the information technology workforce be focused on influencing the developmental process at the point at which girls are acquiring gender identity and an awareness of gender role expectations. Given the young age at which these processes occur, to be effective such interventions must be made at the earliest possible point in girls’ formal and informal education. Perusal of the 2003 and 2004 proceedings of the National Science Foundation’s ITWF & ITR/EWF Principal Investigator Conference suggests that many current programmatic approaches to increasing gender equity in computer and information science, particularly initiatives involving institutions of higher education, focus on young women of high school and college age. There appear to be many fewer such programs targeting girls of middle or junior high school age, and still fewer programs that are structured to reach girls in elementary school and that could truly be described as early interventions. Absent entirely appear to be programs that offer a continuum of technology experiences for girls from elementary school to high school. The lack

of early, long-term programmatic interventions may be due in part to the challenges and complexities of working with very young populations, as well as to the challenges inherent in building and sustaining partnerships with school districts, families, and community organizations over a period of more than a few years. However, these are obstacles that can be and must be surmounted because early intervention is essential to achieving equity in IT. The overall goal of early intervention projects must be to influence girls’ perceptions of gendered cultural expectations, and to support the development of gender role schemas that include female traits as compatible with computer and information science. Recent research suggests that young women may steer away from careers in technology not because they lack interest in technology-related activities as a whole, but because they perceive the culture of technology to be incongruent to their gender identities. That is, they perceive technology to be a male culture, unappealingly boring and antisocial, peopled with “computer geeks” working in isolation on projects that have little relevance in real terms to the advancement of the human condition (AAUW, 2000; Bitten by the Tech Bug, 2000). A gender normative technology environment, one in which a community of girls and women intersects with technology on a continuing long-term basis, offers girls an alternate gender schema that links being female with being technical. In addition, the well-established importance of role models and mentors makes it clear that if we are to attract more young women to the technology and engineering fields, we must provide very early and ongoing exposure to female role models and mentors in these fields (Bitten by the Tech Bug, 2000). For girls, early and ongoing exposure to female role models and mentors illustrates that the pairing of women and technology is both natural and desirable.

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A Psychosocial Framework for IT Education

Future Trends Given the developmental implications of the technology gender gap, future research must focus more on enhancing gender equity in IT education through development of early interventions within a psychosocial framework. Many gender equity in IT research projects incorporate potentially effective strategies, but without explicitly setting them in a psychosocial framework that focuses on influencing construction and acquisition of girls’ gender schemas. Given the similarities of approach among projects, it is clear that we have learned through our assessments that certain components “work,” that is, we can engage girls and young women in computer and information technology activities at certain points in their development, and they express interest in and enjoyment of those activities. Future research might do well to start from broader theoretical frameworks which will enable assessment to go beyond participants’ apparent, but often fleeting, interest and enjoyment to not only identify what is “working,” but also to define from a psychosocial perspective what “working’ means, and why and how some strategies appear to “work” better than others. In this way, we may move toward a higher degree of confidence in identifying strategies that can be generalized across populations to enhance equity in IT education. Given a psychosocial framework, we must direct our IT education research toward exploring intervention at critical early developmental junctures (Brown, 2001). We have often focused on developing projects that engage girls in middle and high school in technical activities, which they clearly enjoy, but we have not paid as much attention to girls’ relationships with technology. In other words, many of our interventions focus on technical learning, unlike the Girl Power 21st Century project, which focuses on girls’ evolving relationship with technology in the context of their gender identity development.

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We have seen that no matter how enjoyable technical experiences are and no matter how female-friendly the environment in which they take place, merely exposing girls to technical experiences does not with any degree of certainty translate into more women entering IT education and career pathways. In the future, it might be wise for researchers to utilize a more developmental approach, intervening early and providing a continuum of experiences that may influence the development of gender schemas, as well as attitudes regarding what is and is not a gender appropriate academic or career interest. A necessary parallel focus on influencing attitudes of family members and other influential individuals in girls’ social networks, such as educators and peers, falls quite naturally within this framework (Smith, Jussim, & Eccles, 1999).

Conclusion Early intervention set in a psychosocial framework is a promising direction for future research. We have long accepted that early intervention is necessary to achieve our goal of equal educational opportunity (e.g., Head Start programs), and equity in IT education requires us to think in similarly developmental terms. We know also that achieving a “critical mass” of women in any field facilitates change, as demonstrated by changes in the practice of medicine and, to a lesser degree, law, and academia. Only at the point of critical mass do women have the power to begin influencing a work culture from within. By intervening early in the psychosocial process that limits perceived career choices for girls, we will be helping girls to develop into young women who have incorporated different expectations into the way they view the world of work. In this way, we will enable them to introduce new cultural norms, and to create change from within the IT education and work culture, even before women have achieved that “critical mass” presence.

A Psychosocial Framework for IT Education

References AAUW (American Association of University Women). (2000). Tech-savvy: Educating girls in the new computer age. Washington, DC: American Association of Women Educational Foundation. Bitten by the Tech Bug. (2000, Fall). AAUW Outlook, 28-34. Borrego, A. M. (2002). Witnesses differ on progress of women in science and engineering since Title IX’s passage. Chronicle of Higher Education. Brown, B. L. (2001). Women and minorities in high-tech careers. ERIC Digest No. 226. Clarke, V. A., & Teague, G. J. (1996). Characterization of computing careers: Students and professionals disagree. Computers and Education, 26, 241-246. Colley, A. M., Gale, M. T., & Harris, T. A. (1994). Effects of gender identity and experience on computer attitude components. Journal of Educational Computing and Research, 10, 129-137. Cooper, J., & Weaver, K. D. (2003). Gender and computers: Understanding the digital divide. Mahwah, NJ: Lawrence Erlbaum Associates. Jackson, A. J. (2004). The beauty of diverse talent. In American Association for the Advancement of Science (AAAS) & National Action Council for Minorities in Engineering (NACME) (Eds.), Standing our ground: A guidebook for STEM educators in the post-Michigan era. Johnston, W. B. (2002). The intentional mentor: Strategies and guidelines for the practice of mentoring. Professional Psychology: Research and Practice, 33, 88-96. Kennelly, I., Misra, J., & Karides, M. (1999). Historical context of gender, race, and class in

the academic labor market. Diversity Folio (Race, Gender, & Class), 6, 125-141. Kohlberg, L. (1966). A cognitive-developmental analysis of children’s sex-role concepts and attitudes. In E. E. Maccoby (Ed.), The development of sex differences (pp. 82-173). Stanford, CA: Stanford University Press. National Center for Educational Statistics (NCES). (2003). Digest of education statistics (NCES 2003060) (pp. 336-337). Washington, DC: U.S. Dept. of Education, Institute of Education Sciences. National Center for Educational Statistics (NCES). (2004). Trends in educational equity of girls and women: 2004 (NCES 2005-016) (pp. 45-46). Washington, DC: U.S. Dept. of Education, Institute of Education Sciences. National Science Foundation (NSF). (2003, October 26-28). Proceedings of the Information Technology Workforce & Information Technology Research/Education and Workforce (ITWF & ITR/EWF) Principal Investigator Conference. Albuquerque, NM: University of New Mexico. National Science Foundation (NSF). (2004, October 24-26). Proceedings of the Information Technology Workforce & Information Technology Research/Education and Workforce (ITWF & ITR/EWF) Principal Investigator Conference. Philadelphia: Pennsylvania State University School of Information Sciences and Technology. Smith, A. E., Jussim, L., & Eccles, J. (1999). Do self-fulfilling prophecies accumulate, dissipate, or remain stable over time? Journal of Personality and Social Psychology, 77, 0022-3514. Smith, L. B. (2000). Socialization of females with regard to a technology-related career: Recommendations for change. Meridian, 3, Summer 2000. Retrieved from www.ncsu.edu/meridian/ sum2000/career/

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Steele, C. M. (1995). Stereotype threat and the intellectual test performance of African-Americans. Journal of Personality and Social Psychology, 69, 797-811.

Gender Normative: Describes activities and behaviors that are perceived to be “normal” for females or males, and which serve to reinforce gender roles within a given culture.

Steele, C. M. (1997). A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist, 52, 613-629.

Gender Role: A set of behaviors and attributes accepted within a cultural context and internalized by the individual as being appropriately linked with one sex or the other.

Threats Within. (2004, November). APA Monitor on Psychology, p. 101. Women Yield High-Tech Field. (1998, August 26). Newsday, pp. A2, A41.

KEY Terms Career Mentoring: Mentoring that is in the form of coaching, protection, and sponsorship and that advances the mentee’s career development and which prepares the mentee for advancement. Coping: Refers to individual behaviors in response to environmental stimuli and can be individually adaptive (resulting in better functioning) or maladaptive (resulting in unchanged or worse functioning). Gender Congruity: The degree to which a behavior or set of behaviors is perceived to align with the culturally defined female or male gender schema. Gender Constancy: The transition between knowing the labels “girl-boy” and recognizing that the labels are immutable which occurs around the ages of 5-6. Gender Identity: An individual’s awareness of her/his own gender and its implications, i.e., what it means, in a context that includes culture as well as biology, to be male or female.

Gender Role Schemas: Organized sets of culturally derived beliefs and expectations about males and females that provide a framework for efficient cognitive processing of information. Psychosocial Mentoring: Mentoring that is in the form of role modeling, counseling, and friendship, and that enhances the mentee’s sense of competence, identity, and work-role effectiveness. Psychosocial: Pertaining to the psychology of social interaction. Role Model: Individual perceived as an exemplar to be emulated in a specific area. Schema: Organized set of beliefs and expectations that guide information processing about a particular thing. Stereotypes: Oversimplified beliefs about a group of people, generalized to individual members of the group based on uncritical judgments. Stereotype Threat: Anxiety and apprehension experienced by individual members of minority groups in a setting where the individual’s performance or behavior has the potential to validate an existing cultural stereotype.

This work was previously published in the Encyclopedia of Gender and Information Technology, edited by E. Trauth, pp. 10291034, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 1.5

Interactive E-Learning Claude Ghaoui Liverpool John Moores University, UK W. A. Janvier Liverpool John Moores University, UK

ABSTRACT This chapter introduces the concept of improving student memory retention using a distance learning tool by establishing the student’s communication preference and learning style before the student uses the module contents. It argues that incorporating a distance learning tool with an intelligent/interactive tutoring system using various components (psychometric tests, communication preference , learning styles, mapping learning/teaching styles, neurolinguistic programming language patterns, subliminal text messaging, motivational factors, novice/expert factor, student model, and the way we learn) combined in WISDeM to create a human-computer interactive interface distance learning tool does indeed enhance memory retention. The authors show that WISDeM’s initial evaluation indicates that a student’s retained knowledge has

been improved from a mean average of 63.57% to 71.09%—moving the student from a B to an A.

INTRODUCTION This chapter discusses interaction between the computer interface and the user in e-learning and indicates that the correct use of component parts, as a result changing the way the interface interacts with each student, is likely to enhance his or her memory. Catania (1992) reports that sensory input is mainly derived from iconic (sight) 60%, auditory (hearing) 30%, haptic (touch) 10%—as little derives from olfactory (smell) and gustatory (taste). Driscoll and Garcia (2000), Fleming (2001), Fleming and Mills (1998), Fuller, Norby, Pearce, and Strand (2000), and Murphy, Newman, Jolosky, and Swank (2002) show that everyone has his or her own sensual preference for

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Interactive E-Learning

exchanging ideas, and acquiring and passing on knowledge. Sadowski and Stanney (1999) report that there is a tendency to prefer one sensory input (visual, auditory, or kinaesthetic—tactile/haptic). Fleming’s 2001 research shows that most students prefer multi-modal communication. Liu, Pastoor, Seifert, and Hurtienne (2000) assert that multimodal interfaces are more natural and engaging, encouraging a wider use of human senses and perceptual systems and that, latterly, video-games are introducing the Haptic sense, with the mouse and joysticks, and balance through headsets.

HYPOTHESIS As this chapter’s authors, we consider that communication preference (CP) linked to learning styles (LS) interaction is not used in e-learning (Janvier & Ghaoui, 2001, 2002a, 2002b). Our research hypothesis is: Matching neurolinguistic (NLP) language patterns in a distance learning tool (DLT)interactive/intelligent tutoring system (ITS) will enhance human-computer interface/interaction (HCI) communication and, thus, enhance the storing of and recall of instances to and from the learner’s memory. WISDeM (Web intelligent/interactive student distance-education model) develops this.

COMPONENTS Distance Learning Tool The learner should find a DLT intuitive to use with either an extranet, intranet, or Internet browser with the ideal DLT encompassing self-directed learning (English & Yazdani, 1999), asynchronous and synchronous communication (Phillos, Merisotis, & O’Brien, 1999; Turgeon, 1999; Wang,

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Jorg, Rubart, & Tietze, 2000), and Intelligent Interaction1 to each learner’s own profile capable of dynamically changing as the learner develops, offering: relevant links to libraries, system resources and WWW websites, hints, structured answers, tracking every learner’s progress and ‘learning’ from the learner’s usage and interactivity (see A’Herran, 2000, for an excellent presentation of the various components usually offered). A DLT should also exhibit easy-intuitive-flexible-authoring facilities; while this is not required for the student, it is vital for the tutor to be able to make changes fast and easily. The questions that need to be posed for any DLT are: 1. 2. 3. 4. 5. 6.

Is authoring easy? Is there an administrative Web database front-end? Can the author create/add/amend/delete content? Can questions and answers be easily created? Is it easy to authorize and control student access? Is online authoring training/support available?

The JCU (2000) report looked for ease of maintenance, flexibility, integration of legacy materials, consistency, a uniform framework, quality of design, and streamlining administrative procedures. Allison, Lawson, McKechan, and Ruddle (2000) suggested that quality of service needs to be addressed for all stakeholders, including students and tutors/authors. Konstandinidis, Ng, and Ghaoui (2000) consider that the number of authoring steps required should be kept low with a simple authoring interface. Technologies (2000) reported that current development authoring DLT programs/modules are experiencing a major shift in thinking: the vision is to create small independent “learning objects” in repositories for modules to be assembled as required.

Interactive E-Learning

Interactive Intelligent Tutoring System Wær (1997) considers that intelligent interfaces must make an improvement: resulting interfaces should be better than other solutions, not just different and technically more advanced. The research area of intelligent interfaces comprises two research complimentary issues: (1) creating an interface design that takes regard of the model’s limitations in reasoning power and interaction modalities, and (2) the extension of the reasoning power and presentation for the interface. The roots for research on intelligent interface design lies mainly in cognitive psychology: ITS should try to adapt to and understand the user’s way of thinking. Canut, Gouarderes, and Sanchis (1999) consider that emerging multi-agent ITSs have four main components: learner model, knowledge model, pedagogical model, and the interface model. Nkambou and Kabanza (2001) report that recent ITS architectures have focused on the tutor or curriculum components, paying little attention to planning intelligent collaboration between different components. They suggest that the ideal architecture contains a curriculum model,2 pedagogical model,3 and a learner model4 (central in ITS).

Sensory Interaction: Neurolinguistic Programming Language Patterns5 E-learning multi-modality uses multiple-studentsensory inputs. Cotton (1995) reports that each type of person uses their main preceptor style to store and recall memories: echoic use auditory perception in communication, iconic use visual perception in communication, and haptic communicate with feelings. The NLP model suggests that subjective experience is encoded in terms of three main representation systems: visual, auditory, and kinesthetic (VAK). Practitioners of NLP claim that people have a tendency to prefer one representation system over another in a given con-

text: the visual system includes external images, as well as remembered or constructed internal mental images; the auditory system includes external sounds and remembered or contrived internal sounds and the internal dialogue (i.e., a person talking to themselves on the inside); and the kinesthetic system includes tactile sensations caused by external forces acting on the body and emotional responses (Sadowski & Stanney, 1999). Pasztor (1998) reports that inter-partner rapport is key to effective communication, and that incorporating NLP language patterns and eye-gaze (see also Colburn, Cohen, & Drucker, 2000; Sadowski & Stanney, 1999) in intelligent agents will allow customization of the (virtual) personal assistant to the particular habits and interests of the user, making the system more user-friendly. Pasztor (1998) confirms that introducing the correct submodality (VAK) will enable the subject to more easily remember and recall instances.

Psychometric Test: Communication Preference Fleming (2001) suggests four sensory-modality categories that reflect students’ experiences are used for learning. Named VARK6, these include: Visually-orientated students prefer information input via their eyes, in charts, graphs, flow charts, and symbolic representation; Aural-orientated students prefer hearing information; Read/writeorientated students prefer information displayed as words; and Kinaesthetic-orientated students prefer to learn by doing, simulating real-world experience and practice. His research shows that the number of multi-modal students in a class can range from approximately 50%-90%, depending upon context. Borchert, Jensen, and Yates (1999) state that the VARK psychometric tests reveal how students prefer to receive and process information, but not necessarily how they learn best, and Driscoll and Garcia (2000) report that results from student class profiles using VARK indicate that their learning styles are firmly in place by the time

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Interactive E-Learning

a student is 18 and may well differ substantially from what their tutors perceive or assume.

Psychometric Test: Personality Type Indicator MBTI® (Myers & Myers, 1995) is a self-report personality inventory designed to provide information about your Jungian psychological type preferences.7 Murphy and colleagues’ (2002) research shows that MBTI® is more widely used by educators in the U.S. than any other tool and that the system is widely used around the world in many languages. MBTI® has four preference categories: 1.

2.

3.

4.

Interpersonal communication: Extroversion focuses outwardly on and gains energy from others; Introversion focuses inwardly and gains energy from ideas and concepts. Information processing: Sensing focuses on the five senses and experience; iNtuition focuses on possibilities, future use, the big picture. Information evaluation: Thinking focuses on objective facts and causes and effect; Feeling focuses on subjective meaning and values. Decision style: Judgment focuses on timely, planned conclusions and decisions; Perception focuses on the adaptive process of decision making.

Most researchers see information processing as the most important of the four categories in terms of implications for education (Borchert et al., 1999).

TOOL, “WISDeM” WISDeM has been developed as a generic DLT with an ITS section; it initially uses two psycho-

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metric tests to establish the student model (SM) BEFORE the module is accessed. The SM represents the student’s CP + LS8 + Novice-Expert9 factor (NE) (Biggs, 1994; Handley, 2002). The DLT uses HTML, DynamicHTML, CSS Style, JavaScript, Active Server Pages, and Structured Query Language, linking to the database using ODBC. The student’s DLT includes: university links, registration and login, low-vision user facility, staff information and module content (overview, specification, main topics, coursework, exam papers, revision (multi-choice question and answer (Q&A)), tutorials, courses (additional information)), resources, download, evaluation, feedback, forum, mail-list, student registration, search, help, MS NetMeeting).

WISDeM Interactive Tutorial Design The multi-choice Q&A interactive interface and SM are dynamically changed in real time as the student progresses through the module topics. The interface provides feedback based on the SM and motivational requirements. The tutorial is designed with two sections, Topic Revision and Course Revision. Topic Revision allows the student to either LEARN or TEST knowledge for any released topic, thus promoting memory rehearsal10 (it offers either a learning11 or an intelligent interactive testing12 tool). Course Revision picks a random multi-choice question from all the released topics; it does not provide interactivity and therefore provides a good test of long-term retained knowledge.

Scenario A new learner, Jo, connects to WISDeM, selects his school and module, and then uses his University Registration ID, password, and Module selection to log on. The system checks if he is new or existing. If the former, the CP question/answer screen is opened where Jo is asked to complete the CP questionnaire by selecting only those state-

Interactive E-Learning

Figure 1. Communication preference & learning styles flow chart used to establish the student’s CP (visual, auditory, or kinaesthetic preference) and LS Student >

cp Communication Preference

VAK Questionnaire Decision on analysis

>

A

>

>

>

v-report

a-report

k-report

>

>

>

ls V-questions

ls A-questions

ls K-questions

>

>

ls Report

>

ls Learning Syle

> K

>

V

Student agrees with report >

Initial Student Profile

ments with which he agrees: his visual, auditory, or kinaesthetic preference is established. When completed, the LS question/answer screens are activated. The questions/answers are couched using his NLP language pattern as ascertained from the CP answers. The resulting Learner Profile is saved in the Learner Profile Repository, and the module front page is opened (see Figure 1). Jo experiments with ‘Topic Learning’ and finds that he can open any topic using the hyperlinks at the top of the table—each topic opens with the first question with three answers. He goes back to Topic 1, Question 1 and reads the header message. He now reads the question and clicks the bibliography link to check if he has the correct reading material for in-depth learning; he likes the way each answer is expanded with feedback, providing him with information about the answer:

studentProfile id-school-cp-ls

why it is incorrect or correct. He notes that the color coding allows him to easily understand the various parts of the page. He clicks the next question button and reads this question. Here he sees that there is a link to a diagram; he clicks the link and remembers that it was used in his lecture. Jo continues to use Topic Learning until he has reached the end of the questions and answers. Note: Each question, answer, and feedback includes a suitable NLP language pattern subliminal text message13 (Catania, 1992; Gustavsson, 1994) header designed to activate Jo’s preferred sensory communication channel (VAK). Jo opens Topic Testing to see how well he has remembered the material. He answers the first question, reads the feedback, and notes that his selected answer was correct. He now proceeds to use the facilities and answer questions, and

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Interactive E-Learning

watches his progress for about an hour before leaving the system. When he returns he logs in again and is pleased to note that the system picks up where he stopped; he completes revision for topic 1. He likes the way he can control feedback output, see all the feedback to each answer. He also finds that the Header Messages and Information Page act as a reminder to enable to him plan his revision.

EVALUATION The evaluation formed two parts: PART 1: Evaluate the LOGON that required the student to report on the results from two psychometric tests. PART 2: evaluated the interactive ITS multi-choice Q&A section of WISDeM. PART 1 had 93 responders (82 male, 11 female): 68.09% visual, 27.66% auditory, 4.26% kinaesthetic. The average time to complete

Figure 2. Personality types (extrovert, introvert, sensing, intuitive, feeling, thinking, perceptive, judgmental) comparative results Learning Styles - Mean 4 3.8 3.6 Range - 3:5 3.4 3.2 3 eNo

iNo

sNo

nNo

fNo

tNo

pNo

jNo

Type

Figure 3. Sixteen learning styles distribution: E = extrovert, I = introvert, S = sensing, N = intuition, F = feeling, T = thinking, P = perception, and J = judgment Learning Styles 14 12 10 8 Number 6 4 2 0 ESFP ENTP INFP

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ESFJ ENTJ INFJ

ESTP ISFP INTP

ESTJ ISFJ INTJ

ENFP ISTP

ENFJ ISTJ

Interactive E-Learning

Figure 4. Comparative gain in student retained knowledge Improvement of Retained Knowledge Control vs. Interactive 75 70 Percentage 65 60 55

Control

Interactive

Learning Type run first

logon and complete the short questionnaire was 15 minutes; 64.29% were extrovert and 35.71% introvert (Extrovert | Introvert: 54/39, Sensing | iNtuitive: 65/28, Feeling | Thinking: 47/30, Perception | Judgment: 30/63). Each type was rated from 0 to 5; the mean rating for the dominant type, from a possible rating of 3 to 5, was E=3.56 | I=3.49, S=3.97 | N=3.25, F=3.67 | T=3.51 and P=3.50 | J=3.73 (see Figure 2). The largest LS was ISTJ—16.678%, with the second being ESFJ—15.48% (see Figure 3). PART 2 had 72 students log into the system. The average time taken for the evaluation/exercise was 84 minutes, varying from 50 minutes to 140 minutes. The mean mark for control subjects was 63.57%, and the mean mark for interactive subjects was 71.09% (see Figure 4). Comparing the mean gain made by students: those who completed the non-interactive Q&As first gained 21.67%; those who completed the interactive Q&As first gained 25.00%. The NE factor was substantially better for the interactive students as compared with the non-interactive students (6.75 : 3.75). In analyzing the use of button and link facility between the two types (interactive and non-interactive interfaces) of Topic Learning and Topic Testing, there was little difference noted in comparing the same buttons for each system. Overall, the interactive

students used the facility buttons 10.21 times each, as compared with 8.93 each for the non-interactive students. There was an additional use of buttons for the interactive-student; the mean usage for each was: Header Messages link = 0.50, Change Feedback Response = 0.75, Header Message = 0.75, Answer Feedback = 1.00, and Statistical Report = 0.88. These links are not available for the non-interactive student.

CONCLUSION The initial evaluation results indicate that WISDeM‘s interactive system is likely to make a significant improvement to student learning and memory. The interactive system produced more rehearsal from students than the control system and improved their marks; it was easier and more interesting to use with greater facilities to research and rehearse knowledge. There was a general belief in the system, “that it did indeed assist knowledge retention.” This in itself is an important factor for the students’ psyche. As compared with the neutral system, the interactive system held interest longer and was more capable of interacting at the student’s own level than the control system.

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Interactive E-Learning

REFERENCES A’Herran, A. (2000). Research & evaluation of online learning systems. Paper presented at ALTC-2000, UMIST Manchester, UK. Allison, C., Lawson, H., McKechan, D., & Ruddle, A. (2000). Quality of service issues in distributed learning environments. St Andrews, Scotland: School of Computer Science, University of St Andrews. Biggs, J. (1994). Student learning research and theory—where do we currently stand? In G. Gibbs (Ed.), Improving student learning—theory and practice. Oxford: Oxford Centre for Staff Development (pp. 1-13). Hong Kong: University of Hong Kong. Borchert, R., Jensen, D., & Yates, D. (1999). Hands-on and visualization modules for enhancement of learning in mechanics: Development and assessment in the context of Myers Briggs Types and VARK learning styles. Paper presented at the ASEE Annual Conference, Charlotte, NC. Canut, M.F., Gouarderes, G., & Sanchis, E. (1999). The Systemion: A new agent model to design intelligent tutoring system. In S.P.L.a.M. Vivet (Ed.), Artificial intelligence in education: Frontiers in artificial intelligence and applications (pp. 54-65). IOS Press. Catania, A.C. (1992). Learning—remembering (3rd ed.). Prentice-Hall International Editions. Colburn, R.A., Cohen, M.F., & Drucker, S.M. (2000). The role of eye gaze in Avatar mediated conversational interfaces. Retrieved September 2002, from http://www.itpapers.com/cgi/PSummaryIT.pl?paperid=10265&scid=431, http://citeseer.nj.nec.com/colburn00role.html Cotton, J. (1995). The theory of learning: An introduction. London: Kogan Page.

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Driscoll, S.A., & Garcia, C.E. (2000). Preferred learning styles for engineering students. Paper presented at the ASEE Annual Conference, St. Louis, Missouri, USA. English, E., & Yazdani, M. (1999). Computersupported cooperative learning in a virtual university. Journal of Computer Assisted Learning, 15, 2-13. Fleming, N. (2001). Teaching and learning styles: VARK strategies. Fleming, N.D., & Mills, C. (1998, May). Not another inventory, rather a catalyst for reflection. VARK for teachers, VARK study strategies. Paper presented at the AAHE’s Focus on Learning, Atlanta, GA. Fuller, D., Norby, R.F., Pearce, K., & Strand, S. (2000). Internet teaching by style: Profiling the online professor. Educational Technology & Society, 3(2), 71-85. Gustavsson, B. (1994). Technologizing of consciousness—Problems in textualizing organizations. Paper presented at the Workshop on Writing, Rationality, and Organization, Brussels, March 21-22. Handley, K. (2002, September 26-27). Comparison of novice and expert learner’s perception of instructional feedback in computer-based training to develop managerial problem-solving skills. Paper presented at the HCT2002 Workshop— Tools for Thought: Communication and Learning Through Digital Technology, Brighton, UK. Janvier, W.A., & Ghaoui, C. (2001, September 26-27). Searching for WISDeM, the Holy Grail of intelligent distance education. Paper presented at the HCT2001 Workshop—Information Technologies and Knowledge Construction: Bringing Together the Best of Two Worlds, University of Sussex, Brighton, UK.

Interactive E-Learning

Janvier, W.A., & Ghaoui, C. (2002a, September 26-27). WISDeM: Communication preference and learning styles in HCI. Paper presented at the HCT2002 Workshop—Tools for Thought: Communication and Learning Through Digital Technology, Brighton, UK. Janvier, W.A., & Ghaoui, C. (2002b, November 1-4). WISDeM—student profiling using communication preference and learning styles mapping to teaching styles. Paper presented at the APCHI 2002—5th Asia Pacific Conference on Computer Human Interaction, Beijing, China. JCU. (2000). Online systems: Research and evaluation. Retrieved September 2002, from http://www.tld.jcu.edu. au/general/syrvey_re/ recs.html Konstandinidis, V., Ng, E.H., & Ghaoui, C. (2000). Dynamic reference to support authoring of Web-based material. School of Computing and Mathematical Sciences, Liverpool John Moores University, UK. Liu, J., Pastoor, S., Seifert, K., & Hurtienne, J. (2000, November 5-8). Three-dimensional PC: Toward novel forms of human-computer interaction. Paper presented at the SPIE International Symposium on Information Technologies, Boston. Murphy, E., Newman, J., Jolosky, T., & Swank, P. (2002). What is the Myers-Briggs Type Indicator (MBTI)®. Retrieved October 2002, from http:// www.aptcentral.org/training/aptcheck.pdf. Myers, I.B., & Myers, P.B. (1995). Gifts differing: Understanding personality type. Palo Alto, CA: Financial Times, Prentice-Hall. Nkambou, R., & Kabanza, F. (2001). Designing intelligent tutoring systems: A multi-agent planning approach. Pasztor, A. (1998). Subjective experience divided and conquered, communication and cognition. In

E. Myin (Ed.), Approaching consciousness, Part II (pp. 73-102). Available online at http://citeseer. nj.nec.com/pasztor98subjective .html. Phillos, R., Merisotis, J., & O’Brien, C. (1999). What’s the difference? A review of contemporary research on the effectiveness of distance learning in higher education. Institute for Higher Education Policy. Sadowski, W., & Stanney, K. (1999). Measuring and managing presence in virtual environments. Retrieved January 2002, from http://vehand.engr. ucf.edu/handbook/Chapters/Chapter45.html Technologies, T.C.f.L. (2000). The design, development and delivery of Internet-based training and education. Available online at http://teleeducation. nb.ca/media/reports.shtml Turgeon, A.J. (1999). Implications of Web-based technology for engaging students in a learning society. Available online at http://www.adec.edu/ user/resource/turgeon-implications.html Wær, A. (1997). What is an intelligent interface? Introduction seminar. Retrieved June 2002, from http://www.sics.se/~annika/papers/intint.html Wang, W.H., Jorg, M., Rubart, J., & Tietze, D. (2000). Supporting cooperative learning of process knowledge on the World Wide Web.

ENDNOTES 1



2



Intelligent interaction: Individual studentprofiles dynamically changing as the student develops, tracking individual progress and ‘learning’ from the student’s usage/interactivity. Curriculum model: Curriculum objects describing subject matter from a domain, pedagogical and didactical point of view, and course object—describing one particular course.

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Interactive E-Learning

3



4



5



6



7



8



9



10



Pedagogical model: Tutorial actions, lesson planner, and multimedia presentation generation. Learner model: Learner model, didactic resource, and GUI interface. Neurolinguistic programming language patterns: For example, in text or speech, using words and descriptions that are ‘visual’ for visual subjects, ‘auditory’ for auditory subjects, and ‘emotional’ for kinaesthetic subjects. VARK: The VARK psychometric test now covers multi-modality as a preference. Jungian psychological type preferences: Carl G. Jung was a Swiss psychiatrist (18751961) who identified certain psychological types (Extroversion/Introversion, Judgment/Perception). Learning styles, in WISDeM, are derived from the 16 personality types developed using Carl Jungian and MBTIÒ (Myers & Myers, 1995) principles. Novice expert factor copes with the changing requirements as a novice becomes more experienced and requires less support. It varies from 0 to 8 (novice to expert), has an initial default of 3, and is incremented for each correct answer or decremented for each incorrect answer; it is set to default for each new topic. Memory rehearsal: Retention of an instance (sensual input) is improved with rehearsal

11



12



13





moving that instance from short-term memory to long-term memory, provided that the perceptual filters allow retention. Topic learning provides information for each module topic, allowing the student to develop knowledge. It covers: Q&As for each topic, select any topic’s Q&As, see the relevant bibliography, select next question. Each answer gives feedback, indicating the reason why it is correct or incorrect. Topic testing allows the student to test retained knowledge. It provides a running % total (carried forward), Q&As for each topic, see question specific bibliography, see correct answer, restart current topic at Q1, restart revision at Topic1/Q1, select next question, see any topic correct answers, view analysis report or statistical report, progress is saved, the student starts where he/she last stopped. Subliminal text messaging: Subliminal images and text (instance input that the conscious mind does not observe but the subconscious does) can have a powerful effect on memory and cognitive memory. Unconscious words are pouring into awareness where conscious thought is experienced, which could from then on be spoken (the lips) and/or written down. (Gustavsson, 1994)

This work was previously published in the International Journal of Distance Education Technologies, Volume 2, No. 3, pp. 26-35, copyright 2004 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 1.6

Innovation and Technology for 21st Century Education Murray Turoff New Jersey Institute of Technology, USA Caroline Howard Touro University International, USA Richard Discenza University of Colorado at Colorado Springs, USA

Introduction What is happening to higher education? There is a search for increasing the effectiveness of learning and expanding educational opportunities by using a combination of information technology and distance education. Teaching with technology takes time. There is the challenge of choosing equipment, redesigning courses, learning software, and building new protocols for projects, quizzes, course administration, feedback routines, lectures, and course administration. Today, these efforts must be somehow carried out in addition to continuing to teach and update current courses via the traditional means. The challenge of each innovation is that it must be carefully measured

against the successes of the traditional approaches. In addition, when dealing with technology, methods and techniques mastered last year or even last semester are often upstaged by new products that involve new time-consuming “re-learning” needs. Technology makes it easier for instructors to respond to students individually, even between classes and after the course is over. It also gives access to more course material, more media, more simulations, and more powerful indexing and search protocols. This article will review common tools and technologies used in distance education and demonstrate why they can facilitate learning and expand the educational opportunities for both distance and traditional students.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovation and Technology for 21st Century Education

BACKGROUND For many years, technologies have been used to facilitate learning. In the early 1980s a group of researchers at the New Jersey Institute of Technology (NJIT) realized the enormous potential of technology to enhance learning when they used a computer-mediated system to facilitate a regular face-to-face class. The system was introduced to students in a number of Computer Science and Information System courses. Due to the amount of material covered in lectures, there was not much time for dialogue and only a few students participated when there was a class discussion. The instructors introduced asynchronous group communication technologies to communicate discussion questions and assigned grade-point credits for student participation. One-hundred percent of the students participated in these discussions outside of regular classroom hours. The extent and depth of the discussions changed the nature of the classes. Most important, because students had the time to reflect on the ongoing discussion before participating, their contributions were comprehensive, with more well-thought-out comments. Also very significant was the equal participation by students for whom English was a second language. They could reread the online discussion as many times as needed before replying. The computer-based activity monitoring and transcripts, electronic recordings of the discussions, showed that foreign students spent two to three times more in a reading mode and reread many discussions far more often than the American students. In addition, professors now have the ability to monitor activities and review the electronic transcripts of student involvement, which gives the instructor insights into how students are learning. By reviewing the transcripts of the online discussions, it becomes obvious what and how students are learning. For courses with a high pragmatic content, such as upper-level and graduate courses

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in topics like the design and management of computer applications, students are required to utilize problem-solving approaches to evaluate the trade-offs between conflicting objectives. In a traditional classroom environment, especially in large classes, it is very difficult to detect whether students are accurately incorporating the problem-solving mental models that the instructor is attempting to convey. When instructors review the transcripts of class discussions, they are given insights into the approaches students are taking to master the material. Unfortunately, in the early 1980s few wanted to hear about a revolution in normal classroom teaching or were willing to expend the effort to dramatically improve classroom education. It was only the rise of distance education that generated interest in learning about the educational potential of the technology. Starr Roxanne Hiltz (1994) performed quasiexperimental studies that compared a population of NJIT students (only familiar with face-to-face classroom education) to a population of students taking the same courses in pure face-to-face sections with pure distance sections using only Computer-Mediated Communication (CMC) technology. The students in the matched sections had the same material, the same assignments, the same exams, and the same instructor. No significant difference was found in the amount of learning or the rate of student satisfaction. This finding is much more significant than a determination based on a study that included a population of distance learners already familiar with traditional correspondence classes. Two critical underlying variables driving the success of this approach were identified by Hiltz (1994). First, the role the instructor needed to take was different from the traditional classroom role. The instructor acted more as an active and dedicated facilitator than a traditional teacher and a consulting expert on the content of the course. Second, collaborative learning and student teamwork were the educational methodology that

Innovation and Technology for 21st Century Education

was shown in later studies to be a key factor in making distance courses as good as or better than face-to-face courses (Hiltz & Wellman, 1997). These results show that distance courses can be as effective as face-to-face courses when using any of the traditional measures, such as exams and grades. Creative, interactive software programs accompanied by background tutoring can effectively teach students to master the skills currently taught in many undergraduate courses. When these courses are automated, the costs incurred are far below typical college tuition. In the future, colleges and universities will not be able to continue to charge current tuition costs for introductory courses that are largely skill oriented. For example, there are many stand-alone and Web-based software programs that offer introductory programming courses, as well as skills in many other areas. These courses are comparable to college courses, and some are even based upon a textbook used on some college campuses. They are available for a few hundred dollars. The major difference is that they do not carry college credits. The technology allows senior professors or department chairs to effectively evaluate and mentor all instructors of particular courses, whether they are teaching traditional classroom courses or distance courses. The ability to review whole class discussions after the class is over gives senior faculty the ability to evaluate distance instructors hired to teach previously developed courses, as well as to review on-site instructors and junior faculty. Thus, they can improve and extend their mentorship and apprenticing relationships. Today’s technology for distance education allows faculty members to live anywhere they want. Unique benefits will be available to outstanding teaching faculty. For example, one of the best full-time instructors for NJIT, which is located in beautiful downtown Newark, is a mother with two small children who never has to be on campus. She is teaching other instructors

how to teach remotely. Similarly, a University of Colorado accounting professor, on sabbatical in Thailand, is able to teach a course in the Distance MBA program. There have been a few master’s programs where some or all of the instructors are located anywhere in the world. It is technically feasible for those wanting to escape winter cold to teach in places that we could previously only dream about, such as Hawaii. The technology makes it feasible, but various administrative policies, unions, insurance companies, benefit programs, and so forth, have not yet caught up to the technology. There is increasing emphasis by accrediting agencies on treating remote instructors the same as on-campus faculty members are treated. This is likely to bringing about a greater degree of equality between instructors and tenured track faculty. The outcome is uncertain, but it may mean that the costs for remote and traditional classes will equalize so that the profit margin in online classes will not be quite so high.

Specific functions of technology that facilitate learning Asynchronous Discussions In the online environment, students can take as much time as they need to reflect on a discussion and polish their comments. This improves the quality of the discussion and changes the psychology and the sociology of communications. Students can address topics in a sequence they choose rather than in a predefined order. This leads to the development of different problem-solving strategies among the individual members of the class. Sometimes courses include synchronous conferences, videoconferencing, and/or video presentations to supplement asynchronous discussions.

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Innovation and Technology for 21st Century Education

Instructor Control of Online Conference and Roles With online course conferences (many per course), instructors control the membership of each, assign roles, and enable other instructors to monitor conferences for joint-teaching exercises involving more than one course. Groups within courses are able to set up private online conferences for team and collaborative work group assignments. Joint editing of items facilitates team work.

Question and Answer Communication Protocol Instructors are able to ask questions during discussions. They can control who views the answer and prevent other students from seeing the answer of the others or engaging in the resulting discussion until they have entered their own answers. In studies of Group Decision Support Systems, it has been shown that asynchronous groups in an online Delphi mode generate many more ideas than unstructured discussions or face-to-face groups of similar size (Cho, Turoff, & Hiltz, 2003). This area has proven to be a valuable tool in forcing equal participation. Use of question-and-answer communication protocol can be used to force each student to independently think through his or her answer without being influenced by the other students.

Anonymity and Pen Name Signature When students with work experience are part of a discussion, they can use their real life experiences to illustrate the concepts the professor is presenting. Such comments from fellow students, rather than the professor, often make the instructor’s message more meaningful to the students. A student confirming the theory

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presented by a faculty member through real-life examples is more effective in making a point than “dry” data from an instructional article. Furthermore, students can talk about disasters in their companies with respect to decisions in any area and provide detail, including costs, when they are not identified and the anonymity of the company for which they work is preserved. Also, the use of pen names allow individuals to develop alternative personas without divulging their real identities and is extremely useful in courses that wish to employ role playing as a collaborative learning method.

Membership Status Lists The monitoring of activities, such as students’ reading and responding to communications, allows the professor to know what each individual has read and how up to date they are in the discussion. This allows the instructor to detect when a student is falling behind. Student collaborative teams can make sure that everyone in the team is up to date. Furthermore, students can easily compare their frequency of contributions relative to other students in the course.

Voting Instant access to group and individual opinions on resolutions and issues are enabled by voting capabilities. This is useful for promoting discussion, and the voting process is continuous so that changes of views can be tracked by everyone. Voting is not used to make decisions; rather, its function is to explore and discover what are the current agreements and disagreements or uncertainties (polarized vs. flat voting distributions) so that the class can focus the continuing discussion on the latter. Students may change their votes at anytime during the discussion.

Innovation and Technology for 21st Century Education

Special Purpose Scaling Methods These useful methods show true group agreements and minimize ambiguity. Currently we have a system that allows each student to contribute a statement at the end of the course describing what he or she thinks is the most important thing learned in the course. Then, after all such statements are compiled, everyone in the class votes by rank ordering all the items on the list. The results are reported using Thurstone’s scaling, which translates the rank order by all the individuals into a single group interval scale. In this interval scale, if 50% prefer A to B and 50% prefer B to A, the two items will be at the same point on the scale. It has been surprising what some of the results have been in some courses. For example, in a Management of Information Systems course, the concept of “runaway” software projects was felt to be twice as important as any other topic. The professor was quite surprised by this result until he began to realize that the students were using this concept of a mental model in which to integrate many of the other things they had learned.

Information Overload This occurs when enthusiastic discussions by students that are meant to augment the quality of the learning process augment only the quantity of the number of comments, leading instead to the problem of “information overload.” Currently this phenomenon limits the size of the group that can be in a single CMC class. Online discussions allow individuals to enter comments whenever it is convenient for them, without waiting for someone else to finish the point he or she is trying to make. This makes it physically possible and also very likely that a great deal more discussion will take place and much more information will be exchanged among the group than if only one person could speak at a time, as in the face-to-face classroom environment. Anything that reduces

the temptation of some students to “contribute” comments or messages that have nothing to do with the meaningful discussions underway will increase the productivity of the discussion without information overload setting in. Among such functional tools the computer can provide are: •

•

•

•

•

Class gradebooks: This eliminates a tremendous amount of electronic mail traffic that would become very difficult for an individual instructor to manage with a large class. Selection lists: The instructor can set up lists of unique choices so that each student may choose only one item and others can see who has chosen what. This is very efficient for conveying individualized assignments and reduces a large portion of communications. Factor lists: Members of a class or group can add ideas, dimensions, goals, tasks, factors, criteria, and other items to a single, shared list that may then be discussed and modified based upon that discussion and later voted upon. Notifications: Short alerts notify individuals when things occur that they need to know about. For instance, students can be notified that a new set of grades or vote distribution has been posted, eliminating the need for individuals to check for these postings. People can attach notifications to conference comments from a select list that provides alternatives like: I agree, I disagree, I applaud, Boo! Such appendages reduce significantly the need to provide paralinguistic cues of reinforcement as additional separate comments. Calendars, agendas, or schedules: Students have access to a space to track the individual and collaborative assignments and their due dates. These are listed in an organized manner that links detailed explanations for

49

Innovation and Technology for 21st Century Education

each assignment, as well as questions and answers related to the assignments. The authors have seen these technologies facilitate learning beyond what can be assessed using traditional measures. Some of the more subtle intangible benefits of technology that we have observed are: •

•

• •

•

Due to social pressures, students tend to be more concerned with how other students view their work quality than how the professor views it. They are significantly more motivated to participate in a meaningful way when their fellow students can view their contributions. When equality of communications is encouraged, students cannot get away with being passive or lazy. The transcript or electronic recording of the discussions shows who is and is not participating. It is readily evident to both the instructor and other students that someone is being lazy. (In fact, students seem to be more concerned with what the other students will think of their performance than what the professor will think.) The scope of what the outstanding students learn becomes even more noticeable. The performance of students at the lower end of the distribution is improved. The communications systems permit them to catch up, because they are able to obtain a better understanding of the material with which they are most uncomfortable or have the least background knowledge. The instructor can become more aware of his/her successes or failures with individual students because of the reflective nature of the student contributions to the discussion.

While these dimensions and concepts need confirmation through long-term longitudinal

50

studies of student performances, the marketplace is also providing confirmation of the beliefs held by many experienced in teaching these classes. We are seeing that collaboratively oriented programs offer a solution to the problems that are inherent in traditional correspondence courses. Students benefit from the ability to electronically store lectures alone or in chunks integrated into other material on the Web. Electronic storage of lectures gives all students the power to choose freely whether they want to attend a face-toface class or take the same course remotely. Traditional face-to-face students can later hear a lecture missed due to illness or travel. Students with English as a second language can listen to a lecture multiple times. Face-to-face students who have to travel or fall sick during the course can use the same tapes to catch up and/or review material prior to exams. In our view, a student in a face-to-face class that is not augmented by a collaborative learning approach and by asynchronous group communications technology is not getting as good an education as the distance student who has those benefits. It is the face-to-face student who may be suffering from the segregation of the college system into separate face-to-face and distance courses. These observations about the past and the present lead to some speculations about the future.

The State of the Technology The technology available today includes at least 250 versions of group communication software. However, many of them may not survive the decade. There are a growing number of software packages for course management. The online learning product landscape is changing at a rapid pace as companies are acquiring their competitors to expand functionality. A recent article gives an excellent summary of the popular platforms and the evolving nature of eLearning (Gray, 2002).

Innovation and Technology for 21st Century Education

There are only a few of these products that have wide usage, and they are beginning to raise their prices to capitalize on their popularity. Most of these packages charge a fee per user, which is not the desirable fee structure for the customer. Many of the older conferences systems charge on a per-server basis, and it does not matter how many students one has. It is far cheaper to spend more on the hardware and a get a more powerful server. Also, the course management systems do not provide many of the useful software features one would like to have for group communications. Given the way prices are going, it might be better to pay some of the undergraduate students to educate some of the faculty on how to create their own Web sites and have their own pages for their courses that they update and maintain directly. This also has desirable long-term consequences in raising the ability of the faculty in this area. Once you have committed all your content to one vendor’s system, you are a captured customer and will have to pay whatever they want to charge. Right now, software development is undergoing rapid evolution, and no customer should put himor herself in the box of only being able to use one vendor. If it is clear that you are using a number of vendors, you may even be able to get some breaks on pricing and will certainly get the top level of service when each of your vendors knows there is an alternative service readily available to you. In the coming decade, one can expect major upgrades for these software systems every few years, and the best one today may not be the best one tomorrow.

Course Development and Delivery Unfortunately, many faculty members do not know how to use the technology to design a successful distance course. As the historical record shows, when transferring an application to computers, it is a mistake to just copy the way

it used to be done onto the computer. Utilizing the methodology of collaborative learning is the key to designing courses using group communications technology. Simple systems that attempt to impose a discussion thread on top of what is electronic mail technology allow the student or the teacher only to view one comment at a time. This approach does not allow an individual to grasp the totality of any complex discussion. Only by placing the complete discussion thread in a single scrolling page can a person review and understand a long discussion. One can browse the discussion and cognitively comprehend it without having to perform extra operations and lose one’s cognitive focus. Users of such simple systems cannot generate a large complex discussion and have no way of realizing that complex discussion is even possible. When online discussions are successful, they can easily go from enthusiastic wonderful discussions to information overload. Current technology must evolve to fully support collaborative learning.

FUTURE TRENDS To facilitate collaborative learning, critical development directions for the future should include: • • • •

• • • •

Tailorability of communication structures by instructor Tailorability of communication protocols by instructor Anonymity and pen name provisions Delphi method tools and the availability of scaling and social judgment (voting methods) Tools for collaborative model building Powerful information retrieval capabilities Tailorability by instructor of applicationoriented icons and graphical components Tools for the analysis of alternative diagrams

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Innovation and Technology for 21st Century Education

Instructors also need to allow students to extend the discourse structure and to vote on the significance of incidents of relationships among factors in the problem domain by using Group Decision Support processes. These systems should allow students to not only develop their own conceptual maps for understanding a problem, but also to detect disagreements about elements of the conceptual map and the meanings of terms. This is valuable preparation for problem solving in their professional lives, a process that requires removing inherent ambiguities and individual meanings in the language used to communicate about a problem with others from diverse backgrounds. Routines should be included that are based upon both scaling and social judgment theories that improve the ability of larger groups to quickly reach mutual understanding. Currently, few tools exist in current systems that support the use of collaborative model building, gaming, and Delphi exercises. The current generation of software does not often include the functions of anonymity and pen names. Course instructors need to have complete control over course communication structures and processes and should be able to use their recently acquired knowledge for future offerings of the course. Currently, systems lack the needed integration of functions to easily evolve the changes in both the relationships and the content in a given field. A long-term advantage of teaching in the collaborative electronic environment is that the students create useful material for future offerings and can aid the instructor in monitoring the new professional literature. Future technology will allow faculty members to organize their material across a whole set of courses into a collaborative knowledge base available to the faculty teaching those courses. This would allow students and faculty to create trails for different objectives and weave the material in that knowledge base to suit a group of students or a set of learning objectives. Individual learning teams would be able to progress through a degree program’s knowledge

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base at the rate best for them, rather than being held to the same timeframe for all learning teams or faculty teams. Faculty, individuals, or teams would take responsibility for a specific domain with in the web of knowledge representing a degree program.

CONCLUSION Collaborative technologies are changing the concept of what constitutes a course. Program material could be an integrated knowledge web based largely on semantic hypertext structures. Over time, the domain experts, the faculty—would continue to develop and evolve their parts of the web and wait for learning groups, composed of any mix of distance and regular students sharing the same learning objectives and needs. Current vendor systems focus on the mass market and concentrate on tools to standardize and present course content. Group communication tools are usually just disguised message servers that offer only a discussion-thread capability and little more—certainly not the complex capabilities discussed above. Vendors have not yet recognized the primary importance of group communications and how faculty members can guide and facilitate the process and be available for consultation as needed. Based upon the conceptual knowledge maps they design, faculty members should be encouraged to develop content structures that are characteristic of their subject matter. In the end, faculty should have the ability to insert group communication activities anywhere in their professional knowledge base (e.g., question/answers, discussion threads, lists, voting, etc.).

NOTE A great deal of recent evaluation studies are beginning to confirm our earlier findings based upon extensive and large scale studies at such

Innovation and Technology for 21st Century Education

places as SUNY, Drexel, Penn State and others. Some of these may be found in the Journal of ALN (http://www.aln.org) and on the ALN Evaluation Community Web site (http://www. alnresearch.org).

REFERENCES Cho, H. K., Turoff, M., & Hiltz, S. R. (2003). The impacts of Delphi. In Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS), January 6-9 (p. 17a). Los Alamitos, CA: IEEE Press. Discenza, R., Howard, C., & Schenk, K. (Eds.). (2002). The design and management of effective distance learning programs. Hershey, PA: Idea Group Publishing. Gray, S. (2003). Moving—elearning vendors take aim in the changing environment. Syllabus, 16(1), 28-31. Harasim, L., Hiltz, R., Teles, L., & Turoff, M. (1995). Learning networks: A field guide to teaching and learning online. Cambridge, MA: MIT Press. Hiltz, S. R. (1993). Correlates of learning in a virtual classroom. International Journal of ManMachine Studies, 39, 71-98. Hiltz, S. R. (1994). The virtual classroom: Learning without limits via computer networks, Human-computer interaction series. Norwood, NJ: Ablex. Hiltz, S. R., & Turoff, M. (1993). The network nation: Human communication via computer (original edition 1978). Cambridge, MA: MIT Press. Hiltz, S. R., & Turoff, M. (2002). What makes learning networks effective. Communications of the ACM, 56-59.

Hiltz, S. R., & Wellman, B. (1997). Asynchronous learning networks as a virtual classroom. Communications of the ACM, 40(9), 44-49. Howard, C., & Discenza, R. (1996, October). A typology for distance learning:Moving from a batch to an on-line educational delivery system. Paper to be presented at the Information Systems Educational Conference (ISECON), St. Louis, MO. Howard, C., & Discenza, R. (2001). The emergence of distance learning in higher education: A revised group decision support system typology with empirical results. In L. Lau (Ed.), Distance education: Emerging trends and issues. Hershey, PA: Idea Group Publishing. McIntyre, S., & Howard, C. (1994). Beyond lecture-test: Expanding focus of control in the classroom. Journal of Education for Management Information Systems. Nelson, T. H. (1965). A file structure for the complex, the changing and the indeterminate. In Proceedings of the ACM 20th National Conference Proceedings, (pp. 84-99). Turoff, M. (1995). A marketplace approach to the information highway. Boardwatch Magazine. Turoff, M. (1996). Costs for the development of a virtual university. Journal of Asynchronous Learning Networks, 1(1). Turoff, M. (1997). Virtuality. Communications of ACM, 40(9), 38-43. Turoff, M. (1998). Alternative futures for distance learning: The force and the darkside. Online Journal of Distance Learning Administration, 1(1). Turoff, M. (1999). Education, commerce, & communications: The era of competition. WebNet Journal: Internet Technologies, Applications & Issues, 1(1), 22-31. Turoff, M. & Hiltz, R. S. (1986). Remote learning: Technologies and opportunities. In Proceedings

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of the World Conference on Continuing Engineering Education. Turoff, M. & Hiltz, R. S. (1995). Software design and the future of the virtual classroom. Journal of Information Technology for Teacher Education, 4(2), 197-215. Turoff, M., Discenza, R., & Howard, C. (in press). Distance learning: Really a better education? In C. Howard, K. Schenk, & R. Discenza (Eds.), Distance learning and university effectiveness: Changing educational paradigms for online learning. Hershey, PA: Idea Group Publishing. Turoff, M., Hiltz, R., Bieber, M., Rana, A., & J. Fjermestad (1999). Collaborative discourse structures in computer mediated group communications. Reprinted in Journal of Computer Mediated Communications on Persistent Conversation, 4(4).

KEY TERMS Asynchronous Group Communication Technologies: Technology that allows participants to send and respond to messages without being online simultaneously.

Distance Education: Learning situations in which the students and instructor are located in different localities at least for a portion of the class. Distributed Learning: Learning situations in which the students and instructor are located in different localities; a bit broader than distance education, as it can be used to refer to both education and training. E-Learning: The use of technology to assist in the educational process. It is often used to refer to learning situations (both education and training) in which the students and instructor are located in different localities. However, the instructor and teacher can be in close proximity. E-Learning Technologies: The technologies used for e-learning. Pen Name Signatures: Names participants choose for online participation that may or may not allow other participants to identify them. Synchronous Group Communication Technologies: Technologies that allow real-time, interactive communications and require participants to be online simultaneously.

This work was previously published in the Encyclopedia of Distance Learning, Volume 3, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 1.7

Making the Case for Case-Based Learning in Computer Information Systems Morgan M. Jennings Metropolitan State College of Denver, USA Charles H. Mawhinney Metropolitan State College of Denver, USA Janos Fustos Metropolitan State College of Denver, USA

ABSTRACT

INTRODUCTION

In this chapter, we report the results of a study comparing current student’s perceptions of computer information systems with student’s perceptions of 12 years past. We found that students continue to prefer more interaction than they perceive an IS career to provide. Given this we (1) report on some programs available in high schools to interest students in a CIS career and (2) discuss case or problem-based learning as a means to provide students with the interaction they desire and show them that it is an integral part of a CIS career.

More than a decade ago, Mawhinney, Callaghan, and Gale (1989) looked at undergraduate business students’ perceptions of the information systems (IS) profession and found that their perceptions were inaccurate and narrowly focused. Have such perceptions changed over the intervening years? Have, for example, the World Wide Web and publicity about dot.com companies and millionaires influenced the perception of computer information systems (CIS) careers?

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Making the Case for Case-Based Learning in Computer Information Systems

The motivation for the original study was a national decline in IS enrollments in the late 1980s that was adversely affecting staffing in the information systems industry. There is still a need to explore this topic because a decade plus later there is a demonstrated lack of qualified workers. According to the Information Technology Association of America (ITAA) over three-quarters of a million skilled workers are currently needed (Bredin, 2000). Mawhinney et al. (1989) believed that the decline in enrollments was due to misperceptions about IS on the part of high school students. The popular understanding was that information systems professionals worked in isolation writing computer programs. This perception is partly true if you look at the majority of the entry-level positions for an IS person. Another reason for a low number of people entering the field may be that this career opportunity is simply not heavily promoted in high schools. A study out of Australia by von Hellens and Nielson (2001) notes that engineering, mathematics, and science receive more press from high schools than IS. They also report, (a) “overall perceptions by both male and female students of the IT degree as difficult and demanding” (p. 46) and (b) perceptions from solely female study participants are that IT people work alone, have little contact with other people and the profession is strongly associated with high math skills. The findings of Mawhinney et al. (1989) were similar. Both the Mawhinney, et al. and the von Hellens and Nielson studies were conducted in the mid to late 1980s, though the later study has collected data through 2000. Statistical data comparing any differencesover-time were not included in the article so it is not clear if perceptions have changed. There are high school programs that are encouraging young people to explore information systems careers. For example, Wings 21, a successful program (Greensberg, 2000) located

56

in Omaha, NE, provides long-term exposure to technology and technology careers. This kind of long-term positive exposure to computer technology may be a means to promote accurate information regarding IS jobs as well as alleviate anxiety related to use of technology, particularity computers. In addition to a lack of understanding related to what an IS worker does in his/her job, the dropout rate within entry-level college IS courses is a problem (Myers, 2001). Many students feel they are computer literate until they enter an IS program. The skills that they possess and the skills needed within an IS degree are likely to be disparate. Rather than a sink or swim attitude on the part of colleges and universities, time spent coaching and encouraging students on relevant computer skills for the IS degree may help them feel confident and able to complete the program (Compeau, 1999). This means more than showing students the benefits of technology or how to use a computer. It may require providing meaningful situations in which to use technology (Venkatesh, 1999). Using the same questionnaire with minor adaptations for our institution, we revisited the original study by Mawhinney et al. (1985) and looked at perceptions held by current undergraduate business students. In this chapter we describe the study, the results and report ways in which CIS is being promoted in high schools and discuss the merits of authentic learning environments, particularly problem-based learning.

METHODOLOGY Hypotheses The first hypothesis tested was the same as the one tested by Mawhinney et al. (1985). It compared the current students’ perceptions of IS position

Making the Case for Case-Based Learning in Computer Information Systems

characteristics against the characteristics of their desired position upon graduation. Stated in null form, the hypothesis tested was:

commuter students. Students have some flexibility concerning when they take the course, though it is the prerequisite for all IS courses.

H1: Students perceive no difference between the work style of the typical IS graduate and their own expected starting position’s work style.

Instrument and Procedure

The second hypothesis tested compared the responses from the current students against the responses from the original study. This two-part hypothesis compares their own expected starting position’s work style and compares their perceptions of the work style of IS graduates. Stated in null form, the hypotheses tested were: H2a: The two groups of students had the same expectations for the work style of their own starting positions. H2b: The two groups of students had the same perceptions of the work style of the typical IS graduate.

Subjects The subjects were students from fifteen sections of our entry-level computing course. Five hundred and nineteen usable responses were received. Like the original study, our sample came from a course that is taught from a common syllabus and is a combination of hands-on computing labs and hardware, software and personal computing concepts. This course is required of all business majors and is often the first exposure they have to CIS. Some institutional differences between the two groups of students should be noted. The original study took place in a private college with traditional full-time residential students who were required to take the course as first semester freshmen. The current study took place in a public college with a large portion of non-traditional

We utilized the original questionnaire that appeared in Mawhinney et al. (1985) with some minor adaptations to our institution. The questionnaire is shown in the Appendix and consisted of 18 items. The first nine items assessed perceptions of the background and work styles of a CIS graduate of the program. Questions 10 - 18 asked the same questions from the perspective of the student’s own background and work-style preferences. A five point Likert scale consisting of Strongly Agree, Agree, Undecided, Disagree, and Strongly Disagree was used for the responses. They were converted to a numeric scale for scoring (strongly disagree equaled one and strongly agree equaled five). Mawhinney et al. (1985) performed factor analysis and subscale reliability analysis to determine if any subscales existed in the instrument. They concluded that there were no sufficiently interpretable and reliable subscales, and treated the perception measures as separate items. Since we were trying to compare our results to theirs we did not do any subscale investigation and simply used the separate items as they did. We performed our data collection during the first week of the semester. The questionnaire was distributed in conjunction with an objective computer literacy screening test that we ordinarily perform at that time in this course. The students were not asked to identify themselves when responding to this questionnaire. Mawhinney et al. (1985) used a somewhat different procedure. The first nine items were included in an initial survey (PRE). Eight months later a follow-up survey using the 18 item questionnaire was mailed to participants who provided their names and addresses.

57

Making the Case for Case-Based Learning in Computer Information Systems

RESULTS

•

Table 1 shows the means and standard deviations for the responses regarding Hypothesis 1: first for the IS graduates perceived work style (IS) and then for their own expected starting positions (SELF). The null hypothesis was tested using t-tests for paired comparisons of the corresponding means. For all nine items the average perceptions of the IS graduate’s work style were significantly different from the average expectations of the students’ own starting positions (one item at p < .05 and the other eight items at p < .001). Compared with their perceptions of the IS graduates’ initial background, the respondents feel they:

• •

• •

• • •

These results are consistent with those of Mawhinney et al. (1985), except that they did not find significant differences for Items #1 and #2. The first part of the second hypothesis (Table 2) compared the responses from the current students against the responses from the original study concerning their own background and preferred work style. The analysis was performed using t-tests for independent samples. The values from the current study are shown as “MSCD” and those from the original study as “Bentley.” The summary values from the original study were used to perform the analysis. Six of the nine items showed significant differences, some of which were quite strong (one item at p < .05, one item at p < .01, and the other four items at p < .001).

Are weaker at mathematics (Item #1) Entered MSCD with a stronger computer background (Item #2)

Compared with their perceptions of the IS graduate’s first job, the respondents expect to: •

Spend more time interacting with other persons (Item #4) Spend less time working alone (Item #5) Be less involved in designing computer hardware (Item #6) Interact less with other computer people (Item #7) Receive a higher starting salary (Item #8) Be less involved in helping managers select new computer systems (Item #9)

Spend less time writing computer programs (Item #3)

Table 1. Perceptions of MSCD SELF vs. IS graduates work-styles Mean

n = 519 t-value

Item

IS

SELF

Signif

IS

SELF

f-value

Signif

1

2.83

2.71

2

2.79

2.99

2.43

*

0.92

1.03

17.59

***

-3.67

***

1.02

1.17

18.32

***

3

2.78

2.24

4

3.58

4.19

10.94

***

0.93

1.00

0.02

-5.81

***

0.88

2.32

0.60

5

2.83

2.45

7.61

***

0.95

0.98

1.65

6

2.68

2.12

11.73

***

0.94

0.94

4.13

*

7

3.17

2.63

10.02

***

1.03

1.15

14.07

***

8

3.26

3.49

-4.82

***

0.88

1.01

9.93

**

9

3.33

2.89

8.30

***

0.92

1.15

32.61

***

Note: (2-tailed) * p < 0.05 ** p < 0.01 *** p < 0.001

58

Standard Deviation

Making the Case for Case-Based Learning in Computer Information Systems

Table 2. Perceptions of SELF: MSCD vs. Bentley students Mean Item

MSCD

Bentley

t-value

1

2.71

2.59

1.14

2

2.99

2.52

4.07

3

2.24

1.77

4.76

4

4.19

4.10

0.41

5

2.45

2.21

2.45

6

2.12

1.67

4.80

7

2.63

2.21

3.71

8

3.49

3.41

0.89

9

2.89

2.58

2.65

Signif

Standard Deviation MSCD

Bentley

f-value

1.03

1.04

0.99

Signif

***

1.17

1.11

1.11

***

1.00

0.72

1.93

*

2.32

0.65

12.69

*

*

0.98

0.84

1.37

*

***

0.94

0.72

1.69

*

***

1.15

0.85

1.83

*

1.01

0.90

1.25

**

1.15

0.98

1.38

*

Note: (2-tailed) * p < 0.05 ** p < 0.01 *** p < 0.001

Table 3. Perceptions of IS graduates: MSCD vs. Bentley students Mean

Standard Deviation

Item

MSCD

Bentley

t-value

Signif

MSCD

Bentley

f-value

1

2.83

2.61

2.18

*

0.92

1.01

0.82

2

2.79

2.72

0.66

1.02

1.08

0.88

3

2.78

2.90

-1.34

0.93

0.90

1.07

4

3.58

3.39

2.05

0.88

0.89

0.97

5

2.83

2.72

1.22

0.95

0.86

1.21

6

2.68

2.65

0.34

0.94

0.89

1.11

7

3.17

3.28

-1.12

1.03

0.94

1.20

8

3.26

3.09

2.00

*

0.88

0.79

1.25

9

3.33

3.52

-2.07

*

0.92

0.73

1.58

*

Signif

*

Note: (2-tailed) * p < 0.05 ** p < 0.01 *** p < 0.001

Compared with the self-perceptions of the Bentley students’ initial background, the MSCD students felt they: •

Entered college with a stronger computer background (Item #2)

Compared with the self-perceptions of the Bentley students’ desired work style, the MSCD students felt they would: • •

Spend more time writing computer programs (Item #3) Spend more time working alone (Item #5)

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Making the Case for Case-Based Learning in Computer Information Systems

• • •

Be more involved in designing computer hardware (Item #6) Interact more with other computer people (Item #7) Be more involved in helping managers select new computer systems (Item #9)

The second part of the second hypothesis (Table 3) compared the responses from the current students against the responses from the original study concerning the background and work style of IS graduates. The analysis was performed using t-tests for independent samples. The values from the current study are shown as “MSCD” and those from the original study as “Bentley”. The summary values from the original study were used to perform the analysis. Four of the nine items showed significant differences, all at p < .05. Compared with the Bentley students’ perceptions of the initial background of IS graduates, the MSCD students felt they: •

Are stronger at mathematics (Item #1)

Compared with the Bentley students’ perceptions of the work style of IS graduates, the MSCD students felt they would: • • •

Spend more time interacting with other persons (Item #4) Receive a higher starting salary (Item #8) Be less involved in helping managers select new computer systems (Item #9)

Hypothesis 1 is rejected and it can be concluded that our students do perceive numerous differences between the work style of the typical IS graduate and their own expected starting position’s work style. This is consistent with the findings of Mawhinney, et al. (1985), except they did not find significant differences for the first two items. This seems to indicate that, like the students 12 years ago, current students prefer more

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interaction with other people than they perceive an IS career to provide. Hypothesis 2a is also be rejected. The MSCD students clearly have a different background than the Bentley students. It should be expected that students would have a stronger computer background than students of twelve years prior, even though the MSCD students are not traditional students. Some institutional differences between the two groups of students should be noted. The original study took place in a private college with traditional full-time residential students who were required to take the course as first semester freshmen. The current study took place in a public college with a large portion of non-traditional commuter students. Students have some flexibility concerning when they take the course, though it is the prerequisite for all IS courses. The MSCD students also exhibit differences in their preferred work style—differences that are more in keeping with their perception of the work style of IS graduates. The Mawhinney, et al. (1985) study does not indicate what proportion of their sample was IS majors. However, they do indicate that it took place at a time of rapidly declining IS enrollments. It is quite likely that the MSCD sample had a substantially higher proportion of IS majors (indeed, 24% of our sample indicated they were CIS majors) and that may very well account for this result. Another possibility is that business students in general perceive themselves and jobs as more technically oriented. Hypothesis 2b is not so clear-cut. Although four of the nine items were significantly different, five were not, and those that were weren’t particularly strong differences. We would argue that the perceptions of the two groups of students regarding the background and work style of IS graduates were more alike than different and would not reject this hypothesis. The similar perceptions are not too surprising if job advertisements influence the perception of information systems work. Between 1970

Making the Case for Case-Based Learning in Computer Information Systems

and 1990 advertisements showed an increase in phrases specifying technical knowledge at the cost of business and systems knowledge (Todd, McKeen, & Gallupe, 1995). This is in contrast to both anecdotal and research evidence that managers often rate the need for ‘soft’ skills (i.e., problem solving, communication, working in groups) higher than technical skills (Turner & Lowry, 2002; Shawyunm, 1999). Given this change of focus over time, an extended questionnaire would provide a more in depth picture of student perceptions of information systems.

DISCUSSION Certainly more research is needed regarding students’ perceptions of an IS career. A review of literature found few recent articles focusing on student perceptions or understanding of IS. While we do not have a clear picture of student perceptions, we do have evidence that when students have an opportunity to experience the field of CIS, many find it to their liking. Anecdotal stories regarding the positive effects of partnerships are included in the literature. Companies spend a great deal of money on student programs. GE spends about 1 billion annually on education and training programs with paid college internships being the largest portion (Kolbasuk-McGee & Mateyaschuk, 1999). Kolbasuk-McGee and Mateyaschuk (1999) present an example of a GE success story that turned a math major from a career in actuary work to an IS related full-time job. The intern’s reason for her career change was that she had the opportunity to experience information systems work in business and found that she enjoyed it. In this study we found that compared to the student’s in the original study, current student’s work style preferences are more in keeping with their perceptions of an IS graduate. While this is positive, there is also indication that more in-

teraction is desired than students perceive an IS career to provide. Given the team or group-based projects approach that are part of a career in this field, promotion of CIS to high school students should include the ‘people’ aspects along with the technical aspects. In addition, authentic learning environments should be included in CIS curriculum. Authentic learning environments provide students with the interaction they desire and show them that interaction is an integral part of a CIS career. In both cases a combination of accurate and persistent promotion of what IS entails and opportunities to experience realistic use of information systems is important.

High School Programs Lack of understanding regarding an IS career is not uncommon. As Mawhinney et al. (1985) and von Hellens and Nielson (2001) found, students’ idea of CIS entailed working alone and required a high level of math. Because of this lack of understanding students may be surprised when they start a program or they may decline entering a program because of the scarce or inaccurate knowledge they have regarding such a degree or career. Early intervention at the high school level may help ameliorate the misperception. There are programs that target high school students. Often it is corporations that are stepping in to train the not-so-future-workers. Cisco is well known for its Networking Academy Program that is open to high school students (Greensberg, 2000). This partnership between business, education and government teach the design, building and maintenance of computer networks. Another partnership program is Generation Yes; a successful nationwide program that partners knowledgeable IT students with teachers. The trained students help the teachers use technology to teach more effectively (Greensberg, 2000). Kolbasuk-McGee and Mateyaschuk (1999) describe how General Electric, Booz Allen &

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Hamilton, IBM, and Prudential Insurance Co. of America, Bell Atlantic and KPMG International are working with students and teachers in K-12. The programs that these companies spend millions of dollars on include volunteerism, training, and internships. The purpose of these programs is to increase the use of technology for both teachers and students. The companies know that they are investing in the long term in order to have a technology knowledgeable work force. Wings 21 located in Omaha, NE, provides long-term exposure to technology and careers (Greensberg, 2000). After completing an introduction to technology course, students have the opportunity to take more advanced courses such as electronic imaging/publishing, computer programming or computer-aided design. Paid internships and contract work with area businesses such as Qwest are also available. The New Technology High School (NTMS) in Napa, CA, is unique. According to Salpeter (1999), the concept for this award winning school is twofold: Prepare local students for a technology rich future and draw businesses to the area. Students learn spreadsheets, databases, word processors, and presentation software through real-world projects. In a multimedia design and production class students use appropriate software and learn and related concepts such as ethical issues regarding manipulating emotions and privacy concerns. Additionally, at least one (per semester) advanced computer course is required at the local community college. Students have access to electronic research databases and other Internet sources through the school library. This kind of a high school environment is enticing because of the real-world collaboration. With authentic learning environments the necessary information technology skills are embedded in the learning process. Also embedded in the learning process are the soft skills that managers say are lacking in employees, such as problem solving, communicating effectively and work-

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ing in group environments (Lee & Trauth, 1995; Todd et al., 1995).

Making a Case for Cases Without programs such as Wings 21 or The New Technology High School and even with them, the computer skills that students possess and the skills needed within an IS degree are often disparate (Easton & Easton, 2002; Karsten & Roth, 1998). Other students rightly assume that they will learn the skills that are needed. In either case, students often find themselves failing, which may contribute to the dropout rate within entry-level college IS courses (Myers, 2001). According to a study completed by ITAA (Information Technology Association of America) managers placed fouryear colleges and private technical institutions as the best method for acquiring overall “pre-hire” skills (ITAA, 2000). Colleges may be the best way to learn IT, but we are doing little to help students succeed and to experience a holistic view of CIS. Addressing this problem seems particularly important because of the shortage of qualified workers. Rather than a sink or swim attitude on the part of colleges and universities, time spent coaching and encouraging students on relevant skills for the IS degree may help them complete the program (Compeau, 1999). As with some of the high school programs, this requires providing meaningful and relevant learning environments in which to use the technology (Venkatesh, 1999) that are similar to actual work-related scenarios (Gallivan, 2000). Without an accurate picture, it is difficult for students to understand the work style of information system professionals. The content of CIS courses are technically-oriented and many students struggle with the content, usually in isolation. This, however, belies the actual business environment where employees usually work together on projects. Learning should take place

Making the Case for Case-Based Learning in Computer Information Systems

in a similar environment. In addition, research suggests that there is a synergistic learning effect within group environments (Savery & Duffy, 1995; Ryan, Bordoloi, & Harrison, 2000). For example, better understanding of a system and development of more accurate mental models was found in a group environment (Gallivan, 2000). An unconstructive aspect of such a learning situation is that negative comments may affect the attitude of group members (Gallivan, 2000). The literature in favor of authentic learning environments outweighs this concern, however.

Authentic Learning Environments There is a body of research and theory on the importance of providing authentic and relevant learning environments (Gallivan, 2000). This is often within the context of constructivism, an umbrella term that identifies a learning philosophy (Lebow, 1993; Savery & Duffy, 1995; Vanderbilt, 1990). Case or problem-based learning, situated cognition, discovery learning, cooperative learning and anchored instruction are some of the models within a constructivist paradigm. While concepts may vary, overriding principles include active engagement, collaboration and personal relevance. The reasons for learning are embedded within rich, authentic contextually relevant environments (Lebow, 1993). Case and problem-based learning (PBL) are examples. Neither cases or PBL (Barrows, 1985) are new concepts and there seem to be negligible differences for purposes of this discussion. Originally known as the Harvard Case Method, cases originated in the 60’s. The objective of the case method was to enhance judgment and decision-making capability and it is widely used because of its success (Potvin, 2000). Problembased learning was developed in the mid 50’s for medical education (Savery & Duffy, 1995). At many medical schools it has replaced the lecture approach for the first two years of medical science

curricula (Savery & Duffy, 1995). Teachers, or facilitators, are mentors and guides who challenge students to problem solve; they model higher order thinking skills (Savery & Duffy, 1995). For discussion purposes we will use these two terms interchangeably. The interaction between peers provided by such learning environments is a successful means to engage students (Vanderbilt, 1990). It is, however, not often used because of the time commitment and the difficulty in devising ‘good’ problems. Contextually-rich cases are available in books and online sources, such as Harvard Online. Properly developed holistic learning environments such as PBL are more likely to develop ownership on the part of the students involved (Savery & Duffy, 1995) and may promote what Agarwal and Karahanna (2000) calls cognitive absorption and (Jennings, 2000) calls cognitive aesthetics. In a PBL environment, over the course of a semester, students work together to devise solutions based on well-articulated problems. The problem is the focus while any use of technology (as is likely to be the case in CIS) is secondary; it is a tool to solve the problem. Focusing on the content and pedagogy rather than on the technology may lead to sustained interest (McKinnon & Nolan, 2000). Savery and Duffy (1995) subscribe to the following instructional principles for PBL that derive from a constructivist approach: 1. 2. 3. 4.

5.

Anchor all learning activities to a larger task or problem Support the learner in developing ownership for the overall problem or task Design an authentic task Design the task and the learning environment to reflect the complexity of the environment they should be able to function in at the end of learning Give the learner ownership of the process used to develop a solution

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6. 7. 8.

Design the learning environment to support and challenge the learner’s thinking Encourage testing ideas against alternative views Provide opportunity for and support reflection on both the content learned and the learning process

As an example, in a problem-based introductory multimedia course students learn about and use the six elements of multimedia (interactivity, audio, video, images, text, animation). The learning is embedded in producing an authentic product, often one that is needed by a local company. The concept is ‘sold’ to the students in order to elicit their support of the problem. The problem is sufficiently complex in order to challenge a learner, but not so technically advanced that it deters students. While students have a responsibility to learn about and use all of the appropriate technology for the problem, the problem rules the use of the technology. Students alternate using the various technologies as they are needed for the product. The benefits of this approach include: (a.) students concentrate on the relevancy of particular element for the product, (b.) they scaffold each other in learning as the semester progresses and (c.) all students learn the appropriate technology. Help is also available in many different forms including help screens, reference materials, just-in-time tutorials by the instructor and other available sources the students find. Objectives for a problem include specific content learning. While traditional PBL uses peer and self-evaluation, variations include traditional testing based on the objectives. Traditional testing may help alleviate instructor concerns regarding student’s learning and contribution to the group effort. It is not enough to simply provide a problem. In order for this paradigm to work, students must become a team and team building must be taught. Wells (2002) uses Katzenbach and Smith’s definition of team work: “A team is a

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small number of people with complementary skills who are committed to a common purpose, performance goals, and approach for which they hold themselves mutually accountable.” Without team building instruction students often perceive group work with disdain: With guidance on team building students are more positive in regard to the experience (Wells, 2002).

Trend Setting Companies have high expectations for CIS graduates (Shawyunm, 1999). It behooves us as educators to provide the business community with students who have had realistic CIS experience. Authentic learning environments provide this. Working together, faculty within CIS degree programs could construct a curriculum based on authentic learning environments such as case or problem-based learning. Team building concepts could be taught in the ubiquitous entry-level computing course so that students would have the skills to work effectively in groups.

CONCLUSION We repeated a study of undergraduate business majors that was performed in 1989, and compared the perceptions of contemporary students with those previously reported (Mawhinney et al.). We found that current student’s perceptions of CIS have not significantly changed: Like students in the original study, current students prefer more interaction than they perceive an IS career to provide. Promoting the ‘soft side’ as well as the technical aspects of CIS to high school students may help change perceptions. Additionally, using case or problem-based learning environments in CIS college programs would provide students with real-world skills and an accurate understanding of CIS. With authentic learning environments and team building instruction, the technology and

Making the Case for Case-Based Learning in Computer Information Systems

soft skills are embedded in the learning process. By using this learning approach CIS majors experience interesting and varied problems during their student tenure. They enter the work force with immediately usable skills and a realistic understanding of their career of choice.

References Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and belief about information technology usage. MIS Quarterly, 24(4), 665-694. Barrows, H. S. (1985). How to design a problembased curriculum for the preclinical years. New York: Springer Publishing. Bredin, S., Malyan-Smith, J. (2000). On the fast track, [Online database]. Wilson Select database [2001, September 23]. Compeau, D. H., C. A. & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158. Easton, G., & Easton, A. (2002, May 19-22). Assessing Computer Literacy: Are Our Students Getting More Proficient? Paper presented at the Information Resources Management Association International Conference, Seattle, WA. Gallivan, M. J. (2000, April 6-8). Examining workgroup influence on technology usage: A community of practice perspective. Paper presented at the ACM SIGCPR Conference, Chicago. Greensberg, R. (2000, October). Filling the gap. Techniques (Association for Career and Technical Education), 75, 2-27. ITAA. (2000). Executive summary - Bridging the gap: Information technology skills for the new millennium, [WWW]. Information Technology Association of America. Available at http://www.

itaa.org/workforce/studeis/hw00execsumm.htm Jennings, M. M. (2000, April). What do good designers know that we don’t? Paper presented at the Information Resources Management Association International Conference, Anchorage, AL. Karsten, R., & Roth, R. (1998). The relationship of computer experience and computer self-efficacy to performance in introductory computer literacy courses. Journal of Research on Computing in Education, 31(1), 14-24. Kolbasuk-McGee, M., & Mateyaschuk, J. (1999, February 15). Educating the masses: Sluga’s IT internship with GE. Information Week, 2002, 61. Lebow, D. (1993). Constructivist values for instructional system design: Five principles toward a new mindset. Educational technology research and development, 41(3), 4-16. Lee, D. M. S., & Trauth, E., Douglas. (1995). Critical skills and knowledge requirements of IS professionals: A joint academic/industry investigation. MIS Quarterly, 19(3), 313-340. McKinnon, D. H., & Nolan, C. J. P. (2000). A longitudinal study of student attitudes toward computers: Resolving an attitude decay paradox. Journal of Research on Computing in Education, 32(3), 325-335. Myers, M. E., Beise, C. M. (2001, April 18-21). Nerd work: Attractors and barriers perceived by students entering the IT field. Paper presented at the ACM SICCPR Conference, San Diego, CA. Potvin, J. (December, 2000). The Case Method, [WWW]. Bellanet Advisor. Available at htt p//w w w.bellanet.org/advisor/index. cfm?Fuseaction=view_article&TheArticle=38 Ryan, S., Bordoloi, B., & Harrison, D. A. (2000). Acquiring conceptual data modeling skills: The effect of cooperative learning and self-efficacy on learning outcomes. The DATA BASE for Advances in Information Systems, 31(4), 9-24.

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Salpeter, J. (1999). New technology high school: Preparing students for the digital age. Technology & Learning, 19(6), 46. Savery, J. R., & Duffy, T. M. (1995). Problem based learning: An instructional model and it’s constructivist framework. Educational Technology, 31-37. Shawyunm, T. (1999). Expectations and influencing factors of IS graduates and education in Thailand: A perspective of the students, academics and business community. Informing Science, 2(1), 19-32. Todd, P. A., McKeen, J. D., & Gallupe, R. B. (1995). The evolution of IS job skills: a content analysis of IS job advertisements from 1970 to 1990. MIS Quarterly, 19(1), 1-18. Turner, R., & Lowry, G. (2002, May 19-22). Towards a profession of information systems and

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technology: The relative importance of “hard” and “soft” skills for IT practitioners. Paper presented at the Information Resourses Management Association International Conference, Seattle, WA. Vanderbilt, T. c. a. T. G. a. (1990). Anchored instruction and it’s relationship to situated cognition. Educational Researcher, 2-10. Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of intrinsic motivation. MIS Quarterly, 23(2), 239-260. von Hellens, L., Nielson, S. (2001, July). Australian women in IT. Communications of the ACM, 44, 46-56. Wells, C. E. (2002). Teaching Teamwork in Information Systems. In E. B. Cohen (Ed.), Challenges of information technology education in the 21st century. Hershey, PA: Idea Group Publishing.

Making the Case for Case-Based Learning in Computer Information Systems

APPENDIX: The Questionnaire My major is:_____________________________________________________________ The following questions deal with your perception of the undergraduate Computer Information Systems program at Metropolitan State College of Denver. Please indicate the strength of your agreement/disagreement with each statement by circling the letter(s) that best describe your feeling about or reaction to each statement. Legend: Strongly Agree (SA) Agree (A) Undecided (U) Disagree (D) Strongly Disagree (SD) The typical graduate of this program:



1.

Is a whiz at mathematics.

SA

A

U

D

SD

2.

Entered Metro with a strong prior background in computers.

SA

A

U

D

SD



During his/her first job after graduation, the typical graduate of this program: 3.

Spends most of his/her working time writing computer programs.

SA

A

U

D

SD

4.

Spends most of his/her working time interacting with other persons.

SA

A

U

D

SD

5.

Spends most of his/her time working alone.

SA

A

U

D

SD

6.

Designs new computer hardware.

SA

A

U

D

SD

7.

Interacts mostly with other computer people.

SA

A

U

D

SD

8.

Has a starting salary above the average Metro graduate.

SA

A

U

D

SD

9.

Helps managers select new computer systems.

SA

A

U

D

SD

The following questions deal with your assessment of your own background and job preferences. I believe that I:



10. Am a whiz at mathematics.

SA

A

U

D

SD

11. Entered Metro with a strong prior background in computers.

SA

A

U

D

SD

12. Spend most of my working time writing computer programs.

SA

A

U

D

SD

13. Spend most of my working time interacting with other persons.

SA

A

U

D

SD

14. Spend most of my time working alone.

SA

A

U

D

SD

15. Design new computer hardware.

SA

A

U

D

SD

16. Interact mostly with other computer people.

SA

A

U

D

SD

17. Have a starting salary above the average Metro graduate.

SA

A

U

D

SD

18. Help managers select new computer systems.

SA

A

U

D

SD

During my first job after graduation, I expect to:

This work was previously published in Current Issues in IT Education, edited by T. McGill, pp. 11-25, copyright 2003 by IRM Press (an imprint of IGI Global).

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Chapter 1.8

What is an Authentic Learning Environment? Anthony Herrington University of Wollongong, Australia Jan Herrington University of Wollongong, Australia

Abstract Recent research and learning theory provides a wealth of thought, ideas and strategies to inform the design and implementation of learner-centered, realistic and effective learning environments. This chapter proposes guidelines for designing authentic learning environments for higher education that can be applied across a range of disciplines and in a variety of modes. Characteristics of the approach are explored in depth, and the chapters of the book are introduced as examples of authentic learning environments in diverse subject areas and contexts. The chapter provides a practical framework for teachers wishing to break away from traditional, teachercentered approaches in higher education, and who are willing to create learning environments where

students are motivated to learn in rich, relevant and real-world contexts.

Toward Authenticity in Higher Education Take a walk around most university campuses and observe what you see in the way of adult teaching and learning. If you are fortunate, you will find students engaged in motivating and challenging activities that require collaboration and support. The tasks the students do reflect the tasks seen in real professions and workplaces, and the problems they solve are complex and sustained, requiring intensive effort. For most students at university today, the reality is very different. Large lecture theatres, centre-staged with discipline experts, continue to transmit theoretical knowledge in bite-sized

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

What is an Authentic Learning Environment?

chunks for passive learners to receive and consume. Collaboration is not encouraged or required. If it occurs at all, it is sought subversively among students away from the formality of the lecture halls. So, why is the second scenario the more probable one to encounter? The approach taken by many teachers in universities today is simply a result of the way they were taught. They are perpetuating a tradition of formal university teaching that has ignored the substantial insights gained from more recent theory and research into the way people learn. Typically, university education has been a place to learn theoretical knowledge devoid of context. Essentially, for students, this has meant that their teachers transmit the facts and skills that they are required to absorb and regurgitate on exams. Textbooks and lecture notes are the main resources for study, with the practice of “cramming” for exams a common learning strategy. Retention and transfer of knowledge was assumed but rarely assessed. For many students a “surface” approach to learning (Marton & Säljö, 1976) assured success. It is not surprising that a growing proportion of graduates now choose to follow their university courses with practical courses at vocationally oriented institutions (Golding & Vallence, 1999). In the wider community it has become increasingly clear to employers of university graduates and governments that fund universities that university learning outcomes are lacking, and no longer meet the needs of a dynamic and changing workforce. What employers, governments and nations require are graduates that display attributes necessary for knowledge building communities: graduates who can create, innovate, and communicate in their chosen profession. If traditional approaches to university education do not result in appropriate learning outcomes, what then are the teaching and learning approaches that universities should adopt? The growing influence of constructivism as a philosophical approach

to learning, and a wide range of research studies and papers investigating alternative models of teaching and learning over the last decade, have prompted many teachers in universities to implement more “authentic” teaching and learning environments. The challenge they have faced is to align university teaching and learning more substantially with the way learning is achieved in real-life settings, and to base instructional methods on more authentic approaches, such as situated learning (Brown, Collins, & Duguid, 1989; Collins, Brown, & Newman, 1989; McLellan, 1996; Cobb & Bowers, 1999). But what does it mean to be authentic? Some have argued that only real-problem contexts should be presented to ensure authenticity. For example, Savery and Duffy (1996) nominated two guidelines in developing problem-based scenarios for teaching and learning: firstly, that the problems must raise the concepts and principles relevant to the content domain, and secondly that the problems must be real. However, other research into the realism of learning environments has indicated that maximum fidelity, either in real situations or simulations, does not necessarily lead to maximum effectiveness in learning, particularly for novice learners (Alessi, 1988). Others argue, however, that in designing learning environments it is impossible to design truly “authentic” learning experiences. Petraglia (1998a, 1998b) contended that authenticity can be neither “predetermined nor preordained,” and such attempts often result in little more than “pre-authentication,” that is, “the attempt to make learning materials and environments correspond to the real world prior to the learner’s interaction with them” (p. 53). Barab, Squire and Dueber (2000) have also argued that authenticity occurs “not in the learner, the task, or the environment, but in the dynamic interactions among these various components … authenticity is manifest in the flow itself, and is not an objective feature of any one component in isolation” (p. 38). Smith (1987) in his review of research related to simulations in

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What is an Authentic Learning Environment?

the classroom concluded that the “physical fidelity” of the simulation materials is less important than the extent to which the simulation promotes “realistic problem-solving processes” (p. 409), a process Smith (1986) describes as the “cognitive realism” of the task. Similarly, we would argue that it is the cognitive authenticity rather than the physical authenticity that is of prime importance in the design of authentic learning environments (Herrington, Oliver, & Reeves, 2003). Authenticity goes beyond mere relevance.

Characteristics of Authentic Learning Recent research and learning theory provides a wealth of thought, ideas and strategies to inform the design and implementation of student-centered, realistic and effective learning environments. This chapter proposes guidelines for designing authentic learning environments in higher education based upon nine critical characteristics of authentic learning identified by Herrington and Oliver (2000) in their extensive review of literature and technology-based learning environments. The guidelines are based on constructivist philosophy and approaches, and specifically on situated learning theory.

different perspectives (Brown et al., 1989; Hill & Hannafin, 2001; Honebein, Duffy, & Fishman, 1993; Reeves & Reeves, 1997). Many courses ignore the rich potential of an authentic context by disembedding course materials from ordinary experience (Sternberg, Wagner, & Okagaki, 1993). Generalised, theoretical principles and skills are taught rather than the situation-specific capabilities, and textbooks often guide curriculum and context rather than the genuine practices of professionals. Such courses are often characterised by subject matter divided into weekly sections (reflecting textbook chapters), and usually presented in lectures/tutorial format. By contrast, a course with a more authentic context is presented as a realistic problem preserving the complexity of the real-life setting. Students are able to access information resources as required, rather than have topics presented in a linear manner through weekly lectures and tutorials. Web-based courses might use an interface that comprises a metaphor representing the elements of the subject matter. For example, a course on marine biology might be represented by an image of a marina, or one on occupational health and safety by an image of a workplace, a teaching course by a classroom, a nursing course by a hospital ward, and so on. In any of its delivery forms, the context provides a realistic and authentic rationale for the study of a complex problem.

Provide an Authentic Context That Reflects the Way the Knowledge Will be Used in Real Life

Authentic Activities

The context needs to be all-embracing, to provide the purpose and motivation for learning, and to provide a sustained and complex learning environment that can be explored at length. It is not sufficient to simply provide suitable examples from real-world situations to illustrate the concept or issue being taught. It needs to encompass a physical environment which reflects the way the knowledge will be used, and a large number of resources to enable sustained examination from

The tasks that students perform are arguably the most crucial aspect of the design of any learning environment. Ideally such tasks should comprise ill-defined activities that have real-world relevance, and which present complex tasks to be completed over a sustained period of time, rather than a series of shorter disconnected examples (Bransford, Vye, Kinzer, & Risko, 1990; Brown et al., 1989; Lebow & Wager, 1994; Reeves & Reeves, 1997).

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What is an Authentic Learning Environment?

University courses often require students to complete tasks and activities that are largely abstract and decontextualised (Lebow & Wager, 1994). They are formulated by others, well-defined and complete in scope (Sternberg et al., 1993), and often lead simply to an enculturation into the practices of universities and classrooms rather than real-world transfer (Clayden, Desforges, Mills, & Rawson, 1994). Such activities bear little resemblance to those of real practitioners (Brown et al., 1989). In contrast to this fragmented and decontextualised approach, a situated learning approach promotes authentic activities that can create the focus for the whole course of study—the activity does not necessarily supplement the course, it can be the course (Herrington, Reeves, Oliver, & Woo, 2004). Lave and Wenger (1991) cautioned that the conception of situated learning was substantially “more encompassing in intent than conventional notions of ‘learning in situ’ or ‘learning by doing’ for which it was used as a rough equivalent” (p. 31). Instead, activities can be complex and ill-defined, and echo the same complexity found in real-world tasks.

Access to Expert Performances and the Modelling of Processes To expose students to expert performance is to give them a model of how a real practitioner behaves in a real situation. Access to such modelling of processes has its origins in the apprenticeship system of learning, where students and craftspeople learned new skills under the guidance of an expert (Collins et al., 1989). Important elements of expert performances are found in modern applications of the apprenticeship model such as internship, and case-based learning (Riesbeck, 1996). In many university courses, students are given no examples of experts performing tasks, or of expert comment, to enable them to model real-

world practice. In order to provide such expert performance, the required skill or performance could be modelled within a real-life context. For example, if a scientific report is the required product, a similar report could be available to students. Video excerpts could show interviews with experts, or short clips of experts performing within their real environments. These allow students to observe the “social periphery” of relevant tasks as they are performed in the real world. Encouraging students to seek out expert opinion on the Internet and to subscribe to listservs gives them access to the ideas of experts and others at varying levels of expertise. The facility of the World Wide Web to create global communities of learners who can interact readily via e-mail, also enables opportunities for the sharing of narratives and stories.

Multiple Roles and Perspectives In a more authentic learning environment, it is important to enable and encourage students to explore different perspectives, and to “criss cross” the learning environment repeatedly (Collins et al., 1989; Spiro, Feltovich, Jacobson, & Coulson, 1991a). Instruction which puts forward a single, “correct” interpretation, is according to Spiro, Feltovich, Jacobson and Coulson (1991b) not false, but inadequate. Frequently, university courses promote learning compartmentalised and constrained by strict discipline boundaries (Relan & Gillani, 1997). Content is often discipline-specific, and presented in modules and sections, with little to offer students seeking alternative viewpoints. By contrast, providing a multitude of perspectives to enable students to examine problems from the point of view of a variety of stakeholders is more conducive to sustained and deep exploration of any issue or problem.

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Collaborative Construction of Knowledge The opportunity for users to collaborate is an important design element, particularly for students who may be learning at a distance (Brown et al., 1989; Collins et al., 1989; Hooper, 1992; Reeves & Reeves, 1997). Collaboration has been defined as “the mutual engagement of participants in a coordinated effort to solve a problem together” (Roschelle & Behrend, 1993, cited in Katz & Lesgold, 1993, p. 289). Forman and Cazden (1985) have suggested that true collaboration is not simply working together but also “solving a problem or creating a product which could not have been completed independently” (p. 329). However, many university courses promote individual endeavour and cognition rather than collaboration, and students’ activities are largely solitary. Students are given little opportunity to collaborate, despite the affordances of physical proximity and technology to enable it. In order to promote collaboration, group work can be facilitated with an appropriate incentive structure for whole group achievement. For example, activities and problems can be addressed to a group such as a board of directors, committee, interest group, department, and so forth. Collaboration can be encouraged through appropriate tasks and communication technology. For example, discussion boards and chat rooms can be used to encourage sharing and joint problem solving within and among groups.

Reflection In order to provide opportunities for students to reflect on their learning, the learning environment needs to provide an authentic context and task, as described earlier, to enable meaningful reflection. Many theorists see reflection as both a process and a product (Collen, 1996), and that it is action-oriented (Kemmis, 1985). Knights

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(1985) contends that reflection is not the kind of activity that its name suggests—a solitary, internal activity—but a two-way process with the “aware attention” of another person. This view is strongly supported in the literature by others who point out that reflection is a social process (Kemmis, 1985), and that collaboration on tasks enables the reflective process to become apparent (von Wright, 1992). In many learning environments, there are few opportunities to reflect because of an emphasis on pre-determined content that needs to be learned, and few opportunities to collaborate means students cannot reflect socially. In order to promote reflection, authentic and meaningful activities can be provided, together with access to expert performance and opinion to enable students to compare themselves to experts. Collaborative groupings enable students to reflect socially, and to engage in meaningful discussions on issues presented. Journals, portfolios and Web logs can provide a tangible outcome of students’ reflections.

Articulation In order to produce a learning environment capable of providing opportunities for articulation, courses need to incorporate inherent opportunities to articulate, and in particular the public presentation of argument to enable defence of the position (Edelson, Pea, & Gomez, 1996; Lave & Wenger, 1991). Baktin (1986) contends that “any true understanding is dialogic in nature” (Brown & Campione, 1994, p. 267). The implication is that the very process of articulating enables formation, awareness, development, and refinement of thought. Vygotsky has influenced the way educators see the role of articulation in learning (cf., Davydov, 1995). Vygotsky believed that speech is not merely the vehicle for the expression of the learner’s beliefs, but that the act of creating the speech profoundly influences the learning process: “Thought undergoes many changes as it

What is an Authentic Learning Environment?

turns into speech. It does not merely find expression in speech; it finds reality and form” (cited in Lee, 1985, p. 79). In many higher education courses, students are not required to articulate and justify their work to their peers. By contrast, more authentic tasks require articulation of ideas in one form or another. Students are required to present and defend their arguments in appropriate forums, such as in face-to-face classes, conferences and seminars, or by publishing on the Internet or on Web-based bulletin boards and listservs.

Coaching and Scaffolding In order to accommodate a coaching and scaffolding role principally by the teacher (but also provided by other students), an authentic learning environment needs to provide collaborative learning, where more able partners can assist with scaffolding and coaching, as well as the means for the teacher to support learning, for example, via appropriate communication technologies (Collins et al., 1989; Greenfield, 1984). Coaching in a situated learning environment requires “powerful, but different roles for teachers” (Choi & Hannafin, 1995, p. 67), where the interactions with students occur mainly at the metacognitive level (Savery & Duffy, 1996). In many university courses, the teacher’s role is a didactic one, “telling” students what they need to know rather than a coaching role (Harley, 1993). The teacher controls the learning situation (Berge, Collins, & Dougherty, 2000; Jonassen, 1993) organising the order of content, activities, and assessment. A common approach used to present tasks and problems is to simplify the topic by breaking it down into its component parts. However, Perkins (1991) has suggested that oversimplification should be resisted, and instead teachers should search for new ways to provide appropriate scaffolding and support. A more authentic environment provides for coaching at

critical times, and scaffolding of support, where the teacher and/or student peer mentors provide the skills, strategies and links that the students are unable to provide to complete the task.

Authentic Assessment In order to provide authentic assessment of student learning, the learning environment needs to ensure the assessment is seamlessly integrated with the activity and provide the opportunity for students to be effective performers with acquired knowledge, and to craft products or performances in collaboration with others (Duchastel, 1997; Reeves & Okey, 1996; Herrington & Herrington, 1998). Arguably, the majority of university learning continues to involve competitive relations and individual assessment. Particularly in online courses, students are frequently assessed with multiple choice or other tests that are easily marked, often revealing only whether students can recognise, recall or “plug in” what was learned out of context (Wiggins, 1990). An alternative approach is to provide for integrated assessment of learning within the tasks, where students present polished products.

Applying Authentic Principles to the Design of Learning for Higher Education Authentic learning has found a place in the education agenda, as greater accountability in higher education grows. As technology continues to open up possibilities for innovative and effective teaching and learning opportunities, students and teachers are no longer happy to accept familiar classroom-based pedagogies that rely on content delivery and little else. While many teachers instinctively find the authentic approach appealing, many have difficulty envisaging how these

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principles could be applied across the disciplines, and how they might work both in face-to-face classes and Web-based environments. As the title suggests, this book is made up of a collection of peer-reviewed chapters that reflect the construct of authenticity in teaching and learning as it is reflected in higher education institutions throughout the world. The book is divided into three sections. Section I provides guidelines to designing authentic learning environments and encompasses the theoretical notions on which these environments are based. Section II contains chapters that describe how authentic activities are instantiated in a range of discipline areas commonly found in university settings. These authors relate the practical designs of their learning environments to both discipline-based theories and situated-learning theories described in part one. Section III chapters discuss generally how authentic environments can be implemented and sustained more widely across an institution. The elements of authenticity presented above comprise one framework for the design of effective and immersive learning environments that are appropriate for both face-to-face and technology-mediated courses, such as online subjects. However, not all the authors of the chapters presented here universally adopt these ideas. Different viewpoints and interpretations of authenticity are presented throughout, adding to a rich and diverse collection of perspectives and consequent learning designs. All the learning environments described in this volume do, however, have one characteristic in common: they universally depict the work of dedicated and innovative teachers with a passion for excellence, and a desire to create inspirational learning experiences for their students. The concept of authentic learning is not new. However, its practice is arbitrary and undefined. The purpose of this book is to define the approach through examples of good practice. We hope that the rich variety of examples of good practice found in this book will provide the reader with

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the inspiration to teach their own subjects and courses in ways that reflect authenticity.

References Alessi, S. (1988). Fidelity in the design of instructional simulations. Journal of Computer-Based Instruction, 15(2), 40-47. Barab, S.A., Squire, K.D., & Dueber, W. (2000). A co-evolutionary model for supporting the emergence of authenticity. Educational Technology Research and Development, 48(2), 37-62. Berge, Z.L., Collins, M., & Dougherty, K. (2000). Design guidelines for web-based courses. In B. Abbey (Ed.), Instructional and cognitive impacts of web-based education (pp. 32-40). Hershey, PA: Idea Group Publishing. Bransford, J.D., Vye, N., Kinzer, C., & Risko, V. (1990). Teaching thinking and content knowledge: Toward an integrated approach. In B. F. Jones & L. Idol (Eds.), Dimensions of thinking and cognitive instruction (pp. 381-413). Hillsdale, NJ: Lawrence Erlbaum. Brown, A.L., & Campione, J.C. (1994). Guided discovery in a community of learners. In K. McGilly (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. 229-270). Cambridge, MA: MIT Press. Brown, J.S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42. Choi, J., & Hannafin, M. (1995). Situated cognition and learning environments: Roles, structures and implications for design. Educational Technology Research and Development, 43(2), 53-69. Clayden, E., Desforges, C., Mills, C., & Rawson, W. (1994). Authentic activity and learning. British Journal of Educational Studies, 42(2), 163-173.

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Cobb, P., & Bowers, J. (1999). Cognitive and situated learning perspectives in theory and practice. Educational Researcher, 28(2), 4-15.

Harley, S. (1993). Situated learning and classroom instruction. Educational Technology, 33(3), 4651.

Collen, A. (1996). Reflection and metaphor in conversation. Educational Technology, 36(1), 54-55.

Herrington, J., & Herrington, A. (1998). Authentic assessment and multimedia: How university students respond to a model of authentic assessment. Higher Education Research & Development, 17(3), 305-322.

Collins, A., Brown, J.S., & Newman, S.E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, learning and instruction: Essays in honour of Robert Glaser (pp. 453-494). Hillsdale, NJ: LEA. Davydov, V.V. (1995). The influence of L.S. Vygotsky on education theory, research and practice. Educational Researcher, 24(3), 12-21. Duchastel, P.C. (1997). A Web-based model for university instruction. Journal of educational technology systems, 25(3), 221-228. Edelson, D.C., Pea, R.D., & Gomez, L. (1996). Constructivism in the collaboratory. In B.G. Wilson (Ed.), Constructivist learning environments: Case studies in instructional design (pp. 151-164). Englewood Cliffs, NJ: Educational Technology. Forman, E.A., & Cazden, C.B. (1985). Exploring Vygotskyan perspectives in education: The cognitive value of peer interaction. In J.V. Wertsch (Ed.), Culture, communication and cognition: Vygotskian perspectives (pp. 323-347). Cambridge: Cambridge University. Golding, B., & Vallence, K. (1999). The university — VET transition. RCVET Working Paper, UTS Research Centre for Vocational Education and Training, Sydney. Greenfield, P.M. (1984). A theory of the teacher in the learning activities of everyday life. In B. Rogoff & J. Lave (Eds.), Everyday cognition: Its development in social context (pp. 117-138). Cambridge, MA: Harvard University.

Herrington, J., & Oliver, R. (2000). An instructional design framework for authentic learning environments. Educational Technology Research and Development, 48, 23-48. Herrington, J., Oliver, R., & Reeves, T.C. (2003). ‘Cognitive realism’ in online authentic learning environments. In D. Lassner & C. McNaught (Eds.), EdMedia World Conference on Educational Multimedia, Hypermedia and Telecommunications (pp. 2115-2121). Norfolk, VA: AACE. Herrington, J., Reeves, T.C., Oliver, R., & Woo, Y. (2004). Designing authentic activities in webbased courses. Journal of Computing in Higher Education, 16(1), 3-29. Hill, J.R., & Hannafin, M.J. (2001). Teaching and learning in digital environments: The resurgence of resource-based learning environments. Educational Technology Research and Development, 49(3), 37-52. Honebein, P.C., Duffy, T.M., & Fishman, B.J. (1993). Constructivism and the design of learning environments: Context and authentic activities for learning. In T.M. Duffy, J. Lowyck & D.H. Jonassen (Eds.), Designing environments for constructive learning (pp. 87-108). Heidelberg: Springer-Verlag. Hooper, S. (1992). Cooperative learning and computer-based design. Educational Technology Research and Development, 40(3), 21-38. Jonassen, D. (1993). The trouble with learning environments. Educational Technology, 33(1), 35-37.

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Katz, S., & Lesgold, A. (1993). The role of the tutor in computer-based collaborative learning situations. In S.P. Lajoie & S.J. Derry (Eds.), Computers as cognitive tools (pp. 289-317). Hillsdale, NJ: Lawrence Erlbaum. Kemmis, S. (1985). Action research and the politics of reflection. In D. Boud, R. Keogh & D. Walker (Eds.), Reflection: Turning experience into learning (pp. 139-163). London: Kogan Page. Knights, S. (1985). Reflection and learning: The importance of a listener. In D. Boud, R. Keogh & D. Walker (Eds.), Reflection: Turning experience into learning (pp. 85-90). London: Kogan Page. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge: Cambridge University. Lebow, D., & Wager, W.W. (1994). Authentic activity as a model for appropriate learning activity: Implications for emerging instructional technologies. Canadian Journal of Educational Communication, 23(3), 231-144. Lee, B. (1985). Intellectual origins of Vygotsky’s semiotic analysis. In J.V. Wertsch (Ed.), Culture, communication and cognition: Vygotskian perspectives (pp. 66-93). Cambridge: Cambridge University. Marton, F., & Säljö, R. (1976). On qualitative differences in learning. I: Outcome and process. British Journal of Educational Psychology, 46, 115-27. McLellan, H. (Ed.). (1996). Situated learning perspectives. Englewood Cliffs, NJ: Educational Technology. Perkins, D.N. (1991). What constructivism demands of the learner. Educational Technology, 31(8), 19-21. Petraglia, J. (1998a). The real world on a short leash: The (mis)application of constructivism to

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the design of educational technology. Educational Technology Research and Development, 46(3), 53-65. Petraglia, J. (1998b). Reality by design: The rhetoric and technology of authenticity in education. Mahwah, NJ: Lawrence Erlbaum. Reeves, T.C., & Okey, J.R. (1996). Alternative assessment for constructivist learning environments. In B.G. Wilson (Ed.), Constructivist learning environments: Case studies in instructional design (pp. 191-202). Englewood Cliffs, NJ: Educational Technology. Reeves, T.C., & Reeves, P.M. (1997). Effective dimensions of interactive learning on the World Wide Web. In B.H. Khan (Ed.), Web-based instruction (pp. 59-66). Englewood Cliffs, NJ: Educational Technology. Relan, A., & Gillani, B.B. (1997). Web-based instruction and the traditional classroom: Similarities and differences. In B.H. Khan (Ed.), Web-based instruction (pp. 41-46). Englewood Cliffs, NJ: Educational Technology. Riesbeck, C.K. (1996). Case-based teaching and constructivism: Carpenters and tools. In B.G. Wilson (Ed.), Constructivist learning environments: Case studies in instructional design (pp. 49-61). Englewood Cliffs, NJ: Educational Technology. Savery, J.R., & Duffy, T.M. (1996). Problem based learning: An instructional model and its constructivist framework. In B.G. Wilson (Ed.), Constructivist learning environments: Case studies in instructional design (pp. 135-148). Englewood Cliffs, NJ: Educational Technology. Smith, P.E. (1986). Instructional simulation: Research, theory and a case study (ED No. 267 793). Smith, P.E. (1987). Simulating the classroom with media and computers. Simulation and Games, 18(3), 395-413.

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Spiro, R.J., Feltovich, P.J., Jacobson, M.J., & Coulson, R.L. (1991a). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. Educational Technology, 31(5), 24-33.

Sternberg, R.J., Wagner, R.K., & Okagaki, L. (1993). Practical intelligence: The nature and role of tacit knowledge in work and at school. In J.M. Puckett & H.W. Reese (Eds.), Mechanisms of everyday cognition (pp. 205-227). Hillsdale, NJ: Lawrence Erlbaum.

Spiro, R.J., Feltovich, P.J., Jacobson, M.J., & Coulson, R.L. (1991b). Knowledge representation, content specification, and the development of skill in situation-specific knowledge assembly: Some constructivist issues as they relate to cognitive flexibility theory and hypertext. Educational Technology, 31(9), 22-25.

von Wright, J. (1992). Reflections on reflection. Learning and Instruction, 2, 59-68. Wiggins, G. (1990). The case for authentic assessment. Washington, DC: ERIC Clearinghouse on Tests, Measurement, and Evaluation.

This work was previously published in Authentic Learning Environments in Higher Education, edited A. Herrington and J. Herrington, pp. 1-14, copyright 2006 by Information Science Publishing (an imprint of IGI Global).

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Chapter 1.9

A Brief History of Networked Classrooms: Effects, Cases, Pedagogy, and Implications Louis Abrahamson The Better Education Foundation, USA

Abstract

Introduction

The objective of this chapter is to explain the huge, burgeoning sense of excitement surrounding response systems, and more generally, networked classrooms today. Also why, for an idea apparently more than 40 years old, it took this long to happen! Beginning with a brief history of early response systems, it takes up the story from the author’s own experience, leading through hardware barriers, misconceptions about pedagogy, and classroom successes, to summarize the variety of uses, and how they lead to improved teaching and learning. It then discusses why this is such a potentially important area of study for improving education, and finally goes on to describe the emerging characteristics of, and rationale for, more powerful types of modern systems.

Today, at almost every university in the USA, somewhere a faculty member in at least one discipline is using a response system in their teaching. This is a phenomenon that has mushroomed to its present stage, mainly within the past three years, from a mere handful of pioneering educators a decade ago. Also, the revolution appears not to be limited to higher education. A cursory Web search, conducted in early 2005, found names of over 3,000 school buildings at the primary and secondary levels in the USA also using response systems. On the technology front, a brief survey showed 12 manufacturers of networked classroom systems,1 compared with one or two a little more than a decade ago. Amazingly, these generally somewhat primitive tools are used in just about every discipline taught. An example from the author’s own experi-

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

A Brief History of Networked Classrooms

ence: in the process of inquiring about response system usage at the University of Texas at Austin2 for a letter of recommendation, I was told that response systems were being used that semester in over 10 disciplines, including physics, chemistry, psychology, biology, mathematics, criminal justice, computer science, library science, pharmacy, and physical education. In education, few things happen this fast or with such endemic impact. Arguably, not since the overhead projector, has a piece of technology received such widespread acceptance as an aid to classroom teaching. The purpose of this chapter is to give some of the history behind this apparently sudden success story, and also to introduce the work described in this volume by giving some of the practical and theoretical background upon which the success has been based.

Personal Background It is a salutary exercise for me, because I have spent a good deal of the past 20 years working with some of the predecessors of today’s response systems, as well as some more advanced networked classrooms, and have firsthand experience of the history and difficulties behind the current successes. I also believe there is an excellent case to be made that current response systems represent only the first, humble step in an exciting, but as yet little explored territory of pedagogical tools that have the power to transform teaching and learning in formal education. My interest in networked classrooms began almost by accident. From an education in physics and applied mathematics, I was 18 years into a career in aerospace3 and managing my own research company when, in 1985, we had a small amount of unbudgeted overhead money that needed to be spent during that year. Within certain limits, as specified on government CPFF4 contracts, the choice on how to spend it was mine, so I decided to use it to pursue an old dream of improving

teaching. With two colleagues (Fred Hartline & Milton Fabert) we built the first prototype of a series of systems known as Classtalk. Classtalk I was a response system constructed of surplus (i.e., junk) Atari keypads, each modified to include an additional communication circuit board, an LED display, and connected to the teacher’s computer by a special-purpose digital multiplexer. Our main test system was installed in a large lecture hall (seating 200 students) at Christopher Newport University,5 where it was used for teaching physics. After a couple of years of use, at the end of every semester, we took surveys of the students. Almost 90% of the students said they understood the subject better, came to class better prepared, paid more attention in classes, and enjoyed it more (Abrahamson, 1999, 2000). The professor (Dr. George Webb) said that the entire atmosphere in his class had changed; that it had become a much more lively, active, and friendly place. He found that weaker students, who would previously have dropped his course, would stay in to risk taking a “D” because they were enjoying it. He also found that the feedback he obtained from the system improved his teaching, and he could engage their interest and thinking in ways that were not possible before (Abrahamson, 1995).

An Early History of Response Systems and Learning Results The idea of using an electronic system in a classroom for gathering and aggregating student answers to questions has been around for almost 40 years. But it is not a story of steady growth and success. Rather, it is one of pioneering efforts, followed by failure, with subsequent reinvention by others who (at least initially) had no knowledge of the prior work. The first systems actually built and used appear to be those installed in a lecture hall at Stanford University in 1966, and another at Cornell University about 1968 (Littauer, 1972). There are also descriptions of German and Japanese patents about this same period, but it is not

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known if working versions of these systems were ever built. Details of the construction of the Stanford and Cornell systems are not available today, but some idea of the technological difficulty of implementing such systems in the premicroprocessor prenetwork age can be inferred from verbal reports of early users of the Stanford system (Linn, 2004) who said that it either “never worked,” or “was a total pain to use.” Some insights into the limitations of the technology of the day can be gained from the patent descriptions, one of which details, for example, a maze of wiring, analogue electronics, and aggregation represented by four voltmeters on the teacher’s podium, each voltmeter dial representing the number of students selecting a particular answer to a multiple choice question. The Cornell system seems to have been more successful, perhaps because it was the brainchild of the same physicist, Raphael Littauer, who actually taught with the system and who seems to be the first person reporting positive classroom experiences from response system use. In their recent paper, Judson and Sawada (2002) give probably the best summary to date of early work on response systems, some of which they report stemmed from research by the military on training techniques. They state that in every one of these early test cases student attitudes towards use of response systems in university lectures was uniformly positive (Bapst, 1971; Brown, 1972; Casanova, 1971; Garg, 1975; Littauer, 1972). However, they also quote early results from Bapst (1971), Bessler (1969), Bessler and Nisbet (1971), Brown (1972), and Casanova (1971), showing no gains in student achievement from the use of response systems.

Two Lucky Accidents Had my colleagues and I known of these results before starting our experiments, we would likely never have built a system at all, or gone to the trouble of wiring it into a lecture hall. But, perhaps fortunately, coming from a background outside

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of education research, we were unaware of them at the time of our work with Classtalk I. We were also the unwitting beneficiaries of two lucky accidents. The first was that (due to cost) we had only 64 keypads in a lecture hall that seated 200 students. So, we designed the software to accept answers from (up to) four students at each keypad, which could be passed between them. Because of the limited two-meter length of the hardwired cord, students formed natural groups, and began conversing with each other: something not usually natural in this commuter school where few students know each other. The second accident was the pedagogical orientation of the professor. At the time he began using the system, George Webb was a Dean at the university, and had taught the same introductory physics course for over 15 years. He not only knew the material like the back of his hand, but despite his other duties, chose to continue teaching because he enjoyed it. The system gave him the opportunity to try out pedagogical ideas, and he was secure enough, both in his knowledge of the material and his professional circumstances, to risk failure. From our observations of early semiembarrassing lecture periods, and from his own reports, both were important, because even using the system every single lecture, he appeared to be still improving with his new teaching methods after three semesters. Perhaps had George Webb known of other people’s failures a decade and half before, there is a possibility he may not have stuck with it. However, in retrospect, I feel this possibility is remote because even after a couple of weeks, he expressed a sense a huge potential. It would also be naïve to think that he was unaware of the significant differences between his approach and underlying philosophy to that which commonly existed in education a decade before when the earlier tests had been conducted. For example, the idea of students speaking to each other carried little utility in an educational world governed by behaviorist dogma, but he encouraged it in his

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lectures, and it worked naturally because the short cords encouraged students to form groups. Interestingly, these groups tended to stay together lecture after lecture, even meeting to study together out of lectures. His questions, and those of his colleague (Professor Randy Caton) who taught a more advanced physics course using the system, covered a range of pedagogical purposes. For example, on introducing a new topic, he would often very carefully choose a question that had an obvious answer based on everyday nonphysicist thinking, but which was invalid. When over 90% of the class chose this answer and found out that they were all wrong, they suddenly became interested and were more than ready to listen to the first part of the lecture. Often, George would do an experiment in class, but ask a question before to have students predict the result. With the aid of unconventional props (on one occasion I recall a crash helmet & goggles) he would try to trick the class into making a wrong prediction. Such questions were intended to motivate and elicit exploratory initial thinking. Subsequent questions were designed to focus attention on specific processes, usually requiring solution of a problem. Next, larger conceptual issues would be addressed to test understanding of the necessary concepts, and the ability to generalize from a specific case to another area or general principle. One of the missing elements in this early work was the comparative measurements of student achievement. Attempts to do comparisons with student achievement from prior years were confounded by the fact that fewer students than before now dropped the course. It is my belief, though, that even if we had been able to obtain such data, doubt and skepticism would still have been a common reaction.

Roots of Doubt and Skepticism A few years ago, a celebrated set of sayings made the rounds on the Internet.6 These were interesting because they revealed misconceptions about

technologies which later became commonplace. These ideas were so thoroughly wrong, and often made by people who should obviously have known better, that today they provoke mirth. Yet, at the time when they were made, one can imagine newspaper reporters and informed readers nodded their heads seriously and accepting these supposedly wise opinions. In the mid-1980s, when I first became involved in prototyping and testing the first version of Classtalk, I received many comments about the dangers of a computer network in classrooms. With 1984 and George Orwell in people’s minds, “Big Brother” was a common appellation. This thinking came from the idea that teachers would use the power of a networked classroom system to constantly watch over, and perhaps to even intimidate and harass students. Although these comments were made by experienced educators, their predictions did not come true, and a few years on, after the classroom successes were becoming too obvious to refute, only one teacher to my knowledge had approached the Orwellian prediction. Before discussing this, it is appropriate to ask why the big brother prediction tends not to happen. Although it is an area where more research is needed, the answer appears to be that in most educational situations, aggressive surveillance poses penalties for the instructor in terms of student attitude, reduced student motivation, and unpleasant classroom atmosphere. These are strong disincentives and they seem to self-correct bad situations. The case of the early teacher—a psychology professor—probably explains it. For reasons best known to himself at the time, he forbad talking in his classes, and to enforce his rule, separated the 30 students out in all directions across the 200 seat lecture hall. Every class period, he asked a large number of factual recall questions and terminology definitions which the students were supposed to know. As a result, they hated the subject, the system, and him. For this unfortunate professor, the problem was self-correcting. Many students dropped his class early

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on, and those who remained gave him low evaluations at the end of the semester. The professor, whereupon, reported back that the system, “was not for him,” and discontinued its use. Much later, with coresearchers at the Ohio State University (Owens et al., 2004), in work with high school teachers and more advanced systems, we uncovered a more powerful explanation for the absence of Orwellian worlds in networked classrooms. That is, the data itself coming from the system appears to lead teachers to question their pedagogical strategies, and to discover better ways to teach. For example, a high school teacher reported: … when I first started using Navigator I thought it was kind of a self-contained device that would give what I needed … with myself in a bubble of just that technology. That’s where I was when I first started. … my perception was I could stand behind the desk, watch the answers coming in. Look at the teacher console and get what I needed and then look at the results of class and get what I need and give them what they need. Well, it didn’t turn out that way! …. I had very strict rules about not talking. … I didn’t want the answers or the results skewed. ... That has come full circle and now I want them to communicate because I think through communication with other students they’re going to get what they need or at least get closer to what they need. (Owens et al., 2004)

Need for a Workable System and Greater Visions In 1992, we were at a turning point. Two years earlier, I had terminated involvement with my NASA business, founded a new, education research company, and quickly received a National Science Foundation (NSF) Small Business Innovation Research (SBIR) Phase I grant for $50,000. This money was quickly used up in early research, and we had languished for a year while NSF tried to make up its mind over a much bigger “Phase II”

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grant. A Russian biophysicist7 (a recent émigré) was working full-time in my spare bedroom, a student programmer8 with my colleague Fred9 in his garage, and my other colleague, Milton,10 was prototyping the electronics in his attic. What we were trying to do was to build a next generation system, one that employed networking in a robust way, with handheld computers for students, and a flexible, easy-to-use interface for the teacher. We were painfully aware (from lengthy repair trips every couple of weeks to repair our Classtalk I system—mending wiring, replacing connectors, or diagnosing failed electronics), that classrooms are hostile environments, and the necessity for even occasional maintenance was unacceptable. Today, our goal of a class-wide computer network sounds simple, but it is easy to forget that this was still pre-Web, and wireless networking was a dream for anything other than high-cost space or military hardware. Some people said then, and others continued to say well into the ’90s, “Well just use hands!” by which they meant, “Why is a response system needed at all?” After all, the reasoning went, raising hands has been used in classrooms for centuries: mainly what was needed now was simply new pedagogy. However, there are two very good reasons why raising hands just does not work very well. First, students lack anonymity, so they tend to look around to see what everyone else is doing, and it is only the very brave who take a low, minority position. In some of my own (unpublished) research teaching at the University of Zimbabwe in 1991, I had gone to significant lengths in preparing packs of six color-coded cards that I handed out to each group of three students in a 75-person software engineering lecture course. When I asked a multiple-choice question, I would write it on the board and color code each option with a color corresponding to one in the packs of cards.11 At counting time, one student in each group would hold up a card, six students would count (one for each color), and from their totals, I could quickly draw a histogram on the board.

A Brief History of Networked Classrooms

All the backs of the cards were white so students could not see what others had chosen unless they turned around, but still I found that many would, and answers would coalesce around one or two options. With hand raising, the problem is much worse because hands are raised sequentially in groups for those favoring each option. The second reason arises from the fact that students are aware there is no record of their positions. So, either they do not respond at all to a question, or they respond without giving the issues much thought. This defeats the object of the process because from a cognitive science perspective, it is the thinking through the issues, establishing positions, and committing to them, that promotes learning. Although it took modern cognitive science to show why the process works, this profound insight into effective pedagogy goes back 2,400 years to Socrates and his teaching on the ancient Greek Agora. By the 1980s, two of the few places that this technique was used regularly in formal education were in the Oxford/Cambridge tutorial system in England, where a few students meet regularly with a professor in his or her study. The reason is obvious: it is extremely difficult to teach in a Socratic way in a classroom of 20 or more students and involve every student all the time. In July 1992, I had a call from Dr. Beverly Hunter at NSF who told me that they were going to remove our project from the small business program as there were severe doubts about its future commercial viability. However, because they believed that the research was important, they intended to transfer our proposal to the research division that normally funded university grants, and would award us twice the amount we had requested—half a million dollars—a lot of money at that time! This early research was very important, although the results were not published till later (Abrahamson, 1998, 1999, 2000), and it is worth describing briefly what they were. First, they showed the enormous pedagogical depth of questioning. Second, that the process of providing answers is generalizable, beyond questioning, to

a wide range of “tasks”. The implications from the conjunction of these results were important to design of the networked software and hardware required to facilitate them. For example, if a task is as simply structured as answering a multiple choice question, then a handheld unit may be very basic, with only as many keys as there are options on the question. On the other hand, a more open-ended question, a set of questions, or inputting homework, probably requires a screen and a full set of alphanumeric keys (or pen input with character recognition). It also needs a more powerful network, and more complex management and aggregation software on the teacher’s computer. It also assumes the ability for task activities to run asynchronously on the various student computers, so students can work through tasks at their own pace, instead of everyone in lockstep. If we take the concept of a task further, to say proving a theorem, executing a simulation, or participating in a learning game with all the students in the class, then local intelligence in a handheld is a necessity, as is the need for system programmability. Here, system programmability means the ability of a system to accept cooperating special-purpose programs that can execute simultaneously on the different computers in the system, but are designed to “know” how to communicate with each other, and be downloadable to handhelds with complimentary parts running on the teacher’s computer. Or, further at the next stage in system capability, the class would be dividable into large groups, with each group performing totally different tasks specifically designed for their learning needs—like remediation of a prerequisite concept-while others who have understood are not held back. Or, small groups working together, to produce a joint consensus answer. Or, a group interaction model of “consensus with dissent” like the U.S. Supreme Court, where a consensus answer is required, but individuals can dissent. To implement these elements of the vision, the software system would need to be able to create different environments at different handhelds

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within the same classroom. The key elements that would make this system dissimilar from standalone computing were that (a) task assignments would be controllable by the teacher, (b) student responses would be transmittable and available on the teacher’s computer, (c) these could be aggregated in pedagogically meaningful ways to permit quick assessment on a class-wide or groupwide basis, (d) private information and feedback would be kept private except at the discretion of the teacher, and (e) aggregated or anonymous collections of individual responses could be shown publicly. We also envisaged roles for two types of authoring: one by teachers taken from existing curricular materials, textbooks, and the like, that could with extreme ease be used with the system with or without the need to copy them into the system; and a raft of more complicated activities which could be programmed by curriculum specialists, companies, or other third-parties. In retrospect, the road ahead would have been much easier if this vision had never existed, but it did color choices for the next generations of systems that were collectively known as Classtalk II.

A Powerful Research Team and Technical Achievement With the new NSF grant, and a powerful group of 14 “expert collaborators”12 from around the USA, Classtalk II systems were developed and installed in lecture halls at five universities13 and two high schools,14 with small test systems at two additional universities.15 It turned out to be an appropriate time. Not only did each member of the research team have their own existing NSF research grants, they were all ready to use the system in their pedagogical research. With two exceptions, they were all physicists. One nonphysicist, Professor Mary Budd Rowe, a Stanford Professor of Education, deserves special mention. Her research in the 1960s on teachers’ questioning had produced interesting results (Rowe, 1974a, 1974b). She had found that while almost all teach-

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ers used questioning in their teaching, that this was sadly superficial from the cognitive point of view. In fact, her timing data showed that almost all teachers paused only long enough for students to access their short term memories. There was not even time for students to retrieve any information from their long-term memories, let alone process the information from a cognitive point of view. In other words, the questioning used by most teachers was useful only for short-term factual recall. Professor Rowe died in 1996, but we treasured her advice and support on this project. The other nonphysicist, Professor Jill Larkin, was a psychologist who had also worked in physics education, and performed widely quoted work on cognition and the differences between the learning of experts and novices (Larkin et al., 1980a, 1980b). The first generation of Classtalk II, developed with the new NSF grant funding, was a modern system and ahead of its time in some respects. It was built around three hardware elements: a Macintosh computer for the teacher, HP palmtop “PC” computers for students, and a special purpose modern network connecting them. All the test site systems (as listed above) were installed and up and running between January and August 1993. The old system at Christopher Newport was replaced first and used as a debug site; UMASS, Harvard, Ohio State, and Carnegie Mellon were next in that order. To give some feeling for the technical difficulty in February 1993, I will describe first use of the Harvard system. Starting on a Saturday with snow thick outside, our team of four PhDs, led by a satellite systems engineer, ran wires and installed network boxes and outlet jacks in the mammoth 500 seat lecture hall, drilling out blocked cable ports and crawling on the ground under the suspended, elevated, concrete floor. After a 12-hour work night Monday, the first class commenced on Tuesday morning with Eric Mazur teaching “RLC circuits” to 250 students. Most were pre-med, they were somewhat unenthusiastic about having to take two

A Brief History of Networked Classrooms

semesters of calculus-based physics, and being Harvard students, decidedly impatient with any experimentation using them as guinea pigs. I stood in the back of the hall as Fred Hartline ran the system and Eric lectured, quaking in my shoes at the thought of a bad system crash. But, the system worked flawlessly, the students loved it, and Eric’s pedagogy, which he had already been practicing with Scantron sheets, was masterful. Only later did I find out that the system had, in fact, crashed, but that as we had designed, Fred was able to automatically restart it and relog in all the students on their palmtops via software, without anyone ever knowing. As an interesting aside, during the system installation and first use, an elderly physicist on sabbatical from Cornell University came and encouraged us, telling of his success with a system he had built over 20 years before. It was Raphael Littauer!

Pedagogical Ferment, Research Results, and Further Barriers In May 1993, and again at the same time in spring 1994, our full research team met in Williamsburg Virginia to discuss pedagogy and results from their use of networked classrooms. There were three main results from these meetings. First, early student survey results from four sites—Harvard, University of Massachusetts (UMass), Ohio State, and Christopher Newport University (CNU)— were uniformly positive, and confirmed the prior data from George Webb’s work (Abrahamson, 1995, 1999, 2000). That is, the great majority of students believed they understood the subject better, came to class better prepared, paid more attention in classes, and enjoyed it more. They also thought that the professor had more insight into their points of difficulty with the subject matter. In addition, data at Harvard (Mazur, 1997) and Ohio State from pre/post-test data on the force concept inventory showed dramatic increases in student conceptual understanding over prior peda-

gogical techniques used by the same professors, and over standard lecturing by other professors in comparable courses (Hake, 1998). These results were complimented by qualitative research from the UMass group (Dufresne & Gerace, 1994; Dufresne, Gerace et al., 1996). Second, there were two, coherent, different pedagogical approaches described. One from Eric Mazur focused on “Peer Instruction” and formative assessment via “ConcepTests,” which he laid out as a seven step process in a seminal work (Mazur, 1997). Probably one of the reasons Mazur’s work has been so enormously influential in the field is because, in this publication, he spelled out in such detail what the pedagogy was, why it was designed as such, how he applied it, what the results were, and also crucially gave a library of all of his ConcepTests, so that it was easy for other physics teachers to begin using them. Also, as Mazur was an energetic, articulate, and charismatic spokesman for his work, he was invited to an untold number of speaking engagements at U.S. universities, conferences, and seminars around the world.16 Because of Mazur’s work, the term “ConcepTests” is now well known in education, and libraries of these have been developed for many additional physics courses, as well as numerous other disciplines, including chemistry, mathematics, biology, geology, astronomy, medicine, business, and economics, among others. An alternate approach developed by the UMASS group of Bill Gerace, Jose Mestre, Bob Dufresne, Bill Leonard, Laura Wenk, and Ian Beatty, was based on constructivist ideas and elicitative questioning, along with formative assessment, resulting in numerous publications (Dufresne & Gerace, 1994; Dufresne et al., 1996; Dufresne et al., 1996; Dufresne et al., 2003; Mestre et al., 2003; Beatty, 2004). This work was more comprehensive in its theoretical underpinnings than any that had come before it, and we shall return to some of the implications later. In the meantime, to return to 1994, at this point another more thoughtful objection was raised,

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namely that of “coverage.” That is, teachers, particularly university professors in the scientific and engineering disciplines, traditionally feel that they have to “cover” every part of their curriculum in lectures. And, curricula are crammed because they have expanded to fill all the available time. So, professors would say, “If I use lecture time to stop, question, and then act upon the information I get back from the students, I’ll never be able to cover the material.” Mazur gave the answer to this problem. He said that one has to step back and think what lectures are really for. He relates a little story where in the beginning, students complained that he went “too fast” in lectures, and there was no time to follow and copy down his notes. So, he had all his notes printed out and distributed to students so they would not have to slavishly copy from the overhead in lectures. Then he was criticized for lecturing, “straight out of his notes!” Then Mazur had a brain wave: perhaps he really was on the track of a bigger idea. After all, students (especially Harvard students) did not need him to read notes to them. They could read the notes themselves and do it before coming to a lecture. Then lectures could become places where students would have time to think, discuss, and best of all, understand. So, initially with Classtalk, he had students answer questions on the readings (notes, textbook, etc.) immediately at the beginning of each class, before he began lecturing. Later he did this over the Web, with a time window for students to answer that terminated a short while before class began. The final objection was perhaps the most honest and the most real. It was made by a professor at the University of Zimbabwe to whom I had given a system in 1987. My idea was that university faculty in a developing country would surely be under less pressure for research, publications, and career advancement, than their counterparts in developed countries. Thus, I reasoned, they might have more time to concentrate on teaching. A year after installing the system, I visited the

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university and was disappointed to learn that it had been used at one international conference, as well as for several presentations to various government officials and university administrators, but only two or three times for actual teaching. My friend, the professor, apologized, and being the honest, decent person he is (as well as being a great teacher), said, “Look, I tried, and I can’t teach like that. I’m in my fifties, I’m isolated here, I’m teaching advanced electronics. When I was at university they taught vacuum tubes! I have trouble staying two chapters ahead of the students in the textbook, and I just don’t have a broad enough overview of the material to teach like that!” These three major pedagogical objections, Orwellian, coverage, and limited teacher knowledge, far from being daunting, were actually very exciting. The first was made by those with the least insight, the second by university faculty who regarded the status quo of passive regurgitative lectures as acceptable pedagogy, and the third showed that the use of a response system practically mandated more competent teaching, as shown by the need for greater subject and pedagogical content knowledge. Better teaching was the goal from the beginning, and it is a valid contention yet to be proved in research that use of a response system (for those who stick with it) ends up teaching teachers both. That is, teachers who are prepared to admit in front of a class that they might not know something have a significant incentive to find out—which process cannot but lead to better subject knowledge. Also, as numerous teachers have reported, it is one thing to find out, from asking a question, that the majority do not understand. It is quite another to then summon up one’s best elucidation of the point in question, ask another question, and find the majority still do not understand. This process again cannot but help teachers from reflecting on their teaching, and motivating the seeking of better pedagogical content knowledge.

A Brief History of Networked Classrooms

Crossing the Chasm From an economic and developmental perspective, to anyone who has studied the adoption of new ideas, particularly ones that involve technology, it is obvious that there is a period, after initial successes, that ideas either succeed or fail. In his book, Moore (1999) refers to this period as, “crossing the chasm.” In the sober times of 1994, well before the dot-com bubble, I had only to have experienced a single system installation like that described earlier at the Harvard Science Center, with its attendant wiring, to realize that the cost of such a process would severely limit the potential of this technology for changing the way that people teach. Also, in addition to the technological hurdles of going wireless, there were those of market understanding of the pedagogy, and the real problems of quantitative research validating the approach at different educational levels, class sizes, student populations, and subject matters, combined with a huge need for curricular materials, and teacher professional development. So, with all these risks, it is little wonder that my attempts to obtain venture capital to make an economically viable system failed, and that in early 1995, I had to lay off 8 of our 11 employees. However, with the help of UMass and NSF, under difficult circumstances, we were able to take the next step of a semiviable “calculator-based” system. This was necessary, as Hewlett Packard had discontinued the palmtop PC that we had used in initial Classtalk II research, and their new model cost close to U.S. $700—far too expensive for students to purchase. We noticed, though, that math and science students did buy graphing calculators. I will not go into the technical issues of networking graphing calculators, save to say that these were significant, but that we were successful, and that over the next half-decade sold more than 100 systems. These systems were not as capable or as slick as the palmtop PC systems, but they worked, and provided a base for continuing pedagogical

development and growth in the core of pioneers who made this development possible. In December 1996, seeing little hope of obtaining the significant amount of technology development funding required, we sold exclusive rights for all our intellectual property (Abrahamson et al., 1989, 1990) to Texas Instruments (TI), the leading maker of graphing calculators in the US, and leading developer of digital signal processing chips for wireless communication worldwide. The catch was, though, that TI would not agree to promise to ever actually make a networked classroom system. So, the enterprise was stuck in a holding pattern with rapidly aging technology, but needing to support the pioneer teachers who were doing increasingly wonderful work with the systems in classrooms. The way out of the impasse came from a very unlikely source. In 1996, we had sold four Classtalk systems to the brand new Hong Kong University of Science and Technology. The head of the physics department there, Professor Nelson Cue, formerly a physics professor in the USA, who purchased and used the systems, saw the power and the limitations. He went to the Hong Kong government with a request for funding a truly commercially viable form of the technology, and his request was granted. Professor Cue also had contacts in the powerful Hong Kong manufacturing sector via a Harvard PhD physics alumnus, who was managing director of an electronics company,17 and a member of the university Board of Regents. Together they decided that Classtalk had been far too ambitious, and that the technology to support such an approach at that point in time, for an acceptable price, was simply not available. They reasoned that rather, if one was prepared to step back and use one-way pseudonetworking via mature and low-cost television remote control technology, then the goal could be accomplished. The key to their reasoning was the obvious problem of cost and maintenance associated with wires in lecture halls. Also, as we had found, hardwired

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systems were almost totally impractical in rooms with movable desks and chairs, which comprise almost all smaller classrooms. Infrared wireless technology solved a multitude of problems associated at that time with RF18 communication, such as interclassroom communication and battery life. Also, since the cost and power of computer projection technology had decreased rapidly by that time, the problem of one-way transmission, inherent in TV remote control technology, could be solved by making students check visually, on the overhead screen, to see if their response had been received by the teacher’s computer. They decided further to cut the cost of student handheld units by eliminating the screen (which would have been required for login), and building in a unique identifier into each handheld. In this way, each student would automatically be uniquely identified no matter where she or he was located in any classroom. This approach also mandated limiting question types to multiple-choice only. This last decision, while somewhat restricting pedagogy, meant that a student need only press a single button to respond to a question in class. Thus, a student could buy, own, and carry his or her unit to any classroom where a system was in use and the system would recognize it, and by inference, the student him or herself. In 1998, I traveled to Hong Kong to meet Professor Cue, and we agreed to work together on the “PRS,” as his system was called, which we did for the following two years. The PRS was an instant success, and immediately provoked imitators. The impact of Eric Mazur’s innovations and his increasing fame had spread, and produced a pent-up demand for costeffective systems. Today, almost all response systems sold worldwide are based on Professor Cue’s groundbreaking simplifications that produced the first, truly commercially viable response system that was also robust, reliable, and low-cost. There have also been notable other innovations. For example, the company eInstruction, based in Dallas,

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Texas, which sells a response system known as the CPS, has cut the price of a student response pad to barely a few dollars (apparently little above their cost), and also sells a Web-based service for which students pay an annual fee in the range of U.S. $12-15 that automatically provides class lists to professors, and updated class-participation grades for that student, with past class response histograms to students, over the company’s Web site.19 These innovations, taken together, mean that a university professor could begin using classroom network-based pedagogy with almost zero initial equipment cost. The costs for the pedagogical changes are significant, however, and we take up this issue in the next section.

Creating Effective Learning Environments In 1990, when, as a scientist, I decided to believe my own data, it seemed, even if it were only partially true, that we had stumbled onto something significant. However, my prior NASA work had done little to prepare me for understanding the true nature of what “it” was or how “it” worked. Thus, when I decided on a change of career, I did not know that the so-called “soft” sciences are actually harder than the “hard” sciences, and that the can-do attitude which flowered in NASA’s earlier days, breeding popular heroes, was a very different world than education, where low wages, lower prestige, and often stupefying management, bred teachers who were unsung, but also true heroes. Also, at the university level, professors who paid too much attention to their teaching (especially if it was at the expense of research) often paid dearly in their career advancement. The science behind what teachers do is really, really hard. It is hard to understand, hard to model from a scientific point of view, and hard to measure. Sometimes, as my wife recovered from breast cancer, or on trips, I would take a load of books, and return a month or two later with no

A Brief History of Networked Classrooms

more apparent understanding than when I had left. With one exception, however, I had, over the years, learned a lot from the UMass group, and Bill Gerace in particular, and when I confided to him my frustrations with the science of learning, he told me of a special blue ribbon committee that had been set up by the National Research Council (NRC) to review and summarize what was known about how people learn. His former student, an early Classtalk user, and now a well-known researcher, Professor Jose Mestre, happened to be serving on this committee. I contacted Jose, and he directed me to the just published book, authored by the committee, called, “How People Learn,” (HPL) (National Research Council, 1999). One small chapter in the middle of this book 20 hit me like a lightening bolt. In it, the NRC Committee on the Science of Learning went well beyond their charter of summarizing what was known about learning, and put it all together, applying it to describing what it took to create effective learning environments. These, they said, should be learner centered, knowledge centered, assessment centered, and community centered. Superficially, these terms may sound like jargon-filled platitudes, but when understanding the breadth and depth that the committee had covered in putting the ideas together, it was a remarkable achievement. Essentially, they had expressed 30 years of research in cognitive science, and synthesized it in the form of four overlapping ideas. For me, it put all the struggles I had had, to make sense of the field, neatly into perspective. Rather than repeat here what the committee said, I will take an extract from a paper with two high school teachers to explain how the four centerednesses play out in networked classrooms (Abrahamson, Davidian, & Lippai, 2000). That is, a networked classroom can help teachers to: 1.

understand the existing conceptions that students bring to a setting, and extend and make connections with students’ prior knowledge;

2.

3.

exert an appropriate amount of pressure on students to think through issues, establish positions, and commit to positions; focus on conceptual understanding, and reveal, diagnose, and remedy misconceptions.

Also, the technology can naturally facilitate formative assessment that: 4.

5.

gives feedback to students, and opportunities for them to reverse and improve the quality of their thinking and learning; stimulates a sense of community where class discussion, peer interaction, lack of embarrassment, and knowledge of class positions, creates the realization that others have the same difficulties, and opens the way to nonconfrontational competition, enthusiastic pride in class achievement, and perception that students and teacher are on the same side.

Thus, as shown in Figure 1, networked classrooms can assist teachers in creating learning environments that raise the level of all the four HPL centerednesses, and do it for all students.

Brief Overview of the Evidence It is highly tempting, at this point, given my new career status as quasi-neophyte educational researcher and cognitive scientist, for me to wish to plunge into summarizing past studies on response systems. And, to go wider and deeper, showing the links between the affordances of networked classrooms, and key results from the past 35 years of cognitive science research. But, the reviewers have restrained me, if only because such an exercise needs to be performed with due gravitas, which is not the nature of this chapter. Also, although much more work is needed, there are other papers in existence that partially cover this ground, and provide an entrée to relevant

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Figure 1. Aspects of the learning environment catalyzed by a networked classroom Aspects of Learning Environments Which are Catalyzed by Wireless Networked Graphing Calculators

1. Learner Centered

(transfer)

Questions, tasks, and activities to: • show existing conceptions that students bring to setting • extend and make connections with previous knowledge

3. Knowledge Centered Focus on: • conceptual understanding • reveal, diagnose, and remedy misconceptions

2. Learner Centered

(active engagement) Appropriate amount of pressure on students to: • think through the issues • establish positions • commit to positions

4. Assessment Centered Formative assessment naturally gives: • feedback to students provides opportunities to reverse and improve quality of thinking and learning • feedback to teacher gives cognizance of class positionsand window in student conceptions

5. Sense of Community Class discussion Lack of embarassment Peer iteraction Pride in class achievement Reasons for actionstaken Know others have same difficulties Knowledge of class positions Cheering and enthusiasm Same side as teacher Non-confrontational competition

bodies of literature. For example, with respect to summarizing other work, Roschelle, Penuel, and Abrahamson (2004) identified 26 studies in mathematics, chemistry, and the humanities reporting positive outcomes. These range from promoting greater student engagement (16 studies), increasing understanding of complex subject matter (11 studies), increasing interest and enjoyment of class (7 studies), promoting discussion and interactivity (6 studies), helping students gauge their own level of understanding (5 studies), teachers having better awareness of student difficulties (4 studies), extending material to be covered beyond class time (2 studies), improving quality of questions asked (1 study), and overcoming shyness (1 study). Also, another chapter in this present volume (Penuel, Abrahamson, & Roschelle, 2005) is specifically aimed at developing a theoretical structure to describe the diverse experiences of students and teachers in networked classrooms.

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There is a philosophical issue, in the nature of desirable future work, for which a comment may be appropriate. That is, from a human point of view, no matter the data or its source, if it is not what people expect, we tend to find reasons for dismissing it. Even in the hard sciences, unexpected results from another team’s work are suspect,21 and it is easy to see why it should be more so in sciences with more difficult experimental conditions. In education today, anything less than a randomized trial tends to be viewed as lacking definitive proof, and studies with this level of rigor clearly need to be done.22 But, in the meantime, going back to aerospace, if one factor was present along with the unexpected results, I found that more often than not, that they would be believed. That crucial factor was a clear and valid explanation of the mechanisms behind the results. And if these made sense, then the disbelief would vanish. So, ways to explain the results also need to be researched.

A Brief History of Networked Classrooms

For nonacademics, it may be simpler still! That is, for them, key indicators, such as the following quote, are already there, and tell it all. The quote comes from a high school math teacher,23 whose students had routinely broken all records at her school in attaining “fives” in AP Calculus BC, widely thought to be the most difficult course it is possible to take in a US high school. But, at this school, with this teacher, students think it is “easy.” The teacher, a prior Presidential Awardee, said, “… the data becomes addictive—after three years of using the system, it’s still teaching me how to be a better teacher!” So, the reasoning goes, if feedback can help a champion teacher grow for three years, then the likelihood exists that it could help less celebrated teachers improve even more.

Rather than describe the functionality of any particular system, I will describe some of my own favorite capabilities (bearing in mind that this list is far from exclusive). 1.

A Look to the Future Most audience response systems currently on the market are, in a sense, single function, being designed to provide quick student responses to multiple-choice questioning, which are automatically aggregated and anonymously displayed. Networked classrooms are potentially capable of doing much more than this. I believe that the present genre of systems is, but the first technological and pedagogical stepping-stone towards a future that will encompass tools that are vastly more powerful and flexible. I indicated before, in this chapter, how visions for such advanced systems have existed since early research with Classtalk I. Finally, now, a decade and a half later, we are beginning to see commercially available production systems that embody this functionality.24 Also, the research domain is vibrant with advanced systems under development at the following universities in the USA: Vanderbilt, the University of Illinois at Champagne-Urbanna, Harvard, University of Massachusetts, and the University of Texas at El Paso, as well as in Germany, Chile, and Taiwan.



Open ended questions and activities. Although multiple-choice is a powerful questioning tool capable of great subtlety and fine distinctions, it is limited by the preconceptions of the questioner or question preparer. These can tend to lead student thinking patterns, or worse, force a choice that does not represent what a student really thinks. Unless reasoning can be explored, the results may be less than meaningful. Aggregating answers in a pedagogically meaningful way is, of course, the central difficulty in open-ended questioning, and space here does not permit a complete discussion of the problem. However, one example from Roschelle, Penuel, and Abrahamson (2004b) shows that creative solutions are not only possible, but can work very well in classrooms. “A glimpse at an 8th grade algebra lesson that Hegedus and Kaput designed shows why these researchers are enthusiastic. After asking each student to ‘count off’ different numbers, the teacher poses a mathematical challenge that varies according to the countoff number. Students work on separate and slightly different challenges. This lesson’s challenge is to create a function whose graph starts at the student’s given number and goes through the point (6, 12). Using a calculator, each student specifies a mathematical function. Using the classroom network, the teacher rapidly “harvests” all the solutions to display on a projector. The students now see their work on a shared screen, which leads to passionate discussion about the functions they created. The teacher can guide the students in investigating new structures

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that appear in the aggregated set of lines, such as the varying slopes of the lines. The graphed functions can also control a motion animation on both the students’ units and the classroom display. Each student’s function thus becomes part of a mathematical model of a race, dance, or parade. Hegedus and Kaput (2003) reveal strong improvements for 7th, 8th, and 9th grade students on items found in state achievement tests. Jim Kaput and co-investigator Stephen Hegedus are excited about more than just the improvement in test scores: Classrooms that integrate dynamic software environments with connectivity can dramatically enhance students’ engagement with core mathematics beyond what we thought possible.” Of course, the activity described above was used in a small classroom, and would obviously not work well in a lecture hall with 300 students. This brings up a crucial point. Twenty years ago, I thought that lecture hall use of a networked classroom system was bound to be more incrementally beneficial than a smaller classroom of say 20 to 30 students. In times before Classtalk II and the beginnings of research in smaller classrooms, almost everyone working in the field would have shared my opinion. Indeed, many would have said that the use of a system in a class of 5 to 10 students was unnecessary, if not inappropriate. I have since changed my opinion completely, and have come to believe that in spite of the enormous improvement possible in large lecture halls, the potential benefits are even greater in smaller classrooms, including those down at the latter range previously considered marginal. This is probably a topic for another volume, because most of the research in smaller classrooms has been conducted at the primary and secondary educational levels, and some of it has also

2.



been with more advanced systems. Nevertheless, one point causing pedagogical differences between small and large classrooms needs to be made here. That is, acoustics. In most lecture halls, the professor wears a cordless microphone, without which he or she would not be heard. Questions are usually not directed to students unless the professor has runners with second, third, or more microphones, something usually only seen at special events, invited lectures, or conferences. This inability to easily communicate by voice imposes severe restrictions on feasible pedagogical strategies, which is why Eric Mazur’s innovation, “Please take a minute, turn to your neighbors, and convince them of your answer!” is such a powerful and popular stratagem for this environment.25 Sharing data. Particularly in the sciences and mathematics, introduction of real world data is an important pedagogical tool, as seen in the following example involving linear and exponential functions from Abrahamson et al. (2000). “In another pre-calculus class we (Davidian & Lippai) had students address an example of the 19th century Malthus Problem comparing exponential population growth with linearly increasing food supply. Students were asked to predict if and when food shortages would occur and how these predictions would change with increased rate (but still linear) of food supply. After seeing the histograms of class predictions, students performed the actual calculations and compared graphs on their calculators. The dramatic power of exponentially increasing quantities over linear was heightened because few had predicted the effect.” These calculations were then used as the basis for discussing actual, real, population growth data downloaded to students over the classroom network from the Internet.

A Brief History of Networked Classrooms

3.



Homework. At the university level, Webbased homework systems have become widely used.26 Time spent out of class, either alone or with other students working in groups, is important because it involves working through issues associated with knowledge currently being addressed in the course. From a cognitive science perspective, the process of thinking, testing, and applying processes and ideas is valuable to learning (Cooper, & Lindsay, 1998). It is also a natural opportunity in which to exercise appropriate formative assessment. Web-based systems do enable such processes, and are certainly cost-effective for huge, introductory university courses when compared with manual grading, but they are also, perhaps, more automated than desirable, focusing almost exclusively on the “right” answer. They can also encourage students to share answers, although many systems now randomize input variables so that every student receives a unique problem. The idea is that students will then discuss processes and reasoning between themselves, rather than answers. Another approach is to use a classroom network and have students input answers to select questions at the beginning of class, as described, for example, in Abrahamson (1998). “Jan Andrews is an 8th grade math teacher. Students push to get into her class to enter their homework on a networked calculator. Jan uses a free-form five-question skeleton set for collecting homework. Every day she identifies five of the previous night’s homework problems on the board. She uses a free text binning because of its simplicity and manually checks exceptions as they come in. Five minutes after the start of class she knows who did their homework, who had problems, & what these are. She will deal with them before moving onto new material.”



4.

5.

For effective, formative assessment, this approach is probably superior to an automated system, but is limited to smaller classes. Although at middle and high school levels, teachers may typically teach as many as 150 students spread over five classes, this method can easily be done at the beginning of every one. Projects, labs, and extended activities. Projects are known to be an extremely effective way to teach (Norman & Schmidt, 1992; Polman & Pea, 1997; Thomas, 1998), but they are also difficult for a teacher to track. That is, some groups may progress rapidly while others languish in unproductive activity. Networks classrooms can be used to track activities and allow a teacher to spot problematic situations, in a timely fashion, through the simple device of an extended activity with responses, answers, conjectures, models, data, or other work products required to be “turned-in” over the network at predetermined stages. Participatory simulations and games. These are very important categories of activities for experiential learning, and add excitement and motivational elements to a classroom. Leading examples of work in this area have been developed under NSF funding by Wilensky and Stroup (2000, 2002) and are known as “Participatory Simulations,” where each member of the entire class participates actively in controlling some aspect of a simulation. For example, using a TI-Navigator in a participatory simulation such as “Disease,” developed as part of the NetLogo project (Wilensky, 1999). The “Disease” model simulates the spread of a disease through a population that consists of on-screen icons (turtles) controlled by individual students using the arrow buttons on their calculator via the TI-Navigator network. Turtles move around a space represented on screen by a grid of patches, possibly catching an infec-

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tion, with a probability determined by the teacher. Sick turtles make patches they land on infectious for a time, during which healthy turtles on the patch have a certain chance of becoming ill. A plot shows the number of infected turtles over time, and there is the option of sick turtles flashing to show that they are infected, or keeping turtles’ state of health hidden from public view. As Owens et al. (2004) note, no matter how the various parameters (chance of infection, initial number of infected turtles, sickness public or hidden) are changed, the same basic plot shape (a logistics curve) emerges. Among the benefits of this sort of activity are (a) an experiential learning experience for students, (b) a cooperative learning experience for students, (c) a physical and visual connection that students can make to mathematical objects such as graphs. Another example from Wilensky and Stroup’s work (2000, 2002) is known as “Gridlock.” The activity relates to an inner-city traffic-light network in the “City of Gridlock.” The Mayor of the city has a terrible problem with traffic flow, and the class has to try to solve it for him. Each student controls one traffic light shown on the computer projection of the inner-city roads, and the class, beginning with trial and error, has ultimately to figure out the algorithm that will get the simulated traffic flowing smoothly. Owens et al. (2004) report the following interview with a teacher that used this activity in her classroom. She began by explaining that she had seen roomfuls of PhDs having significant difficulty with this problem. But, her graduating AP calculus class was different, and exhibited a cohesion that solved the problem more easily than their elevated superiors. Davidian: I said, after the AP [exam] we’re gonna do another fun one, so we did “Gridlock,” and it was just amazing. I’ve seen “Gridlock” done. … I’ve participated in “Gridlock” at confer-

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ences with strangers and it was a disaster, with everybody crashing into everybody, etc. etc.. And, it was interesting in my class because it was all, … they talked to each other, and they listened to each other, and that’s come from having done this all year long, and Navigator has done that, in the way I explained it before, but it’s followed through in even fun activities. So, the class has become a community and it’s established itself and it’s not dependent on anything other than now with, “That’s just the way they are!” According to this teacher’s description, the key to her class’s success in this type of competitive situation seems to have been due to their ability to work together as a team. She also states that, in her opinion, this ability was due to their experience, over the class year, with TI-Navigator. This model of class collaboration is an interesting result, given the fact that the nation’s high schools are often divided many ways in exclusionary cliques and groups. This example is important because it illustrates some of the less obvious benefits of networked classrooms, and how they help learning. For example, the teacher’s perspective was that her class engaged in learning as a “community.” In a later chapter in this volume, Penuel et al. (2005) discuss such effects from a sociocultural perspective, and provide a theoretical explanation as to why they occur. Lastly, I would like to state my belief that an awareness of what is possible is now springing out of experience with today’s simple systems. That is, new, advanced systems will not be created simply because technology continually marches forward. Rather, they will come from increasingly sophisticated pedagogical needs. These new systems will be more capable, and promise additional flexibility over current products, and will also be easier to use. Teaching requires a remarkable degree of multiprocessing. Not only does a teacher have to think of the subject matter and how to teach it, but it is also necessary to

A Brief History of Networked Classrooms

have an image of what is happening “in all those heads” out there in the classroom. Add to that working a computer, interpreting screens and data, keeping order, making frequent eye contact, and the workload is arguably akin to a pilot landing a large, passenger jet aircraft. But, computer technology has made even this easier than it used to be. A couple of years ago (before 9-11), I was privileged to be in the cockpit of a brand new, fully loaded Boeing 747-400 with “all glass” instrumentation displays. We were approaching New York’s Kennedy Airport on autopilot, and it was a beautiful, clear winter morning, with the World Trade Towers rising to our left. A message came from the control tower at Kennedy, changing the runway on which we were to land. The pilot broke his conversation in midsentence, punched in the number “6,” and resumed talking where he had left off, looking back to the rear of the cockpit. The huge plane banked, turned, and executed an S-maneuver. One which, I am sure, none of the passengers realized our pilot was not physically handling the controls to execute. Just before touching down, the pilot took the controls to land the giant plane. I gave this example not because I think the classroom will become more automated, but rather because a teacher needs sophisticated tools, just as an airline pilot, so their precious cargo will arrive safely at the immediate academic destination on their various life journeys.

Conclusion This chapter had four objectives: firstly, to explain the current excitement surrounding response systems and networked classrooms today; secondly, to set this description in historical context from the personal perspective of the author; thirdly, to delineate the tantalizing nature of the effects of these tools on teaching and learning, and how

they augur for additional research; and fourthly, to describe the emerging characteristics of, and rationale for, more powerful types of modern systems. The reader will judge if these goals have been satisfied, but at least it is hoped that the chapter will prove useful, as gaining an overview of this field is not easy. Publications are scattered through a variety of journals and across several disciplines. In many cases they exist only in the form of conference presentations or publications with limited accessibility. Finally, it has been difficult to write this chapter without occasional reference to contemporaneous efforts at primary and secondary educational levels. For this the author apologizes. From another perspective, though, it is encouraging because it shows that far from being a “university only” or “lecture hall only” tool, response systems are being found useful at all segments of the educational spectrum. Thus, it is my personal hope that this edited book will not exist in isolation, but that it will be the first of a series of volumes that will deal with additional parts of the educational spectrum.

Acknowledgment It can be seen from reading this chapter that many people have been mentioned as participating in the development of networked classrooms and associated pedagogical techniques. There are also a great many others who played crucial roles and contributed key ideas, but because of space limitations, as well as the focus of this volume, have not been mentioned. To all of you, I humbly offer my personal thanks, and take the liberty of also hereby thanking you on behalf of all those who have benefited, are benefiting, and will benefit, from better educational experiences associated with networked classrooms.

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References Abrahamson, A. L. (1995). Classtalk: A 21st Century tool for teachers - An ancient concept in teaching (videotape). Yorktown, VA, Better Education Inc. Abrahamson, A. L. (1998, June 3-6). An overview of teaching and learning research with classroom communication systems (CCSs). Paper presented at Samos International Conference on the Teaching of Mathematics, Village of Pythagorion, Samos, Greece. New York: John Wiley & Sons. Abrahamson, A. L. (1999). Teaching with a classroom communication system - What it involves and why it works. Minicourse presented at VII Taller Internacional, Nuevas Tendencias en la Ensenanza de la Fisica, Benemerita Universidad Autonoma de Peubla, Puebla, Mexico. Abrahamson, A. L. (2000). A brief history of Classtalk. Presented at Teachers Teaching with Teachnology (T-Cubed). International Conference, Dallas, Texas. Abrahamson, L., Davidian, A., Lippai, A. (2000). Wireless calculator networks - why they work, where they came from, and where they’re going. Paper presented at the 13th Annual International Conference on Technology in Collegiate Mathematics, Atlanta, Georgia. Abrahamson, A. L., Hartline, F. F., Fabert, M. G., Robson, M. J., & Knapp, R. J. (1989). An electronic classroom enabling self-paced interactive learning. Washington, DC, United States Patent Number 5,002,491. Abrahamson, A. L., Hartline, F. F., Fabert, M. G., Robson, M. J., Knapp, & R. J. (1990). An electronic classroom enabling selfpaced interactive learning. Brussles, Belgium, European Patent Number 90 304 587.0. Bapst, J. J. (1971). The effect of systematic student response upon teaching behavior. Unpublished

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doctoral dissertation, University of Washington, Seattle. (ERIC Document Reproduction Service No. ED060651). Beatty, I. D. (2004). Transforming student learning with classroom communication systems (ERB0403). Educause Center for Applied Research (ECAR) Research Bulletin, Issue 3, Boulder, Colorado. Bessler, W. C. (1969). The effectiveness of an electronic student response system in teaching biology to the non-major utilizing nine grouppaced, linear programs. Muncie, IN, Ball State University. Bessler, W. C., & Nisbet, J. J. (1971). The use of an electronic response system in teaching biology. Science Education, 3, 275-284. Brown, J. D. (1972). An evaluation of the Spitz student response system in teaching a course in logical and mathematical concepts. Journal of Experimental Education, 40(3), 12-20. Casanova, J. (1971). An instructional experiment in organic chemistry, the use of a student response system. Journal of Chemical Education, 48(7), 453-455. Cooper, H., Lindsay, J. J., Greathouse, S., & Nye, B. (1998). Relationships among attitudes about howmework, amount of homework assigned and completed, and student achievement. Journal of Educational Psychology, 90(1). Dufresne, B., & Gerace, B. (1994). Using “extended scenario” to enhance learning during interactive lectures. Retrieved March 25, 2003, from UMass Physics Education Research Group Web site. Dufresne, R. J., Gerace, W. J., Leonard, W. J., Mestre, J. P., & Wenk, L. (1996). Classtalk: A classroom communication system for active learning. Journal of Computing in Higher Education, 7(2), 3-47.

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Dufresne, B., Gerace, B., Leonard, B., Mestre, J., & Wenk, L. (1996). Using the Classtalk classroom communication system for promoting active learning in large lectures. Journal of Computing in Higher Education, Edited volume - Studentactive science: Models of innovation in college science teaching. Dufresne, B., Gerace, B., Leonard, B., Mestre, J., & Wenk, L. (2003). Using a classroom communication system for promoting active learning in large lectures. Journal of Computing in Higher Education, (March). Garg, D.P. (1975). Experiments with a computerized response system: A favorable experience. Paper presented at the Conference on Computers in the Undergraduate Curricula, Fort Worth, TX. (ERIC Document Reproduction Service No. ED111355). Hake, R. R. (1998). Interactive-engagement versus traditional methods. American Journal of Physics 66, 64-74. Hegedus, S., & Kaput, J. (2003, July). The effect of a Simcalc Connected Classrooms on students’ algebraic thinking. Paper presented at the the 27th Conference of the International Group for the Psychology of Mathematics Education held jointly with the 25th Conference of the North American Chapter of the International Group for the Psychology of Mathematics EducationPsychology in Mathematics Education, Honolulu, Hawaii: College of Education, University of Hawaii.

Larkin, J. H., McDermott, J., Simon, D. P., & Simon, H. A. (1980b). Models of competence in solving physics problems. Cognitive Science, 4, 317-349. Linn, M. C. (2004). (Personal Communication). Littauer, R. (1972). Instructional implications of a low-cost electronic student response system. Educational Technology: Teacher and Technology Supplement, 12(10), 69-71. Mazur, E. (1997). Peer instruction: A user’s manual. Upper Saddle River, NJ: Prentice Hall. Meltzer, D. E., & Manivannan, K. (1996). The Physics Teacher, 34, 72. Mestre, J. P., Gerace, W. J., Dufresne, R. J., & Leonard, W. J. (2003). Promoting active learning in large classes using a classroom communication system. Retrieved March 12, 2003, from http://www.psrc-online.org/classrooms/papers/ mestre.html Moore, G. A. (2002). Crossing the chasm: Marketing and selling high-tech products to mainstream customers (revised ed.). New York: HarperCollins Publishers. National Research Council (1999). How people learn: Brain, mind, experience. Washington, D.C., National Academy Press. Norman, G. & Schmidt, H. (1992). The psychological basis of problem-based learning: A review of the evidence. Academic Medicine, 6, 557-565.

Judson, E., & Sawada, D. (2002). Learning from past and present: Electronic response systems in college lecture halls. Journal of Computers in Mathematics and Science Teaching, 21(2), 167-181.

Owens , D. T., Demana , F. A., Louis, A., Meagher, M., & Herman, M. (2004). Developing edagogy for wireless handheld computer networks and researching teacher professional development (ED479499). Washington, DC: ERIC, 137.

Larkin, J., McDermott, J., Simon, D. P., & Simon, H. A. (1980a). Expert and novice performance in solving physics problems. Science, 208, 13351342.

Penuel, W. R., Abrahamson, A. L., &Roschelle, J. (2005). Theorizing the transformed classroom: A sociocultural interpretation of the effects of audience response systems in higher education.

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Audience response systems in higher education: Applications and cases. D. A. Banks. This Volume. Polman, J., & Pea, R. D. (1997). Transformative communication in project science learning discourse (ERIC ED407283). Paper presented at the Annual Meeting of the American Educational Research Association, Chicago. Roschelle, J., Penuel, W. R., & Abrahamson, L. (2004). Classroom response and communication systems: Research review and theory. Paper presented at the American Educational Research Association 2004 Annual Meeting, San Diego, CA.

Endnotes

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Roschelle, J., Penuel, W. R., & Abrahamson, L. (2004b). The networked classroom. Educational Leadership, 61(5), 50-54. Rowe, M. B. (1974a). Wait-time and rewards as instructional variables, their influence on language, logic and fate control: Part I, Fate control. Journal of Research in Science Teaching, 11, 81-94. Rowe, M. B. (1974b). Relation of wait-time and rewards to the development of language, logic, and fate control: Part II, Rewards. Journal of Research in Science Teaching, 11, 291-308. Thomas, J. W. (1998). An overview of projectbased learning. Novato, CA, Buck Institute for Education. Wilensky, U. (1999). NetLogo. Evanston, IL: Center for Connected Learning and Computer-Based Modeling, Northwestern University. Retrieved from http://ccl.northwestern.edu/netlogo Wilensky, U., & Stroup, W. M. (2002). Participatory simulations: Envisioning the networked classroom as a way to support systems learning for all. Annual Meeting of the American Educational Research Association, New Orleans, LA.

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TI, ETS, Promethean, SiliconChalk, eInstruction, GTO-Calcomp, LearnStar, LearnTrac, Renaissance, SynchronEyes, Quizdom, H-ITT The premier institution in the Texas university system —which had included research work on Concorde, Space Shuttle, and Space Station in the fields of acoustics, structural dynamics, heat transfer, and psycho-physics— CPFF: “Cost Plus Fixed Fee” In Newport News, Virginia “I think there is a world market for about five computers.” ~ Thomas J Watson, founder of IBM speaking about the possible future needs of computers.



“Nothing can come along that will beat the horse and buggy.” ~ Chauncey DePew, President of the New York Central Railroad, warning his nephew about investing in Henry Ford’s new company.



“This ‘telephone’ has too many shortcomings to be seriously considered as a means of communication. The device is inherently of no value to us.” ~ Western Union memo, 1877



“There is no reason anyone would want a computer in their home.” ~ Ken Olson, president, chairman and founder of Digital Equipment Corp., 1977



“The wireless music box has no imaginable commercial value. Who would pay for a message sent to nobody in particular?” ~ David Sarnoff’s associates in response to his urgings for investment in the radio in the 1920s.

A Brief History of Networked Classrooms



“Who the hell wants to hear actors talk?” ~ H.M. Warner, Warner Brothers, 1927.



“Heavier-than-air flying machines are impossible.” ~ Lord Kelvin, president, Royal Society, 1895.



“Mr. Bell, after careful consideration of your invention, while it is a very interesting novelty, we have come to the conclusion that it has no commercial possibilities.” ~ J. P. Morgan’s comments on behalf of the officials and engineers of Western Union after a demonstration of the telephone.

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“That is the biggest fool thing we have ever done ... the [atom] bomb will never go off, and I speak as an expert in explosives.” ~ Admiral William Leahy to President Truman (1945)



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“Even if the propeller had the power of propelling a vessel, it would be found altogether useless in practice, because the power being applied in the stern, it would be absolutely impossible to make the vessel steer.” ~ Sir William Symonds, Surveyor of the British Navy (1837)





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Dr. Lev Tannen Robert Knapp Dr. Fred Hartline Milton Fabert Others trying a similar approach later included Mazur Mazur, E. (1997). Peer Instruction: A User’s Manual. Upper Saddle River, NJ, Prentice Hall., and Meltzer (Meltzer, D. E. and K. Manivannan (1996). The Physics Teacher 34: 72.) George and Jane Webb (CNU); Bill Gerace, Jose Mestre, Bob Dufresne, and Bill Leonard (Univ. of Massachusetts); Eric Mazur

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(Harvard Univ.); Fred Reif and Jill Larkin (Carnegie Mellon Univ.); Allan VanHeuvelen (The Ohio State Univ.); Mary Budd Rowe (Stanford Univ.); Jim Minstrell (Mercer Island HS); David Hestenes, and Malcom Wells, (Arizona State Univ.), and Gregg Swackhamer (Glenbrook North HS); Harvard (250 students), Univ. of Mass. Amherst (100 students and 300 students), Christ. Newport Univ. (200 students), Ohio State (250 students), Carnegie Mellon (200 students) Mercer Island (Seattle), Glenbrook North (Chicago) both 30 student classrooms Stanford Univ. and Arizona State. Amazingly, at the same time as conducting groundbreaking pedagogical work, he also continued to head a large physics research team at Harvard with a number of doctoral students. Varitronics RF: Radio frequency electromagnetic waves The concept of providing and charging for such a service was pioneered by Marty Abrahamson, my son, who works for eInstruction. Chapter XIII For example, in aerospace, perhaps their calibrations were off, instrumentation bad, sensors in wrong places, sloppy environmental control, and so forth. I am currently involved in just such a randomized assignment study of student achievement in algebra and physical science involving 130 teachers, funded by the U.S. Dept. of Education- Institute of Education Sciences, “Classroom Connectivity in Promoting Mathematics and Science Achievement,” and begun June 1, 2005. Participants include The Ohio State University, The Better Education Foundation,

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CRESST—Univ. of California Los Angeles, and Texas Instruments. Ann Davidian, MacArthur High School, Levittown, N.Y. For example the just released TI-Navigator 2.0.

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Also, Eric does make use of voice feedback because he turns his microphone off and walks close to groups where he can overhear their discussions. For example, WebAssign, Blackboard, etc.

This work was previously published in Audience Response Systems in Higher Education: Applications and Cases, edited by D.A. Banks, pp. 1-25, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 1.10

Patterns in Electronic Brainstorming Alan R. Dennis Indiana University, USA

Brent Gallupe Queen’s University, Canada

Alain Pinsonneault McGill University, Canada

Mark Huber University of Georgia, USA

Kelly McNamara Hilmer University of Tampa, USA

François Bellavance HEC Montréal, Canada

Henri Barki HEC Montréal, Canada

ABSTRACT Research has shown that some groups using electronic brainstorming generate more unique ideas than groups using nominal group brainstorming, while others do not. This study examined two factors through which group size may affect brainstorming performance: synergy and social loafing. Groups brainstormed using three techniques to manipulate synergy and two group sizes to manipulate social loafing. We found no social

loafing effects. We found a time effect: nominal brainstorming groups that received no synergy from the ideas of others produced more ideas than electronic groups in the first time period and fewer ideas in the last time period. We conclude that synergy from the ideas of others is only important when groups brainstorm for longer time period. We also conclude that electronic brainstorming groups should be given at least 30 minutes to work on tasks, or else they will be unlikely to develop synergy.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Patterns in Electronic Brainstorming

INTRODUCTION The idea of using brainstorming has been around for almost 50 years (Osborn, 1957). Yet, traditional group brainstorming, where group members verbally share their ideas, has not been found to be a very productive idea generation technique when compared to other brainstorming techniques (Mullen, Johnson, & Salas, 1991). A controversy has surfaced recently regarding two other forms of brainstorming—nominal group brainstorming and electronic brainstorming1. Both of these techniques have been found to be more productive than traditional verbal brainstorming, but the question remains as to which one is more productive—nominal or electronic brainstorming. Some studies in the early 1990s found that electronic groups generated more ideas than nominal groups (Dennis & Valacich, 1993; Valacich, Dennis, & Connolly, 1994), but a recent study has cast doubt on these findings and has claimed that the productivity of electronic brainstorming may be an illusion (Pinsonneault et al., 1999a). This is the subject of debate, with some researchers arguing that group size plays an important role: large electronic groups outperform large nominal groups, but small nominal groups outperform small electronic groups (Dennis & Valacich, 1999; Pinsonneault et al., 1999b). The purpose of this paper is to investigate two underlying theoretical factors that may influence the relative productivity of small and large nominal and electronic brainstorming groups: synergy and social loafing. Large electronic brainstorming groups may experience more synergy (and thus produce more ideas) than small groups on a perperson basis, because they have more potential sources of synergy. However, these same large brainstorming groups also may experience more social loafing (and thus produce fewer ideas) than small groups on a per-person basis, because members are more likely to perceive their contributions as less needed. In this paper, we attempt

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to separate these competing factors in order to better understand how group size may affect brainstorming performance.

PREVIOUS RESEARCH Group creativity and brainstorming have long been the subject of academic research. The general conclusion of this body of research is that people generate fewer ideas when they work together in verbally interacting groups than when they work in nominal groups (i.e., when they work separately and later pool their ideas) (Mullen et al., 1991; Paulus, Larey, & Ortega, 1995). Reasons for this are due mainly to production blocking and evaluation apprehension that prevail in verbal communication but do not exist in nominal groups. Production blocking refers to the need to take turns speaking in verbal communication (Diehl & Stroebe, 1987). When participants are prevented from contributing an idea when they first think of it, they may forget it or suppress it, because later, the idea seems less relevant or original. If they try to retain the idea, they must focus on remembering it, which prevents them from generating new ideas or attending to the ideas of others (Diehl & Stroebe, 1991). Evaluation apprehension may cause participants in verbal brainstorming to withhold ideas, because they fear a negative reaction from others (Diehl & Stroebe, 1987; Lamm & Trommsdorff, 1973). Over the last decade, a new form of brainstorming—electronic brainstorming—has emerged. With electronic brainstorming, participants interact via computers. They type their ideas into their computers simultaneously. These ideas are shared via the computers by allowing each member to read on their computer screen the ideas others in the group have generated. Electronic brainstorming does not improve the productivity of small groups but may improve the productivity of large groups (Dennis & Valacich, 1999).

Patterns in Electronic Brainstorming

There have been conflicting results in comparing nominal brainstorming to electronic brainstorming (Pinsonneault et al., 1999a). Much of the prior electronic brainstorming research has been guided by the process gains and losses framework (Steiner, 1972; Hill, 1982). Simply put, communication among group members introduces factors into the brainstorming process that improve performance (process gains) and factors that impair performance (process losses) relative to group members who work separately without communicating but later pool ideas (nominal groups). Several dozen plausible sources of process losses and gains in verbal and electronic brainstorming have been proposed (Camacho & Paulus, 1995; Mullen et al., 1991; Pinsonneault et al., 1999a). The traditionally important process losses of production blocking and evaluation apprehension essentially have been eliminated in electronic brainstorming, because participants need not wait to contribute ideas, and ideas can be contributed anonymously. Nominal groups do not exhibit these losses (Pinsonneault et al., 1999a). Three key differences between electronic brainstorming and nominal group brainstorming that have the potential to change with group size are synergy (a potential process gain), cognitive interference (a potential process loss), and social loafing (another potential loss) (Dennis & Valacich, 1999; Pinsonneault et al., 1999a, 1999b).

Synergy and Cognitive Interference Synergy is the ability of an idea from one participant to trigger a new idea in another participant —an idea that otherwise would not have been produced (Dennis & Valacich, 1993; Lamm & Trommsdorff, 1973). Synergy—or the assembly bonus—is perhaps the most fundamental potential source of process gains. Synergy is caused by the ideas that group members exchange. Osborn’s (1957) advice to piggyback on the ideas of others strives to increase the synergy that participants

derive by building on the ideas of others. Ideas from others can serve both to stimulate ideas within one category or line of thought and to provide additional topic categories that otherwise would have been overlooked (Paulus, 2000). That is, the ideas of others can stimulate both idea fluency and idea flexibility (Guilford, 1975). Synergy is likely to increase as participants are exposed to more ideas, because there are more sources from which to draw inspiration in triggering a new idea (up to some limit, beyond which more ideas simply create information overload) (Dennis & Valacich, 1993; Gallupe, Dennis, Cooper, Valacich, Bastianutti, & Nunamaker, 1992; Valacich, Dennis, & Connolly, 1994). Thus, as the number of ideas a participant receives increases, so too should the number of ideas a participant generates (again, up to some limit) (Dennis & Valacich, 1999). As group size increases, the number of ideas that participants receive from others should increase, and thus, synergy should increase, which is why large electronic brainstorming groups generally have produced more ideas than small electronic brainstorming groups (Dennis & Valacich, 1993; Dennis & Williams, 2005). Because nominal groups are unable to draw on the ideas of others, they experience no synergy and, thus, produce fewer ideas than large electronic brainstorming groups. This argument rests on the presumption that the ideas received by a participant can be used by that participant to trigger new ideas. That is, synergy is only possible if the ideas received from others have some value and simply do not repeat ideas that a participant already has considered. If ideas repeat ideas already considered, they have little potential to induce synergy. Likewise, if the participant is capable of generating ideas with no external stimulation, there is little value to be gained from synergy. That is, synergy only increases the number of ideas produced, if the participant has run out of ideas and cannot generate more without help. If participants

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are capable of producing ideas for the length of time available by themselves, receiving ideas from others will not result in more ideas. In fact, this actually may decrease the number of ideas produced due to cognitive interference. Cognitive interference is in many ways the inverse of synergy. Cognitive interference occurs when ideas generated by other participants interfere with an individual’s idea generation activities (Pinsonneault et al., 1999a; Straus, 1996). Attention must be diverted away from the generation of ideas to the understanding of ideas from other group members, and thus, fewer attention resources are devoted to producing ideas. Cognitive interference also may be due to the content of the ideas contributed by others, because ideas from others serve to stimulate cognitive activity in one area while limiting the flexibility of idea production in others (Nijstad, Diehl, & Stroebe, 2003). That is, ideas from others may narrow one’s conception of the idea space and focus idea generation on only one aspect of the task (Dennis & Valacich, 1993; Pinsonneault et al., 1999a). In summary, there is a tension in the balance of potential process gains from synergy and the potential process losses from cognitive interference. Nominal groups do not benefit from synergy and do not suffer from cognitive interference. Electronic brainstorming groups have the potential to benefit from synergy and suffer from cognitive interference. Synergy and cognitive interference are two sides of the same coin: the ideas of others can both stimulate new ideas and interfere with the production of one’s own ideas. Based on prior research (Dennis & Valacich, 1999), we believe that the potential gains from synergy exceed the potential losses from cognitive interference. Therefore, we hypothesize: H1: The number of ideas produced per person will be higher in groups whose members receive more ideas from others.

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Social Loafing Social loafing (also called free riding) is the tendency for individuals to expend less effort when working in a group than when working individually (Karau & Williams, 1993; Kerr & Bruun, 1983; Weldon & Mustari, 1988). Social loafing may arise because participants believe their contributions are dispensable and not needed for success and/or because responsibility is diffused among many participants (Chapman, Arenson, Carrigan, & Gryckiewiz, 1999; Harkins & Petty, 1982; Karau & Williams, 1993; Latane, Williams, & Harkins, 1979). Social loafing is reduced when participants believe that they are being evaluated as individuals rather than collectively as a group (Karau & Williams, 1993), and thus, differences in performance become more noticeable when members of nominal groups believe that they are working as individuals, not as members of a group. Performance differences are reduced when members of nominal groups believe that they are working as members of a group2. Social loafing can be expected to increase as group size increases, because perceived dispensability and diffusion of responsibility increase as the number of participants increases. As social loafing increases with group size, the number of ideas generated should decrease. Historically, the effects of social loafing on idea production have been difficult to separate from the effects of synergy/cognitive interference, because both synergy/cognitive interference and social loafing tend to increase with group size. As group size increases, synergy increases, and more ideas are produced. However, as group size increases, social loafing increases, resulting in fewer ideas. In this study, we manipulate social loafing separately from synergy in order to better understand their individual effects on the productivity of idea generation. We hypothesize that, as participants perceive themselves to be in larger groups, they will have a greater tendency

Patterns in Electronic Brainstorming

to engage in social loafing and produce fewer ideas. Therefore: H2: The number of ideas produced per person will decrease as group size increases.

METHOD A laboratory experiment with a 2x3 research design with repeated measures on one condition was used. The first condition was group size (small vs. large) intended to manipulate social loafing. The second condition (the repeated condition) was the idea generation technique intended to manipulate synergy (nominal group brainstorming intended to produce no synergy, electronic brainstorming with a small idea pool size intended to produce modest synergy, and electronic brainstorming with a large idea pool size intended to produce high synergy). In traditional brainstorming experiments, it is difficult to separate the social loafing effects (due to group size) from its likely effects on synergy, because larger groups typically generate more total ideas than smaller groups. It is also difficult to control the ideas received by individuals, because each group is different, and individual group members are influenced by the actions of the other members of their group. Therefore, to provide a tightly controlled experimental manipulation in which we could manipulate social loafing and synergy separately, we used a groupware simulator, not a true electronic brainstorming system. A groupware simulator is designed to look and feel like a true electronic brainstorming system, but instead of sharing ideas among group members, the simulator simply presents ideas from a prepared script as the ideas from other group members. Simulators have been used successfully in prior electronic brainstorming and other groupware research (Garfield et al., 2001; Hilmer & Dennis, 2001; Satzinger, Garfield, & Nagasundaram, 1999).

Subjects A sample of 216 sophomore, junior, and senior business students at a large state university received course credit for participating in the study. Subjects were assigned randomly into either a small or a large group, resulting in 10 six-member groups and 13 12-member groups. All subjects within a group generated ideas with each technique, but the order of the techniques differed using a fully blocked experimental design.

Tasks All subjects performed three idea generation tasks similar to those in prior research. One task asked subjects to generate ideas to improve the environment. Another task sought ideas to increase the amount of tourism in the United States. The third task asked for ideas to improve public safety in the United States3. All subjects completed all three tasks, but the order in which the tasks were presented differed, using a fully blocked experimental design. Subjects were given 12 minutes to perform each task. This amount of time was chosen to not unduly fatigue subjects in performing three tasks and because similar lengths of time (e.g., 10 to 15 minutes) have been used in prior brainstorming research (Dennis & Valacich, 1993; Diehl & Stroebe, 1987; Gallupe, Dennis, Cooper, Valacich, Bastianutti, & Nunamaker, 1992; Harkins & Petty, 1982; Paulus & Dzindolet, 1993).

Independent Variables The first independent variable was group size, designed to induce shifts in social loafing. It is difficult to make compelling arguments for the choice of one specific group size over another. Prior empirical research suggests that there is an important point of inflection in electronic brainstorming vs. nominal group performance (around eight- or nine-member groups) (Dennis

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& Valacich, 1999), so we wanted to choose one group size below this point and one above this point. Therefore, we chose to use groups of six and 12 members. These sizes have been used commonly for small and large groups in prior research (Pinsonneault et al., 1999a). To reinforce the group size manipulation, the groupware simulator prominently displayed the size of the group in which the subject was working (even though subjects could look around and count the number of members in their group). The simulator also displayed a counter of the total number of ideas purportedly generated by all members of the group. This idea counter increased from zero to a predetermined end number during each experimental time period following a typical group productivity pattern (i.e., an initial burst of ideas, followed by a slight lull, and then gradually increasing again). The end number for the counters was chosen, based on a typical productivity rate of about one (potentially redundant) idea per person per minute4 (Gallupe, Dennis, Cooper, Valacich, Bastianutti, & Nunamaker, 1992). This consistent per-person level of idea production also was chosen to control any potential matching, whereby group members attempt to produce ideas at the same rate as others (Camacho & Paulus, 1995). For groups of 12, the end numbers were 146, 153, and 154 (remember that each group performed three separate idea generation tasks). For groups of six, the end numbers were 74, 78, and 79. The second independent variable was the idea generation technique, designed to induce different amounts of synergy. In all treatments, participants typed their ideas into the groupware simulator. In the electronic brainstorming treatments, instead of exchanging those ideas with other participants, the simulator presented participants with ideas that appeared to be from other group members but, in fact, were drawn from a script written by the researchers. The ideas displayed in the simulator came from ideas generated in prior experiments using these tasks.

106

Subjects were informed that they would receive some but not all the ideas produced by the other members of their group. Subjects generated ideas for all tasks using a computer, but the number of ideas that they saw from “other group members” varied for each treatment. In the nominal group brainstorming treatment, subjects only saw their own ideas being displayed (i.e., the size of the idea pool was zero); no ideas from others were displayed. The small idea pool treatment was designed to be representative of the number of ideas produced by a small group and consisted of 28 ideas shown (but, of course, idea pool size was manipulated separately from group size). In this treatment, a small amount of ideas was displayed with the subject’s own ideas intermixed with the ideas from others. In the third treatment, a large pool of ideas was displayed (again, intermixed with the subject’s own ideas). The large idea pool treatment was intended to be representative of a large group and displayed 56 ideas.

Procedures Subjects were assigned randomly to groups of six or 12 within a session, and sessions were assigned randomly to a particular sequence of techniques and tasks. Subjects first completed a consent form that also asked for age and gender. Consistent with prior research, we gave the standard brainstorming instructions to all groups in all treatments, which were included with the consent form and repeated on each task sheet (see Appendix A). Next, subjects were shown how to use the groupware simulator. Because the simulator was straightforward, subjects did not have a practice session. Subjects then used the simulator to generate ideas on one task using one of the three techniques (nominal group, electronic-small idea pool, electronic-large idea pool). After generating ideas, subjects filled out a questionnaire that assessed satisfaction with the process. They then received a second task, generated ideas using a different technique, and

Patterns in Electronic Brainstorming

completed the questionnaire again. Subjects then received the third task, generated ideas using a different technique, and completed the questionnaire again. Finally, the subjects were debriefed and released.

Dependent Variables Productivity was measured by the average number of unique ideas generated per participant in a group. For each task, the output of all group members was combined into one file. The number of unique ideas generated by each group in each treatment then was counted according to the procedure described in Bouchard and Hare (1970) and Cooper, Bastianutti, Young, McCallum, Anderson, and Gallupe (1993) and then divided by the number of group members. The transcripts of the group and simulator ideas were evaluated by one coder by following a detailed guide that explained how to identify redundant ideas and how to calculate the number of unique ideas. Another coder using the same coding rules independently coded a random subset of the transcripts. Interrater reliability was acceptable (r = 0.96). The group process satisfaction measure is shown in Appendix B. The items were drawn from previous research (Dennis & Valacich, 1993) and had adequate reliability (α = 0.86).

Statistical Analysis The data were analyzed with a linear model for repeated measures that took into account the incidental effect of the time period (order) in which the three techniques were assigned to the groups of subjects (Keppel & Wickens, 2004). Therefore, the following parameters were included in the statistical model: the main effect of group size, the main effect of technique, the main effect of period, and the two-way and three-way interactions among these effects. Statistical significance was set at the 5% level. The Bonferroni method was used for post hoc multiple comparisons and

computation of 95% confidence intervals (C.I.) for differences between means. The unit of analysis was the group for the average number of unique ideas generated and the subject for the satisfaction measure. All statistical analyses were conducted using SAS statistical software for Windows, release 8.02.

RESULTS Table 1 presents the mean number of unique ideas generated per individual and the standard deviation according to group size and technique. Table 2 presents the results of the analysis of variance for the main effects and for all terms representing two-way and three-way interactions. As can be seen from Table 2, the technique and period main effects as well as the technique-period interaction were significant. Thus, the different techniques appeared to provide different levels of synergy/cognitive interference leading to different performance, but the effects interacted with the time period in which the technique was used. Figure 1 illustrates the cell-level means for the technique by period interaction. The data suggest that the no-synergy nominal groups performed better in the first two time periods, but the electronic brainstorming groups with a small idea pool produced more ideas in the last time period. Overall, the two electronic brainstorming technologies seem to follow a similar pattern. Groups using electronic brainstorming techniques in period three produced significantly more unique ideas per individual than groups using the same electronic brainstorming technique in period one (Electronic-Small Idea Pool: Bonferroni’s adjusted p < 0.005 and the 95% C.I. for the difference: 2.83 ± 2.21; Electronic-Large Idea Pool: Bonferroni’s adjusted p < 0.019 and the 95% C.I. for the difference: 2.74 ± 2.43). In contrast, the productivity of groups using nominal brainstorming was not significantly different from period one to three (Bonferroni’s adjusted p-values for

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Table 1. Mean number of unique ideas per individual by group size and technique Group Size 6 6 6 12 12 12

Technique No Synergy (Nominal Groups) Modest Synergy (Electronic-Small Idea Pool) High Synergy (Electronic-Large Idea Pool) No Synergy (Nominal Groups) Modest Synergy (Electronic-Small Idea Pool) High Synergy (Electronic-Large Idea Pool)

N

Mean

Standard Deviation

10

9.3

1.1

10

8.6

1.9

10

8.3

2.4

13

10.7

1.7

13

9.6

1.7

13

8.7

1.5

F 2.92 10.28 2.09 3.56 0.92 3.32 1.10

p-value 0.102

60

The Knowledge Component of LCS The domain knowledge to be covered needs to be efficiently organized for quick retrieval and update. In this research, a concept hierarchy is constructed to represent content to be covered in Web-based learning. The hierarchy is a directed acyclic graph (DAG) of nodes and links. A node represents a content element and a link represents a relationship between content elements. The hierarchy represents concepts at different abstraction levels and contains multiple relationships including Is-a, Part-of, Contained-in, Assoc-with, Related-to, Example-of, Applicable-to, Easier-than, etc. in a single hierarchy (Lee & Geller, 2002). The hierarchy is used to determine the level of abstraction for a given topic, to interpret relationships between topics, etc. Pointers to lecture notes, tests and homework problems are attached to topic nodes. The knowledge component manages level of difficulty, type of knowledge and problem solving behavior. Knowledge is declarative, procedural, or structural. There are three levels of difficulty (hard, medium and easy). The problem-solving behavior is top-down or bottom-up. The KCA (knowledge component agent) determines the topic and type of knowledge (declarative, procedural or structural) to be presented to the learner.

The Presentation Component of LCS The presentation component responds to the learning proclivities of the learner as shown by the learner’s profile. We implemented two presentation views: e-book view and e-game view. A typical learning episode may require a combination of different presentation views. Presentation views consider the instruction mode (guided, self-learning and game-oriented), presentation mode (audio, video and text), presentation strategy (top-down, bottom-up, local, global, hierarchical

High Performance Publisher/Subscriber Communication for Adaptive, Collaborative Web-Based Learning

and flat) and instruction mode, (model-based, problem-solving-based or theory-based). The e-game view (Figure 5) has a dual purpose: to quiz a student about class material and to let him play a game he will hopefully enjoy. Essentially, the game is the well-known arcade game PacMan with integrated quiz questions. When the game is over, the quiz score will be returned to the Learner Component. We have initiated a set of experiments using our CoSL framework with about 60 students in a discrete nathematics course in computer science. As the first outcome of these experiments, we were able to collect data for learner teaching profiles. These will enable the CoSL system to customize course materials to fit the learning preferences of individual students and also to optimize its own teaching strategy. Further experiments are planned to confirm whether our CoSL system can be used to reinforce the concepts covered in a traditional class.

COMPARISON OF THE CoSL COMMUNICATION SUBSYSTEM For our purposes, middleware is a layer of software, which exists between the Internet and multiple software applications, to provide the connectivity between applications running on different systems (Emmerich, 2000). Today’s most popular examples of middleware include the common object request broker architecture (CORBA), Microsoft’s component object (COM) and Enterprise Java Bean (EJB). Services provided by middleware include communication, identification, concurrency, fault tolerance, and security. In this section, we will compare CoSL with COM+, CORBA, JAVA Message Service (JMS) and EJB. COM+ offers a distributed event system (MSDN, 2001), which is based on the publisher/ subscriber model of communication ideally decoupled between Publishers and Subscribers.

Figure 5. User interface of the presentation component

Which of the following Is NOT a recurrence relation? Choose One

Correct!

The correct answer is C. The recurrence relations described a sequential relationship between terms of the sequence.

6

High Performance Publisher/Subscriber Communication for Adaptive, Collaborative Web-Based Learning

COM+ provides the efficient use of communication mechanisms: local method call, inter-process call and remote call (Emmerich, 2000). CORBA provides synchronous and asynchronous communications through the Notification Service (Bartlett, 2001) and the Event Service (OMG, 2001). The Event Service is a layer on top of the ORB (object request broker) architecture. An event channel can support consumers and suppliers using different communication protocols. The notification service (Bartlett, 2001; Carzaniga, 2001; Gore, 2001) supports the suppliers of an event channel by producing events on demand and the consumers by discovering the event types offered by the suppliers. It determines QoS according to message attributes, such as reliability, priority, expiration times, earliest delivery time, maximum events per consumer, order policy, and discard policy. The notification service is powerful but it is very complex. Within Java Message Service (JMS), publishers and subscribers create connections and sessions explicitly. Publishers and subscribers communicate through message objects. Subscribers have a “message selector” which allows filtering of messages for publishers. Similar to the COM+ and the CORBA services, Publishers and Subscribers communicate indirectly, but JMS is not as complex as the CORBA notification service. The mechanisms of connections and sessions allow more efficient networking than RMI or ORB calls, e.g., via TCP. Many implementations of JMS (Gore, 2001) are available. The basic EJB communication method is RMI-IIOP. Recent enhancements of EJB introduced message-driven beans, which integrate JMS into the EJB component platform. The EJB platform can benefit from JMS’s features like asynchronous delivery, exactly-once reliability and QoS parameters. Because of the need of an application server and increased overhead, EJB might not be ideal for high performance communication in distributed computing.

6

The communication systems are a central factor in determining overall performance and efficiency of a message system. The COM+ event service lacks the transparent distribution capability. Only CORBA and JMS support multicast, which is particularly important when dealing with multiple Subscribers. Only COM+ and CoSL offer an optimized communication mechanism, focused on increasing the efficiency of communication. Lightweight communication (Floyd, 1995) means that the system uses the networking layer directly. COM+ and the CORBA services are tied to their standard communication methods, RPC and ORB calls, which are far from a lightweight communication implementation. JMS extends Java-based explicit connections with sessions, but does not define the connection type. Our CoSL communication subsystem is the only system that is offering lightweight TCP and UDP connections by definition, and which is also open to new connection types. The CoSL communication subsystem allows multiple connections and uses a server-less approach (Table 2).

PERFORMANCE EVALUATION Two experiments were made with CoSL. The first one compared it with RMI and an implementation of the Java messaging service (SwiftMQ). We included RMI, because it is one of the standard Java approaches for distributed computing, however, RMI is not capable of group communication. The Java messaging system and the SwiftMQ implementation are more similar to CoSL, because they offer publish/subscribe communication. Sun’s Java 1.4 Beta 3 Virtual Machine was running in the Server Hotspot mode on a Pentium III 866 MHz with 256 MB RAM. The results show the communication of two separate Virtual Machines on a single machine, i.e., without network connection. Figure 6 illustrates message rates depending on the message size. The results indicate

High Performance Publisher/Subscriber Communication for Adaptive, Collaborative Web-Based Learning

Table 2. Comparison of communication systems COM+ Event Service No No

Transparent Distribution Multicast Optimized non-remote communication Lightweight TCP communication Lightweight UDP communication Plug-in points for custom connection types

Yes (Yes)1

CORBA Notification Service Yes (No)1

JMS (J2EE EJB) Yes (No)1

Yes

No

No

(No)1

Yes

No

No

No

(Yes)1

Yes

No

No

No

No

Yes

No

No

No

No

Yes

CORBA Event Service

CoSL Yes No

Note: 1 It depends on the implementation whether this feature is available.

Number of mes s ages [1/s ec]

Figure 6. Message rates

10000 C osL R MI J MS

1000

100 0

10

100

1024

Mes s age s ize [B ytes ]

1

that CoSL provides exceptionally high rates for small messages, while both RMI and SwiftMQ provide only relatively moderate rates. The rate decreases with an increasing message size, but that is rather related to TCP data processing than to the systems themselves. Therefore, the results for higher message sizes differ less. The throughput (data rate) is outlined by Figure 7. The results indicate that an efficient data communication can be realized especially for small messages in CoSL.

Figure 8 confirms the previous results in a network experiment. The test environment consisted of two identical machines, which were connected with a 100 Mbps ethernet network. Each of the machines was equipped with a 1.4 GHz Pentium 4 CPU, and 256 MB RAM. Figure 8 shows that CoSL has a better data rate than SwiftMQ, especially for small messages. At a certain point, the network bandwidth is reached, which is revealed by the stagnation of the rates. Both experiments provided evidence for the ef-

6

High Performance Publisher/Subscriber Communication for Adaptive, Collaborative Web-Based Learning

Figure 7. Throughput

10000

C osL R MI J MS

C os L J MS

Throughput [KBytes/sec]

T hroughput [K B ytes /s ec]

1000

Figure 8. Throughput experiment 2

100

10

1000

100

10

1

0.1

1 10

100

1024

1 B yte

Mes s age s ize [B ytes ]

ficiency of CoSL. In contrast to other systems, it can handle small messages efficiently.

RELATED WORK Individual or tailored instruction based on learners’ needs and background has not been achieved yet (Luchini, 1998). Researchers have investigated psychological variables affecting the quality of online learning. They have identified different variables, e.g., learning styles (Cox, 2000). The importance of user modeling has been emphasized in the learning community. Milne et al. (1996) focused on the development of composite learner models, incorporating both domain-related data and information about personal attributes such as capabilities and preferences. Schwab et al. (2000) used machine learning methods to acquire a user-interest profile from observed user behavior. Wesley et al. (1999) used distributed rational agents to manage the acquisition and presentation of multimedia information in a distance-learning environment. El-Khouly (1999) developed intelligent computer-aided instruction (ICAI) software using agent technology. Rickel et al. (1997) intro-

6

10 B ytes

100 B ytes

1 K byte

10 K byte

Message Size [Bytes]

duced two types of agents, students and pedagogical agents, communicating using virtual reality. Some researchers focused on the interactions of multiple agents (Maes, 1996) and user models and their maintenance (Brown, 1998). The use of XML has rapidly increased, due to its flexible and powerful features, e.g., in MathWeb (Franke, 1999). A study demonstrated the ineffectiveness of totally self-guided learning and suggested efficient (‘intelligent’) combinations between externally guided and self-guided learning (Schindler, 1986). Gustafson et al. (1998) built instructional models to provide conceptual and communication tools that were used to visualize, direct and manage processes for generating episodes of guided learning. An example of gamebased learning is “dialogue game” (Ravenscroft, 2000). Another study showed that game-oriented learning is more effective than straight tutorial animation (Ford, 1993).

CONCLUSION Our high performance publisher/subscriber communication system supports flexible and efficient

High Performance Publisher/Subscriber Communication for Adaptive, Collaborative Web-Based Learning

communications between agents in CoSL. A prototype of the CoSL system has successfully employed XML-based data exchange and agentbased communication. Experiments with our publisher/subscriber com-munication subsystem show that it is faster than JMS and RMI.

Emmerich, W. (2000). Engineering distributed objects. New York: John Wiley & Sons.

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High Performance Publisher/Subscriber Communication for Adaptive, Collaborative Web-Based Learning

Luchini, K. (1998). Problems and potentials in Web-based instruction with particular focus on distance learning. Educational Technology and Society, 1(1). Maes, P., & Wexelblat, A. (1996). Interface agents. CHI96 Tutorials, 369-370. Milne, S., Shiu, E., & Cook, J. (1996). Development of a model of user attributes and its implementation within an adaptive tutoring system. User Modeling and User-Adapted Interaction, 6(4), 303-35. MSDN (2001). COM+ Events Architecture. http:// msdn.microsoft.com/library/default.asp?url=/library/enus/cossdk/htm/pgservices_events_20rp. asp OMG (2001). Event Service, http://www.omg. org/technology/documents/spec_catalog.htm Ravenscroft, A. (2000). Designing argumentation for conceptual development. Computers and Education, 34(3-4), 241-255. Rickel, J., & Johnson, W. (1997). Mixed-initiative interaction between pedagogical agents and students in virtual environments. In Proceedings of AAAI spring symposium on Computational Models for Mixed Initiative Interaction. Schindler, R., & Schuster, A. (1986). Preknowledge and the efficiency of self-guided user’s learning, ECCE 3. In Proceeding of Third European Conference on Cognitive Ergonomics. Preprints.

Inst. Nat. Recherche Inf. and Autom, Le Chesnay, France (pp. 139-153). Schwab, I., Kobsa, A., & Koychev, I. (2000). Learning about users from observation: Adaptive user interfaces. In Proceedings of AAAI 2000 (pp. 102-106). D’Souza, D.F., & Wills, A.C. (1999). Objects, components, and frameworks with UML: The catalysis approach. Addison Wesley. Sternberg, R. (1997). Thinking styles. New York: Cambridge University Press. Stone, T. (1992). A new look at the role of locus of control in completion rates in distance education. Research in Distance Education, 4(2), 6-9. Thyfault, M. (2000). Learning management systems come of age. http://www.planetit.com/ techcenters/docs/management_issues/news/ PIT20010118S0014 Wesley, L., Shim, S., Atreya, S., & Booth, R. (1999). ROADS: An environment for developing automated intelligent agents to support distance learning. Journal of Interactive Learning Research, Assoc. Advancement Comput. Educ., 10(3-4), 321-333. Wiley, D. The Instructional Use of Learning Objects. http://reusability.org/read/ Wooldridge, M., & Jennings, N. (1995). Intelligent agents: Theory and practice. The Knowledge Engineering Review, 10(2), 115 - 152.

This work was previously published in the International Journal of Distance Education Technologies, Volume 1, No. 3, pp. 14-27, copyright 2003 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 1.58

Evaluating Student Learning in Distance Education Efstratios T. Diamadis Athens University of Economics and Business, Greece George C. Polyzos Athens University of Economics and Business, Greece

INTRODUCTION Evaluating students is critical to education. Evaluation results give students feedback about their performance so that they can learn from their successes and failures. On the other hand, these results allow instructors to determine how well students are performing, and what areas and subjects need more attention. The conventional methodology to evaluate student work is by “pen and paper.” It can take many forms—such as traditional exams, open-books exams, reports, practical work, and others—as the next section illustrates. However, new technologies are bringing changes to the educational process. Over the last few years, distance education has become a popular delivery mode of instruction and learning. Virtual Learning Environments (VLEs) are groupware systems designed to replace or supplement the face-to-face classroom. These

systems provide registered members with a cooperative learning space where learners conduct their activities. They include modules and services for managing pedagogical aspects of the educational process and online teaching activities. Contemporary VLEs (e.g., TopClass and LearningSpace) integrate three main components: •

•

•

The learning management system (LMS), embracing all the functions for student and course management, learning assessment, and tracking and reporting on student progress and activity The learning content management system (LCMS), focusing on creating, reusing, locating, sharing, or improving learning content A variety of asynchronous and synchronous tools (such as e-mail, application and file sharing, chat, live video stream, white-

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Evaluating Student Learning in Distance Education

board, and others) for delivering educational material and enabling interactions among participants Within these settings, new ways of assessment have emerged. The problem is to measure to what degree the learning goal has been achieved. Distance education itself introduces further problems such as the difficulty in user identification or the inapplicability of traditional evaluation methods. The question is whether assessment methods can be successfully integrated in VLEs. It is obvious that both technological and pedagogical requirements of assessment should be addressed. In this chapter, we reflect on these requirements and overview evaluation methods of student learning in distance education. In the following section, the concept of assessment is discussed. Then we explore advantages and disadvantages of various assessment techniques, as well as how existing e-learning platforms address the need for a fair learning assessment. Finally, we present strengths and weaknesses of the process, and our concluding remarks.

BACKGROUND As indicated in the introductory section, assessment is an important task in the teaching and learning process. Some of the reasons are: (a) students can learn from their mistakes and successes; (b) instructors need feedback on how well student learning is going, so that they can adjust and develop their teaching; (c) assessment is often the major factor that gets students down to serious studying; and d) in our society, people are appointed and employed on the basis of their qualifications (Race, 1995). Besides the conventional method, where tutors assess students’ work, three other assessment approaches can be used: self-assessment, peer-assessment, and group assessment (Race,

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2001a). Self-assessment involves students making judgment about their own work, while peer-assessment (also referred to as collaborative assessment) involves students and tutor(s) making thoughtful and critical examination of each student’s coursework. Group assessment, finally, refers to the following three techniques: first, when a tutor assesses student group work; second, when students from other groups assess group work (inter-peer assessment); and third, when students within a group assess the group’s work (intra-peer assessment). It can include selfassessment by individuals or by the group as a whole, as well as their contributions towards the product they have generated. Three are the basic evaluation methods: summative, formative, and comparative (Wolz et al., 1997). Evaluation is summative when it is used with the intention of assigning a rating or grade. When the intention is to give feedback to guide or improve practice, a formative assessment is adopted. Comparative evaluation is used to compare the effectiveness of alternative elements of a course or curriculum (for example, whether or not collaborative learning improved student performance). Key issues for a challenging assessment are the following (Brown, 2001; Race, 2001a, 2001b): •

•

•

Fairness: It is recognized that the greater the diversity in the methods of assessment, the fairer the assessment is to students. Therefore, assessment needs to embrace a variety of kinds of activity, so that candidates have a greater opportunity to demonstrate their skills on at least some of the assessment occasions they encounter Effectiveness: Effectiveness explores whether it is an appropriate approach to assess the learning outcomes Efficiency: This is related to the time spent for assessors to accomplish the assessment task

Evaluating Student Learning in Distance Education

•

•

Reliability: Reliable assessment means that independent of who marks your work, it is expected you will receive the same mark Validity: An assessment is valid if it measures what is intended to be measured

tions, rather than how well they have learned •

Open-book exams: These are similar to traditional exams and have many of the advantages described above. Additional advantages include:  Less stress on memories  It is possible to set questions that measure retrieval skills Disadvantages include:  It is hard to ensure that all students are equally equipped (for example, the impossibility of students purchasing expensive books may be a disadvantage for them)

•

Structured exams: These include multiplechoice exams, true/false, matching, fill-in the blank, and others. Main advantages include:  It is possible to quickly test students’ understanding of theories and concepts  These save staff time and avoid subjectivity Main disadvantages include:  It is possible for students to gain marks by lucky guesses rather than correct decisions  It is harder to design structured questions in time and skill than it is to write traditional open-ended questions

•

Essays: These are often used in some subjects, and in traditional or open-book exams. Major advantages are:  They are an assessment form in which the “best” students can distinguish themselves  Free writing about a topic demonstrates understanding of the learning material

ASSESSMENT FORMS Assessment should accommodate individual differences in students. A diversity of assessment formats and processes should be employed, so as not to disadvantage any particular individual or group of learners. Race (1995) illustrates several assessment forms with advantages and disadvantages as follows: •

Traditional “unseen” exams: Time-constrained written examinations continue to play a large part in the overall assessment picture. Advantages include:  They are economical, although this depends on economies of scale when large numbers of students are examined, or on how much time and money needs to be spent to moderate students’ performance  Exams are fair in the sense that students have all the same tasks to do in the same way and within the same timescale  It is easier to be sure that the work being assessed was done by the candidates and not by others Disadvantages include:  Students get little or no feedback about their performance  Badly set exams encourage surface learning, with students consciously clearing their minds of one subject as they prepare for exams in the next subject  Exams tend to measure how good students are at answering exam ques-

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Evaluating Student Learning in Distance Education

Major disadvantages are: Essay writing is an art in itself, and in this sense some students may be disadvantaged  They take time to write  The danger of subjective marking is greatest





•

Reviews: Reviews allow students to interact in depth with the information they review. Further advantages are:  The reviewing process helps students to avoid reading passively  When students review material from different sources, they are necessarily involved in higher-level mental processes of comparing, contrasting, and evaluating Disadvantages include:  When assessing individuals, the task should be delineated quite firmly  When assessing groups, it is difficult to assess contributions of group members

•

Reports: These are often part of the coursework of many courses. Advantages are:  Report writing allows students to display their individual strengths  It is a skill relevant to many jobs  Writing reports involves students in useful processes such as research, practical work, and others which are hard or impossible to assess directly, and reports provide evidence that these processes have been involved successfully or not Disadvantages are:  Report writing can take a lot of student time, particularly when reports are assessed and they count towards final grades

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

Report marking can take a lot of staff time, making it difficult or impossible Collaboration can be difficult to detect (for example, with laboratory work)

•

Practical work: This is involved in many areas of study. Major advantages include:  It may be really important (for example, none of us wants to be treated by a surgeon with the best theoretical knowledge, but whose practical work is of low quality)  Practical work is learning-by-doing  Employers may need to know how good students’ practical work is and not just how good their reports are Major disadvantages include:  It is easier to assess the end point of practical work rather than the processes and skills involved  It can be difficult to agree on assessment criteria for practical skills

•

Portfolios: These include pieces of students’ work, feedback comments from tutors, and reflective analyses by the students themselves. The main advantage is that they can contain evidence of a wide range of skills and attributes. Disadvantages include:  It can take a long time to assess a portfolio  Because of the individual nature of portfolios, it is harder to decide on a set of assessment criteria and mark them objectively  It may be necessary to couple the assessment of portfolios with a kind of oral assessment or interview in order to authenticate the origin of the contents of portfolios, particularly when they are based on collaborative work

Evaluating Student Learning in Distance Education

•

•

Presentations: It can be argued that the communications skills involved in giving good presentations are more relevant to professional competences needed in the work. Therefore, it is increasingly common to have assessed presentations as a part of students’ assessment process. Advantages are:  There is no doubt whose work is being assessed  The fact that students are preparing for a public performance usually ensures that they are likely to engage in deep learning about the topic concerned  Presentations can also be done as collaborative work Disadvantages are:  With large classes, a round of presentations takes a long time. To address this drawback, the class should be split into groups of (say) 20 students, and facilitate peer assessment of the presentations within each group on the basis of assessment criteria agreed by the whole class  It is difficult to reconsider the merit of a particular presentation (the evidence is transient) unless the presentations have all been recorded  Presentations cannot be anonymous Vivas: Viva-voce exams have long been used to measure skills and knowledge which can elude other forms of assessment. They take the form of interviews or oral examinations. Major advantages are:  It is easy to use vivas to ensure that students are familiar with things that other assessment forms indicated they have learned well  Candidates may be examined fairly, because they may be asked the same

questions, and their responses compared and evaluated Major disadvantages are:  Some candidates under-perform when asked questions by experts and figures of authority  When the same series of questions is posed to a succession of students, it is difficult to avoid communication of candidates who have already been examined with friends whose turn will come

EVALUATION IN DISTANCE EDUCATION In a traditional classroom, teachers use a variety of means, some formal and some informal, to evaluate students’ learning and assign grades. For example, teachers use formal evaluation techniques such as quizzes, tests, examinations, or other assessment forms described above. To evaluate students’ learning informally, teachers also use several techniques. For example, they pose questions, listen to student questions and comments, or monitor body language and facial expressions. Thus, implicit evaluations permit the teacher to slow down or review material in response to questions, confusion, or misunderstanding. The situation becomes more complex in a distance learning environment. Educators have to identify what they want students to know and successfully integrate the educational material in VLEs. Furthermore, distance education itself imposes several problems such as the difficulty in user identification or the absence of proper evaluation methods. When teaching at a distance, instructors no longer have (Willis, 2003): • •

A traditional, familiar classroom A relatively homogeneous group of students

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Evaluating Student Learning in Distance Education

• •

Face-to-face feedback during class (e.g., students’ questions, body language) Convenient opportunities to talk to students individually (p. 1)

VLEs (such as TopClass, LearningSpace, BlackBoard, WebCT, and others) do not yet provide the richness of face-to-face interaction. However, they provide a variety of tools and facilities for replacing or supplementing the faceto-face classroom: student and content management, learning assessment, and communication among participants. The content management system integrates functions for creation, description, importation, or exportation of content, as well as its reuse and sharing such as: • •

• • • •

Learners and trainers communicate through asynchronous and synchronous tools. Asynchronous tools include e-mail, discussion forums, and newsgroups. Synchronous tools include chat, whiteboard, videoconference or audioconference services, and application and file sharing. VLEs also provide facilities allowing the replication of a range of traditional assessment methods online. For example: •

•

Creation of folder structures and learning objects to organize content Post announcements, course materials, assignments, links, and more to the course Web site Support for uploading and delivering files of multiple formats including multimedia Support for downloading course content Reuse of learning objects in multiple courses Course delivery depending on each learner’s individual knowledge level

The student management system contains functions for identifying users and their characteristics such as: • • • •

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Online registration or enrollment Access rights assignment Username and password assignment Through testing and assessment techniques, the system allows students to understand their gaps and identify learning paths that best suit each learner

•

Essays and other assignments can be submitted electronically, marked individually, and returned to students with comments and information for improvement. Instructors can generate tests including multiple question formats, such as multiple choice, true/false, matching, fill-in the blank, and others. Test questions should examine whether educational objectives within the cognitive domain have been achieved. Educational objectives are categorized (Bloom, Englehart, Furst, Hill, & Krathwohl, 1956) in the following hierarchy, from less to more complex: knowledge, comprehension, application, analysis, synthesis, evaluation. It should be noted that this is the classic classification of information and knowledge widely applied by many educators in assessment, testing, and evaluation. Automatic assessment of tests gives immediate feedback for students and the possibility to resubmit answers after receiving the feedback. Research works show that resubmission is a key factor that promotes learning (Malmi, Korhonen, & Saikkonen, 2002) Statistics and analysis of Web portfolios can help instructors to diagnose students’ learning activities. Analysis involves the following types of portfolios: 1) portfolio development activities, such as the submission of assignments; 2) discussion activity and learning behavior in the system to facilitate attendance evaluation, such as: a)

Evaluating Student Learning in Distance Education

•

the frequency of using the learning system (for example, participating in chatting or discussion rooms), and b) reading behavior such as the number of modules accessed and the time spent on each module; 3) portfolios that include assessment results, such as student answers to objective tests and teachers’ assessment of students’ assignments (Liu, Chen, Wang, & Pai, 2001). Further functionality is needed when instructors must answer questions such as: “Do students who often answer others’ questions tend to submit homework on time?” (known as the causality discovery problem, i.e., the need to discover how various student learning behaviors and performances are related) or “If a student often answers others’ questions, what is the probability of that student to achieve a good learning outcome for a particular learning concept?” (commonly referred to as the performance inference problem, i.e., the need to answer probability questions related to estimating a student’s behavior or performance). To address these problems, VLEs need to provide a convenient data mining and machine learning technique, commonly identified as “Bayesian network software” (Liu et al., 2001).

•

•

•

•

•

•

Disadvantages

SUCCESSES AND FAILURES

•

The use of a VLE to assess students over the traditional methods of assessment has benefits and drawbacks (O’Leary, 2001) that can be summarized as follows:

•

Advantages •

Objective marking, since human factors that could affect marking (such as favoritism, fatigue, prejudice, and others) are eliminated

Time saving for instructors, particularly in large classes (this time can be used more productively in other areas of teaching) Analysis of assessment: Indeed, computers can easily and quickly provide statistics and item analysis reports for student answers to objective questions. This feature allows instructors to identify problem areas in their assessment or areas of misunderstanding, and maybe change the teaching style and content Instant marking: Students’ marks can be provided within minutes after the end of an exam Immediate feedback: Students can get valuable feedback on their progress, and the system can suggest learning paths for improvement Provision of sophisticated assessment that can incorporate multimedia into questions, take answers from one question to formulate the next, or give detailed feedback and links to further resources Help improve teaching practice since it allows continuous assessment. In addition, giving students computerized assessment with feedback can promote independent, active learning

•

Unreliable results, since students can guess answers. However, with an increasing range of question types available and careful selection of questions, the problem can be minimized It is difficult to test all the levels of Bloom’s taxonomy through a computer-based assessment (Fuller, 2004) In exams taken from a distance, it is easy to cheat since invigilation is impracticable (for example, trainees can communicate through electronic mail or other communications channels). One solution to make cheating

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Evaluating Student Learning in Distance Education

•

•

more difficult is the randomization of question delivery The development time for writing high-quality assessment questions is probably greater than the time spent on creating assessments in a traditional learning environment. However, once a dataset of questions exists, less time needs to be spent on designing individual assessments VLEs. described above, do not provide functionality for collaborative assessment (Diamadis & Polyzos, 2003). For example, reviewer-mapping mechanisms are missing

CONCLUSION This chapter focused on the evaluation of student learning in distance education from the following points of view. First, it presented several assessment techniques used in education. Second, it revealed how VLEs support evaluation, and discussed strengths and weaknesses arising from the process. The aim was to provide valuable insight for users (educators and students) and developers of such systems.

REFERENCES Bloom, B.S., Englehart, M.D., Furst, E.J., Hill, W.H., & Krathwohl, D.R. (1956). Taxonomy of educational objectives. The classification of educational goals: Handbook I, cognitive domain. New York: David McKay. Brown, G. (2001). Assessment: A guide for lecturers. Learning and Teaching Support Network (LTSN) Generic Centre Publications. Retrieved, June 28, 2004, from http://www.ltsn.ac.uk/ BlackBoard. Retrieved, June 28, 2004, from http://www.blackboard.com/

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Diamadis, E.T. & Polyzos, G.C. (2003). Supporting collaborative assessment in virtual learning environments. In Proceedings of the 10th International Literacy & Education Research Network Conference on Learning (The Learning Conference 2003), University of London. Fuller, M. (2004). Assessment for real in virtual learning environments—how far can we go? Retrieved, June 28, 2004, from http://www.interdisciplinary.net/Assessment_VLE.pdf LearningSpace. (n.d.). Retrieved, June 28, 2004, from http://www.lotus.com/products/learnspace. nsf/wdocs/homepage Liu, C.-C., Chen, G.-D., Wang, C.-Y., & Pai, C.-F. (2001). Student modeling for performance assessment using Bayesian network on Web portfolios. In Proceedings of the World Conference on Educational Multimedia, Hypermedia and Telecommunications (EDMEDIA 2001) (pp. 1145-1150). Malmi, L., Korhonen, A., & Saikkonen, R. (2002). Experiences in automatic assessment on mass courses and issues for designing virtual courses. ACM ITiCSE’02, 34(3), 55-59. O’Leary, R. (2001). An introduction to computerassisted assessment. Retrieved June 28, 2004, from http://www.ltss.bris.ac.uk:8080/pdfs/CAA.pdf Race, P. (1995). The art of assessing. The New Academic, 4(3) and 5(1). Retrieved, June 28, 2004, from http://www.city.londonmet.ac.uk/deliberations/assessment/artof_content.html Race, P. (2001a). A briefing on self, peer and group assessment. Learning and Teaching Support Network (LTSN) Generic Centre Publications. Retrieved, June 28, 2004, from http://www.ltsn. ac.uk/ Race, P. (2001b). Assessment: A guide for students. Learning and Teaching Support Network (LTSN) Generic Centre Publications. Retrieved, June 28, 2004, from http://www.ltsn.ac.uk/

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TopClass by WBT Systems. (n.d.). Retrieved, June 28, 2004, from http://www.wbtsystems.com WebCT. (n.d.). Retrieved, June 28, 2004, from http://www.webct.com Willis, B. (2003). Evaluation for distance educators (guide #4). Retrieved, June 28, 2004, from http://www.uidaho.edu/eo/dist4.html Wolz, U., Palme, J., Anderson, P., Chen Zhi, Dunne, T., Karlsson, G., Laribi, A., Mannikko, S., Spielvogel, R., & Walker, H. (1997). Computer-mediated communication in collaborative educational settings. Report of ITiCSE’97 Working Group on CMC in Collaborative Educational Settings (pp. 51-69). ACM Press.

KEY TERMS Effectiveness: Explores whether it is an appropriate approach to assess the learning outcomes. Efficiency: Related to the time spent for assessors to accomplish the assessment task. Fairness: It is recognized that the greater the diversity in the methods of assessment, the fairer the assessment is to students. Therefore, assessment needs to embrace a variety of kinds of activ-

ity, so that candidates have a greater opportunity to demonstrate their skills on at least some of the assessment occasions they encounter. Formative Evaluation of Learning: Used when the intention is to give feedback to guide or improve practice. Learning Content Management System (LCMS): Focuses on creating, reusing, locating, sharing, or improving learning content. Learning Management System (LMS): Includes all the functions for student and course management, learning assessment, and tracking and reporting on student progress and activity. Reliability: Reliable assessment means that independent of who marks your work, it is expected you will receive the same mark. Summative Evaluation of Learning: Used with the intention of assigning a rating or grade. Validity: An assessment is valid if it measures what is intended to be measured. Virtual Learning Environments (VLEs): Groupware systems that have been developed to replace or supplement conventional classroombased education.

This work was previously published in the Encyclopedia of Distance Learning, Volume 2, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp 891-898, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 1.59

Distance Education Success Factors Cathy Cavanaugh University of North Florida, USA

INTRODUCTION While effective distance education has been practiced and studied for centuries, it has been in just the last decade that networked digital technology has been employed. Technologies and teaching techniques continue to evolve, and the options continue to expand, emphasizing the need for information that will assist distance education planners and participants in making decisions that will result in optimal learning experiences.

BACKGROUND The process of developing and implementing effective distance education happens in an iterative cycle. Broadly considered, the three stages in the cycle are (1) procurement and preparation of the resources necessary to meet the distance education goals; (2) delivery of instruction using the best practices from education, business, and research; and (3) analysis of the results of distance education to gauge achievement of the goals. Each stage

of the Resources-Practices-Results (RPR) cycle continually revisits lessons learned in the other stages and builds upon the successes realized in the other stages. Each stage requires participation of all stakeholders, including students, instructors, support and design professionals, administrators, and the community. The success factors discussed in each stage are based on decades of research and experience with learners from professions, higher education, and K-12 education (Barker, 1999; Bruce et al., 2000; Cavanaugh, 2001; Educational Development Associates, 1998; Fredericksen et al., 2000; Institute for Higher Education Policy, 2000; Mantyla, 1999).

THE RESOURCES PHASE OF THE RPR CYCLE The resources required to sustain a quality distance education program exist to support students, faculty, and the program or institution toward achieving the goal of effective and appropriate learning. Responsive and flexible human resourc-

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Distance Education Success Factors

es, knowledge, skills, policies, procedures, and technical infrastructure enable quality practices and contribute to quality results. Procurement, development, and adaptation of resources are ongoing processes.

Institutional and Program Resources To provide a vigorous quality distance education program, an institution begins with a policy that values distance education as an endeavor that integrates seamlessly with the institution’s mission and goals. In creating a strategic plan, distance education administrators and instructors engage in continuous dialogue with a broad range of stakeholders in specifying quality benchmarks (Vaughan, 2000). The strategic plan is a financial and philosophical commitment that gives direction to personnel who make specific decisions regarding program implementation. It is a commitment to team support for distance educators and students, technology led by the program’s current and future goals, and the development of program standards. Course developers and instructors need target standards to guide course design and delivery. As a partner to the standards, program review procedures must be developed, implemented, and revised frequently to ensure that all components of the program meet standards, and to ensure that the standards contribute to program goals. Administration of a quality distance education program depends on clear and accurate communication to students. Qualified instructors and support staff must be recruited; they must be provided with development opportunities related to instruction, content knowledge, and technical skill; and they must receive feedback on their teaching. Qualitative input about student performance, satisfaction, and success is at least as important as quantitative data such as enrollment, costs, utilization of technology, and hiring rates. The elements of the comprehensive program evaluation process should be communicated to all

stakeholders in advance, and the results should be reported completely and efficiently.

Faculty and Course Support Resources Qualified and experienced distance education instructors are likely to have the desired attitudes and understanding of the distance education teaching and learning process. For faculty members to succeed in distance education, they need to be supported with accurate and complete information and training in order to develop their skills and understanding. Successful distance educators understand the distance learning environment and the options that exist for instruction. In support of the design and delivery of quality courses, institutions are responsible for providing training and resources for instructors. Instructors need continual access to the physical resources and human support that will enable development of high quality teaching materials. The best distance learning courses use complete and up-to-date materials to increase the information literacy of students, while allowing opportunities for creative expression and mastery of concepts.

Student Support Resources The focus of distance education is the students, whose work is made better when they receive welldesigned instruction in a well-planned program. For students to maximize the time and effort they spend on their learning, they must minimize the time and effort they spend on solving non-academic problems and on seeking answers. Some students need hands-on technical training using the tools employed in courses and using general learning tools such as libraries and information archives. As students begin the work of learning, they need continual access to instructors, libraries, and other student resources. Students must have adequate access to resources appropriate to support their learning. The institution must

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Distance Education Success Factors

assess the student’s ability to succeed in online learning (SREB 2000).

Technical Resources Even given the best plan, program, instructors, materials, and students, distance learning does not occur without the technology for delivery. Technology selection decisions involve all stakeholders. A technology plan guides decision makers in considering student outcomes, program goals, and technical feasibility (Council of Regional Accrediting Commissions, 2000). Support extends to all users of the technology for all facets of the learning process. Users require assistance with hardware and software uses.

Success Factors for the Resources Phase • • • • • • • •

• • • •

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Institutional policy that values distance education Strategic plan for delivering distance education to students Stakeholder analysis to determine needs of graduates Financial commitment that gives direction regarding program implementation Team support for distance educators and students Appropriate technology infrastructure Program standards to guide course design and delivery Program review to ensure that all components of the program meet standards and to ensure that the standards contribute to program goals Effective communication of policies and expectations to students Student services: information, advising, orientation, and security Information privacy Qualified, experienced staff and faculty

• • • • • • • • • •

Community involvement in the program’s goals, policies, and outcomes Information provided to faculty about teaching in the distance learning environment Instructor release time for course development Instructor training in distance education pedagogy and technology Course design and delivery assistance Well-designed and appropriate learning materials Student orientation and training Student access to learning resources and instructors Technical support for instructors and students Technology plan to communicate goals to all users

THE PRACTICES PHASE OF THE RPR CYCLE With the right resources in place, the stage is set for dramatic distance learning performance. At this point, the spotlight shifts from the institution to the instructor. Quality distance teaching begins with the careful design of courses, materials, and learning activities. Next, the instructional practices employed during instruction will aim at developing independent learners with the ability to transfer their learning to novel situations. Throughout the course, effective communication and community building are essential foundations for all events.

Course Design Practices Course design is a series of decisions regarding objectives and the most effective methods to ensure that students accomplish the objectives. Distance course design requires the methods to be effective in a technology-mediated environ-

Distance Education Success Factors

ment. The requirements of the curriculum and the needs of the students lead the technological decisions in a well-designed course. A balance of comfort, control, and challenge can be difficult for distant instructors to achieve, and depends on psychosocial rather than academic strategies. The focus is on the needs of learners and the learning process, rather than on content. The quality service approach emphasizes the course structure and interactions in order to supply flexible scaffolding to learners as needed (Vaughan, 2000).

Communication Practices Because learning is an interactive activity and constructed socially, a key to success lies in communication between students and others. A quality benchmark is to involve students in communication during 50% of the time they spend on the course. Frequent and active communication with the instructor, fellow students, or experts in the subject is essential in making students feel that they are part of the community of learners. Interaction in a distance learning course is most effective when it occurs through a variety of media, when it occurs with a variety of sources, and when it is integrated into the overall course design. Interactions are most effective when experienced within the context of other course activities. Communication in a course has the greatest value for students when it authentically approaches the kinds of communication students will experience beyond the course.

Instructional Practices Successful distance educators understand that motivation is among the most important factors in promoting student learning. At the outset, instructors must clearly state the benefits of learning the course content to the student. The course activities should foster both knowledge

construction and content understanding through active learning.

Success Factors for the Practices Phase • • • • • · • • • • • •

Focus on content and students Relevant and important skills and knowledge addressed in courses Structured information presented in motivating context Social strategies to promote student comfort, control, and challenge Fast feedback from instructors to students Consistent design throughout each course Highly interactive activities for student engagement Authentic communication among students, instructors, and experts Course activities designed to maximize student motivation Activities focused on high-level cognitive skills Development of information literacy Development of applied technical skills

THE RESULTS PHASE OF THE RPR CYCLE The only way to know whether a distance education program has achieved quality is to compare the program results to established quality benchmarks. Measures of quality are tied to institutional goals and account for the specific context of the program. To maintain success, a distance education program evaluation must account for institutional and instructional factors, as well as student factors. Evaluation of course and program results is a continual process that involves all stakeholders and requires a wide range of tools.

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Distance Education Success Factors

Assessing Learning

distance education program is offered by a high school, a traditional institute of higher education, or dedicated distance education provider. The public needs information to help them distinguish among the accrediting bodies and the quality control they provide (Council of Regional Accrediting Commissions, 2000; Distance Education and Training Council, 2000; Web Based Education Commission, 2000).

When experiencing quality learning, students shift roles from audience to actors as they acquire skills and display their abilities. The display of student abilities is the most important result of distance education. In the course of developing their abilities, successful students manage their learning by engaging in frequent self-assessment (Palloff & Pratt, 1999). Using varied assessment methods is a key to student assessment that gives an accurate picture of student abilities.

Success Factors for the Results Phase

Program Review

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Evaluation of course effectiveness by students is most useful when it is an ongoing feature of the course. Participation of students, instructors, and the institution is needed to determine the quality of the distance education program. Students should have the opportunity to offer feedback regarding their access to learning activities, course delivery, and technical support (Palloff & Pratt, 1999). The intended program outcomes must undergo review at the institutional level to ensure their clarity and their appropriateness to students who move into work or higher learning roles. Learning outcomes for distance education programs should be clear to instructors and students. Achievement of outcomes in specific courses should be observable and measurable against a known scale or set of criteria.

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Accreditation Accreditation gives an institution a seal of quality because educational standards have been met. A student who expects a distance education course to transfer to another school must be sure that a regionally accredited institution offers the course. Institutions with distance education programs approach accreditation in several ways. The accreditation process varies according to whether a

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• • • • • • • •

Student independence developed through opportunities for self-assessment Peer review of student work as a professional experience Creation of student portfolios to showcase accomplishments Varied assessments for an accurate view of student abilities Open-ended assignments to increase thinking skills and reduce cheating Secure online testing Ongoing course evaluation by students Evaluation of program by students and faculty Review of program outcomes and components by all stakeholders Program accreditation

FUTURE TRENDS Distance education technology and practice will continue to evolve, necessitating ongoing research into effective practice. The lines between distance and traditional education will blur as the points along the continuum become more finely refined in response to education customized to specific needs and contexts. Developers and learners will need more information to help them make the best choices.

Distance Education Success Factors

CONCLUSION A strength of distance education is its potential to focus the learning process on the student. Courses and programs that emphasize their focus on the student’s strengths and needs will succeed in attracting students. In order to build their reputations and keep students, courses and programs must reach quality goals. High-quality distance education achievement is the outcome of the dedication of all constituents in the continual quest for the best possible resources, practices, and results. With an increased need for new career skills and improvement in delivery technology, distance education students will demand evidence of quality and authenticity in distance courses. It is imperative that distance education providers implement and review quality benchmarks regarding RPR in response to the needs of students, employers, and the community. Educational institutions must take the lead in developing and maintaining standards, and they must clearly communicate those standards to the public. When students benefit from an education program that meets their needs, the community benefits, as well.

REFERENCES Barker, K. (1999). Quality guidelines for technology-assisted distance education. Washington, D.C: U.S. Department of Education Office of Learning Technologies. Bruce, B., Fallon, C., & Horton, W. (2000). Getting started with online learning. Macromedia, Inc. Retrieved from http://www.macromedia. com/learning/online_learning _guide.pdf Cavanaugh, C. 2001. The effectiveness of interactive distance education technologies in K-12 learning: A meta-analysis. International Journal of Educational Telecommunications, 7(1), 73-88.

Council of Regional Accrediting Commissions (2000). Statement of the regional accrediting commissions on the evaluation of electronically offered degree and certificate programs and guidelines for the evaluation of electronically offered degree and certificate programs. Retrieved from http://www.ncacihe.org/resources/draftdistance guide/ Distance Education and Training Council (2000). Accreditation standards. Retrieved from http:// www.detc.org/content/ accredStandards.html Educational Development Associates (1998). What quality distance learning courses for an institution? Las Cruces, MN. Fredericksen, E., Peltz, W., & Swan, K. (2000). Student satisfaction and perceived learning with online courses: Principles and examples from the SUNY learning network. Journal of Asynchronous Learning Networks, 4(2). Institute for Higher Education Policy (2000). Quality on the line: Benchmarks for success in Internet-based distance education. Washington, D.C. Johnstone, S. (2001). Does accreditation really mean accredited? Syllabus, 14(6), 22. Kearsley, G. (2000). Online education. Belmont, CA: Wadsworth/Thomson Learning. Mantyla, K. (1999). Interactive distance learning exercises that really work. Alexandria, VA: American Society for Training and Development. Moore, M. (1989). Effects of distance learning: A summary of the literature. Washington, D.C: Office of Technical Assessment. Moore, M., & Thompson, M. (with Quigley, A., Clark, G., & Goff, G.) (1990). The effects of distance learning: A summary of the literature. Research monograph no. 2. University Park, PA: The Pennsylvania State University, American Center for the Study of Distance Education.

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Distance Education Success Factors

Palloff, R., & Pratt, K. (1999). Building learning communities in cyberspace. San Francisco: Jossey-Bass Publishers. Southern Regional Electronic Campus (2000). Principles of good practice. Retrieved from http://www.srec.sreb.org/student/ srecinfo/principles/principles.html

KEY TERMS Accreditation: Endorsement of quality performance by an outside agency. Course Design: Decisions regarding objectives and the most effective methods of ensuring that students accomplish the objectives.

U.S. Department of Commerce (2000). Falling through the net: Toward digital inclusion. Washington, D.C.

Distance Education: A teaching and learning system in which learning occurs in a time and/or place distant from the instructor.

Vaughan, M. (2000). Summary of quality issues in distance education. Retrieved from http://www. lucent.com/cedl/sumqual.html

Scaffolding: Cognitive and instructional supports for learning built into course design.

Web-Based Education Commission (2000). The power of the Internet for learning. Washington, D.C: U.S. Department of Education. Wilkes, C., & Burnham, B. (1991). Adult learner motivations and electronics distance education. American Journal of Distance Education, 5(1), 43-50.

Standards: Benchmarks for quality performance. Strategic Plan: A process by which quality will be improved and maintained in meeting the goals of the organization. Technology Plan: Goals and benchmarks for technology systems and support in an organization.

This work was previously published the Encyclopedia of Information Science and Technology, edited by Mehdi Khosrow-Pour, pp. 897-901, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 1.60

Interactivity in Web-Based Learning Adams Bodomo The University of Hong Kong, Hong Kong

ABSTRACT

INTRODUCTION

This chapter discusses one of the main features of ICT—interactivity. Drawing from many years of Web-based course design and delivery at the University of Hong Kong, it is argued that enhanced interactivity is the single most important reason why teachers should practice Web-based teaching. The notion of conversational learning community (CLC) as a kind of constructivist learning environment is introduced. It is shown that instructional interactivity, defined as active communication in a conversational learning community between instructor(s), learners, course materials, and links to remote experts and resources, is a central aspect of the learning situation. A practical implementation of the CLC model is presented through describing the interactive features of a Web-based course using WebCT. It is concluded that Web-based teaching actually enhances interactivity both within and beyond the classroom setting.

At the beginning of the 21st century, we are faced with an age of rapid technological development in information and communication. Issues of educational reform never have been more urgent than now. One of the major challenges is how to design our educational system, in general, and our methods of instruction, in particular, in order to produce graduates who are better prepared to take up jobs in a knowledge-based environment characterized by a pervasive use of information communications technology (ICT). ICTs, especially modern digital ones, include various types of computers; digital cameras; local area networking; the Internet and the World Wide Web; CD-ROMs and DVDs; and applications such as word processors, spreadsheets, tutorials, simulations, e-mails, digital libraries, computermediated conferencing, videoconferencing, and

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

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virtual reality (Blurton, 1999). Four main features of these modern digital ICTs make them stand out as very useful educational tools: integration of multimedia, flexibility of use, connectivity, and interactivity (Blurton, 1999). The main focus of this chapter is an examination of just one of these features: interactivity. While interactivity has been a subject of considerable attention in the search for newer and more active methods of teaching and learning (Allen, 2003; Parker, 1999; Simms, 1999, 2000), there still remains a lot to be discussed as to how it can be enhanced in learning situations involving a mixture of Web-based course administration and face-to-face classroom instruction. It is quite clear that the introduction of ICTs into distance learning curricula is crucial in enhancing interactivity, given the situation where teacher and student are separated by distance. It is shown here, based on experiences with courses designed for both distance learners and traditional face-to-face classroom students, where there is unity of time and unity of venue, that the use of the Web, one of the new digital ICTs enumerated previously, along with other accessories and software that together give us what is termed Web-based teaching in a course, plays a crucial role in enhancing interactivity. This chapter is organized as follows. The section that follows defines interactivity and shows the important role that it plays in constructive/active learning theories. In the third section, the main features of a course designed to achieve interactivity are described, and it is shown how interaction was achieved. The fourth section of the chapter points to certain challenges that should be overcome in order to create more opportunities for enhancing interactivity in Web-based teaching in the future.

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INTERACTIVITY AND ITS ROLE IN CONSTRUCTIVE LEARNING THEORIES What is Interactivity? Studies that focus on interactivity include Daniel and Marquis (1983), Moore (1992), Wagner (1994), Markwood and Johnstone (1994), Laurillard (1993), Barnard (1995), Moore and Kearsley (1996), Parker (1999), Simms (1999, 2000), Bodomo, Luke, and Anttila (2003), and Allen (2003). The key concepts that run through most of these studies include active learning, two-way communication, critical conversation, transactional distance learning (Moore, 1993), and so forth. All these contrast sharply with what would take place in traditional passive/digestive lecture-type instruction. Moore (1992) offers three types of interactivity, while Markwood and Johnstone (1994) provide four types of interactivity. In Moore’s (1992) typology, we have learner-content, learnerinstructor, and learner-learner interactivity. Learner-content interactivity is illustrated by a student reading a book or a printed study guide (Parker, 1999). The interactivity or otherwise of the content is very much a function of how the material is structured and accessed. This point is crucial in deciding how best to place course notes on the Web. Instructor-learner interaction is the core of the teaching process. The success of the course design will depend largely on whether the conversation between teacher and learner is such that the learner can increase self-direction and construct new knowledge or not. Learnerlearner interaction involves students working together to discuss, debate, and attempt to solve problems that arise in their study of the course materials. Moore (1992) provides practitioners with a very useful framework to discuss how interactivity is achieved in teaching. Indeed, his

Interactivity in Web-Based Learning

notion of transactional distance theory (Moore, 1992, 1993, 1996) has contributed immensely in defining relations between participants not only in a distance learning situation but also in traditional face-to-face classroom learning situations. Markwood and Johnstone (1994:94) describe interaction as the “silent, critical, creative conversation within the learner’s mind that is spurred and supported by the learning environment.” The study outlines four different types of interaction that trigger what it calls critical conversation. The first is interaction with media, where individual students scrutinize textbooks, videotapes, or any other course material. In the course to be discussed, this involves a major textbook supplemented by a number of other book sections and course notes. The second is interaction with resources. Here, individual students or groups may collaborate with tools such as those used by professionals, including word processors, electronic libraries, laboratories, and studios. The third type of interaction, according to Markwood and Johnstone (1994), involves interaction with experts. This would mean students conversing with an instructor or other experts in real time. The last type of interaction is one of interaction through electronic exchange, with students electronically or digitally sharing the results of newly formed knowledge over a period of time (Markwood and Johnstone, 1994). Moore (1992) and Markwood and Johnstone (1994), along with more recent works, such as Simms (1999, 2000) and Allen (2003), provide a solid foundation on which to build an idea of interaction and draw up a typology of interaction within the larger framework of what we introduce here as Conversational Learning Community (CLC). In conceptualizing a CLC, we see the pedagogical process as taking place in an interactive conversational learning community. In this community, we have instructor(s), learners, course materials, and links to remote experts and

resources. All these are the core components for the function of instructional interactivity in a CLC. Allen (2003) defines instructional interactivity as the interaction that actively stimulates the learner’s mind to do those things that improve ability and readiness to perform effectively. Interactivity is shown to be the single cementing factor that binds all the elements together in a CLC.

The Role of Interaction in Constructive/Active Learning Theories Theories of learning within education and allied fields such as psychology and cognitive science have proliferated over the years. New pedagogical methods based on these theories are turning away from passive methods of teaching that require no action on the part of the student beyond listening and taking notes to interactive delivery methods that enable the student to control and manipulate the instructional environment. These active and interactive approaches to instruction may be situated within the framework of what may be called constructivist theories of learning. According to Blurton (1999, p. 9), “modern constructivist education theory emphasizes critical thinking, problem solving, ‘authentic’ learning experiences, social negotiation of knowledge, and collaboration—pedagogical methods that change the role of the teacher from disseminator of information to learning facilitator.” Works like Piaget (1973), Duffy and Jonassen (1992), and Strauss (1994) illustrate such new pedagogical theories. So, what is the role of interaction in these theories of learning? I will now briefly mention four of these theories that are considered to be the most relevant. They are the constructivist theory of Bruner, the conversation theory of Pask, Vygotsky’s social development theory, and, of course, Moore’s Transactional Distance Theory (Moore 1993).

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Bruner An exposition of the constructivist theory is contained in the works of Bruner (1966, 1990). According to Kearsley (1994-2004), a major theme in the theoretical framework of Bruner is that learning is an active process in which learners construct new ideas or concepts based upon their current/past knowledge. The learner selects and transforms information, constructs hypotheses, and makes decisions, relying on a cognitive structure to do so. As far as instruction is concerned, the instructor should try to encourage students to discover principles by themselves. The instructor and student should engage in an active dialog (i.e., Socratic learning). The task of the instructor is to translate information to be learned into a format appropriate to the learner’s current state of understanding. The curriculum should be organized in a spiral manner so that students continually build upon what they already have learned. The role of interaction is fairly prominent in such a theoretical conceptualization. Once again, interactivist terms like active process and, active dialogue come to the fore.

Pask The next theory that is of immediate relevance to an interactive approach to teaching is the conversation theory, as contained in Pask (1975). The fundamental idea of the theory is that learning occurs through conversations about a subject matter that serves to make knowledge explicit. Conversations can be conducted at a number of different levels: natural language (general discussion), object languages (for discussing the subject matter), and metalanguages (for talking about learning/language). In order to facilitate learning, Pask argues that subject matter should be represented in the form of entailment structures that show what is to be learned. Entailment structures exist in a variety of different levels, depending upon the extent of relationships displayed (e.g.,

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super/subordinate concepts, analogies). The critical method of learning according to conversation theory is teachback, in which one person teaches another what they have learned. Pask identified two different types of learning strategies: serialists, who progress through an entailment structure in a sequential fashion, and holists who look for higher-order relations (Kearsley, 1994-2004).

Vygotsky The third theory of much relevance to interactive approaches to learning is the social development theory, as conceptualized by Vygotsky (1962, 1978). The major theme of Vygotsky’s theoretical framework is that social interaction plays a fundamental role in the development of cognition. Another aspect of Vygotsky’s theory is the idea that the potential for cognitive development is limited to a certain time span, which he calls the zone of proximal development (ZPD). Furthermore, full development during the ZPD depends upon full social interaction. The range of skills that can be developed with adult guidance or peer collaboration exceeds what can be attained alone (Kearsley, 1994-2004).

Moore The fourth theory is Moore’s (1992, 1993, 1996) notion of transactional distance theory , which is very much relevant to distance education and attempts to explain the relations between participants in a distance learning situation. Transactional distance is defined to include the psychological and communicative space between learners and teachers. Moore (1993) highlights the issue of interaction when he defined transactional distance within the context of interaction in a course as a function of dialogue, structure, and learner autonomy. Dialogue refers to teacher-student interaction; structure refers to how the program is designed; and, according to Moore, as dialogue increases, structure decreases (i.e., as the interaction between

Interactivity in Web-Based Learning

learner(s) and teacher(s) increases, the teaching programs structure of objectives, activities, and assessment decreases) to accommodate learners’ needs. In other words, learner autonomy leading to self-direction becomes a major fruit in interactive learning situations. With terms like active dialogue, conversations about subject matter, and social interaction resonating across these theories, it is clear that interactivity has a central role to play in these theories of learning, which all may be grouped under the general framework/paradigm of constructivist methods of learning, as previously described.

Indeed, these four theories may be seen as forming a useful foundation for the idea of Conversational Learning Community (CLC) that we evolve as a conceptual framework for designing Web-based courses. Terms like active dialogue, conversations about subject matter, and social interaction form the core of what we may term a conversation learning theory (Figure 1). The main idea of a conversation learning theory is that enhanced interactivity, whether face-to-face or from a distance, such as online instruction, would lead to an effective reciprocal, two-way communication within the learning situation. This enhanced communication is the backbone for the

Figure 1. Conversation learning theory licenses conversation learning community

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efficient exploitation of the resources, experts, and links by both instructor and learners within the learning community.

A DESCRIPTION OF THE DESIGN OF A WEB-BASED COURSE In the last sections, a number of issues, including the need to use ICT in education, Web-based teaching, and interactivity, and its role in constructivist teaching methods have been addressed. This section of the entry constitutes a description of a specific course within my Web-based teaching program and how interactivity was achieved in the course design.

Choosing a Web-Based Course Tool In deciding to do Web-based teaching or to facilitate Web-based learning, course designers have at least two options. They can choose to develop their own tools, or they can choose from the repertoire of many course tools called asynchronous Web-based software suites (Jackson, 1999-2004) that are already available on the market. As an illustration of interactivity, I now concentrate on describing just one course on the relationship between Language and Literacy. The course is titled Language and Literacy in the Information Age (Bodomo, 1999-2004).

WebCT Design of a Course on Language and Literacy The Language and Literacy course is a one-semester, six-credit course for second- and third-year students of Linguistics and related disciplines. Class meetings are conducted in the form of lectures, complemented by a WebCT course platform and face-to-face tutorials. In terms of course contents, it usually begins with an attempt to introduce the students (usually about 20 to 30 in number)

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to the concept of literacy. The course materials, lectures, and tutorials are designed in such a way that students are supposed to discover for themselves that the concept literacy is not limited to just the ability to read and write. Students are supposed to discover for themselves the various linguistic, cognitive, social, and educational issues surrounding the concept. Students are encouraged to gain an understanding of the role of language and literacy in the socioeconomic development efforts of many societies through various activities such as discussions, debates, classroom presentation, tutorials, fieldtrips, interview of resource persons, and so forth.

How Interaction was Achieved in the Course In this subsection, an attempt is made to explain how interaction was achieved in a class. This begins with the creation of a learning community. The course design, whether in the form of face-to-face classroom lectures or WebCT course page activities like discussion and presentations, is guided by the conceptual notion of a conversational learning community comprised of instructor(s), learners, current resources, remote experts, and resources. The first task, then, in the course administration is often to get the group of about 20 to 30 students to communicate and interact with each other and to create a sense of community. The first exercise toward this goal is often in the form of Internet search. The following excerpt from the course explains the exercise: An Exercise for Building Up a Learning Community LING2011: Reading Assignment/Homework 1.

Literacy Information Mining on the Web:

Interactivity in Web-Based Learning

Students should form groups of two to three people. Each group should search the World Wide Web with keywords literacy, language, and combinations of these, and should choose 10 sites. These sites should be analyzed with a view to finding out what literacy is and what common issues are discussed concerning language and literacy courses. Each group of students should spend five minutes in the next lecture explaining how their understanding of literacy has been affected by these 10 Web sites. Students are asked to look up on the Web important concepts in the course like literacy and language and present their findings to the whole class in the lecture the following week. After hearing students’ reports on their findings, the course instructor and teaching assistant would pick up a number of issues from these student presentations and initiate both an in-class debate and, later on, some postings on the WebCT bulletin board in order to encourage participation from students who are less active in lectures. This exercise is meant to encourage students to create both physical and electronic networking among each other, and it often succeeds to a large extent, because it has been noticed that later groups that are formed in the class often reflect this earlier grouping. In addition, this exercise often leads to follow-up discussions in small groups during the first two weeks. Following this exercise, students also are encouraged to create a sense of community through sharing their research findings with their classmates by using the student homepages tool. In addition to sharing their findings, many students actually made available information about themselves, which enabled their classmates to get to know their study interests and specializations. This helped to strengthen the community of partnerships in learning. Once this sense of community is created, the rest of the instructional activities aim to consoli-

date and to strengthen it, developing it into a real conversational learning community. This is done both through face-to-face classroom activities and WebCT design activities. Surprisingly, greater and more sustained aspects of the interaction between students often take place on the WebCT homepage for this course. In the next subsection, some of the main features and resources of this tool will be described, showing what kinds of interactivity take place and how.

Some Interactive WebCT Features of the Course WebCT interactive tools include modules such as Contents, Glossary, Bulletin Board, Student Homepages, and Quiz. We next provide brief descriptions of some of the interactive modules, showing what activities are deployed in each case.

(1) Contents With Glossary Definitions The Contents with Glossary Definitions module of WebCT serves as a kind of online dictionary for the students. Terminologies and other technical phrases on Language and Literacy easily pile up even at the very beginning of the course, and they are very crucial for a sustainable comprehension of the subject matter. This aspect of the course tool thus comes in handy, as the teacher often can use it to outline and to define some of the most important terminologies for each topic. Students are asked to regularly refer to this site as they read through the lecture notes. The reading, then, is more active than would otherwise be the case.

() Links to Useful References The Links feature of WebCT allows a course developer to make useful pointers to various Web sites that are of relevance to the course; for instance, Literacy Online. This issue of making

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links implements the conceptual notion of having remote resources as part of the conversational learning community that we create, illustrating learner-resource interaction, one of the types of interactivity we noted earlier.

() Student Access Statistics The Student Access Statistics feature is a very valuable aspect of WebCT in terms of helping the teacher to track and to manage student progress. Each time a new course material is posted on the Web, the teacher may demand that students read the material before the next scheduled class. Before the start of the class, the teacher may log on to assess how many students already have accessed and, presumably, read the material. This can be gauged by looking at the number of students logging on and also by what pages they visited. Indeed, one could even have an idea of which particular students accessed the material and their frequency of access. It turned out, however, that sometimes, actually more students had accessed the pages than the access statistics indicated. Some students simply asked their friends to download copies of the material for them without accessing the material themselves from their own accounts. One way to solve this problem, if it is thought of as such, is for the teacher to actively discourage this oblique access to the course material on the Web.

() Discussion Forum WebCT’s Bulletin Board and Presentation feature together provide a useful discussion forum for participants in the Language and Literacy course. This, indeed, is the most useful feature with respect to incorporating interactivity (both teacher-learner and learner-learner interactions) in the course. Through the bulletin board, one readily can send information to the class and to individual students about the course. These include reminders of deadlines for assignments,

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clarifications about specific points, and pointers to any errata in the course notes. Students, on the other hand, can use this forum to ask the teacher questions about aspects of the course and to post general messages to other students on the course. Groups of students can use the presentation forum to upload and to discuss a topic, which they subsequently may write up and present to the whole class.

OPPORTUNITIES AND CHALLENGES FOR THE FUTURE Opportunities The foregoing has outlined how a course can be designed on WebCT in order to enhance interactivity, a crucial element in a conversational learning community and, indeed, in any other effective learning situation. A possible question to ask, then, is how successful was the design. Success, failure, and other issues of evaluation are difficult to measure accurately. They may be from the point of view of the instructor or the student. In the following, we briefly point to some qualitative features that make one think that, from an instructor’s point of view, interactivity has been achieved in the course. From an instructor’s point of view, certain features of communication and academic activity, if they are part and parcel of a course, would serve to indicate that the teaching endeavor was successful. Three of these features include critical thinking, initiative on the part of students, and academic rigor.

() Critical Thinking It was noticed that, as time went on, not only were students more forthcoming in discussing and interacting with the teacher and with their fellow classmates, but they were also becoming more critical in their thinking. At certain points during

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the course, students were beginning to question and argue some of the points from the teacher and from their fellow classmates. Sometimes, an issue was presented with regard to the definition and conceptualization of literacy and how it relates to language, and students were then asked to evaluate these views by applying them to the Hong Kong situation and, indeed, other situations that they know. We may consider critical thinking within the conversational learning community as a strong indicator of the success of interactivity in the learning situation. This may be compared with Markwood and Johnstone’s (1994) idea of critical conversation.

() Initiative Another indicator of success with regard to the learning situation is initiative on the part of students. Halfway through the course, students often introduced their own topics of discussion and techniques of information gathering and processing. In our knowledge-based economy, innovation has become a crucial element of an efficient workforce. Initiative is an essential element of innovation, and the pedagogical process should aim at promoting it. This may be compared to Moore’s (1993) ideas of learner autonomy and self-direction, which are products of a successful interactive learning course.

() Academic Rigor A third measure of the fact that the class achieved an enhanced constant interaction was the academic rigor noticed in the essays that many of the students wrote. Students often were generally very knowledgeable about the different shades of opinions regarding a particular technical issue. Indeed, some students even began to question some aspects of the textbooks against the realities of the Hong Kong situation that they know best. In the course evaluation at the end of the semester, comments and feedback generally point to a positive

appraisal of the element of enhanced interactivity in the Web-based learning process.

Challenges In the course of Web-based design of the course on Language and Literacy in the Information Age and, indeed, in other courses, a number of issues such as low interactivity at the beginning of the course were experienced. Rather than perceiving them as problems and obstacles, one should consider them as challenges to be overcome toward an improvement of Web-based teaching.

() Low Written Interaction at the Beginning Described previously are some initial steps taken to ask students to form groups and to begin interacting with each other. However, it is often difficult to get them to start writing and sending messages of discussion on the bulletin board. Indeed, some students never posted a single message throughout the course, although they may have read every bit of discussion going on. Several postings often were made without any responses. In these postings, questions are asked, and students are exhorted to start making use of the forum. The interesting aspect here is that it takes just a few students to begin, and most come on board. In extreme situations of low participation, students are reminded that active participation counts toward the course grade.

SUMMARY AND CONCLUSION This chapter has attempted to demonstrate that interactivity is an essential aspect of studentcentered course design endeavors, whether in traditional face-to-face classrooms or by distance learning. Society seems to require universities and other learning institutions to produce graduates who are creative thinkers and problem solvers and

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graduates who are literate enough to function well in a knowledge-based economy where there is a pervasive use of ICTs. To achieve this educational goal, we need to reform our methods of instruction, moving away from more passive methods of teaching to more active and interactive methods. Based on many years of Web-based course design and delivery, this chapter has proposed some ways to design more interactive courses. Basically, teachers ought to construe their learning environment as one of conversation between instructor and learner. Important components in this environment include instructor(s), learners, course materials, and links to remote experts and resources. All these components are glued together by instructional interactivity. Three types of instructional interactivity ought to be recognized. These are instructor-learner, learnerlearner, and learner-resource interactivity. While there still remain some challenges, it has been shown that by doing interactive Web-based teaching, many positive things, such as critical thinking, initiative, and academic rigor, may be achieved. We may conclude that interactivity on the Web seems to enhance even traditional classroom and tutorial sessions. Interactive Webbased teaching allows teachers to achieve a better management of the course. This issue is relevant for both distance education (i.e., in cyberspace) and traditional classroom teaching. Interactivity thus has the potential of rendering redundant the gap between traditional face-to-face classroom education and distance education. Distance no more would have to be defined in terms of just space but in terms of the presence and absence of interactivity.

REFERENCES Allen, M.W. (2003). Michael Allen’s guide to elearning: Building interactive, fun, and effective learning programs for any company. Hoboken, NJ: John Wiley.

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Barnard, R. (1995). Interactive learning: A key to successful distance delivery. The American Journal of Multimedia, 12, 45-47. Blurton, C. (1999). New directions of ICT-use in education. UNESCO’s World Communication and Information Report 1999. Retrieved from http://www.unesco.org/education/educprog/lwf/ dl/edict.pdf Bodomo, A.B. (1999-2004). Language and literacy in the information age. WebCT Retrieved from http://ecourse.hku.hk:8900/public/LING2011 Bodomo, A.B., Luke, K.K., & Anttila, A. (2003). Evaluating interactivity in Web-based learning. Global E-Journal of Open, Flexible and Distance Education, III. Retrieved from http://www.ignou. ac.in/e-journal/ContentIII/Adamsbodomo.htm Bruner, J. (1966). Toward a theory of instruction. Cambridge, MA: Harvard University Press. Bruner, J. (1990). Acts of meaning. Cambridge, MA: Harvard University Press. Daniel, J., & Marquis, C. (1983). Independence and interaction: Getting the mix right. Teaching at a Distance, 15, 445-460. Duffy, T., & Jonassen, D.H. (1992). Constructivism and the technology of instruction: A conversation. Hillsdale, NJ: Lawrence Erlbaum. Jackson, R.H. (1999-2004). Web based learning resources library. Retrieved from http://www. knowledgeability.biz/weblearning Kearsley, G. (1994-2004). Explorations in Learning & instruction: Theory in practice database. Retrieved from http://tip.psychology.org/ Laurillard, D. (1993). Rethinking university teaching: A framework for the effective use of educational technology. London: Routledge. Markwood, R., & Johnstone, S. (1994). New pathways to a degree: Technology opens the college. Boulder, CO: Western Cooperative for Educa-

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tional Telecommunications, Western Interstate Commission for Higher Education. Moore, M. (1992). Three types of interaction. The American Journal of Distance Education, 3(2), 1-6. Moore, M. (1993). Theory of transactional distance. In D. Keegan (Ed.), Theoretical principles of distance education. London: Routledge. Moore, M., & Kearsley, G. (1996). Distance education: A systems view. Belmont, CA: Wadsworth. Parker, A. (1999). Interaction in distance education: The critical conversation. Education Technology Review, 13. Pask, G. (1975). Conversation, cognition, and learning. New York: Elsevier. Piaget, J. (1973). To understand is to invent. New York: Grossman.

Simms, R. (1999). Interactivity on stage: Strategies for learner-design communication. Australian Journal of Educational Technology, 15(3), 257-272. Simms, R. (2000). An interactive conundrum: Constructs of interactivity and learning theory. Australian Journal of Educational Technology, 16(1), 45-57. Strauss, M.J. (1994). A constructivist dialogue. Journal of Humanistic Education and Development, 32(4), 183-187. Vygotsky, L.S. (1962). Thought and language. Cambridge, MA: MIT Press. Vygotsky, L.S. (1978). Mind in society. Cambridge, MA: Harvard University Press. Wagner, J. (1994). Learning from a distance. The International Journal of Multimedia, 19(2), 12-20.

This work was previously published in the International Journal of Web-Based Learning and Teaching Technologies, Volume 1, Issue 2, edited by Liliane Esnault, pp. 18-30, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 1.61

We’ll Leave the Light on for You: Keeping Learners Motivated in Onine Courses Vanessa Paz Dennen Florida State University, USA Curtis J. Bonk Indiana University, USA

INTRODUCTION Motivating online learners is a key challenge facing instructors in both higher education and corporate settings. Attrition rates and low participation levels in course activities are frequent instructor complaints about online learning environments. Part of the problem is a lack of sophistication in online tools and courseware (Bonk & Dennen, 1999). Added to this problem is that, even when tools exist for engaging and motivating students, instructors lack training in how to effectively use them. Instructors not only need to know the types of online and collaborative tools for engaging students, but also how to embed effective pedagogy when the technologies are weak. Consider for a moment a traditional classroom. Why do students attend their classes? Perhaps their presence is being recorded by the instructor, or perhaps they are particularly interested in the

topic. Regardless, upon enrolling in a face-to-face course, learners are aware that they are expected to devote significant blocks of time each week to that course. But why do students participate in face-to-face course activities? To start, they already are seated in the classroom, so they may as well participate. Additionally, the effects of instructor modeling of desired activities and peer participation can motivate the reluctant learner to become more active. In the online class, attendance is distinctly different. Unless explicitly told how their attendance will be noted, such as through a minimum number of messages posted per week, online learners do not know how or if their course participation will be determined. Consequently, online students turn to required assignments outlined in the course syllabus (Dennen, 2001). The end result is that students complete the basic graded components of the course, but little more.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

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Learner participation in an online class has sometimes been called an “act of faith” (Salmon, 2000). Key problems learners encounter include not knowing participation expectations, not feeling comfortable engaging in activities with people they have never met, and not having enough time to participate in activities. Whereas these first two reasons are clearly linked to motivation, the time factor is also related since highly motivated students will typically budget adequate time to participate. In reviews of the research on motivation, certain key strategies are consistently found to be effective in conventional classrooms. For instance, effective instructors create a supportive but challenging environment, project enthusiasm and intensity, provide choice, create short-term goals, and offer immediate feedback on performance settings (Pintrich & Schunk, 1996; Reeve, 1996; Stipek, 1998). As these researchers have shown, instructors might also attempt to stimulate student curiosity, control, and fantasy. Naturally, they should make content personal and concrete by using relevant and authentic learning tasks and by allowing learners to create and display finished products. Finally, instructors should foster interaction with peers, create fun and game-like activities, embed structure as well as flexibility in assignments, and include activities with divergence or conflict. Many of these principles relate to the highly regarded learner-centered psychological principles from the American Psychological Association (1993) and can be incorporated in Web-based instruction (Bonk & Cummings, 1998). In a recent Delphi study of top distance learning experts in the United States, many of these same principles (i.e., relevancy, authenticity, control, choice, interactivity, project-based, collaborative, etc.) were identified as key indicators of effective online learning environments (Partlow, 2001). If so much is known, why are online courses often suffering from a lack of motivational elements? Problems exist in part because instructors

are unsure of how to manipulate this instructional medium, and in part because adequate instructor support is not yet available. According to recent surveys of college instructors and corporate trainers (Bonk, 2001, 2002), the proliferation of Web courseware and training programs has yet to match the pedagogical needs of higher education and industry. When corporate respondents were asked about various intrinsic motivational techniques, activities such as job reflections, team projects, and guest mentoring were considered highly engaging and useful online. When asked about tools and activities that were more motivational for adult learners in the workplace, respondents favored Web-based learning that contained relevant materials, responsive feedback, goal-driven activities, personal growth, choice or flexibility, and interactivity and collaboration. Unfortunately, such techniques were rarely used online. According to the findings of these surveys, the motivational climate of online instruction is currently deficient. Therefore, in addition to the evaluation of student learning and completion rates, organizations should step back and evaluate the motivational characteristics embedded within their courses. Of course, there also is a need for further research here since the key motivational principles for online training are only starting to emerge. As Bonk and Dennen (2003) contend, online instruction is not a simple task; most instructors still do not understand how to adapt different technology tools to engage their students. At the same time, few designers of e-learning tools have thoroughly considered the motivational or pedagogical principles behind adult learning (Firdyiwek, 1999; Oliver, Omari, & Herrington, 1998). How can such tools motivate adult learner participation while fostering student thinking and collaboration? And what can be done to motivate learners in online environments? These questions must be addressed in order for online education to thrive and be a positive learning experience for students.

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This chapter focuses on 10 key elements for motivating online learners. Each element is discussed separately, along with corresponding course activities that can be used to address that element. Indeed, it is possible to address multiple motivational principles with one well-designed activity (see Table 1). At the same time, not every instructional situation calls for the use of each motivational element. Context-based instructional design and pedagogical decisions should always be made by the individual instructor.

purpose, one is not likely to participant actively in that space. Social ice-breaking activities can be used to set the tone of an online class as well as to help learners become acquainted with one another. They also serve the purpose of familiarizing learners with the course tools without the stress of dealing with course-related subject matter. Some activities that might be employed include: Two truths and one lie: Everyone must post two truths and one lie about themselves. Fellow classmates then try to determine which one is the lie. This activity generates a series of messages and responses, and is a quick way to bring out learner personalities (Kulp, 1999). 8 nouns: In this activity, everyone is required to post eight nouns that describe him or herself. Near the end of this task, it becomes difficult to come up with nouns, thereby forcing participants to share a good deal of information about themselves that their peers as well as the instructor might

•

TONE/CLIMATE The tone or climate of an online class is set at the beginning. These opening moments have the potential to engage and interest learners so that they want to be active participants for the semester, or alternatively to isolate them and provide little motivation to participate (Salmon, 2000). Much like in the physical world, if one visits an online location and finds little reason to go back, feels uncomfortable in that place, or is uncertain of its

•

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9. Critical Friends and Peer Feedback Buddies

10. Gallery Tours

8. Debates and Role Play

7. Electronic Guest Lectures

X X X X

X

6. Brainstorming

X X X X

5. Conference Tracks

4. Cases

1. Tone/Climate 2. Feedback 3. Engagement 4. Meaningfulness 5. Choice 6. Variety 7. Curiosity 8. Tension 9. Peer Interaction 10. Goal Driven

2. Self-Assessments

Motivational Element

1. Ice Breakers

Online Activity 

3. Surveys and Polling

Table 1. Motivational elements addressed by different online activities

X

X X

X X

X

X X X X

X X X

X X X

X X

X X X X X

X X

X X

X X X

X X

X

X X

X

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•

refer to later in the course. In effect, it creates some initial shared understandings and common knowledge (Schrage, 1990). Coffee house expectations: In this activity, students share their expectations for the class—why they enrolled and what they hope to get out of it. Not only does this activity help the instructor shape the class, it is vital for the goal-oriented behavior of adult learners. In effect, posting expectations gives adults with chaotic schedules something definitive to work toward. As an extension, students also can be asked to share what they have to offer to the class community.

These activities are often fun ways of sharing personal information. While learners may not share this much personal information at the beginning of a traditional course, in an online course it is a way of discovering student commonalities and differences. From our experience, both instructors and learners tend to refer back to the messages generated by these activities to get a better sense of who their classmates are. Using the eight nouns activity, for instance, we have had males describe themselves as “knitters,” “tea kettles,” and “dishwashers.” Such comments have made for interesting, and often humorous, social interactions in each of these courses. Research by Dennen (2001) indicates that the instructor should model the expected responses to such activities. An instructor, for instance, might post eight nouns about himself so that learners can know him better. Just as the learners need to know who their peers are, they need to know that their instructor is more than a name.

FEEDBACK Feedback motivates online learners by letting them know how well their performance meets course expectations. Monitoring one’s progress toward a goal is motivational to many students

(Anderson, 2001). Whereas feedback points are typically built into all courses in the form of graded assignments, in an online class, students often feel the need for feedback at other, more formative points in time. This feedback helps them gauge their own performance and motivates them to either maintain or improve the quality of their work. Feedback may come in many forms: •

•

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Self-assessments: Self-assessments can easily be built with most courseware tools, thereby allowing the technology to control the feedback. Reading reactions: Discussion activities in which learners post their reactions to course readings are useful because they allow the learners to know if they are on-track, and let the instructor know if the learners understand the material. Additionally, learners are more motivated to do the required readings if they know they must discuss them. Peer feedback opportunities can be built into such activities, making sure all learners get a response in a manner that is pedagogically beneficial, yet not labor intensive for the instructor. Instructor feedback: Feedback to instructors is also critical to online course success. Instructors, for instance, might have anonymous suggestion boxes on the Web. Watson (2000) recommends that the instructor post the suggestions as well as the corresponding decisions for learners to read. Similarly, Brown (2002) indicates that one-minute reflection and muddiest point papers using e-mail or threaded discussion forums also are highly effective in providing formative course feedback.

ENGAGEMENT Motivated learners are engaged learners. While all of the motivational methods mentioned in this

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chapter are in some way engaging, electronic voting and polling is one technique that can be used to engage learners at the beginning of a new unit of instruction. An instructor might survey class attitudes on an upcoming topic using a free survey tool such as Zoomerang, SurveyShare, or SurveyMonkey, and keep the results sealed until an appropriate point during the instruction. The instructor might then use the results to engage learners in a discussion of the minority point-ofview and then have learners revote or self-assess whether their attitudes have changed as a result of the discussion or additional course instruction.

MEANINGFULNESS Extensive research points to the importance of task meaningfulness and problem-based learning (Singer, Marx, & Krajcik, 2000; Williams, 1992). Simply put, people want to participate in activities that they deem meaningful, authentic, and relevant (Blumenfeld et al., 1991; Savery & Duffy, 1996). In the traditional classroom, meaningfulness is important, but an instructor still can corral students to participate just because they are physically present. In contrast, in the online class, meaningfulness might make the difference between participation and non-participation. Online activities that are meaningful to students often involve real-world scenarios and allow learners to discuss or present their own opinions and experiences relative to these scenarios. For example, students might be asked to post reflection statements that relate their job or field experiences to the concepts being learned. They also might be asked to develop written cases that exemplify a concept, and then respond to the case of a peer with a possible solution or alternative perspective (Bonk, Daytner, Daytner, Dennen, & Malikowski, 2001; Bonk, Hara, Dennen, Malikowski, & Supplee, 2000). Such meaningful and motivating activities give learners an opportunity

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to practice and apply what they know with peers around the globe.

CHOICE Helping students make a personal investment in a course is one way of providing motivational support (Maehr, 1984). Giving learners choices allows them to be active participants and feel in control of some aspect of their learning environment (Bonk, Fischler, & Graham, 2001). It also demonstrates that the instructor is aware that the learners have entered the learning situation with their own personal goals. Online classes can be highly designed experiences wherein learners feel they have no choice and must follow the course outline in a lockstep order. Fortunately, there are many ways in which choice may be built into an online experience. Using a motivational perspective, learners may be given the opportunity to select which discussion topics they wish to participate in. In some cases, they may even be asked to help develop the discussion topics as appropriate. Learners might also sign up for leadership roles in the weekly discussion according to personal interests and expertise (Hara, Bonk, & Angeli, 2000). Similarly, the selection of roles or personalities for online role play gives the learners a sense of control over their learning environment as well as an opportunity to be creative and spontaneous. Some classes might use a conference track approach, in which parallel sets of course requirements are proposed, each addressing a slightly different focus. Learners can then choose to fulfill the requirements that most closely match their goals or interests.

VARIETY Repeating the same set of online tasks for each course activity or module will be boring for

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learners. Our experience indicates that learners enjoy variety in online courses—knowing that there is something new for them to master keeps them alert and attentive as well as interested. Thus, instructors should select a range of different online activities rather than redundantly relying on the same ones. Brainstorming is one simple activity that can interject new life and variety into a course. Learners can be asked to generate as many ideas as possible on a particular topic, without worrying about backing them up, demonstrating the applicability or practicality of the ideas, or ranking them in any way. The results of a brainstorming session might be topics or activities to be addressed or completed later in the course. Collecting multiple class responses, instead of allowing some students to dominate discussion or team projects, is another way to vary the course activities. To really make the course spontaneous, an instructor might utilize “just-in-time teaching” or a “just-intime syllabus” (Novak, 2000). In this technique, the course skeleton is completed at the start of the semester, but can be modified in response to student interests and course performances as well as current events.

CURIOSITY Learner curiosity should be cultivated in an online course, including allowing them to explore ideas beyond those expressed by the instructor. If all learners look to the instructor for answers, their curiosity can only be addressed through limited perspectives. To spark learner curiosity and bring in additional viewpoints, electronic guests may be invited into the online class for short, synchronous chat sessions, some with follow-up asynchronous discussions with those who seek further information. Along these same lines, learners may be mentored electronically by peers or practitioners to help bring in diverse perspectives.

TENSION Points of tension are points of discussion; if we all agree then we probably have little to discuss. The term “tension” frequently has negative connotations, but it can be used to generate fruitful learning discussions. Students, however, may not elect to engage in tension on their own, so debates and assignments that involve role play dialogues can be particularly useful to generate tension in a manner that feels safe to students. Frequently, when students are assigned roles that promote unpopular points of view, they will preface their remarks with statements like “I was told to be the protagonist, so ...” or “As the devil’s advocate here ...” Such declarations allow them to engage in the activity while distancing themselves from the viewpoints they uphold in the activity.

PEER INTERACTION Peer interaction helps engage students with each other. In traditional courses, even when the instructor does not explicitly facilitate peer interaction, students tend to discuss course-related topics before or after class. In an online class, that informal peer interaction is absent since it is often self-paced or the instructor does not grasp how to facilitate it. As a result, the students may feel extremely isolated and drop the course. Many of the techniques referenced in this chapter involve peer interaction on various levels. Discussion-based activities tend to require peer interaction in order to be successful; one-person conversations generally are not motivating. Moving beyond generic discussion, goal-oriented interactions such as collaborative problem solving activities are particularly motivating to learners because of both the peer interdependence and the ability to judge their own knowledge and skills against that of their peers (Hacker & Niederhauser, 2000). Student interaction can also be promoted

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through activities such as online symposia, press conferences, and expert panels. Our research indicates that these techniques are effective, since students in online classes are motivated by measures of how they are performing not only as compared to the instructor’s expectations, but also as compared to classmates (Dennen, 2001). Peer interaction may be considered a key course goal or activity. One technique found effective is the use of the critical friend activity (Bonk, Ehman, Hixon, & Yamagata-Lynch, 2002). In this activity, learners are matched or partnered to provide each other with constructive feedback on assignments. Alternatively, they might be required to send each other reminder messages of upcoming assignments and due dates. These activities may take place publicly via courseware or privately via e-mail. Peer interaction activities help ensure that students are receiving valuable feedback with a minimum of burden on the instructor.

GOAL DRIVEN Student motivation to participate in online class activities tends to be goal driven. If the goals as presented and valued within the course structure and assessments focus on test performance, students are motivated to study for the test. Group problem-solving activities are a great way of avoiding such isolated, low-motivation scenarios. Students who have group goals or final projects to work toward will be motivated to interact with each other. Group problem-solving activities can be semester-long projects or small group-sharing activities akin to a 15-minute group brainstorm in a traditional class. And final projects might be posted online in an online gallery of student work.

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GROUP BASED VS. SELF-PACED One of the dimensions of online courses that influences an instructor’s motivational options is whether or not it is possible to facilitate group interactions. Many people choose distributed learning to meet their educational needs because they desire the flexibility of working at their own pace. Working in isolation, however, can provide some motivational challenges. In part, motivation must come from within, and in part, it is affected by the design of the learning environment and activities. In group-based activities, learners often are motivated by the knowledge that peers will be reading and commenting on their contributions. However, fostering motivation for the independent learner who operates in the absence of social motivators can pose some extra challenges. Allowing for choice, variety, and independent learning styles can help in this regard, as can using active terminology such as “seek” and “explore” when describing learner tasks (Canada, 2000). Self-assessments also serve to motivate the independent learner who might be hungry for feedback.

SYNCHRONOUS VS. ASYNCHRONOUS COMMUNICATIONS Most of the activities presented here may be adapted to accommodate either synchronous or asynchronous communication technologies and may be used across disciplines. Certainly some activities seem better-suited to live interaction, whereas others might be more fruitful when learners take advantage of a lengthy time span for participation or reflection as afforded by asynchronous technologies. In addition, each activity might be varied to further motivate online learners. Table 2 presents some of the adaptations that might be made based on the differences in the communication tools.

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Table 2. Synchronous and asynchronous learning issues and elements within different online activities

Type of Activity

General Structure and Elements

Synchronous Issues

Asynchronous Issues

Ice Breakers

Everyone gets an opportunity to share or participate. There are a wide variety of potential activity frameworks, including Two Truths and One Lie, Coffee House Expectations, and Favorite Web Site Postings.

Turn taking is necessary since it is difficult to hear from everyone. Of course, certain activity frameworks will work better than others.

Learners may only selectively participate and read messages. Effort must be taken to encourage them to “meet” all classmates or read all messages in a new topic ice breaker.

Role Play

Learners are assigned a role or personality to play such as optimist, pessimist, journalist, coach, sage, etc. Alternatively, they might be assigned a particular person or author to assume such as Kant, Nietzsche, Mother Teresa, Sir Edmund Hillary, etc.

Learners must fully understand their roles in order to be able to play them out in real time. Some form of turn-taking must be in place to ensure that all participants are active.

Learners must have participation guidelines and deadlines to ensure that dialogue takes place. Summarization of discussion is important to bring closure, though effort must be taken to encourage learners to read the summaries.

Guest Lectures

Guests from outside of the class, such as experts in the field or authors/scholars that the students have read, are invited to join students for a discussion during a particular period of time. Typically, the guest answers learner questions, although the guest may be asked to comment on work the class has already completed.

Turn-taking must be carefully facilitated or the chat should be moderated to ensure the guest is not bombarded with to many questions at once. Preparation of questions in advance is useful.

Expectations of guest participation (how many times the guest will contribute and when) need to be clear for all participants. Early questions should be posted in advance of the guest’s first interactions.

Learners may be assigned a topic and a side, either as an individual or group, and given time to research and generally prepare for the topic.

Turn-taking must be carefully facilitated to ensure equality for both sides and all members of a group.

Timing must be carefully structured to allow for dialogic interchange between sides. Rebuttals should be deeper and more reflective than in a synchronous debate and appropriate resources and references should be cited.

Learners are asked to review and commend on each other’s ideas and work. Rubrics may be provided to help students focus on the appropriate criteria.

Students providing feedback must review material in advance and be prepared. Students receiving feedback benefit from the ability to seek clarification of muddy points in real time. It is important to have a way of saving feedback for later use.

Asynchronous peer feedback encourages more highly reflective feedback than synchronous feedback sessions. As a result, the timing of making the work available for critique and providing feedback is critical. The instructor may wish to allow learners who receive feedback time to ask their respondents for clarification.

Debates

Peer Feedback



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Regardless of whether one’s communication tools are synchronous or asynchronous, careful consideration should be given to the archiving of learner interactions and work. Such archives prove useful both in promoting learner reflection, as well as in enabling learners who have fallen behind to catch up. For example, a learner who has missed a guest lecture that occurred via a synchronous chat might feel disenfranchised if there were no event archive tools to replay what transpired.

CONCLUSION The 10 motivational elements presented here are essential to the success of online learning environments. Online, as well as live, instructors should look for pivotal points where they can comfortably address these principles within their course design. The important point here is to focus on motivational elements and principles, not just on the range of possible tasks, since activities are simply vehicles through which effective motivation and learning can take place. In addition, the activities presented in this chapter are not intended to be exhaustive in terms of their exemplification of how to motivate online students. Instead, our intention was to provide a few useful examples and ideas that can be adopted and adapted by online instructors in higher education as well as business learning environments (for additional ideas, see Bonk & Dennen, 2003). And as online motivational ideas are modified and expanded, they can now be instantaneously shared with other instructors around the globe. When that occurs, there will hopefully be fewer bored online learners and frustrated online instructors.

ACKNOWLEDGMENT Portions of this chapter were presented at the 2001 and 2002 annual meetings of the Wisconsin



Distance Teaching and Learning Conference, Madison, Wisconsin.

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pedagogy in Web-based distance education. In M. G. Moore & B. Anderson (Eds.), Handbook of distance education (pp. 331-348). Mahwah, NJ: Lawrence Erlbaum. Bonk, C. J., & Dennen, V. P. (1999). Teaching on the Web: With a little help from my pedagogical friends. Journal of Computing in Higher Education, 11(1), 3-28. Bonk, C. J., Ehman, L., Hixon, E., & YamagataLynch, E. (2002). The pedagogical TICKIT: Teacher Institute for Curriculum Knowledge about the Integration of Technology. Journal of Technology and Teacher Education, 10(2), 205-233. Bonk, C. J., Fischler, R. B., & Graham, C. R. (2000). Getting smarter on the Smartweb. In D. G. Brown, (Ed.), Teaching with technology: Seventy-five professors from eight universities tell their stories (pp. 200-205). Boston: Anker Publishing. Bonk, C. J., Hara, H., Dennen, V., Malikowski, S., & Supplee, L. (2000). We’re in TITLE to dream: Envisioning a community of practice, “The intraplanetary teacher learning exchange.” CyberPsychology and Behavior, 3(1), 25-39. Brown, D. (2002, January). Interactive teaching. Syllabus, 15(6), 23. Canada, M. (2000). Students as seekers in online classes. New Directions for Teaching and Learning, 84, 35-40. Dennen, V. P. (2001). The design and facilitation of asynchronous discussion activities in Webbased courses. Unpublished doctoral dissertation, University of Indiana, USA. Firdyiwek, Y. (1999). Web-based courseware tools: Where is the pedagogy? Educational Technology, 39(1), 29-34. Hacker, D. J., & Niederhauser, D. S. (2000). Promoting deep and durable learning in the online

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Savery, J. R., & Duffy, T. M. (1996). Problembased learning: An instructional model and its constructivist framework. In B. G. Wilson (Ed.), Constructivist learning environments: Case studies in instructional design (pp. 135-148). Englewood Cliffs, NJ: Educational Technology Publications. Schrage, M. (1990). Shared minds: The new technologies of collaboration. New York: Random House. Singer, J., Marx, R. W., Krajcik, J., & Chambers, J. C. (2000). Constructing extended inquiry projects: Curriculum materials for science education reform. Educational Psychologist, 35(3), 165-178.

Stipek, D. J. (1998) Motivation to learn: From theory to practice (3rd ed.). Boston: Allyn & Bacon. Watson, G. (2000). PHYS345 electricity and electronics for engineers. In D. G. Brown (Ed.), Teaching with technology: Seventy-five professors from eight universities tell their stories (pp. 63-66). Boston: Anker Publishing. Williams, S. B. (1992). Putting case-based instruction into context: Examples from legal and medical education. The Journal of the Learning Sciences, 2(4), 367-427.

This work was previously published in Flexible Learning in an Information Society, edited by B.H. Khan, pp. 64-76, copyright 2007 by Information Science Publishing (an imprint of IGI Global).



We’ll Leave the Light on for You

Section 2

Online and Distance Learning Development and Design Methodologies This section offers in-depth coverage of conceptual architectures and distance learning frameworks to provide the reader with a comprehensive understanding of the emerging technological developments within the field of online distance learning. From basic designs to abstract developments, chapters found in this section serve to expand the reaches of development and design technologies within the online and distance learning community. Included in this section are over 40 contributions from researchers throughout the world on the topic of online development and methodologies in distance learning.

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Chapter 2.1

Systems Model of Educational Processes Charles E. Beck University of Colarado at Colorado Springs, USA Gary R. Schornack University of Colorado at Denver, USA

INTRODUCTION Distance education involves a wide range of elements, including students, instructors, institutions, classroom technology, state agencies and accrediting boards. The educational process model provides a conceptual framework to integrate these diverse elements. The following discussion begins with a brief background on the systems and communication basis of the new model. Then it elaborates the model’s elements, including the inputs (resources and philosophy), purpose (intentions and audiences), methods (technological genre and educational process); integration (pedagogy); outputs (product and interpretation); and assessment (institutional and research).

BACKGROUND ON PREHENSIVE MODELS While distance education has expanded rapidly over the past few decades, academic study is just beginning to address this phenomenon. To organize research, Shih et al. suggest a starting point based on recent history (2003). Watkins and Schlosser examine the educational foundation of such research, defining guidelines for the alternative research approaches (2003). Lihua and Smaldino use instructional design elements as a means of organizing research in distance processes (2003). Toward a comprehensive model, Willis and Locke outline a pragmatic design model (2004). However, these approaches lack

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Systems Model of Educational Processes

Figure 1. Basic systems model

With distance education as a human communication process, the new model builds on the rhetorical process model, shown in Figure 2. The rhetorical process model divides the systems model horizontally into subjective and objective domains (Beck, 1999). It also elaborates the process into purpose (intentions and audience) and method (genre and process). These elaborations convert a mechanical basic system into a purposive human process.

Feedback

INPUT

INTEGRATION

OUTPUT

a comprehensive means of integrating the elements of distance education. Although Chien et al. present a “model-based system” for distance education, their model serves as a template for course development rather than a comprehensive system. The educational process model integrates theoretical, research and practice in distance education by creating a new model that begins with a basic systems model (Figure 1).

EDUCATIONAL PROCESS MODEL Building on the rhetorical process, the educational process model consists of inputs, an integrative process, outputs and feedback. The objective process includes resources, method and experiences; the subjective process involves philosophy, purpose and outcomes. The integration elements of purpose and method further divide: objectives and audiences; and instructional technology and methodology. These four integration elements

Figure 2. Rhetorical process model INPUT

OUTPUT

INTEGRATION Feedback

SUBJECTIVE

Purpose

Assumptions

Audience

Intentions

Embodiment Process

OBJECTIVE

Status

Genre

Method

Feedback

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Systems Model of Educational Processes

Figure 3. Educational process model

form interactive rather than linear processes, with pedagogy as the integrative center. The educational process model appears in Figure 3.

INPUTS TO THE PROCESS The inputs to the educational process include the objective element of resources and the subjective element of educational philosophy. Delivering education-based, diverse student needs involves the broader approach in delivery, the physical and training needs of the new enterprise, and the faculty philosophy of distance learning.

Resources The multiple resources for distance education involve technology with a capacity for Web sites, e-mail, bulletin boards, chat rooms, instant messaging, audio-video streaming and interactive text. The institution also needs technicians

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to maintain the equipment. More significantly, instructor resources involve faculty training and workload. Developing an online course is far more complicated than simply posting a professor’s lecture notes online (Green, 2000), yet most promotion and evaluation committees “may not take technology work seriously” (Young, 2002), ignoring faculty training. Institutions must address faculty computer literacy rather than assume that “a professor who cannot use a piece of chalk and a blackboard to teach effectively will be able to do better when we give him or her computers, VCRs, DVD players, PowerPoint presentations, video cameras, the Internet and a smorgasbord of digital media” (Strauss, 2002, p. 13).

Educational Philosophy To prepare for distance educational changes, institutions should focus on “making our learners smarter” rather than “making obsolete classrooms smarter” (Strauss, 2002, p. 13). Although distance

Systems Model of Educational Processes

education changes the method of interaction, it actually reinforces the traditional philosophy of effective education. While traditional classrooms provided a “built-in” learning community, distance learning creates a virtual learning community. Although students access from remote locations, they need a sense of belonging; to create such a community, the faculty member must become a role model by “demonstrating depth of mastery, wisdom, knowledge, skill, character and enthusiasm for the subject and profession” (Gilbert, 2002, p. 26).

EDUCATIONAL INTEGRATION Combining resources with philosophy, the educator faces the heart of the educational process, preparing and delivering the content. In the educational process model, this area focuses on integrative pedagogy, consisting of purpose and method.

Purpose In a major growth industry, the institutional motive for establishing distance educational enterprises “is almost always to make money” (Altbach, 2000, p. 29). However, the main intention should be tied more to the nature of education itself. The purpose of education requires a dual focus—meaningful course objectives and diverse audience. Although faculty must determine the essential learning objectives, they must do so in light of the specialized audience for distance learning.

Objectives Distance courses need a different organization from that used in a traditional setting. Institutions must clarify some of these distinctions (Sjogren & Fay, 2002). As a process, distance education “unbundles” traditional faculty roles into various sub-functions (Armstrong, 2000).

This rethinking also requires that students take greater responsibility for their own education in a shared environment (Lin, Sun, & Kao, 2002). Kerres and DeWitt present such a framework in terms of “blended learning” (2003), while Lin et al. focus on network sharing in the design (2002). From a theoretical perspective, Chyung and Stepich apply Bloom’s taxonomy in designing online instruction (2003).

Audiences Within the educational process model, audiences include the individual students as well as how the instructor envisions students during course preparation. Distance learning helps students who need more flexibility than normally provided in a traditional program (Cutshall, 2002). Instructors focus on the specific student audience, recognizing their different learning styles, individual needs and cultural differences (Fay & Hill, 2003). Expanding distance programs reach a different student body, including adults and full-time learners (Branch, 2001; Green, 2000). Successful students in online courses are a select group: motivated, self-directed, comfortable with technology, not afraid to experiment and able to work alone with minimal guidance (McLaughlin, 2002). Delivering to such students requires that faculty stimulate these learners (Barolli & Koyama, 2004).

METHOD The focus on method for distance education usually becomes a focus on technology. Through the Internet, students have access to millions of books and billions of Web pages, but they need to learn how to use them effectively (Strauss, 2002). Following the educational process model method includes both the technology and the methodology that instructors use in developing and presenting course materials.

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E-Media E-media covers the specific technology components: the capacity of the hosting system and the ability of the student’s equipment to interface with the host system. The use of technology highlights recent expanses in distance learning (Chou, 2003; Lu, 2004; Sala, 2003), ranging form use of multimedia to collaboration (Sala, 2003; Schweizer, Paechter, & Weidenmann, 2003; Lu, 2004). For the student, the distance approach brings further difficulties (Beck & Schornack, 2001). Although learning technologies create new possibilities (Grush, 2002), technology merely provides students the means to access in their own time and sequence (Armstrong, 2000). Strauss highlights the way to use the medium, rather than the medium itself (2002). Done properly, distance education blends new technology with traditional learning media, resulting in powerful, accessible learning information source (Boxer & Johnson, 2002).

Process From the instructor’s point of view, conversion to distance education requires a significant commitment in both preparation and content time. Faculty must become familiar with the technology, but they also need extensive and responsive technical support (McLaughlin, 2002). Currently, distance education is labor intensive; but with the growing availability of quality materials, distance education can eliminate the quantity vs. quality tradeoff (Heerema & Rodgers, 2001). With mediated learning software, holding students accountable for their own learning enables instructors to diagnose weaknesses and to know when students fall behind (Barker, 2000).

Methodology Faculty must adapt their methods to the distance media (Brown, 2002), including strategy to

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complete collaborative tasks and group interaction through threaded discussion (Schweizer et al., 2003; Jeong, 2003). Ensuring interaction has become a significant focus of recent research, whether through automatic feedback (Watt, 2002) or a broad range of interactions (Sakai, Naoaki, Yoshimitsu, Shingeno, & Okada, 2004). Combining teaching method with technological skills can help students reach the higher cognitive levels.

PEDAGOGY Pedagogy merges objectives, student audience, technology and methodology to produce the educational experience. Teachers modify their original objectives in view of student needs and the available technology. Method sequences suitable for in-class discussion must change based on the asynchronous nature of the distance process. A pedagogical starting point to address the problems begins with an integrative process (Notar, Wilson, & Ross, 2002). Although distance education starts as a paradigm shift, as it gets integrated into the curriculum, it exerts its own influence on the broader educational process (Barker, 2000). Ultimately, distance education can enhance oncampus pedagogy.

EDUCATIONAL OUTPUTS The outputs of distance education combine the actual experiences of conducting the courses and the ultimate learning outcomes that occur.

EXPERIENCES The output of the educational process model is the actual instruction as presented. Institutions monitor such output in terms of course schedules, equipment usage, contact hours and credit hours

Systems Model of Educational Processes

generated. Regardless of the availability of technology, the instructor affects the educational experience (Shea & Boser, 2001). Distance education represents a classroom furnished with the Internet, e-mail, digital cameras, instant messaging and videoconferencing, enabling students to talk to professors, instructors, industry experts and other students from anywhere in the world using audio and visual components (Frabotta, 2000).

OUTCOMES Virtual education brings both expected and unexpected outcomes for the institution and for the student. For the institution, Internet-based programs demand more faculty preparation time. If institutions jump into distance education too quickly without planning and proper allocation of resources, the Internet could potentially also weaken enrollment in smaller schools that can’t compete with more comprehensive programs (Bascom, 2001). Recent research had attempted to evaluate outcomes based on behaviors (Yen, 2003), learning (Munzer, 2003) and interdisciplinary course preparation (Coogle et al., 2002). Rovai has identified the sense of community along with learning in an asynchronous mode (2002).

ASSESSMENT Assessment serves a critical feedback role in the educational process. In terms of the educational process model, assessment provides feedback for the entire system. Such feedback may not occur instantaneously, but only after the institution has gained some experience. Assessment begins internally, but then involves outside agencies as well.

INTERNAL Distance education begins with an initial adaptation to technology, to students and to new teaching methods. Gradually, these changes begin to affect the rest of the institution; thus, the systems nature of the educational process model. Instructors must become more aware of differences to identify at-risk students, examining low hit rates and inactivity (Wang & Newlin, 2002). Recent research has evaluated computer-mediated conferencing (Curran, Kirby, & Parsons, 2003), pedagogical design (Lim, Hung, Wong, & Hu, 2004), interactive design (He, Zhang, & Cheng, 2004), and quality assurance (Steyn & Schulze, 2003; Clarke, Butler, Schmidt-Hansen, & Somerville, 2004).

EXTERNAL External assessment involves outside experts, government agencies or education associations examining individual schools or programs. According to one overview, “The ‘factory’ university is giving way to the ‘virtual’ university” (Dunn, 2001, p. 28), gaining the attention of unions and accrediting agencies. The American Federation of Teachers has recommended quality standards for content support, technical support and counseling for students, protection of intellectual property rights and proper training for faculty (New AFT Report, 2001). The California Virtual Campus presented the first Teaching Site Awards to recognize exemplary online classes in the areas of educational content, course design, use of multimedia, interactivity, community and disabled access (Matrix, 2001). Because distance education requires a rethinking of the process, it can lead to a paradigm shift in educational theory and practice. A survey of faculty in distance education found the following best outcomes of distance delivery: tutorial functions, flexibility,

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self-paced, privacy, cutting edge and interactive feedback (Perez & Foshay, 2002).

CONCLUSION The interest in distance education forces educators to rethink the entire process. Ultimately, technology does not represent a minor change in delivery; rather, it is an integral part of the educational system, where changing one aspect affects the rest of the system. It can lead to the major assessment considerations for institutions (adapted from Berg, 2001): • • •

• • •

Understand why distance learning is used at specific institutions. Enter into agreements with for-profit entities with great caution. If new revenue generation is a clear institutional motivation, understand the economics. If new revenue generation is a clear institutional motivation, watch the quality. Try for more than automation of the traditional classroom. Faculty compensation and intellectual property are significant issues; use short-term agreements and understand the economics.

The educational process model provides a way to integrate the diverse elements of the distance education process.

REFERENCES Altbach, P.G. (2000). The crisis in multinational higher education. Change, 32(6), 29. Armstrong, L. (2000). Distance learning: The challenge to conventional higher education. Change, 32(6), 20.

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Barker, J. (2000). Sophisticated technology offers higher education options. T H E Journal (Technological Horizons in Education), 28(4), 58. Barolli, L., & Koyama, A. (2004). A distance learning system for delivering appropriate studying materials and stimulating learner volition. International Journal of Distance Education Technologies, 2(1), (Jan-Mar), 1-17. Bascom, L.C. (2001). Budgetary blues: As the annual higher education budget battles heat up, new challenges ranging from the repeal of the estate tax to the Internet pose bottom line problems. Matrix: The Magazine for Leaders in Higher Education, 2(3), 22-26. Beck, C.E. (1999). Managerial communication: Bridging theory and practice. Upper Saddle River, NJ: Prentice-Hall. Beck, C.E., & Schornack, G.R. (2001). Electronic communication: The challenge to innovate. Journal of American Academy of Business, Cambridge, 12(1), 122-130. Berg, G.A. (2001). Distance learning best practices debate. WebNet Journal, 3(2), 5. Boxer, K., & Johnson, B. (2002). How to build an online learning center: Online learning centers may be the new construct for training and development. T&D, 56(8), 36. Branch, A. (2001). Thomson busy, then shuts down Harcourt’s higher education Web site. Matrix: The Magazine for Leaders in Higher Education, 2(4), 13-14. Brown, D.G. (2002). Connecting with students. Syllabus, 16(3), 24. Chen, S.-C., Li, S.-T., & Shyu, M.-L. (2003). Model-based system development for asynchronous distance learning. International Journal of Distance Education Technologies, 1(4), 39-54. Chou, C. (2003). Interactivity and interactive functions in Web-based learning systems: A tech-

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nical framework for designers. British Journal of Educational Technology, 34(3), 265-279.

Green, J. (2000). The online education bubble. The American Prospect, 11(22), 32.

Chyung, S.Y., & Stepich, D. (2003) Applying the “congruence” principle of Bloom’s Taxonomy to designing online instruction. Quarterly Review of Distance Education, 4(3), 317-330.

Grush, M. (2002). Editor’s note. Syllabus, 16(2), 3.

Clarke, M., Butler, C., Schmidt-Hansen, P., & Somerville, M. (2004). Quality assurance for distance learning: A case study at Brunel University. British Journal of Educational Technology, 35(1) (Jan), 5-11. Coogle, C.L., Parham, I.A., Welleford, E.A., & Netting, F.E. (2002). Evaluation of a Distance Learning course in Geriatric Interdisciplinary Teaming. Educational Gerontology, 28,791804. Curran, V., Kirby, F., & Parsons, E. (2003). Discourse analysis of computer-mediated conferencing in World Wide Web-based continuing medical education. Journal of Continuing Education in the Health Professions, 23(4), 229-238. Cutshall, S. (2002). When online learning works. Techniques, 77(5), 22. Debating distance learning. (2000). Communications of the ACM, 43(2), 11. Dunn, S.L. (2001). Fuel for the future. USA Today (magazine), 129, 28. Fay, R., & Hill, M. (2003). Educating language teachers through distance learning: The need for culturally-appropriate DL methodology. Open Learning, 18(1), 9-27. Frabotta, D. (2000). Continuing education: Cornell University’s dean-elect plans to focus on research, technology-based learning. Hotel and Motel Management, 215(10), 7. Gilbert, S.W. (2002). Personalizing pedagogy. Syllabus, 16(3), 26.

He, A., Zhang, G., & Cheng, Z. (2004). A design of real-time and interactive distance education environment. International Journal of Distance Education Technologies, 2(2), 1-12. Heerema, D.L., & Rodgers, R.L. (2001). Avoiding the quality/quantity trade-off in distance education. T H E Journal (Technological Horizons in Education), 29(5), 14-19. Jeong, A.C. (2003). The sequential analysis of group interaction and critical thinking in online threaded discussions. The American Journal of Distance Education, 17(1), 25-43. Johnstone, S.M. (2002). U.S. distance learning: A ‘cottage industry.’ Syllabus, 15(7), 18. Kerres, M., & De Witt, C. (2003) A didactical framework for the design of blended learning arrangements. Journal of Educational Media, 28(2/3), 101-113 Lihua, Z., & Smaldino, S. Key instructional design elements for distance education. Quarterly Review of Distance Education, 4(2), 153-166. Lim, C.P., Hung, D., Wong, P., & Hu, C. (2004). The pedagogical design of ICT integration in online learning: A case study. International Journal of Instructional Media, 31(1), 37-47. Lin, S., Sun, L.C. T., & Kao, G. (2002) Designing a network-shared construction environment. British Journal of Educational Technology, 33(4), 489-492. Lu, H. (2004). Open multi-agent systems for collaborative Web-based learning. International Journal of Distance Education Technologies, 2(2), 36-45.

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Malay, K., Abdel-Wahab, H., Overstreet, C. M., Wild, J.C., Abdel-Hamid, A., Ghanem, S., & Waleed, F. (2003). The essential elements of interactive multimedia distance learning systems. 1(2), 17-36.

Sakai, S., Naoaki, M., Yoshimitsu, Y., Shingeno, H., & Okada, K. (2004). An efficient method of supporting interactions for an integrated distance learning system. Journal of Distance Education Technologies, 2(3), 1-10.

Matrix: The Magazine for Leaders in Higher Education. (2001). 2(1), 62.

Sala, N. (2003). Hypermedia modules for distance education and virtual university: Some examples. Journal of Distance Education Technologies, 1(1), 78-95.

McLaughlin, C. (2002) Learner support in distance and networked learning environments: Ten dimensions for successful design. Distance Education, 23(2), 149-162. McLaughlin, J. (2002). Getting Online. Getting up to speed. International Journal on E-Learning, 1(3), 21. McLaughlin, J. (2002). Surf or turf? Deliberations about distance education. International Journal on E-Learning, 1(2), 18. Munzer, S. (2003). An evaluation of synchronous co-operative distance learning in the field: The importance of instructional design. Educational Media International, 40(1-2), 91-99. New AFT report proposes standards of online programs. (2001). Black Issues in Higher Education, Feb 1, 43. Notar, C., Wilson J., & Ross, K. (2002). Distant learning for the development of higher-level cognitive skills. Education, 122(4), 642. Patterson, J. (2000). Building the virtual classroom. Curriculum Administrator, 36(7), S14. Perez, S., & Foshay, R. (2002). Adding up the distance: Can developmental studies work in a distance learning environment? T H E Journal (Technological Horizons in Education), 29(8), 16. Rovai, A.P. (2002) Sense of community, perceived cognitive learning, and persistence in asynchronous learning networks. The Internet and Higher Education, 5(4), 319-332.

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Samuels, D. (2001). On learning online. Risk Management, 48(2), 8. Schweizer, K., Paechter, M., & Weidenmann, B. (2003). Blended learning as a strategy to improve collaborative task performance. Journal of Educational Media, 28(2), 211-224. Shea, R., & Boser, U. (2001). So where’s the beef? U.S. News & World Report, Oct 15, 44. Shih, T.K., Antoni, G.D., Arndt, T., Asirvatham, A., Chang, C.-T., Chee, Y.S., et al. (n.d.).A survey of distance education challenges and technologies. International Journal of Distance Education Technologies, 1(1), 1-21. Sjogren, J., & Fay, J. (2002). Cost issues in online learning: Using ‘co-opetition’ to advantage. Change, 34(3), 53. Steyn, G.M., & Schulze, S. (2003). Assuring quality of a module in human resource management: Learners’ perceptions. Education, 123(4), 668-680. Stoll, J. (2001). No time for class? Log on to Internet. Automotive News, 75(5915), 28. Strauss, H. (2002). New learning spaces: Smart learners, not smart classrooms. Syllabus, 16(2), 13. Wang, A., & Newlin, M. (2002). Predictors of performance in the virtual classroom: Identifying and helping at-risk cyber-students. T H E Journal (Technological Horizons in Education), 29(10), 21.

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Watkins, R., & Schlosser, C. (2003). Conceptualizing educational research in distance education. Quarterly Review of Distance Education, 4(3), 331-4. Watt, S. (2002). Electronic dourse surveys: Does automating feedback and reporting give better results? Assessment and Evaluation in Higher Education, 27(4), 325-337. Willis, L.L., Lockee, B.B. (2004). A pragmatic instructional design model for distance learning. International Journal of Instructional Media, 31(1), 9-17. Yen, S-J. (2003). An efficient approach for analyzing user behaviors in a Web-based training environment. International Journal of Distance Education Technologies, 1(4), 55-71. Young, J. (2002). Ever so slowly, colleges start to count work with technology in tenure decision. Chronicle of Higher Education, Feb 22, A25.

KEY TERMS Active Learning Techniques: Techniques where students do more than simply listen to a lecture. Students are doing something, including discovering, processing and applying information. Active learning derives from two basic assumptions: (1) learning is by nature an active endeavor, and (2) different people learn in different ways.

Assessment Tools: Methods used to obtain information about student learning to guide a variety of educational strategies and decisions. Distance Education: A formal educational process in which instruction occurs when student and instructor are separated by geographic distance or by time. Instruction may be synchronous or asynchronous. Distance education may employ correspondence study or audio, video or computer technologies. Education Process Model: A basic system’s model, which consists of resources and philosophy as inputs; an integrative process of objectives, methodology, audiences and instructional technology; the outputs of outcomes and experiences; and assessment feedback. Pedagogy: The work of a teacher; the art and science of teaching; instructional methods and strategies. Tutorial Functions: Program used to help students gain and/or refresh understanding of general principles and basic ideas, available in computer format on educator’s Web site. “Virtual” University: An online learning community or environment in which distance education takes place through courses and instructional programs offered on the Internet and other technologically enhanced media.

This work was previously published in the Encyclopedia of Distance Learning, Vol. 4, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P. L. Rogers, and G. A. Berg, pp. 1732-1739, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.2

E-Learning Environment Mizue Kayama Senshu University, Japan Toshio Okamoto University of Electro-Communications, Japan

OVERVIEw OF E-LEARNING

•

Nowadays, the concept/system of e-learning (or eLearning) is widespread with the advent and prevalence of the Internet. Via the Internet, people can communicate with each other at anytime and from anywhere. People can also share, rebuild, stock, and reuse various kinds of information. Here, it is clear that e-learning gets citizenship in the educational society instead of CAI (computerassisted instruction) and CMI (computer-managed instruction). As a response to society’s advance, it is necessary to construct a new learning ecology, such as a learning organization or a learning community. To date, the need for an understanding of e-learning issues has not been met by a coherent set of principles for examining past work and plotting fruitful directions. Obviously, it would be difficult to document the many seeds sown now. The e-learning environment is cataloged as follows (Okamoto, 2000):

• •

Individual learning environment with learning materials Group learning/collaborative learning environment with some shared tools/applications Classroom learning (lecturing)

This learning ecology has the mixed mode of either synchronous or asynchronous by using any teaching/learning contents and audio/visual devices, such as videoconference and other communications tools. e-Learning is a learning/education/training style that uses information technologies. In the past, this type of learning/education/training was called various names, like “distance learning,” “distance education,” “cyber learning,” “virtual learning,” “Web-based training (WBT),” “Webbased learning (WBL),” “online learning,” and so on. Nowadays, e-learning is innovated by using the latest information technologies, including WWW technology for e-learning course deliv-

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E-Learning Environment

ery, movie/speech compression technology for e-learning content production, and the learning technology standards (SC36, 2004), like LOM (learning object metadata), SCORM (sharable content object reference model), and collaborative technology, for keeping the interoperability of e-learning systems/contents/courses. The main advantages of e-learning are, as is well known, from “to any place, at any time” attributes. Often, the free education aspect also appears, although much of the educational software offered today is not free, and many educational institutions offer e-learning programs at a price. Plain, text-based course materials are not enough anymore. The recent increases in bandwidth made more avenues of expression possible, images on the Internet are commonplace, soundtracks and videos are used with growing frequency, and other (multi- and mixed) media types evolved (animation, simulation, collaboration, etc.). Before now, based on learner modeling, adaptation of teaching strategies and intelligent user adaptation in intelligent tutoring system (ITS) were developed. More recently, the field of adaptive hypermedia (De Bra et al., 1999) emerged, at the crossroads of hypertext/hypermedia and user modeling. Adaptive presentation of the educational material can mean one or more of the following: providing prerequisite, additional, or comparative explanations; conditionally including fragments and stretch-text; providing explanation variants; reordering information; etc. Adaptive navigation support can mean one or more of the following: direct guidance, sorting of links, links annotation (Brusilovsky, 1999), link hiding, link disabling, link removal, and map adaptation. Another main advantage of the Internet is that it favors collaborative work, which, in turn, favors learning (Dillenboug, 1999). Moreover, we regard e-learning as meaningful self-development of an environment for lifelong learning. The recent technological changes are influencing our society, and people are asked to acquire new knowledge all the time. The oppor-

tunities to take education with high quality have to be provided for all sorts of people who have different backgrounds, different abilities and knowledge, and various needs. E-Learning is one answer to the rigidity of the present Web-based courses and courseware.

THE DESIGN OF AN E-LEARNING ENVIRONMENT When we think modality of computerization on education, it is generally categorized as follows: 1.

2.

3.

4.

Self-study entity through electronic information media-based materials and courseware Learning entity, with electronic information media (e.g., computer) as learning/problemsolving/representing/knowledge-transmitting tools Learning entity about information and communication technology, social problems, and so forth. Computerizing entity of education

The relationships among those entities should be compensated for mutually, and an e-learning cycle can be developed. The idea here is in line with building the environment for “anybody” to learn something from “anywhere” and at “anytime” in the e-society. There are two purposes for this expansion: on one hand to enlarge the study opportunity, and on the other, to develop people’s new competencies. When we build an e-learning environment, at least three issues should be considered (Okamoto, 2000). The first is the pedagogical goal representing ability and knowledge as learning objectives. The second is the subject contents. The third is the learning forms, defined by seven learning environments:

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E-Learning Environment

1.

2.

3.

4.

5.

6.

7.

Distance individual learning environment for mastery learning. This environment provides courseware for knowledge and skills acquisition, i.e., the typical e-learning course, such as WBT/VOD (video on demand) systems (Hui, 2000). Distance individual learning environment for discovery learning using various search engines (VOD search and navigation mechanism). Distance individual learning environment for problem-solving learning using simulations, such as ILE (interactive learning environment), and so on. Videoconference system in the classroom environment for discussion, instructional presentation, questions and answers sessions, and telecommunications (Chen, 2001; Nieminen, 2001). Collaborative learning environment for a small group or pairs using videoconferencing, some kind of communication tool, or various applications accompanied by a screen-shared viewer and learning log tracking mechanism. Collaborative simulation learning environment for different learners performing different functions in a teamwork learning pattern, and as such, forming a special skill in the learner’s own domain (e.g., a collaborative activity within the jet plane’s cockpit). Linkage and coordination among different organizations and areas (e.g., access the online school library, online museum, etc.).

In the establishment of e-learning environments, the most important idea is to start by defining the instructional goal and then classifying learning contents that are best equipped to build the learning environment. Moreover, the research on the method is required in order to build the asynchronous collaborative learning contents (Dryden, 2001). Further research direc-

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tions should be placed on the study of the learning environment, with emphasis on the virtues of individualized learning and collaborative learning. In this case, transmission of real images and voice data is required. The fundamental environment components for e-learning systems include the whole information system related to e-learning environments. It consists of several management functions, such as curriculum and learning-materials management, learners’ profile and log-data management, LMS (learning management system) and LCMS (learning contents management system). In order to construct those educational management systems, we need, technologically, several data/file-processing modules, such as a distributed file system, synchronous data communications, and so on. If any applications and tools related to e-learning can be plugged in the core framework, we would build an integrated e-learning environment where learners can share and operate these software/data in real time. In addition, the total management system of e-learning is required in order to execute a real educational project or practice, which means research project management, learning schedule management, courseware development, and so on.

COLLABORATIVE LEARNING UNDER E-LEARNING ENVIRONMENT Collaborative learning is a participants’ initiative learning form that has been stressed with the paradigm shift from the teaching side to the learning side in the current learning ecology. The objectives of collaborative learning are the effective and efficient group activity and the collaborative mutual interdependence relations within the group. In collaborative learning, each learner is submitted a subtask, and he or she is expected to accomplish it. As the result, the group goal and each learner’s learning goal would be achieved.

E-Learning Environment

Distributed collaborative learning is a type of collaborative learning that can take place in the Internet environment (e.g., e-learning environment) with multiple learners geographically far from one another (O’Malley, 1994). Geographically, a distanced situation can mean remote or far physically, but this also covers cases where direct interaction and dialogue are not possible among participants due to other reasons. The urgent research topic is how to support distributed collaborative learning, including how to support the collaboration among plural learners according to a teacher’s educational objectives. This type of learning is called CSCL (computer-supported collaborative learning). CSCL focuses not on the efficiency of group work, but on a deep and comprehensive understanding with self-reflecting and self-monitoring (Dillenboug, 1999). In general, the CSCL management software provides two types of activity space: a private working space and a collaborative working space, where the learners can exchange information in a synchronous or an asynchronous manner. Many researches are discussing these two types of activity space: the information exchange types that exist, and those that are necessary (Synnes, 1999). The resources required in a collaborative learning (CL) environment are taken up as follows (Okamoto, 2001): • • • • • • • •

Technologically mediated dialogue channel Shared workplace for a group Personal workplace Learning materials and learning tools Analyzing tools of data/information Repository/memory for data/information revealed in CL Reference channel for the collaborative repository Modeling tools for monitoring the process of CL

In order to support collaborative learning in an e-learning environment, many platforms are proposed. For instance, Timbuku (Netopia), NetMeeting (Microsoft), Media-Fusion (Apple Computer), Habanero (University of Illinois/NCSA), MatchMaker (University of Duisburg), SimPLE (University of Maryland), CSILE/Knowledge Forum (University of Toronto/Learning in Motion) and REX (University of Electro-Communications). We can also mention the performance support system (PSS). In such a system, learning activity is directly connected to problem solutions in the real world. The PSS in a virtual environment is used in many fields, such as flight (flight simulator), shipping (navigation simulator), and fire (fire simulator).

FUTURE wORK The traditional classroom teaching method is limited in time, and it is difficult to supervise all students. In order to realize individual learning, educators must prepare and provide a tailored curriculum teaching method for each student’s needs. However, it is difficult for a teacher to manage such a teaching activity when considering students’ individual differences. On the other hand, the e-learning paradigm provides a solution to these problems. Adaptive/personalized/individualized learning environments seem to be more useful than the traditional classroom teaching environment. In addition, we can enhance the quality of the course contents by effectively using learning media. However, when we build a desirable learning environment to promote learning effectiveness, we have to tackle the following questions: •

Should it be an e-learning system? Who are the target learners, and how far are they from the site? Are these features appropriate for the e-learning paradigm? Can we expect

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E-Learning Environment

•

•

to include the number of learners from a time and location point of view? We should also consider the needed type of e-learning system and the technical tasks of the e-learning system based on those aspects mentioned above. Should it be an intelligent, adaptive system? Are the students very different? Do their backgrounds vary? Do the students belong to different age groups? Are they full-time and part-time students? Are there company workers among them? Does the subject of the course include features that might be relevant to different people? Do all students have to study the whole material, or should there be alternatives according to their needs? How granular is the course presented? In this case, we have to consider both the predicted student attention span and the smallest educational unit containing useful information. These kinds of questions, again, do not only point to whether an adaptive system is needed or not, but they also show what kind of adaptation is necessary. Are various media needed? Does text suffice for the presentation? Can we expect a better student reaction from different media? May the media motivate the learners? May the media make progress in their understanding of the contents? What kind of media is appropriate? What part of the e-learning system (contents presentation module, testing module, education tactics planning module, and so on) will be best suited for the media?

1. 2. 3.

CONCLUSION The retrospective of education in the 20 century is portrayed by classroom teaching and learning, group learning, and individual learnth

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ing in traditional teaching and learning forms and e-learning forms. Education is changing as technology advances. Internet technologies are highly influential in developing and presenting teaching and learning activities. The Internet is used as a place to look for information, communicate, and realize self-development. Moreover, the innovation of technology will prospectively increase the speed and capacity of processing and the availability of access. Learning needs are dynamic and vary in the computerization age. As a response to this society advance, e-learning is here to stay, as it involves the methodology of instruction, cooperative and collaborative learning, self-study, and all kinds of media, and furthermore, it engages various evaluation ideas. Nevertheless, it is important for people to form new competencies and abilities and to create and obtain sound attitudes toward the new era. In keeping with these purposes, we need to design the learning environment to foster deep and wide competency. Moreover, teachers need to put their expertise to this learning environment through their educational practices. The method of group formation and organization, the preparation of the learning contents and media, and teamwork among teachers are the most eloquent and meaningful matters. Finally, we would like to portray some essential matters in order to achieve real success in the e-learning world:

4. 5. 6.

Quality of contents based on well-examined curriculum (or competency library) reflecting the specified learning goals Quality of services from educational and technological perspectives Involvement and commitment of human mentors Copying technology changes Seamless information flow and easy access Knowledge repository for reusing resources

E-Learning Environment

7. 8.

Integration of authoring and delivering Sharing functions such as “plug-ins” for applications and tools

These essential matters set the stage for the 21st century to host collaborative development of infrastructure for large-scale use by the profession, and conduct essential research into the advancement of education.

REFERENCES Brusilovsky, P. (1996). Methods and techniques of adaptive hypermedia. User Modelling and User-Adaptated Interaction, 6, 87–129. Chen, N., & Shin, Y. (2001). Stream-based lecturing system and its instructional design. In Okamoto T., Hartley, R., Kinshuk & Klus, J. (Eds.) Proceedings of International Conference of Advanced Learning Technologies, IEEE Computer Society, CA, USA, (pp. 94–95). De Bra, P., Brusilovsky, P., & Houben, G. J. (1999). Adaptive hypermedia: From systems to framework. ACM Computing Surveys, 31(4), 12. Dillenboug, P. (1999). Collaborative learning, cognitive and computational approaches. Advances in learning and instruction series. Oxford; Elmsford, NY: Pergamon Press. Dilley, J., & Arlitt, M. (1999). Improving proxy cache performance: Analysis of three replacement policies. IEEE Internet Computing, 3(6), 44–55. Dryden, G., & Vos, J. (2001). The learning revolution. Stafford, UK: Network Educational Press Ltd. Hui, S. (2000). Video-On-Demand in education. Retrieved from http://www.cityu.edu. hk/~ccncom/ net14/vod2.htm ISO-IEC JTC1 SC36. (2004). SC36 HomePage. Retrived from http://jtc1sc36.org/

Nieminen, P. (2001). Videolecturing for international students. In Ruokamo, H., Nykänen, O., Pohjolainen, S., Hietala, P. (Eds.), Proceedings of International PEG Conference, Tampere University of Technology, (pp. 162–168). Okamoto, T. (2000). A distance ecological model to support self/collaborative-learning via Internet. In S.S. Young, J. Greer, H. Maurer, Y. S. Chee (Eds.) Proceedings of the International Conference of Computer on Education 2000, AACEAPC/National Tsing Hua University, Taiwan, (pp. 795–799). Okamoto, T., Kayama, M., & Cristea, A. (2001). Considerations for building a common platform of collaborative learning environment. In Lee, C. H., Lajoie, S., Mizoguchi, R., Yoo, Y. D., and du Boulay, B. (Eds.) Proceedings of the International Conference of Computer on Education 2001,AACE-APC/Incheon National University of Education Publications, Seoul, Korea, (pp. 800–807). O’Malley, C. (Ed.). (1994). Computer supported collaborative learning. NATO ASI series, Vol. F-128. Berlin: Springer-Verlag. Synnes, K., Parnes, P., Widen, J., & Schefstroem, D. (1999). Student 2000: Net-based learning for the next millennium. In P. De Bra and J. Leggett (Eds.)Proceedings of the World Conference on the WWW and Internet 1999, AACE, VA, USA, (pp. 1031–1036).

KEY TERMS Collaborative Learning: This is a form of learning that involves collaborative learning processes. It is designed for coaches, helpers and faculty, and groups of learners to fulfill the learning objectives of groups and of each learner through sharing resources and interacting.

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E-Learning Environment

E-Learning: A learning/education/training form/shape using information technologies. Elearning can provide learning/education/training services for anyone, from/to anywhere, and anytime. By network technology and learning technology, the following matters work at the e-learning environment: blending of learning and teaching methods (virtual classroom, simulation, collaboration, community, and classroom); supporting learning and teaching services (from assessment through testing and certification); online administration (handling user and course registration and monitoring learner progress); and so on. Learning Contents Management System (LCMS): This is a system that is used to create, store, assemble, and deliver personalized content in the form of learning objects in an e-learning environment. LCMS includes and combines the functions of a content repository/database or CMS (content management system) and a LMS. Although the LMS has functions to manage the learning courses, the LCMS has functions to manage the content and permit locating stored content, authoring new content, attaching metadata to content, and managing versions of content. Learning Management System (LMS): An e-learning infrastructure with real-time databases that deal with user (learner, coach, faculty, and so on) information, including the user’s learning

competencies, learning objects for each type of learning style and form, and learning activity and performance log tracking. An extended LMS may also support authoring, performance assessment, classroom management, competency management, knowledge management, certification and compliance training, personalization, mentoring and coaching, and communication. Learning Object: This is any entity (digital or nondigital) that may be used for learning/education/training. A learning object is usually the smallest unit of instruction managed by a LMS. However, a learning object may grow increasingly complex, have any internal structure, and may get more size or granularity. In order to reuse, learning objects are described by metadata (LOM : learning object metadata). Learning Technology Standard: This is a de jure standard for learning/education/training with information technology. This type of standard includes a formal accredited normative specification or set of guidelines, typically including conformance criteria. A standard is created by a formal standards development organization (SDO), like the European Committee on Standardization (CEN), the International Organization for Standardization (ISO), and the IEEE Learning Technology Standards Committee (IEEE LTSC).

This work was previously published in the Encyclopedia of Information Science and Technology, Vol. 2, edited by M. KhosrowPour, pp. 1001-1005, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.3

A Conceptual Architecture for the Development of Interactive Educational Multimedia Claus Pahl Dublin City University, Ireland

ABSTRACT

INTRODUCTION

Learning is more than knowledge acquisition; it often involves the active participation of the learner in a variety of knowledge- and skillsbased learning and training activities. Interactive multimedia technology can support the variety of interaction channels and languages required to facilitate interactive learning and teaching. A conceptual architecture for interactive educational multimedia can support the development of such multimedia systems. Such an architecture needs to embed multimedia technology into a coherent educational context. A framework based on an integrated interaction model is needed to capture learning and training activities in an online setting from an educational perspective, to describe them in the human-computer context, and to integrate them with mechanisms and principles of multimedia interaction.

Interactivity is central for teaching and learning (Moore, 1992; Ohl, 2001)—the active involvement of learners is of paramount importance for a successful learning experience (Sims, 1997). This importance is reflected recently by more interactive resources provided for e-learning environments (Northrup, 2001). Platforms such as the World Wide Web are ideal for making learning resources in various forms accessible without any restrictions in time or location. The current predominant focus on knowledge-based learning using Web-based e-learning environments is partly a result of a lack of interactive multimedia technologies. With the recognition of skills training as being equally important to knowledge acquisition, more work has recently been done on

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

A Conceptual Architecture for the Development of Interactive Educational Multimedia

activity-based learning and training supported by interactive multimedia technology. Multimedia technology has been widely used in computer-based teaching and learning (Okamoto, Cristea, & Kayama, 2001; Trikic, 2001). Central to a learner’s interaction with the environment is the interaction with learning content. In particular in e-learning environments, the learner-content interaction is often more central than the learner’s interaction with instructors and peers (Ohl, 2001). Our focus here is on the development of interactive educational multimedia. A variety of learning and training activities can be supported by a variety of multimedia interaction channels and languages (Elsom-Cook, 2001). The acquisition of, firstly, declarative knowledge and, secondly, of procedural knowledge and skills-based experience and expertise through learning and training needs to be integrated through a coherent multimedia channel and language design. Support frameworks for multimedia development for e-learning environments exist (Heller, Martin, Haneef, & Gievska-Krliu, 2001). However, the focus of these frameworks is mainly on knowledge acquisition-oriented environments. Our objective is to introduce a conceptual development architecture for interactive educational multimedia supporting activity-based learning and training. Our aim is to support the development of educational multimedia content, including development activities such as description, classification, and comparison. The development of e-learning technology is a participative effort, requiring collaboration and cooperation among those involved. Instructors, instructional designers, and software developers shall benefit from such an architecture. The proposed architecture is based on three layers, integrating three perspectives of interaction ranging from the educational context to the human-computer interface to the multimedia implementation. An activity model reflects the importance of learning and training activities. Development of educational multimedia content

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is usually a complex process—the three layers address the needs of three different stages in the development process. The purpose of the architecture is to provide a standardised description notation for various aspects and a guideline for a multi-stage development process. A database learning environment called the Interactive Database Learning Environment (IDLE) (Murray, Ryan, & Pahl., 2003; Pahl, Barrett, & Kenny, 2004) will illustrate the concepts and terminology of our architecture. Making knowledge about interaction that is inherent in the design explicit is our objective. Explicit knowledge is a prerequisite for evaluation and comparison, and also the deployment of content elements in intelligent educational systems. Domain and instruction-related knowledge shall be our primary focus.

INTERACTION IN E-LEARNING AND TRAINING SYSTEMS We can distinguish three central aspects of activity-based e-learning and training systems: knowledge and skills learning and training, human-computer interaction, and multimedia implementation (see Figure 1).

Knowledge and Skills Pedagogical theories determine the learning process design. The individual learning activities in this process—the learner interaction with content—are often subject-specific. In general, we can distinguish various types of learner activities. Learning is about the acquisition of knowledge or skills. The purpose of acquiring knowledge on the one hand and skills on the other differs: •

Knowledge: We refer here to what is often called declarative knowledge, namely, facts. The objective of the learner is to be able to reason about knowledge. The style of learning is usually classical studying. We use the

A Conceptual Architecture for the Development of Interactive Educational Multimedia

Figure 1. Learner-content interactions: A layered view interface learning and training interaction

learner activities

sceanrios content models and architecture

human-computer interaction learner

channels and languages

interactive educational multimedia

•

term learning to refer to this activity. Skills: This shall denote here what is sometimes called procedural knowledge, namely, instructions. The objective of the learner is the ability to perform instructions and procedures—in this case, we speak about skills. The style of learning is training.

The basis for this distinction is the meaning of the interaction for the learner in terms of her/his goals and tasks. •

•

Knowledge-level interaction: This is interaction in terms of concepts and relationships of the subject domain. Meaningful communication with these elements is essential for declarative knowledge acquisition and knowledge production. Activity-level interaction: This is interaction in terms of subject-specific procedures and activities. Meaningful activities are important for the acquisition and execution of skills, namely, procedural knowledge and experience.

This distinction is necessary to reflect the different cognitive processes of knowledge and skills acquisition.

Human-Computer Interaction Languages and processes at the interface of a human-computer environment need particular attention in order to meet the requirements of the human user (Dix, Finlay, Abowd, & Beale, 1993). Three models are central: •

•

•

Cognitive models and architectures represent the user’s knowledge, intentions, and abilities. Acquisition and production of plans of activities are central. A hierarchical task and goal model structures the user goals and the corresponding tasks that have to be executed to accomplish the goals. Linguistic models introduce a vocabulary and constrain the interaction through a usersystem grammar.

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A Conceptual Architecture for the Development of Interactive Educational Multimedia

Multimedia Multimedia systems (Elsom-Cook, 2001) are characterised by the channels provided to access and communicate knowledge and to enable activities. •

•

A channel is considered as an abstraction of a connection device used to communicate encoded information. Examples are text or audio. Specific languages are used to communicate information along the channels between the user and the multimedia system. For instance, English is a language that can be communicated along a text channel.

A medium is a set of coordinated channels. Communication using these media needs to be meaningful, that is, it should allow users to determine their behaviour based on communicated information. In this case, we call a communication an interaction. The user interacts with the system in the form of dialogues to access knowledge and to engage in activities.

DEVELOPMENT OF E-LEARNING AND TRAINING SYSTEMS The Development Context The development of e-learning and training systems is a challenging task. These systems are complex, consisting of a number of different components (learning objects and supporting infrastructure). Consequently, their design and implementation involves several activities: •

•

State-of-the-Art In recent years, the focus of research in e-learning technologies has been on the provision of knowledge learning through suitable technologies—work on knowledge media (Ravenscroft, Tait, & Hughes, 1998) addressing adequate media representation and access for learning technology is an example. However, with a change of focus moving towards skills and activities, other types of interactions need to be supported. Ravenscroft et al. (1998) acknowledged that the style and level of interaction is central—a result that needs to be applied to this new context.

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•

•

The development of individual learning objects from scratch is often the central activity. As content can vary from static to interactive or from textual to multimediabased, it is difficult to provide a universal approach here. We will focus on supporting interactive multimedia content here. With increasing complexity of these systems, reusing components is gaining importance. A number of metadata and annotation standards—such as the IEEE Learning Object Metadata standard LOM (IEEE LTSC, 2002)—have been developed that allow providers to describe and publish their learning objects and potential users to discover suitable resources. The assembly of components (e.g., sequencing of learning objects) is another important task. The Learning Technology Standard Architecture LTSA (IEEE LTSC, 2002) is a reference architecture onto which learning objects and other infrastructure components can be mapped. The logical assembly of learning objects or units of learning can be expressed in terms of the SCORM Sequencing and Navigation (SN) standard (ADL, 2004). The final step that follows the design activities in the system implementation. The SCORM Run-Time Environment (RTE) standard (ADL, 2004) addresses the deliv-

A Conceptual Architecture for the Development of Interactive Educational Multimedia

ery of learning content, possibly based on assemblies expressed using SCORM SN.

Figure 2. A conceptual architecture for interactive educational multimedia

Our focus will be on the first aspect even though the context is important, as our approach will need to be embedded into a more comprehensive framework.

Learning Learning Activity Activity · purpose · involvement

problem space

Knowledge and Intelligent Systems An intelligent e-learning and training system is based on three knowledge components: domain, learner, and instructional knowledge (Burns & Capps, 1988). While we do not address the implementation of an intelligent learning or tutoring system here, our aim is to address knowledge aspects that arise during development—in particular with respect to domain and instructional knowledge and their explicit representation.

learning tasks

learning interaction

Cognitive Cognitive Architecture Architecture · concepts · problem space

Goal Goal && Task Task ModelModel · learning goals · tasks and subtasks

Linguistic Linguistic Model Model · interaction style · dialogue

topology

tasks

interaction

infrastructure

activities

language

MediaMedia Functionality Functionality · supported activity · media type

Interface Interface Language Language · lang. elements · grammar

Channels Channels · modality · channel type

State-of-the-Art Recent work addressing the development of educational multimedia (Okamoto et al., 2001; Pahl, 2003; Trikic, 2001) does not provide an adequate conceptual framework that can form an underpinning for the development of these systems. A coherent architecture integrating the different notions of interactivity is, however, necessary to support the seamless implementation of educational concepts in multimedia technology.

A Conceptual Architecture Interaction is central in the development and implementation of learning activity. An interaction model focussing on learner-content interaction forms the core of our conceptual development architecture. It shall capture and relate meaningful activities and interactions with educational multimedia. This will seamlessly embed interactive multimedia into the educational context.

The Architecture The notion of interaction has a meaning in different contexts. Clarifying these meanings in a terminological framework is important. We can distinguish three perspectives on interaction—presented in three layers of the architecture: learning and training interaction, human-computer interaction, and interactive educational multimedia. Overall, the conceptual architecture (see Figure 2) is a combination of: •

•

A taxonomy: a structured terminology that allows the description, classification, and comparison of interaction-related knowledge of educational technology systems; A conceptual model: an integrated model that captures the various perspectives on activities and interaction in the three layers; and

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•

A process model: a development framework that guides instructors, instructional designers, and software developers through the stages of educational multimedia development based on the layered model.

The Case Study Our case study—the Interactive Databases Learning Environment (IDLE)—is a Web-based e-learning and training system providing an online undergraduate introduction to databases (Murray et al., 2003; Pahl et al., 2004). It supports learning and training activities such as design, implementation, and analysis of database applications, enabled by a variety of media features including interactive applets for graphical modelling, audio-supported lectures, simulations and other animation types to explain the behaviour of a database system, and a variety of text-based submission, execution, and feedback features. We describe the development of IDLE in stages that follow the layers of the conceptual architecture.

LEARNING AND TRAINING INTERACTION Learning should be an active process in which interactivity is central (Northrup, 2001). The aim of an interaction model at this level is to support the design of learning activity. Moore (1992) distinguishes three types of interactions—learnerlearner, learner-instructor, and learner-content. It is often argued (Ohl, 2001; Sims, 1997) that content has a more central function in computerbased education than interaction with peers or instructors. Ohl defines interaction as an internal dialogue of reflective thought that occurs between learner and the content.

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Activity Model The learning and training activities facilitated by educational multimedia interactions between learner and content shall be captured in the form of an activity model. We distinguish two aspects: •

•

We can define activity types based on the purpose of the learning process. We introduce three types (see Table 1). The second category is particularly important in the sciences and engineering domain where an understanding of the subject activities is required for a learner. The style of the activity execution can be based on the degree of involvement and influence of the learner on the environment, see Table 2. We can distinguish environment types ranging from system-controlled to learner-controlled.

Often the two aspects are related. Declarative knowledge is often acquired through observation, procedural knowledge for reasoning purposes through controlled animations, and skills through artefact creation and processing. The individual types for each of the categories are not meant to be exclusive—a more fine-granular classification can replace our types if needed.

Learning and Training Interaction: The Case Study The learning-by-doing idea is part of the active learning approach. It captures the interplay of knowledge acquisition and knowledge creation in an interactive process with the learning environment. We have widened this focus in IDLE by considering knowledge acquisition on the one hand and skills and experience acquisition on the other hand as dual sides of learning and training.

A Conceptual Architecture for the Development of Interactive Educational Multimedia

Table 1. Activity types based on learning purpose Activity Type

Description

declarative knowledge acquisition activities

the aim is the acquisition of declarative knowledge in order to reason about it

procedural knowledge acquisition activities

the aim is the acquisition of procedural knowledge in order to reason about it

skills acquisition activities

the aim is the acquisition of procedural knowledge and experience in order to perform the instructions

Table 2. Activity types based on degree of involvement Activity Type

Description

observation

a form of knowledge acquisition with no influence on the environment activities by a passive learner

controlling

a form of knowledge acquisition mixed with knowledge production, based on observational elements, but allowing the learner to influence the environment activities to control their ordering

creation

a form of activity where knowledge or skills are created by producing some form of artefact that can be processed by the learning environment

Table 3. IDLE activities and their types based on learning purpose and degree of involvement Activity

Activity Type (Purpose)

Activity Type (Involvement)

lecture participation

declarative knowledge acquisition

tutorial participation

procedural knowledge acquisition

controlling

lab participation

skills acquisition

creation

The virtual apprenticeship model (Murray et al., 2003) is a pedagogical theory—based on terminology defined in the activity model—that defines an activity-based and skills-oriented learning and training framework for the IDLE system. An apprentice is a learner who is coached by a master to perform a specific task. In an e-learning and training environment, the master’s role is often replaced by an intelligent software tool such as IDLE. Tools reflect the experience that people, such as the apprentice’s master or the instructor,

observation

have had in trying to solve a particular problem. The apprenticeship model determines a number of aspects including the activity purpose and the degree of involvement, interaction styles (e.g., the organisation of learning into sessions and cycles), and the interconnectedness of activities and features. The virtual apprenticeship model puts an emphasis on skills-oriented activities with a high degree of involvement of the learner. The main activity categories are summarised in Table 3. Further categorisation is, however, necessary for a

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detailed design. For instance, the lab activity could be refined into specific activities such as graphical design, programming, or optimisation. One of the skills acquisition activities in the IDLE system is SQL (i.e., database) programming. Integrated with a database system, the student—a virtual apprentice—works through guided material covering a range of individual problems. Each problem is based on a submission- and execution-cycle with a high degree of involvement of the learner through knowledge creation. Each solution—content-specific knowledge that is created by the learner—is analysed and, based on an individual activity history and integrated assessments, personalised feedback is given by the virtual master. At this level, the concern is the abstract classification of learner activities in the context of the pedagogical model. For the database course IDLE, the central design decision at this level is to focus on an integrated approach with a strong support of skills training activities.

HUMAN-COMPUTER INTERACTION Architectures and Models The notion of learning as a dialogue between learner and content (Ohl, 2001) needs to be adapted to the human-computer environment (Dix et al., 1993). Models for this context formulate these interactive dialogues as cycles consisting of computer-based executions and human evaluations (Norman, 1998). Three models are essential for human-computer interaction: •

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A cognitive architecture for the educational context addresses cognitive learning processes as interactions in the humancomputer environment. The architecture provided by a computer-supported learning and training system defines a problem space based on the central concepts of the subject

•

•

domain in which a learner should be able to accomplish a learning goal. The architecture is defined by the actions that allow the learner to traverse the space, namely, to learn and train, and by the desirable states that represent the successful accomplishment of the goal, namely, to find a solution for the learning goal. The task and goal model is based on learner goals and activities. A task is an operation to manipulate concepts of the subject domain, that is, a goal is the desired output from a task. A hierarchy is defined by dividing goals into subgoals and tasks to accomplish these subgoals. A learning strategy defines how learning goals on the same level are connected. The tasks have to be mapped onto the actions supported by the multimedia infrastructure. Different interaction styles and learning activity dialogues, for example, different pedagogical activities, are captured in a linguistic model through basic vocabularies and user-system grammars. Style examples include commands, direct manipulation, menus, or form fill. The purpose of a language capturing the interaction processes is the specification of learner dialogues, including the sentence elements, the legal user actions, and the system responses.

Scenarios A representational form to express learning activities at the human-computer interface are scenarios (Bødker, 2000). Scenarios are brief descriptions of interactions of a user with a system. We use a scenario language that is close to the SCORM sequencing and navigation standard (SN). We use sequencing operators such as choice and flow. We also use rules that constrain behaviour. SCORM SN, however, is a declarative format, whereas we prefer here an operational format. It suits the

A Conceptual Architecture for the Development of Interactive Educational Multimedia

design view for individual content components better, since SCORM SN assumes a navigation approach between components, while we focus on internal behaviour not restricted to navigation. Scenarios can be used to refine the learning activities from the first stage. Scenarios relate to different models on the human-computer interaction layer of our conceptual architecture: •

• •

The cognitive architecture defines the basis including concepts and procedures on which scenarios can be expressed. The possibility to refine abstract activities allows tasks and subtasks to be defined. Scenarios formulate the grammar of a linguistic model.

A scenario language based on the problem space combines two aspects. Firstly, knowledge and content creation and processing aspects are covered. Secondly, dialogue activities and interaction patterns can be described.

Human-Computer Interaction: The Case Study The interface between learner and multimedia system is defined by three models: •

Cognitive architecture: The IDLE learning and problem space is based on sub-

•

•

ject-specific concepts such as data models and implementation languages, as well as subject-specific activities. An example is presented in Figure 3 that classifies queries in the database language SQL. Task and goal model: Learners will traverse the problem space in order to accomplish learning goals. To develop a database application using IDLE is one of the central course goals; it involves tasks such as modelling, implementation, and optimisation. These tasks have to be mapped onto activities that are supported by the educational multimedia environment. Linguistic model: The linguistic model has to enable and structure activities. Different linguistic styles can be deployed; for example, direct manipulation for the data modelling tasks or a forms-based input facility to submit SQL database programs for execution.

The problem space defined by the cognitive architecture resembles a domain ontology for the subject domain—it identifies the central concepts and their properties. Figure 3 is an example. This complements other explicit knowledge, for example, on learning and interaction, that is made explicit. For the database context, the cognitive architecture is defined by concepts such as database table or query statement. Dependencies

Figure 3. Conceptual architecture in form of an activity tree SQL

SQL basic

simple simple

SQL advanced

nested nested

aggregation aggregation

sorted sorted

union union

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between the concepts define the problem space topology. For instance, the table concept is more basic than an SQL query (which is an operation on tables). An example shall illustrate the scenario language to support the task/goal model and the linguistic model (see Figure 4), which is based on an underlying cognitive architecture for SQL organised in form of an activity tree (see Figure 3). The scenario specifies exercise activities for SQL queries that define the user-system dialogue—it combines the tutorial navigation with lab programming activities.

INTERACTIVE EDUCATIONAL MULTIMEDIA Learner-content interaction in computer-supported learning and training actually occurs as interaction between the interactive multimedia features that implement the cognitive architecture and the linguistic model, and that enable the tasks to be executed and the learning goals to be accomplished. Multimedia systems for education are usually hypermedia systems providing structure through hierarchy and guidance for learning tasks through navigation topologies (Jonassen & Mandl, 1990). Different media supporting different activities are connected through hypermedia structures. Crucial for educational multimedia

Figure 4. Scenario SQL training Scenario SQL training SQL : flow basic : flow simple_query(table) nested_query(tables) if completed then continue advanced : choice aggregation(table) sorted_output(table) union(tables) if completed then exit

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are the multimedia interface and the interaction dialogues a multimedia system allows through channels (text, mouse, etc.) and languages (natural, formal, etc.). Interactive multimedia for activity-based learning and training can be distinguished into interaction with knowledge media and with activity media. Activity-based training focuses on skills-oriented activities, but needs to be integrated with knowledge learning aspects. Knowledge media focus on knowledge information to be communicated. Activity media focus on artefacts that are produced and processed in activities. The purpose of interactive educational multimedia is twofold: •

•

In addition to knowledge-level interaction, domain-specific activities need to be facilitated, that is, activity-level interaction with the educational multimedia feature through artefacts and instructions has to be enabled. The instructor can be replaced by a virtual form of an intelligent educational multimedia feature that provides advice and feedback, thus adding more meaning to the interaction.

Educational Media Taxonomy We can classify educational multimedia through different metadata facets (see Table 4) —essentially, different dimensions that allow us to describe educational media. We distinguish two facet types: •

•

General multimedia facets cover multimedia aspects such as channel and language. These facets together describe a medium as a coordinated set of channels and their languages. It is important, however, to develop an education-specific view on multimedia. Education-specific facets cover aspects specific to learning and training such as the

A Conceptual Architecture for the Development of Interactive Educational Multimedia

Table 4. Educational multimedia facets Facet

Type

Range

Description

channel

general

common range

the abstraction of a communication device, characterised by modality

language

general

not restricted but can be categorised

information is encoded in common language for communication over a channel

activity purpose

education

predefined

distinguishes whether declarative knowledge reasoning, procedural knowledge reasoning, or skills acquisition is aimed at

activity style

education

predefined

classification of activities into observation, controlling, and creation that describes the degree of influence of a learner on the environment

content topic

education

no restriction

topic or domain within which activities or knowledge-level access is provided

activity purpose, the activity style, and the content topic. The range in Table 4 refers to the possible set of values of each facet. The aim of this taxonomy is to describe, distinguish, and classify educational multimedia. It supports the development and the comparison of educational media objects. This aims at an abstract description of multimedia from an educational perspective. Strict adherence to description standards is not the primary concern here, since design is our focus. The two general facets of multimedia—channel and language—shall be revisited in the context of education. In comparison with classical uses of multimedia for knowledge-oriented learning (Heller et al., 2001), here the interaction between learner and content, determined by the channels and their languages, is more central.

Educational Multimedia Channels Multimedia is about channels and meaningful communication along these channels. Often, a natural language such as English is used over a text channel (written English) or over an audio channel (spoken English). For our context, we

will identify a number of specific educational channels—supporting partly more formal languages, partly languages specific to the subject or instruction context (see Table 5). We distinguish two types of channels—those that support core content-oriented learning activities and those that are part of the meta-context of instruction; the latter including instruction-related learner actions and coaching actions by a master or instructor.

Educational Multimedia Interface Language Multimedia interface languages capture and constrain the channel communications. A language defines the interaction dialogues; it describes the legal actions, how a learner can engage in an activity, or how a learner can perform a task towards a learning goal. These interaction languages detail dialogue structure captured in the scenario language. The difficulty in defining an adequate language is to capture all three interaction model layers. The learning and training interaction model provides the conceptual model in which the language semantics is to be defined. We can classify languages for the educational context based on content-related aspects:

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A Conceptual Architecture for the Development of Interactive Educational Multimedia

Table 5. Educational channels Channel

• •

•

Type

Description

declarative knowledge

core

declarative knowledge usually communicated in a domain-specific natural or formal language

procedural knowledge

core

procedural knowledge usually communicated in a domain-specific natural or formal language

skills

core

artefacts to be processed in form of activities are communicated with corresponding execution instructions

actions

meta

instruction-related actions executed by the learner (navigation or location of learning units)

feedback

meta

response of the system for each core activity

coaching

meta

meta-level information capturing an instructor’s advice and guidance

Natural languages—in text or audio form— are often the basis of content. Formal languages—in text form—are often involved if some sort of mechanical processing is part of the subject domain. Simulations—automated processing of some real-world activities—are based on objects and procedures from the subject domain.

In addition to the content aspect, dialogue and interaction patterns form the instructional aspect addressed by interface languages. On the most basic level, the learner interacts with multimedia—usually through keyboard- and mousebased input; output can be static visual (text, graphics), dynamic visual (animations, video), or involve other modalities such as audio. The basic inputs are part of low-level activities such as navigation (knowledge acquisition request) or text input/submission (knowledge generation). A learning activity can be composed of more basic activities. The dialogue and interaction part of the language consists of: •

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Basic activities: select (knowledge acquisition by learner), submit (knowledge generation by learner), reply (response to knowledge acquisition/generation) ;

• •

Activity combinators: ; (sequence), ! (iteration), | (choice) ; System components: learner and multimedia system in a simple e-learning architecture.

Interactive Educational Multimedia: The Case Study Activities are supported by multimedia features. IDLE supports three classical forms of third-level teaching—lectures, tutorials, and labs—in a virtual form. These three forms can be described using the educational multimedia classification scheme (see Table 6), which describes how some selected learning activity styles for particular topics are mapped onto multimedia features. For example, a simulation can be a subcategory of a moving pictures/images language. However, the elements of simulations can be identified and have meaning in the context of content (e.g., tables or records in the database context). Equally, operations (simulation activities) are represented in the procedural knowledge. The channel and language characterisation using the taxonomy in Table 6 is high-level. These two aspects can be described in more detail. Table 7 provides a channel-oriented view on IDLE; it lists

A Conceptual Architecture for the Development of Interactive Educational Multimedia

Table 6. Sample IDLE media classification Facet Activity

Channel

Language

Purpose

Type

Topic

lecture

text and audio

declarative knowledge

observation

introduction to database

tutorial

dynamic animation simulation

procedural knowledge

controlling

relational algebra

lab

text

skills-oriented activities

creation

SQL

natural language formal language

Table 7. Sample IDLE media channels Channel

Feature

Activity

declarative knowledge

database introduction lecture

HMTL and audio-based synchronized virtual lecture

natural language (wirtten and spoken)

procedural knowledge

relational algebra animation

interactive simulation of algebra operator execution

formal language (interaction animation control)

skills

SQL programming lab

submission o query solutions and dynamic page update by system

formal language—SQL (solution and result)

action

SQL tutorial navigation

guided tour through a series of connected exercises

formal lnaguage (interaction—navigation)

feedback

SQL programming lab

correction and provision of partial solutions for SQL exercises

semi-formal language (text and error classification

coaching

self-assessment

multiple choice questions and virtual master's feedback

natural language (written)

the educational channel types and some sample features that are based on these channels. The interaction language is based on the scenario language. The expression: ! ( LR.select(exercise); LR.submit(solution); MM.reply(result) )

is the interaction specification of an exercise activity scenario. A language needs to facilitate declarative and procedural knowledge communication, skills-oriented activity execution, learner actions, and meta-level pedagogical interactions (coaching). select denotes a learner action; submit and reply support skills-oriented activities; and reply could, in addition to conveying, for example, SQL submission results, also convey

Language

meta-level feedback and coaching. In contrast to scenarios, we distinguish here between learner (LR) and multimedia system (MM) components. For instance, the SQL multimedia lab system (MM) replies with a result that includes the result of the solution execution and feedback.

FUTURE TRENDS Developments on both the educational and the technological side will influence educational multimedia design and implementation in the future.

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A Conceptual Architecture for the Development of Interactive Educational Multimedia

•

•

The importance of learner involvement and activity has long been recognised (Northrup, 2001). In the corporate sector, activity- and skills-based learning and training is becoming increasingly essential. A number of issues will impact multimedia technology development (Elsom-Cook, 2001). The fact that knowledge is becoming central in our societies will be reflected in multimedia through the integration of knowledge management and the support of processes of communications.

The development of e-learning technology moves closer to systems where multimedia technology excels. On the other hand, multimedia also moves towards knowledge, languages, and the Web—which are all central aspects of computer-supported learning and training technology. Knowledge management is central for intelligent e-learning systems, both for content and learner modelling. Practically, knowledge representation frameworks such as ontologies and other metadata languages and standards will impact the area. Development of interactive educational multimedia is the context of the presented conceptual architecture. Other uses of the architecture can, however, be considered: •

•

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Standardisation and metadata: There is a similarity between the taxonomy we introduced and metadata frameworks, such as the IEEE Learning Object Metadata (LOM) standard. Our focus here is on multimedia, interactivity, and the process of development. An integration with LOM is nonetheless possible. Multimedia development is expensive; therefore, sharing and reuse is desirable and, consequently, annotations are needed to facilitate this. Multimedia integration and assembly: Multimedia features can be combined with complex systems through channel assem-

bly and language integration. This type of context would form part of a development framework for multimedia architectures. The process of educational multimedia development and management needs to be supported by a coherent engineering framework, integrating different development activities.

CONCLUSION Activity-based learning and training based on interactive educational multimedia can provide an answer for the current need to support not only knowledge acquisition, but also skills and experience acquisition in computer-supported educational environments. In this chapter, we have investigated the development of interactive educational multimedia as a platform to implement activity-based learning and training through a conceptual architecture. •

•

A taxonomy based on the conceptual models allows us to describe activities, interactions, and multimedia objects and their channels and languages and compare different systems. Detailed technical descriptions allow the implementation and integration of educational technology components. An intricate understanding of the interaction characteristics of each of these components on all three layers is essential.

This architecture provides support for instructors, instructional designers, and software developers in a participative, multi-stage development environment. It is meant as an open architecture, that is, open to further extensions, integration with other frameworks and standards, and adaptations to particular needs.

A Conceptual Architecture for the Development of Interactive Educational Multimedia

One of the central lessons we have learned over the years of developing, managing, and maintaining educational multimedia systems is that there are a number of reasons for a domainspecific, systematic, and co-operative approach to activity-based learning and training systems development: 1.

2.

3.

4.

Interactivity is central and especially complex in the educational domain. The learning and training activities need to be embedded into a pedagogical framework in order to achieve a high-quality learning experience. A domain-specific approach is therefore needed. The need for activity-based education is increasing. Consequently, the integration and maintenance of educational multimedia is becoming increasingly a problem. Only a systematic approach to development and maintenance can provide a solution. Learning and training are multi-channel and multi-language activities. Seamlessly integrated interactive multimedia is therefore an ideal support technology. Instructors, instructional designers, and software developers need to co-operate in the development of these systems that are characterised by complex learning and instruction processes on the one hand and advanced multimedia technology on the other.

One of our objectives was to provide a central element for such a development approach and to guide educational system design through our architecture. Interactive multimedia has the potential to support innovative approaches of teaching and learning, but in order to be successful, it needs to be embedded into a systematic and comprehensive framework for development and management.

REFERENCES ADL. (2004). Sharable Content Object Reference Model (SCORM)—Content Aggregation Model (CAM), Run-Time Environment (RTE), Sequencing and Navigation (SN). Retrieved June 12, 2004, from http://www.adlnet.org/index. cfm?fuseaction=scormabt Bødker, S. (2000). Scenarios in user-centred design: Setting the stage for reflection and action. Interacting with Computers, 13(1), 61-75. Burns, H.L. & Capps, C.G. (1988). Foundations of intelligent tutoring systems: An introduction. In M.C. Polson & J. J. Richardson (Eds.), Foundations of intelligent tutoring systems. Hillsdale, NJ: Lawrence Erlbaum Associates. Dix, A., Finlay, J., Abowd, G., & Beale, R. (1993). Human-computer interaction. London: Prentice Hall. Elsom-Cook, M. (2001). Principles of interactive multimedia. London: McGraw-Hill. Heller, R.A., Martin, C.D., Haneef, N., & GievskaKrliu, S. (2001). Using a theoretical multimedia taxonomy framework. Journal of Educational Resources in Computing, 1(1). Retrieved June 21, 2005, from http://portal.acm.org/citation. cfm?id=376701 IEEE LTSC (Learning Technology Standards Committee) (2002). Learning Object Metadata (LOM) (1484.12.1) and Learning Technology Standard Architecture (LTSA). Retrieved June 12, 2004, from http://ltsc.ieee.org/ Jonassen, D.H. & Mandl, H. (Eds.) (1990). Designing hypermedia for learning. Berlin: Springer-Verlag. Moore, M.G. (1992). Three types of interaction. The American Journal of Distance Education, 3(2), 1-6.

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Murray, S., Ryan, J., & Pahl, C. (2003). A toolmediated cognitive apprenticeship approach for a computer engineering course. In Proceedings of IEEE International Conference on Advanced Learning Technologies ICALT’03, Athens, Greece, June 9-11 (pp. 2-6). IEEE Press. Norman, K.L. (1998). Collaborative interactions in support of learning: Models, metaphors, and management. In R. Hazemi, S. Wilbur, & S. Hailes (Eds.), The digital university: Reinventing the academy (pp. 39-53). London: Springer-Verlag. Northrup, P. (2001). A framework for designing interactivity into Web-based instruction. Educational Technology, 41(2), 31-39. Ohl, T.M. (2001). An interaction-centric learning model. Journal of Educational Multimedia and Hypermedia, 10(4), 311-332. Okamoto, T., Cristea, A., & Kayama, M. (2001). Future integrated learning environments with multimedia. Journal of Computer Assisted Learning, 17, 4-12.

Pahl, C. (2003). Evolution and change in Webbased teaching and learning environments. Computers & Education, 40(1), 99-114. Pahl, C., Barrett, R., &. Kenny, C. (2004). Supporting active database learning and training through interactive multimedia. In Proceedings of International Conference on Innovation and Technology in Computer Science Education ITiCSE’04, Leeds, UK, June 28-30 (pp. 27-31). New York: ACM Press. Ravenscroft, A., Tait, K., & Hughes, I. (1998). Beyond the media: Knowledge level interaction and guided integration for CBL systems. Computers & Education, 30(1/2), 49-56. Sims, R. (1997). Interactive learning as “emerging” technology: A reassessment of interactive and instructional design strategies. Australian Journal of Educational Technology, 13(1), 68-84. Trikic, A. (2001). Evolving open learning environments using hypermedia technology. Journal of Computer Assisted Learning, 17, 186-199.

This work was previously published in Web-Based Intelligent E-Learning Systems: Technologies and Applications, edited by Z. Ma, pp. 101-121, copyright 2006 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.4

Hypermedia Modules for Distance Learning Nicoletta Sala Università della Svizzera italiana, Switzerland

INTRODUCTION The rapid development of digital, networked multimedia technology such as the Internet, e-mail and computer-based and video conferencing can open new educational opportunities. This chapter describes the use of hypermedia modules in distance learning. This educational experience has been developed by the Department of Electronics (Dipartimento di Elettronica) of the Politecnico of Torino (Italy) in the field of computer-based training in electronic instrumentation and measurements, where the author was a supervisor for the educational process. This project is a part of an Italian study of distance education named “Consorzio Nettuno” that involves different undergraduate courses (Electronic Engineering, Information Technology, and Economic Science). Several modules have been developed using multimedia technologies to assist the students to acquire the fundamentals of the basic electronic instrumentation. A client-server system has been designed in order to allow the students to operate in a remote laboratory for experimental train-

ing. The courseware includes lessons, exercises, and training on virtual instruments that emulate actual instruments. The students can also carry out several real laboratory experiments without actually being in the laboratory by using a clientserver structure based on the Internet.

BACKGROUND The education experiment named “Consorzio Nettuno” (“Neptune Consortium”) was started in Italy in 1991 to create a distance university education using the television as a medium in the learning process. The “Consorzio Nettuno” is comprised of 34 Italian universities and the Open University (UK), and 285 university courses (electronic engineering, economic sciences, etc.). The project’s targets are: • •

To offer a formative approach free from space and time encumbrances To develop active national and transnational collaborations

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Hypermedia Modules for Distance Learning

•

To use the new technologies inside the learning process

The didactic model is a psycho-pedagogical mixed model that empowers, through the use of new technologies, the teaching system of traditional universities. It realizes a synchronic and diachronic teaching and learning system, without limits of time and space that includes a direct phase of interaction between teachers and students, both face-to-face and at a distance (Garito, 2001). In the first step of the experiment, the lectures are broadcast on TV or distributed on videocassettes, and it is possible to use the Internet as a medium to create an educational cyberspace. Using these media, there are some problems in transmitting the correct information on some particular technical subjects; for example, to train students to use electronic instrumentation, because students are still required to attend laboratories to achieve practical experience under the guidance of an instructor. In fact, education in fields such as electronic measurement requires students to gain a reasonable skill in using various kinds of instrumentation (Pisani, Cambiotti, Sala, & Sanpietro, 1995). Such a skill cannot be achieved by theoretical lessons only—an intensive laboratory activity is also always required. This problem exists both for the first level and for qualifying courses (Sala, 1999a). Basic instrumentation teaching is required for first-level courses that are taken by a large number of students. The cost of basic level instruments is often low, but large classes require large workbench availability and a massive and qualified assistance that is not easily found. Qualifying courses are taken by fewer students so that the assistance problem is reduced, but the instrument cost in such a case is often rather high, thus preventing the possibility of arranging more than a few workbenches. For these reasons, some years ago, the Department of Electronics of the Politecnico of Torino was involved in activating traditional degree and diploma courses in several educational structures

750

for the “Consorzio Nettuno.” It was decided to invest time and resources to develop an alternative solution to the laboratory replication by using the new technologies offered by computer-based multimedia courseware. The goal was to allow the students to carry out a pre-training activity outside the laboratory and possibly at home (Sala, 2003). After this pre-training phase, students who enter the laboratory require less assistance and less time to complete the training activity. About seven years ago, several tutorial modules were developed that were organized like lectures, each being on a particular subject. Each module contains theoretical and functional concepts of a basic electronic instrument and allows for simulated instrument exercises by providing a series of instrument simulators. By means of the realistic control panel of the virtual instrument, the students practice under several operating conditions and situations. In addition, it was decided to explore the possibility of making a real instrument laboratory available for use at home.

HYPERMEDIA MODULES TO INTRODUCE THE ELECTRONIC INSTRUMENTATION FOR DISTANCE EDUCATION The actual curriculum of the engineering school includes courses where the first practice electronic laboratory precedes the first lectures in which the students learn the theoretical and functional aspects of the instrumentation; deeper knowledge comes in a successive phase based on the actual student requirements (Brofferio, 1998). It seemed to be necessary to provide the first course to students by multimedia tools that allow them to use basic instrumentation in simple physics and initial electronic circuit laboratories. If these tools are organized based on different levels of knowledge, it is possible to satisfy different needs of different kind of students (undergraduate school level or university education). On the basis of

Hypermedia Modules for Distance Learning

the previous consideration, some hypermedia didactic modules have been designed with the following purposes: •

•

To expose students to a comprehensive range of electronic instruments and basic measurements techniques To allow students to practice on the particular instrument whose front panel is simulated on the monitor and whose behaviour is emulated by computer.

This case is oriented to defined objectives of knowledge, and it is based on a student model with a defined knowledge background, so it was decided to guide the students through a path, based on a structured didactic methodology, to reach the proposed educational goal (Bloom’s taxonomy) (Pisani, Cambiotti, Sala & Sanpietro, 1995). For example, a student of a first electric circuits course should learn the oscilloscope or meter behaviour and should be able to handle them, while the post-graduate student should be more deeply interested in the internal circuitry and use these instruments in more sophisticated applications also involving uncertainty evaluation. Each module is divided into subjects (pages) at the same hierarchical level; each level contains a subset of other pages, placed at a lower levels. Hyperlinks among pages have been studied to give continuity to learning trail. In the modules, different media are involved and their use is calibrated to avoid the cognitive overload (Sala, 1999b). We have: •

•

•

Figure 1 shows a hypermedia page dedicated to the spectrum analyser; there is a video that explains the instrument functions. Virtual instruments are also implemented in the multimedia packages in order to allow simple simulations of the real instruments during the self-training phase. For example, when learning the oscilloscope, the student has a virtual instrument panel available, where he/she can select the input signals and can evaluate the effects of the instrument setting on the display. Each lecture includes several tests to verify the level of the acquired knowledge on the educational objectives and lesson subjects. The test results are stored into a database file, which can be processed by an external Data Base Management System (DBMS) program with the possibility of extracting statistical indicators on the class by DBMS query. The examinations include: •

A puzzle, where students must rebuild an instrument block diagram (e.g., oscilloscope or electronic instrument) or measurement procedures

Figure 1. A hypermedia page dedicated to the spectrum analyser with a video that explains the instrument functions

Animation techniques (which are an efficient learning tool when the teaching of a subject would be difficult by a written description alone) Audio support to emphasize a particular topic in a lesson (e.g., to explain an electronic circuit) Digital television camera images (to zoom-in on an instrument inside)

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Hypermedia Modules for Distance Learning

• •

Laboratory quizzes using multiple choice questions Simple projects that could require some data processing

In all exercises, the data are randomly selected to always generate new projects entry points. The students can adapt the learning rate to their time availability and cultural background. They can study the theory using the hypermedia modules (on CD-ROM) and then self-verify their knowledge level by solving practical exercises and answering a series of questions (available on the CD-ROM). This approach is a kind of Kolb’s experiential learning (Greenaway, 2004; Henry, 1989; Kolb, 1984). Pimentel (1999) affirms that distance learning naturally tends towards the use of Kolb’s Theory of Experiential Learning: “The fundamental idea behind the concept of a technology for learning is a simulated situation designed to create personal experiences for learners that serve to initiate their own process of inquiry and understanding” (p. 64). The student only needs an inexpensive personal computer with a multimedia extension that is available in centralised areas of the university or possibly at home. At present, several modules concerning the basic laboratory instrumentation have been developed using ToolbookTM or HyperText Mark-up Language (HTML), with the aid of several thesis students. Instrument behaviour knowledge is only part of the know-how that is required to carry out a measurement. Performing a measurement is not very easy, as it requires one to define measurement procedures, to use and correctly connect different instruments, and finally to process the experimental data. This knowledge is traditionally achieved by performing practical activities in different subjects. Unfortunately, such an approach, which requires intensive laboratory attendance, cannot be followed in distance learning courses. An additional step is necessary to break the time/distance constraint.

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A possible solution could be attained by taking advantage of modern instrumentation, which is equipped with a standard computer interface and is remotely programmable. The idea is to design a laboratory that is simultaneously and remotely accessible to several students, who concurrently share the same instrumentation but not necessarily the same experiment. The instrumentation and the other hardware resources are accessible in a sort of time-sharing process that is managed by a server and transparent to the user (Pisani, Cambiotti, Corinto, & Romano, 2003). The virtual laboratory architecture is composed of two kinds of subsystems: the measurement server and the measurement clients. The measurement server is a computer located in the laboratory and directly connected to the programmable instrumentation. The server program that runs on the measurement server accepts measurement requests from several clients, dispatches the commands to the instruments, and sends the responses back to the clients. The measurement clients are computers running a program that enables the students to manage their experiments via suitable virtual panels and is able to contact the server and display the measurement results. Many solutions, based on proprietary or standard protocols, can be designed to obtain the connection between clients and the server. The standard protocols that are based on the TCP/IP protocol suite use the highest possible protocol layer. Such a choice restricts the connection flexibility but makes the developed system easily portable to different platforms and greatly simplifies the program development.

FUTURE TRENDS In the rapidly changing cultural environment of our contemporary “knowledge society,” we cannot consider distance education as a simple transfer of contents at distance. Thus, there are

Hypermedia Modules for Distance Learning

some European projects that intend to create the European Virtual University (EVU) as a network of traditional and distance universities and technical companies to adapt, co-produce, and deliver university courses in the field of computer science and telecommunication engineering with the recognition of the related credits at the national and European level. These projects will use new dynamic learning environments. •

•

• •

•

An example in this field is the Learning in Virtual Integrated University System (LIVIUS) Project (http://www.uninettuno. it/livius/livius.htm). The LIVIUS project aims to supply appropriate answers to the needs identified in the action plan for e-Learning, “Defining Tomorrow’s Education.” LIVIUS’s purpose is the development of European knowledge virtual networks that use the Internet and new technologies to enhance the quality of learning, to make access to resources and services easier, and to promote cooperation and the exchange of knowledge and information. The project has the following general objectives:create a new organizational and psycho-pedagogical model of European Virtual Association of Universities Develop cooperation among the partners in order to design didactic paths and common academic curricula that allow the acknowledgement of titles at a European level Transfer knowledge by means of the new technologies Innovate teaching and learning methods and favour the rapid exchange of information and data Answer the need for flexibility to prevent student isolation, matching presence with distance and thereby maintaining direct interaction among the students and between students and professors

•

•

Update the roles of the student and of the teacher who will have to design learning scenarios Produce two pilot modules of 20 hours of video-lessons, each one in four different languages (English, French, Spanish, and Italian) in Computer Science Engineering and Telecommunication Engineering to be broadcast on the two satellite channels, Rainettunosat1 and Rainettunosat2

CONCLUSION A fundamental shift is occurring in education as a result of the increasing use of computers and multimedia technologies (Crinon, 2001; Mishra & Sharma, 2004). Strange (1995) calls the shift a cultural revolution in teaching and learning. The extent of the changes due to this cultural revolution vary depending on the districts, schools, and teachers (Rath, Rieck, & Wadsworth, 1998). The use of multimedia solutions in degree-level courses has proven to be effective in several different fields. The solution presented for Electronic Measurement courses is an example of an integrated solution in which the theoretical part is made available through hypermedia and the laboratory part can be carried out by accessing real instruments through a network connection. Courseware with important laboratory activities can also be tackled by adding an experimental section to the conventional theoretical approach. Teletraining traditionally is related to distance learning and delineates a perspective of education related only to the aspect of computer-communication technology of distance education that is referred to as the separation of teacher and students in space/time, and also to the methodologies improving electronic materials for instruction. The hypermedia modules to train students to use electronic instrumentation is an approach of distance education. This solution, inserted in the “Consorzio Nettuno,” is an

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example of teletraining where the television plays a central role but it is mediated by the use of the Internet, with an educational “cyberspace” created on the World Wide Web. It is also supported by hypermedia modules (on CD-ROM and others available online) that introduce the theoretical parts on basic electronic instrumentation. This approach is in agreement with the Lazarsfeld and Knupfer (1945) point of view that the media of mass communication can be used to build up something like an educational campaign.

REFERENCES Brofferio, S.C. (1998). A university distance lesson system: Experiments, services, and future developments. IEEE Transactions on Education, 41(1): 17- 24. Crinon, J. (2001). Apprendre avec le multimédia et Internet. Paris: Retz. Garito, A.M. (2001). Nettuno. The university to watch, browse and surf on! Retrieved December 10, 2003, from: http://www.uninettuno.it/nettuno/index.htm Greenaway, R. (2004). Experiential learning articles and critiques of David Kolb’s theory. Retrieved May 10, 2004, from: http://reviewing. co.uk/research/experiential.learning.htm Henry, J. (1989). Meaning and practice in experiential learning. In S. Weil & I. McGill (Eds.), Making sense of experiential learning: Diversity in theory and practice (pp. 29-33). Buckingham, UK: SRHE/OU Press, Milton Keynes. Kolb, D.A. (1984). Experiential learning - Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall. Lazarsfeld, P., & Knupfer, G. (1945). Communications research and international cooperation. In R. Linton (Ed.), The science of man in the world crisis. New York: Columbia University Press.

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Mishra, S. & Sharma, R.C. (2004). Interactive multimedia in education and training. Hershey, PA: Idea Group Publishing. Pimentel, J.R. (1999). Design of net-learning systems based on experiential learning. Journal of Asynchronous Learning Networks, 3(2): 64-90. Pisani, U., Cambiotti, F., Sala, N., & Sanpietro, F. (1995). A hypermedia solution for electronic instrumentation and measurements practice. In Proceedings of the 3rd International Conference on Computer Aided Engineering Education, pp. 175-179. Sept. 13-15. Bratislava, Slovakia. Pisani, U., Cambiotti, F., Corinto, F., & Romano, G. (2003). SWILAB:A virtual laboratory for electronics. In Proceedings of the International Conference on Education and Information Systems: Technologies and Applications, pp. 479-482. 31 July – 2 August. Orlando, Florida. Rath, A., Rieck, W. A., & Wadsworth, D. (1998). Educators’ approaches to multimedia CD-ROM development: Programming processes and curricular concepts. Journal Of Technology and Teacher Education, 6(2/3): 205-220. Sala N. (1999a). Multimedia technologies in educational processes: Some examples. In A. Karmouch (Ed.), Multimedia Modeling MMM 99, pp. 489-506. Singapore: World Scientific. Sala, N. (1999b). Multimedia technologies in university courses: Some examples. In Proceedings of the IEEE ICMCS 99, pp. 979 - 981. June 7 -11. Florence, Italy. Sala, N. (2003). Hypermedia modules for distance education and virtual university: Some examples. International Journal of Distance Education Technologies, (1)1: 78-95. Strange, J.H. (1995). A cultural revolution: From books to silver disks. Metropolitan Universities, 6: 39-51.

Hypermedia Modules for Distance Learning

KEY terms CD-ROM (Compact Disc-Read-Only Memory): It is a type of optical disk capable of storing large amounts of data, up to 1GB, although the most common size is 650 Mbytes. Cyberspace: It is a term coined by author William Gibson in his novel Neuromancer (1984). Cyberspace refers to the electronic space created by computers connected together in networks like the Internet. Distance Education: It is the process of extending learning with the instructor and student geographically remote from each other. Historically, Distance Education meant correspondence study. Distance learning may occur by surface mail, videotape, interactive TV, radio, satellite, or any number of Internet technologies such as message boards, chat rooms, and desktop computer conferencing. Experiential Learning: It is a process through which a learner constructs knowledge, skill, and value from direct experiences. Hypermedia: It is an extension to hypertext that supports linking graphics, sound, and video elements in addition to text elements. Hypertext: It is the presentation of information as a linked network of nodes that readers are free to navigate in a non-linear fashion. It allows for multiple authors, a blurring of the author and reader functions, extended works with diffuse boundaries, and multiple reading paths. Interactivity: It is a process whereby students are systematically encouraged to be active par-

ticipants in their own learning. It is achieved by teaching approaches that engage students in the construction of knowledge. Internet: It is a global network connecting millions of computers. The word is derived from INTERconnected NETwork. Learning activities: Activities engaged in by the learner for the purpose of acquiring certain skills, concepts, or knowledge, whether guided by an instructor or not. Learning: Process of acquiring knowledge, attitudes, or skills from study, experience, or instruction. Protocol: It is a special set of rules in a telecommunication connection. It establishes how to transmit the data. TCP/IP protocol: It is the abbreviation for Transmission Control Protocol/Internet Protocol, the suite of communications protocols used to connect hosts on the Internet. Virtual University: It is a university that delivers courses (typically for credit but also noncredit) primarily online, that is, by networks such as the Internet or Intranets, using asynchronous technologies, such as computer conferencing or Web-based technologies especially conceived for education. World Wide Web (WWW): A system of Internet servers that support specially formatted documents. The documents are formatted in a markup language called HyperText Markup Language (HTML) that supports links to other documents.

This work was previously published in the Encyclopedia of Distance Learning, Volume 2, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers and G.A. Berg, pp. 1019-1024, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.5

Understanding Section 508 and Its Implications for Distance Education Mary Hricko Kent State University—Geauga, USA

Abstract

INTRODUCTION

Section 508 of the Rehabilitation Act mandates that federal agencies must ensure the provision of accessible electronic and information technology. Although this legislation has not formally been applied to higher education, it will inevitably have an impact on all academic institutions, particularly in the area of distance education. This analysis examines how the legislation applies to distance education technologies and technical requirements and provisions of the law. An overview of Section 508 standards and its application is distance education is discussed.

On December 21, 2000, the Architectural and Transportation Barriers Compliance Board, also known as the Access Board, issued the final accessibility standards for electronic and information technology under Section 508 of the Rehabilitation Act. Section 508 “requires that when Federal agencies develop, procure, maintain or use electronic and information technology, Federal employees with disabilities have [equal] access to and use of information and data . . .” (Section 508 - 29 U.S.C. ‘ 794d). On June 21, 2001, these standards were put into effect, and specific provisions were outlined for the following technologies: • •

Software applications and operating systems (1194.21) Web-based intranet and internet information and applications (1194.22)

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Understanding Section 508 and Its Implications for Distance Education

• • • •

Telecommunications products (1194.23) Video and multimedia products (1194.24) Self-contained, closed products (1194.25) Desktop and portable computers (1194.26)

For each product category, the Access Board provides a discussion of the performance-based requirements and technical specifications to ensure accessibility and states that “when compliance with the provisions of these standards impose an undue burden, agencies shall provide individuals with disabilities . . . an alternative means of access that allows the individual to use the information and data” (Section 508). The implications of Section 508 are far reaching. IT companies that plan to do business with the federal government must now ensure that their products will adhere to the standards. Likewise, companies that develop equipment for videoconferencing and computer-mediated and Web-based applications will have to modify their products to work well with existing accessibility tools. Since the mandate was not funded, the costs for business and industry to make modifications of its IT products will inevitably affect the private sector. As a result, industry’s compliance to this legislation, combined with the government’s regulatory power, will no doubt have an impact on higher education.

THE U.S. DEPARTMENT OF EDUCATION’S RESPONSE TO SECTION 508 The U.S. Department of Education’s Office of Civil Rights (OCR) has always been involved with ensuring that compliance is met in accordance with all ADA regulations. The department oversees the development and support of several special education programs that promote equitable access to education and responds to any complaint made that raises question on equitable access in

educational facilities. With the emergence of new technologies, the OCR has received an increasing amount of complaints regarding accessibility issues. In response, the OCR has upheld several decisions to make public entities accountable for providing access to Web-based information and related technologies. In her report: “The Growing Digital Divide in Access for People with Disabilities: Overcoming Barriers to Participation, ” Cynthia Waddell (1999) notes three such cases from California.

OCR Letter Docket No. 09-95-2206 (January 25, 1996) Student filed a complaint that a university failed to provide equivalent access to the Internet. Student with a visual disability was required to make appointments with a personal reader attendant as the exclusive mechanism for access to the Internet . . . According to the OCR finding: the issue is not whether the student with the disability is merely provided access, but the issue is rather the extent to which the communication is actually as effective as that provided to others.

OCR Letter Docket No. 09-97-2002 (April 7, 1997) Student filed a complaint that a university failed to provide access to library resources, campus publications, open computer laboratories, training on adaptive computer technology and computer test taking. According to the finding: Title II of the ADA requires a public college to take the appropriate steps to ensure that communications with persons with disabilities are as effective as communications with others” [28 C.F. R. 35.160 (a)]. OCR has repeatedly held that the term “communication” in this context means the transfer of information, including (but not limited to) the presentation of a lecture, the printed text of a book and the resources on the Internet.

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OCR Docket Letter No. 09-99-2041 (April 20, 1999) Student filed a complaint that the university failed to provide access to the College of Business curriculum and other educational programs, including computer laboratories and classes in the College of Business. OCR noted that although the academic community has heavily relied upon centralized units on campus to house and maintain assistive computer technology: such sole reliance upon a single centralized location . . .may run counter to the strong philosophy embodied in Title II and Section 504 regarding the importance of integrating students with disabilities into the mainstream educational programs, unless such services cannot otherwise be provided. (Waddell, 1999 par.3-5) To prepare for the mandate of Section 508, the U.S. Department of Education published a guide entitled: Requirements for Accessible Electronic and Information Technology Design,” and began revising all of the federal procurement policies and directives under its control to incorporate the standards. In April 2001, the department also reinterpreted the Assistive Technology Act (29 U.S.C 3011), to require states and subrecipients receiving assistance under the AT State Grants program to comply with section 508 . . .” This decision is extremely significant because it establishes a precedent for other federal grant programs that fund technology-related initiatives. In turn, higher education institutions that receive federal funding for distance learning projects may now have to adhere to Section 508 standards if the projects involve the use of electronic and information technology now protected under the law. In response to the U.S. Department of Education’s directive, states such as California and Oregon who are recipients of AT funds have created accessibility councils to develop and implement accessibility guidelines at their postsecondary institutions. All institutions of higher education

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should establish a steering committee to review existing campus policies for disability services at their institution and make revisions to address the technical specifications and requirements of Section 508. These policies should specifically address provisions to be made not only for on-campus use of electronic and information technology, but also, and more importantly, in the university’s distance education program. Already, several institutions have developed extensive policy statements and guidelines for accessibility in distance education, but it is very important to ensure that along with these guidelines, institutions map out a detailed plan of implementation. All too often, common practice in most university settings is to establish guidelines with little follow-up to evaluate the effectiveness of the implementation plan. Soon after guidelines are established, the institution’s application of accessibility standards should be reviewed on an ongoing basis to ensure that academic departments are adhering to the policy and that new members of the campus community are informed and aware of the guidelines.

SECTION 508 IMPLEMENTATION IN HIGHER EDUCATION In order to establish an effective strategic plan for implementing accessibility guidelines that satisfy the requirements of Section 508, it is important to centralize the distance education program so that the design, development and delivery of distributed learning courses will be approved by one office and not sanctioned by individual academic departments. Although this approach may raise complaint from academic departments that insist program development should remain decentralized or by educators who are concerned about their academic freedom, this recommendation is not designed to challenge the integrity of academic programs or even the content of the instruction, but rather the accessibility of

Understanding Section 508 and Its Implications for Distance Education

its delivery. Quite frankly, most administrators and educators involved in developing courses for distance education do not anticipate the needs of students with disabilities. Many campus Web designers are unaware of the range of disabilities students possess and may not even consider the possibility that a disabled student will decide to enroll in a distributed learning course. If course designers do not create accessible class materials in the initial development of the course, then the format of the course must be modified to make the necessary accommodations when a disabled student does enroll. In turn, the educator and the technical support staff may not know how to go about making a distance education course accessible. The “hurry-up and fix it” approach to make the necessary accommodations is seriously problematic since it is a direct violation of the law to respond to individual requests for accommodation on an “ad-hoc” basis. According to the Office of Civil Rights (OCR), “there is an affirmative duty to develop a comprehensive policy well in advance of any request for auxiliary aids or services” (Waddell, 1999 pars. 3-5). Hence, distance education administrators have a legal responsibility and moral obligation to ensure equitable access of their program to all students and faculty with disabilities.

various courseware products will be considered tools of computer-mediated instruction.) Some distance education programs even include hybrid courses. Hybrid distance education courses are those that integrate distance education technologies into traditional course formats. For example, a traditional English composition course may make use of a chat room feature in a courseware product for supplemental out of class discussion. In addition, some distance education programs even combine formats. For example, both Web-based and computer-mediated instruction must adhere to the guidelines for Web-Based Intranet and Internet Information and Applications (1194.22).

web-Based Instruction Web assisted or Web-based instruction refers to the delivery of instruction through the use of the World Wide Web. This form of instruction may include the use of a variety of Internet resources and tools to develop a comprehensive instructional Web site. Most of the technical requirements listed in the standard for Web-based Intranet and Internet Information and Applications (1194.22) replicate the Web Content Accessibility Guidelines 1.0 published by the Web Accessibility Initiative. The following recommendations are listed for this standard:

APPLYING SECTION 508 TO DISTANCE EDUCATION

1.

In order to understand how Section 508 will impact distance education, it is best to review how the provisions of the standards relate to distributed learning formats. At most institutions, the common modes of delivery for distance education include: Web-based instruction, two-way interactive videoconferencing (or teleconferencing), and computer-mediated instruction that combines the use of both asynchronous and synchronous technologies. (For the purpose of this discussion,

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A text equivalent for every nontext element shall be provided (e.g., via “alt”, “longdesc” or in element content). Equivalent alternatives for any multimedia presentation shall be synchronized with the presentation. Web pages shall be designed so that all information conveyed with color is also available without color, for example, from context or markup. Documents shall be organized so they are readable without requiring an associated style sheet.

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Redundant text links shall be provided for each active region of a server-side image map. Client-side image maps shall be provided instead of server-side image maps, except where the regions cannot be defined with an available geometric shape. Row and column headers shall be identified for data tables. Markup shall be used to associate data cells and header cells for data tables that have two or more logical levels of row or column headers. Frames shall be titled with text that facilitates frame identification and navigation. Pages shall be designed to avoid causing the screen to flicker with a frequency greater than 2 Hz and lower than 55 Hz. A text-only page, with equivalent information or functionality, shall be provided to make a Web site comply with the provisions of this part, when compliance cannot be accomplished in any other way. The content of the text only page shall be updated whenever the primary page changes. When pages utilize scripting languages to display content, or to create interface elements, the information provided by the script shall be identified with functional text that can be read by assistive technology. When a Web page requires that an applet, plug-in or other application be present on the client system to interpret page content, the page must provide a link to a plug-in or applet that complies with the requirements for software applications and operating systems listed above. When electronic forms are designed to be completed on line, the form shall allow people using assistive technology to access the information, field elements, and functionality required for completion and submission of the form, including all directions and cues.

15. A method shall be provided that permits users to skip repetitive navigation links. 16. When a timed response is required, the user shall be alerted and given sufficient time to indicate more time is required. (See Webbased Intranet and Internet Information and Applications 1194.24.) All instructors who use Web documents to supplement their instruction need to be aware that Web accessibility is important for all of their students. Many instructors who teach in traditional classrooms use the Web for listing a variety of course information. However, in most cases, these instructors do not verify the accessibility of the materials they have created and end up posting inaccessible materials such as lecture notes or, more importantly, their course syllabus. Their assumption that students can gain easy access to these documents is shortsighted. Most students do not own state-of-the-art equipment and software and may have to rely upon different browsers or slower modems to download information. Others lack the applications to download graphic-rich Web pages or large PDF files. Still others may not even have any access. Many students who do not even own a computer end up relying on computers in the campus library or computer lab to access their Web-assisted or Web-based course materials. Since some universities do not support open labs, and library terminals are often targeted for specific library research functions, students are further hindered by time restrictions in accessing material. Furthermore, for students with disabilities, the barriers to access are even greater. Most campus libraries and open computer labs are often ill equipped to meet the needs of disabled students. Some labs may have only a few adaptive workstations; others may not even have one. These workstations are usually neglected by technical staff and are often in need of repair and upgrades. Administrators who coordinate the development of academic computing need to be

Understanding Section 508 and Its Implications for Distance Education

cognizant of the number of accessible workstations available to the disabled population on campus. It is equally important that with each new computer lab update, these workstations are modified with the latest versions of screen reading software and other applications. Having an outdated version of JAWS or other important adaptive technology may render a workstation ineffective in providing equitable access. Even though some educators are aware of the Web accessibility guidelines, for various reasons, they do not want to modify their existing Web pages, and in response, these instructors may attempt to create a text-only equivalent site to accommodate their disabled students. Although it is an easy and practical way to accommodate such students, educators need to realize that this modification may not be comparable to the actual course. Slatin (1998) claims, “it is virtually impossible not to think of the media-rich variant as the “real” and therefore privileged site.” In his view, when it comes to text-only substitutes, “separate is not and cannot be equal” (Slatin, p. 80). One common reason for this problem is that educators often fail to update text-only versions of their Web pages. In turn, the text-only page seems like an older edition of a textbook. Even though it has some of the course material in it, it is not the actual resource that is being used in class. Furthermore, according to Rick Ells (1999), “Just making content available is not education. Learning requires action, interaction, and application” (par 5). As a result, instructors need to ensure that disabled students are provided with a similar learning environment to that of their nondisabled classmates. Educators need to ensure that disabled students have equal opportunities to actively participate in their Web-based class by finding alternative methods of interactive inclusion. Students with disabilities often possess greater skills in computer fluency (because of their experience in using adaptive and assistive devices) and could very well serve as mentors to

students who are having difficulty understanding how the technology works. For those instructors who include multimedia in their Web-based documents, such accommodation may seem rather challenging. However, there are several tools designed to make multimedia more accessible. For example, WinScripter v1.0 is a “unique program that contains image editing, 3-D rendering and WYSIWYG (“What You See Is What You Get”) HTML/DHTML/CSS/ JavaScript editing capabilities all combined into one convenient and easy-to-use package.” Instructors who want to include the use of graphics in their Web sites can make use of the “ALT” tag generator found at the WinScripter site to describe images up to 500 characters. This tool is very easy to use. As the mouse scrolls over the image, a popup box enables the designer to type in a description for the picture. Most screen readers will then be able to read the description. It is important to understand that the use of any graphics should relate to the text displayed. If the graphic does not enhance the content of the information or have any significance to the topic, then it should not be on the page. Instructors also need to know that the smaller the image file, the faster the download. Hence, it is recommended that a 65K or smaller image should be used with a 28.8 modem. In fact, graphics should be limited so that the page can download in less than fifteen seconds. Levin (1996) suggests that the “total size of all images used on a page should be less than 30K” and recommends that users be warned when a hyperlink leads to a larger graphic. Instructors should consider displaying images as “thumbprints” to give students the option of manipulating the graphic. If the students wish to enlarge the image, then they can do so. Instructors can also decrease the file size by selecting fewer colors and cropping the image without really losing the quality of the image. It is also important to avoid blinking, flashing or scrolling graphics. These attributes are not only distracting, but in

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some cases, they are usually inappropriate on an academic course site. Instructors who insist that they cannot comply to the Web accessibility standards because they are using higher-end technologies still must provide an alternative format to their Web pages. Terry Dugas (2001) states, “Any video or audio used in streaming PowerPoint, applications such as Flash, or other animations must have synchronized captioning with the visuals. Webbased captioning can be done using a number of tools such as Synchronized Accessible Media Interchange (SAMI), Synchronized Multimedia Integration Language (SMIL), MAGPie, or the more advanced features of QuickTime.” These tools enable designers to synchronize captions with multimedia elements to ensure that audio and video clips are more accessible. Goldberg and Freed (1998) found that the video and audio of QuickTime movie clips could be transcribed using a simple word processor. The procedure for creating a “text track” involved imbedding text into the clip. The text can either be fixed or timecoded to correlate with the actual movement of the clip. Although this procedure is somewhat timeconsuming, it is an inexpensive way of providing suitable accommodation. Furthermore, Goldberg and Freed assert “adding captions or descriptions to Web-based multimedia preserves bandwidth so users can request and download specific media components” (p. 129). (More information regarding the step-by-step procedure can be found at http://www.wgbh.org/wgbh/pages/ncam/currentprojects/captionedmovies.html.) To further assist in the evaluation of existing Web pages or the development of new documents, checklists such as The Unofficial Section 508 Web Accessibility Checklist (http://access.idyllmtn. com/section508/table_plain.html) and WebAim’s Section 508 Accessibility Checklist (http://www. Webaim.org/standards/508/checklist) are available to assist in assessment. In addition, there is a considerable selection of periodical literature

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and electronic information on WAI’s Web Content Accessibility Guidelines. Almost every disability-related organization has a link or publication that provides information on accessibility. There should be no excuse for not being able to locate information to assist in the development of more accessible Web documents. All existing distance education Web sites and Web pages that supplement any instruction on campus should be evaluated and updated on a regular basis to ensure Web accessibility. In fact, any Web-based material or service (such as online registration) should be made accessible for students with disabilities. It is just as important for a disabled student to be able to register for classes online, use the library’s virtual reference desk and read the Web based version of the campus newspaper.

Videoconferencing or Teleconferencing Videoconferencing is the ability of two or more distant groups to communicate face to face in real time by using a combination of audio and/or video equipment. In a typical videoconferencing lab, the instructor’s workstation contains the controls for the teleconferencing equipment (cameras and monitors) and also the peripheral equipment that is placed in the room. At their seats, students have may have access to microphones or other transmitting devices to interact with classmates at the remote sites. In most cases, the cameras in the room are voice activated, but the instructor may have to use controls to zoom into a specific student so participants at the remote sites can see who is speaking. Some videoconference rooms include computers, whiteboards, fax machines, and other peripheral equipment used to transfer information and course materials to and from the remote sites. Some videoconference units, such as those created by Polycom, are mobile; others are more static and set up in a fixed layout.

Understanding Section 508 and Its Implications for Distance Education

The 508 standards that apply directly to videoconferencing equipment are found in Video and Multimedia Products (1194.24) and include the following technical specifications: 1.

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All analog television displays 13 inches and larger, and computer equipment that includes analog television receiver or display circuitry, shall be equipped with caption decoder circuitry which appropriately receives, decodes and displays closed captions from broadcast, cable, videotape and DVD signals. Television tuners, including tuner cards for use in computers, shall be equipped with secondary audio program and playback circuitry. All training and information video and multimedia productions, regardless of format, that contain speech or other audio information necessary for the comprehension of the content, shall be open or closed captioned. Likewise, material that contains visual information necessary for the comprehension of the content shall be audio described. Display or presentation of alternate text presentation or audio descriptions shall be user-selectable unless permanent.

If we apply these provisions to videoconferencing, then it is recommended that all videoconference units be evaluated for their captioning. Some videoconference systems allot for only closed captioning, while others provide open captioning. Closed captioning requires end users to activate the captioning. Open captioning automatically appears on the screen. It is important to see if students can enable the captioning at the remote sites. Some systems only allow the sending site to make caption modifications. Captioning may be useful for all students, especially when students at the remote sites have difficulty receiving a clear transmission of the lecture from the sending site. Most students may also find it easier to follow along

in the discussion of the class with the included captioning feature. Since students are accustomed to reading captions in frames on various broadcast channels such as ESPN and CNN, enabling this feature is not usually distracting. In addition to captioning, it is very important to examine how materials displayed at the sending site will appear on the teleconference monitors at the remote sites. Instructors need to understand that students at the remote sites are viewing the material much differently than the students who are at the sending site. Instructors at the sending site should not wait until the day the visual will be displayed to find out if students at the remote sites will experience difficulty in viewing it. Instructors who intend to use visuals should adhere to specific universal design guidelines. The Center for Distance Learning Research at Texas A&M suggests the following considerations for using visuals in a videoconferencing course: 1.

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All television screens are wider than they are high by a ratio of 4 to 3. Visuals should be created in the same manner to coincide with the aspect ratio of the screen. Slides should be created in a landscape orientation to optimize the use of space on the screen. This setup is better for viewing graphics such as diagrams and other images on the screen. A 10% border should be left around the entire visual to create an “essential area” for which to work. This setup will ensure that the entire visual is seen t the remote sites. Avoid visuals with complicated details. Present text and information in smaller units (additional slides) so users will have time to process what they are reading. Too much information on a given slide may be difficult for students with learning disabilities to process, particularly if the slide sequencing is fast. Limit the number of words on a page or slide to seven per line and five lines per page. This

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6.

amount of text is a reasonable level for most readers to process. Text should be written in 24–30 point size and in a font that has normal spaces. Do not use scripted fonts but more universal fonts such as Ariel. Make certain that the case of the text is consistent. Avoid all capital letters. Using different texts within a slideshow can be confusing.

All visuals should be described in both audio and text formats and be made available upon requests. It is advisable that this preparation be included as part of the development of content for the course. In this way, the materials will not have to be made during the delivery of the course and will be readily available not only for students with disabilities, but also for any student that may need additional review of the course material. In addition to ensuring accessible course materials, distance education administrators should evaluate the physical layout of the videoconferencing room and its components to ensure it is ADA compliant. Most videoconferencing labs are not furnished with setups that can accommodate adaptive technologies. The physical facilities of a lab should be dynamic to allow flexibility for accommodations. Some areas that administrators should evaluate carefully include the following: 1.

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Instructor station: Some videoconferencing labs set the instructor’s station apart from the student seats by placing it up on a platform. The instructor then stands or sits on a raised chair to adjust the controls for the equipment. Setups such as these are not accessible to students and faculty in wheelchairs. Even if a ramp is built, the height of the desk should be such that the individual can access the controls of the system with little difficulty. Specific height guidelines are listed with diagrams in Section 508’s standard for Self-Contained, Closed Products

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1194.25. These requirements reflect already existing regulations as noted by the ADA. The equipment of the instructor’s station should be placed so that people with disabilities can access the control panel for the room. Control panels vary, but most employ touch screen technologies. For this reason, it is important to check if the controls are easy to access, particularly by individuals who may have motor-disabilities. “Operable controls should not be more than 24 inches behind the reference plane.” (See Self-Contained, Closed Products 1194.25.) According to the provisions listed in the Telecommunications Standard (1194.23), “ Controls and keys shall be operable with one hand and not require tight grasping, pinching, or twisting of the wrist. The force to activate the controls and keys shall be 5lbs (22.2N) maximum. The status of all locking or toggle controls shall be visually discernible either through touch or sound. (See Telecommunications 1194.23.) If the control panel of the videoconference unit utilizes touch screens or touch-operated controls, a redundant set of controls should be made available. (See Self-Contained, Closed Products 1194.25.) In addition, any peripheral equipment such as a whiteboard or projector should be positioned such that it ensures easy access. Cords and cables should be secured as well. Alternative formats of the operating manual should also be provided. Student facilities: Setups for student seating are usually accessible, but the equipment that students use to transmit responses to the instructor or classmates at the remote site may not be compliant. Some may require students to use voice-activated systems that direct the video camera to zoom in on the speaker. Individuals that have speech impairments may have difficulty in getting the system to pick up their voice. Other

Understanding Section 508 and Its Implications for Distance Education

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videoconferencing units require students to press and hold down a microphone control to activate the camera’s attention to them, and then the student speaks to the remote site. This setup can be problematic for students with motor-control disabilities. In addition, “microphones shall be capable of being turned on and off to allow the user to intermix speech with TTY use. (See Telecommunications 1194.23.) Adaptive technology accommodations: All videoconferencing rooms should be equipped with at least one TDD line, because “interactive voice response telecommunication systems shall be usable by TTY users” (Telecommunications 1194.23). Additional outlets for adaptive technology equipment should also be included in an accessible area. Software and hardware that the institution plans to use to make accommodations should be evaluated for compatibility with the videoconferencing system. Adaptive technology should be “network-able” to prevent technical problems during the transmission of the course. It is also important to check that “interference to hearing technologies (including hearing aids, cochlear implants, and assistive listening devices) shall be reduced to the lowest possible level” (1194.23). Individuals responsible for the sound design of the room should ensure that this issue is addressed to improve the overall sound quality of the videoconference. It is also important that adaptive technology be placed in an area of the room that minimizes disruption to the other students.

In addition, distance education administrators should also make plans to tape all of the sessions of each course. These videotapes can then be made available to be transcribed into an alternative format and also used for peer evaluation of videoconference instruction.

Computer-Mediated Instruction Computer-mediated instruction involves the combination of both synchronous and asynchronous learning environments to facilitate instruction. Simple computer-mediated practices can include the use of e-mail or bulletin board/chat room setups to the use of more complex computer conferencing applications or courseware tools such as BlackBoard or WebCT. Computer-mediated instruction is also sometimes used as a supplement to traditional forms of instruction. Many instructors not ready to take on the responsibilities of Web-based course development may use certain features of a courseware product to provide additional Web-assisted instruction, online tutoring or course materials to their oncampus students. Many university libraries have also used these products to set up bibliographic instruction modules or virtual reference desks for remote access students. Perhaps the first area of concern regarding computer-mediated instruction involves the setup of computer workstation. The computer workstation should be placed on an adjustable table that has room beneath it for a wheelchair. The placement of the monitor, the keyboard and other peripheral equipment, such as a printer or scanner, should all be placed within the height and reach recommendations for ADA compliance. If an individual is unable to use a mouse or pointing device to execute commands, keyboard access to a program’s controls becomes very important. In fact, according to the technical requirements listed for Software Applications and Operating Systems (1194.21), “all actions that can be identified or labeled with text are required to be executable from a keyboard.” For Web-assisted, specifically computer-mediated instruction, students may have to use the mouse to execute commands to move forward in the program or to complete specific tasks. Instructors using computer-mediated or Web-assisted formats should determine if

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students could actually execute commands from a keyboard by navigating the Web document using only keyboard commands. In Section 508, the standard: Desktop and Portable Computers (1194.26) outlines the following requirements to ensure accessibility for computer keyboards: 1.

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Controls and keys shall be tactilely discernable without activating the controls of keys. Control and keys shall be operable with one hand and shall not require tight grasping, pinching or twisting of the wrist. The force required to activate controls and keys shall be 5lbs (22.2N) maximum. If key repeat is supported, the delay before repeat shall be adjustable to at least 2 seconds. Key repeat rate shall be adjustable to 2 seconds per character. The status of all locking or toggle controls or keys shall be visually discernable, and discernable either through touch or sound. Where provided, at least one of each type of expansion slots, ports and connectors shall comply with publicly available industry standards.

If possible, all computer labs should be equipped with alternative keyboards. Trewin (2000) lists the following alternative keyboard designs: 1. 2.

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Oversized keyboards with large keys Undersized keyboards that require a smaller range of movement and can fit on a wheelchair tray One-handed keyboards shaped for left-orright handed operation. (These may have a full set of keys, or a reduced set) Chord keyboards for individuals who cannot see the keys but can hear chords that distinguish the keys Membrane keyboards which replace traditional keys with flat touch-sensitive areas

6.

Ergonomic keyboards designed to reduce repetitive use injuries

All universities should consider purchasing at least one of the above keyboard designs to have available in either a computer or distance education lab. However, if it is not feasible to purchase all of these alternative keyboards, then there are ways to make adaptations to improve accessibility. Key guards, which are plastic sheets that fit over the actual keyboard, can be used for students with motor disabilities. The key guard has a hole for each key that ensures accuracy in pressing the key. Key guard kits are relatively inexpensive and easy to use. Other adaptations can be built into the operating system of the computer to allow alternatives in keyboard use. Trewin (2000) in her article “Adapting Keyboards and Mice” suggests that the use of Mouse Keys “allows users to control the on-screen pointer using the keyboard, including click, double click and drag operations . . . by using the numeric keypad on the keyboard.” Trewin also cites the use of voice input, speech recognition systems, head tracking, gesture recognition and switches as additional means for issuing keyboard commands (see Mouse Keys, par. 1-4; other input devices, par.1-5). Specific technical requirements for computer operating systems are also addressed in the standard Software Applications and Operating Systems. Although most educators who teach distance education may not concern themselves with the technical elements of the operating system, it is still important to be aware of the 508 requirements associated with these features. The basic requirement for software applications and operating systems is that the product possesses built-in features of accessibility or be compatible with existing assistive technology. Alternate approaches are allowed as long as the alternate provision offers equivalent or greater access than the actual approach. This specific standard outlines in detail the requirements for several functions needed to facilitate accessibility.

Understanding Section 508 and Its Implications for Distance Education

Perhaps the most important element in operating system design is that the applications being used with the system do not cause or create any the disruption of activated accessibility features that are built into a product. Accessibility features include the ability to reverse the color scheme, show visual prompts or provide “sticky-keys” that allows users to press combinations of keys sequentially. Sometimes, these features are disrupted when the new software program overrides the input or output devices of any existing program. Although this issue may be a concern of the technical support staff, it is important that instructors be aware of the ways in which various software programs interact with one another when loaded together. Students required to use software packages in a Web-based course need to be given information on how to ensure the downloading of this software will not disrupt the application program interface of their computer. Prior to any distributed learning course that requires students to use specific applications, instructors should send students a technical requirement sheet that outlines the technical specifications needed to use the applications in the course. Another issue involving the interface of the computer deals with the input focus of the screen. According to the requirement, the” focus should be programmatically exposed so that the assistive technology can track focus and focus changes” (see 1194.21). The focus on a computer screen refers to the area that is highlighted for an action to take place. If a user clicks on the mouse or hits the enter key, an action will occur on the focus area. For example, if a paragraph of text was highlighted and then the “delete” key was typed, the action would remove the highlighted text from the document. Students needing to modify the focus should be permitted to do so. Sometimes, LAN administrators restrict student access to the controls on a computer to ensure security. The systems administrator or distance program staff can target specific workstations to serve as adaptive technology workstations and

provide login status only to those students listed as disabled users. This practice will ensure the availability of equipment and prevent nondisabled student users from altering or disrupting control panel presets. Since it may be difficult for students to use the mouse to click or double click on the focus, an alternative pointing device may be necessary. Instead of mice, students can use tracker balls, touch pads or joysticks. These pointing devices can actually be beneficial to all users, since many people often have trouble using a mouse. For example, alternative devices have buttons that will initiate and complete difficult drag operations which may be easier than trying to drag and drop with a mouse. If users still have difficulty using a mouse or pointing device, there are still a variety of other input devices that can be used. Lucent Technologies, for example, has developed the Bell Labs Text-to-Speech system (TTS) that has various applications including reading electronic mail messages and generating spoken prompts in voice response systems. Visually-impaired students or those with reading disabilities can cut and paste Web material into a text box located at the Bell lab Web site and use a variety of voices to read the information.) (see http://www1.belllabs.com/project/tts/#demo.) As with the videoconference lab, the room used for computer-mediated instruction must also be made accessible for students with disabilities. Jane Berliss (1991) outlines a detailed guide entitled: Checklists for Implementing Accessibility in Computer Laboratories at Colleges and Universities that provides five checklists for implementing the development of accessible labs. These checklists are arranged to address the least expensive methods of accommodation and gradually build up to a higher level of cost and implementation. This checklist serves as a useful tool for anyone involved in implementing accessibility standards, because it also provides a detailed list of vendors that can meet the accommodations. (For more information, please consult

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http://trace.wisc.edu/docs/accessible_labs/campus.htm?distance=education.) Once the lab has met compliance, it is best to evaluate the accessibility of the applications that will be used in the computer-mediated instruction. The Special Needs Opportunities Windows Project (SNOW) has conducted a series of studies and tests on the accessibility of both courseware and software products that are often used to create computer-mediated courses. In addition, the Web Accessibility Initiative (WAI) has also developed WOMBAT to assist in the creation of accessible authoring tools. (See http://www.w3.org/WAI/ AU/wombat/010712-checklist.html.) Despite the claims of greater accessibility, at this writing, there is no courseware product on the market that is completely accessible. In response to Section 508, developers of various courseware products have rushed to meet the standards to gain a lead in the market. In June 2001, WebCT worked with the Adaptive Technology Resource Centre (ATRC) at the University of Toronto to revise several of the software’s interface features to work better with the JAWS 3.7 screen reader. Although WebCT 3.6 is considered to be more compliant with Section 508 than earlier versions of the learning tool, it is not completely accessible. The chat room features are not accessible with earlier versions of JAWS. For those universities and colleges using earlier versions of WebCT, there are several Web sites that offer suggestions to make these versions more accessible. At present, WebCT version 1.0 is completely inaccessible, and version 2.0 is listed as being only 83% compliant with the Level 1 Checkpoints of the World Wide Consortium Standards. (See WebCT at http://www.Webct.com.) WebCT 3.0 has a bit more compliant features but still does not meet all the technical requirements of Section 508. Some of the problems associated with the earlier versions of WebCT include the failure to provide alt text for buttons and icons, the use of frames and the lack of standard HTML. In response, the Centre for Academic and Adaptive Technology at

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the University of Toronto has developed several guides on how to improve the accessibility of these earlier versions. (See http://booboo.Webct. com/otln/Webct_accessibility.htm.) Another popular courseware product has also been updated to comply with the standards of Section 508. BlackBoard version 5.5 is said to be “almost 100%” compliant with the standards as outlined in Web-Based Intranet and Internet Information and Applications 1194.22. (See Blackboard at http://www.blackboard.com). Partnering with WebAIM and the Standards for Accessible Learning Technologies (SALT) Project, BlackBoard is working on building out additional accessibility features into the product. However, just like WebCT, earlier versions of BlackBoard are not accessible because of the use of frames and applet scripts. (See http://www.blackboard.com.) Both products, despite their revisions, have difficulty with “alt” tags and form elements. In some cases, alt tags are either missing or assigned to the wrong images. The chat room tools in both projects are also inaccessible and do not meet Section 508 guidelines. Likewise, the frames format used in both products makes it difficult to navigate if one is using a screen reader to access the page. As a result, it is imperative that educators review their use of these functions to ensure that students with disabilities who cannot access the chat room will have another way to participate in real-time group discussion. Students who are unable to access these functions of the courseware should not be penalized. It is the instructor’s responsibility to verify each student’s ability to access the features of the courseware and determine alternative methods to facilitate instruction. Other course tools such as chat room platforms, virtual reference systems and electronic bulletin board systems are not accessible. Instructors using these tools need to find ways to improve their accessibility for students with disabilities. It is important to contact the product vendor to determine if a more compliant version of the product exists. If not, the university should consider

Understanding Section 508 and Its Implications for Distance Education

purchasing a more compliant tool for students and faculty to use. In fact, prior to the purchase of any application or enterprise software to manage a digital campus environment, campus administrators should find the answers to the following questions: Is it accessible? How is it accessible? And, which features are not accessible?

OTHER PRACTICAL ADVICE All course materials: lecture notes, handouts, assignments, tests and multimedia presentations, regardless of format, should be made available to each remote site at least one month prior to the start of the first day of class. All too often, course materials are not sent to the receiving sites in time to prepare and have available for the remote campus students. If a student with a disability has enrolled in the class, additional time may be needed to make modifications or acceptable accommodations to the material. Having the materials well in advance of the class prevents the situation of disabled students falling behind in their course work because they have had to wait for the alternative formats to be made. In addition, it is also very useful for the remote sites to have copies of the course materials in case the course does not transmit to the site as a result of technical problems. Doing this enables all students at the absent site to gain access to the course materials that were distributed to the other sites on the same day of the class session. All students and faculty new to the distributed learning environment should receive an extensive orientation. Orientations involving using the technologies in the distributed learning classroom should include instruction on Web accessibility and adaptive technologies. Administrators should provide time for training staff and faculty in the development of accessible multimedia and other course materials. Technical support staff members also need time to see how adaptive technologies work with existing operating systems. Faculty

should see firsthand why certain elements in the courseware products they plan to use may be inaccessible to students with disabilities. Having faculty evaluate their Web-based documents using a validation tool such as Bobby (http://www.cast. org) is a good way to emphasize the importance of Web accessibility. Training should be an ongoing process to keep people abreast of emerging technologies available to individuals with special needs. Students, faculty, technical support staff members and anyone who will be involved in implementing the distance education program should be trained to understand the technical requirements and provisions of Section 508. There are many assistive technology certification programs that provide specialized training in the development of accessible media and courseware products. Both WebCT and BlackBoard have developed partnerships with disability research centers to develop instructional programs to assist their users with information and resources about accessibility topics. Universities should take advantage of these programs if they are using these platforms to distribute their distance education courses. Finally, awareness is the key. University administrators and educators need to be proactive in communicating updates in the legislation that relates to accessibility issues. All universities should revise their existing ADA compliance policies to include discussion of Section 508 standards, regardless of whether or not they are recipients of AT funding, and make certain the campus community is aware of the policy. An accessibility task force consisting of personnel from a variety of departments, particularly distance education, instructional computing and the office of disability services should be created to make recommendations and to conduct annual accessibility reviews of electronic and information technologies on campus. This task force can also examine ways in which the university can improve its overall services to its disabled population, especially for those students and faculty who plan to participate

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in distance education or make use of the campus technologies available on campus.

FUNDING THE MANDATE FOR HIGHER EDUCATION Since the federal government did not fund the industry compliance to Section 508, the IT industry encumbered all of the costs to transform its products. In some cases, entire product lines had to be modified. As a result, higher education will most likely see increases in the costs of new and updated technologies that comply with the Section 508 standards. In addition, some of the older technologies may be taken off the market, and replacement parts may be hard to locate. Newer accessible versions of software may not work well with existing technologies. For this reason, administrators responsible for distance education initiatives at their institutions must include funding for assistive and adaptive technology in the budget planning to ensure that monies are available to meet the needs of students and faculty with disabilities. Berliss (1991) notes, “since 10% of the general population is disabled, a reasonable goal would be to have about 10% of equipment and resources earmarked for accessibility” (par. 5). More importantly, it is highly recommended that individuals responsible for the purchase of new technology model the federal guidelines to procure products which best comply with the standards as outlined by Section 508. The Rehabilitation Engineering and Assistive Technology Society of North America (RESNA) has developed a detailed guide on what types of questions people can ask vendors in purchasing adaptive and assistive technologies. Requiring distance education departments to purchase accessible products at the outset will eliminate the need for expensive retrofitting at a later time. (For more information see http://www.resna. org/taproject/).

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Monies should also be made available for training on the use of adaptive and assistive technology. As mentioned earlier, distance education programs often fail to address issues of training and development of the staff that will implement the adaptive technologies. Very few technical support people have had extensive training in the use and applications of assistive and adaptive technologies. These individuals must have a general knowledge of how to use these tools to understand why people may be having difficulty in using them. In addition, faculty also need to be trained in understanding the needs of students with disabilities. Hricko (2000) asserts, “ prior to the development of any distributed learning course, faculty should receive training in the use of adaptive technologies and Web accessibility. If distance education faculty are required to receive training in the use of distributed learning technologies to teach their courses, it should not be a problem to introduce discussion of Web accessibility and adaptive technology as part of their preparation” (par. 6). There are several research centers that provide training videotapes and materials designed specifically for faculty and staff training. The Trace Center at the University of Wisconsin and the University of Washington’s DO-IT organization offer a wide range of materials at little or no cost to use for developing a comprehensive training program. Additional training opportunities should be integrated into the curriculum of academic programs that specialize in the instruction of electronic and information technologies. Graduate students in library science, computer–related and instructional design degree programs are just a few of the student groups that should receive some training in the use and application of adaptive technologies and Web accessibility. These students should also be encouraged to pursue research in the areas of accessibility-related topics. The objective is to promote further and future investigation into the study of improving emerging technologies so that

Understanding Section 508 and Its Implications for Distance Education

they can be more compliant and in line with the technical requirements of Section 508. Currently, there are several research projects underway to improve the accessibility of higherend technologies. For example, Sun Microsystems and IBM have been involved in developing alternative user formats for JAVA’s programming language. One project, the JAVA Accessibility Bridge to Native Code, is designed to assist screen readers with interpreting the objects of JAVA scripts. According to Mark Stiles (2001), “the screen reader queries the bridge about the JAVA application and the bridge [relays] the queries to the JAVA Utilities. The JAVA Accessibility Utilities would then relay the message to tell the user what is going on in the application” (par. 15). Other projects have concentrated efforts to develop plug-ins for browsers. Caption-IT has been working on developing a captioning plugin that would ease the captioning of streaming media. Other programs have begun to consider alternative techniques to deliver accessible images. MIT have been involved in developing new ways to use thermography. In thermography, the images on the Web are printed in such a way that visually-impaired individuals can scan the image with their fingertips. Even though Section 508 has indeed prompted the inquiry into the development of more accessible technology tools, there still needs to be a concentrated effort on developing the tools and technologies that make it easier to comply.

CONCLUSION The U.S. Department of Education’s commitment to adhere to the standards of Section 508, as well as the historical pattern of higher education to adopt the regulations of previous disability laws, should make educators realize that this legislation will inevitably impact instructional practice, particularly in the area of distance education. Rather

than waiting for higher education to adopt Section 508’s mandate, it is more proactive to adhere to the standards now and revise existing practices to promote and sustain greater accessibility in the use and development of electronic and information technology. If our goal in distance education is to ensure that students are given equitable access to the resources and support that their on-campus peers receive, then it is imperative that we provide and create learning environments that are accessible for all types of learners. The implications of Section 508 for distance education are powerful. It will enrich and enhance the academic experience for those individuals who may not have had the opportunity to participate fully; it will empower disabled students and faculty to teach and learn with new technologies; and it will lead all of us to understand the importance of breaking down barriers.

REFERENCES Access Board Standards. Retrieved March 31, 2002 from http://www.access-board.gov/sec508 Berliss, J. (1991). Checklists for implementing accessibility in computer laboratories at colleges and universities. Version 1.0 University of Wisconsin-Madison: Trace Research and Development Center. Retrieved March 31, 2002 from http://trace.wisc.edu/docs/accessible_labs/campus.htm?distance+education Blackboard. (2002). Retrieved March 31, 2002 from http://products.blackboard.com/cp/bb5/access/index.cgi The Center for Distance Learning Research. (2002). Hints for teaching using technology. Retrieved March 31, 2002, from http://www.coe. tamu.edu/distance/VideoconferencingInfo/teaching.html Dugas, T. (2001). Mandatory ADA compliance. DEOS-L listserv. Penn State University: Ameri-

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can Center for the Study of Distance Education. Retrieved July 10, 2001. Ells, R. (1999). Basic premises of this workshop. Effective use of the web for education: Design principles and pedagogy. Retrieved March 31, 2002, from http://staff.washington.edu/rells/effective/premises.html Goldberg, L., & Freed,G. (1998). Making multimedia accessible on the World Wide Web. Technology & Disability, 8, 127-132. Hricko, M. (2000). Distance education and special needs students: Providing access with adaptive technologies. In Proceedings of the Teaching in the Community Colleges Online Conference. Spring. Retrieved March 31, 2002, from http://leahi.kcc. hawaii.edu/org/tcon2k/paper/paper_hrickom. html Levin, P. (1996). Guide to Web Style. Sun on the Net. Retrieved March 31, 2002, from http://www. sun.com/styleguide Richert, M., & Siller, M. A. (2002). Key areas of the Instructional Materials Accessibility Act (IMAA) of 2002. AFB Textbooks and Instructional Materials Solutions Forum Legislative and Policy Making Group. Retrieved May 23, 2002, from http://www.afb.org/info_document_view. asp?DocumentID-1693 Slatin, J. (2001). The art of ALT: Toward a more accessible Web. Computers and Composition, 18, 73-81.

Stiles, M. (2001). Disability access to virtual learning environments. Retrieved March 31, 2002, from http://www.disinhe.ac.uk/library/print. asp?id=41 The Unofficial Section 508 Web Accessibility Checklist. Retrieved March 31, 2002, from http:// access.idyllmtn.com/section508/table_ plain. html U.S. Department of Education Office of the Chief Information Officer. (2001). Requirements for accessible electronic and information technology design. Version 2.0, February 1. Retrieved March 31, 2002, from http://www.ed.gov/offices/OCFO/ contracts/clibrary/software.html Waddell, C. D. (1999). The growing digital divide in access for people with disabilities: Overcoming barriers to participation. White paper presented at the Understanding the Digital Economy Conference, Washington, DC, May 25-26. Retrieved March 3, 2002, from http://www.aasa.dshs. wa.gov/access/waddell.htm Web Accessibility Initiative (WAI). Retrieved from http://www.w3.org/WAI WebAim. Section 508 Accessibility Checklist. Retrieved March 31, 2002, from http://www. Webaim.org/standards/508/checklist WebCT. (2002). Retrieved March 31, 2002, f r om ht t p://w w w.Web c t .c om /p r o d uc t s / viewpage?name=products_accessibility WinScripter v1.0 Retrieved March 31, 2002, from http://Webmastermatrix.com/scripter/index.htm

This work was previously published in Design and Implementation of Web-Enabled Teaching Tools, edited by M.F. Hricko, pp. 25-46, copyright 2003 by Information Science Publishing (an imprint of IGI Global).

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Inadequate Infrastructure and the Infusion of Technology into K-12 Education Gregg Asher St. Cloud State University, USA

Introduction Although the lack of adequate funding is probably the most significant barrier to the effective infusion of technology (since bundles of money could eliminate almost all other barriers), I will focus on “inadequate infrastructures” as the most impregnable obstacle in rural schools. According to the dictionary, an infrastructure is “an underlying base or foundation” (www.dictionary.com). As I see it, following this definition, a school’s infrastructure would include teachers, the physical requirements needed to support a robust network, and the community of recipients or users. Many of the teachers in rural school districts are older, approaching retirement, relatively set in their ways, and have little interest in infusing technology into their teaching. Many others are relatively new to the profession and, even if prepared in the new technologies, reticent to make waves or move too quickly to change the status quo in the schools in which they have just begun to

teach. The older, more seasoned teachers are from a generation not typically exposed to computers and have had very little opportunity to become familiar with the new technologies. Generally, they have had some training in the use of the most common technological tools, but received no help in how to incorporate these tools into the classroom, much less use them to enhance the curriculum. Most teachers, whether old or new, have begun to use technology for administrative functions, for example, attendance and grade books, but they are not using them in instruction or assessment. Most feel that they have been “successful teachers” in the past without this technology, so they wonder why they would need to incorporate it now. “I’m too old to start learning that stuff now” becomes an excuse for doing things the same old way. Even those teachers who would like to learn how to use and infuse the new technologies generally face many hurdles before being able to do so. In most cases, they teach in small schools that are just now obtaining Internet connections. Many

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Inadequate Infrastructure and the Infusion of Technology into K-12 Education

rural communities are still waiting for adequate bandwidth and high-speed network connections to reach their communities. So, even in the places where there is a critical mass of teachers in a rural school who may realize the enormous potential the new technologies have for dramatically expanding resources and learning horizons for their students, little can be done to infuse technology into their curriculum and instruction until their district and schools have dependable, high-speed access to the Internet. Generally, the local telephone company (telco) or Internet service provider (ISP) is not going to provide this high-speed access because of the “last mile” problem. The last mile problem is associated with the expense a telco has to bear to provide the last mile, that is, a linkage between the cable or other communications channels brought to the edges of a community and potential users in the service area. Many rural schools are located in communities that have small populations, very few retail establishments, and no industrial base. There is little or no economic incentive for a telco or ISP to either provide or upgrade the existing service into the community. To further exacerbate this shortcoming, the existing physical and electronic infrastructures of many rural schools contain a seemingly unending array of challenges to the installation of quality networks and Internet connections. Most are not wired to accommodate any type of highspeed connectivity. Many are old and do not have walls, ceilings, and wiring pathways that would easily accommodate the necessary electrical and network cables required to build robust infrastructures. Some are rife with asbestos, which would have to be removed before improvements are made (usually an expensive process). There are even situations in which the heating ventilation and air conditioning (HVAC) are not conducive to installing quality technology networks. Overhead projectors overheat; the equipment in the telecommunications closet quits because of high heat and humidity; or microcomputers are

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sometimes rendered inoperable in the absence of surge protection.

EDUCATION AND BARRIERS How do educators react to these barriers? New teachers are usually discouraged by the lack of technological resources in these schools and move on to richer suburban districts. They enter teaching with a fresh enthusiasm and want to be the “best” teachers they can be, only to be confronted with aging technology or no technology. All of the tools they were taught to use and had available to them in college are non-existent where they now need to practice. They may have come from a laptop university that has high-speed Internet connections that allowed them to ‘surf’ the Web, send e-mail, chat with their professors, and so forth. Now they are relegated to using the tools of the ’50s. This new teacher is now going to have to depend on the more senior teacher to learn how to use the old media. This backward reality further reinforces the negative views of the more senior teacher about adopting technology. The transference of skills between teachers is stymied. The new teacher could educate the older teacher in the use of the newest techniques, tools, and technology currently available. The more senior teacher could also impart to the new teachers all the tips, strategies, and knowledge gleaned over years of teaching. If a rudimentary adoption of technology is present in the school, this will serve to reinforce a negative attitude of adoption; this attitude may transfer to the new teacher. The policymakers—school boards, city and county officials—are influenced by the members of the communities that comprise the school district. Most of the school districts in rural Minnesota are consolidated. This means that multiple communities and governmental jurisdictions now influence what happens in the newly formed school district. You can have a

Inadequate Infrastructure and the Infusion of Technology into K-12 Education

situation where consolidations have resulted in efforts to integrate districts with widely varying technology capacities. You may have a condition where a district that is extremely advanced technologically merges with one or two others that have little or no technology. In these cases, the existing technology is further diluted, resulting in poor connectivity for everyone. Regardless of the rationale for consolidation, these small communities whose schools have consolidated are fiercely independent, and the attitude of the community as reflected by their elected officials will go a long way in determining the degree and speed with which technology is infused into the district’s schools. The demographics and economies of these small rural communities have changed dramatically in the last 20 years. Most are declining in population. The population is aging. Most local businesses and retail establishments have disappeared. There are very few active churches left. Most of the residents travel for entertainment, groceries, clothes, hardware, and so forth. Now the grain elevator (if there still is one) is the center of community activity. If not the grain elevator, the center is the only remaining café. The folks in these communities are not exposed to the new technologies on a frequent basis. They may experience technology at the bank and grain elevator, but not likely in the café. (With all of the problems

associated with the Year 2000 presidential election, the cynics in these small towns are saying, “With all this technology in place to count votes, they still couldn’t get it right.”). This attitude might prevail when the school district comes to the community with a referendum for technology funding. The prevailing attitude may be: ”There isn’t a lot of extra money around, and we have done real well without it in the past and we will do real well without it in the future!” But can any school and supporting community do without it now? This author responds with an emphatic, “No!” The allocation of scarce resources is always going to be a challenge. Technology is always changing, and there will always be a cost associated with it. However, the biggest barrier to the effective infusion of technology is the hugely complex, uninviting, and highly resistant infrastructure that exists in many currently low technology schools. Most are in rural areas, but many examples can also be found in urban and suburban districts. Without addressing the infrastructure issues as I have defined them, there is little chance that students in thousands of schools across the nation will achieve the four National Technology Goals anytime in the near future. Students in those schools will continue to fall on the wrong side of the “digital divide,” and the divide will increasingly widen.

This work was previously published in the Encyclopedia of Distance Learning, Volume 3, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 1061-1063, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Web-Based Education Accountability System and Organizational Changes: An Actor-Network Approach Xueguang Ma University of Maryland, USA Roy Rada University of Maryland, USA

ABSTRACT The learning and accountability needs in a teacher education department drove the development of a novel, Web-based education accountability system (EAS). To fit the EAS with the organization, actor-network theory (ANT) was used to guide the social and technological development. In the course of this fitting, a novel multi-dimensional perspective to ANT was formalized. Four dimensions of organizational culture, power/politics, process/operation and profession were used. Participant observation, field notes and interviews were used to surface negotiations during periods of controversy to reveal how standard teacher education practices were created and recreated.

Detailed translations occurring at multiple levels provided insight into the technical agency of the EAS and how its inscriptions shaped the emergence of a socio-technical information systems (IS) solution for a teacher education program.

INTRODUCTION To better understand the interplay between technology and organizations, the “black-box” of technology and process must be opened to expose the embedded socio-economic patterns (Bijker & Law, 1992). The implementation of an IS is shaped by the organizational context and

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Web-Based Education Accountability System and Organizational Changes

simultaneously enables and constrains the organization (Orlikowski, 1991). Economic, political and cultural issues should be examined together with the IS as a socio-technical interaction network (Kling, Kim, & King, 2003). Common approaches to researching technological innovation in education focus on the technical aspects of an innovation. Traditional determinism frameworks can not account for the interactions between IS design and organizational changes (Law & Callon, 1988; Scacchi, 2004). IS research needs to explore the interaction between IT and its social context (Orlikowski & Iacono, 2001).ANT offers a good means to achieve this end by its impartial treatment of the contributions of both human and non-human actors. Teacher education accreditation presents great challenges to the teacher education programs in the United States. The National Council for Accreditation of Teacher Education (NCATE) introduced new standards in 2000 (Castenell, Benson, deMarrais, Butchart, & Lewis, 2001; Linn, 2000), and teacher education programs must comply with those standards. The comprehensive data collection mandated by the NCATE 2000 standards required advanced IS solutions and organizational changes (Wise, 2001). This study extends ANT analysis with multidimensional views and property models to examine the translations that occurred during the successful implementation of a Web-based EAS. EAS helps teacher candidates to learn and the unit to comply with NCATE. The impact of Web technology on learning (e.g., Esnault & Zeiliger, 2000; Folkman & Berge, 2002) has been extended in this study to overall program improvement.

THEORETICAL FRAMEwORK Technological determinist approaches to technology innovation contend that all outcomes of technological change are attributable to the technological rather than the social (Grint & Woolgar, 1997). At the other extreme is social determin-

ism, which holds that social factors can be used to explain technological change (Law & Callon, 1988). Intermediate approaches (Barley, 1986; Giddens, 1984; Kling, 1987; Orlikowski, 1992) emphasize the contingent relationship between the social and technical. Seeking an approach that strikes a balance between the social and technical elements leads to ANT (Doolin & Lowe, 2002). In terms of the adoption of technology in education, ANT stands in sharp contrast to diffusion theory (Rogers, 2003). Diffusion theory in education treats technology as immutable in the transmission process in which definable factors affect the adoption (Dooley, 1999), while ANT treats technology transmission as a process of continuous transformation in which technology and social context are mutually shaped. ANT treats human and non-human stakeholders analytically as actors who have aligned interests in a socio-technical actor-network. The actor-network seeks stabilization through the processes of translation and inscription. The interests of various actors are translated, aligned and inscribed into technical and social arrangements, such as business norms or software applications, which stabilize the actor-network, at least temporarily (Callon, 1991). Once stabilized, an actor-network may become seemingly irreversible and thus resistant to further translation (Callon, 1991). Therefore, formation and maintenance of a strong actor-network with aligned interests is crucial to the success of an IS project. Multiple perspectives are valuable for IS development (Hirschheim & Klein, 1989). Multidimensional analysis has its root in “multiple perspectives” theory (Steinbruner, 1974; Checkland, 1981). Examples of multiperspective theory include: technology-organization-people (Linstone, 1999), Wuli-Shili-Renli (Zhu, 2000), and multimodal systems design (de Raadt, 2001). Atkinson’s multidimensional representation of actor-networks identifies four dimensions: the informational, the clinical decision-making, the psychosocial and the power/political (Atkinson,

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2002). However, Atkinson did not explicitly advocate a multidimensional analysis. In this study, dimensions at a macro and micro level are identified from a taxonomy of IS success factors (Larsen, 2003): • •

Macro level: (1) Organizational culture; (2) Power relationship and politics Micro level: (3) Process and operation; (4) Professional

The reason to choose these four dimensions is that they are most relevant to the problem situation in this study: teacher education program improvement and accreditation. Researchers might choose dimensions from the taxonomy of IS success factors that are most relevant to their problems. Actor-networks representing multiple alignment themes can be broken into several actor-networks (Figure 1), and each could be called

a one-dimensional actor-network (ODAN). The same actor can be involved in different ODANs. The more densely connected an ODAN, the more translation and enrollment in the ODAN. No established modeling language represents how an actor-network is formed, aligned and transformed. By using an object-oriented lens, each actor is viewed as an object having properties and actions. Building on the work of de Vreede (de Vreede, van Eijck & Sol, 1996), three models are adapted to illustrate the ODANs: Actor model, Process model and Interaction model (API). The API models highlight particular characteristics of each ODAN (Table 1). The Interaction Model consists of actors communicating with each other by sending messages or constraining each other, such as controlling resources. The symbols used for the graphical representation of an interaction model are given in Figure 2. An example shows a distance education

Figure 1. Convert an actor-network (left) into multidimensional actor-networks (right) Dimension 1

Dimension 2

Di mensi on 3

Table 1. API property models for each ODAN: Each ODAN may be seen through one to three views ODAN 1 Actor Model Process Model Interaction Model

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ODAN 2

ODAN 3

......

ODAN n

Web-Based Education Accountability System and Organizational Changes

system (DES) used for an online masters program (Figure 3). The interaction model is also used to identify actors in the actor-network. Actors are identified by following the interacting activities of the DES. The DES was constrained by the budget, the academic requirement, the developer and the users. The users’ activity would affect the functions and purposes of the DES. In Figure 3, the DES and the academic requirement are mutually constrained; this denotes the emergent features of the DES and the academic requirement—that is, both are changed and shaped interactively via translations and negotiations.

Figure 2. Symbols of the interaction model Flowchart Key Actor A

A constrain B

B

Mutually const rained A B

A

Info. Exchange

B

Single/double c onstraints represent unilateral/bilat eral control relationship, whic h implicitly indicates information exc hanges.

Figure 3. Example of an interaction model Developer Advis or

Budget Dis tance Education Sys tem Academic Requirement Student

The interaction model does not describe how the actor-network was formed and aligned for a certain goal. The Process Model bridges the gap by modeling a sequence of actions along the actor-network alignment process. It captures a complete workflow associated with all related actors in an ODAN. The process model illustrates the procedures related to the alignment process. Symbols depicted in Figure 4 are used to represent a process model, and students’ academic progress is depicted in Figure 5. The process model shows how the various stakeholders use the DES to maintain the online academic programs. The third and final model is the actor model, which depicts the interdependencies of the actions an individual actor has to perform to achieve actornetwork stability. An actor model consists of the same elements as a process model but represents all the actions of individual actors, whereas the process model represents the actions of all actors in an actor-network. Model symbols are pictured in Figure 6, and an actor model is illustrated in Figure 7. The actor model shows how the students are enrolled, taught and administered via DES. The workflow is useful, to reveal the details of each process.

Figure 4. Symbols of the process model Flowchart Key Start/End

Actor Actions

Graduation Committe e

Actor Decision Info. Flow

T he rec tangle shape specifies the actor's ac tion, and the oval shape indic ates a decision proc ess associated with the actor(s)

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Web-Based Education Accountability System and Organizational Changes

Figure 5. Example of a process model

Start

Advisors/Instructors Advise s tudents

Student Apply for graduation

Student Apply for admis sion

Distance Education Sys tem Provide functions for admis sion, c ourses , advising, evaluation, report, exit review Student Take c ourses to f ulfill academic r equirement

Meet r equirement? Y

N Y

Advisors/Instructors Satis fied student's performance?

Start/End

Ac tion Name

De cision

N

N

Qualified candidate? Y

Student

Admission Committee

Get degree a nd diploma

Keep student r ecord

End

End

Figure 6. Symbols of the actor model Flowchart Key

Admission Committee

Graduation Committee

The rectangle and oval shape indic ates actions and dec isions related with an ac tor.

Info. Flow

ally shaped and constructed during and after IS development. Data were collected from both primary and secondary sources. Primary data sources were interviews. Secondary sources were publications, documents and annual reports of the Unit. The interviewees were selected on the basis of their closeness to the topics of the study and their levels of experience in management and organizational issues. Five faculty, four supervisors, six teacher candidates and three administrators were interviewed. Each interview lasted from 1 to 1-1/2 hours. All interviews were digitally recorded and transcribed into Microsoft Word format.

CASE STUDY

ORGANIzATIONAL CULTURE

This case study uses the Department of Education (hereafter referred to as the Unit) at the University of Maryland Baltimore County. This case was chosen because the Unit is undergoing dramatic organizational change. ANT is used to analyze how EAS and organizational changes are mutu-

Organization history, norms, leadership, and environment were identified as the actors to initiate the EAS project. As shown in an interaction model (Figure 8), the inefficiency of the existing IS challenges the Unit Chair. The Unit Chair expected changes to meet the NCATE requirements.

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Web-Based Education Accountability System and Organizational Changes

Figure 7. Example of an actor model Star t

Admitted?

N

Apply for Admission via DES

Y

T ake D E Courses

Seek Advising via DES

Apply Graduation via DES

Graduation Review

DE: Distance Educat ion; DES : Dis tance Education Syst em;

N

Passed?

Y

End

Figure 8. Interaction model: Organizational culture. The actors inside the dotted rectangle represent the final aligned actor-network. Te chnology Committ ee

Capstone

Flowchart Key Actor

Unit Chair

NCATE Mandate MSDE Re de sign

Champion

Existing IS

EAS & Prototype

A

Asse ssme nt Committe e

The Capstone System and the EAS were two competing alternatives. The Champion employed specific strategies to enroll the identified actors (Chair, Technology Lead, Existing IS and Education Community). The Champion portrayed EAS as an indispensable technology and established herself as the obligatory passage point through which other actors could access the EAS. The Technology Lead was persuaded that EAS was superior to the Capstone System and inscribed the EAS proposal into a prototype system, which itself became an actant and spoke for the Champion

B

Mut ually constr ained A B

A

Te ch. Le ad

A c onstrain B

Info. Exc hange

B

Education Community

in many contexts. The advocate of the Capstone did not form any connections with other actors. The EAS prevailed over the Capstone by having more connections with other actors, which made EAS more appealing to the Unit Chair. By enrolling the Unit Chair, the Champion made her actor-network legitimate and temporarily in domination. The translation details were presented in a process model (Figure 9). Faculty members emerged from the assessment redesign with a greater understanding of the collective notion of what teacher candidates

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Web-Based Education Accountability System and Organizational Changes

Figure 9. Process model: Organizational culture. Actors negotiate and compete to form a dominant actor-network. Start

WAM: Web-based Accountability Model EAS: Education Accountability System

NCATE

MSDE

Accreditation Requirement

Redes ign of Teacher Education

Existing IS Awkw ard and Inefficient

Flowchart Key Chair Authorize the Champion to lead an Ass essment Committee

Chair problematization Champion

Propose Capstone

Propose WAM

Technology Committee

Champion Build a Technology Team; Implement a Prototype;

System Conceptualization interes sement

Faculty/Chair

Shape Org. Thinking; Foster Changes;

problematization Technology Committee

EAS Implementation

Set vision to develop an IS for as sessment

interessement

Compare tw o proposals

Ass essment Committee s upervise ass essment systems mobilization

Start/End

Act or Actions Act or Decision I nfo. Flow

Education Community Collaborate to redesign courses and operations End

Decide to go with WAM (enrollment)

should know and be able to do at any given point in their programs. They also emerged from the development process with a greater appreciation of variation in how individuals develop and evaluate assessments. Through practice and collaboration, faculty members were working toward greater consensus. These experiences, in turn, shape the manner in which they assessed teacher candidates.

POLITICS The translation process showed how politics affects decision making during IS development. Politics is defined as the attempt to influence “the distribution of advantages and disadvantages within an organization” (Robbins, 1996). The EAS development demonstrated how the wills of different political groups were translated and negotiated in the academic environment (Figure 10).

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Based on Figure 10, EAS development was constrained by the focal actor (Champion), time (NCATE deadline), budget and resources (Groups A, B, and C). To address the budget constraint, Champion contacted the university Office of Information Technology (OIT) to request hardware and software support for a production system. OIT passed the request to its Web Development Center (called Group A). Group A said that it could not help because its staff was fully occupied with other projects. Champion decided to try implementing EAS with the available resources. After inscribing the EAS proposal into a prototype system, Champion decided to enroll the Office of Institutional Research (called Group B) into the actor-network for data access. Group B was impressed by the prototype and agreed to work with OIT Management (called Group C) to look at the possibility of modifying the data dictionary. This time, Group C paid attention to

Web-Based Education Accountability System and Organizational Changes

Figure 10. Interaction model: Power relation and politics. The actors inside the dotted rectangle represent the final aligned actor-network. Champion controls EAS development while EAS shapes Champion’s view and strategy to interest and enroll other actors. Feedback

NCATE De adline

Champion

Flowchart Key

Feedback

Actor

rt

A

A constrain B

B

Re

t

po

r po Re

Budge t

Group-C

Hardware Software

EAS De ve lopme nt

Data Struct ure

Group-B

M utually const rained A B

updates

Delta Initiative

A

DB Acc ess

Group-A

Info. Exchange

OIT: Offic e of Information Technology; Group-A: OIT Web Development Center; Group-B: Offic e of Institutional Research and Registrar’s Office; Group-C: OIT Top Management;

B

Degree Navigati on

the EAS endeavor because of the political power of Group B. However, Group C was not happy with the Unit’s unilateral conversation with Group B, as reflected in a memorandum sent to Group B that criticized the Unit’s system development and project management. Champion then used the Technology Lead to ease the tension, because the Technology Lead was well connected with Group C. Although Groups B and C were not fully enrolled into the actor-network, they did not jeopardize the actor-network’s stabilization. Champion continued EAS development while keeping Group B and Group C periodically updated. This diplomatic approach was considered crucial in that either of the two groups could negatively affect the development. The continuing network building proved useful when Group C and Group B finally gave the Unit the required support.

PROCESS AND OPERATION The actor-network inscribed EAS into various artifacts, including an IS, Intern Handbooks, training manuals, published papers, and state and federal reports. EAS effectively became the medium for

inscribing social change in the way that the Unit would be operated. Process changes before and after the stabilization of EAS actor-networks are shown in an actor model (Figure 11). A series of program, curricular and operational changes occurred during the EAS implementation. New processes are presented in a process model to visualize the actors’ actions and their interdependencies (Figure 12). The Office of Information and Assessment was established to address both the assessment and EAS development. The EAS pilot results suggested increased demand for student services and placements due to programmatic changes (Figure 11). One candidate commented: “We really need more guidance on technology, as it is beginning to take over.” In response, the Unit established the Office of Student Services and the Office of Teaching Experiences, and created the position of Director of Professional Development Schools. These changes, which were themselves results of EAS inscriptions, supported the EAS actor-network’s evolution and domination. As the Unit discovered the potential to achieve better and more with the EAS, the Unit changed some processes to take advantage of these new capabilities. Major changes included:

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Web-Based Education Accountability System and Organizational Changes

Figure 11. Actor model: Teacher candidate. Involved processes before and after the EAS are separated by the dotted line.

Admitte d?

Program Exit Revie w

Y End

Apply for Admission pape r-base d

N

Apply Fie ld Experie nce paper-base d

Y Fie ld Exp.?

Passe d?

N

Y

N

Tak e EAS Training

Admitte d?

N

Apply for Admission via EAS

N

Apply Fie ld Expe rience via EAS

Y Fie ld Exp.? Y N

Clinical Place me nt?

Apply Clinical Placeme nt via EAS

Flowchart Key Start/End

Pe rform Online Asse ssme nt

Before EAS

Program specific paper asse ssme nt

Start

After EAS

Start

Action Nam e De cisi on

Work on Deve lopme ntal EP

Y

Create Showcase EP

Program Exit Re vie w N

I nfo. Flow

Y

Passed?

End

Figure 12. Process model: Process and operation OSS: Office of Student Services; OIA: Office of Information and Assessment; PDS: Professional Development Schools; OTE: Office of Teaching Experiences; EP: Electronic Portfolio/ePortfolio;

EAS

Unit Create OSS/PDS/OIA/OTE

Flowchart Key

Actor

Actor Decision Info. Flow

OIA/OTE/PDS

N

Start/End

Actions

OIA/PDS/Assessme nt Committee Candidate meet exit requirements? Y Asse ssme nt Committe e

OSS

OIA/PDS Ongoing professional development

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Collec t program evaluation data; Place c andidate via EAS;

Manage admission via EAS; Coordinate advising via EAS; Te acher Candidate Student teac hing and ePortfolio development

Submit qualified candidate list for certification stamping

•

Start

Provide assessment and learning c apability to address acc ountability requirement

Asse ssme nt Committe e

NCATE Committe e

Compile assessment results; Analyze assessment data;

Align teac hing standards with c ourses and instruc tion

OIA/Lab Training; Tec h. Support; End

The Application for Admission to Teacher Certification Program was implemented by the Unit at both the undergraduate and graduate levels to reinforce program entrance criteria and assessments.

•

Education Communit y Using assessment data to improve progr ams; Advise & Assess students;

The EAS and the program-specific content were developed and further refined with the aim of alignment of curriculum, outcomes and assessments with the conceptual framework and various national and state standards.

Web-Based Education Accountability System and Organizational Changes

•

•

•

•

•

Undergraduate and graduate curriculum and advising instruments were revised to align with the benchmarks incorporated in the EAS, and curriculum and advising instruments were developed for two new masters programs. Assessment requirements, administration frequency and timelines were redefined and implemented across programs. A syllabus template was developed to help coordinate instructions, expectations and outcomes across curriculum and programs. A program-wide Clinical Practice Exit Conference was established to holistically and collaboratively evaluate each candidate’s performance. Electronic portfolio development and assessment became requirements.

Users complained about changes when the EAS was in its first pilot semester. One candidate commented “… Too much fluctuation within the program.” To address this concern, Champion developed a series of customized workshops to familiarize users with the program changes (Figure 12).

PROFESSIONAL ISSUES Four different groups used the EAS: teacher candidates, mentors, advisors and supervisors. Teaching professionals are independent and enjoy academic freedom. The actor-network could not successfully persuade professionals to use the EAS by just inscribing its usage into the administration requirements. Special strategies appropriate to the professional characteristics were employed to enroll the professionals into the actor-network. First, Champion enrolled two senior faculty members to help present EAS in various meetings. Second,

Champion persuaded program directors to act as delegates in each program to lead the adoption.

DISCUSSION The analysis indicated that the dominance of one network over another depended on the way in which a network of actors was able to translate and inscribe its ideas into convincing social or technical arrangements, and thus impose its desired structure on other actor-networks. The analysis of translations demonstrated how the political environment shaped technologies, and how it was shaped by technologies. Although Champion initiated the EAS and enrolled other actors in the network, Champion continued to describe the EAS project as a joint effort, involving many actors, and as a part of the University’s strategy. The EAS and the Unit shaped each other during EAS development. Actors enrolled in the actor-network were mobilized to negotiate a temporary stability between the organization’s requirements and the system’s capability. The active involvement of the professionals (faculty, mentors and supervisors), consistent support from the administration (Unit, college and university) and the culture of accepting change (new accreditation standards) were critical to success. The EAS evolved as the leadership and technology teams communicated with each other about various teacher standards and the functions that would be necessary to support those standards. The Unit’s previous hierarchical decision-making process was replaced by decentralized decisionmaking. The Unit established a long-term assessment plan, as required by NCATE. Information practice in the Unit was no longer an invisible act. The EAS permeated all social practices and became part of daily life. Analysis showed that IS and organizational processes were orchestrated to stabilize an actor-network. The actor-network determined the

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Web-Based Education Accountability System and Organizational Changes

organization of workflow and information in the IS. Social forces do not alone wholly shape the IS, nor do technical forces wholly shape the IS; rather, the ongoing interplay of social and technical forces shapes the IS. To differentiate the impact of social and technical forces is challenging. ANT provides a vocabulary and framework to make this differentiation (Latour, 1991). Special characteristics of the teaching profession played an important role in the shaping of the IS. Teachers would only use the system when they considered that the benefits outweighed the costs. When ISs are developed for other professionals, such as doctors in a health care clinic, the actornetwork dynamics of the teachers may recur.

CONCLUSION Few studies in education have exploited the advantages of ANT to study social consequences of information systems. This study used ANT to analyze the implementation of an IS in a teacher education program that had to move to electronic portfolios for students. ANT analysis was applied along four dimensions: organizational culture, power/politics, process/operation, and professional. Translation and inscription of the actor-network were delineated with actor identification, interest translation and actor-network maintenance. Through translation, the interests of the Champion became the interests of a wider network of actors (education community, technicians and higher management). Through inscription, discourse about education accountability became “frozen” in the IS, which helped improve the teacher education program’s decision-making process and operation. The collaborative modeling and system development processes shaped social practices in the teacher education program. Although the IS product was considered useful, the organizational changes introduced during IS development were

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more important than the technological changes. The lesson learned is applicable to other programs in similar settings. This research provides valuable insights into the processes of translation and inscription by which actor-networks develop. The Champion tries to move an actor-network into an irreversible status, from where it is impossible to go back to a point where alternatives exist. To this end, the Champion manipulates contending actor-networks to adjust translation and inscription strategies to keep the current actor-network in dominance. The authors are considering three other educational technology projects in which ANT analysis will be crucial. One concerns the implementation of an online degree program in a university department that has traditionally taught its courses face to face. The challenge is only in a small way to develop or acquire the appropriate ISs. The more difficult part is aligning the interests of the faculty with those of the administration of the university. In another related project, tools are needed to support a team of courseware developers. The different human and technology roles played in courseware development need to be carefully represented and an ANT analysis is appropriate here, too. In an example from another industry, the authors are involved with a hospital that wants to educate patients in online communities. The patients, their family members, nurses, doctors and social workers would be involved in a collaborative effort that requires ISs and organizational support. An actor-network theory approach to the patient education system is appropriate. Education is an intrinsically social phenomenon. Technology is increasingly vital in supporting education. The challenge of successfully implementing social and technical change requires the support of organizational theories, such as actor-network theory.

Web-Based Education Accountability System and Organizational Changes

REFERENCES Atkinson, C. J. (2002, January 7-10). The multidimensional systemic representation of actornetworks: Modelling breast cancer treatment decision-making. In Proceedings of the 35th Hawaii International Conference on System Sciences, HI. Barley, S. R. (1986). Technology as an occasion for structuring: Evidence from observations of CT scanners and the social order of radiology departments. Administrative Science Quarterly, 31, 78-108. Bijker, W. E., & Law, J. (1992). Shaping technology/building society: Studies in sociotechnical change. Cambridge: The MIT Press. Bloomfield, B. P., & Vurdubakis, T. (1997). Paper traces: Inscribing organisations and information technology. In B. P. Bloomfield, R. Coombs, D. Knights, & D. Littler (Eds.), Information technology and organisations (pp. 85-111). Oxford, UK: Oxford University Press. Callon, M. (1987). Society in the making: The study of technology as a tool for sociological analysis. In W. E. Bijker, T. P. Hughes, & T. J. Pinch (Eds.), The social construction of technological systems (pp. 85-103). Cambridge, MA: The MIT Press. Callon, M. (1991). Techno-economic networks and irreversibility. In J. Law (Ed.), A sociology of monsters: Essays on power, technology and domination (pp. 132-161). London: Routledge. Castenell, L. A., Benson, J., deMarrais, K., Butchart, R., & Lewis, J. (2001). From chaos to sanity: Preparing for NCATE 2000 at a comprehensive public institution using an electronic review. Paper presented at AACTE 2001, Dallas, TX. Checkland, P. B. (1981). Systems thinking, systems practice. New York: John Wiley & Sons.

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Larsen, K. R. T. (2003). A taxonomy of antecedents of information systems success: Variable analysis studies. Journal of Management Information Systems, 20(2), 169-246. Latour, B. (1991). Technology is society made durable. In J. Law (Ed.), A sociology of monsters: Essays on power, technology and domination (pp. 103-131). New York: Routledge. Law, J. & Callon, M. (1988). Engineering and sociology in a military aircraft project: A network analysis of technological change. Social Problems, 35(3), 284-297. Law, J., & Callon, M. (1992). The life and death of an artifact: A network analysis of technical change. In W.E. Bijker & J. Law (Eds.), Shaping technology/building society: Studies in sociotechnical change (pp. 21-52). Cambridge: The MIT Press. Linn, R. L. (2000). Assessments and Accountability. Educational Researcher, 23(9), 4-16. Linstone, H. A. (1999). Decision making for technology executives: Using multiple perspec-

Orlikowski, W. J., & Iacono, C. S. (2001). Desperately seeking the ‘IT’ in IT research—A call to theorizing the IT artifact. Information Systems Journal, 12(2), 121-134. Pickering, A. (1995). The mangle of practice: Time, agency and science. Chicago: University of Chicago Press. Robbins, S. P. (1996). Organizational behavior: Concepts, controversies, applications. Englewood Cliffs: Prentice Hall. Scacchi, W. (2004). Socio-technical design. In W. S. Bainbrigde (Ed.), The encyclopedia of human-computer interaction. Berkshire Publishing Group. Steinbruner, J. D. (1974). The cybernetic theory of decision. Princeton: Princeton University Press. Wise, A. E. (2001). Performance-based accreditation: Reform in action. Retrieved April 28, 2005, from www.ncate.org/documents/QualityTeaching/qtspring2000.pdf Zhu, Z. (2000). WSR: A systems approach for information systems development. Systems Research and Behavioral Science, 17(2), 183-203.

This work was previously published in the International Journal of Web-Based Learning and Teaching Technologies, Volume 1, Issue 4, edited by L. Esnault, pp. 1-14, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 2.8

Semantics for the Semantic Web:

The Implicit, the Formal, and the Powerful Amit Sheth University of Georgia, USA Cartic Ramakrishnan University of Georgia, USA Christopher Thomas University of Georgia, USA

ABSTRACT Enabling applications that exploit heterogeneous data in the Semantic Web will require us to harness a broad variety of semantics. Considering the role of semantics in a number of research areas in computer science, we organize semantics in three forms—implicit, formal, and powerful—and explore their roles in enabling some of the key capabilities related to the Semantic Web. The central message of this chapter is that building the Semantic Web purely on description logics will artificially limit its potential, and that we will need to both exploit well-known techniques

that support implicit semantics, and develop more powerful semantic techniques.

INTRODUCTION Semantics has been a part of several scientific disciplines, both in the realm of Computer Science and outside of it. Research areas such as information retrieval (IR), information extraction (IE), computational linguistics (CL), knowledge representation (KR) artificial intelligence (AI), and data(base) management (DB) have all addressed issues pertaining to semantics in their own ways.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Semantics for the Semantic Web

Most of these areas have very different views of what “meaning” is, and these views are all built on some meta-theoretical and epistemological assumptions. These different views imply very different views of cognition, of concepts, and of meaning (Hjorland, 1998). In this chapter, we organize these different views to three forms of semantics: implicit, formal, and powerful (a.k.a. soft). We use these forms to explore the role of semantics that go beyond the narrower interpretation of the Semantic Web (that involve adherence to contemporary Semantic Web standards) and encompass those required for a broad variety of semantic applications. We advocate that for the Semantic Web (SW) to be realized, we must harness the power of a broad variety of semantics encompassing all three forms. IR, IE, and CL techniques primarily draw upon analysis of unstructured texts in addition to document repositories that have a loosely defined and less formal structure. In these sorts of data sources, the semantics are implicit. In the fields of KR, AI, and DB, however, the data representation takes a more formal and/or rigid form. Well-defined syntactic structures are used to represent information or knowledge where these structures have definite semantic interpretations associated with them. There are also definite rules of syntax that govern the ways in which syntactic structures can be combined to represent the meaning of complex syntactic structures. In other words, techniques used in these fields rely on formal semantics. Usually, efforts related to formal semantics have involved limiting expressiveness to allow for acceptable computational characteristics. Since most KR mechanisms and the relational data model are based on set theory, the ability to represent and utilize knowledge that is imprecise, uncertain, partially true, and approximate is lacking, at least in the base/standard models. However, there have been several efforts to extend the base models (e.g., Barbara, Garcia-Molina, & Porter, 1992). Representing and utilizing these types

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of more powerful knowledge is, in our opinion, critical to the success of the Semantic Web. Soft computing has explored these types of powerful semantics. We deem these powerful (soft) semantics as distinguished, albeit not distinct from or orthogonal to formal and implicit semantics. More recently, semantics has been driving the next generation of the Web as the Semantic Web, where the focus is on the role of semantics for automated approaches to exploiting Web resources. This involves two well-recognized, critical enabling capabilities—ontology generation (Maedche & Staab, 2001; Omelayenko, 2001) and automated resource annotation (Hammond, Sheth, & Kochut, 2002; Dill et al., 2003; Handschuh, Staab, & Ciravegna, 2002; Patil, Oundhakar, Sheth, & Verma, 2004), which should be complemented by an appropriate computational approach such as reasoning or query processing. We use a couple of such enabling capabilities to explore the role and importance of all three forms of semantics. A majority of the attention in the Semantic Web has been centered on a logic-based approach, more specifically that of description logic. However, looking at past applications of semantics, it is very likely that more will be expected from the Semantic Web than what the careful compromise of expressiveness and computability represented by description logic and the W3C adopted ontology representation language OWL (even its three flavors) can support. Supporting expressiveness that meet requirements of practical applications and the techniques that support their development is crucial. It is not desirable to limit the Semantic Web to one type of representation where expressiveness has been compromised at the expense of computational property such as decidability. This chapter is not the first to make this above observation. We specifically identify a few. Uschold (2003) has discussed a semantic continuum involving informal to formal and implicit to explicit, and Gruber (2003) has talked about informal, semi-formal, and formal ontolo-

Semantics for the Semantic Web

gies. The way we use the term implicit semantics, however, is different compared to Uschold (2003) insofar as we see implicit semantics in all kinds of data sets, not only in language. We assume that machines can analyze implicit semantics with several, mostly statistical, techniques. Woods has written extensively regarding the limitations of first-order logics (FOLs)—and hence description logics, or DLs—in the context of natural language understanding, although limitations emanating from rigidness and limitation of expressive power, as well as limited value reasoning supported in DLs, can also be identified: Over time, many people have responded to the need for increased rigor in knowledge representation by turning to first-order logic as a semantic criterion. This is distressing, since it is already clear that first-order logic is insufficient to deal with many semantic problems inherent in understanding natural language as well as the semantic requirements of a reasoning system for an intelligent agent using knowledge to interact with the world. (Woods, 2004) We also recall Zadeh’s long-standing work (such as Zadeh, 2002), in which he extensively discussed the need for what constitutes a key part of the “powerful semantics” here. In essence, we hope to provide an integrated and complementary view on the range of options. One may ask what the uses of each of these types of semantics are in the context of the Semantic Web. Here is a quick take. •

Implicit semantics is either largely present in most resources on the Web or can easily (quickly) be extracted. Hence mining and learning algorithms applied to these resources can be utilized to extract structured knowledge or enrich existing structured formal representations. Since formal semantics intrinsically does not exist, implicit semantics is useful in processing data sets or

•

•

corpus to obtain or bootstrap semantics that can be then represented in formal languages, potentially with human involvement. Formal semantics in the form of ontologies is relatively scarce, but representation mechanisms with such semantics have definite semantic interpretations that make them more machine-processable. Representation mechanisms with formal semantics therefore afford applications the luxury of automated reasoning, making the applications more intelligent. Powerful (soft) semantics in the form of fuzzy or probabilistic KR mechanisms attempt to overcome the shortcomings of the rigid set-based interpretations associated with currently prevalent representation mechanisms by allowing for representation of degree of membership and degree of certainty. Some of the domain knowledge human experts possess is intrinsically complex, and may require these more expressive representations and associated computational techniques.

These uses are further exemplified later on using Semantic Web applications as driving examples. In the next section we define and describe implicit, formal and powerful (soft) semantics.

TYPES OF SEMANTICS In this section we give an overview of the three types of semantics mentioned. It is rather informal in nature, as we only give a broad overview without getting in depth about the various formalisms or methods used. We assume that the reader is somewhat familiar with statistical methods on the one hand and description logics/OWL on the other. We present a view of these methods in order to lead towards the necessity of powerful (soft) semantics.

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Implicit Semantics This type of semantics refers to the kind that is implicit from the patterns in data and that is not represented explicitly in any strict machine processable syntax. Examples of this sort of semantics are the kind implied in the following scenarios: •

•

•

•

•

Co-occurrence of documents or terms in the same cluster after a clustering process based on some similarity measure is completed. A document linked to another document via a hyperlink, potentially associating semantic metadata describing the concepts that relate the two documents. The sort of semantics implied by two documents belonging to categories that are siblings of each other in a concept hierarchy. Automatic classification of a document to broadly indicate what a document is about with respect to a chosen taxonomy. Further, use the implied semantics to disambiguate (does the word “palm” in a document refer to a palm tree, the palm of your hand, or a palm-top computer?). Bioinformatics applications that exploit patterns like sequence alignment, secondary and tertiary protein structure analysis, and so forth

One may argue that although there is no strict syntactic and explicit representation, the knowledge about patterns in data may yet be machine processable. For instance, it is possible to get a numeric similarity judgment between documents in a corpus. Although this is possible, this is the only sort of processing possible. It is not possible to look at documents and automatically infer the presence of a named relationship between concepts in the documents. Even though the exploitation of implicit semantics draws upon well-known statistical techniques,

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the wording is not a mere euphemism, but meant to give a different perception of the problem. Many tools and applications for implicit semantics have been developed for decades and are readily available. Basically all machine learning exploits implicit semantics, namely clustering, concept and rule learning, hidden Markov models, artificial neural networks, and others. These techniques supporting implicit semantics are found in early steps towards the Semantic Web, such as clustering in the Vivisimo search engine, as well as in early Semantic Web products, such as metadata extraction on Web Fountain technology (Dill et al., 2003), automatic classification, and automatic metadata extraction in Semagix Freedom (Sheth et al., 2002).

Formal Semantics Humans communicate mostly through language. Natural language, however, is inherently ambiguous—semantically, but also syntactically. Computers lack the ability to disambiguate and understand complex natural language. For these reasons, it is infeasible to use natural language as a means for machines to communicate with other machines. As a first step, statements or facts need to be expressed in a way that computers can process them. Semantics that are represented in some well-formed syntactic form (governed by syntax rules) is referred to as formal semantics. There are some necessary and sufficient features that make a language formal and by association their semantics formal. These features include: •

The notions of model and model theoretic semantics: Expressions in a formal language are interpreted in models. The structure common to all models in which a given language is interpreted (the model structure for the model-theoretic interpretation of the given language) reflects certain basic presuppositions about the “structure of the world” that are implicit in the language.

Semantics for the Semantic Web

•

The principle of compositionality: The meaning of an expression is a function of the meanings of its parts and of the way they are syntactically combined. In other words, the semantics of an expression is computed using the semantics of its parts, obtained using an interpretation function.

From a less technical perspective, formal semantics means machine-processable semantics where the formal language representing the semantics has the above-mentioned features. Basically, the semantics of a statement are unambiguously expressed in the syntax of the statement in the formal language. A very limited subset of natural language is thus made available for computer processing. Examples of such semantics are: •

•

The semantics of subsumption in description logics, reflecting the human tendency of categorizing by means of broader or narrower descriptions. The semantics of partonomy, accounting for what is part of an object, not which category the object belongs to.

Description Logics Recently, description logics have been the dominant formalisms for knowledge representation. Although DLs have gained substantial popularity, there are some fundamental properties of DLs that can be seen as drawbacks when viewed in the context of the Semantic Web and its future. The formal semantics of DLs is based on set theory. A concept in description logics is interpreted as a set of things that share one required common feature. Relationships between concepts or roles are interpreted as a subset of the cross-product of the domain of interpretation. This leaves no scope for the representation of degrees of concept membership or uncertainty associated with concept membership.

DL-based representation and reasoning for both schema and instance data is being applied in Network Inference’s Cerebra product for such problems as data integration. This product uses a highly optimized tableaux algorithm to speed up ABox reasoning, which was the bane of description logics. Although a favorable trade-off between computational complexity and expressive power has been achieved, there is still the fundamental issue of the inability of DLs to allow for representation of fuzzy and probabilistic knowledge.

Powerful (Soft) Semantics The statistical analysis of data allows the exploration of relationships that are not explicitly stated. Statistical techniques give us great insight into a corpus of documents or a large collection of data in general, when a program exists that can actually “pose the right questions to the data,” that is, analyze the data according to our needs. All derived relationships are statistical in nature, and we only have an idea or a likelihood of their validity. The above-mentioned formal knowledge representation techniques give us certainty that the derived knowledge is correct, provided the explicitly stated knowledge was correct in the first place. Deduction is truth preserving. Another positive aspect of a formal representation is its universal usability. Every system that adheres to a certain representation of knowledge will understand, and a well-founded formal semantics guarantees that the expressed statements are interpreted the same way on every system. The restriction of expressiveness to a subset of FOL also allows the system to verify the consistency of its knowledge. But here also lies the crux of this approach. Even though it is desirable to have a consistent knowledge base, it becomes impractical as the size of the knowledge base increases or as knowledge from many sources is added. It is rare that human experts in most scientific domains have

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a full and complete agreement. In these cases it becomes more desirable that the system can deal with inconsistencies. Sometimes it is useful to look at a knowledge base as a map. This map can be partitioned according to different criteria, for example, the source of the facts or their domain. While on such a map the knowledge is usually locally consistent, it is almost impossible and practically infeasible to maintain a global consistency. Experience in developing the Cyc ontology demonstrated this challenge. Hence, a system must be able to identify sources of inconsistency and deal with contradicting statements in such a way that it can still produce derivations that are reliable. In the traditional bivalent-logic-based formalisms, we—that is, the users or the systems—have to make a decision. Once two contradictory statements are identified, one has to be chosen as the right one. While this is possible in domains that are axiomatized, fully explored, or in which statements are true by definition, it is not possible for most scientific domains. In the life sciences, for instance, hypotheses have to be evaluated, contradicting statements have promoting data, and so forth. Decisions have to be deferred until enough data is available that either verifies or falsifies the hypothesis. Nevertheless, it is desirable to express these hypotheses formally to have means to computationally evaluate them on the one hand and to exchange them between different systems on the other. In order to allow the sort of reasoning that would allow this, the expressiveness of the formalism needs to be increased. It is known that increasing the expressive power of a KR language causes problems relating to computability. This has been the main reason for limiting the expressive power of KR languages. The real power behind human reasoning, however, is the ability to do so in the face of imprecision, uncertainty, inconsistencies, partial truth, and approximation. There have been attempts made in the past at building KR languages that allow such expressive power.

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Major approaches to reasoning with imprecision are: (1) probabilistic reasoning, (2) possibilistic reasoning (Dubois, Lang, & Prade, 1994), and (3) fuzzy reasoning. Zadeh (2002) proposed a formalism that combines fuzzy logic with probabilistic reasoning to exploit the merits of both approaches. Other formalisms have focused on resolving local inconsistencies in knowledge bases, for instance the works of Blair, Kifer, Lukasiewicz, Subrahmanian, and others in annotated logic and paraconsistent logic (see Kifer & Subrahmanian, 1992; Blair & Subrahmanian, 1989). Lukasiewicz (2004) proposes a weak probabilistic logic and addresses the problem of inheritance. Cao (2000) proposed an annotated fuzzy logic approach that is able to handle inconsistencies and imprecision; Straccia (e.g., 1998, 2004) has done extensive work on fuzzy description logics. With P-CLASSIC, Koller, Levi, and Peffer (1997) presented an early approach to probabilistic description logics implemented in Bayesian Networks. Other probabilistic description logics have been proposed by Heinsohn (1994) and Jaeger (1994). Early research on Bayesian-style inference on OWL was done by Ding and Peng (2004). In her formalism, OWL is augmented to represent prior probabilities. However, the problem of inconsistencies arising through inheritance of probability values (see Lukasiewicz, 2004) is not taken into account. The combination of probabilistic and fuzzy knowledge under one representation mechanism proposed in Zadeh (2002) appears to be a very promising approach. Zadeh argues that fuzzy logics and probability theory are “complementary rather than competitive.” Under the assumption that humans tend to linguistically categorize a continuous world into discrete classes, but in fact still perceive it as continuous, fuzzy set theory classifies objects into sets with fuzzy boundaries and gives objects degrees of set membership in different sets. Hence it is a way of dealing with a multitude of sets in a computationally tractable way that also follows the human perception of the

Semantics for the Semantic Web

world. Fuzzy logic allows us to blur artificially imposed boundaries between different sets. The other powerful tool in soft computing is probabilistic reasoning. Definitely in the absence of complete knowledge of a domain and probably even in its presence, there is a degree of uncertainty or randomness in the ways we see real-world entities interact. OWL as a description language is meant to explicitly represent knowledge and to deductively derive implicit knowledge. In order to use a similar formalism as a basis for tools that help in the derivation of new knowledge, we need to give this formalism the ability to be used in abductive or inductive reasoning. Bayesian-type reasoning is a way to do abduction in a logically feasible way by virtue of applying probabilities. In order to use these mechanisms, the chosen formalism needs to express probabilities in a meaningful way, that is, a reasoner must be able to meaningfully interpret the probabilistic relationships between classes and between instances. The same holds for the representation of fuzziness. The formalism must give a way of defining classes by their membership functions. A major drawback of logics dealing with uncertainties is the required assignment of prior probabilities and/or fuzzy membership functions. Obviously, there are two ways of doing that—manual assignment by domain experts and automatic assignment using techniques such as machine learning. Manual assignments require the domain expert to assign these values to every class and every relationship. This assignment will be arbitrary, even if the expert has profound knowledge of the domain. Automatic assignments of prior values require a large and representative dataset of annotated instances, and finding or agreeing on what is a representative set is difficult or at times impossible. Annotating instances instead of categorizing them in a top-down approach is tedious and time consuming. Often, however, the probability values for relationships can be obtained from the dataset using statistical

methods, thus we categorize these relationships as implicit semantics. Another major problem here is that machine learning usually deals with flat categories rather than with hierarchical categorizations. Algorithms that take these hierarchies into account need to be developed. Such an algorithm needs to change the prior values of the superclasses according to the changes in the subclasses, when necessary. Most likely, the best way will be a combination of both, when the domain expert assigns prior values that have to be validated and refined using a testing set from the available data. In the end, powerful semantics will combine the benefits of both worlds: hierarchical composition of knowledge and statistical analysis; reasoning on available information, but with the advantage over statistical methods that it can be formalized in a common language and that general purpose reasoners can utilize it, and with the advantage over traditional formal DL representation that it allows abduction as well as induction in addition to deduction. It might be argued that more powerful formalisms are already under development, such as SWRL (Straccia, 1998), which works on top of OWL. These languages extend OWL by a function-free subset of first-order logics, allowing the definition of new rules in the form of Horn clauses. The paradigm is still that of bivalent FOLs, and the lack of function symbols makes it impossible to define functions that can compute probability values. Furthermore, SWRL is undecidable. We believe that abilities to express probabilities and fuzzy membership functions, as well as to cope with inconsistencies, are important. It is desirable (and some would say necessary) that the inference mechanism is sound and complete with respect to the semantics of the formalism and the language is decidable. Straccia (1998) proves this for a restricted fuzzy DL; Giugno and Lukasiewicz (2002) prove soundness and completeness for the probabilistic description logic formalism P-SHOQ(D).

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So far, this powerful semantic and soft computing research has not been utilized in the context of developing the Semantic Web. In our opinion, for this vision to become a reality, it will be necessary to go beyond RDFS and OWL, and work towards standardized formalisms that support powerful semantics.

CORRELATING SEMANTIC CAPABILITIES wITH TYPES OF SEMANTICS Building practical Semantic Web applications (e.g., see TopQuadrant, 2004; Sheth & Ramakrishnan, 2003; Kashyap & Shklar, 2002) require certain core capabilities. A quick look at these core capabilities reveals a sequence of steps towards building such an application. We group this sequence into two categories as shown in Table 1 and identify the type of semantics utilized by each.

APPLICATIONS AND TYPES OF SEMANTICS THEY EXPLOIT In this section we describe some research fields and some specific applications in each field. This list is by no means a comprehensive list, but rather samples of some research areas that attempt solve problems that are crucial to realizing the Semantic Web vision. We cover information integration, information extraction/retrieval, data mining, and analytical applications. We also discuss entity identification/disambiguation in some detail. We associate with each of the techniques in these research areas one or more of the types of semantics we identified earlier.

Information Integration There is, now more than ever, a growing need for several information systems to interoperate

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in a seamless manner. This sort of interoperation requires that the syntactic, structural, and semantic heterogeneities (Hammer & McLeod, 1993; Kashyap & Sheth, 1996) between such information systems be resolved. Resolving such heterogeneities has been the focus of a lot of work in schema integration in the past. With the recent interest in the Semantic Web, there has been a renewed interest in resolving such heterogeneities. A survey of schema matching techniques (Rahm & Bernstein, 2001) identifies a wide variety of techniques that are deployed to solve this problem.

Schema Integration A look at the leaf nodes and the level immediately above it, in the classification tree of schema matching techniques in Rahm and Bernstein (2001), reveals the combination of the technique used and the type of information about the schema used for matching schemas. Depending on whether the schema or the instances are used to determine the match, the type of information harnessed varies. Our aim is to associate one or more types of semantics (from our classification) with each of the bulleted entries at the leaf nodes of the tree shown. Table 1 does just that.

Entity Identification/Disambiguation (EI/D) A much harder, yet fundamental (and related) problem is that of entity identification/disambiguation. This is the problem of identifying that two entities are in fact either the same but treated as being different or that they are in fact two different entities that are being treated as one entity. Techniques used for identification/disambiguation vary widely depending on the nature of the data being used in the process. If the application uses unstructured text as a data source, then the techniques used for EI/D will rely on implicit semantics. On the other hand, if EI/D is being

Semantics for the Semantic Web

attempted on semi-structured data, the application can, for instance, disambiguate entities based on the properties they have. This implies harnessing the power of formal or semi-formal semantics. As listed in Table 1, the constraint-based techniques are ideally suited for use in EI/D when semi-structured data is being used. Dealing with unstructured data will require the use of the techniques listed under linguistic techniques.

Information Retrieval and Information Extraction Let us consider information retrieval applications and the types of data they exploit. Given a

request for information by the user, information retrieval applications have the task of processing unstructured (text corpus) or loosely connected documents (hyperlinked Web pages) to answer the “query.” There are various flavors of such applications.

Search Engines Search engines exploit both the content of Web documents and the structure implicit from the hyperlinks connecting one document to the other. Kleinberg (1998) defines the notions of hubs and authorities in a hyperlinked environment. These notions are crucial to the structural analysis and

Table 1. Some key semantic capabilities and the type of semantics exploited

Bootstrapping Phase (building phase)

Capabilities

Implicit Semantics

Building ontologies either automatically or semiautomatically

Analyzing word cooccurrence patterns in text to learn taxonomies/ontologies (Kashyap et al., 2003)

Annotation of unstructured content wrt. these ontologies (resulting in semantic metadata)

Entity disambiguation

Analyzing word occurrence patterns or hyperlink structures to associate concept names from and ontology with both resources and links between them (Naing, Lim, & Goh, 2002) Using clustering techniques or support vector machines (SVMs) for entity disambiguation (Han, Giles, Zha, Li, & Tsioutsiouliklis, 2004)

Semantic integration of different schemas and ontologies

Analyzing the extension of the ontologies to integrate them (Wang, Wen, Lochovsky, & Ma, 2004)

Semantic metadata enrichment (further enriching the existing metadata)

Analyzing annotated resources in conjunction with an ontology to enhance semantic metadata (Hammond et al., 2002)

Formal Semantics

Using an ontology for entity disambiguation

Possible Use of Powerful (Soft) Semantics Using fuzzy or probabilistic clustering to learn taxonomic structures or ontologies Using fuzzy or probabilistic clustering to learn taxonomic structures or ontologies OR Using fuzzy ontologies Using fuzzy KR mechanisms to represent ontologies that may be used for disambiguation

Schema-based integration techniques (Castano, Antonellis, & Vimercati, 2001) This enrichment could possibly mean annotating with fuzzy ontologies

continued on following page

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Table 1. continued

Capabilities

Implicit Semantics

Hypothesis validation queries (Sheth, Thacker, & Patel, 2003) or path queries (Anyanwu & Sheth, 2002)

Complex query processing

Question answering (QA) systems1

Word frequency and other CL techniques to analyze both the question and answer sources (Ramakrishnan, Chakrabarti, Paranjpe, & Bhattacharya, 2004)

Concept-based search1

Analyzing occurrence of words that are associated with a concept, in resources

Connection and pattern explorer1

Analyzing semistructured data stores to extract patters (technique in Kuramochi & Karypis, 2004, applied to RDF graphs)

Context-aware retriever1

Word frequency and other CL techniques to analyze resources that match the search phrase

Utilization Phase

1

Dynamic user interfaces

Interest-based content delivery1

Analyzing content to identify concept of content so as to match with interest profile

Navigational and research (Guha, McCool, & Miller, 2003) search

Navigational searches will need to analyze unstructured content

Utilization Phase

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Formal Semantics

Using formal ontologies for QA (Atzeni et al., 2004)

Possible Use of Powerful (Soft) Semantics

Providing confidence levels in answers based on fuzzy concepts or probabilistic

Using hypernymy, partonomy, and hyponymy to improve search (Townley, 2000) Using ontologies to extract patterns that are meaningful (Aleman-Meza, Halaschek, & Sahoo, 2003) Using formal ontologies to enhance retrieval Using ontologies to dynamically reconfigure user interfaces (Quan & Karger, 2004) User profile will have ontology associated with it which contains concepts of interest Discovery style queries (Anyanwu & Sheth, 2002) on semistructured data which is a combination of implicit and formal semantics

Using fuzzy KR mechanisms to represent context

Fuzzy matches for research search results

Semantics for the Semantic Web

Table 2. Techniques used for schema integration and the type of semantics they exploit

Linguistic Techniques

Type of Information Used

What Does it Mean?

Name Similarity

Using canonical name representations, synonymy, hypernymy, string edit distance, pronunciation, and N-gram-like techniques to match schemas’ attribute and relation names

Description Similarity

Processing natural language descriptions associated with attributes and relations

Word Frequencies of Key Terms

Using relative frequencies of keywords and word combinations at the instance level

Type Similarity Key Properties Constraint Based Techniques

Graph Matching

Value Patterns and Ranges

Using information about data types of attributes as an indicator of a match between schemas Using foreign keys, part-of relationships, and other constraints Treating the structure of schemas as graph algorithms to determine match degree; between graphs are used to match schemas. Using ranges of attributes and patterns in the value of attributes as an indicator of similarity between the corresponding schemas

the eventual indexing of the Web. A modification of this approach aimed at achieving scalability is used by Google (Brin & Page, 1998). Google has fairly good precision and recall statistics. However, the demands that the Semantic Web places on search engine technology will mean that future search engines will have to deal with information requests that are far more demanding. Guha et al. (2003) identify two kinds of searches: •

Navigational searches: In this class of searches, the user provides the search engine with a phrase or combination of words which s/he expects to find in the documents. There is no straightforward, reasonable interpretation of these words as denoting a concept.

•

Types of Semantics Exploited Implicit Semantics are exploited by string edit distance, pronunciation, and N-gram-like techniques. Formal Semantics are exploited by synonymy, etc. Implicit Semantics are exploited by the NLP techniques deployed.

Implicit Semantics

Formal Semantics Formal Semantics Combination of Implicit and Formal Semantics

Implicit Semantics

In such cases, the user is using the search engine as a navigation tool to navigate to a particular intended document. Using the domain knowledge as specified in relevant domain ontology can enable an improved semantic search (Townley, 2000). Research searches: In many other cases, the user provides the search engine with a phrase that is intended to denote an object about which the user is trying to gather/research information. There is no particular document that the user knows about that s/he is trying to get to. Rather, the user is trying to locate a number of documents, which together will give her/him the information s/he is trying to find.

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We believe that research searches will require a combination of implicit semantics, formal semantics, and what we refer to as powerful semantics.

Question Answering Systems Question answering systems can be viewed as more advanced and more “intelligent” search engines. Current question-answering systems (Brin & Page, 1998; Etzioni et al., 2004; Ramakrishnan et al., 2004) use Natural Language Processing (NLP) and pattern matching techniques to analyze both the question asked of the system and the potential sources of the answers. By comparing the results of these analyses, such systems attempt to match portions of the sources of the answer (for instance, Web pages) with the question, thereby answering them. Such systems therefore still use data like unstructured text and attempt to extract information from it. In other words the semantics are implicit in the text and are extracted from this text. To facilitate question answering, Zadeh (2003) proposes the use of an epistemic lexicon of world knowledge, which would be represented by a weighted graph of objects with uncertain attributes; in our terminology this is the equivalent of an ontology using powerful semantics.

points into clusters, attempt to use this information (implicit semantics) to learn something about the interactions between the clustered entities. The sort of information sought from the clustered data points may range from simple similarity judgments as in query-by-example (QBE) document retrieval systems or systems aimed at extracting more formal semantics from the underlying data, as is the aim of semi-automatic taxonomy generation.

Semi-Automatic Taxonomy Generation (ATG) As described in Kashyap et al. (2003), the aim of Automated Taxonomy Generation is to hierarchically cluster a document corpus and extract from the resulting hierarchy of clusters a sequence of clusters that best captures all the levels of specificity/generality in the corpus, where this sequence is ordered by the value of the specificity/generality measure. This is then followed by a node label extraction phase, where each cluster in the sequence is analyzed to extract from it a set of labels that best captures the topic its documents represent. These sets of labels are then pruned to reduce the number of potential labels for nodes in the final output hierarchy.

Data Mining

Association Rule Mining

The goal of data mining applications is to find non-trivial patterns in unstructured and structured data.

An example of an association rule is given in Agrawal, Imielinski, and Swami (1993) and Agrawal and Srikant (1994) as follows: 90% of the transactions in a transaction database that involve the purchase of bread and butter together also have the purchase of milk involved. This is an example of an application where occurrence patterns of attribute values in a relational database (implicit semantics) are converted in association rules (formal semantics).

Clustering Clustering is defined as the process of grouping similar entities or objects together in groups based on some notion of similarity. Clustering is considered a form of unsupervised learning. The applications of clustering use a given similarity metric and, as a result of the grouping of data

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Analytical Applications These come under the purview of applications that support complex query processing. It would be reasonable to hypothesize that search engines of the future will be required to answer analytical or discovery style queries (Guha et al., 2003; Anyanwu & Sheth, 2002). This is in sharp contrast to the kinds of information requests today’s search engines have to deal with, where the focus is on retrieving resources from the Web that may contain information about the desired keyword. In this current scenario the user is left to sift through vast collections of documents and further analyze the returned results. In addition to querying data from the Web, future search engines will also have to query vast metadata repositories. We discuss one such technique in the following section.

Complex Relationship Discovery As described in Anyanwu and Sheth (2002): Semantic Associations capture complex relationships between entities involving sequences of predicates, and sets of predicate sequences that interact in complex ways. Since the predicates are semantic metadata extracted from heterogeneous multi-source documents, this is an attempt to discover complex relationships between objects described or mentioned in those documents. Detecting such associations is at the heart of many research and analytical activities that are crucial to applications in national security and business intelligence. The datasets that Semantic Associations operate over are RDF/RDFS graphs. The semantics of an edge connecting two nodes in an RDF/RDFS graph are implicit, in the sense that there is no explicit interpretation of the semantics of the edge other than the fact that it is a predicate in a statement (except for rdfs:subPropertyOf or edges that

represent data type properties—for which there is model-theoretic (formal) semantics). Hence the RDF/RDFS graph is composed of a combination of implicit and formal semantics. The objective of Semantic Associations is therefore to find all contextually relevant edge sequences that relate two entities. This is in effect an attempt to combine the implicit and formal semantics of the edges in the RDF/RDFS graph in conjunction with the context of the query to determine the multifaceted (multivalent) semantics of a set of “connections” between entities. We view this multivalent semantics as a form of powerful semantics. In the context of search, Semantic Associations can be thought of as a class of research searches or discovery-style searches.

CONCLUSION We have identified three types of semantics and in the process assorted key capabilities required to build a practical semantic application involving Web resources. We have also qualified each of the listed capabilities with one or more types of semantics, as in Table 1. This table reveals some very basic problems that need to be solved for an application to be termed “semantic.” It is clear from this table that entity disambiguation, question answering capability, context-based retrieval, and navigational and research (discovery) style query capability require the use of all three types of semantics. Therefore by focusing research efforts in representation mechanisms for powerful (soft) semantics in conjunction with fuzzy/probabilistic computational methods supporting techniques that use implicit and formal semantics, it might be possible to solve some of the difficult but practically important problems. In our opinion the current view taken by the Semantic Web community is heavily biased in favor of formal semantics. It is clear, however, that the focus of effort in pursuit of the Semantic

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Web vision needs to move towards an approach that encompasses all three types of semantics in representation, creation methods, and analysis of knowledge. If the capabilities that we identified do in fact turn out to be fundamental capabilities that make an application semantic, these capabilities could serve as a litmus test or a standard against which other applications may be measured to determine if they are “semantic applications.”

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Chapter 2.9

A Comparative Analysis of Computer-Supported Learning Models and Guidelines Fethi Ahmet Inan The University of Memphis, USA Deborah L. Lowther The University of Memphis, USA

ABSTRACT This chapter presents a comprehensive analytical review of computer-supported learning (CSL) design models and guidelines according to the level of emphasis regarding key elements and dimensions of effective teaching and learning within an online environment. The key elements encompass learning activities, learning environment, and/or assessment of student learning. Ultimately our purpose was to identify components that experts considered as critical to achieving effective CSL environments in order to use this information as a framework to design, develop, and implement CSL. The results indicate that the trend in CSL design and development models and guidelines is to create online environments that support constructivist learning that is student-

centered, presents resources in varied formats, supports discussions and/or collaborative and/or problem-based learning as well as independent student research and use of resources.

INTRODUCTION When computer-supported learning (CSL) is coupled with the limitless connectivity of the Internet, educational opportunities expand beyond barriers of traditional learning environments. Learning via interactive, virtual Web-based communities and environments now extends into today’s K12 classrooms, universities, and the workforce. CSL allows education to occur independent of the place and time (Moore & Kearsley, 1996) and provides learners opportunities to search,

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A Comparative Analysis of Computer-Supported Learning Models and Guidelines

discover, and utilize information according to their own individual needs (Dabbagh & BannanRitland, 2005; Khan, 1997). Basically, the Internet is a flexible, interactive, and resource rich system that supports student-centered learning (Hill & Hannafin, 2001). The use of CSL environments is gaining more popularity each day; the number of Web-supported or Web-based courses in training, colleges, and K12 levels are increasing significantly in the United States (Allen & Seman, 2004; Picciano, 2001; Setzer & Lewis, 2005). For example, approximately 54,000 Web-based courses were offered by 1,680 different institutions in 2002 (Simonson, Smaldino, Albright, & Zvacek, 2003). Over 1.9 million students enrolled in online courses in the fall of 2003, and predictions indicate the number will increase to over 2.6 million in 2004 (Allen & Seman, 2004). Regardless of capabilities of the delivery medium, typical CSL applications and practices continue to be teacher-directed and delivery-centered (Carr-Chellman & Duchastel, 2001; Naidu, 2003). Merely delivering course content through use of the Web is a common phenomenon in that many course sites are primarily text driven repositories for syllabi, course notes, and electronic presentations (Palloff & Pratt, 1999). Although online publishing of course syllabi and PowerPoint lecture notes can be of value, developing an effective online course involves much more than just transforming existing course materials to a Web format (Burch, 2001; Discenza, Howard, & Schenk, 2002). Yet, this widely used instructional medium is often developed and implemented upon the basis of “what works” in traditional settings, institution-specific guidelines, or recommendations found in a research article or textbook. “Traditional” approaches often include no or limited use of the attributes and functions of the Web that enable the creation of student-centered learning environments. Considerations for developing student-centered environments include selecting the most appropriate method for presenting

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content, engaging students in learning activities, and supporting the needs of individual learners (Hirumi, 2002b; Naidu, 2003). Most would agree that in order for CSL to be effective, research-based models and guidelines should serve as the structural foundation for systematically planning, designing, developing, and implementing the CSL environment. However, the task of selecting a model becomes daunting in that numerous options are presented in current literature. This chapter used a variety of methods to address these concerns. An initial approach involved operationally defining elements, dimensions, and attributes of CSL models. From these definitions, an analysis schema was developed to assess the frequency with which these components are addressed in “effective” CSL models. It is important to note that the purpose of this chapter is not to report on the “quality” of CSL models and guidelines, but rather to present the results of a comprehensive analytical review of published models and guidelines.

DESCRIPTION OF ANALYSIS SCHEMA The analysis schema for the CSL models and guidelines was created by an extensive review of research on effective teaching and learning in CSL environments (Driscoll, 1999; Hannafin, Hill, & Land, 1997; Hill & Hannafin, 2001; Hirumi, 2002b; Jonassen, Peck, & Wilson, 1999; Land & Hannafin, 2000; Schunk, 2004). The procedure used to create analysis schema includes the following steps: examination of literature, identification of key elements related to teaching and learning in a Web-based learning environment, and grouping these identified elements into main categories. First, to identify key elements, the researchers examined a selection of articles and books related to effective teaching and learning in CSL. Following the examination, a list of key elements was created. For instance, names like

A Comparative Analysis of Computer-Supported Learning Models and Guidelines

“project-based learning,” “performance based assessment,” “scaffolding,” “accessibility,” and “testing” were used. Second, the elements that fit together meaningfully were grouped into major elements such as “learning activities,” “assessment format,” and “assessment source.” These major elements enabled the researcher to identify the main dimensions. Lastly, main dimensions were formed, namely, “learning” and “assessment.” After an analysis schema was developed, the researchers began testing this schema to ensure comprehensiveness of the items. The schema was slightly modified during this pre-analysis process. After the schema was finalized (see Table 1), all articles were reviewed based on the final version of analysis schema. Understandably, learning and assessment emerged as the two major elements impacting CSL design and development. As seen in Table 1, Learning is comprised of a variety of instructor-planned activities, which occur within an environment that consists of different components. When designing CSL, instructors have the option of including student activities that can range from traditional to student-centered methods. Traditional activities would include the use of didactic approaches (e.g., online lecture notes or videos) to disseminate course content and the use of independent learning. On the other hand, student-centered choices might include collaborative, project-based learning that embeds student discussions and interactive communications. Once the activities are chosen as a basis of achieving the course objectives, an effective learning environment can be designed. Multiple options are available to create learning environments that support traditional and/or student-centered activities. These include the provision of scaffolding resources to address remediation needs, instructional feedback to increase learning, and the teacher acting as a facilitator of the “virtual” classroom. Additional dimensions of the learning environment include flexibility to meet individual needs, usability of the course

management software, the level of student support, and types of resources (text, multimedia, and supplemental) available to students. The intent of all CSL courses is student achievement of course goals. Therefore, the next critical element of designing online environments is assessment. Two elements of assessment are addressed: format and source. The format of the assessment does not differ from that which would be used in a non-CSL course in that it addresses knowledge or performance-based measures. The difference occurs in the source of the assessment. Within a CSL environment, students can be assessed by the instructor, peers, or self-evaluations using text or audio comments added to documents, completion of online rubrics, graded assignments returned to students, or scheduled video conferences. The CSL system can also provide assessment data in the form of participation (e.g., e-mail, discussion boards, online chats) records. As with the other design considerations, selection of the appropriate assessment format and source should be determined by overall course goals.

IDENTIFIED CSL MODELS AND GUIDELINES In order to identify target models and guidelines, an extensive literature search was conducted. The review was initiated through the use of electronic libraries (e.g., ERIC, EBSCOhost, PsychINFO) and search portals (e.g., google.com). This was followed by a review of non-digital refereed journals and books. Moreover, references of the articles located through the above searches were scanned. First, over 75 articles related to the teaching and learning process of CSL were gathered. After initial examination, some articles were eliminated based on whether they provided a guideline or model for design and development of CSL. This review process resulted in the identification of over 28 models and guidelines that addressed at least one of the criteria categories identified in

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A Comparative Analysis of Computer-Supported Learning Models and Guidelines

Table 1. Elements, dimensions, and attributes of computer-supported learning environments Elements Learning Activities

Dimensions

Attributes

Discussions

 Generally, planned conversation between students, studentsteacher.  Can be moderated  Academic focused, Not social or informal discussion  Can be synchronous or asynchronous  Examples: Group brainstorming sessions, guided debate  Students work together to understand content, solve problems and/or create product.  Typically planned and facilitated  Examples: Peer reviews, group projects  Student initiated communication between themselves by means of web-based communication tools.  Topics are student-selected and may be non-course related  Enable interpersonal relationships/interactions  Student-centered activities to solve authentic, ill-structured problem(s)  No specific path to solve the problem  Students assume roles of researchers  Generally involve student collaboration to produce a group product  Students construct an artifact or develop a product  Teacher designates specific path of learning outcomes  Learner controls pace of project completion  May involve student collaboration and production of a group product  Examples: Goal based scenarios, Web Quests  Instructor-controlled dissemination of content  Typically lecture format in the form of audio, video, or text  Students follow self-learning activities that may include a wide range of resources, learning activities and assignments:  Independent work to gather fact or answer question  Students are responsible for completing individual assignments  Examples: Writing an individual research paper, reading chapters and answering end-of-chapter questions.  Support strategy or mechanism to assist student learning  Procedural, conceptual, metacognitive, and strategic  Not feedback  Providing information to student action or product  Upon request from students or nature of task  Goes beyond the “correct” and “incorrect”  Mostly, use accepted criteria  Amount of control learners have over their own learning process  Can include navigation, pacing, content, practice, and feedback choices  Supportive, not directive role  Active monitoring of individual or group learning  Academic focus  Navigation and orientation  Ease of use  Consistency of design

Collaborations

Interactive Communication

Problem-based

Project-based

Didactic Independent / Resource-based

Environment

Scaffolding Feedback

Learner Control

Teacher as Facilitator Usability

continued on following page

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A Comparative Analysis of Computer-Supported Learning Models and Guidelines

Table 1. continued Learner Support

Course Content- Text Only

Assessment Format

Course Content - Multimedia

 Different content presentation with different media format (e.g. audio, video)

Flexibility

 Accommodating individual preferences considering access to resources and scheduling  Address learners with disabilities

Knowledge

Peer

 Recognition or recall of conceptual knowledge  Objective based assessments  Test, quizzes, survey  Demonstration of knowledge  Commonly involve use of rubric, checklist or rating scale  Products from project / problem based learning  Examples: Portfolio, role playing, presentation  Instructor assesses student knowledge and performance  System produces reports regarding student participation, number of posts  Students use guided reflection  Feedback by self-scoring by system  Reflection from peers for student learning progress or product

Constructivism

 Learners are the center of the design activity and have major

Performance

Source

Instructor System Student (self)

Profile Origin

 Student access to instructor or facilitator for: - Course-related (e.g., assignments) - Learning (e.g., understanding concepts) - Technical (e.g., uploading assignment)  Organization/structure of the materials  Script for audio/video materials  Content downloadable

learning responsibility

 Use of communication tools to promote interaction and social

activities.

 Encourage problem-based and cooperative learning, self-

evaluation, and student reflection

 Assessment practices involve real life problems in authentic

Cognitivism

settings (Driscoll, 1999; Jonassen et al., 1999; Mishra, 2002).

 Instruction is designed to promote individual information

processing and decrease cognitive overload.

 Uses strategies to promote encoding and increase retrieval of

information efficiently

 Considers learners prior knowledge, competencies, and

Behaviorism

metacognitive abilities (Schunk, 2004)

 Instruction is designed to promote individual pacing in which

learners proceed step-by-step with immediate reinforcement

 Content is divided into small frames or chunks  Assessment involves measuring behavioral objectives (Mishra,

Audience

2002)

Higher Education

 Intended and tested for college or higher level education

Training

 Intended for online training development

Generic

 Applicable for multiple adult audiences

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A Comparative Analysis of Computer-Supported Learning Models and Guidelines

the analysis schema: learning activities, learning environment, and/or assessment of student learning. A brief description of each model or set of guidelines is presented in Table 2.

ANALYSIS OF CSL MODELS AND GUIDELINES Each of the 28 identified CSL models or set of CSL guidelines was assessed on the degree to which the elements, dimensions, and attributes listed in the analysis schema were addressed or supported, for example, fully supported (“X”) or partially supported (“x”). The analysis results can be seen in Table 3. These results were then summarized into frequencies with which each component was fully or partially supported or emphasized in the published models and guidelines (see Table 4). Further analysis revealed a positive trend in CSL environments that is supportive of constructivist learning (n = 18). This philosophy is reflected in the types of learning activities that were most commonly mentioned, for example, engaging students in discussions (n = 13), independent work involving locating and researching a variety of resources (n = 12), collaborative learning (n = 11), as well as problem-based activities (n = 8) (see Figure 1). A similar pattern was seen with regard to learning environments. Almost half of the CSL models and guidelines suggested that the online learning environment should provide feedback (n = 13); offer content in a multiple formats (audio, video, virtual interactions) (n = 13); allow students to control a variety of learning variables (e.g., pace, types of resources) (n = 11); and have teachers serve as facilitators of learning (n = 10) (see Figure 2). With regard to the suggested assessment format, there were no considerable differences between knowledge and performance-based measures; however, there was a slight preference for instructors and peers as the assessment source.

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DISCUSSION As seen, the trend in CSL design and development models and guidelines is to create online environments that support constructivist learning that is student-centered, presents resources in a variety formats, and supports discussions and/or collaborative and/or problem-based learning as well as independent student research and use of resources. The guidelines also suggest that teachers should serve as facilitators and students should be able to receive feedback and have control over various aspects of their learning. Additional recommendations included using both instructors and peers to conduct assessments of student knowledge and performance. Since these proposed environments are different from traditional instructional settings, CSL teachers are faced with new design and development considerations for learning activities and environments.

Learning Activities Social learning has long been an important topic of interest among educators due to its well-established benefits. Students can construct and develop knowledge, attitudes, and values through interaction with others (Woolfolk, 1995). Similarly, learning can occur vicariously when students learn by observing others (Schunk, 2004). As seen in the results, there is a prominence of group-based approaches that emphasize social learning (Brush, 1998; Jonassen, Howland, Moore, & Rose, 2003). In addition, group-based learning often leads to the creation of a learning community that continuously produces and shares information and artifacts while engaging in collaborative learning and reflective practices (Dabbagh & Bannan-Ritland, 2005; Palloff & Pratt, 2003). Guidelines for creating effective learning communities involve the inclusion of: •

Active interaction involving both course content and personal communication

A Comparative Analysis of Computer-Supported Learning Models and Guidelines

•

•

Collaborative learning evidenced by comments directed primarily student to student rather than student to instructor Socially constructed meaning evidenced by agreement or questioning, with the intent to achieve agreement on issues of meaning

• •

Sharing of resources among students Expressions of support and encouragement exchanged between students, as well as willingness to critically evaluate the work of others (Palloff & Pratt, 1999, p. 32)

Table 2. Descriptions of CSL models and/or guidelines included in analysis Model # 1

Authors Alonso, Lâopez, Manrique, and Viänes (2005)

2

Berge (2002)

3

Burch (2001)

4

Carr-Chellman and Duchastel (2001)

5

Cooper (2002)

6

Egbert and Thomas (2001)

7

Fisher (2001)

8

Gillespie (1998)

9

Graham, Cagiltay, Lim, Craner, and Duffy (2001)

10

Hall, Watkins, and Eller (2003)

11

Hirumi and Bermudez (1996)

12

Hirumi (2002a)

13

Ingram and Hathorn (2003)

CSL Model and/or Guideline Description Describes an instructional model for e-learning that utilizes a blended learning approach. Authors base the model on information processing theory and social constructivist theory in that the self-paced design addresses cognitive load, attention, and metacognition with supporting collaborative activities. Provides a framework for implementing constructivist philosophy to create dynamic learning environments which incorporate student-centered learning activities, social interactions, instructor facilitation, and student self-evaluation and reflections. Provides a framework for designing communication in web-based courses. Communication is examined from the user interface (web site design) viewpoint in an effort to allow the learners and web site to interchange messages using two-way communication. Discusses a set of essential components for designing and developing online courses. Components include student support, content, student assessment, social interaction and collaboration, communication, and theoretical origin. Based on the practices of online business computer application courses, the author provides a framework of instructional strategies and management techniques for online courses. Starting from planning the online course, the author primarily portrays application of strategies and techniques for the initial classroom meeting; creating and managing interactions, providing various course materials, and student testing. Applies a traditional instructional design model to develop graduate level online courses. In addition to design guidelines, the authors incorporate studentcentered strategies such as problem-based learning and discussions. Presents an analysis of web-based instructional practices. The intent of the resulting guidelines is to direct educators when developing online course materials. Presents a comparison of a traditional vs. a non-traditional process employed to develop web-based learning. The new model focuses on helping students to develop higher-order thinking and problem solving skills. Uses the seven principles developed for evaluating teaching in traditional, faceto-face courses as a general framework to evaluate online courses. Authors use this framework to provide guidelines for design and development of online courses. A model of designing web-based learning environments, which consists of seven components: directionality, usability, consistency, interactivity, multimodality, adaptability, and accountability. Focuses on analysis, design, development, and evaluation of interactive webbased instruction. The authors examine development of graduate level instructional units by employing strategies to promote interactivity, active learning, and development of learning communities. Introduces a three-level categorization of web-based interaction. The author extends traditional interaction types (student-student, student-teacher, studentcontent) with student self-interaction and student-instruction interaction. Within this environment the interactions are connected to grounded instructional strategies within a organized framework. Presents a model based on the instructional design model of Dick, Carey, and Carey (2001). It assists novice designers to focus on the instructional components of online learning such as content presentation, instructional strategies, and interaction.

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Table 2. continued

812

14

Janicki, Schell, and Weinroth (2002)

15

Johnson and Aragon (2002)

16

Khan (2000)

17

Koszalka and Bianco (2001)

18

Lefoe, Gunn, and Hedberg (2002)

19

20

MacDonald, Stodel, Farres, Breithaupt, and Gabriel (2001) (2001) Mason (2001)

21

Moallem (2001)

22

Naidu (2003)

23

Oliver (1999)

24

Schnitz and Azbell (2004)

25

Schrum and Benson (2002)

26

Shearer (2003)

27

Trentin (2001)

28

Zheng and Smaldino (2003)

Describes the development of a model that guides the creation of web-based instruction by blending behavioral, cognitive, and constructivist learning theories. The model focuses on development of stimulating and interesting content, student engagement, multiple forms of presentation, detailed assessment and feedback. Discusses a conceptual framework to guide development of online courses through the synthesis of multiple theoretical perspectives. The authors provide seven pedagogical factors that the designer should consider (1 ) individual differences, (2) motivation, (3) cognitive overload, (4) authentic context, (5) social interaction, (6) student engagement and practice, and (7) student reflection. Describes a comprehensive framework to guide development of online learning materials, courses, and programs. The framework consists of eight components to embrace pedagogical, technological and administrative issues. Describes practical implications of instructional design process for online learning. The authors examine three design elements; information, instruction, and learning with regard to their contribution to the teaching and learning process. Examines pedagogical, technological, student support, and administrative challenges and problems of online learning. Based on categorization of these challenges, the authors provide recommendations for implementation - taking student perspectives into account. Introduces the Demand-Driven Learning Model (DDLM), which is a framework for designing web-based learning environments. The model consists of five components: superior structure, content, delivery, and service, and learner outcomes. Introduces a model to categorize online programs according to their formation. Furthermore, author provides pedagogical perspective for teaching in an online environment. Introduces a combined model for designing and developing web-based courses by employing constructivist and objectivist learning theories. Also presented are evaluation findings from implementation of the model. Examines the capabilities and limitations of e-learning. The author provides a contemporary perspective on pedagogical approaches to improve efficiency of online learning. Describes a framework for the critical design elements of online learning. These elements include the course content, learner support, and learning activities. The author demonstrates how different web tools address these design issues. The model and guidelines address full capabilities of available technologies. Authors provide a model that leverages the advantages offered by available web-based technologies to overcome challenges of online learning. A book chapter that examines challenges of online learning from the perspectives of learners, online educators and program administration. Authors categorize and provide solution approaches to overcome these challenges. Presents an inclusive list of critical variables and factors to consider when designing online instruction such as learner control, interaction, and access. Distance education is examined from print to two-way video conferencing technologies to display how these technologies address and align with designing online environments. Approaches the design of online courses by examining the course plan and the communication architecture. Key elements addressed in the course plan include learning needs, prerequisites, educational strategies, evaluation criteria, course activities and resources, the schedule and mode of operation. The communication architecture addresses communication requirements, network services, and logical communication structure. Presents essential components of designing instruction for online learning environments. Based on pertinent instructional design models, the authors identify critical elements of online learning (learner analysis, content organization, instructional strategies, and evaluation) and provide suggestions to improve the quality of online instruction.

A Comparative Analysis of Computer-Supported Learning Models and Guidelines

Table 3. Schema analysis of CSL models and guidelines by elements and dimensions of CSL environments ELEMENTS Learning Activities

Environment

Assessment Format Source

Profile Origin Audience

ELEMENTS Learning Activities

Environment

DIMENSIONS Discussions Collaborations Interactive Communication Problem-based Project-based Didactic Independent / Resourcebased Scaffolding Feedback Learner Control Teacher as facilitator Usability Student support Content- Text Only Content - Multimedia Flexibility

1 X x x x X

x

DIMENSIONS Discussions Collaborations Interactive Communication Problem-based Project-based Didactic Independent / Resourcebased Scaffolding Feedback Learner Control Teacher as facilitator Usability Student support Content- Text Only Content - Multimedia Flexibility

3

X

X

x

x

X X x

X X

x

X X x

x

x x X X x

X x

X x

X

x

X

x X

X

X

X

X 11

12

13

x x

x x

X

x x x

X

X

x X

X X

x X X

MODEL # 5 6

X X

X X

X X X X

4

x X X X X

X X

Knowledge Performance Instructor System Student (self) Peer Constructivism Cognitivism Behaviorism Higher Ed. Training Generic

2

X X X x X

X X

14

X

X

X X

x x x x x X x x x x x x x X

X x x

7 x x x

8

9

x

X X

x x

X x X x

X X X x x x x

X X x x x x X

MODEL # 15 16 X X X x X

X

x

x

X

X X x X

X x x x

x X x

X

X

x X

X X X

x X X X

X x X X x x

X x X x

x x x X

X

X x

X

X

X

17

18

19

20

X x x

X X X

X X

x

X X X X X

X

X

X x x X X

x X

10

X x

X

x X X X X X

X x

X x

x X

x X

x

X

continued on following page

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A Comparative Analysis of Computer-Supported Learning Models and Guidelines

Table 3. continued Assessment Format Source

Profile Origin Audience

ELEMENTS Learning Activities

Environment

Assessment Format Source

Profile Origin Audience

814

Knowledge Performance Instructor System Student (self) Peer

X

X

X

X

X x x

X

x

X x x

x x x

X X X

X

X

21

22

23

Discussions Collaborations Interactive Communication Problem-based Project-based Didactic Independent / Resourcebased Scaffolding Feedback Learner Control Teacher as facilitator Usability Student support Content- Text Only Content - Multimedia Flexibility

X X

X

Knowledge Performance Instructor System Student (self) Peer

X X X

Constructivism Cognitivism Behaviorism Higher Ed. Training Generic

X X X X

Constructivism Cognitivism Behaviorism Higher Ed. Training Generic DIMENSIONS

x X X

X X X X

x X X

x x

X

X

X X X X

X X X

X MODEL # 24 25

X

x

X X X x X X

X X

X

X

X

X

X

X X

26

27

28

x

X X X X

x

x

x

X X X X

X X X

X

x

X X X X

X X X X

X X X X

x X x X

X X X

X

X X

X

X

X X

X

X X

X x x

x X X

x x x

X

x x

X x X X X

X X X X x x

X X X

X X

X

X x

X X

X X X X X

X

x X X

X x x X X x

X x x X

X x x X

A Comparative Analysis of Computer-Supported Learning Models and Guidelines

Table 4. Frequency of CSL dimension occurrence by degree of emphasis ELEMENTS LEARNING

DIMENSIONS Activities

Environment

ASSESSMENT Format Source

PROFILE

Origin

Audience

Discussions Independent / Resource-based Collaborations Problem-based Project-based Interactive Communication Didactic Feedback Content – Multimedia Learner Control Teacher as facilitator Content- Text Only Usability Student support Flexibility Scaffolding Performance Knowledge Instructor Peer Student (self) System Constructivism Cognitivism Behaviorism

EMPHASIS Full Partial 13 8 12 7 11 4 8 8 7 3 7 4 1 4 13 4 13 8 11 6 10 7 9 7 8 4 8 3 6 5 5 4 12 6 9 7 11 6 6 3 3 5 1 3 18 7 8 10 5 8

Higher Education Generic Training

16 11 2

Learning Environment Design and development of tools and learning environments that support the creation and support of learning communities and/or collaborative learning is an emerging issue for two primary reasons. First, for cooperation to take place, students must have a shared workspace (Jonassen et al., 2003). The well-established research of the Computer-Supported Intentional Learning Environment, now known as the Knowledge Forum, has addressed these issues. Their approach has

0 0 0

involved examining online knowledge building, organization and sharing systems that support student learning through the generation and sharing of learning artifacts to receive feedback, and update their knowledge (Dabbagh & Bannan-Ritland, 2005). The second issue is a growing concern that the individual differences of learners may not be met when CSL courses increase the focus on group-based activities. Differences among the learner’s skill, aptitude, and preferences can influence learning progress in online environments

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A Comparative Analysis of Computer-Supported Learning Models and Guidelines

Figure 1. Learning activities by frequency of strong emphasis in CSL models and guidelines 14 12 10 8 6 4 2 0

Discussions Learning Activities

Interactive Independent/ Collaborations Problem-based Communication Project-based Resourcebased

13

12

11

8

1

7

7

Didactic

Figure 2. Learning environment by frequency of strong emphasis in CSL modules and guidelines 14 12

10 8 6 4

2 0 Learning Environment

816

Feedback

Content Multimedia

Learner Control

Teacher as facilitator

ContentText Only

Usability

Student support

Flexibility

Scaffolding

13

13

11

10

9

8

8

6

5

A Comparative Analysis of Computer-Supported Learning Models and Guidelines

(Chen, Czerwinski, & Macredie, 2000; Jonassen & Grabowski, 1993). For example, studies that match instructional strategies or content presentation with student learning preferences show that students perform better in matching situations in which instructional treatment is designed to meet individual characteristics (Bajraktarevic, Hall, & Fullick, 2003; Ford & Chen, 2000, 2001; Graff, 2003) Although CSL has many features that support meeting individual student learning goals and preferences, in reality, online courses rarely tailor content or the environment to address individual differences. As this study revealed, individual differences were most frequently accommodated by providing instructional material in a variety of formats. Students are expected to benefit from being able to select and utilize the materials that best match their own individual preferences. In other words, the system, although not personalized, is designed to compensate for individual differences by providing multiple options. Most Web-based learning environments usually provide optimal content presentation, instructional strategies, assessment methods, and interface. The designers/developers expect learners to acclimate and benefit from the provided learning environment (Chen et al., 2000). However, these learning environments are usually limited in that they do not provide immediate teacher support and feedback. Indeed, if the user is inexperienced or not comfortable with the learning environment, many instructional advantages can be lost (Oliver & Herrington, 1995). Several adaptive methods (i.e., adaptive interface, content, and navigation) have been used to address these concerns (Brusilovsky, 2001). Unfortunately these methods only address adaptations of the Web-based context, rather than instructional aspects (Carro, 2002). Adaptive methods should go beyond this limitation to take in support, feedback, interaction, assessment, collaboration, and social context, which are included in adaptive Web-based learning environments (A-

WBLE) (Inan & Grant, 2004). A-WBLE does this by incorporating different instructional strategies, resources, and learning settings that account for individual differences in the online environment (Inan & Grant, 2004).

CONCLUSION We examined CSL design models and guidelines according to the level of support or emphasis regarding identified elements and dimensions of effective teaching and learning within an online environment. The key elements encompass learning activities, learning environment, and/or assessment of student learning. The purpose of this analysis was not to report on the “quality” of CSL models and guidelines, but rather to present the results of a comprehensive analytical review of published models and guidelines. In the effort to provide the most comprehensive model review possible, and in accordance with the parameters of the developed analysis schema, some articles that have significant merit in the field were excluded, not based on the quality of the model that was presented, but due to the absence of the particular characteristics that were being studied. Ultimately, our purpose was to identify components that experts considered as critical to achieving effective CSL environments to enable developers and practitioners to use this information as a framework when designing, developing, and implementing CSL. The key findings are summarized: •

•

There is a prominence of group-based approaches that emphasize social learning that engages students in collaborative work, which often is problem-based and involves the joint creation of products with considering peer feedback as the assessment source. Self-learning activities are more prevalent than those that use a didactic, instructorcontrolled dissemination of content.

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A Comparative Analysis of Computer-Supported Learning Models and Guidelines

•

•

•

•

• •

There was a positive trend in CSL environments that is supportive of constructivist learning, which is reflected in the types of suggested learning activities, for example, engaging students in discussions, collaborative learning, and problem-based activities. The most common method of addressing the individual differences and needs of learners was to provide instructional material in a variety of formats, for example, video, PowerPoint lecture notes. There were no considerable differences between the emphasis on knowledge or performance-based assessments; however, the most common source of assessment was the instructor and/or peers. Explicit student support and scaffolding did not receive substantial attention, which is surprising considering the lack of faceto-face interactions found in traditional settings. Most models were designed and tested for college or higher education. In spite of prevalent constructivist perspective applications, behaviorist and cognitivist strategies were not diminished from researchers’ attention.

Overall, the proposed direction of CSL courses is promising as the prominent models and guidelines suggest a break from traditional approaches of using online environments as a means of distributing text-based information to be learned in an independent, self-paced manner. The new approaches utilize the inherent features of today’s Web-enhanced environments to create learning communities that may result in even higher levels of learning than traditional settings.

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Palloff, R. M., & Pratt, K. (2003). The virtual student: A profile and guide to working with online learners. San Francisco: John Wiley & Sons. Picciano, A. G. (2001). Distance learning: Making connections across virtual space and time. Upper Saddle River, NJ: Prentice-Hall. Schnitz, J. E., & Azbell, J. W. (2004). Instructional design factors and requirements for online courses and modules. In C. Cavanaugh (Ed.), Development and management of virtual schools: Issues and trend (pp. 158-177). Hershey, PA: Idea Group Publishing. Schrum, L., & Benson, A. (2002). Establishing successful online distance learning environment: Distinguishing factors that contribute to online courses and programs. In R. Discenza, C. Howard, & K. Schenk (Eds.), The design and management of effective distance learning programs (pp. 190204). Hershey, PA: Idea Group Publishing. Schunk, D. H. (2004). Learning theories: An educational perspective. Upper Saddle River, NJ: Pearson Education.

Setzer, J. C., & Lewis, L. (2005). Distance education courses for public elementary and secondary school students: 2002-03 (No. NCES 2005-010). Washington, DC: National Center for Education Statistics. Shearer, R. (2003). Instructional design in distance education: An overview. In M. G. Moore & W. G. Anderson (Eds.), Handbook of distance education (pp. 275-286). Mahwah, NJ: Lawrence Erlbaum Associates. Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. (2003). Teaching and learning at a distance: Foundations of distance education. Upper Saddle River, NJ: Pearson Education. Trentin, G. (2001). Designing online education courses. Computers in the Schools, 17(3/4), 4766. Woolfolk, A. E. (1995). Educational psychology. Needham Heights, MA: Allyn & Bacon. Zheng, L., & Smaldino, S. (2003). Key instructional design elements for distance education. Quarterly Review of Distance Education, 4(2), 153-166.

This work was previously published in Advances in Computer-Supported Learning, edited by F. Neto, pp. 1-20, copyright 2007 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.10

Evaluating Learning Management Systems

Leveraging Learned Experiences from Interactive Multimedia Katia Passerini New Jersey Institute of Technology, USA

ABSTRACT This chapter maintains that the use of multimedia content in Web-based instruction—facilitated by the proliferation and standardization of learning management systems (LMS)—calls for the extension of traditional multimedia design and evaluation guidelines to the Web. The compliance with these guidelines needs to be thoroughly evaluated by any institution using (or planning to use) Web-based learning management systems. In addition to providing criteria and examples for the evaluation of these systems, the chapter includes a survey instrument that can be used for university-wide assessments of the design effectiveness of technologies that support learning. As an example, the proposed evaluation instrument is applied to a learning management system developed at a large university in the United States. While the assessment refers to one system, the

model, the instructional and design evaluation criteria, and the questionnaire are built for use in any organization conducting a formative and summative evaluation or a selection of learning technologies.

INTRODUCTION: LEARNING MANAGEMENT SYSTEMS Learning Management Systems (LMS) are Webbased applications that support online teaching or supplement face-to-face instruction. Typical functionalities of LMS include Web course design, Web course collaboration tools, and Web course management (Hall & Hall, 2004; Hills, 2003c). The course design features provide templates for course organization. Instructors control the content and have some impact on the screen lay-

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Evaluating Learning Management Systems

out (changing features such as color and screen placement). Students can post information on personal Web pages or can create areas to post assignments and discussion topics. Search tools are available for quick access to materials. The collaboration tools include synchronous (chat) and asynchronous components (discussions areas similar to listservs). Faculty can use bulletin boards to post course-related announcements. Electronic messaging within the LMS provides a repository for course-related messages. Whiteboards are used especially with mathematical and visual information. File sharing and workgroups are particularly useful for team-based activities enabling simultaneous file editing by several users. The course management features enable student grading, performance tracking throughout the course, and the calculation of time spent using the software applications. They also enable instructors to design online quizzes, randomize questions from a database, and assess response time. In addition to the above, a number of administrative features provide security and technical support for faculty and students. Table 1 lists

typical LMS areas contained in many commercial and open-source applications such as WebCT, Blackboard, and Lotus LMS.

EVALUATING LEARNING MANAGEMENT SYSTEMS Stoner (1996) defines a learning technology as any application of technology for the enhancement of teaching, learning and assessment. This definition includes the use of network communication systems and embraces a large number of multimedia and Web applications. Learning management systems that enable classroom instruction on the Web and/or support face-to-face instruction with access to online learning repositories of course materials fall within this definition of “learning technology.” When integrating a learning technology into a traditional curriculum, a thorough evaluation of its key design and instructional characteristics is a critical element and a pre-requisite for its successful implementation (Bersin, 2005; Hills, 2003b). Stoner proposes a system design approach to the integration of learning technologies into

Table 1. LMS features

Course Design Features Instructor-centered sample course Course templates Search tools Student home pages Course Mgt. Features Student grading Student tracking Assessment tools Timed quizzes

Collaboration Tools Discussion options Asynchronous/threaded Synchronous (chat) Chat sessions logs Bulletin board E-mail File sharing Whiteboard Workgroups Administrative features Security Tech support

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Evaluating Learning Management Systems

traditional courses (or sections thereof). This approach draws on methodologies widely used in the design and implementation of computerizedinformation systems (Lucas, 1994; O’Brien, 2005) and in systems approaches to instructional design (Gagné, Briggs, & Wagner, 1988). Stoner’s model suggests a careful data collection on course type, students, and resources available. He encourages the research of alternative solutions: “These will need to be formulated in some detail, identifying the learning technology [courseware] to be used and how it might be used and integrated within the course(s) being considered.” This chapter presents a framework for the assessment of LMS leveraging the system design approach suggested by Stoner. Particularly, it relies on lessons learned in the design of interactive multimedia. It applies the design evaluation criteria on a specific LMS developed at the George Washington University, the Prometheus system, to introduce a specific example of the evaluation protocol here presented.

Types of Evaluations There are several approaches to conducting evaluations (Johnson & Ruppert, 2002; Hills, 2003b). Ideally, several types of evaluations should be implemented. In reality, financial, temporal, and human resource constraints limit the options (often in favor of “late” summative evaluations). Four main approaches to evaluating learning technologies are seen in Table 2.

Formative Evaluation Formative evaluation is testing conducted on selected samples of the user population while the product is still being developed (prototypes). Formative evaluation use open-ended methods, survey questionnaires, or confidence logs (users’ self-assessment of their knowledge). The key constraint of this method of evaluation is its timing. Authors describing the planning efforts of formative evaluations note that it is difficult to plan and implement testing early enough so that changes can be made (Alessi & Trollip, 1991). Often, resource constraints do not enable the administration of formative evaluations.

Summative Evaluation Summative evaluation is a process that concerns the final evaluation. This evaluation usually focuses on the user (rather than the application) because it is conducted after the product release. It is used to inform decision on future developments, as a product review, and as a user-satisfaction data collection instrument. Traditional surveys or assessment tests can be used, as well as observations, interviews, and other qualitative and quantitative data.

Illuminative Evaluation The aim of illuminative evaluations is to discover what factors and issues are important to the par-

Table 2. Types of evaluations Evaluation Type Formative Summative Illuminative Integrative

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Purpose To help improve the design (conducted during development) To assess the product and its functionality (conducted after release) To uncover important factors latent in applications To help users extract all the benefits of a learning technology

Evaluating Learning Management Systems

ticipants in a particular learning situation, which may differ with the developer’s judgment. Draper, Henderson, Brown, and McAteer (1996) state that “illuminative evaluation has a systematic focus on discovering the unexpected, using approaches inspired by anthropology rather than psychology,” and that these approaches have a significant effect on the users.

Integrative Evaluation Integrative evaluation is “aimed at improving teaching and learning by better integration of the learning technology into the overall situation. It is not primarily either formative or summative of the software, as what is both measured and modified is most often not the software but surrounding materials and activities. It is not merely reporting on measurements as summative evaluation is, because it typically leads to immediate action in the form of changes” (Draper et al., 1996). For example, if all the students in a classroom complain about the use of the technology for a particular learning outcome, the instructor and the developers need to reevaluate the tool and its current application. “Is the feature able to achieve its intended purpose?” If it is not, the developers should promptly modify the system, based on user feedback. This chapter focuses only on the first two types of evaluation: the formative and summative models. The scope of the discussion is limited to two models in consideration of space limitations and to present examples of LMS evaluation models actually run at a large university. It describes the content and assessment procedures for applying these evaluations to learning management systems. The chapter draws from the interactive multimedia literature to identify frameworks and criteria for LMS assessments.

CRITERIA TO EVALUATE LEARNING MANAGEMENT SYSTEMS: BORROwING FROM INTERACTIVE MULTIMEDIA Interactive multimedia instruction is traditionally grounded in several years of experience with interface design, human-computer interaction and computer-supported mediated learning. In the mid-and late nineties, instructional multimedia was partially replaced by LMS systems (Taylor, 2003). New applications competed in emerging as tools to facilitate transfer of in-class materials to the World Wide Web. Initially, these systems failed to leverage the design lessons from interactive multimedia because of the then clear hiatus between the Web and multimedia systems. Today, pervasive broadband access has brought about the possibility of delivering multimedia content in a Web space with a relatively low bandwidth impact. Finally, several multimedia applications have started to be transferred online (Watson & Hardaker, 2005) through Macromedia Flash and Java programs, lowering the gap between interactive multimedia systems and LMS. The distinction between interactive multimedia and the Web is becoming “blurry” (Hedberg, Brown, & Arrighi, 1997). If interactive multimedia was perceived to be bound to the shell of a physical container (the cd-rom), today’s online delivery capabilities enable hyper-linking and navigation as in a Web-based system. And where interactive multimedia systems are still constrained by the boundaries of a self-contained application, also LMS suffer from the same limits. As in interactive multimedia products, LMS rely on a self-contained (online) shell within which both instructors and students (and only the instructor and registered students) coherently navigate to organize and retrieve documents (within the available templates) (Hall & Hall, 2004). In this context, the areas of coincidence among interactive multimedia

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design and Web-design guidelines increase. As the coincidence grows, lessons learned and validated interactive multimedia frameworks can be leveraged to evaluate the effectiveness of an LMS (before its curriculum integration) (Coates, James, & Baldwin, 2005). As discussed next, an examination of multimedia and Web development principles furthers these statements eliciting a close mapping of interactive multimedia design guidelines with Web-based instructional systems design guidelines. It extends multimedia design principles (for example, Reeves, 1993) to LMS models. Designing multimedia for instruction requires major attention to two main factors: coherence and cognitive load (Yi & Davis 2003). Coherence of screen design is a key element of comprehension as it facilitates the construction of the mental models for the learner. The higher the coherence, the easier it is for the learner to comprehend. •

•

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Coherence needs to be reached at a small scale, linking pieces of information together for local coherence, and on a large scale, reminding the user about the relationships between the current screen and the learning domain. Cognitive load is defined as any effort in addition to reading that affects comprehension (i.e. navigation efforts or adjustment to the user interface). The higher the cognitive load the more difficult it is for the learner to comprehend. Strategies for reducing the cognitive load include creating a good balance on “distance”, “focus”, and “proportion” (Szabo & Kanuka, 1999). For example, key elements on the screen can be placed or given a different layout or shape based on importance. Cognitive load is also reduced by using clear navigational strategies. For example, hyperlinks/buttons need to be user-friendly and easily understandable also by a novice user.

Multimedia applications follow screen design, navigation and interactivity design guidelines that are informed by cognitive load and coherence principles: •

•

•

•

•

•

Ease of use. The perceived ease/difficulty of user interaction with a multimedia program: the more intuitive the application user interface, the less impact on the user cognitive load. Screen design. Screen design in multimedia relates to the coordination of text and graphics to present a sequenced content. This content facilitates understanding (Mukherjee & Edmonds, 1993) with each screen providing effective instruction, appropriate navigation tools and pleasing design/visual aesthetics (Milheim & Lavix, 1992). Each screen must display a navigation toolbox at the bottom, title and instruction areas at the top of the screen, with the body area containing media clips in the center (Stemler, 1997). Information presentation. Visual clues and information on the screen cannot be cluttered: too many representational clues (icons) or too much declarative text in one screen creates confusion and overwhelms the user (Overbaugh, 1994). Level of interactivity. Interactivity is a key distinctive feature of interactive multimedia and should be provided frequently, at least every three or four screens (Orr, Golas, & Yao, 1994). Navigation. Navigation should occur through simple interfaces, using facilitating metaphors and familiar concepts (Gurak, 1992). The icons should clearly show whether they are hyperlinks to other screens (by color, form, or mouse-over effects). Quality of media/media integration. Individual media (text, sound, video, and animation) within a multimedia application need to be synchronized based on content, space, and time of the animation.

Evaluating Learning Management Systems

•

Mapping.Thuring et al. (1995) suggest several hyperlinking guidelines. They include the clear identification of hyperlinks, the visualization of the document structure, the inclusion of navigational tools, and so forth.

Web design guidelines are closely related to design principles identified in interactive multimedia. In the following list, design principles identified by Jones, Farquhar, and Surry (1995) are mapped to interactive multimedia guidelines. For example, well-designed Web-based application systems need to: 1.

2.

3.

4.

Provide structural clues: Coherence in interactive multimedia. Information needs to be presented in a consistent manner with clear identification of the structure (Elges, 2003). Strategies include providing overview areas, maps, fixed display formats, and consistent placement of section titles. Clearly identify selectable areas: Navigation in interactive multimedia.Clarity is accomplished by following standard Web conventions (i.e. underline and blue for active hyperlinks) or using icons that clearly indicate alternate navigation paths. A subprinciple to this guideline is to clearly indicate selections made, so that the users have a contextual understanding on where they have been and their current location. Indicate progress made: Interactivity in interactive multimedia.This is an option particularly important when users are navigating through instructional material or taking an online assessment. Feedback on the status of the lecture or progression on the quiz eases navigation and favors cognition. Provide multiple versions of instructional material: Information Presentation. This includes offering a text-only option, a text and graphics option, an audio narrated

presentation, a video, or a variety of media accessible through high speed networks (Fleming, 1997). This is particularly important in order to guarantee broader accessibility (Johnson & Ruppert, 2002). 5. Offer contextual help: Ease of use.Contextual help facilitates navigation and ease of use (Tarafdar & Zhang, 2005). For example, if users experience difficulties in retrieving materials, specific browser options and configuration eases progress. 6. Keep pages short: Screen design.Scrolling may not be enjoyed by users (del Galdo & Nielsen, 1996). Information should be presented on sequential pages, providing the option to print the complete document through a single packaged file, conveniently placed in the first instructional screen. 7. Link to other pages, not to other points in the same page: Mapping.Long documents and text should be broken down in sequential pages. The users will have the ability to “jump” to other sessions or go back to the same paragraph by simply using back buttons and “breadcrumbs.” 8. Select links carefully: Cognitive load.Too many links in the same page may overwhelm the student and disorient (del Galdo & Nielsen, 1996). Links should be placed only at the bottom of the page or at the end of the text that they refer to. Links conveniently placed within the paragraphs offer contextual information and clarification for the learners. 9. Label links appropriately: Navigation.Some textual links or icons may not clearly indicate the destination area. Particular attention needs to be paid to content synchronization. 10. Keep important information at the top of the page: Screen Design.As dynamic text, such as “flying” or moving effects, lower attention and focus (Yi & Davis, 2003), and are not supportive of learning, important

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information should be static and placed at the top of the page. 11. Links and information must be kept updated: Information Presentation & Mapping. Both content and links to other material need to be tested on a periodical basis to check the availability of the link (“active” links). 12. Limit overly long download times: Interactivity. As “traditional human factor guidelines indicate 10 seconds as the maximum response time before users lose interest” care should be used to decrease file size and download times (del Galdo & Nielsen, 1996; Tarafdar & Zhang, 2005). In summary, the principles above map and extend guidelines applicable to interactive multimedia. These principles can provide guidance on how LMS supports learning by decreasing the cognitive load and increasing coherence. The next section presents an example on how these guidelines can be applied to uncover limitations with existing systems and systems under-development.

EXAMPLES OF EVALUATION: PROMETHEUS FORMATIVE EVALUATION Having reviewed design principles and instructional objectives set forth in the literature, this section of the chapter applies these principles to the evaluation of an online courseware application, Prometheus (Johnson & Ruppert, 2002). Prometheus was developed at the George Washington University starting in 1997. The Prometheus LMS evolved during its development through a series of formative evaluations (similar to the model presented in this section) and summative evaluations (described in the next section). The assessment process benefited the design of the system. It was conducted by a team of instructional designers at the Center for

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Instructional Design and Development of the university, including the author. The formative evaluations informed the development team of improvement needs. An example of the design guidelines is discussed below. The evaluation is conducted on a 5-point level (using Harvey balls to represent Very Low to Very High levels) and is summarized in Table 3. Prometheus’ main menu (navigation toolbox) identifies the structure of the course and the key course content. The main menu display is fixed, and coherently placed on each screen (see Figure 1). Hyperlinks within pages are labeled with text descriptions and standard colors for visited/ unvisited links are used. Additional hyperlinks that enable editing and interactivity are clearly identified by consistent yellow boxes placed at the top of each frame (see Figure 1). Prometheus does not provide feedback on the progress made in the completion of the coursework. In the communication section of Prometheus, the discussion area, the provision of feedback on the navigation of the threaded/unthreaded messages is lacking. The user does not know how many messages are left to read when navigating sequentially through each discussion response. Figure 2 shows the navigation screen in the discussion area. Help on the contextual position of the user is missing (How many messages have been read? How many yet to read?). Prometheus enables the integration of video and audio to any type of text and/or PowerPoint presentation. Faculty can deliver their lectures using a variety of media. A re-sizeable pop-up window with a multimedia presentation is available to students (see Figure 3). This window enables learner control (play, pause, and stop buttons) and self-paced learning. Although Prometheus is a particularly user friendly interface, for example, no formal directions and Frequently Asked Questions (FAQ) responses to configure users’ browsers are available. Contextual support with instructions on download

Evaluating Learning Management Systems

Table 3. Summary LMS evaluation web Design Guideline

Interactive Multimedia Equivalent

Coherence

1. Provide structural clues 2. Clearly identify selectable areas

Navigation

3. Indicate progress made

Interactivity

4. Provide multiple version of instructional material

Information presentation

5. Offering contextual help

Ease of use

6. Keep pages short

Screen design

7. Link to other pages, not to other points in the same page

Mapping

8. Select links carefully

Cognitive load

9. Label links appropriately

Navigation

10. Keep important information at the top of the page

Screen design

11. Links and information must be kept updated

Information presentation

12. Limit overly long download times

Interactivity

Legend:

Very Low

Prometheus

Low

could be easily integrated into Prometheus, rather than being handled individually and redundantly by each instructor. The length of the pages in Prometheus vary depending on the amount of information each instructor uploads into the system. Prometheus pages may remain short, become very lengthy, depending on the instructor’s preference for typ-

Medium

High

Very High

ing a lecture in Prometheus or simply uploading a document file that the students can download. Prometheus does not enable hyperlinking within the same page (thus burdening the cognitive load). A new window will open if a file is being downloaded or a hyperlink has been selected. Prometheus enables hyperlinking in specific and coherent areas. Although users can always

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Figure 1. Navigation and information presentation areas

Figure 2. Feedback on navigation

Figure 3. Multiple formats integration

Figure 4. Hyperlinks in selected areas

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create links in any area by using HTML commands, Prometheus fill-in forms enable posting of URLs and other class materials only in selected areas (see “required reading for session x” or “files associated with session x” in Figure 4). Links in Prometheus use text that is explanatory of the function that the selected area will accomplish. Contextual help that provides an overview of features is also available on selected screens. Labels are accurate. Faculty has little control of the placement of information in Prometheus. Most of the placement in the interactive areas (files, projects, and discussion) is based on time of the posting and cannot be rearranged in different order. The forms in Prometheus can be used or left blank. If they are left blank, they do not appear on the screen. If filled, the order cannot be rearranged by the instructor by level of importance for the specific subject matter. This criterion applies only to the information that is pertinent to the functioning of the system (and not the material posted by the instructor). A control mechanism to verify the “active” links and restores back-up files is a needed improvement. Although downloading time will vary depending on type of connection, modem speed and location (U.S. or abroad), the communication areas of Prometheus (i.e., discussion) suffer from long wait times to navigate through messages. Improvements in iterative releases of the software have decreased this problem, although it still remains substantial for users outside the campus. Areas for improvement: the evaluation shows that Prometheus could be improved in: •

•

Interactivity features: Re-designing the discussion areas to provide contextual feedback and better navigation. Technical support: Offering users printable manuals and additional help on how to address the technical problems associated with browser configurations.

•

Screen customization (alias “spatial” and “temporal” synchronization): Allow faculty and content developers to manipulate the layout and place the information that they consider most relevant in the top portions of the screen. A layout that constructs hierarchies of information based on the time of the posting is cumbersome. Allowing users to manipulate placement and order of uploaded information helps in the accomplishment of the learning objectives and guarantees that important information is not overlooked.

The implementation of the above recommendations, and iterative designs conducted from 1997 to 2003, enabled Prometheus to compete with commercial courseware applications and expanded its reach beyond the George Washington University community, for which it was originally intended. In 2003, Blackboard purchased the Prometheus system to integrate some of its developed features in their product offerings. A key factor in the decision to purchase the product was its high response to the needs of the teaching and learning community. This community was better served by using the results of the formative and summative evaluations described here. An evaluation guide for the assessment of LMS systems and their integration within a curriculum is included in the remainder of this chapter to encourage an informed review of commercial applications. Suggestions for criteria and survey administration options are also included.

SUMMATIVE EVALUATION: ADMINISTRATION AND CRITERIA While the formative evaluation was used as part of a process to improve the software during the development, it represented only a selected group of power users. Broader summative evaluations of the user population (faculty and students) en-

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able corrective and developmental maintenance to comply with user expectations. The evaluation instrument presented is developed on the basis of the interactive multimedia design principles earlier described. Each question in the scale (item development) is based on a set of related criteria for the evaluation of interactive multimedia products (Reeves, 1993). All the items in the scale are related to specific related domains. The survey measures attitudes and opinions on a self-reported 5-point Likert scale. Criteria for evaluation are based on the perception of interface design and the perception of usefulness of the application by users (students and faculty).

Administration The survey questions (see Appendix) should be administered to two groups of users (faculty and students). Timing of the survey administration is an important factor—it should take place preferably at the end of an academic semester. In order to enable the evaluation of features that were used in the classroom, respondents should be enabled to access only questions relative to the features they used. Participation in the survey questionnaire may vary. Different strategies could be used to encourage all system users to complete the online survey. For example, incentives could be offered, such as a drawing of free computer software could be conducted for all student respondents. Similarly, faculty participation could be encouraged. Alternatively, participation in the survey could be required of all users (as long as anonymity is guaranteed). For example, users may not be able to access any of the features before they complete the online questionnaire. To avoid user frustration or disruption of user’s work schedule, users could be warned that they will be able to access only 10 additional working sessions, before the system will prompt them to complete the survey in order to be able to proceed. They may choose to take the survey earlier, but they should be informed and

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given enough time to complete important tasks, before the system locks them out. Both approaches have pros and cons. A survey that is completely voluntary may not get enough responses, or may suffer from a response bias. A compulsory survey may frustrate some users, but will engage the entire user population.

Summative Evaluation Criteria Reeves’ evaluation criteria (1993) focus on the user interface of interactive instructional products, such as multimedia programs. As mentioned earlier, these criteria extend to LMS. If the user interface is not well designed, users will have little opportunity to learn from the program. Examples of a student survey instrument are included in the Appendix and key criteria used to define the survey questions (based on Reeves, 1993) are presented in this section. Continuing on the description of the earlier example, the sample questions are referred to a specific LMS system (Prometheus).

Ease of Use “Ease of Use” is concerned with the perceived ease of a user interaction with the program. Figure 5 illustrates Reeves’ dimension as ranging from the perception that the program is very difficult to use to one that is perceived as being very easy to use.

Navigation “Navigation” is concerned with the perceived ability to move through the contents of an interactive program in an intentional manner. Figure 6 illustrates Reeves’ dimension of interactive multimedia ranging from the perception that a program is difficult to navigate to one that is perceived as being easy to navigate. Possible options for navigation include evaluating the clarity of navigation icons.

Evaluating Learning Management Systems

Figure 5. “Ease of Use” Ease of Use Easy

Difficult

Example on a 5-point Likert scale: I was able to learn Prometheus on my own …………………………….

Prometheus menus are intuitive…………………………….

Strongly Agree

Agree





Strongly Agree

Agree





Neither Agree Nor Disagree

 Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Figure 6. “Navigation” Navigation Easy

Difficult

Example on a 5-point Likert scale: The navigation options in Prometheus are clear in each section……………………………

Strongly Agree

Agree





Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable









Figure 7. “Cognitive Load” Cognitive Load Unmanageable

Manageable

Example on a 5-point Likert scale: I do not need to remember several commands to use Prometheus………….…………

Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







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Evaluating Learning Management Systems

Cognitive Load The cognitive load is defined as any effort in addition to reading affects comprehension (i.e., navigation efforts or adjustment to the user interface). The higher the cognitive load the more difficult it is for the learner to comprehend. In terms of “cognitive load”, Reeves states that the user interfaces can seem unmanageable (i.e., confusing) or easily manageable (see Figure 7).

Mapping “Mapping” refers to the program’s ability to track and graphically represent to the user the navigation path through the program. This is a critical variable because users frequently complain of being lost in an interactive program. Evaluations of interactive programs vary from containing no mapping function to an appropriately powerful mapping function (see Figure 8).

Screen Design Screen design is a dimension of interactive programs that evaluates elements such as text (font layout and type), icons, graphics (placement), color (balance), and other visual aspects of interactive programs. “Screen design” ranges from substantial violations of the principles of screen design to general adherence of these principles (see Figure 9).

Knowledge Space Compatibility— [Content] Refers to the compatibility of the product content with the layout of the learning space in the software application. When a novice user initiates a search for information in an interactive program, s/he could perceive the resulting information as compatible with his/her current knowledge space (see Figure 10). If the search results are not compatible, the application is weak in integrat-

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ing content and technical features. This criterion is mostly applicable in interactive multimedia, where the content placement is static. In LMS systems, it can be used as “content” evaluation instruments.

Information Presentation A dimension concerned with whether the information contained in an interactive program is presented in an understandable form. A well-designed user interface is ineffective if the information it is intended to present is incomprehensible to the user. (see Figure 11).

Media Integration Deals with the question on whether the various media (text, graphics, audio, video) work together to form one cohesive program. The media integration dimension is defined as ranging from uncoordinated to coordinated (see Figure 12). This criterion is not applicable in the context of LMS because the integration of media and their quality will be dependent primarily on the quality of the application that the individual content developers (faculty) will upload in the courseware. This criterion can be substituted with questions relative to “class interaction” and collaboration tools, key components of LMS tools that support interaction in multiple ways (audio, voice, and text interaction).

Aesthetics “Aesthetics” deals with a subjective evaluation of the user of the screen layout ranging from displeasing to pleasing (see Figure 13).

Overall Functionality “Overall Functionality” is related to the perceived utility of the program to achieve what its intended purposes are. It will include an evaluation of the

Evaluating Learning Management Systems

Figure 8. “Mapping” Mapping None

Powerful

Example on a 5-point Likert scale: Prometheus navigation layout is consistent………………….….

Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Strongly

Not Applicable

Figure 9. “Screen Design” Screen Design Violates

Follows

Example on a 5-point Likert scale: The text layout on the screen makes it easy to read………..

Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree



Disagree





Figure 10. “Knowledge Space Compatibility” Knowledge Space Compatibility Compatible

Incompatible

Example on a 5-point Likert scale: I can understand the meaning of all the instructions on any Prometheus page……………..

Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







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Evaluating Learning Management Systems

Figure 11. “Information Presentation” Information Presentation Clear

Obtuse

Example on a 5-point Likert scale: Prometheus enables me to access class material in an organized way………………...

Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Figure 12. “Media Integration” Media Integration Coordinated

Uncoordinated

Example on a 5-point Likert scale: Prometheus enables me to easily interact with my instructor………………………

Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Figure 13. "Aesthetics" Aesthetics Displeasing Displeasing

Pleasing Pleasing

Example on a 5-point Likert scale: Prometheus screen design is pleasing………………………….

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Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Evaluating Learning Management Systems

Figure 14. “Overall Functionality” Overall Functionality Highly HighlyFunctional Functional

Dysfunctional Dysfunctional

Example on a 5-point Likert scale: The technical quality of Prometheus is satisfactory..….

Strongly Agree

Agree





factors that affect the perceived quality of the application. Figure 14 illustrates a dimension of the user interface of interactive programs that ranges from dysfunctional to highly functional.

Additional Criteria Since Prometheus contains a series of features (course design tools and collaboration tools) that enable different types of class interaction, evaluation of the usefulness of the individual feature (as perceived by the user) is an important component of a complete summative evaluation. Questions evaluating user’s perception of usefulness of the system will vary depending on whether the user is a student or a faculty member. The questions will cover each of the features available to the users, but will be accessed by the user only if s/he reported being familiar with or having used the feature at the beginning of the survey (see in Appendix), Syllabus, Outline, Projects, Lectures, Files, Email, Discussion, Chat, Utilities questions). The deployment of the survey to a large population of LMS users can provide a better understanding of how LMS supports learning.

Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







CONCLUSION This chapter presents a framework for the evaluation of LMS based on the criteria set forth by the literature on interactive multimedia. It claims that the convergence between multimedia and Web-based learning environments enables the extension of design guidelines to LMS. As in interactive instructional multimedia systems, an effective LMS strives for coherence and focuses on the reduction of the learner’s cognitive load. LMS systems are currently consolidating, but variations and customizations still exist, especially in emerging open-source products representing lower cost solutions (Hall, 2005). Evaluating LMS systems remains a key prerequisite and a first step for evaluating Web-based instruction effectiveness (Hills, 2003a). To address this assessment need, an evaluation protocol for LMS was proposed in this chapter based on the integration of interactive multimedia and Webevaluation criteria. Different types of evaluation and evaluation criteria were presented. Sample questions for each evaluation and strategies for the survey administration were also briefly discussed. These questions may constitute a useful reference tool for LMS evaluations. The survey questionnaire presented in the Appendix could

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be reviewed, changed, and integrated beyond the issues discussed in this chapter. In any event, it could serve as a starting point for a serious effort to evaluate instructional software that has not yet been assessed by the majority of its users before, during, or after its integration in the curriculum. As Stoner (1996) and other authors (Carmean & Haefner, 2002) point out, evaluation is a key element of any proper curriculum implementation.

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Szabo, M., & Kanuka, H. (1999). Effects of violating screen design principles of balance, unity, and focus on recall learning, study time, and completion rates. Journal of Educational Multimedia and Hypermedia, 8(1), 23-42. Tarafdar, M., & Zhang, J. (2005). Analyzing the influence of Web site design parameters on Web site usability. Information Resources Management Journal, 18(4), 62-80. Thuring, M., J. Hannemann, & J. Haake (1995). Hypermedia and cognition: Designing for comprehension. Communications of the ACM 38(8), 57-66. Taylor, P. (2003, June 23). Market in fresh mood of realism: Learning management systems — Customers face difficult choices from a big range of systems. Financial Times. Watson, J., & Hardaker G. (2005). Steps towards personalized learner management system (LMS): SCORM implementation. Campus-Wide Information Systems, 22, 56-70. Yi, M., & Davis, F. (2003). Developing and validating an observational learning model of computer software training and skill acquisition. Information Systems Research, 14, 146.

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Evaluating Learning Management Systems

APPENDIX: SUMMATIVE EVALUATION QUESTIONNAIRE

Sample Student Survey

Please indicate how many courses you took on the LMS _______________(number) Please indicate which features of the LMS your courses used (check all that apply)  Syllabus  Projects  Lectures  Files  Email  Discussion  Chat Please evaluate the LMS based on your overall experience with this Web-based courseware and your experience with the individual features used. Remember that this is an evaluation of the LMS as a software application, and not an evaluation of how well your instructor used the LMS.

Thank you for your time!

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Evaluating Learning Management Systems

[Ease of Use] The LMS menus are intuitive…….……………………….

Strongly Agree

Agree





If I have any problem, The LMS help menu provides useful information…..

Strongly

Agree





I was able to learn The LMS features on my own…………………………..

Strongly Agree

Agree





Agree

Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable









Neither Agree Nor Disagree



Neither Agree Nor Disagree



If I needed help, I had plenty of opportunities to learn additional The LMS features through: - The LMS team support ………... - Support from my instructor ……

- Support from other students……..

Strongly Agree

Agree





Strongly Agree

Agree





Strongly Agree

Agree





Neither Agree Nor Disagree



Neither Agree Nor Disagree



Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







[Navigation] The navigation options in The LMS are clear in each section…………..

Strongly Agree

Agree





Strongly Agree

Agree



Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







[Cognitive Load ] I do not need to remember several commands to use The LMS…….….. Hyperlinks within The LMS clearly indicate what each section is designed for…………….…………

Neither Agree Nor Disagree

Disagree







Strongly Agree

Agree

Neither Agree Nor Disagree

Disagree







Strongly Disagree



Not Applicable





Strongly

Not Applicable

Disagree





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Evaluating Learning Management Systems

[Mapping] The sections in which The LMS is organized are appropriate for my needs……………………….

Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Which other sections would be useful to you? 1. ________________________________________________________________ 2. ________________________________________________________________ 3. ________________________________________________________________

[Screen Design] The text layout on the screen makes it easy to read….……..

Strongly Agree

Agree





Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







[Content] I can understand the meaning of all the instructions on any of the LMS page……………….

Neither Agree Nor Disagree



Which instructions are unclear? 1.________________________________________________________________ 2. ________________________________________________________________ 3. ________________________________________________________________

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Evaluating Learning Management Systems

[Information Presentation] The LMS enables me to access class material in an organized way……………….…………

Strongly Agree

Agree





Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Please, indicate which type of documents you accessed on The LMS (check all that applies).  Plain Text  Word documents  HTML files  Video files  Sound files  PowerPoint presentations  Portable document format (.PDF)  Steaming media files (narrated PPT, audio, video) The media (video, sound, graphics or text) used by my instructors on The LMS enabled me to better understand class information………

The LMS is a useful supplement in my courses….….………………...

Strongly Agree

Agree





Strongly Agree

Agree





Strongly Agree

Agree





Strongly Agree

Agree





Neither Agree Nor Disagree



Neither Agree Nor Disagree



Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







[Interactivity] The LMS enables me to easily interact with my instructor….…… The LMS enables me to easily interact with my classmates………..

Neither Agree Nor Disagree



Neither Agree Nor Disagree



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Evaluating Learning Management Systems

[Overall Technical Functionality] The technical quality of The LMS is satisfactory……………………. Using a modem, I find that The LMS runs at an acceptable speed …. Please indicate your Internet connection characteristics……….. Using a network connection, I find that the LMS runs at an acceptable speed…………………………….

Strongly Agree

Agree





Strongly Agree

Agree





Modem (56k)

Cable Modem





Strongly Agree

Agree





Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







DSL

Wireless Broadband

LAN/ Ethernet

Not Applicable









Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable









Neither Agree Nor Disagree





Which sections of The LMS gave you the most technical problems when accessing them? 1. ________________________________________________________________ 2. ________________________________________________________________ 3. ________________________________________________________________

Which type of problems did you have? 1. ________________________________________________________________ 2. ________________________________________________________________ 3. ________________________________________________________________

Have you used any other LMS?  Yes (please specify________________________________________________)  No If yes, how does it compare with The LMS?

 Better  The same  Not as good

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Evaluating Learning Management Systems

Section Specific Questions [note: Questions in this section should appear in an online survey only if respondent selected that he/she uses the specific The LMS feature] Syllabus The way the syllabus is organized is very useful

Strongly Agree

Agree





The project area enables me to access information coherently

Strongly Agree

Agree





I find the project area very useful

Strongly Agree

Agree





Strongly Agree

Agree





Strongly Agree

Agree





Strongly Agree

Agree





Strongly Agree

Agree





Strongly Agree

Agree





Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable









Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable









Projects/Assignments Neither Agree Nor Disagree



Neither Agree Nor Disagree



Lectures The lectures area enables me access class notes coherently I do not need extra explanations to access class materials in the lectures area

Neither Agree Nor Disagree



Neither Agree Nor Disagree



Files The files area enables me to effectively deliver a variety of files to my classmates The files area enables me to distribute files/information to my classmates coherently I can easily edit any information that I include in the files area



Neither Agree Nor Disagree



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Evaluating Learning Management Systems

E-Mail The broadcast e-mail function is very useful to communicate with my classmates The log of the e-mails sent to my colleagues and instructor is useful The group-e-mail feature enables me to effectively manage communication with classmates

Strongly Agree

Agree





Strongly Agree

Agree



Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable







Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable











Strongly Agree

Agree

Neither Agree Nor Disagree

Disagree

Strongly Disagree

Not Applicable











Strongly Agree

Agree

Disagree

Strongly Disagree

Not Applicable











Strongly Agree

Agree

Disagree

Strongly Disagree

Not Applicable











Strongly Agree

Agree

Disagree

Strongly Disagree

Not Applicable











Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable







Disagree

Strongly Disagree

Not Applicable











Discussion The discussions board effectively enable me to interact with my classmates The different discussions levels (threads) make the discussion easy to follow The speed associated with accessing each discussion reply is acceptable

Neither Agree Nor Disagree



Neither Agree Nor Disagree



Neither Agree Nor Disagree



Chat The chat area effectively enables me to communicate with my classmates The chat room enables me to obtain information coherently I do not run into any technical problem when participating in discussions in the chat room

Strongly Agree

Agree





Strongly Agree

Agree





Strongly Agree

Agree





Neither Agree Nor Disagree



Neither Agree Nor Disagree



Neither Agree Nor Disagree



This work was previously published in the International Journal of Web-Based Learning and Teaching Technologies, Volume 1, Issue 3, edited by L. Esnault, pp. 1-28, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 2.11

Online Education and Manufacturing Mode Roy Rada University of Maryland, Baltimore County, USA

INTRODUCTION Online educational programs are changing the university profession. Two of the prominent organizational forms in modern society are professional and manufacturing. Universities are one example of the professional form; automobile factories are one example of the manufacturing organization. Online education is facilitating the move of teaching at universities from the professional mode to the manufacturing mode. In the early days of online education, research was often about using particular tools to teach particular concepts. Attention is increasingly being drawn to organization-wide issues of online education (Rada, 2001). The Sloan Foundation in the United States (U.S.) moved from funding asynchronous learning experiments that demonstrate some new tool used in a few classrooms to requiring that funded projects demonstrate widespread organizational change. Collis and Ring (1999) emphasized that sociological factors are more important than technical factors in online education.

PROFESSIONAL VS. MACHINE MODE Organizational types include “professional organizations” and “manufacturing organizations” (Mintzberg, 1979): •

•

The professional organization relies on the standardization of skills for coordination. Training and indoctrination first instill those skills in the new professional, and interaction with colleagues through time maintains the standardization (Beshears, 2001). The organization hires duly trained and indoctrinated specialists, and then gives them considerable control over their work. Most coordination between operating professionals is handled by the standardization of skills and knowledge. The manufacturing organization generates its own standards. Its technical staff designs the work standards for its operators, and its line managers enforce them. The machine organization has highly specialized, routine

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Online Education and Manufacturing Mode

operating tasks; formalized procedures in the operating core; and a proliferation of rules, regulations and formalized communication throughout the organization. While the university is a professional organization, introducing online education creates occasions for specialization and mechanization that introduce manufacturing features to the university. Change in the professional organization does not come from new administrators taking office with major reforms. Instead, change arrives by the slow process of changing the professionals – changing who can enter the profession, what they learn in its professional schools (norms as well as knowledge) and, thereafter, how they upgrade their norms and knowledge. The professional administration lacks power relative to manufacturing administration and is decentralized. The administrators typically spend their time handling disruptions and negotiations. Nevertheless, administrative structures serve a key role in creating and modifying the boundaries of the organization. Often, through this boundary manipulation, the administration implements its will (Wetzel, 2001). The modern, American research university operates as a holding company for thousands of faculty entrepreneurs (Duderstadt, 1995). The faculty has teaching duties, but performance in these teaching duties is only modestly linked to salary. The community colleges’ model of operation comes closer to the manufacturing model (Bibby, 1983). At a research university, a professor may typically teach one course a semester, whereas at a community college the professor teaches 10 times that much (Adams, 1976). Places such as the Open University in England and National Radio Institute in the U.S. were created in the mid-20th century. These institutions helped students access university education, despite being somewhere distant from the teacher. They were not research universities, but

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focused on teaching in a systematic (manufacturing-type) way.

Case Study Pace University is a multi-campus private university based in New York City, with 15,000 students. It offers associate, bachelor’s, master’s, and professional degrees, but not PhDs—the focus is more on teaching than on research. Pace had negligible involvement in distance education prior to starting an online associate of arts degree in 1998 for employees of the telecommunications industry. The program developed very quickly under the adroit leadership of the person responsible for continuing education programs, not academic programs. The leader runs programs more in the community-college mode than in the research-university mode. All courses follow a strict pattern. Numerous specialists support various operations of the program; for example, different roles: •

• •

Administer quality control surveys on a regular basis, at times weekly, to students in a class Phone students whose survey responses suggest a problem Answer academic queries about the degree program for students

The teacher of the course is not necessarily the person who developed the course content, schedule, examinations or anything else about the structure or function of the course. Furthermore, the teacher no longer does the quality control or social support expected of a traditional teacher. The development of course content also is specialized: • •

The requirements for the courses have come from industry. The template for all courses is fixed in advance.

Online Education and Manufacturing Mode

•

Technical staff helps place content in courses.

Someone designs the course, but other people teach it. Those who deliver the course are obligated to follow the curriculum developed by the designer. A faculty member gets a few thousand dollars to design an online course, and the university owns the copyright on the course. The director has managed the rapid development of a full complement of online courses for an associate of arts degree and staffed the program for successful delivery. Further evidence of the non-traditional, manufacturing mode of the program is the schedule. Courses each last a traditional 15 weeks. However, rather than starting only in the traditional fall and spring semester, a new semester starts every other month so that students can start whenever they want. The schedule is designed to suit telecommunications workers, whose sense of timing is not tied into the academic fall and spring semester schedule. The program is a wonderful success in terms of rapid development and successful marketing and delivery. The average faculty member at Pace University did not desire all these changes. However, the administration has introduced the program by modifying the boundaries of Pace. First, the program was not officially offered by Pace but by a coalition called NACTEL, which is independent of Pace University. The tuition for employees of telecommunications firms is different than the tuition for other Pace University students, but this information is hidden from the public or university faculty. The tuition fees for employees of telecommunications companies is only learned after one demonstrates that one is an employee and makes a private communication with the NACTEL program.

Health Care Analogy What can be learned from another profession? The health care industry has a professional component. The evolution of the modern American health system can be depicted in three stages (Rada, 2003): • • •

1900-1940–science and technology introduced, 1940-1980–some manufacturing organization characteristics introduced, and 1980-present–quality control introduced.

The increasing role division in health care demonstrates the move from a professional organization to a manufacturing organization. Physicians constituted 30% of all health personnel in 1910 but 10% in 1990. Allied health technicians, technologists, aides and assistants constituted 1% in 1910 and more than half the health workforce in 1990 (Mick & Moscovice, 1993). The U.S. President’s Advisory Commission on “Consumer Protection and Quality in the Health Care Industry” (President, 1998) says information systems are critical to quality health care, but identifies clinician resistance as a key barrier to diffusion. Whoever is involved in new systems in health care has to nurture collective participation (Wetzel, 2001). Decisions cannot be made solely by a centralized administration. The low motivation among professionals to participate in collective efforts may aggravate the situation. System changes are often perceived not to be in the interest of the professional. In some cases, the system-wide benefits may reduce resources to certain departments that will then resist the implementation. The recognition of subtle power plays and existing alliances between various departments assumes a greater role in health care systems than in manufacturing organizations, where well-defined teams have strong authority over new systems implementations. What has

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Online Education and Manufacturing Mode

been said for the challenges of implementing new systems in health care applies equally to universities.

CONCLUSION As universities integrate online courses into online degrees, the challenges of organizational change grow. Administration can monitor activity and de-professionalize various educational tasks in an online degree to an extent not imagined with individual courses. The influential book “Dancing with the Devil: Information Technology and the New Competition in Higher Education” (Katz, 1998) talks about the formidable challenges facing campuses, and says that online education threatens to change the character of the university from a professional one to a manufacturing one. Yet, certain forces make online education likely to grow in importance rather than decrease. Given that some activities of the university, such as research, are intrinsically suited to a professional rather than a manufacturing organization, universities struggle with the sociological and administrative implications of online education.

REFERENCES Adams, W. (1976). Faculty load: improving college and university teaching, 24(4), 215-218. Beshears, F. (2001). Mintzberg’s classification of organizational forms. Retrieved February 7, 2004 from http://ist-socrates.berkeley.edu/~fmb/ articles Bibby, P. (1983). An academic accounting model for community colleges. Ph.D. University of Florida, Gainsville, Florida. Collis, B., & Ring, J. (1999). Scaling up: faculty change and the WWW. Interactive Learning Environments, 7(2/3), 87-92.

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Duderstadt, J. (1995). The modern university. Retrieved August 2004 from www.professionals. com/~chepc/ct_1095/ctov1_1095.html Katz, R. (1998). Dancing with the Devil: information technology and the new competition in higher education. San Francisco: Jossey-Bass. Mick, S., & Mosovice, I. (1993). Health care professionals. In. S. Williams and P. Torrens (Eds.), Introduction to health services (pp. 269-296). New York: Delmar Publishers. Mintzberg, H. (1979). The structuring of organizations. Reading: Prentice Hall. Pace University. (2001). Pace University/NACTEL program. Retrieved August 2004 from http://support.csis.pace.edu/nactel/program/ President’s Advisory Commission. (1998). Chapter 14, Investing in information systems. In Quality first: better health care for all Americans. Retrieved August 2004 from www.hcquality commission.gov/final/chap14.html Rada, R. (2001). Understanding virtual universities. Oxford: Intellect Books. Rada, R. (2003). Information systems for healthcare enterprises (2nd ed.). Baltimore: Hypermedia Solutions Limited. Wetzel, I. (2001). Information systems development with anticipation of change focusing on professional bureaucracies. In Proceedings of Hawaii International Conference on System Sciences, HICCS-34.

KEY TERMS Health Care Industry: The health care industry is the complex of entities engaged in delivering, financing or monitoring health care. Manufacturing Mode: In manufacturing mode, technocrats standardize procedures and outputs.

Online Education and Manufacturing Mode

Online: Online means accessible via computer. Professional Mode: In professional mode, professionals in the operating core (e.g., doctors, professors) rely on roles and skills learned from years of schooling and indoctrination to coordinate their work.

Research University: A research university is a university in which the primary objective is to produce research. Role: A Role is the actions and activities assigned to or required or expected of a person.

This work was previously published in the Encyclopedia of Distance Learning, Volume 3, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 1357-1360, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.12

Bridging the Gap with MAID: A Method for Adaptive Instructional Design Jacopo Armani Università della Svizzera italiana, Switzerland Luca Botturi Università della Svizzera italiana, Switzerland

ABSTRACT This chapter presents MAID, a complete design method for adaptive courseware tailored for non-technical people. Adaptive hypermedia systems represent a great potential for e-learning. Nevertheless, instructors and designers find it difficult to develop adaptive applications in real educational environments, mainly because no structured design method is available. The main principle upon which the method relies is that the basis for the exploitation of adaptive features in education is the definition and implementation of an instructional strategy. The MAID approach provides guidelines and tools that foster and enhance the communication between the technical staff in charge of managing the hypermedia

system and the instructor by adopting her/his instructional strategy as the pivotal point for the communication.

INTRODUCTION The creation of adaptive courseware started with expert systems and CAI (computer assisted instruction) and produced milestone applications as ISIS-TUTOR (Brusilovsky & Pesin, 1994) or SKILL (Neumann & Zirvas, 1998) and TANGOW (Carro, Pulido, & Rodríguez, 2001). These projects developed self-learning courses with adaptive tutoring, and traced a route by which, some years later, adaptive platforms could be developed, such as AHA! (De Bra & Calvi, 1998; De Bra,

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Bridging the Gap with MAID

Aerts, Smits, & Stash, 2002a) or KBS Hyperbook (Henze & Nejdl, 1999). Adaptive platforms are general-purpose systems that allow the production of courseware for any content. It can be surely stated that the last decades of research in the field of adaptive hypermedia systems (AHS) produced a wide leap forward in terms of technical solutions and systems. Nevertheless, “just a handful of these systems are used for teaching real courses, typically in a class lead by one of the authors of the adaptive system” (Brusilovsky, 2004, p. 1), and also few institutions or companies systematically exploit adaptive components in their e-learning programs. We claim that this gap between the maturity of technical developments and their use in the educational practice is also due to a lack of methodological support in the design of adaptive courseware, that is, of expertise in using adaptive components and systems in order to implement and enhance a course as conceived by a nontechnical instructor. The major concern of this chapter is MAID, a method for the design of adaptive educational application, suitable to a situation in which an instructional designer, familiar with some adaptive platform, is producing a course with an instructor or a subject matter expert (SME). A second concern of this chapter is a call to all AHS developers for defining not only tools, but also methods that may make the tools actually usable to educators. This chapter first presents an overview of the literature, with particular emphasis on the instructional strategies, claiming that the definition of a specific strategy is the basis for the sound development of adaptive applications. The MAID method is then presented in detail by a case study. The following section recaps the method, and provides generalization insights and guidelines for designers. Finally, the results of the work are discussed and some outlook is provided.

LITERATURE REVIEw About Instructional Strategies When an instructor or SME thinks of a course, s/he thinks about it in a unitary way, and conceives an instructional strategy, that is, a method for having the students achieve the course goals. The design of instructional events indeed, supported by any kind of technology, from WebCT to virtual reality, requires a strategy (Bates, 1999; Bates & Poole, 2003). Smith and Ragan (1999), building on the foundations by Reigeluth (1983), define a strategy as a plan for action including three main dimensions: 1. 2. 3.

Organization: The structure and clustering of content Delivery: The media involved in the delivery Management: The organization of the learning activity into a unitary schedule

To our concerns, the definition of organizational strategy is the most relevant. Smith and Ragan (1999) write that “organizational strategy characteristics refer to how instruction will be sequenced, what particular content will be presented, and how this content will be presented” (p. 113). In particular, they name a set of activities that should be considered as part of the definition of an organizational strategy, namely: 1. 2. 3. 4. 5.

Content selection Content clustering Content sequencing Definition of generative (active) or supplantive (passive) approach Definition of instructional events

When talking of instructional strategy, we will refer to this definition; a clear assessment of these issues paves the road for an integrated and

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Bridging the Gap with MAID

effective exploitation of adaptive hypermedia techniques into a course. A strategy could be synthetically expressed with a statement such as “this course is problemdriven and learners work in groups” or “this course follows constructivist principles and provides learners with resources they are free to use as they like, provided that they reach the negotiated goals”. The definition or selection of a strategy requires a complete instructional analysis (Dick & Carey, 1996) and should move from the definition of learning goals (Anderson & Krathwohl, 2001; Gagné, Briggs, & Wager, 1992). Educational literature has defined a number of different instructional strategies suitable for different learning goals and drawing from different learning theories, but this is not the place for a thorough discussion or for an exhaustive review. The point is that the definition of an instructional strategy is the basis for the development of an instructional event; more precisely, and this is more relevant for the current analysis, it is the basis for the definition of the role of technologies in the instructional event. This means that: 1. 2.

The decision to use a certain technology such as AHS should be derived from the instructional strategy. The decision about how to use technologies should also be strategy-driven.

The question “How can AHS be profitably exploited in real educational environment?” should be operatively translated into “How can AHS support the implementation of this instructional strategy?” MAID was conceived as a communication support for finding a sound answer in course design.

Design of AEHS: An Open Issue The AHS field has been for years a boiling pot throwing out newer and newer tools and techniques to support learners, and indirectly teachers

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as well. Yet, the issue is: now that we have plenty of tools, how shall we use them? In order to tackle the issue, some researchers (Aroyo, Dicheva, & Cristea, 2002) use task ontology to support instructors and content provider of adaptive educational hypermedia systems (AEHS) in their authoring effort. Their goal is creating an ontology of the most common tasks (adding/removing/editing) and objects (pages, hyperlinks, etc.) authors have to deal with while producing courseware. Based on such an ontology, they aim at the development of an intelligent authoring tool that can provide an intelligent support to the design of adaptive courseware. Other researchers (Brusilovsky, 2004) aim at design straightforward authoring tools for developing adaptive courseware starting from the analysis of the state of the art of the current learning management systems (LMS). Yet in order to use tools (or authoring tools) to build complex applications such as AEHS, we need a method. This change in the way of considering design issues was indirectly addressed by Brusilovsky (2003): his work is the first attempt to raise the issue of AEHS design. The paper presents a review of the design principles embedded in the most relevant AEHS, trying to distil a common design process. According to him, “the design of an adaptive hypermedia system involves three key sub-steps: structuring the knowledge, structuring the hyperspace, and connecting the knowledge space and the hyperspace” (p. 380). 1.

2.

Structuring the knowledge refers to representing the information we have about the domain, the student, and the educational goals in terms of the internal language of the system. Structuring the hyperspace deals with the issue of connecting the pool of pages with each other. The review shows clearly that several strategies (e.g., hierarchical, rhetorical, and object oriented structures) have been applied so far to achieve different goals.

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3.

Connecting the knowledge space and the hyperspace refers, in a few words, to the issue of mapping the knowledge level into the level of pages, content fragments, and links.

Brusilovsky concludes that the field of AHS “is probably too young to produce a good number of design authoring tools … that can be used by non-programming authors to develop an educational AHS … The reason for that is reasonably clear: Before producing a real authoring tool, a research group has to develop an explicit design approach that usually requires developing one or more educational AHS” (Ibidem, p. 342). As Brusilovsky suggests, the problem of the lack of authoring toolkits stems from the lack of design methods. On a parallel track, other researchers (Koch, 2001; Papasalouros & Retalis, 2002) are focusing on design models: high-level representations of how an AEHS should be. These approaches come from software engineering, but unfortunately, the results are usually UML-based schemas which require special training to read, and technical expertise to draw.

Instructional Design and Adaptive Systems Although many research prototypes of AEHSs refer to results from Instructional Design, for instance the emphasis on constructivist approaches (Henze & Nejdl, 1999), and on learning styles (Grigoriadou, Papanikolaou, Kornilakis, & Magoulas, 2001), very little space has been devoted to bridge the existing gap between the communities of instructional design (ID) and AEHS. A contribution in this direction comes from Park and Lee (2004). Their work presents the state of the art of the adaptive instructional systems, starting from the pre-technologic era (adapting classroom-based instruction), to Web-based

systems. They point out that, although the tradition of adaptive instruction precedes the AEHS, nevertheless, the two fields seem never to meet each other: “Unfortunately, this technical development has not contributed significantly to an intellectual breakthrough in the field of learning and instruction” (p. 677). Among the reasons for the limited success of AEHS, the authors see a lack of theoretical foundations.

The AHAM Meta-Model In order to create a framework model, we relied on the work done by De Bra_, Houben, and Wu (1999) with AHAM—adaptive hypermedia application model (Figure 1). AHAM is an attempt to generally describe the main features of the majority of AHS and to provide a sound basis for the development of new AHS. From our point of view, AHAM provides a high-level description that fits the structure of all the major AEHS available—thus describing the elements that we can use for translating and implementing an instructional strategy. The main elements of AHAM are: 1.

2.

3.

4.

The Run-time layer, which comprises the functions for rendering the pages and tracking the user’s responses. The Presentation Specification, that is, the definition of the possible behaviours of the application interface to the actions of the user (adaptive areas and elements, active elements, link annotation, etc.). We will call it Interface Model. The Teaching Model, that is, the set of rules or principles that define the behaviours of the application. We will call it Interaction Model. The User Model, that is, the system representation of the user and of her/his current status.

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5.

6.

The Domain Model, that is, the system representation of the content of the hypermedia application, in terms of structure, concepts, pages, or nodes. The Anchoring and Within-component layer, that is, the primitives for building the adaptive system.

The idea is that any educational AHS defines, explicitly or implicitly, all of these elements. For any of them, several choices are possible. For example, the domain model can consider pages or nodes as its main elements, or abstract concepts with semantic connections (Botturi, 2001). The user model can be a simple copy of the domain model (De Bra & Calvi, 1998) or can contain other static or dynamic information, or can be implemented by a Bayesian network (Armani, 2001, 2003; Henze & Nejdl, 1999).

Figure 1. The AHAM reference model

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MAID: A METHOD FOR THE ADAPTIVE INSTRUCTIONAL DESIGN Going through the presentation of the MAID model, imagine a small design team, where a SME or an instructor, works with an instructional designer and with a media producer or Web programmer. The pivotal point for understanding MAID is the idea that in order to create an adaptive application that actually supports and enhances the educational experience from an adaptive platform, the instructional strategy should be translated into the “language” of the adaptive platform. For achieving this, first it should be understood and shared by all team members. The existence and availability of a method for creating this shared understanding is the key for actualizing the potential of AEHS.

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The MAID Meta-Model According to AHAM, in order to build from scratch an AEHS, a designer should consider all its elements. Yet considering existing general purposes AEHSs (that is to say adaptive platforms), some parts of the AHAM are not at stake. Namely, the storage layer and the presentation specifications are the only parts susceptible to modification by the instructional team; in fact, the run-time layer (which comprises the functions for rendering the pages and tracking the user’s responses) and the within-component layer, with all the primitives for building an adaptive system, are usually part of the system logic. Before focusing on our model, let’s depict the key elements that constitute an adaptive hypermedia system in what we may call a meta-model (Figure 2): the domain model, the user model, the interaction model and finally the interface model. Notice that elements influence each other. For example, the user model is usually built on the

domain model, as in the case of overlay models (De Bra, Aerts, Houben, & Wu, 2000). Moreover, the interface model is created on the basis of the interactions that should be achieved. The interaction model is the real pivotal element, as it defines the rationale for the behavior of the application, and, as it will become clear further on, strictly depends on the instructional strategies. All the elements are affected by the instructional requirements and the technical possibilities and constraints that define the broad boundaries of the application.

The Method The MAID design method starts at a point in which the designers have performed a complete instructional analysis, have defined with the instructor or SME an instructional strategy, and have decided to consider AEHS as a viable support for the course. For example, one may decide to give the students a problem-driven task that must be accomplished autonomously using the

Figure 2. MAID meta-model

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resources available on the adaptive system, or it is possible to decide to adopt a more traditional approach, where the class must attend an online (adaptive) lesson. MAID is composed by five steps that define the process, each with a set of output documents, and by a lifecycle of the process.

MAID Steps The MAID steps cover all the elements of AHAM, and they are: 1. 2. 3. 4. 5.

Interaction model: define the application behavior; Domain model: define the content structure; User model: define the relevant information about the user; Interface model: map the behavior in user interface elements; and Implement and testing: implement and test the system.

MAID Lifecycle As usual with design methods, MAID as well has to cope with creativity and with a set of complex interrelated issues. The meta-model presented in Figure 2 clearly indicates the set of relationship existing between the adaptive application models. The definition of each of them influences all the others, so that a spiral-like lifecycle is unavoidable. For instance, the results of the testing phase also will probably provide indications about the redesign of some parts of the application. The only way to reduce as much as possible the number of iterations between the tasks is to “start with the end in mind”, meaning that a careful instructional analysis of the learning scenario that is going to be designed with MAID can dramatically cut down the cycles in the following design phase. The discussion section will provide additional insights.

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A Case Study: Effective E-Mail for Managers In order to show MAID in a real scenario, in this section we present a complete case study developed at the University of Lugano in May 2003, reporting the production of an adaptive unit about the effective use of e-mail for young managers. The idea was to provide a one-hour self-instruction module about the basic and advanced functions of e-mail (namely of Microsoft Outlook) and about effective e-mail communication. The learners are therefore young managers who use e-mail a lot. They might be considered able to use a computer and browse the Web. They are likely to use the application during their office time, in a set of short sessions (15-20 minutes). The topics they are interested in are basic and advanced e-mail functions, and the effective communicative use of e-mail. The goals for the unit are defined as follows: 1.

2.

3. 4.

Learners master basic e-mail functions (create a message, use formatting, insert automatic signature, etc.); Learners know how to use advanced e-mail functions (out-of-office reply, reception confirmation, rules for automatic archiving, etc.); Learners are aware of the communicative implications in the use of e-mail; Learners improve their use of e-mail according to their communicative goals.

The strategy selected considers the following elements: 1. 2. 3.

Learners will study individually, without any support; The unit will take one-hour average time for completion; The application will consider each learner’s learning styles and offer accordingly specific

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4.

media types (images, audio, text) and content types (explanations or examples); The application will consider each learner’s expertise level (beginner, expert, advanced) and propose topics consequently.

well as interface design. The issue was therefore to exploit AHA! as a low-level adaptive engine, on the top of which a more complex model can be built, implementing the specific instructional strategy.

Technical Solution

STEP 1: Interaction Model

The adaptive platform selected for the implementation was AHA 1.0, at the time the only adaptive system easily downloadable and installable. AHA! supports two kinds of adaptation:

During this step the designer has to decide how the application will behave in response to the user’s interaction. The interaction model specification produced by the designers is presented in Box 1, along with notes clarifying the decision making process. With this specification document, the designers could move to the definition of the domain, user and interface models.

1.

2.

Link annotation: a link may change color for a specific learner according to the prerequirements the learner has achieved. A link can be recommended, to-be-avoided, visited, or neutral. Selective release (of fragments): pages may contain conditional blocks that are visualized to a single user according to her/his level of knowledge, for example, if s/he visited a particular page, or got at least 50 for concept X.

AHA! offers great flexibility, in terms of content structuring and navigation behavior design, as

STEP 2: Domain Model The MAID domain model represents the designer’s knowledge about the content and structure of the learning content, in a form translatable to system internal data structures. Since traditional knowledge-based adaptive systems use a network of nodes for describing the domain model, the MAID domain model specifi-

Box 1. 1. 2. 3. 4. 5. 6. 7.

The application should consider users individually This comes automatically with AHA! that, as the greatest part of current AHS only considers single users, with no grouping, but of course other adaptive platforms may behave differently. The application should consider the learners’ learning styles for selecting media and content types. Learners directly express their preferences via a specific interface device This clearly constitutes an requirement for the Interface Model, as it will be clearer later on. The application should track the expertise level of the learners’, and show recommended topics according to learner’s progress. The learners’ starting expertise is tested at the beginning of their first session, then the system tracks their progress in the background. The user model is closed Meaning that the learner has no control over it. The selection of content should happen through an adaptive navigation menu, which expands with the increase of expertise This is another requirement for the Interface Model.

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cation document takes the form of a network of nodes, or node map. The nodes within the network may represent concepts, pages, or whatever atomic element of the hypermedia. Their interconnections may convey both structural (e.g., part-of, specialisation, etc.) and rhetoric/pedagogic relations (is prerequisite, is analogous to, etc.). First of all, the team draws the node map that represents the domain. The nodes may be clustered in islands for readability concerns, where each island gathers nodes about the same sub-topic (Botturi 2001). For this case, the designers defined three node types (Figure 3): 1. 2. 3.

Explanations with examples; General introductions to topics (tagged with the prefix ‘INTRO_’); and Tests (called ‘TEST’).

Moreover, in order to provide some more structure to the design, the designers used islands, organizing the content in topics (in the figure the labelling of the topics is omitted to improve readability).

Notice that each island contains a ‘TEST’ page: these node are a sort of self-test where the user could get a synthetic self-evaluation of her/his own learning, and are not used for updating the user model (in fact, this was not specified in the strategy). On the node map, the design team has to draw the structural relations that occur between nodes. AHA! allows the definition of two kinds of relationships between pages1: 1.

2.

5.

Figure 3. “Effective e-mail” : domain model (node map)

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Prerequisites, that is, the relationship existing between a concepts A and B when the learner must know B prior to visiting A in order to get a complete understanding of A; and Propagation, that is, the relationship existing between concepts A and B meaning that, when the learner understands A, he also understands “something” of B. The result is shown in Figure 4 and Figure

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Figure 4. “Effective e-mail”: Domain model (prerequisite network)

The basic idea for tracing prerequisites is that learners can visit any page for any island (i.e., topic) only when they first got the introduction to that topic. The only exception, due to nature of content, is between the FOLDER and RULES nodes (in the top right island). Propagations from each node in an island are collected into that island’s pad (Figure 5). Pads are nodes that are not linked to any physical HTML page, that is, they are abstract nodes. In this example, they enable the designer to enhance the system’s tracking of the learners’ knowledge state, by representing an indication of the average value of the learner’s knowledge about the topic of the corresponding island in which the pad is located. Thus in this case study, the domain model specification document is composed by the three sub schemas presented above, namely: the node map (Figure 3), the prerequisite map (Figure 4), and the propagation map (Figure 5).

STEP 3: User Model The user model is the source of the personalisation features of the applications. The data of a user model may be categorized in: 1. 2. 3.

Static data: information about the user such as name, date of birth, and so on; Dynamic data: may contain preferences, knowledge status, and interests; Contextual information: usually session or task states (e.g. current client’s browser, screen resolution, last unfinished topic, etc.).

AHA! user model is composed only by some static data (username and password, university) and by a replication of the domain model for each learner (an overlay model) tagged with further information recording the learner’s interactions and representing her/his knowledge status. The overlay model is kept up-to-date indicating:

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Figure 5. “Effective e-mail”: Domain model (propagation network)

1. 2.

If the learner visited a concept (i.e. the page coupled with that concept); A number quantifying the learner’s knowledge of the concept. Generally speaking, if a learner has all the necessary prerequisites for a concept and s/he visits it, he will get a score of 100; else a lower score, for example, 35.

Since AHA! user model does not explicitly provide ways for adding dynamic user’s traits, the designers defined two non-content islands (Figure 6) recording the learners’ media preference and expertise levels, exploiting the same page/pad notation used in the domain model. According to the interaction model specification, the learner is asked to express her/his media preferences by clicking on particular application pages (therefore they will be included in the interface model), that will store the information in the corresponding preference node.

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Analogously, the expertise level will be tested during the first session (the FIRST_TEST page). The test leads to a result page (“BEGINNER”, “ADVANCED”, or “EXPERT”) that record the initial level in the “LEVEL” pad. During other sessions, the interface is in charge of offering new topics according to the progress of each learner, as specified in the interface model later on. At the end of this step the team has developed the user model specification document composed by: user’s traits model (Figure 6) and the overlay model (omitted here, because it is a copy of Figure 3).

STEP 4: Interface Model The interface is the shallow part of the application, the place where the user-machine interaction occurs—hence it should embody the essence of the interaction model as it has been envisaged in STEP 1.

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Figure 6. “Effective e-mail”: User model (user’s traits model)

The aim of this phase is to define the adaptation features at the user interface level. In particular some issues are extremely relevant, such as: What is the layout of the pages (content/navigation)? What elements of the layout are adaptive and what are static? How does the user control navigation? If it is the case, how does the user update the user model? The interface model is defined through two representations: 1.

2.

One or more layout templates, each of them specifying what interface elements are used for controlling the navigation (i.e., adaptive access to the topics according to the learner’s expertise level) and the media preference. An access and navigation map: it is an annotated copy of node map of the domain model specification document specifying what pages are accessible given a specific user model status.

In our case study, the designers defined only one layout template (Figure 7). At this stage still some interface specifications are missing, as they are strictly dependent on the low level engine which is used to implement the pages.

The access and navigation map is a copy of the node map integrated with information about the navigation dynamic. The navigation behaviour may be expressed both by adding notes to existing nodes in natural language and by drawing paths between nodes. In this example, the design team used only notes (Figure 8). The annotations indicate the conditions that should be verified in the user model for showing the corresponding link to the island introduction in the left frame menu.

STEP 5: Implementation and Testing The implementation of the application from the MAID documentation, in the case study, was a straightforward process: the domain model was translated into three lists (nodes, prerequisites and propagations) to which the additional user model islands were added. The interface was then implemented in HTML, inserting the adaptive code, and then parsed to XML. Figure 9 shows a screenshot from the application. The correct behaviour of the student’s preferred media selection was tested selecting different kinds of media on a page. This task was repeated for a sample of pages that belong to different islands and it was repeated for each kind of user

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Figure 7. “Effective e-mail” interface model layout

Figure 8. “Effective e-mail”: Interface model (access and navigation map)

type (beginner, expert, and advanced). The navigation consistency for each user’s level was also tested, verifying that at each level a user may access only the corresponding topics. This case study showed the whole MAID method in practice. In order to foster its understanding by the reader, the following section will recap the method, and will discuss its generalization with respect to both the application domain, and the adaptive platform.

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MAID: SUMMARY AND GENERALIzATION The five steps that the design team should undergo for the development of an educational adaptive application from an existing adaptive platform according to MAID are shown in Table 1.

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Figure 9. Screenshot taken from “Effective E-mail” adaptive course

STEP 1: Interaction Model During this step the designer should express how the application will behave in a way that allows the technical staff to understand how the system changes state and how the state modifications are reflected in the user interface. This means figuring out how the adaptive application will support the selected instructional strategy. This phase is crucial because it influences the following steps (Figure 2): starting from the interaction model, the designer will design the user model, the domain model, and the interface model so that they implement the expected interaction. Notice that the interaction model usually is strongly application-dependent. Each adaptive platform comes with a set of adaptive features and with specific user tracking features. Thus, depending on the degree of modularity of the target application, this phase could be more or less

time-consuming. In the case of general-purpose adaptive systems, like AHA! v.1.0, Interbook (Brusilovsky, Eklund, & Schwarz, 1998), or KBS Hyperbook, that come with a predefined interaction model that can not be customized at all, the designer, instead of listing the desired interactions, should be aware of the permitted ones. However, recently some new systems allow the designer to define her/his own interaction model (De Bra, Aerts, Smits, & Stash, 2002b; Stash & De Bra, 2003); in this case the task is harder, but also with a higher degree of freedom. The issue at stake here might be phrased as “What are the features that will be used to accomplish a specific goal?” For example, “the system link hiding feature is used to hide the links to not-ready documents until the student passes a test on the topic”. The output of this step is a common list of statements in natural language describing the

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Table 1. MAID: The five steps of the process # 1

STEP INTERACTION MODEL

GOAL Define the application behavior

ISSUES  What can the user do?  How does the system get information from the user’s behaviour?  How does the system adapt to user?  What types of node  What do they mean with respect to the strategy?  What kind of relation types are there?  What are the relations between nodes?

2

DOMAIN MODEL

Represent to the system the designer’s knowledge about content

3

USER MODEL

Represent to the system the relevant user’s infor mation

 What static data are needed?  What dynamic data are needed?  What session data are needed?

4

INTERFACE MODEL

Define adaptive layout

 How is the layout arranged?  What are its elements?  How can the user navigate the hypertex t?  How is the application made understandable?

5

IMPLEMENTING & TESTING

Implement and proof-check the application

 Is the user model gathering infor mation according to specification?  Is the Inter face presenting elements according to interaction specification?  Are there any unreachable pages? Why?

application behaviour; alternatively, some UML diagrams may be coupled with the document in order to better describe the key interactions.

STEP 2: Domain Model Although each platform uses specific definition of nodes, pages, or concepts, the designer has to

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OUTPUT DOC Interaction Model Specification Document (list of all the features of the systems) Domain Model Specification Document:  Node map (list of all the nodes of the networ k, grouping in islands)  Relation networks (a network map for each relation type) User Model Specification Document:User:  Trait’s model (list of the user’s preferences, interests, etc.)  Overlay model (knowledge, interests, etc, related to the Domain Model)  Layout template(s) (one or more template showing the layout of the elements in a page)  Access map (annotated node map showing the access conditions of the pages, and the available paths between them) none

decide what do the nodes represent in this very application: they can be concepts, content pages, lessons, exercises, tasks, scenarios, problems, and so on, or a combination of them. The type of a node depends on the instructional strategy. If the strategy is problem solving, then nodes can straightforwardly represent problem statements and supporting contents for scaffolding. In a

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traditional lesson-oriented course, nodes may represent content pages and exercises. Finally, in a scenario-based course they are likely to be mainly tasks and steps. It is important to notice that the same adaptive features acquire a different meaning according to the types of nodes, and therefore according to the instructional strategy. For example, link hiding might simply mean “the student is not ready for this content” in a content-based application, while is could mean “the student does not need this particular scaffolding for this task” in a problem-based environment. This diversification of node functions is a high-level abstraction that does not need to be necessarily translated as-is to the system logic, but it supports the design team in reflecting on and manipulating the functional elements that set up the domain, thus keeping them focused on the instructional strategy they have adopted. The documentation produced in this step includes: 1.

2.

The node map: As shown in the case study, for creating the domain model, the team essentially draws a map node map that represents the domain. The nodes may be clustered in islands for readability concerns, where each island gathers nodes about the same semantic or functional meaning. Relation networks: On the node map the design team will have to draw the structural, pedagogical/rhetoric relations that occur between nodes. We suggest drawing a diagram for each relation type, in order to improve readability of such networks.

STEP 3: User Model The user model is the source of the different personalisation features the application supports. Generally speaking, the user’s data can be classified in:

1. 2.

User’s traits (data which is not related to domain knowledge) Knowledge-related data

The former set includes the user’s name, date of birth, learning style, and so on. The latter is the set of user’s knowledge/interests/preference level for each specific node of the domain model. This second kind of data is usually represented by an overlay model superimposed to the domain network—this is common in many systems like AHA!, and KBS Hyperbook. In this case, MAID suggests simply copying the node map from the domain model. Moreover, according to the instructional strategy, the designer might need to store in the user profile information that the platform does not consider. MAID proposes to add this additional information directly into this copy of the node map. In this way the domain data and user/session data are kept together, so that it is possible to think about their interaction with ease2. Figure 10 shows the user model from an hypothetic course on “Introduction to the Internet”, where we record the knowledge level of each page taken from the overlay node map (cf. basic concepts and applications islands), and three new variables for each learner (cf. user model island): the type_of_user indicating the learner’s degree of use of the Internet, the learner’s language (language) and prior education (education). Notice that user nodes may also be grouped in islands.

STEP 4: Interface Model The aim of this phase is to define the adaptation features at the user interface level. In particular some issues are extremely relevant, such as: 1. 2.

What is the layout of the pages (content/ navigation)? What elements of the layout are adaptive and what are static?

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Figure 10. Example of user model: Traits and overlay models

3.

What are the opportunities for navigation for the user?

Given the complexity of AEHS, the general usability of the application is the major concern here. During this step, the designer will produce a layout template for each significant page of the application, which defines the main parts of the screen and their functions. Comments may be added in order to specify which adaptive features of the platform will be exploited. It might be necessary to annotate the diagram with a definition of the dynamics of the adaptive menus/maps, for example, stating the conditions for showing/hiding the different parts of the menu on the screen. The example for the “Introduction to the Internet” course is presented in Figure 11. Notice the menu that provides access to all the application pages, plus the slot for the “proposed next step” (i.e., the application proposal for the next page). The annotation points out that the next step is proposed by

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a tutor-icon. The layout should then be developed as a complete graphical mock-up.

Access Map Optionally, an access map can be provided to depict access condition or conditional paths that should be enabled/disabled by the user interface. The access map can be an annotated copy of the familiar node map taken from the domain model documentation, stating paths and conditions among page-nodes.

STEP 5: Implementation and Testing Phase If all the steps have been properly accomplished, the implementation step should be a straightforward process of translation from the MAID documents to the configuration files needed to set up the course on the adaptive platform. The real issue at this stage is the implementation of the single

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Figure 11. Example: Interface model

application pages or files that contain embedded adaptive code, as this might require additional technical expertise from the Web programmers. The resources required and the degree of difficulty strictly depend on the selected adaptive platform, but the idea is that at this stage, the designer, SME and technical staff have developed a sound shared understanding of their goal. During and after the implementation, it is important to check if the application actually behaves as envisaged at design time. MAID suggests conducting a sequence of tests checking the consistent update of the user model (Wu & De Bra, 2001), the effects on the user interface, navigation consistency and eventually code bugs.

DISCUSSION why Using MAID? MAID is a domain-independent design method to create high level representations of an AEHS. Although the method is general, it fits well the implementation stage of virtually every knowledge-based adaptive system. One of its advantages is the graphic notation, integrated within a rational design process of AEH, which allows conveying the basic design objects and principles to nonexperts, making MAID a communication catalyst. MAID’s step-by-step process also provides guidance for the designers, leading them to think systematically to all the necessary ingredients that constitute a (hopefully) successful AEHS, before even starting to implement it.

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Moreover, the way the steps are arranged helps to add system requirements incrementally, without forcing to anticipate design solutions before the time. For instance, design opportunities at the interface model step are only influenced by the statements of the previous steps, in terms of boundaries/requirements: the same interaction requirement may be achieved with different interface design solutions; the same node at the level of the domain model may be accessed in different ways at the level of the interface/navigation model.

A “Hectic” Process We anticipated that the several relations that occur between the different phases of the method may lead to frequent cycles on already taken steps. This is especially the case of the triangle domain model—user model—interface model. The reason is that all of them rely on the interaction model. For example, sometimes we must foresee some hypothesis on the interface model (e.g., defining a first layout diagram with indications of the adaptive parts), in order to define the user model variables and the domain concepts which will be exploited for the adaptation. Moreover, to ensure that the user model and the domain model in concert work as we expect, we have to take them in consideration cyclically. Finally, the testing phase usually shows some inconsistent behaviour that is imputable to mistakes in one of the models.

Limits of the Method MAID was developed through the experience that the authors matured during the design of adaptive courseware with AHA! 1.0. Some of the steps could be more difficult to perform with other adaptive platforms. For example with the KBS Hyperbook system, which adopts a Bayesian Network (BN) as user model, the designer has little to nothing control on the user model update rules, because the BN formalism makes all the infer-

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ences. This increases the importance of domain modelling that must take into account the way the BN works. The domain model of some adaptive platform could have a more complex structure which requires more specific diagrams. The method should be adapted to the design team, for example, it may be useful to write more or less detailed documentation, or use UML diagrams instead of simple text descriptions for the interaction model. Finally, while MAID is certainly useful for structuring small-scale adaptive courses, with a handcrafted nature, it becomes rapidly unmanageable when representing large, data-intensive Web sites; in this scenario, different methods and modelling primitives are being researched.

An Additional (Critical) Step: Achieving the Student’s “Awareness” We have chosen to clearly separate the design phase from the release, because of the different issues that come at stake. Nevertheless, we want to stress the importance of a critical step for the success of the courseware: the first presentation to the end-users. Every Web site usually has a learning curve before the user may use it efficiently; an adaptive course, which has potentially unstable interfaces, with conditional fragments that appear and disappear, needs “aware” users. This student’s awareness can be achieved in different ways, for example, through self-explicative interfaces, or giving the user the possibility to inspect and modify her/his user model, or scheduling a kick-off lesson where the system is presented to the class.

FUTURE TRENDS A complete design model for implementing adaptive applications is one of the key elements for making AHS accessible to a large number of

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potential users. Testing done with MAID indicated that also non-technical instructors and designers, if supported by skilled designers, may exploit the potential of adaptivity in real educational environments. An obvious improvement for MAID would be a refinement of its steps and its accurate testing with different adaptive platforms. The development of a MAID CASE tool would also be an interesting development. Finally, widening the scope of observation, three main elements deserve a particular notice for the evolution of this research track: 1.

2.

3.

Within the AHS field, it is remarkable that some adaptive platforms, like AHA! v. 2.0 are being developed as open systems, supported by a complete authoring tool. We believe that the development of such a tool can be enhanced by the existence of a sound design methodology. In the broader field of educational technologies, the AHS community can look with interest to the development of learning object standards, such as IMS (IMS, 2003) or SCORM (SCORM, 2003). The object oriented modelling of educational applications in fact provides a sound basis for a common definition of AHS; on the other hand, object-oriented e-learning platforms may gain from adaptive features. What is required for creating a real synergy between the two of them is a method for adapting learning unit structures and selecting learner-tailored learning objects. From this point of view, an integration of MAID or of a similar method with a learning-object compliant and adaptive platform would be a promising achievement. Finally, we recall that instructional strategies—that are specific for each instructional unit—belong to broader categories, such as constructivist strategies, problem-based strategies, and so on. An open research

track is the definition of adaptive patterns for types of strategies, under two respects: (a)

(b)

Defining types of adaptive application behaviours suitable to support particular instructional strategies. Defining types of interaction models, domain models (namely types of nodes), and user models that designers can use as starting point for the implementation of particular instructional strategies.

CONCLUSION This chapter started with the observation that, despite the great technical advances achieved by AHS in the last decade, adaptive applications are not a commonly used tool in real educational environments. We claimed that this is due to the lack of a sound design method for the development of adaptive application supported by available adaptive platforms. The core of the chapter provided a complete presentation of MAID (Method for Adaptive Instructional Design). The method is focused on the idea of implementing a particular instructional strategy through its translation into a formal description, understandable by the adaptive platform. The description is based on AHAM, and includes the interaction model, the domain model, the user model, and the interface model. The complete MAID method is structured in five phases. Each of them was introduced and illustrated by examples. The lifecycle of MAID was also discussed. A complete case study proposed a picture of the method in practice. Finally, the method was discussed and some outlooks in the field of AHS and in other fields were presented. The major claim of this chapter is the necessity of offering a design method for supporting the actual exploitation of AHS in real educational environments. From a practical point of view, this means training designers to help instructors and educators to translate their ideas and strategies into

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adaptive applications. In this direction, MAID is a communication tool that enables technical staff, designers, and instructors to share with each other. With MAID, the content of this communication process focuses on the instructional strategy, keeping technical details in the background.

Brusilovsky, P. (2004). KnowledgeTree: A distributed architecture for adaptive e-learning. WWW 2004, New York.

REFERENCES

Brusilovsky, P., Eklund, J., & Schwarz, E. (1998). Web-based education for all: A tool for developing adaptive courseware. Computer Networks and ISDN Systems [Proceedings of 7th International World Wide Web Conference], 30(1-7), 291-300.

Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching and assessing. A revision of bloom’s taxonomy of educational objectives. New York: Addison Wesley Longman. Armani, J. (2001). Progettazione e sviluppo di un’applicazione ipermediale adattativa per uso didattico. Master thesis. Biblioteca centrale del Politecnico di Milano. Armani, J. (2003). The AdLearn framework: Automatic planning and tutoring system for self studying. International Studies in Communication Sciences (in print). Aroyo, L., Dicheva, D., & Cristea, A. (2002). Ontological support for Web courseware authoring. ICALT’02, Las Vegas, NV. Bates, T. W. (1999). Managing technological change. San Francisco: Jossey-Bass. Bates, T. W., & Poole, G. (2003). Effective teaching with technologies in higher education. San Francisco: Jossey-Bass. Botturi, L. (2001). Seaway tracker. An adaptive navigational engine for educational applications. Master thesis. Lugano: BUL. Brusilovsky, P. (2003). Developing adaptive educational hypermedia systems: From design models to authoring tools. In T. Murray, S. Blessing, & S. Ainsworth (Eds.), Authoring tools for advanced technology learning environment (pp. 377-410). Dordrecht: Kluwer Academic Publishers.

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Brusilovsky, P., & Pesin, L. (1994). ISIS-Tutor: An adaptive hypertext learning environment. Japanese-CIS Workshop on Knowledge-Based Software Engineering, Tokyo, Japan.

Carro, R. M., Pulido, E., & Rodríguez, P. (2001). TANGOW: A model for Internet based learning. IJCEELL - International Journal of Continuing Engineering Education and Life-Long Learning, 11(1-2). Retrieved March 2004, from http://www. inderscience.com/ejournal/c/ijceell/ijceell2001/ ijceell2001v11n12.html Cristea, A., & Aroyo, L. (2002). Adaptive authoring of adaptive educational hypermedia. AH 2002, Malaga, Spain. Czarkowski, M., & Kay, J. (2002). Scrutable adaptive hypertext. AH 2002, Malaga, Spain. De Bra, P., & Calvi, L. (1998). AHA! An open adaptive hypermedia architecture. The New Review of Hypermedia and Multimedia, 4, 115-139. De Bra, P., Aerts, A., Houben, G. J., & Wu, H. (2000). Making general-purpose adaptive hypermedia work. AACE WebNet Conference, San Antonio, TX. De Bra, P., Aerts, A., Smits, D., & Stash, N. (2002a). AHA! meets AHAM. AH 2002, Malaga, Spain. De Bra, P., Aerts, A., Smits, D., & Stash, N. (2002b). AHA! Version 2.0, More adaptation flexibility for authors. ELEARN 2002, Montreal, Canada.

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De Bra, P., Houben, G. J., & Wu, H. (1999). AHAM: A dexter-based reference model for adaptive hypermedia. ACM Conference on Hypertext and Hypermedia, Darmstadt, Germany. Dick, W., Carey, W., & Carey, L. (2001). The systematic design of instruction (6th edition). New York: Harper Collins College Publishers. Gagné, R. M., Briggs, R., & Wager, W. (1992). Principles of instructional design (4th edition). TX: HBJ College Publishers. Grigoriadou, M., Papanikolaou, K., Kornilakis, H., & Magoulas, G. (2001). INSPIRE: An INtelligent System for Personalized Instruction in a Remote Environment. Revised Papers from the International Workshops OHS-7, SC-3, and AH-3 on Hypermedia: Openness, Structural Awareness, and Adaptivity, Lecture Notes in Computer Sciences (pp. 215-225). ACM Press. Henze, N., & Nejdl, W. (1999). Adaptivity in the KBS hyperbook system. Second Workshop on Adaptive Systems and User Modeling on the WWW, Banff, Canada. Henze, N., Naceur, K., Nejdl, W., & Wolpers, M. (1999). Adaptive hyperbooks for constructivist teaching. Kunstliche Intelligenz, 4. IMS (2003). IMS Specification. Retrieved September 25, 2003, from http://www.imsproject.org Koch, N. (2001). Software engineering for adaptive hypermedia systems. PhD thesis, Verlag Uni-Druck, Munich. Merrill, M. D. (2003). Does your instruction rate 5 star? Retrieved August 2003, from http://www. id2.usu.edu/5Star/Index.htm Neumann, G., & Zirvas, J. (1998). SKILL – A scalable Internet-based teaching and learning system. WebNet 98, Orlando, FL. Papasalouros, A., & Retalis, S. (2002). Ob-AHEM: A UML-enabled model for adaptive educational

hypermedia Applications. Interactive Educational Multimedia, 4. Park, O., & Lee, J. (2004). Adaptive instructional systems. In D. H. Jonassen (Ed.), Handbook of Research on Educational Communications and Technology (2nd ed). AECT. Retrieved from http://www.aect.org (members only) Quatrani, T. (2001). Introduction to the unified modeling language. Retrieved September 25, 2003, from http://www.rational.com/media/uml/ intro_rdn.pdf Reigeluth, C. M. (1983). Instructional-design theories and models: An overview of their current status. NJ: Lawrence Erlbaum Associates. SCORM (2003). SCORM specification. Retrieved September 25, 2003, from http://www.adlnet. org/index.cfm?fuseaction=scormabt Smith, P. L., & Ragan, T. J. (1999). Instructional design. New York: John Wiley & Sons. Stash, N., & De Bra, P. (2003). Building adaptive presentations with AHA! 2.0. PEG Conference, St. Petersburg, Russia. UML (2003). Resource center. Retrieved September 25, 2003, from http://www.rational. com/uml Wu, H., & De Bra, P. (2001). Sufficient conditions for well-behaved adaptive hypermedia systems. Lecture Notes in AI [Proceedings of the WI Conference], 2198 (pp. 148-152). Wu, H., Houben, G. J., & De Bra, P. (1999). Authoring support for adaptive hypermedia applications. ED-MEDIA 1999, Seattle, WA.

ENDNOTES 1

Both for prerequisites and propagation, AHA! requires the specification of absolute

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2

or relative (percentage) values for each relationship. These were omitted from the maps in order to improve legibility. Another issue we should mention is whether the user profile (or part of it) should be opened to the user (Czarkowski & Kay, 2002) so that s/he can change some particular values (for example, the student may set her/his knowledge levels on some topics), or not. It is important that this decision is made in the perspective of the instructional strategy. It is in fact possible that the activities supported

by the adaptive application are just a part of the whole course or instructional unit, and it may happen that a learner gets a particular insight in some topic during a classroom session, that the adaptive system clearly cannot record. According to the responsibility and learning independence of the learners, the designer may choose to let them directly update values in their profile. In the User Model documentation, the designer may annotate the corresponding variables that can be inspected/modified by the learner.

This work was previously published in Advances in Web-Based Education: Personalized Learning Environment, edited by G.D. Magoulas and S.Y. Chen, pp. 147-177, copyright 2006 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.13

Distributed Learning Objects:

An Open Knowledge Management Model Veronica Diaz The University of Arizona, USA Patricia McGee The University of Texas at San Antonio, USA

ABSTRACT This chapter analyzes the emergence of learning objects as a dynamic and interactive relationship between technology and the organization. We examine the way that organizational objectives are embedded within selected technologies. In other words, how is the selected technology addressing the organization’s needs? Further, we argue for a socially-constructed model of knowledge management. Specifically, we utilize Demarest’s (1997) four-step process of the construction of a knowledge economy. From these processes, via a constructed technological system, a learning object economy emerges, which includes various constituents: the 21st century learner, the subject matter expert (university professor), vendors who support or enable knowledge management, and

populaces that harvest and benefit from the collection of knowledge.

INTRODUCTION As state and federal funds diminish and as higher education resources and university budgets become more restricted, postsecondary institutions are becoming increasingly entrepreneurial in pursuing and developing technological solutions. Meyer (2002) describes a changing marketplace, increasingly global in orientation, where technology enables the provision of adult education, executive training/retraining, competency-based programs, and education to remote geographical areas. Knowledge management,1 in higher education, is a way to retain and manage knowledge products. As higher education organizations increasingly interact with other organizational

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

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types, such as corporations, consortia, and other educational institutions, knowledge products become critical in the exchange process. Technological systems are designed to manage knowledge and are situated in social systems with corresponding cultures, values, and beliefs. As such, higher education, as an organizational structure and a social system, must consider processes, policies, and embedded assumptions about technology, teaching, and learning, not only within their own institution, but also across those with which they interact. The trend toward knowledge management is evidenced in the myriad of technological artifacts that have emerged to capture, categorize, and manage learning objects. During their evolution, learning objects have come to be defined in a number of ways, depending on the context and culture from which they emerge, for example, computer science, education, instructional technology, and so on. For our purposes, we define a learning object as any digital asset that is intended to be used to achieve a learning objective and can be re-used in different contexts. Learning objects may be data or data sets, texts, images or image collections, audio or video materials, executable programs, courses offered through Learning/Course Management Systems (L/CMS), or other resources that can be delivered electronically. Learning objects should be re-useable and re-purposeable over time and location and interoperable across systems and software (see Downes, 2002; Robson, 2001; Wiley, 2000). Additionally, learning objects can be combined or aggregated in different ways providing the potential for individualized learning experiences for specific learners in which their learning styles, prior knowledge, and specific learning needs are accounted for. They may also offer great value in terms of saving time and money in course development, increasing the reusability of content, enhancing students’ learning environment, sharing knowledge within and across disciplines, and engaging faculty members in a dynamic community of practice (Bennett &

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Metros, 2001). Learning objects may be created by individuals or institutions and therefore require consideration of digital rights as well as storage and distribution. How learning objects are stored and subsequently accessed has been primarily addressed through technology systems known as digital learning object repositories. Thomas and Home (2004) have identified four rationales, not only for the development of learning objects, but also for their storage in these digital containers. 1.

2.

3.

4.

The efficiency route: The more institutions work together, the less likely replication of efforts and therefore reduced costs based on the idea that learning objects “deliver industrial economies of scale” (p. 12). The teacher-centered route: The more that educators share resources and best practices, the more likely teaching will improve. In this manner learning object “creation [is] co-production” (p. 12). The pupil-centered route: Learners who have access to a variety of objects designed with different learning needs in mind, can be better supported. In this sense, learning objects become “scalable and networked” (p. 13). The freedom argument: Educators should take ownership and be able to disseminate freely to the larger educational community without struggling with or against issues of institutional ownership, intellectual property or even censorship.

These rationales serve to illustrate the value structures within organizational cultures that determine how technology is used to make knowledge accessible and the reasons for doing so. Such positions are reflected in organizational policies and are particularly critical within crossinstitutional interactions. This chapter analyzes the emergence of learning objects as a dynamic and interactive relation-

Distributed Learning Objects

ship between technology and the organization. We examine the way that organizational objectives are embedded within selected technologies. In other words, how is the selected technology addressing the organization’s needs? Further, we argue for a socially-constructed model of knowledge management. Specifically, we utilize Demarest’s (1997) four-step process of the construction of a knowledge economy. Next, we examine the way that knowledge is transmitted through a selected technological system. From these processes, via a constructed technological system, a learning object economy2 emerges, which includes various constituents: the 21st century learner, the subject matter expert (university professor), vendors who support or enable knowledge management, and populaces that harvest and benefit from the collection of knowledge. We discuss four current models of knowledge management found in higher education: the traditional model, the intellectual capital/appropriative model, the sharing/reciprocal model, and the contribution pedagogy model. We propose a new, relativist model of knowledge management for higher education that accommodates cross-institutional cultures and beliefs about learning technologies, construction of knowledge across systems and institutions, as well as the trend toward learner-centered, disaggregated, and re-aggregated learning objects, and negotiated intellectual property rights.

A Starting Point: Thomas’s Theory of Organizational Technology Thomas (1994) argues that a technical system utilized within an organization can be objective, but also infused with objectives, reflective of the interests or goals of particular groups within the social system. A technological system, he contends, has the ability to define and redefine tasks, responsibilities, and relationships or to evoke or reinforce change. Further, the eventual selection of a specific technology reflects the interests and ideologies of the organizational structure.

Organizations are composed of interdependent social and technological systems where changes in one usually occasion adaptation in the other (e.g., a course management system many interact with a registration system). However, the relationship between technology and the organization is dynamic and interactive, that is, technology may cause organizational change and organizational objectives may produce a change in the technological system. Thomas explains that in order for the technology to be incorporated into organizational life, it must be transformed from a physical object into a social one. In other words, organizational members must recognize that the technology exists and then negotiate a set of understandings about what it is, what it means, and how it defines and redefines tasks, responsibilities, and relationships. Thomas proposes a model of organizational technology whose adoption and use is shaped or determined, to some extent, by the organization that selects it. While he acknowledges that the technological system interacts with the organization and its objectives and vice versa, this model is limited to some extent by those very things: the organization and its objectives. Current knowledge management models are organizationally-centered and are thus limited by the values and interests of their constituents. However, others are arguing for a transformation of the knowledge economy from one that is proprietary to a freestanding, shared knowledge community (Norris, Mason, & Lefrere, 2003). Norris et al. point to eight external and internal forces that are producing this shift: (1) Investments in infrastructure and best practices by “early adopters” of e-knowledge (e.g., associations, governmental agencies, corporations, universities) deliver results that encourage wider adoption, and also facilitate new generations of enterprise applications; (2) Global enterprises that increase competitiveness by developing faster ways to manage their knowledge and strategic learning by creating tools that non-experts can use; (3) Growth in expert networks and easier,

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more productive participation in communities of practice that push e-knowledge practices and competencies; (4) Increasing sophistication by users, who develop an appetite for services that provide significant gains in their capacity to access and assimilate knowledge; (5) Advances in Internet and intranet-based capabilities that enable jump shifts in creating and accessing knowledge stores; (6) Innovations in mobile communications that provide ubiquitous access to perpetual learning solutions, as well as new ways to meet demands for e-commerce in any place or time; (7) Insight into new and more effective ways of experiencing how knowledge drives innovation; and (8) Increased understanding about how to deploy international standards in ways that ensure useful return on investments (e.g., through interoperability) that stimulates continued investment. We believe that these are just some of the local and global changes occurring that are motivating higher education to explore a system of knowledge management that is socially-constructed rather than organizationally-determined. As this trend unfolds, there is an increasing demand for collaborative discourse and negotiation, not just about what technology means, but also how it is designed and how artifacts such as learning objects are shared. This trend is evidenced by such efforts as the IMS Global Learning Consortium, Inc., in which members from around the world work together to develop specifications for e-learning technologies.

Social Construction of Knowledge and Learning Objects The global nature of education within a distributed learning context requires that higher education, particularly considering learning objects as a valuable commodity that can be traded and exchanged, is part of an evolving knowledge economy. Texts, videos, and other materials have proven the value of institutionally-generated knowledge, but traditionally these products have produced revenue for an individual with value capital for the institu-

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tion. Learning objects are forcing institutions to examine the economic exchange of the knowledge capital they are generating as they search for strategies to manage and negotiate value. Following Thomas’s theory of the social or organizational construction of technological systems and drawing from an economic business perspective, Demarest (1997) postulates that organizations value knowledge based on “what works.” Business uses resource capital in order to develop processes and structures that result in increased sales and revenue. Davenport, DeLong, and Beers (1998) found four distinct types of knowledge management initiatives in corporations that were intended to: 1. 2. 3. 4.

Provide repositories for internally generated policy and informational knowledge Provide access to knowledge or transfer among individuals Facilitate the generation and use of knowledge Manage knowledge assets in such a way that value is apparent

Corporate knowledge management comes from an economic model that is based on a knowledgeable workforce that increases the organization’s return on investment. Davenport, et al. believe an economic model is appropriate for learning objects in higher education in that they are, by definition, designed to be re-used and shared. Whether or not they have a monetary value assigned to them is incidental, it is the investment of development and dissemination that belies their institutional value. In higher education, “what works” is similar to that of business, but involves “human capital,” which may result in increased enrollments, higher post-graduation employment rates, and academic recognition and prestige for the knowledge generated and disseminated. It is the latter that applies most directly to learning objects in that academic recognition comes from the intellectual production of knowledge that is

Distributed Learning Objects

to be disseminated across institutions, and to a large extent contributes to the knowledge base of those institutions. Higher education values philosophical and scientific knowledge that is generated by the scholarship of its members. Such knowledge has traditionally driven innovation and production (Lyotard, 1984). The commodification of knowledge through information distributed through technologies such as the Internet has expanded the power of university-generated knowledge that can reach beyond business and government to everyone with access to the Internet. However, the value of philosophical and scientific knowledge may be confused with knowledge that keeps the organization performing. For Demarest (1997) this includes: •

•

•

•

A shared understanding of how value is determined, assigned, maintained, and communicated throughout the organization and with external groups or individuals with whom the organization interacts A set of processes and systems—technical or human—that support and help channel the [organization’s] value-creating activities (p. 1) A set of indicators that associate the valuecreation process with the measures of the organization’s success A set of systems that as a part of the “knowledge management infrastructure that monitor the efficiency and effectiveness of that value creation process, indicate opportunities for performance improvement and generally signal the relative rise or decline in value creation” (p. 1)

Higher education has parallel types of performance knowledge manifested in standards for knowledge acquisition by the learner (program requirements, degree audits, grades), standards of academic knowledge (criteria for merit and tenure, peer review of intellectual property), struc-

tures and processes for control of organizational knowledge (publications, events, training), and standards for institutional knowledge (internal reviews, accreditation). The sum total of these types of knowledge and the mechanisms through which their value is determined and tied to performance is what allows the institution to function and yet varies among institutions, challenging the cross-fertilization and reciprocation that goes hand-in-hand with exchange of resources. Demarest believes organizational knowledge is socially constructed, and shared. This occurs through four processes: construction, embodiment, dissemination, and use. Construction is “the process of discovering or structuring a kind of knowledge” (p.6). Organizations that are learning-focused (i.e., K-12, higher education, and workplace professional development departments) utilize specific processes of identifying valued knowledge. Value propositions in such organizations, and to a certain extent in industry where learning is seen as training, may come from external events or forces (community needs, governmental mandates, etc.) or from experience through interaction with client populations (focus sessions, course or training evaluations, documented complaints, etc.). Valued knowledge emerges through an iterative process of examining and implementing the governing body’s mandates (government, professional organization, and certifying agencies), determining community- or client-based values and needs, and identifying best practices and policies that support the identified organizational outcomes. Embodiment is “the process of choosing a container for knowledge once it is constructed” (p. 6). The container may take a variety of forms, most typically a document: manual, memoranda, report, tutorial, or speech. In higher education, such embodiments may be captured as learning objects and stored in a repository or learning content management system (L/CMS). How the embodiment is conceptualized may reflect the organizational cultural beliefs about the social

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relationships, communication processes, and the structures of authority. For example, L/CMSs that are course-based and only accessible to registered members of the course may indicate intellectual property controls or return on investment as indicated by course registration. Dissemination “refers to the human processes and technical infrastructure that make embodied knowledge, such as documents, available to the people that use the documents and the bodies of knowledge” (p.6) that serve a function to achieve the organizational goals. Such knowledge dissemination is increasingly digital, although issues of access through systems and (perhaps) limitations of user’s technical skills may be why some educational organizations rely on printed media. Digitization has enabled knowledge updates, re-organization, and re-purposing to be quickly and easily possible. Communication about such changes however must be made to the population who uses the knowledge. Use refers to the ultimate objective of any knowledge management system: the “production” (p. 6) of value. At this point, Thomas’s value proposition is most evident. Organizational knowledge may be constructed, embodied, and disseminated but until it is used, its value is only a construct. Use, it can be argued, is what determines the value of any knowledge. Learning objects stored in repositories or located by “Googling,” but finding out by whom, when, or for what reason (much less for what outcome) is marginally addressed through metadata, but more directly addressed through strategies such as Digital Rights Management (DRM). DRM identifies the rights of holders, permissions, and tracks usage. The Digital Object Identifier (DOI®) system identifies and tracks use of digital objects, primarily to protect and document how intellectual property is being used, but not to discover the knowledge value of an object. As tracking strategies become adopted and uniformly used, we suspect value will be determined more by frequency of use than by other indicators, such as

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return on investment (ROI), or by the knowledge value to the user. Most importantly, the social construction of organizational knowledge does not address knowledge acquisition, which is a primary function of higher education.

Technology-Supported Knowledge Acquisition and Construction in Higher Education The US history of funding technology as a strategy for reform illustrates the theory of technological determinism3, but belies the reality of the application and adoption of technology and the difficulty, if not impossibility of its predictability and control (Hughes, 2001). Technological relativism4 embraces this ambiguity and better reflects what actually occurs in the post-structuralist learning environment where faculty conduct scholarship and the learner engages in social learning through a variety of technologies, in a variety of ways, in different contexts that support the institutional goals and philosophy. Sørensen (1996) discusses the prevailing discourse about learning through doing, using, and interacting by which a learning economy is produced, based on the notion that learner actions involve production that is supported by various technological systems. As learners increasingly access objects within structured learning experiences they are also generating objects that document, describe, illustrate, or share their own knowledge acquisition. This process reflects Demarest’s focus on performance enacted through his social model of knowledge management. In higher education, performance outside of pedagogically-driven environments is less valued because it occurs outside of the economy. The organization assigns value based on the source of the knowledge. Because the learner can access knowledge anywhere or anytime, value propositions erode and are relative, at least for the learner. The nature of learning object construction and re-use as disaggregated5 course content that

Distributed Learning Objects

may be re-aggregated in different ways reflects current thinking about the social construction of knowledge espoused in pedagogical models of online learning (Simonson, Smaldino, Albright, & Zvacek, 2003), the commodification of the course (Diaz, 2004), and the instructional use of learning objects (Higgs, Meredith, & Hand, 2003). Figure 1 below illustrates learning designs in distributed learning systems. Linear learning designs are more content-driven with little deviation from the instructional path and low interactivity with others or the content that is predetermined and a strategy for sharing knowledge. Such designs are highly re-usable and functional when concept, principle, and procedural knowledge are the goal. As the learner moves to the right of the continuum they are afforded more choices about the path of instruction, information formats, and sources, and how they will demonstrate and document their knowledge acquisition. The learner becomes, to a degree, a designer of their own instruction and a generator of knowledge. Difficult to replicate and re-use, this design holds more promise for transfer of knowledge to other contexts and deeper learning (Carmean, 2002). The generation of knowledge and eventual dissemination via learning objects represents a shift, not only in who generates and how generation occurs, but also in how constituencies receive the knowledge.

Didactic instruction is a universally used approach to teaching in classroom settings. The traditional approach to instruction in higher education is instructor-dependent, content-driven, and situated in knowledge transfer (Gibbons & Wentworth, 2001). This is at odds with what is known about adult learning in college and the workplace (Mentkowski, 2000) and in research indicating that as educators use technology in general, their role as subject matter expert shifts to that of guide and facilitator, reflecting an epistemological shift with a variety of associated outcomes (Reeves, 2002). A learning object pedagogy, unlike the traditional model, is one in which the learner makes decisions and choices about a task or problem as they locate relevant information, and construct and generate knowledge eventually embodied in a learning object. The instructor and LCMSs, serve as guide and facilitator. Objects that are used within larger pedagogical frameworks, classrooms, L/CMSs, or blended learning environments, have embedded systems which determine or sanction the function of the object and which operate within the instructional designer’s pedagogical determinism. Although objects that are learner-centered achieve multiple objectives and are more likely to be generative, they are also confined to some degree by the system, process, and technology

Figure 1. Learning designs in distributed learning systems • Rote • Memorization • Habitualization • Routinization Linear Single user • High re-usability • ID design • Instructor/trainer as designer/director Knowledge Sharing Technological determinism

Branched

Hyper-content

Deeper learning • Transferability • Relevance/applicability • Guided Discovery Learner-centered Multiple users • Low reusability • Emergent design • Instructor/trainer as facilitator/resource Knowledge Generation Technological relativism

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within which they operate. The disaggregation of the course has provided a natural opportunity for the learner to modify existing objects or create new ones that become a part of the knowledge used by others to learn (Collis & Stijker, 2003). It is the opportunity for knowledge generation that informs the social model of knowledge management through knowledge management learning designs that operate across institutions, through cross-fertilization, be it intentional (determinist) or selected (relativist).

Transmission of Knowledge Across, Through, and in Spite of Organizations The challenge of any institutionalized knowledge base and system of transmission, transferal, or adoption is that no learner remains within the organizational context throughout their day-to-day life, and they move between contexts across their learning and working life. As workers who are engaged in continual learning, we move between and among organizations that use technologies, the use of which, for the most part, is defined for us by the organizations in which we are situated. Learning environments, rules, procedures, and intended outcomes change as we move from school to work to training. Thus within an institution, the individual acts and interacts from a personal point of view. In post-secondary education, technology is used to support learning, primarily as an Information Communication Technology (ICT) through which knowledge is constructed, learning is managed, or learning objects are disseminated. Elearning has become standard in higher education, as evidenced by the burgeoning and robust market for course management systems, Web-based tutorials and simulations, and mobile computing. Of course, learners in formal educational environments also acquire knowledge from family, social groups, and other social, religious, or civic organizations (Bransford, Brown, & Cocking, 2000).

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Social learning is ill-structured and not necessarily outcome-driven, while learning that is not situated in work or education is typically uniquely structured and without conditional assessment measures. For most of us, our preparation to learn strategically in formal and organized settings begins at an early age in traditional educational institutions. The nature of this type of learning is so institutionalized that it crosses most cultures, economic groups, and generations. Yet when we leave an educational setting and are required to learn in workplace environments, the nature of learning shifts. In the workplace, technology is also used as an ICT although the focus is more on job skills training for just-in-time, just-in-need, or justin-case learning that relates to job tasks, seen as performance support. Designs for workplace knowledge management systems are equally recommended to be learner-oriented in interface and content as well as management design (Raybould, 2002). Over the developmental life of the learner, then, the organizational uses and expectations of technology shifts at the macro level as well as the micro level as discussed by Thomas (1994). An often-missing component from the decision to implement a technology-mediated learning strategy is evaluation or effectiveness studies to determine if the selected technology has the ability to address institutional goals and concerns. The literature in this area looks at “satisfaction” in a way that does not always address actual learning outcomes and overall, there exists a lack of empirical studies showing that the use of instructional technology actually improves learning regardless of the context (Arbaugh, 2002; Buckley, 2002; McClelland, 2001; McGorry, 2003; Neal, 1998). Studies conclude that the full potential of instructional technology is reached only by a full transformation of the learning process, faculty development, and institutional systems (Buckley, 2002; Jamieson, Fisher, Gilding, Taylor, & Trevitt, 2000; Moore, 2002). The research on the effectiveness of distance educa-

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tion or online learning programs shows difficulty with student-instructor communication, lack of socialization both with the instructor and other students, student engagement and interaction, innovation in teaching, and technical difficulties or support (McGorry, 2003; Salisbury, Pearson, Miller, & Marett, 2002). Finally, the instructor’s actual technological expertise (Lea, Clayton, Draude, & Barlow, 2001; Webster & Hackley, 1997) along with their ability to overcome interaction problems (Berger, 1999) has been found to be important both in faculty member’s decisions to adopt instructional technology and in students’ satisfaction and learning outcomes. These findings are at odds with return on investment (ROI) arguments that distributed education can serve large populations without denigrating effectiveness, a trend seen in higher education. Technology has shifted the nature of traditional learning and training by removing the learner from contexts, such as school and workplace. Taylor (2001) has developed a model that describes the shift in distributed learning from linear and printbased to flexible and modular/digital based: • •

•

•

•

The “correspondence model” relies on printbased resources. The “multimedia model” provides learning resources through a variety of media including print. The “tele-learning model” incorporates modes of presentation of materials to include audio or video-conferencing and broadcast TV or radio. The “flexible learning model” requires that students engage in interactive, online computer-mediated resources and activities. The “intelligent flexible learning model” is the next generation model in which the learner accesses learning processes and resources through portals.

Learning through and with learning objects enables the learner to self-direct their experiences

and engage with others for purposes that best support their learning, while utilizing objects that best match their needs. Diaz (2004) notes that the more complex and autonomous the system, the more it allows the learner to manage their own learning, but the higher the degree of technical skills necessary, and the larger the institutional investment. Conversely (or perversely), the more the learner is engaged in making choices and directing learning experiences, the greater the likelihood they will generate knowledge. Personally constructed knowledge is then influenced by the organizational knowledge that shapes our behaviors, values, and norms that we bring to learning or working context. The process of knowledge construction is reflected in the way organizations approach knowledge management. Learner- or worker-generated knowledge is not without limitations and barriers within certain models of knowledge management.

Four Models of Knowledge Management Existing models of knowledge management have emerged from policy and practice. Although the tradition of distributed instructional materials is not new for higher education, the shift toward digitalization has affected the nature of distribution, as well as policy decisions. Learning objects are a relatively new concept with regard to knowledge management, and the idea of re-use and re-purposing has necessitated specific management and ownership considerations. Typically, learning objects originate with ideas generated by faculty members and are created with supports from the university, then distributed through a local or external repository. Rights of ownership and attribution are critical as are permissions to re-use, revise, and maintain the objects. Prelearning object policy has not fully accounted for the unique provisions of reuse. In this evolving context of learning objects, we have identified four models that address control and ownership

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in varying ways: traditional pre-digital, intellectual capital/appropriative, sharing/reciprocal, and contribution-pedagogy.

Traditional Pre-Digital Model The traditional model of ownership in the area of copyright predates technology. Up until the passing of the Digital Millennium Copyright Act of 1998 (DMCA), and perhaps after, long established legal principles grant to employees, such as faculty members, the inherent right of ownership to their inventions (Chew, 1992). Intellectual property policy language, especially in the area of digital works such as learning objects, can sometimes be ambiguous. McMillen (2001) finds that academic custom, the informal principles of university practice, impact copyright ownership in two ways. First, if there is ambiguity in a faculty member’s contract or other written document that expressly assigns copyright ownership, courts may look at custom and usage to determine the university and professor’s intent regarding ownership. In other words, courts could decide to take into account an institution’s established practices in deciding who should retain property rights. Second, if no contract, policy, or written document regarding copyright ownership exists, courts are permitted to use the academic custom and usage within or outside the institution to determine what the parties would have agreed to had they addressed copyright ownership. In Rhoades (1998) examination of the actual ownership of faculty products, he found that, of the contracts analyzed, a majority of them had extensive provision for faculty ownership; in fact, the institution does not always claim ownership, even when it is a “work for hire.” The “conditions” of production or use of resources are pivotal in determining ownership and assigning profits. In her analysis of intellectual property ownership in the institution of higher education in the United States, Chew (1992) reexamines ownership via social tradition and case law. Surprisingly, her

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findings reveal that, despite common assumptions, long established legal principles grant to employees, such as faculty, the inherent right of ownership to their inventions. Faculty members’ claims on their inventions and the enforceability of university policies are unclear. However, as distributed learning technology evolves and requires greater use and infusion of institutional resources, ownership, and control may begin to away from individual creators and contributors and toward resource providers. Further adding to the ownership ambiguity is the vast array of digital products that are being produced within commercial and non-commercial collaborations and partnerships.

Intellectual Capital/Appropriative Model The intellectual capital or appropriative model holds that ownership, control, and maintenance of intellectual property, especially in the area of distributed learning, is important. Under this model, institutional resources expended are carefully monitored and among other factors, become the criteria for ownership and control. Further, the vast majority of higher education institutions’ intellectual property policies are increasingly based on this model (Diaz, 2004). The arrival of technology into the area of copyright has created a new market for products that previously had little or no commercial value. In fact, many copyright sections of intellectual property policies differentiate between digital and non-digital property and contain specific and substantial rights over these economically viable products. The intersection of intellectual property rights, specifically in the area of copyright, and technology in higher education is the realm of distributed learning, including distance education, learning objects, digital repositories, and electronic courseware products. Consistent with previous studies in the area of intellectual property copyright policy transformation and the corresponding commodification of

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educational products (Chew, 1992; Lape, 1992; Packard, 2002; Slaughter & Rhoades, 2004), Diaz (2004) finds that policies are evolving to further address distributed learning products in a variety of ways. Findings indicate that institutions are revising policies to further deal with and capture instructional products. Policies are aligned with the organizational change that is occurring in higher education within a larger context of an information-based economy (Castells, 2000). Additionally, the new instructional model is heavily dependent on information technology in the form of network connectivity, infrastructure and support staff, thus making it resource intensive. Policies reflect this change by mimicking the shift in ownership conditions away from those required in a traditional setting to those required in a high technology setting. Use of institutional resources in the instructional process has been nominal (i.e., secretarial support, libraries), compared to those required now: media specialists, instructional designers, and so on. Ownership terms changed to address the new instructional model, but claims on instructional products have appeared where there were previously none. Institutions are asserting ownership where they previously had not because online courses and course materials present a potential source of revenue from which the institution could benefit. Several explanations exist for this increasingly appropriative behavior. Faculty-developed electronic content and courseware materials (especially in specialized academic areas where the market is deficient) present a potential source of revenue and savings, as the institution will not have to pay costly licensing fees to purchase or utilize externally developed products. Increasing “contracted” education serves the dual purpose of producing salary savings while providing oneon-one attention to students and improving their performance (Twigg, 2000). The appropriation of digital knowledge may also be a preemptive move on behalf of universities that fear faculty members will package their courses and make them avail-

able to multiple markets (while employed at the present institution or after they have left), perhaps in competition with the college or university that employs them.

Sharing/Reciprocal Model The sharing reciprocal model is based on shared value and the exchange of learning objects and other digital materials across organizations and institutions (Diaz & McGee, 2004). The focus here is on the support of learning activities. Individual institutions support the assembly of learning objects, which may be shared across departments but, more commonly, objects are imported from many other places. Table 1 illustrates the many partners that may be involved in these consortia. Organizational support mechanisms and systems moderate costs. Many institutions join consortium in order to create a system for storing and distributing objects in what becomes a mutually beneficial learning object economy (Learning Content eXchange, 2003). Consortia often articulate content and evaluation standardization as a strategy to increase the market value of an object. DRM, Royalty Rights Management (RRM), index, and search functions as well as supporting technologies are collectively addressed and operated through a well-organized consortia initiative. Such collaboration allows members to establish pre-determined policies and procedures that articulate a negotiated value and standard of quality for the objects that are shared. Learning object registries can provide standards and access for institutions that may not be interested in partnerships. One example is the Learning Object Network (LON) (http://www. learningobjectsnetwork.com) that uses Digital Object Identifier (DOI) as the identifier mechanism and collects object metadata and location information so they can direct potential users to the source. Institutions or consortia must determine the degree of access and set policy that sets the rights of the owner of the object. One approach

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Table 1. eLearning Partnerships Organizational partnership EDUCAUSE Corporate Partner Program (http://www.educause.edu/partners/about.html) Massachusetts Institute of Technology DSpace Federation (http://dspace.org) The Fedora Project (http://www.fedora.info/)

to DRM is the Creative Commons Project6 that provides no-cost licenses so that copyright holders can inform potential users about copyright restrictions. Knowledge management systems that can serve consortia provide customizable interfaces that can meet the unique needs and preferences of a group regardless of their funding level or size. For example, EZ Reusable Objects (EZRO) is an open source, free Web application that requires little to no technical expertise to configure and operates to manage learning objects. EZRO is scalable and responds to the specific needs of consortia driven by a variety of goals and directed by institutional policy. The first three models discussed above fail to address the value of knowledge acquisition acquired through learner-object interaction, which should be an expectation and criteria in the learning object economy. Instead, they focus specifically on the exchange of goods in terms of the agreed-upon market value rather than the knowledge value that informs the “buyer” of whether or not, as Demarest would argue, the product “works.” For higher education the value should reside in the object’s actual knowledge value.

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• • • • •

• • • • •

Partners IT professionals (public/private) Technologists Managers Higher education executives Columbia University, Cornell University, Ohio State University, and the Universities of Rochester, Toronto, and Washington Hewlett-Packard MIT Libraries University of Virginia Andrew W. Mellon Foundation Cornell University

Contribution Pedagogy Model The focus of the contribution-pedagogy model is that learners contribute to object development or generate objects themselves, thereby contributing to the knowledge base of the institution. This reflects the shift toward a learning object pedagogy in which learners, not only learn from experience by participating in the generation of the object, but by contributing to the learning of others through object development and re-use. Collis and Striker (2003) suggest that by having learners generate learning objects, and contribute to a course repository that grows with each offering of the course, the burden of producing objects is shifted away from the institution and the instructional process. This results in a variety of benefits: time is saved for the instructor or content-generator, resources are designed by the population for which they are intended by providing a locally better “fit” with the intended audience, learners can contribute and revise objects over time by updating content or presentation, and the tacit knowledge of the learner is transparent and can be shared or studied by the institution (Collis & Winnips, 2002). Laurillard and McAndrew (2003) illustrate the contribution-pedagogy model in their design

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of generic learning activities that shift teaching from a transmission model to a construction model. A design of generic learning activities shifts teaching from a transmission model to a construction model as illustrated by Laurillard’s “Conversational Framework” for learning. This iterative process requires the learner to engage, act, and reflect upon what they know and how they come to learn. An analysis of scalable (individuals or groups) and sustainable (efficient and economic) learning designs address how to design for diversity of learner experiences, goalbased learning, re-use of objects, use of online learning tools for learning outcomes, clear and succinct instructions, and dynamic technology function. Specific recommendations are made for the design of objects to be used in multiple courses. When multiple applications are considered at the design stage, there is an increased likelihood of increased re-use across disciplines. Additionally, objects can be easily re-versioned depending on the needs of new or revised courses and pedagogy is wrapped around objects, activities, and supports. The Sharing/Reciprocal and

Contribution-Pedagogy models impact how value is attributed, estimated, and assigned to learning objects and reflect Thomas and Home’s (2003) Student-centered Route and Freedom Argument for the distribution and access of learning objects that suggests a new economy.

Learning Object Economy Higher education’s new approach to its knowledge products has led to the emergence of a learning object economy. Johnson (2003) notes that the learning object economy has at least five markets of exchange: proprietary, commercial, free, shared, and peer-to-peer. Each of these “markets” has a corresponding culture and has been met with varying degrees of success. He argues that a fully functioning learning object economy would satisfy the needs and requirements of its constituents: market-makers (repository builders), instructors, end users, assemblers, regulators, publishers, resellers, and authors. Figure 2 illustrates the way that various constituents intersect and exchange in this new economy (Johnson, 2003).

Figure 2. Learning object economy (Adapted from Johnson, 2003)

Authors Experts Organizers Faculty

Market Makers Repository Builders Tool Builders

Resellers Market Place Publishers

Assemblers Instructional Designers

Endusers Students Communities of Practice Academic Depts/Disciplines

Regulators

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Technologies, if they resonate and are adopted, can generate an economy that is derived from the value placed on them by a social group. Groups may have different interpretations of the basis of the value. Since learning objects require group collaboration, represent knowledge construction, and are disseminated across populations, there is a high level of mediating variables and processes. Technological systems, if they resonate with the organization and are adopted, can generate an economy that is derived from the value placed on them by a social group. Groups may have different interpretations of value, and since learning objects require group collaboration, represent knowledge construction, and are disseminated across varied populations, a high level of mediating variables and processes exist. Johnson (2003) describes five markets, each with a different exchange approach, in which learning objects operate. These markets—proprietary, commercial, free, shared, and peer-to-peer—are described in Table 2. Each of the aforementioned four knowledge management models (traditional-pre digital, intellectual capital/appropriative, sharing/reciprocal, and contribution pedagogy) intersects with one or more of Johnson’s learning object economy markets. For instance, the traditional-pre digital, intellectual capital/appropriative models exist within the value system of the proprietary and commercial markets. The last three markets, free, shared, and peer-to-peer, also exist in higher education settings. It is possible for appropriative and non-appropriative models to coexist, for instance

within a college or department. Each market satisfies those constituents’ needs and is aligned with a set of culture-specific values. Implicit needs must also be met in order for exchange to flourish. For instance, learning objects must be credible or carry some quality assurance regardless of the system within which they operate. Although the literature (Hart, 2004; Kidwell, Vander Linde, & Johnson, 2000; Norris et al., 2003) suggests a maturing of knowledge management practices that have resulted in a myriad of systems, the learning object economy in all markets is still weak at best. As Johnson (2003) points out, the current level of activity has not yet reached a “tipping point.” The solution, he postulates, is an “economy of content in which individuals and organizations can acquire, adapt, and repurpose content” (p.7). Table 3 presents a summary of Johnson’s drivers, enablers, and mediators to a thriving learning object economy. Several of these drivers, enablers, and mediators are present in the models discussed earlier and suggest some explanation for the under use of learning objects. For instance, higher education intellectual property policies governing the control and ownership of digital instructional products or learning objects are often structured in such a way as to inhibit development and sharing outside of the originating institution (Diaz, 2004). This type of behavior, evident in the Intellectual Capital/Appropriative Model, also prohibits the sharing of resources and distribution of costs: mediators in the economy. The Appropriative Model and other

Table 2. Learning object economy and the five markets Market Proprietary Commercial Free Shared Peer-to-peer

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Product example Private company training repository E-learning companies selling learning objects MERLOT or the Educational Learning Object Exchange Higher education LO consortia Sharing systems between higher education institutions

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Table 3. The learning object economy: Drivers, enablers, and mediators (Adapted from Johnson, 2003) Drivers Enablers Mediators

Definition Knowledge, productivity, competition, readiness, infrastructure Learning technologies, learning design, standards Resources, policies, perceived value

models discussed are limited, to some extent, by their social context. Each is operating within the boundaries of their organizational context and corresponding values and is thus limited by those constraints. In response to these limitations, we propose a new relativist model. We argue that in order for a learning object economy to succeed, it must be able to take advantage of and utilize its drivers, enablers, and mediators independently of a social or organizational context.

Open Knowledge Model Knowledge sharing and re-construction with intellectual property rights attribution and learnerowner intellectual property rights are necessary in an increasingly globalized and distributed learning ecosystem.7 The Open Knowledge Model embodies trends in a variety of disciplines: computer science (see OKI and OSPI), education (see McGee & Robinson, 2004), science (see Cottey, 2003), and social justice (see Open Knowledge Network) in that it utilizes a relativist construction and accommodates cross-institutional cultures and beliefs about learning technologies, the construction of knowledge across systems and institutions, as well as the trend toward learner-centered e-learning, disaggregated and re-aggregated learning objects, and negotiated intellectual property rights.

Higher education example Faculty-, student-, staff-produced knowledge; L/CMSs; wireless learning environments. A menu of learning technologies available to educators; learning technologists as support staff to enhance learning and teaching functions. Learning technologies centers; flexible and adaptable intellectual property policies.

We build on Thomas’ and Demarest’s conceptual frameworks in an attempt to address the emergent model of knowledge management in higher education that reflects current beliefs about the learner, the function of the institution, the trend toward knowledge generation, and the evolution of existing models. In that the function, definition, and value of technology are relative to organizational culture and values, we assert that no organizational position is more or less valid than another (Wescott, 2001). The Open Knowledge Model provides for this caveat. This is not to say that value is not shared across higher education systems, but rather that individual organizations and their members have come to contribute to the value given to the knowledge that is generated within them. The first component of the Open Knowledge Model addresses how the culture and actions of higher education tacitly and explicitly determine the value, purpose, and role of knowledge for the institution at large. The culture of each higher education institution determines the value and use of knowledge, rather than the technology. This is clearly reflected in institutional efforts such at MIT’s OpenCourseWare project in which course syllabi and materials are accessible to all in an effort to support their “mission to advance knowledge and education, and serve the world in the 21st century. It is true to MIT’s values of excel-

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lence, innovation, and leadership” (MIT, 2004). MIT has chosen to share intellectual property that represents the values, norms, and standards of learning of their unique and specific mission. We see such efforts as supporting the inherent purpose of higher education: as a primarily generator of bodies of knowledge that should be made freely available to the public. Traditional models of knowledge dissemination that are tied to processes of tenure and promotion (peer-referred journals with limited circulation) restrict knowledge access. In the Open Knowledge Model, intellectual property is digitized and distributed with rigorous standards of review, but made available to anyone who is interested, rather than a privileged few through repositories (Crow, 2002). Traditionally, intellectual property rights policy has indicated the market value higher education has placed on learning objects, however, documented knowledge acquisition (through learner generation) and use of learning objects (through tracking) is a more authentic indicator of value. In the Open Knowledge Model, intellectual property rights are determined by the generator and negotiated by the end user who may choose to re-purpose the content through licenses allowed through systems. The growing number of repositories and referatories indicates that learning objects are a valid and valued knowledge source both within and outside of any one institution. Additionally, we propose that knowledge value is reflected in use and re-use of learning objects. The second area of focus deals with the ways in which knowledge is created, embodied, disseminated, and used in higher education; the relationship between knowledge and technological innovations; and the relationship between knowledge, innovations, and performance standards that higher education requires in order to meet its strategic objectives. Higher education, as an institution, embodies cultures that are both shared and not shared. For instance, sharing and collaboration in a learning object economy can occur within and across disciplines, departments,

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and the institution as a whole. In this sense, the academic setting is unique in that cross-cultural/ organizational generation, sharing, and re-purposing, is possible and brings the added benefit of greater innovation and diffusion of knowledge. Further, repositories and referatories, as technological systems, make this possible as learning objects grow and become more meaningful with use and reuse. With successful cross-pollination comes increased funding; consortia and leveraged resources and capital, standardization by industry in accordance with established values to support reuse. The third area of focus deals with the strategic and material commercial benefits that higher education expects to gain from more effective knowledge management practices and performances. These may include increased revenue, prestige, partnerships, cross-organizational fertilization, and higher skilled faculty and graduates. Several factors have contributed to the development of knowledge management. The literature in the area of globalization in higher education points to information technology, organizational change, and productivity growth (Castells, 1997, 2000; Tiffin & Rajasingham, 2003). The development of new intellectual property policies, and the extensive revision of existing ones (Olivas, 1994), is one signal of the organizational transformation and the effort to harness productivity to the benefit of the institution. Globalization, increased competition among non-profit and for-profit educational entities, and changes in funding structures has all contributed to changes in the way higher education institutions deliver services and leverage their instructional products. The utilization of distributed learning technologies and systems has several benefits for the academy: increased research productivity, generation of tuition revenue via increased access, institutional acquisition of instructional products, and improved learning. While some of these outcomes are yet unproven, they are well documented in the language that surrounds policy. Several

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Table 4. Stages of organizational learning Precipitating Jolts



Learning Stage I

    

Learning Stage II Diffusion Institutional Copyright Policy Transformation

        

Proliferation of information technology (IT) in higher education (HED) Increased entrepreneurial behavior in HED Increased competition or economic pressure Emerging HED IT profession Established HED entrepreneurial behavior (patents) Collaborative HED/IT professional organizations (EDUCAUSE) Elite organizational behavior (MIT’s OKI, DSpace) Higher education develops L/CMSs Current technology is expensive and insufficient Organizations seek to “retain” knowledge Social consensus via organizational leaders (in process) Lower level orgs mimic behavior Whole policy revisions Addendums to existing policies Instructional technology/software clauses

studies have suggested higher education’s move toward commercializing instructional products (Anderson, 2001; Slaughter & Rhoades, 2004; Welsh, 2000). One can speculate on what has prompted such activity in this area. Organizational learning theory tells us that a number of precipitating jolts, both external and internal to the organization, can prompt such changes (see Table 4). Such jolts can come from the changing economy, changing technology, and pressure to improve learning outcomes (Castells, 2000). The Open Knowledge Model represents the drivers of knowledge management: the methods for management and the conceptual framework that guides processes of knowledge generation. It supports a new economy based on authentic knowledge value in which human capital is embraced and recognized as the core of educational institutions and that which higher education can best support and sustain.

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McMillen, J. (2001). Intellectual property: Copyright ownership in higher education, university, faculty, & student rights. Asheville, NC: College Administration Publications, Inc. Mentkowski, M. & Associates. (2000). Learning that lasts: Integrating learning, development, and performance in college and beyond. San Francisco: Jossey-Bass. Meyer, K. (2002). Quality in distance learning. ASHE-ERIC Higher Education Report, 29(4), 1-121. MIT (2004). OpenCourseWare. Retrieved from http://ocw.mit.edu/index.html Moore, M. & Kearsley, G. (1996). Distance education: A systems view. Wadsworth Publishing. Neal, E. (1998). Using technology in teaching: We need to exercise healthy skepticism. The Chronicle of Higher Education, B4. Nichols, R. (1996). The value of education and training. Discourse, 2(1), 13. Norris, D., Mason, J., & Lefrere, P. (2003). A revolution in the sharing of knowledge: Transforming e-Knowledge. Ann Arbor, Michigan: Society for College and University Planning. Olivas, M. (1992). The political economy of immigration, intellectual property, and racial harassment: Case studies of the implementation of legal changes on campus. Journal of Higher Education, 63, 570-598. Open Knowledge Initiative (OKI) (2004). http:// web.mit.edu/oki/index.html

Perdue, P. (1994). Technological determinism in agrarian societies. In M.R. Smith & L. Marx, (Eds.), Does technology drive history? The dilemma of technological determinism. Cambridge, MA: MIT Press. Por, G. (1997). Designing knowledge ecosystems for communities of practice. Paper presented at the Advancing Organizational Capability via Knowledge Management Conference, Los Angeles, California. Retrieved February 10, 2004, from http://www.co-i-l.com/coil/knowledge-garden/dkescop/index.shtml Raybould, B. (2002). Building performance-centered Web-based systems, information systems, and knowledge management systems in the 21st century. In A. Rossett (Ed.), The ASTD e-learning handbook, 338-353. New York: McGraw-Hill. Reeves, T. (2002). Evaluating what really matters in computer-based education. Retrieved June 15, 2004, from http://www.educat io nau.ed u.au/archives/cp/reeves.htm Rhoades, G. (1998). Managed professionals: Unionized faculty and restructuring academic labor. Albany: State University of New York Press. Robson, R. (2001). All about learning objects. Retrieved June 15, 2004, from http://www.eduworks. com/LOTT/tutorial/learningobjects.html Rossett, A. & Donello, J. (1999). Knowledge management for training professionals. Retrieved February 3, 2004, from http://defcon.sdsu.edu/1/ objects/km/map/index.htm

Open Source Portfolio Initiative (OSPI) (2004). http://www.theospi.org/

Rossett, A. & Marshall, J. (1999). Signposts on the road to knowledge management. In K.P. Kuchinke (Ed.), In Proceedings of the 1999 AHRD conference: Vol. 1 (pp. 496-503). Baton Rouge, LA: Academy of Human Resource Development.

Packard, A. (2002). Copyright or copy wrong: An analysis of university claims to faculty work. Communication Law and Policy, 7, 275-315.

Salisbury, W., Pearson, R., Miller, D., & Marett, L. (2002). The limits of information: A cautionary tale about one course delivery experience in

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the distance education environment, e-Service Journal, 1(2). Sieczka, K. (n.d.). Workplace training versus traditional classroom training. Retrieved February 16, 2004, from http://www.ideamar kete rs.com/library/article.cfm?articleid=25789 Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. (2003). Teaching and learning at a distance: Foundations of distance learning (2nd ed.). Upper Saddle, NJ: Pearson Education, Inc. Slaughter, S. & Rhoades, G. (2004). Academic capitalism in the new economy. Baltimore: Johns Hopkins Press. Smith, M. & Marx, L. (Eds.) (1994). Does technology drive history: The dilemma of technological determinism. Cambridge, MA: MIT Press. Solmon, L. & Wiederhorn, J. (2000). Progress of technology in the schools 1999: Report on 27 states. Milken Foundation. Retrieved February 12, 2004, from http://www.mff.org/publications/ publications.taf?p age=277 Sørensen, K. (1996). Learning technology, constructing culture: Socio-technical change as social learning. STS working paper no 18/96, University of Trondheim: Centre for technology and society. Retrieved June 15, 2004, from http://www. rcss.ed.ac.uk/SLIM/public/phase1/knut.html Taylor, J. (2001). Fifth generation distance education. Higher Education Series, 40. Retrieved June 15, 2004, from http:// www.dest.gov.au/highered/ hes/hes40/hes40.pdf Thomas, G. & Home, T. (2004). Using ICT to share the tools of the teaching trade: A report on open source teaching. Becta ICT Research. Retrieved April 9, 2004, from http://www.see veaz.mys chools.net/Bestpractice/OSDDB6.pdf Thomas, R. (1994). What machines can’t do: Politics and technology in the industrial enterprise. Berkeley: University of California Press.

Tiffin, L. & Rajasingham, L. (2003). Global virtual university. London; New York; Canada: Routledge. Twigg, C. (2000). Who owns online courses and course materials: Intellectual property policies for a new learning environment. The Pew Learning and Technology Program, Center for Academic Transformation at Renssalaer Polytechnic Institute. Webster, J. & Hackley, P. (1997). Teaching effectiveness in technology-mediated distance learning. Academy of Management Journal, 40, 1282-1309. Welsh, J. (2000). Course ownership in a new technological context: The dynamics of problem definition. The Journal of Higher Education, 71(6), 668-699. Wescott, E. (2001). The Internet encyclopedia of Philosophy. Retrieved March 18, 2004, from http://www.iep.utm.edu/r/relativi.htm Wiley, D. (2000). Connecting learning objects to instructional design theory: A definition, a metaphor, and a taxonomy. The instructional use of learning objects: Online version. Retrieved June 15, 2004, from http://www.reusability.org/read/ Wiley, D. (2003). Learning objects: Difficulties and opportunities. Retrieved June 15, 2004, from http://wiley.ed.usu.edu/docs/lo_do.pdf Winner, L. (1977). Autonomous technology: Technics-out-of-control as a theme in political thought. Cambridge, MA: MIT Press.

ENDNOTES 1

“Knowledge management involves recognizing, documenting, and distributing the explicit and tacit knowledge resident in an organization” (Rossett & Marshall, 1999).

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2

3

4

A learning object economy requires that individual objects are created and shared across institutions (Johnson, 2003). Technology drives change and events. In teaching and learner this means that pedagogy and learner’s actions are determined by technology and indeed effect changes in practice. The authors see this more as a result of technological drift (Winner, 1997) through which organizations have been inattentive to the determinism that has become enculturated (see Perdue, 1994). In our view, technological relativism means that the function, definition, and value of technology are relative to the organizational culture and values and the beliefs about the value within the higher education community. Additionally, we assert that no organizational position is more or less valid than another (Wescott, 2001), but equal consideration must be given to each value position. Additionally, individuals choose what and how they use and adapt technologies to their own purposes (Chandler, 1996).

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Learning objects typically are parts of a larger course or unit of study. Aggregation involves combining objects to create a scope of learning content. Creative Commons (2004) is a free licensing service that “uses private rights to create public goods: creative works set free for certain uses. Like the free software and open-source movements, our ends are cooperative and community-minded, but our means are voluntary and libertarian. We work to offer creators a best-of-both-worlds way to protect their works while encouraging certain uses of them—to declare “some rights reserved.” An ecosystem is a combination of systems that interact to support the survival and generation of organisms that exist within it. The authors see the tools, resources, people, and experiences accessible to the higher education student as constituting a digital learning ecosystem that contributes to a digital knowledge ecosystem (Por, 1997).

This work was previously published in Knowledge Management and Higher Education: A Critical Analysis, edited by A. Metcalfe, pp. 147-181, copyright 2006 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.14

Innovations for Online Collaborative Learning in Mathematics Rodney Nason Qyeensland University of Technology, Australia Earl Woodruff OISE-University of Toronto, Canada

INTRODUCTION The field of computer-supported collaborative learning (CSCL) has been growing in a number of areas and across a number of subjects (Koschmann, 1996; Koschmann, Hall, & Miyake, 2002; Wasson, Baggetun, Hoppe, & Ludvigsen, 2003). One of the most promising pedagogical advances, however, for online collaborative learning that has emerged in recent years is Scardamalia and Bereiter’s (1996) notion of knowledge-building communities. Unfortunately, establishing and maintaining knowledge-building communities in CSCL environments such as Knowledge Forum® in the domain of mathematics has been found to be a rather intractable problem (Bereiter, 2002b; Nason, Brett, & Woodruff, 1996). In this chapter, we begin by identifying two major reasons why computer-supported knowledge-building com-

munities in mathematics have been difficult to establish and maintain. 1.

2.

The inability of most “textbook” math problems to elicit ongoing discourse and other knowledge-building activity Limitations inherent in most CSCL environments’ math representational tools

Therefore, in this chapter, we argue that if mathematics education is to exploit the potentially powerful new ways of learning mathematics being provided by online knowledge-building communities, then the following innovations need to be designed and integrated into CSCL environments: 1.

Authentic mathematical problems that involve students in the production of math-

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovations for Online Collaborative Learning in Mathematics

2.

ematical models that can be discussed, critiqued, and improved Comprehension-modeling tools that (a) enable students to adequately represent mathematical problems and to translate within and across representation modes during problem solving, and (b) facilitate online student-student and teacher-student hypermedia-mediated discourse.

Both of the above innovations are directed at promoting and sustaining mathematical discourse. The requirement that the mathematical problems need to be authentic ensures that the students will have the contextual understanding necessary to promote a discussion about the mathematical models. Comprehension-modeling (Woodruff & Nason, 2003) further promotes the discourse by making student understanding yet an additional object for discussion. Most textbook math problems do not require multiple cycles of designing, testing, and refining (Lesh & Doerr, in press), and therefore do not elicit the collaboration between people with special abilities that most authentic math problems elicit (Nason & Woodruff, 2004). Another factor that limits the potential of most textbook math problems for eliciting knowledge-building discourse is that the answers generated from textbook math problems do not provide students with much worth discussing (Bereiter, 2002b). Another factor that has prevented most students from engaging in ongoing discourse and other mathematical knowledge-building activity within CSCL environments is the limitations inherent in their mathematical representational tools (Nason et al., 1996). Most of these tools are unable to carry out the crucial knowledge-building functions of (a) generating multiple representations of mathematical concepts, (b) linking the different representations, and (c) transmitting meaning, sense, and understanding. Two clear implications can be derived from this review of the previous research. First is that

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different types of mathematical problems that have more in common with the authentic types of mathematical problems investigated by mathematics practitioners than most existing types of textbook math problems need to be designed and integrated into CSCL environments. Second, a new generation of iconic mathematical representation tools also needs to be designed and integrated into CSCL environments. In order to differentiate these tools from previous iconic math representation tools, we have labeled our new generation of tools as comprehension-modeling tools. Each of these two issues will be discussed in the next two sections of this chapter.

AUTHENTIC MATH PROBLEMS Credence for the viewpoint that the integration of more authentic types of mathematical problems into CSCL environments may lead to conditions necessary for the establishment and maintenance of knowledge-building activity is provided by the findings from two recent research studies conducted by the coauthors. Although both of these studies were situated within elementary schools, it should be noted that the same math problems used in these research studies could also be used within online CSCL environments to facilitate the development of mathematical subject-matter knowledge in high school students and preservice teacher-education students. Therefore, we believe that the findings from these two studies have much relevance for the establishment and maintenance of math knowledge-building communities not only in elementary schools, but also in secondary school and higher education institutions, too. In a series of research studies, Nason, Woodruff, and Lesh have been investigating whether having students engage in model-eliciting mathematical problems with collective discourse mediated by Knowledge Forum would achieve authentic, sustained, and progressive online knowledge-building activity. In this section, we

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focus on two of these research studies. In the first of the research studies (Nason & Woodruff, 2004), 21 students in a Grade-6 class at a private urban Canadian school for girls were asked to devise an alternative model that could be used for ranking nations’ performance at the Olympic games that de-emphasized the mind-set of “gold or nothing.” In the second research study (Nason, Woodruff, & Lesh, 2002), 22 students in another Grade-6 class at the same school were asked to build a model that could help rank Canadian cities in terms of quality of life. In both studies, the students were initially presented with an article setting the scene for the model-eliciting activity and a set of focus questions based on the article. After this 45-minute warm-up activity, the students went through the phases of (a) initial model building (Phase 1, one session of 45 minutes), (b) sharing of initial models (Phase 2, one session of 45 minutes), and (c) iterative online critiquing and revision of models within Knowledge Forum (Phase 3, four sessions of 45 minutes). The sharing of the initial models in Phase 2 was done face to face within the classroom. After the face-to-face sharing of the initial models had been completed, each group attached their math model to a Knowledge Forum note where it could be viewed and evaluated by other participants within the online CSCL community. During the online critiquing and revision of models in Phase 3, Knowledge Forum provided the contexts and scaffolds for intergroup online discourse. Five important elements of activity consistent with Scardamalia’s (2002) principles of knowledge building were observed during the course of these two studies. 1. 2.

Redefinition of the problems, which highlights Scardamalia’s principles of improvable ideas and rising above Inventive use of mathematical tools, which highlights Scardamalia’s principle of improvable ideas

3.

4.

5.

Posing and exploration of conjectures, which highlights Scardamalia’s principles of idea diversity and knowledge-building discourse Collective pursuit of the understanding of key mathematical concepts, highlighting Scardamalia’s principles of community knowledge and collective responsibility Incremental improvement of mathematical models, which highlights Scardamalia’s principle of improvable ideas

Much of the success in establishing and maintaining the online mathematics knowledgebuilding communities in these two studies can be attributed to the rich context for mathematical knowledge-building discourse provided by the model-eliciting problems. In both problems, students were required to produce a mathematical model for issues that the students found meaningful and relevant. Therefore, they were willing to proceed through multiple cycles of developing, evaluating, and revising their models. This process of proceeding through multiple cycles encouraged much online discourse between the groups in each classroom. The model-eliciting problems also had many different possible solutions. Because of this, there was much heterogeneity in the initial models produced by the groups of students. In order to understand other groups’ models and also to explain their own model to other groups, each group had to engage in much iterative online discourse with other groups. During this discourse, they had to ask good questions, propose how other groups’ models could be improved, and elaborate on and/or modify their explanations. Finally, the models themselves provided students with artifacts that could be discussed, evaluated, compared, and improved (just like the artifacts built by mathematics practitioners). Unlike the answers produced in most textbook problems that tend to only enable discourse about correctness (or incorrectness), the models produced from the model-eliciting problems were artifacts that

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could be evaluated and discussed in terms of not only correct usage of mathematical concepts and processes, but also in terms of subjective, nonmathematical factors.

COMPREHENSION MODELING Evidence to support the notion that the inclusion within a CSCL learning environment of comprehension-modeling tools can do much to facilitate knowledge-building discourse has been provided by research during the development of CHiLE (constructivist hypermedia interactive learning environment; Charles & Nason, 2000). CHiLE situates the learning of fractions in the context of a restaurant in which the children play the role of a waiter and are asked to partition and share out equal objects such as pizza and apple pies to customers sitting at the restaurant table (see Figure 1). The number of customers sitting at the table and the number of objects to be partitioned and shared can be varied. CHiLE provides the children with five different slicers (a knife-like tool) that enable objects to be cut in halves, thirds, fifths, sevenths, and ninths. With these slicers,

Figure 1. Screen shot of the problem students are attempting to solve

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the children can also create other fractions such as quarters (by halving the halves) and sixths (by halving the thirds). CHiLE enables children to generate multiple representations of fraction problems and provides the iconic tools for facilitating synchronous hypermedia-mediated, knowledge-building, child-child and teacher-child discourse. CHiLE, however, has an added facility that enables teachers and children to also engage in online asynchronous knowledge-building discourse. With CHiLE, children are able to make an animated sequence of slides with accompanying text that not only enables them to communicate the solution to a fraction problem, but also the process (or model) that was used to generate the solution. CHiLE thus uses hypermedia as a way to animate and promote mathematical discourse: The strategy (or model) is reified on the screen via the iconic representation, the animation shows the “story,” and everything is recorded, thus promoting reflection and revisitation. This is illustrated below in a series of figures (see Figures 1 to 4) generated by two 8-year-old children who had been asked to share one pizza fairly between three people.

Figure 2. Early screen shot of students’ initial steps toward a solution

Innovations for Online Collaborative Learning in Mathematics

Nason and Woodruff (2004) have found that online knowledge-building discourse facilitated by CHiLE operates on two different levels. First, the discourse can occur at the global level and focus on the overall strategy (or model). For example, another group of students, when given the same problem as in Figure 1, decided to slice the pizza into sixths and give two sixths to each person. After looking at one another’s models, the two groups of students engaged in robust online debate about which was the “better” strategy (and solution). During this debate, they were able to identify similarities and differences between the strategies, but more importantly, build conceptual links between thirds and sixths. Second, the discourse can occur at the language level. For example, there can be discourse about the best language to insert in a sequence of slides. This discourse often provides the contexts for the introduction of formal mathematical language as a more precise way of communicating meaning within mathematical contexts than natural language. The hypermedia facilities provided by CHiLE enabled children to engage in online knowledge-

Figure 3. Screen shot midway toward a solution

building discourse synchronously and asynchronously via iconic, natural language, and/or mathematical language representations. CHiLE thus provided one of the most important dynamics that Scardamalia (2002) identified as being a technical determinant of knowledge building and knowledge advancement within online CSCL environments. CHiLE also provided two other dynamics that Scardamalia indicated were technological determinants of knowledge building and knowledge advancement. First, there is her notion that computer technology should include facilities for bringing together different ideas in such a way that productive use can be made of diversity. The iconic tools provided by CHiLE met this criterion by enabling children to readily 1. 2.

Generate diverse solutions and solution processes to the same mathematics problem, and Communicate both synchronously and asynchronously via the iconic models, natural and mathematical language, and mathematical symbols their diverse solutions and solution

Figure 4. Screen shot of students’ proposed solution

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processes to others within the online learning community. Scardamalia also indicated that the computer technology also should provide children with the opportunity and the means to make revisions. Without this, she claimed that children will not be able to work continuously to improve the quality, coherence, and the utility of their ideas. One of the major qualities of CHiLE is the ease with which children can revisit and revise the sequences of slides and their accompanying text. The comprehension-modeling tools provided by CHiLE thus promoted idea diversity, improvable ideas, and knowledge-building discourse, three of the sociological and technological determinants of knowledge building identified in Scardamalia (2002).

FUTURE TRENDS The research in progress reported in the previous two sections indicates that the inclusion of model-eliciting problems and of comprehension-modeling tools (such as CHiLE) into online collaborative learning environments both have the potential to facilitate the establishment and maintenance of online collaborative mathematics knowledge-building communities in schools and higher education institutes. However, two important issues still need to be addressed before this potential can be realized. First, the set of principles for informing the design of model-eliciting problems developed by Lesh and Doerr (2003) need to be modified to take cognizance of the differences between online collaborative and traditional classroom environments. Second, the theoretical framework informing the design of comprehension-modeling tools needs to be modified to include not just ideas from research into external mathematical representations that were used to inform the design of CHiLE (e.g., Kaput, 1992; Olive, 2000), but also ideas from

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research conducted in other areas such as online collaboration (e.g., Klopfer & Woodruff, 2002), cognitive science, and multimedia learning (e.g., Mayer, 2001; Sweller, 1999). Both these issues are the foci of a series of design experiments (Bereiter, 2002a) currently being conducted by Nason and Woodruff.

CONCLUSION In this chapter, we identified two major reasons why mathematics educators have had limited success in establishing and maintaining online knowledge-building communities. 1.

2.

The inability of most textbook math problems to elicit ongoing discourse and other knowledge-building activity Limitations inherent in most CSCL environments’ math representational tools

We then proposed how these two problems could be overcome, namely, by the inclusion of mathematical problems that children can analyze and describe through a mathematical model (such as the steps necessary to divide two pizzas among three people) and comprehension-modeling tools (that allow observers to later see how the students have solved the problem) within CSCL environments. We have targeted our discussion within one CSCL groupware product called Knowledge Forum, but we believe the same principles will apply to any online computer-supported collaborative learning system. To that end, we argued that the development of model-eliciting problems suitable for use in online CSCL environments and of comprehension-modeling tools is being restricted by the lack of adequate theoretical frameworks to inform the research and development of these two types of artifacts. Therefore, we have proposed that the development of adequate theoretical frameworks to inform the design of

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these two types of artifacts should be a major research priority in this field.

REFERENCES Bereiter, C. (2002a). Design research for sustained innovation. Cognitive Studies, Bulletin of the Japanese Cognitive Science Society, 9(3), 321-327. Bereiter, C. (2002b). Education and mind in the knowledge age. Mahwah, NJ: Erlbaum. Charles, K., & Nason, R. A. (2000). Towards the specification of a multimedia environment to facilitate the learning of fractions. Themes in Education, 1(3), 263-288. Kaput, J. J. (1992). Technology and mathematics education. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 515-556). New York: Macmillan. Klopfer, E., & Woodruff, E. (2002). The impact of distributed and ubiquitous computational devices on the collaborative learning environment. Proceedings from the Annual CSCL Conference, Boulder, CO. Koschmann, T. (Ed.). (1996). CSCL, theory and practice of an emerging paradigm. Mahwah, NJ: L. Erlbaum. Koschmann, T., Hall, R., & Miyake, N. (Eds.). (2002). CSCL2: Carrying forward the conversation. Mahwah, NJ: L. Erlbaum. Lesh, R., & Doerr, H. (2003). Foundations of a models and modelling perspective on mathematics teaching, learning and problem solving. In H. Doerr & R. Lesh (Eds.), Beyond constructivism: A models and modelling perspective on mathematics learning, problem solving and teaching. Mahwah, NJ: Erlbaum. Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press.

Nason, R. A., Brett, C., & Woodruff, E. (1996). Creating and maintaining knowledge-building communities of practice during mathematical investigations. In P. Clarkson (Ed.), Technology in mathematics education (pp. 20-29). Melbourne: Mathematics Education Research Group of Australasia. Nason, R. A., & Woodruff, E. (2004). Online collaborative learning in mathematics: Some necessary innovations. In T. Roberts (Ed.), Online learning: Practical and theoretical considerations (pp. 103-131). Hershey, PA: Idea Group Inc. Nason, R. A., Woodruff, E., & Lesh, R. (2002). Fostering authentic, sustained and progressive mathematical knowledge-building activity in CSCL communities. In B. Barton, C. Irwin, M. Pfannkuch, & M. O. J. Thomas (Eds.), Mathematics education in the South Pacific (Proceedings of the Annual Conference of the Mathematics Education Research Group of Australasia, Auckland, pp. 504-511). Sydney, Australia: MERGA. Olive, J. (2000). Computer tools for interactive mathematical activity in the elementary school. International Journal of Computers for Mathematical Learning, 5(3), 241-62. Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith (Ed.), Liberal education in a knowledge society (pp. 67-98). Chicago: Open Court. Scardamalia, M., & Bereiter, C. (1996). Adaptation and understanding: A case for new cultures of schooling. In S. Vosniadou, E. De Corte, R. Glaser, & H. Mandel (Eds.), International perspectives on the psychological foundations of technology-based learning environments (pp. 149-165). Mahwah, NJ: Lawrence Erlbaum Associates. Sweller, J. (1999). Instructional design in technical areas. Melbourne: ACER. Wasson, B., Baggetun, R., Hoppe, U., & Ludvigsen, S. (Eds.). (2003). CSCL2003: Community

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events, communication and interaction. Bergen, Norway: University of Bergen.

CSCL: Acronym for computer-supported collaborative learning.

Woodruff, E., & Nason, R. (2003). Math tools for knowledge-building and comprehension modeling in CSCL. In B. Wasson, R. Baggetun, U. Hoppe, & S. Ludvigsen (Eds.), International Conference on Computer Support for Collaborative Learning, CSCL 2003: Community Events, Communication and Interaction (pp. 31-34). Bergen, Norway: University of Bergen.

Knowledge Building: Production and improvement of knowledge objects that can be discussed, tested, compared, hypothetically modified, and so forth, and not simply the completion of school tasks.

KEY TERMS Comprehension-Modeling Tools: Math representation tools that enable users to (a) generate multiple representations of mathematical concepts and processes, (b) dynamically link the different representations, (c) communicate the mathematical ideas they have constructed, and (d) make movie-like sequences of animation slides that enable others to replay the process used to generate the solution. Computer-Supported Collaborative Learning: collaborative learning mediated by computers.

Knowledge Forum ®: A single, communal multimedia database designed to facilitate computer-supported collaborative learning. Mathematical Representations: concrete, pictorial, and symbolic models used to represent mathematical ideas. Model-Eliciting Problems: Mathematical problems that involve producing models for constructing, describing, explaining, manipulating, predicting, and controlling complex systems (Lesh & Doerr, 2003). Problem Solving: Situation involving an initial state, a goal (or solution) state, and a blockage between the initial and goal states that requires the construction of new knowledge to proceed from the initial to the goal state.

This work was previously published in the Encyclopedia of Information Science and Technology, Volume 3, edited by Mehdi Khosrow-Pour, pp. 1529-1534, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.15

Strategic Design for Web-Based Teaching and Learning: Making Corporate Technololgy Systems Work for the Learning Organization Brian Corbitt RMIT University, Australia Dale Holt Deakin University, Australia Stephen Segrave Deakin University, Australia

Abstract Deakin University has established and integrated a major, corporate technology infrastructure to unify and enhance its on‑campus and distance education. This environment is called Deakin Online. Efforts to realize its potential for creating enduring teaching and learning benefits are understood in the context of the University’s commitment to “relevance, respon‑ siveness and innovation.” How are these values and benefits realized in an evolving, educational enterprise using the new digital, corporate technologies and new concepts of organizational structure and func‑

tion? We argue for the transforming influence of a new academic teacher role, new forms of academic development and open collegiality. Moreover, changes in role and process need to be grounded in systemic, organization‑wide and program‑wide approaches to designing and working within comprehensively conceived, contemporary learning environments. We argue for system‑wide education design, situating e‑learning within broader curricular and pedagogical concerns to create enduring benefits in the learning environments of higher education.

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Strategic Design for Web-Based Teaching and Learning

INTRODUCTION Deakin University, as with so many other universities nationally and internationally, has established in the last 5 years an institution-wide approach to enhancing its distance education and on-campus education through networked, Web-based technologies. The establishment of the Deakin Online campus, supported by a suite of integrated corporate technologies, has been progressively implemented over this time. There has been a much needed focus on putting in place the necessary corporate infrastructure requiring the acquisition, deployment and development of an institutional gateway, portal, learning management system (LMS), content management system, synchronous communication system, and streamed audio and video solutions. The drive to establish the infrastructure was based on a range of educational, competitive advantage, cost, commercial and legal concerns. Various institutional stakeholders have different legitimate needs and interests in supporting the various component technologies constituting the University’s enterprise-level solution. With so many technology developments, so many interests and so many possible benefits to be obtained through this large organizational investment, it can be easy to lose sight of the particular perspectives of the University’s most significant constituency—academic teaching staff and their students. The focus can inadvertently be on products and short-term training needs. While necessary, this is not a sufficient condition for maximizing corporate technology potentials, and such a focus holds all of the attendant dangers of what we have called “product centricism” (Corbitt, Holt, & Segrave, 2004). As with many universities now in a similar position, the enduring teaching and learning value anticipated from an investment in corporate technologies must be realized, but realized in a Deakin

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way for Deakin staff and Deakin students. This represents a critical challenge to universities. It requires ongoing significant change in the role of the academic teacher, while still recognizing the centrality and criticality of the role. Academic teachers’ agency—vis-a-vis other internal and external parties with a stake in educating their students—must still be respected. In this chapter, we argue that new forms of academic collegiality are required, and that institutions, which are able to cultivate such powerful forms of engagement, will excel in designing quality learning environments and therefore differentiate themselves in the market. Such differentiation does not result from the procurement of technology infrastructure alone. Moreover, these forms need to be open to the contributions of others and based on broader systemic, programmatic concerns. Designing for the new learning environments requires a student-centered, learning outcomes approach that sees programs of study as coherent, integrated educational experiences. Therefore, we argue that a new form of education design thinking is also required as a basis for curriculum review and renewal, and appropriate forms of professional development. This strategic education design enterprise requires expansive, peripheral curriculum design, where a Web of interconnections can be mapped within and across units, year levels, programs of study and faculty/ school offerings in the areas of generic student attributes, assessment strategies, and the use of various media and technologies. We believe that a systems-based education design approach is the key to help unlock the teaching and learning value of the corporate technologies for universities. It is both in philosophy and process, we believe, a critical orientation for the university as a learning organization wishing to continuously improve its collective learning and performance in the new digital knowledge era.

Strategic Design for Web-Based Teaching and Learning

NEw VISIONS FOR ONLINE TEACHING AND LEARNING IN THE E-KNOwLEDGE AGE This is a case study of an Australian University and its attempts to move towards what Taylor (2001) describes as Fifth Generation models of open and distance education, catering flexibly and responsively to the needs of a diverse and broad range of learners studying across multi campuses and off campus (both nationally and internationally) using an integrated suite of institutionally supported educational and administrative technologies. Taylor (2001) locates his own institution and its directions within the Fifth Generation paradigm, encompassing automated courseware production systems, automated pedagogical advice systems and automated business systems. Deakin, like other universities, was confronted with the global e-learning challenge, and we use our own institution as a vehicle for examining the possibilities and benefits of engaging constructively with external pressures and internal responses towards institution-wide courses of action. We believe the potential educational benefits identified, education design approaches suggested and cultural changes outlined in relation to the learning organization are all transferable to other educational institutions attempting to position themselves strongly in the global e-knowledge age. Deakin University values its large, diverse and dispersed community of learners, from those studying on each of its campuses across three cities in Victoria to those studying off campus (some 40%) throughout Australia and overseas. Deakin faced the challenge of providing all its students with opportunities to learn about the University, actively participate in its learning community and gain support in moving into graduate employment. The University has addressed this challenge by establishing Deakin Online over the last 5 years (see Taking Deakin University Forward strategic plan). Deakin Online is the conceptual, educa-

tional and technical basis for connecting all of Deakin’s student groups, wherever and however they might study, to a broad range of online educational and administrative services. This broad range of services contributes to maximizing the learning of the University’s students and their sense of belonging to the Deakin learning community. Deakin Online aimed to build on the University’s strengths in: distance and online education; online teaching and learning; effective online support and administrative services; and emerging infrastructure of networks, Web sites and management systems. Over the last 5 years, the underlying corporate infrastructure to support this concept has largely been implemented. By corporate infrastructure or, corporate-level or enterprise-level technologies, we mean those technologies that are acquired, developed, deployed and maintained across the entire organization and used by a broad range of its key stakeholders, in the case of universities these being students and academic teaching staff. Corporate technologies are approved and funded by the organization’s Senior Executive for these broad institutional purposes. They can be compared with local technologies which, in a university setting, are acquired, developed and used in selected settings (like particular disciplines or professional fields) by more limited numbers of teaching staff and students for specialized purposes. The University is using Deakin Online as a key strategy for supporting Deakin’s transition from provider-directed, print-based distance education to the new educational paradigm of flexible and interactive, student-centered, online-enhanced learning. The Deakin of the future, thus, will be a real-time, real-place university that uses its expertise to develop the context for a successful online university experience, irrespective of the learner’s location. Deakin Online provides a structured and total approach to the use of online technologies, which will enrich learning experiences for all students. We acknowledge that all of

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this is strongly aspirational, that the University is in a state of long transition, some may say flux, and that much work still needs to be done to achieve organizational transformation. The University’s commitment to Deakin Online needs to be understood in relation to more fundamental economic and social shifts around the move to the global knowledge economy and the life-long learning phenomenon associated with it. Social capital is again receiving attention as the major economic resource and a sustaining competitive advantage in a world driven by the power of knowledge—its creation, storage, use and development by individuals, groups and organizations. Information and communications technologies both shape and support the creation and use of knowledge, and much is now demanded in the creation and use of these technologies for personal, professional and economic benefit. Deakin Online is an institution-wide architecture designed to generate a diversity of knowledge spaces beneficial to learning in the new e-knowledge age. The ecological metaphor is taken up by Segrave and Holt (2003) in relation to designing and working within contemporary learning environments for excellence in professional education. This perspective emphasizes the multiple parties involved in contributing to the ‘education’ of students in the world of e-learning, the criticality of ensuring the integration of both the physical and virtual dimensions of the new learning environments/habitats/ecologies, and the organic, evolving nature of the knowledges created and used in such environments. Knowledges may be created by any combination of academic teachers, students, academic support agencies and parties external to the institution in industry and the professions, and so forth.

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THE NEw ERA OF ENTERPRISE-LEVEL DEVELOPMENTS Holt, Rice, Smissen and Bowly (2001) examined the interests of the various stakeholders involved in the move towards enterprise-level technology developments, particularly relating to the acquisition and deployment of commercial LMS. Deakin Online also incorporates an LMS, integrated with other gateway, portal, administrative, content management, synchronous communication, streamed audio and video technologies. The configuration of technologies supporting Deakin Online is shown in Figure 1. The integrated suite of corporate technologies undergirding Deakin Online aims to: incorporate the Web-based delivery of teaching and learning and other Web-based services of the University; enhance the delivery of and easy access to teaching and learning; provide learning resources and communicative opportunities in a timely fashion; provide a consistent branding by having one system interface for all parties; reduce training costs associated with use of the environment; and reduce support and maintenance costs for the University.

THE DANGERS OF A PRODUCT-CENTRIC APPROACH Smissen and Sims (2002), and the accompanying Web site (Smissen 2002), provide a detailed view of the process Deakin University worked through in selecting an enterprise-level LMS. Similar acquisition processes were undertaken for a content management system (McKnight & Livingston 2003), a synchronous communication system and a corporate solution for audio and video streaming. These major technology acquisition

Strategic Design for Web-Based Teaching and Learning

Figure 1. Corporate technology infrastructure supporting Deakin Online (Source: Australian Awards for University Teaching, 2004; assisting student learning in Deakin University’s community of learners through Deakin Online, Supporting Material, Nomination for an institutional award: Category 1, p.1)

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processes are exacting and exhaustive, but not fail-safe. Much rests on their efficacy in leading to the adoption of products most appropriate for the University’s needs. It is understandable that those most centrally involved in these processes become preoccupied with the particular features of a range of best of breed products competing against each other in the global e-learning marketplace. This may be to the detriment of an in-depth understanding of other technology products and components constituting the corporate technology infrastructure. Moreover, with an acute and narrowing focus on product and feature assessment comes a diminution of broader views of the benefits (many of which are synergistic, based on interfaces with other corporate technologies) relating to teachers/teaching and learners/learning. A preoccupation with getting the technology acquisition right can lead to blind spots in the consideration of the often daunting array of organizational culture, political and power-related factors involved in the successful implementation of the systems. Peter Senge expressed the challenge thus: All around us are examples of “systemic breakdowns”—problems that have no simple cause. Similarly, organizations break down, despite individual brilliance and innovative products, because they are unable to pull their diverse functions and talents into a productive whole. (Senge, 1992, pp. 68-69) Peszynski, Corbitt, and Saundage (2004) assert that the implementation of strategic systems is fundamentally “a political act.” In the realm of strategic online teaching and learning systems, many actors can act with ‘much power’ to the advancement or detriment of the systems being implemented. At this point, newly acquired corporate technologies meet with a vengeance the realities of entrenched pedagogical cultures and politics; the new technologies’ possibilities and

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local pedagogical concerns can easily miss each other in a whirlpool of political forces. Pockley (2004) suggests that “A gap between vision and reality can (in the short term) be bridged by faith if there is sufficient strength of will, but when a vision is founded on values that are not shared, it is difficult to attract participants” (Pockley, 2004, p.8). This is the problem faced by senior management when driving change without understanding the diversity of values across the organization and also the implications for shifts in power and control when major changes in technology are imposed. We appreciate the difficulty of holding an all-at-once, specialized examination of particular products, with broader ‘notions of fit’ of technologies in generating potentially synergistic and enduring teaching and learning value. However, a preoccupation with product, features and their promotion can in turn shape teachers’ views around a similar set of usage concerns; that is, how much work will be involved in using a new product’s features (see Ford 2003a, 2003b), and constrain thinking about larger possibilities. Holt and Segrave (2003) have identified potentially new forms of technological and pedagogical disjunction—a magnified corporate technology imperative that might seem coercive rather than liberating to teachers and learners—through such narrowness and partiality of view and lines of action. Corbitt et al. (2004) refer to this as the danger of adopting a product-centric approach. A new mindset requires holistic thinking, new perspectives on the transforming role of the academic teacher, the identification of key areas of potential teaching and learning benefit, and a way of thinking about and implementing a systems-wide approach to education design. Strategic design is required to enhance organizationally the online teaching and learning imperatives. What this strategic design thinking and approach might look like, is examined in the remainder of the chapter.

Strategic Design for Web-Based Teaching and Learning

THE TRANSFORMING ROLE OF THE ACADEMIC TEACHER IN HIGHER EDUCATION Holt and Segrave (2003) argue in support of the changing role of the academic teacher in higher education. This is potentially transformational. Increasingly, higher education demands the academic to operate in strategic ways, using his or her expertise in undertaking the interrelated tasks of teaching, research, consultancy and community service. More than this, university employers increasingly expect that individual academics and the functional groups to which they belong will act in commercial/competitive strategic ways to improve the university’s achievements and standing relative to others in regard to economic performance, market positioning and public awareness of identity/branding. These tasks are linked with the central thread of creating, disseminating and using academic learning in the service of students and the community. The uniqueness of these interrelationships defines the special character of the academic, and the special purpose of universities in society. The new corporate technologies are supportive of a broader range of contributions being made by a broader range of internal and external parties acting in concert for the education of students, in some ways previously considered the responsibility of academics. We argue that through trust, networking and partnership academics can redirect certain aspects of supporting the learning of their students, whether it be redirecting to other educational agents in the system and/or to the technology itself through the automation of certain basic teaching/learning processes, and subsequently concentrate on those things that encapsulate and take full advantage of the academic’s unique capabilities. That is, the knowledge and passion of the subject matter, and the desire to support students’ understandings of it through various relationships rich in

personality and meaning, increasingly cultivated in both physical and virtual settings (see Deakin Studies Online: Contemporary online teaching cases, 2005, as reported in Holt, Borland, Farmer, Rice & Mulready, 2005). The letting go of some areas does not mean the marginalization of the academic teaching role in the new evolving educational enterprise, however. We are concerned when such impressions are given by those riding the wave of technologically induced change to teaching practices. Academic staff members’ agency, their sense of being in control and being able to change things based on their own values and informed actions, is still critical in our view to the achievement of more enduring teaching and learning benefits made possible by corporate technologies. Administrative leaders and managers in universities need to better understand (in terms of academic culture, academic identity, academic power, etc.) not only the diverse understandings/interpretations of corporate strategic plans, but the meaning of such strategy inferred by academics in terms of individual and group agency in teaching and research.

NEw AREAS OF POTENTIAL ENDURING VALUE FOR TEACHING AND LEARNING Responding to the challenge of behaving more strategically, academic teachers are ever alert to the enduring value of any—and more particularly, technology-based—initiatives for which they are expected to make a contribution. What might be these new areas of potentially enduring teaching and learning value? Where do we look for these benefits beyond the next corporate technology acquisition? How might we achieve the benefits and sustain them based on systems-wide educational design thinking? Elsewhere Holt and Se-

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grave (2003) have identified six potential areas for creating e-learning environments of enduring value for teachers and learners: 1.

2.

3.

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Broadened and direct contributions to enhance collaborative learning in learning environments from institutional stakeholders already involved in learning support. The resources and services of various academic and administrative support groups can be integrated seamlessly and directly with the students’ virtual learning environment. This ranges across various library digital resources and information literacy skills, information technology support and software applications, e-enrollment and tutorial allocation, and advice on academic study skills and career and employment guidance. An opening up of learning environments to enhance collaborative learning, involving diverse external participants able to add targeted value to learner experiences. External parties from the professions, industry, alumni, other teaching institutions and government can be connected using the technologies to contribute to the relevance and meaningfulness of the academic curriculum. Automated customization, personalization and individualization of learning experiences for diverse student cohorts enrolled in large, multi-modal courses. Even within the constraints of standardized curricula, pedagogies and assessment regimes for large, multi-modal classes, various media and technology channels can be used to provide options catering for different learning styles and needs. Furthermore, resources and activities in different media formats can be selectively and automatically released to different student cohorts depending on the particular rhythms of their study, work and personal lifestyles.

4.

5.

A sharing of learning resources within and between courses created, acquired and accessed by the institution. The technologies facilitate the institution, leveraging its buying power in acquiring and accessing multimedia learning resources in high volume from external sources for multiple internal purposes. Within the institution, homegrown media resources (new and legacy) can be created, stored and (re)used in multiple ways in support of the study of disciplines and professional fields at different academic levels, or across related disciplines/fields at the same academic level. Development of virtual practica supportive of grounded professional learning that motivates and engages students. Virtual practica may take different forms, from the development of computer-based simulations preparing or substituting in part for actual work placements to communications technologies being used to support learners as they undertake fieldwork education and in reflecting on their experiences post-placement (see Challis, Holt, & Rice, 2005). Additionally, along with bringing academic teaching support to the physical world of workplace learning, the technologies can bring back to the academic institution for immediate consideration by students on campus the live experiences of those on actual work placement. In Deakin University, a Strategic Teaching and Learning Grants Scheme (STALGS) has funded a project titled “Experiential Learning Through Simulations: Enhancing education in the professions through interactive computer simulations online.” Several faculties are collaborating to develop a simulation environment and educational scenarios in four professions: law, psychology, information systems requirements engineering, and public relations. A shared purpose is to engage students in a new learning relationship,

Strategic Design for Web-Based Teaching and Learning

6.

inviting engagement in professional roles and situated knowledge building rather than abstract content learning. The project will demonstrate the applicability of simulations across the professions for use both on and off campus by students in individual work and formal class settings, such as tutorials and examinations. All variants of virtual experiential learning can draw on collaborative as well as individual student engagement. The notion of networked communities of professional practice is also integral to the use of virtual practica. Development of e-learning environments ecologically responsive to teaching and learning needs and opportunities. E-learning environments should not be prescriptively designed and set in concrete forever. Through systematic evaluation of teaching and learning impacts, the new technologies should easily allow changes in the structures, elements and resources in ways that should be flexible, timely and developed organically. Learning environments must be designed and technologically enabled to change in concert with the rapidly changing knowledges and the know-how of disciplines and professional fields. Recent Web publishing technologies labeled social software (e.g., blogs, wikis and RSS) facilitate for participants various forms of self-organized development (Fielder, 2003) and research (Paquet, 2002). If we are to avoid “mechanistic,” “rote” approaches, academic teachers need to use individual and group communication technologies with their students that enable responsive and flexible forms, relationship building and collaboration for knowledge construction.

REALIzING THESE POTENTIALS THROUGH ADOPTING SYSTEMS-wIDE EDUCATION DESIGN In the management literature, systems thinking has been applied to the understanding of organizational behavior (Morgan, 1997). In higher education, both Biggs (2003) and Ramsden (2003) examine the determinants of teaching for quality learning in relation to the organization conceived of as teaching system. In evaluating the enablers and inhibitors of quality teaching, they focus on the individual academic teacher in their subject context, and the more encompassing departmental and organizational contexts that impact on student learning, arguing for reflective teaching practice by the individual and the institution collectively. Systems then are bounded sets of interacting units and activities that adapt to internal and external factors over time, often to achieve expressed goals. Designing technology-enhanced learning environments requires an appreciation of the interrelatedness of various teaching and learning contexts, from the unit/micro domain to the institutional/macro domain. Allied with systems thinking in understanding organizational behavior, is transactional thinking (better known in the literature as interactivity), which emphasizes the relationships between key actors and stakeholders in the organization; that is, the analysis of who in the organization does what, why, when and how. Again, Peszynski et al. (2004) highlight the imperative of understanding the power dynamics in such analyses. In what follows, we combine transactional thinking within the broad view of systems dynamics for our purposes. Designing educational enterprises requires the conception of actors, roles and sets of activities that relate to the following five areas: 1.

Curriculum (the what and why of teaching)

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2. 3. 4.

5.

Pedagogy (how students should be learning the curriculum) Assessment (how student learning should be judged) Media/technology (the various ways curriculum, pedagogy and assessment are enacted, delivered and supported) Evaluation (making overall sense of the impact of the educational enterprise on student learning—judging where the value lies)

Each of these five areas must be well aligned and mutually self-reinforcing areas of the educational enterprise if it is to be well designed (see Figure 2). All of the areas must be proactively, interactively influenced through design in relation to the differing contexts of learning and the differing experiences that students bring to the learning context. Within the five aligned areas, seven key types of human transaction or interactivity can be generated; namely: 1.

2. 3. 4. 5. 6. 7.

Learner interaction with learning resources created by the organization and outsourced Learner-teacher interaction Learner-learner interaction Teacher-teacher interaction Learner interaction with professional and industry partners Learner interaction with academic support parties Learner interaction with administrative support parties.

These types of interactivity are represented diagrammatically in Figure 2. Their dynamics and impacts in the five areas and the wider organization are the subject of ongoing reflection and research in the Institute of Teaching and Learning at Deakin University and are reported in the Web site of the Institute.

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Forms of interaction supported by e-learning are similarly enunciated by Garrison and Anderson (2003). For the potentials of the corporate technologies to be understood and realized, these interdependencies and the multiple parties interacting within the designed learning environments ought be identified, and informed actions taken to incorporate e-learning within these broader conceptualizations. The most advantageous uses of the technology infrastructure, therefore, become dependent on various domains of the educational enterprise being deliberately designed and enacted to yield these generative interactivity benefits. Usually this fusion of the five areas and the seven interactions only results from a more fundamental and active commitment to a review and renewal of curricula.

THE SCOPE AND IMPACT OF EDUCATION DESIGN MODELING Consider the spiraling scope and impact of strategic design as focus/attention ranges from small modules in a course unit through to the integrated functions of the university as a learning organization (see Figure 2). In putting forward the notion of education design thinking and approaches, we are not arguing for a prescriptive, mechanistic model of how academic teaching agents should go about designing and working within different learning environments as they relate to different learning needs, styles, contexts, subject matter and media/technology factors. That is to say, we are not arguing that this is what you must do, in these circumstances, to achieve declared learning outcomes. We do not see how learning environments can be so neatly segregated and treated based on systems thinking in educational worlds increasingly interconnected and changeable. We are, however, arguing for a descriptive type of education design modeling (For an illustration of an initiative designed for this purpose, see

Strategic Design for Web-Based Teaching and Learning

Deakin Studies Online: Contemporary online teaching cases, 2005), which sensitises academic teaching staff to the different factors at play and the highly contingent nature of designed environments requiring a deep understanding of local process and context, and which are being increasingly enhanced through a range of other educational support parties within and outside the organization. Education design modeling (as a strategic endeavor) may occur in many different domains within the organization. The corporate technology infrastructure provides foundational supports for these domains of education design activity. These domains of activity are overlapping and interconnected. In relation to the core sphere of academic teaching and learning, modules belong to units, units to majors, majors to courses, courses to fields of professional study, fields of study to schools and faculties, and faculty offerings and continuing professional education through separate entrepreneurial operations to the university (see Figure 2). Each domain of teaching/learning

activity carries with it particular education design concerns, challenges and opportunities. Each requires certain types of effective academic teaching leadership and management. While teacher agency may be loosely bounded by the immediate work of designing and working within a domain, each domain must be open to, is impacted by and, therefore, relates to others, illustrating the expansive scope and impact of strategic design. There is within the system a sense of smaller domains operating within bigger domains, with the overall organizational system interconnected with other potential organizational systems and general external environmental factors. An appreciation of the scope and impact of strategic design thinking within and between domains is critical in the effective use of corporate technologies. Learning value is enhanced through corporate technologies being orchestrated to support the enmeshing of the various domains of education design. This requires holistic appreciations that ideally will lead to synergistic effects. Whatever the initial domain of strategic design—macro,

Figure 2. Modeling education design concerns and system-wide impacts of education design (Source: Corbitt et al., 2004, p.10)

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intermediate or micro—we argue that attention must flow to the five critical areas of the educational enterprise and the seven forms of interactivity (human transactions) comprising the designed learning environment. But they must be considered contingently based on learner profiling, learning context and particular concerns of the discipline/professional field of study. Segrave, Holt and Farmer (2005, p.123) represent diagrammatically the constellation of education design domains and their interrelationships from an organizational perspective as reproduced in Figure 2. It also shows the foundational nature of the corporate technology infrastructure and the supporting sphere of activities of other internal and external educational support agents and their communities now actively contributing to academic teachers’ student learning. It should be noted that we advocate appropriate design attention for each domain in the organizational system, with a commensurate awareness of and engagement in a specifically reflexive design within and between five critical areas of the educational enterprise and the seven forms of interactivity within that domain. Of course, each will be of interest individually and in relation to others within and possibly beyond any individual domain. Armatas, Holt and Rice (2004a) present a case study of the application of this strategic design thinking in designing computer-enhanced, distributed, learning environments to support professional development in the field of psychology. The different uses of digital and online technologies are examined in five key phases of the professional development of psychology students/participants; namely: 1.

2.

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Building professional capabilities for the aspiring psychologist: Three-year programs (for first-year undergraduate studies) Becoming a psychologist: Fourth-year programs (for advanced undergraduate studies)

3. 4. 5.

Entering the field of psychological practice (for postgraduate coursework studies) Advancing as a professional psychologist (for research higher degree programs) Maintaining and enhancing psychological professionalism (for continuing professional education)

TOwARDS THE LEARNING ORGANIzATION: CULTIVATING STRATEGIC DESIGN What is required to engage constructively in strategic design thinking and action whatever the domain? What is needed to realize education design intent through effective practices in the designed environments? What are the fundamental values, characteristics and practices of a true learning organization that can create and sustain enduring teaching and learning value, supported by corporate technologies? We see vision, leadership, trust, encouragement, reward, appropriate forms of staff recognition and development, facilitative structures and continuity of action (especially executive action) all being important ingredients in generating real educational value that is organization-wide. These are the implications for future e-learning developments at Deakin and for other universities positioning themselves to take advantage of the global e-knowledge economy. Without an understanding of a true learning organization and a commitment to enact its characteristics, universities will struggle to generate enduring pedagogical benefits through strategic design, as shaped by strong teacher agency and student participation in virtual learning environments (operating within the corporate technology infrastructure). The focus on strategic system-based design (‘new mental models’), fortified through commitments to ‘shared vision’ and ‘team learning’ induce key core disciplines examined by Senge (1992) in building the learning organization.

Strategic Design for Web-Based Teaching and Learning

VISION AND CORE COMMITMENTS

GAINING AND ENHANCING TRUST

On the matter of vision and core commitments, we find much that is compelling in our own organization. Deakin University has been highly consultative in crafting such things while implementing strategic and operational plans and the subsequent enabling polices. In regards to mission, the University aspires to be relevant, innovative and responsive; its core commitments relate to rural and regional engagement, continuing education and life-long learning, and equity and access for disadvantaged individuals and groups (Taking Deakin University Forward, 2005). Each one informs the potential use of the corporate technologies in the areas of identified enduring teaching and learning value. For example, a commitment to life-long learning has shaped the University’s commitment to the strategic design of wholly online units, at least one of which must be taken by all undergraduate students in their studies irrespective of their mode of enrollment (see Armatas, Holt, & Rice, 2004b). More recently, the strategic funding of e-simulations to enhance education across multiple professions substantiates genuine engagement in the creation of curriculum resources that are relevant and innovative. Academic teachers can rise to the challenge by allowing vision, mission and policy to shape and infuse their own teaching practices. These strong influencers of action, however, must be seen as enhancing, not undermining, teacher agency. The corporate technologies must be seen to be yielding new forms of enduring teaching and learning value. They must be located within a strategic design. Vision, mission and policy must be believable, it must be seen as followed through by executive-level academic leadership, and committed to by all levels of academic leadership and management.

How can vision and policy be seen to be an ongoing, positive force by those on the ground? Academic teachers need implicit or overt permission to engage imaginatively with the new forms of education design. These ‘permissions’ need to come from the more immediate academic leadership/management level in particular. Encouragement and support for education design innovations may come from many parties across and outside the organization—once the initial permission is given. With such permission, encouragement and support must come a recognition of the forms of cost to the individual in extending themselves and taking risks, and the possibilities for compensating or career-enhancing rewards at some point. Academics should be considered mature professionals mostly focused on the intrinsic interests and benefits of their work. Consequently, they are often able to defer needs for immediate tangible gratification in perseverance of creating enduring value. However, teachers must have trust in their academic leadership that their efforts will be recognized, concretely supported and rewarded in time. We believe that academic leaders who themselves have had experience in education design innovation involving e-learning technologies and broadly conceived learning environments in particular are probably in a better position to judge the needs and achievements of others pursuing the same course of action.

ENCOURAGING DIVERSITY AND INNOVATION Universities, as knowledge-based organizations, change perpetually. In a sense, there can be forced or contrived, centrally driven organizational change, or grassroots, evolutionary change. Both are needed in varying degrees at different stages

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of an organization’s development as it relates to e-learning. The next waves of education design innovation around new corporate technologies, however, will come from multiple, distributed areas of academic strategic thinking and action. There will be much needed diversity in approach. Within it, there will be a need for continuities of commitment of effort over longer periods of time to realize the designed benefits. Continuities of effort will need to be carefully balanced against short-term imperatives to engineer change for its own sake. At Deakin, creative approaches to the development of academic teaching staff have been pursued to support the next waves of diversity and innovation in the creation, use and development of digital media and online environments to enhance teaching and learning in the six key areas of enduring value. In this regard, the University ran an Online Teaching and Learning Fellowship program in 2003 and 2004. The Fellows were selected to experiment with the development and operation of extended and wholly online environments. Case reports of their work and many other digital and online exemplars have been prepared (see Holt et al., 2005). As noted previously, the cases can be found on the University’s Web site (Deakin Studies Online: Contemporary online teaching cases, 2005). An earlier version of exemplary cases was also presented at various face-to-face sessions around the University, with an associated CD-ROM distributed. The dual objectives of the cases’ site and the showcasing events were to give recognition to the outstanding work done by many teachers throughout the organization and to show interested staff how digital media and technologies can be developed and used to achieve desired learning outcomes in a variety of appropriate pedagogical ways. The cases, therefore, evolved through the phases of Fellowship cases to a broader range of cases presented in face-to-face sessions and in a minimalist form on CD, to a full-blown case Web site with multiple views, browse and search features, all in response

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to feedback and contributions volunteered by staff in the Deakin community. Together these various developments represented a key academic professional development (APD) strategy to stimulate teachers’ thinking about high potential areas for teaching and learning enhancement.

APPROACHES TO RECOGNIzING AND DEVELOPING TEACHING STAFF Segrave et al. (2005) extended their framework for designing e-learning environments for enduring teaching and learning value to incorporate six areas of staff capacity development and six strategic initiatives that can be taken to advance academic professional development for enhanced online teaching and learning. The six areas of staff capacity development are: (1) designing for learning online; (2) the three Cs: communicating, collaborating and community development online; (3) assessing student learning online; (4) developing learning resources for online; (5) experiential learning online; and (6) continuous quality improvement online. The six strategic initiatives covered a number of developments examined in the previous section (Segrave et al., 2005). The combined effect of the interactions of the six areas of enduring value, six staff capacities and six strategic initiatives is depicted diagrammatically in The 6three model for enhancing academic teachers’ capacities for effective online teaching and learning (see Segrave et al., 2005, p. 120). In examining more closely the layers of interaction among professional development modules, which could be developed around each of the six staff capacity areas, and various professional development activities that might in turn relate to these modular learning experiences, Figure 3 has been formulated. The figure also highlights four learning processes that should permeate the organizational learning system.

Strategic Design for Web-Based Teaching and Learning

Figure 3. An integrated approach to the development of online professional development modules and other related activities, resources and events (Source: Farmer, Segrave, & Holt, 2003)

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FACILITATIVE ORGANIzATIONAL STRUCTURES AND SUPPORT SYSTEMS Academic structures tend to be most supportive of discipline-based teaching and highly specialized research. However, structures in our University are changing in ways aimed at bringing together disciplines and professional fields around real-world concerns. The domains of strategic design do traverse academic departmental boundaries. Evidence of this can be seen in plans underway for e-simulations dealing with the needs of human service professionals; for example, police, nurses, lawyers, psychologists and teachers, specifically, those employed in areas responsible for interviewing clients at risk, such as abused children and individuals for whom trauma, grief, race, sex, religion and so forth are significant factors. Such a proposal for simulated interviews with members of a virtual medical team, for use in university studies of cross-discipline, inter-professional issues, is a recent response to expressed contemporary needs for new approaches to education in the professions based on evidence-based practice. A strong, student-centered, learning-outcomes approach demands no less. It remains to be seen how academic structures might evolve, and how new structural models might work for the benefit of teachers and learners. We believe one promising ‘structure’ for effective education design modeling lies in reflexive forms of communities of practice, which we have thus far alluded to as open academic collegiality. Such communities represent a contemporary expression of the familiar team teaching approach, but in an extensible e-learning environment. These communities need to be nurtured around the domains of activity and can involve all parties inside and outside the organization with a passion and interest in designing for enhanced teaching and learning within the domain. As Norris, Mason and Lefrere (2003) observe:

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It has become an article of faith among developers of organizational technology infrastructures that the ultimate value from technology investment lies in its capacity to enable/leverage the reinvention and innovation of business processes. But the term “process reinvention” does not do justice to the entire scope of innovation. In reality, the goal is reinvent the “conversational space” of the enterprise—the dynamics and relationships of the organization that are embedded in business processes, communities of practice and other elements of the organizational system’s social ecology (p. 112). The introduction of corporate-level/organization-wide technology is often proposed on the basis of economic benefits and corporate, strategic alignments without recognizing its impact on other processes, responsibilities and authority in the organization—not recognizing that it is also about the relocation of power and control, if not its centralization (Peszynski et al., 2004). Domains of strategic design will be increasingly overlaid across traditional academic structures in the service of designing new types of learning environments. This has not and will not happen without various degrees of organizational tension. The constructive resolution of such tension will again be another challenge for academic leadership and management. However, even within current communities of campus-based and discipline-based practice, distributed and local support systems are required. Rather than taking staff out of their own teaching environments, it is important to embed support and development staff, at least in the physical sense, within these natural contexts for working, learning and teaching (see Smissen, 2004). As Smissen (2004, p. 4) observes with Deakin’s learning management system, Deakin Studies Online (DSO), “The most frequent request from staff regarding [using the DSO interface] was to have someone provide ‘over-the-shoulder’ support for brief sessions to help improve their work practices and the structure of their units in DSO.”

Strategic Design for Web-Based Teaching and Learning

CONCLUSION With the establishment and integration of corporate technologies comes the time for major new waves of innovation in relation to new types of designed learning environments, and the development of new types of staffing capabilities to work effectively within them. We are seeing the emergence of a new wave of innovation in our own University. These learning environments are, and will represent, different combinations and permutations of the virtual and physical, contingent on the various educational enterprise and interactivity considerations outlined. To support and encourage the new innovations, we have proposed that they be grounded in strategic design from unit to university, as we have put it. The mindset and tools of strategic design, we believe, provide the best way forward in exploiting the potentials of the corporate technologies for achieving the enduring benefits for all parties with a stake in educating the organization’s learners. Notable, however, is the need to develop new forms of academic teacher agency and student engagement with contemporary learning environments rich in e-learning potentials. Our ongoing research will focus on the substantive evidence of achievement in the areas of enduring teaching and learning value as experienced by academic teachers and students, benchmarked against the progress made by other universities strongly committed to e-learning.

REFERENCES Armatas, C., Holt, D. M., & Rice, M. (2004a). Designing distributed learning environments in support of professional development in the field of psychology. Educational Media International, 41(4), 315-326. Armatas, C., Holt, D. M., & Rice, M. (2004b). From online-enhanced to wholly online: Reflec-

tions on e-learning developments in psychology in higher education. In R. Atkinson, C. McBeath, D. Jonas-Dwyer, & R. Phillips (Eds.), Beyond the comfort zone. In Proceedings of the 21st Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education (ASCILITE) (pp. 78-87). Biggs, J. (2003). Teaching for quality learning at university: What the student does. Buckingham: SRHE & Open University Press. Challis, D., Holt, D. M., & Rice, M. (2005). Staff perceptions of the role of technology in experiential learning: A case study from an Australian university. Australasian Journal of Educational Technology, 21(1), 19-39. Corbitt, B., Holt, D. M., & Segrave, S. (2004). From product centricism to systems-wide education design: Making corporate technology systems work for the learning organization. In Proceedings of the Eighth Pacific Asia Conference on Information Systems (pp. 673-686). Deakin Studies Online. (2005). Contemporary online teaching cases. Retrieved October 19, 2005, from www.deakin.edu.au/teachlearn/cases/ Deakin University. (2005). Taking Deakin University forward. Retrieved October 19, 2005, from www.deakin.edu.au/vc/planning-reporting.php Deakin University. (n.d.). Institute of teaching and learning. Retrieved March 20, 2006, from www. deakin.edu.au/itl/index.php Farmer, J., Segrave, S., & Holt, D. M. (2003). Concept proposal online teaching and learning modules: Deakin University Academic Professional Development (APD) (internal document). Geelong: Deakin University. Fielder, S. (2003). Personal Web publishing as a reflective conversational tool for self-organized learning. In T. N. Burg (Ed.), Blogtalks (pp. 190216). Wien: Libri.

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Ford, J. (2003a). Deakin studies online: The first two years. Internal Report 1: Preliminary results of Stage 1 and early in Stage 2 2003. Geelong: Deakin University Ford, J. (2003b). Deakin studies online: The first two years. Internal Report 2: Staff and student experiences of using DSO in semester 1, 2003. Geelong: Deakin University. Garrison, D. R., & Anderson, T. (2003). E-learning in the 21st century: A framework for research and practice. London: Routledge Falmer. Holt, D. M., Borland, R., Farmer, J., Rice, M., & Mulready, P. (2005). Casing out teaching and learning online: Enhancing fidelity into the mainstream. Balance, fidelity, mobility: Maintaining the momentum? In Proceedings of the 22nd Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education (ASCILITE), Brisbane. Holt, D. M., Rice, M., Smissen, I., & Bowly, J. (2001). Towards institution-wide online teaching and learning systems: Trends, drivers and issues. In G. Kennedy, M. Keppell, C. McNaught, & T. Petrovic (Eds.), Meeting at the crossroads. In Proceedings of the 18th Annual ASCILITE Conference, The University of Melbourne, Australia (pp. 271-280). Holt, D. M., & Segrave, S. (2003). Creating and sustaining quality e-learning environments of enduring value for teachers and learners. In G. Crisp, D. Thiele, I. Scholton, S. Baker, & J. Baron (Eds.), Interact integrate impact . In Proceedings of the 20th Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education (ASCILITE), Vol.1, Adelaide, Australia(pp. 226-235). Retrieved November 29, 2005, from www.ascilite.org.au/conferences/adelaide03/docs/pdf/226.pdf McKnight, S., & Livingston, H. (2003). Reuse of learning objects? Why, how and when? In Proceedings of the Educause in Australasia

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Conference, Expanding the Learning Community: Meeting the Challenges, Adelaide. Morgan, G. (1997). Images of organization. Thousand Oaks, CA: Sage. Norris, D., Mason, J., & Lefrere, P. (2003). A revolution in the sharing of knowledge transforming e-knowledge. Ann Arbor: Society for College and University Planning. Paquet, S. (2002). Personal knowledge publishing and its uses in research. Retrieved November 29, 2005, from www.knowledgeboard.com/cgi-bin/ item.cgi?ap=1&id=96934 Peszynski, K., Corbitt, B., & Saundage, D. (2004). Deconstructing power within a strategic information system. In Proceedings of the 15th Australasian Conference on Information Systems, University of Tasmania, Hobart. Pockley, S. (2004). Metadata and the arts—The art of metadata. In G. Gorman (Ed.), Metadata applications and management. London: Facet Publishers. Ramsden, P. (2003). Learning to teach in higher education. London: RoutledgeFalmer. Segrave, S., & Holt, D. M. (2003). Contemporary learning environments: Designing e-learning for education in the professions. Distance Education: An International Journal, 24(1), 7-24. Segrave, S., Holt, D. M., & Farmer, J. (2005). The power of the 6three model for enhancing capacities for effective online teaching and learning: Benefits, initiatives and future directions. Australasian Journal of Educational Technology (AJET), 21(1), 118-135. Retrieved November 29, 2005, from www.ascilite.org.au/ajet/ajet.html Senge, P. (1992). The fifth discipline: The art & practice of the learning organization. NSW: Random House. Smissen, I. (2002). Evaluation of corporate applications for online teaching and learning.

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Retrieved November 29, 2005, from www.deakin. edu.au/teachlearn/content/lms-evaluation/index. htm Smissen, I. (2004). Training and support requirements for DSO. Survey of academic staff report to pro vice-chancellor. Retrieved October 19, 2005, from www.deakin.edu.au/dso/dsohelp/resources/index.php

Smissen, I., & Sims, R. (2002). Requirements for online teaching and learning at Deakin University: A case study. In Proceedings of The Eighth Australian World Wide Web Conference (pp.167-185). Retrieved November 29, 2005, from http://ausweb.scu.edu.au/aw02/papers/refereed/ smissen/paper.html Taylor, J. C. (2001). The future of learning— Learning for the future: Shaping the transition. Open Praxis, 2, 20-24.

This work was previously published in the International Journal of Web-Based Learning and Teaching Technologies, Volume 1, Issue 4, pp. 15-35, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 2.16

The Essential Elements of Interactive Multimedia Distance Learning Systems Kurt Maly Old Dominion University, USA

Ayman Abdel-Hamid Old Dominion University, USA

Hussein Abdel-Wahab Old Dominion University, USA

Sahar Ghanem Old Dominion University, USA

C. Michael Overstreet Old Dominion University, USA

Waleed Farag Old Dominion University, USA

J. Christian Wild Old Dominion University, USA

Abstract In recent years, we have seen the introduction and use of many distance learning systems. Some of these systems are characterized as interactive, which means the dominant mode of instruction is live or synchronous using networked multimedia technology such as audio, video and shared workspaces. In this chapter, we present the common features and essential elements that should be implemented in such systems. Throughout this chapter, we will use as a model and case study the IRI-h system (for Interactive Remote Instruc-

tion-heterogeneous) that we have developed and implemented in Java and have used to support distance learning at Old Dominion University.

INTRODUCTION In recent years, interest in using the Internet and the World Wide Web as tools for distance learning has increased. Many of these systems are based on an asynchronous learning paradigm which makes course contents available on the Web; students learn the material at their own pace,

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The Essential Elements of Interactive Multimedia Distance Learning Systems

they may seek help from the instructor using email and various multimedia teleconferencing tools (e.g., Hilt & Kuhmunch, 1999; Ibrahim & Franklin, 1995). Other systems are based on a synchronous learning paradigm where the instructor and the students meet at the same time, but not necessarily in the same room, and use the Internet as the primary means of communications (Hilt & Kuhmunch, 1999; Maly et al., 1997; Synnes, Lachapelle, Parnes & Schefstrom, 1998). An example of such synchronous systems is the interactive remote Instruction (IRI) project that has been developed and used in the Department of Computer Science at Old Dominion University over the last six years (Synnes et al., 1998; Maly et al., 2001). The IRI system offers a synchronous virtual classroom environment, with audio, video, and tool-sharing capabilities. Past experience with the original IRI system (Synnes et al., 1998) has enabled us to identify several inherent deficiencies that limit its large-scale deployment. The main identified deficiencies were platform dependence, limited scalability, and the need for a homogeneous controlled network environment. The need for a multi-platform, multi-network environment scalable system prompted us to embark on the design and implementation of a new IRI system which we termed IRI-h (http://www.cs.odu.edu/~iri-h; Maly et al., 2001). The “h” in the acronym stands for heterogeneous; it distinguishes the fact that IRIh is designed to run on heterogeneous platforms and within heterogeneous network environments. An IRI-h prototype (Maly et al., 2001) was fully implemented in Java (http://java.sun.com) and has been tested on multiple platforms, including PCs running various versions of Windows and Unix machines running the Solaris operating system. In addition, the developed prototype has been successfully used to teach a semester-long computer science course across sites 20 miles apart. In this chapter, we leverage our previous and ongoing experience in the distance learning arena to identify a set of essential features for interactive distance learning systems. We present as a case

study our own IRI-h system, highlighting how most of the identified features are integrated and implemented. Next we discuss a set of features that we believe should be available in any interactive distance learning system. Then we present a general design overview of IRI-h highlighting main design components and functionality, including the session participant, the session manager, application-level gateways to handle network heterogeneity, and recording and playback services to provide asynchronous learning capabilities. The next section summarizes how most of the essential features identified earlier are supported by IRI-h design and components. Finally, the chapter is concluded along with future work.

ESSENTIAL ELEMENTS OF AN INTERACTIVE DISTANCE LEARNING SYSTEM In this section, we identify a set of essential elements that we believe should be present in any interactive distance learning system. Typically, a semester-long class meets as a series of synchronous sessions lasting an hour or so. Some of the session participants can be gathered or co-located in specially equipped sites, e.g., a university lab, or a conferencing room in a corporate network setup. Other class members participate from home or work. In terms of network connectivity, some participants can utilize high-speed scalable group communication, e.g., by being located on a high-speed multicast-capable intranet (Deering, 1989) while others may be less capable in terms of the unavailability of multicast communications, limited connectivity bandwidth or long incurred delay. It is desirable not to reduce quality of service to some participants even when others have more limited connectivity. Based on our experience with IRI, we strongly recommend that most, if not all, of the following features should be available in any interactive distance learning system:

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Audio and video conferencing: For the instructor and students to talk and see each other and facilitate interaction. Any participant should be able to transmit her audio and/or video to join a discussion, although desktop landscape and the available bandwidth might limit the number of simultaneous video and/or audio transmitters and may require a management scheme for controlling the audio and/or video transmission. Application sharing: To present and enhance class material by sharing tools. Examples include presenting class material through a Web browser or PowerPoint. Tool-sharing should allow any participant to control and manipulate the tool. For example, an engineering design tool may allow participants, one at a time, to alter the design parameters, and subsequently view the effects of their input on the design. Scalable group communication: For efficient and scalable delivery of data streams to session participants. Participants should be shielded from network heterogeneity specifics through an abstracted view of session membership, regardless of the participant’s network connectivity. Some participants may rely on scalable one-to-many group communication such as multicast technology, whereas other participants may need unicast services from an application-level gateway. Application-level gateways: To handle network heterogeneity and accommodate less capable participants. Gateways may perform format transcoding and rate adaptation of media streams. In addition, packet relaying may be necessary to bridge the gap between multicast-enabled sites and multicast-disabled participants. Recording and playback: To record and playback different media and data streams. Students may review recorded material at

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any time at their own pace. Playback can also take place during a life session to review material recorded in an earlier session. In addition, recording provides a backup capability in case a student is not able to attend the live lecture or due to technical difficulties was not able to join the session. A common shared view: To maintain a common view of any shared activities across all participants within a session (e.g., windows content and positions, pointers, annotations). Such a feature provides the same view for all participants as dictated by the person who controls the shared view. This feature requires a layout management tool that disseminates shared view changes to all session participants. Presentation aids: To assist in class material presentation capabilities, such as annotation and pointer tools. Such presentation aids need to be accessible for all participants, albeit in a token-controlled manner. Annotation and pointer tools are used to annotate and point at the common shared view, hence resulting annotations, or pointer movements must be propagated to all participants. Note taking and post-session notes availability: To allow participants to privately take notes during the session, and the availability of these notes after the session termination, either locally on their private disks, or through a Web browser. Monitoring and feedback: To monitor the status of the session and report any exceptional events. Such tools can make available to a teacher or a system administrator a snapshot of the current status of the system, e.g., the list of current participants or the quality of a participant’s video or audio transmission. Furthermore, special purpose tools such as site videos can be deployed to allow monitoring of students in remote sites. Other intelligent feedback tools can be used

The Essential Elements of Interactive Multimedia Distance Learning Systems

to automatically adapt the behavior of the system, e.g., change the transmission rate of a video stream due to network congestion. 10. Simple interface: Easy to use and learn by both the instructor and the students, providing one-click access to commonly used tasks. A participant should be able to quickly learn how to manipulate such an interface. This is a very subjective feature that is hard to quantify; however, we listed it here to emphasize the importance of this issue to the success and wide adoption of distance learning systems. 11. Tutoring and subgroup collaboration: To allow students to study together in small groups, or to enable an instructor to partition a class of participants into discussion groups to work on an assignment or a term project. Most, if not all, the feature listed here should be made available to the participants of such groups. 12. Testing and evaluation tools: For taking tests, submitting assignments and grading. Examples of such tools include assessment capabilities within Learning Space (http:// www.lotus.com/home.nsf/welcome/learnspace), and the Blackboard learning system (Yaskin & Gilphus). 13. Administration tools: To efficiently manage and administer the distance learning system and environment. Administration tools can be classified as offline and as insession management tools. Offline tools are used to setup and startup a session (based on administrative registration lists). In-session tools can be used for management of an ongoing session, for example selecting which student joins an ongoing discussion or answers a question.

IRI-H DESIGN AND ARCHITECTURE Providing the features identified in the previous section in an integrated fashion requires a robust infrastructure for establishing and coordinating sessions. In this section, we describe the design of IRI-h’s software architecture as an example of a successful distance learning system capable of providing these essential features. Figure 1 illustrates a typical setting for an IRI-h session with two sites involved. A session consists of a single session manager (SM), and several session participants (SPs). The SM is a central server that runs on a designated machine, represents a rendezvous point for SPs, and provides control information for all participants. The SP is a client running on each desktop participating in the session. A special purpose SP is deployed in Site 2 to act as a Recording Replay Server (RRS). By default, IRI-h sessions are recorded for backup and to provide asynchronous learning capabilities through a playback functionality. Please refer to the third section for more details on the recording and replay functionality within IRI-h. The SM operates and manages several virtual rooms. Virtual rooms can be used to subdivide SPs, for example to form special discussion groups. An SP is a member of one virtual room at one instant of time. A session can be pre-configured with several virtual rooms, and new virtual rooms can be created as needed. In addition, SPs can move from one virtual room to another. In each room, a set of services is available for SPs, including audio, video, tool sharing, annotation, and pointer services. Services use shared resources that are allocated and managed through the SM, e.g. group communication channels. IRI-h services require one or more group communication channels. We classify a group communication channel as unreliable, reliable, or semi-reliable. Unreliable group communication can be provided through IP multicast (Deering, 1989). Reliable group communication can be provided through a

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Figure 1. A typical IRI-h session with supporting servers Directory Server

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reliable multicast protocol, e.g., RMP (Whetten, Montgomery & Kaplan, 1994). Semi-reliable group communication can be achieved by means of a tailored retransmission protocol that provides some degree of reliability. The current IRI-h prototype implementation offers a mix of unreliable and semi-reliable group communication. Unreliable group communication is provided through IP multicast and is used for audio and video services. Semi-reliable group communication is offered through basic IP multicast, enhanced using a controlled retransmission policy, and is used for tool sharing, pointer, and annotation services. In adopting a semi-reliable group communication model for data services, we rely on an eventual consistency paradigm that improves the architecture support for heterogeneous network environments and avoids the extra overhead if a reliable multicast protocol is used otherwise.

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The SP and SM exchange control information through a client-server approach in which the SP connects to SM by means of a permanent TCP connection. This connection remains active as long as the session is ongoing, and is used to convey control information between SP and SM. We have made a tradeoff between reliability and scalability by eliminating any distributed servers that maintain considerable state information about the session. A session is managed by only one SM and is responsible for distributing any control or state information to all participants. Although a central server approach for session control reduces the robustness and fault tolerance of such a system, it greatly simplifies the design, and achieves the desired level of scalability of supporting a maximum of hundreds of control connections to the session manager within a session. Some of the SPs might be located in high bandwidth multicast-enabled intranets. Other

The Essential Elements of Interactive Multimedia Distance Learning Systems

SPs can have limited capabilities, say a student participating in the class from home or work. The latter SPs may require the services of a gateway (GW), which offers data packet relaying from multicast groups, transcoding, and rate adaptation services. The SM is connected to each of the GWs involved in the session with a permanent TCP connection to ensure that such GWs remain functional during the life of the session and to pass control information from the SM to the GW. Within each site data for various services are sent through multicast channels. IRI-h supporting servers are deployed independently of IRI-h sessions, including a directory server (DS) and a notes server. The Directory Server provides lookup functionality for ongoing sessions. Upon startup, an SM is required to attempt to register with a well-known DS by establishing a permanent TCP connection. An SP later queries the DS through a transient TCP connection, selecting which ongoing session to join. The Notes Server provides a back-end server for collecting participants’ notes when a participant leaves a session and stores these notes in a class directory structure to allow later retrieval through a Web interface. During the course of the session, a participant can take notes using a note-taking tool and is asked when exiting if she wishes to upload her notes to be accessible through an IRI-h Web server. If the upload option is selected, a transient TCP connection is established between the SP and the notes server to transfer the notes, and create the appropriate notes directory structure. The third section is organized as follows. First we present the session participant along with available services and session views. Then the session manager’s software architecture is introduced, explaining how resource management, group communication, and late join are realized. We explain how the architecture supports network heterogeneity by offering gateway services to less-capable session participants and present the

design of recording and replay services to allow for asynchronous learning capabilities.

Session Participant Figure 2 illustrates the SP software architecture in which the SP operates several services controlled through service managers. Supported services are audio, video, site video, tool-sharing, annotation, pointer, layout management, and replay. The Audio and Video service allow sending and receiving audio and video streams. The Java Media Framework (JMF) (http://java. sun.com/products/java-media/jmf/index.html) is used for both capturing and playing the audio and video of each participant. JMF uses RTP/RTCP (Schulzrinne, 1996) to transmit the captured media across the network. The Site Video service allows sending and receiving a site video at a low frame rate from a machine configured to act as the video server for a site. Hence, the service’s receiver component is available at all participants, whereas the sender component is only available at a designated video server per site. The site video sender operates at a low frame rate, e.g., one video frame per second. The Tool-Sharing service allows any participant to share applications with other participants. At the sender side, images of the windows in the application being shared are captured, compared to previous images to see if the image has changed (for removing temporal redundancy), compressed, and transmitted over a group communication channel. At the receiver side, the images are received, decompressed, and displayed. See Gonzalez, Abdel-Wahab and Wild (2001) for design details and performance results for the tool-sharing engine (IPV for Interactive Program Video). The Annotation, Pointer, and Layout Management services are token-controlled and allow the current token holder to annotate on top of the shared view, move a shared pointer to any position in the shared view, and arrange all shared view windows (videos, shared tools, etc.),

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respectively. The Replay functionality is managed by a Main Replay Manager which controls several individual replay services and in turn operates replay receivers that are invoked during playback of a previously recorded session. Note that each recorded service requires a corresponding replay service. Currently, the recorded services are audio, video, tool-sharing, annotation, pointer, and layout management. An SP has two views of the current session: a shared view and a private view. The virtual room that the SP belongs to has a shared view that is consistent across all participants in that room. Changes can be made to the shared view by the presenter, the token holder of the layout management service, which are propagated to other participants. The shared view consists of any received video windows, annotations, and shared tools’ windows. In addition to the shared view, a participant has a configurable private view of private tools such as a collection of session

monitors and a note-taking tool. Session monitors include a “Class Monitor,” a “Participant State Monitor,” a “Log Viewer” and a “Site Camera View”. The “Class Monitor” displays information about all members currently logged in or expected to participate in the session. Class participants are known beforehand through a class enrollment database. For example, a currently logged-in participant entry would provide the participant login, used machine name, and perceived role for this participant as being a student, teacher, or administrator. In addition, the “Class Monitor” is capable of providing a view of the currently connected machines to the session manager, regardless of whether a member is logged in using this machine or not. The “Participant State Monitor” shows each service state at each logged-in machine. For example the state of a video sender could be one of three states (can’t send video, can send video and is not sending, or is sending his video). The “Log Viewer” displays messages reported by all

Figure 2. Session Participant (SP) software architecture SP

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The Essential Elements of Interactive Multimedia Distance Learning Systems

participants. Session monitors are provided with up-to-date information affecting the state of the session through the session manager, which has a global view of all participants. The site camera view provides a “site view” through a camera at each site (site video service in Figure 2). Figure 3 is a collection of snapshots of the IRIh interface in different session scenarios. Figure 3(a) is a snapshot of a discussion scenario where two participants’ video windows (small size) and a presenter’s video window (large size) are visible. Figure 3(b) is a snapshot of a presentation scenario where the presenter is presenting class material using a shared Web browser, a shared Unix tool (an xterm), some annotations, and a pointer. Figure 3(c) depicts a snapshot of a collaboration scenario where a simulation tool is being shared, and participants are taking turns in controlling the simulation parameters affecting the outcome of the simulation.

Session Manager Figure 4 illustrates the SM software architecture. The SM maintains the session’s state including session rooms and services running within each room. Furthermore, the SM allocates the resources needed by each service. Resources are observers, group communication channels, tokens, queue managers, or gateway servers. For example, the resources required by the video service are a group communication channel and a gateway server. The resources required by the annotation service are a group communication channel, a token, an annotation observer, and a gateway server. Observers are used to maintain the state of stateful services such as annotation, and are used to provide a newly logged-in participant with the relevant services’ state which helps solve the late join problem. Group communication channels are used to transport each service’s data streams and are allocated by a Group Communication Server (GC server). Tokens are

Figure 3(a). A shared view snapshot illustrating a discussion scenario

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Figure 3(b). A shared view snapshot illustrating a presentation scenario

Figure 3(c). A shared view snapshot illustrating a collaboration scenario

used within token-controlled services, and are controlled by Token Managers running within the SM machine. Queue managers are used within video and audio services to manage the current audio/video senders. Gateway servers provide data packets relaying rate adaptation services

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to participants with no multicast capabilities, or limited connectivity bandwidth. A “Log Server” is responsible for collecting all reported messages from all participants and writing them into a log file. Upon startup, Participants connect to it through an independent

The Essential Elements of Interactive Multimedia Distance Learning Systems

TCP connection maintained for the lifetime of the session. Each reported message has a message header that includes a timestamp, the reporting participant IP, the reporting object name/method and a message level to allow filtering of messages. Messages can be classified as error, status reporting, or program degugging messages.

Late Join While a session is in progress, participants joining the session need to know the current shared view state such as the presence of video windows, their positions, and if any annotations exist on the shared view. Note that any previous session views could have been recorded as part of a recording functionality, but only the latest updated view is provided to a latecomer. Observers are threads running within the SM for pointer, annotation and layout-management services. The observer joins the service’s data communication channel (unreliable channel) and receives every packet sent through the channel. Upon a late join (participant login), SM notifies all observers to send their latest state of each service. In order to avoid a startup explosion problem (many requests in a short period of time), a timer is set by the observer to guarantee a minimum period of time

before honoring any new requests to resend the maintained state. The pointer service requires a stateless observer that keeps only the last snapshot of the pointer state that is the last position of the pointer (x and y). New packets with newer timestamps continuously update such state. On the other hand, the annotation service requires a stateful observer that maintains the state of a whole annotation frame, including any annotation objects and their respective positions within that frame. Whenever a new frame is detected, the saved frame’s state is cleared. The layout management service requires a window observer that maintains the latest boundaries (x, y, height, width) of every uniquely identified window within the shared view. New participants detect existing video and audio streams through RTP mechanisms (Schulzrinne, 1996) after joining the audio/video channels. Hence, no observer is required for such services.

Group Communication A group communication API is designed to provide group communication capabilities to IRI-h services in a uniform and transparent manner. Transparency in this context implies that an API

Figure 4. Session Manager (SM) software architecture Gateway

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layer hides from upper code layers the implementation details of the communication channel. For example, the same annotation service code can be used unchanged for a multicast-enabled SP that utilizes a multicast-based group communication channel or a multicast-disabled SP that utilizes a unicast communication channel. Figure 5 illustrates the API layers used to provide group communication capabilities to IRI-h services. As noted previously, the Group Communication Server (GC server) allocates group communication channels requested for services. A group communication channel identifier is a (textual-name, implementation-type) pair such as (“Room1-Video Group,” “Unreliable Multicast”). The SM automatically generates the channel textual name, in order to ensure its uniqueness. The GC server maintains a database of mappings from a group communication channel identifier to networking entities such as a (multicast-IP-address, port) pair. The SM requests from the GC server the creation of a new group communication channel within a specific virtual room. The GC server generates the associated networking entities and saves this mapping in its database. Later on, an SP connects to the GC server using a transient TCP connection in order to request the associated networking entities of a specific group

Figure 5. API layers to provide group communication to IRI-h services IRI-h services

IRI-h group communication API IRI-h networking API Java networking API

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IRI-h

communication channel. A transient TCP connection implies that the connection is closed after the SP receives the reply. Each service requiring a group communication channel is guaranteed a unique (multicast-IP-address, port) pair, across all running IRI-h sessions (if any), through the GC server allocation policy. To support virtual rooms, each room is assigned a unique multicast address. This multicast address is used by all services requiring group communication channels within this room. It is formed as a function of the SM machine’s IP address, SM server port, and the room number.

Token Management A token manager is required for each tokencontrolled service (pointer, annotation, and layout-management). The SM allocates the token managers, and provides an SP with their corresponding IP addresses and port. An SP connects to the token manager through a TCP channel. The token manager manages one token and guarantees that only one participant holds that token at one instant of time. The token holder is the only participant that is allowed to send data through the token-controlled service channel(s). A stateless token resource is allocated for pointer and layoutmanagement services. Alternatively, a stateful token resource is a token that maintains a state and sends it reliably from the old token holder to the new token holder. It is used by the annotation service to send a frame number and a sequence number. This information is crucial in ensuring the correct sequence of annotation packets, since the annotation packets are sent unreliably.

Queue Management for Audio and Video Services Queue managers are data structures used by audio and video services to manage participants currently transmitting their audio and video. This management is required because of the need to

The Essential Elements of Interactive Multimedia Distance Learning Systems

impose a physical constraint on the number of simultaneous video streams and to limit the number of participants joining a discussion. The physical constraint on the number of simultaneous video streams arises from shared view landscape limitations and the need to minimize the generated video streams’ bandwidth flowing in the network. When a participant is transmitting his audio/video, his ID is kept in the queue. When there is no room in the queue, the first participant who started transmitting is forced to stop transmitting his audio/video and is removed from the queue. The current presenter, the layout-management token holder, is shielded from this forced remove until he is no longer a presenter.

Application-Level Gateway In this section, we introduce the design and operation of application-level gateways that are seamlessly integrated within the overall architecture to handle class participants with no multicast connectivity or limited bandwidth such as home users. Each IRI-h site has one or more designated gateways. A session manager is provided the list of currently designated gateways and establishes TCP connections to all the identified gateways. Such TCP connections are used to pass requests from the SM to the GW and to monitor the availability of the GW during the life of the session. The list of gateways to which an SM is able to connect constitutes a list of currently active gateways that is supplied to a newly connected SP as part of a participant startup protocol. When allocating a new multicast-based group communication channel, the SM requests the creation of a corresponding gateway server (GS) from each active gateway. Gateway servers are gateway components that can provide data packet relaying and rate adaptation services for multicast-disabled participants or participants with limited connectivity bandwidth. A GW is responsible for classifying whether an SP is multicast-enabled or disabled by means

of a multicast capability test. If this SP is multicast-disabled, a round trip time (RTT) measurement is conducted between the SP and the set of designated GWs for this session. The purpose of the RTT measurement is to identify which GW will service this SP, i.e., provide data packets relaying functionality to this SP. The GW with the minimum RTT is selected as the candidate GW to service this SP. Other factors affecting the candidate GW selection are GW load, and network path bandwidth between the SP and each GW. Incorporating such factors in the candidate GW selection process is left for future investigation. The SP reports back to the SM the results of its multicast test, and if multicast-disabled, the candidate GW. A SP needs to be informed if its serving gateway becomes unavailable during the life of the session. Hence, the SM uses its GW permanent TCP connection to sense if a GW becomes unavailable and informs all session participants serviced by that GW. In this case, each affected SP attempts to recover by choosing a new candidate GW.

Gateway Design Gateway servers handle a specific multicast-based group communication channel and hence are supplied with the multicast group and port used for this channel in the high-speed multicast-enabled intranet. When a GS receives a new datagram packet from one of its clients, it extracts the payload of the packet and encapsulates this payload into datagram packets destined for each individual serviced client except the originating client. Such datagram packet processing is the same whether the data packet was received from a multicast group or from one of the SPs currently serviced by this GS. In addition, this approach does not preclude the GS from serving other SPs that are multicast-enabled but only require rate-limiting or media transcoding. Tool-sharing, layout management, pointer, and annotation services require generic gateway

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servers. However, video and audio services are RTP-based and hence require an RTP gateway server. In our current prototype, RTP gateway servers are implemented using the Java Media Framework (JMF) (http://java.sun.com/products/ java-media/jmf/index.html). Adopting a relay approach creates a problem for video window identification for purposes of layout management within the SP’s interface. A video window identifier is based on the originating sender machine IP address. Obviously a video stream received at the multicast-disabled SP will be identified as originating from the GW and not from the original video sender. To solve this problem, an identified video source at the SP is inspected to determine if it is a gateway machine, and if so it is contacted to retrieve the original video sender machine name corresponding to the relayed RTP stream. To provide such lookup functionality, each GS stores the SSRC (Synchronization Source) (Schulzrinne, 1996) for each generated RTP stream. Another functionality of gateway servers is to perform rate limiting or media transcoding, if required, to cope with the expected limited connectivity bandwidth for home users. For example, a video gateway server might drop video frames, or transcode the incoming video stream to a less bandwidth consuming video format. Tool-sharing and video streams are the most bandwidth consuming streams within IRI-h services (Maly et al., 2001). IRI-h video streams use a JPEG capture format, hence can be rate limited by dropping entire video frames. The tool-sharing data stream requires a buffering and flow-control approach in order to effectively implement rate limiting and smooth peak bit rates (bursts).

Recording and Playback Service In this section, we present the design and functionality of the recording and playback service. Six main streams need to be recorded for proper playback: video, audio, tool-sharing, annotations, pointer, and layout management. Each stream

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is recorded along with the timing information needed for future synchronized playback. Figure 6 depicts the architecture of the recording service. A recording agent runs on a separate machine (the recording and/or replay server) that can be regarded as a special purpose participant. Such architecture has the advantage of enabling playback of recorded sessions during live sessions. As illustrated in Figure 6, the recording agent spawns a different thread upon the reception of a new stream from any of the multicast channels. Each IRI-h service requires a servicespecific recording agent. For each IRI-h stream, two types of files are recorded. The first contains the payload information for a specific stream, while the second type is either timing files for audio and video streams or token information for token-controlled services (tool-sharing, pointer, annotation, and layout). Because storage requirements are a concern, several experiments were performed to measure typical values of storage spaces. In a typical IRI-h session, assuming the continuous presence of two videos, three audio streams, a shared application, and moderate use of pointer, annotations, and presenter services, an estimate for one hour’s storage is about 840 MB. This figure is affordable due to the reduction in storage media cost offered by current secondary storage technologies. Video recording agent (VRA): Up to three participant videos can be active at the same time. Hence, the recording agent can receive a maximum of three simultaneous video streams. Each of the received streams is processed and converted to a format suitable for storage (a QuickTime format in our case). Other timing information is stored in index files to facilitate synchronized playback of these streams. Audio recording agent (ARA): Unlike video streams, many audio streams can be active at the same time. For each received stream a separate audio processor is created whose function is to process the stream by converting it into a basic audio (.au) format then saving it on secondary

The Essential Elements of Interactive Multimedia Distance Learning Systems

Figure 6. The architecture of the recording service Session Manager

Recording server

Recording Agent (RA) SP

SP

VRA video

ARA audio

LRA layout

IPVA sharing PRA pointer

ANA annotation

Secondary Storage

Semi-reliable multicast channels TCP connection Data path to disk

storage. The timing files mark the beginning and end time stamps (TSs) of all received streams. All TSs are measured at the receiver side for both audio and video index files. This is mainly due to the variable times taken by each processor to be created, and consequently we are recording all TSs at the receiver side. Tool-sharing recording agent (IPVA): Tool sharing is provided by IPV (Gonzalez, AbdelWahab, & Wild, 2001). The IPV recording agent listens to the specific multicast channels for IPV streams and directs any received payload to disk files along with the required time indexes. More than one IPV application can be shared at a time provided that each sender is on a different machine. A separate thread is created for each IPV stream to handle any simultaneously active streams. Pointer recording agent (PRA): The coordinates of the pointer are sent periodically as

Thread Multicast connection

packets over the multicast channel. These packets are captured by the recording agent then directed to a disk file following a specific protocol for organizing the recorded data. The pointer is a token-controlled service that only one participant can control at a time. Thus, in addition to normal pointer packets, token events are recorded in order to duplicate what happened in the live session during future playback. Annotations recording agent (ANA): Performs a function similar to the pointer agent with the difference that annotation objects (circles, polygons, text, etc.) are the recorded payloads instead of pointer packets. Layout recording agent (LRA): The semantics of the shared view in IRI-h is achieved if all participants can see exactly the same view. To preserve that assumption during playback, windows’ location information is recorded during a

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live session. In addition, the layout management token events (change of presenter) are recorded since this service is token-controlled.

Playback Service The replay functionality can be invoked by any session participant upon startup or later during the course of the session. Replay services differ from normal IRI-h services in that they only require the receiver component of the service and do not need a sender component (see Figure 2). A participant can navigate through the recording archive and select the class, semester, and date of the session to be played back. Every class member can initiate replay with the restriction that the initiator of the replay must hold the presenter token. After browsing the recording archive and selecting a session to be replayed, the initiator participant needs to communicate the selected session to the replay machine through the session manager. At the replay server, a separate reader reads each recorded stream file, i.e., payload data and timing information, and sends the payload data over the multicast channel based on the timing information. Each reader tries to emulate the functionality of one IRI-h service and sends payload information using the same data packets’ format as live session packets. Moreover, any IRI-h visual effect that occurred in a live session is replicated in the replayed session, for instance the change of the color of the indicator light signaling whether a participant currently has the presenter token. In order to extend late join functionality to accommodate replay services, an observer is associated with each of pointer, annotations, and layout replay services. The purpose of such an observer is to maintain the current state of the service. For example, all annotation objects sent within the current annotation frame are saved and later sent to the multicast channel when a late joiner logs in. This insures that all late joiners get the current status of all replay services. The

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current prototype implementation does not allow recursive playback, i.e., playback of a recorded session that contains a previously recorded session. We limit the level of playback recursion to one due to the performance capability of current machines. Recorded sessions can be replayed during a live class, either as part of the lesson plan or in response to questions from students regarding previously covered material. Because the availability of events that are recorded along with the information streams (e.g., who has control of the token, when does a student speak, etc.), it is possible to more quickly access relevant material than is possible using VCR replay technology. We are working on adding additional semantic information (such as titles of slides or URLs of browsed sites) that would allow the selection of semantically related material to be presented over all class sessions. In addition, one issue that we leave for future research is the availability of class material for online access through the Web, using any Web browser without the need to actually start an IRI-h session.

INTERACTIVE DISTANCE LEARNING SYSTEMS’ FEATURES REVISITED In this section, we summarize how the interactive distance leaning systems’ features, identified earlier, are manifested in IRI-h design and functionality. We attempt to clarify, where appropriate, how the availability of a feature affected the design and components of IRI-h. 1.

Audio and video conferencing: Audio and video conferencing is fully supported in a platform-independent manner. Desktop landscape and bandwidth limitations necessitated a management scheme for video transmitters. Up to three video windows can be active at any point of time, with one

The Essential Elements of Interactive Multimedia Distance Learning Systems

2.

3.

4.

of the video senders acting as a presenter. Similarly, an audio transmitter’s management scheme is imposed to limit the number of participants able to join a discussion; this is currently set to ten participants. Application sharing: IPV (interactive program video) (Gonzalez, Abdel-Wahab, & Wild, 2001) offers tool-sharing capabilities. Any desktop application with multiple windows can be shared. Windows applications are shared directly. Unix applications can be shared by running on a PC through an X server. A tool-sharing engine relying on capturing shared windows necessitated a separate dedicated machine to be deployed as an “application server.” Hence, a subsequent problem presented itself in how to remotely control such dedicated machines. We devised a session-independent solution based on remote controlling the application server desktop from the teacher machine by using the remote desktop sharing capabilities in Microsoft Windows NetMeeting (http:// www. microsoft.com/windows/netmeeting). We are currently developing a session-integrated customized remote desktop control solution that will allow selecting tools to be shared, and control sizes and positions of such tools’ windows. Scalable group communication: A group communication API provides a middleware layer for IRI-h services. Where applicable, multicast communications is adopted as a scalable group communication implementation. Audio and video streams use unreliable multicast communication. However, data streams rely on a semi-reliable multicast scheme. Application-level gateways: Session-independent gateways are deployed within high-speed multicast-enabled Intranets. Availability of gateways enables the system to handle network heterogeneity, however raises several issues which we attempt to

5.

6.

7.

8.

summarize along with our current solutions. How does a participant know about • the availability of a gateway? Through a session manager participant startup protocol. How does a participant know if she re• quires services of a gateway? Through a multicast capability test with the set of available gateways. Which gateway serves the participant? • The gateway with the least round trip time (RTT) measurement to the participant. Recording and playback: IRI-h sessions are by default recorded. Recording functionality is provided through a deployed specialized session participant, the Recording and/or Replay server. In-session playback of previously recorded sessions is provided. The ability to access recorded material independent of the session, for example through Web access, is left for future work. Common shared view: We enforce a common shared view policy in which shared view updates, such as windows movements and resizing, are propagated to other participants which requires a layout management service. Changes to the shared view are token controlled and only allowed by the current presenter. Presentation aids: Annotation and pointer services are provided as part of IRI-h services. Access to both services is token controlled. The token holder of either the annotation or pointer service might be different than the current presenter. This is useful in situations where for example a student would like to point a location in the common shared view to ask a question, while an instructor has the presenter token. Note taking and post-session notes availability: A note-taking tool is provided with the ability to upload notes into an IRI-h

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repository for post-session access through a Web browser. The note-uploading capability requires the availability of a back-end notes server that receives and stores the notes . 9. Monitoring and feedback: Several monitoring and feedback tools are available within IRI-h. A site video tool provides a capability to monitor students in remote sites. A class monitor provides the current list of participants along with a summary of their network connectivity capabilities. A services’ state monitor reports on the state of various IRI-h services at each participant, for example a transmitted video stream bandwidth, and the total video bandwidth received by a participant. A log viewer permits inspection of current status and/or error messages generated by all session participants and the session manager. Integration of intelligent feedback tools to report and adapt to network delays and congestion is planned for future work, e.g., feedback between a participant and the serving gateway. 10. Simple interface: The IRI-h interface is role-based, which implies it can be customized for students or teachers and session administrators with more control capabilities for teachers and administrators, and a concise set of capabilities for students. A human-machine interface study may be required to evaluate how each type of user perceives the current interface design. 11. Tutoring and subgroup collaboration: Virtual rooms offer opportunities for subgroup work. Session participants can be subdivided into groups for smaller group discussions or collaborative work. Supporting virtual rooms affects graphical user interface design, group communication channels allocation, and gateway servers operation. The current IRI-h interface operates using only one virtual room. Nevertheless, the underlying group communication channel allocation

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process and the operation of gateway servers fully support n virtual rooms. 12. Testing and evaluation tools: A sessionintegrated testing or evaluation tool is not currently part of the IRI-h prototype. Nevertheless, the previous IRI system (Maly et al., 1997 offered an in-session exam tool by directing a student web browser to a Learning Space (http://www.lotus.com/home. nsf/welcome/learnspace) server that hosted assignment and exams for IRI courses. A similar approach is feasible within IRI-h. 13. Administration tools: IRI-h administration tools can be classified as offline, startup, and in-session management tools. Offline and startup tools are Web-based for “anywhere” accessibility. Offline tools allow management of various configuration files, for example, identification of available Intranet machines and servers within sites, creation of new classes along with lists of participants, and access to participants’ session notes (http://www.cs.odu.edu/!iri-h). Startup tools automate the startup of a session by selecting required server machines and actually performing a startup process, where a session is initiated on participating intranet machines (Maly et al., 2001). In-session management tools include a call-student tool that offers the capability to remotely call upon students to join an ongoing discussion, or to present their class material, hence activating their video and audio transmission.

CONCLUSION AND FUTURE wORK In this chapter, we presented the basic building blocks for interactive multimedia distance learning systems as typified by the IRI project at Old Dominion University over the last six years. The latest version of IRI, called IRI-h, is completely written in Java and provides a plat-

The Essential Elements of Interactive Multimedia Distance Learning Systems

form-independent virtual classroom with audio, video, tool-sharing capabilities. Furthermore, network heterogeneity is overcome by deploying application-level gateways to serve less-capable participants, in terms of multicast capability and connectivity bandwidth. In addition, asynchronous learning capabilities are provided through recording and playback services. Experiences with an IRI-h prototype demonstrated design feasibility and student acceptance, but required an expected administration overhead to set up and maintain IRI-h sessions. Future IRI-h session management work includes implementing the virtual rooms functionality, including initial setup of a session with several virtual rooms, extending the session participant interface to allow for creation and removal of virtual rooms, navigation through a set of virtual rooms, and effect of multiple virtual rooms on existing components’ functionality such as recording, playback and gateway services. In addition, we are currently developing a customized solution for remote desktop control of the application server machine. Future application-level gateways work includes implementing rate control and bandwidth management policies (e.g. Amir, McCanne & Katz, 1997). Moreover, we will explore the use of semantic information to guide the intelligent dropping of data streams to reduce bandwidth when necessary and the addition of priorities to relayed data streams, for example prioritize more crucial audio streams over other session streams. In addition, we intend to research the effect of delays introduced by buffering and flow control on the interactivity feature. Finally, we are currently in the process of establishing a test bed to evaluate IRI-h’s performance using currently available high-speed home connections such as xDSL and cable modem technologies.

REFERENCES Amir, E., McCanne, S., & Katz, R. (1997). Receiver-driven bandwidth adaptation for light-weight sessions. In Proceedings of ACM Multimedia 97 (pp. 415-426). Seattle, WA. Deering, S. (1989). Host extensions for IP multicasting. Request for Comments (Proposed Standard) 1112, Internet Engineering Task Force, August. González, A.J., Abdel-Wahab, H., & Wild, J.C. (2001).Lightweight scalable tool sharing for the Internet. In Proceedings of the 6th IEEE International Symposium on Computers and Communications (ISCC2001) (pp. 86-91). Hammamet, Tunisia. Hilt, V., & Kuhmünch, C. (1999). New tools for synchronous and asynchronous teaching and learning in the Internet. In Proceedings of The World Conference on Educational Multimedia, Hypermedia & Telecommunications 1999 (ED-MEDIA and ED-TELECOM 1999), Seattle, WA. Ibrahim, B., & Franklin, S. (1995). Advanced educational uses of the World-Wide Web. In Proceedings of the 3rd Int’l Conference WWW Conference (WWW3), Darmstadt, Germany. IRI-h home page, at URL http://www.cs.odu. edu/~iri-h Sun’s Java home page, at URL http://java.sun. com/ Sun’s Java Media Framework (JMF) home page, at URL http://java.sun.com/products/java-media/ jmf/index.html IBM’s Learning Space at URL http://www.lotus. com/home.nsf/welcome/learnspace Maly, K., Abdel-Wahab, H., Overstreet, C.M., Wild, C., Gupta, A., Youssef, A., Stoica, E., & Al-Shaer, E. (1997). Distance learning and train-

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ing over intranets. IEEE Internet Computing, 1(1), 60-71 Maly, K., Abdel-Wahab, H., Wild, C., Overstreet, C.M., Gupta, A., Abdel-Hamid, A., Ghanem, S., González, A.J., & Zhu, X. (2001). IRI-h: A Javabased distance education system: Architecture and performance. ACM Journal for Education Resources in Computing (JERIC), 1(1). Microsoft’s NetMeeting home page, at URL http:// www.microsoft.com/windows/netmeeting/. Schulzrinne, H.(1996). RTP: A transport protocol for real-time applications. Request For Comments (Proposed Standard) 1889, Internet Engineering Task Force, January.

Synnes, K., Lachapelle, S., Parnes, P., & Schefstrom, D. (1998). Distributed education using the mStar environment. In Proceedings of the World Conference on the WWW and Internet 1998 (WebNet 1998), Orlando, Florida. Whetten, B., Montgomery, T., & Kaplan, S. (1994). A high-performance totally ordered multicast protocol. Theory and Practice in Distributed Systems (LCNS 938, pp. 33-57). Springer Verlag. Yaskin, D., & Gilphus, S. (n.d.). Introducing the Blackboard 5 Learning System. http://company. blackboard.com/docs/cp/orientation/Enterprise LearningWhitePaper.pdf

This work was previously published in the International Journal of Distance Education Technologies, Volume 1, No. 2, edited by S. Chang and T. Shih, pp., 17-36, copyright 2003 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 2.17

Using Virtual Instrument to Develop a Real-Time Web-Based Laboratory Kin Cheong Chu Hong Kong Institute of Vocational Education, Hong Kong

ABSTRACT In this study, an online experiment was developed for sub-degree students at remote locations to control and obtain real-time measurements or experimental data. Online video is set up for better visual impact of what is going on in the remote site. The intention of this Web-based laboratory package is to make the experiment more interactive, attractive, and easily accessed. Background knowledge is included for better understanding of the theory behind the experiment and gives an overview of the operation of the remote controlled software used in this remote laboratory. Multimedia elements including sound, video, and animation are added for better explanation and easier understanding of software as well as basic theory for this remote laboratory. This remote equipment control and monitor was

added as a supplement laboratory to a class of engineering students. Positive feedback from students was obtained through questionnaires and interviews. These results throw light on doing remote laboratory through the Internet and direction for improvement.

INTRODUCTION Most distance learning development programs are focused on online lectures and tutorials. A practical training system that allows instruments to be monitored and controlled over the Internet leaves a lot of room to be studied. This training system can easily be turned into an online experiment that allows students at remote locations to control and obtain real-time measurements or experimental data (Tan & Soh, 2001).

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Using Virtual Insrument to Develop a Real-Time Web-Based Laboratory

Actually, there has been an increasing emphasis on student experience in higher education, focusing not only on the development of academic and intellectual capabilities and subject knowledge, but also on the development of skills to equip students for employability (Noble, 1999). Also, some students like to read books while others prefer to experiment (Whelan, 1997; Chu, 2000). Both of these knowledge-based and investigative types of learning styles have profound and different effects on the delivery and acceptance of engineering education. The teaching of engineering subjects is bound to include a variety of rules, theorems, and devices, which involve primarily knowledge-based learning, and must be understood by the students. But at the same time students must also learn how to apply the learned knowledge through problem solving and design exercises (Ericksen & Kim, 1998). This provides another good reason to support remote-access practical work for this Web-based or virtual teaching system. Study at East Carolina University also finds that the virtual laboratory helps students understand the concept and theory of those online courses (Yang, 1999). There are an increasing number of virtual laboratories provided by universities and distance learning institutes (Tan & Soh, 2001). A virtual laboratory developed by using a simple matrix assembly Java applet provides an instrument simulator which forms a powerful auxiliary didactic tool to give students a basic idea of the instruments, control and operation (Cabell, Rencis & Grandin, 1997). Another laboratory running remotely via a Web interface allows user to conduct experiment in the Control Engineering Laboratory at Oregon State University (Shor & Bhandari, 1998). The Bytronic Process Control unit at Case Western Reserve University can be accessed remotely via the Internet (Shaheen, Loparo & Buchner, 1998).

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Comparing with the traditional laboratory, the virtual laboratory is particular useful when some experiment involving equipment may cause harmful effects to human beings. The laser virtual laboratory developed by the Physics Department of Dalhousie University (Paton, 1999) shows how to perform a real-time dangerous laser experiment with the help of commanding equipment through the Internet. Another objective of a virtual laboratory is to provide remote hands-on lab activities to enhance online courses. Ko (Ko, et al., 2000) creates a virtual laboratory system using real-time video capture of actual oscilloscope display rather than simulating the oscilloscope display on the client. The use of the mouse to turn the control buttons and knobs of the oscilloscope has been implemented so that a more realistic feel of the instrument is provided. Sharing resources is another strong point to control laboratory via the Internet (Henry, 1998). At the University of Tennessee, equipment of the chemical department can be shared by other engineering schools after introducing a Web-based laboratory. One thousand first-year undergraduate engineering students also experience the Webbased oscilloscope experiment at the National University of Singapore (Ko et al., 2000). This increase of utilization rate of equipment via the Internet compared with traditional laboratory has another effect—to provide more learning opportunities for students with scheduling conflicts (Henry, 1998). Funded by the Hong Kong Industry Department, a consultancy project concerning a virtual instrument from Hong Kong University of Science and Technology was given to the Hong Kong Institute of Vocational Education (Tsing Yi). This study was based on the result of this cooperative industrial project to further develop an online experiment for students at remote locations to control and obtain real-time experimental data.

Using Virtual Instrument to Develop a Real-Time Web-Based Laboratory

The intention of this Web-based laboratory package is to make the experiment more interactive, attractive, and easily accessed. Online video, which is for better visual impact of what is going on in the remote site, is sent to the user through a real-time video server. Background knowledge is included for easily accessing the theory behind the experiment and gives an overview of the operation of the remote controlled software used in this remote laboratory. Multimedia elements including sound, video, and animation are added for better explanation and easier understanding of software as well as basic theory for this remote laboratory.

DESIGN OF REMOTE LABORATORY An interactive Web-based laboratory for the subject ‘Digital Electronics’ was set up. Students are no longer limited to information provided by traditional laboratory sheets. Updated laboratory sheets and digital video instructions can be distributed to students through the Internet and displayed on a Web browser. Students are able to conduct simple logic experiment anywhere through their computers via the Internet. They simply undertake work using the graphical virtual environment provided by the software LabVIEW to test their logic design. On the other hand, students have a real hands-on experience by remotely accessing instruments set up on the laboratory through the Internet. They just select the suitable logic levels or analog waveforms inputted to the circuit. All the outputs from the logic circuits are monitored through the real-time video display transmitted back to the students’ homes. Students will have a feeling that they are doing a real logic experiment at home. The current content of Web-based laboratory includes the following parts and the design is aimed to be interactive, easier to learn, and interesting to the student.

Background Information For a traditional laboratory, the background section does not provide enough information for reference. Students have to bring a textbook, notes, or other information searched from a library. However, the Web-based laboratory system is designed to be self-contained. All necessary basic concepts and theories tailor-made to perform the corresponding experiment can be found in this background section (Figure 1). This saves students time in finding related information to support them in conducting the experiment in different sources or locations. Students can easily review the basic knowledge before going to perform the Web-based experiment or they just refer back to this section once they find something that is not clear. Also, the information is explained in a hierarchical way to suit students with different backgrounds. A short test is included in this section to let students review how much they have learned for these topics.

LabVIEw Seminar LabVIEW is easy-to-use software that can rapidly create control and automation applications using intuitive graphical development. Combined with simple hardware, this software allows a user to connect to equipment in the laboratory through standard industrial buses. More important is that this software prepares the Internet remotely accessed program quite easily. However, users of this Web-based laboratory may not be so familiar with the software LabVIEW. This section provides detailed (Figure 2) and short guidelines (Figure 3) of using LabVIEW. For the detailed guideline, description of what the LabVIEW software is and how to write graphical programming into it will be found in this part. This is suitable to users without much knowledge of using LabVIEW. For the short guideline, only brief explanation in point form is included for quick reference. This

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Figure 1. Background section to supply necessary information

Figure 2. Detailed guidelines

Figure 3. Short guidelines

is prepared for those with previous knowledge or for users who would like to obtain an idea of how to use LabVIEW quickly in a short period of time. Examples of practical circuits designed by using LabVIEW are also included in this section for reference.

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In traditional laboratory, teachers usually explain the content of the experiment verbally beforehand. This multimedia explanation and demonstration

Using Virtual Instrument to Develop a Real-Time Web-Based Laboratory

section provides a similar function; but with the help of multimedia technology, they are more interesting and easier to understand. Figure 4 shows one of these video demo for explaining how to construct a circuit using LabVIEW. In addition, this section provides different video and audio aids to demonstrate the construction

and running in different simulation environments (Figure 5). In order to give students a sense of hands-on experience and experimental operation, video aids are included to introduce equipment and integrated circuits used in the real laboratory as well as operation and safety procedures.

Figure 4. Video clip to demonstrate the LabVIEW circuit construction

Figure 5. Video clip to demonstrate the circuit simulation using MMLogic

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Download Section for Lab Sheet, Data Sheet and Shareware Simulator To perform a traditional experiment, the laboratory tables are messy with lab sheets, databooks, and equipment. To solve this problem, this section (Figure 6) provides an all-in-one location to obtain updated lab sheet, utility program (e.g., Adobe Acrobat), and simulation software (e.g., EasySim, MMLogic). All of these software are freeware or shareware and users can freely download them from corresponding Web sites. If students want to construct a real circuit, data sheets are included in this section. Students can simply open lab sheets and follow the procedures to perform the Web-based experiment at any time and any place. Any related information can be obtained through a search engine inside this section.

tion clips (Figure 7 and 8) to give an idea of what is going on in some practical circuits. A different combination of inputs can be selected on the left-hand side of the screen. Those paths that are logically “High” will be highlighted in the image so that users can understand better the flow of the signals from inputs to outputs. There are two real-time Web-based experiments prepared for users to complete from remote sites. The equipment setup is shown in Figure 9. The hardware involved in this remote control and monitoring are listed below: • • •

Remote Laboratory This section is divided into two parts – software simulation and real-time remote laboratory. For the simulation part, it uses the predefined anima-

Figure 6. Download section

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•

Two computers—one is for the server and the other is to simulate user in remote site Hub—to simulate remote access through Internet HP 54600 digital oscilloscope—for displaying result waveform from the circuit under test on the screen and sending captured data back to server HP 33120A function generator— for receiving command from the server and generating

Using Virtual Instrument to Develop a Real-Time Web-Based Laboratory

Figure 7. Simulation for half adder circuit

Figure 8. Simulation for full adder circuit

Figure 9. Hardware setup in the remote laboratory

•

•

selected analog testing signals inputted to circuit under test NI GPIB card—located inside the server and used for remote connection to the two HP instruments NI DAQ card—located inside the server and used for sending digital signal to the circuit

•

under test and receiving digital signal back from it Testing circuits—two set of testing circuits are prepared. One is for digital input/output test while the other is for analog input/output test

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Using Virtual Insrument to Develop a Real-Time Web-Based Laboratory

•

Web camera—for remote monitoring the whole process during the operation of the laboratory

LabVIEW supports Common Gateway Interface (CGI) to facilitate interactive remote access in this remote laboratory (Figure 10). With the LabVIEW Internet Developer Toolkit, you can easily create many powerful Web interfaces to LabVIEW (Bishop, 2001). Figure 11 shows that

CGI allows remote users to load and run a graphical LabVIEW program dynamically from a Web browser. Users can siimply fill out an HTML form and then it will indirectly pass those inputs to the LabVIEW program. The results will be published back to the Web browser at the remote site. Figure 12 shows the corresponding LabVIEW program responsible for CGI decoding and transmitting the HTML page back to the user with suitable responses from the system.

Figure 10. Remote access through CGI WWW Browser (on client)

Submit completed form

Server

application CGI

HTML form User

Figure 11. LabVIEW program for CGI control

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CGI program’s response

CGI program’s response

Using Virtual Instrument to Develop a Real-Time Web-Based Laboratory

Figure 13 shows the overview of the hardware connections of the remote experiment for a digital circuit. As it is real-time control, this Web-based remote laboratory can allow only one pre-registered student to access for control while other users can only monitor the result transmitted from Webcam. The remote user sends commands through the Internet to the server (Figure 13). Upon re-

ceiving the command, the server sets the logical levels of inputs to the digital under test through the NI DAQ card and other external hardware. The outputs generated from the corresponding inputs will then transmit from NI DAQ card back to the server and remotely display on the user’s screen. Webcam is implemented for monitoring the whole process. As the delay introduces by video server and the related infrastructure is very

Figure 12. Remote webpage control and result displayed in LabVIEW

Figure 13. Overview of the hardware connections

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Using Virtual Insrument to Develop a Real-Time Web-Based Laboratory

small (only less than one second), this gives the user a real-life feeling of what is going on at the remote site (Figure 14). Only the resolution of the Webcam prevents complex objects or circuits to be displayed clearly in remote site. This is actually a tradeoff between resolution and speed of transmitting the video.

this Web-based laboratory for two hours. Before trying this system, students had a 6-hour handson laboratory relating to the basic concept of the content of this system. This gave students experience with a traditional laboratory and a Web-based laboratory of the same topics, and they could make a comparison between these two types of experimental work.

EVALUATION OF THE SYSTEM

Instruments

Subjects

In order to assess students’ views of this laboratory approach, a questionnaire was given to each student immediately after their first experience of using this Web-based laboratory. In addition, students could freely write down their feedback to this study at the back of the questionnaire. Also, clearer feedback was obtained through short discussion with some groups of students shortly after the laboratory. The questionnaire aims mainly to obtain students’ views towards existing functions of the system, about learning how to use the Web-based laboratory, user interface, the needs of students

One hundred year-one sub-degree engineering students of the Hong Kong Institute of Vocational Education (Tsing Yi) joined the pilot test of this Web-based laboratory. Most of them are male students and all of them had their own computers or a computer shared with their families. In this study, students were divided into groups with around 10 students in a group. A demonstration for each group about how to use this Web-based laboratory system was arranged in a computer laboratory. After that they can freely access

Figure 14. Web-based remote laboratory for a digital circuit

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Using Virtual Instrument to Develop a Real-Time Web-Based Laboratory

in this Web-based laboratory, and comparison with a hands-on laboratory. All the students (N=100) responded to the questionnaire and the result was analyzed.

Results Table 1 displays the results obtained from the questionnaire. It shows the distribution of the selection (strongly agree(SA), agree(A), disagree(D), strongly disagree(SD)) for each question. From the overall result of questionnaire, most students show a positive attitude towards this Web-based laboratory system. When comparing to the traditional laboratory, many students (85%) agree that this system is easier to use than normal laboratory work. They need not care about the loose wire connection problem or availability of the components or

equipment. In fact, this system is better than the traditional laboratory by just verifying the design quickly and easier by using the simulation part of this system. This is why 81% of students are interested in doing experiments through virtual media. Many students (71%) even reflect that they are encouraged to spend more time experimenting using this system. Similarly, it is faster and easier to work in both simulated and remote control environments. Control parameters in the simulated environment can be changed easily until the optimum solution is obtained. That is why students report that this system is better than the normal laboratory environment in learning design work (75%) and learning concept (75%). With the help of multimedia environment and updated information displayed through the browser, students (80%) find that environment

Table 1. Result of the questionnaire

Question You like the information provided in the background section. You like the video/animation demo in the multimedia section. You are interested in doing experiment through this virtual media. You will spend more time in doing practical work after using web-based laboratory. After doing the experiment using web-based laboratory, it can review how much you learn from the topic taught. Web-based laboratory is easier to do than normal laboratory work. Web-based laboratory is better than normal laboratory work in learning concept. Web-based laboratory is better than normal laboratory work in learning design work. Web-based laboratory can replace normal experimental work in the laboratory. You would like some quizzes in the content.

SA (%) 25

A (%) 55

D (%) 20

SD (%) 0

SA +A (%) 80

SD +D (%) 20

38

59

3

0

97

3

19

62

19

0

81

19

20

51

25

4

71

29

17

62

21

0

79

21

24

61

14

1

85

15

16

59

21

4

75

25

19

56

23

2

75

25

19

36

40

5

55

45

14

60

20

6

74

26

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Using Virtual Insrument to Develop a Real-Time Web-Based Laboratory

of this system is easier for them to obtain the necessary background information than from the normal laboratory sheet. Also, 97% of students like the video/animation demonstrations. The only comment from students about these demonstrations was the poor video quality. Actually, this is the trade off between download speed and quality. There is a small test included in the background section to let students review how much they are familiar with the topic. Students like this way of reflection and many of them (74%) like more quizzes provided in the content to test their understanding of the topic before or after doing the remote experiment. However, nearly half of the students (45%) disagree that this system can replace normal experimental work in the laboratory during the survey because they consider that the traditional laboratory environment provides real hands-on experience to them. This kind of real hands-on experience cannot easily be achieved from Webbased simulation or remote laboratory. Feedback from students shows that practical experience can help students to learn deeper. They like to work with the help of Web-based laboratory to understand basic theories before completing the real experiment in the laboratory.

CONCLUSION The current interactive remote control technology was implemented in this Web-based laboratory system. Most previous studies of similar topic were set up for undergraduates. This system was built and tried to find out the response from a group of sub-degree engineering students. This Web-based laboratory was different from the previous system of similar nature. It was developed mainly using LabVIEW technology and this could simplify a lot of remote control software development. With the Internet Toolkit

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of LabVIEW, a programmer can create CGI using standard graphical programming techniques of accepting information from a client (e.g., Web browser). This is much easier to use and can be developed by a less experienced software engineer. The current non-stop Web-based laboratory system provides a multimedia learning environment to motivate students, and promotes a more active form of learning. Users can perform this system at any time and any place atb their own pace. Feedback from those sub-degree students indicates that they also like this innovative webbased working environment and interactive video demo. They feel encouraged to learn in this way and would like to integrate this Web-based laboratory into the lecture notes. Although positive feedback was collected from students, this Web-based laboratory has potential limitations in the current design. For a simple experiment, the development or setup cost is relatively higher than the conventional laboratory. This system is more suitable for providing simulations of complex or dangerous scientific processes that are less likely to occur in a normal laboratory. Video quality is another part of this system that needs to be improved. Better video will let students know what is happening in the distance laboratory and study clearly the change of outputs corresponding to different inputs. With the help of popular use of boardband connection and advance technique of image compression, better video quality with limited file size can be achieved in the near future. The number of students concurrently accessing this system is also limited, unless more setup time and equipment are available remotely at the laboratory. The fact that the students do not have real hands-on experience is considered a disadvantage to the students, especially from the engineering classes. Feedback from students reflected that they like to learn from mistakes. The Web-based

Using Virtual Instrument to Develop a Real-Time Web-Based Laboratory

laboratory is well prepared against human errors, especially in connecting wires between circuits or component. Although the survey reflects students’ disagreement to the assumption that this system can replace normal experimental work in the laboratory, more future studies are encouraged to find out what and how we can convince the students to use the Web-based laboratory to replace the traditional laboratory.

ACKNOwLEDGMENTS The author would like to thank Chan Ho Ming and Lee Ka Shun for their help in developing the Web-based laboratory package for this study. Appreciation is also given to Queendy Lam for her support and verification of this paper.

REFERENCES Bishop, R.H. (2001). LabVIEW Student Edition 6i. Englewood Cliffs, NJ: Prentice Hall. Cabell, V.B., Rencis, J.J., & Grandin, H.T. (1997). Using Java to develop interactive learning material for the WWW. International Journal of Engineering Education, 6(13), 397-406. Chu, K.C. (2000). On-line interactive manual. The Hong Kong Educational Research Association 17th Annual Conference, Hong Kong. Ericksen, L., & Kim, E. (1998). Projects for the Internet. Addison-Wesley.

Henry, J. (1998). Running laboratory experiments via the World Wide Web. American Society for Engineering Education Annual Conference, USA. Ko, C.C., et al. (2000). A large-scale Web-based virtual Oscilloscope Laboratory Experiment. Engineering Science and Education Journal, 2(9), 69-76. Noble, M. (1999). Enhancing academic practice, teaching and learning for employability, Handbook for Teaching and Learning in Higher Education. Academic Press. Paton, B. (1999). sensor.phys.dal.ca. Virtual Laser Laboratory Shaheen, M., Loparo, A., & Buchner, M.R. (1998). Remote laboratory experimentation. In Proceeding of yhe American Control Conference, Philadephia (pp. 1326-1329). Shor, M., & Bhandari, A. (1998). Access to an instructional control laboratory experiment through the WWW. In Proceedings of the American Control Conference, Philadephia (pp. 1319-1325). Tan, K.K., & Soh, C.Y. (2001). Instrumentation on the Internet. Engineering Science and Education Journal, 5(6), 61-67. Whelan, P.F. (1997). Remote access to continuing engineering education (RACeE). Engineering Science and Education Journal, 5(6), 205-211. Yang, B. (1999). Virtual Lab: Bring the handson activity to online courses, American Society for Engineering Education Annual Conference, USA.

This work was previously published in the International Journal of Distance Education Technologies, Volume 2, No. 1, pp. 18-30, copyright 2004 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 2.18

Evaluating Online Learning Applications:

Development of Quality-Related Models Leping Liu University of Nevada, Reno, USA

Abstract The purpose of this study was to explore the influence of the design-quality of current online K-12 learning applications on student learning via three learning-related variables (student enjoyment, motivation, and anxiety level when using those online applications). Nine hundred online K-12 applications (WebQuests, online drills, games, tests, and other applications) were evaluated in terms of four design factors (quality of information, design of information, quality of technology use, and design of technology use) in relation to the three learning-related variables. Three prediction models were generated and tested in this study. An intermediate effect was found between the design of online application and student learning, which may provide some insights for teachers when they integrate online applications

into teaching and learning. The target audience of this paper may be school teachers, designers, or professionals who use online applications for education purposes.

Introduction The Internet has been used in many ways to promote teaching and learning (Aviv & Golan, 1998; Barnard, 1997; Berge, 1997; Coombs & Rodd, 2001), from the use of Web-based resources to the employment of Web-based instruction (Berge, Collins & Dougherty, 2000; Bonk, Cummings, Hara, Fischler & Lee, 2000; Miller, & Miller, 2000; Fishman, 1997; Riel, 1992; Trentin, 2001). In the literature, one common use of the Web in K-12 teaching and learning appeared to be the

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Evaluating Online Learning Applications

utilization of existing online learning applications, such as tutorials, drills, games, or video products that were developed and posted onto the Web by other educators or designers (Liu, 2001; Murphy, 2004; Shelly, Cashman, Gunter & Gunter, 2003). It is hard to imagine and estimate the number of learning applications available on the Web today: a Google search on “math game” could result in 691,735 items; and a random exploration on 10 links found that, on average, 25 to 35 online math games were under each link. Unfortunately, the effectiveness of using those online learning applications on student learning achievement was ambiguous (Maddux, EwingTaylor & Johnson, 2002). In a study that consisted of 102 technology integration cases, Johnson and Liu (2000) found that the use of existing Web activity did not contribute significantly to either the success of the technology integration or to student learning-outcome. The issue is that if the use of those online applications could not effectively improve learning, such a tremendous amount of resources would be a huge waste, and sometimes may cause confusion. Many studies have explored the possible causes of such unsatisfied use of the Web and suggested that a lack of design was one common weakness in educational applications such as online communication, online courses, and online instructional content or activity (Boer & Collis, 2001; Liu, 2003; Liu & Maddux, 2003; Schweizer, Whipp, & Hayslett, 2002). The purpose of this study is to explore the influence of the design-quality of current K-12 online learning applications on student learning. In this chapter, the definitions and major types of K-12 online learning applications are introduced first. Next, variables examined in this study are identified, including four design-related variables (quality of information, the design of information, quality of technology use, and the design of technology use) that are derived from a technology integration model (Liu & Johnson, 2003a, 2003b; Liu & Velasques-Bryant, 2003)

and three learning-related variables (enjoyment, motivation, and anxiety) that have been found to have direct impact on learning achievement (Liu & Johnson, 1998; Liu, Maddux & Johnson, 2004). The four design-related variables then are used to evaluate the quality of 900 online K-12 learning applications in relation to the three learning-related variables. At the end, a set of qualityrelated models that illustrate the relationships are generated and tested.

ONLINE LEARNING APPLICATIONS Definition In the context of current study, the term online learning application can be defined as any entity of instructional contents or activities delivered through the Web that has the following features: 1. 2. 3. 4.

Intends to teach a focused concept; Meets specific learning objectives; Provides a learner-centered context; and Is an individual piece that can be used and reused.

The concept of learning application in this chapter is very much similar to that of a widely discussed term—learning object—where a learning object is an object-oriented application (Barker, Winterstein & Wright, 2004; Dodero, Aedo & Diaz, 2002; Murphy, 2004). The author carefully chose not to use the term learning object because some learning applications examined in this study were not object-oriented, and could not concisely fit the definition of a learning object.

Types of Online Learning Applications A learning application can present learning content, provide learning activity, contain simulation,

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Evaluating Online Learning Applications

or allow for student assessment. Generally, types of online learning application can be sorted by format and function. Two major formats of online learning applications are hypertext format and hypermedia format. Hypertext-format learning applications are developed with HTML or other hypertext editors. Examples are WebQuests, online lecture notes, reading materials, or other text-based instructional materials. There are two types of hypermediaformat learning applications. One type includes applications developed directly with scripting language such as HTML, DHTML, XHTML, or JAVA, incorporating multimedia products such as graphics, animations, and video or audio clips. The other type includes those initially developed with multimedia authoring software such as Flash, Director, Authorware, ToolBook, or HyperStudio. They are converted to Web run-version and then published onto the Internet. Examples are online games, drills, tests, or video products. Two major functions of current online learning applications are providing information and providing interactions. Some applications are developed to provide content information or guidelines to learning activities, most of which are hypertext format. Some dynamic Web activities or those predesigned multimedia instructional programs are developed to carry out interactions, which enable users to interact with the learning application directly from the Web. Currently, more and more online learning applications tend to have both functions. To select an appropriate online learning application for students, teachers may want to consider whether its format and function fit the learning objectives, content structures, the nature of activities, or the grade level of the students. The selections usually are based upon the designrelated quality of the application.

VARIABLES EXAMINED IN THIS STUDY Design-Related Variables According to a design model Liu and VelasquesBryant (2003) summarized from a 20-year review of research and practice in the field of technology integration, successful design of a technologybased instructional application should reflect the merge of three components: information, technology, and instructional design. Based on this model, four variables are identified to measure the design-related quality of an online learning application: 1.

2.

3.

4.

Quality of information: Evaluates the quality of content information (e.g., the accuracy, clarity, currency, or verifiability of the contents). Design of information: Measures the extent to which instructional design components are integrated into the content (e.g., audience analysis, content analysis, assignment design and delivery, assessment implementation, or the match between the required thinking skill and the developmental stage of the targeted audience). Quality of technology use: Measures the quality of technology applied in the learning application (e.g., screen design, orientation, navigation, or interactions). Design of technology use: Examines the extent to which instructional design principles are integrated into the use of technology (e.g., the match between content information and the media use or delivery methods, or the match between required technology skill and the grade level of targeted audience).

All online learning applications in this study were evaluated with these four design-related variables in relation to three learning-related variables.

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Evaluating Online Learning Applications

Learning-Related Variables

1.

Research findings suggest that student learning achievement is influenced by three variables: enjoyment, motivation, and anxiety (Liu, 1999; Liu & Johnson, 1998; Liu, Maddux & Johnson, 2004). Students tend to have better performances and higher achievement scores when they enjoy learning (King & Bond, 1996; Temple & Lips, 1989), when they are motivated to learn (Clariana, 1993; Kellenberfer, 1996; Keller, 1983), or when they feel less anxious to learn (Ayersman, 1996; Liu, 1997). This study examined these three learning-related variables in terms of how students feel about using an online learning application:

2.

1.

2.

3.

Enjoyment. Measures the degree to which a student enjoys learning with an online application; Motivation. Measures the extent to which a student is motivated to learn with an online application; Freedom from anxiety. Measures the anxiety level of a student when he or she learns with an online application.

According to the purpose of this study, the three learning-related variables were examined to determine an intermediate effect as described in the following logic procedures.

UNDERLYING LOGIC OF THE STUDY This study was designed to explore the relationships among (a) the design-quality of an online learning application, (b) learning-related variables, and (c) student learning achievement. The underlying logic of current study follows the three steps:

3.

We have known that B influences C (from literature) If we can determine that A influences B (to be determined) We can conclude that A can influence C via B (conclusion)

Based on this conclusion, we say that B is the intermediate variable between A and C; and the influence transferred via B between A and C is the intermediate effect. In other words, knowing that the learning-related variables influence learning achievement, if the quality of learning applications influence the learning-related variables, we can conclude that the quality of the learning applications influence learning achievement indirectly, and, therefore, an intermediate effect exists. This is a method known as detecting intermediate variable or effect in educational research (Liu, Maddux & Johnson, 2004). In this study, only the second step was examined.

RESEARCH QUESTIONS The research questions for this study were: 1.

2.

3.

Can enjoyment (the degree to which a student enjoys learning with an online application) be predicted by any of the four design variables (quality of information, design of information, quality of technology use, and design of technology use)? Can motivation (the extent to which a student is motivated to learn with an online application) be predicted by any of the four design variables? Can freedom from anxiety (the anxiety level of a student when he or she learns with an online application) be predicted by any of the four design variables?

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classes of an introductory technology course and four classes of a design course in an Eastern state university from 1999 to 2002. The distribution of the subject areas and the types of applications are shown in Tables 1 and 2.

METHODS Samples The sample of this study was 900 online K-12 learning applications on the subject areas of arithmetic, algebra, geometry, reading, writing, science, Spanish, history, geography, and social science. They were WebQuests, instructional materials, drills, games, tests, and instructional video clips. Over 92% of the WebQuests and instructional materials were hypertext information, and over 86% of the drills, games, and tests were hypermedia applications with online interactions. Of the 900 online learning applications, 375 (see Table 1) were selected by 75 graduate teacher education students from six classes of an introductory technology course in a Western state university from 2002 to 2004. The other 525 applications (see Table 2) were selected by 105 graduate teacher education students from four

Procedures The author was the instructor of all three courses in the two universities. In the introductory information technology course, students learned basic computing skills and the strategies of technology integration. In the design course, students learned theory and design of computer-based instruction and created multimedia instructional segments using authoring tools such as Derictor or ToolBook. The data were obtained from a technology integration project required for all three courses. In completing this project, each student (referred to as a mentor) first located a K-12 student at any grade level (referred to as a protégé). Together,

Table 1. Online learning applications evaluated at the western site Types of Learning Application

Subject Areas

WebQuests

960

Instructional Materials

Drills

Games

Tests

14

16

10

12

13

3

6

12

2

Videos

Other Activities

Total

Arithmetic

12

Algebra

10

Geometry

8

1

Reading

14

8

5

5

9

Writing

5

2

15

15

5

Science

6

3

11

18

6

4

48

Spanish

10

2

15

3

8

1

39

5

12

4

2

4

32

5

8

3

1

21

History

5

Geography

4

Social Study

5

5

7

6

2

Total

79

26

102

100

50

52 38

1

30

1

1

43

4

1

47

25 15

3

375

Evaluating Online Learning Applications

Table 2. Online learning applications evaluated at the eastern site Types of Learning Applications

Subject Areas

WebQuests Arithmetic

24

Instructional Materials 5

Drills

Games

Tests

8

18

10

Videos

Other Activities 1

Total 66

Algebra

10

2

8

8

7

35

Geometry

8

1

16

10

5

40

Reading

21

4

18

11

8

2

Writing

19

3

16

12

10

2

1

65 62

Science

10

4

15

16

12

1

Spanish

20

5

11

10

8

2

1

57

History

12

3

12

9

10

1

1

48

Geography

9

6

11

10

8

Social Study

23

5

7

9

6

Total

156

38

122

113

84

they then determined five learning objectives in one to two subject areas. After the objectives were determined, the mentor needed to select five online learning applications. The mentor was required to do a thorough search on the Web, evaluate seven or more K-12 online learning applications using the design-quality instrument (Appendix A), and determine five applications that were consistent with the learning objectives. The mentor then developed five lesson plans. The mentor was required to create five learnercentered activities with the use of the five online applications. The instructor provided an instructional worksheet for the mentor to design those learning procedures and activities, which ensured that the major components and procedures of instructional design were included. The protégé followed the lesson plans, interacted with the five online applications, performed the five activities, and completed the assigned learning tasks. Simultaneously, the mentor observed the learning process, and scored the performances

58

44 50 8

4

525

in terms of the protégé’s enjoyment, motivation, and anxiety level toward each online application (using the instrument in Appendix B). By the time the technology integration project was completed, each mentor had evaluated five online applications and observed the protégé’s performances on five learning activities. Therefore, the mentor had collected 10 sets of data: five sets of quality evaluation scores on the online learning applications and five sets of observation scores on the three learning-related variables. The same procedures were repeated in all classes involved in this study from the two universities. All data were coded and saved for data analysis.

Instruments, Measurements, and Scoring As previously described, two instruments were used in this study. The four design-related variables (Quality of Information, Design of Information, Quality of Technology Use, and Design of

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Technology Use) were measured by a Likert-style instrument (Appendix A) consisting of 32 positive statements sorted into four categories with eight statements in each category. The eight statements in each category measured one design-related variable. Each statement was scored from 1 (strongly disagree) to 5 (strongly agree). The score for each variable was the sum of eight statements, and the highest possible score was 40. Higher scores represented better qualities of a learning application. The reliability coefficient alpha for this instrument was 0.826 from the current study. The three learning-related variables (Enjoyment, Motivation, and Freedom from Anxiety) were measured by another Likert-style instrument (Appendix B) consisting of 18 statements sorted into three categories with three positive statements and three negative statements in each category. The six statements in each category measured one variable. The answer for each statement was chosen from strongly disagree (SD), disagree (D), undecided (U), agree (A), or strongly agree (SA). For the positive statements, the score for answer SA was the highest (5 points) and for SD was the lowest (1 point); for negative statements, reversely, the score for answer SD was the highest (5 points) and for SA was the lowest (1 point). The score for each variable was the sum of the six statements, and the highest possible score was 30. Higher scores indicate a more positive approach toward the use of an online learning application. The reliability coefficient alpha for this instrument was 0.832 from the current study. The seven variables were qualitative variables. In this study, they were measured quantitatively with the scoring method described previously. The Likert scaling implied that each of the items had the same level of difficulty; that is, respondents found them equally easy or difficult to endorse. The reliability coefficient alpha values (0.825, and 0.832) indicated that each instrument did reliably measure each variable, and the scores were “reasonably reliable for respondents like those in this study” (Green & Salkind, 2003, p. 315).

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DATA ANALYSIS AND RESULTS Data analysis was performed in two phases. In the first phase, the western data (data from the western state university, N = 375) were used to perform multiple regression analyses in developing the prediction models. In the second phase, the eastern data (data from the eastern state university, N = 525) were used to test the prediction models with paired t tests. Data exploration plots showed that the assumptions of normality and equal variance were not violated, and no extreme outliers were found in the two sets of data.

Phase One: Model Development and Results The western data (N = 375) were used in three multiple regression analyses to develop the prediction models in correspondence with the three research questions. The four design-related variables were treated as predictor variables, and regressed to each of the three learning related variables.

Results From the First Regression Analysis In the first regression analysis, the predictor variables were the four design variables: quality of information (QI), design of information (DI), quality of technology use (QT), and design of technology use (DT); and the response variable was Enjoyment (E). In the first run that included the four predictor variables, the linear model was found significant (F (4, 374) = 96.373, p < 0.0001), but one predictor variable—Quality of Information (QI)—was found not significant to the model (t = 0.664, p< 0.507). Therefore, the next run only included the other three variables: (DI), (QT), and (DT). The results showed the following:

Evaluating Online Learning Applications

The linear regression trend was significant (F (3, 374) = 128.546, p < 0.0001). The F ratio indicated that the linear model was the desired model that represented the data better than other regression models. The t statistic for each predictor variable was significant: Design of Information (t = 2.296, p< 0.022), Quality of Technology Use (t = 5.491, p< 0.001), and Design of Technology Use (t = 5.339, p

2003- 05- 17

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An E-Learning System Based on the Top-Down Method and the Cellular Models

VHDL are mostly used to describe circuits for FPGAs. For designing the digital circuit on PC, the design process follows the sequence of function test, design synthesis, and timing simulation. Furthermore, the designed circuit can be actually implemented on FPGA or CPLD attached to the PC, and can be tested by running the hardware. These CAD tasks were usually performed by central servers in a time-sharing fashion. Nowadays, PCs become powerful enough to perform such tasks locally without the servers. So, each student can design hardware independently. Students can even get data and know how to design the circuits through the Internet. Thus, the logic circuit design course is a suitable area to adopt the TDeLS.

Hardware Description Language The logic circuit can be designed by using the hardware description language (HDL). HDL is a programming language designed to describe behavior of logic circuits. As the gate size of FPGA becomes very large, the schematic entry method becomes impractical and the use of HDL has become popular. Thanks to the recent advancement in logic synthesis tools, obtained circuit quality is comparable with human design. The generated circuits by the logic synthesis tools are verified their correctness through logic simulations. The circuit described by HDL consists of a hierarchical combination of modules. The behavior of each circuit module is described in the form of input/output signals and internal module functions. Complicated larger circuit module can be designed by a combination of less complicated smaller modules. The circuit module is then converted into a net-list, where the circuit is described in the form of the connection of components.

Circuit Design Using Hardware Description Language In this section, the method of decomposing the circuit specification into a collection of modules is described. At first, the design specification of the circuit is described, and then it is decomposed into the circuit of modules, which perform independent functions. Next, each module is designed according to its specification. When already designed module is again attempted to be designed, the system find the designed module description and reuse it, instead of duplicating the design. As an example of VerilogHDL, Figure 5 shows the example of a circuit development and mounting. The target circuit is decomposed into two modules: Module A and B. These modules are further implemented separately and then combined to implement the desired circuit module. The hardware description language, such as VerilogHDL or VHDL, allows us to employ the top-down design method or top-down development method. Figure 5 shows a typical design procedure in accordance with the top-down design method. According to the specification of this target circuit, it is decomposed into two module specifications (Module A and B). After that, Module A and B are further decomposed into the detailed modules. Finally, the target circuit is implemented by the combination of decomposed modules (Module A1, A2, A3, B1, and C1). It is important to note that the module C1 is denoted as a common module. As C1 appears both in Module A and Module B, duplicated design is avoided and their design can be shared by using this common module notation.

The Contents for Hardware Logic Design As an example of the circuit design with VerilogHDL, an 8 bits CPU (Module name: TinyCPU) is employed for the final target circuit. Figure 6

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An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 5. Sample of hardware design procedure by HDL Target Module

（Attached Module）

Specification of ModuleA

Target Circuit

Module A

Module A

Specification of ModuleA1

Module A1

Module A1

Module A1

Specification of ModuleA2

Module A2

Module A2

Module A2

Module C1

Module C1

Specification of ModuleC1

Decomposit ion Specificat ion of ModuleB

Decomposit ion Specification of ModuleB1 Specification of ModuleC1

At tachment

Design

Module B

Module B

Module B1

Module B1

Module B1

Module C1

Module C1

Module C1

Figure 6. Block diagram of the TinyCPU Lat ch レジスタ

Input A

A

Q1

D

Q4

Lat ch

Tiny ALU ENB

レジスタ

A

Q1

D

Q4

OUT

Lat ch レジスタ

Input B

A

Q1

D

Q4

ENB

ENB

Lat ch OP code

Controller

レジスタ

A

Q1

D

Q4

ENB

S1

D1

S2

D4 ENB

Clock

shows the block diagram of an 8 bits TinyCPU circuit and Figure 7 shows the composition module structure of this TinyCPU. Figure 8 shows the top module description of a TinyCPU. It contains two module A (see Figure 9) and module B (see Figure 10). These modules’

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source codes are described with VerilogHDT. L.he module A shows the ALU of TinyCPU and the module B shows xbitLatch. The TinyCPU is composed of an arithmetic logic unit (ALU) and an xbitLatch, as shown in Figure 7. It shows the layered structure. The arith-

An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 7. Module structure for the TinyCPU

Cont roller

TinyCPU ALU nbit Lat ch

Cont roller Decoder Mult iplexer

Decoder P.G.

Mult iplexer P.G.

ALU

ADD SUB

ADD P.G.

SUB P.G.

AND

AND P.G.

nbit Latch Lat ch

OR

OR P.G.

Lat ch P.G.

Primit ive Gat e (P.G.)

Figure 8. Top module / / Top Module / / Module TinyCPU.TinyCPU.TinyCPU / / Created: // by - khiro (KATSUMATA) // at - 12:32:27 05/ 17/ 03 ` reset all ` timescale 1ns/ 10ps module TinyCPU( A, B, OPCODE, OUT, CLK ); paramet er WIDTH = 4; input [WIDTH- 1:0] A,B; input [1:0] OPCODE; input CLK; output [WIDTH- 1:0] OUT; / / internal wire wire [WIDTH- 1:0] A_i,B_i,R_i; wire [1:0] OP_i; ALU alu( .A(A), .B(B), .FUNC(OP_i), .R(R_i) ); xbit Latch a_lat ch( .IN(A), .OUT(A_i), .CLK(CLK) ); xbit Latch b_lat ch( .IN(B), .OUT(B_i), .CLK(CLK) ); xbit Latch r_lat ch( .IN(r_i), .OUT(OUT), .CLK(CLK) ); xbit Latch op_lat ch( .IN(OPCODE), .OUT(OP_i), .CLK(CLK) ); endmodule

metic logic unit further consists of ALU={ADD, SUB, AND, OR}. Also, the xbitLatch can be composed in similar fashion as the ALU. Figure 11 shows the ADD module which is one of the composition modules of the ALU.

EXPRESSION OF LOGIC CIRCUIT MODULE PACKED wITH XML The use of cellular models with XML document is explained in this section. The details of the tags are described in Figure 12 and Table 2. An attribute is added to compose the cellular models. Using

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An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 9. Module A (ALU) / / M o d u le A / / M o d u le T in y C P U .A L U .A L U / / C r eat ed: / / b y - k h ir o (K A T S U M A T A ) / / a t - 1 3 :0 0 :3 2 0 5 / 1 7 / 0 3 ` r e s e t a ll ` t im e s c a le 1 n s / 1 0 p s m o d u le A L U ( A , B , O P C O D E , R ); p ar a m e t e r WID T H = 4 ; in p u t [ WID T H - 1 :0 ] A ,B ; in p u t [ 3 :0 ] O P C O D E ; o u t p u t [ WID T H - 1 :0 ] R ; A N D f u n c _a n d ( .IN 1 (A ) , .IN 2 (B ), .O U T ( a n d _o u t ) ); A D D f u n c _a d d ( .IN 1 (A ), .IN 2 (B ) , .O U T (a d d _o u t ) ); S U B f u n c _s u b ( .IN 1 ( A ), .IN 2 (B ), .O U T (s u b _o u t ) ); O R f u n c _o r ( .IN 1 (A ), .IN 2 (B ), .O U T (o r _o u t ) ); M U X m u x( .IN 1 (a n d _o u t ), .IN 2 ( a d d _o u t ), .IN 3 ( s u b _o u t ), .IN 4 ( o r _o u t ), .S E L (O P C O D E ) ); e n d m o d u le

Figure 10. Module B (xbitLatch) / / Module B / / Module TinyCPU.xbitLatch.xbitLatch / / Created: // by - khiro (KATSUMATA) // at - 13:04:21 05/ 17/ 03 ` resetall ` timescale 1ns/ 10ps module xbitLatch( D, CLK, Q ); parameter WIDTH = 4; input [WIDTH- 1:0] D; input CLK; output [WIDTH- 1:0] Q; Latch latch(D,CLK,Q); endmodule

this attribute, each module can be combined with the cellular database. Also, the circuit module can be uniquely specified on the Web. Figure 13 shows an XML document of the ALU module. A module named testbench is also needed for the simulation of the designed circuit. The testbench generates the test patterns. Figure 14 shows the testbench used to simulate the target module.

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Figure 11. Module A1 (ADD) / / Module A1 / / Module TinyCPU.ADD.ADD // / / Creat ed: // by - khiro.UNKNOWN (KATSUMATA) // at - 13:08:00 05/ 17/ 03 // ` reset all ` t imescale 1ns/ 10ps module ADD( IN1, IN2, OUT ); paramet er WIDTH = 4; input [WIDTH- 1:0] IN1,IN2; out put [WIDTH- 1:0] OUT; assign OUT = IN1 + IN2; endmodule

THE ORGANIzATION OF LEARNING MATERIALS USING THE CELLULAR MODELS Figure 15 shows the outline of learning material using the cellular models. The header of a learning material identifies a cell and its pre-cells information. The pre-cells have inter-cell connecting information. This header also provides information

An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 12. XML document of VerilogHDL

verilogmodule module_profile aut hor

module_name

module module_spec

generated_date

module_type

port

t arget Module testbench Module name

module_id

direction

sourcecode

signal

length

status

Input

Data

Output

Control

Inout

Clock

Table 2. XML document tag definitions Tag Name module_id module_profile module_spec generated_date author module module_name

Meaning of Tag Unique ID of Module The profile of this module Outline specification of Module Date that this cell generated Author name Details of this VerilogHDL module Module name Indicate Target module or Simulation module_type module port Port Specification of Module signal About the input-output port name Port name direction Input, Output, Inout length Bandwidth of Port status Kind of Signal (Data, Control, Clock) sourcecode HDL Source Code sentence Source Code

of common cells (refer to 3.2 Common Cells with XML) for hardware logic design. The content has specifications and a source code of circuits, and a testbench for simulation in VerilogHDL (refer to 4.5 Logic Circuit Module packed with XML).

The Courseware Generation Algorithm The courseware is generated in three stages. The first stage is to build the data structure including

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An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 13. XML document of ALU Module

322 2

A L U ,A D D ,S U B ,A N D ,O R 2 003 - 05 - 1 7 H ir o m it su K at sum at a

alu t ar get

A inpu t 8 dat a

B inpu t 8 dat a

O P C O D E inpu t 4 c o nt r o l

R ou t put 8 dat a



Figure 14. XML Document of Testbench

F ： testbench testbench F：

F// source code bench at ：/Describe / Describe source codeofofa atest testbench athere. here.



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An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 15. Outline of learning material using cellular models Learning Material

Details of Learning Material

Header

Cell & Pre-cells Information

Status of Modulation in VerilogHDL Content Source Code and Testbench in VerilogHDL

Figure 16. The structure of courseware A4

B3

F2

F2 Z2

B3

E2

E2 G1

Z2 Z1

F1

F1

H1

W0

M0

W0

G1J

J0

W0

H 1 L0 H0

L0

0

K0

Y0

Z1

C0

Y0

H0

C0

X0

X0

P0

H1

G1

C0

P0 M0

J0 K0

the learning materials, which are aimed at the learning goal. The second stage is to extract all lower dimensional cells, which include necessary and sufficient related materials (we call this processing optimization). Finally, the optimized courseware is serialized by the Navigation Path Generation (we refer this as serialization hereafter).

Building of the Data Structure It is necessary to retrieve the cellular data from the cellular database, and extract necessary cellular data. The learning material cell implements the TDeLS (see Figure 19). It uses information on the pre-cell and the lower dimensional cell, in order to prepare the courseware selection function.

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An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 17. Optimized courseware (A) and needless courseware (B) A4 B3

A

F2

F2 Z2

F1

F1

B3

M0

M0 E2 H

Z2

G1

Z1

P0 1

W0

Y0

C0

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G1J

J0

H0

L0

0

K0

X0

Y0

W0

H 1 L0

H0

C0

X0

J0

B

K0

Figure 18. A sample of the generating courseware Top Cell

S tart

M

T K

N

C

A J

B

I

H

R

L

P

1st S tage Top Cell

D

E

F

G

C

A

T

B D

F

N R

G P

2nd S tage

Top Cell

S et of Learning m aterials

Q

Attaching the selected materials

C

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Optimizing the attached materials

3rd S tage

A Top Cell

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T

N

R

C

B

D

G

Serializing the optimized materials

An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 19. Outline of TDeLS eLearning Server Sit e Navigat or Block

Web Server

Aut horing Block

Aut hor Sit e

These functions are as follows: 1. 2.

Cell search function: To search the learning materials in the cellular database Cell attaching function: To attach the cellular data with pre-cell information. Figure 16 shows the data structure of courseware after the build

The Courseware Optimization Figure 17 shows the optimized courseware (A) and the unnecessary courseware (B) after optimized. It also shows the study route and the learning material cellular structure. The TDeLS accumulates the learning history data including the learning evaluation into the database. This history data is utilized to optimize the attached materials.

The Navigation Path Generation The learning content is presented in a hierarchical order according to the learner’s demand. The

At t

Ge C ne ell ra to r

Cell Dat abase

ac h

Routing Engine

h arc Se

LAN/ WAN

Ge Ro ne ut ra e to r

Learner Sit e

serialization (Yukita & Kunii, 2003) is to decide and to offer the order of the learning materials in the learning contents. For the serialization, three kinds of methods are employed to investigate the learning material cellular structure and to decide the order. The on-demanding serialization is offered first, according to the learner’s current study order history. If it is not accepted, the second alternative is offered, determined by the automatic study ordering. •

•

On demanding serialization: The TDeLS can offer the courseware according to the learner’s demand. The learner is requested to decide which to be selected as a learning material among them when there are two or more learning materials candidates Automatic serialization: This is a method that the TDeLS automatically generates the order of offering the learning material according to the following serializing algorithm

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An E-Learning System Based on the Top-Down Method and the Cellular Models

Serialization is the act of deciding the order of the learning material in the learning contents. We have examined the following three methods for automatic serialization that makes full use of the optimized courseware example in Figure 17-A. The first two kinds of the serializing methods are the Breadth-First type (BF Type) and the Depth-First type (DF Type). Other one method is Combined Type (Combine BF type and DF type). 1.

3.

The Breadth-First type (BF type): The TDeLS pays attention to the dimension which is one of cell information and offers the learning material of the same dimension. Higher dimensional cells have higher priority than the lower ones in the serialization, like in the breadth first algorithm. From Figure 17-A, the serialized order of cells is A4 ->B3 ->Z2 ->F2 ->Z1 ->F1 ->Y0 ->X0 ->M0 . means the serialized order

Ser1 = Ser2 = Ser3 = The Ser1 is serialized using the BF type. The Ser2 and Ser3 are the results of the serialization by processing of the DF type. It becomes the following order when it is serialized by this method.

Serialized Order =

2.

The Depth-First type (DF type): The TDeLS offers the learning material of the lower dimension than the current dimension. Cells are ordered in the depth first way from Figure 17-A, the following two kinds of serialized order are obtained Ser1 = Ser2 = The TDeLS composes these two serialized orders. Serialized Order = = It is shown that Ser1 and Ser2 have derived from the B3 cell in Figure 17-A. It is necessary to judge which cell should be selected

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for serialization. Offered top-down e-learning tools is decided according to learner’s information. The Combined type: This is a serialize method which uses the BF type together with the DF type. The learner can switch the DF type and BF type search at any point of navigation in the courseware. In this example, the learner switches from the BF type to the DF type after reaching cell Z1. After this choice, the learner visits all the related subordinated cells below cell Z1 , then comes back to the BF search.

Serialized Order = =

The Navigation Path Generation Example This section shows an example (Figure 18) of the navigation path generation (NPG). Roughly speaking, the first task of NPG is to select the needed learning materials in the database. The next task is to build the courseware ready to be delivered to learners in an appropriate order. Details are given in the following. •

•

1s t Stage - Building of the data structure: The TDeLS searches the learning materials (cellular data) in the learning materials database (cellular database) and then attach them with connecting information (pre-cell). 2n d Stage - The courseware optimization:

An E-Learning System Based on the Top-Down Method and the Cellular Models

•

The TDeLS accumulates the learning history data including the learning evaluation into the database. This history data is utilized to optimize the attached materials. 3r d Stage - The navigation path generation: This sample employed DF Type to serialize methods and is executed. The following two kinds of serialized order are obtained. Ser1 = Ser2 = The e-learning system composes these two serialized orders. Serialized Order = = Finally, TDeLS can offer the materials to the learners via the Web, according to the order: A, T, N, R, C, B, D, and G.

TOP-DOwN E-LEARNING SYSTEM System Outline Figure 19 shows top-down e-learning system (TDeLS) outline. 1.

2. 3.

4.

Web server block: This block is Web base processing to offer the learning materials and the production of the learning materials. Authoring block: It is a learning contents producing site. Navigation block: This block has a navigating function, whose sub-functions are to register the learner, to analyze the learner’s needs, learning history, and the level of understanding, to determine the information to be fed to the Web server. Routing engine block: It is a courseware search engine to offer the best learning contents for learners. Table 3 shows the

5.

functions that the routing engine operates. And it plays an ancillary role for the learner to select the learning contents. This routing engine has also the function of the serialization function as previously mentioned. Cellular database block: This block decides the best courseware based on learner’s demand and learning history.

SYSTEM DESIGN We are developing top-down e-learning systems (TDeLS) based on MVC (model-view-controller) (Burbeck, 1992; Sun Microsystems, 2002) model. MVC model is the design pattern suitable for developing a large-scale Web application and interactive applications like our e-learning system as shown in Figure 20. We, therefore, employed MVC model for the implementation of our e-learning system. MVC model organizes an interactive application into three separate modules as follows. • •

•

Model: The model contains the core of the application’s functionality. The model encapsulates the state of the application. View: The view provides the presentation of the model. It is the look of the application. The view can access the model getters, but it has no knowledge of the setters. In addition, it knows nothing about the controller. The view should be notified when changes to the model occur. Controller: The controller reacts to the user input. It creates and sets the model.

Forms on Browser In order to show how the TDeLS acts, the following four browser forms are shown as examples: the Learner’s Background Form, the Query Form, the Learning history Form, and the Learning Material Form.

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An E-Learning System Based on the Top-Down Method and the Cellular Models

Table 3. The function of the routing engine Block

Function

Searching

To search the learning materials in the cellular database.

Attaching Route Generator

To attach the learning materials To decided the courseware based on the learning history and learner information. A new learning material becomes a cellular data and is registered in Cell Generator the database.

Figure 20. System design Top- Down eLearning Syst em Controller

Ge C ne ell ra to r

At ta ch

Learner Sit e

Rout ing Engine

h ar c Se

Aut horing Block

Ge Ro ne ut e ra to r

Navigat or Block

Model

LAN/ WAN

Web Sit e Aut hor Site

View

Learner’s Background Form The information retrieved from the background form as shown in Figure 21 is used to analyze the learner’s understanding level regarding the logic circuit.

Query Form Learner can set data of the goal of learning using this query form (Figure 22) to search the first learning material of logic circuit module in

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Cell Database

VerilogHDL. Input items are title, module specification, module name, input/output signal name, and so on. The result of the searching defines the first learning material shown as the Top Cell A4 in Figure 16.

Learning History Form This learning history form (Figure 23) displays the learning history. Using this screen, the learner can confirm one’s learning history. This screen shot shows the list of the available learning ma-

An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 21. Learner’s background form

Figure 22. Query form

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An E-Learning System Based on the Top-Down Method and the Cellular Models

Figure 23. Learning history form

Figure 24. Learning material form

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An E-Learning System Based on the Top-Down Method and the Cellular Models

terials to study and the contents that the learner has already learned.

Learning Material Form The Learning Material Form (Figure 24) displays the Verilog HDL source code, the references about circuits, and the details of material. The learner registers one’s self-evaluation in the learning history file.

CONCLUSION The effectiveness of the proposed TDeLS is demonstrated with an example of an 8 bits ALU design. It is shown that the learners are offered an appropriate learning material selected by the serialization process. Learning materials are organized as the cell data, in order to be compiled as a cellular database and to be utilized as a Web-based courseware. The system automatically selects the contents and dynamically generates and proposes an appropriate learning courseware based on the learner’s learning history, his or her learning ability and study-needs. The system finds the suitable material from already learned materials or from new learning materials. We proposed three priority rules to perform the serialization. It is scheduled that a large-scale circuit such as 32 bits CPU will be included as a learning target. The verification of TDeLS functionalities and the evaluations of the ability whether an appropriate learning materials can be offered, are planned. We expect the following benefits by employing the top-down method and the e-learning system. It is possible to build an e-learning system which allows two-way communication between learners and educators. The learning material selection can be determined based on the learner’s skill, achievement, and degree of interest. The TDeLS

keeps the learners’ interests and motivations, to lead them to the final goal efficiently. Because of the generality of the cellular model, we expect this system to be useful for other applications such as a software programming course or distributed computation course. This architecture is applicable not only to hardware but also to software.

REFERENCES Abe, T., Yukita, S., & Kunii, T. L. (2003, November 5-8). Top-down learning navigator based on the cellular models. Proceedings of Frontiers in Education Conference 2003, Boulder, Colorado. Burbeck, S. (1992). How to use model-view-controller. Retrieved January 7, 2004, from http:// st-www.cs.uiuc.edu/users/smarch/st-docs/mvc. html Fujii, N., Imai, A., Abe, T., Suzuta, N., Yukita, S., Kunii, T. L., & Koike, N. (2003, November 5-8). Top-down education for digital logic design course based on cellular methods. Proceedings of Frontiers in Education Conference 2003, Boulder, Colorado. Fujii, N., Yukita, S., Koike, N., & Kunii, T. L. (2003, December 3-5). Top-down e-learning tools for hardware logic design. Proceedings of International Conference on Cyberworlds (CW2003), Singapore. Haiya, H., Horai, H., & Saeki, M. (2002). AGORA: Attributed goal-oriented requirements analysis method. IEEE Joint International Conference on Requirements Engineering (RE2002). Hayashi, Y., Yamasaki, R., Ikeda, M., & Mizoguchi, R. (2003). An ontology-aware design environment for learning contents. Journal of Information Processing Society of Japan, 44(1), 195-208. (In Japanese). Retrieved January 7, 2004, from http://www.ei.sanken.osaka-u.ac. jp/pub/hayashi/

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The IEEE Verilog standard #1364. (2001). An IEEE working group was established in 1993 under the Design Automation Sub-Committee to produce the IEEE Verilog standard #1364. Verilog became IEEE Standard #1364 - 1995. It has recently been revised and standardized as IEEE standard #1364-2001. Information Processing Society of Japan. (1999). Curriculum of computer science education for information system subject of faculty of science and engineering of university. J97 Version 1.1, September. ipsj-iDesigner-hayashi.pdf. Kunii, T. L. (1993). Computer science curriculum. Bit separate volume. Kyoritsu Shuppan Co. Kunii, T. L. (1999). Valid computational shape modeling: Design and modeling. International Journal of Shape Modeling, 5(2), 123-133. Kunii, T. L., & Kunii, S. H. (2001). A cellular Web model — For information management on the

Web. September 14, 2001. Corrected and Revised: September 18-20. Ohmori, K., &Kunii, T. L. (2001). Shape modeling using homotopy in shape modeling and applications. SMI 2001. IEEE Computer Society Press, 126-133. Stojanovic, L., Staab, S., & Studer, R. (2001). eLearning based on the Semantic Web. WebNet2001—World Conference on the WWW and Internet, Orlando, Florida. Sun Microsystems. (2002). Java BluePrints model-view-controller. Retrieved January 7, 2004, from http://java.sun.com/blueprints/patterns/MVC-detailed.html Yukita, S., & Kunii, T. L. (2003, November 5-8). Development of topdown courseware and cellular models. Proceedings of Frontiers in Education Conference 2003, Boulder, Colorado.

This work was previously published in Future Directions in Distance Learning and Communication Technologies, edited by T. K. Shih, pp. 27-51, copyright 2007 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.24

Tertiary Education and the Internet Paul Darbyshire Victoria University, Australia Stephen Burgess Victoria University, Australia

Introduction For many years, information technology (IT) has been used to find ways to add value for customers to entice them to purchase the products and services of a business. Many educators use the Internet to supplement existing modes of delivery. Importantly, the Internet is providing a number of added value supplemental benefits for subjects and courses delivered using this new, hybrid teaching mode. There are two aspects to subject delivery to where added value benefits may be applied, and that is in the administrative tasks associated with a subject and the educational tasks. In both instances, IT solutions can be employed to either fully or partially process some of these tasks. Given the complex and often fluid nature of the education process, it is rare that a fully integrated solution can be found to adequately service both aspects of subject delivery. Most solutions are partial in that key components are targeted by

IT solutions to assist the subject coordinator in the process. If we examine closely the underlying benefits gained in the application of IT to these tasks, there is a strong parallel to the benefits to be gained by business organizations with similar applications of IT. While the actual benefits actually sought by academics depend on the motivation for the IT solution, the perceived benefits can be classified using standard categories used to gauge similar commercial applications. This chapter examines the possibility of translating the benefits of added value to the use of the Internet by tertiary educators for subject and course delivery. A brief discussion will occur on aspects of course and subject delivery in tertiary education and the use of information technology for added value. These concepts are drawn together to indicate how the Internet may be used for added value in tertiary education. Finally, these concepts were tested with a survey of members of the IS World list serve.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Tertiary Education and the Internet

BACKGROUND

•

Aspects of Course and Subject Delivery in Tertiary Education For the purposes of this chapter, when the authors refer to tertiary education they mean university level education. There are two overall aspects to course and subject delivery, the educational and administrative components (Darbyshire & Wenn, 2000). Delivery of the educational component of a subject to students is the primary responsibility of the subject coordinator, and this task is the most visible from a student’s perspective. However, the administration tasks associated with a subject form a major component of subject coordination, but these responsibilities are not immediately obvious or visible to the students. It is essential that all aspects of subject delivery be carried out as efficiently as possible. To this end, IT, and in particular, Web-based solutions can be applied to both aspects of subject delivery. That Web-based solutions are a suitable vehicle to use has been almost universally accepted by students, teachers and academic administrators (Scott Tillett, 2000). Other advantages are the ease with which information can be disseminated, its interactivity, its use as a real-time communication medium and the ability to use text, graphics, audio and video (Kaynama & Keesling, 2000). There are a number of administrative tasks associated with subject coordination for which IT solutions can be applied in the application. These include (Byrnes & Lo, 1996; Darbyshire & Wenn, 2000): •

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Student enrollment: While most universities have a student enrolment system administered at the institute level, there are often local tasks associated with enrolment such as user account creation and compilation of mail lists, and so forth. Some of these tasks can be automated (Darbyshire & Wenn, 2000).

• •

Assignment distribution, collection and grading: The written assignment remains the basic unit of assessment for the vast majority of educators, and there have been many initiatives to computerize aspects of this task. Some of these include Submit (Hassan, 1991), NetFace (Thompson, 1988), ClassNet (Boysen & Van Gorp, 1997) and TRIX (Byrnes & Lo, 1996). Grades distribution and reporting: Techniques for this range from email, to password protected Web-based database lookup. Informing all students of important notices: Notice boards and sophisticated managed discussion facilities can be found in many systems. Examples include products such as TopClass, Learning Space, Virtual-U, WebCT, and First Class (Landon, 1998).

Many of the tasks viewed as educational can also employ IT solutions in order to gain perceived benefits. Some of these include: online class discussions; learning; course outline distribution; seminar notes distribution; answering student queries. Just how many of these are actually implemented will relate to a number of factors, such as the amount of face-to-face contact between lecturers and students. However, using the Internet for many of these can address the traditional problems of students misplacing handouts, and staff running out of available copies. Discussion management systems are being integrated into many Web-based solutions. These are usually implemented as threaded discussions, which are easily implemented as a series of Web pages. Other tools can include chat rooms or listserv facilities. Answering student queries can take place in two forums, either as part of a class discussion or privately. Private discussions online are usually best handled via an email facility, or in some instances, store and forward messaging systems may replace email. Implementing IT solutions to aid in the actual learning process is difficult. These can range from

Tertiary Education and the Internet

intelligent tutoring systems (Cheikes, 1995; Ritter & Koedinger, 1995), to facilitated online learning (Bedore, Bedore, & Bedore, 1998). However the major use of IT solutions in the learning process is usually a simple and straight forward use of the Web to present hypertext-based structured material as a supplement to traditional learning.

• •

Information Technology: Efficiency and Added Value There are a number of reasons for using IT in organisations today (O’Brien, 1999): •

•

•

For the support of business operations. This is usually to make the business operation more efficient (by making it faster, cheaper and more accurate). For the support of managerial decision making, by allowing more sophisticated cost benefit analyses, providing decision support tools and so forth. For the support of strategic advantage. This refers to the use of Porter and Millar’s (1985) three generic strategies as a means of using information technology to improve competitiveness by adding value to products and services.

It has been recognised for a number of decades that the use of computers can provide cost savings and improvements in efficiencies in many organisations. Porter & Millar (1985) have generally been credited with recognising that the capabilities of information technology can extend further to providing organisations with the opportunity to add value to their goods. Value is measured by the amount that buyers are willing to pay for a product or service. Porter & Millar (1985) identify three ways that organisations can add value to their commodities or services (known as generic strategies for improving competitiveness):

•

Be the lowest cost producer. Produce a unique or differentiated good (providing value in a product or service that a competitor cannot provide or match, at least for a period of time). If an organisation is the first to introduce a particular feature, it may gain a competitive advantage over its rivals for a period. Some ways in which information technology can be used to differentiate between products and/or services are (Sandy & Burgess, 1999):  Quality  Product Support  Time Provide a good that meets the requirements of a specialised market.

The next sections examine the possibility of translating the benefits of added value to a particular application of IT, the use of the Internet by tertiary educators, to assist with subject and course delivery.

Using Internet Technologies to Improve Efficiency and Add Value With the recent explosion in Internet usage, educators have been turning to the Internet in attempts to gain benefits by the introduction of IT into the educational process. In this chapter, subject delivery at the university level is only considered. The benefits sought from such activity depend on the driving motivation of the IT solution being implemented. While many may not perceive a university as a business (and it is not advocated here), it is nonetheless possible to match the current uses of the Internet in tertiary education with traditional theory related to the reasons why firms use IT. Internet technologies in education, which are used for the learning process itself, target the student as the main stakeholder. While the mo-

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tivation may be the enhancement of the learning process to achieve a higher quality outcome, we can loosely map this to the “support of managerial decision making” concept identified earlier. Such technologies allow educators to obtain a far more sophisticated analysis of individual student’s learning progress, and thus provide them with decision support tools on courses of action to take to influence this process. Technology solutions, which target the academic as the stakeholder (Darbyshire & Wenn, 2000, Central Point), implement improvements or efficiencies that can be mapped to the “support of the business operation” previously identified. Improvements or efficiencies gained from such implementations are usually in the form of automated record keeping and faster processing time, ultimately resulting in lower costs in terms of academic time, and added value to the students. By default, the university also becomes a stakeholder in the implementation of either of the above types of technology enhancements. Benefits gained by students and staff by such uses of technology translates ultimately to lower costs for the institution or the provision of more and/or better quality information. The benefits of such systems can be mapped onto the “support of strategic advantage” concept (as Porter’s low cost and differentiation strategies), previously identified as a reason for using technology in business. If these institutions are to regard themselves as a business, then the successful use of IT in subject delivery could give the university a strategic advantage over other universities, which it would regard as its business competitors. Most of the reported advantages gained from online supplementation of teaching relate to cost savings in terms of efficiency, flexibility and/or convenience. These represent the traditional added value benefits of lower cost and faster access to goods in the commercial world. Thus, we can use the measures of money savings, time savings, improved quality and better product information as categories to

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measure the benefits gained from the introduction of IT to supplement teaching.

A SURVEY OF IS wORLD MEMBERS The authors were interested to investigate the extent of appreciation of the added value benefits that the Internet can offer to tertiary educators, institutions and their students. In the first instance, a simple survey was conducted through the IS World discussion list to gain an initial idea of the level of appreciation that existed. IS World is a Web-based resource which has been set up for the benefit of information systems academics and researchers around the world. A general email was posted to the IS World discussion list on January 29, 2001. A request was made for tertiary educators to respond, outlining their uses of the Internet in tertiary education and how the uses added value for the institution and for students. There were 43 responses to the survey between January 29, and February 4, 2001. Most of these (33) were within one day of the initial email. All respondents to the survey identified as least one type of Internet usage to assist them. Approximately seven out of 10 adopted administrative uses and roughly the same proportion adopted educational uses. This supports the notion identified in the literature that the technology would be accepted in the tertiary education field. The following findings support the notion that educators identify the added value uses of the Internet in tertiary education. The most common benefit for administrative uses was to save time for the institution and for students. Most administrative benefits were similar for both groups, except for “save money” (where more than twice the respondents felt that the institution saved money than students). The “information provision” administrative us-

Tertiary Education and the Internet

ages were the most commonly used (important notices, schedules/ timetables, assignment and grade distribution). Less common were the more “interactive” options, assignment collection and student enrolment. Educational uses of the Internet were seen as providing slightly more benefits for students than institutions. Their use were seen as providing more information and improving quality more on average than the administrative uses. As with administrative usages, the easiest educational features to set up were the most commonly used (distribute course/ subject notes, provide external links). Less common were the more “interactive” options, discussion lists and online chat groups. About three quarters of respondents used the Internet to answer student queries (probably by email). As with administrative uses, most of the benefits are similar for students and the institution, with (again) some differences for instances where the benefits save money more for the institution than students. More respondents saw the differences in the benefits of educational uses flowing to students than to institutions than with administrative uses. In three of the uses, saving time was not the most common benefit identified. These were the provision of external links to additional resources, discussion lists and online chats, where improved quality of information and more information were more commonly identified.

FUTURE TRENDS We believe that research into the use of the Internet for educational purposes will continue to expand, as the “added value” opportunities to provide a better service to students begin to mature. At the same time, we believe that the administrative uses will continue to expand, without perhaps the recognition or body of research that is devoted to learning outcomes. Although this is understandable, the administrative improvements that the Internet can provide should not be ignored completely.

CONCLUSION The majority of tertiary educators use the Internet to supplement existing modes of delivery. Importantly, the Internet is providing a number of added value supplemental benefits for subjects and courses delivered. There are two aspects to subject delivery to where added value benefits may be applied, and that is in the administrative tasks associated with a subject and the educational tasks. Most of the reported advantages gained from online supplementation of teaching relate to cost savings in terms of efficiency, flexibility and/or convenience. These represent the traditional added value benefits of lower cost and faster access to goods in the commercial world. The measures of money savings, time savings, improved quality and better product information can be used as categories to measure the benefits gained from the introduction of IT to supplement teaching. A survey of 43 tertiary educators, conducted through the IS World discussion list, revealed similar usage levels of administrative and educational features to aid tertiary education on the Internet. The administrative uses showed slightly more benefits for the institution than for students and vice-versa for educational uses. In both types of uses, their adoption seemed to be based upon how difficult the feature was to set up as well as the added value benefits it provided.

REFERENCES Bedore, G.L., Bedore, M.R., & Bedore, Jr., G.L. (1998). Online education: The future is now. Socrates Distance Learning Technologies Group, Academic Research and Technologies. Boysen, P., & Van Gorp, M. J. (1997). ClassNet: Automated support of Web classes. Paper presented at the 25th ACM SIGUCCS Conference for University and College Computing Services, Monterey, California.

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Byrnes, R. & Lo, B. (1996). A computer-aided assignment management system: Improving the teaching-learning feedback cycle. Retrieved on December 2, 1999 from http://www.opennet.net. au/cmluga/byrnesw2.htm Cheikes, B.A. (1995). GIA: An agent-based architecture for intelligent tutoring systems. Paper presented at the Proceedings of the CIKM’95 Workshop on Intelligent Information Agents. Darbyshire, P. (1999). Distributed Web based assignment submission and access. ProceedingsInternational Resource Management Association, IRMA99, Hershey, USA. Darbyshire, P. & Wenn, A. (2000). A matter of necessity: Implementing Web-based subject administration. Chapter in Managing Web enabled technologies in organizations. Hershey, PA: Idea Group Publishing. Hassan, H. (1991). The paperless classroom. Paper presented at ASCILITE ’91. University of Tasmania, Launceston, Australia. Kaynama, S.A. & Keesling, G. (2000, August). Development of a Web-based Internet marketing course. Journal of Marketing Education, 22(2), 84-89. Landon, B. (1998, 10/4/98). On-line educational delivery applications: A Web tool for comparative analysis [Web Page]. Centre for Curriculum, Transfer and Technology, Canada. Retrieved on October 10, 1998 from http://www.ctt.bc.ca/landonline/ O’Brien, J.A.. (1999). Management information systems, managing information technology in the Internet worked enterprise (4th ed.). Irwin MaGraw Hill. Porter, M.E. & Millar, V E., (1985, July-August). How information gives you competitive advantage, Harvard Business Review, 63(4), 149-160.

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Ritter, S., & Koedinger, K.R. (1995). Towards lightweight tutoring agents. Paper presented at the AI-ED 95—World Conference on Artificial Intelligence in Education, Washington, DC. Sandy, G. & Burgess, S. (1999). Adding value to consumer goods via marketing channels through the use of the Internet. CollECTeR’99: 3r d Annual CollECTeR Conference on Electronic Commerce, Wellington, New Zealand, November. Scott Tillett, L. (2000). Educators begin to reach out – The net cuts costs, simplifies management and could make distance learning a winner. InternetWeek, Manhasset, Iss.835, October 30, pp.49-56. Thompson, D. (1988, 14/3/98). WebFace overview and history [Web page]. Monash University. Retrieved on February 1, 1999 from http://mugca. cc.monash.edu.au/~webface/history.html

KEY TERMS Administrative Tasks: The tasks that support educational tasks (such as enrolment, recording results, and so forth). Educational Tasks: Those tasks directly associated with the delivery of the educational component to students (e.g., lecturers, tutorials, assessment, and so forth). Efficiency: From an IT viewpoint, this usually relates to improvements within the business, so for a business it may mean IT systems that reduce costs or perform tasks more reliably or faster. Internet Technologies: That group of technologies that allow users to access information and communication over the World Wide Web (Web browsers, ftp, email, associated hardware, internet service providers and so forth).

Tertiary Education and the Internet

Value: The amount a “buyer” is willing to “pay” for a product or service. A business can add value by being a low cost providing, providing

a unique or differentiated product or service or filling a niche market.

This work was previously published in the Encyclopedia of Information Science and Technology, Vol. 5, edited by M. KhosrowPour, pp. 2788-2792, copyright 2005 by Idea Group Reference (a former imprint of IGI Global).

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Chapter 2.25

Innovative Approach to Teaching Database Design Through WWW:

A Case Study and Usability Evaluation Joanna Jedrzejowicz University of Gdansk, Poland

ABSTRACT

INTRODUCTION

The objective of this chapter is to describe the Postcourse project, which is an e-course on database design. It can be reached via the World Wide Web and allows authorized students to create and work with their own databases placed on the university server. The system has been created from scratch, as no authoring package offered tools to interact with databases, which is the innovative feature of the project. The evaluation performed after the system had been used for two years proved that it is a valuable material for self-paced work.

The World Wide Web has considerable potential for improving delivery and quality of education programs, and the benefits in re-engineering higher education are widely recognized. Educators have been quick to spot this potential and thousands of Web-based courses and other educational applications have been made available on the Web. Unfortunately, according to many researchers, the currently available Web-based courses and other innovative approaches based on Internet technologies are often poor in educational content. The e-education is a relatively new technology and the online courses are often developed by computer-enthusiastic staff who are not necessarily knowledgeable about educational concepts, or by educators who lack the computer knowledge.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovative Approach to Teaching Database Design Through WWW

The objective of the chapter is to describe, analyse and, possibly, learn the lesson from the experience of creating a Web-based course on database design, which makes full use of the interactivity offered by the Internet. The first version of the course was reported in (Jedrzejowicz et al., 2001). The core part of the course, called the Postcourse, is exercises, which require creating and updating the databases stored on the university server. Thus the Postcourse makes use of the educational model of teaching by doing. This paradigm, translated into the fully implemented solution, means that students can interactively design, develop, and test their database projects through Internet. The described feature can be considered as an innovative approach extending the existing range of e-education models. The chapter is organised as follows. We describe the context of use of the course—that is, the subject, the students who enrol for the subject and the online part that is the Postcourse. We give a general description of the Postcourse, comment briefly on the implementation issues and concentrate our attention on usability analysis and evaluation. The latter is based on ideas and methodology proposed in Nielsen (1993). Using Nielsen’s approach, heuristic evaluation of the Postcourse usability was performed and its results are duly reported. Evaluation process has been supported by data obtained from a questionnaire, which is placed on the Web site of the course. In the last part of the chapter, the plans for future developments are sketched and some general conclusions are presented. Our experience of using the Postcourse to train groups of teachers gaining further education on post-graduate courses is limited since it has only been available for two academic years. However, our initial observations are encouraging. Students appreciated the enhanced access to support materials and information. Because they had access to exam questions and answers they were able to test their own understanding and learn more deeply. Most students have gained a better understanding

of the subject compared to previous years and got better results during the exams. The observations confirm that students largely had positive perception of the interactive features, self-testing and monitoring facilities and appreciated the ready access to online information.

CONTEXT OF USE: STUDY SITE AND THE STUDENTS The starting point for developing an e-learning course, from the pedagogic point of view, is to identify the target group of recipients. The target group is characterised by describing their learning situation. In this case the target group are students who take part in three-semester, post-graduate courses for teachers aimed at further education in computer science. Usually around 70 teachers enrol for the course. The teachers spend five weekends in each semester at the university having lectures and tutorials in a traditional format. The majority of the work has to be undertaken by students in between the teaching weekends. To ease the task, varied materials are being prepared by the teaching staff. An introduction to database systems is an important component in the curriculum of the course. The course is based on one textbook (Ullman & Widom, 1997). When teaching this subject, a common belief of tutors was that some form of online teaching would be particularly useful in assisting students since they are of differing abilities and background in computer science. Some of them work as computer science teachers and their knowledge of the subject is often impressive, and some have never had anything to do with computers and have to struggle to keep pace with the rest. Besides, they are mature learners comfortable with independent learning, thus well prepared for online learning. An online course allows them to set their own pace of work, choose the time when they want to use it and decide which parts of the syllabus they want and need to study.

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During the past two years the Postcourse has been well integrated with the course on databases and established its role as a valuable supplement for the students. There are four groups of users of the Postcourse: • • • •

“Anyone” Learner-student Tutor Course Administrator

We distinguished the group of students from “anyone” since some parts of the course; that is exercises and online questionnaires, are available only for those users who were given passwords and their access to the course has been authorised. Tutors are responsible for managing the course; that is deciding which materials should be included within it. The course administrator maintains the course on the Web server; that is loads any changes and modifications, as well as authorises the access of the students, as was already noted. Students register for using the Postcourse when they first login; they enter the name, suggested login and password. Once they are authorised they have full use of all the parts of the course. The access to exercises has to be limited since exercises require creating databases, inserting and modifying data in tables—and all this is performed on the server. Thus each user with a password is allowed some personal space on the server. The role of the tutor and course administrator are separated since the tasks of the course administrator are of a technical character while those of tutors are of an academic nature—answering students’ questions that are sent in as e-mails, grading assignments and designing the final version of the course. It is worth noting that the administration of a Web-based course on technology implies a number of tasks and challenges that are not typical of conventional approaches.

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THE TEACHING METHOD The term “online courses” is used to apply to nearly any course which makes even a passing use of the Internet, as well as to those where every aspect of the course is only accessible electronically. The described course lies just between those two boundaries. The teaching method designed for the database course was aimed at solving the problems of differing abilities by using online teaching approach. Presently the database course is organised as follows: • • • •

Students have on-campus lectures and laboratories They have assignments in between the teaching weekends which are sent by email All learning material is distributed via the WWW The Postcourse is an online part of the course, which can be used as an additional material; the students are free to choose the parts which they want to work with depending on their learning strategy

Awarding marks for online work is a concern since it is difficult to be sure who is actually doing the tests and exercises. Therefore, before introducing the Postcourse it was decided that its use will not be obligatory and just offered as an additional help for those students who want to use it. The three varieties of presentation styles supported by the Postcourse are narrative (tell), example (show) and exercise (do) with a strong emphasis on the last one. Learners have different preferences in the manner they learn best. Some learners like to learn by reading a narrative of new information. Some need examples, which is similar to the way crafts are learned from an expert in the field. The third view of learning is by doing quizzes, or tests and exercises. Interactive tutorials are meant to be a repetition and extension of the knowledge already acquired.

Innovative Approach to Teaching Database Design Through WWW

Figure 1. Students’ menu

Students can review the lectures and, with the help of illustrative accompanying exercises, observe how the contents of the database are changed by appropriate instructions. Tests, which are usually multiple-choice questions, cover most of the subjects of the fundamental course on databases. After a student completes a test the system recapitulates the results and shows, if necessary, the mistakes. Online exercises are an essential part of the system. They make full use of computer-aided learning. They allow users to work with their own databases. To ensure security this is allowed only for users with passwords. Each user has a personal area on the server identified by the login, so that there is no intruding and interference; besides, the tasks can be solved gradually at each login session, as the data is always there, at the server. Exercises are the main module of the course. This module has an activity based approach and introduces students to common applications of SQL (Structured Query Language). The discussed module offers an innovative feature of providing each student with a possibil-

ity of developing her/his own learning case and gaining experience with working with it. A typical student’s session consists of the following steps: 1. 2.

The student enters the name, login and password and the Postcourse performs authorisation The Postcourse displays the exercise, for example:

The tables CUSTOMERS, ORDERS were created by the following SQL commands: CREATE TABLE Customers (c-number char(10), lname char(20), fname char(20), addr char(20), town char(10) ) CREATE TABLE Orders char(10), (c-number

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Innovative Approach to Teaching Database Design Through WWW

Figure 2. The postcourse login screen

number amt date descript paid )

integer, money, date, money

3. char(30),

You may check the current contents of the tables CUSTOMERS, ORDERS (selecting any name will produce the current contents)

1.

Create the table DRIVERS that inherits all the attributes from CUSTOMERS and contains one additional attribute driving licence of type char(10).

2.

1.

- write your command here – 2.

Create the view CUST_GDA consisting of all the customers from Gdansk. - write your command here –

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Create the view, which has two attributes, a customer number (c-number from CUSTOMERS) and an order description (descript from ORDERS), for those customers who have at least one tuple in the ORDERS table. - write your command here – The student’s answers submitted to the Postcourse are checked, and if syntactically correct, then are sent to Postgres which performs the queries, otherwise the error message is displayed The student has the possibility of checking the contents of the database by sending a query to dictionary tables pg_database, pg_user

Observe that this type of exercises makes use of these features of online teaching, which cannot be replaced by a manual, CD-ROM or any other form of a teaching material. The user can observe

Innovative Approach to Teaching Database Design Through WWW

the dynamic changes in the database performed by his queries. Another important part of the Postcourse is past exams together with the answers. Usually 40% of the course final mark is based on the assignments and work in the computer laboratory during the teaching weekends and the rest, 60%, is the exam. The exam question usually follows the pattern: we describe some situation from every day life and ask students to design a relational database schema so that the required information can be kept. The rest of the question concerns defining constraints, triggers queries in SQL for the schema. Below we list the important parts of a typical exam question: Consider the following set of requirements for a university database that is used to keep track of students’ transcripts: •

•

The university keeps track of each student’s name, student number, current address and phone, permanent address and phone, birthdate, sex, class, department, degree program. Student number has a unique value for each student Each department is described by a name, department code, office number, office phone, and address. Both name and code have unique values for each department, ...

Design an entity-relationship schema for this application and draw an ER diagram for that schema. Specify key attributes for each entity type and structural constraints on each relational type. Note any unspecified requirements, and make appropriate assumptions to make the specification complete. Specify the following queries in relational algebra:

• •

List the names of students who will be 21 on January 1, 2001 Retrieve the departments based in Gdansk which have more than 50 PhD students ... Define the following queries in SQL:

•

Retrieve the name and transcript of each senior student; a transcript includes course name, course number, credit hours, semester, year, and grade for each course completed by the student ...

Since there are several possible ways of designing a database satisfying the above requirements of the exam question, we put on the Web site one solution which we consider the most appropriate, pointing out those parts which are often most difficult or neglected by students (for example in the above case—the structural constraints for each relation). The past exams with answers allow students to test their understanding, receive feedback (for example, via email) and then retest their understanding. Thus students can observe that memorizing is insufficient and deep understanding is required. In Mason (1998) it was observed that there are three elements which form the backbone of what continues to constitute the world of online courses. They are: asynchronous group and individual messaging, Web access to course materials, and real-time interactive events. As follows from the above description of our course it contains all of the mentioned elements except the possibility of asynchronous group messaging, which in fact could be a valuable component and can be added in future.

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SOFTwARE DESCRIPTION AND IMPLEMENTATION Currently, the existing authoring systems like, for example, ToolBook (ToolBook, 2001), WebCT (WebCT, 2001), and TopClass (TopClass, 2001), provide a limited set of templates for developers. These tools provide significant file management and some limited HTML assistance so that one can create Web-based course content without the need for a deeper knowledge of the Internet technology. They allow to present knowledge and data. However a major weakness of these systems is that they do not provide assistance to create learning content, which would teach by doing. The course on databases has a very practical aspect. We wanted to make the full use of the interactivity offered by online teaching as the student interest in the learning process is drastically increased when the level of interactivity is high. As we did not find an authoring system suitable for our purposes, the Postcourse was designed and then implemented from scratch. When designing the Postcourse it was decided to make it simple and platform independent—so that it can be used by any of the popular browsers, not necessarily the latest version. Our students, who are mainly working teachers, have access to all kinds of equipment. It is not always a state-ofthe-art teaching laboratory, which can be used for their studies and exercises as well. Sometimes they can access only a stand-alone, modem-connected PC at home. Besides, transmission speeds are a constant issue for the designers and programmers of Web pages. Therefore in our project it was agreed that Web page design should be driven by the needs of students with slower connections. For this reason, it was decided that all pages should be created in basic HTML with limited (or fast loading) graphics. The Postcourse makes use of the following software tools:

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• • • •

Operating system—Linux Web server—Apache Database management system—Postgres User’s interface—HTML and PHP

Apache is one of the most popular WWW servers for the Unix environment. It has a modular structure, which allowed us to incorporate modules needed for the system, that is PHP (Personal Home Page Tool) and the PostgreSql module. The first one is responsible for performing authorisation and interpreting students’ answers to tests — checking and displaying incorrect information, if any. In case of online exercises, PHP module is performing the following actions: • •

•

•

Syntax analysis of the text filled-in by a student If the text is syntactically correct then PHP sends a suitable statement to the PostgreSql module PostgreSql module performs the action on the appropriate database (that is the one identified by the login of the user) and sends back to PHP the information on the result PHP interprets the result, which is either the acknowledgment of a database transaction or information on encountered errors

USABILITY ANALYSIS OF THE POSTCOURSE AS A SOFTwARE PRODUCT Following Nielsen (1993), by usability we understand the sum of characteristics, which make software productive and also easy to understand, learn and use. In other words, usability of a software product is the extent to which the product is convenient and practical to use. The intuitive view of usability is sometimes called user-friendliness. Usability perception is subjective, it depends heavily on the context of use of the product—that is,

Innovative Approach to Teaching Database Design Through WWW

the specific circumstances when and where the software is used. Several methods of analysing and assessing software usability have been proposed in the literature. For example, multi-criteria analysis described in Fenton and Pfleeger (1997), and AHP methodology (Analytic Hierarchy Process) introduced in Saaty (1990). It seems that so far there does not exist a consistent methodology tailored to meet the needs of the educational software, an interesting proposition was recently introduced in Maurer (2002). To perform the usability analysis it is important to distinguish the groups of users because each group has its own priorities and expectations concerning the future use of the software product. In case of Web-based education software the following groups are important: •

•

•

•

Learner-student, for whom the following factors are the most important: functionality, reliability, user friendliness and time effectiveness Teacher-tutor, for whom learning effectiveness, knowledge gains and satisfaction of students is of importance Software administrator-considers mainly how difficult it is to configure the system, what other tools are needed, also considers security issues and error-resistance Education manager, responsible for buying suitable software for an educational institution takes under the consideration the following aspects: costs, expected advantages for students and teaching staff, improvement of teaching methods

So far the Postcourse is not a commercial product; one university on experimental basis has used it for two academic years. Therefore in our analysis below we omit two groups and concentrate our attention on users-learners, who are the target recipients, and teachers-tutors. System design process, which was iterative and followed the pattern design-test-redesign,

included a heuristic evaluation of software usability. It is a usability engineering method defined in Nielsen and Mollich (1990) for solving usability problems during the user interface design. The approach involves up to 10 usability heuristics: •

•

•

•

•

•

•

Visibility of system status: The system should always keep users informed about what is going on, through appropriate feedback within reasonable time. Match between system and the real world: The system should speak the users’ language, with words, phrases and concepts familiar to the user, rather than system-oriented terms. Follow real-world conventions, making information appear in a natural and logical order. User control and freedom: Users often choose system functions by mistake and will need a clearly marked “emergency exit” to leave the unwanted state without having to go through an extended dialogue. Support, undo and redo. Consistency and standards: Users should not have to wonder whether different words, situations, or actions mean the same thing. Follow platform conventions. Error prevention: Even better than good error messages is a careful design, which prevents a problem from occurring in the first place. Recognition rather than recall: Make objects, actions, and options visible. The user should not have to remember information from one part of the dialogue to another. Instructions for use of the system should be visible or easily retrievable whenever appropriate. Flexibility and efficiency of use: Accelerators—unseen by the novice user—may often speed up the interaction for the expert user such that the system can cater to both inexperienced and experienced users. Allow users to tailor frequent actions.

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Innovative Approach to Teaching Database Design Through WWW

•

•

•

Aesthetic and minimalist design: Dialogues should not contain information which is irrelevant or rarely needed. Every extra unit of information in a dialogue competes with the relevant units of information and diminishes their relative visibility. Help users recognise, diagnose, and recover from errors: Error messages should be expressed in plain language (no codes), precisely indicate the problem, and constructively suggest a solution. Help and documentation: Even though it is better if the system can be used without documentation, it may be necessary to provide help and documentation. Any such information should be easy to search, focused on the user’s task, list concrete steps to be carried out, and not be too large.

It is recommended (Nielsen & Mollich, 1990) to use three to five evaluators since one does not gain much additional information by using larger number. In our case three evaluators from the department performed the evaluation. From our previous experience with designing educational software, we realised that a successful adoption of a computer-based teaching tool can follow only a well-planned pilot development that included consultation across all parties involved or likely to be involved in the future. A tool developed by an individual working in isolation without input from colleagues is very unlikely to be adopted by the rest of the academic unit. The evaluation helped to eliminate at least some problems in the final version. For example, it appeared that some users were lost in the authorisation process. They were astonished that after introducing their login they still could not use the Postcourse, forgetting that the authorisation of the course administrator is needed as well, which usually takes a day or two. Evidently, some information for the user was missing, violating the first usability heuristic. As a result, an additional message was placed on the login screen.

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What is more, after the Postcourse was introduced into teaching and was available for the first time, four students, all experienced computer science teachers, agreed to repeat the process of heuristic evaluation. It was performed after they had completed the subject and passed the exam. Each individual evaluator inspected the interface alone without communicating with other evaluators. During each evaluation session there was an observer present who could listen to comments of the evaluators and then prepare a written report. The team working on the project then discussed the report. To ease the task we asked each evaluator to evaluate each of the ten heuristics using a fivepoint scale (1-strongly disagree, 2-disagree, 3neutral, 4-agree, 5-strongly agree). The obtained average scores are shown in Table 1. Table 1 summarises the overall positive perception of the interface. Lower values for H9, H10 can be explained as follows. Some error messages are independent from the Postcourse and are drawn from Postgres; that is the database management system that works in the background. Its messages are meant for database professionals and are shortened to a minimal possible length. For some tasks the help system and documentation is not present online—this is a feature which needs to be worked on in the future version, if prepared. A few words on the usability analysis by teachers-tutors should be said. In fact, it was performed at each stage of the work on the project since tutors developed it. For this group of users the important issue is the productivity and effectiveness of the educational software. From a short experience of using the system it appears that students who used the Postcourse had better final results (the details are explained in the next section). We realise that the Postcourse is not user-friendly enough for tutors, and to encourage more teaching staff to use it there is an urgent need to develop tools to enable them to add their own materials, tests, exercises etc. The extension of the project based on XML technology has just been started.

Innovative Approach to Teaching Database Design Through WWW

Table 1. Heuristic

Mean

H1: the system keeps users well informed of what is going on 3

.8

H2: the language is natural and familiar to the user 4

.2

H3: it is easy to leave the unwanted state 4

.8

H4: the system is consistent 4

.5

H5: the system prevents errors 4

.4

H6: all the objects are well visible 3

.8

H7: accelerators are efficiently used

3.3

H8: dialogues are well tailored

4.2

H9: error messages are meaningful and helpful 3

.1

H10: well defined help system and documentation 2

.3

POSTCOURSE TEACHING TRIAL The Postcourse was used for the first time in the winter semester 1999 and then in the summer semester 2000. The number of students taking part in the survey is given in Table 2. It is worth noting that prior to this trial students had little or no experience with the Internet as shown in Table 3’s survey performed with students of 1999 trial. To encourage the students to use the Postcourse as an additional material, they had a presentation of the system during their first visit to the database laboratory. Then their access was authorised so that they could make the full use of all the parts of the online course. The use of the Postcourse was on voluntary basis. It was stressed that the information whether a student used it or not, will have no effect on the final marks awarded for the course. The rather low number of students of 1999

group using this software was caused by their little experience with World Wide Web and/or no Internet connection at home or at school. This number doubled during the next semester, which is partly due to more students having Internet as well as the encouragement they have received from the students in the first group. We compared the final results in the exam of those students who had the opportunity of using the Postcourse with those who had never really used it (except having it shown at the university). It seems that the Postcourse was valuable, since the average result of those from the first group was 4.21 (on the scale 2-5 used in Poland, with 5 the best) versus 3.67 in the second group, which makes a 15% increase. There is also another possible explanation of this result—simply those who had decided to use the Postcourse had more experience with WWW and generally broader knowledge in computer science. So they would have had better results anyhow!

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Table 2. Year

Total number of students

Students using Postcourse

1999 7

5

10

2000 6

8

22

Table 3. Experience

Email

expert 9

9

some competence

25 2

9

little experience

19 2

3

no experience 1

0

7

no information

2

2

STUDENTS’ EVALUATION OF THE POSTCOURSE To gather opinions from the students three different methodologies were used: observation, interview and document review. First, the observations were conducted at the university computer labs. We observed human-computer interaction and asked them to “think aloud” while they used the Postcourse. Second, we conducted an interview with some students immediately after they had finished their tasks. The interview following the observation lasted about half an hour for each student. Moreover, data were collected from an informal conversation with two students and one teaching assistant. Third, we examined various types of documents including the written report of the already described heuristic evaluation, assignments and students answers to the questionnaire.

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W eb-browsers

The questionnaire is placed on the course Web site. It helps to evaluate the course and get information to what extent the users found the Postcourse valuable as an additional teaching material. We received the questionnaire back from almost all the users (see Table 4). In the first part of the questionnaire we asked some general questions on the course and in the second part they were connected with the Postcourse. Below we list all the questions and in brackets we give mean of answers for 9 + 19 = 28 questionnaires’ returns, received from users—on the five-point scale as before, for all except Q1, Q7, Q8, Q9, Q13, Q14: Q1: How much time do you spend working on the database course monthly? (6.8 hours) Q2: The subject was relevant to the requirements of my profession. (4.8)

Innovative Approach to Teaching Database Design Through WWW

Q3: I find the subject difficult. (3.7) Q4: The aims of the subject were clearly stated. (4.0) Q5: The assignments could be completed within the allocated time. (3.6) Q6: The feedback on assignments I received was well explained. (3.7) Q7: Do you have access to the Internet at home? (35% yes) Q8: How many times did you log on the Postcourse site? (6.7 times) Q9: Which parts of the Postcourse did you find most useful? (choose one) (see Table 5) Q10: I found the Postcourse friendly to use. (3.8) Q11: The questions and exercises were clearly formulated. (4.2) Q12: I found the Postcourse helpful. (4.4) Q13: Please comment on those features, which were most useful. Q14: Please comment what changes would you expect in future versions. The responses confirmed that some students found the course on databases difficult. They commented positively about having an extra source of materials. As was expected, interactive exercises proved to be useful for students who appreciated yet another opportunity to work on SQL queries and the possibility of email consultations in case of any doubts. This is especially important for students on this course who do not have an everyday contact with academics and have less chance of accessing materials in the library or working

in the university computer labs. The responses to the open questions prove that the Postcourse aided the development of their understanding of databases. For example, because students had access to exam questions as well as answers they were able to test their own understanding, receive feedback and then subsequently retest their understanding. Some people pointed out that using the Postcourse encouraged them to use Internet, which they have never done before. Of course there were some negative aspects pointed out as well. From the observations, interviews and questionnaire responses we found two kinds of students’ distress. The first one was technological problems. Unfortunately, due to the breakdown of the university server, which happened twice in those two semesters, students had no possibility of using the Postcourse for some time. Besides, even when it worked often the transmission was slow. As expected, the majority of students accessed the Internet via a modem and were charged by the hour. As a result, working online was not only slow but also it could also be expensive. Some people indicated that these negative aspects caused them to lose interest in using the Postcourse. For some people, working online meant a change of study habits that they could not cope with. They were frustrated when something went wrong and could not get support or guidance from the tutor (or a colleague) at once. This feature was surprising since we expected that people with some experience in professional life would not have frustrations of that kind. It seems that the introduction of a discussion list could at least partially solve this problem. Obviously, there is another negative impact of online learning as a whole that is disfranchising those students who lack Web access. We believe that this problem will be gone in the very near future.

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FUTURE wORK

CONCLUSION

Since our experience with using the Postcourse is quite encouraging, further developments of the system are planned:

Although the data regarding the usefulness and effectiveness of using the Postcourse are limited due to the relative newness of this software and a rather limited number of users, the reactions of those who have used it are positive. Obviously, there is an initial effort for students in becoming familiar with the software. However, in the longer run, Postcourse features are of help in better organising a self-paced work of the student, realising which parts of the syllabus need to be worked upon and choosing the most appropriate time for studying. The most valuable and innovative feature of the approach is the combination of the online interactivity and underlying Internet technologies with the learning-by-doing paradigm. In computer science courses (as the one discussed) such combination seems natural. In other areas of education the approach would require more effort for interface development and, especially, for design and implementation of virtual models of respective domains. Nevertheless, looking at various innovations brought about by Internet technologies, their ability to provide a virtual space to learning by doing solutions seems to be the most important one in terms of enhancing and re-engineering the education process. In the last years, online education has attracted much attention and seems well on its way to becoming a standard feature of a modern university. The literature (Blackhurst & Hales, 1997; Hartwig et al., 2002; Janicki & Liegle, 2001; Mason, 1998; Schutte, 2000) shows that innovations in online learning and pedagogy offer a range of advantages and can supply a number of significant improvements to teaching and learning. A study (Schutte, 2000) reports an average of 20% higher test scores for students randomly assigned to a Web-learning environment, in relation to those assigned to a traditional classroom. Our experience with the Postcourse confirms those facts widely.

•

•

•

•

•

Develop software tools to enable tutors to prepare new tests and exercises, as well as create new pages. Extend the group of tutors willing to use the Postcourse as supplementary material for database courses; this requires picking the right people—those who are enthusiastic and willing to spend some time to get acquainted with the system. Increase access for students to ensure efficient, seven-days-a week access to the server—so far the Postcourse is placed on an experimental server working on predetermined days only. Introduce discussion lists—there is an agreement in literature that collaborative learning (Wright, 1999) provides clear educational advantages. Monitor students’ experience with using the Postcourse.

After further development, we plan for more evaluation—this time not only by students but also by professionals who are tutors and had never used the system before, and also to measure the usability. Although usability has received widespread attention within the software community there are few agreed measures that capture the intuitive meaning. User performance measures defined in the MUSiC project (Bevan, 1995), for example, task effectiveness, temporal efficiency, productive period, and relative user efficiency, seem useful for our educational software. The plans are to perform the usability study of the Postcourse with the help of the above measures.

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REFERENCES Bevan, N. (1995). Measuring usability as quality of use. Software Quality Journal, 4(2), 115-130. Blackhurst, A.E., & Hales, R.M. (1997). Using an education server software system to deliver special education coursework via the World Wide Web. Retrieved July 11, 2001, from http://serc.gws. uky.edu/www/ukat/TopClass/tc.html Fenton, N. E., & Pfleeger, S. L. (1997). Software metrics. Boston: PWS Publishing. Hartwig, R., Triebe, J.K., & Herczeg, M. (2002). Usability engineering as an important part of quality management for a virtual university. Networked Learning in a Global Environment World Congress, NL2002, Technical University of Berlin. Janicki, T., & Liegle, J.O. (2001). Development and evaluation of a framework for creating web-based learning modules: A pedagogical and system perspective. Retrieved September 3, 2001, from http://www.aln.org/alnweb/journal/vol5_issue1/janicki/janicki.htm Jedrzejowicz, J., Kwapulinski, M., & Kwapulinski, P. (2001). Postcourse: WWW-based course on databases. In G.H. Chapman (Ed.), Proceedings of the Conference on Computer Based Learning in Science, CBLIS’01 (paper E4), Brno, Czech Republic. Mason, R. (1998). Models of online courses. Retrieved November 24, 2000, from http://www.aln. org/alnweb/magazine/vol2_issue2/masonfinal. htm

Maurer, H. (2002). New aspects of e-learning. Networked Learning in a Global Environment World Congress, NL2002, Technical University of Berlin. Nielsen, J. (1993). Usability engineering. New York: Academic Press. Nielsen, J., & Mollich, R. (1990). Heuristic evaluation of user interfaces. In Proceedings CHI’90 Conference of Human Factors in Computing Systems (pp. 249-256). New York: ACM Press. Saaty, T.L. (1990). How to make a decision: The analytic hierarchy process. Pittsburgh: RWS Publications. Schutte, J.G. (2000). Virtual teaching in higher education. Retrieved July 30, 2001, from http:// www.csun.edu/sociology/virexp.htm ToolBook. Retrieved July 30, 2001, from http:// www.asymetrix.com Ullman, J.D, & Widom, J. (1997). A first course on database systems. Englewood Cliffs, NJ: Prentice-Hall. WBT Systems Topclass. Retrieved July 30, 2001, from http://www.wbtsystems.com WebCT. Retrieved July 30, 2001, from http:// www.webct.com Wright, P.W. (1999). Use of information and communication technology in education, some emerging areas of interest and related issues. In G.H. Chapman (Ed.), Proceedings of the Conference on Computer Based Learning in Science, CBLIS’99 (paper A2), University of Twente, Enschede, The Netherlands.

This work was previously published in E-Education Applications: Human Factors and Innovative Approaches, edited by C. Ghaoui, pp. 28-43, copyright 2004 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.26

Usability of Online Learning Systems and Course Materials Elizabeth Furtado Universidade de Fortaleza, Brazil

INTRODUCTION Human-computer interaction (HCI) aims to design and develop high-usability interactive systems (ISs) focusing on users’ needs and ergonomic principles, among others. The usability of an IS refers to how easy it is to use and to learn. Similarly, software engineering (SE) aims to design and develop high-quality ISs focusing on schedule, budget, communication, and productivity. The quality of an IS refers to how satisfied the system clients and/or users are, verifying whether the system is performing exactly what was requested. In order to achieve both IS usability and quality, it is necessary to integrate HCI concepts into an IS development method. HCI concepts can be characteristics of users (such as their preferences, language, culture, and system experience) and of their context of use (such as easy accessibility and good luminosity of the environment). In the online learning context, it is necessary to integrate HCI concepts into an online learning

system development method. The pedagogic usability of an online learning system is related to how easy and effective it is for a student to learn something using the system. For these reasons, it is important not only to think about the IS quality, but about its usability as well. In this text, an online learning system on the Web is composed of a virtual learning environment (VLE), with tools to support a collaborative learning and online course materials available for the users through this environment. So, it is important not only to think about the VLE usability, but also about the online course material usability. We have identified some problems to achieve a successful deployment of online learning systems (Furtado, Mattos, Furtado & Vanderdonckt, 2003): •

Lack of learning quality: Many academic staffs are not worried about the design of online course materials. The material of a face-to-face course is hardly ever adapted to online course material. Whenever a course is to be published on the Internet, it

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Usability of Online Learning Systems and Course Materials

•

•

is important to envision the virtual course as the software. This way, it is expected that a course is to be developed with the same severity as the software is planned. Lack of adaptive tools and guidelines: Learning systems are very useful, but most of them are not adaptive and neither is the user model predefined (Gomes & Viccari, 1999). In addition, user interfaces of such systems are generally specified without taking into account guidelines (Eleuterio & Eberspacher, 1999). Lack of training in collaborative technologies and methods: Any academic staff (such as a teacher), as part of his/her professional development, needs continuous training. Such training is often carried out without using technologies that can deal with adaptive and collaborative processes. It is necessary to fulfill these needs by adopting an integrated pedagogical-technological content (Perrenoud, 2001).

All of these issues have a critical impact on the usability and quality of online learning systems. Thus, we developed a general architecture for such systems, which aims to show the concepts that must be considered to increase the quality of the learning process and to increase their user interface (UI) usability. The remainder of this article is structured as follows: in the next section, we explain the main concepts that helped us to develop such general architecture. Then, we provide the best practices used in a development cycle of an IS, focusing on the usability issue. Finally, we summarize the main points of this text.

VLE AND ONLINE COURSE MATERIAL BACKGROUND As we have mentioned before, an online learning system is composed of a VLE and online course instructional materials.

A VLE has to provide students with spatial freedom and time flexibility. It has to be flexible enough so that every student may profit from his/her own skills and abilities, use his/her previously developed idiosyncratic characteristics (cognitive, social, or emotional), and apply his/ her previously gained experience and expertise (Karoulis & Pombortsis, 2003). Some tools available in a VLE are the following: links to tutorials and course materials, collaborative tools (as discussion forums, chats), evaluation tools, and administrative tools. The main focus in instructional material is on: content, exercises and solutions, and project and lecture notes. The online course material needs ad hoc preparation: target and expected results must be stated, keywords must be provided, and a review must be present at the beginning and at the end of each chapter. Some authoring tools allow teachers to develop their own instructional materials. Other tools, such as those for specific programming languages (HTML, FLASH, SVG), are only used by specialized teams.

BASIC CONCEPTS RELATED TO USABILITY IN ONLINE LEARNING SYSTEMS The general architecture proposed here (see Figure 1) aims at the development of VLE and online course instructional materials, taking into account some concepts studied in different areas (human-computer interaction, cognitive sciences, ergonomic, artificial intelligence, and pedagogy). According to this figure, an online learning system’s usability can be assured when its components have been built with quality and when users’ needs have been taken into account. Quality of a component means: (i) quality in the application corresponds to content, which refers to the information and knowledge involved in the system. Information (such as learning stories

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Figure 1. General architecture proposed Quality of the User (eg. Allowing the user to collaborate and communicate with other users)

Usability of the User Interface Guidelines Multimedia Adaptive User Interaction

Usability through Interaction Devices Video and microphone

Quality of the Learning Application

Learning stories and objects Ontology Cases studies User model

Usability of the VLE Usability of the Overall On-line Learning System

and objects) are related to the development of instructional materials, and knowledge (such as cases) are especially related to the collaborative practice in forums, for instance; (ii) usability in the UI, which refers to a good specification of the interactive information of the system (its windows, its buttons, etc.); and (iii) usability through interaction devices, which makes the interaction with different media (sound, text, image) possible through devices as cameras, microphones, and so on. The quality of the user refers to his/her ability to use new interaction devices and technologies, experience with computer-based systems, and acquaintance of the domain in question. The concepts related to usability in an online learning system are the following: •

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Utilization of ontology to assure the flexibility in modeling learning applications. The ontology notion comes from the artificial intelligence area where it is identified as the set of formal terms with one knowledge representation, since the representation completely determines what “exists” in the system (Guarino, 1995). During an application modeling, models (such as the user model), knowledge (such as cases studies), and learning stories and their learning

•

objects associated to an instructional material can be represented using ontology. The advantage of using this representation is that the ontology can be defined once and used as many times as necessary (evolutionary approach). In addition, the ontology is useful to create learning objects and reuse them when a new course is initialized. Utilization of guidelines and human factors to assure learnability (effective interaction and maximum performance) and flexibility (multiplicity of ways the user and the system exchange information). Human factors, such as the teachers’ beliefs, and guidelines related to graphic aspects and characteristics of the users and their context of use, must be considered. Guidelines are suggestions about the ergonomic aspects of the interfaces, such as showing only the necessary information or letting the user control the system dialog (Bastien & Scapin, 1993; Bodart & Vanderdonckt, 1993). Taking into account guidelines during the interface design of a system allows the designer to determine the best way in which the information is to be provided to users and to ensure optimal accessibility of the system.

Usability of Online Learning Systems and Course Materials

•

•

Utilization of multimedia resources to improve interaction. The use of different interaction devices (such as microphone and video camera) makes it possible to provide a multimedia environment. Specify a multimedia-supporting system derives from the worldwide desire for non-textual information. Non-textual information characterizes systems that use different channels, and codes in their interactions with the user. Utilization of collaboration and communication mechanisms to assure the quality of the user and the continuous usability of the learning system. Some VLEs implement the collaborative aspect by allowing users to share an application (such as TELE (Neto, 2001)) and/or by using forums and chats. It allows users to share knowledge, when they are motivated to collaborate through principles of participation, for instance, in problem definition practical situations. There is a need to continuously assure usability of a system due to technological changes and to the evolution of users’ needs. We believe instructional materials of a course should evolve from human interactions between students and teachers occurring within an online discussion forum (Mattos, Maia & Furtado, 2003). Hence, we believe in a collaborative process between users and designers to adjust accessibility, acceptability, and usability criteria of a system.

USABILITY OF ONLINE LEARNING SYSTEMS: THE BEST PRACTICES OF REQUIREMENTS ENGINEERING In this section, the concept of usability (learnability, flexibility, and robustness) is related to some best practices of the requirements modeling and validation of an IS (see Table 1). An IS must be developed with the participation of users throughout the development process,

because it is easier for developers to define and evaluate the functional and non-functional (usability) requirements. The functional requirements of a VLE are related to the tasks that the user wants to perform (user tasks), for instance, to interact with other students and tutors, and to access the rules and regulations of the course. Usability requirements are related to users’ satisfaction and the performance of the system. These requirements directly influence aspects of the system quality of use (e.g., never lose sight of navigational functions). Sutcliffe (2002) gives practical guidance for requirements modeling and validation based on scenarios. A scenario represents a story or example of events taken from real-world experience. These stories are close to the common sense use of the word and may include details of the context of use for a system. These representations help users think about how the system would support their tasks. During the material design, students must be able to inform their learning requirements, which are related to content (students must perform the study tasks for a particular unit). These requirements are usually represented in storyboard sketch or animated sequences. A storyboard represents a future vision of a designed material with sequences of behavior and possibly contextual description. These representations help teachers focus on the pedagogical functions of the material. However, a single scenario or storyboard shows only some possible sequences of events among many possible sequences permitted during the interaction of a user with an IS. Interactive prototype is an interactive medium that allows the users to explore all alternative paths, and it gives a look and feel overview of the IS. Before doing prototypes, Constantine, Windls, Nolbe, and Lockwood (2003) suggest completion of an abstract content model, or an abstract prototype, because it facilitates creative thinking, leading to more innovative solutions instead of thinking over the real interfaces.

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During a session of requirements validation, it is necessary to actively engage users in checking that the designed IS actually does what they want. If the IS developed is accepted by the user, we can say that its development process was user centered, according to their needs and suggestions. As we mentioned, the usability of an online learning system is not just the UI. The focus must also be on the support that the VLE or instructional material provides for its online students. As requirements are so volatile, it is important to examine how they can be specified so software can evolve and adapt to the users´ needs. The evolutionary process involves continuous requirement adjustments in two points of view: (i) of the user—when using the system, his/her practices and working methods can be adapted to satisfy the evolving needs individually and/or collectively; and (ii) of the system—the system’s behavior can be adapted. The evolution of users’ needs can involve modifying a system’s characteristics related to its design options, for instance. In order for an IS to be considered evolutionary, its quality must be continuously verified. In VLEs, this means that its functionalities must be changed (for instance, to realize that students would like to publish their work to be viewed by any of their tutors other than themselves). In course materials, the changes can require a definition of a new learning object from an existing one.

To develop an adaptive IS, the UI designer must consider guidelines that must conform to usability requirements defined previously and users’ characteristics and their context of use. It is usual to gather users sharing the same value for a given set of characteristics into stereotype. The problem is there is no predefined information on the users to ensure that an IS has high quality of interaction to a stereotype of all users (Furtado et al., 2001). Ontology can be used to represent a variety of parameters that are not necessarily identified nor truly considered in the requirements analysis. The notion of ontology allows the definition of the meta-models, which define the specification language with which any model can be specified. This resource makes it easier to consider new information in models (Vanderdonckt et al., 2004). In online adaptive learning systems, a flexible user modeling approach is very important. The ontology of a user model can be updated accordingly to consider more information. So the success of an IS will depend on a complex trade-off between the classic view of requirements being satisfied by a design, but evolving, and the desired degree of satisfaction in acquiring the desired product (Sutcliffe, 2002). These practices and the HCI concepts described here are more detailed in the description of the lifecycle called CONE (Furtado & Sousa,

Table 1. Summary of requirements engineering practices to have usability Usability of VLEs Participatory design of users User-centered design Focuses on the UI and pedagogical functions of the VLE Requirements are represented in scenarios and prototypes Evolutionary and adaptive VLE

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Usability of Course Instructional Materials Participatory design of students and teachers Student-centered design Focuses on the UI and pedagogical content of the material Requirements are represented in storyboards and prototypes Evolutionary and adaptive material

Usability of Online Learning Systems and Course Materials

2003). It provides the developers and users a new spatial organization, including the activities that must be performed according to these practices and using these HCI concepts and artifacts. This organization aims to facilitate the participation of users, clients, and development team members in monitoring any iterative and incremental process.

FUTURE TRENDS The multidisciplinary dimension of this work is characterized by the studies done in diverse areas of knowledge, from human-computer interaction and software engineering to pedagogy. Distance learning adheres to a vision where online learning applications are developed for the widest population of users in the most varied contexts of use by taking into account individual differences. This population of users is being called “online community”. To create an online communitycentered design will be the best practice of the requirements engineering for developing the applications, which will be able to better support the collaborative learning. In addition, it will be possible to develop applications with adaptive user interfaces. These interfaces must be able to adapt themselves to the community and contexts of use characteristics.

CONCLUSION From our experience with the community of students and teachers in the online learning systems and with the development of interactive systems, it was possible to establish the following conclusion about how to obtain more usable ISs: the main question for the success of learning processes for users through the Internet does not lie exclusively on the choice of pedagogical methodology and techniques. It lies, fundamentally, on three factors: i) the understanding of the needs of both teachers

and students though a participatory design, ii) the transformation of such needs in a consistent UI and adaptive functions of a VLE and its available course materials; and iii) the need to continuously assure usability of a system through an extensible representation of requirements.

REFERENCES Bastien, J.M.C., & Scapin, D.L. (1993). Ergonomic criteria for the evaluation of user interfaces. INRIA, 156. Bodart, F., & Vanderdonckt, J. (1993). Expressing guidelines into an ergonomical style-guide for highly interactive applications. In S. Ashlundn, K. Mullet, A. Henderson, E.L. Hollnagel & T. White (Eds.), In Proceedings of InterCHI’93 (pp. 35-36). Constantine, L., Windls, H., Nolbe, J., & Lockwood, L. (2003). From abstraction to realization in user interface designs: Abstract prototype based on canonical abstract components. Working Paper on Tutorial Usage-Centered Software Engineering. ICSE’03, Portland, Oregon. Eleuterio, M., & Eberspacher, H. (1999). A knowledge management approach to virtual learning environments. Proceedings of the International Workshop on Virtual Education (WISE 1999) (pp. 55-61). Fortaleza. Demócrito Rocha Editora. Furtado, E., Mattos, F.L., Furtado, J.J.V., & Vanderdonckt, J. (2003). Improving usability of an online learning system. In C. Ghaoui (Ed.), Usability evaluation of online learning programs (pp. 69-86). Furtado, E., Furtado, V., Bezerra, W., William, D., Taddeo, L., Limbourg, Q., & Vanderdonckt, J. (2001). An ontology-based method for universal design of user interfaces. In Proceedings of the Workshop on Multiple User Interfaces over the Internet: Engineering and Applications Trends, France. Retrieved July, 10, 2001, from www.

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cs.concordia.ca/%7Efaculty/seffah/ihm2001/program.html. Furtado, E., & Sousa, K. (2003). A user interface generation process based on the RUP and represented in a new spatial organization. Retrieved March 1, 2004, from ead.unifor.br Gomes, F., & Viccari, R. (1999). Uso de heurísticas no projeto de interfaces inteligentes. In Proceedings of the International Workshop on Virtual Education (WISE 1999) (pp. 103-109). Fortaleza. Demócrito Rocha Editora. Guarino, N. (1995). Formal ontology, conceptual analysis and knowledge representation: The role of formal ontology in information technology. International Journal of Human-Computer Studies, 43(5-6), 623-640. Karoulis, A. & Pombortsis, A. (2003). Heuristic evaluation of Web-based ODL programs. In C. Ghaoui (Ed.), Usability evaluation of online learning programs (pp. 89-109). Mattos, F.L., Maia, M. &, Furtado, E.S. (2003). Formação docente em processos colaborativos online: Em direção a novos “círculos de cultura”? In Proceedings of the Workshop em Informática na Educação (WIE). Neto, H., Raimir H., Bezerra W., & Sarquis O. (2000). Especificando o tele-ambiente no contexto da educação a distância. Proceedings of the Simpósio Brasileiro de Informática Educativa (SBIE’2000) (pp. 120-132). Alagoas. Universidade Federal de Alagoas Editora. Perrenoud, P. (2001). Formando professores profissionais: Quais estratégias? Quais competências? Porto Alegre: Artmed.

Sutcliffe, A. (2002). User-centred requirements engineering. Theory and practice. London: Springer-Verlag. Vanderdonckt, J., Furtado, E., Furtado, V., Limbourg, Q., Bezerra, W., William, D., & Taddeo, L.. (2004). Multi-model and multi-layer development of user interfaces in multiple user interfaces. London: Ahmed Seffah and Homa Javahery, John Wiley & Sons.

KEY TERMS CONE: A new life cycle in which development process occurs in iteration cycles, each one having many activities grouped together in phases. Evolutionary System: Involves continuous adjustments of its functionalities and UI according to the user and/or technological changes. Extensible Representations of Requirements: Ways to represent easy requirements that were not necessarily identified nor truly considered in the requirements analysis. Pedagogic Usability of an Online Learning System: Related to how easy and effective it is for a student to learn something using the system. Requirements Engineering: The human acts of identifying and understanding what people want from an IS. Usability of an IS: Refers to how easy it is to use and learn the system. Usability Requirements: Related to users’ satisfaction and the performance of the system.

This work was previously published in the Encyclopedia of Information Science and Technology, Vol. 5, edited by M. KhosrowPour, pp. 2939-2943, copyright 2005 by Idea Group Reference (a former imprint of IGI Global).

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Chapter 2.27

Web-Based Distance Learning and the Second Digital Divide Sheryl Burgstahler University of Washington, USA

INTRODUCTION In no field have we witnessed a greater impact of emerging technologies than in that of distance learning. Correspondence courses using printed material and postal mail have been replaced by Web-based courses with the potential to make learning available to anyone, anywhere at anytime. This potential cannot be realized, however, unless two digital divides are eliminated. Some people are on the wrong side of the first “digital divide” between the technology “haves” and the technology “have-nots”. The benefits of technology are less available to those who are poor, who live in rural areas, who are members of minority racial or ethnic groups, and/or who have disabilities (Kaye, 2000; U.S. Department of Commerce, 1999). Lack of access to new technologies limits their options for taking and teaching technologybased courses. This is true for individuals with disabilities, even though the rapid development of assistive technology makes it possible for an individual with almost any type of disability to operate a computer (2003 Closing the Gap Re-

source Directory, 2003). Unfortunately, many people with disabilities still do not have access to these empowering tools, putting them on the “have not” side of the first digital divide. Within the group of “haves” with respect to the first digital divide, however, many people with disabilities face a “second digital divide.” This line separates people who can make full use of the technological tools, services, and information to which they have access, from those who cannot. Too often people with disabilities lucky enough to be on the right side of the first digital divide, find themselves on the wrong side of this second digital divide (Waddell, 1999). For example, a person who is blind may use a text-to-speech system that reads aloud text that appears on the screen. Because it cannot interpret graphics, it will simply say “image map” at a place where an image map would be displayed to someone using the full features of a multimedia Web browser. It cannot read aloud information within this and other graphic images. This person cannot access the content presented unless this content is provided in a text-based form.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Web-Based Distance Learning and the Second Digital Divide

BACKGROUND Section 504 of the Rehabilitation Act of 1973 mandated that qualified people with disabilities be provided with access to programs and services that receive federal funds. The Americans with Disabilities Act (ADA) of 1990 reinforced and extended Section 504, requiring that people with disabilities have access to public programs and services, regardless of whether or not they are federally funded. According to these laws, no otherwise qualified individuals with disabilities shall, solely by reason of their disabilities, be excluded from the participation in, be denied the benefits of, or be subjected to discrimination in these programs and services, unless it would pose an undue burden to do so. A United States Department of Justice ruling (ADA Accessibility, 1996) clarified that ADA accessibility requirements apply to programs offered on the Internet by stating, “Covered entities that use the Internet for communications regarding their programs, goods, or services must be prepared to offer those communications through accessible means as well.” Clearly, if qualified individuals with disabilities enroll in distance learning courses or are qualified to teach them, these opportunities should be made accessible to them. However, the inaccessible design of most Web-based distance learning courses imposes barriers to people with some types of disabilities (Schmetzke, 2001).

UNIVERSAL DESIGN If an applicant who is blind is the best candidate to teach a Web-based course which has been developed without text alternatives for critical content displayed using graphics, the course will need to be modified in order for him to teach it. If planning for access was done as the course was being developed, this costly redesign would not be necessary. Simple design decisions could have

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been made to assure accessibility to potential students and instructors with a wide range of abilities and disabilities. This proactive process is called “universal design”. Universal design is defined as “the design of products and environments to be usable by all people, to the greatest extent possible, without the need for adaptation or specialized design” (National Center for Universal Design, 2003, p.1). Applying universal design principles makes products and environments usable by people with a wide variety of characteristics, including gender, height, age, ethnicity, primary language, and level of ability to see, hear, speak, and move. The concept of universal design was first applied to architecture. It has since been applied to the design of household appliances, instructional learning environments, Web sites and other products and environments (Bar & Galluzzo, 1999; Bowe, 2000; Burgstahler, 2001). When the wide range of characteristics of potential students and instructors is considered, distance learning course designers can create learning environments that are accessible to all participants, just as sidewalks with curbcuts are used by everyone, including those who push delivery carts, baby strollers, and wheelchairs. For many years, examples of isolated distance learning courses designed to be accessible to individuals with disabilities could be found, including a course co-taught by the author of this chapter and a professor who is blind (Burgstahler, 2000). However, few distance learning programs have policies and guidelines that specifically address the accessibility of distance learning tools and resources (Burgstahler, 2000; Kessler & Keefe, 1999; Schmetzke, 2001). Comprehensive policies, such as the mandate that distance learning options offered by California Community Colleges must afford students with disabilities maximum access (Distance education: Access guidelines for students with disabilities, 1999), are rare.

Web-Based Distance Learning and the Second Digital Divide

EXAMPLES OF ACCESSIBLE DESIGN FEATURES To create Web pages that are accessible to everyone, developers must either avoid certain types of inaccessible features or formats or create alternative methods for navigating or accessing content provided through inaccessible features or formats (Thompson, Burgstahler, & Comden, 2003). For example, including attributes with descriptive text makes graphic image content accessible to individuals who are blind. Developers should also assure that all functions at a Web site can be accessed using a keyboard alone, so that those who cannot manipulate a mouse can navigate the pages using the keyboard or a keyboard alternative. Another useful feature is to add a “Skip Navigation” link to the top of each page; otherwise, most speech-to-text systems for individuals who are blind will read through all of the navigation links on a page before reading the content in the body of the page. Students and instructors who have limited vision may use software that enlarges screen images, but allows them to view only a small portion of the content of a standard screen image at one time. Page layouts that are uncluttered and consistent from page to page can facilitate locating and understanding Web content for people with low vision, as well as for those with some types of learning disabilities. Assuring that content and navigation do not require that a viewer distinguish one color from another makes Web-based distance learning accessible to those who are colorblind. Internet resources that do not require the ability to hear are accessible to people who are deaf or hard of hearing. However, when Web sites include audio output without providing text captioning or transcription, they cannot access the content. Similarly, distance learning programs should provide audio-descriptions (i.e., aural descriptions) of visual content or text-based descriptions for those who are blind.

Some distance learning programs employ realtime “chat” communication in their courses. In this case, students communicate synchronously (at the same time). Synchronous communication is difficult or impossible to use by someone whose input method is slow. For example, a person with limited hand use who can only type characters slowly or someone with a learning disability who takes a long time to compose his thoughts may not be fully included in the discussion. In contrast, with a synchronous tool such as electronic mail, all students and instructors can fully participate. In addition, since flickers at certain rates (often between 2 to 55 hertz) can induce seizures for people who are susceptible to them, they should be avoided.

Tools, Guidelines, and Standards for Accessibility The most current version of HTML (hypertext markup language) makes it relatively easy to develop accessible Web sites. Commonly used development tools such as WebCT™(n.d.) and Blackboard™ (n.d.) include accessibility tools as well. Electronic tools that can test Web resources for some accessibility features and training courses and reference materials to help distance learning designers develop skills for making distance learning programs accessible are also widely available (Disabilities, Opportunities, Internetworking, and Technology, n.d.). Technical guidelines and standards have been developed to provide guidance to organizations that wish to make Web content accessible to students with disabilities. The most widely used are those created by the World Wide Web Consortium and the U.S. federal government. The Web Accessibility Initiative (WAI) of the World Wide Web Consortium developed Web Content Accessibility Guidelines (1999) for designing Web pages that are accessible to people with disabilities. Besides providing comprehensive

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Table 1. Quick tips to make accessible Web sites For Complete Guidelines & Checklist: www.w3.org/WAI • • • • • • • • • •

Images & animations: Use the alt attribute to describe the function of each visual. Image maps: Use the client-side map and text for hotspots. Multimedia. Provide captioning and transcripts of audio, and descriptions of video. Hypertext links: Use text that makes sense when read out of context. For example, avoid “click here”. Page organization: Use headings, lists, and consistent structure. Use CSS for layout and style where possible. Graphs & charts: Summarize or use the longdesc attribute. Scripts, applets, & plug-ins: Provide alternative content in case active features are inaccessible or unsupported. Frames: Use the noframes element and meaningful titles. Tables: Make line-by-line reading sensible. Summarize. Check your work. Validate. Use tools, checklist, and guidelines at http://www.w3.org/TR/WCAG

Table 2. Steps to creating accessible distance learning programs • • • • • • • • • • • •

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Make sure that all stakeholders, including potential students and instructors with disabilities, are represented as accessibility policies, procedures, and guidelines are being developed. Review policies and guidelines that have been created by other organizations, such as the California Community Colleges. Develop a policy statement that commits the organization to making programs, services, and resources accessible to people with disabilities. Articulate access challenges that may face potential participants with disabilities in the context of the programs, services, and/or resources offered and the tools used for their delivery. Consult with legal experts to fully understand the requirements for program, information, and service accessibility mandated by the ADA and other legislation relevant to your organization. Develop guidelines for all media, tools and strategies used in the distance learning courses; consider Section 508 standards as a model as appropriate. Assign a person or a department within the organization to be responsible for updating disability-related program access policies and guidelines and assuring compliance throughout the organization. Disseminate accessibility policy, guidelines, and procedures throughout the organization. Provide regular training and support regarding accessibility issues. Consider developing a plan to phase in compliance with program accessibility guidelines for previously developed courses, with a date at which all programs will be compliant. Regularly evaluate progress toward accessibility. Besides taking proactive steps to assure accessibility, develop procedures for responding quickly to requests for disability-related accommodations.

Web-Based Distance Learning and the Second Digital Divide

guidelines, the WAI provides the quick tips for making accessible Web pages listed in Table 1 (World Wide Web Consortium Web Accessibility Initiative, 2001). Section 508, which was added in 1986 to the Rehabilitation Act of 1973 (Architectural and Transportation Barriers Compliance Board, 2000), requires that electronic and information technologies that federal agencies procure, develop, maintain, and use are accessible to people with disabilities, both employees and members of the public, unless it would pose an undue burden to do so. As mandated in Section 508, the U.S. Architectural and Transportation Barriers Compliance Board (Access Board) developed accessibility standards to which federal agencies must comply (Electronic and Information Technology Accessibility Standards, 2000). Although most distance learning programs are not covered entities under this legislation, they can use the Section 508 standards as guidelines for designing accessible courses. These programs can also benefit from following the leadership of the federal government in being pro-active with respect to the accessibility of information technology (IT). “Use of an ‘ad hoc’ or ‘as needed’ approach to IT accessibility will result in barriers for persons with disabilities. A much better approach is to integrate accessibility reviews into the earliest stages of design, development, and procurement of IT.” (U.S. Department of Justice, 2002)

FUTURE TRENDS AND STEPS TO AN ACCESSIBLE DISTANCE LEARNING PROGRAM It is unlikely that distance learning courses in the future will be universally designed unless relevant policies, guidelines, and procedures are in place within distance learning programs. Organizations can begin the process of developing accessibility policies, procedures, and guidelines by addressing

issues listed in Table 2, as published in Educational Technology Review (Burgstahler, 2002).

CONCLUSION Well-designed distance learning courses create learning opportunities for everyone and thus do not erect barriers for potential students and instructors with disabilities. Employing universal design principles as distance learning courses are created can make learning opportunities accessible to everyone, everywhere, at any time and thereby eliminate the second digital divide.

ACKNOwLEDGMENT This chapter is based upon work supported by the National Science Foundation (Cooperative agreement # HRD-0227995) and the U.S. Department of Education, Office of Postsecondary Education (grant #P33A020044). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of federal government.

REFERENCES 2003 Closing the Gap Resource Directory. (2003). Closing the Gap, 21(6), 37-195. ADA accessibility requirements apply to Internet Web pages (1996). The Law Reporter, 10(6), 1053-1084. Americans with Disabilities Act of 1990, 42 U.S.C.A. § 12101 (1990). Architectural and Transportation Barriers Compliance Board. (2000). Electronic and information technology accessibility standards, Federal Reg-

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ister, 36 CFR Part 1194 December 21. Retrieved March 7, 2004, from http://www.access-board. gov/sec508/508standards.htm Bar, L., & Galluzzo, J. (1999). The accessible school: Universal design for educational settings. Berkeley, CA: MIG Communications. Blackboard, Inc. (n.d.). Blackboard accessibility. Retrieved March 7, 2004, from http://www.blackboard.com/products/access/index.htm Bowe, F.G. (2000). Universal design in education. Westport, CT: Bergin & Garvey. Burgstahler, S. (2000). Access to Internet-based instruction for people with disabilities. In L.A. Petrides (Ed.), Case studies on information technology in higher education (pp.76-88). Hershey, PA: Idea Group Publishing. Burgstahler, S. (2001). Universal design of instruction. Seattle: DO-IT, University of Washington. Retrieved March 7, 2004, from http://www. washington.edu/doit/Brochures/Academics/instruction.html Burgstahler, S. (2002). Distance learning: Universal design, universal access. Educational Technology Review, 10(1). Disabilities, Opportunities, Internetworking and Technology. (n.d.). Technology and universal design. Retrieved March 7, 2004, from http:// www.washington.edu/doit/Resources/technology.html Distance education: Access guidelines for students with disabilities. (1999). California Community Colleges Chancellor’s Office. Retrieved March 7, 2004, from http://www.htctu.fhda.edu/publications/guidelines/distance_ed/disted.htm Electronic and Information Technology Accessibility Standards. (December 21, 2000). The Federal Register, 65(246), 80499-80528.

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Kaye, H.S. (2000). Disability and the digital divide. San Francisco: University of California Disability Statistics Center. Retrieved March 7, 2004, from http://dsc.ucsf.edu/publication. php?pub_id=6 Kessler, D., & Keefe, B. (1999). Going the distance. American School and University, 7(11), 44-46. National Center for Universal Design. (2003) What is universal design? Retrieved March 7, 2004, from http://www.design.ncsu.edu/cud/univ_design/ud.htm Schmetzke, A. (2001). Online distance education—“Anytime, anywhere” but not for everyone. Information Technology and Disability Journal, 7(2). Retrieved March 7, 2004, from http://www. rit.edu/~easi/itd/itdv07n2/axel.htm Section 504 of the Rehabilitation Act of 1973. 29 O.S.C. § 794(a) (1973). Section 508 of the Rehabilitation Act of 1973. 29 U.S.C. § 794(d) (1998). Technology-Related Assistance of Individuals with Disabilities Act of 1988, 29 U.S.C. 2201 et seq. Thompson, T., Burgstahler, S., & Comden, D. (2003). Research on Web accessibility in higher education. Journal of Information Technology and Disabilities, 9(2). U.S. Department of Commerce, National Telecommunications and Information Administration. (1999). Falling through the net: Defining the digital divide. Washington. D.C. Retrieved March 7, 2004, from http://www.ntia.doc.gov/ ntiahome/fttn99/ U.S. Department of Justice (2002). Information technology and people with disabilities: The current state of federal accessibility, Section II, Introduction. Retrieved March 7, 2004, from http:// www.usdoj.gov/crt/508/report/content.htm

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Waddell, C.D. (1999). The growing digital divide in access for people with disabilities: Overcoming barriers to participation in the digital economy. Understanding the Digital Economy Conference, May. Retrieved March 7, 2004, from http://www. icdri.org/CynthiaW/the_digital_divide.htm Waddell, C.D., & Urban, M.D. (2001). An overview of law and policy for IT accessibility: A resource for state and municipal IT policy makers. International Center for Disability Resources on the Internet. Retrieved March 7, 2004, from http:// www.icdri.org/CynthiaW/SL508overview.html WebCT, Inc. (n.d.). WebCT standards. Retrieved March 7, 2004, from http://www.webct.com/accessibility/home World Wide Web Consortium. (1999). Web content accessibility guidelines. Retrieved March 7, 2004, from http://www.w3.org/tr/wai-webcontent World Wide Web Consortium Web Accessibility Initiative. (2001). Quick tips to make accessible Web sites. Retrieved March 7, 2004, from http:// www.w3.org/WAI/References/QuickTips/

KEY TERMS Accessible: A product, information, or environment that is fully usable by a person, with or without assistive technology. Assistive Technology: “Any item, piece of equipment, or system, whether acquired commercially, modified, or customized, that is commonly used to increase, maintain, or improve functional capabilities of individuals with disabilities.” (Technology-Related Assistance, 1988). Examples of assistive technology include wheelchairs, hand controls for automobiles, prostheses, communication aids, hand splints, hearing aids, and alterna-

tives to computer keyboards (Technology-Related Assistance). Electronic Technology: Encompasses information technology, but also includes any equipment or interconnected system or subsystem of equipment, that is used in the creation, conversion, or duplication of data or information. Electronic technology includes telecommunications products such as telephones and office equipment such as fax machines. Hypertext Markup Language (HTML): A language used to organize and present content on Web pages. HTML uses tags such as and to structure text into headings, paragraphs, lists, hypertext links, and so forth. Information Technology: “Any equipment or interconnected system or subsystem of equipment, that is used in the automatic acquisition, storage, manipulation, management, movement, control, display, switching, interchange, transmission, or reception of data or information.” Information technology includes “computers, ancillary equipment, software, firmware and similar procedures” (Electronic and Information Technology Accessibility Standards, 2000, p.80499). Person with a Disability: Any “person who (a) has a physical or mental impairment that substantially limits one or more major life activities, (b) has record of such an impairment, or (c) is regarded as having such an impairment. Major life activities include walking, seeing, hearing, speaking, breathing, learning, working, caring for oneself, and performing manual tasks” (Americans with Disabilities Act of 1990). Universal Design: “The design of products and environments to be usable by all people, to the greatest extent possible, without the need for adaptation or specialized design” (National Center for Universal Design).

This work was previously published in Design and Implementation of Web-Enabled Teaching Tools, edited by M. F. Hricko, pp. 83-97, copyright 2003 by Information Science Publishing (an imprint of IGI Global). 1083

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Chapter 2.28

Applying Semantic Web in Competence Management Mikko Laukkanen TeliaSonera, Finland Heikki Helin TeliaSonera, Finland

ABSTRACT

INTRODUCTION

Efficient competence management is essential in knowledge-based companies. This chapter describes how the Semantic Web technologies can be used in managing employee competencies. Applying the Semantic Web technologies in competence management enables building systems that support highly dynamic environments, are extensible as well as interoperable between different application domains, and benefit from the use of machine-accessible semantics. Competence management systems should be available not only for managers but for all the employees of the company. As companies get larger, it becomes increasingly difficult to manage the knowledge and competencies that their employees have. Utilizing the Semantic Web opens many possibilities for building flexible systems for competence management.

For companies with intellectual property, it is crucial to have an environment where the knowledge can be captured and shared efficiently within the company. Competence management is becoming increasingly important in today’s competitive markets. Firstly, companies are constantly re-structuring their organization to better meet the challenges of the markets, which may result in employees with critical competencies being moved away from the company’s core competence areas. Secondly, when downsizing the current personnel, it is crucial not to lose core competencies from the company. Similarly, when hiring new employees, it is also important to select the best candidates in terms of the core competencies of the company. Thirdly, new products and technologies are constantly entering the markets.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Applying Semantic Web in Competence Management

This requires new skills and competencies from the employees in the company. Fourthly, successful project work requires that the project group be created from the best available candidates based on the competencies needed in the project. A properly handled competence management builds a solid base for defining the business strategies for companies; the core competencies should be focused on the core business areas. Companies must decide how to arrange resources and employees to form core competencies, which then can be used to satisfy customer needs by implementing business strategies. The business strategy defines the position of a company in the industry and the relation to its competitors. A well-known model for helping to define business strategies is Porter’s Five Forces Model, which outlines the primary forces that determine competitiveness within an industry: rivalry, new entrants, suppliers’ power, substitute products, and buyers’ power (Porter, 1998). In order to develop effective business strategies, managers must decide how to react to these external forces. A competence management system enables a company to place the most competent employees in the core competence areas, and, thus, have the best possible resources to meet the external forces. Traditionally, competence management systems have been aimed at managers in the company (O’Leary, 1998). That is, the competencies are collected in one way or another from the employees by a human resource department, which uses a competence management system for refining and providing the information to the executives (Lindgren, Stenmark, & Ljungberg, 2003). However, an emerging trend is that the competence management systems are also designed for the entire company. In doing so, the employees of the company are able to publish and share their competencies not only for the managers but also between other employees. One way of sharing knowledge—and maybe

the most common one—is to first establish a network of contacts; that is, an employee knows what kind of competencies his/her co-workers have. After that, the knowledge can be shared by asking the person with a given competence directly. As companies get larger, it becomes increasingly difficult to manage the knowledge and competencies that their employees have. The knowledge sharing within small companies usually happens in a face-to-face fashion between the employees; everyone knows each other and the competencies of their co-workers. However, in large companies, which usually are geographically distributed between different countries and cultures, the contact network of an employee usually covers only a small fraction of the whole company. In such companies, efficient knowledge sharing is extremely challenging. This chapter describes how the Semantic Web technologies (Berners-Lee, Hendler, & Lassila, 2001) can be used to help solve the aforementioned issues. We also introduce an innovative Semantic Web-based solution for managing employee competencies and other relevant resources, such as documents, customers, and projects. Using machine-accessible semantics is the main difference between the Semantic Web-based solutions and other seemingly similar competence management solutions. In traditional competence management systems—whether implemented by using rather simple information technology (IT) systems or (in) formal questionnaires—employees can only state their exact competencies. Because of the lack of explicit semantics, it is typically hard to infer competencies that the employees may have without explicitly knowing about them by themselves. In our Semantic Web-based approach not only can those employees who have competence directly on a competence topic be found but also employees that have competencies on some closely related competence topics. This means that we can look up persons who are the best possible candidates for a competence topic

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or a set of competence topics. TheSemantic Web and ontologies also enable flexible portability between different domains. For instance, in the area of competence management, a marketing department may require a totally different ontology for its competencies than a research and development department. Still, the application logic is identical for both departments. Utilizing the Semantic Web and ontologies opens many possibilities for building flexible systems for competence management. The knowledge base in our solution is modeled as ontologies; thus, it demonstrates how the Semantic Web technologies can be used in a practical application on the area of competence management. The rest of this chapter is organized as follows. First, we provide background information about competence management, the Semantic Web, and ontologies. Then we proceed to discuss how competence management systems benefit from using Semantic Web technologies. After this, we introduce a Semantic Web-based system for managing and sharing competencies; we describe the ontologies used in the system and explain the algorithms for search operations, and show how the system is used from an end user’s perspective. At the end, we discuss some open issues and future trends, and, finally, conclude this chapter.

BACKGROUND

management systems to capture the knowledge and make it reusable by the other employees in the company. Secondly, competitive pressures reduce the size of the work force that holds valuable business knowledge. The downsizing of the personnel in companies is a common trend today, which may result in key knowledge holders leaving the company and taking the knowledge with them. Thirdly, the amount of time available to experience and acquire knowledge has diminished. In order for a knowledge-based company to stay on the bleeding edge of the technology, the most recent and relevant knowledge has to be available and applicable as soon as possible. Fourthly, the increase in mobility of the work force leads to a loss or disconnection of knowledge. As the mobility of the employees increases, the knowledge sharing in traditional ways (e.g., face-to-face discussions) becomes extremely challenging. Thus, more efficient and modern knowledge and competence management systems are needed. Fifthly, changes in strategic direction of a company may result in the loss of knowledge in a specific area. This applies especially for companies that follow the market trends and constantly adapt their strategy to meet the market needs. These issues can be extended by the following issues raised by Barclay and Murray (1997): •

Knowledge and Competence Management within Organizations Competence management is gaining importance in knowledge-based organizations for several reasons. In the following, we point out the most relevant issues in terms of this chapter. Firstly, the reductions in staffing create a need to replace informal knowledge with formal methods. This means that it is important to formalize the knowledge of the employees in order for the competence

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•

•

Most of our work is knowledge based: This has been an obvious fact for IT companies, but the need for knowledge and competence management is becoming increasingly important also in non-IT companies, such as the paper industry, where the nature of work has changed from manual and physical work into controlling automated high-tech paper machines. Organizations compete on the basis of knowledge: One example of this is when the companies “buy” the key persons from their competitors. Products and services are increasingly

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•

complex, endowing them with a significant information component: This places demands on both the product/service providers and consumers. The need for life-long learning is an inescapable reality.

When speaking about competence management, many terms are defined in various ways. In O’Leary (1998) it is discussed how a company’s knowledge can be captured and made available to all its members. In this context, O’Leary says that “enterprise knowledge management entails formally managing knowledge resources in order to facilitate access and reuse of knowledge, typically by using advanced information technology” (p. 54). From this definition, we could pick up a few issues relevant to this chapter. Firstly, knowledge (or competence) management should be formalized and made explicit so that it can be effectively analyzed and utilized. Secondly, the knowledge resources do not necessarily mean only employees’ (immaterial) competencies or skills. They should also cover resources that the employees are—based on their competencies and skills—linked to in one way or another. These kinds of resources are, for instance, documents they have written and projects they have participated in, but also other employees they know. Thirdly, the use of advanced information technology, as is proposed later in this chapter, is a necessity in order to build “intelligent” and flexible competence management systems. One important aspect is obviously the definition of the competence itself, which also has many definitions and terms associated and interpreted in the literature. Harzallah and Vernadat (2002) consider a theoretical model of three components of competency, which consist of knowledge, know-how, and know-whom. The knowledge is everything that requires training or learning. The know-how, on the other hand, deals with competencies acquired by performing tasks, such as working experiences. The skills can be seen as a

synonym for know-how. The know-whom is about individual characteristics, which are comprised of abilities such as creativity, communication capabilities, and interests. As compared to the theoretical definitions of competency, a more pragmatic way of defining competency in the form of a data schema has also been introduced (Sicilia, 2005). The HR-XML Consortium (Allen, 2006) proposes a common structure for competency, which aims at bringing interoperability between systems exchanging competency-related information. The competencies are defined using XML fragments, which include information such as competence name and description, importance, and possible reference to taxonomy. Although a machine is able to parse these, the XML fragments lack the model for semantics, which is the main difference to our solution. Languages like XML define the structure of a document but lack a semantic model—intuitively an XML document may be clear, but computers lack the intuition. When operating on a syntactic level, a computer is not able to know if the terms Java and Java Language mean the same thing or not. Thus, while in HR-XML a competency name Java is of type string, we could state that it would refer to a concept of Java. That is, when we add semantics to the system, the terms Java and Java Language would relate to the same concept of Java, and a computer would be able to know that they both mean the same thing. Another advantage of adding semantics is the possibility of reasoning. In XML-based systems a computer has no way to reason whether the word Java refers to a programming language or an island in Indonesia. With semantics, we can define that a concept Java would relate to a concept of Programming Language; thus, the computer in this case could reason that the Java actually is a kind of programming language. In this chapter, we define the competency to be an ability to know something or perform some action about something. In our solution, this practically implies an abstract unidirectional

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link from a resource to a competence topic. This definition can then be specialized to cover relations that are more concrete, such as a person can have knowledge on some competence topic. A competence topic represents either a physical object, such as a mobile phone, or immaterial thing, such as foreign language skills or abilities to lead large projects. The competence topics are structured as a semantically meaningful hierarchy. The definition of a single competence topic follows the idea presented in Sicilia (2005), although it is not as broad as the definition in HR-XML. However, unlike in HR-XML, our taxonomies are built into the competence topic hierarchy, and the other properties, such as importance, are related to the employee’s or other resource’s competence topic. The competence management systems in the past were like expert systems that included a process for discovering and capturing knowledge about various data sources, such as documents, Web pages, spreadsheets, presentations, and databases (Staab, Studer, Schnurr, & Sure, 2001). After being captured, the knowledge is then made available, accessible, and usable by the human resources department and managers. However, the current trend in competence management is that the competence management systems should be open for all the members of organizations. As the authors Sunassee and Sewry (2002, p. 241) argue that: “the contribution of the employees in a knowledge management effort is invaluable to any organization.” Therefore, in addition to the human resource departments and managers, the employees of companies should have access to the competence management systems in order to manage their own competence descriptions and make queries about the competencies of their fellow employees. When competence management systems are made available for not only human resource experts but for all the members of a company, the system has to be as easy to use and maintain as possible. It must provide as much “intelligence” in terms of helping the user when

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maintaining his/her competencies and provide semantically sound results when making queries. This is where IT systems would play an important role, but they would require that the information in the competence management system be in a machine-accessible and understandable format. The Semantic Web technologies provide tools for implementing such a competence management system.

The Semantic web In our solutions, we apply Semantic Web technologies for competence management. Currently, the World Wide Web (WWW) is based primarily on documents (Web pages) written in HTML, which structures the documents using a set of tags. For instance, a text block between tags “” and “” means that the text is in boldface. The visualization and interpretation of these tags are meant for human users perceiving the HTML document. The HTML documents may also contain links to other HTML documents, but only a human knows what these links mean. Thus, the WWW is meant for humans, and machines are not able to understand about the information on the WWW. The same applies to languages like XML, which only define the structure of a document and not the semantic model of the document. The Semantic Web defines the meaning for the information so that not only the humans but also the machines are able to process the information. The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries (World Wide Web Consortium, 2001). Therefore, the Semantic Web can be seen as a mesh of information linked up in such a way as to be easily processed by machines on a global scale. The Semantic Web principles are implemented in the layers of Web technologies and standards. The layers are presented in Figure 1. At the lowest layer, the Unicode asserts that the information is encoded in international character sets, and the

Applying Semantic Web in Competence Management

Figure 1. Layers of the Semantic Web

URI provides means for identifying resources in a unique manner in the Semantic Web. The syntax of URIs is governed by the IETF (Berners-Lee, Fielding, & Masinter, 1998). The XML layer with namespace and schema definitions integrates the Semantic Web definitions with the other XML-based standards. The XML is maybe the most popular and widely used serialization for the information in the Semantic Web (Becket, 2004), although it is not the only syntax; see, for instance, Notation3 (Berners-Lee, 2001). Whereas the two lowest layers are about

identifiers and syntax, the layers above those are the ones that enable adding the meaning (semantics) to the information. The resource description framework (RDF) (McBride, 2004) is a data model that forms the third layer in Figure 1. The RDF consists of triples, which are groups of three URIs. In a triple, a resource (the subject) is linked to another resource (the object) through an arc labeled with a third resource (the predicate). Therefore, triples allow defining statements like Model XYZ is of type Laptop (see Figure 2). The RDF Schema (Brickley & Guha, 2004) is a document that controls a set of terms in an RDF document. Thus, the RDF schema is a data-typing model for RDF. The RDF schema allows defining taxonomies like Laptop and Desktop as subclasses of a Computer (see Figure 2). The ontology layer supports the evolution of RDF schema vocabularies, as it can define relations between the different concepts. Because the ontologies are the most important building blocks of the Semantic Web, and also the most important layer from this chapter’s viewpoint, we will have a more detailed look at the ontologies in the next section. The top three layers, logic, proof, and trust, are currently being researched. The logic layer enables the writing of rules while the proof layer executes the rules and evaluates, together with the trust layer mechanism for applications,

Figure 2. Example of using RDF and RDF schema

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whether to trust the given proof or not.

Ontologies Ontologies are intended for knowledge sharing and knowledge reuse. To enter a discussion, communicating parties need to share a common terminology and meaning of the terms used (Gruber, 1993). Otherwise, profitable communication is infeasible because of a lack of shared understanding. With software systems, this is especially true—two systems cannot interact with each other without common understanding of terms used in the communication. Until now, this common understanding is achieved by hard coding this information to applications, making the systems static and impractical. This is where ontologies come into the picture. Ontologies describe the concepts and their relationships—with different levels of formality—in a domain of discourse (Gruber, 1993). An ontology is more than a taxonomy (classification of terms) since it includes richer relationships between defined terms. For some applications, taxonomy can be enough, but without rich relationships between terms, it is impossible to express domain-specific knowledge without defining new terms. Ontologies have been an active research area for a long time. One of the most problematic issues in developing ontologies is the actual conceptualization of the domain—competencies and other related resources, in our case. In recent years, ontology languages based on Web technologies have been introduced. DAML+OIL (Hendler & McGuinness, 2000), which is based on RDF schema (Brickley & Guha, 2004), is one such language. It provides a basic infrastructure that allows machines to make simple reasoning. Recently, DAML+OIL language was adopted by W3C, which is taking the work further by developing it to a Web ontology language (OWL) (McGuinness & Harmelen, 2004). Like DAML+OIL, OWL is based on RDF schema, but both of these languages

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provide additional vocabulary—for example, relations between classes, cardinality, equality, richer typing of properties, characteristics of properties, and enumerated classes—along with a formal semantics to facilitate greater machine readability. OWL has quite strong industry support, and therefore it is expected to become a dominant ontology language for Semantic Web.

SEMANTIC wEB-BASED COMPETENCE MANAGEMENT In Berners-Lee et al. (2001, p. 35), the authors state that “the Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.” This definition is well aligned with the current trend in competence management, where competence management systems are no longer aimed at managers and executives but at all the employees in organizations (O’Leary, 1998). When applying the Semantic Web technologies in competence management, we can build systems that benefit from the use of machine-accessible semantics, support highly dynamic environments, and are extensible as well as interoperable between different application domains. These issues are discussed in the following sections.

Reasoning Over Competence Ontologies The ontologies are described using a language with formally defined semantics. For instance, OWL allows defining classes and their instances as well as properties for those. In addition, there are many other inbuilt relations that can be defined between classes, such as taxonomies (subClassOf and subPropertyOf ) and restrictions (unionOf, intersectionOf, etc.). In addition to these inbuilt properties of OWL, one can of course define

Applying Semantic Web in Competence Management

Figure 3. Example ontology for programming languages

the domain specific properties for the application. Using these semantics, reasoning about ontologies and their instances can be made. For instance, let us consider the ontology presented in Figure 3. First, we can see that Java and C++ are object-oriented languages, and, more generally, Programming Languages. Similarly, Pascal is a procedural programming language but also a programming language, just like the Java and C++. The prog:supports property is a domain specific property from the programming domain, which is used between two pairs of resources; the object-oriented languages supports inheritance, and programming languages support a conditional IF-THEN clause. Now, because Java and C++ are subclasses of object-oriented languages, they both also support inheritance. This can be reasoned because the properties in OWL are inherited by the subclasses. In addition, because Java and C++ are also Programming Languages, they both support conditional IF-THEN clause. Pascal on the other hand only inherits the properties from the Programming Language, thus, we can reason that Pascal also supports conditional IF-THEN clause, but not inheritance. When applying the reasoning capabilities to the competence management systems, we can extend the searches to cover situations where

direct matches are not found. In this case, the people with competence on nearby topic(s) can be searched for. This is crucial today, when, for instance, new products hit the markets rapidly. Let us consider the following example, which is depicted in Figure 4. A person working for a software vendor has competence on a mobile phone model α. Then, the mobile phone manufacturer releases a new mobile phone β, which is based on the model α but on which nobody has yet competence at the software vendor. However, at some point when competencies at the software vendor for the new mobile phone β are needed, a competence management system with Semantic Web-based reasoning is able to find the persons having competence on the phone model α. Although this is not an exact match, it is a very close one, because usually the given phones are similar in functionality. Furthermore, the person having competence on phone model α can be considered a candidate when searching for persons having competence on Series 80 phone models, although the competence level is lower than for the Series 60 phone models. Therefore, adding or changing the competence topic structure does not necessarily require corresponding updates to the competencies of the persons. The reasoning can be extended even further

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Figure 4. Sample ontology for mobile phones

by taking into account also other relations than the ones between an employee and his/her competencies. The term social network was coined by Barnes (1954), and it means a social structure between actors, in our case, employees within companies. The social networks also have been researched by the Semantic Web community, from which a FOAF (Friend of a Friend) specification (Brickley & Miller, 2005) has emerged. By incorporating FOAF descriptions of the employees into the competence management system and then examining the social networks of the employees and the other resources that the employees are related to enables more “intelligent” searches. For instance, consider a case where an employee is searching for competent Java programmers to help with his/her Java-related problem. Let us then assume that the competence management system finds a person who is not available at the time. Therefore, the employee requests the competence management system for the social network (colleagues) of that person. If these new persons have a competence on Java and they are available, the employee can contact them. Similarly, if the examining of the social network does not provide any results, the other resource of the person can be requested. For instance, the projects and documents, which the person is

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related to, can be looked up, and further search for the persons related to those resources is possible. Should any of these persons be competent on Java and available at the time, the employee can contact them.

Handling Dynamic Environments with Ontologies Because the competence structure and the whole data model in the competence management system will most likely change dynamically over time, the competence management system needs to have a clean separation between the data and the application logic. While the traditional systems typically allow attaching and modifying resources to the existing data model, they usually do not allow changing the data model itself. Ontologies make it possible not only to add new concepts, but also new relationships between the concepts, without needing modifications to the application logic. The Semantic Web and ontologies also enable flexible portability between different domains. For instance, in the area of competence management, a marketing department may require a totally different ontology for its competencies than a research and development department. Still, the application logic is identical for both

Applying Semantic Web in Competence Management

departments.

COMPETENCE MANAGER: A SEMANTIC wEB-BASED TOOL FOR MANAGING COMPETENCIES In this section, we introduce a system called competence manager, which is a tool for managing and sharing competencies. The knowledge base in the competence manager is implemented as ontologies; thus, this section describes how the theory presented in the previous sections can be implemented in practice. The main tasks for the use of the competence manager are as follows. Firstly, the competence manager can be used to track down persons with a given competence within a company. This functionality could be used when a person needs assistance or help for some topic, a project manager is gathering persons with given competencies for a project, or a document writer needs some background information on a specific topic. Secondly, the competence manager can be used as a tool during performance appraisal between superiors and their employees; the current competencies and the competence areas needing improvements can be identified, a development path(s) can be planned, and employee development can be later tracked. Thirdly, the competence manager can serve as a tool for company management in strategic coordination activities. The overall competence levels on various areas can be identified, and, in the case of defining the company’s business strategy, the competence manager can be used for competence gap analysis; the areas needing more or less competence can be identified.

Ontologies in the Competence Manager Competence manager employs OWL (McGuinness & Harmelen, 2004) for the ontologies, which are divided into general and domain-specific

parts. The general ontology defines the mandatory classes and properties for the competence topic hierarchy. The domain ontologies define the domain-specific resources, and must conform to the general ontology. This asserts that the reasoning engine using simple protocol for RDF query language (SPARQL) (Prud’hommeaux & Seaborne, 2005) queries works correctly with the domain ontologies. The general ontology defines the topic hierarchy, resources, and their properties. Figure 51 depicts the classes and properties defining the topic hierarchy, which in the domain-specific ontology is realized as an instance of the topic class. The parent-child relations are defined using the hasParentTopic property. The instances of the grade class specify the competence level of some resource (e.g., a person’s competence) to a certain topic. The grade value in the competence manager can get integer values from one to five. For instance, an employee having excellent knowledge on some topic may set the grade value to five, whereas some other employee with only some background information about the same topic could set the value to one. To the end-user, the grade values are presented using more descriptive terms. For instance, a grade value of five could be presented as “excellent” competence, whereas a grade value of one could map to “poor” competence. In order to provide semantically sound results, the hierarchy has to be designed well. In other words, semantically similar topics in the hierarchy have to be located close to each other in the topic hierarchy. This may sound obvious, but in some cases, it may be quite tricky to define the topic hierarchy. Consider, for instance, topics C and C++. The former is procedural language, similarly to, for instance, Pascal, whereas the latter is an object-oriented language, like, for instance, Java. Therefore, C and Pascal as well as C++ and Java would be closer to each other than C and C++. However, those that are familiar with programming languages know that C and C++ are very close to each other in a certain sense. To alleviate

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Figure 5. General ontology for competence topics

Figure 6. General ontology for resources

this problem, the competence manager allows definition of similarity links, which can be used to explicitly state that two topics are similar to each other to some extent. Thus, similarity links “bring the topics closer to each other” regardless of how far they are located in the topic hierarchy. The modeling of the similarity is depicted in Figure 5. The similarity class has two properties, sourceTopic and destTopic, with which the unidirectional similarity link is defined. The similarity

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link also has a non-negative weight defining the “closeness” of the two topics. The other (resource-related) classes and properties defined in the general ontology are depicted in Figure 6. The group class allows tying a group of resources together. This is useful for instance when modeling static organizational units within a company, but also when creating cross-organizational groups of persons with given competencies dynamically. The resource

Applying Semantic Web in Competence Management

Figure 7. A sample of a domain ontology

Figure 8. Sample instances for a topic hierarchy

class is an abstract class, which is extended by concrete person, project, and document classes. HasResource is an abstract property that can be used to link domain-specific objects (things) to the resources of the competence management ontology (see examples in Figure 7). For instance, the hasMember property is a sub-property of hasResource, and links a person to a project. Furthermore, each resource can be available—specified

using isAvailable property—during a specific time period(s), which can be specified by the calendar class. The calendar class in the general ontology is an abstract class allowing the domain-specific ontology and application area to use whichever calendar is preferred. The hasCompetence and hasInterest abstract properties are for defining competencies and interests, respectively, by linking a resource to

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Figure 9. Sample instances of resources linked to topic instances

a topic (through a grade instance). The hasCompetence property specifies that a resource has some competence on topic. The hasInterest, on the other hand, specifies a desire of a resource to learn more about some topic. Similarly, a negative hasInterest implies that a resource dislikes a topic and does not want to or cannot learn about nor deal with the topic. As with the hasResource, the hasCompetence and hasInterest properties can and should have more specialized sub-properties. An example of such sub-property is the hasTopic, which states that a project can be about some topic. The domain ontology allows further defining such classes, properties, and their instances, which are specific to the application area and which are not covered in the general ontology. The resources can be freely defined as domain-specific classes,

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as long as they are sub-classes of the resource class. Furthermore, the relationships (properties) between the domain-specific resources can also be freely defined, but the properties must be defined as a sub-property of the hasResource property. Similarly, competence relationships have to be sub-properties of the hasCompetence property. The domain ontology depicted in Figure 7 gives examples of these kinds of specializations. Firstly, it defines sub-properties knowsAbout and knowsHowto for the hasCompetence. Secondly, it extends the person class for defining more fine-grained roles in a company by sub-classes employee, manager, and consultant. Thirdly, the document class is extended to allow a distinction between an InternalDocument and a PublicDocument. Once the general and domain ontologies have

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been defined, the application area-specific data can be created by making instances of the ontologies. Figure 8 depicts a sample fragment of a topic instance hierarchy under the software technologies topic, while Figure 9 depicts a sample instances for the domain ontology. In both figures, a rectangle represents an instance, and the identifier inside “” characters denotes the class, which the instance realizes. The properties follow the same scheme as in Figures 5, 7, and 8. In Figure 9, the instance Mikko of an employee class has competencies on topics OWL and Java, with grade levels 4 and 5, respectively. Mikko has also a calendar instance attached to it specifying the availability of Mikko. Further, Mikko is an author (authorOf ) in a public document named Deliverable 2.1, which is about RDF(S). The Deliverable 2.1 again belongs to a project called Semantic Web prestudy, which is about Semantic Web.

Finding Closest Matches

UC (O1 , H ) ∩ UC (O2 , H ) UC (O1 , H ) ∪ UC (O2 , H )

(2)

The output value of the object match algorithm is a float value between 0 and 1; the greater the value, the closer the objects are to each other. Figures 10 and 11 depict two simple object hierarchies, which we will use to illustrate the upward cotopy and the object match algorithms. Let us first consider Figure 10. The distance between objects E and F for hierarchy H1 are calculated by first defining their upward cotopy: UC ( E , H1 ) = E , C , A UC ( F , H1 ) = F , C ,A

The distance between E and F is then as follows: OM ( E , F , H1 ) :=

| UC ( E , H1 )  UC ( F , H1 ) | | UC ( E , H1 )  UC ( F , H1 ) |

| E, C, A  F , C, A | | E, C, A  F , C, A | | C, A | 2 = = = 0,5 | E , C , A, F | 4 =

In a case where direct matches are not found, the people with competence on nearby topic(s) can be searched for. The distance calculation between competence topics is based on formally defined semantics and an algorithm called Object Match (OM) (Stojanovic, Maedche, Staab, Studer, & Sure, 2001), which calculates the distance to the neighboring topics and returns the resources related to the closest ones. The object match uses an algorithm called upward cotopy (UC) (Stojanovic et al., 2001), which measures the distance from an object Oi to the root node of a hierarchy H by collecting all the objects Oj to a set: UC (Oi , H ) := {O j H (Oi , O j ) ∨ O j = Oi }

OM (O1 , O2 , H ) :=

(1)

The distance between any two objects O1 and O2 is then calculated by the object match algorithm, which is defined as:

One of the most powerful features of the object match algorithm lies in its ability to take into account the depth of the object hierarchy. That is, the objects deeper in the hierarchy are also semantically closer to each other. This can be seen by calculating the object match in the case of hierarchy H2 as shown in Figure 11.

UC ( E , H 2 ) = E , C , A, X UC ( F , H 2 ) = F , C ,A, X OM ( E , F , H 2 ) :=

| UC ( E , H 2 )  UC ( F , H 2 ) | | UC ( E , H 2 )  UC ( F , H 2 ) |

| E , C , A, X  F , C , A, X | | E , C , A, X  F , C , A, X | | C , A, X | 3 = = = 0,6 | E , C , A, F , X | 5 =

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Figure 10. Object hierarchy H1 with depth of 3

Figure 11. Object hierarchy H2 with depth of 4

As we can see, by adding a new root node—that is, making the hierarchy deeper—affects the object match value of E and F; in Figure 11 E and F are semantically closer to each other than in Figure 10. The object match is especially useful in cases where the best candidates (i.e., the persons having competence directly on the searched topic(s)) are

not available, but some candidates having competence on nearby topic(s) are found. For instance, when persons with given competencies or other resources on the searched topic Perl are not available, the persons having competence on—or the resources related to—topics TCL, Python, or even C, which does not have the same direct parent topic with the others, might be close enough to the

Figure 12. Closest matches when searching for Topic Perl

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searched topic, and they could be still accepted. This is depicted in Figure 12, where the closest topics (with percentages) to Perl are shown. Resource match function calculates the relevance of a resource to a searched topic:

The resource match can also be extended to cover multiple topics. In doing so, the searcher defines a set of competence topics with importance weights, for which the best candidates should be found. The combined resource match can be calculated as follows:

1, s ∈ O  n RM ( s, O, SG , H ) =  1 − ∏ OM ( s, Oi , H ) ∗ SGi , s ∉ O  i =1

CRM ( S , O, SG ,W , H ) =

where s is the searched topic, O is a set of topics to which the resource has a relation of type hasCompetence or hasInterest, and SG contains scaled grade values for each Oi 0 O. Each scaled grade value (SGi) is calculated based on the corresponding grade value and the distance between s and Oi. When applying the resource match to the example illustrated in Figure 12, the closest match for the search would be Mikko Laukkanen, who has direct competence on topic Python. This is because the topic Python matches with a percentage of 85.73, which is higher than, for instance, with Heikki Helin, whose competence on C language would produce a match with a percentage of 66.01.

where S is a set of searched topics, and W contains the importance weights for each Si 0 S. The combined resource matching is useful when employees with multiple competencies are searched for. Referring back to Figure 12, let us assume we would like to search for a person who has competence on both Pascal and Perl programming languages. In addition, the competence on Pascal is considered far more important than Perl; thus, on the scale from one to five, Pascal is given a weight of five, whereas Perl is given a weight of 1. Following the equation 4, the closest match in this case would be Heikki Helin with a percentage of 82.45, while Mikko Laukkanen would have a weaker match with a percentage of 69.29.

(3)

1 S ∗ ∑ RM ( Si , O, SG , H ) * Wi S i =1

(4)

Figure 13. Competence manager architecture

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The Competence Manager Architecture The architecture and the general parts of the competence manager are depicted in Figure 13. The users (clients) access the system through a front-end server, which renders the user interface according to the client device. The front end is implemented as a Microsoft .NET Web application, because it allows an easy and fast way to develop graphic user interfaces that are able to adapt to a variety of client devices. The back-end of the competence manager is exposed as a Web service, which the front-end server accesses in delivering the requests from the user interface. One reason for choosing the .NET for implementing the front-end is its built-in support for Web services. However, the front-end could be implemented with other technologies as well, such as Java-based application servers. Furthermore, due to the Web service interface, the competence manager could be accessed by Web service-enabled clients or devices directly. The Java Web Service Development Pack (JWSDP) is used to implement the Web service interface and the implementation, and the Tomcat application server hosts the deployed Web service. The Web service implementation forwards all the requests to the competence manager, which implements the real functionality. This loose coupling between the Web service implementation and the competence manager makes it easy to switch the JWSDP to another Web service application server, if desired. The functionality in the competence manager is divided in three modules. The “search” module implements all functions that are related to search requests from the user interface. The “admin” module, on the other hand, handles all the management functionality, such as updates to the ontologies. The “common” module implements functions, which can be shared by the other modules. These functions include, for instance,

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initializations and wrappers for accessing ontologies and SPARQL queries (Prud’hommeaux & Seaborne, 2005). All the modules have access to the ontologies and SPARQL query database, which are implemented on top of Jena (McBride, 2002).

USING THE COMPETENCE MANAGER The operations the competence manager supports can be divided into two parts. The management interface can be used to manage the domain ontologies, and it supports functionality to import new ontologies and modify the existing ones. The browsing interface can be used to make queries to the competence manager and display (graphical) reports about the information stored in the knowledge base. In the following subsections, we will cover these operations shortly.

Managing the Domain Ontologies The management interface allows importing new domain ontologies to the competence manager and managing the existing ones. The competence manager supports multiple domain ontologies, which can be imported at runtime. In addition to maintaining multiple simultaneous domain ontologies, the portability—for instance, from one organization to another—does not require changes to the implementation. The only thing that has to be done is to define the domain ontology and import it to the competence manager. The management of the existing ontologies is about adding, modifying, and deleting the topics and resources of the domain ontology. For instance, after attending a course on Java programming language, the employee may increase her competence on Java to the higher level and optionally add to the competence description about the things learned on the course. Respectively,

Applying Semantic Web in Competence Management

Figure 14. Search results with exact and closest matches

Figure 15. Details of a resource and information about the other resources

other kind of domain-specific resources—such as persons, documents, and projects—can be managed for instance by linking people and documents to projects.

Making Queries The competence manager provides three ways of making queries to the knowledge base. The regular expression-enabled searches (see Figure

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14, search area) can be used to find some specific resources. These kinds of searches do not make use of any ontological relationships but apply the search on all the instances in the knowledge base. The second kind of query takes a competence topic as a parameter and returns all the related resources found in the knowledge base. In this case, only the exact matches—that is, resources referring to that specific topic in the query—are displayed. For the exact matches, the knowledge level is displayed as bullets ranging from one to five (see Figure 14, exact matches area). The current availability of each resource is also indicated using a graphical symbol. Competence manager also allows multiple search terms to be used, in which case the search will combine the matches. If there are no exact matches, the third kind of query allows querying the resources that are closest to the queried topic, as described above (see Figure 14, closest matches area). Once the resource(s) has been found, the topics and other related resources can be retrieved (see Figure 15). The calendar showing availability (free/busy) information can be also queried.

DISCUSSION AND FUTURE TRENDS This chapter and the competence manager concentrate on the representation—ontologies—of the competencies and other related resources, and describes how this kind of system allows intelligent and flexible management and searching operations. However, a successful competence management system also needs to implement efficient ways to acquire knowledge—competencies in our case—as easily and automatically as possible. As Abecker, Bernardi, Hinkelmann, Kühn, and Sintek (1998, p. 46) claim concerning knowledge-based systems and organizational memories: “Knowledge acquisition and maintenance—the main reasons why knowledge-based systems so

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often failed in industrial practice—also pose a serious challenge for organization memories.” They also suggest that the existing data sources should be exploited and automatic tools for knowledge acquisition should be used. In our system, we expect that the end-users—employees in an organization—maintain their own competencies, but we acknowledge the risks of this approach in terms of usability and user acceptance. In order to keep the end-users maintaining their competencies, they should have a feeling that they benefit from doing so. In the future, we will improve our system to exploit the existing IT infrastructure—e-mails, documents, groupware systems, and different kinds of system logs and traces—for acquiring and extracting competencies (semi) automatically. Trust plays an essential role in systems like competence manager, which are open to all the employees of an organization and where the employees may state their own competencies. The essential challenge is to assure that the information published is accurate. We believe that in this kind of collaborative systems, the abusers will eventually be exposed. Reputation among superiors and other employees is important, and it would be unwise to ruin it by publishing false competencies. Although the competence manager supports multiple domain ontologies, it does not support automatic sharing and merging of those ontologies. This is not in line with the principles of the Semantic Web. In the future we will work toward more open ontology management, where different domain ontologies may borrow concepts from each other. These include both topics and other resources. For instance, the same person having competence on topics in her company’s topic hierarchy could also have competence on topics defined by her gardening club. The scenarios then would be extended to cover cases where the competence manager could be used between multiple organizations. In doing so, our system

Applying Semantic Web in Competence Management

could be used as a tool for finding organizations based on their real competencies.

CONCLUSION The competence management is becoming increasingly important in competitive environments, especially in knowledge-based organizations. The competence management systems are made available for all the members of a company. These kinds of systems have to be as easy to use and maintain as possible. They must provide as much “intelligence” in terms of helping the user when maintaining his/her competencies and provide semantically sound results when making queries. This would require that the information in the competence management system is in a machine-accessible and machine-understandable format. The Semantic Web technologies provide tools for implementing such a competence management system. This chapter described how the Semantic Web technologies can be used in competence management. When applying the Semantic Web technologies in competence management, we can build systems that benefit from the use of machine-accessible semantics, support highly dynamic environments, and are extensible as well as interoperable between different application domains. In Semantic Web-based approach not only those employees that have competence directly on a topic area can be found, but also employees that have competencies on some closely related areas. This means that we can look up persons who are the best possible candidates for a competence topic. We also introduced an innovative Semantic Web-based tool, called competence manager for managing employee competencies and other relevant resources (documents, customers, projects, and so on). The knowledge base in competence

manager is modeled as ontologies. Therefore, it demonstrates how the Semantic Web technologies can be used in a practical application on the area of competence management.

REFERENCES Abecker, A., Bernardi, A., Hinkelmann, K., Kühn, O., & Sintek, M. (1998). Toward a technology for organizational memories. IEEE Intelligent Systems 13(3), 40-48. Allen, C. (Ed.). (2006). Competencies (measurable characteristics). HR-XML consortium recommendation. Retrieved March 14, 2006, from http://ns.hr-xml.org/2_4/HR-XML-2_4/ CPO/Competencies.html Barclay, R. O., & Murray, P. C. (1997). What is knowledge management. Retrieved January 25, 2005, from http://www.media-access.com/whatis. html Barnes, J. A. (1954). Class and committees in a Norwegian island parish. Human Relations, 7, 39-58. Becket, D. (Ed.). (2004). RDF/XML syntax specification (revised), W3C recommendation. Retrieved January 25, 2006, from http://www. w3.org/TR/rdf-syntax-grammar/ Berners-Lee, T. (2001). Notation 3: An RDF language for the Semantic Web. Retrieved January 25, 2006, from http://www.w3.org/DesignIssues/ Notation3.html Berners-Lee, T., Fielding, R., & Masinter, L. (1998). IETF RFC2396: Uniform resource identifiers (URI): Generic syntax. Retrieved January 25, 2005, from http://www.ietf.org/rfc/rfc2396.txt Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American, 284(5), 34-43.

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Brickley, D., & Guha, R. V. (Eds.). (2004). RDF vocabulary description language (1.0): RDF schema, W3C recommendation. Retrieved January 25, 2005, from http://www.w3.org/TR/rdfschema/ Brickley, D., & Miller, L. (2005). FOAF vocabulary specification, namespace document 27. Retrieved January 25, 2006, from http://xmlns. com/foaf/0.1/ Gruber, T. R. (1993). A translation approach to portable ontology specifications. (Tech. Rep. KSL 92-71). Stanford, CA: Stanford University, Computer Science Department. Harzallah, M., & Vernadat, F. (2002). IT-based competency modeling and management: From theory to practice in enterprise engineering and operations. Computers in Industry, 48(2), 157-179. Hendler, J., & McGuinness, D. L. (2000). The DARPA agent markup language. IEEE Intelligent Systems, 15(6), 67-73. Lindgren, R., Stenmark D., & Ljunberg, J. (2003). Rethinking competence management systems for knowledge-based organizations. European Journal of Information Systems, 12(1), 18-29. McBride, B. (2002). Jena: A Semantic Web toolkit. IEEE Internet Computing 6(6), 55-59. McBride, B. (2004). RDF primer, W3C recommendation. Retrieved January 25, 2006, from http://www.w3.org/TR/rdf-primer/ McGuinness, D., & Harmelen, F. (2004). OWL Web ontology language overview, W3C recommendation. Retrieved January 25, 2006, from http://www.w3.org/TR/owl-features/ O’Leary, D. E. (1998). Enterprise knowledge management. Computer, 31(3), 54-61.

Porter, M. E. (1998). Competitive strategy: Techniques for analyzing industries and competitors. New York: Free Press. Prud’hommeaux, E., & Seaborne, A. (2005). SPARQL query language for RDF, W3C working draft 23. Retrieved January 25, 2006, from http://www.w3.org/TR/rdf-sparql-query/ Sicilia, M. A. (2005). Ontology-based competency management: Infrastructures for the knowledgeintensive learning organization. In M. Lytras & A. Naeve (Eds.), Intelligent learning infrastructures in knowledge intensive organizations: A Semantic Web perspective (pp. 302-324). Hershey, PA: Information Science Publishing. Staab, S., Studer, R., Schnurr, H. P., & Sure, Y. (2001). Knowledge processes and ontologies. IEEE Intelligent Systems, 16(1), 26-34. Stojanovic, N., Maedche, A., Staab, S., Studer, R., & Sure, Y. (2001). SEAL: A framework for developing SEmantic portALs. In Proceedings of the International Conference on Knowledge Capture (pp. 155-162). Sunassee, N., & Sewry, D. (2002). A theoretical framework for knowledge management implementation. In Proceedings of the 2002 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists on Enablement through Technology, 235-245. World Wide Web Consortium. (2001). Semantic Web. Retrieved January 25, 2006, from http:// www.w3.org/2001/sw/

ENDNOTE 1

The notation of all the ontology figures is based on VisioOWL; see http://web.tampabay.rr.com/ flynn/VisioOWL/VisioOWL.htm.

This work was previously published in Competencies in Organizational E-Learning: Concepts and Tools, edited by M. A. Sicilia, pp. 333-257, copyright 2007 by Information Science Publishing (an imprint of IGI Global). 1104

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Chapter 2.29

Intelligent Agents Supporting Distributed Collaborative Learning Weiqin Chen University of Bergen, Norway Barbara Wasson University of Bergen, Norway

ABSTRACT In the context of distributed collaborative learning, it is usually difficult for students to be aware of others’ activities and for instructors to overview the process and regulate the collaboration. In order to facilitate collaborative learning, intelligent agents were developed to support the awareness and regulation of the collaboration. This chapter discusses the facilitation role of intelligent agents and how they support students and instructors in distributed collaborative-learning environments. By monitoring the collaboration, the agents compute statistics, detect possible problems, and give advice synchronously and asynchronously to the students and instructor based on their activities and requests. In so doing, the agents not only

help students to self-regulate their activities but also help instructors to maintain an overview of the collaboration so that they can intervene when necessary.

INTRODUCTION Agent technology has been used in educational environments for some time, and a number of agents and multiagent systems have been designed specifically for educational purposes. In these systems, agents play different roles, such as tutors (Johnson et al., 2000) or co-learners (Chan, 1996). Another role for an agent is that of a facilitator (Chen & Wasson, 2003). For example, in a distributed collaborative-learning environment where users are geographically distributed

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Intelligent Agents Supporting Distributed Collaborative Learning

and collaborate through a Web-based learning environment, an agent can facilitate collaboration processes such as coordination, teacher intervention, group interaction, etc. In computer-supported collaborative work (CSCW), facilitation was studied in group supporting systems (GSSs) (Hirokawa & Gouran, 1989; Pollard & Vogel, 1991; Antunes & Ho, 1999). The activities of the facilitator in supporting group work have been identified. They are, among others, ensuring member identity and maintaining a discussion focus and a procedure for that focus; ensuring everyone has an opportunity to contribute to the discussion and decision regarding focus, procedures and decision issues; providing structure to focus group limits and boundaries; intervening when appropriate; and maintaining awareness of own feelings as an indicator (Chilberg, 1989; Shelli & Hayne, 1992). The facilitator is thought of as a servant to the group rather than a master (Jay, 1976). In the context of distributed collaborative learning, where students and instructors are geographically distributed, intelligent agents have been developed to support group learning (Okamoto et al., 1995; Ayala & Yano, 1996; Dillenbourg et al., 1997; Soller, 2001). Our research is partially inspired by these previous works and aims at testing the facilitation role of agents in both synchronous and asynchronous environments. It is also inspired by work on awareness within the CSCW field (Dourish & Bellotti, 1992; Gutwin et al., 1995). In the DoCTA-NSS project (http://intermedia. uib.no/projects/docta), we developed intelligent agents for both asynchronous (Chen & Wasson, 2002) and synchronous (Dragsnes et al., 2002) collaborative-learning environments and used these environments to support student collaboration in a learning scenario on gene technology, where Grade 10 students in two Norwegian cities collaborated through a groupware system. The chapter is organized as follows. After the background of facilitation agents in distributed collaborative learning, Section 2 discusses design

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issues of agents in distributed collaborative-learning environments, including problems that often occur in the collaboration process, awareness, and how to present the awareness information and advice effectively and nonintrusively. Sections 3 and 4 describe the agents integrated in FLE3 (asynchronous environment) and in the Mindmap Building Tool (synchronous environment). The design, development, integration with the environments, and evaluation of these agents will be described in detail in these two sections. Related work is discussed and compared with our research in Section 5. Section 6 provides our conclusions and future work.

DESIGN ISSUES OF INTELLIGENT AGENTS AS FACILITATORS In this section, we discuss design issues of facilitator agents in distributed collaborative-learning environments, including problems that often occur in the collaboration process, awareness, and how to present the awareness information and advice effectively and nonintrusively.

Software Agents and Pedagogical Agents The term “agents” has been used in a variety of fields of computer science and artificial intelligence. It has been applied in many different ways in different situations for different purposes. However, there is no commonly accepted notion of what it is that constitutes an agent. As Shoham (1993) pointed out, the number of diverse uses of the term “agent” are so many that it is almost meaningless without reference to a particular concept of agent. Many researchers have attempted to address this problem by characterizing agents along certain dimensions. For example, Franklin and Graesser (1997) constructed an agent taxonomy aimed at identifying the key features of agent sys-

Intelligent Agents Supporting Distributed Collaborative Learning

tems in relation to different branches of the field. They then classified existing notions of agents within a taxonomic hierarchy. Nwana (1996) classified agents according to three ideal and primary attributes that agents should exhibit: autonomy, cooperation, and learning. Autonomy refers to the principle that agents can operate on their own without the need for human guidance. They “take initiative” instead of acting simply in proactive response to their environments (Wooldridge & Jennings, 1998). Cooperation refers to the ability to interact with other agents and possibly humans via some communication language, which means they should possess a social ability. Agent learning refers to agents’ capability of improving their performance over time. Using the three characteristics, Nwana derived four types of agents in the agent typology: collaborative agents, collaborative learning agents, interface agents, and smart agents (Figure 1). Although the facilitator agents described in this paper have the ability to learn and to act autonomously, their ability to communicate with users is simple. In this sense, the facilitator agents fall into the interface agent category. Malone, Grant, and Lai (1997) reviewed their experience in designing agents to support humans working together (sharing information and coor-

Figure 1. Agent topology (Source: Nwana, 1996) Smart Agents

Collaborative Learning Agents

Cooperative

Learn

Autonomous

Collaborative Agents

Interface Agents

dination). From the experience, they found two design principles: •

•

Semiformal systems: Do not build computational agents that try to solve complex problems all by themselves. Instead, build systems where the boundary between what the agents do and what the humans do is flexible. Radical tailorability: Do not build agents that try to figure out for themselves things that humans could easily tell them. Instead, try to build systems that make it as easy as possible for humans to see and modify the same information and reasoning processes their agents are using.

The design of our facilitator agents follows these two principles. On one hand, the agents are designed not to replace instructors but to work together with them to support the collaboration. On the other hand, the agents can be started, stopped, and turned off at the will of the users (students or instructors). We will also allow the users to customize the services provided by agents. There are two more concerns when agents are built: competence and trust (Maes, 1997). Competence refers to how an agent acquires the knowledge it needs to decide when, what, and how to perform the task. In our case, will the agent depend only on the rules written by the instructor? Should it be able to improve its performance by learning? For agent systems to be truly “smart,” we believe that they would have to learn as they react and interact with their external environments. The ability to learn is a key attribute for intelligent agents. Trust refers to how we can guarantee that the user, in our case the instructor, feels comfortable in following the advice of the agent or delegating tasks to the agent, for example, letting the agents send e-mails to students directly without the instructor’s confirmation. It is probably not a good idea to give a user an interface agent that is sophisticated, qualified, and autonomous from

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the start (Maes, 1997). That would leave the user with a feeling of loss of control and understanding. We have tried different methods. One of our solutions is that at the beginning, the agents work together with the instructor, providing advice and explaining its reasoning process. Gradually the agents learn from the instructor’s feedback on its advice, improve their performance over time, and build a trust relationship, until a point is reached where the agents are allowed to perform actions without confirmation from the instructor. Pedagogical agents are defined, according to Johnson et al. (2000), as “autonomous and/or interface agents that support human learning in the context of an interactive learning environment.” They are built upon previous research on intelligent tutoring systems (ITSs) (Wenger, 1987). Many researchers have designed and developed pedagogical agents for ITSs (Johnson & Rickel, 1997; Lester et al., 1999; Cassell, 2000), where the agents play the role of a guide or tutor. They tell the students what to do and lead them through the process of performing a task. Most of them tend to dominate the interface and constantly require the student’s attention. Unlike the agents of many ITSs, the facilitator agents of distributed collaborative-learning environments work in the background. They monitor the collaboration, collect data, compute statistics, and provide students and instructors with awareness information and advice, which can be ignored if it is considered of low priority. This makes the agents less intrusive so that the students can concentrate on their collaboration without feeling disturbed.

Awareness Awareness of individual and group activities is critical to successful collaboration. Dourish and Bellotti (1992) defined awareness as “an understanding of the activities of others, which provides a context for your own activity.” They further explained that the context is used to ensure that individual contributions are relevant to

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the group’s activity as a whole and to evaluate individual actions with respect to group goals and progress. The information, then, allows groups to manage the process of collaborative working. Awareness information is always required to coordinate group activities. Gutwin and Greenberg (1995) identified four types of student awareness: social awareness, task awareness, concept awareness, and workspace awareness. Social awareness is the awareness that students have about the social connections within the group. Task awareness is the awareness of how the task will be completed. Concept awareness is the awareness of how a particular activity or piece of knowledge fits into the student’s existing knowledge. Workspace awareness is the up-to-the-moment understanding of another person’s interaction with a shared workspace. It involves knowledge about such things as who is in the workspace, where they are working, and what they are doing. They further point out that ”Workspace awareness reduces the effort needed to coordinate tasks and resources, helps people move between individual and shared activities, provides a context in which to interpret utterances and allow anticipation of others’ actions.” They demonstrated that workspace awareness widgets facilitate coordination for synchronous groupware (Gutwin et al., 1996; Gutwin & Greenberg, 1998). Other proposals facilitate coordination for asynchronous groupware (Roseman & Greenberg, 1996; Tam et al., 2000). Awareness is taken for granted in everyday face-to-face environments, but when the setting changes to distributed environments, many of the normal cues and information sources that people use to maintain mutual awareness are lost. This awareness is important in collaborative learning for two reasons (Gutwin et al., 1995). First, it reduces the overhead of working together, allowing learners to interact more naturally and more effectively. Second, it enables learners to engage in the practices that allow collaborative learning to occur.

Intelligent Agents Supporting Distributed Collaborative Learning

Various mechanisms are used to provide awareness among participants. Some provide explicit facilities through which participants inform each other of their activities. Others provide explicit role support, which gives awareness among participants of each other’s possible activities. In their research on distributed groupware systems, Gutwin and his colleagues (Gutwin et al., 1995) observed that an excess of awareness information can result in awareness overload. Often, when large amounts of information are presented, users have trouble discerning between useful information and unimportant information. Too much awareness information will also distract users from their work. Therefore, the choices and presentation of awareness information are very important. These design considerations are discussed in the Agents as Facilitators section. In our research, the facilitator agents provide awareness information to students and instructors so that students can regulate their collaborations themselves, and instructors can use the information to gain an overview of the collaboration and detect possible problems more easily.

Coordination Coordination, along with communication, is one main component of collaboration. Malone and Crowston (1994) described coordination theory as a research area focused on the interdisciplinary study of how coordination can occur in diverse kinds of systems. They also proposed an agenda for coordination research, where “designing new technologies for supporting human coordination” is considered to be one of the methodologies useful in developing coordination theory. In CSCW, understanding how computer systems can contribute to reducing the complexity of coordinating cooperative activities has been a major research issue and has been investigated by a range of eminent CSCW researchers (Carstensen & Sørensen, 1996; Divitini et al., 1996; Malone et al., 1997).

In distributed collaborative learning, challenges to provide coordination and scaffold effective collaboration have been intensively investigated (Bourdeau & Wasson, 1997; Wasson, 1998; Mildrad et al., 1999; Baggetun et al., 2001; Chen & Wasson, 2003). After examining the social psychological literature, Salomon (1992) identified several problems that often occur in a collaborative learning process: •

•

•

•

“Free rider” effect: Where one team member just leaves it to the others to complete the task (Kerr, 1983; Kerr & Bruun, 1983). “Sucker” effect: Where a more active or able member of a team discovers that he or she is taken for a free ride by other team members (Kerr & Bruun, 1983). “Status sensitivity” effect: Where able or very active members take charge and thus, have an increasing impact on the team’s activities and products (Dembo & McAuliffe, 1987). “Ganging up on the task”: Where team members collaborate with each other to get the whole task over with as easily and as fast as possible (Salomon & Globerson, 1987).

If these problems are not solved properly, effective outcomes cannot be obtained by the collaboration learning. Salomon further recommended that collaborative-learning environments should be designed to encourage mindful engagement among participants through genuine interdependence. Following Salomon’s recommendation and Malone and Crowston’s coordination theory (Malone & Crowston, 1994), Boudeau and Wasson (1997) extended the definition of coordination as “managing dependencies between activities and supporting (inter-)dependencies among actors.” By analyzing the dependencies between actors in three collaborative telelearning scenarios, Wasson (1998) suggested two types of coordination agents: coordination managers and coordination

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facilitators. Coordination managers mediate administrative aspects of collaboration for individual actors and groups or teams, while coordination facilitators support students involved in collaborative-learning activities by mediating processes. These analyses stimulated our design of facilitator agents in distributed collaborative learning.

•

Agents as Facilitators Many research efforts on agents in CSCL environments have implemented agents that possess characteristics of a facilitator. Such characteristics are as follows (Hmelo-Silver, 2002): •

•

•

•

•

Monitoring: Monitor progress, collaboration, participation, and time consumption; detect misunderstandings and/or disagreement Group dynamics: Responsible for making the users follow an outlined scenario or method, directing users into activities that happen at certain stages in the collaboration Clarifications: Encourage discussions when or if disagreements are detected by the monitoring responsibilities Direct manipulations: Initiate breakdown when or if the collaborative processes have run into a deadlock Change behavior: Observe the learners’ reactions as a result of the interaction, thus enabling the agent to judge and adapt its behavior

•

To avoid information overload (including awareness overload), facilitator agents should tailor the information. Schedule: When should facilitator agents present information to users? Should the agents give immediate response to the user’s action, or should the agents wait until the user has repeated the same action several times? Should the agent’s intervention repeatedly happen or just once in a while? Presentation: In what format should facilitator agents present information to users? Should the agents use text or speech to interact with users? If using text, should the information be presented in a pop-up window that needs the user to acknowledge it before he/she can continue, or should the information be in a fixed text area that the user can choose to ignore?

Cao and Greer (2003) developed a system that allows users to specify the rules that the agent will use to present the awareness information. Alarcon and Fuller (2002) mapped users’ actions to a semantic network in order to find out what awareness information is relevant. As a principle in a distributed-learning environment, the facilitator agents should allow users to minimize the interruption of their current tasks while remaining aware of their communications and work contexts.

FACILITATOR AGENTS IN FLE

In addition to these characteristics, designing facilitator agents also need to take into consideration how agents should interact with users (including instructors and students). We identified four factors in this interaction:

This section describes the facilitator agent we have built for an FLE learning environment—its design, implementation, and evaluation.

Relevance: What information should facilitator agents present to users? It depends on the context of the users and their preferences.

FLE (Muukkonen et al., 1999) is a Web-based groupware for computer-supported collaborative learning (CSCL). It is designed to support

•

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FLE

Intelligent Agents Supporting Distributed Collaborative Learning

Figure 2. Progressive inquiry model (Source: Muukkonen, Hakkarainen, & Lakkala, 1999) Creating Working Theories

Presenting Research Problems

Critical Evaluation

Setting up the Context

Distributed

New Theory

Expertise

Developing Deepening Problems

a collaborative process of progressive inquiry learning. Progressive inquiry (Figure 2) entails that new knowledge is not simply assimilated but jointly constructed through solving problems and building mutual understanding (Scardamalia & Bereiter, 1996). The main ideas behind this model are the development of self-regulative and metacognitive skills (Boekaerts, 1999), reflective and critical-thinking skills (Beyer, 1985), and demonstrated academic literacy in reading and writing (Geisler, 1994). Self-regulated learners are generally characterized as active learners who efficiently manage their own learning in different ways. Self-regulated learning is an active construction process whereby learners set goals for their learning and then attempt to monitor, regulate, and control their cognition, motivation, and behavior. Complementing this, reflective and critical-thinking skills are considered as a frame of mind involving alertness to the need to evaluate information as well as mental operations such as testing opinions and considering different viewpoints. There is also a need for the students to demonstrate their reading and writing skills. According to Geisler (Geisler, 1994), the

Searching Deepening Knowledge

students need knowledge of the content domain as well as knowledge of the discipline’s rhetorical processes. Characteristic of progressive inquiry then, is that students treat new information as something problematic that needs to be explained (Scardamalia & Bereiter, 1996). By imitating practices of scientific research communities, students can be guided to engage in extended processes of questions-and-explanation-driven inquiries. An essential aspect of this kind of inquiry is to engage collaboratively in improving the understanding of shared knowledge objects, i.e., problems, hypotheses, theories, explanations, or interpretations (Scardamalia & Bereiter, 1993). Through intensive collaboration and peer interaction, resources of the whole learning community may be used to facilitate advancement of the inquiry process. By synthesizing results of the philosophy of science and cognitive research, essential elements of progressive inquiry emerge. As a starting point of the knowledge-building process, the instructor has to set up the context and the goal for a study project in order for the students to understand why the topic is worthwhile

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Intelligent Agents Supporting Distributed Collaborative Learning

investigating. Then the instructor or the students present their research problems that define the directions where the inquiry goes. As the inquiry proceeds, more refined questions will be posted. Focusing on the research problems, the students construct their working theories, hypotheses, and interpretations based on their background knowledge and their research. Then the students assess strengths and weaknesses of different explanations and identify contradictions and gaps of knowledge. To refine the explanation, fill in the knowledge gaps, and provide deeper explanation, the students have to do research and acquire new information on the related topics. This may result in new working theories. In so doing, the students move step by step toward building knowledge to answer the initial question. To support the collaborative progressive inquiry process, FLE provides several modules, such

as WebTop, Knowledge Building module, Chat module and Administration module, including Course Management and User Management. The Knowledge Building module is considered to be the scaffolding module for progressive inquiry, where the students post their messages to the common workspace according to predefined categories. The categories they can use are Problem, My Explanation, Scientific Explanation, Evaluation of the Process, and Summary (Figure 3). These categories are defined to reflect the different phases in the progressive inquiry process. All Knowledge Building messages within a course are visible as lists of messages that can be sorted by topic (thread), person, category, and date. The WebTop module is a supporting module, where instructors and students can store and share resources, such as documents (research proposals, term papers, designs, or project reports), knowledge-building

Figure 3. Screenshot of the FLE with a facilitator agent

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notes, and links related to their studies, organize them to folders, and share them with others. The Administration module allows administrators and instructors to create, manage courses and participants, and make time tables (Muukkonen et al., 1999).

Facilitator Agent Design In this section, the design of the facilitator agent for monitoring collaboration, giving synchronous advice to students, supporting awareness, and giving asynchronous advice is described.

Agent Monitoring the Collaboration In FLE, an agent is first designed to monitor the collaboration activities. It looks over the shoulders of students and gathers information on the collaboration process and stores it in a database. This functions as the basis to provide awareness information and give advice. Most Web-based applications have a server-side log that is mainly a comprehensive event report to help the administrator in troubleshooting. In a collaborative-learning environment, the information in most server logs is often insufficient or unreadable for regulating the learning process. In the knowledge-building process of FLE, the main activity of the students is to post messages according to categories. Therefore, the information collected by the agent includes the properties of the messages posted by the students. It includes the following: • • • •

Category: To which category is a message posted? Student-Post: Who posts the message? Time-Stamp: When is the message posted? Msg-Correspond: To which message does the message correspond?

•

Depth: At which depth of the thread is the message?

Additionally, the agent monitors the activities of instructors and students in the virtual WebTop so that it can get the updates and send notifications to other participants. By querying the database, the agent is able to provide statistical information on the collaboration process. For example, how many notes have been posted in each category? How many notes has a certain student posted? How often does a certain student post messages? How many notes has each student posted in a certain category? How many notes has a certain student posted corresponding to a certain message?, etc. This information is intensively used to provide awareness information and give advice.

Agent Giving Synchronous Advice to Students The knowledge-building process begins by informing the students about why a topic is worth investigating. For example, in DoCTA-NSS, we used a trigger video, a gene technology documentary, to set the context. Then students engage in the knowledge-building by posting problems, generating hypotheses, developing working theories, finding reliable support for the theories and substantiating preliminary findings, then generating new subproblems and theories in an iterative manner. The progressive inquiry model suggests a sequence and structure for the knowledge-building process. Students are supposed to follow the sequence when choosing categories for their messages. However, in the knowledgebuilding process in FLE, students were found to have difficulties in following the structure and utilizing the categories in the Knowledge Building module (Omdahl, 2002). To help the students understand the structure and sequence of the knowledge-building process, an agent is designed

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Intelligent Agents Supporting Distributed Collaborative Learning

Figure 4. Agent gives advice in the agent message box

to give advice to them when they are found to be unaware of the structure and use wrong categories (Figure 4). For example, if students post messages only in the “My Explanation” category, the agent will give the following advice:

Agent Supporting Awareness

You should comment more on each other’s notes rather than replying only to roger’s notes. You have mainly used “My explanation”. Why not post some “Scientific Explanation” to support your opinion?

•

Because the agent only advises the students how to use the categories and not on how to follow the “rules” strictly, the advice is presented in an agent message window (Figure 4), allowing the student to choose to follow or ignore the advice. Thus, the agent does not create a breakdown in the process.

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In FLE, awareness information is provided by an awareness agent to each student (Figure 5). It includes the following:

•

•

“Who is online”: Shows all the online group members. The students can send e-mail or start a chat with other members. “Update in virtual WebTop”: Shows all the updates on the virtual WebTop of the group members (with links to virtual WebTop of the members) since his or her last log-on. By clicking the link, the students can go directly to the newly uploaded materials. The update list can be sorted by time stamp or poster’s name. “Update in Knowledge Building”: Shows all the newly posted messages on the knowl-

Intelligent Agents Supporting Distributed Collaborative Learning

•

edge building since the student’s last log-on. Each entry on the list includes a link to the message and its properties, such as time stamp, category, name of the student who posted it, and the link to its corresponding message. From the updates, the student can easily find out who has read and responded to his or her message. “Collaboration statistics”: Shows an overview of the statistical information of the collaboration. The students can choose what to view (message-category or messagestudent, etc.) and how he or she would like the information to be presented (pie chart, bar chart, line chart, or table). By viewing the statistics, students can get a feeling of their collaboration efforts compared to others in the collaboration group so that they can improve their self-regulation.

The agent can also send the awareness information by e-mail to the student while he or she is not online. It can notify the student of the updates in Virtual WebTop and Knowledge Building, inform

the student when his or her message is read by other students, or when other students respond to his or her message. The same awareness information is also presented to instructors. With the help of the collaboration statistics, instructors can have a quick overview of the collaboration process and detect possible problems more easily without having to follow every single activity. If instructors find problems by viewing the statistics, they can intervene by participating the collaboration, sending e-mails to students, or chatting with students online.

Agent Giving Asynchronous Advice By checking the statistics, the agent can detect some possible problems in the collaboration. If a problem is detected, the agent is able to create an advice from the rules. The advice is given to the instructor, and the instructor can view the advice and ask the agent to explain it. It is up to the instructor to make a decision on whether he or she should intervene or send advice to the

Figure 5. Awareness agent provides information

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Figure 6. Agent gives asynchronous advice

Figure 7. Integration of facilitator agent and FLE Facilitator Agent logon/off(person, timestamp)

update in WebTop (person, content, timestamp)

monitoring

response to advice (advice, delete/exlain/send)

advice analyzing

FLE

awareness info generator (updates & statistics)

awareness (updates, statistics)

learning

advice generator

rules

advice

database

update in KB (msg, person, category, context, timestamp)

student. The instructor can also save the advice to a file and review it later (Figure 6). If the instructor decides to send advice to the student, an agent can be delegated to do so. Using the e-mail template, the agent translates the advice into an e-mail and sends it to the student. Details about the rules and e-mail template are presented in the E-mail Template section. Here is one example of the advice e-mail:

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From: [email protected] To: [email protected] Subject: less active participation Hi Helge, Lately you have posted fewer messages than others; you may need to participate more. Weiqin.

Intelligent Agents Supporting Distributed Collaborative Learning

Table 1. Message table id

user

Category

Title

reply-to

depth

timestamp

… 15

jand

Working theory

New ‘supercrops’ will wipe out natural flora

1

2

2002-03-25 18:38:35

16

jand

Deepening knowledge

Diversity of crops is being reduced

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peter

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The reliability of that paper is questionable!

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peter

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What do you mean by ‘supercrops’?

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Christan

Working theory

Genetically modified food means the end of world hunger

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…

Implementation Details Figure 7 shows the integration of the facilitator agent with the FLE server. The input from FLE to the facilitator agent are the students and the instructor activities, including log-on/off (logon/off, person, time stamp), update in knowledge building (message, person, category, context, time stamp), update in WebTop (person, content, time stamp), and response to advice (advice, delete/explain/send/save). The monitoring module in the facilitator agent collects these data and saves them into a database. In FLE, we add a button that the students and instructors can click to require various awareness information from the agent. When this button is clicked, the awareness information generator processes the data in the database, generates update information, computes statistics, and presents them in FLE. The advice generator generates advice based on the data in the database and the rules in the knowledge base that contain the instructor’s expertise on how to regulate the collaboration. The facilitator agent can also learn from the feedback of the students and the instructor. Based on the analysis of the advice and the students’ and instructor’s responses to the advice, the agent

revises the rules. These rules are validated by the instructor before they can be used by the advice generator.

Database and Knowledge Base To add, access, and process data in the database, we choose to use MySQL (http://www.mysql. com/), one of the most popular open-sourced SQL database management systems (Table 1). The expertise is represented in the form of production rules in the knowledge base (KB). In the beginning, the instructor can put some general rules in the KB. Based on these rules, the agent generates its advice. Over time, the agent learns from the instructor’s feedback on the advice and induces more specific rules. When used for reasoning by the agent, specific rules have a higher priority than general rules. Externally, the rules are represented in RuleML (http://www.dfki. uni-kl.de/ruleml/). RuleML is an XML-based rule markup language. It allows rule storage, interchange, and retrieval through WWW. Here is a simple rule example in RuleXL format: “Send a msgNotification to a student (confidence factor is 1.0) if a message is marked as “new” to him/her”. This rule corresponds to the message template No. 3 in the E-mail Template section. 1117

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send st udentNa me msgI D msg Not if icat ion 1.0

the advice), and view the content of the message to be sent to students. Each advice presented to the instructor becomes one training example for the CN2 algorithm in the form of feature set: {msg_feature, student_feature, instructor_activity, confidence}. Going through the training examples, CN2 creates a new set of rules and writes it out to KB in the form of RuleML. Afterward, these new rules will be used in generating advice.

new msgI D st udentNa me

E-Mail Template The advice generated by the agent is based on predefined templates that mostly suggest the instructor send an e-mail to a specific student. Some example e-mail templates follow:

Learning The learning algorithm we choose is CN2 (Clark & Niblett, 1989). It can induce new production rules periodically instead of each time new feedback is provided. We believe that this feature fits asynchronous environments, where real-time update is not as crucial as compared to that in synchronous environments. The input of the CN2 algorithm are the features of advice and the instructor’s activities to the advice. The features of advice include the following: • • •

Message feature: Category, student-post, time stamp, etc. Student feature: Last-logout, last-messagepost, etc. Confidence factor: How confident the agent is on the advice

The instructor’s activities include send (delegate the agent to send the advice to students), explain (ask the agent to explain how it generates

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1. Hi [StudentName], Lately you have posted fewer messages than others; you may need to participate more. [InstructorName] 2. Hi [StudentName], [AnotherStudentName] has posted a message [LinkToMessage] corresponding to the message [MessageTitle] you posted. Would you like to read it? [InstructorName] 3. Hi [StudentName], [AnotherStudentName] has posted a message [link to the message], which is quite interesting but hasn’t been paid much attention. I think you should read it. [InstructorName]

Evaluation The evaluation consists of three phases: •

Phase 1: An informal evaluation of the prototype was undertaken at a teacher workshop in Bergen at the end of April 2002. The goal of the informal evaluation was to gather

Intelligent Agents Supporting Distributed Collaborative Learning

•

•

feedback and requirements from instructors and use them as guidelines for further development of the prototype. Phase 2: A formative evaluation was undertaken in a university course INFO281 (Artificial Intelligence—Introduction) in Fall 2002. The goal of this evaluation was to discover potential improvements to the design of the prototype. We focused on functionality and user interface issues. Phase 3: A more extensive evaluation with focus on the performance of the agents was carried out in Fall 2003 in INFO281. In this scenario, over 50 students discussed issues related to Artificial Intelligence through FLE3. For the performance of agents, the evaluation focused on student reactions, instructor reaction and judgments, the role of domain knowledge, and the style of presenting information. Through the experiment, we hope to learn if and how the interventions of the agents will assist the students and instructors in improving the task performance, the engagement, and awareness in distributed collaborative-learning environments.

FACILITATOR AGENT IN MINDMAP BUILDING TOOL In this section, the design and implementation of the facilitator agent in Mindmap Building Tool will be described.

Mindmap Building Tool The Mindmap program is a collaborative tool where distributed users model their conceptual understanding of a topic. The workspace consists of an individual and a shared Mindmap. Users can switch between these two maps by pressing the “teleview” buttons. Based upon each individual contribution in their personal Mindmaps, the

group members must negotiate and agree upon one common representation (Buzan, 2000). The main purpose of this program is for users to have a meeting place where they can brainstorm and build individual Mindmaps and joint Mindmaps. The agent has two roles in this program. The first is to monitor user actions. This includes saving data into log files, updating the internal representation of the environment. The second role of the agent is to function as a coordinator, meaning it will not contribute to the tasks but will facilitate the process. To accomplish this task, the agent analyzes the data contained in the internal representation, which consist of user actions and compares them with earlier agent interactions. This might result in the agent giving warning messages, providing meta-information about the collaboration process, giving initiatives to start discussions, and encouraging passive members to participate more.

Facilitator Agent Design To reduce the amount of inappropriate messages presented to users, we designed a two-layer structure (content layer and presentation layer) in the agent architecture, which was implemented in three modules: advice generation, advice selection, and presentation selection modules (Figure 8). The advice generation module is responsible for generating the content of advice. The advice selection module selects which advice to present to students, while the presentation selection module is mainly concerned about how the chosen content should be presented. All modules utilize the agent context in the database, which is sequential information about user actions, agent interactions, and corresponding user reactions throughout the session and the rules in the knowledge base, which contains the expertise of instructors in facilitating collaboration. All user actions considered important are automatically stored as the agent context in the database. An aggregation of user actions at some

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Figure 8. Architecture of facilitator agent in Mindmap building tool Facilitator Agent

monitoring

Mindmap Building Tool

advice selection

advice

presentation selection

time (t) will make up an internal contextual state in the agent context. The agent evaluates the current context state and how it differs from the last three states (t - 1, t - 2, t - 3). Based on the gathered information, the facilitator compares the refined state with the content rules in the database. Each rule that fires will be evaluated independently, which means that the agent can generate several possible outputs. All outputs are seen as opportunities to interact with the users. Then the agent transfers focus to the advice selecting module. In the advice selection module, the facilitator agent specifies the importance of each advice. The rating of a rule is calculated as a function of that rule’s initial importance rating, modified by the frequency of appearance in the agent context and user reactions. To illustrate this, the contextual history can typically tell the agent that a certain advice has been given to that specific user two

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rules

student activities (person, action, content, timestamp)

database

chat log

times before. The agent uses this information to degrade the potential output to a less important level. Thus, the same request for output could have a varying level of importance over time. When the phase of rating advice is over, the advice selection module compares the advice and decides to display the advice with the highest rated score. When the facilitator has decided which advice to present, it has to decide how this advice should be presented. The rated score of an advice determines to some degree which presentation form to use. Possible presentation techniques are either synchronous, such as dialogue boxes or fixed agent output areas, or asynchronous (e-mail or SMS). For urgent advice, the facilitator will take the form of dialogue boxes, while less important advice is presented in the fixed agent output area. The presentation selection module is also designed to be able to choose appropriate colors for presenting different advice, where strong (and

Intelligent Agents Supporting Distributed Collaborative Learning

sometimes blinking) colors in the background can indicate a high degree of importance. In addition, the agent can supply critical advice with a warning alarm. Sounds can direct the attention of a learner directly to the agent, and this is especially useful if the agent notices that a user is using another program and there are important events happening in the Mindmap. On the other hand, the facilitator agent should be careful when presenting advice with sounds, because they can be intrusive and create unintended breakdown situations. For example, if the advice presented in the dialogue box is evaluated for the third time in a row, it would get a lower importance rating based on the agent context, and thus probably not qualify to be presented in a dialogue box. If the advice competed with other potential outputs, these outputs might be rated with a higher score, thus beating the displayed advice in the dialogue box. It is also important to prevent that low-rated advice from being displayed to the users. To hinder this, all potential advice that is not displayed will get a level of importance increase for each time they are ignored. The danger of this tactic could be that when an advice is finally displayed, it will always be displayed in a dialogue box, thus disturbing the collaboration. To prevent this, each rule that generates a certain advice must also contain a threshold for what level of importance a specific advice must reach before it can take a certain form. To summarize, we have three factors that decide advice’s level of importance: 1. 2. 3.

An advice’s initial level of importance The advice’s current level of importance, calculated by the rule rating function An independent estimate for what degree of importance an advice must reach to take a certain form

We believe that such an approach is necessary when designing the agent architecture for

frequency of agent interaction and how this interaction should be presented to collaborative learners/users.

Evaluation The Mindmap Building Tool has been tested iteratively during development by a test group consisting of two Ph.D. students and one expert user. Testing of the implemented agent has not been the focus of this group, and we wanted to get more hands-on data about how the agent prototype would work in a distributed collaborative setting. Precisely, we wanted to see how students react to the system and the agent without giving them any prior knowledge of the tools. Thus, we conducted a formative usability test using techniques such as observation, concurrent verbal protocols, and interviews focusing on attitude measures (Booth, 1995). In order to conduct the formative usability test, three Master students and one Ph.D. student collaborated to solve a common problem. First, the participants were given a short briefing (about 20 minutes) about the ideas behind the system. Then they went into different computer labs to simulate a distributed setting. The assignment was to brainstorm individually about how to design an intelligent system and then meet in the shared Mindmap workspace to build a joint and agreedupon solution to the initial problem. The test was arranged at the end of a course in INFO281 (Artificial Intelligence), so all the participants were knowledgeable to some extent about the topic. The project lasted for about four hours. The feedback from the participants was positive, in general. In the meantime, we also received critique about the functionality and presentation of the facilitator agents. Further analysis of the data collected is being carried out.

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RELATED wORK Concerning agents in facilitating CSCL, several related works are worth noting.

Understanding Collaboration In order to provide efficient and effective support to students in distributed collaborative-learning environments, many researchers choose to start by understanding the collaboration. Therefore, most efforts in facilitator agents such as IDLC (Okamoto et al., 1995), GRACILE (Ayala & Yano, 1996), and EPSILON (Soller, 2001) have been placed on designing intelligent modules that replace the instructor’s role in the collaboration. In order to obtain this goal, students are restricted to using “semistructured” interfaces such as menu-driven or sentence-openers to collaborate, which restrain the interaction channels and slow the communication process. Furthermore, the advice generated by these intelligent systems is based on its own understanding of the collaboration process, which has a high possibility of misinterpretation or misunderstanding. As a result, the advice might sometimes be inappropriate and confuse the students.

Intelligent Agents in Synchronous Collaborative-Learning Environment Constantino-Conzalez and Suthers (2001) reported their research on coaching collaboration in a synchronous distance-learning environment with minimal reliance on the restricted communication devices such as sentence openers. They evaluated the potential contribution of tracking student participation and comparing students’ individual and group solutions. The coach has the ability to recognize relevant learning opportunities and to provide advice that encourages students to take these opportunities. They identified several

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advice types, such as discussion, participation, and feedback, from which the coach can choose. The experiment results showed that reasonable collaboration advice could be generated without the need for expert solutions or discourse understanding. Our research is partially inspired by their work and aims at testing the role of agents in an asynchronous environment.

Instructor’s Role in Collaborative Learning Dillenbourg (1999) claimed that the instructor retains a role in the success of collaborative learning. He further defines the “facilitator” role of an instructor as not to provide the right answer or to say which group member is right, but to perform a minimal pedagogical intervention (e.g., provide some hint) in order to redirect the group work in a productive direction or to monitor which members are left out of the interaction. He identified three main categories of agents in a CSCL environment (Dillenbourg et al., 1997): subagents, co-agents and superagents. The facilitator agents presented in this chapter fit in the superagents category.

Plug-In Agents in Learning Environments Ritter and Koedinger (1996) attempted to build learning environments that incorporate tutoring agents into pre-existing software packages. The tutor agent is designed to be general so that it can be integrated to a wide range of complex tools. To achieve this goal, a translator is designed to transfer the tool-specific information into the internal representation of the tutor agent. With the help of the translator, tools in different domains are able to share the same tutor agent. The facilitator agents we present are designed with a similar idea in mind.

Intelligent Agents Supporting Distributed Collaborative Learning

CONCLUSION AND FUTURE wORK This chapter presents intelligent agents facilitating distributed collaborative learning. It covers agent design issues and implementation details. In our research, we provide different support to users (including students and instructors). We have combined awareness information and advice, agent regulation, students’ self-regulation, and instructor regulation. The performances of these agents have been explored in various scenarios, both in asynchronous and synchronous collaborative environments, and positive feedback was received from students and instructors. Several issues merit our further investigation: •

•

Determining what feedback is useful to the students is an empirical question. A fine-tuning of content of messages is a collaboration between the instructors and the system developers, taking into consideration the student’s opinion about the usefulness of the feedback. This is one of the issues in focus during the current user testing. In our design, agent feedback is tailorable by the instructor, depending on what he or she wants the agent to say to the students. The instructor writes the feedback in a text file, and the agent loads the content and presents it to the students. A more extensive testing was planned in conjunction with a large field trial in the DoCTA-NSS project in the Fall of 2002. In this scenario, students in two Grade 10 classes, one in Bergen and one in Oslo, collaborate on gene technology through FLE3. However, due to technical problems at the schools, the test was not possible. We are currently evaluating the agents in a university course with over 50 students. Data are being collected from server logs, questionnaires, and interviews. For the ef-

•

•

•

fectiveness of the facilitator agent, we plan to measure how helpful the awareness and statistical information is for the students (student opinion) and how effective the advice is in regulating the collaboration (e.g., look at actual changes in use of categories, see if participation level has increased, etc.). We will also be interested in how the students respond to the way in which the agent presents the awareness, statistical information, and advice. Our aim is to build a plug-in agent to support distributed collaborative learning. Therefore, we need to consider the reusability of the agent. How could we improve the reusability? For an agent to effectively regulate the distributed collaborative learning, it is crucial for it to understand the interactions between computers and students and between students and students. Although a few efforts have been made to study this topic (Barros & Verdejo, 1999, 2000; Mulenbruck & Hoppe, 1999) and some progress has been made, it still needs further investigation. For example, when the students are keeping “silent” in the collaboration, there is no way for the system to know whether the student is reflecting or doing something else. It seems that with the facilitator agent, the collaborative-learning process is well regulated. However, one can ask if it is good to have this regulation, or is it better to give the students more flexibility? We hope the results of our experiment will also help us answer some of these questions.

ACKNOwLEDGMENT This project is a part of DoCTA-NSS, a project funded by ITU (IT in Education) program of KUF (Norwegian Ministry of Church Affairs, Education, and Research). The authors would also

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like to thank the anonymous reviewers for their constructive comments and all the participants, especially Jon Dolonen, Steinar Dragsnes, Rune Baggetun and Anders Mørch, in the pedagogical agent group in DoCTA-NSS.

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study. Unpublished Master Thesis, University of Bergen, Bergen. Pollard, C., & Vogel, D. (1991). Group support system product comparisons. In Proceedings of Hawaiian International Conference on System Sciences (pp. 771-778). Ritter, S., & Koedinger, K. (1996). An architecture for plug-in tutor agents. Journal of Artificial Intelligence in Education, 7(3/4), 315-347. Roseman, M., & Greenberg, S. (1996). Teamrooms: Network places for collaboration. Paper presented at the ACM CSCW’96 Places for Collaboration. Salomon, G. (1992). What does the design of effective CSCL require and how do we study its effects? SIGCUE Outlook, special issue on CSCL, (3), 62-68. Salomon, G., & Globerson, T. (1987). When teams do not function the way they ought to. International Journal of Educational Research, (13), 89-100. Scardamalia, M., & Bereiter, C. (1993). Technologies for knowledge-building discourse. Communication of the ACM, (36), 37-41. Scardamalia, M., & Bereiter, C. (1996). Computer support for knowledge-building communities. In CSCL: Theory and practice of an emerging paradigm (pp. 249-268). Shelli, D., & Hayne, S. (1992). Distributed facilitation: A concept whose time has come? In Proceedings of ACM CSCW’92 (pp. 314-321). Toronto, Canada. Shoham, Y. (1993). Agent-oriented programming. Artificial Intelligence, (60), 51-92. Soller, A. L. (2001). Supporting social interaction in an intelligent collaborative learning system. International Journal of Artificial Intelligence in Education, 12(1), 40-62.

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This work was previously published in Designing Distributed Learning Environments with Intelligent Software Agents, edited by F. O. Lin, pp. 33-66, copyright 2005 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 2.30

Conceiving a Learning Organization Model for Online Education Kam Hou Vat University of Macau, Macau

INTRODUCTION As online technologies and information resources rise in salience, experience has shown (Vat, 2000, 2001, 2002a, 2002b) that online education must be based on theories of learning and instructional design principles to guide usage of the tools and resources for mediating collaboration and social exchanges within communities of learners (CoL). Relatively recent discussions in the literature (Cobb & Yackel, 1996; Marshall, 1996; O’Connor, 1998; Vygotsky, 1978) suggest that learning is increasingly viewed as a constructive process occurring during one’s participation in and contribution to the practices of the community. This is supported by a current shift (Brown et al., 1993) from the cognitive focus on knowledge structures presumed in the mind of the individual learner, to a constructivist focus on the learner as an active

participant in a social context. Indeed, we have been witnessing classroom culture being enriched with tools such as the Web-based search engines that mediate knowledge building and social exchanges among peers as participants in discourse communities (Bonk, Medury, & Reynolds, 1994; Bonk & Reynolds, 1997; Fabos & Young, 1999). These communities open opportunities for learners to interact with multiple perspectives, which challenge their existing knowledge constructions and impose cognitive conflicts (Piaget, 1952) requiring negotiations. The theme of this chapter is to investigate strategies to enhance learning and knowledge sharing in the learners’ communities through the idea of a learning organization model. Its aim is to develop the collective intellect of the CoL through appropriate design of information system (IS) support so as to expand its capacity to adapt to future challenges.

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Conceiving a Learning Organization Model for Online Education

THE IDEAL OF LEARNING ORGANIzATION The concept of the learning organization took seed several decades ago and gained major recognition with the incredible success of Peter Senge’s 1990 book The Fifth Discipline. Senge (1990) describes a learning organization as a place where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free, and where people are continually learning how to learn together. At the core of Senge’s formulation are five essential learning components: personal mastery, mental models, shared vision, team learning, and systems thinking, which may be briefly described as follows. Personal mastery has to do with individual learning, and can be seen as the basic building block through the actualization of which the learning organization is typically constructed. Mental models are about how individuals reflect on their own knowledge, using such models to improve the internal understanding of an organization’s functions and processes. Shared vision implies a sense of group commitment to a matrix of organizational goals, while team learning describes a sharing and utilization of knowledge involving collective thinking skills. The purpose of systems thinking is to understand relationships and interrelationships, as well as the context and the forces that affect the behavior of the organization. To learner-centered teachers, it is not difficult to perceive that the learning organization model somewhat represents an educational context through which students can learn by dealing with others, exchanging ideas, and comparing our ideas with other people. In fact, Vygotsky’s theory (1978) suggests that we learn first through person-to-person interactions and then individually through the internalization process that leads to deep understanding. This belief in the

social process of knowledge sharing is based on people’s mutual understanding of their own and others’ interests and purposes, and the recognition that their interests are somehow bound up in doing something to which they all contribute. Indeed, at one time or another, we might have experienced being a member of a great team. We probably remember the trust, the relationships, the acceptance, the synergy, and the results that we achieved as a group of individuals. Though it takes time to develop the knowledge of working as a whole, when a group of people who over time have learned to enhance their capacity to create what they truly desire to create, this is, in fact, an instance of a learning organization.

THE EDUCATION PHILOSOPHY FOR ONLINE LEARNING In realizing the learning organization ideal of providing educational services, it is observed that there has been a major shift from the linear view to a dynamic view of managing education (Bates, 1995; Berreman, 1997). The first challenge for educators is to figure out how to harness the power of the new media to take advantage of its capacity to support flexibility, concurrency, and just-in-time design, instead of merely using the new media to deliver the same old stuff. In the linear model of education, learning design proceeded in a linear fashion from defining objectives to lesson planning to course delivery. Educators first engaged in a comprehensive learning needs analysis process, often based on assessments done by others about competencies and learning objectives. Comprehensive syllabi were developed. Finally, the course was delivered as planned. Associated with this linear approach were a set of teaching strategies which matched its linear qualities, characterized by being predominantly one way, centralized, and broadcast oriented. When students appeared bored and unengaged

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in this type of program, the solution was to find ways to use new media to make the one-way broadcast more entertaining. Much early online learning was nothing more than a way to generate a broadcast of an expert and his or her multimedia slides with good production values. Today, we need a renewed mindset for education, especially when it is offered through the Internet. Teaching and learning is currently seen as an ongoing process rather than a program with a fixed starting and ending point. The importance of widespread participation by learners in the design of their own learning has been widely recognized (Kimball, 1995). ICTs (information and communications technologies) are particularly well suited to a more dynamic approach to managing education. Good teachers have also always been open to changing their lessons plans based on student input. New media makes it easier. And online environments can provide electronic spaces for continuing conversation among students and teachers about what is working and what is not working in the process. The idea of participatory course design is not to be neglected. The online environment provides an opportunity to support collaborative learning in ways we have not been able to do before. Yet, just putting participants together in some kind of common electronic space will not turn them into a collaborative group automatically. The key is to design a framework for group work, which requires the team to grapple with roles, protocols for working inter-dependently, and mutual accountability.

THE APPRECIATIVE SETTINGS FOR KNOwLEDGE SHARING In selecting the pedagogical devices to support knowledge sharing according to the learning organization model, we have borrowed some legacies from some educational visionaries in trying to blend the art and science of constructiv-

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ist teaching. For example, John Dewey’s designs embedded learning in experience (Dewey, 1938). He advocated field studies and immersion in experiences to stimulate learning. Jean Piaget’s work influences constructivist educators through designs of discovery learning (Piaget, 1970). Students manipulate subject matter and objects representing the subject matter as they interpret their findings. Piaget believed that learners’ internalization leads to structural changes in how they think about something as they assimilate incoming data. Today, constructing meaning on the basis of one’s interpretation of data is indeed the heart of science inquiry. Besides, Feuerstein’s (1980) mediated learning theory refutes the concept of an unchanging intelligent quotient and leads to intense examination of how the classroom setting affects students’ meta-cognition. On examining the varied work of these master architects, we see an array of constructivist settings to enable knowledge sharing. What follows is our appreciation of three important processes considered as indispensable in the operations of the CoL in terms of their collective knowledge activities: the personal process, the social process, and the organizational process. Of particular interest here is the idea of appreciative settings, which according to Vickers (1972) could refer to the body of linked connotations of personal interest, discrimination, and valuation, which we bring to the exercise of judgment and which tacitly determine what we shall notice, how we shall discriminate situations from the general confusion of an ongoing event, and how we shall regard them. The word “settings” is used because such categories and criteria are usually mutually related; a change in one is likely to affect others.

The Personal Process Consider ourselves as individuals conscious of the world outside our physical boundaries. This consciousness means that we can think about the

Conceiving a Learning Organization Model for Online Education

world in different ways, relate these concepts to our experience of the world, and so form judgments that can affect our intentions and, ultimately, our actions. This line of thought suggests a basic model for the active human agent in the world. In this model we are able to perceive parts of the world, attribute meanings to what we perceive, make judgments about our perceptions, form intentions to take particular actions, and carry out those actions. These change the perceived world, however slightly, so that the process begins again, becoming a cycle. Nonetheless, this simple model requires some elaborations. First, we always selectively perceive parts of the world as a result of our interests and previous history. Second, the act of attributing meaning and making judgments implies the existence of standards against which comparisons can be made. Third, the source of standards, for which there is normally no ultimate authority, can only be the previous history of the very process we are describing, and the standards will themselves often change over time as new experience accumulates. This is the process model for the active human agents in the world of CoL, through their individual appreciative settings. This model has to allow for the visions and actions which ultimately belong to an autonomous individual, for individuals do not have to conform to the perceptions, meaning attributions and judgments that are common, even though there may be great social pressure to do so; after all, we are a social animal.

The Social Process Although each human being retains at least the potential selectively to perceive and interpret the world in their own unique way, the norm for a social animal is that our perceptions of the world, our meaning attributions, and our judgments of it will all be strongly conditioned by our exchanges with others. The most obvious characteristic of group life is the never-ending dialogue, discussion, debate, and discourse in which we all try

to affect one another’s perceptions, judgments, intentions, and actions. This means that we can assume that while the personal process model in the world of CoL continues to apply to the individual, the social situation will be that much of the process will be carried out inter-subjectively in discourse among individuals, the purpose of which is to affect the thinking and actions of at least one other party. As a result of the discourse that ensues, accommodations may be reached which lead to action being taken. Consequently, this model of the social process which leads to purposeful or intentional action, then, is one in which appreciative settings lead to particular features of situations, as well as the situations themselves, being noticed and judged in specific ways by standards built up from previous experience. Meanwhile, the standards by which judgments are made may well be changed through time as our personal and social history unfolds. There is no permanent social reality except at the broadest possible level, immune from the events and ideas, which, in the normal social process, continually change it.

The Organizational Process Our personal appreciative settings may well be unique since we all have a unique experience of the world, but oftentimes these settings will overlap with those of people with whom we are closely associated or who have had similar experiences. Tellingly, appreciative settings may be attributed to a group of people, including members of a team, or the larger organization as a whole, even though we must remember that there will hardly be complete congruence between the individual and the group settings. It would also be naïve to assume that all members of an organization such as a CoL share the same settings, those which lead them unambiguously to collaborate together in pursuit of collective goals. The reality is that though the idea of the attributed appreciative settings of a CoL as a whole is a usable concept, the

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content of those settings, whatever attributions are made, will never be completely static. Changes both internal and external to the CoL will change individual and group perceptions and judgments, leading to new accommodations related to evolving intentions and purposes. Subsequently, the organizational process will be one in which the data-rich world outside is perceived selectively by individuals and by groups of individuals. The selectivity will be the result of our predispositions to “select, amplify, reject, attenuate, or distort” (Land, 1985, p. 212) because of previous experience, and individuals will interact with the world not only as individuals, but also through their simultaneous membership of multiple groups, some formally organized, some informal. Perceptions will be exchanged, shared, challenged, argued over, in a discourse, which will consist of the inter-subjective creation of selected data and meanings. Those meanings will create information and knowledge which will lead to accommodations being made, intentions being formed, and purposeful action undertaken. Both the thinking and the action will change the perceived world and may change the appreciative settings that filter our perceptions. This organizational process is a cyclic one, and it is a process of continuous learning and should be richer if more people take part in it. And it should fit into the context of our learning organization model.

CRITICAL IS DESIGN ISSUES FOR PURPOSEFUL ACTION According to Checkland and Holwell (1995), the main role of an information system is that of a support function; such systems do not exist for their own sake. The IS function is to support people taking purposeful action by indicating that the purposeful action can itself be expressed via some activity models, which are also called the “human activity systems” (HAS) models from the perspective of soft systems methodol-

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ogy (Checkland & Scholes, 1990). The function of providing IS support can also be thought of as entailing a pair of systems, one a system that is served (the people taking the action), and the other a system that does the serving (namely, a system that contains a data storage element and a data processing element, as well as the people to maintain, operate, and modify it). Thereby, whenever a system serves or supports another, it is a very basic principle of systems thinking (Checkland, 1983) that the necessary features of the system that serves can be worked out only on the basis of a prior account of the system served. This is because the nature of the system servedthe way it is thought about-will dictate what counts as service, and hence what functions the system which provides that service must contain (Checkland, 1981). Thus, an IS strategy concerning support to an organization, such as a CoL, can be coherently designed and set up only on the basis of a clear concept of the CoL. This is true not only for the IS strategy of the CoL as a whole, but also for the thinking concerning each detailed system created within that strategy. Consequently, the process of IS development (ISD) needs to start not with attention quickly focused on data and technology, but with a focus on the actions served by the intended system. Given that principle, we can now indicate the broad features of our ISD process for CoL. The first requirement, in the general case, is a thorough examination of the ways in which people in the CoL perceive their world. It is necessary to get a grasp of those perceptions as they lead to the particular assumptions about meanings and purposes that cause certain purposeful action to be regarded as both necessary and in need of data-processing support. We need to understand why, among these people, certain data are selected and treated as relevant items in order to get the best possible definitions of accepted purposes and the intentional action, which follows from pursuing them. The examination of meanings and purposes should be broadly based, and its

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richness will be greater the larger the number of people who take part in it. Nevertheless, the examination should try to home in on the question: If we want to pursue this purpose, which seems meaningful to us, what would we have to do and how could we do it? Remembering the many relationships that have to be managed, we have to acknowledge the rarity of complete consensus. What are sought are often the accommodations, which enable energy to be enlisted in undertaking action relevant to plausible purposes. Once the action to be supported has been decided and described, which can usefully be done using activity models, we can proceed to decide whether support should take the form of either or both of the following: automating action, which is currently being carried out by people; or providing information support to people as they carry out their tasks. In the case of the latter, we need to distinguish the informational support that will help people take the desired action, and that which will help people monitor the action and take control action with respect to it if desired outcomes are not emerging. Often the monitoring and control need to be thought about carefully in terms of declared measures of performance, which should derive from how the purposeful activity is conceptualized. From an analysis of the information support appropriate for whomever is concerned with taking the intentional action in the CoL, it is now legitimate to turn attention to the system, which will provide that support through the elaboration of suitable information technologies. Yet, this is not to deny that on occasion new emerging technical possibilities may make possible new intentional action. The key point is that in order to conceptualize and so create a system that serves, it is first necessary to conceptualize that which is served, since the way the latter is thought of will dictate what would be necessary to serve or support it.

CONCLUSION This chapter describes an initiative to develop a learning organization model for online education, paying particular attention to the design issues in support of participatory knowledge construction. The idea is aimed to create collaborative learning experiences, which invite students (lifelong learners) to construct knowledge and to make meaning of their worlds of learning. Specifically, we discuss the educational framework of our design from the constructivist’s perspective of cultivating the collective intellect conglomerated from the communities of learners (CoL), in the form of essential knowledge processes in the context of a learning organization. Our discussion intends to clarify the ideal of a CoL whose growth is often based not so much on delineated learning paths, but rather on knowledge sharing, and reciprocal support for tackling day-to-day problems in the various learning scenarios. We elaborated the design issues of three important knowledge processes (the individual, the social, and the organizational), which the design of a learning organization model for online education must support to help structure and facilitate knowledge interconnectivity. Through the exposition of the individual, social, and organizational processes in which, in a specific organizational context, a particular group of people can conceptualize their world and hence the purposeful action they wish to undertake, the chapter also renders a perspective of a learning context in which our CoLs could be considered as cultural processes in which social reality is continually defined and re-defined in both the talk and action which carries and expresses their multiple agendas of interest and concerns. This provides the basis for ascertaining such issues as: what technical support is needed by those undertaking the learning action, and how modern IS design can help to provide that support. The chapter concludes by reiterating the challenge of

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designing IS support as human activity systems in which purposeful actions of the CoLs can be supported through the elaboration of suitable information technologies.

REFERENCES

Checkland, P. & Scholes, J. (1990). Soft systems methodology in action. Chichester: John Wiley & Sons. Cobb, P. & Yackel, E. (1996). Constructivist, emergent, and sociocultural perspectives in the context of developmental research. Educational Psychologist, 31(3/4), 175-190.

Bates, A.W. (1995). Technology, open learning and distance education. London: Routledge.

Dewey, J. (1938). Experience and education. New York: Macmillan.

Berreman, I. (1997). An improvisational model for groupware technologies. In W. Orlikowski & D. Hofman (Eds.), Sloan Management Review, (Winter).

Fabos, B. & Young, M. (1999). Telecommunications in the classroom: Rhetoric versus reality. Review of Educational Research, 69(3), 217-259.

Bonk, C. & Reynolds, T. (1997). Learner-centered Web instruction for higher-order thinking, teamwork, and apprenticeship. In B.H. Kahn (Ed.), Web-based instruction (pp.167-178). Englewood Cliffs, NJ: Educational Technology Publications. Bonk, C., Medury, P., & Reynolds, T. (1994). Cooperative hypermedia: The marriage of collaborative writing and mediated environments. Computers in the Schools, 10(1&2), 79-124. Brown, A.L., Ash, D., Rutherford, M., Nakagawa, K., Gordon, A., & Campione, J.C. (1993). Distributed expertise in the classroom. In G. Salomon (Ed.), Distributed cognitions: Psychological and educational considerations (pp. 188-228). New York: Cambridge University Press. Checkland, P. (1981). Systems thinking, systems practice. Chichester: John Wiley & Sons. Checkland, P. (1983). Information systems and systems thinking: Time to unite? International Journal of Information Management, 8, 230248. Checkland, P. & Holwell, S. (1995). Information systems: What’s the big idea? Systemist, 17(1), 7-13.

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Feuerstein, R. (1980). Instrumental enrichment: An intervention program for cognitive modifiability. Baltimore, MD: University Park Press. Kimball, L. (1995). Ten ways to make online learning groups work. Educational Leadership, (October). Land, F. (1985). Is an information theory enough? The Computer Journal, 28(3), 211-215. Marshall, H. (1996). Recent and emerging theoretical frameworks for research on classroom learning: Contributions and limitations. Educational Psychologist, 31(3/4), 147-244. O’Connor, M.C. (1998). Can we trace the efficacy of social constructivism? In P.D. Pearson & A. Iran-Nejad (Eds.), Review of Research in Education, 23, 25-71. Piaget, J. (1970). Piaget’s theory. In P. Mussen (Ed.), Carmichael’s manual of child psychology. New York: John Wiley & Sons. Piaget, J (1952). The origins of intelligence in children. New York: Norton. Senge, P. (1990). The fifth discipline: The art and practice of the learning organization. London: Currency Doubleday.

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Vat, K.H. (2000, November 21-24). Online education: A learner-centred model with constructivism. Proceedings of the 8th International Conference on Computers in Education (ICCE 2000) (pp. 560-568), Taipei, Taiwan. Vat, K.H. (2001). Web-based asynchronous support for collaborative learning. Journal of Computing in Small Colleges, 17(2), 310-328. Vat, K.H. (2002a, May 1-4). Developing e-learning architectures for communities of practice: A knowledge perspective. CD-Proceedings of the 2002 World Conference on Networked Learning in a Global Environment: Challenges and Solutions for Virtual Education (NL2002). Berlin: Natural and Artificial Intelligence Systems Organization (NAISO). Vat, K.H. (2002b, March 1-2). Developing learning organization strategy for online education: A knowledge perspective. Proceedings of the 5th Annual Conference of the Southern Association for Information Systems (SAIS2002) (pp. 291298). Savannah, GA: Southern Association for Information Systems. Vickers, G. (1972). Communication and appreciation. In Adams et al. (Eds.), Policymaking, communication and social learning: Essays of Sir Geoffrey Vickers. New Brunswick, NJ: Transaction Books. Vygotsky, L.S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.

KEY TERMS Appreciative Settings: A body of linked connotations of personal or collective interest, discrimination, and valuation which we bring to the exercise of judgment and which tacitly determine what we shall notice, how we shall discriminate situations of concern from the gen-

eral confusion of an ongoing event, and how we shall regard them. CoL: Acronym referring to the community of learners whose learning is fundamentally a social phenomenon. Namely, a CoL focuses on engagement in social practice as the fundamental process by which we learn and so become who we are. Collaborative Learning: Learning is integrated in the life of communities that share values, beliefs, languages, and ways of doing things. What holds the learners together is a common sense of purpose and a real need to know what the other knows. The essence is the underlying process of shared creation involving two or more individuals interacting to create shared understanding where none could have existed on its own. Constructivism: A theory of learning based on the idea that knowledge is constructed as learners attempt to make sense of their experiences. It is assumed that learners are not empty vessels waiting to be filled, but rather active organisms seeking meaning: regardless of what is being learned, learners form, elaborate, and test candidate mental structures until a satisfactory one emerges. IS Support: An information systems (IS) function supporting people taking purposeful action. This is often done by indicating that the purposeful action can itself be expressed via activity models, a fundamental re-thinking of what is entailed in providing informational support to purposeful action. The idea is that in order to conceptualize and so create an IS support which serves, it is first necessary to conceptualize that which is served, since the way the latter is thought of will dictate what would be necessary to serve or support it. Knowledge Sharing: A process of leveraging the collective individual learning of an organization such as a group of people, to produce a higher-

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level organization-wide intellectual asset. It is supposed to be a continuous process of creating, acquiring, and transferring knowledge accompanied by a possible modification of behavior to reflect new knowledge and insight, and produce a higher-level intellectual content.

Learning Organization: An organization that helps transfer learning from individuals to a group, provide for organizational renewal, keep an open attitude to the outside world, and support a commitment to knowledge.

This work was previously published in the Encyclopedia of Distance Learning, Vol. 1, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P. L. Rogers, and G. A. Berg, pp. 367-373, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.31

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A Pedagogical Multi-Agent System for Virtual Environment for Training Cédric Buche CERV/ENIB, France Ronan Querrec CERV/ENIB, France Pierre De Loor CERV/ENIB, France Pierre Chevaillier CERV/ENIB, France

ABSTRACT This study concerns virtual environments for training in operational conditions. The principal developed idea is that these environments are heterogeneous and open multi-agent systems. The MASCARET model is proposed to organize the interactions between agents and to provide them reactive, cognitive and social abilities to simulate the physical and social environment. The physical environment represents, in a realistic way, the phenomena that learners and teachers have to take

into account. The social environment is simulated by agents executing collaborative and adaptive tasks. These agents realize, in team, procedures that they have to adapt to the environment. The users participate to the training environment through their avatar. In this chapter, we explain how we integrated, in MASCARET, models necessary to the creation of intelligent tutoring system. We notably incorporate pedagogical strategies and pedagogical actions. We present pedagogical agents. To validate our model, the SÉCURÉVI application for fire fighters’ training is developed.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

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INTRODUCTION This study concerns the design of virtual environments for training (VET). We want to immerse learners in their professional environment simulated using virtual reality techniques. This enables them to manipulate the environment so that they can “learn while doing”. This idea is driven by the “constructivism” paradigm defined by Piaget (1978) and can find a good implementation in virtual reality techniques as presented by Burdea and Coiffet (1993). Our definition of virtual reality is the one proposed by Tisseau (2001), who proposes to give autonomy to models evolving in the virtual environment by giving them the “triple mediation of senses, decision and action”. So, the main developed idea is that virtual environments for training are heterogeneous and open multi-agent systems. Those multi-agent systems (MAS) had been presented by Demazeau (1995) using the VOWELS model considering a MAS with four vowels: Agent, Environment, Interaction and Organisation. It also has been use for collaborative work simulation by Clancey (2002). We consider the user of a virtual environment as other autonomous agents because he or she can interact with the environment and with other agents or users in the same way. Then, as Tisseau, we propose to add a last vowel, the letter U for User, in the VOWELS model. Our goal is to provide an agent-based model to create a virtual environment for training (VET) integrating an intelligent tutoring system (ITS) in order to provide students with dedicated tutoring. ITSs are based on four models (Woolf, 1992): domain model (Anderson, 1988), learner model (Self, 1988), pedagogical model (Wenger, 1987) and the interface model (Miller, 1988). Comparing to STEVE (Rickel & Johnson, 1999), which is a mono-agent system based on a virtual tutor, we propose a multi-agent system where each entity can contribute to the pedagogy. Moreover, pedagogical skills are not imposed by our model; they are viewed as knowledge items

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manipulated by agents. These elements provide flexibility and adaptability to our VET. In Lourdeaux, Fuchs and Burkhardt (2001), HAL is a pedagogical agent (based on a pedagogical model) helped by environment-agent and scenario-agent responsible to the detection of the learner actions and intentions. The present work goes further; it takes into account all the ITSs models and both the learner environment (physical and social context) and the pedagogical one are considered as a multi-agent system. A major issue in multi-agent system is the definition of agents’ interactions. In our case, interactions have to be flexible and controlled by pedagogy. Therefore, we propose a model centred on the concept of organisation, which permits to structure these interactions. We show that information about organisation can also structure knowledge upon classical ITS models and thus allows agents to make pedagogical decisions. After an overview on ITS models, we present our MASCARET model (multi-agent system for collaborative adaptive and realistic environment for training). We start by defining a generic model, which is then derived to represent the different types of interaction in our VET. Next we explain how the different models of ITSs are taken into account by pedagogical agents, defining therefore the pedagogical organisation. Finally we briefly present the application of MASCARET to a firefighter training environment: SÉCURÉVI.

INTELLIGENT TUTORING SYSTEMS Intelligent tutoring systems (ITS) are computer processing systems for training incorporating communication techniques of knowledge and skills. They were conceived from the combination of interactive learning environments (ILE) and artificial intelligence (AI) techniques. Such systems were developed with the objective to adapt speed and level of the knowledge representation to the student’s needs. The system uses an

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internal representation of this knowledge and has possibility of reasoning. In the last 10 years, ITSs were used within the framework of training and had proved their effectiveness (Shute, 1990). For example, students using LISP tutor (Anderson, 1990) finish their exercises 30% faster than those that receive a traditional training. The final examination shows a difference of 43% in result between the two methods. Traditionally an ITS is described using four major functions or components (Wenger, 1987). Thus, an ITS is composed of models, each one playing a particular role and contributing to ITS decision-making. The first ITSs were composed of an expertise on the domain, an expertise on what must be learned and a representation of what the student learned or misunderstood. Burns and Capps (1988) identify these components as the three models of an ITS. They correspond to the “expert module” (Anderson, 1988), to the “diagnostic module of the student” (VanLehn, 1988) and to the “instruction and curriculum module” (Halff, 1988). Later, a fourth model has been introduced, augmenting the first three, the “interface module” providing knowledge about environment representation. Although there is no standard, an ITS generally consists of four models, identified in Woolf (1992): • • •

•

a domain model, representing the expert knowledge, a learner model, permitting to get the state of knowledge at a given moment, a pedagogic model, permitting to carry out teaching choices according to the learner behaviour, an interface model, allowing the information exchange between system and user.

Domain Model The domain model represents the expertise on the domain (Nkambou, Gauthier & Frasson, 1997).

It is also called expert model since it defines the expert knowledge in a field of knowledge. The domain model does not contain only a description of competences to acquire, but also a representation of knowledge to transmit. It has to be able to propose several paths possibilities to achieve an objective. It consists of two components: the declarative knowledge and the procedural knowledge. On one hand the declarative brings a base of knowledge representing elements the professor would like to transmit. On the other hand the procedural proposes a reasoning system able to interpret the knowledge base. The purpose of expertise on the domain is to allow a comparison with solutions suggested by the student. For that, the domain model has to be able to generate solutions on the problems in the same context as the student one, so respective answers can be compared. Thus the system is able to determine differences and correspondences between student actions and those awaited. It can also evaluate performances and locate student difficulties. Lastly, the knowledge on the domain allows the generation of explanations related to the expert solution. The knowledge representation requires the use of formalism. The logical formalism was one of the first formalisms suggested to represent knowledge. It uses a language, axioms and rules (logic proposal, fuzzy, modal, etc.) allowing the representation of veracity, uncertainty, temporality, and so forth. Moreover, cognitive sciences, which are interested in intelligence mechanisms, generally use a formalism based on graphs. It gathers, in the shape of graph concepts, notions representing knowledge and their inter-connections. Semantic networks (Quillian, 1968), networks with markers propagation (Fahlman, 1979) or conceptual graphs (Sowa, 1984) allow the representation of knowledge. An inference mechanism brings know-how. Lastly, a logical description formalism of knowledge representation called frame (Minsky, 1975) is also used. A frame is a structure to represent a concept or a situation as “a room” or

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“to be in a room”. This formalism associates for each knowledge a know-how.

1.

Student Model Whereas the domain model contains expert knowledge on the problem resolution, the learner model (Leman, Marcenac, & Giroux 1996; Py, 1998) brings a measurement of student knowledge on this problem. It is as called a diagnostic model since it allows measuring the student progression. Ideally, this model must contain an advanced representation of the student profile. It must provide all the specific aspects of each student’s behaviour and knowledge in the form of a model. The student profile is established and updated through the interactions he or she operates with his/her environment. Using information of the learner model, the system adapts itself to the student. The profile must integrate learner knowledge on the domain model, called epistemic sub-model (Delestre, 2000). The objective of the epistemic sub-model is to determine the state of student knowledge for concepts present in the domain. Moreover, it must integrate his or her not-epistemic characteristics representing his/her pedagogical preferences or objectives, called the behavioural sub-model (Delestre, 2000). It defines pedagogical objectives of the current exercise. The system must take into account these objectives, while being more or less flexible according to the training type. In the same way, the student must have the possibility to choose the point of view of such or such teacher. Lastly, the system must deal with the specific student capacities according to fields of teaching. One of the learner model objectives is to allow the evaluation of each knowledge element to acquire. Incorrect behaviours can occur; also incorrect knowledge must be represented with the aim to identify errors. Several methods exist to evaluate knowledge to be acquired:

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2.

3.

Model tracing compares stages achieved by the student and existing stages in procedural rules defined in the domain model. This approach was used by tutor LISP (Anderson & Reiser 1985); Issue tracing is a modification of model tracing. The purpose of this model is not to model the problem resolution process but rather to determine competences and solutions to use. An update of the competences acquired by the student is used. Tutor WEST (Burton & Brown, 1982) uses this method; Expert systems analyze the student answers. The conclusions of the domain model are used to update the learner model. HANDLEBAR (Clancey, 1983) uses this method.

The representation of the epistemic and behavioural sub-models can use various methods: 1.

The method called the overlay proposes to cut out the expertise in basic units. The student model is composed of a subset of these entities. The student knowledge is regarded as under part of the expert knowledge. An empty model corresponds to a student who would not have any domain knowledge, while a model identical to the expert corresponds to a student who would have reached the same level of control as a domain expert. Each knowledge item can be labelled with a discrete value (known/ unknown) or a continue value (from 0 to 1). This principle was used by tutors WUSOR (Stansfield, Carr & Goldstein, 1976) and HANDLEBAR. The errors made by the student are explained in terms of knowledge absence: it is the ignorance of such rule or such concept which leads the student not to do the best possibility. This model considers the student will learn nothing except what the expert had provided. Thus there is no

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2.

3.

mechanism to know not acquired knowledge and those which were not still presented; The method called differential, which is an extension of the overlay, where knowledge is separated considering if the student was exposed to such or such knowledge or was not. This method was used for tutor WEST; The method called the buggy model, which is also an extension of the overlay. The approach consists to present in the learner model rules whose application produces an incorrect result. This method was used by Brown and Burton in systems BUGGY (Brown & Burton, 1978) and DEBUGGY (Burton, 1982). Knowledge is represented by an elementary procedures network. Any correct procedure can be replaced by an incorrect procedure having the same domain applicability. From a set of answers given by a student, DEBUGGY builds the correct and incorrect procedures network whose behaviour approaches most the student.

•

•

Pedagogical Model The pedagogical model allows defining the pedagogical activities aiming at helping the teacher in the training process. It allows simulating the teacher decisional behaviour relative to a pedagogical intervention, based on differences between the domain model and the learner model. Then, the main objective of the pedagogical model is to answer three questions (Lourdeaux et al., 2001; Wenger, 1987): •

When intervene? The pedagogical model determines when an intervention is desirable, if the student must be stopped or not. The trainers can intervene at various times: following errors made by formed, before errors in order to show up the risks of errors, following student questions, and so forth. To determine when to intervene is a subtle

decision. To guide a student, it is sometimes more effective to let the student seek during one moment than to stop him or her each time. On another side, been left to him or herself, the student probably will be lost. Why intervene? Moreover, the pedagogical model determines why to intervene. The objective can be to check student knowledge acquired or guide him or her in its training. Thus, Lourdeaux et al. (2001) proposes two types of interventions: 1. Pedagogical strategies related to the scenario modification allowing trainers to check student knowledge; 2. Pedagogical strategies related to the student guidance are distributed according to two categories: active methods (training by the action) and explanatory methods (training by the explanation). How intervene? Much more, the pedagogical model determines the nature of the assistance. It can be a modification of the environment, the exercise or simply an addition of information. For that, it must take into account the student profile and the environment characteristics. Lourdeaux proposes a categorization in the various ways of representing the “pedagogical assistances” according to various levels of realism: enrichment, degradation, simplification, and so forth (Lourdeaux et al., 2001).

The pedagogical model must choose possible interventions allowing helping the student. For that, it can specify and control its interventions based on one or more “methods”: •

Socratic method: the system asks questions to the student in order to encourage him/her to analyze its own errors (used by SCHOLAR and WHY);

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•

•

•

Coaching method: the system lets the student act and waits until he/she asks for assistance (used by SOPHIE, WUMPUS and WEST); Learning by doing method: the system is active and encourages the student to select information and deduce orientations on the domain model; Learning while doing method: the system remains in background task and only provides punctually tips.

2.

Interface Model The interface model allows communication and finalizes the form by which the system wants to transmit information. This model is in co-operation with the diagnostic and didactic of the system. It transforms the internal representation of the system into comprehensible information for the learner. This model can transmit the same knowledge more or less clearly. Indeed, even if the pedagogical model decides course and contents of the didactic actions, the interface model deals with its final form. More generally, this model takes care of communications between the student and the system remainder (Miller, 1988). Thus, it is in charge of the bidirectional communication between the internal representation of the system and a comprehensible interface for the student (Wenger, 1987). We can define two directions for the communication: 1.

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System towards learner: it is the ergonomic of the interface, the way of defining which type of media to use to translate the system information. One of the difficulties in this context is the difficulty of adaptation to users. Indeed, various users will have different behaviours with various types of interface. For example, certain people will be more receptive to a purely visual interface, oth-

ers with sound, and so forth. The interface designer will be able to discover which type of stimuli the user will be most receptive to, based on the learner model. Learner towards system: it is the detection of action/intention, the way of recovering information coming from the user in order to be able to analyze them. Burkhardt (2003) underlines the fact that the intention detection of the user is a central problem regarding interactions. It is necessary and important to separate action detection from of intention detection. Indeed, the intention does not imply the action and conversely.

We noticed three systems setting up one or more facets of the interface model: •

•

•

METADYNE (Delestre, 2000) is an adaptive hypermedia able to get student actions following hypertexts links used. Ergonomics is directed by the hypermedia, and consequently presents little interest in an immersive virtual environment; HAL (Lourdeaux et al., 2001) proposes to recognize actions using message communication between environment agents and compares these data with a preset scenario to extract important information; STEVE (Rickel et al., 1999) also proposes to recognize actions using communication of messages between environment agents and build a scenario considering a final objective. It sets up an animated virtual tutor able to recognize and generate speech.

The use of the interface does not have to impose a burden for the training that would block the real training (Wenger, 1987). The interface must use the advantage of existing communication conventions, like the natural language, while introducing some news, such as mouse (Vigano, Mottura, Calabi & Sacco, 2003).

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MASCARET MODEL Our goal is to train teams to collaborative and procedural work in a physical environment. In this case, we have to simulate in a realistic way this physical environment and the collaborative and adaptive team member’s behaviour in the social environment. Evolution of those environments results from simulation of autonomous agent’s local behaviour and their interactions. We propose a model, called MASCARET, where we use multiagent systems to simulate collaborative, adaptive and realistic environments for training. This model aims at organizing the interactions between agents in the virtual environment and provides them with abilities to evolve in this context. In addition, it allows the establishment of models necessary to the creation of an intelligent tutoring system. In this context, the stress is put on the organisation facet of the MAS. The organisational model specifies if agents may interact or not, the way they can do it and what they are expected to do according to their capabilities (their potential behaviour and the information they are supposed to hold). Because agents may have to adapt their behaviour according to this information, they must maintain knowledge about organisations. It is a major issue in a VET where learners and teachers have to build representations about their environment. They have to know how this environment is structured and it is necessary to control what kind of interaction may arise. The generic model of organisation is given in the next section. Its derivation to the modelling of specific interaction contexts is detailed in the followings.

Organisational Model The generic organisational model is presented as a UML class diagram (Figure 1). It is based on the concepts of agent, organisation, role and behavioural feature. Hannoun, Boissier, Sichiman and

Sayettat (1999) have already proposed an organisational model for multi-agent systems, but this model, dedicated to the collaborative realisation of procedures, is not generic enough to solve our problem. Ferber and Gutknecht (1998) have also proposed such a model called agent/group/role, but this model seems to be more a pattern for MAS design than a model that formalises the concepts of organisation and roles. In our model, the aim of the organisation is to structure interactions between agents; it enables each agent to know its partners and the role they are playing in the collaboration. The concept of role represents agent responsibilities in the organisation (corresponding to their behavioural features). Agents have then an organisational behaviour that permits them to play or abandon a role in an organisation. This behaviour also enables agents to take into account the existence of other members. This model is a generic model in the way that all the resulting classes are abstract. The organisational model is then derived to implement specific organisations. Figure 2 gives examples of different instances of specific organisations that can be modelled using MASCARET. This figure is not an exhaustive view of what the organisation may be and many other organisational entities may be imagined. Interaction patterns may differ by the number of agent involved and the roles they play. Notice that one agent can play roles in different organisations. Physical organisation specifies the interactions that occur between entities compounding the physical environment of the trainees. Because the participation of an agent to an organisation is explicit, the designer of the training session can decide to activate or ignore different kinds of physical interactions. Thereby the difficulty level of the exercise can be controlled. Virtual human and users’ avatar may be involved (or not) in physical organisation because they have to manipulate it and to undergo their environment

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Figure 1. Generic organisational model (UML class diagram)

Figure 2. Different types of organisation in MASCARET user

student

proxy Mediation

student

Human org

Avatar

physicalObject

teamMember

Social org teamMember

VirtualHuman teacher

user

tutor

PedagogicalAgent Mediation

Agent Type

proxy

expert

PedagogicalAgent

Physical org physicalObject

Org. Type

(e.g., depending on its learning experiences, a fire-fighter trainee may or not have to undergo the toxicity of a gas due to an accidental lick). Social organisation represents social interactions that are a major point in collaborative training. This kind of organisation involved agents representing humans: virtual humans (their expected behaviour is simulated), avatars

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physicalObject

Pedagogical Org

that represent users’ actions (trainees, teachers or co-workers). Pedagogical organisation allows specifying what trainees are supposed to do and what kind of actions and knowledge may be performed by pedagogical agents. These agents can be artificial agents (as an intelligent tutor in an ITS) or humans. In this last case, their actions are mediated by

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their proxy (see mediation organisation below). Pedagogical agent can play a wide variety of roles, for example, tutor, domain experts, learning companion, troublemaker … Mediation organisation makes explicit the way the user can interact in the virtual environment and how far he or she can delegate actions to his avatar: for example the actions corresponding to movement from points to points can be delegated to the avatar so that the learner can focus his or her attention on more specific learning objects. Actions the learner is supposed to do and actions delegated to his/her avatar are specified by their respective roles. Human organisation is not completely under the control of the VET: corresponding interactions are not mediated by the system. Anyway, assumptions may be made about these kinds of interactions and it can be decided to prevent them (when users are in different rooms) or to encourage them (by an invitation to ask a question to the teacher for example).

Physical Interactions In a virtual environment for training, the user’s (learner and teacher) physical environment must be realistic, interactive and act in “real-time”. Then, to reach the constraints of virtual reality, models we use to simulate physical phenomena are obviously simplified. Therefore, the teacher may want, for pedagogical reasons, to inhibit some phenomena. For that, we must propose models that are compatible to a disconnection between the phenomena. Moreover, although all interactions have potential effects on the two agents involved, we consider that the interactions between agents have a privileged direction. Then, the reactive agents’ behaviour evolving in physical environment is to perceive situations and to act consequently. A practical limit of the individual based model is that each agent can potentially perceive all others. The complexity

of the algorithm is in this case O(n 2). Then, we have to design rules to organise these interactions between reactive agents. For that, we use the generic organisational model we have proposed before. In this case the organisation is a network where agents are connected together when they are in interaction. We call this organisation an interaction network (InteractionNet, Figure 3). To represent the concept of privileged direction in interactions, we define two particular roles called source and target. The goal of source agents is to give information on their internal states to other agents (targets) so that they can compute the interaction’s “strength” and their internal state. The interaction can be detected by the two agents involved, but, for “real-time” computation reasons, it is better if only one agent detects it (one of two agents or another one else). We then define a recruiting role, which has the responsibility to maintain the knowledge of each agent upon the structure of the organisation. This means that an agent playing this role has to detect the interaction situations. The internal architecture of reactive agents matches the constraint of physical phenomena disconnection presented before, because an agent can have several reactive behaviours, each one participating in a different interaction network. This elementary behaviour (see ReactiveBehaviour class in Figure 3) consists in the computation of a vector of internal state variables after the evaluation of inputs (from the interactions where the agent is a target) and presents a pertinent external representation of its state (output) to other agents (potentially targets of an interaction where the former agent is a source).

Social Interactions The environment is also populated by more “intelligent” agents representing humans. They are undergoing the environment and acting on it as reactive agents, but the way they choose their actions is carried out on a higher level of abstrac-

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Figure 3. Interactions network

Figure 4. Team model

tion. Those agents are various humans involved in the formation (learners, teachers) who are played by autonomous agents. In our case, the social environment is structured and each member knows its roles and those of its partners. In a specific organisation the interactions between the team members are also structured by the mean of

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domain specific procedures known by all members. We thus derive our generic organisational model to formalise this concept of team (Figure 4). We are interested in the case where the action’s coordination between team members is already stated and written in procedure. On the other hand, the environment being dynamic, agents

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can need to adapt the scenario to the environment. The procedure must then have a semantic representation so that agents can reason above. Then we use a high level language to describe a procedure (Allen temporal logic). The reasoning of team members relates on organisation, procedures and actions. We propose a model of agent having local organisational knowledge. A rational agent is divided into a decisional part and a part represented by modules of perception of the physical environment, communication and actions (Figure 5). It must carry out actions of the procedure and adapt to situations not envisaged. The procedure describes interactions between agents in an optimal situation, and leaves to the agent the responsibility to build implicit plans (not clarified in the procedure) considered as “natural” within an applicative situation. Moreover, the procedure coordinates actions of a semantic level which we call “actions trades” such as “sprinkling a fire” in the case of firefighter procedures, whereas the implicit plans arrange actions of a generic semantic level for humans such as “going at a point”. For that, the agent must be able to reason on actions and we propose a model of goal directed actions having pre-conditions and post-conditions. Thus, before carrying out an action, the agent must make sure that pre-conditions of this one are checked. If it is not the case, it builds itself a plan by back chaining on pre-conditions and post-conditions of actions. When an agent starts or stops actions, it broadcasts a message that enables other members to update their knowledge on the evolution of the procedure. When this behaviour failed, the agent calls its organisational behaviour, which can help it to find a solution with another team member. Thus, in a hierarchical organisation, when an agent has a problem that it cannot solve, it refers to its superior. Then, the superior has the responsibility to find a solution among its subordinates (if it does not find any, it refers to its own superior about it). We represent this mechanism by a method like a Contract Net Protocol.

Users Interactions The avatar in MASCARET is not only the representation of the user but has also its own behaviour (reactive and rational). Therefore the avatar model in MASCARET is the same as rational agent. In order to provide the decision making responsibilities to the user (student) the link between the collaborative behaviour and the action module (Start Action message) can be inhibited. This inhibition is dynamic, meaning a learner can take the control of an autonomous agent during the simulation. It becomes then his or her avatar. At any time, the user can release control on the avatar. Their adaptive behaviour is supported by the dynamics of roles attribution between the user and his or her avatar (see mediation organisation Figure 2). All modules composing the avatar are still active and thus remain potentially usable. The Action’s Result message provides information to the Facts database. The avatar has the knowledge on the action historic and on the current action running. In addition, the avatar is still informed about result of other member’s actions and still informs them about action done by the user. The knowledge on the evolution of the collaborative procedure is still consistent. As the collaborative behaviour of the avatar is inhibited, it does not call any more the organisational behaviour (in case of an action failure). It becomes the responsibilities of the user to find a solution.

Figure 5. Architecture of rational agents

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Management of ITS Models Our objective is to integrate a differentiated pedagogy based upon context. Intelligent tutoring system (ITS) presented earlier aim at providing students with dedicated tutoring. In MASCARET, the information presented by classical ITS models are accessible. The goal of this paragraph is to show how we can represent the four models of an ITS. In MASCARET, the models are seen as bases of knowledge constructed and manipulated by agents or humans (human or virtual).

The Domain Model The expert model represents the knowledge that the learner has to acquire. In our case this knowledge is essentially procedural, but also “know-how” to act in the environment. Therefore the domain model presents knowledge on the social and physical environment. In order to represent this knowledge, this model is based upon the Team and InteractionNet models proposed by MASCARET. This means that comparing to models presented in the ITS overview section, our formalism is based on a logical representation (action pre-conditions and goals), but also on a graph representation to explicit links between the actions of roles and interaction between the physical entities. The expert model is not represented as a special class but is represented by the set of organisations. But in no way must the expert model reference each instance of organisation. It only refers to the knowledge on organisations structures. An agent asking information to the agent maintaining the expert model never asks information in a specific context (“which action the user can do now?”), which is the responsibility of agents maintaining the user model for example, but asks question in a generic case (“what actions can be done after this action in this type of organisation?”). In that way the reification of the concept of organisation is very important.

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Then, about the social environment, the agent maintaining knowledge on the expert model is able to answer questions about roles, actions and procedures. This information is written by the expert according to models proposed by MASCARET. Therefore, as STEVE for example, the expert model is able to inform on pre-conditions or goal of actions, the order of those actions and responsibilities of each intervenient. The way this information is used depends on other agent behaviour. For example an agent can ask infor mation on the goal of actions to explain it to the learner. For the physical environment, the expert model maintains information on casual links between the different roles (sources, targets …) intervening in physical phenomena. This knowledge is written by the expert and the application designer. An agent can then ask information, for example what can change the direction of the lick of gas and have the answer that it is an agent playing role “source” in a “gas propagation” interaction net.

Errors Model As in some ITS presented by Py (1998), we consider errors as crucial information. Therefore we decided to introduce the errors model in our ITS. An error model is a knowledge base on classical errors done by learners. It can be compared to the buggy model presented earlier; its goal is to help to identify the error and determine the reason for this error. This information is written by the teacher and takes the form of the rule: “usually students do action C after action A; it is an error because something,” where “something” is classically a domain-specific rule. Using the organisation model of MASCARET, a pedagogical agent can detect errors on procedure (“not the right action or not done by the right team member”). The responsibility of the agent managing errors is then to exploit its knowledge about typical errors (the left part of the rule) in order to give more accurate information on the

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error (the right part of the rule). Therefore the tutor can perform a particular action, for example explain the “something”. The agent managing errors can record information about error occurrences. This information may be used to enrich the knowledge about typical errors. It is under the control of the human teacher; in the future, the agent might learn it.

Learner Model As seen earlier, the learner model could be divided on psychological information, curriculum, and learner current actions and state. In MASCARET, a special agent maintains information on the learner current state and action. This agent is the avatar agent; it maintains knowledge on the actions done by the user, which roles he or she plays in which organisations. In that way it can assimilate to an overlay method because it contains a subset of the expert model. Moreover, the avatar can plays roles in physical phenomena (InteractionNet); then it maintains also this knowledge and can inform on the influences the user is currently overcoming. We could have decided to give its pedagogical autonomy to this avatar. In this case, the avatar could decide to explain/do the next action or decide not to overcome some physical phenomena for pedagogical reasons. But we prefer to give the avatar its pedagogical responsibilities by the means of pedagogical roles in pedagogical organisation and then let the teacher express its pedagogical rules which is the role of the pedagogical model. Psychological criteria of the learner are, for example, student’s emotion state or level. In MASCARET, this information is not yet accessible, but we are planning to work on it, based on Kermarrec’s (2002) works.

Interface Model This model permits the communication between the system and the user. It presents information to the student and detects his or her actions. Virtual environment for training has the specificity to tend to be immersive. Therefore the user is supposed to perceive and to act as naturally as possible. In MASCARET, this model has not been represented yet. But we can consider that we have the same problems as Lourdeaux et al. (2001), whose work is addressed to decision making and not technical gesture. This method is based on virtual behaviour primitives. This means the correspondence between values of sensors (FOB, mouse, gloves…) with actions (walk, take…) and the procedure knowledge. We also want to detect the intention of the user to act differently according to the difference between the user actions and intention. We consider that the user verbalises his or her intentions and then they can be detected by the system with voice recognition.

Pedagogical Model The pedagogical model defined pedagogical strategies issued from psychological and didactic research. We are particularly interested in collaborative strategies. Therefore the pedagogical model is based on knowledge about roles (pedagogical actions), interaction (exchange of information about the different ITS models) and organisation (action coordination to reach the shared pedagogical goal). To our point of view, the pedagogical model shares characteristics of the domain model, where the domain is “pedagogy”. As in the former case, general knowledge about pedagogical organisation is needed, instead of particular configuration of a training session. The pedagogical organisation structure is explained in the next section.

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Pedagogical Interactions Pedagogical agents are defined as agents playing pedagogical roles. In MASCARET, potentially any agent can hold pedagogical skills. So these agents may have the following representations: 1.

2. 3.

4.

an autonomous artificial agent, which can have or not a representation in the virtual environment; an avatar of a teacher playing no roles in the social environment of the trainees; an avatar of a user (teacher or trainee) playing an active role in the environment (in this case the agent has three types of roles: domain specific, proxy of the user and pedagogical ones); an autonomous artificial agent simulating a human or a physical object (it is part of the environment and also exhibits pedagogical skills).

The contribution of these agents to the different ITS models presented in this chapter is obviously not the same. The first category of agents cor-

Figure 6. Pedagogical agent/role/actions

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responds typically to tutors of traditional ITSs: they maintain information about the ITS models and communicate it to other pedagogical agents. The teacher can be personified in the environment in order to facilitate the communication with learners. The contribution of the learner avatar is important because it can gather information about the learner (user-avatar interactions). As the avatar participates also to social organisation it holds information about the domain (procedures to be performed). A pedagogical agent participating to the realisation of a collaborative procedure can play pedagogical roles as a companion or a troublemaker; in this way its behaviour is part of the pedagogical model. Physical objects of the environment are knowledge items of the domain model; they constitute also elements of the interface model (to control the way information is presented to the learner and the type of behaviour they can trigger in reaction to a user action in a particular pedagogical context); finally, to a certain extend they can also contribute to the pedagogical strategy: they can perform actions like to inform the user about its structure or its potential behaviour. Generally, these agents are mostly reactive

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Figure 7. Pedagogical process

as proactive agents and the pedagogical strategy is under the responsibility of deliberative agents like artificial tutors. Every pedagogical agent shares the same goal: to increase the student’s skills. Different strategies may be applied to reach this goal. The pedagogical organisation defines the different roles that have to be played in a particular pedagogical context, that is, the sets of pedagogical action to be performed. Figure 6 gives examples of pedagogical actions. Notice that each action can contribute to a different objective. The pedagogical action Suggest informs the user about the next action. It provides goal and pre-conditions on the next action. The pedagogical action Show simulates such action. The pedagogical action Explain provides current action goal. Strategies are defined by roles, corresponding to sub-goals. For example, the goal of a disturbing strategy is to suggest solutions that can be erroneous (Chan & Baskin, 2000). It is a means to force the learner to evaluate his/her self-confidence in his or her own solutions. For example this strategy may consist to modify the orientation

of the wind in order to show up gas propagation. Disturbing the learner is achieved by modifying the behaviour of the agents playing the Source role in this InteractionNet. Using the four models, a pedagogical multiagent system can help students with dedicated tutoring. We proposed an overall process resulting in interactions (data-flows) between the five ITS models (Figure 7). The pedagogical process, which constitutes the resulting behaviour of the MAS, is a five-step cycle. First, a pedagogical agent observes the student’s action using the interface model. The avatar of the student has the knowledge on the current running action. Such observation permits updating the learner model. Second, we compare the expert model to the learner model. That way, we are able to detect an error. For example, if the goal of an exercise is to respect a procedure. The student achieves action A and starts action C. The expert model provides information on the procedure. Therefore we know that after action A the student should start action B. The comparison detects an error corresponding to a layout.

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The error detection uses the error model and updates the learner model. In addition, we can increase the errors model. According to information on the error and using the pedagogical model (strategies), the learner model (level, emotion state ...) and the Context (Figure 7), the pedagogical agent selects a pedagogical action. Finally, the pedagogical action selected is represented to the student using the interface model.

SÉCURÉVI SÉCURÉVI (security and virtual reality) is an application of MASCARET to civil safety (Figure 8). It is dedicated to the training of fire-fighter officers for operational management and for commandment. A complete description of SÉCURÉVI is presented in Querrec, Buche, Maffre and Chevaillier (2003). In a typical exercise, gas lick in an industrial site, the physical environment is constituted of the site where exercises take place as well as physical phenomena (fire, smoked, water jets...) being able to intervene. The application designer’s work in SÉCURÉVI is essentially to implement elements of physical and social environment by inheriting MASCARET. Thus, the application designer has to conceive his or her own agents to simulate a specific phenomenon.

Figure 8. Picture from SécuRéVi

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This is possible by inheriting INAgent as well as its reactive behaviour (inheriting Reactive Behaviour). Then he or she defines the interactions networks (InteractionNet). The application designer of social environment composed of FPT teams (Fire engine Thunders Pumps) in charge of the incident attack or CMIC team (the Intervention Chemical Movable Cell) follows the same path by inheriting model of social environment proposed by MASCARET. Thus, the application designer has to describe new teams and roles as well as actions that agents have to perform. SÉCURÉVI is implemented using the platform AREVI/ORIS (Harrouet, Tisseau, Reignier & Chevaillier, 2002). The domain model consists first of knowledge on FPT and CMIC team structure. Each type of organisation is structured by four or five roles and up to 20 procedures. The learners play roles of leaders intervening in those teams during the incident. Teachers can participate in the simulation to trigger malfunctions, help the learners or play a role in a team. Then we can create two mediation organisations, one for the learner and the other for the teacher. In each one, the user avatar intervenes. In the learner mediation organisation, the role of the learner is to choose the action he or she has to do according to the action done by the

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other team members. The role of the avatar is to realise in the environment the action ordered by the learner and to overcome some of the physical phenomena in the environment. In that way the avatar knows student historic and current action running. Therefore the avatar plays a role in a pedagogical organisation where he or she has the responsibility to maintain the student model. As the avatar is also in charge of detecting a learner’s action, it has the responsibility to manage the interface model. In fact, this agent has information about roles and actions played by the learner. It can, using communicating with the agent maintaining the domain model, have information about all actions done by the learner. Then, according to pedagogical rules, it can choose to propose an interface where the learner has to verbalise the next action or select in a list constructed from the information retrieved by the avatar. But this agent is not the one to manage this interface model; another one can propose information on the environment. For example, the agent could display elements that are not visible in the real world as wind curve or gas cloud, in order to specify to the student specific conditions. The teacher can also intervene in the simulation, by the mean of his or her avatar for example to play a role in the same team of the user. In addition, he or she can participate to a pedagogical organisation where he/she has the responsibility to decide which pedagogical action to do, and another agent, not visible in the environment realises those pedagogical actions. For example the teacher may want to disturb the learner by modifying the environment. Then, if the mission goal is to stop gas propagation, disturbing consists of showing up gas propagation. That means an agent will ask the agent maintaining the domain model the roles that can modify this phenomenon. Then it will ask the agents playing these roles to change their behaviour to increase the wind power or show the wind direction.

CONCLUSION AND FUTURE wORK Considering a virtual environment for training as a multi-agent system, we propose the MASCARET model. It provides a framework to design multi-agent systems dedicated to collaborative, adaptive and realistic environment for training. This VET aims to put trainees in operational position by simulating their physical and social environment in such a way that they can learn to perform some collective tasks. These tasks are described as sets of actions, which define roles, allocated to agents representing human actors. We stated that the system is adaptive in the way that the set of instantiated agents, roles allocation and agent decisional rules are not imposed upon pedagogical designer: all these elements can be dynamically defined in order to adapt pedagogy to learner profiles and pedagogical objectives. Not only has the behaviour of pedagogical agent to be adaptive but the physical environment ones too: it is necessary to remain in control of reactive objects manipulated by learners, or having influence on them, and more precisely of the type of physical phenomena to be activated or inhibited. Physical environment behaviour has to be controlled but must remain consistent in order to be intelligible to learners. We stressed the point that information about potential interactions and action realisation are a major issue in the management of pedagogical knowledge, not only for teachers but also for learners. This knowledge is based on a piece of information about organisations that structure interactions. We have made no assumption about the nature of these interactions and the way agents perform their actions because we think that this issue is still open. We agree that it will be helpful to propose solutions concerning this point to VET designers. It is the major objective of our future works.

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We have shown how to take into account the four classical ITS models (enriched by the error model) in an agent-based VET. A key point is that knowledge about these models is distributed among agents that perceive actively their environment and exchange information, according to the pedagogical role they play. The resulting behaviour of the multi-agent system defines the pedagogical process we propose. Our objective is that MASCARET will be multi-strategic VET, as in Mengelle and Frasson (1996). It will be achieved by the specification of different pedagogical roles. First, we are interested by the tutor role. Using the notion of procedure as described in the social environment, the agents playing this role can provide deductive reasoning and explications. Second, we propose the use of the role of companion (Chan & Baskin, 2000). The companion is a virtual actor that will cooperate for the realisation of tasks, exchange ideas on the problem and share the learner’s goals. We are also interested in the role of troublemaker (Aïmeur et al., 2000), whose goal is to disturb the learner by proposing solutions that can sometimes be erroneous. Finally, we want to provide to our system the possibility to adapt pedagogical behaviour to a specific student. In this option,, the choice of pedagogical actions will be more adaptive. Due to the number of input variable and pedagogical rules, we envisage the use of machine learning techniques as classifier systems (Wilson, 1994).

REFERENCES Aïmeur, E., Frasson, C., & Dufort, H. (2000). Cooperative learning strategies for intelligent tutoring systems. Applied Artificial Intelligence, 14, 465-489. Anderson, J.R. (1988). The expert module. In M.C. Polson & J.J. Richardson (Eds.), Foundations of

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intelligent tutoring systems (pp. 21-53). Hillsdale, NJ: Erlbaum. Anderson, J.R. (1990). Analysis of student performance with the lisp tutor. In A.L.M. S.N. Fredericksen & R. Glaser (Eds.), Diagnostic monitoring of skill and knowledge acquisition (pp. 27-50). Anderson, J.R., & Reiser, B.J. (1985). The lisp tutor. Byte, 10, 159-175. Brown, J.S., & Burton, R.R. (1978). A paradigmatic example of an artificially intelligent instructional system. Int. Journal of Man-Machine Studies, 10, 323-339. Burdea, G., & Coiffet, P. (1993). Virtual Reality Technology. Wiley Interscience. Burkhardt, J.-M. (2003). Réalité virtuelle et ergonomie: Quelques apports réciproques. Le Travail Humain, 66(1), 65-91. Burns, H.L., & Capps, C.G. (1988). Foundations of intelligent tutoring systems: An introduction. In M.C. Polson & J.J. Richardson (Eds.), Foundations of intelligent tutoring systems (pp.1-19). Hillsdale, NJ: Erlbaum. Burton, R. (1982). Diagnosing bugs in a simple procedural skill. Intelligent tutoring systems. In D. Sleeman & J. Brown (Eds.), Intelligent tutoring systems. Burton, R., & Brown, J. (1982). An investigation of computer coaching for informal learning activities. In D. Sleeman & B. Brown (Eds.), Intelligent tutoring systems. Academic Press. Chan, T., & Baskin, A. (2000). Learning compagnion systems. In C. Frasson & G. Gauthier (Eds.), Intelligent tutoring systems: At the crossroad of artificial intelligence and education (pp. 159-167). Bristol. Clancey, W. (1983). Guidon. Journal of ComputerBased Instruction, 10(1), 8-14.

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Clancey, W. (2002). Simulating activities: Relating motives, deliberation and attentive coordination. Cognitive Systems Research, 3(3).

virtual environments. Fifth World Multiconference on Systemics, Cybernetics and Informatics, Orlando, USA.

Delestre, N. (2000). Metadyne, un hypermédia adaptatif dynamique pour l’enseignement. PhD Thesis, University of Rouen.

Mengelle, T., & Frasson, C. (1996). A multi-agent architecture for an ITS with multiple strategies. CALISCE (pp. 96-104).

Demazeau, Y. (1995). From interactions to collective behaviour in agent-based systems. The European Conference on Cognitive Science (pp. 117-132). Saint Malo.

Miller, J.R. (1988). The role of human-computer interaction in intelligent tutoring systems. In M.C. Polson & J.J. Richardson (Eds.), Foundations of intelligent tutoring systems (pp. 143-189). Hillsdale, NJ: Erlbaum.

Fahlman, S. (1979). Netl: A System for Representing and Using Real-World Knowledge. Cambridge, MA: MIT Press. Ferber, J., & Gutknecht, O. (1998). A meta-model for the analysis and design of organizations in multi-agent systems. Third International Conference on Multi-Agent Systems (pp. 91-105). Halff, H.M. (1988). Curriculum and instruction in automated tutors. In M.C. Polson & J.J. Richardson (Eds.), Foundations of intelligent tutoring systems (pp. 79-108). Hillsdale, NJ: Erlbaum. Hannoun, M., Boissier, O., Sichman, J., & Sayettat, C. (1999). MOISE: An organizational model for multi-agent systems. IBERAMIA-SBIA 2000 (pp. 156-165).

Minsky, M. (1975). A framework for representating knowledge. In P.H. Winston (Ed.), The psychology of computer vision (pp. 211-277). NewYork: McGraw-Hill. Nkambou, G., Gauthier, R., & Frasson, C. (1997). Un modèle de représentation des connaissances relatives au contenu dans un système tutoriel intelligent. Sciences et Techniques Educatives, 4(3), 299-330. Piaget, J. (1978). Behavior and Evolution. New York: Pantheon Books. Py, D. (1998). Quelques méthodes d’intelligence artificielle pour la modélisation de l’élève. Sciences et Techniques Educatives, 5(2).

Harrouet, F., Tisseau, J., Reignier, P., & Chevaillier, P. (2002). oRis: Un environnement de simulation interactive multi-agents. Revue des Sciences et Technologie de l’Information, série Technique et Science Informatiques, 21(4), 499-524.

Querrec, R., Buche, C., Maffre, E., & Chevaillier, P. (2003). SécuRéVi: Virtual environments for fire-fighting training. In S. Richir, P. Richard & B. Taravel (Eds.), Fifth Virtual Reality International Conference (pp. 169-175).

Kermarrec, G. (2002). Stratégies d’apprentissage et autorégulation en EPS, une recherché descriptive en contexte scolaire. PhD Thesis, University of Rennes II.

Quillian, M.R. (1968). Semantic memory. In M. Minsky (Ed.), Semantic information processing (pp. 227-270). MIT Press.

Leman, S., Marcenac, P., & Giroux, S. (1996). Un modèle multi-agents de l’apprenant. Sciences et Techniques Educatives, 3(4), 465-483.

Rickel, J., & Johnson, L. (1999). Animated agents for procedural training in virtual reality: Perception, cognition, and motor control. Applied Artificial Intelligence, 13.

Lourdeaux, D., Fuchs, P., & Burkhardt, J.-M. (2001). An intelligent tutorial agent for training

Self, J. (1988). Artificial intelligence tools in education. In P.E. R. Lewis (Ed.) (pp. 73-85). North-

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Holland: Elsevier Science Publishers B.V. Shute, V. (1990). Rose garden promises of intelligent tutoring systems: Blossom or thorn? Space Operations and Research (SOAR) Symposium. Sowa, J.F. (1984). Conceptual Structures: Information Processing in Mind and Machine. Addison-Wesley. Stansfield, J., Carr, B., & Goldstein, I. (1976). Wumpus advisor 1: A first implementation of a program that tutors logical and probabilistic reasoning skills (Tech. Rep.). MIT, Artificial Intelligence Laboratory. Tisseau, J. (2001). Virtual Reality: In virtuo autonomy [Accreditation to Direct Research]. University of Rennes I.

VanLehn, K. (1988). Student modeling. In M.C. Polson & J.J. Richardson (Eds.), Foundations of intelligent tutoring systems (pp. 55-78). Hillsdale, NJ: Erlbaum. Vigano, G., Mottura, S., Calabi, D., & Sacco, M. (2003). The virtual reality design tool: Case studies and interfacing open topics. Virtual Concept 2003 (pp. 364-371). Wenger, E. (1987). Artificial intelligence and tutoring systems. Morgan Kaufmann. Wilson, S.W. (1994). ZCS: A zeroth level classifier system. Evolutionary Computation, 2(1), 1-18. Woolf, B.P. (1992). Building knowledge based tutors. In I. Tomek (Ed.), Fourth International Conference of Computer Assisted Learning (pp. 46-60). Berlin, Heidelberg: Springer.

This work was previously published in the International Journal of Distance Education Technologies, Vol. 2, No. 4, pp. 41-61, copyright 2004 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 2.32

Interactive Multimedia Technologies for Distance Education Systems Hakikur Rahman SDNP, Bangladesh

INFORMATION Information is typically stored, manipulated, delivered and retrieved using a plethora of existing and emerging technologies. Businesses and organizations must adopt these emerging technologies to remain competitive. However, the evolution and progress of the technology (object orientation, high-speed networking, Internet, etc.) has been so rapid that organizations are constantly facing new challenges in end-user training programs. These new technologies are impacting the whole organization, creating a paradigm shift that in turn enables them to do business in ways never possible before (Chatterjee & Jin, 1997). Information systems based on hypertext can be extended to include a wide range of data types, resulting in hypermedia, providing a new approach to information access with data storage devices such as magnetic media, video disk and compact disc (CD). Along with alphanumeric

data, today’s computer systems can handle text, graphics and images, thus bringing audio and video into everyday use. The Distance Education Task Force (DETF) Report (2000) refers that technology can be classified into non-interactive and time-delayed interactive systems, and interactive distance learning systems. Non-interactive and time-delayed interactive systems include printed materials, correspondence, one-way radio and television broadcasting. Different types of telecommunications technology are available for the delivery of educational programs to single and multiple sites throughout disunited areas and locations. However, delivering content via the World Wide Web (WWW) has been tormented by unreliability and inconsistency of information transfer, resulting in unacceptable delays and the inability to effectively deliver complex multimedia elements including audio, video and graphics. A CD/Web hybrid, a Web site on a CD, combining

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Interactive Multimedia Technologies for Distance Education Systems

the strengths of the CD-ROM and the WWW, can facilitate the delivery of multimedia elements by preserving connectivity, even at constricted bandwidth. Compressing a Web site onto a CD-ROM can reduce the amount of time that students spend interacting with a given technology, and can increase the amount of time they spend learning. University teaching and learning experiences are being replicated independently of time and place via appropriate technology-mediated learning processes, like the Internet, the Web, CD-ROM and so forth, to increase the educational gains possible by using the Internet while continuing to optimize the integration of other learning media and resources through interactive multimedia communications. Among other conventional interactive teaching methods, Interactive Multimedia Methods (IMMs) seem to be adopted as another mainstream in the path of the distance learning system.

BACKGROUND F. Hofstetter in his book (Multimedia Instruction Literacy) defined “Multimedia Instruction” as “the use of a computer to present and combine text, graphics, audio and video, with links and tools that let the user navigate, interact, create and communicate.” Interactive Multimedia enables the exchange of ideas and thoughts via most appropriate presentation and transmission media. The goal is to provide an empowering environment where multimedia may be used anytime, anywhere, at moderate cost and in a user-friendly manner. Yet the technologies employed must remain apparently transparent to the end user. Interactive distance learning systems can be termed as “live interactive” or “stored interactive,” and range from satellite and compressed videoconferencing to stand-alone computer-assisted instruction with two or more participants linked together, but

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situated in locations that are separated by time and/or place. Interactive multimedia provides a unique avenue for the communication of engineering concepts. Although most engineering materials today are paper based, more and more educators are examining ways to implement publishergenerated materials or custom, self-developed digital utilities into their curricula (Mohler, 2001). Mohler (2001) also referred that it is vital for engineering educators to continue integrating digital tools into their classrooms, because they provide unique avenues for activating students in learning opportunities and describe engineering content in such a way that is not possible with traditional methods. The recent media of learning constitutes a new form of virtual learning-communication. It very probably demands an interacting subject that is changed in its self-image. The problem of translation causes a shift of meaning for the contents of knowledge. Questions must be asked: Who and what is communicating there? In which way? And about which specific contents of knowledge? The connection between communication and interaction finally raises the philosophical question of the nature of social relationships of Internet communities, especially with reference to user groups of learning technologies in distance education, generally to the medium in its whole range (Cornet, 2001). Many people, including educators and learners, enquire among themselves whether distant learners learn as much as those receiving traditional face-to-face instruction. Research indicates that teaching and studying at a distance can be as effective as traditional instruction when the method and technologies used are appropriate to the instructional tasks with intensive learner-to-learner interactions, instructor-to-learner interactions and instructor-to-instructor interactions (Rahman, 2003a). With the convergence of high-speed computing, broadband networking and integrated

Interactive Multimedia Technologies for Distance Education Systems

telecommunication techniques, this new form of interactive multimedia technology has broadened the horizon of distance education systems through diversified innovative methodologies.

MAIN FOCUS Innovations in the sector of information technology has led educators, scientists, researchers and technocrats to work together for betterment of the communities through effective utilization of available benefits. By far, the learners and educators are among the best beneficiaries at the frontiers of adoptive technologies. Education is no longer a time-bound, schedule-bound or domain-bound learning process. A learner can learn at prolonged pace with enough flexibility in the learning processes, and at the same time, an educator can provide services to the learners through much more flexible media, open to multiple choices. Using diversified media (local-area network, wide-area network, fiber optics backbone, ISDN, T1, radio link and conventional telephone link), education has been able to reach remotely located learners at faster speed and lesser effort. At the very leading edge of the boomlet in mobile wireless data applications are those that involve sending multimedia data—images, and eventually video—over cellular networks (Blackwell, 2004). Technology-integrated learning systems can interact with learners both in the mode similar to the conventional instructors and in new modes of information technology through simulations of logical and physical sequences. With fast networks and multimedia instruction-based workstations in distributed classrooms and distributed laboratories, with support from information dense storage media like write-able discs/CDs, structured interactions with multimedia instruction presentations can be delivered across both time and distance.

Several technologies exist within the realm of distance learning and the WWW that can facilitate self-directed, practice-centered learning and meet the challenges of educational delivery to the learner. Several forms of synchronous (real-time) and asynchronous (delayed-time) technology can provide communication between educator and learner that is stimulating and meets the needs of the learner. The Web is 24 hours a day. Substantial benefits are obtained from using the Web as part of the service strategy (RightNow, 2003). Using the Web format, an essentially infinite number of hyperlinks may be created, enabling content provided by one member to be linked to relevant information provided by another. Any particular subject is treated as a collection of educational objects, like images, theories, problems, online quizzes and case studies. The Web browser interface lets the individual control how content is displayed, such as opening additional windows to other topics for direct comparison and contrast, or changing text size and placement (Tuthill, 1999). Interactive and animated educational software combined with text, images and case simulations relevant to basic and advanced learning can be built to serve the learners’ community. Utilizing client server technology, Ethernet and LAN/WAN networks can easily span around campus areas and regions. Interactive modules can be created using Macromedia Authorware, Flash, Java applets and other available utilities. They can be migrated to html-based programming, permitting platform independence and widespread availability via WWW. A few technology implications are provided in Table 1 that show the transformation of educational paradigms. Macromedia Director can be used to create interactive materials for use on the WWW in addition to basic html editors. Some applications of multimedia technologies are: • •

analog/digital video audio conferencing

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Interactive Multimedia Technologies for Distance Education Systems

Table 1. Transformation of educational paradigms Old Model Classroom lectures

New Model Individual participation

Passive assimilation

Active involvement N

Emphasize on individual learning Teacher at center and at total control Static content Homogeneity in access

Emphasize on group learning Teacher as educator and guide Dynamic content Diversity in access

Technology Implications LAN-connected PCs with access to information ecessitates skill development and simulation knowledge Benefits from learning tools and application software Relies on access to network, servers and utilities Demands networks and publishing tools Involves various IMM tools and techniques

Table 2. Types of interaction methods

• • • • • • • • • • • • •

Interaction methods

Media

Advantage

Disadvantage

Through teachers

E-mail, Usenet, Chat, Conferencing

Quality in teaching

Time consuming

Interactive discussions

Interactive Software

Collaborative learning

E-mail, Usenet, Chat, Conferencing

Conferencing Systems, Video processing techniques Reusability, easier Lengthy High-definition installation development time audio and video broadcasts Inexpensive, easy Less control and Conferencing access supervision systems and discussion tools

authoring software CD-ROMs, drives collaborative utility software digital signal processors hypermedia laserdiscs e-books speech processors, synthesizers animation video conferencing virtual reality video capture video cams

Introducing highly interactive multimedia technology as part of the learning curriculum can offer the best possibilities of development for the future of distance learning. The system should include a conferencing system, a dynamic Web

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Further development

site carrying useful information to use within the course, and access to discussion tools. Workstations are the primary delivery system, but the interaction process can be implemented through various methods as described in Table 2. Furthermore, course materials used in interactive learning techniques may involve some flexible methods (with little or no interactions) as presented in Table 3. Miller (1998) and Koyabe (1999) put emphasis on the increased use of multicasting in interactive learning and extensive usage of computers and network equipment in multicasting (routers, switches and high-end LAN equipment). The shaded cell in Table 4 represents real-time multicast applications supported by Real-Time Transport Protocol (RTTP), Real-Time Control Protocol (RTCP) or Real-Time Streaming Protocol (RTSP), while the un-shaded cells show multicast data applications

Interactive Multimedia Technologies for Distance Education Systems

Table 3. Delivery methods in interactive learning Methods

Media

Point to point

Controlling agents Educator or learner

Point to multi-point

Teacher or guide

Multi-point to multipoint

Teacher of guide

Streaming, audio, text and video

Student or learner

Desktop PC, conferencing system Conferencing system, Desktop PC, LAN/WAN Internet or intranet

Desktop PC

Advantage/ Disadvantage Better interaction, one-to-one communication /Very expensive Flexible/Little interaction

Further development To make it an acceptable solution in a big university or in a developing country situation Improved interaction

More flexible/ Little or no interaction

Improved technology

Time and place independent/No Interaction (except simulated techniques)

Improved material presentation

Table 4. Different multicast applications Topology Multimedia

Real-time Video server, Video conferencing, Internet audio, Multimedia events, Web casting (live)

Data Only

Stock quotes, News feeds, Whiteboards, Interactive gaming

supported by reliable (data) multicast protocols. Finally, underneath these applications, above the infrastructure, asynchronous transfer mode (ATM) seems to be the most promising emerging technology enabling the development of integrated, interactive multimedia environment for distance education services appropriate for the developing country context. ATM offers economical broadband networking, combining high-quality, real-time video streams with high-speed data packets, even at constricted bandwidth. It also provides flexibility in bandwidth management within the communication protocol, stability in the content, by minimizing data noise, unwanted filter and cheaper delivery by reducing costs of networking.

Non Real-Time Replication (Video/Web servers, kiosks), Content delivery (intranets and Internet), Streaming, Web casting (stored) Data delivery (peer/peer, sender/client), Database replication, Software distribution, Dynamic caching

FUTURE TRENDS New technologies have established esteemed standing in education and training despite various shortcomings in their performances. Technological innovations have been applied to improve the quality of education for many years. There are instances where applications of the technology had the potential to completely revolutionize the educational systems. Reformed usage of devices like radio, television and video recorders are among many as the starter. Interconnected computers with Internet are the non-concatenated connection between the traditional and innovative techniques. The recent addition of gadgets like personal digital assistants (PDAs), and software

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like virtual libraries could be some ways out to advanced researchers among many innovative methods on interactive learning. When prospects of future usage of new technologies emerge in educational settings, there seems to be an innate acknowledgment that positive outcomes will be achieved and these outcomes will justify the expenses. When research is conducted to verify these assumptions, the actual outcomes may sometime be less than those expected. The research methodology behind interactive learning should be based on the notion that the interactivity be provided in the learning context to create environments where information can be shared, critically analyzed and applied, and along the process it becomes knowledge in the mind of the learner. The use of interactive television as a medium for multimedia-based learning is an application of the technology that needs further investigation by the researchers. Research needs to study the impact of the interactions on the quality of the instructional delivery and develop guidelines for educators and instructional designers to maximize the advantage obtained from this mode of learning in broadcast, narrowcast and multicast modes. Another emergent technology that appears to hold considerable promise for networked learning is the data broadcasting system (DBS). This technology provides the facility to insert a data stream into a broadcast television signal. Research needs to investigate the utility and efficacy of this technology for use in interactive learning sequences. Current IMM context has found concrete ground and high potential in distance education methodologies. Further research needs to be carried out towards the cost-effective implementation of this technology. Emphasis should be given to study applications of the technology being used as a vehicle for the delivery of information and instruction and identifying existing problems. Research also needs to focus on developing ap-

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plications that should make full use of the potentiality offered by this technology. While security has been extensively addressed in the context of wired networks, the deployment of high-speed wireless data and multimedia communications ushers in new and greater challenges (Bhatkar, 2003). Broadband has emerged as the third wave of technology, offering high bandwidth connectivity across wide-area networks, opening enormous opportunities for information retrieval and interactive learning systems (Rahman, 2003b). However, until the browser software includes built-in support for various audio and video compression schemes, it needs cautious approach from the instructional designer to select the plug-in software that supports multiple platforms and various file formats. Using multimedia files that require proprietary plug-ins usually force the user to install numerous pieces of software in order to access multimedia elements. It is pertinent that all the newly evolved technologies now exist that are necessary to cost effectively support the revolution in an IMM-based learning system so sorely needed by the developing world. Researchers should take the opportunity to initiate a revolution over the coming years. The main challenges lie in linking and coordinating the “bottom-up” piloting of concepts (at the design stage) with the “top-down” policy-making (at the implementation stage) and budgeting processes from the local (in modular format) to the global level (in repository concept).

CONCLUSION Regardless of geographical locations, the future learning system cannot be dissociated with information and communication technologies. As technology becomes more and more ubiquitous and affordable, virtual learning carries the greatest potential to educate masses in the rural communities in anything and everything. This

Interactive Multimedia Technologies for Distance Education Systems

system of learning can and will revolutionize the education system at the global context, especially in the developing world. The whole issue of the use of IMM in the learning process is the subject of considerable debate in academic arena. While many educators are embracing applications of multimedia technologies and computer-managed learning, they are advised to be cautious in their expectations and anticipations by their contemporary colleagues. Research in this aspect clearly indicate that media themselves do not influence learning, but it is the instructional design accompanying the media that influences the quality of learning. The success of the technology in these areas is acknowledged, as is the current move within world-famous universities to embrace a number of the instructional methodologies into their oncampus education system. Much expectation is there for those educators concerned, as well as those wary of assuming that gains will be achieved from these methods and technologies. However, there is a need for appropriate research to support and guide the forms of divergence that have taken place during the last decade in the field of distance education. One of the long-standing problems in delivering educational content via WWW has been the unpredictability and inconsistency of information transfer via Internet connections. Whether connection to the WWW is established over conventional telephone lines or high-speed LANs/WANs, often, communication is delayed or terminated because of bottlenecks at the server level, congestion in the line of transmission and many unexpected hangouts. Furthermore, the current state of technology does not allow for the optimal delivery of multimedia elements, including audio, video and animation at expected rate. Larger multimedia files require longer download times, which means that students have to wait for a much longer time to deal with these files. Even simple graphics may cause unacceptable delays in congested bandwidth. A CD/Web hybrid, a Web

site on a CD, can serve as an acceptable solution in these situations.

REFERENCES Bhatkar, A. (2003). Transmission and Computational Energy Modeling for Wireless Video Streaming, 21. Blackwell, G. (2004). Taking advantage of wireless multimedia technology. January 27. Chatterjee, S., & Jin, L. (1997). Broadband residential multimedia systems as a training and learning tool. Atlanta: Georgia State University. Cornet, E. (2001, April 1-5). The future of learning—Learning for the future: Shaping the transition. The 20th World Conference on Open Learning and Distance Education, Düsseldorf. Distance Education Task Force. (2000). Distance Education Task Force Report. University of Florida. Koyabe, M.W. (1999). Large-scale multicast Internet success via satellite: Benefits and challenges in developing countries. Aberdeen, UK: King’s College. Miller, K. (1998). Multicasting networking and applications. Addison-Wesley. Mohler, J.L. (2001). Using interactive multimedia technologies to improve student understanding of spatially-dependent engineering concepts. GraphiCon 2001. Rahman, H, (2003a). Framework of a technology based distance education university in Bangladesh. Proceedings of the International Workshop on Distributed Internet Infrastructure for Education and Research (IWIER2003), Dhaka, Bangladesh, December 30, 2003-January 2, 2004.

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Rahman, H. (2003b). Distributed learning sequences for the future generation. Proceedings of the Closing Gaps in the Digital Divide: Regional Conference on Digital GMS, Asian Institute of Technology, Bangkok, Thailand, February 2628. RightNow Technologies Inc. (2003). Best practices for the Web-enabled contact center, 1. Tuthill, J. M. (1999). Creation of a network based, interactive multimedia computer assisted instruction program for medical student education with migration from a proprietary Apple Macintosh platform to the World Wide Web. University of Vermont College of Medicine.

KEY TERMS Hypermedia: Hypermedia is a computerbased information retrieval system that enables a user to gain or provide access to texts, audio and video recordings, photographs and computer graphics related to a particular subject. Integrated Services Digital Network (ISDN): ISDN is a set of CCITT/ITU (Comité Consultatif International Téléphonique et Télégraphique/International Telecommunications Union) standards for digital transmission over ordinary telephone copper wire as well as over other media. ISDN in concept is the integration of both analog or voice data together with digital data over the same network. Interactive Learning: Interactive learning is defined as the process of exchanging and sharing of knowledge resources conducive to innovation between an innovator, its suppliers and/or its

clients. It may start with a resource-based argument, specified by introducing competing and complementary theoretical arguments, such as the complexity and structuring of innovative activities and cross-sectoral technological dynamics. Interactive Multimedia Method (IMM): It is a multimedia system in which related items of information are connected and can be presented together. This system combines different media for its communication purposes, such as text, graphics, sound and so forth. Multicast: Multicast is communication between a single sender and multiple receivers on a network. Typical uses include the updating of mobile personnel from a home office and the periodic issuance of online newsletters. Together with anycast and unicast, multicast is one of the packet types in the Internet Protocol Version 6 (IPv6). Multimedia/Multimedia Technology: Multimedia is more than one concurrent presentation medium (for example, CD-ROM or a Web site). Although still images are a different medium than text, multimedia is typically used to mean the combination of text, sound and/or motion video. T1: The T1 (or T-1) carrier is the most commonly used digital line in the United States, Canada and Japan. In these countries, it carries 24 pulse code modulation (PCM) signals using time-division multiplexing (TDM) at an overall rate of 1.544 million bits per second (Mbps). In the T-1 system, voice signals are sampled 8,000 times a second and each sample is digitized into an 8-bit word.

This work was previously published in Encyclopedia of Multimedia Technology and Networking, edited by M. Pagani, pp. 454-460, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.33

Qualitative Standards for E-Learning:

The Demand-Driven Learning Model Krista Breithaupt American Institute for CPAs, USA Colla J. MacDonald University of Ottawa, Canada

ABSTRACT

INTRODUCTION

This study compliments the theoretical work that led to the development of a new e-learning model, termed the demand-driven learning model (DDLM), and describes the development of a survey that can be used to determine the quality of e-learning programs. Scores from the survey are intended to provide a useful indication of the extent to which e-learning programs provide evidence of quality defined by the DDLM. In this way, the DDLM represents a proposed standard for the quality of online learning. The authors also provide a description of the development and pilot study of the survey measure, and propose this survey as a means of assessing the quality of e-learning programs against this standard.

The tension between improving employee skills and meeting the daily demands in the organization has led employers in many industries to endorse, fund, and even design and deliver alternative education and training programs. Internet, online or e-learning, is becoming a popular way to address this issue whereby staff can pursue higher credentials without interrupting their service to employers. However, a close examination of new e-learning programs has indicated a critical gap between the use of technology and sound pedagogical models (Khan, 1997; Salmon, 2000; Willis, 2000). Several researchers have written about the need for quality standards to ensure the

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Qualitative Standards for E-Learning

integrity of e-learning programs (Benson, 2003; Carstens & Worsfold, 2000; DeBard & Guidera, 2000; Salmon & Speck, 2000). This study complements the theoretical work that led to the development of a new e-learning model, termed the Demand-Driven Learning Model (DDLM), and describes the development of a survey that can be used to determine the quality of e-learning programs. Scores from the survey are intended to provide a useful indication of the extent to which e-learning programs provide evidence of quality defined by the DDLM. In this way, the DDLM represents a proposed standard for the quality of online learning. The authors also provide a conceptually sound tool (survey measure) that may be used to assess the quality of any application of e-learning against this standard. Specifically, research represented here describes the pilot study of the DDLM and survey tool used to assess three e-learning programs, and poses three research questions: 1. 2.

3.

Is there evidence of score validity and reliability? Is the expected relationship between constructs in the DDLM present in pilot study response data? How do the online programs in the pilot study compare based on the DDLM?

The development process that resulted in the DDLM required collaboration between academics and experts from commercial, private, and public industries. An early draft describing the DDLM was presented to a panel of industry experts. Present at this meeting were representatives from highly respected national and international commercial organizations influential in online technology and education, including Nortel Networks, Alcatel, Lucent Technologies, Cisco Systems, Arthur D. Little Business School, Learnsoft Corporation, and KGMP Consulting Services. These representatives reacted with enthusiasm and interest in the DDLM, and also

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provided recommendations for future refinement and utility. Specifically, the authors identified a need to reflect in the DDLM practical and logistic features required for success in e-learning. These elements were identified during the process of planning the pilot study, and continually defining and refining the DDLM survey through ongoing consultations with industry representatives over a two-year period. After a brief introduction to the DDLM and the e-learning context, a short description of the initial development of the online survey is provided, followed by the results from the authors’ pilot study with three e-learning programs. These results furnish some initial evidence for the validity of the DDLM and the utility of the DDLM online survey used to examine program quality. The model and survey are intended to support a confident evaluation of a wide range of e-learning programs.

DDLM The DDLM is grounded within a constructivist framework and defined by five main components: the quality standard of superior structure; three consumer demands of content, delivery, and service; and learner outcomes. Further, it is framed within frequent opportunities for ongoing adaptation, improvement, and evaluation. Superior structure can be viewed as a standard of high quality attained only by e-learning programs that meet specific requirements. The elements of superior structure are required for excellence in content, delivery, and service. As a result, learner outcomes will be optimized (MacDonald, Stodel, Farres, Breithaupt, & Gabriel, 2001). The DDLM has the following distinguishing features that make it an appropriate quality standard for adult e-learning. The DDLM:

•

emerged out of a concern for the lack of standards and validated models for e-learning, specifically e-learning for adults;

Qualitative Standards for E-Learning

•

•

•

•

was built specifically to address the needs and concerns of adult learners and educators in this climate of rapid technological advancement; was created with a specific purpose: to support and guide e-learning designers, developers, evaluators, and facilitators, and ensure the most significant challenges of e-learning are anticipated and met in practice; was developed through a collaborative process between academics and industry experts to ensure the model was relevant and practical for learners, secondary beneficiaries (employers), and educators (including program designers, developers, and evaluators); and includes an “outcomes” component to ensure a comprehensive evaluation of e-learning.

The dynamic relationship between DDLM constructs may be presented graphically (see Figure 1). The five central constructs in the DDLM are superior structure, content, delivery, service, and outcomes. These are organized in the graphic to emphasize the interplay between outcomes, content, delivery, and service as indicators of the

more global quality standard, superior structure. Two unifying themes are represented as text on the left and right sides of the graphic to indicate the importance of ongoing monitoring and adaptation in establishing and measuring quality. Utility of the model was a key principle in conceptulatization of the DDLM, and in the identification of a means of evaluating e-learning programs against the DDLM standard. To ensure utility, it was considered essential that any measure of DDLM features must be easily applicable in a variety of e-learning programs. An online survey was developed to operationalize each construct to define the DDLM, because this mode of assessment fit well within the context of distance learning programs. The development of the survey and the pilot study in three e-learning programs is discussed in the final section of this chapter. A detailed research report is available in MacDonald, Breithaupt, Stodel, Farres, and Gabriel (2002).

Context of E-Learning The rapid development of the Internet from a text-only medium to an expanding multimedia

Figure 1. Demand-driven learning model (DDLM) n

io at

u al

m

O

ng

oi

ng

a gr

Ev

ro

P

Content Authentic, industry driven, comprehensive

Co Outcomes Lower cost, convenience, aquired knowledge Delivery Usability, tools, inter-activity

nt

in

ua

lA

da

pt

at

io

n

an

d Im Service pr ov Resources, em accessible, admin en t & technical support

Superior Structure Learner needs, motivation, evaluation, convenience Program environment, goals, pedagogical strategy

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communication system has increased and diversified delivery mechanisms of quality education. These developments are challenging common conceptions of the teaching-learning process (Bonk & Cummings, 1998). Accompanying this increased use of technology is an increase in the expectations of all stakeholders (Baker & O’Neil, 1994). As a result, quality assurance, defensibility, and accountability in e-learning programs have become critical. Consumers and educators demand that e-learning programs be evaluated to determine and guarantee effectiveness and high quality. Educators and researchers have voiced concern over the lack of appropriately rigorous evaluation studies of e-learning programs (e.g., Cheung, 1998; Lockyer, Patterson, & Harper, 1999; Reeves & Reeves, 1997). The dearth of e-learning evaluation efforts may be in part a result of competing priorities. Funding into the development and deployment of novel programs may be emphasized, while resources are not tagged to support expertise for evaluation (Wills & Alexander, 2000). In addition, evaluation methods used in more conventional programs may not be appropriate for e-learning courses and programs. New methodologies need to be devised (Zuniga & Pease, 1998). Some researchers have made steps towards developing evaluation instruments to assess elearning programs (e.g., Biner, 1993; Cheung, 1998; Stanford, 1997). Such instruments are most often developed to assess only specific program content and are not suitable for wider application. Perhaps this lack of generic utility is the reason these measures are usually not subjected to rigorous psychometric study. There appears to be a need in many fields of education for validated online measures with desirable psychometric properties. Any study of the validity of a generic measure of the quality of e-learning must be referenced to an underlying theoretical framework. To this end, the DDLM was used as the basis for an evaluation measure that could be administered

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online to examine the effectiveness of e-learning programs from any discipline. The authors intend this measure to be applied easily for immediate feedback to program providers. This will permit rapid identification of strengths and weaknesses of various programs, and afford timely intervention and resource allocation. The purpose of sharing this work is to place this measure and the development effort under the scrutiny of educators and program researchers who might benefit from its use.

Online DDLM Survey Tool While culling survey questions from a wide variety of sources, the authors sought to include only questions that are relevant, clear, and that elicit the expected information reflecting DDLM constructs. The survey must be as brief as possible, retaining a sufficient number of questions to gain a confident estimate of the underlying construct of interest. Close to two-thirds of the initial questions were dropped based on the authors’ analysis of the pilot survey. Once the short survey was constructed, tests of the hypothesized model and the relationship between included constructs were possible. This step of psychometric evaluation of any new survey usually requires extensive pilot testing. To date, attempts to develop online measures have had only limited success and sometimes lack scientific rigor. The questions were targeted to elicit the learner’s appraisal of the efficiency and ease of participating in the program, and the quality and relevance of curriculum content. Questions in the content, delivery, and structure sections were accompanied by five response options: never, rarely, sometimes, often, and always. Questions in the outcomes area were presented with four response options: strongly disagree, disagree, agree, and strongly agree. Higher scores were associated with positive responses (e.g., always = 5, strongly agree = 4). The original pilot instrument (long

Qualitative Standards for E-Learning

survey) is available from the authors. The short survey is appended here (Appendix). The survey is used to generate five scores based on the DDLM for content, delivery, service, outcomes, and superior structure. Based on the hypothesized relationships between these constructs, the superior structure scale acts as a holistic measure of desirable e-learning program features or as a high-quality standard. By contrast, the content, delivery, service, and learner outcomes can be viewed as indicators that have a logical predictive relationship to this goal. The development work and pilot study of the DDLM survey provide appropriate initial evidence that the scores and interpretations of these scores are linked to a conceptually meaningful pedagogical framework. Practitioners may be confident in using the survey that it is explicitly based on a sound theoretical framework, and that there is evidence of score validity and reliability. Ideally, the survey could be used to evaluate any

distance education program, and as the application is extended, our understanding of score properties will be improved. The DDLM is not limited to any content area, and may be used to evaluate e-learning courses and programs in any discipline.

Pilot Evaluation of Three Operational E-Learning Programs The characteristics of participants involved in the pilot study are described in Table 1. Participants were considered eligible for the study if they were enrolled in online programs in which the program executives shared the authors’ goal of gaining a better understanding of the features that make learning effective, relevant, and accessible. Participants were adult learners who were engaged in e-learning programs during the 2000-2001 academic school year. A total of 46% of learners in these programs completed the survey.

Table 1. Pilot study sample demographic profile Program 1 N

Program 2 N

Program 3 N

Total N (%)a

7 3

14 14

33 20

54 (58) 37 (40)

5 5 2

13 15 -

21 32 -

39 (42) 52 (56) 2 (2)

10 2

1 27 -

2 51 -

3 (3) 88 (95) 2 (2)

Marital Status Single Single parent Married with children Married no children

1 1 6 2

2 2 16 8

10 1 30 12

13 (14) 4 (4) 52 (56) 22 (24)

Total Participants 1

2

28 5

3

93

Demographic Gender Male Female Education University College High school Age . The adoption of alt tags may be a quick solution for the use of decorative graphics or graphics that emphasize a point. Some experts also suggest that

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if an image is not relevant to someone receiving the information auditorily, a null alt tag should be provided to tell the user that this image is not relevant to the content. An example of this would be a separator line. In this case the code might read as: . One important use of alt tags is to describe a link embedded within an image. For example, if a house is used at the bottom of the page to indicate a link to the homepage, the alt tag should indicate the purpose of the image. Just writing something such as “link” or “click here” is not descriptive enough. The reader may not know the path for this link. A more descriptive tag would say ”link to homepage.” When an image is too complex to be described by an alt tag, it is recommended that a “longdesc” attribute also be attached to the html code. For example, in an assistive technology course in which the photograph of a bowl on top of a shelf-lining square is used to convey the message that low cost and low tech solutions—such as a shelf-lining sheet as opposed to specialized materials such as dycem — may be available to enhance stability for persons with motor impairments. In this case, a tag that just says “bowl and shelf lining” may make not make enough sense to the student. Unless a text description of the image is provided below it, it is important to add a “longdesc” attribute. The html code might read: . The shelf-lining page could then be opened by the user for a more detailed description of the image. This same procedure can be used to further describe charts, graphs, photographs of people and places, etc. An important alert to Web designers, however, is that, at this point, the longdesc attribute is not fully supported by all types of assistive technology, so an additional convention is needed to ensure access; it is referred to as the “D-link.” In simple terms, when activated, the D-link directs the user to the page containing the detailed information.

Universal Design for Online Education

In the example above, an the designer would add to the code already containing the alt tag and the longdesc attribute: D. Next to the picture of the bowl, an underlined capital D would appear, indicating a link to the page with additional descriptive information, which the student could choose to read or ignore. Size and resolution are also an important issues when planning to include images in the Web site. Because the disk space required by graphic images often slows the process of downloading Web pages, images should not be very large in size. A student with low vision might have difficulty with small images, which could become distorted when going through screen magnification, especially if resolution of the original image is low. If a given image is considered crucial to the comprehension of specific content, the instructor may consider linking the smaller image to a page where a bigger version of it can be seen.

Colored Text Like images, color can enhance the aesthetic of a Web site. If used correctly, it will pose no problems to persons with disabilities. If used in excess, it may be distracting. If used as the only means of conveying information, it can be a big obstacle to navigation. We often rely on color to indicate links, highlight information, or to organize content into categories. A student who is color blind may not see the red color indicating a link to another page, for example. A simple question to be posed while planning the structure for content display would be “If I could only see a black and white version of this page, could I still understand all the information and navigate all the controls?” It is not a crime to use color, as long as it is not the only way to communicate. There are other ways to emphasize certain points, such as making text bold. Text links could be underlined. Preferably, however, if a number of text links are to be included in a page, a better solution might

be to repeat the information at the bottom of the page, under a title such as “Links to Additional Information.”

Link Aside from what has already been said about using images and color to indicate links, there are other conventions that facilitate usability and accessibility. For example, providing the user with the possibility to skip navigational links is very useful to persons utilizing a screen reader. As previously mentioned, it may be very timeconsuming for a blind person to navigate a page that includes menus with links at the top. While a sighted person can focus directly on the main content of a page, a person using a screen reader will have to listen to all the items on the menu before being able to go to other sections of the page. Although this may facilitate orientation the first time someone accesses a given site, it becomes a waste of time on repeated visits. A solution to this problem is the use of an anchor (also known as “bookmark” in FrontPage®) that allows the user to skip navigational links and go directly to the main content of the page. This anchor can be displayed on the very top of the page (with the target immediately before the main content section) or can be hidden from sighted users by a picture or background colors containing html code that the screen reader identifies as the anchor command.

Tables It is not advisable to use tables (i.e., lay-out tables) simply to format information that does not need to be read as a table. When thinking about using a table, faculty should ask how the information would read after being “linearized” (read from top to bottom, left to right). When tables are necessary (i.e., data tables), certain conventions should be followed to make sure that the person relying on auditory output can integrate the infor-

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mation displayed on each row and column. The most important features are the header element and the scope attribute, which indicate to the reader which cells are intended as headings and which ones are row or column headers. For more complex tables, where information is not aligned simply at the intersection of one main column header and row header, the header attribute should also be considered. Two other attributes that can greatly enhance understanding of tables are the caption and the summary attributes. As the term indicates, a caption attribute briefly describes the contents of the table. For example, the caption of a table might read “Increase in the Older Population in the United States by Cohort in the Twentieth Century.” Similarly, the summary attribute would provide an idea of the purpose and organization of the table contents. Such a summary might say “This is a three columns and three rows table, depicting the numbers of older adults in the United States, ages 65 to 74, 75 to 84, and 85 plus, in 1900, 1950, and 1999.” Because specific coded examples of these features would take more space than what is available for this chapter, readers interested in specific html coding for these attributes can refer to the books on Web accessibility listed under Resources or visit Web sites from organizations such as the W3C (www. w3c.org) or WebAIM (www.webain.org).

Frames As previously mentioned, frames are not always interpreted correctly by software packages used by students with disabilities. The same may be true for a student using a text only browser. Most experts suggest that designers find alternatives to the frame layout; if this is not feasible, the noframes attribute should be added to the html code so that the user can access the same information in an alternate format. A caution often associated with advice about the noframes attribute is to ensure that the content in alternative noframes pages and the content of the regular pages are updated

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simultaneously to avoid discrepancies in information. Frames should be given titles that help the user understand their purpose and decide whether or not to read its contents.

Forms When interactive forms are used, it is important to make sure that the user is able to control input even if not using a regular mouse to point and click. If a file cannot be accessed by the arrow keys, some students with physical limitations may not be able to enter the required information. Forms are also tricky for individuals using screen readers, particularly if they use a variety of elements such as radio buttons, pull-down menus, and cells for entering text information. Often these elements are images, and some readers may have a difficult time identifying them if a text descriptor is not used to define the expected commands for data entry and submission. Labeling the input type as text, checkboxes, or buttons, identifying text areas for data entry, or indicating which options are available to be checked can make desired actions much easier for a screen reader user to grasp. Like tables, forms can be a complex component for faculty not experienced in writing programming code, so it is recommended that resources providing step-by-step design instructions and examples be consulted prior to engaging in this task.

Multimedia Academic sites are increasingly making use of features such as animation and video and audio recordings to appeal to different learning preferences. It would be contrary to good pedagogical practices to ask faculty to ignore the benefits of such features. A student who learns more effectively through auditory channels may find a course much more enjoyable if sound is used to enhance learning. The reverse may apply to a student who prefers visual input. When additional sensory input is incorporated into a Web site, instructors

Universal Design for Online Education

need to make sure equivalent alternatives are given to students with sensory limitations. A common problem to avoid is the use of animations or elements that blink or flicker merely to produce a visual effect. These should be avoided if possible, particularly if elements flicker at a rate of 2 to 55 cycles per second, which can induce seizures. When necessary to convey a message, animations should also have descriptive information associated with them. Let us consider the example of narrated PowerPoint presentations. A deaf student may miss important information if the slides have only brief outlines of what the professor says while narrating each slide in greater detail. The same is true for video or audio recordings inserted into the Web site. To accommodate students with hearing impairments, two options are available: captioning and transcriptions. Before uploading the video recording, faculty may ask technical support staff for help with captioning. By doing this, students may read the text while watching the video. A concern, aside from the time need to captioned videos, is the fact that videos opened through programs such as Quicktime or Real Player often open as much smaller images than what would be seen if shown on a television monitor. A simpler solution may be to provide a text transcript of the auditory content. Transcripts are not only beneficial to persons who cannot hear, but also to those who do not possess the plugs-ins needed to access media or to those who simply want a faster way to look at the information. Screen reader users, for example, may prefer to open a transcript of an interview, knowing that their software will read the contents much faster than the time it would take for them to listen to the original recording. For persons with visual impairments, video recording may also be problematic because of the visual cues that are missed when only the auditory contents can be accessed. In this case, a transcript may not be sufficient. Audio descriptions are recommended for videos that contain a

large amount of information delivered only in a visual format. For example, if the video is used to demonstrate a technique that is not described verbally by the narrator, it may be necessary to add an audio description. If this seems too time-consuming and hard to combine with the existing sound version of the video, it may be better to provide such description within the text transcript provided. These alternate versions should be provided as optional links so as not to clutter any given page. Faculty members should not perceive these accommodations as a burden, but as ways to cater to individuals with various learning styles and technology resources. By having to provide these alternatives, faculty are led to examine more carefully what types of multimedia are truly effective and meaningful to their courses. These accommodations are no different from what is already required for face-to-face courses. Although a bit more time-consuming to tackle once a course is already being taught, they can be easily accomplished when planned from the very beginning and implemented gradually. Another potential problem with multimedia is the need for plug-ins or specific software to open files. It is recommended that faculty assume that not all students will have the necessary technology to open such files. A good practice is to tell students in the beginning of the semester what types of programs they need to download to be able to access all course information. Accessibility guidelines also recommend that links should be provided to a disability-accessible page from which the programs and plug-ins can be downloaded.

Does Using Courseware to Build Online Courses Already Provide for Accessibility? There are many examples of educational courseware packages in the market. Academic institutions typically adopt a commercial courseware

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package or develop one in-house. Courseware packages organize information in sections, so it is easier for instructors to upload their own documents and to interact with students. Some of the leading companies, such as Blackboard and WebCT, have made a concerted effort to comply with accessibility guidelines. On its Web site, Blackboard explains how its Web designers have implemented Section 508 (see http://products. blackboard.com/cp/bb5/access/section508.cgi). For example, they have added row and column headers to tables within its platform. Because they have added a description field, complex images or media can receive a more detailed description when uploaded onto the platform. WebCT has also done considerable work on the first priority level of WAI guidelines. They have also created help files on accessibility for their online help (Harrison, 2000). However, there are still issues to be resolved before these platforms will be in total compliance. For example, Blackboard alerts users that the chat tool in Version five is not yet in compliance. Although students can go back to read the archives of any given chat, they may not be able to participate in one with other students if they are using a screen reader. These advances are exciting and show commitment from some of the courseware companies in developing truly useable products. But even if these companies fully comply with all accessibility guidelines, there are issues that are beyond their control. For example, although they can make sure their courseware pages are in compliance, they cannot automatically transform a page added by the instructor to the “documents” or “links” sections of the courseware package. If an instructor creates word documents with pictures or tables, he or she should not assume that the platform has the power to add markups to the html code to provide for accessibility. The html code from the original document will transfer onto the platform. It would be unreasonable to expect that the courseware developers would add mechanisms for the product to “guess” what the

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instructor wishes to say with a given picture, math equation, music notation, or video clip. It is very important, therefore, for instructors to check the pages they develop before uploading them. If Web -authoring software such as FrontPage® or Dreamweaver® are used, it is possible to go into the html code to include alt tags or other accessibility markups. Increasingly, Web -authoring software includes features that check accessibility. The following statement was taken from the University of Iowa site, referring to Dreamweaver’s® accessibility extension: This new Dreamweaver evaluation tool allows Web pages to be “accessibility-checked” much in the same way as you “spell-check” a Word document. The extension covers Section 508 and level 1 W3C guidelines and a report can be run on one page, a complete Web site, selected section or any folder. The user can select sub-groups of the guidelines to customize tests to run on different Web pages. The extension allows the user to collect answers to manual tests and includes content that explains how to perform tests, why the problems found could be accessibility issues and explains with examples how the problem can be fixed. In addition to the free extension, the user can link through to LIFT Online a service from UsableNet that allows tests to be automatically scheduled on live public Web sites (University of Iowa, 2002, p. 4). This extension can be downloaded from the Macromedia site by down clicking on “accessibility” and then on “508 Accessibility Suite” (http://dynamic.macromedia.com/bin/MM/exchange/main.jsp?product=dreamweaver) Similarly, FrontPage® can be checked for accessibility through a new tool called AccVerify® SE™. Microsoft and HiSoftware have partnered to develop this tool. According to HiSoftware (2002), this tool provides verification and reports all errors /non-compliance with accessibility policy and standards for Web sites under the WCAG 1.0 P1-P3 Guidelines and the Section 508 standards.” This software also provides a complete checklist

Universal Design for Online Education

for standards that the Web site designer has to verify manually in order to achieve complete accessibility. This checklist is available on the HiSoftware’s Web site (http://www.hisoftware. com/msacc/). One of the advantages of using authoring software such as FrontPage® is the existence of built-in features that facilitate compliance with accessibility guidelines. For instance, it is possible to import a file into FrontPage® and manually insert alt tags without having to go into the html code. By right clicking on an image and going to “image properties,” it is possible to fill in the blank tag for text under alternative representations. By doing so a brief description of the image is created and added to the html code as an alt tag. Those using a screen reader can read the description, but sighted viewers can also see it when the mouse is on the image. Similarly, a PowerPoint presentation may be edited to include alternative descriptors. However, according to WebAIM (2002b), the html code generated is not accessible to screen readers. Saving the file as a Web page does not assure accessibility either. Some Web technicians suggest that the outline version be used as a solution; however, the outline does not include features such as textbox, graphs, pictures, or multimedia. If used in the presentation, instructors still need to describe them along with the rest of the text. A new plug-in is being tested at this time and can be downloaded from the Division of Rehabilitation, Education Services of the University of Illinois at Urbana/Champaign. According to its Web site: This PowerPoint Accessibility Wizard offers an alternative to PowerPoint’s Web Publishing feature. The standard Power Point Web Publishing option creates XML-based Web content that can only be used by Microsoft Internet Explorer. Even if non-XML options are selected, users cannot easily add information that is required for accessibility. This PowerPoint Accessibility Wizard simplifies the task of converting PowerPoint presentations to text pure html through an

easy-to-use user interface, and automates much of the conversion of PowerPoint Presentations to an html format that includes required accessibility information (Division of Rehabilitation, UI, 2002, p. 1).

Accessibility of Other Components of Online Courses Online courses do not solely rely on Web pages. They use other channels for conveying information and for faculty-student interactions. One of the most frequent modes of interaction is email. It is a fairly expedient way for faculty to communicate with each student individually and answer questions. One of the greatest advantages of e-mail is that a student can pose a question at any time, which the instructor can also read and answer a convenient time. E-mail is often quite accessible to all students. One word of caution concerns checking for errors in spelling when we reply to questions or send out announcements. A screen reader reads words as they are spelled. If a letter is missing or an acronym is being used, the output may not make much sense to the student. A similar caution applies to listservs. Another interactive technique gaining more popularity among online instructors is that of synchronized chat sessions. Before requiring them, instructors should be sure that their students can access the technology. This is especially true for text chats that do not use html-coded text. Norman Coombs from Equal Access to Software and Information (EASI), a provider of online training on accessible information technology for persons with disabilities, makes the following remarks regarding text chats: In the old DOS days they worked rather well with a screen reader. When someone posted a new item, the screen reader read the new material. Worked nicely. Most chats in Windows do one of two things, neither very good: (1) What is new on the screen is not automatically spoken. I have to guess maybe something might have

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Universal Design for Online Education

happened and use the Jaws cursor to explore the screen to find out if anything new happened. (2) The other is that the software redraws the entire screen whenever anything new happens and the screen reader reads the entire screen each time over and over and over and over and over and over . . . (August 21, 2002b, Listserv ACT@ MAELSTROM.STJOHNS.EDU). Instant messenger chats such as those provided by AOL, MSN, and Yahoo are somewhat better for screen readers, although the user must still make adjustments to settings in order to increase accessibility. As awareness increases, chat features should become increasingly more accessible. Companies such as HorizonLive have been working to achieve 508 compliance. Its 3.0 version released in the Fall of 2002 has added features to accommodate users with disabilities, such as an html messaging system, the ability to display text-only versions of slides, and keyboard shortcuts (HorizonLive, 2002). WebAIM (2002c, p. 16) recommends that the following questions be investigated before adopting a chat program: 1 2. 3. 4. 5. 6.

Is the interface accessible through the keyboard only? Does the program work with common screen readers? Can the user control the scrolling and/or refreshing of messages? Does sound alone convey important information? Are the controls easy to use and clear? If Java is being used, is it designed to work with Jaws and other screen readers?

For students with visual disabilities, perhaps the best solution is an audio chat (using a microphone and speakers) or a phone conference. This may also facilitate access for those with physical disabilities who may find it hard to type fast enough to follow the pace of an online text chat.

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Needless to say, hearing-impaired students will not be able to participate in such chats without proper accommodations. For the deaf student, the text chat may work well, but an audio chat or phone conference may also be possible with the appropriate accommodations. For instance, for a brief phone conference, the Telecommunication Relay Service (a toll-free service) may be contacted so that an operator links the student and faculty though a TTY (a combination of telephone, keyboard, and display used for text-based communication). This way, the student will be able to get the messages the operator types and sends to his TTY phone and can type his replies so that the operator reads it aloud. In case of a chat, it may be necessary to have someone doing live captioning for the student. For example, if a live presentation is being broadcast through the Internet, the deaf student may be connected to a text chat system so that he or she can read the content being typed by the transcriptionist (the person providing the captioning services) and send back questions to the instructor or guest speaker as needed. The instructor following the chat transcripts can then relay questions or comments from the student to the rest of the audience. Similarly, if a video camera is available, an interpreter could be asked to provide sign language interpretation while the presentation takes place. This may be challenging, however, because most cameras that are compatible with computers do not have the range to show both the speaker and the sign language interpreter. If the institution has video-conferencing classrooms equipped for distance-learning events, it may be a better solution to use that equipment for such events (Chancellor’s Office of California Community Colleges, 1999). In the case of video conferencing, it is important to keep in mind that although a blind student will be able to listen to the content, he or she may miss important non-verbal information. The use of PowerPoint slides or any other visual input should be accompanied by a narration of what is

Universal Design for Online Education

being shown, similar to what would happen in a face-to-face classroom. If an instructor makes frequent reference to text-based materials, such materials should be posted or sent in advance via e-mail so that the student has an opportunity to review them. It is unlikely that multiple disabilities will be represented in one course; therefore, as long as the instructor understands the needs of different students, a decision about the technology and accommodations necessary for access can be made after discussing the issue with the student. Unlike a Web site, which is hard to change once developed, modes of interaction offer more flexibility. Knowing what options are available, faculty can experiment with different types of accommodation before deciding what method is the most efficient and effective for all students in the course. In addition, academic institutions are already mandated to offer services to disabled students such as interpreters and captioning for live events, so the instructor can contact the office in charge of providing such services and make arrangements for the online course the same way in which it is done for face-to-face courses.

CONCLUSION This chapter provided some basic information on how to design online courses that accommodate individuals with diverse functional abilities. Instructors interested in evaluating their existing online courses for accessibility—or courses under construction—may consult Appendix A for suggestions on how to perform such evaluation. When limitations are identified, it is important not to become overwhelmed with the potential amount of work required. Instructors who do not possess the expertise needed to make more sophisticated changes to their course sites are not likely to have created complex accessibility problems to begin with. Often, hard-to-fix accessibility infractions are a result of new technology, not yet

modified to include accessibility options. Testing technology for access not only by persons with disabilities, but also by individuals with slower connections, older computers, or different browsers is always a wise idea. If the modifications seem to exceed the faculty member’s technical capabilities, support staff available either though online education or computer services programs should be consulted. Not all support staff members will be aware of accessibility requirements, but they will have the skills to produce the necessary modifications if the instructor is able to communicate his or her needs to them. Faculty members can become advocates for greater technical support by educating university administration to the legal, ethical, and practical reasons for compliance with accessibility guidelines. Finally, recognizing that space is limited for the vast amount of information available on the topic of accessibility, the authors have prepared a list of resources that include print and online materials on the issues identified throughout this chapter. As technology moves increasingly faster, many other resources are likely to become available by the time this chapter is published. Readers are encouraged to consult the major Web sites listed in Appendix B in order to acquire state-of-theart information and to bookmark those sites that appear the most useful for ongoing technical assistance.

REFERENCES Abramson (2000). Digital divide widens. Retrieved from http://www.thestandard.com/article/ display/0,1151,19429,00.html Alexander, K., & Alexander, M.D. (1995). The law of schools, students and teachers. Saint Paul, MN: West Group. The Alliance for Technology Access. (2000). Computer and Web resources for people with disabilities: A guide to exploring today’s assis-

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tive technology (3rd ed.) Alameda, CA: Hunter House Publishers. Amazon.com. (2002). Home page. Retrieved from http://www.amazon.com American Association or Retired Persons. (2001). Profile of older adults. Administration on Aging, U.S. Department of Health and Human Services. Bergman, E., & Johnson, E. (1995). Towards accessible human-computer interaction. In J. Nielsen (Ed.), Advances in human-computer interaction. Norwood, NJ: Ablex Publishing. Retrieved from http://www.sun.com/access/developers/updt.HCI. advance.html Blackboard. (2002). Accessibility – Section 508. Retrieved from http://products.blackboard.com/ cp/bb5/access/section508.cgi Bobby (2002). Home page. Retrieved from http:// www.cast.org/bobby/ Brummel, S. (1994). White Paper - National information infrastructure — People with disabilities and the NII: Breaking down barriers, building choice. Retrieved from http://www.gsa. gov/attachments/GSA_PUBLICATIONS/pub/People %20with%20Disabilities %20and%20the%20Nati onal%20 Information%20Infrastructure. doc Burgstahler, S. (2002). Universal design of distance learning. Information Technology and Disabilities. Retrieved from http://www.rit. edu/~easi/itd/itdv08n1/burgstahler.htm Campbell, L., & Waddell, C. (1997). Electronic curbcuts: How to build accessible Web sites. Retrieved from The International Center for Disability Resources on the Internet http://www. icdri.org/CynthiaW/ecc.htm The Center for the Partially Sighted. (2001). About low vision. Retrieved from http://www.low-vision. org/low-vision.html.

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The Center for Universal Design. (2002a). What is universal design? Retrieved from http://www. design.ncsu.edu/cud/univ_design/ud.htm The Center for Universal Design. (2002b). Principles of universal design. Retrieved from http://www.design.ncsu.edu/cud/univ_design/ princ_overview.htm Chancellor’s Office of California Community Colleges. (1999). Distance education: Access guidelines for students with disabilities. Developed by the High Tech Center Training Unit in collaboration with the Distance Education Accessibility Workgroup. Retrieved from http://www. catsca.org/articles/dis_guidelines.html Coombs, N. (2002a). Barrier-free e-learning. Online course offered by EASI (Equal Access to Software and Information). Retrieved from http://easi.cc/workshops/bfel.htm Coombs, N. (2002b). Comments on text chat posted on the [email protected]. EDU listserv on August 21, 2002. Danielson, L. (1999, Fall). Universal design: Ensuring access to the general education curriculum. Research Connections, 5, 2-3. Retrieved from http://www.rit.edu/~easi/law/weblaw1.html Division of Rehabilitation, Education Services, University of Illinois at Urbana-Champaign. (2002). Microsoft Power Point WWW Publishing Accessibility Wizard. Retrieved from http://www. rehab.uiuc.edu/ppt/overview.html Federal Communications Commission (FCC). (2002a). About section 508. Retrieved from http:// ftp.fcc.gov/cgb/dro/ab508.html Federal Communications Commission (FCC). (2002b). Section 225. Telecommunications access for people with disabilities. Retrieved from http://www.fcc.gov/cgb/consumerfacts/section255.html

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Gardner, H. (2000). Intelligence reframed: Multiple intelligences for the 21st century. New York: Basic. Harrison, L. (2000). Accessible web design and curriculum adaptive technology. Colorado Conference on Assistive Technology in Higher Education, EASI roundtable discussions, Colorado, November. Retrieved from http://easi. cc/colconf/trans/laurie7.htm

Schwitzer, A., Ancis, J. & Brown, N. (2001). Promoting student learning and student development at a distance. Lanham, MD: American College Personnel Association. Tanchak, T., & Sawyer, S. (1995). Assistive technology. In K.F. Flippo, K.J. Inge, & J. Michael Barcus (Eds.), Assistive technology: A resource for school, work, and community. Baltimore: Paul H. Brookes.

Henry, S. (2002). Accessibility-usability synergy. In J. Tacher, P Bohman, M. Burks, S. Henry, B., Regan, S., Swierenga, M., Urban, & C. Wandell (Eds.), Constructing accessible Web sites. Birmingham, UK: Glasshaus.

Thatcher, J. (2002a). Accessible data input. In P. Bohmnan, M. Burks, S. Henry, B. Regan, S. Swierenga, M. Urban, & C. Waddel (Eds.), Constructing accessible Web sites. Birmingham, UK: Glasshaus.

HiSoftware. (2002a). Frequently asked questions (AccVerify). Retrieved from http://www.hisoftware.com/access/faqs.html

Thatcher, J. (2002b). Accessible navigation. In P. Bohmnan, M. Burks, S. Henry, B. Regan, S. Swierenga, M. Urban, & C. Waddell (Eds.), Constructing accessible Web sites. Birmingham, UK: Glasshaus.

HiSoftware. (2002b). AccVerify® SE™ for FrontPage. Retrieved from http://www.hisoftware. com/msacc/ HorizonLive. (2002). Web’s 1s t conferencing solution fully accessible to people with disabilities. Retrieved from http://www.horizonlive.com/ aboutus/pr_102402.html Mace, R. (1998, Summer). A perspective on universal design. UD Newsline, 1(4). Maromedia. (2002). Macromedia exchange for Dreamweaver. Retrieved from http://dynamic. macromedia.com/bin/MM/exchange/main. jsp?product=dreamweaver Nielsen, J. (1999, June). Disabled accessibility: The Pragmatic approach. Alertbox. Retrieved from http://www.useit.com/alertbox/990613. html Oregon Commission for the Blind. (2000) Frequently asked questions. Retrieved from http:// www.cfb.state.or.us/faq.htm Paciello, M. (2000). WEB accessibility for people with disabilities. Lawrence, KS: CMP Books.

Thatcher, J. (2002c). Creating accessible content. In P. Bohmnan, M. Burks, S. Henry, B. Regan, S. Swierenga, M. Urban, & C. Waddell (Eds.), Constructing accessible Web sites. Birmingham, UK: Glasshaus. Tucker, B. (1998). Federal disability law. Saint Paul, MN: West Group. University of Iowa. (2002). Dreamweaver resources. nTITLE — New Technology in the Learning Environments. Retrieved from http://www.uiowa. edu/~ntitle/resources/dreamweaver.shtml U.S. Architectural and Transportation Barriers Compliance Board. (2000). Electronic and information technology accessibility standards. Retrieved from http://www.access-board.gov/ sec508/508standards.htm Vanderheiden, G. (1990). Thirty-something million: Should they be exceptions? Human Factors, 32(4), 383-396.

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Waddell, C. (1998). Applying the ADA to the Internet: A Web accessibility standard. Retrieved from http://www.rit.edu/~easi/law/weblaw1.htm Waddell, C. (2002). U.S. Web accessibility law in depth. In P. Bohmnan, M. Burks, S. Henry, B. Regan, S. Swierenga, M. Urban, & C. Waddel (Eds.), Constructing accessible Web sites. Birmingham, UK: Glasshaus. Wallace, J., Flippo, K., Barcus, M., & Behrmann, M. (1995). Legislative foundation of assistive technology policy in the United States. In K. Flippo, K. Inge, & M. Barcus (Eds), Assistive technology: A resource for school, work and community. Baltimore: Paul H. Brooks. WAVE. Retrieved from. http://www.temple. edu/inst_disabilities/piat/wave WebAIM. (2002a). Introduction to web accessibility. Retrieved from http://www.webaim. org/intro/

WAI-WEBCONTENT-19990505/checkpoint-list. html World Wide Web Consortium (W3C). (1999e). Priorities. Retrieved from http://www.w3.org/ TR/WAI-WEBCONTENT/#priorities World Wide Consortium. (2000a). W3C Techniques for Web content accessibility guidelines. Retrieved from http://www.w3.org/TR/WCAG10TECHS/#gl-own-interface World Wide Consortium. (2000b). Curriculum for Web accessibility guidelines. Retrieved from http://www.w3.org/WAI/wcag~curric/intl0.htm

ENDNOTES 1

WebAIM (2002b). Accessibility training CDROM. Retrieved from www.webaim.org WebAIM (2002c). Accessibility of online chat programs. Retrieved from http://www.webaim. org/articles/chats

2

World Wide Web Consortium (W3C). (1999a). About the World Wide Web Consortium (W3C). Retrieved from http://www.w3.org/Consortium/ World Wide Consortium (W3c). (1999b). Fact sheet for “Web content accessibility guidelines 1.0.” Retrieved from http://www.w3.org/1999/05/ WCAG-REC-fact.html World Wide Consortium (W3C). (1999c). Web content accessibility guidelines 1.0: W3C Recommendations (Latest version). Retrieved from http://www.w3.org/TR/WAI-WEBCONTENT/ #Guidelines. World Wide Web Consortium (W3C). (1999d). List of checkpoints for web accessibility guidelines. Retrieved from http://www.w3.org/TR/1999/

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Removing barriers that present persons with disabilities from engaging in substantial life activities and from using services, products and information in everyday life (Bergman & Johnson, 1995). The Assistive Technology Act of 1988 (PL 100-407) defined assistive technology devices as any device, piece of equipment, or product system that is used to increase, maintain, or improve functional capabilities of individuals with disabilities. It also emphasized the importance of services to assist consumers in the selection, acquisition, or use of assistive technology devices (Wallace, Flippo, Barcus, & Behrmann, 1995). Legal blindness is defined as central vision accuracy of 200/20 or less in the better eye, after best correction. If central visual acuity is better than 20/200, it must be accompanied by a limit to the field of vision to such a degree that its widest diameter allows an angle of no greater than 20 degrees (Oregon Commission for the Blind, 2000).

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4

5

6

7

Uses a synthesized voice to “speak” the information on the screen (The Alliance for Technology Access, 2000). Provides tactile output by forming Braille characters, that can be “refreshed” after the user reads each line (The Alliance for Technology Access, 2000). Denotes significant reduction in visual function. Clear vision is not achieved by the use of eyeglasses, contact lenses, or intraocular lens implants. Differs from blindness because visual devices can improve vision to some extent (The Center for the Partially Sighted, 2001). This keyboard enhancement provides keyboard control of cursor and button functions

8

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by pressing the numeric keyboard and other key combinations (Bergman & Johnson, 1995). Voice recognition software allows the user to speak to the computer to control data input or to control functions such as e-mail, Internet, and other applications (Bergman & Johnson, 1995). Augmentative and Alternative Communication (AAC) is defined as the integration of a variety of strategies and techniques, other than speech, that enhance independent and interactive communication. AAC communication aids range from low-tech communication boards to high-tech electronic devices (Tanchak & Sawyer, 1995).

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APPENDIX A Validation Issues How can you insure that, if you follow the recommendations in this chapter, your site is actually accessible? Following are three basic steps that will assist you in validating the accessibility of your site.

Step 1: Make Every Effort to Do Things “Right” the First Time Part of what makes for good design is attention to design issues from the outset of the project, not as an afterthought when problems have already become apparent. A good first step that also offers an inexpensive and enlightening way to check your site is the following “quick tip” available on the WEBAim homepage (http://www.webaim.org): Quick Tip # 9 What happens when you use only your keyboard to access your site (no mouse)? Can you get to all of the links? Is it easy to navigate? What happens when you turn off all images? Is your site understandable (even if it isn’t as “pretty”)? What if you turn off the volume on the computer? Is your multimedia still usable? These simple tests are a good starting point for anyone who wants to gauge the accessibility of their site. Another key question to keep in mind is “What do I want the site to do or teach?” — as opposed to “How do I want the site to look?” This question will help to keep the emphasis on “good teaching,” which is the issue that drives the design.

Step 2: Checking Your Site Throughout the Design Process with Tools Marketed Specifically to Help with Design Issues Many of these tools are based on the Section 508 Standards and/or the W3C and WIA guidelines. Some of these tools are available for free or at a minimal cost. They will point out design flaws and suggest possible remedial activities. “Bobby” (http://www.cast.org/bobby/) and “WAVE” (http://www.temple.edu/inst_disabilities/piat/ wave) are two such tools specifically designed to help a designer locate potential elements of a Web page that may cause some users to have difficulty accessing all or part of a site. There are other tools available as well, and you will find a selection listed in Appendix B of this chapter. It is important to consider all of the elements of your site as you do a design check. Many validation tools have been constructed for specific purposes, for example, to check html code or to provide a developer with alternatives to the use of common site elements like the use of color, pictures, tables, and text placement. Other elements of your site, such as a PowerPoint® presentation, an audio file, or the use of specific programs, might require that you utilize specific techniques to insure compliance with accessibility standards. Do not be put off by the need to put in a little more work “up front.” There are specific evaluation tools, tutorials, and free downloads available to help to maximize compliance with

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508 Standards even when using software like PowerPoint® , Dreamweaver® , and FrontPage® . Remember, having a site that is accessible does not mean having a site that is only text-based. “Accessibility is about designing so that more people can use your Web site effectively in more situations” (http://WEBAim. org). Accessibility is not about being boring or having to forgo common instructional methodologies. Also remember that if you make changes to your site, perhaps starting with simple elements and then adding more complexity as your own skill level increases, you should run a “validity check” each time you modify your site.

Step 3: Get Input from “Experts” Who Are Available to You Experts include staff from computer services and instructional support. Other faculty members who are experienced in designing online education and user-friendly sites may also be willing to serve as resources. But most importantly, actively solicit input from students with disabilities. Many students would much rather be asked what they need and how it can best be provided before the fact, rather than being faced with the frustration of sometimes less than adequate adjustments that are made later on. You should solicit input from students with a range of disabilities, including visual, auditory, motor, cognitive, and visual-perceptual conditions. Make a special effort to recruit students with hidden disabilities such as epilepsy or learning disabilities that can impact the ability to use online modalities. Act on the input you receive, and remember to ask your audience to review your revised site.

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APPENDIX B Resources Websites General Sites: These are extensive Web sites on the topic of Web accessibility. Although it may take some time, it is worthwhile to explore these sites in detail. CAST: The Center for Applied Special Technology (http://www.cast.org) CAST is a “not-for-profit organization that uses technology to expand opportunities for all people, especially those with disabilities.” This is an extensive site with multiple pages containing a variety of resources for educators, Web designer, and other individuals with an interest in making the Web accessible to all. Note the pages on Universal Design for Learning and The National Center on Accessing the General Curriculum. CAST is also the home of “Bobby,” a free tool that can be used to check the accessibility of any Web site. The International Center For Disability Resources on the Internet (http://www.icdri.org) This site contains the collected works of Cynthia Waddell, noted expert on accessible Web design. There is also a searchable database of other assistive technology and information technology resources at this site. WebABLE! (http://www.webable.org) The WebABLE! library is “a collection of books, press releases, white papers, articles, plans, standards, reference guidelines, and journals that focus on accessibility, assistive and adaptive technology for people with disabilities.” The homepage also contains a link, “Tools and Utilities,” that will direct the user to many sites that describe and provide access to software, guidelines, and other tools to maximize Web site accessibility. Web Accessibility Initiative (WIA) (http://www.w3.org/WAI) WAI, in coordination with organizations around the world, pursues accessibility of the Web through five primary areas of work: technology, guidelines, tools, education and outreach, and research and development. The Web site includes page-authoring guidelines to maximize the accessibility of a Web site. WebAIM Web Accessibility in Mind Homepage (http://www.webaim.org) This page offers “Web accessibility information and solutions.” There is something here for the novice as well as the experienced Web designer. Includes a “Tip of the Day,” a “508 Checklist,” and a Discussion Group on accessible Web design and a searchable list of resources on Web site accessibility, as well as a variety of other resources.

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Sites on Specific Aspects of Accessible Web Design Adobe and PDF Accessibility (http://access.adobe.com) This site provides information on Adobe accessibility and free tools such as Acrobat Reader to assist in making portable document files accessible. Macromedia (http://www.macromedia.com/macromedia/accessibility) This is a site describing accessible Macromedia tools. Plug-ins for Flash and Shockwave are featured, as are extensions designed to enhance the accessibility of Dreamweaver. Free templates for designing accessible Web sites are also available. Section 508 Homepage (http://www.section508.gov) The U.S. Government site designed to provide information about Section 508. Applying the ADA to the Internet: A Web Accessibility Standard by Cynthia D. Waddell, JD, ADA, Coordinator, City of San Jose, CA, USA (http://www.rit.edu/~easi/law/weblaw1.html) The Growing Digital Divide in Access for People with Disabilities: Overcoming Barriers to Participation by Cynthia D. Waddell, JD (http://www.aasa.dshs.wa.gov/access/waddell.html) Web Accessibility Initiative Policy Page (http://www.w3.org/WAI/Policy) The WAI keeps an updated overview of laws pertaining to Web accessibility on its site. THOMAS—Legislative Information on the Internet (http://thomas.loc.gov) If you wish to review the actual text of U.S. legislation, THOMAS is the definitive source. To read the text of the laws cited in this chapter, simply search by Public Law number (P.L. xxx-xxx).

Website Evaluation Tools Bobby (http://bobby.watchfire.com/bobby/html/en/index.jsp) “Bobby” software was first introduced in 1996 and was the first tool created to assist in implementing Web accessibility guidelines. Bobby will check your site one page at a time for free. To check an extensive site, a commercial version of the software is available. WAVE (http://www.temple.edu/inst_disabilities/piat/wave) WAVE is a tool that provides feedback for Web developers. It uses an iconic system to convey information about potential problems with accessibility.

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A user can create a bookmark in a preferred Web browser, then simply open a page in the browser and click on the bookmark to have it checked by WAVE. A-Prompt (http://aprompt.snow.utoronto.ca) A-Prompt is another accessibility check developed at the University of Toronto. It can be used at no cost. A variety of products are available commercially. These include the commercial version of Bobby and the others listed here. InFocus (http://www.ssbtechnologies.com/products/InFocus.php) Page Screamer and Accessibility Monitor — Page Screamer will evaluate single pages, multipage sites, and complex multi-layer sites. Accessibility Monitor provides the designer with information specific to 508 guidelines. Verify (http://www.hisoftware.com/access/Index.html) AccVerify™ specifically checks for section 508 compliance. AccRepair™ assists a user in making changes to maximize accessibility. AccVerify™ Server, spiders entire sites and flags Section 508 violations. AccRepair™ Plugin for AccVerify Server, allows for repair of pages across a server. AccRepair™ and for AccVerify™ for FrontPage® , work within FrontPage. AccessEnable (http://www.retroaccess.com) RetroAccess provides a Web -based accessibility checker that will crawl through a Web site and report on the errors that it finds. The evaluation is based on Section 508 Guidelines. AccessEnable “provides site-wide automatic and interactive fixes for a number of accessibility and syntax violations.” WebABLE Accessibility Monitor (http://www.accessibilitymonitor.com) The WebABLE Accessibility Monitor is a fee-based online service. It provides scheduling of monitor services, customizable reports, e-mail alerts, W3C WAI, and Section 508 reporting and other features. It can monitor entire sites.

Books

Note: All publisher comments and reviews are quoted from the Amazon Web site —http://www.amazon.com. Homepage Usability: 50 Websites Deconstructed By: Jakob Nielsen and Marie Tahir, New Riders, Indianapolis, IN, 2001 While there is a plethora of books available that provide tips on Web design, most authors leave a significant gap between the theory and practice—a gap that is left up to the reader to fill. Homepage Usability: 50 Websites Deconstructed boldly steps into that gap with specific observations and suggestions backed with solid quantitative analysis. This book focuses only on home page design as the most important point of presence for any Web site.

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Web Accessibility for People With Disabilities By: Michael G. Paciello, CMP Books, Lawrence, KS, 2000 Paciello’s book is a critical resource for removing barriers to effective communication and commerce and should be on everyone’s bookshelf. Teaching Every Student in the Digital Age: Universal Design for Learning By: David H. Rose and Anne Meyer, Association for Supervision and Curriculum Development, 2002 Discusses and illustrates Universal Design for Learning as a framework for understanding the needs of diverse learners and educating them. Drs. Anne Meyer and David Rose and contributing writers present case studies of diverse students, illustrations of teacher practice, demonstrations of software tools and learner technologies, and research from neuroscience and psychology. Maximum Accessibility: Making Your Web site More Useable By Everyone By: John M. Slatin and Sharon Rush, Addison Wesley Professional, 2002 This book by is described as “a comprehensive resource for creating Web sites that comply with new U.S. accessibility standards and conform to the World Wide Web Consortium’s Web Content Accessibility Guidelines 1.0. This book offers an overview of key issues, discusses the standards in depth, and presents practical design techniques, up-to-date technologies, and testing methods to implement these standards for maximum accessibility.” Constructing Accessible Web sites By: Thacher, Waddell, Swierenga, Urban, Burks, Regan, Bohman, Glasshaus, 2002 Accessibility is about making Web sites that do not exclude people with visual, aural, or physical disabilities. This book will enable Web professionals to create or retrofit accessible Web sites quickly and easily. It is a practical book; the accessibility techniques outlined within are illustrated with real world examples from live sites, demonstrating that accessibility is not the enemy of great visual design.

This work was previously published in The Distance Education Evolution: Issues and Case Studies, edited by D. Monolescu, C. Schifter, and L. Greenwood, pp. 67-115, copyright 2004 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.39

Curriculum Development in Web-Based Education Johanna Lammintakanen University of Kuopio, Finland

INTRODUCTION A paradigm shift has taken place in the last decade, with a move from traditional to Webbased education at different educational levels (Harasim, 2000; Karuppan, 2001; Kilby, 2001). Web-based education (WBE) has moved on from the delivery of educational content to Web-based sites with interactive functions (Carty & Philip, 2001). Concurrently, new innovative kinds of pedagogical experiments have shifted the paradigm from teaching to learning (Pahl, 2003). As summarised by Armstrong (2001), what educators have in fact realised is that a good Web-based education theory and good education theory are one and the same; the only difference is that WBE transcends the barriers of space and time. The paradigmatic shift has occurred as part of planned educational policy, while at the same time good international or national experiences have also supported the growth of WBE. In addition, there have been attempts to have more coherent and cohesive educational systems and degrees especially in the European context (The Bologna Declaration, 1999.)

The aim of this chapter is to pursue the discussion of some essential issues and promoting factors facing Web-based curriculum development (Figure 1). At the beginning, the main concerns in curriculum development are quite often related to students, new technology and pedagogical issues. However, the curriculum development is a process due to constantly evolving information technology and changes in course contents. The second part of this chapter focuses on this. Additionally, curriculum development does not happen in a vacuum. Therefore, quality, ethics and management are briefly summarized as important contextual concerns in WBE curriculum development.

BACKGROUND Curriculum Development in web-Based Education Basic questions at the first phase of the WBE curriculum development have been summarized in this review into three overall themes: 1) stu-

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Curriculum Development in Web-Based Education

Figure 1. Curriculum development as a continuous process CONTEXTUAL FACTORS

Quality

Management

Student analysis

Content

Information technology

Format Infrastructure

Teaching and learning design

Pedagogy

Basic questions in curriculum development

Main reasons for constant development

Ethics

dent analysis; (2) information technology; and (3) teaching and learning design (adapted from Alexander, 2001).

Student Analysis One crucial component in curriculum development is the identification of potential users, and analysis of their needs (Karuppan, 2001; Lammintakanen & Rissanen, 2003). Variables such as age, gender, being employed or unemployed are premised as having an effect on computer use (Karuppan, 2001; compare to Lu, Yu, & Liu, 2003). Furthermore, learning materials should support the student’s particular learning style in order to facilitate learning (Karuppan, 2001). At best, Web-based education encourages the student to take control over his or her own learning. In turn, curriculum development should support this by promoting a completely new way of thinking in students: from what they hope to acquire from the course to what they themselves contribute to the creation of knowledge (McFadzean & McKenzie, 2001).

Although Web-based learning is said to be a flexible way of learning in terms of availability (anywhere and anytime), it is crucial to take into consideration the place from where the students participate, for example, the home or work place, and also the kind of skills that they have. The following reasons have been recognized as major obstacles in students’ use of information and communication technology (ICT): 1) a lack of student workstations; 2) students’ lack of time; 3) students’ ICT skills; 4) course overlap; 5) insufficient course hours; and 6) teachers’ lack of time (Sinko & Lehtinen, 1999). Careful consideration of these aspects provides an idea of what kinds of learner support systems are needed from the educational institution (e.g., tutoring, technical support; Lammintakanen & Rissanen, 2003). In sum, support from the educational organization and other students, as well as the individual’s experience of technology have a major influence on the student’s learning experiences (Alexander, 2001).

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Information Technology Similarly, fundamental questions exist concerning the technology used in education. One of the problems concerns the interaction between the equipment used, for example, is technology available to students, and is it accessible especially if interactive text, video and voice are combined? What does the technology cost learner? This is something that should especially be taken into consideration in those countries where tuition fees are not implemented (e.g., Lammintakanen & Rissanen, 2003). Web-based education is supposed to be cost-effective from the organizational side (e.g., Karuppan, 2001), although hardware, software and labour costs are somewhat expensive. Similarly, it would be imperative that the equipment be available for both the students and educators “just on time” because of the rapid development of information technology (IT).

Teaching and Learning Design Although the choices made during the planning process determine whether the Web-based education is based on constructivism or other learning theories, constructivism is usually closely related to WBE (Jefferies & Hussain, 1998). Web-based education is believed to promote a constructivist approach by allowing all-round interaction, transferring the responsibility of learning to the student, and enhancing the construction of knowledge by interaction. During the curriculum development stage, a careful evaluation is needed on whether or not the chosen technology supports teaching strategies that encourage active involvement, critical thinking, and fosters relationships between learners (Armstrong, 2001). It has, however, been shown that although teachers have adopted the model of constructivist epistemology in principle, they have not always implemented it in the ways they organize the learning situations (Sinko & Lehtinen, 1999).

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The changing roles of teachers are obvious in WBE. Previous research has shown that the role of the teacher is not diminished, however, traditional teacher duties, such as instructing the learners and information communication, are. The teacher’s new role can be described as a learning catalyst and knowledge navigator, or as tutor acting as a facilitator for learning and group processes (see Volery & Lord, 2000). Moreover, the tutor’s duty is to maintain a safe environment for learning, and encourage novel problem solving processes (McFadzean & McKenzie, 2001). Web-based learning forces teachers to become course designers who make decisions based on their understanding of the probable needs, expectations and behaviors of students on their own campuses (Blythe, 2001). To briefly summarize, previous studies have shown that the technology affects learning in many ways (e.g., McFadzean & McKenzie, 2001; Sinko & Lehtinen, 1999). Curriculum development is a time-intensive requiring adequate financial resources in order to develop tightly organised courses. In addition, it is to be expected that the faculty workload would increase (Armstrong, 2001; Carty & Philip, 2001). Unfortunately, too many WBE applications are still mere tutorials or online books (Kilby, 2001).

Curriculum Development as a Constant Process The focus of the Web-based education and especially curriculum development has taken a step forward during the last years. However, while a substantial body of research has focused on this new teaching medium, the results have been mixed and with no significant improvement over traditional methods. Additionally, there is a lack of systematic and scientific knowledge, especially with regard to the effects and outcomes of WBE (Karuppan, 2001; Lu et al., 2003; Reisman, Dear, & Edge, 2001). Still, the use of WBE has rapidly increased.

Curriculum Development in Web-Based Education

Table 1. The factors of change promoting curriculum development (Source: Pahl, 2003) Content

Format

Infrastructure

Pedagogy

The course subject evolves Changes in content to improve the material Changes in • Staff • Student body (qualifications, numbers, mode of learning) • Timetable (where and when the course takes place) • Syllabus (the content and organization of the course) • Curriculum (level, extent, prerequisites) • Legal and/or financial environment Improvements in hardware technology Systems and language technology face constant minor changes Learning devices are developing Knowledge acquisition, modeling of and access to educational knowledge Active learning in terms of engaging the student through interactive systems Collaborative learning supportive systems Autonomous learning Evolving instructional design

Previously, the challenges of curriculum development focused merely on the lack of skills and suitable equipment for WBE. Often flexibility and maintenance aspects have been neglected in the design and development of new technologies. In fact, while in previous stages, the main concerns were in the planning processes (i.e., how to begin with WBE); nowadays, important questions are how to up-date the curriculum and develop it further. The curriculum development can be based on students’ evaluations, experiences of others as well as previous studies (e.g., Lammintakanen & Rissanen, 2003). But, there exits also factors that “force” us to develop the curriculum. For example, Pahl (2003) has summarized both internal and external reasons why the curriculum needs to be constantly evolved (Table 1). The evolvement of the design of a Web-based course can be due to four dimensions: content, format, infrastructure, and pedagogy.

FUTURE TRENDS The Context of Curriculum Development In previous sections, the WBE curriculum development has been described from the pragmatic perspective. However, some existing and concurrently future challenges that have not been mentioned yet have become more important during the curriculum development process. These themes have been summarized into three interrelated categories: (1) ethical and legal issues; (2) quality assurance and accreditation; and (3) managerial and organizational issues. The challenges arose partly from the literature, and partly from practical experiences (e.g., Alexander, 2001; Kilby, 2001; Roffe, 2002), and concern both national and international curriculum development, since a more global perspective in design and courseware provision is expected (Kilby, 2001; see e.g., MIT Open Courseware, Potts, 2003).

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Ethical and Legal Issues Web-based education provides good opportunities to make use of the many information sources available via the Internet (Jefferies & Hussain, 1998). The problem is, however, the quality of knowledge: how to select appropriate information from among the mass, and how to avoid the use of misinformation (Calvert, 1999). At its worst, the Internet is a tool towards fabrication, falsification and plagiarism, which leads to copyright considerations. In addition, from the ethical perspective, students’ privacy and confidentiality, and their respectful and dignified treatment on the Web-based environment are imperative (Armstrong, 2001).

Quality Assurance and Accreditation Quality is a crucial concern in WBE: there are no common quality standards for course design, delivery and evaluation, nor is there is an accreditation system. Some institutions and countries (e.g., the UK) have developed quality assurance protocols that demonstrate that the online programmes are of equal quality to those delivered by traditional methods (Roffe, 2002). From the students’ point of view, the important question is how the courses can be accepted as part of the curriculum; how different educational institutes recognise the courses offered from other institutions nationally and internationally. One quality issue concerns the lack of information bases (portals, registers), which include information on Web-based courses, learning materials or tools for learning that are available on the Internet. In terms of curriculum development, this kind of meta-knowledge would be very useful, and could potentially even reduce the teacher’s workload. But, teachers are not very keen to share material, which they themselves have made, and experiences with colleagues across the educational institutions. However, MIT Open Courseware is an exception, and it is

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open and available all over the world. MIT offers a standardized process for course modelling and encourages extending collaboration and interdisciplinary teaching (Potts, 2003). Registers would also provide students with the information on the available Web-based courses.

Managerial and Organizational Issues The tradition of individualism in teaching is still part of the organizational culture at different educational institutions. At best, the organizational culture can support both Web-based curriculum development and joint teaching. The allocation of both human and technical resources, and a clear strategic decision from managers are requirements for faculty development, and the incorporation of WBE into the curriculum (Carty & Philip, 2001). As well as time and resources, it is essential that the organization and its managers have a positive attitude to WBE, and that they promote its implementation (e.g., Alexander, 2001). However, the managerial approach to lead teaching and curriculum development work is not yet visible in different educational organizations.

CONCLUSION In conclusion, there is no consistent paradigm for WBE, rather there are multiple ways of making use of the Web in education, and these will vary depending on the subject being taught and the needs of the learner. Curriculum development requires a great deal of effort from different stakeholders, and therefore, motivation and commitment for long-term WBE development strategies are also needed at organisational level. In addition, Webbased education appears to support cultural cohesion and more rapid information transformation. Standardization and registers are an essential part of future steps towards the improved utilization of WBE requiring international co-operation

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(see ISO/IEC, which has developed standards for information technology for learning, education and training, http://jtsc36.org).

REFERENCES Alexander, S. (2001). E-learning developments and experiences. Education and Training 43(4/5), 240-248. Armstrong, M.L. (2001). Distance education: Using technology to learn. In V. Saba & K.A. McCormick (Eds.), Essentials of computers for nurses—Information for the new millennium (3r d ed.) (pp.413-436). McGraw-Hill. Blythe, S. (2001). Designing online courses: Usercentred practices. Computers and Composition, 18(4), 329-346. The Bologna Declaration (1999). Retrieved on October 24, 2003 from http://www.minedu. fi/opm/koulutus/yliopistokoulutus/bolognaprosessi.html Calvert, P.J. (1999). Web-based misinformation in the context of higher education. Asian Libraries, 8(3), 83-91. Carty, B., & Philip, E. (2001). The nursing curriculum in the Information Age. In V. Saba & K.A. McCormick (Eds.), Essentials of computers for nurses – Information for the new millennium (3r d ed.) (pp.393-412). McGraw-Hill. Harasim, L. (2000). Shift happens. Online Education as a New Paradigm in Learning. Internet and Higher Education, 3(1-2), 41-61. ISO/IEC JTC1 SG36. Retrieved on March 31, 2004 from http://jtc1sc36.org/ Jefferies, P., & Hussain, F. (1998). Using the Internet as a teaching resource. Education + Training, 40(8), 359-365.

Karuppan, C.M. (2001). Web-based teaching materials: A user’s profile. Internet Research: Electronic Networking Applications and Policy, 11(2), 138-148. Kilby, T. (2001). The direction of Web-based training: A practitioner’s view. The Learning Organization, 8(5), 194-199. Lammintakanen, J. & Rissanen, S. (2003). An evaluation of Web-based education at a Finnish University. In A. Aggarwal, (Ed.), Web-based education. Learning from experience (pp.440-453). Hershey, PA: Information Science Publishing. Lu, J., Yu, C-S., & Liu, C. (2003). Learning style, learning patterns and learning performance in a WebCT–based MIS course. Information & Management, 40(6), 497-507. McFadzean , E., & McKenzie, J. (2001). Facilitating virtual learning groups. A practical approach. Journal of Management Development, 20(6), 470-494. Pahl, C. (2003). Managing evolution and change in Web-based teaching and learning environments. Computers and Education, 40(2), 99-114. Potts, J.P. (2003). A new model for open sharing. A presentation in WCET Annual Conference, November 5t h , 2003. Retrieved on March 31, 2004 from http://ocw.mit.edu/OcwWeb/index.htm Reisman, S., Dear, R.G., & Edge, D. (2001). Evolution of Web-based distance learning strategies. The International Journal of Educational Management, 15(5), 245-251. Roffe, I. (2002). E-learning: Engagement, enhancement and execution. Quality Assurance in Education, 10(1), 40-50. Sinko, M., & Lehtinen, E. (1999). The challenges of ICT in Finnish education. Helsinki: Atena. Electronic Publication available via the Internet: http://www.sitra.fi/eng/index.asp?DirID=297

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Volery, T., & Lord, D. (2000). Critical success factors in online education. The International Journal of Educational Management, 14(5), 216-223.

Portal: Acts as a channel between the content creator and end user. It does not typically have a content of its own.

KEY TERMS

Synchronous Mode: Real-time education where students and teachers can have a dialogue simultaneously, e.g., by using chat.

Asynchronous Mode: A non-real-time education where students and teachers interact with each other but no at same time, e.g., by using bulletin board or email. Computer and Information Literacy: The abilities to perform computer operations at a skill level high enough to meet the demands of the society, and to use the tool of automation in the process of accessing, evaluating and utilizing information (Carty & Philip, 2001). Learning Style: The way in which individuals acquire and use information, strategies to process information in learning, and problem solving situations (Karuppan, 2001). Learning Tools: Included in web-based learning environments for managing the course and are geared to facilitating student learning in the environment.

Web-Based Education (WBE): Differs from traditional classroom teaching in two essential elements: 1) physical distance and 2) time, allowing more flexibility to the learner. The most basic form of WBE is to deliver syllabi, lecture notes, reading materials and assignments via the Internet. The more advanced level includes computer conference facilities, a help desk, linkage of conferencing and web page assignment, testing and course management tools and evaluation (Karuppan, 2001). Web-Based Learning Environment: A specially developed programme using Internet technology for the design and development of teaching and learning purposes. Trademarks are, for example, WebCT, WebBoard, Top Class, Virtual – U. Web-Based Misinformation: Used to describe information found in the Internet that does not fit normative patterns of “truth”, i.e., it is incomplete, out-of-date, confused, or low consensus “knowledge” (Calvert, 1999).

This work was previously published in Encyclopedia of Information Science and Technology, Vol. 1, edited by Mehdi KhosrowPour, pp. 675-679, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.40

Starting with What We Know: A CILS Framework for Moving from Physical to Virtual Science Learning Environments Bronwyn Bevan Exploratorium, USA

ABSTRACT

INTRODUCTION

This chapter examines attributes of learning in informal environments, using a research framework developed by the Center for Informal Learning and Schools. It considers how essential characteristics of learning within science centers can translate and apply to learning in Web-based informal learning environments. It argues that in designing virtual environments, informal science institutions need to build on their particular strengths and pedagogical design principles in order to fill an educational niche in the Web landscape, and not compete with commercial or even K-12 educational agencies similarly engaged in the development of online learning environments.

Cultural institutions—historical societies, art museums, zoos, botanic gardens, science museums, and science centers, for example—offer their communities unique sets of subject-matter resources and expertise. They are adept at designing environments that can engage learners at all age levels and prior knowledge. They know something about sparking curiosity and more deeply drawing visitors into the subject matter. Yet, much of this knowledge is unanalyzed and unarticulated among educator practitioners in these institutions. As cultural institutions move from the development and mediation of exhibit environments to the development of print or Web-based learning tools and environments, it is important that they start from who they are and what they are (Bevan & Wanner, 2003). They need to build from their unique approaches, pedagogies, and collections in order to be the best that they can be, and

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

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also to avoid competing with commercial or even K-12 entities on terms that are not their own. At the Center for Informal Learning and Schools, a U.S. National Science Foundationfunded initiative1 to strengthen K-12 science education through the generation of new leaders and knowledge in the domain of informal learning, we focus our work with practitioners on deepening their understanding of the environments that they work in and the underlying pedagogical principles that inform those environments. We do this through series of institutes that meet over a two-year period to create shared experiences involving learning science through the exhibit collections, as well as promoting group discourse around a number of ideas and thinkers concerned with science teaching and learning. CILS is a partnership of the Exploratorium, King’s College London, and the University of California Santa Cruz. Since its inception in 2002, CILS has worked with over 100 museum educators, has enrolled two dozen graduate students, and has launched a dozen studies investigating informal learning institutions and opportunities. The purpose of CILS is to strengthen alliances between informal and formal systems of education. These alliances can be leveraged to enhance and expand student interest and understanding of the subject matter taught in schools. They also can ensure that the wealth of cultural resources housed in museums are made accessible to, and shape experiences of, audiences from socio-economic groups who traditionally do not visit museums. CILS has begun to articulate areas of knowledge informal educators require in order to form effective alliances with schools. We have also developed a research framework for asking questions of these environments and alliances. Drawing on these two areas of focus—on practice and research—this chapter will examine, from a practitioner point of view, some of the particular attributes of learning environments of cultural institutions and their implications for the design

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of virtual environments, particularly for school audiences.

LOOKING AT CULTURAL INSTITUTIONS While schools, too, are cultural institutions, within this chapter the use of the term “cultural institutions” refers to institutions and organizations that collect, curate, and program public learning environments for visitors of all ages and backgrounds. These include museums, historical societies, botanic gardens, nature centers, science centers, zoos, etc. I use the shorthand “museums” for “cultural institutions” interchangeably throughout this article, because I also seek to avoid the word “informal” and therefore do not want to use the even shorter term “ISI,” for informal science institution. The experiences that many museums aim to promote, as Hein (1998) points out, are not unique to cultural institutions, but fall within a range of educational designs reflective of theories of knowledge and theories of learning. While some museums may follow didactic theories of education, most science centers, as well as growing numbers of other types of cultural institutions, attempt to create discovery-based or constructivist learning experiences consonant with Dewey’s progressive theories of education (Hein, 2004) and found in progressive K-12 schools around the globe. By situating museum-based learning on the progressive end of the continuum of learning experiences, we can begin to dispel the formal/informal dichotomy that operates to separate, indeed marginalize, museum-based learning from other types of learning, notably school-based learning. In the U.S., this marginalization adversely affects public funding and utilization of cultural institutions, and results in an imbalance in equity and access issues relating to families and individuals who have the capacity and cultural traditions to

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draw upon the wealth of cultural resources in a community and those who do not. Situating museum-based learning in this way also provides museum educators with a firmer grounding, and a more robust research base, upon which to make design decisions, and to find ways to better integrate the museum experience into experiences outside of the museum, including K-12 learning.

Learning in Cultural Institutions We learn—accrue and assimilate knowledge and experience—at least from the moment we first open our eyes. Our environments, from the beginning, are curated by our socio-economic circumstances as well as by the interventions of those expert adults, our parents and other family figures. Rogoff et al. (2003) point out that from the earliest stages, children learn through active observation and listening. Proficiency in at least one spoken language is generally developed before much formal schooling takes place, and usually without direct instruction by an adult. What might casually be called “informal” learning—in that it occurs outside of school walls or without direct, formal instruction—Rogoff et al. call intent participation, meaning that children learn by keenly or intently observing and listening, and with the intention of joining, engaging in, or adopting the actions or skills they observe of others. This mode of learning (not limited to children) can be clearly witnessed at home or on the playground. It is seen less often in classrooms where, at least traditionally, children learn subject matter through direct and usually de-contextualized, or abstract, representations of knowledge. A key attribute of intent participation is that the learner is motivated to observe, listen, and learn because she intends to engage in the activities she is observing. At school we participate in the process of learning a range of agreed-upon subject matter, ideas, processes, and social conventions. In these

settings, expert adults (teachers) supervise the successful acquisition or development of new knowledge and understanding. In most cases, the learners have little choice about what they are supposed to learn. However, they have a great deal of control over what they choose to learn, by either agreeing to or resisting participation. Motivating students to learn, particularly at the higher grade levels, is of primary concern to teachers, and increasing concern to the education reform community. To engage students in school learning—cognitively, emotionally, and behaviorally—school reformers advocate for learning experiences that are seen by students as authentic (relevant), realizable, and that capture the imagination (NRC, 2004). An evolving vision for school learning is one that provides students with a range of experiences—gained through listening, reading, researching, designing, collaborating, building, and experimenting—both individually and socially constructed. Different contexts for learning—classrooms, homes, museums, Web environments and television—can also support and contextualize student knowledge, interest, and motivation to learn that, it is posited, can create a readiness or capacity to learn in schools. While there are many highly functioning schools, teachers and students, this particular moment in history—with the advent of the information age as well as advances in the cognitive sciences—poses particularly challenging problems and questions to the school community, having to do with what people need to know and understand, and the most effective ways of achieving those goals. Osborne (2004) explores this question as it regards science education, arguing that in addition to the stuff of science (content knowledge) it is increasingly important for students to understand the nature of science and the processes of science in order to achieve a scientifically literate citizenry (consumers and producers of science and the products of science).

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In cultural institutions, communities have access to a range of rich resources, experiences, and expertise usually pertaining to specific disciplines (e.g., physical science, modern art, natural history). These institutions provide highly formalized learning environments, designed through an elaborate process of research, prototype, design, test, and feedback. Over the past half-century, many cultural institutions have sought to redefine themselves from the formal collection and taxonomies of artifacts (still critical in terms of curation and collection, but seen less relevant to engaging learning) into places that celebrate the subject matter, and draw visitors into the associated human experience of either the subject matter or the study of it (as with natural history museums) (Bevan, 2002). They thus attempt to capture the imagination and to make the material relevant to a broad range of visitors. In addition to supporting the assimilation of a body of knowledge, museums can impart insights into the discipline or medium—kinesthetic, tangible, and evocative experiences that can provide a starting place for deeper inquiries, including traditional academic study and the development of expertise. Entering a room filled floor to ceiling with beetle specimens provides the visitor, at once, with a glimpse into the world not only of beetles, but also of the study of beetles. Indeed, Crowley and Callanan (1998) maintain that the most important learning outcome from children’s visits to museums, specifically science museums, may be the opportunities to engage in the core processes of science—asking questions, considering evidence, describing results—rather than learning and retaining sets of facts. The attributes of learning and of instructional design that we will describe here are not exclusive to cultural institutions, and cross many contexts. Yet, the context for learning can play a critical role in one’s interest, motivation, participation, and meaning-making. Some contexts are alienating and might shut down willingness to learn; some

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are inclusive and encouraging of intellectual community. And different people respond differently, although through the study of culturally and linguistically diverse classrooms, patterns of behavior, comfort, and participation may begin to emerge that suggest that specific contexts and structures for participation may encourage more or less motivation and engagement (Lee, 2001). The next section will look at ways in which cultural institutions design learning experiences to motivate and engage learners. We do this to extrapolate to virtual environments and the role they can play in enhancing formal K-12 science.

FRAMES FOR CONSIDERATION The Center for Informal Learning and Schools (CILS) has developed a research framework that identifies four themes for investigation of CILS questions. They are: 1. 2. 3. 4.

Learning environments and their designs Means and structures of participation Explanation, communication, and discourse Systems and structures that support alliances between K-12 and cultural institutions

This framework overlaps with aspects of the framework developed earlier by the Museum Learning Collaborative (Schauble et al., 1997), which is foundational to the work of CILS. The Museum Learning Collaborative framework was based strongly on socio-cultural theory whereas the CILS framework draws on a wider range of theoretical perspectives, as represented by the CILS faculty. These include research and scholarship in developmental psychology, science education, the natural sciences, and museum education. Many of these perspectives are, however, strongly influenced by socio-cultural theory. The Museum Learning Collaborative (MLC) identified three research themes: learning and

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learning environments; interpretation, meaning, and explanation; and identity, motivation, and interest. We see these themes as being different (but consonant) with the CILS themes. They are consonant in that the focus on learning and learning environments are shared (Theme 1), as is the interest in interpretation, meaning and explanation (Theme 3). The MLC theme of “learning and learning environments” has been resolved by CILS into two themes of “learning environments and their design” (Theme 1) and “means and structures of participation in informal learning” (Theme 2). Motivation, identity, and interest feature in both of these CILS themes. Because of the CILS focus on schools, we have, additionally, a research interest in the systems and structures that support informal learning institutions and opportunities and their connections with schools. This section will consider—from the practitioner perspective—some of the salient features of learning in informal settings using the CILS framework as a thematic guide for analysis. To do this, the paper will refer to science centers, and more specifically to the case of the Exploratorium. The Exploratorium was founded in 1969 and pioneered, with others, the design of interactive science learning environments. It is interesting to note that the original Exploratorium exhibit collection was largely a direct three-dimensional translation of a school physical sciences curriculum. Exhibits were organized around physics topics, themes, and activities found in the Elementary Science Study (ESS) kits, produced by Education Development Center in the 1960s. Topics included Light & Color, Sound & Hearing, and Electricity & Magnetism. ESS took an interdisciplinary approach to science learning, particularly through integrating, to varying degrees, aesthetics and the arts. The exhibits thus built upon sound principles of progressive classroom curriculum and instruction, but translated them to a three-dimensional public learning

environment, facilitated not by classroom teachers but by museum educators and docents.

Capturing the Imagination: Learning Environments and Their Designs The design and spatial, as well as thematic, organization of the environment and/or collections is a form of explanation and/or narrative that conveys the meaning of the subject matter to the visitors. It is a physical manifestation of the ways in which the museum thinks about and understands its own collections, and in particular how it relates to the public, and vice versa. Insights into the subject matter. A critical design element is the identification of compelling subject matter and the development of innovative perspectives on the topic. Indeed experiences of exhibitions that fall flat, despite the bells and whistles, may relate to a lack of insight into the core of the subject matter and what it has to engage our interest—how it resonates with human experience and thus makes a personal appeal to the visitor. For example, an exhibition that the Exploratorium held in the 1990s, on medical imaging, approached the subject through the lens of how popular culture, dating back centuries, used current technologies—from Renaissance wax anatomical figures to fetal ultrasound images on late 20t h century automobile billboards—to shape conceptions about our bodies and human life. This award winning show shifted the focus from simply showcasing a range of medical imaging technologies, to pushing visitors to think about the relationships between the imaging and imagining of our bodies, and the social, historical and ethical implications of this relationship. Additionally, museums build on insight into their subject matter to design generative exhibits that can engage at multiple levels of experience. These exhibits—not designed solely for novice or expert—offer opportunities for people, over

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Figure 1. ‘Sun Painting’ exhibit (Photo by Susan Schwartzenberg)

time, to get to deeper levels of understanding. They become like great books—always offering new insights and experiences, depending on the times in life one reads them. Personal. Ultimately, the museum experience aims to resonate with the individual, to trigger curiosity, wonder, and interest—to help the learner along a path toward long-term (life-long) engagement with the subject-matter. Our success stories often relate to evidence from later times that people continued to think about or study the subject matter encountered in cultural institutions. A key to developing a personal connection is to stimulate a person’s curiosity or wonder, and to do this in playful (not intimidating) ways. A classic example of engaging visitors through a visceral aesthetic experience is a long-time centerpiece of our light and color collection: Sun Painting, by artist Bob Miller. The Sun Painting is a shifting, colorful panel that reflects sunlight coming into the building through a shaft and filtered through an array of prisms. Clouds in the sky and visitors manipulating the prisms change the splashes of light and color on the billboard-sized panel. The beauty of the colors, the delight in being able to

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play with sunlight to create a painting, and the science of refraction draws the visitor into the collections where they can engage in more sustained inquiries into prisms, light, and color. Many exhibits use the counterintuitive or odd juxtapositions to puzzle the passer-by and provoke their curiosity. Why do things behave unexpectedly? A classic example is the Touch the Spring exhibit. Visitors see a spring sitting inside a box and are asked to touch it. When they reach for it, they find it is not there. What is going on? By groping around in the box, visitors will find that the spring is lodged upside down in the front of the box, and concave mirrors are used to project an incredibly realistic image standing in the space of the box. This firsthand experience draws visitors into thinking and further explorations of mirrors, images, and light. Finally, by connecting phenomena with their real world contexts or applications, exhibits seek to situate the science within a commonplace frame of reference. At the Exploratorium we have a number of exhibits—dealing with complexity, resonance, vibration, or patterns that use sand as their central medium. Almost everybody has walked on sand,

Starting with What We Know

whether in a sandbox or at the beach. We all marvel at the natural contours of sandy landscapes, and when one encounters sand, it is difficult not to mold it, carve it, trickle it into new shapes. The experience, prior and current, of sand is a way into looking at the effects of a vibrating drum. It is a way into thinking about complexity. It is a way into thinking about fluid motion. It is not intimidating. It reinforces the idea that science is all around us, and not confined to textbooks, classrooms, or even science museums.

Encouraging Active Learning: Means and Structures of Participation Participating in learning in cultural institutions is both personal and social in nature. As Duensing (2004) points out, the nature of the social space varies with the cultural context. In Mexico City, Exploratorium exhibits have more space between them to allow for larger family groups. More manipulatives, as adjuncts to exhibits, were incorporated into exhibits had been in Brazil. Each museum considers its dominant culture or cultures when designing spaces for participation. Here we want to discuss facets of participation in the U.S. that include the role of observation and the relationships of experts and novices in collaborative learning arrangements. Observation. Rogoff et al. point out that observation is a part of participation (Rogoff, 2002). Observing provides ideas and models for participation and can motivate people to engage more deeply. Museum environments are designed for observation of objects, people interacting with the objects, and the people interacting with each other. (Classrooms, on the other hand, are typically designed for students to observe the teacher, and not each other.) To encourage observation and participation, museums create a visual horizon that allows people to see where they are coming from and where they might go next. Semper (1998) likens a museum environment like the Exploratorium’s to a work-

ing town, with different neighborhoods (the biology neighborhood, the electricity neighborhood, etc.), piazza-like gathering and observing spaces, avenues for passage, and a visible infrastructure like power, pipes, and signage. In such a setting, groups assemble and disassemble—this populated environment offers a wide variety of choices for interaction, as well as models for interaction. Because most visitors are actively engaging with exhibits, other visitors can observe them engaged in this meaningful activity — see smiles of delight, watch as people beckon their friends over to “try this,” and watch as some visitors become deeply engaged in an activity that clearly has the power to fascinate. It is common to see visitors watching other visitors at exhibits, and then go up behind them and replicate the actions that they have observed. This is as true of adults watching children as of children watching adults. Experts and novices in collaborative learning. Museum visitors often attend in mixed-aged groups, and take different roles in the process of noticing, manipulating, and discussing objects or exhibits in the cultural institution. At any given exhibit, a different person in the group may be the “expert” (who knows the content or knows the idea, or knows the exhibit) at a given moment. To encourage interactions, exhibits are often designed to allow for several users to engage at once, and in some cases may require more than one user for the exhibit to fulfill its purpose. For example, with Resonant Pendulum the visitor swings a small magnet onto a steel collar attached to a 300-lb. pendulum hung from the ceiling. Because of the weak magnet, the visitor learns that only by pulling in time with the swing of the pendulum (in resonance), can the pendulum be moved. Two magnets are tied to the fence at 90 degrees to each other so the users, if they cooperate, can alter the pattern in which the pendulum swings (circle, ellipse, line, etc.). Visitors need to discuss strategies to get this exhibit to work easily, thus building a sense of learning as a social endeavor.

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As Crowley and Callanan (1998) point out, museums provide children settings where they can learn in ways that allow children and adults to equally control what they pay attention to, how they engage and learn, and when the learning is done (and they can move on to a new exhibit). Through the process of shared engagement and discussion, through articulating what they are thinking and finding, children are more likely to remember what they have learned and to have more powerful learning experiences than if they were learning in isolation. The social environment thus affords particular opportunities for children to develop experience and knowledge. Expertise may sometimes exist outside of the immediate family or social group. People in cultural institutions observe other people in the process of observing, reading, interacting with the collections. They may become interested in objects by virtue of noticing other people’s interests, or overhearing other peoples’ conversations, including those led by trained museum educators.

Developing Understanding: Explanation, Communication and Discourse Explanation refers both to the explicit descriptions of how and why things occur—which may be found in exhibit labels, in conversations with or presentations by museum docents, in audio or tour guides, or in conversations among visitor groups—as well as the implicit messages and meanings conveyed by the ways in which the subject-matter is presented. As both the MLC and the CILS research frameworks note, research has begun to tie the learning of science to the nature of the discourse, both in and out of classrooms. Language is seen as an essential tool for creating scientific explanations, arguments, narratives, metaphors, and analogies. While constructing and communicating (i.e., explaining) their ideas or understandings about

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what they encounter, visitors externalize, clarify, and restructure their knowledge. Contextualization. An important part of the implicit explanation of the subject matter relates to how the phenomena are presented from a disciplinary point of view. To generate a broader frame of reference, as well as to provide a gestalt for the subject matter, contextualization helps visitors understand the nature of the discipline and how it is investigated and developed. In school settings subject matter, and perhaps science in particular, is presented as so many bricks of knowledge (Osborne, 2000). Few school students gain an understanding of the whole, either as a discipline or as an endeavor. Museums have time and space to give visitors a more holistic sense of the subject matter. For instance, the Seeing collection at the Exploratorium raises big questions about the human experience of seeing—In what ways is seeing a subjective activity? How do we actively construct understanding from what we see and notice? How do we interpret the physical phenomenon of light into mental and visual images?—and in so doing, relates the science of optics, cognition, visual perception as parts of an integrated, daily experience. Science museums can also foster an understanding of how phenomena operate under different conditions and in relationship to one another. One way to do this is through redundancy, providing multiple entry points for visitors, and multiple modes of representation of the phenomena. Redundancy provides the possibility of multiple perspectives on the same phenomenon. It reveals different aspects and behaviors of the phenomena. It opens broader vistas for understanding. Rather than encouraging narrow conceptualizations, visitors are able to develop more complex understandings, and begin to make connections among phenomena or behaviors of phenomena. Redundancy also tends toward the use of different media—video, audio, hands-on demonstrations, mediated discussions, open-ended

Starting with What We Know

Figure 2. ‘Bells’ exhibit (Photo by Susan Schwartzenberg)

investigations—to provide a range of visitors (different ages and levels of prior knowledge) with multiple ways of knowing and seeing. For example, one can learn about resonance through a number of different exhibits at the Exploratorium. Some, like Bells, provide direct hands-on experiences with aesthetically compelling materials. Bells consists of two metal plates which vibrate when they are stroked along their edges with a rosined bow. When each plate vibrates at a specific tone, sand bounces on the vibrating regions of the plates and collects in those areas where there is no vibration, forming intricate, beautiful patterns. Pipes of Pan, on the other hand, provides visitors with an aural encounter with resonance. This exhibit demonstrates how tubes of varying length act to select and amplify sound waves of different frequencies. Ten glass tubes of different length filter out specific tones from the ambient noise of the museum. Each pipe is resonant at a certain frequency, which is determined by its length. If you listen to each pipe in turn, from longer to shorter, you will hear a progression from low-pitched tones to higher ones.

The process of encountering the same or related phenomena in a range of forms (such as finding waves in sound as well as in light, in water and in sand) conveys the message to the visitor that learning and scientific investigation itself is a process of repeated encounters with the phenomenon. Cultural institutions thus send an important message to their audiences when they present material through the accretion of relevant encounters and experiences. Returning to Crowley and Callanan’s point (1998)—they can lead visitors into the heart of the matter.

Integrating Into Educational Infrastructure: Systems and Structures Supporting Informal Learning CILS’s questions about structures to support stronger integration of the resources and learning opportunities of cultural institutions into the K-12 system of learning focus largely on funding and policy issues—on how these resources are in fact used, what drives their use and what impedes their use. 1267

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Programs designed to support K-12 science— particularly teacher development programs and field trips—are designed primarily to support/ boost the teaching and learning as envisioned by the school system. That is, they address common curriculum foci, standards, and assessment. They develop teacher and student content knowledge, as well as understanding and relationships with the nature of science and science process skills. In general, work of museums to support schools or other systems is programmatic and not objectbased. In other words, it is the interpretation and facilitation of the use of the collections, and not the collections themselves. The Exploratorium experimented with one large-scale exhibition project where a set of exhibits was designed according to the latest California state science framework themes. While overall there was mixed response to the exhibition, the constraints of the school curriculum did not match the goals of the public environment. However, museums have the resources upon which to build significant programs that can provide direct and personal experiences with science to nurture interest and engagement with the subject matter (in addition to skill or knowledge levels). Museums can work well at two levels that schools struggle with—the novice level and the expert level. Both for elementary teachers with little science background, and for students who are unengaged in science, museums can provide programs that motivate inquiry, interest, and the development of self-conceptions as successful science learners. In addition, museums can offer advanced science content experiences for high school teachers as well as for students whose interest in science extends beyond what is offered by schools. Science museums—dedicated to the discipline of science and to science learning—can provide teachers with content-rich immersions. Here their conversations with colleagues are about science and the teaching of science, and emanate from

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the doing of science and science investigations. Whereas within the school and classroom environment, much of teacher talk has by necessity to do with administrative and student issues. That is, museums can serve as an oasis for teachers, to rekindle and rejuvenate their passion for their subject matter. They also can use these environments to more deeply engage in thinking about and reflecting on the nature of science—and the importance of understanding the epistemological aspects of science for both themselves and their students.

Summary Using the CILS Research Framework as a way of identifying attributes of learning in cultural institutions that we need to attend to when building learning experiences for the virtual world, we thus identify the following parameters: 1.

2.

3.

4.

Learning designs and environments that provide compelling human perspectives on the subject matter and that do so in ways that viscerally and/or aesthetically stimulate the learner’s curiosity and interest. Participation structures and social environments that allow learners to browse, to enter and participate at varying levels of active engagement and expertise. Explanatory structures that allow learners to build understanding together, engage in discourse, and that contextualize the subject matter within a broader epistemological framework. Systemic structures and avenues that suggest ways that the resources can be mapped into supporting, and enriching, a broader educational framework.

In the next section, we will explore how two Exploratorium Web sites—Origins and Global Climate Change—reflect these design principles, and look at new design and learning opportunities

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afforded by the Web environment. Note that both of these Web sites were developed as a learning environment unto itself—that is, not as an extension of a pubic floor experience.

INTO THE wEB ENVIRONMENT When the Exploratorium launched its Web site in 1993 it was among the first of several hundred Web sites in the world, and one of only a handful that were operated by cultural institutions. Like the cavernous building that beckoned to a mixed group of scientists, artists, and educators who created the Exploratorium, the Internet was viewed as a place of huge possibility—one that had as much potential for active engagement as the physical exhibit floor. It was also imagined that, as with the early Exploratorium, visitors were as likely to stumble into the virtual space as they were to seek it out specifically for science content and learning. The space was therefore developed to be playful, to catch the eye and the whimsy of the accidental visitor. The Web site was developed for the remote audience, not as a marketing tool but as a learning space. Only recently have we begun to also explore its potential to extend the physical visit to the museum in San Francisco. Like the museum floor, the Exploratorium Web site is a convergence of ideas and experiences. But there are also many differences. For one thing, Web visitors usually visit alone; that is, they are not sitting at the computer with friends or family. They are not engaged in discussion and discourse. They also cannot “see” fellow visitors engaged in learning. So the experience is by definition not a physically social one—yet to the extent to which the Web learner engages with the ideas and products of society, it may be extremely social in other dimensions. Another striking difference is that although Web learners are visiting a carefully curated and

designed environment, it is logistically easy and by nature quite likely that visitors can, with a click, depart for entirely different environments and subject matter. That is, one can move quickly from the Exploratorium site to a news site, a shopping site, or any other site on the Web. Entrances and exits can be both quick and unanticipated. Not only can the visitor bypass the gift store near the exit, but they can also remain unaware of entire rooms of knowledge and content just around the corner. Finally, the Web site is a less sensory experience—there are few sounds, no smells, no touch—and thus the experience becomes primarily visual and intellectual. It is fundamentally text dependent, and requires a kind of verbal and graphical literacy that the physical museum does not—it therefore is less prepared to engage younger audiences, or visitors who do not read English. It thus targets, perhaps, a more literate and sophisticated audience than the physical environment. It goes without saying that it is therefore socially somewhat exclusive. On the other hand, our Web site currently reaches 18 million people annually, while our physical building only receives about 500,000 per year. Given these differences, how do we—as cultural institutions—design for engaging Web experiences, building on what we know about developing engaging public floor experiences and about engaging science learning? How do we motivate inquiry and learning in the virtual environment? How do the opportunities provided by the Web support the goals of schools for student and teacher learning? Two Web sites will serve as reference points for investigating these questions.

Inroads and Insights to People and Places: Origins The Live@ Exploratorium: Origins Web site (www.exploratorium.edu/origins) was developed

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Figure 3. The “Origins” fronts page includes a selection of clickable animations for each of the six primary locations, enabling visitors to the site to get a sense of the research locations before entering the full site.

to explore and communicate cutting edge science related to origins of matter, the universe, Earth, and life on Earth. Rather than simply telling the story of the science and the current scientific research, the project is conceptualized as a series of virtual expeditions, or field trips, to remote places where fundamental research is being performed in particle physics, cosmology and biology. Sites include a rain forest research station in Las Cuevas, Belize operated by the Natural History Museum in London; McMurdo Station, Antarctica; and an underground particle accelerator at CERN in Geneva, Switzerland. A total of six research institutions are featured with interactive elements, video clips, articles, images, and live webcasts that enable users to virtually tour the facilities and provide a window into the world of the research as it unfolds. As of 2004, Origins has been visited by over 3 million people.

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Learning design. It is difficult for a visitor to experience current science research and get a sense of the enterprise, the endeavor, and the science itself—what the questions are and why they matter; who the people are and what they do; the instrumentation; the implications; the connections with what we know and don’t know. Origins takes two particular, innovative perspectives on the challenge of communicating current scientific research—that of place, and that of the human endeavor of scientific research—who are the people doing this work, and what drives them? How do they live and what tools do they use? What do they worry about and what do they dream about? To enhance the sense of “placeness” of the six research locations—to fully realize the metaphor of the field trip—the Web site is designed to create a sensory experience through an extensive collection of visual images (taken by photographic artists). These images include the broad landscape

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of the site—through aerial photos, manipulateable 360-degree views of the facilities, and maps highlighting the scientific instrumentation and laboratories. They also include peeks into the nooks and crannies, the behind the scenes, close ups on a scientist’s hand holding a beetle, or on the scribbled notes in a field notebook. These images create an aesthetic and textural sense of place that is then organized into structures that underscore the humanness of the endeavor. Images on the Cold Spring Harbor site are organized like Polaroids pinned to a bulletin board, each a snapshot memory of a trip abroad. Clicking on an image takes the visitor to an interview, a quote, some insight into the science or the scientific discussions taking place at Cold Spring Harbor. Building on another human metaphor, the Las Cuevas images and text are situated in a lined notebook that includes hand scribbled side notes, and links and references to other “pages” in the book. In all of these and other constructs, the human beings engaged in the work, or their scientific forebears, are highlighted, interviewed, photographed, and quoted. We meet scientists and technicians, cooks, and guides. Like an exhibit floor, this approach to the material and the Web site creates a populated landscape of choices, objects, faces, and ideas. It allows visitors first-hand, if virtual, encounters with a rich tableau of science and scientists and a variety of scientific activities. It creates contexts for understanding how different experiments or research teams interrelate, and what the meaning of their work may be. In some ways it is less playful or whimsical than the museum floor experience—geared as it is to a highly literate, older audience. (Although whimsy is highlighted as it is encountered.) Yet it affords a fundamentally personal journey, driven by what intrigues the visitor, which may be one of the fortunate confluences of Internet-based learning and museum-based learning.

Participation structures. The Web is uniquely suited, through its variety of media-based entry points, to make the journey into a complex environment (such as cutting edge scientific research) a compelling one. The mix of text, photos, video clips, sound, layered images, branching data sets, and Web design tools that can show movement, time, and dimension, creates a huge number of possibilities for how to approach the subject matter, and (in this case) the place, ideas, and tools surrounding the research. Unbounded by the temporal or spatial constraints of the museum visit, these resources, interviews and “field trips” are available for personalized, directed, or exhaustive Web visits that can unfold over time in ways that a museum visit could never provide for. In a rich Web site like Origins, where there are scores of layers of information and images, the subjective feeling of being able to meander along pathways of one’s own choosing, creates a sense of infinite choice and the feeling of personalizing one’s journey—of following one’s own interests and looking more deeply into the thing that catches one’s eye. This sense of choice, as well as sudden encounters with new ideas and images, parallels the personal experiences one has on the museum floor in choosing pathways and engaging directly with phenomena. But unlike the museum experience, this journey is undertaken alone, albeit in collaboration (or complicity) with the Web site curators, educators and developers. This is a difficult transition for museum educators—steeped in a social environment and culture designed to support social interactions—to grapple with. To experiment with social interactions and different kinds of participation structures for Internet visitors, the Origins team soon began to experiment with how emergent webcast technologies could be used to create more discussion and collaboration among visitors. Over the course of the project, the team developed over a hundred live webcast components that

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connected remote scientists at the research labs with live Exploratorium visitor audiences as well as with live Internet audiences. While visitors were less able to interact with each other, they were able to interact directly with scientists at the research sites and at the Exploratorium, through e-mailing questions and observations—and indirectly by following up with questions and comments from previous visitors. These webcasts—a form of broadcasting over the Internet that can be watched live or later retrieved on demand—enabled remote audiences to connect in real time to scientists and activities as they were happening. Mediated by Exploratorium scientists, working before a live audience in the museum’s webcast studio facility, these 30- to 60-minute programs allowed for time-based material to be introduced to both remote viewers and studio audiences. Examples of the most compelling live timebased events were the unveiling of a new Hubble image, looking inside a bat researcher’s bag after a day of collecting, and speaking with scientists at CERN after they announced that they had produced anti-matter. Many such events lose some of their luster when re-packaged into exhibition or magazine/Web site-like entities. They lose their 3-D-ness and they also lose the essential connections to the people involved in the science: the person holding his breath before opening the bag of bats. Webcasts also were structured so that Exploratorium science educators could build and demonstrate, on the museum floor, 3-D models of various events, thus providing visitors with opportunities to conceptualize the location of the Hubble in relationship to the earth and the moon by having educators, holding tennis balls, stand at a distance to one another that represented the distances between the telescope, Earth, and Moon. Audiences were able to predict and direct where the scientists would stand before they moved into position, showing how close the Hubble is in relationship to Earth.

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Thus Origins experimented with ways to mix novices and experts, learners and teachers, through a variety of live interactions. The archival value of these interactions is not clear – in some cases, such as the unveiling of the Hubble, later visitors might be interested in viewing the dated material. In some cases, the webcasts served to create an historical record — interviews with scientists and others engaged in the process of discovery. One day in the future, these video archives may prove a valuable piece of history. But, from the point of view of designing engaging learning experiences, their real value was in the live, unexpected, and interactive format. They allowed people to interact with other people interested in the science, and they also allowed people to interact with significant scientific events in real-time. Such encounters, like chat rooms, and to a lesser degree bulletin boards, begin to suggest active social engagement that allows people to develop new questions or insights not only from the material presented by the museum, but from the ways in which others are engaging with and interpreting that material. Explanatory structures. To encourage visitors to engage with the material, the site seeks to develop explanatory and narrative structures that establish the broader framework into which the individual stories and insights fit. It organizes the material, first, by research site/topic, and, second, by cross-cutting themes of people, places, tools, and ideas. The sites are indexed in ways that will bring them up quickly in a Google search on the specific topic. But it is also anticipated that people who find their way there more serendipitously will be drawn in by the stories of the places and people. The site index is organized to provide visitors with a kind of visual horizon within which they can develop their own pathway. It allows them to “see” what the site has to offer in terms of people to meet, tools to learn about and representations of the science to be explored. It presents the stories

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Figure 4. Site index for Origins allows visitors to navigate either by research location or by topic area. For example visitors to the site may “tour” all of the tools across research locations sampling those used for collecting particle data and those used for sampling biodiversity. Or a visitor may examine each of the locations as a unit. Clicking on an image takes you directly to the that section of the sub-site.

as layered landscapes of people and ideas—vertically, by research enterprise, and horizontally, by human endeavor. It thus creates a context that both makes connections and illuminates pathways. Once you choose a starting point, your path takes you to pages with a plethora of links to new stories and people and questions. One story leads to another story. For example when we click on the question “Why are there so many living things?” in the Las Cuevas site, we meet botanist Nancy Garwood. By clicking on her name, we encounter images of her work in the rain forest, which leads us to links back to London’s Natural History Museum where further research is conducted on the collected specimens. Whole new worlds of visual images and places—from the collection, study, and preservation perspective—are opened up. The narrative in Origins is about the interlinked activities that together make up scientific process, endeavor, and discovery. That the activities are driven by human passion to know and under-

stand, by human obsession with the minute and the cosmological, is at the heart of the narrative. This provides the context for further exploring the science that the site details. The looped nature of the narratives serves in its own way as a pedagogical redundancy. While specific ideas may not be encountered in many forms, in the way that science phenomena are on the museum floor, aspects of the scientific enterprise as a human one are repeatedly revisited. This is done through the complex layering of information and insight—through the branching and looping of the Web site, and through the narrative construct, as described above, of organizing the material in terms of location as well as people, tools, and ideas. Systemic structures. Origins experimented with ways of connecting the science research Web resources to the school system, although it did not develop Web resources specifically for this audience. However, for each research insti-

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tution, the team developed targeted webcasts for specific classroom groups from middle schools or high schools. Classrooms attended these live webcasts as part of a field trip to the museum and interacted beforehand in a special program warm-up. They would then join the live studio audience at the museum during broadcast and have more opportunities to converse with and question scientists at the remote location during the webcast. Teachers would prepare students beforehand by using the Web site or project representatives would visit the classroom. In research we conducted on the outcomes of these experiments, we found that the nature of the live webcast—where many events, some technological, some human—intervened to delay, repurpose, or redirect the transmissions, did not match well with the nature of the K-12 classroom, where teachers have plans and goals for their students. For example, in one case a class was prepared to interact with and ask questions of a particular scientist in Belize. However, due to technical difficulties, the webcast had to be conducted in a one-way stream from Belize to the Exploratorium and the Internet. This was an important learning experience for us, and has redirected our examination of the material for K-12 audiences away from webcasts (as a live event) and toward webcasts as archived resource material along with other Web site resources. The live event of the webcast is inherently opportunistic and open-ended, and cannot easily be slotted into a prescribed curriculum. On the other hand, when the technology worked—as with our webcasts of a scientist at the Licancabur Volcano in Chile—the webcast allowed students opportunities, and a sense of excitement—seeing, hearing, and talking with somebody who they had previously only read about—that traditional means of communication (letters, books) would not. In the Chilean instance, a collaboration with a professional development program called Project ARISE focusing on “research at the extremes,” students were

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able to interact directly with a scientist whose work they had been studying for two years. In addition to these interactions, Exploratorium science educators developed a series of teacher professional development workshops for Project ARISE, building on the science from Origins to support the program and its teachers. This connection between schools and science research, and the mediating role that places like the Exploratorium can play, is an area we continue to grapple with. For the Mars Rover Web site, we developed a series of hands-on classroom activities to support teacher use of the resource. We intend to do the same, post-hoc, for Origins. The other system that the Web site may allow cultural institutions to tap into is the system of scientific conferences. The Exploratorium has had some experience webcasting conferences and meetings from Cold Spring Harbor, and has expanded this way of connecting a system of scientific enterprise—through conferences such as the annual American Association for the Advancement of Science, or the American Geophysicists Union annual meeting.

Interpreting Current Research: Global Climate Change Research Explorer The Exploratorium’s Global Climate Change Web site (www.exploratorium.edu/climate) offers another approach to science learning in a Web environment by exploring the potential of using the Web to provide access to and insight into the world of research through a very current and somewhat (in the U.S.) politically controversial topic: global climate change. The study of the phenomenon of global climate change involves a variety of scientific disciplines. Data featured on the site are organized into four research areas: Atmosphere, Hydrosphere, Cryosphere, and Biosphere. Data are mostly short-term or near real-time—meaning constantly current—with some long-term data

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Figure 5. Home page of the Global Climate Change Research Explorer. Animation displays the variety of data accessible through the site. In this example the cryosphere is shown.

where available. The data come from a variety of institutions, including the Massachusetts Institute of Technology, University of Wisconsin, Florida State University, Boston University, the National Science Foundation, NASA, and the National Weather Service. Deep linking to data ensures regular updates of the site. Each data set is accompanied by analysis and commentary about the data collection methodologies and the implications for climate change. A comprehensive selection of links allows visitors to access the source of data and search in areas of interest. The Global Climate Change Web site allowed the Exploratorium to experiment with the mediation of complex, text-heavy, value-laden science by bringing to bear pedagogical approaches inherent

in the museum floor. These principles include both isolating (in the instantiation of one exhibit or one visual graph) and contextualizing (within an exhibit collection or a Web page) the phenomena. They also include building visual representations of complex ideas, and providing accessible explanatory texts to support learners. Learning design. The Global Climate Change Web site approaches the subject of global climate change in two ways. First, it provides visitors with first-hand experiences with the data themselves. Second, it stresses the inter-relatedness and complexity of the data, measures, and interpretations—and how scientists accrue these different data to suggest trends and probabilities. It thus provides Web visitors with experiences (the data) that provide a context for understanding the di-

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lemmas facing scientists. In so doing, it provides insights into the scientific process of trying to understand a complex phenomenon. Understanding global climate change involves examining and interpreting a wide range of data sets within many different disciplines. In addition to an introductory text, the site is divided into five sections—one for each of the four “spheres” (hydro, atmo, bio, and cryo), and one that focuses on overall effects of changes in these spheres. In each section, visitors can explore data collected in the study of one of these spheres. The site represents this complex array of data through a series of images, graphs, charts, and maps, accompanied by explanatory texts. This highly visual environment is designed, like an exhibit floor, to offer the visitor a variety of visual prompts and choices that effectively break down the complexities of this topic into bite-sized pieces. Links lead to more detailed descriptions and data, as well as to other research domains found on the site. Like scientists engaged in understanding global climate change, visitors soon understand that the science is highly inter-related. For example, data in the biosphere section show how coral systems are being impacted by increased seawater temperatures, which are represented in data found in the hydrosphere section. In the cryosphere section, data exploring decreasing ice mass is linked to changes in water levels explored in the hydrosphere section. The visitor comes to understand that in a complex system like climate, evidence must be assembled slowly and carefully, and pieced together to form a picture of the whole. Participatory structures. The site is developed in ways that allow for wide-ranging navigation and an egalitarian approach to what is important to notice or know. Like a browser in a library or in a museum, visitors to the Global Climate Change site are confronted with a large number of possibilities and choices, indexed in

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ways that allow personal interests or proclivities to control the learning. No one “sphere” is deemed more important to examine than another. No one piece of data takes precedence over another. Although each page has an explanatory text that provides an overview to the data, the text does not dominate the page, but is placed in a column on the left-hand side. The dominant images are the colorful series of visual representations of the data. The learner can decide where to start—with images and data, or with context and narrative. Drawn to an image, caption, or headline, visitors can click on screen items and go deeper into the subject matter. Or they can go back. Information is layered in ways that inquiry-rich exhibits might be layered, with ever deepening possibilities. As new questions are raised, new links lead to new answers or consideration of the questions. Although they can’t observe the learning of others, the materials are organized in ways that allow the visitor to observe the many different directions that science and scientists themselves are taking in order to better understand the science of climate change. They can observe on the Hydrosphere page, for example, that there is being data collected on sea temperatures, sea currents, and precipitation. And that this relates to the data being collected in the Cryosphere related to ice on the earth’s surface, and measurements of glacier growth or decline. Thus, there may be something about the Web environment that allows visitors not to participate with their peer and family groups, as a museum environment does, but rather with an enterprise, such as scientific research. Museums also seek to do this in their physical spaces, but the Web may be more effective in engaging people socially with the social and cultural products and processes of a field or discipline. There is also a mediated environment for posing questions, where visitors can ask questions about a specific data set, and get responses from Exploratorium staff, who consult with science advisors, as required.

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Figure 6. The e-mail form for submitting questions about one of the atmospheric data sets

Explanatory structures. The Web site is structured to not only share or explain the process of scientists grappling with complex questions and systems, but in fact to allow visitors to engage in that process themselves in order to better understand both the science and the scientific investigation of global climate change. In essence, the Web site is structured to support a visitor’s trajectory through the processes of starting from curiosity or a question, moving to the selection and examination (although not the collection) of data, to considering (through mediation provided by texts as well as the data) the evidence, to thinking about predictions—how one would make them, what they might be. Within this overarching explanatory framework, the Global Climate Change Web site seeks to make the complexities manageable, as well as compelling. The site has an extensive six pages of text introducing the visitor to the big picture, and the questions that are being asked. The Exploratorium’s decades of experience making science, including scientific research, accessible

and digestible mean that even in the more formal and didactic narratives, the tone and the terms are carefully made accessible to audiences of many ages and levels of prior knowledge. Each page has a glossary section (which can be printed in toto) that gives definitions for words ranging from anomaly to phenology. Each of the four “sphere” sections is organized into “what we know” and “what we don’t know.” The “what we know” section is the data, presented in visual as well as textual form. The “what we don’t know” is generally text that considers the evidence (from the what we know part) and the uncertainties that confront the scientific community, as well as the society in general, in interpreting the data. The narrative thus allows the learner to experience and consider the processes of science—of trying to make sense of a mass of data, from a variety of sources, to consider the uncertainties, and to think about what types of predictions are possible. A section called Global Effects looks at the results of the data in the four “spheres” and

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explores how scientists go about predicting global climate change. The site also reinforces an understanding of science as data-driven. By taking different looks at different elements—not only at the cryosphere and the biosphere, but also at the golden toad and the polar bear—scientists piece together their best understanding, explanations, and predictions of the world they are investigating. Systemic structures. There were no specific efforts to link this site to K-12 science education. However, in online user surveys, 44% of respondents stated that they were teachers, professional developers, or students. The site is so data rich that it can serve as a dynamic (albeit upper grades) textbook for studies of the environment, as well as of specific topics or subjects. Like with Origins, we have assembled a team of staff to think about ways in which we can make these resources accessible and used by school audiences.

CONCLUSION This examination of two Exploratorium Web sites, Origins and Global Climate Change, point out perhaps that many of our approaches to the learning design—which fundamentally involve humanizing science and the process of science (whether it means using common materials like sand in exhibits or putting faces and names to the researchers exploring the ends of the earth)—can cross the boundaries between physical and virtual. While the hands-on nature of the presentation is slightly different, in that it is not tactile, clearly it can be hands-on, including use of online exhibits where people can manipulate variables with keystrokes instead of with buttons or levers. While Web-based participation structures are by definition less social in nature — in that it is currently much more common to travel alone when

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visiting Web sites than it is when visiting museums—they need not be any less learner-driven. Indeed the choices are manifestly greater with the Web’s ability to link to a myriad other ideas or places. Rather than building on local social groupings, the Web may offer a greater connection between the learner and the designer or the learner and the cultural products of science and scientists—creating new inroads and insights into the world of science that is different than what can be provided in a museum, but perhaps no less important. In time, talk of networked learners and distributed learning environments may become more real than projected, and may even begin to reach across the socio-economic ranks to include a broad array of learners. Explanations offered through Web-based media can go far deeper and far wider than what can commonly be offered in physical environments. The explosion of space and time, in that the learner can spend hours and hours—in one sitting or stretched over multiple visits—interacting with enormous quantities of ideas and people is substantially different, and is an important way in which people learn, augmenting the vital socially dynamic relationships that people have learning with other people in shared physical environments and discourse. Because they are predominantly text-dependent, these sites currently operate best for more advanced learners, more literate learners, and, in these two cases, English language speakers. However, there is much work underway to explore how to expand Web-based explanatory structures to be compelling and non-text dependent, and there are plenty of examples of powerful Web sites that do this—although perhaps not so many that do this in science and get to core science content or process domains. As explored above, the connection of the Web resources into systemic structures continues to challenge us. Is it enough to build it and let them (whoever “them” may be) come? This is of great interest to the Center for Informal Learning and Schools. Many cultural institutions have been

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built by the ideas and work of groups of creative, rather iconoclastic and independent thinkers. This may (or may not) be truer for the younger field of science centers. It may be especially true for new media designers working in science centers! For many of these thinkers and designers, schools represent a stifling approach to learning. Thus, engaging them in designing for school audiences and uses is not easy. On the other hand, as I hope this chapter begins to suggest, the learning designs that these creative iconoclasts can build in the Web environment may be tremendously powerful learning tools—especially for kids who don’t come to museums, and who might not naturally seek out science resources on the Web. With the iconoclasm often comes a sense of egalitarianism, but schools—despite the fact that they are our communities’ most ubiquitous and democratic institutions—fail to be perceived as such by most of us. Schools are an important audience for cultural institutions (Delacote, 2003). Working with schools is one way in which a museum can pay attention to issues of access and equity for its community’s citizenry. It may be the beginning of a long-term relationship with future adults. It may support the nature of how schools think about and present knowledge and experience related to the field (Bevan, 2002). For these reasons, thinking about how schools use our resources is important for cultural institutions to grapple with, including the use of Web resources. Like museums, which are designed for public audiences, these Web resources may be designed for the general public of all ages, but we may need to think about specific ways in which to adapt or mediate the virtual environments so that they can be accessed and used by school audiences (teachers and students). It is useful to think about the special tools, guides, and docents that many museums provide for field trip visitors. These facilitators seek to augment and/or focus the museum experience in ways that can reinforce school learning goals.

In addition to better understanding how the field trip is incorporated into the school experience—what attributes of engaging with scientific phenomena, the process of inquiry, and learning science support the content goals of schools, and how?—we need to examine how virtual resources, designed by museums, can similarly move beyond the straight content goals of many K-12 and commercial Web resources to examine how we can support student understanding of the nature and processes of science, and build motivation to learn more about science. By building on what we do best—which includes but goes beyond science content knowledge and encompasses developing understandings of the epistemology and nature of the subject matter — cultural institutions can play an important role and fill a niche in supporting science learning in K-12 and beyond.

REFERENCES Bevan, B. (2002). Windows onto worlds. In J. Amdur-Spitz & M. Thom (Eds.), Urban network: Museums embracing communities. Chicago: The Field Museum. Bevan, B., & Wanner, N. (2003). Science centre on a screen. International Journal of Technology Management, 25(5), 371-380. Crowley, K., & Callanan, M.A. (1998). Identifying and supporting shared scientific reasoning in parent-child interactions. Journal of Museum Education, 23, 12-17. Delacote, G. (2003). Apoptosis: The way for science centres to thrive. International Journal of Technology Management, 25(5), 371-380. Duensing, S. (2004). Culture matters: Informal science centers and cultural contexts. In Learning in places: The informal education reader. New York: Peter Lang Publishers.

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Hein, G. (1998). Learning in the museum. London: Routledge. Hein, G. (in press). John Dewey and museums. Curator. Lee, C. (2001). Is October Brown Chinese? A cultural modeling activity system for underachieving students. American Educational Research Journal, 38(1), 97-141. National Research Council and the Institute of Medicine. (2004). Engaging schools: Fostering high school students’ motivation to learn. Committee on Increasing High School Students’ Engagement and Motivation to Learn. Board on Children Youth, and Families, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press. Osborne, J. (2000). Science for citizenship. In M. Monk & J. Osborne (Eds.), Good practices in science teaching: What research has to say. Buckingham, UK: Open University Press. Osborne, J. (2004). What “Ideas-about-Science” should be taught in school science? A Delphi study of the expert community. Journal of Research in Science Teaching, 40, 692-720.

Rogoff, B., Paradise, R., Mejia Arauz, R., CorreaChavez, M., & Angelillo, C. (2003). Firsthand learning through intent participation. Annual Review of Psychology. Schauble, L., Leinhardt, G., & Martin, L. (1997). A framework for organizing a cumulative research agenda in informal learning contexts. Journal of Museum Education, 22(2&3). Semper, R.J. (1996). The importance of place. In About learning: A field guide for museums (pp. 3-8). Association of Science-Technology Centers Newsletter. Washington, DC: ASTC.

ENDNOTE 1

CILS is funded through the U.S. National Science Foundation as one of 13 Centers for Learning and Teaching, each of which is funded to address some critical aspect of the national education infrastructure in K-12 science and mathematics. CILS is the only center to focus on informal learning. Other centers focus on issues such as student assessment, rural education, equity in education, mathematics curriculum, technology integration, etc.

This work was previously published in E-Learning and Virtual Science Centers, edited by R. Subramaniam and L. Tan, pp. 68-92, copyright 2005 by Information Science Publishing (an imprint of IGI Global).

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Frameworks for CMS Design and Evaluation Marwin Britto Central Washington University, USA

ABSTRACT In recent years, institutions of higher education have been migrating to the Web for instruction in record numbers. While Web-based course management systems (CMS) offer many exciting possibilities for instructors and students, their efficacy in terms of teaching and learning has not been thoroughly evaluated. This chapter explores the inherent capabilities and limitations of five models of conceptual frameworks for the design of CMS. The chapter concludes with a discussion of CMS evaluation instruments, advice for instructors transitioning to CMS, and a call for more research in this growing area.

INTRODUCTION The next big killer application for the Internet is going to be education. Education over the Internet

is going to be so big it is going to make e-mail usage look like a rounding error. (John Chambers, reported by Friedman, 1999, p. A25) John Chambers, the chief executive officer of Cisco Systems, made this prophetic statement six years ago. Although his prediction has not yet come to be in any sector of education, there has certainly been movement in this direction in higher education. The use of the Internet to deliver instruction at all levels of education has increased steadily from the beginnings of the Web but has recently exploded partly due to the advent and proliferation of CMS in the last few years. Part of the popularity of CMS is due to the simplicity with which instructors can create and deliver digital content online, administer tests online, manage student data, engage students in interactive activities, and provide opportunities for students to participate in meaningful asynchronous and real-time conversations without

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Frameworks for CMS Design and Evaluation

needing knowledge of programming or Web development skills. Over the years, a number of frameworks have emerged to guide the design of CMS. A few models have been borrowed from other fields, others have new roots, and there may be others still that have value and potential in consideration for CMS design. The fourth wave of CMS (Boettcher, 2003) spurred by the formation of the Open Knowledge Initiative (OKI) boasts even more design standards and flexibility, and future generations of CMS hold even greater design promises as described in other chapters in this book. The combination of escalating costs and increasing use of CMS has renewed interest in examining the return on investments (ROI) issue as university administrators search for solid evidence to justify and support their decisions to invest so heavily in CMS. These significant instructional costs have helped focus attention on the important question: How effective are CMS in impacting teaching and learning? In turn, these costs have also sparked some research in the development of CMS evaluation instruments. One of the reasons for a paucity of research in CMS evaluation instruments may be the absence of robust theory and rigorous research in Webbased instruction (WBI) and the resulting lack of appropriate WBI models on which to base these instruments. As a result, educators and researchers have turned to other sources, borrowing and adapting existing research and models for use in this context. This chapter explores conceptual frameworks for the design and evaluation of CMS. In addition, it provides examples of how these frameworks can be used to support instructional activities in course management systems. It is important to note that the CMS tools that are listed in this chapter as supporting components of each model are not meant to represent an exclusive list, nor do they necessarily support model components as is suggested. Ultimately, the manner and strategy in which each of the CMS tools are employed will determine how effectively they

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will support and facilitate various components of each model.

INTERACTIVE LEARNING DIMENSIONS MODEL To help guide research in the design and evaluation of WBI in CMS, a more comprehensive and richer understanding of Web-supported interactive learning dimensions is needed. To address this need, Reeves and Reeves (1997) proposed a model that describes ten pedagogical dimensions that the Web can support (Figure 1). The authors have grounded and couched the dimensions in research, theory, and literature from the domains of adult learning, cognitive science, and instructional technology. In addition, the authors provide examples of the dimensions with respect to WBI. In this model, each dimension is represented on a two-ended continuum, with contrasting values at either end. Although Reeves and Reeves (1997) acknowledge that the set of pedagogical dimensions in this model is not exhaustive, they suggest their model can serve as the foundation for constructing an instrument that can be employed in studies of the effectiveness and impact of WBI. Ultimately, the effectiveness of WBI in CMS is a function of the degree to which it supports appropriate pedagogical dimensions since these dimensions—rather than the technological aspects of the Web—influence learning most directly (Clark, 1994; Reeves & Reeves, 1997; Reeves, 2000).

THE INTERACTIVE LEARNING DIMENSIONS MODEL SUPPORTED IN CMS According to Reeves and Reeves (1997), the location of a learning environment on any individual dimension is not as important as the overall profile

Frameworks for CMS Design and Evaluation

Figure 1. A model of WWW interactive learning dimensions (Source: Reeves & Reeves, 1997) Instructivist Constructivist Behavioral Cognitive Sharply Focused General Academic Authentic Extrinsic Intrinsic Didactic Facilitative Unsupported Integrated Unsupported Integral Insensitive Respectful Fixed Open

Pedagogical Philosophy Learning Theory Goal Orientation Task Orientation Source of Motivation Teacher Role Metacognitive Support Collaborative Learning Strategies Cultural Sensitivity Structural Flexibility

of the environment across all ten dimensions (Figure 2). The latter is intended to represent the overall pedagogical or instructional design and can be used for course comparison purposes. The specific application of CMS tools determines at what points on the continuum each learning dimension is addressed. It proves challenging to map specific CMS tools to various dimensions due in part to the nature of the learning dimensions and the flexible nature of the tools capable of being adapted and utilized in a variety of ways, often even in opposite ways (i.e., supporting opposite ends of a learning dimension continuum). The choice of tools used in a CMS also directly addresses which learning dimen-

sions can be supported and facilitated. Figure 2 provides an example of two courses using this model. The numbers 1 through 5 are provided as reference points along each learning dimension continuum. In this example, the CMS tools in Course A support a mix of instructivist and constructivist perspectives in contrast to CMS tools in Course B, which are employed strictly in a constructivist design fashion. The choice and the implementation of tools in each course can radically impact the pedagogical and instructional design of courses. The use of this model also has implications in evaluation, although to date no such reliable or validated evaluation instrument based on this model exists.

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Figure 2. Comparing two courses using the interactive learning dimensions model (Instructivist) (Behavioral) (Focused) (Academic) (Extrinsic) (Didactic) (Unsupported) (Unsupported) (Insensitive) (Fixed)

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Another useful framework in this area is Chickering and Gamson’s (1987) “Seven principles for good practice in undergraduate education,” which is based on their review of 50 years of research on teaching and learning in higher education. Their work has been applied to the online environment both as a framework for evaluative research and for design of WBI in CMS. These seven principles are those teaching practices that (1) encourage student-faculty contact, (2) encourage cooperation among students, (3) encourage active learning, (4) give prompt feedback, (5) emphasize time on task, (6) communicate high expectations, and (7) respect diverse talents and ways of learning.

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(Cognitive) (General) (Authentic) (Intrinsic) (Facilitative) (Integrated) (Integral) (Respectful) (Open)

Nine years later Chickering and Ehrmann (1996), recognizing the potential for the newer technologies to support these principles, published an article describing how technologies can be leveraged to advance these seven principles. WebCT, Inc. adopted Chickering and Gamson’s seven principles as the framework for training clients on its CMS and as part of the curriculum for some of its workshops designed to teach faculty and support personnel about effective WebCT use. WebCT provides a table of CMS tools (www.webct.com/WYW/ ViewContent?contentID=2627458) and describes how each of them could be used to support these various principles. Graham, Cagiltay, Lim, Craner, and Duffy (2001) used Chickering and Gamson’s seven

Frameworks for CMS Design and Evaluation

principles as a framework to evaluate four online courses at a large Midwestern university. Their analysis was focused on online course materials, student and instructor discussion forum postings, and faculty interviews. The evaluators found examples of each of the seven principles in the four courses. Based on their observations and analysis of the particular principle in each course, the evaluators offered “lessons learned” and recommendations on how each principle could be best supported in an online environment. Though qualitative in nature, the four case studies provided useful insights into the evaluation team and for others exploring this model.

The Good Teaching Principles Model Supported in CMS WebCT provides a table of examples of how CMS tools can be used to support these seven principles and lists the principles the various tools can support (see www.webct.com/WYW/ ViewContent?contentID=2627458). Figure 3 shows an example of one tool, the discussions tool, as an example of tool use and the good teaching principle it supports. This “mapping” of CMS tools to specific principles provides a useful resource for faculty when designing instruction. By first deciding on the principles they wish to support in their CMS course, and then choosing appropriate CMS tools (that support these principles) to facilitate the relevant instructional activities and implementing them appropriately, faculty can utilize this table as a practical guide in the instructional design of their courses.

framework to design and implement their Webbased undergraduate educational psychology course. Wagner and McCombs (1995) devised these 14 principles in an attempt to identify and describe what they called “learner-centered educational practice.” According to the APA, the principles are “consistent with more than a century of research on teaching and learning… and…integrate research and practice in various areas of psychology, including developmental, educational, experimental, social, clinical, organizational, community and school psychology” (1997, p.1). These 14 principles are: Cognitive and metacognitive factors: 1. 2. 3. 4. 5. 6.

Nature of the learning process. Goals of the learning process. Construction of knowledge. Strategic thinking. Thinking about thinking. Context of learning.

Motivational and affective factors: 7. 8. 9.

Motivational and emotional influences on learning. Intrinsic motivation to learn. Effects of motivation on effort.

Developmental and social factors: 10. Developmental influences on learning. 11. Social influences on learning. Individual differences factors:

LEARNER PEDAGOGICAL DIMENSIONS MODEL

12. Individual differences in learning. 13. Learning and diversity. 14. Standards and assessment.

Bonk and Cummings (1998) used the 14 learnercentered principles (LCPs) from the American Psychological Association, or APA (1997), as a

Based on their experiences teaching this Web course, as well as feedback from student formative and summative evaluations, Bonk and

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Cummings adapted the 14 principles and proposed 12 pedagogical recommendations. These recommendations connect WBI to the 14 LCPs and are designed to “foster student thinking skills, problem solving abilities, teamwork and social interaction and debate” within an online environment (1998, p. 82). These 12 learner-centered pedagogical recommendations include: Establish a safe environment and a sense of community. 2. Exploit the potential of the medium for deeper student engagement. 3. Let there be choice. 4. Facilitate, don’t dictate. 5. Use public and private forums of feedback. 6. Vary the forms of electronic mentoring and apprenticeship. 7. Employ recursive assignments that build personal knowledge. 8. Vary the forms of electronic writing, reflection, and other pedagogical activities. 9. Use student Web explorations to enhance course content. 10. Provide clear expectations and prompt task structuring. 11. Embed thinking skill and portfolio assessment as an integral part of Web assignments. 12. Look for ways to personalize the Web experience. 1.

Bonk and Cummings provide explanations and examples of each of these recommendations in a Web-based environment.

The Learner Pedagogical Dimensions Model Supported in CMS The tools in Figure 4, when implemented appropriately, have the potential of supporting the 12 pedagogical dimensions as described by Bonk

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and Cummings (1998). This is not meant to be an exhaustive list—other CMS tools may be useful to this end contingent on the instructional activity.

QUALITIES OF MEANINGFUL LEARNING MODELS Jonassen (1995) identified and described seven characteristics or qualities of meaningful learning. Jonassen saw technology as a means to support these qualities through various activities that would engage the learners in meaningful conversation. He described these qualities as “interrelated, interactive, and interdependent” (p.61) and used the model in Figure 5 to convey these relationships. Figure 6 presents this same information in table format. LeJeune and Richardson (1998) view good instruction as being grounded in educational theory regardless of the context, content, or technology used to deliver the instruction. They assert that effective WBI must be couched in traditional learning theories. Their model for WBI is based on Jonasson’s seven qualities, which they refer to as learning strategies. Lejeune and Richardson describe each learning strategy’s origins in theory and research, tying them each to complementary learning theories. In addition, the authors extend these strategies to the Web, employing research on Web-based instruction to discuss effective implementation. Their article offers a practical tool for those looking to adapt Jonassen’s model for WBI.

The Qualities of the Meaningful Learning Model Supported in CMS Although there are multiple ways of supporting this model with a CMS (as with any of the other models in this chapter), the most practical approach is to provide a mapping of specific tools to model components. Figure 7 lists a number of the tools that, when implemented effectively, can be used

Frameworks for CMS Design and Evaluation

Figure 3. The discussions tool and the good teaching principles model. WebCT Tool

Discussions

How the Tool Is Being Used “I have an attendance forum where the online students are required to post a brief ‘attendance’ message each week. I have a public forum for each major topic we cover in the course and I require the students to post a certain number of messages and/or replies to these forums. For example, I might have a forum called ‘Societal Issues and the Internet’ where students can post their thoughts on legal and ethical issues, or post information about articles they have read that are related to the topic.”

to support the seven qualities or key learning strategies in this meaningful learning model.

THE wEB-BASED COURSE DESIGN MODEL Campbell (n.d.) offers six conceptual frameworks for the design of Web-based instructional environments (Figure 8). The frameworks are based on a constructivist perspective and employ a variety of cognitive instructional strategies/learning theories. The author describes appropriate applications of the framework and provides URLs of real examples of Web-designed instruction based on these frameworks.

The web-Based Course Design Model Supported in CMS Figure 9 lists the six frameworks in this model, the media elements for each framework, and the various CMS tools that can be used to support them.

Good Teaching Principles the Tool Facilitates • Faculty-student interaction • Student-student interaction • Rich, rapid feedback • Active learning • Respect for diverse learning

Transitioning from the Traditional Mode to wBI in CMS Regardless of the model adopted, faculty generally proceed through “stages of development” from a traditional environment to the Web. This transition may be unconscious and undeliberate. Studies have indicated that the CMS tools and the CMS environment may be directly responsible in facilitating this transitionary process. Dabbagh and Schmitt (1998) examined the pedagogical implications of redesigning instruction for Web-based delivery through a case study of an undergraduate computer science course originally designed for a traditional learning environment but later transformed to a Web-based course. Dabbagh and Schmitt concluded that the components and tools of their CMS and the attributes of the Web-based environment and tools encouraged and afforded instructional events and activities that were not possible or perceived in a traditional mode. They use three terms to describe these instructional activities: “generative development” through the posting of drafts and focused discussions, “facilitation” evidenced

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through asynchronous tools such as e-mail and threaded electronic discussion boards, and “inside collaboration” demonstrated through online group work supported through a variety of tools. The authors reported that the use of their CMS enabled learning strategies and instructional methods that transformed the course from an instructivist orientation to a constructivist one. Collis (1997) refers to this transformative process as “pedagogical re-engineering.” Collis recommends a “pedagogical re-engineering” approach to WBI that capitalizes on the unique affordances of the Web to change the profile of learning activities and provide new learning opportunities focused on a more collaborative and learner-centered perspective. Freeman and Abeygunawardena (2002) also provide evidence of this type of transformation with the transition to CMS. Their study examined how a CMS was used by instructors as a supplement to classroom instruction. Their goal was to evaluate whether the availability of Webbased tools influenced instructors’ pedagogical practices in undergraduate education. The study involved 15 instructors in 19 courses with 828 undergraduate students participating. The authors employed a mixed methodology using semistructured interviews and surveys with faculty and anonymous surveys with students. Faculty interviews revealed that: Their decision to use WebCT™ and the subsequent choices they made in how to use the tools was guided not by pedagogical need but by the perception of possible gains in administrative efficiency…instructors did not intentionally adapt their pedagogical choices to the opportunities afforded by Web-based instructional tools. (p. 8) Student responses to open-ended questions and anecdotal conversations with faculty suggested that the addition of Web-based tools was causing changes in the learning environment; instructors were discovering new ways of distributing teach-

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ing time and students in these courses were taking more responsibility for their learning. In a similarly purposed study involving interviews, logs, and surveys of more than 730 faculty and instructional staff throughout the University of Wisconsin system using course management systems for teaching, Morgan (2003) found evidence to support that faculty often unintentionally do rethink their course instruction and their instructional context, resulting in an “accidental pedagogy.” Similar studies have found that although many faculty initially choose to use CMS for reasons other than pedagogy (convenience, administrative advantages, better course organization, etc.), with continued use, some faculty change their methods of teaching and online pedagogy as a direct result of their experience in CMS (Britto, 2002; Freeman & Abeygunawardena, 2002; Morgan, 2003).

SUMMARY OF MODELS Five models have been presented in this chapter for design and evaluation considerations. It is clear the sophistication and flexibility of CMS afford a myriad of instructional and learning possibilities. Research is emerging that indicates that the World Wide Web is technically capable of supporting virtually any instructional strategy and is wellsuited to being utilized as a powerful cognitive tool in a variety of learning activities (Lajoie, 2000). Mounting evidence also shows that the unique attributes of the Web offer unparalleled instructional advantages and opportunities (Aggarwal, 2000). However, shaping and designing CMS to support appropriate instructional methods and strategies is often a complex task. There are no guidelines, cookbooks, or shortcuts to quickly or easily create the appropriate learning environment. The instructor needs to fully understand the inherent capabilities and limitations of CMS in order to effectively design instruction in these systems. Many contend that CMS, like other in-

Frameworks for CMS Design and Evaluation

structional tools, can be employed effectively or poorly in instruction. The power lies in instructors using CMS to create effective lessons in stimulating learning environments. As Owston states, “the key to promoting improved learning with the Web appears to lie in how effectively the medium is exploited in the teaching and learning situation” (1997, p. 29). Of course, an instructor needs to understand how to design a good learning environment in any context. Sadly, regardless of the design options available, there is evidence to suggest that faculty new to CMS do not carefully or deliberately plan or design their courses differently online—they simply attempt to replicate their traditional classroom and choose tools that align with their traditional instructional strategies (Britto, 2002; Morgan, 2003). As Bonk and Cummings put it, “perhaps the greatest challenge of the Web is to create learning activities that take advantage of the characteristics and assets of the medium, rather than duplicating activities that typify conventional classrooms” (1998, p. 84).

CMS EVALUATION INSTRUMENTS In 1995, Nichols (as reported in Henke, 1997) predicted that “the potential benefit from formulating evaluation methodologies for the Web [for instructional materials] depends on whether or not the Web will become a permanent medium or a passing fad” (p. 1). A passing fad, it is not—no one would argue that use of the Web and CMS is not firmly entrenched and growing in the instructional corridors of higher education. Unfortunately, as Izat, McKinzie, Mize and McCallie (2000) conclude, there is a “dearth of research studies published that offer validated evaluation survey instruments specifically written for World Wide Web–delivered courseware” (p.2). A literature review in 2004 demonstrated that this trend has continued with rare exceptions. Education journals and publications are replete with studies involving the use of CMS in instruc-

tion. Sadly, many of these studies tend to be non-research-oriented focusing more on practical experiences. Most of the studies that focus on the development of new CMS evaluation instruments appear to lack the rigor of appropriate design and research to give any credibility or usefulness to their instruments, making their results and findings highly suspect. Better and more rigorous research in CMS studies is urgently needed. Scholars have described how CMS have been and can be harnessed to support a variety of pedagogical philosophies and teaching and learning styles, how to design instruction appropriately and effectively in these environments, and how CMS can be integrated into instruction in a number of ways and at a number of levels using a variety of instructional methods and strategies. However, it is still not clear how each choice and the combination of these choices impacts student learning and how these results can be evaluated. Clearly, more evaluative research of CMS is warranted. Unfortunately, evaluation models of CMS are in great demand but in short supply.

CONCLUSION Despite enormous resources committed to CMS in higher education, there is a dearth of information concerning its effectiveness and impacts on how faculty members teach and what students learn. Educational institutions have invested and continue to invest heavily in CMS without a clear understanding of its influence on teaching and learning. As the use of CMS in higher education continues to grow at an incredible pace, it becomes imperative that institutions be able to evaluate their effectiveness. As more and more faculty members move into CMS, evaluation needs to be an integral component of the design and planning process. Although there is a great deal of descriptive and anecdotal information concerning CMS in higher education, studies that provide reliable and

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valid information concerning faculty and student perceptions of CMS are relatively rare. One reason for this is the lack of robust, validated evaluation instruments for measuring the implementation of the pedagogical dimensions of CMS. To date, there appears to be a paucity of sound research examining the effectiveness of CMS, due in part to a lack of robust evaluation models and evaluation instruments in WBI that are necessary to aid in the design and development of effective WBI in CMS. Other factors include the relative newness of the field, the broad scope, the diversity and vagueness of WBI, and a lack of unified theoretical framework for WBI evaluation (Yu, n.d.). As CMS continue to grow and flourish in higher education institutions, a concerted and coordinated effort must be made to nurture and cultivate ongoing research directed at exploring, testing, and eventually validating effective CMS evaluation instruments. Furthermore, the evaluation of teaching and learning in CMS must be approached from a multidisciplinary perspective because of the variety of appropriate methodological paradigms in a variety of disciplines that may be beneficial for this type of research (Spires & Estes, 2002). CMS have the potential to influence teaching and learning like no other technology. As CMS continue to improve and evolve, design and evaluation considerations must be a vital part of future developments for this potential to be realized.

REFERENCES Aggarwal, A. (Ed.). (2000). Web-based learning and teaching technologies: Opportunities and challenges. Hershey, PA: Idea Group Publishing. American Psychological Association. (1997). Learner-centered psychological principles: A framework for school redesign and reform.

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Retrieved July 12, 2001, from http://www.apa. org/ed/lcp.html Boettcher, J.V. (2003). Course management systems and learning principles: Getting to know each other. Syllabus. Retrieved November 25, 2003, from http://www.syllabus.com/article. asp?id=7888 Bonk, C.J. & Cummings, J.A. (1998). A dozen recommendations for placing the student at the center of Web-based learning. Educational Media International, 35(2), 82-89. Britto, M. (2002). An exploratory study in the development of a survey instrument to measure the pedagogical dimensions of Web-based instruction. Unpublished doctoral dissertation. Athens, GA: University of Georgia. Campbell, K. (n.d.). The Web: Design for active learning. University of Alberta. Retrieved on July 3, 2001, from http://www.atl.ualberta.ca/articles/ idesign/active1.cfm Chickering, A. W., & Ehrmann, S.C. (1996). Implementing the seven principles: Technology as lever. Retrieved June 12, 2001, from http://www. aahe.org/Bulletin/SevenPrinciples.htm Chickering, A.W. & Gamson, Z.F. (1987). Seven principles for good practice in undergraduate education. AAHE Bulletin, 39(7), 3-7. Clark, R.E. (1994). Media will never influence learning. Educational Technology, Research and Development, 42(2), 21-29. Collis, B. (1997). Pedagogical reengineering: A pedagogical approach to enrichment and redesign with the World Wide Web. Educational Technology Review, 8, 11-15. Dabbagh, N.H., & Schmitt, J. (1998). Redesigning instruction through Web-based course authoring tools. Educational Media International, 35(2), 106-110.

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Freeman, W.E., & Abeygunawardena, H. (2002). Faculty and student reflections on using Web tools to support undergraduate classroom-based instruction across faculties. Proceedings of the American Educational Research Association Conference 2002, New Orleans, LA.

LeJeune, N., & Richardson, K. (1998). Learning theories applied to Web-based instruction. Retrieved February 19, 2001, from http://ouray. cudenver.edu/~nflejeun/doctoralweb/Courses/ EPSY6710 _Learning_Theory/LearningTheories-WBI.htm

Friedman, T.L. (1999). Next, it’s e-ducation. The New York Times, (pp. A25). November 17. Retrieved June 3, 2001, from http://crab.rutgers. edu/~goertzel/e-education.htm

Morgan, G. (2003). Faculty use of course management systems. Boulder, CO: ECAR Research Publication.

Graham, C., Cagiltay, K., Lim, B., Craner, J., & Duffy, T. (2001). Seven principles of effective teaching: A practical lens for evaluating online courses. Retrieved June 18, 2001, from http://horizon.unc. edu/TS/default.asp?show=article&id=839 Green, K.C. (2000). The campus computing project. Retrieved June 01, 2001, from http://www. campuscomputing.net/summaries/2000/index. html Henke, H. (1997). Evaluating Web-based instructional design. Retrieved on June 23, 2001, from http://scis.nova.edu/~henkeh.story1.htm Izat, J.G., McKinzie, L., Mize, C.D., & McCallie, T. (2000). Evaluation of World Wide Web delivered university courseware: Creating an instrument appropriate for a new course delivery medium. In Proceedings of the Society for Information Technology & Teacher Education International Conference, San Diego, FL. Jonnasen, D.H. (1995). Supporting communities of learners with technology: A vision for integrating technology with learning in schools. Educational Technology, 35(4), 60-63. Lajoie, S.P. (Ed.). (2000). Computers as cognitive tools: No more walls (Vol. 2). Mahwah, NJ: Lawrence Erlbaum Associates.

Owston, R.D. (1997). The World Wide Web: A technology to enhance teaching and learning? Educational Researcher, 26(2), 27-33. Reeves, T.C. (2000). Teaching and learning online: Opportunities and responsibilities. Guest Speaker Series at Pathways Colloquia, University of Alberta, Edmonton, Alberta. Available online at http://www.atl.ualberta.ca/pathways/reevesppt. ppt Reeves, T.C. & Reeves, P.M. (1997). Effective dimensions of interactive learning on the World Wide Web. In B.H. Khan (Ed.), Web-based instruction (pp. 59-66). Englewood Cliffs, NJ: Educational Technology Publications. Spires, H.A. & Estes, T.H. (2002). Reading in Web-based learning environments. In C.C. Block & M. Pressley (Eds.). Comprehension instruction: Research-based best practices (pp.115-125). New York: Guilford Press. Wagner, E.D. & McCombs, B.L. (1995). Learnercentered psychological principles in practice: Designs for distance education. Educational Technology, 35(2), 32-35. Yu, A. (n.d.). An input-process-output structural framework for evaluating Web-based instruction. Retrieved July 25, 2002, from http://seamonkey. ed.asu.edu/~alex/teaching/assessment/structure1. html

This work was previously published in Course Management Systems for Learning: Beyond Accidental Pedagogy edited by P. McGee, C. Carmean and A. Jafari, pp. 69-89, copyright 2005 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.42

Educational Software Evaluation Michael Shaughnessy Washington & Jefferson College, USA

INTRODUCTION From 1980 to 2000, there were many articles written on the subject of software review and evaluation. Upon initial investigation of educational software methodologies, it appears that there are as many evaluation methodologies as there are authors presenting them. Several articles (methodology analyses) have been written describing these evaluation techniques (Bryson & Cullen, 1984; Eraut, 1989; Holznagel, 1983; Jones et al., 1999; McDougall & Squires, 1995; Reiser & Kegelmann, 1994, 1996; Russell & Blake, 1988). Each of these articles describes various methodologies and presents the most current evaluation methodology available, but fails to provide a complete history of the types of evaluation methodologies. These analyses of evaluation methodologies focus on the individual methodology, but refrain from putting individual methodologies into a greater systematic context. As new individual methodologies arise over the years, many of these fit into the same “type” categories of evaluation methodology that were previously developed. The author is proposing a type analysis of educational-software evaluation

methodologies. This classification will show that while many evaluation methodologies progress, new methodologies arise that are similar to previously developed theories. This method allows for needed flexibility due to the nonlinear nature of academic research in this field. This chapter proceeds with three types of educational-software evaluation methodologies. 1. 2. 3.

Teacher centered User centered Design centered

TEACHER-CENTERED EVALUATION METHODOLOGIES Guidebooks In 1983, the University of Hawaii conducted a study of educational-software production (Truett, 1984). Over half of the software producers did evaluate their products as a part of the production process, and the major factor in design was teacher evaluation. Since teachers were also the primary consumers, as well as the source of some

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Educational Software Evaluation

opinion about educational-software products, information gathered regarding the opinions of teachers was collected and published. These consumer guidebooks first appeared around 1982. Some of these first guides for educational software were Educational Software Directory: A Subject Guide to Microcomputer Software, The Educational Software Selector, and The Yellow Book: A Parent’s Guide to Teacher-Tested Educational Software. A detailed listing of these published directories of software evaluation is provided by Crovello (1984) in “Evaluation of Educational Software.” The guidebooks were characteristically simple, providing companies’ names and addresses, along with lists of programs divided up by subject area. The target audience was K-12 teachers. These guidebooks provided “objective” information regarding available software, but few provided the means to evaluate the software on one’s own. This lack of individual methods to evaluate software and the predominance of guidebooks as the method for software review created a commercial relationship between software-reviewing bodies and the software companies. Software companies were eager to have their products “teacher tested.” While directories like the Yellow Book, Softwhere, and Facts on File provided educators with listings of educational software, the need for self-evaluation became evident. This need developed into self-evaluation guidelines for teachers.

Guidelines Most educators at this time had little experience with using computers in education, but those who did allowed others to participate by publishing their “method” for evaluation (Weintraub & Thompson, 1985). These first teacher-tip evaluations came in the form of guidelines and checklists. Evaluation guidelines were generally short published articles describing the teacher’s attitudes toward software evaluation. The guidelines developed a

set of principles for use when evaluating educational software, but shied away from providing a definitive quantitative method. In many of these articles, just as with the Yellow Book, technological considerations were placed at the forefront. While these early evaluation guides are independent of each other, they all share similar characteristics. Evaluation guidelines propose a “new” methodology that is directed at teachers. They seek to provide a practical software-selection method for teachers who often have little technical training. But for each of these guidelines, there is a new set of standards. Weintraub and Thompson (1985) propose a three-pronged evaluation theory that focuses on instructional design, format, and documentation. Another shared characteristic of these early evaluation guidelines is the common focus on technology. While the educational aspects and opportunities of the relatively new educational-software programs are a factor, the technological considerations appear to be overwhelming the discussion about software evaluation.

Checklists The individuality of the teacher guidelines prompted other educators to formulate a clearer, more concise approach to evaluation. These first steps toward a methodology came in the form of the evaluation checklist or evaluation form (Caffarella, 1987; Chang & Osguthorpe, 1987; Fetter, 1984; Gorth & Nassif, 1984; Perreault, 1985; Reynolds, 1985; Richards & Fukuzawa, 1989). These forms quickly became the standard in educational-software evaluation due to the lack of an evaluation theory. The checklists were often long and extremely technical, even more so than the guidelines, and they focused heavily on the technical aspects of the software. Many were simply fact-finding checklists to identify the technical aspects of the program including methods of data entry, technical specifications, hardware requirements, methods of scoring, and so forth. Few had

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options for positively or negatively evaluating aspects of the program (Gorth & Nassif). One of the few new aspects in evaluation checklists is the inclusion of educational concerns as main subject headings. Caffarella places the educational goals of the program at the top of the evaluation form, but still dedicates a great deal of the evaluation form to technical considerations. This is similar to Dudley-Marling and Owston’s (1987) proposal of a four-point criterion-based evaluation system, in contrast to the prevailing checklist methods. Their method highlights the following four aspects of the software program. 1. 2. 3. 4.

Pedagogical content Instructional presentation Documentation Technical adequacy

While paying lip service to pedagogy and placing educational concerns at or near the top of their checklists, these checklists were still dominated by technical considerations.

USER-CENTERED METHODS There appears to be a natural tendency for educational-software evaluation methods to move from teacher- to student-based evaluation. The trend in teacher-based evaluation models from the technical to the educational aspects in evaluation led to the natural focus on the subject of education: the student (Reigeluth, 1987). Caldwell (1992, p. 38) cites guidelines stating, “Allowing your students to use the program is the ultimate evaluation. Observe their responses to the program.”

Student Opinions As if responding years earlier to Caldwell’s call for student observation, Miller (1987) dedicates a section of his work Selecting and Implementing Educational Software to student involvement. The

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student evaluation form consists mostly of comment spaces, with three multiple-choice questions regarding students’ opinions and experiences with the program. Student opinion was valued as a way not only to select software, but also to determine important features in the products. Sherman, Divine, and Johnson (1985) conducted a study of 4-year-olds to determine if there were any preferences based on the gender of the child. They stated that there was no significant difference in software preferences based on gender, but that children preferred programs that had “animation, color, closure, reinforcement and sound” (p. 41). Similarly, Smith and Keep (1986) found that children interviewed in England place excitement and audiovisual stimulation at the top of their list of important features in software. Perhaps in the same way that guidebooks were offered to teachers, these opinions were offered to childhood-education specialists to aid in software selection. Callison and Haycock (1988) take student involvement a step further and develop a methodology from student involvement in educationalsoftware evaluation. Their method is based on the following steps. Preview the software. Match student grade level to software difficulty level. 3. Students should have some experience with other software programs. 4. There should be no passive observation. 5. Teachers should not express their opinion. 6. Complete an evaluation for each program. 7. Tabulate group percentage agreement. 8. Involve as many students as possible. 9. Group the evaluations by grade level. 10. Remove evaluations that are not complete or were completed by students who were not actively involved.

1. 2.

Educational Software Evaluation

Students were then expected to express agreement with certain opinion statements. These opinion statements can be modified depending on the evaluation. Student agreement is calculated between the groups and an agreement score of 90% or higher is considered to be significant: “…it’s not until the group agreement reaches 90% that one could definitely say there is a strong opinion from students in support of ‘x’ statement” (Callison & Haycock, 1988, p. 30). The results of a 3year study reflect findings by other student-based surveys. According to Callison and Haycock (p. 26), “‘Helpful graphics’ tended to be associated with high ratings given by the student evaluators.” As previous studies have shown (Borton & Rossett, 1989; Callison, 1987; Papert, 1987), teachers tend to rate the technical side of the program highly. Callison and Haycock’s study reveals that student and teacher evaluation tended not to agree on highly rated programs, but did agree on poorly rated programs. The authors define the importance of student evaluation due to the fact that the software, unlike other instructional materials, is interactive. These attitude studies were the first to show the difference in teacher and student opinions and to hint at a trend that will later be known as usability.

OUTCOME STUDIES The use of and need for quantitative data regarding educational effectiveness goes to the heart of many educational topics, both past and present. Studies that cite quantitative results for evaluating educational software are not uncommon. However, without a method for measuring the effectiveness of educational software, each study creates its own set of variables that could affect the outcome. Without the possibility of transferring information from the effectiveness study to other educational-software products, effectiveness studies are seen to be fundamentally flawed (Decoo, 1984).

Kulik, Kulik, and Cohen’s 1980 article, “Effectiveness of Computer-Based College Teaching: A Meta-Analysis of Findings,” has been cited by almost every author dealing with effectiveness studies. However, the Kulik et al. study focuses on studies of large-scale mainframe computers that were conducted between 1969 and 1978. This study is premicrocomputer and precludes smallscale involvement in classrooms in K-12 education and in small-scale classroom use at universities, which has become the standard. Microcomputer educational-software evaluation was dominated in the 1980s by the teachercentered approaches. As mentioned earlier, these evaluation guidebooks, guidelines, and checklists tended to produce a yes-or-no answer to the question of software recommendation. For many teachers and researchers, the fact that the software program was “recommended” was simply not enough. There were several researchers who called for a departure from these teacher-centered evaluation methods. Muller (1985, p. 27) agreed, “If a program is intended to be educational, it would seem reasonable to conclude that the students should learn when using it.” Muller’s methodology for assessing the effectiveness of educational software is based on traditional educational models for effectiveness studies (Campbell & Stanley, 1963). He employs a pretest-posttest model with groups of students randomly assigned to control and treatment groups, the treatment group being the students experiencing the computer-aided instruction (CAI) and the control group being the students without CAI. These data are compared to a complete group of “treated” students without a control group to see if the difference between control group and treatment group was significant (Muller). Howard Kleinmann’s 1987 study on English as a second language (ESL) reading achievement employed similar methods as laid out by Muller. Treatment and control groups were established and pre- and posttests were given to the students.

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Out of four control groups, three that utilized CAI produced higher scores than those without CAI. Kleinmann (p. 271) comments, “[N]o significant differences between control and treatment groups were found in the gains they achieved.” Both control and treatment groups made gains in reading achievement, but the difference between the CAI and non-CAI groups was not statistically significant for Kleinmann. In an attempt to establish the validity of computer-based instruction, these researchers stumbled onto the no-significance factor in computer-assisted instruction. Prosser (1984), in contrast to Kulik et al. (1980), outlines the nosignificance factor in outcome-based studies for older mainframe computer metastudies. He sees these “small” differences cited by Kulik et al. as being insignificant. Prosser cites several articles that show that 80% of outcome-based studies of instructional technology produce no significant difference from instruction without technology. Tovar and Barker (1986) seek to improve the process of outcome-based studies by improving on the process of field testing. Their conclusions are fairly self-evident: The main purpose of this article was to demonstrate the evaluation design.…we proposed that evaluators should consider designs that: Answer their evaluation question, collect the maximum amount of evidence on which to base conclusion of instructional effectiveness, and take into consideration the practical limitations of the setting in which the evaluation is conducted. (p. 188) In a similar attempt to identify the nature of effectiveness studies, Jolicouer and Berger (1986) take a different approach. They analyze the history and types of outcome-based studies. Their criteria for inclusion in the study are the following. 1.

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The study must have measured the effects of an individual software program.

2. 3.

Performance must have been measured by an objective test. There must have been a control group.

From the list of 47 outcome studies they compiled, they stated, “Only two of the 47 studies…met all requirements for the proposed metaanalysis” (p. 7). Jolicouer and Berger go on to critique current methods of software evaluation. They conducted a study comparing the MicroSIFT and EPIE software-evaluation services. They find that there was little correlation between the two services. They use this data to cite the failure of current evaluation techniques and to call for outcome-based studies: The only way to establish the validity of a system of evaluation for educational software is to demonstrate that highly rated programs do in fact teach academic objectives better and/or faster than lower rated programs. This means that controlled outcome studies are required, whereby gains in academic achievement attributed to the use of specific software can be measured with objective tests. (p. 10) Jolicouer and Berger’s 1988 (1988a, 1988b) two-part follow-up study on effectiveness expands on their earlier conclusions. Whereas previously they showed the miscorrelation between softwareevaluation agencies, their 1988 study highlights a miscorrelation between actual effectiveness and opinions about effectiveness. As with previous user-centered evaluation studies, they surveyed students as to their opinions about the software programs they were using. Simultaneously, they conducted effectiveness studies using the same software programs. They found that the calculated effectiveness of the software programs did not correspond with the students’ perceptions regarding the most effective programs. They concluded:

Educational Software Evaluation

The students were not accurate in their estimates of how much they had learned using the educational software. Since students are not accurate at predicting the educational value of the software, they should not be left on their own to determine the order and parts of a software program they will use. (1988a, 1988b, p. 18) Just as these studies point out that students are not accurate predictors of effectiveness through opinion, Jolicouer and Berger’s study found that teachers were also not accurate predictors of effectiveness in educational software. Gill, Dick, Reiser, and Zahner (1992) cite the differences in student and evaluator perceptions of educationalsoftware effectiveness as the main reason for a new approach to educational-software evaluation. They recognize the importance of student involvement in the evaluation process, but call for “performance data” to rectify the differences in attitude surveys. While Jolicouer and Berger (1986, 1988a, 1988b) conclude that student perceptions are inappropriate when measuring the overall effectiveness of educational software, Gill et al. seek to utilize both sets of data to make a better informed decision in the software-selection process. Gill et al. are, in fact, utilizing user-centered methodologies; they are placing it in the context of teacher-centered methods that seek to provide a yes-or-no answer to the practical question of software adoption: “As more software becomes available, it becomes increasingly important that educators are able to make accurate judgments about the instructional quality of a piece of software before they make a decision to adopt it for use with their students” (p. 39). The Jolicouer and Berger study from 1988, while predating the later Gill et al. (1992) study, is looking toward the future of educational-software evaluation. They seek to answer questions about theoretical issues rather than focusing merely on the practical and technical side of educationalsoftware evaluation. Their study goes to the heart

of the user-centered evaluations and effectiveness studies by stating: If we can measure the academic effectiveness of individual educational-software programs, then we can begin to discover the specific factors that contribute significantly to good and poor quality software. Once successful software factors are identified, educational-software developers can focus on building these factors into all educational software, thus improving the quality of the software. (1988b, p. 13) Educators stopped worrying so much about the technical side and implementation of the software and started concerning themselves with the design and construction of educational software.

DESIGN-CENTERED EVALUATIONS The issue of design is clearly important to educational software, and software producers have been taking evaluation methods into account when designing their software. Academics jumped on the design bandwagon relatively early in the development of microcomputer software. As early as 1984, a major work appeared outlining the issues in educational-software design: Instructional Software: Principles and Perspectives for Design and Use, edited by Walker and Hess. The development of educational-software design criteria mirrors other evaluation-design methods in that several studies place evaluation criteria above all others, thus implying the need for a unique methodology. The belief that the overall effectiveness of the educational-software program can be altered by the manipulation of individual aspects of design is behind the design-centered evaluation movement. Rothe (1983) states that the perspectives of the designers affect the overall educational validity of the software programs. The hidden assump-

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tions and prejudices of programmers and designers affect the “social” categories he cites. Thus, the individual elements and aspects of software development are to be critically examined. Rothe (1983) is an early example of the critique of outcome-based studies. The basic premise behind this is that even though the outcome may be “measurable,” the social contexts of the software program are important for questions of educational-software validity. If the educational tenants of the software package are not valid, then any outcome study loses any educational meaning. Though Rothe called for design-based evaluation, he is clearly opposed to outcome studies. This opposition is expressed later by Reeves (1992) and Reeves and Harmon (1994), though on different grounds. Despite this early opposition to outcome-based studies, many design-based evaluation techniques employed outcome-based studies as the primary factor in design evaluation.

Formative and Summative Evaluation In Formative Instructional Product Evaluation, Lawson (1974) lays the basic groundwork for formative evaluation theory, which subsequently influenced theorists dealing with educational software: “Formative product evaluation can be defined as the appraisal of instructional sequences and materials during their stages of formulation and development” (p. 5). Whereas formative evaluation is the process of evaluation during the design and development process, summative evaluation is the evaluation of the finished educational-software product. In the context of general educational-software evaluation, many have identified the difference between formative and summative evaluation and sought to provide a better definition of the two evaluation approaches. Most of the comparisons, however, come in the context of an introduction to formative evaluation. While formative evaluation deals with design issues, summative evaluation

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deals with broader, more practical issues. In Price’s book (1991), Computer-Aided Instruction: A Guide for Authors, the difference is accurately summarized: Formative evaluation should be more or less ongoing throughout the development process. Evaluations are made and revisions incorporated into a developing program with the goal being to make the lesson as good as possible by the time it is completed. Summative evaluation is usually conducted for the purpose of making major decisions concerning the entire program and is not conducted to determine specific features for modification or revision. It is typically used to make decisions regarding adoption or publication. (p. 106) While there are many categorizations for formative design evaluation, the author has grouped them into two main categories, as employed by both Ilgen-Lieth and Hazen (1987a, 1987b, 1987c) and Price (1991). 1. 2.

Data-based design evaluation Opinion-based design evaluation

DATA-BASED DESIGN EVALUATION Data Collection Reeves and Lent (1984) cite data collection under the category of “documentation.” They highlight practical concerns such as expenditure documentation in order to analyze the cost-effectiveness of a given project. They also list “automatic record keeping” as a way to measure the effectiveness of a given program during the developmental stages. They call for documentation of “names, ID numbers, educational status…time-on-system…student responses…and curricular progress status”(p. 191). Similarly, Hazen (1985) calls for data on the time on the task, number of correct answers, and student responses.

Educational Software Evaluation

Field Testing Field testing is ideally the real-life implementation of the software package. This is often the main source of data collection for the software developers. As Price (1991) states: The primary purpose of the field test is to confirm the effectiveness of the lesson after revisions have been made. Field test evaluations should be conducted in the same environment in which the program will eventually be implemented, while carefully monitoring the learners’attitudes, attainment of objectives, comments, reactions, and time required to complete the program. (p. 109) The difference between data collection and field-testing is the location of testing and the completeness of the program. Tovar and Barker (1986), in their method for field-testing educational software, cite environment as a key consideration for proper field-testing. Field-test evaluations are also a part of the overall design process and are therefore utilized before the final implementation of the program so that revisions may be made. It is unlikely, therefore, that major revisions involving the overall structure of the program would be made after field-testing as the crux of the work involved in design has already been completed. The greatest practical contribution to the concept of educational software was first introduced by the theorists in design evaluation who promoted implementation in a real-life setting. Software designers realized that there is an actual target environment for the educational-software programs. Design-evaluation techniques are the first to systematically identify this as a basic principle when dealing with educational-software evaluation. Hinostroza, Rehbein, Mella, and Preston (2000) go as far as to say that all software evaluation must be a part of a field-testing environment. This clearly breaks away from the design component in that the overall evaluation

is to be placed within a real-life setting, not to merely fix the bugs, but to add validity to the evaluation process.

OPINION-BASED DESIGN EVALUATION Expert Review While it may be clear that most teachers are considered subject experts, and thus would be involved in summative software evaluation, there are articles that call for the use of subject experts in the developmental stage: Reeves and Lent (1984), and Ilgen-Lieth and Hazen (1987a, 1987b, 1987c). The latter cites several studies that show the value of involving expert evaluators. In their article they call for the use of instructional-design experts in the design-evaluation process. The use of expert review is also recommended by Price (1991). He recommends a one-on-one evaluation strategy with the designer and an expert, though he does not specify whether this should be a content expert or an instructional-design expert. This is seen as a way to avoid investing time in poor design strategies.

Formal and Informal Opinion Collection Reeves and Lent (1984) cite the need for formal “personal observation”: Not all the data for complete and meaningful documentation of a CBI [computer-based instruction] project can be collected by computer-based program. Human beings must collect and report data concerning external factors which may affect the implementation of CBI such as power failure, equipment breakdowns, and fluctuations in the available student population. (p.191)

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Formal opinion collection during the design process involves targeted questions and organized questionnaires. Informal opinion collection differs only in the sense that the opinion collection is openended, with little or no express direction from the designers. Walker and Hess (1984) promote the use of open-ended reviews with experienced subject experts.

USABILITY Like many authors on this subject, a single factor is often the genesis of a new software-evaluation method. Hazen (1985) cites user frustration when interacting with computers as a reason for decreased learning. The attempt to diminish this frustration was taken up by a secondary movement of design-based evaluation, namely, that of usability. Usability shifts the focus of evaluation to the relationship between user and design and more specifically between the individual design elements that affect the interaction between user and computer. It is often simply equated with “user friendliness” and “ease of use” (Lee, 1999). Usability as an evaluation focus in educational software was introduced soon after the concept appeared in the general arena of software engineering. As the focus on educational software slowly shifts from teacher to student, usability takes user ergonomics to the extreme. It is perhaps due to the newness of the subject, to the proliferation of journals in the 1990s, or maybe to both the “artistic” and “scientific” sides of usability, but usability as a discipline occupies the greatest amount of research and publication of all the educational-software evaluation techniques. Usability is the newest theory in educational-software evaluation and in many ways it is the culmination of all other aspects of educational-software evaluation. It incorporates both teacher and student opinions and implies a real-world setting. As many have pointed out,

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however, usability strays from the very heart of educational-software evaluation: education. There are many definitions of usability, and the context in which usability is applied often skews these definitions toward a different perspective. As Lee (1999) points out, “Usability, equated with such concepts as ‘user-friendliness’ or ‘ease of use,’ is not a new concept, but it is relatively new to the field of computer software production and rarely well defined.” Lee (1999) explores several different definitions of usability that incorporate themes of effectiveness, satisfaction, and efficiency. The basic principle behind usability is the extended focus on the interaction between user and interface. The concept of ergonomics plays a major role in usability. This defines usability within the framework of a student-centered evaluation method as the user is the primary target of concern during evaluation. Similar to other issues in design, usability can be applied in both formative and summative evaluations. It is therefore strongly connected and should be understood as a subsection of design evaluation. In usability evaluation, the designer seeks to analyze the specific interaction between user and machine in order to maximize a positive interaction. The term positive interaction purposefully implies the subjectivity involved in usability evaluation. Depending on the type of software, and on the perspective of the evaluator, different aspects become targets of focus when employing usability evaluation.

Usability History As the capabilities in the technology of design increase, so do the possibilities. Software designers in the early 1990s were confronted with rapidly changing hardware capabilities, and thus were given the freedom to explore other possibilities in interface design. As the previous analysis of design theory indicates, usability is the natural culmination of design-based evaluation theories that focus on human-computer interaction. Ravden

Educational Software Evaluation

and Johnson (1989) cite the influence of software ergonomic studies from the 1980s as a major contributor. This is supported by Pilj (1996), who cites a progression in system-design theory resulting in usability theory. Lee (1999) makes the direct connection to design-based evaluation: “Formative evaluation, sometimes called prototype evaluation or learner validation, could be considered as the theoretical base of usability testing.”

Usability Evaluation as a Discipline Ravden and Johnson (1989) published one of the first comprehensive methods to evaluate usability in software. While they did not focus directly on educational software, the principles developed for usability testing are generally carried directly over into educational-software evaluation (e.g., Bhattacharya, Akahori, & Kumar, 1999; Demetriadis, Karoulis, & Pombortsis, 1999; Jones et al., 1999; Plass, 1998; Squires & Preece, 1999). First, the author will explore usability as a discipline, then focus on specific educational evaluation applications of this field. Ravden and Johnson’s method focused on nine points. 1. 2. 3. 4. 5. 6. 7. 8. 9.

Visual clarity Consistency Compatibility Informative feedback Explicitness Appropriate functionality Flexibility and control Error prevention and correction User guidance and support

Similar to the development from guidelines to checklists in teacher-centered educationalsoftware evaluation models, Ravden and Johnson develop a checklist method for usability testing from a critique of existing guidelines for software ergonomics. As Lee (1999) stated, the principles of software (design) engineering clearly influenced the field

of usability evaluation. This field, in contrast to Ravden and Johnson (1989), was concerned with quantitative analysis based on data collection within design evaluation. Three concepts of effectiveness, efficiency, and satisfaction, as defined by Park and Lim (1999), show the preferences of software designers. Quantitative effectiveness criteria in evaluation involve the following. 1. 2. 3.

Percentage of users successfully completing the task Number of user errors Ratio of successful interactions to errors

According to their categorization, effectiveness is defined as a measurable item. It can therefore be given a numbered score, and items of interface design can be modified in order to increase this score. This overall score is considered to be a usability satisfaction score.

Usability and Environment One of the key concerns involving usability evaluation is the environment in which the evaluation takes place. For any evaluation method that places such a high value on the user, an authentic testing environment is crucial. Sweeney, Maquire, and Shackel (1993) provide several simple definitions and outline usability evaluation. They include the issue of environment: “For measurement of usability it is important to include characteristics underlying user, task and environment in the ‘usability evaluation equation’” (p. 691). In understanding the concept of environment, they propose modeling it in a theoretical way through a simulation, abstraction, or expert opinion. Similarly, Squires and Preece (1996), identifying the environment in educational software as an educational context, state “it is not possible to evaluate an educational software application predictively without reference to a perceived educational setting” (p. 19). Like Sweeney et al., Squires and Preece accept a

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theoretical environment as acceptable in usability evaluation.

Usability and Education The dilemma in usability testing and education is that ultimately, and despite the insistence on real-life environment testing, usability testing inherently focuses away from the educational aspects of the software program and places more emphasis on external qualities such as graphics, layout, sound, and animation. As student-based and teacher-based opinion studies have shown, these aspects of software programs have little to do with the overall educational effectiveness, despite their perceived importance. However, the focus on environment to determine effectiveness of user-computer interaction was gladly accepted and promoted by the field of educational-software evaluation. Despite the origins of usability in the software-engineering field, the marriage of usability and education is shown through the numerous articles analyzing the usability of educational software. This is in part due to the perception of educational software as being poorly designed. ID Magazine’s 2000 edition of the Interactive Media Design Review stated bluntly, “I think one of the big problems for education software is that it’s so ugly it’s discouraging” (p. 65). Despite the natural focus on ergonomics, navigation, and appearance, educational-software evaluation utilizing usability testing has established itself as different than traditional usability testing. Usability testing in education starts by highlighting the user (student) and environment. Plass (1998, p. 36) saw the connection to education in that “a User-centered design takes human factors into account.” Usability evaluation in education, though, modified the traditional criteria and moved toward the inclusion of more contexts. The synthesis between usability and education is the attempt to draw conclusions about learning through the analysis of usability techniques. The techniques of usability testing are used, but the

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focus is squarely on education. As Park and Lim (1999) highlight, the three main considerations in usability testing allow for quantitative analysis. This has produced traditional usability studies that focus on quantitative results. Educational approaches, on the other hand, differ in that they focus more on the qualitative aspects. Parlangeli, Marchigiani, and Bagnara (1999, p. 40) purposefully try to avoid “…biases due to the sensitiveness of the method” by employing usability testing for both user and expert. Usability testing in educational software depends on the “education” that is tested. Through both quantitative studies on navigation and the time on tasks, and qualitative opinion studies usability testing in education has broadened its scope of focus. Where Parlangeli et al. used questionnaires to measure the overall learning of concepts, Squires and Preece (1996) sought to establish the effectiveness of the software program on task-based learning. Both, in this sense, are focusing on individual aspects of the program and learning, and building their evaluation model upon these criteria. Much like earlier design-based evaluation models, educational usability testing focuses evaluation on individual skills or concepts that the program is to teach or convey.

CONCLUSION By taking a chronological approach in the study of educational-software evaluation, patterns in the development of software itself emerge and are reflected in evaluation methodologies. Despite the fact that many older methods have been discounted, they still appear regularly. Usability evaluation is currently the state of the art in educational-software evaluation, but surely new methods will arise in the future. Nevertheless, the key factors—student, teacher, designer, and environment—will still play a role in the evaluation of overall effectiveness in educational software.

Educational Software Evaluation

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Jones, A, Scanlon, E., Tosunoglu, C., Morris, E., Ross, S., Buthcer, P., et al. (1999). Contexts for evaluating educational software. Interacting with Computers, 11, 499-516. Kleinmann, H. (1987). The effect of computer assisted instruction on ESL reading achievement. Modern Language Journal, 71(3), 267-276. Kulik, J. A., & Kulik, C. (1987). Review of recent research literature on computer-based instruction. Contemporary Educational Psychology, 12, 222-230. Kulik, J. A., Kulik, C., & Cohen, P. A. (1980). Effectiveness of computer-based college teaching: A meta-analysis of findings. Review of Educational Research, 50(4), 525-544. Lawson, T. (1974). Formative instructional product evaluation. Englewood, NJ: Educational Technology Publications. Lee, S. H. (1999). Usability testing for developing effective interactive multimedia software: Concepts, dimensions and procedures. Educational Technology and Society, 2(2). McDougall, A., & Squires, D. (1995). A critical examination of the checklist approach in software

Educational Software Evaluation

selection. Journal of Educational Computing Research, 12(3), 263-274. Miller, S. K. (1987). Selecting and implementing educational software. Boston: Allyn and Bacon. Muller, E. W. (1985). Application of experimental and quasi-experimental research designs to educational software evaluation. Educational Technology, 25(10), 27-31. Papert, S. (1987, January/February). Computer criticism vs. technocentric thinking. Educational Researcher, 22-30. Park, K. S., & Lim, C. H. (1999). A structured methodology for comparative evaluation of user interface designs using usability criteria and measures. International Journal of Industrial Ergonomics, 23, 379-389. Parlangeli, O., Marchigiani, E., & Bagnara, S. (1999). Multimedia systems in distance education: Effects of usability on learning. Interacting with Computers, 12, 37-49. Perreault, H. R. (1985). Evaluate software like any other educational resource. Journal of Business Education, 60(3), 257-259. Pilj, G. (1996). Lessons from the software engineering literature. Retrieved February 17, 2000, from http://www.phys.ksu.edu/~pilj/article.html Plass, J. L. (1998). Design and evaluation of the user interface of foreign language multimedia software: A cognitive approach. Language Learning and Technology, 2(1), 35-45. Preece, J., & Jones, A. (1985). Training teachers to select educational computer software: Results of a formative evaluation of an open university pack. British Journal of Educational Technology, 16(1), 9-20 Price, R. (1991). Computer-aided instruction: A Guide for authors. Pacific Grove, CA: Brooks/ Cole.

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This work was previously published in the Encyclopedia of Distance Learning, Vol. 2, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 699-711, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 2.43

An Adaptive Predictive Model for Student Modeling Gladys Castillo University of Aveiro, Portugal João Gama University of Porto, Portugal Ana M. Breda University of Aveiro, Portugal

AbstrAct This chapter presents an adaptive predictive model for a student modeling prediction task in the context of an adaptive educational hypermedia system (AEHS). The task, that consists in determining what kind of learning resources are more appropriate to a particular learning style, presents two issues that are critical. The first is related to the uncertainty of the information about the student’s learning style acquired by psychometric instruments. The second is related to the changes over time of the student’s preferences (concept drift). To approach this task, we propose a probabilistic adaptive predictive model that includes a method to handle concept drift based on statistical quality

control. We claim that our approach is able to adapt quickly to changes in the student’s preferences and that it should be successfully used in similar user modeling prediction tasks, where uncertainty and concept drift are presented.

IntroductIon In the last decade we have attended to an increased development of adaptive educational hypermedia and Web-based systems (AEHS). An AEHS is able to adapt its contents and presentations to specific characteristics of students. The keys for adaptation are the domain model and the student model. The former represents the knowledge about the subjects to be learned and serves as

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An Adaptive Predictive Model for Student Modeling

the base for structuring the hypermedia contents. The latter stores different assumptions about the student (e.g., knowledge, preferences, goals, etc.). An AHES uses the information stored in both models to implement adaptive algorithms and techniques. An extended discussion of adaptive hypermedia, and in particular, AEHSs can be found in Brusilovsky (2001). Student modeling involves the construction and updating of the student model. Traditionally, most of student modeling systems have been limited to maintain assumptions related with the student’s knowledge, which can be acquired during evaluation activities. However, over the last years there has been an augmented interest in modeling other kind of assumptions about the student, such as the learning style and preferences. An AEHS can make use of this kind of information to decide more effectively how to adapt itself to each student individually. Usually the students’ learning style is acquired using one of existing psychometric instruments. By matching a learning style with some relevant characteristics of the learning resources, these systems can determine which resources are most appropriate for a particular student. As a rule, the acquired assumptions about the students’ learning style are no longer updated during their interactions with the system. Moreover, the deterministic rules included in their decision models also never change. There are some typical issues that are critical concerning a successful implementation of the prediction task, that consists in determining what kind of learning resources are more appropriate to a particular learning style in a real student modeling scenario: 1.

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Although multiple models to categorize the students according to their learning styles have been developed it is difficult to determine how exactly a person learns. Therefore, the information about the student’s learning

2.

style acquired by psychometric instruments encloses some grade of uncertainty. During the interactions with the system, the student can change his/her preferences for another kind of learning resource that no longer matches with his/her determined learning style. It is because either the acquired learning style information needs to be adjusted or the student simply changes his/her preferences motivated by other unknown reasons (some hidden contexts). This kind of problem is known as concept drift in the machine learning community.

This chapter aims at presenting a new adaptive machine learning approach for the described prediction task. Our approach is based on an adaptive predictive model capable of fine-tuning its parameters to reflect more accurately the student’s preferences. Moreover, this also includes a method to handle concept drift (Castillo, Gama, & Medas, 2003). This method uses a P-Chart (Montgomery, 1997), an attribute Shewhart control chart, to monitor the learner’s performance over time. Although this drift-detection method is broadly applicable to a range of domains and learning algorithms, we choose Naïve Bayes classifier (Mitchell, 1997), one of the most used learning algorithms in user modelling, as our predictive model. Furthermore, we propose the use of Adaptive Bayes (Gama & Castillo, 2002), an incremental adaptive version of the Naïve Bayes classifier. This algorithm includes an updating scheme that allows better fitting of the current model to new observations. We argue that the proposed adaptive predictive model can be implemented in any AEHS where we need to adapt the presentation based on the student’s learning style and preferences. Finally, we claim that our approach should be successfully used in similar user modeling prediction tasks, where uncertainty and concept drift are presented. The next section reviews some student modeling approaches based on learning styles. We

An Adaptive Predictive Model for Student Modeling

then cover the use of machine learning in user modeling. This section focuses the concept drift problem in concept learning. We present some adaptive learning approaches to deal with concept drift developed in the area of information filtering. Finally, we briefly introduce the concept drift detection method using P-Chart. The following section describes GIAS, an AEHS that we are actually developing to illustrate our approach. The subsequent sections describe the adaptive predictive model for the prediction task based on learning styles and present some experiments to evaluate our approach using simulated students. Finally, we present the conclusions and future work.

LEARNING STYLE IN STUDENT MODELING Learning style can be defined as the different ways a person collects, processes, and organizes information. As was argued in several works, we also claim that to effectively adapt interaction a student model must include information about the student’s learning style. This assertion is based on the fact that different people learn differently (Felder, 1996): some people tend to learn by doing, whereas others tend to learn concepts; some of them like better written text and/or spoken explanations, whereas others prefer learning by visual formats of information (pictures, diagrams, etc.). Consequently, the student’s learning style can influence the student’s preferences that usually guide the system’s adaptation. Moreover, the learning style information is not subject-specific, and can be used across many AEHSs. A pioneer work incorporating learning styles in AEHSs was proposed by Carver, Howard, and Lane (1999) to support a computer science hypermedia course. The authors developed an adaptive hypermedia interface to tailor the presentation of course material based on the determination of what types of media are appropriate for different

learning styles. For each course tool they compute a rate (on a scale from 0 to 100) to determine the amount of support for each learning style. The obtained rate is combined with the student’s profile to produce a unique ranking of each media type from each learning style. USD (teaching support units) is an intelligent tutoring system to support distance learning in the WEB (Peña, Marzo, & de la Rosa, 2002). The adaptation technique is approached by a multi-agent system named MAS-PLANG. The student agent implements case-based reasoning for student modeling with the aim to retrieve the relevant didactic contents (taking into account media formats and instructional strategies), navigation tools and navigation strategies based on the student’s learning style. The learning style is acquired, as usually, by a psychometric instrument. Next, they assign some distributions to different materials considering which learning styles are more appropriate for different instructional strategies, media formats, and navigation tools. Although the authors refer that the initial student’s profile is fine-tuned to reflect more faithfully the student’s learning style here it is not clear how this updating is carried out. INSPIRE (Papanikolaou, Grigoriadou, Magoulas, & Kornilakis, 2002) is an AHES that integrates theories of instructional design with learning styles. The student’s learning style can be acquired using a psychometric instrument or defined by the own student. The domain model is structured in three hierarchical levels: learning goals, concepts, and educational materials. Lessons are based on combinations of educational materials. The adaptation is based on the students’ knowledge level and learning style. The former is used to adapt the lesson contents and the navigation support. The latter is used to determine the appropriate instructional strategy for presenting the content, that is, lessons are tailored to learners according to his/her learning styles. In MANIC (Stern & Woolf, 2000) the student’s learning style is not directly used, but it is ap-

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An Adaptive Predictive Model for Student Modeling

proached by the student’s preferences concerning the type of media, the instructional type and the level of abstraction of the content objects, as well as the place where these objects must be presented to the students. The tutor learns the student’s preferences via machine learning by observing which objects he/she shows or hides (a stretchtext technique is used to adapt the presentation). A Naïve Bayes classifier predicts whether a student will want certain content objects. Those objects predicted as “wanted” will be shown to the user, while the others will not be shown. For each student, an example space is created based on the information about the content objects that, in the past, were either wanted or not wanted by the student. Population data is used to improve the accuracy of predictions. Finally, a good survey of other works related with the use of learning styles in AEHS can be found in Papanikolaou et al. (2002).

MACHINE LEARNING FOR USER MODELING User modeling systems are basically concerned with making inferences about the user’s assumptions from observations of their behavior during his/her interaction with the system. On the other hand, machine learning is concerned with the formation of models from observations. Hence, in the last years, the use of machine learning techniques in user modeling has become increasingly popular. Observations of the user’s behavior can provide training examples that a machine learning system can use to induce a model designed to predict future actions (Webb, Pazzani, & Billsus, 2001).

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Concept Drift in Supervised Learning The prediction task based on learning styles is related to the task of concept learning, a particular case of supervised learning (Mitchell, 1997). Suppose that f: X→C maps from a feature space X ⊂ ℜN to a fixed set C of k classes C={c1 ,…,ck}. The goal of supervised learning is therefore: given a set of labeled examples (x, f(x)) to induce a learner (hypothesis) hL : X→C that approximates f as closely as possible. The function f is called the target concept. In the case of concept learning the outputs are Boolean (e.g., C={yes, no}). A positive (negative) example is an example labeled “yes”(“no”). As a rule, supervised learning assumes the stability of the target concept. Nevertheless in many real-world problems, when the data is collected over an extended period of time, the learning task can be complicated by changes in the distribution underlying the data or changes in the own target concept. This problem is known as concept drift. Concept drift scenarios require incremental learning algorithms, able to adjust quickly to drifting concepts (Webb et al., 2001). Depending on the rate of the changes we can distinguish concept drift (gradual changes) of concept shift (abrupt changes). For instance, in the context of our predictive task the student preferences of learning resources can change with time. In machine learning drifting concepts are often handled by time windows or weighted examples according to their age or utility (see Klinkenberg & Renz, 1998, for a brief review). In general, approaches to cope with concept drift can be classified into two categories: (i) approaches that adapt a learner at regular intervals without considering whether changes have really occurred; (ii) approaches that first detect concept changes, and next, adapt the learner to these changes accordingly.

An Adaptive Predictive Model for Student Modeling

Examples of the former approaches are weighted examples and time windows of fixed size. Weighted examples are based on the fact that the importance of an example should decrease with time. When a time window is used, at each time step the learner is induced only from the examples that are included in the window. Here, the key difficulty is how to select the appropriate window size: a small window can assure a fast adaptability in phases with concept changes but in more stable phases it can affect the learner performance, while a large window would produce good and stable learning results in stable phases but can not react quickly to concept changes. To detect concept changes, the second group of approaches monitor the value of some performance indicators over time. If during the monitoring process a concept drift is detected, the learner is adapted accordingly. For instance, such an approach was proposed by Klinkenberg and Renz (1998) and by Lanquillon (2001). A deeper discussion about these and other similar approaches can be found in Castillo et al. (2003).

The Concept Drift Detection Method Based on P-Chart Similar to Lanquillon, the underlying theory we use is the Statistical Quality Control (SQC) theory (Montgomery, 1997). The main idea behind SQC is to monitor the value of some quality characteristic in the production processes. Shewhart controls

chart, the basic tool of SQC, is a useful monitoring technique that helps distinguish trends and out-of-control conditions in a process. This allows process correction thus reducing its variability. The values of the quality characteristic are plotted on the chart in time order and connected by a line. The chart has a center line and upper and lower control limits. If a value falls outside the control limits, we assume that the process is out-of-control, that is, some “special causes” have shifted the process off target. In addition to control limits we can also use upper and lower warning limits, which are usually set a bit closer to the center line than the control limits. If the distribution of the quality characteristic is (approximately) normal with mean µ and standard deviation σ, it is well known, that approximately 99.7% of the observations will fall within three standard deviations of the mean of the statistics. Therefore, if µ and σ are known we can use them to set the parameters of the control chart, as shown in equation 3.1. However, in most cases µ and σ are unknown and they must be estimated from previously observed values. The control charts are classified according to the type of quality characteristic that they monitor: variables or attributes. P-Chart is an attribute control chart for the proportion of a dichotomous “count” attribute. The quality characteristic represents the sample proportion of one of the two outcomes. For large sample size n the

Equation 3.1 CL= = µ - the center line is set to the mean value LCL = µ-3σ and UCL = µ+3σ - the lower and upper control limits LWL = µ-kσ and UWL = µ +k σ, 0 WCL then /* concept drift suspected If LastAlert=t-1 then /* consecutive alerts LastAlert:=t else /* it can be a false alarm {learner:= UpdateWith(learner , Bactht) FirstAlert:=t, LastAlert:=t} else /* no changes was detected learner ←UpdateWith(learner , Batcht); Next t; return: learner End

We assume that a new context is beginning and only the examples from this new context are used to re-learn the learner. If the last alert occurred at the previous time step (LastAlert=t-1) a new context began at the time indicated in FirstAlert. If the current sample error is above the upper warning limit and it occurred at two or more consecutive times a concept drift is suspected and the examples of this batch are not used to update the learner. If neither a concept shift nor concept drift is suspected the learner is updated to combine the current learner with the examples of the current batch. The precise way in which a learner can be updated in order to include new data depends basically on the learning algorithm employed. There are two main approaches: (i) re-build the learner from scratch; (ii) update the learner combining the current model with the new data. For instance, updating a Naïve Bayes classifier

is simple: the counters required for calculating the prior probabilities can be increased as new examples arrive.

GIAS: AN ADAPTIVE HYPERMEDIA EDUCATIONAL SYSTEM GIAS is a prototype WWW-based adaptive authoring-tool to support learning and teaching. The authors can organize all the available online learning resources associated to each topic of the course to support the learning processes of their students. On the other hand, the students can make use of this repository of learning resources for consulting and studying. The main function of GIAS’s adaptation is to help the students to explore a repository of learning resources associated to a set of educational goals. The ideal situation is when the student has too

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An Adaptive Predictive Model for Student Modeling

many options to choose from and the system can recommend him/her to explore those resources which are more appropriate to his/her learning style and preferences. Therefore, the adaptation techniques are focused on the appropriate selection of the course’s topics and learning resources based on the student’s goals, knowledge level, learning style, and preferences. The main difference between our approach and other similar approaches is that we try to adapt and fine-tune the initial acquired information about the student’s learning style and preferences by observing the student’s interactions with the system. We represent the matches between the student’s learning style and the characteristics of learning resources into a predictive model (a learner). Moreover, we propose an adaptive predictive model capable of adapting quickly to any change of the student’s preferences. Similar to most of AEHSs, the main components of GIAS are the domain model and the student model. The domain model is composed by the cognitive model (for knowledge representation) and the course model (for course representation). The student model represents, collects, and predicts assumptions about the student’s characteristics. Moreover, GIAS includes an author module to manage the information of the domain model and an instructional module to make decisions about how and what to adapt based on the information stored in the domain and student models. This includes three main processes: course generation, topic generation, and test generation. Here, we focus on the course model, the student model, and the topic generation process.

Course Model The course model (see Figure 2) is organized into three-layers: the goal layer (the course’s goals), the topic layer (the course’s topics), and the resource layer (a set of learning resources). Each goal is associated to a set of topics and each course topic is associated to a set of learn-

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ing resources. Between the topics we can define aggregation relationships. A learning resource is an implementation of a learning activity in a multimedia support. Table 1 shows the resource features and their possible values. Different learning resources may support a learning activity in different multimedia formats. For example, suppose we have a theorem proof supported by two different media formats: a static text that describes this proof, or an animated image with voice that explains this proof step by step. We should suggest to a visual student the study of this proof using the animated image with voice, and to a verbal student the study of the proof using the static text.

The Student Model A student model can represent individual students (individual approach) or group of users with similar characteristics (stereotype approach). In GIAS we use both of these approaches to model the student. For each student his/her individual student model is composed of:

Figure 2. GIAS course model

Topic Layer Goal Layer

Resource Layer

An Adaptive Predictive Model for Student Modeling

Table 1. Establishing resource features and their possible values Attribute

Value

ResourceID Description Author Language

Portuguese/ Spanish/ English

Creation Data Lesson objectives/Explanation/ Example/Conceptual Map/SyntheLearning Activity (LA)

sis Diagram/ Glossary / Summary /Bibliography /HistoricalReview /Inter.Activity to explain the new concepts/ to

Activity Type

exemplify the new concepts/ to support the cognitive process/ to help or to coach the student Text/HTML Text/Picture/Animat-

Resource Type (RT)

ed Picture/ Animated Picture with Voice/ Audio /Video /Software

Difficulty Level

Low/Medium/High

Concept/skill List

The learning style model that we adopted is the Felder-Sylverman model (Felder, 1996). This classifies students in five dimensions: input (visual vs. verbal), perception (sensing vs. intuitive), organization (inductive vs. deductive), processing (active vs. reflective), understanding (sequential vs. global). We use the Index of Learning Styles questionnaire (ILSQ) of Felder and Soloman to assess preferences on input, perception, and understanding. For each dimension a person is classified as having a mild, moderate, or strong preference for one category. The acquisition of student’s learning style is done explicitly or implicitly. When a new student logs into the system, he/she is given the option of exploring the course according to his/her learning style or without it. If a student chooses to use learning style, the student must answer to the ILSQ and the obtained scores are recorded in his/her profile model. On the contrary, the student’s learning style should be inferred by observing the student’s interactions with the system. In this chapter we assume that the acquisition of the student’s learning style is done explicitly.

The Topic Generation Process •

•

• •

Profile model: Stores personal information about the student (name, age, learning style) Cognitive overlay: Records the system beliefs of the student’s knowledge about the domain cognitive model. Consequently, the student is classified as novice, intermediate or expert. Predictive model: Represents the student preferences about the learning resources. Course overlay: Stores the information gathered by the system about the student’s interactions with the course (e.g., how many times he/she has visited a topic or learning resource, performance in evaluation activities, etc.).

The topic generation process (see Figure 3) is executed whenever a student requests the contents of a topic. The student’s predictive model is used to classify the available resources. The choice of the suitable learning resources for a topic depends on the resource’s characteristics and on the student’s cognitive state, learning style and preferences. This process is performed according to the following steps: 1.

Filtering: Using some deterministic rules, the learning resources are filtered according to the matching between the resource’s difficulty level and the student’s knowledge level.

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An Adaptive Predictive Model for Student Modeling

Figure 3. The topic generation process

Topic’s Resources

Se

le

ct

To

pi

Student’s Cognitive Overlay

c

Resources’s Difficulty Level

Student’s Cognitive State

Filtered Resources

Student’s Profile Learning Style: Visual Sensing Sequential

Feedback?

Examples Generation

Predictive Model Update Topic Content

Suggested for study

Content Adaptation

Not Appropriate

Other Resources

2.

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Prediction: Using the actual predictive model, each filtered resource is classified as “appropriate” or “not appropriate” for the student. With this purpose, examples including the learning style features (stored in the student model) and the resource’s characteristics (stored in the domain model) are automatically generated and classified by the actual predictive model. As a result the set of available resources is partitioned into these two classes.

Appropriate

3.

4.

Decision: An HTML page is sent to the student including two separated ranked lists: “resources suggested for study” list with the links for those resources classified as “appropriate” and “other resources for study” list with the links for those resources classified as “not appropriate”. Adaptation: Whenever a new example is observed and evaluated, the predictive model is adapted accordingly.

An Adaptive Predictive Model for Student Modeling

Figure 4. The prediction task

THE USER MODELING PREDICTION TASK Figure 4 shows the prediction task that consists of determining whether a given resource is or not appropriate for a specific learning style by using the information about the resource and the student’s learning style as input, and having the output category representing how strongly the resource is appropriate for this student.

The Example Features and Its Values The examples are described through five attributes: the first three characterizing the student’s learning style and the last two characterizing the learning resource. The possible values for each attribute are presented in Table 2. For instance, suppose the following example: VisualVerbal:Verbalmoderate; SensingConceptual:Sensingmild; SequentialGlobal:Globalmild; Learning Activity: explanation; Resource Type: audio. The predictive model must determine if a learning resource that implements a learning activity such as “explanation” in a multimedia support of type “audio” would be appropriate for a student with a moderate preference for verbal category, a mild preference for sensing category, and a mild preference for a global category.

Further, to simplify the prediction task we will not discriminate the preferences for a category as mild, moderate or strong. For example, in the previous example, the student is simply classified as verbal, sensing, and global. Consequently we only have eight different learning styles.

Table 2. Establishing attributes and their possible values Attributes

Values

Characterizing the student’s learning style VisualVerbal

VVi, VV ∈ {Visual, Verbal}, i ∈ {mild, moderate, strong}

SensingConceptual

SCi, SC ∈ {Sensing, Conceptual}, i ∈ {mild, moderate, strong}

GlobalSequential

GSi, GS ∈ {Global, Sequential}, i ∈ {mild, moderate, strong}

Characterizing the learning resource Lear ning Activity

Lesson objectives/Explanation/Ex-

(LA)

ample/Conceptual Map/Synthesis Diagram/ Glossary / Summary /Bibliography /HistoricalReview /Inter. Activity

Resource Type (RT)

Text/HTML Text/Picture/Animated Picture/ Animated Picture with Voice/ Audio /Video /Software

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An Adaptive Predictive Model for Student Modeling

The Predictive Model Naïve Bayes (NB) classifiers (Mitchell, 1997) are probabilistic classifiers that are suitable for problems where there is uncertainty as to the correct answer. They use Bayes theorem with the assumption that the attributes are independent given the class (hence the term Naïve) to compute class probability distributions in term of their prior probabilities and the conditional probabilities of the attributes. All the required probabilities are computed from the training data: a frequency counter is required for each class, and a frequency counter for each attribute-value in combination with each class. Although it is well known that most real world problems do not meet independence assumptions on which the NB classifier is based, because of its simplicity, easy use, and incremental nature, it is one of the most implemented classifiers in real-world applications. NB classifier, in particular, has been successfully applied in many user modeling system (e.g., information filtering) for acquiring interest profiles. For instance, in Pazzani and Billsus (1997) an intelligent agent called Syskill&Webert uses a NB classifier to determine whether a page would be interesting to a user. Billsus and Pazzani (1999) developed an intelligent agent named New Dudes, which learns about users’ interests to compile daily news stories. This agent uses a short-term model that learns from the most recent observations and a long-term model (a NB classifier) that computes the predictions for stories not classified by the short model. The personalized WebMatcher proposed by Mladenic (1996) also implements a NB classifier to recommend links on other Web pages. Schwab, Wolfgang, and Koychev (2000) implement NB classifiers to learn interest profiles from positive evidence only. We use Adaptive Bayes (Gama & Castillo, 2002), an adaptive version of the NB classifier, to induce the predictive model. Adaptive Bayes includes an updating scheme to better fit the cur-

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rent model to new data: after seeing each example, first, we increment the counters, and then we adjust them in order to increase the confidence on the correct class. The amount of adjustment is proportional to the discrepancy between the predicted class and the observed class.

Implementation Details We implement a stereotyping approach to initialize each student’s predictive model. For this purpose, we also maintain a stereotype predictive model for each learning style. Firstly, we define some matching rules between a learning style and the resource’s characteristics to determine which resources are more appropriate to a particular learning style. After that, we use the predefined matching rules to randomly generate some training examples, and then we use these generated examples to initialize the counters for each stereotype predictive model. Therefore, the acquired information about the student’s learning style helps us to initialize the student’s predictive model from its related stereotype model. During the further interactions with the system, the student’s predictive model will adapt to better fit the current student’s preferences by observing the student’s behavior. The most recent observations gathered trough relevant feedbacks represent the user’s current preferences better than older ones. A critical task at this point is how to obtain relevant feedback, that is, a relevant set of positive and negative examples for the learning task. We propose obtaining positive examples implicitly by observing visited links. However, obtaining a relevant set of negative examples is more difficult. With this aim, we propose the user to rate the resources explicitly. In future works we plan to investigate other methods to obtain more relevant feedback. The set of obtained examples are used to adapt the student’s predictive model in the way it is explained in the previous chapter.

An Adaptive Predictive Model for Student Modeling

EVALUATION OF THE PREDICTIVE MODEL

tive model must learn another concept (“rule”), like this:

Our evaluation measures the accuracy of the model’s predictions on a set of artificial datasets that were specially generated to simulate concept drift scenarios for the described prediction task. Namely, we employed simulated students (Vanlehn, Ohlsson, & Nason, 1994), a technique commonly used in student modeling, to evaluate the predictive model’s performance. Therefore, each generated artificial dataset represents a simulated student.

IF LearningStyle Is Verbal AND (ResourceLearningActivity OR ResourceType) matches Visual THEN Resource is Appropriate

Dataset Generation and Experimental Setup Note that students’ predictive models enclose different underlying target concepts for different learning styles, and that, each individual predictive model is initialized from its associated stereotype model according to the student’s learning style. The basic idea enclosed in the generation of simulated students is based on the following facts that really exist in this context: for instance, suppose a verbal student. Learning resources that match with a verbal student should be appropriate for him/her. Hence, the underlying target concept can be represented by the following logical rule: IF LearningStyle Is Verbal AND (ResourceLearningActivity OR ResourceType) matches Verbal THEN Resource is Appropriate

Nevertheless, during the further interaction with the system, the student can change his/her preferences for another kind of learning resource that no longer matches with his/her predefined learning style. This means that the initial concept no longer matches the student’s behaviour (a concept change happened), and thus, the predic-

Moreover, these changes in the student’s preferences can lead to further adjustments in the student learning style. Therefore, we generated simulated students for the eight possible learning styles. For each learning style, we generated datasets with 1600 examples: first, we randomly generated each feature value (see Table 2), and then, we classified each example according to the current concept. After every 400 examples the concept was changed. We grouped the examples into 32 batches of equal size (50 examples each). We also generated training datasets with 200 examples (according to the first concept) to initialize the stereotype predictive models. We conducted the experiments in the online framework for supervised learning described in the previous chapter section. We evaluated the predictive accuracy of two learning algorithms: Naïve Bayes (NB) and Adaptive Bayes (AB) in combination with each of the following approaches: a non-adaptive approach (the baseline approach), fixed size window with a size of six batches (FSW) and our approach (Figure 1) using the min value as mean estimator and k=1. We denote our approach PMin. For each learning style, we estimated the predictive accuracy over 10 runs (in each run we used a different generated dataset). The final estimator of the predictive accuracy of each combination “algorithm-approach” is the average of the eight accuracy estimations (one for each learning style).

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An Adaptive Predictive Model for Student Modeling

belong to the same context and they all are used to re-learn the model. Figure 6 shows the averaged accuracy of all the combinations “algorithm-approach” after each batch, respectively. At first, the performance of all approaches is good enough; however, those combined with Adaptive Bayes show a better performance. After the first change has occurred, the performance of non-adaptive approaches decreases significantly (they can not identify concept changes), and the performance of the FSW approach can recover a little because it relearns regularly from the last six batches. In contrast, Pmin can quickly recover its performance decrease as the learning progresses. Moreover, PMin, instead of the FSW, whose performance depends on the window size, doesn’t depend on any parameter. Table 3 compares, for all the learning styles and combinations “algorithm-approach”, the

Experimental Results and Analysis In Figure 5 you can see an illustration of one Pchart for monitoring the sample error rate in one of the generated datasets. The sample error rates are plotted on the chart and connected by a line. In each time step, the center line is adjusted according to the minimum value of the error rate in the current context. This P-Chart detected the three concept shifts that really exist in the data: the two first concept shifts (after t=8 and t=16) were detected immediately (those points that fall above the current control limit) and the third concept shift (after t=24) was detected with slight delay. However, beginning at t=25, the P-Chart starts detecting an upward trend of the sample error, that is, a concept drift (those points that fall outside the warning limits). When further, at t=27 the concept shift is signaled, all the examples beginning at t=25 are considered to

Figure 5. A P-chart for monitoring the sample error rate 45,00%

Sample Error Rate CL (MinError) UCL UWL

40,00%

35,00%

30,00%

25,00%

20,00%

15,00%

10,00%

5,00%

0,00%

0

2

4

6

8

10

12

14

16

Batch

1320

18

20

22

24

26

28

30

32

An Adaptive Predictive Model for Student Modeling

Figure 6. Comparison of the averaged accuracy of each combination “algorithm-approach” 100,00% 95,00% 90,00% 85,00% 80,00% 75,00% 70,00% 65,00%

NB NB & WFS NB & PMin

60,00% 55,00%

0

2

4

6

8

AB AB & WFS AB & PMin

10

12

average predictive accuracy over all the batches, and Table 4 shows some comparative studies of the performance for a pair of approaches using paired t-tests with a confidence level of 95 percent. A + (-) sign in the column “mean” means that the first approach obtains a better (worse) result with statistic significance. Note that the mean of the accuracy is significantly different with high probability as given by the p-value. Studies I and II compare adaptive approaches that deal with concept drift against the baseline non-adaptive approach in combination with Naïve Bayes and Adaptive Bayes, respectively. The results show that a significant improvement is achieved by using any adaptive method instead of the non-adaptive one for both the learning algorithms. Study III compares the two adaptive approaches FSW and PMin in combination with the two learning algorithms, respectively. The results shows that the performance of P-Chart is significantly superior to the performance of FSW, where the learner is adapted regularly without

14 16 Batch

18

20

22

24

26

28

30

32

considering whether a concept change really occurs. The last study (IV) compares the two learning algorithms. The results show that Adaptive Bayes significantly outperforms Naïve Bayes for all the approaches. In general, a more significant improvement is achieved when adaptive methods are combined with Adaptive Bayes.

CONCLUSION AND FUTURE wORK In this chapter, we presented an adaptive predictive model for a student modeling prediction task based on learning styles. The main difference between our approach and other similar approaches is that we try to adapt and fine-tune the initial acquired information about the student’s learning style and preferences from the student’s interactions with the system using machine learning techniques. We represent the matches between the learning resources and the student’s learning style into an adaptive predictive model that is able to quickly

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An Adaptive Predictive Model for Student Modeling

Table 3. Predictive accuracy of the two learning algorithms (NB and AB) combined with three approaches (baseline, FSW, PMin) for the 8 different learning styles Approaches

LS 1

LS 2

LS 3

LS 4

LS 5

LS 6

LS 7

LS 8

Avg Acc.

(1) NB

70.50

64.42

69.59

64.71

77.33

77.27

57.83

60.51

67.77

(2) NB & FSW

86.86

85.11

83.06

78.81

87.48

85.98

86.66

84.48

84.80

(3) NB & PMin

91.41

90.96

91.24

89.15

90.27

90.03

90.25

89.30

90.04

(4) AB

75.73

70.79

73.42

67.01

80.61

80.09

70.38

68.24

73.28

(5) AB & FSW

89.04

87.39

86.69

82.01

89.33

88.43

89.06

87.12

87.38

(6) AB & PMin

91.90

91.61

92.62

90.87

91.77

90.60

91.84

89.30

91.31

Table 4. Summary of results comparing the predictive accuracy of a pair of approaches. Results for the differences

Paired t-test

between the averaged accuracies Mean I

II

III

IV

Std Err

Median

Min

Max

p-value

(2) vs. (1)

+

17.03

6.96

15.23

8.71

28.83

0.00023

(3) vs. (1)

+

22.27

6.80

23.05

12.76

32.42

0.00004

(5) vs (4)

+

14.01

4.04

14.16

8.34

18.88

0.00002

(6) vs (4)

+

18.03

4.95

20.01

10.51

23.86

0.00002

(3) vs. (2)

+

5.24

2.75

4.30

2.56

10.34

0.00101

(6) vs (5)

+

3.93

2.37

2.82

2.17

8.86

0.00222

(4) vs. (1)

+

5.51

3.39

4.53

2.30

12.55

0.00250

(5) vs. (2)

+

2.58

0.58

2.42

1.85

3.63

0.00000

(6) vs. (3)

+

1.27

0.64

1.44

0.49

2.26

0.00078

adapt to any change of the student’s preferences. We also present a general method to handle concept drift using P-Charts, which is broadly applicable to a range of domains and learning algorithms.

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Two sided, ∝=0.05

Although we have not performed an evaluation yet with real users, the obtained results using artificial students show that our adaptive approach consistently recognizes concept changes and that, the learner can adapt quickly to these

An Adaptive Predictive Model for Student Modeling

changes in order to maintain its performance level. This means that our predictive model is able to adapt quickly to the changes in the user behavior in order to reflect more accurately the current student’s preferences. In the near future, we plan to evaluate our approach with real students and with other Bayesian Network classifiers.

ACKNOwLEDGMENT This work was developed in the context of project ALESII (POSI/EIA/55340/2004).

REFERENCES Billsus, D., & Pazzani, M. J. (1999). A hybrid user model for news stories classifications. In J. Kay (Ed.), Proceedings of the Seventh International Conference on User Modeling, Canada (pp. 99108). Springer-Verlag.

Gama, J., & Castillo, G. (2002). Adaptive Bayes. In F. Garijo, J. Riquelme, & M. Toro (Eds.), Advances in Artificial Intelligence - IBERAMIA 2002, Lecture Notes in artificial intelligence (Vol. 2527, pp. 765-774). Springer-Verlag. Klinkenberg, R., & Renz, I. (1998) Adaptive information filtering: Learning in the presence of concept drifts. Proceedings of the ICML-98 workshop Learning for Text Categorization (pp. 33-40). AAAI Press. Lanquillon, C. (2001). Enhancing test classification to improve information filtering. Ph.D. Dissertation, University of Madgbeburg, Germany. Retrieved from http://diglib.uni-magdeburg. de/Dissertationen/2001/carlanquillon.pdf Mitchell, T. (1997). Machine learning. McGraw Hill. Mladenic, D. (1996). Personal WebWatcher: Implementation and design. Technical Report, IJS-DP-7472.

Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-Adapted Interaction, 11, 87-110.

Montgomery, D. C. (1997). Introduction to statistical quality control (3rd ed.). New York: John Wiley & Sons.

Carver, C. A., Howard, R. A., & Lane, W. D. (1999). Enhancing student learning trough hypermedia courseware and incorporation of student learning styles. IEEE Transactions on Education, 42(1), 33-38.

Papanikolaou, K. A., Grigoriadou, M., Magoulas, G. D., & Kornilakis, H. (2002). Towards new forms of knowledge communication: The adaptive dimension of a Web-based learning environment. Computers and Education, 39(4), 333-360.

Castillo, G., Gama, J., & Medas, P. (2003). Adaptation to drifting concepts. In F. M. Pires & S. Abreu (Eds.), Progress in Artificial Intelligence, Lecture Notes in Artificial Intelligence, 2902 (pp. 279-293). Springer-Verlag.

Pazzani, M. J., & Billsus, D. (1997). Learning and revising user profiles: The identification of interesting Web sites. Maching Learning, 27, 313-331.

Felder, R. M. (1996). Matters of style. ASEE Prism, 6(4), 18-23. Felder, R. M., & Soloman, B. A. (n.d.). Index of learning style questionnaire. Retrieved from http://www2.ncsu.edu/unity/lockers/users/f/ felder/public/ILSdir/ilsweb.html

Peña, C. I., Marzo, J. L., & de la Rosa, J. L. (2002). Intelligent agents in a teaching and learning environment on the Web. Proceedings of the Second International Conference on Advanced Learning Technologies (ICALT2002), Russia. Schwab, I., Wolfgang, P., & Koychev, I. (2000). Learning to recommend from positive evidence.

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Proceedings of intelligent user interfaces (pp. 241-247). ACM Press. Stern, M. K., & Woolf, B. P. (2000). Adaptive content in an online lecture system. In P. Brusilovsky, O. Stock, & C. Strapparava (Eds.), Adaptive hypermedia and adaptive Web-based systems. Lecture notes in computer science, Vol. 1982 (pp. 227-238). Berlin: Springer-Verlag.

Vanlehn, K., Ohlsson, S., & Nason, R. (1994). Applications of simulated students: An exploration. Journal of Artificial Intelligence in Education, 5(2), 135-175. Webb, G., Pazzani, M., & Billsus, D. (2001). Maching learning for user modeling. User Modelling and User-Adapted Interaction, 11, 19-29.

This work was previously published in Advances in Web-Based Education: Personalized Learning Environments, edited by G. D. Magoulas and S. Y. Chen, pp. 70-92, copyright 2006 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.44

Applying Contextual Design to Educational Software Development Mark Notess Indiana University, USA

ABSTRACT

INTRODUCTION

Contextual design is a methodology for developing information systems from a rich understanding of customer work practice. This chapter considers how contextual design can be applied to educational software development and how contextual design might interact with instructional systems design (ISD). Following a brief overview of ISD, I describe contextual design and provide a detailed case study of its application to educational software development—to the design of an online tool for music listening and analysis in undergraduate and graduate music education. I conclude with some reflections on the relevance of contextual design to instructional designers.

Contextual design is a methodology for designing information systems from a rich understanding of customer work practice (Beyer & Holtzblatt, 1998). This chapter considers how the contextual design methodology can be applied to the development of educational software and how contextual design might interact with instructional systems design (ISD). I begin with a brief overview of ISD, brief because I assume readers of this chapter will already have some acquaintance with ISD. I then describe contextual design and provide a detailed case study of its application to educational software development—to the design of an online tool for music listening and analysis in undergraduate and graduate music education. I conclude with some reflections on the relevance of Contextual Design to instructional designers.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Applying Contextual Design to Educational Software Development

INSTRUCTIONAL SYSTEMS DESIGN

CONTEXTUAL DESIGN

The ADDIE (analysis, design, development, implementation, evaluation) model of instructional systems design provides a general framework for designing instruction. The model seems to have emerged anonymously during the 1960s (Michael Molenda, personal communication, August 1, 2002) but has since become broadly known. In a 1988 booklet from ASTD, ADDIE is described as one of a variety of models for instructional systems design (ASTD, 1988, p. 2). A Web search of “addie” and “instructional systems” yields hundreds of hits. ADDIE is widely known and is sometimes even described as the instructional systems design model (e.g., Fardouly, 1998). However, ADDIE is not the only model for instructional systems design. Over the years, more refined, comprehensive, flexible models have evolved; it is these more recent models that structure the textbooks in the field (e.g., Dick & Carey, 1996; Kemp, Morrison, & Ross, 1998). For example, the Kemp, Morrison, and Ross model contains nine elements (their preferred term) instead of five (pp. 5-7):

Contextual design and ISD have different backgrounds. ISD models are process models for the development of instruction or instructional systems. In this context, “systems” refers to the interrelatedness of all the parts of an instructional program and the attempt of the development process to account for the many parts and their interdependencies. ISD primarily targets instructional content (objectives, material, sequencing, testing). Contextual design grew out of very different soil—a soil in which “systems” means “information systems,” i.e., computers, software, and related technology. As a (computer) system design method, contextual design focuses on how best to design systems (hardware, software) to meet customers’ needs. While these needs may include learning or training, the concern is less with learning how to do something than with actually doing it—quickly, cheaply, effectively. With instructional design, content is nearly always critical. With contextual design, as will be seen below, work practice is critical. Though they sprang from different soil, contextual design and ISD have some occasion to become acquainted. One reason is that learning must be taken into account if work performance is to excel. A second reason—and the one motivating this case study—is that learning itself is a variety of “work.” Moreover, with the growth of online learning environments, designing instruction (or learning) is not always easily separable from the design of the technology used in delivery. This linkage is not new. Instructional designers have had to concern themselves with the design of delivery technology for decades. But the capability and malleability of computer-based and especially Web-based delivery technologies has heightened the need for instructional designers to attend to technology design. I will return to this distinction

1. 2. 3. 4. 5. 6. 7. 8. 9.

Instructional problems Learner characteristics Task analysis Instructional objectives Content sequencing Instructional strategies Designing the message Instructional delivery Evaluation instruments

Kemp, Morrison, and Ross add some additional overarching topics such as project management, planning, and support services, and state that not all steps need be included in every situation, nor do the steps need to be strictly linear (pp. 5-7). They also emphasize the need for formative evaluation and revision during design (pp. 162-163).

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at the end of the chapter. While some instructional designers may have the luxury—or the curse—of designing instruction within a predetermined technical framework, others must concern themselves with the simultaneous design of instruction and its delivery technology. Still others design delivery technologies without designing instruction at the same time, hoping (or naively assuming) that the technology will suit the educational needs it purports to address. Such is the case I will introduce later, after first describing contextual design.

Overview Contextual design is a user-centered design methodology created by Karen Holtzblatt and Hugh Beyer to address the needs of commercial software and information system development (Beyer & Holtzblatt, 1998). Contextual design emphasizes the need to base design decisions on a shared understanding of how real people do real work in real contexts. Contextual design has been applied to such varied design problems as enterprise portals, system administration tools, and library systems (Holtzblatt, 2001; Rockwell, 1999; Curtis et al., 1999; Normore, 1999). My own experience with contextual design goes back to the early 1990s, when I introduced contextual design into one of Hewlett-Packard’s development groups (Rockwell, 1999; Curtis et al., 1999). Subsequently, I have been exploring the applicability of Contextual Design (and other methods from the field of human-computer interaction) to instructional contexts (Notess, 2001). Because contextual design is described in great detail in Beyer and Holtzblatt (1998), this chapter will provide only a brief overview of the pieces of the process, yet with enough detail to render the case study comprehensible. Contextual design consists of six steps: 1.

Contextual inquiry

2. 3. 4. 5. 6.

Work modeling Consolidation Work redesign User environment design Paper prototyping

In describing each of the six steps, I will make connections, chiefly through examples, to instructional settings.

Contextual Inquiry Designers identify real users (or potential real users) and go visit them in their places of work. The inquiry is a combination of observation and interviewing. The interviewing focuses on understanding the users, their work, and the context of their work. A key assumption behind contextual inquiry is that if you take people away from their work tasks and context, they cannot give you an adequate explanation of their work (what they do, why they do it, how they do it). Their decontextualized explanations are less detailed and less accurate than what you learn if you observe and discuss in situ. The reason for this difference is that skilled workers are skilled and productive because they do not rely exclusively on what is in their conscious awareness. Much of one’s work knowledge is either internalized to the point where it is subconscious, or the knowledge is embedded in the environment, including tools and processes. In contextual inquiry, the interviewer asks the users to continue doing their work while the interviewer observes and plies them with questions about what is happening and why. Contextual inquiry is typically done in one to three hour sessions, and in some situations the session may be recorded, although often this is not necessary. The interviewer takes notes, makes sketches, and asks clarifying questions in order to form a detailed picture of the work. An important function of the inquiry is to arrive at an accurate understanding of the activity being observed.

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Applying Contextual Design to Educational Software Development

As the interviewer watches, he or she will form hypotheses about the work—e.g., why something is being done. The interviewer then articulates the hypotheses to see if they are accurate. Beyer and Holtzblatt (1998, p. 56) call this validation process “interpretation.” Although we use the term “work” to describe what we are interested in understanding, the word should be taken in its broadest sense of purposeful activity. In an educational environment, “work” could include reading, doing assignments, preparing a lesson, lecturing, answering student email, meeting in a study group, browsing the Web, etc. Any of these tasks are potentially relevant targets for contextual inquiry.

•

Work Modeling The contextual interview is followed by the interpretation session. In the interpretation session, the design team (or a subset) meets to hear the interviewer “replay” the interview—to talk through the entire interview, describing what was seen and heard. During the replay, design team members ask clarifying questions and capture data in the following types of models: •

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The flow model identifies the key people/ roles involved in the work and what moves between them (communication, work products). For example, in a classroom setting, the key people are the teacher and the student. Some of the work products that move between them are assignments (teacher-tostudent) and completed homework (studentto-teacher). However, the goal of contextual inquiry is to capture realistic detail, not just idealized descriptions. So a flow model might well include seemingly peripheral people such as departmental secretary or roommate—anyone with whom the user interacted in the course of doing the work of interest. Another important type of data

•

to capture on flow models are work breakdowns. Breakdowns on the model indicate problem areas in the work. For example, if a student is doing homework and is confused about one of the requirements but cannot find his or her assignment sheet, that is a work breakdown. Breakdowns are important because they indicate opportunities for new systems to make improvements. The sequence model captures the actual sequence of steps the user followed, along with what triggered each activity and what the motivating goals and intents were. If work is purposeful activity, it then becomes crucial to understand the intents that drive the work. Nevertheless, much of what people do is the result of certain triggering events in their environment. For example, I may be working on writing a paper—my intent is to finish it and hand it in. But while I’m writing, I notice that my email icon appears, and so I stop what I’m doing and open my e-mail. Reacting or replying to my email may lead to another work sequence and set of intents, which may or may not be relevant to my original intent. But regardless of their relevancy, an interruption is an important aspect of my work environment, one which needs to be taken account of in design (can I find my place in my initial task quickly after I’m diverted into a secondary task?). As with flow models, sequence models also capture work breakdowns. A work sequence breakdown is seen when a user goal is thwarted because the action doesn’t accomplish its purpose, either because it was the wrong action or because it didn’t work properly. A cultural model shows the power, influences, pressures, and emotions that operate in the user’s environment, impacting the work. For example, in a group project, students may feel a certain amount of pressure from the teacher’s expectations and attitudes, but they also respond to expectations within

Applying Contextual Design to Educational Software Development

•

•

the group. In addition, students’ actions may be influenced by their friends, their parents, or by their attitudes towards current events. Instructional technology needs to account for the cultural realities where it is deployed. If you are designing a discussion board for an online class, for example, key decisions need to be made about privacy, protection, and monitoring. These design decisions need to be driven not only by official policy but also by the informal culture. Breakdowns in a culture also occur, manifesting themselves as interpersonal conflict, resentment, anger, cheating, etc. Physical models depict workplace layout, network topologies, the organization of windows on a computer screen, or anything else in the physical environment relevant to the work. Physical models of a student using a home computer to do homework might include such data as the layout of the home computer work area, what windows or icons the students has on the screen, and how the computer is connected to other computers. Breakdowns noted on physical models might include ergonomic issues or inefficiencies in how the environment is organized. Often people find ways to “work around” problems in their environment. Technology redesign has the opportunity to remove these obstacles. Artifact models describe key “things”—artifacts created or used in the course of work, e.g., notebook, bulletin board, cheat-sheet. In an educational context, examples of artifacts include assignment books/planners, grade books, syllabi, course Web pages, and assignment sheets. Since a common role of technology is to move paper-based artifacts online, it becomes particularly important to examine all such artifacts and understand their role in the work. Artifacts are not always used as intended by their designers. Again, breakdowns can be associated with

artifacts as well—the student writes the assignment on a slip of paper that gets lost, or the course website is out of date, has broken links, etc. Each of these models represents important information about the user’s work. Having the design team work together to construct these models enables everyone to design from a common base of understanding. Ideally, the design team is not just instructional designers or technology people. Sharing data in a cross-functional team can help align people with differing motivations and backgrounds around a single purpose (Holtzblatt, 1994).

Consolidation Contextual design typically involves multiple observations. A two-hour observation only reveals slice of the work, and an individual may be idiosyncratic. To broaden their understanding of the work, contextual design teams observe a wide variety of user (or context) types and then consolidate their learnings across users. Taking the results from multiple contextual inquiry modeling sessions, the design team consolidates each type of model across the different users. For example, all the flow models are consolidated into a single consolidated workflow model. Consolidated models are detailed rather than generalized so that important variations in the data are not lost. The work modeling sessions also generate a large number of short notes from the interview that may not fit into any of the models. These notes—sometimes hundreds of them—are consolidated using an affinity diagram process. Consolidated models are used for communicating the work of the design team to a broader audience of stakeholders. Consolidation has a dual emphasis on similarity and difference. Similar work patterns are combined, but differences are not ignored. In an educational setting, there is often a wide variance

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of practice, as a result of individual differences, comfort levels with technology, departmental history and culture, etc. Consolidated models can capture common elements (e.g., instructors produce syllabi or grade assignments) while not losing the variety of details (e.g., syllabi may be online or on paper).

Work Redesign The design team, often with help from the broader audience, creates a vision for how the work could be improved. This vision is developed in some detail with storyboards, which show how the original work story (represented in the consolidated models) is transformed and improved by the new design. The redesign is not just a design of technology (a program or a user interface). It is a redesign of the work practice, the larger system within which the technology operates. This stage of the process is what many people mean by “design”—coming up with new or improved ideas. But in contextual design, the generation and refinement of new ideas emerges from a wealth of shared understanding—of users, their work, and the context of their work. This yields solutions more likely to succeed. Traditionally, many educational systems designs are technology driven: people see new technology and then think of ways to deploy it in educational settings. But without a detailed awareness of how people are learning, teaching, or training without the new technology, people throw technology at problems and achieve random results. For example, there have been numerous reports of “a computer in every classroom” efforts resulting in lots of underused computers. Grounding design in real work data helps avoid this tendency, even on highly technical teams.

User Environment Design This is the phase where the system’s functions and structures are defined in a way that supports the

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new work process as envisioned in the redesign and specified in the storyboards. Beyer and Holtzblatt (1998, p. 306) liken the user environment design (UED) to an architectural model or “floor plan” for the new system. A floor plan for a house shows rooms. The UED shows “focus areas,” which are places in the system where users perform an activity. Often, focus areas become distinct windows or Web pages in the resulting system. Focus areas, and the connections between them, are built by walking through the storyboards and making the focus areas that the storyboards suggest or require. If one were building a learning management system for a corporate environment, focus areas might include browse course calendar, register for a course, review personal development plan, or perform gap analysis against a new job classification. If I am browsing the course calendar and see a class that interests me, I should have a direct link to register for a course. The storyboards help determine the directness (or salience) of the links between focus areas and the data and functions required by each focus area. A “register for a course” focus area, for instance, may need a function for obtaining supervisor approval if the target environment requires such approval. That requirement would have been captured in a sequence and/or flow model and would have been included in the storyboard about signing up for a course.

Paper Prototyping Paper-based user interface prototypes are generated directly from the user environment design and are taken back to users (in their real contexts) to see how well they address users’ needs. Feedback from prototype interviews is incorporated back into the work models, user environment design, and user interface design. Paper prototype iterations continue as new ideas need to be tested during actual system development. Why use paper prototypes when online prototypes are often so easy to create? The answer to this

Applying Contextual Design to Educational Software Development

question lies in the intended use of the prototypes. The prototypes are not intended as exact replicas of the final project, to be given to developers so they know what to build. The purpose of the prototypes is to allow validation of the design with users. Finished-looking online prototypes tend to intimidate users, who are often polite and reluctant to criticize something that looks as if it took a long time to create. Paper prototypes look provisional and can be modified by anyone with a pencil, scissors, or tape. Paper prototypes level the playing field between designer and user so that users can feel comfortable criticizing, reorganizing, changing, and improving. The feedback users give on the prototype has to be sorted into appropriate categories by the design team. One level of feedback is superficial, having only to do with the representation in the user interface. For instance, a button may need to be relabeled “class” instead of “course” if the former term is the familiar one in the target environment. A deeper level of feedback occurs when users identify problems in the system structure. If a user says, “How would I get my supervisor’s permission first?,” the problem may be that the UED provides no function for getting permission from the course registration focus area. However, if the design team never considered the possibility of employees needing permission to take a course, the problem is even deeper—an incomplete understanding of workflow, and so the work models need to be corrected and the changes propagated through all levels of the design.

• •

To this list I would add several more distinguishing characteristics1, even though they are perhaps implicit in the first three. •

•

•

Principles of Contextual Design Contextual Design coheres, in part because it is guided by some underlying principles. Beyer and Holtzblatt identify three principles in their book (1998, pp. 416-421): •

Data: “Ground all design action in an explicit, trustworthy understanding of your

customers and how they work.” (p. 416) The team: “Design is done by people, and managing people is an important part of any design.” (p. 417) Design thinking: “Support the needs of design thinking itself. A design process naturally alternates between working out a piece of design sequentially, then stepping back and considering the whole design as a structure.” (p. 420)

•

Context: Work data is largely embedded in its context—to get the data you have to examine the context. Apart from this examination, the data are not “trustworthy” (as required above). Partnership: Too much technology is foisted on people. The contextual inquiry and paper prototyping steps of contextual design provide a way for users to participate in the design process as expert partners. This yields a better design and facilitates acceptance. Visualization: A key strength of contextual design is the diagrammatic representation of data and design throughout the process. From the initial individual work models to consolidated models and the affinity, to visioning, storyboarding, the UED, and ultimately the paper prototypes, these graphical representations of data and design help the team pay attention to all the various faces of work and manage the design process. Iteration: Contextual design is not strictly linear. Paper prototyping assumes design iteration is necessary (cf., Beyer & Holtzblatt, 1998, pp. 409-411) and leads to iterative refinement of the work products from the earlier phases of the process (consolidated models, affinity, UED). The need for itera-

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tive refinement through prototyping is well known in instructional design (e.g., Tripp & Bichelmeyer, 1990). Many of the elements of contextual design are not unique. Observing users doing real work, examining artifacts, creating diagrams to represent task flow, using paper prototypes—these and other techniques are widely described and, one hopes, widely used. But contextual design is more than just an assortment of techniques to be used as needed; it is a systematic process where each step builds on the preceding ones.

THE CASE STUDY Variations2 is Indiana University’s NSF-funded Digital Music Library project (Variations2, 2002). One of the main goals for the project is to integrate digital music content (audio, video, and scores) into undergraduate and graduate music education. Thus in addition to creating a body of digitized content, the project is developing software that students will use for music listening and analysis assignments. This case study describes how Contextual Design has been applied to the development of this educational software. When this study was carried out, the first version of Variations2 had already been designed and was being developed. The researchers in this study, apart from myself, were not part of the Variations2 software team, but were students in a graduate course in human-computer interaction. One benefit of this arrangement was that most of the researchers were unaware of design work that had already been done for Variations2, so the contextual design process was expected to provide new data to assist with future versions of Variations2, and to confirm or challenge our earlier design decisions. This case study illustrates the contextual

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design process. It describes the activities undertaken and exhibits some of the resultant diagrams and data. It shows the initial contextual inquiry, modeling and consolidation, redesign, and paper prototyping phases. But it omits the system design (user environment design) phase because of the time constraints of the academic semester.

Contextual Inquiry When designing something new, you cannot observe people using that new thing because it does not yet exist. Typically, however, the work that the new tool will support is work that is done today, but with different tools. In this case, music students are of course already going to the music library, listening to music, following along with a score in hand, and performing various kinds of analysis. Researchers therefore conducted contextual inquiry into this current work practice. Five researchers observed undergraduate music students who were completing listening and/or analysis assignments in the Cook Music Library on the IU Bloomington campus. During the observations students were doing real work (class assignments, studying for a test, preparing for a recital) using today’s production system called Variations (Variations, 2002). Researchers then created Contextual Design work models during interpretation sessions.

Flow Model Figure 1 shows one of the individual flow models created after conducting contextual inquiry with a music student preparing for a recital. U1 is the code name for the student. During the interpretation session, the models are drawn on flipchart paper with markers. Subsequently, they may be redrawn or put online. In the model, the bubbles represent roles and

Applying Contextual Design to Educational Software Development

Figure 2. Sequence model

Figure 1. Flow model Peer - help my peers

Asks question

Doesn’t know answer

Assigns pieces

Teacher - direct learning - stimulate growth

U1 (Student) - learn music

Provides training

Librarian - help patrons use resources

the responsibilities those roles demonstrate. The arcs between bubbles show the communication or flow between the roles. A dark, squiggly line (usually drawn in red) indicates a work breakdown. Work breakdowns represent occasions when the student had a difficulty. In this case the student attempted to get an answer to a question but was unable to. This is a fairly simple flow model as studying tends to be a solitary activity. The activities performed by the teacher and the librarian were not actually observed during the inquiry session. However, in response to questions by the researcher, the events were reported by the student. Asking about previous events can yield valuable data. Beyer and Holtzblatt call this “retrospective accounting” (1998, p. 49). Retrospective accounts of real events should not be confused with generalizations about behavior (e.g., “I usually do things this way”), which do not describe actual events and are less accurate guides to understanding.

Sequence Model Figure 2 shows the second page of a sequence model. The sequence model shows four work breakdowns (abbreviated BD on the left-hand side and shown by a dark squiggle on the right-hand

Adjusts volume up by hand during quiet part Adjusts master volume up by hand Mo ves slider back a bit to listen to section again BD?: Overshoots by 40 seconds - but Looks for second recital piece (“schubert and says it’s OK--not piano and sonatas and http”) in a hurry Finds only one in variations--teacher said this isn’t a good one Loads it While loading, looks at some other recordings Scans “Contents” field to see if it includes the right piece BD: hard to scan for piece Finds another one Also loads it Starts listening to first one Intent: identify 2nd Goes to library database search performer page where received Types in performer’s name training BD: misunderstands database search; Decides 1st recording is too slow doesn’t Switches to second recording remember how Goes to google to use it; librarian Types in “bilson and malcolm showed her once and biograph” (BD: Typo) Notices error (? No results?) Goes back, adds “y” to “biography”

side)—occasions when the student had difficulties. The left-hand side of the sequence model captures the researcher’s meta-level notes about what is going on. The right-hand side captures the user’s actions and the system’s response. Typical annotations on the left-hand side capture “intents”—the specific objective the student was trying to accomplish—as well as work breakdowns or other explanatory notes.

Cultural Model The cultural model (Figure 3) shows the person being observed at the center of the surrounding cultural influences. Arrows represent pressures (e.g., a teacher telling the student to play a piece in a particular way) and push back (e.g., the student insisting on following her own interpretive instincts). Most of the cultural model data were gathered through clarifying discussion with the student about why she was doing certain things (retrospective accounting). She reported conver-

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Figure 4. Physical model of the workspace

Figure 3. Cultural model

How WE play it

Play it THIS way

Teacher

Broaden your horizons

I will listen & decide myself

(See next model)

Carrel in M373 Lab

Famous Performers

Up to 5 headphones plug in here. Individual and master volume controls

Student

I’m not technical; I I don’t like forget; train this piece! me

Paper for note-taking goes here

Fingers drum on edge, here!

Use our tools Library Technologists

Figure 5. Physical model of the computer display

sations with her teacher and explained why she was looking for a variety of recordings. She also expressed frustration at how little she knew about how to use the technology. In fact, the library had provided training, but she couldn’t remember what she’d learned.

Physical Model In this study, we captured two aspects of the physical work environment in models: the workspace (Figure 4) and the computer display (Figure 5). Again, the models are annotated to show the relevant pieces and observed behavior, even as trivial as noting that the student drummed her fingers on the edge of the desk. While not all of these details (or indeed details from the other models) may be useful in subsequent design, they help imprint a memorable image of the user’s experience into the minds of the designers.

Artifact Model The artifact model (Figure 6) shows a diagram

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Full-screen web browser, usually with IUCA T BD: Have to scan Contents field to look for a piece

BD: Slider is hard to control accurately

Variations player in corner

of the work artifact, annotated with explanations. In this example, the artifact was a half-sheet of paper upon which the student wrote notes to herself while listening.

Insights At the end of each interpretation session, participants created a list of insights—what we’d learned about the work. Insights from the U1 interpretation session are shown in Figure 7. The “DI” abbreviation after the last insight in the list was a “design idea” offered by one of the researchers. Design

Applying Contextual Design to Educational Software Development

Figure 6. Artifact model M od er a to no r it . y Ba ss mel od S ing ppp

Table 1. Work notes

Timing

7: 30

I II

I II

e met r onom

Three movements of piece Notes to self as reminder on a half-sheet of paper.

ideas are flagged so that we do not confuse them with user data, and so that we can go back and look at our design ideas before we do redesign. While not all of the insights are profound, the seeds of nearly all of our significant work redesigns were captured in one or more insight lists.

U1

1

Profile: performance student prep. for recital; pieces memorized; listening to interpretations to compare to teacher’s.

U1

2

Realizes (too late) that Variations doesn’t work on a Mac.

U1

3

Moves to another computer with a different monitor, but it is also a Mac.

U1

4

In Var., moved back 40s too far using slider bar.

U1

5

She does not use a score b/c it distracts her; pieces already memorized.

U1

6

Her teacher is very opinionated but compromise on interpretations is possible.

U1

7

Teacher comments have influence on her choice of recital pieces.

U1

8

Hard to scan ‘contents’ field for a piece on a CD.

U1

9

Asks interviewer how to search a library database.

U1

10 No results for search for performer name in library DB.

U1

11 Misspelling error in Google search query: ‘biograph’ instead of ‘biography’.

U1

12 Goes to “bad” results page; not clear which results pages are best.

U1

13 Wanted the bio. info. purely for her own knowledge.

U1

14 Domain ‘experts’/larger community standards influence her perception of appropriate performance time, interpretation, etc.

U1

15 Listens to music on CDNow/Borders instead of using available library recordings; possible professor influence.

U1

16 Q: Is she going to go back and do detailed listening? Is high level all she needs?

U1

17 Frequent IE browser error messages; public access computers have to be ‘retrained’ for profiles.

U1

18 Q: Why didn’t she use Var. track buttons or Options menu?

U1

19 Has never been instructed on how to use Var.; would like a “Clippie” feature to assist her.

U1

20 DI: Include a link to info. about the performer.

work Notes During the interpretation session, a running list is kept of any data that is mentioned but doesn’t fit into one of the other work models. Table 1 shows the work notes from the U1 interpretation session.

Figure 7. Interpretation session insights •

Lack of Mac support w/ Variations is a problem

•

“High-level” listening tasks are different from detailed listening

•

High-level listening can be multi-tasking

•

Finding resources on the Web is easier/more familiar than using library resources

•

Need user education

•

Didn’t use any non-visible features (hidden behind button or menu)

•

Need a way to see all performances of the same piece. DI: do this in Variations.

Consolidation After all of the interpretation sessions were complete and all the individual models were built, we consolidated the models. Table 2 shows one of our consolidated models—the consolidated sequence model. (Space does not permit the inclusion of all of the consolidated models.) Reading down the left-hand column yields a sense of the main kinds of work in which Variations use was involved. The center column lists the users’ intents for each of the activities. The right-hand column shows alternative steps users took to accomplish their intents, at a higher level of abstraction than the individual models. In addition to consolidating work models, we also consolidated the work notes, using an af-

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Table 2. Consolidated sequence model Activity Figure out what to do

Intent • Focus activity • Prepare for correct assignment or test

Gather/locate resources

• Find the piece needed for assignment • Locate multiple versions of pieces to prepare for performance

Listen (overview)

1. Get a sense for the piece 2. Determine appropriateness of the piece for intended need 1. Analyze chord changes 2. Find transitions in the music 3. Prepare for transcription

Listen (detailed/ analytical)

Abstract Step • Read paper syllabus copy or • Go to course website Go to course syllabus site or • Go to IU Cat o Course reserve lists -oro Search or • Go to CDNow.com or other commercial site 1. Search 2. Listen to clips

Table 3. Affinity section for “I figure out or find what to work on” I figure out or find what to work on • How I figure out the assignment o Reads description in syllabus + underlines two sentences to “keep straight what I should be listening for…” o Looks in day planner for assignment notes. Planner is a detailed artifact with many course notes. o She says that she still hasn’t obtained a binder for her paper scores and class notes. “I really need” one, she says. o Found piece in Variations from class syllabus [explained this after interview started]. o Checked e-mail using Webmail interface for message and link to class webpage from instructor. o Working Section F of syllabus. o BD: “Transcription looks wrong compared to example and what I am hearing…” • How I find what I need to listen to o Listens to music on CDNow/Borders instead of using available library recordings; possible professor influence. o Hard to scan ‘contents’ field for a piece on a CD. o Always tries to use listening list in course reserve page to find correct version. o Retrospective: got to Variations from class listening list. o BD: Locating correct version of piece difficult in IUCAT. o BD: Initially played the wrong piece in the Variations player. Says “it doesn’t seem right.” • How I find what I need to look at o BD: Hard to specify score or recording in IUCAT, search criteria are for books not music. o DI: Would like to be able to find paper score along with recording in same search. • I need to find more information o Goes to “bad” results page; not clear which results pages are best. o Wanted the bio. info. purely for her own knowledge. o DI: Include a link to info. about the performer.

• Determine if appropriate music has been found 1. Click play on variations 2. Listen 3. Make notations on paper score 1. Click play on variations player 2. Listen 3. Stop 4. Restart from beginning -or- pause 1. Move slider back to try to find beginning of section 2. Click play • Make notations on score • Repeat

finity diagram process. In all, the interpretation sessions generated 99 work notes. Table 3 shows data from one of the five major sections of the resultant affinity diagram. Work breakdowns (BDs) and design ideas (DIs) also find their way into the affinity.

paper prototypes. Figure 8 shows one part of the redesign sketch, indicating the ability to navigate by measure number: •

work Redesign Based on what we had learned about users of Variations, we brainstormed ideas for making improvements that would better support people’s work, creating rough vision sketches on flipchart paper. We decided to focus on addressing three recurrent issues: figuring out how to use the system, finding the desired media, and doing detailed listening. We created storyboards showing improved methods for each of these tasks. The storyboards were summarized in a redesign diagram that became the basis for the

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•

Live Help: To help users more easily figure out how to use the system, we decided to take advantage of current instant messaging technology to design a means for users to ask for help from a librarian right when the help is needed. This way, instead of having to flounder or ask students working nearby, users could instead get immediate expert advice from reference desk personnel. Search for Music: A second observed difficulty was searching for a listening piece. The current library catalog system does not make this easy. Students could do keyword searches for the name of the composer or the piece, but then had to sift through many bibliographic records, visually scanning for

Applying Contextual Design to Educational Software Development

Figure 8. Part of the redesign diagram

•

the name of the piece or composer amid many other fields of data. Our improvement idea here was to allow for more specific searches such as composer, performer, and/or genre, in effect introducing music-specific concepts into the search and retrieval process. Set Loop/Navigate by Measure: The Variations tool provides a slider control and typical media control buttons (previous/next track, fast forward/rewind, pause, stop, and play). Nevertheless assignments often required students to answer questions about specific segments of a musical work, e.g., “Discuss several ways in which Beethoven creates disruption, or discontinuity, in the music between measures 37-59.” To locate the exact measures, students referred to a paper-based score and typically played with the slider trying to find the right location so they could answer the question. Often,

students wanted to listen to the same segment repeatedly in order to complete their analysis. Yet the only precise locations in the audio by which students could navigate were the beginnings of each track. So they resorted to using the slider to try to find the right location. In our work redesign, we provided two ideas: allow students to navigate by measure number and to set specific repeat loops. Given that these redesign ideas emerged from acquaintance with the data in isolation from the development team, it was interesting to note the extent to which our redesign correlated with the Variations2 design work. Of these three redesign ideas, the first one (Live Help) was wholly absent from the Variations2 plans. This is not surprising, because contextual design, with its comprehensive look at what people are doing to accomplish their work, often uncovers problems that are systemic and reach beyond the feature set of a particular piece of software. The second redesign idea (Search for Music) is squarely in the center of one of the main emphases of Variations2, so the Contextual Design work merely confirmed the need for cataloging schemes that work well for music. The third redesign idea (Set Loop) had mostly emerged in Variations2, which can provide measure-by-measure navigation and offers a bookmarking mechanism somewhat analogous to the “set loop” functionality. Version 1 of Variations2 provides a way for users to add a bookmark at any point in a recording or score. These bookmarks can then be brought up in a separate window and used for navigation. Our research results yielded a mechanism more tuned to the student tasks we observed—listening repeatedly to a segment with a defined beginning and end.

Paper Prototyping Paper-based prototypes based on the redesigns

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created were taken back to the music library, where we put them in front of music students and asked them to attempt to “use” the prototype to do a task they needed to do or had recently done. Figure 9 shows one of the paper prototypes. As can be seen, the prototypes are quick and easy to construct and invite correction or improvement. In the earlier discussion of paper prototyping, I mentioned that paper prototyping interviews gather data on three levels. Data may address the user interface, the underlying system structure, or our understanding of the user’s work practice. The 31 issues we gathered from our paper prototyping interviews were therefore categorized appropriately. Table 4 shows a few examples from each of these three categories. User interface problems tend to be the easiest to fix. In the Table 4 examples, re-labeling will solve any of these issues. Issues with system structure run a little deeper and have a large impact on design. For example, providing “in-depth information about a musical piece from within Variations” would certainly require additional user interface elements and would likely require significant changes to the underlying implementation in order to provide this additional data within (or from) the listening window. Work practice

issues have the potential to transform a design completely. In the Table 4 examples, the first two work practice issues have fairly minor impact, but the last issue rules out the entire mechanism used by the paper prototype to set markers—a separate dialog box with data entry requirements is too disruptive; students need a simple way to set a mark while listening. So the impact of this work practice issue ripples through the system design and the user interface design. The paper prototypes were rapidly developed and tested, and after only four interviews, we gathered a wealth of user data that validated and invalidated aspects of our user interface design, system structure, or understanding of the work practice.

The Ongoing Value of the Data Although the contextual design piece was only a small and somewhat disconnected effort in the scope of the overall Variations2 project, results from the study continue to influence the require-

Table 4. Sample categorized feedback from paper prototype interviews Category

Issue

User Interface

“Ask the Librarian” should include the word “live” or some other note to let users know that the function is live help.

User Interface

Better name for theory listening may be bookmark repeat or loop listening.

User Interface

Likes “Set Loop” and recognizes this terminology to set marks in music; didn’t care for the term “bookmark”. She suggested “begin loop” and “end loop”.

System Structure

Students want the ability to get in-depth information about a musical piece from within Variations.

System Structure

Leave theory listening window open while repeating.

Work Practice

Many students may not know in advance how many times they want a section repeated, so maybe just keep repeating until the user stops.

Work Practice

Grads want to compare recordings often -- this subject would like to see unique information in the title window to distinguish between different recordings.

Work Practice

There is a whole type of listening we missed in the first round of interviews. This is listening for some sort of theme that needs to be supported by a marker that won’t stop the piece, but allows the student to go back easily and hear again.

Figure 9. Sketch for a paper prototype

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Applying Contextual Design to Educational Software Development

ments and design for future versions. For example, in response to the loop concept, we are now planning to include, in version 2, the ability to define an excerpt—a segment with a beginning and end (not just a beginning as with the bookmark concept). In addition, having observed the difficulty students have finding the right listening piece, we have prototyped a visual syllabus that would allow students to go to an online syllabus with a link directly to the pieces or segments for each assignment (Notess & Minibayeva, 2002).

CONTEXTUAL DESIGN AND INSTRUCTIONAL SYSTEMS DESIGN Having now seen contextual design described and having also seen an example of its use, what can we conclude about the relationship between it and ISD? I offer several thoughts. First, contextual design may be both susceptible and resistant to two recent criticisms of ISD. Second, contextual design may offer some needed process commonality between the design of instruction and the design of the technology used in instructional delivery. And finally, contextual design offers a vision for the future, a future in which contextual design enables cross-functional teams to deliver superior learning solutions.

Contextual Design and Criticisms of ISD Recently, ISD has been the target of significant criticism (Gordon & Zemke, 2000). Among the criticisms are the assertions that ISD: • •

Is slow and cumbersome Focuses designers on following a process rather than on achieving meaningful results.

I call out these two criticisms because, over the years, I have heard these same criticisms leveled

at contextual design by casual observers of the process. Seeing the work that goes into contextual design and the bewildering (to outsiders) array of flip-chart paper and sticky notes it generates, some people assume that contextual design is a long, slow process. In my experience, the slowest part of the process is not the data gathering, analysis, redesign, or prototyping—these can move very quickly. In our case study, the first three phases of contextual design—interviewing, interpreting, and consolidating—were all completed within two weeks’ time, by people who were working at other jobs and/or enrolled in other classes. The redesign, prototyping, prototype interviews, and the consolidation of the results took even less total time although they were spread over a month of calendar time due to a vacation break and delays in recruiting students for the prototype interviews. It is this latter problem of recruiting interviewees and scheduling the interviews that can stretch out contextual design schedules. But that problem becomes manageable as design teams gain more experience with the issues. Any disciplined process takes time to learn and execute. Beyer and Holtzblatt (1990) offer many suggestions on how to make contextual design fast and effective for a variety of situations. The second criticism of ISD mentioned above is that it can focus people on following a process instead of achieving results. Certainly this can happen with contextual design too: it is always a risk when there is a detailed process to learn. However, contextual design may be less susceptible to this weakness than other processes because of its insistence on putting all members of the design team face-to-face with real users. Most users don’t particularly care what process we use, but they do care a great deal about the results we give them. Having the images of those users imprinted on our minds and their work breakdowns called out in red on the work models we’ve built, we are less likely to disregard users’ needs in favor of following a process for its own sake. In a follow-up article, Zemke and Rossett

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(2002) summarize some of the responses received to the original Gordon and Zemke article that criticized the ISD process. They divided the responses into two groups. The first group blames ISD itself as a faulty process and the second group blames practitioners of ISD for faulty practice. Zemke and Rossett conclude that, though ISD may be flawed, it is (quoting Marc Rosenberg) “the best thing we have if we use it correctly” (p. 34). In both the original article and the follow-up, there is repeated emphasis on the expertise of the practitioner having a large impact on the quality of the results. Contextual Design, in my experience, has a similar dependency. In all of the Contextual Design projects I’ve seen that could be termed successful, there was strong leadership from one or more skilled practitioners who had developed those skills under the watchful eye of an expert. Typically, an expert has internalized the principles a process expresses, and can therefore adapt and streamline the process to become effective in a given situation. Contextual design needs this expertise as much as does ISD.

Technology Design and Instructional Design In our case study, we see contextual design used to guide the design of a software system deployed in an educational context, and indeed it seems as useful here as it is for other systems’ design problems. It also seems apparent, even though our case study did not examine this, that contextual design might provide a useful approach for integrating technology design and instructional design. The need for this integration is experienced whenever an instructional designer and a software developer try to work together on a project or whenever the instructional designer tries to fill the role of both technology designer and instructional designer. Consider, for example, if our case study had involved not only the development of software for music listening and analysis, but had also included the development

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of instructional content—a set of lessons to teach music theory, for instance. Table 5 illustrates, by partial example, both the dichotomy and unity of interests between an instructional designer and a software designer during just the analysis and design phases of such a project. Instructional designers have their own expertise: learning theory, evaluation, message design, etc. Software designers also have their own expertise: programming, software architecture, characteristics of different technologies, etc. But both types of designers have a common interest in understanding the intended users and uses of the system, and both have a large stake in the design of the user interface. Contextual design might help address the common information and design needs in such a cross-functional team.

A Vision for the Future Imagine a cross-functional team, including both

Table 5. Dichotomy and unity of interests between instructional and software design Analysis

Instructional Designer

Software Designer

What music theory content do the students need to learn? What are the characteristics of the music students? In what contexts will they be learning (classroom, library, dorm room, computer lab)?

What kinds and amounts of data will be needed (audio, image, video, text)? What kinds of user interaction with the data are needed? What technical constraints do we face (network bandwidth, display resolution)?

Who will be using the system (how many users, how often, etc.)? What tasks does the system need to support? What other people besides students will need to interact with the system (e.g., faculty? librarians? administrative staff? graduate assistants?) Design

What are the instructional objectives or outcomes we are trying to achieve? How should the content be sequenced? What instructional strategies best fit the goals and content?

What technologies (e.g., database, user interface, programming languages, software packages, networking, security) should we use? What software architecture best meets the requirements?

What should the user interface look like? How can we best support collaboration and communication among users?

Applying Contextual Design to Educational Software Development

technologists and instructional designers as well as graphics designers, editors, and other stakeholders. All team members participate in all phases of contextual design: observing users/learners, building work models, consolidating the data, redesigning the work, and then designing and prototyping the new solution, refining the design through prototype interviews. The technologists bring their expertise in what can be done with different technologies, and the instructional designers bring their expertise in designing effective learning experiences. Other stakeholders bring their own expertise. Each role has its own responsibilities in delivering the final system, but all are designing based on a shared understanding of the users, and all have learned a common representation for modeling that understanding. All have learned a common process for arriving at and refining that understanding. For the vision just described to be tenable, we have to continue exploring the usefulness of contextual design for instructional designers. The present case study offers an introduction to the approach and, I hope, enough encouragement to continue the exploration (see the Appendix at the end of this chapter for a summary of contextual design steps and benefits). One major area of need is to investigate the extent to which contextual design is valuable for instructional content design. Contextual inquiry and work modeling look promising for the job/task analysis pieces of instructional needs analysis. An unanswered question is whether subsequent steps of designing content such as sequencing and the selection of instructional strategies are helped, or at least not hindered, by Contextual Design. Others are recommending or exploring the application of contextual design methods to educational problems. Maish Nichani points to contextual design as one of several approaches which exemplify what he calls “empathic instructional design” (Nichani, 2002). Allison Druin, in her work with designing technologies for children, has developed a design approach

called “Cooperative Inquiry,” which leverages in particular the contextual inquiry piece of contextual design (Druin, 1999). She has applied this approach in designing a digital library for young children (Druin et al., 2001). If future studies in these areas offer good results, it may well be that contextual design or a derivative can provide a process whereby user-centered technology design and learner-centered instructional design work together for the benefit of all.

ACKNOwLEDGMENT I would like to thank my students who helped with this research: George Bergstrom, Rovy Branon, Jason Cooper, and Cynthia Spann. I would also like to thank Elizabeth Boling and Karen Holtzblatt for providing expert critique. This material is based upon work supported by the National Science Foundation under Grant No. 9909068. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

REFERENCES American Society for Training and Development. (1988). Basics of instructional systems development. Info-Line (Issue 8803). Beyer, H., & Holtzblatt, K. (1998). Contextual design: Defining customer-centered systems. San Francisco: Morgan Kaufmann Publishers. Beyer, H., & Holtzblatt, K. (1999). Contextual design. Interactions, 4(1), 32-42. Curtis, P., Heiserman, T., Jobusch, D., Notess, M., & Webb, J. (1999). Customer-focused design data in a large, multi-site organization. Proceedings of the CHI 99 Conference on Human Factors in

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Computing Systems (pp. 608-615). Dick, W., & Carey, L. (1996). The systematic design of instruction (4th ed.). New York: Harper Collins. Druin, A. (1999). Cooperative inquiry: Developing new technologies for children with children. Proceedings of the CHI 99 Conference on Human Factors in Computing Systems (pp. 592-599). Druin, A., Bederson, B., Hourcade, J.P., Sherman, L., Revelle, G., Platner, M., & Weng, S. (2001). Designing a digital library for young children: An intergenerational partnership. Proceedings of the ACM/IEEEE-CS Joint Conference on Digital Libraries (JCDL ’01) (pp. 398-405). Fardouly, N. (1988). Instructional design of learning materials. Retrieved August 3, 2002, from University of New South Wales Faculty of the Built Environment website http://www.fbe.unsw.edu. au/learning/instructionaldesign/materials.htm Gordon, J., & Zemke, R. (2000). The attack on ISD. Training, 37(4), 42-53. Holtzblatt, K. (1994). If we’re a team why don’t we act like one? Interactions, 1(3), 17-20. Holtzblatt, K. (2001). Creating new work paradigms for the enterprise portal. SAP Design Guild. Retrieved on August 3, 2002, from http://www. incent.com/pubs/SAPDGPortal.html Kemp, J., Morrison, G., & Ross, S. (1998). Designing effective instruction (2nd ed.). Upper Saddle River, NJ: Prentice-Hall. Nichani, M. (2002, February). Empathic instructional design. Retrieved on August 7, 2002, from http://www.elearningpost.com/features/archives/001003.asp Norman, D. (1988). The psychology of everyday things. New York: Basic Books.

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Normore, L. (1999, January/February) Reference in context explores the reference process. OCLC Newsletter, n. 237. Retrieved on August 3, 2002, from http://www.oclc.org/oclc/new/n237/ research/01research.htm Notess, M. (2001, August). Usability, user experience, and learner experience. eLearn Magazine. Archived at http://www.elearnmag.org/subpage/ sub_page.cfm?section=4&list_item=2&page=1 Notess, M., & Minibayeva, N. (2002). Variations2: Toward visual interfaces for digital music libraries. Presented at the Second International Workshop on Visual Interfaces to Digital Libraries at the ACM+IEEE Joint Conference on Digital Libraries, July 18, Portland, OR. Paper available online at http://vw.indiana.edu/visual02/Notess.pdf Rockwell, C. (1999). Customer connection creates a winning product. Interactions, 4(1), 50-57. Tripp, S.D., & Bichelmeyer, B. (1990). Rapid prototyping: An alternative instructional design strategy. Educational Technology Research and Development, 38(1), 31-44. Variations. Retrieved August 3, 2002, from http:// www.dlib.indiana.edu/variations/ Variations2: The IU Digital Music Library. Retrieved August 3, 2002, from http://variations2. indiana.edu Zemke, R., & Rossett, A. (2002). A hard look at ISD. Training, 39(2), 26-34.

ENDNOTE 1

The principles of context and partnership are mentioned by Beyer and Holtzblatt as principles of contextual inquiry (1998, pp. 47-56), but these principles are important motivators for Contextual Design as a whole.

Applying Contextual Design to Educational Software Development

Appendix: Outline Of cOntextuAl design Step Contextual Inquiry

Activities

Benefits

Observe people doing their real work in its actual

Can be used for instructional system design (study

setting. During and/or afterwards, ask questions to

potential users of the system) or content (study people

determine what was going on and why.

doing the work you want people to learn).

Build models from observational data: work flow, Work Modeling

sequence, cultural, physical, and artifact. Highlight breakdowns in current work process.

Consolidation

Work Redesign

User Environment Design

Paper Prototyping

Modeling is best done by a cross-functional team. Technologists, instructional designers, subject matter experts, etc., can work from a shared understanding of the data.

Look for the patterns across observation sessions.

Model consolidation helps designers see the core work

Identify the patterns in consolidations of the above

patterns the system needs to support. Consolidation

models without losing the detail.

also allows key differences to be identified.

Create a vision for improved work practice. De-

Tying the storyboards back to the consolidated models

velop storyboards to elaborate and illustrate the

increases the chances of user acceptance and avoids

new design.

technology-driven design.

Develop a system “floor plan” showing the needed modules and how they connect.

This phase lets instructional designers participate in the technology design and help ensure it stays grounded in real user work practice.

Create low-fidelity, paper-based prototypes. Inter-

Prototype interview feedback addresses multiple

view users with these prototypes to validate (and

levels of the design: the models, the system, and the

improve) the design.

user interface.

This work was previously published in Instructional Design in the Real World: A View from the Trenches, edited by A.-M. Armstrong, pp. 74-103, copyright 2004 by Information Science Publishing (an imprint of IGI Global).

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Chapter 2.45

A Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones Akio Koyama Yamagata University, Japan Leonard Barolli Fukuoka Institute of Technology, Japan

­AbstrAct In this chapter, a campus information providing system (CIPS) for cellular phones is proposed. By using this system, the search time to find the necessary information in the campus is reduced. Users can access the system using the cellular phone terminal and by clicking the links or by inserting a keyword in the form they can get easily the campus information. The system has four agents, which deals with Web information required by users, Net News, the student’s login state, campus navigation and the filtering of the received campus information for cellular phone terminal. Therefore, the proposed system can provide different media information to a cellular phone. By using the proposed ubiquitous system, the users are able to get the information anywhere

and anytime. The system performance was evaluated using a questionnaire. From the questionnaire results, we found that the system was able to show the required information.

IntroductIon Presently, the number of cellular phone users is increasing at a very fast rate. They have Internet access from their phones and have access to many different kinds of information (ZDNet, 2001). By using the cellular phone, it is possible to get various services such as everyday life information, money exchange rates, databases, games, and music distribution. NTT DoCoMo has already

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

started a service called IMT-2000, which is an international standard of the mobile communication systems and can be used all over the world (NTT DoCoMo, 2003). Therefore, a lot of information can be handled using the cellular phone. Now, many universities have their own campus information on their homepages and the students by using homepage, e-mail, Net News, campus bulletin board can get a lot of information (Fujii & Sugiyama, 2000; Kubota, Maeda, & Kikuchi, 2001). However, the logging in a terminal, starting to work with a personal computer (PC), or going to see a bulletin board takes a lot of time. Also, getting information by starting a browser and typing a command such as “mnews” it will take time because two or more systems should be used. Therefore, getting the information by using only one system anywhere and anytime will decrease the number of operations and will save more time for users. In order to solve these problems, we propose campus information providing system (CIPS). This system supports a user which acquires the campus information. By using the cellular phone, the user is able to get the information anywhere and anytime. The proposed system is implemented by the common gateway interface (CGI) and consists of four agents (Hattori, Sakama, & Morihara, 1998). The Web information agent (WIA) gets the information on Web databases, such as a timetable, examination schedule and syllabus information. The Net News agent (NNA) gets the information on Net News, such as newsgroups of the university. The Personal Information Agent (PIA) can search the information of a vacant terminal or the users who login. The navigation agent (NA) navigates a room in the campus. Using these agents, the proposed system can provide different media information for the cellular phone. When a user wants to get the information using the proposed system, the system gets the information and filters it in order to optimize the information for cellular phone. In order to evaluate the performance of the proposed system, the system was used by ten

cellular phone users, and by using a questionnaire we asked them some questions such as how was the information search by the proposed system compared with other information searching systems, how was the system operation, and what merits and demerits have the proposed system. The chapter is organized as follows. First, we introduce the proposed system. Next, we discuss the performance evaluation. Finally, some conclusions are given.

PROPOSED SYSTEM System Outline The proposed system has the following features. • •

•

It is possible to check the campus information anytime and anywhere One system realizes various services (Web, news, students login state, vacant terminal information in the computer rooms and campus navigation) The information retrieval and the information filtering are done in the real time. If the information is updated, a new information can be retrieved automatically

The system is implemented by CGI using Perl language. The system structure is shown in Figure 1. When a user accesses the system, a menu screen appears as shown in Figure 2. The user selects the information by choosing a link in the menu. After that, the system agents are activated and they check for the required information in the WWW and news servers. They refer the commands output and analyze the order how the maps should be shown. Then, they filter this information in order to be appropriate to be shown in the mobile phone terminal.

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Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

Figure 1. System

Figure 2. System interface

Request of information providing

Send page to cellular phone

CGI Page transfer server

Web server News server

WIA NNA

Command

PIA

Map

NA Acquiring information

wIA The information of some universities is accessible via the university homepage. The students can get via the homepage the information such as timetable, examination schedule, and the syllabus information. However, when the information whereabouts are unknown, it is necessary to follow the links in order to search inside the Web page. Even if the page structure is known, it may take time to get the required information. Furthermore, when someone wants to find some information, he needs to find a computer in order to access the homepage. Therefore, considering these cases, it will be better to use a mobile phone information system. By using WIA, the proposed system is able to support the information retrieval anywhere and anytime.

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[1] Timetable, examination schedule [2] Net news [3] Campus navigation [4] Subject retrieval [5] Terminal retrieval

Flow of Web Information Retrieval When a user wants to find Web information, a link related to the timetable, examination schedule, or subject retrieval is chosen from the menu screen. When, the timetable and examination schedule are chosen, a new screen by which can be selected the class and a day as shown in Figure 3 is displayed. When the subject retrieval is chosen, a new screen which depicts a form where a keyword can be inserted as shown in Figure 4 is displayed. An agent accesses the WWW server and requires a corresponding page. From the retrieved page, the agent extracts the information related with the required subject information (subject name, professor name, the number of units, etc.) and deletes unnecessary character sequences such as the line tags. Then, the character sequence which processing is finished is used in the HTML sentence and is displayed in the cellular phone. The timetable shows the subject name, professor name, and classroom name from the first period to the fifth period. The examination schedule shows the examination subject name, class, and classroom name from the first period to the fifth period. The subject reference shows the subject name, course year, required/selection, the number of units, and the professor name. Furthermore, in the subject reference, if the link showing the

Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

Figure 3. Operations required for timetable information

Figure 4. Operations required for subject

Input keyword Select a class name

Select a day

Subject: Computer Literacy II Course Period: 2nd Course Year: 1st Course Type: Required Credit: 3 Professor: X, Y, Z

1st period Operating System (Professor A) 2nd period Database (Professor B) rd 3 period Computer System (Professor C) 4th, 5th period Programming Ex. (Professor D)

Outline

4.

outline of a subject is chosen, the outline and the purpose of the subject can be seen.

WIA Algorithm 1.

2.

3.

When a user demands information providing, the agents accesses the WWW server and retrieve the related page information. The source of the retrieved page is checked line by line. In the case of timetable or examination schedule, a line with the subject name is extracted. In the case of subject retrieval, the line containing the character sequence which the user inserted in the form is searched and the line which matches the information is extracted. The tag is deleted from the extracted line.

Select a subject

5.

6.

In the case of a timetable or an examination schedule, the character sequence whose the unnecessary tag was deleted is stored in array based on the day information. In the subject retrieval case, the information is stored in the variables for every subject name or number of units, and the subject outline and purpose are stored in an array. In the case of the timetable information or examination schedule, based on the user demands, a suitable information is chosen from the array. The information is adapted for the HTML format of the cellular phones. In subject retrieval case, a variable is used for the HTML sentence of the cellular phones, and when a link related to the subject outline is chosen, the information stored in the array is displayed.

NNA There is another way to get the campus information by using Net News. A student can get news

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Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

by typing “mnews” command. By using Net News various information such as newsgroups, announcements, circle information, class information, part-time job, lost articles, can be found. However, the same as in WEB information, to get Net News information the user should have a computer connected to the campus network. In our system, by using NNA, the user is able to find the information anywhere and anytime.

NNA Algorithm

Flow of Net News Information Retrieval

1.

When a user wants to find some information using Net News, from the menu, the “News” link is selected. As shown in Figure 5, an agent accesses a news server and chooses a group to which the report is submitted from the newsgroup of the University of Aizu. Then, it makes a list and the prepared list is displayed. The user chooses a group from a newsgroups list. The agent selects from the chosen group 10 articles and prepares and displays the title list.

Then, the agent investigates whether in the selected articles there is any space in the head of line. Since the space is displayed as it is on a cellular phone, in the case when there is a space, it is deleted. The article which processing is finished is used in the HTML sentence and it is displayed on the cellular phone.

2.

3.

4. 5.

When there is a demand for information providing from a user, a news server is accessed and the university newsgroups list is displayed. Each newsgroup is investigated whether exist or not submitted articles. If there are groups which have not submitted articles, they are deleted from the newsgroups list. The newsgroup which the user selected is accessed, and the titles for ten articles are retrieved and displayed. The article which the user selected is retrieved and stored in an array. The array information is filtered to be appropriate for displaying in the cellular phone.

PIA Figure 5. Operations required for net news information

Select a newsgroup

Select an article Announcement of Yearbook Spec: A4 size, 30 pages, All colors Price: 7000 Yen

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The students of the University of Aizu receive the lectures and solve the exercises using UNIX workstations. To find who is using the terminal, a special command is used. However, for the sake of security, we will not give the command name in this paper. If the special command can be used for cellular phone, it will save a lot of time. By using the PIA, the student login state can be displayed on a cellular phone.

Flow of Personal Information Retrieval In order to get the result from the special command, a link of terminal search is chosen from a menu

Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

screen. Next, as shown in Figure 6, a user inputs a keyword (student ID number or name or host name) into the form, and the form is transmitted. The results of the executed the special command are written in a file every five minutes using the “crontab” command. The PIA extracts the line which matches the keyword. When there are many people, the list of the individual name is created and displayed. The results of the executed the special command are ordered as login ID, name, host name, place, and login time. By using these data, the information of the person who matches the keyword is chosen from the name list and is displayed. But, for the sake of security, the login ID, host name and terminal names are not displayed. Instead, the terminal number and the room number are displayed. Moreover, when the same person has accessed two or more terminals using rlogin or telnet, the special command indicates the whole state of the user. In Figure 6, the user’s name is shown after “REAL-LIFE,” the terminal number and the room number are shown after “HOST.” When many hosts are accessed by one person from the same place (this place is shown after “FROM”), only the host which the time is close to the present one is selected and shown after “HOST” and the login time is shown after “SINCE.” This is done in order to ensure that the person shown in “FROM” is the same with the person logged here. Moreover, when the same person has accessed the system from the different places, both cases are displayed. The PIA can be used also for searching a vacant host, for getting how many terminals of each exercise room are vacant, or which terminal is vacant using the result of the special command.

Figure 6. Personal information in cellular phone

NA

In the case when a user uses the NA for the university guidance, he inserts in the form its present location and destination as shown in Figure 7. The NA offers the map made beforehand by us. It may happen that a professor moves from a room to another one. In this case, if this information is updated in the university homepage, the map

The campus map is placed everywhere in the University of Aizu. This is very convenient for the students who come for the first time to the university. However, if a place is far from another one, it is difficult to memorize the route. Also, if a

X106

Input keyword

Select a student

student can not find the map, he can not get even the route. Recently, KDDI started a new service called “GPS keitai.” The function called eznavigation provide the accurate location information (KDDI, 2001). However, the detailed navigation for inside a building does not exist. Based on NA, the proposed system is able to guide the students using the university map.

Flow of Navigation Information Retrieval

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Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

information can be also updated. On the map, a red circle shows a present location and a blue arrow shows the destination. A user moves from the present location to the destination. When a user arrives at the destination, as shown in Figure 8, the picture which shows the next destination from that place is displayed by choosing a link called “next.” Thus, when a user arrives at a place

shown in the map, the link which displays the next picture is chosen. When a user lose the way, a link showing the present location is selected. Then, the user inserts in a form as keywords the rooms of an institution, the number of stairs of a building, etc. By using these keywords, the present location is judged and the route from the present location to the destination is shown again.

Figure 7. Navigation agent structure

Analyze the shortest path

WWW server Input keyword

Figure 8. Navigation operation

Input keyword

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Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

PERFORMANCE EVALUATION Experiment Outline We evaluated the proposed system using a questionnaire. Ten cellular phone users used the system and the performance of the system was evaluated using three items: the system operation, viewability, and convenience.

Questionnaire Results and Considerations The questionnaire results are shown in Table 1. The name of users are shown as A, B, C, D, E, F, G, H, I, and J. We received the following comments for the agents 1.

2.

3.

4.

WIA • For timetable and examination schedule it will be better to be able to select a day and a period. NNA • In some articles, without reading the full text, the user could get the meaning. Therefore, if the text will be divided in some parts it will be better. PIA • Sometime the special command can not be used. Therefore, in such a case if there is another procedure it will be better. NA • The entrance of the room was not clear.

Based on the previously mentioned comments, we conclude that a cellular phone system provides good campus information. However, the system operation and its viewability should be improved.

Table 1. Questionnaire results Users

Operation

Viewability

Convenience

A

Good

Normal

Good

B

Normal

Good

Good

C

Normal

Good

Good

D

Good

Normal

Good

E

Normal

Normal

Good

F

Good

Normal

Good

G

Normal

Bad

Good

H

Normal

Normal

Good

I

Good

Normal

Good

J

Normal

Bad

Good

CONCLUSION In this chapter, a campus information providing system for cellular phones was proposed. A user can check the campus information easily using the cellular phone anywhere and anytime. In order to get the information, a user needs to insert only the keywords in a form and to click a link. After that, the system retrieves the information and filters it in order to be appropriate for a cellular phone. When information is updated, the retrieved information is updated automatically. The proposed system can provide different media information such as Web, News, login state, vacant terminal, and campus navigation to the cellular phone. The performance evaluation shows that a cellular phone system is convenient and provides good campus information. However, the system operation and its viewability should be improved.

REFERENCES Fujii, K., & Sugiyama, K. (2000). Route guide map generation system for mobile communication. IPSJ Journal, 41(9), 2394-2403.

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Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

Hattori, F., Sakama, Y., & Morihara, I. (1998). Intelligent agent communication, Ohmsha.

NTT DoCoMo Home Page. (2003). Retrieved from http://www.nttdocomo.co.jp/

KDDI Corporation. (2001). Retrieved from http:// www.kddi.com/release/2001/1129-1/

ZDNet JAPAN. (2001). Retrieved from http:// www.zdnet.co.jp/mobile/0112/07/n_tca.html

Kubota, K., Maeda F., & Kikuchi, Y. (2001). Proposal and evaluation of pedestrian navigation system. IPSJ Journal, 42(7), 1858-1865.

This work was previously published in Future Directions in Distance Learning and Communication Technologies, edited by T. K. Shih, pp. 94-107, copyright 2007 by Information Science Publishing (an imprint of IGI Global).

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Ubiquitous Agent-Based Campus Information Providing System for Cellular Phones

Section 3

Online and Distance Learning Tools and Technologies This section presents an extensive coverage of various tools and technologies available in the field of distance learning that practicing educators can utilize to develop different techniques in support of the development of distance learning educational programs. Research within this section enlightens readers about fundamental research on some of the many tools used to facilitate and enhance the distance learning experience. Also explored are some of the recent technologies that have been deployed in support of distance learning course offerings. With more than 35 chapters, this section offers a broad treatment of some of the many tools and technologies within the online and distance learning community.

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Chapter 3.1

Core Principles of Educational Multimedia Geraldine Torrisi-Steele Griffith University, Australia

IntroductIon The notion of using technology for educational purposes is not new. In fact, it can be traced back to the early 1900s during which school museums were used to distribute portable exhibits. This was the beginning of the visual education movement that persisted throughout the 1930s, as advances in technology such as radio and sound motion pictures continued. The training needs of World War II stimulated serious growth in the audiovisual instruction movement. Instructional television arrived in the 1950s but had little impact, due mainly to the expense of installing and maintaining systems. The advent of computers in the 1950s laid the foundation for CAI (computer assisted instruction) through the 1960s and 1970s. However, it wasn’t until the 1980s that computers began to make a major impact on education (Reiser, 2001). Early applications of computer resources included the use of primitive simulation. These early simulations had little graphic

capabilities and did little to enhance the learning experience (Munro, 2000). Since the 1990s, there have been rapid advances in computer technologies in the area of multimedia production tools, delivery, and storage devices. Throughout the 1990s, numerous CD-ROM educational multimedia software was produced and was used in educational settings. More recently, the advent of the World Wide Web (WWW) and associated information and communications technologies (ICT) has opened a vast array of possibilities for the use of multimedia technologies to enrich the learning environment. Today, educational institutions are investing considerable effort and money into the use of multimedia. The use of multimedia technologies in educational institutions is seen as necessary for keeping education relevant to the 21s t century (Selwyn & Gordard, 2003). The term multimedia as used in this chapter refers to any technologies that make possible “the entirely digital delivery of content pre-

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Core Principles of Educational Multimedia

sented by using an integrated combination of audio, video, images (two-dimensional, threedimensional) and text,” along with the capacity to support user interaction (Torrisi-Steele, 2004, p. 24). Multimedia encompasses related communications technologies such as e-mail, chat, video-conferencing, and so forth. “The concept of interaction may be conceptualised as occurring along two dimensions: the capacity of the system to allow individual to control the pace of presentation and to make choices about which pathways are followed to move through the content; and the ability of the system to accept input from the user and provide appropriate feedback to that input.… Multimedia may be delivered on computer via CD-ROM, DVD, via the internet or on other devices such as mobile phones and personal digital assistants or any digital device capable of supporting interactive and integrated delivery of digital audio, video, image and text data” (Torrisi-Steele, 2004, p. 24). The fundamental belief underlying this chapter is that the goal of implementing multimedia into educational contexts is to exploit the attributes of multimedia technologies in order to support deeper, more meaningful learner-centered learning. Furthermore, if multimedia is integrated effectively into educational contexts, then teaching and learning practice must necessarily be transformed (Torrisi-Steele, 2004). It is intended that this chapter will serve as a useful starting point for educators beginning to use multimedia. This chapter attempts to provide an overview of concepts related to the effective application of multimedia technologies to educational contexts. First, constructivist perspective is discussed as the accepted framework for the design of multimedia learning environments. Following this, the characteristics of constructivist multimedia learning environments are noted, and then some important professional development issues are highlighted.

theoretIcal foundatIons for the role of multImedIa In educatIonal contexts Traditionally, teaching practices have focused on knowledge acquisition, direct instruction, and the recall of facts and procedures. This approach suited the needs of a society needing “assembly line workers” (Reigeluth, 1999, p. 18). However, in today’s knowledge-based society, there is a necessity to emphasize deeper learning that occurs through creative thinking, problem solving, analysis, and evaluation, rather than the simple recall of facts and procedures emphasized in more traditional approaches (Bates, 2000). The advent of multimedia technologies has been heralded by educators as having the capacity to facilitate the required shift away from traditional teaching practices in order to innovate and improve on traditional practices (LeFoe, 1998; Relan & Gillani, 1997). Theoretically, the shift away from traditional teaching practices is conceptualized as a shift from a teacher-centered instructivist perspective to a learner-centered constructivist perspective on teaching and learning. The constructivist perspective is widely accepted as the framework for design of educational multimedia applications (Strommen, 1999). The constructivist perspective describes a “theory of development whereby learners build their own knowledge by constructing mental models, or schemas, based on their own experiences” (Tse-Kian, 2003, p. 295). The constructivist view embodies notions that are in direct opposition to the traditional instructivist teaching methods that have been used in educational institutions for decades (see Table 1). Expanding on Table 1, learning environments designed on constructivist principles tend to result in open-ended learning environments in which: •

Learners have different preferences of learning styles, cognitive abilities, and prior knowledge; they construct knowledge

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Core Principles of Educational Multimedia

Table 1. Key principles of the constructivist view of teaching and learning vs. key principles of the instructivist view of teaching and learning

•

•

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CONSTRUCTIVIST

INSTRUCTIVIST

Learner-centred perspective: the learner is the focus of the learning environment – learners as individuals

Teacher-centred perspective: the teacher is focus of the learning environment- group learning

Encourages students independence in learning

Encourages student dependence on teacher

Teacher as facilitator that acts as a guide

Teacher as instructor

Learner and facilitator engage in a collaborative learning experience

Teacher in control of learning and in position of power over learner

Learners actively constructing knowledge in their own individual manner

Learners passively acquiring knowledge from the instructor

Process of knowledge acquisition is important – how are learners interacting with the learning environment

Acquisition of content and factual knowledge is key abjective of learning episode

Curriculum design as development of knowledge spaces which allow active exploration by the learner

Curriculum design as goal orientated, strictly structured and ordered knowledge transmission

Higher order thinking skills emphasised, createive thinking, problem solving, evaluation, synthesis

Behavioural objectives focusing on recall of facts and procedures, surface learning

Open-ended learing environment (OELE)

Directed instruction

in individual ways by choosing their own pathways. Learning is affected by its contexts as well as the beliefs and attitudes of the learner; Optimal learning occurs when learners are active learners (e.g., learn by doing and learn by discovery; Learning is a process of construction whereby learners build knowledge through a process of scaffolding. Scaffolding is the process whereby learners link new knowledge with existing knowledge;

•

•

Knowledge construction is facilitated through authentic problem-solving experiences; The process of learning is just as important as learning outcomes. Learners are encouraged to “articulate what they are doing in the environment and reasons for their actions” (Jonassen, 1999, p. 217).

Multimedia, by virtue of its capacity f or interactivity, media integration, and communication, can be easily implemented as a tool for informa-

Core Principles of Educational Multimedia

tion gathering, communication, and knowledge construction. Multimedia lends itself well to the “creation and maintenance of learning environments which scaffold the personal and social construction of knowledge” (Richards & Nason, 1999). It is worth noting that the interactivity attribute of multimedia is considered extremely important from a constructivist perspective. Interactivity in terms of navigation allows learners to take responsibility for the pathways they follow in following learning goals. This supports the constructivist principles of personal construction of knowledge, learning by discovery, and emphasis on process and learner control. Interactivity in terms of feedback to user input into the system (e.g., responses to quizzes, etc.) allows for guided support of the learner. This also is congruent with constructivist principles of instruction as facilitation and also consistent with the notion of scaffolding, whereby learners are encouraged to link new to existing knowledge. Using the constructivist views as a foundation, the key potentials of multimedia to facilitate constructivist learning are summarized by Kramer and Schmidt (2001) as: • •

•

•

•

Cognitive flexibility through different accesses for the same topic; Multi-modal presentations to assist understanding, especially for learners with differing learning styles; “Flexible navigation” to allow learners to explore “networked information at their own pace” and to provide rigid guidance, if required; “Interaction facilities provide learners with opportunities for experimentation, context-dependent feedback, and constructive problem solving”; Asynchronous and synchronous communication and collaboration facilities to bridge geographical distances; and

•

Virtual laboratories and environments can offer near authentic situations for experimentation and problem solving.

the effectIve ImplementatIon of multImedIa In educatIonal contexts Instructional design principles Founded on constructivist principles, Savery and Duffy (1996) propose eight constructivist principles useful for guiding the instructional design of multimedia learning environments: • • • •

• • • •

Anchor all learning activities to a larger task or problem. Support learning in developing ownership for the overall problem or task. Design an authentic task. Design the tasks and learning environment to reflect the complexity of the environment that students should be able to function in at the end of learning. Give the learner ownership of the process to develop a solution. Design the learning environment to support and challenge the learner’s thinking. Encourage testing ideas against alternative views and contexts. Provide opportunity for and support reflection on both the content learned and the process itself.

Along similar lines, Jonassen (1994) summarizes the basic tenets of the constructivist-guided instructional design models to develop learning environments that: • •

Provide multiple representations of reality; Represent the natural complexity of the real world;

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Core Principles of Educational Multimedia

• • •

• •

Focus on knowledge construction, not reproduction; Present authentic tasks (contextualizing rather than abstracting instruction); Provide real-world, case-based learning environments rather than pre-determined instructional sequences; Foster reflective practice; Enable context-dependent and content-dependent knowledge construction; and support collaborative construction of knowledge through social negotiation, not competition among learners for recognition.

professional development Issues

Principle 1: Transformation in Practice as an Evolutionary Process Transformation of practice through the integration of multimedia is a process occurring over time that is best conceptualized perhaps by the continuum of stages of instructional evolution presented by Sandholtz, Ringstaff, and Dwyer (1997):

•

•

While multimedia is perceived as having the potential to reshape teaching practice, oftentimes the attributes of multimedia technologies are not exploited effectively in order to maximize and create new learning opportunities, resulting in little impact on the learning environment. At the crux of this issue is the failure of educators to effectively integrate the multimedia technologies into the learning context.

•

[S]imply thinking up clever ways to use computers in traditional courses [relegates] technology to a secondary, supplemental role that fails to capitalise on its most potent strengths. (Strommen, 1999, p. 2)

•

The use of information technology has the potential to radically change what happens in higher education...every tutor who uses it in more than a superficial way will need to re-examine his or her approach to teaching and learning and adopt new strategies. (Tearle, Dillon, & Davis, 1999, p. 10) Two key principles should underlie professional development efforts aimed at facilitating the effective integration of technology in such a way so as to produce positive innovative changes in practice:

•

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Stage One: Entry point for technology use where there is an awareness of possibilities, but the technology does not significantly impact on practice. Stage Two: Adaptation stage where there is some evidence of integrating technology into existing practice Stage Three: Transformation stage where the technology is a catalyst for significant changes in practice.

The idea of progressive technology adoption is supported by others. For example, Goddard (2002) recognizes five stages of progression:

•

•

•

Knowledge Stage: Awareness of technology existence. Persuasion Stage: Technology as support for traditional productivity rather than curriculum related. Decision Stage: Acceptance or rejection of technology for curriculum use (acceptance leading to supplemental uses). Implementation Stage: Recognition that technology can help achieve some curriculum goals. Confirmation Stage: Use of technology leads to redefinition of learning environment—true integration leading to change.

The recognition that technology integration is an evolutionary process precipitates the second key principle that should underlie professional development programs—reflective practice.

Core Principles of Educational Multimedia

Principle 2: Transformation is Necessarily Fueled by Reflective Practice A lack of reflection often leads to perpetuation of traditional teaching methods that may be inappropriate and thus fail to bring about “high quality student learning” (Ballantyne, Bain & Packer, 1999, p. 237). It is important that professional development programs focus on sustained reflection on practice from the beginning of endeavors in multimedia materials development through completion stages, followed by debriefing and further reflection feedback into a cycle of continuous evolution of thought and practice. The need for educators to reflect on their practice in order to facilitate effective and transformative integration of multimedia technologies cannot be understated. In addition to these two principles, the following considerations for professional development programs, arising from the authors’ investigation into the training needs for educators developing multimedia materials, are also important: •

•

•

•

•

The knowledge-delivery view of online technologies must be challenged, as it merely replicates teacher-centered models of knowledge transmission and has little value in reshaping practice; Empathising with and addressing concerns that arise from educators’ attempts at innovation through technology; Equipping educators with knowledge about the potential of the new technologies (i.e., online) must occur within the context of the total curriculum rather than in isolation of the academic’s curriculum needs; Fostering a team-orientated, collaborative, and supportive approach to online materials production; Providing opportunities for developing basic computer competencies necessary for

developing confidence in using technology as a normal part of teaching activities.

lookIng to the future Undeniably, rapid changes in technologies available for implementation in learning contexts will persist. There is no doubt that emerging technologies will offer a greater array of possibilities for enhancing learning. Simply implementing new technologies in ways that replicate traditional teaching strategies is counterproductive. Thus, there is an urgent and continuing need for ongoing research into how to best exploit the attributes of emerging technologies to further enhance the quality of teaching and learning environments so as to facilitate development of lifelong learners, who are adequately equipped to participate in society.

conclusIon This chapter has reviewed core principles of the constructivist view of learning, the accepted framework for guiding the design of technologybased learning environments. Special note was made of the importance of interactivity to support constructivist principles. Design guidelines based on constructivist principles also were noted. Finally, the importance of professional development for educators that focuses on reflective practice and evolutionary approach to practice transformation was discussed. In implementing future technologies in educational contexts, the goal must remain to improve the quality of teaching and learning.

references Ballantyne, R., Bain, J.D., & Packer, J. (1999). Researching university teaching in Australia:

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Themes and issues in academics’ reflections. Studies in Higher Education, 24(2), 237-257.

tional media. Educational Technology, Research and Development, 49(1), 53-75.

Bates, A.W. (2000). Managing technological change. San Francisco: Jossey-Bass.

Relan, A., & Gillani, B. (1997). Web-based instruction and the traditional classroom: Similarities and differences. In B.H. Khan (Ed.), Webbased instruction (pp. 41-46). Englewood Cliffs, NJ: Educational Technology Publications.

Goddard, M. (2002). What do we do with these computers? Reflections on technology in the classroom. Journal of Research on Technology in Education, 35(1), 19-26. Hannafin, M., Land, S., & Oliver, K. (1999). Open learning environments: Foundations, methods and models. In C. Reigeluth (Ed.), Instructional-design theories and models (pp. 115-140). Hillsdale, NJ: Erlbaum. Jonassen, D.H. (1994). Thinking technology: Toward a constructivist design model. Educational Technology, Research and Development, 34(4), 34-37. Jonassen, D.H. (1999). Designing constructivist learning environments. In C. Reigeluth (Ed.), Instructional-design theories and models (pp. 215-239). Hillsdale, NJ: Erlbaum. Kramer, B.J., & Schmidt, H. (2001). Components and tools for on-line education. European Journal of Education, 36(2), 195-222. Lefoe, G. (1998). Creating constructivist learning environments on the Web: The challenge of higher education. Retrieved August 10, 2004, from http://www.ascilite.org.au/conferences/wollongong98/ascpapers98.html Munro, R. (2000). Exploring and explaining the past: ICT and history. Educational Media International, 37(4), 251-256. Reigeluth, C. (1999). What is instructional-design theory and how is it changing? In C. Reigeluth (Ed.), Instructional-design theories and models (pp. 5-29). Hillsdale, NJ: Erlbaum. Reiser, R.A. (2001). A history of instructional design and technology: Part I: A history of instruc-

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Richards, C., & Nason, R. (1999). Prerequisite principles for integrating (not just tacking-on) new technologies in the curricula of tertiary education large classes. In J. Winn (Ed.) ASCILITE ’99 Responding to diversity conference proceedings. Brisbane: QUT. Retrieved March 9, 2005 from http://www.ascilite.org.au/conferences/brisbane99/papers/papers.htm Sandholtz, J., Ringstaff, C., & Dwyer, D. (1997). Teaching with technology. New York: Teachers College Press. Savery J.R. & Duffy T.M. (1996). An instructional model and its constructivist framework. In B Wilson (Ed.), Constructivist learning environments: Case studies in instructional design. Englewood Cliffs, NJ: Educational Technology Publications. Selwyn, N., & Gorard, S. (2003). Reality bytes: Examining the rhetoric of widening educational participation via ICT. British Journal of Educational Technology, 34(2), 169-181. Strommen, D. (1999). Constructivism, technology, and the future of classroom learning. Retrieved September 27, 1999, from http://www.ilt. columbia.edu/ilt/papers/construct.html Tearle, P., Dillon, P., & Davis, N. (1999). Use of information technology by English university teachers. Developments and trends at the time of the national inquiry into higher education. Journal of Further and Higher Education, 23(1), 5-15. Torrisi, G., & Davis, G. (2000). Online learning as a catalyst for reshaping practice—The experiences of some academics developing online materials.

Core Principles of Educational Multimedia

International Journal of Academic Development, 5(2), 166-176. Torrisi-Steele, G. (2004). Toward effective use of multimedia technologies in education In S. Mishra & R.C. Sharma (Eds.), Interactive multimedia in education and training (pp. 25-46). Hershey, PA: Idea Group Publishing. Tse-Kian, K.N. (2003). Using multimedia in a constructivist learning environment in the Malaysian classroom. Australian Journal of Educational Technology, 19(3), 293-310.

key terms Active Learning: A key concept within the constructivist perspective on learning that perceives learners as mentally active in seeking to make meaning. Constructivist Perspective: A perspective on learning that places emphasis on learners as building their own internal and individual representation of knowledge. Directed Instruction: A learning environment characterized by directed instruction is one in which the emphasis is on “external engineering” (by the teacher) of “what is to be learned” as well as strategies for “how it will be learned” (Hannafin, Land & Oliver, 1999, p. 122).

Instructivist Perspective: A perspective on learning that places emphasis on the teacher in the role of an instructor that is in control of what is to be learned and how it is to be learned. The learner is the passive recipient of knowledge. Often referred to as teacher-centered learning environment. Interactivity: The ability of a multimedia system to respond to user input. The interactivity element of multimedia is considered of central importance from the point of view that it facilitates the active knowledge construction by enabling learners to make decisions about pathways they will follow through content. Multimedia: The entirely digital delivery of content presented by using an integrated combination of audio, video, images (two-dimensional, three-dimensional) and text, along with the capacity to support user interaction (Torrisi-Steele, 2004). OELE: Multimedia learning environments based on constructivist principles tend to be openended learning environments (OELEs). OELEs are open-ended in that they allow the individual learner some degree of control in establishing learning goals and/or pathways chosen to achieve learning. Reflective Practice: Refers to the notion that educators need to think continuously about and evaluate the effectiveness of the strategies and learning environment designs they are using.

This work was previously published in the Encyclopedia of Multimedia Technology and Networking, edited by M. Pagani, pp. 130-136, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.2

Knowledge Management as a Reference Theory for E-Learning: A Conceptual and Technological Perspective Miltiadis D. Lytras, Athens University of Economics and Business, Greece Ambjörn Naeve Royal Institute of Technology (KTH), Stockholm, Sweden Athanasia Pouloudi Athens University of Economics and Business, Greece

abstract E-learning as a scientific field is in an era of transition. In the last decade, several scientific fields worked as reference disciplines for the promotion of the value delivery that new technologies offered to learning. In this paper, we will emphasize the role of knowledge management as a reference theory for e-learning.

IntroductIon

through technology requires a multifold consideration of issues that fall into the categories of cognition, behavior, beliefs, attitudes, and social constructions such as networks, communities, group formations, recommendations, and utilization of human capital. Knowledge management, on the other hand, poses a critical question to researchers: How do we justify abstractions that provide a systematic way for the management of knowledge? Extremely interesting literature covers a wide range of issues that relate to knowledge management processes

E-learning provides an extremely challenging research context. The facilitation of learning

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Knowledge Management as a Reference Theory for E-Learning

and knowledge category models, as well as to knowledge networks and communities. From another point of view, the discussion of knowledge management strategies is based on a five-layer approach: Artifact, Individual, Group, Organization, and Interorganizational Network are recognized as critical locations where knowledge can be identified and utilized. This chapter summarizes the importance of knowledge management for e-learning. In the past, researchers have tried to investigate the role of knowledge management for e-learning. The convergence of these approaches is visualized in Figure 1. In Figure 1, knowledge management is presented as a critical diode, where a plethora of knowledge objects have to be managed and adopted in order to fulfill the requirements for learning utilization. The issue of learning utilization is not a linear function nor even guided from a well-defined cause-and-effect formula, where learning outcome is directly related to independent variables. Knowledge management can be utilized in many different ways in the context of e-learning. A first point of argument is the direct linkage of knowledge to learning content and, thus, the need to justify the ways that diverse knowledge objects are used in an e-learning system in order to provide learning material. The downsizing of knowledge in reusable parts, the annotation of

relevant knowledge objects, and the establishment of effective management mechanisms require the promotion of standards as well as the specification of a clear learning strategy. These issues are critical milestones for knowledge management and e-learning convergence. In this article, two general pillars from the knowledge management literature are discussed further: •

•

The knowledge artifact approach, where knowledge management’s main emphasis is on the epistemology of knowledge and the specification of relevant types of knowledge. As depicted in Figure 2, there is a direct linkage of knowledge types to learning content types. The debate on tacit and explicit knowledge provides an epistemological background for the analysis of their implications in an e-learning environment: In the past years, the e-learning community seems to have been dominated by the learning objects research stream, where the relevant research agenda includes semantic annotation, embodiment of instructional design, and guidance on the transformation of learning content to the learning object metaphor. The knowledge process approach, where several value-adding processes summarize

Figure 1. Investigating knowledge management role in e-learning Kno Man wledge age men t Downsizing Knowledge Providers Knowledge Objects

Cataloguing Annotation Learning Adoption Motivation Reusability Standards

rning E-lea tion Adop

Recommendations

Learning Content

Standards Pedagogy Motivation Semantic Density

Learning Strategy & Scenario

Community

Learners

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Knowledge Management as a Reference Theory for E-Learning

significant transformation mechanisms and a life cycle that brings together providers and users of knowledge. A number of complementary approaches to knowledge category models promote an interesting discussion for types of learning content that can be identified and managed in an e-learning setting. The evolution of databases, multimedia technologies, human computer interactivity, adaptive hypermedia, mobile and wireless technologies, and the advent of the Semantic Web have moved the emphasis from the traditional artifact approaches to a process approach to the utilization of unstructured content. Figure 2 summarizes the underlying linkage between knowledge types and learning content. Knowledge management literature utilizes further the epistemology of knowledge and promotes a number of knowledge category models.

The knowledge management research community has promoted an interesting discussion on the role of ontological engineering toward the development of adaptive, flexible, and dynamic systems. Miguel-Ángel Sicilia and Elena García from the University of Alcala, Spain, provide an excellent discussion on the convergence of formal ontologies and standardized e-learning. Current efforts to standardize e-learning resources are centered on the notion of a learning object as a piece of content that can be reused in diverse educational contexts. The embodiment of instructional design to learning objects poses new challenges for the standardization process: In e-learning, the key issue is neither the interoperability nor the reusability of content, but rather the support of learning as a cognitive and constructive process. For the development of this critical milestone, knowledge management and ontologies provide several alternative options and new reference

Figure 2. A rich picture Knowledge Types

Tacit

Explicit

Knowledge Management and E-learning Convergence

Community

Flow of Instruction

Learners Community / Network Learners Unstructured

Structured

Learning Content

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Knowledge Management as a Reference Theory for E-Learning

models for the representation and diffusion of content. Value delivery through annotation and semantics will be forthcoming as an excellent research context for e-learning. The other critical point of view for the convergence of knowledge management and e-learning refers directly to the community of learners that promote the social character of e-learning. This community is anticipated to have a great potential of unutilized knowledge, which basically is considered to be unstructured. The next chapter summarizes a quite promising work: Sheizaf Rafaeli and Yuval Dan-Gur from the University of Haifa, Mt. Carmel, Israel, and Miri Barak from the Massachusetts Institute of Technology, discuss the importance of the social recommendation systems on e-learning. In such systems, users can receive guidance in locating and ranking references, knowledge bits, test items, and so forth. In these systems, users’ ratings can be applied to items, users, other users’ ratings, and, if allowed, raters of raters of items recursively. This is an interesting issue concerning the flow of instruction. The traditional author-led design and implementation of online learning experiences require a greater openness and utilization of contributions directly derived from learners (with some prerequisites). In the same context, agent-based e-learning systems will realize sophisticated and integrated approaches to dynamic learning content assembly. H.K. Yau, E.W.T. Ngai, and T.C.E. Cheng from Hong Kong Polytechnic University, Hong Kong, PR China, provide an interesting conceptual model and an architecture for an agent-based and knowledge-management-enabled e-learning system.

dIscussIon of key proposItIons and the contrIbutIon of thIs chapter The initial idea for a special issue on the role of knowledge management for E-learning was derived from the extraordinary interest of many researchers all around the world to investigate conceptual frameworks and technologies from the knowledge management field toward the promotion of more effective, dynamic, and personalized e-learning. The decision of JDET editors to approve our idea for this chapter was a critical milestone, and several alternative strategies were considered in order to promote a high-quality issue with balanced contributions. With an acceptance rate of 15%, we decided finally to accept three areas that cover a wide range of knowledge management aspects and pose significant research questions for the future. Moreover, we decided to follow a strategy in which selected topics as a whole volume could promote a balanced theoretical and practical overview with a significant contribution for the emerging, knowledge-management-enabled research agenda in e-learning. In this section, we will try to outline the contribution of this special issue. From the beginning, we have said that in each section of the issue, there are several significant “hidden” aspects that could initiate a PhD research. In Figure 3, the e-learning and knowledge management convergence is linked to five general pillars of literature: • • • • •

Knowledge Category Models Knowledge Flows Knowledge Representation Knowledge Management Processes and Life Cycle Models Communities and Social Capital

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Knowledge Management as a Reference Theory for E-Learning

Figure 3. Aspects of e-learning and knowledge management convergence E-Learning as

Knowledge Management Main Approaches

Resources / Content Downsizing Learning Objects Semantic Density Learning Adoption Standards

Process/ Educational-Social Instructional Design Learning Strategy Learning Activities

Knowledge Category Models Knowledge Flows

Knowledge Representation

KM Processes Life Cycle Models

Community

E-learning Facilitation Social / Community Exploitation

In this issue, Sicilia and Garcia discuss from an interesting point of view the convergence of formal ontologies and standardized e-learning. In fact, they extend the debate on learning objects’ metadata and provide to the reader an excellent and intensive presentation of organizational and technical issues that have to be addressed. According to their concluding remark, “the use of modern Web-enabled ontology languages has been sketched, and an illustration of the benefits of the integration of learning object descriptions has been provided through OpenCyc examples. More comprehensive learning object specifications, including the description of learning process, should be addressed in the future.”

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From this point of view, the annotation of the learning objects has to promote further the dynamic features of modern e-learning systems as well as their value proposition. In fact, this criticism brings forward the need to define learning objects. The literature on learning objects is extremely substantial (McGreal, 2004). The limited length of this chapter does not allow us to present it in detail. Instead, we will summarize the basic properties of a learning object. In other words, we have selected some typical characteristics for learning objects found either in the literature or in practical implementations of e-learning systems. In Figure 4, a three-dimensional space provides

Knowledge Management as a Reference Theory for E-Learning

Figure 4. Outlining learning object metaphors in e-learning

Learning Object “Metaphors” in E learning

Social

Discussions

Knowledge features

Beliefs & Meaning

Comments & Recommendations Interactive Sessions

Semi-Dynamic pages

Learning Seanarios

Mature

Adaptive Hypermedia

Artifact

Semantics and Metadata

Solid Ontologies

Gran u

larity

Semantic Items n -1...

the setting for our constructive point of view. Several items directly related to learning objects have been summarized, and three paths (from several others already mapped in our research) have been indicated. The basic idea is that three critical perceptions provide significant considerations for value adding features of learning objects: •

•

Knowledge features: Ranges from artifact to social (an analogy of explicit to tacit); the great challenge is to investigate new ways for utilizing meaning, belief, and community. Granularity: refers to the modular nature of learning objects. This dimension ranges from solid, in which case only a component realizes the LO, to Semantic Items, where a significant number of semantic items provide new meaningful insights to learning objects

•

(e.g., context, learning processes, target groups, etc.). Maturity: This dimension is a critical but rather blurred dimension. Maturity is perceived as a continuous process where the usage of innovative technologies provides new possibilities for adaptive and personalized e-learning environments. This aspect will not be discussed in detail in this chapter but provides input for the process of designing new generations of learning objects.

In Figure 4 we have specified a number of heterogeneous metaphors for learning objects that depict the quite different approaches in LO design: static HTML pages, comments and recommendations, learners’ profiles, interactive sessions, adaptive hypermedia, learning scenarios, ontologies, semantic, and metadata

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provide an overall idea. From this point of view, it is extremely interesting as outlined in the work of Rafaeli, Dan-Gur, and Barak, to investigate new methods for incorporating tacit knowledge elements in learning objects. The annotation of LOs should not be considered as a technical issue but purely as a cognitive process with direct linkage to the learning outcome. According to Rafaeli, Dan-Gur, and Barak, the convergence of recommenders in e-learning requires learners to employ critical judgment, first when they rank various knowledge items, and then when they choose the source of recommendation. The sharing of their judgments and information in a way that encourages collaboration and trust can increase the delivered value of an e-learning system and also has the potential to enhance critical thinking and promote the growth of tactic knowledge among its users. By implementing various recommendation approaches, learners engage in critical reading and learn to choose the most sought and required knowledge items. Moreover, participating in the community of learners might designate the intuitions that are gained through experience and enhance the sense of competency acquired by participating in communities of practice. The work of Sicilia and Garcia as well as the interesting proposition of Rafaeli, Dan-Gur, and Barak justify the need to modify our mental model of learning objects in order to meet pedagogical as well as social and learning challenges. In this context, we will use the term Semantic learning cube in order to summarize this new paradigm for learning content. Learning cubes are an alternative proposition for learning objects representation and utilization. In fact, they can be defined in a simple way: learning objects (LOs) with well defined meaning and scalable embedded pedagogical value that can be adjusted to social characteristics of learners promoting a mature learning experience in highly adaptive e-learning environments. From their definition, learning cubes require significant work in several issues and themes

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which can be undertaken in the near future from several researches whose origins are in various disciplines: artificial intelligence, semantic web, knowledge management, e-business, and so forth. Concerning well-defined meaning, ontologies and the Semantic Web set specific challenges to the Semantic learning cube paradigm. In our perspective, ontology of learning cubes provides answers to three critical questions: 1. 2. 3.

How do we codify scalable pedagogical value in LOs? How do we incorporate social or tacit knowledge features with LOs? How do we outline the paths for mature learning experiences through constructive learning tasks?

Scalable embedded pedagogical value relates to semantic annotation of content that promotes the learning context realization in terms of learning processes. The benefits from such a practice have been pointed out in extensive literature. Associating meaning to content through semantic markup will facilitate search, interoperability, and the composition of complex information through an interoperable meaning (Fiensel et al., 2000). According to Lytras et al. (2002a), e-learning cannot be evaluated as value-adding without promoting unique learning experiences. Semantic learning cubes go a step further in this approach by developing a Semantic-Web-enabled tool for the composition of learning cubes and relevant services (marketplaces of learning cubes, dynamic learning cubes composition). Towards this direction, the work of Yau, Ngai and Cheng is extremely important. The design and implementation of intelligent agents is critical for the promotion of e-learning. In order to be successful, intelligent infrastructures supporting unique learning experiences and fulfilling a motivating learning context will have to be based on well chosen theoretical abstractions.

Knowledge Management as a Reference Theory for E-Learning

Multiagent Societies will provide an extremely interesting research area within the near future. The mobility of agents is also an exciting area for further research. Mobile agents that travel from one machine to another (e.g., from a desktop to a palm pilot) will promote the vision of ubiquitous learning. In order to summarize this chapter, we have tried to develop a “rich misture” of research problems that are linked directly to the convergence of knowledge management and e-learning. In Figure 5, a four-level approach to e-learning strategy is provided. Four levels provide a concrete strategy targeting the utilization of different knowledge items for learning purposes: •

•

•

Integrated information factory layer: Refers to a number of diverse technologies like agents, Semantic Web, mobile and wireless networks, knowledge management technologies, and so forth, that have established a holistic approach for the management of information resources. Knowledge handling layer: This layer addresses the key demand for managing knowledge in codified formats and social flows. Thus, knowledge artifacts, Social Network, Profiles Management, Specifications of Rules, and logic are issues of critical significance for the performance of knowledge resident in an Information Factory. Learning content layer: In e-learning implementations, this layer is of critical importance. Several dynamic aggregation methods provide the convergence of knowledge handling and learning content layer. Diverse knowledge items are utilized in a learning content item, and for this reason, we have to decide on the structural unit. In our LO Cube approach the learning objects formation is facilitated by the advent of Semantic Web Engineering. This is depicted as the first critical aspect of the research problem: The specification of SW-enabled content

•

formation according to clear descriptive logic. Ontologies and other approaches play a key role in this direction. In our approach, a new ontology titled Learning Process (Figure 5) is the key contribution toward this direction. The second critical aspect of the research problem is the Embedding of Instructional Design Principles in Learning Objects. This ultimate objective requires an extensive transformation of guiding learning theories to principles and guidance for LO construction. In the next step, learning context (Figure 5) is anticipated as the third pillar of our research problem. Learning strategy layer: The fourth layer guides the whole process. Learning strategy has to be crafted, and several decisions have to be made. In Figure 2, we did not provide an exhaustive list of relevant themes, but in our whole approach, there is a concrete discussion of the whole strategy agenda.

Over the next years, we will face an extraordinary interest in research in e-learning and KM. According to Prof. Michael Spector: Technology changes. Technology changes what people do and can do. Technology is changing how people learn and work. Embracing innovation and changes is characteristically human. Technology-based changes are pervasive, which means that researchers interested in the impact of technology on learning and working are living in the best of times. How fortunate. (Spector in Lytras, 2002, Knowledge and Learning Management, Papasotiriou Publications) In this direction, we encourage researchers to continue and to strengthen their interest in the convergence of Knowledge Management and E-Learning. In a visioning section at the end of the chapter titled, “A Knowledge Management Roadmap for E-Learning: The Way Ahead,” we discuss in more detail the future of this convergence.

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Knowledge Management as a Reference Theory for E-Learning

Figure 5. A four-level approach to LOs formation Learning Strategy Layer Return on e-Learning

Learning Sequence

Knowledge Management

……

Learning Content Layer learning objects formation

How?

Learning Content

research problem no. 1

aggregation methods

semantic web engineering

embedding Instructional design in learning objects

learning scenarios

research problem 2

research problem 3

learning theories Instructional principles

adaptive dynamic

Knowledge Handling Layer Social Knowledge Network / Artifacts Profiles Annotation Downsizing Semantic Density Agents

Rules/ Logic

Recommendations Adaptiveness Network Realization Semantic Web

Mobile & Wireless

Reference Layers Profile Matching Multi-criteria

Multimedia Technologies

acknowledgment For their various forms of support in our effforts of compiling this special issue, we would like to express our gratitude to our colleagues in our respective research units: Elpida Prasopoulou, Xenia Ziouvelou, Olga Chaidou, Korina Diamanti, Ilias Kastritis, Irini Kaliamvakou, Lina Ioannou,Ioannis Sideris, Maria Tsaousoglou, Nikos Tsipouras, Panagiotis Ziotopoulos, Achilleas Anagnostopoulos, Nikos Labropoulos and Sotiris Michalakos from the ELTRUN Research Unit (http://www.eltrun.gr) of the Athens University of Economics and Business in Greece, and Mikael Nilsson, Matthias Palmér, Fredrik Paulsson, Claus Knudsen, Henrik Eriksson, Pär Sjöberg, Richard Wessblad and Ioana Predonescu

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KM technologies

Integrated Information Factory Layer

from the KMR group (http://kmr.nada.kth.se) at the Royal Institute of Technology (KTH) in Stockholm, Sweden. We would also like to acknowledge a number of colleagues within our national and international networks of excellence for technology enhanced learning, people who share a common vision for the future role of advanced learning technologies and who have extraordinary abilities to collaborate: AIS SIGSEMIS (http://www. sigsemis.org): Amit P. Sheth, Gottfried Vossen, Ram Ramesh, Karl Aberer, Richard Benjamins, Francois Bry, Christoph Bussler, Jorge Cardoso, Jesus Contreras, Oscar Corcho, John Davies, Ming Dong, Dieter Fensel, Farshad Fotouhi, William I. Grosky, Jorge Gómez, Asuncion Gomez-Perez, James Hendler, Lakshmi S. Iyer, Ramesh Jain, Henry M. Kim,

Knowledge Management as a Reference Theory for E-Learning

Kinshuk, Rajiv Kishore, Ralf Klischewski, Henrik Legind Larsen, Shiyong Lu, Lisa Neal, Al Salam, Demetrios Sampson, Miguel-Angel Sicilia, Rahul Singh, York Sure, Marinos Themistocleous, Bhavani Thuraisingham, Kim Veltman, Ubbo Visser, Gerd Wagner, and Lina Zhou. AIS SIGRLO (http://www.sigrlo. org): Mohamed Ally, Tom Boyle, Juan-Manuel Dodero, Stephen Downes, Wolfgang Greller, Jian Qin, Pithamber Polsani, and Salvador SanchezAlonso. CID-Media/KTH (http://cid.nada. kth.se/en): Yngve Sundblad, Nils Enlund, Kerstin Severinson-Eklundh, Kai-Mikael Jää-Aro, Björn Ejderbäck, Åke Walldius, Ann Lantz, Björn Thuresson, Gustav Taxén, Olle Sundblad, Bosse Westerlund, Leif Handberg, Alex Jonsson, Mats Erixon, and Patrik Rydberg. WGLN (http://www.wgln.org): Stig Hagström, Mia Lindegren, Craig Heller, Brad Osgood, Stefan Decker, Mikael Sintek, Rudi Studer, Steffen Staab, Gerd Stumme, Wolf Siberski, Ingo Brunkhorst, Stefan Seipel, Calle Jansson, Tore Risch, Eva Müller, and Donald Broady. PROLEARN (http://www.prolearn-project. org): Wolfgang Nejdl, Martin Wolpers, Erik Duval, Wayne Hodgins, Gustaf Neumann, Bernd Simon, Zoltan Miklos, Fridolin Wild, Peter Scott, Kevin Quick, Nils Faltin, Bernardo Wagner, Torsten Fransson, Juan Quemada, Marcus Specht, Milos Kravcik, Paul de Bra, Alexander Karapidis, Till Becker, Jaques Dang, Tapio Koskinen, Katherine Maillet, Peter Dolog, Ralf Klamma, Stefaan Ternier, Michel Klein, Barbara Kieslinger, Margit Hofer, Elke Dall, Constantin Macropoulos, Vana Kamtsiou, and Effie Lai-Chong Law.

references Adams, E., & Freeman, C. (2000). Communities of practice: Bridging technology and knowledge assessment. Journal of Knowledge Management, 4(1), 38-44.

Benjamins, R., Fensel, D., & Gomez Perez, A. (1998). Knowledge management through ontologies. In U. Reimer (Ed.), Proceedings of the Second International Conference on Practical Aspects of Knowledge Management, Oct 29-30, Basel, Switzerland (p. 5). Bhatt, G.D. (2000). Organizing knowledge in the knowledge development cycle. Journal of Knowledge Management, 4(1), 15-26. Binney, D. (2001). The knowledge management spectrum—Understanding the KM landscape. Journal of Knowledge Management, 5(1), 3342. Hahn, J., & Subramani, M. (2000). A framework of knowledge management systems: Issues and challenges for theory and practice. 21st Annual International Conference on Information Systems, Brisbane, Australia. Holsapple C.W., & Joshi, K.D. (2001). Organizational knowledge resources. Decision Support Systems, 31(1), 39-54. Lytras, M.D., & Pouloudi, A. (2001). E-learning: Just a waste of time. In D. Strong, D. Straub, & J.I. DeGross (Eds.), Proceedings of the Seventh Americas Conference on Information Systems (pp. 216-222), Boston. Lytras M., Pouloudi, A., & Korfiatis, N. (2003). An ontological oriented approach on e-learning: Integrating semantics for adaptive e-learning systems. In Ciborra (Ed.), New paradigms in organizations, markets and society. Proceedings of the 11th European Conference on Information Systems. Lytras, M., Pouloudi, A., & Poulymenakou, A. (2002). Dynamic e-learning settings through advanced semantics: The value justification of a knowledge management oriented metadata schema. International Journal on E-Learning 1(4), 49-61.

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Lytras M., Pouloudi, N., & Poulymenakou, A. (2002). Knowledge management convergence: Expanding learning frontiers. Journal of Knowledge Management, 6(1), 40-51.

Naeve, A., Nilsson, M., Palmér, M., & Paulsson, F. (2005). Contributions to a public e-learning platform: Infrastructure, architecture, frameworks, and tools.

Lytras M., Tsilira, A., Themistocleous, M. (2003). Towards the semantic e-learning: An ontological oriented discussion of the new research agenda within the e-learning field. Proceedings of the 9th Americas Conference on Information Systems.

Nilsson, M., Naeve, A. & Palmér, M. (2004). The Edutella P2P Network: Supporting Democratic e-learning and communities of practice. In R. McGreal (Ed.), Online education using learning objects. New York: Routledge-Falmer.

Maedche, A. & Staab, S. (2001). Ontology learning for the semantic Web. IEEE Intelligent Systems, 16(2), 72-79.

Norris, D., Mason, J. & Lefrere, P. (2003). Transforming e-knowledge: A revolution in the sharing of knowledge. Society for College and University Planning. http://www.scup.org/eknowledge.

McAdam, R., & McCreedy, S. (1999). A critical review of knowledge management models. The Learning Organization: An International Journal, 6(3), 91-101. Naeve, A. (2001). The concept browser: A new form of knowledge management tool. Proceedings of the Second European Web-Based Learning Environment Conference (WBLE 2001) October 24-26, Lund, Sweden (pp. 151-161). http://kmr. nadad.kth.se/papers/ConceptualBrowsing/ConceptBrowser.pdf Naeve, A. (2001). The knowledge manifold: An educational architecture that supports inquirybased customizable forms of e-learning. Proceedings of the Second European Web-Based Learning Environments Conference (WBLE 2001) October 24-26, Lund, Sweden, (pp. 200-212). http://kmr. nada.kth.se/papers/knowledgemanifolds/knowledge manifold.pdf.

Rubenstein-Montano, B., Liebowitz, J.B., & McCaw, D. (2001). A systems thinking framework for knowledge management. Decisions Support Systems Journal, 31(1), 5-16. Zack, M.H. (1999a), Developing a knowledge strategy. California Management Review 41(3), 125-145. Zack, M.H. (1999b). Managing codified knowledge. Sloan Management Review, 40(4), 45-58. Zhang, H., Kim, D.J., & Ramesh, R. (2001). Multiagent systems: An ontological meta-model. In D. Strong, D. Straub, & J.I. DeGross (Eds.), Proceedings of the Seventh Americas Conference on Information Systems (AMCIS) (pp. 406-408), Boston.

This work was previously published in the International Journal of Distance Education Technologies, Vol. 3, No. 2, edited by Shi-Kuo Chang and Timothy K. Shih, pp. 1-12, copyright 2005 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 3.3

Mathematics Education Over the Internet Based on Vega Grid Technology Zhiwei Xu Chinese Academy of Sciences, China Wei Li Chinese Academy of Sciences, China Hongguang Fu Chinese Academy of Sciences, China Zhenbing Zeng Chinese Academy of Sciences, China

abstract

IntroductIon

This chapter presents research work conducted at the Chinese Academy of Sciences, on the Vega Grid technology and dynamic geometry technology, and how the two can integrate to provide a dynamic geometry education system based on grid technology. Such an approach could help solve the interconnect problem, the performance problem and the intellectual property problem for Internet-based education systems.

This chapter presents research work conducted at the Chinese Academy of Sciences, on the Vega Grid technology and dynamic geometry technology, and how these two technologies can integrate to provide a Vega Education Grid, a grid-based education system for mathematics. Vega Grid is a research project at the Institute of Computing Technology, Chinese Academy of Sciences. MXP (Math Experience) is a dynamic geometric education system developed at the

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Mathematics Education Over the Internet Based on Vega Grid Technology

Automated Reasoning Laboratory, Chinese Academy of Sciences. Currently, these two teams are collaborating to develop a high-performance intelligent education software deployable on a wide-area grid platform. The initial focus is mathematics education, with strong emphasis on dynamic geometry. In the second section, we discuss the Vega Grid research project. We then describe the MXP system, identify challenges of the MXP system, and present the architecture of the Vega Education Grid, a grid-based mathematics education system under development.

the vega grId project The Vega Grid project aims to promote learning of fundamental properties of grid computing, and developing key techniques that are essential for building grid systems and applications. The Vega team currently consists of more than 100 people, and is conducting research work in the following areas: • •

•

•

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Dawning Superservers: Terascale gridenabling clusters on Linux/Intel and AIX/ PowerPC platforms. Vega Grid Software Platform: This work includes research on grid system software, grid application development tools, and grid user interface. The objectives are to enable resource sharing, collaboration, service composition, and dynamic deployment, utilizing open standards such as OGSA and Web services standards. Vega Information Grid: Enabling information sharing, information management, and information services in a wide-area enterprise environment or an ASP environment. Vega Knowledge Grid: Research on knowledge sharing, knowledge management, and

knowledge services in a wide area Web environment. The Vega Grid research is both a basic research and an applied research project. As such, it is driven by technology trends and application trends. We have closely followed development in computing grid (e.g., Globus), data grid, information grid and knowledge grid, and business grid (e.g., OGSA and Web services). More importantly, we constantly talk to users in China to identify applications requirements. We covered more than 20 applications fields in China, ranging from scientific research, e-government, biology and medicine, space industry, manufacturing industry, resource and environment protection, education, transportation, and social security. The research results of the Vega Grid project are currently being used in several application fields, such as Digital Olympics, bioinformatics grid, education grid, and integrated information sharing systems in the railway industry. In this section, we outline some research progresses from the Vega Grid project, including the VEGA Service Grid principle, a grid computer model, and the Vega Grid architecture.

the vega service grid principle After carefully analyzing applications requirements, we identified the VEGA Service Grid Principle to guide our development. The service grid concept abstracts three aspects of applications requirements: (1) The Vega Grid should enable user-visible services, not just an infrastructure. For instance, we need to not only develop lowlevel, user-invisible grid kernel technology, but also provide utilities, developing tools, and user environment technology to help users develop, deploy, and utilize grid technology. (2) Service is the main mechanism for users to interact with grid. (3) The criteria used to evaluate grid functionality and performance should evolve from traditional criteria (e.g., speed and throughput) to service-

Mathematics Education Over the Internet Based on Vega Grid Technology

oriented criteria, such as Service Level Agreement (SLA). To realize the service grid concept, the Vega Grid project adopts the following four VEGA principles: •

•

•

Versatile Services and Resources: The grid should have the ability to support various services and resources, not just scientific computation. The Vega Grid project aims to provide for the minimal common requirements of various grid applications. Enabling Intelligence: The grid should support intelligent computing, such as automatic production of information, knowledge, and services. However, the grid itself is not the intelligence provider, but it provides enabling technology to assist developers and users to achieve intelligent grid applications. Global Uniformity: From the user’s viewpoint, the grid can be viewed as a single virtual computer, supporting Single System Image, Single Sign-On,

and other related technologies. Heterogeneous resources among geographically distributed grid nodes should form a uniform, connected, interoperable resource pool, instead of many isolated small islands.

•

Autonomous Control. The grid should not be ruled by a central administration. All components can freely join or leave the grid at their own will. A resource provider has full control of its resource exported, and a resource user can use resources as he likes within the purview of his right.

a grid computing model with active memory Turing machines and random access machines (RAMs) are basic computer models, especially for sequential computing at a single site. The PRAM model extends RAM to cover parallel computing. The Vega Grid team proposed a new model of Computer with Active Memory (CAM), where the memory cells are equipped with traditional read/write operations as well as new execution operations. This CAM model can be used to study architectural mechanisms and algorithms design and analysis of grid computing. The CAM model differs from the RAM model in several aspects, as illustrated in Figure 1. In a traditional RAM (or PRAM) model, a processor can only read from or write to a memory cell. In the CAM model, a processor can also execute a memory cell. This is accomplished by new instructions specific to CAM.

Figure 1. Comparison among three computing models: RAM, PRAM and CAM P

Memory

(a) RAM

P

P

Memory

(b) PRAM

P

Grid

f

P

A

B

C

(c) CAM for Grid

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This CAM model is better suited than RAM and PRAM for modeling grid computing. Each memory cell in CAM can be viewed as a grid node. The entire memory can be viewed as the grid. A processor of CAM represents a client device or a user of the grid. Instructions of CAM can be viewed as users’ requests to the grid for desired services. For instance, suppose a memory cell X in a CAM is divided into four fields, labeled as (X, 0), (X, 1), (X, 2), (X, 3). A CAM instruction “store (X, 0), f ” deploys service f on grid node X. An instruction “move (X, 3), Y” transfers data from node Y into node X. A CAM instruction “execute X” then can be interpreted as execute service f, with parameter (X,2) and (X,3), and writes the service results into (X,1).

the vega grid architecture The CAM model has been used in designing our Vega Grid system. Its hardware topology is illustrated in Figure 2 and its software structure is illustrated in Figure 3. At the grid hardware layer, we are developing Dawning 4000 and Dawning 5000 superservers as compute resources (indicated by CR in Figure 2), which are clusters with enabling technology to support grid platforms and applications. Other components at the grid hardware layer include a client device and a router. The Vega Grid Client is a thin client device for grid users. The Vega Grid Router (indicated by GR in Figure 2) enables application-level con-

nectivity and allows resources to be efficiently deployed and discovered. Based on the hardware topology in Figure 2, the Vega Grid has a Three-Tier software architecture in Figure 3, which includes a Grid Browser (the Client-Tier), a GSML server (the Middle-Tier), and Grid services (the Resource-Tier). At the Client-Tier, there is a software called grid “browser” (also called GSML browser), which renders GSML pages and provides an interface for users to access a grid. This grid browser is different from a Web browser in that it allows the users not only to read contents from a grid, but also to write to and to operate a grid, by sending (lightweight) service requests to a GSML server. At the Middle-Tier, there is a set of tools and protocols called Vega Grid user environment, which enables end users to use grid resources conveniently. We are developing a suite of software, called the GSML suite, to approach this goal. The GSML software suite consists of the following protocols and tools, as illustrated in Figure 3. • •

• •

Figure 2. The Vega Grid hardware topology • CR

CR GR

Vega Grid Client

GR CR

GR GR CR

Vega Grid

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A language called GSML, for users to program a grid and to access a grid. A software grid server (also known as GSML server) that receives service requests from the client side, processes the requests, and sends results back to the client side. A protocol for the interactions between the GSML server and the GSML browser, called Grid Service Request Protocol (GSRP). A software tool called grid Resource Mapper, which converts native grid resources into virtual resources. A software tool called grid Resource Composer, by which a user can browse/select virtual resources and integrate them into a GSML page.

When designing the Vega Grid user environment, we focus on two important issues: how to empower users with the ability to program the grid

Mathematics Education Over the Internet Based on Vega Grid Technology

Figure 3. The Vega Grid three-tier architecture Resource Composer

Resource Mapper

GSML Page

Grid Browser

GS GS

GS Grid Community

Grid Resources GS GS

GSRP GSML Server

Client-Tier

GS

Middle-Tier

and at the same time, how to keep the complexity manageable. The objective is to have an interface that has enough power while still usable, so that an end user with simple training can use it. For the programmability issue, we propose the grid service markup language (GSML), which is based on XML and includes a set of tags to describe various grid resources such as contents, services, databases, etc. The GSML supplies the programming ability to end users, who can construct a customized resource view easily and quickly. For the usability issue, we adopt a three-point approach. First, we restrict the power of GSML to less than that of finite state machines. Second, we design the GSML suite to be an amplifier, so that a simple user request can be translated into a lot of activities at the grid side. Third, we map the global grid resources to a user-specific view. The last two points are helped by a new concept called grid community. Following the wisdom in computer architecture and operating systems development, we view the grid resources to form something similar to the address space in a computer system, including physical addresses, virtual addresses, and effective addresses.

GS

GS

GS Resource-Tier

Analogously, we can use a three-level scheme to view grid resources: the first one is the native grid resource level (physical resources), which includes all resources in the grid; the second one is the grid community level (virtual resources), which is a subset of grid resources; the third one is the GSML page level (effective resources), which is a user-specific resource collection. The role of the Resource Mapper is to convert the distributed heterogeneous resource to virtual resources in a “centralized” community. After this three-level conversion, the content of a GSML page can be a small resource collection and user-specific, which enables users to make a customized resource view easily. The grid community concept offers two additional advantages. The first one is that a grid community can serve as a container of common functions of the community of users and resources, such as access control, context, and trust. By just specifying a community name in the head part of a GSML page, users can implicitly take advantage of all common benefits offered by the community, taking it for granted that the GSML software suite will take care of all the ensuing operational details.

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The second advantage of grid community is to simplify users’ needs of technical skills. We can classify users into three roles: executive, the executive’s secretary, and technical staff. We envision that the technical staff will use the Resource Mapper to convert physical resources into the community level, which will be in such a form that the secretary could understand. The secretary can create a customized grid service in the form of a GSML page, using the Resource Composer tool. The executive can then read, write, and operate the grid with the personalized GSML page through the grid browser. Our eventual goal is that, as the GSML suite matures, any high-school graduate (such as a farmer) will be able to program and to use grid. At the Resource-Tier, the grid resources are abstracted as grid services (indicated by GS in Figure 3) conforming to the OGSA standard. With the help of such abstractions, the GSML server can access the distributed, heterogeneous resources in a uniform and standard pattern.

the math experIence (mxp) project Ever since their introduction in the 1990s, dynamic geometry software (DGS) packages have become a standard tool for students, teachers, and mathematicians to build dynamic visual models to assist teaching and learning of various mathematical concepts and theorems. They allowed students to become geometric experimenters, and to make their own discoveries. But a common drawback of these types of software is that they cannot answer why. If you want a readable and logical proof process produced by a computer automatically for a problem, the previous DGS cannot do it, because they did not include an automated reasoning engine (prover) and a symbolic computation platform (solver). Symbolic computation software like Mathematica and Maple provide powerful tools of solving mathematical

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problems, but solving geometric problems is still a weak point. In recent years, we are researching and developing a dynamic geometric system named MXP (Math Experience) with a geometry information search system (prover) and a symbolic computation platform (solver). The DGS part of the software is used to generate a problem, the prover and solver are used to solve the problem automatically. In the following, we use an example to illustrate how MXP can be used to generate a geometric problem and to provide a readable proof.

problem generation in mxp A geometric problem includes the known and conclusion parts. If a problem is input by keyboard directly, we have to face the understanding of nature language, but it is very difficult. It is fortunate that the dynamic geometry is a constructive process and the semantic of every step is definite. So we can let the computer automatically generate problems by the constructive process. The approach to generate a geometric problem can be divided into two steps: (1) generating the statements (known and conclusion) of the problem by the drawing process; (2) constructing the database of the known and conclusion. With the MXP software, a user selects the drawing tools to construct the geometric sketch in the worksheet and generate the conclusion by selecting the pattern of conclusions. The statements of constructions are shown in the window labeled “Problem.” The database of the known and conclusion is a black-box for users, which has a specific data structure. Figure 4 shows an example of the problem generating process. Table 1 illustrates the relationship among drawing sketch, statements, and inner data structure.

theorem proving in mxp In order to let a computer produce a traditional proof automatically, a geometry information

Mathematics Education Over the Internet Based on Vega Grid Technology

Figure 4. Problem generating in MXP

Table 1. Relationship among drawing sketch, statements and inner data structure Step 1

Drawing Process

Expressing Sentences

Free Point A

Data structure (point A)

2

Free Point B

(point B)

3

Free Point C

(point C)

4

Middle Point E of Point A and Point B

E Is The Midpoint OF Point A and Point B.

(:mp E (:segment A B))

5

Middle Point F of Point B and Point C

F Is The Midpoint OF Point B and Point C.

(:mp F (:segment B C))

6

Middle Point G of Point C and Point D

G Is The Midpoint OF Point C and Point D.

(:mp G (:segment C D))

7

Middle Point H of Point A and Point D

H Is The Midpoint OF Point A and Point D.

(:mp H (:segment A D))

8

Adding Conclusion

Quadrilateral EFGH IS Parallelogram.

(px4 (:4gon E F G H))

Free Point D

(point D)

search system (prover) and symbolic computation platform (solver) are introduced into the MXP. The prover is a geometry information search system based on the rules including axioms, concepts, and theorems. The solver is a computer algebra system based on symbolic computation including polynomial computations, factorization, and equations solving. Because the solver is just a tool to be used in proving geometry theorems, in this chapter we don’t want to explain how to design

the solver in detail. We will focus on designing the prover. Firstly, we should establish a rule database by collecting the axioms, definitions, and theorems in textbooks. Then, we can formalize every rule as a function with inputs and outputs, so that some new facts can be outputted automatically when all the input facts of a function are satisfied. Secondly, we classify all facts and establish a fact database. Then we can get an expanding fact 1379

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database by applying every rule in rule database to the fact database. It is obvious that the expanding fact database has a limited fact database owing to the limited number of rules. So the automated reasoning process is closed. Thirdly, we should check whether the conclusion is in the fact database or not till the fact database reaches its limitation. If it is true, we can get a proof, otherwise the prover cannot answer the problem. Maybe we should add new rules in the rule database. The whole process is summarized in Figure 5. Though the above algorithm is not very difficult, we should consider the equivalence class, data structure, and the search efficiency carefully. Otherwise, the expanding facts will extend the memory of the computer. On a general person-

nel computer, we get a proof in several seconds for the example in Figure 4 by MXP. The proof is showed in Figure 6. Obviously, every step is readable and verification.

summary of mxp As a dynamic geometry software, MXP can be used to build dynamic visual models to assist teaching and learning of various mathematical concepts. As an automated reasoning software, MXP can be used to build dynamic logic models which can do reasoning themselves. MXP is a powerful computer program for geometric reasoning. Within its domain, it invites comparison with the best of human geometry provers. It implements most of the effective methods

Figure 5. Automated reasoning based on rules Known Data Classify facts

Facts 1

Rule 1

Facts 2

Rule 2

Facts n

Rule k

Verify Conclusion Construct Proof Show Proof Process STOP

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Figure 6. The proof of the example in Figure 4

for geometric reasoning introduced in the past 20 years, including the deductive base method, Wu’s method, the area method, the Groebner basis method, the vector method, and the full-angle method. With these methods, users may automated prove geometry theorems, to discover new properties of theorems, and to generate readable proofs for many geometry theorems. MXP supports the concept of dynamic visual models, that is, models built by computer software that can be changed dynamically. With MXP, we can build four classes of dynamic visual models: geometric transformations, and loci generation, diagrams of functions.

the vega educatIon grId The current MXP software is implemented with Java on the PC platform, as a standalone software system. As such, it encounters several challenges:

•

•

•

The Interconnect Problem: The current MXP system considered network support (e.g., using Java to code the system). But, it is no trivial matter to enable application-level connectivity among people and machines to build a grid-based learning community. The Performance Problem: The performance and functionality of MXP is limited by a user’s PC (e.g., a user cannot perform large-scale factorization). Although there may be many powerful resources on a grid, we lack the means to share them. The Intellectual Property Problem: As a standalone PC software, MXP is easy target for piracy. Any third-party add-on, either software or knowledge base, is also susceptible to this problem.

To solve these problems, we are developing a Vega Education Grid system (VEG). Its architecture is shown in Figure 7, based on the Vega Grid architecture in Figure 2 and Figure 3.

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The interconnect problem is challenging, because it involves building communities (see Table 2) among students, teachers, and machines. The latter include hardware, software, and knowledge base on a grid platform. The parties involved have different knowledge structures and different ways of communication. Two Vega Grid technologies, the Vega Grid Browser (VGB) and the GSML, play an important role in helping solve the interconnect problem. The VEG client is more powerful than a traditional Web browser, as it must provide graphic, interactive functions needed by the MXP, and it needs peer-to-peer functions to support S2S, S2T, T2S, and T2T interactions. The GSML language provides a means for students and teachers to add knowledge and services to the Vega Education Grid, without programming. The Vega Education Grid is equipped with a transparent, resource sharing interface, allowing “out-sourcing” computation tasks and knowledge base queries to powerful back-end servers as well as client-side machines. This helps solve the performance problem. Another feature of Vega Grid, called dynamic deployment, helps alleviate the intellectual property problem. The VEG client, although it contains most software of MXP, is not a standalone system anymore. It must be connected to the grid to function properly. At boot time and runtime, essential modules of MXP are transparently loaded via the VEG server into a client machine’s memory through the Internet. These modules are not stored into the disk file system of the client machine, even when the VEG client exits. We have successfully implemented such dynamic deployment system for operating system kernel-level mandatory access control. Initial experiments show that such dynamic deployment only takes a few seconds.

conclusIon In this chapter, we described research progress of the Vega Grid project and the Math Experience (MXP) project. We identified three challenges of standalone education software, and proposed a Vega Education Grid architecture to help solve the problems. The Vega Grid project has implemented a running prototype, and some Vega technology (e.g., the resource monitoring system) has been deployed in field applications. The MXP project has produced a stable software system in Chinese version, and a preliminary English version of the software is available for download at http://www. acailab.com/. The Vega Education Grid is under development.

references Chou, S.C., Gao, X.S., & Zhang, J.Z. (1994). Machine proofs in geometry. World Scientific. Cook, S.A., & Reckhow, R.A. (1973). Time bounded random access machines. Journal of Computer and System Science, 7(4), 354-375. Fortune, S., & Wyllie, J. (1978). Parallelism in random access machines, Proceedings of the 10th ACM Symposium on Theory of Computing, May, 114-118. Foster, I., Kesselman, C., Nick, J., & Tuecke, S. (2002). The physiology of the Grid: An open Grid services architecture for distributed systems integration, January. Hwang, K., & Xu, Z. (1998). Scalable parallel computers: Technology, architecture, programming. New York: McGraw-Hill. IEEE Intelligent Systems. (2002). Special Issue on Intelligent Web Services, (January.) Jin, X., & Wang, D. (1994). Mechanical theorem proving in geometries: Basic principles (Trans-

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lated from the Chinese). Texts and Monographs in Symbolic Computation, Berlin: Springer-Verlag.

Valiant, L.G. (1990). General purpose parallel architectures. In J. van Leeuwen (Ed.), Handbook of theoretical computer science (Vol. A). Elsevier.

Kortenkamp, U. (1999). Foundations of dynamic geometry, Doctoral Thesis, ETH Zurich, Institut fur Theoretische Informatik.

Wu, W.T. (1984). On the decision problem and the mechanization of theorem-proving in elementary geometry. Contemporary Mathematics, 29, 213-234.

MXP (Math Experience: A Dynamic Geometry Software with a Prover and Solver). (2002). Available online at http://www.acailab.com

Zhuge, H. (2002). A knowledge grid model and platform for global knowledge sharing. Expert Systems with Applications, 22(4), 313-320.

This work was previously published in the International Journal of Distance Education Technologies, Vol. 1, No. 3, edited by Qing Li and Weijia Jia, pp. 1-13, copyright 2003 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 3.4

IT to Facilitate Distance Education M. Gordon Hunter The University of Lethbridge, Canada Peter Carr Athabasca University, Canada

IntroductIon The essence of distance education is the physical separation of teacher and learner (Sauve, 1993). In many countries, universities are increasingly employing distance education. Some institutions are incorporating distance education as a way to extend the classroom by employing delivery mechanisms that replicate the presentation of material in a manner similar to face-to-face communication. Other institutions are investigating new delivery mechanisms that support a revised perspective on education. These latter institutions are revising their processes for interacting with students and taking a more customer-centered approach to the delivery of education. There are many options available to universities when deciding how to employ technology to support delivery of distance education. The purpose of this investigation was to document the various modes of delivery mechanisms

currently employed in distance education. It was anticipated that this documentation process would help to determine an understanding of the alternative mechanisms. It was also anticipated that an outline of all approaches, with an indication of the more innovative ones, could serve to provide guidance to institutions regarding the adoption of technology to support delivery mechanisms in distance education and to individuals researching the area. This chapter discusses the impact of technology on the delivery mechanisms employed in distance education. To begin, the next section reviews appropriately related research in distance education. A proposed framework is then presented that outlines alternative delivery mechanisms for various levels of employing technology to support distance education. The proposed framework provides an overview of the relationship between technology-based delivery mechanisms and the extent to which the innovative

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IT to Facilitate Distance Education

use of technology can affect distance education. Finally, conclusions are presented that outline the more innovative concepts involving the use of technology in distance education and include a call to action for other researchers interested in investigating this subject area.

background As the use of technology to support distance education increases, so does research into various aspects involved in the relationship between tech-

nology and the various forms of delivery of course material. The data in Table 1 presents examples of selected research projects involving investigations into technology and delivery mechanisms. The data in the table suggests the emergence of two major themes. First, it is incumbent upon institutions to consider students more like customers. This means that student demographics should be studied when considering modifications to delivery mechanisms. Thus, a specific type of individual (non-traditional, self-motivated, and mature) is more inclined to satisfactorily perform academically in a distance education situation.

Table 1. Distance education research projects TOPIC

SOURCE

FINDINGS •

TECHNOLOGY

INTERNET

• • • • •

Menlove and Lignugaris/Kraft (2004) McWright (2003) Perreault et al (2002) Papp (1999) Reif and Kruck (1999)

• • • • •

Knowlton (2003) Oravec (2003) Williams (2003) Paulson (2002) Darbyshire and Burgess (1999)

• • • • • •

• PROFILES

SATISFACTION

• • • • •

Collins and Pascarella (2003) Conrad (2002) Kung (2002) Thurmond et al. (2002) Aggarwal and Kemery (1999)

• • • • • •

Jamieson (2004) Stein and Glazer (2003) Van Schaik et al. (2003) Zheng and Smaldino (2003) Aragon et al. (2002) Kekkonen-Moneta and Moneta (2002) Wheeler (2002) Lou et al. (1999) Motiwala and Duggal (1998)

• • •

•

• • • •

Technology is used to increase course enrollments and respond to student flexibility requirements Success depends on the effective use of technology Students familiar with the technology appreciate the flexibility Student and instructor competence contributed to successful delivery Basic skills become more important Teaching using the Internet is more productive and rewarding Stakeholders could see the benefit of employing the Internet to deliver material and facilitate course administration Learners’ sense of engagement is more dependent on their connection with the material than instructors or colleagues The most important student profile would be a non-traditional, self-motivated, mature individual who requires schedule flexibility because of other life commitments Students can learn equally well in either delivery format regardless of learning style Students’ perceived satisfaction would be the same for both face-to-face delivery and technology-mediated delivery The use of interactive e-learning modules fosters higher-order learning outcomes Students were satisfied with the self-paced flexibility of the asynchronous discussion threads

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Second, the adoption of an asynchronous mode of delivery, found to be satisfactory in some research situations, represents an innovative use of technology. This, in turn, leads to the use of a delivery mechanism that supports learning that is independent of both time and place. The issue of time and place independence is discussed further in the following section.

alternatIve delIvery mechanIsms: a proposed framework Figure 1 presents a description of alternative modes of generic delivery mechanisms. Whalen and Wright (1998) describe distance education as technology-based delivery of course material where faculty and students are separated both spatially and temporally. Thus, place concerns

the location for the delivery of educational material, while time relates to the relationship between presentation and receipt of the message. Both Time and Place have been categorized as “same” or “different” in Figure 1. The bottom left quadrant in Figure 1 represents the traditional lecture mode of delivery with both the student and instructor at the same place, at the same time. While technology may be employed to enhance the delivery of material in this case and is representative of the term “educational technology,” it is not considered to represent a form of delivery mode for distance education. The bottom right quadrant is characteristic of a library. Thus, material in the form of a manuscript is developed by an instructor and made available for students to read. The Place is the same, the library, but the Time may be different. This mode of delivery allows the student to choose when the delivery will be incurred. Further, there may be some technology incorporated in the

Figure 1. Delivery mechanisms in education Place Specificity

use of Technology

Different

Interactive

Asynchronous

Same

Lecture

Library

PLACE

Same

Different TIME

T

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ime Specificity

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form of CD-ROMs or other electronic versions of manuscripts. The top half of Figure 1 represents modes of delivery that incorporate technology having the ability to change the perspective of education and also to support the concepts underlying distance education. The top left quadrant represents an interactive delivery mode. Material may be delivered at the same time, but the student and instructor may be in different places. Technology supports this form of delivery through telecommunications. Both audio and video communication may be used in this delivery mode. It is, thus, possible to have interaction between student and instructor in a synchronous mode. The top right quadrant also employs technology, but in an asynchronous delivery mode. The material to be delivered is made available by the instructor through technology, and the students are able to access the material based upon their own schedules. The Centre for Innovative Management (CIM) at Athabasca University in Canada employs this delivery mechanism. Athabasca University is Canada’s leading distance university, with over 22,000 students. CIM provides the world’s first and largest online Executive MBA, with over 1,000 students participating online in asynchronous learning. This program has roughly 30% of the Canadian Executive MBA market. The bricks and mortar for CIM are in St. Albert, just north of Edmonton, Alberta, but this location is of little consequence, as the students and instructors may be located anywhere they can access the Internet. This also means that students and instructors can be very mobile, attending to other work and family commitments during the delivery of a course.

conclusIon Universities are in the information dissemination business and computers are changing the way

they work. Accordingly, “… while IT can offer new experiences and a diminished dependence on rigid University structures, the social aspect of learning remains a vital component of successful education” (Forer, Goldstone, & Tan, 1999, p. 331). While technology has changed the nature of non-classroom-based education by allowing physical separation, it has also enabled interaction, which is considered by some researchers to be the basis for successful education. Further, “the impact of IT in our society, undeniably, presents us with significant pressure to re-evaluate and rethink education” (Wilson & Meadows, 1999, p. 324). However, “… if technology is used simply to automate traditional models of teaching and learning, then it’ll have very little impact” (O’Neil, 1995, p. 6). These comments suggest that the most benefit from technology can be gained by those institutions that adopt a delivery mechanism for distance education more related to the top right quadrant in Figure 1. This approach represents the only true innovative use of technology in education. In effect, the other three delivery mechanisms employ technology in various forms to improve the efficiency of the presentation of educational material. There is little change in the learning environment or knowledge acquisition process. However, the asynchronous mode of delivery represents an attempt to modify the environment and the process in order to be more effective. Further, this approach to education has some major positive impact from a global perspective. First, as noted above, the technology supports temporal and spatial separation. These two aspects represent the major inhibiting factors to the effective expansion of traditional delivery mechanisms. Thus, with the proposed technology-based approach, it becomes possible for learner and instructor (through the course material) to interact asynchronously, separated both temporally and spatially. The underlying concepts of a learnercentered, self-paced educational experience relate to time and place. Thus, learners will be better

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served through temporal and spatial separation of the delivery/learning process. Second, it will be possible then to have a multi-cultural based cohort. This environment (students with varied backgrounds) may be employed to contribute to an enriched experience by incorporating student interaction into the learning process. Researchers interested in studying the application of technology to distance education will find this a rich subject for investigation. The adoption of the concepts surrounding learner-centered education is currently considered novel. It would be interesting to investigate student satisfaction in such an environment. Another aspect to investigate here relates to instructors’ attitudes toward change and how they attempt to adapt to the learner-centered environment. Another area of investigation relates to temporal and spatial separation. Of interest here would be a determination of how student satisfaction and performance are affected by the introduction of technology into distance education. Further, because the use of technology in distance education facilitates temporal and spatial separation, it is possible to organize a multi-cultural cohort. Investigation questions could relate to group dynamics and individual responses to a cross-cultural distance education experience. Finally, according to Wilson and Meadows (1999), university: … services will become based on the conveniences of the “customer” rather than that of the institutions. The expectation, or ideal, is that truly learner-centered education, individualized, will be delivered directly to the individual at a time and in a place determined by the learner. (p.314) This approach will be facilitated by the adoption of technology to support the delivery of asynchronous distance education.

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note This chapter is based upon and is a summary of the following earlier publication: Hunter, M. Gordon and Carr, Peter: Technology in distance education: A global perspective to alternative delivery mechanisms. Journal of Global Information Management, 10(2), 50-54.

references Aggarwal, A. K. & Kemery, E. R. (1999). Webbased teaching: Is it for real? In M. Khosrow-pour (Ed.), Proceedings of 1999 Information Resources Management Association International Conference, (pp. 1-4). Hershey, PA: Idea Group Publishing Aragon, S. R., Johnson, S.D., & Shaik, N. (2002). The influence of learning style preferences on student success in online versus face-to-face environments. The American Journal of Distance Education, 16(4), 227-244. Collins, J. & Pascarella, E.T. (2003). Learning on campus and learning at a distance: A randomized instructional experiment. Research in Higher Education, (3), 315-326. Conrad, D. (2002). Engagement, excitement, anxiety, and fear: Learners’ experiences of starting an online course. The American Journal of Distance Education, (4), 205-226. Darbyshire, P. & Burgess, S. (1999). Using the Internet to assist with subject delivery: A case study. In M. Khosrow-Pour (Ed.), Proceedings of 1999 Information Resources Management Association International Conference, (pp. 234-240). Hershey, PA: Idea Group Publishing. Forer, P. C., Goldstone, M., & Tan, F.B. (1999). Implementing flexible learning in GIS education: Experiments at the University of Auckland, a spatial analysis facility. In F. B. Tan, P. S. Corbett,

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& Y. Y. Wong (Eds.), Information technology diffusion in the Asia Pacific: Perspectives on policy, electronic commerce and education, Chapter 20. Hershey, PA: Idea Group Publishing. Jamieson, P. (2004). The university as workplace: Preparing lecturers to teach in online environments. The Quarterly Review of Distance Education, (1), 21-27. Kekkonen-Moneta, S. & Moneta, G.B. (2002). E-Learning in Hong Kong: Comparing learning outcomes in online multimedia and lecture versions of an introductory computing course. British Journal of Education Technology, (4), 423-433. Knowlton, D. S. (2003). Evaluating college students’ efforts in synchronous discussion: A systematic process. The Quarterly Review of Distance Education, (1), 31-41. Kung, S. C. (2002). Factors that affect students’ decision to take distance learning courses: A study of technical college students in Taiwan. Education Media International, (3/4), 299-305. Lou, H., Van Slyke, C., & Luo, W. (1999). Asynchronous collaborative learning: The mitigating influence of Learning Space ™. In M. Khosrowpour (Ed.), Proceedings of 1999 Information Resources Management Association International Conference, (pp. 874-875). Hershey, PA: Idea Group Publishing. McWright, B. L. (2003). Educational technology at a distance. The Quarterly Review of Distance Education, (2), 167-176. Menlove, R. & Lignugaris/Kraft, B. (2004). Preparing rural distance education Preservice special educators to succeed. Rural Special Education Quarterly, (2), 18-26. Motiwala, L. & Duggal, J.S. (1998). Distance learning on the Internet: A virtual classroom framework. In M. Khosrow-Pour (Ed.), Proceedings of the 1998 Information Resources Manage-

ment Association International Conference, (pp. 787-791). Hershey, PA: Idea Group Publishing. O’Neil, J. (1995). On technology and schools: A conversation with Chris Dede. Educational Leadership, (2), 6-12. Oravec, J. A. (2003). Some influences of online distance learning on U.S. higher education. Journal of Further and Higher Education, (1), 89-103. Papp, R. (1999). The road to the electronic classroom: Overcoming roadblocks and avoiding speed bumps, In M. Khosrow-pour (Ed.), Proceedings of 1999 Information Resources Management Association International Conference, (pp. 939-942). Hershey, PA: Idea Group Publishing. Paulson, K. (2002). FIPSE: Thirty years of learning anytime and anywhere. Change, September/ October, 36-41. Perreault, H., Waldman, L., Alexander, M., & Zhao, J. (2002). Overcoming barriers to successful delivery of distance-learning courses. Journal of Education for Business, July/August, 313-318. Reif, H. L. & Kruck, S.E. (1999). Towards an understanding of online degree programs. In M. Khosrow-Pour (Ed.), Proceedings of 1999 Information Resources Management Association International Conference, (pp. 847-848). Hershey, PA: Idea Group Publishing. Sauve, L. (1993). What’s behind the development of a course on the concept of distance education? In D. Keegan (Ed.), Theoretical principles of distance education. London: Routledge. Stein, D. & Glazer, H.R. (2003). Mentoring the adult learner in academic midlife at a distance education university. The American Journal of Distance Education, (1), 7-23. Thurmond, V. A., Wambach, K., Connors, H.R., & Frey, B.B. (2002). Evaluation of student satisfaction: Determining the impact of a Web-based

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environment by controlling for student characteristics. The American Journal of Distance Education, (3), 169-189. Van Shaik, P., Barker, P., & Beckstrand, S. (2003). A comparison of on-campus and online course delivery methods in Southern Nevada. Innovations in Education and Teaching International, (1), 5-15. Whalen, T. & Wright, D. (1998). Distance training in the virtual workplace. In M. Igbaria, & M. Tan (Eds.), The virtual workplace. Hershey, PA: Idea Group Publishing. Wheeler, S. (2002). Student perceptions of learning support in distance education. The Quarterly Review of Distance Education, (4), 419-429. Williams, P. E. (2003). Roles and competencies for distance education programs in higher education institutions. The American Journal of Distance Education, (1), 45-57. Wilson, R E. & Meadows, C.J. (1999). Tele-teaching: Australia’s competitive questions. In F.B. Tan, P. S. Corbett, & Y. Y. Wong (Eds.), Information technology diffusion in the Asia Pacific: Perspectives on policy, electronic commerce and education, Chapter 19. Hershey, PA: Idea Group Publishing.

Zheng, L. & Smaldino, S. (2003). Key instructional design elements for distance education. The Quarterly Review of Distance Education, (2), 153-166.

keyterms Asynchronous Delivery Mode: Material to be delivered is made available by the instructor through technology and students are able to access the material based upon their own schedules. Delivery Mechanisms: Processes for delivering course material. Distance Education: Physical separation of teacher and learner. Information Technology: Computer-based methods for processing data into a useable form for users. Interactive Delivery Mode: Interaction between student and instructor in a synchronous mode. Spatial: Of or concerning space. Temporal: Of or relating to time.

This work was previously published in the Encyclopedia of Distance Learning, Vol. 3, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 1156-1161, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.5

Interactive Response Systems in Higher Education Mick Wood University of Central Lancashire, UK

Abstract The University of Central Lancashire (UCLAN) undertook an “interactive response system” (IRS) pilot scheme using IML Question Wizard (IML), complete with 100 handsets, during semester one of the 2004/2005 academic year. This case study will explain the scheme rationale and methodology of implementation. A number of example applications will be explored and evaluated, including IRS use by academic and support staff, as well as utilising the system at a number of conferences. The case study will conclude with a look at UCLAN’s future plans to expand the system.

Introduction The University of Central Lancashire,the sixth largest university in the UK with approximately 36,000 students and 2,500 staff located on four campuses, has a mission-led commitment to widening participation with the aim “to provide

the widest possible access to those individuals who seek to benefit from its educational activities and to remove barriers to those with special needs.”1 UCLAN has a diverse student population, and exceeds Higher Education Funding Council for England (HEFCE)2 derived benchmarks3 against a range of factors including disability, students from the socio-economic classes 4, 5, 6, and 74, and low participation neighbourhoods. UCLAN also has the third highest number of part-time students across the sector.5 Senior management at UCLAN recognised that the diversity of the student population could lead to a higher than average number of students dropping out of their degree programmes. “In many cases it is institutions taking risks in student recruitment by admitting mature students and those without traditional. ‘A-Level’ qualifications or “highers” that inevitably have the highest drop out rates.” (MacLeod, 2002). It is also worth pointing out that behind the statistics lie real people, each one with hopes, dreams, and ambitions, and that “students who discontinue their studies could be

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Interactive Response Systems in Higher Education

damaging their self-confidence and self-esteem” (McGivney, 1996). An institutional research project (as yet unpublished)—The Student Experience Project (SEP)—began in 2001. The aim was to gain a greater insight into the student experience by tracking a cohort of 750 students, from pre-enrollment through to the completion of their degree in June 2004, in order to gain an overall picture of their student experience. The SEP discovered that, although many students were extremely satisfied with their time at UCLAN, others were finding the University experience much more challenging. For example, students enrolled in classes with a large cohort often felt isolated and had little or no connection with other students. This was particularly prevalent for those students who had come from relatively small sixth form colleges where they were more likely to have known their peers well. These findings are consistent with the results of the Institute for Access Studies at Staffordshire University which state that “loneliness is the most likely cause of students dropping out of university … the feeling of belonging was central to the decision to stay or go” (Times Higher, 2002). Academically, the SEP revealed that many students were used to the highly-structured learning environment of preuniversity education. Although many students enjoyed the challenge of independent learning, others found it difficult to cope with the greater personal freedom of degree-level studies. Some students admitted that they had little idea of what was actually required of them at University, or of how well they were progressing. One solution to this problem is the greater use of active learning in the classroom, that is, “involving students in doing things and thinking about the things they are doing” (Bonwell & Eison, 1991, p. 2). According to Boyle and Nicol (2003), “there is now a considerable body of research that shows deep and lasting learning is fostered when students actively engage with the concepts they are learning…” An IRS system could encourage active and

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group/collaborative learning, thereby drawing the more isolated students into the mainstream; be used for both summative and formative testing; and be used in revision classes to help students gauge their own performance.

IRS Procurement6 Professor Patrick McGhee, Pro Vice-Chancellor (Academic) is responsible for identifying new technologies that may have a beneficial impact on learning and teaching. Following consultation with representatives of the Learning Development Unit (LDU) and Information Systems Services (ISS), Professor McGhee authorised the purchase of an IRS to evaluate its suitability in dealing with the issues raised as a result of the SEP. The IRS selection process began in March 2003. UCLAN required a flexible and scaleable system with many features, and which was modern, robust, and easy to set up and use. In addition, the system had to fit in with the existing IT systems and infrastructure. IML visited UCLAN to demonstrate Question Wizard and the decision was taken to proceed with IML. The initial investment, equating to approximately $50,000 for a one hundred handset system, places IML at the high end of the IRS financial spectrum. “The IML IRS provides diverse functionality that allows us to integrate the system with a wide range of teaching and discussion activities. Students and staff immediately recognise the positive benefits of the technology and, unlike so many other classroom devices, the impact is neither superficial, nor short-lasting. Having used the system personally there is no doubt that it provides an immediacy that other technologies do not offer. In particular it allows the less confident audience members to participate as equals alongside the more vocal constituencies, ensuring that sessions are genuinely inclusive.” Professor Patrick McGhee, Pro Vice-Chancellor (Academic).

Interactive Response Systems in Higher Education

IML Overview

IML Technical Issues

IML Question Wizard is Microsoft Windows based software, and requires an IBM-compatible PC running Microsoft Windows XP, 2000, ME, 98, 95, or NT4 with Service Pack 4. In effect, Question Wizard is a Microsoft PowerPoint™

The installation of the Question Wizard software on the UCLAN network coincided with the rollout of a new Windows XP image. Although initial network testing was satisfactory, a number of technical issues were discovered, some of which took several weeks to resolve. For example, Question Wizard 6 was not compatible with Microsoft PowerPointTM 2003. IML updated the software to Question Wizard 7, which necessitated an update of the BIOS on the communicator handsets and base station. The default file directories (which store the presentations, results, databases, etc.) were changed to overcome network “write” permission constraints, and various “ini” files were reconfigured. To run the system, a stand-alone computer is required with a serial port to connect the base station. A serial port to USB converter was used to enable the system to work with laptop computers that did not have a serial port. This also required the reconfiguration of the “com” port, and the installation of driver and dll updates. A number of other minor issues were easily resolved. For example, the standard IRS dongle is PS2, but many new laptops lack a PS2 input. IML quickly supplied a USB dongle.

plug-in, although it is also compatible with Lotus Freelance Graphics and SPC Harvard Graphics. Presenters can create new or use pre-existing presentations with Question Wizard; question “objects” are simply added as additional slides that the presenter then displays during a presentation. Each element of the question object can be formatted to match the existing slides, ensuring uniformity of presentation. Audience responses, which are stored in a relational database for future reference, are instantly displayed on screen in chart form. IML “communicator” radio handsets are selfpowered input devices that allow users to respond to questions. Each handset consists of a keypad with an LCD display window and in-built microphone to facilitate two-way communication. One particularly useful feature of the LCD is the word “valid” or “invalid” that is displayed when users have voted. This has the benefit of informing participants whether their vote has been received and counted. The handsets communicate via a “base station” that is connected by a data cable to a serial port on the PC, or via an USB-serial converter. Each base station can simultaneously support up to 1,500 handsets. The handsets themselves can also be used as a base station, although this is only useful for relatively short periods of time as the handset operates on battery power in this scenario. Question Wizard requires a licensing “dongle” that is plugged in to the parallel port on the computer. Question Wizard can also be run in simulation mode to generate test data. This is useful for both evaluating the system, and creating and testing questions prior to a “live” presentation.

Question Wizard Features Question Wizard supports a variety of question types including single digit responses to multiple-choice questions, 127 character free-text responses, multiple-digit responses (including decimal points), ranking questions, multistage questions, and cost-benefit analysis. A variety of queries can also be performed and displayed in real time, based on previous responses. Ad hoc questions can easily be added “live” to a presentation at any time in response to audience feedback. Questions can also be timed so that a vote automatically closes after a predetermined

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period. UCLAN has obtained permission from a UK national TV company, Channel 4, to use their famous “Countdown” clock music, something that UK students really relate to and enjoy. Responses can be displayed in a variety of ways. If questions are sensitive in nature, the presenter can opt not to display responses at all, although the data is still captured. Responses can also be stored within the handsets, and downloaded by the presenter at a later stage. This feature is useful for summative testing, perhaps used in conjunction with smart cards. Users particularly enjoyed the free-text questions. A Macromedia Flash based executable file selects the text responses from the database and displays them dynamically on screen. IML gave the LDU access to the source Flash file, which we then modified to optionally play mp3 files as the text responses are displayed. It should be noted that responses are not vetted before being displayed: malicious users could potentially text obscene or offensive messages although this has not happened in practice. Over time, a bank of questions are created and stored within IML. It is easy to browse and select such questions if required, saving users the time and effort of retyping. Data is stored independently for each IRS session, meaning that the same presentation can be given to multiple audiences or classes. Data derived from multisessions can be combined and queried to produce “global” results. The IRS database can also be used to create a variety of queries. For example, answers to one question (e.g., What is your gender?) can be cross-referenced by the answers to another question (e.g., Do you like the IRS system?) and immediately displayed on screen and saved within the presentation. This, in effect, is how the quiz /scoreboard/team functionality works. An initial question can be used to assign users to teams. The software then tracks responses, based on the initial answers, and will display scoreboards based on individual and/or team responses. Presenters can assign marks for both correct answers and near misses.

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Individual responses can be tracked using smart cards. User information is “burned” on to the smart card so that when the card is inserted into the slot on the handset, the IRS automatically associates inputs from the specific handset with the user. In this situation, users can vote anonymously by simply removing the card. Smart card technology lends itself to both summative and formative assessment although, at present, UCLAN has not used this feature, preferring instead to allow anonymous responses. Post presentation users can print the PowerPoint™ slides, including charts, data, scoreboards, and so forth, as normal. A variety of reports can also be produced.

Training I undertook a two-day training course with IML to gain familiarity with the IRS. I also visited a number of other institutions, both academic and nonacademic, to evaluate their use of the system. I produced a 30-page “Getting Started” guide, and an accompanying Web site7, drawing upon the material used at the initial training. The guide concentrated on the basic functionality of IML, but did not include sections on the more advanced IRS features such as two-way audio, or the ability to store responses for future recovery. I felt that these features should be introduced at a later date, rather than confuse potential users with too much information. I publicised a training course based upon the guide in a twice-weekly global email sent out to all members of staff at UCLAN. Initial response to the publicity was encouraging, with more than 30 replies from academic staff across a range of subject disciplines including law, biology, languages, physiology, and psychology. This led to the facilitation of a number of training courses, including one specifically for UCLAN technicians who would provide technical support, if required, for staff wishing to use the system.

Interactive Response Systems in Higher Education

Each academic member of staff who undertook a training course was invited to take part in the pilot scheme, and several accepted the invitation. Time pressure, and a (perceived) increase in workload, were the main reasons for declining the invitation, although each person indicated that they would adopt the system at some future date. I was keen to ensure that the pilot scheme was successful, so I “volunteered” to prepare and format questions and presentations on the users’ behalf. I transported and set up the equipment at the various venues, and “drove” the presentation to ensure that there were no technical hitches. Unfortunately, this seems to have become a “job for life,” although the process has reinforced my skills and expertise in using the IRS.

IRS “In Action” Planning Your Career, a level two elective module8 drawing second- and final-year undergraduate students from across the university, used the IRS to test students individually and in teams, using multiple-choice questions (MCQ). E-Marketing involved approximately 150 students in two cohorts. One cohort used the IRS for summative testing, the other cohort considered the IRS as a possible marketing tool, and also had a team quiz. However, the most extensive pilot of the IRS involved a cohort of approximately 200 students enrolled on three “level-one” physiology modules. Lectures form the core material for the physiology modules, that are, in turn, compulsory to nine different degree programmes. The lectures are supported by additional tutorial and laboratory classes for various groups. The modules aim to introduce the student to some essential physiological, neurological, endocrinological, immunological, and biochemical principles. The modules are a core prerequisite for second-year physiology modules, and are perceived by students to be difficult. There is a wide age range and gender balance across the modules and courses. The diversity of the group has, for a number of years, presented a challenge for teaching staff.

Many students are mature, with no formal study, whilst others do not have a science background. Increasing student numbers has made communication between the lecturer and students difficult, as individuals are generally reluctant to ask questions or interact with the lecturer, even if encouraged to do so. Feedback about how the course material is being received and understood by students is, therefore, hard to obtain. A quiz was held using the IRS every third lecture. Students were given a calendar showing when the quizzes would occur, as well as being reminded the week before they were held. Handsets were provided to groups of two or three students and used to register the group by identifying the course they were studying. Approximately 10 multiplechoice questions were asked per session, based on the material from previous weeks’ lectures. The groups discussed the options before submitting their vote. Competition was encouraged as each response counted towards an “end-of-semester” team score. The first time that the IRS was used, the students were briefed on the use of the handsets and the purpose of the system. It was contextualised as part of a series of in-class tests that would assess student knowledge and revision of a number of biological topics. This process took less than 5 minutes. Distribution of the handsets required that one student from each of the groups had to collect (and eventually return) a handset on behalf of their colleagues. I did not receive any negative comments from the students about this process. In subsequent sessions, the students automatically collected handsets en route to their seats. A typical IRS session was observed by Ros Healy (Senior Lecturer, Centre for Employability), who then produced a report. In her report, Ros wrote: Michael led the interactive process whilst Darrell Brooks (Senior Lecturer, Department of Biological Sciences) explained and elaborated upon the responses. This seemed to work particularly well as it freed the lecturer to concentrate on the

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content whilst the technical aspect was managed by the expert. Students responded very positively to the experience and they had no difficulty in understanding the process or in using the equipment. The questions posed evoked discussion in the small groups and some disagreement about the correct response. It was clear the groups were thinking carefully about the problems that had been posed. It was a good technique to reveal the answers after the lecturer had explained the varying options as more detailed discussion took place in the groups before the correct answer was revealed. Once answers to the questions were displayed students became very animated and were pleased to see visual confirmation of (correct) responses, again this led to engagement and enthusiasm. By the time team scores were displayed students were exceptionally engaged and animated; concentration on responses seemed to be improved and there were spontaneous rounds of applause when students correctly answered a question. I would say the system is an excellent tool for team building and team development. My overall impression was that students greatly enjoyed the interactivity offered by the system. It exploits the natural competitiveness between groups though I do think this has to be sensitively handled. It is a very useful learning tool for a group dealing with a difficult academic topic as it makes learning fun.

IRS Evaluation “Planning Your Career” students were informally asked at the end of IRS sessions whether they had found them useful and enjoyable. The result was unanimously positive. Several students explicitly mentioned the IRS in their module

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evaluation questionnaire (MEQ),9 commenting how much they enjoyed using the IRS technology in lectures. The “E-Marketing” MEQ explicitly asked students three IRS related questions. When asked whether using the technology was useful and an aid to concentration, 81.8% (N=66) agreed, whilst 18.2% found the technology distracting. When asked whether the IRS had been useful for testing prior knowledge (N=70) 28.6% responded “Very Useful,” 61.4% responded “Useful,” whilst 10% responded “Not Useful.” Finally, when asked if the IRS was a useful method of introducing new concepts (N=71) 21.1% responded “Very Useful,” 67.6% responded “Useful,” whilst 11.3% responded “Not Useful.” A more formal evaluation took place of the physiology module using a combination of online questionnaires, peer observation, a small focus group of three students, and a direct comparison of examination results between 2003 and 2004. It should be noted that the results of this evaluation should be considered as preliminary; a more detailed and structured evaluation will be undertaken when the IRS system is fully implemented across UCLAN.

Online Questionnaire A total of 95 students completed the online questionnaire (almost 50% of the class), with the results input into SPSS10 for statistical analysis. The questionnaire consisted of 11 statements with 5 possible responses ranging from “strongly disagree” to “strongly agree.” The results of the questionnaire were overwhelmingly positive. For example, of those students who completed the questionnaire, 99% liked using the system, 99% preferred “IRS lectures” to the more traditional type, 97% liked the timed questions, 90% thought that the IRS made them pay more attention than they would normally have done, 93% thought that the IRS enabled them to evaluate their progress in relation to the rest of the class, and 96% thought that more lecturers

Interactive Response Systems in Higher Education

should use the technology. In summary, more than 90% of the students were positive about every aspect of the IRS.

Peer Observation As part of a Teaching Peer Observation System11 at UCLAN, other academic staff attended the IML quiz sessions, and provided feedback. It was pointed out that at one of the early sessions, it took over 10 minutes for the system to be set up. This raised the concern that the benefit of using the system was outweighed by the time to produce the quizzes and set up the IRS at the start of each lecture. Another member of staff sat amongst the students and noticed that, while some groups were actively engaged in the quiz, discussing the questions, others were not. In the latter case, the students were going with a “gut” feeling about the answer, without the benefit of discussion. Strategies to improve the dialogue between group members will need to be considered in the future.

Focus Group The physiology students were invited to participate in a focus group, and approximately 12 students volunteered. Unfortunately, the focus group had to be scaled down due to unforeseen circumstances. It is recognised that the three students who did take part were all females, in their early twenties, and not truly representative of the student cohort. However, when questioned, the responses from the three students were consistent with the results of the online questionnaire. The students did not feel that the novelty of using the IRS would wear off, “…doing a quiz like that is fun anyway”; they all felt that using the IRS was an improvement over traditional lectures, “… I found I was actually reading back over the work so that when a quiz came I knew more of the answers;” and class attendance improved, “…

when there was a quiz coming up there was more people in the lecture theatre … if there wasn’t going to be a quiz, then you tend to think ‘oh well I can get the notes off Web CT’12.” The students felt that the IRS helped them honestly gauge their own progress, “… you were listening more so that you could find out exactly where you’d gone wrong … in a normal lecture the lecturer would give out the answer and you could say ‘yeah I was going to say that’ but with the handsets you know that you were wrong so it highlights your weaknesses.” When used in group work, the students were very positive, “… everyone was discussing the answer, so it got us working together … it’s like we’re teaching each other … one person would say ‘I think it’s this answer because …’ and the others will say ‘no you’re wrong because …’” Finally, the students felt that the IRS was particularly good for revision purposes, “… I thought it was really useful. It really showed us what we needed to know for the exam.”

Examination Results Comparison The physiology module assessment includes a variety of tests, quizzes, and written work. It includes two “end of semester” examinations consisting of 40 MCQs, each with four possible answers. The “end-of-semester” examination questions were in exactly the same format as those used in the IRS lectures. Students need to score an average of 40% over the different assessment methods to pass the module. Fundamentally, the only difference between the teaching methods of the two cohorts was the use of the IRS. In other words, the same lectures were delivered by the same lecturer, in the same location, with the same assessment criteria required to pass the module. In order to usefully compare results, the students were divided into three main groups, depending on their main degree course. There was a quite large spread of results across each group. It is important to note that this was the students’

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first experience of examination pressures, and that they nearly always improve when the second “end-of-semester” examination is taken. The following statistical analysis compares semester-1 examination results between the 2003 and 2004 student cohorts. Differences were tested using a one-tailed t-test. •

•

•

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Group 1 consists of mainstream physiology students studying biology/biomedical sciences. Their career path would lead them into work in hospital laboratories. These students are highly motivated academically, being fresh out of college with recent experience of learning. The difference between the results for this group was highly significant (p = 0.001), with the average scores increasing from 41.5% (N=58) to 54.9% (N=76), an increase of 13.4% in absolute terms. This group won the end of year prize. Group 2 consists of complementary medicine students. They were mainly mature students with no recent formal education or qualifications. They are considered to be highly motivated, and committed to studying well anyway. They were already working hard, and the IRS helped to alleviate any anxiety they may have felt about their academic performance. The average scores for students in this group increased from 49.7% (N=43) to 55.9% (N=41), an increase of 6.2% in absolute terms. Group 3 students are sports scientists and therapists. These students required excellent “A” level results to get on the course, but they tend to be more interested in the actual sport itself, rather than academic study. The average scores for students in this group increased from 33.5% (N=63) to 34.8% (N=72), an increase of just 1.3% in absolute terms. These students, as mentioned in the peer observation comments, appeared to treat the IRS as a bit of fun, and did not really engage in the process.

All groups showed some improvement, although there was quite a large standard deviation across each group. It is difficult to wholly attribute the improvement in performance to the use of the IRS, and there may well be unrelated “non-IRS” factors to take into account. However, as previously mentioned (Boyle, & Nicol, 2003), increased engagement with learning is likely to improve learning. The IRS promoted student discussion about the course material; made lectures more entertaining; improved attention and attendance; improved confidence about what students should expect in the examination; and increased student motivation to research, review, and learn the course material. Ultimately, the results and student feedback concerning the use of the IRS are very encouraging.

Additional Benefits of IRS Although the IRS was purchased to deal with issues raised by the SEP, it has also been used for a variety of other purposes, perhaps helping to justify the expenditure incurred in purchasing the system. For example:

Service Departments •

•

•

Information Systems Services (ISS) have used the system to ascertain staff thoughts on a number of department “away days.” Library and Learning Resources (LLRS) use the system to test the effectiveness of their student induction training. Human Resources (HR) regularly use the system when training staff to serve on recruitment panels to clarify how much information the delegate had taken in and understood.

“The IRS is extremely successful. Every opportunity we’ve had to use it the feedback has been excellent. Some of the delegates themselves are extremely interested in using the IRS in their own remit.” Wilma Butterworth, Staff Development Advisor, Human Resources.

Interactive Response Systems in Higher Education

Conferences The IRS was used at the fourth annual LDU conference, which was held at UCLAN in the summer of 2004. The theme of the “Accessibility in Practice” conference was the practical implications of implementing the UK’s Special Education Needs and Disability Act 2001 (SENDA), particularly in relation to the accessibility of Web sites. The IRS enabled presenters to ask conference delegates their opinions about a variety of Web accessibility issues. Bob Regan, the Senior Product Manager of Macromedia, used the system to ascertain the technical knowledge of the audience before delivering his presentation, thus enabling him to “pitch” his presentation at the right level—I have termed this “contingent presenting.”13 There are a few things I think that are interesting about the using of IRS. It provides everyone with a chance to share their opinion. If there is no wrong answer, then there is no reason to be concerned about sharing your thoughts. One technique I love using with these types of systems is to call on individuals students to ask how they voted, and explain why. It is better than the old ‘paper chase’ model of call and answer but students must still stay engaged at a deeper level than passive listening. If done properly, it can be a powerful tool for discussion. (Bob Regan, Macromedia) The IRS was also used at the annual “Heads” conference, attended by approximately 70 of UCLAN’s senior management. UCLAN’s commitment to the IRS was reinforced by the Vice-Chancellor, Malcolm McVicar, who used the system to obtain the views of senior management, across a range of issues. At the end of the conference, the “Heads” were asked two specific IRS questions. There were 71 responses to both questions. Q1—Did the voting system add value to the conference?

Yes—A lot—80% Yes—A bit—8% Not really—8% Sell it on EBay—4% Q2—Do you intend to encourage use of the voting system with your staff and students? Yes—For teaching—17% Yes—For general meetings—37% Yes—For both—25% Can’t see an application for the system—19% No—2% As a result of the conference, three “Heads” volunteered to pilot the IRS within their own academic departments.

Future Plans The evaluation of the IRS indicates a successful pilot scheme. Informal discussions between IRS stakeholders at UCLAN have confirmed their overall satisfaction with the IRS. The next phase requires that the IRS be integrated into mainstream student and academic life at UCLAN. This raises a number of issues that must be considered as the integration process proceeds over time. Managing the IRS itself requires that the equipment be in a certain place at a certain time; that handsets are fully charged up, and so forth. Whilst implementing the pilot scheme I have been undertaking these duties personally, but it is impractical to expect this situation to continue indefinitely. Therefore, plans are being formulated to install IRS into the main lecture theatres, enabling staff to access the system on demand. This would help to resolve the (perceived) time issue, raised previously. A centrally-located repository of handsets may be created to issue handsets as required. A number of portable systems would also need to be available for staff lecturing in smaller teaching rooms. The responsibility for manag-

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ing the IRS still needs to be formalised, but it is hoped that university technicians will agree to this additional role. Requests to use the IRS have been increasing on a regular basis. I have been creating questions on behalf of IRS users, but this is impractical on a long-term basis. Training materials have already been written, tested, and used, but the responsibility for the long-term training and development needs of staff wishing to use the IRS needs to be established.

Conclusion The IML IRS is a powerful demonstration of how technology can add real value to the contemporary learning experience. We have used the system in a variety of fora, from small seminar teaching to large conferences, at UCLAN and in each application the system offered staff and students immediate audience response and the opportunity to analyse the data in more detail post event. (Malcolm McVicar, Vice Chancellor, UCLAN) There has been a very positive response from the vast majority of IRS participants, both presenters and delegates. The implementation has been achieved without any real problems of substance, with the participants keen to make the pilot scheme successful. Staff at UCLAN, at all levels, recognise that the diversity of the student population could lead to a higher-than-average number of students dropping out of their degree programmes. They also recognise the contribution that technology can make in engaging those students in their own learning process. However, in order that technology can contribute to the academic enterprise, it must be accepted by both academics and learning technologists. Successful implementation of any change process requires leadership from all levels of any organisation, but initially, the commitment and resources must come from senior manage-

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ment. Recognition and celebration of UCLAN’s diverse student population, and the contribution that this specific technology can make to student engagement, was supported by senior management. The responsibility for implementing the pilot scheme was the politically neutral Learning Development Unit. This Unit promotes the integration of traditional teaching approaches with new technologies, and is respected across academic, functional, and financial boundaries of the institution. This is essential for the introduction of any new technology. Many of the issues raised by students during the SEP have been addressed, at least in part, through the introduction of the IRS, although it is too early to say whether the actual retention figures have improved. Research has shown that the vast majority of students enjoy using the IRS system. The system addresses a number of the key SEP issues and is a valuable addition to the academic teaching toolkit. (Diane Richardson, Student Experience Project Leader)

References Bonwell, C. C., & Eison, J. A. (1991). Active learning: Creating excitement in the classroom (Report 1). ASHE-ERIC Higher Education Reports. Boyle, J. T., & Nicol, D. J. (2003). Using classroom communication systems to support interaction and discussion in large class settings. Association for Learning Technology Journal (ALT-J), 11(3), 43-57. Lonely students quit as hard-up students hang on. (2002, September 13). The Times Higher, Based on research by Liz Thomas, Director of the Institute for Access Studies, Staffordshire University, UK. MacLeod, D. (2002, December 18). Loss and retention. The Guardian.

Interactive Response Systems in Higher Education

McGivney, V. (1996). Staying or leaving the course. NonCompletion and retention of mature students in further and higher education. NIACE

7 8

Endnotes 1



2



3



4

5

6





UCLAN, Widening Participation Strategy (Section 1.1) available online at http://www. uclan.ac.uk/other/sds/local/documents/corporate/strategies/widepartstrat.doc Further information about HEFCE can be found at http://www.hefce.ac.uk/ The benchmarks are performance indicators, a range of statistical indicators intended to offer an objective measure of how a higher education institution (HEI) is performing - http://www.hefce.ac.uk/Learning/PerfInd/2003/guide/what.asp For a tabular description of the socio-economic classes see http://www.statistics.gov. uk/methods_quality/ns_sec/class_collapse. asp Statistics from Higher Education Statistics Agency (HESA) - http://www.hesa.ac.uk/ Please note that the author had no input in the purchase decision, and is unaware of whether other IRS were considered or evaluated before deciding to proceed with

9





10



11



12



13



IML. The author has no financial interest in IML. http://www.uclan.ac.uk/ldu/irs/ For an overview of modules, levels, electives, and so forth, see http://www.uclan. ac.uk/ldu/resources/toolkit/modcats/ The Module Evaluation Questionnaire (MEQ) is used by UCLAN to gather student feedback. Its purpose is twofold in that the student feedback provided will enhance the students’ experience of learning and teaching, and it will contribute to the monitoring and review of quality and standards. http:// www.uclan.ac.uk/quality/meq/index.htm SPSS is a statistical software package developed for use in the social sciences. http://www.spss.com/ Peer Support for Learning and Teaching Through Observation http://www.uclan. ac.uk/quality/peerobs/app_01.htm Web Course Tools (Web CT) is the online virtual learning environment (VLE) used by academic staff at UCLAN to enhance their teaching. See http://www.webct.com/ For a discussion of contingent teaching as it applies to IRS, see “Degrees of contingency,” by Steve Draper, Department of Psychology, University of Glasgow. http://www.psy.gla. ac.uk/~steve/ilig/contingent.html

This work was previously published in Audience Response Systems in Higher Education: Applications and Cases, edited by D. A. Banks, pp. 305-320, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 3.6

Hyper Video for Distance Learning Mario Bochicchio University of Lecce, Italy Nichola Fiore University of Lecce, Italy

IntroductIon In general, the production of hypermedia applications is a complex and expensive task, requiring both technical skills and communicative abilities (Bochicchio, Paiano & Paolini, 1999a, 1999b). Nevertheless, some specific kinds of multimedia production can give good quality results, even without specialized IT skills, at a low cost. We have concentrated on this particular field, with the goal of supplying a valid tool to teachers who want to publish their educational material easily and at a low cost. It is easy for a good teacher to give a lesson and to explain concepts using images and slides to show objects, to write on the blackboard, and to use his body language to grab and hold the attention of his students. In our opinion, these kinds of lessons can be effortlessly transformed into very usable and ef-

fective multimedia applications based on the video of the lesson, on a simple and regular navigation structure, and on a little set of user-friendly multimedia objects.

background Various research and commercial tools, such as GRiNS (2001), MTEACH (Montessoro & Caschi, 1999), Video Madeus (Roisin, Tran-Thuong & Villard, 2000), and Real Presenter (PresenterPlus, 2001), are based on this assumption, but their effectiveness is limited by a number of issues: •

•

their technical complexity makes them unsuitable for a large number of teachers with low technical aptitude; in general, they are more data-driven than user-centered;

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Hyper Video for Distance Learning

•

•

the time and the budget needed for a non trivial production (e.g., a course of 10 hours or more) can be remarkable; and they are often limited to specific lesson styles (e.g., a frontal lesson based on MS PowerPoint presentations).

Moreover, it is well known that long video sequences (e.g., 1 hour or more) are not compelling and not interactive, and the usual linear cursors and VTR-like controls can be ineffective for navigating video sequences longer than a few minutes. To solve these problems we created LEZI, an experimental tool oriented to the very easy production of video clips enriched with hierarchical indexes, hyper-textual elements and other multimedia objects (hypervideos).

lezI project: reQuIrements An accurate analysis of both research and commercial tools permitted us to extrapolate the essential requirements of a good development environment based on indexed video. Starting from these requirements, a LEZI prototype was developed at the Hypermedia Open Center (HOC) of the Politecnico di Milano, and a number of real lessons were produced and tested (Bochicchio, Paiano, Paolini, Andreassi & Montanaro, 2000). A project for a more complete prototype, called LEZI II, was then started at the SET-Lab of the University of Lecce, within a large research project focused on the development of innovative educational tools and applications. The first fundamental requirement for LEZI is that it be very easy to use, so that it can be truly accessible even to users with very basic computer knowledge. The second, even more important requirement is to keep production times down (ideally to about one hour of work or less for each hour

of the lesson). In some cases (e.g., conferences or special events), it may be important to extend this constraint up to the “real time production” limit (i.e., the indexed hypervideo of the event should be available on CD/DVD, and online, by the end of the event itself!). A third very important requirement is the ability to effectively support the most common “authoring situations”, like those in which a teacher: •

•

•

•

Presents his lesson in a classroom, with a blackboard, or outside the classroom (on the field), if this is appropriate for the topic concerned Uses gestures to “animate” some concept expressed by “static schema” (typically a slide), so that students need to simultaneously view the two different information sources (the teacher and the schema) Uses his PC to explain how to use a specific computer program when the attention focus is on the display of the PC, on the voice of the teacher and, optionally, on a blackboard Uses his PC to make a PowerPoint presentation. The attention focus is on the display of the PC and on the voice of the teacher.

The fourth requirement relates to finding the various topics and subtopics in the lesson. The user needs a fast and effective way to find out the contents of the video lesson, so they can easily find and reach the subjects of interest without wasting time on uninteresting or already-known video sequences. We maintain that the most common video players (Real Player, Microsoft Media Player and QuickTime player) generally do not offer an adequate solution to this problem. The fifth requirement concerns the technical skills needed in the authoring phase; it is important to have a high-level authoring tool to simplify all technical tasks and to fully support teachers and

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Figure 1. LEZI II: Hyperbase in the large >

lesson

Child of >

topic

0...1

> Title String Description Text Author String

Belongs to

> Title String Description Text Author String

0... n >

0...n

video sequence > Title String Topic Video Short Title String Start Time Time End Time Time > Title String Topic Video Short Title String

Related to > >

>

bibliographyc

teaching

reference

material

> Reference String Description Text > Reference String Description Text

lecturers, whatever technical knowledge they may have. A final requirement concerns the possibility of linking suitable comments, bibliographic references, and other teaching materials to the indexed hypervideo. The most common digital document formats (PDF, HTML, PPT, etc.) should be supported.

conceptual modelIng The W2000 (Baresi, Garzotto & Paolini, 2001) methodology has been adopted to refine the informal description presented so far, to obtain a suitable conceptual model for LEZI II, and to derive from it the current LEZI II prototype. W2000 is a user-centered methodology for conceiving and defining hypermedia applications. It organizes the overall development process into a number of interdependent tasks. Each activity produces a set of related diagrams which describes

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relatess to

glossary term

> Title String Description Text File Name String

> Name String Description Text

> Title String Description Text

> Name String Description Text

some aspects of the hypermedia application, and is based on UML. The idea underlying W2000 is a requirements-driven, user-focused approach to design. In brief, for the LEZI prototype we have identified the following roles: • •

• •

Author: manages his public/private lessons and related students; Registered Student: attends public/private lessons and can perform second level authoring (co-authoring) operations (Garzotto, Mainetti & Paolini, 1995). Unregistered Student: can only attend public lessons; and LEZI Manager: manages the system.

It should be observed that the users of the LEZI II system are not rigidly associated with a single role. A registered student of a given lesson, for example, could also play the role of author for a different lesson. Specifying roles is the best way

Hyper Video for Distance Learning

Figure 2. W2000 functional use-case diagram of LEZI II Manages his course

A course is a collection of lessons about the same topic

Jots down in a lesson Author

Manages the lesson A lesson consists of forms and videos

Organizes the glossary

Manages the bibliography Manages the educational materials

Searches Courses/Lessons/Topics

Registered Student

Attends a private lesson

Customizes his lesson 2nd level authoring

Creates a personal view of the topics of the lesson

Attends a public lesson Unknown Student

Promotion (TopTen )

Lezi Manager

Manages the system

to make user profiles explicit and to avoid duplicating functionalities. In Figure 1, the hyperbase diagram of LEZI II is outlined in terms of HDM2000 primitives (Baresi, Garzotto & Paolini, 2001).

The hyperbase schema is adopted to specify: •

the information structures needed by the various classes of users (information design)

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•

the navigation paths that allow users to find the piece of information suitable for their task (semantic navigation design).

In Figure 2, we show the main functional usecase diagrams, in which the main functionalities are associated with the previously identified roles.

the lezI II prototype Different LEZI prototypes have been produced since July 2001 at the SET-Lab of the University of Lecce (http://mb.unile.it/Lezi). Referring to the fourth requirement, in all prototypes the main access structure has been implemented as a tree, organized into topic and subtopic nodes. Each topic node corresponds to the sequence of the videos associated with its subtopics, and the root corresponds to the entire lesson. No more than four subtopic levels are allowed, and each leaf of the tree corresponds

Figure 3. The “Hyperbase and Access Layers” topic

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to 2-5 minutes of video. Each node (both topic and subtopic) of the tree contains a short textual description of the video associated to that node and the indication of its duration. This short description is very effective for finding the interesting topics and skipping the uninteresting (or the already-familiar) ones. The tree-index acts as a hierarchical table of contents (TOC in the following). It can be generated manually or semi-automatically by creating a sequence of nodes equally-spaced in time. The authors of the lesson can then add/delete/modify the text associated with each node, as well as its duration and its start/end time. Multiple tree-indexes can be created for a given lesson, so that the same lesson can be easily re-adapted for different purposes and different users. The prototype has two distinct parts: the authoring part, suitable for creating a new LEZI lesson, and the fruition part which may be used to navigate among existing lessons and to select and play the desired one.

Hyper Video for Distance Learning

From the technical point of view, the online LEZI environment requires a networked workstation, equipped with RealServer (for the video streaming) and Internet Information Server (for the lesson server), while the online LEZI client, suitable for both authoring and fruition, can be executed in any browser supporting JavaScript and equipped with the RealVideo plug-in. Different user interface styles (multi-skin) and a customizable set of interface objects (background, buttons, colors, fonts, etc.) are supported to better adapt each LEZI II lesson to the expected audience. From the implementation point of view, the online version is based on the MicroSoft-ASP object model for server-side scripting and on JavaScript and DHTML to implement the visual interface for the client. A SMIL program (SMIL, 2001) has been used to correctly synchronize the tree-index with the video streams. In comparison with the MicroSoft-ASF format the RealVideo format was more reliable and performed better. In particular, with RealVideo it was very simple and effective producing video clips for multiple bandwidth targets, able to automatically switch to lower/higher bit-rates according to network conditions. The first step in creating a lesson with the LEZI prototype is to produce the movie in RealVideo format. The lesson can be recorded on a PC or on a notebook equipped with RealProducer by means of a USB video-converter and a video source. If the lesson is already in digital format, they will have to be converted into the RealMedia format before other steps. Further steps to produce the lesson with LEZI II, are: • •

To create a tree index at the end of the recording session To add teaching materials (if available as digital documents) and bibliographical references to the indexed video

•

To generate the LEZI II lesson (both for CD/DVD and for online use)

valIdatIon The University of Lecce has produced many applications with LEZI II, to empirically validate the proposed approach. An example is the computer-graphics class given by Professor Paolo Paolini (Milano-LecceComo, 2001). The screen shot in Figure 3 is related to a group of topics on the design/modeling methodology W2000. The class is given to students at the university level. In order to provide an example of TOC, let us consider the topic “Information Design” that is structured into sub-topics: “Hyperbase and Access Layers”, “Segments”, and “Collections”. The user is free to “attend” the lesson starting from any point he prefers. For instance, if the paragraph “Information Design” is chosen, it is not necessary to run the video at higher hierarchical levels, which can be skipped over to go directly to the selected node. The described LEZI application, that is very cheap and easy to produce, is used to support the normal (“in presence”) teaching activity and is considered extremely useful from all involved students.

future trends The described idea is very simple: it is possible to publish good educational multimedia applications developed by academic staff with very little technical effort, in a short time, and with limited financial resources. The future trends in this field come around to support the re-use of existing contents on the net. To better support the LEZI philosophy, it is important the adoption of a content-sharing

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model and the opening to the standards given by Advance Distance Learning (ADL, 2003) or IEEE (2003) to obtain a common interface for all the learning systems.

conclusIon LEZI philosophy enables teaching staffs without specific technical preparation in multimedia production but with valid content and good teaching skills, to easily prepare good interactive multimedia lessons, both for disk-based (CD/DVD) or online (Web) purposes. More generally, the widespread use of LEZI or other similar tools can effectively support the development and use of educational multimedia content in universities and schools. Obviously, this kind of multimedia content is not intended to replace the publications of professional editors.

references Advanced Distributed Learning. (2003). Retrieved August 2003, from http://www.adlnet.org Baresi, L., Garzotto, F., & Paolini P. (2001). Extending UML for modeling Web applications. In Proceedings of the 34th Hawaii International Conference on System Sciences (HICSS’01), Maui, USA. Bochicchio, M.A., Paiano, R., & Paolini, P. (1999a). JWeb: An HDM environment for fast development of Web applications. In Proceedings of the Multimedia Computing and Systems (IEEE ICMCS ’99), 2, 809-813. Bochicchio, M.A., Paiano, R., & Paolini, P. (1999b). JWeb: An innovative architecture for Web applications. In Proceedings of the IEEE ICSC ’99, Hong Kong.

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Bochicchio, M.A, Paiano, R., Paolini, P., Andreassi, E., & Montanaro, T.(2000). LEZI uno strumento per un facile sviluppo di video interattivi a scopo educativo. In Proceedings of the DIDAMATICA 2000, Cesena, Italy (pp.72-78). Garzotto, F., Mainetti, L., & Paolini, P. (1995). Hypermedia application design: A structured approach. Designing user interfaces for hypermedia. Springer Verlag. GriNS. (n.d.). Retrieved August 2000, from www. oratrix.com/GRiNS IEEE. (2003). Draft standard learning object metadata. Retrieved August 2003, from http:// www.ieee.org JMF. (n.d.). Retrieved August 2000, from http:// www.javasoft.com/products/java-media/jmf/index.html Montessoro, P.L., & Caschi, S. (1999). MTEACH: Didactic multimedia production. In Proceedings of the Multimedia Computing and Systems 1999 (IEEE ICMCS ’99), 2, 1017-1019. PresenterPlus. (n.d.). Retrieved August 2000, from http://www.realnetworks.com/products/ presenterplus RealServer Guide. (n.d.). RealNetworks 19952000 (chs. 4-5). Roisin, C., Tran-Thuong, T., & Villard, L. (2000). A proposal for a video modeling for composing multimedia document. In Proceedings of theMMM2000, Nagano, Japan. SMIL. (n.d.). Retrieved August 2000, from http:// www. w2.org/Audio/Video Windows Media Technologies. (n.d.). Retrieved June 2002, from http://www.microsoft.com/windows/windowsmedia/overview/default.asp

Hyper Video for Distance Learning

key terms DVD (Digital Versatile Disc): An optical disc technology that is expected to rapidly replace the CD-ROM disc (as well as the audio compact disc) over the next few years. The digital versatile disc (DVD) holds 4.7 gigabyte of information on one of its two sides, or enough for a 133-minute movie. HDM: The modeling language used by W2000 to describe the information, navigation and presentation aspects of a hypermedia application. Hypervideo: Indexed video enriched with hypertextual and multimedia elements. It is a fast and effective way to “navigate” in long video clips and to find out the main contents of the video. USB (Universal Serial Bus): A plug-and-play interface between a computer and add-on devices

(such as audio players, joysticks, keyboards, telephones, scanners, and printers). With USB, a new device can be added to a computer without having to add an adapter card or even having to turn the computer off Video Adapter: An integrated circuit card in a computer or, in some cases, a monitor that provides digital-to-analog conversion and a video controller so that data can be sent to a computer’s display (alternate terms include graphics card, display adapter, video card, video board and almost any combination of the words in these terms). Video Streaming: A video sequence that is sent in compressed form over the Internet and displayed by the viewer as they arrive W2000: A user-centered methodology for conceiving and defining, at conceptual level, hypermedia applications.

This work was previously published in the Encyclopedia of Information Science and Technology, Vol. 3, edited by M. KhosrowPour, pp. 1361-1366, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.7

Rubrics as an Assessment Tool in Distance Education Bonnie L. MacGregor Bryant & Stratton College, USA

IntroductIon Effective communication of the grading process to students is a concern that many online instructors face. The purpose of this entry is to show how the use of a rubric as an assessment tool clarifies for distance education instructors and their students the expectations, criteria, and performance levels of assignments, plus—more importantly—how the rubric details the description of the earned grade. Many student activities can be assessed similarly in a distance learning situation to the building-based environment. There are traditional assignments, such as multiple choice tests and homework, which measure students’ ability to absorb content information. Alternate assessments—such as paintings, stories, projects, essays, portfolios, journals, web page designs, simulations, group activities, PowerPoint® presentations, self-evaluations, etc.—ask the student to demonstrate their knowledge about the learning

process or the quality and effectiveness of some product that they have authored. Herman, Aschbacher, and Winters (1992) describe the process of creating alternative assessments to include linking assessment and instruction, selecting assessment tasks, setting criteria, ensuring reliable scoring, completing student self-assessment activities, and identifying decision making moments. Often, when adopting the ideas of alternative assessments, instructors focus only on creating new and innovative activity directions without matching them to reliable scoring. Montgomery (2002) identifies that traditional grading for these alternative assessments often is through proofreader marks or teacher comments in the margins of the document that can be open to interpretation. Without specific criteria identified that match the learning objective for the activity, the grading becomes subjective and non-effective for student improvement (Andrade 2000: Herman, Aschbacher & Winters, 1992; Montgomery 2002; & Sanders, 2001).

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Rubrics as an Assessment Tool in Distance Education

what Is a rubrIc? The Latin rubrica terra (or red earth) is the origin of the word “rubric.” The evolution of the word over time moved from marking sections of medieval manuscripts with red notations to the identification of various sections of rules. The term rubric today is a set of rules for grading a classroom activity that includes defining the outcomes to be evaluated at a basic through mastery level (Marzano, Pickering, & McTighe, 1993; Popham, 1997; Taggart, Phifer, Nixon, & Wood, 1998). A rubric lists the criteria of the activity that matches the instructional performance objectives of the lesson or course. The rubric can be categorical—a simple checklist—to see if various parts of the assignment are present. It can offer details on scoring which identifies each specific criteria of the activity plus degrees of performance, usually using words that describe

the levels as poor, good, better, and best. Or the rubric can be holistic where there is a summative list of characteristics sorted by performance that can be used to show overall what is exemplary, standard, or poor work. One type of rubric that can be utilized effectively to assist the communication between asynchronous teachers and students who are at a distance is called either the detailed or descriptive rubric.

descriptive rubric Once the instructional and performance objectives have been identified for a lesson or course, the following step is to design the alternative assessment including both the directions of the activity plus the rubric with scoring criteria and performance levels. Both criteria and performance levels are “described” in a grid format so that students visually can see that they can move from one level to the next higher level to obtain a higher grade (see Figure 1).

Figure 1. Sample descriptive rubric format

Criterion 1 Criterion 2 Criterion 3

Performance Low Poor Poor Poor

Performance Basic Good Good Good

Performance Standard Better Better Better

Performance Commendable Best Best Best

Figure 2. Sample graded descriptive rubric format Performance Low 0 points

Performance Basic 1 point

Performance Standard 3 points

Performance Commendable 5 points

Criterion 1

Poor

Good

Better

Best

Criterion 2

Poor

Good

Better

Best

Criterion 3

Poor

Good

Better

Best

Criterion 4

Poor

Good

Better

Best

Criterion 5

Poor

Good

Better

Best

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Rubrics as an Assessment Tool in Distance Education

Points are assigned for each column of performance with the low column often showing no points, the basic column shows some points, the standard “passing” points, and the commendable shows exceptional points identifying 100% mastery of the criteria. Students use the rubric while creating their product to “see” what the teacher means by “ok” versus “exceptional” work. Some students are willing to “slide by” with a minimum effort, and, using the rubric, they now have the details of what they must do minimally to pass this activity. Other students are over achievers and they will do everything that they can to hit the “mastery level” performance for all criteria activities. By “seeing” what the teacher wants before the activity is created, distance learners can budget their time for the “level” that they are targeting for their performance and their grade.

a chance to “reflect” on the process of learning that evolved through completing this activity. Once submitted, the instructor can grade students’ products by choosing the level of performance for each criterion. By adjudicating students’ work against the predefined rubric, each grade is assigned. By analyzing all rubrics for that class and activity, the instructor can identify if there are trends within a certain number of student products where certain criteria have not been met, where directions may not have been clear, or where the rubric performance level descriptions were ambiguous. This can lead to remedial or new instruction on the missed criteria and/or a “lesson learned” to change the directions or wording on the directions or rubric for next term.

using the descriptive rubric

A graded rubric, whether through student selfreflection or instructor final adjudication, shows that most students do not stay strictly within one column or another for performance but they float through different mastery levels that are particular to each criterion (see Figure 2). In this illustration, both the student and the instructor know that Criteria 2 and 4 have been met at a mastery level, criteria 1 and 5 have been

After the product is completed, the student uses the rubric for self-evaluation purposes. This gives the opportunity to check the product once again against the criteria to be sure that all items have been included, and, if not, gives the student an opportunity to edit or “fix” the item that is missing or incomplete. This activity also gives the student

grading with the descriptive rubric

Figure 3. Sample “in between” graded descriptive rubric format

Criteria 1

Performance L ow 0 points Poor

Performance B asic 1 points Good

Performance Standard 3 points B etter

Performance Commendable 5points B est

Criteria 2

Poor

Good

B etter

B est

Criteria 3

Poor

Good

B etter

B est

Criteria 4

Poor

Good

B etter

B est

Criteria 5

Poor

Good

B etter

B est

Note: Total per column =

0

+0

Total earned = 19 points/ 25 possible = 76% overall mastery

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+2

+3

+4

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Rubrics as an Assessment Tool in Distance Education

met generally, and criteria 3 needs some remediation. On this particular rubric, the points have been assigned by “skipping” over the “unlisted” points 2 and 4. In some situations, the instructor might identify a person who is somewhere “in between’ two columns and be able to assign “unlisted” points to show the student that they are moving away from one level, toward the next one, but that they have not yet fully arrived (see Figure 3). Here the student can see that movement is achieved for criteria 3 and 5 but that full performance for the next level has not yet been demonstrated. Criteria within an activity are not always equal in status for the assignment. In that case, the rubric can display the criteria and its weight to the whole assignment. To calculate the overall student performance on a weighted criteria rubric, each criteria’s earned points are multiplied times its weight. The results for each weighted criteria are added together to gain an overall mastery score (see Figure 4). Rubrics can be separate documents attached to the assignment or, depending on the activity, they can be electronically copied and pasted at the end of the activity (for example, the rubric can be included at the end of an essay or term paper typed and submitted within Microsoft Word®). This gives the distance learner a “visual clue” — via a text-based communication — as to how the activity was evaluated by the instructor and where the strengths and weaknesses are. There are various web sites set up to assist an instructor in the creation and design of a rubric. A webpage authored by Starr (2000) has links to help with designing the rubric, using project based learning checklists, finding the rubric construction set, and learning about the product the Rubricator™ Dodge (2001) describes the process for identifying elements to each criterion and ties its dimensions of learning to different elements. For example, for an instructional goal of “collaboration,” Dodge suggests terms to for

criteria as cooperation, taking responsibility, and conflict resolution. Teach-nology’s (2003) web page includes links to rubric generators and sample rubrics for such topics as oral expression, paragraph writing, persuasive writing, team work, research report, projects and presentations.

benefIts/obstacles to usIng rubrIcs There are two major benefits for using a rubric from the students’ viewpoint. First, by receiving a rubric at the same time as receiving the directions for an assignment, students can see the criteria and performance levels/standards for scoring before they actually begin the activity. Second, by completing a self-evaluation of the activity using the rubric prior to submitting the activity to the instructor, students are learning to proofread and assess their own performance against a standard. A benefit of using a rubric for the instructor is to have the criteria and scoring standards defined to ease the activities of correcting the activity. Once the corrected paper is returned to the student with the graded rubric, the student can “see” where the exact strengths and weaknesses are located in the performance of the activity. This overall increases communication between instructor and student and is a major benefit of using rubrics. There are obstacles to effective use of rubrics. Popham (October 1997) describes how poorly constructed rubrics often focus on task-specific details instead of the actual skill itself, or there is way too many criteria with way too many scoring opportunities. If the rubric is not written effectively, the student will not have a clear understanding of the expectation and the instructor will have difficulty in scoring. This becomes ineffective communications and is a major obstacle to communications between instructor and student.

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usIng rubrIcs In dIstance educatIon Bauer & Anderson (2000) share illustrations of rubrics for online content assessment, expression in formal online postings, online participation in the discussion forum, and assessing e-portfolios. Knowlton (2003) describes using a rubric to evaluate asynchronous discussions. His criteria for the initial message include student communication for mechanics, clarity, addressing specific topics, and critical thinking. The criteria for replies include respectful tone, inspiring further discussion, and developing scope of discussion. The performance levels describe the activity of discussion for his class. He assigns his grading in ranges to give himself some room to show students their “in between” status of performance. Included within his criteria is the opportunity for students to self-evaluate their own contributions and evaluate peers through the use of checklists and self-reflection of the discussion activity.

future trends The use of the rubric is moving into distance education classrooms. As shown in this chapter, the rubric can assist in grading Internet-based activities including the discussion forum. In addition, there is a future trend appearing where rubrics are expanding to someday become an assessment tool to evaluate distance programs or classes by accrediting institutions, the college itself, or peer reviews. In the beginning of this trend, Simonson (1997) discusses the AEIOU approach for program evaluation to distance education. He applies the Accountability, Effectiveness, Impact, Organizational context, and Unanticipated consequences (AEIOU) of this approach to Internet-based programs. He includes criteria and questions that might be asked for each of these areas for distance education. While he does not go as far as creating

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a rubric with performance levels, he does identify methods used to gather data to support the AEIOU criteria including interviews, focus groups, journals, surveys that include narrative information, record data, and direct observations. The trend evolves with Bresciani (2002) describing the rubric that was designed to be used within program evaluation at North Carolina State University. While this is not distance education specific, it describes how the choice was to develop a holistic rubric for program reviews. This is important since many distance education courses are tied closely to the building-based equivalent programs offered by the college or university. In many locations, regional (Middle States Commission on Higher Education, 2003) or state education departments are asking for overall program evaluations of higher education, and there is no differentiation between if the program is offered in a building-based or Internet-based delivery format. Lorenzetti (2004) describes a recent project where four educators collaborated on creating a rubric to assist in peer review for Online classes. The need for the rubric was created when it was realized that traditional methods of building-based class observation/evaluation cannot completely evaluate Online teaching. The rubric identifies 16 criteria areas and a 5 point rating scale that can be used by Internet-based instructors either personally—or for a peer review—and is fully supported by research for the criteria or performance items listed (Ashcraft, McMahon, Lesh, and Tabrizi, 2002).

conclusIon The use of rubrics as assessment tools in distance education can assist the asynchronous, text-based communication between instructor and student. Because rubrics are distributed to students along with the directions for alternative assessments, the student knows what the instructor “wants” for

Rubrics as an Assessment Tool in Distance Education

grading purposes. Students can use the rubric as a guide during the creation of the assignment and as a self-evaluation tool just prior to submission. The instructor uses the rubrics on individual submissions and then can analyze the total number of rubrics to identify if any criteria within the assignment were missed by a majority of students. This analysis can lead to additional instruction (remedial or new), or clarification of the rubric or directions. Rubrics can be used for all types of alternate assessments, including asynchronous discussion activities, as well as for instructional peer, course, and program reviews.

references Andrade, H.G. (2000). Using rubrics to promote thinking and learning. Educational Leadership, 57(5), 13-18. Ashcraft, M., McMahon, J., Lesh, S., & Tabrizi, M. (2002). Peer review for online learning. Retrieved July 14, 2004, from http://www.towson. edu/~mcmahon/peerreview/On-linerubric.pdf Bauer, J.F., & Anderson, R.S. (2000) Evaluating students’ written performance in the online classroom. In R.E. Weiss, D.S. Knowlton, & B.W. Speck (Eds.), Principles of effective teaching in the online classroom. New directions for teaching and learning No. 84 (pp. 65-71). San Francisco CA: Jossey-Bass Publishers. Bresciani, M.J. (2002). Development of a rubric to evaluate academic program assessment plans at North Carolina State University. Assessment Update, 14(6), 14-15. Dodge, B. (2001). Creating a rubric for a given task. Retrieved July 14, 2004, from http://webquest.sdsu. edu/rubrics/rubrics.html Herman, J. L., Aschbacher, P.R., & Winters, L. (1992). A practical guide to alternative assess-

ment. Alexandria, VA: Association for Supervision and Curriculum Development. Knowlton, D.S. (2003). Evaluating college students’ efforts in asynchronous discussion. The Quarterly Review of Distance Education, 4(1), 31-41. Lorenzetti, J.P. (2004, January 15). Faculty peer review: A rubric for the online classroom. Distance Education Report, 8. Marzano, R.J., Pickering, D., & McTighe, J. (1993). Assessing student outcomes: Performance assessment using the dimensions of learning model. Alexandria, Virginia: Association for Supervision and Curriculum Development. Middle States Commission on Higher Education. (2003). Student learning assessment: Options and resources. Philadelphia, PA. Montgomery, K. (2002). Authentic tasks and rubrics: Going beyond traditional assessments in college teaching. College Teaching, 50(1), 4-39 Popham, W.J. (1997). What’s wrong—and what’s right—with rubrics. Educational Leadership, 56(2), 72-75. Roblyer, M.D., & Ekhaml, L. (2000). How interactive are YOUR distance courses? A rubric for assessing interaction in distance learning. Journal of Distance Learning Administration, 3(2) Retrieved July 14, 2004, from http://www. westga.edu/~distance/roblyer32.html Sanders, L.R. (2001). Improving assessment in university classrooms. College Teaching, 49(2), 62-64. Simonson, M.R. (1997). Evaluating teaching and learning at a distance. In T.E. Cyrs (Ed.), Teaching and learning at a distance: What it takes to effectively design, deliver, and evaluate programs: New directions for teaching and learning No 71 (pp. 87-94). San Francisco, CA: Jossey-Bass Publishers.

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Starr, L. (2000). Creating rubrics: Tools you can use. Education World. Retrieved July 14, 2004, from http://www.education-world.com/a_curr/ curr248.shtml Taggart, G.L., Phifer, S.J., Nixon, J.A., & Wood, M. (Eds.) (1998). Rubrics a handbook for construction and use. Lancaster, PA: Technomic Publishing. Teach-nology. (2003). Rubric and rubrics makers. Teach-nology. Retrieved July 14, 2004, from http:// www.teach-nology.com/web_tools/rubrics/

key terms Alternative Assessment: Activities developed by an instructor to assist the student identify the processes and products of learning beyond the “one right answer” approach, and where the scoring or rating criteria are distributed at the same time as the assignment directions.

Criteria: Each goal within the alternative assessment that ties into the instructional objectives of the lesson, unit, or course. Performance Level: The description of the levels of quality attainment within each criterion that are incrementally identified as low, good, better, and best. Rubric: A document that identifies the instructional goals criteria of the activity plus the levels of potential performance; the rubric is distributed with the activity directions so that (1) students can monitor their own progress, process, and product quality and (2) instructors can evaluate against the rubric’s information. Self-Evaluation: An activity where the student compares the rubric to their alternative assessment activity prior to final submission to the instructor; assisting students to evaluate their own work offers opportunities for editing/correcting prior to teacher grading and for self-reflection on the learning process.

This work was previously published in the Encyclopedia of Distance Learning, Vol. 4, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 1583-1588, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.8

Education, the Internet, and the World Wide Web John F. Clayton Waikato Institute of Technology, New Zealand

IntroductIon what is the Internet? The development of the Internet has a relatively brief and well-documented history (Cerf, 2001; Griffiths, 2001; Leiner et al., 2000; Tyson, 2002). The initial concept was first mooted in the early 1960s. American computer specialists visualized the creation of a globally interconnected set of computers through which everyone quickly could access data and programs from any node, or place, in the world. In the early 1970s, a research project initiated by the United States Department of Defense investigated techniques and technologies to interlink packet networks of various kinds. This was called the Internetting project, and the system of connected networks that emerged from the project was known as the Internet. The initial networks created were purpose-built (i.e., they were intended for and largely restricted to closed specialist communities of research scholars). However, other scholars, other government

departments, and the commercial sector realized the system of protocols developed during this research (Transmission Control Protocol [TCP] and Internet Protocol [IP], collectively known as the TCP/IP Protocol Suite) had the potential to revolutionize data and program sharing in all parts of the community. A flurry of activity, beginning with the National Science Foundation (NSF) network NSFNET in 1986, over the last two decades of the 20th century created the Internet as we know it today. In essence, the Internet is a collection of computers joined together with cables and connectors following standard communication protocols.

what is the world wide web? For many involved in education, there appears to be an interchangeability of the terms Internet and World Wide Web (WWW). For example, teachers often will instruct students to “surf the Web,” to use the “dub.dub.dub,” or alternatively, to find information “on the net” with the assump-

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Education, the Internet, and the World Wide Web

tion that there is little, if any, difference among them. However, there are significant differences. As mentioned in the previous section, the Internet is a collection of computers networked together using cables, connectors, and protocols. The connection established could be regarded as physical. Without prior knowledge or detailed instructions, the operators of the connected computers are unaware of the value, nature, or appropriateness of the material stored at the node with which they have connected. The concepts underlying the WWW can be seen to address this problem. As with the Internet, the WWW has a brief but well-documented history (Boutell, 2002; Cailliau, 1995; Griffiths, 2001). Tim Benners-Lee is recognized as the driving force behind the development of the protocols, simplifying the process locating the addresses of networked computers and retrieving specific documents for viewing. It is best to imagine the WWW as a virtual space of electronic information storage. Information contained within the network of sites making up the Internet can be searched for and retrieved by a special protocol known as a Hypertext Transfer Protocol (HTTP). While the WWW has no single, recognizable, central, or physical location, the specific information requested could be located and displayed on users’ connected devices quickly by using HTTP. The development and refinement of HTTP were followed by the design of a system allowing the links (the HTTP code) to be hidden behind plain text, activated by a click with the mouse, and thus, we have the creation and use of Hypertext Markup Language (HTML). In short, HTTP and HTML made the Internet useful to people who were interested solely in the information and data contained on the nodes of the network and were uninterested in computers, connectors, and cables.

background educational Involvement The use and development of the Internet in the 1970s was almost entirely science-led and restricted to a small number of United States government departments and research institutions accessing online documentation. The broader academic community was not introduced to the communicative power of networking until the start of the 1980s with the creation of BITNET, (Because It’s Time Network) and EARN (European Academic and Research Network) (Griffiths, 2001). BITNET and EARN were electronic communication networks among higher education institutes and was based on the power of electronic mail (e-mail). The development of these early networks was boosted by policy decisions of national governments; for example, the British JANET (Joint Academic Network) and the United States NSFNET (National Science Foundation Network) programs that explicitly encouraged the use of the Internet throughout the higher educational system, regardless of discipline (Leiner et al., 2000). By 1987, the number of computer hosts connected to networks had climbed to 28,000, and by 1990, 300,000 computers were attached (Griffiths, 2001). However, the development of the World Wide Web and Hypertext Markup Language, combined with parallel development of browser software applications such as Netscape and Internet Explorer, led to the eventual decline of these e-mail-based communication networks (CREN, 2002). Educational institutions at all levels joined the knowledge age.

future trends The advances in and decreasing costs of computer software and hardware in the 1980s resulted in

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Education, the Internet, and the World Wide Web

increased use of and confidence in computer technologies by teachers and learners. By the mid1990s, a number of educational institutions were fully exploiting the power of the Internet and the World Wide Web. Search engines to locate and retrieve information had been developed, and a mini-publication boom of Web sites occurred (Griffiths, 2001). In the early stages, educational institutions established simple Websites providing potential students with information on staff roles and responsibilities; physical resources and layout of the institution; past, present, and upcoming events; and a range of policy documents. As confidence grew, institutions began to use a range of Web-based applications such as e-mail, file storage, and exams, to make available separate course units or entire and programs to a global market (Bonk et al., 1999). Currently, educational institutions from elementary levels to universities are using the WWW and the Internet to supplement classroom instruction, to give learners the ability to connect to information (instructional and other resources), and to deliver learning experiences (Clayton, 2002; Haynes, 2002; Rata Skudder et al., 2003). In short, the Internet and the WWW altered some approaches to education and changed the way some teachers communicated with students (McGovern & Norton, 2001; Newhouse, 2001). There was and continues to be an explosion of instructional ideas, resources, and courses on the WWW during the past decades as well as new funding opportunities for creating courses with WWW components (Bonk, 2001; Bonk et al., 1999; van der Veen et al., 2000). While some educators regard online education with suspicion and are critical that online learning is based on imitating what happens in the classroom (Bork, 2001), advocates of online, Web-assisted, or Internet learning would argue that combining face-to-face teaching with online resources and communication provides a richer learning context and enables differences in learning styles and preferences to be better accommodated (Aldred & Reid, 2003; Bates, 2000; Dalziel, 2003; Mann,

2000). In the not-too-distant future, the use of compact, handheld, Internet-connected computers will launch the fourth wave of the evolution of educational use of the Internet and the WWW (Savill-Smith & Kent, 2003). It is envisaged that young people with literacy and numeracy problems will be motivated to use the compact power of these evolving technologies in learning (Mitchell & Doherty, 2003). These students will be truly mobile, choosing when, how, and what they will learn.

conclusIon The initial computer-programming-led concept of the Internet first mooted in the early 1960s has expanded to influence all aspects of modern society. The development of the Hypertext Transfer Protocol to identify specific locations and the subsequent development of Hypertext Markup Language to display content have enabled meaningful connections to be made from all corners of the globe. As procedures and protocols were established, search facilities were developed to speed up the discovery of resources. At this stage, educationalists and educational institutions began to use the power of the Internet to enhance educational activities. Although in essence, all we basically are doing is tapping into a bank of computers that act as storage devices, the potential for transformation of educational activity is limitless. Increasingly, students will independently search for resources and seek external expert advice, and student-centered learning will have arrived.

references Aldred, L., & Reid, B. (2003). Adopting an innovative multiple media approach to learning for equity groups: Electronically-mediated learning for off-campus students. In Proceedings of the 20th

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Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education.

ence of the Australasian Society for Computers in Learning in Tertiary Education.

Bates, T. (2000). Distance education in dual mode higher education institutions: Challenges and changes. Retrieved March 15, 2003, from http://bates. cstudies.ubc.ca/

Griffiths, R. T. (2001). History of the Internet, Internet for historians (and just about everyone else). Retrieved June 7, 2002, from http://www.let. leidenuniv.nl/history/ivh/frame_theorie.html

Bonk, C. (2001). Online teaching in an online world. Retrieved from http://PublicationShare. com

Haynes, D. (2002). The social dimensions of online learning: Perceptions, theories and practical responses. Proceedings of the Distance Education Association of New Zealand, Wellington, New Zealand.

Bonk, C., Cummings, J., Hara, N., Fischler, R., & Lee, S. (1999). A ten level Web integration continuum for higher education: New resources, partners, courses, and markets. Retrieved May 1, 2002, from http://php.indiana.edu/~cjbonk/paper/edmdia99. html Bork, A. (2001). What is needed for effective learning on the Internet. Education Technology & Society, 4(3). Retrieved September, 12, 2005, from http://ifets.ieee.org/periodical/vol_3_2001/ bork.pdf Boutell, T. (2002). Introduction to the World Wide Web. Retrieved June 14, 2002, from http://www. w3.org/Overview.html Cailliau, R. (1995). A little history of the World Wide Web. Retrieved June 14, 2002, from http:// www.w3.org/ Cerf, V.G. (2001). A brief history of the Internet and related networks. Retrieved June 4, 2002, from http://www.isoc.org/ Clayton, J. (2002). Using Web-based assessment to engage learners. In Proceedings of the DEANZ: Evolving e-Learning Conference, Wellington, New Zealand. CREN. (2002). CREN history and future. Retrieved June 11, 2002, from http://www.cren. net/ Dalziel, J. (2003). Implementing learning design: The learning activity management system (LAMS). Proceedings of the 20th Annual Confer-

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Leiner, B., et al. (2000). A brief history of the Internet. Retrieved May 20, 2002, from http://www. isoc.org/internet/history/brief.shtml# Origins Mann, B. (2000). Internet provision of enrichment opportunities to school and home. Australian Educational Computing, 15(1), 17-21. McGovern, G., & Norton, R. (2001). Content critical: Gaining competitive advantage through high-quality Web content. London: Financial Times Prentice Hall. Mitchell, A., & Doherty, M. (2003). m-Learning support for disadvantaged young adults: A midstage review. Retrieved August 18, 2004, from http://www.m-learning.org/index.shtml Newhouse, P. (2001). Wireless portable technology unlocks the potential for computers to support learning in primary schools. Australian Educational Computing, 16(2), 6-13. Rata Skudder, N., Angeth, D., & Clayton, J. (2003). All aboard the online express: issues and implications for Pasefica e-learners. Proceedings of the 20th Annual Conference of the Australasian Society for Computers in Learning in Tertiary Education. Savill-Smith, C., & Kent, P. (2003). The use of palmtop computers for learning: A review of the literature. Retrieved August 17, 2004, from http://www.m-learning.org/index.shtml

Education, the Internet, and the World Wide Web

Tyson, J. (2002). How the Internet works. Retrieved May 20, 2002, from http://www.howstuff works.com/ van der Veen, J., de Boer, W., & van de Ven, M. (2000). W3LS: Evaluation framework for World Wide Web learning. Journal of International Forum of Educational Technology & Society, 3(4), 132-138.

key terms HTML: Hypertext Markup Language (HTML) was originally developed for the use of plain text to hide HTTP links. HTTP: Hypertext Transfer Protocol (HTTP) is a protocol allowing the searching and retrieval of information from the Internet. Internet: An internet (note the small i) is any set of networks interconnected with routers forwarding

data. The Internet (with a capital I) is the largest internet in the world. Intranet: A computer network that provides services within an organization. Node: These are the points where devices (computers, servers, or other digital devices) are connected to the Internet and more often called a host. Protocol: A set of formal rules defining how to transmit data. TCP/IP Protocol Suite: The system of protocols developed to network computers and to share information. There are two protocols: the Transmission Control Protocol (TCP) and the Internet Protocol (IP). World Wide Web: A virtual space of electronic information and data storage.

This work was previously published in the Encyclopedia of Human Computer Interaction, edited by C. Ghaoui, pp. 175-178, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.9

Learning Portals as New Academic Spaces Katy Campbell University of Alberta, Canada

IntroductIon

background

Many functional definitions emphasize a portal as an integrated system providing a gateway to organized data (c.f., Batson, 2000; Copeland, 2001; Eisler, 2001; Looney & Lyman, 2000). However, a learning portal may go beyond the information management function to provide important mechanisms for reaching out to new populations of learners and engaging them in new ways to facilitate learning and development. Beyond serving as a gateway and an organizer, a portal can provide access to a broader range of contemporary information and learning resources (experts, teachers, researchers, mentors), encourage enriched interaction with those resources and with other learners anywhere in the world, and support new models of teaching, learning and research. Ultimately, a collaborative, communitybased process of designing and implementing a portal may support institutions in reorienting towards a user-centered learning community.

portals and a transformed learning environment Universities are seeking ways to manage emerging areas of research and discipline specialization, learner profiles, and partnerships with learning providers that challenge the autonomy of the single-source institution. The public has expressed strong interest in alternative methods for delivering, supporting, and facilitating learning — any time, any place, any pace — required in new knowledge-intensive environments and enabled by converging information and communication technologies. Therefore, the decision to implement a campus portal for enhanced learning opportunities must address issues of equity and access, flexibility, innovation, personalization, credibility, quality, transparency, and transferability within the framework of evolving institutional goals and strategies.

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Learning Portals as New Academics Spaces

Both Campbell (2001) and Batson (2000) contend that commercial portals are built on different values and assumptions than those of the academic community, and pursue different goals and purposes. Erhmann (2000) identifies service provision, flexibility and responsiveness of instruction, the enrichment and extension of academic communities, attracting and retaining students and staff, fostering universal, frequent use of computing communications, and sustainability. A learning portal expands on traditional academic space, which has traditionally been defined as physical infrastructure with related resource structures that shapes the nature of the interactions that occur within it (Batson, 2000). This space has an important socialization function: Members of the community know how to speak and act within these spaces, understand power relationships by the way these spaces organize interactions (e.g., rows of desks with a lectern at the front of the room) and, once acculturated, can subvert the purposes of these spaces. The nature of teaching and learning has been entirely defined by a familiar landscape, the physical classroom, where learning events were structured by place and time and format. This landscape has fundamentally changed. Faculty have old maps and must redefine their relationships with learners, with new ways of representing knowledge, with research colleagues, and with external communities such as the corporate world. Learners demand customized learning experiences that are flexible, authentic, and relevant, have no brand-loyalty and expect program mobility. This is a challenge to administrators whose management strategy focuses on internal factors like time-definite program completion (e.g., the 4-year undergraduate degree).

future trends Although institutions have ranged themselves along an academic space continuum from primarily face-to-face to primarily virtual, most have settled on a technology-enhanced, or blended approach to learning and access. Employing alternative forms of instructional and delivery models, this approach includes: synchronous tools and environments such as classroom lectures, audio and videoconferencing, and data conferencing; and asynchronous tools such as computer-mediated conferencing and other communications systems, learning management systems, and print and digital media. Much of the learning content and interactions can be stored as learning objects and extended and reused in digital repositories. This approach fundamentally realigns and redefines institutional infrastructure to be more learner-centric and open in design and support and include extended information services. It also has a significant social effect on the academic community, raising questions about academic freedom, intellectual property rights management, and the nature of knowledge discovery, representation, and stewardship. Learning portals can provide the functionality of consumer systems, and at the same time, support the social, cultural, and political goals of HE. While more or less resisting the culture of the corporation, universities nevertheless have begun to adopt the concept of portals as learning storefronts (Galant, 2000). Yet, in order to respect HE values of knowledge creation and dissemination for the greater social good, these portals must go beyond the functional requirements and gateway view of commercial portals. Gilbert (2000) and Eisler (2000) identify major categories into which a variety of portal features and functions can be organized: gateways to infor-

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mation, points of access for constituent groups, and community/learning hubs. A synthesis of public reports identifies the range of stakeholders that should be involved in this task, and their values and functional requirements. Principles for the new portal-as-learning-environment include: •

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Inclusiveness: the portal design must support diverse communities including learners who are: older professionals, at a distance, challenged, at different life cycles, learning outside of formal structures, and those with alternative languages, cultural, and perceptual needs; both present and virtual faculty; multidisciplinary teams of researchers; local and international academic, business, and political partners, and others. Integration: learning management systems such as Blackboardä and WebCTä have begun to develop and refine enterprise systems that integrate instructional, delivery, and administrative systems. These portals have evolved from a teaching/learning orientation and reflect institutional movement towards a seamless, multi-purpose, integrated learning environment. Learner-centeredness: portal design is based on the interrelated concepts of customization and personalization, reflecting learning environments in which learners can build learning portfolios based on their circumstances, experiences, and current needs. Traditionally, institutional Web sites have been owner-centric. Accessibility: the new economy implies that the intellectual resources of the university should be packaged and made available to a global community. Portals identify, organize, and represent these resources in ways that make them easy to retrieve, use, and reuse (see, for example, MIT’s Open Knowledge Initiative, or OKI). Flexibility: for many reasons, including changes in professional accreditation, a glob-

•

•

•

ally mobile workforce, new and emerging professions, and life events, individuals will search for opportunities to time-shift, placeshift, and construct individual programs from many providers. A well-designed learning portal will be scalable and act as a gateway to these opportunities. Transparency: a learning portal makes the institution’s strategic directions visible to the community. Learners, external research communities, the private sector, and others construct their own “footprint”. They can search for all of the services they need, and deal directly with the systems that facilitate their interactions with the environment. Portals can help the community discover and promulgate best practices. Accountability: as the learning and support environment becomes more transparent, and as learning opportunities become more available and flexible, community members will expect to be able to evaluate the services and resources to which they have access. As rich information hubs, learning portals can make the institution’s quality framework apparent and available for querying. Expanded and blended learning communities: a learning portal manages transparent and reliable communication tools, which increase access to resources and social learning communities. These tools are easily accessible from the portal and can therefore include and support group members from different institutions, organizations, regions, and cultures. These communities broaden and enrich the learning environment and enhance inclusiveness. Looney and Lyman (2000) believe that the value of a learning portal is that “it can be used to engage constituent groups, empower them with access to information resources and communication tools, and ultimately retain them by providing a more encompassing sense of

Learning Portals as New Academics Spaces

•

membership in an academic community” (p.33). Flattened structures: virtual academic spaces do not support status clues to the same extent as traditional spaces. For example, a physical campus contains buildings with classrooms, labs, information resources, and administrative offices. Very often administrative offices are grouped around department chairs and the dean’s office – there is an inner sanctum access to which is constrained by furniture, walls, workstations, and staff.

•

Appointments must be made. Classrooms sometimes have permanently fixed seating arrangements (e.g., tiers) facing a lectern. Resources are under lock and key. There are barriers. These physical constraints disappear with online access. Implications include democratizing interactions within, and external to, the institution. Collaboration: a campus learning portal will fundamentally change the way universities treat its intellectual capital, increasing opportunities for collaborative work on

Figure 1. Resources and services for instructors, students, and the public

• • • • • • •

R esour ces and Ser vices for I nstr uctor s, Students and the Public T ools E xample A School of B usiness develops a portal that includes an array of interactive multi-media tools a large database of digital resources for courses in extended elements of traditional library economics, organizational behavior, accounting and services increasingly rich interlinked libraries of management and information systems. R esources both traditional and electronic resources include case studies (text and video), simulations access to extra-curricular virtual events (video), interactive demonstrations (e.g. graphs in a broadband-enhanced learning object which variables can be changed), exemplars of repository student projects, historical artifacts, etc. Faculty and online advising students can search for and download these uniformity of single campus-wide resources using a custom search engine, and can also interface linking all courses share or ‘‘deposit’’ new resources, extend existing materials with quizzes; commentary, additional activities. T he database (or repository) links directly to other repositories like ME R L OT . Users are invited to review resources, similar to A mazon.com’ s system. T he repository also links to the University’ s library system which is increasing its full-text journal holdings online and is also acquiring digital resources such as archived speeches. Users can customize their portals by example, there are several student-led clubs that hold regular meetings, sponsor guest speakers and which of these clubs to include on their portal so that they receive only those announcements on the homepage. T he School’ s IT department has created a library of templates that faculty may use/customize for their own courses. T he templates include casebased, collaborative projects, role-plays and other methods --- faculty upload text or med templates in categories including ‘‘course objectives’’, ‘‘course readings’’, etc. T he templates can be used with a campus-wide L MS. T he IT team has created a library of graphics, banners, assessment activities, etc.

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Figure 2. Learning environments and tools

• • • • • •

L ear ning E nvir onments and T ools T ools E xample One university is developing a learning portal intelligent agents, such as ‘‘tutors’’ for faculty called the Faculty T oolkit. course space Designed to support faculty professional access to learning support systems development, the portal is based on a dynamic interactive discussion spaces, open content management system and includes to the world tools and resources for faculty interested in an integrated suite of tools for redesigning their courses or learning instructional designers, content activities. T he management system will authors, instructors and learners contain examples of course designs; access to peer mentors and their stories and observations; links to research on teaching and learning in HE ; templates, checklists, guides, and information resources; scheduled conferences, workshops and institutes, both virtual and campus-based; moderated discussion forums; team-based activities; access to online consultations with instructional designers; evaluation tools, and more. Faculties will be able to design their own interfaces to sit on top of the database. For example, the Faculty of E ducation is libraries, and classrooms.

campus, nationally, and internationally. It is critical to involve the owners of this capital in the design of the portal environment. As faculty members, support staff, librarians, learners, administrators, alumni, the public,

and partner institutions engage each other a deeper, transformed understanding of the whole knowledge management enterprise will emerge (Beller & Or, 1999).

Figure 3. Research and administrative support

• • • •

R esear ch and A dministr ative Suppor t T ools E xample One Faculty of A dult and Continuing E ducation publishing tools links to the student information system has implemented a portal for internal and external communities --- including the professional a capacity for individual users to associations with which their programs are customize and organize personal aligned. For example, the A ssociation of resources external to the campus horizontal links among departments on Professional E ngineers can select only those activities, program announcements, course campus and vertical links to national changes etc that relate directly to their professional development needs, and include the link on their own site. When their members logon to the A PE site, they link directly only to provided to online research tools such as qualitative analysis software, style guides, and tutorials on proposal writing. T he Faculty maintains its own student registration system but the portal allows it to tie in to the campus’ administrative system for record-coordination,

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conclusIon The learning portal can be designed to include a wide range of information, communication, and development tools (Alharti, Bourne, Dawant, & Mayadas, 2000; Eisler, 2000; Erhmann, 2000; Gold, 2001; Moore, 2002; Paadre, Heiki, & King, 2000). These tools could be divided into categories such as those included in Figures 1-3.

note This chapter is based on: Campbell, K. & Aucoin, R. (2003). Values-based design of learning portals as new academic spaces. In M. Sheehan & Ali Jafari (Eds.), Designing portals: Opportunities and challenges (pp.148-170). Hershey, PA: Idea Group Publishing.

references Alharti, M., Bourne, J., Dawant, M., & Mayadas, F. (2000, November). Web portals for online learning. Paper presented at the 6th International Conference on ALN. Batson, T. (2000, November). Campus portals and faculty development. Paper presented at Syllabus 2000: New Dimensions in Educational Technology Conference held in Boston, Massachusetts. Beller, M., & Or, E. (1999, October). On the transition from traditional and open university models to a virtual university model. Paper presented at the 5th International Conference on ALN, Maryland. Campbell, J. (2001). The case for creating a scholars’ portal to the Web: A white paper. Portal: Libraries and the Academy, 1(1), 15-21.

computerworld.com/cwi/story/0,1199,NAV47_ STO61399,00.html Eisler, D.L. (2000, September). Campus portals: Supportive mechanisms for university communication, collaboration, and organizational change. Syllabus Magazine, 14(1). Retrieved November 5, 2003 from the World Wide Web at http://www. syllabus.com/syllabusmagazine/sep00_fea.html Erhmann, S. (2000, November). Evaluating campus portals - Key ideas. Syllabus 2000: New Dimensions in Educational Technology Conference, Boston, MASS. Galant, N. (2000, November). The Portal for online objects in learning (POOL): An advanced eLearning solution. Paper presented at TeleLearning NCE 5th Annual Conference, Toronto, ON. Gilbert, S. (2000, August). Portal decisions demand collaboration: can portals support it? The TLT Group. Retrieved November 8, 2003 from the World Wide Web at http://www.tltgroup. org/gilbert/SyllabusCol2.htm Gold, S. (2001). A constructivist approach to online training for online teachers. Journal of Asynchronous Learning Networks, 5(1), 35-57. Looney, M., & Lyman, P. (2000, July/August). Portals in higher education: What are they, and what is their potential? EDUCAUSE Review. Moore, J.C. (2002). Elements of quality: Synthesis of the August 2002 seminar. Needham, MA: The Sloan Consortium. Paadre, H., & King, S. (2000). Electronic community and portals. Holy Cross College. Retrieved November 7, 2003 from the World Wide Web at http://www.mis2.udel.edu/ja-sig/holycross.doc

Copeland, L. (2001, June). Ford launches massive corporate portal. Retrieved November 7, 2003 from the World Wide Web at http://www.

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key terms Accessibility: Refers to problems encountered by Internet users with perceptual and cognitive challenges, physical conditions or other factors such as geographical location, sociocultural, political and economic issues, language, and so forth, which influence their use of the Web. Blended Learning: Defined broadly, blended learning is the integration of classroom faceto-face learning with online or technology-supported learning, including a range of pedagogical approaches and delivery systems. Strategic applications of blended learning have shown achievement of learning gains while tackling other problems faced by our universities, most notably the pressures of increasing class sizes, and limitations in funding, classroom space, and learning support. Inclusiveness: In this context, inclusiveness is a both a value and a design process. Inclusive environments are purposefully designed to address accessibility challenges and to make resources and services available to the broadest (and most diverse) possible audience. An approach based

on inclusiveness is also known as Universal Instructional Design (UID), and User-Centered Design (UCD). Learning Portals: Integrate information, administrative, communication, research, teaching, and learning support systems with global networks of resources and services. Learning portals are typically designed to increase flexibility and accessibility to institutional resources and to encourage interaction and engagement with diverse communities of users. User-Centered Design (UCD): A client or user-centered philosophy in which the individual is at the center of an iterative design process encompassing multiple factors in an interaction between user and information product. UCD considers cognitive, sociocultural, political, and technological factors involved in defining user tasks and goals that drive the design and development of software, Web sites, information systems and processes–anything with which people interact. UCD is concerned with the usefulness, usability, desirability, legibility, learnability, accessibility and meaningfulness of an information product.

This work was previously published in the Encyclopedia of Information Science and Technology, Vol. 3, edited by M. KhosrowPour, pp. 1815-1819, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.10

Learning Systems Engineering Valentina Plekhanova University of Sunderland, UK

background Traditionally multi-agent learning is considered as the intersection of two subfields of artificial intelligence: multi-agent systems and machine learning. Conventional machine learning involves a single agent that is trying to maximise some utility function without any awareness of existence of other agents in the environment (Mitchell, 1997). Meanwhile, multi-agent systems consider mechanisms for the interaction of autonomous agents. Learning system is defined as a system where an agent learns to interact with other agents (e.g., Clouse, 1996; Crites & Barto, 1998; Parsons, Wooldridge & Amgoud, 2003). There are two problems that agents need to overcome in order to interact with each other to reach their individual or shared goals: since agents can be available/unavailable (i.e., they might appear and/or disappear at any time), they must be able to find each other, and they must be able to interact (Jennings, Sycara & Wooldridge, 1998). Contemporary approaches to the modelling of learning systems in a multi-agent setting do not analyse nature of learning/cognitive tasks and quality of agents’ resources that have impact

on the formation of multi-agent system and its learning performance. It is recognised that in most cognitively driven tasks, consideration of agents’ resource quality and their management may provide considerable improvement of performance process. However, most existing process models and conventional resource management approaches do not consider cognitive processes and agents’ resource quality (e.g., Norman et al., 2003). Instead they overemphasise the technical components, resource existence/availability problems. For this reason, their practical utilisation is restricted to those applications where agents’ resources are not a critical variable. Formal representation and incorporation of cognitive processes in modelling frameworks is seen as very challenging for systems engineering research. Therefore, future work in engineering the learning processes in cognitive system is considered with an emphasis on cognitive processes and knowledge/skills of cognitive agents as a resource in performance processes. There are many issues that need new and further research in engineering cognitive processes in learning system. New/novel directions in the fields of systems engineering,

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Learning Systems Engineering

machine learning, knowledge engineering, and mathematical theories should be outlined to lead to the development of formal methods for the modelling and engineering of learning systems. This article describes a framework for formalisation and engineering the cognitive processes, which is based on applications of computational methods. The proposed work studies cognitive processes, and considers a cognitive system as a multi-agents system. This project brings together work in systems engineering, knowledge engineering and machine learning for modelling cognitive systems and cognitive processes. A synthesis of formal methods and heuristic approaches to engineering tasks is used for the evaluation, comparison, analysis, evolution and improvement of cognitive processes. In order to define learning processes, cognitive processes are engineered via a study of knowledge capabilities of cognitive systems. We are not interested in chaotic activities and interactions between cognitive agents (since cognitive tasks require self-managing activities/work), nor interested in detailed tasks descriptions, detailed steps of tasks performance and internal pathways of thoughts. Rather, we are interested in how avail-

able knowledge/skills of cognitive agents satisfy required knowledge/skills for the performance of the cognitive tasks. The proposed research addresses the problem of cognitive system formation with respect to the given cognitive tasks and considers the cognitive agent’s capabilities and compatibilities factors as critical variables, because these factors have an impact on the formation of cognitive systems, the quality of performance processes and applications of different learning methods. It is recognised that different initial knowledge capabilities of the cognitive system define different performance and require different hybrid learning methods. This work studies how cognitive agents utilise their knowledge for learning the cognitive tasks. Learning methods lead the cognitive agent to the solution of cognitive tasks. The proposed research considers a learning method as a guide to the successful performance. That is, initial knowledge capabilities of cognitive agents are correlated with learning methods that define cognitive processes. An analysis of impact of different cognitive processes on the performance of cognitive agents is provided. This work ensures support for a solution to resource-based problems in knowledge integra-

Figure 1. A scenario for engineering the cognitive processes

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Modelling learning tasks

If new tasks and/or requirements are identified, repeat the process

Measurement and analysis of the agent’s knowledge capabilities and compatibilities with respect to the tasks

Measurement of results of the learning processes with respect to the required artefact

Application of an integration model to form a cognitive system which consists of knowledge-interdependent agents

Scheduling/allocation of agents and machine learning methods to the specific tasks

Matching the learning tasks, capable agents and learning methods that can be used for the learning of cognitive tasks

Identification of critical areas for improvement of the learning processes

Learning Systems Engineering

The individual measurable objectives are:

tion and scheduling of cognitive processes to form a capable cognitive system for learning the required tasks.

•

aIms and objectIves

•

The aims of the project are to develop a formal method for the modelling and engineering of cognitive processes. Capability and compatibility factors have an impact on the formation of cognitive systems, the performance processes and define different learning methods. Therefore this work studies cognitive processes and knowledge capabilities of cognitive systems to ensure the required level of the learning and performance of the cognitive systems. In order to support the formation of a cognitive system that will be capable of learning the required tasks within the given constrains, this work addresses problems of the knowledge integration and scheduling for cognitive system modelling, taking into account critical capability and compatibility factors. Study of learning conditions in cognitive systems defines an important task of the proposed project.

•

• •

•

Evaluation of knowledge integration and scheduling approaches in cognitive systems. Evaluation of existing machine learning approaches in cognitive systems. Determination of the impact of capability and compatibility factors on the formation of cognitive systems. Development of knowledge integration metrics. Development of knowledge integration models for the formation of the cognitive systems. Development of scheduling models for learning of cognitive systems.

methodology and justIfIcatIon In order to identify the best learning processes we analyse the cognitive processes. A scenario for engineering the cognitive processes is based on the following steps (Figure 1).

Table 1. A comparison of capability and compatibility problems Technical Systems In technical systems the internal characteristics of technical elements are described in specifications, standards and formal documents (i.e., are known a priori) from which it is not difficult to conclude whether combinations of elements are capable and compatible or not and whether they can be used for technical system design, development and construction. Each capability and compatibility factor can be represented by one characteristic.

Soft Systems There are a number of real-world examples when an object factor cannot be described by just one characteristic. For example, systems such as human resources, software, information systems, and cognitive agents, where the internal multifaceted properties can be changed with time, and capability and compatibility factors cannot be defined by one characteristic alone, and cannot be explicitly measured. These systems are termed soft systems. At the present time there are problems in the formal definition of specifications/standards and metrics that allow one to determine the capability and compatibility of such complex systems. For this reason, heuristic approaches are used for soft complex system modelling.

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The methodology of the proposed project is based on the following new theoretical basis (Plekhanova, 2003). •

Profile theory and machine learning: For formal modelling of complex systems we utilise the profile theory (Plekhanova, 1999a). A profile is considered as a method for describing and registering multifaceted properties of objects. There are important practical applications of the profile theory (Plekhanova, 2000a, 2000b). For instance, internal properties of the system elements such as capability and compatibility factors are critical variables in modelling, design, integration, development and management of most modern complex systems and their structure. Table 1 provides a comparison of capability and compatibility problems of technical and soft systems.

Profile theory is used for formal modelling of cognitive agents/systems since existing mathematical theories are limited. In particular, con-

temporary mathematical theories describe objects, where each internal factor is represented by one meaningful piece (e.g., set theory - an element) or two pieces of meaningful information (e.g., fuzzy set theory - an element and a membership function). Knowledge factors are considered as basic internal factors in the modelling of cognitive agents, since agents must have particular knowledge capabilities to perform and learn their tasks. In a description of the knowledge of cognitive agents we identify the importance/weight of the factor for the performance of the task; time or factor existence/non-existence; and other specific internal multifaceted properties, for example the property (level, grade, degree) of the factor. In particular, knowledge of the cognitive agent is described by a set of knowledge factors; each factor is defined by multiple characteristics. A set of such factors forms a knowledge profile (Plekhanova, 1999a). Each factor is represented by qualitative and quantitative information. Quantitative description of the ith knowledge factor is defined by an indicator characteristic,

Figure 2. Definition of the profile A profile b is defined as a set of factors b1 , b2 ,..., bn : b = { bi , i = 1, n }, where the ith factor

bi is represented by a pair bi = ( i , ei ) with • •

n - a number of factors

•

ei - the 3-tuple of the ith factor as the Cartesian product: ei = < i , vi , wi >, where

i

o

o o

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- an identification of the ith factor, that is, a name or label or type of the ith factor

i

- indicator characteristic, which indicates the factor presence in the description of

a cognitive agent, the existence of certain conditions; for example, i may represent a binary c ase; a n umber of t imes o f factor u tilisation; or m ay b e defined as a t ime characteristic i = i (t )

vi - property of the ith factor: vi ≥ 0 ; vi can be defined as a function of time vi = vi (t ) wi - w eight of a f actor which defines either t he f actor importance o r the factor priority: wi ≥ 0 ; wi can be also considered as a function of time wi = wi (t ) .

Learning Systems Engineering

property, and weight. In a simple way, a profile can be defined as follows (see Figure 2): The profile theory is used for formalisation of cognitive systems and cognitive processes, and for the identification of critical areas in learning performance where improvement should be taken. In particular, engineering the cognitive processes is considered to provide improvement of learning process by means of integrating adaptive machine learning into the profile theory. In order to model cognitive processes the profile theory is combined with machine learning methods, which are applied to the initial available knowledge capabilities of the cognitive system to define learning methods. (It is expected that different initial knowledge capabilities of the cognitive system require different hybrid learning methods.) Machine learning methods are used for formalisation and modelling of learning processes via applications of the profiles. It allows consideration of dynamics in learning processes (i.e., modelling of the ith profile factor = in the profile ). We should analyse existing machine learning methods, match them to learning tasks with relevance to available knowledge capabilities of cognitive agents and consider cognitive processes. A profile is considered as a model for the description of cognitive processes. That is, a new machine learning method will be developed and incorporated into an engineering framework for cognitive processes. This research considers knowledge factors as critical variables in learning processes and addresses problems in the formation of a cognitive system that can be capable of learning. In particular, a cognitive system is defined by knowledge-interrelated agents, their flexible cognitive structure and cognitive processes. A teacher is defined as a learning oracle. Soft factors may be defined as a “noise” in data modelling for the training sets in machine learning. This work addresses the problems of knowledge integration of the cognitive system in order to provide a better learning performance. A

challenge for learning is to ensure the existence of a desired level of performance of a cognitive system. There is a need to make a formal analysis of the available knowledge of cognitive agents in order to ensure the learning of the tasks at a desired performance level while utilising the available knowledge capabilities effectively and efficiently. This research deals with the problem of agent allocation in a cognitive system. This problem addresses not only task scheduling as in traditional approaches but also scheduling machine learning methods and knowledge of cognitive agents. The proposed project will develop a new scheduling approach where the agent allocation problem has specific emphasis on the following aspects: cognitive agents are allocated to tasks according to their multiple knowledge capabilities; the agent’s knowledge capabilities must satisfy the particular combination of knowledge required for a task; agents of the cognitive systems should be compatible with each other (Plekhanova, 1999b); and learning methods are relevant to the available knowledge capabilities of the cognitive agents and system. The consideration of all these aspects defines a problem of knowledge integration in cognitive systems. This work will use formal methods for an integration of cognitive capabilities and compatibilities, and for an analysis of how system capabilities satisfy the learning of the tasks. Capability and compatibility factors have considerable impact on the process of system integration. An integration model encompasses integration criteria, priorities of the knowledge profiles and knowledge integration goals. Knowledge integration goals are the improvement of available knowledge or generation of new/novel knowledge for better learning performance. This work addresses problems of effectiveness of the learning processes, their convergence (Vapnik, 1998), stability and accuracy. Therefore, the adventure in this research is that cognitive processes will be incorporated

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into multi-agent system development by a synthesis of systems engineering with knowledge engineering and machine learning methods. The combination of machine learning methods with profile theory will provide a more flexible adaptive framework for cognitive tasks performance. That is, the proposed method for the modelling and engineering of cognitive systems and cognitive processes can be used in systems engineering and machine learning for a formalisation of cognitive processes, cognitive systems, and capability and compatibility aspects.

•

novelty The proposed project is particularly novel in its approach to learning processes that incorporate a synthesis of systems engineering, knowledge engineering and machine learning methods. There are no formal methods for knowledge integration and scheduling for learning of cognitive systems where capability and compatibility factors are critical variables. Existing machine learning approaches do not address scheduling problems in learning methods. We will develop a new scheduling approach where we consider scheduling machine learning methods and knowledge of cognitive agents versus task scheduling in traditional approaches. New machine learning methods will be developed and incorporated into an engineering framework for cognitive processes. Moreover, the proposed project brings together work in cognitive systems, systems engineering, knowledge engineering and machine learning for the modelling of cognitive processes. The proposed project is timely because of the availability of new formal methods for engineering cognitive systems. The work is highly topical at present as demonstrated by a large interest in academia and great needs of industry, in particular, in:

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Software/systems engineering: Project resource capability and compatibility aspects have become the focus of performance process improvement. However, most contemporary approaches to the formation of project resources (Norman et al., 2003) do not examine their capability and compatibility factors. There is a need to develop evaluation techniques for people’s capability, resource capability and compatibility in order to provide support for effective solutions to resource integration management in cognitive systems (Plekhanova, 2002). In particular, methods are of particular merit that incorporate a comparison of cognitive processes, resource capabilities and compatibilities. Scheduling: Contemporary approaches to resource scheduling are based on the detailed description of tasks assuming that a resource pool is given and defined by a manager and resources are capable of performing any project task. Existing resource scheduling methods address the issues of resource availability and utilisation, and are not concerned with the capability and compatibility of project resources. Furthermore, in traditional scheduling approaches, the objectives for the allocation of limited resources are to determine the allocation of resources that maximise total benefits subject to the limited resource availability. Contemporary approaches to resource allocation are founded on the assumption that different tasks require equal capability resources, and only one skill is involved. Hence, they cannot be successfully used for software projects where different software tasks require changing different sets of multiple knowledge and skill capabilities in an overall system (Plekhanova, 1998).

Learning Systems Engineering

•

•

Software tools for resource scheduling: There are many scheduling tools that provide different approaches: event-oriented (PERT), activity-oriented (CPM), actionsoriented (TASKey PERSONAL), or offer a wide variety of scheduling options (SAP). Nevertheless, there are no tools that support an analysis of resource capabilities/compatibilities and their impact on project scheduling (Plekhanova, 2000c). Most existing tools (Microsoft Project, SAP, Up and Running) have facilities for entering new resources, but do not deal with an analysis of cognitive processes, and resource quality based on which resources can be added to the resource pool. Therefore, the existing scheduling tools cannot be effectively used for management of processes where resources are a critical variable. Theory/tools in machine learning: Existing machine learning techniques (e.g., Boosting (Schapire, 1999), Lazy Learning (Aha, 1997), Neural Nets, Decision Tree Learning (Quinlan, 1990; Utgoff, 1989), Support Vector Machine (Vapnik, 1998), Reinforcement Learning (Sutton & Barto, 1998)), and contemporary machine learning tools (e.g., WEKA, AutoClass, mySVM) have not yet been examined in terms of agents’ capability/compatibility and scheduling problems.

There is a direct relationship between the representation and the learning mechanisms. In many cases the underlying representations in machine learning have been of limited structure (e.g., vectors, trees, networks). A hybrid integration of various machine learning mechanisms for engineering of structured objects is novel and will be examined in this project in the context of the profile theory.

benefIcIarIes •

•

Engineering the complex systems: Research in engineering of complex systems will provide insight into new methods and approaches to learning in cognitive systems. Research in machine learning will deliver adaptiveness to knowledge integration and scheduling of learning methods. Scientists in cognitive systems research will receive a formal method for modelling of cognitive processes. By developing integration metrics using the profile theory we can provide analysis, development, integration, modelling and management of complex systems and their elements where weight, time and other internal multifaceted properties are critical variables. Further development of the profile theory will establish a new branch in mathematics and extend its applications. Industry: New evaluation techniques could provide support for a solution to the resourcebased problems in cognitive processes in software and IT projects such as team formation and integration in connection with process tasks.

The application of a new approach could provide learning organisations with: • •

•

superior management of resource capabilities and compatibilities; streamlining of process development through better management of project resources and tasks; increased opportunities for organisations to implement process improvement based on the constructive criticism derived from self analysis.

It is apparent that there is a worldwide interest in the application of this research. Since most

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modern processes are cognitively driven our method can be used for the formal modelling of cognitive systems. It is important for the future competitiveness of the software and IT industry to employ a scientific (vs. heuristic) approach to the engineering of cognitive processes. •

Technology: The profile-based approach assures a virtual prototyping of system development within different environment settings. An important application of this approach is that it gives the means of providing systemic methods of study, analysis, prediction, improvement, control and management of a system development. Moreover, this technology demonstrates a modelling flexibility that permits one to represent a fine-granularity of system components as well as to generate different system models of a wide diversity of system development processes. Thus, any traditional system model becomes a special case of the capability- and compatibility-based modelling framework.

Formal modelling of the capability and compatibility of cognitive systems ensures the automation in system modelling. It leads to development of new technologies in system modelling. Some of the enhancements that we intend to offer through this method are to provide support for development and engineering of new knowledge capabilities of cognitive systems, that is, innovative technologies.

references Aha, D. (Ed.). (1997). Lazy learning. Dordrecht: Kluwer Academic Publisher.

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Clouse, J.A. (1996). Learning from an automated training agent. In G. Weiß & S. Sen (Eds.), Adaptation and learning in multiagent systems. Berlin: Springer Verlag. Crites, R., & Barto, A. (1998). Elevator group control using multiple reinforcement learning agents. Machine Learning, 33, 235-262. Jennings, N.R., Sycara, K., & Wooldridge, M.A. (1998). Roadmap of agent research and development. In N.R. Jennings, K. Sycara & M. Georgeff (Eds.), Autonomous Agents and Multi-Agent Systems Journal, 1(1), 7-38.Boston: Kluwer Academic Publishers. Mitchell, T.M. (1997). Machine learning. Boston: WCB/McGraw-Hill. Norman, T.J., Preece, A., Chalmers, S., Jennings, N.R., Luck, M., Dang, V.D., Nguyen, T. D., Deora, V., Shao, J., Gray, A., & Fiddian, N. (2003). CONOISE: Agent-based formation of virtual organisations. Proceedings of the 23rd SGAI International Conference on Innovative Techniques and Applications of AI, Cambridge, UK (pp. 353-366). Parsons, S., Wooldridge, M., & Amgoud L. (2003). Properties and complexity of some formal interagent dialogues. Journal of Logic & Computation, 13(3), 347-376. Plekhanova, V. (1998). On project management scheduling where human resource is a critical variable. Proceedings of the Sixth European Workshop on Software Process Technology, Lecture Notes in Computer Science Series (pp. 116-121). London: Springer-Verlag. Plekhanova, V. (1999a). A capability- and compatibility-based approach to software process modelling. Unpublished doctoral thesis. Macquarie University, Sydney, Australia and the Institute of Information Technologies and Applied Mathematics, Russian Academy of Sciences.

Learning Systems Engineering

Plekhanova, V. (1999b). Capability and compatibility measurement in software process improvement. Proceedings of the 2nd European Software Measurement Conference, Amsterdam, Netherlands, Technological Institute Publications, Antwerp, Belgium (pp. 179-188). Plekhanova, V. (2000a). Profile theory and its applications. International Conference on Information Society on the 21st Century: Emerging Technologies and New Challenges, The University of Aizu, Fukushima, Japan (pp. 237-240). Plekhanova, V. (2000b). Applications of the profile theory to software engineering and knowledge engineering. Proceedings of the Twelfth International Conference on Software Engineering and Knowledge Engineering, Chicago, USA (pp. 133-141). Plekhanova, V. (2000c). On the compatibility of contemporary project management tools with software project management. Proceedings of the 4th World Multiconference on Systemics, Cybernetics, Orlando, Florida, USA (vol. I, pp. 71-76). Plekhanova, V. (2002). Concurrent engineering: Cognitive systems and knowledge integration. Proceedings of the 9th European Concurrent Engineering Conference, Modena, Italy (pp. 26-31). A Publication of SCS Europe (Society for Computer Simulation). Plekhanova, V. (2003). Learning systems and their engineering: A project proposal. In J. Peckham & S. Lloy (Eds.), Practicing software engineering in the 21st century (pp. 164-177). Hershey, PA: Idea Group Publishing. Quinlan, J.R. (1990). Probabilistic decision trees. In In Y. Kodratoff & R.S. Michalski (Eds.), Machine learning: An artificial intelligence approach (vol. 3, pp. 140-152). California: Morgan Kaufmann Publishers, Inc.

Schapire, R. (1999). Theoretical views of boosting and applications. In O. Watanabe & T. Yokomori (Eds.), Proceedings of the Tenth International Conference on Algorithmic Learning Theory (pp. 13-25). Sutton, R.S., & Barto, A.G. (1998). Reinforcement learning: An introduction. Cambridge: MIT Press. Utgoff, P.E. (1989). Incremental induction of decision trees. Machine Learning, 4, 161-186. Vapnik, V.N. (1998). Statistical learning theory. Chichester: Wiley.

key terms Agent: A complex system constituting elements that are individual performers, which can be described by their interrelationships, knowledge/ skill, performance and constraints factors. Agent’s Compatibility: A capability of agent to work with other agents without adaptation, adjustment and modification. Cognitive Process: • The performance of some composite cognitive activity. • A set of connected series of cognitive activities intended to reach a goal. Cognitive activities can be considered as a function of their embodied experience. Cognitive System: A complex system that learns and develops knowledge. It can be a human, a group, an organization, an agent, a computer, or some combination. It can provide computational representations of human cognitive processes to augment the cognitive capacities of human agents.

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Complex System: A collection of interrelated elements organised to accomplish a specific function or a set of functions. Complexity can be considered in terms of a number of elements and/or complexity of relationships.

Machine Learning: The ability of a machine to improve its performance based on previous results. Multi-Agent System: A set of interrelated agents that work together to perform tasks.

This work was previously published in the Encyclopedia of Information Science and Technology, Vol.3, edited by M. KhosrowPour, pp. 1820-1826, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.11

Storytelling-Based Edutainment Applications Anja Hoffmann ZGDV e.V. - Computer Graphics Center, Darmstadt, Germany Stefan Göbel ZGDV e.V. - Computer Graphics Center, Darmstadt, Germany Oliver Schneider ZGDV e.V. - Computer Graphics Center, Darmstadt, Germany Ido Iurgel ZGDV e.V. - Computer Graphics Center, Darmstadt, Germany

abstract Within this chapter, the authors—all members of the Digital Storytelling group at ZGDV Darmstadt e.V.—provide an overview of the potential of storytelling-based edutainment applications and approaches for narrative learning applications. This covers not only online applications, but also off-line edutainment components, as well as hybrid scenarios combining both types. The chapter is structured into five parts. At the beginning, a global scenario of edutainment applications for museums is introduced and key issues concerning the establishment of edutainment applications and the level of interactivity for online applications

are highlighted. These open and relevant issues are discussed within a technology-oriented, stateof-the art analysis concentrating on the authoring process, storytelling aspects, dramaturgy and learning issues. Based on this brief STAR analysis, storytelling methods and concepts, as well as a technical platform for the establishment of storytelling-based edutainment applications, are described. The strengths and weaknesses of these approaches are discussed within the context of the edutainment projects, art-E-fact and DinoHunter Senckenberg. Finally, the major results are summarized in a short conclusion and further research and application-driven trends (context: museums) are pointed out.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Storytelling-Based Edutainment Applications

global scenarIo of edutaInment applIcatIons for museums The multifaceted scenario of edutainment applications for museums includes key players and user groups, as well as major components and aspects, for both online applications within the museums and Web-based scenarios using the museum (Web site) as document archive or knowledge pool, enabling teachers to enhance lessons through multimedia content provided by the museum’s archives and collections (see Figure 1). Some general questions address various needs and aspects of the different user groups involved in these museum scenarios:

• • • • • • •

How to enter content into the exhibition and make it available via interactive artefacts? How to visualize (scientific) background information? How to build valuable exhibitions with learning effects? Which learning methods are appropriate? How is learning interconnected with Gaming/Fun? How much technology is appropriate? What are the benefits of combining museums with the Web?

• • •

How to measure success of artefacts & exhibitions? How to finance artefacts and exhibitions? Which business models are appropriate?

Whereas the two first questions concern the authoring process and its outcome (as input) for run-time systems, such as interactive artefacts or terminal applications, the subsequent questions are more general in nature, encompassing learning and methodological-didactic aspects, as well as marketing- and business-oriented issues. Within this chapter, we concentrate on the more technical aspects behind these questions and analyse the benefits of storytelling-based approaches in order to answer these questions and to make edutainment applications and museum exhibitions more valuable in a broader sense. Referring to online edutainment applications and “Web sites with learning components” from the technical point of view, the most interesting question concerns the level of interactivity. Göbel & Sauer (2003) provided a short overview of those levels in their workshop, Combine the Exhibition and Your Web Visitors. Integrated Concepts of Interactive Digital Media for Museums, presented at Museums and the Web 2003 in Charlotte, NC:

Figure 1. Multifaceted scenario of edutainment applications for museums

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Figure 2. Levels of interactivity within edutainment applications for museums

Whereas plain Web sites providing text, images or further media, such as audio and video clips, are very popular (low-cost production), enhanced technological methods and concepts increase the level of interactivity for users and, subsequently, the level of experience. Examples of this include interactive tours or virtual museums providing (more or less detailed) 3-D models of the real museum, enabling users to wander around and interact with elements, objects, and artefacts. Peculiarities of these scenarios are guided tours, such as the Interactive Tour provided by Deutsche Bank in Germany. Hereby, an isometric chat room is used to improve interactivity and overall experience of the users. Some virtual museums provide interaction metaphors and experience is focused on interactive media—others consciously avoid interactivity with objects/artefacts and interaction is limited to navigation metaphors. Virtual exhibitions provide Web-based artefacts and users have a direct experience through the Web site—similar to the experience with “real/physical” artefacts within museums. Finally, Markus Bader’s “Lux” provides an example of a hybrid system combining (visitors of) the virtual (Web) with the real (museum), enabling a bidirectional experience. (Bader, 2004) In summary, an appropriate slogan might be “the more interactivity, the more experience, the better the learning effect.” Apart from the inter-

activity aspect, another current trend concerns stories and storytelling issues as new media for both knowledge transmission and interactive experience and the learning environment. An example of this trend is provided by Educational Web Adventures (Eduweb, 2004): “Eduweb’s mission is to create exciting and effective learning experiences that hit the sweet spot where learning theory, Web technology, and fun meet.” Underlying methods and concepts for such storytelling-based edutainment applications and learning environments are discussed in other sections of this chapter; other aspects, such as Museums as Information Archives and Knowledge Pools for teachers, pupils and interested people (Museum of Tolerance, 2004) or Organizing Data Collections and Making Them Accessible through the Web (Vernon, 2004), are not the focus of this chapter.

current research The following paragraph gives an overview of current research in interactive storytelling. Many disciplines affect this field and it is largely influenced by traditional forms of storytelling, such as literature and movies. For the creation of these complex applications, it is helpful to look at methods and structures coming from, for example, script writing. This state-of-the art survey concentrates on

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•

general aspects of storytelling and their application for interactive digital storytelling, the authoring process, dramaturgy in museums, and learning issues.

•

From our point of view, the most challenging issues encompass the provision of “appropriate” authoring environments for the different user groups and the integration or harmonization of interactive storytelling with learning issues.

•

• • •

Interactive digital storytelling Although stories are widely used in game-based learning applications (for example, Chemicus, Physicus, Klett, 2004), there is still a lack of appropriate integration of story and instruction: “The instructional design was generally concentrated in an isolated instructional space that existed independently of the story arc” (Noah, 2004). The result is that the learning-supportive characteristics of stories are limited because of the interruption of immersion and engagement. To avoid this limitation, our approach aims at a full symbiosis of learning and story content. Possible definitions for story models as the basis for story instances and story development are:

Figure 3. Suspense curve based on story models

on

nt ueme

cti

a ing

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Exposition Time

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Deno

Tension level

Climax

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Definition: “A Component, which integrates Structure, Content, Context and Development” (Mellon & Webb, 1997); Story Models represent narrations in an abstract way to underline the structure of the story; Story Models represent frameworks/templates for story instances.

Most story models are finally based on the simple dramaturgic arc model of Aristotle for telling linear stories: “Exposition,” “Rising Action to Climax,” and “Denouement.” Other examples of widespread story models are provided by Syd Field (1988), who extended the Aristotle Model with regard to its usage for film scripts – hereby, script pages (= film minutes) are used for temporal structuring. The difference between Hollywood films and European film productions in terms of the usage of story models for films is very interesting. To form your own opinion, please compare the Hollywood film “City of Angels,” directed by Brad Silberling (1998), and the European film “Wings of Desire,” directed by Wim Wenders (1987). Tobias (1999) provides 20 master plots; the Russian formalist Vladimir Propp (1998) analysed hundreds of Russian fairy tales and extracted 15 morphological functions/components appearing in all these stories. Further, Propp defined char-

Storytelling-Based Edutainment Applications

acters (Dramatis Personae) representing rules within the stories, for example, an enemy, a hero, a magic agent (helper) or a princess (prize/award). Our integrated storytelling concepts and first reference examples, such as GEIST, developed at ZGDV Darmstadt, are primarily based on Propp’s story model and morphological functions. The application domains for Interactive Storytelling projects range from pure entertainment scenarios (e.g., Façade; OZ ; Mateas, 1997; Mateas & Stern, 2002) to marketing applications (e.g., interactive kiosk systems) or systems with therapeutic purposes (e.g., Carmen’s Bright IDEAS, Marsella, 2003). All of the above-mentioned projects have one question in common: How can the narrative structure be combined with interaction? User interaction means an interruption of an ongoing story flow. The challenge is to design the story somewhere between emergent and predefined. One of the major results of our comprehensive research in the area of Interactive Storytelling is the realization that the characteristics of stories foster the design of engaging and motivating learning environments for several different reasons: 1.

Cultural tradition: Stories are fundamental to culture and human understanding. They have familiar structures, which are recognizable and can easily be understood. In human tradition, stories were a means for information transmission and knowledge acquisition, for example, within families and cultural communities. Today, kids are growing up with fairy tales (and moral education), learning words with story books and learning about several topics ranging from history to biology through TV shows, such as the famous French series “Il était une fois...” ( “Once upon a time…”) (1979). Unfortunately, as a means for the education of adults, storytelling is being widely lost.

Springer, Kajder, and Borst Brazas (2004) summarize the pedagogical dimensions of storytelling as follows: Stories are: a.

b.

c.

d. e.

f.

2.

3.

Humanistic: A culturally rich and venerated practice, global in relevance; encourages people to value their experiences, both imaginary and real, and it puts us in touch with ourselves and others. Stories communicate values. Cross-disciplinary: Stories apply to many K-12 subjects, including language arts, history, social studies, and humanities. Cross-cultural: Narrative structures cut across cultural and geographic spaces and unite oral, written, and technological literacies. Multi-sensory, multi-modal: They have visual, auditory, kinaesthetic properties. Constructivist: Storytelling is user-centred (learner); tales are created out of an individual’s knowledge and experience. Learning-directed: “We learn in narrative structures and think in terms of stories.” Emotion and immersion: Another fact is that stories are structured in a suspenseful way and foster emotional engagement. Experiencing a good story (e.g., within films or novels) can cause total immersion in the imaginary world for the recipient, forgetting time and space. The research results in the area of Affective Computing show the considerable effects of emotional user interfaces (Picard, 1997). Studies in neuronal sciences point out the importance of emotional engagement for learning efforts and motivation (Spitzer, 2002). Support of basic functionalities: We can find essential functionalities for learning environments, such as focusing the learner’s

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4.

attention, provision of information and feedback about the learner’s efforts (Gagne, Briggs, & Wagner, 1992). In addition, stories are not limited to certain topics. That means that any area of interest can be told in a narrative way. Furthermore, virtual worlds promote a deeper and active understanding. Core functions of cognition: Indeed, according to R. Shank (1995), stories constitute nothing less than the main building block of intelligence, memory, creativity, learning, and cognition in general. Educating with stories employs a most appropriate learning method, because it respects the way the mind truly works. According to Shank, we adapt to new situations and solve problems by recurring to already available stories, rearranging and recombining them in an attempt to cope with new challenges (“Case Based Reasoning”).

These statements totally cover current trends within the “Museums and Web” community: Everybody talks about “stories” and “storytell-

Figure 4. Authoring process

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ing,” but, as the means of providing a background story about history, the biography of an author or circumstances of an artist creating some piece of art, without taking into account underlying storytelling concepts (e.g., story models) and theory. This fact motivates our daily work in developing methods and concepts for a storytelling platform as a basis for the wide range of edutainment applications based on storytelling fundamentals, taking into account the different needs of various people involved with the authoring process and global scenario of storytelling-based edutainment applications – with this paper focusing on edutainment applications for museums.

authoring process and authoring environment Authoring of interactive stories is an iterative process, conducted by an interdisciplinary team consisting of designers, technicians, content providers and other participating disciplines. Figure 4 describes the multi-step authoring process with the three major phases brainstorming, preparation and fine-tuning.

Storytelling-Based Edutainment Applications

All the engines for interactive storytelling are worthless without content. Therefore, content has to be created and be put into the interactive storytelling environment. There are lots of authoring environments for interactive presentation available, such as Macromedia Director and Flash or Blender (Macromedia Director MX, 2004; Flash MX, 2004; Blender 2004), but they do not provide any help in structuring a story or suspense-rich storytelling. For screenplay scripts the authoring software Dramatica (Dramatica, 2004) can be very helpful, but it does not offer any possibility to write an interactive story. One of the main problems is that most of the software applications—including computer games - are only action-driven and most of the current stories are without interaction (e.g., films and books). If we just look back a few years, we can see that interactive storytelling had once been very common. Stories were relayed to the recipients by narrators. Because this had been a life process, the recipients could interact with the storyteller by asking questions or just being interested (or not). Today, parents often tell their children fairy tales before they sleep in a similar manner. Before any narrator can tell a story, he needs to know the story. And because of the possible interactions, he needs to know more about the story and its world than he can narrate on his own. This is the main concept of our authoring environment for interactive storytelling. As mentioned above, there are three groups: The author, the narrator and the recipient. The author creates the story and explains it to the narrator. The narrator tells the story to the recipients. At the end, everybody has his own story world in mind. But if everybody has done a good job, the recipient’s story world is somewhat the same as the author’s story world. The better the author has explained the story to the narrator, the better he in turn is able to narrate the author’s thoughts. Hence, it’s easier for them if they each know how the other works and what to do to achieve a good result.

In the case of Interactive Storytelling, the role of the narrator is generated by the storytelling environment. It “knows” about story structure, suspense, immersion and how to narrate. But, of course, it does not know anything about the author’s content. With our authoring environment, we primarily address regular book or film authors, because they are used to writing suspenseful stories. As much as possible, we give them the environment they are used to, but push them smoothly along toward interaction. Hence, we divided the authoring process into three parts: brainstorming, preparation and tuning. Within the brainstorming process, the author grasps the first ideas for his narrative. The main aspects are what should be told and how should it be told. Therefore, an abstract with about five lines is written down. Moreover, the author creates the characters of the story. Creating the main characters is hard work, because it includes complete CVs and everything about each character’s life, behaviours, and more. The story’s world is of great importance: In which era do the characters live, what are the circumstances, in which part of the world (or universe) do they live? Lots of sources have to be worked through for a believable and immersive story. Additionally, a first structuring of the narrative takes place during the brainstorming process: When and why should what happen, and which result should the story have? Normally, a concise version of the beginning and the end of the story are written down. The most important points of the story will be defined (in common stories, they are known as plot points). After that, the ideas for the missing scenes are noted and ordered, so that the journey through the story is full of suspense. Now having an idea about the story, the preparation for the realization begins. The author has to choose the story model. He has got to decide which kinds of interactions should be possible (interaction metaphors). Furthermore, the modalities and media used are of huge importance for the following work. After all preparations are done,

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Figure 5. Authoring environment Keating, Authoring environment Cyranus

the story and its world can be created. This process depends a lot on the decisions taken before. This is the time when the storyteller gets prepared by the author. Hence, the whole storytelling run-time environment and its helpers are fed the author’s content. Similar to other media, this can’t be done by the author alone. He needs a helping team as, for example, the director and cameraman for a film or the printer for a book. So, depending on the kind of presentation, a team of creative people will fulfil the author’s imagined world. To create these worlds, we use available software as much as possible. For example, for creating and animating characters and the surrounding world for Virtual/Augmented/Mixed Reality projects, 3-D software, such as Maya (Alias Maya, 2004), Blender (Blender, 2004) or 3D Studio Max (Discreet 3D Studio Max, 2004), is used. The data is exported as VRML files, which the render engines can use for presenting the world. However, there is no authoring software for our interactive storytelling run-time environment. So, we created Keating with the help of authors, designers and programmers. Keating is an authoring environment for structuring stories. With Keating, stories can be edited, combined with some media and verified.

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It helps during the brainstorming process and presents the decisions taken there for finishing a suspenseful story structure. Therefore, it gives different and flexible views of the story model, the story structure and the content. Via “drag and drop,” structure can be changed or new content can be included. At each step of the creative process, the StoryEngine can be started to view and verify the work that has been completed thus far (Schneider, Braun, & Habinger, 2003; Schneider, 2002). We have tested this tool in some projects and the way it works seems to fit an author’s needs. Expansions have been undertaken with Cyranus (cf., Iurgel, 2004), which helps with authoring believable interactive dialogues. For the future, more work will be done to include an interactive world in the authoring software and to make it understand real storybooks for a much easier start in creating interactive narratives.

dramaturgy in museums Museums are not only archives for cultural heritage and places for education and information, but also places for cultural development. Digital media and interactive exhibits within the museum’s

Storytelling-Based Edutainment Applications

environment are of significant value to increase attractiveness and competitive advantage. In the same way, the presence of a museum on the Internet is of great importance, for example, for art galleries or science centres. The ordinary presentation of exhibits, such as Web sites full of images and explanations, doesn’t seem sufficient any more. Besides information, visitors of (virtual) museums and science centres are seeking entertainment, playful education and convincing experiences. Examples like “One Wright Way” of The Franklin Institute Science Museum demonstrate how collections could become classrooms with educational activities. There, students can make their own “Flight Forecasts” and learn more about the flight pioneers, the Wright brothers (Elinich, 2004). Being part of the story contributes to an active occupation with the topic. Springer, Kajder, & Borst Brazas (2004) also aim for the application of digital storytelling to make personal connections to visual art and museum artefacts in the National Gallery of Art in Chicago. In an interactive CD-ROM application, contemporary witnesses become the protagonists of a story: One example is a film that shows youngsters riding kickboards (a Swiss invention and therefore shown at Musée Suisse) and talking about the vehicles and their social context (Kraemer & Jaggi, 2003).

The examples show that stories are a powerful means to impart knowledge, especially for museums and science centres. However, none of them are interactive in such a way that the user might influence the story’s flow and still experience a consistent narration. Therefore, we aim for interactive storytelling environments in order to improve individual learning efforts.

learning Issues E-learning is one of the current buzzwords in our information society and simultaneously represents a key area of EU Frameworks or national action lines for science and education. Recently, a number of approaches, such as notebook university Darmstadt (Notebook, 2004) or various school subject-oriented projects initiated and funded by the German Ministry for Science and Education (Neue Medien, 2004), have been initiated and carried out. On the other hand, in addition to those R&D projects, various learning applications, platforms and products, such as learnexact from Giunti (Learnexact, 2004), have been launched. Hereby, the amazing and exciting fact is that learning concepts are mostly limited to

•

The usage of multimedia to express and explain content or

Figure 6. Learning software: 3-D and string of pearls

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• •

The usage of constructivist learning concepts, which could be freely interpreted and The realization of learning applications as hypertext-oriented courses

Another interesting issue concerns the usage (and benefit?) of 3-D learning environments or virtual characters as tutors guiding the user through learning applications. Examples of this are role games, such as the famous Final Fantasy Series (Final Fantasy, 2004) or Tomb Raider (Tomb Raider, 2004) and Doom (Doom, 2004), using the so-called “String of Pearls” technique for sub-linear narration (see right half of Figure 6). Further on, Figure 6 presents “Ritter Rost” as an example of interactive learning software for languages, “Mathica” (Klett-Heureka, 2004), proposed for pupils (age >= 10 years) using behaviouristic and cognitivistic learning methods, and “Der Manager im Handelsbetrieb” (Dekra, 2004), proposed for trainees in the commodities market economy using constructivistic learning methods. Based on these approaches and learning examples, we invested research effort into the development of attractive, interactive and narrative learning software combining storytelling techniques with learning methods. Our first conFigure 7. Narration environment

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cepts providing a three-level concept are described in the following sections.

storytellIng concepts for edutaInment applIcatIons Based on this state-of-the-art analysis, storytelling methods and concepts, as well as a technical platform for the establishment of storytelling-based edutainment applications, are described. The global aim of our approaches developed by the interdisciplinary Digital Storytelling group at ZGDV Darmstadt is to combine different approaches from the fields of fairy tales, theatre, film or game-based learning and to establish narrative environments:

• • •

For information and knowledge transmission For learning, training and education To increase immersion through suspense and suspenseful stories

Thus, taken altogether, some kind of new user interface paradigm in the form of “narrative user interfaces” has been introduced.

Storytelling-Based Edutainment Applications

From a technical point of view, the basis for our storytelling-based edutainment applications is a storytelling platform providing a content layer (for story models, media, document archives, museum collections, etc.), an authoring environment with various editors, such as a story editor, scene editor, character or interaction editor, and a run-time system consisting of a story engine as control unit, as well as a scene engine, character engines and a rendering platform (scalable from mobile devices to simple Web sites or workstation screens up to complex physical set-ups for interactive artefacts within a museum).

storytelling run-time environment As already indicated above, in any interactive storytelling application, the balancing act is between the degree of freedom (emergent stories that evolve from the parametric description of actions and interactions) and a predefined story plot. It is even more challenging for the design of interactive learning environments: the learner’s autonomy must be balanced with the storyline and an instructional goal (Collins, 1996; Jonassen, 1989). How we deal with these problems will be explained in our approaches to an interactive storytelling environment. Then, we will present our integrated concept for educational applications. For creating interactive storytelling projects, we use both a run-time and an authoring environment developed at the Digital Storytelling group at ZGDV Darmstadt. In order to follow a user-centred development approach, the user’s needs directly influence the design of the run-time applications, as well. For example, the API used is very close to instructions used by directors on a film set. So both the run-time environment and the authoring environment influence the development process and vice versa. Authoring does not begin with creating an application for authors, but with building the whole environment, including the API, the MLs and the overall structure, with their needs in mind. The storytelling run-time environment

consists of several modules for narration, scene and—for VR, AR and MR applications—character controlling and user behaviour interpretation. Additionally, a set of mark-up languages and scripts, as well as content databases, is used.

storyengine The StoryEngine takes care of the narration of the overall story. Hence, it knows about the story structure and has implemented algorithms for creating suspense within an immersive form of storytelling. Therefore, it uses a story model provided by the StoryModelML. We have just developed the descriptions for some types of story-like presentations as fairy tales, story-driven education and business presentations. Additionally, some information is needed about suspense. This is done by the SuspenseML, which describes the storyline and how to combine it with the possible scenes. With this information, the StoryEngine processes the content interactively with regard to the user’s preferences. All the user’s interactions influence the kind of storytelling but, of course, not the story itself. Unlike common computer games, the story will always come to an end, so the user will experience satisfaction about the presented content.

sceneengine The SceneEngine is responsible for setting the scene and controlling the interaction with the user. A scene is the presentation of some content at a certain time and place. It gets a context description from the StoryEngine, so the SceneEngine controls which part of story should be presented at the moment. To have the same interpretation, it uses the SuspenseML, as well. Additionally, it loads a description about the actual place (stage) and the SceneScript. For SceneScript, we currently use an extension to the scripting language Phyton, which is well-known by game developers. It handles the content itself, the form of its

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Figure 8. Learning systems—Linear structures vs. story-based 3-level concept

presentation and the manner of interactions. For controlling the following modules, we specified the DirectionML. This is a non-blocking, asynchronous protocol with distributed systems and tasks in mind. Again, it has been developed for usage, which can be controlled by authors who are not programmers.

Integrated learning concepts Our approach to an integrated concept for storytelling-based education purposes consists of three levels: story level, knowledge level and learning level. At each level, specific information must be described. In the following paragraph, we will explain what kind of information the author has to include in the design. Figure 8 contrasts our concept with traditional linear structures of existing learning software, such as a learning platform provided by Telekom, providing different levels for beginners, advanced and professional users, but very predefined structures.

story level As described above, an interesting story with suspenseful structure has to be designed on the story level. As is already known from experiences

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from (non-linear) script writing and literature (McKee, 1997; Seger, 1990) we can differentiate between two approaches: story-driven approach (top-down) and character-driven approach (bottom-up) (Spierling, Grasbon, Braun, & Iurgel, 2002). Starting from the top, the author defines the whole storyline, including beginning and ending of the story, as well as plot points where the story turns, under consideration of dramaturgical aspects. With knowledge of the whole story, the author can work out scenes, characters, interactions and dialogue in detail. Using the characterdriven approach, the story evolves from a precise description of the (main) characters. In this case, authoring for interactive storytelling means a detailed definition of parameters and rules to control the character’s behaviour. Practically speaking, a combination of both authoring methods is useful and must be supported by the authoring environment. During run-time, the data on the Story Level is processed by the StoryEngine and SceneEngine.

knowledge level The knowledge base consists of modular fragments of information. It contains the information,

Storytelling-Based Edutainment Applications

Figure 9. Impressions of the GEIST project

which should be transferred and understood by the learner. Actually, the information is not part of the story, but rather serves as input for the author to develop an appropriate and consistent story. Therefore, content-related fragments should be designed for reuse and modification for other application domains. For museums, it is important to archive content for different presentation media, such as Web sites, onsite information or brochures.

learning level At the learning level, the author decides about the education goal of the application. The design of the story depends on a decision as to whether the goal is to initialize general interest in a topic or achieve deeper knowledge. In any case, the learning part shouldn’t undermine the power of the story (suspense, engagement, immersion). Educational parts must be integrated in the storyline. An exemplary situation shall explain a possibility of how it can be integrated: The learner needs to apply already acquired knowledge, but is obviously not able. During the following scenes, the necessary information should be presented in an alternative way so that he has another chance to

succeed. In current (learning) games, the learner risks getting stuck in a similar situation. Consequently, the learning model has to present how the user will proceed in his learning process—similar to a story model that presents the procession of the narrative.

reference examples The strengths and weaknesses of these approaches are discussed in the context of the edutainment projects GEIST (2004), art-E-fact (2004) and DinoHunter Senckenberg. Our approach to storytelling-based education and edutainment applications is currently realized in several projects: •

•

GEIST is an augmented reality system to experience historical coherences in the urban environment with interactive storytelling, funded by the Federal Ministry of Education and Research (BMBF). art-E-fact is an EU-funded project providing a generic platform for art (for both the creation and presentation of art).

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•

DinoHunter is an integrated concept in the wide range of museum applications and is partially implemented in the Senckenberg Museum in Frankfurt (DinoSim Senckenberg and DinoExplorer Senckenberg).

Hereby, the different projects address both edutainment applications within museums as tourist sites, as well as scenarios on the Web for museum Web sites, online courses and education or virtual science centres.

geIst: storytelling system for experiencing history The GEIST project (GEIST, 2004) represents a mobile outdoor Augmented Reality system to experience historical coherences in the urban environment with interactive storytelling. Hence, by telling a story, GEIST motivates the user to go sightseeing in Heidelberg while also introducing the user to the events that took place during the Thirty Years War. The users are supported to learn playfully, which awakens their natural interest to learn. Therefore, GEIST combines interactive storytelling with AR technology. The so-called “Magic Equipment” has been designed as user-centred input-/output equipment. It consists of AR glasses headsets for presenting the story. For tracking the user’s position and view, a combination of GPS (Global Positioning System), a tracker and a video tracking system was developed. It provides the possibility to track the user’s location and direction very accurately. Foremost, this equipment is used for displaying the AR information. For the GEIST project, we have placed virtual stages around the city of Heidelberg. The story will be presented upon these stages. The information concerning which stage the user is on at the moment is provided by the tracking system, which exerts a huge influence on the kind of presentation from a narrative point of view. In combination with the other input equipment like

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magic maps and pointers, the GEIST system can always adjust the flow of the story presentation to the user’s needs and keep it interesting. A magic book offers further historical information about the location, the people and the time. Thereby, users are able to answer questions which may arise independently, satisfying their developing thirst for knowledge right away. Altogether, GEIST, as one representative of storytelling-based edutainment approaches, covers story models, learning and gaming aspects, Virtual Reality/Augmented Reality technology, location-based services, as well as virtual and physical props. These features show the great variety of interactive storytelling and storytelling-based edutainment applications with a lot of different underlying research disciplines, such as computer graphics, interaction and communication design, but also history, pedagogy or artificial intelligence (concerning the dialogue modelling between the virtual characters and the user or among virtual characters).

art-e-fact: Interactive edutainment platform art-E-fact (art-E-fact, 2004) is an EU-funded project for interactive storytelling in Mixed Reality. The aim of the project is to offer the user an engaging way to understand and experience art and art history from a philosophical perspective. The scenario is designed for a museum site or an exhibition hall. As the focus of the installation, a work of art (e.g., Byzantine icons) will be presented. A group of virtual characters is situated close to the painting. When the visitor enters the installation, the narration begins and the characters begin a lively discussion. During the ongoing story, the user has the possibility to interact, for example, by text input via keyboard. At this moment, the visitor becomes part of the discussion group and can express his opinion, ask questions or change topics. He can also choose to enjoy the

Storytelling-Based Edutainment Applications

Figure 10. art-E-fact scenario and components of the platform

story passively. Then, one of the characters will take over the role of a non-expert to allow the visitor a certain degree of identification with the character. In any case, the narration touches on different areas of interest without massive interruption of the story line (Iurgel, 2002; Spierling & Iurgel, 2003). Additionally, the visitor can use physical props to interact with the painting, for example, using a sponge for replacing layers or a magnifying glass for zooming in/out. Therefore, a video tracking system for gesture recognition is implemented. A planned Web-based application will offer the same conversational interactions and adequate replacements for the interaction possibilities in Mixed Reality. The art-E-fact approach aims at the transmission of information within an interactive dialogue with virtual characters and multi-modal interaction possibilities. Each character is representing

a particular perspective on the work of art. The main topic of the story can be influenced by the user without departing from a consistent storyline. During the narration, the user will be prompted by the characters from time to time, for example, to give an answer. If he doesn’t react, they will answer the question during the ongoing conversation. art-E-fact is an example of the purposeful use of emotionally involving and personality-rich virtual humans in edutainment. Here, the information is transmitted in a natural way, involving emotion, dialogue and social aspects. Indeed, one of the core future issues for such virtual character-based educational applications will certainly be the guided establishment of social bounds for the human student with the virtual characters, since the importance of affective relations with teachers and comrades is a well-established phenomenon in learning. Accordingly, a learner should be able to establish a kind of “friendship” with the

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Figure 11. Global DinoHunter scenario for museums Supervisor (Museum Paedagogues, Teachers...) Individual Museum Visitor Museum Staff Applications & Devices (Kiosks, mobiles, etc.) Visitor Groups, e.g. Classes

Exhibition, Artifacts Information - learning - edutaining - entertaining - interaction - cooperation - communication - evaluation

Individual Web Visitor

virtual companions, and feel affection and trust towards the virtual teacher (cf., Bandura, 1997; Iurgel, 2003).

dinohunter: edutainment applications for museums The global aim of DinoHunter is to develop integrated concepts for mobile edutainment applications and knowledge environments. Typical examples of this are interactive scenarios for museums, theme parks or various kinds of exhibits and trade fairs. From the technical point of view, DinoHunter combines computer graphics technology with interactive storytelling, user interface and user interaction concepts, such as Kids Innovation or momuna (mobile museum navigator) (Göbel & Sauer, 2003). From a global perspective, DinoHunter provides integrated concepts for the wide range of interactive museum (or any other edutainment) applications. The basic principle is to combine computer graphics technology, such as 3-D Rendering,

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groups@web (Classes, families, etc)

Virtual and Augmented Reality or multi-modal interfaces (speech recognition, video recognition, gestures, etc.), with interactive storytelling approaches established in the field of film, theatre or fairy tales and further user interface and user interaction concepts. With the support of mobile devices, location-based services and pedagogic aspects (learning models and concepts), DinoHunter transforms the museum into an interactive learning and gaming environment. Hereby, the setting of DinoHunter takes into account the needs and knowledge of various users and user groups involved in the multi-faceted domain of museum applications (see Figure 11): individual visitors, families or school classes as visitor groups, museum guides, scientific, administrative or marketing staff at the museum, or all the different user groups visiting virtual museums via the museum’s Web site. Apart from a comprehensive DinoHunter platform providing tools, methods and concepts for all these different user groups, additional case studies and pre-defined templates help to support:

Storytelling-Based Edutainment Applications

Figure 12. DinoSim Senckenberg

•

•

•

•

• •

•

Museum staff to archive library data and artefacts and make them available within digital museum applications Administrative staff to monitor user behaviour and the success of individual artefacts or parts of exhibitions by measuring the retention period of visitors at special exhibits Scientific staff to get a visual feedback of their research, providing 3-D reconstructions of dinosaurs or visualizing appearance and behaviour (such as walking). This also includes a rapid prototype environment as part of the authoring environment Museum educators to enter digital media, didactic methods and learning models or any hints leading the visitor to “the most important” artefact Teachers in preparing (and post-processing) the museum visit of a school class Kids/pupils interacting and communicating among one another or sending messages in order to solve a group-based task associated with a museum’s rally or game Marketing people to combine the content layer (artefacts, exhibits and digital media or even access to further repositories) with the museum’s shop or the Web site or event calendars

dinosim senckenberg One example of the successful combination of onsite exhibits and online services is the DinoSim project for the Senckenberg Natural History Museum (Senckenberg, 2004). On the occasion of its re-opening in November 2003, Senckenberg had a great interest in improving their exhibition by integrating multimedia systems. In addition to a general visitor information and navigation system, two kiosk terminals around the most exciting exhibits (skeletons of T-Rex and Diplodocus) are enhanced by the DinoSim application, which provides a 3-D real-time simulation and animation of dinosaurs. The primary goal of DinoSim is to visualize different scientific-related theories about appearance, movements and behaviour of dinosaurs. Visitors can freely navigate around the dinosaurs within a 3-D environment and can take pictures from their own view (point). These pictures are then sent by e-mail to the visitor’s e-mail address, where users can then take advantage of the T-Online Fotoservice (T-Online Fotoservice, 2004) and have T-shirts, cups or bags printed with their individual dinosaur. The visitor will get his unique souvenir and, for the museum, the application is part of its comprehensive customer relationship management.

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Figure 13. DinoSim Senckenberg: Modelling process

Figure 14. DinoExplorer Senckenberg

Figure 13 shows DinoSim’s multi-phase modelling process, starting with real fossils, 3-D reconstructions by the palaeontologists, the extraction of geometry, appearance and skeleton, and the animation with Maya software, resulting in a touch screen application on terminals in front of the T-Rex and Diplodocus in the dinosaur hall of the Senckenberg Museum.

dinoexplorer senckenberg DinoExplorer represents a game-oriented application that is available for download on the Sencken-

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berg Web site. Within a hide-and-seek style game the user can explore the virtual Senckenberg and its exhibits with the task of finding a particular animal (Leptictidium). As the user succeeds in finding the Leptictidium, further functionality is available on a virtual mobile device. For example, users can experience different layers for the skeleton, inner organs, muscles or possible appearances (colour, structure) of skins. Further along, the breathing of dinosaurs is presented via 3-D animations. Figure 14 shows a snapshot of the DinoExplorer Senckenberg hide-and-seek game with an

Storytelling-Based Edutainment Applications

emulated PDA providing augmented information about the appearance of dinosaurs. Detailed descriptions about the global DinoHunter scenario, as well as DinoSim, DinoExplorer and further applications out of the DinoHunter series, are provided in various publications of the Museums and Web and ICHIM conference series (Sauer et al., 2004; Göbel & Sauer, 2003a; Sauer & Göbel, 2003b). A similar approach to DinoSim and DinoExplorer is provided by the Canadian Museum of Nature (Canadian Museum, 2004), underlining the usage of 3-D computer graphics technology to visualize geometry, appearance and behaviour of dinosaurs. Concerning the question, “What are the uses and benefits of 3-D imaging?,” they list both exhibition enhancement by virtually displayed artefacts and specimens, as well as benefits in education by enhanced and animated data, for the provision of dynamic learning experiences.

conclusIon Finally, the major results are summarized in a short conclusion and further research and application-driven trends (context: museums) are pointed out. Within the wide range of museum applications and scenarios, this chapter describes methods and concepts for the establishment of storytelling-based edutainment applications. Hereby, the global aim is to combine traditional learning methods and concepts with dramaturgic and narrative elements in order to improve knowledge transmission, to increase the user immersion and finally to produce positive learning effects. This is realized by a storytelling platform, providing a content layer, an authoring environment with various editors for different user groups (such as storytellers, museum pedagogues and scientists or teachers), a complex run-time system with different story engines and a set of player components

ranging from online Web sites for simple PC workstations up to complex physical set-ups and installations for interactive exhibits within museums. With regard to the integration of storytelling methods and components, such as story models or story engines and learning methods, a 3-level concept is introduced, providing a story level, knowledge level and learning level. The practical use and usage of these concepts are discussed in the context of the reference examples, GEIST, art-E-fact (EU-funded project concentrating on character-based conversations and Mixed Reality) and the two DinoHunter applications, DinoSim and DinoExplorer, developed and realized for the Senckenberg Museum in Frankfurt, Germany. Regarding DinoHunter, first user studies have shown the great benefit of storytelling and gamebased approaches enhanced by interactive Virtual and Augmented Reality technology: Especially young visitors—used to computer games and new media—are fascinated by interactive applications and like this form of playing and learning. From the research-oriented point of view, further effort will be invested into the field of integration and harmonization of various story models providing suspense and dramaturgy with learning models providing learning methods, content and media. Later on, both the authoring and run-time environment of the storytelling platform for edutainment applications will be improved in relation to learning aspects, as well as personalization and individualization. On the other hand, application-driven issues and obstacles affect the integration of content management systems with edutainment applications or the necessity (especially for museums) to find appropriate business models financing digital media, (interactive) museum Web sites, high-end installations or hardware and software for storytelling-based edutainment applications in general.

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references Alias Maya. (2004). Retrieved June 16, 2004, from http://www.alias.com/eng/products-services/maya/ art-E-fact. (2004). Generic platform for interactive storytelling in mixed reality. EU-funded project (IST-2001-37924). Retrieved March 15, 2004, from http://www.art-e-fact.org Bader, M. (2004). Retrieved June 16, 2004, from http://www.natural-reality.de/ Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice-Hall.Blender. (2004). Retrieved June 16, 2004 from http://www. blender3d.com/ Campbell, J. (1973). The hero with a thousand faces. Princeton, NJ: Princeton University Press. Canadian Museum. (2004). Canadian Museum of Nature, Canada, 3D Imaging Center. Retrieved March 15, 2004, from http://www.nature.ca/3D/ Collins, A. (1996). Design issues for learning environments. In S. Vosniadou, E.D. Corte, R. Glaser, & H. Mandl (Eds.), International perspectives on the design of technology-supported learning environments (pp. 347-362). Mahway, NJ: Lawrence Erlbaum Associates. Crawford, C. (n.d.). Interactivizing stories. Retrieved March 15, 2004, from http://www.erasmatazz.com/library/Lilan/interactivizing.html Crawford, C. (n.d.). Plot versus interactivity. Retrieved March 15, 2004, from http://www. erasmatazz.com/library/Lilan/plot.html Csikszentmihalyi, M., & Csikszentmihalyi, I.S. (1997). Optimal experience. Cambridge, UK: Cambridge University Press. Dekra Akademie GmbH. (2004). Der Manager im Handelsbetrieb. Retrieved March 15, 2004, from http://www.dekra-akademie.de/

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Discreet 3D Studio Max. (2004). Retrieved June 16, 2004, from http://www.3dmax.com/ Doom. (2004). Retrieved March 15, 2004, from http://www.doom3.com/ Dramatica. (2004). Retrieved June 16, 2004, from http://www.dramatica.com/Eduweb Educational Web Adventures. (n.d.). Retrieved March 15, 2004, from http://www.eduweb.com/ Elinich, K. (2004). One Wright way: From collections to classrooms. In D. Bearman, & J. Trant (Eds.), Museums and the Web 2004: Proceedings. Toronto: Archives & Museum Informatics. Feix, A., Hoffmann, A., Osswald, K., & Sauer, S. (2003). DinoHunter: Collaborative learning experience in museums with interactive storytelling and kids innovation. In S. Göbel, N. Braun, U. Spierling, J. Dechau, & H. Diener (Eds.), Proceedings of TIDSE 2003 (pp. 388-393). Darmstadt. Field, S. (1988). The screenwriter’s workbook. New York: Dell Publishing Company Final Fantasy. (2004). Final Fantasy Series. Retrieved March 15, 2004, from http://www. ffonline.com/ Gagne, R.M., Briggs, L.J., & Wager, W.W. (1992). Principles of instructional design. Fort Worth: HBJ College Publishers. GEIST. (2004). Project (01IRA12B GEIST) funded by the German Ministry of Science and Education (BMBF). Retrieved March 15, 2004, from http://www.tourgeist.com Göbel, S., & Sauer, S. (2003a). Combine the exhibition and your Web-visitors. Integrated concepts of interactive digital media for museums. In Workshop at Museums and the Web 2003. Charlotte, NC. Göbel, S., & Sauer, S. (2003b). DinoHunter: Game based learning experience in museums. In Pro-

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ceedings of ICHIM’03, École du Louvre, Paris. CD-ROM. Archives & Museum Informatics. Il était une fois... L’homme, France/Japan. (1978). Retrieved March 15, 2004, from http://www. generiquestele.com/details_id-20_n-Il,etait,une, fois,l,homme.htm Iurgel, I. (2002). Emotional interaction in a hybrid conversation group. In PRICAI-02. Workshop on Lifelike Animated Agents. Tokyo, Japan. JSPS. Iurgel, I. (2003). Virtual actors in interactivated storytelling. In IVA 2003 (pp. 254-258). Iurgel, I. (2004). Narrative dialogues for educational installations. In NILE 2004 (in press). Jonassen, D.H. (1989). Hypertext/hypermedia. Englewood Cliffs, NJ: Educational Technology Publications. Klett-Heureka. (2004). Retrieved March 15, 2004, from http://www.klett-verlag.de/heureka/ Kraemer, H., & Jaggi, K. (2003). Virtual Transfer Musee Suisse. Unpublished CD-ROM. Retrieved from http://www.musee-suisse.com Learnexact. (2004). Retrieved March 15, 2004, from http://www.learnexact.com/ Macromedia Director. (2004). Retrieved June 16, 2004, from http://www.macromedia.com/software/director/ Macromedia Flash. (2004). Retrieved June 16, 2004, from http://www.macromedia.com/software/flash/ Marsella, S.C. (2003). Interactive pedagogical drama: Carmen’s bright IDEAS assessed. In Intelligent virtual agents: Lecture notes in artificial intelligence (LNAI 2792) (pp. 1-4). Berlin: Springer. Mateas, M. (1997). An oz-centric review of interactive drama and believable agents. Technical Report. Pittsburgh PA: School of Computer Science, Carnegie Mellon University.

Mateas, M., & Stern, A. (2003). Integrating plot, character and natural language processing in the interactive drama façade. In S. Göbel, N. Braun, U. Spierling, J. Dechau, & H. Diener (Eds.), Proceedings of TIDSE 2003 (pp. 139-151). Darmstadt. McKee, R. (1997). Story: Substance, structure, style and the principles of screenwriting. Regan Books. Museum of Tolerance. (2004). Teachers’ guide Web site. Museum of Tolerance, New York. Retrieved March 15, 2004, from http://teachers. museumof tolerance.com/ Noah, D. (2003). An analysis of narrative-based educational software. Retrieved March 15, 2004, from http://naturalhistory.uga.edu/narrative_paper.htm Notebook. (2004). Notebook University Darmstadt. Retrieved March 15, 2004, from http://www. nu.tu-darmstadt.de/ Picard, R.W. (1997). Affective computing. Cambridge, MA: MIT Press. Propp, V. (1998). Morphology of the folktale. Austin: University of Texas Press. Sauer, S., & Göbel, S. (2003). Focus your young visitors: Kids Innovation, Fundamental changes in digital edutainment. In D. Bearman & J. Trant (Eds.), Museums and the Web 2003: Selected papers from an international conference (pp. 131-141). Toronto: Archives and Museums Informatics. Sauer, S., Osswald, K., Göbel, S., Feix, A., & Zumack, R. (2004). Edutainment environments. A field report on DinoHunter: Technologies, methods and evaluation results. In D. Bearman & J. Trant (Eds.), Museums and the Web 2004: Selected papers from an international conference (pp. 165-172). Toronto: Archives and Museums Informatics.

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Schell, J. (2002). Understanding entertainment: Story and gameplay are one. In J.A. Jacko,& A. Sears (Eds.), The human-computer interaction handbook: Fundamentals, evolving technologies and emerging applications. Mahwah, NJ: Lawrence Erlbaum Associates. Schneider, O. (2002). Storyworld creation: Authoring for interactive storytelling. In V. Skala (Ed.), Journal of WSCG (Vol. 10, No. 2). International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2002 (pp. pp. 405-412). Plzen: University of West Bohemia. Schneider, O., & Braun, N. (2003). Content presentation in augmented spaces by the narration of interactive scenes. In Proceedings of First Research Workshop on Augmented Virtual Reality (AVIR). Genf, Switzerland. Schneider, O., Braun, N., & Habinger, G. (2003). Storylining suspense: An authoring environment for structuring non-linear interactive narratives. In V. Skala (Ed.), Journal of WSCG (Vol 11, No. 3). International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2002 (pp. 411-417). Plzen: University of West Bohemia. Seger, L. (1990). Creating unforgettable characters. New York: Henry Holt & Company. Senckenberg. (2004). Retrieved June 16, 2004, from http://www.senckenberg.de/

Shank, R., & Cleary, C. (1995). Engines for education. Mahwah, NJ: Lawrence Erlbaum. Spierling, U., & Iurgel, I. (2003). Just talking about art. In Virtual Storytelling. Proceedings Second International Conference, ICVS 2003 (pp. 189197). (LNCS 2897). Toulouse, France. Spierling, U., Grasbon, D., Braun, N., & Iurgel, I. (2002). Setting the scene: Playing digital director in interactive storytelling and creation. Computers & Graphics, 26 (1), 31-44. Spitzer, M. (2002). Lernen. Gehirnforschung und die Schule des Lebens. Spektrum Akademischer Verlag, Heidelberg. Springer, J., Kajder, K., & Borst Brazas, J. (2004). Digital storytelling at the National Gallery of Art. In D. Bearman & J. Trant (Eds.), Museums and the Web 2004: Proceedings. Toronto: Archives & Museum Informatics. T-Online Fotoservice. (2004). Retrieved June 16, 2004, from http://service.t-online.de/ c/00/01/36/1360.html Tobias, R.B.(1999). 20 Masterplots. Frankfurt am Main: Zweitausendeins. Vernon. (2004). Vernon Systems. Auckland, New Zealand. Retrieved March 15, 2004, from http://www.vernonsystems.com/ Vogler, C. (1998). A writer’s journey. Studio City, CA: Wiese Productions.

This work was previously published in E-Learning and Virtual Science Centers, edited by R. Subramaniam and L. Tan, pp. 190-214, copyright 2005 by Information Science Publishing (an imprint of IGI Global).

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Chapter 3.12

Web Conferencing in Distance Education M. Michelle Panton Bemidji State University, USA

IntroductIon Web conferencing is a technology that allows groups of individuals in a variety of diverse locations to communicate and share information without having to leave their desks. It provides features such as whiteboarding, screen sharing, chat, and polling. It eliminates the need to travel, reduces downtime, increases efficiency, and reduces costs. AT&T worked on proofs of concepts and prototypes for personal conferencing systems for 20 years and finally released its product in 1993 (Perey, 2003). Microsoft released NetMeeting in about 1995. Wooley now lists 95 real-time collaboration products and Web sites on his Web site, ThinkofIt.com. The growth of real-time collaboration has grown significantly and been more successful in the last few years, as the CPUs in PCs are faster, the PCs have more memory, and more bandwidth is available and cheaper. Frost and Sullivan’s 2002 report estimates that by 2008, $2 billion will be spent on Web conferencing (as cited by Perey, 2003). This technology allows a business to conduct training simultaneously, glob-

ally creating a collaborative learning environment while keeping costs down. Wintrob (2003) cites an example provided by Sam Mazotta, WorldCom Canada’s director of product management, where it costs $2,000 per person to fly 50 people to an in-person meeting for travel, hotel, meals, and related expenses for a total of $100,000. For a Web conference for the same 50 people, plus an additional 100 people watching live in the same location: $4,100 for audio-visual production, $1,100 for signal capture, $12,800 for streaming, $500 for 180-day archiving, for a total of $18,500 or $370 per person. This article will discuss two Web conferencing tools: Microsoft® Office Live Meeting and IBM Lotus Instant Messaging and Web Conferencing. Microsoft purchased PlaceWare in February 2003 and developed a new business unit, the Real Time Collaboration Group. At the time of purchase, PlaceWare was offering services to 3,100 enterprise accounts (Perey, 2003). These accounts include companies such as BASF, Computer Associates, TD Waterhouse, Siemens, HP, Cisco

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Web Conferencing in Distance Education

Figure 1. Administrator’s conference center; fields required to create a meeting

Systems, and Bristol-Myers Squibb Company. The 9/11 incident made travel safety issues for corporate America look into alternative solutions for training and meetings with clients and global offices. The 2003 SARS epidemic was another incident that escalated the use of Web conferencing. PlaceWare, now called Live Meeting, is a hosted Web conferencing service. It requires a telephone and a PC with a Web browser and an Internet connection. Presenters (meeting facilitators or trainers) develop their presentations in a presentation program such as Microsoft PowerPoint, upload the slides into the application from their desktop, set up a conference call, invitations are sent via e-mail to the participants with a logon and password, and the presenter logs on as the host. Live Meeting Now appears to be a feature recently added to Microsoft® Office Live Meeting. This capability allows the presenter to schedule a meeting on the fly from either Outlook or Lotus Notes. This feature is not used in Metavante Corporation, as sufficient licenses are not available to provide this feature to the general population.

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The second Web conferencing tool available to all Metavante employees is IBM Lotus Instant Messaging and Web Conferencing. This tool was released to the general public in the second quarter of 2004. The instant messaging portion of this tool was previously called Sametime, which has been available for a few years, but only available to Metavante employees for approximately one month.

lIve meetIng Live Meeting is available for a free 30-day trial evaluation. It is available via purchased seats at a yearly rate or at $.35 per minute per user. It can handle groups from two to 2,500 without leaving their desks. It consists of two meeting environments: the Auditorium Place and the Web Meeting Place. The Auditorium Place is intended for training and seminars up to 2,500 individuals. The Auditorium Place allows for multiple presenters to present simultaneously to a large group. At

Web Conferencing in Distance Education

Figure 2. Administrator’s conference center, cont.

Figure 3. Typical presenter’s e-mail

any time a presenter can become the active presenter without having to pass control back and forth. Text questions can be answered by any of the presenters at any time. An attendee can get a private answer, or the answer can be posted for all to see. There is a seating chart and feedback to help the presenter pace the session or to high-

light a specific individual’s needs. Plug-ins are not required for any of the attendants. Following are features of the Auditorium Place: • •

Application and desktop sharing and viewing Annotation tools

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Figure 4. Typical attendee’s e-mail

• • • • •

Microsoft® Outlook® integration Printing One-touch record and playback Attendance charts Web tour (Microsoft, 2004a)

The Web Meeting Place is intended for smaller collaborative groups: interactive sales, marketing, and training or learning groups. It has advanced collaboration features that can be used with these smaller groups. Presentations can be delivered, applications shared, text and whiteboard tools used interactively. A presenter remains in control at all times, but can share controls and take them back at any time. A presenter can visit the online room at any time and can add materials prior to the meeting. The specific features of the Web Meeting Place are as follows: • • • • • • •

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The ability to show and share any application, document, graphics, or illustrations Annotation tools Integrated two-way instant messaging Web slides Whiteboards Web tour Printing and handout capabilities (in PDF format) (Microsoft, 2004a)

Both the training and marketing departments are under contract for 30 concurrent licenses. If all 60 licenses are being used, additional seats are available at $.50 per minute. Branding is available; this means that when a client attends a training session or marketing presentation, the Microsoft logo is removed and replaced by the specific company’s logo. The Web Meeting Place appears to be what the corporate training department uses for their training sessions. While the primary usage of Live Meeting is to present interactive meetings and training sessions, the presentation can be recorded. These recordings can be saved and played back later, either for subsequent meetings or training sessions, or can be played back on the intranet, Web site, or CD. A PlaceWare Replay Wrapper utility is available for download to provide the audience the ability to view the recorded session. The utility requires Windows Media Player to be installed on the computer (Microsoft, 2004b). The Conference Center is the administrator’s tool for scheduling meetings. Figure 1 and Figure 2 show the setup of a typical meeting. The typical time to set up a meeting, including sending presenter and attendees e-mails, is approximately 10 minutes. The administrator or someone who has scheduling privileges can generate a variety of

Web Conferencing in Distance Education

management reports: Meeting Lists (meetings and attendance for a specified period of time), Meeting Attendance (users and roles, the browser used, time arrived, and duration of attendance), and Meeting Poll (indicates if each attendee responded to each polling slide) (Microsoft, 2004c). Figure 3 depicts the e-mail sent by the administrator to the presenter. This will include a link that can be clicked on or pasted into a Web browser for the presenter to access the meeting. Figure 4 depicts the attendees’ e-mail sent to the presenter to send to the attendees. If the meeting has been set up as a Web Meeting Place, the presenter can access the meeting at any time to prepare the meeting presentation. Once in the meeting, the presenter can upload an existing PowerPoint presentation. Web, poll, application sharing, and text slides can then be inserted into the PowerPoint presentation. The presentation can be exported as a PDF file for saving or printing if desired. While attending the meeting, the attendees also have this option. A PlaceWare Add-In for PowerPoint is available for download. This add-in gives the presenter the ability to prepare Web, poll, application sharing, and text slides in advance prior to uploading. Figure 5 shows a

Figure 5. A poll slide being created using the PowerPoint add-in

poll slide being created in PowerPoint using this add-in. It allows the presenter to add his/her image and name to the presentation. It allows the presenter to export PowerPoint presentations to the PlaceWare Slide Set Format (.pwp). It allows the presenter to upload slides from a computer that might not have PowerPoint and saves time during uploading. Once a PowerPoint presentation has been uploaded, additional slide types can be inserted: •

•

• •

•

Whiteboard slide: A blank image slide which can be drawn on, text added to, stamps added to, and information highlighted using various annotation tools. Web slide: A URL is placed on page to display a Web page. Attendees can click on the links on the page to access further information. Text slide: A blank editable slide on which the presenter can type, copy, and paste text. Polling slide: Used to obtain feedback from the attendees by presenting questions and providing them with several responses to the questions. Snapshot slide: Displays a captured screen shot of a computer screen which can then be annotated.

Figure 6. The display of the presenter’s screen for a Web Meeting Place

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•

Sharing slide: This is not actually a slide, but a placeholder to be able to share a view of the presenter’s computer or use of an application with an attendee (Microsoft, 2004d).

The sharing slide allows full interaction during a meeting or training session. The presenter can allow an attendee to take over control of the presenter’s computer. There are three ways to share: frame, application, or desktop (Microsoft, 2004e).

mIcrosoft offIce lIve meetIng In dIstance educatIon After 9/11, Metavante began using PlaceWare to provide client training in order to cut travel costs and to limit travel with the hesitancy to travel. A concept called the virtual classroom was developed. Corporate trainers began training from their desks rather than traveling to the client or having the client travel to the trainer. Sessions are recorded and available for playback both for review and as a method of providing a self-directed training session. Without the replay-wrapper the self-directed training involves administrator intervention. Metavante upgraded PlaceWare to Live Meeting 2003 in mid-2004. This author had a approximately one hour of introduction to the development of a PlaceWare meeting and created one training session. At that time, it was decided to use Sametime Connect instant meeting for the required training of remote users due to the potential cost to the department. The upgrade to Live Meeting was viewed as a positive move forward. The interface is more intuitive, and a meeting was created with limited documentation in less than one hour.

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Ibm lotus Instant messagIng and web conferencIng Unlike Live Meeting, which is a hosted Web conferencing service, Lotus’ Web conferencing product requires a server, server software license, and a client. The instant messaging chat-only client is free with the Lotus Notes 6.5.1 client. The thick client called Sametime Connect requires a client license. Sametime Connect provides both instant messaging as well as instant meetings, similar to the Live Meeting Now, with screen and application sharing. The IBM Lotus Instant Message and Web Conferencing server provides similar functionality to the Live Meeting Web Meeting Place. No administrator is required. Each presenter is able to access the server and schedule a meeting. PowerPoint slides can be uploaded prior to the meeting. The capabilities of polling, whiteboarding, application sharing, and screen sharing exist, but this author was unable to determine if there was a way to insert a ‘slide’ into the presentation as a placeholder for the subsequent meeting. It appeared that they had to be done on the fly. This would require more effort on the trainer’s part during the presentation. One feature that exists, which is perceived as being better than Live Meeting, is that during the use of a polling slide, the correct results of a polling slide used for feedback or a quiz can be immediately displayed to the attendee. Another advantage of this product is that it works with voice and video over IP. While experimentation of this product was not possible, this author has used the instant meeting feature with screen sharing for distance training of products. Attendees were able to figure out how to share their screen in less than five minutes without any presenter intervention.

Web Conferencing in Distance Education

web conferencIng as a dIstance learnIng tool The immediate need to deploy and train employees on instant messaging exists. Live Meeting can be used with a presenter/trainer to train remote employees. The trainer’s image and name can be added to the presentation so the attendees can associate an image with the voice and name. The sharing application slide can be used to demonstrate the various setup and procedural techniques such as adding groups and individuals to buddy lists. This technique will make use of both auditory and visual stimuli. Control of the screen can be passed to the attendees to allow them to practice the procedure, providing them with kinesthetic stimuli. The attendees will be encouraged to print the presentation for future reference. Feedback and evaluation of the training will be conducted via the polling slides. The session can be recorded for future playback and remediation. The recorded meeting session can be modified for individuals who prefer self-directed study. Rather than using the screen sharing slide, a Web slide can be substituted. This Web slide can then be used to run a FLASH file. An application such as Camtasia Studio by TechSmith Corporation can be used to record the keystrokes of a procedure, add audio narrative, and annotate the procedures. These sessions should be kept brief, preferably under 15 minutes. Lastly, an animated image or character in line with current marketing themes will be used to add interest to the presentation.

conclusIon At their current levels of evolution, both products have a place in corporate Web conferencing and corporate training. Live Meeting appears to be a better product for formalized training, but appears to be a more costly solution, as it has been limited to a designated number of concurrent seats. IBM

Lotus Instant Messaging and Web Conferencing is still in its infancy, but appears to be a less costly solution to provide a corporate-wide instant Web conferencing tool. The instant meetings without administrator intervention could lead to spontaneous training or meeting sessions.

references Metavante Corp. (2003). Tips & tricks for Metavante trainers. Retrieved July 23, 2004, from the Metavante intranet. Microsoft Office Live Meeting, A PlaceWare Service. (2004). http://main.placeware.com Microsoft Office Live Meeting. (2004a). Meeting environm ents. Retrieved July 24, 2004, from http://main.placeware.com/services/meeting_envi ronments.cfm Microsoft Office Live Meeting. (2004b). PlaceWare replay wrapper utility. Retrieved July 24, 2004, from http://mail.placeware.com/support/ pw_replay_ wrapper_info.cfm Microsoft Office Live Meeting. (2004c). Generating reports. Retrieved July 24, 2004, from http:// main.placeware.com/training/customer_guides. cfm Microsoft Office Live Meeting. (2004d). Presenting slides. Retrieved July 24, 2004, from http:// main.placeware.com/training/customer_guides. cfm Microsoft Office Live Meeting. (2004e). Sharing applications. Retrieved July 24, 2004, from http:// main.placeware.com/training/customer_guides. cfm Perey, C. (2003). Microsoft announces its intention to acqu ire PlaceWare. Retrieved July 24, 2004, from http://www.streamingmedia.com/r/printer friendly.asp?id=8293

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PlaceWare, Inc. (2003a). Creating present ations guide. Retrieved July 24, 2004, from http://main. placeware.com/tra ining/customer_guides.cfm

Microsoft® Office Live Meeting: A hosted Web-conferencing service, previously known as PlaceWare.

PlaceWare, Inc. (2003b). Organizer’s and member’s guide. Retrieved July 24, 2004, from http:// main.placeware.com/training/customer_guides. cfm

PlaceWare: A hosted Web-conferencing service, now owned by Microsoft.

PlaceWare, Inc. (2003c). Presenting at or attending a Microsoft Office live meeting. Retrieved July 24, 2004, from http://main.placeware.com/training/customer_guides.cfm Wintrob, S. (2003). Web conferencing: Communication links take off as people are grounded. National Post. Retrieved July 24, 2004, from http://main.placeware.com Wooley, D.R. (2004). Conferencing on the Web. Think of it. Retrieved July 24, 2004, from http://www.thinkofit.com/Webconf/realtime. htm#general

key terms Chat/Instant Messaging: A technology that provides the capability of instant, textual conversation with another individual through a computer session. Metavante Corporation: A financial service bureau and wholly owned subsidiary of Marshall and Ilsley Corporation.

Polling: A technology associated with online meetings that allows a presenter to a display a multiple choice or true/false question to the attendees for feedback purposes. Sametime: An IBM Lotus instant messaging client now known as IBM Lotus Instant Messaging. Screen Sharing: A technology associated with online meetings that allows multiple individuals in different physical locations to view and transfer control of a computer screen used during a Web conference or online meeting. Web Conferencing: A relatively new technology that uses the telephone or voice over IP, a workstation, and a Web browser. It provides the capability to individuals in multiple locations to have online meetings and training sessions using features such as whiteboarding, screen sharing, and polling. Whiteboarding: A technology that allows a presenter to draw on a computer screen using the mouse pointer, generally for the purposes of highlighting a particular screen area.

This work was previously published in Encyclopedia of Distance Learning, Vol. 4, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P. L. Rogers, and G. A. Berg, pp. 1997-2003, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.13

Wireless Technologies in Education Chia-chi Yang University of Missouri - Columbia, USA

background The development and change in computer technologies today is so incredibly fast, and the lifecycle of technologies has been so shortened, that new technologies sprout up to replace old ones like bamboo shoots after a spring rain. However, the utilization of common features of the computer and the Internet, such as using spreadsheets and searching for resources over the Internet, are still considered to be essential for supporting learning in all levels of education. The Internet began facilitating Web-based learning in the early 1990s, and wireless technology has been offering stunning opportunities for educators since the late 1990s. A growing volume of research suggests that wireless and mobile technologies have the potential to enable collaborative learning (DiGiano, Yarnall, Patton, Roschelle, Tatar, & Manley, 2002), sharing of resources faster and more effectively (Kranz, 2002), and connection to resources at any time and from any place, as well as to have a positive impact on motivation (Wangemann, Lewis & Squires, 2003). Boerner (2002) has identified

the benefits of implementing wireless networking on campus; these include mobility, ease of installation, less space constraints, less cost, and the flexibility to expand and upgrade systems. Improving communication technologies and affordable mobile devices accelerates the adoption of wireless technologies in the classroom, and more and more schools have been connecting to the Internet with wireless technologies.

IntroductIon of wIreless technologIes Wireless technologies extend the use of LANs (local area networks) and WANs (wide area networks), and enable communication via the airwaves with infrared (IR, which means beaming) or radio frequency (RF, including 802.11, and mobile phones), better known as Wi-Fi. The convenience of networking without wires increases the utilization of online resources and the mobility of portable devices. Through the Access Point (AP)—an antenna that transmits

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Wireless Technologies in Education

and receives signals—users can connect to the Internet and to other computers or devices. The Institute of Electrical and Electronic Engineers’ (IEEE) official 802 committee approved 802.11 for a wireless network standard protocol in 1997 (CyberScience Lab, 2003). Then IEEE enhanced the 802.11 wireless networking standard and made revisions, which include 802.11b, 802.11a, and 802.11g, all to help adapt the technology to the industry’s needs. The IEEE 802.11b standard so far is the most widely used, because of the faster transmission speeds and smaller expense that it offers (Prakash, 2001). The newly introduced mobile devices all comply with this standard to ensure their compatibility in the wireless environment. Compared to the wired network, wireless technologies require less infrastructure work, share resources more effectively, and support ubiquitous learning, and have the potential to enable “anytime, anywhere” learning. Rather than discussing the technological terms, the following sections address the practices, opportunities, and issues about the use of wireless technologies in education.

characterIstIcs of mobIle devIces wIth wIreless technologIes The push for wireless technologies brings learning opportunities with numerous possibilities. The mobility that wireless technologies offer makes the entire campus become a learning environment. Currently, the common devices of wireless technologies in educational use today include the following mobile devices: the PDA (Personal Digital Assistant), the laptop computer, and the TabletPC. These mobile devices and the wireless network are extremely complimentary. The PDA is a handheld device providing numerous functions for personal or business use, such as computing and information storing,

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retrieving, and organizing. Compared to other mobile devices, the PDA is thin, small, and mobile, and it can connect to the Internet through Wi-Fi, or communicate with another PDA through infrared. The cost of the PDA is relatively small compared to other mobile devices, which helps make 1:1 student-to-computer ratios affordable (CTL, n.d.). The criticism of the use of a PDA for learning purposes centers on its limited screen and inconvenient input method. Learners have to use a stylus to write letter-by-letter on the tiny screen, or install an expensive external keyboard in order to input data. Connecting to a desktop or laptop is still necessary in order to fully utilize the functions of the PDA. The laptop is a portable computer that provides almost the same functions as a desktop. Compared to a desktop, a laptop is easy to carry; however, it is difficult to use on the move (Wood, 2003). Although a laptop is compatible with the wireless network, the batteries on some models are weak, and a power cord is required in order to use them for long periods of time, which means that mobility is indeed limited. The TabletPC is an adaptation of the laptop. TablectPCs are equipped with large and touchsensitive screens. Users can draw larger graphics or make notes on the screen directly with a stylus, which is a vast improvement for inputting data. For example, compared to a laptop, a TabletPC easily allows one to illustrate scientific charts, mathematical notations, or diagrams. Besides, these drawings can be saved into JPEG-compressed format, which is a common used file format to optimize images and makes sharing files with others more convenient. The TabletPC provides docking stations and infrared keyboards so the users can decide how to assemble their TabletPC to accommodate different learning environments. The common feature of these devices is mobility. In a wireless environment, users can remain connected to the Internet with the mobile devices regardless of the geographical constraint, which

Wireless Technologies in Education

allows instructors to integrate these devices in various educational settings and to assign diverse tasks. Based on their educational needs, learners can use the peripheral extensions of mobile devices to connect to digital cameras, GPSs (global positioning systems), or other modules to make them more versatile and enrich their learning experiences.

2.

opportunItIes generated by ubIQuItous computIng In educatIon The convergence of wireless technologies and mobile devices provides new possibilities to enable ubiquitous learning. In addition, instructors can design learning activities that are less dependent on locations (e.g., libraries or computer labs). Current researchers (Chang, Sheu & Chan, 2003; Roschelle, 2003) have identified the following types of learning activities that accommodate wireless technologies and mobile devices, and which have a great potential to enable both collaborative and individual learning. 1.

Data gathering: Gathering and analyzing data is a critical activity for field trips. The University of Michigan combined the TabletPC, wireless networking GPS into the GeoPad to support students in gathering geological data collaboratively during a field trip, and to visualize the data gathered by the whole group immediately (Russell, 2004). The other successful project was conducted by the University of Berkeley, and encouraged learners to aggregate data collaboratively on an observational activity, then use a Web-based Inquiry Science Environment (WISE) to grasp difficult scientific concepts (Aleahmad & Slotta, 2002). In these research activities, mobile devices provided necessary mobility, and the wireless network offered a channel for an individual learner

3.

4.

to observe data contributed by the group. Learners could analyze and interpret results collaboratively after gathering the data. Instant feedback: Instructors can gauge students’ level of understanding by sending out questions, and asking them to reply immediately and anonymously after delivering the instructional content. Similarly, instructors might require students to participate in polling to share their ideas with the whole class or to gather the consensus (Fallon, 2002). Along this line, Mazur (1997) conducted research on the implementation of wireless devices during the class itself. The instructor gave students a multiple-choice question and collected their individual responses via wireless devices. Once students saw the result of polling from the whole class, they had to discuss the answer with a peer to correct their misconceptions and then respond to the question again. This strategy has been described as “peer instruction.” Participatory simulations: This is a group activity requiring each student to act as an individual unit to contribute data through the wireless network and then to observe the overall phenomena. Many simulation scenarios have been designed in which students may participate, such as virus and traffic jam simulation (Colella, 2000). Such activities are commonly seen when learning science concepts. Guiding systems: A mobile device equipped with guidance systems helps learners go through the learning environment (such as a museum) individually, while still receiving thorough explanations of the exhibits at hand (Chang et al., 2003; Smordal & Gregory, 2003). When learners are approaching the specific exhibit, the infrared signal senders installed on the exhibit will automatically activate their devices and display information. This type of activity is commonly seen in informal or lifelong learning settings.

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Issues of IntegratIng wIreless technologIes In educatIon As we move toward a more seamless synergy of the wireless network and mobile technologies, we continually face new challenges regarding the implementation of these cutting-edge technologies in education. In order to maximize the effectiveness of wireless technologies in learning, it is suggested that teachers should investigate available applications and pedagogies for integrating wireless technologies, especially the strategies of supporting collaborative learning. Furthermore, teachers will be burdened with technology training, designing lesson plans, and evaluating the results of implementation, which will take a lot of time from their regular classroom teaching. Advanced technologies are not a panacea. In addition, teachers’ attitudes and skills for adapting and handling innovations need to be taken into account to find the best balance, in order to best leverage wireless technologies for learning. The advantages of the wireless network can be abused by students, so teachers have to be aware of distraction allowed by this technology. Students may play games, engage in sending instant messages, browse non-relevant Web sites, or e-mail friends, while ignoring the lectures or activities that the teacher assigned during the class (Yuen & Yuen, 2002). Some schools use the firewall to prevent the use of certain applications or resources, such as chat rooms and inappropriate Web sites, and protect the security of system and private databases, which may result in adding more steps to the procedure or placing limitations on utilizing these technologies. In short, teachers have to pay more attention to their classroom management in order to prevent the side effects possible with introducing wireless technology into the classroom. The mobile devices that support wireless technologies are versatile in information display formats, input methods, operating systems, ex-

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pansion modules, and supportive applications. Therefore, when deciding on adapting a specific learning technology, teachers are facing a pool of possibilities. However, the lack of common platforms or standards across these technologies may cause problems for designing and implementing learning activities, and teachers may confront dilemmas when some new applications will work with old technologies, but not vice- versa. The fast-moving technology might make current technologies out of date very soon, and researchers and instructional technologists need to be aware of promising possibilities and compatibilities of newer technologies.

conclusIon Wireless technology has been penetrating both K-12 and higher education because of its mobility, connectivity, and promotion of learning on demand. Both practitioners and researchers have increasingly emphasized the potential of implementing wireless technologies in learning environments. PDAs, laptops, and the TabletPC have been adopted as essential learning tools in the wireless network environment; in the meanwhile, the combination of wireless technologies and mobile devices has been leveraging the impact of the computer on learning. However, all this does not guarantee a successful learning experience. As wireless technologies become more widely utilized in the learning environment, teachers have to pay more attention to preventing students’ distractions that can result from using these technologies, and spend more time on investigating and implementing appropriate pedagogies. In order to use the wireless technologies effectively, teachers need to consider the goals and objectives of the course, students’ prior knowledge and computer skills, and the propensities of mobile devices to engage students in meaningful learning activities.

Wireless Technologies in Education

references Aleahmad, T. & Slotta, J. (2002). Integrating handheld technology and Web-based science activities. Proceedings of the World Conference on Educational Multimedia, Hypermedia and Telecommunications (pp. 25-30). Boerner, G. (2002). The brave new world of wireless technologies: A primer for educators. Syllabus, 16(3), 19-20, 22, 30. Retrieved April, 1, 2004, from http://www.syllabus.com/article. asp?id=6771 Center for Technology in Learning (CTL). (n.d.). Wireless Internet learning devices (WILD). Retrieved April, 1, 2004, from http://ctl.sri.com/ projects/displayProject.jsp?Nick=wild Chang, Y.C., Sheu, J.P. & Chan, T.W. (2003). Concept and design of ad hoc and mobile classrooms. Journal of Computer Assisted Learning, 19, 336-346. Colella, V. (2000). Participatory simulations: Building collaborative understanding through immersive dynamic modeling. Journal of the Learning Sciences, 9, 471-500.

Kranz, M. (2002). Broadband comes to the schoolroom. School Planning and Management, 41(5), 32-36. Mazur, E. (1997). Peer instruction: A user’s manual. Edgewood Cliffs, NJ: Prentice-Hall. Prakash, N. (2001). Wireless wide area networks for school districts. National Clearinghouse for Educational Facilities. Retrieved April, 1, 2004, from http://www.edfacilities.org/pubs/wireless. pdf Roschelle, J. (2003). Keynote paper: Unlocking the learning value of wireless mobile devices. Journal of Computer Assisted Learning, 19, 260-272. Russell, H. (2004). GeoPad hits the road: Rugged TabletPC gets workout from U-M Student. Advanced Image, 1. Retrieved April, 1, 2004, from http://www.advancedimagingmag.com/ai/script/ search.asp?SearchSiteURL=/ai/articles/newsletters/2004/0104/0104_nfb.htm Smordal, O. & Gregory, J. (2003). Personal digital assistants in medical education and practice. Journal of Computer Assisted Learning, 19, 320-329.

CyberScience Laboratory. (2003). Introduction to the 802.11 wireless network standard. Retrieved April, 1, 2004, from http://www.nlectc.org/pdffiles/introduction_to_802.11_networks.pdf

Wangemann, P., Lewis, N. & Squires, D.A. (2003). Portable technology comes of age. THE Journal, 11. Retrieved April, 1, 2004, from http://www.the journal.com/magazine/vault/articleprintversion. cfm?aid=4567

DiGiano, C., Yarnall, L., Patton, C., Roschelle, J., Tatar, D. & Manley, M. (2002). Collaboration design patterns: Conceptual tools for planning for the wireless classroom. In Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (pp. 39-47).

Wood, K. (2003). Introduction to mobile learning. Technology for e-learning. Retrieved April, 1, 2004, from http://ferl.becta.org.uk/display. cfm ?page=65&catid=192&resid=5194&p rintable=1

Fallon, M. (2002). Handheld devices: Toward a more mobile campus. Syllabus, 16(4). Retrieved April, 1, 2004, from http://www.syllabus.com/article.asp?id=6896

Yuen, S. & Yuen, P. (2002). Handheld computing in education. Proceedings of the World Conference on E-Learning in Corporations, Government, Health, & Higher Education (pp. 2442-2447).

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key terms Infrared (IR): A wireless technology that enables short-range communication between senders and receivers through beaming. The signal goes straight, and will not go through walls. M-Learning: Mobile learning, or integrating mobile devices such as PDAs, laptops, and TabletPCs into the learning environment, in order to communicate through the wireless network. Mobile learning has a great potential to provide effective collaborative or individual learning experiences. Radio Frequency (RF): Refers to the use of radio carrier waves to transmit a broadcast signal. RF is essential in wireless communication, such as broadcast TV and GPS (Global Positioning System). Simulation in Education: Simulation is an application used to imitate real-life events. Real-life events are very complex; the more sophisticated the simulation application, the more representative the simulation. The leaner can use the application to manage the event by manipulating factors and observing the results of simulation, thus realizing the impact of each factor on the simulation. It is difficult for the teacher to show learners real-

life events, and simulation application provides the best opportunity for learners to understand abstract scientific concepts, such as virus reproduction or organization management. Ubiquitous Computing: Includes computers everywhere, the wireless technologies wave, and various portable and networked technologies in our daily lives. Ubiquitous computing can help to create an “anytime, anywhere” learning environment that learners, teachers, and parents can access easily. Ubiquitous computing has been changing the way teachers and students utilize technologies in the classroom. Wireless Fidelity (Wi-Fi): Any 802.11 products (including 802.11b, 80.211a, and 802.11g). This term is promulgated by the Wi-Fi Alliance. Wi-Fi offers broadband access without the physical restraint, and the users can accis installed, for example, in a coffee shop. Wireless Local Area Network (WLAN): A wireless network installed in a local area such as a building. Wireless Wide Area Network (WWAN): A wireless network that extends over a large geographical area by utilizing such devices as satellite dishes or antennae.

This work was previously published in Encyclopedia of Distance Learning, Vol. 4, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P. L. Robergs, and G. A. Berg, pp. 2051-2055, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.14

Multiple Internet Technologies in In-Class Education Mihir A. Parikh University of Central Florida, USA Neeraj Parolia University of Central Florida, USA

IntroductIon The Internet has a symbiotic relationship with academia. The Internet sprung from and is continually improved by academic research. In parallel, the Internet is also changing the way academia provides education and training. Most universities now disseminate administrative information to students through the Internet. However, despite this recent upsurge in the adoption of the Internet, educational institutes have yet to fully utilize the power of various Internet technologies. Other than the Web, educational institutes have largely ignored various Internet technologies, which can aid students in the learning process. We have to go beyond the Web and leverage multiple Internet technologies to support in-class education. Alternate Internet technologies have to be integrated under a unifying framework to make classroom-based education more efficient and effective. We need to deploy a right combination of multiple Internet technologies with appropriate

teaching methods and instructional material to improve education (Huang, 2001; Mahoney, 1998; Spooner et al., 1998; Sumner & Hostetler, 1999). Web-only education support has several inherent problems. We have to deploy the framework to alleviate these problems and improve learning effectiveness yielded by the new methodology.

early experIences wIth the web The Internet can provide valuable contributions to all three learning environments listed in Table 1. In the computer microworld environment, it can help distribute, maintain, and update training software and educational modules. In the classroom-based learning environment, it can help distribute course material, such as lecture notes and assignments, via course Web sites and provide e-mail-based communication between the instructor and students. In the virtual learning environment, it can

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Multiple Internet Technologies in In-Class Education

Table 1. Classification of learning environments by Wilson (1996) Computer microworld: Self-contained computer based learning environment Classroom-based learning environment: Traditional educational setup involving students and teacher. Virtual learning environment: Telecommunications-based learning environment in which students are dispersed over large geographic area

• • •

replace the traditional telecommunications-based video conferencing network with a ubiquitous, multimedia network. When the Web is used to support classroom instruction, several problems emerge. Some of these problems are listed in Table 2. These problems create disappointment and prompt several instructors to reduce the use of the Web in their courses. To lessen these problems, off-the-shelf software products, like WebCT, TopClass, and BlackBoard, are used. However, at the time of this study, they also had their own problems such as server-based content management; they require efforts on the part of the student to check the Web site regularly and offer no support for off-line browsing. They also require reformatting of the content developed through commonly used software like Word and PowerPoint. While they

do help technologically-challenged instructors to easily develop and maintain course Web sites, they do little to eradicate most of the above problems. We have to look for an alternate solution.

IntegratIng Internet technologIes The above problems relate primarily to the inherent limitations of the Web and insufficient utilization of other Internet technologies. It is easy to put documents on course Web sites, but leveraging the full potential of the Internet requires integrating visual, aural, and textual material and providing nonlinear access to course material (Baer, 1998). Different Internet technologies will play an increasingly important role in the universities of the future (DosSantos & Wright, 2001). This leads to the development and utilization of a novel, integrative model to support education (Figure 1, adapted from Parikh & Verma, 2002). This model goes beyond the Web to provide a unifying framework that can integrate and leverage various Internet technologies, such as the Web, FTP, chat, security, and Internet-based database in supporting education in the classroom-based learning environment. It has three main modules: central repository, which stores student

Table 2. Problems with using the Web Untimely review of material: The instructor regularly updates lecture notes and assignments on course Web sites, but they are not regularly reviewed by all students. No confirmation loop: The instructor does not always know who has reviewed the material and who has not. Wastage of classroom time: Significant portion of the classroom time goes in discussing and resolving technical problems. Wastage of instructor time: The instructors usually spend substantial amount of time outside of class to develop and maintain course Web site and provide technical support to their students.

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Lack of interactivity: Interactivity needed for many learning activities and methods, such as group discussion, case study analysis, and real-time questions and answers are not welldeveloped on course Web sites. High cost, no reward: Substantial costs are involved in developing Internet-compatible course material, in terms of time and efforts, but it brings little monetary or professional rewards for the instructor. Varied behavioral response: Some students display support for the new support technologies, while some students resist it.

Multiple Internet Technologies in In-Class Education

Figure 1. Integrating multiple Internet technologies Internet technologies

Web, FTP, Push, Chat, WAP, Security, XML, Internet-based Database

Instructor

Local Replicated Database

Student

Interface

Interface

Instructor Support Modules

Student Support Modules

Comm. Protocol

Comm. Protocol

Instructor Client

central repository

Local Replicated Database

Student Client

Student Profiles, Course Information, Lecture Notes, Discussion Archives, Shared Documents, FAQ, and Software Updates

On the University Server

Table 3. Advantages of the framework Collaborative environment: Provides a collaborative environment, to facilitate free and easy interaction among students Instructor visibility: Increases the visibility of instructors among students through synchronous and asynchronous communication. Confirmation loop and timely feedback: Enables the instructor to track whether a student has reviewed the assigned material or not; timely feedback is provided to the needy students Increase in efficiency: Reduces overall time spent by instructors in managing the course. Reduced unnecessary meetings: Unnecessary student-instructor interactions are reduced because of FAQ and threaded discussion group databases. Utilization of preferred technology: Enables the instructors to upload lecture notes and other course information in the original format.

and course-related information; instructor client, which assists the instructor in managing course information and administering the course; and student client, which assists students in accessing course information. Various Internet technologies connect these three modules and help perform information exchange task required for effective education.

Secure delivery: Enables secured delivery of course information, a significant part of which is usually an intellectual property of the instructor. Mass customization: Using student profiles developed through the interactions with students, individual students are targeted with content customization Ease of use: System modules are very simple to install and easy to use. Ease of maintenance: Push technology enables automatic transfer and installation on all clients without knowledge of instructors or students. Empirical findings: In an empirical test, the system was found to be user friendly, to be useful, to increase convenience for students, and to provide accurate information which conformed to the needs of students in a timely manner.

new educatIon support system Based on this model, a new easy-to-use education support system was developed and utilized it in eight sections of various types of courses in three semesters. It was found that the new system was more advantageous in supporting all three types of learning activities (pre-, in, and post-class activities). The observations are in Table 3.

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future trends Technology has become an integral part of learning environments. Computer hardware and software technologies provide support in computer microworld type learning environment and communications technologies provide support in the virtual learning environment. The model described previously was designed primarily for the classroom-based educational environment, but it can also be extended to the other two learning environments to simulate an interactive learning platform through synchronous and asynchronous interactivity. On the technology front, two types of technologies are expected to have significant growth and influence in the upcoming years, peer-to-peer (p2p) technologies (e.g., Gnutella, Kazaa, etc.) and wireless combined with handheld technologies. These emerging technologies can also be utilized in the context of education under the same model discussed previously, as these technologies become omnipresent in the student community. Such technologies will involve multiple types of student client modules for various hardware types. However, all of these modules will synchronize with the single student profile stored on the central repository and replicated to all clients of the student. These technologies will further increase interactivity, facilitating the creation and sustenance of virtual communities that foster social relationships among the learners. These communities will further blur the boundaries of space and time within which education has been taking place. Learning is not limited to the confines of academic institutions. Studies have shown that learning continues even in adulthood as individuals always adapt and learn through experiences (McCall et al., 1988). While the academic institutions are not yet at the stage of abandoning traditional degrees and adopting “learning contracts,” they are preparing for the “life-long learning” as Alvin Toffler predicted. In close collaboration with

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corporations, they are embracing e-learning as a form of continuing education. Charles Handy (1989), a famous management guru, has foreseen that corporations would increasingly resemble universities or colleges in the years to come. We are already witnessing the beginning of this effect. U.S. corporations are spending over $60 billion annually on education with the growth of average 5% over the past decade (Prewitt, 1997). To benefit most from these efforts, going beyond the Web and leveraging all available technologies is necessary. The model discussed in this article can be the first right step in that direction.

conclusIon Internet will bring about significant change in all aspects of education and training over the next decade (Aniebonam, 2000; Brandon & Hollingshead, 1999). A number of other users of Internet technologies to support university courses have suggested that they can be very effective (Jones & Rice, 2000; Stith, 2000). As the Internet is being increasingly integrated in education, it is imperative that we understand the limitations of using only one Internet technology, the Web. The Web is a powerful medium for delivering content or transferring knowledge. However, the core competency of educational institutions is developing knowledge, which can be done through intricate and robust networks and communities of students that last beyond the formal degree (Brown & Duguid, 1996). The Web falls short in this respect, probably because it is too broad and too open. To provide more effective platform to support learning, we have to look beyond the Web. Many new Internet-based technologies have emerged recently and new ones continue to surface time and again. These technologies can provide complementary support to various educational activities that are not effectively supported by the Web. This article presented a case study of a

Multiple Internet Technologies in In-Class Education

system that integrated multiple Internet technologies, including the Web, to support learning. The system was indigenously developed with built-in flexibility to adapt to various types of courses. Further development and deployment of systems like this will provide the next frontier and drive the educational effort in the coming decades.

references Aniebonam, M.C. (2000, October). Effective distance learning methods as a curriculum delivery tool in diverse university environments: The case of traditional vs. historically black colleges and universities. Communications of the Association for Information Systems, 41–33. Baer, W.S. (1998). Will the Internet transform higher education? The emerging Internet: Annual review of the Institute for Information Studies. Aspen, CO: The Aspen Institute. http://www. aspeninst.org/dir/polpro/CSP/IIS/98/98.html Brandon, D.P., & Hollingshead, A.B. (1999, April). Collaborative learning and computersupported groups. Communication Education, 48, 109–126. Brown, J.S., & Duguid, P. (1996). Universities in the digital age. Change, 28(4), 11-19. DosSantos, B., & Wright, A. (2001). Information Services and Use, 21(2), 53-64. Handy, C. (1989). The age of unreason. Boston: Harvard Business School Press. Huang, A.H. (2001). Problems associated with using information technology in teaching: A research proposal. Proceedings of the Seventh Americas Conference on Information Systems (pp. 39-40). Jones, N.B., & Rice, M. (2000). Can Web-based knowledge sharing tools improve the learning

process in an MBA consulting class? The Journal, 27(9), 100–104. Mahoney, J. (1998). Higher education in a dangerous time: Will technology really improve the university? Journal of College Admission, 24(3), 161. McCall, M.W., Jr., Lombardo, M.M., & Morrison, A.M. (1988). The lessons of experience. Lexignton, MA: D.C. Heath. Parikh, M.A., & Verma, S.A. (2002). Utilizing Internet technologies to support learning: An empirical analysis. International Journal of Information Management, 22(1), 27-46. Prewitt, E. (1997, January). What managers should know about how adults learn? Management Update, 2, 5. Spooner, F., Spooner, M., Algozzine, B., & Jordan, L. (1998). Distance education and special education: Promises, practices, and potential pitfalls. Teacher Education and Special Education, 21(2), 121-131. Stith, B. (2000). Web-enhanced lecture course scores big with students and faculty. The Journal, 27(8), 20–25. Sumner, M., & Hostetler, D. (1999). Factors influencing the adoption of technology in teaching. Proceedings of the Fifth Americas Conference on Information Systems (pp. 951-953). Wilson, B.G. (1996). Constructivist learning environments: Case studies in instructional design. Englewood Cliffs, NJ: Educational Technology Publication.

key terms FTP: A protocol used to transfer files over a TCP/IP network (Internet, UNIX, etc.).

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Handheld Technology: A computing device that can be easily held in one hand while the other hand is used to operate it. Peer-to-Peer (P2P) Technology: Often referred to simply as peer-to-peer, or abbreviated P2P, a type of network in which each workstation has equivalent capabilities and responsibilities. Push Technology: A data distribution technology in which selected data are automatically delivered into the user’s computer at prescribed intervals or based on some event that occurs. Replicated Database: A regular database in which tables, queries, and reports cannot be modified in design. Video Conferencing: A video communications session among three or more people who are geographically separated.

Virtual Communities: A group of individuals who share a common interest via e-mail, chat rooms or newsgroups (threaded discussions). Members of a virtual community are self-subscribing. WAP: A standard for providing cellular phones, pagers and other handheld devices with secure access to e-mail and text-based Web pages. eXtensible Markup Language (XML): An open standard, developed by the W3C, that involves formal syntax for adding structure and/or content information in a Web-based document. This subset of SGML defines data elements in a neutral way for easy interchange of structured data, such as mark-up tags, definitions, transmission validation, and interpretations across applications and organizations.

This work was previously published in Encyclopedia of Information Science and Technology, Vol. 4, edited by M. KhosrowPour, pp. 2069-2073, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.15

Change Management and Distance Education Parviz Partow-Navid California State University – Los Angeles, USA Ludwig Slusky California State University – Los Angeles, USA

IntroductIon E-learning is defined as the transmission of knowledge whereby the instructor and/or the student participate in the learning process from different places and/or different times (Henry, 2001). Many organizations have adopted e-learning as a way to make the learning process faster and better (Roshan, 2002). However, recent studies have revealed that about 85% of students participating in e-learning and distance education fall short of completing their program. Low completion leads to low retention, which leads to low performance (Land, 2002). The problem, exacerbated by rapid changes in information technology (IT), lies on the shoulder of the universities and the students. For universities, e-learning often is such a giant technological and managerial change that the faculty attempts to deal with it by scaling instructions down to merely automated text lectures with a primary focus on the delivery of instructional materials, rather than addressing the students’

needs. For students, e-learning is usually a short experience coupled with little-known technologies for which they need extra guidance and support that is more persistent. However, the challenge is how to employ this new technology and bring students the help they need when they need it (Gordon, 2003; Roberts, 2001). With constant changes in IT, higher education institutions are experiencing volatility and uncertainty in instructional methods. E-learning is the first to encounter these changes in IT. Rather than becoming overwhelmed and defensive, universities and colleges must implement strategies to aggressively respond to and sustain these changes. In reality, however, higher education institutions are often ill-prepared for proactive management of changes and are resorting to reactive, defensive responses to the IT changes, focusing on the situational procedural objectives rather than on the strategic educational goals (Austin, 2003). Introducing e-learning involves a shift in culture and requires a change in management (Faden, 2000).

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Change Management and Distance Education

Resistance to technology originates mainly from a fear of risk. IT impact is most obvious in e-learning. This chapter discusses how to overcome this resistance, principally in distance learning.

change management Change is the driving force of progress, but peoples’ reactions to change are often irrational and defensive. Thus, change management is an essential part of business evolution and advancement. According to Fred Nickols (2004), change management should focus on three issues: 1.

2.

3.

The task of managing change is internal but usually triggered by external factors. Changes prompted by implementation of e-learning practices must be anticipated in advance. However, universities often do not have any planned responses. E-learning is a highly specialized customeroriented business that requires methodological support; one important aspect of such support is to have a planned change management. A body of knowledge needs to have content and process. It is one thing, for instance, to introduce e-learning courses for professional advancement or continuing education in a corporate center or at a Continuing Education division. It is quite another to introduce a linked set of e-learning courses with prerequisites in an online university. It is yet again a different one to introduce a blended e-learning and traditional curriculum with prerequisite courses being either online or of the traditional type.

Generally, the scope of organizational change may vary from organization-wide to a narrow departmental or group level. Examples of organization-wide changes include modification of the organization’s mission, restructuring of

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operations, and introduction of new technologies and programs. E-learning should be viewed as an organization-wide transformation. Change should not be introduced for the sake of change—it is crucial to plan to achieve some overall goal. Usually, the most significant change in the way a higher education institution operates is motivation factors, such as substantial cuts or infusion of funding, technological innovations, actions by competitors and the need for dramatic increases in services. Change in curriculum will inevitably demand from the faculty a different style of instruction. Faculty training will be needed to overcome a lack of technical skills. Student services must be expanded to support e-learning as an experience equivalent to on-campus courses. Due to e-learning’s heavy dependency on technology, organized IT training and support for students are extremely important. Off-loading such support from the university IT help desk to instructors is a major deterrent for instructors who consider teaching online classes. The issues of copyright of one’s work and fair use of published materials that belong to others are challenging to online instructors, and may require updating of university policies and procedures. Above all, a change in the organizational culture is required when a vision and plan for the implementation of e-learning is realized. The all-too-familiar attributes of this process include a systematic approach to planning of organizational changes, faculty involvement, learning and adaptation to the new technologies, and shift of resources. As we mentioned earlier, introduction of change is typically met with strong resistance. Many of the faculty and staff may believe that the current situation is just fine and do not identify with the need for change. Others are intrinsically skeptical about change. Some doubt that there are sufficient resources to accomplish major organizational change. Often, there are conflicting goals in the institutions; for example, increasing resources to deal with the change, yet concurrently cutting

Change Management and Distance Education

costs to remain viable. Organization-wide change frequently is in opposition to the values cherished by members of the institution; that is, the change may contradict the faculty and staff’s thoughts of how things should be done. That is why much of organizational change literature discusses the changes needed in the culture of the organization, including changes in the members’ values and beliefs, and in the way they enact these values and beliefs (McNamara, 2004).

strategIc overvIew Strategic overview starts from the e-learning vision statement and a mission statement defined separately from the university’s overall vision and mission statements. To a large degree, e-learning strategic view is shaped by up-and-coming technologies. University administrators should envision the opportunities and challenges inherent in these changes and translate effectively into both planning and development of a long-term strategy for managing e-learning business. Many of these IT-driven changes have been already affecting day-to-day operations of educational institutions, but there is still a widespread lack of realization among administrative ranks of how comprehensive the imminent technological shifts and strategic challenges are. Strategic planning, which shows mapping technology trends into various online educational processes, will help provide a better understanding of this technological transformation in e-learning (Canton, 1999). The higher education mega-trends affecting e-learning are as follows (Butler, 2003): 1.

2.

Fundamental switch towards anywhere, anytime, transparent computing based on global networks will make highly interactive courses of the future more convenient and entertaining than in-class courses. Distance education enrollments offering both convenience and speed are soaring.

3.

Profit opportunities in e-learning are beginning to attract corporations and entrepreneurs who compete with universities in educating corporate employees: It takes fewer on-the-job lost hours and speeds up graduation. 4. Adult students are the fastest-growing educational demographic group, significantly affecting the educational culture of universities; they prefer part-time studies, demand more time flexibility and are market-driven in “shopping” for courses. 5. Rising tuition coupled with declining federal aid make the e-learning option more viable and appealing. 6. Education is transforming towards open market, where monolithic structures of oldfashion universities will be in competition with e-learning enterprises providing better customer service, faster completion of degrees and better curriculum quality more consistent with market demands. 7. Rising need for knowledge and skills to st manage the convergence of 21 century powerful computers, networks, biotech and nanotechnology will create the highest-yield opportunities for universities in educational market. 8. Every institution of higher education that wants to survive must learn to evolve into an e-business: communicating, servicing and delivering courses on the Web. 9. Real-time agility, how fast a university can embrace leading-edge technology, will determine the efficiency, speed and cost-effectiveness of its operations. 10. Learning to embrace technology innovation, risk taking and out-of-the-box thinking will st be critical for the 21 century universities. The evolution in the perception of university administration about how to optimally apply technology to meet strategies and attain targets is often much slower than the dynamics of tech-

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nological innovations. As a result, sluggishness in change management becomes a barrier on the way of technology implementation, although, for some businesses, technological conservatism is a way to ensure high operational reliability; educational institutions by their nature are proponents of innovations, including the technological ones. Consequently, institutions’ change management must be as dynamic as the changes in the subject matters and domains of knowledge being taught or researched. Change management is a fundamental actor in shaping the organization’s business strategies, policies and procedures. Like other major organizations, educational institutions are seeking ways to restructure and increase their flexibility and effectiveness in this climate of change. Change management affects not only the education providers, but the recipients as well. Educational excellence has become a moving target. While basic skills such as reading, writing and math will likely remain at the core of the curriculum, the abilities built on this foundation continue to change in our society. Focus on technology also can cause misplaced priorities. So far, the developers of e-learning academic programs have been preoccupied by the ease of use of technology, rather than the needs of learners. In part, these programs have been promoted as a way to reduce the universities’ costs. The main thrust has been on the development of generic material for students. This is logical, given the importance of cost savings, but it has resulted in a painful lesson for the profession. Developing generic Web-based courseware and making it available through the Internet while hoping that the learners will somehow absorb the material is not working. Short-term cost reductions can be attained that way, but with the exception of rare circumstances, longterm payback will not materialize. The e-learning process must be far more customized to the complex characteristics of the learning subjects, students’ skills and job market needs. E-learning is one component of a wider solution—“blended” learning. Researchers commonly

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agree that contrary to today’s static online courseware, e-learning will emerge with more specific dynamic content, driven by better authoring programs and supported by tools for measuring the e-learning progress against specific learning objectives. Additionally, the acceptance of standards for e-learning content will be a vital step in allowing the content to be transferred between organizations. This will encourage collaboration and cooperation between different faculty to produce better and more suitable content (Sloman, 2002). Three factors characterize the results of the e-learning process: speed, ease and durability of knowledge acquisition. An interesting aspect of change needed to speed up the knowledge acquisition is the “miniaturization” of e-learning components. These components are content simplification, effortless presentations and ease of reusability and re-packaging. Technology is clearly the vehicle for performance acceleration in e-learning knowledge acquisition. Ultimately, the success in developing a highly effective workforce comes from aligning the strategic intent with people, processes and technology. E-learning components will be useless unless the culture within the organization rewards knowledge sharing and personal development (Brokbank, 2002). Finally, it is important to recognize the complexity and diversity of various universities and colleges. E-learning is not a ‘one-size-fits-all’ solution. Each university and college has unique business, human resource and technology environments. An e-learning strategy should assess the appropriateness of the process and the program to the organization. It should define how e-learning could enhance the teaching process (D’Druz, 2002).

strategIes for ImplementIng organIzatIon-wIde change The strategy of change in e-learning resembles some of the aspects of strategic change in busi-

Change Management and Distance Education

ness enterprises. Learning and adaptation process leading to strategic change can be described as consisting of four steps (LSI, 2004): 1.

2.

3.

4.

Strategic analysis: Determines the organization’s effectiveness and efficiency in meeting its present strategic objectives and fulfilling the mission of the organization Strategic direction: Based on mission, goals, objectives, and dominant and distinctive strengths/competencies Strategic change plan design: A roadmap for how to move from the current strategic orientation to the desired future position, considering educational alliances, the intrinsic character of the educational institution and its readiness to support transition to e-learning environment Strategic change plan implementation: Assigns responsibilities based on individual motivation and group dynamics for organizational change issues such as alignment, adaptability, participation, teamwork, success measurements and e-learning review activities

Successful change must involve top administrators and a champion who initially instigates the change by being visionary, convincing and unswerving. At the same time, the Strategic Change Plan for e-learning implementation should not ignore people who have a conscientious objection or differing perceptions of fundamental changes in the role, mission and methods of higher education that prevent them from playing an active role in a new technology-based method of teaching. These people are referred to as the Core group. An organization becomes whatever its people perceive that the Core group needs and wants it to become (Kleiner, 2003). Educational institutions embrace all kinds of faculty and staff; some of them may be proponents of “conservatism” in education and simply be opposed to change. This can result from adapted or

assumed pedagogical concepts of the past, or from lack of exposure to better ways of doing things, or from slowness of decision making. Opposing opinions are unavoidable, and it is worthwhile to attempt to understand their position. However, this should not preclude an institution from going forward with what it determined is right. With the convergence of knowledge and methods, the convergence of opinions will come as well. To sustain change, the organizational structures of the university may need to be modified, including strategic plans, policies and procedures. It typically involves an “unfreezing, change and re-freezing” process. However, as Fred Nickols (2004) argues, “the beginning and ending point of the unfreeze-change-refreeze model is stability— which, for some people and some organizations, is a luxury.” In addition to IT-driven advances, constantly changing educational content further reduces stability of this model for e-leaning organizations. As in any human organization, the best approach to address resistance is through increased and sustained communication and education, particularly to the faculty that feels their professionalism is being questioned or challenged. When undertaking educational change, a combination of bottom-up and top-down change should be followed. Although the bottom-up component will slow implementation of changes, it will also result in less resistance than the top-down approach, as faculty can discuss issues and get a sense of ownership to the problems and the solutions. In the process of managing change, it is important for educational leaders to reward and celebrate success and milestones. Educational leaders should also ensure that there are no discrepancies between the rhetoric and how the university rewards faculty and staff. Educational leaders need to be prepared for the games people play and deal with them instantly. Game playing can be employed to slow down change, or to portray the appearance of change while maintaining the status quo. Before initiating

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a major change, university leaders must ensure that other key problem areas are addressed and improved before the change program commences. Examples would be to ensure the efficiency and reliability of the administration and communication systems. This would help cement the change and prevent other organizational problems from being used to distract faculty from embracing the change (Grant, 2003). In addition to the general guidelines listed above, there are a few other basic guidelines to keep in mind: •

•

•

•

• •

Display concern and care: Once it is clear who is losing what, losses need to be acknowledged (manager to subordinate and peer to peer) openly and sympathetically, even though these losses may be subjective. Communicate: Transparent and consistent communications from the top down, the bottom up, side to side, and peer to peer are critical to the success of organizations experiencing significant change. With changes, there is more ‘unknown’ than ‘known,’ and a cultural tendency to reduce communications until the picture becomes clearer is the worst thing managers could do. Use a consultant: Ensure the consultant is highly experienced in organization-wide change Obtain feedback: Get as much feedback as is practical from employees, including what they think the problems are and what should be done to resolve them Keep perspective: Stay focused on meeting the needs of the students and faculty Avoid safeguarding from change: Do not attempt to isolate the business from change; rather, expect, understand and manage it

One thing remains unanswered, however: Why should leaders care? One of the key characteristics of an organization experiencing significant change is that employees’ productivity falls significantly.

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Therefore, leaders need to understand what areas of their overall organization are faced with significant ‘loss’ and be committed to managing the resulting transitions to minimize the dip in productivity and efficiency that occurs (Austin, 2003).

conclusIon E-learning is a fast-evolving, Internet-dependent method of learning and education. Tight coupling between changes in IT and changes in e-learning provide opportunities and challenges. One of the main challenges is a rapid and perpetual change management. With the rapidly changing world of IT and e-learning management, success requires a clear vision, purpose and strategic direction. Change management methodology must include strategic direction and planning, communication and curriculum. Change management must also include instructional skills and resistance to change. Full realization of strategic aspects of change management discussed above is essential for the successful implementation and growth of an elearning system in the volatile and heterogeneous world of the Internet.

references Austin, J., & Currie, B. (2003). Changing organizations for a knowledge economy: The theory and practice of change management. Journal of Facilities and Management, 2(3), 229-239. Brockbank, B. (2002). Unleashing performance. Executive Excellence, 19(8), 10. Butler, D.W. (2003). Six higher education mega trends - What they mean for the distance learners. Newsweek, 142(9), 44. Canton, J. (1999). Techofutures: How leadingedge technology will transform business in the 21s t century. Carlsbad: Hay House Inc.

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D’Druz, D. (2002). Adopting e-learning? Then do it right. New Zealand Management, 49(2), 30-33.

Roberts, B. (2001). E-learning, new twist on CBT. HR Magazine, 46(4), 99-104.

Faden, M. (2000). Get ready for new training push: E-business. Information Week, 812, 812-817.

Roshan, V. (2002). How one corporation got a charge out of e-learning. Medical Marketing and Media, (2), 46-52.

Gordon, J. (2003). What’s stalling the e-volution. Learning & Training Innovations, 4(6), 25-30.

Sloman, M. (2002). Breaking through the e-barriers. T + D, 56(10), 36-43.

Grant, K. (2003). Making sense of education change at Thistle College: The existence of witchcraft, witches and shamans. The International Journal of Educational Management, 17(2/3), 71-84. Henry, P. (2001). E-learning technology, content and services. Education & Training, 43(4/5), 249-256. Kleiner, A. (2003). Core groups: a theory of power and influence for “learning” organizations. Journal of Organizational Change Management, 16(6), 666-683. Land, T. (2002). Future trends in e-distance learning; its impact on individuals and organizations in community. Proceedings of the Annual Quality Congress, 691-695. LSI. (2004). Leadership Strategies International. Strategic change consulting. Retrieved June 18, 2004 from www.innovation-workshops.com/strategic _change_consulting.htm McNamara, C. (2004). Basic context for organizational change. Retrieved June 18, 2004 from www. mapnp.org/library/mgmnt/orgchnge.htm Nickols, F. (2004). Change management 101: A primer. Retrieved June 18, 2004 from http://home. att.net/~nickols/change.htm

key terms Change Management: Change management is an organized application of knowledge, tools and resources that helps organizations to achieve their business strategy. Core Groups: Core groups stands for the repositories of knowledge, influence and power in organizations. Curriculum: A comprehensive overview of what students should learn, how they will learn it, what role the instructor is playing and the framework in which learning and teaching will take place. E-Learning: E-learning is the transmission of knowledge whereby the instructor and/or students participating in the learning process are in different places and/or at different times. Information Technology (IT): Information technology is defined as the use of hardware, software, services and supporting infrastructure to handle and deliver information using voice, data and video. Strategy: It is an elaborate and systematic plan of action to achieve a goal or objective.

This work was previously published in the Encyclopedia of Distnace Learning, Vol. 1, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P. L. Rogers, and G. A. Berg, pp. 218-223, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.16

Distance Education Delivery Carol Wright Pennsylvania State University, USA

IntroductIon The term distance education is used to describe educational initiatives designed to compensate for and diminish distance in geography or distance in time. The introduction of technology to distance education has fundamentally changed the delivery, scope, expectations, and potential of distance education practices. Distance education programs are offered at all levels, including primary, secondary, higher, and professional education. The earliest antecedents of distance education at all levels are found worldwide in programs described most commonly as correspondence study, a print-dependent approach prolific in geographic areas where distance was a formidable obstacle to education. As each new technology over the last century became more commonly available, it was adopted by educational practitioners eager to improve communication and remove barriers between students and teachers.

background Each developmental stage of technology incorporated elements of the old technology while pursuing

new ones. Thus, early use of technology involved telephone, television, radio, audiotape, videotape, and primitive applications of computer-assisted learning to supplement print materials. The next iteration of distance education technologies, facilitating interactive conferencing capabilities, included teleconferencing, audioteleconferencing, and audiographic communication. Rapid adoption of the Internet and electronic communication has supported enhanced interactivity for both independent and collaborative work, access to dynamic databases, and the ability for students to create as well as assimilate knowledge. The rapid and pervasive incorporation of technology into all levels of education has been to a significant degree led by those involved in distance education. Virtual universities have evolved worldwide to offer comprehensive degrees. Yet, the technological advances are a threat to those who find themselves on the wrong side of the digital divide. As distance delivery programs have increasingly incorporated technology, the term distance education has been used to distinguish them from more traditional, non-technology-based correspondence programs. As traditional resident higher education programs have adopted many of the technologies first introduced in distance

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Distance Education Delivery

education programs, the strong divisions between distance and resident programs have become increasingly blurred and have resulted in growing respect for distance education programs. In postsecondary education, technology-based distance education has gradually evolved into a profitable and attractive venture for corporations, creating strong competition for academic institutions. The involvement of the for-profit sector in the delivery of technical, professional, and academic degrees and certificates has, in turn, been a driving force in the renewed discussion of perennial higher education academic issues such as the nature of the learning and teaching experience; educational assessment; academic and professional accreditation; the delivery of student support services such as libraries, computing, and counseling services; and faculty issues such as promotion and tenure, workload, and compensation.

dIstance educatIon applIcatIons In the primary and secondary environment, distance education is a successful solution for resource sharing for school districts unable to support specialized subject areas, students with mental or physical disabilities who are temporarily or permanently homebound, students with difficulties in a traditional classroom environment, repeat students in summer-school classes, advanced-placement students who are able to access college-level programs, adults seeking to complete GED requirements, and the increasing numbers of families who choose a home-schooling option. In the college and university environment, distance education is an attractive option for adult and nontraditional students, students who need to be away from campus for a semester, or those who have difficulties scheduling required courses in resident programs. Distance education delivery options have become a common

dimension of almost all traditional institutions. For-profit entities are becoming a dominant force in the distance education arena as education evolves into a commodity, especially for advanced professional education and training, because of their ability to target the marketplace. With the certain need for continuing education and training across government, industry, business, higher education, and health care; the increasing affordability of technologies; and the growing demand for “just-in-time,” on-demand delivery, distance education promises to be the answer for those who want and need the learning experience and necessary content delivered to their desktops at home or at their place of employment.

technologIes supportIng dIstance learnIng Distance technologies involve transmitting combinations of voice, video, and data. The amount of bandwidth available determines the transmission capacity. More expensive, large-bandwidth systems include microwave signals, fiber optics, or wireless systems. Advanced distance education technologies include network infrastructures, real-time protocols, broadband and wireless communication tools, multimedia-streaming technology, distributed systems, mobile systems, multimedia-synchronization tools, intelligent tutoring, individualized distance learning, automatic FAQ (frequently asked question) reply methods, and copyright-protection and authentication mechanisms. The network architecture determines the extent and flexibility of delivery. Discrete systems for Web support, course postings, course delivery, collaboration, discussion, and student support services are being replaced by Web-based learning-management or course-management systems that fully integrate all dimensions of the teachinglearning experience. These systems are supported by a network of networks that include hardware,

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software applications, and licensing; they connect intranets and off-campus, regional, national, and international networks. Wireless networks are rapidly expanding on multiple levels, including smaller personal-area networks with increased speed, wireless local-area networks (WLANS/ WiFi) that serve confined spaces such as office buildings or libraries, metropolitan-area networks (WMANs) that connect buildings over a broader geographic area, and third-generation wireless cellular voice infrastructure that can transmit data. Internet 2 is a consortium of 206 universities in partnership with industry and government to develop and deploy advanced network applications and technologies, and it is a primary factor in the implementation of technological advances in distance and higher education. Another initiative, National LambdaRail (NLR), is composed of U.S. research universities and private-sector technology companies to provide a national-scale infrastructure for research and experimentation in next-generation networking technologies and applications, and to solve challenges of network architecture, end-to-end performance, and scaling. Distance education delivery systems are commonly divided into two broad types: synchronous or asynchronous. Synchronous delivery requires that all participants—students, teachers, and facilitators—be connected at the same time with the ability to interact, transmit messages, and respond simultaneously. Online chat, interactive audio, or videoconferencing provide real-time interaction. The requirement that all participants come together at the same time, however, increases time constraints and decreases individual flexibility. Asynchronous delivery defines the anytime, anywhere experience where all participants work independently at times convenient to them, and it includes methods such as online discussion boards, e-mail, and video programming. The absence of immediate interaction with the teacher or other students is often criticized because of the isolation of participants, but this

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is acceptable for certain content areas and for adult or self-motivated learners. Sophisticated course design often seeks to integrate elements of both synchronous and asynchronous methods to meet individual needs and course goals. The selection of effective technologies must focus on instructional outcomes, the needs of the learners, the requirements of the content, and internal and external constraints. Typically, this systematic approach will result in a mix of media, each serving a specific purpose. Multimedia tools are critical because of the need to compensate for the lack of face-to-face contact. Distance education uses media for dual purposes—to deliver information and convey subject content—and also to facilitate communication between students and teachers. This attention to emerging media has meant that distance education has often taken a leadership position in the adoption of technology and multimedia by the broader educational community. The definition of multimedia continually changes since new applications and technological advances result in a constantly evolving array of hardware and software, which allow audio and visual data to be combined in new ways. The personal computer, the Internet, authoring and editing software, and newer media such as wireless personal devices have created dynamic digital learning environments that facilitate interactivity, autonomous learning, assessment opportunities, and virtual learning communities. Multimedia packages that consist of suites of software applications facilitate the integration of state-of-the-art communication, collaboration, content-delivery, student-assessment, and course-management capabilities.

evaluatIon of dIstance educatIon programs Comprehensive evaluation must be an integral component of distance education programs. SWOT analysis, a critical component of the

Distance Education Delivery

strategic planning process, is an effective tool that helps to identify resources and capabilities, and to formulate strategies to accomplish goals. SWOT involves a scan of the internal and external environment, and identifies internal environmental factors as strengths (S) or weaknesses (W), and external factors as opportunities (O) or threats (T). Early efforts to evaluate distance education focused on the transfer of course content and found that, compared to traditional course delivery and face-to-face instruction, there is no significant difference. Future evaluation should examine more substantive and fundamental questions, such as the success in meeting stated learner outcomes, student-to-student interactions, teacher feedback, the development of learning communities, the incorporation of various learning styles, the development of effective teacher-training programs, the degree to which courses and programs are recognized in professional and employment arenas, the transferability of coursework across institutions, and enrollment and course-completion rates.

future trends: Issues and challenges Among the continuing challenges for distance education are online ethics, intellectual property and copyrights, faculty issues, institutional accreditation, financial aid, and student support services.

ethics in the online environment Ethical behavior and academic honesty among students is of concern in any educational environment, and the online distance environment lends itself to significant abuse. Strategies to discourage and identify such behaviors require advance planning and aggressive attention. Course design,

teaching techniques, and subscriptions to online services that help faculty detect plagiarism can be effective. Some useful approaches include designing assignments that are project based and focus on a task resulting in a product, and that require some degree of cooperation and coordination among students. Such products should incorporate students’ own experiences and emphasize the process rather that simply the end result. Assignments can rotate across different semesters so that they are less predictable. Assignments that consist of small, sequential, individualized tasks can ensure that students keep up with class readings and respond to class assignments. High levels of instructor and student interaction, frequent e-mail contact, and online chats can ensure participation. An electronic archived record of all correspondence permits the tracking of content and variations in a student’s writing style. All courses should include an academic integrity policy. In an electronic environment where downloading and cut-and-paste are routine habits of information gathering, instructors must directly address ethical issues concerning the submission of such materials as a student’s own work.

Intellectual property and copyright Internationally, intellectual property and copyright issues are regulated primarily by the World Intellectual Property Organization (WIPO) and the European Union (EU). WIPO, including 180 member states, aims to ensure that the rights of creators and owners of intellectual property are protected worldwide. EU is concerned with these issues with the objectives of enhancing the functioning of the single market and harmonizing rules to insure uniform protection within the EU. In a traditional classroom environment, faculty develop course materials, select appropriate readings, and develop a syllabus and curriculum for which they correctly claim intellectual property rights and ownership. Occasionally, this work is translated to textbooks for which faculty likewise

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maintain intellectual property rights. Conversely, in the online environment, institutions often claim either complete or partial ownership of the intellectual content because the work, when posted on the Internet, goes beyond the confines of the classroom; because online courses are often commissioned separately from standard employment contracts; and because the infrastructure supporting the transmission of the content is owned by the institution. The question of ownership is a divisive one, and debate continues; a resolution may found in varying formulas that divide royalties among faculty, departments and colleges, and research offices. Prior to the TEACH Act of 2002 (Technology, Education and Copyright Harmonization Act), using copyright-protected materials in a self-contained classroom in the United States was within fair use, but posting the same materials on a Web page with potential worldwide distribution exceeded fair-use guidelines. The limitation posed a severe handicap on U.S. distance education programs. In November 2002, the TEACH Act generally extended to non-profit, accredited institutions, for mediated instructional activities only, the same type of right to use copyright-protected materials that a teacher would be allowed to use in a physical classroom. TEACH expands existing exemptions to allow for the digital transmission of copyrighted materials, including through Web sites, so they may be viewed by enrolled students.

faculty Issues Whereas for-profit distance education institutions hire faculty with the express purpose of teaching specific courses, the climate and culture of traditional academic institutions often does not support distance education initiatives. Distance courses are frequently not included in a standard faculty workload, raising questions of faculty incentives and rewards. In cases where research institutions have promotion and tenure requirements that

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emphasize scholarship, service, and research at least as much as teaching, it is difficult for young faculty to commit to additional teaching assignments even if monetary compensation is provided. Even in universities and colleges where selected courses and programs are successful, limited institutional resources may prohibit program growth and diminish scalability. Beyond the usual skills required of instructors, distance education faculty must meet additional expectations. They must develop an understanding of the characteristics and needs of distant students, become highly proficient in technology delivery, adapt their teaching styles to accommodate the needs and expectations of multiple and diverse audiences, and be a skilled facilitator as well as content provider. They therefore require strong institutional support for course design and delivery, technical support, and colleagues with whom to share common interests and concerns.

financial aid Distance education students often have far fewer options for financial aid than do traditional students. Financial aid is often not available to students who are enrolled at school less than half time or who attend less than 30 weeks of instruction in an academic year; for courses that provide less than 12 weeks of instruction, examination, or preparation for examinations or that are not tied to standard course lengths such as semesters or quarters; or for courses offered by institutions where more than 50% of the students are distance learners or more than 50% of the courses are offered by computer, correspondence, or video. Such regulations, developed to curb abuses exacerbated by Internet diploma mills, are in direct contradiction to the flexibility and advantages offered by distance programs. In 1988, the United States amended the 1965 Higher Education Act to support a distance education demonstration program, still in progress, intended to study the factors that define quality distance education

Distance Education Delivery

experiences and to test the viability of increased financial support.

accreditation Accreditation has long been viewed as the vehicle to monitor the quality of educational institutions. Accreditation in countries outside of the United States is normally handled by ministries of education or other government entities. The Council for Higher Education Accreditation (CHEA), in conjunction with other higher education groups, is working to maintain and expand international accreditation and quality assurance. U.S. accreditation is offered through regional bodies or specialized professional or programmatic groups, and is complicated by overlaps between federal, regional, and state accrediting agencies. The rise of distance programs has increased the number of nationally accredited institutions, generally forprofit colleges and universities, whose students find that their courses are routinely not transferable to regionally accredited institutions. Students are sometimes able to persuade other schools to accept distance credits, but many do not. The dilemma demonstrates existing prejudice against distance education and is a serious deterrent to students, slowing the growth of online education. Recent discussion has suggested that the entire accreditation process be reviewed and restructured by the U.S. Department of Education.

student support services Distance students require many of the same academic support services offered to traditional students. Primary ones include academic advising and access to library and information resources. The professional associations for each of these areas (the Association of College and Research Libraries/American Library Association and the National Academic Advising Association/ Nacada) have developed standards to guide the

delivery of quality service to distance students. Such guidelines assure equitable treatment and are a mechanism to measure quality for accreditation. The best designed courses and programs can fail without careful attention to executing the myriad details required for program success. Examples include application and admissions processes, student orientation, course registration processes, course drops or deferrals, placement examinations, computer technical support, financial-aid support, disability services, general student advocacy issues, materials duplication and distribution, textbook ordering, and securing of copyright clearances.

conclusIon Distance education promises to become an increasingly pervasive and dominant force in educational delivery, accelerated by advancing communication and information technologies. It will help answer the demands for education within a digital information environment, the ever-increasing needs for continuing training on a global scale, and individual interest in lifelong learning. The expansion of distance education will likely force significant changes in the way more traditional education is delivered, and will in time be totally assimilated into the educational experience.

references Chien, C. (2003). Interactivity and interactive functions in Web-based learning systems: A technical framework for designers. British Journal of Educational Technology, 34(3), 265-279. D’Antoni, S. (Ed.). (2004). The virtual university models and messages: Lessons from case studies. Paris: UNESCO/International Institute

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for Educational Planning. Retrieved August 13, 2004, from http://www.unesco.org/iiep/virtualuniversity/home.php Discenza, R., Howard, C., & Schenk, K. D. (Eds.). (2002). Design and management of effective distance learning programs. Hershey, PA: Idea Group Publishing. DiStefano, A., Rudestam, K., & Silverman, R. (Eds.). (2004). Encyclopedia of distributed learning. Thousand Oaks, CA: Sage Publications. Heberling, M. (2002). Maintaining academic integrity in online education. Online Journal of Distance Learning Administration, 5(1). Retrieved August 13, 2004, from http://www.westga.edu/ %7Edistance/ojdla/spring51/herberling51.html Holzer, E. (2004). Professional development of teacher educators in asynchronous electronic environments: Challenges, opportunities and preliminary insights from practice. Educational Media International, 41(1). Instructional Technology Council. (2004). Distance education reports and abstracts. Washington, DC: Author. Retrieved August 13, 2004 from http://144.162.197.250/reports.htm#Costs%2 0for%20Distance%20Learning Internet 2. (2004). Retrieved August 13, 2004 from http://www.internet2.edu/ Johnston, J., & Toms Barker, L. (2002). Assessing the impact of technology in teaching and learning: A sourcebook for evaluators. Arbor, MI: University of Michigan, Institute for Social Research. Lynch, M. M. (2002). The online educator: A guide to creating the virtual classroom. New York: Routledge Falmer. Moore, M. G., & Anderson, W. G. (Eds.). (2003). Handbook of distance education. Mahwah, NJ: Lawrence Erlbaum Associates.

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National LambdaRail. (2004). Retrieved August 13, 2004 from http://www.nlr.net/ Potashnik, M., & Capper, J. (1998, March). Distance education: Growth and diversity. Finance & Development, 35(1). Retrieved from http://www.worldbank.org/fandd/english/0398/ articles/0110398.htm Rovai, A. P. (2003). A practical framework for evaluating online distance education programs. The Internet and Higher Education, 6(2), 109124. Salmon, G. (2003). E-moderating: The key to teaching and learning online (2nd ed.). London: Routledge Falmer. Taylor, J. C. (1999). Distance education: The fifth generation. Nineteenth ICDE World Conference on Open Learning and Distance Education, Vienna Austria. Retrieved August 13, 2004, from http://www.usq.edu.au/users/taylorj/publications_ presentations/1999vienna_ 5thGeneration. doc Technology, Education and Copyright Harmonization Act. (2002). U.S. Copyright Office. Retrieved August 13, 2004 from http://www. copyright.gov/legislation/pl107-273.html#13301 Threlkeld, R., & Brzoska, K. (1994). Research in distance education. In B. Willis (Ed.), Distance education: Strategies and tools, (pp. 41-66). Englewood Cliffs, NJ: Educational Technology Publications, Inc. Tiene, D. (2002). Addressing the global digital divide and its impact on educational opportunity. Educational Media International, 39(3-4), 211-222. Tiffin, J., & Rajasingham, L. (2003). The global university. London: Routledge Falmer.

Distance Education Delivery

key terms Asynchronous Distance Delivery: An anytime, anywhere experience where all participants work independently at times convenient to them and that include methods such as online discussion boards, e-mail, and video programming, and the implicit absence of immediate interaction with the teacher or other students. Audiographic Communication: A multimedia approach with simultaneous resources for listening, viewing, and interacting with materials. Audioteleconferencing: Voice-only communication via ordinary phone lines. Audio systems include telephone conference calls as well as more sophisticated systems that connect multiple locations.

Synchronous Distance Delivery: Requires that all involved—students, teachers, and facilitators—be connected and participating at the same time with the ability to interact and to transmit messages and responses simultaneously. Teleconferencing: Communication that allows participants to hear and see each other at multiple remote locations. Virtual Universities: Institutions that exclusively offer distance courses and programs, often on a global scale. Web Conferencing: Communication that allows audio participation with simultaneous visual presentation through a Web browser.

This work was previously published in the Encyclopedia of Multimedia Technology and Networking, edited by M. Pagani, pp. 219-225, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.17

One-to-One Video-Conferencing Education Hock Chuan Chan National University of Singapore, Singapore Bernard C.Y. Tan National University of Singapore, Singapore Wei-Ping Tan National University of Singapore, Singapore

IntroductIon Technologies have become a critical component affecting teaching and learning effectiveness. Technologies enable informal computer-mediated interaction among instructors and students, for example, through electronic mail or bulletin boards. The Internet has changed the dynamics of teaching and learning by enabling distance direct personal tutoring, whereby a tutor (a private or personal instructor) provides personal additional instruction and attention to a student. The cost of video-conferencing using standard personal computers and off-the-shelf software involves a low set-up cost and very low usage fee (local phone charges). Its low cost can lead to a proliferation of its use. Students are no longer physically constrained in their quest for tutors.

It is important to research the factors that may facilitate or hinder learning via Internet videoconferencing capabilities. A case study was conducted, through multiple data collection methods, with two tutors and three students in Singapore. The impacts of four critical factors (system characteristics, mode characteristics, social presence, and media richness) on the effectiveness of teaching and learning were studied. This study helps to fill a gap in knowledge that arises because prior studies tend to concentrate on big virtual classroom settings.

background Earlier studies on the use of information technology for education have focused on student usage

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

One-to-One Video-Conferencing Education

of learning software, or on group interactions. For example, Sankar et al. (1997) investigated two different ways of delivering lectures with video-conferencing, without any instructorstudent interaction. There are very few studies on one-to-one distance education. Graesser and Person (1994) found that the quality of student questions was correlated with grades in one-to-one tutoring sessions on mathematics. It was found that collaborative problem solving, prompt question answering, and clarity of explanation using examples contributed significantly to learning effectiveness (Graesser et al., 1995). Hume et al. (1996), studying one-to-one tutoring effectiveness, found that hints encouraged students to engage in active cognitive processes that promoted long-term retention and deeper understanding. Chi (1996) found that certain types of interaction between tutors and students, during one-to-one tutoring sessions, could produce deep learning. The body of literature on one-to-one distance education motivates this research effort in two ways. First, like all the existing studies, this study seeks to identify factors that may enhance the effectiveness of teaching and learning in such an environment. In this study, effectiveness is measured by asking instructors to indicate their perceived ability to teach and asking students to indicate their perceived ability to learn via distance education, relative to traditional face-to-face education sessions. Second, while the results of all the existing studies alluded to the importance of

communication between the tutor and the instructor, this issue has never been directly investigated. Therefore, this study focuses on identifying factors that may impact the communication process between the instructor and the student, thereby affecting distance learning effectiveness. One-to-one distance education is examined in the context of desktop video-conferencing because the economy and prevalence of desktop video-conferencing facilities are likely to make it a dominant mode of distance education in the future (Rhodes, 2001). Table 1 presents four critical factors that can affect the success of using desktop video-conferencing facilities for education.

system characteristics Every desktop video-conferencing facility has both hardware and software components. A digital camera and a video card (in some products) are needed to capture images. A microphone, a sound card, and speakers are needed to capture and project voices. Many windows are needed to display the captured images (of the tutor or the student), the chat window, and other applications such as Word. In addition, the software should facilitate document sharing. Bandwidth limitations on the Internet and processing speed could lead to grainy pictures and a lack of synchronization between video and audio signals (Tackett, 1995), thereby affecting teaching and learning effectiveness.

Table 1. Factors affecting teaching and learning effectiveness Factor System characteristics Mode characteristics Social presence Media richness

Key aspects of factor Hardware, software, and bandwidth Usefulness, challenge, attractiveness, and clarity Sociability, warmth, and personal focus Multiple cues and interactivity

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mode characteristics Four key perceptual characteristics of a mode of instruction determine its effectiveness: usefulness, challenge, attractiveness, and clarity (Champness & DeAlberdi, 1981; Sankar et al., 1995). Usefulness refers to how much the mode of instruction is perceived to be appropriate for the learning task. Challenge is the extent to which the mode of instruction is able to facilitate learning of difficult concepts. Attractiveness is the extent to which the mode of instruction is perceived to be lively, exciting, and interesting. Clarity refers to the extent with which the mode of instruction is perceived to allow comprehensible communication.

social presence Social presence is defined as the extent to which a communication medium allows the actual physical presence of the communicating partners to be conveyed, and how far it allows communicating parties to socialize with each other, feel the warmth of each other, and exchange messages that are personal in nature (Markus, 1994; Short et al., 1976). Short et al. (1976) rank the following five communication media in order of decreasing social presence: face-to-face, television, multispeaker audio, telephone, and business letter. The literature suggests that desktop video-conferencing may enable people to transmit more warmth and sociability than the telephone. Video images can help people who have just met recently to become more familiar with one another (Czeck, 1995). Facial signals can allow the instructor to assess student understanding.

media richness Media richness is defined as the extent to which a communication medium can facilitate shared understanding (Daft et al., 1987). Rich media enable people to overcome equivocality, the existence of

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different interpretations. Variables typically used to gauge media richness include multiple cues and interactivity. Trevino et al. (1987) provide this ranking, in decreasing order of media richness: face-to-face, telephone, and printed documents. Face-to-face meeting has interactivity and immediate feedback so that mutual understanding between communicating parties can be checked and differences in interpretations reconciled. This medium also carries visual, verbal, and textual cues. Printed documents have neither interactivity nor immediate feedback. Desktop video-conferencing facilities may be less rich than face-to-face meetings because interactivity may be lower (Rice, 1992). Interactivity between the instructor and the student is a critical success factor for distance education (Milhem, 1996; Millbank, 1994).

research methodology A case study research approach is appropriate for examining a phenomenon in its natural setting, and it leads to in-depth answers (Yin, 2002). A prior survey with undergraduates and high school students revealed that most of them had no experience with distance education via desktop-videoconferencing facilities (Tan & Chan, 1998). Since this mode of learning was relatively new, the case study research methodology was employed. Five subjects (two tutors and three students) volunteered for this study. All the one-to-one tutoring sessions involved two individuals interacting with each other. However, the primary interest of this study was to identify factors that influence the communication efforts of an individual (tutor or student), thereby impacting his or her ability to teach or learn. Prior studies on one-to-one tutoring sessions have also focused on the perceptions of an individual, rather than the interaction between two individuals (Chi, 1996). The two tutors were undergraduates from a large university. They each had about 2 years of experience with one-to-one

One-to-One Video-Conferencing Education

tuition in a traditional face-to-face context. The three students were attending high school. They had been receiving one-to-one tuition from the two tutors for a year at their respective homes. All the tutors and students had no prior experience with distance education of any kind. The topic of instruction was mathematics at a high school level. All tuition sessions were conducted using desktop video-conferencing tools and involved a tutor and a student. All personal computers used for desktop video-conferencing tuition sessions in this study were connected to the Internet via either a local area network or a 56 kbps modem. This speed was more reflective of distance education, where students and tutors are connected through the telephones. Microsoft NetMeeting was installed to facilitate communication. A digital camera and a video card were used to capture video signals. A microphone, a sound card, and two speakers were used to capture and project voice signals. For each subject (tutor or student), data from five such desktop video-conferencing tuition sessions were collected. To preserve the realism of the natural tuition context, there was minimal control over the instructional process and materials (Yin, 2002). Multiple methods for data collection including on-site observation, computer and video recording, and interviews were used (Miles & Huberman, 1994; Yin, 2002).

data analyses For each case, all the data were analysed for the four main factors (system characteristics, mode characteristics, social presence, and media richness) and perceptions of effectiveness in teaching or learning. Analysis results were verified with the subjects. The subjects also contributed additional insights and highlighted issues that were of particular concern to them. Overall, two subjects were in favour of the video-conferencing tutoring, while three provided unfavorable feedback. The

evidence suggests that subjects were affected by system characteristics. Those who experienced technical difficulties in starting up their systems and had more problems with visual and voice signals tended to form poorer perceptions of their tuition sessions. Although they were clearly frustrated when they encountered system problems, subjects were generally optimistic when asked to comment on the future of such applications. The results on mode characteristics suggest that subjects tend to have better perceptions of their tuition sessions if they could understand complex concepts through these means, or if the ideas exchanged were clear enough to them. Ways to enhance exchange of complex ideas include having “some methods to decompose a complex idea into several simpler ideas before communication” as suggested by a tutor. Overall, subjects felt this mode of education had increased their interest in mathematics because it was “interesting,” “amazing” and “fun”. Results on social presence and media richness suggest that subjects tend to form better perceptions of their tuition sessions if they could feel the presence of the other party, if they could send personal messages, or if they could get replies quickly. People who have developed shared understanding on how to work with each other through the new technology are less affected by changes in social presence and media richness (Lee, 1994). Therefore, tutors and students are likely to be able to free themselves from such restrictions if “we have enough experience with such tuition sessions”. It is evident from Table 2 that the four factors are reasonably good predictors of success with distance education employing one-to-one desktop video-conferencing. As each of these four factors improves, the overall experience is likely to be enhanced. Specifically, the strongest discriminatory factor for success seems to be media richness, while the weakest discriminatory factor seems to be system characteristics. Given their predictive power, these four factors could serve as a basis

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for future research efforts on distance education involving large-scale surveys.

future trends While the use of desktop video-conferencing facilities for one-to-one tuition sessions has its limitations, it has a promising future too. The subjects have some technical and procedural suggestions on how to improve the quality of such tuition sessions in the future (see Table 3). Future research can implement or fine-tune software tools to put in place procedural routines. Future research can also replicate this study with

different topics of instruction (e.g., languages or sciences) and different levels of instruction (e.g., middle school or college). This study has focused solely on tutors and students from Singapore but future research efforts can examine the same phenomenon in a multi-cultural context. Research has shown that culture does moderate the impact of technologies on human behavior (Tan et al., 1998), particularly since distance learning via desktop video-conferencing capabilities can match tutors and students from different cultures. Also, as network speed improves, further studies could be made to ascertain whether better speed has any significant positive effects on the other factors.

Table 2. Summary of ratings Subject

System characteristics

Method characteristics

Social presence

Media richness

Overall experience

Student X

Fair

Fair

Poor

Poor

Poor

Student X

Neutral

Neutral

Poor

Poor

Fair

Tutor B

Neutral

Good

Fair

Neutral

Neutral

Tutor A

Fair

Good

Neutral

Neutral

Good

Student Z

Good

Excellent

Excellent

Excellent

Excellent

Table 3. Suggestions for improvement Category Technical

Suggestions  Use pen-based interface to draw pictures and write formulae.  Replace the white board with shared document to increase shared space.  The system should capture all the transmitted information for reference.  Consider using ICQ instead of NetMeeting to speed up connection time.  Bypass the Internet if other connections are available (e.g., direct phone). Procedural  Should speak slower with regular intervals to enhance audio quality.  Close video window to improve overall transmission quality.  Use multiple means to make explanation of complex concepts clearer.  Solicit feedback at regular intervals.  Respond quickly to suggestions or queries.  Try to engage in more small talk or share jokes more frequently.  Should meet face-to-face before using the technology.

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conclusIon This study demonstrates the promise of desktop video-conferencing technologies as a means for conducting one-to-one distance education. Given the widespread availability of low-cost personal computers and Internet access, it is plausible that this mode of distance education may partially replace face-to-face tuition sessions. More importantly, the benefits of the technological capabilities examined in this chapter can extend beyond one-to-one tuition sessions to larger-scale distance education efforts. Although this study focuses on desktop video-conferencing technologies, other technologies must not be neglected. In addition to seeing each technology as a solution to an existing problem, it is also fruitful to examine how a collection of information and communication technologies may open up new and exciting possibilities for education. Information and communication technologies have permeated many aspects of education. These technologies will continue to impact education in the future. An example of how such technologies may alter the future of education is a course on Global Project Coordination, jointly conducted by National University of Singapore, Stanford University, and Swedish Royal Institute of Technology. In this course, students from the three universities enrol in the same global class. Faculties from the three universities take turns to give weekly lectures to the entire global class via a three-way video-conferencing facility, based on real-time multicast technologies. Students also form global teams to work on large-scale projects sponsored by the industry. As part of this course, faculties and students employ a wide range of technologies to communicate with and learn from each other. The desktop videoconferencing capabilities investigated here can certainly facilitate such learning efforts by helping to breach geographical barriers among faculties and students of such a global class.

Although this chapter focuses on desktop video-conferencing technologies as a means for distance education, other existing and emerging technologies based on the Internet must not be neglected. In the 21st century, when information and communication technologies are likely to play a critical role in enabling effective education, knowledge accumulated on existing and emerging technologies can guide us in terms of what technologies are appropriate under what circumstances. Rather than seeing each technology as a solution to an existing problem, it is more fruitful to examine how the collection of information and communication technologies may complement each other to open up new and exciting possibilities for educating people.

references Champness, B., & DeAlberdi, M. (1981). Measuring subjective reactions to teletext page design. NSF Grant DAR-7924489-A02. New York, NY: Alternate Media Centre, New York University. Chi, M.T.H. (1996). Constructing self-explanations and scaffolded explanations in tutoring. Applied Cognitive Psychology, 10(Special Issue), S33-S49. Czeck, R. (1995). Videoconferencing: Benefits and disadvantages to communication. http://www. ils.unc.edu/cscw Daft, R.L., Lengel, R.H., & Trevino, L.K. (1987). Message equivocality, media selection, and manager performance: Implications for information systems. MIS Quarterly, 11(3), 355-366. Graesser, A.C., & Person, N.K. (1994). Question asking during tutoring. American Educational Research Journal, 31(1), 104-137. Graesser, A.C., Person, N.K., & Magliano, J.P. (1995). Collaborative dialogue patterns in natu-

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ralistic one-to-one tutoring. Applied Cognitive Psychology, 9(6), 495-522. Hume, G., Michael, J., Rovick, A., & Evens, M. (1996). Hinting as a tactic in one-to-one tutoring. Journal of the Learning Sciences, 5(1), 23-47. Lee, A.S. (1994). Electronic mail as a medium for rich communication: An empirical investigation using hermeneutic interpretation. MIS Quarterly, 18(2), 143-157. Markus, M.L. (1994). Electronic mail as the medium of managerial choice. Organization Science, 5(4), 502-527. Miles, M.B., & Huberman, A.M. (1994). Qualitative data analysis: An expanded sourcebook. Newbury Park, CA: Sage. Milhem, W.D. (1996). Interactivity and computerbased interaction. Journal of Education Technology Systems, 23(3). Millbank, G. (1994). Writing multimedia training with integrated simulation. Writers’ Retreat on Interactive Technology and Equipment. Vancouver, BC: University of British Columbia. Rhodes, J. (2001). Videoconferencing for the real world: Implementing effective visual communications systems. Focal Press. Rice, R.E. (1992). Task analyzability, use of new media, and effectiveness: A multi-site exploration of media richness. Organization Science, 3(4), 475-500. Sankar, C.S., Ford, F.N., & Terase, N. (1997). Impact of videoconferencing in teaching an introductory MIS course. Journal of Educational Technology Systems, 26(1), 67-85. Sankar, C.S., Kramer, S.W., & Hingorani, K. (1995). Teaching real-world issues: Comparison of written versus annotated still image case study. Journal of Educational Technology Systems, 24(1), 31-53.

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Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. New York, NY: John Wiley. Tackett, R. (1995). Pain worth the gain? Network World, 42(12). Tan, B.C.Y., Wei, K.K., Watson, R.T., Clapper, D.L., & McLean, E.R. (1998). Computer-mediated communication and majority influence: Assessing the impact in an individualistic and a collectivistic culture. Management Science, 44(9), 1263-1278. Tan, W.P., & Chan, H.C. (1998). A TAM-based assessment of videoconferencing for remote tutoring. In Proceedings of the Fourth Annual Association for Information Systems Americas Conference (pp. 1094-1096). Trevino, L.K., Lengel, R.H., & Daft, R.L. (1987). Media symbolism, media richness, and media choices: A symbolic interactionist perspective. Communication Research, 14(5), 533-575. Yin, R.K. (2002). Case study research: Design and methods (3rd ed.). Newbury Park, CA: Sage.

key terms Interactivity: The level of interaction among communication partners. Media Richness: Media richness is the extent to which a communication medium can facilitate shared understanding among the communicating partners. Mode Characteristics: Mode characteristics refer to the characteristics of a mode of instruction. The relevant characteristics identified for this study are: usefulness, challenge, attractiveness and clarity. Microsoft NetMeeting: “NetMeeting lets you hold video conference calls, send text messages,

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collaborate on shared documents, and draw on an electronic whiteboard over the Internet or an intranet.” (www.microsoft.com) One-to-One Tutoring: Unlike a classroom setting with one instructor and many students, this is tuition (teaching-learning interaction) between one tutor and one student.

Social Presence: In this study, social presence refers to the extent to which a communication medium projects the physical presence of the communicating partners. Video-Conferencing: Video-conferencing is the use of information and communications technology to allow people at different locations to hear, see and speak to one another. It often includes the sharing of documents and textual communications.

This work was previously published in the Encyclopedia of Information Science and Technololgy, Volume 4, edited by M. Khosrow-Pour, pp. 2194-2198, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.18

Automatic Authoring of Adaptive Education Hypermedia Alexandra I. Cristea Eindhoven University of Technology, The Netherlands Craig Stewart University of Notingham, UK

abstract Adaptive Hypermedia (AH) can be considered the solution to the problems arising from the “onesize-fits-all” approach to information delivery prevalent throughout the WWW today. Adaptive Educational Hypermedia (AEH) aims to deliver educational content appropriate to each learner, adapted to his or her preference and educational background. The development of AEH authoring tools has lagged behind that of delivery systems. Recently, AEH authoring has come to the fore, with the aim of automating the complex task of AEH authoring, not only within a system but also porting material between different AEHs. Advances in intra-system automation are described using the LAOS framework, whereby an

author is only required to create a small amount of educational material that then automatically propagates throughout the system. Advances in inter-system conversions are also described; the aim is to move away from a “create once, use once” authoring paradigm currently in force with most AEH systems, towards a “create once, use many” paradigm. The goal is to allow authors to use their content in the AEH delivery system of their choice, irrespective of the original authoring environment. As a step along this road, we describe the usage of a single authoring environment (MOT) to deliver content in three independently-designed Educational Hypermedia systems—AHA!, WHURLE and SCORM-compliant Blackboard. Therefore, this chapter describes advances in automatic authoring and conversion towards a simple and flexible AEH authoring paradigm.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Automatic Authoring of Adaptive Educational Hypermedia

IntroductIon to aeh authorIng Adaptive hypermedia (AH) (Brusilovsky, 2001a) started as a spin-off of hypermedia and Intelligent Tutoring Systems (ITS) (Murray, 1999). Its goal was to bring the user model capacity of ITS into hypermedia. However, due to technical limitations, such as bandwidth and time constraints, AH only implemented simple user models. This simplicity also gave AH its power as, suddenly, there were many new application fields and also implementation was considerably easier. Early AH research concentrated on variations of simple techniques for adaptive response to changes in user model. No wonder that most of AH development was research oriented, applied only to the limited domain of courses the researchers themselves were giving (e.g., AHA!, De Bra & Calvi, 1998; Interbook, Brusilovsky, Eklund, & Schwarz, 1998; TANGOW, Carro, Pudilo, & Rodriguez, 2001) and with very rare commercial applications (e.g., Firefly, developed at MIT Media Lab and acquired by Microsoft). Recently there has been a shift in attitudes. The development of the Semantic Web (Berners-Lee, 2003) and the ongoing push to develop Ontologies (Gruber, 1992) for knowledge domains has extended the importance of AH. Indeed, AH now appears to be the tool of choice for collating the static information of these new approaches and bringing then to life. Moreover, AH is spreading from its traditional application domain—education—to others, especially the commercial realm, which is eager to be able to provide personalization for its customers. Indeed, we often see the phenomenon of other communities re-inventing adaptive hypermedia for their own purposes and applications. Adaptive Educational Hypermedia (AEH) (Brusilovsky, 2001b) is, in principle, superior to regular Educational Hypermedia (EH) as it allows for personalization of the educational experience. Regular EH, such as that delivered by WebCT and

Blackboard, is not adaptive—exactly the same lesson is delivered to each student. Pedagogical research has shown that different learners learn in different ways (Coffield, 2004). This is a truth self-evident to most teachers; if a student is having trouble learning a subject, then the teacher will alter the manner in which he or she is teaching it and try a different approach. Traditional EH systems could be compared to inflexible teachers who base their lesson mainly on drilling and repetition. Educational systems (real or virtual) that adapt their presentation to the needs of each learner aim to improve the efficiency and effectiveness of the learning process (Stach, Cristea, & De Bra, 2004). If each learner has his or her own Learning Style (Coffield, 2004) and is given a set of resources specific to that particular style then that learner will not only learn “better,” but will be able to more effectively develop the given information into deeper understanding and knowledge. AEH systems seek to address the inflexibility of current EH methods. Systems such as My Online Teacher (MOT), AHA!, and WHURLE all answer the need for an adaptive and flexible approach to teaching. They allow current online educational systems to break away from the “one-size-fits-all” mentality and move towards having an appropriate lesson for each student. AEH systems aim to improve upon current static EH systems. This is not to say that AEH is the universal panacea for online education. Education is not undertaken in a vacuum; the social aspect is also vital. It is essential for learners: to be able to build common ground; to ask and answer (negotiate meaning); to argue and debate; to explicate mental models; to share expertise; to collaborate; and to construct novel ideas and understanding. Work on computer-supported cooperative work (CSCW) addresses this side of the educational process, and often AEH systems will fold this research into them (for example, WHURLE can be used in such a social manner). Collaborative work can be encouraged by the use of simple online social tools: e-mail, for

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asynchronous communications; fora, for persistent asynchronous group discussions; and chat rooms, for synchronous group discussions. The addition of Adaptation to this whole structure is another improvement to the student’s personal online educational experience. However, with increasing numbers of students and the resulting increase in class size of many learning bodies, traditional methods of education (such as the tutorial and the field trip) often become impractical in terms of time and cost. Online education can help to fill this need. EH and AEH were developed to do just this. Given the qualities of AEH systems, it might be reasonable to expect a much wider uptake than actually is happening. A major hindrance of this is that the creation of good quality AEH is not trivial, often involving a greater expenditure of time and money to produce than standard online educational systems. Creating content within a single AEH system can be a complex and difficult undertaking. Many issues must be considered, among them: • • •

• •

•

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What knowledge domain(s) will the lesson partake of? Do any previous e-learning materials exist that are both available and re-usable? What are the objectives of the lesson and how are they to be achieved for a heterogeneous group of learners? Which traits of a learner are to be modelled and how is this user model created? How is the data concerning these traits to be gathered, implicitly (without the learner’s knowledge) or explicitly (information is requested from the learner)? Given that there exists a heterogeneous group of learners, how many versions of the same material need to be created? For example, if a group of learners are to be divided into two sub-groups, one that requires visual materials and the other that requires text-

•

•

based materials, then it follows that at least two sets of the material will be required to teach that lesson. What are the rules for adaptation? Does the author of the lesson have any control over their use or creation? How are the various versions to be presented to the learner, and does the learner have any control over this?

Most AEH systems require the author to consider these issues with little or no help. The author is left adrift and often must become an expert in Adaptive Hypertext before creating anything. It is hardly surprising then, that AEH systems are not used widely outside of their own development circles, as these developers are the only people with the required level of expertise to create content for them! This problem arose while AEH was still a new area of research. A natural “one-to-one” paradigm developed, with developers creating an AEH system that was specific to their desires and insights, along with the necessary authoring tools. Cross-platform considerations were not important; transporting data between systems was generally considered irrelevant. Nowadays, a lot of research effort concentrates on the “authoring challenge” (Cristea & Cristea, 2004; Murray, 2003; Specht, Kravcik, Pesin, & Klemke, 2001; Wu, Houben, & DeBra, 1998; Cristea & De Bra, 2002) in AEH, with the goal of reducing complexity, thereby delivering the greater flexibility of an AEH for the same cost as current online systems. This chapter approaches this challenge from the point of view of automation, minimizing but not restricting the author’s input and reducing overload. Advances in inter-system conversions are also described, the aim being to move away from a “create once, use once” authoring paradigm, as with most AEH systems, towards a “create once, use often” paradigm. The goal is to allow authors to use their content in the AEH system of their choice,

Automatic Authoring of Adaptive Educational Hypermedia

irrespective of the original authoring environment. As a step down this road, we describe using a single authoring environment (MOT) to deliver content in three independently designed Educational Hypermedia systems (AHA!, WHURLE, and SCORM-compliant Blackboard). The remainder of this chapter is organized as follows. First, we present LAOS, a generic AH authoring framework that incorporates several layers of semantics to better express the authored AEH. The major part of this chapter focuses on the two major dimensions of AEH authoring automation that we have identified: automation within an AEH authoring environment, and automation outside it, comprising conversion between AEH systems. Finally, we draw conclusions.

laos layered model The Layered AHS Authoring-Model and Operators (LAOS) model (Cristea & De Mooij, 2003b) (Figure 1) addresses the issue of AEH authoring complexity by dividing it into subtasks corresponding to five explicit semantic layers of adaptive hypermedia (authoring) that together act as a framework for designing an AEH. These five semantic layers of LAOS are: • •

• •

Domain model (DM): Containing the basic concepts of the contents and their representation (such as learning resources). Goal and constraints model (GM): A constrained version of the domain model. The constraints are based on educational goals and motivations. User model (UM): Represents a model of the learner’s educational traits. Adaptation model (AM): A more complex layer that determines the dynamics of the AH system. Traditionally, this layer is composed of IF-THEN rules and therefore the LAOS version also translates such rules at the lowest level.

•

Presentation model (PM): Provided to reflect the physical properties and the environment of the presentation; it reflects choices, such as the appropriate background contrast to support a learner with poor eyesight.

Each of these semantic layers is composed of semantic elements. LAOS allows flexible (re-) composition of the defining semantic elements of the layers, according to each learner’s personalization requirements. We are not going to go into details about the semantic elements, except for those directly used in internal automatic transformations or external conversion. At this point, it suffices to remark that the LAOS structure simply serves to make explicit the complex layers of an AEH system. Such a detailed structure requires a lot of time to populate with AEH instances. As an alternative, we discuss semi-automatic authoring techniques (Cristea & De Mooij, 2003a), which populate the whole structure based on a small initial subset that has been authored by a human. Here we analyze two different possible initial subsets: •

•

Internal semi-automatic authoring: The theoretical analysis of the semi-automatic generation of one LAOS layer based on the content and structure of another one. The practical analysis of this is performed in MOT (My Online Teacher) (Cristea & De Mooij, 2003c). MOT can be downloaded from http://adaptmot.sourceforge.net/ and a comprehensive MOT page (with links to downloads, papers, online trial systems) can be found at http://www.is.win.tue. nl/~acristea/mot.html. In short, we see this research line as another step towards adaptive hypermedia that “writes itself.” External semi-automatic authoring: The theoretical and practical analysis of conversions between AEH authoring systems, such as MOT, into AEH delivery systems, such as AHA! and WHURLE (Moore, Brailsford, &

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Figure 1. LAOS adaptive hypermedia (authoring) framework

Stewart, 2001) or educational systems, such as Blackboard. We examine the structures resulting from using a single authoring system to convert content for use in each system. In effect, we propose a paradigm shift for AEH authoring, away from “write once, use once” (i.e., every AEH has its own authoring systems) towards a middleware

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system that allows for delivery of the same material to many different AEHs. We describe the current “state of the art” towards this goal—using MOT as an authoring environment to deliver adaptive content to WHURLE and AHA! (also the connection to Blackboard).

Automatic Authoring of Adaptive Educational Hypermedia

transformatIons wIthIn an aeh system Adaptive Educational material is obviously more difficult to create than linear educational material because of the alternative content versions and path descriptions. Therefore, we investigate the possibilities of automatic generation of some of the LAOS layers, using information from other layers. In the following sections, we will sketch some of these transformations, focussing on their semantics. The flexibility of general transformations has been addressed by Cristea (2004).

from domain model to Itself (DM→DM) The DM contains the learning resources of the AEH, such as the actual course materials, figures, graphs, videos, and so forth. These resources are grouped under the domain concept to which they belong, using the established domain semantics. That is, resources are grouped into attributes of given (rhetoric or other) types, such as “text,” “introduction,” “conclusion,” “figure,” and the like. The DM also contains the links between the semantic wrappers of the domain resources, such as links between concepts, grouping them into concept hierarchies or other relatedness links. This section discusses the way in which the DM can be automatically (adaptively, adaptably) enriched by interpreting the semantics of its structure and contents.

New Semantic Links The easiest way to enrich the domain model is by automatically finding new domain links between existing domain concepts.1 For instance, new relatedness relations can be generated for relations between concepts that share a common topic. This commonality can be computed at concept attribute level and, therefore, can automatically

be labelled with a type that corresponds to the type attribute of the connecting attribute. In the following, we illustrate this with the help of an abstract example. Consider, we have two domain concepts from two possibly different domain concept maps, c1C1, c2C2 (concept “NN Introduction” and concept “The biological neuron” from the concept maps “Neural Networks I” and “Neural Networks II,” respectively2). Now consider two respective attributes of these concepts, a1c1, a2c2; these attributes can be given as pairs of variable names and their respective values: a1=, a2=. If the attributes are of the same type (var1= var2=var; for instance, var=“keywords”), then a weighted, typed semantic domain link can be generated between the two concepts c1 and c2, with the link type (label) given by the type of the attribute, and the weight defined as the number of common features between the two value fields: weight=number_common_ features(val1,val2). This link will only make sense if the weight is positive. This is one semantically explicit, symbolic way of generating new links between domain concepts. Another way is, for instance, to apply an algorithm that checks the domain map for missing link types and prompts the author, asking if new ones should be searched for.

New Semantic Attributes A different method to enrich the domain model involves link analysis to compare semantically similar concepts (semantically similar can mean similar from a link point of view, such as concepts sharing the same ancestor-concept, for example; concepts at the same level of the hierarchy; or concepts related to each other via some special link (of a given type), etc.) and to determine if some attributes (or even sub-concepts) are missing. For instance, consider a concept called “Discrete Neuron Perceptrons” from a Neural

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Networks course that has an attribute of the type “Example.” whereas the concept “Continuous Neuron Perceptrons” does not, although they are linked via a relatedness relation as described in the previous subsection. In this case, the system can signal the author concerning the possible “missing” content item, corresponding to the semantics (attribute, sub-concept, etc.). It may even look for possible candidates for the “Example” attribute via other links to this concept. This search space is not limited in scope but can continue “outside” the LAOS model, leading to a transition from a closed space to the Open Adaptive Educational Hypermedia space.

from domain model to goal and Constraints Model (DM→GM) The Goal and Constraints Model filters, constrains, and restructures the Domain Model, corresponding to a pedagogic goal. For instance, a lesson aimed at beginners starts by filtering the necessary introductory information from a larger pool defined by one or more appropriate domain maps. Therefore, the primary content of the GM is not resources, but copies of (or, rather, to avoid redundancy, pointers to) the resources. The Goal and Constraints Model also contains prerequisite relationships that establish the general recommended order of visiting the course items. Moreover, here the differentiation is made between alternative content (OR relations) and obligatory content (AND relations). Therefore, the GM Model contains mainly structural elements or links. The GM can also contain resources if these are of a pedagogical nature only (such as a text explaining why it is better for beginners to study resources, grouped as attributes, with the type “Introduction”). Automatic (adaptive, adaptable) Goal and Constraints Model enrichment or creation based on the Domain Model can be achieved based on semantic presentation constraints or goals (e.g.,

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envisioned pedagogical strategies or pedagogical techniques). This transformation represents the first step from information to knowledge, therefore promoting a higher level of semantics.

Semantic Generation of Primary Content Concept attributes, as has been mentioned, can be grouped into types. A semantically relevant subset of these types can be used to determine a semantic filter for the selection of the items that will appear in the Goal and Constraints Model. The filter represents the constraints in the GM model, while the semantics of the filter represents the goal. For instance, a lesson dedicated to beginners can form a filter containing domain attributes of types such as: “Introduction” or “Explanation.” These attributes can be semantically grouped in the GM as alternative contents (OR) and obligatory contents (AND) concepts.

Semantic Generation of Links Links in the domain layer can be, as previously noted, hierarchical or of another nature. These link types can be used to generate specific links at the level of the GM model. For instance, the GM model can be generated by filtering only links of a specific semantically relevant type (e.g., only hierarchical links). These links then are semantically interpreted, therefore becoming prerequisite relations. In MOT, automatic transformations of hierarchical links are used to create a hierarchical, ordered-link structure; that is, the selected attribute subset will keep the same hierarchical structure as its DM source. However, the semantics change from an inclusion hierarchy to that of a prerequisite hierarchy.

Automatic Authoring of Adaptive Educational Hypermedia

from domain model to adaptation Model (DM→AM)

of concept c1 after the attributes with types “title” and “introduction” were accessed:

The role of the adaptation model is to interpret the other models: the domain, goal, and even presentation model. Moreover, it can update these models and generate the presentation. Typical elements of the adaptation model are condition-action (or IF-THEN) rules that change learner model variable values or presentation aspects. LAOS actually uses the Layered Adaptive Granulation (LAG) model (Cristea & Calvi, 2003) to express adaptation with richer semantics. LAG has, at the lowest level, adaptation assembly rules such as IF-THEN rules, but wraps them in a second layer of an adaptation language, and at the highest level adaptation strategies. There are not many semantic descriptions at the lowest LAG level, hence the semantics are built into the other layers. The semantics of the adaptation language correspond to typical educational adaptation constructs that commonly appear during different adaptive interactions with the learner. The highest level, adaptation strategies, corresponds semantically to pedagogic strategies. Automatic (adaptive, adaptable) adaptation model enrichment based on the Domain Model is also a matter of semantic interpretation, with respect to a goal, for example, a pedagogical strategy.

IF(c1.title.access=‘TRUE’ AND c1.introduction. access=‘TRUE’) THEN c1. text.available=’TRUE’;

Automatic Semantic Rule Generation Based on Attribute Types Attribute types can be used to semantically create rules that control the display of specific types of attributes under specific conditions. These conditions can be automatically deduced by the system (as in adaptivity) or triggered by the AH user (adaptability). For instance, a generated specific automatic adaptive rule can express the fact that we only want to show the domain attribute of type “text”

Note that we wrote the condition in this form for simplification purposes, and that attribute states such as “access” and “available” are part of the user model. In order for this to be a generic automatic transformation rule that can be applied to any concept in the domain model, the rule becomes: IF(concept.title.access=‘TRUE’AND concept. introduction.access=‘TRUE’) THEN concept. text.available=’TRUE’;

from goal and constraints model to Adaptation Model (GM→AM) The Adaptation Model should actually work together with the Goal and Constraints Model, as the latter is the filtered version of the initial information, tailored for the group (stereotype) of learners envisioned. The Adaptation Model finetunes this stereotyping, catering to the individual learner’s needs as opposed to the group’s needs. Enriching or generating the Adaptation Model based on the GM means semantically interpreting the GM according to an adaptation strategy or technique (e.g., based on a pedagogical strategy or technique).

Automatic Semantic Rule Generation Based on Link Type The GM, as said, contains pre-ordered and preselected information from the DM. This structure can already be semantically interpreted in terms of the adaptation that is to be performed on it. For instance, the GM allows “AND” relations

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between concepts, as well as “OR” relations with some weights. These can be used to automatically generate rules that express the requirement that all concepts in an “AND” relation must be read: IF ((c.name.access=‘TRUE’ OR c.contents. access=‘TRUE’) AND link(c,c2,’AND’,*)) THEN { c2.name.accessible=‘TRUE’; c2.contents. accessible=‘TRUE’;} In a similar way, an “OR” relationship can be semantically interpreted into inhibition rules: IF ((c.name.access=’TRUE’ OR c.contents.access =’TRUE’) AND link(c,c2,’OR’,*) ) THEN { c2.name.accessible=’no’; c2.contents. accessible=’no’;} In such a way, various constructs can be automatically added to the generic adaptation rules, directly by interpreting the goal and constraints model.

from user model to adaptation Model (UM→AM) The LAOS user model is a hybrid model (similar to Zakaria & Brailsford, 2002). This means that the learner model consist of a stereotype model and an overlay model. The first consists of variable-value pairs, which specify information on a student; for instance: • • • • •

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Interests (e.g., main interests, cross-domain interests, etc.) Current educational status Residential constraints (e.g., preferred cities, maximum distance to travel per day, etc.) Preferred study duration Language (e.g., mother tongue, preferred study language)

• •

Medical status Age

Such variables can enter conditions in adaptive rules or can be modified by these rules. The second model specifies not only variable-values but also the relationships between these variables, which can be deduced from the underlying domain model (or goal and constraints model).

Automatic Semantic Rule Generation Based on Attribute Type To illustrate a semantic interpretation of user model elements to generate an AM rule, we consider the state of “interest” a learner manifests about a concept. A possible semantical interpretation of this state, evaluated via the domain overlay attribute with the same name, is to generate a rule that displays everything in the concept, if this concept is of interest to the user: IF (concept.interest > threshold) THEN{concept.name.available=’TRUE’; concept.contents.available=’TRUE’;} Note that this rule is a generic rule, which can be applied on all concepts in a concept map, drastically reducing the workload.

UM→AM: By Link Type Link type can only be used when the UM is itself a concept map. Via UM links, we can express, for instance, the fact that two states in the user model are related. Here, however, we try to look at a different type of link between UM concepts. For this, we will consider the link of type “influence.” Such a link can be automatically interpreted into a rule saying that the interest in a subject c might decrease if the user is interested in another subject c2.

Automatic Authoring of Adaptive Educational Hypermedia

IF LINK(c,c2,’influence’,*)





THEN {c.interest= c.interest – c2.interest;}

conversIons between aeh systems Paradigm Shift (One-to-One → Manyto-many) LAOS addresses many of the issues regarding the complexity of authoring but cannot cover all of them. This is because the problem is compounded when one considers other factors, such as software rot and the multitude of systems available. Software rot occurs over time because software is not maintained or software necessary for the correct workings of a program is altered in such a way that the original code ceases to function correctly. Imagine a situation where an author goes to the not inconsiderable time and trouble to create a lesson in an AEH system, be it based on LAOS or not. What happens if this system ceases to be maintained? As many AEH systems are currently developed by individual research groups around the world, the above situation has occurred many times and will occur again. Before this happens, the author must consider the future. Does he stay with the old system that will slowly rot away? Or does he spend the time and effort to learn how to author in a new AEH system? It is possible that the original content is locked into the previous format, hence he may have to re-create all of his old lessons. With the ongoing growth and maturation of AEH, these issues are raised. It is more widely recognised as desirable to move away from a “one-to-one” AH authoring paradigm to a general “many-to-many.” That is, an author may create a lesson in any system in which he is an expert or wishes to spend the time and effort to learn, and export (or convert) this data for use in an other system. It would then be of no concern if

an individual system “rotted” or was no longer available; a simple conversion from that system to a new one would solve this problem. This is an extended form of authoring. What follows is a description of the first steps taken in this direction. However, rather than the ultimate goal of a “many-to-many” system, we describe a half-way point—a “one-to-many” methodology. Using MOT as an authoring tool (as it is based on the powerful and flexible LAOS framework), it is possible to create whatever content is desired. It is then possible to transform the lesson into one of three different formats: AHA!, Blackboard, or WHURLE (actually there are four formats, but the original MOT delivery format requires no conversion). The process involved in doing this is described in the following sections.

Existing Multi-System Authoring Environments In the following sections we will analyze some inter-system authoring experiments. We will discuss how learning material can be created in one system, MOT, and converted into other delivery systems. The conversions described below represent the one-to-many paradigm shift. MOT → AHA! My Online Teacher (MOT) is an AEH authoring system based on the LAOS framework. At the time of the writing, MOT implements the: • • • •

Domain model, as a conceptual domain model for courses Goal and constraints model, as a Lesson map User model, featuring stereotypes and overlay user model (Wu, 2002) Adaptation model (MOT-adapt), in the form of an (instructional) adaptive strategy (Cristea, 2004b) creation tool, based on an adap-

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•

tive language (Cristea & Calvi, 2003) that uses as an intermediate representation level of LAG (Layers of Adaptive Granulation) grammar (Cristea & Verschoor, 2004) presentation model is currently being implemented, in the form of a hybrid model, similar to the user model.

AHA! is a general-purpose, adaptive Webbased engine, first created as a simple support engine for adaptive online courses (De Bra & Calvi, 1998). The key features of AHA! (Version 2.0) are: • • • • • • •

Open Source project Web-based adaptive engine Built on Java Servlet technology Authoring through Java Applets General-purpose user-model and adaptation rules Extensive use of XML Database support using mySQL

In addition to these, AHA! Version 3.0 contains constructs called “objects.” These “objects” allow a complex inclusion structure of elements of a learner presentation, in a more flexible way than in earlier versions. As MOT’s first version implemented only the domain and the lesson maps, the first MOT to AHA! conversion focussed on the conversion of these maps only. The version currently under implementation is aiming to make use of the new facilities in AHA! 3.0 and the extensions in MOT. In the following, these conversions will be sketched separately, from a semantic and implementation point of view.

Semantic Mapping of the Domain Model The MOT domain model layer contains a hierarchy of domain concepts and their respective

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domain attributes. Moreover, the DM contains also (typed and weighted) relatedness relations between domain concepts. The conversion from MOT to AHA! was initially performed using AHA! v2.0. AHA! v2.0 only knew how to handle conditional inclusion of fragments, which are parts of an (xhtml) page. Therefore, the (xhtml) pages had to be generated for the AHA! v2.0 engine. Note, however, that if a concept attribute appeared in more than one condition, it had to be pasted as a conditional fragment in each of the (xhtml) pages in which it could appear. The object inclusion in AHA! 3.0 solves this redundancy problem. This is the reason why the conversion process only started to function closer to the desired requirements with the advent of AHA! 3.0. A conversion of MOT domain concept maps into AHA! 3.0 involves the following steps: 1.

2.

3.

Creation of an XHTML (basic) resource file for every domain attribute in MOT.3 This will generate AHA! object concepts4 for each attribute (Attr 1 to Attr k) in Figure 2 Grouping of domain attributes (representing the different aspects of a concept that should appear when certain instructional strategies are triggered) into XHTML files, containing lists of “objects,” pointing to the XHTML files created in Step 1. This will generate AHA! page concepts (as shown in Figure 2) Writing the actual conditions that determine which (or how many) of the alternatives are really shown to the student in AHA! rules during conversion

Semantically, this means that MOT domain attributes correspond to AHA! resources, whereas MOT domain concepts correspond to a special type of AHA! concept called “page concept.” The actual representation of the domain map conversion in the AHA! implementation is shown

Automatic Authoring of Adaptive Educational Hypermedia

Figure 2. Semantic representation of MOT domain concepts and domain attributes in AHA! AHA! object concepts AHA! page concept XHTML file MOT DM concept

Attr. 1

XHTML files

Attr. 2

Attr. 3

… Attr. k

Figure 3. Implementation of MOT domain concepts and domain attributes in AHA!

AHA! page concept (corresponding to MOT concept)



. . XHTML file

in Figure 3. The figure shows how an AHA! page concept can be created by connecting together a list of object concepts. The actual display of the object concepts can be made to depend on some conditions (such as user preferences, state, etc.).

Semantic Mapping of the Lesson Model The Lesson map has similar elements to the DM (according to the LAOS model), so similar conversions can be expected. One major difference is determined by the (weighted) AND-OR relations, which can be directly interpreted as prerequisite relations, allowed by the AHA! engine.

Lesson map conversion into AHA! 3.0 structure is similar to the conversion of domain concept maps. The semantics are represented in Figure 4. The contents of the MOT lesson concepts have previously been created as XHTML basic resources during the domain attribute conversion, therefore this process is not repeated (i.e., the resources that are connected to the attributes Attr. 1 to 3 in Figure 4 are already bound to some AHA! object concepts, as shown in Figure 2. This is due to the LAOS restriction that attributes of the Domain map become concepts in the Lesson map). These MOT lesson concepts are then converted into AHA! page concepts, in a similar way.

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Figure 4. Semantic representation of MOT lesson concepts in AHA! already exist

AHA! page concept XHTML file

GM concept 1

MOT GM concept

GM concept 2 GM concept 3

… GM concept list k1

…

AHA! object (pointer) concepts XHTML files

To enforce the hierarchy and order relationship, the XHTML files translating lessons contain a separate, ordered list of sub-lesson pointers in addition to the list of object alternatives (as shown in the Figure 4). The access to sub-lessons might not be always desirable, depending on the instructional strategy. Therefore, the implementation is again via the “object” paradigm in AHA!. Moreover, a small trick is here necessary, as for sub-lessons AHA! should not display the content but the link to the content. This can be realized in AHA! with the help of some extra link concepts containing just a link to the respective sub-lesson (see Figure 5, AHA! concept corresponding to XHTML link).

MOT → WHURLE Web-based Hierarchical Universal Reactive Learning Environment (WHURLE) is an adaptive learning environment (Brailsford, Stewart, Zakaria, & Moore, 2002; Moore, Brailsford, & Stewart, 2001; Zakaria, Moore, Stewart, & Brailsford, 2003) that stores information as atomic units, called chunks. These are the smallest possible, conceptually self-contained units of information

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that can be used by the system. They may be as small as a captioned image or a paragraph of text, or as large as an entire legal or historical document. Lessons consist of a collection of chunks, together with a default pathway, or lesson plan, defined by authors. The lesson plan is filtered by an adaptation filter that implements the user model based on data stored in the user profile. WHURLE, however, has no specific authoring system. Both chunks and lesson plans are created using XML editors; anything from a simple text editor to an XML authoring environment may be used. Meanwhile, the user profile has, in part, to be created using SQL statements that are entered manually into the MySQL database. For a novice author with no expertise in XML or SQL, creating lessons in WHURLE is a time consuming and confusing process. Using MOT as an authoring tool solves many of the problems that novice, or even experienced, authors have when authoring in WHURLE. Learning to use MOT is a simple feat compared to learning to author in WHURLE, as MOT authors are only required to understand HTML at the outset. There are still design decisions that need to be made, but they are of a pedagogical nature, not a technical one.

Automatic Authoring of Adaptive Educational Hypermedia

Figure 5. Implementation of MOT lesson concepts in AHA!

AHA! page concept (corresponding to MOT concept)



. .

. . XHTML file

AHA!-Concept (corresponding to XHTML Link)

AHA!-Concept (corresponding to XHTML Link)

AHA!-Concept (corresponding to XHTML Link)

subles1 XHTML

subles2 XHTML

subles3 XHTML

Authoring in MOT is a many stage process. Initially, the domain maps are built; then the lesson map is created using the concepts from whichever domain maps are appropriate. The MOT-to-WHURLE conversion focuses on these two steps and therefore has two options: the conversion of domain maps or lesson maps.

Semantic Mapping of the Domain Model This is a simple method of conversion resulting in a WHURLE lesson plan that has no adaptation built into it. A single MOT concept (Figure 6) is converted into a single WHURLE chunk by gathering all of the attributes for that concept, extracting the title, keywords, and placing the rest of the attribute contents into the body of the chunk. Of course, in addition to chunks, WHURLE requires a lesson plan. This is also a part of the

conversion output, and a section of the lesson plan produced from the domain map in Figure 6 is shown in Figure 8. As a domain map has no adaptation information contained within it, it is not necessary to convert any further information. This can be seen in Figure 8, where the value for the “domain” is “general” and both “stereotype1” and “stereotype2” are left blank. This indicates that there is no adaptation taking place in this lesson plan. By ignoring adaptation, this simple form of conversion does not take full advantage of the functionality of WHURLE. For that, we must turn to the second method of conversion.

Semantic Mapping of the Lesson Model Examine Figure 9 and the highlighted areas within it. These mark two of the major differences between a MOT domain map and a lesson map.

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Automatic Authoring of Adaptive Educational Hypermedia

Figure 6. A MOT Domain Map, Biochemistry, with a single concept

Figure 7. The WHURLE chunk created after conversion of the MOT concept in Figure 6. The original order of the attributes in the concept is maintained, hence “introduction” at the end of the attribute list.

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Figure 8. A section of a WHURLE lesson plan, produced by transforming the MOT domain map in Figure 6.

Figure 9. A MOT lesson map. The highlighted region shows that the attributes for this concept are all part of an “OR” and that each attribute has a “weight”—identified by the percentage (0%, 10% and 90%).

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Figure 10. MOT lesson maps can be built from concepts from many domain maps

Compared to a MOT domain map, the lesson map allows for the possibility of adaptation. It does this by allowing an author to assign an “OR” condition to any particular concept (“AND” is the default). This signifies that all of that concept’s children—be they attributes or sub-concepts— can have a “weight” (and a “label,” not shown) associated with them. The MOT-to-WHURLE lesson map conversion has three stages: 1.

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Define structure: This stage of the conversion trawls through the lesson map and creates the WHURLE lesson plan. Each concept has to be linked to its parent, siblings, and children. As lesson maps can be made up from many domain maps (Figure 10), each concept must also have its parent domain map identified as this will be used

as the value for the “domain” section of a lesson plan (Figure 11). As can be seen from Figure 11, the value of “domain” is a number (“113” or “119”), because WHURLE requires a numeric value here. This is linked to the “real” name (“MOT user guide” and “Biochemistry,” respectively) for each domain, in the WHURLE database. Once the structure has been defined, the final process during this stage is to produce the WHURLE lesson plan. To do this, additional structures (e.g., XML specific data, a title, author information, etc.) are added to the lesson plan. 2.

Associate attributes: As the first process is ongoing (lesson plan elucidation), this second process, production of the chunks, begins. Whenever a concept is encoun-

Automatic Authoring of Adaptive Educational Hypermedia

tered, all of the attributes for that concept are gathered and sorted according to their MOT “weights.” Each weight is associated with others of the same weight, except for weight “0.” Weight “0” is treated as a special case, as it allows the author to determine which attributes are to be “common,” that is, available to all chunks created from that concept. Table 1 shows which attributes will be associated with which chunks after conversion. The standard, weight “0,” attributes are collected together and form chunk C1. Chunk C2 is made up from the standard attributes plus all those with a weight of “’90,” while chunk C3 collects together the attributes of weight “10” and “0.” So far, this is of no obvious use to the author. However, used in conjunction with a table like Table 2, it becomes possible for the author to determine his own weight boundaries when deciding which attributes belong to which WHURLE knowledge level: “beg” (beginner), “int” (intermediate) or “adv”(advanced). 3.

Update WHURLE database: The final step in the MOT->WHURLE conversion is to create the SQL commands that will update the WHURLE database. Like MOT, WHURLE uses a MySQL database, which is used to record certain information about each of the WHURLE lessons, for example, the name and unique ID of each lesson, a list of the knowledge domains (appearing as numbers in Figure 11,“ online Face-to-face > online Face-to-face > online Face-to-face > online Face-to-face > online

Result in Correct Direction? T F T T T F

six dependent variables, it never does so at a statistically significant level. One interpretation of this is that online BM training is no worse than F2F BM training across all dependent variables. (Trainees in the online BM condition actually score higher than F2F BM trainees in IFT.) The pattern of results for F2F BM suggests that trainers might choose online BM—which ought to be a less costly alternative to F2F BM—without making any significant sacrifice in either learning or trainee reaction outcomes. The complex picture of the implications of these four treatments must be more clearly illustrated. Two methods can illustrate this complexity. The first is the “insufficient difference” finding between online BM and F2F BM. The second is the beginning of a strategy for online asynchronous software training. As a first result, the conclusion of “insufficient difference” between online BM and F2F BM depends on being able to say there is not enough difference between their effects to justify the difference in their costs. A practical difference between F2F BM and online BM—one that matters in cost/benefit terms—must have some minimum size. Specifying a practical difference involves knowing the costs of F2F BM and online BM, as well as how effect size maps to benefits. Ability to detect effect sizes is nothing more than statistical power (Cohen, 1977). In information systems research, “studies are unlikely to

Significant p-value? n.s. n.s. n.s. n.s. n.s. n.s.

display large effects and that, typically, smallto medium-effect sizes should be anticipated” (Baroudi & Orlikowski, 1989, p. 90). Because this study exercised due care with experimental procedure and made use of reliable instruments, there is justification in addressing statistically insignificant results. Before executing the experiment, efforts were made to maximize the difference between F2F BM and online BM conditions; a Delphi study was conducted regarding the design of course materials to reflect the different training approaches. Despite this careful control over operationalization, there was not enough difference between F2F BM and online BM effects to justify the difference in their costs. Due to the undeveloped nature of research in this area, it may be inappropriate to establish an index for effect size based on prior research on software-training strategy in the traditional environment (Mazen et al., 1987). To explain the phenomenon carefully, we employ Cohen’s (1977) approach to estimate proxy effect-size levels based on the standardized difference d of two populations taking different training approaches (see Table 5). The estimated effect size is 0.5 for all dependent variables except KNT and PEOU. Since PEOU is related to the design of the e-learning system rather than the treatment of training approach, smaller effect size across different groups is understandable. However, the study cannot detect

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Table 5. Effect size estimation

Dependent Variables Knowledge NT (KNT) Knowledge FT (KFT) OS PEOU PU

Standardized Difference between F2F BM and online BM

* Estimated Effect Size

25.47%

0.20

-46.45%

0.50

58.82% -21.05% 57.97%

0.50 0.20 0.50

Note: * Calculated based on Cohen’s (1977) Effect Size Conventions

differences of effect size for KNT. This indicates that it makes no difference whether F2F BM or online BM is employed to improve KNT. Online trainers can choose either F2F BM or online BM to improve end-users’ KNT if either approach has relatively similar costs. Contrary to the expectation of hypotheses, a larger effect size was detected for KFT in the short term and long term. This practical difference indicates that the benefits of online BM outweigh F2F BM for KFT in the short and long term. Larger effect size was also detected for the measures of end-user satisfaction: OS and PU. This practical difference supports that F2F BM is a better approach than online BM to improve end-user satisfaction. The difference between knowledge absorption capability and end-user satisfaction poses many interesting questions. As a second result, this study can offer concrete suggestions about the beginning of a strategy for online asynchronous software training. One result of interest is that F2F BM might be better than online behavior modeling. Of the six hypotheses concerning relationships between these two methods, four are in the expected direction, none significantly so.

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These findings indicate that use of online BM may be the best software-training strategy for the online asynchronous setting. To confidently offer such suggestions, the study needs to discuss the design decisions that trainers face in the online asynchronous environment. The study provides support for using online BM over exploration- and instruction-based training, given that the prior contribution makes the point of favoring online BM over F2F BM. Since our suggestions are a start on an online asynchronous software training strategy, we will present the outline of the strategy that includes “to-do” and “not-to-do” lists. This online asynchronous software training strategy will allow trainers and vendors to capitalize on these opportunities and avoid costly mistakes. The largest implication for practice is that online BM may provide a cost-effective substitute for F2F BM without significant reductions in training outcomes. Compared to F2F BM, online BM allows trainees to have more control over their learning. Cognitive learning theory indicates that the learning process can be improved via active learning (Shuell, 1986) and problem-solving learning (Alavi, 1994). In the virtual learning environment (VLE), trainees have higher control of learning and can choose to use exploration- or instruction-based training approaches depending on tasks and individual needs. For instance, trainees with more experience and knowledge related to a particular trainee may resort to meaningful learning and use relevant examples to practice. Trainees with little knowledge about another trainee may resort to rote learning and use generic examples to practice. The VLE allows trainees to switch freely between meaningful and rote learning, to their advantages. Since trainees have control flexibility, online BM can be viewed as more effective than the F2F BM in helping trainees perform well on neartransfer and far-transfer tasks. In the VLE, the individualized and contextual learning provides anchoring for trainees to transform their mental

Online Behavior Modeling

models. While more must be learned about this relationship, it is encouraging to see evidence that there may be a desirable leverage from online asynchronous software training. Another thing trainers need to bear in mind when designing an online asynchronous software training strategy is that the effectiveness of online asynchronous software training methods does not necessarily go hand-in-hand with overall satisfaction, perceived ease of use and perceived usefulness. In particular, it may still be the case that learning effectiveness is neutral to learning style. Improving satisfaction by customizing learning approaches may be the right decision to make, but performance might not be the deciding factor. Online BM and F2F BM allow trainees to have some control of the learning process and information acquisition regarding its content, accuracy, format, ease of use and timeliness (Doll, Xia, & Torkzadeh, 1994), which leads to somewhat higher satisfaction levels. In itself, higher levels of satisfaction may be justification for online BM and F2F BM use, but much remains to be learned about the effects of these methods for training performance. Assimilation Theory suggests that being receptive to new procedural knowledge on how to operate a new target system is the prerequisite to meaningful learning (Mayer, 1981) or farknowledge transfer. With the time constraints, a more focused learning approach can be useful at assimilating new knowledge. Hence, the online BM approach is a logical solution for meaningful learning, because the approach allows trainees to not only acquire new knowledge, but also gives them flexibility to search their long-term memory for “appropriate anchoring ideas or concepts” (p. 64) and to use the ideas to interact with new knowledge (Davis & Bostrom, 1993).

lImItatIons While it seems unlikely, given the care taken in the design of the study, there is always the possibility that the independent variable, training method, could inadequately represent its intended construct. With any complex treatment, such as the establishment of a training method here, there is a chance that operationalization can be less than what is needed for effects to occur. Additional research is required to refine and perfect the training method treatments as much as possible. There is no simple manipulation check for verifying the efficacy of this kind of treatment, but continued investigation should reveal the extent to which the manipulation is a successful one. Future research can attempt to improve the reliability of the findings by controlling the experimental environment more tightly (e.g., equal cell size, larger cell size and longer training sessions) or by improving the strategy’s generalizability through the examination other variables (e.g., trainees vs. professional workers, number of training duration sessions, type of training media, self efficacy, experiences of using the online learning system and software types).

ImplIcatIons for research The findings here raise additional questions for research. Some that might be addressed in the immediate future include: •

•

To replicate the experimental equivalence of F2F BM and online BM methods of software training with different software and trainees. With this, to demonstrate a practical (i.e., cost-based) advantage of online BM over F2F BM for software training in practical settings. To study the impact of training duration on performance and trainee reactions. Train-

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•

•

•

•

ees should be exposed to the same training methods for different durations. To improve the reliability of the study by manipulating some useful blocking variables. A series of comparative studies can be conducted to assess the impact of individualism as a cultural characteristic, computer self-efficacy, task complexity, professional backgrounds, and the ratio of the training duration to the quantity of information to be processed, among others. To investigate the impacts of social presence and information richness (SPIR) (Fulk, 1993) features of online asynchronous software training media on training outcomes. Future studies might vary the SPIR features of training media (e.g., F2F vs. online asynchronous scripted or Web cam modes). To conduct longitudinal studies of the influence of learning style on learning performance and trainee reaction. To continue to study the relationship between learning style, training methods and training outcomes. Learning style is somewhat associated with the cultural backgrounds of online trainees. Trainees with varying cultural backgrounds may prefer to adopt training media with different SPIR features. Cultural differences, such as relative degree of individualism, may affect preference for SPIR characteristics. Some combination of training methods, learning style and SPIR attributes may jointly determine learning outcomes.

Implications for practice The largest implication for practice is that online BM may provide a cost-effective substitute for F2F BM without significant reductions in training outcomes. While more must be learned about this relationship, it is encouraging to see evidence that there may be a desirable leverage from online asynchronous software training.

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Also, when designing an online asynchronous software training strategy, trainers need to bear in mind that both F2F BM and online BM are equally effective to improve learning outcomes (including satisfaction), and performance might not be the decision factor if these two approaches need to be chosen from. Other decision factors, such as trainer’s preference, equipment availability, budget and scheduling, could be more important than the efficacy issue. Online BM and F2F BM allow trainees to have some control of the learning process, leading to somewhat higher satisfaction levels. This advantage in itself may be justification for their use, but much remains to be learned about the effects of these methods for training performance.

conclusIon The success of an online asynchronous software training strategy depends on its effectiveness in improving learning outcomes. This study builds on a well-accepted framework for training research (Bostrom, Olfman & Sein, 1990; Simon, Grover, Teng & Whitcomb, 1996), examines the relative effectiveness of four training methods and begins to derive a strategy for online asynchronous software training. Testing the following hypotheses provides an empirical basis for the development of an online asynchronous software training strategy: (1) F2F BM is more effective than online BM for learning performance and trainee reactions, and (2) online BM is more cost effective than F2F BM. While these hypotheses are not fully supported statistically, and while many of the observed results are difficult to interpret, the study discovers important potential implications for practitioners and researchers. The formulated online asynchronous software training strategy suggests that trainers customize their training methods based on desired learning outcomes.

Online Behavior Modeling

What is learned from this study can be summarized as follows: When conducting software training, it may be as effective to use an online BM method as it is to use a more costly F2F BM method. Although somewhat better results are sometimes evident for F2F BM, observed differences are not significant, nor are their patterns consistent. The study has accomplished its major goal—it provides evidence as to the relative effectiveness of various methods, particularly those of an online asynchronous nature, for software training. Within its limits, this research takes a first step in developing a strategy for online asynchronous software training.

references Allen, I. E. & Seaman, J. (2003). Sizing the opportunity: The quality and extent of online education in the United States, 2002-2003. Needham, MA: The Sloan Consortium. Ausubel, D. P. (1963). The psychology of meaningful verbal learning. New York: Grune and Stratton. Aytes, K., & Connolly, T. (2004, July-September). Computer Security and Risky Computing Practices: A Rational Choice Perspective. Journal of Organizational and End User Computing 16(3), 22-40. Bandura, A. (1986). Social foundations of thought & action. Englewood Cliffs: Prentice-Hall. Baroudi, J. J., & Orlikowski, W. J. (1988). A short form measure of user information satisfaction: A psychometric evaluation and notes. Journal of Management Information Systems, 4, 45-59. Bassi, L.J., Ludwig, J., McMurrer, D.P. & Van Buren, M. (2000, September). Profiting from learning: Do firms’ investments in education

and training pay off? The American Society for Training and Development (ASTD) and Saba, Alexandria, VA. Retrieved January 3, 2006, from http://www.astd.org/NR/rdonlyres/15C0E2ABB16D-4E3C-A081-4205B865DA3F/0/PFLWhitePaper.pdf Bell, J. (2004, March/April). Why software training is a priority? Booktech the Magazine, 7, 8. Bielefield, A., & Cheeseman, L. (1997). Technology and copyright law. New York: Neal-Schuman Publishers. Bloom, M. (2003, April 2). E-learning in Canada, Findings from 2003 E-survey: Top line findings from a survey of the conference board of Canada’s customers on current e-learning practices. The Conference Board of Canada. Retreived June 6, 2005, from http://www.conferenceboard.ca/education/reports/pdfs/TopLine_report.pdf Brown, J. (2000, December 15). Employee turnover costs billions annually. Computing Canada, 26, 25. Bruner, J. (1966). Toward a theory of instruction. New York: Norton. Cohen, J. (1977). Statistical power analysis for the behavioral sciences. New York: Academic Press. Compeau, D. R. & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19, 189-211. Compeau, D. R., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158. Davis, D. L., & Davis, D. F. (1990). The effect of training techniques and personal characteristics on training end users of information systems. Journal of Management Information Systems, 7(2), 93-110.

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Davis, F. D. (1989, September). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319339. Decker, P. J. & Nathan, B. R. (1985). Behavior modeling training. New York: Praeger. Fulk, J. (1993). Social construction of communication technology. Academy of Management Journal, 36, 921-950. Gist, M. E., Schwoerer, C., & Rosen, B. (1989). Effects of alternative training methods on selfefficacy and performance in computer software training. Journal of Applied Psychology, 74(6), 884-891. Heller, M. (2003, November 15). Six ways to boost morale. CIO Magazine, 1. Horton, W. (2000). Designing Web-based training. New York: John Wiley & Sons. International Data Corp. (2002, September 30). While Corporate Training Markets Will Not Live up to Earlier Forecasts, IDC Suggests Reasons for Optimism, Particularly eLearning. International Data Corporation. Retrieved March 5, 2003, from http://www.idc.com/getdoc. jhtml?containerId=pr2002_09_17_150550 Ives, B., Olson, M., & Baroudi, S. (1983). The measurement of user information satisfaction. Communications of the ACM, 26, 785-793. Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research. New York: Harcourt Brace College Publishers. Kirpatrick, D. L. (Ed.). (1967). Evaluation of training. Training and development handbook. New York: McGraw Hill. Leidner, D. E., & Jarvenpaa, S. L. (1995). The use of information technology to enhance manage-

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ment school education: A theoretical view. MIS Quarterly, 19, 265-291. Mazen, A. M., Graf, L. A., Kellogg, C. E., & Hemmasi, M. (1987). Statistical Power in Contemporary Management Research. Academy of Management Journal, 30, 369-380. McEvoy, G. M., & Cascio, W. F. (1987, December). Do good or poor performers leave? A metaanalysis of the relationship between performance and turnover. Academy of Management Journal, 30(4), 744-762. McGehee, W., & Tullar, W. (1978). A note on evaluating behavior modification and behavior modeling as industrial training techniques. Personal Psychology, 31, 477-484. Piccoli, G., Ahmad, R., & Ives, B. (2001). Webbased virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic IT skills training. MIS Quarterly, 25(4). Simon, S. J., Grover, V., Teng, J. T. C., & Whitcomb, K. (1996, December). The relationship of information system training methods and cognitive ability to end-user satisfaction, comprehension, and skill transfer: A longitudinal field study. Information Systems Research, 7(4), 466-490. Skinner, B. F. (1938). The behavior of organisms: An experimental analysis.New York: B. F. Skinner Foundation. Taba, H. (1963). Learning by discovery: Psychological and educational rationale. Elementary School, 308-316. Wexley, K. N., & Baldwin, T. T. (1986). Posttraining strategies for facilitating positive transfer: An empirical exploration. Academy of Management Journal, 29, 503-520.

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Yi, M. Y. & Davis, F. D. (2001). Improving computer training effectiveness for decision technologies: Behavior modeling and retention enhancement. Decision Sciences, 32(3), 521-544.

Yi, Y. (Ed.). (1990). A critical review of consumer satisfaction: Review of marketing. Chicago: American Marketing Association.

This work was previously published in the International Journal of Web-Based Learning and Teaching Technologies, Volume 1, Issue 4, edited by L. Esnault, pp. 36-53, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 3.31

Interactive Multimedia Technologies for Distance Education in Developing Countries Hakikur Rahman SDNP, Bangladesh

IntroductIon With the extended application of information technologies (IT), the conventional education system has crossed physical boundaries to reach the un-reached through a virtual education system. In the distant mode of education, students get the opportunity for education through self-learning methods with the use of technology-mediated techniques. Accumulating a few other available technologies, efforts are being made to promote distance education in the remotest regions of developing countries through institutional collaborations and adaptive use of collaborative learning systems (Rahman, 2000a). Distance education in a networked environment demands extensive use of computerized Local-Area and Wide-Area Networks (LAN/WAN), excessive use of bandwidth and expensive use of sophisticated networking equipment; in a sense

this has become a hard-to-achieve target in developing countries. High initial investment cost always demarcates thorough usage of networked hierarchies where the basic backbone infrastructure of IT is in a rudimentary stage. Developed countries are taking a leading role in spearheading distance education through flexible learning methods, and many renowned universities of the western world are offering highly specialized and demanding distance education courses by using their dedicated high-bandwidth computer networks. Many others have accepted a dual mode of education rather than sticking to the conventional education system. Research indicates that teaching and studying at a distance can be as effective as traditional instruction when the method and technologies used are appropriate to the instructional tasks with intensive learnerto-learner interactions and instructor-to-learner interactions. Radio, television and computer

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Interactive Multimedia Technologies for Distance Education in Developing Countries

technologies, including the Internet and interactive multimedia methods, are major components of virtual learning methodologies. The goals of distance education, as an alternative to traditional education, have been to offer accredited education programs, to eradicate illiteracy in developing countries, to provide capacity-development programs for better economic growth, and to offer curriculum enrichment in a non-formal educational arena. Distance education has experienced dramatic global growth since the early 1980s. It has evolved from early correspondence learning using primarily print-based materials into a global movement using various technologies.

background Distance education has been defined as an educational process in which a significant proportion of the teaching is conducted by someone removed in space and/or time from the learner. Open learning, in turn, is an organized educational activity based on the use of teaching materials, in which constraints on study are minimized in terms either of access, or of time and place, pace, method of study or any combination of these (UNESCO, 2001). There is no ideal model of distance education, but several are innovative for very different reasons. Philosophies of an approach to distance education differ (Thach & Murphy, 1994). With the advent of educational technology-based resources (CD-ROMs, the Internet, Web pages, etc.), flexible learning methodologies are getting popular to a large mass of the population who otherwise was missing the opportunity of accessing formal education (Kochmer, 1995). Murphy (1995) reported that to reframe the quality of teaching and learning at a distance, four types of interaction are necessary: learner-content, learner-teacher, learner-learner and learner-interface. Interaction also represents the connectivity the students feel

with their professor, aides, facilitators and peers (Sherry, 1996). Responsibility for this sort of interaction mainly depends upon the instructor (Barker & Baker, 1995). The goal of utilizing multimedia technologies in education is to provide learners with an empowering environment where multimedia may be used anytime, anywhere, at a moderate cost and in an extremely user-friendly manner. However, the technologies employed must remain transparent to the user. Such a computer-based, interactive multimedia environment for distance education is achievable now, but at the cost of high bandwidth infrastructure and sophisticated delivery facilities. Once this has been established for distance education, many other information services essential for accelerated development (e.g., health, governance, business, etc.) may be developed and delivered over the same facilities. Due to the recent development of information technology, educational courses using a variety of media are being delivered to students in diversified locations to serve the educational needs of the fast-growing populations. Developments in technology allow distance education programs to provide specialized courses to students in remote geographic areas, with increasing interactivity between student and educator. Although the ways in which distance education is implemented differ remarkably from country to country, most distance learning programs rely on technologies that are either already in place or being replicated for their cost effectiveness. Such programs are particularly beneficial for the many people who are not financially, physically or geographically able to obtain conventional education, especially for participants in the developing countries. Cunningham et al. (2000) referred in their report that “notwithstanding the rapid growth of online delivery among the traditional and new provisions of higher education, there is as yet little evidence of successful, established virtual institutions.” However, in a 2002 survey of 75 randomly chosen colleges providing distance

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Interactive Multimedia Technololgies for Distance Education in Developing Countries

learning programs, results revealed an astounding growth rate of 41% per program in the higher education distance learning (Primary Research Group, 2002). Gunawardena and McIsaac (2003), in their Handbook of Distance Education, has inferred from the same research case that, “In this time of shrinking budgets, distance learning programs are reporting 41% average annual enrollment growth. Thirty percent of the programs are being developed to meet the needs of professional continuing education for adults. Twenty-four percent of distance students have high-speed bandwidth at home. These developments signal a drastic redirection of traditional distance education.” According to an estimate, IT-based education and the e-learning market across the globe is projected at $11.4 billion (United States dollars) in 2003 (Mahajan, Sanone & Gujar, 2003). It is vital that learners should be able to deal with real-world tasks that require problem-solving skills, integrate knowledge incorporating their own experiences, and produce new insights in their career. Adult learners and their instructors

should be able to handle a number of challenges before actual learning starts; make themselves resourceful by utilizing their own strengths, skills and demands by maintaining self-esteem; and clarify themselves by defining what has been learned, how much it is useful to society and how the content would be effectively utilized for the community in a knowledge-building effort. One of the barriers to success and development in Open Learning in The Commonwealth developing countries is lack of sound management practice. Sometimes the people who are appointed to high office in open and distance learning do not have proper management skills. As a result, their management practice is poor. They often lack professionalism, proper management ethics and so forth. They lack strategic management skills, they cannot build conducive working environments for staff, nor can they build team spirit required in a learning institution (Tarusikirwa, 2001). The basic hierarchy of a distance education provider in a country can be shown in Figure 1, adapted from Rahman (2001a).

Figure 1. Communication/management hierarchy of open learning system

Central Campus

Communication hierarchy Regional Resource Centres (RRCs)

District Centres (DCs)/Town Centres (TCs)

Community Centres (CCs)/Local Centres (LCs)

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Interactive Multimedia Technologies for Distance Education in Developing Countries

maIn focus There is no mystery to the way effective distance education programs develop. They do not happen spontaneously; they evolve through the hard work and dedicated efforts of many highly committed individuals and organizations. In fact, successful distance education programs rely on the consistent and integrated efforts of learners, faculty, facilitators, support staff and administrators (Suandi, 2001). By adapting available telephone technology, it is easy to implement computer communications through dial-up connectivity. Due to non-availability of high-speed backbone, the bandwidth may be very low, but this technique can be made popular within organizations, academics, researchers, individuals and so forth. The recent global trend of cost reduction in Internet browsing has increased Internet users in many countries. However, as most of the ISPs are located either in the capital or larger metropolitan cities, establishment of regional centres and remote tele-centres located at distant places are now time-demanding. Teleconferencing, videoconferencing, computer-based interactive multimedia packages and various forms of computer-mediated communications are technologies that facilitate synchronous delivery of content and real-time interaction between teacher and students as well as opportunities for problem-solving, either individually or as a team (Rickards, 2000). Students in developing countries with limited assets may have very little access to these technologies and thus fall further behind in terms of information infrastructure. On the other hand, new telecommunications avenues, such as satellite telephone service, could open channels at a reasonable cost to the remotest areas of the world. Integrated audio, video and data systems associated with interactive multimedia have been successful distance education media for providing educational opportunities to learners of all ages,

at all levels of education and dispersed in diversified geographical locations (Rahman, 2001b). To make the learning processes independent of time and place in combination with technologybased resources, steps need to be taken towards interactive multimedia methods for disseminating education to remote rural-based learners. Computer technology evolves so quickly that the distant educator focused solely on innovation “not meeting tangible needs” will constantly change equipment in an effort to keep pace with the “latest” technical advancements (Tarusikirwa, 2001). Hence, availability of compatible equipment at a reduced price and integration of them for optimized output becomes extremely difficult during the implementation period, and most of the time, the implementation methodology differs from theoretical design. Sometimes the implementation becomes costly, too, in comparison to the output benefit in the context of a developing country. Initially, computers with multimedia facilities can be delivered to regional resource centres and media rooms can be established in those centres to be used as multimedia labs. Running those labs would necessitate involvement of two or three IT personnel in each centre. To implement and ascertain the necessity, importance, effectiveness, demand and efficiency, an initial questionnaire can be developed. Distributing periodical surveys among the learners would reflect the effectiveness of the project for necessary fine-tuning. After complete installation and operation of a few pilot tests in specific regions, the whole country can be brought under a common network through these regional centres. With a bare minimum information and communications technology (ICT) infrastructure support at the national level, the learning centre can initially focus around 40Km periphery around the main campus, providing line-of-sight radio connectivity ranging from 2Km to 40Km depending on demand and connectivity cost to the nodal/subnodal learning centres. These could be schools

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or community information centres, or affiliated learning centres under the main campus. To avail the best opportunity of interactive communications, collaborative approaches could be considered with similar institutions. Offering Internet services at the grass-roots level and effective collaborations among the distance educator and other service providers can set a viable model at the outset. Figure 2, adapted from Rahman (2001a), shows the growth pattern and mode of connectivity between these types of institutions. In the future, more such institutions can easily be brought under this communications umbrella. A needs-based survey may be necessary during the inception period to enquire about the physical location, demand of the community, requirement of different programs, connectivity issues, the sustainability perspective and other related issues before the establishment of RRCs/DCs/CCs. Following different national consensus, education statistics and demand of local populations, the

locations need to be justified (Rahman, 2003). The survey may even become vital for the learning centre authority at a later stage during operation and management.

future trends In the absence of a high-speed Internet backbone and basic tele-communications infrastructure, it is extremely difficult to accommodate a transparent communications link with a dial-up connection, and at the same time it is not at all cost effective to enter the Internet with dial-up connectivity. However, in recent days, availability of VSAT (Single Channel Per Carrier/Multiple Channel Per Carrier), radio link (line of sight and non-line of sight) and other Wireless-Fidelity (Wi-Fi) technology has become more receptive to the terminal entrepreneurs and in a way more acceptable to the large group of communities.

Figure 2. Growth pattern and mode of communications between main campus of the distance education provider and other service providers Main Campus

ISPs/Link providers

Mode of Communications

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RRCs

Their regional offices

District centres/ Community centres

Their local offices

Interactive Multimedia Technologies for Distance Education in Developing Countries

Using appropriate techniques, Web-based multimedia technology would be cheaper and more interactive at the front end, accumulating all acquired expenses (Suandi, 2001). Diversified communications methods could easily be adapted to establish a national information backbone. By superimposing it with other available discrete backbones in time without restricting each other’s usage, the main backbone can be made more powerful and, hence, be effectively utilized. A combination of media can be used in an integrated way by distant mode course developers. The materials may include specially designed printed self-study texts, study guides and a variety of select articles; or course resource packs for learners containing print, video cassettes, audio cassettes and CDs for each course stage. Computer communication between learners and learners and educators plays a key role in using the education network system (e-mail, Internet, MSN, tele-conferencing, video conferencing, media streaming, etc.). These distance education strategies may form hybrid combinations of distance and traditional education in the form of distributed learning, networked learning or flexible learning, in which multiple intelligence are addressed through various modes of information retrieval (Gunawardena & McIsaac, 2003). At the same time, infrastructures need to be developed to cope with the increasing number of distant students and availability of low-cost multimedia technologies. In this regard, a dedicated Web server can be treated as an added resource among the server facilities. The Web server is to act as a resource to all students, tutors, staffs and outsiders, providing necessary support in the knowledge dissemination process and a tool for collaborative learning/teaching. Information infrastructure has to be established, so remote stations could log into the Web server and download necessary documents, files and data at reasonably high speed.

conclusIon Effective utilization of capital resources, enhancement towards an improved situation and success of collaborative learning depends largely on socio-economics, geographical pattern, political stability, motivation and ethical issues (Rahman, 2000b). Through sincere effort, concrete ideology, strong positive attitude, dedicated eagerness, sincerity and efficiency, distance educators may achieve the target of enlightening the common citizen of the country by raising the general platform of education. This sort of huge project may involve not only technology issues, but also moral, legal, ethical, social and economic issues, as well. Hence, this type of project may also need to determine the most effective mix of technology in a given learning environment to offer technology-based distant teaching as efficient as traditional face-to-face teaching. Other diversified facts should be explored, especially by low-income-generating countries, when considering adoption of these advanced technology-based methods in distance education. Socio-economic structure comes first, then availability with affordability, as well as whether those remotely located students could at least be provided with hands-on multimedia technology familiarity. While university academics may debate the educational merits of interactive multimedia environments from theoretical viewpoints, practical issues like accessibility and flexibility of learning experiences have potentially significant impact on the effectiveness of student learning. With a huge population living in rural areas, spreading education to the rural-based community needs tremendous planning and effort (Rahman et. al., 2000), and a gigantic amount of financing for its successful implementation. Affordability of high-tech infrastructure would necessitate a huge amount of resources, which might not be justified at the initial period, where demand of the

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livelihood would divert towards some other basic emergency requirements. High initial investment cost would discourage entrepreneurs to be easily convinced, and gear up beyond a pre-conceived state of impression with additional funding. Absence of a high bandwidth backbone of information infrastructure in developing countries would put the high-tech plan in indisputable difficulties for smooth implementation and operation. A limited number of PCs per student/academic/ staff would contradict with the motive of affordable distribution of technology-based methods to remotely located stations.

references Barker, B., & Baker, M. (1995). Strategies to ensure interaction in telecommunicated distance learning. Paper presented at Teaching Strategies for Distance Learning, 11th Annual Conference on Teaching and Learning, 17-23. Cunningham, S. et al. (2000). The Business of Borderless Education, Canberra, Department of Education, 2000. Gunawardena, C.N., & McIsaac, M.S. (2003). Handbook of distance education. Kochmer, J. (1995). Internet passport: Northwestnet’s guide to our world online. Bellevue: NorthWestNet and Northwest Academic Computing Consortium. Mahajan, S., Sanone, A.B., & Gujar, R. (2003). Exploring the application of interactive multimedia in vocational and technical training through open and distance education. In Proceedings of the 17th AAOU Annual Conference, Bangkok, November 12-14. Murphy, K. (1995). Designing online courses mindfully. Invitational Research Conference in Distance Education. The American Center for the Study of Distance Education.

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Primary Research Group. (2002). The survey of distance and cyber-learning programs in higher education (2002 edition). New York: Primary Research Group. Rahman, H. (2000a, September 27-30). A turning point towards the virtuality, the lone distance educator: Compromise or gain. Paper in the Learning 2000: Reassessing the Virtual University Conference, Virginia Tech. Rahman, H. (2000b, September 14-17). Integration of adaptive technologies in building information infrastructure for rural based communities in coastal belt of Bangladesh. Paper in the First Conference of the Association of Internet Researchers, University of Kansas, Lawrence. Rahman, H. (2001a, April 1-5). Replacing tutors with interactive multimedia CD in Bangladesh Open University: A dream or a reality. Paper in the 20th World Conference on Open Learning and Distance Education, Dusseldorf, Germany. Rahman, H. (2001b, June 1-3). Spreading distance education through networked remote information centres. Paper at the ICIMADE2001, International Conference on Intelligent Multimedia and Distance Education, Fargo, ND. Rahman, H. (2003). Framework of a technology based distance education university in Bangladesh. In Proceedings of International Workshop on Distributed Internet Infrastructure for Education and research, BUET, Dhaka, Bangladesh, December 30, 2003-January 2, 2004. Rahman, M.H., Rahman, S.M., & Alam, M.S. (2000). Interactive multimedia technology for distance education in Bangladesh Open University. In Proceedings of the 15th International Conference on Computers and their Applications (CATA2000), New Orleans, LA, March 29-31. Rickards, J. (2000). The virtual campus: Impact on teaching and learning. In Proceedings of the IATUL2000, Queensland, Australia, July 3-7.

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Sherry, L. (1996). Issues in distance learning. International Journal of Distance Education, AACE. Suandi, T. (2001). Institutionalizing support distance learning at Universiti Putra Malaysia. In Proceedings of the Second Pan Commonwealth Forum of Open Learning PCF2, Durban, South Africa, July 29-August 2. Tarusikirwa, M.C. (2001). Accessing education in the new millennium: The road to success and development through open and distance learning in the Commonwealth. In Proceedings of the Second Pan Commonwealth Forum of Open Learning PCF2, Durban, South Africa, July 29-August 2. Thach, L., & Murphy, K. (1994). Collaboration in distance education: from local to international perspectives. American Journal of Distance Education, 8(3), 5-21. UNESCO. (2001). Teacher education through distance learning, summary of case studies. October 2001.

key terms Developing Countries: Developing countries are those countries in which the average annual income is low, most of the population is usually engaged in agriculture and the majority live near the subsistence level. In general, developing countries are not highly industrialized, dependent on foreign capital and development aid, whose economies are mostly dependent on agriculture and primary resources, and do not have a strong industrial base. These countries generally have a gross national product below $1,890 per capita (as defined by the World Bank in 1986).

Information and Communications Technology (ICT): ICT is an umbrella term that includes any communication device or application, encompassing: radio, television, cellular phones, computer and network hardware and software, satellite systems and so on, as well as the various services and applications associated with them, such as videoconferencing and distance learning. ICTs are often spoken of in a particular context, such as ICTs in education, health care or libraries. Interactive Multimedia Techniques: Techniques that a multimedia system uses and in which related items of information are connected and can be presented together. Multimedia can arguably be distinguished from traditional motion pictures or movies both by the scale of the production (multimedia is usually smaller and less expensive) and by the possibility of audience interactivity or involvement (in which case, it is usually called interactive multimedia). Interactive elements can include: voice command, mouse manipulation, text entry, touch screen, video capture of the user or live participation (in live presentations). Multiple Channel Per Carrier (MCPC): This technology refers to the multiplexing of a number of digital channels (video programs, audio programs and data services) into a common digital bit stream, which are then used to modulate a single carrier that conveys all of the services to the end user. Single Channel Per Carrier (SCPC): In SCPC systems, each communication signal is individually modulated onto its own carrier, which is used to convey that signal to the end user. It is a type of Frequency Division Multiplexing/Frequency Time Division Multiplexing (FDM/FTDM) transmission where each carrier contains only one communications channel.

This work was previously published in the Encyclopedia of Multimedia Technology and Networking, edited by M. Pagani, pp. 447-453, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.32

Geographic Information Systems Research and Data Centers John Abresch University of South Florida-Tampa, USA

AbstrAct The use of geographic information in a variety of research and educational endeavors has created a number of challenges involving data management and dissemination in support of educational processes. Academic libraries, using computing services and virtual libraries, have provided a framework for supporting the use of geographic information within academic communities. This chapter examines the development and implementation of a geographic information systems (GIS) research and data center within the digital environment of a “virtual library” in a large urban university. The chapter will also highlight specific organizational, design, and technical aspects of three exemplary digital geospatial centers, which served as the basis for creating a model GIS Center. In addition, federal data standards

and issues for cataloguing geospatial data will be examined. The chapter concludes with a discussion of future issues and technological challenges for GIS research and data centers.

OVErVIEW OF GIs Geographic information systems programs are more than tools for the production of maps. A GIS can store and manipulate geographic data for spatial analysis in a variety of environments, including urban planning, resource management, transportation networks, and public administration. In addition, GIS applications have been adapted to academic research as academicians find GIS a valuable tool for research grants and projects.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Geographic Information Systems Research and Data Centers

Designed for use on computer mainframes and written in languages such as UNIX, early GIS programs were organizationally complex and not intuitive to the average user. During the 1990s, technological developments in computer hardware and software provided impetus for the rapid growth in the field of GIS, from hardware configurations to the production of maps. A significant impact to the field was the introduction of desktop mapping software programs, such as Environmental Systems Research Institute’s (ESRI) PC Arc/Info, Arcview, and MapInfo Corporation’s MapInfo software series. These GIS software programs, designed for a Windows operating environment, broadened the scope of users of the programs and were designed for a variety of user skill levels.

the development of gIs In 1990, the Geography Department at the University of South Florida (USF) began offering courses in GIS methods and techniques, using ESRI’s desktop software, ArcInfo, and ArcView. The GIS classes explored the underlying spatial theories of GIS, environmental modeling, and socioeconomic trends in urban analysis. These classes also educated the initial group of GIS users on the USF campus, increasing the computer literacy and use of these programs by other faculty, staff, and students. Soon, GIS programs, data, and applications were being utilized by a number of academic disciplines (anthropology, biology, civil engineering, and geology) and in a number of research institutes (the Center for Urban Transportation and Research, the Florida Center for Community Design and Research, and the Louis de la Parte Florida Mental Health Institute). To facilitate access to products, USF procured a university-wide site license from ESRI for a suite of software applications. Faculty

began producing voluminous amounts of digital geospatial and other related data in a wide variety of subjects. The data was produced in a range of heterogeneous formats for research projects and for use within classrooms. Through its Virtual Library, the USF Library System plays an important role in providing support to the university’s increasingly networked computing community. The library system offers educational and research support through an online interface that leads the user to a variety of library services, accessibile to electronic databases, and the library catalog. The foundation of the online services and resources are the traditional library strengths of information collection, description, organization, and dissemination. The combination of the traditional and innovative strengths of the library system makes it well suited to support the educational and research needs of the GIS community at the University of South Florida. By 1999, in response to the growing use of GIS, the Council of Deans adopted a proposal to investigate the feasibility of establishing a library-facilitated geographic information systems (GIS) research and data center. A year later, a task force, comprised of research and teaching faculty in conjunction with public and private sector GIS practitioners, determined that the main mission of a GIS Research and Data Center was data stewardship and management to support the University’s GIS research needs as well as to serve as a bridge to external GIS communities (Reader, Chavez, Abresch, et al., 2000). To further define the primary functions of the Center, the Task Force Committee examined both Association of Research Libraries directives and the role of other libraries in the establishment of other regional spatial data centers.

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exemplary dIgItal geospatIal centers alexandria digital library A significant effort in establishing a digital spatial library was the creation of the Alexandria Digital Library at the University of California - Santa Barbara, funded by the National Science Foundation in 1994. The Library’s collection and services focused on georeferenced information: maps, images, data sets, and other information sources with links to geographic locations (Hill et al., 2000). Much of the information in the collection was primarily of the University’s service area and adjoining Southern California region. A key aspect of this collection was the ability to perform data queries and retrieve results by geographic location. The basic means of describing and finding information utilized a geographic footprint. A footprint depicts the location on the surface of the earth associated either with an object in the collection or with a user’s query. Either a point or a polygon represents the footprint, with latitude and longitude coordinates (Hill et al., 2000). As a user queries the collection through a user interface, the user creates a footprint or an interactive map to indicate the area of interest (the query area). The query area is matched with the object footprints in the metadata to retrieve relevant objects about the query area. This approach to query structure allows the user to choose arbitrary query areas and is not limited to geographic areas with place names. The objects in the collection that fall within a particular query area do not require the names associated with them that the user enters (Hill et al., 2000). By translating a user’s text-based query into a footprint query, the user can retrieve all types of information about a location including remote sensed images, data sets, aerial photographs, and textual information. The Alexandria Digital

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Library configured its catalog for searches to retrieve objects that are in both online and physical formats (Hill et al., 2000).

Idaho geospatial data center In 1996, building upon the Alexandria Digital Library model, a team of geographers, geologists, and librarians created the Idaho Geospatial Data Center (IGDC) as a digital library of public domain geographic data (Jankowska & Jankowski, 2000). Funded via a grant from the Idaho Board of Education’s Technology Incentive Program, the library contained a number of digital geospatial datasets. Much of the collection contained public domain information from federal and state sources. For example, digital line graphs (DLGs) and digital raster graphics were obtained from the United States Geological Survey, and the TIGER boundary files for the state of Idaho were obtained from the United States Bureau of the Census. The site provided an interactive visual analysis of selected demographic and economic data for counties in Idaho. It also provided interactive links to other state and national spatial data repositories. As a theoretical and practical foundation, the team used a set of parameters defined by Goodchild (1998). Goodchild’s geolibrary includes a browser (or specialized software application) running on the user’s computer which provides access to the geolibrary through a network connection, and a basemap or geographic frame of reference for the browser’s queries. A basemap provides an image of an area corresponding to the geographical extent of the geolibrary collection. The size of the basemap depends on the scale of the search, ranging from a large geographic area (such as a state) to a smaller location (such as a city block). In addition, the geolibrary has a gazetteer (or index) linking place names to a map and a large numbers of collection catalogs on distributed computer servers. Through basic

Geographic Information Systems Research and Data Centers

server-client architectures, users access servers over a network via their browser. Ideally, a geolibrary would provide open access to many types of information with geographic referenced queries regardless of the storage media (Jankowska & Jankowski, 2000). The development of the geolibrary’s browser, using Microsoft Visual Basic 5.0 and ESRI MapObjects technology, was a key aspect of the IGDC. The browser interface consists of three panels, resembling the Microsoft Outlook user interface. From the first or map panel, a user explores the geographic coverage of the geolibrary and selects an area of interest. The second panel in the interface indicates where the query is performed. The final panel displays the query results for analysis and options to download the spatial data (Jankowska & Jankowski, 2000).

cornell university geospatial Information repository (cugIr) The concept of an Internet-based geospatial data distribution system was the underlying theme in establishing the Cornell University Geospatial Information Repository (CUGIR) at the Albert R. Mann Library. In 1997, the Mann Library received a grant from the Federal Geographic Data Committee’s Cooperative Agreements Program (CCAP) to build a clearinghouse node as part of the National Spatial Data Infrastructure (NSDI) Federal Geospatial Clearinghouse (Herold, Gale and Turner, 1999). CUGIR contains geospatial data and metadata related to the state of New York. Standardization was a significant theme in organizing the library’s existing collection of digital geospatial data. The library first converted original file formats of its TIGER/Line files and DLG files into shapefile formats. Additional data covered a variety of socio-economic and physical features for each of the 62 counties in the state of

New York. Since the accessibility of this information from remote users would depend on metadata and information retrieval standards, the Mann Library chose the content standard of the Federal Geographic Data Committee (FGDC).

creatIon of the usf gIs research and data center After reviewing the structures and practices of these three digital geospatial data centers, the USF Task Force identified eight specific tasks for its emerging Center: to provide and maintain a Web-based GIS interface to view spatial data and perform basic data manipulations; to provide virtual and on-site access to spatial data collections and GIS information; to serve as a point of data receipt from federal, state, and local sources; to describe and organize (i.e., catalog) existing and future spatial data collections in accordance with established metadata standards; to acquire and maintain spatial data collections; to provide a spatial data “interlibrary loan” service; and to catalog and disseminate information about USF GIS research initiatives and activities. The final task was to provide additional services including establishing a referral database; providing support for grant writers and instructors; acting as a liaison between university and public/private-sector GIS users; and securing access to ESRI software applications (Reader et al., 2000). Identified as the first task, the proposed Website would enable different search modes for the Center’s holdings, including subject, keyword, and geographic-based searches. The site would also include an extensive and categorized listing of digital spatial data links, including links to agencies and organizations that contributed data. Finally, the site would function as the main information and advertising gateway for the Center (Reader et al., 2000).

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Implementation Beginning in July 2000 under the direction of a GIS Librarian, the Center began assembling the necessary computer hardware. Two network servers and a number of Dell workstations (with enough memory and processing speed to handle GIS data transactions) were procured and loaded with a suite of ESRI GIS products. A Hewlett Packard plotter and printers were used for the production of paper maps and other output. Library support staff attended workshops to acquire basic knowledge of spatial skills and to operate and apply the GIS software to databases. With an emphasis on acquiring data holdings pertinent to the USF service area, the center staff began to acquire digital spatial data. The first information layers acquired were of the USF service area. Subsequently, the Center acquired spatial data from a number of other federal agencies, state and local governments, and public and private organizations that produced spatially referenced data. The initial data holdings were built from local governmental agency data (such as the Planning Commission and Property Appraiser’s Office of Hillsborough County and the City of Tampa). The information, acquired in ArcView shapefile format, was easily imported. The shapefiles contained a variety of physical, political, and socioeconomic layers of information. The GIS coverages were built by adding extensive local attribute information to public domain data, such as United States Census TIGER/LINE Files. Information for surrounding counties and cities were provided by their respective agencies. Additional digital spatial data was provided by state agencies. For example, the Southwest Florida Water Management District provided shapefiles that described a diversified array of data from environmental assessments that mapped to the Department of Revenue’s Florida County fiscal

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reports. Different types of imagery, such as satellite imagery and aerial photography, were also acquired in shapefile format. Once acquired, all digital spatial information had to be catalogued using commonly employed techniques in bibliographic description.

descrIptIon documentatIon and geospatIal InformatIon Most digital spatial data is distributed in CDROM form and comes in a variety of GIS data formats, including thematic vector information on a particular location or raster files of a unique area satellite image. Other digital spatial data may be disseminated as a computer file in a specialized GIS software format via FTP (file transfer protocol) or by an e-mail attachment. (Larsgaard, 1999). All this data is accompanied by a file on its attributes, commonly known as metadata.

metadata Simply defined, metadata is data about data. One definition of metadata for spatial information is “…the data that describes the content, data definition and structural representation, extent (both geographic and temporal), spatial reference, quality, availability, status and administration of a geographic dataset” (Smits, 1999, p.305). Metadata can be interpreted as the equivalent of the recto and verso of the title page of a book, where catalogers search first for data when creating a bibliographic description for an item (Welch & Williams, 1999). The producer of the geospatial data creates most metadata. With digital media, metadata may be supplied by an accompanying printed document, a CD-ROM or diskette file (named metadata), or as a “readme” text file attachment. Sometimes the cataloger may have to contact the

Geographic Information Systems Research and Data Centers

producer of the geospatial data for further information. Most digital geospatial data generally adhere to Federal Geographic Data Committee (FGDC) Data Content Standards.

federal geographic data committee data content standard All federal data producers are required to produce metadata for their geospatial data using the FGDC data content standard. Many state data producers, who contribute to state spatial data clearinghouses, also follow the FGDC standard (Welch & Williams, 1999). Digital geospatial data acquired from local government agencies often lack the level of encoding performed by state or federal data producers. Commercially available GIS software and data from private developers usually contain comprehensive metadata describing items, such as data source and scale. Developed from the user’s perspective, the FGDC content standard is based on four factors: what information is necessary to determine the availability of a set of geospatial data; the fitness of the set of geospatial data for an intended use; the means of accessing the set of data, and what is needed for the successful transfer of the data. The FGDC (2001) has established names, definitions, and values for the data and compound elements. The FGDC Manual, which includes a glossary, outlines all of the items to be included in a metadata description. There are seven basic types of information found in the standard: identification information, data quality information, spatial data organization; spatial reference information, entity and attribute information, distribution information, and metadata reference information (Herold et al., 1999). A second feature of the standard is the definition of mandatory fields. Only information about the production of metadata is mandatory for all records. All other sections of the standard are mandatory if applicable. Then, within each section are subfields that can be defined as mandatory,

mandatory if applicable, or optional. The flexibility of description allows metadata creators to determine the level of detail that they can provide or the level of support based on perceived user needs. Finally, the FGDC content standard only defines the content of the record; it does not define how to organize the information or how data should be displayed. The FGDC uses Standard Generalized Markup Language (SGML) for document type definition, which makes metadata records easy to index and to share. The server software uses a Z39.50 protocol, which enables seamless searching of collections. By using the FGDC content standard, SGML, and the Z39.50 protocol, digital geospatial data can be easily utilized by remote users (Herold et al., 1999). The next step is how best to incorporate the metadata of the geospatial data into the metadata of the MARC (Machine Readable Cataloging) bibliographic record, in order to provide full access to geospatial data through a library’s online catalog.

the marc format and digital cartographic data The MARC bibliographic record is an industrywide standard for cataloging bibliographic information, used extensively by libraries, database vendors, and library services companies across the United States. The MARC record contains descriptive information of an item including author(s), titles and variants of titles, subject headings, a classification (or call) number, as well as other bibliographic data elements based upon the format of the item (Furrie, 2000). Recently, the academic library community has begun to address how to describe digital geospatial information using the MARC format (Welch & Williams, 1999). In 1998, several offices of the Library of Congress (the Cataloging Policy and Support Office, Network Development and MARC Standards Office, and the Geography and Map Division) issued standards for identifying

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materials to be catalogued as a map format and as a computer (formerly machine-readable data file) format (Larsgaard, 1999). More recently, the Joint Steering Committee for the Revision of the AACR2 (Anglo-American Cataloging Rules 2nd edition) discussed changes in the rules. Chapter 3 of the AACR2r deals with the graphic representation of information concerning digital cartographic materials. Chapter 9 outlines the description of computer files and data, though the focus of the chapter appears to be on numeric databases rather than geospatial data. By interpreting information about the spatial data provided by the producer of the geospatial dataset, a cataloger can create a more detailed bibliographic description (Larsgaard, 1999). In describing the primary nature of an item, especially its intellectual and physical form, Larsgaard (1999) offers several MARC examples for geospatial data on CD-ROM. For example, if the 007 field, which describes most cartographic materials, is used to describe an electronic atlas, it would display as: 007 |a a{GMD: map} |b d {SMD; atlas} |c {do not use this subfield} |d c{multicolor} |e e {physical medium: synthetic} |f n {type of reproduction:not applicable} |g z {production/reproduction details: other} |h n {positive/negative aspect:not applicable} (Larsgaard, 1999, p. 366). After the 007 field, the 008 field is intended for coding primary characteristics of the material. Values for the 008 field are often given in the mnemonic beginning line of a record. Larsgaard (1999) notes that each 008 field begins with the same 00-17 positions and ends with the same 35-39 positions. These positions have to do with dates (Date), language (Lang), when the record was modified (Mrec), and cataloging source (Srce). The remaining fields are Relief, Projection, Type of cartographic material, Government publica-

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tion, Index, and Special format characteristics (Larsgaard, 1999, p. 367). In the 245 field (General Material Designation), the Anglo-American Cataloging Committee for Cartographic Materials is considering using the term electronic resource in the 245 field, as a substitute for computer file, to better reflect digital geospatial data. For example, 245 |h {cartographic material {electronic resource}} (Larsgaard, 1999, p. 367). Welch and Williams (1999) also note several concerns with cataloging digital data within the Mathematical Data Area, including the 256 field on file characteristics, the 352 field on digital graphic representation, and the 342 and 343 fields on geospatial reference data area. For example, classifying scale for geospatial objects is difficult. Since the user can zoom in and out of different scales within a GIS interface, the phrase “scale not given” is used for descriptive purposes. Another aspect of scale is that of the input scale. When a digital cartographic item has been digitized from a paper map, certain elements are included in the electronic version selected on basis of scale. The input scale would then affect both the content of the item and the extent to which the data can be used for other purposes. Used in recording projection, the 342 field uses additional subfields to add information on the longitude of central meridians and latitude of projection centers. In effect, the 342 field records information about the vertical and horizontal coordinate systems of a data set (projection or grid) and may be repeated (Welch & Williams, 1999). The 255 field also contains the geographic extent (coordinates) of the geospatial dataset in a subfield of c. The information described above is derived from the metadata description when the metadata producer has followed FGDC standards. Describing digital geospatial data can be difficult because it utilizes a specialized nomenclature that is often

Geographic Information Systems Research and Data Centers

unfamiliar to non-map catalogers. The availability and comprehensiveness of metadata and local library cataloging policies determine the amount of information entered in the Digital Graphic Representation Fields (352) and Geospatial Reference Data fields (342 and 343) (Welch & Williams, 1999; Larsgaard, 1999). For example, the standard adopted by the USF GIS Research and Data Center includes basic descriptive bibliographic and cartographic elements of the GIS item, including data source, title, spatial display characteristics, and software requirements for viewing. The 352 and 342 fields are used when a need arises for records that are more comprehensive. When the cataloger cannot adequately describe the geospatial data using the mathematical data fields, additional information can be included in the MARC note fields. The 514 field (data quality note) contains information about the accuracy and completeness of the data. The 551 field (entity attribute) allows the cataloger to add attribute information to the record. The 538 field (systems requirements) would include notes on the type of GIS software processing abilities needed to properly display the digital spatial data. (Welch & Williams, 1999). When classifying geospatial data (050 field), the Library of Congress treats digital cartographic material as a form subdivision in its G classification schedule. The cataloger classifies geospatial data by map or atlas number without regard to style, and uses a format indicator to indicate the location of the CD-ROM or diskette. When creating subject headings for this data, the Library of Congress uses the 653 field form, which allows the construction of an index term added entry that is not constructed by standard subject heading/thesaurus-building conventions (e.g., Maps—Digital—Raster or Maps—Digital—Vector). Use of this form division can also be used after other materials designations such as Remote-Sensed Images-Digital-Raster (Welch & Williams, 1999; Larsgaard, 1999).

The amount of bibliographic information for geospatial data can become quite lengthy. If there is good metadata and original documentation available, the cataloger can create detailed MARC records for the data. Another strategy to enable access to information is to mount the geospatial metadata on a separate webpage, and then supply the URL for the user through the MARC record via either the 500 field (general note) or the preferred 856 field (electronic location and access) (Welch & Williams, 1999).

conclusIon Using ESRI’s ArcIMS software, the USF Library System established a beta-site on which initial coverages of various aspects of socioeconomic data pertaining to Hillsborough County were mounted. In using standards, such as Chapters 3 and 9 from the ACCR2 and with additional classification information from the FGDC metadata standards, it is easy to catalog geospatial items using the MARC format. The MARC format enables the tagging of important descriptive data elements of the bibliographic record for information retrieval purposes. For the next phase of the USF GIS Research and Data Center, staff will be actively involved in the creation of a search interface, using fields, coordinates, and free text keywords about geospatial data. The building of a Web-based interface will create an efficient and flexible means to distribute and collect digital geospatial data.

future Issues The use of GIS technology in the online environment of the Virtual Library will continue to evolve as an important resource for academic communities across the nation. The GIS Research and Data Center initially functioned solely in a

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data storage capacity, acquiring and archiving significant digital geospatial data. Academic GIS Centers have a number of important roles in their communities. First, GIS centers play a vital role in community development, both as a data storage center and in data analysis for local and state agencies. Second, the use of GIS as a teaching resource is expanding, as faculty, staff, and students receive instruction in the proper use of GIS software. This will require academic institutions to address issues of accessibility and site licensing issues. In addition, feedback from the community of GIS users will assist in evaluating computer hardware and software needs and shaping collection development policies.

references Decker, D. (2001). GIS data sources. New York: John Wiley & Sons. Federal Geographic Data Committee (2001). Content standard for digital geospatial metadata. Retrieved November 12, 2001, from Federal Geographic Data Committee Web site at http://www. fgdc.gov/metadata/contstan.html Frank, S. (1994). Cataloging digital geographicdata in the information infrastructure: A literature and technology review. Information Processing & Management, 30(5), 587-606. Furrie, B. (2000). Understanding MARC bibliographic machine readable cataloging. Washington, DC: Library of Congress. Goodchild, M.F. (1998). What is a GeoLibrary? White Paper for the Distributed GeoLibraries Workshop, 15-16 June 1998, Washington, DC, hosted by National Research Council Distributed GeoLibraries Panel. Retrieved November 12, 2001, from http://www4.nationalacademies. org/cger/besr.nsf/

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Herold, P., Gale, T. D., & Turner, T. P. (1999, winter). Optimizing Web access to geospatial data: The Cornell University Geospatial Information Repository (CUGIR). Issues in Science and Technology Librarianship. Retrieved November 11, 2001, from http://www.library.ucsb.edu/istl/ previous.html Hill, L. L., Janee, G., Dolin, R., Frew, J., & Larsgaard, M. (1999). Collection metadata solutions for digital library applications. Journal of the American Society for Information Science, 50(13), 1169-1181. Hill, L. L., Carver, L., Larsgaard, M., Dolin, R. Smith, T.R., Frew, J., & Rae, M-A. (2000). Alexandria Digital Library: User evaluation studies and system design. Journal of the American Society for Information Science, 51(3), 246-259. Jankowska, M. A., & Jankowski, P. (2000). Is this a geolibrary? A case of the Idaho Geospatial Data Center. Information Technology and Libraries, 19(1), 4-10. Joint Steering Committee for Revision of AngloAmerican Cataloguing Rules (2001) News & Announcements:Outcomes of the Meeting of the Joint Steering Committee Held in Washington, DC USA, 2-4 April 2001 Retrieved November 10, 2001, from http://www.nlc-bnc.ca/jsc/0104out.html Korte, G. B. (2001). The GIS book. Albany: OnWord Press. Larsgaard, M. L. (1999). Cataloging cartographic materials on CD-ROMs. Cataloging & Classification Quarterly, 27(3/4), 363-374. McGlamery, T. P. (2000). Issues of authenticity of spatial data. IFLA Council And General Conference: Conference Proceedings. Retrieved ERIC database (ERIC Reproduction Service. Microfiche. No ED 450 779). McGlamery, T. P. (1995). Identifying issues and concerns:The University Of Connecticuts’s

Geographic Information Systems Research and Data Centers

MAGIC-A Case Study. Information Technology and Libraries, 14(2), 116-122. Reader, S., Chavez, T., Abresch, J. (2000). Report to the Council of Deans. GIS Research and Data Center Task Force. Unpublished manuscript, University of South Florida, Tampa. Rigaux, P., Scholl, M., & Voisard, A. (2002). Spatial databases: With application to GIS. New York: Morgan Kaufmann. Smith, L. C., & Gluck, M. (Eds.). (1996). Geographic information systems and libraries: Patrons, maps, and spatial information. Urbana: Graduate School of Library and Information Science, University of Illinois. Smits, J. (1999). Metadata: An introduction. Cataloging and Classification Quarterly, 27(3/4), 303-319.

Teng, A.T. (1991). Building geographic databases with input from federal digital data Files. Technical Papers ACSM/ASPRS annual convention, Baltimore. Bethesda: American Society for Photogrammetry and Remote Sensing and American Congress on Surveying and Mapping, pp. 208-216. U.S. Census Bureau. (2001) TIGER Overview. Retrieved November 11, 2001, from http://www. census.gov/geo/www/tiger/overview.html U.S. Geological Survey. (2001) USGS Digital Line Graph Data. Retrieved November 10, 2001, from http://edcwww.cr.usgs.gov/glis/hyper/guide/usgs_dlg Welch, G. D., & Williams, F. (1999). Cataloguing digital cartographic materials. Cataloging & Classification Quarterly, 27(3/4), 343-362.

This work was previously published in Building a Virtual Library, edited by A. Hanson and B. Levin, pp. 52-64, copyright 2003 by Information Science Publishing (an imprint of IGI Global).

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Chapter 3.33

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning Degan Zhang University of Science and Technology of Beijing, China Yuan-chao Li China University of Petroleum, P.R. China Huaiyu Zhang Northwest University, China Xinshang Zhang Jidong Oilfield, P.R. China Guangping Zeng University of Science and Technology of Beijing, China

AbstrAct As a new kind of computing paradigm, pervasive computing will meet the requirements of human being that anybody maybe obtain services in anywhere and at anytime, task-oriented seamless migration is one of its applications. Apparently, the function of seamless mobility is suitable for mobile

services, such as mobile Web-based learning. In this chapter, under the banner of seamless mobility, we propose a kind of approach supporting task-oriented mobile distance learning paradigm. Web-based seamless migration, which has the capability that task for mobile distance learning (MDL) dynamically follows the learner from place to place and machine to machine without learner’s

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

awareness or intervention by active service. Our key idea is this capability can be achieved by architecture of component smart platform and agent-based migrating mechanism. In order to clarify the approach, firstly, a description of the task for mobile distance learning and migrating granularity of task has been suggested. Then, the mechanism of seamless migration has been described, including solving several important sub-problems, such as transferring delay, transferring failure, residual computation dependency. Finally, our implemented platform for Web-based seamless migration has been explained, the validity comparison and evaluation of this kind of mobile distance learning paradigm is shown by an experimental demo. Suggested Web-based learning paradigm by seamless migration is convenient to distance learn during mobility and is useful for the busy or mobile distance learner.

IntroductIon It is known to all that pervasive/ubiquitous computing (Weiser, 1991) is a new computing paradigm fusing the technologies of computing, communication, and digital multimedia, which integrates information space and physical space of human being’s life, so it makes the computing and communication just like the life necessity, such as water, electricity, and air. This paradigm meets the requirements of human being that anybody maybe obtain services in anywhere and at anytime, so it is full of future. Nowadays, many ambitious projects have been proposed and carried on to welcome the advent of pervasive computing. There are a bunch of branch research fields under the banner of it, such as Seamless Mobility (Satyanarayanan, 2001). For seamless mobility, the history and context of computing task will be migrated with person’s mobility, and the computing device and software resource around this task will make adaptive change. The chief function requirement of seam-

less mobility is on the continuity and adaptability of computing task. The continuity is that the application can pause and continue the work without the loss of the current state and the running history. The adaptability is that the application is not restricted by computing device and context of service but adaptable to its environment. Apparently, this function of seamless mobility is suitable for mobile learning paradigm (Takasugi, 2001, 2003). For learner, it is necessary and accessible when he or she can NOT complete his or her learning task/courseware, such as video, audio, text, picture, etc., in one specified scene, he or she can go on learning the uncompleted task/courseware in other spots by seamless mobility based on the Web. In our opinion, this is a kind of mobile working paradigm—learning by seamless migration with computing task. But when seamless migration for computing task of learning is realized on PC, laptop, or PDA, there are several difficult problems to be solved: (1) Meet different networked Web environment, such as different OS platform. (2) Manage the seamless-service among multiple machine devices. (3) Describe computing task of learning and only migrate the relative parts of task interested by learner in order to reduce the delay produced by migrated data. In this chapter, we propose a test bed of learning by seamless migration for mobile learning, which can be suitable for the required dynamic changes to the network and environment without learner awareness or intervention, and the condition of only sitting in front of the desktop PC for mobile learning is unnecessary. The structure, mechanism, result of experimental evaluation of the test bed is reported. It makes the ultimate mobile system possible by dynamically implementing the changes required to follow the learner from place to place and machine to machine. The rest of this chapter will be organized as follows. Firstly, we give formal description of task of mobile distance learning and migrating

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granularity of task of learning. After that, we design and discuss efficient approach of Seamless Mobility based on agent for task-oriented mobile distance learning, along with the description of our implemented platform for Seamless Mobility. Finally, we evaluate the validity of the approach and platform for mobile distance learning and draw a conclusion.

descrIptIon for task of learnIng In order to clarify and realize how to transfer tasks of learning among different distance computing environments, firstly, a formal description and classification of task is required, which is independent of the realization mechanism. To adapt the environment of pervasive computing, a universal description language for task of learning should be used. Nowadays, the description languages for workflow or task of learning are mainly based on stationary computing environment (Simmons & Apfelbaum, 2001). However, the computing environment of seamless mobility is dynamic and mobile, so the description language should be abstract and self-adapted. Based on our knowledge, XML (Extended Markup Language) and SMIL (Synchronized Multimedia Integration Language) released by W3C can be used (Shi & Xie, 2003). The task or transaction of learning cared by learner is our alleged Task (in brief, T), which consists of subtask or sub-transaction Ti, each Ti is an independent unit of function. Because of the diversity of task, its subtask or atomic task may be different from each other. In order to keep the compatibility, the description of subtask should be abstract, mainly, the key and necessary parameters, such as Qos of subtask, environments, etc. During mobile distance learning, the task can be classified into three kinds based on DATA TYPE of its contents:

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1.

2.

3.

Event-Type: It is strict with the delay, the transferred bytes of subtask is few, but timely, semantic and no loss during transferring. Once the command of operation is done, the result should be shown. Stream-Type: It is not strict with delay and semantics, permitting a certain loss during transferring, but strict with jitteriness of transferring. Bulk-Type: It is different from event type because the transferred byte of subtask is much larger (maybe several Mbytes), and it is also different from stream type because when executed, it requires the integrality of data.

Described formally task of learning by SMIL is as follows:







…….



mobIle granularIty of the task How to deal with the problem of task-oriented mobile distance learning under the banner of seamless mobility? Currently, the usable technology is based on Mobile IP used as network-level

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

protocol and stationary or mobile agent used in application-level. Active and intelligent mobile agent controlled by running container can deploy or adjust dynamically its services according to application requirement or running status of network. As a kind of special computing resource, agent supports deployment of computing resource and mobility freely, which makes the system manage and adjust easily, so it is suitable for application of seamless mobility. During the task-oriented mobile distance learning, mobile granularity of the task should be traded off reliability, the communication volume of network, and so forth. According to integrity of transferred contents of the task, the mobile granularity of the task may be divided into “Strong Transfer” and “Weak Transfer,” and the mode of transferring may be controlled by the Travel Schedule/Plan. Strong Transferring means that total information involved in the current task must be transferred, after reaching the target terminal, the task can execute continuously from snapshot point. But in mobile WWW, it is difficult to collect total information of current task, to describe and record the executed status and necessity of task under the high bandwidth network, so the burden of this mode is very heavy and complex. Nowadays, the JVM is not supported this mode. Weak Transferring is only done for partial executing status and data, its speed is much faster then that of Strong Transferring, and its delay is much shorter then that of Strong Transferring. Of course, Weak Transferring has its shortcomings, for instance, the total historical executing status of task is difficult to be restored. So it is decided only by detailed scenario that which mode should be adopted in the application.

agent-based approach of task-orIented seamless mobIlIty Because the proliferation of mobile devices and the appearance of runtime environment give new challenges to support user mobility, we give a mechanism of integrating mobile devices into runtime environments to provide more computational, communication and storage capabilities to mobile distance learner. In this mechanism, we think that the data migrating is needed between different computing devices by different network, such as wireless infrastructure-based communication, multi-hop ad-hoc networks, dynamic topology without any infrastructurebased communication, Internet-based networks and different computing devices interconnected using IEEE 802.11x and Bluetooth technology. So a seamless and transparent migrating mechanism between different networking interfaces is needed. Seamless migrating between different networks for different computing devices by mobile agents is a basic feature for improving the quality of a perceived service under the pervasive computing mode. However, the heterogeneity also implies that the services are also distributed over the accessible networks. Based on context information, our mechanism spontaneously interoperates with available resources discovered in runtime environment so that it can improve the performance of mobile interactive distance learning.

Classification of Agent On the attribute of agent, it can be classified into two types. One is Stationary Agent, which is not mobile and kept in the agent environment (AE). The other is Mobile Agent (MA), which may be transferred in the AE. On the function of agent, it can be classified into three types, Terminal Agent (TA) (including User Agent (UA)), Naviga-

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tion Agent (VA) (including Network Capability Agent (NCA) and Location management Agent (LMA)), Task Agent (KA) (including Execution/code Agent (EA) and Data Agent (DA, such as Service Agent (SA), User Document Database Agent (UDDA))). These agents may be Stationary or Mobile Agent. Stationary or Mobile Agent (Danny & Mitsuru, 2001) is a kind of program with its name and can interact with other agents or resources when transferring from one network to another in different heterogeneous network (Karnik, 1991). This program can dynamically decide when and where to transfer. It can suspend at any running point or transfer to another computer and execute continuously. Mobile Agent also can clone itself or produce its sub-agent and transfer to other computer to do complex task in cooperation mode. Besides common attributes (such as autonomous, initiative, intelligent), mobility is its main attribute, which makes it roam among different networks. Mobile Agent is suitable for computing of large heterogeneous network like Internet. Mobile agent system (MAS) (Ciancarini, 2002) is a kind of system for creating, explaining, executing, scheduling, transferring, and terminating agent. Each system can run many agents. TA is one interactive interface for human and terminal devices. Users may search, browse, subscribe, and publish new service by TA. UA is on half of the user, which may transfer among different environments with the user. UA can partly store attribute data of the user and be used as buffer of current terminal. VA is used as addressing in the MAS and carry KA in its “MessageBox (MB).” KA is used as restoring runtime environment, executing task in the new environment, and recording each snapshot as current and history execution status.

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new approach of seamless mobility based on agent The basic strategy of transferring based on agents has two modes: 1. 2.

Strong Transfer from source node to target node Weak Transfer from source node to target node

The first mode is adapted for seamless mobile scenarios with smaller amount of transferred data, such as task of “Event-Type.” If the task is “Stream-Type” or “Bulk-Type,” the delay of transferring and unnecessary amount of data are larger, which is not adapted for seamless transferring on Mobile WWW. The second one may be implemented through two methods: partial information has been loaded on the target node/terminal station, downloaded the relative partial information timely during the runtime of task. This mode is adapted for the task with “Stream-Type” or “Bulk-Type,” which can reduce the transferred amount of data, the delay of transferring and improve the running efficiency, but occupied a certain storage space of target node. The basic transferring step of agents is as follows: 1. 2. 3.

4.

Determine the agents running on the source node Suspend the agents Snapshot or record the information of running agents and transfer them to target node Reconstruct or restore the information of running agents on the target node

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

In our opinion, the design of transferring method is considered from two aspects: 1. 2.

The transferring amount of data is total or partial. The occasion of suspending agent on the source node and restoring agent on the target node.

The existing transferring mechanisms (Takasugi, 2003) have NOT analyzed and discussed both of them deeply, especially, how to adapt for the application requirement of seamlessness of pervasive computing. In our opinion, it must deal with the problems of seamless transferring method, transferring delay, transferring failure and residual dependency, and so forth. Based on the basic strategy of transferring mentioned previously, now we discuss the new efficient mechanism of seamless mobility suggested by us. If the transferred amount of data is partial, and this part of information must be transferred firstly so that the task can restore the runtime environment and run continuously on the target node, this part of information is named “Key Set,” such as executing code, running status, and so on. According to the classification of agent discussed earlier, we make the following rule: 1.

2.

Navigation agent (VA): Need NOT do direct relative works with the task, which is familiar with the topological structure of subnet of target node and addressing in the network. The Data Structure of VA may be divided into two parts: one is itself “function body,” another is MessageBox (MB, mark as ) used as loading moved object and transferring in the subnet. Task agent (KA): Ddoes detail jobs, which includes executing the code, managing the data and environmental status, and so on. It can transfer with the Navigation Agent

3.

(VA) in the network and need NOT know the subnet’s structure. When transferred, KA looks up relative VA and joins in its MB firstly, and then sent to target node by VA.

For the sake of convenience, we give a kind of general case: TA wants KA on the logic node PA2 (Persona Avatar 2) to be transferred to another logic node PA3 (Persona Avatar 3), according to the time-topological relation of transferred object, the “TRAVEL SCHEDULE/PLAN” which is a kind of DATA STRUCTURE independent of agent has been made. The current scenario is that the TA is connected with logic node PA1 which is connected to logic node PA2 through double direction link, The arrow shows the connected direction and solid line with arrow shows KA can transit the logic link. The designed algorithm of seamless mobility includes eight main steps: 1.

2.

According to the subscribed TRAVEL SCHEDULE/PLAN for transferring, logic node PA2 lets VA begin addressing in the network according to the address supplied by logic node PA3, when the connection is successful, VA sends instruction “TransferNode” to Logic node PA3 as target node, VA+ transfer to PA3 after packing, the packet consists of the recorded structure of KA, the association relationship between KA, the space occupied by KA, the type of KA, the information of VA for task transferring and “Messenger” information for scheduling all agent (including VA, EA and DA), the state of arrived Messenger is not “Executing” but “Waiting” and storing in the queue of PA3. Logic node PA3 sends instruction “UpdateLinking” to all logic nodes connected

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3.

4.

5.

6.

7.

8.

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to PA2, such as logic node PA1 (Persona Avatar 1). The instruction includes the information modifying the link address, such as link ID, IP and Port of two ends. During the transferring, the Messengers to PA3 store in the relative queue and wait for executing unless the Key Set or the total task is finished to be transferred. When PA1 has received the instruction “UpdateLinking,” it creates the association to new link, and sends instruction “LinksUpdated” to logic node PA2. When PA2 has received all expected message “LinkUpdated,” and then sends instruction “ActiveNode” to logic node PA3. The message includes the list of all arrived Messenger. At the same time, PA2 delete the transferred VA+. When PA3 has received the message “ActiveNode,” received Messenger from PA2 listed in the tail of the queue. According to the topological relationship, under the rule of FIFO, PA3 activates the Messenger. Up to now, the transferring work is finished. When all Messengers are activated, each KA will restore running environment and do instruction “ExecuteTask.” During the executing of each KA, on the one hand, the historical snapshots will be recorded and saved (including the structure of KA, the association relationship between KA, the space occupied by KA, the type of KA, the information of VA for task transferring and Messenger information for scheduling all agent (including VA, EA and DA), the state of Messenger for scheduling), on the other hand, VA do the instruction “ListenTask” continuously and get the next transferring instruction “TransferSignal.” During the executing of KA, if no instruction “TransferSignal” is got by VA, KA will execute its task continuously until the task is completed, otherwise, it will stop executing and go to Step 1 for preparing the new

turn of transferring. The new turn process will be subject to the subscribed TRAVEL SCHEDULE/PLAN. The whole process of transferring is seamless. The previous approach is for a kind of general case. The other special cases is similar to this one, such as if TA wants to interact with PA2/PA3, PA1/PA2 should be involved according to the subscribed TRAVEL SCHEDULE/PLAN.

transferring failure problem In the pervasive computing environment, because the position of agent is often variable, the cases may be occurred. When the agent1 is being transferred to agent2 and wanted to be embedded in agent2 on node C to deal with the task together, but the agent2 has moved from node C to node D during the transferring of the agent1. That is to say, when agent1 arrives at node C, the agent2 can’t be found by the agent1. This case is so-called transferring failure problem. This kind of problem can’t keep the continuity of transferring of task. In order to solve this problem, there are three factors should be considered: 1.

2. 3.

When the position of agent has moved, how to know this change by other relative agents. When the transferring of agent, how to deal with the message sent to it. During the transferring of agent, whether the receiving agent can be transferred freely or not. Our solution is as follows:

1.

2.

When the agent moves to new node, it should send “Notification” Message to all other relative agents. Before the agent prepares to be transferred, it should look up the current position of receiving agent, at the same time, the transferring

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

3.

relationship and event should be sent to it by message The transferring topological relationship of agent should be determined. We select the rule “FIFO (First In First Out)” for it. When some agents begin to be transferred, the other receiving agent should be locked. After the transferring process is over, the receiving agent should be unlocked at once. Based on this rule, a signal semaphore may be set up.

The “Notification” Message may adopt three kinds: Unicast, Multicast, Broadcast. For different applications, in detail, it can be divided as follows: 1. 2. 3. 4.

Unicast, Multicast, Broadcast in the GROUP Unicast, Multicast, Broadcast among the GROUPS Broadcast from a agent to MAS Unicast, Multicast, Broadcast among different MAS

The formal expression of “Notification” Message of agent is that: Agent_Message_Notify (Sender, Receiver , Message) Correspondingly, the formal expression of Unicast, Multicast, Broadcast is that: Agent_Message_Notify (agent1, agent2, Message) Agent_Message_Notify (agent, Multicast (agentX) , Message) where “agentX” shows other agents Agent_Message_Notify (agent, Broadcast (Any), Message) where “Any” shows any agent of Groups

Based on the “time-topological” relationship, we design a kind of synchronal mechanism “addressing first, then locking and transmitting,” which can realize the synchronization between transferring agent and receiving agent. So the transferring failure problem can be solved radically and adapted for all kinds of application pattern. The “time-topological” relationship can be used in the “Travel Schedule for transferring.” The schedule may consist of certain travel sequences, each travel sequence includes the following DATA STRUCTURE: Schedule ID TP_ID, Schedule Name TP_ Name, Schedule Made Date TP_Time, Travel Number No, Transferring Object TP_Object, Transferring granularity TP_Granule, Source Address of Transferring Object TO_IPC, Target Address of Transferring Object TO_IPD, Transferring Condition TP_Condi, Transferring Mark TP_SnapshotPoint, Entry Address for Re-running TP_RunEntry. Transferring Condition TP_Condi, Transferring Mark TP_SnapshotPoint, Entry Address for Re-running TP_RunEntry are important for basic transferring operation, that is to say, Only the TP_Condi is OK, the “Travel Schedule for transferring” may be run, meanwhile, record and save “TP_ Snapshot Point” and “TP_RunEntry,” both for restoring the running environment. Whether TP_Condi is OK or NOT, the following aspects should be set and checked: 1.

2. 3. 4.

Whether or not the current status (may be divided into five kinds: Ready 1, Waiting 2, Transferring 3, Running 4, Destroyed 5) of agent is “Waiting 2.” Whether the target address TO_IPD may be reached or not. Whether the threshold of transferring delay is OK or not Whether the residual dependency cases may occur or not.

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transferring delay It is named “Transferring Delay” that the time interval from the suspended snapshot point of a running agent to the re-run snapshot point on the target node. The delay is one of main parameters to access the seamless mobility. The information for transferring an agent includes that instruction sets, address sets, runtime state when suspending, executing code, data, Messenger schedule information, and so on. Messenger schedule information and runtime state after being suspended must be transferred totally, but other information may not be transferred totally. Once the necessary information has been restored on the target node, especially the snapshot point of runtime state before being transferred, the agent may be re-run. Three factors is mainly involved in the transferring delay of agent: 1. 2.

3.

Which kind of transferring granularity, Strong Transfer or Weak Transfer. When will the agent be transferred, which is the suspending time of the agent. The occasion of suspending agent is divided into three kinds: Suspend immediately after determining to transfer, Suspend after the total information is transferred completely, Suspend after the Key Set is transferred successfully. When will the agent be restored and run, which is the restoring time of agent. The occasion of restoring agent on the target node is divided into two cases: restore after the total information is transferred completely, restore after the Key Set is transferred successfully.

In fact, there are three valid mapping forms based on the previous three factors:

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1.

2.

3.

Strong Transfer: Suspend after transferring, restore and run after finishing the whole information. Strong Transfer: Suspend after transferring, restore and run timely after finishing the Key Set information (at the same time, the whole residual information will continue transmitting). Weak Transfer: Suspend after transferring, restore and run after finishing the Key Set information (at the same time, the selected partially information will continue transmitting to the target node).

In the first mode, the transferring delay of agent includes that packing the whole information and transmitting, restoring the agent and the whole information on the target node. In the second mode, includes that packing the Key Set information and transmitting, restoring the agent and the Key Set. In the third mode, includes that packing the Key Set information and transmitting, restoring the agent and the Key Set. In the same condition, the delay of the first one is longest, the third one in shortest.

residual computation dependency problem In the second and third transferring mode, because of selecting a part information as the “Key Set” and being transferred firstly, but different applications, it is NOT known which part of information is necessary. So a certain “Key Set” may NOT transferred to the target node timely, the running agent must wait for it. That is to say, running agent is still dependent on part of information on the source node. This case is named “residual computation dependency.” This problem may lengthen the transferring delay of agent, when serious, it will influence the seamlessness. So the cases must be avoided. In our opinion, the “residual dependency” problem will be solved from two aspects:

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

1.

2.

Tuning reasonably the transferring granularity of Execution/code Agent (EA), Data Agent (DA) and other agents (such as environment-state agent). If too larger, it is restricted by the bandwidth. If too smaller, transferring time is much more. Both may lengthen the delay. Based on analyzing from theory and application tests, we suggests a partition method named “subsection” or “pagination,” which determines the size or number of “section” or “page” by bandwidth, buffer, volume of MessageBox. When the cases are occurred, the necessary information may be transmitted through “section interruption” or “page interruption,” but the frequency should be adjusted automatically according to historical record information. Optimize the Key Set. The Key Set will be determined automatically according to nearest principle and used frequently principle and cut off the redundancy information. The relative adapted strategy may be referred the bibliography (Milojicic, 2002; Takasugi, 2001).

communication primary for migration In order to support Web-based seamless migration, we have designed several communication primaries for transferring agent, a part of them are as follows: 1.

BeginToListen Primary: VA will invoke the BeginToListen Primary to listen the port nPort, meanwhile, register the callback function OnAccept to receive connection message from other agents, when VA have received the connection request, the OnAccept will call back the connection_ID Connection_ ID. The Primary is:

BeginToListen(UINT nPort,ACCEPT_ CALLBACK callback); Void (CAgent::* ACCEPT_CALLBACK) (UINT& Connection_ID). 2.

3.

BeginToRequest Primary: When VA wants to set up connection to target agent, it will invoke BeginToRequest Primary to send request to the agent with IP:nPort, if it is successful, the connection ID nConnection_ID will be called back. The Primary is: BeginToRequest(UINT &nConnection_ID, CString IP,UINT nPort). Tranfer Primary: When agent wants to send messages or transfer task to other objects, it will invoke Tranfer Primary to do it. The Primary is:

Transfer (UINT nConnection_ID, CString strMsg, CDate time_stamp). Similarly: PrepareForRecv Primary for receive message or data stream: PrepareForRecv(UINT nConnection_ID, RECEIVE_CALLBACK callback); Void (CAgent::* RECEIVE_CALLBACK) (CString &strMsg, UINT& ConnectionID). PrepareForClose Primary for close or end the connection: PrepareForClose(UINT nConnection_ID, CLOSE_CALLBACK callback); Void (CAgent::* CLOSE_CALLBACK) (UINT &Connection_ID).

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Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

the Implemented platform The function and service of software platform (Simon, 2002) supporting task-oriented mobile distance learning paradigm — Web-based seamless migration should include: 1.

2.

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Management method of resource and services: When a new mobile device is brought into a space or new module or component used in the old device, the software manager can know how to spontaneously discovery them and what is wanted to be interactive. Because the resources of device are not same in a system, they may be embedded device, wearable computing device, mobile computing device, etc. their computing capability, memory capability, interactive mode are different. When the device is mobile or nomadic in the different environment, the interconnection problem is existed. The infrastructure can transform or translate the contents. Support for message-oriented, streamoriented or bulk-oriented communication: Here we argue that actually there are three catalogs of communications needs in runtime environment of mobile distance learning with different QoS requirements. Message-oriented communication is a kind of communication that occasionally happens and usually has high-level semantics for distance learning, e.g. a command asking a module or component to play the specified information. These communications are sensitive to the loss of messages; whereas their requirements on the delivery latency are moderate, as long as it is within a reasonable boundary, say, 50 ms, according to the cognitive character of human. Stream-oriented communication is a kind of communication that constantly occurs. Their semantic level usually is relatively low and the drop of several data units is usually

3.

tolerable. However, they are sensitive to the variation of the delivery latency, while in most cases their requirement on the delivery latency is also moderate. Bulk-oriented communication is a kind of communication with much larger Bytes amount (maybe several K/Mbytes) to be delivered, which is not much sensitive to the variation of the delivery latency. The work paradigm may be Client/Server, Browse/Server and Peer-toPeer, so the protocol stack of communication is a certain kind of link of IP—TCP/UDP/ RTP—HTTP/FTP. Coordination mechanism of continuity and self-adaptability: As a distributed mode, the infrastructure can coordinate the relationship of association, communication, collaboration of modules, so coordination mechanism of continuity and self-adaptability among modules or component is more important to the whole function and services. Of course it is important that supporting one-to-many communication, heterogeneous platforms and implementation languages. It is common in runtime environment of mobile distance learning that a message should be delivered to many modules or components simultaneously. Even in the case of stream-oriented communication, there will be multiple learners of a single stream. Therefore, it is necessary for software platform to have the one-tomany communication capability. Modules or components in a runtime environment usually impose different requirements on the underlying hardware and OS. Moreover, they are often implemented in different languages. A software platform should have the adequate capability to deal with all these diversities.

Based on analyzing to the function and service of software platform, we have designed and developed it. Figure 1 is the structure description of our

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

Figure 1. Structure description of platform Application/Agent Smart Platform API/XML

Stream

Sys Service

Message

Bulk

Control link with Asynchronous message handle RTP/UDP IP Multicast

TCP

XML/TCP

Environment Discovery Module

IrDA

Bluetooth Proxy Agent

Ethernet/WLAN System API OS/Network

Figure 2. Structure of seamless migration embedded in the platform

Seamless Migration Platform OS ND

SM-session layer

T

SMconnection layer

T

SM-path layer

T

A

MA

A

T

MA

A

T

A

T

SM-connection

A C

SM-link layer

MA SM-path

SM-link

SM-link(IP,IP)

IP Address

Link layer

MAC Address Wired Lan

C

SM-path

TCP/IP layer

Physical layer

A

SM-session

Wireless Lan

WAN

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Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

implemented platform supporting task-oriented mobile distance learning paradigm—Web-based seamless migration. Figure 2 is the structure of seamless migration embedded in this implemented platform, which includes four layers: SM-link layer, SM-path layer, SM-connection layer and SM-session layer. In Figure 2, “T” stands for “Task,” ”A” stands for “Agent,” “MA” stands for “Mobile Agent” and “C” stands for “Container,” which is a daemon threads component installed in each relative mobile devices. Their working principle has been previously mentioned. Our implemented platform can work in Client/Server, Browse/Server and Peer-to-Peer paradigm. The platform is a multi-agent system. The structure can be divided into multiple levels. Multiple agents are collaborated for seamless mobility. Each one has its special function. The agent class and container class can be partially defined as follows: class CAgent { public: CAgent(); virtual ~CAgent(); BOOL Register(); BOOL Quit(); BOOL Subscribe(CString strGrpName, NOTIFY_CALLBACK callback, CString strTemplate=””); U I N T G et Sh a r e d Fi le ( LPCTST R url,LPCTSTR lpszTagInfo=NULL); virtual void OnConnect(); virtual void OnDisconnect(); ... }; class Ccontainer { public: CContainer(); virtual ~CContainer(); BOOL LaunchAgentByName(CString strAgtName); BOOL Launch AgentByPath(CString strPath);

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void ProcessDSCmd(CDSMsg & msg); …; typedef struct _MINIHTTP_REQUEST { SOCKET socket; char* http_data; unsigned long http_data_size; MINIHTTP_FIRST_LINE* first_line; } MINIHTTP_REQUEST; typedef struct _MINIHTTP_RESPONSE { range_begin; unsigned int unsigned int range_end; unsigned long http_data_size; int http_response_code; } MINIHTTP_RESPONSE; ... } There are four kinds of components in our platform: Management Interface Component, Task Manager Component, Continuity Manager Component, and Service Manager Component. The interface is often used as defining the attributes of agent, such as ID of Agent, Name of Agent, Type of Agent (such as TA, SA, UA, VA, EA, DA, and so on), Current Status of Agent (five status are “Ready,” “Waiting,” “Transferring,” “Running,” “Dead” or “Destroyed”), Association Relationship of agent (including relationship between agent and task, relationship between two agents). The task manager is for application service, which manages the application/task array, including task description, task analyzing, mapping, or binding between task and service, loading, executing, scheduling of task, etc. The continuity manager is for agent management, context-awareness computing, and history/status recording, such as making of “Transferring Travel Schedule” of agent, addressing of VA, determining of transferring granularity which is for avoiding the transferring failure, reducing the residual dependency and contracting the transferring delay, etc. The service manager conducts the registration of service, discovery of service, service association, and mapping or binding between task and service of mobile distance learning. Service discovery is the base of seamless mobility of task of

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

learning. Currently, several discovery ideas have been designed or used, such as Service Location Protocol, Jini, Salutation, Universal Plug and Play, Bluetooth Service Discovery Protocol, and others (Garlan & Siewiorek, 2002). These components can communication each other, and may be controlled by application interactive interface including agents and global control of task, which is interface of human computers, such as PC, laptop, PDA, Mobile phone, embedded devices. The stationary or mobile agent is the basic encapsulation of the software modules in the system for management of service and mobility. Each computer in the runtime environment of mobile distance learning will host a dedicated process called Container, which provides system-level services for the agents that run on the computer and manages them as well. It makes the details of other parts of the system transparent to agent and provides a simple communication interface for stationary or mobile agent. There is one global dedicated process in the environment, which mediates the “delegated communication”

between stationary or mobile agent and provides services such as directory service, dependency resolution.

test of mobIle dIstance learnIng based on our platform Our implemented platform can show many scenarios, such as Web-based seamless migration with “Event-Type” task, “Bulk-Type” task, “Stream-Type” task for task-oriented mobile distance learning. Here is an example that includes Web-based seamless migration for task of learning on PC, laptop, or PDA under dynamic changes of the network and environment without user awareness or intervention. Just like Figure 3, the task of learning can follow me form one device to another device or from my house to other places, such as my office, stadium, coffee house, park, airport, etc., and vice versa.

Figure 3. Task can be migrated with me from one place to another place

Office

Coffee house

House

Stadium

Park

Airport

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Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

Now supposing the task of learning consists of three sub-tasks of mobile distance learning: playing video, playing mp3, and reading documents. As a demo of many scenarios, this kind of task of learning is described partially by SIML as follows:











The previous task of learning has three subtasks of learning: Playing Pervasiv.avi, playing IloveChina.mp3, reading Pervasive.txt. They will be done according to the time-sequence in parallel mode based on the algorithm mentioned previously. With the learner’s movement from one station (such as House) to another station (such as Airport), these uncompleted sub-tasks of distance learning can seamlessly migrate from PC of his or her house to laptop, or PDA with him or her in Airport and go on learning (watching, listening, and reading) continuously by mobile agent

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on our platform supporting Web-based seamless migration. In our experiments of mobile distance learning, the deployment of device is the CPU frequency, RAM of PC and laptop (a kind of mobile device) are 1.2 GHz, 512 MBytes,respectively, and 450 MHz, 64 MBytes RAM are for PDA (another kind of mobile device), the speed of wired network and wireless network is 10 M/100 MHZ, 1-3 MHZ, respectively. The nodes were connected by wireless and wired Web network—Internet.

conclusIon In order to meet the application requirements of mobile distance learning, we have proposed a kind of novel distance learning paradigm — taskoriented Web-based seamless migration, which supplies the function that the task of distance learning dynamically follows the learner from place to place and machine to machine, so it is convenient to learn during mobility, and is useful or helpful for the mobile learner or mobile attendee. Our key idea is that this capability can be achieved by layering architecture of component platform and agent-based migrating mechanism. In this chapter, we have given the formal description of the task of mobile distance learning, discussed the migrating granularity of the task of learning. The innovative significance is that we have designed a kind of approach of Web-based seamless migration, including solving these problems, such as shortening migration delay, avoiding migration failure and residual computation dependency. The validity of this approach and its corresponding software platform for mobile distance learning has been tested by many demos.

references Ciancarini, P. (2002). Coordinating multi-agent applications on the WWW: A reference archi-

Web-Based Seamless Migration for Task-Oriented Mobile Distance Learning

tecture. IEEE Trans. on Software Engineering, 24(5), 363-375. Danny, B. L., & Mitsuru, O. (2001). Seven good reasons for mobile agents. Communications of the ACM, 42(3), 86-89. David, K., & Robert, S. G. (2002). Mobile agents and the future of the Internet. ACM Operating Systems Review, 33(3), 7-13. Garlan, D., & Siewiorek, D. P. (2002). Project aura: Toward distraction-free pervasive computing. IEEE Pervasive Computing, 1(2), 22-31. Karnik, N. M. (1991). Design Issues in mobile agent programming systems. IEEE Concurrency, 6(3), 125-132. Milojicic, D. (2002). Mobile agent applications. IEEE Concurrency, 7(3), 80-90. Satyanarayanan, M. (2001). Pervasive computing: Vision and challenges. IEEE Personal Communications, 8(8), 10-17.

Shi, Y. C., & Xie, W. K. (2003). The smart classroom: Merging technologies for seamless teleeducation. IEEE Pervasive Computing Magazine, 2(2), 25-33. Simmons, R., & Apfelbaum, D. (2001). A task description language for robot control. In Proceedings Conference on Intelligent Robotics and Systems, New York (Vol. 1, No. 10, pp. 138-147). Simon, S. (2002). A model for software configuration in ubiquitous computing environments. In Proceedings of Pervasive. LNCS 2414, Zürich (Vol. 1, No. 7, pp. 181-194). Takasugi, K. (2001). Adaptive system for service continuity in a mobile environment. In Proceedings of IEEE APCC, Tokyo, Japan (Vol. 1, No. 9, pp. 75-83). Takasugi, K. (2003). Seamless service platform for following a user’s movement in a dynamic network environment. In Proceedings of PerCom’03 (Vol. 1, No. 8, pp. 125-132). Weiser, M. (1991). The computer for the twentyfirst century. Scientific American, 265(3), 94104.

This work was previously published in the International Journal of Distance Education Technololgies, Volume 4, Issue 3, edited by S. Chang and T.K. Shih, pp. 62-76, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 3.34

Evaluating the Learning Effectiveness of Using Web-Based Instruction:

An Individual Differences Approach Sherry Y. Chen Brunel University, UK

abstract The use of Web-based instruction is becoming widespread in higher education; however, much remains to be learned about how different learners react to such instructional programs. The study presented in this chapter evaluates students’ learning performance and their perceptions in a Web-based instructional program, which was applied to teach students how to use HTML in Brunel University’s Department of Information Systems and Computing. Sixty-one master’s students participated in this study. A number of interesting interactions were found. Students’ task achievements were affected by the levels of their previous system experience. On the other hand, the post-test and gain scores were positively

influenced by their perceptions and attitudes toward the Web-based instructional program. The implications of these findings are discussed.

IntroductIon Due to the popularity of the World Wide Web (Web), there has been a considerable growth in the use of Web-based instruction. Bonk et al. (2001) stated that no technology has so rapidly become prominent in educational settings as the Web-based instruction. From educational insights, Web-based instruction seems to provide answers to problems confronted by traditional teaching in higher education, such as large class (Freeman, 1997), and students from disperse locations (Dede,

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Evaluating the Learning Effectiveness of Using Web-Based Instruction

1996). However, the drawback is that Web-based instruction employs hypermedia techniques to present information in a non-linear format. On the one hand, non-linear interaction provides learners some control over the instruction. On the other hand, the responsibility for designing learning paths becomes that of the students. Learners have to decide in what order the topics will be accessed (Sweany et al., 1996). If learners lack such a skill, their performance may be hindered; in turn, they may have more negative attitudes toward using Web-based instruction programs (Dringus, 2000). It suggests that the use of the Web-based instruction may not improve learning effectiveness (Cummings, Bonk & Jacobs, 2002), and individual differences are critical factors for the successful use of Web-based instruction programs (Chen, 2002). However, there is little empirical evidence of the learning effectiveness of Web-based instruction (Bork, 2001). Therefore, many more empirical studies are needed, because such evaluation can provide concrete prescriptions for improving the design of Web-based instruction. In this vein, the study reported in this chapter aims to investigate how individual differences influence students’ learning effectiveness within a Web-based instruction program. The chapter begins by building a theoretical framework to present the relationships between Web-based instructional programs and individual differences. It then progresses to describe an empirical study of students’ learning experiences in a Web-based instructional program. Subsequently, the design implications are discussed based on the findings of this empirical study.

theoretIcal framework web-based Instruction Web-based instruction provides a revolutionary educational environment (Brooks, 1997), and it is

increasingly being used to deliver course content in higher education (Nachmias & Segev, 2003). Perhaps the most obvious advantages perceived by the students are dynamic interaction and flexible schedule. In terms of dynamic interaction, the Web-based instruction presents an enormous amount of information through various interconnections that offer students a rich exploration environment. The development of Web-based instruction provides learners with many opportunities to explore, discover, and learn in theory according to their own individual needs. Students can create individualized learning paths to reach the desired goals, move at their own speed and retrieve additional information as needed (Hui & Cheung, 1999). There is a shift away from didactic instruction to discovery of information (Smaldino, 1999). This approach is in line with the constructivist philosophy of learning where the learner is encouraged to interact with the environment to construct individual knowledge structure (MacDonald et al., 2001). With regard to flexible schedule, Web-based instruction allows learners to read course content through a computer network at any time and at different places (Chang et al., 1998). Burton and Goldsmith (2002) found that such flexible schedule makes Web-based instruction appealing to the students, including the convenience of not having to be on campus during the week, ease of arranging personal commitments, and ability to take courses around work schedules. This type of learning may be particularly beneficial to individuals who live in remote places (Daugherty, 1998). The individuals living in remote areas can have access to the same course content as those living in big cities. This is the reason why many educators have tried to develop a distance-learning program on the Web. As pointed by Clark and Lyon (1999), the Web-based instruction has been predicted to be the future of all types of distance learning programs. However, these advantages may come with a price. Power and Roth (1999) reported that the

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Evaluating the Learning Effectiveness of Using Web-Based Instruction

Web-based instruction is more dynamic and flexible than other learning material, but it creates new challenges related to the effect on learners’ comprehension. Ng and Gunstrone (2002) indicated that although students had positive perceptions to self-based learning provided by Web-based instruction, the unstructured nature of the Web made some of the students need more time to search information. Quintana (1996) stated that while students gained the advantage of flexibility in time, pace, and distance with Web-based instruction, many students, on the other hand, felt isolated, experienced lack of motivation, or lack of support and feedback, and consequently to dropped out of the course. Hedberg, Harper, and Corrent-Agostinho (1998) indicated that some students are still working to come to grips with a new and difficult way of learning. They exemplify the concern by asking for more incentive, more time, more structure, and more guidance. These studies provide evidence that not all types of students appreciate being given freedom in their learning processes. In particular, students who need more guidance through the learning process may meet an increased number of problems in using the Web-based instructional programs. To address this limitation, the Web-based instruction should be developed to support the unique needs of each individual learner (Carter, 2002). Only when their needs are identified can developers of programs effectively enhance functionality and increase learners’ satisfaction (Ke, Kwakkelaarb, Taic, & Chen, 2002). Therefore, understanding of learners’ individual differences arguably becomes an important consideration in the development of Web-based instruction programs.

Individual differences Individual differences play an important role in learning. Individuals differ in traits such as skills, aptitudes and preferences for processing information, constructing meaning from information and applying it to real-world situations (Jonassen &

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Grabowski, 1993). The effects of users’ individual differences on task performance in a computerbased learning environment have been one of the growing research areas (Wang & Jonassen, 1993). According to Egan, there are at least two reasons why system designers should pay attention to the differences among the users: First, individual differences usually play a major role in determining whether humans can use a computer to perform a task effectively. Second, our understanding and technology have reached the point where it is possible to accommodate more user differences. (Egan, 1988, p. 544) Individual differences variables that have been found to be influential factors accounting for learning performance include gender differences (Ford & Chen, 2000; Ford & Miller, 1996), domain knowledge (Lawless & Kulikowich, 1998), and system experience (Chen & Ford, 1998; Reed & Oughton, 1997). In terms of gender differences, previous research indicates that gender differences influence users’ navigation strategies in Web-based instruction. Schwarz (2001) found that females and males request different kinds of support when locating particular information. Male users need a larger frame of reference while female users ask procedural directions. With respect to domain knowledge, research suggests that less knowledgeable users experienced more disorientation problems in Web-based instruction (Last et al., 2001). This may be due to the fact that they are unfamiliar with the subject matter of the text, so they cannot rely on prior knowledge to help them structure the text. On the other hand, more knowledgeable users may experience fewer navigation problems because their greater grasp of the conceptual structure of the subject matter can enable them to impose structure on the Web (McDonald & Stevenson, 1998). In regard to system experience, novices and experts demonstrate different attitudes toward the use of Web-based instruction. Liaw (2002)

Evaluating the Learning Effectiveness of Using Web-Based Instruction

found students’ experience using the Internet to be a good predictor of their computer and Web attitudes. Furthermore, Torkzadeh and Van Dyke (2002) found the transition from low experience to high experience could improve Internet selfefficacy. Results from these studies suggest that individual differences play an important role in the use of Web-based instruction programs. These studies also indicate that further empirical works are needed to identify the learners’ different preferences, and their results may help to guide the development and evaluation of Web-based instructional programs. This chapter presents such a study, which aims to examine how individual differences influence students’ learning effectiveness within a Web-based instructional program.

research desIgn web-based Instruction program The Web-based instructional program that was used to host the HTML tutorial began by introducing the learning objectives and explaining the available navigation approaches provided in the instructional program. The contents were divided into three sections: (1) What is HTML? (2) Working with HTML, and (3) Relations with SGML and WWW. Section 2 is the key element of the Web-based instructional program that covers 12 sub-topics of HTML authoring. Each sub-topic was further split into five parts comprising (a) overview, (b) detailed techniques, (c) examples, (d) related skills, and (e) references. Information was presented in texts, tables, index, and maps. The tutorial screen was divided using frames. In the top frame, there was a title bar showing the section name being viewed and the other available section buttons. In the left frame were the Main Menu, Index, Map, and Quit buttons. The right frame displayed the main content for each

section, including topic buttons and text-based hypertext links. In terms of navigation control, the Web-based instruction program took advantage of the features of non-linear learning and provided students with freedom of navigation. Topics and sub-topics could be studied in any order. In other words, students were allowed to decide their own navigational routes through the subject matter. Three types of navigation control were available in this tutorial as shown in Table 1.

pre-test and post-test Examining student learning outcome in theoretical knowledge was conducted by using a pre-test and a post-test methodology. The students were evaluated with the pre-test to examine their levels of prior HTML knowledge and with the post-test to assess learning achievement. Both tests were presented in paper-based formats and included 20 multiple-choice questions with only one right answer. The formats of the questions were similar, with only the specific subject of the question modified. The questions covered all three sections of the Web-based instruction program from basic concepts to advanced topics. Students were allotted 20 minutes to answer each test and were not allowed to examine the content presented in the program at the same time. Student learning outcome was assessed by: •

•

Post-test score: Each student’s score on the post-test, ranging from 0 to 20, in order to identify general learning performance Gain score: Score difference between the pre-test and post-test in order to measure improved learning performance by taking the HTML tutorial

task sheet Students were assigned to do a practical task that involved constructing a Web page using Notepad

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Evaluating the Learning Effectiveness of Using Web-Based Instruction

Table 1. Illustration of the three types of navigation control Control Sequence Control

Content Control

Display Control

Purposes To allow students to decide the sequence of subjects to be learn

To allow students to control the selection of the contents they wish to learn To allow students to choose one of several display options that cover the same concept

in order to measure skill-based learning outcomes. The practical task entailed 10 key areas (e.g., creating hypertext links, changing background colors, formatting text, etc.). A printed task sheet describing the detailed features of the Web page to be completed was given to the students, who were allowed to decide the order in which they attempted to complete the task activities on the sheet. They were also allowed to look at the content of the HTML tutorial simultaneously. One and a half hours were allocated to complete the task. The starting time and the end time for each student were recorded. Student task achievement was evaluated by: •

•

Task Score: a score consisting of summing items successfully completed, on a 0-10 scale; Task Time: the total time spent for completing the tasks.

exit Questionnaire The questionnaire was divided into two parts. The first sought information regarding bio-

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Tools 

Subject Maps: to show all topics and subtopics in a hierarchical way;



Keyword Index: to list keywords in an alphabetical way;



Back/Forward: to see the page previously visited;



Section Buttons: to choose three sections of the main content;



Main Menu: to present main topics;



Hypertext Links: to connect relevant concepts;



Display Options: to include overview, examples, detailed techniques, and so forth.

graphical data relating to the student and her/his experience of using computers, the Internet, and HTML. The second, which was the main focus, consisted of three open-ended questions and 47 closed statements to collect student responses to the Web-based instructional program. It took students approximately 20 minutes to respond to all of the questions. The open-ended questions were related to student opinions about the strengths and weaknesses of the HTML tutorial and the barriers that they met. Students were requested to express their opinions in their own words. Enough space was provided for them to write their opinions. The closed statements were designed to collect information about student comprehension, preferences, and satisfaction or dissatisfaction with the Web-based instructional program. It included five sections: (A) level of understanding; (B) content presentation; (C) interaction styles; (D) functionality and usability; and (E) difficulties and problems. Each closed statement could be classified as either in favor or not in favor of the program. The number of “favored” statements was almost

Evaluating the Learning Effectiveness of Using Web-Based Instruction

equal to the “not-favored” statements (20 favored statements and 27 not-favored statements), in an attempt to reduce bias in the questionnaire. All statements used a five-point Likert scale consisting of: “strongly agree,” “agree,” “neutral,” “disagree,” and “strongly disagree”. Students were required to indicate agreement or disagreement with each statement by placing a check mark at the response alternative that most closely reflected their opinion. Their perceptions and attitudes were measured by: •

•

Positive Perceptions: the total score for all favored statements of the exit questionnaire with the same Likert scale; Negative Attitudes: the total score for all not-favored statements of the exit questionnaire with the same Likert scale.

procedure All participants took part in the study in the same room at the same time and interacted with the Webbased instructional program using Microsoft’s Internet Explorer. The participants were asked to do the following activities: 1. 2. 3. 4. 5.

Complete the pre-test to ascertain levels of prior knowledge of HTML Interact with the Web-based instructional program (i.e., HTML Tutorial) Complete a practical task, which involved constructing a Web page using HTML Complete the post-test to identify their learning performance Complete a paper-based exit questionnaire to describe their personal details and to reflect on their opinions of the Web-based instructional program.

data analyses To investigate how individual differences influence student learning in the Web-based instructional program, the data obtained from pre- and post tests, practical tasks, and exit questionnaire were used to conduct statistical analyses to identify student learning experiences. Pearson’s r was applied to find the correlations between individual student differences (i.e., gender differences and prior knowledge) and their learning experience (i.e., learning performance and perceptions). The Pearson correlation test reveals the nature and extent of association between two variables and is appropriate for the analyses of binary data and interval data (Stephen & Hornby, 1997). A significance level of p < .05 was adopted for the study. In addition, the mean scores are employed to describe the learning outcome for each individual group.

fIndIngs overall results The participants (N=61) consisted of Master’s students at Brunel University’s Department of Information Systems and Computing. Despite the fact that the participants volunteered to take part in the experiment, the sample was evenly distributed in terms of gender and system experience. They were 32 males and 29 females. The computer experience and Internet experience reported by the participants ranged from average to excellent on a five-point scale. Their familiarity with the subject content, HTML authoring, ranged from none to good. There was similar proportion of computer and Internet experience and HTML authoring in both male and female groups. In terms of the perceptions and attitudes, a majority of the students (78%) felt that the Web-based instruction program was useful and they liked the Web treatment of the content.

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tasks vs. tests As indicated earlier, students needed to be assessed by both practical task and paper-based tests. It is important to note that both task and tests were markedly different; distinctions similar to those between open-book examination and closed-book examination were noted. The practical task was completed in open-book examination style, with students building Web pages guided by the task sheet. The practical task could be completed successfully without recourse to memory by applying knowledge read from the screen at the particular time it was needed. On the other hand, the post-test, which was a multiple choice factual test, entailed recalling knowledge from memory, and completed after learning using the Web-based instructional program, looked like a closed-book examination. These differences can also be associated with those between procedural knowledge and declarative knowledge. Derry (1990) distinguishes between these two. Procedural refers to knowledge of how to do things, while declarative refers to knowledge about the world and its properties (McGilly, 1994). Practical tasks refer to procedure knowledge of how to use HTML, while paper-based tests refer to declarative knowledge about the properties of HTML. Pearson’s correlations found that student task scores were affected by the levels of their previous Internet experience (r=.44) and HTML authoring (r=.35). On the other hand, the post-test and gain scores were positively influenced by student perceptions and attitudes toward the Web-based instructional program. In other words, the students who had more positive perceptions toward the Web-based instructional program (r=.40) could obtain better post-test and gain scores than those who had more negative attitudes (r=.46) toward the program. The findings of the study implied that performance on the practical task of applying procedural knowledge could be promoted by prior system

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experience in using the Internet and HTML authoring, but it would not be affected by the matching or mismatching of instruction with the student preferences. Conversely, the ability to recall declarative knowledge appears to have been mainly facilitated by matching instructional presentation with learners’ preferences, but it is not influenced by prior system experience of using the Internet and HTML authoring.

gender differences There were interesting correlations between student learning performance and gender differences. Female students performed better than male students in the post-test. Conversely, the male students outperformed the female students in the practical task (r=.39). The differences between the post-test and practical task can be related with those between declarative knowledge and procedural knowledge. It implies that female students are better at acquiring declarative knowledge rather than procedural knowledge. Conversely, male students are skilled at gaining procedural knowledge instead of declarative knowledge. For learning attitudes, male students were patient in completing the task. On the other hand, female students felt nervous doing the tasks, and some of them (N = 10) gave up doing the tasks within 15 minutes. In addition, female students needed more guidance than male students did. Female students tended to ask for instruction from the tutor instead of trying to correct errors by themselves. These findings are in line with some previous studies that found males showed more interest in using and learning about computers while females reported fear of using computers and feeling helpless around them (Koch, 1994; Shashaani, 1994). For this phenomenon, educators should help female students build their confidence in facing the challenge of using computers instead of giving too detailed instructions. In addition, educational settings should ensure that instructional programs developed should not place any

Evaluating the Learning Effectiveness of Using Web-Based Instruction

students at a disadvantage due to their gender differences (Owen & Liles, 1998).

prior knowledge Through analyzing student prior knowledge, one thing seems evident. For doing practical tasks, students who had greater experience using the Internet (r=.27) or HTML authoring (r=.28) seemed able to look for relevant information in an efficient way. Conversely, students who were lacking prior knowledge of the subject content needed more time to decide the learning paths for completing the task. It seemed that students’ existing knowledge did influence their interaction with the Web-based instructional program. These findings arguably supported results from previous studies (Gay, 1986; Shih & Gamon, 1999) that found a positive relationship between learner control and prior knowledge. Expert learners who had an adequate amount of prior knowledge of the subject felt familiar with the interface and the contents of the Webbased instructional program. They were confident about being more active when navigating the Web-based instructional system. On the other hand, novice learners might not be aware of the best order to read the material or recognize the most important information. Therefore, it is important to provide novice learners with an initial phase of orientation relating to both interface and domain contents (Linard & Zeillger, 1995). One of the ways is to provide visual paths that can be displayed by means of cues to indicate how far students are along a path or by giving some conceptual description for the possible sequences. The alternative way is to provide good labels for the pages. Labels that clearly indicate the role of a particular page may help novices successfully decide on the appropriate coherent path (Lewis & Polson, 1990).

learning by doing In this Web-based instruction program, students were asked to do a practical task (i.e., design a Web page with HTML). A significant number of students (44%) reported that doing the task was a useful way of helping them to set a focus in the Web-based instructional program. From these 44% of students, 52% of them could obtain the post-test scores above the average (= 10.4) and 63% of them demonstrated more positive perceptions of the Web-based instructional program. These results implied that “learning by doing” could assist some students to set their effective learning strategies. As indicated by Smith and Parks (1997), tasks serve to simulate “goal directed” browsing in such a way that learning performance can be enhanced. On the other hand, a few students (30%) reported that doing the task hindered their learning. They found that they lost other important information that they needed to learn because they were concentrating on doing the task. From these 30% of students, 58% of them obtained the post-test scores below the average and 54% of them showed more negative attitudes toward the Web-based instructional program. This raises some interesting questions for further studies to consider (a) whether task activities can facilitate promoting student learning performance in a Web-based instructional program; and (b) what the relationships are between student attitudes and their learning patterns as reflected in a Web-based instructional program with/without setting tasks.

conclusIon The aforementioned findings provide evidence that Web-based instructional programs may not be suitable for all learners as an instructional methodology. Instructors must be aware of individual differences such as gender and levels of

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prior knowledge possessed. Some learners, for example novice learners, may need greater support and guidance from the instructors, while others may be able to follow Web-based instructional programs relatively independently. Thus, instructors should not assume that every student would benefit equally from Web-based instructional programs in educational settings. There remains the need for guidance to ensure that all learners attain their learning potential. Implementing Web-based instructional programs is a complex process composed of interactions among students, instructional content, and the features of Web-based instructional programs. It is important for educational settings to have a good plan in advance. Instructors should remain cautious about making a sweeping decision to convert entire curricula into Web-based instructional programs. The goals of such a process should be weighed against the potential problems (e.g., alienating certain learners). To avoid alienating a certain group, instructors should continue to incorporate a number of different teaching strategies into their lectures. In addition, this transition requires time for the student and time in the classroom to acquaint the students with Web-based instructional programs. This is especially the case for students who have difficulties in independent learning; there is a need to let them have more time for this shift. With this issue in mind, such innovation in teaching and learning will be more meaningful and valuable. This study has shown the importance of understanding individual differences in the development of Web-based instructional programs, but it was only a small-scale study. Further studies need to be undertaken with a larger sample to provide additional evidence. The other limitation is that this study adopted a self-developed pre-test and posttest, so the reliability and validity of these tests are questionable. Therefore, testing and modification of the tests are needed in the future. There is a need to conduct future research that would examine the impact of other individual differences

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such as cognitive styles, cultural background, or domain knowledge. Such research should also be conducted within a more sophisticated multimedia Web-based instructional program, including the presentation of animation and video. It would be interesting to see how individual differences influence student learning in multimedia Webbased instructional programs. The findings of such studies could be integrated to build robust user models for the development of personalized Web-based instructional programs that can accommodate individual differences.

edItor’s note The author has generously offered an expanded discussion of the research design as well as the survey instruments and assessment tools explored in this chapter. For copies of this supplementary information, please contact the author via e-mail.

acknowledgment This study has been performed as part of the project “Human Factors in the Design of Adaptive Hypermedia Systems: A Cognitive Style Approach” funded by the UK Engineering and Physical Sciences Research Council (EPSRC Grant References: GR/R57737/01).

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& Society, 4(3). Retrieved October 10, 2002 from: http://ifets.ieee.org/periodical/vol_3_2001/bork. html Brooks, D.W. (1997). Web-teaching: A guide to designing interactive teaching for the World Wide Web. New York: Plenum.

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Burton, L., & Goldsmith, D. (2002). Students’ experience in online course: A study using asynchronous online focus groups. Connecticut Distance Learning Consortium, CT.

Derry, S.J. (1990). Learning strategies for acquiring useful knowledge. In B.F. Jones & L. Idol (Eds.), Dimensions of thinking and cognitive instruction (pp. 347-379). Hillsdale, NJ: Lawrence Erlbaum Associates.

Carter, E.W. (2002). Doing the best you can with what you have: Lessons learned from outcomes assessment. Journal of Academic Librarianship, 28, 36-41.

Dringus, L.P. (2000). Towards active online learning: A dramatic shift in perspective for learners. The Internet and Higher Education, 2(4), 189-195.

Chang, H.H., Henriquez, A., Honey, M., Light, D., Moeller, B., & Ross, N. (1998). The Union City story: Education reform and technology students’ performance on standardized tests. New York: Center for Children and Technology.

Egan, D. (1988). Individual differences in human-computer interaction. In M. Helander (Ed.), Handbook of human-computer interaction (pp. 543-568). North-Holland: Elsevier.

Chen, S.Y. (2002, December 10-13). The relationships between individual differences and the quality of learning outcomes in Web-based instruction. In Proceedings of the ICEB 2nd International Conference on Electronic Business (pp. 345-351). Taipei, Taiwan. Chen, S.Y., & Ford, N.J. (1998). Modeling user navigation behaviours in a hypermedia-based learning system: An individual differences approach. International Journal of Knowledge Organization, 25(3), 67-78. Clark, R., & Lyons, C. (1999). Using Web-based training wisely. Training, 36(7), 51-61. Cummings, J.A., Bonk, C.J., & Jacobs, F.R. (2002). Twenty-first century college syllabi options for online communication and interactivity. The Internet and Higher Education, 5(1),1-19. Daugherty, M., & Funke, B.L. (1998). University faculty and student perceptions of Web-based

Ford, N., & Chen, S.Y. (2000). Individual differences, hypermedia navigation and learning: An empirical study. Journal of Educational Multimedia and Hypermedia, 9(4), 281-312. Ford, N., & Miller, D. (1996). Gender differences in Internet perceptions and use. Aslib Proceedings, 48,183-92. Freeman, M. (1997). Flexibility in access, interaction and assessment: The case for Web-based teaching programs. Australian Journal of Educational Technology, 13(1), 23-39. Gay, G. (1986). Interaction of learner control and prior understanding in computer-assisted video instruction. Journal of Educational Psychology, 78(3), 225-227. Hedberg, J.G., & Corrent-Agostinho, S. (2000). Creating a postgraduate virtual community: Assessment drives learning. Educational Media International, 37(2), 83-90. Hui, S., & Cheung, K.P. (1999). Developing a Web-based learning environment for building

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Web as a research and teaching tool in science learning. Research in Science Education, 32(4), 489-510. Owen, M.B., & Liles, R. (1998). Factors contributing to the use of Internet by educators. Available: http://outreach.missouri.edu/netc98/manuscripts/ owen-liles.html Power, D.J., & Roth, R.M. (1999). Issues in designing and using Web-based teaching cases. In Proceedings of the 5th Americas Conference on Information System (AMCIS 1999) (pp. 936938). Quintana, Y. (1996). Evaluating the value and effectiveness of Internet-based learning. http:// www.crim.ca/inet96/pa pers/c1/c1_4.htm Rafi Nachmias, R., & Segev, L. (2003). Students’ use of content in Web-supported academic courses. The Internet and Higher Education, 6(2), 145-157. Reed, W.M., & Oughton, J.M. (1997). Computer experience and interval-based hypermedia navigation. Journal of Research on Computing in Education, 30, 38-52. Schwarz, J. (2001). Lost in virtual space: Gender differences are magnified. Retrieved October 15, 2002 from: http://www.washington.edu/newsroom/news/2001archive/06-01archive/k061301. html Shashaani, L. (1994). Gender differences in computer experience and its influence on computer attitudes. Journal of Educational Computing Research, 11(4), 347-367. Shih, C., & Gamon, J. (1999). Student learning styles, motivation, learning strategies, and achievement in Web-based courses. Available: http://iccel.wfu.edu/publications/journals/jcel/ jcel990305/ccshih.htm Smaldino, S. (1999). Instructional design for distance education. Techtrends, 43(5), 9-13.

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Smith and Parks. (1997). Virtual hierarchies and virtual networks: Some lessons from hypermedia usability research applied to the World Wide Web. Retrieved December 4, 1998 from: http://ijhcs. open.ac.uk/smith/smith-nf.html Stephen, P., & Hornby, S. (1997). Simple statistics for library and information professionals. London: Library Association. Sweany, N.D., McManus, T.F., Williams, D.C., & Tothero, K.D. (1996). The use of cognitive and metacognitive strategies in a hypermedia envi-

ronment. Poster presented at World Educational Media Conference, Boston, MA. Torkzadeh, G., & Van Dyke, T.P. (2002). Effects of training on Internet self-efficacy and computer user attitudes. Computers in Human Behavior, 18, 479-494. Wang, S.R., & Jonassen, D.H. (1993). Investigating the effects of individual differences on performance in cognitive flexibility hypertexts. Annual Meeting of the American Educational Research Association, Atlanta, GA.

This work was previously published in the International Journal of Information and Communication Technology Education, Volume 1, Number 1, pp. 69-82, copyright 2005 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 3.35

Multimedia Technologies in Education Armando Cirrincione SDA Bocconi School of Management, Italy

what are multImedIa technologIes Multimedia technologies (MMT) are all that kind of technological tools that make us able to transmit information in a very large meaning, transforming information into knowledge through stimulating the cognitive schemes of learners and leveraging the learning power of human senses. This transformation can acquire several different forms: from digitalized images to virtual reconstructions, from simple text to iper-texts that allow customized, fast, and cheap research within texts; from communications framework like the Web to tools that enhance all our sense, allowing complete educational experiences (Piacente, 2002b). MMT are composed by two great conceptually different frameworks (Piacente, 2002a): •

Technological supports, as hardware and software: All kinds of technological tools such as mother boards, displays, videos,

•

audio tools, databases, communications software and hardware, and so on Contents: Information and to knowledge transmitted with MMT tools. Information are simply data (such as visiting timetable of museum, cost of tickets, the name of the author of a picture), while knowledge comes from information elaborated in order to get a goal. For instance, a complex ipertext about a work of art, where much information is connected in a logical discourse, is knowledge. For the same reason, a virtual reconstruction comes from knowledge about the rebuilt facts.

It’s relevant to underline that to some extent technological supports represent a condition and a limit for contents (Wallace, 1995). In other words, content could be expressed just through technological supports, and this means that content has to be made in order to fit for specific technological support and that the limits of a specific technological support are also the limits of its content. For

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Multimedia Technologies in Education

instance the specific architecture of a database represents a limit within which contents have to be recorded and have to be traced. This is also evident thinking about content as a communicative action: communication is strictly conditioned by the tool we are using. Essentially, we can distinguish between two areas of application of MMT (Spencer, 2002) in education: 1.

2.

Inside the educational institution (schools, museums, libraries), with regard to all tools that foster the value of lessons or visiting during time they takes place. Here we mean “enhancing” as enhancing moments of learning for students or visitors: hypertexts, simulation, virtual cases, virtual reconstructions, active touch-screen, video, and audio tools; In respect of outside the educational institution, this is the case of communication technologies such as Web, software for managing communities, chats, forums, newsgroups, for long-distance sharing materials, and so on. The power of these tools lies on the possibilities to interact and to cooperate in order to effectively create knowledge, since knowledge is a social construct (Nonaka & Konno, 1998; von Foester, 1984; von Glaserfeld, 1984).

Behind these different applications of MMT lies a common database, the heart of the multimedia system (Pearce, 1995). The contents of both applications are contained into the database, and so the way applications can use information recorded into database is strictly conditioned by the architecture of database itself.

dIfferent dImensIons of mmt In teachIng and learnIng We can distinguish two broader framework for understanding contributions of MMT to teaching and learning. The first pattern concerns the place of teaching; while in the past, learning generally required the simultaneous presence of teacher and students for interaction, now it is possible to teach long distance, thanks to MMT. The second pattern refers to the way people learn; they can be passive or they can interact. The interaction fosters learning process and makes it possible to generate more knowledge in less time.

teaching on site and distance teaching Talking about MMT applications in education requires to separate learning on-site and distance learning, although both are called e-learning (electronic learning). E-learning is a way of fostering learning activity using electronic tools based on multimedia technologies (Scardamaglia & Bereiter, 1993). The first pattern generally uses MMT tools as a support to traditional classroom lessons; the use of videos, images, sounds, and so on can dramatically foster the retention of contents in student’s minds (Bereiter, Scardamaglia, Cassels, & Hewitt, 1997). The second pattern, distance teaching, requires MMT applications for a completely different environment, where students are more involved in managing their commitment. In other words, students in e-learning have to use MMT applications more independently than they are required to do during a lesson on site. Although this difference is not so clear among MMT applications in education, and it is possible to get e-learning

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tools built as they had to be used during on-site lessons and vice-versa, it is quite important to underline the main feature of e-learning not just as a distant learning but as a more independent and responsible learning (Collins, Brown, & Newman, 1995). There are two types of distance e-learning: self-paced and leader-led. The first one is referred to the process students access computer-based (CBT) or Web-based (WBT) training materials at their own pace. Learners select what they wish to learn and decide when they will learn it. The second one, leader-led e-learning, involves an instructor and learners can access real-time materials (synchronous) via videoconferencing or audio or text messaging, or they can access delayed materials (asynchronous). Both the cited types of distance learning use performance support tools (PST) that help students in performing a task or in self-evaluating.

passive and Interactive learning The topic of MMT applications in an educational environment suggests distinguishing two general groups of applications referring to required students behaviour: passive or interactive. Passive tools are ones teachers use just to enhance the explanation power of their teaching: videos, sounds, pictures, graphics, and so on. In this case, students do not interact with MMT tools; that means MMT application current contents don’t change according to the behaviour of students. Interactive MMT tools change current contents according to the behaviour of students; students can chose to change contents according with their own interests and levels. Interactive MMT tools use the same pattern as the passive ones, such as videos, sounds, and texts, but they also allow the attainment of special information a single student requires, or they give answers just on demand. For instance, self-evaluation tools are

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interactive applications. Through interacting, students can foster the value of time they spent in learning, because they can use it more efficiently and effectively. Interaction is one of the most powerful instruments for learning, since it makes possible active cooperation in order to build knowledge. Knowledge is always a social construct, a sensemaking activity (Weick, 1995) that consists in giving meaning to experience. Common sensemaking fosters knowledge building thanks to the richness of experiences and meanings people can exchange. Everyone can express his own meaning for an experience, and interacting this meaning can be elaborated and it can be changed until it becomes common knowledge. MMT help this process since they make possible interaction in less time and over long distance.

the learnIng process behInd e-learnIng Using MMT applications in education allows to foster learning process since there are several evidences that people learn more rapidly and deeply from words, images, animations, and sounds, than from words alone (Mayer, 1989; Mayer and Gallini, 1990). For instance, in the museum sector there is some evidence of the effectiveness of MMT devices too: Economou (1998) found firstly that people spend more time and learn more within a museum environment where there are MMT devices. The second reason why MMT fosters learning derives from interaction they make possible. MMT allow building a common context of meaning, to socialize individual knowledge, to create a network of exchanges among teacher and learners. This kind of network is more effective when we consider situated knowledge, a kind of knowledge adults require that is quite related to problem-solving.

Multimedia Technologies in Education

Children and adults have different pattern of learning, since adults are more autonomous in the learning activity and they also need to refer new knowledge to the old one they possess. Elearning technologies have developed a powerful method in order to respond more effectively and efficiently to the needs of children and adults: the “learning objects” (LO). Learning objects are single, discrete modules of educational contents with a certain goal and target. Every learning object is characterized by content and a teaching method that foster a certain learning tool: intellect, senses (sight, heard, and so on), fantasy, analogy, metaphor, and so on. In this way, every learner (or every teacher, for children) can choose its own module of knowledge and the learning methods that fit better with his own level and characteristics. As far as the reason why people learn more with MMT tools, it is useful to consider two different theories about learning: the information delivery theory and the cognitive theory. The first one stresses teaching as just a delivery of information and it looks at students as just recipients of information. The second one, the cognitive theory, considers learning as a sense-making activity and teaching as an attempt to foster appropriate cognitive processing in the learner. According to this theory, instructors have to enable and encourage students to actively process information: an important part of active processing is to construct pictorial and verbal representations of the lesson’s topics and to mentally connect them. Furthermore, archetypical cognitive processes are based on senses, that means: humans learn immediately with all five senses, elaborating stimuli that come from environment. MTT applications can be seen as virtual reproductions of environment stimuli, and this is another reason why MMT can dramatically fostering learning through leveraging senses.

contrIbutIons and effectIveness of mmt In educatIon MMT allow transferring information with no time and space constraints (Fahy, 1995). Space constraints refer to those obstacles that arise from costs of transferring from one place to another. For instance, looking at a specific exhibition of a museum, or a school lesson, required to travel to the town where it happens; participating to a specific meeting or lesson that takes place in a museum or a school required to be there; preparing an exhibition required to meet work group daily. MMT allows the transmission of information everywhere very quickly and cheaply, and this can limit the space-constraint; people can visit an exhibition stay at home, just browsing with a computer connected on internet. Scholars can participate to meeting and seminars just connecting to the specific web site of the museum. People who are organizing exhibitions can stay in touch with the Internet, sending to each other their daily work at zero cost. Time constraint has several dimensions: it refers to the need to catch something just when it takes place. For instance, a lesson requires to be attended when it takes place, or a temporary exhibition requires to be visited during the days it’s open and just for the period it will stay in. For the same reason, participating in a seminar needs to be there when it takes place. But time constraint refers also to the limits people suffer in acquiring knowledge: people can pay attention during a visit just for a limited period of time, and this is a constraint for their capability of learning about what they’re looking for during the visiting. Another dimension of time constraint refers to the problem of rebuilding something that happened in the past; in the museum sector, it is the case of extemporary art (body art, environmental installations, and so on) or the case of an archaeological site, and so on.

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MMT help to solve these kinds of problems (Crean, 2002; Dufresne-Tassé, 1995; Sayre, 2002) by making it possible: •

•

•

•

•

To attend school lessons on the Web, using videostreamer or cd-rom, allowing repetition of the lesson or just one difficult passage of the lesson (solving the problem of decreasing attention over time) To socialize the process of sense making, and so to socialized knowledge, creating networks of learners To prepare the visit through a virtual visit to the Web site: this option allows knowing ex-ante what we are going to visit, and doing so, allows selection of a route more quickly and simply than a printed catalogue. In fact, thanks to iper-text technologies, people can obtain lot of information about a picture just when they want and just as they like. So MMT make it possible to organize information and knowledge about heritage into databases in order to customize the way of approaching cultural products. Recently the Minneapolis Institute of Art has started a new project on Web, projected by its Multimedia department, that allow consumers to get all kind of information to plan a deep organized visit To cheaply create different routes for different kind of visitors (adults, children, researcher, academics, and so on); embodying these routes into high tech tools (PCpalm, LapTop) is cheaper than offering expensive and not so effective guided tours To re-create and record on digital supports something that happened in the past and cannot be renewed. For instance the virtual re-creation of an archaeological site, or the recording of an extemporary performance (so diffuse in contemporary art)

For all the above reasons, MMT enormously reduces time and space constraints, therefore

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stretching and changing the way of teaching and learning.

references Bereiter C., Scardamalia M., Cassels C., & Hewitt J. (1997). Postmodernism, knowledge building and elementary sciences, The Elementary School Journal, 97(4), 329-341. Collins, A., Brown, J.S., & Newman S. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing and mathematics. In Resnick, L.B. (Ed.), Cognition and instructions: Issues and agendas, Lawrence Erlbaum Associates. Crean B. (2002). Audio-visual hardware. In B. Lord & G.D. Lord (Eds.), The manual of museum exhibitions, Altamira Press. Dufresne-Tassé, C. (1995). Andragogy (adult education) in the museum: A critical analysis and new formulation. In E. Hooper-Greenhill (Ed.), Museum, media, message, London: Routledge. Economou, M. (1998). The evaluation of museum multimedia applications: Lessons from research. Museum Management and Curatorship, 17(2), 173-187. Fahy, A. (1995). Information, the hidden resources, museum and the Internet. Cambridge: Museum Documentation Association. Mayer, R.E. (1989). Systematic thinking fostered by illustrations in scientific text. Journal of Educational Psychology, 81(2), 240-246. Mayer, R.E. & Gallini, J.K. (1990). When is an illustration worth ten thousand words? Journal of Educational Psychology, 82(4), 715-726. Nonaka, I. & Konno, N. (1998). The concept of Ba: Building a foundation for knowledge creation. California Management Review, 40(3), 40-54.

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Pearce, S. (1995). Collecting as medium and message. In E. Hooper-Greenhill (Ed.), Museum, media, message. London: Routledge.

Cognitive Theory: Learning as a sense-making activity and teaching as an attempt to foster appropriate cognitive processing in the learner.

Piacente, M. (2002a) Multimedia: Enhancing the experience. In B. Lord & G.D. Lord (Eds.), The manual of museum exhibitions. Altamira Press.

E-Learning: A way of fostering learning activity using electronic tools based on multimedia tecnologies.

Piacente, M. (2002b). The language of multimedia. In B. Lord & G.D. Lord (Eds.), The manual of museum exhibitions. Altamira Press.

Information Delivery Theory: Teaching is just a delivery of information and students are just recipients of information.

Sayre, S. (2002). Multimedia investment strategies at the Minneapolis Institute of Art. In B. Lord & G.D. Lord (Eds.), The manual of museum exhibitions. Altamira Press.

Leader-Led E-Learning: Electronic learning that involves an instructor and where students can access real-time materials (synchronous) via videoconferencing or audio or text messaging, or they can access delayed materials (asynchronous).

Spencer, H.A.D. (2002). Advanced media in museum exhibitions. In B. Lord & G.D. Lord (Eds.), The manual of museum exhibitions. Altamira Press. Von Foester, H. (1984). Building a reality. In P. Watzlawick (Ed.), Invented reality. New York: WWNorton & C. Von Glaserfeld, E. (1984). Radical constructivism: An introduction. In P. Watzlawick (Ed.) Invented Reality. New York: WWNorton & C. Wallace, M. (1995). Changing media, changing message. In E. Hooper-Greenhill (Ed.), Museum, media, message. London: Routledge. Watzlawick, P. (Ed.) (1984). Invented reality. New York: WWNorton & C. Weick, K. (1995). Sensemaking in organizations. Thousand Oaks, CA: Sage Publications.

key terms CBT: Computer based training; training material is delivered using hard support (CDRom, films, and so on) or on site.

LO: Learning objects; single, discrete modules of educational contents with a certain goal and target, characterized by content and a teaching method that foster a certain learning tool: intellect, senses (sight, heard, and so on), fantasy, analogy, metaphor, and so on. MMT: Multimedia technologies; all technological tools that make us able to transmit information in a very large meaning, leveraging the learning power of human senses and transforming information into knowledge stimulating the cognitive schemes of learners. PST: Performance support tools; software that helps students in performing a task or in self-evaluating. Self Paced E-Learning: Students access computer based (CBT) or Web-based (WBT) training materials at their own pace and so select what they wish to learn and decide when they will learn it. Space Constraints: All kind of obstacles that arise costs of transferring from a place to another.

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Multimedia Technologies in Education

Time Constraints: It refers to the need to catch something just when it takes place because time flows.

WBT: Web-based training; training material is delivered using the World Wide Web.

This work was previously published in the Encyclopedia of Multimedia Technology and Networking, edited by M. Pagani, pp. 737-741, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.36

Advancing the Effective Use of Technology in Higher Education Sally M. Johnstone Western Cooperative for Educational Telecommunications, USA

In 1989 the Western Interstate Commission for Higher Education (WICHE) located in Boulder, Colorado, founded the Western Cooperative for Educational Telecommunications (WCET) as a resource for the 15 western states. At the first annual meeting, delegates from outside the WICHE states petitioned to join. The original membership agreed. By 2004, WCET had over 250 members representing 43 states and seven countries. WCET had become an international, member-driven service agency. WCET’s initial mission was to assist the western states and their higher education institutions integrate telecommunications technology into their academic services. Early projects included brokering electronic degree and certificate programs between states, and sorting out the western states’ regulatory policies to make inter-state distance learning programs more reasonable to operate. The first degree program WCET brokered was the University of Arizona’s Master’s in Library Science. It had students in states where there were no graduate library programs. Students had video and telephone links with the Arizona

faculty, and were required to spend a few weeks on the campus in the summer. The US Department of Commerce assisted in funding the brokering program that was run by Russell Poulin. By 1995, in addition to library science, WCET had brokered six degree and certificate programs in the areas of health, information technology, environmental engineering, and space studies. In the early 1990s WCET worked to make the state regulatory structure easier to navigate for colleges and universities that were willing to offer distance learning outside their own states. In the process, WCET staff discovered the dominant role that regional accrediting played in state regulations. We began working with the regional accreditors, and the Principles of Good Practice that most of the states adopted were also used by the accrediting community to assess distance learning programs. Emphasis on Good Practice led WCET to a strong focus on students and the services and information they need to have to be successful. With the help of funding from the US Department of Education’s Fund for the Improvement of Post

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Advancing the Effective Use of Technology in Higher Education

Secondary Education (FIPSE), WCET’s Barbra Krauth surveyed colleges and universities to find good examples of online services. This resulted in a Web tour of the different approaches institutions had for serving distance learning students. Taking this further, Patricia Shea managed a project funded by the US Department of Education’s Learning Anytime, Anyplace Program (LAAP) to assist different types of institutions as they completely re-worked their services to students to take full advantage of the Web. Teams from a research university, a community college, and a private university worked together and on their own campuses with consultants through the transformation process. Regular Webcasts were offered to the higher education community which focused on specific services, and the advances and issues that were emerging for each. The models that the WCET team put together are currently being used to help universities, colleges, and statewide systems improve their Web-based services to students. After working with the regulatory side of quality in distance learning, WCET staff realized that students also needed to be better informed as they chose a distance learning provider. WCET produced a Consumer’s Guide for potential distance learning students that was distributed through state higher education executive offices; however, not many students contacted those offices when they were seeking a provider. WCET staff decided to work with a commercial publisher, Prentice-Hall, to get information directly to the consumers. The first edition of the Distance Learner’s Guide was published in 1999. Sales were sufficient to have Prentice-Hall request an updated version for a second edition released in 2005. The book was produced by having experts from the WCET membership write the various chapters and using a central editor. The second edition helps a learner assess his or her readiness for distance learning, know the questions to ask of a potential provider, and figure out his or her

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equipment needs, and it offers a lot of information useful for the successful distance learner. In 1996, the Western Governors Association (WGA) wanted to explore the use of technology for higher education in the 18 states represented by the member governors. WGA staff turned to WCET for assistance. The lead governors were Mike Leavitt from Utah and Roy Romer from Colorado. They wanted to create a new type of learning opportunity for people in the western states that would focus on state workforce needs, grant certifications based on outcomes, and use new technologies. Governors Leavitt and Romer worked with WCET staff, WGA staff, and staff from the National Center for Higher Education Management Systems (NCHEMS) to create the Western Governors University (WGU). By 1999 WGU had its own staff and was on the road to becoming a degree-granting, independent institution. During the formation of WGU, the regional accrediting associations began working more closely together. They formed the Council of Regional Accrediting Commissions (C-RAC) to address common issues. One issue C-RAC took on was the creation of common principles upon which they could base their standards for distance learning programs. C-RAC turned to WCET to work with them to create those principles. Based on the earlier set of principles developed for the states, WCET staff revised and updated the Principles of Good Practice for C-RAC. WCET staff also worked with the staffs of the regional accrediting associations to interpret the principles. By 2001 the commissions of all the regional accrediting associations had adopted the same set of principles. During its first decade, WCET evolved into a real service organization, taking on projects no single institution or even a single state could tackle on its own. WCET members identified issues, and WCET staff created projects for funding. One of these was the Technology Costing Methodol-

Advancing the Effective Use of Technology in Higher Education

ogy (TCM) that was funded by FIPSE and the Andrew Mellon Foundation. WCET partnered again with NCHEMS, whose president, Dennis Jones, designed the framework for the costing model. TCM was tested in dozens of settings and modified accordingly. The value of TCM is for planners. It created a consistent set of metrics that can be applied across departments within an institution, or across institutions in a state to allow the real costs of a particular academic model to be known. The TCM framework, case studies, and interactive tabulator are all online for anyone to use without any charges. An online “how to use TCM” course was also produced. As the century turned, WCET began developing more resources for its members and the higher education community. With funding from the William and Flora Hewlett Foundation, WCET staff began work with Bruce Landon (the creator of Landon-line housed at Douglas College in British Columbia) in the development of EduTools, which has become a worldwide resource (www.edutools. info). EduTools is a decision site on the Web with independent information and reviews of course management software products, student support services, and institutional policy issues. The tools on the site let people compare the products on a common set of features and step the user through a rational decision process. By 2004, the site had been translated into several languages and was linked by sites all over the world. Another part of WCET’s expanding list of services was direct assistance to campuses and state higher education systems on a wide variety of topics relating to the integration of technology into academic activities both on and off campus. WCET staff and members worked on technology planning projects, auditing Web-based student support services, professionally developing campus leaders, developing new e-learning programs, evaluating programs and projects, as well as educating state and federal legislators. WCET staff also assisted with the academic manage-

ment of the eArmy University. In addition, the staff mentored a new organization—The North American Council for Online Learning (www. NACOL.org)—developed to assist virtual high schools with research and policy information. It was financially supported by the William and Melinda Gates and the William and Flora Hewlett Foundations. In 2002 WCET staff took a leadership role in the international movement for Open Educational Resources. Staff worked with the United Nations Educational, Scientific, and Cultural Organization (UNESCO) to introduce universities around the world to MIT’s OpenCourseWare Creative Commons project, Rice University’s Connexions project, EduTools, and Carnegie Mellon’s Open Learning Initiative. Just a few years later, open educational resources began developing in the Indian Ocean region, China, and other areas around the world. The original vision of the people at WICHE to create an organization that could serve as a catalyst for greater use of technology in higher education in western states blossomed into a world-wide resource. WCET’s annual conference, held each fall, attracts hundreds of higher education leaders to learn from one another and to discuss solutions to problems they are facing. The original mission of WCET to share intellectual and electronic resources throughout higher education continues to expand. WCET’s resources can be found at www.wcet.info.

key terms Accrediting Commissions: In the US there are both regional and professional accreditation systems that serve as the gatekeepers for quality in higher education. The six geographic regions of the US each have their own commissions (some have two) that are made up of individuals from the member institutions served by the region. These

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regional accrediting commissions also serve a role in determining institutional eligibility to administer federal financial aid for students.

Connexions Project, and other resources created electronically and made available worldwide for no cost.

Course Management Systems (CMSs): Also known as “learning management software or systems,” these have proliferated in the last few years. There are both proprietary and open-source CMSs now available to colleges and universities. Their goal is to integrate many of the functions associated with offering and managing an online course, so students and faculty members have only one program to use. The aggregated functions can include: discussion forums, real-time chats, orientation/help, self-assessments, registration integration, online grading tools, and about 35 others identified by WCET (see www.edutools. info for full list of functions).

Principles of Good Practice: Guidelines for institutions, state agencies, and accreditors on the institutional responsibilities for distance learning support to learners and faculty.

Distance Learner’s Guide: Originally published in 1999 by Prentice-Hall, it is a consumer’s guide to help prospective online students make intelligent decisions about their provider and the tools they will need to be successful. FIPSE (Fund for the Improvement of Post Secondary Education): A granting group within the US Department of Education. In the last 10 years it has been instrumental in supporting the development of new approaches to teaching and learning online. North American Council for Online Learning: Founded in 2002 by the William and Flora Hewlett Foundation to assist virtual high schools in policy and research. Online at www.NACOL. org. Open Educational Resources: The term accepted by the international higher education community through UNESCO to refer to such projects as MIT’s OpenCourseWare, Rice University’s

Quality Assurance: System for ensuring student experiences in online learning are valid. There are two approaches to quality assurance. One is regulatory through accrediting and governmental agencies. The other is through consumer protection, which requires educating potential students about their options and responsibilities. Technology Costing: Techniques and tools for determining the full costs of technology integration into the teaching and learning process. Western Cooperative for Educational Telecommunications (WCET): The cooperative advancing the effective use of technology in higher education founded in 1989 by WICHE. Western Governors University: Founded by the governors of the 18 member-states of the western Governors Association as an alternative to traditional higher education institutions. It is headquartered in Salt Lake City, Utah, and helps adult students earn degrees using learning outcomes. Western Interstate Commission for Higher Education (WICHE): Founded in the 1950s to assist the western states share higher education resources. Sister organizations exist in New England (NEBE), the South (SREB), and the Midwest (MHEC). WICHE runs a vast network of student exchange programs among the 15 western states, conducts national research projects, and is active in higher education policy.

This work was previously published in the Encyclopedia of Distance Learning, Volume 1, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 79-82, copyright 2005 by Idea Group Publishing (an imprint of IGI Global). 1762

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Chapter 3.37

Design Levels for Distance and Online Learning Judith V. Boettcher Designing for Learning and the University of Florida, USA

IntroductIon The importance of design for instructional programs—whether on campus or online or at a distance — increases with the possible combinations of students, content, skills to be acquired, and the teaching and learning environments. Instructional design—as a profession and a process—has been quietly developing over the last 50 years. It is a multidisciplinary profession combining knowledge of the learning process, humans as learners, and the characteristics of the environments for teaching and learning. The theorists providing the philosophical bases for this knowledge include Dewey (1933), Bruner (1963), and Pinker (1997). The theorists providing the educational and research bases include Vygotsky (1962), Knowles (1998), Schank (1996), and Bransford, Brown, and Cocking (1999). Instructional design offers a structured approach to analyzing an instructional problem and creating a design for meeting the instructional content and skill needs of a population of learn-

ers usually within a specific period of time. An instructional design theory is a “theory that offers explicit guidance on how to better help people learn and develop” (Reigeluth, 1999).

background This entry describes a multi-level design process for online and distance learning programs that builds on a philosophical base grounded in learning theory, instructional design, and the principles of the process of change as reflected in the writings of the theorists listed above. This design model builds on traditional instructional design principles, as described by Gagne (1965), Dick & Carey (1989), and Moore & Kearsley (1996). It integrates the strategic planning principles and the structure of the institutional context as described in Kaufman (1992) and Boettcher & Kumar (1999), and also integrates the principles of technological innovation and the processes of change as described by E. M. Rogers (1995) and R. S. Rosenbloom (1998).

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Design Levels for Distance and Online Learning

This entry describes a six-level design process promoting congruency and consistency at the institution, infrastructure, program, course, activity, and assessment level. It also suggests a set of principles and questions derived from that framework to guide the instructional design process.

sIx levels of desIgn Effective instructional design for online and distance learning benefits from instructional planning at six levels. Figure 1 summarizes these six levels of design, and identifies the group or individuals usually responsible for the design at that level and the length of the design cycle at each level. Ideally, the design at each of these six levels reflects philosophies of teaching and learning that are consistent with the institutional mission and consistent with the expectations of the students and society being served.

level one: Institutional design The design work to be done at an institutional level is similar to the strategic planning and positioning

of an institution. Institutional planning generally begins with an institution’s current vision and mission statements and then proceeds through a data collection and input process that addresses a set of questions such as the following:

Institutional Questions: • • • • • •

What programs and services comprise our primary mission? For whom? To what societal needs and goals is our institution attempting to respond? What life goals are most of our students working to achieve? What type of learning experiences are our students searching for? What changes in our infrastructure are needed to match our desired services, programs, and students? Does our institution have any special core competencies, resources, or missions that are unique regionally or nationally that might form the basis for specialized online and distance programs? What are the strengths of our mature faculty? Of our young faculty?

Figure 1. Six levels of design for learning Six Levels of Design Institution

Sponsor/Leader

Design and Review Cycle 3-5 Years

Degree, Program

Entire campus leadership and community Campus and Technology Staff College/Deans/Faculty

Provost, CIO and Vicepresidents Provost, CIO and Vicepresidents Dean and Chairs

Course

Faculty

Dept Chair

1-2 Years

Unit/Learning Activity Student Assessment

Faculty

Faculty and or Faculty team

1-2 Years

Faculty

Faculty and or Faculty team

1-2 Years

Infrastructure

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Design Responsibility

2-3 Years 1-3 Years

Design Levels for Distance and Online Learning

level two: Infrastructure design People often think that buildings, classrooms, Web applications, communication services, and servers are neutral as far as having an effect on teaching and learning. Nothing could be more misleading. Design of the infrastructure includes design of all the elements of the environment that impact the teaching and learning experiences of faculty and students and the staff supporting these experiences. It includes design of the following: • • •

Student services, faculty services, and learning resources. Design of administrative services, including admission processes, financial processes, and institutional community life events. Design of physical spaces for program launching events, hands-on, lab, or network gathering events, as well as celebratory graduation events.

physical and digital plants Infrastructure design for online and distance teaching and learning programs focuses on the design of the network and Web infrastructure. Infrastructures for online learning have offices, classrooms, libraries, and gathering spaces for the delivery and management of learning and teaching. However, these offices and classrooms are accessed through Web services, rather than through physical buildings. The good news about online infrastructures is that they support an unparalleled new responsiveness, feedback, and access for learning activities. After almost ten years of building online campuses, we now know that a “digital plant” infrastructure is needed to support the new flexible online and distance environments. We know that this new digital plant needs to be designed, built, planned, maintained, and staffed. The infrastructure to support the new programs cannot be done with what some have called “budget

dust” (McCredie, 2000). It is not nearly as easy or inexpensive as we all first thought. Some experts suggest that, a “full implementation of a plan for technology support on campus costs about the same as support of a library — approximately 5% of the education and general budget” (Brown, 2000).

components of a digital Infrastructure What exactly is a digital plant infrastructure? One way of describing this infrastructure is to think of it in four major categories of personal communication tools, networks, hardware for servers, and software applications. A key component of the digital infrastructure is the group of individuals who make the systems work. This digital plant is shown in Figure 2 (Boettcher and Kumar, 2000). Some of the questions that might be used to guide the development of the digital infrastructure follow.

personal communication tools and applications: • •

Will all students have their own computer? Their own laptop? Do we expect students all to be proficient with word processing applications, mail, Web applications, researching on the Internet? With collaborative tools and with one or more course management systems?

networks that provide access to web applications and resources and to remote, national, and global networks: •

What physical wired or wireless networks are needed to support Web applications, such as e-mail servers, directory servers, and Web application services?

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Design Levels for Distance and Online Learning

Figure 2. Teaching and learning infrastructure—“digital plant”

Network Hardware and S oftware: Intranets , links to regional and global networks

C ontent and data providers , Including IS P s , databas es plus free and s hared content res ources

•

How often will higher bandwidths be needed for video conferencing for programs? For meetings? For downloading large files? For streaming video?

dedicated servers and software applications that manage campus services: •

• •

What types of interactive Web services will be provided? What hardware and software will be required? What type of administrative systems and course management system will we use? What do we need to do to assure student, faculty, and staff accessibility from anywhere at anytime?

Software applications and services from external providers, such as research and library services that are licensed to the institutional community, Internet services, and out-sourced services, such as network services:

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Application S ervices , web s ervers , mail s ervers , directory s ervers , etc,

P eople

• •

P ers onal computing tools , s oftware. applications and s ervices

What licensed services are required and desired? What budget is required to support these services currently and into the future?

Technology decisions for students have always been part of the instructional design process for distance learning. A comforting way of thinking about the technology for the infrastructure design level is in terms of the generations of technologies used in distance learning. (Sherron and Boettcher, 1997). Distance learning was made possible with the widespread availability of technologies, such as the mail, radio, telephone, television, and audio and videocassettes. In the 21st century we simply have more technology and more choices. Now let’s look at the design of programs and courses. Design issues at these levels are principally the responsibility of the institutional academic leadership.

level three: program design At the program level of design, instructional planners answer questions about the type of program

Design Levels for Distance and Online Learning

to be offered, to whom, and over what period of time and at what cost. When venturing into new business areas, the following two guidelines are useful: (1) focus on programs that can leverage institutional core competencies and strengths, (2) plan a phased approach, gaining experience in delivering programs in one or two areas before launching others, and (3) recognize that online and distance learners generally are interested in achieving or completing an instructional goal that can assist in their current or future career path. It is in the next four levels of design that the principles of Vygotsky are most applied, building on Vygotsky’s (1962, 1978) view of the learner as a goal-oriented learner within a specific learning context using specific resources as directed by a teacher. These four core elements of all learning experiences provide a framework for the design process: • • • •

The person doing the learning—the learner The person guiding and managing the learning—the faculty/teacher/mentor The content /knowledge/skill to be acquired/ or problem to be solved The environment or context within which the learning experience occurs

Program Level Planning Questions: Program planning design has four categories of planning—curriculum, design/development process, faculty, and student.

in a box” with a minimal amount of interaction or a highly interactive and collaborative course requiring or using many online resources and applications?

design and development Questions: • •

•

•

faculty Questions: • • • •

curriculum Questions: •

•

What is the degree or certificate program to be offered online? Will it be a full master’s degree (10 to 16 courses), an undergraduate minor (four to six courses) or a certificate program (two to four courses)? What types of courses are envisioned? Will these courses be a fully developed “course

Who are the faculty who will design, develop and deliver the courses in the program? Who will lead the effort to develop the degree or certificate program for online or distance delivery? Which organization will be marketing the program? What course management system or similar Web tool will be used for the content management? What tools and resources will be available and supported for the interaction and collaboration activities? What is the schedule for design and development and delivery of courses and program? For the marketing and recruiting of the students?

What training will be available to faculty as they transition to online teaching and learning programs? What tools and resources and support will be available to faculty? Will faculty have any released time or budget for teaching and learning resources in the new online or distance environment? What type of access to the network is recommended and available? Will dial-up be sufficient, or will DSL or cable access be recommended or required?

student Questions: •

Who are the students who will enroll in this course of study? How will we find them and market the program to them?

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Design Levels for Distance and Online Learning

• • •

What will our students bring to the program experience? What tools and resources will the student in this program or certificate program require or be likely to use? Where will the students be doing their learning and with what types of content resources and applications? What level of network access is required or recommended?

The question of technology access for students was particularly important in the mid-1990s, when technology access was relatively scarce. However, the latest data from the Campus Computing Study of 2002 suggests that more than 75% of all students own their own desktop or notebook computer (Green, 2002). If all students have their own computers and access to the Internet, this access greatly impacts the design of communication activities and course experiences.

course design—level four Design at the course level is usually considered to be the responsibility of the faculty member. In online and distance courses, however, the stand-alone course is the exception rather than the rule. Most online and distance courses are part of a curriculum, certificate, or degree program. This means course-level design occurs within the context of the larger program and that many of the design decisions are made in collaboration with other faculty within the academic program or department. Faculty at the course level are primarily responsible for design decisions on content, objectives, student goals, learning experiences, and assessment for a particular course. Many of these questions for this design level parallel questions at the program level design. The following questions are more specific to a single course:

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course Questions: •

• •

•

Where does this course fit within the context of the degree or certificate program to be offered online? Is it an early course focused on core discipline concepts, peer discussions, and standard problems or a later course focusing on applications and complex scenarios? What is the core set of knowledge, skills, and attitudes/values to be acquired by the students? What is the set of content resources required and recommended? What content resources will students use to customize the learning experience for their needs and state of knowledge and personal interests? Will students be a cohesive cohort group?

design and development Questions: •

•

•

What types of instructional activities and experiences will support student learning of the knowledge, skills, and attitudes of the students? What course management system or similar Web tool will be used for the content management? For the interaction and collaboration activities? What is the schedule for design and development and delivery of this course?

faculty Questions: • •

What training is needed for a faculty member to transition to online teaching and learning programs? What tools and resources and support will be needed to support the delivery of this course?

Design Levels for Distance and Online Learning

student Questions: •

•

•

•

•

Who are the students taking this course? What are their hopes and expectations? What future courses will depend on the knowledge, skills, and attitudes acquired in this course? What knowledge and expertise do the students bring to the course? What is their zone of proximal development (Vygotsky, 1978)? What types of teaching and learning strategies best suit the students in this course? What are the life style and learning styles of the students? When and where will the students be likely to gather for their collaborative work? When and where will they do their more self-study activities? Where will the students be doing their learning? What level of network access is required or recommended?

The next two design levels are within the course parameters and generally are the responsibility of the faculty designing the course.

ments in a learner’s current life situation. Where will the learner be working? Will they have a personal space where they can control sound, temperature, disturbances, and network access? Will they have to “ask” their family if they can access the network? A life-style focus encourages analysis of the where, when, with whom, and with what resources the learner is going to be doing their learning work. Learning work consists of constructing new knowledge, applying and integrating knowledge, and solving problems with that new knowledge. Mobile, wireless technologies enable learners to study anywhere at any time. Initially, the ability to study anywhere seemed to hold the promise of solving many problems associated with access to learning. However, we have not addressed the question of just when and just where this “anytime” is likely to occur.

learning activity Questions: • •

level five: unit/learning activity Many of the design questions for the unit/learning activity level and the student assessment level are derived from a design model that focuses on integrating student life style and learning styles into instructional planning (Boettcher, 2003). Examples of cognitive learning style design questions include: “How do students process information?”; “How do students respond in their minds when challenged with new concepts and rich content structures?”, “What knowledge do students bring to the learning experience?” The life style of the learner is also addressed in these questions. Life style includes all the ele-

• • •

•

What is the knowledge, skill or attitude that is the desired outcome of this learning activity? What kinds of problems can students solve now? What kinds of problems do we want students to be able to solve at the conclusion of the experience? What instructional strategy or experience will support the learner learning the desired knowledge, skill, or attitude? When, where, with whom, and with what resources is the instructional activity envisioned to occur? What role will the teacher/mentor/faculty play during this activity? Will the teacher be present physically or at a distance, synchronously or asynchronously? When will a learner know that he/she knows? What feedback or result from a problem being solved will make the learner’s knowledge evident?

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Design Levels for Distance and Online Learning

level six: assessment of student learning Assessment is fundamental to the design process. Assessment planning helps to balance the goals of learning effectiveness and teaching and learning efficiency. In productive, customized, enriched learning experiences, each learner begins with an existing, personal store of knowledge representation. Learning experiences expand and enrich that knowledge base in individual and personal ways. Productive learning experiences mean that all students complete a learning experience with an expanded, yet different, store of knowledge. The goal is that learners learn core principles so that the core principles can be effectively applied, but the particular way the knowledge base is constructed in individuals is unique. What we can design into instructional planning is that all learners share some of the same experiences and that assessment focuses on the common learning that is achieved. Assessment can also provide for demonstration of knowledge and skills in more complex environments and for some elements of customized knowledge acquisition. Here are some selected questions for assessing student learning:

assessment Questions •

•

• •

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How will the learners know the goals and objectives for the learning? It is good to plan for core concepts, practice of core concepts, and customized applications of concepts. Will learners be generating a set of their own goals for learning? How will the faculty mentor and learner communicate and agree on goals for learning, particularly for customized applications of concepts? In what ways and where will the students be evaluated and graded? How will students demonstrate their competency in concept formation? In solving problems?

•

If we don’t see the students on a regular basis, can we design ways to “see” their minds virtually through conversation and experiences?

The portfolio project within the National Learning Infrastructure Initiative (NLII) is also useful as an assessment of complex learning (www.educause.edu/nlii/keythemes/eportfolios. asp).

future trends The process of instructional design is a professional task requiring knowledge of educational research, learning processes, and, increasingly, a respect for context, and a comfort level with innovation and instructional technologies. It is a labor-intensive task requiring interaction with content experts and administrators and institutional representatives. Much of the current instructional design processes focus on the analyses of needs and contexts for learning for learners, their tools and their resources — as a group. Future work in instructional design will focus more on the learner as an individual with unique knowledge structures and thus promote the needs for a rich contextual learning environment that is multi-leveled and customizable. The design of instructional planning will become more of a priority as the demand for effective and efficient learning grows as a result of time pressures, budget pressures, and increasing demands for accountability in education.

conclusIon These instructional design principles reaffirm the iterative nature of design work and the sharing of design work among the hierarchical groups of an institution. Instructional design, when done well, results in delighted and productive learn-

Design Levels for Distance and Online Learning

ers and faculty pleased with their roles and their work. Consistently applied, instructional design principles keep teaching and learning focused on the who, when, where, how, and why of teaching and learning and help to ensure that the money and time invested in learning programs provide an appropriate return for individuals and for society. Instructional design is a powerful tool that moves teaching and learning into the science of learning and knowing.

references Boettcher, J.V. (2000). How much does it cost to put a course online? It all depends. In M.J. Finkelstein, C. Francis, F. Jewett, & B. Scholz (Eds.), Dollars, distance, and online education: The new economics of college teaching and learning (pp. 172-197). Phoenix, AZ: American Council on Education/Oryx Press. Boettcher, J.V. (2003). Design levels for distance and online learning. In R. Discenza, C. Howard, & K. Schenk (Eds.), Distance learning and university effectiveness: Changing educational paradigms for online learning. Hershey, PA: Idea Group. Boettcher, J.V., & Kumar, V.M.S. (2000, June). The other infrastructure: Distance education’s digital plant. Syllabus, (13), 14-22. Bransford, J.D., Brown, A.L., & Cocking, R.R. (1999). How people learn. Brain, mind, experience, and school. Washington, DC: National Academy Press. Retrieved from the World Wide Web at: www.nap.edu/books/0309070368/html/ Brown, D.G. (2000). Academic planning and technology. In J.V. Boettcher, M.M. Doyle, & R.W. Jensen (Eds.), Technology-driven planning: Principles to practice (pp. 61-68). Ann Arbor, MI: Society for College and University Planning.

Bruner, J.S. (1963). The process of education. New York: Vintage Books. Business-Higher Ed Forum.(2003). Building a nation of learners: The need for changes in teaching and learning to meet global challenges. American Council on Education. Retrieved from the World Wide Web at: www.acenet. edu/bookstore/pubInfo.cfm?pubID=285 Dewey, J. (1933). How we think (1998 ed.). Boston, MA: Houghton-Mifflin. Dick, W., & Carey, L. (1989). The systemic design of instruction. New York, Harper Collins. Gagne, R. M. (1965). The conditions of learning. New York: Holt, Rinehart & Winston. Green, K. C. (2002). Campus computing, 2002. Encino, CA: The Campus Computing Project. Retrieved from the World Wide Web at: www. campuscomputing.net Kaufman, R. (1992). Strategic planning plus : An organizational guide. Thousand Oaks, CA: Sage Publications. Knowles, M. (1998). The adult learner: A neglected species. Houston, TX: Gulf. Moore, M.G., & Kearsley. G. (1996). Distance education: A systems view. Belmont, CA: Wadsworth. Newell, H.A. (1996). Sciences of the artificial. Boston, MIT Press. Pinker, S. (1997). How the mind works. New York: W.W. Norton. Reigeluth, C.M. (1999). What is instructionaldesign theory and how is it changing? In C.M. Reigeluth (Ed.), Instructional-design theories and models, volume II: A new paradigm of instructional theory (pp. 5-29). Mahwah, NJ: Lawrence Erlbaum.

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Rogers, E.M. (1995). Diffusion of innovations. New York, Free Press.

dent learning within an affordable and accessible delivery format.

Rosenbloom, R.S. (1998). Sustaining American innovation: Where will technology come from? Forum on Harnessing Science and Technology for American’s Economic Future, National Academy of Sciences Building, Washington, DC, National Academy of Science.

Instructional Design Theory: A “theory that offers explicit guidance on how to better help people learn and develop” (Reigeluth, 1999).

Schank, R.C. (1996). Goal-based scenarios: Casebased reasoning meets learning by doing. In D. Leake (Ed.), Case-based reasoning: Experiences, lessons & future directions (pp. 295-347). AAAI Press/The MIT Press. Schrum, L. & Benson, A. (2002). Establishing successful online distance learning environments: Distinguishing Factors that contribute to online courses and programs. In R. Discenza, C. Howard, & K. Schenk (Eds.), The design and management of effective distance learning programs (pp. 190204). Hershey, PA: Idea Group. Sherron, G. T., & Boettcher, J. V. (1997). Distance learning: The shift to interactivity. CAUSE Professional Paper Series #17. Retrieved September 22, 2004 from the World Wide Web at: www.educause.edu/asp/doclib/abstract.asp?ID=pub3017 Vygotsky, L.S. (1962). Thought and language. (E. Hanfmann & G. Vakar, trans.) Cambridge: MIT Press. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge: Harvard University Press.

key terms Instructional Design: The process of analyzing the students, content, and intended context of an instructional program to provide detailed specifications for an instructional program or curriculum to achieve effective and efficient stu-

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Instructional Strategy: An instructional strategy is a communication activity used to engage the learner in an educational experience and to assist the learner in acquiring the planned knowledge, skill, or attitude. Instructional strategies include lectures, discussions, reading assignments, panel presentations, study and media projects, problem analysis and solutions, field trips and assessment activities. Learning Infrastructure: The set of physical and digital buildings, applications, services, and people that provide and support the environments for learning. Learning Theory: A set of hypotheses or beliefs that explain the process of learning or acquiring knowledge and skill. Online Course: A set of instructional experiences using the digital network for interaction, learning and dialogue. An online course does not require any face-to-face meetings in a physical location. Similar courses such as web-centric courses (also called hybrid or blended courses) are similar to online courses, but require regular scheduled face-to-face classes or meetings. Zone of Proximal Development: This is a key concept in Lev Vygotsky’s theory of learning. The Zone of Proximal Development (ZPD) is the “distance between the actual developmental level as determined by independent problem solving and the level of potential development as determined through problem solving under the adult guidance or in collaboration with more capable peers” (Vygotsky, 1986).

Design Levels for Distance and Online Learning

endnote Note: This chapter is an adaptation of the following book chapter. Boettcher, J.V. (2003).

Design levels for distance and online learning. In R. Discenza, C. Howard, & K. Schenk (Eds.), Distance learning and university effectiveness: Changing educational paradigms for online learning. Hershey, PA: Idea Group.

This work was previously published in Distance Learning and University Effectiveness: Changing Educational Paradigms for Online Learning, pp. 21-54, copyright 2004 by Information Science Publishing (an imprint of IGI Global).

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Chapter 3.38

Care2x in Medical Informatics Education Andreas Holzinger Medical University Graz (MUG), Austria Harald Burgsteiner Graz University of Applied Sciences, Austria Helfrid Maresch Graz University of Applied Sciences, Austria

AbstrAct In this chapter the authors report about their experiences in education of both students of healthcare engineering at Graz University of Applied Sciences, and students of medicine at the Medical University Graz, gained during the winter term 2004. Care2x is an open source Web-based integrated healthcare environment (IHE). It allows the integration of data, information, functions, and workflows in one environment. The system is currently consisting of four major components, which can also function independently: hospital information system (HIS), practice management

(PM), a central data server (CDS) and a health exchange protocol (HXP). Although the components are under heavy development, the HIS has reached a degree of stability, where one can use it at least for educational purposes. Various groups also report the usage of enhanced versions of Care2x in real life settings. Our experiences in both—very different—student groups have been very promising. In both groups the acceptance was high and Care2x provided good insights into the principles of a hospital information system. The medical students learned the principal handling of a HIS, whereas the engineering students had the possibility to go deeper into technical details.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Care2x in Medical Informatics Education

IntroductIon In this chapter, the authors report about their experiences in the education of students of healthcare engineering (HCE) at Graz University of Applied Sciences, and students of medicine at the Medical University Graz, gained during the winter term of 2004. Care2x is an open-source Web-based integrated healthcare environment (IHE). It allows the integration of data, information, functions, and work flows in one environment. The system currently consists of four major components, which can also function independently: the hospital information system (HIS), practice management (PM), a central data server (CDS), and a health exchange protocol (HXP). Although the components are under heavy development, the HIS has reached a degree of stability so that one can use it at least for educational purposes. Various groups also report the usage of enhanced versions of Care2x in real-life settings. Our experiences with both—very different—student groups have been very promising. In both groups, the acceptance was high and Care2x provided good insights into the principles of a hospital information system. The medical students learned the principal handling of an HIS, whereas the engineering students had the possibility to go deeper into technical details. How to prepare both medical and engineering students in the best possible way for their later work with modern HISs is a common question. Whereas students of engineering are rather enthusiastic about IT, students of medicine are skeptical in general about using it. However, HISs are not widely accepted by healthcare professionals; that is, barriers to the use of HIS are primarily sociological, cultural, and organizational rather than technological (Moore, 1996). It seems plausible to not only give students theoretical background about the structure, functions, and common tasks of an HIS, but to also let them work with a fully functional HIS during

lectures. This is essential, particularly if students are required to be able to work with possibly any HIS in practice after only a short period of vocational adjustment. However, it depends on many different factors regarding which HIS to choose. One of the most important is whether it is necessary to teach (with) a particular HIS of a certain vendor, for example, if this system is deployed in a network of local hospitals. Another key factor, especially for noncommercial educational institutions, is the economic impact of the introduction of a commercial HIS at the university. Third, for the education of students of medical informatics, it might also be reasonable to teach the process of developing (parts of) a bigger software engineering project. Hence, the need for an open-source system arises if one does not want to start the development of his or her own HIS. Although there are many more factors to consider in general, we chose Care2x as our primary educational HIS for the following reasons.

care2x Care2x is a generic multilanguage, open-source project that implements a modern hospital information system (the Web page of Care2x is located at http://www.care2x.org/). The project was started in May 2002 with the release of the first beta version of Care2x by a nurse who was dissatisfied with the HIS in the hospital where he was working. As of today, the development team has grown to over 100 members from over 20 countries. Care2x is a Web-based HIS that is built upon other open-source projects: the Apache Web server from the Apache Foundation (http://www.apache. org/), the script language PHP (http://www.php. org/), and the relational database-management system (RDMS) mySQL (http://www.mysql. com/). There exist several source-code branches that try to integrate the option to choose from other RDBMSs like Oracle and postgreSQL. The latter one is already supported in the current version

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at the time of this writing (Deployment 2.1). For our investigations, we chose the most feature-rich version that was available from the Care2x Web page in early fall of 2004. This release had the version number 2.0.2. Some minor deficiencies that we report later may already be fixed in the current version, Deployment 2.1. Care2x is a very feature-rich HIS that is fully configurable for any clinical structure. It is built upon different modules, which include, for example, in and outpatient administration, admission, pharmacy, radiology (including DICOM [Digital Imaging and Communications in Medicine] image uploads), laboratories, ambulatories, nursing, medics, DRGs (diagnosis-related groups), and so forth. Online help is available for some clinical paths. See Figure 1 for an example.

reverse engIneerIng The reverse engineering of existing complex software packages starting at the source-code

level has a higher value for practical education than a new development. Bothe (2001) argues that groups of students will rarely be able to develop a project further than to a prototype stage during a single lecture. Access to the source code is not available for most commercial HISs, which is another advantage of using Care2x as an educational system. In our first lecture, the students of HCE were asked to test all functions and paths of Care2x. They had to set up a small virtual clinic and employ doctors, nurses, and technical stuff. Finally, patients had to be admitted, attended to, and dismissed at all stations. In a second lecture in the upcoming semester, our students have the assignment to analyze a fully functional HIS at the source-code level. Since Care2x is built upon a modular structure, small teams of programmers have tasks like finding and fixing bugs in the current version, adding simple modules for special functions not included in the official version, or implementing interfaces to other existing information systems or medical equipment. In the spirit of open-source projects, reasonable additions and

Figure 1. Help page describing the clinical path for starting a new surgery-operation document

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modifications can and should be published to the Care2x community Web page.

During the education, the students were faced with the following strengths and weaknesses of Care2x.

lessons learned Approximately 100 students from medicine and 25 from HCE participated (Figure 2). The whole lecture was built in the following way: 1. 2. 3. 4. 5. 6.

Theoretical foundations of HIS in traditional lectures Principles of Care2x explained (HCE group’s lecture was more technology orientated) Familiarization with Care2x in practical sessions Practical work, specific work flows Applying reverse engineering (HCE group only in the second part of the lecture) Examination (both theoretical and practical)

Strengths: • • • • • • • • •

Everyone can make his or her own tools Work does not have to be done in a strict order Very flexible Easy to handle Continuing design and development Open source Lots of different languages Bg community that takes care of Care2x Easy to select the different departments and stations

Figure 2. Students at work with Crae2x (We assigned groups of 2-3 students with different tasks related to the administration of a virtual hospital)

Figure 1 different tasks related to the administration of a virtual hospital

3 students w ith

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Weaknesses: • • • • • •

No real standard between the modules Documentation is only rudimentary A few tools are not really easy to interpret Lack of security measures Not a state-of-the-art user interface There is no global list of patients from which to select one

obstacles IdentIfIed During our lectures and trainings, there emerged several problems while using Care2x. There are a lot of small bugs that caused troubles. The biggest problem was that sometimes the browser responded with an “inactivity error” and the session would time out. Most of the time this error message was shown, the last click had not been made but one single minute ago. The next problem with the handling was that sometimes the back button on the Web browser would lead

to nowhere because Care2x does not manage this. Much later, we found out that the back button of the browser is unnecessary because the program has included this function. That did not solve the problem completely: Every now and then the integrated back button of Care2x led to nowhere, too. In addition, some pages did not include the Care2x back button (inconsistency), resulting in a blank page. This required the user to restart at the very beginning and click through all the menus once again, which was boring for the students. The general software problems that did not concern the running process were not severe. However, there is a serious problem when it is possible to admit a patient to more than one station, or when it is possible to alter a patient’s record after his or her death. A severe problem that has to be solved is that patients have to be discharged and then hospitalized again when we just want them to be transferred from the ambulatory to a station. There are some translation errors and missing notes. For example, if a new patient record

Figure 3. Example of a graphically embedded complex form, the diagnostic test order

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Figure 4. Nursing information about stationary occupancy for one of our virtual wards

is being applied, there are red stars above some properties. Although this is an obvious sign for experienced users, it is not noted anywhere why these stars appear. The students found out that these stars show the minimum amount of data that is required to create a patient record, but how would the students of medicine with little experience in IT know this fact? It is also sometimes annoying that bits of information are hidden behind a link. For example, if you want to hospitalize a patient, you have to remember the social insurance number because it is not shown in the place it is needed. This is due to the fact that Care2x works with only one window. Sometimes there might just be too little space to provide all the information needed, and then the user has to write this information down or remember it; this cannot be the aim of an HIS.

conclusIon Care2x is flexible open-source software. Although there are some bugs, it has the potential to become

functional software to support work flows within a (real) hospital. We think the biggest problems are the documentation and the deduction of treatments. Working with Care2x as a beginner is not very comfortable, and the software is not very intuitive. However, if one trains with Care2x, the work flows become clearer and more logical. The online help of Care2x should be better and more comprehensive. Working with the software was very fun because you really can play with a virtual hospital. Care2x is a very good possibility for training with work flows in a hospital. Further improvement of Care2x will open new areas to work with this software.

references Alpay, L., & Murray, P. (1998). Challenges for delivering healthcare education through telematics. International Journal of Medical Informatics, 50(1-3), 267-271.

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Bemmel, J. H. v., & Musen, M. A. (2000). Handbook of medical informatics. Berlin, Germany: Springer. Bothe, K. (2001). Reverse engineering: The challenge of large-scale real-world educational projects. 14th Conference on Software Engineering Education and Training (p. 115). Fieschi, M. (2002). Information technology is changing the way society sees health care delivery. International Journal of Medical Informatics, 66(1-3), 85-93. Haux, R. (1998). Health and medical informatics education: Perspectives for the next decade. International Journal of Medical Informatics, 50(1-3), 7-19. Haux, R. (2002). Health care in the information society: What should be the role of medical informatics? Methods of Information in Medicine, 41(1), 31-35. Haux, R., Hasman, A., Leven, F. J., Protti, D. J., & Musen, M. A. (1997). Education and training in medical informatics. In J. Bemmel, J. V. Bemmel, & M. A. Musen (Eds.), Handbook of medical informatics (p. 537ff). Heidelberg, Germany: Springer. Haux, R., & Knaup, P. (2000). Recommendations of the International Medical Informatics Association (IMIA) on education in health and medical informatics. Methods of Information in Medicine, 39(3), 267-277. Hovenga, E. J. S. (2004). Globalisation of health and medical informatics education: What are the issues? International Journal of Medical Informatics, 73(2), 101-109. Moore, M. B. (1996). Acceptance of information technology by health care professionals. Symposium on Computers and the Quality of Life (pp. 57-60).

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key terms Care2x: An open-source HIS available from http://www.care2x.org/. Care2x is a quite mature and stable product that can be used at least for educational purposes for both students of medicine and students of medical informatics. Some groups report the deployment of enhanced and adopted versions in real hospitals. Diagnosis-Related Group (DRG): The DRG system is an inpatient classification system based on several factors: the principal diagnosis, secondary diagnosis, surgical factors, age, sex, and discharge status. Under the Medicare prospective payment system, hospitals are paid a set fee for treating patients in a single DRG category, regardless of the actual cost of care for the individual. Digital Imaging and Communications in Medicine (DICOM): The DICOM image format is commonly used for the transfer and storage of medical images. Visit Chris Rorden’s DICOM page for information about the format and free software to view and manipulate it. Hospital Information System (HIS): It is the central medical information system in most hospitals in which most healthcare-related data (e.g., personnel, stations, patients and their medical history, etc.) are stored. Medical Informatics: The rapidly developing scientific field that deals with biomedical information, data, and knowledge: their storage, retrieval, and optimal use for problem solving and decision making. The emergence of this new discipline has been attributed to advances in computing and communications technology, to an increasing awareness that the knowledge base of medicine is essentially unmanageable by traditional paper-based methods, and to a growing conviction that the process of informed decision making is as important to modern biomedicine as is the collection of facts on which clinical decisions or research plans are made (Shortliffe, 1995).

Care2x in Medical Informatics Education

Open Source: The idea of sharing the source code of applications or tools for free. Other people are invited to elaborate on future extensions and improvements. Most open-source projects are committed to one of the Gnu public licenses (see http://www.gnu.org/licenses/licenses.html). RDBMS (Relational Database Management System): A software package that manages a

relational database, optimized for the rapid and flexible retrieval of data. It is also called a database engine. Reverse Engineering: Taking apart an existing system to analyze smaller or single parts. The reduced complexity simplifies the process of enhancing or understanding its functions.

This work was previously published in the Handbook of Research on Informatics in Healthcare and Biomedicine, edited by A. A. Lazakidou, pp. 81-88, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 3.39

An Expert-Based Evaluation Concerning Human Factors in ODL Programs: A Preliminary Investigation Athanasis Karoulis Aristotle University of Thessaloniki, Greece Ioannis Tarnanas Aristotle University of Thessaloniki, Greece Andreas Pombortsis Aristotle University of Thessaloniki, Greece

abstract In this chapter we describe the expert-based approach in evaluating open and distance learning (ODL) environments. Our study is mainly concerned with the domains of human-computer interaction (HCI) and human factors (HF), and the synergy between them in the field of ODL. The most promising approach to evaluating ODL is one which attempts to frame the ideas from distributed cognition research in a way that is more usable by HCI designers. Though the distributed cognition framework acknowledges

a vast majority of cases suited to HCI designers and evaluators, it has never been tried before as a framework for the evaluation of the cognitive work that is distributed among people, between persons and artifacts, across time and between abstract resources of information in the ODL domain. So, the main contribution of this chapter is on one hand to present the contemporary research on the domain, and, on the other hand to pinpoint the main concerns and to propose trends for further research on this complicated field that combines ODL, HCI and HF in such a holistic manner.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

An Expert-Based Evaluation Concerning Human Factors in ODL Programs

IntroductIon Most contemporary organizations spend enormous amounts on education and training in order to enhance the abilities of their human resources. A clear tendency in this direction is to utilize some alternative educational approaches, like computer based training (CBT), distance learning or another technology-enhanced variation that better suits the needs of the particular organization. Contemporary research on human factors has been concerned with participation and skill in the design and use of computer-based systems. Collaboration between researchers and users on this theme, starting with the pioneering work of Donald Norman (Norman, 1986) and Alan Newel (Card et al., 1983), has created a shift from the idea that Human Factors is a passive observation of users to the idea of Human Actors, where you create models for the interactions between actors, artifacts and the settings in which interaction occurs (Preece et al., 1994).

the communIcatIon channel Apart from its theoretical foundation as a research field, open and distance learning still carries its “childhood diseases”: the isolation of the student and the subsequent inactivity and loss of interest. Many solutions have been proposed, with varying levels of success, however, we believe the roots of this problem lie with an issue that almost any researcher of the field pinpoints: the transition of the traditional class to its distant counterpart breaks the personal contact between the participating parts and leads to the isolation of the student. However, the interaction between the members of the class has been proven to be of paramount importance in every educational environment and must not be underestimated. In terms of the scientific domains involved, the communication channel described here is the fusion of human factors, ODL and HCI. Rogers and Ellis (1994)

argue that traditional task analysis is ineffective for modeling open distance learning and instead argue that a more appropriate unit of analysis is the network of people and technological artifacts involved in the work. In this approach, analysis focuses on the transformation of information representations as they are propagated around the network, and also how shared representations are used to coordinate learning through the communication channel. This so-called distributed cognition (DC) perspective has been used to describe a range of activities from navigating warships to solving children’s puzzles, and DC has been discussed as one component of a theory to bridge research in CSCW, ODL and HCI (Nardi, 1996). Yet, despite this claim and despite the fact that the DC perspective is so obviously relevant to HCI theory and design, the ideas from distributed cognition research have not really gained visibility in the HCI community. So, we can argue that similarities and differentiations of traditional education and ODL emerge from the fact of granting knowledge, and from the method of granting it as well. The definition we prefer to follow here is that “the communication channel is the modes, the methods and the tools that realize the communicative interaction between the participants and the instructional environment.” To clarify this definition, we also attempt to describe it schematically. In the following diagrams, the whole set of arrowed lines constitutes the communication channel. The thickness of the line indicates the potential of the interaction, i.e., a thicker line indicates a stronger interaction, while a dotted line means a weaker interaction. In the traditional approach, we experience the pattern in Figure 1. The instructor belongs to the educational organization and has a strong interaction with the educational material, which is produced by him/her (lectures, exercises, etc.) and by the educational organization (printed material, etc.). The “class” comes into contact with the educational material via the instructor, while the students

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Figure 1. Traditional communication channel Educational Organization

Learner

Learner

Learner

Learner

Instructor

Instructional Material

Figure 2. ODL communication channel Learner Organization Educational Learner Instructor Learner Instructional Material

maintain a strong social relationship amongst themselves, thus facilitating the exchange of knowledge and meta-knowledge. However, in the case where physical distance is experienced between the participants, as in the case of distance learning environments, the above pattern alters to that shown in Figure 2. The notion of the class is no longer apparent, due to the individualization effect that occurs in all forms of distance learning. In addition, the notion of the teacher is much weaker as well, who is in this case often called the “tutor” because the learners mainly come into direct contact with the

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educational material, while the tutor fades out to a more supporting role. In this context the role of the tutor alters to a manager and facilitator of learning, rather than a director (Squires & McDougall, 1994). At the same time, the breaking up of the class in its parts (the students) leads to an individualised interaction between the tutor and every student, which however is also weaker. It is now commonly advocated that cognition and learning are situated in specific learning contexts (e.g., Brown et al., 1989). A situated view of learning implies that effects on learning of using information and communication technology will

An Expert-Based Evaluation Concerning Human Factors in ODL Programs

depend on the context in which it is used, with all the components of a learning environment (people and artifacts) interacting and contributing to the learning process. According to this point of view, the attempt of third generation ODL systems has long been to upgrade the interaction between tutor and learners and learners themselves to a level that will be of advantage over the present situation. So, the communication channel seems to be a very substantial component of ODL, and its presence must be maintained at every cost. The first signs in this direction are positive. Indeed, an applicable solution seems to be telematics, which is based on ICT. For many providers of distance education, telematics (all forms of electronic communication) has stepped in and is often portrayed as a viable substitute for face-to-face contact, if not indeed a panacea for distance education in particular and education in general (Mugler & Landbeck, 2000).

the educatIonal evaluatIon Many writers have expressed their hope that constructivism will lead to better educational software and better learning (e.g., Brown et al., 1989; Papert, 1993). They stress the need for open-ended exploratory authentic learning environments in which learners can develop personally meaningful and transferable knowledge and understanding. The lead provided by these writers has resulted in the proposition of guidelines and criteria for the development of constructivist software and the identification of new pedagogies. A recurrent theme of these guidelines, software developments and suggestions for use is that learning should be authentic, on a cognitive and contextual level. A tenet of constructivism is that learning is a personal, idiosyncratic process, characterised by individuals developing knowledge and understanding by forming and refining concepts (Piaget, 1952), which finally

leads to the five main socio-constructive learning criteria (Squires & Preece, 1999) that must be met in order to characterize an educational piece as socio-constructive: credibility, complexity, ownership, collaboration and curriculum. Human Factors research in the educational domain is investigating the visual search of computer menus and screen layouts. These models provide detailed empirically validated explanations of the perceptual, cognitive and motor processing involved (Kieras, 1988). However, there are certain known difficulties in the evaluation of educational environments in general, such as the difficulty to anticipate the instructional path every student will follow during the use of the software (Tselios et al., 2002), or the fact that such environments usually expand as they are used by the students (Hoyles, 1993). Nevertheless, in general, it is acclaimed to study the usability of an educational piece in relation to its educational value (Squires & Preece, 1999; Tselios et al., 2002). However, the problem of evaluating educational software in terms of Human Factors is one shared by many HCI practitioners. It is important to know if a design is being used as it was intended. When a design is being used differently than intended, then it is important to discover if that use is compatible with current domain practice. The most promising approach to evaluating educational HF (human factors) is one which attempts to frame the ideas from DC (distributed cognition) research in a way that is more usable by HCI designers. This approach is described as the distributed information resources model (or resources model for short). The Resources Model takes seriously the idea introduced to HCI by Suchman (1987) that various types of information can serve as resources for action and a set of abstract information structures can be distributed between people and technological artifacts. The Resources Model also introduces the concept of interaction strategy and describes the way in which different interaction strategies exploit different information

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structures as resources for action. In this sense the Resources Model is an HCI model in the DC tradition. The aim of the continuing work on the domain is to apply the Resources Model to collaborative distance educational settings where resources are shared between individuals. In this way it is hoped to explore the value of the resources model as a framework for bridging between HCI, ODL and CSCW research. Apart from Zhang’s work on ODL (Zhang & Norman, 1994), there have been few explicit attempts to use the ideas of distributed cognition to account for HCI phenomena. Scaife and Rogers (1996) analyse graphical representations as forms of external cognition and emphasise the importance of considering how the properties of such representations can affect thinking and reasoning. However, they do not provide an account of action or interaction. Monk (1999) has pointed out that these models of display-based interaction represent only one kind of interaction. By developing a framework for classifying different interaction models, Monk demonstrates that graphical representation models are unable to model certain types of interaction, such as interaction with moded interfaces. Since control of action is entirely relegated to the display in these models, they would be unable to model error-free interaction with an interface possessing hidden modes. In order to avoid mode errors in these kinds of interfaces, the user’s internal memory for the effects of previous actions must also play a role in controlling interaction. In order to capture a broader range of interaction styles, a more generic approach to the role of display information in supporting interaction is required, one which is capable of spanning a range of interaction styles. The resources model described earlier aims to achieve this by a more considered use of the ideas from distributed cognition described above.

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expert-based vs. user-based evaluatIons The most commonly applied evaluation methodologies are the expert-based and the empirical (user-based) evaluation ones, according to the taxonomy of most researchers on the field (e.g., Preece et al., 1994; Lewis & Rieman, 1994). Expert-based evaluation is a relatively cheap and efficient formative evaluation method applied even on system prototypes or design specifications up to the almost ready-to-ship product. The main idea is to present the tasks supported by the interface to an interdisciplinary group of experts who will play as professional users and try to identify possible deficiencies in the interface design. However, according to Lewis and Rieman (1994), “you can’t really tell how good or bad your interface is going to be without getting people to use it.” This phrase expresses the broad belief that user testing is inevitable in order to assess an interface. Why then, don’t we just use empirical evaluations and continue to research expert-based approaches as well? This is because the efficiency of these methods is strongly diminished by the required resources and by various psychological restrictions of the participating subjects. On the other hand, expert-based approaches have meanwhile matured enough to provide a good alternative. Nowadays, expert-based evaluation approaches are well established in the domain of HCI. Cognitive Walkthrough (Polson et al., 1992) and its variations (Rowley & Rhoades, 1992; Karoulis et al., 2000), Heuristic Evaluation (Nielsen & Molich, 1990) and its variations (Nielsen, 1993) and Formal Usability Inspection (Kahn & Prail, 1994) are the most encountered approaches in the field. An expert-based approach to human factors evaluation for educational software is primarily performed by using a distributed cognition approach and a multidisciplinary team of experts (Williams, 1993). A lot of the drawbacks to the

An Expert-Based Evaluation Concerning Human Factors in ODL Programs

application of this theory are shared with many other evaluation techniques used in HCI, particularly those relying on heuristics. One advantage of distributed cognition, with respect to too much data, is that the theory helps focus on where to look in the data by the emphasis on domain expertise and task relevant representational state. A second problem is that this method is time consuming, as with all analysis. Again, this is a problem that many analysis methods face, even those not videobased. It is a problem encountered in virtually all educational industries using HCI, where the pressure to “get the product out” is essential.

adaptatIon to the web According to Marchionini (1990), the use of hypermedia and the web allows the learners access to vast quantities of information of different types, control over the learning process, and interaction with the computer and other learners. A pilot study performed at Cornell University (Fitzelle & Trochim, 1996) had, as its primary research question, whether the web site enhanced student perceptions of learning. The research findings showed that students thought that the web site significantly enhanced their learning of course content. Student perceptions of performance in the course were also predicted by variables of enjoyment and control of the learning pace. Every web-based instructional program is a collaborative environment on its own, allowing users to communicate and interact with all participating entities; therefore, in common with current thinking, cognition is “distributed” between users, the environment and learning artifacts, including computers, when learning takes place (Brown et al., 1989; Salomon, 1996). The distribution of cognition leads learners to construct their own concepts, which they use to learn. In the domain of the evaluation of web-based courses, educational psychology provides many theoretical principles for application in the de-

velopment and evaluation of online instructional technology. Milheim and Martin (1991), in studying learner control motivation, attribution and informational processing theory, identify learner control as an important variable in developing the pedagogy of web sites. It is beneficial to generally maximize learner control as it enhances the relevance of learning, expectations for success and general satisfaction, contributing to heightened motivation (Keller & Knopp, 1987). This research looked specifically at the control of pace by the student as a factor in building on existing theory. A tenet of constructivism is that learners direct their own learning either individually or through collaborative experiences. This implies that learners need to find their own pathways through learning; a philosophy that underpins hypertext and many web-based instructional systems (Murray, 1997). E-mail, listserves and web browsers also support this approach by enabling students to search for information and discuss issues with others around the world. So, one can infer that the collaborative and interactive nature of the web mainly supports learning by means of the augmented motivation of the student. On the other hand, it is common for students to make wrong assumptions or possess an incorrect mental model of the domain they study. However, HCI researchers are much better at understanding and augmenting the artifact. The artifact, in conjunction with the user, determines which operators users can apply to reach their goals and often plays a central role in maintaining state information for the task. It is time-consuming to evaluate sessions with users, and setting up a usability laboratory may cost a lot of money. There are researchers that suggest a way to overcome these problems, which is to move the usability laboratories to the users and experts (Catledge & Pitkow, 1995). By using the web as a usability laboratory, we are able to reach a wide range of users and experts. In order to achieve that, tools are needed that can monitor users’ actions as well as allowing experts to send feedback about the interface. One environment

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suitable for the task at hand is the web itself. By creating interfaces in html and catching user events in the html pages, it also captures users’ actions and cognitive states.

from human factors to human actors Computational cognitive modeling is emerging as an effective means to construct predictive engineering models of people interacting with computer systems (Preece et al., 1994). Cognitive models permit aspects of user interfaces to be evaluated for usability by making predictions based on task analysis and established principles of human performance. Cognitive models can predict aspects of performance, such as task execution time, based on a specification of the interface and task. Cognitive modeling can thus reduce the need for user testing early in the development cycle. Cognitive models can also reveal underlying processing that people use to accomplish a task, which can help designers to build interfaces and interaction techniques that better complement the actual processing that humans apply to a task. When built with an architecture such as EPIC (executive process-interactive control, Kieras, 1988),

ACT-R/PM (atomic components of thought with rational analysis and perceptual/motor enhancements, Anderson & Garisson, 1995), or EPIC-Soar (the Soar architecture with enhancements from EPIC), cognitive models also contribute to Allen Newell’s grand vision of a unified theory of cognition (Card et al., 1983). Methodologies for applying cognitive architectures to predict aspects of human performance and learnability are still evolving (Kirschenbaum et al., 1996). On the other hand, Heuristic Evaluation (Nielsen & Molich, 1990) and formal usability inspection (Kahn & Prail, 1994) are criteria- or heuristic-based methodologies. So, the next point of concern is the appropriate list of criteria or heuristics needed to assess the environment. As already stated, a good starting point provides the socio-constructivist view of instruction. Some studies in the field (e.g., Tselios et al., 2001) are based on the constructivist approach for open learning environments, sometimes also known as micro-worlds (Papert, 1980). Their study concludes by presenting a set of learnability heuristics (see Table 1). Squires and Preece (1999) proceed one step further: they do not make a combination, but a fusion of Nielsen’s heuristics with the five socio-constructivist learning criteria (credibil-

Table 1. The learnability heuristic list (According to Tselios et al., 2001) a1 a2 a3 a4 a5 a6 a7 a8

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Does the system facilitate the active interaction of the user? Is the development of personal problem solving strategies by the learners possible? Are tools available, corresponding to the way he learns and to his/her cognitive level? Are the available tools of alternating transparency, so that it is possible to express differentiations between students as well as intrinsic differentiations of every student? Does the environment afford experimentation with the acquired knowledge? Are there multiple representations and multiple solutions that students can explore? Is there adequate system feedback and progress feedback, so that the student can reconsider his/her strategies? Is there the possibility for the student to assess his/her activities on his/her own?

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ity, complexity, ownership, collaboration and curriculum) thus providing a new list, which they claim to be a versatile tool in predictably evaluating educational pieces by their usability and simultaneous learnability. They state that the underlying socio-constructivist theory of nearly every contemporary educational environment is, to a high degree, compatible to the stated Nielsen-heuristics. The authors conclude with a list of “learning heuristics,” as shown in Table 2 (Squires & Preece, 1999). Finally, a study performed by Karoulis and Pombortsis (2003) regarding ODL environments concluded with a more comprehensive criteria list, containing 10 axes with 53 criteria, which is intended for a more holistic and detailed evaluation of the environment (see Table 3).

A different approach, with comparable goals, is to arrange for a cognitive HF model to interact directly with applications through their user interfaces. The main drawback is that the model must now address a new set of complexities dealing with visual processing, object manipulation, action planning, and so forth, to a greater level of detail than required by the approaches above. The potential advantages of extending a cognitive model in this way, however, are compelling: •

Ecological validity: By their nature, interface simulations and specifications are abstractions; they often pay attention to unimportant details of a real interface. Real user interfaces exhibit variations in timing, predictability and reliability of actions, as

Table 2. Learning heuristics (According to Squires & Preece, 1999) 1. 2. 3. 4. 5. 6. 7. 8.

Match between designers’ and learners’ mental models. Ensure navigational fidelity. Provide appropriate levels of learner control. Prevent peripheral cognitive errors. Understandable and meaningful symbolic representation. Support personally significant approaches to learning. Build strategies for the cognitive error recognition, diagnosis and recovery cycle. Match with the curriculum.

Table 3. Holistic list (According to Karoulis & Pombortsis, 2003; criteria are omitted) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Content ODL adaptation and integration User interface Use of technologies Interactivity with the instructional material Student’s support Communication channel Acquisition of knowledge Projects and “learning by doing” Assessment and self-assessment

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•

•

•

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well as the occurrence of events uninitiated by the user, among other behavioral properties, which may or may not be relevant to the performance on a given task. Neglecting these subtleties, however, can bring the validity of empirical cognitive modeling results into question. We can forestall potential objections along these lines by reducing the distance between cognitive models and real environments. Real-world problem relevance: Cognitive modeling goals usually include a concern for solving problems of general interest, rather than focusing solely on problems for model calibration or benchmarking. Real user interfaces easily provide real-world problems; additional design and maintenance effort is required to replicate such problems in a simulation or specification. External standards for comparison: Progress in cognitive modeling often arises from comparisons of different models on the same problem. In some cases it is straightforward to determine whether two instances of a problem are directly comparable. However, as researchers take on more complex problems in richer environments, this determination can be more difficult, especially if the tested interfaces differ significantly (e.g., an active simulation in one case and a symbolic specification in another). This difficulty can be isolated if environmental information and interactions stem from a single independent source, a real user interface. Development effort: In some cognitive modeling efforts, considerable work is devoted to developing realistic user interface scenarios, either as static representations or device simulations. Ironically, much of this effort reproduces functionality that already exists in a form appropriate for human users, but is inaccessible (e.g., programmatically) to a cognitive model.

concerns The main question that remains unanswered with regards to the learnability of the environment is whether the experts are really able to predict the problems experienced by the learners and the cognitive domain of the environment. Some studies in the field (e.g., Tselios et al., 2001) argue that an expert evaluator cannot predict the students’ performance, although he/she can assess heuristically the learnability of the environment, with mediocre results. Another issue that needs further research is the protest stated by Spoole and Schröder (2001) regarding the optimal number of evaluators. The authors presented the results of some recent research that brings into question the long-standing rule of thumb put forth by Jakob Nielsen (Nielsen & Molich, 1990), concerning his description of heuristic evaluation. The point of contention is whether one can truly find the majority of usability problems in complex web sites by employing a very small number of testers. The Nielsen rule of thumb, referred to by the authors as the “parabola of optimism,” states that five testers can find 85% of the problems in a web site regardless of its size. In contrast, Spoole and Schröder’s research indicates that the number of testers needed increases linearly with the size of the web site. There are some objections to this statement, mainly because the heuristic methodology is not task-based and because simple test users have been proven not to perform well in heuristic approaches. However, the claim of Spoole and Schröder (2001) becomes too important to be ignored, because educational sites can expand greatly, users mainly perform tasks in such sites and ODL includes de facto the cognitive parameter of inexperienced users.

future trends The expert-based approach, as presented in this chapter, does not yet seem suitable for a holistic

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evaluation of the environment. We are entering the age of ubiquitous computing in which our environment is evolving to contain computing technology in a variety of forms. Such environments, also called “media spaces” (Stults, 1988) are developments in ubiquitous computing technology, involving a combination of audio, video and computer networking. They are the focus of an increasing amount of research and industrial interest into support for distributed collaborative work. These concerns are of interest for ODL ubiquitous environments, as a large amount of educational and private data is circulating between the participating entities. The assessment of such an environment is a challenge for expert-based evaluation of human factors.

task of deciding which observed representations are actually relevant representational states for a particular cognitive activity. Theory and domain expertise work together during observation to aid an analyst in determining these task relevant representational states. However, the method differs from these other fields by the pervasive influence of the distributed cognition theory. Cognitive theory is far from sacrosanct. Indeed, in recent years the dynamicism of mainstream cognitive theory has been shown by its adaptation and incorporation of the connectionist challenge from below and its recent response to the challenge of situated action from above (e.g., Zhang & Norman, 1994). We firmly believe that applied cognition must be based upon cognitive theory.

conclusIon

references

The two roles of expert-based evaluation in human computer interaction (HCI) are to aid design and analysis. Distributed cognition is a theoretical framework that differs from mainstream cognitive science by not concentrating on the individual human actor as the unit of analysis. Distributed cognition acknowledges that in a vast majority of cases cognitive work is not being done in isolation inside our heads but is distributed among people, between persons and artifacts, and across time. This has a natural fit for ODL, where the behavior we are interested in is the interaction of all the involved entities through the communication channel, the system of people and artifacts. What makes a system cognitive is the presence of processes applied to representational states that result in cognitive work. Tracking the representational states can uncover the specific cognitive processes being employed. In a system, these representational states can be directly observable. While the movement of the boundary of the unit of analysis from individual to system facilitates observation, there is still the difficult

Anderson, T.D., & Garisson, D.R. (1995). Critical thinking in distance education: Developing critical communities in an audio teleconferencing context. Higher Education, 29, 183-199. Brown, J.S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42. Card, S.K., Moran, T.P., & Newell, A. (1983). The psychology of human-computer interaction. Hillsdale, NJ: Lawrence Erlbaum Associates. Catledge, L. D., & Pitkow, J. E. (1995). Characterizing browsing strategies in the World Wide Web. Computer Networks and ISDN Systems, 27, 1065-1073. Fitzelle, G., & Trochim, W. (1996). Survey evaluation of web site instructional technology: Does it increase student learning? Retrieved from http:// trochim.human.cornell.edu/webeval/intro.htm Hoyles, C. (1993). Microworlds/schoolworlds: The transformation of an innovation. In C. Keitel

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& K. Ruthven (Eds.), Learning from computers: Mathematics educational technology (pp. 1-7). Berlin: Springer-Verlag. Kahn, M., & Prail, A. (1994). Formal usability inspections. In J. Nielsen & R. L. Mack (Eds.), Usability inspection methods (pp. 141-171). New York: John Wiley & Sons. Karoulis, A., & Pombortsis, A. (2003). Heuristic evaluation of web-based ODL programs. In C. Ghaoui (Ed.), Usability evaluation of on-line learning programs (pp. 86-107). New York: IDEA. Karoulis, A., Demetriades, S., & Pombortsis, A. (2000). The cognitive graphical jogthrough – An evaluation method with assessment capabilities. In Applied Informatics 2000 Conference Proceedings, Innsbruck, Austria (pp. 369-373). Anaheim, CA: IASTED/ACTA. Keller, J., & Knopp, T. (1987). Instructional theories in action: Lessons illustrating theories and models. Hillsdale, NJ: Erlbaum Associates. Kieras, D. E. (1988). Towards a practical GOMS model methodology for user interface design. In M. Helander (Ed.), The handbook of humancomputer interaction (pp. 135-158). Amsterdam: North-Holland. Kirschenbaum, S. A., Gray, W. D., & Young. (1996). Cognitive architectures for human-computer interaction. SIGCHI Bulletin. Lewis, C., & Rieman, J. (1994). Task-centered user interface design: A practical introduction. Retrieved from ftp.cs.colorado.edu/pub/cs/distribs/HCI-Design-Book Marchionini, G. (1990). Evaluating hypermediabased learning. In D. H. Jonassen & H. Mandl (Eds.), Designing hypermedia for learning (pp. 355-376). NATO ASI Series, 67. Springer Verlag.

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Milheim, W.D., & Martin, B.L. (1991). Theoretical bases for the use of learner control: Three different perspectives. Journal of Computer-Based Instruction, 18(3), 99-105. Monk, A.F. (1999). Modeling cyclic interaction. Behaviour & Information Technology, 18(2), 127-139. Mugler, Fr., & Landbeck, R. (2000). Learning, memorisation and understanding among distance learners in the South Pacific. Learning and Instruction, 10(2), 179-201. Murray, J. H. (1997). Hamlet on the Holodeck: The future of narrative in cyberspace. New York: The Free Press. Nardi, B.A. (1996). Context and consciousness: Activity theory and human-computer interaction. Cambridge: MIT Press. Nielsen, J. (1993). Usability engineering. San Diego: Academic Press. Nielsen, J., & Molich, R. (1990). Heuristic evaluation of user interfaces. In Proceedings of Computer-Human Interaction Conference (CHI) (pp. 249-256). Seattle, WA. Norman, D.A. (1986). Cognitive engineering. In D. Norman & S. Draper (Eds.), User centered system design. Hillsdale, NJ: Lawrence Erlbaum Associates. Papert, S. (1980). Mindstorm: Children, computers and powerful ideas. New York: Basic Books. Papert, S. (1993). The children’s machine: Rethinking school in the age of the computer. New York: Basic Books. Piaget, J. (1952). The origins of intelligence in children. New York: International University Press. Polson, P.G., Lewis, C., Rieman, J., & Warton, C. (1992). Cognitive walkthroughs: A method for theory-based evaluation of user interfaces.

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International Journal of Man-Machine Studies, 36, 741-773. Preece, J., Rogers, Y., Sharp, H., Benyon, D., Holland, S., & Carey, T. (1994). Human-computer interaction. Addison-Wesley. Rogers, Y., & Ellis, J. (1994). Distributed cognition: an alternative framework for analysing and explaining collaborative working. Journal of Information Technology, 9(2), 119-128. Rowley, D., & Rhoades, D. (1992, May). The cognitive jogthrough: A fast-paced user interface evaluation procedure. In Proceedings of the ACM, CHI ’92 (pp. 389-395). Monterey, CA. Salomon, G. (Ed.). (1996). Distributed cognitions: Psychological and educational considerations. Cambridge: Cambridge University Press. Scaife, M., & Rogers, Y. (1996). External cognition: How do graphical representations work? International Journal of Human-Computer Studies, 45, 185-213. Spoole, J., & Schröder, W. (2001). Testing web sites: Five users is nowhere near enough. In Proceedings of the ACM - CHI 2001. Squires, D., & McDougall, A. (1994). Choosing and using educational software: A teachers’ guide. London: Falmer Press.

Squires, D., & Preece, J. (1999). Predicting quality in educational software: Evaluating for learning, usability, and the synergy between them. Interacting with Computers, 11(5) 467-483 Stults, R. (1988). The experimental use of video to support design activities. Xerox PARC Technical Report SSL-89-19. Palo Alto, California. Suchman, L.A. (1987). Plans and situated actions: The problem of human computer interaction. Cambridge: Cambridge University Press. Tselios, N., Avouris, N., & Kordaki, M. (2002). Student task modeling in design and evaluation of open problem-solving environments. Education and Information Technologies, 7(1) 19-42. Tselios, N.K., Avouris, N.M., & Kordaki, M. (2001). A tool to model user interaction in open problem solving environments. In N. Avouris & N. Fakotakis (Eds.), Advances in human-computer interaction (pp. 91-95). Patras, Greece: Typorama. Williams, K. E. (1993). Automating the cognitive task modeling process: An extension to GOMS for HCI. In Proceedings of the Fifth International Conference on Human-Computer Interaction Poster Sessions (Vol 3., p. 182). Abridged Proceedings. Zhang, J., & Norman, D.A. (1994). Representations in distributed cognitive tasks. Cognitive Science, 18, 87-122.

This work was previously published in E-Education Applications: Human Factors and Innovative Approaches, edited by C. Ghaoui, pp. 84-96, copyright 2004 by Information Science Publishing (an imprint of IGI Global).

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Chapter 3.40

An Organizational Memory Tool for E-Learning Marie-Hélène Abel University of Compiègne, France

Abstract Learning can be considered an outcome associated with acquiring new competencies (Sicilia, 2005) and adding new knowledge. A competence is a way to put into practice some knowledge in a specific context. The process of competency acquisition starts from a need in this specific context. It may induce the search and the selection of relevant resources. Numerous resources may be used during e-learning, their access is a real problem. Different approaches may be adopted to exploit them. This chapter describes the tool E-MEMORAe, which supports an organizational goal-driven approach based on the concept of learning organizational memory. In such a memory, ontologies are used to define knowledge that indexes resources; the capitalization and the organization of knowledge, information, and resources relating to a specific context can be realized. End-users have a direct

access to the memory. The organizational environment E-MEMORAe was evaluated in the context of two courses taught at the university (algorithms, mathematics).

Introduction and Background Learning can be considered an outcome associated with acquiring new competencies (Sicilia, 2005) and adding new knowledge. A competence is a way to put into practice some knowledge in a specific context. From an educational point of view, knowledge is defined as all the notions and the principles that a person acquires through study, observation, or experience, which can be integrated into skills. However, studying an encyclopaedia is not sufficient to get knowledge; Didactic work has to be made.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

An Organizational Memory Tool for E-Learning

The process of competency acquisition starts from a need in a given context. It may induce the search and the selection of relevant resources. Numerous learning resources may be used during e-learning. E-learning becomes part of a complex organizational conduct, in which lack of required competencies trigger the search for appropriate contents (Sicilia, 2005). Different approaches may be adopted to exploit such contents. They can be stored in learning objects repositories and then reused, combined and adapted in different contexts. They can also be selected and organized in learning memories that are directly accessed by learners. These approaches offer a goal-driven organizational learning. Over the last few years, many projects aiming at building bases of learning resources, in order to share and re-use them, have been launched. These projects often rely on a network of contributors that feed the base with collaboratively controlled resources. Conversely, each contributor can benefit from resources brought by other contributors. We can make a distinction between learning object repositories (LOR), which usually group many subject matters, and what we call “thematic resource bases” that contain resources related to only one domain. LOR usually group all subject matters. Their scope can be restricted to one or several universities or to a country; it can also be international. If expected scope is wide, LOR are based on a network of contributors or on a consortium of institutions. The restriction in resources related to a particular domain brings more homogeneity; resources and associated knowledge can be managed more precisely. Thus, relying on knowledge engineering techniques, Paquette (Paquette, 2001) designed knowledge and resources base on tele-learning. As in the case of repositories, the idea is also to share and re-use resources. These resources are not ready to be used by learners; instructional design work is usually needed beforehand.

On the contrary, within the Memorae project (in French, Mémoire organisationnelle appliquée au e-learning) supported by the pole Systèms et Technologies de l’Education et de la Formation (STEF) of the Picardy area, France, our goal is to let learners directly access the resources of a course memory. Following a knowledge engineering approach, we organise the resources in a learning organizational memory based on ontologies (Abel, Barry, Benayache, Chaput, Lenne, & Moulin, 2004). In fact, it is a course memory, where a course is seen as an organization. This memory is different from a classical organizational memory because its goal is to provide pedagogycal users with content. This content is the result of two pieces of work: (1) the capitalization of knowledge, information, and learning resources relating to the learning context (a course unit); (2) a pedagogical work concerning the choice and the organization of this capitalization. In order to give learners direct access to the memory, part of the instructional design work has to be made earlier. The advantage is that the memory is ready to be used by learners, provided that pedagogical and didactical choices made earlier are acceptable. This can therefore lead to a loss of flexibility, but we make the assumption that these choices can at least be shared by a teacher community that could act as a “community of practice” (Wenger, 1998). We realized two pilot applications to evaluate our propositions: the first one concerns NF01, a course on algorithms and programming at the University of Technology of Compiègne, and the second one concerns B31.1, a course on applied mathematics at the University of Picardy (France). In the following, we first specify links between competencies and knowledge. Then we specify the role of knowledge in organizations and the parallel between knowledge management and e-learning. Afterward, we introduce the project MEMORAe, founded on the concept of learning organizational memory based on ontologies. We

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show how we modeled the memory. Finally, we present the organizational environment built from this model: E-MEMORAe (http://www.hds.utc. fr/~ememorae/Site-MEMORAe/). All examples come from the B31.1 application.

competencIes and knowledge We can find different definitions of the concept of competency. Meanwhile, all the definitions seem to agree on three fundamental characteristics (Harzallah & Vernadat, 2002): resources, context, and objective. A competency is made of resources structured into categories. We can consider three main categories of resources: knowledge, know-how, behaviours (Harzallah, Leclère, & Trichet 2002). Knowledge is something that we acquire and store intellectually. It concerns everything that can be learned in an education system. For example, this category is concerned with theoretical knowledge, procedural knowledge. Know-how is related to personal experience and working conditions. It is acquired by putting into practice knowledge in a specific context. Behaviours are individual characters that lead someone to act or react in a particular way under particular circumstances. They often condition the way knowledge or knowhow is put into practice. According to Baugh (1997), we can distinguish two types of competencies: •

•

Hard competencies identify the basic resources that require performing an activity. These resources are generally expressed in terms of knowledge, skills, and abilities. Soft competencies correspond to personal behaviours, personal traits and motives (Wooddruff 1991), for example: working with others, leadership, etc.

The competency context is related to the environment in which the competency is situated.

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It represents the conditions and the constraints in which competencies should be mobilized. Competency is related to reaching a goal or to the accomplishment of one or more missions, or tasks. These goals, missions, or tasks constitute the objective of the competency. Finally, acquiring competencies needs to select resources, to manage their combination and to control the way of bringing them into play. In this chapter, we focus on hard competencies and particularly knowledge resource, context, and objective of the competency.

knowledge and organIzatIon Knowledge in an organization is the collection of expertise, experience, and information that individuals and workgroups use during the execution of their task (Abecker, & Decker, 1999). A knowledge organisation is one in which the key asset is knowledge (Conklin 1996). An organization’s knowledge is built upon experience of their human resources and the lessons they learn. The effective management of this knowledge is addressed through research in the field of knowledge management: organizational memory. In order to share information in an organization, actors have to use common terminology, especially when they are geographically distant. It is one of the reasons why organizational memories are often based on ontologies.

organizational memory According to Van Heijst, Schreiber, and Wielinga (1997), one of the attempts of knowledge management is to make sure that an organization is able to apply the right knowledge at the right place and at the right time to achieve its business goal. Another attempt concerns the development of a knowledge policy based on business strategy. It necessitates a knowledge infrastructure to implement it and to monitor the functioning of

An Organizational Memory Tool for E-Learning

the knowledge infrastructure (is the knowledge policy still adequate? Does the knowledge infrastructure adequately support it?). Two necessary conditions for accessible knowledge are: an efficient way of finding information related to some information need, and an efficient way of investigating the “context” of information found in order to establish its relevance and reliability (Martin, 1993). A common approach to tackle the knowledge management problem in an organization consists of designing an organizational memory (OM). Such a memory can be seen as “an explicit and persistent representation of knowledge and information in an organization, in order to facilitate their access and reuse by members of the organization for their tasks” (Rabarijaona, Dieng, Corby, & Ouaddari, 2000, p. 56). The first role of an OM is to support the growth, the transmission and the conservation of knowledge (Steels, 1993). To that end, organizational memory management is based on the following stages (Dieng, Corby, Giboin, & Ribière 1998): • • • • • •

Needs detection Construction and structuring Diffusion of the contents Exploitation of the contents Evaluation of the objectives Maintenance and evolution of the contents

Organizational memories should comprise the knowledge of an organization collected over time (Klemke, 2000). It includes a model to describe information resources and the context in which these sources are created. It also includes knowledge in the form of personal memories of users (their knowledge, resources, etc.).

ontology is an explicit formal specification of how to represent objects, concepts and other entities that are assumed to exist in some area of interest and the relationships that hold among them. What “exists” is that which can be represented. According to Gruber (1993) “An ontology is an explicit specification of a conceptualization.” Guarino gives precision on this definition, considering that ontologies are necessarily a partial specification of a conceptualization (Guarino & Giaretta, 1995). We can add with Gruber “an ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents.” Using ontologies in AI systems is important. Indeed, ontological analysis clarifies the structure of knowledge. If we don’t have the conceptualizations that underlie knowledge, then we do not have a vocabulary for representing knowledge. Another point is that they provide a means for sharing knowledge (Chandrasekaran, Josephson, & Benjamins, 1998). Finally, an ontology is a catalog of the types of things that are assumed to exist in a domain of interest D from the perspective of a person who uses a language L for the purpose of talking about D. The types in the ontology represent the predicates, word senses, or concept and relation types of the language L when used to discuss topics in the domain D (Sowa, 2003). According to (Van Heijst et al., 1997), we can distinguish different kinds of ontologies: •

•

ontologies The term ontology is borrowed from philosophy, where ontology is a systematic account of existence. For artificial intelligence (AI) systems,

•

Domain ontology: Represents specific conceptualizations of a domain. These representations are reusable for several applications of this domain. Application ontology: Represents domain knowledge useful for a given application. This knowledge is specific and not reusable. Generic ontology: Represents valid conceptualisations for different domains.

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•

Meta-ontology: Represents language primitives of knowledge representation.

knowledge management and e-learnIng Currently, several approaches concern the pedagogical content management for e-learning. They are often based on the use of large sets of learning objects. A set of learning objects can be a “repository” shared by a network of actors whose goal is to reuse and adapt learning material. It can also be a “learning memory” where resources are structured and organized in order to support distance learning. Learning object repositories (LOR) usually group all subject matters. Their scope can be restricted to one or several universities or to a country; they can also be international. If expected scope is wide, LOR are based on a network of contributors or on a consortium of institutions. In Europe, the Alliance of Remote Instructional and Distribution Networks for Europe (ARIADNE, 2004) focuses on the share and re-use of hypermedia learning documents. These resources are stored in a “knowledge pool system” and are indexed by metadata based on the LOM (learning object metadata) standard (LOM, 2002). The re-use of these resources can be made by: • •

Creating new materials from pieces of material to which the author can add new elements Making a new presentation of an existing course material obtained by a rearrangement of its semantic components

This implies that each author involved in the knowledge pool experience allows, under citation restrictions, the use and modification of the components he brings in it. Conversely, he can do the same thing with other components.

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ARIADNE has thus interesting selection and access features, but one can notice that an instructional design work remains necessary to re-use the resources. The restriction in resources related to a particular domain brings more homogeneity; resources and associated knowledge can be managed more precisely. Thus, relying on knowledge engineering techniques, Paquette (2001) designed knowledge and resources base on tele-learning. To this end they rely on task ontology, based on use cases, and on a domain ontology that allows them to better index the resources. As in the case of repositories, the idea is also to share and re-use resources. These resources are not ready to be used by learners; an instructional design work is usually needed beforehand. On the contrary, within the MEMORAe project, our goal is to let learners directly access the resources of a course memory. Following a knowledge engineering approach, we organise the resources in an organizational memory. In fact, it is a course memory, where a course is seen as an organization. It can rather be seen as a memory of concepts and resources that teachers or designers find useful in the framework of a particular course. In order to give learners direct access to the memory, part of the instructional design work has to be made earlier. The advantage is that the memory is ready to be used by learners, provided that pedagogical and didactical choices made earlier are acceptable. This can therefore lead to a loss of flexibility, but we make the assumption that these choices can at least be shared by a teacher community that could act as a “community of practice” (Wenger, 1998). In using such a course memory, the learner can access the appropriate learning activities. It can be considered a goal-driven organizational learning.

An Organizational Memory Tool for E-Learning

a learnIng organIzatIonal memory: the project memorae The project MEMORAe was started from two points: •

•

A course unit is based on knowledge and competencies it should provide, on actors (learners, instructors, trainers, course designers, administrators, etc.), and on resources of different types (definitions, exercises with or without solution, case studies, etc.) and different forms (reports, books, Web sites, etc.). In this sense, a course is an organization. An effective organizational memory is a prerequisite for organizational learning (Balasubramanian, 1995). Indeed, both the demonstrability and usability of learning depend on the effectiveness of the organization’s memory.

Within the MEMORAe project, we propose to manage the resources and knowledge of a course by the means of a “learning organizational memory” based on ontologies (Abel et al., 2004).

learning organizational memory/organizational memory A learning organizational memory is different from a classical organizational memory because its goal is to provide pedagogical users with content. This content is the result of two pieces of work: (1) the capitalization of knowledge, information, and resources relating to the training or course unit; (2) a pedagogical work concerning the choice and the organization of this capitalization. The pedagogical content is composed of the notions to learn, the links between these notions, and the resources they index. Notions are not only chosen because they are related to the course unit, they are also the result

of a reflection on the course itself. For example, with NF01, why and how to make a link between the “loop” and “array” notions? Resources have to be selected relying on pedagogical goals. The choice of their indexing terms is related to this goal, too. It is not an automatic indexing. The course manager is responsible for the relevance of the links. It is not because a document treats of a notion to acquire that it will be necessary indexed by this notion. The choice is explicit; that is to say, the document must have been evaluated as sufficiently adapted to the learning of this notion. These choices are part of the pedagogical scenario the course manager wants to implement. In a classical organizational memory, there is no pedagogical scenario because the objective of this kind of memory is not training. The learning organizational memory we propose aims at facilitating knowledge organization and management for a given course or training, and at clarifying competencies it permits acquiring. An organizational memory allows capitalizing not only on learning resources related to the contents of the course but also on information on actors themselves (specificities, background, profile, etc.). Administrative management (registration, notes, etc.) of the course can also be realised. Beyond the pedagogical content, the memory capitalizes: •

•

Any information related to the learning environment that can be useful to users trainers, staffs, entry form, learners, etc. Users’ knowledge

pedagogical content of a learning organizational memory The pedagogical content of a learning organizational memory is mainly composed of the notions to learn, the links relating them, and the resources indexed by them. The manager of a training memory is responsible for its content,

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that is to say, the choice of the notions to learn and the resources indexed by these notions. In this sense, there is no course design (as it can exist in a linear course) but more precisely pedagogical content selection. The only material created is the set of notions, links, and annotations that can accompany them (for instance, why is this concept difficult). Resources are reused as they are.

notion to learn The design of an e-learning application implies focus on the learner, giving him/her the means to be active, to make him/her understand the resources that are at his/her disposal, and to teach him/her how to search and use them. In knowledge engineering, a notion is any entity of thinking; it is used to structure knowledge and the perception of the world. Notions to learn are used as indexes to access documents related to them. A notion to learn can refer to several resources (giving several means to acquire it), and a resource can be referred to by several notions (giving several means to retrieve it). Note that a digital document can be made of several parts that can be themselves indexed. It will, however, remain a document as a whole for which the author has no writing guidelines to follow.

learning resources Learning resources are generally documents: course texts, course notes, slides, e-books, reports, books presentations, and so forth. They may also be anything useful for training (for example, software, links to Web site). Among the represented resources, some (digital resources) are stored in the memory and others are references or description to physical resources. Resources can get accessed according to different rights. They can be private. In this case, users only store them in the memory and do not want to give other users access to them. They can be

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annotations, work in progress, or downloaded and not yet analyzed documents. Resources can also be semi-public or public, that is to say, shared by part or all of the users. For example, an annotation of a reader giving his/her motivated impression on a resource can help memory users choose appropriate resources. Moreover, several annotations written by different authors or relying on different notions can be attached to a same resource. Resources can also have different status. They can be terminated and validated resources, or, on the contrary, working resources created by one or more users and therefore shared by them during the time of their realization.

annotations Our reflection on annotations started from two observations: On one hand, when users of the memory access a notion to learn, there are faced with several resources related to this notion. The choice can be based, as it is presently, on several associated characteristics: author, resource type (book, Web site), but it also could be guided by other information such as comments or remarks on the resources. On the other hand, the role of an organizational memory is to capitalize knowledge. It is then useful to keep track of the reasons that led a course manager to choose a resource, a notion, or a link between two notions. We propose to take into account this information by using annotations. In the MEMORAe project we consider that an annotation: • •

Is a resource, result of an annotation action Is related to a target that can be a notion to learn (concept), a link between concepts, a resource, a part of a resource, a collection of resources

An Organizational Memory Tool for E-Learning

•

•

• •

Has one or several authors and presents its/their comments on the target. These comments are created at a given date with a precise objective and are directed to a precise audience (that can be the author himself in case of a personal annotation) Is not part of the target itself. It is then necessary to make a link between the target and the annotation Makes sense only in its context (target, author, goal, audience) Can be text, graphic, voice, or illustration

Note that a target must have a representation in the memory in order to be annotated. As an annotation is a resource, it can be itself annotated. Following this conception, our notions to learn are not annotations; they are metadata. We will now see how we represent them using ontologies.

the memorae model The MEMORAe model relies on the expected use of the memory: e-learning. We mainly tried to: • •

Determine and present the notions to learn and resources describing these notions Offer a natural and easy access to the memory contents

For this purpose, we were interested, on the one hand, in ontologies to represent the notions to learn and their links (definition of a common vocabulary) and on the other hand in topic maps (XTM, 2001) as representation formalism facilitating navigation and access to the learning resources. The ontology structure is also used to navigate among the concepts, as in a roadmap. The learner has to reach the learning resources that are appropriate for him.

ontologies For navigating through the memory, the end-users (learners, teachers, etc.) need a shared vocabulary and knowledge structured. That is why we decided to model the memory with ontologies. From the different ontology types defined by Van Heijst et al. (1997), generic ontologies, domain ontologies, application ontologies, and meta-ontologies, we only use the second and third categories. We have to consider two aspects for modeling the memory and building ontologies (Breuker & Muntjewerff, 1999). First, the domain of training has its own characteristics. Second, it must be linked to the application domain of a particular training program. The first ontology (domain ontology) we specify describes the concepts of the « training » domain (cf. Figure 1). They can be users’ types (teacher, administrative), document types (book, slides for oral presentation, Web page, site, etc.), and media types (text, image, audio, and video). They can also be pedagogical characteristics (activity type), and they can refer to point of view (annotation). Learning resources are not organized following the way recommended by the learning object metadata standard in the educational category, because we do not agree to associate various activity types, like exercise or simulation, with data representation like a diagram, figure, or graph in the same set. A description of the LOM standard can be found in the document 1484.12.1, http://ltsc.ieee.org/wg12/index.html. The second ontology (application ontology) specifies the organization of theoretical notions that are studied during training session. In the example of B31.1 course, some notions like “set” or “infinite set” are explained. It is possible, but not mandatory, to consider “infinite set” and “finite set” as sub-concepts of the concept “set” and to define the relation “has cardinality” between the concepts “finite set” and “cardinal” (in this case, they are the domain and range value of this relation). According to the Ontospec method (Kassel,

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Figure 1. Elements of domain ontology Resourceaccess

Document Picture

Digital Audio

Person Administrative

Graph Diagram

Video Text Image

Exercise Message Annotation Lecture

Solid Image

Student Technicien Teacher Course NF01 B31.1

Index

CD Paper Slide

Slide show Book

Audiotape Videotape

Figure 2. Specializations of the “set” notion Set Axe 1: cardinality finite/infinite

Set operation Infinite set Axe 1.1: cardinal value

Axe 2: countable/uncountable Axe 3: super/sub

Complement

Finite set Empty set Singleton Pair

Union Intersection Cartesian product

Uncountable set Countable set Superset Subset Strict subset Full subset

2005), concepts can be specialized according to “semantic axes.” For example, the concept “set” is specialized according to three axes: finite/infinite, countable/uncountable, subset/superset (cf. Figure 2).

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These ontologies are not independent; the second one is necessarily attached to the first one. For example, to express that a document is an introduction to “infinite set,” we join the two concepts “introduction” and “infinite set” that

An Organizational Memory Tool for E-Learning

do not belong to the same ontology. Pedagogical relations like “prerequisite” or “uses” that occur between concepts of the application ontology are defined in the domain ontology. However, specific roles can belong to the application ontology (for example, for the B31.1 application, “has-cardinality”).

topic maps The modeling of a training memory, which is presented here, contains three elements: two ontological parts and the way to index documents on them. The modeling must at least allow three operations: • •

•

The reunion of two ontologies: the generic one and the application one; The substitution of an application ontology by another one coming from another domain; The attachment of document indexing on the reunion of two ontologies.

The modeling must also favour the answering to queries on the memory like: •

•

What are the documents (books, presentations, Web pages) that talk about, introduce, and develop a notion that appears in the training? What are the notions associated (pre-requisite, studied in the same time…) with a given notion?

The Choice of the Topics Maps Formalism The choice of the formalism(s) for representing the memory is very decisive. It must go beyond the hybrid aspect of the modeling (ontology and indexing) and favour the interoperability between various tools that have to deal with the memory

(edition, updater, consultation, navigation, etc.). Two paths can be followed: either to choose the languages better adapted to the specific nature of each element of the modeling or to choose a unique language. The first choice requires a system to easily integrate data coming from the two formalisms. The advantage of the second choice is to unify the description of data. It can be valid only if this formalism allows describing some features that it is not worded for. The second choice can be split into two parts: We can choose a formalism adapted to ontology features representation or a formalism adapted to document indexing. The main aspect of the memory and its main use influence the choice of the formalism. Even if the indexing of the learning documents is the main aspect of the memory, it is necessary to use a formalism allowing representation of ontological elements. Several formalisms can be envisaged, but we recommend the topic maps (TM) formalism (IEC, 1999). This formalism is useful to define and manipulate the information attached to resources. That provides a logical organization a large quantity of resources, keeping them accessible and facilitating the navigation between them. Since 2001, it has been possible to write a TM using the norm XTM 1.0 (XTM 2001) that can be considered a particular extensible markup language (XML). The building of a TM is based on an organization of topics. Each resource is directly attached to one or more topics by an “occurrence link.” The « Association » concept allows defined roles between topics. Moreover, the TM standard allows reifying some associations in order to place them in a particular “scope.” Some resources can also be reified as a topic when it is necessary to attach other resources or data on them. In this manner, we can add annotations to resources. Annotations are resources that express a point of view on other resources. Overall, we chose the TM formalism because it keeps a semantic level close enough to the

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model of our memory. With an ontology-oriented point of view, also developed in (Park, 2002), this formalism allows envisaging the important following characteristics: •

•

• •

•

It is possible to consider some topics as generic concepts and other as concept instances. It is possible to consider associations, scopes, and occurrences as roles between concept topics. Associations have no limitation in their member number. The occurrence relation allows to directly attach resources to concepts (the same resource can appear in several occurrence relations and be accessible from more than one concept). Relations (associations, occurrence) and concept labels can be defined inside scopes. This allows simply implementing annotations (or points of view in the memory).

To definitely adopt this formalism, we verified it was possible to take into account ontological features, mainly the relation superclass-subclass for building hierarchies of concepts.

An Example Let’s consider the notion finite set; its definition is « a finite set is a set which has a cardinal ». It is represented by: • •

three topics: finite set, set, cardinal Two associat ions: superclass-sub class (subsumption link between “finite set” and “set”), possess.

The notion “finite set” is treated on the Web site http://www.planete-maths.com/html/. Figure 3 presents the XTM syntax of the topics map formalism corresponding to this sentence.

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the envIronment e-memorae With the organizational environment E-MEMORAe (Abel, Benayache, Lenne, & Moulin, 2006), resources can be reached by navigating through a graphical display of the ontologies on which it relies. It integrates tools to facilitate autonomous learning. We present this environment by using examples coming from the B31.1 application.

the user Interface E-MEMORAe aims at helping the users of the memory acquire the notions of a given course. To this end, the users have to navigate through the application ontology that is related to the course and access the indexed resources thanks to this ontology. The general principle is to propose to the learner, at each step, either precise information on what he is searching for or graphically displayed links that allow him to continue navigating through the memory. He has no need to use the keyboard in order to formulate a request, even if it is possible through the environment. To be more precise, the user interface (cf. Figure 4) proposes: •

•

Entry points (left of the screen) allowing one to start the navigation with a given concept: An entry point provides a direct access to a concept of the memory and, consequently, to the part of the memory dedicated to notions. The person who is in charge of the course has to define the notions that (s)he considers as essential. Resources (bottom of the screen), the contents of which are related to the current concept: They are ordered by type (books, course notes, sites, examples, comments, etc.). Starting from a notion, an entry point, or a notion reached by the means of the ontology, the user can directly access associated

An Organizational Memory Tool for E-Learning

Figure 3. Extrait XTM d’une topic map 1.

2.

………

3.

4.

5.

6.

7.

8.

Ensemble fini

9. 10.

11.

12.

13.

14.

15.

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17.

18.

19.



20. 21.

22.

cardinal

23. 24.

25.

26.

27.

28.

29.

30.

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32.

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36.

37.

38.

39.

40.

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………

44.

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Figure 4. Vertical navigation in the memory

•

•

•

resources. Descriptions of these resources help the user to choose among them. A short definition of the current notion: The learner has a preview of the notion; he can decide if (s)he has to work it or not. A history of the navigation: The learner can remind and be aware of the path (s)he followed before. Of course, (s)he can get back to a previously studied notion if (s)he wants to. Least but not last, the part of the ontology describing the current resource is displayed at the centre of the screen.

If the learner wants access to a notion that is not an entry point, he or she has to choose the entry point that he or she thinks is the closest point from the searched notion.

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learning by exploration through the memory Vertical navigation allows exploration of subsumption relations and related concepts. For example, if the user wants to discover the “finite set” notion, the best entry point is “set (population).” By choosing this entry point, (s)he has access to the local taxonomy associated with the notion of set. Among the sub-concepts of “set,” (s)he can find “finite set.” By clicking on this concept, a local taxonomy centred on this new concept is displayed (cf. Figure 4). Thus the learner can browse the ontology using its taxonomic form. Some presentation rules are used in order to help the user visually explore this hierarchical organization: The current concept C is at the centre of the screen; all the sub-concepts of C that

An Organizational Memory Tool for E-Learning

represent more specific notions are presented; at last, the super-concept of C, which represents a more general notion, is also presented. We did not find it useful to extend this representation. Our goal was to keep it understandable. To end with the hierarchical navigation, let us finally note that the representation uses semantic axes. In order to visualize them, we used different colours for each of these axes. At this stage, their meaning is not explicit. Let us suppose now that the learner decides to temporarily stop the navigation and focus on a particular concept. This concept is at first described by a short definition. If the user wants to learn more on the selected notion, (s)he has access to a list of resources ordered by type. For example, Figure 4 shows that if the user wants to deepen the notion of “Finite Set”, (s)he can select among the associated resources—for example, a book entitled “Mathematics for Computer Science”—by left-clicking on the name of this resource. A description text is then displayed in a new window (cf. Figure 5). Other bibliographic information such as ISBN number, authors, pub-

lisher, and so forth are also available. When the resource is digital, it can be displayed or sent to someone by e-mail. A concept can refer to concepts other than those that are displayed in the taxonomy. Access to these concepts is sometimes needed in order to understand some notions. Proximity relations (other than subsumption) are useful for that. Examples of these relations are: prerequisite-of, in-the-definition-of, suggests, and so forth. Other application-specific relations such as subset-of, has-cardinal, and so forth can also be considered. We call this kind of navigation “horizontal navigation,” in comparison with the “vertical navigation” that we considered before. These relations are accessed by right-clicking on the source concept C; a popup menu contextually displays the available relations starting from C. Let us consider one more time the case of the finite set concept (cf. Figure 4). Among the available horizontal relations, the learner can choose, for example, “prerequisite-of” and learn more about prerequisite notions such as “countable set” or “cardinal” (cf. Figure 6).

Figure 5. A book resource

Display the resource

Send

Print the information

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Choosing the “countable set” concept in the list of the prerequisite concepts of “finite set” allows switching back to a vertical navigation centred on this new concept of “countable set.” Finally, one can see that the navigation through the application ontology is made very easy by combining vertical (left-click) and horizontal (right-click) moves. After each exploration action made by the learner, the history (cf. Figures 4 and 6, right frame) is actualized. This history keeps track of the path followed by the user during his (her)

Figure 6. Horizontal navigation

Figure 7. Searching the « finite set » notion

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exploration. Of course, it is possible to go back to a previously visited notion by clicking on it in the history.

learning by Querying the memory We have seen in the previous section how to access the contents of the memory by navigation (“consult menu”). It is also possible to directly access a notion by querying the memory (“Search menu”). This interface allows searching for a word in the textual data contained in the memory. The

An Organizational Memory Tool for E-Learning

word can be all or a part of an author, notion, or resource name, or it can be included in the textual description of the notion, and so forth. For example, Figure 7 shows the search results for the “set” word. When choosing a notion in the search results, the user has access to the part of the taxonomy related to this notion. He or she can continue to explore the memory horizontally or vertically (cf. learning by exploration through the memory).

conclusIon

archItecture The architecture of the E-MEMORAe environment is a three-tier architecture: PHP/MySQL, Appach, and JavaScript/HTML+SVG. This type of architecture separates the application in three levels of distinct services: presentation, treatment, and storage. Figure 8 shows the functional architecture of the E-MEMORAe environment: one can indeed find a storage part (MySql data base), a treatment part (Topic Maps modeling, etc.), and an information presentation part. The MEMORAe web site is accessible at the following URL: http://www.hds.utc. fr/~ememorae/Site-MEMORAe/.

We presented in this chapter a goal-driven organizational approach to facilitate the search for appropriate resources to acquire new competencies. Indeed, numerous resources may be used during e-learning. Their access is a real problem. E-learning becomes part of a complex organizational conduct. Learners have to access the right resources at the right time. This kind of problem is a problem of knowledge management, and we propose to achieve it in using the concept of learning organizational memory based on ontologies. This memory is different from a classical organizational memory because its goal is to provide pedagogical users with content. This content is the result of two pieces of work: (1) the capitalization of knowledge, information, and resources relating to the learning context (for example, a training); (2) a pedagogical work concerning the choice and the organization of this capitalization. The opposite of the approach that is generally adopted with learning objects repositories or thematic resources bases, this course memory is bound to be directly used by learners. This implies doing an earlier part of the instructional design work. Let us note, however, that this approach is

Figure 8. Functional architecture of the E-MEMORAe environment PRESENTATION XTM file (import)

PROCESSING

STORAGE

JavaScript menu Topic maps

MEMORAe Web Site

XTM File (export)

HTML pages SVG graph PHP/SQL codes

BD conversion PHP/SQL conversion XTM conversion

MySQL

DB

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only feasible with learners having self-regulating abilities. The E-MEMORAe environment we developed is based on the use of ontologies and topic maps. It is used as a support for e-learning. The objective is to help users understand the notions starting from resources selected by teachers. The indexing of the documents is supplemented by pedagogical criteria that help the learner appreciate his or her relevance. We think that using such a memory enhances the activity and the autonomy of the learner. We made a first evaluation of E-MEMORAe with students in the framework of the B31.1 mathematics training at the University of Picardy in France and of the NF01 algorithms training at the University of Compiègne. Our objective was to see how learners could discover alone new notions to learn through E-MEMORAe. In order to assess the understanding of these notions, the learners had to solve some problems related to the notions in a given time. In the two cases, we obtained encouraging results: the majority of students solved the problem and accessed to the right notions (seen in the recorded history). After presenting our prototype to our colleagues, we have received different demands to use E-MEMORAe. We plan to assess E-MEMORAe according to the teachers’ point of view. Currently we are working on the extension of E-MEMORAe in order to assess such a memory for collaborative learning, computer support for collaborative learning (Stahl, 2002). We also search partners from industry to test E-MEMORAe in an organizational learning context.

references Abecker, & Decker. (1999). Organisational memory: Knowledge acquisition, integration, and retrieval issues. In F. Pope (Ed.), Knowledge

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based systems, survey and future directions. In Proceedings of the 5th German Conference on Knowledge Based Systems, Lectures Notes in Artificial (LNAI), (Vol. 1570). Springer-Verlag. Abel, M. H., Barry, C., Benayache, A., Chaput, B., Lenne, D., & Moulin, C. (2004). Ontologybased organizational memory for e-learning. Educational Technology & Society Journal, 7(4), 98-111. Abel, M. H., Benayache, A., Lenne, D., & Moulin, C. (2006). E-MEMORAe: A content-oriented environment for e-learning. In S. Pierre (Ed.), E-learning networked environments and Architectures: A Knowledge processing perspective (pp. 186-205). Springer Book. Alliance of Remote Instructional and Distribution Networks for Europe (ARIADNE). (2004). Alliance of remote instructional and distribution networks for Europe 2004. Balasubramanian, V. (1995, May). Organizational learning and information. ISWorld Net. Retrieved from http://www.e-papyrus.com/personal/orglrn. html Baugh, J. (1997, Spring). Rewarding competencies in flatter organizations. Competency: The Journal of Performance through People, 4(3). Breuker, J., & Muntjewerff, A. (1999, July 18-19). Ontological Modelling for Designing Educational Systems. In Proceedings of The Workshop on Ontologies for Intelligent Educational Systems, Ninth International Conference on Artificial Intelligence in Education, AI-ED’99, Le Mans, France Chandrasekaran, B., Josephson, J. R., & Benjamins, R. (1998, April 23). The ontology of tasks and methods. In Proceedings of KAW’98, Eleventh Workshop on Knowledge Acquisition, Modeling and Management Voyager Inn, Banff, Alberta, Canada. Conklin, E. (1996). Designing organizational memory: Preserving intellectual assets in a

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Martin, P. (1993). Scholarly Web sites as organisational memory system. Retrieved from http:// www.cs.nott.ac.uk/~hla/HTF/HTFVII/Martin. htm#Conklin%201993

Guarino, N., & Giaretta, P. (1995). Ontologies and knowledge bases, towards a terminological clarification. In E. N. Mars (Ed.), Towards very large knowledge bases: knowledge building and knowledge sharing (pp. 25-32). ISO Press. Gruber, T. (1993). A Translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), 199-220. Harzallah, M., Leclère, M., & Trichet, F. (2002). In Proceedings of Fourteenth International Conference on Software Engineering and Knowledge Engineering (SEKE’02), Ischia, Italy. Harzallah, M., & Vernadat, F. (2002). IT-based competency modeling and management: From theory to practice. Enterprise Engineering and Operations, Computers in Industry, 48(2), 157179. International Electronical Commission (IEC). (1999, April 19). International organisation for standardization (ISO). Topic map (International Standard ISO/IEC 13250). Kassel, G. (2005). Integration of the DOLCE toplevel ontology into the OntoSpec methodology. https://hal.ccsd.cnrs.fr/ccsd-00012203 Klemke, R. (2000, October 30-31). Context framework: An open approach to enhance organisational memory systems with context modelling techniques. In Proceedings of PAKM2000: Third International Conference on Practical Aspects of Knowledge Management, Basel, Switzerland.

Paquette, G. (2001). Telelearning systems engineering: Towards a new ISD model. Journal of Structural Learning and Intelligent Systems, 14(4), 319-154. Park, J. (2002). XML topic maps, creating and using topic maps for the Web. Jack Park Editor 2002. Rabarijaona, A., Dieng, R., Corby O., & Ouaddari, R. (2000). Building a XML-based corporate memory [Special issue]. IEEE Intelligent Systems, 56-64. Sicilia, M. A. (2005). Ontology-based competency management: Infrastructures for the knowledgeintensive learning organization. In M. D. Lytras & A. Naeve (Eds.), Intelligent learning infrastructures in knowledge intensive organizations: A Semantic Web perspective (pp. 302-324). Hershey, PA: Idea Group Inc. Sowa, J. F. (2003). Ontology. Retrieved from http://www.jfsowa.com/ontology/ Stahl, G. (Ed.) (2002). Computer support for collaborative learning: Foundations for a CSCL community. In Proceeding of CSCL 2002, Boulder, Colorado. Steels, L. (1993). Corporate knowledge management. In Proceedings of the International Symposium on the Management of Industrial and Corporate Knowledge (ISMICK’93) (pp. 9-30). Van Heijst, G. (1997, September). Knowledge infrastructures: Re-engineering for learning. In Proceedings of Workshop on Knowledge-Based Systems for Knowledge Management in Enter-

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prises, The 21st Annual German Conference on AI ’97, Freiburg, Germany. Retrieved from http://www.dfki.uni-kl.de/~aabecker/Freiburg/ Heijst/index.htm Van Heijst, G., Schreiber, A., & Wielinga, B. (1997). Using explicit ontologies in KBS development. International Journal of Human-Computer Studies, 46, 183-298.

XTM. (2001, 3 March). TopicMaps.org XTM authoring group, XML Topic Maps (XTM) (1.0): TopicMaps.org Specification. Wenger, E. (1998). Communities of practice. Learning, meaning and identity. Learning in doing: social, cognitive, computational perspectives. Cambridge, MA: Cambridge University Press. Wooddruff, C. (1991). Competent by any other name. People Management Journal.

This work was previously published in Competencies in Organizational E-Learning: Concepts and Tools, edited by M.A. Sicilia, pp. 146-168, copyright 2007 by Information Science Publishing (an imprint of IGI Global).

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Section 4

Utilization and Application of Online and Distance Learning This section discusses a variety of applications and opportunities available that can be considered by practicing educators in developing viable and effective distance learning educational programs. This section includes more than 40 chapters which incorporate applications of distance learning into institutions within the educational system as well as application of online learning in the corporate realm. Contributions included in this section also provide excellent coverage of today’s global community and how distance learning technologies and education are impacting the social fabric of our present-day global village.

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Chapter 4.1

Role Adjustment for Learners in an Online Community of Inquiry: Identifying the Challenges of Incoming Online Learners Martha Cleveland-Innes Athabasca University, Canada Randy Garrison University of Calgary, Canada Ellen Kinsel Odyssey Learning Systems, Canada

AbstrAct This study outlines the process of adjustment learners experience when first participating in an online environment. Findings from a pilot study of adjustment to online learning environments validate differences found in three presences in an online community of inquiry. Using pre- and post-questionnaires, students enrolled in entrylevel courses in two graduate degree programs at Athabasca University, Canada, describe their adjustment to online learning. Responses were analyzed in relation to the elements of cognitive,

social, and teaching presence, defined by Garrison, Anderson, and Archer (2000) as core dimensions of student role requirements in an online community of inquiry. In each of these presences, five areas of adjustment characterize the move toward competence in online learning: interaction, self-identity, instructor role, course design, and technology. Student comments provide understanding of the experience of first time online learners, including the challenges, interventions, and resolutions that present themselves as unique incidents. Recommendations for the support and facilitation of adjustment are made.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Role Adjustment for Learners in an Online Community of Inquiry

IntroductIon The move to online delivery in postsecondary education institutions has increased exponentially over the last decade. Early concerns were raised about the extent to which students would embrace online education. However, recent evaluation of student enrolment in online courses indicates much willingness to engage; optimistic online enrolment projections are now a reality and there are implications that growth will continue. “Online enrolments continue to grow at rates faster than for the overall student body, and schools expect the rate of growth to further increase” (Allen & Seaman, 2004, Introduction, 3rd para.). As growth continues, more and more students will experience online education. Students will have to develop new skills required to be competent online learners, and will modify behaviours from classroom learning to fit the online environment. The details of this adjustment process for students to this new delivery method are still underexplored; “there is also (sic) a need for better understanding of students’ adaptation to online learning over time” (Wilson, Varnhagen, Krupa, Kasprzak, Hunting, & Taylor, 2003). Adaptation to the role of online learner can be understood by looking at the structure of the online pedagogical environment, or community of inquiry (Garrison, Anderson, & Archer, 2000) and tenets of role theory (Blau & Goodman, 1995) and how role change occurs (Turner, 1990). The integration of new behaviours into one’s role repertoire (Kopp, 2000) occurs in a context (Katz & Kahn, 1978) and through an intricate process of role taking, role exploration, and role making (Blau & Goodman, 1995). As the context of teaching and learning in online environments is very different from long standing classroom structure, and will act as a catalyst for role adjustment for individual students moving online. This article outlines the character of adjustment made by such students, determined from a study of novice online learners. Students responded to

open-ended questions before and after (pre and post) their first online experience; responses were coded and categorized according to adjustment to cognitive, social, and teaching presence. With each of the presences, responses formed a pattern around activities and outcomes in the following thematic areas: interaction, instructor role, selfidentity, course design, and technology. In addition, a process of meeting challenges presented by this new environment is outlined. This data provide understanding of the experience of first time online learners. Recommendations are made for incorporating this understanding into instructional design and facilitation in order to ease adjustment for students new to the online environment.

LIterAture revIew online community of Inquiry The community of inquiry model, originally proposed by Garrison, Anderson, and Archer (2000), served as the conceptual framework around which to study online learning and learner adjustment. The theoretical foundation of this framework is based upon the work of John Dewey (1938). At the core of Dewey’s philosophy are collaboration, free intercourse, and the juxtaposition of the subjective and shared worlds. This is the essence of a community of inquiry. Consistent with his philosophy of pragmatism, Dewey (1933) viewed inquiry as a practical endeavour. Inquiry emerged from practice and shaped practice. Dewey’s work on reflective thinking and inquiry provided the inspiration for operationalizing cognitive presence and purposeful learning in the community of inquiry framework (Garrison & Archer, 2000). The other elements of the community of inquiry model, social presence, and teaching presence were derived from other educational sources, but are consistent with Dewey’s philosophy and the

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Role Adjustment for Learners in an Online Community of Inquiry

framework of a community of inquiry (Garrison & Anderson, 2003). The community of inquiry framework has attracted considerable attention in higher education research. In particular, it has framed many studies of online learning. This speaks to both the importance of community in higher education as well as the usefulness of the framework and how the elements are operationalized. Moreover, the structural validity of the framework has been tested and confirmed through factor analysis (Arbaugh & Hwang, 2006; Garrison, ClevelandInnes, & Fung, 2004). A review of the research using the framework and the identification of current research issues is provided by Garrison (2006). An online community of inquiry, replete with interaction opportunities in several places of “presence” (Garrison & Anderson, 2003) provides a supportive context for the redevelopment of the role of learner. The relationship among these dimensions is depicted in Figure 1. These are the core elements in an educational experience and key to understanding role adjustment. Cognitive, social, and teaching presences represent

the primary dimensions of role in an educational context; it has a character of its own in an online environment. Changes in cognitive, social, and teaching presence, as a result of a new context and communication medium, will necessitate role adjustments by the learners. Cognitive presence is defined “as the extent to which learners are able to construct and confirm meaning through sustained reflection and discourse” (Garrison, Anderson & Archer, 2001, p. 11). Role adjustment here reflects the nature of the communication medium: spontaneous, verbal communication is supplanted by a reflective, textbased medium. This represents a radical departure from classroom interaction. A more precise and recorded form of communication, the text-based medium has the potential to support deep and meaningful learning outcomes. Social presence is defined as “the ability of participants in a community of inquiry to project themselves socially and emotionally … through the medium of communication” (Garrison, Anderson, & Archer, 2000, p. 94). The challenge of asynchronous written communication is the lack of nonverbal cues. Since the educational experience

Figure 1.

Community of Inquiry

SOCIAL PRESENCE

Supporting Discourse

COGNITIVE PRESENCE

EDUCATIONAL EXPERIENCE Selecting Content

TEACHING PRESENCE (Stucture/Process)

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is a social transaction, special consideration must be given to the social interactions and climate. Social presence represents a major role adjustment in moving from a real-time face-to-face classroom experience to a virtual community. Teaching presence is defined as “the design, facilitation and direction of cognitive and social processes for the purpose of realizing personally meaningful and educationally worthwhile learning outcomes” (Anderson, Rourke, Garrison, & Archer, 2001). It is what binds all the elements together in a purposeful community of inquiry. The properties of the online community also necessitate significant design changes and role adjustment for the teacher. Teaching presence must recognize and utilize the unique features of the medium and structure and model appropriate learning activities. This translates into an experience and role that may not be at all familiar to the learner.

role Adjustment “Role” is used here as a sociological construct, defined as a collection of behavioral requirements associated with a certain social position in a group, organization, or society (Kendall, Murray, & Linden, 2000). At its most general level, role expectations are dictated by the social structure. Individuals who engage in the role are guided, through a process of socialization, to appropriate role performance. Socialization then refers to the “process by which people learn the characteristics of their group … (and) the attitudes, values and actions thought appropriate for them” (Kanwar & Swenson, 2000, p. 397). Under conditions of long-standing roles, individuals engage in “role-taking” behavior, where observation and mimicry of role models allow those new to the role to “practice” appropriate role behaviors. “Role making” occurs as individuals construct aspects of the role with their own individual meanings and satisfying behaviors attached. This occurs under social conditions where

such individual autonomy is allowed. It also occurs where role models are not readily available, and construction of the role is required. Such is the case for becoming an online learner. An adjustment from the more generalized role of learner, the responsibilities and requirements of working online are not readily apparent to those new to the role. The transition to, and adjustment in, the role of online learner, is part of the current social climate in online learning. While maintaining the usual expectations and privileges attached to the role of learner, online learners add such things as: • •

• •

knowledge about, skill with, and acceptance of the technology; new amounts and modes of communication with instructors, peers, and administrators; increased levels of learner self-direction; and a new “place” for learning in time (anytime, usually determined by the learner and their life circumstances) and space (anywhere, dependent upon equipment requirements).

An online community of inquiry is a distinct personal and public search for meaning and understanding. New roles are necessitated in an online community by the nature of the communication that compels students to assume greater responsibility for and control over their learning. As McLuhan observed, “each form of transport not only carries, but translates and transforms the sender, the receiver and the message” (McLuhan, 1995, p. 90). An asynchronous and collaborative learning community necessitates the adoption of personal responsibility and shared control. This goes to the heart of an online learning community and represents a significant shift from the information transmission of the lecture hall and the passive role of students. Thus, online learning communities demand role adjustments. This

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Role Adjustment for Learners in an Online Community of Inquiry

brings another need: to understand changes in responsibilities and roles. Differences in the required activities of online learning, in comparison to classroom based faceto-face, result in new, required expectations and behaviors for learners. These new activities cluster into a pattern that is seen as the “role” of online learner. The term role refers to the expected and generally accepted ways of behaving, acting, and interacting (Knuttila, 2002). Taking on a role (e.g., teacher, mother, learner) involves learning what the expected behaviors are through a process of observation and trial and error attempts at the role (Collier, 2001). While the adoption and enactment of social roles is a standard, commonplace element of everyday experience, becoming an online learner has a unique characteristic. For many learners, role models for learning the required and expected activities are not present until one is already engaged in an online course (Garrison & Cleveland-Innes, 2003). Role acquisition is part of individuation in the experience of working online. Each online learner engages in the experience of learning online and the process of role taking and role making occurs concurrently within the learning experience. From the perspective of the individual, learning online requires the development of competencies in the role of “online learner.” As a new social role, the pathway to competence will occur over time as the role becomes prevalent and normalized. In this early stage, online communities will contribute to the socialization process for those engaging in this new role. The result is a new role and a new identity for learners.

MethodoLogy sample Students participating in this study were enrolled in two graduate programs at Athabasca University. Students came from 19 distinct course groups

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over four terms. 217 students from core courses normally taken early in each program, courses purposively selected in order to include the greatest number of novice online learners, agreed to participate. Of the 217 students consenting to participate, 150 returned both questionnaires, 33% male and 58% female (9% did not indicate gender). Respondents indicated their age as follows: 20-29 years—10%, 30-39 years—24%, 40-49 years—43%, 50+ years—23%. All courses were delivered using a combination of print and electronic media and online conferencing. The online conferencing component provided the opportunity for student engagement and group interaction. Required conference participation was used for assessment in some courses while it remained a voluntary activity in others.

data collection This study used a previously validated instrument (Garrison, Cleveland-Innes, & Fung, 2004) to measure the extent of student identification with the behaviours, expectations, and requirements of the role of online learner. Identical questionnaires were sent by email during the first two weeks of each term and again during the final two weeks of each term. The questionnaire collected both quantitative and qualitative data. Quantitative data were generated from 28 Likert-type scaled responses to statements derived from the community of inquiry model. After the scaled items, seven open-ended questions about the adjustment to online learning were presented. These questions were written and pretested with a select sample of students and faculty familiar with online learning. This qualitative data were analyzed and summarized in relation to the adjustment process to the role of online learner, and is the evidence used for this discussion. 46% of the participants reported this as their first experience in an online learning environment (n = 73). This group is the focus for this article, as the other respondents would have experienced

Role Adjustment for Learners in an Online Community of Inquiry

their primary adjustment to online learning in previous courses. Written, detailed responses were gathered from open-ended questions related to activities and outcomes, becoming part of the online learning community, and the design and facilitation of online learning.

data Analysis The constant comparison method was used to code responses to questions; open, axial, and confirmatory coding progression was employed. Five themes emerged from this process: interaction, instructor role, self-identity, course design, and technology. Definitions of these constructs are outlined next.

Interaction Respondents identified issues such as quality, quantity, and value of dialogue with classmates and instructors, often comparing it to interaction in the face-to-face learning environment and describing their transition from verbal to written communication.

Instructor Role Respondents commented on the visibility of the instructor in the conference forums, the quantity, quality, and timing of feedback.

Self-Identity Respondents showed evidence of reflection on self-concept, learning style, personal needs, and increasing responsibility and ownership for learning.

Course Design Respondents commented on the effectiveness of course structure and delivery and the availability of institutional support.

Technology Respondents pointed out technology issues that may inhibit their participation in the community of inquiry and slow their adjustment to the role of online learner.

FIndIngs The purpose of this study was to assess the experiences of first-time online learners and their perceptions of the adjustment to online learning. Their responses to the open-ended questions reflect varying aspects of adjustment clustering around the emergent themes of interaction, instructor role, self-identity, course design, and technology. These themes are explored in relation to cognitive, social, and teaching presence in the online environment.

cognitive Presence Table 1 provides sample comments from first time online learners regarding adjustments in cognitive presence in an online community of inquiry specific to each of the themes (numbers indicate respondent ID codes). Learners voiced concern regarding their adjustment to contributing to online content discussions that lack the visual cues available in face-to-face interaction. Some mentioned their fear of being misunderstood or saying something wrong. First time online learners also reported an adjustment to assuming more responsibility for their own understanding of the material without direct instruction from the professors. Concern was voiced that without more direction from the instructor, it became necessary to rely on fellow students for interpretation, and this could lead to uncertainty or dissatisfaction with learning outcomes. Several learners commented that their participation in online discussions was greater than in a traditional classroom where they were often shy and reluctant to speak

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Table 1. Adjustment in cognitive presence Interaction

At first, I hesitated in fear of saying something wrong (similar feelings in F2F situations as well). However, after receiving feedback from other colleagues, the online conference engagements became enjoyable and valuable from a learning outcome perspective. (#195)

Instructor Role

I have found that it is more difficult to be sure that you understand the material in the online learning because there is little discussion with the professor. The professor seems to set up the lecture and then let us talk amongst ourselves with no interaction to let us know if we are on the right track. (#331)

Self-Identity

I feel that I don’t have as much to offer as others, either because I have had a more limited scope of learning or life experiences or because I can be intimidated by huge thoughts from bright people. (#250)

Course Design

Gaining equal participation and a common understanding in group work was a challenge. At the same time, it led to bonding between some group members. Group assignments early in the class helped to get us started quickly. (#335)

Technology

I like asking questions, but I rarely do on-line. I like clarifying things, but I rarely do on-line. I like to participate in class, but I’m a slow typist, so I rarely do on-line. (#390)

Table 2. Adjustment in social presence Interaction

I did notice my emotional, social ability to communicate became easier and I felt more relaxed as the course progressed. (#197)

Instructor Role

The only aspect (once again) that I found challenging was that I didn’t really feel that I got a sense of ‘knowing’ the instructor, nor did he really get to ‘know’ me. (#421)

Self-identity

I find that I am much more open and interactive on-line than I am in person… I am not able to “hide in the corner” as I could in a live class. (#58)

Course Design

I found the use of small working groups to be a positive way of getting people to interact with one another, allowing me to project myself as a “real” person ... . It may be tougher to do this in the context of the larger class (i.e. those in other working groups.) One does not have the same degree of back and forth “organizational” communication with these other people. I think I may be less of a three dimensional person to these other people. (#284)

Technology

Not ever having learned how to type may also be a factor as I [consider it] to be a handicap the same way someone who has difficulty expressing themselves verbally would. (#37)

up, while others reported a feeling of intimidation when they perceived that classmates had a greater understanding of the concepts or dominated the forum discussions.

social Presence In terms of social presence, first time online learners expressed a need for time to feel comfortable communicating in a text only environment and to adjust to expressing emotion and communicating openly in an environment that lacks visual or other nontextual cues that provide context to

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communications in a face-to-face setting. Some appreciated opportunities to connect with one or a few other learners in a small group activity while others found this difficult to manage, particularly when one group member was dominant in the group. One learner expressed concern that “This mode of learning, however convenient for my schedule, is dehumanizing the learning process for me, and I’m not sure I’m happy with that” (#279). Sample comments on adjustment in social presence in an online community of inquiry are shown in Table 2.

Role Adjustment for Learners in an Online Community of Inquiry

teaching Presence Table 3 includes sample comments from first time online learners regarding their adjustment to a changed teaching presence from past experience in face-to-face learning environments. Many indicated that a more visible teaching presence at the very beginning is desired to ease the adjustment from traditional learning environments to the online environment where the instructor is more of a facilitator and guide. Some reported that they adjusted by assuming more responsibility for their own learning outcomes while others expressed concern that the students were left to discuss content on their own without assistance from the instructor to let them know if they were on the right track. All three types of presence addressed in the online community of inquiry model are evident in the responses from new online learners. Adjustments were demonstrated in the identification of things that were unexpected or new, and the response to that newness. Five components of the online environment emerged as themes in the adjustment process, separately for all three presences. Performing the first analysis, an interesting pattern was noted in the data. Respondents

provided enough detail to demonstrate the process of adjustment in some answers. A second analysis was performed, using pre-identified codes of challenge, intervention, and resolution. This coding structure identified any challenges reported in each presence, the intervening action on the part of student or others, and the result that followed. Constant comparison, with interrater confirmation, was employed as a process. Specific challenges and the resolution of these challenges provide another window on the adjustment process. Challenges are identified as those things students find difficult, uncomfortable, or in any way problematic regarding the online learning environment. Interventions are any occurrence that ensued after the challenge, either deliberately or incidentally. Resolution refers to what the students describe as happening after. In some cases, the result was a positive one. In other cases, what happened resulted in an unsatisfactory outcome. Table 4 provides examples of the adjustment process, by presence.

dIscussIon It is clear that an adjustment is taking place for students engaging in online learning, and that

Table 3. Adjustment to teaching presence Interaction

Once we were comfortable with his role as more of a guide and facilitator than an omnipresent being, we were able to take more ownership for our role in the program and for our own investment in the course. (#407)

Instructor Role

I’m certain that [the professor] reviewed the discussion threads regularly but he seemed more like the virtual “fly on the wall” than an active participant. (#204)

Self-identity

I personally felt that a little more input and guidance from the instructor might have removed some anxiety and stimulated some interaction on my part. (#197)

Course Design

I think the instructor needs to be a very active participant at the beginning of the course. Everyone seems eager to talk to each other at the beginning (how many times did I log in on the first day to see if there was anything new?), and the instructor should tap into that by starting to focus that energy on the content. (#211)

Technology

Most emails sent by my instructor disappeared and I did not know what I had to do. (#146)

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Table 4. Adjustment process by presence Challenge At first, I hesitated in fear of saying something wrong I have found that it is more difficult to be sure that you understand the material online …

Cognitive Presence

I feel that I don’t have as much to offer as others, either because I have had a more limited scope of learning or life experiences or because I can be intimidated by huge thoughts from bright people. (#250) Gaining equal participation and a common understanding in group work was a challenge … I like asking questions, I like clarifying things, I like to participate in class, but I’m a slow typist My emotional, social and ability to communicate

Social Presence

Intervention … after receiving feedback from other colleagues …

… the professor seems to set up the lecture and then let us talk amongst ourselves …

... led to bonding between some group members … … so I rarely do on-line. (#390)

Teaching presence

(such that) group assignments early in the class helped to get us started quickly. (#335)

… I find that I am much more open and interactive on-line than I am in person. (#58) Small working groups to be a positive way of getting people to interact with one another …

was something we had to get more comfortable with

a little more input and guidance from the instructor

Most emails sent by my instructor disappeared.

… with no interaction to let us know if we are on the right track. (#331)

... became easier and I felt more relaxed (#197)

I am not able to “hide in the corner” as I could in a live class.

Instructor role as more of a guide and facilitator than an omni-present being

… online conference engagements became enjoyable and valuable from a learning outcome perspective. (#195)

as the course progressed

The only aspect (once again) that I found challenging was that I didn’t really feel that I got a sense of “knowing” the instructor, nor did he really get to ‘know’ me. (#421)

Not ever having learned how to type may also be a factor as I [consider it] to be a handicap the same way someone who has difficulty expressing themselves verbally would. (#37)

Result

I think the instructor needs to be a very active participant at the beginning of the course.

allowing me to project myself as a “real” person. (#284)

Once we were, we were able to take more ownership for our role in the program and for our own investment in the course. (#407) might have removed some anxiety and stimulated some interaction on my part. (#197) Everyone seems eager to talk to each other at the beginning (how many times did I log in on the first day to see if there was anything new?), and the instructor should tap into that by starting to focus that energy on the content. (#211) I did not know what I had to do. (#146)

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students can articulate the processes of this adjustment when asked. Using the community of inquiry model provided a valuable heuristic device for organizing the character of this adjustment. In each element of presence, the same five themes identified areas where change is taking place. Evident in student descriptions of their experience is a unique orientation to five thematic areas, which together embody the experience of being an online learner. These five thematic areas do not act in isolation. Consider that technology use occurs within a particular course design and is more or less optimized by the role of the instructor. WebCT, for example, provides the opportunity to chat synchronously; if the course design does not require it, or the instructor does not provide time to use it, students may or may not experience this technological opportunity. As another example, interaction can be fostered or hindered by the instructor’s ability to invite students to participate, the students’ sense of competence regarding the presentation of ideas in print, the technological possibilities for interaction, and the design of the course in question. In other words, all five themes can be examined separately as they relate to online learning, but must be considered in comprehensive relation to each other if we are to illuminate the student experience online. This is also the case as we examine all five themes in each area of presence. What emerges is a multidimensional perspective that must guide thinking as we design online courses to engage and support students as they adjust to, move into and become competent performing in the online community of inquiry. Technology, for example, has a unique role to play in each of cognitive, social, and teaching presence. Social presence becomes possible as students use the technology to present themselves as individuals through the written word or verbal language. This use of the technology overlaps with, but is unique from cognitive presence, where intellectual reasoning

is presented as a portion of individual identity. Teaching presence emerges where the technology allows for presentation of material, directions from self to others, and the interpretation of material. Specific challenges and the resolution of these challenges demonstrate places where students are not prepared, and must respond or change to manoeuvre the online environment. Challenges are any requirement that students find difficult, uncomfortable, or in any way problematic regarding the online learning environment. Interventions ensued after the challenge, deliberately or incidentally. Resolution happens afterwards, in some cases but not all. Challenges may resolve themselves (#195), require intervention from the instructor (#331), or remain a challenge (#390); the latter, in particular, need attention by instructional designers or instructors.

concLusIon And recoMMendAtIons The adjustment process to the characteristics and requirements of online learning is not merely a matter of comfort or student satisfaction. It has practical and pedagogical implications as well. Much research demonstrates the authenticity of social, cognitive, and teaching presence online (see, for example, Meyer, 2003; Shea, Pickett, & Pelz, 2004; Swan, 2003). These elements are unique to the medium and will require established roles for students and instructors. Competent online learners are essential to creating community and contributing to higher-order learning activities. “Balancing socio-emotional interaction, building group cohesion and facilitating and modeling respectful critical discourse are essential for productive inquiry” (Garrison, 2006, p. 7). Evidence supports the premise that students experience a dynamic adjustment to the role of online learner, made up of particular ways of behaving, acting, and interacting (Knuttila, 2002).

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As the role of online learner is still undefined, students grapple with requirements, looking to their own reasoning, other students, and the instructor for direction about the right things to do. Adjustments occur in all three areas of presence, and each presence is both constrained and enabled by course design, technology, the instructor, personal self-identity, and the interaction within the community. Attention to these online elements in relation to the “getting up to speed” or adjustment for learners, each time they join an online community, will smooth this move to competence. In order to become present in the important functionalities of an online community of inquiry, adjustment must occur. Without adjustment to competence as an online learner, the learning process may be hindered. Support for students to move to a place of comfort and sense of competence is of value. Based on the comments of first time online learners describing their adjustment to the online community of inquiry in terms of cognitive presence, social presence, and teaching presence, we recommend the following be incorporated into the instructional design and delivery of online courses in order to ease the adjustment to the role of online learner and enhance the elements that contribute to an effective community of inquiry. •

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Acknowledge and make explicit the initial adjustment process, and provide a venue to identify challenges, consider interventions, and ensure resolution. Professional development opportunities for instructors should focus on techniques for easing learner adjustment to the online learning environment. Instructors should learn to recognize indicators of adjustment and be prepared to suggest appropriate support services if required. Provide ample opportunity for those unfamiliar with the technology to gain skills and

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•

•

feel comfortable so they do not feel they are at a disadvantage vis à vis their classmates. An orientation conference forum moderated by experienced online learners and facilitators should be available well in advance of the course start date. Encourage participants to separate content related dialogue from socializing. This can be accomplished by providing a café-style conference for those who enjoy chatting while those who have limited time or prefer not to socialize can focus on content. Include greater instructor involvement at the beginning of introductory level courses and judiciously thereafter. This will ease the adjustment for first-time online learners as they assume greater responsibility for meeting learning outcomes, gain comfort in contributing to discussions often dominated by more experienced online learners, and become more confident in their new role without the immediate feedback from the instructor that occurs in the face-to-face classroom. Request that participants limit the length of their conference postings to one screen and insist that discussions remain focused on content other than in the online café. Time is an issue for distance learners, and adjusting to the role of online learner includes learning to balance that role with others in adult life including work, family, and community. Provide instruction on proper conference netiquette. Also, if one member of the class uses emoticons, hyperlinks, or other special tools in their postings, ask them to publish the instructions for the group so everyone has access to the same tools. Request through private email that learners who appear to be dominating the conversation limit their postings to avoid intimidating novice conference participants. At the same

Role Adjustment for Learners in an Online Community of Inquiry

time, private e-mail can be used to encourage the less active participants to contribute. One effective technique is to include students’ names in conference postings and replies in order to draw them further into the conversation. This is the equivalent of being called on in a face-to-face classroom. Changed practice implies role adjustment for the instructors as well as the learners. Professional development activities that focus on the affective components of course delivery will enable instructors to ease the adjustment of the learners to online learning as well as increase their own comfort level and effectiveness.

LIMItAtIons Participants in this study were new to online learning, but most were new to graduate study as well. The adjustment to online learning would occur in conjunction with adjustment to graduate study; this needs to be considered in interpretation of findings. In addition, awareness of the requirements of online learning may have been created by completing the prequestionnaire. This may have affected the adjustment process and student response to it.

Future reseArch The next step in this research program is to review data from conference transcripts involving these respondents. We expect this will demonstrate adjustments to conference behaviour from course commencement to completion. This view of student activity will allow comparison of what students say happened against what really happened, at least within the conferences themselves.

Further research will clarify the stages of adjustment for first time online learners, and similarly for experienced online learners each time they begin a new course. Challenges and appropriate interventions in each of social, cognitive, and teaching presence must be made explicit through research such that responses may be recommended. These responses will ultimately identify what must be in place to ensure complete and competent engagement for online students. It is this latter understanding that is a critical conclusion to this work on student adjustment in online environments.

AcKnowLedgMent Funding for this research was received from the Athabasca University Mission Critical Research Fund and the Social Sciences and Humanities Research Council of Canada.

reFerences Allen, I. E., & Seaman, J. (2004). Entering the mainstream: The quality and extent of online education in the United States, 2003 and 2004. Needham, MA: Sloan-C. Retrieved August 16, 2005, from http://www.sloan-c.org/resources/entering_mainstream.pdf. Anderson, T., Rourke, L., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing context. Journal of Asynchronous Learning Networks, 5(2). Retrieved August 16, 2006, from, http://www.aln.org/alnweb/journal/jaln-vol5issue2v2.htm. Arbaugh, J. B., & Hwang, A. (2006). Does “teaching presence” exist in online MBA courses? The Internet and Higher Education, 9(1), 9-21.

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Blau, J. R., & Goodman, N. (Eds.) (1995). Social roles & social institutions. New Brunswick: Transaction Publishers. Collier, P. (2001). A differentiated model of role identity acquisition. Symbolic Interactionist, 24(2), 217-235. Dewey, J. (1933). How we think (rev. ed.). Boston: D.C. Heath. Dewey, J. (1938). Experience and education (7th printing, 1967). New York: Collier. Garrison, D. R. (2006, August). Online community of inquiry review: Understanding social, cognitive and teaching presence. Invited paper presented to the Sloan Consortium Asynchronous Learning Network Invitational Workshop, Baltimore, Maryland. Garrison, D. R., & Anderson, T. (2003). E-Learning in the 21st century: A framework for research and practice. London: Routledge/Falmer. Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. Internet and Higher Education, 11(2), 1-14.

Garrison, R., Cleveland-Innes, M., & Fung, T. (2004). Student role adjustment in online communities of inquiry: Model and instrument validation. Journal of Asynchronous Learning Networks, 8(2), 61-74. Retrieved August 16, 2006, from, http://www.sloan-c.org/publications/jaln/v8n2/ pdf/v8n2_garrison.pdf. Kanwar, M., & Swenson, D. (2000). Canadian sociology. Dubuque, IA: Kendall/Hunt Publishing Company. Katz, D., & Kahn, R. (1978). The social psychology of organizations. New York: Wiley. Kendall, D., Murray, J., & Linden, R. (2000). Sociology in our times (2nd ed.). Ontario: Nelson Thompson Learning. Knuttila, M. (2002). Introducing sociology: A critical perspective. Don Mills, Ontario: Oxford University Press. Kopp, S. F. (2000). The role of self-esteem. LukeNotes, 4(2). Retrieved August 16, 2006, from, http://www.sli.org/page80.html. McLuhan, M. (1995). Understanding media: The extensions of man. Cambridge: The MIT Press.

Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence and computer conferencing in distance education. American Journal of Distance Education, 15(1), 7-23.

Meyer, K. A. (2003). Face-to-face versus threaded discussions: The role of time and higher-order thinking. Journal of Asynchronous Learning Networks, 7(3), 55-65.

Garrison, D. R., & Archer, W. (2000). A transactional perspective on teaching-learning: A framework for adult and higher education. Oxford, UK: Pergamon.

Shea, P., Pickett, A., & Pelz, W. (2004). Enhancing student satisfaction through faculty development: The importance of teaching presence. In J. Bourne & J. Moore (Eds.), Elements of quality online education: Into the mainstream. Needham, MA: Sloan-C.

Garrison, D. R., & Cleveland-Innes, M. (2003). Critical factors in student satisfaction and success: Facilitating student role adjustment in online communities of inquiry. In J. Bourne & J. Moore (Eds.), Elements of quality online education: Into the mainstream (Vol 4 in the Sloan-C Series, pp. 29-38). Needham, MA: Sloan-C.

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Swan, K. (2003). Developing social presence in online discussions. In S. Naidu (Ed.), Learning and teaching with technology: Principles and practices (pp. 147-164). London: Kogan Page.

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Turner, J. (1990). Role change. Annual Review of Sociology, 16, 87-110. Wilson, D., Varnhagen, S., Krupa, E., Kasprzak, S., Hunting, V., & Taylor, A. (2003) Instructors’

adaptation to online graduate education in health promotion: A qualitative study. Journal of Distance Education, 18(2), 1-15.

This work was previously published in the International Journal of Web-Based Learning and Teaching Technologies, Vol. 2, Issue 1, edited by L. Esnault, pp. 1-16, copyright 2007 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 4.2

Videoconferencing Communities:

Documenting Online User Interactions Dianna L. Newman University of Albany/SUNY, USA Patricia Barbanell Project VIEW, USA John Falco College of Saint Rose, USA

AbstrAct Online communities have expanded to include a complex array of technologies that allow us to integrate multiple modes of interaction among participants. One such method of interaction is videoconferencing. As part of a multi-year national program, the authors developed and investigated multiple methods by which videoconferencing could be used to expand PK-12 educational communities such that students at geographically distanced sites have opportunities to interact with external resources. The authors identified four major types of videoconferencing

communities and common patterns within each that help to support effective use of the process. The chapter examines the nature and structure of these videoconferencing communities, provides examples of successful use, summarizes key user variables that impact the process, and makes recommendations for methods that should be used when studying videoconferencing communities. Education is longing for a deeper more connected, more inclusive and more aware way of knowing. (Kind, Irwin, Grauer, & DeCosson, 2005, p. 33)

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Videoconferencing Communities

IntroductIon As the 21st-century online revolution gains momentum, there is growing understanding that new modes of education consist of intersecting communities of teachers, administrators, parents, students, and informal educators (e.g., museum educators, zoo educators, librarians, artists, scientists, etc.). While these communities have divergent missions and goals, they clearly unite in their common desire to provide resources that will result in higher levels of student achievement (Barbanell, Falco, & Newman, 2003). As a result, educators are creating new online structures using innovative tools to provide content that will enable students to reach higher standards while preparing for the interactive digital world of their future. Online instructional environments encompass structures that facilitate access to Web-based learning resources and the learning tools embedded in those resources. Access to high-level learning resources is supported in online environments through both synchronous and asynchronous communications that use e-mail, digital bulletin boards and discussion groups, and, sometimes, videoconferencing. As noted by Rigou, Sirmakessis, Stravrinoudis, and Xenos (Chapter X, this volume) and Schwier and Daniel (Chapter II, this volume), these online communication modalities possess different characteristics and provide different levels of interaction, which include but are not limited to linear written response, asynchronous analytic discussion, and real-time interactive socialization. These differences in turn promote different types of communities. Online learning, in its many manifestations, is emerging as a primary mode for transforming existing content and curriculum into a more cognitively engaging medium, and as a result is leading to a more efficient and productive education of the new era. Online learning has been shown to yield positive educational results in several areas. For example, several authors (e.g., Childers & Berner,

2000; Hardwick, 2000; Heragu, Graves, Malmbourg, Jennings, & Newman, 2003; Hull, 1999) have shown that Web-based (online) education can increase student motivation and participation in both class discussions and student projects. Lauzon (1992) indicated that online technologies provide an excellent medium for allowing learners to interact in meaningful ways with both a distant instructor and other distant students. Online forums and bulletin boards also have been shown to provide platforms that support variations in interpretation and construction of meaning among students. Alexander (1995) noted that learners interpret reality individually as they engage in apprehending structure, integrating parts, and acting and reflecting on the world. One of the most interactive modes of online learning is videoconferencing. This medium breaks down the barriers of communication among participants by providing online access to learning and information in a way that encourages the building of interactive communities. Videoconferencing has been defined as “a live connection between people in separate locations for the purpose of communication, usually involving audio and often text as well as video” (Tufts University: Educational Media Center, n.d.). Unlike many other forms of online communication, videoconferencing requires the participants’ real-time physical presence to communicate with learners at distant sites. To take advantage of this modality, learning communities must adapt pedagogy and educational content to form a more dynamic mode of interaction. In the best of scenarios, students participate in classroom activities that include interactive questioning and discussion with presenters, thereby merging the local classroom community with others at geographically distanced sites. Proponents of the medium believe that using videoconferencing in the classroom community has many advantages. One of the benefits of videoconferencing rests in its capacity to import external resources to the classroom via advanced

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technology (Motamedi, 2001). In addition, it is believed that videoconferencing can better accommodate communities of diverse learning styles than do other online tools in which instructional strategies may be asynchronously mismatched with learners’ needs. In fact, many state that it is the interactive element of videoconferencing that is the real key to its success when combined with well-planned, student-centered instruction (Greenberg, 2004; Omatseye, 1996). Project VIEW, a U.S. Department of Education-funded Technology Innovation Challenge Grant,1 has developed a model for transforming 20th-century education structures into successful 21st-century education communities via videoconferencing. A key purpose of Project VIEW was to explore the possibilities of videoconferencing as a means of expanding the community of education in the PK-12 classroom; this was to be accomplished by enabling teachers, administrators, students, and external content providers to become immersed in the development and use of this interactive resource. As a result, Project VIEW has created a model of participant engagement involving the creation of learning communities through a combination of constructivist training and handson program development. This model fosters interactive cooperation among the collaborating communities, as well as the creation of formal and informal educational societies, by nurturing the collaborations that are founded on true partnerships and sharing of experiences and resources. As a result, new alignments of educational communities are developed to integrate interactive digital content into all levels of curriculum. Over the five years of the grant, a core element in the creation of VIEW’s interactive educational communities was the formative evaluation and research embedded within design and use. As part of this process, the research and evaluation team gathered data pertaining to implementation of more than 100 videoconferences in over 40 buildings and 70 classrooms that encompassed

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more than 2,000 children and 30 providers. Both quantitative and qualitative methodologies were used. Paper-pencil surveys, randomly selected classroom observations, and structured interviews were used to generate an overview of community building. In addition, case studies of selected teachers and buildings provided an in-depth look at supporting practices. This documentation has resulted in the identification of four major types of videoconferencing communities found in PK-12 educational settings: provider-classroom videoconferencing, collaborative classroom videoconferencing, multi-point videoconferencing, and electronic field trip videoconferencing. Each of these four types of communities has unique user characteristics and patterns of interaction that reflect variations in goals and member composition. The remainder of this chapter examines the nature and structure of these videoconferencing communities, provides examples of successful use, summarizes key user variables that impact the process, and makes recommendations for methods that should be used when designing and studying videoconferencing communities.

ProvIder-cLAssrooM vIdeoconFerencIng In provider-classroom videoconferencing, a classroom of students uses videoconferencing to communicate directly with a representative of an external expert provider organization. Provider organizations may consist of museums, zoos, historical sites, scientific organizations, and so forth.2 The provider community representative may be a member of the educational staff, an expert in the field, a group of program sponsors, or others who have external information that can be shared with a group of students. The majority of providers utilize a series of replicable curriculum units based on their internal archives and gallery programs. In Project VIEW, these programs are co-developed with teams of teachers to ensure that the program

Videoconferencing Communities

and supporting materials align with content-based learning standards and are adaptable to differing classroom and student needs. Classroom communities involved in providervideoconferencing represent all grade levels (PreK through 12 as well as higher education) and include all ability levels of students. This method of videoconferencing is possible in schools with varying technological complexity; schools need only a modern computer, a communication connection, a video camera, and videoconferencing software (Penn, 1998). As a result, classrooms are able to become part of active online learning communities, allowing all students to benefit from a mutual learning context (Menlove, Hansford, & Lignugaris-Kraft, 2000). Teachers may integrate these external provider-based videoconferences in many ways to support their traditional curriculum; videoconferencing may serve several purposes such as an advanced organizer, enrichment of regular instruction, exposure to primary resources, and summary overviews. In providerclassroom videoconferencing, teachers are no longer viewed as the primary experts, but rather as facilitators whose major task is to enable students to gain insight from these external experts, and to interact with artifacts and resources not usually available within the traditional boundaries of a

local school community (Silverman & Silverman, 1999). A brief example of a provider-classroom scenario may be found in Vignette One. Many school systems use provider-classroom videoconferencing to counteract issues of equity, student safety, and a decreasing economic base. Provider-classroom videoconferencing promotes equal access to resources and increases the quality of educational opportunity for learners in remote or economically disadvantaged schools; it provides access to subject matter experts and career role models for students across gender, ethnic, and racial divisions; it eliminates security issues related to travel; and it overcomes time and budgetary constraints typically associated with field trips. In general, researchers have found that students who participate in videoconferencing are more motivated and interested in the topic at hand, and report high levels of achievement in problem-solving and critical thinking than before access (Gernstein, 2000; Silverman & Silverman, 1999). Studies conducted as part of Project VIEW indicate that, as a result of participation in provider-classroom videoconferencing, students are more interested in learning the topic, have a greater interest in continuing to learn more, want more access to similar resources, and perceive that

Vignette One

Janet, a first-grade teacher, brought 5 one-hour videoconferences to her class from a variety of content providers including the Smithsonian Environmental Research Center and the Buffalo Zoo. She used pre-materials to prepare her students for the videoconference and asked them to write to providers asking questions. During the videoconferences, the providers showed students authentic objects, conducted simple experiments, and engaged students in lively discussions. Janet took the role of classroom manager during the videoconferences and, at the end of each, assigned students tasks that included writing about connections, drawing conclusions, and making predictions based on what they had learned. Janet noted that videoconferencing has great potential value as an educational tool and allows her to explore different topics much more in depth than she had in previous years. She reported that videoconferencing generates excitement among students and that lessons involving videoconferencing are much more likely to motivate students to learn. In Janet’s words, students “are becoming responsible partners in their own learning.

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Videoconferencing Communities

they have a better understanding of the material. Teachers report that students gain a wider perspective of the material, are more actively involved in learning, and work at higher levels of cognition than when exposed only to in-class teaching (Newman et al., 2004; Newman, 2005). Newman, Gligora, King, and Guckemus (2005) also found over a series of studies that students involved in provider-classroom videoconferencing tended to have greater gains in content-related academic outcomes than did students who received parallel traditional classroom instruction. Several features of the videoconference session contribute to learning and gains in academic outcomes. One of the key characteristics studied, as part of Project VIEW, was the role of the

external expert within the provider-classroom community. Abrahamson (1998) noted that the success or failure of the use of interactive television as a means of instruction depended largely on the effectiveness of the content provider and the amount of interaction between provider and students. As a result, Project VIEW research and evaluation of provider-classroom videoconferencing investigated the relationship between provider roles, provider-student interactions, and perceived outcomes of the videoconferencing experience. A key study conducted by Newman and Goodwin-Segal (2003) investigated the outcomes of 32 videoconferences using 13 different providers, delivered to 550 students across 14 buildings. As part of delivery assessment, students were asked

Table 1. Instructional groups occurring in provider-classroom videoconferencing Provider-Centered (n=250)

Student-Centered (n=104)

Activity

Weighta

Activity

Weight

Activity

Weight

Watching the program

.93

Watching the program

.93

Watching the program

.93

Answering questions

.48

Answering questions

.87

Participating in an activity with the presenter

.74

Asking questions

.43

Working in a group

.85

Asking questions

.72

Talking with my friends

.21

Discussing the topic with others

.76

Participating in an activity with my teacher

.64

Discussing the topic with others

.18

Designing or making something

.76

Answering questions

.23

Working in a group

.12

Asking questions

.71

Discussing the topic with others

.10

Participating in an activity with my teacher

.64

Taking with my friends

.54

Taking notes

.49

Solving a problem with the presenter

.43

Note: aWeights represent relative contribution to the construct of activities

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Provider-Guided Inquiry (n=196)

Videoconferencing Communities

to indicate the activities in which they participated during videoconferencing with an external provider and the degree to which the program was interactive. All videoconferences were observed in the classroom setting by evaluators to validate student-provider interactions. Findings indicate that 95% of the students were actively engaged in watching the program, 59% asked and answered questions, and 52% participated in activities directed by the content provider. To determine if patterns of activities supportive of instructional styles could be documented, a cluster analysis of possible interaction variables was performed. Presented in Table 1 are the results of that analysis. Based on student reported and evaluator-validated activities, three distinct patterns of community interactions, each with distinct roles and relationships, were identified: provider-centered, provider-guided inquiry, and student-centered. The first group, labeled provider-centered, was the largest, consisting of 250 students (45% of the respondents). The majority of the students in this scenario watched the program, but only a few were involved in asking and answering questions. The remainder of potential instructional activities was not part of these students’ videoconference experience. In essence, the students were observers to the development of the community. The role of the teacher in this scenario was that of classroom management or technology monitor. Student and provider interactions in this type of community are similar to those of a teacher-centered classroom, in which an expert provides information to learners who are expected to acquire knowledge via a passive role. The second group of students (n=196), representing 36% of the participants, was labeled provider-guided inquiry. Students in this type of community tended to passively receive information from a provider for the first part of the program and then participated in an activity led by the provider. During this later stage of the videoconference, the provider instructed the

students in the steps they were to take as part of the activity, corrected their mistakes, and led them to the correct outcome. The students contributed to an emerging educational community, and were moderately active in asking and answering questions and discussing the topics with other students as they sought to follow directions and reach the correct outcome. In this type of community, the role of the teacher expanded to that of a facilitator: helping to identify students who had questions of the provider, indicating those who had achieved correct or incorrect outcomes, and managing the distribution of local archives. The provider-student relationship in this community was similar to that found in guided inquiry classrooms, but did allow for interaction with an external expert and use of materials that would not otherwise be available. The final group of students (n=104; 19% of all students), representing participation in student-centered settings, tended to reflect the most hands-on interactive learning community. These students worked in groups, asking and answering questions with the provider, and discussing the topic with other students as well as the teacher. Additionally, these students tended to be involved actively in solving a problem with the presenter, designing or making something, writing or taking notes about the topic, or participating in a teacherled activity. In this setting, both the teacher and the content provider were active in facilitating learning. The provider allowed students to make mistakes, responded to student-suggested solutions to problems, and encouraged all students to be active in developing scenarios, generating hypotheses, and solving problems. The role of the teacher was that of a co-instructor who helped encourage all students to question the provider, other students’ work, and their own work. This provider-classroom community is similar to a constructivist classroom setting but has been enhanced to include an outside expert as well as hands-on problem solving.

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Videoconferencing Communities

coLLAborAtIve cLAssrooMs vIdeoconFerencIng The second type of videoconferencing community evidenced by Project VIEW incorporated the concept of collaborative classrooms. In this setting, two classrooms at geographically distanced sites use videoconferencing as a means of accessing, sharing, or transmitting information between each other (Newman, 2005). The overall goal of a collaborative classroom is to engage students in the process of instruction and assessment, thereby modeling and supporting higher-level thinking and problem solving (Jonassen, 2002). Instructional practices generally include students at various performance levels working together in small groups toward a common academic goal (Gokhale, 1995). Several researchers (e.g., Davis, 1993; Totten, Sills, Digby, & Russ, 1991; Woolfolk, 2004) have offered empirical evidence that students are more satisfied with learning, engage in higher levels of thought, have greater retention and improved oral skills, and take greater responsibility for their own learning when working in a collaborative setting within their own classroom. The use of collaboration, however, does not decrease the need for individual learning. According to Slavin (1989), effective collaboration settings incorporate the establishment of common group goals backed by individual accountability. This impetus for collaborative learning has been further strengthened by advances in technology and changes in the workplace that emphasize the need for collaborative skills (Beckman, 1990; Gokhale, 1995). When technology becomes part of this process, classroom collaboration can be expanded to include students in separate locations communicating via Web-cams, streaming audio, and the Internet. The use of videoconferencing adds to this process by making it possible for students to see and hear each other, in both small and large groupings. Collaboration is no longer just within the classroom; it is now synchronous across two communities, and involves the shar-

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ing of instruction, resources, and assessment (Newman, 2005). Educators are exploring four major types of collaborative classroom videoconferencing at the current time. Though similar in overall objective, each serves a distinct group of users, and has unique characteristics and special evaluation needs. The first of these, student-to-student collaborative videoconferencing, is utilized when two classrooms or groups of students geographically distanced from each other use videoconferencing as part of their regular instructional process. The goal of the videoconference is to share instructional and learning opportunities across classrooms studying similar content, usually with learners who are similar in ability level and grade placement. In this setting, an interactive community evolves as students work both with their classroom peers and with peers at an alternative site, under the guidance of teachers at both sites, to plan and implement projects, share and present information, and investigate or do research on common themes. Vignette Two provides a brief description of a collaborative classroom videoconferencing community. The second type of collaborative classroom experience builds on the sharing of information across grade and ability barriers. In tutoring collaborations, students who are more advanced or at a higher ability level form online videoconferencing communities with students who are learning basic concepts. In this setting, advanced students work with teachers in both classrooms to determine basic concepts related to specific content, develop innovative ways of teaching and reinforcing these concepts, and serve as tutors or lay instructors to lower-level students in geographically distanced classrooms. For instance, students in an eighth-grade middle school American History class may teach components of the American Revolution to students in a fifth-grade class located in an elementary school. Without the use of videoconferencing, formation of these interactive communities would require

Videoconferencing Communities

Vignette Two A collaborative classroom videoconferencing project was developed by two sixth-grade teachers who met at Project VIEW training. Teachers jointly created preparatory activities in which all students were paired with another student from the partner school. The pairs corresponded via e-mail for three months (at least one correspondence exchange per pair per month) and eventually met face-to face through a classroom-to-classroom videoconference. Both classes then participated in separate provider-classroom videoconferences with the Museum of Television and Radio (MTR) on the theme, “Not judging others by their outward appearance,” in which the museum showed TV clips relating to stereotyping. During this videoconference, the presenter engaged the students in a discussion on stereotypes, and asked them to make predictions and draw conclusions based on the clips they had seen. Following the MTR videoconferences, the students again held classroom-to-classroom videoconferences. The purpose of these exchanges was for students to make presentations on the books they had studied (students from one school had read Foxman; students from the other had read The Witch of Blackbird Pond). Student presentations reflected on similarities between the MTR videoconference resources and the books. Teachers helped students work collaboratively on their presentations via e-mail, and in some cases via videoconferencing.

transportation of one or both groups, thereby limiting involvement to classrooms within the same building or, at best, within the same district, and curtailing the frequency of community contact. The use of videoconferencing allows these communities to be formed without consideration of geographical distance or limitations of frequency. Tutorial videoconferencing communities provide tremendous advantages to both student groups; the advanced students have the opportunity to review, enlarge, and enhance their knowledge base as they select and develop methods of sharing knowledge; students who are gaining basic knowledge are, in turn, more motivated to learn the material and see it as more relevant because it is presented by other students. The third type of collaborative classroom assists in serving the needs of students with special needs. This method combines the tutorial approach with student-to-student collaboration and allows for the formation of videoconferencing communities that support the academic, social, physical, and emotional needs of students who

are in inclusion and self-contained classrooms. The communities may be composed of students, geographically distanced, who have similar or dissimilar needs and ability levels, and are working together to master skills and knowledge under the guidance of either teachers or advanced students. For example, students in an inclusion classroom may form, via videoconferencing, collaborative learning groups with students with similar needs in another geographically distanced inclusion classroom. Similarly, students in a self-contained classroom may, through the use of videoconferencing, become part of a collaborative group within a heterogeneous classroom. Through the use of videoconferencing, students with special needs have the opportunity to eliminate geographical and structural boundaries that have limited their interactions with other students and curtailed their learning opportunities. After-school collaboration is the fourth type of collaborative online community being studied by those who are exploring the different uses of videoconferencing. As a result of social, economic,

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Videoconferencing Communities

and educational requirements, almost all K-12 districts now have some form of a local afterschool program housed within their buildings. These programs represent a sub-community of the larger educational domain, frequently reflecting those students and families most in need of additional academic support, social assistance, or who have limited access to cultural experiences. Multiple types of videoconferencing communities can be formed in these settings to meet these needs. Student-to-student, tutorial, and special needs collaboration models can be adapted in after-school settings to assist in meeting the academic needs of students; geographically distanced study groups of students with equivalent needs in content and ability level can work in a more relaxed environment while obtaining extra help;

expert tutors, both adult and peer, can become part of study teams, but still be geographically distanced from the learning site. The use of these active, synchronous, and highly involved online communities also fosters the development of social and emotional supports needed by many of these students. Designing and evaluating collaborative videoconferencing communities requires additional input and resources to those involved in providerto-classroom videoconferencing. Because two sub-communities representing the two classrooms are involved in the process, there is a need to delineate the unique characteristics of each and to determine their specific role in the relationship. This includes identifying the contextual, cultural, and technological variables located at each site,

Table 2. Collaborative classroom videoconferencing

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Instructional Purpose

Communities Involved and Their Role

Instructional Placement

Advanced organizer

Older students introducing materials to younger students

At the beginning of a unit

Resource for research

Older students providing, assisting younger students with insights, resource clarification, assistance in finding information

Mid-unit, after the classroom teachers have covered materials with both groups

Sharing resources for research

Same aged and ability level of students, studying the same content while sharing insights, resources, and conclusions

Throughout the unit, with instruction from teachers interspersed with student work

Reporting and presenting

Same aged and ability level of students reinforcing and sharing learning; older students reporting to younger students

At the end of units; prior videoconferencing not required

Assessment

Older students observing and providing feedback to younger students or to students of equal ability without the pressure of friendship bias

Informal assessment midway through units and prior to summative assessments; summative assessment at the end of units

Tutoring

Older students to younger students; older students with special needs to younger students; peer-to-peer

Before and during instruction

Remediation

Older students to younger students; parents to students

During instruction and as part of after-school programs

Motivation

Older students to younger students or to students with special needs; parents or community adults with student groups to other student groups

Before, during, and after instruction; classroom and after-school programs

Videoconferencing Communities

as well as the student and teacher variables. Variations in learner ability, access to technology, layout of the classroom, and local support for the process have all been shown to impact the process. As a result, while there is positive evidence supporting the impact of collaborative classroom videoconferencing on learning (e.g., Andrews & Marshall, 2000; Newman, 2005), the complex relationship of these contextual variables has only begun to be studied. As part of Project VIEW’s investigation of the variables involved in collaborative classroom videoconferencing, a major review of collaborative classroom videoconferencing was undertaken. This included selected observations of multiple short- and long-term collaborative communities, in-depth case study documentation of three communities, and an in-depth review of 68 collaborative classroom videoconferencing curriculum plans. In summarizing the findings of this work, Newman (2005) confirmed the diversity and adaptability of collaborative videoconferencing efforts, noting that they served multiple purposes including functioning as/or supporting advance organization efforts, sharing resources and research materials, practicing oral and visual reporting, assessing students, tutoring, and practicing direct remediation. Observations of these collaborative interactions indicated that students were more engaged in learning, tended to perceive more ownership of their work, accessed a broader array of resources (both paper and electronic), and participated in more complex problem solving than when working only within their classroom. In addition, the use of videoconferencing allowed the students to work with students of different ethnic, socio-cultural backgrounds and reinforced respect for multiple viewpoints. These studies also supported the hypothesis that collaborative classroom videoconferencing is a complex, dynamic process that is actually made up of interdependent communities. The evolving collaborative roles of the teachers influenced the

interactions of the students both within and across the communities. The evolution of the teachers’ roles, however, was influenced in large part by the availability of technology and technology support during the planning stage as well as during the implementation stage. Teachers who used videoconferencing to develop their collaborative classroom plans had greater access to technology and technical support, involved the students in videoconferencing more frequently and in a more independent manner, and also saw the need to develop means by which students used other modes of communication. Subsequently, teachers who were more comfortable with videoconferencing, and whose students where more involved in the process, also tended to arrange for telephone calls, letters, and, where possible, in-person visits after the videoconference. In these settings, the community developed by the collaborating classroom videoconference endured longer and allowed for more sharing of cultural and social knowledge.

MuLtI-PoInt vIdeoconFerencIng coMMunItIes Multi-point videoconferencing is an expansion of classroom videoconferencing to involve three or more communities. These communities may be composed of all students, or a combination of students and content providers. Variations in the types of communities and the timing, the placement, and the frequency of their involvement make almost every multi-point videoconference unique; however, there are some underlying similar characteristics that can be noted. The most common patterns are expansions of the provider-classroom videoconferencing and collaborative classroom videoconferencing approaches described earlier. In multi-point provider-classroom videoconferencing, a provider simultaneously works with

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two or three classrooms, sharing not only his or her organization’s resources, but also facilitating the sharing of resources among and across the communities of students in the distanced classrooms. This process is synchronous; representatives of all communities are videoconferencing at the same time. In these settings, the students are generally studying similar content and are typically of the same ability level. The role of the provider varies; in some situations, artifacts and discussions are used as advance organizers or for the generation of hypotheses, and students share their thoughts, theories, and hypotheses across classrooms as well as with the provider. In other settings, the provider may serve, along with students in a distant classroom, as an audience and respondent to student questions and presentations from one of the participating classrooms. In the most successful multi-point videoconferences, the provider members of the community begin with a provider-centered approach to learning, presenting facts, and leading a discussion, but then switch to a student-centered approach, acting as the facilitator and moderator between the classroom communities. In multi-point collaborative classroom communities, three or more classrooms of students are simultaneously sharing information, resources, and student-generated products under the guidance of the teachers. Each classroom serves as a provider and an audience to the needs of the other classrooms. This model can be used successfully among students studying the same content. When the method is used for tutorial, research, or reporting purposes, usually at least two of the three classrooms should be at the same cognitive ability level. In situations when the goal of videoconferencing is related directly to the sharing of culture as well as academic information, it is beneficial to have frequent interactions among classrooms at similar ability levels learning similar content. This allows for more opportunity for discussions of different interpretations, and for more secondary questions and elaboration on about why different

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cultures might perceive information differently. The use of pre-planned or guided inquiry on the part of the collaborating teachers can facilitate this sharing of culture so that it happens in a non-threatening manner.

eLectronIc FIeLd trIP vIdeoconFerencIng The fourth type of videoconferencing community provides a unique opportunity for interaction between providers and educational communities, and represents an extreme variation of videoconferencing methodologies. In this scenario, a provider community simultaneously broadcasts to a large number of classroom communities, generally for a limited duration for a limited number of times. In this situation, because there are too many classroom communities for student-to-student interactions or for provider-to-student interactions, the predominant mode of communication is provider-centered. In most cases, the provider community has a pre-developed but informal script that is used to guide the presentation of pre-selected artifacts and resources, and the student communities primarily serve as recipients of information during the videoconference. In Project VIEW electronic field trips, teachers assisted in the development of the scripts, ensuring that they met national learning standards, and in many cases, students were included in the design and piloting of supporting instructional materials. Students also played a role in the delivery of the videoconferences, serving as aides in use of archives and in asking and responding to selected provider-generated questions. In some settings, students who were members of the geographically distanced communities played active roles by submitting real-time questions, hypotheses, and comments during the videoconference via e-mail or telephone. Although electronic field trips are by necessity provider-centered and with limited student

Videoconferencing Communities

interactions, there are scenarios in which they may be the best method of forming a community of short duration that can share important information. Examples include electronic field trip videoconferences of the National Baseball Hall of Fame (e.g., “Untold Stories: Baseball & The Multi-Cultural Experience”), Space Center Houston and Johnson Space Center (e.g., “Journey to the International Space Station”), and the Whitney Museum of American Art (e.g., “Over the Line: The Art & Life of Jacob Lawrence”). Each of these settings involved a unique user characteristic that could not easily be replicated because of the nature of the provider-experts (e.g., membership in the Negro Baseball League or a retired astronaut), the cost of the enterprise, or security issues pertaining to archival access. As a result, a “one-time-only” scenario exists that makes it necessary to allow access to as many learner communities as possible. Most providers have some resources or archives that can only be accessed for a limited time period, and consequently, there is a need to increase access to as wide an audience as is possible. As a result, electronic field trips have a special place in education. Worthington and Ellefson (n.d.) found that a key benefit of electronic field trips was student exposure to “real” people and events that could not be accessed any other way, thereby giving classroom content more meaning by connecting facts to people and occurrences. The unique characteristics of these communities necessitate a different form of evaluation that emphasizes group goals and socialization/culturalization instead of individual changes. As noted in Newman (2003), students were less engaged and less motivated to continue learning the content when part of this videoconferencing community than in any of the other types; however, in settings where it was documented that teachers embedded the electronic field trip within their regular curriculum and made use of supporting materials before and after the presentation, students’ motivation to learn increased on par with other

types of videoconferencing, and teacher-assessed outcomes were achieved.

concLusIon The role of online communities in the field of education is expanding in an exponential manner. Educators are developing and implementing, on a regular basis, online courses, online components of courses, and online supplements to courses. Studies of human-computer interactions that examine the relationships among individuals and computers have led to the identification of patterns of user interaction variables. Knowledge that relationships exist among users has challenged us to expand our research to study the community of the learner involved in the process, not just the individual learner. At the same time, we also have expanded the technologies being used to support learning so that it is no longer human-computer interactions that are important, but rather community-technology interactions that must be studied. The use of videoconferencing in the formation of technology-based communities, their interactions and outcomes, and the sustainability of these communities exemplify the need for inclusion of user characteristics when designing and supporting online communities. Through its five-year program, Project VIEW designed, implemented, and studied four major types of online videoconferencing communities: provider-classroom, collaborative classroom, multi-point, and electronic field trip. Within each type, common roles and characteristics of the participants were noted that set that community type apart from the others and which yielded explicit implications for user-centered design. •

Provider-classroom communities had as their major objective the expansion of resources to include distant expert participants. Within this goal, varying patterns of interaction were noted that allowed for the

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•

•

•

formation of different types of relationships with the provider. Collaborative classroom communities had as their major objective the expansion of opportunities for collaborative learning such that students could engage with those who were outside their own building’s culture. Again, variations in user characteristics played an important role. Teacher, student, building, and culture interacted to yield variations in the process of reaching the overall goal of collaborative learning. Multi-point videoconferencing communities combined the complexities of these two approaches and revealed the importance of flexibility, creativity, and organization in identifying the roles of the participants, and the frequency and depth of the interactions among the key users. Studies of electronic field trip videoconferencing also highlighted their unique place in videoconferencing; when providers represent, or only allow access, to a limited resource, tradeoffs of some community members’ status may be needed to allow for more equitable access to more members.

Each of these unique settings calls for identification and acknowledgement of different types of planning, implementation, and assessment. As the role of the provider shifts from that of an expert to a peer, from that of a one-time interaction to a series of ongoing, developing conversations, the variables in planning will shift, the types of resources needed for implementation will change, and the outcomes identified as primary to assessment will be altered. In addition, as the size of the community and the sub-communities change, the complexities of the interactions and relationships supporting the community will change and will require different forms of documentation and different variables. Videoconferencing as a form of online community building is only beginning to be explored.

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Many school and provider organizations are only now seeing the potential of this method of sharing information. As the technology improves, as more schools and providers are trained and acquire equipment, as more consumers become accustomed to and expect to have this means available to them, the role of videoconferencing will change. Within the next few years, this “innovative” mode of forming communities across geographic boundaries will become common. As this evolution occurs, there is a need to continue to study the characteristics of the members of the communities, and to determine the methods and resources that best meet those members.

reFerences Abrahamson, C. (1998). Issues in interactive communications in distance education. College Student Journal, 32(1), 33-43. Alexander, S. (1995). Teaching and learning on the World Wide Web. Retrieved September 15, 2005, from http://ausweb.scu.edu.au/aw95/education2/alexander/index.html Andrews, K., & Marshall, K. (2000). Making learning connections through telelearning. Educational Leadership, 53-56. Barbanell, P., Falco, J., & Newman, D. (2003). Accessing museums through the Web: A model for evaluating the impact of museum and school partnerships In J. Trant & D. Bearman (Eds.), Museums and the Web 2005. Toronto: Archives & Museum Informatics. Retrieved September 15, 2005, from http://www.archimuse.com/mw2003/ abstracts/prg_200000770.html Beckman, M. (1990). Collaborative learning: Preparation for the workplace and democracy. College Teaching, 38, 128-133. Childers, J. L., & Berner, R. T. (2000). General education issues, distance education practices:

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Building community and classroom interaction through the integration of curriculum, instructional design, and technology. Journal of General Education, 49(1), 53-65. Davis, B. G. (1993). Tools for teaching. San Francisco: Jossey-Bass. Gernstein, R. B. (2000). Videoconferencing in the classroom: Special projects toward cultural understanding. Integration of Technology in the Classroom, 16, 177-186. Gokhale, A. A. (1995). Collaborative learning enhances critical thinking. Journal of Technology Education, 7, 1045-1064. Greenberg, A. (2004, February). Navigating the sea of research on videoconferencing-based distance education: A platform for understanding research into the technology’s effectiveness and value. Retrieved September 9, 2005, from http://www.wainhouse.com/files/papers/wrnavseadistedu.pdf Hardwick, S. W. (2000). Humanizing the technology landscape through collaborative pedagogy. Journal of Geography in Higher Education, 24, 123-130. Heragu, S. S., Graves, R. J., Malmbourg, C. J., Jennings, S., & Newman, D. L. (2003). Multimedia tools for use in materials handling classes. European Journal of Engineering Education, 28(3), 375-393. Hull, D. (1999). The power and peril in technology. Community College Journal, 70(1), 38-44. Jonassen, D. H. (2002). Engaging and supporting problem solving in online learning. The Quarterly Review of Distance Education, 3, 1-13. Kind, S., Irwin, R. L., Grauer, K., & DeCosson, A. (2005). Medicine wheel inag(in)ings: Exploring holistic curriculum perspectives. Art Education, 58, 33-38.

Lauzon, A. (1992). Integrating computer-based instruction with computer conferencing: An evaluation of a model for designing online education. American Journal of Distance Education, 6, 32-46. Menlove, R., Hansford, D., & Lignugaris-Kraft, B. (2000). Creating a community of distance learners: Putting technology to work. Proceedings of the American Council on Rural Special Education on Capitalizing on Leadership in Rural Special Education: Making a Difference for Children and Families, Alexandria, VA. Motamedi, V. (2001). A critical look at the use of videoconferencing in United States distance education. Retrieved September 15, 2005, from http://www.highbeam.com Newman, D. L. (2003). The virtual information education Web project: Formative evaluation of the Schenectady City School District Technology Innovation Challenge Grant, Schenectady Component, Year Three 2002-2003 Report. Albany, NY: SUNY Albany Evaluation Consortium. Newman, D. L. (2005, March). Beyond the barriers: Benefits of K-12 teacher participation in collaborative classroom videoconferencing training. Proceedings of the Annual Meeting of SITE Conference, Phoenix, AZ. Newman, D. L., Gligora, M. A., King, J., & Guckemus, S. (2005, April). Breaking down the classroom walls: The impact of external videoconferencing on children’s cognition. Proceedings of the Annual Meeting of the American Educational Research Association, Montreal, Canada. Newman, D. L., & Goodwin-Segal, T. (2003, November). Evaluation of a technology integration challenge grant program: Using technology to connect museums and classrooms. Proceedings of the Annual Meeting of the American Educational Research Association, Chicago.

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Newman, D. L., King, J. A., Gligora, M. A., Guckemus, S. M., & Pruden, J. M. (2004, November). Evaluating the impact of videoconferencing: Documenting teacher outcomes and changes in instructional strategies. Proceedings of the Annual Meeting of the American Evaluation Association, Atlanta, GA. Newman, D. L., Nolan, A., & Quinlan, B. (2004, April). Views from opposite sides of the camera: Teachers’ perceptions of videoconferencing. Proceedings of the Annual Meeting of the American Educational Research Association, San Diego, CA. Omatseye, J. N. (1999). Teaching through tele-conferencing: Some curriculum challenges. College Student Journal, 33(3), 346-353. Penn, M. (1998). Videoconferencing one-to-one but far from home. Technology Connections, 5(2), 22-23. Silverman, S., & Silverman, G. (1999). The educational enterprise zone: Where knowledge comes from. T H E Journal, 26. Slavin, R. E. (1989). Research on cooperative learning: An international perspective. Scandinavian Journal of Educational Research, 33, 231-243.

Special Education Programs. (1990). The use of technology with special needs students. Research Progress, 8, 1-5. Totten, S., Sills, T., Digby, A., & Russ, P. (1991). Cooperative learning: A guide to research. New York: Garland. Tufts University Educational Media Center (n.d.). Glossary. Retrieved September 15, 2005, from http://www.tufts.edu/orgs/edmedia/gloss.shtml Woolfolk, A. (2004). Educational psychology (9th ed.). Boston: Pearson Education. Worthington, V., & Ellefson, N. (n.d.). Electronic field trips; theoretical rational. Retrieved September 15, 2005, from http://commtechlab.msu. edu/sites/letsnet/noframes/bigideas/b1/b1thor. html

endnotes 1

U.S. Department of Education Award Number R303A000002.

2

A list of potential providers may be found at www. projectview.org.

This work was previously published in User-Centered Design of Online Learning Communities, edited by N. Lambropoulos, P. Zaphiris, pp. 122-140, copyright 2007 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.3

Library Services for Distance Education Students in Higher Education Elizabeth Buchanan University of Wisconsin-Milwaukee, USA

IntroductIon Contemporary distance education has its roots in early forms of postal correspondence study but has evolved to sophisticated, technologically grounded forms of education. It has progressed from simplistic forms of written, correspondence study, known as the first wave of distance education (1870-1970), to early forms of television, satellite, and compressed video delivery and open education, known as the second wave (1970-1992), to its present stage of computer-based delivery, mainly over the Internet and its multimedia component, the World Wide Web (WWW). This form constitutes the third wave or phase. While the means by which institutions of higher learning deliver education remotely will continue to change, there is at least one constant—distance students will need support from their institutions and, in particular, access to library resources and services to successfully

complete their educational endeavors. Libraries’ roles are indeed changing in light of Web-based distance learning, as well as such developments as full-text databases, e-books, and on-demand services. For years, libraries have struggled with the tension between “just-in-time” versus “justin-case” collection development, and the need to now serve remote users and on-site students exacerbates this tension. Yet, serving remote students is not novel—the Association of College and Research Libraries (ACRL) issued its first guidelines for serving “extension students” in 1963. The ACRL Guidelines are now in their fourth revision (ACRL, 2000). What must a library do for its distance students? It is useful to cite the ACRL’s definition of “distance learning library services”: Distance learning library services refers to those library services in support of college, university, or other post-secondary courses and programs of-

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Library Services for Distance Education Students in Higher Education

fered away from a main campus, or in the absence of a traditional campus, and regardless of where credit is given. These courses may be taught in traditional or nontraditional formats or media, may or may not require physical facilities, and may or may not involve live interaction of teachers and students. The phrase is inclusive of courses in all post-secondary programs designated as: extension, extended, off-campus, extended campus, distance, distributed, open, flexible,franchising, virtual, synchronous, or asynchronous. Given the potential range of responsibilities generated out of this definition, newfound roles for the library emerge. First, a change in perspective enables serving distance students appropriately: The library is no longer a passive entity awaiting patrons to walk through its doors, but is now a proactive entity that reaches out through a variety of methods and services to its users. Secondly, the library must reposition itself as a central entity and key player on university and college campuses. As colleges and universities forge ahead with new online programs—with the National Center for Educational Statistics reporting that 85% of higher education institutions engage in some form of distance education (NCES, 2001)—they must be cognizant of the importance of the library in serving these students. The library should be central as a planning board as new programs are launched; any institution that does not fully involve the library in planning for distance programs is doomed to fail. Specifically, the library’s role in planning entails (Buchanan, 2001): • •

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Employing a full-time DE librarian (or realigning duties so there is a designee for DE students); Working closely with programs offering and planning to offer DE to determine resource needs;

•

•

• •

•

Working closely with IT or Network Operations Personnel to monitor technology needs and resources; Developing a virtual student advisory board to enable communication with the students it must serve remotely; Holding virtual focus groups to hear from students on library services; Participating in regular meetings or contacts with faculty/program representatives to ensure faculty and programmatic needs are being met; and Overseeing accessibility measures so Web pages are accessible for screen readers and other accessibility devices.

Thirdly, new services should emerge out of the unique needs of distance learning students.

eMergIng LIbrAry servIces Libraries must serve distance students on a number of levels: access, instruction, and materials are three critical areas involved in serving remote students. Jones (2003) has suggested that services off-campus must always be equivalent to those on-campus. That doesn’t necessarily mean exactly the same, but it does mean that distance learning students should have access, somehow, to library/learning resources and services, designed to support the specific programs offered. These services/resources should meet the same standard of academic quality as the same courses offered in traditional settings. In the realm of access, libraries must provide easy proxy or other remote access to databases, indexes, e-books, and other tools. Regardless of their location, students should have the same means of access to facilitate their studies. Libraries will need clear, concise, and simplistic instructions to set up and use proxy servers, if

Library Services for Distance Education Students in Higher Education

applicable. Moreover, libraries involved in serving remote students should become more demanding of restrictive vendors to permit easy off-campus access to licensed databases and indexes. The days of on-site use only are gone. Thus, it is critical that libraries have ample user licenses for remote access; students should not be denied access at any time of the day or night because too many users are on a system. Accessibility also means libraries must provide alternative formats for screen-readers, voice recognition software, and other accessibility devices. Libraries must consider the World Wide Web Consortium’s Web Accessibility Initiative (2003) for guidance on these significant issues. Finally, in terms of access, libraries must make themselves available to remote students through a designated toll-free phone line, as well as e-mail address, and synchronous chat room. The phone line and e-mail address can be used to leave procedural questions or report problems, and students should be given a standard turnaround time for responses. Typically, a two-day time frame is acceptable, and the policy for weekend responses should be clearly articulated. A designated phone line should be implemented in conjunction with campus network services so students can call to check on network downtime. Planned network outages for maintenance should be announced well in advance so students can plan accordingly. A synchronous chat room can be used for ready-reference questions, as well as for instructional purposes. Ultimately, remote students need equal access to the library’s services. A typical problem facing institutions offering distance learning revolves around expectations—many expect students to rely on their local libraries or, worse, the Internet for their research materials. Universities and colleges have a responsibility to serve remote students with high-quality library resources, and students must have adequate access to do quality work.

The next area where libraries must revise their policies and procedures is instructional opportunities. Bibliographic Instruction (BI) can be offered to remote students through videotapes that can be checked out of the library and mailed to students; pre-recorded BI sessions can be streamed from the library’s Web pages; and live BI sessions can be broadcast to students, with accompanying chat rooms open to provide students the opportunity to ask questions in real time. Students should also have easily comprehensible instructional materials available for download from the library’s distance education-specific Web page or portal. Where appropriate, tutorials or modules where step-by-step instructions are demonstrated should be developed in html format. Libraries should avoid excessive programming where students will need to download plug-ins or other tools. The bottom line with instructional materials is to keep them simple and easily accessible. This will save the time of students and librarians alike (Buchanan, 2001). Lastly, all materials must be made available to remote students as if they were on-site students. Timely document delivery is the key, and libraries may need to extend their borrowing time for remote students to compensate for delivery times. Serving remote students with materials means that books must be mailed to remote students at their homes or a suitable library; database services must be accessible through electronic means; e-books and e-journals must be adopted where appropriate and feasible; and a stable electronic reserve system must be implemented. Libraries must consider the copyright implications of each of these and work to assure compliance while serving their remote students equitably. Libraries also should consider entering consortial arrangements, which may prove to be the best means by which libraries can serve their remote students with the best array of services and resources. Consortia “open the stacks” of multiple libraries

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to students in valuable ways, while simultaneously assisting libraries struggling with budget cuts and growing costs of resources, especially journals and licenses.

concLusIon University and college libraries are undergoing a dramatic transformation in light of the new roles and responsibilities they must assume to serve the growing number of distance students enrolling in their home institutions. While this discussion provides a starting point from which libraries can begin to serve remote students with services and resources, it should be noted that distance learning library services are a fluid process that will continue to evolve as technologies change and as universities and colleges embrace more distance learning opportunities. The first set of ACRL guidelines, from the 1960s, has certainly changed, and yet, the principles remain the same—serving remote students is a responsibility that must be taken seriously.

reFerences Association of Academic and Research Libraries. ACRL Distance Learning Section Guidelines Committee. (2000). Guidelines for distance learning library services. Retrieved September 20, 2003, from: http://www.ala.org/acrl/guides/ distlrng .html Buchanan, E. (2002). Institutional and library services for distance education courses and programs. In R. Discensa, C. Howard, & K. Schenk (Eds.), The design and management of effective distance learning programs, (pp. 141-154). Hershey, PA: Idea Group Publishing.

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Jones, M. (2003). Getting started: A guide for new distance learning librarians. Retrieved September 12, 2003, from: http://caspian.switchinc. org/~distlearn/guidelines/getting_started.html National Center for Education Statistics. (2001). Distance education at degree-granting postsecondary institutions: 2000–2001. Retrieved September 29, 2003, from: http://www.nces. ed.gov/surveys/peqis/publications/2003017/ Syllabus (2001). Ready or not, they’re here: Library portals. 14(2), 30-31, 38. World Wide Web Consortium. (2003). Web accessibility initiative. Retrieved September 26, 2003, from: http://www.w3.org/WAI/

Key terMs Bibliographic Instruction (BI): Teaching and presenting information on library and information resources in a systematic way to library users/patrons. How to access, use, analyze, and critique information are all parts of BI. Distance Learning Library Services (ACRL Definition): Refers to those library services in support of college, university, or other post-secondary courses and programs offered away from a main campus, or in the absence of a traditional campus, and regardless of where credit is given. These courses may be taught in traditional or non-traditional formats or media, may or may not require physical facilities, and may or may not involve live interaction of teachers and students. The phrase is inclusive of courses in all postsecondary programs designated as: extension, extended, off-campus, extended campus, distance, distributed, open, flexible, franchising, virtual, synchronous, or asynchronous.

Library Services for Distance Education Students in Higher Education

Electronic Reserve: A digitized collection of reading materials, accessible via a Web browser. A common file format is .pdf, read through Adobe Acrobat Reader®.

Portal: A WWW gateway or entrance site for users when they get connected to the Web or that users tend to visit as an anchor site.

This work was previously published in the Encyclopedia of Distance Learning, Volume 3, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 1261-1264, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.4

Perspectives from Multiplayer Video Gamers Jonathan B. Beedle University of Southern Mississippi, USA Vivian H. Wright University of Alabama, USA

AbstrAct

gAMIng And LeArnIng

The purpose of this study is to determine whether multiplayer video gamers perceive that playing video games can increase higher order thinking skills such as motivation, problem-solving, communication, and creativity. Multiplayer video gaming allows participants the opportunity to collectively discuss problems with other players, find solutions, and accomplish objectives. This study was used as a barometer to determine if multiplayer gamers perceived that playing multiplayer games had educational value. This research specifically sought to verify whether multiplayer video gamers perceived that higher-order thinking skills such as motivation, communication, problem solving, and creativity were increased by playing multiplayer video games. The bulk of respondents reported that they somewhat felt there was learning occurring in all of these areas.

Approximately six billion people around the world play computer games (King, 2002), including hundreds of thousands of people who participate in multiplayer online games. Multiplayer gaming is a term used to describe multiplayer online games (consoles and personal computers), video arcade games, and network games (both intranet and Internet). Berger (2002) indicated that most people are surprised when they find out that the video games industry is a bigger business than the film industry. According to the Entertainment Software Association (2003), the video game industry generated $6.9 billion in 2002 in the United States alone, which was up 8% from 2001. In 2000, video gaming was a $17.7 billion global industry (Lange, 2002). In 2000, the computer and video gaming industry grew at more than twice the rate of the U.S. economy (IDSA, 2002).

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Perspectives from Multiplayer Video Gamers

Most likely, gaming will continue to experience such growth. As educators, we have a responsibility to research the use of games, specifically in areas of teaching and learning. Aldrich (2004) proposed that there must be extensive learning taking place during game playing as players learn by participating and practicing until they become successful against others playing the game. This success requires gamers to learn roles, understand direction, and comprehend the complex systems within the game’s structure. The computer’s artificial intelligence (AI) works as a flexible rules-based organizational mechanism to keep the game challenging to the players by presenting problems that players must solve in groups instead of solo. Players are able to construct their own meaning, relationships, character skills, and appearance in many of today’s video game titles. This allows the gamer the opportunity to create and experiment with different configurations and attributes while role-playing characters that might be unlike himself or herself or any other real-life people. Role-playing allows the gamer to immerse himself or herself in a character and allows for experimentation. Video games are increasingly using greater narratives and stories to envelop characters into the storyline. Where books and video games differ is that in many video games there are communities of users who develop programs to mod or add new content and stories to games. Previous research on video games typically focuses on negative aspects surrounding video games like aggressive behavior (Gentile, Lynch, Linder, & Walsh, 2004), violence (Thompson, 2001), and addiction (Chiu, Lee, & Huang, 2004), even though Sherry (2001) performed a meta-analysis of the video gaming literature and found only a minute relationship between hostile behavior and violent video games. It appears that limited research has been conducted concerning gaming and its educational potential. In 1999, the independent research firm

MediaScope found only 16 studies involving video gaming (Thompson, 2002). Most of the research currently available tends to focus on the negative side of games (i.e., addiction) and not on the potential educational benefits of games. According to Griffiths and Davies (2002), online games may have a larger impact on education than traditional single player games. Many online games are roleplaying adventures or other teamwork-related games that require cooperation from several participants to accomplish game objectives. A study for the Pew Internet & American Life Project (Jones, 2003) found that although some instructors and professors believe students can learn from games, 69% of those surveyed indicated they had never had an educational experience in the classroom with video, computer, or multiplayer gaming. In the same survey, one of every five student participants felt that multiplayer computer games helped them make new friends and further develop relationships. Gaming has become much more than a solitary hobby and is, instead, a social activity involving both old and new friends (Jones, 2003). This evolution of gaming into an interactive experience can potentially assist in motivating students and helping to develop problem solving, creative and communication skills. According to Hosen, Solovey-Hosen, and Stern (2002), in order for useful learning to take place, incidental learning and peer interaction must be key elements in the educational process. Incidental learning has been identified as the foremost way language skills are developed and learned (Verspoor & Lowie, 2003). Unintended, or incidental, learning occurs through one’s experiences, including mistakes, successes, and interactions with others (Marsick & Watkins, 1990). Aldrich (2004) indicated that when learners engage with computer simulations, they become engaged in an atmosphere where they possess complete authority and are ruler supreme, such that everything within the context of the game environment is dependent on their actions. These

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Perspectives from Multiplayer Video Gamers

learners become immersed in the relationships they develop within the game, and those relationships are enormously significant. Aldrich (2003) also stated that today’s students need intricacy and that the traditional lecture classrooms are not providing the environments that students need for enhanced scholarship. These computer simulations provide non-linear role-playing environments where the players can immerse themselves in a stirring education environment (Squire, 2003).

the Integration of gaming into education Gaming is a social activity for children, just as playing outside with others is considered a social activity (Durkin, as cited in Colman, 1999; Gros, 2003; Squire, 2003). The games children play also become the conversation of the next day in school (Colman, 1999; Greenfield, 1984; Squire, 2003). These discussions encourage new and creative ideas to be passed around at school (Colman, 1999; Squire, 2003). For example, some games can be modded (the code can be changed) in order to create different endings or new adventures. Modding allows participants the opportunity to become actively engaged in the learning process while constructing their own educational experience. Some games ship with tools that allow the games to be modded easily and without any programming knowledge (Herz, 2002b). Game life can be extended through networked users who create new levels, maps, characters, and any other useful adjustments to enhance games (Herz, 2002a). All of these new aspects of a game can be uploaded to public or private online community sites like GameSpy, which records the number of times the modification has been downloaded. Console systems like the PlayStation II and the XBOX provide some content for download, but additional hardware that connects to a computer like the SharkPort for Playstation II games, and

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the Action Replay for the XBOX, PlayStation II, and GameCube provides user made content that is downloadable onto a memory unit and is often more up-to-date and in demand than the manufacturer’s content. Many games now provide tools that allow the user to make custom mods, so that the game has added value to the consumer. Civilization IV is one such game where all of the design tools used to create the single player mission are given to all game owners. One of the benefits of these tools is that anyone can turn these modules (mods) into an educational opportunity for students by creating a historic simulation, a geology experiment, or an archeological expedition without any programming skills. In fact, educators at MIT have used the Neverwinter Nights tools to create a historical game based on a battle in the Revolutionary War (King, 2003). Games are being released that reviewers claim are more realistic simulations of historical events, like Battlefield 2, which portrays the agonizing conflict of World War II. Unfortunately, rather than using games for such creative uses, those that use computer software in educational settings typically use them for drill-and-skill activities, which are nothing more than workbook-type activities (Greenfield, 1984) and which fail to take advantage of all of the possibilities for learning through games. It is imperative that game developers, academicians, and programmers join together to create educationally sound games that are fun and that motivate students (Gee, 2003; Kirriemuir & McFarlane, 2003). According to Pivec, Dziabenko, and Shinnerl (2003), computer games motivate the gamer to manipulate various patterns and objectives in order to achieve the most desirable outcomes. These favorable outcomes come from a combination of expressive and intellectual feedback and interactions with oneself and other gamers. The new generation of students is accustomed to fast flashing screens like those found on Music Television (MTV) and is comfortable with and exceptionally gifted at multitasking (Wiegel, 2002).

Perspectives from Multiplayer Video Gamers

Multitasking, or parallel processing, is defined by Greenfield (1984) as the processing of knowledge from more than one source concurrently. Jones (2003) found that gaming gives students multitasking opportunities and that gaming is often one of numerous activities in which a student is concurrently engaged. Gros (2003) stated that games provide a field that has the “potential for reaching, motivating, and fully involving learners” (p. 1). Games can provide motivation (Jenkins, 2003), enhance problem-solving skills (Tews, 2001), communication skills (Morton, 1998), and develop creativity through activities such as roleplaying (BECTA, 2001b). According to BECTA (2001a), motivation can foster joint interactions, innovative contests, and teamwork, as well as setup a diversified but equal chance for all participants to be successful.

Motivation Gros (2003) stated that games could potentially fully engage learners and provide motivation. However, King (2003) indicated that software companies have not embraced the educational sector as much as the entertainment side, as only 7% of the total software created for console games is educational in nature. Games can provide built-in motivation for players (Jenkins, 2003). A study conducted by Kirriemuir and McFarlane (2003) found that teachers provided motivation through use of computer games. Dawes and Dumbleton (BECTA, 2001a) found that computer games provide motivation, support teamwork, and develop cognitive abilities. Students use their intellect to solve complex problems and issues within games and try different solutions to find the best possible answer (Jenkins, 2003).

Problem-solving Children are initially attracted to computer games in the same way that they are drawn to certain television shows—through dynamic visual action.

Children learn more information from seeing action, like television, than just by hearing descriptions, like on radio or stereo (Greenfield, 1984). The advantage that computer gaming has over both of these mediums is that it is interactive. Video games are the first interactive medium to combine video and audio components and allow the user to participate in and solve problems (Greenfield, 1984), enjoy adventures, and compete with others. When a game player becomes frustrated with being stuck on a certain level, many times he/she will stop, and come back after a period of time. Going through struggles, and then working through them, is essential if problem solving is to take place (Aldrich, 2004). Gee adds that the real potential of computer games is to get students to think about problem solving and to analyze the complex relationships within gaming environments (The Chronicle of Higher Education, 2003). Multiplayer games can give teachers and instructors an opportunity to observe how students solve problems and collaborate together. According to Tews (2001), games might have more influence on behavior, problem-solving, and social management than any other medium.

communication Gee, as cited on The Chronicle of Higher Education’s Web site (2003), said he sees multiplayer online gaming becoming an entertainment medium that is as well liked as intercollegiate sports. These games allow players the opportunity to not only explore new worlds, but to explore diverse new beings and to increase camaraderie with others across the globe. The importance and fun of online gaming is found, not in the technology, but with the person with whom you are communicating and collaborating (Costikyan, 1999). In other words, fun and significant collaboration happens between people not because of the elaborate interface of the game but because of the richness of the interactions (Manninen, 2003).

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Perspectives from Multiplayer Video Gamers

Multiplayer games are constantly evolving and improving because of technology that improves graphics and the speed of the game. Fifty-five percent of Americans who use the Internet now have high-speed access at home or at work, and 39% of those have high-speed access at home (Horrigan, 2004). Other improvements flow from the creative input of those who are actually playing the games. Multiplayer games allow users to communicate and collaborate in the same game sessions synchronously. The main objective for the players in these types of games is to play with or against someone else (Manninen, 2003). Many of these games allow for in-game text chat, while XBOX Live allows gamers to use a headset and talk back and forth during a game. Others feature game message boards on the Internet. For example, many guilds, clans, or other groups from World of Warcraft, Everquest, Tribes, and other multiplayer video games have their own private message boards, separate from the ones provided on the game sites. Members of the guilds come together to plan strategies for battle, plan for resource gathering, devise community responsibilities, and share stories. These message boards become powerful communication tools that are beneficial to a rewarding gaming and learning experience.

creativity According to A Parent’s Guide to Role-Playing Games, role-playing games tend to develop creative skills as well as allow players the chance to play leading roles and heroes, unlike movies, books, and other forms of entertainment (Hudson, 2003). Games are one of the only instruments or channels that are available to some to actually experience guilt and experiment with various actions. Games based on historical simulations allow the gamer to take on different roles as oppressor or oppressed. Many games now have multiple paths gamers can assume, and each choice

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has significance (Jenkins & Squire, 2003). These consequences allow the gamer to reflect on the morality of their choices. Computer games can affect all players in different ways through play, but it is important for developers to allow players to reflect and act in new ways, outside of their daily routines. Research shows that people tend to learn best when entertained and when they can use their own creative skills to attain complex goals (Carlson, 2003). As a video game player and educational student for the past 25 years or so, my curiosity has fostered an interest in the connection between multiplayer video gaming and critical thinking skills. This study was based on a desire to better understand the feelings and perceptions of colleagues who also play multiplayer video games and to determine if they believe that these games can possibly add to traditional educational curricula through the development of motivational, collaboration, creativity, and problem-solving skills.

descrIPtIon oF study Several impetuses prompted this study. Interest in the topic by the researchers emerged from direct observations of gaming participation (and enjoyment) by colleagues, friends, and family and the perceived potential for educational value in games. The limited amount of research on how multiplayer gaming may benefit learners also pointed to a need for additional research and awareness in this area that appears to be an emerging technological trend in education. For the most part, empirical studies have focused on the negative aspects of computer gaming, like violence (Chang, 2003), anger, and obsession (Griffiths, 1998). Jayakanthan (2002) challenged teachers and game developers to analyze how computer games can be used to improve education. The authors felt that perhaps addressing how gamers perceive themselves improving their skills in areas such as communication, motivation, problem solving,

Perspectives from Multiplayer Video Gamers

higher order thinking, and creativity, would result in a contribution to the current body of research and also point to additional needed research. For the purposes of this research, multiplayer gaming was used to describe multiplayer online games (consoles and personal computers), videogames, as well as local area network (LAN) games. While the study was concerned with who was playing multiplayer video and computer games, the primary goal was to investigate if the multiplayer gamers perceived that multiplayer video and computer games increased and/or promoted skills in motivation, communication, problem-solving, and creativity.

benefits of the study, and a link to the informed consent. Those agreeing to participate completed an online survey that included questions and statements regarding demographic characteristics in the initial part and later a scale to determine personal feelings about motivation, teamwork, problem solving, and creativity, as well as statements used to determine whether these skills are perceived to be increased during game play. The researchers assumed that the participants in the study composed a representative sample of gamers playing multiplayer games. It was further assumed that these participants provided truthful responses on the survey instrument.

MethodoLogy

the survey

The sample for this study was drawn from snowball, networking, or chain sampling (Bogdan & Bicklen, 1982; Meltzoff, 1999). Snowball sampling is a useful method of sampling when the population proposed to be analyzed is complex and difficult to locate (Gall, Gall, & Borg, 2003). Because the entire population of multiplayer gamers numbers in the tens of millions, the researchers could not realistically contact everyone in the population to complete this online survey. Unfortunately, there was no readily available group of participants to study; therefore, this study began by approaching a few gaming guild and online message board members and sending e-mails to several listservs, colleagues, coworkers, and friends asking for their help in disseminating prewritten information concerning the survey. The participants were asked to refer the researchers to other associates within the multiplayer gaming community who might be willing to participate in the study (Bogdan & Bicklen, 1982). Data were collected over a six-week period. Snowball sampling provided the researchers with 346 usable responses during this time period. Included in the e-mail were a brief description of the survey, including the purpose and the

The online survey (see Appendix A) was developed by researching previous studies of gaming and other similar technology topics including distance education test assessment (Hartman, 2001), technostress studies (Weil & Rosen, 1997), and Saphore’s (1999) A Psychometric Comparison of an Electronic and Classical Survey Instrument. The survey assessed the demographics of multiplayer gamers, their Internet usage, and their online game playing time. It also included Likert-type items regarding the gamers’ perceptions of the educational benefits of playing multiplayer games. The Likert scale had responses of 1 through 6, with 1 being strongly disagree and 6 being strongly agree. Several of the statements used negative undertones (i.e., not) in order to detect acquiescence response sets that occur when respondents support statements without regard to the actual content (Gall, Gall, & Borg, 2003). Cronbach’s Coefficient Alpha test was used to indicate if there was internal consistency within each of the response sets. If the overall raw Alpha is above .70, the score is considered to be reliable (Kelley, Cronbach, Rajaratnam, & Glesertnam, 1996; Nunnaly, 1978). When Cronbach’s Coefficient Alpha is high (i.e.,

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Perspectives from Multiplayer Video Gamers

> 70), then the set of statements or questions have high internal reliability and consistency.

dAtA AnALyses demographics More than 83% of the participants in this survey responded that they were male Caucasians with a reported mean age of 25.9. In this study, over 42% of the respondents reported they were 21-30, and almost 30% reported ages within the 10 to 20 year age group. A total of 66% of all the respondents reported household incomes in categories of $35,000 plus. The largest percentage of players (29.5%) indicated that they had completed studies at a four-year college or university, and almost 20% reported they had finished graduate or professional school. Almost 50% of the respondents reported spending more than 20 hours a week on the Internet. Approximately 40% of the respondents reported playing multiplayer games for more than 15 years, and nearly 14% played multiplayer games more than 20 hours a week.

Is gaming Motivational? The means and standard deviations for motivation-focused statements 12, 20, 24, 25, and 26 can be found in Table 1. Scores for the motivation statements (12, 20, 24, 25, and 26) were above the midpoint between strongly disagree (1) and strongly agree (6). The means and standard deviations for the perceptions of motivation skills ranged from 3.8 to 4.7 and from 1.2 to 1.6, respectively. Cronbach’s Alpha was computed at .68, indicating that the motivational items cannot be used as a scale. No significant gain in the Alpha level could be achieved by the deletion of any one item. Therefore, each item was described individually using frequencies and percents (see Table 2). Almost 74% of the respondents agreed that multiplayer games encouraged game players to read guidebooks and other related materials. Responses were more mixed with the statement that indicated multiplayer games encouraged completion of schoolwork or tasks. Fifty-nine percent of the respondents agreed, while 41% disagreed with

Table 1. Means and standard deviations of motivation-related statements Mean

SD

12. Encourages investigation of game’s background

4.6

1.6

20. Encourages reading guide books and associated materials

4.2

1.4

24. Encourages completion of school and/or work tasks

3.8

1.6

25. Encourages learning of rules and intricacies of game

4.6

1.3

26. Encourages discussion about game strategies

4.7

1.2

Table 2. Frequencies and percentages on perceptions of the development of motivational skills in multiplayer games Encourages investigation of game’s background Strongly Disagree

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Frequency 28

Disagree

24

Somewhat Disagree

19

Percent 8.1 6.9 5.5 continued on following page

Perspectives from Multiplayer Video Gamers

Table 2. continued Somewhat Agree

44

12.7

Agree

95

27.5

Strongly Agree

136

39.3

Strongly Disagree

12

3.5

Disagree

38

11.0

Somewhat Disagree

41

11.8

Somewhat Agree

82

23.7

Agree

109

31.5

Strongly Agree

64

18.5

Strongly Disagree

36

10.4

Disagree

46

13.3

Somewhat Disagree

60

17.3

Somewhat Agree

83

24.0

Agree

67

19.4

Strongly Agree

54

15.6

Strongly Disagree

9

2.6

Disagree

27

7.8

Somewhat Disagree

26

7.5

Somewhat Agree

68

19.7

Agree

106

30.6

Strongly Agree

110

31.8

7

2.0

Disagree

15

4.3

Somewhat Disagree

7.2

25

Encourages reading guide books and associated materials

Encourages completion of school and/or work tasks

Encourages learning of rules and intricacies of game

Encourages discussion about game strategies Strongly Disagree

Somewhat Agree

87

25.1

Agree

112

32.4

Strongly Agree

100

28.9

the statement. More than 82% of the respondents felt that multiplayer games motivated players to learn the intricacies and rules of the game, and more than 86% of the respondents perceived that multiplayer games encouraged discussions about strategies and planning.

can gaming Promote communication? The means and standard deviations for the communication-focused statements 13, 16, 22, 28, and 33 can be found in Table 3. Scores for all

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communication statements range from strongly disagree (1) to strongly agree (6). The means and standard deviations for the perceptions of communication skills ranged from 2.2 to 4.7 and from 1.3 to 1.5, respectively. Cronbach’s Alpha was computed to be .80, indicating good reliability as a scale. Deletion of item 33 would have raised the Alpha minimally to .81. Therefore, scores of all five communication statements were summed for a total communication score. The mean of the communication scale score was 17.2 with a standard deviation of 3.0. Scores ranged from 6 to 26 and were relatively normally distributed. Skewness was found to be -.62, and the kurtosis was .90. Each item was described individually using frequencies and percents before reverse coding (see Table 4). The majority of respondents reported they felt that multiplayer games encouraged communication through interaction and also allowed communication with diverse individuals.

can gaming Promote Problem solving? The means and standard deviations for problemsolving-focused statements of 11, 18, 21, 23, and 30 can be found in Table 5. Scores for all problem-solving statements were above the midpoint between strongly disagree (1) and strongly agree (6). The means and standard deviations for the perceptions of problem-solving skills ranged from 3.8 to 4.4 and from 1.3 to 1.4, respectively. Cronbach’s Alpha was computed to be .82, indicating good reliability as a scale. The deletion of any item would not have lowered the Alpha under .82. Scores of all five problem-solving statements were summed for a total problem-solving score. The mean of the problem-solving scale score was 20.7 with a standard deviation of 5.1. Scores range from 6 to 26 and were relatively normally distributed. Skewness was found to be -.55, and

Table 3. Means and standard deviations of communication-related statements Mean

SD

13. Does not promote development of communication skills

3.0

1.5

16.

Helps develop ability to communicate with others

3.5

1.5

22. Interaction develops interpersonal communication

3.8

1.4

28. Promotes communication with diverse individuals

4.7

1.4

33.

2.2

1.3

Does not encourage communication

Table 4. Frequencies and percentages on perceptions of the development of communication skills in multiplayer games Frequency

Percent

Does not promote development of communication skills

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Strongly Disagree

58

16.8

Disagree

107

30.9

Somewhat Disagree

65

18.8

Somewhat Agree

53

15.3

Agree

38

11.0

Strongly Agree

25

7.2 continued on following page

Perspectives from Multiplayer Video Gamers

Table 4. continued Helps develop ability to communicate with others Strongly Disagree

46

13.3

Disagree

47

13.6

Somewhat Disagree

68

19.7

Somewhat Agree

82

23.7

Agree

64

18.5

Strongly Agree

39

11.3

21

6.1

Interaction develops interpersonal communication Strongly Disagree Disagree

52

15.0

Somewhat Disagree

56

16.2

Somewhat Agree

113

32.7

Agree

59

17.1

Strongly Agree

45

13.0

Strongly Disagree

14

4.0

Disagree

25

7.2

Somewhat Disagree

24

6.9

Somewhat Agree

58

16.8

Promotes communication with diverse individuals

Agree

96

27.7

Strongly Agree

129

37.3

Does not encourage communication Strongly Disagree

133

38.4

Disagree

96

27.7

Somewhat Disagree

57

16.5

Somewhat Agree

33

9.5

Agree

20

5.8

Strongly Agree

7

2.0

Table 5. Means and standard deviations of problem-solving-related statements Mean

SD

11. Encourages joint problem-solving

4.4

1.3

18. Encourages consideration of options and consequences

4.2

1.4

21. Promotes exposure to new ideas

4.4

1.3

23. Promotes the development of problem-solving skills

3.8

1.4

30. Encourages thinking outside of the box

3.9

1.3

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Perspectives from Multiplayer Video Gamers

the kurtosis was -.05. Each item was described individually using frequencies and percents (see Table 6). All of the mean scores were above the median for the statements regarding problem solving. Cronbach’s Alpha was computed at .82, giving the problem-solving set of statements high reliability as a scale. Participants in the survey reported that they felt multiplayer gaming encouraged joint problem solving, promoted exposure to new ideas, and encouraged players to consider multiple options and scenarios. Shotton (1989) pointed out that video games can increase the rate of the gamer’s neural pathways thereby speeding up the decisionmaking processes. Often in school coursework or work assignments, people are instructed by teachers or superiors of one way to complete the task. Frequently, this recommendation is assumed to be the best choice for completing the assign-

ment, and the student or worker is not given the chance to look for other, possibly better options and explore other avenues.

can gaming Promote creativity? The means and standard deviations for creativity-focused statements 17, 27, 29, 34, and 35 can be found in Table 7. Scores for all creativity statements were between strongly disagree (1) and strongly agree (6). The means and standard deviations for the perceptions of creativity skills ranged from 2.9 to 4.2 and from 1.4 to 1.5, respectively. Cronbach’s Alpha was computed to be .81, indicating good reliability as a scale. Deletion of item 17 would have raised the Alpha to .84. Therefore, scores of all five creativity statements were summed for a total creativity score. The

Table 6. Frequencies and percentages on perceptions of the development of problem-solving skills in multiplayer games Frequency

Percent

Strongly Disagree

9

2.6

Encourages joint problem-solving Disagree

22

6.4

Somewhat Disagree

45

13.0

Somewhat Agree

103

29.8

Agree

97

28.0

Strongly Agree

70

20.2

14

4.0

Disagree

35

10.1

Somewhat Disagree

40

11.6

Somewhat Agree

94

27.2

Agree

97

28.0

Strongly Agree

66

19.1

Strongly Disagree

5

1.4

Disagree

38

Encourages consideration of options and consequences Strongly Disagree

Promotes exposure to new ideas 11.0 continued on following page

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Perspectives from Multiplayer Video Gamers

Table 6. continued Somewhat Disagree

34

9.8

Somewhat Agree

89

25.7

Agree

98

28.3

Strongly Agree

82

23.7

Strongly Disagree

27

7.8

Disagree

40

11.6

Somewhat Disagree

60

17.3

Somewhat Agree

106

30.6

Promotes the development of problem-solving skills

Agree

75

21.7

Strongly Agree

38

11.0

Encourages thinking outside of the box Strongly Disagree

21

6.1

Disagree

29

8.4

Somewhat Disagree

66

19.1

Somewhat Agree

110

31.8

Agree

81

23.4

Strongly Agree

39

11.3

mean of the creativity scale score was 17.4 with a standard deviation of 3.3. Scores range from 6 to 26 and were relatively normally distributed. Skewness was found to be -.15, and the kurtosis was -.08. Each item was described individually using frequencies and percentages before reverse coding (see Table 8). Almost 69% of the respondents disagreed with the statement that multiplayer games do not encourage transferable creative skills, and more than 70% believed that multiplayer games inspired creativity. Over 56% of the respondents agreed that multiplayer games encouraged the creation of artistic works, but almost 44% disagreed. The largest percentage of respondents (26.9%) somewhat agreed that multiplayer games encouraged the creation of imaginative works, but 21.7% of the respondents somewhat disagreed. Only 32% of the respondents thought that multiplayer games do not promote creative skills. Two statements in the creativity statement set were negatively drawn and included the word “not”

to help protect against acquiescence response sets. There were no acquiescence response sets found in this set of statements. Reverse coding was completed on this set to determine Cronbach’s Alpha, which was computed to be .81, giving the set good reliability.

Ideas for the classroom Video gaming, especially the multiplayer variety, allows the participant the chance to interact with both the computer AI and other players. This lets learners shroud themselves inside the game world. One possible idea for the classroom is to have educators ask students to design new worlds or attempt to recreate past events. Other groups within the classroom could then create the objectives and design rules and objectives for the class. These activities would promote basic computer skills and advanced skills such as programming, scripting, and design. Educators could help facilitate the project to ensure that all 1859

Perspectives from Multiplayer Video Gamers

Table 7. Means and standard deviations of creativity-related statements Mean

SD

17. Does not develop transferable creative skills

2.9

1.4

27. Inspires creativity

4.2

1.4

29. Encourages creation of artistic works

3.7

1.5

34. Promotes creation of imaginative works

3.7

1.5

35. Does not promote creative skills

3.0

1.5

Table 8. Frequencies and percentages on perceptions of the development of creativity skills in multiplayer games Frequency

Percent

Does not develop transferable creative skills Strongly Disagree

59

17.1

Disagree

102

29.5

Somewhat Disagree

76

22.0

Somewhat Agree

56

16.2

Agree

43

12.4

Strongly Agree

10

2.9

Inspires creativity Strongly Disagree

13

3.8

Disagree

38

11.0

Somewhat Disagree

52

15.0

Somewhat Agree

83

24.0

Agree

77

22.3

Strongly Agree

83

24.0

Encourages creation of artistic works Strongly Disagree

34

9.8

Disagree

47

13.6

Somewhat Disagree

68

19.7

Somewhat Agree

90

26.0

Agree

61

17.6

Strongly Agree

46

13.3

Strongly Disagree

24

6.9

Disagree

52

15.0

Somewhat Disagree

75

21.7

Promotes creation of imaginative works

Somewhat Agree

93

26.9

Agree

68

19.7

Strongly Agree

34

9.8

68

19.7

Does not promote creative skills Strongly Disagree

continued on following page

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Perspectives from Multiplayer Video Gamers

Table 8. continued Disagree

75

21.7

Somewhat Disagree

91

26.3

Somewhat Agree

49

14.2

Agree

33

9.5

Strongly Agree

30

8.7

students were communicating properly, equally solving problems, developing teamwork skills, and learning to build off of each other’s creativity. Motivation is the fun part, and if everyone is involved in some aspect from the evaluation, design, development, implementation, or assessment then these incidental skills should develop in ways not assessed in previous research. Educators could use games and communication software to encourage peer discussion about game strategies, mechanics, storylines, morality, economics, or politics. Educators could also use games in teacher training and professional development (Thiagarajan & Parker, 1999). Educators could use multiplayer games as a fun way to encourage students to spend time playing with a diverse group of students and to further multicultural studies. Multiplayer games seem to bring people from all over the world together to socialize and interact with each other. Further studies could be conducted at gaming conventions and shows around the world and could incorporate a more qualitative approach. This would allow the researchers to verify participants’ demographic information and to delve deeper into user experiences, feelings, interpretations, and motivations as they relate to multiplayer games. An inquiry into the nationality of the gamer should also be included in any future research. Gaming is an international endeavor and business, and a question regarding nationality should have been included in this questionnaire.

concLusIon And PotentIAL With the increase of video game sales, and the corresponding increase in the number of people playing these games (IDSA, 2002), it is of great importance to understand why multiplayer video games are being played and what educators can learn from multiplayer gamers. Many respondents reported they at least somewhat believed multiplayer games encouraged, promoted, and inspired creative thinking. Gamers play games to have fun and to be challenged (IDSA, 2002). Games are different from movies because of the interactive experience, but many are incorporating cinematic features within these games. Creativity helps users develop characters more deeply in role-playing adventures and solve problems that are sometimes built around the uniqueness of the game’s premise. Games also spur gamers to create modifications to the game such as new content, modules, characters, scripts, and items. Game developers also get many new ideas from gamers to incorporate in expansion packs and new games and encourage gamers to use the toolsets they provide to develop the games further. Many multiplayer video games require users to utilize high-speed connections, so that most people share the same experiences during games. Low bandwidth, referred to as lag, tends to pull the other players’ experiences down. For educational courses, more interactive multimedia

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Perspectives from Multiplayer Video Gamers

projects can be planned if there is a greater trend toward high-speed connections. This study should be used as a point of reference for future research into multiplayer gaming and learning. There is much that can be found within games, such as the structure, organization, dialogue, and basic programming that can benefit students in areas such as math, reading, social studies, and science. The use of video games within curricula could initially be timeconsuming, especially for those educators who are not familiar with gaming. Familiarity with different genres, as well as the construction of video games, could well benefit instructors who would like to use games as part of their courses. There is much more to learn in the area of gaming research, but from this research it can be seen that there are educational benefits in areas of motivation, communication, problem-solving, teamwork, and creativity skills. To really take advantage of this medium, researchers should further study multiplayer games so that educators across the globe can take advantage of the unique educational attributes multiplayer video games can bring to the classroom.

reFerences Aldrich, C. (2004). Simulations and the future of learning: An innovative (and perhaps revolutionary) approach to e-learning. San Francisco: Pfeiffer. BECTA. (2001a). Computer games in education project. Retrieved January 26, 2005, from http://www.becta.org.uk/research/research. cfm?section=1&id=2846. BECTA. (2001b). What aspects of games may contribute to education? Retrieved November 6, 2003, from http://www.becta.org.uk/page_documents/research/ cge/aspects.pdf.

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Berger, A. A. (2002). Video games: A popular culture phenomenon. New Brunswick: Transaction Publishers. Bogdan, R. C., & Biklen, S. K. (1982). Qualitative research for education: An introduction to theory and methods. Newton, MA: Allyn & Bacon. Carlson, S. (2003). Can Grand Theft Auto inspire professors? Educators say the virtual worlds of video games help students think more broadly. Retrieved October 16, 2003, from http://chronicle. com/prm/weekly/v49/i49/49a03101.htm. Chang, A. (2003). Video games could be good for you. Retrieved October 15, 2003, from http://msnbc.com/m/pt/printthis_main. asp?storyID=919010. Chiu, S., Lee, J., & Huang, D. (2004). Video game addiction in children and teenagers in Taiwan. CyberPsychology & Behavior, 7(5), 571-581. Colman, A. (1999). Computer games. Youth Studies Australia, 18(1), 10. Costikyan, G. (1999). Why online games suck (and how to design ones that don’t). Retrieved November 4, 2003, from http://www.costik. com/onlinsux.html. Entertainment Software Association. (2003). Top ten industry facts. Retrieved October 10, 2003, from http://www.theesa.com/pressroom.html. Gall, M. D., Gall, J. P., & Borg, W. R. (2003). Educational research: An introduction (7th ed.). Boston: Allyn and Bacon. Gee, J. P. (2003). What video games have to teach us about learning and literacy. New York: Palgrave Macmillan. Gentile, D., Lynch, P., Linder, J., & Walsh, D. (2004). The effects of violent video game habits on adolescent hostility, aggressive behaviors, and school performance. Journal of Adolescence, 27(1), 5-22.

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Greenfield, P. M. (1984). Mind and media: The effects of television, video games, and computers. Cambridge: Harvard University Press. Griffiths, M. D. (1998). Violent video games and aggression: A review of the literature. Aggression and Violent Behavior, 4(2), 203-212. Griffiths, M. D., & Davies, M. N. (2002). Excessive online computer gaming: Implications for education. Journal of Computer Assisted Learning, 18(3), 379-380. Gros, B. (2003). The impact of digital games in education. Retrieved October 17, 2003, from http:// www.firstmonday.dk/issues/issue8_7/xyzgros/. Hartman, J. A. (2001). AFTY-R: Psychometric properties and predictive value for academic performance in online learning. Doctoral dissertation, University of Alabama at Tuscaloosa. Dissertation Abstracts International, 62, 3019. Herz, J. C. (2002a). Gaming the system: Multiplayer worlds online. In L. King (Ed.), Game on: The history and culture of videogames (pp. 86-97). New York: Universe Publishing. Herz, J. C. (2002b). Gaming the system: What higher education can learn from multiplayer online worlds. Retrieved February 11, 2004, from http://www.educause.edu/ir/library/pdf/ffpiu019. pdf. Horrigan, J. B. (2004). Broadband penetration on the upswing: 55% of adult Internet users have broadband at home or work. Retrieved April 24, 2004, from http://www.pewinternet.org/reports/ pdfs/PIP_Broadband04.DataMemo.pdf. Hosen, R., Solovey-Hosen, D., & Stern, L. (2002). The acquisition of beliefs that promote subjective well-being. Journal of Instructional Psychology, 29(4), 231-244. Hudson, C. (2003). A parent’s guide to role-playing games. Retrieved October 16, 2003, from

http://www.geocities.com/TimesSquare/Dungeon/1257/parents2.html. IDSA. (2002). Essential facts about the computer and video game industry. Retrieved November 6, 2003, from http://www.theesa.com/IDSABooklet.pdf. Jayakathan, R. (2002). Application of computer games in the field of education. Electronic Library, 20(2), 98-102. Jenkins, H. (2003). How should we teach kids Newtonian physics? Simple. Play computer games. Retrieved November 4, 2003, from http:// www.technologyreview.com/ articles/print_version/wo_ jenkins032902.asp. Jenkins, H., & Squire, K. (2003, November). Meaningful violence: How to make sense out of senseless acts. Computer Games, 156, 108. Jones, S. (2003). Let the games begin: Gaming technology and entertainment among college students. Retrieved November 7, 2003, from http:// www.pewinternet.org/reports/pdfs/PIP_College_Gaming_Reporta.pdf. Kelley, T., Cronbach, L., Rajaratnam, N., & Glesertnam, G. (1996). Reliability. In A. Ward, M. Murray-Ward, & H. Stoker (Eds.), Education measurement: Origins, theories, and explications. Vol. 1: Basic concepts and theories (pp. 245-286). Lanham, MD: University Press of America. King, B. (2003). Educators turn to games for help. Wired News. Retrieved October 17, 2003, from http://www.wired.com/news/ games/0,2101,59855,00.html. King, L. (2002). Introduction. In L. King (Ed.), Game on: The history and culture of video games (pp. 8-19). New York: Universe Publishing. Kirriemuir, J., & McFarlane, A. (2003, November). Use of computer games and video games in the classroom. Paper presented at the DIGRA 2003 Conference, Level up, Holland.

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Lange, A. (2002). Report from the PAL zone: European games culture. In L. King (Ed.), Game on: The history and culture of videogames (pp. 46-55). New York: Universe Publishing. Manninen, T. (2003). Interaction forms and communicative actions in multiplayer games [Electronic version]. The International Journal of Computer Game Research, 3(1), Article 031. Retrieved November 6, 2003, from http://www. gamestudies. org/ 0301/manninen. Marsick, V. J., & Watkins, K. (1990). Informal and incidental learning in the workplace. New York: Routledge. Meltzoff, J. (1999). Critical thinking about research: Psychology and related fields. Washington, DC: American Psychological Association. Morton, D. (1998). Study sounds alarm over video game use: Isolation, helplessness, characterize the world of heavy players, study finds. Retrieved April 24, 2004, from http://www.sfu.ca/mediapr/ sfnews/1998/April2/kline.html. Nunnaly, J. (1978). Psychometric theory. New York: McGraw-Hill. Pivec, M., Dziabenko, O., & Shinnerl, I. (2003, July 2-4). Aspects of game-based learning. In Proceedings of the Third International Conference on Knowledge Management (I-KNOW ‘03), Graz, Austria (pp. 216-225). Retrieved November 11, 2003, from http://www.unigame.net/html/IKnow_GBL-2704.pdf. Saphore, R. B. (1999). A psychometric comparison of an electronic and classical survey instrument. Doctoral dissertation, University of Alabama at Tuscaloosa. Dissertation Abstracts International, 60, 3976.

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Sherry, J. L. (2001). The effects of violent video games on aggression: A meta-analysis. Human Communication Research, 27(3), 409-431. Shotton, M. (1989). Computer addiction? A study of computer dependency. London: Taylor and Francis. Squire, K. (2003). Video games in education. International Journal of Simulations and Gaming, 2(1), 49-62. Tews, R. R. (2001). Archetypes on acid: Video games and culture. In J. Wolf (Ed.), The medium of the video game (pp. 169-182). Austin: University of Texas Press. The Chronicle of Higher Education. (2003). Video games in the classroom. Retrieved August 27, 2003, from http://chronicle.com/colloquylive/2003/08/video/. Thiagarajan, S., & Parker, G. (1999). Teamwork and teamplay: Games and activities for building and training teams. San Francisco: JosseyBass. Thompson, C. (2002). Violence and the political life of videogames. In L. King (Ed.), Game on: The history and culture of video games (pp. 2231). New York: Universe Publishing. Thompson, K. (2001). Violence in E-rated video games. Journal of the American Medical Association, 286(5), 591-598. Verspoor, M., & Lowie, W. (2003). Making sense of polysemous words. Language Learning, 53(3), 547-586. Weigel, V. B. (2002). Deep learning for a Digital Age: Technology’s untapped potential to enrich higher education. San Francisco: Jossey-Bass. Weil, M. M., & Rosen, L. D. (1997). Technology: Coping with technology @ work @ home @ play. New York: John Wiley & Sons.

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APPendIx A SURVEY SECTION I Please select the most appropriate answer to each question. You must be at least 18 years of age or have your legal guardian’s permission to participate in this study. 1.

Type your age in years. _____

2.

What is your gender? Female Male

3.

What is the highest level of education you completed? Kindergarten through 12th grade High school graduate or GED Junior, community or technical college Four-year college or university Graduate or professional school

4.

What is your annual household income? Under $20,000 per year $20,001 - $35,000 per year $35,001 - $50,000 per year $50,001 - $80,000 per year $80,001 or greater per year Don’t know

5.

Which category best describes your ethnicity? Please select one. African-American or of African descent Asian-American or of Asian descent Caucasian or of European descent Hispanic-American or of Latin descent Native American Other _________

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SECTION II Please select the answer that best describes personal technology related habit. For purposes of this survey, multiplayer games refer to both video and computer games. 6.

How much time do you spend each week on the Internet? Please select one. 0 - 5 hours 6 - 10 hours 11 - 15 hours 16 - 20 hours More than 20 hours

7.

How long have you been playing video or computer games? Please select one. 0 - 1 year 2 - 5 years 6 - 10 years 11 - 15 years More than 15 years

8.

How much time do you spend each week playing multiplayer video or computer games? Please select one. 0 - 5 hours 6 - 10 hours 11 - 15 hours 16 - 20 hours More than 20 hours

9.

What type(s) of multiplayer games do you play? Please select all that apply. Role-playing (i.e., Neverwinter Nights, Everquest, Star Wars Galaxies) Strategy (i.e., Age of Empires II, Civilization III, Cossacks) Sports (i.e., Madden, ESPN, XSN sports title) First-Person Shooters (i.e., Quake, Doom, Halo, Rainbow 6) Simulations (i.e., Sims, Microsoft Flight Simulator) Card and Board (i.e., Checkers, Spades, Cribbage, Monopoly, Scrabble) Other. Please specify. __________

10. Which platform(s) do you use to play most of your multiplayer games? Please select all that apply. PC Mac

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XBOX PlayStation II Game Cube Game Boy or Game Boy Advance PDA Mobile Telephone Ngage Dreamcast Other __________ SECTION III For each of the following items please select the answer that best represents how much you agree or disagree with the statement. The numbers correspond to the following responses: (1) Strongly Disagree; (2) Disagree; (3) Somewhat Disagree; (4) Somewhat Agree; (5) Agree; and (6) Strongly Agree. 11.

I think that playing multiplayer games helps me learn to work with others to solve problems or accomplish goals. Strongly Disagree 1 2 3 4 5 6 Strongly Agree

12. I think that playing multiplayer games encourages me to look to web sites with related materials to find more information about the game’s background. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 13. I do not think that playing multiplayer games encourages me to develop my communication skills. 6 Strongly Agree Strongly Disagree 1 2 3 4 5 14. I think that it is easier to reach a new level or complete a mission in a multiplayer game when I am working with others. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 15. I think I succeed at multiplayer games without cooperating with other players. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 16. I think that my ability to express my thoughts and ideas is improved through playing multiplayer games. Strongly Disagree 1 2 3 4 5 17.

6

Strongly Agree

I do not think that I use any of the creative skills I use in multiplayer games in my everyday life. Strongly Disagree 1 2 3 4 5 6 Strongly Agree

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18. I think playing multiplayer games makes me think about options and their consequences in order to be successful. 6 Strongly Agree Strongly Disagree 1 2 3 4 5 19.

I think playing with others in multiplayer games makes it easier for me to collaborate with peers at work or school. 6 Strongly Agree Strongly Disagree 1 2 3 4 5

20. I think that the competition of multiplayer games encourages me to try harder to succeed at the game, including seeking hints in guidebooks or other sources. 6 Strongly Agree Strongly Disagree 1 2 3 4 5 21.

I think that multiplayer games expose me to ideas and approaches to problems that are different from my own ideas and approaches. 6 Strongly Agree Strongly Disagree 1 2 3 4 5

22. I think that interacting with others in multiplayer games helps me develop my ability to communicate with others. 6 Strongly Agree Strongly Disagree 1 2 3 4 5 23. I think that I learn how to solve problems through playing multiplayer games. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 24. I think that my desire to have free time in which to play multiplayer games motivates me to complete tasks at work or school. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 25. I think that I am enthusiastic about learning the rules of controls of a multiplayer game when I first begin to play. 6 Strongly Agree Strongly Disagree 1 2 3 4 5 26. I think that playing multiplayer games encourages me to talk with other players about game strategies. 6 Strongly Agree Strongly Disagree 1 2 3 4 5 27.

I think that the imagination shown by the graphics and stories within multiplayer games inspires my own creativity. 6 Strongly Agree Strongly Disagree 1 2 3 4 5

28. I think that playing multiplayer games provides me the opportunity to communicate with a diverse group of individuals. 6 Strongly Agree Strongly Disagree 1 2 3 4 5

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29. I think the authors, coders, and designers of multiplayer games inspire me to create artistic works. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 30. I think that the situations encountered in multiplayer games force me to think outside my comfort zone to find solutions. 6 Strongly Agree Strongly Disagree 1 2 3 4 5 31.

I think multiplayer games are isolating. Strongly Disagree 1 2 3 4 5 6 Strongly Agree

32. I think that I am successful if I can help another player succeed within the multiplayer game. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 33. I think that communication with others is rare during multiplayer games. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 34. I think that multiplayer games lead me to create my own imaginative works. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 35. I do not think that playing multiplayer games has any effect on my creative skills. Strongly Disagree 1 2 3 4 5 6 Strongly Agree 36. How do you think games can benefit education? __________________________________ ____________________________________________________________________ ____________________________________________________________________ ____________________________ 37.

How did you hear about this study? ____________________________________

This work was previously published in Games and Simulations in Online Learning: Research and Development Frameworks, edited by D. Gibson, pp. 150-174, copyright 2007 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.5

Game Mods:

Customizable Learning in a K16 Setting Elizabeth Fanning The University of Virginia, USA

AbstrAct

IntroductIon

A game mod describes a modification within an existing commercial computer-based game that has been created by a user. By game modding, a user can participate in the creative process by taking the setting of his or her favorite game and customizing it for entertainment purposes or to convey information. For years, commercial computer-based game developers committed considerable resources toward preventing users from hacking into or hijacking their games. Now several computer-based game developers provide editors with their products to encourage users to create content and to allow educators, for instance, to take advantage of the benefits and production quality of commercial computer games in order to create customized instruction. This chapter focuses on mainstream, accessible games with straightforward modding tools that easily can be integrated into a learning environment.

what do computer games have to do with Learning? Anyone who thinks there is a difference between education and entertainment doesn’t know the first thing about either. (Marshall McLuhan, Communications Theorist) Learning theorists from Piaget to Jonassen contend that profound, lasting learning culminates from the participant exploring, discovering, and interacting with his or her environment and culture in order to assimilate and create new meaning within his or her personal schema (Donaldson, 1984; Jonassen, 1988; Satterly, 1987). For a computer-based, constructivist learning environment, the quality of the user’s learning experience is vested in the extent to which the computer responds in a way that is consistent with the learner’s information processing needs (Jonassen, 1988). The level of the user’s interactivity and consequent sense of empowerment and

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Game Mods

control over his or her learning experience will affect the extent to which surface or deep learning will occur (Jonassen, 1988). Studies using computer games in learning settings, particularly the classroom, indicate that while student test scores may not improve significantly from using games, students do learn on a more profound level and are able to describe, for instance, why an answer to a test question is correct or incorrect (Squire, 2002). While this outcome appears marginal at this point, it is worth exploring what computer games do afford a user empowerment, motivation, insight, and engagement (Gee, 2003; Prensky, 2001). How might one harness and channel a game’s learning opportunities into the classroom in a way that empowers self-directed learning and the development of conceptual tools? Recognizing that emerging and even current learners most likely have grown up with a mouse in hand or at least developed considerable schema shaped by interacting with computer-based technology, computer games have gone beyond satiating the game-playing public as a dalliance or source of entertainment and have evolved into a meaningful, socially expressive medium, a platform for discussion and reflection that continues after the game session is over and outside the context of the game. However, the resources needed to create a commercial computer-based game are formidable, in many cases requiring the expertise of game designers, computer artists, and programmers, not to mention robust marketing support. Many have endeavored to create educational games for the classroom and workplace, but most have neither the resources nor the expertise to match the production quality and comprehensiveness of content characterized by more mainstream, commercial, computer-based games. Given these requirements and constraints, how might one harness and channel a game’s learning opportunities into the classroom? Perhaps game mods could provide a means for educators to use the quality and basic format of commercial

games to create customized instruction for enabling students to create meaning in their own learning. A game mod describes a modification within an existing commercial computer-based game that has been created by a user. To do this, a user works with the game’s existing assets to alter a small segment of the game’s graphics, text, audio, or interactivity. In effect, a user can participate in the creative process by taking the setting of his or her favorite game and customizing it for entertainment purposes or to convey information.

Mods: rules of the game and terms of engagement For years, commercial computer-based game developers committed considerable resources toward preventing users from hacking into or hijacking their games (Holt, 2004); however, and perhaps in keeping with the spirit of gameplay, many game users considered these prohibitive efforts simply another challenge to master within the game environment (Holt, 2004). Now, several computer-based game developers are providing editors with their products to encourage users to create content (Marriott, 2003; Prensky, 2003). It is important to note that these editors do not reveal the entire code but only enough for the user to create several levels of modification (Holt, 2004; Marriott, 2003; Prensky, 2003). Why do commercial game developers even offer this much? According to Chaptman (2004), Holt (2004), and Prensky (2003): •

•

Within the game cultures, cool game companies encourage modding; they are more respected for their responsiveness and their show of confidence in their users’ technical competencies. The game developers are ensured continued play and sales, especially as the user can make the game continue to expand to more levels.

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In keeping with the gaming culture, a game’s modding capability comes with several rules spelled out in the license that comes with the game’s software: • • •

The modder cannot make money off of their mods. The modder needs to own the base games. The modder cannot combine mods from different games into one mod.

To what extend does modding serve the modder? According to Holt (2004) and Prensky (2003): • •

•

The mods are free to make. Modding provides a way for gamers to make their own games (“I can do it better”). The modder creates a new free game and extends gameplay of a game that otherwise may satisfy for two to three weeks. The modder can upload their mod to a modder’s forum to showcase their work and to participate in a large community of workers, fans, and game players.

Note, too, that modding can be done at different levels, from a simple change to the appearance of a character to a more complex creation of a completely new setting, complete with AI. For the purposes of classroom use, however, what follows is an examination of how to bring modding into the classroom as a creative learning exercise without the encumbrance of complicated prerequisite technical skills.

tools for the classroom Two popular computer games—Civilization, created by Sid Meiers and published by Firaxis software; and Electronic Arts’ The Sims, created by Will Wright—provide easy-to-use, easy-to access tools for customizing gameplay. Civilization is considered the penultimate commercial

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educational game (Squire, 2004). Played alone or with several players, Civilization is a geographically oriented and world-history, fact-driven game. Its gameplay requires the user to use maps and resources to manage the development of a civilization, based on the limits and opportunities presented by topography, resources, cultural affectation, and interactions with surrounding cultures (Squire, 2001, 2002, 2004). By comparison, The Sims is another popular but less educational game that allows user customization as well, but its outcomes are shaped less by geographic and political landscape and more by social considerations (Squire, 2001, 2004). The Sims often is described as less of a game and more of a simulation (hence, its name) or a toy, in that it is not designed around a more concrete goal (Fortugno & Zimmerman, 2005). Others argue that the goal of The Sims is to succeed in keeping the Sims going (Wright, 2003). Regardless of the arguments, the game does suggest a potential for application beyond simply engaging the user in a digital dollhouse. The Sims already has been modded for use in language curricula (Squire, 2004). Instructors have gone into the code layer to change the prompting language from English to French, for instance, to encourage incidental language learning via the gameplay experience. Others have taken its modding capabilities even further and into exciting new directions by creating public service advertisements1 and replications of music videos2 with The Sims’ video capture tools.

building a Plantation To see how game modding can be used in a classroom setting, we used the popular, more flexible game The Sims, created by Electronic Arts. The Sims’ game engine also allows and encourages the user to create buildings as simple as a modest bungalow, for example, or as complex as a historical landmark, such as Thomas Jefferson’s Monticello. We endeavored to create a virtual

Game Mods

Monticello (Figure 1) to see how far we could go with The Sims” game engine to create a mod based on the structure and its social interaction and then to determine the extent to which the final product might foster motivation, game literacy, or media dialogue. We spent 20 hours using The Sims’ tools to create Monticello, based on research of the plantation’s blueprints and house plans as well as the historic significance of the time in which it was built. While The Sims has an engine that allows for elaborate construction, it did present some limitations: •

•

Pop art and modern home furnishings that the user can access to decorate the structure, thus interfering with the historical integrity of the house. Timed programming variables that can be difficult to alter. At one point, a school bus drove by and took Patsy Jefferson with it. It was necessary to wait until another gameplay session in order for Patsy to return (by bus).

To customize a mod further, a user can venture, as we did, into the online community proliferating around The Sims in order to find tools for importing furniture. Some of these tools are created by modders not affiliated with The Sims who often expanded on the existing Sims editor code to enable more elaborate modifications (s 2). Similarly, to create more real-life, Monticellobased characters, Sims Creator (Start/Programs/ Maxix/Sims/Sims Creator) was used to create a specific type of person, from personality attributes to physical appearance and gender (Figure 3).

reactions: the Learner To begin our study, we opened the mod to a group of four high school students. Two of them were regular Sims players. At first, they wanted to sit back and watch, hoping to observe a historical reenactment of what might have taken place in the plantation they all had visited in person at least once. As is typical of female Sims players (Chu, Heeter, Egidio, & Mishra, 2004), the girls were more interested in what people in the house were

Figure 1. Virtual Monticello

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Figure 2. Jefferson’s revolving bookstand

Figure 3. Peter Fosset description

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doing and how they got along. Sally Hemmings worked on the first floor. Another cooked in the basement. A butler wandered between the entryway and Thomas Jefferson’s bedroom, where Jefferson stood pensively. Eventually, the cook caught on fire, and the girls used their Sims skills to attempt to save the cook—despite their efforts, death intervened. In time, the focus group also explored the mischief that players typically get into by fooling the game and by directing characters to behave badly to see what would happen (perhaps this is the digital-age version of teasing the cat or a prank phone call). Mischief accomplished or not, the focus group collectively expressed interest in accessing the blueprints for the plantation’s gardens so that they could recreate them within the mod. Hence, despite the shortcomings of our virtual Monticello, our focus group validated Gee (2003) and answered the call that beckoned from the computer game: to pursue self-directed learning by solving complex problems. Such self-directed exploration to go beyond the boundaries

of one’s current understanding to create and assimilate meaning is also, of course, rich in constructivist learning implications (Jonassen, 1992; Satterly, 1987).

reactions: the classroom teacher We then presented the Monticello mod to five middle school and high school teachers for whom we demonstrated the Monticello mod and then asked to explore it on their own. Afterwards, we discussed with them the extent to which they found such a tool feasible for classroom use and how they might use it for learning. All of the instructors in the group were familiar with The Sims, but none had previous experience with it. The instructors’ first responses to the virtual Monticello mod was that it looked like a digital replacement of the traditional, second-grade diorama in the shoebox assignment. Initial issues with the mod were that it does not quite accurately

represent the plantation physically. One indicated that they would like the ability to: • • •

•

Import historically relevant artifacts into the framework. Change character attributes to accurately represent historic personalities. Change the rules so that characters could not earn creativity points based on artistic accomplishments but rather earn points based on something that would have been important for that character during a given time period, or remove the point option altogether. “History is not a game,” as one ardent history teacher explained. Reshape the going-shopping metaphor in the game engine that allows users to spend Sims dollars to construct and furnish the house. We used cheats to access Sims dollars to create this mod, following a financing strategy similar to that which Jefferson sometimes used to construct and furnish his own Monticello.

The teachers also expressed concern that a student might be more engaged in the gameplay than in the learning. One suggested that in the classroom, the student would want to use a mod like the virtual Monticello to emphasize its historical significance, toning down the novelty of its gameplay. Another expressed that that he was “excited about the possibility of bringing the past to the present” with mods, citing their value as “an observation tool,” and liked the idea of being able to go in and move around, adding, “I can explore the past and explore interactions!” By doing so, he felt that his students could gain insight through exploration and inference by considering the period characteristic values and experiences of historical figures that might shape their choices and behaviors. Even with programming limits of The Sims, most teachers felt that their students could use

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such mods to experience a “good approximation” of the past, one that would help them to construct their understanding of the time period and issues that shaped decisions. Given this utility, one instructor noted that historically contextual game mods could fortify the development of his students’ mental models, and that as a teacher, he would have better insight into his students’ historical reasoning, based on the decisions they made within the framework.

•

I could present [a mod] as an alternative assessment, opposed to a test or paper,” he explained, adding, “That you can change things is very exciting for the study of history.

•

contextualizing the Mod in the classroom As teachers explored how they might use the virtual Monticello mod in a classroom setting, their ideas for implementation included:

Figure 4. Jefferson in his study

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•

A class inquiry. The teacher could run the mod on the projector and discuss how to interact with it with the class. Later, the students could work in groups on their own mods to explore and create shared meanings. The instructor could alternate between using class and group mods to promote inquiry and discussion. As one teacher pointed out, “There’s a lot of value just in creating the scenario and having the students do the research for that.” An examination of character. “I want to see Monticello and send in Nat Turner,” one explained, to see how a character programmed with Nat’s attributes would react in a plantation setting. One instructor suggested replacing Jefferson with Napoleon for the same reasons. A yearlong study. One teacher suggested that the creation of the scenario could be an ongoing project, divided across academic quarters, each dealing with a different part

Game Mods

of its construction in a way that parallels the course content delivery. Integrating any type of computer game into a curriculum shifts the culture of the classroom from one that is teacher-driven to one that is a more user-centered learning environment; the teacher becomes a facilitator rather than a proffer of knowledge (King 2003; Squire 2004). However, when computer games are introduced into the classroom, the teacher has an amplifying effect on the learning outcome. If the teacher is appropriately prepared to use a game in his or her curriculum, it augments the learning success. Unfortunately, the inverse is true if the teacher is less aware of how to facilitate learning using computer games (Squire 2004). Perhaps we can begin managing this amplifying effect by focusing on what the teacher can do to prepare for bringing game-based learning into the classroom by: • •

•

• • •

Identifying the equipment and entry behaviors required for the game. Determining the time required for the game to make an impact on learning. Typically, a student needs time to understand how to use a game before he or she can begin learning with it. Recognizing the types of learning that computer-based learning facilitates, which is more knowledge-based and, to an extent, subjective. Determining how computer-based learning can support the learning goals. Choosing an appropriate game or game editor for creating mods. Contextualizing the game into the curriculum in a way that encourages exploration, discovery, and the development of conceptual tools.

•

Including appropriate scaffolding as well as off-line activities that encourage reflection, dialog, and shared meanings among the learners beyond the context of the game.

It is also worth exploring if an IT specialist should be familiar with the utility of game-based learning and how to use it in a classroom setting as well in order to support the classroom teachers in meeting their learning goals. This same person could be called upon to create simple learning mods or skeletons for the students to work with, as specified by an instructor, or based on a given curriculum’s learning goals. Finally, and perhaps most importantly, the instructor needs to be game-literate, recognizing and understanding that computer games are a means of expression and representation (Green, 2004) and that, like reading and writing, game literacy develops when the learner has the tools and ability to create his or her own games (Clark, Perrone, & Repenning, 2005; King, 2003).

concLusIon The purpose of this discussion is to examine how game mods might provide an affordable, comparable, and customizable alternative to wildly successful commercial games, an alternative that could be used in a classroom setting to facilitate a meaningful learning experience. However, the success of the use of game mods in the classroom will depend not only on the novelty of a good idea or on how comfortable the instructor and learner are with using computers and making simple changes to existing applications, but also on how well the modding activities are contextualized within the curriculum. Creating meaning still needs to be forged within an evocative and relevant context.

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AcKnowLedgMent Rodney van Zyl, The University of Virginia, USA, for the artwork included in this chapter.

reFerences Boards. The creative edge in commercial production. (2005). Public Health Department, Belgium—Teenage Mum. Retrieved from http:// www.boardsmag.com/screeningroom/animation/1146/ Chaptman, D. (2004). Video-games in the classroom. Wisconsin Technology Network. Retrieved from http://www.wistechnology.com/article. php?id=513. Chu, K., Heeter, C., Egidio, R., & Mishra, P. (2004). Girls and games literature review. Michigan State University Mind Games Collaboratory. Retrieved March 10, 2005, from http://spacepioneers.msu. edu/girls_and_games_lit_review.htm. Clark, D., Perrone, C., & Repenning, A. (2005). Webquest: Using WWW & interactive simulation games in the classroom. First Monday. Retrieved from http://www.firstmonday.dk/issues/issue5/ perrone/. Donaldson, M. (1984). Children’s minds. London: Fontana. Fortugno, N., & Zimmerman, E. (2005). Soapbox: Learning to play to learn—Lessons in educational game design. Gamesutra. Retrieved from http:// www.gamasutra.com/features/20050405/zimmerman_01.shtml. Gee, J.P. (2003). What video games have to teach us about learning and literacy. New York: Palgrave Macmillan. Gorilla Mask. (2005). “Trapped in the closet” performed by The Sims (Part 1). Retrieved from http://gorillamask.net/rksims1.shtml

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Green, H. (2004). Researchers and teachers push for games in schools. The Institute of Education, University of London. Retrieved March 10, 2005, from http://ioewebserver.ioe.ac.uk/ioe/cms/get. asp?cid=1397&1397_1=10817. Holt, T. (2004). How mods are really built. Serious Games Summit DC. Retrieved March 10, 2005, from http://www.cmpevents.com/GDe04/ a.asp?option=C&V=11&SessID=3305&Mgt=0 &RVid=0. Jonassen, D. (Ed.). (1988). Instructional designs for microcomputer courseware101. Hillsdale, NJ: Lawrence Erlbaum. Kim, L.S. (1995). Creative games for the language class. Forum, 33(1), 35. King, B. (2003). Educators turn to games for help. Wired News. Retrieved March 10, 2005, from http:// www.wired.com/news/games/0,2101,59855,00. html. Marriott, M. (2003). Games made for remaking. The New York Times. Retrieved March 10, 2005, from http://www.nytimes.com/2003/12/04/technology/circuits/04modd.html?ex=1135227600&e n=0fc160f73ad53e42&ei=5070. Prensky, M. (2001). Digital game-based learning. New York: McGraw Hill. Prensky, M. (2003). “Modding”—The newest authoring tool. Retrieved from http://www.marcprensky.com/writing/Prensky%20-%20Modding%20-%20The%20Newest%20Authoring% 20Tool.pdf. Satterly, D. (1987). Piaget and education. In R.L. Gregory (Ed.), The Oxford companion to the mind. Oxford: Oxford University Press. Squire, K. (2001). Games to teach project. Education Arcade. Retrieved from http://www.educationarcade.org/gtt/. Squire, K. (2002a). Cultural framing of computer/ video games. Game Studies, 2(3).

Game Mods

Squire, K. (2002b). Replaying history: Learning world history through playing civilization III. Retrieved from http://website.education.wisc. edu/kdsquire.

http://www.cmpevents.com/GDe04/a.asp?optio n=C&V=11&SessID=3250.

Squire, K. (2004). What happens when games go into any classroom situation? Serious Games Summit DC. Retrieved March 10, 2005, from

endnotes 1

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http://www.boardsmag.com/screeningroom/animation/1146/ http://gorillamask.net/rksims1.shtml

This work was previously published in the International Journal of Information and Communication Technology Education, Vol. 2, Issue 4, edited by L. Tomei, pp. 15-23, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Issues of E-Learning in Third World Countries Shantha Fernando University of Moratuwa, Sri Lanka

Introduction Around the world, e-learning is becoming popular, especially among higher education institutes (universities). Many highly ranked universities have either already deployed an e-learning system and are fully operational, or they are in a process of deployment where e-learning-based and non e-learning-based educational environments co-exist. It is also possible to find a few virtual universities. The amount of money and effort that has to be spent on e-learning is high. In addition to the initial e-learning system installation costs, there are ongoing maintenance, management and content development costs. Due to the rapid growth in the field of e-learning and the role it plays in today’s education systems, those working in the field have begun to introduce standards for different aspects of e-learning. The Open Knowledge Initiative (OKI) which is described as “a collaboration among leading universities and specification and standards organizations to support innovative learning technology in higher education” is an example (OKI, 2003).

Many highly ranked universities use commercial e-learning systems such as BlackBoard, WebCT, e-college, Netschool, etc. Several open source products are available though their usage is not wide spread, although it is expected that collaborative projects such as Sakai will enable large-scale open source products to be introduced to the market. This effort is described on the Sakai website as, “The University of Michigan, Indiana University, MIT, Stanford, the uPortal Consortium, and the Open Knowledge Initiative (OKI) are joining forces to integrate and synchronize their considerable educational software into a modular, pre-integrated collection of open source tools” (OKI, 2003).

Background Many third world countries have become “Transitional Countries”. The term “transitional country” has been used in different ways in different times and different contexts. However, today’s meaning of a “transitional country” is a country

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Issues of E-Learning in Third World Countries

that lies between a developed and a developing country, and has an evolving market economy. Dung (2003) states: Generally speaking, the expression ‘transition’ is used, mainly by political scientists, in the context of changes that have followed the fall of regimes, usually when dictatorial regimes have given way to more democratic ones, but this usage has been extended to contexts where previously rigid structures, such as those governing the economy, are giving way to more liberal, market-friendly structures and associated features of liberal democracy. Third world or transitional countries require sustainable development. Sustainable development of a country is very much dependent on industry, higher education and research, hence university education is vital. The importance of the higher education is stressed in the United Nations Resolution on the Decade of Education For Sustainable Development January 2005 – December 2014 (UN Report, 2002). For a third world country, as De Rebello (2003) puts it, “The university system was seen as being uniquely equipped to lead the way by their special mission in teaching and training the leaders of tomorrow, their experience in transdisciplinary research and by their fundamental nature as engines of knowledge.”

current trends In InForMAtIon technoLogy In thIrd worLd countrIes IT is becoming a driving force of economy. Realizing its potential, many transitional countries have embarked on projects in collaboration with funding agencies to improve IT services, though their IT infrastructure facilities are not adequate. Many foreign investors start IT based companies in transitional countries. The products are aimed

at the US or European market, where the parent companies are based. India, in particular, exemplifies this for the IT sector, and many major IT companies have branches in India. In Sri Lanka, due to the limited market, poor infrastructure and slightly higher labor costs, such foreign investments are limited. However, the level of IT expertise is at a competitive level. Many local IT companies carryout sub-contracts for foreign IT companies. A few companies directly interact with the global market. Realizing the potential, the Sri Lankan government embarked on “e-Sri Lanka move” project to introduce e-governance and to improve e-services within the country, and formed the ICT Agency using World Bank funds (Development Gateway, 2003). Motivated by these initiatives and realizing the importance of e-learning for today’s form of higher education, some Sri Lankan universities have deployed elearning systems as pilot projects and a few others have started exploring the possibility of using e-learning for their university education. Due to the employment opportunities offered for IT professionals of transitional countries by developed countries, many professional IT programs have been initiated in transitional countries. In Sri Lanka, income generated by foreign employment has now become considerable compared to its other income sources such as garment, tea, rubber, minerals, spices, etc. Though most employment opportunities are labor-oriented, many professional opportunities are in the IT sector. However, this causes “brain drain”.

IMPortAnce oF e-LeArnIng For hIgher educAtIon In thIrd worLd countrIes In order to understand the importance of e-learning, it is important to consider what we mean by e-learning. According to the definition of NCSA’s e-learning group (Wentling, T.L. et al., 2000):

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E-learning is the acquisition and use of knowledge distributed and facilitated primarily by electronic means. This form of learning currently depends on networks and computers but will likely evolve into systems consisting of a variety of channels (e.g., wireless, satellite), and technologies (e.g., cellular phones, PDA’s) as they are developed and adopted. E-learning can take the form of courses as well as modules and smaller learning objects. E-learning may incorporate synchronous or asynchronous access and may be distributed geographically with varied limits of time. In an abstract form, I would define it as “electronically facilitated, enhanced and managed learning”. It can consist of many components or elements of a learning environment of a university system if they can be electronically facilitated, enhanced and managed. Some aspects that could be integrated into an e-learning system to make an impact in a university system, especially in the context of a third world country, are given below. • • • • •

Curriculum related aspects: Courses and course contents, discussions, library catalogues, etc. Academic administration related aspects: Registrations, student information, grading, etc. Technology infrastructure related aspects: Alternative technologies, lab facilities, home use, etc. Societal context related aspects: Cultural events, forums, activities, etc. Industrial collaboration related aspects: Industrial expertise and contents, know-how dissemination, guidance to/from industry, etc.

These aspects, when incorporated in an elearning system, will improve the quality of the higher education, if implemented using strategies and technologies suitable for constrained

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environments in third world countries. However, deployment of a suitable e-learning system requires a particular educational, administrative and technological environment, and the university educational system will also need to undergo changes. This is where the issues are faced in third world countries. One should not think that the deployment of e-learning is an adaptation to the required educational change. Contrarily, an ability to adapt is a must for the deployment of e-learning. Bates (2000) states that higher education institutes consider technology-based learning for the following reasons: • • •

The need to do more with less The changing learning needs of society The impact of new technologies on teaching and learning (Bates, 2000, p. 8)

Although we observe that mainly the universities in developed countries tend to consider the above reasons, they are applicable to any university. It is in this context that e-learning is becoming attractive. However, when universities in third world countries embark on e-learningbased educational transformations, they face many barriers. In many cases, e-learning cannot be implemented in the way it is done at US or European universities. The approach has to be tailored to the environment, if it is to be a success.

coMMon Issues to be Addressed Administrative Issues Most of the universities in third world countries are traditional universities. Gunn (2000) in his keynote paper states the following: Perhaps the most critical challenge to traditional universities is develop capacity to change. This

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calls for major restructuring, removal of unnecessary processes and streamlined administration procedures. Motivation to progress, change and develop is hard found in the current insecure climate. . . The challenge this raises is being able to exploit the resources of commercial interests while maintaining quality and standards of service as a priority area. Ability to achieve the right balance between opposing forces of cost and quality without reducing education to the lowest common factor will be a powerful survival strategy. In many third world countries university academic administration is stream-lined and rigid. Changes are usually not welcomed. Many fear loosing the value of their jobs if IT strategies are introduced. Many administrative officers have the mentality that the others should come to them to get the work done. While this shows an attitude problem or an inferiority complex, it affects many productive plans. However, rigid administrative procedures are sometimes required to prevent exploitation and use of facilities for personal advantage. Some administrative functions can be handled efficiently through e-learning. Typical examples would be student semester and exam registrations, yearly progress archiving, student information management, etc. However, administrative officers such as registrars, examination branch officers, etc, are not comfortable when it is handled entirely by the e-learning system. There is the fear they might loose their job. Another fear is whether they will have any value for the university. A valid concern that is raised is whether the e-learning system is secure enough to protect confidential data and prevent students tampering with data.

It Infrastructure Issues IT infrastructure facilities in third world countries are often primitive. While IT infrastructure needs improvement for better interconnectivity of academic institutes, a countryman’s concern

is food, water supply, clothing, roads and transportation, housing, primary schools, and other essential items for their living. Governments in these countries have to allocate the majority of their funds for the latter and a low priority is given for IT infrastructure. It is not justifiable to allocate huge funds for the improvement of IT infrastructure when the basic needs of the people are not met. The good news is that some form of infrastructure is already available. The solution we propose for the improvement of higher education using e-learning has to consider alternative techniques given this serious limitation. This is not to say that mobile communications and other new inventions are not penetrating the market. Consider Sri Lanka as a case, every university is interconnected by a university network called LEARN (Lanka Academic and Research Network). Some universities have 2 Mbps E1 links, while the rest have only 128 or 64 kbps links. Very soon the latter will be upgraded, but the maximum would be 2 Mbps in the foreseeable future. The current international bandwidth allocated for the whole university network is below 2 Mbps. This will gradually increase on demand, but on-demand increase implies the presence of congestion. The universities also experience disruption of the telecom services, either due to faults or non-payment of bills. However, within these infrastructure constraints, the majority of universities are able to have an acceptable level of communication for the current IT operations within the country. Web servers are acceptably fast and e-mail is heavily used for communication and collaboration among academics. A few e-learning systems are also operational. Any e-learning-based solution has to work within these IT infrastructure constraints. Within a university it will work acceptably since many universities have local area networks with either gigabit fibre optics, or fast Ethernet or at least 10 Mbps links. Between universities it will work as long as it does not have heavy content delivery, congesting the links. However, international

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collaborations through e-learning will not be at the levels required by many e-learning systems in the near future.

Limitation of equipment In third world countries, equipment such as servers, routers, cabling, laboratory computers, etc. are usually procured under special university budgets, or grants and loans from funding agencies. It is not possible to expect frequent upgrades to equipment. It is very unlikely that high-end servers with redundant power supplies and disk arrays will be always available for the deployment of an e-learning system and redundancy and backup systems are not a priority. Sometimes valuable information stored in the system may be at stake. However alternative approaches such as weekly or critical time-based backups may be carried out. Thus, any approach to introducing e-learning has to start with a low-end solution. Once the importance is recognized by the authorities, some form of ongoing support is feasible. Strategic planning is required to get the funds for improving the performance and reliability of the systems gradually. It is not possible to assume that students will always have access to computers. While a few have their own computers, the majority of the students in transitional countries use common lab facilities to access computers. Labs are open only during working hours and usually scheduled for different groups of students based on assignments and workloads. In most cases, e-learning-based learning activities also need to be planned accordingly. For an example, if an assignment is given with a deadline for the submission through the e-learning system, this deadline has to be flexible in situations such as insufficient computers, labs being not open on demand, workers’ strikes which are frequent in many third world countries, long electricity power cuts, etc.

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cost Factors of e-Learning systems Most of the commercially developed e-learning systems such as BlackBoard, WebCT, etc, used by US and European universities are extremely expensive for the third world countries to purchase. A monetary grant may be a possibility, but then the question would be maintenance costs, purchase of additional modules to suite the changes as time passes, costs of customizations, etc., if these costs have to be born by the university, which are very high given the limited budgets. Therefore, any grant must include these costs. Otherwise, it will be a waste of funds. An alternative is to select an open source solution. However, currently it is difficult to find the exact match of an open source solution, or to customize it to a particular university’s environment. Projects such as Sakai may help solve this situation in the future, but we have to wait until their collaborative environment is functional. However, there is the concern whether it also will assume state-of-the-art technology infrastructure. Another alternative is in-house development, however, for this to be a success, continuous employment of developers and good software development approaches with research input from an e-learning perspective is required. Finding developers is not a difficulty in most transitional countries, and the costs for this will be far below the purchase of a commercial e-learning system. To succeed, however, a vision to continue the project, and institutionalized incentives to the people involved, should be in place. While the result of this approach may not be as sophisticated as, or as reliable as, available commercial systems, it is possible to come up with an acceptable solution at a very low cost. In the author’s environment, it was possible to get a group of students to start on the development of an e-learning system using research findings. Later, an expert was used to further improve it to be used as a production

Issues of E-Learning in Third World Countries

system. It needs further development, but the advantage is, while the required institutional changes for an e-learning-based education are conveyed to the rest of the faculty, the changes can also be synchronized with the development cycle, as illustrated by Collis and Moonen (2001). Even if a fully fledged e-learning system had been purchased, it would have been a failure due to the faculty being not ready to adapt immediately.

reliability Issues Reliability issues have already been mentioned under IT infrastructure issues and limitation of equipment. The following summary is provided to emphasize the issue of reliability. • • • •

Frequent electricity power failures Data communication connectivity failures or disruptions due to non payment of bills Congested links Less emphasis on backup and redundant systems

socio-cultural Issues In most of the third world countries, especially in South Asian and African continents, sociocultural setting is very prominent. It affects how people engage in learning activities. Verbal and physical interactions are important and hence total virtual learning environments may not produce good results. This situation may change in the years to come, especially among the urban population. However, socio-cultural aspects cannot be neglected when dealing with education, and it is true also for technology-based education, as described by Gunawardena (1998). Most of the e-learning systems and available contents are based on popular languages. However, this is not to say that they do not support other languages, but it will require an additional effort to prepare contents in native languages. In many

third world countries primary education is done in native languages, although at university level popular languages like English or Spanish may be the medium. This situation can create communication barriers in e-learning-based learning processes. Many people in third world countries believe that developments in IT will cause many people to lose their jobs. This is a serious social issue. However, there are situations where it is thought to be the other way round. For an example, in e-Sri Lanka move, the government expects that there will be an increase in job opportunities if IT is promoted. For an example, to deploy e-learning in a university environment, additional support staff is required for facilitation, content creation, maintenance, etc.

Future trends And concLusIon E-learning can play a major role in higher education in third world and transitional countries. It will help improve the higher education, thereby contributing to sustainable development. Using e-learning it is possible to improve curriculum, academic administration, industry collaboration, etc. Emerging related standards such as Sharable Content Object Reference Model (SCORM, 2003), IEEE Learning Technology Standards Committee (LTSC, 2002) and collaborative work currently being carried out such as OKI (OKI, 2003) will make e-learning more widespread. However it may not be possible to deploy it in third world countries in the way it is done in the highly ranked universities in the US and European countries. First, the related issues have to be addressed and alternative solutions should be explored. Given suitable alternative solutions, or desirable approaches, e-learning can be a success in many third world and transitional countries.

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reFerences Bates, A. W. (2000). Managing technological change: Strategies for college and university leaders. San Francisco: Jossey-Bass Publishers. Collis, B., & Moonen, J. (2001). Flexible learning in a digital world: Experiences and expectations. UK: Kogan Page. De Rebello, D. (2003). What is the role for higher education institutions in the UN decade of education for sustainable development?, Theme IV, International Conference on Education for a Sustainable Future (pp. 10-11). Prague, Czech Republic: Charles University, Karolinum. Development Gateway. (2004). e-Sri Lanka: Transforming government, business and society (December 29, 2003). Retrieved March 01, 2004, from http://www.developmentgateway.com/ node/133831/sdm/docview?docid=841120 Dung, L. T. (2003). Judicial independence in transitional countries, The Democratic Governance Fellowship Program, United Nations Development Program, Oslo Governance Centre, January 2003 (page 5). [Electronic version]retrieved March 02, 2004, from http://www.undp.org/oslocentre/ docsjuly03/DungTienLuu-v2.pdf Gunawardena, C. (1998). Designing collaborative learning environments mediated by computer conferencing: Issues and challenges in the Asian socio-cultural context. Indian Journal of Open Learning, 7(1), 101-119. Gunn, C. (2000, Decmber). Identity, control and changing reality. Keynote paper at ASCILTE Conference, Coffs Harbour. [Electronic version] retrieved June 25, 2003, from http://www.ascilite. org.au/conferences/coffs00/papers/cathy_gunn_ keynote.pdf LTSC. (2002). Learning object metadata. Learning Object Metadata Working Group, Learning

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Technology Standards Committee (LTSC), IEEE. Retrieved March 24, 2004, from http://ltsc.ieee. org/wg12/index.html OKI Project. (2003). Open knowledge initiative. Retrieved March 02, 2004, from OKI Project web site http://web.mit.edu/oki/ Sakai Project. (2003). Retrieved March 02, 2004, from Sakai Project Web site http://www. sakaiproject.org/ SCORM. (2003). SCORM overview. Advanced Distributed Learning. Retrieved May 05, 2004, from http://www.adlnet.org/index. cfm?fuseaction=scormabt UN Report. (2002). World summit on sustainable development: Plan of implementation (para 117d). Retrieved March 01, 2004, from http://www. johannesburg summit.org/html/documents/summit_docs/2309_planfinal.htm Wentling, T.L., Waight, C., Gallaher, J., La Fleur, J., Wang, C., & Kanfer, A. (2000, September), Elearning—A review of literature. Knowledge and Learning Systems Group, University of Illinois at Urbana-Champaign, NCSA.

Key terMs Academic Administration: Administration procedures or formalities linked with university education, such as registrations for semesters or examinations, progress reviews and monitoring, eligibility formalities, student history records or progress archiving, promotions to levels or years, academic timetables, etc. E-Learning: Electronically facilitated, enhanced and managed learning. IT Infrastructure: Technological infrastructure that enables the transfer of information.

Issues of E-Learning in Third World Countries

Learning Environment: Overall university setting in which many educational and administrative processes interact. Open Source E-learning Systems: E-learning systems developed by the Open Source Community and freely distributed with their own license or a GPL (General Purpose License) to use, modify and distribute together with the source code.

Third World Countries: Countries that are not yet developed. Transitional Countries: A third world country that is in a transition process based on more liberal, market-friendly structures and associated features of liberal democracy. Virtual Universities: All the learning and administration activities are done through e-learning and very minimum physical interactions, or no physical interactions at all.

This work was previously published in the Encyclopedia of Information Science and Technology, Volume 3, edited by M. Khosrow-Pour, pp. 1702-1707, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.7

Knowledge Representation in Intelligent Educational Systems Ioannis Hatzilygeroudis University of Patras, and Research Academic Computer Technology Institute, Greece Jim Prentzas Technological Educational Institute of Lamia and Research Academic Computer Technololgy Institute, Greeece

AbstrAct In this chapter, we deal with knowledge representation in Intelligent Educational Systems (IESs). We make an effort to define requirements for Knowledge Representation (KR) in an IES. The requirements concern all stages of an IES’s life cycle (construction, operation, and maintenance), all types of users (experts, engineers, learners) and all its modules (domain knowledge, user model, pedagogical model). We also briefly present various KR schemes, focusing on neurules, a kind of hybrid rules integrating symbolic rules and nuerocomputing. We then compare all of them as far as the specified KR requirements are concerned. It appears that various hybrid approaches to knowledge representation can satisfy the requirements in a greater degree than

that of single representations. Another finding is that there is not a hybrid scheme that can satisfy the requirements of all the modules of an IES. So, multiple representations or a multi-paradigm representation environment could provide a solution to requirements satisfaction.

IntroductIon Recent developments in computer-based educational systems resulted in a new generation of systems encompassing intelligence, to increase their effectiveness; they are called Intelligent Educational Systems (IESs). Intelligent Tutoring Systems (ITSs) constitute a popular type of IESs. ITSs take into account the user’s knowledge level and skills and adapt the presentation of the teach-

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Knowledge Representation in Intelligent Educational Systems

ing material to the needs and abilities of individual users. This is achieved by using Artificial Intelligence (AI) techniques to represent pedagogical decisions as well as domain knowledge and information regarding each student. ITSs were usually developed as stand-alone systems. However, the emergence of the WWW gave rise to a number of Web-based ITSs (Brusilovsky, 1999), which are a type of Web-Based Intelligent Educational System (WBIES) (Hatzilygeroudis, 2004). Adaptive Educational Hypermedia System (AEHS) (Brusilovsky, Kobsa, & Vassileva, 1998) are another type of educational system. These systems are specifically developed for hypertext environments such as the WWW. The main services offered to their users are adaptive presentation of the teaching content and adaptive navigation by adapting the page hyperlinks. Compared to ITSs, they offer a greater sense of freedom to the user, since they allow a guided navigation to the user-adapted educational pages. Furthermore, they dynamically construct or adapt the educational pages, in contrast to ITSs where the contents of pages are typically static. Enhancing AEHSs with aspects and techniques from ITSs creates another type of WBIES. A crucial aspect in IESs (hence, WBIESs) is making decisions on the proper adaptation of the system to the user needs. This is mainly done by mimicking corresponding human decision making. So, a crucial aspect in the development of an IES, and hence of a WBIES, is how related knowledge is represented and how reasoning for decision making is accomplished. Various knowledge representation (KR) schemes have been used in IESs. An aspect that has not received much attention yet is defining requirements for knowledge representation in IESs. The definition of such requirements is important, since it can assist in the selection of the suitable KR scheme(s). In this chapter, we present an effort to specify a number of requirements that a KR scheme that is going to be used in an IES should meet in order to be adequate. Based on them and a comparison

of various KR schemes, we argue that hybrid schemes satisfy those requirements to a larger degree than single schemes. Such a hybrid scheme, called neurules, is presented as an example. However, our final argument is that only multiple representations or a multi-paradigm environment would be adequate for the development of an IES. This chapter is an extension of the work of Hatzilygeroudis and Prentzas (2004b). The chapter is organized as follows. The following section specifies the KR requirements. Then, a number of KR schemes and how they satisfy the requirements are presented. The next section compares the KR schemes and, finally, we end the chapter with our conclusions.

Kr requIreMents Introductory Aspects As in other knowledge-based systems, we distinguish three main phases in the life cycle of an IES: the construction phase, the operation phase, and the maintenance phase. The main difference from other knowledge-based systems is that an IES requires a great deal of feedback from the users and iteration between phases. Three types of users are involved: domain experts, knowledge engineers, and learners. Each type of user has different requirements for the KR scheme(s) to be used. We call them user requirements, since they mainly concern the needs of the users. Some of the user requirements are related to the general requirements for a KR language, such as efficiency and naturalness. Efficiency mainly refers to how quickly conclusions are drawn, whereas naturalness refers to how easy it is to construct and understand sentences of a KR language as well as inference steps (Reichgelt, 1991). On the other hand, the system itself imposes a number of KR requirements. An IES (as well as a WBIES) consists of three main modules

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(see Figure 1): (a) the domain knowledge, which contains the teaching content and meta-information about the subject to be taught, (b) the user model, which records information concerning the user, and (c) the pedagogical model, which encompasses knowledge regarding various pedagogical decisions. Each component imposes different KR requirements. We call them system requirements, since they are related to the system components.

user requirements Domain Expert The domain expert provides knowledge concerning the application domain. He/she is a person who has in-depth knowledge about the possible problems, the way to deal with them, and various practices obtained through his/her experience. In IESs, the domain experts are mainly the tutors. Tutors are highly involved in the construction and maintenance stages. However, in most cases, their relation to AI or even to computers is rather superficial. This may potentially make them restrained in their interactions with the knowledge engineer. Furthermore, the teaching theories to be incorporated in the system are rather difficult to express.

Figure 1. The basic structure of an intelligent educational system (IES)

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So, it is evident that one main requirement that tutors impose is naturalness of representation. Naturalness facilitates interaction with the knowledge engineer and helps the tutor in overcoming his/her possible restraints with AI and computers in general. In addition, it assists the tutor in proposing updates to the existing knowledge. Also, expert is involved in checking the validity of the represented knowledge—a tedious task. So, the capability of providing explanations is another requirement from the expert, which is of great help in checking represented knowledge.

Knowledge Engineer The knowledge engineer manages the development of an IES and directs its various phases. The main tasks of the knowledge engineer are: acquire knowledge from the domain expert and/or other knowledge sources, select the implementation tools, and effectively represent the acquired knowledge. He/she is the one who chooses (or designs) the KR scheme to be employed. Finally, he/she maintains the produced knowledge base. Obviously, naturalness is again a basic requirement. The more natural the KR scheme, the easier it is for the knowledge engineer to transfer expert knowledge. Furthermore, during construction, tutors may frequently change part (small or big) of the represented knowledge. Also, even if the system’s operation is satisfactory, changes and updates of the incorporated expert knowledge may be required. This demands ease of updates. Additionally, the KR scheme should facilitate the knowledge acquisition (KA) process. KA is usually a bottleneck in the development of a knowledge-based system. Facilitation can be achieved if the KR scheme allows acquiring knowledge from alternative (to experts) sources, such as databases of empirical data or past cases, in an automated or semi-automated way. So, ease of knowledge acquisition is another requirement.

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In developing knowledge-based systems, a prototype is usually constructed before the final system. The prototype includes a small part of the whole knowledge. The rest of it is gradually added to the system. This is called incremental development of the system, and it is a desirable feature. Furthermore, testing the continually incremented prototype can call for arduous efforts. In this context, two important factors are the inference engine performance and the capability of providing explanations. Efficient inferences reduce the time spent by the knowledge engineer. Also, provision of explanations is important, because it can assist in the location of deficiencies in the knowledge base.

end-user An end-user (learner) is the one who uses the system in its operation stage. The basic requirement for KR, from the point of view of end-users, concerns time efficiency. IESs are highly interactive knowledge-based systems requiring timeefficient responses to the users’ actions, which mainly depend on inference engine responses. In the case of WBIESs, time performance is even more crucial, since the Web imposes additional time constraints due to multiple users and the restricted communication bandwidth. In addition to efficiency, the inference engine should also be able to reach conclusions from partially known inputs. During a learning session, the user may not be able or does not want to provide values for all parameters. However, the system should be able to make inferences without having all inputs known.

system requirements Types of Knowledge System requirements refer to representation of the knowledge involved in the components of an IES. These requirements are mainly based

on the required type(s) of involved knowledge, since different types of knowledge are more easily represented in different KR schemes (Reichgelt, 1991). A first type of knowledge is called structural knowledge. Structural knowledge is concerned with types of entities (i.e., concepts, objects, etc.) and how they are interrelated. It reflects the structure of the domain knowledge. Often, those relationships are hierarchical, that is, they concern generalization/specialization relationships, for example, “math is a form of an academic course, which itself is a form of a course.” Another type of knowledge is relational knowledge. Relational knowledge concerns relations between entities of the domain. Those relations may be causal relations, for example, “smoking causes cancer” or dependency relations, for example, “mark depends on the number of attempts and the help asked.” From another point of view, there is heuristic knowledge. It is knowledge in the form of “rules of thumb”—practical knowledge about how to solve problems based on experience. Sometimes, knowledge is not clear enough, but uncertain or vague. For example, values “low” and “medium,” used to characterize the knowledge level of a student are vague, since their boundaries are not clear. Also, knowledge may be not certain, but may have a degree of certainty.

Domain Knowledge The domain knowledge module contains knowledge related to the subject to be taught as well as the actual teaching material. It usually consists of two parts: (a) knowledge model, and (b) course units. Knowledge model refers to the basic concepts that constitute the subject to be taught and the types of relationships between them, for example, the “prerequisite” or “specialization,” relationships. Finally, they are associated with course units, which constitute the teaching content.

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Usually, concepts are organized in a type of structure. So, it is evident that the KR scheme should be able to naturally represent structural and relational knowledge.

User Model The user model (or student model) records information about the learner’s knowledge state and traits. This information is vital for the system to be able to adapt to the user’s needs. The process of inferring a user model from observable behavior is called “diagnosis.” There are many possible user characteristics that can be recorded in the user model. One of them is the knowledge that the user has learned. In this case, diagnosis refers to an estimation (or evaluation) of the learner’s knowledge level. Diagnosis of other characteristics such as learning ability and concentration means estimations based on learner behavior while interacting with the system. Diagnosis of learner’s characteristics is not a clear process. Also, there is not a clear-cut distinction between various levels (values) of the characteristics. So, it is quite obvious that a representation scheme for the user model should be able to deal with uncertain and vague knowledge. Also, representation of heuristic knowledge is needed to make estimations about the values of the student characteristics.

Pedagogical Model The pedagogical model represents the teaching process. It provides the knowledge infrastructure in order to tailor the presentation of teaching content according to the information recorded in the user model. The pedagogical model of a “classical” IES mainly performs the following tasks: (a) course planning (or knowledge sequencing), (b) teaching method selection, and (c) learning content selection. The main task in (a) is planning, that is, selecting and appropriately ordering the concepts

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to be taught. The main task involved in (b) and (c) is also selection, for example, how a teaching method is selected based on the learner’s state and the learning goal. This is a reasoning process whose resulting conclusion depends on the logical combinations of the values of the user model characteristics, which is a function of heuristic knowledge. Furthermore, selection is not always clear, so uncertain knowledge representation may be required. The above analysis of the requirements of knowledge representation for an IES is depicted in Tables 1 and 2.

KnowLedge rePresentAtIon scheMes In this section, we investigate satisfaction of the requirements specified above by various KR schemes. We distinguish between single and hybrid KR schemes.

single schemes Structured Representations Semantic nets and their descendants ( frames or schemas) (Negnevitsky, 2002) represent knowledge in the form of a graph (or a hierarchy). Nodes in a semantic net graph represent concepts and the edges represent relations between the concepts. Nodes in a frame hierarchy also represent concepts, but they have internal structure that describes the corresponding concept via a set of attributes. They are very natural and well suited for representing structural and relational knowledge. They can also make efficient inferences for small to medium graphs (hierarchies). However, it is difficult to represent heuristic knowledge, uncertain knowledge, and make inferences from partial inputs. Also, explanations are not provided and knowledge updates are difficult.

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Table 1. Users’ requirements E xper t • naturalness • explanations

USE R S’ R E QUI R E M E NT S E ngineer L ear ner • naturalness • efficient inferences • ease of updates • partial input inferences • incremental development • ease of knowledge acquisition • explanations

Table 2. System requirements SY ST E M R E QUI R E M E NT S Domain K nowledge User M odel Pedagogical M odel • structural knowledge • vague knowledge • heuristic knowledge • relational knowledge • uncertain knowledge • uncertain knowledge • heuristic knowledge

Conceptual graphs are similar to semantic nets, whereas ontologies (Staab & Studer, 2004) refer to a representation scheme similar to frames, but more restrictive. In IESs, semantic networks have been used mainly for the representation of the domain knowledge structure.

Symbolic Rules Symbolic rules are one of the most popular KR methods (Negnevitsky, 2002). They represent general domain knowledge in the form of if-then rules: if then , where the term represents the conditions of a rule, whereas the term represents its conclusion. The conditions are connected with one or more logical operators such as “and,” “or,” and “not.” The conclusion of a rule is derived when the logical function connecting its conditions results to true. Expert systems constitute

the most well-known type of rule-based systems. The main parts of a typical expert system are: rule base, inference engine, working memory, and explanation mechanism. The inference engine uses the knowledge in the rule base as well as facts about the problem at hand to draw conclusions. Typically, facts are provided by the user during inference. There are two main inference methods: backward chaining (guided by the goals) and forward chaining (guided by the data). The explanation mechanism provides explanations regarding the drawn conclusions. Rules are natural (easy to comprehend) and rule-base updates (removing/inserting rules) can be easily made. Also, incremental development of a rule base is a quite natural process. In addition, heuristic knowledge is naturally represented by rules. However, a major drawback is the difficulty in acquiring them. KA may turn out to be a bottleneck. Furthermore, the acquired rules may be imperfect. Efficiency of the inference process

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depends on the length of the inference chains. Additionally, conclusions cannot be derived if some of the inputs are unknown. Finally, pure rules cannot represent uncertain or vague knowledge and are not suitable for representing structural and relational knowledge. Symbolic rules have been used in IESs mainly to diagnose the learner’s characteristics and to perform various pedagogical tasks (Simic & Devedzic, 2003; Vassileva, 1998). The system described by Vassileva (1998) uses heuristic knowledge in the form of rules (classified into groups with different functionality) to manage course generation based on learner’s performance and the domain knowledge.

case-based representations Case-based representations (Leake, 1996) store a large set of past cases with their solutions in the case base and use them whenever a similar new case has to be dealt with. A case-based system performs inference in four phases: (1) retrieve, (2) reuse, (3) revise, and (4) retain. In the retrieval phase, the most relevant stored case(s) to the new case is (are) retrieved. Similarity measures and indexing schemes are used in this context. In the reuse phase, the retrieved case is combined with the new case to create a solution. The revise phase validates the correctness of the proposed solution. Finally, the retain phase decides on retention (or not) of the new case. Cases are usually easy to obtain and, unlike other schemes, case acquisition can also take place during the system’s operation. Cases are natural. Explanations cannot be provided in a straightforward way as in rule-based systems, due to the similarity functions. Even if some of the inputs are not known, conclusions can be reached through similarity to stored cases. Updates can be easily made. However, the efficiency of the inference process depends on the size of the case base. Finally, cases are not suitable for

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representing structural, uncertain, and heuristic knowledge. In IESs, case-based reasoning has been used in the user model to assess the learner’s knowledge and in the pedagogical model to perform instructional tasks (Guin-Duclosson, Jean-Danbias, & Norgy, 2002; Shiri, Aimeur, & Frasson, 1998). The approach described by Guin-Duclosson et al. (2002) uses case-based reasoning to teach problem-solving methods. The system enables modeling the knowledge observed in learners by explicitly defining a problem classification, the reformulation, and the solution knowledge associated with it. According to that model, an expert in the teaching domain defines a hierarchy of problem classes and reformulation knowledge for the classification of a new problem based on discriminating attributes.

neural networks Neural networks represent a totally different approach to AI, known as connectionism (Gallant, 1993). A neural network consists of many simple interconnected processing units called neurons. Each connection from neuron uj to neuron ui is associated with a numerical weight wij corresponding to the influence of uj to ui. The output of a neuron is based on its inputs and corresponding weights. Usually, neural networks are organized in three levels: input, intermediate (or hidden), and output level. The weights of a neural network are determined via a training process using empirical data. Input neurons are fed with the input values of the problem. These values are propagated through the network and produce the outputs by activating the corresponding neurons. Neural networks are very efficient in producing conclusions, since inference is based on numerical calculations, and can reach conclusions based on partially known inputs due to their generalization ability. On the other hand, neural networks lack naturalness of representation, that is, the

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encompassed knowledge is incomprehensible, and explanations for the reached conclusions cannot be provided. It is also difficult to make structural updates to specific parts of the network. Neural networks do not possess inherent mechanisms for representing structural, relational, and uncertain knowledge. Heuristic knowledge can be represented to some degree via supervised training. The system described by Tchetagui and Nkambou (2002) employs a neural network to classify the learner into a knowledge level.

Belief Networks Belief networks (or probabilistic nets) (Russell & Norvig, 2003) are graphs, where nodes represent statistical concepts and links represent mainly causal relations between them. Each link is assigned a probability, which represents how certain is it that the concept where the link departs from causes (leads to) the concept where the link ultimately arrives. Belief nets are good at representing causal relations between concepts. Also, they can represent heuristic knowledge to some extent. Furthermore, they can represent uncertain knowledge through the probabilities and make relatively efficient inferences (via computations of probabilities propagation). However, estimation of probabilities is difficult, making the KA process a problem. For the same reason, it is difficult to make updates. Also, explanations are difficult to produce, since the inference steps cannot be easily followed by humans. Furthermore, their naturalness is reduced. In IESs, belief networks have been used mainly in user modeling (Jameson, 1995; Tchetagui & Nkambou, 2002; Vanlehn & Zhendong, 2001). The system described by Tchetagui and Nkambou (2002) uses Bayesian reasoning to aggregate performance values throughout the network of the domain knowledge structure.

hybrid schemes Hybrid schemes are integrations of two or more single KR schemes. In this section, we focus on the most popular ones.

Fuzzy Rules Fuzzy logic is good at representing imprecise and fuzzy terms, like “low” and “high.” Fuzzy logic extends traditional logic and set membership by defining membership functions over the range [0.0, 1.0], where 0.0 denotes absolute falseness and 1.0 absolute truth. Fuzzy expert systems constitute the most popular application of fuzzy logic. In such systems, sets of fuzzy rules (Dubois, Pride, & Yager, 1993) are used to infer conclusions based on input data. Fuzzy rules include fuzzy variables. Inference process includes three phases: fuzzification of inputs (via membership functions), application of fuzzy rules, and defuzzification (to produce the output). Given the above, fuzzy rules are good at representing vagueness. However, fuzzy rules are not as natural as symbolic rules (due to membership functions), a fact that complicates the KA process and the updates to the rule base. It is difficult to specify membership functions. Inference is more complicated and less natural than in simple rule-based reasoning, although its overall performance is not worse (because a fuzzy rule corresponds to more than one simple rule). Provision of explanations is feasible, but not all reasoning steps can be explained. Fuzzy rules have proven quite helpful in the user modeling component of various ITSs (Hwang, 1998; Nkambou 1999). The Web-based ITS described by Hwang (1998) employs a fuzzy expert system to assess learner characteristics and guide the learning process. The user model records fuzzy characteristics (like knowledge level, concentration, etc.) and non-fuzzy characteristics (like total session time, effective learning time, etc.). The

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non-fuzzy characteristics are used to determine the values of the fuzzy ones. Fuzzy rules are used for subject material selection.

Connectionist Rule-Based Representations A number of neuro-symbolic approaches have been developed, but we concentrate here on connectionist expert systems, because they satisfy more requirements. Connectionist expert systems (Gallant, 1993) combine neural networks with rule-based expert systems. The knowledge base is a network whose nodes correspond to domain concepts. Dependency information regarding the concepts is used to create links among nodes. The network’s weights are calculated through a training process using a set of training patterns. In addition to the knowledge base, connectionist expert systems also consist of an inference engine and an explanation mechanism. Compared to neural networks, they offer more natural representation and can provide some type of explanation. Naturalness is enhanced due to the fact that most of the nodes correspond to domain concepts.

Neuro-Fuzzy Representations There are various ways to integrate neural networks and fuzzy logic (Nauck, Klawonn, & Kruse, 1997). We are interested in integrations where the two component representations are indistinguishable. Such integrations are the fuzzy neural networks and the hybrid neuro-fuzzy representations. Fuzzy neural networks are fuzzified neural networks—they retain the basic properties and architectures of neural networks and “fuzzify” some of their elements (i.e., input values, weights, activations, outputs). In a hybrid neuro-fuzzy system, both fuzzy techniques and neural networks play a key role. Each does its own job in serving different functions in the system. Hybrid neurofuzzy systems seem to satisfy KR requirements to a greater degree than fuzzy neural networks.

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They retain more benefits of their component representations in a more satisfactory way. The system described by Magoulas, Papanikolaou, and Grigoriadou (2001) is an Adaptive Educational Hypermedia System, which uses neural and fuzzy modules to accomplish its tasks. Neural and fuzzy modules are used in the domain knowledge, the learner evaluation, and the pedagogical model. This hybrid approach enables the representation of incomplete, imprecise, and vague information about the learner and also exploits the generalization capability of neural networks.

Integrations of Rules and Cases Another trend in hybrid knowledge representation is the integrations of rule-based reasoning with case-based reasoning (Golding & Rosenbloom, 1996). We refer here to approaches where one method (either rules or cases) dominates and not to balanced approaches, because reasoning in them is more complicated. In such systems, naturalness of the underlying components is retained. Compared to “pure” case-based reasoning, their key advantage is the improvement in the performance of the inference engine and the ability to represent heuristic and relational knowledge. Furthermore, the synergism of rules and cases can cover up deficiencies of rules (improved knowledge acquisition) and also enable partial input inferences. The existence of rules in such hybrid schemes makes updates more difficult than “pure” case-based representations. Also, explanations can be provided but not as easily as in pure rule-based representations, given that similarity functions are still present.

Description Logics Description Logics (DLs) (Baader, Calvanese, McGuiness, Nardi, & Patel-Schneider, 2002) combine aspects from frames, semantic nets, and logic. They consist of two main components, the

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Tbox and the Abox. Tbox contains definitions of concepts and roles (i.e., their attributes) called terminological knowledge, whereas ABox contains logical assertions about concepts and roles called assertional knowledge. DLs offer clear semantics and sound inferences. They are usually used for building and maintaining ontologies and for classification tasks related to ontologies. Also, DLs can be built on existing Semantic Web standards (XML, RDF, RDFS), so they are quite suitable for representing structural and relational knowledge. Also, being logic-based, they can represent heuristic knowledge. Furthermore, their Tboxes can be formally updated. Their representation is natural, but not as much as that of symbolic rules. Inferences in DLs may have efficiency problems. Explanations cannot be easily provided.

neurules Syntax and Semantics Neurules are a type of hybrid rules integrating symbolic rules with neurocomputing (Hatzilygeroudis & Prentzas, 2000, 2001a). In contrast to other hybrid approaches, the constructed knowledge base retains the modularity of rules, since it

consists of autonomous units (neurules), and also retains their naturalness in a great degree, since neurules look much like symbolic rules. The form of a neurule is depicted in Figure 2a. Each condition Ci is assigned a number sfi, called its significance factor. Moreover, each rule itself is assigned a number sf0, called its bias factor. Internally, each neurule is considered as an adaline unit (Fig. 2b). The inputs Ci (i =1,...,n) of the unit are the conditions of the rule. The weights of the unit are the significance factors of the neurule and its bias is the bias factor of the neurule. Each input takes a value from the following set of discrete values: [1 (true), 0 (false), 0.5 (unknown)]. The output D represents the conclusion of the rule. The output can take one of two values (‘-1’, ‘1’) representing failure and success of the rule respectively. The general syntax of a condition Ci and the conclusion D is: ::= where denotes a variable, for example, “mark-level,” “solution-attempts,” and so on. denotes a symbolic (is, isnot) or a

Figure 2. (a) Form of a neurule; (b) corresponding adaline unit

D

(sfo) if C1 (sf1), C2 (sf2),

(sf0) (sf1)

Cn (sfn)

(sfn)

(sf2)

Then D

C1 (a)

C2

Cn (b) 1897

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Table 3. A neurule for assigning examination marks (-9.7) if assistance-times is 1 (4.7), assistance-times is 0 (4.6), solution-attempts is 2 (4.6), requested-examples is >1 (3.2), requested-examples is 1 (1.4) then mark is average

numeric (, =) predicate (not used in conclusions). denotes a value (a symbol or a number). The significance factor of a condition represents the significance (weight) of the condition in drawing the conclusion. Table 3 presents an example of a neurule used in assigning examination marks to a student. Neurules can be constructed either from symbolic rules (Hatzilygeroudis & Prentzas, 2000), thus exploiting existing symbolic rule bases, or empirical data (Hatzilygeroudis & Prentzas 2001a). Each adaline unit is individually trained via the Least Mean Square (LMS) algorithm. A neurule-based system consists of the same basic components as a rule-based system. The neurule-based inference engine is based on a backward chaining strategy and uses neurules and facts (typically acquired from the user) to draw conclusions. Evaluation of a neurule is based on special neurocomputing measures (Hatzilygeroudis & Prentzas, 2001b). A neurule fires if the output of the corresponding adaline unit is computed to be “1” after evaluation of its conditions. A neurule is said to be “blocked” if the output of the corresponding adaline unit is computed to be “-1” after evaluation of its conditions. Experiments have shown that the neurulebased inference process not only does better than simple rules but also better than other similar systems, like MACIE (Gallant, 1993). Neurules are also associated with an explanation mechanism capable of providing explanations of various

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types in the form of if-then rules. Experiments have shown that neurules’ explanation mechanism produces more natural explanations with less rules (Hatzilygeroudis & Prentzas 2001b).

Using Neurules in an ITS We constructed an intelligent tutoring system using neurules as its main knowledge representation scheme (Hatzilygeroudis & Prentzas 2004a; Prentzas, Hatzilygeroudis, & Garofalakis, 2002). Neurules were used for representing knowledge in the user modeling unit and the pedagogical unit. In the user modeling unit, neurules were used for user classification in some stereotype and for student evaluation. In the pedagogical unit, they were used for three tasks: method selection, concept selection, and unit selection. There is a neurule-based expert system, which makes pedagogical decisions during the learning process, with a neurule-based inference engine, and a neurule base consisting of five partial neurule bases, distributed between the user modeling and the pedagogical unit. An important characteristic of the ITS is the existence of a special unit, called knowledge management unit (KMU). KMU has facilities for (a) acquiring knowledge from various sources (experts, existing symbolic rule bases, empirical data), and (b) updating the knowledge stored in the neurule bases. The use of neurules in the development of the ITS revealed a number of benefits: •

•

Neurules can be acquired in a semi-automated way from various sources, such as symbolic rules, empirical data, or an expert. This is very important for IESs, given that KA is harder than other systems due to the existence of more than one knowledge-based module. Neurules support incremental development of the neurule bases. One can easily add new neurules to or remove old neurules from a

Knowledge Representation in Intelligent Educational Systems

•

•

•

•

neurule base. This is difficult for other hybrid approaches. Neurules are space-efficient; they produce much smaller knowledge bases compared to simple rules. The size reduction in the ITS was 35-40%. Neurules can make robust inferences. In contrast to simple rules, neurules can derive conclusions from partially known inputs. This feature is useful because, values of some parameters may be unknown during a learning session. Neurules provide a more time-efficient inference engine than simple rules. This is very important, since an IES is a highly interactive knowledge-based system. Neurule bases can be efficiently updated, that is, without thorough reconstruction of them. This is quite helpful during the construction and maintenance stage, where many updates are required. Knowledge base updates constitute a bottleneck for other hybrid approaches.

Despite the above benefits, we experienced some difficulties too. First, we could not use neurules to represent domain knowledge, due to its structural nature. So we had to rely on degenerate (hence, weak) representation methods like relational tables. Another difficulty was that we could not represent vague knowledge. So we had to use clear cut distinctions among various classes of a test mark level or the knowledge level of a student (low, average, high, etc.).

coMPArIson oF Kr scheMes Table 4 compares the KR schemes discussed in the previous sections, as far as satisfaction of KR requirements for IESs is concerned. Symbol “-” means “unsatisfactory”; “√-” “average”; “√” “good”; and “√+” “very good.”

A conclusion that can be drawn from the table is that none of the single or hybrid schemes satisfies all the requirements for an IES. However, some of them satisfy the requirements of one or two modules of an IES. So, taking into account only the learner’s and system requirements, one can say that semantic nets, frames, description logics, and belief networks are more suitable for representing knowledge in the domain model. Also, fuzzy rules, belief networks, and neurofuzzy representations are more suitable for the student modeling module. Finally, symbolic rules and neurules are more suitable for the pedagogical model. Hybrid schemes, in general, demonstrate improvements compared to most or all of their component schemes and therefore are preferable. However, a solution to the representational problem of an IES could be the use of different representation schemes (single or hybrid) for the implementation of different IES modules. Hence, the idea of a multi-paradigm development environment seems to be interesting.

concLusIon In this chapter, we make an effort to define requirements for knowledge representation in an IES. This work was motivated by the fact that we found symbolic rules inadequate to construct an ITS. The requirements concern all stages of an IES’s life cycle (construction, operation, and maintenance), all types of users (experts, engineers, and learners), and all its modules (domain knowledge, user model, and pedagogical model). According to our knowledge, such requirements have not been defined yet in the IES literature. However, we consider them of great importance as they can assist in choosing the KR schemes for representing knowledge in the components of an IES. To this end, we briefly present and compare various KR schemes. Our decision about the satisfaction level of a requirement by a KR scheme

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Table 4. Comparison of KR schemes

-

√+

√+

-

-

-

√+

√+

√+

√-

-

-

√-

-

-

√+

√+

√+

√

√

√+

√

-

√

-

-

-

√√

-

√+ √+ √

-

√√+ √-

√+ -

√ -

√+ √√-

√+ √-

√√+

√√√+

√-

√-

√+

√-

√+

√+

-

√-

-

-

√-

√-

-

√

-

√

√-

-

√-

√-

√+

√

√+ √ √

√ √√

√ √√+

√ √√+

√ √ √+

√ √+

√+ -

√ √+ √-

-

-

√ √ √+

Heuristic knowledge

√

Vague knowledge

Relational knowledge

-

√

Uncertain knowledge

Structural knowledge

√+

Partial input inferences

√-

K nowledge Acquisition

E fficient Inference

√+

E xplanations

E ase of Update

Semantic nets/frames Symbolic rules Case-based representations Belief networks Neural networks F uzzy rules Connectionist expert systems Neurofuzzy representations Cases and rules Description logics Neurules

SY ST E M R E QUI R E M E NT S

Naturalness

USE R S’ R E QUI R E M E NT S

is based on advanced basic research results from the literature. It appears that various hybrid approaches to KR can satisfy the requirements to a greater degree than that of single representations. The use of hybrid approaches to knowledge representation in IESs can become a popular research trend, although, until now, few IESs employed hybrid KR schemes. Another finding is that there is not a hybrid scheme that can satisfy the requirements of all of the modules of an IES, but rather, each one individually. So, multiple representations or a multi-paradigm representation environment could provide a solution.

Brusilovski, P. (1999). Adaptive and intelligent technologies for Web-based education. In C. Rollinger & C. Peylo (Eds.), Kustliche Intelligenz, Special Issue on Intelligent Systems and Teleteaching, 4, 19-25.

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Brusilovsky, P., Kobsa, A., & Vassileva, J. (Eds.) (1998). Adaptive hypertext and hypermedia. The Netherlands: Kluwer Academic Publishers. Dubois, D., Pride, H., & Yager, R. R. (Eds.) (1993). Fuzzy rules in knowledge-based systems. In Reading in fuzzy sets for intelligent systems. San Francisco: Morgan Kaufmann. Gallant, S.I. (1993). Neural network learning and expert systems. Cambridge, MA: MIT Press.

Guin-Duclosson, N., Jean-Danbias, S., & Norgy, S. (2002). The AMBRE ILE: How to use case-

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based reasoning to teach methods. In S.A. Cerri, G. Gouarderes, & F. Paraguacu (Eds.), Sixth International Conference on Intelligent Tutoring Systems. Lecture Notes in Computer Science (Vol. 2363, pp. 782-791). Berlin: Springer-Verlag. Hatzilygeroudis, I. (guest editor) (2004). Special Issue on AI Techniques in Web-Based Educational Systems. International Journal on AI Tools (IJAIT), 13(2). Hatzilygeroudis, I. & Prentzas, J. (2000). Neurules: Improving the performance of symbolic rules. International Journal on Artificial Intelligence Tools, 9, 113-130. Hatzilygeroudis, I. & Prentzas, J. (2001a). Constructing modular hybrid rule bases for expert systems. International Journal on Artificial Intelligence Tools, 10, 87-105. Hatzilygeroudis, I. & Prentzas, J. (2001b). An efficient hybrid rule based inference engine with explanation capability. Proceedings of the 14th International Florida Artificial Intelligence Research Society Conference (pp. 227-231). Menlo Park, CA: AAAI Press. Hatzilygeroudis, I. & Prentzas, J. (2004a). Using a hybrid rule-based approach in developing an intelligent tutoring system with knowledge acquisition and update capabilities. Journal of Expert Systems with Applications, 26, 477-492. Hatzilygeroudis, I. & Prentzas, J. (2004b). Knowledge representation requirements for intelligent tutoring systems. In J.C. Lester, R.M. Viccari, & F. Paraguacu (Eds.), The 7th International Conference on Intelligent Tutoring Systems (ITS 2004). In Proceedings. Lecture Notes in Computer Science (Vol. 3220, pp. 87-97). Berlin: Springer-Verlag. Hwang, G.-J. (1998). A tutoring strategy supporting system for distance learning on computer networks. IEEE Transactions on Education, 41(4), 1-19.

Jameson, A. (1995). Numerical uncertainty management in user and student modeling: An overview of systems and issues. User Modeling and User-Adapted Interaction, 5(3-4), 193-251. Leake, D.B. (Ed.) (1996). Case-based reasoning: Experiences, lessons & future directions. Menlo Park, CA: AAAI Press/MIT Press. Magoulas, G.D., Papanikolaou, K.A., & Grigoriadou, M. (2001). Neuro-fuzzy synergism for planning the content in a Web-based course. Informatica, 25, 39-48. Nauck, D., Klawonn, F., & Kruse, R. (1997). Foundations of neuro-fuzzy systems. New York: John Wiley & Sons. Negnevitsky, M. (2002). Artificial intelligence: A guide to intelligent systems. Reading, MA: Addison Wesley. Nkambou, R. (1999). Managing inference process in student modeling for intelligent tutoring systems. In Proceedings of the Eleventh IEEE International Conference on Tools with Artificial Intelligence (pp. 19-23). Los Alamitos, CA: IEEE Computer Society Press. Prentzas, J., Hatzilygeroudis, I., & Garofalakis, J. (2002). A Web-based intelligent tutoring system using hybrid rules as its representational basis. In S.A. Cerri, G. Gouarderes, & F. Paraguacu (Eds.), Sixth International Conference on Intelligent Tutoring Systems. Lecture Notes in Computer Science (Vol. 2363, pp. 119-128). Berlin: Springer-Verlag. Reichgelt, H. (1991). Knowledge representation: An AI perspective. Norwood, NJ: Ablex Publishing. Russel, S. & Norvig, P. (2003). Artificial intelligence, A modern approach. Englewood Cliffs, NJ: Prentice Hall. Shiri, M. E., Aimeur, E., & Frasson, C. (1998). Student modelling by case-based reasoning. In

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B. P. Goettl, H. M. Halff, C. L. Redfield, & V.J. Shute (Eds.), Fourth International Conference on Intelligent Tutoring Systems (Vol. 1452, pp. 394-404). Berlin: Springer-Verlag.

Cerri, G. Gouarderes, & F. Paraguacu (Eds.), Sixth International Conference on Intelligent Tutoring Systems. Lecture Notes in Computer Science (Vol. 2363, pp. 708-717). Berlin: Springer-Verlag.

Simic, G. & Devedzic, V. (2003). Building an intelligent system using modern Internet technologies. Expert Systems with Applications, 25, 231-146.

Vanlehn, K. & Zhendong, N. (2001). Bayesian student modeling, user interfaces and feedback: A sensitivity analysis. International Journal of AI in Education, 12, 155-184.

Staab, S. & Studer, R. (Eds.) (2004). Handbook on Ontologies. Berlin: Springer-Verlag. Tchetagui, J. M. P. & Nkambou, R. (2002). Hierarchical representation and evaluation of the students in an intelligent tutoring system. In S.A.

Vassileva, J. (1998). Dynamic course generation on the WWW. British Journal of Educational Technologies, 29, 5-14.

This work was previously published in Web-Based Intelligent E-Learning Systems: Technologies and Applications, edited by Z. Ma, pp. 175-192, copyright 2006 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.8

Modes of Openness and Flexibility in Cognitive Flexibility Hypertext Learning Environments Rand J. Spiro Michigan State University, USA Brian P. Collins Michigan State University, USA Aparna R. Ramchandran Michigan State University, USA

IntroductIon The words openness and flexibility—the latter is the topic of this volume—are joined in the title of this chapter. We see them as two sides of the same coin—structure and process, as well as antecedent and consequent. Closed structures of presentation (how instructional materials are organized in delivery systems) and of representation (how knowledge is structured and operated upon in the mind) produce rigidity of thought and action. The antithesis of this rigidity is a kind of “openness-based” flexibility necessary

for adaptive knowledge application, for transfer of knowledge to new situations, for situationsensitive use of knowledge, and for the kind of world-fitting complexity of understanding that cognitive flexibility depends upon—and that the increasingly complex modern world of life and work needs now more than ever. Rigidity and oversimplification are rampant in learning and teaching (e.g., Feltovich, Coulson, & Spiro, 2001; Feltovich, Spiro, & Coulson, 1989, 1996; Spiro, Feltovich, & Coulson, 1996), but with the affordances of new media, we do not need to live complacently with this state of affairs (Spiro, in press).

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Modes of Openness and Flexibility in Cognitive Flexibility Hypertext Learning Environments

The perspective of cognitive flexibility theory (CFT; Mishra, Spiro, & Feltovich, 1996; Spiro, Coulson, Feltovich, & Anderson, 1988, 2004; Spiro, Feltovich, Jacobson, & Coulson, 1992a, 1992b; Spiro & Jehng, 1990) enacts openness in many ways—in the theory itself and in the multimedia learning systems based on the theory (cognitive flexibility hypertext learning environments, CFHs). A recent overview of CFT can be found in Spiro, Collins, and Thota (2003).

A non-exhAustIve cAtALogue oF Modes oF oPenness And FLexIbILIty In cognItIve FLexIbILIty systeMs Openness—and related flexibility—come into play in a wide variety of ways in learning systems based on CFT. Although we provide here the first cataloguing of a substantial sample of those ways that CFHs are characterized by forms of openness that promote flexibility, it is worth emphasizing that this is just a sample, that there are many more ways that each of the types listed below can be considered “open” and, in turn, create flexibility; and that there are more types than just these. It should also be noted that in this short chapter we will be talking only about characteristics of CFHs. We recognize that some of the features we discuss may be employed in other instructional design approaches in forms of varying similarity and difference to that used in CFHs. Each of the following kinds of openness are found in all CFHs, with the exception of the ones that are specific to digital video cases, where the features are built into the subspecies of CFHs called EASEs (experience acceleration support environments). To see operative examples of many of the points that follow, see EASE-history (http://www.easehistory.org/), a system that uses presidential campaign ads, historical events, and core values to support the learning and teaching

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of U.S. history (Collins, Ramchandran, & Spiro, in preparation).1

the Foundation: complex, open, and Flexible habits of Mind Most important of all in fostering more flexible thinking is the establishment of appropriate habits of mind (ways of thinking, worldviews, mindsets, and so on that prefigure the kinds of knowledge that will be built by an individual). People too often adopt a knowledge stance that we have characterized as the reductive world view, made up of a number of Reductive Biases (Feltovich et al., 1989, 1996, 2001; Spiro et al., 1996, 1988, 2004). This is a tendency to see the world as made up of events and phenomena that are orderly, predictable, decomposable into additive elements, non-contingent, and well structured, and accordingly to have personal epistemologies that see learning as best accomplished by approaches that lead to representations that are simple and highly general (capturing a topic with a single schema, prototype example, set of general principles and definitions, etc.), compartmentalized or “chapterized,” and so on. When these habits of mind are prevalent, the result is structures of knowledge that are relatively more closed and, as a result, inflexible in operation. The alternative—necessary in complex and more ill-structured arenas of knowledge—counters the tendencies just described with approaches that foster the building of knowledge characterized by multiple representation, interconnectedness, contingency (context-dependence, a tendency to recognize when it is appropriate to say “it depends” and to acknowledge that many situations are not “either/or,” but rather shades of gray in between). All of the kinds of openness built into CFHs, as outlined below, are intended to shift habits of mind from the relatively closed to the more open, as well as to build specific content knowledge that has various forms of openness.

Modes of Openness and Flexibility in Cognitive Flexibility Hypertext Learning Environments

opening up of comparison and contrast: beyond Pairs The latest versions of CFHs (EASE systems) permit video examples to be compared in pairs on the screen. However, an important innovation has been the ability to set up results from multiple theme searches in each of four quadrants. Fourway comparisons open up categories to reveal subtle but important differences (e.g., “example one is kind of like example two in one way, but like examples three and four in yet other ways, even though all are similarly categorized”)—and these nuanced differences are a basis for flexible application of knowledge in situations that also differ from each other in subtle ways. (An even greater expansion of the notion of comparison and contrast is found in CFH/EASEs’ use of as many as a dozen rapidly comparable short versions of larger, overlearned video cases to permit a manytimes increase in the number of comparisons that can be made in a relatively short amount of time. This is a key feature promoting experience acceleration in these new systems).

crossroads cases Instruction in CFHs begins with carefully chosen examples that are rich in the lessons they teach, and that we call “crossroads cases.” The lesson for openness is that events in a knowledge domain are not just examples of one thing, but rather involve the intersection of multiple concepts and are amenable to a continuing process of making additional interpretations (all of which require justification, of course). Cases, occurrences, events, and examples are open, and therefore they are precedents/experiences that act as a basis for future knowledge assembly in a wider variety of ways—thus the openness of individual cases promotes flexibility.

Many cases CFHs employ large numbers of cases, opening up the space of possible precedents/prototypes for greater flexibility in later knowledge application. Furthermore, the fundamental organizing unit of CFHs is the mini-case. Larger cases are broken into several small segments so that coding of the CFH can be based on unique local properties rather than only those of the larger case they are drawn from, which would reduce the coding to a common denominator (which would miss much that is important) or, at the other extreme, include too much that applies only to a small region within a larger case and thus is misleading about the case as a whole. (Structuring in small segments also permits a new incrementalism of instructional sequencing in which one can begin learning with bite-size chunks of cognitively manageable complexity that establishes appropriately complex habits of mind from the beginning of instruction without overwhelming learners.) By breaking cases into a set of mini-cases, the number of examples worked with is greatly increased, further opening the space of possible prototypes for future action and providing many more opportunities for relating new instances to old ones—a many-fold increase in the bases for flexibility.

conceptual variability One of the first instructional moves in any CFH is a conceptual-variability search. By clicking on a concept or theme, one finds a variety of real-world examples that illustrate that theme. The lesson that is immediately taught is that complex concepts do not have a denotative semantic core that limits their possibilities for application, but rather are governed by family resemblance relations. The conceptual-variability search illustrates the variety of ways the concept is used. This opening

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up of the range of possible uses of a concept in turn enables learners to use it in more different ways—that is, to employ the concept with greater flexibility.

Multiple higher-order conceptual themes CFHs always employ multiple ideas “at the top.” That is, we analyze the subject area to identify several different concepts that different experts have proposed as the “most important and central.” And then we use them all. By opening up the topmost structure of a domain and providing learners with multiple entry points, each a candidate for “best superordinate concept,” the chances of being able to optimize the prior knowledge activated to fit a new context is greatly increased—and situation-sensitive flexibility in applying knowledge is enhanced.

Multiple theme search: Playgrounds for combining Ideas CFHs permit searches for examples that illustrate the combination of concepts or themes. This allows for learners to form increasingly more sophisticated hypotheses about the subject area they are studying, the problem they are trying to solve, or the essay they are trying to write. The CFH acts as a kind of Combinatorial Idea Playground, all the while tied to actual occurrences (to insure that the ideas do not end up in the clouds, unconnected to realities on the ground). This permits a many-times expansion of the ways material can be organized, and this opening up of the organizational space enables a great increase in the flexibility with which material can be conceptually captured and later deployed.

Multiple Interconnectedness By having a large number of mini-cases coded with a large number of conceptual themes, CFHs

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automatically produce highly interconnected structures that intertwine along multiple dimensions. This produces a huge number of possible retrieval routes in memory and possibilities for flexible knowledge assembly in new contexts, as situational information ‘carves out’ alternative paths through the Web-like representation.

nonlinear Juxtaposition A basic feature of all CFHs is that they create juxtapositions, sometimes quite unexpected ones, of cases that diverge from ordinary conceptual category membership. These “jumps” are the result of an opening of the organizational space, and this flexibility of organization instills habits of mind of flexibility, showing learners that they need not be bound by preestablished “lines of thought.”

Perceptual overlays to open Perception Some CFHs for digital video cases (EASE systems) employ various kinds of perceptual overlays to open and deepen perception. For example, when learners tend to watch one part of a video scene to the exclusion of other parts, we show the scene again, this time perhaps in slow motion and with spotlights on the neglected parts. People quickly get the message that what they first see is not all they can and should see—and they develop the habit to look more closely, and then to look again to see more. When we find that people accept what they see uncritically, we use editing effects to cause the appearance of the video image shattering into fragmented shards, accompanied by a sudden loud noise—dissonance is created and complacent viewers are shaken out of their too great ease with what they think they are seeing. Again, habits of mind are hard to change, and strong measures are required to capture their attention, make them realize they are seeing too simply, and show them

Modes of Openness and Flexibility in Cognitive Flexibility Hypertext Learning Environments

that they are capable of seeing more if they look harder and with fewer blinders on. Sometimes we have learners associate musical soundtracks that correspond to conceptual stances (as people naturally associate certain kinds of music in a film with suspense, for example), and then play the same video scene with different soundtracks. Learners quickly see that a scene, say from a classroom, is very much open to interpretation. (We do similar things with color filters, in much the same way as was done in the film, “Traffic.”) These are just a few of the ways that CFT uses perceptual enhancements to open up perception (and, incidentally, to reduce cognitive capacity demands). And the more one sees in a case, the more ways that case can be interpreted. As a result, there is a greater range of future uses to which the knowledge acquired from the case can be put—an important source of flexibility.

opening time We are too often bound by temporal adjacency— events that occur near each other in time are easily related to each other, while those that are more temporally distant are less likely to be connected in our knowledge representations. CFH/EASE systems employ a convention for the placement of picture-in-picture videos to more organically connect events that have distant antecedents and consequents (with the former occurring in the lower left of the screen and the latter in the lower right of the screen, as an example of part of the time-representation scheme). By opening time, we increase the opportunity to form connections flexibly.

concLusIon Various modes of openness in learning environments based on cognitive flexibility theory have been presented. The more ways that presenta-

tion formats and knowledge representations converge to promote open rather than closed thinking (though never in an “anything goes” manner—there must always be a warrant for any “opening” of representation), the greater the flexibility in future knowledge application that will result. This will be due in part to the greater opportunities for flexible knowledge assembly that open knowledge structures permit; but it will also be due to the more complex and flexible ways of thinking that will be formed and begin to become habitual. The result is the creation of mindsets that perpetuate the development of flexibly applicable knowledge and that eventually do not depend upon external support from computer learning environments—habits of mind that are the basis for independent, adaptive learning. And given the widespread bias toward rigid and oversimplified ways of thinking, the value of any learning approaches that combat that powerful trend cannot be underestimated—the reductive bias must be combated with all the resources that random access technologies can offer.

reFerences Collins, B. P., Ramchandran, A. R., & Spiro, R. J. (in preparation). EASE history: A cognitive flexibility hypermedia system that supports history learning. Feltovich, P. J., Coulson, R. L., & Spiro, R. J. (2001). Learners’ understanding of important and difficult concepts: A challenge to smart machines in education. In P. J. Feltovich & K. Forbus (Eds.), Smart machines in education. Cambridge, MA: MIT Press. Feltovich, P. J., Spiro, R. J., & Coulson, R. L. (1989). The nature of conceptual understanding in biomedicine: The deep structure of complex ideas and the development of misconceptions. In D. Evans & V. Patel (Eds.), The cognitive

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sciences in medicine (pp. 113-172). Cambridge, MA: MIT Press. Feltovich, P. J, Spiro, R. J., & Coulson, R. L. (1997). Issues of expert flexibility in contexts characterized by complexity and change. In P. J. Feltovich, K. M. Ford, & R. R. Hoffman (Eds.), Expertise in context: Human and machine. Cambridge, MA: MIT Press. Mishra, P., Spiro, R. J., & Feltovich, P. J. (1996). Technology, representation, and cognition: The prefiguring of knowledge in Cognitive Flexibility Hypertexts. In H. van Oostendorp & A. de Mul (Eds.), Cognitive aspects of electronic text processing (pp. 287-305). Norwood, NJ: Ablex. Spiro, R. J. (in press). The new Gutenberg revolution. Educational Technology. Spiro, R. J., Collins, B. P. Thota, J. J., & Feltovich, P. J. (2003). Cognitive flexibility theory: Hypermedia for complex learning, adaptive knowledge application, and experience acceleration. Educational Technology, 44(5), 5-10. Spiro, R. J., Coulson, R. L., Feltovich, P. J., & Anderson, D. (2004). Cognitive flexibility theory: Advanced knowledge acquisition in ill-structured domains. In R. B. Ruddell (Ed.), Theoretical models and processes of reading (5th ed., pp. 602-616). Newark, DE: International Reading Association. [Reprinted from Proceedings of the 10th Annual Conference of the Cognitive Science Society (1988). Hillsdale, NJ: Lawrence Erlbaum] Spiro, R. J., Feltovich, P. J., & Coulson, R. L. (1996). Two epistemic world-views: Prefigurative schemas and learning in complex domains. Applied Cognitive Psychology, 10, 52-61. Spiro, R. J., Feltovich, P. J., Jacobson, M. J., & Coulson, R. L. (1992a). Cognitive flexibility, constructivism, and hypertext: Random access

instruction for advanced knowledge acquisition in ill-structured domains. In T. Duffy & D. Jonassen (Eds.), Constructivism and the technology of instruction (pp. 57-75). Hillsdale, NJ: Lawrence Erlbaum. (Reprinted from a special issue of the journal Educational Technology on Constructivism.) Spiro, R. J., Feltovich, P. J., Jacobson, M. J., & Coulson, R. L. (1992b). Knowledge representation, content specification, and the development of skill in situation-specific knowledge assembly: Some constructivist issues as they relate to cognitive flexibility theory and hypertext. In T. Duffy & D. Jonassen (Eds.), Constructivism and the technology of instruction (pp. 121-128). Hillsdale, NJ: Lawrence Erlbaum. (Reprinted from a special issue of the journal Educational Technology on Constructivism.) Spiro, R. J., & Jehng, J. C. (1990). Cognitive flexibility and hypertext: Theory and technology for the nonlinear and multidimensional traversal of complex subject matter. In D. Nix & R. J. Spiro (Eds.), Cognition, education, and multimedia: Explorations in high technology (pp. 163-205). Hillsdale, NJ: Lawrence Erlbaum. Spiro, R. J., Vispoel, W. L., Schmitz, J., Samarapungavan, A., & Boerger, A. (1987). Knowledge acquisition for application: Cognitive flexibility and transfer in complex content domains. In B. C. Britton & S. Glynn (Eds.), Executive control processes. Hillsdale, NJ: Lawrence Erlbaum.

endnote 1

For access to other systems that have a fuller set of features, send a note requesting URLs and a password to [email protected].

This work was previously published in Flexible Learning in an Information Society, edited by B. H. Khan, pp. 18-25, copyright 2007 by Information Science Publishing (an imprint of IGI Global). 1908

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Chapter 4.9

Overcoming Organizational Barriers to Web Accessibility in Higher Education: A Case Study

Amy Scott Metcalfe The University of Arizona, USA

Abstract The number of students with disabilities who attend college is rising, which may be one of the many positive outcomes of the Americans with Disabilities Act of 1990. While issues of adequate access to assistive technologies in computer labs, classrooms and libraries continue to be of importance for students with disabilities, it is apparent that consideration of the accessibility of academic cyberspace is also important for this growing population of students. This chapter is a case study of a successful Web accessibility initiative at the University of Arizona. Recommendations for both policy and implementation are included,

with a discussion of how organizational culture and structure affects such efforts.

INTRODUCTION The impact of the Americans with Disabilities Act of 1990 has been felt in nearly every aspect of our society. People with disabilities, a group that includes about 53 million Americans,1 have more opportunities to attend school, to work and to participate in activities common to nondisabled people ten years ago. At the start of the 21st century, the tenth anniversary of this important piece of social legislation, the application of ADA law to the realm of information technology, has

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Overcoming Organizational Barriers to Web Accessibility in Higher Education

the potential for even greater social reform. In Information Access and Adaptive Technology (1997), Cunningham and Coombs describe how technology can affect the lives of people with disabilities: This cultural revolution is taking place at precisely the same time that America is reaching the peak of the Information Age, a period in which computer technology and electronic information are becoming integral to our society. This technology has been a boon for people with disabilities. Adaptive input and output devices make it possible for people with any type of disability or combination of disabilities to manipulate and use computers, while special computing software and hardware packages have provided unprecedented ways for people with disabilities to accomplish tasks and access information. However, the promise of computer technology to lead to greater educational and employment opportunities for people with disabilities is often dependent upon the creation and use of assistive technology (hardware) and accessible electronic information (software and Web sites). Unlike other populations experiencing the Digital Divide, for people with disabilities, access to computers is only part of the problem. Assistive technologies, created to interface with computer hardware and software, are often necessary (and costly). At the software and Web-page level, inaccessible coding and scripts create barriers to input, navigation and informational content. In many cases, specialized training, awareness building and organizational support are necessary for widespread changes in accessibility status to occur within an institution’s Web space. Unfortunately, the mere existence of guidelines and policies has not been sufficient impetus for change in some organizations. The issue of Web accessibility, which concerns Web content and its particular coding, is an excellent example of a case where institutional values and obligations are not automatically made evident

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in the electronic environment of the World Wide Web. If “institutional Web space” exists, then do the same rules and standards of behavior that apply to an organization in real life also apply to its corner of cyberspace? An important place to study the concept of institutional Web space is in the field of higher education. By the absence of institutional policies that mandate electronic accessibility, barriers to equal educational and work opportunities currently exist within colleges and universities (Burgstahler, 2000). Due to the increasing awareness about the topic at an administrative level, some institutions have chosen to examine their accessibility status and create policies to ensure equal access (Foster, 2001).2 Other institutions have yet to make any assessments regarding the issue. The process of creating an accessible Internet has been slow thus far. Although international standards for Web accessibility have been set by the World Wide Web Consortium’s (W3C) Web Accessibility Initiative (WAI), few institutions have mandated implementation of the guidelines. Perhaps this is due, in part, to the egalitarian nature of the Internet, which has made regulation of the Web environment a politicized issue (Lessig, 1999; Liberty, 1999; Resnick, 1997). Thus, the perceived “freedom” of the Internet may in fact inhibit the implementation and enforcement of ADA legislation regarding Web accessibility. The role of individual institutions and organizations in the creation of policies that require compliance with accessibility measures within their cyber-domains is important to the understanding of the interplay between Internet regulation and civil rights issues in electronic environments. This issue deserves thorough study. In particular, research into the process of accessibility policy formation and implementation at the institutional level has the potential to identify the social and organizational factors that may either contribute to or inhibit reforms that could foster greater independence and quality of life for persons with disabilities.

Overcoming Organizational Barriers to Web Accessibility in Higher Education

bAcKground A recent Harris Poll (June, 2000)3 shows the extent to which the Internet has offered a degree of independence for people with disabilities. The poll, “How the Internet is Improving the Lives of Americans with Disabilities,” demonstrates that the positive impact of online services and communication is much greater for adults with disabilities than for those who are not disabled. The poll reported that of people who are using the Internet: •

•

•

Adults with disabilities spend, on average, twice as much time online as adults without disabilities (20 hours per week compared to 10 hours per week). Adults with disabilities (48%) report that the Internet has significantly improved the quality of their lives, compared to 27% of nondisabled adults who said this. Young people (under 30) with disabilities use the Internet much more than young people without disabilities: 25 hours a week versus 8 hours a week.

The significance of this poll to the field of higher education is that students with disabilities are likely to perceive the Internet as a positive aspect of their lives. As the use of computers continues to rise dramatically among all college students, those with disabilities will likely benefit from the availability of electronic educational materials, and will probably find themselves face-to-face with issues of electronic access.

students with disabilities in Postsecondary education The number of students with disabilities who attend college is small, but rising. Three research studies conducted in the late 1990s have provided a profile of students with disabilities in higher

education. One of the reports, “An Institutional Perspective on Students with Disabilities in Postsecondary Education” (NCES, 1999), stated that about 428,280 students with disabilities were enrolled at institutions of higher education in 1996-1997 or 1997-1998. While this study, based on the Postsecondary Education Quick Information System (PEQIS), provided some information about students with disabilities at 2-year and 4-year institutions, it did not report the total sample of students. The U.S. Department of Education document, “Students with Disabilities in Postsecondary Education: A Profile of Preparation, Participation, and Outcomes” (NCES, 1999), provided a breakdown of disability status among college students surveyed. In 1996, the National Postsecondary Student Aid Study (NPSAS:96), a nationally representative sample of undergraduate students (about 21,000), were asked to respond to the following question: “Do you have any disabilities, such as hearing, speech, mobility impairment, or vision problems that can’t be corrected with glasses?” Six percent of the sample responded yes: of those students, 29% indicated they had a learning disability; 23% said they had an orthopedic disability; 16% had a hearing loss; 16% were visually impaired; 3% had speech impairments; and 21% noted “other” disabilities or impairments. (Note that some students had multiple disabilities, so the sum does not equal 100%.) Yet another study on students with disabilities, “College Freshmen with Disabilities: A Biennial Statistical Profile” (Henderson, 1999) was published by the American Council on Education. The data for the report was gathered by the Cooperative Institutional Research Program (CIRP), which surveyed full-time freshmen who enrolled at public and private nonprofit universities and colleges in 1998. In the survey year, 154,520 freshmen indicated they had a disability, which was 9% of the total respondents. The report stated:

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In 1978, the first year the CIRP survey included a question on disabilities, slightly less than 3 percent of freshmen reported a disability. By 1998, the percentage had more than tripled to 9 percent. This meant that one in every 11 freshmen enrolled full time reported at least one disability. Thus, college and university campuses are experiencing an increase in enrollment of students who self-identify as having a disability. When reviewing statistics of college students with disabilities, it is very important to note the differences that exist among the various types of disabilities present in the group. For example, the Henderson report states that students with learning disabilities are more likely than other disabled students to be white, be from high-income families, and have earned C or D averages in high school. In contrast, students with visual impairments are more likely than other disabled students to be female, come from lower middle-class families, and have earned an A average in high school. Among all 1998 freshmen, students with disabilities were more likely than the general cohort to be male, white, and be slightly older than other first-time freshmen. In addition, freshmen with disabilities were more likely than other students to enter a twoyear college and aspire to a vocational certificate or associates degree (Henderson, 1999). The policy implications for institutions of higher education revolve around the increasing numbers of students with disabilities who are attending college and the rise of computing services on campuses. While issues of adequate access to assistive technologies in computer labs, classrooms and libraries continues to be of importance for students with disabilities, it is apparent that consideration of the accessibility of academic cyberspace is also imperative for this rising population of students.

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Academic cyberspace and students with disabilities In the decentralized world of academic cyberspace, Web accessibility guidelines challenge norms of self-regulation inherent to the Internet culture, while simultaneously reinforcing egalitarian notions of unfettered access to higher education. As one of the first nationally recognized issues to affect the governance of cyberspace, the topic of Web accessibility brings to light previously hidden organizational hierarchies that are endemic to collegiate computing networks. Further, Web accessibility guidelines have tested the boundaries and budgets of centralized computing services and have amplified the need for more training of Web-authoring staff in most departments and academic units. In addition, attempts to formulate Web accessibility plans call to question the locus of authority over academic cyberspace. This chapter examines these issues as they became evident during a Web accessibility implementation effort at the University of Arizona. In this process, the University’s Web council found that a “point-ofcontact” evaluation and endorsement procedure fit the organizational culture best and helped to create an environment of promotion rather than enforcement.

cAse study: the unIversIty oF ArIZonA The University of Arizona is a Research I institution, established in 1885 when Arizona was still a U.S. Territory. The University opened its doors in 1891 to just 32 students. Considerable growth has occurred in subsequent years, with 34,488 students enrolled in 2000. A similar pattern of growth has marked the university’s cyberspace. Although the main Web site began with just under 100 hyperlinked pages in 1994, today many thousands of Web pages share Arizona’s “edu” extension. Since the site’s inception, usability and

Overcoming Organizational Barriers to Web Accessibility in Higher Education

accessibility have been a main developmental concern. The University of Arizona’s main Web site (www.arizona.edu) is managed by the UA Web Council, an appointed committee of 13 volunteers and two paid staff members. Although the membership roster of the council has changed many times since the Web site was created in 1994, this council is still comprised of representatives from the university who are responsible for the dissemination of vital information to the campus community. The council has served to guide the fledgling Web site and to inform university administrators of issues related to this new media. In the early days of the Web site (1994–1998), the demand and expectation for Internet-based information was low, allowing the “lean” management and technical staffing structure to proceed without much trouble. However, today’s students and staff members are much more interested in using Web pages as part of their daily contact with the university. For example, according to server logs, during a one-week period in October 2001, the university’s main pages were visited by 64,884 “distinct hosts,” which roughly corresponds to the numbers of individuals who enter the UA’s cyberspace.4 In comparison, server logs for the same week in 1998 show 31,046 distinct hosts having accessed the UA’s Web pages, which is less than half the number of visitors in 2001. Yet precisely when interest in the Web site has risen, state appropriations for new staff and equipment has not kept up with the demand for new or expanded services throughout the University.5 As a result, the UA Web Council remains a volunteer body, and the number of technical staff has not grown much despite increased responsibilities. Thus, centralized services remain limited, leaving many departments with the role of hiring Web designers or training their own Web-authoring personnel. Needless to say, this has resulted in an uneven distribution of technical staff throughout the university and has contributed to the culture

of decentralization so common to academic computing and network services. In spite of these challenges, the University of Arizona’s Web management structure has taken considerable strides toward overall usability of the campus Web and toward the specific issue of Web accessibility for computer users with disabilities. Today, the home page is completely accessible to users with disabilities, the result of a conscious effort by the institution’s Web managers and designers. In addition, the UA Web Council and the technical staff behind the UA’s main pages have brought the issue of Web accessibility before the campus community in a concentrated six-month effort, which has resulted in an overall rise of accessible pages at the rate of about 18%. This project will be described below.

uA web Accessibility Plan While the basic connection to the Internet is technically operated much like telephone services, the contribution of campus units to the content of academic cyberspace is unlike other communications media. The UA’s Web site is a mosaic of pages with multiple authors. Like many academic Webs, it is not governed by a single administrative unit with a distinct office and a well-delineated hierarchy of authority. Instead, the UA Web site operates more like a collective repository with a grassroots management structure. This characteristic has been intentionally cultivated by those who began using the Web in the early years, and is very much representative of the self-governance norms of the Internet as a whole. While the lack of central authority over academic cyberspace can create difficulties for policy-makers, it is precisely this culture of academic freedom that makes the Web so appealing and useful for campus units. The introduction of Web accessibility came to the University of Arizona in a gradual stream, starting with early efforts to make pages usable by

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anyone, anywhere. As an outgrowth of usability issues, the importance of Web accessibility seemed to come naturally to the UA’s Web management team. However, due to the exponential growth of the university’s cyberspace, only a fraction of the pages that claim a part of the “arizona.edu” domain are centrally managed and under the direct purview of the UA Web Council. Rather, most pages are managed by academic units, administrative offices and other service centers on campus. As such, there is no governing body that has influence over the entire “arizona.edu” domain. While this structure is not uncommon for academic Web sites, it provides challenges to the formulation and implementation of Web accessibility plans. While the issues of Web accessibility at a basic level had been part of the Council’s focus from the beginning, a more formalized approach to the topic began during the spring semester of 2001. It became apparent to the Council that issues of Web accessibility would require creative uses of resources and an investment of time from the largely volunteer Council’s membership. In addition, the Council began to form a working relationship with the University’s Disability Resource Center (DRC) and the ADA Coordinator’s office. Further, the Council sought advice from the university’s Attorney’s Office and Center for Computing and Information Technology (CCIT) administrators. The UA Web Council’s central role in a campus-wide Web accessibility plan was influenced by three factors: precedent for overseeing Web-related issues, member contact with federally funded grants that highlighted issues of access for the disabled and an institutional request to investigate the university’s responsibilities in light of federal legislation. Much of the success of the UA Web Council’s efforts toward bringing the issues of Web accessibility to the foreground was due to the direct and indirect influence of three federally funded projects devoted to increasing access to higher education for students with disabilities. The first

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of these grants was the Department of Education’s Office of Postsecondary Education grant program titled “Demonstration Projects to Ensure Quality Higher Education for Students with Disabilities.” The University of Arizona’s grant is titled “Program to Enhance and Ensure Learning (PEEL) for Students with Disabilities.”6 As the UA’s grant was housed in the University Teaching Center, a campus entity that plays a role in providing technical training to faculty who desire to create instructional Web pages, raising awareness of electronic access issues became part of PEEL’s contribution to a more open academic environment for students with disabilities. Through several PEEL projects, campus computing staff and staff from the Disability Resource Center became working partners, thus paving the way for later discussions on ways in which to improve Web accessibility campus-wide. Another federal program, the Department of Education’s Fund for the Improvement of Postsecondary Education (FIPSE) Learning Anytime Anywhere Partnerships (LAAP), also provided assistance to the UA Web Council during the initial phases of formulating the campus Web accessibility plan. One of the LAAP projects, the Virtual Adaptive Learning Architecture (VALA)7 program, included an emphasis on meeting federal guidelines for Web accessibility. Through staff training efforts and project team discussions, the VALA site was adapted for accessibility. In a short time, the staff involved in the VALA project became accessibility consultants for others in the instructional computing area, which also added to the resources available to the UA Web Council when the time came for a thorough discussion of Web accessibility. In the process of reviewing other LAAP grants, the WebAIM8 project was discovered. WebAIM was started to provide information via the Internet to postsecondary institutions on the topic of Web accessibility. Staff members from the WebAIM program were invited to the University of Arizona in April 2001 to work with the VALA project team and

Overcoming Organizational Barriers to Web Accessibility in Higher Education

to offer specific information about organizing a campus-wide accessibility plan. A presentation by WebAIM staff was organized for the campus community and was attended by over 90 campus Webmasters and staff from various departments. This event was the first of several university-wide presentations sponsored by the UA Web Council on the topic of Web accessibility and was helpful in raising awareness of the legal and ethical issues surrounding the use of the Web at institutions of higher education. With the help of WebAIM staff and cooperative efforts from the Disability Resource Center and ADA Coordinator, the UA Web Council developed a plan to address the issue of Web accessibility on campus. First, it was decided that a baseline study was needed to better understand the present state of accessibility of high-level campus Web pages. Second, the complicated recommendations and guidelines for accessibility issued by various federal and nonprofit agencies would be simplified for the campus audience to account for varying comfort levels with hand-coding HTML. Third, a detailed Web-based resource would be created for the campus community, and workshops would be given to introduce the resource to campus Webmasters. Fourth, a logo would be created for use on Web sites that met accessibility guidelines, and a paper certificate would be created as an award for the departments making the necessary changes. This four-part plan was begun in May 2001 and continued through the summer and into the following academic year.

baseline study In May of 2001, the UA Web Council’s Web Resources Committee and the Disability Resource Center tested 224 departmental home pages, which were hyperlinked from the main university Web site. Although several methods of accessibility testing were discussed, it was determined that the best method for an initial test was to use the Bobby Downloadable Accessibility Tool, also known as

Bobby 3.2.9 The decision to use the Bobby tool was based on the fact that it was free and available to anyone over the Internet (enabling departments to test their own sites if they desired), it had been used by other researchers (see Schmetzke, 1999, 2000), and it was quick. However, there were drawbacks to the Bobby system in that it was only able to check for very basic accessibility guidelines and could not detect errors that required subjective reasoning. In this way, it was highly unlikely for Bobby to generate a “not approved” rating for an accessible site given that the features it was able to check were fairly straightforward (alt-tags and NOFRAMES tags). In addition, these features were the easiest to correct by someone wanting to make a site accessible. However, it was very likely that the Bobby tool would provide a false “approved” rating in that many more features would have to be manually checked in order to ensure that a site was indeed fully accessible. Therefore, the data generated from the baseline test can only be used as a general guide and are not intended to report actual accessibility rates for any set of Web sites. Of the 224 pages checked during the first baseline test in May of 2001, 45 pages received an “approved” rating (20%) and 179 received a “not approved rating” (80%). When the test was repeated in October 2001, more pages had been hyperlinked to the index page, resulting in a sample of 262 pages. Of these 262 pages, 100 received an “approved” rating (38%), and 162 received the “not approved” rating (62%). Thus, in the time since the first test, the number of “approved” pages that were hyperlinked from the departmental home page index rose by 18%. In this six-month period of time, the UA Web Council gave seven presentations on Web accessibility to over 232 campus Webmasters and other staff members and had made available a Web site on accessibility (discussed below). For sake of comparison, a similar study conducted at the University of Wisconsin system by Schmetzke shows that the UW-Madison campus’s academic

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department pages rose from 38% accessible in 1999 to 44% accessible in 2001, for a change of just 6% over two years.10 While the rise in the number of accessible Web pages at the University of Arizona during the period of May to October 2001 may not be indisputable evidence of the effectiveness of the workshops and resources provided by the UA Web Council, the number suggests that campus Webmasters were responding to the issue and making changes to their sites. External factors, such as increased exposure to Section 508 guidelines through trade magazines and conferences, may be responsible for the changes. A more detailed study would be needed to examine which departments and administrative units have made accessibility changes and to find patterns that might exist to explain why they were able and willing to make their Web pages accessible, while other departments were not. It is likely that the availability of resources, both in skilled labor and technology, might have an impact on a campus unit’s ability to revise Web pages for accessibility. This is no small factor, especially given that software companies have not made significant strides in creating adequate WYSIWIG Web-authoring tools that automatically create accessible Web pages.

web Accessibility resources online After the completion of the first baseline study, it was apparent that an easy-to-use guide for making accessible Web pages was needed to help the University of Arizona’s Webmasters. The Web Resources Committee created a series of pages dedicated to Web accessibility as part of an overall effort to create online resource pages on various topics of Web design for use by campus Webmasters. The Web Accessibility Resources area (http://uaWeb.arizona.edu/resources/accessibility.shtml) is divided into the following sections: Why Accessible?, Testing Tools, Support, Makeovers & Examples, UA Web Accessibility Implementation Plan and UA Accessible Web

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Sites. Each content area contains many pages that provide detailed information about how to make Web pages accessible and the rationale for doing so. While many useful Web sites already exist that explain how to code Web pages for accessibility, the Web Resources Committee decided that the University of Arizona’s Webmasters and Web authors would be more comfortable with a homegrown version that specified campus policies and provided local support information. It was also decided that examples specific to the University of Arizona would provide incentive for Webmasters to participate in the move toward accessibility and would strengthen the Web community on campus. Part of this process was to ask a few departments and administrative units if their sites could be “made-over” by the UA Web Team and displayed on the Web Accessibility site in a “before and after” fashion. It was also discovered during campus presentations that a “dummy” site containing several accessibility errors was useful as an example, and it provided an opportunity to have a “makeover” that did not cause potential embarrassment to any specific campus entity. The dummy site also allowed for a detailed set of alternative displays, such as a page that provides a “transcript” of a JAWS screen reader as it would sound reading both the inaccessible and the accessible versions, an image of the pages as if they were being viewed with a text-only browser and an image of the pages as if they were being viewed with images turned off in the browser. Examples such as these have proven invaluable for instructional purposes when presented to Web site developers at campus workshops. An important part of the Web Accessibility Resources site is the inclusion of the UA Web Accessibility Implementation Plan. In the absence of specific institutional policy regarding Web accessibility, the UA Web Council partnered with the Disability Resource Center and the ADA Coordinator to develop a three-phase plan to gradually introduce accessibility guidelines to

Overcoming Organizational Barriers to Web Accessibility in Higher Education

campus Webmasters. It was felt that W3C guidelines and Section 508 guidelines were somewhat confusing for the average Web author on campus. As such, the guidelines were broken down into three phases, with the compliance goal for Phase One set at January 1, 2002 and the goal for Phase Two at January 1, 2003. The date for Phase Three is unset due to questions the council has about the feasibility of achieving compliance with the guidelines, such as those for synchronous captioning for multimedia elements. It is hoped that as technical solutions are found for these guidelines, a realistic compliance goal can be set, sometime in the near future. Phase One of the UA Web Accessibility Implementation Plan was the primary focus of Council workshops and presentations in 2001. Phase One guidelines are similar to Section 508 guidelines, and they address the most common accessibility errors. The Phase One guidelines are as follows: 1. 2.

3.

4.

5.

6.

ALT Tags: A text equivalent for every nontext element shall be provided for every image within the Web site. Image Maps: Image maps must be made as accessible as possible by adding ALT tags for each hot spot and providing redundant text links. Color: Color-coding shall not be used as the only means of conveying information. The contrast between colors used should be distinct. Hyperlink Titles: The titles for each hyperlink must be meaningful. Titles like “Click Here” can cause problems. Frames: If your Web site is using frames, a NOFRAMES section with equivalent content will be provided. Meaningful titles will be provided for each frame. Charts and Graphs: The content and meaning of a chart or graph should be described in text to make it accessible to all users.

7.

8.

Form Labels: Form elements will be tagged with the label attribute. Contact information will be provided on each page with a form. Scripts, Applets and Plug-Ins/PDF: Provide contact information on each page with a script, applet or plug-in so that users can ask questions or request the information in an alternative format.

On the Web Accessibility Resources site, each numbered guideline is hyperlinked to a set of pages that contain detailed directions for making HTML changes to correct accessibility errors. In addition to the eight areas above, the Phase One guideline page also mentions how to create user-centered Web pages, discusses text-only equivalents, includes information about what to do with archived or out-of-date pages and contains some thoughts about Webmaster responsibilities. Phase Two guidelines add four guideline areas for campus Webmasters to consider: tables, cascading style sheets, skip navigation links and a discussion of how to make changes to dynamic HTML to improve accessibility. Many of the changes recommended in Phase Two are beneficial for accessibility but may require more technical skill than many campus Web developers currently posses or may address issues that are not being utilized by the majority of Web developers at the university. For example, cascading style sheets are helpful for many users, yet many WYSIWIG Web-authoring tools do not provide adequate support to create them without specialized technical knowledge. Likewise, the use of scripts such as Java is not widely found on campus Web sites, but someone with this experience could read the guidelines and make the necessary changes. It is also hoped that Webmasters with high skill levels will jump beyond the Phase One guidelines quickly and move on to the more complicated accessibility fixes as they are able.

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web Accessibility Icon and Certificate Program As the UA Web Council was not in the position to review Web sites for accessibility compliance or to require changes be made, it decided that a recognition program would provide an incentive for departments to voluntarily review their sites and make accessibility changes. A series of icons (Figure 1) was developed that is used to identify pages within the university’s domain that have been rendered accessible by the responsible Webmaster or departmental representative. The concept was patterned after other successful programs such as the Bobby Accessible logo and the W3C’s HTML conformance icons. Approved applicants may display the UA Web Accessible icon on their page, provided that they hyperlink it to the Web Accessibility Resources home page and utilize an appropriate alt-tag on the image. In the first few months of the program, more than 30 campus departments completed the Phase One requirements and requested permission to use one of the “UA Web Accessible” icons on their pages. In addition to the use of the icons, a certificate is provided with each approval, which can be framed and displayed in the Webmaster’s office or in a public area. It is hoped that these incentives will contribute to a culture of access that has already begun to form in the University of Arizona’s electronic environment.

Point-of-contact Model Creating a culture of access is only the first step to a truly accessible Web environment. To be Figure 1. Web accessibility icons

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fully accessible, a system of accountability and oversight must be developed and maintained. Due to the decentralized management structure of the University of Arizona’s Web site as a whole, there was no existing reporting structure or hierarchy of personnel that might provide the backbone of such a system. However, the main Web pages, from which hundreds of campus pages are hyperlinked and indexed, are centrally maintained by the UA Web Team. As part of the “hyperlink policy,” the Webmasters of campus Web pages currently agree to abide by specified guidelines in order to be indexed from the main university pages. The addition of Web accessibility guidelines to the hyperlink policy would serve to reinforce institutional commitment to such issues, while providing a mechanism for compliance review. At this time, the UA Web Council does not feel that it would be fair to “unlink” sites that do not comply with changes in the hyperlink guidelines, but adding a “buffer” page might be an option. On the one hand, unlinking a site would not cause a page to disappear from the Web, but it would have to be found through a search tool on the university’s main page, a departmental page or by using a Web browser. The buffer page, however, would leave the nonconforming page hyperlinked to the main pages and would require users to pass through a disclaimer page that indicated that the page had not met university guidelines. Either scenario would be unappealing to Webmasters, and probably to visitors to the university’s Web site. Yet, this “point-of-contact” with the main Web page is important, and for some units, it is vital to the dissemination of their information. A “buffer-page” policy might unfairly penalize academic units or departments for lack of technical skill to make changes to their sites or for the inability to provide timely revisions. In response, some Webmasters may feel that it is a better short-term solution to remove themselves from the main Web page and indexes, thus creating an informational void and absence of participation by that academic unit or department. That

Overcoming Organizational Barriers to Web Accessibility in Higher Education

would not be a “win-win” scenario. In addition, this type of “top-down” management structure goes against much of the grassroots characteristics of academic cyberspace and does not reflect the nature of the Web environment as a whole. Careful consideration of the hyperlink policy is currently underway so as to not place an undue burden on campus Webmasters and to prevent a loss of informational content from the university’s Web community.

Future IMPLIcAtIons The study of policy formation in regard to Web accessibility is essential to the understanding of institutional responsibility in academic cyberspace. Whereas colleges and universities have responded to the needs of disabled students, faculty, staff and visitors in the physical world, only recently has there been an organized effort to accommodate their needs in the Web environment. Complete understanding of the institutional climate surrounding the use of Web-space is critical to the full implementation of accessibility policy. For example, to implement ADA policy in physical spaces, architects and contractors are required to submit specific blueprints, plans and budgets reflecting ADA compliance before work begins. However, as institutional Web space is not managed like architectural improvements, it is much more difficult to ensure compliance with an accessibility policy, even if one exists. This is in part due to: a. b. c.

The participatory nature of the Internet, as many people (staff and nonstaff) contribute to a college or university’s Web space A lack of Web site supervision and evaluation on many campuses A lack of formal introduction to institutional Web policies for designers

Additionally, in an era of increasing interest in online registration, course information and student services, it is imperative that administrators understand the potential barriers to electronic information access before noncompliant systems (commercial or homegrown) are installed. The knowledge of “best-practice” cases and an indepth analysis of the process of accessibility policy formation would inform disability advocates and educational administrators in the ways their organizations can best serve their constituents (current and future) and avoid costly litigation. One of the challenges yet to be met by many institutions of higher education is the issue of accessible electronic course materials. While many colleges and universities have struggled to create and implement policies that govern institutional Web space and to foster an accessible online environment with their public pages, individual courses are often exempt from these efforts. Part of the reasoning usually behind this is that individual students who need accommodations are routinely offered services through disability resource centers and the like. It is surmised that the students who need access to online content will obtain help from these service centers. While this may be true, colleges and universities are going to have to examine the expense and inconvenience caused by providing the same accommodations over and over again to different students. It may be more cost effective and considerate to make all online course content accessible from the start, rather than to make accommodations on a caseby-case basis. However, it will take considerable funding and effort to raise the issue of electronic accessibility among instructional staff and faculty and to provide adequate training and oversight. It is this balancing of resources and responsibility that has left this issue at a standstill. Further, as one of the promises of distance learning is that it has the potential to reach a new group of students who are not otherwise served by an on-campus educational environment, it is

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imperative that colleges and universities examine the process of accessibility policy formation in order to best utilize Web-based teaching methods. It would be a tragic oversight if distance learning programs were formed without attention paid to the needs of disabled students and an understanding of the institutional attitudes that may either promote or inhibit the accessibility of online courses. In addition, institutions of higher education may serve as examples for other organizations in regard to this issue. By building awareness of accessibility and providing a more equal and participatory Web-environment, colleges and universities can serve as social models for balancing the needs of free speech and open source with the protection of civil rights for minority populations. Further, it is imperative that this opportunity be recognized before institutions purchase and implement software and infrastructure systems that are not accessible, which may lead to costly compliance upgrades in the future or a solidification of electronic-access barriers.

concLusIon And recoMMendAtIons Academic cyberspace is a unique blend of traditional collegiate culture that supports norms of academic freedom and computing culture that adheres to its independence, even through the development of complex networks and interoperable systems. Neither culture is particularly predisposed to regulation or oversight, which must be acknowledged by those interested in creating guidelines or policies that concern use and management of the Internet in academia. Yet, public institutions of higher education are conferred with a particular social contract: open access to education. Due to this notion, Web accessibility guidelines may have less resistance than other regulatory measures that may affect academic cyberspace. Yet, it is important to note that the

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nature of the Web is egalitarian, and institutional strong-arming will not likely be met with favor where the Web is concerned. Several steps should be taken by institutions that are considering Web accessibility guidelines, or the implementation of such policies. First, an assessment of the institution’s cyberspace should be undertaken. An understanding of the management structure of campus computing networks, existing policies that affect Web sites and a feel for the culture and value-systems of the Web are necessary to successful planning. Second, alliances between campus units must be created. In particular, campus computing staff and disability services staff should create a working relationship. Other areas to include might be library staff and instructional support personnel. Without strong networks between these units, Web accessibility guidelines may be underdeveloped and misrepresented across campus. Third, the utilization of external resources is a very important factor to the success of Web accessibility implementation. Postsecondary educational institutions are unique, and a better understanding of best practices from other campus communities is essential to an honest appraisal of the workload and resources necessary to create a viable plan. In addition, federally funded groups such as WebAIM are excellent resources with tailor-made solutions for higher education. Finally, it is essential to create an atmosphere that rewards change. Through promotions such as accessibility icons and certificates, Webmasters are recognized for the efforts that they have taken to contribute to a culture of access. It is important to note that Web sites are often maintained by staff and students who have not been fully trained in Web development. Their efforts to learn how to code HTML for accessibility deserve praise, yet their work may not be noticed in their departments or academic units. A process by which the Web community at large can recognize the work of these accessibility advocates will help to alleviate some of the isolation that can be found in academic cyberspace. Also,

Overcoming Organizational Barriers to Web Accessibility in Higher Education

the professional-caliber computing personnel who take the time to learn about Web accessibility deserve kudos as well. Many computer experts in academe are overworked, trying to keep up with the demand of increased services, so strides made toward accessibility are worthy of reward. In summation, Web accessibility policies must be created and implemented with mutual respect in mind: respect for the time and effort it will take for staff members to adapt to the new guidelines as well as respect for the prospective and current students and staff members who will be aided by the changes.

endnotes 1

2

3

4

5

According to a 1997 U.S. Census Bureau report, 5.26 million Americans reported some type of disability, equaling 19.7% of the population. The full report can be read online at http://www.census.gov/hhes/www/ disable/sipp/disable97.html. Notable examples of Web accessibility policies can be found in the California Community College system, the University of Wisconsin at Madison, the SUNY system and Massachusetts Institute of Technology. For a discussion of Web accessibility policies, legislation and controversies, see the WAI’s page at http://www.w3.org/WAI/ Policy/. “How the Internet is Improving the Lives of Americans with Disabilities,” Harris Poll #30, June 7, 2000. http://www.harrisinteractive.com/harris_poll/index.asp?PID=93. Server statistics for the University of Arizona can be found at http://www.arizona. edu/usage/. The state of Arizona increased appropriations to the University of Arizona by 6% in 1998–1999, but only by 2.6% in 2000–2001. See the Chronicle of Higher Education’s

6

7

8

9

10

index of State Appropriations for Higher Education, 12/15/2000 and 11/27/1998. The Department of Education’s Web site for this grant can be found at http://www.ed.gov/ offices/OPE/disabilities/index.html. Information about the VALA project can be found at www.vala.arizona.edu. Information about WebAIM can be found on their Web site at www.Webaim.org. Bobby 3.2 can be found on the Center for Applied Special Technology (CAST)’s Web site at www.cast.org/bobby. Schmetzke’s analysis can been seen at http:// library.uwsp.edu/aschmetz/Accessible/UWCampuses/Survey2001/data.htm.

reFerences Anonymous. (2000). Web page accessibility on University of Wisconsin campuses: 2000 survey data. Retrieved March 6, 2002, from http://library. uwsp.edu/aschmetz/Accessible/UW-Campuses/ Survey2000/contents2000.htm Burgstahler, S. (2000). Access to Internet-based instruction for people with disabilities. In L.A. Petrides (Ed.), Case studies on information technology in higher education: Implications for policy and practice (pp. 76-88). Hershey, PA: Idea Group Publishing. Cunningham, C., & Coombs, N. (1997). Information access and adaptive technology. Phoenix, AZ: Oryx Press. Foster, A. L. (2001). Colleges focus on making Web sites work for people with disabilities. The Chronicle of Higher Education, January 26. Henderson, C. (1999). College Freshmen with Disabilities: A Biennial Statistical Profile. Washington, DC: American Council on Education. Retrieved March 6, 2002, from http://www.acenet. edu/bookstore/pdf/CollegeFresh.pdf

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Horn, L., & Berktold, J. (1999). Students with disabilities in postsecondary Eeducation: A profile of preparation, participation, and outcomes. Washington, DC: U.S. Department of Education, Office of Educational Research and Improvement, National Center for Education Statistics. Retrieved March 6, 2002, from http://www.nces. ed.gov/pubs99/1999187.pdf Lessig, L. (1999). Code and other laws of cyberspace. New York: Basic Books. Lewis, L., & Farris, E. (1999). An institutional perspective on students with disabilities in postsecondary education. Washington, DC: U.S. Department of Education, National Center for Educational Statistics, NCES 1999-046.

Libery (The National Council for Civil Liberties). (Ed.). (1999). Liberating cyberspace: Civil liberties, human rights, and the Internet. Sterling, VA: Pluto Press. Resnick, D. (1997). Politics on the Internet: The normalization of cyberspace. New Political Science, Fall, 47-67. Schmetzke, A. (1999). Web page accessibility on University of Wisconsin campuses: A comparative study. Retrieved March 6, 2002, from ttp://library. uwsp.edu/aschmetz/Accessible/UW-Campuses/ contents.htm Taylor, H. (2000). How the Internet is improving the lives of Americans with disabilities. Harris Poll #30. Retrieved March 6, 2002, from http:// www.harrisinteractive.com/harris_poll/index. asp?PID=93

This work was previously published in Design and Implementation of Web-Enabled Teaching Tools, edited by M. F. Hricko, pp. 190-207, copyright 2003 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.10

Creating and Using Multiple Media in an Online Course Maurice W. Wright Temple University, USA

AbstrAct

bAcKground

The adaptation of a traditional, face-to-face course to an online format presents both challenges and opportunities. A face-to-face fundamentals course treating the science of musical sound and the methods used to code and transform musical sound using digital computers was adapted for online delivery. The history of the course and the composition of its audience are discussed, as are the decisions to create movies, Web pages, electronic mail, and a paper textbook for the course. Practical choices for technology, which reflect the conflicting benefits of choosing simple versus more sophisticated technology, are outlined and the reactions of the students to these choices are discussed. An anecdotal comparison between an online and a face-to-face course section is offered, along with ideas for future development.

Computers in Musical Applications is a course that has been offered in the Esther Boyer College of Music for 16 years and serves as a prerequisite for three music technology courses. The course was designed to provide students who expressed an interest in electronic and computer music with a detailed knowledge of the principles of acoustics and computer engineering that define the processes of digital recording, editing and synthesis of sound, and, to a more limited extent, digital video. When the university faculty adopted a core curriculum in 1986 that required a two-course sequence in science and technology, Computers in Musical Applications was proposed to serve as a second-semester core science course. The course would follow an acoustics class that was offered by the Physics Department and required of all music students. Since 1986, it has been offered each year with section enrollments ranging from 10 to 60 students. Initially the course was taught in a traditional, face-to-face format that included a weekly, two-

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Creating and Using Multiple Media in an Online Course

hour lecture class and a one-hour laboratory section comprised of small groups of students taught by a graduate student. The textbook for the course (Dodge & Jerse, 1985) was the same one used in a subsequent software synthesis class. The transition in 1986 from a small, self-selected class of technology enthusiasts to a large group of students with varied interests was challenging and was made more so by external factors such as the absence of a large lecture room with desks, difficulty in recruiting lab instructors with the necessary background and teaching skills, students’ lapses in retained knowledge from the acoustics class, and complaints about the purchase of an expensive textbook of which only a few chapters were used. Another challenge was offered by the academic schedule of music students. Music ensembles such as orchestra carry only a one semester-hour credit but meet at least three hours per week with additional rehearsals and performances according to the college performance schedule. Faculty are expected to routinely excuse students from academic classes several times in a semester to participate in rehearsals and performances, and graduating seniors miss additional classes during the week of their senior recitals. As a result, class attendance is less than consistent. Also, the instructor is asked to provide considerable time outside of class teaching missed material. Finally, many music students are foreign students for whom English is a second language, and who struggle with comprehension in lecture classes. An opportunity arose to revise the course to address these challenges when Computers in Musical Applications was offered as an online course.

course desIgn Students in the online course used a textbook, a CD-ROM, course Web pages, and e-mail. The online course was designed for asynchronous delivery and could accommodate any student’s

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schedule; however, examinations had to be taken on campus unless special arrangements were made in advance of the examination date. Face-to-face group orientation sessions were added to the online class in later years to help students start the course, although all orientation materials were available online. The textbook’s 10 chapters correspond to 10 major lecture topics for the course and contain all the basic material from which examination questions are composed (see Appendix A). There is a midterm and a final examination with 50 to 60 multiple choice questions, most requiring calculation. Easy questions test one fact or formula in a form that is familiar to students from their class materials, but more difficult questions combine several facts and formulas in problems that also contain unfamiliar data. The CD-ROM contained 10 condensed lectures in the form of QuickTime movies, each about 10 minutes long. Also included was a freeware application and 33 sound examples used for lab experiments, which gave students ample opportunity to experiment with digital manipulation of sound. The creation of the CD-ROM and course Website will be discussed later in this chapter. The face-to-face laboratory sections were replaced by 10 laboratory experiments designed to use Dale Veeneman’s SoundHandle software.1 Students can use SoundHandle to view waveforms and edit short sounds, create sounds using various waveforms and noise, and compute and view the frequency spectrum of sounds using the Fast Fourier Transform 2 (Veeneman, 1995). The lab experiments involve the measurement and perception of sound, the confirmation of Nyquist’s limit,3 and the source of and quality of digital noise. Students e-mail their lab reports to the instructor for grading and comment. There are opportunities within these experiments for qualitative discussion via return e-mail, which also allow the instructor to develop some rapport with the students (see Appendix B). The course Website serves as the portal to the class, presenting the syllabus, the orientation

Creating and Using Multiple Media in an Online Course

material, the lab assignments, and the weekly schedule of requirements. The current URL is www.oll.temple.edu/MUS-ST-C315/cma. Each student must use the CD-ROM, the textbook, the Website, and e-mail to complete each week’s assignment. The course took a more intensive approach to mathematics than the prerequisite acoustics course because that course emphasized a qualitative approach to the subject. According to the published description (Temple University Undergraduate Bulletin, 2002), the prerequisite acoustics course includes: Elementary principles of wave motion and discussion and analysis of musical sounds from a large variety of sources including live voices, instruments, oscillators, synthesizers, and recording media of all sorts. Factors, which permit the performer and listener to understand and more fully control musical sounds. Demonstrations and video to relate the signals received by the ears to visual and technical analysis. For music students, but useful to anyone interested in communications. Open to all students. (p. 20)

Minimal Mathematics Many students who have completed the prerequisite acoustics course are not familiar with the simple mathematics that explain the frequencies of partials in a harmonic series—one of the most basic properties of musical sound (Pierce, 1992). All periodic sounds, which comprise the sounds of pitched musical instrument, contain harmonic overtones of varying intensity that occur above the fundamental pitch. Unique combinations of overtones contribute to the timbre, or tone quality, of a musical sound. The pattern of overtones is easily described with simple algebra. The most complicated mathematical concept in Computers in Musical Applications is the logarithm, used to calculate decibels. This subject is treated in

the text, the Web pages, and the labs. The binary number system is also discussed at length.

the vALue oF MuLtIPLe MedIA Before this course became part of the University’s core science curriculum, it served as a pre-requisite for music technology courses, and thus was elected by students who were, for the most part, interested in the science underlying the technological application. Those students were satisfied with fairly succinct “chalk-talk” lectures with recorded audio examples and the opportunity to ask many questions. However, students required to take the course as a science requirement were less interested and demonstrated varying degrees of motivation. Based on a review of course evaluations, I tried to create online course materials that would approach the subject matter from several perspectives at once. Richard P. Feynman (1999), Nobel Laureate and Physics Professor at the California Institute Of Technology, was asked about his teaching philosophy in a interview broadcast by the BBC in 1981: All those students are in the class: Now you ask me how should I best teach them? Should I teach them from the point of view of the history of science, from the applications? My theory is that the best way to teach is to have no philosophy, [it] is to be chaotic and [to] confuse it in the sense that you use every possible way of doing it. That’s the only way I can see to answer it, so as to catch this guy or that guy on different hooks as you go along, [so] that during the time when the fellow who’s interested in history’s being bored by the abstract mathematics, on the other hand the fellow who likes the abstractions is being bored another time by the history—if you can do it so you don’t bore them all, all the time, perhaps you’re better off. I really don’t know how to do it. (p. 20)

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Feynman’s refreshingly honest suggestion to try many ways to present ideas and information is a reasonable goal for an online course. Movies and Web pages are only some of the presentation methods that can be used. Within each method lies the possibility for multiple modes of presentation as well. A video can include animation, a talkinghead lecture, physical examples, and metaphor. There is also room for humor if it helps to deliver the message. John Allen Paulos (1988), in a popular book about mathematics, writes: Both mathematics and humor are combinatorial, taking apart and putting together ideas for the fun of it–juxtaposing, generalizing, iterating, reversing (AIXELSYD [“Dyslexia” spelled backwards]). What if I relax this condition and strengthen that one? What does this idea—say, the knotting of braids—have in common with that one in some other seemingly disparate area—say, the symmetries of some geometric figure? Of course, this aspect of mathematics isn’t very well know even to the numerate, since it’s necessary to have some mathematical ideas first before you can play around with them. As well, ingenuity, a feeling incongruity, and a sense of economical expression are crucial to both mathematics and humor... (p. 76). If mathematics education communicated this playful aspect of the subject, either formally at the elementary, secondary, or college level or informally via popular books, I don’t think innumeracy would be as widespread as it is. (p. 77) Paulos’ encouragement of humor again suggests the value of multiple meanings and surprise shifts in point of view—elements easily incorporated in movies or Web pages. Most students who sought help at office hours admitted to “math anxiety,” and seemed almost afraid of simple equations. Whenever possible, mathematical concepts were presented in a playful, cartoon-like style. For example, the second lecture-movie treats the use of binary numbers to express the quantity of

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variety, progressing from two-value decisions (e.g., yes/no, male/female, dead/alive) to four value decisions (e.g., North/East/South/West), and so on. To show how three binary digits completely capture an eight-valued decision, a “waiter” offers the viewer the following breakfast choices: 111 110 101 100 011 010 001 000

Eggs, Potatoes and Onions Eggs and Potatoes Eggs and Onions Just Eggs Potatoes and Onions Just Potatoes Just Onions Nothing at All

The waiter character is played by a 10-year-old boy wearing a white wig and glasses, intended to project a harmless, non-threatening persona. If the student’s memory is jogged the next time he or she orders breakfast, the metaphor will help the student recall the lecture topic and, possibly, better remember that numbers can represent codes as well as quantities. I created the 10 QuickTime movies for the CDROM using a VHS camcorder, a PowerMac 8500 computer, and Adobe’s Premiere and Photoshop software. Each of the 10 subject units for the course was described on the course Website, and included reading from the text, a lecture-movie, a series of Web pages, and a lab assignment. The introduction to the lecture-movie provides an excellent opportunity to employ metaphor, because the viewer will form an opinion that will color the visual experience that follows. The framing image for the movie portion of the lecture is a handsome, red-brick mansion with a long walkway, adapted from a photograph of the Governor’s Palace in Williamsburg, Virginia. This Virtual Lecture Hall image denotes stability, tradition, and the 18th century (an era familiar to music students). The soundtrack combines a recording of feet crunching on gravel, perhaps the student trudging to the front door, and soft, gentle

Creating and Using Multiple Media in an Online Course

music.4 The effect is intended to be soothing and elevating. This visual is used to introduce the first four lectures. The topic for the fifth lecture is the synthesis of musical sound, a technology that has changed the lives and livelihoods of musicians. Digital sampling technology continues to reduce the need for “commodity” musicians begun by the introduction of recording and radio broadcasting, while creating new opportunities for technologists and “star” performers. During the introduction to the fifth lecture, the Virtual Lecture Hall bursts into flames, accompanied by a synthesized recording of an excerpt from the beginning of the last movement of Beethoven’s Ninth Symphony. The sixth lecture examines different kinds of synthesis strategies (e.g., “additive” synthesis, in which overtones are combined to make a complex waveform, and “subtractive” synthesis, in which a complex source is filtered to remove overtones). The introduction to this lecture shows the burned shell of the mansion, with workers changing the shape of the exterior, and a dumpster in front to collect parts of the reduced structure. The transformation is a metaphor for subtractive synthesis, in which the mansion is “filtered” down to a different scale. The seventh lecture is an overview of filter theory, which is the general principal governing the creation and use of filters for subtractive synthesis and digital signal processing techniques like reverberation. A picture of the remodeled mansion, now a bank with a drive-through window, accompanied by the Destiny leitmotif from Wagner’s Ring, introduces the lecture. The somber tones are rendered by the sounds of air blown over the top of glass bottles, an example of filtering heard in the lecture. A brief trip by virtual auto brings the viewer to a squat, cinder block building with a flat roof where the Lecturer discusses digital filters against the geometric pattern of 1960s era wallpaper. Thus the comfort and security of the Virtual Lecture Hall is replaced by something decidedly artificial and possibly unstable, a visual metaphor that introduces the discussion of artifacts and instabilities in

digital filters. The introductions to the subsequent lectures are intended to be equally provocative, presenting the student with metaphors that color the discussion of the subjects at hand. Students learn to use different media by the course requiring them to confront a densely constructed movie, use a simple CD-ROM, connect to the Web, run a simple software application, and send reports by e-mail. Through these activities, students become aware of the interfaces to different applications and learn to devise strategies for shifting among applications to accomplish a task. Using multiple media in this way has a teaching value in and of itself, especially if the physical features of the various media are discussed as part of the course.

creAtIng vIdeo sequences The author of media materials must decide whether to purchase production services or to personally assume that responsibility. In an academic environment, the institution may provide production services, or a publisher might contract with an instructor for specific components of a media project. But the questions of control and decisionmaking authority over the production process must be grappled with as it would in any collaborative endeavor where budget issues are concerned. To maintain control of the process, the author can do most of the work, purchasing services only if necessary. Cameras and editing software are readily available. Apple Computer (2002) now offers a desktop computer with software for word processing, drawing, painting, spreadsheets, databases, video editing (with tutorial materials), and video input/output capacity, all for about $1,000. A digital video camera is also available for about $600. According to the most recent report from the Bureau of Labor Statistics (2002), $1,600 today is equivalent to $310 in 1968, which is approximately what a good electric typewriter would have cost. Clearly, video production equipment is affordable

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for most college professors and does not require a great amount of expertise. An instructor who can stand and lecture to a class can learn to lecture to a camera. You mount the camera on a tripod, focus on a stand-in, and then record some test shots. When lecturing from notes, you can use a medium close-up shot so that your note pad is visible. You need not mimic television announcers to create interesting and effective video. Indeed, there is something to be gained by not mimicking the rituals of broadcast television. Unless the image of the lecturer is especially compelling, other images should also be introduced during the editing process. These images can be scanned using a flatbed scanner and image processing software; however, the high resolution of such scans is often wasted when converted to a video image. If images are intended for use in video, they can be scanned easily and quickly using a video camera by aiming a light source at a stand on which the image is placed. You can then capture the video as a still image. Effective graphics can also be created with simple drawing or painting software and even animated images can be rendered in a sequence of still frames. Despite the “Fair Use” provisions in the Copyright Law, educators should consider creating their own graphic and sound materials and obtaining permission from copyright owners for other material. Many institutions offer digital images online. Temple University’s Digital Diamond Collection (2002) contains hundreds of photographs from the Philadelphia Bulletin newspaper and other sources, and the process for obtaining permission for their use is included with each image in the searchable collection. Editing images and sounds can be the most time-consuming part of the process because large amounts of information must be manipulated and organized. The following strategies help to make editing move more quickly:

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• • • • •

Become familiar with the editing software by completing the tutorials. Use a reduced frame size, e.g., 320 by 240 pixels, for the first project. Avoid complicated video effects by learning how to make effective cuts. Do not try to compete with the presentation style of commercial television. Make a series of short movies and combine them later.

A simple recording of a seated lecturer, enhanced with effects to illustrate the lecture topic, and combined with text and images, provides an opportunity for visual illustration not available in a face-to-face lecture. A shot-by-shot analysis of a movie segment discussing digital noise is included in Appendix C. Once the movie I created for the class was edited, it was compressed to fit the space available on the CD-ROM and to play back properly on moderately slow computers. One of the problems faced by the author of computer media is whether to assume that the user has a high-performance computer system of recent manufacture, or an older, more modest system. Unless the highest quality images are necessary, it seems more humane to consider the needs of the student with fewer resources. Although a rate of 30 frames per second will yield smooth motion on some systems, a slower computer might drop frames or freeze intermittently. Ironically, smoother motion might be achieved with a slower frame rate (Adobe, 1994, p. 221). The movies used in Computers in Musical Applications were stored on CD-ROM with a frame rate of 10 frames per second. Frame size and compression scheme also affect picture quality, data rate, and file size. The largest frame commonly used for multimedia measures 640 pixels wide by 480 pixels high, or 307,200 square pixels total (Apple Computer, 2001, p. 379). The standard Red-Green-Blue (RGB) color-coding uses one byte per color per

Creating and Using Multiple Media in an Online Course

pixel (Adobe, 2002, p. 78), so the total byte count for a single color frame is 307,200 times three, or 921,600 bytes. Multiplying this byte count by the frame rate yields the data rate. The video data rate for several standard frame rates (see Table 1) is about 24 megabytes per second (one megabyte = 1,048,576 bytes). The audio portion of the program will add up to 176,000 bytes per second depending on the number of channels and the audio quality. A moment’s reflection on the capacity of a typical CD-ROM reveals the scale of the data rate problem. A 650megabyte CD will hold only about 27 seconds of video with a data rate of 24 megabytes per second. Furthermore, few computer systems can sustain a transfer rate from CD-ROM greater than one megabyte per second (WhatIs.com, 1999). CDROM transfer speeds are rated as 1x, 2x, etc., where the “x” means 150 kilobytes per second (one kilobyte equals 1024 bytes). It is my experience that a peak data rate of 400 kilobytes per second is a reasonable upper limit for CD-ROM movies, so there will need to be a significant reduction in data from the 24 megabyte per second transfer rate mentioned previously.

There are a number of ways to reduce and compress video data, but each method has a cost. The frame size can be reduced if a smaller image or lower-resolution image is acceptable. An image 320 wide by 240 high pixels would use 25% of the data of a 640 pixel by 480-pixel image. A motion sequence rendered at 10 frames per second would require 33% as much information as the same sequence at 30 frames per second. A black and white movie requires only 33% of the data of a color movie. If the image size, the frame rate, and the color information were reduced, the savings would compound (see Table 2). Even this 97% decrease does not bring the data rate below 400 kilobytes per second, so other methods of reducing or compressing the video data must be used. Video-editing software provides schemes for coding video data that the display software can decode during playback. The methods, called CODECs (for COder/DECoder), can achieve significant compression. The amount of compression depends on the nature of the scheme employed and how well it works with the particular data provided. Some CODECs preserve image resolution at the expense of smooth motion;

Table 1. Data rates for uncompressed video Standard Frames/Second Bytes/Frame Bytes/Second ________________________________________________________________________ NTSC Video 29.97 921,600 27,620,350 PAL Video 25 921,600 23,040,000 Motion Picture 24 921,600 22,118,400 ________________________________________________________________________

Table 2. Effect of image quality on data rate Frame Size Pixels/Frame Bytes/Pixel Bytes/FrameFrames/Second Bytes/Frame ________________________________________________________________________ 640 by 480 307,200 3 (color) 921,600 29.97 27,620,350 320 by 240 76,800 3 (color) 230,400 29.97 6,905,088 320 by 240 76,800 3 (color) 230,400 10 2,304,000 320 by 240 76,800 1 (grayscale) 76,800 10 768,000 ________________________________________________________________________

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others sacrifice resolution but preserve motion. An engineer who wishes to show the operation of a gear mechanism might want to preserve resolution and sacrifice color. An art historian may elect to preserve resolution and color but use a very low frame rate. A surgeon illustrating a technique for suturing may retain resolution and color and decide to play the images in slow motion. The choice of CODEC will vary depending on the program material; experimentation will suggest the best choice for a given set of constraints.

creAtIng web PAges Programs to design Web pages (with tutorials) are available for free (Netscape Composer). A Web page author will need to remember that the transfer of information over normal telephone lines is limited to 56,000 bits, not bytes, per second, and that most transfers occur at lower rates. To illustrate this phenomenon, I connected to five different Web servers using a 56 kBaud modem, a 733 mHz G4 processor, and an up-todate Web browser (Microsoft Internet Explorer, Version 5.1), and downloaded a Web page from each, then loaded each page a second time. The results are shown in Table 3. Why did the initial loads take so long? Why were the reloads faster? Why were some faster than others? Each site has a number of small images interspersed among areas of text. During the initial load, the text is loaded first, then the

background, and then the images. Each part of the download begins with the modem requesting a data transfer. Then there is a short delay, followed by the download of the file. Once the images are stored in the local computer, the page can be reloaded quickly from the local files. Some sites sell commercial space on their Web pages and change the panels frequently, requiring a new set of downloads each time the page is requested. A popular site may have many users connected at once, all trying to get to the same data. When this happens, the delay after the image is requested will lengthen, and the rate at which the data is served will decrease. Transfer rates as low as 100 bytes per second are not uncommon, regardless of the speed of the Internet connection itself. Web pages can be made to load quickly by avoiding graphic clutter and complex backgrounds. Text is quick to load, but a picture of text is not. A 200 x 290 pixel uncompressed color picture contains 174,000 bytes of data. By contrast, the text portion of this chapter thus far contains only about 25,000 bytes of data. Using the file transfer protocol, I was able to receive 174,080 bytes in 21.4 seconds, a transfer rate of 8,135 bytes per second. Even at this high rate (for telephone line transfers), students will grow impatient if the images take too long to load. Because images are cached in the local computer, pages that reuse images will load faster than pages using unique images, so the designer is advised to create a library of reusable images. Although images can be used to guide the reader

Table 3. Download and reload times for five Web pages URL First Load Time Second Load Time ________________________________________________________________________ www.temple.edu/music 15 seconds 2 seconds www.princeton.edu 30 seconds 5 seconds www.kodak.com 30 seconds 7 seconds www.microsoft.com 22 seconds 12 seconds www.mapquest.com 40 seconds 30 seconds ________________________________________________________________________

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through a complicated topic, the value of each image is inversely proportional to the total number of images. Indeed a visually “busy” page might discourage deep thinking by encouraging a superficial race through the links, clicking with abandon to see what comes next. “White space” is soothing and conducive to thought. Less is more. Pages that are image-dependent need to be tested thoroughly to be sure that the images will appear the same on different platforms and browsers. The simpler the page design and the less the page relies on specific browser features, the more portable the result will be. The World Wide Web Consortium (W3C) will check html code for compliance with its standards and will validate properly formed pages. To use this service, go to http://validator.w3.org.

outcoMes The online version of Computers in Musical Applications was written in the Fall of 1996 and first used for classes during the Spring semester of 1997. It has been used each semester since then and sometimes offered in the same semester as the face-to-face course. Although a detailed, systematic comparison of grades for the traditional and online sections has not been undertaken, the grade distribution of the various sections seems stable and consistent. The course was given in both online (n = 17) and traditional (n = 21) formats in the Spring 2000 semester. The grade distributions (see Figure 1) were similar. The scores on the midterm and final examinations are also comparable (see Table 4). Students

Figure 1. Comparison of grade distributions in an online section and a traditional section

Table 4. Examination scores in an online and a traditional section Test Section N Mean Standard Deviation __________________________________________________________________ __________________________________________________________________ Midterm Midterm Midterm Midterm Final Final Final

Final

Online Online 1 Traditional Traditional Online Online 1 Traditional

17 7 21 2 17 1 21 7 Traditional 2 1

6060 69 69 58 5958

59

21.7 21.7 16.6 16.6 18.0 18.0 22.6

22.6

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Table 5. Examination scores in an online section and a traditional section with students failing to submit lab Work excluded Test Section N Mean Standard Deviation __________________________________________________________________ Midterm Online 15 63 21.5 Midterm Traditional 20 70 16.7 Final Online 15 62 13.6 Final Traditional 20 61 22.2 _________________________________________________________________

who did not complete all of the laboratory assignments also performed poorly on the examinations. Two students in the online section turned in only two lab assignments, and one student in the traditional section turned in no lab assignment at all. These students’ grades account for the “F” grades in each section. When their scores are removed from the examination grades, the scores of the two sections remain similar (see Table 5). The two sections were not completely separated because students who missed class in the face-to-face sections were encouraged to use the online materials. Conversely, students who were having difficulty with the online material were encouraged to attend the face-to-face lectures. A comprehensive, quantitative assessment of student evaluations of Computers in Musical Applications has yet to be completed, but a preliminary calculation shows that the instructor rating has improved from 4.0 (out of 5.0) in 1993 to 4.2 in 2000, suggesting that the effort spent in preparing the online materials may have had a positive effect on the teaching of the course in general.

thoughts For the Future Preparation of multiple media for an online course was a labor-intensive process that was undertaken in the spirit of experimentation. The principal benefits of this process were the increased aware1932

ness of one’s lecture style, the possibility of timeshifting class work for students, and a portfolio of movies, Web pages, and lab experiments that could be recycled for future online and face-toface classes. The biggest problem for the online students was the increase in opportunities for procrastination. The result was late submission of lab reports followed by poor examination results. To lessen students’ propensity for procrastination, strict deadlines for submission of reports need to be given and enforced. Because I did not capture information related to students’ access of Web site materials, there was no way to know whether a student had trouble understanding the concepts or was simply not accessing the course materials. Information that could prove useful could be gained by including short quiz questions throughout the course Web pages to test students’ knowledge of concepts and by tracking their use of and access to online course materials. The online lab assignments are more time consuming to grade than face-to-face lab assignments because they are text-based and require the instructor to make corrections in spelling and grammar. Text-based feedback (via e-mail) is also required. Because of these requirements, students may not receive grades and comments on their lab reports for several days. In the interim, serious misunderstandings about important concepts might go unchallenged. An automatic lab-grading program used in conjunction with the instructor’s comments would be helpful for

Creating and Using Multiple Media in an Online Course

students. The most often heard complaint about the course is that the material “will not be useful in real life” or that the student “expected it to be more hands on.” Perhaps a proficiency requirement for one or two software applications could be included in the course syllabus, but the rigor of a course where the instructor would function as a human manual reader for commercial software is doubtful. Whether the concepts introduced in Computers in Musical Applications are introduced with the assistance of innovative multimedia technology or whether they are presented in a more traditional format, the value of the more abstract and quantitative science and engineering concepts that underlie commercial software programs is great. Long after the current generation of computer equipment is obsolete, concepts such as Nyquist’s limit will remain valid, and the decibel will continue to be the logarithm of the ratio of two quantities. Students who have acquired a basic, but not oversimplified, understanding of the technology used in musical pursuits will be better able to understand how it affects them and their careers.

endnotes 1

2

SoundHandle is a shareware program whose author generously granted permission to duplicate for the class. SoundHandle will work with older or newer Macintosh computers and supports several file formats. Fourier’s transform can be used to analyze the frequency content of periodic waveforms. The calculation converts a signal representation in time space to an equivalent expression in frequency space, and viceversa. By altering the parameters of the transformation, a sound can be shortened or lengthened in time without altering its pitch, or its pitch can be altered independent

3

4

of duration. The Fast Fourier Transform, an efficient algorithm for computing the discrete Fourier Transform, is a ubiquitous digital signal-processing tool. Nyquist’s limit is a physical law that determines the range of frequencies that can be represented in a digital signal, and is one of the two most important (the other is quantization noise) determinants of fidelity for digital recording and synthesis of sound. Filtering a recording of applause created the soothing music heard during the opening sequence. The process is explained in the class unit on filtering.

reFerences Adobe Software. (1994). Premiere: User guide (Version 4.0). Adobe Software. (2002). Photoshop: User guide (Version 7.0). Apple Computer. (2001). Final cut pro: Users manual (Version 3). Apple Computer. (2002). The E-Mac. Retrieved July 6, 2002 from http://www.apple.com/emac Bureau of Labor Statistics. (2002). Consumer Price Index, May 2002. Retrieved July 6, 2002 from ftp://ftp.bls.gov/pub/special.requests/cpi/ cpiai.txt Dodge, C. & Jerse, T. A. (1985). Computer music: Synthesis, composition, and performance. New York: Schirmer Books. Feynman, R.P. (1999). The pleasure of finding things out. Cambridge, MA: Perseus Books. Paulos, J. A. (1988). Innumeracy: Mathematical illiteracy and is consequences. New York: Hill and Wang. Pierce, J. R. (1992). The science of musical sound. New York: Freeman Books.

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Temple University. (2002). Digital diamond collection. Retrieved July 6, 2002, from http://diamond. temple.edu:81/search Temple University. (2002). Undergraduate bulletin. Retrieved July 6, 2002 from http://www. temple.edu/bulletin/ugradbulletin/ucd/ucd_ physics.html Veeneman, D. (1995). SoundHandle (Version 1.0.3). Retrieved July 8, 2002 from http://wuarchive.wustl.edu/systems/mac/amug/files/music

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WhatIs.com. (1999). Optical media: CD, CDROM, DVD and their variations. Retrieved July 6, 2002 from http://www.nightflightstudios. com/Tech_Write/Opti_Media.htm Wright, M. W. (1995). Computers in musical applications. Unpublished manuscript.

Creating and Using Multiple Media in an Online Course

APPendIx A In the 1995 version of the text (Wright, 1995) one reads: He [Harry Nyquist] tells us that a sampling rate of S is needed to capture frequencies as high as S/2. Stated another way, if samples are taken every T seconds, then events with periods of 2T seconds or greater will be correctly represented. The notion of the Nyquist limit is easier to understand when studying digital representation of audio signals. If we know that the frequencies in an audio signal fall between 20 Hz and 10,000 Hz then Nyquist’s limit says that we must sample at a rate of at least 20,000 samples per second to capture the highest frequencies. Conversely, a system sampling at 20,000 Hz can correctly represent frequencies up to 10,000 Hz. (p. 21) One easy question on the 1995 midterm examination, drawn from that section of the text, reads: If the sampling rate is 50000 Hz, what is the Nyquist frequency? A. 100 kHz B. 50 kHz C. 25 kHz D. about 20 kHz At least 15 other examination questions depend on an understanding of Nyquist’s limit, and are drawn from examples in the textbook.

APPendIx b Here is a typical lab assignment (images omitted). Underlined text links to help pages and text in italics are questions that must be answered in the lab report:

Laboratory Assignment #5 quantizing noise Discussion As the number of amplitude levels used to describe a function decreases, the quantizing error increases. Quantization noise is more noticeable than analog hiss because it is not steady state: it tracks the amplitude of the signal and contains frequency components that vary according to the frequency components of the signal. Open SoundHandle (remember how to use it?) and open Lab05Sound01. Listen to the sound and examine a small part of the waveform. Then Edit-Select All, followed by Modify-Scale...as before, the “Left Scale” refers to the scaling value at the beginning of the window, the “Right Scale” to the scal-

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ing value at the beginning of the window, the “Right Scale” to the value at the end. Rescale the whole window by 10%. This reduces the level by 20 decibels. Listen to the file. Did the noise level increase? Now scale the reduced signal by 1000% (+20 db). Did the noise level increase? Examine the waveform. How does it differ from the original? Perform the same experiment on the file Lab05Sound02, but scale it by 5% and 2000%, respectively. Describe the noise that results from the rescaling. Why does it have this quality (hint: examine the “before” and “after” waveforms carefully). Mail in your notes (remember how?). The student has responded by transcribing the questions from the lab. They are preceded by a hyphen, and the student’s answers follow immediately after: Are there increases in noise? Yes, I heard the noise increase and volume decrease at the same time. When reduced signal by 1000%, did noise increase? Not necessarily. The whole thing got louder but the ratio of noise and sound is the same. How does the waveform differ from original? The waveform is less precise and it is rougher. Describe the sound of lab05sound02 after reduced. They no longer have a smooth tone but have a tone with lots of noise. Why do they have this quality? Because as they got re-scaled (especially by 5%), they lost preciseness in amplitude. Instead of having many different levels of amplitudes, they only have three levels.

• • • • •

The student received full credit for this lab report.

APPendIx c Here is an example from a movie used in Computers in Musical Applications, a transcription of a segment about sampling theory. This is a relatively complicated section, but the zoom effects and superimposition of text is done efficiently by the computer editing software: 5:14 Medium shot of seated lecturer, reading from notes: “One can think of the sample rate as the time resolution of the sample process, and the error in measurement as the amplitude resolution.” 5:22 Medium shot, continued. Begin posterize effect, reducing the image to only a few brightness levels. Reading continues: “As an image is represented by fewer levels of resolution, artificial boundaries appear.” 5:30 Freeze frame on posterized image. Voice over: “Something similar happens with sound.” 5:33 Dissolve to graphic of high-resolution sine wave. Voice over: “Consider a sine wave captured at two different resolutions.” 5:36 Graphic of high-resolution sine wave. Voice over: “In the first case the wave is represented with many levels.” 5:39 Dissolve to graphic of low-resolution sine wave. Voice over: “But in the second, only 16 levels. The shaded areas in the second diagram represent the errors of measurement.”

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Creating and Using Multiple Media in an Online Course

5:45 Zoom out and pan right. Voice over: “The ratio of the maximum signal that can be represented...” 5:50 Zoom continues. Superimpose text: “Maximum Signal/Error Noise.” Voice over: “...to the error noise in a digital representation is called...” 5:55 Zoom continues. Additional superimposed text: “Signal-to-Noise Ratio.” Voice over: “...the signalto-noise ratio and is directly related to the size of the sample word in bits.” 6:00 Extreme close-up of lecturer, looking directly at camera. Voice: “Each additional bit of resolution in the sample word doubles the signal-to-noise ratio...” 6:06 Extreme close-up, continued. Superimpose text: about six DB per bit. Voice: “...increasing it by about six decibels.” 6:08 Medium shot of lecturer in chair. Reading: “This error signal could be annoying because it is not a steady hiss that could be easily ignored but instead a signal of varying intensity and possessing frequency components that change according to the frequencies present in the input signal. To maximize fidelity in a sampled system, high sample rates and accurate measures can be used. But if high sample rates and very accurate measurements are used, the amount of data that has to be stored and transmitted becomes significant. 6:40 Extreme close-up of lecturer, looking directly at camera. Voice: “Beyond some point we cannot appreciate improvements in frequency and amplitude range and the digital signal...” 6:47 Jump cut to same close-up to remove pause. Voice: “...although discrete in time and amplitude.” 6:51 Iris wipe to outdoor scene with trees waving gently in the breeze. Voice over “...seems perfectly natural.” 6:53 Outdoor scene. Sound of air, birds, etc. 6:58 Dissolve to graphic of a house. Text: “Copyright © 1997 by Maurice Wright.” 7:02 Same graphic. Text dissolves to: “Produzione Propria.” 7:03 End of movie. Freeze on graphic and house. This one-minute and 49-second segment uses a single long take of the lecturer reading from notes and looking up to the camera from time to time. The two close-ups were added later to stress important facts. The two sine wave graphics were created in SoundHandle, the same software the students use for lab assignments, and were pasted into a painting program so they could be colored and perfectly aligned. The dissolve from the high-resolution image (see Figure 1) to the low-resolution image (see Figure 2) is intended to help the viewer recognize the appearance of an under-digitized waveform, whose distorted shape will later be the subject of a lab experiment. The outdoor scene was a wide-angle view of the author’s backyard, the choice of grass and trees emphasizing the phrase “perfectly natural” with a visual pun. The text superimposed over the final image, “Produzione Propria,” means “homemade.”

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Creating and Using Multiple Media in an Online Course

Figure 1. Sine Wave Quantized to 256 Levels

Figure 2. Sine Wave Quantized to 16 Levels

This work was previously published in The Distance Education Evolution: Issues and Case Studies, edited by D. Monolescu, C. Schifter, & L. Greenwood, pp. 192-213, copyright 2004 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.11

Educational Theory into Practice Software (ETIPS) Sara Dexter University of Virginia, USA

AbstrAct

IntroductIon

The ETIPS software is a Web-based learning environment that delivers cases that allow educators to practice instructional decision making. Here I recount its development but mainly emphasize the two key concepts that were central to our design process. The first was the Conceptual Assessment Framework, an evidentiary reasoning and design perspective that helped us to focus on which key attributes to build into the software and cases. The second concept is described as extreme programming, which is an iterative approach to software programming based upon user stories and rapid prototyping. The story of developing the ETIPS cases illustrates the need to know very clearly what the point is of the educational experience you are creating and to design software where form follows function.

In this chapter, I recount the important aspects of the creation of the ETIPS software and its cases but mainly emphasize the two key concepts that were central to our design process. The first was the Conceptual Assessment Framework, developed by Mislevy, Steinberg, Almond, Haertel, and Penuel (2001); this framework helped us to focus on which key attributes to build into the software and cases. The second concept is described as extreme programming (Beck & Fowler, 2000), which is an iterative approach to software programming based upon user stories and rapid prototyping. The story of developing the ETIPS cases illustrates the need to know very clearly what the point is of the educational experience you are creating and to design software where form follows function. The first generation of ETIPS cases was created with existing case-authoring software; halfway through this four-year project our team realized that this software constrained the sort of learning experience we wanted the

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Educational Theory into Practice Software (ETIPS)

cases to provide. During the project’s third year we began to create from scratch software for a second generation of cases and an interface that brought to fruition our case-based pedagogical approach. We used the Conceptual Assessment Framework (Mislevy et al., 2001) to guide the development and refinement of each user story for the software; this helped us to connect form to function in the second generation of software and to recognize how our case-based pedagogy could be used with other topic areas as well. Thus, a side benefit of using these conceptual approaches was that we increased our product’s sustainability through broader user bases, potential co-authoring partnerships, and licensing.

portunities to see how these principles can guide instructional decision making about technology integration and implementation in a variety of school contexts. The six principles summarize what research suggests are the conditions that should be present in order for educational technology integration and implementation to be effective (Dexter, 2002). The first three educational technology principles focus on integration, meaning teachers’ instructional decision-making process when considering the use of educational technology resources in their classrooms. Discussion of these principles develops the premise that a teacher must act as an instructional designer and plan for the use of the technology to support student learning.

educAtIonAL PurPose oF the cAses

•

The purpose of the ETIPS project was to create teacher education cases that were learning exercises about educational technology integration and implementation. The primary audience for our cases was pre-service teacher education classes on either educational technology or pedagogical methods. Key premises upon which we based the software for our second generation of cases were that teaching is decision making—and decision making is a process that can be taught and requires practice in order to learn—and that instructional decisions are guided by schemas, or mental models. The cases allowed students studying to be teachers to practice making instructional decisions about educational technology use in classrooms and schools using the Educational Technology Integration and Implementation Principles as a schema, or the basis of a schema, for those decisions. By providing instructors nine virtual yet realistic schools among which to choose to set these decision-making exercises in it allowed them to give their students multiple practice op-

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• •

Principle 1: Learning outcomes drive the selection of technology. Principle 2: Technology use provides added value to teaching and learning. Principle 3: Technology assists in the assessment of the learning outcomes.

The last three educational technology principles focus on the implementation of technology at the school level—that is, how a school setting can create a supportive context that provides teachers with the necessary access to technology, technical and instructional support, and a positive climate for professional collaboration about educational technology tools. •

•

•

Principle 4: Ready access to supported, managed hardware/software resources is provided. Principle 5: Professional development is targeted at successful technology integration. Principle 6: Professional community enhances technology integration and implementation.

Educational Theory into Practice Software (ETIPS)

unIque FeAtures oF the etIPs cAse Method ETIPS stands for Educational Theory into Practice Software. It is a Web-based learning environment in which students complete cases that are set in a K-12 school and focus on an educational theory. Unlike text-based cases, which are read in a linear fashion and emphasize the multiplicity of perspectives inherent in an event that is often told in chronological fashion, cases in ETIPS present learners with a scenario in which they need to make an instructional decision, and require them to select which information they think they will need to make that decision. The case is an opportunity to practice reasoning with a guiding theory that relates to the case topic and to develop an understanding of how the different school contexts in which the cases are set might influence how that theory is applied in practice. This case approach emphasizes learners’ metacognition—their thinking about their thinking—through a software feature called a PlanMap. The PlanMap asks students to check off what information they think they will need to make the decision posed in the scenario (see Figure 1); if they return to their PlanMap during the case,

they will see that these choices are noted with a checkmark (see Figure 2). As students look at information in the case—and their choices are not limited to only what they checked while planning their search—the software records what they access and uses a different icon to record it on their PlanMap; in addition, experts’ recommendations of which key items should be considered are indicated with yellow highlighting. Thus, the PlanMap provides feedback to the learners on their planned and actual progress as well as an in-progress check of their approach as compared to experts’. Another formative assessment tool in ETIPS is automated essay scoring, which students can use to get feedback on their decision; this feedback is in the form of a predicted score of their short answer responses against a rubric before they submit it to their instructor for a final grade (see Figure 3). The automated essay scoring engine software compares the student’s response to other essays, which were scored by humans against the same rubric, predicts which score a student is most likely to receive, and presents it and the scoring criteria to them. In addition, if students have not yet been to the case information items

Figure 1. The PlanMap page view initially explains to students the purpose of the PlanMap, and asks them to click in the box next to each category of case information they think will be necessary to access in order to complete the case PlanMap Directions

Categories of the available menu items in the school’s Web site

Menu items you will be able to select to view in the school’s Web site

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Educational Theory into Practice Software (ETIPS)

Figure 2. This close up of a PlanMap from a case in progress shows how checkmarks indicate items the user planned to visit; green arrows indicate what case information the user has viewed so far, and yellow highlighting shows which pieces of information experts deem as key for making a decision such as the case requires

Yellow highlighted text shows information experts consider as key when making such a decision.

A checkmark indicates that the user planned to go to that item. A green arrow indicates that have been to that item during their search through case information.

Figure 3. On the submit answer page, students can chose to save their work as a draft, use the automated essay scoring feature, or submit their response to their instructor as a final answer

Enter your responses in the text boxes

Chose button that matches your desired option: • receive automated feedback, save your draft, •submit final answer

that experts consider to be key, it suggests they review that information.

etIPs ProJect teAM MeMbers The ETIPS project was funded by a grant from the US Department of Education through its Preparing Tomorrow’s Teachers to Use Technology (PT3) initiative. A majority of the grants

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were made to colleges of education; consortiums were encouraged, and awardees were required to include a project evaluator to collect data for performance feedback. The initial ETIPS team represented a strategic alliance among the project lead, which was a college of education at a major research university, a software development lab based at a similar type of institution, and a nonprofit organization with extensive experience developing software and delivering professional

Educational Theory into Practice Software (ETIPS)

Figure 4. The automated essay scoring engine shows the student their predicted score for that answer, the rubric criteria, and suggests any of the case’s information items they should also take into consideration

development. Toward the end of the second year of the project, when the project director decided to create from scratch the software that was the basis for the second generation of cases, the software development lab agreed to bow out of the partnership. At the lead university the team included the half-time project director, who had educational technology and teacher education expertise, a full-time project coordinator and two half-time graduate assistants who wrote case content and supported our test-bed of faculty members and their students, and a half-time project evaluator. At the non-profit organization there were two part-time collaborators who brought extensive assessment experience to the project as well as a software programming company with whom they had successfully worked and that we hired on an hourly basis.

ProJect chALLenges The major challenge that the project faced was articulating clearly the pedagogical purpose of

the case-based learning experience we wanted to provide to learners. Because at the outset of the project we began to create cases using the software developed previously by the university-based software development lab in our consortium we initially assumed the learning experience functions inherent in that software. While aspects of the resulting learning experience worked well for this audience and these topics, other aspects were not well suited to practicing instructional decision making. The first generation of cases was based upon the case approach pioneered by the IMMEX Software Development Lab at UCLA (Stevens, 1991). The IMMEX approach posed a problem to the learner and presented him or her with a menu-driven approach to selecting information necessary in order to solve it. The problem had a right answer, which—after having looked through sufficient case information—the user would select from a multiple-choice format. IMMEX software allowed case designers to elect to limit how much information the users could select through a points system. This rewarded learners who understood the correct problem solving approach and could

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Educational Theory into Practice Software (ETIPS)

recognize what information to seek out and how to interpret it because they could use the least number of points to determine the correct answer choice. The software tracked their information choices and graphically portrayed the sequence of their choices and the time spent at each using IMMEX’s proprietary SearchPath Map. The SearchPath Map was designed to show learners’ strategic responses to solving the problem. Each labeled icon on a SearchPath Map represents one menu item; the lines connecting the icons illustrate the path a student took in trying to solve the challenge presented in the case. Lines lead from the upper left-hand corner of an icon to the middle of the icon of the next menu item that was accessed. In this way, the SearchPath Map also illustrates the order in which students visited menu items. The map on the left represents that the student explored many menu items and thus made a rather complete search of the problem space. The performance of the student at right shows only two general areas of the problem space were explored, indicating they do not have a firm grasp of the concepts underlying the problem that was presented The IMMEX developers applied neural network analysis to determine the most common problem-solving approaches used by students who selected correct and incorrect answers, and to infer the likely student misconceptions that would lead to their taking such paths (Stevens, Johnson, & Soller, 2005; Stevens, Wand, & Lopo, 1996). At the outset of the ETIPS project it appeared that the major change to IMMEX that would be required to create cases about technology integration and implementation for pre-service teachers would be to allow for short answer responses. Adding a text box for responses was easy, but soon our test-bed faculty members wanted online modules for scoring essays, recording the scores, and then reporting them to students. We also saw that the instructional decision making exercise at

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the core of the ETIPS cases did not have a right or wrong answer and that scoring was a key point of the analysis of IMMEX cases. Further, students’ searches through case information did not result in predictable, categorizable sequences that the SearchPath maps could help illustrate. Consequently, our test-bed instructors reported that they often did not use the maps with students, which reduced the case experience’s potential for helping students become aware of their schema for their instructional decision making about technology integration. User performances and faculty feedback made clear to the project leadership team which aspects of the emerging vision of the ETIPS case-based pedagogy were not compatible with the IMMEX software’s features, and so we redirected a significant portion of the project’s budget away from this partner and to the programming company associated with the non-profit organization. This mid-course redesign was thus a challenge to the project’s budget, timeline, and consortium partner relationships. In retrospect, the initial design of the ETIPS cases in the IMMEX software served as a fast way to create a prototype and proof of concept for an online case-based pedagogy that was focused on student reasoning and decision making. The downside to this rapid start-up was that by using an existing software to author the cases it let us skip over what we now would argue is an essential step of creating educational games or simulations: articulating what you want to learn about the student’s knowledge and skills, and determining what tasks in the game or simulation will elicit that information. The data we collected through the evaluation component of the project reinforced the project director’s impressions that there were discontinuities between our users’ intended and actual experiences with the cases. The evaluation process enabled us to attend in a rigorous way to our testbed faculty members’ experiences with the cases

Educational Theory into Practice Software (ETIPS)

as an instructional resource and whether or not their students learned what we wanted them to learn about the case’s use. At the time project leaders decided to create our own ETIPS software some project leadership team members had been reading about assessment design, namely the Conceptual Assessment Framework developed by Robert Mislevy and his colleagues. Applying this framework forced us to articulate what we wanted the cases to help the user learn, and what task we would create in order to elicit that knowledge and skills, and then how to interpret and report their performance data. Through this process we determined how our software could be thought of as a general casebased pedagogy where the virtual schools could serve as the settings for cases on a variety of topics. We then began to think of ETIPS as standing for Educational Theory into Practice Software and that the Educational Technology Integration and Implementation Principles, for which the acronym was originally coined, would be just one topic about which we would offer cases. We enlisted two other organizations, chosen because of their large member bases and project leaders’ connections to them, as co-authors of cases about urban teaching and digital equity. At the outset of designing the software that would anchor the second generation of cases, the software programming company the project leaders hired (Green River; see http://greenriver.org), asked us to read Extreme Programming (Beck & Fowler, 2000) and to take that approach to our development work together. From the project leadership team’s perspective as a client, this is a user-centered design process that is articulated through descriptions of desired functionalities called user stories that are then checked out through usability testing and revised accordingly. Thus it was congruent with our on-going evaluation process. Table 1 recounts the timeline of the key steps during the development of the ETIPS software that anchored the second generation of the cases.

The overall budget allocated for the software development, as well as the domain name and hosting costs, over this two-year process was approximately $450,000. The personnel costs for the project director and coordinator and graduate students at the lead institution and the team members at the non-profit organization were approximately $640,000. Additional costs were incurred for travel to project meetings and for dissemination and co-authoring work that was undertaken. All the personnel costs given are for the entire life of the grant; during the first two years this went mostly for case topic conceptualization and case authoring work and in the latter two years it was for test-bed member implementation support, coauthoring, and dissemination efforts. The portion of the budget allocated for the evaluation work was approximately $210,000. In addition, the direct cost for the training and travel to project meetings for the test-bed faculty members’ was approximately $80,000.

Lessons to PAss ALong to others Games and simulations produced for educational purposes in effect serve as a sort of formative, and perhaps summative, assessment. That is, they allow the user to practice doing something that is based upon some key premises that guide the operational rules of the game or simulation. It is likely that through his or her performance the software indicates, among other things, how well the user understands those key premises. From the outset, the ETIPS project leaders knew we wanted the cases to be an opportunity to practice instructional decision making while keeping an educational technology integration and implementation principle in mind. But when designing the specifics of the software—especially what feedback we could give to the learner during the case—Mislevy et al.’s (2001) Conceptual Assessment Framework helped us to work more

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Educational Theory into Practice Software (ETIPS)

Table 1. Timeline for key development steps of ETIPS Timeline

Key steps

2003

Project Year Two

April

Software development planning meeting with Green River

May

Consultations with Mislevy on Conceptual Assessment Framework Test-bed faculty meeting at end of Year 1 of generation 1 cases’ use

June

Programming commences

July

Review of key elements in ETIPS engine with project leadership team

August

Alpha testing with students and faculty, usability expert’s review

September

Programming meeting and beta testing with one test-bed faculty member’s students

October

Planning for more responsive feedback to students on their case performance User interface planning for incorporating cases on multiple topics Co-authoring of cases on new topics begins with selected organizations Graphic re-design of interfaces for public part of site, post log-in, and cases

November

Programmer’s meeting to develop PlanMap feature Systematic data collection on students’ reaction to automated essay scoring

December

Begin discussion with publisher about bundling cases with book

2004

Project Year Three

January

New Web site interfaces deployed PlanMap deployed

March

Usability testing of new interfaces with faculty and students

May

Section 508 compliance review

July

Revise navigation scheme per users’ and 508 report input

September

Implement revisions Design better feedback on answer to students per results from student data

October

Begin controlled experiments with students to determine impact of a student’s use of the automated essay scorer on his or her essay’s quality

2005

Project Year Four

February

Begin controlled experiments with students to determine impact of a student’s use of the PlanMap on his or her essay’s quality

June

Improve performance of automated essay scorer

efficiently, as well as with confidence since this framework draws upon contemporary learning and assessment theory. The National Academy of Sciences report How People Learn: Brain, Mind, Experience and

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School, (Bransford, 1999) suggested that effective learning environments, among other things, are assessment-centered in the sense of providing multiple opportunities to make students’ thinking visible so they can receive feedback and be

Educational Theory into Practice Software (ETIPS)

given chances to revise and to learn about their own learning. The companion National Academy of Sciences report, Knowing What Students Know: The Science and Design of Educational Assessment (Pellegrino, Chudowsky, & Glaser, 2001), addresses principles of assessment design for learning situations aligned with the findings reported in How People Learn. According to Pellegrino et al. (2001), central to assessment is reasoning from evidence generated through a process consisting of three points: “a model of how students represent knowledge and develop competence in the subject domain, tasks or situations that allow one to observe students’ performance, and an interpretation method for drawing inferences from the performance evidence thus obtained” (p. 2). Mislevy et al. (2001) incorporate these same three points into their Conceptual Assessment Framework by specifying it consists of a student model, task model, and an evidence model. Almond, Steinberg, and Mislevy (2002) write that the student model is “the knowledge, skills, and abilities…to measure for each participant” (p. 35); the task model includes “the presentation material to be presented to the user…[and] a description of the work products that will be returned as a result of user interaction with the task” (p.24); and the evidence model acts as a bridge between the student and task models in that it describes how to analyze the evidence called for by the task model and so as to assess the student’s understanding. In writing about assessment designers, Mislevy et al. (2001) and Pellegrino et al. (2001) assert that networks, new media, and new methodologies have much to offer us in the way of support and enhancement of assessment but that technology has the potential to lure designers into creating complex tasks where substantial amounts of data are collected without any plan for analyzing how it can combine as an assessment of learner progress. To guard against this, Mislevy and colleagues (2001; Almond et al., 2002) promote using evidentiary reasoning and a design perspective during

the development of instruction and assessment materials so that the focus remains on construct definition, forms of evidence in keeping with the construct, and the creation of tasks that would produce such evidence. Extreme programming is an approach to programming developed by Beck and Fowler (2000) that describes how a team of software programmers works together with the client to efficiently create reliable code. Its creators describe it more as a set of values and disciplined approach than a strict set of steps. From our programmer’s use of it and the project director’s and other team leaders’ experience designing ETIPS, this strategic approach was excellent for letting the design of a case-based pedagogy emerge. This included the focus on developing an overall metaphor to illuminate what you are creating and then expressing distinct aspects of functionality in user stories that are coded, reviewed by the client and users, and then revised as needed. Extreme programming demands a lot of communication between the client and the programmers, often on a quick-turnaround basis. Further, to the degree the design process is driven by user testing, this requires advance planning for data collection, analysis, and reporting so that the code revisions can occur on a timeline that meets deadlines. Our team used a wiki to record our user stories and record notes from project meetings. The project director and programmers used a trouble ticket system to record the priority of the various user stories, recorded one per ticket, and their timelines and related communication. Working with the project evaluator, the project director and coordinator arranged for data collection from faculty and student users as needed. We also consulted experts on the usability of our site, including our compliance with disabled users’ needs as specified Section 508 of the Rehabilitation Act. Considering the Conceptual Assessment Framework during the design phase and following the approach advocated in Extreme Programming

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to bring that design into code can help creators of games and simulations work efficiently toward the educational purpose of their work. More importantly, it will encourage the development of assessment-centered learning environments, which we know will aid learning.

whAt Is next For our teAM At the time of this writing the project has about six months of funding left and so in addition to refining all features and user interfaces and support materials, we are focused on creating a revenue stream that will ensure the sustainability of our work. Over the last year we explored various models for generating income from the use of the cases. We have decided upon three related strategies. The first is to consider the functionality of the software and the case-based pedagogy it supports as a separate product that can be marketed to developers of educational cases on various topic areas. Developers would pay to license the ETIPS engine, and any income could help to improve the software. This strategy involved setting up working arrangements with a company that is focused on marketing the ETIPS engine as well as other educational software. A second strategy is that we will work with the membership networks and organizations that inspired the cases that we authored on additional topics. They, in turn, may promote the use of these cases to their members, who may then purchase access to the cases. The third, and most promising, strategy pertains to just the ETIPS cases on technology integration and implementation. The project director and a long-time test-bed faculty member are writing a series of books on technology integration in secondary science, mathematics, social studies, and English language arts. The educational technology integration and implementation principles serve as an organizational framework for the books; in the

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chapters about each of the six principles the online ETIPS cases are presented as homework exercises that learners complete to practice applying the main idea from that chapter. With this strategy the student who purchase the book is then very likely to purchase access to the cases, through an e-commerce functionality we have added. This model of students assuming responsibility for the costs of the educational materials associated with a class is familiar to students and faculty alike, and also allows our development team to leverage the publishing company’s expertise in marketing, selling, and distributing the books, and their inherent relationship to some of the ETIPS cases.

reFerences Almond, R. G., Steinberg, L. S., & Mislevy, R. J. (2002). Enhancing the design and delivery of assessment systems: A four-process architecture. Journal of Technology, Learning, and Assessment, 5. Retrieved from http://www.jtla.org Beck, K., & Fowler, M. (2000). Extreme programming explained. Boston: Addison-Wesley. Bransford, J. D., Brown, A. L., & Cocking, R. R. (1999). How people learn: Brain, mind, experience, and school. Committee on Developments in the Science of Learning with additional material from the Committee on Learning Research and Educational Practice, National Research Council. Washington, D.C.: National Academy Press. Retrieved May 24, 2002, from http://www.nap. edu/html/howpeople1/ Dexter, S. (2002). eTIPS-Educational technology integration and implementation principles. In P. Rodgers (Ed.), Designing instruction for technology-enhanced learning (pp.56-70). Hershey, PA: Idea Group Publishing. Mislevy, R. J., Steinberg, L. S., Almond, R. G., Haertel, G. D., & Penuel, W. B. (2001). Leverage

Educational Theory into Practice Software (ETIPS)

points for improving educational assessment (Tech. Rep. No. 534). Retrieved from http://cse. ucla.edu/CRESST/Summary/534.htm Pellegrino, J., Chudowsky, N., & Glaser, R. (2001). Knowing what students know. Washington, DC: National Academy Press. Stevens, R. H. (1991). Search path mapping: A versatile approach for visualizing problem-solving behavior. Academic Medicine, 66(9), S72-S75.

Stevens, R., Johnson, D., & Soller, A., (2005). Probabilities and predictions: Modeling the development of scientific problem solving skills. Cell biology education, 4(1), 42-57. Stevens, R., Wang, P., & Lopo, A. (1996). Artificial neural networks can distinguish novice and expert strategies during complex problem-solving. JAMIA, 3(2), 131-138.

This work was previously published in Games and Simulations in Online Learning: Research and Development Framework, edited by D. Gibson, pp. 223-238, copyright 2007 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.12

Combining Synchronous and Asynchronous Distance Learning for Adult Training in Military Environments Ilias Maglogiannis University of the Aegean, Greece Kostas Karpouzis National Technical University of Athens, Greece

AbstrAct A major issue problem in military training is the territorial dispersion of military personnel in a wide geographical area. Typically in every military training course, officers are gathered in training camps and attend the lessons. The specific model obliges officers to leave their position, their units to lose their services, and is extremely costly, as the learners have to move and reside near the training camp during their training. The application of distance learning techniques seems in a position to solve such problems. The School of Research and Informatics for Officers of the Greek Army in cooperation with the academic community in Greece studied the possibility of

training military personnel via a computer assisted distance-learning system and then implemented a pilot program in operational business management. This chapter describes the results of this study, the experience acquired during the implementation, and an overall assessment of the pilot program.

IntroductIon The increasing degree of technology shift and the growth of available information for consumption transform education into an incessant process. Furthermore, managerial needs impose the continuous strengthening of the capacities of human resources, since the human capital provides the

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Combining Synchronous and Asynchronous DL for Adult Training in Military Environments

impetus of any organization. As a result, the utmost priority of any modern army is the constant training and education of the military personnel in a wide gamut of issues. Current telecommunications and information technologies provide the indispensable capabilities for lifelong education without the need for presence at a physical classroom; this is defined as “distance learning” (Moore & Kearsley, 1996). In essence, this is a form of open education, in which the teacher and the learner need not be in the same space, since they are in touch by means of synchronous or asynchronous communication. In general, distance learning comes in many forms: some try to simulate the classroom paradigm’s two-way, synchronous communication in real time, while others support independent study controlled by the learner. The latter scheme is supported by most current distance learning environments (Broady, 1996). One of the goals of open distance learning is to provide access to all levels of education to individuals that distance or personal circumstances make it very difficult for them to attend conventional classes. Another goal is to teach courses to remote locations or military camps that are difficult for teachers to access. Consequently, the military environment is one of the best suited for distance learning, since learners are geographically dispersed and absence from their positions usually causes additional problems in the operation of their units (Maglogiannis, Mpourletides, & Karpouzis, 2003). Several studies have proven the efficiency of distance learning in vocational training of the personnel in big public organizations (Folkman, 2002; Gemeinhardt, 2002; Sampson, Karagiannidis, Schenone, & Cardinali, 2002). This chapter sums up the results of a pilot distance learning course, taught to military personnel. Fundamentally, distance learning is education delivered over a distance to one or more individuals located in one or more venues. Distance learning includes two modes of operation: “synchronous

distance learning,” which occurs when teacher and student are present at the same time during the instruction, even if they are in two different places, and “asynchronous communication,” which occurs when students and teachers do not have person-to-person simultaneous interaction during teaching. Asynchronous distance learning is delivered through open networks such as the World Wide Web, private intranets, or home computer-based study applications, while student faculty communication occurs via e-mail, including comments on homework assignments.

AcAdeMIc Issues Models of Learning environments A distance learning training program may be directed to learners of different degrees of educational level, minors or adults. In the case of learners in military service, the special circumstances of their profession impose special requirements, as well as special demands, on a distance learning environment. As a result, it is extremely necessary to pinpoint their individual needs, so as to prepare measures for satisfying them to the greatest extent. According to Knowles (1990), some of the most important “counter-measures” are: • • • • • •

Introduction of cooperative learning climate Establishment of mechanisms for teachers’ and learners’ mutual planning Identification of learner needs and interests Identification of learning objectives based on the diagnosed needs and interests Preparation of sequential activities for achieving the objectives Execution of planning via careful choice of methods, educational material, and required resources

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•

Evaluation of the quality of the learning experience while rediagnosing needs for further learning (Flottemesch, 2000)

For distance learning application to succeed in meeting the demands of all kinds of learners and be successful as a new educational paradigm that supports synergistic learning and active participation of learners, there have to exist a number of key elements and principles to be followed. These principles can be classified in five axes (Broady, 1996): 1. 2. 3. 4. 5.

Learning goals and content presentation Interactions Assessment and measurement Instructional media and tools Learner support and services

As far as realization of a distance learning environment is concerned, one can assume three fundamental models. The distinctive characteristic of these models is the means of control with respect to the actual teaching space and the pace of training (Blythe, 2001; Cronjé, 2001; Dzakiria, 2004; Schellens & Valcke, 2005). For example, in some models learners possess complete control and responsibility over their progress, while other models are based on stricter control enforced by the teacher or another central party (Bourdeau & Bates, 1996; Massicotte, 1997).

The “Distributed Classroom” Model This model essentially extends the educational curriculum offered in a traditional classroom to a group of learners in one or more distant locations, using advanced interactive means of communication. This form of teaching imitates that of the conventional classroom as far as both the teacher and the learner are concerned. As one may deduce, control over the learning process is

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centralized in this model, thus the control rests with the teacher.

The “Independent Learning” Model This model alleviates the burden of the learners’ presence in a particular location for a long time. Learners are provided with a wide variety of learning material, including a study guide and access to members of the teaching staff. This member acts as a tutor, offering guidance, solving problems, and evaluating the learner’s performance. Communication between the learner and tutor may include both conventional means (telephone, postal mail, etc.), as well as electronic (e-mail, teleconferencing, online forums, etc.).

The “Open Learning and Classroom” Model Utilization of this model combines the usage of a print study guide with additional educational material in electronic form, enabling individual learners to complete studying in their own pace. This model is integrated with modern communications technology so as to facilitate virtual class meetings between the learners. In this model, the teaching material is available in different forms and can be studied in a place and time that learners themselves choose. Usually, the same material is employed in more than one educational term and may be directly associated to a specific teacher. In some occasions, learners are gathered in pre-defined locations to attend lectures via interactive teleconferencing environments. Aim of these meetings is to discuss concepts and principles, inspire activity to solve specific issues, engage in laboratory work, and carry out educational exercises (Koumpouros, Maglogiannis, & Koutsouris, 2000). The characteristics of each model are presented in Table 1.

Combining Synchronous and Asynchronous DL for Adult Training in Military Environments

Table 1. Models of learning environments and their characteristics The “distributed classroom” model •

•

•

• •

Class sessions involve synchronous communication; students and faculty are required to be in a particular place at a particular time (once a week at a minimum) Number of sites varies from two (point-to-point) to five or more (point-tomultipoint); the greater the number of sites, the greater the complexity—technically, logistically, and perceptually Students may enroll at sites more convenient to their homes or work locations than the campus Institutions are able to serve small numbers of students in each location The nature of the experience mimics that of the classroom for both the instructor and the student

The “independent learning” model •

• •

•

There are no class sessions; students study independently, following the detailed guidelines in the syllabus Students may interact with the instructor and, in some cases, with other students Presentation of course content is through print, computer disk, or videotape, all of which students can review at a place and time of their own choosing Course materials are used over a period of several years, and generally are the result of a structured development process that involves instructional designers, content experts, and media specialists; not specific to a particular instructor

e-LeArnIng ProgrAM The distance learning program described in this chapter was in the field of operational business management for the Greek Army personnel. The specific program was realized using an adaptation of the open learning and classroom model, with strictest rules for the learners, aiming to the provision of better guidance and control. This concept is congruent with the basic principle of discipline, which dominates the military environment. More specifically, the educational model is summarized in the following points: •

An adapted curriculum was formed using a combination of synchronous and asynchro-

•

The “open learning and classroom” model •

•

•

•

Presentation of course content is through print, computer disk, or videotape, all of which students can review at a place and time of their own choosing, either individually or in groups Course materials (for content presentation) are used for more than one semester; often specific to the particular instructor (e.g., a videotape of the instructor’s lectures) Students come together periodically in groups in specified locations for instructor-led class sessions through interactive technologies (following the distributed classroom model) Class sessions are for students to discuss and clarify concepts and engage in problem-solving activities, group work, laboratory experiences, simulations, and other applied learning exercises

nous distance learning. The asynchronous part comprised of six courses, and each one of them was divided in several teaching units. The synchronous part included 15 lectures and presentations; some of them were reviews of the course material, thus these lectures were closely linked with the asynchronous course, while others dealt with subjects in the scientific area of the operational business management curriculum. The teaching material that supported the program was produced with the basic principles of open distance learning for adults in mind. This material was user friendly, included a multitude of self-evaluation exercises, as well as a study guide for each teaching unit,

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•

•

besides six printed books that were shipped to the learners. These books matched the six courses of the program, providing learners with the conventional print material, which they are usually more comfortable with, besides the online pages. Specific educational objectives were identified so as to promote the cooperative learning climate. A fundamental objective was to familiarize the Greek Army staff with the exploitation of a computer and the Internet as an educational medium. Thus, the staff was not merely trained in operational business management issues, but also in self-training and evaluation using computers. For every asynchronous teaching session, an academic and an Army staff representative were appointed to overlook the procedure. Every learner had mail and phone access to them so as to make specific questions, requests, or suggestions either on the process or on the actual content of the course.

networKIng And coLLAborAtIon The network architecture of the distance learning environment is described in Figure 1. All learners had personal Internet accounts in independent ISPs. This scheme provides a number of advantages: • • •

Low deployment cost Deployment was based on existing ISP infrastructure Inexpensive access to the material for the learners, at a place and time of their choice, without the need for extra hardware besides a PC and Internet access

However, this open architecture imposes a number of security measures during data transfer. In a nutshell, the network architecture consists of the distance learning software and systems development laboratory, the content development laboratory, and the teaching support group. The

Figure 1. Distance learning integrated architecture

Systems Development Lab

Support personnel Telephone

Content Servers Content Development Lab Firewall

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Internet

Learner

Modem

Trainer

Combining Synchronous and Asynchronous DL for Adult Training in Military Environments

Figure 2. The asynchronous distance learning platform

Figure 3. Screenshot from the online virtual classroom

latter includes personnel supporting the educational material, as well as technical support staff that help on matters related to the utilization of PCs and the distance learning environment. The distance learning environment that was employed for the operational business management course was Topclass from WBT (www.wbtsystems.com). Advantages of this system include:

•

•

•

AICC (Aviation Industry Computer-Based Training Committee) certification

• • •

Secure user management, organization in different classes, preparation of progress reports and tests Facility to use multimedia applications as educational material E-mail-based communication between learners and teachers CSCW-oriented tools, such as bulletin boards, attachments, forums, and so forth Straightforward test compilation and paper assignment based on actual progress of the learners

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•

Reporting that includes progress of the learners, total study time and coverage of material, and so forth

The educational material that learners had access to was partitioned to distinct teaching units, each covering about 15 pages of a standard textbook. Each teaching unit included expected results and key concepts, as well as solved exercises, self-evaluation exercises, and case studies (see Figure 2). In order to extend asynchronous teaching with constructive activities, synchronous teaching was implemented in the form of online presentations. Learners were able to attend high-level lectures by members of the academia or established business people, ask questions on scientific or applied matters, and, in general, comprehend the teaching material by participating in a distance education virtual classroom. This part of the curriculum consisted of 15 lectures, delivered by the Centra symposium application, part of the e-class services of Otenet, a major Greek ISP. The lectures were of perorational nature, but also gave the presenters the opportunity to elaborate on current socioeconomical issues or answer learners’ questions on the curriculum (see Figure 3). This service provided users with: • • • •

• • • •

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Integrated audiovisual teleconferencing Use of Windows applications in a multi-user environment Interactive chatting Provision of co-instructors (the main instructor was able to pass this role to any of the participants) Division of the e-class to breakout groups Lecture recording and playback on demand Recording of learners’ responses for further evaluation Tracking and recording of participation

Besides these, the learners were provided with a business plan preparation application and given access to a related digital library, with plenty of material for further study.

Administrative Issues Evaluation of acquired knowledge was performed both in-course and afterward. More specifically, following each of the six courses of asynchronous learning, learners took a two-hour online test and submitted a written paper, based on the curriculum of the course. After the completion of the six courses, learners took a written test in the UoA premises and submitted a final thesis, the subject of which was chosen amongst six possible subjects. Control of the learning process was centralized. Every two weeks, members of the teaching staff of UoA met with personnel of the School of Research and Informatics Officers of the Hellenic Army to address issues raised from the process or from the learners. Participants of the pilot program included 60 professionals of the Greek Army, widely dispersed with respect to their rank and academic background, as well as the particular object of their everyday occupation. All successful participants were presented with a relevant training certificate.

ProgrAM evALuAtIon evaluation criteria The pilot distance learning course was successfully completed by 48 participants, while 12 failed to pass the final examinations. The assessment process was two-fold: a.

Technological evaluation of the system, with respect to the functionality and the reliability of the platform (software problems, stability, response speed, etc.)

Combining Synchronous and Asynchronous DL for Adult Training in Military Environments

b.

Academic assessment of the system, with respect to its effectiveness from an educational point of view (material comprehension level, acceptance from learners, teaching staff, etc.) and was completed via: questionnaires filled in by the learners, statistical data amassed by the e-learning platforms, regarding the stability and utilization of the system, and taking into account test results and other means of learner evaluation

Technological evaluation of the system was based on system reports and notes by the system administrators. The 60 participants did not encounter any particular problems regarding their access to the distance learning platforms. The reports showed that e-class participation was about 75% average, essentially indicating that each learner dedicated about four hours of study daily. It has to be noted that since learners were provided with printed material, they were able to put in additional study hours without utilizing the asynchronous e-learning platform, which was particularly overloaded during weekends and public holidays. Usage statistics of the synchronous learning platform display quite interesting

results; therefore, they are discussed separately in the following subsection.

statistics from the synchronous Learning Platform The participation figures during the synchronous virtual meetings fluctuated from 68% to 100%. The highest percentages refer to the beginning of the course, while the lowest occurred after three months. The figures increased again as the courses were close to the end but did not reach 100%. The most popular application was the “playback on request” utility. According to the reports 39 out of 60 participants used this service a few hours or a few days later to recite the session. Other popular utilities that were used thoroughly are the “chat service,” “evaluation tests,” and “application sharing.” A significant conclusion extracted from the technical reports is that although 35 learners used the chat service to set a question for the instructor or other participants during the online lectures, only 20 of them asked to take the floor in order to speak online. This figure, along with the 21 learners that did not communicate at all in

Table 2. How the participants used the synchronous platform Number of Participants Used the Service

Expression as Part of Total

Playback on Request

39 participants

65%

Chat Service

35 participants

59%

Evaluation Tests

32 participants

54%

Ask to participate

20 participants

34%

Other Tools

9 participants

15%

Web Safari

8 participants

12%

41 times

2.7 PER SESSION

12 presentations

0.8 PER SESSION

E-Class Services

Application Sharing PowerPoint presentation

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the virtual classroom (they only indicated their presence by answering yes or no to typical questions), shows a relative reluctance in using the new interactive communication tools for speaking with the instructor. Therefore the corresponding speaker should always encourage the learners to participate, so as he was in an actual classroom with physical presence. A more complete figure of how the participants used the synchronous platform is displayed in Table 2.

•

questionnaire supported overall Assessment of the Project Evaluation of the questionnaires filled in by the learners was extremely useful in recognizing potential malfunctions in the distance learning process. The input consisted of questions concentrating on general issues on the program methodology, the quality of the material, and the availability of the instructors, interactive questions, and questions regarding the teaching material itself. Results from gathering and processing the learners’ responses indicated that: •

•

•

•

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Ninety-eight percent of the participants experienced distance learning for the first time. Sixty-one percent were particularly satisfied with the course, 30% mildly satisfied, and only 9% were not satisfied at all. Forty-three percent of the participating military personnel declared that delivery via distance learning platforms is appropriate, because job obligations do not leave much time for continuing education. A major part of the participants also stated that one of the main reasons for enrolling in the program was that it was offered by an established, non-military academic institution and not by an internal military office. For most participants, distance learning and especially synchronous sessions were quite

•

•

entertaining and original, since they offered a means of communication and interaction with colleagues. When this process was supplemented with academic activities (papers, test, etc.) the learners realized that synchronous teaching was not merely a communication tool, but part of the greater image. Eighty percent of the participants stated that quality of the material was exceptional, but requested more in-depth analysis on concepts that the authors regarded as self-evident, as well as wider access to specialized digital libraries. Sixty-five percent mentioned that self-evaluation exercises should indicate correct answers, while 30% thought that the duration of the program was less than necessary. In the question “how many hours did you spend on the program on a weekly basis,” 45% answered 15-20 hours, 38% 10-15 hours, 10% over 20 hours, and only 7% dedicated less than five hours per week. These responses prove the interest displayed from the part of the learners. An important part of the questionnaire concerned the direct communication between learners and instructors. Fifty-three percent of the participants mentioned that they used this feature extensively, while 47% hardly resorted to e-mails for questions and other problems. Indeed, the platform statistics show that 123 e-mail messages were answered monthly, which account for 2.5 messages per active participant. This essentially means that almost half of the participants did not need any additional help with the course or the platforms, at least besides any assistance provided during the synchronous sessions.

As a general rule, questionnaire evaluation showed that 90% of the participants were satisfied from the online sessions and requested additional

Combining Synchronous and Asynchronous DL for Adult Training in Military Environments

online meetings with instructors. This form of distance learning is closely related to conventional classroom teaching. Combination of synchronous and asynchronous teaching seems to be indispensable to eliminate the feeling of isolation, which is common in distance learning learners. Besides this, synchronous teaching served instructors’ needs as well, since it provided the opportunity to contact the learners every two weeks, solve any group questions, and track their progress.

best PrActIces Successful practices of the pilot program include the combination of synchronous and asynchronous distance learning and the limited number of participants, which facilitated performance tracking and evaluation. More specifically, the platform combination seems to be the optimal teaching scheme, since it combines advantages from both distributed and open learning classroom models. The requirement of the learners for more online lectures indicates the significance of the synchronous part in a distance learning environment. Moreover, regarding the synchronous part, the questionnaires showed that the opinion of the learners for their instructors was reflected on their participation and their interaction in the virtual class. The instructors that had better performance according to the answers had also bigger participation in their synchronous classrooms according to the extracted reports. This fact shows the criticality of the instructor’s competence for the success of the synchronous learning. The weak point of the program was the procedure followed for the selection of the trainees and the absence of a preparatory phase. Interrelating the trainee’s background with their performance, it became evident that the students with the lower participation and performance were those that exhibited low motivation when they applied for the

course or were not familiar with the new technology. Therefore, before the start of a course, the learners must be selected and informed carefully, checked for their motivation, test the necessary infrastructure, and become familiar with the tools to be used within the course, as it is very easy for them to feel disappointed and abandon the education procedure.

sustAInAbILIty And concLusIon Problem and solution tracking can assure the viability of any educational system. The correct evaluation of the integration of material, platforms, and architecture will guarantee identification of correct practices, room for possible improvement or expansions, and conclusions for similar future programs. During the specific pilot course it was proved that distance learning can be successfully applied for military training. The trainees liked very much the facts that an academic institution organized the course, they could attend the lessons without leaving their positions, and they could communicate with their colleagues located in distant units. The overall percentage of learners that successfully completed the distance learning course was approximately 85%. Future expansion of the project should include the enhancement of asynchronous teaching material with adaptive multimedia information, which is essential with respect to keeping learners focused and stimulating their interest. With respect to the course content itself, possible ideas for enrichment include concepts deemed fundamental for any military organization, for example, document management, human resource management, foreign languages, and ICT basic skills.

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reFerences Blythe, S. (2001). Designing online courses: Usercentered practices. Computers and Composition, 18(4), 329-346. Bourdeau, J., & Bates, A. (1996). Instructional design for distance learning. Journal of Science, Education and Technology, 5(4), 267-283. Broady, E. (1996). You are your own best resource: Promoting confidence and autonomous learning in teacher education at a distance—a case study. In E. Broady & M. M. Kenning (Eds.), Promoting learner autonomy in university language teaching (pp. 49-65). London: CILT. Cowan, J. (1995). The advantages and disadvantages of distance education. In R. Howard & I. McGrath (Eds.), Distance education for language teachers (pp. 14-20). Clevedon: Multilingual Matters Ltd. Cronjé, J. (2001). Metaphors and models in Internet-based learning. Computers & Education, 37(3-4), 241-256. Dzakiria, H. (2004). Models for open and distance learning. International Journal of Educational Development, 24(5), 575-576. Flottemesch, K. (2000). Building effective interaction in distance education: A review of the literature. Educational Technology, 40(3), 46-512. Folkman, K. (2002). Integrating distributed learning in work situations: A case study. Educational Technology & Society, 5(2), 75-80. Gemeinhardt, G. (2002). Best practices in technology-mediated learning in American business education. Educational Technology & Society, 5(2), 39-46.

Knowles, M. (1990). The adult learner: A neglected species. Houston: Gulf Publishing. Koumpouros, Y., Maglogiannis, Ι., & Koutsouris, D. (2000). A new tool for distance education. In E. Wagner & A. Szucs (Eds.), Research and innovation in open and distance learning (pp. 91-93). Budapest: European Distance Education Network. Maglogiannis, I., Mpourletides, C., & Karpouzis, K. (2003). Combining synchronous and asynchronous distance learning for adult education: The Greek Army case. In V. Devedzic, J. Spector, D. Sampson, & Kinshuk (Eds.), Proceedings of the 3rd IEEE International Conference on Advanced Learning Technologies (ICALT-2003) (pp. 358 -359). Athens, Greece: IEEE Computer Society Press. Massicotte, G. (1997). Groupware as a way of integration of classical and distance learning models in higher education. European Journal of Engineering Education, 22(1), 3-9. Moore, M., & Kearsley, G. (1996). Distance education: A systems view. Belmont, CA: Wadsworth Publishing Company. Sampson, D., Karagiannidis, C., Schenone, A., & Cardinali, F. (2002). Knowledge-on-demand in e-learning and e-working settings. Educational Technology & Society, 5(2), 107-112. Schellens, T., & Valcke, M. (2005). Collaborative learning in asynchronous discussion groups: What about the impact on cognitive processing? Computers in Human Behavior, 21(6), 957-975. WBT Systems. (n.d.). Retrieved May 1, 2006, from http://www.wbtsystems.com/

This work was previously published in Cases on Global E-Learning Practices: Successes and Pitfalls, edited by R. Sharma & S. Mishra, pp. 22-34, copyright 2007 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.13

Reflection and Intellectual Amplification in Online Communities of Collaborative Learning Elsebeth Korsgaard Sorensen Aalborg University, Denmark

AbstrAct An alternative theoretical framework for analyzing and designing computer-supported collaborative learning environments is introduced. Bateson’s theory (1973) is used as a starting point for considering in what sense the specific dialogical conditions and qualities of virtual environments may support learning. We need more stringent analytical approaches of research that relate communicative qualities of virtual contexts to qualities of the collaborative knowledge-building process. This approach suggests that new didactic and instructional methods, addressing the learner’s communicative awareness at a meta-level, need to be developed in order to fully utilize the interactive and reflective potential of online collaborative learning. A deeper understanding of the reflective

nature of the online environment and its potential for enhancing intellectual amplification will give rise to the birth of new and more innovative designs of online collaborative learning.

IntroductIon Flexible computer-supported learning is rapidly emerging as the educational method of choice in modern society. Although most applications of computer-supported learning are primarily interactions of the learner with software, the envisioned educational expectation within distributed computer-supported collaborative learning (CSCL)1 is design and delivery of flexible learning environments with deeper collaborative and interactive learning qualities (Kaye, 1994). This

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Reflection and Intellectual Amplification in Online Communities of Collaborative Learning

expectation has so far not been realized (Collis, 1996; Fjuk, 1998; Sorensen, 1997b, 1998; Collins, Mulholland, & Watt, 2001), primarily because achieving peer interaction remains a complex challenge. Several studies based on practical applications identify shortcomings in the technology as the main reason for the lack of collaborative learning. They conclude that learning situations unfolding face to face are more conducive to good quality learning than online CSCL situations. In contrast, within CSCL research, the problem of achieving online peer interaction is identified as a shortcoming of not being able to integrate pedagogy, organization and technology (Bates, 1995; Fjuk & Sorensen, 1997) in appropriate ways. CSCL researchers do not interpret online CSCL as lower level quality learning compared to face-to-face learning; instead there is a growing awareness that a more generalized understanding of human interaction and communication is the key to unlocking the interactive learning potential of CSCL (Dillenbourg, Baker, Blaye, &O’Malley, 1995). New insights are needed into the interactive learning conditions of virtual environments. The general principles of collaborative learning theory are assumed to be at the core of CSCL (Harasim, 1990; Sorensen, 1996, 1997b). However, these principles are only vaguely defined in the continuum between theory and practice and are not focused enough to analyze learning qualities in the virtual environment. We need more stringent analytical approaches that relate communicative potential and qualities of the virtual communicative context to qualities of the learning process. Such insights are expected to inspire new, alternative instructional designs and didactic methods (Koschmann, 1996; Pea, 1994). This chapter presents an alternative theoretical framework for analyzing and designing CSCL environments, and argues that online collaborative learning environments are conducive to intellectual amplification. It addresses the learning potential of distributed CSCL and the need for

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and role of meta-instruction. I will assert that the inability to stimulate online interaction may be traced to a lack of understanding among designers and instructors of the characteristics of dialogue in virtual environments. On this basis, I will attempt to explain how specific dialogical conditions and qualities of virtual environments may enhance interaction and intellectual amplification in asynchronous distributed CSCL. Based on the theoretical perspective of Gregory Bateson (1973) and basic “ontological” principles of online learning environments, I suggest potential reasons for the mixed successes in previous attempts to achieve collaborative learning online. I assume that key impediments to success relate to interconnections between meta-communication and scaffolding (Bruner, Olver, Greenfield, et al., 1966). Empirical examples will be given to illustrate the hypothesis that successful online learning environments that are rich in opportunities for reflection require careful design of meta-communicative scaffolding and instruction. “Premises of Collaborative Online Dialogue” describes “ontological” premises and conditions for inter-human interaction in asynchronous online learning environments that are significant from the perspective of designing for collaborative learning online. This is followed with a section that presents the core elements in Gregory Bateson’s (1973) learning theory on which my theoretical approach and insights for reflective amplification in online collaborative learning are built. In Section 4, I introduce three reflective principles, which I assert contribute to making an online collaborative learning paradigm an amplified intellectual endeavor. Next, the chapter outlines some empirical findings illustrating the amplified reflective collaborative learning process of the online environment, enhanced through the implementation of meta-communicative instruction and scaffolding. The chapter then discusses my conclusions on collaborative learning environments as ideally promoting intellectual amplification,

Reflection and Intellectual Amplification in Online Communities of Collaborative Learning

and concludes with a section that suggests areas of future research.

PreMIses oF coLLAborAtIve onLIne dIALogue Inter-human communication is the basic medium for collaboration and collaborative knowledge building in learning, so communication must be considered at a basic level before designing any structure that involves linguistic collaboration between learners.

the Missing Link: A new dialogical Paradigm Stimulating peer interaction is essential when designing distributed collaborative learning processes (Harasim, 1989; Sorensen, 1993). This applies to asynchronous virtual environments (be they client-server facilities or Web-based) as well as face-to-face environments. It is customary, however, to assume that conditions of face-toface dialogues, and the way they are stimulated, are the basis for creating support for distributed interaction in virtual environments (Sorensen, 1997b). In other words, we have assumed that in design and management asynchronous distributed CSCL processes of online dialogues are the same as for face-to-face dialogues. However, the thinking behind the design and management of distributed CSCL, before even considering learning processes, must have a deeper understanding of asynchronous online dialogue. We need to understand what happens to inter-human online dialogues that are no longer routed and embedded in a physical time and context. Such research must be central, when considering dialogue and interaction in online CSCL (Harasim, 1989; Sorensen, 1997a).

characteristics of online dialogues The assumptions of face-to-face interaction influence the way we understand and apply the role and tasks of the online instructor (Sorensen, 1999). Only a few research studies (Eklundh, 1986; Sorensen, 1993) have attempted to clarify the specific conditions and premises of online dialogue. Sorensen (1993) analyzed large quantities of electronic dialogues from a linguistic perspective and reported four basic characteristics of online dialogues.

The Elasticity of Time and Context One feature of online dialogues is the dynamic relationship between the level of “interactivity” and the linguistic character of the interaction. Although the significance of social and organizational factors, like roles (e.g., moderator of conference, teacher of a course, etc.) and levels of formality, or “loyalty,” toward the traditional style of writing in electronic dialogues should not be underestimated, there seems to be a dynamic relationship between frequency of interactive moves and the level of context dependency of the linguistic character of the moves. Consider the example of a language game (Eklundh, 1986), which has an opening, perhaps one or more intermediate “moves” and a closing comment. Language games work toward termination. A context that is established and shared mentally stimulates a frequent exchange of moves (Sorensen, 1993). If too much time elapses between the exchanges, the context has to be rebuilt. In this case the speed of the information exchange is reduced. In other words, higher “interactivity” elevates the level of mentally shared context and background knowledge between interlocutors. Thus, higher “interactivity” moves toward “synchrony” in the interaction (i.e., toward the situation of face-to-face meetings), which leads to a more shared “presence” in the style of linguistic moves between interlocutors. Furthermore, the frequency

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Reflection and Intellectual Amplification in Online Communities of Collaborative Learning

of message exchange determines to what level the character and features of the linguistic interaction resemble the prototypical spoken interaction and language. When the exchange of messages occurs at longer intervals in time, the character of the interaction and use of language will resemble the prototypical written interaction. Although this appears as a general dynamic principle of the electronic interaction, there seem to be certain properties of the electronic interaction that distinguish it from spoken interaction. Even at a high level of interactivity, electronically mediated dialogue will never be as transient as spoken dialogue. The possibility for retrieval classifies electronic interaction more like written dialogue, even under high frequency of message exchange. Another invariant feature is the single communication pathway. Regardless of the level of interactivity, this will always be (at this point in time) a condition of the electronic interaction. A third constant feature, which the electronic dialogue seems to have taken over from written interaction, is the lack of tendency to practice “gear change” (i.e., a mechanism of slowing down the speed of the interaction in order to make explicit an implied presupposition made by the other interlocutor). The gear-shift mechanism is an important dialogic feature that is very valuable in various types of spoken interaction. In particular, in pedagogical design situations, it may be important to realize that high gear utterances, which often have highly embedded structures with many latent presuppositions, put much more strain on a listener than a low gear variant with a low level of embedding.

Compensational Behavior An experience shared by many learners is that electronic interaction seems more similar to spoken dialogue than to written interaction. Nevertheless, the interaction is not a face-to-face interaction and does not share the same conditions as that of spoken dialogue. The only semiotic sign through

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which the interaction of an electronic dialogue can manifest itself is the written word. Several elements, normally contained in nonverbal communication, are pertinent to the interpretation of spoken linguistic communication, and nonverbal communication is fundamental to us, in the sense that we cannot avoid nonverbal communication. Pragmatically, nonverbal behavior seems to entail not only the expression of social identity, personal traits and psychological states, but also sends a signal in parallel with the verbal component that stimulates the communication partner to react. In addition, it is fairly well established that the course of a conversation is strongly influenced by the participants’ inferences and attributions as to the social identity, personality disposition and respective psychological states of their partners (Van Dijk, 1985). Inability to communicate feelings, states of mind and attitudes to a communication partner is an obstacle in the electronic interaction. Because electronic interaction in conferencing systems is mainly monosemiotic (takes place mainly through writing), the most widely used method for communicating these elements, and, thereby, stimulating a stronger social connection between participants, is creation of a visual image by use of those written symbols offered by the computer keyboard (e.g., {{8-)—indicating a happy face with glasses). Compensational behavior clearly demonstrates a need for communication methods other than those offered by the written language. There seems to be a need to invest “presence” and personal aspects into the interaction. This need that may be caused by a physical separation (where chances for “in between face-to-face encounters” are limited) and limitations imposed on the interaction as a consequence of the monosemiotic condition. In principle, compensational behavior can be translated into traditional written descriptions. However, doing so would create a general delay and inertia in the communication process, which would be frustrating and would remove all the

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spontaneity of the interaction (and, after all, it is the social, interactive aspect of conferencing systems that stimulates communication). Compensating iconographical/indexical behavior can be viewed as a new and innovative element in writing, which has appeared concurrently with the increased importance of communication based on pictures or combinations of pictures and text. Iconic/indexical signs are easy to interpret because they do not require translation in the same sense as a written description, but are understood more directly through the impression they make on the senses. They may be superior to verbal communication for expressing feelings, states of minds, attitudes, etc.

The Continuing Dialogue An ongoing electronic dialogue tends to be kept alive and to be experienced by learners as a never-ending discussion. If we adapt the perspective of language games (Wittgenstein, 1974; Sorensen & Takle, 2002), the interaction may be seen as parallel and/or as continuously progressing sequences of language games. The amount of closure in electronic language games (i.e., a condition where no language game is open and no expectations with respect to a continuation of the game are unfulfilled) is low in comparison to spoken dialogues. This may be part of the reason for the rather common experience of conferencing systems users that response means success (at some level), while silence definitely indicates failure. If all expectations in a language game apparently are satisfied, there is a tendency to avoid closure and to provide instead “extra” information in order to create a sufficient and “legitimate” basis for keeping the dialogue alive. Typically, the language game will continue, for example, by one of the interlocutors responding to some extra information in the closing move, and in this way introducing a partly new frame.

Although the problem of termination of electronic dialogues is rather complex due to the many-to-many interaction (e.g., it is never too late to respond), the gradual displacement of linguistic frame/context to keep the language game going seems to be a general pattern. A large proportion of electronic language games has a phatic function by which social contact and interaction between the communicating parties is established and maintained. The frequency of attempts in electronic dialogues to avoid closure and promote continuing interaction clearly indicates the importance of the social/phatic aspects of the interaction. It seems to be vitally important to keep the interaction going, so much so that it is conceivable that the “true” intention of many language games is not to achieve fulfillment of expectations, but rather to maintain social relations—even if the games, structurally, would be classified differently. Newer learning environments, like, e.g., GCPortfolio (Takle, Sorensen, & Herzmann, 2003) and Knowledge Forum (Scardamalia, 2002), use descriptive categories as a way of supporting progression in online CSCL. Successful knowledge building is assumed to be characterized by reflective thinking skills and deep embedding of ideas in larger conceptual structures, as well as in the practices of the knowledge building community. While the GC Portfolio uses the category of “synthesis,” Knowledge Forum uses the category “rise above” for promoting closure in the dialogue. This may be a fruitful way of managing the needed synthesis and convergence of ideas in knowledge building discourse. Yet to be determined is the extent to which such promising designs may handle the significantly enlarged social needs of a truly distributed group of learners.

The Independence of Time and Space An electronic interaction appears like a complex mixture of distance and closeness. The feeling of distance may be related not so much to the “real”

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geographical distance between interlocutors, as to the impossibility of overcoming the asynchronous condition. Although the feeling of distance may vary quantitatively, an element of distance will always be present (of course, also reinforced by the lack of nonverbal behavior). It is conceivable that this condition reduces obligation, or a least urgency, to respond. Similar behavior is common in face-to-face dialogues, but it is not considered a problem because it gets regulated through repair games/subgames, which are easily and smoothly introduced. The feeling of closeness may derive partly from the fact that the interlocutor always has opportunity to “be close” or participate, if he wishes, by responding to or initiating a language game. The metaphor of a shared room for the interaction may engender a feeling of closeness. A final consequence to be pointed out here, which is related to the independence of the interaction from time and space, is an issue mostly affecting the receiving situation of the interlocutor. As production and comprehension of messages occur at different times and independently of each other, a move is never topical viewed in relation to the mind of the author. Passing time separates author from subject. The importance of time intervals and the dynamic establishment of context/frame for the interaction can create interpretative problems, as the responding interlocutor cannot predict the time that will elapse before his answer gets read. The above-mentioned characteristics of online dialogues inevitably will influence instructional and scaffolding decisions made as part of any online learning design (Sorensen, 1997a).

Presence online Social presence online, the fundamental element for creation of a collaborative knowledge-building (KB) process through what Wenger calls “negotiation of meaning” (Wenger, 1998, p. 87), is threatened by lack of both participation (in-

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teraction) and engagement (Gunawardena, 1995; Rourke, Anderson, Garrison, & Archer, 1999). Creation of an online presence in net-based distributed collaborative learning processes based on participation and mutual engagement in order to ensure the negotiation of meaning is a pedagogical challenge that is tied into the symbolic nature of the online environment. Online presence is established through the process of submitting comments. A comment, therefore, has two communicative functions: to communicate its content and to communicate presence. (Co)existence in the virtual environment is established through interactive production of contributions. In other words, (co)existence and (inter)action takes place via communication (Feenberg, 1989; Sorensen, 1999; Bygholm, 2002). Far too many designs of online collaborative learning implicitly assume that self understanding, interaction and communicative actions in a virtual, asynchronous written universe are operationalized by the same mechanisms valid in a traditional, synchronous spoken face-to-face setting (Sorensen, 2000). As pointed out earlier, virtual asynchronous communication rests on fundamentally different principles for communicative unfolding than faceto-face communication. We understand ourselves and our social behavior as phenomena closely related to the contexts of time and space. But we have failed to recognize and exploit the special communicative conditions for actions and interactions provided by a virtual, asynchronous written context. Our traditional social (co)existence in terms of social interaction is inextricably tied into a synchronous reality of time and space. In a virtual environment (co)existence is freed from these constraints. A pedagogical model of design and virtual instruction for distributed CSCL, therefore, must take into account the interplay between collaborative principles of learning and the communicative conditions of virtual (co)existence and (inter)action. Basically, we need different

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analytical approaches that look not only at online dialogues themselves but that relate the communicative potential and qualities of the virtual environment to qualities of the learning process. Such an approach may be inspired by some general principles of the learning theory studies of Gregory Bateson (1973).

theoretIcAL PersPectIve In this section I outline the core elements in Gregory Bateson’s learning theory (1973) that inspired my theoretical perspective on reflective amplification in online collaborative learning.

communication and Learning in the Light of bateson (1973) Although Bateson is not a linguist, he works from the basic assumption known from the field of semiotics of communication as a multi-semiotic phenomenon (Sorensen, 1997b), viewing all signs in a communication (verbal and nonverbal) as communicators that play a role in creating and forming the communicative message. In his understanding, the meta-communicative context is essential in learning, as it is active in forming the

communicative message. He considers all types of learning to be communication phenomena and that learning must, in some basic way, be subject to the same rules that apply to communication (Bateson, 1973). A very central idea in Bateson’s theory is that incidents of learning—being basically communicative in their nature—unfold as meta-communicative movements in different levels of reflection 2 or communicative contexts3 , in a continuum bounded by “no reflection” on the one end and “several levels of reflection” on the other. Bateson views meta-reflection as a necessary precondition, as well as a result of learning. His understanding of the learning phenomenon as processes of reflection and meta-communication may be visualized by Hermansen’s model (see Figure 1, Hermansen, 1996). Bateson conceptualizes learning as transcendence of levels of reflection taking place on hierarchical layers of context (meta-communication). In learning level 0 + 1, there is a direct relationship between the learner/subject (S) and object (O), which has to be learned. At this point in learning, there is no reflection on the learning process, but the foundation for reflection is developed. We could say that there is a more or less random testing of possibilities.

Figure 1. Learning as transcendence of levels of reflection

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Learning level 2 is characterized by an indirect relationship between the learner and the object, as the learner uses reflection as one of the means in his/her learning process. At this level there is a systematic reflection on how to solve a problem, and the learner is conscious about the fact that he/she is learning. He/she is consciously tied to the situated conditions (in a wide sense) and actively using what he/she has learned at other (lower) levels. At learning level 3 there is a relationship of reflection, in relation to reflection, in learning. At this level the learner has a reflective attitude to how he/she approaches learning. This level of learning usually happens outside concretely related contexts. Level 4 is difficult to conceptualize. Much interpretation of Bateson sees learning at this level as the momentary “aha!” experience in which we may sense faintly the whole connection of something. Other interpretations hold that this is the level of learning or insight, which may also bring a conscious opposition in the learner, and is a consequence of having achieved the problempenetrating insight into a problem. In summary, we could say that the general learning principle in the Bateson model is that “you should always relate yourself to yourself, while you relate to something,” and that the level of learning achieved changes all the time because the frame (or context) within which it happens changes.

PrIncIPLes oF dIstrIbuted cscL: FroM reALIty to vIrtuALIty Engeström (1987) points out that reflection over the learning process is essential if learning is to develop and expand in depth and in width. Contrary to the physical world, in which some philosophers view the existential state of “involvement” to precede the state of “reflection” (Heidegger,

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1986), the virtual universe provides a context and an “ontology” in which reflection may be viewed as preceding involvement (Sorensen, 2003). The move from physical reality to virtual reality creates a change in context, a change of principles and premises of being and, acting through insertion of a meta-level of symbols and representations, creates a reflective distance to the learner. With regard to “ontological” conditions for action and interaction, three basic “ontological” principles emerge in the move to the distributed, virtual symbolic world:

From Appearance (being) to representativity (signs of being) It is only through signs and symbols produced by a learner that the learner is “present” in the shared virtual environment. In other words, presence in a discussion is confirmed through the action of making a comment. Thus, a comment communicates presence and content. By extension, any action (communicative or non-communicative) taken by the learner is carried out not directly, but symbolically through manipulation of symbols and representations (Foucault, 1970; Sorensen, 1997b). Moreover, it is not only the learner’s actions and interactions that take place through representative signs (e.g., the written sign). The signs and communication from the learner’s context(s)—a concept of great complexity for the distributed learner (Sorensen, 1997b)—must, through processes of reflection, be transformed into verbal language and communicated with the language games of the interaction with other people. The only parts of the learning context, which are shared, are the virtual environment, as well as the context of the language games constructed socially through the interaction with other learners and with the teacher. The view that “context” is an important factor in communication is not new. The linguist, Roman Jakobsen, in his model of communication talks about “the referential function to the context”

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(Ricouer, 1978, p. 222), and the American philosopher, Peirce, from the perspective of semiotics, focuses on the indexical relationship of any sign to the embedding world (Suchman, 1987). Also, the HCI-researcher Lucy Suchman is concerned with the role of context and states that the significance of a linguistic expression on some actual location lies in its relationship to circumstances (Suchman, 1987). Finally, Bateson uses the term “context” to describe the (not materialistic) situational conditions—that are communicatively effective in creating meaning—in which a message, incident or behavior occurs (Bateson, 1973).

From Primarily being Involved in Interaction to Primarily Reflecting on Interaction In the virtual environment the learner cannot interact (make a comment) without being prompted to reflect at a meta-level about the content of his/her comment. There is no level of (inter)action without a process of reflection (Sorensen, 2003). The move of learning processes to a distributed virtual symbolic environment introduces a meta-communicative level in all of the learner’s actions and interactions. This creates “distance” between the acting subject (the learner) and the object (the intended action or interaction). Processes of reflection not only imply distance, they are preconditioned by distance.

Consequently, we may conclude that the virtual universe—contrary to the physical world in which involvement may be viewed as preceding reflection (Heidegger, 1986)—provides a context and an “ontology” in which reflection precedes involvement. The fact that reflective processes (implying distance) precede involvement in distributed virtual environments may also explain the frequent instructional experience that transferring collaborative learning processes to virtual environments usually uncovers and makes visible (to a much higher extent than face-to-face processes) design features and the learners’ communicative acts. The reflective character of our actions in the virtual space implies the distance, which causes us to acknowledge them. At a practical level, the learner experiences an enlarged need for reflection in the virtual environment, when he/she makes the simple communicative act of composing a message. Before submitting the message, the learner is asked to reflect on the content of his/her message and, through reflective engagement at a meta-communicative level, to decide on a descriptive title in relation to the content of the message. Summing up, we may conclude that the virtual environment enhances processes of reflection (Figure 2). More specifically, if we acknowledge that reflection is involved even at the first level of learner actions in virtual environments, then we may generally conclude that learning processes

Figure 2. Virtual learning processes initiated at a higher reflective level

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unfolding in virtual environments are initiated at a higher reflective level (level 2) of learning (Figure 2), than physical learning processes that unfold in relation to the learning content.

From Involved Speech to Reflective writing The move from dialogically composed speech to monologically composed writing is an environmental change that defines the basic reflective conditions for learning processes in distributed virtual environments. From the theoretical view of Bateson (1973), insertion of a symbolic level through the use of the written sign in learning actions and interactions also has a clear learning value (Sorensen, 1999). Not only does it promote increased reflection and thinking at the shared collaborative and interactive level, it also represents a kind of “tool” for individual intellectual amplification. The process of writing something down creates a distance between the thought and the thinker. Much research and literature acknowledges this view on writing. For example, Johansen (1998) states that linguistic forms are the forms of thought and that writing is the technology of thinking. In the same way, writing is said to be thinking made tangible, and that the road to clearer understanding of one’s thoughts is traveled on paper. It is often through the search for words to express ideas that we discover what we think. The need for explicitness that is implied in writing promotes learning processes when viewed, as in the case of Bateson, as transcendence of reflective levels in the continuum between no reflection and reflections on reflections on reflections. The principles presented above and the requirement for enhanced meta-communicative awareness have significant implications for didactic and instructional design. They indicate a need for an enhanced focus and awareness at the meta-communicative level of instruction and scaffolding in communities of online collaborative learning.

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eMPIrIcAL exPerIences To illustrate the amplified reflective collaborative learning process of the online environment, I describe a study in which enhanced metacommunicative instruction and scaffolding was implemented. A pedagogical design for encouraging reflection and meta-communication has been implemented in a course on global environmental change at Iowa State University (Takle et al., 2003). Global Change (GC)4 is a conventional science course for senior undergraduates or beginning graduate students at a U.S. university. It gradually has been migrated to a Web base over the last nine years, with new features being added as ancillary software has become available. Learner-centred activities in place of or supplemental to conventional lectures have been introduced. The course consists of a sequence of learning modules on different global-change topics, each having evolved from a conventional university class. Each unit has a set of objectives, summary information on the topic, student-submitted collaborative (twothree students) summary of class time discussion, “problems to ponder” as discussion starters for the electronic dialogue and extensive lists of Web and other information on the learning module topic. Each unit has its own electronic dialogue for student discussion among themselves and with outside experts or representatives of selected groups. Electronic dialogue on individual learning unit topics is graded. The course is viewed, by the designers, as a laboratory for experimenting with a variety of pedagogical techniques and initiatives (Taber et al., 1997). Students are asked to employ reflection in their online dialogue on global change topics by declaring, as a label on their posting, the particular knowledge-building skill (KBS) they are using. At the end of each of three successive five-week periods, students are asked, by means of an online self-assessment, to reflect on their use of these skills, and how use of these skills has

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contributed to the knowledge base for each topic. The instructor evaluates (online) the self-assessments on the basis of students’ understanding of KBS and its use in building a knowledge base. In the second and third assessment cycles, the student and instructor together (through online self assessment and evaluation in light of current and preceding assessment cycles) reflect on the progress the student is making toward effective use of KBS in the global change context. Metacommunication in the latter cycles, therefore, is at a higher level and examines fundamentals of the learning process (how specific KBS achieve specific goals of learning), in addition to building a global change knowledge base (primary focus of first assessment cycle). Implementing categories of collaborative KBS requires a corresponding meta-functional pedagogy or instruction that facilitates and motivates a collaborative dialogue. Thus, students were given a set of meta-categories (i.e., a set of KBS) with examples of how each could be implemented. These categories were (Stahl, 1999):

• • • • • •

Brainstorming is the introduction of new ideas that relate to the topic or task and offer a perspective not previously considered; Articulating includes explaining complex or difficult concepts; Reacting provides an alternative or amplified perspective on a concept previously introduced by a student; Organizing refers to assembling existing thoughts or perspectives in such a way that a new perspective emerges; Analysis includes comparing or contrasting previously articulated views or puts new understanding on existing data; and Generalization takes comments or data already presented and extracts new information or knowledge that applies to a broader set of conditions.

An analysis of this course (Sorensen & Takle, 2002) reported on the role and nature of the instructions in the requirements given to students to stimulate interaction. Characteristics of student dialogue and its relationship to course requirements were evaluated by assembling 10 comments from 1995, 10 from 1997, and 10 from 2000. The analysis assessed whether meta-communication in terms of providing meta-awareness of “the function of a comment” in the KB process would improve the quality of the KB dialogue and, thus, enhance intellectual amplification (Sorensen & Takle, 2002). A subjective measure of quality (0-10) of online comments was applied to dialogue from (a) 1995 when no requirements were placed on the number of comments and KBS were not required; (b) 1997 when requirements were put on the minimum number of postings made by each student; and (c) 2000 when the KBS were described and required. Evaluation of a random sample of comments from these three implementations revealed that the quality value went from 4.4 (1995) to 3.2 (1997) to 5.3 (2000). We ascribe the drop in quality from 1995 to 1997 to the demand for more postings, which generated more but shallower comments. We attribute the rise in quality from 1995/1997 to 2000 to reflection, meta-communication and self-assessment surrounding the use of KBS. Average word counts of the comments in these three years went from 88 to 93 to more than 300, suggesting deeper engagement in the topic of the posting when KBS were required.

concLusIon In this chapter, I have addressed the reflective nature of the online environment and its potential for enhancing intellectual amplification. From a Batesonian perspective, I have attempted to establish principles describing to what extent

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and in what sense virtual learning processes possess learning qualities hitherto unknown in face-to-face learning situations. On the basis of this initial theoretical exploration, I conclude that intellectual amplification — in as far as processes of reflection are viewed to be central aspects of learning — inherently receive special support in online learning environments. Through the insertion of a meta-communicative layer of context, virtual environments seem to promote processes of increased reflection in learning. Thus, when learning processes move up the reflection ladder, we need to provide meta-communicative weaving techniques and to support meta-communicative structures of scaffolding. The fact that distributed collaborative learning processes unfold on the basis of a dialogical paradigm different from familiar face-to-face processes indicates that we need to review existing instructional techniques and to incorporate new and innovative methodological initiatives. The very different learning conditions provided through the new dialogical paradigm may be part of the reason for the general lack of success of learning design in terms of stimulating online interaction. The new dialogical conditions create a need for didactic change related to design of collaborative learning processes and to teaching methods within collaborative learning. In this process, some central instructional CSCL concepts and ideas may have to be reviewed, broadened or redefined. Viewed from the processes of meta-communication and meta-reflection as these appear through the glasses of Bateson, scaffolding should not primarily be related to the decomposition of learning content or tasks. Rather, as transcendence of learning levels appears to be the key in learning, scaffolding should be directed toward supporting the learners’ navigation through metacommunicative levels. Promoting this thinking, however, is a challenge that is likely to affect, not only instruction, scaffolding, and didactic

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elements of distributed learning processes, but also the actual development and construction of virtual environments for distributed collaborative learning online.

Future PersPectIves The emphasis on reflective processes in learning, however, should not lead us to overlook the important dimension of practice. Virtual spaces and virtual learning environments provide rich opportunities for future research aimed at finding ways to implement these concepts in the virtual universe of learning. New collaborative tools (e.g., white boards, shared documents, etc.) and new and innovative use of existing tools provide environments for conducting controlled, hypothesis-driven statistically-based research that will clarify which design structures most effectively exploit the virtual environment to enhance learning. This paper has addressed asynchronous distributed collaborative learning from the theoretical perspective, but the challenge ahead may be to investigate empirically, and more thoroughly, to what extent the reflective principles described are manifested in practice.

AcKnowLedgMent Valuable and insightful comments on both the content and language of this chapter have been provided by Professor Eugene S. Takle, Department of Agronomy and Department of Geological and Atmospheric Sciences, Iowa State University, USA.

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Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith (Ed.), Liberal education in a knowledge society (pp. 67-98). Chicago: Open Court. Sorensen, E. K. (1993). Dialogues in networks. In P. B. Andersen, B. Holmqvist, & J. F. Jensen (Eds.), The computer as medium (pp. 389-421). Cambridge, UK: Cambridge University Press. Sorensen, E. K. (1996). Learning online through linguistic interaction. Innovation in Teaching and Learning: An International Journal for the Critical Practitioner, 2(2), 12-17. Sorensen, E. K. (1997a). På vej mod et virtuelt laeringsparadigme. In J. C. Jacobsen (Ed.), Refleksive laereprocesser (pp. 78-109). Copenhagen, Denmark: Politisk Revy. Sorensen, E. K. (1997b). Learning in virtual contexts: Navigation, interaction, and collaboration. Unpublished doctoral dissertation, Aalborg University, Denmark. Sorensen, E. K. (1998). Design of TeleLearning: A collaborative activity in search of time and context. In T. Chan, A. Collins, & J. Lin (Eds.), Proceedings of ICCE’98: International Conference on Computers in Education: Global Education On the Net, 2 (pp. 438-442). Sorensen, E. K. (1999). Collaborative learning in virtual contexts: Representation, reflection and didactic change. Proceedings from the Sixteenth International Conference on Technology and Education, ICTE99 (pp. 454-456). Sorensen, E. K. (2000). Interaktion og laering i virtuelle rum. In S. B. Heilesen (Ed.), Universiteter

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Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge, UK: Cambridge University Press.

2

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endnotes 1

The term “distributed CSCL” denotes computer-supported collaborative learning designs in which most of the educational dialogue in the learning process takes place asynchronously and collaboratively between people over the Web (Sorensen & Fjuk, 1997).

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Mads Hermansen has in his book “From the Horizon of Learning” introduced the interpretation of the various learning levels of Bateson, as corresponding to levels and meta-levels of reflection in learning (Hermansen, 1996). Bateson uses the term “context” to describe the (not materialistic) situational conditions that are communicatively effective in creating meaning and in which a message, an incident or a behavior occur (Bateson, 1973). The public access to the Global Change course is at the web site: http://www.meteor.iastate. edu/gccourse/.

This work was previously published in Online Collaborative Learning: Theory and Practice, edited by T. S. Roberts, pp. 242261, copyright 2004 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 4.14

Project Management in Student Information Technology Projects Maria Delia Rojas Murdoch University, Australia Tanya McGill Murdoch University, Australia Arnold Depickere Murdoch University, Australia

Abstract Universities teach project management to information technology (IT) students. The project management principles that students previously have learned often are put into practice in a project course that is intended to give final-year students the experience of applying their knowledge to real or simulated projects. This article reports on research that investigated the use and usefulness of project management in student IT projects. The results show that there was a wide range in the application of project management practices, with students being more likely to produce the initial documentation associated with some of the project management knowledge areas than to make use of it throughout the project to monitor the project’s progress. The results also showed that the number of project management guidelines applied in stu-

dent projects was not linked to IT project success. However, there was a strong relationship between project management plan quality and obtaining a good software product.

INTRODUCTION Universities all over the world teach project management to information technology (IT) students (Goold, 2003; Grundy, 1997; Stein, 2002). The project management principles and system development methodologies that students previously have learned often are put into practice in an IT project course that is intended to give final-year IT students the experience of applying theoretical concepts and practical techniques to real or simulated student projects (Grundy, 1997). The

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Project Management in Student Information Technology Projects

research reported on in this article investigated the use and usefulness of project management in student IT projects. Student projects usually are defined and scoped to run on a one- or two-semester basis within an academic program and are not as complex as industry projects (Jih, 2003). Within the time limitation placed on these projects, students have to plan, design, and implement their systems and create relevant documentation. While student projects are not comparable in size and complexity to industry projects, the rigor expected is the same as for industry projects. Past experience reveals that IT students find it difficult to manage their project for reasons such as lack of understanding of project management tools and techniques (Lowe, 2000; Pournaghshband, 1990). The Project Management Institute’s (PMI) ‘Project Management Body of Knowledge’ (PMBOK) provides a solid base of standards, procedures, and practices for managing all types of projects and is used by many organizations to apply project management principles to projects (Freedman, 2002). The goal of project management guidelines is for project managers to achieve better outcomes in projects. IT students also can make use of project management guidelines in order to try to achieve the same goal.

Project Management and the PMboK guide Project management is “the application of knowledge, skills, tools, and techniques to project activities to meet project requirements” (Project Management Institute, 2000, p. 6). The PMBOK Guide is a handbook that provides broadly accepted knowledge and practices that are generally applicable to most projects. There has been widespread consensus as to the value and usefulness of these guidelines (Schwalbe, 2004). The PMBOK Guide consists of five project management process groups and also is divided into nine key sections called the project manage-

ment knowledge areas. These knowledge areas are divided further into their component project management processes, which describe the activities that need to be fulfilled for each knowledge area. In addition, each of the nine knowledge areas has specific project management tools and techniques that help to carry out the activities in each process. The project methodologies and practices presented in the PMBOK Guide are used to control and manage projects and cover every aspect of project development.

the role of Project Management in It Projects Generally, project management is considered important for three reasons. First, project management can clarify a project’s goals because it makes the project manager produce documentation that identifies the project’s unique characteristics, which have to be addressed throughout the project. Second, project management will enable a project manager to identify the required resources, thus assuring the project’s stakeholders that resources are being managed effectively. Finally, project management can help to succeed in the achievement of both project and organizational goals. There has been some research into the value of project management in IT projects. An early study by Pinto and Slevin (1988) tested the importance of factors that are believed to be critical to project success. Each of the critical factors was tested independently against project success, and the results showed that having a project schedule and plans was significantly related to project success. They concluded that project managers need to create project schedules and plans and to use them on a regular basis. More recently, the Standish Group’s (2001) CHAOS project investigated the scope of software project failures and the major factors that cause software projects to fail. The results showed that project success rates have increased since 1994, which partially is attributable to better project

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management, including the availability of better tools to monitor and control progress, better skilled project managers, and better management processes. This study also found that 46% of successful projects used a formal project management methodology, compared to 30% of challenged and failed projects. Hence, having a formal project management methodology appeared to increase the chances of success by about 16% (The Standish Group, 2001). This research is supported by the findings of Aladwani (2002), who studied the mediating effect of project planning among three project uncertainty variables and IT project success and showed that IT project planning was the most important contributor to IT project success. Gowan and Mathieu (2003) tested a model of the relationship between technical complexity, project size, use of a project management methodology, and project performance. The results showed that the use of a formal project management methodology is positively related to project performance, particularly when project size is large. The research already described illustrates the value of applying project management practices to IT industry projects, and hence, it is vital for IT students to learn and apply the standard practices in order to manage projects successfully. Phillips, Fairholme, and Luca (1998) noted that while student project teams address some project management issues, many focus more on the development of the product. IT students need to be aware of the value of project management, and they need to be encouraged to use project management principles. Du, Johnson, and Keil (2004) conducted a project to find out what project management topics are being covered in information systems curriculums and concluded that project management practices have not been incorporated fully into university IT degree programs. They argue that preparing future IT graduates to apply project management guidelines will increase the success rates of industry projects.

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reseArch questIons The study reported on in this article was conducted in order to explore the use and usefulness of project management in student IT projects. It considered both project management in general and, more specifically, the application of PMBOK guidelines. Phillips et al. (1998) argued that it is important for IT students to be aware of project management guidelines. Therefore, the first research question relates to awareness of project management principles: RQ1. Are IT students aware of project management principles that can be applied to student projects? An objective of the research was to establish how IT students apply PMBOK Guide practices and to identify any relevant project management knowledge areas that are not applied. The second and third research questions, therefore, relate to actual application of project management principles: RQ2. Do IT students apply PMBOK Guide practices in their IT development projects? RQ3. What are IT students’ perceptions of the usefulness of PMBOK Guide practices? The final objective of the research was to identify whether the application of project management principles increases the likelihood of students completing IT projects successfully. Therefore, the final research question is: RQ4. Does the application of project management principles increase the success of student IT projects?

Project Management in Student Information Technology Projects

Given the evidence that use of project management increases the likelihood of industry project success (Aladwani, 2002; Gowan & Mathieu, 2003; Pinto & Slevin, 1988; The Standish Group, 2001), it is likely that this is also the case for student projects. Therefore, the following hypotheses were proposed:

for the purpose of the study. Forty-one students completed the questionnaire. They represented 14 project groups. Evaluations of project management plan quality and IT project success for the groups also were used in the analysis. These were based on course assessment undertaken by the project group supervisors.

H1: The application of project management practices increases the chances of completing student projects successfully.

the questionnaire

H2: Increasing the quality of project management plans increases the chances of completing student projects successfully.

the study The research sample consisted of final-year IT students enrolled in an IT project course at an Australian University. Students formed their own project groups to undertake the project. However, groups were subject to approval by the course coordinator to ensure that they were well-balanced in terms of the skills of the group members. Each group had approximately five students. The group members were assigned different roles, but after a few weeks, the roles were rotated. The students had a range of IT project management backgrounds prior to the project. However, most students had completed at least a systems analysis and design course that included an introduction to project management. The data for this study were collected partly by means of a questionnaire that was administered during the final weeks of the IT project course. The questionnaires were given to the course coordinator, who distributed questionnaires to all students during project group meetings. It was stressed that the completion of the questionnaire was voluntary, that all information would be kept confidential, and that data would be used only

The questionnaire included the following sections (see Appendix 1 for a complete set of the questions asked).

Background Information Background information, including gender, age, and major(s), was collected for each student.

PMBOK Awareness Each participant was asked to rate his or her awareness of project management and PMBOK Guide practices before starting and after completing the IT development project. The answers were measured on a five-point scale from 1 (very little) to 5 (a lot).

PMBOK Use The section of the questionnaire relating to PMBOK use was divided into seven sections that corresponded to seven of the nine project management knowledge areas: Project Integration Management, Project Scope Management, Project Time Management, Project Quality Management, Human Resource Management, Project Communication Management, and Project Risk Management. Project Cost Management and Project Procurement Management were not included in the questionnaire because these projects were not given a budget and did not obtain people or sources from an outside organization. Use of

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the guidelines that corresponded to the seven knowledge areas were measured with a series of question that were answered Yes or No.

Perceived Usefulness of PMBOK Guide Practices Students’ perceptions of the usefulness of the individual PMBOK practices were measured on five-point scales from 1 (not useful) to 5 (very useful).

Additional study variables The following variables were measured separately from the questionnaire after completion of the projects.

Quality of Project Management Plan The IT students worked in groups and, hence, produced only one project management plan per group. Project management plan quality was measured based on the mark that each group of students received from its supervisor for their project plan.

Project Management Practices Applied The number of project management practices that were applied by each group was used as a measure of overall application of project management principles. In each student group, there were up to five students. In some groups, all students were involved in all parts of project management, but in some groups, students were involved in only some. Therefore, if any member of the group had carried out a particular practice, it was counted toward the total for the project group, and this was used as a measure of the number of project management practices that were carried out.

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IT Project Success Traditionally, project success has been measured in terms of the project objectives of time, cost, and scope known as the triple constraint (Brock, Hendricks, Linnell, & Smith, 2003; Schwalbe, 2004). The triple constraint makes it relatively easy to evaluate project success by comparing the actual time, cost, and performance with the planned time, cost, and performance objectives. However, in these student projects, only one of the three criteria was applicable. There was an absolute deadline for completion set, and the projects were not given a budget. Therefore, this study used only one of the triple constraint criteria. This was the scope and software quality of the software product that was created for the client. As was mentioned before, the participants worked in groups, and they developed only one software product per group. This software product was marked by the team’s supervisor. Consequently, each group had only one IT project success score.

resuLts And dIscussIon It students’ Awareness of Project Management guidelines The first research question related to student awareness of project management principles. Table 1 shows the levels of awareness of project management in general, and of PMBOK both before and after completing the IT project. These were compared using t tests. Students’ awareness of general project management practices was significantly higher after completing the IT project course (t=-6.58, df=39, p Video; RCV is Relative Content Value. According to the transcoding or transforming operation on the Media Object, this value can be from 1 to 0;

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Project Smart Remote Classroom

be optimally distributed to each media object in the document, of course including the document itself, so as to render the most valuable result to the user. The adaptive process of the AMTM can be described as selecting the optimal resource allocation scheme and associated transformation plan for the embedded Media Objects by searching in the Status Space of Transforming. Our aim is to obtain the largest CV of the document while transforming the Media Object in real-time. To solve the problem, we constructed some formulas to relate the consumed time resource (including the time of media transformation) to the resulting content value, and optimally distributed the resource using Lagrangian method, then searched in the status trees to get the best sequence of trans-coding operations. Figure 2 (b) illustrates a typical transforming status tree, where the original media is labeled with Status0, and converted into the new node Status11 through operation1 with parameter1, while sub-node Status13 is transformed to newer nodes, namely Status21, Status 22, Status 23 and so on. AMTM couples the time/space impact of the media transformation and delivery into the optimal transformation policy to implement the media adaptation. This policy is implemented in the RMS of TORM.

sAMevIew: soFtwAre For rtIvc SameView is a software system developed for real-time interactive distance learning application based on the proposed TORM and AMTM platform (see Figure 3).

Interaction Approaches SameView provides a set of interaction approaches for the teacher and students to efficiently gain their ends of teaching and learning.

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1.

2.

3.

Mediaboard, which is a shared whiteboard, is capable of displaying multimedia contents in HTML format. The teacher can show any materials for the class on the board as long as it is in HTML format or can be embedded in an HTML page. Or it can even open an Internet URL here. Moreover, she can add annotations or scribble on the slides on the fly. All actions the teacher makes on the board, such as jumping between slides, scrolling the slides and writing on the slides, will be synchronously displayed on each student’s client. When permitted by the teacher, a student can also dominate the Mediaboard, for example, write down his solution to a problem issued by the teacher. Audio/Video. The students can hear the audio and see the video come from the teacher side. In addition, a student can also broadcast his audio and video to the others, when permitted by the teacher, for example, when the teacher asks him to give comments on a topic. The audio/video compressing and de-compressing are developed on MS DirectX SDK, so any DirectX compliant codec can be utilized by the system, for instance, DivX or Intel Indeo. Chat. In addition, teachers and students can communicate by text messages.

sessIon MAnAgeMent The users participating in a class through SameView will play different roles in the class. The possible roles include Chair, Addresser, Audience and Anonymous. Chart 1 shows their respective privileges. The teacher usually plays the role of Chair, while students are always initially assigned to the role of Audience. As a class going, the teacher can dynamically change the role of a student if necessary, for example, to invite the student to

Project Smart Remote Classroom

Chart 1. Privileges of different roles Role

Change other users’ role

Action on Mediaboard

Chair Addresser Audience Anonymous

Allowed NA NA NA

Allowed Allowed NA NA

Broadcast Audio/ Video to others Allowed Allowed NA NA

User number with this role 1 >=0 >=0 >=0

Listed on Participant List Yes Yes Yes No

Figure 4. Login window of SameView client application

Figure 5. Main user-interface of the SameView client Li s tList ofof par tparticipating i ci pat i ng s t udent s students Vi Video deo f from r om Teacher Teacher s islide de

give comments on a topic. An audience can also send a request to the Chair if he/she wants to be an addresser. If more than one participant broadcasts Audio/Video at the same time, only the one who speaks loudest will get the right of speaking. Remote students use a client program to take part in a RTIVC held with SameView. On running this program, the student will first see a login dialog

Medi aboar d Mediaboard and t he the slides sand l i des displayed on on it di s pl ayed it

as in Figure 4. The upper part of this dialog is for getting the information related to student’s personal information, such as his/her name and desired role in the session. The lower part of this dialog is for configuring the parameters related to the underlying TORM session, such as whether this program should function as an RMS or an RMC and the address of the direct upper-stream

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Project Smart Remote Classroom

server in the TORM hierarchy. If this node is not in the same IP-Multicast-capable subnet as the upper-stream server, the “link to upper-level server through tunnel” should be checked to establish tunnel with Unicast. Figure 5 shows the main user-interface of the SameView Client application after login into a session. On the right is the window for the Mediaboard. As shown, a HTML page is displayed on it. The panel on the left lists all the participants of this RTIVC session and their state, such as their role and whether a role-upgrading request is pending for that participant. Another separated floating window is used to show the live video of other participants who are broadcasting their video, according to selection policy described in the previous section.

cLAss recordIng SameView can capture the exact process of a class by recording everything that happened on all interaction approaches, such as the slides the teacher showed, the annotations made on the slides, as well as the live video and audio, and integrate into a structured compound document in a synchronized manner. Actually, this recorded document is a good starting point for developing a courseware for e-learning. Toward this direction, we provide a post-edit toolkit for the teacher to edit the recorded document as necessary, such as to correct some mistakes made in the class, or to add some tags and indices to the document so that retrieval of the content of the document becomes more efficient. Figure 6 shows the interface of the post-editing tool. It is composed of four main windows. The upper-right window displays the contents and events that appeared on the Mediaboard, including the loaded HTML page, the added annotations and the browsing sequence. The upper-left window displays the recorded live video. The lower-right window is for modifying properties of a recorded event. The lower-left window

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displays the recorded events in a time-line style. The timing relation between each event is obvious through this view. The cursor on the timeline can be easily dragged right and left to locate the wanted time point, and the content in the other three windows will jump to the correct position with the moving of the cursor. After post-edition, the recorded document can be put on a website, and students can download and play this document through a provided SameView Player program at any time they want after the class. Figure 7 shows the SameView Player program, which is similar to the SameView Client program, except for an additional VCR-like panel for playback control. For the students to rapidly find the information they need while viewing the recorded class, two kinds of retrieval technique are provided. The first one is seeking by time, similar to a VTR control. The second one is seeking by keyword. For this kind of retrieval to function, the teacher should have manually tagged each event-of-interest in the recorded document in advance with the post-edit tool. We are currently considering using certain natural-language processing technologies such as digesting to automatically generate index tags for each recorded event in the document.

sMArt cLAssrooM: A nAturAL Front-end oF sAMevIew As analyzed in the introduction section, the desktop-based experience in most of today’s RTIVC systems is not acceptable for many teachers. For them, face-to-face classroom education is most familiar and efficient. Therefore, a question for researchers of RTIVC technologies is whether it is possible for the teachers to have the same experience as in a traditional classroom. Our answer to this is the Smart Classroom. Smart Classroom is inspired by the research filed of Smart Space. A Smart Space is a richly instrumented physical environment where people

Project Smart Remote Classroom

Figure 7. SameView player

can get transparent access to information and assistance from computers while performing their ordinary tasks in this space. (Refer to NIST, an overview of the research filed of Smart Space.) Smart Classroom is just such an effort to turn an ordinarily classroom into a Smart Space for Tele-education (Xie, 2001; Xie, 2002 Sep). We equipped an ordinary classroom with wall-sized displays, sensors, cameras and the associated software modules such as gesture-tracking module and speech-recognition module so as to allow the teacher presenting in the classroom to access the SameView system transparently, rather than appeal to a desktop computer. Through Smart Classroom, we actually extend the user interface

of the SameView for the teachers from a desktop computer into the 3-D space of the classroom.

room setting The space of a classroom usually can be divided into two parts - the teaching area that is mostly used and occupied by the teacher, and the audience area where local students reside. The most significant physical instrumentations in a Smart Classroom, as illustrated in Figure 8, are two large projector screens in the teaching area. The one on the front wall is a touch-sensitive screen, replacing the usual blackboard or whiteboard found in a classroom. It functions as a physical embodi-

Figure 8. Snapshot of the Smart Classroom Remote Students Studentboard

Mediaboard

Virtual Assistant

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Project Smart Remote Classroom

ment of the shared Mediaboard component of the SameView software at the teacher side. (We also call this physical screen a Mediaboard. Whether this name refers to the software component in the SameView system or this physical screen will be clear according to the context.) Another screen called Student Board is on the sidewall. It is the window for remote students, on which the image of remote students participating in a SameView session with Addresser roles will be displayed and the video and audio of the remote student who takes the floor will be played here too. Besides these two obvious facilities, there are about a half-dozen cameras, each with different usage, installed at different places in the classroom. Some are used to recognize the action of the teacher and the result is interpreted as an interaction command to the underlying SameView system. Others are used to capture the live video of the classroom for broadcasting to the remote students. In addition, the teacher wears a wireless microphone to capture his speech.

2.

unrestricted natural teaching experience In Smart Classroom, in order to give classes to remote students, the teacher no longer needs to remain stationary in front of a desktop computer and, for most common tasks involved in a class, the teacher no longer needs to use the keyboard and mouse either. For this aim, the following technologies are developed and integrated in the Smart Classroom. 1.

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Pen-Based UI: As mentioned above, the Mediaboard is displayed on a touch-sensitive screen, which is actually a commercial product called SmartBoard. Most functions of a mouse found in a desktop setting can be accomplished by operating directly on this board. For example teachers can control the display of the slides. Moreover, using the provided pens and erasers, teachers can

3.

write comments and scribbles on the slides or wipe the strokes, as illustrated in Figure 7, which provides just the same experience as using a real blackboard or whiteboard. Speech-Capable Virtual Assistant: The Smart Classroom incorporates a speech-recognition module as well as a text-to-speech module. Therefore the teacher can complete several common tasks in a class by voice command such as “Give the floor to Tom” or “Jump to the previous page.” The system can also use the synthesized voice to notify the teacher of certain events. For example when a remote student named Peter asks for the floor, the system will alert the teacher, “Peter is asking for the floor.” But interacting with a dummy room by voice will seem funny in some sense, so we introduced a Virtual Assistant figure into the Smart Classroom to impersonate the classroom. The Virtual Assistant shows a face of a virtual person, which is displayed on the StudentBoard as illustrated in Figure 8 as well as in Figure 10, and its face expression and lips movement is synchronized with the synthesized voice of the system. Thus the teacher can see a vivid virtual assistant that can understand her/his voice command and give notifications or feedback through speech, just as if there is a real assistant. Laser Pointer as An Interactive Tool: Laser pointers are widely used as a tool for indicating the focus nowadays. Besides this common utility, in Smart Classroom the teacher can even use a laser pointer as an interactive tool. The function is provided by a computer vision module that can track the movement of the spot of the laser pointer and recognize its certain movement patterns. This recognition result is interpreted differently according to whether the spot is on the Mediaboard or the Studentboard. If on the Mediaboard, the movement of the spot is interpreted as the mouse movement

Project Smart Remote Classroom

Figure 9. Give the floor to a remote student by a laser pointer plus voice command

the representing image of a remote student is highlighted as the teacher pointed the laser pointer on it

Figure 10. Teacher login to the Smart Classroom Virtual assistant

A camera of face recognition is installed behind the mirror

event and circling the spot around a point is interpreted as the mouse-click event, so that the teacher can select and open a link on the HTML page by laser pointer. Although the same task can be completed by manipulating on the Mediaboard directly, this is useful, for the teacher does not need to approach the Mediaboard every time he/she needs to open a link. If the spot is on the Studentboard, the recognition result is interpreted as the current selection of a remote student, and as an indication, this remote student’s representing image will be highlighted. Together with voice command, it provides a convenient method for the teacher to control the

4.

floor among remote students. For example, the teacher can point the laser pointer at a remote student’s representing image and say “Go ahead” (as shown in Figure 9), which will make the system give the floor to this remote student. Login in to the Classroom Based on Biometric Characteristic: Since a Smart Classroom is a public space, each teacher who gives a class in it needs to identify him/herself as the member of the system in order to be authorized to use the facilities in the classroom. The common way of authentication on a desktop computer is inputting one’s ID and Password with keyboard. In

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Project Smart Remote Classroom

Smart Classroom, we use a combination of face-recognition and speaker-verification technology to automatically identify the teacher, and provide the teachers an unrestricted experience while logging into the classroom. As the teacher enters the Smart Classroom, he first should show up in front of a mirror (behind which a camera for capturing the teacher’s face is installed) and speak out his name. If both the facerecognition and the speaker-verification are passed, the Virtual Assistant will greet him, indicating the Smart Classroom is now ready to serve him. This procedure is shown in Figure 10. Moreover, the system will use the teacher’s identification information to load the right voice model for the teacher into the speech-recognition module if the teacher has trained such a model in advance, which is beneficial for the accuracy rate of the recognition result.

smart cameraman When taking a class in a real classroom, the students will change the focus of their sights as the context of the class changes. For example, when the teacher is writing a formula on the blackboard, the students will focus their sight on the formula, while when the teacher is showing a model in his hand, the students will focus their sight on the model. However, in most current RTIVC systems,

the students can only get the teacher-side video with a fixed scene no matter how the context of the class changes, which significantly decreases the efficiency of understanding of the teacher’s instruction. To overcome this problem, a facility called Smart Cameraman is introduced into Smart Classroom, which can distinguish among several kinds of contexts in a class by observing some cues in the classroom, and then select a camera with proper view according the context from an array of available ones as the source of the live video to remote students. Currently, this module can successfully distinguish the following three kinds of contexts: 1.

2.

3.

Teacher Writing on Mediaboard, where the teacher is writing or scribbling on the Mediaboard. In this case, the camera which focuses on the Mediaboard will be selected, as Figure 11(a) shows. Teacher Showing a Model, where the teacher is holding a model in his hand. In this case, the camera which follows the teacher’s hand will be selected as Figure 11(b) shows. Others, for all other situations. In this case, the camera with a overview of the whole classroom will be selected, as Figure 11(c) shows.

The cues used by the Smart Cameraman to estimate the current context includes the output

Figure 11. Different scenes remote students get according to context of the class

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Project Smart Remote Classroom

of a Person-Tracking module which tracks the position of the teacher, a Gesture-Recognition module that can decide whether the teacher is holding something in his hand and the touch event as reported by the SmartBoard.

composing modules are carefully designed and developed, the interconnection of modules takes a loose-coupling policy. First, we use message passing instead of RPC so that one module will not block the completion of a communication request. This also reduces the blocking possibility of another module which is communicating with a halting module. Secondly, we use a mediated communication scheme, in that all the modules only need to maintain a connection with a centralized message dispatcher module and all the inter-module communications are dominated by this dispatcher. This structure reduces the recovery work needed when a module is restarted after failure.

the software of smart classroom As we have seen, besides the SameView software, there are many other software modules running in the Smart Classroom that provide periphery services for the SameView system such as speechrecognition module, text-to-speech module, hand gesture tracking module and so on. In total we have about a dozen modules running on eight distributed computers and we developed a multi-agent system called Smart Platform (Xie, 2002 Oct) to interconnect and coordinate these modules. Here each module is running in a separate process; they communicate with each other through predefined XML format messages. For example, the module in charge of the laser pointer tracking will periodically send a message to the module in charge of the Mediaboard to update the location of the cursor while detecting a laser pointer spot. Since the Smart Classroom is a fairly complicated system, its reliability is an important issue that needs careful consideration. Besides each

the overall scenario Figure 12 depicts how the above-described parts of the Smart Remote Classroom project are integrated into an overall scenario to enable a revolutionary real-time interactive distance learning practice. In this scenario, a teacher gives a class with natural ways in a Smart Classroom, where there might be local students, while the remote students connected by Internet access this classroom with SameView clients. The remote students can see the present class materials, the annotations

Figure 12. Smart remote classroom system Smart Classroom Camera

Camera

Display

Camera

Internet

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made during the lecture, the live audio/video of the classroom and also can take the initiative to interact with the teacher and local students in the classroom, just like attending the classroom locally. Furthermore, the process of the lecture will be recorded as a multimedia courseware for review after class.

concLusIon We developed a set of key technologies for a realtime interactive distance learning system and made a new paradigm of real-time interactive distance learning with the following characteristics possible: 1) unifying the face-to-face education and tele-education in the Smart Classroom, which on one hand provides a consistent teaching experience for teachers and on the other hand reduces the teacher workforce needed, for the teacher does not need to give the same class for the on-campus students and remote students separately; 2) accepting large-scale users to access the virtual classroom simultaneously with different network and device capabilities; 3) allowing the class to be recorded and turned into a piece of courseware for review of the class of E-learning. Currently we have made concrete achievements in each part of the project and the prototype system runs quite well in initial informal evaluations. (Welcome to http://media.cs.tsinghua.edu. cn/~pervasive.) We are planning a formal user study of this system in the near future. We are also cooperating with the Distance Learning School of Tsinghua University for the large-scope user experiments of this system.

endnote *

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This chapter is the extended version of the preliminary paper the appeared in ICWL2002 conference proceedings. The related research is supported by NSFC, “863”

High-tech Plan, The Ministry of Education, China, and IBM China Research Lab.

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Tan, K., Shi, Y.C., & Xu, G.Y. (2000). A pragmatic semantic reliable multicast architecture. In Proceedings of The Third International Conference On Multimodal Interfaces, Beijing, China (pp. 658-665).

Xie, W.K., Shi, Y.C., Xu, G.Y., & Mao, Y,H. (2002, Oct). Smart platform - A software infrastructure for smart space (SISS). The Fourth International Conference on Multimodal Interfaces (ICMI2002), Pittsburgh (pp. 429-434).

Xie, W.K., Shi, Y.C., & Xu G.Y. (2001). Smart Classroom: An Intelligent Environment for Tele-education. In Proceedings of The Second Pacific-Rim Conference on Multimedia (PCM 2001), Beijing, China (pp. 662-668).

Zhuang, Z.Y., Pei, Y.Z., & Shi, Y.C. (2002). Loss recovery performance comparison of two reliable multicast protocols (SRM and TORM). Computer Engineering (in Chinese), 28(11), 170-173.

Xie, W.K., Shi, Y.C., & Xu G.Y. (2002, Sep). Toward a better user experience in tele-education: Recent advance in smart classroom project. The Fourth International Conference on Ubiquitous Computing (UbiComp 2002), Goteborg, Sweden, Adjunct Proceedings (pp. 51-52). Available at

Zhang, H.J. (2000, January 13-15). Adaptive content delivery: A new research area in media computing. Proceedings of The International Workshop on Multimedia Data Storage, Retrieval, Integration and Applications 2000, Hong Kong.

This work was previously published in International Journal of Distance Education Technologies, Vol. 1, No. 3, pp. 28-45, copyright 20034 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 4.19

The Role of Project Management in Technology Literacy Daniel Brandon Christian Brothers University, USA

INTRODUCTION A key component in technology literacy involves the management of technology resources. In industries that “build things”, that management of technology is largely encompassed within the discipline of Project Management. Project Management is “the application of knowledge, skills, tools, and techniques to the project activities in order to met or exceed stakeholder needs and expectations from a project.” (Duncan, 1996) A project is defined as “a temporary endeavor undertaken to create a unique product or service” (PMI, 2000). In such industries, the first level management job for a technical person is typically in a “project manager” role.

BACKGROUND Despite ongoing innovations in project management, many projects fail; in some industries,

particularly Information Technology (IT), most projects still fail. A Standish Group study found that only 16% of all IT projects come in on time and within budget (Cafasso, 1994). Field’s study discovered 40% of IS projects were canceled before completion (Field, 1997). The problem is so widespread that many IT professionals accept project failure as inevitable (Cale, 1987; Hildebrand, 1998).

PROJECT MANAGEMENT IN PROFESSIONAL ORGANIZATIONS A number of professional organizations have developed around the world to address and foster this specific discipline. Most notable is the Project Management Institute (PMI, www.pmi.org) with about 140,000 members worldwide. Other major international organizations are the Association for Project Management (APM) and the International Project Management Association (IPMA) (Mor-

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The Role of Project Management in Technology Literacy

Figure 1. PMI processing groups and knowledge areas Initiation Integration scope

Initiation

Planning

executing

controling

Project Plan Development

Project Plan Execution Overall Change Control

Scope Planning

Scope Verification

Scope Change Control

closing Scope Verification

Scope Definition

time

Activity Definition

Schedule Control

Activity Sequencing Activity Duration Estimation Schedule Development

cost

Resource Planning

Cost Control

Cost Estimating Cost Budgetting

quality

Quality Planning

Quality Ass urance

Quality Control

human resources

Organizational Planning

Staff Acquisition

Team Development

communications

Communications Planning

Information Distribution Performance Reporting

risk

Risk Identification Risk Identification

Administrative Closure

Risk Response Control

Risk Quantification Risk Response Development

Procurement

Procurement Planning

Solicitation

Soliciation Planning

Source Selection

Contract Administration

Contract Closeout

Contract Administration

ris, 2001). These organizations have recognized there is a distinct skill set necessary and level of technology literacy for successful project managers, and the organizations are devoted to assisting their members develop, improve, and keep current these skills (Boyatzis, 1982; Caupin, 1998). The Project Management Institute has developed an index of project management skills and knowledge called the “Project Management Body of Knowledge” (PMBOK). The PMBOK has been developed through several iterations over many years; the first version was developed in 1976 (Cook, 1977). The latest version (PMBOK 2000) was just released (for certification testing beginning 1/2002) (PMI, 2000). It defines nine “Knowledge Areas” (KA) which are organized into 37 “Processes”. The processes are grouped into 5 “Process Groups” (PG). This is illustrated in Figure 1 (for PMBOK, 1996) (Duncan, 1996). The KA’s represent the technology literacy necessary

for effective project management: scope management, time management, cost management, risk management, quality management, human resources, communication, and procurement. PMI (and the other international project management organizations) have a certification program, and for PMI the designation for the most important certification level is “Project Management Professional” (PMP). To obtain PMP certification an individual must have 4500 hours of documented project management experience over a period of six years, have a BS level college degree, and pass a rigorous four hour examination. The first PMP exam was given in 1984 to about 30 people, and today there are over 30,000 PMP’s worldwide (Foti, 2001). These professional organizations recognize that while there is a large set of common technology literacy amongst industries, each industry (and each government sector) has it’s own spe-

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cialized extensions in both the breadth and depth of this body of knowledge. PMI has a new book (PMI, 2002) that details the way project work is typically organized in a number of industries as well as the US government. In addition PMI has books on PMBOK extensions for the largest industry sector of project management, the construction industry (PMI, 2003), and for US government (PMI, 2002). Many other books are also available on Project Management in particular industries such as Information Technology (Schwalbe, 2001).

ProJect MAnAgeMent In the AcAdeMIc coMMunIty Several universities have also recognized the fact that project management involves distinct skills and technology literacies, and that the traditional degree programs and courses in both business schools and other schools do not adequately cover and/or integrate these components. (Brandon, 2003) The Chronicle of Higher Education recently reported that seven Philadelphia-area corporations established ties with four universities in that region to improve the business skills of computer science and IT students; most of these key skills involved the project management skill sets (Chronicles of Higher Education, 2001). Perhaps self evident from the previous paragraph is the fact that the knowledge and training needed by project managers covers both traditional business disciplines and disciplines involved with building or making things. Often the skills involved with building or making things would be found in an engineering curriculum, and also in information technology or computer science curriculums. Since the skill sets needed by project managers are extensive, and since these skills involve both business and engineering disciplines, and also since most candidate students are degreed working adults, most schools have developed

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their project management curriculums as graduate school programs. A number of universities also have a single “Project Management” course typically offered as a graduate course.

graduate degree Programs An analysis of universities currently offering graduate project management programs indicates several types of programs being offered: 1.

2. 3.

A masters level general degree program (such as an MBA) with a specialization in Project Management. A full masters level (generally MS) program in Project Management A “certification program” of several Project Management Courses

Some universities offer more than one of these program types. Also in some universities the program is offered in the School of Business (or Management) and in some schools the program is offered in the School of Engineering. In most universities, many of the courses appeared to be shared with other graduate degree programs; in other words not all the courses in the program are focused on project management. Once a PMP status is obtained, an individual must earn 60 Professional Development Units (PDUs) each three years. Some universities offer a PMP Exam Preparation course or cover exam prep material in one of their project management courses. However most graduate programs do not cover exam prep; in fact the graduate programs are more geared to providing the PDU credits for PMP’s. Figure 2 summarizes the program types for most of the U.S. universities offering project management programs “certified” by PMI. The list of such schools is on the PMI website (www.pmi. org). Out of the 19 schools listed, 11 offer a certifi-

The Role of Project Management in Technology Literacy

Figure 2. Institutions offering graduate credit programs in project management university

organize

Amberton KA American Graduate Univ. KA Boston University KA City University KA Colorado Technical University Step George Washington University Step Int'l School of Info. Mgmt. Step Keller School of Management KA Northwestern Step Regis University PG Stevens Inst. Of Technology Step U. of Management & Tech. KA U. of Wisconsin - Madison KA U. of Wisconsin - Platteville Step University of Central Florida Step University of Maryland Step + K A University of Texas - Dallas Step Western Carolina University PG Wright State University Step

school

certificate Program MbA/Ms specialization PM Masters degree # courses # PM # courses # PM # courses # PM

Business Business Business Business Both Business Business Business Engineering Business Business Both Business Business Engineering Engineering Business Business Business

cate program, 6 offer an MBA/MS specialization, and 8 off a full Masters is Project Management. In 14 of the 19 schools, the program is entirely in the Business (or Management) school.

ProJect MAnAgeMent LIterAcy orgAnIZAtIon Since so many resources have been put into the development and refinement of the PMBOK and it has been so well received by the project management community, it seems prudent to organize university program courses around the processes defined within PMBOK. The issue then becomes how does one “slice and dice” the processes as shown in Figure 1 into distinct (but integrated) courses. The PMBOK document itself organizes its write-up by Knowledge Area. However, most classic overall project management books and textbooks are organized by process groups (Badiru,

4

4

8 6 6

8 6 6

3 6

3 4

4 7 6

4 7 6

5

1

6

1

13

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12

4

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10

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12

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1988; Cleland, 1988; Hajek, 1984; Kerzner, 1980; Meredith, 1989; Royce, 1998; Verzuh, 1999). There are however a number of books concerning particular parts of project management and these cover particular Knowledge Areas, but they are not specifically written as “textbooks” (Fisher, 2000; Fleming, 2000; Pinto, 1999; Schuyer, 2001; Verma, 1996). Looking at the universities currently offering degree programs to see how their curricula were organized, we defined three general types of organization: 1.

2.

“Step” Courses are organized in the traditional manner from less depth to more depth over most of the knowledge areas. For example the first course might be “Introduction to Project Management”; the next might be “Intermediate Project Management”; and the next would be “Advanced Project Management”. “KA” Follows the PMBOK knowledge areas (Scope, Time, Cost, …)

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The Role of Project Management in Technology Literacy

3.

“PG” Follows the PMBOK process groups (Initiation, Planning, …)

Most programs do not fit entirely into one of these molds, but they were categorized according to the best fit. Overall out of the 19 schools, 10 use primarily the Step method, 6 use primarily the KA method, and two use the PG area. For schools offering certification, 5 use the Step method, 6 use the KA method, and none use the PG method. For schools offering the MBA/MS specialization, none use the KA method, one uses the PG method, and the rest use the Step method. For schools offering the full MS in Project Management, 2 use KA’s, one uses PG’s, and the rest (5) use the Step method.

ProJect MAnAgeMent content And deLIvery In ProgrAMs As can be seen from Figure 2, not all of the courses in a project management program are project management specific courses. For most schools, the certification offering is made up of mostly project management specific courses (the #PM in Figure 1 is the number of project management specific courses). For the project management specialization, most schools use three to six project management specific courses. For the full MS project management degree, the number of project management specific courses is about one-third to one-half of the courses. These nonspecific courses in the full MS degree program vary widely from school to school especially if the degree is in the engineering school instead of the business school. Some of these non project management specific courses are typically: general management, organizational behavior, leadership, managerial accounting, information technology, finance, human resources, quantitative methods, quality assurance, procurement and contracting, and risk management.

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Some universities are offering some, all, or portions of their courses in the form of “distance learning”. So the issue becomes where on the spectrum from “bricks to clicks” should a program position itself. There are many pro’s and con’s on both sides of this issue, and most of those pro’s and con’s depend on exactly how a course is made available “on-line” and the university’s overall vision, mission, and tradition. This issue encompasses most degree programs (not just project management), so we are not going to further debate it here, except to indicate it is highly dependent on a particular school’s mission, tradition, and demographics. As discussed below, the potential students for such a graduate program are working adults, so attention has to be given to the best delivery for that market. Many schools are holding classes on weekends or evenings to accommodate the adult audiences for these types of programs (San Diego Business Journal, 2001).

Future trends The university programs surveyed above were all relatively new programs, so there is little or no data available for a statistical or comparative historical analysis at this time. In the future, one may be able to survey graduates from the different types of programs to determine the pros and cons of each type of technology organization based on surveys of graduates or performance metrics tied to graduates of the different programs. The issue of course material organization is a difficult one for a learning environment. As discussed above, universities offering these programs are taking different approaches in this area. The “Step” approach is most appropriate for programs that have only 2 or 3 project specific courses. The “KA” approach requires much more “course preparation” time, textbooks are limited, and instructors need depth in these skills. One possible

The Role of Project Management in Technology Literacy

curriculum design would be to use a combination of “PG” and “KA”. For “PG”, separation into two process “super-groups” may be appropriate: project planning and project control; both covering scope, time, and cost. Separate “KA” courses would likely involve: Procurement, Risk, Quality, and Human Resources & Communications.

concLusIon For a comprehensive project management literacy learning program, we have identified four dimensions to such literacy. The PMI PMBOK focuses on the dimension of breadth of the Knowledge Area’s (and the 37 processes) but intentionally does not go into much depth. Going into depth gets into method and tool specifics. Thus the first two dimensions likely needed in a technology learning program beyond the PMP Certification are both the breadth and depth of these 37 processes. The third dimension identified is industry particulars. While there is much commonality to project management in all industries, there is also much that is specific to each area. For example task estimation for an IT project is much different than task estimation in a construction project. So this would be another added dimension to a program, certainly not for all industries but for the major ones of concern in a school’s region. The fourth dimension we identified was that of time or “currency”. This not only includes the use of current tools, but the practice of project management in the current business and technical environment. Textbooks addressing parts of this fourth dimension are just starting to become available. (Klastorin, 2004) Issues such as “virtual teams”, international coverage, and web based systems are included in this dimension.

reFerences Badiru, A. B. (1989). Project Management in Manufacturing and High Technical Operations, Wiley Interscience Boyatzis, R. (1982). The Competent Manager: A Model for Effective Performance, Wiley Brandon, Daniel. (2003). “Developing a Graduate Program in Project Management”, Chapter in Technologies & Methodologies for Evaluating Information Technology in Business, IDEA Group Publishing Cale, E. G., Curley JR and Curley K. F. (1987). “Measuring Implementation Outcome”. Information and Management 3(1): pp. 245-253. Cafasso, R. (1994). “Few IS Projects Come in on Time, on Budget”, Computerworld 28(50): p.20. Caupin, G., Knopfel, H., Morris, P. (1998). ICB IPMA Competence Baseline, Zurich: International Project Management Association Chronicles of Higher Education. (2001, August 10). 47(48), p A45. Cleland, D. I. And King, W.R. (1988).Project Management Handbook, Van Nostrand Reinhold Cook, D. L. (2002). Certification of Project Managers – Fantasy or Reality, Project Management Quarterly, 8(2), 32 - 34 Duncan, William. (1996). A Guide to the Project Management Body of Knowledge, Project Management Institute Field, T. (1997).“When Bad Things Happen to Good Projects”, CIO 11(2): pp.54-62 Fisher, K. and Fisher, M. (2000). The Distance Manager: A Hands On Guide to Managing OffSite and Virtual Teams, McGrW-Hill

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Fleming, Q. and Koppelman, J. (2000). Earned Value Project Management, PMI Foti, R., (2001). The Case for Certification, PM Network, September Hajek, V.G. (1984). Management of Engineering Projects, McGraw Hill Hildebrand, C. (1998). “If at First You Don’t Succeed”, CIO Enterprise Section 2 (4/15) Kerzner, H. (1980). Project Management. A Systems Approach to Planning, Scheduling, and Controlling, Van Nostrand Klastorin, T. (2004). Project Management: Tools and Trade-Offs, Wiley Meredith, S.R. and Mantel, S.J. (1989). Project Management, A Management Approach, John Wiley and Sons. Morris, P. (2001, September). Updating the Project Management Bodies of Knowledge, Project Management Journal. Pinto, J. and Trailer, J. (1999). Essentials of Project Control, PMI

PMI. (2002) .Government Extension to the Project Management Body of Knowledge, Project Management Institute PMI. (2003). Construction Extension to the Project Management Body of Knowledge, Project Management Institute PMI. (2002). Project Management Institute Practice Standard for Work Breakdown Structures, Project Management Institute Royce, Walker. (1988). Software Project Management, Addison-Wesley, 1998 San Diego Business Journal (6 August 2001). 22(32), 23. Schuyler, J., (2001). Risk and Decision Analysis in Projects, PMI Schwalbe, Kathy. (2001). Information Technology Project Management, Course Technology Verma, V. and Thamhain, H. (1996). Human Resource Skills for the Project Manager, PMI Verzuh, Eric. (1999). Fast Forward MBA in Project Management, John Wiley & Sons

PMI. (2000). A Guide to the Project Management Body of Knowledge, Project Management Institute

This work was previously published in Technology Literacy Applications in Learning Environments, edited by D.D. Carbonara, pp. 299-306, copyright 2005 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.20

It Was Hard Work, but It Was Worth It:

ePortfolios in Teacher Education Andrea Bartlett, University of Hawaii at Manoa, USA

Abstract

INTRODUCTION

Student ePortfolios offer both advantages and challenges for teacher educators. The purpose of this case study is to identify benefits that make the effort worthwhile. Two groups of preservice teachers—one undergraduate and one graduate—created complex ePortfolios under the direction of a non-technology faculty member. Faculty observations and student evaluations revealed ePortfolios enhance students’ educational technology learning, reflection, and collaboration. The author concludes creating ePortfolios was “worth it,” and she provides recommendations for making ePortfolios even more valuable for preservice teachers, their programs, and the schools in which they will someday teach.

Portfolio proponents assert that engaging in portfolio development is linked to self-reflection and the possibility of improved practice; however, few researchers have examined what that involvement has meant for pre-service teachers. (Delandshire & Arens, 2003, p. 58) In contrast to many other professions, portfolios have been used to assess teaching for only the past 25 years, and electronic portfolios are an even more recent development. Teaching portfolios have been found to provide many benefits, including: (a) a richer, more contextualized view of teaching than standardized tests (Shulman, 1998); (b) enhanced reflection by teachers

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

It Was Hard Work, But It Was Worth It

on their own (McLaughlin & Vogt, 1996; Valli & Rennert-Ariev, 2002) and students’ learning (Fetter, 2003); (c) experience collaborating with peers (Wolf, Whinery, & Hagerty, 1995); and (d) a record of accomplishments for job searches and certification (e.g., Interstate New Teacher Assessment and Support Consortium, National Board of Professional Teaching Standards). Portfolio assessment also contributes to the professionalization of teaching by giving teachers responsibility for their own evaluation (Lyons, 1998a). The use of multimedia to create ePortfolios provides additional benefits beyond those of traditional paper-based portfolios, such as linking artifacts to teaching standards. This interconnectivity is likely to result in teachers’ greater understanding of themselves and the standards, when compared to paper-based portfolios (Norton-Meier, 2003). ePortfolios are also easier to update, store, and share than traditional portfolios. Another important benefit is that pre-service teachers who create ePortfolios learn about technology (Bartlett, 2002). Since ePortfolios may span the teacher education program, they provide an effective vehicle for integrating technology into the teacher education program (Bartlett, 2002) and make it more likely pre-service teachers will implement technology in their classrooms (Goldsby & Fazal, 2000; McKinney, 1998). While there are substantial advantages, portfolios also present challenges for educators and institutions. Teacher educators who use ePortfolios, in particular, face many hurdles allocating the time, resources, and support necessary to complete a technology-oriented project (e.g., McKinney, 1998; Milman, 1999). Other potential pitfalls include failing to communicate evolving guidelines (Lamson, Thomas, Aldrich, & King, 2001) and focusing on the “bells and whistles” of technology rather than creators’ goals (Lieberman & Rueter, 1997). This chapter is a case study encompassing four years of successful ePortfolio implementation by

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a teacher educator who began the project with limited technology skills. Two groups of preservice teachers—undergraduate and masters’ students—created complex, standards-based, multimedia portfolios during their two-year programs. Students’ perceptions, collected during teacher education and after four months of full-time teaching, are also reported. Zeichner and Wray (2001) explained the value of such case studies: “It makes little sense to talk about the consequences of using teaching portfolios in general, without an understanding of the particular conditions under which they are constructed and the purposes toward which they are directed” (p. 619). Therefore, the purposes of the chapter are to explain the particular conditions and purposes under which our ePortfolios were created, and to determine whether the implementation was worthwhile through a critical evaluation of successes, problems encountered, and recommended solutions.

bAcKground As a faculty member in Curriculum Studies, rather than technology, I began exploring ePortfolios shortly after receiving tenure. One of my professional roles was coordinator for groups of approximately 25 students as they progressed through their two-year teacher education programs. ePortfolios caught my interest because they appeared to offer the benefits of traditional portfolios, plus the advantages afforded by technology. After reviewing the literature on portfolios, I decided to go forward, even though I had little idea of what ePortfolios looked like or how I would accomplish my goal. I hoped ePortfolios would benefit my teacher education students, serve as effective performance assessment, and become my new research agenda. Since I had limited technology skills, the technical support

It Was Hard Work, But It Was Worth It

offered by a Preparing Tomorrow’s Teachers to Use Technology (PT3) Grant in the college gave me the courage to pursue this new interest. My first experience with ePortfolios was when I created a sample, based on a student’s traditional portfolio and videotaped lessons, with the help of a technology assistant. As I edited the videotape into a two-minute teaching clip that would encapsulate this student’s strengths as a teacher, I could see the potential for reflection this process offered, and I determined to implement ePortfolios with my next group of pre-service teachers.

undergraduate Pre-service teacher education cohort The ePortfolio sample became the template for a group of 23 undergraduate elementary education majors who developed portfolios over their two-year program, 2000-2002. This portfolio followed Bullock and Hawk’s (2001) concept of teaching portfolios: ... a teaching portfolio often contains gathered samples of lessons, units of study, and professional documents that reflect the knowledge, skills, and beliefs of the teacher ... The teacher reflects on each piece of work, highlighting strengths, weaknesses, and changes he or she would make in teaching. The teacher’s portfolio is used for self-evaluation or external review. (p. 13) Furthermore, media were used to put these portfolios into electronic form as defined by Constantino and De Lorenzo (2002): Unlike the paper-based portfolio, the electronic portfolio is a multimedia approach that allows the teacher to present teaching, learning and reflective artifacts in a variety of formats (audio, video, graphics, and text). (p. 48) The portfolios consisted of: welcome page, résumé, teaching philosophy, self-evaluation based on state teacher standards, and instructional unit(s). Instructional units included lesson plans

with reflections, two to three minutes of teaching video, still photos, and scanned student work samples. The undergraduates used PowerPoint to create their portfolios, which were burned onto CDs and labeled with the college logo. At the outset of the program, few of the preservice teachers were familiar with the technology that would be needed to create their portfolios. Since “comprehensive training” has been recommended in the literature (Lamson et al., 2001, p. 13), I arranged for technology assistants, available through the PT3 grant, to provide 17 hours of technology workshops and 18 hours of assistance during class time. Students also had access to a well-equipped and staffed technology center. Despite this high level of support, some students reported they could have used more time, technology instruction, and specific guidelines to complete their portfolios. A colleague and I used a five-point holistic scoring guide to assess the final portfolios. All but one of the portfolios received a score of 3 or better, meaning they included all required elements in a way that met minimum guidelines. Students received specific comments about the reasons for their scores, focusing mainly on creativity, organization, and use of technology. Levels of reflection were not considered in the assessment, however, and this emphasis would have made feedback even more meaningful (Delandshire & Arens, 2003).

graduate-Level Pre-service cohort Although pleased with the overall success of our first ePortfolios, I was still far from satisfied. Therefore, I looked forward to a smoother process with my next cohort of 22 students preparing for elementary or secondary certification and a master’s degree. In contrast to the traditional teacher education sequence (with student teaching fourth semester), these pre-service teachers student-taught third semester and engaged in a supervised, paid internship fourth semester. This

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fourth semester internship allowed me to follow students into their first four months as full-time teachers. Since I had been through the process once, this time I had sample portfolios to show the new cohort. Based on recommendations from former students and the literature (Lamson et al., 2001), I provided a handout with rationale, descriptions of portfolio components, and a timeline for when, over the next three semesters, students would complete each component. We went over the handout at the beginning of each semester, and I referred to it regularly throughout the portfolio process. The structure of the portfolio was similar to the one the undergraduates had done. Since these students were in a graduate program, I added research activities and career goals to the previous components of welcome page, résumé, teaching philosophy, self-evaluation based on state teacher standards, and instructional unit(s) (see Figure 1 for welcome page template). To create Web-ready portfolios, we changed our software program from PowerPoint to DreamWeaver. Less technology assistance was available when the graduate-level students created their portfolios than when the undergraduates did theirs. One technology graduate student assisted this second group during the 42 hours of class time and 16 hours of open lab required to complete their portfolios, without benefit of the convenient technology center. Although I originally thought today’s students, who grew up with technology, would

Figure 1. ePortfolio welcome page template

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have little difficulty with DreamWeaver, many struggled. By the middle of third semester, some students had individualistic, creative ePortfolios; however, others had completed little. Knowing something had to be done, cohort faculty asked the technology assistant to develop a template. Once they had the template, struggling students took off and completed their portfolios with much less frustration. Other researchers (e.g., Lamson et al., 2001) have noted the value of templates in creating electronic portfolios, and our experience strongly supports this view. To improve the holistic assessment process used with the first cohort, I developed a rubric as recommended in the literature (Goldsby & Fazal, 2001). This rubric more clearly delineated expectations for each portfolio component, including reflection when appropriate. Students critiqued my draft of the rubric, and I incorporated their suggestions into the final form.

wAs creAtIng e-PortFoLIos “worth It”? In spite of the challenges encountered, there is evidence to support the assertion, “the experience was worth it.” This evidence involves both my evaluation of the project and students’ perceptions of some of the elements. Students’ perceptions were collected through two surveys after submitting their portfolios for evaluation. The first survey was a Likert-scale survey (1 – strongly disagree to 5 – strongly agree), based on Kirkpatrick’s Four Levels of Evaluation (1994): (a) attitudes, (b) learning, (c) on-the-job behavior, and (d) organizational impact. The second survey consisted of open-ended questions in which students described what they learned, the benefits, and future uses of their ePortfolios. This evidence will be used to evaluate ePortfolios for their usefulness in enhancing teaching as a career and for assessing student learning and program effectiveness. Findings of the current study will

It Was Hard Work, But It Was Worth It

be followed by a comprehensive list of ways to make portfolios even more valuable to students and faculty.

enhancing teaching as a career Teacher retention is a serious issue for schools today, and I am convinced teachers who renew their teaching expertise by using new teaching methods, engaging in ongoing inquiry about teaching, and assuming leadership positions are more likely to remain in the field. These dynamic, evolving, motivated teachers will create better learning environments for children, and contribute more fully to their schools, than teachers who do not engage in such growth-oriented activities. The following sections discuss evidence collected from students and my own observations concerning the impact of ePortfolios on pre-service teachers’ use of (a) technology as an innovative teaching strategy, (b) reflection to improve teaching, and (c) teacher leadership for school improvement.

technology expertise and Applications to teaching It is widely acknowledged that pre-service teachers (PSTs) need to learn about technology and how to apply it effectively in teaching contexts (Milken Exchange, 1999). PSTs who created portfolios in the present study indicated learning about technology was the main benefit of ePortfolios. These comments are typical: “The ePortfolio forces the student to keep up with the technological curve” and “ePortfolios keep you up with today’s technology.” These findings support an earlier study by Milman (1999) in which PSTs who completed an electronic portfolio course believed the course provided useful technology skills. While there was strong agreement among the PSTs that they learned about technology, applications to teaching were less clear. Students who wrote about classroom technology tended to qualify their comments, based on what they

knew about local schools: “The technological advantages are great. I can use what I learned to teach my students (if we have the resources) or to help the computer teachers” and “If everyone does it, I see a step towards the future and a new awesome way of teaching.” Although students agreed they were more likely to apply technology in their future employment after creating ePortfolios, the PSTs were less likely to anticipate having their own students create ePortfolios. Wilson, Wright, and Stallworth (2003) found this same lack of enthusiasm for implementing electronic portfolios among the secondary PSTs in their study. It is likely students’ attitudes would improve if technology were less of an obstacle, and they were given adequate support. The following semester, these students were full-time interns, responsible for children in local schools. After four months, the new teachers reported using technology in many ways with their students, and two interns actually implemented ePortfolios with their students. The interns did not necessarily credit ePortfolios for this usage, however. These findings, before and during full-time teaching, indicate a need for ongoing, implicit connections between technology used for ePortfolios and possible classroom applications. To be most effective, these connections would include specific application examples and ways to overcome the roadblocks that often stand in the way of educational technology advancement.

Reflection and Self-Evaluation Reflection is almost universally considered to be an important goal of teacher education (e.g., Lyons, 1998b). My observations indicate ePortfolios facilitate reflection and self-evaluation, and this was borne out by students’ responses to the two surveys. For example, one student wrote the following benefit of her ePortfolio: “Having to organize a portfolio meant I had to organize my thoughts. I found I was more reflective.”

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Another student saw reflection as a future use of her portfolio: “I will use it for reflecting on what I am discovering about myself as I continue to grow as a teacher.” Pre-service teacher reflection on the ability to adapt instruction for diverse learners is an area of particular importance in today’s schools. On the quantitative survey, pre-service teachers in the present study did agree their portfolios reflected their understandings of a wide range of learners. Thus, the portfolios addressed, to some extent, the test put forth by Zeichner and Wray (2001): If the reflection stimulated by teaching portfolios does not help challenge student teacher perspectives that help to maintain the gap between the poor and others in U.S. schooling, then its value is problematic. (p. 627) While the findings in the area of reflection were encouraging, reflection, like other aspects of teaching, can always be (and should be) improved. Most student reflections were perfunctory analyses of what went well, and I should have led them to consider deeper questions about “ ... the students, the curriculum, the institutional setting, and the larger social role of schools ... ” (Liston & Zeichner, 1990, p. 240). Assessment rubrics provide further opportunities for enhancing reflection. With the second cohort, I presented a draft rubric to students for their comments, and incorporated their suggestions in the final instrument. Looking back, I see it would have been better to start with students’ ideas, instead of my own, and then have students include self-evaluations based on the rubric in their portfolios. Increasing student involvement would have made the process more “student/owner-centric” (E-Portfolio Consortium, 2003, p. 11), and more in keeping with feminist, as opposed to interpretivistic, assessment approaches (Shapiro, 1992, cited in Johnston, 2004).

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collaboration and teacher Leadership for school Improvement A teaching career currently requires collaboration with other teachers, administrators, students, and parents. Responses to the quantitative instrument indicated students were slightly positive about whether the process of creating ePortfolios was collaborative, and slightly negative about whether they had sufficient opportunity to view peers’ portfolios. Students were even less satisfied with the amount of faculty feedback than with the amount of feedback they received from peers. These findings indicate students would benefit from appreciably more peer and faculty review. The goal would be to create a “portfolio culture” by “developing a kind of learning environment of intense expectations, care and richness” (Wolf, 1998, p. 41). According to Lyons (1998a), “Validation and understanding emerge through portfolio conversations with peers and mentors, the presentation of portfolio evidence, and the recognition of the new knowledge and practice generated through the process” (p. 5). In another area related to school improvement, I had hoped my students would come to picture themselves as advocates for electronic portfolios when they became teachers. In actuality, few PSTs planned to advocate for electronic portfolios for either student or teacher assessment at their schools. This finding led me to consider how ePortfolios could be used as a focus for discussions about teacher leadership. Students should be encouraged to articulate what they believe the benefits and/or disadvantages of portfolios are, and practice presenting their ideas to small groups of peers. More attention should also be paid to school culture and how such cultures can be changed.

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Assessments of student Learning Delandshire and Arens (2003) found teacher educators and students had different goals for a teaching portfolio. Students considered a portfolio as “an exhibit of their personal development (showing growth and who they are as teachers) and as a useful tool for seeking employment” (p. 61), and instructors were more likely to emphasize performance-based assessment. These goals will be examined in the next sections.

Showcase for Job Searches Results of the current study indicate students saw multiple purposes for their ePortfolios, with job searches being most prevalent. One student wrote, “After this class is over, I would like to keep adding to this ePortfolio. I would add units from my other education classes and hopefully use the portfolio after our program to assist me in finding a job.” A second student stated, “I hope to show it off as I go for my interviews,” while a third reported, “It impressed my interviewers with my willingness to use technology.” Pre-service teachers’ focus on the usefulness of the portfolio as a job tool is understandable, since most were scheduling job interviews as they finished their portfolios, and other researchers (Meyer & Tusin, 1999; Wilson et al., 2003) have reached similar conclusions. In our case, students emphasized job searches even though handouts listed multiple benefits. Our experience points to a need for ongoing conversations about the uses and purposes of portfolios.

Standards-Based Performance Assessment Students typically complete a range of assignments as they progress through the foundations courses, methods courses, and field experiences that make up most teacher education programs.

However, these assignments are likely to be discarded, along with faculty comments, unless a portfolio is required. A major strength of portfolio assessment, then, is the potential for formative assessment, or the ability to monitor growth over the entire teacher education program. A critical evaluation of our ePortfolios led me to conclude they function mainly as a summative assessment, and not a formative assessment to the degree I had hoped. The key components—philosophy, teaching unit, and self-evaluation—concentrate on field experiences, and the portfolio could have been expanded to include other parts of the teacher education program. Furthermore, the time spent on the technology of putting the portfolio together meant portfolios remained sketchy until the end of the student teaching semester. While portfolios provided an overall idea of how students were progressing during the program, other assessments were more important in that regard. The formative assessment value of the portfolio was also affected by the use of performance standards, in our case state teaching standards. The value of standards in teacher education has been a source of some debate. Delandshire and Arens (2003) pointed out teaching standards may lead to fragmented assessments of teaching and serve as substitutes for theory. In our case, students often commented about the overlap among the standards. For portfolios organized around teaching standards, an overall evaluation that connects to teaching philosophy would make portfolios more meaningful. In this way, standards would function as a “guide to thinking about teaching and learning” (Diez & Blackwell, 1999, p. 359), thereby avoiding some of the pitfalls of standards-based assessment. Ongoing critique of the standards (Darling-Hammond et al., 1998), as they relate to each period in teacher development, would further enhance the portfolio process.

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Comprehensive Program Evaluation ePortfolios have much potential as a means for comprehensive program evaluation. Given the time and technology expertise necessary to complete this type of individualistic ePortfolio, it is unlikely our college would ever receive faculty support for this initiative. An easier, more convenient way to store evidence would need to be found before ePortfolios could be used to assess program effectiveness. Once these issues are worked out, faculty would be able to use portfolios to determine which aspects of the teacher education program are working and which need to be changed. For example, Snyder, Lippincott, and Bower (1998) found some courses receiving poor student evaluations were mentioned often in portfolios, leading faculty to gain new appreciation for these courses. In addition to program evaluation, ePortfolios could be used to document teacher education programs’ effectiveness when seeking accreditation. In our case, ePortfolios played only a small role in our last National Council for the Accreditation of Teacher Education evaluation, since they were just one of the many types of assessment exhibited. To be used for accreditation purposes, some teacher education programs are standardizing student portfolios. Allington (2005) pointed out the contradictions: “Our students are pressed to develop standardized ePortfolios (seems oxymoronic to me)” (p. 199). The challenge is to make portfolios that can be used for accreditation purposes, while allowing them to be individualized enough for students to maintain ownership. Ultimately, student ePortfolios would become part of a teacher education Web portfolio for accreditation purposes (Banta, 2003). Our college is currently moving toward a program-wide evaluation of this type. A university-wide system would further support this program initiative, and some universities currently provide software and servers for student portfolios (e.g., Yost, Brzycki, &

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Onyett, 2002). This overall structure would help faculty maintain, update, and share information, including portfolio files.

Future trends Based on our experiences and the literature, I believe ePortfolios of the future should include the following elements:

technology 1.

2.

3.

4.

Students take an educational technology course, or show they have the needed skills for making a portfolio, before beginning the portfolio process. Hardware and software is easy to learn and use. In teacher education, technology with clear applications to classroom teaching is best. Students have convenient access to computers and software. (In our college, incoming teacher education students will soon be required to have laptops with certain specifications and necessary software.) Students and faculty have convenient access to technology support. For example, educators in our state are discussing plans to collaborate on a 24/7 technology help line.

Reflection 1.

2. 3.

Reflections go beyond “How did I do?” to look at larger issues of schools and schooling. Reflection is emphasized through ongoing conversations and evaluations. Students use educational literature, such as action research and conceptual articles, to deepen their understandings of classroom experiences (Snyder et al., 1998).

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collaboration

Program evaluation

1.

1.

2.

3. 4.

5.

6.

There are frequent opportunities for peer sharing, faculty review, and input. Students contribute to the evaluation rubric, and use it to assess their own and peers’ portfolios. There are periodic portfolio presentations to peers, faculty, and others. Students present their portfolios in a dissertation-style defense to the whole class or a portfolio review committee. Mentor teachers and other members of the school community participate in the review process. There is a mechanism for sharing with those in and outside the college (some commercial ePortfolio programs now have this feature).

Job searches 1. 2.

Faculty stress multiple purposes of ePortfolios throughout the process. Students use their portfolios to role play job interviews (Georgi & Crowe, 1998).

standards-based Performance Assessment 1.

2.

3.

Portfolios are organized by state teaching standards, but with connections and continuous critique of standards. Working files are set up as a learning portfolio, with bins for each standard. Students review their portfolios often and select samples for each semester to show growth. Students write strong philosophy statements, based on theory, which link to all other aspects of the portfolio.

2.

Students provide feedback on the process and how it could be improved. Student ePortfolios become part of a Webbased institutional portfolio for evaluation and accreditation purposes.

concLusIon ePortfolios have much promise for improving learning and assessment in teacher education and in the schools in which our students will teach. For this promise to be fully realized, new technology will be needed that is simpler and less cumbersome. As Willis (2001) concluded, “Technology should be in the background; it can never be The Focus” (p. 4). This new technology would facilitate reflection and sharing, rather than detract from it, and move us toward a more ideal teaching portfolio that is: ... a structured collection of teacher and student work created across diverse contexts over time, framed by reflection and enriched through collaboration, that has as its ultimate aim the advancement of teacher and student learning. (Wolf & Dietz, 1998, p. 13) Putting technology in the background would allow faculty to put the emphasis back on theory, reflection, and collaboration—the way teacher education was meant to be. Overall, I agree with the student who wrote, “Making an ePortfolio was hard work, but it was worth it.” Although not for the faint of heart or risk-adverse faculty member, I encourage other teacher educators to try ePortfolios for the combined advantages that cannot be achieved in the same totality by any other means.

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AcKnowLedgMent The author would like to thank the Lei Aloha Preparing Teachers to Teach with Technology Grant staff for their support with this project. (For a video and student sample from the first cohort’s ePortfolio project, please see http://etec. hawaii.edu/oldsite/vr/videos/the_record/feature. htm-teachsource.)

reFerences Allington, R. L. (2005). Ignoring the policy makers to improve teacher preparation. Journal of Teacher Education, 56(3), 199-204. Banta, T. W. (2003). Electronic portfolios for accreditation? Assessment Update, 15(4), 3-4. Bartlett, A. (2002). Preparing pre-service teachers to implement performance assessment and technology through electronic portfolios. Action in Teacher Education, 24, 90-97. Bullock, A. A., & Hawk, P. P. (2001). Developing a teaching portfolio: A guide for pre-service and practicing teachers. Upper Saddle River, NJ: Merrill Prentice-Hall. Constantino, P. M., & De Lorenzo, M. N. (2002). Developing a professional teaching portfolio. Boston: Allyn and Bacon. Darling-Hammond, L., Diez, M. E., Moss, P., Pecheone, R. M., Pullin, D., Schafer, W. D., et al. (1998). The role of standards and assessment: A dialogue. In M. E. Diez (Ed.), Changing the practice of teacher education: Standards and assessment as a lever for change. (ERIC Document Reproduction Service No. ED417157.) Delandshire, G., & Arens, S. A. (2003). Examining the quality of the evidence in pre-service teacher portfolios. Journal of Teacher Education, 54, 57-73.

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Diez, M. E., & Blackwell, P. (1999). Improving master’s education for practicing teachers: The impact of the National Board for Professional Teaching Standards. Teaching and Change, 6(4), 350-363. E-Portfolio Consortium. (2003). Electronic portfolio whitepaper, version 1.0. Retrieved May 21, 2005, from http://eportconsortium.org Fetter, W. R. (2003). A conceptual model for integrating field experiences, professional development schools, and performance assessment in a world of NCATE 2000. (ERIC Document Reproduction Service No. ED472396) Georgi, D., & Crowe, J. (1998). Digital portfolios: A confluence of portfolio assessment and technology. Teacher Education Quarterly, 25(1), 73-84. Goldsby, D., & Fazal, M. (2000). Technology’s answer to portfolios for teachers. Kappa Delta Pi Record, 36(3), 121-123. Goldsby, D., & Fazal, M. (2001). Now that your students have created Web-based digital portfolios, how do you evaluate them? Journal of Technology and Teacher Education, 9(4), 607-616. Johnston, B. (2004). Summative assessment of portfolios: An examination of different approaches to agreement over outcomes. Studies in Higher Education, 29(3), 395-413. Kirkpatrick, D. (1994). Evaluating training programs: The four levels. San Francisco: BerrrettKoehler. Lamson, S., Thomas, K. R., Aldrich, J., & King, A. (2001). Assessing pre-service candidates’ Webbased electronic portfolios. (ERIC Document Reproduction Service No. ED458202) Lieberman, D. A., & Rueter, J. (1997). The electronically augmented teaching portfolio. In P. Seldin (Ed.), The teaching portfolio: A practical guide to improved performance and promo-

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tion/tenure decisions (2n d ed., pp. 47-57). Bolton, MA: Anker.

teacher education. Journal of Adolescent & Adult Literacy, 46(6), 516-518.

Liston, D. P., & Zeichner, K. M. (1990). Reflective teaching and action research in pre-service teacher education. Journal of Education for Teaching, 16(3), 235-254.

Shapiro, J. P. (1992). What is feminist assessment? In C.M. Musil (Ed.), Students at the centre: Feminist assessment. Washington, DC: Association of American Colleges.

Lyons, N. (1998a). Portfolio possibilities: Validating a new teacher professionalism. In N. Lyons (Ed.), With portfolios in hand: Validating the new teacher professionalism (pp. 11-22). New York: Teachers College Press.

Shulman, L. (1998). Teacher portfolios: A theoretical activity. In N. Lyons. (Ed.), With portfolio in hand: Validating the new teacher professionalism (pp. 23-38). New York: Teachers College Press.

Lyons, N. (1998b). Reflection in teaching: Can it be developmental? A portfolio perspective. Teacher Education Quarterly, 25, 115-127.

Snyder, J., Lippincott, A., & Bower, D. (1998). The inherent tensions in the multiple uses of portfolios in teacher education. Teacher Education Quarterly, 25, 45-60.

McKinney, M. (1998). Pre-service teachers’ electronic portfolios: Integrating technology, self-assessment, and reflection, Teacher Education Quarterly, 25, 85-103.

Valli, L., & Rennert-Ariev, P. (2002). New standards and assessments? Curriculum transformation in teacher education. Journal of Curriculum Studies, 2, 201-225.

McLaughlin, M., & Vogt, M. (1996). Portfolios in teacher education. Newark, DE: International Reading Association.

Willis, J. (2001). Foundational assumptions for information technology and teacher education. Contemporary Issues in Technology and Teacher Education, 1(3).

Meyer, D. K., & Tusin, L. F. (1999). Pre-service teachers’ perceptions of portfolios: Process versus product. Journal of Teacher Education, 50(2), 131-139. Milken Exchange on Education Technology. (1999). Will new teachers be prepared to teach in a digital age? A national survey on information technology in teacher education. Santa Monica, CA: Author. (ERIC Document Reproduction Service No. ED428072) Milman, N. B. (1999). Web-based electronic teaching portfolios for pre-service teachers. Proceedings of the International Meeting of the Society for Information Technology and Teacher Education, San Antonio, TX. (ERIC Document Reproduction Service ED 432273) Norton-Meier, L. A. (2003). To e-foliate or not to e-foliate? The rise of the electronic portfolio in

Wilson, E. K., Wright, V.H., & Stallworth, B. J. (2003). Secondary pre-service teachers’ development of electronic portfolios: An examination of perceptions. Journal of Technology and Teacher Education, 11(4), 515-528. Wolf, D. (1998). Creating a portfolio culture. In N. Lyons (Ed.), With portfolio in hand: Validating the new teacher professionalism (pp. 41-50). New York: Teachers College Press. Wolf, K., & Dietz, M. (1998). Teaching portfolios: Purposes and possibilities. Teacher Education Quarterly, 25, 9-22. Wolf, K., Whinery, B., & Hagerty, P. (1995). Teaching portfolios and portfolio conversations for teacher educators and teachers. Action in Teacher Education, 17, 30-39.

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Yost, N., Brzycki, D., & Onyett, L.C. (2002). Electronic portfolios on a grand scale. Proceedings of the Annual Meeting of the Society for Information Technology and Teacher Education (pp. 594-579). Nashville, TN. Retrieved May 28, 2005, from http://dl.aace.org/10835 Zeichner, K., & Wray, S. (2001). The teaching portfolio in U.S. teacher education programs: What we know and what we need to know. Teaching and Teacher Education, 17(5), 613-621.

Key terMs The following definitions were retrieved from the Education Resources Information Center, Thesaurus of ERIC Descriptors, http://www. eric.ed.gov/. Accreditation: Formal or informal assessment of an institution from without, often for accreditation purposes. Assessment: Data collection and interpretation concerning attainment of educational objectives (nationwide, statewide, or locally) for use in educational planning, development, policy formation, and resource allocation. Case Study: Detailed analysis, usually focusing on a particular problem of an individual, group, or organization.

Certification: Statement attesting recipient has abilities, aptitudes, achievements, or other personal characteristics that suit an individual to particular positions or tasks. Educational Technology: Systematic identification, development, organization, or utilization of educational resources and/or the management of these processes—occasionally used in a more limited sense to describe the use of equipment-oriented techniques or audiovisual aids in educational settings. Related term: classroom technology. Educational Technology Integration: Process of making technological tools and services, such as computer systems and the Internet, a part of the educational environment—includes changes made to the curriculum as well as to educational facilities. Faculty: Academic staff members engaged in instruction, research, administration, or related educational activities in a school, college, or university. Rubrics: Evaluation tools, usually grids, that list the criteria for a task or performance, and articulate gradations of quality for each criterion. Teacher Education: Programs of academic study that prepare students to enter or advance in the education field.

This work was previously published in the Handbook of Research on ePortfolios, edited by A. Jafari, pp. 327-339, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.21

Supporting and Facilitating Academic Integrity in Distance Education Through Student Services: Brian F. Fox Santa Fe Community College, USA

AbstrAct This chapter briefly describes the growing concern over a lack of academic integrity in higher education and the traditional methods employed to detect and prevent it. Arguing that these possess inherent shortcomings, the author describes a systems approach that incorporates all aspects of student services: admissions, marketing, and orientation; instructional support; instructional technology; library services; and counseling and advocacy. For academic integrity policies and programs to truly be effective, they must be universal and preventative in scope and include all segments of student services and the student body itself. Regular assessment must be conducted and the topic incorporated into professional development. The primary goal for educational institutions

should be to foster and support the development of academic integrity in their students.

deFInIng the ProbLeM The concern over a lack of academic integrity in education is certainly on the rise in recent years, with an increasing number of articles, papers, and presentations describing the results of surveys on academic integrity or the actions of colleges and universities against suspected cheaters. With regard to distance education (DE), regional accreditation groups are clearly requiring that institutions take steps to ensure the integrity of student work and the credibility of degrees and credits awarded (Commission on Colleges and Schools, 2000). At the same time, a

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Supporting and Facilitating Academic Integrity in Distance Education Through Student Services

growing number of organizations and institutions are actively pursing violations of copyright and intellectual property laws. Although it is certainly impossible to determine the true extent of academic dishonesty, some statistics and examples provide both illustrations and indications. For example, in 2002, 47 students at Simon Frasier University turned in nearly identical economics papers (Hamlin & Ryan, 2003). The Center for Academic Integrity (CAI) at Duke University conducted a 1999 survey of 2,100 students on 21 campuses across the country, with about one-third admitting to serious test cheating, and half admitting to one or more instances of serious cheating on written assignments (Hamlin & Ryan, 2003). In a survey of 4,500 students at 25 high schools, over half admitted to having engaged in some level of plagiarism on written assignments using the Internet (Mayfield, 2001). Research by CAI members and others concluded that “student cheating is on the rise and that pressures and opportunities for dishonest behavior are increasing in many academic and professional contexts” (CAI, 1999, p. 4). With regard to student populations, Dr. Diane Waryold, executive director for the CAI, stated that certain trends may be found in academic dishonesty: top students competing for spots in grad school; students with lower GPAs (survival); students who value grades over learning and honesty; females and males, though males tend to self-report more cheating; members of Greek organizations; business and engineering majors; younger students; and all cultural backgrounds. Waryold offers the following rule of thumb: 20% will never cheat, 20% will cheat whenever possible, and 60% are open to influence (Waryold, 2002). Although further research is certainly needed in terms of understanding the demographics of cheaters, the question remains as to how this data might be used in constructive ways. Though the rise and development of the World Wide Web clearly cannot be blamed for a lack of academic integrity on the part of some students,

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it has certainly provided new opportunities for cheating, where the “age-old concerns about ethical practices in assessment ... take on new twists in the distance-learning environment” (Abbott, Siskivic, Nogues, & Williams, 2000). McMurtry (2001) described several methods, including copying and pasting text directly from articles, sharing assignments through e-mail attachments, and simply purchasing and downloading papers through sites such as EssayWorld.com, Planet Papers, Evil House of Cheat, Other People’s Papers, and School Sucks, all of which offer thousands of papers on a wide diversity of topics. Hinman (2000) states that there are three possible approaches to minimizing online cheating and plagiarism: virtue (developing students who do not want to cheat), prevention (eliminating or reducing opportunities and reducing the pressure to cheat), and policing (catching and punishing cheaters). While some educators advocate an aggressive program of detection and punishment as the most effective method to deal with academic dishonesty, it may be argued that a primarily “downstream” approach lacks learner-centeredness and institution-wide coordination and will inevitably fail as a result. Therefore, in order to more effectively address these issues, this paper will argue for a systems approach to student services in order to better support and facilitate academic integrity.

Academic Integrity, student services, and the systems Approach Rumble (2000) argued that distance educators have generally been better at articulating what they mean by student services than traditional educators, and he adds that a systems approach to DE is embedded in the literature and that it is part of the culture of DE that includes student support. Lyons (1990) reminded us that student services exist to serve the institution’s mission and objectives, and that this will determine to a large degree where resources are focused. As a result,

Supporting and Facilitating Academic Integrity in Distance Education Through Student Services

it is absolutely critical that academic integrity be one of the guiding principles and objectives of the institution, embedded within all aspects of the college or university. Brindley (1995) further added that “any interventions which are made should be consistent with the unique context in which they are offered, reflecting institutional values and objectives,” leading inevitably to the conclusion that there is no one right method to supporting and facilitating academic integrity for all institutions (Tait, 1995). Bearing these guidelines in mind, the CAI (1999) stated that all institutions should have “clear academic integrity statements, policies, and procedures that are consistently implemented” (p. 10). Because all campus constituencies have a role in supporting and facilitating academic integrity (CAI, 1999), it is imperative that the institution’s honor codes, conduct codes, and administrative policies and procedures dealing with academic integrity be developed through collaboration on the part of administrators, faculty, staff, and students, all of whom must “buy in” to them if success is to be achieved. Additionally, community input should be solicited to support the development and implementation of the program in order to increase its chances for success; for example, statements from local business leaders condemning academic dishonesty might lend support to institutional policies and statements (these might be gained through business advisory committees, marketing campaigns, etc.), while cooperation with local K-12 schools could serve to better prepare students for higher education.

student services Activities and their roles in Academic Integrity The term student services has been defined in various ways throughout open and DE literature. This chapter will broadly define these functions, drawing primarily upon Brindley’s (1995), Simpson’s (2000), and Tait’s (1995) definitions in order to

outline the roles various systems might play in supporting and facilitating academic integrity.

Admissions, Marketing, and orientation One of the seven recommendations made by the CAI (1999) is to “inform and educate the entire community regarding academic integrity policies and procedures” (p. 10). To this end, institutions should take every opportunity to advertise their commitment to academic integrity. Materials should be developed in print, multimedia, and Web-based formats that would be included in information packets mailed to interested students and in advertising campaigns. Statements of support from community and business leaders and alumni might be included in these; for example, “Acme, Inc., strongly supports the high standards of academic integrity set by State U. Your graduates possess the values we are seeking in future employees.” Orientation programs have always been instrumental in terms of helping students effectively embark on their studies. DE students, removed from a great deal of campus culture and often nontraditionally aged and returning to formal education after many years, may benefit greatly from full orientation programs that prepare them for their new study activities. Topics might include organization, time-management, study skills, distance learning success, writing, independent study, stress management, and so forth (Granger & Benke, 1998). It is through the orientation process that campus academic integrity policies and procedures should be formally and thoroughly shared and discussed with all students. Because of DE students’ physical separation from campus, accommodations should be made to support all of these objectives with videotape, multimedia CD-ROMs, telephone, and Web support methods being currently utilized by a growing number of

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institutions. Orientation processes should also ensure that students are properly assessed in terms of their preparedness for college-level work. For those students needing remediation, advisement should be provided to assist them through the requirements or to explain alternatives when appropriate.

InstructIonAL suPPort: (tutorIng-teAchIngProctorIng) First, academic integrity must be modeled by all members of the faculty. The CAI (1999) stated, “Fair and accurate evaluation is essential in the educational process. For students, important components of fairness are predictability, clear expectations, and a consistent and just response to dishonesty” (p. 7). Faculty members also need to be aware that learners must first learn how to learn skills to be effective online learners, and that these skills need to be explicitly supported and taught. Drawing upon a range of theory, McLoughlin and Marshall (2000) maintained that effective online learning requires a variety of skills: articulation (connecting instructions and resources to course objectives and assessment measures), self-regulation (maintaining discipline in terms of class participation expectations and deadlines), a repertoire of learning strategies, and self-assessment and self-evaluation. The authors turn to sociocultural theory, which states that learning involves social interaction and dialogue, negotiation, and collaboration and that “scaffolded” or assisted learning (wherein instructors utilize a developmental approach, supporting individual students so that they gain increasing degrees of autonomy and competence in their learning) can increase cognitive growth and understanding. This can be demonstrated by instructors who require a progressive sequence of

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work from their students; as an example, for papers this might consist of a proposed topic, outline, research, draft, and then a final paper. Due to the growing concern over Internet plagiarism, Web-based Internet detection services, both fee-based and non-fee-based, are being increasingly utilized (Hamlin & Ryan, 2003). These services operate in a variety of ways but frequently compare a student’s electronic paper to a full-text database of thousands of documents and the Web in general, testing for possible matches of text, and then automatically feeding back a report with the findings. Turnitin.com© is a popular example of such a service, with over 20,000 registered users in 19 countries (McCarroll, 2001). While these plagiarism-detection services are attracting a growing number of proponents and customers, some concerns have been raised: Copyright considerations for student papers (Foster, 2002), cost in an era of tightening budgets, degradation of the relationship between faculty members and their students, incomplete databases providing false negatives, and false positives due to commonly utilized phrases (Foster, 2002). McMurtry (2001) recommended eight suggestions for faculty to more effectively combat e-cheating: 1. 2. 3. 4. 5.

6.

Take time to explain and discuss your college’s academic integrity policy. Design writing assignments with specific goals and instructions. Know what is available online before assigning a paper. Give students enough time to do an assignment. Require oral presentations of student papers or have students submit a letter of transferal to you, explaining briefly their thesis statement, research process, and so forth. Have students submit essays electronically.

Supporting and Facilitating Academic Integrity in Distance Education Through Student Services

7. 8.

When you suspect e-cheating, use a full-text search engine. Consider subscribing to a plagiarism search service.

With these last two recommendations, many educators view these services as being more valuable in terms of their deterrence than in their ability to detect plagiarism (Hafner, 2001); in order to be truly effective, therefore, students should be informed at the beginning of the semester that the instructor reserves the right to utilize these methods. Other educators add to these recommendations the use of pop quizzes and class participation requirements on discussion boards (Hamlin & Ryan, 2003), project-based assessments (Olt, 2002), signing academic integrity statements, proctored exams, and writing assignments that change each semester. The use of course journals, where students are required to summarize what they have learned and their thoughts and impressions as they progress through the course, makes plagiarism quite difficult, particularly if the journals are collected and reviewed frequently by the instructor. This assessment measure also clearly supports the goal of scaffolded learning. In addition, there is a growing movement toward the use of electronic portfolios; although there is to date little agreement over their makeup and format, many educators see them as a valuable assessment tool for both online and face-to-face classes (Ahn, 2004). Another issue requiring attention is that of proctoring. Many distance and open educators argue for strict adherence to flexible assessment, striving for “anytime/anywhere” —which by its nature prohibits proctored examinations. Others, however, see DE as being on a spectrum with traditional education; while maximum flexibility is the goal, there are situations where proctored exams are required for pedagogical or licensure and certification reasons. When this is the case, institutions must ensure that proper facilities

and staff are available, to include at a minimum supervised assessment centers with flexible hours and coordinators for off-site proctoring.

Instructional technology With the rapid implementation of Web-based technologies in DE, there is a growing concern over the verifiability of students’ identities online. While this is certainly not a new concern of DE educators, new technologies are providing additional tools to institutions. It is now common for all course management systems (CMS), learning management systems (LMS), and college portals to require both a login identification as well as a password. With a widespread goal being ease of use, many institutions implement a single sign-on for all Web-based services and resources (registration, transcript review, online library, access to learning platforms, etc.), requiring the user to authenticate only once. Authentication is the process wherein a network user establishes a right to an identity, while authorization is the process of determining whether an identity—plus a set of attributes associated with that identity—is permitted to perform some action, such as accessing a resource (Mickool, 2004). Although a variety of technologies have been or are being developed to address the issue of authentication (e.g., passwords, certificates, smart cards, biometric techniques), to date passwords are by far the most commonly used. This system easily lends itself to abuse; for example, student A might simply give his or her login identification and password to student B in order to allow student B access to an online classroom to take a test. In the traditional classroom, this is easily dealt with by simply recognizing one’s students or by requiring a photo ID. Even if more advanced technologies are utilized, however, the potential for abuse will not disappear. For this reason, many online instructors prefer using assessment

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Supporting and Facilitating Academic Integrity in Distance Education Through Student Services

measures other than or in addition to tests or require proctoring (as described above). A single sign-on, however, might also serve a secondary role in preventing students’ sharing of their login identifications and passwords if they understand that this gives others access to their financial aid information, grades, e-mail account, registration, and so forth. The key here is to adequately publicize this fact.

LIbrAry servIces Library services may support and facilitate academic integrity in a variety of ways. Self-paced online learning tutorials have been established at many institutions that allow students to learn research and writing skills, proper citation formats, and how to avoid plagiarism. Examples of such tutorials may be found at the University of Maryland University College’s (UMUC) Virtual Academic Integrity Laboratory (UMUC, 2003). Additionally, support through chat, telephone, and e-mail may be provided to support students more flexibly as they perform their research. As proposed by some (Foster, 2002), plagiarismdetection services could be made available to students to allow them to review their own papers before submission to assist them in avoiding plagiarism.

counseLIng And AdvocAcy At every available opportunity, counselors should seek to support the institution’s academic integrity policy through such activities as presentations to high schools and other groups, meetings with student government, and campus educational campaigns. Through dialogue with students, counselors should remain vigilant to signs of stress, frustration, and problems with grades, all of which can increase the probability of cheating.

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Counselors, be they full-time professional staff or faculty, should be proactive in advising moderation to their students with respect to course load and in consideration of the occasional need to withdraw from a course. Counselors may also serve as additional contacts for students wishing to report acts of academic dishonesty. As Robinson (1995) reminded us, “Not all open and distance learners are adults, highly motivated or self-managing”(p. 223). Just as with any population of students, there will certainly be some DE students who violate the institution’s academic integrity policy. In order to properly address such situations, a “clear, accessible, and equitable system to adjudicate suspected violations of policy” (CAI, 1999, p. 10) should be created. All students accused of academic dishonesty should be provided with counseling and possibly advocacy in such circumstances, as well as after a judgment is rendered. At a minimum, students should be fully informed of the charges against them, their rights and options, the official proceedings, and the consequences of being found guilty. Institutions might choose to go further than this, providing for optional representation for the accused as well as the accuser, thereby creating a true honor court.

concLusIon Although most educators understandably find the topic of academic dishonesty unpleasant, Hamlin and Ryan (2003) reminded us that “unfortunately, cheating has always existed and will continue as long as there is temptation to do so.” For academic integrity programs and policies to truly be effective, they must be preventive and universal in scope. All segments of student services must be involved in the development, implementation, and review of the policies. Regular assessment must be conducted, and the institution should remain ever vigilant to trends in higher education and

Supporting and Facilitating Academic Integrity in Distance Education Through Student Services

technology that might impact academic integrity on campus (CAI, 1999). Just as students should be able to expect fair treatment in potential cases of academic dishonesty, faculty and staff must also have a right to expect the same (CAI, 1999). Additionally, institutions must include these topics in their professional development programs, particularly in faculty and staff orientation, and whenever possible students should be invited to share their views and concerns. Although it is certainly the case that the effective use of technology may help to prevent or expose academic dishonesty, it should never be viewed as a cure-all. Academic integrity or dishonesty is based upon the actions of human beings, and it is here that our attentions and efforts should be largely focused. Every technology can be circumvented and every rule broken if students are dedicated to these goals and believe that they can do so with little or no chance for detection and punishment. It should also be understood that any institution that sets high standards and actively monitors academic integrity will inevitably discover it, and that this is not a sign of failure. The trick for educational institutions is to encourage and foster the development of academic integrity in their students so that they make no attempt to cheat in the first place.

reFerences Abbott, L., Siskovic, H., Nogues, V., & Williams, J.G. (2000). Student assessment in multimedia instruction: Considerations for the instructional designer (ERIC Document Reproduction Service No. ED 444 516). Retrieved June 11, 2002, from http://newfirstsearch.oclc.org Ahn, J. (2004, April). Electronic portfolios: Blending technology, accountability & assessment. Retrieved May 11, 2004, from http://www. thejournal.com/magazine/vault/A4757C.cfm

Brindley, J. E. (1995). Learner services: Theory and practice. Retrieved August 28, 2003, from http://www.uni-oldenburg.de/zef/cde/support/ readings/brind95.pdf Center for Academic Integrity. (1999). The fundamental values of academic integrity [Brochure]. Commission on Colleges and Schools. (2000). Distance education: Definitions and principles—A policy statement. Retrieved November 3, 2003, from http://www.sacscoc.org/pdf/distance.pdf Foster, A. (2002, May 17). Plagiarism-detection tool creates legal quandary. Retrieved February 27, 2003, from http://chronicle.com/free/v48/ i36/36a03701.htm Granger, D., & Benke, M. (1998). Supporting learners at a distance from inquiry through completion. In C. C. Gibson (Ed.), Distance learners in higher education (pp. 127-137). Madison, WI: Atwood Publishing. Retrieved September 20, 2003, from http://www.uni-oldenburg.de/zef/cde/ support/readings/grang98.pdf Hafner, K. (2001, June 28). Lessons in Internet plagiarism. Retrieved February 27, 2003, from http://www.nytimes.com/2001/06/28/technology/ 28CHEA.html?0628i Hamlin, L., & Ryan, W. (2003). Probing for plagiarism in the virtual classroom. Retrieved May 1, 2003, from http://www.syllabus.com/article. asp?id=7627 Hinman, L. M. (2000). Academic integrity and the World Wide Web. Retrieved February 28, 2003 from http://ethics.acusd.edu/presentations/ cai2000/index_files/frame.htm Lyons, J. W. (1990). Examining the validity of basic assumptions and beliefs. In M. J. Barr, M. L. Upcraft, & Associates (Eds.), New futures for student affairs (pp. 22-40). San Francisco: Jossey-Bass.

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Mayfield, K. (2001). Cheating’s never been easier. Wired. Retrieved February 27, 2003, from http:// www.wired.com/news/school/0,1383,45803,00. html McCarroll, C. (2001, August 28). Beating Web cheaters at their own game. Christian Science Monitor. Retrieved February 27, 2003, from http:// www.csmonitor.com/2001/0828/p16sl-lekt.html McLoughlin, C.,& Marshall, L. (2000, February 2-4). Scaffolding: A model for learner support in an online teaching environment. Proceedings of the 9th Annual Teaching Learning Forum, Perth, Australia. Retrieved September 18, 2003. from http://www.uni-oldenburg.de/zef/cde/support/ readings/loughlin2.htm McMurtry, K. (2001). E-cheating: Combating a 21st century challenge.Retrieved February 27, 2003, from http://www.thejournal.com/magazine/ vault/A3724.cfm Mickool, R. (2004, April 1). The challenge of single sign-on. Retrieved April 10, 2004 from http://www.syllabus.com/article.asp?id=9194 Olt, M. (2002). Ethics and distance education: Strategies for minimizing academic dishonesty in online assessment. Retrieved February 27, 2002,

from http://www.westga.edu/%7Edistance/ojdla/ fall53/olt53.html Robinson, B. (1995). Research and pragmatism in learner support. In F. Lockwood (Ed.), Open and distance learning today (pp. 221-231). London: Routledge. Rumble, G. (2000). Student support in distance education in the 21st century: Learning from service management. Distance Education, 21(2), 216-235. Simpson, O. (2000). Supporting students in open and distance learning. London: Kogan Page. Tait, A. (1995). Student support in open and distance learning. In F. Lockwood (Ed.), Open and distance learning today (pp. 232-241). London: Routledge. UMUC. (2003). Virtual academic integrity laboratory. Retrieved November 4, 2003, from http://www-apps.umuc.edu/forums/pageshow. php? forumid=3&s=bf1d29e4e3b1752749478eb 5cfb7836d Waryold, D. (2002, November 14). Establishing a climate of academic integrity on campus. Workshop conducted at Santa Fe Community College in Gainesville, FL.

This work was previously published in Online Assessment and Measurement: Foundations and Challenges, edited by M. Hricko & S. L. Howell, pp. 330-340, copyright 2006 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.22

ePortfolio and Educational Change in Higher Education in The Netherlands M. W. (Wijnand) Aalderink Windesheim University for Professional Education, The Netherlands M. H. C. H. (Marij) Veugelers Universiteit van Amsterdam, The Netherlands

AbstrAct This chapter describes the important role that the concept of ePortfolio plays in new pedagogical paradigms in The Netherlands. ePortfolio can be seen both as a consequence of and a stimulus for the movement towards student-centered, competence-based learning in Dutch higher education. The authors present lessons learned in ePortfolio implementation, derived from experience from the past five years in the Low Countries, both in local institutional projects and in large-scale national projects. They then describe the cases of their own universities, being Windesheim University for Professional Education and the University of Amsterdam. The chapter ends with conclusions

and future developments in the field of ePortfolio in The Netherlands.

IntroductIon In Dutch institutions of higher education, the subject of ePortfolio continues to attract increasing interest. This can be explained partly by the focus on competence-oriented education in universities of professional education, in which the emphasis is placed on student development, but also by academic universities’ attention to fostering academic maturity. In the process of educational innovation, the ePortfolio is frequently used as an aid for guiding the learning process or as an assessment tool. It also offers the “Net Generation” students (Aalderink & Veugelers,

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

ePortfolio and Educational Change in Higher Education in The Netherlands

2005a) of today the possibility of presenting themselves to various target groups. ePortfolios have the potential to offer clarity and flexibility, for which various stakeholders in education have a particular need, in learning, teaching, and administrative processes. Much useful experience with the implementation of ePortfolios has been acquired in The Netherlands, through both national projects and initiatives set up by most institutions of higher education. The aim of NL Portfolio1 , established in the spring of 2004, is to combine, share, and expand this experience. NL Portfolio is one of the SURF Foundation’s special interest groups. SURF2 is the Dutch partnership organization for information and communications technology (ICT) in Dutch higher education and research.

Lessons LeArned In ePortFoLIo IMPLeMentAtIon From the different projects that have been carried out in The Netherlands, different lessons can be learned which are first presented here and will then be illustrated by the cases of Windesheim University of Professional Education and the University of Amsterdam.

Lesson 1: Pedagogy comes First In educational change processes using informaFigure 1. tion technology, it is very important to start off from the functional perspective of the learner and the teacher, and to avoid a technology push. In The Netherlands this view is well accepted and is also found to be a key factor in ePortfolio implementation in large-scale, nationwide projects like the E-Folio Project3 and the LMS/DPF (Learning Management System/Digital Portfolio) Project (Kokx, Van de Laar, Veltman-Van Vugt, & Van Veen, 2004). Students in the LMS/DPF Project have reported that the greater amount of self-responsibility in learning with an ePortfolio

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was a stimulus for them that evoked them into intrinsic learning in which they were motivated to reflect on and improve their learning processes. One of the conclusions of the E-Folio Project was that the extra value of the use of portfolios lays in learning in authentic situations, creating room for individual development, and investing in coaching and alternative assessment. In the model of Van Tartwijk et al. (2003), the pedagogical field is located in the center of the picture, representing an approach that most Dutch institutes share as common ground: it all starts with the learner. The model also shows elements of the lessons that follow (see Figure 4).

Lesson 2: Clear Definition of Goals and results is Important ePortfolio tends to be a container term used for a variety of tools in a wide range of approaches. Traditionally, an ePortfolio refers to a file-sharing system used as a showcase for an individual by which he provides an overview of his achievements in a certain field. Another large-scale project in The Netherlands carried out by the Digital University4 (Veugelers et al., 2004) has shown that different approaches on ePortfolio implementation can be categorized in a scenario model in three ePortfolio and Educational Change in Higher Education in The Netherlands

Figure 1. Scenarios for ePortfolio implementa-

Scenarios tion for ePortfolio implementation

Scenarios in ePortfolio implementation COUNSELING Scenario 1

+ ASSESSING Scenario 2

+ PLANNING Scenario 3

University-wide 4-year program in department 1-year program in department Pilot

Universities differ in starting points, goals, and strategies

a lot of large- and small-scale projects, it has become clear that implementing a portfolio requires much more than just providing a tool. As concluded in the E-Folio Project: ePortfolios

ers and team members have to do a lot of communication and must actively organize sessions for groups of key users that function as a sounding board. The central finding of a lot of

ePortfolio and Educational Change in Higher Education in The Netherlands

major areas according to their primary focus on career counseling and/or assessment and/or personal development planning (see Figure 1). In The Netherlands, academic universities tend to choose a career counseling portfolio, as the case of the University of Amsterdam will show later on, whereas in universities of Professional Education, like Windesheim, all goals (counseling, assessing, and planning) are at stake in an integrated portfolio approach. From a lot of large- and small-scale projects, it has become clear that implementing a portfolio requires much more than just providing a tool. As concluded in the E-Folio Project: ePortfolios should be tailored to the purposes for which they are used in the learning environment.

Lesson 3: Maintaining Multiple stakeholders’ Perspectives is vital At the organizational side, the question in the ePortfolio case is how to keep the different perspectives of involved stakeholders in line with each other. It has become clear that a multidisciplinary approach in development and implementation is essential with the involvement of all of the stakeholders (students, teachers, coaches, assessors, work field, managers, administration employees, and technicians). Depending on the level of implementation from single-class experiments up to institution-wide ePortfolio projects, this multidisciplinary approach becomes more crucial. Project managers and team members have to do a lot of communication and must actively organize sessions for groups of key users that function as a sounding board. The central finding of a lot of experience so far has been that ePortfolio implementation tends to be more successful if the different stakeholders can define the institute’s own specific form of folio thinking together. Different processes, whether they are pedagogical, administrative, or technical, should be developed and tested in collaboration.

Lesson 4: support by Management is crucial Support by management is crucial: the lines of development are best chosen as a result of a bottom-up process, but after the decisions are made, management should support, facilitate, and monitor them top-down by defining a clear strategic framework. Change management is what is needed in ePortfolio projects, bringing about change in effective ways, a process in which existing human resources are a vital link. The art of change management consists of making effective use of existing as well as incoming energy. The Net Generation student, who is much more into technology than most teachers are, is in a position to play a leading part in this process. In different pilots, students have proven to be good change agents in the development and implementation of eLearning. With regard to ePortfolio implementation, the change management approach tallies interestingly with a further shift of accent from tools to processes. When embedded adequately in the processes or workflow of the different stakeholders, their motivation for the application of the ePortfolio system as a tool will be influenced in a positive way.

Lesson 5: Functional and technical support is Also crucial The different users of an ePortfolio system need tailor-made performance support in an accessible form, since ePortfolio implementation is not another routine project, but in most cases part of a complex educational innovation. Support should be set up both on the functional-pedagogical and on the technical-instrumental side in the local departments in cooperation with institution-wide support units for IT and educational development. A common strategy for implementation in The Netherlands is to start with small-scale pilots in several departments, to explore the eP-

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ortfolio case in each specific context, define the workflow, and train the local key players. These “locals” are the ones that play a very important role in the subsequent phases of scaling up. The different local portfolio project managers are then facilitated as a community of practice together with the “central” project managers. In this way support can be co-organized and facilitated in an effective way. The form in which the support is organized may vary from department to department and also within departments. It may be a mix of training sessions, workshops, paper manuals, a good support site with tutorials and best practices, office visits, and so forth.

Lesson 6: technological choices Matter too Although the “pedagogy comes first” axiom has very strong appeal in The Netherlands, there is of course also the technical challenge of how to create functional workflows in an integrated technical infrastructure. In The Netherlands there is a growing tendency to work with integrated architecture approaches, giving attention to open standards and interoperability5 . Systems for digital portfolios are in technical terms still in a considerable state of flux; this also applies, for example, to their relationship to digital learning environments and study registration systems. In most cases the ePortfolio is not just a single tool (just one piece of software), it is more often part of a larger technical configuration in which the required functionality may be met by the cooperation of different hardware and software tools.

two exAMPLes oF ePortFoLIo IMPLeMentAtIon In the netherLAnds It will be clear from the two cases described below that the implementation of an electronic portfolio in higher education needs a long breath, a lot of

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flexible attitude, and a strong conviction that this will be the tool for the future in lifelong learning. The implementation struggles and strategies we describe will provide more insight into the learning process that led to the lessons learned of the previous paragraphs.

case one: windesheim university of Professional education—Portfolio in the heart of the organization During the past four years, Windesheim has worked on an integrated and functional strategy for the development and implementation of a campus-wide ePortfolio system (Aalderink, 2004). In the developed pedagogical model, using an ePortfolio is not to be just some extra activity that stands apart for the teachers and the students. Instead it should be a fundamental cornerstone for the pedagogical process on the one hand and the educational institute’s administrative processes on the other. When implemented in the heart of both, an ePortfolio can make learning and teaching more efficient and effective. It supports and improves students’ acquisition of competencies, and it also brings about a more transparent and flexible workflow for the different stakeholders involved. In this picture, the ePortfolio fulfills vital demands for overview and flexibility. Windesheim plans to use the ePortfolio as a tool for both students and faculty in all of the courses, starting with the cohort of 2006-2007. The results of two intensive rounds of pilots have shown that it can make learning and teaching more efficient and effective when embedded in the workflow of students and faculty. An important element of ePortfolio development and implementation at Windesheim so far has been that the different stakeholders have been involved from the start of the program in 2001. By working this way, there is common ground regarding the functional specifications, the key processes, and the selected tool.

ePortfolio and Educational Change in Higher Education in The Netherlands

Windesheim has run pilots in nine of the total number of 10 departments. It is now preparing for an intensive implementation project in terms of educational and administrative processes. Parallel educational standards for the application of ePortfolios in student-centered, competence-based education within the major-minor model are being developed at a strategic level in the so-called Windesheim Educational Standards. At Windesheim, ePortfolios will eventually cover the following primary functions: career counseling, assessing, and planning in both Windesheim’s more classic subject courses and especially in so-called integrated professional tasks that students work on over a longer period of time. Figure 2 shows the central position of the student from plan to progress in Windesheim’s competence-based process model that students go through each half year. A circular model like this one is common in several student-centered ePortfolio approaches in Dutch higher education; one can see the learning cycle of Kolb (1984) shining through.

Figure 2. Processes in competency-focused, student-centered education Stakeholders: fellow student, coach and/or assessor in department and/or in workfield

Key processes: 1. Learning and teaching 2. Career coaching 3. Administrative workflow

Student Windesheim Education Standards

In the portfolio system that Windesheim develops in cooperation with Concord6 , assessment matrices provide an actual overview of work in progress and work done by the students. In this manner the system supports the student-centered approach Windesheim chooses, with the focus on competency acquisition in flexible curricula. Students assemble their personal development plan (PDP) within the portfolio system, in a cooperative setting with stakeholders in the institute itself (fellow-students, coaches, assessors) and in the working field (coaches, assessors). All of the plans, all of the tasks, all of the work in progress, and all of the work done by each student are accessible through the hyperlinks in the matrices in a structured way. Justification arguments for competency and skills certification in the portfolio system may be circulated for discussion with peers and other selected parties, and be made part of the justification process. Each justification can be held at one of several justification levels (see Figure 3): Proposed, Required, Plan, Draft, Feedback, Closed, Withdrawn, Finished, and Complete. The communication and feedback involved can also be stored in the system. The assessment matrix is where the primary requirements of both reflection and registration are being met. For the students there is always an answer to be found in the matrices on common but vital questions like, “Where do I stand?” and “How did I get here?” and “Where do I move next?”—answers that can be quite relevant to the other stakeholders in a student’s learning process as well, especially in a setting where collaborative learning is important. Students are invited to propose learning tasks themselves to give them more responsibility for their own learning. At Windesheim the ePortfolio project has recently become part of a strategic program, “IT for Student-Centered Education,” consisting of the following projects:

Technically and functionally integrated systems

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ePortfolio and Educational Change in Higher Education in The Netherlands

Figure 3. Course matrix following Windesheim Educational Standards Pedagogical workflow course

Course matrix following Windesheim Education Standards Title of course. Course-code—Title course. Short description from Major Minor-Course Catalogue Matrix status: Under construction Teacher: [ ] Headteacher: [ ]

1. 2. 3. 4. 5. 6.

7.

Learning task/product

Status

Title learning task / learning product product 11

Required

Title learning task / learning product product 22

Required

Title free learning task / learning learning product product

Proposed (Required)

Final assessment assessment

Required

The upgrade of the student information system The development of an electronic catalog for majors, minors, and courses The ePortfolio project A qualitative approach to the virtual learning environment Information architecture and personalized “my Windesheim” portal Reorganization of the processes and tools for scheduling, testing, and progress registration Integrated training and support for the whole set of new systems, developed per stakeholder and implemented per department

The program of projects creates as much synergy as possible in the development (using Internet technology, Web services for system cooperation and integration) and implementation of the different new IT tools involved that will scaffold all of the administrative and pedagogical processes and stakeholders in an integrated way. As a result, the organizational shift at Windesheim University will be supported with information technology in an effective and efficient way, with the ePortfolio as an important key element.

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°

Proposed

•

Required

° ° °

Plan

°

Close

• • • •

Draft Feedback Finished Completed Revise Withdraw

case two: university of Amsterdam—A step-by-step three-Pillar Model The University of Amsterdam is an academic university with “traditional” education: lectures, work groups, and laboratory courses. The departments are reasonably autonomous and formulate their educational concept themselves. Ever since 2001, there have been numerous pilots focused on working with an electronic portfolio (Veugelers, 2004). In the space of three years, the plans have been put into effect at nine of the 24 university departments. Progress was so rapid all over that in January 2003, the decision was made at the central level to draw up a university-wide implementation plan. The situation was described for a two-year rollout in an effort to have 40% of the 22,000 students working with an electronic portfolio by 2005. Due to the great financial investments this would involve, the decision was made to first discuss the matter with all the educational directors to enroll their commitment to the project. After their commitment was clear, a new strategic plan was written in February 2004 to prepare a Go/No Go decision for December 2004, so the university board could make a

ePortfolio and Educational Change in Higher Education in The Netherlands

decision. This implementation will be based on the University of Amsterdam three-pillar model (Fisser & Dekker 2003) of pedagogy, management strategy, and technology. The following aspects are to be prepared:

•

• • • • • • • •

A teacher training program for the new role as coach (instead of the role as an expert), supporting faculty members in their development from sage on the stage to guide on the side Best practices with examples of assignment instructions and student portfolios to be shown on the university Web site portfolio A pedagogical support framework The appointment of a team of professionals to help with the new initiatives A format for the technology support at the university A proposal for a tool selection A financial overview of various hosting models A discussion with educational managers about the new challenges in educational innovation at a university A checklist of pre-conditions for the management of new initiatives

Figure 4. University of Amsterdam “ePortfolio concept model”(Adapted from Van Tartwijk et al., 2003) Management Portfolio concept

goals Learning activities Learning environment

People

Infrastructure Support

The model of portfolio and educational innovation attention areas from Van Tartwijk et al. (2003) was used since October 2003 for all the initiatives and appeared to be a useful model (Veugelers & Korterink, 2005). The University of Amsterdam recommends that there should be an extra circle behind the model for the central organized support by the (educational and strategic) implementation in the whole university so that all the knowledge can be shared (see the lessons learned in the first part of this chapter and Figure 4). Besides, it is maybe better to speak about a “portfolio concept” instead of an ePortfolio system, because the concept is more than the “tool”: the concept is the whole idea of taking up self-responsibility as a student for student growth, thinking in reflection, giving stimulating feedback, and so on. The increasing focus on academic training and skills is the main reason to start with a portfolio at this university without a central concept of competence-based education, like there is at Windesheim in the previously described case. Stimulating the growth of these academic skills and making them visible in an ePortfolio are the bases for all of the pilots. Simultaneously with this movement, there is also renewed interest in arriving at a collective concept of education. And as a result of the collaboration with a local university of professional education, the Amsterdam University of Professional Education, the improvement of the student career counseling is once again on the agenda. All these movements converge in the University of Amsterdam portfolio implementation route and can be viewed as an example of the Scenario 1 route (see Figure 1). This scenario in which career counseling and personal development predominate is expected to serve as the guideline for the next few years. In view of the strong autonomous role of the departments at the University of Amsterdam, up to now the change approach—according to the classification by De Caluwé and Vermaak (2002)—has

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been characterized as a “yellow change” with attention for creating a support base/sharing views/involving the context. The implementation of an electronic portfolio will however require a “blue” approach with a blueprint for a study career-counseling route, with checklists for the managers to steer the pilots and new initiatives. This is an approach that is common practice in the IT world, but not so much at this university. There will also have to be a “red” focus on stimulating and encouraging teachers to grow in their changing role from expert to coach by setting up a route for their professional development. In 2002 a consortium of 10 universities (the Digital University) introduced a portfolio tool that could be used by various educational universities and commercial firms in The Netherlands. The University of Amsterdam used this tool from the beginning. It is a very “open” tool: students can create their own look and feel; there is not a fixed format for presentations. The system runs on a server outside the organization. During the last two years a lot of the participating universities chose for their own university a system with more possibilities for technical connection to other university tools. For that reason the Digital University has decided that the tool could not become a financial success, and from August 2005 on, the tool will be no longer available. So in Autumn 2004, the University of Amsterdam decided to select another portfolio system: based on technical requirements (besides the educational functional requirements), the university chose the Open Source Portfolio from OSPI because they believe in the Sakai concept for the future, where OSPI is embedded. During 2005, the university prepared the rollout of version 2.1 (October 2005) and hopes that in April 2006, version 2.5 will be ready for all of the university. As a member of Sakai, the University of Amsterdam shares its knowledge in the OSPI community7 .

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concLusIon From the two higher education case studies that were presented above, and from many other projects in other parts of the educational sector in The Netherlands and worldwide, we can learn that developing and implementing an ePortfolio is a challenging job that takes a lot of time and energy. It calls for context-dependent folio thinking that can only succeed when linked closely with educational change in the specific organization at different levels and from different perspectives. The lessons learned as presented are these: pedagogy comes first; we must work on welldefined goals towards planned results; all stakeholders should be involved in a multidisciplinary approach; management support cannot be missed, as is the case for functional and technical support; and the different IT tools have to interoperate in a technical architecture that is user friendly in a personalized way. We can expect more progress in the field of ePortfolio if we succeed in learning and applying these lessons together.

Future deveLoPMents In the netherLAnds Within Dutch higher education, SURF funds special interest groups, a concept that has already been applied successfully for the subjects of streaming audio and video in the “Webstroom”8 group and for standardization in the “SIX” special interest group9 . As yet, another of these special interest groups, “NL Portfolio,” has defined its activities for the coming two years, including:

• •

Setting up a coordinating Web site10 that will be the portal to the subject of ePortfolio for Dutch institutions of higher education Participating in existing innovation projects in The Netherlands, grassroots projects, and eLearning research projects

ePortfolio and Educational Change in Higher Education in The Netherlands

• • •

•

Initiating its own project tender among Dutch institutions of higher education Cooperating internationally in the field of ePortfolio Exploring and developing the subject of “lifelong learning” in The Netherlands, thereby cooperating with partners in the educational sector, the government, and the professional field Disseminating project-related information by means of national and international conferences and seminars

•

International cooperation on ePortfolios is also a field in which participation from The Netherlands evolves.

•

Cooperation in The Netherlands on ePortfolios has been taken up already, as the following examples make clear (see also Aalderink & Veugelers, 2005b):

•

•

•

In a trend study on ePortfolio in higher education (Slotman et al., 2005) as part of an eLearning research project by SURF, aiming specifically at the audience of higher education managers, results describe the lessons learned by different institutions regarding ePortfolio, in terms of “actors, factors, and strategies.” Also, different higher education consortia in the Netherlands, like Apollo11 , E-Merge1 2 , and the Digital University1 3 , have done ePortfolio tool studies to explore the future in this field together. Across the educational sector, different partners, from primary education up to higher and further education, have worked together on a broad state-of-the-art study on ePortfolio in The Netherlands. The report (Hensen, 2004) describes five possible routes for future development in terms of cooperation: from doing nothing (route 1), up to one system for ePortfolio on a national scale (route 5). The report advises working towards “route 4” by creating “one mutual highway” that will set standards for both functional and technical specifications that

can be applied regionally and in different sectors of education. Also in other sectors of education, initiatives on portfolios exist. An example is the “Platform Portfolio” in the professional education sector14 .

•

•

•

A recent example of cooperation by Dutch universities was organized by SURF and ALT1 5 (UK). Portfolio specialists from both countries have exchanged knowledge and experience in a working seminar and have written a briefing paper together (Cotterill et al., 2004). The paper highlights apparent similarities and differences in approaches between the UK and the Netherlands, as well as opportunities for future collaboration. In the 2005 edition of this meeting, ILTA16 from Ireland also joined the conference and research seminar (Roberts, Aalderink, Cook, et al., 2005). The University of Maastricht participates in the European Union-funded EPICC project17 , which describes use cases and scenarios. As part of an intensive cooperation program between JISC18 and SURF, new projects will start soon on ePortfolio. Experts from both countries’ joint workforces will exchange information and come up with joint PDP/ePortfolio formats and advices on coordinated future development of assessment models. Also, more collaboration workshops will be planned in the near future.

reFerences Aalderink, W. (2004, June 29-July 2). Digital portfolio: Tool for flexible learning and teach-

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ing in competency focused higher education. In Proceedings of Eunis 2004—IT Innovation in a Changing World, Ljubljana (pp. 25-29). Aalderink, W., & Veugelers, M. (2005a, June 2023). Educating the Net Generation: More focus on the student in the USA. In W. Aalderink & M. Veugelers (Eds.), Educause 2004: IT from a higher vantage point (pp. 133-139). SURF Edutripreport 2004, Helsinki, The Netherlands. Aalderink, W., & Veugelers, M. (2005b). E-portfolio’s in The Netherlands: Stimulus for educational change and lifelong learning. In Proceedings of EDEN 2005-Lifelong E-Learning. Cotterill, S., Darby, J., Rees Jones, P, Roberts, G., Van Tartwijk, J., & Veugelers, M. (2004, April 22-23). ALT-SURF seminar: E-portfolios and digital repositories. Edinburgh. Utrecht: Stichting SURF. De Caluwé, L., & Vermaak, H. (2002). Learning how to change: Handbook for the change manager. Deventer: Kluwer. Fisser, P. H. G., & Dekker, P. J. (2003, July 2-4). Implementing a university-wide electronic learning environment, technology, communication and didactics. In Proceedings of EUNIS 2003, Amsterdam (pp. 154-156). Hensen, T. (2004). Research e-portfolio: An organizational and infrastructural challenge. Kennisnet, The Hague. Kolb, D. A. (1984). Experiential learning. Englewood Cliffs, NJ: Prentice-Hall. Kokx, P., Van de Laar, H., Veltman-Van Vugt, F., & Van Veen, J. (2004). From wish to reality (SURF Project LMS-DPF). The Netherlands. Roberts, G., Aalderink, W., Cook, J. et al. (2005, April 1). Reflective learning, future thinking: Digital repositories, e-portfolios, informal learning and ubiquitous computing. In Proceedings of

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the ALT-SURF-ILTA Report on the E-Portfolio Research Seminar, Dublin. Slotman, K., Fisser, P., Gulmans, M., Braspenning, C., Van der Veen, J., & Logtenberg, H. (2005). E-portfolio: Beyond the hype or limited optimism? The Netherlands: SURF E-learning Research. Van Tartwijk, J., Driessen, E., Hoeberigs, B., Kösters, J., Ritzen, M., Stokking, K.M., & Van der Vleuten, C. (2003). Working with an electronic portfolio. Hoger Onderwijs Praktijk. Groningen: Wolters-Noordhoff. (English version available at http://e-learning.surf.nl/portfolio, see Handbook.) Veugelers, M. (2004). Electronic portfolio: Be aware of the pedagogical challenges and the technology struggle. In Proceedings of Eunis 2004—IT Innovation in a Changing World. Veugelers, M., Gulmans, M., Van Kayzel, R., Kemps, A., Kinkhorst, G., Meeder, S., & Slotman, K. (2004). Portfolio-implementatie. Utrecht: Digitale Universiteit. Veugelers, M., & Kemps, A. (2004, October 2829). The manager’s challenge: With one toolkit, three scenarios and change management, start the portfolio implementation. In Proceedings of the 2004 E-Portfolio Conference (pp. 119-134). La Rochelle, France. Veugelers, M., & Korterink, A. (2005). Implementation of electronic portfolio, experiences of the University of Amsterdam. From trend to transformation. Digital University, The Netherlands.

Key terMs Assessment: The process of documenting, usually in measurable terms, knowledge, skills, attitudes, and beliefs. Assessment is often used in an educational context (to refer, for example, to the work of institutional researchers), but it

ePortfolio and Educational Change in Higher Education in The Netherlands

applies to other fields as well (such as health and finance). Assessments can be classified in many different ways. The most important distinctions are: (1) formative and summative; (2) objective and subjective; and (3) criterion-referenced and norm-referenced. Career Counseling: Provides one-on-one or group professional assistance in exploration and decision-making tasks related to choosing a major/ occupation, transitioning into the world of work, or further professional training. The field is vast and includes career placement, career planning, learning strategies, and student development. Career counseling advisors assess people’s interests, personality, values, and skills, and also help them explore career options and research graduate and professional schools. Competence: In human resources, a standardized requirement for a individual to properly perform a specific job. ePortfolio: In the context of education and learning, a portfolio based on using electronic media and services. It consists of a personal digital record containing information such as a collection of artifacts or evidence demonstrating what one knows and can do. Implementation: In engineering and computer science, the practical application of a methodology or algorithm to fulfill a desired purpose. Pedagogy: The art or science of teaching. Pedagogy is also sometimes referred to as the correct use of teaching strategies (see instructional theory). Personal Development Planning: A structured process undertaken by the individual to re-

flect upon their own learning performance and/or achievement, to support personal, educational, and career development. In an ideal world, students’ would be enabled to enhance achievement through reflection on current attainment, make strategic decisions based on their strengths and weaknesses, and ‘evidence’ their learning processes.

endnotes 1 2 3

4

5

6 7 8

9 10 11 12 13 14

15 16 17

18

http://e-learning.surf.nl/portfolio http://www.surf.nl http://www.surf.nl/en/projecten/index2. php?oid=62 http://www.du.nl/portfolioimplementatie (an English version of this Web site is in preparation) The SURF SiX Special Interest Group is very active in this field of standards. http://elearning.surf.nl/six http://www.concord-usa.com http://www.theospi.org http://video.surfnet.nl/info/webstroom/ home.jsp http://e-learning.surf.nl/six http://e-learning.surf.nl/portfolio http://www.apolloplatform.nl http://www.emerge.nl http://www.du.nl http://www.cinop.nl/projecten/platform portfolio/Default.asp http://www.alt.ac.uk http://www.ilta.net http://www.qwiki.info/projects/Europortfolio/epicc http://www.jisc.ac.uk

This work was previously published in the Handbook of Research on ePortfolios, edited by A. Jafari, pp. 358-369, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.23

ICT in Medical Education in Trinidad and Tobago Marilyn Lewis The University of the West Indies, Trinidad and Tobago

IntroductIon And bAcKground Information and communication technology (ICT) allows users to access information without taking geographic position into account. These users are also unconstrained by time, volume, or format of the information. ICT applications have enormous potential as a tool for aiding development in countries such as Trinidad and Tobago. Telemedicine, which can provide medical services to persons in isolated places, in emergencies, to the homebound, or the physically challenged, is but one example. Mansell and Wehn de Montalvo (1998) noted that “ICT applications facilitate telemedicine” (p. 85), and that “economic development can be fostered by tele-working and tele-services in some developing countries” (p. 83). The twin-island nation of Trinidad and Tobago lies at the southern end of the Caribbean chain of islands, approximately seven miles off the north-

east coast of Venezuela. The area covers 1,864 square miles (5,128 sq. km.), with a population of approximately 1.5 million. The economy of this small nation state is based mainly on petroleum and gas-based industries, but there is a growing service sector. PAHO figures (2002a, b) show a highly literate population with an overall adult literacy rate of 98.5% (males at 99.1% and females at 97.9%). Transshipment and telecommunications facilities contribute to this country’s position as the most industrialized in the Caribbean. The country’s technical capacity and access to information have grown enormously in recent years. Telecommunication tools extend to the vast majority of the population. Per capita GDP stands at US$8,500. There is a shortage of medical staff in general, with the ratio of doctors to inhabitants at 7.5 per 10,000. Shortages in primary health care are more acute than in other areas and have re-

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ICT in Medical Education in Trinidad and Tobago

sulted in the employment of retired nurses and the recruitment of professional staff from other countries, particularly from Nigeria, India, and more recently, from Cuba. Trinidad and Tobago therefore stands poised to benefit from further development by fully embracing ICT, especially in the areas of education and medicine.

MedIcAL educAtIon In trInIdAd And tobAgo Medical education in Trinidad and Tobago engenders self-directed, lifelong learning through the use of the problem-based learning (PBL) method of teaching. The Faculty of Medical Sciences (FMS) of the University of the West Indies opened in St. Augustine, Trinidad and Tobago, in 1989, and has utilized PBL from its inception. Students’ relative independence has been noted (Donner & Bickley, 1993) in students following PBL programs. Donner and Bickley noted that “they differ markedly from those following traditional medical programmes… [becoming] more skilled at an eclectic style of learning” (p. 297). These students show particular personal characteristics that encourage them to take a proactive role in their own learning, making them lifelong learners. Research has also shown that PBL students make maximum use of library resources and that librarians taught the use of technology as a means of accessing, organizing, and managing information (Marshall, 1993). Library instruction is therefore a required part of the curriculum. Librarians become not just providers of books and other materials but also instructors in the use of modern technology. The library, therefore, prepares medical students for wider use of other applications and technologies to support their future information needs. This has implications for how these students will operate when faced with adverse conditions such as rural health offices and hospitals with limited resources, and for

development in the community generally; these students in their homes, in their practices, and in the wider community will generate a multiplier effect.

InstructIons In the use oF Modern technoLogIes In the MsL From its inception, the Medical Sciences Library (MSL) has embarked on a program of information literacy for undergraduates and other categories of users. From as early as 1993, topics such as “MEDLINE: basic and advanced”; “International Pharmaceutical Abstracts (IPA)”; “MedCarib—health literature for the Caribbean”; “ProCite”; “Introduction to Computers”; and later, “EPI Info”; “Introduction to the Internet” and “PubMed” have been taught. In facilitating this training, the library equips its clientele with survival skills for the 21st century. The Trinidad and Tobago Ministry of Health also recognized a need for retraining, because new demands were being placed on practitioners by health care transition, health care reforms, increased public and patient expectations, and advances in medical sciences and technology. The Ministry found that medical practitioners required additional skills. This was part of the rationale for the introduction in 2000 of a new postgraduate diploma in Primary Care and Family Medicine being offered by dual mode, face-to face initially, and thereafter, through distance education. The library component of this course focused on skills such as “Locating and evaluating health information”; “Skills base for managing health information resources”; “Innovations in health information practice”; “Effective search and retrieval principles”; “MEDLINE on the Internet”; “Finding biomedical information on the Internet”; “Evaluating information resources”; and “Managing bibliographic references”. Assessment tasks included:

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ICT in Medical Education in Trinidad and Tobago

• • • • • •

Joining and leaving an electronic discussion group Subscribing and unsubscribing to a mailing list Posting to a discussion group Locating an electronic serial and printing an article or abstract Executing a search on MEDLINE or PubMed and printing the results Creating a small database and generating a bibliography

Each session represented distinct skills requirements and supported the utilization of applications to manage the efficient exchange of information among health professionals.

Ict In educAtIon: PrIMAry, secondAry, And tertIAry Primary and secondary schools in Trinidad and Tobago are also embracing the technology. Many secondary schools have computer science as a subject on the curriculum and typically have computer laboratories. More than 35% of the 78 primary and 120 secondary schools listed in the telephone directory for 2003–2004 have computers with Internet access facilitated by Telecommunication Services of Trinidad and Tobago (TSTT), the only telephone company on the twin islands. Additionally, there are 22 Internet cafes listed in the yellow pages of this directory. Some of these Internet cafes are located in rural areas such as Enterprise, in Central Trinidad, and Penal in the south of the island. Eighteen Internet Service Providers are listed as well. Other initiatives to produce a computer literate society in Trinidad and Tobago include the government making computer loans available to all public servants. In 2002, the government also launched an initiative, the National Information and Communications Technology Plan (2004), that aims “to connect people, communities, busi-

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ness, government and educational institutions through an integrated technology network. It will also examine the policy, financial and skills development requirements that will be necessary to ensure sustainability and to ensure that the benefits of connectivity continue to grow, and accelerate, as new technologies, innovation and thinking emerge.” A survey (NIHERST, 2002) designed to provide empirical data on the penetration of ICT in private households reflects the varying penetration of ICT in private homes of varying socioeconomic status. Data were collected from a representative sample of 2,812 households throughout Trinidad and Tobago. Thirteen percent (13%) of the households in Trinidad and Tobago (approximately 44,600 households based on national statistics for 2000) had a home computer as of June 2001. By comparison, more than 30% of the households in a number of Organisation for Economic Cooperation and Development (OECD) countries were equipped with computers in 1997, and more than half (54%) of the households in Australia had computers in May 2000. Other important findings of the survey were that affordability was the major constraint in 56% of all households without computers; ranging from 43.9% in the City of Port of Spain to 78% in the Borough of Point Fortin. Also, 53% of households purchased computers from private savings; 13% accessed government loans. Households (20%) with gross monthly incomes of $6,000–$7,999 had the largest proportion of home computers, followed by 15% of households with incomes of $4,000–$5,999. Only 5% of households with monthly incomes of less than $2,000 had computers. In 2000, 27% of the computers were acquired compared with 6.7% in 1997. Almost three out of four persons (73%) in each household used the computer. The proportion of male (51%) to female (49%) computer users was generally similar. Approximately 16.6% of computer users were between 15 and 19 years of age, 16.3% between 30 and 39 years and 14.5% between 40 and 49 years. Of computer users, 50%

ICT in Medical Education in Trinidad and Tobago

had acquired secondary level education, and only 3.8% had a university level education in computer studies. Approximately 50% of computer users were employed and self-employed, and 39% were students. In private enterprises, 59.8% of employees used the computer compared with 29.7% in government. Windows 98 and 95 were the main operating systems in 74.4% of households. Most households (70.8%) used the computer daily between two and five or more hours. Only 11.8% of households were engaged in software development, and 20.2% accessed distance learning/education compared with other activities such as games (78.4%), Microsoft Office (66%), e-mail (62.4%), and Web searches (61.5%). Apart from the Faculty of Medical Sciences, the university as a whole is also involved in programs to implement ICT applications. The UWI, St. Augustine, in its latest strategic plan (2003–2007) identified student-centeredness as one of its strategic objectives. The campus libraries, of which the MSL is a branch, determined that promoting the use of ICT in delivery of service and products was one way of meeting this objective. Additionally, an increasingly complex print and digital environment was emerging, and people began to expect certain services without coming to the library. Facilitated by the technology, the libraries were able to accomplish one of their main missions by launching a valuable new campuswide online course, “Foundations of Information Literacy” on March 2, 2004. It is a modular course covering the following seven topics: 1. 2. 3. 4. 5. 6. 7.

Basic computer literacy Basic research skills Using the OPAC (online public access catalogue) The Internet as a research tool West Indiana and Special Collections Online databases Managing references

There were tutorials on how to use each of the databases to which the libraries subscribe, as well as a quiz and online feedback, discussion board, and on-campus WebCT server. In its quest to keep abreast of technology, the St. Augustine campus libraries is looking at further ways to implement applications in ICT in its ongoing program of work. Initiatives such as a digital reference service are also being considered. This project aims to answer students’ reference queries in real time and will enable persons needing live human assistance while using the Web to immediately get the help they need from librarians who can quickly provide the answers. Speed and responsiveness are critical to this initiative, which will radically change the way we serve and support our clientele.

A tooL For coMMunIty deveLoPMent Based on our epidemiological circumstances, where the Caribbean is second only to Southern Africa in the proliferation of HIV/AIDS and other STDs, ICT can indeed be seen as an effective tool for development. The toll of HIV/AIDS is heaviest on young persons between the ages of 18 and 45, who form the majority of the workforce. CAREC figures indicate that in Trinidad and Tobago, 5,000 persons have died of AIDS since 1985. The nature of the response to these diseases has to do with preventive education, capacity building, and treatment, care, and support. ICT can play a role in the way people connect with information. Through ICT, people in remote areas can have access to the same information as many of the people in developed countries. With an infusion of ICT learning, people in underdeveloped countries such as Trinidad and Tobago can access and share critical health information that can help in the fight against HIV and AIDS, and its related morbidity and mortality. Ideally, health

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education should begin in primary schools. When this occurs, the transformative nature of ICT on the epidemiological status of affected countries can become visible.

concLusIon The type of medical education available in Trinidad and Tobago, the campus libraries’ program of instruction in the use of ICT, the government’s initiatives to make computers available to public servants, the provision of computers in primary and secondary schools, the burgeoning economy, and the developing infrastructure all signal that this country is capable of embracing fully ICT applications that can enhance community development. Additionally, the postgraduate course has been viewed as an investment in the health care of Trinidad and Tobago nationals, in terms of an enhanced quality of health care that will be rendered by the practitioners involved. Healthy individuals contribute to a more productive economy. The course is ongoing, therefore, there will need to be an increment to those receiving training, as well as those receiving enhanced care. Three further cycles of the postgraduate course have been held, resulting in at least 60 primary care physicians who have already been exposed to and benefited from the postgraduate training provided by the MSL. By teaching the core competencies of information literacy, identifying the information needs, accessing information, and understanding the legal and other issues in the use of information, the St. Augustine campus libraries aim first to increase the competitiveness of the student. However, not only have the libraries supported the academic enterprise, but they have also made available resources for knowledge creation and capacity building. At the Medical Sciences Library, we assisted in the retraining of primary care physicians to make them comfortable with

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the new technologies. This has resulted in more effective, efficient high-quality health care for the national community and has contributed to development. Today’s information consumer wants seamless access whenever and wherever they want it. They are comfortable with Web-based information. In this complex and rapidly changing, increasingly interconnected environment, ICT can be an effective tool for community development.

reFerences Donner, R. S., & Bickley, H. (1993). Problembased learning in American medical education: An overview. Bulletin of the Medical Library Association, 81(3), 294-298. FOLDOC. (2004). Free online dictionary of computing. Retrieved September 27, 2004, from http://foldoc.doc.ic. ac.uk/foldoc/index.html Mansell, R., & Wehn de Montalvo, U. (1998). Knowledge societies information technology for sustainable development. Oxford: United Nations Commission on Science and Technology for Development/Oxford UP. Marshall, J. G., Fitzgerald, D., Busby, L., & Heaton, G. (1993). A study of library use in problem-based and traditional medical curricula. Bulletin of the Medical Library Association, 81(3), 299-305. National Institute of Higher Education Research Science and Technology. (2002). Utilisation of information technology by households, 2001. NIHERST: Port of Spain. Pan American Health Organization. (2002a). Country health profiles. Retrieved September 25, 2004, from http://www.google.tt/search?q=cac he:YxVT NV_AD20J: www.paho.org/english/ HIA1998/Trinidad.pdf+ trinidad+ and+toba go+doctor+p atient+ratio&hl=en

ICT in Medical Education in Trinidad and Tobago

Pan American Health Organization. (2002b). Promoting health in the Americas. Retrieved September 22, 2004, from http://www.paho. org/english/dd/ais/cp_780.htm [Trinidad and Tobago] Ministry of Public Administration and Information [home page]. (2004). National Information and Communication Technology Plan. Retrieved September 27, 2004, from http://www.nict.gov.tt/plan/documents/summary.asp

Key terMs Digital Reference Service: A human-mediated, Internet-based service in which users’ queries are answered in real time. Discussion Group: Any system that supports group messaging, e.g., a shared mailbox, Usenet, bulletin board system, or possibly a mailing list, used to publish messages on some particular topic (FOLDOC, 2004). Information Communications Technology (ICT): The study of the technology used to handle information and aid communication. The phrase was coined by Stevenson in his 1997 report to the UK government and promoted by the new National Curriculum documents for the UK in 2000 (FOLDOC, 2004). Listserv: An automatic mailing list server, initially written to run under IBM’s VM operating system by Eric Thomas. Listserv is a user name on some computers on BITNET/EARN which

processes e-mail requests for addition to or deletion from mailing lists. Examples are listserv@ ucsd.edu, [email protected]. Some listservs provide other facilities such as retrieving files from archives and searching databases. Full details of available services can usually be obtained by sending a message with the word HELP in the subject and body to the listserv address. Eric Thomas has recently formed an international corporation, L-Soft, and has ported Listserv to a number of other platforms including Unix. Listserv has simultaneously been enhanced to use both the Internet and BITNET. Two other major mailing list processors, both of which run under Unix, are Majordomo, a freeware system, and Listproc, currently owned and developed by BITNET (FOLDOC, 2004). MedCarib: A database of the health literature of the Caribbean. MEDLINE: A CD-ROM database of medical literature in journals produced by the National Library of Medicine, United States. Problem-Based Learning (PBL): A concept in which students focus from the beginning of their course on a series of real professional issues, where the knowledge of the various academic disciplines that relate to these issues is integrated. PubMed: An online database of over 14 million citations of biomedical articles from 1950 to the present time. This database is available free over the Internet. WebCT: Software that provides electronic learning in a flexible integrated environment.

This work was previously published in the Encyclopedia of Developing Regional Communities with Information and Communication Technology, edited by S. Marshall, W. Taylor, and X.Yu, pp. 1-28, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.24

ICT, Education, and Regional Development in Swiss Peripheral Areas Chiara Giorgi Università della Svizzera Italiana (USI), Switzerland Dieter Schürch Università della Svizzera Italiana (USI), Switzerland

INTRODUCTION Since the end of 20th Century, the introduction of Information and Communication Technologies (ICT) has deeply influenced many aspects of everyday life, leading to the creation of new meanings for the traditional concepts of identity, culture, economy and, above all, communication (Mantovani, 1995; Perriault, 1989; Rullani, 2002). Trends about technological development show how, in the next years, the change will gradually concern all elementary daily actions, due to spreading of the electronic devices in the environment (OCDE, 2002; Saracco, 2003). If ICT will be ever more deeply-rooted in our reality, how fast will they consequently influence our socio-cultural identity? What sort of consequences do we have to imagine at economic level? What variety of scenarios can we draw about our future?

And, above all, how will the concept of development change? If on the one hand the global trend seems to lead towards a reality without any kind of borders, on the other one the political and cultural centres are privileged in taking advantage of the opportunities opened by ICT. Therefore, peripheral areas1 run the risk of becoming more and more isolated and excluded from the innovation process. Is it possible to reverse this tendency by using ICT as developmental devices? Can we re-direct the attention on those areas that seem to be “dead” regions? And in what way?

BACKGROUND The relationship between communication and regional development has deeply influenced the

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ICT, Education, and Regional Development in Swiss Peripheral Areas

fate of a great number of geographical areas; examples are the building of railways, of roads and fluvial connections. If and in what way can the CmC2 be considered a factor, parallel to those we have mentioned, to open new opportunities for peripheral regions? The rapid spread of communication networks—ignoring the presence of natural and political boundaries—is changing the economic and social scenarios. In this context, new kinds of “regions” are emerging, the so-called “learning regions” (Florida, 1995). They are characterized by a system in which communication networks and data processing work give both shape and substance to connections between public institutions (such as schools and universities) and private institutions (firms), this leading to generate new knowledge and productiveness. In Switzerland, a country characterized by a strong multicultural and multilingual tradition (above all in valleys of alpine regions), the creation of a new idea of “region” meets several kinds of dissensions. There are a lot of questions about the way to get over mental and cultural borders (see Arnaud & Perriault, 2002; Bressaud & Dirtler, 2003; Calvo, Ciotti, Roncaglia & Zela, 1998). The behavioural changes always continue in daily action, and the action always places itself in a human, social, geographical, cultural and economic territory (Brown, Collins & Duguid, 1989). The use of communication devices can’t escape this rule, because they’ve got a sense if they can be interpreted and situated by the people who live in that particular area (Galimberti & Riva, 1997). The process of interpretation of these devices had to consider, on the one hand, the starting of forms of “unlearning” (Grabher, 1993), and on the other one the building of a different nature of the concept of territory that has to be identified and tested (Delai & Marcantoni, 1992).

regIonAL deveLoPMent In swIss PerIPherAL AreAs situation in Peripheral sub-Alpine regions Swiss reality is characterized by fragmentation at several levels. From a geographical perspective, the mountainous territorial morphology creates several natural partitions, causing the isolation of some areas and particularly those distributed along the Alpine chain. Besides, the Swiss Confederation is a set of 26 political Cantons, each of these having its own administrative independence even if partial, and with four official languages3. At a deeper level, the fragmentation is perceived as socio-cultural complexity: geographical and political configurations, in fact, don’t correspond to an unequivocal identity; very often different cultural and language realities—including dialects - are present on the same territory, giving it a cross cultural profile4. The process of globalisation over the last decade has led to the trend of concentring the power in the centres, namely those places having infrastructures and accessibility to innovation, and so to choose a developmental way. These centres become the reference point for all the relevant activities. These are the “places of the knowledge,” the places where people decide the future trends of development, definitely the places that the peripheral regions “gravitate around.” From this perspective, the break between central and peripheral areas becomes even more perceivable. Peripheral regions seem to have neither any kind of power about their future development, nor interesting elements making them recognizable as “cultural regions.” If this trend is observed at a general level, now it has repercussions also on Swiss Confederation, European symbol of a perfect integration between different cultures and ethnic groups.

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What is actually going on in these regions, often coincident with valleys? First of all, it is important to point out the trend of native people moving out from the territory, frequently youth, to find a better working perspective just in the centres. This leads, obviously, to a progressive death of the local economy and working activities. The economic sphere, anyway, can’t be separate by the question regarding education, in which the working world is deeply-rooted. If this movement from the regions begins in the young age, it’s necessary to understand the reason underlying that. During the period of education, the young decide to abandon his/her own place of origin to look for better education and training opportunities. In some cases, the young have no other choice. This problem is strongly felt about vocational training, that represents a relevant portion of educational system: more than 60% of young people, in the age of secondary education, choose the way of apprenticeship. Swiss apprenticeship is based on the dual vocational system coming from the German tradition. Apprentices work in a company or small firm and at the same time attend Vocational School. The dual system spans over the whole training period, up to four years, thus insuring the connection between school and education and the working world. What happens in remote regions? Vocational Schools collect different professional trainings and are often dislocated far away. The apprentice is forced to leave his native territory during the week to move to the place where he can study and carry on his/her apprenticeship in a firm. This situation of eradication from the native territory leads the young to a progressive loss of his/her own socio-cultural identity, to get hold of the place he/she will study or work. Finally, we have to face a sociological problem: the development of a negative mentality. If valleys are characterized by the elements mentioned before, the young person—but not only our youth—is led to relate his/her native region with lack of real opportunities for the future, and definitely not to recognize any chance of development.

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What long-term consequences can we imagine for the increasingly isolated valleys? How is it possible to intervene, so as to change this vision about the future? Can the introduction of ICT change this situation?

swiss regional development Since 1995, Swiss peripheral zones of sub-alpine arch (see Figure 1) are involved in projects of regional development, based on the conviction that changes take place not simply by giving direct financial support, but by setting up educational and training devices, to achieve a revaluation of these regions as characterized by their owns specific social, cultural and economic values and so to allow them to survive both on the identity level and the economic one.

Poschiavo Project: A Pilot Project The pilot project, Progetto Poschiavo5, started in 1995 involving the area of Poschiavo Valley, a region of the Grisons Canton at the boundaries with Italy, speaking Italian, German and Romansh. The aims of the project were both the revaluation of the cultural and linguistic reality by a human ecology approach6, and the realization of a communication network that allows a cultural exchange not only within Poschiavo region, but also between this territory and the centres, to promote a reversal of the tendency towards isolation. From a practical point of view, the project followed a regional development strategy founded on the direct involvement of the local people. After an initial contact with local institutions, a group of people was trained to take the role of Practice Assistant in Distance-Education (APFD)7, to accompany the local population in project of territorial development. In this sense, it was important that APFD were native people, to avoid any hindrance to the developmental process itself. The second step was the setting up of project groups (composed of local people and

ICT, Education, and Regional Development in Swiss Peripheral Areas

Figure 1. Swiss peripheral territories involved in projects of regional development

accompanied by an APFD) and the introduction of Information and Communication Technologies. During this period, participants acquired both the means to “read” the territory through a human ecology approach and the necessary know-how to use ICT. The project groups took the role of connection between the valley and the centres. Finally, in a consolidation phase, project groups began a more operative and practical work, involving in their activities the whole population and local Institutions. Nowadays, we can observe a new trend for Poschiavo Valley, characterized by a consciousness about the value of its own cultural identity, a new esteem of the role of education in processes of regional development, a consolidated trend to self-entrepreneurship and a resumption of economic vitality. A simple example is represented by Polo Poschiavo: a body born from the pilot project, now institutionally recognized as a reference point for the development of the region, that is the promoter and responsible for some training projects in the valley. The progress of the Poschiavo Project and the relapses of the project itself (Rieder, Giuliani &

Schürch, 2000; Schürch, 1999, 2000), show how it is possible to achieve concrete regional development, without betraying the region’s historical and geographical roots, to satisfy the demands of the present time and create innovative scenarios for future years.

movingAlps Project In 2000, these outcomes lead to the birth of the movingAlps Project8, based on Progetto Poschiavo experience and representing its natural consequence. If the old Poschiavo Project focused on a limited area, movingAlps extends its action field to all the peripheral regions of the sub-alpine arch at the boundaries with Italy. movingAlps tries to work out and to practice a regional development model that may represent both a rediscovery of the peripheral areas as characterized by specific elements and a chance to increase the values of these areas themselves. To allow the isolated regions to identify and develop opportunities that may be synonymous of social and cultural identity survival9, movingAlps chooses to start moving from local people project

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ideas. This implies an analysis of the ground and of people expectations and representations about their future. Financial support is given only in a second time. By this strategy, the developing process not only fits the demands of the region, but it’s shared by the involved people. This also allows the creation, step by step, of a new vision about the opportunity to act on and modify the current situation going towards a better one. The process of development is then characterized by a steady and progressive adaptation of the project to consider and to include the unexpected elements rising up from the territory and people living in. In conclusion, movingAlps aims to: 1.

2.

Perform a change of social perceptions, allowing a gradual and progressive re-appropriation of entrepreneurial, working and formative culture that finds its origins and nourishment in the region itself Overturn the relationship between centres and peripheral areas, to reverse a process of progressive isolation of the peripheral zones as regards to the centres, and to reach a joint and mutual exchange of knowledge and culture

the role of Ict How to achieve this reversal of relationship between centres and peripheral regions? In this developmental approach, the introduction of Information and Communication Technologies (ICT) can play a central role, both by making easier the involvement of the isolated zones in the intercultural exchange typical of the global village and by supporting a push towards innovation and development. To overcome temporal and spatial barriers by ICT means the establishment of continuity and interchange relationships between centres and peripheral areas. ICT enables the onset of a process of de-centralization of knowledge, by

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offering the opportunity of training “in situ” that may emphasize the value of the cultural traditions of the territory which people belong to. From another perspective, this process leads to a renewal and updates the knowledge and skills acquired over the formative itinerary (Schürch, 2004). Education and its links with the economic and working spheres have obviously to be considered as the key-points from which development becomes possible. ICT, in this sense, provide access to a kind of knowledge that is typical of the information age and that’s becoming the base enabling participants to act and work in the future daily life.

education and Ict in movingAlps Project: A concrete Micro-example A concrete example of regional development with the help of ICT is represented by a project10 involving the vocational school of Samaden, in Bregaglia Valley, and in particular a class of bricklayer apprentices living in various dispersed locations in the valley. As mentioned previously, apprentices are forced to leave their villages to reach the place of study and carry on their apprenticeship. Often this situation leads to migration to these centres and consequently to an abandonment of the native valley. On the other hand, a series of studies in Bregaglia Valley11 have pointed out how it is characterized by the presence of multiple diversified sectors of production, covering the entire outline of traditional regional activities. This means a working reality that is still alive, at least at a potential level. The question is: how to meet young people’s demands and to rebirth the local economy? The way chosen by movingAlps-Bregaglia was to develop a net of collaborations between educational bodies and private firms by using ICT, to allow the apprentices to study without leaving their locations in the valley. This should lead, on one hand, to creating the necessary conditions

ICT, Education, and Regional Development in Swiss Peripheral Areas

to encourage the introduction of young people in the local working activities, but also lead to a renewal of the professions based on the new approaches brought in by the apprentice who has learnt to use ICT. The experience of Progetto Muratori, started in May 2002 and stopped in June 2003, has given the opportunity to a group of 12 bricklayer apprentices to attend courses in General Studies and in Professional Knowledge in a blended-learning form12. The course ran from December 2002 to May 2003, and took the form of three three-week distance sessions alternated with periods of classroom-based learning. Over the distance-learning phase, communication and interaction between apprentices, teachers and the other people involved in the project has been secured by a virtual learning environment (Giorgi & Schürch, 2004). This experience shows, at several levels, what are the opportunities arising from a territorial intervention. Briefly, it has lead to: 1.

2.

3.

4.

Overcoming the problem of spatial and temporal distances—by the use of technology—leading to apprentices having wider accessibility to training and to knowledge in general; Moving from a vocational training based on the culture of the “places of knowledge” towards an education founded on the values and on the identity characteristics of the native region; The development of a training system preparing young people to face changes due to the introduction of ICT in professional world, by integrating them within the formative itinerary; and The development of the necessary basis for a revaluation of vocational training and of professional activities within Bregaglia Valley, and an input towards innovation.

concLusIon Regional development goes through both the revaluation of the culture and of the regional identity, and education and training in a large sense. To be effective, this process has to occur at different levels; some can be considered at micro-levels (as in the case of Progetto Muratori, focused on a limited target), others regard wider spheres such as the projects of territorial development considered as a whole. Sharing of future sceneries and collaboration between institutions and local people are central elements for development that becomes possible. Information and Communication Technologies offer interesting tools for the revaluation of peripheral areas own identity, introducing at the same time a wave of innovation. It’s not a question of assimilating a particular territory to defined standards but instead to make the innovation a means to give a new value to the culture, economy and local identity. However a question still remains open: Is it possible to define a model of regional development, integrating ICT, that is flexible enough to be adapted and transferable to every territory? Furthermore, can such a model be characterized by a defined structure of functioning?

reFerences Arnaud, M., & Perriault, J. (2002). Les espaces publics d’accès à internet. Paris: PUF. Bressaud, A., & Dirtler, C. (2003). Il tempo dell’economia: Collisione di orizzonti o carenze negoziate? In D. De Kerkhove (Ed.), La conquista del tempo (pp. 61-74). Roma: Editori Riuniti. Brown, J.S., Collins, A., & Duguid, P. (1989). Situated learning and the culture of learning. Educational Researcher, 18(1), 32-42.

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Calvo, M., Ciotti, F., Roncaglia, G., & Zela, M.A. (1998). Internet ’98. Bari: Laterza. Delai, N., & Marcantoni, M. (1992). Il giusto confine. Milano: Il Sole 24 Ore. Florida, R. (1995). Toward the learning region. Futures, 27, 527-536. Galimberti, C., & Riva, G. (1997). La comunicazione virtuale. Milano: Guerini e Associati. Giorgi, C., & Schürch, D. (2004). Distance learning: A dimension without presence? In H.M. Niegemann, D. Leutner, & R. Brünken (Eds.), Instructional design for multimedia learning. Proceedings of the 5th International Workshop of SIG 6 Instructional Design of the European Association for Research on Learning and Instruction (EARLI), June 27-29, 2002 in Erfurt (pp. 223-236). Münster, New York: Waxmann. Grabher, G. (1993). The weakness of strong ties: The lock-in of regional development in the Ruhr area. In G. Grabher (Ed.), The embedded firm: On the socio-economics of industrial networks. London: Routledge. Mantovani, G. (1995). Comunicazione e identità. Bologna: Il Mulino. OCDE. (2002). Science, technologie et industrie: Perspecitves de l’OCDE 2002. Québec: Publications Gouvernementales 2002-2004. Perriault, J. (1989). La logique de l’usage. Essai sur les machines à communiquer. Paris: Flammarion. Rieder, P., Giuliani, G., & Schürch, D. (2000). Identità e sviluppo delle regioni dell’arco sud alpino: Un progetto di educazione innovativa che fa capo anche alla comunicazione Mediata da Computer per offrire ai giovani nuove opportunità di lavoro. Lugano: Istituto Svizzero di Pedagogia per la Formazione Professionale.

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Rullani, E. (2002). Innovazione e complessità. In G. Ardrizzo (Ed.), Ragioni di Confine. Bologna: Il Mulino. Saracco, R. (2003, September). Ubiquitous Computing. Mondo Digitale, 7, 19-30. Retrieved May 25, 2004, from http://www.mondodigitale.net/ Rivista/03_numero_tre/Saracco_ p.19-30.pdf Schürch, D. (1999). L’esperienza del Progetto Poschiavo. Proceedings of the Conference of Società Economica Valtellinese “Lavoro, formazione e imprenditorialità in Provincia di Sondrio” (pp.128-135). Milano: Franco Angeli. Schürch, D. (2000). Verso una pedagogia dello sviluppo territoriale: Il Progetto Poschiavo. In P.L. Amietta (Ed.), I luoghi dell’apprendimento (pp. 83-122). Milano: Franco Angeli. Schürch, D. (2004). Nouvelles technologies et valeurs de l’éducation – réflexion épistémologique. In M. Gather-Thurler & J.P. Bronckart (Eds.), Transfomer l’école (pp. 169-191). Bruxelles: De Boeck.

Key terMs Developing Project: Creation of a small group of people that work on an existing problematic theme and design solutions where Information and Communication Technologies make sense. Human Ecology: In a holistic vision of the environment, human ecology is an approach to read changes and transformation in action; a way of integration of history, culture and work in peripheral regions in a communicative and distance-exchange perspective; a tool for creating conditions for sustainable development. Information and Communication Technologies: Technology referring to IDP systems; examples include the Internet, videoconferencing, videostreaming, text-editing, robotics, productive processes automation, etc.

ICT, Education, and Regional Development in Swiss Peripheral Areas

Peripheral Regions: Geographical areas characterized by a particular territorial morphology that causes the isolation from bordering zones inhabited by a linguistic and cultural identity minority. Areas cut off from economic and cultural development. Regional Development: The notion of development that has been recently better defined with the concept of “learning region” (“regionalità apprendente”) that suggests the existance of a dynamic net of relationships among different activity sectors (economic, administrative, educational and cultural) of a region. It is thought that education and training represent the central device of such development.

6

7

Regional Edentity: Is a linguistic and cultural concept linked to the feeling of belonging shown by the inhabitants.

endnotes 1 2 3

4

5

For example, mountainous zones. Computer-mediated-Communication. These are: French, German, Italian and Romansh. For instance, in some areas of the Grison Canton, which is open to Italy and where Italian is spoken, we can perceive that, although politically belonging to Switzerland cultural traditions are strongly rooted in Italian culture. Progetto Poschiavo is born from the collaboration of Istituto Svizzero di Pedagogia per la Formazione Professionale (ISPFP) of Lugano, Cantons Ticino and Grisons, Jacobs Foundation, Progetto Poschiavo Foundation, Ufficio Federale per la Formazione e la

8

9

10 11

12

Tecnologia (UFFT), Swisscom, University of Svizzera Italiana of Lugano, University of Ginevra, University of Neuchâtel and University of Bologna; web site: http://www. progetto-poschiavo.ch. The concept of “human ecology” refers to the environment in a global sense, originated by the consideration of all its components and where the human being has an important role. The APFD, or Assistente di Pratica in Formazione a Distanza was a new professional category created within the ISPFP of Lugano; their role is to accompany groups of development projects, offering both technical and pedagogical assistance, sometimes at a distance but mainly face-to-face. The particular characteristic of the APFD, however, is that they originate in the same regions as the people themselves, and so share the same socio-cultural background as the people they are working with. As Progetto Poschiavo, movingAlps derives from the collaboration of Istituto Svizzero di Pedagogia per la Formazione Professionale (ISPFP) of Lugano, Cantons Ticino and Grisons, Jacobs Foundation, Progetto Poschiavo Foundation, Ufficio Federale per la Formazione e la Tecnologia (UFFT), Swisscom, University of Svizzera Italiana of Lugano, University of Ginevra, University of Neuchâtel and University of Bologna; Web site: http://www.moving alps.ch. Obviously, in a sense of multi-culture and multilingualism survival. That is Progetto Muratori. The studies were carried out by ISPFP-Lugano and Politecnico Federale of Zurigo. Either face-to-face or through ICT-based distance learning.

This work was previously published in the Encyclopedia of Developing Regional Communities with Information and Communication Technology, edited by S. Marshall, W. Taylor, and X Yu, pp. 393-398, copyright 2006 by Idea Group Reference (an imprint of IGI Global). 2093

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Chapter 4.25

Applications of Agent-Based Technologies in Smart Organizations László Zsolt Varga Hungarian Academy of Sciences, Hungary

AbstrAct This chapter introduces agent technology as a means of creating dynamic software systems for the changing needs of smart organizations. The notion of agency is introduced, and individual and collective agent architectures are described. Agent interaction methods and agent system design techniques are discussed. Application areas of agent technology are overviewed. The chapter argues that the autonomous and proactive nature of agent systems make them suitable as the new information infrastructure for the networked components of dynamically changing smart organizations.

IntroductIon

to the Internet, then it has serious competitive drawbacks. Private persons are using the Internet more and more as well, so organizations keep contact with their clients through e-mail and give them information on their products and services on information portals. Customers can do the shopping in electronic shops and get all the information they want from the portal server; they can even configure the product they want to order. In order to satisfy individual needs, smart organizations must feed online information from the Internet into their internal information system and then further to their internal production control, accounting, design, resource planning, and several other components. The organization can adapt to these requirements only if it requires the same type of information management from its suppliers, so the interorganizational com-

Nowadays the whole world is networked into the Internet and if an organization is not connected Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Applications of Agent-Based Technologies in Smart Organizations

munication must become part of this networked environment as well. In this environment, we can less and less talk about individual software products, because software components are interconnected and sooner or later almost every software component must be capable to interoperate with other software systems. This way, the information system of smart organizations becomes part of the worldwide Internet, so individual solutions cannot be applied. The software technology of smart organizations means less and less the design and implementation of individual software systems; rather, we can talk about the development of the design and implementation of a single distributed worldwide information system. In this context, the designers of subsystems cannot apply individual solutions, they have to adapt to global practice and standards. At the time of the design of such a global information system, the designer does not have enough information and resources to make a complete solution, so the designed system must integrate into the worldwide system with the ability to adapt to unforeseen changes and requirements using incomplete information at run-time. Satisfying these requirements is among the goals of several technologies, including the Web services technology characterized by SOAP1, WSDL2, UDDI3 abbreviations (Web Services, 2004; UDDI, 2004), the semantic Web technology (Berners-Lee, Hendler, & Lassila, 2001), the grid (Foster & Kesselman, 1999) and maybe the most complete approach, which is agent-based computing (Wooldridge, 2002). This chapter presents the most important elements of agent technology and how they can be applied in smart organizations. First, we define what agents and agent systems are, then we overview the history of agent developments. We discuss the internal structures of agents, then how these agents can form smart organizations, then the methods of agent system analysis and design. Finally, we

discuss the applications of agent systems and the conditions of their wide adoption.

the Agent MetAPhor The word “agent” has different meanings in different contexts, so computer scientists working in the agent field may have somewhat different definitions of agency. There is agreement on the main characteristics, but some researchers consider other characteristics important as well, while some researchers think that these are not important, depending on their background.

Intelligent Agents The notion of agent emerged from many different fields, including economics, game theory, philosophy, logic, ecology, social sciences, computer science, artificial intelligence, and later distributed artificial intelligence. In all these fields, an agent is an active component that behaves intelligently in a complex environment to achieve some kind of goal. Artificial intelligence is the branch of computer science which investigates how to implement in computer systems intelligence comparable to human intelligence. While the goal of artificial intelligence focuses mainly on intelligent performance comparable to an individual person, distributed artificial intelligence investigates how a group of software components called agents can achieve intelligent behavior comparable to a group of persons. From a software technology point of view, agent technology promises to enable system designers to handle more complex systems than before. As systems become more and more complex, software development processes need higher and higher abstractions. In the beginning, functional and modular programming techniques provided enough level of abstraction, then objectoriented systems became the most commonly

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used technique to model complex systems. Agent technology promises to handle systems that objectoriented techniques cannot adequately model, like large, distributed organizations with incomplete information and distributed responsibility, where individual components must dynamically adapt to unforeseen changes. Experts from the different fields tend to agree that the most important characteristics of agents are those which are defined by Wooldridge and Jennings (1995) and shown in Figure 1. First of all, an agent is a computer system situated in some environment. The agent is reactive, which means that it is capable of sensing its environment and acting on it. The agent can autonomously act in its environment and make decisions itself. The agent has design objectives and can decide itself how to achieve them. While taking the decisions the agent is not just passive, but can take initiatives towards its goals. The agent has social abilities and can interact with the actors in its environment.

Agents as building blocks in smart organizations The above-mentioned characteristics make the agent concept an important element in model-

ing systems needed for smart organizations. First of all, multi-agent systems are distributed cooperative computing systems, therefore they themselves form an intelligent organization. The reactive, autonomous, and proactive features of agents require that they are knowledge-driven, dynamically adaptive, agile, and learning computing elements. The social abilities of agents mean that they are usually internetworked, as well as dynamically adaptive to new organizational forms and practices. Since these features are necessary for smart organizations, we can expect that software systems built with agent technology will play an important role in smart organizations. A multi-agent system itself can be regarded as a smart organization, because the above-mentioned characteristics are in line with the definition of smart organizations. The term “smart organization” is used for organizations that are knowledge-driven, internetworked, dynamically adaptive to new organizational forms and practices, learning, as well as agile in their ability to create and exploit the opportunities offered by the new economy (Filos & Banahan, 2000). In the following sections, we will discuss agent systems in order to be able to understand their importance for smart organizations. Agent

Figure 1. The most important characteristics of intelligent agents Social abilities

Agent

Design objectives

Sensor input

Action output Autonomous and proactive behavior

Environment

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Social abilities

Applications of Agent-Based Technologies in Smart Organizations

technology offers new techniques for smart organizations, but it cannot solve everything. Several design techniques and software tools have been developed to support and implement agent oriented systems. Although these techniques and tools allow the designer to think in the way an agent system needs, the major challenge in implementing agent systems is related to the intelligence of the agents.

of reactive and deliberative approaches was later replaced with the practical reasoning approach, where reasoning is influenced by a kind of mental state with three components: Beliefs, desires, and intentions, where beliefs represent the information that the agent has about its environment, desires represent the different possible states the agent may choose to commit to, and intentions represent the states the agent has chosen and committed resources to.

hIstory And stAndArds

the beginnings

Current interest in autonomous agents emerged mainly from artificial intelligence research, but object-oriented programming and human-computer interface design also contributed among the many other fields mentioned earlier. Although we could think that agency is central to artificial intelligence (AI), because AI is about building intelligent systems, artificial intelligence researchers did not intensively study intelligent agents until the 1980s. The focus of AI research was on the different components of intelligent behavior, like learning, reasoning, problem solving, and so forth. Among these independent investigations, AI planning was most closely related to agents, because AI planning is related to what and how to do, and agents also have to plan what they are going to perform autonomously in their environment. AI planning first used a symbolic reasoning approach, but when the ultimate viability of this approach was questioned, the attention of researchers turned toward behavioral or reactive AI. According to this approach, theorem provers cannot produce intelligent behavior; rather, intelligence is a product of the interaction between the intelligent system and its environment. In this approach, intelligence emerges from the interaction of several simpler behaviors and competing behaviors can suppress each other. However, emergence is purely reactive, so in the early 1990s researchers started to combine reactive behavior with the deliberative approach of symbolic reasoning. The combination

Agent research became a separate branch of AI in 1980 at the first Distributed Artificial Intelligence (DAI) workshop at the Massachusetts Institute of Technology, where participants decided that there is need to investigate issues of how intelligent problem solvers can coordinate their activities to solve common problems, and these issues are on a higher level than the parallelism issues of how to distribute processing over machines and parallelize centralized algorithms. The first multi-agent model was the actors model, in which self-contained, interactive components communicate by asynchronous message passing. Task allocation then became an important topic, and the Contract Net Protocol was defined to allocate tasks from the contractor to bidders through an announcement—bidding—allocation process. The early applications were related to the coordination of physically moving vehicles. Later, the research focused on teams working toward a common goal, and theoretical foundations of cooperation were investigated, including notions of commitment and joint intention. A group of agents jointly intends a team action if all of them are committed to completing the team action and they mutually believe that they are doing it. In this case, the joint commitment is a joint persistent goal. Agents enter into a joint commitment by establishing appropriate mutual beliefs and commitments through an exchange of request and confirm speech acts.

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The investigation of how to achieve joint commitment centered on the notion of negotiation. It turned out that negotiation was a good method for coordination, conflict resolution, communication of plan changes, task allocation, and resolution of constraints violations as well. The common characteristics of these are that agents have to resolve some conflict in a distributed way by exchanging proposals and counter proposals, the agents have their own goals, they have bounded rationality and incomplete information. At this time, agent architectures focused on the internal modules of agents and how the above-mentioned concepts can be handled with software engineering methods. Agents usually had five components: the communication layer, the agent acquaintance module, the self module, the inference engine, and the knowledge base. The communication layer was responsible for performing the necessary transformations on the messages the agent wanted to send and receive to and from its environment, in order that these messages conform to the external and the internal world of the agent. The agent acquaintance module contained information about the environment of the agent and modeled the capabilities of the agents to interact with. The self module contained information about the capabilities of the agent itself. The inference engine was responsible for executing the actions of the agent based on the knowledge of the agent stored in the knowledge base.

networked Agents In the 1990s, the Internet and hypertext protocol was spreading rapidly, and more and more applications were deployed on the Internet. This open environment gave way to the wide-spread application of software agents communicating over Internet protocols. Previously, multi-agent systems were designed and implemented usually by a single team, but now multi-agent systems from different backgrounds and design approaches

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had to communicate and interact. The most important issues in this environment are discovery and interoperability. Discovery is the problem of how agents can find each other even when they do not know anything about the other agent. Interoperability is the problem of understanding the syntax and semantics of the language of other agents, which means that agents have to be able to parse the message of other agents and find out the meaning of the elements of the messages. To solve the discovery issue in open environments, the notion of middle agents has been introduced. Agents can advertise their capabilities to some kind of middle agent. Different types of middle agents have been identified, including yellow page middle agents that match advertisements with requested capabilities, blackboard middle agents that collect requests, and broker middle agents that do both. Of course, this middle agent approach works only if agents know how to find the appropriate middle agent. In practice, this can be solved by having a few well-known middle agents, which preferably even talk with each other so that if there is no match at a specific middle agent, then the request can be forwarded to another one. These well-known middle agents form the basis of the infrastructure of an open agent environment. The first attempt for a world wide agent infrastructure was the Agentcities network (Willmott, Dale, Burg, Charlton, & O’Brien,2001). Solving agent interoperability is approached on two levels: on the agent communication language level and the agent content language level. The agent communication language defines the types and the format of the messages between agents. Agent communication languages provide a set of performatives, like “request” and “inform,” based on the speech acts theory (Searle, 1969), where communications are modeled as actions that change the mental state of communication participants. Using the agent communication language, an agent can send to another one a request for “something,” or can inform the other agent

Applications of Agent-Based Technologies in Smart Organizations

about “something,” where the “something” is the content of the message. The schema for the agent content language is the ontology which formally describes a domain of discourse. Agents can understand the content of the messages if they share their content language ontologies, preferably by publishing them on ontology servers. Ontology servers are also an important part of an open agent infrastructure like the Agentcities network (Willmott et al., 2001)

World Wide Web Consortium (W3C) and the Global Grid Forum (GGF), because developments such as Web Services (Web Services, 2004) and Semantic Web Services (DAML Services Coalition, 2002; Bussler, Maedche, & Fensel, 2002) also investigate many of the issues agent technologies have already addressed. Figure 2 summarizes the history and trends in agent research as discussed in this section.

standards and FIPA

Agent ArchItectures

The need for interoperable agent communication created the standardization body of agent systems, which is called Foundation for Intelligent Physical Agents (FIPA). FIPA was founded in 1996 and registered in Geneva, Switzerland as an international nonprofit organization. The aim of FIPA is to develop software standards for heterogeneous and interoperating agents and agent systems, in order to enable the interworking of agents and agent systems operating on platforms of different vendors in industrial and commercial environments. As a result of the FIPA standardization activity, many research labs and industrial organizations started to develop competing agent platforms independently all over the world. FIPA standard agent platforms provide an environment where agents can be deployed, and with the help of the agent platform services they can interact with other agents on any FIPA standard agent platform in a FIPA conformant way, achieving agent communication level interoperability. Agent platforms from more than 15 vendors show interoperability in the Agentcities testbed. More than half of the Agentcities nodes use the Jade agent platform from Telecom Italia Laboratories (Balboni, 2003). The most important agent standardization activities are done in FIPA, but significant activity was also carried out in the Object Management Group (OMG) and agent standards are starting to become highly relevant to bodies such as the

As we have seen in the previous section, the agent concept evolved over time. Different aspects of agency were discovered and in the end merged into the currently applied agent architectures. Nowadays, agents that show traits of only one aspect are not considered real intelligent agents. For example, a stock exchange trading agent in charge of a stop-loss order is a purely reactive agent, but does not satisfy the current notion of intelligent agency. In this section, we are going to elaborate on the different aspects of agency.

reactive Agents and Agents with state One of the first aspects is that agents are reactive. A purely reactive agent decides what to do without reference to its history. The behavior of a purely reactive agent is the function of the state of its environment. This type of agent architecture has two main subsystems: perception and action. The perception subsystem contains the agent’s ability to observe its environment. In the case of agents in the physical world, like robots, this may be a video camera, and in the case of an agent in the software world this may be system or network routines like finger, ping, or network messages. The output of the perception module is a percept, or the internal representation of the environment. The action subsystem of the agent contains the agent’s ability to act on its environment. In the

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Figure 2. Trends in agent research

1980

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Speech acts theory AI research focus on intelligent behavior AI planning with symbolic reasoning Behavioral and reactive AI Distributed Artificial Intelligence Actors model Contract Net Protocol Cooperation, commitment, joint intention Negotiation, coordination, conflict resolution Agent architectures Software agents on the Internet FIPA Agentcities testbed Web Ontology Language

case of a physical agent this may be a robot arm, and in the case of a software agent this may be system commands. The action subsystem maps the sequences of percepts into actions. The perception subsystem of the agent grabs those features of the environment which are relevant for the goals of the agent. For example, in the case of the stock exchange trading agent in charge of a stop-loss order, the whole range of the stock price is mapped into two values: hold and sell. If the price falls below a certain value, then the agent has to issue a sell order. Purely reactive agents often compose a finegrained multi-agent system. A fine-grained multiagent system consists of many simple agents, and the intelligent behavior of the fine-grained multi-agent system emerges from the interaction of the simple agents. Coarse-grained multi-agent systems consist of fewer, but more intelligent, agents. Agents in a coarse-grained multi-agent system usually have one of the architectures discussed below. Purely reactive agents do not remember the history of their environment. Agents with state, shown in Figure 3, can do so by having additional components in their architecture: a state and a next function. The state represents the current mental

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status of the agent, while the next function maps the percept of the agent and the current state of the agent to the next state of the agent. The action subsystem of agents with state maps the current state of the agent into actions. Agents with state have the full power of agency; they are behaviorally equivalent to agent architectures discussed later in this section, but the other architectures grab more of intelligent behavior and help better understand the notion of agency.

Agent reasoning Agents usually have to act in a dynamically changing environment, therefore it is better not to tell the agent exactly how to carry out the tasks. It is better to tell the agent what to do without telling how to do it. This can be done by defining tasks indirectly with some kind of performance measure. One way of defining tasks indirectly is by associating utilities with states of the environment. The utility function maps the environment states to real numbers and tells how good the state is: the higher the value, the better the state. A disadvantage of the utility function is that it assigns utilities to local states and does not take

Applications of Agent-Based Technologies in Smart Organizations

Figure 3. Agent with state Agent Sensor

Action Next

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Environment

into account long term values. However, we can use overall utility; for example, by defining the worst state that might be encountered by the agent or as the average utility of all states encountered. Although this model is useful to understanding agent behavior, in practice sometimes it is very difficult or even impossible to implement the desired utility function. Another way of indirect task specification is predicate task specification. Predicates are utility functions that have either true or false values. A predicate task specification maps the set of all possible runs of the agent to true or false value, and the agent achieves the desired goal if the predicate function results in true value either for all runs, or at least for one run or for a given percentage of runs of the agent, depending on how pessimistic or optimistic the definition of success is. Some common forms of predicate task specifications are the achievement tasks and the maintenance tasks. In the achievement task the goal of the agent is to achieve a state, while in the maintenance task the goal of the agent is to maintain a state. In the achievement task, the agent is successful if it can force its environment into one of the goal states, while in the maintenance task the goal of the agent can be characterized as to avoid some state. Complex tasks can be specified as combinations of achievement and maintenance tasks.

Deductive reasoning agents originate from symbolic AI, which says that intelligent behavior can be generated using logical deduction or theorem proving from symbolic representation of the world. In this approach there are two key problems: the transduction and the reasoning problem. The transduction problem is how to translate the real world into an accurate and adequate symbolic representation. This may be very hard; for example, in the case when a photo has to be converted into a set of declarative statements representing that photo. The reasoning problem is how to manipulate symbolic information to be useful in time. Since the computational complexity of theorem proving may require long computation, theorem provers may not always operate effectively in time-constrained environments. A deductive reasoning agent (shown in Figure 4) is an agent with state and its perception module translates external information into symbolic representation. Once there is a symbolic representation of a fact in the database of an agent, then the agent believes this fact, although in the real world this might not be the case. The next function of the deductive reasoning agent maps the agent database and a perception into a new database. The action subsystem of deductive reasoning agents use deductive reasoning to deduce the action of the agent. The deduction rules of the agent are

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Figure 4. Deductive reasoning agent believes P e r c e p t i o n

A

deduction rules A^B→do x

do x

A^C→do y

do y

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defined in a way that if a formula “do action A” can be derived from the fact database using the rule database, then the action of the agent will be action “A.” The reasoning engine of the action subsystem takes each of the possible actions “x” of the agent and tries to prove “do action x.” If there is no action for which this formula can be proved, then the reasoning engine tries to find an action “x” for which “do not do action x” cannot be derived. If there is such action “x,” then this action is consistent with the rules, so the agent can execute this action. If this also fails, then the agent does nothing. Practical reasoning agents try to improve the deductive reasoning agent architecture by reducing the search space of deductive reasoning. One of the main problems of deductive reasoning agents is that deducing all possible logical consequences takes too much time and sometimes is even impossible. In practical human reasoning, the logical reasoning is influenced by the current state of the mind. Human practical reasoning first tries to reduce the search space by deciding what state we want to achieve. This is called deliberation. Once deliberation is done, the reasoning concentrates on how to achieve the selected state. This is called means-ends reasoning. There must be a good balance between deliberation and means-ends reasoning, or else

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possible actions A c t i o n

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practical reasoning agents do not perform well or even do nothing. Deliberation cannot go on forever—some goal state has to be chosen and the process of achieving this state has to be started even if the selected goal state is not optimal. The process of achieving the selected goal state is called intention. Intention involves the process of creating a plan to achieve the selected goal state and actions taken according to the created plan. Deliberation and intention are shown in Figure 5. Intentions drive the means-end reasoning and if one plan creation fails, then another is tried. An intention must persist typically until it is believed that it is successfully achieved, or it is believed that it cannot be achieved, or it is believed that the reason for the intention no longer exists. Intentions constrain deliberation, and options which are not consistent with the current intentions are dropped. Intentions restrict the beliefs on which practical reasoning is based, and beliefs that are not consistent with the intention are dropped. The deliberation process of practical reasoning agents has two parts: the option generation function and the filtering function. The option generation function produces a set of options, called desires. The filter function selects the best one(s) from the set of desires based on the current beliefs, desires, and intentions.

Applications of Agent-Based Technologies in Smart Organizations

Figure 5. Steps of practical reasoning deliberation all possible goal states

intention selected set of goal states

Once a desire passes the filter function and becomes part of the set of currently selected intentions of the agent, then we say that the agent has made a commitment to that intention. The commitment strategy of the agent is the mechanism used to determine how long a commitment must persist. Blind commitment strategy is to keep the intention as long as the agent believes that the intention has been achieved. Single-minded commitment strategy is to keep the intention as long as the agent believes that either the intention has been achieved, or the agent currently has no plans to achieve the goals of the intention. Open-minded commitment strategy is to keep the intention as long as the agent believes that the goals of the intention are possible. The agent has to reconsider its commitments from time to time to check if they still have to be kept. There must be a good balance, because if the agent reconsiders its commitments very often, then it does not have enough computing resources to achieve them; on the other hand, if the agent does not reconsider its commitments often enough, then it may continue to pursue them for a long time after it is obvious that they cannot be achieved. Means-ends reasoning produces a plan to achieve the selected goal state based on the current intentions, the current beliefs (i.e., the state of the environment), and the actions available to the agent. In many implementations, the planning function does not create a plan from scratch; rather, the agent has a set of plans given by the agent

selected plans and actions

designer, and the agent searches through the set of plans to find one that has the needed intention as a post condition and is in accordance with the current beliefs and available actions.

Layered Agent Architectures An alternative to the reasoning agent architecture is the hybrid agent architecture, or layered agent architecture, in which there are layers responsible for different agent-like behaviors. In the horizontally layered hybrid architecture, each layer is directly connected to the perception and the activation modules, as shown in Figure 6. In horizontal layering, each layer produces competing suggestions as to what to do, and a control subsystem must decide which layer actually takes control over the agent. Some of the layers are responsible for low-level actions; for example, in a financial organization, to avoid bankruptcy some of the other layers are responsible for higher-level actions like deciding where to invest. The control subsystem gives priority to low-level actions in urgency and gives way to higher levels otherwise. In vertically layered hybrid architectures, perception and activation are connected to at most one layer, as shown in Figure 7. Layers make processing and pass information to each other. In two pass vertical layering information flaws up the architecture to higher and higher level processing. Decision is made at the upper-most

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Figure 6. Horizontally layered agent architecture Layer 1 Layer 2 Perception

Action

Layer 3 …

Figure 7. Vertically layered agent architectures Action …

…

Layer 3

Layer 3

Layer 2

Layer 2

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level where action is generated, which then flaws down to lower levels. Not long ago, a popular agent model was the mobile agent architecture. In this model, agents are seen as programs roaming the network to collect business-related data. This approach had a lot of problems related to authorization policies; that is, hosts and agents had to be protected against each other. Since network bandwidth is usually available, mobile agents did not have much advantage over nonmobile agents except in a few cases—for example, in auctions when different network latencies were not allowed for fairness. Because of the difficulties, mobile agents have not yet been taken up by the mainstream; however, mobility issues

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Perception

Action

may be investigated again when agents running on mobile devices become widespread.

Agent orgAnIZAtIons Up to now, we have been discussing how agents can organize and plan their activity on their own, but agents have to act in a networked environment; for example, as part of a smart organization. In this environment, they act on the real world, and sometimes the real world imposes restrictions on their activities; for example, because two agents want to use the same resource at the same time. In this case, it is obvious that the agents have to

Applications of Agent-Based Technologies in Smart Organizations

coordinate their plans. Even if there is no conflict in the real world, the agents want to distribute the task allocations among themselves, and there must be some kind of interaction between the agents. The interactions are even more complex when the conflict in the real world arises between the activities of two groups of agents. In this case, the groups of agents have to coordinate among themselves as how to interact with the other group. In order to model the interactions among agents, the utility function is used. The utility function of an agent assigns to each state a real value. If the utility function gives higher value for a state s1 than for another state s2, then the agent has preference for s1 compared to s2. Many times the utility function is linear, but nonlinear utility function models that situation when the agent achieved most of its goals and is satisfied with the state, therefore its utility function does not give much higher values when the state improves somewhat. Similarly, if the agent has not achieved any goal, then a small improvement in the state gives higher increase in its utility function than in a more or less satisfied status.

Properties of Agent organizations When several agents act on the environment, their actions may depend on the actions of the other agents. If one agent makes a choice, then the other agent is already restricted and has to make a choice depending on the choice of the other agent. In an ideal situation, the different agents have preference for the same state and all other states are less preferable for all of the agents. A somewhat less ideal but still very good situation is when agents can still find a state which is most preferable for all the agents, but there are other states which give the same utility value for all the agents. In this case, agents can select one of these preferable states, but they must agree which one, because if an agent deviates from this state toward another more preferable state, then none of the agents achieve the most preferred state. It

is also possible that there are more than one state with which agents are all satisfied and do not want to deviate from it if the others do not deviate; however, one of these preferable states may be better than the other one. All the situations in this paragraph are called Nash equilibrium, because no agent has the incentive to unilaterally deviate from the preferable state. The efficiency of the agent system can be measured as a combination of the utility functions of all of the agents. A simple efficiency measure is the sum of the utilities of all the agents, and according to this measure an agent system is in sum optimal state if the sum of the utilities is maximal. An agent system is in a Hicks optimal state if the utility is maximized for all of the agents in the agent system. An agent system is in Pareto optimal state if it satisfies, more or less, all of the agents, and in all other states at least one agent’s utility function gives smaller value if at least another agent’s utility function gives higher value. Note that Hicks optimal state cannot always be achieved. Also note that sum optimal and Pareto optimal state may not be equilibrium state, if at least one agent might achieve better utility by deviating from the optimal state. An example of this is the prisoner’s dilemma, in which the equilibrium is not optimal.

Agreement in Agent organizations Now that we have seen the different types of states multiple agents can achieve, let us turn our attention to how they can reach agreement to get to the desired state. Agents coordinate their actions by exchanging messages. The messages are exchanged similarly to usual network communication protocols, which are governed by protocol rules so that the participating partners can get to some useful result and are not locked in, for example, a deadlock. Agent interaction protocols build on communication protocols and strive to ensure, for example, community level results (Sandholm, 1999). It is expected

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that an agent interaction protocol guarantees that agents eventually get to some agreement and this agreement leads to either sum, Hicks, or Pareto optimal state. Participating in agent interaction protocols must be Nash equilibrium behavior for the participating agents, that is, all of the agents must be interested in keeping to the protocol rules, which must be simple enough so that agents can easily determine the optimal strategy. Multi-agent systems are usually distributed and there is no centralized node, and this must be the case for agent interaction protocols as well. Although agents may interact in many different ways, there are three types of interaction protocols which are the most used and studied. These are the auction, the negotiation, and the argumentation interaction protocols. The auction protocol can be used to allocate a given resource to one of the agents from a group. The resource can be a good or a task to be executed; in the latter case the auction protocol is also called a contract net protocol. The roles in the auction protocol are the auctioneer and the bidder. The auctioneer agent has the resource to be allocated and wants to maximize the price for it. The bidders are the agents to which the resource is to be allocated and want to minimize its price. In many cases the exact value of the resource is not known or is not unambiguous. The agents may value the price of the resource differently according to their different interests in the resource and different knowledge about the current and future value of the resource. The auction protocol helps the agents agree on a price and allocation which is most acceptable for them. According to the different rules, the auction interaction protocol can be one shot, if there is only a single round of bids, or it can be ascending or descending sequential, if there are several rounds with the necessity of ascending or descending bids. The auction interaction protocol can be open cry, if every agent sees the bid of every other agent, or can be sealed bid, if they do not see each other’s bid. The auction protocol is first price if the winner is the one with the best bid

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and pays its own bid, or it can be second price if the winner is the one with the best bid, but pays the second best bid. Auction is a special form of negotiation which is a somewhat more general form of agent interaction. The negotiation interaction protocol is defined with the negotiation set, the proposal order, a set of strategies, and an agreement criterion. The negotiation set contains all the possible proposals the agents can make. In the simplest case, the proposal contains one issue to be negotiated, like the price in auction protocols, or can contain multiple issues which may be interrelated. The proposal order defines the set of allowed proposals as a function of the negotiation history and the timing of proposal making. Typically, agents make the proposals at the same time or one after the other, and they are not allowed to repeat previous proposals. Each agent has a negotiation strategy which defines the proposal selection method from its allowed proposals. Negotiation strategies are not public and are related to how the agent is going to achieve its goal. The agreement criterion defines when the negotiation stops and what the accepted proposal is. The most complex form of agent interaction protocol is argumentation, which most resembles human negotiation and allows dynamic negotiation and the justification of the negotiated deal. Argumentation is based on formal logic. In formal logic there are statements and logic rules. Using the logic rules other statements can be derived from a set of statements. In the beginning of the argumentation interaction protocol, the agents have in their knowledge base different sets of statements which represent their beliefs about the state of affairs. During the argumentation process agents can send each other the statements they have, the derivation rules they are capable of, and concrete derivation instances in order to get to a status when all the agents have the same statement about the issue to be agreed in their knowledge base.

Applications of Agent-Based Technologies in Smart Organizations

communication in Agent organizations We have seen how agents can get to agreements by exchanging messages; now let us see how they communicate these messages. In usual-distributed computing environments, like in object-oriented systems, one object can call the method of another remote object. In this kind of communication, the calling object causes the execution of the procedure in the remote object. This may happen synchronously if the thread of control returns to the calling object only after the execution of the remote procedure, or asynchronously if the thread of control immediately returns to the calling object and the remote procedure is executed in parallel. In both cases the calling object executes the remote procedure. However, agents are autonomous and their communication is even less coupled, as in the asynchronous remote procedure call. Agents are autonomous, and when agents send messages to each other, they do not force the execution of a remote procedure, or write data into the internal data representation of the remote agent. When a sending agent sends a message to a remote agent, the sending agent performs an action to influence the behavior or the beliefs of the remote agent. This kind of communication is based on the speech act theory, which treats communication as action (Austin, 1962; Searle, 1969). When a fact is sent from the sending agent as an information to the remote agent, the sending agent intends the remote agent to believe the fact, but it is up to the remote agent whether it trusts the sending agent and builds the belief into its knowledge base or not, as shown in Figure 8. Based on the speech act theory, the Knowledge Query and Manipulation Language (KQML) was developed (Finin, McKay, Fritzson, & McEntire, 1993) in the framework of the DARPA funded Knowledge Sharing Effort. The KQML language defines the envelope format for agent messages, and the content of the message is described in the Knowledge Interchange Format (KIF) (Gen-

esereth & Fikes, 1992). The KQML envelope contains what the intention of the sending agent is with the information contained in the content part. The KQML part of the message has slots for the type of the message (inform, request, reply, etc.), the sender, the receiver, the language of the content (e.g., KIF), the ontology the content is related to (e.g., electronic products), the content itself, and possibly other features. We should say a few words about the content language and the ontology. The content language is the format of the description of the content. However, the content cannot be anything, it belongs to a specific domain of discourse that both agents understand. The ontology specifies the notions of the allowed content, the possible properties of the notions, and relations between the notions of the domain. Roughly we could say that the content is the data and the ontology is the schema of the content, but the ontology defines not only the syntax of the allowed content, but the semantic dependencies as well. An ontology describes the common understanding of a specific domain of discourse; it is described in an ontology description language, and it is usually published so that everybody can use it to understand the same. KIF itself is an ontology language, but the most recent ontology language used on the Web is the Web Ontology Language (OWL) defined and standardized by the World Wide Web Consortium (Dean & Schreiber, 2004). Although KQML defined a framework for agent communication, it was never precisely defined, therefore many versions of KQML were implemented and when agents started to inhabit the Internet, they could not interoperate. Based on the KQML efforts, FIPA standardized agent communication with the specification of the FIPA Agent Communication Language (ACL), interaction protocols, and architecture. As a result of the standardization effort, many vendors implemented agent platforms interoperable on the communication language level.

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Figure 8. Autonomous communication Agent message

received message

decision do nothing

message

result or rejection

trust and security In industrial and business environments, special attention has to be made to trust and security aspects, especially in the open and dynamically changing society of agents forming smart organizations. In the open and dynamic environment, agents interact with each other on an occasional basis without having reliable information on each other and the organization they represent. As identified by Wong and Sycara (1999), the most important security threats in agent systems are the corrupted naming and directory services, the insecure communication channels, the insecure delegation, and the lack of accountability. A naming service in a distributed environment maps names of components to their addresses. A directory service maps services and capabilities to their providers. These services are not part of agent architectures; rather, they are part of the infrastructure of an agent society. However, the agent society cannot function if the members cannot find each other and their services. A naming service or a directory service is corrupted if some entries are missing or contain a wrong value. A wrong value may be entered, for example, by a misbehaving agent.

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The communication channels are secure if authentication, integrity, confidentiality, and nonrepudiation are guaranteed. Authentication means that agents know that they talk to agents they think they are talking to. Integrity of messages is guaranteed if the message is not modified or falsely inserted in the communication channel. The message is confidential if other agents cannot intercept the message. Nonrepudiation is guaranteed if nobody can deny having sent a message which was sent. Insecure delegation occurs if an agent impersonates itself as a delegate of someone who did not entrust to it. Lack of accountability occurs if agents cannot be held accountable for what they are doing and their services cannot be trusted. As proposed by Wong and Sycara (1999), several measures have to be taken in an agent society to give protection against the abovementioned trust and security threats. The naming and directory services must service only valid requests coming from a rightful requester and the request is valid. The naming and directory service databases must be kept consistent. The agents and their delegators must have unique identity which can safely be proved. The communication channels must be protected. Agents can be deployed

Applications of Agent-Based Technologies in Smart Organizations

only if there is someone who can be made liable for their actions. Theoretical models have been developed to guarantee these protective elements, and agent architectures implement more and more of them.

Agent-orIented soFtwAre engIneerIng In the previous sections, we wrote about how agent systems work, but if we want to write about how such agent systems can be designed and implemented, then we have to select from several approaches. Many agent systems have been implemented and now there are dominant standards, tools, and platforms to operate them, but there is no unique methodology for their design. As we have seen, agent systems propose solutions to problems which the traditional software products do not cover; therefore, we cannot expect that traditional software engineering techniques provide solution to agent-oriented software engineering. Of course, when a specific component of an agent system has to be implemented, then traditional software engineering methods can be applied and traditional software components can be used in the implementation. However, we need new methodology until we get to the point at which we can apply traditional techniques. Usually an analysis and design method provides techniques to understand the problem domain and how to handle the complexity of the system so that it can be designed. This is usually done by creating models of the system at different levels, and then transforming higher level models to models closer to the implementation using formal guidelines. What are needed for agent-oriented software engineering are those high-level models that are above the traditional software engineering methods. There are many agent-oriented software engineering approaches (Giorgini, Müller, & Odell, 2002) among which probably the agent exten-

sions of UML (Odell, Parunak, & Bauer, 2001) and the Gaia methods (Wooldridge, Jennings, & Kinny, 2000) are the most well known. We are going to write about the latter one here, because this method focuses mainly on the agent levels of agent-oriented software engineering and is based on the organizational view of the system, which is important for smart organizations. The Gaia methodology starts from the requirements statements, which are the textual and formal descriptions of what the system is supposed to do. The requirements capture phase is independent of the paradigm used for the analysis and design, so traditional methods can be used. The Gaia methodology uses the roles and the interactions models for analysis, and the agent, services, and acquaintance models for design. These models and their dependency, as shown in Figure 9, are discussed in the following paragraphs. The roles model identifies the key roles in the system. The role is an abstract description of the expected function of an entity. The roles are similar to offices in organizations. The role is characterized by the responsibilities and the permissions of the role. The responsibilities are the functions to be performed by the role. A responsibility can either be liveness or safety responsibility. A liveness responsibility says what the role is supposed to do, while safety responsibility is an invariant that the role must keep. Invariants are described as predicates. The permissions associated with the role either identify the resources that can be used to carry out the responsibilities of the role, or define the resource limits within which the execution of the responsibilities can be carried out. The interaction model captures the interaction links between the various roles in a smart organization. The interaction model consists of a set of protocol definitions for each type of interrole interaction. In this model, a protocol is abstracted away from the concrete execution steps and is described by a brief textual description of the protocol, the roles responsible for starting the interaction, the roles with which the initiator in-

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Figure 9. Gaia models Agent Model Roles Model Requirements Statements

Services Model Interactions Model Acquaintance Model

teracts, the information used by the initiator while executing the protocol, the information supplied by the initiator and responder roles, and a brief textual description of the processing activities during the protocol execution. The agent model consists of a set of agent types used in the system under development. The agent types are marked with information on how many instances of them will be implemented in the actual system (zero, one or more, n to m, etc.). The agent type is defined as a set of agent roles to be fulfilled by an agent of the given type. Agent types are organized into an agent type tree, where the leaf nodes correspond to roles and the upperlevel nodes correspond to agent types. An agent type is composed of the roles of its children agent types in the tree. The agent type tree is derived from the roles model. The service model specifies the functions associated with each agent role. A service is a single coherent block of activity to be carried out by the given agent type. A service is specified with the inputs, outputs, pre-conditions, and postconditions of the service. The inputs and outputs are derived from the protocol definitions of the interaction model, while the pre- and post-conditions are derived from the safety responsibilities of the roles model.

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The acquaintance model defines the communication links between agent types. The agent acquaintance model is a directed graph in which each graph node corresponds to agent types and arcs correspond to communication links. Arcs are directed and indicate that an agent of one type will send messages to an agent of the other type. The acquaintance model does not specify what messages are sent or when messages are sent, the goal of the acquaintance model is to identify potential communication bottlenecks. Using these models the designer can specify most of the agent features of the system under development. Further design and implementation can use any traditional design techniques to implement the agent instances.

Agent APPLIcAtIons In the previous sections, we discussed what agents are, what their internal structure can be, how agents behave in organizations, and how agent systems can be designed. Now we are going to discuss the applications of agent systems in smart organizations. Basically, agent applications in smart organizations can be classified into three categories: distributed agent systems

Applications of Agent-Based Technologies in Smart Organizations

(or multi-agent systems), assistant agents, and multi-agent simulation systems. In the first two types of applications, agents become part of the smart organization, while in the third type of applications agents are used to evaluate and design the structure of the organization. In the first type of applications, several agents make collective decisions and actions within the organization to improve the operation of the organization. In the second type of applications there may be several agents deployed within the organization, and these agents may even interact with each other, but the main function of each agent is to assist its individual user in autonomous and proactive decision-making. In distributed agent system applications the agent system becomes an integral part of the organization and agents assist the distributed intelligent operation of the organization. Typical areas where distributed agent systems can be applied are business process management, distributed sensing, distributed resource management, process control, trading and purchasing networks. Distributed agent systems can outperform centralized business process management systems, because they are more responsive and are able to cope with unpredictable events. In an agent-based business process management system, the organizational structure and the roles in the organization are mapped to agents, which are responsible for the given role and embody the knowledge needed for the role. These agents can then autonomously and proactively execute most of the automatic processes of the organization with minimal user intervention and approval. Distributed agent systems help distributed sensing by allowing cooperation between the sensors and predicting future trends in the area of one sensor from the data of another sensor. Distributed resource management can benefit from the proactive behavior of agent systems. For example, agents can monitor the network load in telecommunication networks and jointly make predictions on trends and future needs to reallocate resources. Agents

can coordinate the workload and the schedule of the field engineers—for example, of electricity provider or telecommunication companies—by taking into account the location and capabilities of the field engineers. Agents can execute the job of automatically negotiating and trading with the suppliers of an organization. Since agents are dynamic, they can adapt to the changing needs of virtual organizations and supply chains. Assistant agents help their users in gathering and filtering information, or executing some task on behalf of their users. Information retrieval agents can gather information and categorize it according to predefined conditions. This helps the user overview huge amounts of information. More advanced assistant agents learn from the activities of their users; for example, by recording the activities and decisions of the user and deriving rules with knowledge discovery and data mining techniques. Organizations can also benefit from multiagent simulation systems, which can simulate real-world environments with a high degree of complexity and dynamism. In a multi-agent simulation system, many individual behaviors can be encoded, thus giving a more complex and real picture of what might happen. The organization can make decisions regarding future products and product features based on a multi-agent simulation of the market where the product is to be sold.

Agents suPPortIng sMArt orgAnIZAtIons As we can see, agent technology discussed in this section has a lot of features that support smart organizations. Smart organizations act in a globally distributed system in which software applications must appear in a new way. A software application in this distributed system is just a component with possible utilizations not completely known at design time. The designer implements some functionalities into the component, but the

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component may be dynamically included in different temporary compositions in the globally distributed environment. The software component provides services to other software components and it may invoke services of other components. This architecture is in line with the dynamically changing organizations of the economy. Software components advertise their services and other software components can search for the desired services. In order to achieve the goals, software components can select and invoke the desired software services based on the service descriptions, the trust and reputation information available from different sources. In this environment, software components are formed into temporary alliances and their services are dynamically combined. The experiences learned in one temporary alliance are reused in another composition dynamically created later. This way, any software component available on the Web may become part of a Web application. Agent-based computing provides a new software technology for this new changing environment of smart organizations. Agent technology allows that the creation of the complete functionality of the software system can be postponed beyond design, implementation, and deployment time to operation time, when the software components themselves compose their relation to other software components. This new way of software composition requires that the software components have dynamic and autonomous features. It is also important that agent technology standards provide the glue for tightening the software components together. Agent technology standards provide machine processable, formal descriptions for the functionality, accessibility, and quality properties of the software components, the data used by the software components, as well as how they can be composed in a workflow. Agent technology also provides standards for registering and searching agents and their services in registries.

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Agent technology also takes software components considerably closer to semantic interoperability, which is crucial to smart organizations. Semantics is the relation between the formal notation systems used by the computers and the real objects and notions used by humans. Although simple bit sequences may have semantic meaning, it is better to have the computer representation closer to the human representation, because this way computer interaction on a higher semantic level can be implemented more easily.

suMMAry In this chapter, we discussed how agent-based technologies can contribute to smart organizations. Agent technology forms the base of knowledge-driven, internetworked, dynamically changing systems like smart organizations. The most important characteristics of agents are that they are reactive, autonomous, have design objectives, can take initiatives towards their goals, have social abilities, and can interact with the actors in their environment. Agent technology emerged from artificial intelligence by dealing with distributed aspects, and lead to the semantic interoperability technologies of the current Internet. Agent architectures provide means for agents to organize and plan their activity on their own. The types of states multiple agents can achieve can be classified from stability, efficiency, and optimality aspects. Agents reach agreement to get to the desired state by exchanging messages. Agent interaction protocols build on communication protocols and strive to ensure community level results. Agent technology can also be viewed as a software engineering approach to design large, open, networked, dynamic software systems. Agent technology applications can be classified into three categories: distributed agent systems (or multi-agent systems), assistant agents, and multi-agent simulation systems. The methods

Applications of Agent-Based Technologies in Smart Organizations

and approaches discussed in this chapter show that agent technology is fundamental to smart organizations.

and Sharing of Very Large-Scale Knowledge Bases, Tokyo, Japan.

reFerences

Foster, I., & Kesselman, C. (Eds.). (1999). The grid: Blueprint for a new computing infrastructure. San Francisco: Morgan Kaufmann.

Austin, J. L. (1962). How to do things with words. Oxford: Oxford University Press. Balboni, G. P. (Ed.). (2003). EXP - in search of innovation [Special Issue]. JADE, 3(3), 1-141. Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American 284(5), 34-43. Bussler, C., Maedche, A., & Fensel, D. (2002). A conceptual architecture for Semantic Web enabled Web services. ACM Special Interest Group on Management of Data, 31(4). DAML Services Coalition (2002). (alphabetically Ankolenkar, A., Burstein, M., Hobbs, J.R., Lassila, O., Martin, D.L., McDermott, D., McIlraith, S.A., Narayanan, S., Paolucci, M., Payne, T.R., Sycara, K.) DAML-S: Web Service Description for the Semantic Web. The First International Semantic Web Conference (ISWC). Sardinia (Italy). Dean, M., & Schreiber, G. (Eds.). (2004). OWL Web Ontology Language Reference. Retrieved February 10, 2004, from http://www.w3.org/TR/ owl-ref/ Filos, E., & Banahan, E. (2000). Will the organisation disappear? The challenges of the new economy and future perspectives. In L. M. Camarinha-Matos, H. Afsarmanesh, & R. J. Rabelo, R.J. (Eds.), E-business & virtual enterprises (pp. 3-20). Dordrecht: Kluwer. Finin, T., McKay, D., Fritzson, R., & McEntire, R. (1993, December). KQML: an information and knowledge exchange protocol. In Proceedings of the 1993 International Conference on Building

FIPA (2001). The Foundation for Intelligent Physical Agents. http://www.fipa.org/.

Genesereth, M. R., & Fikes, R. E. (1992). Knowledge interchange format, Version 3.0 reference manual (Tech. Rep. logic-92-1). Stanford, CA: Stanford University, Computer Science Department. Giorgini, P., Müller, J. P., & Odell, J. (Eds.). (2002). Agent-oriented software engineering IV. In Proceedings of the 4th International Workshop, AOSE 2003, Computer Science, 2935. Odell, J., Parunak, H. V. D., & Bauer, B. (2001). Representing agent interaction protocols in UML. In: Agent-oriented software engineering. In Proceedings of the First International Workshop AOSE-2000 (editors Ciancarini, P. & Wooldridge, M.). Computer Science,1957,121-140. Sandholm, T. (1999). Distributed rational decisionmaking. In G. Weiss (Ed.), Multiagent systems (pp. 201-258). Cambridge, MA: MIT Press. Searle, J. R., (1969). Speech acts. Cambridge University Press. UDDI (2004), Universal Description, Discovery and Integration of Business for the Web. Retrieved from http://www.uddi.org/ Web Services (2004). Retrieved from http://www. webservices.org/ Willmott, S. N., Dale, J., Burg, B., Charlton, P., & O’Brien, P. (2001). Agentcities: A worldwide open agent network [Electronic version]. Agentlink News, 8, 13-15.

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Wong, H. C., & Sycara, K., (1999). Adding security and trust to multi-agent systems. In Proceedings of Autonomous Agents ’99 (pp. 149-161).

endnotes 1

Wooldridge, M. (2002). An introduction to multiagent systems. Chichester, UK: John Wiley & Sons Wooldridge, M., & Jennings, N. R. (1995). Intelligent agents: Theory and practice. The Knowledge Engineering Review, 10(2), 115-152. Wooldridge, M., Jennings, N. R., & Kinny, D. (2000). The Gaia methodology for agent-oriented analysis and design: Autonomous agents and multi-agent systems, 3(3), 285-312. Boston: Kluwer Academic Publishers.

2

3

SOAP: Simple Object Access Protocol— SOAP is an XML (Extensible Markup Language)-based, lightweight protocol for exchange of information in a decentralized, distributed environment. WSDL: Web Services Description Language—WSDL is an XML format for describing network services as a set of endpoints operating on messages containing either document-oriented or procedure-oriented information. UDDI: Universal Description, Discovery, and Integration—The UDDI protocol creates a standard interoperable platform that enables companies and applications to quickly, easily, and dynamically find and use Web services over the Internet.

This work was previously published in Integration of ICT in Smart Organizations, edited by I. Mezgar, pp. 39-67, copyright 2006 by Idea Group Publishing (an imprint of IGI Global).

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Enriching and International Program Graduate Offering: A Blended Delivery Model Vivian H. Wright The University of Alabama, USA Jon Beedle Mississippi State University, USA Ronnie Stanford The University of Alabama, USA

AbstrAct

bAcKground

Portions of an international master’s program were designed for a blended, online delivery in one pilot course. This approach allowed students in Central and South America to interact with the professor and other students prior to instructor arrival on-site and after instructor departure. Student reactions to this blended approach were positive. Students indicated an increase in skills and knowledge using Web-based materials, and an increase in interaction with their peers and instructor.

Educational technology allows organizations the ability to modify courses and curriculums, and at the same time become more flexible in their delivery (Kvavik, 2002). Graves (2001) predicted that higher education is moving toward a more student-centric approach and away from the traditional instructor-focused environment. Accessibility of information electronically allows students the occasion to explore, discover, create, and communicate more efficiently than in the past (Tiene & Ingram, 2001, p. 32).

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Enriching and International Program Graduate Offering

With these challenges come new opportunities to serve students at all levels and from locations around the world. The International Programs office in the College of Education at the University of Alabama offers Master’s of Arts degree programs in Elementary and Secondary Education to teachers at U.S.-type schools in Latin American countries. The office was interested in using available technological tools to enhance its current course offerings, while also answering international student demands for more accessible course materials. To this end, professors within the College of Education at the University of Alabama, and a doctoral student in Instructional Leadership/Technology, focused on providing portions of a master’s program online. The College of Education International Programs office at The University of Alabama provides overseas instruction within countries in Central and South America, the Caribbean, and Mexico. The advanced degrees offered are beneficial to those looking for advancement, greater professional opportunities, and increased remuneration. On-site courses typically last two weeks, providing limited time to complete instruction. The purpose of this project was to provide students with online learning materials and assignments before the instructor arrives on location, and access to appropriate materials after the instructor leaves the international site. Creating an online component through a Web-enabled course gives instructors and students a greater opportunity for interaction and learning (Dabbagh & Schmitt, 1998), and provides opportunities for the students to become acquainted with the course materials and their peers in advance of the instructor’s on-site arrival. It is our intent that this increased access to peers and information will provide these students with educational opportunities and learning experiences that would not have been possible without such access.

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our Approach to course development WebCT is course management software used by many academic institutions to distribute resources, providing tools for online instruction. WebCT allows instructors to manage online or Web-enhanced courses, and provides tools and online help aides for the student. One of the goals of this project was to create an improved, student-centered approach to learning by blending both face-to-face and Web-based instruction. Twigg (2003) indicated that enhanced quality of individualized education is important to faculty working to redesign courses for online use. A team approach can be valuable in creating and implementing an instructional technologyenhanced learning environment. To accomplish this team approach, all of those involved with this project are involved with progress and modifications as needed. WebCT provides instructional designers and course instructors the ability to use electronic resources to communicate and to facilitate discussions in the form of e-mail, synchronous chat rooms, and asynchronous electronic message boards (McLean & Murrell, 2002). One of the many benefits of networks and computers for students is the ability to communicate with groups of people around the world with relatively less expense than would be incurred through telephone calls (Tiene & Ingram, 2001). Cognitive processes increase due to the frequent interactions with others and with the tools provided through the WebCT course management software. Learners gain knowledge through participation, practice, and engaging in problem-solving activities with their colleagues. Students are participative learners and not just reactive observers who respond to certain stimuli, like some behaviorists believe (Deubel, 2003).

Enriching and International Program Graduate Offering

our Pilot course

Lessons Learned

The pilot WebCT course we created, as a model for other faculty, was an elective course entitled “Computer-Based Instructional Technology.” The course has 12 main links from the homepage. These include sections for: before the instructor arrives, syllabus, assignment summary, reading list, course links, course topics, library use instructions, examples of student work, glossary, calendar, discussion board, and after the instructor leaves instructions. As Deubel (2003) suggested, we used various media throughout the Web site, and included colorful graphics and animation useful in directing and keeping the students’ attention and focus. Careful guidance by the instructors provides students with the necessary skills and tools to access the vast relevant resources on the Internet. Twigg (2003) indicated the necessity of constant enhancement of online courses, not only from semester to semester, but within the current semester as well. Palloff and Pratt (2001) suggested instructors typically will have a much more positive outlook on using Web-enhanced courses if they are given the freedom to make adjustments, as if this is the first time the course will be taught. Additionally, it is essential that instructors understand how to upload content and other information to the Web site if they need to make changes or add more materials. For the purposes of this project, an instructional technology graduate student was employed to work with faculty and to assist with these efforts. For students, online discourse may be one of the most important characteristics of pedagogy used to benefit and facilitate this effective communicative practice (Pittinsky, 2003). Some of the guidelines we followed are given by Palloff and Pratt (2001), and include collaborative assignments, posting of assignments so that peers can provide feedback, online areas to communicate (discussion boards and e-mail), and requesting a certain number of posts per week to the course Web site.

We piloted the “Computer-Based Instructional Technology” course in February 2004 at our Quito, Equator site. The instructor began the class online via WebCT two weeks prior to arrival in Quito. Assignments and postings were due up to two weeks after the instructor’s departure. Every aspect of the pilot was tested during these few weeks. One area that needed to be addressed before the class began was issues relating to student enrollment in the WebCT course. It was imperative that students were enrolled early to ensure they received their university-wide account information in order to access the Web site and the university’s library online databases. Student information services can vary, and traditional identifiers such as a Social Security number may not always apply. These details were addressed before the first contact with the course professor. Additionally, a library tutorial was created and posted on the WebCT course in both Portable Document File (PDF) and Hyper Text Markup Language (HTML) file formats. From past instructor experiences with online supplements, we were aware that some students’ network connections at home, work, or school were of limited bandwidth, and the use of PDF files would result in longer download times, therefore requiring our use of HTML files in addition to PDF files. It was our goal not to give students too much technology in the beginning, but to scaffold the technology into the course by allowing the students to become familiar with WebCT through the “Before Instructor Arrives” assignment on the homepage. This process worked well with this pilot course, with the exception of some students who did not have an Adobe Reader loaded on their machines and therefore could not read the PDF file. This problem created additional e-mails between the instructor and students prior to the instructor’s arrival on-site. We noted this for future revisions to the Web site. It is important to constantly note

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and work toward eliminating any problems that might occur with the technology (Weil & Rosen, 1997). With the International Programs office located in one country and the students located in another, it is sometimes difficult to understand some of the problems students might encounter. The instructor for this pilot course maintained field notes of all problems encountered throughout the weeks of instruction in an effort to better inform future instructors using the WebCT model. For example, some students had problems properly posting to the threaded discussions. Directing the students to a tutorial prior to their first use of the discussion board tool would have been helpful.

student Impressions There were 14 Quito students enrolled in this pilot course. The students received e-mail instructions on how to enroll in the WebCT course, and how to locate and complete the first assignment. Once this first assignment was completed, students were then directed fully from the WebCT instructions for each topic associated with the class. Tutorials on how to complete the assignments and links to helpful Internet sites were all part of the WebCT course. Additionally, students were required to use the WebCT e-mail tool to communicate with the instructor and others enrolled in the class. Students also completed several assignments via the discussion board. After the instructor’s visit on-site and upon her return to campus, the instructor queried the students via the discussion board on their blended course delivery experience. Overall the comments were positive, and students enjoyed and appreciated the interactivity of the course. One student noted: This is a good way to keep in touch with the teacher and also with the rest of the students. With this page we can read what the other classmates think about a certain topic which is good.

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Another student wrote: Overall, the WebCT experience for me has been technologically enriching and challenging but not beyond comprehension with some effort. Of the problems students noted in this discussion posting, most were associated with logging on the course and with the first assignment, presented online in PDF format. One student commented: I don’t feel confident and sure about if I’m doing the correct job. I had problems with topic one, because my computer couldn’t open it. Another wrote: It is easy to work with, but did take me a little while to understand the first time I logged on. A couple of the students noted that the calendar tool had not been updated promptly as assignment due dates were adjusted, with one student writing: Another recommendation would be to allow students to have the original tentative calendar with the teacher’s entries and to create a new one with the modifications that the teacher sends afterwards. In addition to articulating the problems they experienced, several students noted positive attributes regarding the feedback, instructions, and interactivity with other students. For example, one student wrote: In terms of logging in to the program, I did not have any problems. Dr. ____’s instructions sent via e-mail were clear.

Enriching and International Program Graduate Offering

Another commented: The system is user friendly, I have found clear instructions and tutorials. There are many helpful links too. Another student said that he was surprised more instructors do not use an online component, writing: I have been really surprised how little and how rarely this technology has been taken advantage of. Finally, a student noted: It has the possibility to unite people over vast distances.

concLusIon The participants in this study believed there were many advantages to using this blended course delivery approach. Students gained supplementary content through the online instruction, while gaining additional skills and knowledge using Web-based materials and interacting with their peers and instructor. The students must be able to e-mail the instructor with any problems or questions about the course before the instructor’s arrival at the course site. Another important issue was the ability to respond to student inquiries in a timely manner. Success in implementing this course and future courses for the International Programs office will continue to rely on continuous evaluation and instructor/student reflections. While instructors should be trained on the tools of WebCT (or the course management system of choice), students should also receive advance instruction through the development of tutorials or extensive e-mail instruction prior to first use. Students in this pilot

course appreciated clear instructions, in addition to the immediate feedback of the instructor and the interaction WebCT tools afforded them with the other students enrolled.

reFerences Dabbagh, N., & Schmitt, J. (1998). Redesigning instruction through Web-based course authoring tools. Educational Media International, 35(2), 106-110. Deubel, P. (2003). An investigation of behaviorist and cognitive approaches to instructional multimedia design. Journal of Multimedia and Hypermedia, 12(1), 63-90. Graves, W.H. (2001). Transforming traditional faculty roles. In C.A. Barone & P.R. Hagner (Eds.), Technology-enhanced teaching and learning: Leading and supporting the transformation on your campus (pp. 35-44). San-Francisco: Jossey-Bass. Kvavik, R.B. (2002). E-business in higher education. In R.N. Katz & Associates (Eds.), Web portals & higher education: Technologies to make IT personal (pp. 41-68). San-Francisco: Jossey-Bass. McLean, M., & Murrell, K. (2002). WebCT: Integrating computer-mediated communication and resource delivery into a new problem-based curriculum. Journal of Audiovisual Media in Medicine, 25(1), 8-15. Palloff, R.M., & Pratt, K. (2001). Lessons from the cyberspace classroom: The realities of online teaching. San Francisco: Jossey-Bass. Pittinsky, M.S. (2003). Transformation through evolution. In M.S. Pittinsky (Ed.), The wired tower: Perspectives on the impact of the Internet on higher education (pp. 1-11). Upper Saddle River, NJ: Pearson Education.

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Tiene, D., & Ingram, A. (2001). Exploring current trends in educational technology. New York: McGraw-Hill.

Weigel, V.B. (2002). Deep learning for a digital age: Technology’s untapped potential to enrich higher education. San Francisco: Jossey-Bass.

Twigg, C.A. (2003). Quality, cost and access: The case for redesign. In M.S. Pittinsky (Ed.), The wired tower: Perspectives on the impact of the Internet on higher education (pp. 111-143). Upper Saddle River, NJ: Pearson Education.

Weil, M.M., & Rosen, L.D. (1997). Technostress: Coping with technology @ work @ home @ play. New York: John Wiley & Sons.

This work was previously published in the International Journal of Information and Communication Technology Education, Volume 1, No. 2, pp. 40-46, copyright 2005 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 4.27

Continuing Science Education of the Global Public Leo Tan Wee Hin Nanyang Technological University, Singapore R. Subramaniam Nanyang Technological University, Singapore

IntroductIon Continuing education constitutes an important aspect of furthering the process of learning beyond the formal years of schooling. Leveraging mainly on the individual’s penchant for self-improvement, it fulfils a useful role in endowing skill sets and other competencies to a person. Continuing education has largely remained the mainstay of tertiary institutions, commercial schools and adult education centers. An entire gamut of evening courses catering to diverse interests is offered here. The need to keep abreast of continuing developments in science and technology is important in today’s society, as science and technology are regarded as agents of socio-economic development for a country (Tan & Subramaniam, 1999). From an institutional context, science and technology centers have been performing an admirable role in popularizing science and technology among the masses (Tan & Subramaniam, 1998; Dela-

cote, 1999; Subramaniam, 2003). Attendances to science and technology centers have been increasing over the years, and more science and technology centers are being set up in various countries (Tan & Subramaniam, 2003a). One aspect of the continuing education of the public that has not been given adequate attention is the need to address the public’s queries about science and technology. Addressing these queries constitutes an important aspect of furthering the promotion of science and technology among people. No proper institutional mechanism exists to fulfill this need, probably because of the cost, manpower and diversity of resources needed to service such learning needs. This may well have been the case up to a few years back, when the Internet was still a fledgling infrastructure. With the reach and hold of the Internet now extending real-time across the world, the marshalling of manpower and resources is no longer a problem, and connection to a vast knowledge base is possible

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Continuing Science Education of the Global Public

within a few seconds to anyone with a personal computer and network connection. This chapter describes a university-science center partnership called Science Net, which has been functioning as a Web-based institution for the continuing (science) education of the global public in general and the Singapore public in particular since 1998. The global public, including students, can seek answers or explanations to any of their scientific queries, doubts or misconceptions via this forum (Tan & Subramaniam, 2004). Science Net is hosted on the Web site of the Singapore Science Centre (www.science.edu.sg), an institution for the popularization of science and technology, and is not to be found in the portals of other science centers or science museums. Science Net provides access to a rich knowledge repository of more than 6,000 questions and answers on various aspects of science and technology—these represent the authored products of the scientific community in Singapore.

bAcKground The Singapore Science Center has been popularizing science and technology to students and the public in multi-dimensional ways since its establishment in 1977. Singapore Scientist, a best-selling science magazine that the center has been publishing since its opening, has a popular section called “The Scientist Answers.” In this section, students get their doubts in science answered by the scientific staff of the science center. However, the quarterly nature of this print publication means that only a limited number of questions can be answered in any issue. On an average of five questions and answers per issue, this equals about 20 questions and answers a year, or 200 questions and answers in 10 years. And the huge pile of questions awaiting answers means that a valuable opportunity is foregone to address learning needs.

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When the Internet became a buzz word in the mid 1990s and Internet penetration rates in Singapore started to increase, especially with the establishment of a broadband network (Tan & Subramaniam, 2001), a decision was made to open a virtual annex of the science center. The utility of a virtual annex for science centers has been well recognized internationally (Jackson, 1996; Orfinger, 1998; Bevan & Wanner, 2003). The virtual science center in Singapore features information about the science center, virtual exhibits and a range of science learning resources (Tan &Subramaniam, 2003b; Tan, Subramaniam, & Aggarwal, 2003). Among the science learning resources featured here is the online equivalent of “The Scientist Answers,” called Science Net. A major reason for instituting this section is the need to encourage the public to keep abreast of developments in science and technology through a platform for use in clarifying any doubts they may have in science and technology. Freed from the frequency schedule and page limitations of the print medium, the Science Net has enabled “The Scientist Answers” section to be scaled up dramatically on the Web. In fact, the number of questions and answers published in the first 20 years of the print “The Scientist Answers” section was exceeded within the first few months of operation of Science Net! The Science Net is a good example of a “learner interaction with the experts” forum. Published studies on the effectiveness of learner interaction with experts are, however, lacking in primary journal literature, probably because the field is new and still evolving. While Science Net is unique in that it is the only such forum to be hosted on the Web of a science center or science museum and is backed by a large ensemble of scientists, there are other variants of this service on the Web. For example: 1.

Ask the Experts (www.sciam.com/askexpert_directory.cfm): Administered by

Continuing Science Education of the Global Public

2.

3.

4.

Scientific American magazine, this service features nine categories in science. An average of one answer to a question is posted every week. Ask Dr Universe (http://druniverse.wsu. edu/sendquest.asp): Hosted by Washington State University, one can ask any question—not just in science—and answers will be obtained from its faculty. However, the database of questions and answers is not large. Ask The Experts (www.physlink.com/ Education/AskExperts/): This site caters to questions and answers in physics and astronomy. The database, however, is not large. ScienceNet (www.sciencenet.org.uk): Hosted in the United Kingdom, this site features questions and answers on a range of science topics. However, it entertains questions only from within the United Kingdom.

These Web sites, though serving a useful purpose, do not provide as comprehensive or as frequent a coverage as Science Net, which reaches out to both generalist and specialist audiences. Some of the sites have restrictions—for example, ScienceNet entertains questions only from within the United Kingdom.

desIgn oF scIence net The database of questions and answers in Science Net is organized according to broad schema and sub-classifications: seven categories and nearly 70 sub-categories (Table 1). The hierarchical classification system is more a reflection of the need to categorize the thousands of questions and answers into a logical format that would permit ease of retrieval. From an operational standpoint, the categorizing of content in

multifarious ways has the advantage that visitors need not download entire files in order to access the database—this would be rather time-consuming on a slow network. The use of a simple layout, presence of a design motif without flamboyant elements, minimal use of colors and graphics, and use of simple fonts to present information contributes to the aesthetics of the site. Also, multimedia is not featured in the section. These strategies help to minimize eye discomfort and make the appropriate subset of the section less bandwidth-intensive for access—significant considerations in ensuring that the site stays breezy and popular. Navigation aids are provided on all pages, and this helps visitors migrate from one category to another seamlessly. A noteworthy aspect is that the section is updated almost every day—an important consideration in ensuring its dynamism and vibrancy.

IMPLeMentAtIon MechAnIcs Since its introduction in 1998, more than 20,000 questions have been posted by the global public. Nearly 6,000 of these questions have been answered by the organizers—the others are repeat questions, school homework assignments (which are strongly discouraged) and, to a small extent, unanswered questions. It is difficult for a single institution to take on the formidable task of answering all the questions posted because of the diversity of expertise and the number of personnel that would be needed for such an exercise. To address this challenge, the Singapore Science Center inducted the two premier universities in Singapore, the National University of Singapore and the Nanyang Technological University, as co-organizers also of this section. Science centers and universities make complimentary allies because they share a common focus in education. Such a partnership

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Table 1. Classification of questions and answers in Science Net Category Computer Science/ Information Technology/ Mathematics

Sub-categories Computer systems Computer vision & machine intelligence Database Internet

Earth Science

Agriculture/Farming Auroras/Northern lights Geology & Geophysics

Engineering/Technology/ Engineering Materials

Acoustics Aviation Biotechnology/Bioengineering Civil/Structural Engineering Electrical Engineering Electronic Engineering

Life Sciences

Animal behavior/Zoology Biochemistry/Biophysics Botany Ecology/Environment General Biology Genetics/Reproduction Genomics/Bioinformatics Human Anatomy Marine Biology

Physical Sciences

Analytical/Clinical Chemistry Fluid Dynamics General Chemistry General Physics High Energy/Particle/ Plasma Physics Lasers/Optics/Photonics Astrophysics/Cosmology Comets/Asteroids/Meteors General Astronomy Observatories/Telescopes Planetaria/Constellations

Astronomy & Space Science

Others

Science policies Tips on passing science examinations And so forth

is also necessary to endow the section with even greater credibility and in building up the database, important considerations in drawing visitors. The two universities provide faculty—more than 100 academics, who, together with (science) gradu-

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Sub-categories Mathematics/Algorithms Network & Communications Programming languages/ Computer software Robotics/Automation Security & Encryption Meteorology Natural resources Oceanography/Hydrology Food Technology Industrial/Production Engineering Materials Science/Polymers Mechanical Engineering Optical Engineering/ Photography Microbiology Molecular & Cell Biology Neuroscience/Vision Pharmacology/Medicine/Disease Physiology Safety/Health Systematics/Taxonomy Human Behaviour/Psychology Magnetism/Electricity Mechanics/Waves/Vibrations Organic/Theoretical Chemistry Relativity Theoretical/Quantum Physics Milky Way/Galaxies Radio Astronomy Search for Extra-Terrestrial Intelligence Space Exploration Satellites Solar System

ate staff of the Singapore Science Center, help to answer questions closest to their field of specialization. Some questions have two answers—this is more a consequence of some interesting or tricky questions being directed simultaneously

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to two experts. Besides diminishing the response time of getting at least one answer for a question, the strategy also offers the public the benefit of obtaining multiple perspectives. Sometimes, it may not be that easy to answer a question—such questions are then posted on the Web site itself, soliciting answers from the public. Hyperlinks are provided for some answers; this is not to be construed as a quick-fix solution for answers that are brief, but more as an extension of the textual narrative and also as a recognition that there needs to be a limit on the word count for each answer. The use of hyperlinks also encourages surfers to continue their learning experience, an important consideration in their continuing education. To facilitate the posting of questions by the global public, user-friendly features are incorporated in the site. Once a question is entered, a click-button sends it to the Science Net coordinator, who decides on the course of action. Has the question been answered before? Is it a school homework assignment? Is it a question for which the answer can be readily found by consulting standard books? Is it a question that will add

quality and build up the database? If the latter is the case, then the question is routed to the relevant expert in the resource panel. A search protocol is available for entering key words describing a topic or concept so as to facilitate checking the database. The search protocol helps to minimize the cognitive effort needed to browse the thousands of documents in the database. Explanations are usually kept to about one screen length to minimize cerebral indigestion. Lengthy explanations would require the cyber visitor to connect at different cognitive levels, and these generally have been avoided. In answering the questions, the organizers strive to strike a balance between scientific exactitude and popular appeal so as many people as possible can reasonably be expected to benefit from the answers given. A sample of a question and answer extracted from the Science Net database is presented in Figure 1. Science Net is available free to anyone with a personal computer and network connection. It

Figure 1. Example of Science Net entry in general physics Question No. 9931 We know that solid has a melting point. My students want to know how a gas can have a ‘ melting p oint’. T hanks.

States of matter are forms (solid, liquid, gas or plasma) in which material can exist. Whether a material is solid, liquid, or gas depends on its temperature and the pressure on it. Your students might have been confused when they read that the melting point of helium is -272.15 degrees C. They might have thought that helium is always a gas. At room temperature, helium is in gaseous state. But at temperature below -252.88 degrees C, helium is in liquid state. Helium freezes into solid state at -272.15 degrees C. The melting and boiling points of hydrogen, oxygen and nitrogen are as follows: m.p. (deg C) f.p. (deg C) Hydrogen -259.35 -252.88 Oxygen -218.4 -182.96 Nitrogen -210.01 -195

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is a good example of how communities of interest—scientists, with their specialist expertise, and the online public, hungering to satiate their curiosity—can engage in mutually enriching partnerships to achieve important educational goals.

AssessMent oF LeArnIng PotentIAL As Science Net is a forum for the public to obtain answers to their scientific queries, it is difficult to comment on the effectiveness of the learning that takes place. Several facts, however, attest to the effectiveness of the learning potential: (a)

(b)

(c)

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Since answers are generally pitched at the popular level, it is reasonable to assume that they are quite amenable to comprehension by the online public. The large number of questions posted and answered indicates that the section is drawing cyber visitors and fulfilling a useful role. Data in Table 2 show that the site has grown in size and complexity. Assuming that each answer occupies about half an A-4 size paper, the Science Net section itself comes to about 3,000 pages! Analyses of server logs have produced information on the popularity of the section. For the two-year period from January 1, 2001 to December 31, 2002, 24.8% of the total hits registered at the virtual science center has been for the Science Net section. This translates to a daily average of 17,533 hits and 3,771 page views for Science Net (Table 3). That is, the Science Net section is helping significantly to draw more online visitors to the virtual science center. About 80% of the surfers are from the Western world as well as some from other parts of Asia, while only 20% of the surfers are from Singapore!

We now comment on the cognitive dimension of the informal science learning engaged in by users. Since the activity focuses on learner interaction with experts through questions and answers, it is different from traditional learning contexts. For an activity to conform to the constructivist philosophy, four pedagogical aspects would have to be satisfied (Taylor, 1992; Phillips, 1998; Gance, 2002). • •

•

•

The user must be cognitively engaged in wanting to explore the environment for new information. The user must be immersed in a learning context that admits of problem-solving situations. There must be interaction with the learning environment through a hands-on, dialogic mode. The user must be ensconced in a social setting that permits interaction with other learners and mentors.

When users access the Science Net, it is clear that they seek to bridge gaps in their understanding of a particular topic or satiate their curiosity about some matter. This posits the stance that the user wants to explore the environment for new information through appropriate cognitive engagement. The learner is thus motivated to be

Table 2. Distribution of questions posted on Science Net by year Year 1998 1999 2000 2001 2002 2003 TOTAL

Number of questions posted 2,064 3,686 5,664 4,382 3,208 3,000 (estimate) 22,004

Continuing Science Education of the Global Public

Table 3. Web site statistics of Singapore Science Center for the period from January 1, 2001 to December 31, 2002 Section

Total hits

Average hits per day

Total number of page views

Virtual Science Center Science Net

52,377,282

71,749

10,208,973

Average number of page views per day 13,984

12,799,165

17,533

2,753,308

3,771

self-directed and independent in his learning attempts. The first postulate of the constructivist philosophy, therefore, is essentially satisfied. As for the second postulate, it is unlikely that this is satisfied because the essentially dialogic nature of the question-and -answer approach leaves little room for authentic problem-solving situations. The third postulate is satisfied to a significant extent, since one can argue that the interaction with the Science Net section is basically a hands-on session, with the computer mediating the learning experience; the presence of hyperlinks in a number of answers also provides a platform to continue the learning experience. Moreover, the question-and-answer format mirrors somewhat a conceptual dialogic session; that is, it is akin to an interaction between the learner and the material. The fourth postulate is partially satisfied in that there is learner interaction with experts by those who post questions, though there is no interaction with other users. It is clear that both the constructivist and didactic philosophies are at work in the Science Net section. While the nature of the question-andanswer format is compatible with the behaviorist and information transfer model relating to the didactic view, the shift from teaching to learning required of the users does confer significant strains of constructivism on the section, since the users are now empowered to take control of their learning needs in order to construct or extend their understanding of a topic.

Future trends The success of Science Net points to its possible replication in other non-formal learning environments, such as culture, national history and philosophy, as well as a range of enrichment needs. It is important to assemble a team of experts and host the section on the portal of a suitable institution. Tertiary institutions wishing to forge closer links with the local community can also try this example to address appropriate learning needs.

concLusIon Science Net has established itself as an online institution for the continuing (science) education of the public. Even though it serves the global public, it is recognized as a key node in the knowledge network formed by universities, schools and the community in Singapore. Opening a gateway to a wealth of resources, it has been an innovative experiment in reaching out to the online public as part of their informal education in science and technology, thus contributing in its own unique way to the development of a learning society in today’s networked world!

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reFerences Bevan, B., & Wanner, N.(2003). Science center on a screen. Int. J. Tech. Management, 25(5), 427-440. Delacote, G. (1998). Putting science in the hand of the public. Science, 280, 252-253. Gance, S. (2002). Are constructivism and computer-based learning environments incompatible? J. Assoc. for History & Computing, 5, 1-5. Jackson, R. (1996). The virtual visit: towards a new concept for an electronic center. In Conference on Here and How: Improving the Presentation of Contemporary Science and Technology in Museum and Science Centers, London. Orfinger, B. (1998). Virtual science museums as learning environments: interactions for education. The Informal Learning Review, 1-10. Phillips, D.C. (1995). The good, the bad and the ugly: The many faces of constructivism. Educational Researcher, 24, 5-12. Subramaniam, R. (2003). Science and technology centers have come of age. Int. J. Tech. Management, 25(5), 363-370. Tan, W.H.L., & Subramaniam, R. (1998). Developing nations need to popularize science. New Scientist, 2139, 52. Tan, W.H.L., & Subramaniam, R. (1999). Scientific societies build better nations. Nature, 399, 633. Tan, W.H.L., & Subramaniam, R. (2000). Wiring up the island state. Science, 288, 621-623. Tan, W.H.L., & Subramaniam, R. (2003a). Science and technology centers a agents for promoting science culture in developing nations. Int. J. Tech. Management, 25(5), 413-426. Tan, W.H.L., & Subramaniam, R. (2003b). Virtual science centers: web-based environments

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for promotion of non formal science education. In A.K. Aggarwal (Ed.), Web-based Education: Learning from Experience (pp. 308-329). Hershey, PA: Idea Group Publishing. Tan, W.H.L., & Subramaniam, R. (2004). Science Net: A virtual school for the extension (science) education of the public in Singapore. In C. Cavanaugh (Ed.), Development and management of virtual schools (pp. 244-251). Hershey, PA: Idea Group Publishing. Tan, W.H.L., Subramaniam, R., & Aggarwal, A.K. (2003). Virtual science centers: A new genre of learning in web-based promotion of science education. Proceedings of the 36th Hawaii International Conference on Systems Science. Taylor, P. (1998). Constructivism: Value added. In B.J. Fraser, & K. Tobin (Eds.), The International Handbook of Science Education, (pp. 1111-1123). Dordecht: Kluwer Academic Publishers.

Key terMs Broadband Network: A telecommunications network that leverages on various technologies to vastly speed up rates of information transfer between communication devices such as computers. Constructivist Learning: A learning philosophy that contends that learning occurs in incremental steps, leveraging on the previous knowledge of the learner about the topic. Continuing Education: The process of learning that continues beyond the formal years of education and/or outside the formal curriculum. Log Files: A record of all online activities occurring on the Web site as captured by the software monitoring the server. Online Learning: Learning that is leveraged on the Internet.

Continuing Science Education of the Global Public

Portal: A one-stop destination for online information.

Science Center: An institution for the popularization and promotion of science and technology to students and the public.

This work was previously published in the Encyclopedia of Distance Learning, Volume 1, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 408-414, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.28

Improving Electronic Information Literacy in West African Higher Education Ibrahima Poda Miami University, USA William F. Brescia University of Arkansas, USA

IntroductIon Electronic information literacy has gained increased importance with the advent of the new information and communication technologies which, driven by the convergence of computers and telecommunications media, are crucial for facilitating, supporting, and enhancing learning and for the knowledge-based economy of the future. In “Africa’s Information Society Initiative (AISI): An Action Framework to Build Africa’s Information and Communication Infrastructure,” African ICT experts appointed by the Economic Commission for Africa (ECA), have described the potential of the Internet to improve learning in higher education and established the foundation for this to become a reality in Sub-Saharan Africa. The AISI document that the group of experts produced was adopted by the ECA Con-

ference of Ministers as the African Information Society Initiative (AISI) in 1996. The document calls for the implementation of communication infrastructure plans that would be integrated into higher education in the following ways: a. b. c.

d.

e.

Providing equitable access to technological resources for distance education Strengthening local educational capacity Connecting schools, universities, and research centers to national and international distance education facilities, national and international databases, libraries, research laboratories, and computing facilities Reducing communications and administrative costs by building communications networks linking all educational establishments Promoting and supporting collaboration among teachers and researchers

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Improving Electronic Information Literacy in West African Higher Education

f.

Extending the reach of educational facilities in informal learning, especially to community level (ECA, 1999, p. 4)

Information literacy has been defined as a set of abilities to “recognize when information is needed and have the ability to locate, evaluate, and use needed information effectively” (Rader, 2002, p. 2). There are extremely few electronic information-literate scholars including administrators, faculty members, and students on campuses in Sub-Saharan West Africa because this part of the world has only marginally benefited from the explosion of the information and communication technologies. For instance, in its 1999 Human Development Report, the United Nations Development Programme (UNDP) found that developing countries suffer from the most serious infectious diseases. Yet they often have the least access to information to combat them. The information and communication technologies would deliver critical knowledge to information-poor hospitals (UNDP, 1999, p. 59). Concurrently, these technologies can bring critical knowledge and information to schools, colleges, and universities.

stAte oF dIFFusIon oF InForMAtIon technoLogy And InForMAtIon LIterAcy The information revolution has enabled academic institutions to provide a more flexible and open learning environment for scholars. For higher education institutions in Sub-Saharan Africa, the information and communication technologies represent an important opportunity for revitalizing higher education. They can provide a way for academics to overcome their isolation (Useem, 1999). As a result, there is a concerted effort to solve the problem of information technology access and its utilization in higher education institutions. In the 1994 Statement of Ouagadougou, Burkina Faso, administrators, academics, and researchers have

identified implementation strategies to develop and improve Internet access and use. Suggested strategies include the promotion the use of electronic communication technologies, the setup of required equipment for faculty in every discipline, the improvement of links between organizations, and the coordination of action (Renaud, 1994). Although there is now growing recognition of the far-reaching impact of the new information and communication technologies on learning, a number of issues continue to restrict its diffusion through public higher education institutions in Sub-Saharan African countries. Many of the scholars and administrators who want and need to use information technology have low ICT literacy levels. The shortage of financial and human resources, the lack of knowledge on the availability of potential tools, the insufficient telecommunications infrastructure, and rapid changes in technology are all contributing to this issue (Ali-Dinar, 1996). The greatest obstacle to use of information technology is not its acceptance as a tool in education, but how this tool will be acquired. Additional challenges for users in higher education institutions include lack of training to use technology features and services, follow-up, and continuity in utilization. Furthermore, educational and training facilities to help administrators, faculty members, and students become literate and acquire the proper skills are insufficient at most institutions (Odera, et al., 1996). A survey by the Association of African Universities (AAU) in 1998 found that only 52 of the 232 academic and research institutions had full Internet connectivity, while the remaining 180 institutions had access that was deemed inadequate (Useem, 1999). Consequently, the higher education community in Sub-Saharan West Africa lacks skills in areas including systems analysis, programming, maintenance and consulting, and at all operational levels that negatively affect their productivity. Higher education, largely state and publicsupported, is not only allocated decreasing appropriations but is also affected by the roaming

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influence of under-developed telecommunications infrastructure and limited available equipment. The state of higher education indicates and continues to reflect the levels of socio-economic status and policy making in the majority of the countries.

chALLenges to Ict And InForMAtIon LIterAcy In sub-sAhArAn west AFrIcA The major obstacles to widespread information technology access and literacy improvement include limited telecommunications infrastructure, cost of information technology equipment, and lack of support and expertise.

telecommunications Infrastructure The insufficiency of telecommunications infrastructure is expressed in abundant statistical information, available both in print and on the World Wide Web. Joyce-Hasham (2001) reported that less than 5% of the world’s population was online, more than 80% of the world’s population had never heard a dial tone, and fewer than 2% were connected to the Internet. Elliot (2000) noted that Sub-Saharan West Africa had 12% of the world’s population but just 2% of its telephone lines. Two of the major reasons for the sluggishness in infrastructure development are financial and political (African Development Forum, 2000). Political decisions failed to bring telecommunications services into rural areas, where more than 75% of the population lives. The existing telecommunications infrastructure is not adequate to sustain a reliance on distance education as a principal method for improving and expanding higher education. Low bandwidth is a limitation experienced by higher education institutions.

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costs Costs for ICT access in Sub-Saharan West Africa are out of reach for the majority of people. Burnheim (1999, p. 4) stated the following about the use of the Internet: Its outreach is largely confined to an educated and affluent elite living in the major cities. In many countries where local calls cost for Internet use for example upwards of U.S. $4 per hour (in some countries as high as $10 per hour). In addition, inefficiency and lack of customer service and user support are major factors that affect access and costs.

technology support and expertise Maintaining, repairing existing equipment, and software troubleshooting are major challenges, especially in rural areas where skilled information technology technicians are scarce or non-existent. Jensen (1999) reported that many computers are old and poorly maintained and found that support and training for technology use are under-funded. Numerous computers are not repaired and therefore remain unused, and available equipment is under-utilized due to illiteracy and lack of skills.

equIty oF oPPortunIty on cAMPuses While current level of ICT use might appear low, it represents a considerable increase over just a few years ago (Useem, 1999). Some countries have raced to establish the Internet on campuses. These campuses were the vanguard of information technology developments, and most of them provide all Internet services today. The French-

Improving Electronic Information Literacy in West African Higher Education

speaking countries have a higher profile on the Internet and greater institutional connectivity than the non-French-speaking countries. This is largely due to the strong assistance provided by the various Francophone support agencies and the Canadian and French governments, whose assistance was designed to balance the dominance of the English language on the Internet. While a number of higher education institutions have established distance education departments, the delivery platform to date has been text and correspondence-based supported by print material. Among the institutions that are currently using the Internet, some are beginning to explore video-conferencing and other forms of multimedia (Association for the Development of Education in Africa, 1999). For instance, the FORST program links Benin and three other countries with McGill University in Canada. The Réseau Africain de Formation a Distance (RESAFAD), or the African Network for Distance Education program in Benin, Burkina Faso, Guinea, Mali, Mauritania, Sénégal, and Togo, provides teacher training from French universities. The most ambitious distance education initiative on the continent to date is the African Virtual University (AVU) Project. This is the first satellite-based attempt to harness the power of information technologies to deliver university education in the disciplines of science and engineering, non-credit/continuing education programs, and remedial instruction to students in Sub-Saharan Africa. The AVU project was designed to deliver instructional programs, strengthen the capacity in African partner institutions, implement a network infrastructure, and implement a digital library program. The AVU Project plans for five Anglophone and five Francophone African countries to be linked in the initial pilot phase. Another virtual university program supported by the Agence de la Francophonie, or the Francophone Agency, is the Université Francophone Virtuelle or the Francophone Virtual University (Darkwa and Mazibuko, 2000). These

programs address many concerns relative to technology and information literacy and skills. Regardless of the linguistic difference, the interest in information literacy has been spurred by systematic transformation of education at all levels, and the adoption of information technology in higher education is increasing. Politicians and scholars are working to integrate the ICT into curricula to achieve relevant learning outcomes and augment electronic information literacy. User education in electronic information literacy has become an area of research, and most institutions of higher education are involved in activities in that area (Rader, 2002).

strAtegIes For IMProvIng Ict LIterAcy In hIgher educAtIon The combination of information and communication technologies infrastructure, weak policy and regulatory frameworks, and limited human resources has resulted in inadequate access to affordable telephones, broadcasting, computers, and the Internet. As a result, Sub-Saharan African countries have been unable to capitalize on information technology as a tool for enhancing livelihoods and creating new business and learning opportunities. Cross-border linkages at national, regional, and global levels have been constrained. In order to bring about change, the New Partnership for Africa’s Development (NEPAD) has set the following objectives: a.

b. c. d.

To double teledensity to two lines per 100 people by 2005, with an adequate level of access for households To lower the cost and improve reliability of service To achieve e-readiness for all countries in Africa To develop and produce a pool of information and communication technology-proficient

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Improving Electronic Information Literacy in West African Higher Education

e.

youth and students from which Africa can draw trainee information and communication technology engineers, programmers, and software developers To develop local content software, based specifically on Africa’s cultural legacy (NEPAD, 2001)

Even though the applications of information technology in higher education in Sub-Saharan West Africa have been severely underused and a lower level of information literacy still persists, there was tremendous improvement during the first years of the 21st century. Several studies have indicated that issues of access and quality should be addressed. Kinyanjui (2004) has emphasized a number of areas, including teacher or faculty development, math, science and technology, quality of elementary education, and access to tertiary education. The key priorities are to develop information and communication technologies infrastructure across the African continent and to develop skills in a critical mass of the population. ICT literature is available to help find, select, and implement the best strategies to improve ICT in Sub-Saharan West Africa. The most significant point identified is that the absence of ongoing training, professional development, and adequate administrative support for technology negatively impact Internet use in colleges and universities in emerging countries.

ongoing training Training has been found to be a key factor in promoting technology use. Providing faculty, staff, and students with needed skills to operate computers and use new applications is a necessary ingredient in Internet use. Yet, training is often the most underfunded item in an institution’s technology budget.

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Professional development Faculty, staff, and students need continual training in order to make technology applicable, and useful to them and to increase their performance. As a result, the provision of professional development activities will improve administration, teaching, and learning and contributes to achieving colleges’ and universities’ missions.

Administrative support Effective strategic planning and flexible processes in setting priorities according to the institution’s mission and resources allocation to meet institutional objectives, are key components of successful implementation of ICT. Decision makers and administrators must find ways to acquire computers and provide training, support, and incentives that encourage technology use. In order for effective information and communication technologies use to occur and the electronic information literacy to be integrated at institutions of higher education in Sub-Saharan West Africa, the following must occur:

Providing strong Leadership for change Campus officials must provide the strong leadership required to effectively bring about technological change. Without leadership and a strong sense of support for change in colleges and universities, the barriers affecting technology will remain. Leaders should implement tested methods for strategic planning that lead to technological change on a reasonable schedule, tested methods for generating the needed support, and for successful ways of financing technology.

Improving Electronic Information Literacy in West African Higher Education

developing a shared campus vision Developing a shared vision concerning the value and future impact of information and communications technologies is important. It is critical for campus opinion leaders, decision makers, and other important stakeholders to understand and agree that a shared vision is necessary and that it must be the guiding force behind campus planning and resulting strategy.

Implementing Faculty and staff development and training In this time of rapid changes in ICT, faculty and staff development is increasingly recognized as a key factor in enabling their successful use of computer and Internet technologies. At the institutional level, there must be a strong commitment to faculty and staff development and the provision of ongoing organizational support and training.

building consensus through a campus-wide strategic Plan

building Partnerships and Fostering Inter-Institutional collaboration

In addition to a shared vision, a written strategic plan for information and communications technologies that is understood and embraced by all must be employed. All key stakeholders must see the Internet (including the campus network) as an integral part of the institution’s information and communication-based resources. Institutional leaders must nurture this consensus and build on it to generate the funding and human resources necessary to effectively integrate the Internet into all aspects of the campus information and communications infrastructure. Institutions of higher education must create effective organizations that address all aspects of human and technical support for information and communications technologies. This information technology organization must establish and implement a computer-use support system and training campus-wide. The structure of the information technology organization encompasses a mix of centralized and decentralized strategies to support constituencies on campus. For instance, colleges and universities can establish a pyramid of support that offers both decentralized and centralized consultation for more complex issues.

Campus leaders must take the initiative in establishing and promoting institutional partnerships and collaboration at the community, regional, national, and international level. The purpose of partnerships should be to exchange experiences and learn from each other, facilitate exchange of students and staff, conduct joint research, implement network-based applications, and/or share the cost of joint course development and delivery. A campus can join or even form a regional network, actively participate in relevant national organizations, and involve an ever-wider circle of its opinion-leaders in developing a shared vision of networking for higher education.

concLusIon How should Sub-Saharan West African higher education institutions develop or improve electronic information literacy in the absence of or with limited information and communication technologies? Accessibility to the new information technology is still the major challenge in Sub-Saharan West African countries and, specifically, in higher education institutions. Meanwhile, scholars need training for effective new information technology use in order to function productively in

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work, social, and learning environments. Higher education institutions should provide leadership in learning and in training future citizens. Effective information and communication technologies integration and literacy will require a commitment from administrators and the full participation of faculty members and students.

reFerences African Development Forum (March 2000). Theme 4: Democratizing access to the information society. Retrieved July 27, 2004, from http://www. uneca.org/aisi/ Ali-Dinar, A. B. (1996). Prospects for information technology in Africa. Retrieved June 9, 2004, from http://www.sas.upenn.edu/African_Studies/ECA/eca_plnrs6.html Association for the Development of Education in Africa. (1999). Tertiary distance learning in SubSaharan Africa. ADEA Newsletter, 11(1), 1-4. Association of African Universities. (2000, May). Technical experts meeting on the use and application of Information and communication technologies in higher education institutions in Africa. Tanzania: University of Dar Es Salam 17-19. Burnheim, S. (1999, February). The right to communicate: The Internet in Africa. Retrieved July 27, 2004, from http://www.article19.org/docimages/591.doc Darkwa, O., & Mazibuko, F. (2000). Creating virtual learning communities in Africa: Challenges and prospects. Retrieved June 14, 2004, from http://www.first monday.dk/issues/issue5_5/ darkwa/ Economic Commission for Africa. (1999, July). Developing national information and communications infrastructure (NICI) policies, plans, and strategies: The “why” and “how.” Retrieved

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January 31, 2002, from http://www.anais.org/ARTICLES/DOC20.HTML Elliot, A. (2000, July). Internet issues in Africa. Retrieved July 27, 2004, from http://www.middle march. co.nz/anne/africa/intro.html Jensen, M. (1999, July ). ICT infrastructure in Africa: A summary. Retrieved July 27, 2004, from http://www3. sn.apc.org/africa/infra.htm Joyce-Hasham, J. (2001, March). Web offence. The World Today, 11-13. Kinyanjui, P. E. (2004). New partnership for Africa’s development initiatives in information and communications technologies and associated capacity of building. Retrieved June 14, 2004, from http://www.africa odl.org/conference/paper_kinyajui.htm New Partnership for Africa’s Development. (2001). The new partnership for Africa’s development. Retrieved June 14, 2004, from http://www.uneca. org/eca_resources/Conference_Reports_and_ Other_ Documents/nepad/NEPAD.htm Odera, M., Lawrie, M., Bennett, M., & Goodman, S. (1996). Information technology in Sub-Saharan Africa. Retrieved June 9, 2004, from http://www. sas. upenn.edu/African_Studies/Comp_Articles/ Information_Technology_117.html Rader, B. H. (2002). Information literacy: An emerging global priority. Retrieved June 9, 2004, from http://www.nclis.gov/libinter/ infolitconf&meet/papers/rader-fullpaper.pdf Renaud, P. (1994). Statement of Ouagadougou. Ouagadougou, Burkina Faso: ORSTOM. United Nations Development Programme. (1999). New technologies and the global race for knowledge. Human Development Report, 57-76. Useem, A. (1999, April). Wiring African universities proves a formidable challenge. The Chronicle of Higher Education, A25.

Improving Electronic Information Literacy in West African Higher Education

Key terMs Centralized Strategies: A managerial approach through which support for information technology use for all constituencies is provided by a single on-campus structure. Cross-Border Linkage: An active connection, relation, or association between two or more institutions separated by a geographic distance or boundary. Decentralized Strategies: The structure of the information technology organization encompassing supporting units that are located at the school or college level. Diffusion: The act of a higher education institution using information, professional relationships, and structured methods to incorporate an innovation into learning, research, and administration, bringing about new integrated system-wide change.

E-Readiness: The state of being prepared to operate and utilize electronic technology. Information Literacy: An ability that has been acquired by training to locate, understand, evaluate, and use needed data efficiently and effectively. Institutional Connectivity: Refers to an organization or institution’s ability to link with others’ networks and the rate at which this connection is made. Stakeholders: A group of individuals or organizations who has a share or interest in the successful outcome of the establishment and sustainability of an enterprise. Strategic Plan: A formulation of an organization or institution’s scheme or program for the accomplishment, enactment, or attainment of essential goals within a specified period of time. Teledensity: The number of telephone lines per 100 inhabitants in a given geographic area.

This work was previously published in the Encyclopedia of Developing Regional Communities with Information and Communication Technology, edited by S. Marshall, W. Taylor, and X. Yu, pp. 427-432, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.29

How ePortfolios Support Development in Early Teacher Education Victor McNair University of Ulster, Northern Ireland Kevin Marshall Trinity College Dublin, Ireland

AbstrAct This chapter reports on a pilot study which examined how student teachers of a one-year Post Graduate Certificate in Education course in Northern Ireland developed reflective ePortfolios and then used them to embed ICT in their first (Induction) year as qualified teachers. Two central themes emerged. First, the process of constructing the ePortfolio developed confidence among the beginning teachers which supported them when faced with the challenges of starting teaching. Second, the ePortfolio was used to ease the transition from Initial Teacher Education to

Induction, but where there is a lack of critical reflection, barriers to professional development can emerge. These issues are discussed within the context of technology policy, teacher training, and emerging technology in Northern Ireland.

IntroductIon Our society is undergoing profound changes, with a resulting increase in the demands placed upon our education system. At the same time, technology is opening up new possibilities regarding when and how learning can take place.

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How ePortfolios Support Development in Early Teacher Education

Educating teachers in the effective use of information and communications technology (ICT) in the classroom is a key requirement to ensure that the learning potential of new technologies is fully exploited. But ICT can also extend beyond how it can be used to improve children’s learning (Wishart & Blease, 1999) to create more effective teaching resources (Barron, 1998) and to generate new learning models (Somekh, 2000). Increasing the ICT literacy of teachers, particularly at the early stages of their teacher education, can enhance how and when they themselves learn about teaching. This chapter reports on a pilot study which examined how 36 of the 125 student teachers of a one-year Post Graduate Certificate in Education (PGCE) course at the University of Ulster in Northern Ireland developed reflective electronic or ePortfolios, and then used them to embed ICT in their first (Induction) year as qualified teachers. Their practices and concerns are highlighted through an analysis of how they used the ePortfolio as a tool for critical reflective practice, and as a catalyst for initiating professional dialogue with their school-based colleagues in order to improve their teaching. Teacher tutors in schools were also interviewed to determine the use they made of the information and structure of the ePortfolio. Central to the chapter is how they articulated their professional competence, how they identified appropriate professional development trajectories, and how, when qualified, they continued to develop those trajectories. The support roles of their Induction tutors are also examined to determine how they identified specific needs and how they provided accurate and appropriate support pathways. The study discusses the implications for Northern Ireland’s eLearning policy framework, and also comments on how ePortfolios have the potential to enhance the professional development of beginning teachers by providing access to a range of data that can support more targeted progression pathways.

bAcKground to the study In Northern Ireland, the Education Technology (ET) Strategy (DENI, 1998), derived from the United Kingdom “National Grid for Learning” (DfEE, 1997), laid the policy foundation that gave rise to a development program called Classroom 2000 (C2K). The program provided a comprehensive computing infrastructure for Northern Ireland’s 1,245 schools, and mandatory ICT training for its 20,700 full-time teachers. It also procured high-speed connectivity with 40,000 networked computers. A managed learning environment (MLE) now supports this infrastructure with administration and professional development services (Department of Education, 2004), with ICT strongly integrated into teaching through the provision of a wide range of curriculum-based and specialist software. More recently, the ET strategy has been replaced by “emPowering Schools” (Department of Education, 2004) which further centralizes eLearning, online collaboration, and the widespread use of digital technologies to support lifelong learning for all teachers and children (Anderson & Stewart, 2004). Where the ET strategy was characterized by varying rates of development and different ICT practices in schools (Clarke, 2000; Anderson & Stewart, 2004), “emPowering Schools” has set targets for individualized learning, greater coherence across schools in the use of ICT, and better access by teachers and children to rich multimedia resources. For higher education institutions (HEIs) responsible for initial teacher education (ITE), emPowering schools offers the possibility of more focused professional support for student teachers through greater online collaboration, and more reliable and faster connectivity. Primarily, however, the continuously converging and improving ICT practices of schools mean that professional support dialogue with student teachers can focus more on effective teaching and learning and on reflections about that teaching. These can be better

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recorded, accessed, and commented on by peers and others. The now ubiquitous use of ICT means that an emerging data-rich personal history can be summarized in ways that allow both the user and support personnel to identify salient professional development issues, to articulate the potential impact of those issues on teacher progression, and to plot pathways for future development and growth.

Moving Toward Reflective ePortfolios Traditionally, the portfolio was a simple way of archiving a student’s finest work in folders (Herbert, 1998). In essence, it was viewed as a container of work. Of late, however, the portfolio has become a central component in the debate regarding alternative methods of assessment. Proponents of authentic assessment argue that portfolios offer students the opportunity to display creatively who they are and what they can do (Darling-Hammond & Falk, 1997; Gensishi, 1997; Wolf, 1999). Thus, the opportunities to demonstrate growth as opposed to static assessment methods (i.e., tests) are afforded to students. The debate about the use of portfolios has intensified in the domain of teacher professional development (Campbell, Cignetti, Melenyzer, Nettles, & Wyman, 2000). Ellsworth (2002) argued that the development of a portfolio has led to a deeper understanding of teachers’ professional practices. Similarly, Wolf (1995) argued that portfolios document teacher effectiveness and provide opportunities for reflection, collegiality, and professional dialogue. Moreover, the time and effort spent by students reflecting on teaching episodes create a deeper awareness of the characteristics of effective teaching (DuttDoner & Gilman, 1998). In short, the process of developing a portfolio encourages students to think about the type of teachers they want to be. Additionally, development throughout any teacher education course can be used to document

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learning and may ease the transition from ITE to Induction by allowing those in schools responsible for beginning teachers to review their history and experiences. McLaughlin and Vogt (1996) argued that portfolios present what candidates have learned; they also validate the credibility of the teacher training program and increase the candidates’ self-confidence. Similarly, they can have the added advantage of being used as a marketing tool when the prospective teacher is seeking employment. In recent years, technology has enabled the move from portfolios to ePortfolios that facilitate focused interrogation of their contents through hyperlinking and searching tools in ways that allow different support personnel to target quickly those issues that they can help address. In the same way, portability offered by either Web-based or harddisk-based storage methods means that distribution to, and access by, a range of interested support personnel are not bounded by time or distance. Moreover, the mechanisms for commenting on, collaborating with, and discussion of issues raised in the ePortfolio are more easily accommodated through tools such as comment features, online discussion groups, and synchronous forums. The benefits of ePortfolios include the integration of ICT-based teaching into the means of displaying its teaching potentials and gains through reflection, critical thinking, and evaluative comment. More easily can teachers present a wide range of materials, along with different forms of media to offer an expanded picture of achievement (Goldsb & Fazal, 2000). In a growing climate of ICT use, therefore, ePortfolios serve as an integral part of a process for monitoring ongoing professional growth. To realize the full potential in their teaching, student teachers must come to view them as tools for reflection on practice and for assessing professional growth over time. Reflective thinking is the “active, persistent and careful consideration of any belief or supposed form of knowledge in light of the grounds that support it and the further

How ePortfolios Support Development in Early Teacher Education

Figure 1.

conclusions to which it tends” (Dewey, 1933, p. 9). Consequently, to be useful, ePortfolios must be clear, organized, and goal driven, and must provide evidence that documents the attainment of the knowledge, skills, and dispositions required to be a successful teacher. In addition to discussing ePortfolios as an effective tool in teacher professional development, the concepts of “reflection” and “critical reflection” have entered the vernacular

regarding teacher education and particularly that of ITE. There is a body of research arguing that reflection supports the development of teaching competence by providing a framework in which student teachers can think critically about their teaching (Convery, 1998; Hatton & Smith, 1995; Harrington, 1992). However, it is insufficient to provide such a structure without the opportunity for student teachers to reflect on their own think-

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ing and experience. This study aimed to provide such a framework, and consequently, we have defined a professional ePortfolio as: A digital profile of teaching experiences and reflections through which a community of practitioners can engage in online professional dialogue and support. To demonstrate this, as part of their assessment of teaching, students were required to build a reflective ePortfolio during their PGCE year. The focus for the assessment was the application of ICT in their teaching, an example of which is shown in Figure 1. Slide A shows the front of the “Home” page with its linked sections (the navigation column on the left). Each section has an introductory slide similar that that of Slide B, with further links (shown as an icon) that, when clicked, open up more detailed evidence and comment about the use of ICT in that section (Slide C). Finally, a summary comment allows the student to highlight areas for development in his or her Induction year (Slide D).

MethodoLogy For this pilot study, 10 Art and Design, 15 Geography, and 11 Technology and Design students developed ePortfolios, while all other PGCE students compiled traditional paper-based accounts of ICT in their teaching. Semi-structured interviews were conducted with 19 of the 36 former students after six months of teaching (some had not secured teaching posts, some were teaching in other countries, and some could not be contacted). The interviews sought to probe whether the ePortfolio had been used in their teaching, if it had, in fact, been the expected catalyst for dialogue in their employing school, and if the trajectories they had established had been maintained. Conversely, if the ePortfolio had not been used, it was important to identify the barriers to dialogue and to deter-

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mine what professional development strategies were needed to reverse this in future. To support triangulation, semi-structured interviews were conducted with six of their teacher tutors in schools to determine how they viewed the former students’ use of ICT to support learning and teaching activities, and whether the ePortfolio had been a source of professional dialogue and support. All teacher tutors had been involved with the beginning teachers we interviewed.

resuLts From the data, two main themes emerged and are summarized as follows: 1.

2.

How the process of construction and the ePortfolio itself developed confidence among the student teachers, but also how that confidence was set against the challenges of starting teaching. How the beginning teachers used the ePortfolio to ease the transition from ITE to Induction, and how—when there is a lack of reflection—barriers to professional development can emerge.

the ePortfolio as a basis for Developing Confidence Confidence was the strongest theme and was mainly derived from teachers’ reflections on the increased range of teaching strategies ICT gave them, and their claims for children’s increased motivation as a result of ICT in teaching. In relation to varying teaching strategies, teachers linked the process of compiling the ePortfolio to the development of child-centered learning: “[The process of analyzing my actions] changed my teaching in that I allow the pupils to work by themselves more.” They also linked the ePortfolio to children’s deeper levels of understanding of the subject: “[Compiling the ePortfolio] gave me more

How ePortfolios Support Development in Early Teacher Education

time to focus on the initial principle of a topic.” In relation to how the use of multimedia in their teaching was reported to increase pupil motivation, one art and design teacher commented: “Well, [compiling the ePortfolio] opened up my eyes to the ways in which ICT can be used in an art classroom ... The children give me good feedback and they seemed to be very pleased with themselves, thinking they had achieved something that looked good ... ” Confidence also related to beginning teachers’ ability to make deeply reflective comments about their teaching, going beyond pragmatic surface analysis (Kyriacou, 1985) and examining deeper pedagogical beliefs (Davies, 2003): “[Compiling the ePortfolio] made me totally rethink my attitudes to teaching. I realized that every pupil is an individual and they have their own needs, they all have to be reached on different levels.” These deep levels of analysis were also recognized by teacher tutors in schools. One tutor reported “ ... very well thought-out applications of ICT ... ,” and another teacher tutor indicated that “the beginning teacher knew enough to go beyond simple use of ICT but to integrate it into pupil learning.” The above comments show how the focus on ICT in teaching was enhanced by beginning teachers’ reflections, to the extent that teacher tutors recognized their teaching as effective. What is interesting about these comments is that the beginning teachers linked the process of compiling the ePortfolio to positive influences, pupil learning, and motivation. Other confidence indicators were more utilitarian in nature and were linked to the ePortfolio as a product from which to draw the accumulated resources. Teacher confidence arose from the view that they had seemingly rich material to support their planning, offering choices for teaching strategies that were easily accessible and adaptable: “ ... it is good to have it all on disk and bring the information if and when you need it, it’s like having your own teaching file.” This teacher valued the accessibility of the ePortfolio as a resource, while others valued its availability as

a source from which to review their own skills: “ ... you know that when it comes to teaching a topic you have the resources you need to recap on how it is done.” Other comments linked the ePortfolio to their range of skills and experiences: “I think [the purpose of the ePortfolio] was so that I had a log of all of the work I had completed to date ... ” “Well [the ePortfolio] enables me to look back over everything I know in relation to ICT ... ” Skill range was an important issue when it came to validating their competence to their more experienced colleagues: “Putting all of your skills, not just from the PGCE, into one file to prove you are ICT competent, and to make you feel more confident in yourself.” Or when seeking employment: “[Citing examples from the ePortfolio] sounds impressive when you are in an interview and when you are writing a CV.” Indeed, teacher tutors in schools promoted the use of the ePortfolio as a confidence builder: “(T)he ePortfolio has an intrinsic value to the induction teacher ... it summarizes what they can do.” Some caution, however, needs to be used when attributing a positive attitude to the development of the ePortfolio. We acknowledge that to have this resource as a “good start” when seeking employment is a high priority for beginning teachers. Teacher comments above show the contrast between those reflections that view the ePortfolio as an accumulation of resources, and those that foster a deeper understanding of the nature of teaching. The former are, of course, essential, but we view them as the starting point for competence. The latter represent more developed understanding of the function of the ePortfolio and, indeed, reflective practice in teaching. The contrast between these issues will be further discussed in the conclusion.

transitional Issues related to Ict in teaching The beginning teachers reported both positive and negative Induction experiences which, respec-

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tively, were seen as supports for and barriers to the transition from ITE to Induction. Predominantly, beginning teachers’ own perceptions shaped their dialogue with schools, and two main issues emerged. The first was that the ePortfolio was used as a means of personal development, and the second was that the beginning teachers were seen as having expertise that the school could use, not an uncommon finding (McNair & Galanouli, 2002, p. 193). Regarding personal development, comments related to how beginning teachers had identified their own strengths and weaknesses through constructing the ePortfolio. One teacher, on commencing employment, continued the process, making judgments about how her needs matched those of the school: “I have been developing my ePortfolio as part of my induction ... The actual practice of putting together the ePortfolio made me push myself further than I would have ... ” This aspect of the benefit of the portfolio was also highlighted by her teacher tutor who noted that the beginning teacher “was very good at augmenting ICT into her teaching.” On the basis of the previous section, most beginning teachers had a strong reflective view of their teaching, and it was important, therefore, to determine if they were able to translate these positive views into actions and to establish dialogue about their use of ICT with other teachers. Where this was the case, dialogue tended to focus on the beginning teachers as “experts.” For example, when the ePortfolio was presented to their employing schools, the roles were reversed and experienced teachers were supported by the beginning teacher. In one situation the ePortfolio was “ ... being used in the geography department ... ,” indicating a possible emphasis on content rather than on any process of professional development. (By content we mean resources, such as worksheets and other teaching media, rather than emphasis on the teaching skills and understanding that gave rise to them.) However, it shows how the teacher’s work, even as a resource, can be a

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potential initiator of dialogue. Other participants reported that dialogue was more focused on their own development: I explained that I had completed an ePortfolio and the interview panel seemed very interested, it was from here that the Head asked to see the work when I got the job and asked me to become involved in the whole school’s eLearning program. Other initiators of dialogue were seen either in a whole-school context or with close subject specialists: I have shown it to my fellow teachers and my teacher tutor, they think it is a good idea to have a record of all that you know and can do in relation to ICT. This comment again shows how the perceptions of the ePortfolio can focus on content rather than the process of building effective teaching practices. Nevertheless, there was evidence of reflective practice itself being used as an initiator of dialogue: “[The process of compiling the ePortfolio] did make me ask for more help in ICT.” Other data, though, showed that the beginning teacher’s dialogue was strongly influenced by the school’s reactions. For one, dialogue stopped as a result of the school’s apparent lack of knowledge about the ICT-focused ePortfolio: “I have mentioned it to [the staff in school], but I felt like they quickly skimmed over it because they didn’t know what it was.” Some beginning teachers, in spite of their confidence in the use of ICT, were reluctant to broach any discussion about this, possibly because they saw a contrast between their expertise and the use they had observed in the school: “As I was a new teacher I did not think colleagues would have an idea what it is for and how it should be used.” Others were more reluctant to initiate dialogue in schools for reasons based on their own percep-

How ePortfolios Support Development in Early Teacher Education

tions of the need for it: “[I assumed that the ICT portfolio] was only for myself, for resources and for reflection” or “I was unsure of its relevance to the school.” Others seemed to prefer to leave any initiative to the school: “No one asked to see [the ICT portfolio].” These comments may indicate a schooldominated agenda that inadvertently suppresses dialogue, at least in this area of teaching. The reasons behind these comments are not certain. One teacher tutor deliberately focused, for the first term, on immediate issues such as “survival ... getting established ... and coping with the workload.” Indeed, when asked about ICT-related dialogue, it was said that she and the beginning teacher “had other things to talk about.” Beginning teachers in such situations may prefer to adhere to the school’s agenda and continue to teach in their established ways—happy, it seems, that other teachers left them to it: “I don’t think anyone else has asked about it because they just assume I know about ICT.” This comment was borne out by one teacher tutor who stated that, “ [The] beginning teacher’s competence in ICT was such that they could integrate it into their lesson with ease.” With the exception of the last two comments, these findings contrast with the established culture of the PGCE course from which the beginning teachers have emerged, where they are required to routinely engage with subject-department teachers and student-tutor staff on a range of issues (PGCE, 2005). For example, one beginning teacher showed how the dialogue with her former placement school supported her work, “I had no problems asking for help. I found my placement school [during the PGCE course] very accommodating ... which really helped.” While former students may regard the university requirements for dialogue as no longer necessary, it is also possible that as beginning teachers they defer such dialogue in favor of more pressing issues suggested by the teacher tutors. In these cases, some eight months

between taking up post and being interviewed for this study, the lack of discussion may inhibit the Northern Ireland-wide implementation of ICT and may indicate the need for senior school management and education support personnel to provide a more explicit structure for initial professional development in ICT-related issues. These beginning teachers’ apparent reluctance to initiate discussion may point to the need for ITE tutors to develop a more proactive approach to engaging in professional dialogue with schools so that interaction patterns and skills are more established. Similarly, Subject Heads and Senior Teachers responsible for beginning teachers may need to promote more structured and sustained dialogue. This was illustrated by one beginning teacher who decided to defer any dialogue: “I will discuss [the ICT portfolio] when I get established.” This stance was supported by that of another who blamed the lack of dialogue regarding the ePortfolio on the belief that it was new to the school: “I felt that the whole experience was new for everyone including the staff.” Beginning teachers demonstrated awareness of the need for schools to be more proactive in initiating dialogue based on the ePortfolio. The comments below indicate their beliefs about how schools could make very good use of the information they receive: “I feel that if the schools [examined] it more they would realize that it is an untapped resource, that would be useful for the whole school, teachers and pupils.” Another beginning teacher could see the contrast between previous experiences and the school’s stance on the ePortfolio: “[ePortfolios] will become more relevant when the schools learn how to use them properly.”

dIscussIon There are two major issues that emerge as a result of this study, namely, how the use of ePortfolios can move from pragmatic to strategic application,

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How ePortfolios Support Development in Early Teacher Education

and how HEIs and schools can best identify development pathways that synergize their acceptance by all support personnel.

From Pragmatic to strategic Application The study has highlighted confidence as a major positive influence on beginning teachers, one that resulted from being able to demonstrate ICT competence and from having the ePortfolio as a resource bank that allowed them a “pragmatic” start in teaching. This, in turn, supported them in initiating and sustaining dialogue with peers. While this “pragmatic” role of the ePortfolio is, perhaps, secondary to the aims of HEI and school tutors, it is clear that the workload of beginning teachers is alleviated through drawing on such resources. However, such dialogue was initiated only in a minority of cases investigated, beginning teachers preferring to leave the initiative and the agenda for professional development to schools. Faced with the opportunities that the ICT ePortfolio offered, this trend suggests that there are significant differences between what HEI tutors saw as student needs and what teachers saw as beginning teacher needs. This “needs gap” leaves students with the expectation that the practices

they develop in ITE will further be fostered in Induction. The study has shown that this expectation can be realized, and when it is, there is positive professional development that highlights the consistency of approach between schools and HEIs. Other less consistent experiences highlight the need for schools to liaise with HEIs to develop the common approaches to support. Effective professional development ensues, we believe, when beginning teachers’ individual needs are augmented with more strategic use of the information provided within the ePortfolio. Under these conditions, students have the confidence to identify their own needs and articulate them to others in the school in ways that support both sets of needs. The strength of the ePortfolio lies in the variety of access it provides to a range of support personnel. We found limited use of the ePortfolio in this way, in spite of strong guidance provided in ITE about how best to use it. This is, of course, partly to do with teacher tutors allowing students to get started in the school and also allowing main themes to emerge through observation, not least, the issue of classroom management. However, we take the view that there is a range of data that would be of interest to different support personnel and that the culture of identifying, discussing, and acting on a range of data needs to be developed.

Figure 2. The link between the pragmatic and strategic approaches

Pragmatic Application Personal Confidence Resource Bank Individual Use

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Strategic Application Effective Professional Initiating Dialogue Development Planning Pathways Developing Partners

How ePortfolios Support Development in Early Teacher Education

The link between the pragmatic and strategic approaches is illustrated in Figure 2, which shows that effective professional development is fostered by integrating both.

ePortfolios: development Pathways In the context of Northern Ireland’s developing eLearning infrastructure, opportunities are emerging that allow the data-capturing, synchronous and asynchronous access properties of ePortfolios to provide different forms of support than are currently the case. At present, support is largely concentrated in the schools where close colleagues and the teacher tutor provide the bulk of support. ePortfolios allow a broader constituency to form partnerships with the schools by allowing access to, and comment on, emerging issues that the strictly sequential transition from Initial to Induction prevents. ePortfolios allow HEIs and schools to overlap their support, thus providing, for the beginning teacher, greater continuity. In Northern Ireland, school autonomy and HEI funding need to be reviewed for such collaboration to take place. We suggest three development pathways. First, while the data in this study was essentially textbased with graphic media, the emerging ICT infrastructure in Northern Ireland will soon support a wider range of media. HEIs and schools should investigate the technical and professional development implications of the wider use of multimedia to formatively evaluate teaching. Second, protocols for access to ePortfolios need to transcend the Initial Induction sequence in which HEIs, in practice, have limited involvement in Induction. Rather, an integrated and mutually inclusive support mechanism based on multimedia and online formats would allow overlapping support and would provide consistency and consensus in how to use data and what actions to take following their analysis. Third, such partnerships have to

evolve within a policy framework agreed upon and supported by all teachers and HEIs. This will require a major shift in thinking towards a culture where support is asynchronous, collaborative, and inclusive of comment beyond the school. The major question facing all support personnel is how to agree on such an ePortfolio structure so that students, teachers, and HEI tutors have a common approach to its development and use. Finally, we add a word of caution. Harrington (1992) argued that reflection is a habit of mind central to the development of effective teachers. Consequently, the recording of reflective practice should, therefore, lie at the heart of this process. The temptation may be to develop the technology to its full potential while ignoring our guiding principle of developing confident, competent, and effective teachers. In effect, technology enables the practice of reflection and profession dialogue, but is not the driver in this process.

concLusIon Over the next 10 years, technology will enable more collaboration and partnership among a range of institutions, with greater remote access to a wider range of information that can be managed better and provide a more accurate picture of beginning teacher needs. The challenge facing the education community is that, with the variety of mobile and wireless technologies set to increase, the accumulation, management, and dissemination of professional development support should be based on a consensus of what constitutes valid information, how it informs good teaching, and how development pathways can improve pupil learning.

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AcKnowLedgMent This project was funded by the Northern Ireland E-Learning Partnership (http://elearningfutures. co.uk) and the Microsoft Ireland Innovative Teachers Programme (INTP) (http://microsoft. com/ireland/education). The Innovative Teachers Programme (INTP is part of the Partners in Learning (PiL) programme aimed at providing a framework for teachers to integrate technology in their respective subjects.

reFerences Anderson, J., & Stewart, J. (2005). Relevant, reliable and risk-free. In M. Sellinger (Ed.), Connected schools. London: Cisco Systems.

inclusion: Embracing all our children. New York: Routledge. Davies, D. (2003). Pragmatism, pedagogy and philosophy: A model of thought and action in primary technology and science teacher education. International Journal of Technology and Design Education, 13(3), 207-221. Department of Education. (2004). Empowering schools in Northern Ireland. Bangor, NI: Department of Education. Department of Education for Northern Ireland. (1988). A strategy for education technology in Northern Ireland. Bangor, NI: Department of Education for Northern Ireland. Dewey, J. (1933). How we think. Lexington, MA: D.C. Heath.

Barron, A. (1998). Designing Web-based training. British Journal of Educational Technology, 29(4), 355-370.

DfEE (Department for Education and Employment). (1997). Connecting the learning society. London: DfEE.

Barton, J., & Collins, A. (1993). Portfolios in teacher education. Journal of Technology for Teacher Education, 44(2), 200-211.

Dutt-Doner, K., & Gilman, D. (1998). Students react to portfolio assessment. Contemporary Education, 69(3), 159-165.

Campbell, D., Cignetti, P., Melenyzer, B., Nettles, D., & Wyman, R. (2000). Portfolio and performance assessment in teacher education. Boston: Allyn and Bacon.

Ellsworth, J. Z. (2002). Using student portfolios to increase reflective practice among elementary teachers. Journal of Technology for Teacher Education, 53(4), 342-355.

Clarke, L.M. (2002). Putting the ‘C’ in ICT: Using computer conferencing to foster a community of practice among student teachers. Technology, Pedagogy and Education, 11(2), 163-180.

Genishi, C. (1997). Assessing against the grain: A conceptual framework for alternative assessments. In A. L. Goodwin (Ed.), Assessment for equity and inclusion: Embracing all our children. New York: Routledge.

Convery, A. (1998). A teacher’s response to ‘reflection-in-action’. Cambridge Journal of Education, 28(2), 197-205. Darling-Hammond, L., & Falk, B. (1997). Supporting teaching and learning for all students: Policies for authentic assessment systems. In A.L. Goodwin (Ed.), Assessment for equity and

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Goldsby, D., & Fazal, M. (2000). Technology’s answer to portfolios for teachers. Kappa Delta Pi Record, 36(3), 121-123. Harrington, H. (1992). Fostering critical reflection through technology: Preparing prospective teachers for a changing society. Journal of Information Technology for Teacher Education, 1(1), 67-82.

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Hatton, N., & Smith, D. (1995). Reflection in teacher education: Towards definition an implementation. Teacher and Teacher Education, 11(1), 33-49. Herbert, E. A. (1998). Lessons learned about student portfolios. Phi Delta Kappan, 79(8), 583-586. Kyriacou, C. (1985). Conceptualizing research on effective teaching. British Journal of Education Psychology, 55(1), 148-155. Littlejohn, A. (2002). Improving continuing professional development in the use of ICT. Journal of Computer Assisted Learning, 18(2), 166-174. McLaughlin, M., & Vogt, M. (1996). Portfolios in teacher education. Washington, DC: International Reading Association. McNair, V., & Galanouli, D. (2002). Information and communications technology in teacher education: Can a reflective portfolio enhance reflective practice? Journal of Technology for Teacher Education, 11(2), 181-196. Rees, R. (2002). Second year teacher education candidates reflect on information technology in Ontario secondary schools: How it is being used and the challenges it presents. Technology, Pedagogy and Education, 11(2), 143-162. Somekh, B. (2000). New technology and learning: Policy and practice in the UK, 1980-2010. Education and Information Technologies, 5(1), 19-37.

Wishart, J., & Blease, D. (1999). Theories underlying perceived changes in teaching and learning after installing a computer network in a secondary school. British Journal of Educational Technology, 30(1), 25-41. Wolf, K. (1999). Teaching portfolios and portfolio conversations for teacher educators and teachers. Action in Teacher Education, 17(1), 30-39.

Key terMs Electronic Learning (eLearning): Developing new understandings using any form of technology as a medium. Initial Teacher Education (ITE): The preparation of teachers before they gain employment. Lifelong Learning: Learning that is continuous throughout life, irrespective of employment, lifestyle, or age contexts. Managed Learning Environment (MLE): A virtual workspace in which curriculum, resources, and online activities are supported, monitored, and facilitated. Professional Competence: Levels of knowledge and understanding that are applied to professional activities in ways that produce meaningful outcomes.

This work was previously published in the Handbook of Research on ePortfolios, edited by A. Jafari, pp. 474-485, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.30

Examining Perceptual Barriers to Technology:

A Study on the Diffusion of Educational Technology and Education Reform LeAnne K. Robinson Western Washington University, USA

AbstrAct This study examines educators’ perceived barriers to technology integration and the relationship to education reform. Educators and administrators from four elementary schools in Washington State were interviewed in their classrooms during a three-month period. The schools differed in size, location, and social economic status and reported variances in their Washington Assessment of Student Learning (WASL) scores. While all of the schools reported similar barriers to the use of educational technology, distinct differences appeared between those schools that had done long-range planning during the reform process and those that had not. Specifically, staff in the two schools that coordinated curricula, performance standards, and a variety of assessment tools while

simultaneously allowing teachers the flexibility to alter the curricula, were more likely to state personal responsibility for student learning, and they also were more likely to have overcome barriers to the use of technology.

bAcKground In a recent campaign commercial, a candidate spoke of the need to improve education and to create quality schools. Lined up along a white wall behind him were rows of computers with elementary students quietly absorbed in the computer screens. The message to the public was clear: computers and computing technology are not only necessary for quality schools, but

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Examining Perceptual Barriers to Technology

they are indicative of good teaching and student learning. If the state was to have youth who would eventually be competitive in a global economy, technology would need to be at the forefront of funding and government support. Computing technology has been marketed as the current solution to education’s problems (Rockman, 2000), and the quest for technologically equipped schools has grown dramatically. In 1996-1997, an estimated $4.3 billion was spent by school districts in order to upgrade and incorporate computing technology in classrooms (Healy, 1998). In the year 2000, the number of computers in schools numbered over 10 million (Becker, 2000).

PurPose Research in the integration and institutionalization of educational technology was limited in scope in 1994 (Seels & Richey, 1994), and although educational technology is available, it is not integrated into classrooms today (Becker, 2000; NCES, 2000). Only 43% of elementary classrooms surveyed used computers on more than 20 occasions during the school year (Becker, 2000). Nationwide, districts are grappling with education reform and accountability while simultaneously attempting to financially support computing technology and encourage integration by classroom teachers. Currently, there is no clear rationale that explains the apparent difficulty with incorporating the use of educational technology and whether or not there is a relationship between the level of technology integration and the pressure teachers experience as a result of education reform efforts. The purpose of this study was to examine how educators in several schools in Washington state were responding to the pressure to integrate technology while simultaneously being accountable for student achievement.

revIew oF the LIterAture In January 2002, President George W. Bush reauthorized the Elementary and Secondary Education Act. This bill contained an even larger allotment of money and support for technology from the federal government than previous education bills did (Fletcher, 2002). Currently, 48 states have adopted or are developing assessments that align with standards-based reform efforts (Stecher & Chun, 2001). Reform and standards have impacted classroom practice, and schools and teachers have responded in multiple ways (Adcock & Patton, 2001). Often, technology reform and education reform have paralleled each other as opposed to being incorporated (Peters, 2000), meaning that in many instances, the purchasing of computing tools and related technology, as well as a plan for staff development, were not coordinated with a building’s reorganization and examination of the curriculum and instructional processes. When both education reform and technology integration have been combined fully with curriculum reform, which includes examining pedagogy, positive results have been found for students (Bain & Smith, 2000).

bArrIers to technoLogy use In spite of significant pressure to integrate the use of technology into the curriculum, the presence and accessibility of computers in the schools has not shown that the technology is being used by educators or that students actually can or do use it (Cuban, Kirkpatrick & Peck, 2002; Kalkowski, 2001). Although they are accessible, computers have not transformed the practices of a majority of teachers (Becker, 2000; Labbo & Reinking, 1999), and Willis, Thompson, and Sadera (1999) have pointed out that integration of computers into the classroom has actually been a slow process.

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Defining Barriers In initial efforts to understand why teachers have failed to integrate technology barriers have been defined as being primary and secondary (Ertmer, Addison, Lane, Ross & Woods, 1999; Judson & Sawada, 2000; Prater, 2001). Both primary and secondary barriers are explained as being both intrinsic and extrinsic (Ertmer, Addison, Lane, Ross & Woods, 1999). Primary barriers include lack of access to computers and software, insufficient time to plan instruction, and inadequate technical and administrative support. Secondary barriers include beliefs about teaching, beliefs about computers, established classroom practices, and unwillingness to change.

diffusion of Innovations and educational technology In addition to defining barriers, researchers have sought to understand why some specific technologies are adopted. The diffusion of innovations is the study of the process by which the use of a perceived new idea, practice, or object is adopted within a given social system (Rogers, 1995). The study of the diffusion of innovations is present in many research traditions, including: anthropology, marketing, geography, communication, and education. Within the overall research arena, fewer than 10% of the studies of innovations have been conducted in education (Rogers, 1995). While Rogers (1995) provides a generic model of the process of the adoption of an innovation, case studies are showing that alternative models may be more applicable to school systems. These models specifically identify educational technology as the innovation being studied, thus the phrase diffusion of educational technology is often used in place of diffusion of innovations. The diffusion of educational technology models that have been recently presented is non-

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linear, implying that many factors are involved in the adoption (or lack of adoption) of educational technology (Dooley, 1999; James, Lamb, Bailey & Householder, 2000; Rogers, 2000; Sherry, Billig, Tavalin & Gibson, 2000). These models vary from the commonly cited model posed by Everett Rogers (1995), as they focus solely on educational technology and attempt to identify more specifically those factors that will lead to the adoption of an innovation in a school setting. All of the models have been developed using a limited number of schools, and none of the models clearly indicate why technology integration has been a slow process.

Pilot Study on Media Selection In the spring of 2001, the researcher conducted a pilot study at a K-6 elementary school to determine how teachers in this particular setting made decisions regarding media selection. While the majority of staff verbally supported the use of computing tools, few used educational technology and, instead, tended to blame others or cite circumstances that they felt were out of their control for a lack of use. The common theme that emerged from all of the interviews was that regardless of the reason for failing to integrate technology, the teachers in the building were making the majority of decisions based on a highly-structured reading program that had been adopted during a school reform process. All related the lack of technology use to some aspect of the school’s focus on educational reform and to their concerns related to teacher accountability and a state required assessment, the Washington Assessment of Student Learning (WASL). The results of the pilot study provided an additional foundation for further examination of the relationship between education reform, educational technology, and educators’ perceived barriers to technology integration.

Examining Perceptual Barriers to Technology

MethodoLogy

Site Selection

theoretical underpinnings

Four separate sites from the same Educational Service District in western Washington were purposively selected. A stratified sample was used (Patton, 1990), meaning that the four sites represented four different subgroups for comparison. Two of the schools were located in rural settings and reported variances between their WASL scores (demographics are reported in Table 1). Access was granted through a key individual at each site, and snowball sampling (Patton, 1990) was used. Semi-structured questions were asked, and observations were made of the classroom setup and equipment available.

Authentic technologies (Clark & Estes, 1999) are “educational solutions resulting from systematic analysis that identifies the problem being solved, selects and translates appropriate, well designed research and applies it to design culturally appropriate educational solutions” (p. 243). A fourstage model proposed by Clark and Estes (1999) for conducting research in the development of authentic technologies provided the theoretical underpinnings for this study. Authentic technologies can include teaching strategies and processes, not merely computing tools. This research is based in the first, or Descriptive Scientific Research Stage, where the defining of constructs and hypotheses generation are the key goals. Two research questions guided the study: 1.

2.

Data Collection Twenty individuals were interviewed between March and May of 2002. Interviewees included: three administrators, one administrative intern, three reading specialists, 13 classroom teachers, a counselor, and a P.E. teacher. Each interview lasted between 45 and 90 minutes. All of the interviews occurred within the individual teacher’s classroom or the administrator’s office. Following the transcriptions of the interviews and during the analysis, the initial contact person at each school

What are teachers’ perceptions of barriers to the use of educational technology/technology integration, and how do the barriers connect to education reform? What are the connections between perceived barriers to the responsibility for computing technology?

Table 1. Enrollment and WASL scores of selected stes (2001)

School

Location

Enrollment

% of Free and Reduced Lunch

% Passing Reading WASL (66.1 state)

% Passing Math WASL (43.9 state)

% Passing Writing WASL (43.5 state)

% Passing Listening WASL (72.4 state)

Wrangle

Urban

370 K-6

56.8

48.8

23.3

27.9

58.1

Sandal Creek

Suburb

444 K-4

10.3

52.7

28

43

71

East Lake

Rural

263 K-6

34.4

55.8

30.2

23.3

72.1

Woodland

Rural

304 K-6

44.4

73.2

39

43.9

80.5

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Examining Perceptual Barriers to Technology

remained available to answer specific questions via phone and e-mail. The International Society for Technology in Education (ISTE) has developed frameworks that provide progressive descriptions that range from teachers who do not integrate technology to teachers that fully integrate technology (ISTE Homepage, 1999). These frameworks were converted into a survey, and each teacher was asked to identify his or her current level of technology integration. Notes were taken during the interviews, and observations and comparisons were made between the information gathered during the interview and the teacher’s reported level of integration.

Data Analysis Each interview was read multiple times, and the researcher looked for themes within each broad category. A list of themes was generated, and selective sections of the interviews that corresponded to the potential themes were labeled. For the teachers, the following themes were identified: primary barriers, secondary barriers, school climate, favorite parts of teaching, frustration/needs, teaching practices, accountability, and technology specific responses. Interviews were coded and sorted in several ways. The responses of those who had high integration scores on the technology integration survey and those that scored lower were separated for comparison. In addition, responses to both primary and secondary barriers were separated into two groups: those who saw an identified barrier as an obstacle that they could not or would not overcome, and those that were attempting to or had overcome the identified barrier. Patterns within and between schools, including those who rated themselves high on the integration survey and those who rated themselves as lower, were identified. Individual profiles for each school were developed and used to confirm the researcher’s initial findings from the organizational charts.

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Interpretation After reviewing the analysis, several distinct differences and similarities appeared between the schools. Remarkably similar were the hindrances to technology integration. All barriers cited in the literature were mentioned at every school. These included inappropriate training or inservice (Kay, 1996; Maor, 1999), collegial jealousy or predefined roles (Reinking & Watkins, 2000; Sherry & Billig, 2002; Wood, 2000), lack of appropriate or relevant software instruction (Becker, 2000; Rockman, 2000; Rogers, 2000; Ruberg, 1993; Sia, 1992), teachers failing to find the relevance of technology use or applications to classroom practices (Maor, 1999; Rogers, 2000; Sherry, Billig, Tavalin & Gibson, 2000), as well as teachers having a lack of space and time within the curriculum (Cuban, Kirkpatrick & Peck, 2001; James, Lamb, Bailey & Householder, 2000). What differed were the role of curricula within the school reform process, the types and uses of assessments, and teachers’ statements of personal responsibility for both the use of technology and for student learning. Although all of the schools had participated in school reform efforts, the connection between curricula, assessment, and instruction varied. These connections and teacher statements of responsibility at the four elementary schools will be highlighted in the following section.

curriculum, Assessment, Instruction, and teacher responsibility for student Learning Looking at a Disconnect: Sandal Creek and Wrangle A disconnect between curriculum, assessment, and instruction existed in two of the four schools: Sandal Creek and Wrangle. At Wrangle, teachers were using the structured curriculum as the

Examining Perceptual Barriers to Technology

primary means of addressing problems with student achievement in reading. Teachers were not the decision makers when it came to reading instruction. Instead, representatives from the adopted reading program and a reading coordinator reviewed scores on a regular basis and directed adjustments. The adjustments were not generally instructional but related to group placement. Teachers felt that they had little say in what and how to teach and were frustrated. In addition, this highly-structured curriculum impacted all other school decisions. I wish I had more time in the day to teach what we are being expected to teach for one thing. I wish I could veer from the hard and fast philosophy we are living with now….I would like to branch out and be a little more creative. It is the way I used to teach. Now we have to stay with the party line. It is boring for me and it is boring for the kids. (6th Grade Teacher, Wrangle, March 28, 2002) At the other end of the spectrum was Sandal Creek, where very little structured curricula existed. Like Wrangle , teachers at Sandal Creek were also frustrated, but because of a lack of structure. Actually I am sitting on a committee right now that is trying to purchase a curriculum. We are all frustrated with the hodgepodge. (Third Grade Teacher, Sandal Creek, May 8, 2002) For new teachers it is really hard [the reading program]. The program itself is really hard to follow because, the way it is set up, there are two different books. It is just hard logistically because the materials that come with it, well, there aren’t any….philosophically they [the teachers] like it, but it is not helpful as far as providing resources. (Reading Teacher and Administrative Intern, Sandal Creek, May 8, 2002)

Sandal Creek had virtually no structure or connection between curriculum, assessment, and classroom instruction. No curriculum existed, just frameworks. Wrangle teachers were not the decision makers but were directed by adopted curriculum. Neither of these two schools had teachers who commented on being responsible for the actual learning of the students. I know there needs to be some sort of accountability…but I wish they were less centered on the teachers…and that the politicians who actually came up with this stuff would point their finger where the real issue is, which is in the home. (6th Grade Teacher, Wrangle, March 28, 2002)

Making a Connection: East Lake and Woodland At the two other elementary schools, East Lake and Woodland, teachers discussed multiple types of assessments and multiple purposes for assessment. WASL scores were reviewed, but the results from this assessment were not the only measure of student success. District and classroom assessments were used to adjust instruction and determine individual student needs. Both formal and informal assessments were combined to assist in curricular decisions and teachers were expected to make decisions based on their own professional judgment. Like I said, in major areas they [the District] do have priorities where you can teach. Now the way you get there, obviously, is up to the teacher and up to your classroom. There are other teachers in our district, in our school, that don’t stick closely to the adopted reading curriculum but they do hit the major component parts of it. (Sixth Grade Teacher, East Lake, May 6, 2002) [A]nd if all of that work has been done [the curriculum process] the curriculum is critical; how its adjusted and adapted and delivered to the

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Examining Perceptual Barriers to Technology

students is totally a professional obligation and responsibility of that classroom teacher, but they need to be able to know the curriculum well enough to how to adapt it. I would encourage all teachers the first year to use the curriculum closely…They are going to have to do some adapting and they’ll probably have to work with the special education teachers. We check every day on how they are doing. (Principal, Woodland, May 10, 2002)

Assertion 1

I don’t feel really badly if we don’t make the WASL because it is a different cohort. There are other conditions that apply. Certainly it is a goal for us to look at, and it certainly is one measurement,

Comparing the four schools, it appeared that when education reform efforts included the integration of curriculum, assessment, and classroom instruction, such as at Woodland and East Lake

but I am more interested in looking at individual students over time. If I see that kids aren’t making adequate progress in our classroom assessment then we have to do something different and that going to adjust our school plan, which ultimately should result in the WASL improvement. (Principal, East Lake, March 28, 2002)

Table 2. The role of curricula between Wrangle, Woodland, East Lake, and Sandal Creek Wrangle

East Lake

Sandal Creek

Woodland

Primary Assessments Classroom School

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X*

X

X

X*

X

X

X

District State

X

X

Role of Curricula Highly Structured

X

Adopted Curricula and District Frameworks with Flexibility to Adjust No Adopted Curricula and District Frameworks

X

Teachers State Responsibility for Student Learning Teachers State Responsibility for Technology Integration Teachers State Plans for Overcoming Barriers Note: * Indicates a single teacher

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Examining Perceptual Barriers to Technology

did, teachers were more likely to take personal responsibility for student learning. At East Lake and Woodland, curriculum, assessment, and classroom instruction seemed closely connected. There was a clear understanding of both formal and informal assessments. It was only at these two schools that teachers commented on being responsible for student learning and being accountable to themselves. As one teacher stated, “It’s the teacher’s responsibility.”

Integrating technology with reform and teacher responsibility At Sandal Creek and Wrangle, technology remained separate from the rest of the school happenings. For example, a technology plan was being developed for Sandal Creek at the district level, as opposed to the school staff formulating the plan. Staff at both schools rarely cited efforts to overcome barriers. They blamed others for the existing barriers and individuals, and made no problem-solving references to how to personally overcome an obstacle or influence policy and practice related to technology integration. [B]ecause people aren’t telling us what the research base is, so I’m just finding whatever’s there and that’s what I will use, but I’m not using it to teach kids with. I’m using it as like a reward for having completed whatever things they’ve done in the classroom, so I’m not thinking of it in terms of curriculum. It is more like…it is not part of our curriculum, it is something extra for kids who are finished and need an extension of whatever. (Second Grade Teacher, Wrangle, May 7, 2002) At both Woodland and East Lake, teachers were more likely to mention having overcome obstacles to technology use. Technology use was seen as part of the total overall piece of instruction, not as something that was separate from or in addition to the existing curriculum. There had been both long-range planning and the integration of

assessment with instruction. Technology had been used as a part of the process; both districts had adopted software that committees felt supported the curriculum and classroom instruction. I think it’s [technology] supportive of the curriculum, it just depends on what you’re going to use it for. (Fifth Grade Teacher, Woodland, May 10, 2002) Technology is a tool. It is not to be, I mean it is not the goal, the technology is not the goal, it is the means to the end and the is…we model this for kids… we don’t have time in the day to do those free standing things that aren’t tied directly to goals we have for student learning. (Principal, Woodland, May 10, 2002)

Assertion 2 Teachers took more responsibility for technology use when technology integration was not separate from curricula and/or reform efforts. Even if a teacher had not fully integrated technology, teachers at East Lake and Woodland made statements of personal responsibility for technology use. It is definitely not what we have now, you know, last year I could have said we don’t have great computers. But I think it is just a comfort level for me and I think I need to get in and experiment to how to use it myself and then be able to expect my kids do that, so I think it is something that will happen, maybe next year. (Third Grade Teacher, Woodland, May 10, 2002)

Access to technoLogy The concept of homophiliy (Rogers, 1995) suggests that the adoption of a new technology is more likely to occur if someone similar, such as an equal colleague, introduces it or is successful at using the new technology. It was interesting to note that Wrangle, one of the schools with a

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Examining Perceptual Barriers to Technology

disconnect between curriculum, assessment, and instruction, had more computers per student than any of the other schools. Three of the teachers had received a total of four large grants, and every teacher had at least one computer in the classroom. Of all of those interviewed, Wrangle also had a teacher that scored higher than any other on the integration survey. However, Wrangle had less technology use as measured by the Technology Integration Scale. The large grants received by one specific teacher seemed to have isolated her. The technology provided by the grant stayed within the individual classrooms, although the grant recipients did collaborate with each other. On the other hand, Woodland had received a large grant where the technology moved with the students. Following the initial grant year, the student took the technology (in this case, portable word processors) with them to the next grade. The new teachers then began utilizing the technology because the students were accustomed to it, and it was still available to them. Wood (2000) found that teachers who were next to one grant recipient often were jealous, and those with the technology were often discouraged from sharing and isolating themselves from their peers. This was seen at Wrangle. Teachers were often angered by the technology grant recipients who collaborated every year in the creation of a play. Two classrooms were involved in the development of the play, and the integration of technology throughout was apparent; brochures, advertising, film editing, lights, and music were all developed. One of the teachers who was interviewed and had observed the play asked the researcher to figure out, “How, exactly, does that fit with curriculum?”

Assertion 3 In order for technology to be used in a school, access to technology needs to be made for all. It should be noted that the literature suggests that access to technology doesn’t guarantee that teach-

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ers will utilize it (Cuban, Kirkpatrick, & Peck, 2001). At Woodland, where the lab provided ample access, some teachers still hadn’t used the lab. However, even though the teachers were hesitant, they weren’t unwilling to try or had future plans to increase use. Once access is provided, addressing individual perceptual barriers and actual needs may be the next step. In schools where there is no access or where access is restricted to specific classrooms, it seems unlikely that other teachers will seek to integrate technology.

dIscussIon Schools cannot be centered solely on technology, assessment, or curricula. Schools that become too focused on one area can neglect the others. In order to better understand how technology use can be supported, the school first processes need to be viewed from the perspective of student learning. What are the factors that directly influence and impact student learning? Such things as the relationship of curricula, assessment, accountability, leadership style, resources, and the individual needs of the teacher need to be examined in a global context. Technology integration fits in to many of the categories, but technology alone won’t guarantee student learning. It is simply one factor that may contribute to meeting student learning goals. Two models of the diffusion of educational technology have identified that the point of rejection of a new technology occurred when teachers failed to see relevance for the learner (Rogers, 2000; Sherry, Bilig, Tavalin & Gibson, 2000). Upon completion of this study, it seems necessary to further define the diffusion of educational technology models so that they encompass more than one technology and provide direction related to the overall process of technology integration. Technology integration within schools must exceed the adoption or use of a single technological device or application. Most of the models of

Examining Perceptual Barriers to Technology

Figure 1. Conceptualization of the role of technology

adoption take a technology-centered view. Even an holistic model presented by Dooley (2000), where internal and external factors of integration are viewed in the context of the school along with types of change facilitators, presents technology as the central focus.

concLusIon reconceptualizing the role of technology The integration of technology into today’s classroom needs to be viewed as an integral component of a more comprehensive package of education reform. Although the literature often uses the phrase “integrate technology” to imply that technology is to be part of multiple areas of education, including curriculum, assessment, and instruction, it often is presented as the focal point or treated as a separate component. Student learning is truly at the center of education. Perhaps a more appropriate phrase would be to

“enhance teaching and learning through the effective use of technology.” Performance standards or frameworks are in place in almost every state. Curriculum and assessment should be used to inform instruction. Technology and best practices need to be examined within the context of each area of the educational system, and technology integration needs to be reconceptualized and presented within the context of an entire school system (Figure 1). In order for teachers to overcome barriers to technology integration, they need to feel in control both of the classroom and the available technology, be able to take responsibility, and have a sense of accomplishment. These three areas can be applied to the use of a single technological innovation but can and should be applied to the broader context of a school system. Too many schools are taking away the ability for teachers to be responsible. Teachers are being given scripted curricula and are told what to teach and which assessments must be given, as opposed to being given the freedom to make appropriate choices about instruction and appropriate assessment.

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Examining Perceptual Barriers to Technology

recoMMendAtIons For schooL IMProveMent Several recommendations can be made for school improvement and restructuring. First, combine technology with other reform efforts. Make the connection between the use of certain technologies or best practice with continued student achievement. This can take many forms: projects for increasing student learning, specific software applications for student use, appropriate assessment, and continued classroom management. Isolating technology or any other component of reform, such as curricula, creates frustrations and limits vision. Second, schools need to have the ability to overcome multiple primary barriers. Focusing on one barrier, such as access alone, neglects the others. Teachers are unique, have differing skills, and need different opportunities for growth. Meeting one need does not guarantee integration; other barriers will arise, and the ability to address them needs to be available for all. This includes not limiting materials and resources provided by a grant to a single classroom. This can isolate a teacher from his or her peers and create potential school climate issues. If a teacher does receive a grant, plans for future growth for other teachers within the building need to be thought through. This is the same for the students. What about those students who spend a year in a technology-rich classroom followed by several years in a technology-poor classroom; or what if those students at the same grade, because of placement in a certain classroom, are then denied access to computing tools? Solutions to the one technology classroom may include team teaching or crossage projects. Third, long-range planning needs to be done for all school restructuring. School goals need to be created within a holistic context that includes close scrutiny of curriculum, assessment practices, how teachers are matching classroom practices

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with established frameworks, and how teachers are implementing best practices in instruction. Building goals should be developed, followed with the examination of individual teacher needs. It simply is not enough to set goals without taking into consideration different barriers that individual teachers may face. Teachers need to be active participants in the decision-making process. Student needs are more likely to be met when teachers are able to make active decisions regarding curriculum, assessment, instruction, and the use of technology.

reFerences Adcock, S.G., & Patton, M.M. (2001). Views of effective early childhood educators regarding systemic constraints that affect their teaching. Journal of Research in Childhood Education, 15(2), 194-208. Bain, A., & Smith, D. (2000). Technology enabling school reform. Technological Horizons in Education Journal, 28(3), 90-97. Becker, H.J. (2000). Findings from the teaching, learning, and computing survey: Is Larry Cuban right? Education Policy Analysis Archives, 8(51). Clark, R.E., & Estes, F. (1999). New directions: How to develop “authentic technologies.” In R.E. Clark (Ed.), Learning from media: Arguments, analysis, and evidence (pp.241-262). Greenwich, CT: Information Age Publishing. Cuban, L., Kirkpatrick, H., & Peck, C. (2001). High access and low use of technologies in high school classrooms: Explaining an apparent paradox. American Educational Research Journal, 38(4), 813-834. Dooley, K.E. (1999). Towards a holistic model for the diffusion of educational technologies: An

Examining Perceptual Barriers to Technology

integrative review of educational innovation studies [Electronic version]. Educational Technology and Society, 2(4). Ertmer, R.A., Addison, P., Lane, M., Ross, E., & Woods, D. (1999). Examining teachers’ beliefs about the role of technology in the elementary classroom. Journal of Research on Computing in Education, 32(1), 54-62. Fletcher, G. (2002). Education act sets stage for technology reform. Technological Horizons in Education Journal, 29(7), 56. Healy, J.M. (1998). Failure to connect: How computers affect our children’s minds—And what we can do about it. New York: Simon & Schuster. ISTE. (1999). Online supplement: Levels of technology implementation framework [Electronic version]. Learning and Leading With Technology, 26(8). ISTE. (2000). National educational technology standards for teachers. International Society for Technology in Education. James, R.K., Lamb, C.E., Bailey, M.A., & Householder, D.L. (2000). Integrating science, mathematics, and technology in middle school technology-rich environments: A study of implementation and change. School Science and Mathematics, 100(1), 27-35. Judson, E., & Sawada, D. (2000). Examining the effects of a reformed junior high school science class on students’ math achievement. School Science and Mathematics, 100(8), 419-425. Kalkowski, M.A. (2001). Focus on learning and technology. Communication: Journalism Education Today, 34(4), 19-22, 25, 27. Kay, A. (1996). Revealing the elephant: The use and misuse of computers in education [Electronic version]. Educom Review, 31(4).

Labbo, L.D., & Reinking, D. (1999). Negotiating the multiple realities of technology in literacy research and instruction. Reading Research Quarterly, 34(4), 478-492. Maor, D. (1999). Teachers-as-learners: The role of multimedia professional development program in changing classroom practice. Australian Science Teachers Journal, 45(3), 45-50. NCES. (2000). The condition of education 2000. Quality Elementary and Secondary Educational Environments. Retrieved October 17, 2001, from http://nces.ed.gov/pubs2000/coe2000/section4/indicators45.html Patton, M.Q. (1990). Qualitative evaluation and research methods. Newbury Park, CA: Sage Publications. Peters, L. (2000). Joining forces: A third millennial challenge: Harness the power of educational technology to advance the standards movement. Technology Horizons in Education Journal, 28(2), 94-102. Reinking, D., & Watkins, J. (2000). A formative experiment investigating the use of multimedia book reviews to increase elementary students’ independent reading. Reading Research Quarterly, 35(3), 384-419. Rogers, E. (1995). Diffusion of innovations. New York: The Free Press. Rogers, P.L. (2000). Barriers to adopting emerging technologies in education. Journal of Educational Computing Research, 22(4), 455-472. Ruberg, L. (1993). The impact of digital technologies on the elementary school classroom. Proceedings of the Annual Conference of the International Visual Literacy Association, Rochester, New York. Schneiderman, B. (1998). Designing the user interface. Reading, MA: Addison Wesley Longman, Inc.

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Seels, B.B., & Richey, R.C. (1994). Instructional technology: The definition and domains of the field. Washington, D.C.: Association for Educational Communications and Technology. Sherry, L., & Billing, S.H. (2002). Redefining a “virtual community of learners.” Tech Trends, 46(1), 48-51. Sherry, L., Billig, S., Tavalin, F., & Gibson, D. (2000). New insights on technology adoption in communities of learners. Proceedings of the Society for Information Technology & Teacher Education International Conference, San Diego, California. Sia, A. (1992, February). Enhancing instruction through software infusion. Proceedings of the

American Technology Education Conference, Orlando, Florida. Stecher, B., & Chun, L. (2001). School and classroom practices during two years of education reform in Washington state. Los Angeles: University of California. Willis, J., Thompson, A., & Sadera, W. (1999). Research on technology and teacher education: Current status and future directions. Educational Technology Research and Development, 47(4), 29-45. Wood, J.M. (2000). Innovative teachers hindered by the green-eyed monster. Retrieved March 3, 2002, from http://www.edletter.org/past/issues/2000-ja/innovative.html.

This work was previously published in the International Journal of Information and Communication Technology Education, Vol. 1, No. 3, edited by L. A. Tomei, pp. 47-59, copyright 2005 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 4.31

Sustaining ePortfolio:

Progress, Challenges, and Dynamics in Teacher Education Yi-Ping Huang University of Maryland, USA

AbstrAct

IntroductIon

The teacher education programs at the University of Maryland Baltimore County (UMBC) and its professional community have undergone substantial changes, as developing and sustaining interventions for systemic impact involve changes in culture, policy, and practice. This chapter discusses the progress, challenges, and changing dynamics associated with sustaining an ePortfolio. An ePortfolio is an integral part of a Web-based Education Accountability System (EAS) developed and implemented by the author and the Department of Education to facilitate community-based teaching and learning, to help address national and state accreditation mandates, and to ensure continual improvements.

The teacher education programs at the University of Maryland Baltimore County (UMBC) and its professional community have undergone substantial changes, as developing and sustaining interventions for systemic impact involve changes in culture, policy, and practice. This chapter discusses the progress, challenges, and changing dynamics associated with sustaining an ePortfolio. An ePortfolio is an integral part of a Web-based Education Accountability System (EAS, http://education.umbc.edu) developed and implemented by the author and the Department of Education to facilitate community-based teaching and learning, to help address national and state accreditation mandates, and to ensure continual improvements.1 The discussion of ePortfolio endeavors will be provided in the rich context of EAS and the

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Sustaining ePortfolio

Figure 1. Education Accountability Systems (EAS) Teacher Education University of Maryland Baltimore County

Co

ity mm

Accountablitity Accountability Center Center

al

Co

ion un

ati

on

mm

al

at

un

uc

Content Management Electronic Electronic Portfolio Portfolio

P-12 Professional Development Schools

ity

2164

The EAS is based on national and state standards. The goals are reflective of UMBC’s mission of developing teachers with strong academic background through an authentic professional development continuum. Summaries of major objectives are as follows: First, the learning and assessments are continual and systematic to promote collaboration, encourage reflection, maximize learning opportunities, facilitate growth, and increase effectiveness. Second, the learning and assessments are inclusive of qualitative and quantitative performance opportunities and measures, including coursework, evaluative observations

Ed

The framework of EAS is built upon capacity and linkage building. Capacity is viewed as existing within discrete yet interconnected policy domains, and is embodied by individuals within these domains. Capacity building for sustainable reform within institutions and communities requires engaging interventions for individual capacity, collective capacity, and material capacity (Spillane & Thompson, 1997; Fullan & Stielgelbauer, 1991; Fullan, 2000). Linkage facilitates connection, communication, and transfer of capacity. Linkage building critically increases the probabilities for successful and sustainable reform. The EAS implementation thus devotes much energy to building structural, relational, ideological, and temporal linkages among the capacities. Grounded in such a conceptual framework, the EAS model (see Figure 1) takes a holistic approach by actively engaging and encouraging collaborative interactions among stakeholders of the UMBC teacher education programs, its P-12 professional development schools (PDSs), and national and state accreditation agencies. Core to the EAS are three integrated production components: Accountability Center, Performance Assessment, and Electronic Portfolio. These three sub-systems are orchestrated through a

education Accountability system (eAs)

uc

concePtuAL desIgn

centralized content management component. The community-based model enables opportunities for continual observation and influence of interactions among constituents in the community. The fully integrated model further provides viable solutions to the competing and often conflicting paradigms in the assessment management system and electronic portfolio (Barrett, 2004; Barrett & Wilkerson, 2004), as degrees of differences exist in needs, goals, and functionalities.

Ed

UMBC educational community. The first section discourses conceptual issues relating to the design of the ePortfolio and the EAS. The structure of EAS with technical specifications is then described, followed by a discussion of the progress, challenges, and changing dynamics in organizational culture and infrastructure; in program, curriculum, and assessment; and in resources, support, and system renewal. Finally, critical factors in sustaining an ePortfolio as a viable profession-based teaching, learning, and assessment medium for preparing teachers within the education community are summarized.

Performance Performance Assessment Assessment

Educational Community

Accredidating Agencies/ Specialized Professional Associations

Sustaining ePortfolio

via assessment instruments administrated by the teacher education unit and the institution, process and results of ePortfolio development and review, and results of standardized tests such as Praxis I and II. Third, learning and assessments are conducted and analyzed based on multiple sources and multiple assessments, with multiple indicators in both formative and summative forms to assure reliability and validity. Fourth, learning and assessments are aligned with professional standards, unit-expected competencies, and outcomes within program-specific operations, and are developmentally appropriate at benchmarks. Lastly, results of triangulated assessments (by candidates, supervisors, and mentors) are made available to the various constituents dynamically via the EAS to ensure timeliness of feedback and effective use of data for continual development and improvement. Details of the EAS (see Figure 2) are discussed.

Accountability center The Accountability Center is designed to facilitate tracking of candidate performance, monitoring of program quality, and maximizing departmental productivity. It is a centralized database that documents and displays over 550 different fields of personal, academic, and performance data captured by each of the three production components of the EAS. Central to the Accountability Center are functions that allow faculty and administrators to document an individual candidate’s program outlook, provide academic advisement and services, conduct assessments, review performance, determine remedial needs, and make progress decisions at benchmarks. A live querying and reporting center further facilitates the analysis and reporting of data at individual, program, and unit levels.

Figure 2. Education Accountability System (EAS) Accountability Center Benchmarks 1. Program Entrance

Electronic Portforlio

Performance Assessment Admission Assessment

Demographic Information Application & Admission Information

Introduction to ePortFolio Focus: ePortFolio Process, Standards and Technology

Early Field Experience Assessment

Academic Advisement & Course Records Field Experience Information & Assessment Results

Developmental ePortFolio Focus: INTASC & Conceptual Framework

3. Clinical Practice

Clinical Practice Performance Assessment • Candldate, Program and Unit Evaluations

Clinical Practice Information & Assessment Results

Developmental ePortFolio Focus: Specialized Professional Standards & Maryland Teacher Technology Standards

4. Program Exit

Program Exit Assessment • Candldate, Program and Unit Evaluations

2. Course & Field Experience

5. Post Graduation

Post Graduation Assessment • Alumni & Employers Surveys

Certification & Testing Records Program Exit Information Graduation & Post Graduation Information

Showcase ePortFolio Focus: Reflect, Project and celebration ePortFolio Presentation and Review

Professional ePortFolio Focus: National Board for Professional Teaching Standards

Dynamic Querying & Reporting

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Figure 3. Developmental ePortfolio

Figure 4. Showcase ePortfolio

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Performance Assessment The Performance Assessment component consists of two integrated tracks: candidate assessment, and program and unit assessment. Candidate assessment emphasizes measurements of candidates’ knowledge, skills, and dispositions, and examines the impact of candidates’ work on student learning in P-12 settings. Program and unit assessment emphasizes efficacy in aligning instruction and curriculum with professional, state, and local standards; efficacy of courses, field/clinical experiences, and program qualities; and, efficacy of candidates’ content, pedagogical, and professional proficiencies that lead to student learning.

A total of 15 assessment instruments, each with a five-point scale, are provided for candidate, program, and unit assessments. A triangulated candidate evaluation was designed to evaluate the candidates’ field experience and clinical practice through assessments conducted by clinical instructors, university supervisors, and candidates. A triangulated program and unit evaluation was also designed to assess the efficacy of faculty, curriculum, instruction, and candidate performance by clinical instructors, university supervisors, and teacher candidates. Such triangulated administrations help maximize teaching and learning opportunities, and help ensure validity and reliability. Results of the assessments are made available through the secure, Web-based EAS

Table 1. Content and organization of ePortfolio Content Categories

Sub-Categories Introduction

Introduction

Personal and Professional Information Context Studies of Field Experience and Clinical Practice Philosophy and Dispositions

Philosophy and Dispositions

Professional Development Plan Reflective Journals INTASC Principles Maryland Teacher Technology Standards (MTTS)

Standards-Based

Standards Developed by Specialized Professional Associations (SPAs):

Achievements

ACEI, NAEYC, NCSS, NCTE, NCTM, NSTA, and TESOL Minimum requirements for meeting standards include an interpretive statement, two artifacts, and rationales for each of the standards.

Credentials and

Résumé

Achievements

Professional Credentials and Achievements

Additional Content Categories

As defined and created by the user

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in real time to provide candidates with ongoing feedback. Aggregated and disaggregated performance data on candidates, programs, and the unit are generated dynamically through querying and reporting functions to facilitate the making of informed decisions for improvement.

ePortfolio content requirements for teacher candidates are summarized in Table 1. Greater options and control of content and presentation are granted to other types of ePortfolio authors, such as alumni, faculty, and mentors.

electronic Portfolio

technIcAL sPecIFIcAtIons oF the eAs

There are three milestones implemented to ease transitions and bridge academic and professional learning and practice: Developmental, Showcase, and Professional ePortfolios. The Developmental ePortfolio (see Figure 3) provides candidates with opportunities to generate, record, reflect, and assess their growth and performance across the teacher preparation cycle. The Showcase ePortfolio (see Figure 4) is a self-selected, “best evidence” collection of documents and artifacts demonstrating competencies on the standards and on professional growth. The Professional ePortfolio enables UMBC graduates and mentor teachers from the PDSs to continue generating, documenting, and celebrating their performance, growth, and achievement. To this end, the unit is now collaborating with local school systems in customizing professional ePortfolios that are aligned with county review guidelines and national board certification requirements for inservice teachers.

The EAS combines advanced Web application technology with a service-oriented architecture (SOA). SOA enables EAS to interact and potentially integrate with the existing university information systems, such as the student information system (SIS), on data collection and reporting. A three-tiered architecture was utilized to maximize the application’s lifecycle by enhancing system reusability, flexibility, manageability, maintainability, and scalability. The three-tiered architecture of EAS (see Figure 5) includes the presentation tier, middle tier, and data tier. The EAS is built on the robust computing platform of Microsoft .NET™ architecture, with a relational database management system at the back end and JavaScript-enabled Web browsers at the front end. A Microsoft Internet information server is utilized in the middle tier to address user requests.

Figure 5. Three-tiered architecture of EAS

Internet

Internet

Data Access Data Process Oracle Relational DB Data Tier (DB Server)

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Business Logic Request/Response

Microsoft IIS/.Net Middle Tier (Web/Application Server)

Dynamic Pages

Workstations Laptops

Web Browser Presentation Tier (Client)

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content Management Content management provides an integrated online authorizing environment, ranging from text editing to multimedia management, and allows multiple user access with differentiated privileges and responsibilities. This component empowers authorized users at both course and program levels to customize content and assessment needs in an open, flexible, and user-friendly environment. These may include authoring and management of assessment questionnaires, rubrics, reporting criteria, and formats. A template-driven structure is achieved by the use of back-end Oracle database tables and XML (eXtensible Markup Language) files. Microsoft ASP.NET technology is also used to enable dynamic creation and presentation of content. Interoperability and transportability are enhanced by enabling reusable and exportable content in XML format for exchange with other systems.

Stored content can also be published in various formats, such as HTML and PDF.

Accountability center The Accountability Center is a centralized data bank that documents and displays personal, academic, and performance data captured by each of the three production components of the EAS. Confidential information, such as Social Security numbers, is encrypted with a Triple-DES algorithm for security. Tasks, structures, access privileges, and responsibilities are as specified in the content management component. Intelligent agents are employed in facilitating secretarial and administrative operations. Central to the Accountability Center are functions provided by the dynamic query builder which allow the users to document, organize, analyze, and generate qualitative and quantitative reports at individual, program, and unit levels. Metadata are

Figure 6. DynaMatrix

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also enabled to document and analyze the levels of congruence among curriculum, assessment, professional standards, and the unit’s conceptual framework. The dynamic analysis and reporting functions increase the accessibility and expand the usability of assessment data in monitoring progress, in identifying needs, in defining strategies for improvements, and in compiling documentation for accreditation purposes.

•

•

Performance Assessment Performance Assessment utilizes role-based access control, enabling users to access, conduct, and review predefined assessments tasks and results that are appropriate to the specified user type. The role-based model is particularly important, as a triangulated assessment model is utilized to evaluate the candidate, program, and the unit. Content of the assessment instruments are created and managed through the content management component. Individual assessment progress and results are displayed through DynaMatrix, a dynamic and personalized content presentation based on the user’s role privilege (see Figure 6). Data analysis and reports at individual, program, and unit levels can be generated through querying and reporting functions provided in the Accountability Center. Surveys that are designated anonymous, such as pre- and post-clinical program evaluations, are de-identified. These various functions are enabled by using server-side (ASP. NET) and client-side (Java Script) programming to interface with users and data.

electronic Portfolio (ePortfolio) The ePortfolio consists of four core modules: Artifact Manager, Narrative Manager, Review Manager, and Publishing Manager (see Figure 7). The Artifact Manager module allows users to upload, organize, and control access, display, and share artifacts.

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•

•

•

Artifact types range from basic text files to advanced multimedia files and are organized into categories and elements. Categories may contain file folders and subfolders. Elements are granular units of information which cannot be further divided for sharing purposes. Uploading is conducted via the Web with a single file size limitation of 8 MB to prevent potentially dangerous Web site attacks. Space quota is allotted for each user, and adjusted on demand basis. Access, display, and sharing of artifacts are provided through a user control interface. The author of the ePortfolio is empowered to finely define and control who, when, and what can be accessed, shared, and/or published. Digital rights management is in place to assure the author’s intellectual rights. Users are required to clarify ownership of the artifacts and/or acquire release permissions. Once published, images are watermarked with the customized watermarking function. Authentication and assurance of artifacts and content are being developed. Management functions are provided for both individuals and administrators, including creating/deleting/renaming folders and deleting/moving/renaming files. An artifact search function is also provided. Individuals can search artifacts by filename, label, uploading date, or belonging sections associated with her/his ePortfolio. Administrators can search artifacts across all ePortfolios.

The Narrative Manager module enables the author to incorporate narratives in each of the core content sections of Introduction, Philosophy and Disposition, Field and Clinical Practice, Standards-Based Achievement, and Credential and Achievements. An embedded Word-like editor provides users full-fledged editing and formatting capabilities for Web publishing, such

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Figure 7.

Artifact Manager

Narrative Manager

Formative Review Across Benchmarks

Introduction Personal Information Field and Clinical Practice Philosophy and Dispositions Standards-Based Achievements Credential and Achievements Additional Sections as created by Author

Publishing Manager

Showcase ePortFolio

Professional ePortFolio

Review Manager

Formative Review

Summative Review

Fail

Pass

Module

Data Sections

Decisions

Predefined Process

as color, font, paragraph, bullets, numbering, hyperlink, and spell-check. A special HTML tidyup function of the online editor is set in place to ensure that pasted or formatted text conforms to the W3C XHTML 1.0 standard for storing and presentation compatibility. The ePortfolio Narrative Manager module further supports multiple entries to facilitate documentation of learning in and across time, and to encourage reflection and deep learning.

Professional ePortFolio

The Review Manager module consists of assessment tasks, rubrics, scoring, reporting, and a commentary section. Content of the showcase ePortfolio, evaluation rubrics, and scoring scheme are displayed in a split window. Multiple reviewers and scores are supported. Inter-rater reliability analysis is enabled as results of multiple reviewers can be compiled and displayed at individual, program, and unit levels. Query and reports can be dynamically generated through weighted

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calculation of scores at individual, program, and unit levels. Lastly, the commentary section enables further communication and collaboration between the author and reviewer(s). This Review Manager is being tested for implementation in the 2005-2006 academic year. The Publishing Manager module enables Web-based, computer-based and paper-based presentation and publication.

•

•

•

•

The developmental ePortfolio (see Figure 3) interface consists of three frames: top, navigation, and workplace. The top frame contains author identification and links to other components in the EAS. The navigation fold/unfold frame allows the Web browser to populate items on the navigating section that are dynamically retrieved from the backend server. The workplace frame displays details of the selected section. The showcase ePortfolio (see Figure 4) interface allows a juxtaposing display of artifacts, interpretive statements, and rationales for the artifacts. The professional ePortfolio is similar to the construct of the showcase ePortfolio, with additional functions allowing greater control over content, structure, and presentation. A user control interface empowers the author to finely define and control who, when, where, and what can be accessed, shared, and/or published. A collection of presentation templates are made available for personalizing the feel and look of the ePortfolio. These functions encourage ownership and promote collaboration and sharing, while respecting individual privacy and rights. The Publishing Manager is based on a dynamic retrieval and packaging process, allowing storage and presentation on the secured EAS environment, on the open Web, via CD-ROM, and/or in print. For privacy and security reasons, teacher candidates are

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requested to publish their ePortfolios in the secured EAS environment. Invitations may be issued to viewers without MyEDUC accounts to access the EAS. Teacher candidates may also submit requests to publish on the open Web. Other types of users such as graduates, mentors, and faculty have greater control of accessibility.

Progess, chALLenges And chAngIng dynAMIcs organizational culture and Infrastructure With the vision of community-supported teaching, learning, and assessment, and the high stakes accreditation mandates, the Department of Education began a series of changes in its organizational infrastructure with the implementation of EAS in late 2001. The resulting structure at present is depicted in Figure 8. Structures that existed prior to 2003 are represented by oval-shaped boxes, while structures that were established after 2003 are represented by rectangle-shaped boxes. In particular, the newly instituted structures are program-based committees addressing programmatic and curriculum issues, and standards-based committees addressing policies and practices relating to NCATE, state, and SPA standards and accountability. The establishment of specialized committees heightens awareness of capacity and need for change, and encourages the building of individual, organizational, and material capacities. The involvement of a critical mass of faculty in committee activities with often overlapping membership further provides opportunities to create structural, relational, ideological, and temporal linkages necessary for effective and sustained intervention. By actively engaging and challenging members of the department, the

Sustaining ePortfolio

Figure 8. UMBC Teacher Education organization chart UMBC Teacher Education Organization Chart P-16 Coordinating Council

Chair

Faculty Council

Chair’s Advisory Council

Associate Chair

Program Committee & Coordinator

ECE Coordinator

ELEM Coordinator

ESOL Co-coordinatiors

SEC Coordinator

Graduate Pro. Director

P&T Committee

Dean Arts & Sciences

Infrastucture incl. Technology

Standards-Based Committee & Director

Assessment Director

Diversity Coordinator Professional Development Schools Director Student Services Director

MAE Co-coordinators

Teaching Experiences Director

P-12 Art, Dance, Music, & Theatre

Technology Coordinator

Structure Established prior to 2003 Structure Existed prior to 2003 ECE-Early Childhood Education, ELEM-Elementray Education, SEC-Secondary Education, MAE-Master of Arts in Education program for in-service teachers.

organizational infrastructure facilitates shared leadership in creating and adapting to a new culture and environment. The evolving culture and environment are reflective of the changing dynamic in policymaking and teaching practice, and are critical for institutionalization. Since 2003, the ePortfolio has become a clinical practice exit requirement for all initial teacher certification programs. The initiation, enhancement, and sustenance of processes and procedures leading to institutionalization result both from and in constant interactions

among programs, assessment, and standards committees. Examples of these enabling processes and procedures include systemic coordination and collaboration on curriculum planning and execution, on ePortfolio development and evaluation, on professional development and technical support, and on resource allocation and distribution. The process of organizational change and faculty change is complex (Abbey, 1997; Candiotti, 1998; Waddoups, Wentworth, & Earle; 2004), and is most likely to be successful in an enabling context with a robust support structure and ap-

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propriate rewards (Dusick, 1998). In the context of UMBC, the areas that thrive with progress also are areas with persisting challenges. These include leadership, commitment, collaboration, and support. Changing preconceptions and cultivating new understanding and practice call for shared vision and leadership. Sustaining complex infrastructure, nevertheless, requires centralized leadership with champions of change. Systemic interventions demand collaborations in capacity and linkage building. Evolving visions, goals, and needs, however, require careful and longterm management for validity and reliability. The realization of the ePortfolio as a learning and assessment medium relies on long-term commitment. Successful implementation of electronic portfolio is not merely student readiness, but full faculty participation (Gathercoal, Bryde, Mahler, Love, & McKean, 2002). Commitment and participation are energy, time, and resource consuming. Sustained implementation thus requires careful planning on change management, with realistic budgeting of resources, support, and expectations.

Program, curriculum, and Assessment Progress, challenges, and changing dynamics persist in program, curriculum, and assessment policy and practice. Renewed views of ePortfolio emerge from changing the preconception of the ePortfolio as mere digitization of paper variation to evolving understandings of the ePortfolio as a means of encouraging and celebrating “deep learning”—learning that is reflective, developmental, integrative, self-directive, and lifelong (Cambridge, 2004). The institutionalization of the ePortfolio, hence, reflects a grounded premise that the construction of the ePortfolio substantiates a persistent, learner-centered, standards-based, and outcome-oriented approach in generating and assessing learning and achievement in and over time.

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A significant shift in the process toward institutionalization at UMBC is the extension from product ePortfolio in its initial implementation to focusing on process ePortfolio across the teacher education cycle. Process ePortfolio provides a rich candidate development and advisement environment, and facilitates development of transcendental skills that are critical in the twenty-first global society, such as critical thinking, information literacy, and cultural competencies. Product ePortfolio provides opportunities for the reviewer to assess declarative, procedural, and metacognitive knowledge (Huba & Freed, 2000), and empowers authors to construct and celebrate learning and achievements. The blended approach to process and product portfolios encourages more balanced development across the professional development continuum. This shift, however, demands re-thinking of curriculum, instruction, outcome, and assessment in a systematic manner. Inconsistencies in these areas tend to be magnified in a program-wide ePortfolio where curriculum content and outcomes make up significant portions of the ePortfolio. Commitment to systematic curriculum planning and execution are thus critical to ensure logical and supportive development, leading to candidate mastery of program standards and desired outcomes. The commonly held notion of course ownership needs to be expanded and transformed to program ownership. The faculty needs to reconsider content, instruction, assignment, outcome, and assessment in the context of individual courses, and in relation to other content and professional courses in the program. Processes and mechanisms need to be defined to facilitate community-wide collaborations that take into consideration feedback, and formative and summative reviews provided by the faculty, supervisors, and mentor teachers across the developmental cycle. UMBC’s endeavor toward systemic integration is reflected in the development of the Curriculum and Assessment Master Plan for each of the certification programs. Table 2 is an example

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Table 2. Sample curriculum and assessment master plan: ESOL/BL Program

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from the ESOL/BL program, showing two of the five benchmarks. The top row indicates the benchmarks across the teacher education cycle, course title, credits, field experience component, outcomes, desired portfolio artifacts, and criteria for progressing to the next teacher education benchmark. As with any program improvement effort, the master plans have gone through many revisions based on evolving visions, needs, and goals of the faculty, the programs, and the standards instituted by state and national accrediting agencies. Concurrent with the mapping of curriculum, standards, outcomes, and assessments is the implementation of a syllabus template to facilitate the coordination and the restructuring of courses to ensure logical and supportive development. The internship seminar, for example, has been subdivided to two separated but related courses, allowing more focused discussion, development, and review of the showcase ePortfolio, a designated clinical practice exit requirement. Experiences with the new learning and assessment paradigm afforded by the ePortfolio led to renewed interest in interactions and collaborations, and resulted in the creation of a profession-based learning community (see Figure 1). ePortfolio development demands candidates to be self-directed in creating content and constructing meaning. It demands faculty to assume multiple roles as facilitator, conveyor, mentor, and evaluator to actively coordinate and support learning. It demands mentors in the PDSs to provide contextual responses and guidance of real-world experiences. To strengthen collaborative and profession-based learning, the department expanded its ePortfolio services to include all faculty, teacher candidates, alumni, and PDS mentors and coordinators. Specifically, mentors and school administrators are asked to participate in the process of ePortfolio development, review, and system renewal. They are also provided with hardware, software, and publishing services for the creation of their own Professional ePortfolio. The broadened spectrum

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of participants potentially extends the traditional institution-based evaluation to profession-based learning, assessment, and celebration of achievements. Another enabling factor in creating and sustaining an ePortfolio culture is a built-in review and renewal process that facilitates organizational and individual learning. In the context of UMBC’s teacher education programs, outcome data, process feedback, and experience gained through implementation are analyzed and interpreted by the program, assessment, and the standards committees. The results are translated into change actions for improvement. Examples include curriculum mapping, alignment of outcomes and assessments, and revision of assessment rubric, process, and procedures to address barriers and enhance effectiveness of implementation. Like benefits, barriers exist on multiple levels and may include:

•

•

•

•

Content Barrier: Utility, validity, and reliability need to be considered for variations of scope and breadth of content within and among programs. Changing requirements and expectations over time need to be carefully planned, communicated, and monitored. Technology Barrier: Differences in technological abilities, equity of access to technology, and support need to be taken into consideration for spectrum-wide enterprise services. Process Barrier: Developmentally appropriate guidance, support, expectation, and feedback need to be provided by faculty, mentors, and supervisors. Time for development and revision should be allotted and honored, as fluency of the ePortfolio process, standards, and technology require time and commitment. Review Barrier: Review rubric, processes, and procedures need to be clearly articulated and communicated. Formative evaluation at

Sustaining ePortfolio

benchmarks requires careful programmatic coordination to avoid conflict and redundancy. Summative evaluation ideally should include multiple reviewers, such as faculty, supervisors, mentors, and other professionals in the education community. Reviewer training and professional development need to be conducted cyclically to ensure coherence and consistency. Lastly, content and construct of assessments and rubric should take into consideration exemplary assessment characteristics—such as those identified by Huba and Freed (2000)—as being valid, coherent, authentic, rigorous, engaging, challenging, respectful, and responsive.

resources, support, and system renewal Sustaining a comprehensive system requires long-term commitment with resources and support infrastructures, as the institution is accountable to its constituents once implemented. In the context of UMBC, the design, development, implementation, and management of the EAS as a whole are led by the author and a multitasking team, with close collaboration among the various programs and standards committees. The frequent formal and informal interactions facilitate a cyclical review and renewal process, which is particularly important as it epitomizes and encapsulates capacity and linkage building for sustained implementation. The review and renewal process is based on outcome data, feedback, and experiences gained through implementation. It enables faculty and the management team to refine conceptual designs by further customizing functional and technical requirements and services. It facilitates the revision of software designs that strengthen architectures and interfaces for enhanced interactions. Lastly, the process helps adjust implementation plans that are responsive to the changing culture

and environment with evolving visions, goals, and needs. A multitasking team providing spectrum-wide support and services is another important component, particularly in the context of restricted resources. On the system side, the team is responsible for managing business and operational processes, and software and hardware upgrades. On the user support side, the team is responsible for providing a wide variety of services to candidates, faculty, supervisors, mentors, alumni, and other reviewers from the education community. Candidate support includes development and delivery of instructional modules on the ePortfolio process, standards, and technology in online, blended, and in-person classrooms. The team also develops and distributes Web-based and printed supporting materials, such as the E-Portfolio Handbook, which consists of policies, processes, content authoring, evaluation, media release, and process feedback documents. A computer lab, the Portfolio Place, was established and staffed to increase accessibility to technology and services. Support for other stakeholders includes professional development and technical training for members of the department and faculty at P-12 PDSs, and reviewer training conducted at the institution and on site at its PDSs. Publishing services (via CD-ROM and the Internet) are provided to all users. As with other educational interventions, the necessary resources and support for the ePortfolio and EAS are often greater than what they appear to be or what are available. Advocacy in the institution, strong leaders in the department, and persistent communication among stakeholders help manage expectations and operations for sustained implementation.

suMMAry This chapter narrates an institution’s experience in designing, implementing, and sustaining an ePortfolio and the EAS in its education com-

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munity. Factors and conditions that facilitate implementation and correlate to sustainability and effectiveness are summarized below. •

•

•

•

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Capacity and Linkage:  Sustaining effective interventions requires attention at multiple levels that build capacity and linkage, and requires community-wide commitment and engagement. Organizational Capacity and Linkage:  Organizational infrastructure is critical to enabling connections, communications, and transfer of capacities.  Institutionalization demands sustained leadership, commitment, collaboration, support, and resources, and requires enabling conditions provided by the organizational infrastructure.  Strong leadership with champions of change facilitates change management and encourages creation and adoption of a new culture. Technological Capacity and Linkage:  A robust system needs to be grounded in a coherent conceptual framework, and should be capable of realizing evolving visions, goals, and needs of the community.  A core team responsible for system design, management, upgrades, and user support is necessary, as the institution is accountable to its stakeholders. Curriculum and ePortfolio Culture:  Commitment to systematic curriculum planning and execution is critical to assure logical and supportive development, leading to candidate mastery of program standards and desired outcomes.  Cultivating an ePortfolio culture requires well-articulated policies, processes, and strategies addressing potential barriers in areas of content,

•

•

technology, process, and review to ensure utility, validity, and reliability.  A profession-based learning community inclusive of candidates, faculty, mentors, and other colleagues in the profession potentially extends the traditional institution-based evaluation to profession-based learning, assessment, and celebration of achievements. Support and Resource:  Sustaining the implementation of a comprehensive system requires careful planning on change management with realistic budgeting of resources, support, and expectations. System Renewal:  A built-in review and renewal process facilitates organizational and individual learning, and increases probabilities for successful and sustained reform. Whether in the areas of conceptual, software, or implementation designs, outcomes data, process feedback, and experience gained through implementation need to be analyzed, interpreted, and translated into change actions for improvements.

As progress continues to be made, new challenges continue to emerge. The institution and its community will need to continue to adjust policies and practices in the effort to create a dynamic learning community that takes advantage of the new teaching, learning, and assessment paradigm afforded by systems such as the ePortfolio and the EAS.

reFerences Abbey, G. (1997). Developing a technologyfriendly faculty in higher education. In D. Willis, B. Robin, J. Willis, L. Price, & S. McNeil (Eds.), Technology and teacher education annual 1997

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(pp. 351-353). Charlottesville, VA: Association for the Advancement of Computing in Education.

of American Educational Research Association (AERA), New Orleans, LA.

Barrett, H. (2004). Differentiating electronic portfolios and online assessment management systems. In Proceedings of the 2004 Conference of the Society for Information Technology and Teacher Education. Retrieved June 2004 from http://electronicportfolios.org/portfolios/SITE2004paper.pdf

Hill, D. (2002). Electronic portfolios: Teacher candidate development and assessment. In Proceedings of the 54t h Annual Meeting of the American Association of Colleges for Teacher Education, New York.

Barrett, H., & Wilkerson, J. (2004). Conflicting paradigms in electronic portfolio approaches. Retrieved June 2004 from http://electronicportfolios.com/sytems/paradigms. html Cambridge, B. (2004, February 11). Electronic portfolios: Why now? In Proceedings of the EDUCAUSE Live Teleconference. Candiotti, A., & Clarke, N. (1998). Combining universal access with faculty development and academic facilities. Communications of the ACM, 41(1), 36-41.

Huang, Y. (2003). UMBC performance assessment system. In Assessing education candidate performance: A look at changing practices. Washington, DC: National Council for Accreditation of Teacher Education. Huba, M. E., & Freed, J. E. (2000). Learner-centered assessment on college campuses: Shifting the focus from teaching to learning. Boston: Allyn and Bacon. Jafari, A. (2004). The sticky e-portfolio system: Tackling challenges and identifying attributes. EDUCAUSE Review, 39(4), 38-48.

Danielson, C., & Abrutyn, L. (1997). An introduction to using portfolios in the classroom. Alexandria, VA: Association for Supervision and Curriculum Development.

Spillane, J. P., & Thompson, C. L. (1997). reconstructing conceptions of local capacity: The local education agency’s capacity for ambitious instructional reform. Education Evaluation and Policy Analysis, 19(2), 185-203.

Dusick, D. M. (1998). What social cognitive factors influence faculty members’ use of computer for teaching? A Literature Review. Journal of Research on Computing in Education, 31(2), 21-36.

Waddoups, G., Wentworth, N., & Earle, R. (2004). Teaming with technology: A case study of a faculty design team developing an electronic portfolio. Journal of Computing in Teacher Education, 20(3), 113-120.

Fullan, M. (2000). The return of large-scale reform. Journal of Educational Change, (1), 1-23.

Key terMs

Fullan, M.G., & Stielgelbauer, S. (1991). The new meaning of educational change (2n d ed.). New York: Teachers School Press. Gathercoal, P., Bryde, B., Mahler, J., Love, D., & McKean, G. (2002). Preservice teacher standards and the magnetic connections electronic portfolio. In Proceedings of the Annual Meeting

Accreditation: A process of assessing and enhancing academic, educational, and or organizational quality through peer review conducted by national and/or state agencies. Assessment System: A comprehensive and integrated set of evaluation measures that provides information in monitoring, managing, and improving candidate performance, program

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quality, and organizational operations associated with teacher education. Definition adopted from National Council for Accreditation of Teacher Education (NCATE). Benchmark: A description of individual or organizational performance and/or outcome that serves as a standard of comparison for evaluation or judging quality. Developmental ePortfolio: A process that facilitates the generation, recording, reflection, and assessment of one’s own growth and performance throughout the teacher preparation cycle. Education Accountability System (EAS): A comprehensive and dynamic lear ning management system developed and implemented by the University of Maryland Baltimore County. It consists of three integrated production components: Accountability Center, Performance Assessment, and Electronic Portfolio. Professional ePortfolio: A process that encourages practicing educators in the education community to continue generating, documenting, and celebrating one’s own performance, growth, and achievement.

Showcase ePortfolio: A self-selected, “best evidence” collection of documents and artifacts that demonstrate competencies on the standards and professional growth.

endnote 1

The EAS is copyrighted with a technology invention disclosure granted to the author and the lead programmer, Alan Ma. The Performance Assessment component was selected as a part of the National Assessment Examples Project (Huang, 2003) by the National Council for Accreditation of Teacher Education (NCATE). The ePortfolio component was awarded a Preparing Tomorrow’s Teacher for Technology (PT3) sub-grant by the Maryland State Department of Education, with the author serving as principle investigator. The technical specification section of the chapter is written with assistance provided by the lead programmer.

This work was previously published in the Handbook of Research on ePortfolios, edited by A. Jafari, pp. 503-519, copyright 2006 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.32

Delivering Management Education via Tutored-Video Instruction L.W. Murray University of San Francisco, USA Alev M. Efendioglu University of San Francisco, USA

IntroductIon The University of San Francisco (USF) initially contracted with a Hong Kong-based, Chinese multinational firm, China Resources Holding Company (CRC), to deliver an entire MBA program to approximately 40 of its fast-tracked employees. The technologies known as TutoredVideo Instruction (TVI) were selected as the means of delivery. The success of the first cycle resulted in a contract with a second Chinese company, Guangdong Enterprises (GD), based in Guangdong (Canton). During 1989–2000, a total of five academic cycles were undertaken, each lasting approximately two years. Three of the cycles involved students from CRC, designated in this paper as CRC1, CRC2 and CRC3, and the remaining two cycles involved students from GD, designated GD1 and GD2. Both programs utilized lock-step cohorts; that is, a group of students taking

the same classes at the same time throughout the MBA program, with no elective course choices. Each cohort group averaged about 35 students; a total of 175 students received their MBA degrees during the five cycles of instruction.

bAcKground tutored-video Instruction TVI was developed by the Stanford University School of Engineering so they could teach graduate engineering to students at a remote location. The initial evaluation of this program reported that TVI students performed better than students of a similar background and age taking the same course on campus (Gibbons, 1977). When a course is presented via TVI, classroom lectures to on-campus students are taped

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Delivering Management Education via Tutored-Video Instruction

and shown to the TVI students at a later date. TVI students watch the videotaped lectures as a group and if they encounter something that they don’t understand, they ask the tutor to stop the tape to discuss what they have seen with the other students in an attempt to learn from one another. At the end of the video discussion, the tutor then conducts a formal discussion using questions supplied by the instructor. The tutor’s role is to make sure the group viewings occur, to attend to the details of handout materials, assignments and handling of the tapes, and to funnel group questions and feedback to the instructor. The early studies of TVI found that the discussions were more effective if the tutor was not skilled in the subject matter, but was adequately trained in the art of discussion. Further, subsequent research concluded that the tutored discussions were the key ingredient to successful learning outcomes (Gibbons, Kincheloe, & Down, 1977). Subsequent studies confirmed the effectiveness of TVI. A study by Stone (1990) validated the

Stanford study. Arentz (1993) reported on the use of TVI to teach engineering courses to distance students in Norway using a variety of distance education technologies, and concluded that TVI was clearly the students’ preferred method of learning. In a study of undergraduate students, TVI was found to be more effective as a learning technology when compared to the other forms of distance learning being used by the institution at the same time: correspondence education, audio taped programs and videotaped courses. It was estimated that across a multi-campus system, TVI courses cost from 10%-15% less to deliver than other distance education technologies (Appleton, Decker, & Sharma, 1989). Thach and Murphy (1995) and Lucey and Burdett (1991) reported similar cost reductions from using TVI.

context In 1988, USF contracted to deliver all of the courses required for a MBA degree to selected employees

Table 1. Student GPA for all programs and all courses by program and by teaching area TEACHING AREA Program

MGMT

MIS

3.55

3.37

3.28

3.40

3.37

3.21

3.67

3.42

3.52

3.33

3.44

3.41

3.08

3.52

3.71

3.35

3.00

3.35

3.55

3.57

3.40

3.96

3.41

3.52

3.38

3.85

3.50

3.37

3.27

3.41

3.15

3.33

3.46

3.06

3.36

3.34

Average of USF GPA

3.21

3.62

3.31

3.20

3.39

3.51

3.26

3.47

3.39

Average of China GPA

3.52

3.45

3.37

3.34

3.40

Average of USF GPA

3.45

3.51

3.43

3.08

Overall Average of China GPA

3.41

3.47

3.38

3.12

3.54

Overall Average of USF GPA

3.32

3.56

3.39

3.22

3.70

CRC3

GD1

GD2

2182

COMM

DS

ECON

Average of China GPA

3.34

4.00

3.30

3.13

Average of USF GPA

3.39

3.53

3.35

Average of China GPA

3.47

3.39

Average of USF GPA

3.29

Average of China GPA

ENV/ LAW

FIN

CRC2

ACC

3.52

3.28

MKT

Overall

3.44

3.24

3.57

3.37

3.41

3.36

3.15

3.35

3.35

3.41

3.51

3.30

3.59

3.43

Delivering Management Education via Tutored-Video Instruction

of a company owned by the Ministry of Foreign Trade of the People’s Republic of China. Faculty within the School of Business Administration and Management (SOBAM) were desirous of opportunities for foreign study and to learn more about distance education. Therefore, this opportunity was solidly supported by the faculty. After examining alternative distance education methods, we decided to use TVI, because the research on distance education, as referenced above, showed that it was effective, specifically as it related to student performance and learning. USF received specific approval for this program from its accrediting organization, the Western Association of Schools and Colleges, who required that the initial cycle must include an assessment of TVI students’ performances compared directly to the performances of on-campus students taking the same course “live”.

Process A USF professor flew to Hong Kong to direct the selection of 40 students for the first cycle from a pool of approximately 100 executives that had expressed interest. Two local tutors were then hired and trained. On-campus courses were videotaped at USF and the faculty teaching these courses were required to also develop a learning plan for the TVI students in China. Faculty were required to use the same examinations and assignments that they used for their “live” students for the assessment of their TVI students. TVI students were enrolled in two MBA courses during each

10-week teaching modules. Once during each CRC module, two USF faculty would fly to Hong Kong to meet with the students daily over a 5-day period; the students received an average of nine to 11 hours of “live” classroom instruction during those five days. In 1993, USF signed the GD contract. A similar process was used to select students from those nominated by the company. One local tutor was hired and trained to lead discussions. Because of the location of these students’ jobs, USF faculty did the “live” teaching components at two separate locations, Guangdong and Hong Kong; and by agreement, the tutor was supposed to lead discussions at both locations.

Assessment Three formal evaluations of these programs were undertaken. We first wanted to know, did the TVI students perform better than the “live” students?” As shown in Table 1, overall the students in the last four cohorts did not, as determined by comparing the TVI students’ average grade point average (GPA) to the average of all USF MBA students who took the same courses on-campus. As shown in this table, we also grouped the GPA’s by the respective disciplines; for example, accounting, finance, and so forth. The average GPAs of the TVI students and the students who were taking the same MBA courses on campus are shown in Table 2. Overall, the TVI student performance was significantly below that of the on-campus students in every teaching

Table 2. Summary of student GPAs for all programs and all courses TEACHING AREA ACC

COMM

DS

ECON

ENV/LAW

FIN

MGMT

MIS

MKT

Grand Total

Average of USF GPA

3.32

3.56

3.39

3.22

3.70

3.41

3.51

3.30

3.59

3.43

Average of China GPA

3.41

3.47

3.38

3.12

3.54

3.41

3.36

3.15

3.35

3.36

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Delivering Management Education via Tutored-Video Instruction

Table 3. Average of response means for comparable questions, “live” vs. TVI PROGRAM CRC2

GD1

CRC3

USF Fall 97

USF Spring 98

a. Well-defined course objectives

4.16

3.98

4.225

4.00

4.10

b. Appropriate difficulty level

3.83

3.66

3.935

3.50

3.50

c. Helpful assignments

3.99

3.64

4.024

3.50

3.40

d. Helpful to my professional activity

3.85

3.63

4.103

4.30

4.30

e. Helpful to my professional goals

4.11

3.81

4.158

4.00

4.00

f. Reading assignments helpful & easy

3.83

3.58

3.939

3.60

3.60

g. Fair exams

3.83

3.33

3.975

2.40

2.20

e. Lectures were well organized

3.86

3.66

3.990

4.00

4.10

f. Lectures were easy to follow

3.68

3.54

3.949

3.90

4.00

g. Lectures help me understand the material

3.80

3.58

3.985

a. Lectures were useful

4.35

3.82

4.272

3.70

3.80

b. Discussions with professor were helpful

4.22

3.94

4.186

4.10

4.10

c. Class activities with professor were valuable

4.26

3.71

4.238

COURSE CONTENT:

VIDEO TAPES:

ON-LOCATION LIVE TEACHING:

(Off-site scale: 1=Strongly Disagree to 5=Strongly Agree; On-site scale: 1=Hardly Ever to 5=Almost Always)

area except accounting and finance. Statistically significant higher averages are bolded in this table; p < .05. Second, we did a direct comparison of average student course evaluations with three of the TVI cohorts and compared them against the average responses of the “live” students. As shown in Table 3, TVI students generally felt that overall the courses they had taken had great value. However, there were two areas of disagreement. First, the TVI students felt that their courses were not well organized. Second, they felt that although the course materials were not helpful to their professional activities, they were helpful to their professional goals. Many of the differences between the means of the “live” and TVI students were found to be statistically significant.

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A full discussion of these comparisons is shown in Murray and Efendioglu (1999). Third, several evaluations of the TVI programs were directed towards the faculty who were teaching in it. Overall, the faculty who taught in the program felt that their TVI experiences were positive. Further, the opportunity to teach in this program was also highly valued by faculty, because it gave them the opportunity to travel to China and be exposed to that foreign culture.

outcomes Many aspects of our experience with distance teaching have been positive. The Chinese students were generally enthusiastic. They believe their time and effort was valuable to them personally

Delivering Management Education via Tutored-Video Instruction

and that their companies would benefit from the knowledge they acquired. The opportunity to teach in this program was highly valued by faculty, because of the international exposure opportunities it provided. The logistical demands of the taping also meant that many of their lectures were better prepared, and in some cases this left them with a set of very well-organized materials for subsequent offerings of the same courses. In addition, the school became much more aware of the demands of doing this type of training and now has much greater capability to do it successfully.

concLusIon Contrary to previous research, the average grade for the TVI students was lower than the average grade for students in the “live” classes. The faculty who taught in these programs developed several hypotheses as to why program performances and student achievements differed from those expected. We found that few of the faculty used the tutor as intended. In the later cohorts, the role of the tutor was functionally downgraded to that of course assistant; for example, starting the video, mailing the assignments, and so forth. Further, many of the students actually watched videotapes individually without the benefit of the group interaction and active questioning inherent in the TVI model. Specifically: 1.

2.

3.

For a majority of courses offered via TVI, the client companies decided not to provide the required level of tutoring or to require the students to engage in discussions. Many of the faculty were not fully aware of the underlying concepts of TVI, and often the USF-based program coordinators did not require that the TVI model be followed. Approximately one-third of the class contact hours of the TVI courses were eventually

4.

taught ”live” by USF faculty, in direct contrast to the TVI model that uses no “live” instruction. The TVI program did not take full advantage of the learning curve; that is, the experiences of the faculty teaching in the program were not captured, analyzed, organized and presented to faculty who were teaching in the program for the first time.

A full discussion of these conclusions can be found in Murray and Efendioglu (2001).

Future The version of the TVI technology that we used in China would be more appropriately labeled “Video Instruction,” because the students actually received courses without the necessary tutor-directed discussion. Modifications by the faculty and administration of these cohort programs significantly reduced the effectiveness of the TVI technology. Correspondence received by faculty from the CRC1 and CRC2 students contains many references to the significance of the role of the tutor and the discussions to their learning. We therefore feel that tutor and the structured discussions are the critical elements in the successful use of TVI.

reFerences Appleton, A., Dekkers, J., & Sharma, R. (1989). Improved teaching excellence by using tutored video instruction: an Australian case study. Presented at the 11t h EAIR Forum, Trier, Germany. Arentz, H.C. (1995). A survey of TVI learners within cost engineering. Cost Engineering, 37(10), 26-35. Efendioglu, A. (1989). The problems and opportunities in developing international business

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Delivering Management Education via Tutored-Video Instruction

programs. Journal of Teaching in International Business, 1(2).

Presented at the Frontiers in Education Conference, Vienna, Austria.

Gibbons, J. (1977). Tutored Videotape Instruction. Presented at the Conference on Education Applications of Satellites, Arlington, Virginia.

Thach, E., & Murphy, K. (1995). Training via distance learning. Training & Development, 49(12), 44-47.

Gibbons, J., Kincheloe, W., & Down, K. (1977). Tutored Videotape Instruction: A new use of electronic media in education. Science, (March 18), 1139-1146. Lucey, J., & Burdett, F., (1991). Institute MBA at University of Aston Business School. Management Services, 35(8), 22-23. Murray, L., & Efendioglu, A. (1999). Distance education: delivery systems and student perceptions of business education in China. Proceedings at the Decision Sciences Institute Annual Meeting, 281-283. Murray, L., & Efendioglu, A. (2001). Using Tutored Video Instruction to deliver management education in China at a distance. In R. Discenza, C. Howard, & K. Schenk (Eds.), The design and management of effective distance learning programs (pp. 218-232). Hershey: Idea Group Publishing. Sparkes, J. (1985). On the design of effective distance teaching courses. Presented at the Annual Conference of the International Council on Distance Education, Melbourne, Australia. Stone, H. (1990). A multi-institutional evaluation of video-based distance engineering education.

Key terMs Cohort: A group of students who take the same courses together throughout their academic program. Cycle: The time period required for each student to enter and complete all courses required for an academic degree; for example, MBA. “Live” Students: On-campus students who were enrolled in the classes that were videotaped. Program: A set of academic courses required for the award of an academic degree; for example, MBA. Tutor: A person trained to lead discussions of questions supplied by the instructor and to report back to the instructor with a summary of the student responses and additional questions raised by the discussion on a timely basis. Tutored-Video Instruction: A distance education technology whereby students watch a video-taped classroom lecture as a group and then undergo an organized, systematic discussion of that lecture led by a tutor.

This work was previously published in the Encyclopedia of Distance Learning, Vol. 2 , edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 505-509, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.33

E-Moderating in Higher Education Gilly Salmon Open University Business School, UK

AbstrAct

IntroductIon And rAtIonALe

There are few published reports of structured approaches to developing lecturers for new online roles. However, both campus and distance learning institutions can offer some experiences in developing lecturing staff to moderate and teach with low cost text-based online conferencing. This role is known as e-moderating. Staff development is often asserted as a key issue in the success of everything from a project, a course or a whole institution to an online environment. The current climate asserts the importance both for university and college lecturers of adopting a good practice and an understanding of teaching in addition to academic competence. This chapter considers and explores the knowledge and skills that the best e-moderators have and how they can be recruited, trained and developed.

The challenge of developing new kinds of online teaching and learning processes, while remaining true to educational or training missions, is at the forefront of the implementation of information and communication technologies in the early 21s t century. Alexander, McKenzie et al. (1988) show that staff development is one of the main factors in determining the success of institutional attempts to make the transition to online delivery. The term moderator has grown up with the use of online text-based discussion and group work, in teaching and learning contexts. In 2000, I first used the term “e-moderating” to capture the wide variety of roles and skills that the online teacher, lecturer or trainer needs to acquire. Supporting learning online through synchronous and asynchronous conferencing (bulletin boards, forums) requires e-moderators to have a wider range of expertise compared to working with face-to-face learning groups. Hence, the role of the lecturer

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E-Moderating in Higher Education

or teacher in higher education needs to change to include e-moderating to match the development and potential of new online environments. Successful and productive e-moderating is a key feature of positive, scalable and affordable e-learning projects and processes. Regardless of the sophistication of the technology, online learners do not wish to do without their human supporters. How many people, for example, have been heard to say, “I’m great at art because of my inspirational computer”? Not any that I’ve met, on or off-line! Instead, learners talk of challenge and support by their teachers or of contact with the thoughts and the work of others. Most people also mention the fun and companionship of working and learning together. Such benefits do not have to be abandoned if developing online learning results in a cohort of trained e-moderators to support the online learners. Many words have been written about new technologies and their potential, but not much about what the human supporters of the learning actually do online. The greatest impact of all on the quality of the students’ learning resides in the way a technology is used and not in the characteristics of the medium itself (Inglis, Ling et al., 2000). Although increasing numbers of learners are working online, few lecturers have themselves learned this way. Therefore, e-moderating is not a set of skills most lecturers have acquired vicariously through observing teachers while they themselves were learning. Many lecturers naturally believe that learning to e-moderate mostly has to do with learning new software or computing skills. This is not the case. In textbased asynchronous environments, a critically important role for the e-moderator is promoting the surfacing and sharing of understanding and knowledge through online writing and dialogue (Barker, 2002). Furthermore, successful e-moderating cannot be achieved by doing what lecturers always did in the classroom. As of yet, there

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are few online mentors to guide them through step-by-step, nor is there time for long-term apprenticeships. It follows that e-moderators must be specially recruited, trained and developed. Currently, e-moderating continues to be a labour-intensive service. The UK Open University, for example, works to an average of 25 students per online teaching discussion group. The forprofit University of Phoenix in the US operates in learning groups of eight to 15 students, each with an online teacher. This means that we are likely to witness a growth in demand for online teachers in the next few years.

deFInItIons And context There are many definitions of an online course. These include classroom-based teaching supplemented by lecture notes posted on a web site or by electronic communication such as e-mail. At the other end of the spectrum, materials may be made available and interactions occur exclusively through networked technologies. Currently, in the UK, completely online courses are rare. Most courses are mixed mode or blended in some way. I use the term online to mean teaching and learning which takes place over a computer network of some kind (e.g., an intranet or the Internet) and in which interaction between people is an important form of support for the learning process. This rules out learning which is purely “resource-based,” e.g., learning using some Webbased courseware without recourse to any kind of human interaction. It includes both synchronous and asynchronous forms of interaction and also interaction through text, video, audio and in shared virtual worlds (Goodyear, Salmon et al., 2001). To date, text-based asynchronous computer mediated conferencing or forums have been the most extensively used for teaching and learning

E-Moderating in Higher Education

in higher education, both on and off campus, and hence I concentrate especially on the roles of emoderators in asynchronous networked learning environments. Platforms most commonly in use include FirstClass, Blackboard and WebCT, but there are a wide variety of others, including commercial systems and those developed in-house. E-moderating draws on aspects of both faceto-face teaching and traditional print-based distance teaching. However, it also calls for the introduction of a range of new understandings and techniques that are specific to online delivery. The key factor in e-moderating is that the e-moderator operates for part of the time in the electronic environment along with his or her students or learners. Online teaching also requires an attitude change for teaching staff. Some researchers argue this is nothing less than a major cultural change (Williams, 2002). There are two main ways that lecturers in universities and colleges can be developed to engage successfully in online teaching opportunities. One approach is to enhance the technical knowledge of teaching staff to enable them directly to design, develop and produce online materials and teach online with their students. Some of the platforms in use, such as Blackboard, have been developed to make these tasks as simple and as non-technical as possible. However, a second and more common method is to take a specialist approach to staff development. This involves increasing the skills of lecturers to focus on the successful delivery of online teaching and facilitating and the support of online students, usually in combination with their other (off-line) duties. This means that other people also must be recruited, such as instructional designers, graphic designers, computer technicians, multimedia programmers, audio-visual technicians, editors of text, e-librarians and resource providers. (See Inglis, Ling et al., 2000, for further exploration of these issues.)

coMPetencIes And sKILLs For e-ModerAtors Goodyear, Salmon et al. (2001) detail the online teacher’s roles as follows: 1.

2.

3.

4.

5.

6.

7.

8.

Process facilitator: Facilitating the range of online activities that are supportive of student learning. Adviser/counselor: Working on an individual/private basis, offering advice or counseling learners to help them get the most out of their engagement in a course. Assessor: Concerned with providing grades, feedback, validation of learners’ work, etc. Researcher: Concerned with engagement in production of new knowledge of relevance to the content areas being taught. Content facilitator: Concerned directly with facilitating the learners’ growing understanding of course content. Technologist: Concerned with making or helping to make technological choices that improve the environment available to learners. Designer: Concerned with designing worthwhile online learning tasks (both “pre-course” and “in course”). Manager/administrator: Concerned with issues of learner registration, security, record keeping, etc.

Of these, the most difficult to grasp and achieve are the process roles, e.g., one to five. These are the roles that I call e-moderating. I have analysed the qualities and characteristics of successful e-moderators—the competencies they should acquire through training and experience (Salmon, 2002) (see Figure 1).

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2190

E

Characteristics

Personal

D

Content expertise

C

Online communication skills

B

Technical skills

A

Understanding of online process

Characteristic

Quality/

Is able to encourage sound contributions from others, know of useful online resources for their topic.

Has knowledge & experience to share, willingness to add own contributions.

Is able to establish an online identity as e-moderator.

Is able to trigger debates by posing intriguing questions.

Is able to write concise, energizing, personable online messages.

Has determination & motivation to become an e-moderator.

Is able to engage with people online (not the machine or the software), responds to messages appropriately, be appropriately “visible” online, elicit & manage students’ expectations.

Is able to adapt to new teaching contexts, methods, audiences & roles.

Know how to “scale up” without consuming inordinate amounts of personal time, by using the software productively.

Provides courteous & respectful in online (written) communication, able to pace & use time appropriately

Knows how to use special features of software for e-moderators, e.g. controlling, weaving, archiving.

Has ability to develop & enable others, act as catalyst, foster discussion, summarize, restate, challenge, monitor understanding & misunderstanding, take feedback.

DEVELOMENTAL

III

Is able to appreciate the basic structures of CMC, & the WWW & Internet’s potential for learning.

Understands the potential of online learning & groups.

Is able to build online trust & purpose for others.

CONSTRUCTIVE

II

Has operational understanding of software in use reasonable keyboard skills; able to read fairly comfortably on screen, good, regular, mobile access to the Internet.

Has personal experience as an online learner, flexibility in approaches to teaching & learning. Empathy with the challenges of becoming an online learner.

CONFIDENT

I

Shows sensitivity to online relationships & communication.

Carries authority by awarding marks fairly to students for their participation & contributions.

Able to gradually increase the number of learners dealt with successfully online, without huge amounts of extra personal time

Is able to interact through e mail & conferencing & achieve interaction between others, be a role model.

Is able to use special features of software to explore learner’s use e.g. message history.

Knows when to control groups, when to let go, how to bring in non-participants, know how to pace discussion & use time on line, understand the 5-stage scaffolding process & how to use it.

FACILITATING

IV I

Is able to enliven conferences through use of multi media & electronic resources, able to give creative feedback & build on participants’ ideas. Knows how to create & sustain a useful, relevant online learning community.

Shows a positive attitude, commitment & enthusiasm for online learning.

Is able to communicate comfortably without visual cues, able to diagnose & solve problems & opportunities online, use humour online, use & work with emotion online, handle conflict constructively.

Is able to use software facilities to create & manipulate conferences & to generate an online learning environment, able to use alternative software & platforms.

Is able to use a range of approaches from structured activities (e-tivities) to free wheeling discussions, & to evaluate & judge success of these.

CREATIVE

V

Knows about valuable resources (e.g. on the WWW) & refer participants to them.

Is able to value diversity with cultural sensitivity, explore differences & meanings.

Creates links between CMC & other features of learning programmes.

Can explore ideas, develop arguments, promote valuable threads, close off unproductive threads, choose when to archive.

V KNOWLEDGE SHARING

E-Moderating in Higher Education

Figure 1. Table of e-moderator competencies (Source: Salmon, 2000)

E-Moderating in Higher Education

recruItIng your e-ModerAtors Given the required competencies, how do you set about acquiring the right e-moderating staff? Most institutions face re-skilling experienced staff, or adding e-moderation to training programmes for new teaching staff. Currently, it is most unusual for lecturers or tutors to be recruited for e-moderating skills per se or for their previous experience in teaching online. In the future, however, I predict that there will be more specialisation, and some categories of staff will demonstrate their particular aptitude for working online. A long list of relevant teaching qualifications or experiences is unlikely to be found at this stage of the development of online lecturers and trainers. The e-moderators you recruit should, of course, be credible as members of the learning community. I suggest that you try to recruit emoderators with the qualities from columns one and two of Figure 1, if possible. Teachers who have something of a vision of the importance of online learning in the future and how to prepare themselves to operate successfully and happily within such an environment are those to be spotted and supported (Waeytens, Lens et al., 2002). However, at the moment, there are very few such people available. I tend to select applicants who show empathy and flexibility in working online, plus exhibit a willingness to be trained as e-moderators. Before asking them to work online, you must train them in the competencies described in columns three and four in Table 1. I would expect e-moderators to have developed the skills in columns five and six by the time they had been working online with their participants for about one year. If lecturers or academics are used to being considered an “expert” in their subject, the levelling effect and informality of online networking can be very challenging for them. As e-moderators, they will probably have to work a little harder to

establish their credentials as an experienced professional in the online environment, as opposed to being in a face-to-face group. Even those recruits who are used to developing distance learning materials need to explore how online materials can underpin and extend their teaching. It follows that e-moderators will also need to develop good working relationships with librarians who are rapidly transforming themselves into ICT resource providers. Understanding ICT resource provision is another aspect that can be checked out during recruitment by asking, for example, about a favourite web site for their subject. It is most important to look at the potential, as well as at the existing skills of recruits. Emoderators will need to know about online communication, rather than only learn the software. They will need to have the ability to provide support and counseling through e-mail, as well as the creativity and flexibility to design and adapt collaborative opportunities for differing purposes, individual and organisational missions and needs. They must be able to work cross-culturally and value diversity. They must be flexible in considering approaches to online assessment, evaluation and achievement. They must understand the benefits of online working and, hence, are able to act as resource guides and monitors. Furthermore, they will have personal metacognitive and adaptable approaches to learning and the ability to reflect and have input into overall course learning processes. The following table suggests some questions to ask to establish such potentials. Skills in a particular platform are unimportant at the recruitment stage. These can be taught and retaught as needed. To summarise, at the moment there are few people available with the skills I have listed in Figure 1. Most newcomers to e-moderating are more familiar with teaching face-to-face, where they rely perhaps on personal charisma to stimulate and hold their students’ interest. So what is most important in recruiting e-moderators? The main enemy of operating successfully as an e-

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E-Moderating in Higher Education

moderator in asynchronous environments is time. Therefore, you need to look for people who will not try to cover everything. But, instead look for those who have student-focused strategies based on encouraging the students to change their view of the world—strategies that are based on what the students do. E-moderator recruits also need to be very organised. There is rarely the same opportunity to improvise as there is in face-toface teaching. I would consider the most essential skills are empathy online and a flexible approach to working, teaching and learning online. Any recruit will have to be willing to be trained and developed in the e-moderating role. They will need good keyboarding skills and some experience of using computers, including online networking. “Black and white thinkers” are generally to be avoided. What you are recruiting for, to a large extent, is the ability to adapt to technological and online environment changes, as well as to operate successfully using current platforms. Look for people who have cross-cultural sensitivity which includes the ability to handle ambiguity and multiple viewpoints. However, given those requirements, good e-moderators come from many different backgrounds, with very varied learning and teaching experiences. Where they live, their domestic or work commitments or any disabilities that reduce their ability to travel are unimportant.

trAInIng e-ModerAtors Even if teachers have an excellent record in conventional settings, it is difficult to predict who will do well in online teaching. Currently, few universities and colleges offer much in the way of training for e-moderating skills and the best methods are yet to be identified (Kearsley, 2000). However, the acquisition of e-moderating skills cannot be achieved vicariously by lecturers observing other online teachers or by looking at exemplary web sites. Enabling lecturers to use

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technology in their teaching, means providing training that is motivating, attention gaining, relevant and confidence building. A tall order, indeed!

scAFFoLdIng: A ModeL oF onLIne deveLoPMent Figure 2 offers a model of teaching and learning online, researched and developed with business school students and tutors in the Open University over several years and since applied across many learning disciplines, contexts and levels. This model can be used as a scaffold for training and developing e-moderators. Scaffolding suggests a way of structuring online interaction and collaboration, starting with recruitment of interest, establishing and maintaining an orientation towards task-relevant goals, highlighting critical features that might be overlooked, demonstrating how to achieve those goals and helping to control frustration (Wood & Wood, 1996). It is especially important to concentrate on the communicative aspects of the use of the online learning platform (Monteith and Smith, 2001). Each level of the five-stage model involves somewhat different activities for the participants. What the e-moderator does online, and how much, varies according to the purposes, intentions, plans and hopes for online learning. There is growing evidence that teachers benefit from a developmental approach to learning new techniques (Cornford, 2002). There are certain key stages in the progression of the trainee e-moderator. First, there is a crucial understanding that gradually increasing the comfort of online learners will increase participation and completion rates. Second, an appreciation develops that the design of online activities and interaction is as important as sophisticated, but nondynamic, design and delivery of content. Third, that the evolving role of the e-moderator, who is much more than just a facilitator or responder to questions, will make or break the experience

E-Moderating in Higher Education

Figure 2. (Source: Salmon, 2000) Development Providing links outside closed conferences

Supporting, responding

Knowledge construcetion Facilitating process

Information giving and receiving Facilitating tasks and supporting use of learning materials

Searching, personalising software

Online socialisation Sending and receiving messages

Interactivity

Conferencing

Familiarising and providing bridges between cultural, social and learning environments

Access and motivation Setting up system and accessing

Welcoming and encouraging

E-Moderating Technical support

for the learners. Fourth, there is a recognition that there is considerable evidence that people become more independent and more responsible for their own development as they move through the model, whether in structured or informal learning settings. To date, most lecturers have acquired e-moderating skills through informal networking and self-teaching, often in a situation of severe time poverty (Bennett, 2002). I will now outline the model, before going into detail. Facilitating individual access is an essential prerequisite for conference participation (stage one, at the base of the flight of steps). Stage two involves individual participants establishing their online identities and then finding others with whom to interact. At stage three, participants give and receive information freely to each other. Up to and including stage three, a form of co-operation occurs, i.e., support by the online group for each

person’s goals. At stage four, course-related group discussions occur and the interaction becomes more collaborative. The communication depends on the establishment of common understandings. At stage five, participants look for more benefits from the system to help them achieve personal goals, explore how to integrate online learning into other forms of learning and reflect on the learning processes. Each stage requires participants to master certain technical skills (shown in the bottom left of each step). Each stage calls for different emoderating skills (shown on the right top of each step). The “interactivity bar” running along the right of the flight of steps suggests the intensity of interactivity that you can expect between the participants at each stage. At first, at stage one, they interact only with one or two others. After stage two, the numbers of others with whom

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they interact, as well as the frequency, gradually increases, although stage five often results in a return to more individual pursuits. Given appropriate technical support, an emoderator, and a purpose for taking part in online networking, nearly all participants will progress through these stages of use in online learning. There will, however, be very different responses in terms how much time they need at each stage before progressing. The model applies to all online learning platforms. If experienced participants are introduced to software that is new to them, they will tend to linger for a while at stages one or two, but then move on quite rapidly up the steps again. The chief benefit of using the model to design development processes for e-moderators is that there is a greater readiness by e-moderators, once trained, to contribute to student learning online. E-moderators who understand the model and apply it should enjoy online learning and find that their work runs smoothly. They will spend much less time and achieve a more productive experience for their students. If suitable technical and e-moderating help is given to participants at each stage of the model, they are more likely to move up through the stages, to arrive comfortably and happily at stages three through five. These stages are the ones that are most productive and constructive for learning development purposes.

stage one: Access and Motivation For e-moderators, being able to gain access quickly and easily to the online learning system is one key issue at stage one. The other is being motivated to spend time and effort. The participant needs information and technical support to get online and strong motivation and encouragement to put in the necessary time and effort. Like learning any new piece of software, mastering the system seems fairly daunting to start with. However, it is important to reassure lecturers that successful achievement of e-moderation

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does not depend on previous computer literacy (online networking often appeals to inexperienced computer users). At this stage, computer skills will vary enormously. Use of e-mail is almost universal, whereas competent, effective communication with it is not. And few people are really skilled in using asynchronous groupware. Most people will be unfamiliar with the tools you choose to use. However, many trainee e-moderators need some form of individual technical help at this stage, as well as general encouragement. Problems are often specific to a particular configuration of hardware, software and network access or else related to the loss of a password. Access to technical support needs to be available, probably through a telephone helpline, particularly when the trainee is struggling to get online on his or her own. However, it is a mistake to offer extensive face-to-face workshops to lecturers in an attempt to enable them to feel more comfortable with the technology. They need to develop these skills in the relevant context of their own teaching. The simplest approach is to emulate the student experience for the lecturers, since few of them have been online learners. Another aspect of access is special needs of various kinds. In the spirit of wide diversity and empowerment, it is good that the disabilities of users with special needs are not usually obvious online. It is normally impossible to tell from the messages in a conference that a participant or an e-moderator has restricted vision or hearing or problems of mobility, unless that person wishes to volunteer the information. People who have problems with their speech or hearing are not at a disadvantage in text-based conferencing. However, those who have problems with their vision or physical movement may well find that the keyboard and screen prevent them from doing as much as they would like. Dyslexics still have some difficulties online, even with electronic help available. It is very important that trainee e-moderators understand the nature of special needs and facilitate learning through the medium.

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Strong motivation is a prime factor at this first stage, when participants have to tackle the technical problems. Nearly all studies have shown that trainee e-moderators are extremely resistant to insistence on their participation (Salmon, 2000; Collis and Moonen, 2001; Inglis, Ling et al., 2001), so carrots are much more likely to be successful than sticks. No doubt, all staff will have heard horror stories about the time required for e-moderation processes. So they need reassurance, training and clear agreements about the time required from them.

stage two: online socialisation In stage two, participants get used to being in the new online environment. Many of the benefits of online learning in education and training flow from building an online community of people who work together at common tasks. Stage two is a critical stage and cannot be left out. It provides the motivation and creates the important building blocks of professional development. Networked learning offers the “affordance” of online socialising. Affordance means that the technology enables or creates the opportunity (Gaver, 1996). In the case of online conferencing, it has an inherent social component, as well as the ability to convey feelings and build relationships. However, online learning will not in itself create social interaction. Sensitive and appropriate online conference design and the intervening support of more experienced e-moderators will cause the socialisation to occur. It is essential to offer trainee e-moderators the experience of working online with others. A sense of continuity, a connectedness with time and place, and a connectedness with others contribute to online socialising. Our own internalised set of instructions for how to behave and how to make judgements, for feeling comfortable together and “at home in one’s world,” and the reassurance of the familiar—these all help enable

us to find our roots in the social world. When online teaching fragments and expands this sense of time and place, the usual pillars of well-being may be less available. There is evidence at stage two that all trainee e-moderators struggle to find their sense of time and place in the online environment. Hence, the importance of enabling induction into online learning to take place with support and in an explicitly targeted way. Stage two participants recognise the need to identify with each other, to develop a sense of direction online and they need some guide to judgement and behaviour. A wide range of responses occurs. Some are initially reluctant to commit themselves fully to public participation in conferencing, and should be encouraged to read and enjoy other’s contributions to the conferences for a short while, before taking the plunge and posting their own messages. This behaviour is sometimes known as “lurking,” although the term can cause offence! “Browsing” or “vicarious learning” are perhaps safer words. Browsing appears to be a natural and normal part of socialisation into online learning and should, therefore, be encouraged for a while as a first step. When participants feel at home with the online culture, and reasonably comfortable with the technology, they move on to contributing. E-moderators really do have to learn to use their skills to ensure that participants develop a sense of community in the medium. O’Brien tells us, from nursing education online, that integration of beliefs and practices of individuals from all social and cultural groups in society is very important for professional development (1998). This is applicable for all online groups, especially as we teach and learn in increasingly international communities. The idea is simply that we should encourage participants to identify and share their own beliefs and values, and acknowledge that they are different from those of others.

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stage three: Information exchange A key characteristic of online learning is that the system provides all participants with access to information in the same way. At stage three, participants start to appreciate the broad range of information available online. Information exchanges flow very freely since the “cost” of responding to a request for information is quite low. In my experience, participants become excited, even joyful, about the immediate access and fast information exchange. They also show consternation at the volume of information suddenly becoming available. E-moderators can be helped to become independent, confident, and enthusiastic about working online at this stage. Trainee e-moderators need to know how to exchange information in online conferences and forums. Information exchange proficiency is essential before they move on to full-scale interaction in stage four. Demands for help can be considerable because their experience in searching and selection may still be low. There can be many queries about where to find one thing or another online. In summary, trainee e-moderators develop a variety of strategies to deal with the potential information overload at this stage. Some do not try to read all messages. Some remove themselves from conferences of little or no interest to them, and save or download others. Others try to read everything and spend considerable time happily online, responding where appropriate. Yet, others try to read everything, but rarely respond. These participants sometimes become irritated and frustrated. They may even disappear offline.

stage Four: Knowledge construction Familiarity with the technology must be achieved by this stage. If familiarity is not achieved, then it will only provide a distraction from the much more demanding experience of learning and

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development in unknown territory and the relationships that now develop. At this stage, trainee e-moderators will become very interested in likeminded communities that are available to them online, especially those from their own areas of interest or disciplines. The issues that can be dealt with best at this stage are those that have no one right or obvious answers, or ones that participants need to make sense of, or a series of ideas or challenges. These issues are likely to be strategic, problem, or practice-based ones. Most importantly, the development of tacit knowledge and its impact on practice can be very strong at this stage, and especially important in practice-based or clinical-based learning, such as management or medicine. Developing advanced skills in e-moderating is important at this stage. The best e-moderators demonstrate online the highest levels of tutoring skills related to building and sustaining groups. Feenberg (1989) coined the term “weaving” to describe the flow of discussion and how it can be pulled together. Online learning makes weaving easier to promote than learning in face-to-face groups, since everything that has been “said” is available in the conference text. The best e-moderators undertake the “weaving.” They pull together the participants’ contributions by, for example, collecting statements and relating them to concepts and theories from the course. They enable the development of ideas through discussion and collaboration. They summarise from time to time, span wide-ranging views and provide new topics when discussions founder. They stimulate fresh strands of thought, introduce new themes and suggest alternative approaches. In doing all this work, their techniques for sharing good practice and for facilitating the processes become critical. Trainee e-moderators need to learn how to add value to the online discussion forum or conference contributions at level four. First, the contributor needs to be acknowledged in order to be “heard.” Secondly, online contributions will be recorded,

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made available for others to read and become a form of inventory. The e-moderator’s role is that of a recorder creating the inventory to be surfaced and used by others. In a collective conference, personal “reflections” may be responded to in various ways. One person may need more time to explore issues, while another may reach conclusions quickly and then become impatient with those who are still thinking. It is important that the e-moderator avoids the temptation to discount the experience in any way or to counter it and enter into argument. Instead, he or she can draw on the evidence that is presented to try and explore overall conclusions. Thirdly, the e-moderator should comment at an appropriate moment on the sufficiency of the data being presented and, fourthly, on the quality of the argument around it. These ways ensure that the experiences, while valued, are not necessarily considered complete in themselves. The e-moderator is thereby modelling ways of exploring and developing arguments. The locus of power in more formal learning relationships is very much with the tutor, lecturer or academic expert. In online learning at stage four, however, there is much less of a hierarchy and greater potential for individual responsibility for development.

stage Five: development In higher education, e-moderators need to be able to engage in reflective practice themselves (Orsini-Jones and Davidson, 1999) and to be very democratic and open about their roles (Hunt, 1998). The challenge is to enable participants to recognise the narrowness of their own experience and be open to other evidence. The e-moderator should learn to prompt, encourage and enable such openness, while acknowledging personal experience. Sensitivity and courage may be needed to explore an experience with well-established, well-focused people! At stage five, trainee e-moderators will start to display considerable confidence, independence

and autonomy in the online environment. Indeed, they frequently start reverting to levels of confidence that they display in their more familiar offline worlds! They will become responsible for their own teaching and development through computer-mediated opportunities and need little support beyond that already available. Rather different skills come into play at this stage. These are skills of critical thinking and the ability to challenge the “givens.” Meta-cognitive learning skills are focussed on the impact of their teaching in new contexts or how they might apply concepts and ideas. When trainee e-moderators are learning through a new medium, such as online learning, their understanding of the processes of using the software and of the experience of teaching in new ways is being constructed, too. It is, therefore, common at stage five for trainee e-moderators to reflect on and discuss how they are networking and to evaluate the technology and its impact on the learning processes for their arenas of teaching.

successFuL e-ModerAtor trAInIng e-Moderating training design Columns three and four in Figure 1 provide competencies and objectives for training e-moderators. The model described in Figure 3 can be used to provide a framework for training. The training programme should be intrinsically motivating and lead to competent practice. The task is, therefore, to develop a programme that, while providing the development of essential basic skills, such as online confidence and competence, also represents as closely as possible the realities of teaching and learning online. Providing training of this kind is the best way of scaling up from the innovators and early adopters to the bulk of the lecturing and teaching team (Carlson and Repman, 2002).

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In order to indicate to trainee e-moderators that learning to teach online needs to be undertaken online, the training programme should use networked technologies and be accessed from the trainees’ own machines. Furthermore, the training should focus on pedagogical knowledge, built up through personal and collective reflection on practice, rather than on merely acquiring a technical grasp of the hardware and software. Most importantly, trainee e-moderators must have the experience of working, participating and themselves learning through others online for the training to be successful (Tsui and Ki, 2002). Such an approach sends a powerful message and provides an invaluable confidence builder. The programme should create a series of “micro-worlds” in which the trainees can interact with each other, with the e-convenors (trainer of the trainers, e-moderator of the e-moderators) and with the software, before progressing to the next stage. They should be advised of appropriate ways of undertaking the tasks, but could also construct their own approach. They need to learn to use the software as a matter of routine, while raising their awareness of the teaching and learning aspects. The importance ascribed in constructivism to the building of relationships between new and existing knowledge (Bruner, 1986) means the careful choice of titles for conferences, and the use of familiar metaphors for explaining aspects of online learning. E-moderator training must be meaningful and worthwhile for all lecturers if it is to be judged a success. Each stage in the training model should provide a “scaffold” or guide for training teachers (both new and experienced) from novice to expert status in and through the online environment itself. Basic computer literacy can be assumed. If teachers lack basic computing knowledge, they should be offered familiarity training and experience first. However, even advanced skills, for example, in using the Internet, will be insufficient. Experienced online users should be reassured that the programme is about e-moderating skills

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and not general technological competence. The process should be interactive (with other trainees and online trainers), with additional downloadable support material. The programme should include training in declarative knowledge (What is this icon?) and procedural knowledge (e.g., How do I send a message?). But, it should focus mainly on more strategic knowledge (What can I do with my emoderating skills?). However, trainees should acquire these various kinds of knowledge in an integrated way. The online training programme should not only be about acquiring new skills, but it should also help trainees to explore their attitudes about online learning and its meaning for their own teaching. Helping trainees to control their frustration is a key aspect of learning to learn online. A balance between a trainee struggling with too much complexity and being given enough involvement in the task needs to be achieved. Give more help when trainees get into difficulties and less as they gain proficiency. I suggest evaluation should be based on tracking the trainees through the stages in the programme by a series of online conferences and questionnaires of a quantitative and qualitative nature. A certificate of completion should be provided, as well as other motivators and incentives, if possible.

ActIon bAsed e-ModerAtor trAInIng: A ModeL desIgn Offering a small piece of information, which I call the “spark,” and then asking for some action or reaction on the part of trainees has proved the cheapest, easiest and most effective design to date. This is called “e-tivities” (Salmon, 2002). It has the advantage that little specialised technical knowledge is needed. It is also cheap and easy to set up within an existing online platform in use in a university or college.

E-Moderating in Higher Education

Each session is offered for one week. The programme lasts for five weeks. Participants are expected to take part for between three to five hours a week. It works best if they log on for a half an hour each day, but many other patterns of participation are also possible. Session 1 includes reading résumés, writing your own résumé, practising writing messages, practising sending e-moderating messages, exploring online chat facilities, encouraging contributions, using help, learning to quiz, evaluating contributions, and beginning the practice of reflecting. Session 2 includes getting the feel of online working, sharing experiences of being online, responding encouragingly, writing encouraging replies, identifying good and bad practice, practising expressing emotion, determining how frequently you should be online, exploring the nature of vicarious learners online, establishing your group, and more reflecting. Session 3 e-tivities include evaluating messages for encouragement, weaving, summarising, compiling information, being encouraging without answering questions, information exchanging, and building on reflection with others. Session 4 e-tivities include creating e-tivities, setting objectives, getting everyone up to the same level, asking questions, acknowledging, identifying new knowledge, producing a summary, becoming more knowledgeable, working in different size groups, and applying reflection to practice. Session 5 e-tivities include exploring meanings, identifying ways of helping adults learn through online interaction, planning for personal development in e-moderating skills, planning for further development in your e-moderating skills, building your development plan for further improvement in your e-moderating skills, identifying examples of interventions, building resources to aid development of your e-moderating work in future, reflecting on overall experience, and farewells.

Exemplar: University of Glamorgan E-College Project: Online Staff Development in Blackboard The core activity of the University of Glamorgan (http://www.glam.ac.uk) is the traditional delivery of courses at the University campus, as well as through agreements with its Associate and other Partner Colleges. Most lecturing staff have experience only in face-to-face methods of teaching. A few have been involved with traditional printbased, distance learning. It was decided to build on this experience and success and to work with partners in the public, private and voluntary sectors to widen the accessibility of the University’s Business and Management Courses through new methods of delivery. This work is intended to pilot the University through its Enterprise College (e-college) initiative (http://www.enterprisecollegewales.co.uk). The concept of the project is based upon forming an alliance of complementary organisations in the commercial, educational, media, communications, public and voluntary sectors to deliver training and skills development. The e-college initiative provides the additional flexibility of training and support of the University’s students through online entrepreneurial programmes. The flexibility of online delivery removes barriers and reaches an increased constituency of individuals, businesses (particularly those in the SME sector), and public and voluntary sector bodies. European Structural Funds support the development of course material and the delivery of the training for staff. Students are able to study at home, at work and on the college campus. They also have access to leased computer equipment installed in their homes. This initiative provides a significant opportunity for the University to evaluate the development, delivery and assessment of e-learning and to create a pedagogy or androgogy for this form of education. In order to provide staff with some expertise in e-moderating, the e-college undertook a major

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staff development programme. Unusually, staff development was put in place prior to going live with students and staff appreciated this development. The programme was based on an online asynchronous participative programme in Blackboard. It used the five-stage model of e-moderating development as a framework and interactive activities (e-tivities) to maintain interest and interaction between participants (see Figure 1). The staff development programme was built and run on the e-college’s server. Staffs were expected to take part around three hours per week over a five-week period in September and October 2001. Overall aims of the training programme were: • Provide lecturers with the skills to access and use Blackboard conferencing and to undertake a range of tasks online. • Provide lecturers with the experience and confidence to use the online discussion system as a key resource in building a student-based online learning community, and enable mobilisation of the learning of those students through simple interactive and emoderated participation (called e-tivities). • Enable lecturers to become active members of an online community for E-college emoderators participating in and contributing to the College’s successes, achievement and online interaction.

Evaluation The online programme introduced a set of simple motivational goals, by requiring participants to reflect “deliberately” on learning at each stage. They were encouraged to take part, to post at least one message at each of the five levels, to contribute to the “reflections” conferences, to complete their exit-questionnaires—and only then to ask for their certificate of completion.

Results Thirty-four lecturers involved in the E-college project started the course on or around September 10, 2001. Twenty-seven successfully completed the course by mid-October 2001. Another seven continued to work through the online activities more slowly. Although staff found the online e-moderation development programme very challenging, nearly all appreciated the opportunity to take part, and felt that they had achieved the objectives. Some of their final reflections are copied below: Some interesting reflections posted … it is heartening to know that others are feeling the same as me—being an e-learner has made me see the other side of the coin. I have learned a lot about learning online—a whole range of emotions from feeling very lonely at times, experiencing happiness when I achieve something and guilt when I know I am not contributing as much as I should be. (CH October 01) It also made me realise that e-moderating is not something you can do in small parcels of time (the odd hour between classes). It needs more attention and thought than that. (ES December 01) I can’t believe I’ve actually reached this stage—final reflections. Overall, I have found the course beneficial. I feel that my confidence in online learning has increased and my navigation skills have certainly improved (although they still are far from perfect). I also feel that I have a better understanding and knowledge of e-learning. This course has, however, also made me realise just how much more I’ve got to learn—I think there is a very steep learning curve ahead of me. (GG October 01) I have enjoyed the course and I feel I have learned a lot. I now feel more confident about my navigation skills and a little more confident about my

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e-moderating skills. I will be even more confident once I have tried it for real. Unlike some, I enjoyed the early stages. Finding out so much about each other helped me feel even more the importance of online socialisation. (NJ October 01) Dr. Norah Jones, the Project Manager, wrote: The programme was a success at two levels. First, it enabled us to gain greater confidence in using the software package (Blackboard) and secondly we were able to appreciate the need to fully engage e-learners. We also benefited by staff from many different locations in Wales working together online and getting to know each other through the development programme. We see this form of staff development essential and plan to spread development of this kind across the University for other e-learning projects.

deveLoPIng e-ModerAtIng In servIce After the training and when e-moderators start to work with their online learners, development needs to continue. During this phase I’d expect emphasis to be put on an understanding of the benefits and role of creative thinking in e-moderating and in the development of online group activities (see columns five and six in Figure 1). As experience is gained, e-moderators also start to display considerable confidence and skill in keeping their online teaching fresh, alive and varied by the use of creative thinking and inspired activities, typically going beyond the use of online forums only for discussion. There are two main ways that development can occur. One is through online networking with others, and the other is through peer to peer visits to observe online processes. Teacher education offers an example of building online learning communities with an impact

on professional practice, going further than what is possible in specific training events (Leach and Moon, 1999; Selinger and Pearson, 1999). By working in such a community, participants can extend their networking beyond the institution in which they work. They can also work with others from different educational traditions. Selinger shows us that this aids their attempts to seek out and understand new ideas and opinions. Thus, teacher trainees explore new ways of tackling everyday problems and report the results to the online community. To gradually build up appropriate and consistent e-moderating practice and ensure quality, you need to set up monitoring of your e-moderators’ work. You may, like the Open University, wish to base this on a peer review system. It is better to review and monitor the work of e-moderators online. I suggest you make sure that the reviewers are fully comfortable and competent themselves as e-moderators, so they don’t apply old paradigms of teaching and learning to the new environment! I suggest monitoring that concentrates on the key issues in Section 9. If e-moderators are coping with these issues, then you can be sure that not only are their skills building up, but participant satisfaction also will be growing. Of course, another important way of determining the success of the work of the e-moderators is to explore the responses of the participants, themselves.

e-ModerAtIng costs Some vendors of online learning solutions make their return-on-investment cases by disposing entirely of lecturer or trainer costs. Disposing of the e-moderator is very rarely appropriate in higher and further education. Enormous value is added to the student experience by skilled emoderation. Increases to the student-to-lecturer ratio are often considered detrimental to student learning and major causes of lecturer pressures. However, skilled and trained e-moderators can

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often handle large numbers of students online. The student-to-e-moderator ratio depends largely on the purpose of the online learning. Costing each activity related to online working is difficult, but not impossible. Much depends on the assumptions behind the figures. For example, I compared the estimated costs of training Open University Business School e-moderators face-toface with the actual costs of training them online. My estimates were based on costs in 1996 of a face-to-face weekend for 180 e-moderators, drawn from all over the UK and Western Europe, including travel and subsistence, attendance fees and set up costs, excluding staffing costs and overheads. These came to roughly £35,000 in 1996. The actual costs of the online training for 147 e-moderators totalled roughly £9,000, again without including staffing costs and overheads. The two sets of figures do hide quite a few assumptions, but the cost advantage was apparently considerable in that particular context. For the business school, there is a very substantial competitive advantage in having a large cohort of trained e-moderators for all courses that include online learning now or will do so in the next few years. This advantage, if it could be costed, is probably worth far more than the total cost to date of developing Internet technologies in the school! Here are some ways of keeping e-moderating costs down:

Keeping E-Moderating Costs Down 1.

2.

3.

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Make clear decisions about roles and numbers of e-moderators that you will need and the student-to-e-moderator ratio. Keep your e-moderator support to students focused and specify what you expect them to do and when—if necessary, publish total number of hours per week or month available to participants. Establish early on how much e-moderators should be expected to do and what reason-

able expectations there are on the part of students. 4. Ensure they are trained in advance of starting work with their students. 5. Train e-moderators online, rather than faceto-face. 6. Train e-moderators using the online platform, itself, thus creating confidence in the platform, as well as creating an e-moderating skill base. 7. Ensure that e-moderators can upload and download messages offline if they wish. 8. Train them how to use your conferencing software or platform software to best their advantage to save time. 9. Look into transfer of costs of hardware, software and connection to students, perhaps with grants for those unable to afford the cost. 10. Set up good helpdesk and online support systems, and encourage competent students to support others, leaving more of your emoderators’ online time for learning related e-moderating skills. 11. Use existing resources and knowledge constructed online as much as possible, rather than develop materials and/or pay for expensive third party materials. 12. Develop systems for re-use of online conferencing materials. 13. Build up economies of scale as rapidly as possible — choose only systems that can be expanded cheaply.

concLusIon In empowering teachers and academic staff to become e-moderators, we need to deploy an underlying approach to transformative learning for their development involving a process of deconstruction and reconstruction (Vieira, 2002). Dominant paradigms do need to be challenged

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(Rolfe, 2002). We need to get below the surface and beyond the myths already grown up around the nature of e-moderating and working online and get into offering real development help. Currently, the “richness” of the Web depends largely on its volume and the multimedia presentation of information. However, I believe the future brings us greater interaction—and interaction is fundamental to learning, so long as it is appropriately e-moderated and embedded in the overall learning methods. From these small beginnings, a new body of knowledge and practice will build up for e-moderators that will transfer again and again, even as more connected technologies become available. The need for skillful e-moderation will not disappear, regardless of how sophisticated and fast-moving the technological environments become. E-moderators add the real value! I think that the most successful teaching and learning organisations and associations will be those that understand, recruit, train, support and give free creative rein to their e-moderators, while addressing the natural fears of loss of power and perceived quality from traditional teaching staff.

reFerences Alexander, S., et al. (1988). An evaluation of information technology projects for university learning. Committee for University Teaching and Staff Development. Canberra: Australian Government Publishing Service.

Carlson, R. D., & Repman, J. (2002, July/September). Show me the money? Rewards and incentives for e-learning. International Journal on E-Learning, 9-11. Collis, B., & Moonen, J. (2001). Flexible learning in a digital world: Experiences and expectations. Falmer, London: Routledge. Cornford, I. R. (2002). Reflective teaching: Empirical research findings and some implications for teacher education. Journal of VocationalEducation and Training, 54(2), 219-235. Feenberg, A. (1989). The written word. In R. D. Mason & A. R. Kaye (Eds.), Mindweave, communication, computers & distance education. Oxford: Pergamon. Gaver, W. (1996). Affordances for interaction: The social is material for design. Ecological Psychology, 8(2), 111-129. Goodyear, P., et al. (2001). Competencies for online teaching. Education Training & Development, 49(1), 65-72. Hunt, C. (1998). Learning from learner: Reflections on facilitating reflective practice. Journal of Further and Higher Education, 22(1), 25-31. Inglis, A., et al. (2000). Delivering digitally. London; Sterling: Kogan. Kearsley, G. (2000). Online education: Learning and teaching in cyberspace. Belmot, CA: Wadsworth/Thomson Learning.

Barker, P. (2002). On being an online tutor. IETI, 39(1), 3-13.

Leach, J., & Moon, B. (1999). Recreating pedagogy. Learners and pedagogy. London: Paul Chapman.

Bennett, R. (2002). Lecturers’ attitudes towards new teaching methods. The International Journal of Management Education, 43-58.

Monteith, M., & Smith, J. (2001). Learning in a virtual campus: The pedagogical implications of students’ experiences. IETI, 38(2), 119-127.

Bruner, J. (1986). The language of education. Actual minds, possible worlds. Cambridge, MA: Harvard University Press.

O’Brien, B. S. (1998). Opening minds: Values clarification via electronic meetings. Computers in Nursing, 16(5), 266-271.

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Orsini-Jones, M. and Davidson, A. (1999, July). From reflective learners to reflective lecturers via WebCT. Active Learning, 10, 32-38.

psychological dimensions. Journal of Information Technology for Teacher Education, 1, 23-44.

Rolfe, G. (2002). Reflective practice: Where now? Nurse Education in Practice, 2, 21-29.

Vieira, F. (2002). Pedagogic quality at university: What teachers and students think. Quality in Higher Education, 3, 256-272.

Salmon, G. (2000). E-moderating: The key to teaching and learning online. Falmer, London: Routledge.

Waeytens, K., et al. (2002). Learning to learn: Teachers’ conception of their supporting role. Learning and Instruction, 12, 305-322.

Salmon, G. (2002). E-tivities: The key to active online learning. Falmer, London: Routledge.

Williams, C. (2002). Learning on-line: A review of recent literature in a rapidly expanding field. Journal of further and Higher Education, 26(3), 263-272.

Selinger, M., & Pearson, J. (Eds.). (1999). Telematics in education: Trends and issues. Oxford: Elsevier. Tsui, A. B. M., & Ki, W. W. (2002). Teacher participation in computer conferencing: Socio-

Wood, D., & Wood, H. (1996). Vygotsky, tutoring & learning. Oxford Review of Education, 22(1) 5-15.

This work was previously published in Distance Learning and University Effectiveness: Changing Educational Paradigms for Online Learning, edited by C. Howard, K. Schenk and R. Discenza, pp. 55-78, copyright 2004 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.34

Diffusion of Web-Based Education in Singapore and Australia Y.Y. Jessie Wong Independent Educational Researcher, Canada R. Gerber University of New England, Australia K.A. Toh Nanyang Technological University, Singapore

IntroductIon The Internet has transformed the way education is delivered in the 21st century. Web-based education has been developed on the basis of the capability and potential of the Internet. The idea of Webbased education was first developed about 15 years ago from a simple form of online learning, using mainly e-mail as a form of communication and consisting of mainly text, with no multimedia. Soon after, a variety of new software and services were developed to support Web-based education. In late 1990s, the development of new technologies for this purpose accelerated. They gradually transformed the way by which distance education was delivered. Today, it is common for both private and public educational institutions

to offer Web-based courses. However, only a few virtual universities exist today with all of their courses and activities Web-based. Books discussing the different aspects of Web-based education have also mushroomed. Khan (1997), Tan, Corbett, and Wong (1998), Aggarwal (2000), and Moore and Cozine (2000) provide a good understanding of the major aspects in Web-based Education, such as Web-based instructions, Web-based communications, Webbased Education technology, and Web-based Education diffusion. Taylor (2001), working in the Australian higher education context, has described distance learning now as having reached the fifth generation, involving Web capabilities. In his report entitled the “Fifth Generation Distance Education,” he described the fifth generation of

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Diffusion of Web-Based Education in Singapore and Australia

distance learning as the intelligent flexible learning model. Here, he provides a comprehensive basis for considering Web-based education as a distinctive form of distance education that possesses a variety of characteristics of delivery technologies. According to Taylor (2001), the key elements of Web-based education are: 1. 2. 3.

4.

Offering interactive multimedia online from the institution Offering Internet-based access to other World Wide Web resources Providing computer-mediated communications using automated response systems to control costs Having campus portal access to institutional processes and resources

What is distinctive about these elements is that they are delineated according to the following differing characteristics of delivery technologies. Each element offers flexibility in terms of time, place, and the pace at which people can learn using the materials. The materials that are developed for Web-based Education are highly refined and involve advanced interactive delivery. Through this approach it is possible to reduce the institutional variable costs to a low figure (Taylor, Kemp, & Burgess, 1993), thus making the Webbased education very cost effective. As the system matures, sufficient materials are available; the access to the materials via the World Wide Web, especially, saves costs in creating one’s own materials. Therefore, when compared to other forms of distance education, Web-based education is likely to: be less expensive; provide students with better quality learning experiences; be more effective in pedagogic terms; and allow for more efficient administrative services. Such a form of learning allows institutions to become “fast, flexible and fluid” (Taylor, 2001). It provides the opportunity for students from any global location to engage in a highly personalized educational experience at a relatively modest cost.

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Taylor (2001) categorizes the five stages of the development of distance education. They are: the correspondence model that is based on print technology; the multimedia model that is based on print, audio, and video technologies; the telelearning model that is based on the applications of telecommunications technologies to promote synchronous communication; the flexible learning model that is based on online delivery via the Internet; and the emerging intelligent flexible learning model that extends the fourth model by focusing on selected features of the Internet and the World Wide Web. He declares that for the first four models variable costs tended to increase or decrease directly with the variations in the volume of the activity. However, the final model is one that can actually decrease costs by providing access to institutional processes and online tuition. The distinctive feature of the fifth generation model is that it is Web-based, and therefore cost effective. Compared to classroom learning, Web-based learning saves the costs of employing classroom teachers. Learners access the Web-based materials themselves, at their own time, and they deal with them at their own pace. The learners may access teaching staff via the e-mail or chat rooms to discuss any issues relevant to the materials. This results in much lower costs for Web-based learning. Perhaps, this is the direction in which education should be moving, especially for adult learners. This model shows clearly that there are some applications of Web-based education in Generation 4, but it increases in Generation 5. Traditional methods of correspondence are generally used in Generations 1 to 3. Taylor (2001) does not suggest that Web-based Education is perfect. The power of Web-based Education to transform the educational experience is tremendous, but there are also risks (Web-based Education Commission, 2000). Most countries have realized the need to develop new policies to ensure that Web-based education will enhance and not frustrate learn-

Diffusion of Web-Based Education in Singapore and Australia

Table 1. Comparative attainment chart: Three levels of education in Singapore and Australia Models of D.L. involving WBE and their characteristics

Levels of education Singapore

Levels of education Australia

School

Poly

University

School

TAFE

University

Yes

Yes

Yes

Var

Yes

Yes

Var Yes Var No

Yes Yes Yes No

Yes Yes Yes No

Var Yes Var No

Yes Yes Yes No

Yes Yes Yes Var

Internet-based access to www resources Characteristics: Flexibility through time, place and pace Evidence of refined materials Advanced interactive delivery Institutional costs approaching to zero

Yes

Yes

Yes

Yes

Yes

Yes

Var Yes Var No

Yes Yes Yes No

Yes Yes Yes No

Var Yes Var No

Yes Yes Yes No

Yes Yes Yes Var

Computer mediated communication Characteristics: Flexibility through time, place and pace Evidence of refined materials Advanced interactive delivery

Yes

Yes

Yes

Var

Yes

Yes

Yes Var Var

Yes Yes Yes

Yes Yes Yes

Yes Yes Var

Yes Yes Yes

Yes Yes Yes

No

Yes

Yes

Var

Yes

Yes

Yes Yes Yes No

Yes Yes Yes No

Yes Yes Yes No

Yes Yes Yes Var

Yes Yes Yes Var

Yes

Yes

Var

Yes

Yes

Yes Yes Yes No

Yes Yes Yes No

Yes Yes Yes Var

Yes Yes Yes Var

Yes Yes Yes Var

No Yes No Yes

No Yes No Yes

N.A. N.A. No Var

No Yes No Yes

Var Var No Var

Generation 4 Interactive multimedia online Characteristics: Flexibility through time, place and pace Evidence of refined materials Advanced interactive delivery Institutional costs approaching to zero

Generation 5 Computer-mediated communication using automated response systems Characteristics: Flexibility through time, place, and pace Evidence of refined materials Advanced interactive delivery Institutional costs approaching to zero Computer portal access to institutional processes and resources Characteristics: Flexibility through time, place and pace Evidence of refined materials Advanced interactive delivery Institutional costs approaching to zero Level of usage of WBE applications 100% of D.L. web-based 50% or less of D.L. web-based 100% of on-campus courses web-based 50% or less of on-campus courses webbased

No

N.A. N.A. No No

ing. However, it needs to be developed and used properly. It is not a means by which to sell and buy education with increased profits, but it is a means to promote more efficient and effective

education for all, irrespective of nationality, age, or gender. In the United States, the Congress has established the Web-based Education Commission to address this important issue. The Commission

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Diffusion of Web-Based Education in Singapore and Australia

is aware of the tremendous power of the Internet to empower individual learners and teachers, as well as the barriers that frustrate learning in this new environment. It was given the task of addressing these challenges of a rapidly changing educational landscape. In Singapore and Australia, similar bodies have also been established to consider the issues of the development of Web-based Education in their respective countries. These establishments are important to ensure that the benefits of Webbased Education are being harnessed and that the risks are being minimized.

Method oF coMPArAtIve study This study is based on the categories used in Taylor’s (2001) report. It differs by comparing Web-based information from Australia and Singapore through a review of relevant literature, and with some contacts with the institutions in the study. There were two steps in this study. First, the stages in education are seen as they occur in the school, the polytechnics (equivalent to colleges of Technical and Further Education in Australia), and the university. Web-based education (WBE) diffusion in Singapore and Australia are compared at these three levels. A meta-analysis is conducted using a modified Taylor’s model, and the results are represented in the achievement table (Table 1). Second, the National University of Singapore and the University of Southern Queensland are compared in their attainment of using Web-based education for distance education as well as for on-campus programs. They are chosen because they represent more advanced universities in Webbased education in their respective countries. A detailed comparison is done in this way in order to focus on the differences and similarities as experienced by the particular university in each country (see Table 2).

the ProbLeMs In coMPArIng 2208

wbe dIFFusIon between sIngAPore And AustrALIA Singapore is a democratic city-state with a small population and one educational system for the whole nation. It is obvious that there is less difficulty for the diffusion of Web-based education to occur consistently nationwide in Singapore than in a bigger nation such as Australia. Individual territories and states in Australia have their own educational policies and practices. Therefore, there ought to be varieties instead of consistencies. To arrive at a general picture in Web-based education for the whole of Australia is difficult or inaccurate. In order to achieve a fair result of comparison between Web-based Education in Singapore and Australia, there is a need to look at not just the generalization but some case studies. While this study is general, an attempt is made to look at developments at some individual institutions.

Meta-Analysis The results of the meta-analysis are shown in Table 1. The x-axis indicates the three levels of education in Singapore and Australia. The y-axis indicates the fourth and fifth generations of Distance Learning, and their respective characteristics. An additional row is added to show the actual level of usage of Web-based Education applications on the y-axis. Each matrix is then marked with “Yes” or “No” or “Var,” indicating the attainment of Web-based Education, respectively. Only Generations 4 and 5 are included and applied, because Generations 1-3 in Taylor’s (2001) model refer to characteristics of distance learning other than the web-based approach. They are, therefore, not taken into consideration in this study. A quick perusal of Table 1 would suggest that, at the school level, there is consistency in Singapore in the application of Web-based Education. In Australia, there are more variations and

Diffusion of Web-Based Education in Singapore and Australia

Table 2. WBE diffusion at NUS and USQ NUS

USQ

WBE platform

IVLE U

WBE for internal courses

Yes

Yes

Applying Generation 4 & 5 in WBE Taylor’s Model

Yes

Yes

Cost of WBE approaching zero

No. Cost i s Moderately high No Y No Y

Moderate. Gradually decreasing

Separate Distance Education Arm Developing e-university

differences across the schools. While the Ministry of Education in Singapore guarantees all schools access to World Wide Web resources, interactive multimedia online, and online- or computer-mediated communication, the situation is different in Australia. Some schools have already been doing good work in Web-based education, with good use of interactive multimedia delivery in their teaching and learning, flexible access to World Wide Web for all in the school, and the use of management systems for all processes in administrative work. This is an exception rather than the norm in the school sector in Australia. Most schools in both Singapore and Australia have the basic infrastructure for Web-based education. However, as is shown in the Table 1, the situation is different in practice. The proportion of Web-based education to the conventional face-to-face method is still small at school level. The main reason is that while Web-based Education is considered worth trying, and may enhance teaching and learning, there is no intention for all courses to be Web-based at school level. In Singapore, the Ministry of Education set the standard of 30% of the curriculum in school to be Web-based by 2002. In Australia, there is no

SQOnline

es. Using WBE instead of correspondence es

such set standard. Thus, there is a greater variation in terms of Web-based Education at school level in Australia than in Singapore. In practice, the level of usage of Web-based Education is less than 50% in any case in both Singapore and Australia. One would enter a normal classroom with some forms of Web-based delivery only part of the time. Students, however, do involve in Webbased learning activity once in a while—more often in some schools, less frequent in others. Each of the five main characteristics in Generations 4 and 5 are further defined by four ingredients: flexibility through time, place, and pace; evidence of refined materials; advanced interactive delivery; and institutional costs approaching zero. As shown in Table 1, there is no case where the costs approach zero in delivering Web-based Education. In Singapore, the cost for all schools to install a Web-based education infrastructure is high. However, the cost for usage is less so, and becoming increasingly less expensive as time passes by. There is certainly evidence of refined materials in some schools. However, the schools share these resources through the World Wide Web. Advanced interactive delivery is certainly available in all schools in Singapore. However,

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Diffusion of Web-Based Education in Singapore and Australia

the usage by teachers varies considerably. Unlike students in higher institutions of learning, there is less flexibility for school students to gain access to World Wide Web resources and Web-based education materials; some schools in Singapore arrange a schedule for each class to use a computer lab where the main access to the World Wide Web is organized. After school, the students may access most of these materials through their own computers at home; however, not even half of the students have access to the World Wide Web at home. There are other common areas such as the library, where students can access resource materials through the World Wide Web at all times, as long as the library is open. It is not fair to say that such access and sharing of resources through the World Wide Web is not available in Australian schools. It is true that there are different mechanisms open to students for such access in Australia. There are still a reasonable amount of resource materials meant for internal access only in some schools in Singapore. Some are very good learning materials but are not being shared. It is very clear that there is little or no sign at all of any school attaining Generation 5 of Web-based education as defined in Taylor’s (2001) model. The Generation 5 features are more common features at higher institutions of learning, especially those with all or nearly all of their courses off-campus. Web-based education diffusion at the polytechnic level in Singapore is compared with the technical and further education in Australia. They are not exactly functioning in the same way, but they do both sit between the schools and the universities. In Singapore, the polytechnics are modern in their approach of teaching. Emphasis is given to learning more about technologies. They are keen in Web-based education and offer off-campus courses. As shown in Table 1, in some ways, Technical and Further Education in Australia and polytechnics in Singapore have achieved all the features of Web-based education

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as described by Generation 4 and 5 in Taylor’s model. One exception is, however, that the cost for providing Web-based Education in Singapore polytechnics is still high. As there are variations in Australia, a small number of the technical and further education colleges may be operating Web-based Education with the cost approaching zero. In general, the cost factor is there and the institutions are not fully virtual institutions of learning. This is shown as having 50% or less of the courses being taught fully via Web-based education. As compared to the school level, there is much more flexibility through time, place, and pace in learning. Of course, there are refined materials that are Web-based, both for sharing and for individual use. Interactive online multimedia delivery is possible in all the six polytechnics in Singapore although the degree of use may differ from one to another. There is a moderate degree of usage of computer-mediated communication and portal access at the polytechnics and technical and further education colleges. Table 1 also shows that the universities in both Singapore and Australia have achieved most of the characteristics defined by Generation 4 and 5 in Taylor’s model of Web-based education, with one particular exception. This exception is the “operational cost approaching zero.” In Singapore, the universities have either developed their own course management system or purchased licenses from developers of Blackboard or other platforms. Considering the use of manpower in development and the time needed for development, the cost is not negligible. However, it is cost effective if the university has developed its own platform such as the Integrated Virtual Learning Environment. Right now, the cost is far from approaching zero. Taking the cost factor away, it is fair to say that Web-based Education at the universities in both countries are actually in Generation 4 and 5 in Taylor’s model. However, in actual practice, not even 50% of the courses are totally Web-based. Therefore, Taylor’s model is only theoretical,

Diffusion of Web-Based Education in Singapore and Australia

and the actual situation of Web-based Education diffusion cannot be clearly shown. In this study, we go beyond this model and look at the actual practice of Web-based education. The second part of this analysis involves a closer look at what National University of Singapore and University of Southern Queensland have done to promote e-learning. These two institutions are chosen because of their advanced approach to Web-based Education. Comparing one institution in Singapore with a similar institution in Australia would help to illustrate the similarities and differences not included in a general comparison. As can been seen from Table 2, the University of Southern Queensland focuses on developing itself into an e-university, concentrating on three main areas: e-information repositories, e-applications, and the e-interface. The National University of Singapore focuses on developing an advanced integrated virtual learning environment with features increasingly catering to the needs of the students at the university. Main areas of interest include links with the outside world, library resources, and access to interactive lectures and tutorial materials. It has no intention of giving up its on-campus program. However, it aims at providing an equivalent quality of Webbased education for its on-campus students and its off-campus students (mainly local part-time students). It also has no intention of developing itself into an e-university. On the other hand, the University of Southern Queensland has developed its e-university where students learn and are supported through the innovative and strategic use of educational Web-based technologies that encourage e-world expertise. It has an online education arm, providing a good number of courses in almost all areas of learning, ranging from the awarding of a certificate to a master’s degree. Using the USQOnline (which is the Internet-based delivery mode that has been developed by the university as part of its commitment to provide quality flexible education, anywhere, anytime),

students from all over the world can register and receive an award from the University at a cost, ranging from AUD3000 to 15,000 (in 2001). USQOnline was developed for students who would like to enhance their career and/or attain university-accredited qualifications by study via the Internet. USQOnline is also a way for people all over the world in many different situations to continue their education and enhance their professional skills. There is no flexibility with regard to when to start a course or program. USQOnline offers three periods of study per year. Semester 1 commences in March, Semester 2 commences in July, and Semester 3 commences in November. The National University of Singapore has not used its integrated virtual learning environment online in the same way as USQOnline. Its main objective is to provide Web-based Education experiences for its local students, the main users being the professors and the students—definitely not for enrolling distance learning students from all over the world as USQOnline is doing now. Unlike the University of Southern Queensland, which is already operating an e-university within the main university, the National University of Singapore is still operating on a single arm, emphasizing traditional on-campus courses, using Web-based education applications, and convenience from the benefits of modern technology. Having compared the main areas with regard to Web-based education in these two universities, it is clear that in terms of Web-based Education diffusion, they have attained similar levels. They are both considered to be more advanced universities in the application of and approach to Web-based Education. In terms of usage, however, they are very different. In terms of using Webbased education in the truest sense of providing distance learning, the University of Southern Queensland has achieved that. The National University of Singapore has not, and is unlikely to do so in the near future. The integrated virtual

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Diffusion of Web-Based Education in Singapore and Australia

learning environment is an added advantage for its local students, both part-time and full-time. Using Web-based education to enhance learning, teaching, communication, resources, and other administrative work will continue to form the main focus of the National University of Singapore for the time being.

dIscussIon The Singapore situation is unique in the sense that the control and planning of Web-based education have been from top down, especially in the case of planning for Web-based education at the school level. Consistency was an important issue. The Ministry of Education has plans for all schools, and it makes sure that no school is disadvantaged. This approach has proved very successful in a small nation with a strong government. An interesting observation suggests that this top-down direction is strong, but it discourages private Web-based Education developments. Australia is not a small nation. Instead of consistency, there is a great deal of variation in Web-based education experimentation and practices at all levels of education. This is expected. The initiatives were from the institutions themselves or from the individual states or territories. As a small nation, Singapore is alert to world developments. The idea of developing its Information Technology infrastructure for the betterment of the whole nation came rather early. The concept of introducing Web-based education at different levels of education was just part of the main concern. Singapore is not behind the bigger nations, such as Australia, in its preparation and implementation of Web-based education. However, there are sizeable differences in the choices of Web-based education platform and development of Web-based education as a whole. With the National University of Singapore developing its Open Integrated Virtual Learning Environment,

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Singapore Polytechnic, its Virtual College, and Temasek Polytechnic, its Online Learning Environment, it does give us an impression that each institution in Singapore favors the development of its very own Web-based education platform instead of adopting one from somewhere else. And all of them chose to use Microsoft technology. An obvious advantage of developing one’s own platform is that it serves its own purpose. One can choose a cost-effective development method. The experience of developing is challenging and valuable. The product can also be sold to other interested institutions. It is not to say that Australian institutions of higher learning prefer adopting well-developed platforms such as WebCT, TopClass, or Blackboard. However, this study does suggest that WebCT, TopClass, or Blackboard have been adopted for use by some universities in Australia. Of course, there is a price to pay for using them as well, but it is simpler than developing one’s own. Perhaps, it is easier and faster to adopt Web-based Education by using developed and already tested platforms than having to develop one’s own in each university. There are also a number of online learning platforms being developed in Australian institutions such as USQonline, WestOne Online, TAFE South Australia Online, Queensland Open Learning Network, TAFE Online Queensland, and so on. Their purposes range from offering online courses for adult students to just promoting and supporting online delivery for everyone involved in training, including private companies. A number of Australian universities have their bases in Singapore and other countries. However, Singapore universities do not have bases in other countries. Therefore, Web-based Education platforms in Singapore universities mainly serve their own local students. Those Australian universities with bases in other countries are using Web-based education to revamp their distance education arm from traditional correspondence methods to totally e-learning environments.

Diffusion of Web-Based Education in Singapore and Australia

The situation of Web-based education diffusion at school level in Australia is unclear. Unlike the Singapore schools, there is no central agency to plan and implement Web-based Education in the schools nationwide. As a result, pockets of schools with well-developed Web-based education may exist side-by-side with schools that have little or no usage of Web-based education. Unless a thorough study covering all schools in the entire country is done, there are not many ways we can compare schools. Which is better, a consistent development of Web-based education in all schools or letting each school choose whether or not to introduce Web-based education? This comparative study indicates that even with a central agency to overlook this matter, schools in Singapore are at different levels of using Web-based Education. One thing for sure is that Web-based Education is planned to supplement the school curriculum, not to replace face-to-face learning. All students are required to physically attend school, and the teachers still teach in a classroom environment, whether using Web-based materials or not. Full technology adoption (the virtual university) has not happened in Singapore yet. Perhaps it will, but not in the near future. Considering the distance learning experience of some of the universities in Australia, it appears that the virtual university will become a common thing in the future. While the successful top-down approach in Singapore may provide lessons to learn for other nations, the top-down direction is found to be minimal or non-existent in Australia.

concLusIon This study leads us to conclude that though Singapore has never been known as an advanced country like the United States, Australia, Canada, or the UK, it has embraced Web-based Education as quickly as these countries. Today, Web-based Education is playing an increasingly important

role in all levels of education. The consistency of the development in line with government policies suggests that all students in Singapore have a chance to use Web-based resources in the school and to experience the nature of Web-based Education, with the guidance from the teacher. All students at the polytechnics or the universities have the same opportunity to use Web-based Education as a student at a similar level of education in an advanced country. It also leads to the conclusion that, because of the size of Australia and therefore the greater variation in the development of Webbased Education in Australia, not all children at primary level would have a chance to participate in Web-based Education as he/she would like to. The opportunity definitely increases as one advances up the ladder in education. All university students should have opportunities for Web-based learning in one way or another. The broader picture suggests that virtual or e-university is in the making in Australia. It is not in Singapore.

reFerences Aggarwal, A. (2000). Web-based learning and teaching technologies: Opportunities and challenges. Hershey, PA: Idea Group Publishing. Khan, B. H. (1997). Web-based instruction. Englewood Cliffs, NJ: Educational Technology Publications. Moore, M.G. & Cozine, G.T. (2000). Web-based communications, the Internet and Distance Education. Readings in Distance Education Series, No. 7. University Park, PA: American Center for the Study of Distance Education. Tan, F., Corbett, P.S, & Wong, Y.Y. (1999). Information technology diffusion in the Asia Pacific: Perspectives on policy, electronic commerce and education. Hershey, PA: Idea Group Publishing.

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Taylor, J. (2001). Fifth generation distance education. Higher Education Series, Report No.40. Department of Education, Training and Youth Affairs, Canberra, AU. Taylor, J., Kemp, J., & Burgess, J. (1993). Mixedmode approaches to industry training: Staff attitudes and cost effectiveness. Report to the Department of Employment, Education and Training’s Evaluations and Investigations Program. Canberra, AU. Web-based Education Commission (2000). The power of the Internet for learning: Moving from promise to practice. Report of the Web-based Education Commission to the President and Congress of the United States.

web REsources A guide to Singapore Official Statistics. http:// www.Singstat.gov.sg. Ministry of Education. Launch of Masterplan for IT in Education, 28 Apr 1997, http://www. moe.edu.sg Nanyang Technological University. http://www. ntu.edu.sg National University of Singapore. http://www. nus.edu.sg Singapore Government Directory. http://www. gov.sg Singapore Polytechnic. http://www.sp.edu.sg Temasek Polytechnic. http://www.tp.edu.sg

This work was previously published in the Encyclopedia of Distance Learning, Vol. 2, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 573-580, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.35

Effective Technology-Mediated Education for Adult Chinese Learners Hsianghoo Steve Ching City University of Hong Kong, Hong Kong Carmel McNaught The Chinese University of Hong Kong, Hong Kong Paul W.T. Poon University Librarian, University of Macau, Macau, China

IntroductIon This chapter will address several areas relating to online learning and technology. We will report on work done in the development of four models that have been used to deliver effective professional development for adult learners. The courses are run in Taiwan from a base at Feng Chia University in Taichung, and all the attendees are Chinese. The key content is developed by instructors who are all native speakers of English from a range of countries. Some of this key content is delivered face-to-face and some is delivered virtually. Course facilitators are experienced in online learning and are Chinese. Our models thus utilize both internationally known teachers and

local expertise. In addressing the training and education development needs of adult learners in a Chinese context, we needed to consider and accommodate three types of challenges: • • •

Constraints and demands on busy adult learners Challenges of second language learning Use of technology-mediated distance education

Each of these areas is challenging and complex in its own right. Many of the contributions in this encyclopedia will address one or more of these areas in some depth. This chapter should be considered as complementary to those focused

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Effective Technology-Mediated Education for Adult Chinese Learners

contributions. Our globalized world is complex and multi-faceted, and this chapter attempts to show how the application of knowledge and experience in several areas can be combined.

bAcKground Adult second Language Learners There is a vast literature on adult education. Recurring themes in this literature are that adult learners are often more motivated than younger learners and come to a specific educational program with relatively clear goals in mind. They can also often relate course material to their own work settings and thus internalize and adapt knowledge in a way that can be immediately useful in the workplace. However, there are several problems that adult learners face. These include the need to juggle time constraints so that the demands of the educational program can be fitted into busy professional lives and family commitments. Adult learners, even those in senior positions, may no longer be accustomed to the discipline of structured educational offerings; many comment that it has been a long time since they were on the “education conveyor belt.” Finally, when technology is involved, many adult learners have lower levels of confidence in becoming accustomed to and using online forums and Internet searching. All these factors are well documented, for example, in Jarvis (1995) and Galbraith, Sisco, and Guglielmino (1997). The adult learner who is working in a second language faces additional challenges. Spack and Zamel (1998) argue that the conventions, concepts, and terms that a teacher uses in any classroom creates a unique subculture, and successful learners are those who learn to read and interpret this culture. If the language nuances are not understood, it is very difficult for learners to work effectively. The level of English in Taiwan is not high (Yiu, 2003), and so this challenge

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needed special attention in the design of courses. Contributors to Duke (1987) echo this need and provide some local examples of successful practice in China. These examples all highlight the need for building flexibility into the design of educational programs so that the needs of individual learners can be met; in the language of constructivism, so that there is adequate scaffolding for all learners. These learning needs include both linguistic and cultural factors that are often difficult to define a priori; hence, the need for ongoing facilitation and negotiation. Chang’s (2004) study of different strategies adopted by adult education trainers in the United States and in Taiwan clearly demonstrates the primacy of the factor of cultural negotiation.

ensuring that technology Facilitates Learning It is quite curious that early Web-based teaching appeared to be regressive in that the drive to put materials “on the Web” led to a didactic environment. However, we seem to be moving out of this phase now and the communicative power of the Web has come to the fore. There are excellent guides available now about how to support elearners in communicating online and developing meaningful online communities. The five-stage model of Salmon (2004) is useful in this regard. She discusses the importance of first ensuring good connectivity and motivation, then setting up online socialization, before there is any real academic information exchange or knowledge construction that might lead to more permanent ongoing development. Mature designs for online learning make use of the multiple functions of the Web and the art lies in using an appropriate mix. McNaught (2002) matches common online facilities such as forums, quizzes, upload areas, and the like to the four major functions of communicative interaction, conducting assessment and providing feedback to learners, supporting progress through a formal program of

Effective Technology-Mediated Education for Adult Chinese Learners

Table 1. Models for technology-mediated education for adult Chinese learners Model 1

Development of key content Developed by international instructors in English. These instructors act as resource experts at a distance.

2

Developed by international instructors in English who come to Taiwan for face-to-face (F2F) classes

3

Developed mostly by international teachers in English. Saved digitally for use by local instructors. Some guest speakers come to Taiwan.

4

The development of eLearning course materials into a repository that can be produced on demand. Here there is a key role for the Library in the management and coordination of the course materials production. Constant revision and updating is also an important component. This is an adaptation of the concept of just-in-time course development and delivery-ondemand in a variety of formats (print, CD, online).

Facilitation of learning Two tiers of local facilitators, one group working in Chinese and one group working bilingually. Complex questions are fed back to the international instructor as needed. Less reliance on the formal tiered system as there has been bilingual facilitation in the F2F classes. The role of the local facilitators is to bridge the gap between international theory and practice and local institutional environments. The nature of the F2F classes change with the possibility of more Chinese explanations being available for difficult English material when the local instructors are teaching. The design of each course can be customized to the group of learners. The mix of virtual modules, local instructor-led F2F classes, and international guest speakers can vary as needed.

study, and providing resources for students to use. Alexander (2001) comments that such attention to detailed design must also take into account teachers’ pedagogical beliefs and the nature of the student population. So, again, we highlight the need to have flexible, adaptable models and designs (Blass & Davis, 2003). As noted earlier, adult learners may find online learning more daunting than younger learners (Cahoon, 1998) and so the need for careful, supportive, flexible designs is even more important.

the Four ModeLs These four models have all been used in Taiwan in various professional development courses for adult learners. They are summarized in Table 1.

Use of technology 100% online. These are called eWorkshops. See Figure 1.

F2F supplemented with the use of a learning management system (LMS). See Figure 2.

F2F supplemented with the use of a learning management system (LMS). More F2F than in model 2. See Figure 3. Materials incorporated into an LMS. Balance of F2F and LMS as appropriate. This model enables a flexible blended use of technology. See Figure 4.

Model 1 Model 1 was developed during the time of the Severe Acute Respiratory Syndrome (SARS) outbreak in the first half of 2003 and was used by 180 participants learning about e-learning management and design (Ching, Poon, & McNaught, 2003). These virtual e-workshops were developed rapidly, to replace a face-to-face international conference that had to be postponed because of the SARS epidemic. It was gratifying that the whole process ran so smoothly. The seven international instructors from Australia, Hong Kong, New Zealand, and the United States produced course packs that included narrated presentations and a course reader in English. The tiered support system used for the online discussions involved a Chinese-intensive discussion at the first level, 2217

Effective Technology-Mediated Education for Adult Chinese Learners

Figure 1. Architecture of eWorkshops (Model 1) INSTRUCTOR

Asynchronous Q&A (academic Qs)

FACILITATOR

Interactive

* Learning guidance * Assess & evaluate

*Prepare course materials * Answer key questions

Forward academic Qs Progress report & support

GROUP 1 heterogeneous grouping Cooperative learning Peer discussion; intra- & inter-groups

Reply to Qs Request support

LEARNER 1 LEARNER N

Asynchronous Q&A (administrative Qs)

Provide course materials

LEARNER 40

TUTOR * Learning progress control * Learning support

Provide course pack

240 participants in 6 groups of 40

Email Communication channels

Telephone Asynchronous learning environment using a LMS

Global (English)

Local (Chinese & English)

Figure 2. Model 2

International instructors

Share

•Draw on international literature and models

•Development course materials and suggest broad lines of inquiry

F2F (classroom)

Apply knowledge Integrate with prior knowledge Accept new knowledge Compare new knowledge

Local Facilitators

•

Focus on local problems and depth of understanding

•Sustain increasingly advanced inquiry •Ensure the group is working at the forefront

of their collective understanding

•Assess learners’ learning performance

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Asynchronous Q&A, online discussion forum

Structured representation Source

Learners’ Knowledge building

Effective Technology-Mediated Education for Adult Chinese Learners

Figure 3. Model 3 week1 week2 week3… F2F

F2F

F2F

week12 week13…….week17 week18 DE+F2F

DE+F2F

F2F

Learners

F2F

International instructors

Local Instructors

Figure 4. Model 4

Course materials development

Library eLearning support team

Educational service to enable sharing and reuse of materials

Design, Edit, Copyright

external subject experts

Information service: Publication of course materials, versioning by format, content, medium

Academic review

with questions being referred to more experienced online facilitators with good bilingual skills. If necessary, the questions could be translated into English and sent to the international instructors. The data from the evaluation of these eWorkshops is reported in Ching, Poon, and McNaught (2003) and is summarized briefly in Table 2.

Flexibly designed modules and courses

subject experts

Model 2 Model 2 was used in the period February to May 2004 for a three-credit postgraduate- level certificate course with 50 participants also learning about e-learning management and design. A sandwich arrangement was used, with two modules being run as full-weekend intensive sessions followed by a month of online activity, then two more weekends of more advanced modules and

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Effective Technology-Mediated Education for Adult Chinese Learners

Table 2. Successes and challenges from the use of Model 1 during the time of SARS Key Successes Participants found the eWorkshops interesting, attractive and relevant. There was a synergy between the eLearning administrative and strategic research group, the learning support team, and the technical support team.

This model is relatively cost effective Participants from all over Taiwan have successfully cultivated a sense of community by learning through LMS. A pool of participants’ contributions was built up that can be shared with peers or other interested persons to stimulate scholarly thought.

another month of online activity which, at the time of writing, is just concluding. Midway through the course an evaluation was carried out. The richness of the face-to-face weekends has been appreciated. But it has been hard to sustain the “high” of these weekends into the forums. Many of the participants have very senior posts in Taiwan and a sustained commitment to online discussion has been very hard to maintain. It is interesting that the online activity level during the SARS eWorkshops was quite high. Maybe isolation has its advantages! Also, the time of the SARS outbreak was a time of heightened awareness of the benefits of technology, and the commitment to using technology was high (McNaught, 2004). It has been valuable for the Taiwanese team planning professional development for e-learning to have the experience of these two models in action and become aware of how societal dynamics impact the success of the implementation of a model.

Model 3 Model 3 has been used in teaching different topics than e-learning. One example is a graduate-level

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Key Challenges or Ideas for Improvement More case studies using a variety of media in the eWorkshops and more thought into the design of discussion questions would be enhancements. Despite the success, a more continuous monitoring and reporting system is needed to assist with both administrative issues such as scheduling, and technical hardware and software problems. A Frequently Asked Questions (FAQs) section on the Web site would be useful. Eventually, the interaction between participants and facilitators needs more attention if the model is to be truly effective. Time for study was a key challenge for these learners. Several participants did not contribute their own thoughts in the forum.

course on local economic development run for 18 students in 2003 by the College of Construction and Development at Feng Chia University. The intensive teaching by the international instructor occurred over a two-week period in June. She had prepared the course materials in the United States and sent a CD to Taiwan. She was then available online during that time. Local instructors used the LMS to facilitate students’ learning by narrowing the gaps of language, culture, and institutional difference between the United States and Taiwan. The face-to-face component was an off-campus learning and field trip that tested the U.S. principles in a Taiwanese context. This use of an international instructor is more cost-effective when long distances are involved. Another example of Model 3 where the international instructor came to Taiwan is a module on population and development in East Asia that ran in the Spring semester of 2003 with 48 students. The international instructor works in Hong Kong. He prepared the course materials in Hong Kong and then came to Taiwan to present his lectures, which were recorded. He also discussed the operational issues of the online course with the

Effective Technology-Mediated Education for Adult Chinese Learners

local instructor. When travel costs are low, the dual benefit of having the international instructor present in Taiwan and also having a full set of course materials can be achieved. The final example of Model 3 highlights the need to maximize the value of international instructors who have skills that are rare in a particular country. There is no law librarian at all at Feng Chia University and, consequently, there has never been an information literacy course unit specializing in law. A module on law library research in comparative and international law has been developed in a similar way to the previous example, except that in this case the international instructor from Hong Kong also trained the reference librarian at Feng Chia University so that she could run the course again using the recorded lectures and other course materials developed by the international instructor. In all the three models presented above, a growing number of courseware modules now exist in Taiwan. Provided the quality of production is adequate, it doesn’t matter whether the production of course materials occurs overseas (Models 1 and 2 and first example of Model 3) or in Taiwan (second and third examples of Model 3). This growing repository of materials has led quite naturally to the development of Model 4, which we believe represents a more pragmatic and cost-effective use of local and global expertise.

Future trends Model 4 We believe that Model 4 represents the model of the future. The e-learning infrastructure for Model 4 is the same as for the other models. The initial development of new modules for the repository is a partnership between an academic department and the Feng Chia University Library. The design of the course and payment for any local or international instructors resides with the academic

department, as does the costs of any copyright clearance. Rules for instructional design, copyright advice, and suggested publishing plans are given to the department. The actual materials production and continued management of the materials occurs in the Library. The publisher is the FCU e-press. An example that shows the potential for reuse of this model is the topic of economic development in Greater China. This topic, which is in line with the strategic focus of Feng Chia University, has been explored in a regular focus forum for some time in the College of Business with various invited speakers whose presentations have been recorded and who have been generous with providing suitable readings. The materials have been packaged so that they can be reused in modules for the American Institute in Taiwan training professional U.S. ambassadors coming to work in China. There is a potential for sales in this case to other businesses or political parties interested in this topic. The reuse of materials produced under Model 4 requires careful instructional design so that the resources are tied to suitable discussion questions and tasks for the participants in the educational program. Also, an appropriate use of facilitators working in both Chinese and English needs to be included in the plan. Reuse often fails when the resource materials are not embedded in an appropriately designed learning environment (Littlejohn, 2003). Tu and Twu (2002) noted that a lecture-oriented mode of distance education has been dominant in Taiwan. The integration of skilled facilitators as a key element in all the four models is a move to address this situation.

AcKnowLedgMent The authors would like to thank the Taiwan Ministry of Education and Feng Chia University, Taiwan, for their sponsorship of the project undertaken by Development of International Research Center for e-Learning and Digital

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Content Strategic Management, which resulted in the development of the four models delineated in this paper.

concLusIon In this chapter we have tried to show that there is a diversity of models that might be of use in developing educational offerings for adult learners in a bilingual environment. Trying to get the right balance across all three areas of technology use, culture and life style demands of the learners, and language levels and needs has been a truly fascinating challenge. We feel that the multi-faceted nature of our models may well be of value to colleagues working in a range of transnational educational ventures in this globalized world.

reFerences Alexander, S. (2001). E-learning developments and experiences. Education + Training, 43(4-5): 240-248. Blass, E. & Davis, A. (2003). Building on solid foundations: Establishing criteria for e-learning development. Journal of Further and Higher Education 27(3): 227-245. Cahoon, B. (Ed.) (1998). Adult learning and the Internet. San Francisco, CA: Jossey-Bass Publishers. Chang W.-W. (2004). A cross-cultural case study of a multinational training program in the United States and Taiwan. Adult Education Quarterly, 54(3): 174-192. Ching, H. S., Poon, P. W. T., & McNaught, C. (2003). Virtual workshops of distance learning: Practising what we preach. International Journal of Distance Education Technologies, 2(1): ii-v.

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Duke, C. (Ed.) (1987). Adult education: International perspectives from China. London: Croom Helm. Galbraith, M. W., Sisco, B. R., & Guglielmino, L. M. (1997). Administering successful programs for adults: Promoting excellence in adult, community, and continuing education. Malabar, FL.: Krieger Publishing. Jarvis, P. (1995). Adult and continuing education: Theory and practice (2nd ed.). London: Routledge. Littlejohn, A. (Ed.) (2003). Reusing online resources: A sustainable approach to eLearning. London: Kogan Page. McNaught, C. (2002). Adopting technology should mean adapting it to meet learning needs. On The Horizon, 10(4), 14-18. McNaught, C. (2004). Using narrative to understand the convergence of distance and campusbased learning during the time of SARS in Hong Kong. Educational Media International, 41(3), 183-193. Salmon, G. (2004). E-moderating: The key to teaching and learning online (2nd ed.). London: RoutledgeFalmer. Spack, R., & Zamel, V. (Eds.). (1998). Negotiating academic literacies: Teaching and learning across languages and cultures. Mahwah, NJ: Lawrence Erlbaum Associates. Tu, C., & Twu, H. (2002). The transformation, reform, and prospect of distance education in Taiwan. In Proceedings of the Society for Information Technology and Teacher Education International Conference 2002(1) (pp. 2461-2465). Norfolk, VA: Association for the Advancement of Computers in Education (AACE). Yiu, C. (2003). Taiwanese students’ English disappoints. Taipei Times, Friday, 7 November, 2.

Effective Technology-Mediated Education for Adult Chinese Learners

Key terMs Adult Education: This term is used to show awareness of the reality that many adults come to formal educational programs with different orientations to study, motivations, and prior experiences from younger learners. These differences need to be accommodated in the learning designs used. Bilingual Learning Environments: Learning contexts where two languages are needed. Often this is because the course content is in English but the learners are not fluent in English. Discussion and exploration of meaning occurs in a language other than English. Translation is needed before questions can be asked of any international instructors (see below) involved in the teaching. Bilingual Learning Facilitators: Tutors and local instructors whose first language is the same as the learners, but who are reasonably fluent in English as well, and also familiar with the content domain. These facilitators have a major role in bridging the gap between the international instructors and the local learners. E-Press: A publishing service with a strong emphasis on the publishing of digital courseware. This does not mean that print and traditional media, such as film, are not used. However, the courseware packs are predominantly electronic.

International Instructors: In many regions of Asia and Africa, professional development programs rely on expertise from elsewhere in the world, and there is heavy use of experienced invited speakers. Increasingly, these invited speakers provide electronic resources and also teach online. They may even do all of their teaching in an online mode. These invited teachers, many of whom teach in English, are described as international instructors. Technology-Mediated Distance Education: In many distance education programs, technology has assumed a central role. As in any educational situation, the relationships of significance are between teachers and students. The use of technology can facilitate or mediate this relationship. In this sense, technology provides strategies to bridge the gap between, or bring closer, teachers and learners. Transnational Education (TNE): This term has arisen to describe the type of educational program that involves organizers, and usually teachers, from more than one country. The phenomenon is not new, but the rapid growth of TNE and the financial and cultural implications for educational institutions and teachers in both countries are significant. There are many arrangements that TNE can take, a few of which are described in this chapter.

This work was previously published in the Encyclopedia of Distance Learning, Vol. 2, edited by C. Howard, J. Boettcher, L. Justice, K. Schenk, P.L. Rogers, and G.A. Berg, pp. 724-731, copyright 2005 by Idea Group Reference (an imprint of IGI Global).

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Chapter 4.36

Integrating Writing into IT/MIS Courses Jeffrey W. Merhout Miami University, USA Stephanie J. Etter Aloysius College, USA

AbstrAct As popular literature claims that college graduates are entering the workforce lacking sufficient writing skills, this chapter argues that the integration of writing into the MIS/IT curriculum is an important and achievable goal necessary for the overall development of students in information technology or management information systems degree programs. While traditional IT/MIS programs rely heavily on technology-based courses, it is argued that these technology courses also must promote effective writing habits needed for career growth in the IT/MIS fields. By providing examples of writing assignments currently used in several programs, this chapter illustrates for all educators in an IT or MIS program how writing assignments can be used in most MIS/IT classes. Research papers, journaling, written exams, and micro-themed papers are some of the current

methods used to incorporate writing into the IT/MIS curriculum.

IntroductIon The intended outcomes of traditional information technology (IT) and management information systems (MIS) programs in higher education are multi-faceted. IT/MIS students are expected to excel in mastering topics such as hardware, software, communication technologies, programming languages, and database management. However, the IT/MIS curriculum often is focused so intently on technology that students may fulfill degree requirements without fully learning other skills essential to successful career development. In an era of extremely competitive job markets and high unemployment rates, IT/MIS students need to graduate with skills that will provide for suc-

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Integrating Writing into IT/MIS Courses

cess in whatever paths their careers may take. In order to accomplish this task, educators should strive to help develop IT/MIS students from a liberal education standpoint. The purpose of this chapter is to argue that integrating writing into the IT/MIS curriculum is an important and achievable goal for the further development of our students and, more specifically, to illustrate how writing can be incorporated into IT/MIS courses at both the undergraduate and graduate levels. While much of the following discussion may be culturally specific to Western societies and principally to the United States (Fox, 1994), educators in any country who are interested in developing well-rounded graduates may benefit from this chapter.

IMPortAnce oF wrItIng Countless educators lament that many (or most) students cannot express themselves well (Bean, 2001; Epstein, 1999; Plutsky & Wilson, 2001), and this phenomenon threatens a nation’s ability to develop citizens who can fully participate in political and economic processes. Moreover, when one cannot write well, it is often a symptom of a failure to think critically, which can be more damaging than just a lack of communication skills, especially for IT workers. The decline in the communication skills of college students is perhaps the best argument for including writing requirements in courses that traditionally do not have a writing component, such as those found in IT/MIS curricula. In a 2003 survey, employers in the U.S. reported that many college students graduate without the communication and writing skills necessary to succeed in the workplace (Malveaux, 2003). This problem is not specific to the U.S., however, as employers in the UK are also reporting a shortage of fundamental skills in job seekers who are recent graduates, specifically in the areas of communication and problem-solving abilities (Parrish, 1998).

As many U.S. degree programs require only one or two composition courses, it is assumed that the skills learned in these courses are not sufficient to provide students with appropriate speaking and writing skills. Some institutions still count solely on language (e.g., English) or communications courses as the only sources for developing effective writing and speaking skills, part of a discipline-by-discipline approach in which courses rarely cover concepts outside of a specific discipline. Many institutions, however, are breaking this discipline-by-discipline tradition by incorporating programs known in the U.S. as “writing-across-the-curriculum” and in Canada and Great Britain as “language-acrossthe curriculum.” Writing-across-the-curriculum calls for the inclusion of writing requirements in courses throughout a student’s college curriculum (Bean, 2001). Carnes, Jennings, Vice, and Wiedmaier (2001) further explain that a writing-across-the-curriculum program “enables faculty of non-communication disciplines to build on the writing skills taught in communication courses, provides students with the opportunity to strengthen and reinforce communication skills and encourages consistency in communication training and assessment” (p. 1). Moreover, this movement argues that the development of writing competence is a shared responsibility between the various disciplines and the language departments within a college or university (Tynjala, Mason & Lonka, 2001; Weimer, 2001). We believe that those responsible for educating tomorrow’s information resources managers should share in the development of these future leaders’ writing and critical thinking abilities by incorporating writing requirements throughout MIS/IT curriculums. This argument is supported by Nelson (1992), who contends that the development of key learning skills, including critical thinking and problem-solving abilities, is imperative in order for technical workers to keep up with rapid technological innovations.

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Integrating Writing into IT/MIS Courses

Bean (2001) argues that writing is a key way to develop critical thinking abilities and problemsolving skills and notes that “integrating writing and other critical thinking activities into a course increases students’ learning while teaching them thinking skills for posing questions, proposing hypotheses, gathering and analyzing data, and making arguments” (p. 1). Tynjala et al. (2001) argue that “[w]riting is a tool for thinking and a tool for learning” (p. 17). Bonwell and Eison (1991) add that informal in-class writing exercises, which can even be used in large class sections, can assist in student acquisition of course content. Hence, an argument can be made that improving an MIS student’s writing abilities by requiring and guiding written assignments can enhance his or her communication skills and critical thinking abilities while simultaneously assisting in the acquisition of the key concepts of a given course.

chALLenges oF IMPLeMentIng wrItIng In the It/MIs currIcuLuM Implementing writing into any curriculum not traditionally considered to be writing-intensive can be difficult on several levels. A 2001 study by Plutsky and Wilson (2001) found that faculty members were especially concerned with their ability to provide appropriate feedback for writing and grammar. According to Bean (2001), in addition to feeling that their own writing skills are inadequate to provide appropriate feedback, faculty members may hold other misconceptions about incorporating writing assignments, including the idea that time is taken away from coverage of content, that writing assignments are not appropriate for certain types of courses, and that writing assignments will bury the instructor in paper grading. The challenges of incorporating writing into IT/MIS curriculums may also include, as Bean discusses, designing problemoriented assignments, coaching students to be

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better writers and critical thinkers, commenting on and grading assignments, and dealing with grammar and sentence correctness. In order to maximize the effectiveness of writing assignments, instructors must carefully design problem-based assignments that generate in-depth analysis of the course content and develop critical thinking skills while creating a finished product that can be fairly graded in a manageable fashion. Carnes et al. (2001) present a checklist for creating writing assignments: carefully planning the assignment and grading criteria; detailing the assignment in writing; explaining the grading criteria, preferably with a checklist; stating the details of when the assignment is due and in what format; providing opportunities for interim feedback; and using a detailed evaluation sheet that is very similar to the assignment grading criteria checklist. Gelinas, Rama, and Skelton (1997) echo the importance of careful planning by identifying three critical planning decisions for integrating writing- across-the-curriculum programs: defining measurements of quality for student writing, selecting forms of communication appropriate for the discipline, and selecting the appropriate mix of communication skills to teach in class. Bean (2001) discusses the significance of coaching the writing process, of writing appropriate comments on papers (e.g., positive feedback whenever possible), and of explicating and adhering to detailed grading criteria. The goal in coaching the writing process is to efficiently assist in the development of students’ writing abilities by guiding the process without becoming overly burdened by grading requirements. Bean (2001) notes the traditional means of coaching writing by making “copious, red-penciled comments on finished student products [is] almost universally regarded among composition specialists as an inefficient use of teacher energy” (p. 237). Rather, the instructor should identify potential problem writers as early in the process as possible by having them submit early drafts to peers and/or to the

Integrating Writing into IT/MIS Courses

Table 1. Grading rubric Requirement The problem statement is well developed, and the problem is significant. The thesis statement is clear and succinct. Evidence to support the thesis statement is relevant and strong. The paper makes a contribution. Arguments are logical. Ideas are well developed and logically arranged. There are smooth transitions between sections, between paragraphs, and between sentences. The voice, tone, and style are appropriate for the assignment. Sentences are grammatically correct with zero misspelled words. Appropriate use and explanation of acronyms and abbreviations. Peer review comments are attended to and/or responded to in a separate paper.

instructor for feedback. Another idea in guiding the process is to refer students to a university writing center, assuming one exists. Once the writing process is near completion, the instructor can make high-level comments that require revision for a final draft. After receiving the final draft, the instructor should make minimal comments, as it is unlikely students will benefit from this unless they are required to make revisions. Instead of making detailed notes on the paper to justify a grade, an instructor should use a grading or scoring scale, often called a scoring or assessment rubric, preferably based on the same scale that was presented to the student at the beginning of the assignment as criteria for evaluating the student’s work. An example of a rubric used to score a research paper for an MIS course is provided in Table 1.

exAMPLes oF It/MIs wrItIng AssIgnMents Bean (2001) classifies writing assignments as formal or informal exploratory assignments. The use of informal assignments, such as inclass writing, journals, reading logs, creativity exercises, practice essay exams, early drafts of

YES

NO M

aybe

essays, and memos to oneself (e.g., to explain a process), can serve as a writing component in any course without burdening the instructor with a heavy grading requirement. The goal of these assignments is to get the student thinking about the key concepts of the course. Bean (2001) argues that “exploratory writing, focusing on the process rather than the product of thinking, deepens most students’ engagement with course materials while enhancing learning and developing critical thinking” (p. 118). Informal writing assignments also have a place in the IT/MIS curriculum, such as five-minute essays at the end of class that ask students to sum up the key points of the class in relation to another topic (e.g., a current event or their future career plans). Brief writing assignments during class time are one way to engage students in an active manner and seem to be appropriate for all types of courses, including those in IT education. For example, when teaching data modeling, we require our students to think about and summarize their thoughts on the process of creating a well-designed data model rather than just grading their finished product (i.e., their entity relationship model). The purpose of such an assignment is to help the student realize that data modeling is a creative process that often requires iteration and that the

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Integrating Writing into IT/MIS Courses

finished product should constantly be challenged as to its robustness. Even if an individual student did not actually make these exact points, an ensuing class discussion, perhaps in lieu of grading the student’s writing, could help the student to understand that data modeling is just as much a process as it is an end product. Formal writing assignments include short write-to-learn assignments (also called microthemes), thesis-based term papers, formal exploratory essays, reflection papers, essay questions on exams, and a variety of other assignments that can be tailored to specific disciplines, such as poetry in psychology or creating word problems for mathematics class (Bean, 2001). Microthemes can be an effective way to assess how well the class as a whole is learning (or not learning) the key conceptual material in a course. Bean provides an example of a psychology professor presenting a scenario of cats reacting to being fed and then asking students to write an essay where the student applies several behavioral theories from psychology to explain the scene. Similarly, in a database course, we could ask our students to critique a database design that has several faults, such as not being properly normalized and/or omitting relationships between entities that would be needed to facilitate certain key queries. Thesis-based term papers are very appropriate for MIS courses that survey the various information technologies and discuss the implications of these technologies from different perspectives, such as from a strategic, managerial, and organizational impact standpoint. In thesis-driven papers, the thesis is usually presented near the beginning of the paper, where the purpose of the remainder of the essay is to present appropriate evidence and make persuasive (i.e., logical) arguments in support of the thesis. Assignments requiring a thesis are usually superior to simply asking students to write about a general topic appropriate for the class. Such a general course-related assignment likely would not require the student to develop the deep analysis and synthesis that is normally the

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product of effectively developing and defending a specific thesis about a topic. An example of a thesis-governed assignment used in a graduate course will be presented in the next section of this chapter. Adding writing to the IT/MIS curriculum also may include using writing during exams. The addition of essay or short answer questions to exams in the IT/MIS curriculum serves several purposes. First, it breaks up the cycle of rote memorization often required for successful completion of a multiple choice exam, a very common exam method used in IT related courses. Second, it allows the instructor to see if students really have an understanding of the material or if they have simply memorized the notes for the exam. Bloom, Englehart, Furst, Hill, and Krathwohl’s (1956) well known taxonomy of learning (knowledge, comprehension, application, analysis, synthesis, and evaluation) proposes that different levels of understanding can be achieved across subject areas. Short-answer or essay exam questions require higher levels of organizational skills to frame cogent answers, higher levels of recall about the subject matters, more integrative knowledge, and, of course, good writing skills (Zeidner, 1987). While an exam entirely made of short-answer or essay questions may not be considered practical, combining the common methods of multiple choice and true/false questions with one or two essay questions, may not only help to evolve the communication skills of the student, but it also may help the instructor to evaluate the course by determining whether or not the student can actually synthesize working, productive output from the material provided in the course.

detAILed exAMPLes oF wrItIng AssIgnMents For the purposes of providing more specific examples of writing assignments incorporated into IT/MIS courses, this chapter describes as-

Integrating Writing into IT/MIS Courses

signments used in two postsecondary schools located in Ohio and Pennsylvania. In MIS survey courses offered at both the undergraduate and MBA-level, a semester term paper has proven to be a successful writing assignment. For undergraduate systems analysis and database courses, a semester group project with a final report writeup has been required. In some cases, more than one writing assignment is appropriate. For example, a semester group project report and an individual term paper were both required in a graduate-level database course. An example of a writing assignment currently used in an undergraduate database course is a short event summary paper. The objectives of the short paper are to give the students more practice in writing, in critiquing their peers’ writing and to encourage their participation in extracurricular activities. Students are required to attend at least one of the many outside speaker presentations sponsored by the Miami University School of Business during a semester. While many of these events have very informative speakers, the sessions are sometimes sparsely attended. Requiring students to attend one of these educational events and to write about their experience is intended to assist in their overall personal development. Students then write a short 300- to 400-word review of the event attended, including a synopsis of the presentation, an analysis of the speaker’s thesis, and a personal reflection about how the speaker’s topic was relevant to their IT/MIS education. Moreover, an ancillary goal is that some students will become enlightened enough by these presentations that they will plan to attend more outside speaker events in the future. Another example of a writing assignment in an undergraduate database course is a semester group project report. The objective of this assignment is to require the students to think about the business purpose for investing in data management systems and to consider the organizational context of the problem domain for which they are designing a database. Students in the course are

given explicit guidelines for the types of issues they must discuss and have a significant amount deducted off their project grade if they fail to address this requirement. While the main focus of their semester project is to properly design an effective relational database, this requirement forces them to think about how communications are part of every systems development project. One of the drawbacks that is realized up front is that this written part of the project package, which will also include items like data models and query results, likely will be composed by only one (or maybe a couple) of the team members. Hence, the entire group also is required to present its project to the class, which requires, at minimum, that each student practice his or her oral communication skills In a graduate program, it is often much easier to incorporate written assignments into the curriculum, as many students now have industry experience and are aware of the communication skills needed to succeed in the workplace. A research paper assignment has been used successfully in a graduate-level IT management course. The objective of the paper is to require students to research an appropriate IT topic over and beyond what is covered in their textbook and in class in order to focus on the strategic, managerial, organizational, and social implications of investments in IT. These analytical components of the paper, when outlined at the beginning of the assignment, can be used as part of a grading rubric (as discussed earlier) in addition to items such as a clearly defined thesis and argument. The requirement of a thesis will force the student to think in terms of organizational problems and research questions rather than just creating a “data dump” (Bean, 2001, p. 90). In essence, this format requires deep analysis and synthesis, the type of higher-order thinking instructors should strive for in all IT/MIS courses. In addition to a thesis, the assignment requires a sequence of deliverables that forces students to work on the paper throughout the entire term.

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Integrating Writing into IT/MIS Courses

The first deliverable is to propose a topic and problem statement early in the semester, which includes a discussion of the process of how they formulated their problem statement. Requiring students to write about how they formed their problem statements will force them to think about the development of a problem statement as process rather than as a finished product. Moreover, it provides feedback so the instructor can guide and coach problem development as a process of asking researchable questions. It also may help to prevent or deter plagiarism, because the student will not be able to simply borrow or purchase (e.g., copy and paste from the Internet) a problem statement. The instructor then reviews the work and makes detailed, written comments about the topic and problem statement, which are then resubmitted with all subsequent submissions. The second deliverable due around mid-semester requires an informal outline, a draft of their introductory paragraph(s) that includes a thesis statement, and submission of all drafts created thus far in their writing process (as further protection against plagiarism). Once again, the instructor makes written comments that must be addressed in later submissions. The third deliverable due two weeks before their final submission is a draft of their complete paper for a fellow student to review and critique within the following week. The first student (i.e., the author) then has one week to attend to their cohort’s comments (either in the paper or on a separate response sheet) before turning in their final draft for grading. This final draft must be part of a package of all prior submissions that have been reviewed by the instructor, including instructor comments. By requiring all previous drafts and submissions, the instructor can assess whether they made an honest effort to improve their product as they went through this process. This explicit sequence of steps and deliverables will result in a deeper analysis of a student’s chosen topic, which inevitably will enhance the student’s learning of IT while helping to develop his or her writing

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and argumentation skills. Moreover, as suggested by writing advocates (Bean, 2001; Carnes et al., 2001), the instructor should provide a detailed set of grading criteria for the assignment, outlining the requirements for an “A” paper and a grading rubric that provides the checklist to be used for a quick and clear assessment of the paper as it is read to determine the grade. Thus, the students will know up front what is expected of them. For example, one of the criteria in Table 1 is “the problem statement is well-developed.” On the rubric, the instructor can check “yes” or “no” or “maybe” and provide a brief explanation for answers other than “yes.” This method is usually a much more effective means of assessing each paper rather than making detailed notes in the margins noting relatively minor issues, such as clarity and grammar. Not all writing assignments have to be conducted outside of the classroom. If an already work-intensive course does not have time during the semester to include a formal paper or group project, smaller in-class writing assignments can be used. For example, an undergraduate introduction to computer security class occasionally includes short writing assignments at the end of a class based on the material discussed in that class or the past several classes. For example, at the end of a class period spent on the discussion of password security and authentication tactics, the instructor may ask students to write an explanation of the necessity of password security for an executive who has limited knowledge and IT background. In addition to practicing writing skills, students also are given the opportunity to try to explain these concepts in basic terms. This exercise also helps the instructor to determine if the students truly understand the concepts or are just memorizing facts and figures. As previously noted, short writing assignments also can be used in exams. The same undergraduate computer security class requires students to answer at least one essay question per exam, providing students with an opportunity to

Integrating Writing into IT/MIS Courses

explain concepts in detail and often argue their opinion. For example, students may be given a brief biography of a company and are then asked to recommend, based on the company’s needs and line of business, a method of cryptography. This allows students to not only provide an explanation of a topic, but also to demonstrate their comprehension of its application in a real-world scenario. Adding a journal requirement to any IT/MIS course is an easy way to incorporate writing into the curriculum. Students may be asked to write in the journal weekly about things such as current events relating to the class or personal reflections on class materials or guest speakers. For example, students can be asked to contemplate how they might use relational databases in their careers with the goal of having them realize the relevancy of taking a database design course (this is especially useful for non-MIS majors who might take such a course). Instructors then can collect the journals every few weeks to provide feedback. Again, a rubric can be used as a scoring method. Journals are often a successful way not only to further develop writing skills, but also for instructors to get a feel for student comprehension of the subject matter and perceptions of the course.

AvoIdIng PLAgIArIsM Faculty in non-writing intensive areas have rarely had to deal with plagiarism, so adding a writing requirement to the IT/MIS curriculum often takes us into uncharted waters. An awareness of plagiarism and its hold on colleges and universities in today’s Web-based world is necessary before jumping head first into writing assignments. In a recent New York Times article, a student from Duke University said that using a small paragraph that has been cut and pasted from the Internet and slightly altered as part of his research paper is “no big deal…it’s not cheating” (Zernike, 2002, p. 10). This acceptance of cutting

and pasting seems to be common among college students. The same Duke student explained that “as long as I can manipulate it to be my words, change a few, it’s not cheating” (Zernike, 2002, p. 10). Information technology, specifically word processing software and the Internet, has allowed students to copy full paragraphs, change a couple of words, and think that they’ve done nothing wrong. This form of plagiarism is identified by Iverson et al. (1998) as “mosaic plagiarism,” but it is also known as “patchwriting” (Howard, 1999) or “paraphragiarism” (Levin & Marshall, 1993). According to Fox (1994), Western academics indicate that international students often have different notions about plagiarism. Evans and Merhout (2004) explain that countries that have a more collaborative work style may view plagiarism issues differently than Western countries that focus on individual contributions. Bean (2001) elaborates on Fox’s discussion and further explains that some international students are surprised by Western writers’ acknowledgment that other “individuals can ‘own’ [their original] words and ideas” (p. 43). Given Western students’ changing view of plagiarism, thanks to the availability of Internet resources and the cultural views brought by international students, it is imperative to make a note on the course syllabus and discuss plagiarism with all students at the beginning of any class that contains writing assignments. It is also wise to check suspicious submissions by doing a Google search on strings of text that seem out of character for the student writer.

concLusIon Writing assignments are both appropriate and beneficial for students in MIS and IT courses. Specific examples of writing assignments that have been successfully implemented, including short papers, group projects, research papers, and in-class writing have been discussed. In order to

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create employable graduates, faculty members must begin to take responsibility for the development of the whole student, and not simply accept responsibility for discipline-specific skills only. Key to the success of incorporating writing into a curriculum is providing clear grading requirements to students as well as feedback. Plutsky and Wilson (2001) suggest some critical success factors for writing-across-the-curriculum, including developing standards for writing and assessment and providing training programs for faculty. Accordingly we offer this chapter as a tool that MIS/IT faculty members can use as a starting point for incorporating writing into their own courses.

Carnes, L., Jennings, M., Vice, J., & Wiedmaier, C. (2001). The role of the business educator in a writing-across-the-curriculum program. Journal of Education for Business, 76(4), 216-219.

note

Gelinas, U.J., Rama, D.V., & Skelton, T.M. (1997). Selection of technical communications concepts for integration into an accounting information systems course: A WAC case study. Technical Communication Quarterly, 6(4), 381-401.

An earlier version of parts of this chapter was presented at the 2004 Information Resources Management Association (IRMA) International Conference (Merhout, 2004).

reFerences Bean, J.C. (2001). Engaging ideas: The professor’s guide to integrating writing, critical thinking, and active learning in the classroom. San Francisco: Jossey-Bass Publishers. Bloom, B., Englehart, M., Furst, E., Hill, H., & Krathwohl, D. (Eds.). (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. New York: David McKay Company. Bonwell, C., & Eison, J. (1991). Active learning: Creating excitement in the classroom. ASHEERIC Higher Education Report No. 1. Washington, DC: The George Washington School of Education and Human Development.

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Epstein, M.H. (1999). Teaching field-specific writing: Results of a WAC survey. Business Communication Quarterly, 62(1), 29-41. Evans, D., & Merhout, J.W. (2004). Impacts of IT on human behavior in library settings. Proceedings of the 2004 Information Resources Management Association International Conference, New Orleans, LA. Fox, H. (1994). Listening to the world: Cultural issues in academic writing. Urbana, IL: National Council of Teachers of English.

Howard, R. (1999). The new abolitionism comes to plagiarism. In L. Buranen, & M. Roy (Eds.), Perspectives on plagiarism and intellectual property in a postmodern world. New York: State University of New York. Iverson, C., et al. (1998). American medical association manual of style: A guide for authors and editors. Baltimore: Williams and Wilkins. Levin, J., & Marshall, H. (1993). Publishing in the Journal of Educational Psychology: Reflections at midstream. Journal of Educational Psychology, 85, 3-6. Malveaux, J. (2003). Workplace 2003: What’s next for graduating seniors? Black Issues in Higher Education, 20(6), 35. Merhout, J.W. (2004). Integrating writing requirements into MIS courses. In M. Khosrow-Pour

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(Ed.), Innovations through information technology (pp. 299-301). Proceedings of the 2004 Information Resources Management Association International Conference, New Orleans, LA.

(Eds.), Studies in writing: Volume 7: Writing as a learning tool: Integrating theory and practice (pp. 7-22). Dordecht, The Netherlands: Kluwer Academic Publishers.

Nelson, J. (1992). Case study: Teaching learning skills as a foundation for technical training. Educational & Training Technology International, 29(2), 89-93.

Weimer, M. (2001). Foreword. In J.C. Bean, Engaging ideas: The professor’s guide to integrating writing, critical thinking, and active learning in the classroom (pp. xvii-xx). San Francisco: Jossey-Bass Publishers.

Parrish, D. (1998). One day, my son, all these key skills will be yours. New Statesman, 11(530), 21. Plutsky, S., & Wilson, B.A. (2001). Writing across the curriculum in a college of business and economics. Business Communication Quarterly, 64(4), 26-41. Tynjala, P., Mason, L., & Lonka, K. (2001). Writing as a learning tool: An introduction. In G. Rijlaarsdam, P. Tynjala, L. Mason, & K. Lonka

Zeidner, M. (1987). Essay versus multiple-choice type classroom exams: The student’s perspective. Journal of Educational Research, 80(6), 352-358. Zernike, K. (2002, November 2). With student cheating on the rise, more colleges are turning to honor codes [Electronic version]. New York Times. Retrieved February 19, 2003: www.proquest.com

This work was previously published in the International Journal of Information and Communication Technology Education 1(3), edited by L. Tomei, pp. 74-84, copyright July-September 2005 by Idea Group Publishing (an imprint of IGI Global).

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Chapter 4.37

Supporting Creativity in Software Development: An Application in IT Education Aybüke Aurum The University of New South Wales, Australia Meliha Handzic The University of New South Wales, Australia Adrian Gardiner The University of New South Wales, Australia

AbstrAct This chapter examines the potential of the application of an individual creativity-enhancing technique (called SoloBrainstorming, or SBS) to improve the level of creativity of information technology (IT) students in performing information system (IS) requirements determination. Requirements determination, in the context of software development, involves gaining an understanding of the underlying issues related to a business problem, and also considering potential solutions. The chapter begins with a definition of creativity, followed by an overview of strategies suggested to enhance creativity. The SBS tech-

nique is then introduced, followed by a report of empirical results from its application. Finally, we offer advice for IT education in terms of incorporating creativity-enhancing techniques into the IT course curriculum.

IntroductIon Most business problems have a number of potential solutions, some of which may prove to be more beneficial than others. As many of these solutions may not be at first obvious, or previously imagined, management needs to be highly creative in order to identify the best candidate solutions.

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Supporting Creativity in Software Development

However, identification of candidate solutions may depend upon first successfully identifying the underlying issues associated with the business problem. Identification of these issues also requires creativity, as a full understanding of the problem may only emerge through extensive creative discourse (e.g., through Joint Application Development). As contemporary solutions to business problems frequently require the development of computer-based IS, it therefore follows that creativity is important to IS design and development. As Keegan (1998, p. 239) put it: “Today’s constraining factor is not the software, not the hardware, not the network. It is human creativity. We still need skilled, imaginative individuals who can research a business opportunity and integrate the technology needed to put the required process in place.” If we accept the argument that the level of creativity applied to a business problem may significantly impact the quality of the resulting IS, it seems reasonable to expect that students studying systems analysis should be well-versed in the importance of creativity within the software development process and also be skilled in applying creativity-enhancing techniques. However, the authors fear that for many university courses in IS, creativity is not emphasized, and students may therefore graduate with only a rudimentary understanding of this important area. In this respect, the authors feel that the IS teaching community can learn from other disciplines that also focus upon the creation of artifacts, such as architecture and engineering. These disciplines have long acknowledged the importance of creativity by encouraging their students to express themselves creatively, and by incorporating creative problem solving and design techniques throughout their curricula. We therefore argue that IT education and training should more openly acknowledge the role and importance of creativity training and support to the successful development of IS. We believe that training IS and IT professionals in

creativity will allow them to be more successful in their future roles as innovative professionals and business people. Moreover, these concerns have motivated the authors to investigate the potential of an individual creativity-enhancing technique to facilitate requirements determination.

bAcKground on creAtIvIty Defining Creativity The literature offers diverse conceptual definitions of creativity. Tomas (1999), for example, defined creativity in terms of an original idea. Synonyms used by researchers to describe this quality may include uniqueness, surprising, novel, unusualness, innovative, and newness (Thurstone, 1952). A more restricted definition of creativity focuses solely on rare revolutionary and paradigm shifting ideas, while a looser definition includes useful evolutionary contributions that refine and apply existing paradigms (Shneiderman, 2000). The appropriateness of new ideas is also important in order to distinguish creative ideas from surreal ideas that may be unique but have unlawful or highly unrealistic implications. Synonyms used by researchers to describe this quality may include workable, practical, worthwhile, plausible, relevant, and intelligible. What is seen as appropriateness may change depending upon prior insights, the initial problem definition, and the level of available resources for implementing ideas. Furthermore, when discussing creativity, it is helpful to distinguish between the four elements of creativity as identified by Mooney (1963):

• • • •

The creative environment (place, context, setting, or situation) The creative person (levels of individual creativity) The creative process (how creativity is undertaken) The creative product (all output).

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supporting creativity Most findings from past empirical studies indicate that creative performance is highly contingent upon a variety of environmental, cognitive, technological, and other factors. Variables that produced different degrees of creativity include problem importance, common perspectives, familiarity with possible solutions, trust, flexibility of process, external forces, and feedback (Ford & Gioia, 2000). The optimal condition for high creativity involves working alone with no expectation of evaluation (Shalley, 1995). In addition, being given creative examples and informational feedback can also improve creative performance (Shalley & Perry-Smith, 2001). Consistent with the view that creative thinking can be learned by appropriate stimulation and instruction, many techniques for idea generation have been developed to assist the production of novel ideas. For general reviews, see Van Gundy (1988), who identifies 61 tools for group idea generation; and Higgins (1994), who offers 101 creative problem-solving techniques that can be used to increase the level of corporate innovation. Mind mapping is an example of a method that involves recording the free flow of ideas by drawing a map that iterates your ideas (Tomas, 1999). Moreover, a variety of technologies have been developed that follow specific creative techniques (e.g., Ideafisher, Mindlink, IdeaPro, etc.) to facilitate “out of the box” thinking (Sridhar, 2001). Many of the available techniques to facilitate creativity are derivatives of brainstorming. Brainstorming was originally proposed by Alex Osborn (1957) as a means of generating as many ideas as possible from group work. He claimed that a group can generate twice as many ideas as individuals working alone, provided that the group follows a systematic approach and adopts four rules. Osborn’s purpose in suggesting these rules was to overcome social and motivational

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difficulties that might inhibit the generation of ideas in groups. The four rules are as follows: 1. 2. 3. 4.

No criticism is allowed. Freewheeling is welcome. Quantity is wanted. Combination and improvement are sought.

For a brainstorming session, which can be conducted electronically or verbally, a group is formed, and members of the group are encouraged to think freely and propose ideas. The objective of brainstorming is to encourage associations. The basic assumption is that it is possible to generate many ideas, provided that the individual is exposed to stimuli and has experience, knowledge, the personal flexibility to develop various permutations and combinations, and the capacity to make correct selections. The best ideas are listed, and this forms the basis on which the group develops its solution strategy. This method initially emphasizes the quantity of ideas generated, leaving the assessment of quality to a later stage. This method is used to uncover ideas without being constrained, as the outcome is not permanent. Brainstorming also allows individuals or groups to capture all of their thoughts.

Individual brainstorming While most brainstorming-related techniques are designed for group use, individuals can also perform brainstorming. Individual brainstorming may produce a greater number of ideas than group brainstorming, as less time is generally spent on developing ideas in depth (Mullen, Johnson, & Salas, 1991; Stroebe & Diehl, 1994). Development of individual ideas may also be thwarted from the individual running up against problems they cannot solve on their own. One individual creativity technique is SoloBrainstorming (SBS), originally proposed by one

Supporting Creativity in Software Development

Figure 1. Overview of the SBS technique (Adapted from Aurum et al., 2001)

of the authors (Aurum, 1997). This technique uses a form of brainstorming and is especially suited to environments where sentential analysis is appropriate or where information sources are document based (e.g., reports, abstracts, testimonies, interview transcripts, Web publications). The SBS technique (as shown in Figure 1) requires the individual to adhere to a formal protocol (procedure), where a series of documents are examined (“reading” stage), and then edited (“editing” stage). The editing stage consists of the following activities: typing a summary of each document; making lateral comments and links (e.g., making connections between documents; noting ideas as they occur); and nominating issues to be followed up. The ultimate aim in a SBS session is to determine a sufficient set of issues. As applications of the SBS protocol have been computer-based, all issues are automatically available in electronic form for further analysis. Typically, to measure the level of creativity attributable to application of the protocol, before interacting with the document set, users are asked to list issues they are already aware of. Once the

individual has completed to their satisfaction the SBS protocol (i.e., all documents have been examined), the issues that were raised can be analyzed across various dimensions (e.g., originality, workability, and relevance). Central to the SBS protocol is the encouragement of participants to use their cognitive abilities by asking them to make “lateral comments” (e.g., being instructed to make conceptual connections between issues and between documents). Lateral thinking is a function of knowledge and imagination that may bring out discovery, innovation, imagination, and exploration. It is also an aid to creativity when one needs to have diverse ideas. Lateral thinking is a way of thinking that seeks as many alternative options as possible to the extent of one’s adventurousness. In other words, it is a mental activity involving making connections between knowledge and ideas that were previously unrelated. In idea generation sessions, it is important to think expansively and to suspend judgment. In a SBS session, lateral comments involve input from the participant as well as from differ-

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Supporting Creativity in Software Development

ent “authors” of the abstracts and views featured within the other documents. The interaction between these two sources of inputs brings forth creativity, acts as a rich source for stimuli that will trigger greater recollection of relevant knowledge (tacit knowledge), and makes it possible for the participant to see relationships between different elements, make analogies, and look at scenery from different points of view. If the participant does not have any “lateral comments,” then essentially they are restricted to only the material in abstracts. There is no universally accepted set of lateral-thinking or creative-thinking criteria. Aurum (1997) suggested that the level of “laterality” for any thought for a given problem can only be assessed with respect to the thoughts generated by others for the same problem. In addition, the value of SBS also lies in it being a “formal” protocol — one that places specific (yet flexible) demands upon participants to adhere to a set of behaviors designed to enhance the level of an individual’s creativity. Adherence to the SBS regime will thus encourage a higher level of intrinsic motivation (discipline), application of a systematic and thorough approach to analysis, as well as reflective and lateral thinking. As a technique to facilitate creativity, the SBS protocol touches upon an important issue in creativity: the link between an individual’s level of domain knowledge and their capacity to be creative within that domain. (For example, does being truly creative require a rich mental model of the domain?; or can only experts within a domain truly provide creative insights or solutions?) In a typical SBS session, participants are presented with factual-type information. It can, therefore, be argued that this information may allow participants to learn more about the domain, thereby evolving their mental model of causal connections (e.g., identifying previously unknown variables, parameters, or links; or weakening existing links and associations). Supporting this view is Ama-

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bile (1983), who identifies domain knowledge or expertise as the foundation of creative activity. A similar view of the importance of knowledge in creativity is held by Holyoak and Thagard (1995), who regard analogical reasoning (which requires a rich source of potential referents and, therefore, knowledge) as an important potential source of creative thinking. In contrast, Finke et al. (1992) specifically mention the need to suspend one’s expertise as a precursor to creativity, and in doing so, reduce the possibility of fixation. Purcell and Gero (1996), commenting about architectural design, explain fixation as people being unable to see new ways of using objects, which could lead to an innovative solution to a problem, because they are blocked or fixated on well-learned uses or properties of the object. It follows that experts would be expected to have more well-learned routines and ways of problem solving than novices, which thus may lead to fixation on more established ways of doing things. In addition, proponents of the view that an individual’s level of creativity is an individual trait may argue that any increase in creativity possible from mere provision of a richer level of domain knowledge will be constrained by the individual’s intrinsic level of creative ability. Individuals may also need a requisite level of motivation and degree of reflection to integrate new information successfully and overcome the cognitive load (mental demands) required to integrate and preprocess the incoming information in order to be able to leverage this information within a demanding creative task. Overall, the relationship between one’s knowledge and level of creativity may be mitigated by a number of factors (e.g., personal level of creativity). Thus, one cannot merely assume that availability of a richer information set (and hence, greater available domain knowledge) will necessarily lead to the level of mental connections and permutations of cognitive structures required to produce creative insights.

Supporting Creativity in Software Development

Figure 2. Mean rating scores for participants’ creative performance before and after their interaction with the technology

IndIvIduAL brAInstorMIng For requIreMents deterMInAtIon Aurum et al. (2002) (see, also, Aurum & Martin, 1999, for related findings) reported results of a study investigating whether application of the SBS protocol would deliver a richer set of requirement statements and insights.

experimental task An experiment was conducted in which participants were told to assume the role of a systems analyst (SA), who had been retained by a fictitious organization to write a requirements specification for their main information systems. The fictitious organization was the Cultural Heritage Authority (CHA), with a corporate charter that was to coordinate the marketing of Australia’s cultural heritage. In developing their requirements specification, each participant was required to utilize the software developed for the experiment, which

was specifically designed to support application of the SBS protocol. This tool allowed subjects free access to the document set. The type of documents within the document set included fictitious interviews with users and other people holding authoritative positions within CHA and the wider industry and abstracts from published articles addressing heritage or marketing issues. In developing the tool, particular attention was paid to designing the interface. It was important to prevent substantial cognitive resources from being diverted from the task in response to demands from the user-interface. The aim was to produce an interface that would have minimal impact on cognitive load: one that could be learned easily by a novice user and yet was comprehensive enough to satisfy the experienced user.

subjects and Procedure A total of 16 subjects participated in the study on a voluntary basis. The participants were drawn from a pool of graduate students enrolled in a System Analysis and Design course at a large

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Supporting Creativity in Software Development

Australian university. Each received a monetary incentive of $45 for their participation. The experimental session was conducted in a microcomputer laboratory. On arrival, subjects were seated at individual workstations and worked alone. They received instructions regarding the case study and task requirements. They also had an opportunity for practice prior to commencing the experiment and to ask questions during the experiment. The session lasted 3 hours.

dependent Measures and results Before using the SBS software (and therefore accessing the document set), participants were asked to generate ideas with respect to the anticipated requirements for CHA’s information systems. These ideas were then compared with the ideas generated during application of the protocol in order to determine whether the application of the SBS protocol had led to a richer level of requirement specifications. Specifically, this study focused upon whether application of the protocol would result in identification of more relevant, workable, and original requirements issues (in other words, a subject’s creative performance was evaluated in terms of relevance, originality, and workability of ideas generated before and after interaction with the tool, as assessed by an expert judge). The judge was a software developer with over 30 years of experience. The judge examined students’ ideas and evaluated them for relevance, originality, and workability by rating each on a 5-point Likert scale, with 1 as the lowest and 5 as the highest possible score. In order to understand the effects of the proposed learning tool on subjects’ creative performance, we statistically analyzed the changes in the nature of ideas generated “after” the interaction with the tool compared to those “before.” The paired t-test was selected as the most suitable method for the analysis (Huck et al., 1974). Results of the analysis are shown graphically in Figure 2.

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Overall, the results of the analysis indicated that the tool had a significant positive impact on the originality of ideas generated but had no significant impact on their relevance or workability. As shown in Figure 2, there was a significant increase in the originality of ideas generated by the participants after their interaction with the tool. More specifically, the overall mean score for originality increased significantly from 1.4 before to 1.8 after the interaction (p < 0.01). These scores indicated a qualitative change from mostly “very common” (low score) to “slightly novel” (high score) thoughts. In contrast, the analysis indicated no significant impact of the tool on relevance or workability of the ideas generated. Figure 2 shows that the mean rating score for relevance decreased slightly after interaction with the tool. However, the change was not statistically significant (3.1 versus 3.0, ns). These scores indicated that similarly “relevant” requirements were addressed by the participants, irrespective of the change in their originality. Similarly, there was no significant change in the workability of the ideas generated due to tool use. The mean rating score after interaction was not significantly different from that before the interaction with the tool (2.5 versus 2.5, ns). These scores also suggest that “workable” ideas were generated, irrespective of their increased level of originality. The value of increasing originality of ideas would have been undermined if the ideas were less workable or relevant – however, this was not the case. Therefore, application of the protocol increased the overall quality of the elicited requirements. The results of this study support the idea that thought-assisting applications can be developed, learned, practiced, and used to generate ideas.

Findings The main findings of the present study indicate that a solo-brainstorming-based learning tool

Supporting Creativity in Software Development

had a positive effect on students’ creative performances in a systems requirements specification task. This outcome was evident in the originality aspect of task performance but not in relevance and workability. Users were found to generate significantly more original ideas as the result of their interaction with the tool, while maintaining similar levels of relevance and workability (i.e., increases in originality did not come at the cost of less workable or less relevant ideas). The results of the current study provide support for the view that creative performance can be enhanced by appropriate stimulation and instruction as suggested by some theorists (Ford & Gioia, 2000; Marakas, 1998). More specifically, the study revealed that significant improvement was achieved in the originality of ideas generated by the participating students due to their interaction with the tool studied here. Participants were found to shift their thoughts from common and well-known concepts to slightly novel ones after participating in the interacting session. The results also agree with our earlier findings of improved quality of creative performance from another similar empirical study conducted in the decisionmaking context (Aurum et al., 2001). Essentially, the results support the idea that thought-assisting applications can be developed, learned, practiced, and used to generate ideas. Thus, they can enable an individual to think creatively, provided that the principles are clearly understood. Furthermore, the results of the current study indicate that increased originality did not have an adverse effect on the appropriateness of ideas (e.g., workability, relevance) generated by the participants. The study found that participants tended to continue generating similarly relevant and workable ideas irrespective of the change in their originality. This is an important finding, as it suggests that the tool encouraged innovative rather than simply original thought. According to Shalley and Perry-Smith (2001), translating creative ideas into innovative products requires these ideas to be appropriate. The current study

demonstrated the required appropriateness in terms of adequate relevancy and workability of generated ideas. It is possible that the design feature of the proposed tool that provided idea storage and retrieval capabilities helped participants in the final assessment. The results of our study also indicate that the brainstorming technique underlying our tool is a promising method for stimulating creative thinking and idea generation in a software development task. It has been suggested in the literature (Satzinger et al., 1999) that the idea generation method is one of the most important sources of encouraging creativity. Essentially, the brainstorming session helped students uncover ideas without being constrained, stimulate their own thinking by external influences, and capture their thoughts. Finally, the results of the study support the proposition that an electronic tool following a specific creativity-enhancing technique can assist the creative process (Sridhar, 2001). One of the main advantages of such a tool is the speed at which ideas can be produced. Furthermore, the ideas can be stored and revisited at a later time. The tool can also provide a variety of stimuli that can enhance creativity. The electronic tool tested in this study provided all of the above, plus a formal protocol that brought a much needed structure to the idea generation process. Although the overall results of this study are encouraging, there is room for further improvement to originality. The level or originality of ideas achieved due to interaction with the proposed tool was less than desired. One possible reason for the lack of “highly original” thought may be the participants’ feeling of pressure from consideration of implementation issues. Alternatively, it can be attributed to the participants’ traditional IT education, which places more emphasis on developing their analytical and systems thinking skills rather than creative and innovative thinking skills. Furthermore, the subjects in the study had only one interactive session with the tool, and this

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Supporting Creativity in Software Development

might have been insufficient to produce a more substantial shift in their thinking patterns.

Limitations and Future research While the current study provides a number of interesting findings, some caution is necessary regarding their generalizability due to a number of limiting factors. The application of laboratory conditions is a major limitation of this study. Furthermore, the conclusions drawn based on the assessments of expert judges may be biased. We also speculate that the performance of users in an interaction session can be affected by their state of mind or previous experience. The emphasis of the present study was on individual students. It would be interesting to examine the effect of the tool on the creative performance of groups. Future research may address some of these limitations.

IMPLIcAtIons For Future It educAtIon Our findings may have some important implications for IT education. They suggest that creativity can be improved to an extent that higher-quality software designs may be possible. Thus, IT schools need to acknowledge this and include creativity within their courses to prepare students. It is encouraging that some governments and educational institutions are starting to emphasize the significance of promoting creative thinking of the young through education (Sunderland, 2000) and are beginning to implement changes in courses taught in business schools (Sangran, 2001). The results of this study suggest that the type of tool tested here may be a useful teaching tool in a variety of courses involving creative thinking and problem solving. Furthermore, the tool is likely to be most valuable in situations where the problem is unstructured, goals are indistinct, and

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the outcome of an action cannot always be clearly identified. The tool is rather generic, because it uses a technique that can be applied to a variety of scenarios and can help people process relevant documents while identifying issues. These documents act like a “trigger” to stimulate domainspecific ideas from users.

concLusIon This study proposed and empirically tested a specific learning tool aimed at stimulating creative problem solving of IT students. The tool was designed on the basis of a brainstorming technique. The essence of the tool was to provide users with external stimuli and expose them to a large number of ideas over a short period of time. The tool was tested in the context of an information system requirements specification task. The results of the test indicated that the tool was useful in enhancing creative performance of the users. After interacting with the tool, participants were able to generate more original ideas while maintaining levels of relevance and workability necessary for innovative software designs. Our findings imply that creativity can and should be taught to IT students, and that the learning tool described in this study can potentially be a valuable facilitator of the process.

reFerences Amabile, T. (1983). The social psychology of creativity, New York: Springer-Verlag. Aurum, A. (1997). Solo brainstorming: Behavioral analysis of decision-makers, Unpublished PhD thesis, University of New South Wales, Australia. Aurum, A. (1999). Validation of semantic techniques used in solo brainstorming documents. In

Supporting Creativity in Software Development

H. Jaakkolam, H. Kangassalo, & E. Kawaguchi (Eds.), Information modelling and knowledge bases X (pp. 67-79).

of creative talent. In C. W. Taylor & F. Barron (Eds.), Scientific creativity: Its recognition and development (pp. 331-340). New York: Wiley.

Aurum, A., Handzic, M., & Gardiner, A. (2002). Preparing IT professionals for the knowledge economy. Proceedings of Information Resources Association International Conference, Seattle, WA.

Mullen, B., Johnson, C., & Salas, E. (1991). Productivity loss in brainstorming groups: A metaanalytic integration. Basic and Applied Social Psychology, 12, 3-23.

Aurum, A., Handzic, M., Cross, J., & Van Toorn, C. (2001). Software support for creative problem solving. Proceedings of the IEEE, International Conference on Advanced Learning Technologies (ICALT2001), Madison, WI (pp. 160-163). Finke, R. A., Ward, T. B., & Smith, S. M. (1992). Creative cognition. Cambridge, MA: MIT Press. Ford, C. M., & Gioia, D. A. (2000). Factors influencing creativity in the domain of managerial decision making, Journal of Management, 26(4), 705-732. Higgins, J. M. (1994). 101 creative problem solving techniques: The handbook of new ideas for business. FL: The New Management Publishing Company. Holyoak, K. J., & Thagard, P. (1995). Mental leaps. Cambridge, MA: MIT Press. Huck, S. W., Cormier, W. H., & Bounds, W. G. Jr. (1974). Reading statistics and research. New York: Harper and Row Publishers. Keegan, D. (1998). The virtual countinghouse: Finance transformed by electronics. In D. Leebart (Ed.), The future of electronic marketplace. Cambridge, MA: MIT Press. Marakas, G. M. (1998). Decision support systems in the twenty-first century. Upper Saddle River, NJ: Prentice Hall. Mooney, R. L. (1963). A conceptual model for integrating four approaches to the identification

Osborn, A. (1957). Applied imagination: Principles and procedures of creative thinking. New York: Charles Scribner’s Sons. Purcell, T. A., & Gero, J. S. (1996). Design and other types of fixation. Design Studies, 17(4), 363-383. Sangran, S. (2001). Preparing students to be Kprofessionals. Computimes Malaysia, February 22, 1-2. Satzinger, J. W., Garfield, J. M., & Nagasundaram, M. (1999). The creative process: The effects of group memory on individual idea generation. Journal of Management Information Systems, 14(4), 143-160. Shalley, C. E. (1995). Effects of coaction, expected evaluation and goal setting on creativity and productivity. Academy of Management Journal, 38, 483-503. Shalley, C. E., & Perry-Smith, J. E. (2001). Effects of social-psychological factors on creative performance: The role of informational and controlling expected evaluation and modelling experience. Organizational Behaviour and Human Decision Processes, 84(1), 1-22. Shneiderman, B. (2000). Creating creativity: User interfaces for supporting innovation. ACM Transactions on Computer-Human Interaction, 7(1), 114-138. Sridhar, R. (2001). India: Software for breaking mental blocks! Business Line, India, February 22, 1-3.

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Stroebe, W., & Diehl, M. (1994). Why groups are less effective than their members: On productivity losses in idea-generating groups. In W. Stroebe & M. Hewstone (Eds.), European review of social psychology. London: Wiley. Sunderland, K. (2000). The power of a silly idea. Charter, 71(6), 49-51.

Thurstone, L. L. (1952). Creative talent. In L. L. Thurstone (Ed.), Applications of psychology (pp. 18-37). New York: Harper and Row. Tomas, S. (1999). Creative problem solving: An approach to generating ideas. Hospital Material Management Quarterly, 20(4), 33-45. Van Gundy, A. B. (1988). Techniques for structured problem solving (2nd ed.). New York: Van Nostrand Reinhold.

This work was previously published in Current Issues in IT Education, edited by T. McGill, pp. 77-87, copyright 2003 by IRM Press (an imprint of IGI Global).

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Chapter 4.38

Online Assessment of Foreign Language Proficiency: Meeting Development, Design, and Delivery Challenges Paula M. Winke Michigan State University, USA

AbstrAct

IntroductIon

In this chapter, the challenges involved in creating online Arabic and Russian proficiency tests by using a commercial test product are discussed. Guidelines used for item and test development are presented, along with specific challenges test developers faced in designing computerized, semiadaptable tests. Also discussed are the issues involved in delivering the tests securely over the Internet to examinees, who took them on computers in college and university language labs across the United States and abroad. The chapter concludes with a list of five important lessons that could help others who are contemplating a similar test development project.

Standardized tests of foreign language proficiency for languages that are less commonly taught in the United States—that is, languages other than Spanish, French, German, or English (Walker & McGinnis, 1995)—are needed more than ever to meet the growing demand for accurate information concerning students’ foreign language proficiency in these languages. One common challenge for professionals teaching less commonly taught languages (LCTLs) is the lack of available tests that measure students’ progress and proficiency or help with the placement of new students into the appropriate levels of instruction. (See Hughes, 1989, or Bachman & Palmer, 1996, for more information about different kinds of foreign and second language tests.) Because college and university departments and programs that need such

Copyright © 2008, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Online Assessment of Foreign Language Proficiency

language tests are typically small and have low numbers of potential test-takers, few resources are allocated for the development of nationally available standardized tests. In addition, currently available paper and pencil tests for the LCTLs in the United States are often difficult to locate, are inconvenient, and are expensive to administer and score due to the small volume of use. One solution is to create Web-based proficiency tests for these languages. Such tests are more easily available, allow for use by a large variety of programs and institutions, and provide the option of automatic and immediate scoring of test items. However, Web-based testing of these languages poses a few problems: (a) LCTLs in the United States include languages with logographic (e.g., Chinese) or non-Roman (e.g., Arabic and Russian) alphabets that can be difficult to enter into Web formats; (b) reliable resources for creating authentic test items are scarce; (c) individuals who know the languages well enough to create items may not be at the same location and may not be trained as test developers; and (d) the development of a Web-delivery system for such tests can be time-consuming and costly (Chalhoub-Deville & Deville, 1999; Dunkel, 1999b), especially when compared to the small audience for the tests. In this chapter, the challenges involved in creating two online LCTL proficiency tests, one for Arabic and one for Russian, at the Center for Applied Linguistics are discussed. Each test has two sections, listening and reading, that can be taken separately or back-to-back in either order. The basic template for these two semiadaptable1 tests is provided, and insights are offered into how other foreign language online test developers, especially LCTL test developers, could start a similar project.

bAcKground The Center for Applied Linguistics (CAL) is a not-for-profit institution in Washington, DC,

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committed to improving communication through a better understanding of language and culture. CAL’s Language Testing Division has maintained the paper and pencil Arabic Proficiency Test (APT), developed by Dr. Raji M. Rammuny and Dr. Mahmoud E. Sieny at the University of Michigan, since it became operational in 1993. The APT is administered to about 200 students per year.

Project goals In 1999, in response to widespread use of networked computer labs at institutions of higher education and advances in computer-assisted and computer-adaptive testing for foreign languages (Brown, 1997; Chalhoub-Deville & Deville, 1999; Chapelle, 2001), CAL proposed to the United States Department of Education the adaptation of the APT to a Web-based, semiadaptive format. The primary goal was to facilitate administration of the test. A second project goal was to replicate the creation of the Web-based Arabic test to create a new Russian proficiency test. Because there are few blueprints for second language test developers who want to create computer-adaptive tests (Dunkel, 1999a), CAL also proposed to develop a general framework for this project—the mandate, test guidelines, and item specifications—so that other institutions interested in creating their own Web-based tests would have a template for doing so. (See Davidson & Lynch, 2002, for more information on general foreign language test mandates and specifications and Eignor, 1999, for foreign language computer-adaptive test specifications in particular.) In 2000, CAL’s Language Testing Division received a grant from the United States Department of Education to develop online, semiadaptive listening and reading proficiency tests in Arabic and Russian.

Project teams Before test development could begin, four teams were identified to work on the project. The first

Online Assessment of Foreign Language Proficiency

team consisted of the CAL staff members who would manage the project. The second team, whose role was to review the framework and the item specifications after they were drafted by CAL staff, consisted of one representative each from the American Council on the Teaching of Foreign Languages (ACTFL) and the governmental Interagency Language Roundtable (ILR) and six members of the National Council of Organizations of Less Commonly Taught Languages (NCOLCTL). The third team, all native speakers of Arabic, worked specifically on the Arabic test. The team consisted of Arabic item writers; an external board that reviewed the items created by the writers; and a group of graduate students who evaluated the effectiveness of the items, commented on the items’ interest levels, and provided technical language assistance to CAL staff when needed. The fourth team worked on the Russian test. The Russian team mirrored the Arabic team in composition and tasks. However, because the Russian item development team needed to create considerably more items than the Arabic team (because the Russian test did not incorporate items from a previously existing assessment), there were two more Russian item writers than Arabic item writers. Other native speaking consultants were called upon to help re-record audio files for some of the listening items whose original audio files were of poor digital quality.

MeetIng deveLoPMent chALLenges creating online Listening and reading Items Because reliable resources and materials for LCTL instruction and testing in the United States are scarce (Janus, 2000), the test developers decided to use the Web as a materials source for creat-

ing authentic listening and reading test items. All Arabic and Russian item writers attended item development sessions at CAL, where they discussed with CAL staff the procedures for developing items based on the ACTFL Proficiency Guidelines for listening and reading (Byrnes & Canale, 1987) and based on the language-specific guidelines for Arabic and Russian (American Council on the Teaching of Foreign Languages, 1988, 1989). The American Council on the Teaching of Foreign Languages (ACTFL) guidelines describe four main levels of proficiency: novice, intermediate, advanced, and superior, which are the target levels of proficiency to be assessed by the Arabic and Russian Web tests. The item writers for this project were professors and experts in their language fields, but CAL staff were concerned that some of them might not be technically prepared to develop authentic items for insertion into an online examination. To address this issue, all item writers were given the following suggestions: 1.

2.

3.

Download audio files from Russian and Arabic news Web sites according to copyright guidelines. Standard audio files can be edited by using the Windows accessories program Sound Recorder. More sophisticated digital audio editing can be done at CAL with the program Sound Forge from Sony Media ($400; available online at http://mediasoftware.sonypictures.com/products/soundforgefamily.asp). Make recordings from Web-based radio stations by using Total Recorder from High Criteria, Inc. ($11.95; available online at http://www.highcriteria.com). Lists of Arabic and Russian online radio station guides can be found at CAL’s Web site (2004). Use the print screen (Print Scrn) button on a PC to create a screen shot of any Internet Web page. Create a graphic JPEG file of the relevant parts with the standard Windows accessories program Paint.

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4.

Go to CAL’s Web site (2004) for tips on how to view Arabic or Russian text through an Internet browser, and see Madhany (2003) for tips on how to set Windows to read and write in Arabic.

Arabic and Russian teams developed, reviewed, and revised approximately 125 items for each language’s reading and listening test sections, about 500 items total. Items were developed across the full range of ACTFL proficiency levels for listening and reading, from novice to superior.

choosing a commercial online Assessment Product Instead of building a new program to administer online foreign language proficiency tests, CAL staff members decided to purchase existing commercial software for Web-based assessment

(Chalhoub-Deville, 2002). Table 1 lists currently available test packages, though this list is by no means exhaustive. Test products are listed in alphabetical order, along with the company name and URL. Not listed are the item types available with each test package (e.g., multiple choice, essay, matching, and fill in the blank), because each package has many item types available. Included are adaptability functions (item-by-item or testlet level2 adaptability; see Wainer et al., 2000, pp. 245-254 for an elaboration on testlets), options for security, and availability of a hosting service. (With a hosting service, the company, usually for a fee, hosts your Web-based tests, the media associated with them, and the scores, all of which are accessed via the Web.) Price information is also included. Prices are often dependent on the complexity of the test program (i.e., adaptability levels), the type of organization purchasing the product (tax exempt or not), and the number of administrators and potential examinees involved.

Table 1. Currently available off-the-shelf online testing packages Product, Company, & Web Site

Adaptability Security

1) i-assess, EQL International Ltd., http://www.iassess.com

No

2) Perception for Web, Questionmark, http://www.quest

Item-by-item Password & logins, option to use free or testlet secure browser (locked, proctor can Available branching be required) for PCs available

Contact Questionmark for pricing

3) Test Generator Enterprise, Fain & Company, http://www.testshop.com

Passord & logins, other features such Not available as a locked browser or dual login Available yet requirement available

Contact Fain & Company for pricing

4) Test Pilot Enterprise, ClearLearning, McGraw-Hill Higher Education, http://www.clearlearning.com

Item-by-item Login ID & password restrictions or testlet available branching

Available

$750 to $20,000 depending on number of participants

5) Quiz Factory 2, LearningWare Inc., http://www.learningware.com

No

No

No

$6,995 to install player on an unlimited basis, 3 creators

6) WebMCQ, WebMCQ Pty Ltd., http://www.webmcq.com

No

General access codes to individual logins and passwords are available

Free, part of Contact WebMCQ for the system pricing

7) WebQuiz XP, SmartLite Software, http://www.smartlite.it

No

No

No

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Student login ID & password restriction is integrated

Hosting

Price

No

Contact i-assess for pricing

$499.95, custom services extra

Online Assessment of Foreign Language Proficiency

For the Arabic and Russian Web tests CAL purchased the software product Perception, for Web and a Microsoft SQL Server. This test package and server system was chosen because Perception for Web had all the features needed for these particular tests—graphic and audio file capabilities, high security, multiple choice and essay items, and adaptability at the testlet level3 —at an affordable price. Perception for Web requires examinees to have a designated login name and password to log on. CAL staff can restrict the time and date for the test period, the amount of time to be spent on the test, and the number of times the test can be attempted. The program comes with a secure browser, which is free for examinees; tests can also be set so that the examinees cannot exit the test until they have completed all items, nor can they copy, paste, or print. Secure browsers are readily available with many online testing packages. Unfortunately, Perception for Web’s secure browser only works with PCs. However, if tests are not restricted to be administered with a secure browser, tests developed with Perception for Web can be taken on either a PC or a Macintosh. Because the Arabic and Russian Web tests are relatively high-stakes tests, a secure browser is needed (along with an on-site proctor who checks student IDs and monitors the test session), so CAL restricted the Arabic and Russian Web tests to PC administration only.

MeetIng desIgn chALLenges specifying Item types Two different item types are used in the online Arabic and Russian proficiency tests: standard multiple choice (Haladyna, 2004) and essay response. Although Perception for Web offers a variety of item formats, including the use of video and the incorporation of JavaScript-based drag and drop items, CAL staff members restricted the item

types to be used on the Arabic and Russian tests for four reasons. First, developing numerous item types would have taken more time, money, and server space than allotted to this project. Second, for high-stakes testing, it would take too much time and space to give examinees directions for several item types. Third, the test developers decided, in this case, it would be better to focus resources on the content of the items rather than on bells and whistles that would not necessarily improve the assessment of examinees’ language proficiency. Finally, video files would have been too large to be sent efficiently to examinees at remote computers. This case study illustrates the dilemma often faced by computer-adaptive test developers (Grabe, 2000). Bells and whistles are attractive. Some argue that innovative item types may improve measurement by reducing the amount of guessing by examinees and by expanding the content coverage of a test (Parshall, Spray, Kalohn, & Davey, 2002), but practical issues, in this case, outweighed the benefits of multiple item types and video.

specifying Item Layouts For the Arabic and Russian Web tests, each item is presented first with an orientation, that is, a context in which the examinee might come across the reading text or listening passage. Next, the listening file (a linked MP3 listening file) or the reading text (a JPEG graphic) is given. Then the question is presented and either the multiple choice options are listed or a text box is presented in which test takers type their response in English. The essay items are the most difficult items on the test; they are at the superior level on the ACTFL scale. Essay questions are not scored automatically: The scoring of a Web test is fully automatic only for students at lower levels of proficiency, that is, those who do not reach the superior-level items and who are tested only with multiple choice questions. Examples of an Arabic

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Figure 1. Novice-level, multiple-choice Arabic reading item

Figure 2. Superior-level, essay-response Russian listening item

novice-level, multiple choice reading item and a Russian superior-level, essay response listening item are presented in Figures 1 and 2. All Arabic and Russian reading texts are presented as JPEGs because Perception for Web does not support non-Roman fonts. Using JPEGs

2250

allows the incorporation of authentic items exactly as they appear on the Web or in print, with their different fonts, colors, and photos. The inability of Perception for Web to support non-Roman fonts also means that all essay responses must be in English. This is a limitation, but CAL staff

Online Assessment of Foreign Language Proficiency

believe that not all the test takers would know how to type in Arabic or Russian. In addition, having the responses in English facilitates the scoring of the essay items. English speakers at CAL are trained to use the scoring rubrics and assign scores based on content, not on spelling or punctuation. A downside to this method is that at the highest levels of proficiency, students are forced to use English to demonstrate their comprehension of Arabic or Russian. Students who are native speakers of English may be at an advantage over native speakers of other languages who take these tests, especially at the higher levels of proficiency.

Determining Item Difficulties To calibrate the items developed for this project, the items were first field tested at more than 25 different institutions. Students of Arabic and Russian from all levels participated in the field testing, which was organized by CAL and the proctors at each institution who administered and monitored the test taking sessions. At CAL, a Rasch analysis using Winsteps was performed for each test to calibrate the items and to determine each item’s difficulty level. (For more information about Rasch analyses, see Athanasou, 2001; Bond & Fox, 2001; El-Korashy, 1995; and McNamara, 1990.) The difficulty levels corresponded significantly with the items’ predetermined ACTFL levels at approximately the 0.70 level for each test (Spearman’s rho, 2-tailed correlations, p < .01). After the item difficulties were determined, the items were separated into four levels of item difficulty according to a modified bookmarking procedure based on Mitzel, Lewis, Patz, and Green (2001). In preparation for the item analyses, CAL staff first formatted the examinee responses for the statistical analyses. Although many off the shelf test packages come with built in statistical features, the statistical features provided are generally not intended for analyzing data in connection

with large scale, standardized test development projects. Getting results from field test forms that were administered selectively across institutions and classes and that contained a set of repeated items taken by each examinee (the anchor items) was beyond the scope of Perception for Web’s reporting program. (See Ward & Murray-Ward, 1994, for more information on item banking and anchor items.) Thus, scores received by individuals from each institution on the different field test forms were downloaded into Excel spreadsheets. The data were then merged appropriately for the Rasch analyses. Rudner (1998) warned that compiling test forms, making testing arrangements, collecting data, and preparing data for processing are particularly important steps in creating item banks. He stated that “depending on the frequency of students taking multiple subtests from different levels and forms, this . . . can be a major undertaking” (p. 4). Even with the progress in technology and the advanced reporting features that come with online test packages, this is still the case.

MeetIng deLIvery chALLenges creating Item banks and the test Path For a Web test, two separate item banks are necessary: one for the preliminary placer test and one for the testlets. In Figure 3, the placer test is shown as having 20 items pooled from all levels of the test, from the easiest items to the most difficult. Figure 4 shows the testlet item bank. The superior-level items in this pool are either essay or multiple-choice, whereas in the placer test, the superior-level items are only multiple-choice. In Figures 3 and 4, the item difficulty levels, which were used to separate the items for placement into the item banks, do not align strictly according to ACTFL levels; correspondence was

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Figure 3. Item databank for the placer test

Hardest items - Easiest items

Placer Test Item Bank Novice

6 Placer Test

Intermediate

6

Advanced

6

Superior*

2

20 items (NoviceSuperior)

Total items in bank: at least 20 Note: *All Superior-level items (the hardest items) in the placer test item bank are multiple-choice.

*All Superior-level items (the hardest items) in the placer test item bank are multiple-choice.

highly significant at the 0.70 level, but not 100%. Therefore, the graphic displays of the ACTFL levels corresponding with the difficulty levels in Figures 3 and 4 are an idealistic representation. When an examinee logs in for a test, he or she is first presented with the placer test that has 20 items ranging from the easiest (ideally novice level) to the hardest (ideally superior level). The outcome of the placer test directs the examinee to an appropriate testlet with items centralized around his or her ability level. If the examinee does as well as expected on the first testlet (e.g., receives a score between 33% and 66%), the examinee’s test ends, and he or she receives a score report. However, if the examinee does not do as well as expected, he or she will take a second testlet at a lower or higher level of difficulty, depending on the first testlet’s outcome. In this case, the score report is issued after the second testlet. This test path is represented in Figure 5.

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According to this semiadaptive template, depending on whether an examinee takes one or two testlets, a test has either 44 or 68 items. Students at lower proficiency levels are expected to take less time because their items are shorter, while students at the advanced or superior level need more time. The time, however, is also influenced by the number of testlets (one or two) the examinee takes. There is no time limit on the Arabic or Russian tests. In general, the semiadaptability of a test makes it shorter than a standard fix-form test, which typically has more items at all difficulty levels for each test taker (Young, Shermis, Brutten, & Perkins, 1996).

Adapting to changing test technology The Arabic and Russian Web test project was budgeted to take three years. However, several

Online Assessment of Foreign Language Proficiency

Figure 4. Item databank for the testlets 24-Item Testlets

Hardest items - Easiest items

Testlet Item Bank 8 8 8 8 8 8 8 8 8 8

Novice

Intermediate

Advanced Superior*

Testlet 1 (Novice) Testlet 4 (Intermediate) Testlet 7 (Advanced)

Testlet 2 (NoviceIntermediate) Testlet 5 (IntermediateAdvanced) Testlet 8 (AdvancedSuperior)

Testlet 3 (NoviceIntermediate) Testlet 6 (IntermediateAdvanced)

Total items in bank: at least 80 Note: *Superior-level items (the hardest items) in the testlet item bank are either multiple-choice or essay.

*Superior-level items (the hardest items) in the testlet item bank are either multiple-choice or essay.

Figure 5. The test taker’s path Test Taker's Path

Placer Test

Testlet

20 items

24 items

Score above or below testlet level Score matches testlet level

problems arose. The original budget was written in 1999, but changes in technology costs between 2000, when the project began, and 2004, when it was finished, affected the project design and influenced the test development process. Originally, $6,000 was budgeted for the Web-based assessment program, Perception for Web. By the end of 2001, the cost for most programs was over $10,000, and prices have continued to climb since then. In 2000, the audio files to be used in the tests were created in standard AU (audio file; the file

2nd Testlet 24 items

Score report

Score report

extension is .au) formats. However, during the first round of pilot testing, many university computers did not have audio players that could open these files. Therefore, the audio format was switched in 2001 to WAV (Windows waveform), which was more accessible to examinees in computer labs at colleges and universities. Over time, as the field testing expanded and more examinees logged in simultaneously, it was found that these files were hard for remote computers to download due to the relatively small bandwidth and server capacity available at CAL.

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In 2003, CAL upgraded to a newer version of Perception for Web (version 3.4). This newer version allowed for the insertion of MP3 (MPEG audio layer 3) files, which are considerably smaller than WAV or AU files, so CAL staff converted all the audio files to MP3s. Staff members on the project were fortunate to have a license with Questionmark that provided free product upgrades as long as CAL’s Language Testing Division continued to pay the annual support fees.

than once. Forced to eliminate JavaScript, CAL staff created two items for every one listening item: an unscored audio-file-empty item and an exact duplicate with the audio file embedded and set to play automatically. On a listening Web test, these two items are always presented as a set. This solution is not as good as using JavaScript, but it works and allows the tests to be accessible to more examinees.

Living with Program constraints

concLudIng Lessons For the Future

Not wanting institutions’ technical limitations to prevent them from having access to the tests, the test development project needed to adapt according to the constraints on computers and server systems at typical institutions across the United States. Thus, for example, when it was discovered that some of the possible test users—universities that wanted to use the Arabic test for placement—had internal server blocks (firewalls) and browser specifications set up against incoming JavaScript on the public computers used in testing, CAL staff eliminated all JavaScript utilities in the tests to prevent losing this significant population of potential test takers. This was unfortunate for two reasons. First, Perception for Web has a test tracking bar that can be included in a test. The bar can be used by an examinee to flag items to review later before submitting the answers and maps where the examinee is in the test, how many test questions have been answered, and how many remain. CAL staff had to eliminate the test tracking features because they run with JavaScript. Instead, the items were numbered manually (e.g., 12 out of 24). Secondly, CAL staff was using JavaScript to restrict the number of times an examinee could listen to an audio file. Perception for Web has no built-in feature for this. With JavaScript, CAL staff had examinees access a listening file through a link that would disappear when clicked, thus taking away the option to hear the passage more

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In this chapter, I discussed the challenges involved in creating online Arabic and Russian proficiency tests using a commercial product. I provided suggestions for developing online test items and for purchasing an off-the-shelf test package. In addition, I described the challenges CAL staff faced in designing and delivering tests securely over the Internet. Staff members in CAL’s Language Testing Division hope to use the knowledge they gained in refining their approaches to developing online tests for developing Web-based proficiency tests in other LCTLs. The five major lessons CAL staff learned that could help test developers begin a similar online test development project are summarized in the following list: 1.

Be prepared to spend considerable time with foreign language item developers, who sometimes have limited experience with computers or with test development. They will need help in creating items using materials currently available on the Web. They will not only need to know which Web sites to visit but also be provided with the tools to download and edit materials from the Web. They also need to know how to record where they found the materials they have chosen in order to request copyright permissions.

Online Assessment of Foreign Language Proficiency

2.

3.

4.

5.

Be prepared for software and other materials to cost much more than originally budgeted. Unforeseen expenses tend to arise, such as having to pay for audio files to be converted or needing to buy more memory for your server space as you add new multimedia to your items. Something that costs $1,000 today may cost $2,000 tomorrow. When using an off-the-shelf testing product, make sure it can grow and change with your project and with current trends in technology. Get a renewable site license that will provide upgrades and newer versions of the software with annual support payments. Consider having the test project hosted by the test company’s server system for a monthly or annual fee (or on a per test basis) rather than buying and maintaining your own server, especially if you are a small institution. One of the major problems in online testing, especially when large multimedia files are involved, is getting the items or the entire test delivered in a fast and efficient manner. The efficiency depends on remote computer download speeds, Internet traffic, the size of the multimedia, and the bandwidth and competing incoming and outgoing data at the host server’s door. It depends very little on the online test program you are using. Be prepared for constraints caused by limitations on your end or on the test takers’ end. Some features of commercial test packages, such as security measures, reduce the number of platforms or browsers on which the tests are administrable. Other features, such as JavaScript-supported timers and counters, novel item formats, or test tracking bars, may not be usable due to delivery problems. Sometimes the programming language of these features will reduce the number of potential test takers because examinees’ computers do not allow the features; they may be blocked by firewalls or public computer lab download restrictions.

Despite the challenges involved in creating online, standardized tests of foreign language proficiency, especially for the LCTLs in the United States, the benefits are worth it. The challenges to the tests’ development can be met by being prepared: Establish item and test development guidelines ahead of time, be savvy when it comes to purchasing commercial test products, and research what others have done to learn from their mistakes and successes.

AcKnowLedgMent A special thanks to Dr. Dorry M. Kenyon, director of the Arabic and Russian Web test project and the Language Testing Division at CAL, for his guidance and instruction.

reFerences American Council on the Teaching of Foreign Languages. (1988). ACTFL Russian proficiency guidelines. Foreign Language Annals, 21(2), 177-197. American Council on the Teaching of Foreign Languages. (1989). ACTFL Arabic proficiency guidelines. Foreign Language Annals, 22(4), 373-392. Athanasou, J. A. (2001). Analysis of responses to vocational interest items: A study of Australian high school students. Journal of Career Assessment, 9(1), 61-79. Bachman, L. F., & Palmer, A. S. (1996). Language testing in practice. UK: Oxford University Press. Bond, T. G., & Fox, C. M. (2001). Applying the Rasch model: Fundamental measurement in the human sciences. Mahwah, NJ: Erlbaum.

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Brown, J. D. (1997). Computers in language testing: Present research and some future directions. Language Learning and Technology, 1(1), 44-59. Byrnes, H., & Canale, M. (Eds.). (1987). Defining and developing proficiency: Guidelines, implementations and concepts. Lincolnwood, IL: National Textbook. Center for Applied Linguistics. (2004). Arabic and Russian Web test project. Retrieved September 4, 2004, from http://www.cal.org/projects/webtest/ Chalhoub-Deville, M. (2002). Technology in standardized language assessments. In R. B. Kaplan (Ed.), The Oxford handbook of applied linguistics (pp. 471-486). New York: Oxford University Press. Chalhoub-Deville, M., & Deville, C. (1999). Computer adaptive testing in second language contexts. Annual Review of Applied Linguistics, 19, 273-299. Chapelle, C. A. (2001). Computer applications in second language acquisition. UK: Cambridge University Press. Davidson, F., & Lynch, B. K. (2002). Testcraft: A teacher’s guide to writing and using language test specifications. New Haven, CT: Yale University Press. Dunkel, P. A. (1999a). Considerations in developing or using second/foreign language proficiency computer-adaptive tests. Language Learning and Technology, 2(2), 77-93. Dunkel, P. A. (1999b). Research and development of computer-adaptive test of listening comprehension in the less commonly taught language Hausa. In M. Chalhoub-Deville (Ed.), Issues in computer-adaptive testing of reading proficiency: Vol. 10 (pp. 91-121). UK: Cambridge University Press.

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Eignor, D. (1999). Selected technical issues in the creation of computer-adaptive tests of second language reading proficiency. In M. ChalhoubDeville (Ed.), Issues in computer-adaptive testing of reading proficiency: Vol. 10 (pp. 167-181). UK: Cambridge University Press. El-Korashy, A.-F. (1995). Applying the Rasch model to the selection of items for a mental ability test. Educational and Psychological Measurement, 55(5), 753-763. Grabe, W. (2000). Reading research and its implications for reading assessment. In A. J. Kunnan (Ed.), Fairness and validation in language assessment: Vol. 9 (pp. 226–262). UK: Cambridge University Press. Haladyna, T. M. (2004). Developing and validating multiple choice test items (3rd ed.). Mahwah, NJ: Erlbaum. Hughes, A. (1989). Testing for language teachers. UK: Cambridge University Press. Janus, L. (2000). An overview of less commonly taught languages in the United States. NASSP Bulletin, 84(612), 25-29. Madhany, al-H. N. (2003). Arabicizing Windows: Enabling Windows applications to read and write Arabic. Retrieved April 10, 2004, from http://www.nclrc.org/inst-arabic3.pdf McNamara, T. F. (1990). Item response theory and the validation of an ESP test for health professionals. Language Testing, 7(1), 52-75. Mitzel, H. C., Lewis, D. M., Patz, R. J., & Green, D. R. (2001). The bookmark procedure: Psychological perspectives. In G. J. Cizek (Ed.), Setting performance standards: Concepts, methods, and perspectives (pp. 249-281). Mahwah, NJ: Erlbaum. Parshall, C. G., Spray, J. A., Kalohn, J. C., & Davey, T. (2002). Practical considerations in

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computer-based testing (pp. 71-91). New York: Springer. Rudner, L. (1998). Item banking. Washington, DC: ERIC Clearinghouse on Assessment and Evaluation. (ERIC Document Reproduction Service No. ED423310) Wainer, H., Dorans, N. J., Green, B. F., Mislevy, R. J., Steinberg, L., & Thissen, D. (2000). Future challenges. In H. Wainer (Ed.), Computerized adaptive testing: A primer (2nd ed., pp. 231-270). Mahwah, NJ: Erlbaum. Walker, G., & McGinnis, S. (1995). Learning less commonly taught languages: An agreement on the bases for the training of teachers (The Ohio State University Foreign Language Publications Series No. FLP01). Bryn Mawr, PA: National Council of Organizations of Less Commonly Taught Languages. (ERIC Document No. ED438729) Ward, A. W., & Murray-Ward, M. (1994). Guidelines for the development of item banks: An NCME instructional module. Educational Measurement: Issues and Practice, 13(1), 34-39. Young, R., Shermis, M. D., Brutten, S. R., & Perkins, K. (1996). From conventional to computeradaptive testing of ESL reading comprehension. System, 24(1), 23-40.

endnotes 1

An adaptable test is “one in which the examinee’s responses to earlier items in the test influence which subsequent items

2

3

must be answered in the same test” (Young, Shermis, Brutten, & Perkins, 1996, p. 23). Some tests are adaptable at the item level (fully adaptable tests), while others are adaptable after a group of items are administered (semiadaptable tests). In item-level adaptable tests, if an examinee gets an item right, the next item is more difficult; if the examinee gets an item wrong, the next item is easier (Young et al., 1996). In semiadaptable tests, the score an examinee receives on a group of items determines the difficulty level of the next group of items he or she will receive. For our purposes, a testlet is a group or “prearranged cluster” of items (Wainer et al., 2000, p. 238) that may be presented to an examinee based on his or her ability level (as predetermined by a placer test, for example). His or her outcome on the testlet determines the following path that the examinee will take. Assessments that are adaptable with testlets are semiadaptable tests. Item-level adaptable tests demand an extremely large item pool in order to function; therefore, thousands of examinees must be available to field test and validate the items (Chalhoub-Deville & Deville, 1999, p. 276). Resources are not available for the LCTLs to produce and validate item banks with thousands of items. Therefore, we believe semiadaptable tests with testlets (prearranged clusters or groups of items) are more appropriate for LCTL tests of this kind. They need fewer items and can be validated adequately on the smaller number of LCTL students available for field testing.

This work was previously published in Online Assessment and Measurement: Case Studies from Higher Education, K-12 and Corporate, edited by S. L. Howell & M. Hricko, pp. 82-97, copyright 2006 by Information Science Publishing (an imprint of IGI Global).

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Chapter 4.39

Diffusion of E-Learning as an Educational Innovation Petek Askar Hacettepe University, Turkey Ugur Halıcı Middle East Technical University, Turkey

IntroductIon Most of the discussions related to education are about technological innovations. Indeed as Rogers (1995) stated, we often use the word “innovation” and “technology” as synonyms. Technology is regarded as an agent of change in educational settings, and a quick analysis of the educational projects all over the world shows us that it is not possible to define a future vision of education without technology, especially e-learning, which brings two important concepts together: technology and learning. Therefore as a form of distance learning, e-learning has become a major instructional force in the world. Besides the technological developments, the last two decades have brought a tremendous increase in knowledge in education, particularly in learning. The emerging views of learning which should be taken into consideration for every

learning environment could be stated as follows: personalized, flexible, and coherent (learning is connected to real-life issues); not bounded by physical, geographic, or temporal space; rich in information and learning experiences for all learners; committed to increasing different intelligences and learning styles; interconnected and collaborative; fostering interorganizational linkages; engaged in dialogue with community members; accountable to the learner to provide adaptive instructional environments (Marshall, 1997). WWW is an environment that fits the new paradigm of learning and facilitates “e-learning” which faces a challenge of diffusion. Diffusion is defined by Rogers (1995) as the process by which an innovation is communicated through certain channels over time among the members of a social system. Therefore the adoption of WWW as a learning environment is influenced by the following set of factors: 1) the individuals’ percep-

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Diffusion of E-Learning as an Educational Innovation

tion of the attributes of e-learning, 2) the nature of the communication channels, 3) the nature of the social system, and 4) the extent of the change agents’ efforts in the e-learning. These are the variables that affect the diffusion of e-learning in the schools and countries.

e-LeArnIng And InstructIonAL desIgn E-learning not only opens up new ways of learning and teaching, but also leads to a new way of thinking and organizing learning content. Collaborations among different stakeholders cause new standards for design of knowledge on the Internet. In traditional computer-based instruction, content comes in units called courses. However a new paradigm for designing instruction, grounded in the object-oriented notion of computer science, is called “learning objects.” Learning object is defined by the Learning Technology Standards Committee (2002) of the Institute of Electrical and Electronics (IEEE) as any entity, digital or non-digital, that can be used, re-used, or referenced during technologysupported learning. The features of learning objects are self-contained, interactive, reusable, and tagged with metadata. By the use of learning objects, one can learn just enough, just in time, and just for them. Learning objects can be considered a movement within the field of e-learning, one aimed at the componentization of learning resources, with a view to reusability (Duchastel, 2004). The idea of educational software as a package is becoming outdated and making way for learning objects as a new way of designing instructional materials. In designing learning objects, the studies on multiple representation of knowledge become important since people have different learning styles and strategies. The associations between these two constructs are the main focus of the new instructional design principles. Therefore,

the development of learning objects and the way of creating teaching units are well suited for what we call the Information Age. A representation of knowledge could be decomposed into its parts, where the parts are far from arbitrary. Then they can be used and reused in a great variety of combinations, like a child’s set of building blocks. Every combination is meaningful and serves as an instructional whole. Holland (1995) compares building blocks to the features of the human face. The common building blocks are: hair, forehead, eyebrows, eyes, and so on. Any combination is different and may never appear twice. This analogy could be true of e-learning platforms, where learning objects are put together to make up a meaningful whole, which we call instructional materials. The five fundamental components of instructional design process are learners, content, objectives, methods, and assessment. Hence, for a systematic instructional design of a subject matter, the basic steps are: learner characteristic identification, task analysis, objectives, content sequencing, instructional strategies, message design, and instructional delivery and evaluation. The awareness of learner differences with respect to entry competencies, learning styles and strategies, motivation, and interest are critical. However it is difficult to accomplish this task by using ongoing approaches. Indeed, new technologies, if used properly, enable us to make the lessons more individualized. The Learning Objects Metadata Working Group (IEEE, 2002) stated its goal as: to enable computer agents to automatically and dynamically compose personalized lessons for an individual learner. This leads a paradigm shift to approaches to instructional design. As Wiley (2001) stated, a problem arose when people began to actually consider what it meant for a computer to “automatically and dynamically compose personalized lessons.” It seems that the idea of learning objects is challenging, but opens to new concepts, strategies, and research areas in the instructional design process.

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e-LeArnIng And schooL MAnAgeMent For most of the last two decades, technology has been implemented in schools, and its potential to change the educational systems has been argued for. There are tremendous efforts to encourage the integration of computers and Internet into schools. However, in one of the diffusion studies conducted by Askar and Usluel (2001), two paths to the adoption of computers are presented. One path is related to the use of technology in the school management system; the other one is related to the use of technology in the teaching and learning process. For many reasons the rate of adoption of computers in management applications is quicker than the learning-teaching applications. Indeed the concerns related to use of computers in the teaching-learning process are still at the awareness stage. On the other hand, the need for using computers and the Internet for management purposes is more relevant and seems more convenient for the current school system. Educators assert that the central purpose of school management systems should be to improve instructional program quality. In light of this idea, a typical configuration of a Web-based school management system designed—taking this idea into consideration—includes administration, assessment, and communication. The features are: student enrollment, attendance, registration, test scores, grades and other record-keeping tasks, formative and summative evaluation, and feedback to parents and teachers about student learning and performance. In addition, new online management systems include item- banking capability for adaptive testing and online learning modules.

e-LeArnIng And the coMMunIty The modern world requires individuals and communities to be able to continually develop and

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utilize different skills and knowledge. There is growing consensus among OECD countries that modern economies cannot afford a significant number of uneducated people (OECD, 2000). However, education systems throughout the world are ill equipped to address individual and community learning needs. The existing school system is not flexible for those who for some reason left school early. Distance education is a recognized solution all over the world for bridging the learning and education divide between the educated and poorly educated. It gives people the opportunity to continue their formal education. Despite the initial concerns that distance education might be lower in quality than traditional method of schooling, many forms of distance education are gaining acceptance (Belanger & Jordan, 2000). Therefore distance education is receiving positive attention from governments as a solution to the educational problem mentioned above. Also, the trend towards lifelong learning is universal. The transformations taking place in all societies require an increasing participation of individuals, an ability to innovate and solve problems, and a capacity to learn and go on learning (Mayor, 1994). Moreover, the term “open learning” is used to lower barriers that stand in the way of individuals and communities wishing to engage in different learning opportunities. One of the solutions for the above mentioned problems is learning centers, which are flexible learning organizations and which serve the learning needs of the individuals and communities. A school that is well equipped and organized could be opened during non-traditional school hours. Therefore, schools as learning centers can be critical resources to meet the growing need for distance education students and other community members. However, in highly centralized education systems, it is very difficult to organize schools for those other than the registered students. The rules and regulations for conventional school

Diffusion of E-Learning as an Educational Innovation

become real barriers for open learning environments.

While adopting the current technology for enhancing teaching and learning, advances in micro- and nano-technology push the limits of miniaturization, and of minimizing the costs and power of microelectronic components and micro-systems. Explorations of alternative materials are expected to allow organic flexible materials for displays, sensors, and actuators so that they can be placed anywhere and can take any shape. Furthermore it is expected that not only PCs, but also all our surroundings, will be interfaced. Instead of only “ writing and reading” in human-computer interaction, all senses are to be used intuitively. Information search will be context-based instead of “word “ based. Mobile and wireless devices will be used not only for voice transfer, but also for full multimedia (IST WP, 2002) As information and communication technologies change, open systems and services are to be developed in support of ubiquitous, experiential and contextualized learning, and virtual collaborative learning communities improving the efficiency and cost-effectiveness of learning for individuals and organizations, independent of time, place, and pace. Next-generation learning solutions are expected to combine cognitive and knowledge-based approaches, with new media having intelligence, virtual and augmented reality, virtual presence, and simulation (ISTC, 2001).

limits of e-learning environments, special care should be taken in educational and organizational frameworks. The stakeholders of the systems are students, teachers, principals, learners, and community. Their attitudes, needs, and expectations from e-learning are important issues for the change process. The innovation adoption variables of relative advantage, compatibility, visibility, ease of use, results demonstrability, and triability should be considered by school administrators seeking to increase the rate of adoption of e-learning within their organization (Jebeile & Reeve, 2003). Complexity is another issue to be considered. Fullan (1991) defines complexity