Handbook of Mobile Teaching and Learning [2nd ed. 2019] 9789811327650, 9789811327667

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Yu (Aimee) Zhang Dean Cristol Editors

Handbook of Mobile Teaching and Learning Second Edition

Handbook of Mobile Teaching and Learning

Yu (Aimee) Zhang • Dean Cristol Editors

Handbook of Mobile Teaching and Learning Second Edition

With 372 Figures and 95 Tables

Editors Yu (Aimee) Zhang WEMOSOFT Wollongong, NSW, Australia

Dean Cristol Department of Teaching and Learning The Ohio State University Lima, OH, USA

ISBN 978-981-13-2765-0 ISBN 978-981-13-2766-7 (eBook) ISBN 978-981-13-2767-4 (print and electronic bundle) https://doi.org/10.1007/978-981-13-2766-7 1st edition: © Springer-Verlag Berlin Heidelberg 2015 2nd edition: © Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Foreword

The spread and adoption of mobile technologies have been phenomenal in recent years. The number of smartphone users across the globe has reached three billion in 2018, with the Asia-Pacific region accounting for more than half of that number, according to a report by market researcher Newzoo. By 2021, the number of smartphone users will exceed 3.8 billion. The continued prodigious growth of social media coupled with unheralded connectivity through mobile devices means that mobile technologies are transforming the sociocultural landscapes which will shape our living, work, play, and learning. At the same time, the demand for teaching and learning at various levels of education and at various age groups has grown enormously. Many countries and regions are trying to provide quality education to prepare their citizens for employability. Universities and schools are providing e-learning courses, MOOCs, continuing education, and other training services to reach different segments of the populations that need learning and training. As economies are facing structural changes, industrial revolutions, and disruptions, they need to train and retrain workers for new jobs. Such an era brings about a rich ecology of those requiring and benefiting from the teaching and learning opportunities and those supplying the learning services. Pervasive mobile technologies play an essential role by enabling learning anywhere and anytime. And indeed for anyone, be it the preschool child trying to learn how to code to the retiree who is learning a new hobby, language, or skill. The mobile infrastructure has enabled many mobile apps that provide entrepreneurial teaching and learning opportunities. The proliferation of social media tools means that increasingly savvy users are tapping on online resources, communities, and tools to direct, support, and sustain learning by themselves. When mobile technologies are ready-at-hand as well as becoming low cost, there are more opportunities for learners to access, share, and construct knowledge readily in different settings and modes. The uniqueness of mobile learning makes it stand apart from access to traditional learning. Informed by the fields of the learning sciences, neurosciences, educational psychology, and educational technologies, designers of learning can make use of identified and proven affordances, or design new affordances to create learning and instructional spaces, scenarios, tasks, and experiences that foster relevant, deep, and meaningful learning. v

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Foreword

In recent years, mobile learning has also evolved with its deep integration with other emerging technologies. Multiple efforts abound in the integration or immersion of mobile learning with other technologies such as Virtual Reality, Augmented Reality, Artificial Intelligence, wearables, sensor-based technologies, and other forms of human–computer interfaces. At the same time, mobile learning has enabled the adoption, reinterpretation, and implementation of teaching models like seamless learning, the flipped classroom model, and MOOCs. Recently, mobile learning work has been complemented with approaches of learning analytics such as learning behavior analyses. A further case in point is that the UNESCO Mobile Learning Week of 2019 features a host of symposia, talks, and events, all mostly centered on the field of Artificial Intelligence. Given this expansive backdrop, this handbook is a timely contribution on the various multifaceted approaches, contexts, perspectives, applications, and research of mobile teaching and learning in various parts of the world. The chapters are organized into the themes of design, development, adoption, collaboration, evaluation, expectations, future, and cutting edge. The diverse perspectives as presented in the chapters within these themes will indeed support the handbook’s intent of presenting a multitude of mobile teaching and learning perspectives to inspire, investigate, and collaborate. The large collection of chapters in the handbook provides an opportunity to rise above after scanning and understanding the landscape of these teaching and learning designs, and interpreting them in their different contexts and perspectives. In terms of policy design and implementation, we can understand issues about quality learning, equity of access, lowering the barriers to adoption, sustained use in learning practices, scaling up, and research grand challenges. All these will add to our knowledge base on the foundational underpinning, feasible designs, and implementation challenges of mobile learning. National Institute of Education Nanyang Technological University Singapore

Professor Chee-Kit Looi

Preface to the Second Edition

A product of the new globalized educational systems is the development of indigenous high-technology capabilities such as mobile learning devices. These mobile technologies’ ubiquitous influence on learning is evident in all areas of teaching and learning, from formal and informal learning environments (preschools to universities), to small businesses and large corporations, to governmental and nongovernmental organizations. For most consumers, these mobile devices are relatively affordable and accessible, and often reinforce difficult concepts and a mechanism for collaboration. Potentially, mobile learning technology can level the learning field, due to the relatively low cost, and accessibility for most businesses, organizations, and households, including those that lack laptop or desktop computers or connection to the Internet. The following themes guide the book’s seven parts: design, development, adoption, partnerships, evaluation, future, and innovation. Each section includes historical and contextual perspectives, mobile teaching and learning empirical studies, and descriptions of current and potential studies and projects. Authors of this second edition reside in 21 countries allowing readers to experience mobile teaching and learning in a variety of global contexts and perspectives. The goal of the second edition of Handbook of Mobile Teaching and Learning is to present several mobile teaching and learning perspectives to inspire, investigate, and collaborate among scholars, practitioners, policymakers, and entrepreneurs. Wollongong, Australia Lima, USA August 2019

Yu (Aimee) Zhang Dean Cristol Editors

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Preface to the First Edition

Mobile technologies have been used in higher education for many years. They provide good solutions for teaching and learning and make learning available anywhere and anytime. The aim of this handbook is to collect and share the knowledge and experience from the designers’, developers’, teachers’, and students’ views and provide suggestions and advice for future mobile teaching and learning programs. This book includes six sections: design, development, adoption, collaboration, evaluation, and future of mobile teaching and learning technology in education. It includes different projects and practices across different countries and different cultures. The book provides in-depth background information and cases studies in high-technology teaching and learning and future expectations for new technology in higher education. The variety of projects and programs running in different countries helps boost innovation and discussion in future projects and practices. It also provides guidelines for future design and development of mobile applications for higher education.

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Acknowledgment

We would like to thank the many authors and editors who are responsible for making the book. Tina Shelton, Emmie Yang, Nivedita Baroi, D. Hinduja, and Nick Melchior from Springer provided their expertise for all the essential parts to make this book a reality. The tireless work by the section editors provided the coordination, organization, and editing for such a monumental task: Dr. Belinda Gimbert, Dr. Hea-Jin Lee, Dr. Real Moore, Dr. Yanguo Jing, Dr. Rob Power, Dr. Kshama Pandey, and Jun Hu. The group which is the backbone of the handbook are the amazing authors from across the globe; they provided the fantastic stories, ideas, and research about a topic that we all believe in so passionately. We want to express our deepest sense of gratitude to each of you for your dedication and persistence to make the handbook possible.

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List of Terms

3G

4G 5G ACCC

ACIF

ACMA

ADMA ADSL

ADSL 2+

AI AMPS

Third-generation networks, which are high-capacity radio access wireless networks providing enhanced data services, improved Internet access and increased voice capacity The fourth generation of mobile phone communication technology standards Next-generation improved wireless network deployed in 2018 Australian Competition and Consumer Commission, the government body responsible for administering price caps related to Telstra and for regulating competition policy, anticompetitive conduct, or unfair business practices and enforcing the Competition and Consumer Act 2010 Australian Communications Industry Forum is an independent body established by industry to manage telecommunications self-regulation Australian Communications and Media Authority, which came into existence on 1 July 2005, is responsible for the regulation of broadcasting, radio communications, telecommunications, and online content Australian Direct Marketing Authority is the peak trade association representing the direct marketing industry Asymmetric Digital Subscriber Line, a technology used to transmit data at fast rates (between 16 kbit/s and 640 kbit/s up-stream; up to 8 Mbit/s downstream) Successor product to ADSL that raises the maximum data rate to 16 Mbit/s (downstream) or 1 Mbit/s (upstream) Artificial Intelligence First Generation Technology Advanced Mobile Phone System, a mobile telephone system predominantly based on analogue transmission xiii

xiv

AMTA

Analogue

Android App Store AR

ARPU

ASP Asynchronous Bandwidth

Base Station

Big data analytics

Blended-learning Blog Bluetooth

bps Broadband

List of Terms

Australian Mobile Telecommunications Association is the national body representing the mobile telecommunications industry in Australia The term used to describe the continuously variable wave form nature of voices and other signals. A signal for which the amplitude (strength) and frequency (tone) vary continuously A popular smartphone OS from Google Apple applications online store Augmented reality allows users to see digital information on the physical world, which combines virtual objects and physical environment together Average Revenue Per User. The ratio of service revenues in a given period to the average number of wireless subscribers in the same period. It is presented on a monthly basis Application Service Providing, a service that enables enterprises to lease IT applications Interactions happen at different time Denotes the width of the frequency band used to transmit data. The broader the bandwidth, the faster the connection Part of the infrastructure essential for network operation, base stations contain the radio equipment which serves the “cell” The process of analyzing and identifying hidden patterns embedded in large amounts of data by using various methodologies from multiple areas such as machine learning, pattern recognition, artificial intelligence, and statistical theories and principles A learning method combined with traditional face-toface learning and online learning A personal online journal A system that allows the interrelated communication between mobile phones and stationery devices (such as computers) Bits per second. Basic unit of measurement for serial data transmission capacity Broadband is a general term that refers to high-speed connections such as cable, ADSL, and satellite. For broadband services, Internet access is not timebased as it is an “always on” connection, the exception being the uplink for satellite

List of Terms

Capex

Carrier

CDMA

Churn CJV Cloud computing CND Content Provider CSP

DCITA DE DGP DGT DSLAM

Digital

DIY DVB-H

ECS EDGE

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Capital Expenditure. Accrued capital expenditures related to the expansion of the telecommunications infrastructure In very general terms, a carrier provides the physical infrastructure used to supply carriage services to the public Code Division Multiple Access is a type of digital mobile service that differs from GSM digital. CDMA replaced the analogue service The process of transferring customer accounts between service providers in Australia Contractual joint ventures Delocalized resources and computing activities to an online server from a service provider Calling Number Display is a service that allows a caller’s number to be viewed by the person receiving the call A company that provides services to mobile phone users or network operators Carriage service provider in Australia. Person supplying or proposing to supply certain carriage services, including a commercial entity acquiring telecommunications capacity or services from a carrier for resale to a third party The Department of Communications, Information Technology and the Arts in Australia Distance learning is learning activities via long distance Directorate General of Posts of China Directorate General of Telecommunications of China Digital subscriber line access multiplexer is a piece of infrastructure at the exchange that allows for ADSL and a standard phone service to be provided on the same line The representation of a signal in the form of a stream of binary numbers rather than as an analogue electrical signal Do It Yourself Digital Video Broadcasting–Handheld, a transmission standard that enables users to receive digital TV channels on their mobile phones Enterprise Communication Services Enhanced Data Rates for GSM Evolution, modulation on the air interface to enhance data rates in GSM (Global System for Mobile Communications) and TDMA (Time Division Multiple Access) networks

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EJV ET F2F or FTF Generation Y

GHz (gigahertz) GPRS GSAs GSM HCS HCI HSDPA

i-mode ICT ICV IEEE Interconnection

Internet/intranet

iOS IOT IP IPTV ISDN

ISP

IT Lab ITU IVR

List of Terms

Equity joint ventures Emerging technologies include cloud computing, mobile technology, and new developed technologies Face-to-face teaching and learning or traditional teaching The generation born between 1982 and 1995 is also known as Generation Why, Generation Next, the www generation, the Millennium Generation, or Echo Boomers One billion hertz General Packet Radio Service, technology allowing higher data transmission rates in GSM networks Global strategic alliances Global System for Mobile Communications, global digital mobile communication standard Home Communication Services Human computer interface or user’s interface (UI) High-Speed Downlink Packet Access, packet-based protocol that enhances data rates in UMTS networks and lifts transmission speeds into the megabit range A customized packet-based mobile service Information and Communication Technology International cooperative venture Institute of Electrical and Electronics Engineers Term used to denote the connections between networks run by various providers, as regulated by the German Telecommunications Act The Internet is a worldwide Internet Protocol (IP)–based computer network that has no central network management. By contrast, intranets are managed IP networks that can be accessed only by specific user groups iPhone/iPad operating systems of Apple Inc. Internet of Things Internet Protocol Internet Protocol television, a system where a digital television service is delivered using the Internet Protocol Integrated Services Digital Network integrates telecommunications services such as telephone, fax, and data communication in one single network Internet Service Provider offers various technical services that are required to use or operate Internet services, usually in return for a fee IT laboratory International Telecommunications Union Interactive Voice Response, a service for mobile voice talk or other services

List of Terms

Java Kbps LCS

LMS M-commerce

MALL Mbit/s MBD MII MISP Micro-credentialing MMS

MNE M-learning Mobile Internet

Mobile payment/wallet

Mobile TV

MOOC MPT MSP Multimedia

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An industry standard object-oriented language and virtual machine Kilobits (thousands of bits) per second Local carriage service. This is where the access provider provides the wholesale or network elements of local calls, and the access seeker provides the retail elements such as billing Learning Management Systems Mobile commerce, generated after electronic commerce based on mobile network and wireless technologies (e.g., ring tones, icons, wallpapers, games, and premium SMS for reality TV voting and competitions) Mobile-assisted language learning Megabits per second, unit of data transmission speed Mobile broadband devices such as tablets and smartphones Ministry of Information Industry of the People’s Republic of China Managed Internet Service Provider A pedagogical practice that splits up learning programs into smaller sized units Multimedia Message Service allows the transmission of various media such as text, image, animations, and video and audio clips in a single message Multinational enterprise Mobile learning or m-learning is the learning activity on mobile devices or learning anytime and anywhere Mobile customers can gain wireless access to the Internet anytime and anywhere by using wireless terminals such as mobile handsets and mobile Internet terminals An integrated mobile payment service can be classified as remote payment and on-site payment, which provides customers with functions such as recharging, payment, and enquiries through RFID, WWW, SMS/MMS, etc. Mobile TV is expected to drive margins and 3G penetration for carriers. Popular forms of mobile TV are expected to be news clips, sport highlights, music video clips, and “mobisodes” (shows specially made for mobile handsets) Massive Open Online Courses Ministry of Posts and Telecommunications of China Managed Service Provider Term used to denote the real-time integration of text with still images and graphics, video, and sound

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MLP MTE Naive Bayes classifier NN

Number portability

Objective-C OER Packet switching

PCS PDA Prepaid

Polyphonic

Postpaid

Premium services PTT

Real (or true) tones RF RIA Roaming

List of Terms

Multi-layer Perception is a method used in computing intelligence to train the system Mobile Teaching Environment A Naïve Bayes classifier is a simple probabilistic classifier based on applying Bayes’ theorem Artificial neural networks are composed of interconnecting artificial neurons to mimic the properties of biological neurons Portability is an arrangement that allows subscribers of a telecommunications service to change carriers without having to change their number Primary program language for iOS and MacOS software development Open educational resources A method of transmitting messages by subdividing them into short packets containing the data and a destination address. Each is passed from source to destination through intermediate nodes which direct each packet onward, not necessarily by the same route. The packets are reassembled into the original message at the receiving end Personal Communication Services A personal digital assistant is also known as a palmtop computer, or personal data assistant In contrast to postpaid contracts, prepaid communication services are services for which credit has been purchased in advance with no fixed-term contract obligations Polyphonic ring tones vary in specification from phone to phone, but all polyphonic phones support the playing of more than one note together, so a ring tone is generally more musical Subscriber that has a contract for the use of airtime. The client has no need of activating airtime, it is done so immediately A carriage service or a content service using a number with a prefix starting with “190” in Australia Push to Talk (PPT) offers consumers the ability to talk to another individual or group without having to make additional calls Ring tones that are an extract from patented music Radio frequency Rich Internet application with multimedia and interactive contents Roaming allows customers to use their mobile phones on other networks (other than the one for which they

List of Terms

Social media

SMS SOC Spam Spectrum SWOT Synchronous TDD modulation

TDMA TIO

TTS UI UMTS Value-added services

Virtual Private Network

W-CDMA

VDSL

VMNOS VOIP

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currently pay). Roaming can be national wide or international Social media such as Facebook, Twitter, WeChat, and LinkedIn are combined with mobile technology in teaching and learning to provide instant communication and supports to students Short Message Service (SMS) enables mobile phones to send and receive text messages System on Chip Unsolicited marketing e-mail and SMS messages to mobile phones The bandwidth of a communications system expressed in terms of the frequencies it can carry Strengths, weaknesses, opportunities, and threats Interactions happen at the same time Time Division Duplexing, a broadband transmission method where the sending and receiving channels use the same frequency but at different times Time division multiple access The Telecommunications Industry Ombudsman (TIO) is a free and independent service for residential customers and small business in Australia that can help them resolve complaints about phone and Internet problems Text-to-speech applications User’s interface, the designed page for users Universal Mobile Telecommunications System, thirdgeneration international mobile communication standard Services provided over a public or private network which, in some way, add value to the basic carriage services (such as storing and forwarding messages) A software defined network offered by telephone carriers for voice and data communications among multiple sites. The network provides the appearance of a private network, except that it makes use of the public switched network rather than physically dedicated leased lines Wideband Code Division Multiple Access, a technology for wideband digital radio communications of Internet, multimedia, video, and other capacity-demanding applications Very high bit rate Digital Subscriber Line, a new technology used to transmit exceptionally high data rates (5 Mbit/s upstream, 50 Mbit/s downstream) Virtual Mobile Network Operators Voice over Internet Protocol, technology used to make telephone calls via the Internet

xx

VR Wallpaper WAP Web 2.0 Wearable devices Wholesale

WIKI WIL WLAN

Wi-Fi Wi-MAX

WOS WTO

Xcode

List of Terms

Virtual reality provides virtual environment for teaching and learning Wallpaper is the background of the mobile phone display Wireless Application Protocol, a service for mobile Internet access It uses technology beyond the static pages of earlier Web sites. It is widely adopted in online teaching and learning Wearable devices such as glasses and smart watch provide extra functions to users with mobile technologies The business of selling services to third parties who in turn sell them to their own end users either directly or after further processing Wikipedia, a website for users to add and edit learning content Work integrated learning Wireless Local Area Network, wireless networks for mobile Internet access. The network can also connect multiple computers to each other or to a central information system, a printer, or a scanner Wireless Fidelity, based on 2.5G technology Worldwide Interoperability for Microwave Access, a telecommunications technology aimed at providing wireless data over long distances in a variety of ways, from point-to-point links to full mobile cellular type access. It is based on the IEEE 802.16 standard Wholly owned subsidiary The World Trade Organization (WTO) deals with the global rules of trade between nations. Its main function is to ensure that trade flows as smoothly, predictably, and freely as possible Official integrated development environment for iOS and MacOS software programing

Contents

Volume 1 Part I Design of Mobile Teaching and Learning in Higher Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Design of Mobile Teaching and Learning in Higher Education: An Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Robert Power

2

Characteristics of Mobile Teaching and Learning . . . . . . . . . . . . . Yu (Aimee) Zhang

3

Transformation of Traditional Face-to-Face Teaching to Mobile Teaching and Learning: Pedagogical Perspectives . . . . . . . Jan Turbill

4

Flexible Spaces and Sustainable Opportunities: Designing Online Professional Learning for Sessional Teachers . . . . . . . . . . . Bonnie Amelia Dean, Kathryn Harden-Thew, Janine Delahunty, and Lisa Thomas

1

3 13

35

49

5

Business Models for Mobile Learning and Teaching . . . . . . . . . . . Cassey Lee

6

Micro-credentialing in Mobile Learning: Implications for Impactful Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ekaterina Pechenkina

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Applying Open-Book-Open-Web Assessment in Postgraduate Accounting Subject: Flipping Test . . . . . . . . . . . . . . . . . . . . . . . . . Corinne Cortese, Sanja Pupovac, and Lina Xu

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7

8

Use of Mobile Devices for Learning and Student Support in the Pacific Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibhya Sharma, Pritika Reddy, Emmenual Reddy, Swasti Narayan, Vineet Singh, Raneel Kumar, Ravishel Naicker, and Rajnesh Prasad

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109

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Contents

9

Parental Education: A Missing Part in Education . . . . . . . . . . . . . Yu (Aimee) Zhang

10

Design and Implementation of Chinese as Second Language Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yu (Aimee) Zhang, Wangweilai Xiang, and Qifang Xue

11

12

The Graduation Game: Leveraging Mobile Technologies to Reimagine Academic Advising in Higher Education . . . . . . . . . . . Tressa M. Haderlie, Apoorva Chauhan, Whitney Lewis, and Breanne K. Litts Learning from Social Impact Games to Support Integration into Middle School Classrooms . . . . . . . . . . . . . . . . . . . . . . . . . . . . Renee E. Jackson and Emily Sheepy

13

Design Considerations for Mobile Learning . . . . . . . . . . . . . . . . . . Jason Haag and Peter Berking

14

Mobile Learning and Engagement: Designing Effective Mobile Lessons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kimberly Vincent-Layton

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161

179

199 221

241

15

Framework for Design of Mobile Learning Strategies . . . . . . . . . . Oscar R. Boude Figueredo and Jairo A. Jimenez Villamizar

16

Foreign Language Teachers as Instructional Designers: Customizing Mobile-Assisted Language Learning Technology . . . Michael Barcomb, Jennica Grimshaw, and Walcir Cardoso

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Learning and Researching Across Places in Mobile City Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deborah Silvis, Jeremiah Kalir, and Katie Headrick Taylor

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Mobile Learning and Education: Synthesis of Open-Access Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Teresa Cardoso and Renato Abreu

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17

18

Part II Development of Mobile Application for Teaching and Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

20

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Development of Mobile Application for Higher Education: An Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yu (Aimee) Zhang and Jun Hu

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A Novel Education Pattern Applied to Global Crowd of All Ages: Mobile Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fosse (Jing) Zhang

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Contents

21

Study on Networked Teleoperation Applied in Mobile Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qiongjie Luo, Haiping Du, and Jun Hu

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359

22

SmartLab Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hu Yin and Jun Hu

371

23

Mobile Learning Initiatives in Nursing Education . . . . . . . . . . . . . Sharon Rees, Clint Moloney, and Helen Farley

387

24

Construction Safety Knowledge Sharing via Smartphone Apps and Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rita Yi Man Li and Herru Ching Yu Li

25

26

Developing an Adaptive Mobile Tool to Scaffold the Communication and Vocabulary Acquisition of Language Learners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carrie Demmans Epp Development of Application to Learn Spanish as a Second Language: Lessons Learned . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Izabel Rego de Andrade

27

Tutors in Pockets for Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . Yu (Aimee) Zhang and Jun Hu

28

Development of Chinese Character-Writing Program for Mobile Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yu (Aimee) Zhang and Jun Hu

Part III Adoption of Mobile Technology in Teaching and Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

30

403

417

445 461

479

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Adoption of Mobile Technology in Higher Education: An Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hea-Jin Lee and Jun Hu

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Mobile Learning in Southeast Asia: Opportunities and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Helen Farley and Helena Song

503

31

The Development of Mobile Learning in China’s Universities . . . . Nan Ma, Xiaofen Zhang, and Yu (Aimee) Zhang

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32

Accessibility Challenges in Mobile Learning . . . . . . . . . . . . . . . . . Linda Robson

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33

Mobile Education via Social Media: Case Study on WeChat . . . . . Yu (Aimee) Zhang

565

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34

35

36

37

38

Contents

Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts . . . . . . . . . . . . . . . . . . . . Wendy L. Kraglund-Gauthier

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Mobile Web 2.0 Tools and Applications in Online Training and Tutoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zuzana Palkova

609

Tangible Objects and Mobile Technology: Interactive Learning Environments for Students with Learning Disabilities . . . . . . . . . . Elif Polat, Kursat Cagiltay, and Necdet Karasu

635

Use of Mobile Digital Technology and iPod Touches in Physical Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Crawford and Patricia Fitzpatrick

655

Gatekeepers to Millennial Careers: Adoption of Technology in Education by Teachers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Debra L. White

665

39

Trust/Distrust: Impact on Engaged Learning . . . . . . . . . . . . . . . . . Martha J. Hoff

40

Evidence-Based Teaching and Real-Time Assessment: Adoption of Mobile Interactive Apps . . . . . . . . . . . . . . . . . . . . . . . Muztaba Fuad

41

Instructional Design Principles for Mobile Learning . . . . . . . . . . . Eun-Ok Baek and Qi Guo

679

697 717

Volume 2 Part IV Higher Education Partnerships with Nonprofit and Profit Organizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Higher Education Partnerships with Nonprofit and Profit Organizations: An Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . Belinda Gimbert

43

Trends in Mobile Learning: 2010–2017 . . . . . . . . . . . . . . . . . . . . . Moonsun Choi and Dean Cristol

44

P-16 Partnerships for Learning with Mobile Technologies: Design, Implement, and Evaluate . . . . . . . . . . . . . . . . . . . . . . . . . . Belinda Gimbert, Lauren Acree, Kui Xie, and Anika Ball Anthony

45

Mobile Technologies for Teaching and Learning . . . . . . . . . . . . . . Rajiv Ramnath and Ajay Kuriakose

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741 747

763 791

Contents

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46

Mobile Devices for Preschool-Aged Children . . . . . . . . . . . . . . . . . Rachel Ralph and Stephen Petrina

47

Highs and Lows of Mobile Digital Technology Integration in Kindergarten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Monica McGlynn-Stewart, Nicola Maguire, Emma Mogyorodi, Leah Brathwaite, and Lisa Hobman

48

49

50

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1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lauren Eutsler

873

Cross-Country University Collaboration Barriers and Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yongzheng Liu, Ziqui Zhang, and Yu (Aimee) Zhang

889

Evaluation of Mobile Teaching and Learning Projects . . . .

Evaluation of Mobile Teaching and Learning Projects: An Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Raeal Moore

52

Student Feedback in Mobile Teaching and Learning . . . . . . . . . . . Yu (Aimee) Zhang

53

Moving Towards the Effective Evaluation of Mobile Learning Initiatives in Higher Education Institutions . . . . . . . . . . . . . . . . . . Helen Farley, Angela Murphy, Nicole Ann Todd, Michael Lane, Abdul Hafeez-Baig, Warren Midgley, and Chris Johnson

54

55

56

57

825

Role for Instructional Technology Leadership in K-12 Public Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thomas Edelberg

Part V 51

809

909

911 917

939

Internet-Based Peer-Assisted Learning: Current Models, Future Applications, and Potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tairan Kevin Huang, Jin Cui, Corinne Cortese, and Matthew Pepper

959

Mobiles, Online Learning, and the Small Group Discovery Classroom: Reflections from South Australia . . . . . . . . . . . . . . . . . Melissa Nursey-Bray

977

Mobile-Assisted Language Learning: How Gamification Improves the Learning Experience . . . . . . . . . . . . . . . . . . . . . . . . . Izabel Rego de Andrade

991

Service-Learning Application in an M-Learning Course . . . . . . . . 1007 Margaret Sass

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Contents

58

Technology-Mediated Assessment in Crossover Learning Assessment Design (CLAD): A Case from Sustainable Engineering Design Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1023 Fariha Hayat Salman and David R. Riley

59

Adapting to Change: A Reflective History of Online Graduate Certificate and Its Implications for Teaching Geography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1043 Melissa Nursey-Bray and Robert Palmer

Part VI Expectations from Future Technologies in Higher Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1059

60

Expectations from Future Technologies in Higher Education: An Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1061 Kshama Pandey

61

M-Learning: Visible Approach for Invisible World . . . . . . . . . . . . 1067 Kshama Pandey

62

Problems and Challenges of Mobile Learning in Nigerian University System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1085 David Jimoh Kayode, Afusat Titilayo Alabi, Abayomi Olumade Sofoluwe, and Rhoda Olape Oduwaiye

63

Expectations from Future Technologies and E-Learning in Higher Education in Albania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1101 Irena Nikaj

64

Mobile Technologies and Learning: Expectations, Myths, and Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1117 Lina Petrakieva and David McArthur

65

Advanced Image Retrieval Technology in Future Mobile Teaching and Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1133 Lei Wang and Yu (Aimee) Zhang

66

Mobile Learning Beyond Tablets and Smartphones: How Mobile and Networked Devices Enable New Mobile Learning Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1149 Daniel Stoller-Schai

67

M-Learning and U-Learning Environments to Enhance EFL Communicative Competence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1169 Soraya Garcia-Sanchez and Carmen Lujan-Garcia

68

How Irish Postgraduate Students Use Mobile Devices to Access Learning Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1189 Ann Marcus-Quinn and Yvonne Cleary

Contents

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Enhancing Student Learning Experience with Practical Big Data Analytics Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1205 Eric P. Jiang

Part VII

VR, AR, and Wearable Technologies in Education . . . . . .

1221

70

VR, AR, and Wearable Technologies in Education: An Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1223 Yanguo Jing

71

Mobile AR Trails and Games for Authentic Language Learning . . . 1229 Mark Pegrum

72

Virtual Reality and Its Applications in Vocational Education and Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1245 Zuzana Palkova and Ioannis Hatzilygeroudis

73

Location and Place: Two Design Dimensions of Augmented Reality in Mobile Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1275 Apoorva Chauhan, Whitney Lewis, and Breanne K. Litts

74

Wearable Technologies as a Research Tool for Studying Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1291 Jimmy Jaldemark, Sofia Bergström-Eriksson, Hugo von Zeipel, and Anna-Karin Westman

75

Augmented Reality and 3D Technologies: Mapping Case Studies in Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1307 Teresa Cardoso, Teresa Coimbra, and Artur Mateus

76

Employing Virtual Reality to Teach Face-Based Emotion Recognition to Individuals with Autism Spectrum Disorder . . . . . 1327 Rebecca Hite, Wesley Dotson, and Rebecca Beights

77

Augmented Reality in Education Joseph M. Reilly and Chris Dede

78

Mobile-Based Virtual Reality: Why and How Does It Support Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1353 Karen Ladendorf, Danielle Eve Schneider, and Ying Xie

79

VR and AR for Future Education . . . . . . . . . . . . . . . . . . . . . . . . . 1373 Ken Kencevski and Yu (Aimee) Zhang

80

Review of Virtual Reality Hardware Employed in K-20 Science Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1389 Rebecca Hite, Gina Childers, and M. Gail Jones

. . . . . . . . . . . . . . . . . . . . . . . . . . 1337

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1401

About the Editors

Dr. Yu (Aimee) Zhang is the CEO and founder of the World Educators Mobile – WEMOSOFT and Wolong School in Wollongong, Australia. She was a Lecturer in the University of Wollongong School of Economics from 2009 to 2014. She has been teaching economics for more than 5 years. Her innovative teaching and learning with mobile technology received many awards and grants from the university and faculty. Her 5 years working experience in telecommunication industry as remote educational system designer, developer, project manager, and quality assurance manager in different companies also contributed to the cross-discipline innovations. Passionate in both teaching and mobile technology, she designed and developed the mobile application “Tutors in Pockets” for mobile teaching and learning for both iOS and Android mobile devices. She also collaborated with different universities and institutions on mobile projects in higher education teaching and learning. Dean Cristol Ph.D. is Associate Professor in the Department of Teaching and Learning in the College of Education and Human Ecology at the Ohio State University. His area of research is to establish and maintain university-school partnerships, professional development in educational settings for marginalized students and teachers, and preparing people to teach and learn in twenty-first-century educational environments. Currently, he is using this research framework to integrate technology into learning contexts, specifically mobile learning and technology. He has researched in many educational settings, from large and small school systems in the United States to Mexican preschools and xxix

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About the Editors

schools in Bangladesh, working closely with governmental and nongovernmental organizations. He has participated in several national and state partnering grants; published his research in numerous international, national, and state journals; published several chapters in books; presented his research at several international, national, and state conferences; and served on several journal editorial boards. Currently, he is an Associate Editor for Theory Into Practice and a member of the Executive Committee for the International Association for Mobile Learning.

About the Section Editors

Belinda Gimbert Ph.D. is Associate Professor, Educational Administration, Department of Educational Studies, the Ohio State University. Her research addresses strategic management of human resources in chronically, low performing and hard-to-staff urban and rural school systems. Gimbert teaches course related to strategic management of human capital/talent management, introduction to educational administration, and K-12 supervision. She taught mathematics and computing science for 15 years in secondary schools (Grades 7–12) in rural New South Wales, Australia, and administered in Human Resources and Staff Development with Newport News Public Schools, VA. Dr. Gimbert led the project KNOTtT – Kansas, Nevada, Ohio and Texas Transition to Teaching (2007–2013) that hired and retained 560 new teachers. She was the Principal Investigator for Mobilizing National Educator Talent (2011–2017), a partnership of colleges/universities and school districts in 12 states, the District of Columbia, and Puerto Rico that transitioned 1,656 teachers to state certification, while addressing the national issue of teacher quality. Dr. Gimbert was also a Co-Principal Investigator for a Teacher Quality partnership, Project ASPIRE (2009–2014) that prepared new teachers through a school-university residency OH program. Currently, Dr. Gimbert is the Project Director/PI for the national project Educators and Families for English Language Learners (2017–2022) that partners with charter schools in the District of Columbia, Harris County Department of Education (TX), and Columbus City Schools (OH) and is sponsored by US ED’s Office of English Language Acquisition. Dr. Gimbert has

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About the Section Editors

authored/coauthored 80 journal articles and evaluation reports and delivered more than 150 local, state, and national presentations. Jun Hu was awarded a Master of Computer Science with Distinction from University of Wollongong (Aus- tralia) in 2008 and a Bachelor of Computer Science and Software Engineering from Beijing Information Science and Technology University (formerly known as Beijing Information Technology Institute, P.R. China) in 2001. From 2001 to 2003, he was a Development Manager at Tsinghua Tongfang Co., Ltd. (Beijing, P.R. China). Then he led the Research and Development Department at Beijing Oriental Caesar Technology Co., Ltd. (Beijing, P.R. China) from 2003 to 2005. From 2005 to 2006, he was the Group Leader of the wireless application team at Techfaith Wireless Communication Technology Co., Ltd. (NASDAQ: CNTF, Beijing, P.R. China). From 2008 to 2010, he worked at Information Technology Services (ITS), University of Wollongong (NSW, Australia). Since late 2010 he is a computer systems officer at Faculty of Engineering and Information Sciences, University of Wollongong (NSW, Australia). He developed various software including distance cyber education system, short messaging service system (SMS), multimedia messaging system (MMS) on personal digital assistant (PDA), interactive applications and games for Wireless Application Protocol (WAP) website; Java 2 Platform, Micro Edition (J2ME); and Android and iOS devices. Now he is providing professional services to satisfy the teaching, learning, research, and administration requirements from the Faculty of Engineering and Information Sciences, University of Wollongong. His research interests include multimedia, artificial intelligence, and pattern recognition. Dr. Yanguo Jing is Associate Dean at Coventry University, UK. He has a Ph.D. (Heriot-Watt University), an M.Sc., and a first class B.Sc. (Hons.) in Computer Science. He has over 20 years’ teaching, research, and commercial experience. Yanguo is a Fellow of the British Computer Society, a Charter IT professional, and a Fellow of the Higher Education Academy in the UK. Yanguo is interested in using technologies (e.g., mobile and Internet) to support teaching and learning. He has over 10 years’ experience in facilitating online teaching in higher education. He chaired a number of

About the Section Editors

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national workshops on Teaching and Learning using Mobile and Tablet Devices. His work has led to a series of research papers in this area. Yanguo works very closely with industry, employers, and professional associations which enables him to teach students the most relevant workplace knowledge and to provide them with real-world case studies taken from research and industry projects, so that they can see the relevance to their future career. Yanguo is passionate about working with business to address digital skill shortages and work force upskilling. He has been instrumental in securing the successful bid for the £40M national Institute of Coding (IoC) in the UK, which aims to address digital skills shortages in the industry and to create a talent pipeline of appropriate digital skills from diverse backgrounds. Yanguo is interested in providing students opportunities to learn by applying their knowledge to real-life projects while at the university. He set up a Work-Related Learning framework, which has been adopted in a universitywide scheme in the UK. He was the Managing Director of a successful university software company which was set up to provide university computer science students real commercial work experience on live projects. Yanguo’s prime research interests are AI and data analytics. His recent research work focuses on the use of statistical and machine-learning methods to capture interaction and user behavior patterns that can be used to develop intelligent applications. This research has been applied in applications such as business analytics, sports analytics, and user behavior pattern recognition in social networks and extra-care/Assisted Living settings. He participated in a number of research and enterprise projects with sponsors and clients such as Cadent Gas, Pfizer, Welsh Government, KPIT, UK’s Comic Relief charity, and JISC in the UK. He has won a number of awards including a University Staff Excellency Award for Best Enterprise Initiative and a University Teaching Fellow Award recognizing his excellence in teaching and learning.

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About the Section Editors

Hea-Jin Lee Ph.D. is Associate Professor of Mathematics Education in the Department of Teaching and Learning at the Ohio State University at Lima. Lee’s research areas are related to mathematics teacher education, including improving teacher competencies, developing professional development programs, teaching mathematics utilizing digital resources, and culturally responsive teaching of mathematics. She is also interested in the area of teaching mathematics to students with special needs. Dr. Lee has served as the Principal Investigator (PI) on a number of state-funded projects, such as Discovery programs and Improving Teachers Quality programs. She has developed and administrated more than 10 successful professional development programs for mathematics teachers. Raeal Moore Ph.D. is Senior Research Scientist at ACT, Inc. in the Department of Research. Her area of research is identifying best practices in K-12 and higher education. She has over a decade of experience conducting evaluation studies of critical educational initiatives. She focuses on LEA program implementation and evaluation, value-added professional development, and school reform. She has evaluated multilevel projects such as the statewide Mathematics and Science Partnership (MSP) in Ohio, the federal Teacher Quality Partnership (TQP) initiative, the IES Striving Readers grant, and 21st Century Community Learning programs. She has participated in several state and national partnership grants, published research in national journals, and presented her research at several conferences, and is a member of a number of evaluation professional organizations. Dr. Kshama Pandey is Associate Professor in the Department of B.Ed./M.Ed., MJP Rohilkhand University, Bareilly. She has more than 13 years teaching experience. She has completed her M.Ed. from the University of Allahabad and also holds a postgraduate degree in Hindi. She has been awarded her D.Phil. degree from University of Allahabad. Her doctoral work relates to the Human Rights Understanding and Consciousness. Her research interests include ICT-based education, innovative learning pedagogy, and human rights and peace education. Her area of

About the Section Editors

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research is to prepare the students for a techno-oriented society without uprooting them from their values and cultural moorings. An international edited book Handbook of Research on Promoting Global Peace and Civic Engagement Through Education has been published by IGI Publication, USA. She is editorial board member of four international journals, i.e., Computers & Education, Elsevier; Independent Journal of Management & Production, Brazil; Sukimat Multidisciplinary Research Journal, University of Baguio, Philippines; and European Journal of Applied Social Science Research (EJASSR). She has published various research papers in national and international journals. Her various chapters have been published in edited books with national and international repute like Springer, IGI Global Publication, International Book Series, USA, etc. She has also secured best paper award for two research papers. Besides, she has presented 35 papers in international seminars/conferences and more than 70 in national seminars/conferences. She is a life member of various educational organizations. She also served as resource person in different workshops organized by NEUPA (National Institute of Educational Planning and Administration, India), NCERT (National Council of Educational Research and Training, India), CASE (Council for Advancement and Support of Education), and IASE (Institute of Advanced Studies in Education, India). Rob Power Ed.D. is the Manager of Learning Experience Design at Lethbridge College in Alberta, Canada. Rob has been working in the Education sector since 2001, and has taught at the K-12, college, undergraduate, and graduate levels. He has also been working as an instructional development specialist since 2013, and has served as an Instructional Developer with the College of the North Atlantic – Qatar, as the Leader of Online Learning with the Fraser Health Authority, as an Instructional Development Consultant with the British Columbia Institute of Technology, and as an independent instructional developer and an Adjunct Professor of Educational Technology for various Canadian higher education institutions. Since 2011, Rob has been actively involved in the mobile learning research community. His work has

xxxvi

About the Section Editors

included the development of the Mobile Teacher’s Sense of Efficacy Scale research instrument, and the Collaborative Situated Active Mobile (CSAM) learning design framework. Rob has also taken a leading role within the International Association for Mobile Learning (IAmLearn). In 2013, Rob served as the Project Manager and Conference Chair for the 12th World Conference on Mobile and Contextual Learning (mLearn 2013) in Doha, Qatar, where he was elected to the IAmLearn Executive Committee. Rob was elected President of the IAmLearn Executive Committee at mLearn 2017 in Larnaca, Cyprus. Rob has also served as a judge for the GSMA Global Mobile Awards (Best Educational Innovation category) since 2016. His research interests include teacher preparation for and pedagogical approaches to instructional design for mobile and ubiquitous learning.

Contributors

Renato Abreu LE@D, Elearning and Distance Education Lab, UID4372-FCTMCTES, Universidade Aberta (Open University of Portugal), Lisbon, Portugal Department of Laboratory Sciences and Community Health, Escola Superior de Tecnologia da Saúde de Lisboa, Instituto Politécnico de Lisboa, Lisbon, Portugal Lauren Acree Department of Educational Studies, Educational Administration, The Ohio State University, Columbus, OH, USA Afusat Titilayo Alabi Department of Educational Management, Faculty of Education, University of Ilorin, Ilorin, Kwara State, Nigeria Anika Ball Anthony Department of Educational Studies, Educational Administration, The Ohio State University, Columbus, OH, USA Eun-Ok Baek College of Education, California State University San Bernardino, San Bernardino, CA, USA Michael Barcomb Education, Concordia University, Montreal, QC, Canada Rebecca Beights Texas Tech University, Lubbock, TX, USA Sofia Bergström-Eriksson Mid Sweden University, Sundsvall, Sweden Peter Berking The Mobile Learning Research Team Advanced Distributed Learning (ADL) Initiative, Alexandria, VA, USA Leah Brathwaite George Brown College, Toronto, ON, Canada Kursat Cagiltay Faculty of Education, Computer Education and Instructional Technology Department, Middle East Technical University, Ankara, Turkey Teresa Cardoso LE@D, Elearning and Distance Education Lab, Department of Education and Distance Learning and Teaching, UID4372-FCT-MCTES, Universidade Aberta (Open University of Portugal), Lisbon, Portugal Walcir Cardoso Education, Concordia University, Montreal, QC, Canada Apoorva Chauhan Department of Computer Science, Utah State University, Logan, UT, USA xxxvii

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Contributors

Gina Childers Teacher Education, University of North Georgia, Dahlonega, GA, USA Moonsun Choi Center on Education and Training for Employment, The Ohio State University, Columbus, OH, USA Yvonne Cleary School of Languages, Literature, Culture and Communication, University of Limerick, Limerick, Ireland Teresa Coimbra LE@D, Elearning and Distance Education Lab, UID4372-FCTMCTES, Universidade Aberta (Open University of Portugal), Lisbon, Portugal Corinne Cortese School of Accounting, Economics and Finance, Faculty of Business, University of Wollongong, Wollongong, NSW, Australia S. Crawford Sports Studies and Physical Education, School of Education, University College Cork, Cork, Munster, Ireland Dean Cristol Department of Teaching and Learning, The Ohio State University, Lima, OH, USA Jin Cui School of Accounting, Economics and Finance, Faculty of Business, University of Wollongong, Wollongong, NSW, Australia Bonnie Amelia Dean Learning, Teaching and Curriculum, University of Wollongong, Wollongong, NSW, Australia Chris Dede Graduate School of Education, Harvard University, Cambridge, MA, USA Janine Delahunty Learning, Teaching and Curriculum, University of Wollongong, Wollongong, NSW, Australia Carrie Demmans Epp Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA EdTeKLA Research Group, Department of Computing Science, University of Alberta, Edmonton, PA, Canada Wesley Dotson Texas Tech University, Lubbock, TX, USA Haiping Du Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia Thomas Edelberg Instructional Systems Technology, Indiana University, Bloomington, Bloomington, IN, USA Lauren Eutsler University of North Texas, Denton, TX, USA Helen Farley Digital Life Lab, University of Southern Queensland, Toowoomba, QLD, Australia Oscar R. Boude Figueredo Academy Technology Center, La Sabana University, Chia, Cundinamarca, Colombia

Contributors

xxxix

Patricia Fitzpatrick Sports Studies and Physical Education, School of Education, University College Cork, Cork, Munster, Ireland Muztaba Fuad Department of Computer Science, Winston-Salem State University, Winston-Salem, NC, USA Soraya Garcia-Sanchez Department of Modern Philology, Translation and Interpreting, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain Belinda Gimbert Department of Educational Studies, Educational Administration, The Ohio State University, Columbus, OH, USA Jennica Grimshaw Education, Concordia University, Montreal, QC, Canada Qi Guo College of Education, California State University San Bernardino, San Bernardino, CA, USA Jason Haag The Mobile Learning Research Team Advanced Distributed Learning (ADL) Initiative, Alexandria, VA, USA Tressa M. Haderlie The Department of Psychology, Utah State University, Logan, UT, USA Abdul Hafeez-Baig School of Management and Enterprise, University of Southern Queensland, Toowoomba, QLD, Australia Kathryn Harden-Thew Learning, Teaching and Curriculum, University of Wollongong, Wollongong, NSW, Australia Ioannis Hatzilygeroudis University of Patras, Patras, Greece Rebecca Hite Curriculum and Instruction, Texas Tech University, Lubbock, TX, USA Lisa Hobman George Brown College, Toronto, ON, Canada Martha J. Hoff Department of Teaching and Curriculum, Warner School of Education and Human Development, University of Rochester, Rochester, NY, USA Jun Hu WEMOSOFT, Wollongong, NSW, Australia Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia Tairan Kevin Huang School of Accounting and Finance, Faculty of Business, Justice and Behavioural Science, Charles Sturt University, Port Macquarie, NSW, Australia Renee E. Jackson Temple University, Philadelphia, PA, USA Jimmy Jaldemark Mid Sweden University, Sundsvall, Sweden

xl

Contributors

Eric P. Jiang Department of Computer Science, Shiley Marcos School of Engineering, University of San Diego, San Diego, CA, USA Yanguo Jing Coventry University, Coventry, UK Chris Johnson Research School of Computer Science, Australian National University, Canberra, ACT, Australia M. Gail Jones Department of STEM Education, North Carolina State University, Raleigh, NC, USA Jeremiah Kalir Learning Design and Technology, School of Education and Human Development, University of Colorado Denver, Denver, CO, USA Necdet Karasu Faculty of Education, Special Education Department, Gazi University, Ankara, Turkey David Jimoh Kayode Department of Educational Management, Faculty of Education, University of Ilorin, Ilorin, Kwara State, Nigeria Ken Kencevski Devika World, Smart Building, University of Wollongong, Wollongong, NSW, Australia Wendy L. Kraglund-Gauthier St. Francis Xavier University, Antigonish, NS, Canada Faculty of Education, Yorkville University, Fredericton, NS, Canada Raneel Kumar Faculty of Science, Technology and Environment, University of the South Pacific, Suva, Fiji Ajay Kuriakose Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA Karen Ladendorf Educational Technology, Research and Assessment, Northern Illinois University, DeKalb, IL, USA Michael Lane School of Management and Enterprise, University of Southern Queensland, Toowoomba, QLD, Australia Whitney Lewis Instructional Teaching and Learning Sciences Department, Utah State University, Logan, UT, USA Hea-Jin Lee Faculty of College of Education and Human Ecology, The Ohio State University at Lima, Lima, OH, USA Cassey Lee Institute of Southeast Asian Studies, Singapore, Singapore Rita Yi Man Li Real Estate and Economics Research Lab, Hong Kong Shue Yan University, Hong Kong, China Department of Economics and Finance, Hong Kong Shue Yan University, Hong Kong, China

Contributors

xli

Herru Ching Yu Li School of Computer Science, University of St. Andrews, St. Andrews, UK Breanne K. Litts Instructional Teaching and Learning Sciences Department, Utah State University, Logan, UT, USA Yongzheng Liu New Zealand International Education Exchange and Trade Development and Immigration Services Co. Ltd, Levin, New Zealand Carmen Lujan-Garcia Department of Modern Philology, Translation and Interpreting, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain Qiongjie Luo Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia Macquarie University, Sydney, NSW, Australia Nan Ma College of Information Technology, Beijing Union University, Beijing, China Nicola Maguire George Brown College, Toronto, ON, Canada Ann Marcus-Quinn School of Languages, Literature, Culture and Communication, University of Limerick, Limerick, Ireland Artur Mateus CDRsp – Centre for Rapid and Sustainable Product Development, Polytechnic Institute of Leiria, Marinha Grande, Portugal David McArthur Learning Development Centre / School of Computing, Engineering, and the Built Environment, Glasgow Caledonian University, Glasgow, UK Monica McGlynn-Stewart School of Early Childhood, George Brown College, Toronto, ON, Canada Warren Midgley School of Linguistics, Adult and Specialist Education, University of Southern Queensland, Toowoomba, QLD, Australia Emma Mogyorodi Ryerson University, Toronto, ON, USA Clint Moloney School of Nursing and Midwifery, University of Southern Queensland, Toowoomba, QLD, Australia Raeal Moore ACT, Inc., Iowa City, IA, USA Angela Murphy Australian Digital Futures Institute, University of Southern Queensland, Toowoomba, QLD, Australia Ravishel Naicker Faculty of Science, Technology and Environment, University of the South Pacific, Suva, Fiji Swasti Narayan Faculty of Science, Technology and Environment, University of the South Pacific, Suva, Fiji

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Contributors

Irena Nikaj Faculty of Education and Philology, “Fan S. Noli” University of Korça, Korca, Albania Melissa Nursey-Bray Department of Geography, Environment and Population, Faculty of Arts, University of Adelaide, Adelaide, SA, Australia Rhoda Olape Oduwaiye Department of Educational Management, Faculty of Education, University of Ilorin, Ilorin, Kwara State, Nigeria Zuzana Palkova Department of Electrical Engineering, Automation and Informatics (TF), Slovak University of Agriculture in Nitra, Nitra, Slovakia Robert Palmer Department of Media, Faculty of Arts, University of Adelaide, Adelaide, SA, Australia Kshama Pandey Department of B.Ed./M.Ed., Faculty of Education and Allied Sciences, MJP Rohilkhand University, Bareilly, India Ekaterina Pechenkina Learning Transformations Unit, Swinburne University of Technology, Melbourne, VIC, Australia Mark Pegrum The Graduate School of Education, The University of Western Australia, Crawley, Perth, WA, Australia Matthew Pepper School of Management, Operations and Marketing, Faculty of Business, University of Wollongong, Wollongong, NSW, Australia Lina Petrakieva Learning Development Centre / School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK Stephen Petrina The University of British Columbia, Vancouver, BC, Canada Elif Polat Faculty of Education, Computer Education and Instructional Technology Department, Istanbul University – Cerrahpasa, Istanbul, Turkey Robert Power British Columbia Institute of Technology, Surrey, BC, Canada Rajnesh Prasad Faculty of Science, Technology and Environment, University of the South Pacific, Suva, Fiji Sanja Pupovac School of Accounting, Economics and Finance, Faculty of Business, University of Wollongong, Wollongong, NSW, Australia Rachel Ralph The University of British Columbia, Vancouver, BC, Canada Rajiv Ramnath Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA Emmenual Reddy Faculty of Science, Technology and Environment, University of the South Pacific, Suva, Fiji Pritika Reddy Faculty of Science, Technology and Environment, University of the South Pacific, Suva, Fiji

Contributors

xliii

Sharon Rees School of Nursing and Midwifery, University of Southern Queensland, Toowoomba, QLD, Australia Izabel Rego de Andrade Education Management, Serviço Nacional de Aprendizagem Industrial (SENAI-SP), São Paulo, SP, Brazil Campinas State University (Unicamp) – Campinas, São Paulo, SP, Brazil Joseph M. Reilly Graduate School of Education, Harvard University, Cambridge, MA, USA David R. Riley Architectural Engineering, College of Engineering, Pennsylvania State University, University Park, PA, USA Linda Robson The Open University, Milton Keynes, UK Fariha Hayat Salman Learning and Performance Systems, College of Education, Pennsylvania State University, University Park, PA, USA Margaret Sass Communication Department, College of Southern Idaho, Twin Falls, ID, USA Danielle Eve Schneider Educational Technology, Research and Assessment, Northern Illinois University, DeKalb, IL, USA Bibhya Sharma Faculty of Science, Technology and Environment, University of the South Pacific, Suva, Fiji Emily Sheepy Concordia University, Montréal, Canada Deborah Silvis Learning Sciences and Human Development, College of Education, University of Washington, Seattle, WA, USA Vineet Singh Faculty of Science, Technology and Environment, University of the South Pacific, Suva, Fiji Abayomi Olumade Sofoluwe Department of Educational Management, Faculty of Education, University of Ilorin, Ilorin, Kwara State, Nigeria Helena Song Faculty of Creative Multimedia, Multimedia University, Malaysia, Cyberjaya, Selangor, Malaysia Daniel Stoller-Schai CREALOGIX Digital Learning, Zurich, Switzerland Katie Headrick Taylor Learning Sciences and Human Development, College of Education, University of Washington, Seattle, WA, USA Lisa Thomas Learning, Teaching and Curriculum, University of Wollongong, Wollongong, NSW, Australia Nicole Ann Todd School of Linguistics, Adult and Specialist Education, University of Southern Queensland, Springfield Central, QLD, Australia Jan Turbill University of Wollongong, Wollongong, NSW, Australia

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Contributors

Jairo A. Jimenez Villamizar Katholieke Universiteit Leuven, Leuven, Belgium Kimberly Vincent-Layton Department of Communication, College of eLearning, Humboldt State University, Arcata, CA, USA Hugo von Zeipel Mid Sweden University, Sundsvall, Sweden Lei Wang Faculty of Engineering and Computer Science, University of Wollongong, Wollongong, NSW, Australia Anna-Karin Westman Mid Sweden University, Sundsvall, Sweden Debra L. White Liberty University, Lynchburg, VA, USA Wangweilai Xiang Wollongong Chinese Language School, Wollongong, NSW, Australia Kui Xie Department of Educational Studies, Learning Technologies, The Ohio State University, Columbus, OH, USA Ying Xie Educational Technology, Research and Assessment, Northern Illinois University, DeKalb, IL, USA Lina Xu School of Accounting, Economics and Finance, Faculty of Business, University of Wollongong, Wollongong, NSW, Australia Qifang Xue Wollongong Chinese Language School, Wollongong, NSW, Australia Hu Yin Beijing Oriental Caesar Ltd., Beijing, China Yu (Aimee) Zhang WEMOSOFT, Wollongong, NSW, Australia Fosse (Jing) Zhang MADE IT Biotech (Beijing) Limited, North Gate of Tsinghua University of Power Plant, Beijing, China Xiaofen Zhang College of Information Technology, Beijing Union University, Beijing, China Ziqui Zhang Beijing Information Science and Technology University, Beijing, China

Part I Design of Mobile Teaching and Learning in Higher Education

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Design of Mobile Teaching and Learning in Higher Education: An Introduction Robert Power

Abstract

The rapid evolution of mobile technologies has been accompanied by equally rapid changes in how people interact with each other, and with society. These changes have implications for teaching and learning. They also present exciting possibilities for changes to how educators, instructional designers, and students themselves approach teaching and learning. Despite this, many questions remain as to how best to design learning environments and resources to meet changing demands, and leverage emerging resources. This chapter provides an overview of some of the issues and trends reflected in this section of the Handbook of Mobile Teaching and Learning, which focuses on recent experiences and innovations in the design of mobile teaching and learning in higher education. Introductions are provided for the seventeen chapters that make up this book section, which cover topics ranging from pedagogical perspectives on the transformation of face-toface learning to mobile contexts, to how to design effective mobile lessons, business models for mobile teaching and learning, and new instructional design frameworks. Mobile technologies have rapidly evolved in recent years. Alongside this, evolution has been dramatic changes in how people interact with information, technology, and each other. These changes have had impacts across many sectors, including in the fields of formal and informal education. The increasing penetration of mobile devices has led to increased interest in mobile teaching and learning (m-learning). This increased interest has caused scholars to focus on a range of technical and pedagogical issues that need to be addressed in order to effectively leverage mobile technologies in education. Some of the problems that scholars have identified include questions of how to transform traditional curricula and resources into digital R. Power (*) British Columbia Institute of Technology, Surrey, BC, Canada e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_10

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content, and how to appropriately design content for mobile platforms and teaching methodologies. There are also questions of a more technical nature, such as how to improve interactivity and communications functionality, how to ensure the stability and security of network connectivity, and how to protect intellectual property (IP) and confidential information. Importantly, there are also questions of how to prepare educators to integrate mobile technologies and approaches into their practices, and how to ensure students are engaged with learning resources and activities, instead of distracted by games, social media, or other features of mobile devices. Designing appropriate mobile learning curricula and applications requires an understanding of students’ needs and requirements. It also requires an understanding of the technologies that are available, the affordances and limitations of those technologies, and issues of technology access (include affordability). Some instructional content and activities can easily be adapted into digital and mobile-friendly formats. Other practical teaching and learning activities may remain inappropriate for mobile learning approaches. For instance, developing competence with medical procedures may require a more hands-on approach, with in-person observations to certify competency. In some cases, even resources that could easily be digitized may not be appropriate for mobile delivery, such as long text-based documents, or digital media content or learning artifacts that require large amounts of storage space, or bandwidth to transmit. The ease of reading text on smaller screens, the expense of bandwidth needed to access resources, the overall stability of network connectivity, and even physical and data security for users must be carefully considered when making decisions about mobile learning approaches. Fortunately, there is a growing body of research and resources available to provide guidance with these considerations. The development of mobile learning programs and resources can be a detailed process that involves the design, production, and testing efforts of curriculum and instructional designers, software application developers, and learners themselves. These efforts can have important payouts as a result of the special affordances of mobile technologies, including social connectivity, cooperative and collaborative interaction, multimedia resource access, general mobility, and the ability to situate learners and learning scenarios in the right time and space for a learning experience. These attributes have the potential to engage students in self-motivated and selfdirected learning. They have the potential to increase engagement, as well as assist with the learning process itself, and increase efficiency for students. Features available in mobile devices can also be leveraged to increase the accessibility of learning for students with special needs. Mobile technologies provide greater access to teaching and learning resources, and have the potential enhance performance and to make learning a more personalized experience. However, factors such as affordability and access to technology and connectivity, safety, security and privacy concerns, and the time and effort needed to develop appropriate curricula and resources, continue to limit what can be achieved. In the chapters that follow, the some authors present reviews of literature on traditional teaching methods, newly developed mobile learning programs, and summaries and recommendations for the design and delivery of mobile learning in

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higher education. Other authors discuss the advantages and disadvantages that have been noted when using mobile learning strategies. Frameworks to provide guidance with mobile instructional and curriculum design are presented. Some of the chapters that follow focus on existing technologies and their potential for mobile learning, while others explore the potential of new and emerging technologies for future educational endeavors. The authors present viewpoints from multiple disciplines and regional perspectives, and discuss the challenges that can be expected in future mobile learning initiatives. Many educators are familiar with traditional face-to-face teaching methods. In decades past, students were often active during class sessions, communicated with their instructors, and read a lot of text-based resources. In ▶ Chap. 3, “Transformation of Traditional Face-to-Face Teaching to Mobile Teaching and Learning: Pedagogical Perspectives,” Dr. Jan Turbill describes the experience of transforming approaches to suit a new generation of learners. These learners frequently come to class with their mobile devices in tow and use those devices to do much of their reading, searching, and learning. Dr. Turbill describes the need to change teaching methods to keep up with new learner profiles and the resources they are accustomed to using. Dr. Turbill needed to design and develop online and mobile-compatible curricula from traditional teaching resources. Many teachers and tutors became involved with what turned out to be a successful endeavor. Students were asked to bring their background knowledge and beliefs about what they were going to learn, and that underpin their existing knowledge, attitudes, and actions. These factors were challenged and informed by new information, actions, and practices. All of these dimensions were brought together to inform the development of a new online model. Dr. Turbill’s chapter reviews the literature on traditional classroom learning and introduces the transformation to a technology-integrated approach. Dr. Turbill also compares the differing perspectives of traditional and technology-integrated teaching, and presents the advantages from both models. In ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning,” Dr. Aimee Zhang introduces the process of mobile technology development, along with the strengths and limitations of mobile technology. Zhang provides an overview from the literature and empirical studies on the development of mobile teaching and learning that focuses on its advantages and disadvantages. The chapter suggests some important determinants of a good mobile learning program from a designer’s view, including the need for both the designer and educator to have the technical skills and knowledge to design curriculum and content for mobile teaching and learning. Due to current hardware and connectivity limitations, Zhang points out how not all digital content is suitable for mobile delivery. She also notes that learners from different countries are situated in different social, cultural, economic, and technical contexts, all of which influence the types of content and pedagogical approaches that might be appropriate. Empirical studies in Australia and China revealed differences in market shares amongst students, as well as different levels of adoption of mobile learning approaches. Students from different contexts also have differing views on what should be implemented to increase engagement and

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enhance impacts on learning. Zhang also presents the limitations and barriers faced by mobile learning programs, discusses potential solutions, and presents future design considerations for mobile teaching and learning. Geographic dispersion can create unique challenges for mobile teaching and learning. In ▶ Chap. 8, “Use of Mobile Devices for Learning and Student Support in the Pacific Region,” by Dr. Bubhya Sharma and Dr. Anjeela Jokhan describe how short message notification service (SMS) was integrated into a mobile learning model at the University of the South Pacific in 2011. The SMS service is designed to link with the MOODLE learning management system already in widespread use at the university. The authors discuss the administration of a student survey about their mobile learning experiences. Feedback from students appears positive for the use of the SMS service in teaching and learning, as well as for its adoption by other university departments such as Campus Life, Student Administration Services, Campus Directors, Marketing, and the Emergency Working Group. The authors indicate that mobile learning has had a positive contribution to teaching and learning at the university, and throughout the region. They also demonstrate how SMS services can be integrated to support both teaching and learning practices, as well as general student and campus support services in higher education. The Open University is becoming increasingly popular because of its efforts to open knowledge and learning opportunities to people in many different countries. In ▶ Chap. 18, “Mobile Learning and Education: Synthesis of Open-Access Research,” by Dr. Teresa Cardoso and Renato Abreu discuss the use of mobile technology in the Open University. Mobile technologies increase the ability of learners to study at a distance. This chapter focuses on the characteristics of mobile learning types and environments, and includes a SWOT (strengths, weaknesses, opportunities, and threats) analysis on mobile learning. The authors explore students’ and teachers’ perceptions and practices, and the determining factors they consider important to the use of mobile devices in teaching and learning. A comparison is presented of 15 journals and databases for mobile or online education, showing that teachers overwhelmingly lack motivation to promote mobile learning approaches. Teacher training and policy supports are shown to be important factors in the acceptance and promotion of mobile learning. The authors shed light on future development and design of a mobile open knowledge framework. Dr. Sanja Pupovac, Dr. Lina Xu, and Dr. Corinne Cortese from the University of Wollongong extend the notion of the “flipped” classroom to subject assessment. In their ▶ Chap. 7, “Applying Open-Book-Open-Web Assessment in Postgraduate Accounting Subject: Flipping Test,” by Pupavoc, Xu, and Cortese describe how they adopted a “flipped” approach in all assessments in a postgraduate accounting course, including final exams. The idea was to encourage collaborate learning, increase student engagement, and develop critical thinking skills. The authors review research on peer-learning in accounting education and focus on six key streams. They discuss the use of mobile technology in learning and assessment, and the solutions it presents. Feedback to the flipped approach to assessment was positive, with students expressing a belief that the flipped model enhanced their learning experience. The authors also show that international students in particular benefited

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from the flipped model. The flipped approach reduced pressure to memorize content and increased the potential for engagement in deeper learning. The authors note that the teacher plays an important role when adopting peer-based learning approach such as flipped learning. Their findings represent important considerations for future development of mobile education programs and resources for learning and assessment. Kimberley Vincent-Layton from Humboldt State University argues that educators should play a vital role in the development of mobile lessons to support authentic learning that incorporates collaboration and critical thinking. Vincent-Layton shares a case study of mobile teaching and practice in the ▶ Chap. 14, “Mobile Learning and Engagement: Designing Effective Mobile Lessons.” The chapter outlines a mobile lesson template that was adopted for the Scavenger Hunt Mobile Lesson on Motivational Appeals. The proposed template includes the assignment name, goal, learning outcomes, materials/resources, instruction, assessment, weighting of the assignment, submitting assignment for evaluation, time commitment, deadline, feedback expectations, examples, and technology considerations. After demonstrating how the lesson template was used in the case study, the author advocates for increased collaboration in mobile learning activities across course and curricula in higher education. Jason Haag and Peter Berking discuss how mobile technologies can assist the learning process for special mobile curriculum design in the ▶ Chap. 13, “Design Considerations for Mobile Learning.” The authors review the literature and discuss definitions of mobile technologies and mobile learning. They note that learners are now leveraging mobile devices for support and self-directed learning. With an emerging paradigm shift that offers new opportunities for improving performance and augmenting skills, the authors argue that the current analysis, design, develop, implement, and evaluate (ADDIE) framework of curriculum design is not the best model for curriculum design for mobile learning. Current gaps in design knowledge for educators, instructors, and instructional designers are important considerations. The authors present a new learner-centered design approach to mobile learning design. With the ability to satisfy users, many interfacing with different screen sizes and hardware configurations, as a key factor in determining the utility of a mobile learning solution, the authors argue that the designers of mobile learning interfaces should be encouraged to work closely with instructional designers. The chapter categorizes and compares mobile learning on different devices. It also emphasizes the importance of spaced learning in mobile learning contexts and reviews relevant learning theories and conceptual frameworks for mobile instructional design. The authors conclude that mobile learning has the greatest potential to offer rich, contextual learning experiences. Their chapter offers valuable insights and a new framework for mobile curriculum design. Dr. Cassey Lee believes that it is important to address the financial aspect of offering and accessing mobile learning. In ▶ Chap. 5, “Business Models for Mobile Learning and Teaching,” Lee proposes new business models for e-commerce teaching and learning. These models provide insights for financial sustainability for mobile teaching and learning. Lee surveys the types of business models and relates

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them to mobile learning services, and proposes that the key factors for financial sustainability of mobile learning in higher education and other industries. Dr. Oscar R. Boude Figueredo and Dr. Jairo A. Jimenez Villamizar from La Sabana University discuss the difficulties facing teachers in mobile teaching design and implementation in ▶ Chap. 15, “Framework for Design of Mobile Learning Strategies.” They review previous theoretical and empirical works, and design a new model for mobile teaching and learning. Their model includes six stages: recognition, analysis, identification, bases, design, and implementation. The importance of teacher awareness of the educational process, benefits, and limitations using mobile technologies is emphasized. Dr. Ekaterina (Katya) Pechenkina focuses on micro-credentials and mobile learning in ▶ Chap. 6, “Micro-credentialing in Mobile Learning: Implications for Impactful Design.” Pechenkina discusses the literature and empirical studies on microcredentials and mobile learning, and identifies the gaps between the studies linking them. With micro-credentialing, larger programs are split into smaller units of study. Mobile learning is described as having the benefit of providing “anytime/anywhere” access to learning opportunities. The author argues that while both microcredentialing and mobile learning try to make learning more flexible, the two approaches are rarely considered in tandem. The chapter explores various intersections between the two approaches and considers key elements for impactful instructional design. The author emphases the importance of mobile micro-credentials in formal institutional course design. An augmented reality mobile learning game is introduced ▶ Chap. 11, “The Graduation Game: Leveraging Mobile Technologies to Reimagine Academic Advising in Higher Education.” Tressa M. Haderlie, Dr. Apporva Chauhan, Whitney Lewis, and Dr. Breanne Littsfrom Utah State University describe the Graduation Game. The aim of the project was to leverage AR to introduce and provide meaningful earlier connections between students and their academic advisors and institution. The chapter describes how the Graduation Game was designed, tested, and implemented to improve students’ advising experiences. An email distribution of the game in 2017 was not successful. However, a distribution of the game at a university orientation saw higher response rates, and the evaluation of the project has been positive. The authors argue that utilizing mobile technologies for advising in higher education has great potential to enhance the critical role played by advising in promoting positive perceptions, and increasing student persistence through their education. The influence of parents’ education on their children’s academic experience is the focus of Dr. Aimee (Yu) Zhang’s ▶ Chap. 9, “Parental Education: A Missing Part in Education.” Zhang explores the literature and empirical studies that focus on parents’ education and notes its significant impact on children’s academic performance, behavior, and general development. The author also notes that while many jurisdictions do now emphasize parental education, it is still undervalued. While some programs and resources are available online, they are not easily accessible or wellpromoted. Zhang discusses the benefits of parental education, which include spillover effects such as enhanced standard of living for families, and the prevention of

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social, criminal, and mental health issues in the community. The author proposes a possible solution for parental education using mobile technologies, which are increasingly widely available to most parents. The existing availability of mobile devices means a reduced startup cost for access to parental education resources. Additionally, most parents are already familiar with the technical use of their own devices, further increasing the ease of dissemination and access. Zhang notes that parents are ready and willing to learn to assist their children’s learning. Dr. Aimee (Yu) Zhang, along with Ms. Wangweilai Xiang and Ms. Qifang Xue, introduce the design and implementation of a Chinese teaching and learning second language program in an Australian language school in ▶ Chap. 10, “Design and Implementation of Chinese as Second Language Learning.” The authors describe the challenge of designing and implementing a teaching program for students who came from different cultural and linguistic backgrounds and who had varied experience and knowledge with the Chinese language. The initial learning program goal was established as increasing awareness of Chinese culture and interest in learning the Chinese language. A further goal was to meet the challenge of teaching Chinese writing, which includes strokes derived from ancient drawing, and which required plenty of repeated practice. A mobile learning application was developed and implemented in 2016, and met with a successful response. Students appeared to be highly engaged in in-class learning activities that included both practice and competition, and were eager to continue with the competitive tasks outside of the classroom. The project demonstrates that mobile learning approaches can generate positive results in language teaching and learning. Mobile-assisted language learning (MALL) is the focus of ▶ Chap. 16, “Foreign Language Teachers as Instructional Designers: Customizing Mobile-Assisted Language Learning Technology,” by Jennica Grimshaw, Michael Barcomb, and Dr. Walcir Cardoso, from the Concordia University, Canada. The authors introduce the three levels of teacher involvement with MALL technology. This involvement includes adapting pre-made materials at Level 1, modifying pre-made materials at Level 2, and creating new materials at Level 3. The chapter illustrates the implementation of the three levels of teacher involvement in a MALL environment. It also introduces examples of MALL resources to foreign language teachers as instructional designers, including Duolingo, Quizlet, and Moodle. One of the challenges faced by the foreign language teachers was limited time and resources, while the MALL implementation itself required long-term dedication and sustained effort. Grimshaw, Barcomb, and Cardoso argue that instructional design is more important than technology in helping students to achieve learning outcomes, and the purpose of their chapter is to provide teachers with a potential solution for foreign language instruction. The role of the Mobile City Science (MCS) project in developing new spatial literacies through the study of local issues is the focus of ▶ Chap. 17, “Learning and Researching Across Places in Mobile City Science.” Deborah Silvis, Dr. Jeremiah Kalir, and Dr. Kate Headrick Taylor from the University of Washington and University of Colorado Denver discuss the MCS project, which brought together university-based researchers and youth-serving organizations in

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three US cities. The MCS project used location-enabled mobile devices, GPS-enabled action cameras, and mapping technologies to locate and represent places of personal interest in participants’ local neighborhoods. Among the benefits of the MCS project described by the authors was a more in-depth and critical understanding of smart and connected cities. The authors also argued that the project supported youth to envision smarter cities by involving them in data collection and scientific inquiry. ▶ Chapter 4, “Flexible Spaces and Sustainable Opportunities: Designing Online Professional Learning for Sessional Teachers” introduces two professional development programs at the University of Wollongong in Australia. Dr. Bonnie Dean, Dr. Kathryn Harden-Thew, Dr. Janine Delahunty, and Dr. Lisa Thomas provide insights from their empirical projects as to shift in professional development from traditional modes of delivery to a more practice-based focus. The chapter reviews the literature on methods of supporting sessional teachers at Australian universities. The authors discuss the importance of building technical professional skills at an institutional level, as well as addressing the needs of individual sessional teachers. They highlight a practical, flexible teacher training module. The authors also demonstrate the vital importance to mobile teaching and learning of technical skills and professional knowledge with online and mobile technologies, as well as the importance for both institutions and staff to have the same goals and training plans for new challenges. In the wake of The Civic Potential of Video Games report, Dr. Renee Jackson and Emily Sheepy believe that there is a relationship between social impact game playing and positive citizenship outcomes. The authors introduce the social game, Get Water! in ▶ Chap. 12, “Learning from Social Impact Games to Support Integration into Middle School Classrooms.” The chapter presents a qualitative study involving players and parents of the Get Water! game. Most participants showed a positive response to the game, which they described as fun and addicting. The authors note that there needs to be a balance between gamification and learning, and indicate that there is a critical role for the teacher to play. In terms of learning, the experiences and technical skills of a teacher are vital in such gamified education. The authors draw upon some suggestions from participant students to provide guidelines for the design of social impact games. They argue that by enabling exploration of issues of global and public concern, social impact games such as Get Water! play an important role in increasing political knowledge, volunteerism, and the preparation of informed participants in democratic processes. The views and experiences of mobile teaching and learning design shared by the authors in this section show that methods of mobile teaching and learning vary in different countries and institutions. These differences in development, design, and delivery are influenced by many factors. Geographic location, available technologies, mobile device adoption rates and preferences, connectivity rates and costs, organizational goals, and the skills of designers and educators all play roles in determining mobile teaching and learning design practices. The chapters in this section bring together different viewpoints, new frameworks, and new ideas for the design and development of mobile teaching and learning. While one design model is

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not suitable for either mobile devices or mobile learning programs, the resources presented in this section may provide insights into general rules for mobile teaching and learning design. The knowledge and experiences shared by the authors may also open a door for future cross-country learning system design and skills training for designers and educators.

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Characteristics of Mobile Teaching and Learning Yu (Aimee) Zhang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Traditional, Online, and Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Characteristics of Mobile Devices and Learning via Mobile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Anytime and Anywhere? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Characteristics of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Differences in Mobile Learners and Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Design for Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A: Survey from Australian Undergraduate Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix B: Survey from Chinese Undergraduate Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile technology has been a growing trend for higher education and personalized learning (Peng et al. 2009; Alley 2009; Ainge 1995). Regarded as a vital learning tool for a new generation of students and teachers, it has attracted considerable attention in recent years (Alhassan 2016; Doug et al. 2009). Some researchers have argued mobile teaching and learning should be distinguished from online learning because of its own characteristics and functions (Alley 2009; Peng et al. 2009; Fraga 2012; Hennig 2016). A mobile device has different hardware features, software, and connection limitations to traditional computers (Zhang 2012). The characteristics of mobile devices and learning through mobile device are discussed in this chapter. The usage of mobile devices and the time requirements are different compared with learning on fixed computers Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_5

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(Yuh-Shyan et al. 2004; Doug et al. 2009). The advantages and limitation of mobile learning is also discussed in this chapter. The cost of the mobile network and connection quality also limited the learning activities on mobile devices (Zhang 2012). Online survey results from university students in different countries provided some intriguing findings about the future of mobile learning program design. Education program designers, schools, industry developers, and government should work together to provide a stable and safe mobile learning environment for students and individuals. But avoiding the potential risks when adopting mobile technology must be taken seriously.

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Introduction

Mobile teaching and learning (M-learning) has been a popular research topic in recent years because of the increasing penetration rate of mobile devices globally (Fraga 2012; Sharples 2000; Metzgar 2017; Sun and Looi 2017; Hennig 2016). New mobile devices and technologies have changed the way humans live (Hennig 2016; ITU 2016), by the way people communicate and socialize with each other, adding value to mobile learning (Ahn and Shin 2013; Al-Rahmi et al. 2014; Baage 2013; Britt 2013; Buffington 2013; Castro 2012; Dabbagh and Kitsantas 2012; Ferris and Wilder 2013; Haipinge 2013; Heatley and Lattimer 2013; Jenkins and Dillon 2013; Kaplan and Haenlein 2010; Poore 2013; Tyree 2013; Zidoun et al. 2016) (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). Educators in universities and schools have researched the motives and advantages of mobile learning compared with traditional learning methods (Fraga 2012; Evans 2008). Some of the researchers developed, adopted, and assessed their mobile applications in courses (Ahn and Shin 2013; Alkhezzi and Al-Dousari 2016; Bredl and Bösche 2013; Doug et al. 2009; Evans 2008; Hwang and Chang 2011; Sung and Hwang 2013; Zidoun et al. 2016). These studies describe the future trends and development of mobile technology. Often, promoters of mobile learning are often criticized for their boasts about its real “anytime” and “anywhere,” because there are many technical limitations and little understanding of mobile (Alkhezzi and Al-Dousari 2016; Yousafzai et al. 2016; Mccombs 2010). Students use mobile phones in smaller time slots, such as waiting for friends or on a bus, and they spend a large chunk of time playing games (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). Instead, a well-designed learning application should assist student learning using small time slots.

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Traditional, Online, and Mobile Learning

The skills, knowledge, and expectation of current students (the millennium or technical generation) are rapidly changing because they grew up using electronic devices and technologies (Hunt and Zhou 2017; Zidoun et al. 2016; Alkhezzi and

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Al-Dousari 2016; Alhassan 2016; Oblinger and Oblinger 2005; Alley 2009; Fraga 2012; Prensky 2001) (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). They are more familiar with those technologies and mobile devices compared to older generations of people often described as more innovative and efficient in learning (Oblinger and Oblinger 2005). Ten years ago, people preferred to stay in libraries reading hardcopy books, but today, students are reading electronic materials anytime and anywhere with their mobile devices (Zhang 2012a). As more students travel around the world and study abroad, they are learning to communicate with other people from multiple cultural backgrounds (OECD 2016a) developing an understanding of different cultures and how to learn from others (see ▶ Chap. 50, “Cross-Country University Collaboration Barriers and Solutions”). These multicultural opportunities are forcing teaching methodologies to be reexamined (Dunbar 2017). Education experienced the technology revolution as for other industries from traditional methods to online education, mobile education, and wearable education. Although the face-to-face (FTF) learning has some irreplaceable advantages, such as communicated through facial and body expressions, emotional transfer, and active experience (Stewart 2011; Lewin 1948; Kolb 1984), online teaching and mobile teaching are becoming more pervasive in educational institutions (Peng et al. 2009; Alkhezzi and Al-Dousari 2016; Hennig 2016). In 2016, 95% of the world population was covered by mobile cellular network and the cost of handset-based mobile broadband prices reduced dramatically compared to 2015 (ITU 2016). The high penetration rate brought opportunity for the development of mobile education (Alhassan 2016; Butoi et al. 2013; Sun and Looi 2017). From 2016, the new wearable mobile devices and technologies are becoming popular in the world mobile market (Yousafzai et al. 2016; Hennig 2016), which brought future development of mobile education through new devices. Many universities and schools have implemented mobile devices and infrastructures to facilitate mobile learning in class (Mccombs 2010; Alkhezzi and Al-Dousari 2016; Alhassan 2016; Doug et al. 2009; Fraga 2012). With its increased development, mobile learning encountered some technical and ethical challenges and problems. Currently, M-learning continues to have significant barriers providing seamless learning experiences on mobile devices anytime and anywhere (Doug et al. 2009; Mccombs 2010; Williams 2009). The lack of Internet access in some remote regions, lack of continuity of mobile data transfer between tall buildings, and the different qualities of mobile signals in different regions are noteworthy technical barriers to overcome (Alhassan 2016; Castro 2012; Mccombs 2010). The high costs of mobile data access (Table 1) and different mobile rates in different states and countries are continually increasing, making it more difficult to adopt efficient mobile learning experiences (ITU 2016; Metzgar 2017; Yousafzai et al. 2016). Ethical challenges, such as screen time length and distractions for younger children, are still concerning many educators and parents (Flewitt et al. 2015; Hennig 2016; KFRR 2016). Back to the 1990s, mobile learning practices on 2G networks (as shown in Table 1) were still limited by the five-line contents on each screen (Zhang 2012a),

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Table 1 The development of mobile technologies, from 1G to 4G. (Source: Zhang 2012a) Generations 1G (1980–1990s) 2G (1990s–current)

2.5G (1990s –current) 3G (2000s–current)

4G (future)

Major characters Analog communication Digital communication

Wideband and medium speed data Broadband and high speed data

Global roaming and higher speed

Major standards and protocols AMPS TDMA, GSM, PDC, CDMA one, Wi-Fi 802.11b CDMA one, GPRS, WiFi802.11 g CDMA 2000, WCDMA, HSDPA, WiFi802.11n, WiMax 802.16 m, LTE, developing standards

Capability Simple communication Limited data services

Sample of usages Mobile call Fax, short message, social network

Medium speed data transfer

WAP, MMS, file sharing

144 Kbps (in car), 384 Kbps (walking), 2 Mbps (indoor)

Video conference, streaming video, application shops Future innovations

Objective: 1 Gbps

and no multimedia content was available. Although it is not long time ago and most of the current educators had experience the time, but it is hardly to remember the time without the rich mobile applications now. With the enhancement of mobile transfer capacity, more applications with creative effects and functions have been implemented (Zhang 2012a). Wearable devices and 3D technologies have dominated the development of the market in 2018 (Hennig 2016; Yousafzai et al. 2016). With the development of new hardware (such as calculation capabilities and screen sizes) and software, the gaps between mobile learning and learning via computers are diminishing. The higher capacity of data transfer on mobile devices provides better communication and interaction experiences with mobile learning, which greatly enhanced the mobile learning practices. The decreasing costsof mobile access and data transfer also helped on the bloom of mobile education (ITU 2016).

3

Characteristics of Mobile Devices and Learning via Mobile

Mobile devices have experienced a rapid period of development from 2000 to 2017 (Sun and Looi 2017; Alhassan 2016; Cochrane 2016; Kabugo et al. 2016; Shu-Chun et al. 2017; Yousafzai et al. 2016) (see ▶ Chap. 79, “VR and AR for Future Education”). Mobile devices are primarily used for voice and text message communication, to send pictures, listen to music, record video, watch TV, play games, surf the Internet, check email, manage schedules, browse and create documents, and socialize with others (Hennig 2016; Rennie and Morrison 2013).

2

Characteristics of Mobile Teaching and Learning

17

The adoption of 3D VR (Virtual Reality) technology and wearable devices in mobile education have allowed for new ways to teach and learn (Bredl and Bösche 2013; Hennig 2016) (see ▶ Chap. 79, “VR and AR for Future Education”). Mobile phone user research demonstrate consumers view the benefits of mobile devices as saving money, saving time, and providing useful information (Friedman 2007) (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). Wireless networks are a pervasive technology changing the way people work and play (Williams 2009) with mobile services and data services offering potential for new patterns of teaching and learning (Hunt and Zhou 2017; ITU 2016; Sun and Looi 2017). One of the advertised advantages associated with 4G is always being connected (Kumar et al. 2010). However, some barriers still exist to achieve the anytime and anywhere experience with mobile devices (Alkhezzi and Al-Dousari 2016; Hwang and Chang 2016; ITU 2016; Yousafzai et al. 2016; Mccombs 2010).

3.1

Anytime and Anywhere?

Can mobile education provide a real seamless access for learning purpose today? The answer is yes but no. The most expensive mobile access through satellite signal (mostly used by military departments) can provide worldwide seamless mobile access and data download (based on expectation of no technical issue or other nature influence on signal transfer). But for general individual mobile access, the signals are not good enough to provide a real anytime and anywhere access yet. For example, on the main campus of University of Wollongong in Australia, the whole campus was exclaimed to be covered by Wi-Fi. However, it required a login to use the Wi-Fi service. While inside or behind some buildings, the 3G signal was not available due to the poor signal. Even in big cities, the signals are usually poor or unavailable in basements, in subways, or between the high buildings. There are many areas blocked for mobile signals for medical or security reasons. Besides these location problems, the mobile handsets sometimes disconnected Wi-Fi and used 3G automatically without notice by users (users can close 3G data and cellular network in settings). If video learning is running during the time, it is very costly (as in Australia, less than 1 h video transferring will cost about 200 AUD via 3G or 4G). Those technical and ethical barriers obstruct the seamless mobile education and discouraged the usage of mobile teaching and learning. To achieve a real anytime and anywhere learning, industry, educational institutions, and government should work together to solve the problems. To design a better mobile learning system or program, it is important to focus on the differences between mobile learning and online learning or traditional learning. Designers must understand the requirements of the educators and learners (with affordable costs, available devices, and good solutions to solve their problems) (see ▶ Chap. 28, “Development of Chinese Character-Writing Program for Mobile Devices”). A possible solution is to change the structure of mobile learning system combining online and offline requirements. For example, the first version of Tutors

18

Y. A. Zhang

in Pockets for Economics (see ▶ Chap. 27, “Tutors in Pockets for Economics”) only had an online design. Students downloaded all the figures with a mobile signal connection through Wi-Fi or cellular network to view the content. In the second version, both online and offline were offered, so students could view all the content. It only needed a connection to the server when for content updated. The advantage was students can achieve learning with or without mobile signal.

3.2

Characteristics of Mobile Learning

Peng et al. (2009) argued mobile learning still lacks a theoretical framework and indicated mobility is the primary difference between mobile learning and online learning. However, the situation has been changed with the newly developed mobile devices with high resolution and computing capabilities (Hennig 2016). Thecharacteristics of mobile devices should be considered when designing an effective mobile learning program (Castro 2012; Harris et al. 2016; Poore 2013). Mobile access has limitations on the size of contents and some social media platforms have restrictions uploaded content (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”) (Tyree 2013; Seo 2013). Some popular learning resources for online learning may not suit the mobile devices. For example, videos are effective resources for online learning (Butoi et al. 2013; Hennig 2016), but they are cumbersome and inefficient on mobile devices in term of file size and downloading time (Zhang 2012a). Transfer of video content is slow or costly if the user is connecting with 3G (Zhang 2012b). It may be difficult to read the subtitles on a small screen too. The smaller the file/video and the easier to use, the more likely the user will have improved learning experience and will adopt the mobile learning method (Zhang 2012a). The different sizes of screens need enhanced device suitability (Zhang 2012a), to view the content especially the word size and font (Zhang 2012a). Mobile devices are smaller and lighter than traditional computers, which makes them easier to carry and use. The designer for mobile learning program should take into account the characteristics of mobile devices and the user’s usage pattern for mobile learning when designing mobile learning applications (Hsu et al. 2013) (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). The cost of mobile learning is still the major concern when choose mobile education (ITU 2016). There are several reasons for the high costs of mobile learning. Firstly, the mobile handset is expensive, and most of the popular educational applications are only available for smart Apple devices or Android devices (Statista 2016). Secondly, the cost of building basic infrastructures for mobile communication is very high (Zhang 2012a), including the operator’s initial investment, service providers and content providers’ costs (Zhang 2012a). This can be explained in Fig. 1 showing scenarios of access to phone calls, short messages, and the Internet via mobile phone or mobile devices. As shown in Fig. 1, initial mobile education focused on the voice communication functions (Sharples 2000). With the development of new hardware, mobile education has experienced increased

2

Characteristics of Mobile Teaching and Learning

19

Owned by Operators Normal Call Customer 1

PDA

Base Station

Base Station

Mobile Phone Customer 2

Produced by Device providers Operators Service providers Short Message Base Station Customer 1

PDA

Base Station Customer 2 Mobile Phone

Short Message Center Service providers Operators

Download Games Customer 1

Internet PDA

Data

Content Server Content providers

Base Station

Fig. 1 Scenarios of mobile teaching and learning. (Source: Zhang 2012a)

usage short messages, the broadcasting function of mobile devices, and real-time multimedia education (Alhassan 2016; Alkhezzi and Al-Dousari 2016; Yousafzai et al. 2016). The improvement of hardware devices and interactive software applications also associate with increasing costs. Although the cost has decreased gradually during recent years (OECD 2016b), affordability is still a major barrier for mobile learning (ITU 2016). Free courses for online education are not really free (consider the cost of the devices and data transfer). In the current stage, mobile access is still costly in terms of hardware purchasing, network connection, and maintenance of the hardware and software (Zhang 2012a). Although the costs are sometimes “invisible” to users (until the bill arrives), the slower loading process or influence playing process may reduce usage and download rates (ITU 2016; Hennig 2016). To reduce the accessing costs of mobile learning, it is important to develop suitable content for mobile teaching and learning (see ▶ Chap. 27, “Tutors in Pockets for Economics”). The size of the content, readability of words, fitness to different-sized screens, flexible access, freedom for learners and colors adopted are important factors when designing suitable contents for mobile teaching and learning (Hennig 2016).

3.3

Differences in Mobile Learners and Mobile Learning

Mobile learners have different expectation and pattern of mobile device usage compared to other traditional face-to-face learners (Alkhezzi and Al-Dousari 2016; Prensky 2001; Zidoun et al. 2016; Sun and Looi 2017). Rennie and Morrison (2012) summarized characteristics of millennial generation from

20

Y. A. Zhang

previous empirical research. This generation prefer multitasking, multimedia and teamwork (Alkhezzi and Al-Dousari 2016; Hunt and Zhou 2017; Zidoun et al. 2016; Oblinger and Oblinger 2005). But they have shorter attention spans, poorer text literacies, cavalier attitudes to quality of sources, and lack of the ability to reflect (Rennie and Morrison 2012) (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). Mobile learners have their own learning habits (Zidoun et al. 2016). Learners usually use mobile phones for smaller time fragments compared with computers learners (Hennig 2016). If a study process is interrupted several times, it may have negative effects on its experience and results (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). Therefore, big graphics and long paragraphs are not suitable for mobile teaching and learning (Hennig 2016; Zhang 2012b). They should be separated into smaller parts to provide more flexible access and study on mobile devices (Zhang 2012b). Different students from different countries or culture backgrounds may have different understanding and adoption level for mobile learning (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). To understand the learning habits of students on mobile devices and mobile learning programs and the differences between Australian and Chinese students in mobile learning, a survey was designed and conducted in Australia and China (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). In 2013, the Chinese survey was conducted at three universities in China, sample size were 183 undergraduate and postgraduate students in three different provinces (Beijing, Anhui, and Jiangxi). The Australian survey was conducted at the University of Wollongong; sample size was 54 students from first year undergraduate macroeconomics tutorials, in which a mobile learning application – Tutors in Pockets – was introduced (see ▶ Chap. 27, “Tutors in Pockets for Economics”). In Fig. 2, the results of survey (as in Appendix A) indicated a total 70% of students were using Apple mobile devices, and 23% of students were using Android devices in Australia. The other mobile devices (such as Windows mobile phone) accounted for only 7% of the market in Australia. The market share has changed between 2013 and 2017 where Android devices use was larger than iOS devices use (ITU 2016). As shown in Fig. 3, Chinese market (in Appendix B) is shared by many hardware competitors. Apple mobile devices accounted for 24% in the Chinese students’ sample group. Android devices accounted for 34% in the survey results, and 42% were other platform run mobile devices (such as Xiaomi mobile phone in China) (Table 2). Table 2 shows the different using habits of Australian students and Chinese students. In Australia, majority of the surveyed students use mobile phones in lectures and tutorials (65%), when meeting friends (70%), waiting (94%), or walking or on transportations (85%). And 59% use mobile phone when they are having food, and 41% use mobile phone when working (in Appendix A). In China (in Appendix B), most students use mobile phone after class (67%) or when they are waiting for buses or friends (52%). Students rarely use mobile

2

Characteristics of Mobile Teaching and Learning

Fig. 2 Australian mobile devices market share. (Source: Data collected for this study)

21

Mobile devices market share Others 7%

Android 23%

Apple 70%

Fig. 3 Chinese mobile devices market share. (Source: Data collected for this study)

Mobile devices market share

Apple 24% Others 42%

Android 34%

phones in class, meeting friends (20%), or for work (6%). And 48% of students use their mobile phone at home. Australian students use mobile phones more than Chinese students. One possible reason is the requirements of using mobile devices and applications in class or as a tool for new information and articles by teachers. Most teachers in China still have negative attitudes toward mobile devices in class as indicated by the interviewed teachers in China. Another difference between Australian and Chinese university students are part-time jobs. Most Australian students have

22

Y. A. Zhang

Table 2 Differences on the usages of mobile devices by Australian and Chinese students Australian students use mobile In lectures and tutorialsa Meeting friends Waiting Walking or on transportationsa Having fooda Working

Percentage (%) 65 70 94 85

Chinese students use mobile In classa Meeting friends Waiting After classa

Percentage (%) 20 20 52 67

59 41

At homea Working

48 6

a

Note: The questions were adjusted to suit different cultures in different countries Source: Data collected for this study

part-time jobs after class. However, Chinese parents usually pay tuition fees and living fees for students during their study and require them to focus on their studies instead of seeking for part-time jobs, which influenced the using habits of mobile devices (Fig. 4). Australian students and Chinese students access different sources when using mobile devices for learning purposes. Australian students (in Appendix A) prefer Google (91%), E-learning from university website (57%), Youtube (55%), and Wikipedia (34%). Tutors in Pockets was introduced to the sample group and adopted by 27% of total students (see ▶ Chap. 27, “Tutors in Pockets for Economics”). Some of them access mobile news (23%) and download applications in iTunes or Google Play for learning (16%). Chinese students have very different learning habits from Australian students. Google and other social media applications were blocked or semi-blocked in mainland China and the popular social media applications are different from western countries in China (Zhang 2012a) (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). The number of subscribers of Weibo and WeChat (the most popular Chinese social media applications) are on the top of the global social media lists because of the huge population base. The questionnaire in China was modified to suit the different students’ groups. As in Appendix B, online learning still dominates (61%) in China due to university requirement. But interactive learning (16%), mobile learning (9%), and multimedia learning (12%) are lagged behind developed countries in 2013. As shown in Fig. 5, the length of mobile learning times per day are similar in Australia and China (in Appendixes A and B), ranged from 0 to 8 h per day. The average learning time on mobile device is 40–50 min per day for both Australian and Chinese students. It is a natural time length for all mobile learners. As shown in Table 3, in terms of expectation and benefits of mobile learning, the results are slightly different in Australia and China (in Appendixes A and B). Learning efficiency, anytime and anywhere, and utilizing the small time slots are still the top benefits for mobile learning methods. Most Australian students appreciate the time flexibility for learn anytime and anywhere (56%), and majority

2

Characteristics of Mobile Teaching and Learning

23

Sources 100%

Sources

90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Google

University Youtube Wikipedia Tutors in site Pockets

Mobile news

App store

Fig. 4 Sources of mobile learning in Australia. (Source: Data collected for the surveys in Australia and China in this study)

Chinese Students Mobile learning Mobile life

Other time per day Australian Students

0

5

10

15

20

25

30

Fig. 5 Length of mobile learning time per day. (Source: Data collected for this study)

of Chinese students appreciate more the utilization of small time slots for mobile learning (54%). Mobile learning can increase learning efficiency (38% by Australian students and 52% by Chinese students). Australian students use mobile devices in class (38%) to help understand and memory, while only 22% Chinese students use their mobile devices in class. There are continuing discussions about students using mobile devices in class (Alkhezzi and Al-Dousari 2016; Vogel et al. 2009; Alhassan 2016; Sana et al. 2013). However, with new technology and more digital content available, mobile devices are becoming a vital learning tool in classroom learning. The surveyed students agreed mobile learning increased their interests in learning (26% in Australia and 17% in China). Students agreed mobile learning contributes to in-class discussion and subject performance (as in Appendix A and B). One important issue one should be

24

Y. A. Zhang

Table 3 Expectations and benefits from mobile learning by Australian and Chinese students. (Source: Data collected for this study) Expectation and benefits from mobile learning It increased my learning efficiency It helped me study anytime and anywhere It helped me study utilizing the small time slots (e.g., waiting for bus) It helped my lecture/tutorial study It made me feel interested in this subject It engaged me in a discussion with other students or teachers It increased my performance in this subject Others (including no difference)

Australian (%) 38 56 32

Chinese (%) 52 41 54

38 26 9 26 15

22 17 12 12 8

aware of is the group of students who indicated they are not benefited from mobile learning methods (6% in both Australia and China as in Appendix A and B). To give equal access to all students and provide inclusive learning opportunity for all students, the students without mobile phone, smartphone, or skills in using mobile devices should be taken into account in any mobile learning programs. This study shows different mobile device using habits in Australia and China, which shed a light on mobile learning program design for students from different cultural backgrounds. The findings support when design global mobile learning programs, cultural differences, and different using habits from different students groups should be taken into account.

4

Design for Mobile Learning

Although many empirical studies have found mobile learning has a positive influence on learning performance (Williams 2009; Hwang and Chang 2011; Evans 2008; Doug et al. 2009; Bredl and Bösche 2013), mobile learning programs are very different in terms of course design, target group, learning methods, and implementation environment (Alhassan 2016; Alkhezzi and Al-Dousari 2016; Evans 2008; Mishra 2013; Yousafzai et al. 2016). To design an effective mobile learning program, designers need to consider the different characteristics of mobile devices and mobile learners. Small in size, easy to use, personalized materials, and flexible learning contents are key features for such programs. Interactive functions and social communication are believed to be important to engage students and increase long-term memory. Discussions between students and teachers help the students understand the classroom content, especially when the content is used to solve real problems. Mobile technology brings more possibilities into education (Alhassan 2016; Sun and Looi 2017). For example, real-time exchange rates, interactive management activities, communication, and co-work online interactions can be brought into class anytime and anywhere. Prensky (2001) suggested combining

2

Characteristics of Mobile Teaching and Learning

25

“legacy” and “future” content should be designed and developed for all subjects at all levels. He indicated games are effective to teach the new generation of learners. However, just like the game-based learning, mobile learning is faced with a dualism between knowledge transfer and gamification. Too much gamification can distract the students from their main learning tasks, but too much guidance will inhibit creativity(Bredl and Bösche 2013). Some ethical issues, such as the length of screen time for younger kids, distraction from main learning activities, and safety issues, concerned educators and parents (OECD 2016a; Alkhezzi and Al-Dousari 2016; Peng et al. 2009; Yousafzai et al. 2016). Successful mobile learning is not based on the technology itself (Rennie and Morrison 2012). Digitalization of curriculum has been introduced in educational design for many countries (Hennig 2016; Becker et al. 2016; OECD 2016a) (see ▶ Chap. 13, “Design Considerations for Mobile Learning). New multimedia content, online education, and robotic technologies have been added into curriculum design to assist the teaching and learning of educators and students and may generate a spill-over effect to industry and other countries. Beside the innovative curriculum, a good teacher and good instruction design with inspiring contents are vital for a successful mobile learning program. Mobile technology provides opportunities for flexible personalized learning for different groups in the same classroom (Hsu et al. 2013; Kukulska-Hulme and Traxler 2005). It limits the restrictions on learning and provides individual discovery experiences. Implementing differential teaching, a well-designed flexible pedagogy and course content are important factors for successful mobile learning experiences. Designers should not be limited by traditional PDF, readings, forum, or online voting but utilize the interactive and communicative functions on mobile devices (Holotescu and Grosseck 2011; Oblinger and Oblinger 2005). Additionally, wearable technology and 3D technology opened a door for future mobile learning opportunities (Alkhezzi and Al-Dousari 2016; Yousafzai et al. 2016; Hennig 2016). As more international students are seeking higher educational degrees in developed countries (see ▶ Chap. 50, “Cross-Country University Collaboration Barriers and Solutions”), there are several challenges to engage students from different cultural backgrounds, how to encourage both high-performance student groups and low-performance student groups in the same class, and how to help disadvantaged students in class (OECD 2015). To solve these problems, new teaching methods based on advanced technologies and innovations must be adopted in teaching and learning (Kennedy et al. 2013; Zhang 2012b). Many new innovations encourage learning experiences to occur inside and outside the classroom to enhance the learning experiences (see ▶ Chaps. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning” and ▶ 79, “VR and AR for Future Education”). For many students, learning through case studies is the preferred learning method for both local and international students (Zhang 2012b). Case studies aligned with the students’ experiences provide aid all students during group discussions. A well-designed and developed content is important for either face-to-face teaching and learning or online/mobile learning.

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Y. A. Zhang

Students are different today (OECD 2016b; Alhassan 2016). Educators should be equipped with not only extensive knowledge in their area of teaching but also should know the latest research findings, new technologies, new ideas, different methods, case studies, and great passion for teaching. Mobile teaching and learning is the trend for the future (Castro 2012; Prensky 2001; Sun and Looi 2017). As indicated by Prensky (2001), “if Digital Immigrant educators really want to reach Digital Natives – i.e., all their students – they will have to change.” (p. 6).

5

Future Directions

Mobile teaching and learning has been a growing trend for higher education, K-12 education, skills training, and individual leaning (Evans 2008; Alhassan 2016; Sun and Looi 2017; Zidoun et al. 2016; Hennig 2016; Fraga 2012). Many universities and schools are designing and developing teaching programs on mobile devices (see ▶ Chaps. 27, “Tutors in Pockets for Economics” and ▶ 29, “Adoption of Mobile Technology in Higher Education: An Introduction”). Apple, Google, Microsoft, IBM, and most of the major companies have provided different solutions for online and mobile learning. A well-designed mobile learning program should focus not only on the quality of content but also on the characteristics of mobile devices and mobile learners. This study collected primary data from Australia and China to understand better students’ pattern of mobile usage, mobile learning, and their expectations on mobile learning. Some interesting findings are identified. Students prefer blended learning methods and real case studies (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). The new generation of students can adapt to mobile learning faster and better than previous generations of students (Hunt and Zhou 2017; Oblinger and Oblinger 2005; Zidoun et al. 2016). However, they have shorter attention spans and lack of text literacy. Students from different countries and cultural backgrounds have different mobile learning preferences and expectations. Mobile technology can provide the flexible and personalized contents to meet the needs from different student groups (Hsu et al. 2013; Sun et al. 2016). Educators and designers are important in new content design and development to meet the needs for mobile learners. A well-designed flexible and extendable structure is important for mobile learning program. Some designers and teachers are limited by technical supports, funds, and energies. Some prototypes and mobile learning projects which have been developed by different universities could benefit more students and individuals in the world if they are publicly accessible. Some of the mobile learning practices are introduced in this book to bring them to the students, teachers, and designers for future mobile learning programs. New emerging technologies as introduced in the VR, AR, and wearable technologies section in this book will meet the gap and bring innovations into education to make

2

Characteristics of Mobile Teaching and Learning

27

it more engaging and interesting (Hennig 2016; Alkhezzi and Al-Dousari 2016; Yousafzai et al. 2016) (see ▶ Chaps. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning,” ▶ 74, “Wearable Technologies as a Research Tool for Studying Learning,” ▶ 77, “Augmented Reality in Education,” ▶ 78, “Mobile-Based Virtual Reality: Why and How Does It Support Learning” and ▶ 79, “VR and AR for Future Education”).

6

Cross-References

▶ Adoption of Mobile Technology in Higher Education: An Introduction ▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Augmented Reality in Education ▶ Cross-Country University Collaboration Barriers and Solutions ▶ Design and Implementation of Chinese as Second Language Learning ▶ Design Considerations for Mobile Learning ▶ Development of Chinese Character-Writing Program for Mobile Devices ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Mobile-Based Virtual Reality: Why and How Does It Support Learning ▶ Parental Education: A Missing Part in Education ▶ SmartLab Technologies ▶ Student Feedback in Mobile Teaching and Learning ▶ Tutors in Pockets for Economics ▶ VR and AR for Future Education ▶ Wearable Technologies as a Research Tool for Studying Learning

Appendix A: Survey from Australian Undergraduate Students When do you usually use your mobile phone/devices? #

Answer

%

4

Having foods

59 %

1

In lectures or tutorials

65 %

7

Meeting my friends

70 %

2

Studying at home/ library

76 %

3

Waiting

94 %

5

Walking or on transportations

85 %

6

Working

41 %

What brand of mobile device(s) you are currently using?

28

Y. A. Zhang

#

Answer

%

1

iPhone or IOS devices

74 %

2

Mobile devices with Android systems

24 %

3

Others (Please specify)

7%

Which applications or websites you usually access when you study on your mobile phone? #

Answer

%

1

Google

91 %

2

Wikipedia

34 %

3

Youtube

55 %

4

E-learning site from university

57 %

5

iTunes U or Google Play applications

16 %

6

On-line news

23 %

7

Tutors in Pockets

27 %

8

Others (Please indicate)

5%

How long you use your mobile phone to study per day? Min Value

Max Value

Average Value

0.00

8.00

0.73

Do you think the mobile application have positive influences on the following aspects of your study? #

Answer

Response

%

1

It increased my learning efficiency

13

38 %

2

It helped me study anytime and anywhere

19

56 %

3

It helped me study utilizing the small time slots (e.g. waiting for bus)

11

32 %

4

It helped my lecture/tutorial study

13

38 %

5

It made me feel interested in this subject

9

26 %

6

It engaged me in a discussion with other students or teachers

3

9%

7

It increased my performance in this subject

9

26 %

8

Others (Please specify)

5

15 %

2

Characteristics of Mobile Teaching and Learning

29

Appendix B: Survey from Chinese Undergraduate Students Did you try any of these studying methods after class? #

Answer

Response

%

1

Online study

89

61 %

2

Interactive study

24

16 %

3

Mobile study

13

9%

4

Multimedia study

18

12 %

5

Others

3

2%

Total

147

100 %

What mobile phone (system) are you using? #

Answer

Response

%

1

IOS

35

24 %

2

Android

50

34 %

3

Nokia mobile devices

28

19 %

4

Motorola

8

5%

5

Others

26

18 %

Total

147

100 %

When do you usually use your mobile phone? #

Answer

Response

%

1

At home

71

48 %

2

On the way or waiting for bus

76

52 %

3

In class

29

20 %

4

After class

99

67 %

5

Doing part-time job

9

6%

6

Having party with my friends

30

20 %

7

Other time

9

6%

The average length of your mobile study is: Min Value

Max Value

Average Value

0.00

8.00

0.60

30

Y. A. Zhang

What would you think mobile learning would help? #

Answer

Response

%

1

Increase learning efficiency

76

52 %

2

Study anywhere and anytime

60

41 %

3

Utilise smaller time slots to study

80

54 %

4

Increase my searching and learning in class

33

22 %

5

Increase my interests in learning

25

17 %

6

Engage me in discussion with students and teachers

18

12 %

7

Increase my performance

18

12 %

8

No difference to me

9

6%

9

Others

3

2%

References Ahn, D., and D.-H. Shin. 2013. Is the social use of media for seeking connectedness or for avoiding social isolation? Mechanisms underlying media use and subjective well-being. Computers in Human Behavior 29: 2453. Alhassan, R. 2016. Mobile learning as a method of ubiquitous learning: Students’ attitudes, readiness, and possible barriers to implementation in higher education. Journal of Education and Learning 5: 176. Alkhezzi, F., and W. Al-Dousari. 2016. The impact of mobile learning on ESP learners’ performance. The Journal of Educators Online 13: 73. Alley, M. 2009. Mobile learning. Edmonton: AU Press. Al-Rahmi, W.M., M.S. Othman, and M.A. Musa. 2014. The improvement of students’ academic performance by using social media through collaborative learning in Malaysian higher education. Asian Social Science 10: 210. Baage, S.U. 2013. Using Wimba Voice Board to facilitate foreign language conversation course. In The plugged-in professor tips and techniques for teaching with social media, ed. S.P. Ferris and H.A. Wilder. Oxford, UK: Chandos Publishing. Becker, A.S., A. Freeman, C. Giesinger Hall, M. Cummins, and B. Yuhnke. 2016. NMC/CoSN Horizon Report: 2016 K-12 Edition. Austin: The New Media Consortium. Bredl, K., and W. Bösche. 2013. Serious games and virtual worlds in education, professional development, and healthcare. Hershey: IGI Global. Britt, L.L. 2013. Writing for Wikipedia: Co-constructing knowledge and writing for a public audience. In The plugged-in professor tips and techniques for teaching with social media, ed. S.P. Ferris and H.A. Wilder. Oxford, UK: Chandos Publishing. Buffington, M.L. 2013. Organizing with pinterest and delicious. In The plugged-in professor tips and techniques for teaching with social media, ed. S.P. Ferris and H.A. Wilder. Oxford, UK: Chandos Publishing. Butoi, A., N. Tomai, and L. Mocean. 2013. Cloud-based mobile learning. Informatica Economica 17: 27–40. Castro, J.C. 2012. Learning and teaching art: Through social media. Studies in Art Education 53: 152–169. Cochrane, T. 2016. Mobile VR in education from the fringe to the mainstream. International Journal of Mobile and Blended Learning 8: 44. Dabbagh, N., and A. Kitsantas. 2012. Personal Learning Environments, social media, and selfregulated learning: A natural formula for connecting formal and informal learning. The Internet and Higher Education 15: 3–8.

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Transformation of Traditional Face-to-Face Teaching to Mobile Teaching and Learning: Pedagogical Perspectives Jan Turbill

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 A Framework for Designing and Implementing “Online” Pedagogy . . . . . . . . . . . . . . . . . . . . . . . 4 Principles for Designing and Implementing Online Courses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Building an Online Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Running the Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Teaching students in a face-to-face context has been and, in many institutions of education, still is the only form of teaching in higher education. However, in the past 20 years, there has been a slowly increasing movement toward transforming the higher education teaching and learning experience from face-to-face to a mobile online learning experience. For most teachers this move is quite a challenge and raises many issues and questions. These include questions such as: What mobile technologies are available to employ? What teaching practices are best to use? Will student learning outcomes be better or worse as a result? And for many the question asked is simply how can this be done? In this chapter a framework for designing and implementing “online” pedagogy is shared. This framework is underpinned by Turbill’s (From a personal theory to a grounded theory in staff development. Unpublished doctoral dissertation, University of Wollongong, Wollongong, 1994; The role of a facilitator in a professional learning system: the frameworks project. In: Hoban G (ed) Teacher learning for J. Turbill (*) University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_54

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educational change: a systems thinking approach. Open University Press, Buckingham, pp 94–114, 2002) integrative theory of learning and draws on Herrington and Bunker’s (Quality teaching online: putting pedagogy first. In: Quality conversations, proceedings of the 25th HERDSA annual conference, Perth, 7–10 July 2002, pp 305–312) pedagogical guidelines. Both are unpacked and explained using a case study that provides the reader with a pedagogical perspective that is both doable and proven to be successful.

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Introduction

In the past 20 years, there has been a slowly increasing movement toward transforming higher education teaching and learning experiences from traditional face-to-face to mobile online learning. For most teachers this move has been quite a challenge and raised many issues, concerns, and questions. These include questions such as: What mobile technologies are available to employ? What teaching practices are best to use? Will student learning outcomes be better or worse as a result? And for many the question asked is simply how can this be done? In this chapter a framework for designing and implementing “online” pedagogy is explored. This framework is underpinned by Turbill’s (1994, 2002) integrative theory of learning and draws on Herrington and Bunker’s (2002) pedagogical guidelines. Both are unpacked and explained using a case study that provides the reader with a pedagogical perspective that is both doable and proven to be successful.

2

Background

Most teachers enjoy their face-to-face teaching in higher education learning. It has been the “tried and true” way of teaching for many decades, and they feel comfortable and confident in this “way” of teaching. Usually the face-to-face approach for large cohorts of students comprises 1–2 h of lectures followed by 1 h smaller tutorial classes. In some cases when the cohort of students is smaller, it is possible to run 2–3 h face-to-face classes. Teaching Reading was such a class. The class of usually 10–15 students was developed and designed by a senior academic (who for the purpose of this chapter will be named Dr. Brock) and aimed to explore the range of theories and practices involved in the teaching of reading at the postgraduate level. The student cohort of mostly practicing teachers came together for 3 h “same time, same place” each week for 13 weeks (Redmond 2011). The class had been rated highly by the students for 5 years in each semester of the academic year. The predictable flow of the 3 h involved: • Discussion of set weekly readings and tasks in groups of three • New input provided in the form of “mini” lecture by the teacher

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• Collaborative small group workshops aimed to discuss and apply new input • A whole group sharing and “pulling together” of ideas, outcomes, and challenges • Review of homework for the following week, clarification of assessments (when needed), and any other issues Critical to the effectiveness of the class was the assessment practices/tasks that were designed to be accumulative over the 13 weeks. Each week students were required to read and review a set article (between-session readings [BSR]) and to trial and review a given teaching practice (between-session tasks [BST]). They were asked to provide a one-page summary for each, identifying connections to their current and future professional practice. Students used their reflective one pager during the weekly sharing and discussion that always began our class. They submitted their weekly responses for marking every few weeks, and the marks are accumulated into final grades for assessments 1 and 2, respectively. The final assessment required students to review all their responses for the two assignments, reread where needed, and write an evidence-based rationale and teaching plan on the topic “Effective Teaching of Reading in My Context.” Overall students and teacher rated the subject as very effective for their learning and for the changes in reading pedagogy that followed. Students learned a lot from each other as well as from the teacher. They were able to discuss current issues as they arose and keep each other up to date with new reading research and practices. The teacher was able to introduce points of interest from the media and newly published articles as they occurred. As the weeks passed students became a “community of learners” (Barth 1990), sharing personal experiences of family and homelife as well as teaching and learning experiences from their respective classrooms. In any one class there was a range of teaching contexts and experiences. For example, in one class there were three teachers of many years of experience who had taught children from Grade 1 through to Grade 6, two high school teachers both with a science background, two specialist teachers of English, one teacher in his third year of teaching Grade 1, a teacher in the local prison, and another who taught vocational education (plumbing). Such a range of experiences led to rich discussions and many stories. Therefore when this small but successful face-to-face graduate class was forced to “go online” using mobile technologies, it created a great deal of anxiety and uncertainty for Dr. Brock. There were two key reasons provided for this decision. Firstly, Dr. Brock was informed that the faculty could no longer sustain small classes of 10 or so students, and secondly, it was hoped that the online format would attract both national and international graduate students who were prepared to enroll in asynchronous classes. In particular a small private university in Minnesota, USA, had shown keen interest in offering an online version of this course in their newly developed doctoral program. And so the challenge began for this teacher. Just how does one transform a 13-week effective 3-h face-to-face class into an online format without losing teaching and learning opportunities such as interaction, reflection, sharing, and most importantly collaboration? How does one create the community of learners that was so evident in the face-to-face approach?

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At the time there was little published research to guide such a move, nor were there sophisticated learning platforms available today. However, Dr. Brock had just completed her doctoral studies into what constituted effective professional development for teachers. The study developed a grounded theory of pedagogy that led to active and deep professional learning. Dr. Brock believed that this theory could be used as a framework to both guide and support the transformation of her face-to-face class to an online space. In what follows is a clear explanation of this grounded theory and how it “works.” Moreover the principles of this theory are used to demonstrate how Dr. Brock transformed her face-to-face synchronous class to an effective online asynchronous learning experience. Current research is juxtaposed throughout the explanation in order to respond to the many issues raised throughout this transformation. Finally key principles are highlighted in order to provide a sound pedagogical perspective for developing online and mobile learning.

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A Framework for Designing and Implementing “Online” Pedagogy

The model described in Fig. 1 is a visual representation of “an integrative theory of learning” (Turbill 1994, 2002). The theory emerged from research that investigated the “why” and “how” of a highly successful professional learning program for teachers. It can be used as a guide and frame for developing any teaching and learning enterprises. It aligns readily with action learning (Aubusson et al. 2009; Albers 2008) and transformative pedagogy (Meyers 2008) and is underpinned by the principles of social constructivism (Twomey Fosnot 1996). Briefly, the model depicted in Fig. 1 demonstrates that there are personal (insideout view) and external (outside in view) dimensions of learning that need to be considered in any learning enterprise. All learners (students) bring some background knowledge, beliefs, and/or views about that which they are about to learn (My Personal Theory) that underpin their existing knowledge, attitudes, and actions (My Theory in Practice). This inside-out view is constantly being challenged and informed (or should be) by new information, ideas and input (The Theories of Others), and new actions and practices (Theories of Others in Practice). Both dimensions are important and need to be valued equally. Critical in the construction of “new learning or knowledge” is the integration between “my inside view” and “the outside view” of that which is to be learned. Key drivers of such integration are the interactive processes that occur through reflection, sharing, and collaboration. The model dictates therefore that certain structures and processes should be put in place for such interaction and integration to occur. This, in turn, leads to deep learning and understandings that becomes My Personal Theory. Langer (1998) refers to such learning as moving toward “mindful learning” in that the knowledge and understandings are said to be “known”; however, the knower is conscious that such knowing will be constantly challenged and changing.

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Fig. 1 An integrated theory of learning (Turbill 1994, 2002) My Personal Theory

Inside outview

Collaboration Reflection Sharing

Theories of Others

My Personal Theory in Practice

Collaboration Reflection Sharing Outside in view

Theory of Others in Practice

For such a state of knowing to occur, the structures (e.g., teaching practices, assessments) and processes need to be carefully aligned and indeed synergistic in their operation. Thus the challenge for the teacher, the designer, the developer, or facilitator of that which is to be “learned” becomes choosing the “right” mix of structures and their respective processes so that optimal learning conditions not only exist but are made operational in such a way that they will become synergistic (Turbill 1994, 2002). With the skillful and judicious selection of structures (teaching practices and assessment tasks), a learning culture is created in which there are sufficient learning processes in place to engage and enable deep learning. These include: • • • • • •

Time for reflection, both written and spoken Time for sharing experiences and responses to readings with peers Opportunities for collaborative learning in small groups Opportunities to try and/or apply new practices Input (new knowledge) through a variety of media Readings that support, extend, and challenge the various concepts introduced in the course • Opportunities to work collaboratively (Turbill 2001) No one structure is sufficient, and none is more important than another, but together they operate synergistically so that any potential inhibiting factor in the learning culture will have only a temporary lifespan as learners work through what they want or need to know and learn. In such learning cultures, trusting and caring relationships develop. Learners become highly supportive of one another’s efforts

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and understandings. A shared meaning begins to develop among the learners and with it a shared language. This does not mean that everyone has the same views, beliefs, or depth of knowledge – far from it – but it does mean that members of the learning culture begin to understand one another’s perspectives. The learning culture moves toward what Barth (1990) calls a “community of learners.” Such a community develops a sense of belonging that Lave and Wenger (1991) argue is an intrinsic condition for the creation and sharing of knowledge.

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Principles for Designing and Implementing Online Courses

Having made the decision to go “online,” Dr. Brock found there were many more decisions ahead. Before trying to adapt the teaching and learning activities (the structures) she had used successfully in her face-to-face teaching space, it was found she needed to learn just what technologies were available to her and her students in an online learning space, a learning space where students would no longer participate in the “same time, same place” approach. In particular, it was necessary to learn what mobile technologies her institution supported and just how to go about seeking support in knowing what affordances these offered to best enhance her teaching and engage her learners. Redmond (2011, p. 1051) explains, “The changing nature of both the student body and available technologies have required academics to change their approaches.” She offers four categories of teaching and learning spaces, namely: 1. Same time, same place – participants operate in the more traditional face-to-face teaching approach. 2. Different time, same place – participants interact in the same space with all participants, but at a time they choose, for example, asynchronous online discussions. 3. Same time, difference place – participants work independently but, at the same time, use online social media tools such as Skype and videoconferencing. 4. Different time, different place – participants are separated geographically and by time and operate always in asynchronous mode. The choice of teaching and learning space is contingent upon the range and availability of technology tools and the affordances these offer. Redesigning a face-to-face traditional course using an integrative pedagogical approach underpinned by constructivism also requires changes in roles and responsibilities of teacher and students, use of technology, relationships, and sometimes a perceived change of prestige and power (Redmond 2011). There are many successful structures that Dr. Brock had used in face-toface teaching. But which of these would transfer successfully to an online learning space was an unknown in the first instance. Herrington and Bunker’s (2002, p. 307) pedagogical guidelines help to address this decision. Their guidelines take into account the affordances offered by the mobile

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technologies and “assist both academics and instructional designers as they design new online units.” Moreover the guidelines can be used as an evaluative tool “to assess the quality of existing online units determining areas of possible improvement.” These guidelines serve as a useful framework to keep in mind as one moves to the actual designing of the online course.

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Building an Online Course

The first step in developing an online course should be to scope out a “big picture” of all the “structures” needed in the course. Figure 2 is such a scoping of the big picture of the online course for the graduate class Teaching Reading that Dr. Brock developed. The process of scoping the overview highlighted the many connections between and among the range of structures that had been so effectively part of the face-to-face class and that were highly desirable to be part of an online class. Working through this process also highlighted the areas where there was going to be the need for technology designer support. Having scoped out the design of the course as a whole, it became apparent that the weekly topics, activities, workshops, and readings for the whole course need to be prepared and “ready to go” before the course began. The teaching space, “different time – different place” (Redmond 2011), required that the logic and flow of the key concepts, workshop tasks, and understandings needed to be clearly written and highly explicit so students could move through the topics with as little confusion as possible. Keeping the guidelines in Table 1 clearly in mind supported Dr. Brock’s desire to develop an engaging learner-centered environment with many opportunities for collaboration and real-life tasks and problems in the teaching of reading.

Fig. 2 Structures in teaching reading course

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Table 1 Pedagogical guidelines (Herrington and Bunker 2002) Authentic tasks

Description The learning activities involve tasks that reflect the way in which the knowledge will be used in real-life settings

Opportunities for collaboration

Students collaborate to create products that could not be produced individually

Learnercentered environments

There is a focus on student learning rather than teaching

Engaging

Learning environments and tasks challenge and motivate learners

Meaningful assessments

Authentic and integrated assessment is used to evaluate students’ achievement

Examples • Problem-based learning activities using real-life contexts • Learning tasks based in workplace settings • Tasks are complex and sustained • Tasks are set that require students to collaborate meaningfully • Peer evaluation, industry mentors • Buddy systems employed to connect learners • Teacher’s role is one of coach and facilitator • Inquiry and problem-based learning tasks • Activities support and develop students’ metacognitive skills • Interesting complex problems and activities rather than decontextualized theory • Activities arouse students’ curiosity and interests • Activities and assessments linked to learners’ own experiences • Assessment is integrated with activities rather than separated from them • Opportunity to present polished products rather than simple drafts • Opportunities exist for students and their teachers to provide support on academic endeavor

Ten topics were developed to be completed by students in the 13-week session. A predictable navigation pane contained all the above structures and was predictable in that it was used for each topic (Fig. 3). The Introduction to Topic outlined the key concepts covered in each topic. Workshop Tasks were designed for students to explore the concepts that were being introduced. Students were required to work through these tasks and respond accordingly. Some topics had only one task, while others had up to four shorter tasks. Students were asked to write their responses online and posted them for all to read (pink outline indicates students’ submitted responses). Making Connections provided a summary of the key connections that were deemed important in that topic. Students were asked to add further connections, particularly any pertaining to their workplace. For the Next Topic listed Between Topic Reading(s) (BTRs) and Between Topic Activities (BTAs) that students were required to carry out and respond to between topics. The former were set readings that students were asked to respond to using two key questions as a framework:

Transformation of Traditional Face-to-Face Teaching to Mobile Teaching and. . .

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Introduction to Topic

Workshop Tasks

Making Connections

For the Next Topic

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Student Responses

Fig. 3 Predictable navigation pane

• What are the key points for me in this article? • What are the implications of these points for my teaching of reading in my particular context? The students’ responses were to be composed in “academic” writing, using appropriate citations and referencing, and posted to the online discussion forum found in Student Responses. Where relevant, students were to cite their classmates’ comments, as these were perceived as published pieces and thus constituted the “theories of others.” Students were also encouraged to make connections between their set readings and the practical activities. These responses in turn accumulated, as in the face-to-face class, into two of the three assessment tasks.

6

Running the Course

The first online cohort began with nine students and had mixed results. Both students and teacher found it “a lot of work.” All argued that the workload had to be reduced. The discussion space was the typical threaded forum and it became unwieldy and confusing. Students complained that often they could not find their peers’ responses, and if they did, there was no time to read them, let alone make any personal comments. The discussion space, it was decided, had to be reviewed and changed. An even more disturbing outcome was that students commented that they tended to feel isolated and did not feel they “knew” their fellow classmates. They certainly did not feel part of an “engaging learning community.” Thus while the assessment tasks were deemed to be authentic and meaningful as Herrington and Bunker (2002) suggest, the opportunities to collaborate with peers and to feel part of an engaging learning environment were wanting. It was deemed therefore necessary to explore new ways of interacting and sharing with each other within the online space. Thus several “structures” had to be changed. First, it was decided that in the Workshop Tasks students would still be required to post their responses to the activities, but they would be no longer required to respond to each other’s posts, although they were encouraged to read each other’s postings. Second, in Making Connections, it was decided that no response would be required at all. This decision was based on the students’ comments that any response they may have posted in Making Connections will mostly likely be repeated in their final response. Third, in Students’ Responses a more organized threaded forum was designed for students to post their structured responses to set readings (BTRs) and activities (BTAs). And finally students were no longer required to respond to each other’s postings in this space, unless they wanted to do so.

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In order to set up a more informal mode of interaction, an e-mail Listserv was introduced to which students subscribed in the first week of the course. Because e-mail was perceived as more informal, it was hoped students would be more prepared to “talk” to the teacher and one another as they might do in a face-to-face setting. It was in this space where interaction, sharing, reflection, and collaboration could take place, it was hoped, albeit in an asynchronous space. To ensure that students began to “know” each other, they were asked to post personal background information in their first week’s post and where relevant throughout the course. They were also invited to upload a photo of themselves. Dr. Brock modeled this in the first weeks by sharing information about her weekend, her anticipation in meeting new students online, and, as in later posts, stories about her dog, important events, and so on. Students followed suit and shared their teaching contexts, school happenings, stories about their own children and those they taught, and more. Such “chatter” served an important role in allowing all to “know” each member on the Listserv and thus build a “community of learners.” In many cases students who found they lived near each other organized to meet offline over coffee and chat about their work. Those who lived overseas or interstate also developed online friendships by e-mailing and even Skyping each other outside of the class space. While students’ responses to the readings (BTRs) and activities (BTAs) were posted on the designated forum, they were also encouraged to use the Listserv to share key connections, ideas, and questions. This led to some very interesting discussions and debates. As the facilitator (and if needed moderator) of the Listserv, it was important for Dr. Brock to post (and thus model) relevant news items, web links to YouTube, useful sites, and probing questions and generally to encourage interaction. (It is important to note that social media has now many different mobile technologies that could have been used other than Listserv, and there will be many chapters in this handbook that will provide information about these tools.) A critical “structure” change was that of the teacher’s role. Too often Dr. Brock found that responses to students’ questions and comments turned into “mini lectures.” This practice tended to deter students from providing comments and input. The literature strongly suggests that it is important that the lecturer not be perceived as the expert (Burton 1998; Pelz 2004). The course had many “experts” in those who had written the book chapters and journal articles that made up the assigned readings, as well as articles, news items, and so on, that students posted. A teacher’s role should be to participate in, mediate, and facilitate student learning in a safe and inviting environment (Meyers 2008). Taking on a more facilitating role rather than an expert role is not easy for teachers. However, many have argued that it is most important that the teacher needs to be the “guide on the side” rather than the “sage on the stage.”

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Future Directions

Over the ensuring years, these structures and processes have “worked” in each session’s course to build a strong community of learners who are highly engaged, who are willing to share and challenge each other, and who develop deep knowledge

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and analytic skills about the teaching of reading (Meyers 2008). While the online space allows for a general “repository” for the input, tasks, and students’ responses, the use of interactive mobile tools is critical in bringing together the personal dimension (inside-out view) and external dimensions (outside in view), as outlined in Fig. 1, in order that there are many opportunities to reflect, collaborate, and share. Students who come from various educational backgrounds and geographical locations become online professional colleagues and friends. A foundation of trust develops where students become self-directed and empowered learners. Meyers (2008, p. 220) suggests that online discussions allow students to “express themselves thoughtfully without interruption, which is particularly significant for those at a greater risk for marginalization in [face-to-face] class due to their gender, race, social class or even personality style.” Figure 4 demonstrates an analysis of the nature of interactions that occurred on the Listserv (or need to occur using any social online medium). Each of these four key interactive structures management and organization, personal contextualizing, professional contextualizing, and knowledge building plays a critical and synergistic role in building that foundation of trust that in turn leads to highly effective learning communities. The case study experiences and theory shared in this chapter suggest that there are several key practical principles to be learned and used in order to design and develop effective mobile teaching and learning. These include:

Fig. 4 Structures involved in effective online interaction

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• Tasks need to be clearly described, with the purpose of each made very clear. • Assessment tasks need to be clearly described and serve as learning experiences in themselves. • Communication tools need to be chosen to provide students with opportunities “to get to know” and trust each other in order to become a member of a learning community. • The teacher needs to be a participant in and facilitator of students’ learning. • The teacher needs to “listen” to students and be prepared to be flexible according to their needs. The pedagogical perspective explored in this chapter can be neatly summarized by Pelz’s (2004) principles of effective online pedagogy: • Let the students do (most of) the work. • Interactivity is heart and soul of effective asynchronous learning. • Strive for presence.

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Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Flexible Spaces and Sustainable Opportunities: Designing Online Professional Learning for Sessional Teachers

References Albers, Cheryl. 2008. Improving pedagogy through action learning and scholarship of teaching and learning. Teaching Sociology 36(1):79–86. Aubusson, Peter, Robyn Ewing, and Garry Hoban. 2009. Action learning in schools: Reframing teachers’ professional learning and development. London/New York: Routledge. Barth, Roland. 1990. Improving schools from within. San Francisco: Jossey-Bass. Burton, Wendy. 1998. Facilitating online learning: Charting the conversation. Paper presented at the third annual teaching in the Community Colleges conference, online instruction: trends & issues II, Honolulu. http://tcc.kcc.hawaii.edu/previous/TCC%201998/paper/burton.html. Accessed Jan 2011. Herrington, Anthony and Bunker, Alison. 2002. Quality teaching online: Putting pedagogy first. In Quality conversations, proceedings of the 25th HERDSA annual conference, Perth, Western Australia, 7–10 July 2002, 305–312. http://www.herdsa.org.au/wp-content/uploads/conference/ 2002/papers/HerringtonA.pdf. Accessed 20 July 2014. Langer, Ellen. 1998. The power of mindfulness learning. Reading: De Capo Press. Lave, Jean and Etienne Wenger. 1991. Situated learning: Legitimate peripheral participation. New Jersey, USA:Cambridge University Press. Meyers, Steven A. 2008. Using transformative pedagogy when teaching online. College Teaching (Fall):219–224. http://sites.roosevelt.edu/smeyers/files/2011/04/transformative.pdf. Accessed 20 July 2014.

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Pelz, Bill. 2004. (My) Three principles of effective online pedagogy. Journal of Asynchronous Learning Networks 8(3):33–46. https://www.ccri.edu/distancefaculty/pdfs/Online-PedagogyPelz.pdf. Accessed 20 July 2014. Redmond, Petrea. 2011. From face-to-face teaching to online teaching: pedagogical transitions. In ASCILITE 2011: 28th annual conference of the Australasian Society for computers in learning in tertiary education: Changing demands, changing directions, 4–7 Dec 2011, Hobart. http:// eprints.usq.edu.au/20400/. Accessed 20 July 2014. Turbill, Jan. 1994. From a personal theory to a grounded theory in staff development. Unpublished doctoral dissertation, University of Wollongong, Wollongong. Turbill, Jan. 2001. A face-to-face graduate class goes online: Challenges and successes. Reading Online 5(1). http://www.readingonline.org/international/inter_index.asp?HREF=turbill1/index. html. Accessed 20 July 2014. Turbill, Jan. 2002. The role of a facilitator in a professional learning system: The Frameworks project. In Teacher learning for educational change: A systems thinking approach, ed. Garry Hoban, 94–114. Buckingham: Open University Press. Twomey Fosnot, Catherine (ed.). 1996. Constructivism: Theory, perspectives, and practice. New York: Teachers College Press.

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Flexible Spaces and Sustainable Opportunities: Designing Online Professional Learning for Sessional Teachers Bonnie Amelia Dean, Kathryn Harden-Thew, Janine Delahunty, and Lisa Thomas

Contents 1 2 3 4 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (Casually) Teaching the (Casual) Teachers: A Need for Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . Considerations for Designing a Program to Support Sessional Teaching . . . . . . . . . . . . . . . . . . . Online Design to Enhance Delivery of Professional Development . . . . . . . . . . . . . . . . . . . . . . . . . Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Case Study 1: Online Modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Case Study 2: Sessional Teacher’s Professional Development Program . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The provision of mobile technologies in higher education has unquestionably opened possibilities for how we design learning environments. Opportunity arises to explore mobile design features not only for engaging students but also for how we support and develop university teachers. This chapter explores pedagogic principles of designing an online learning environment for the professional development of teachers. Specifically, this chapter looks at programs that enhance teaching and learning skills and capacities for sessional teachers, those on casual, contractual or part-time employment, who play a crucial role at the coalface of student learning. Two cases are presented that demonstrate different, yet complimentary design features of online programs. These cases utilize flexible spaces and enable sustainable opportunities for engagement by promoting greater access and support for sessional teachers’ professional learning. B. A. Dean (*) · K. Harden-Thew · J. Delahunty · L. Thomas Learning, Teaching and Curriculum, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected]; [email protected]; [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_134

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Introduction

The uptake of technology has created new learning spaces in higher education, radically changing approaches to learner engagement (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Online affordances have freed barriers associated with traditional face-to-face approaches in a range of educational settings, including the way teachers teach their subjects as well as the medium in which those same teachers attend to their own professional development. Not only are teachers required to use these new technologies themselves, but the way in which these technologies and other aspects of teaching are learned has transformed due to the opportunities created by online, flexible spaces. As institutions continue to encourage, explore, and embed technological solutions in curriculum, opportunities arise to support staff through demonstrating the ways in which teaching and learning can be mobilized (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Traditionally, professional development of teaching comprised face-to-face workshops or programs, designed as mandatory for particular career stages (e.g., the new academic) or voluntary one-off events around a particular topic or innovation. In these cases, invitation to participate was restricted, usually to academic staff, and presenters “modelled” best practice in a physical context to provide teachers with techniques which they can then replicate, apply, or adapt in their contexts. In order to equip teachers with the tools to authentically use technology, these methods must also be employed during training. The aim of this chapter is to present two online initiatives that aim to build teacher’s teaching skills and practice at one institution that enable professional development through flexible and sustainable platforms. These initiatives meet a distinctive need for teaching staff, designed specifically for those teachers who are contractual or sessional. The first is a suite of online professional development modules on topics relating to teaching and learning in higher education. The second is a semester-long online program tailored for practice sharing and community building for sessional teachers across disciplines. The two online initiatives are different in design yet complimentary, are open to all sessional staff, are available year-round, and enable teachers to remain close to their teaching contexts during participation.

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(Casually) Teaching the (Casual) Teachers: A Need for Change

Professional development is an imperative for all teachers. In Australia, the majority of university teaching, including demonstrating, tutoring, and lecturing, is undertaken by sessional staff (May et al. 2013). While absolute figures are unknown, research claims between 20% up to 80% of faculty teachers as sessional (Percy et al. 2008). Sessional teachers are any nonpermanent teachers employed on a course-by-course (subject-by-subject) or sessional basis, including postgraduate students, research fellows, industry professionals, clinical tutors, or casually employed lecturers.

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Historically, it has been reported that sessional staff have not had the same opportunities to access professional development and work resources compared to that of ongoing staff (May et al. 2013; Johannes et al. 2013; Percy et al. 2008; Brown et al. 2016). Having limited access to resources, such as a desk and computer or learning materials, as well as to teaching support, such as professional learning programs or resources, cannot only impact job satisfaction (May et al. 2013) but also affect the quality of student’s learning experience (Myconos 2005). It has been said that “the quality of education suffers when students are taught by teachers who cannot be available, who are exhausted, demoralized, and frustrated, who lack the time to be as well prepared as they would like to be. . .” (Dannin 2003, p. 10). Recently, sessional teaching support and development practices have become more visible (Gunson et al. 2016; Savage and Pollard 2016; Thomas et al. 2016; Williams and Beovich 2017). Large-scale reviews and research into sessional practices have contributed to this visibility. In Australia over a decade ago a national project by Percy et al. (2008) broke ground in this area, exploring the recognition, enhancement, and development of casual teachers. Known as The RED Report, this study illuminated the discrepancies and disadvantages experienced by sessional staff relating to teaching load, remuneration, support received and employment conditions, and issues with accessing accurate data. Taking the findings from The RED Report further, Harvey et al. (2014) proposed the BLASST model, benchmarking leadership and advancement of standards for sessional teaching. This model was developed for adaption at the institution, faculty/school, department, and individual level and designed to be used as a reflection and evaluation tool. The BLASST model has featured widely across Australia in university’s sessional support practices (Brown et al. 2013, 2016; Gilbert 2017; Gunson et al. 2016). The emergence of contextual and practice-based studies among other national events and initiatives indicates that importance of support for sessional staff is increasingly being realized across the sector (Harvey 2017). This recent movement enables institutions to not only disseminate good practice but also allow the academic community to learn what sessional teachers really want in regard to professional learning.

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Considerations for Designing a Program to Support Sessional Teaching

In order to adequately support our frontline teachers, focus needs to be afforded to the development of programs or opportunities that enhance sessional teacher’s teaching skills (Gunson et al. 2016; Savage and Pollard 2016; Thomas et al. 2016; Williams and Beovich 2017). While there are various ways to design programs that support the development of teaching capacities, Shackleton-Jones (2012) has grouped these as either “push” or “pull” delivery models. In a “push” model, learning outcomes are crafted prior to engagement, and selected information is delivered to participants, that is, “pushing” the information forward. In a “pull” model the participant is more self-directed, choosing to engage in opportunities and “pulling” meaningful information forward when needed.

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There are benefits and restrictions to adopting either a push or pull delivery model. Pull models, for example, are more flexible and acquiescent to preexisting knowledge, allowing participants greater autonomy to explore areas of interest. Push models work well in more structured environments, where learning outcomes are made explicit and are measurable. However, several concerns surface with push and pull models when it concerns sessional teachers. First, one-off events can often preclude ongoing engagement or community building that arises from practice sharing and networking among like-minded peers, and therefore a program that continues (ongoing or for a period of time) is more desirable to build trust and relationships (Dean et al. 2015). Second, formal courses run the risk of being too far removed from an individual’s teaching context, and therefore relevancy through direct application and reflection on practice is necessary to make any real and lasting change (Boud and Brew 2013; Dean et al. 2015). Third, given the temporary affordances of sessional teaching, programs or resources that are available throughout the year would offer the greatest reach and allow for the differences in timing of university teaching. Therefore a mix of push and pull designs would offer the greatest opportunity to reach the needs and learning requirements of sessional teachers. In a study investigating the role of community in an online program for sessional teachers, Dean et al. (2017) found several benefits in drawing casual teachers together in an online space to talk about their teaching. Teachers reported the inclusive nature of the online program curtailed the sense of isolation previously experienced in being “casual.” Teachers also highlighted an increase in collegiality with teachers across disciplines, changes to their teaching practice, confidence in teaching, and increased opportunity for reflection. These findings resonate with others, such as Harvey (2017, p. 5) who states: [we] need to provide professional development that is context specific, whether that be generic and institutional or disciplinary. As sessional staff are a diverse group, we need to respond with multiple and flexible modes of delivery for professional development, ranging from face-to-face block mode or modularised sessions, to workshops and online options, but all within a Community of Practice framework.

There is a critical need to establish professional development opportunities for sessional teachers through multiple and flexible modes of delivery (Harvey 2017). As teaching modes shift from predominately face-to-face to including more online and blended forms of delivery, opportunities arise for designing professional development programs that employ this same technology.

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Online Design to Enhance Delivery of Professional Development

The rapid expansion of online learning options and mobile technologies in our classrooms presents emerging opportunities to enhance the quality of learning not just for the students but also for teachers. Teachers (tutors, lecturers, demonstrators) could benefit from learning through various technologies as a means of providing

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flexible opportunities for professional learning (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). As a tool, technologies make these opportunities much more accessible, enabling just-in-time accessibility of information (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Online design of professional development is an important pedagogical movement in higher education academic development that currently seems to be lacking in uptake and explication of best practice (Dean et al. 2015; Delahunty et al. 2014). According to Dean and colleagues (2015), the prolific use of mobile technologies such as phones, tablets, or notebooks in everyday life offers innovative tools for engaging teachers in professional development, including tailoring opportunities for sessional staff. They insist the affordances of mobile technologies for professional development include: • Context independency: enabling greater reach of teachers (including those in diverse physical locations) and allowing teachers to remain in their teaching context • Accessibility: information available “in the palm of your hand” • Temporal proximity: just-in-time and when needed based on experiences, knowledge, and skill level • Practice relevancy: allowing teachers to directly, and readily, transform their practice While not intended as a replacement for the experience of face-to-face learning, technologies provide great potential for collaboration and interaction both in blended and fully online learning experiences (Delahunty et al. 2014). The design features of online professional development programs must take into consideration user familiarity, accessibility, and flexibility afforded by mobile technologies (see ▶ Chap. 27, “Tutors in Pockets for Economics”). There is no one-sizefits-all approach; rather each program must address the question: how can technology be used to enhance learning and engagement? The purpose of the program must be made explicit in order to inform program design, for instance, does the program aim to bring participants together to discuss key topics and build a community of practice (push design) or is the aim to offer support and greater autonomy in an asynchronous environment that is always available (pull design). In either case, there are certain basic principles of pedagogic online design. Adapted from Verenikina et al. (2017), these include: • Authentic activities that: – Stimulate participation and have relevance to a range of teaching environments – Promote reflection and action – Contain “bite-sized” pieces of information with links to explore further • Clarifying expectations to reduce ambiguity and foster a sense of belonging • Orchestrated opportunities for: – Personal reflection – Discussion and sharing of experiences and resources – Future planning or adaption of ideas into personal teaching contexts

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Clear expectations are essential for participants to feel comfortable and navigate the online learning space. Participants need to know what to do, where to go, why they’re doing it, how to engage, how it relates to them personally and where else they could go to seek further information or support. Clarity in the online environment aids learning as links between prior knowledge and new understandings are more easily found. This is certainly challenged when the mode of learning shifts from face-to-face to online, technologymediated modes, which removes many opportunities usually relied on for gaining immediate clarification. Predictability – knowing what to expect – in online learning contexts becomes a more important consideration when clarity of meaning can be the difference between time spent actually engaging in the learning and time spent wondering what exactly needs to be done (Delahunty et al. 2014, p. 77). Possible approaches to check the clarity of instructions include peer feedback prior to opening an online space, asking for participant feedback, or looking for cues from questions asked in forums. Using these feedback avenues can then aid clarifying design or site structure. Providing consistent and predictable support is also essential and can take the form of the facilitator’s “tone of voice” (use of conversational verses formal language), the ease of navigation and predictability of the site and its activities, access to resources, appropriate guidance in discussion spaces, and contact information to seek further assistance (Delahunty et al. 2014). Research suggests that participant’s sense of belonging in an online learning environment is essential to the educational experience (Thomas et al. 2014). This belonging can be established in multiple ways and contribute to developing a community of practice. A simple yet effective pedagogic strategy to start building a community is to include an “introduce yourself” activity, particularly if participants are off campus and may not have the opportunity to physically meet (Delahunty 2012; Delahunty et al. 2014). Asynchronous discussion forums enable participants to share, respond, and reflect at a time that suits them. There is more incentive to participate in further discussion online when people feel familiar with those in the group and that they are making valuable and appreciated contributions to the group as a whole (Verenikina et al. 2017). Following this, activities could be built around “discussable” topics such as a problem to solve, a case study, a common or current issue, or challenge facing staff – in short, something which is relevant and encourages participants to draw on their own experience and contribute to their own perspectives. There is great potential for “Aha!” moments when real or substantive conversation leads to moments of realization. This can occur online as asynchronous communication can lead to more thoughtful or deliberate interaction. It’s important to recognize however that interaction in an online space usually doesn’t “just happen” because the forum has been established. Participants need a meaningful reason to contribute and to feel safe to share their stories. To explore tools and techniques for enhancing online discussion, the FOLD website (Fostering Online Discussion) at http://www.fold.org.au/ is a valuable resource.

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Case Studies

The following case studies are presented as methods our team of academic developers at the University of Wollongong have employed to support the professional development of sessional teachers, adopting online design pedagogical principles. Our activities to mobilize professional development for sessional teachers are drawn from strong pedagogical foundations underpinned by Thomas et al.’s (2016) teambased curriculum design for creating continuing professional development for university teaching staff. This approach enabled our team to draw on the collective expertise of staff from across the institution and build programs that accommodate disciplinary, departmental, and institutional factors that impact on teaching. In the two case studies that follow, we take a learning-centered approach to demonstrate and encourage inclusive, active, and collaborative learning environments for quality teaching in higher education (Hunt and Chalmers 2012). The cases present ways in which we have designed active learning in the online context, whether it is in a fully facilitated, asynchronous program or a wholly self-directed online module. A pertinent feature of each case study also lies in the inclusion of reflective activity to encourage the participants to embed the conceptual content into everyday teaching practice in their own contexts.

5.1

Case Study 1: Online Modules

Since 2014, the Academic Development and Recognition team, in the Learning, Teaching and Curriculum (LTC) unit at the University of Wollongong (Australia), have developed a suite of online modules to support teaching and learning. The modules are available online, through the learning platform Moodle. They are self-enrolled which means any staff member at the University with a staff username can access these modules. Aligning with a “pull” design approach, these modules are self-paced and asynchronous, allowing participants to enter and browse at their own pace, in their own locations, at their own interest, and in their own time. These modules are not compulsory but instead are designed to support teachers to explore more about university teaching and learning. Each module focusses specifically on a content area relating to teaching and learning in higher education. The online module Designing Learning, for example, relates to ways of developing teaching activities to encourage deep learning of university students. Three modules align with enhancing assessment and feedback practices; they are Why Assess?, Designing Assessment, and Effective Feedback. These modules explore theoretical perspectives, practical examples, and resources through engaging participants in activities around core concepts. Designing Assessment is specifically designed for learners to engage with the University’s Assessment and Feedback Principles, thereby deepening understanding of university policy, context, standards, and practices. There are currently 13 modules with more under development. Table 1 depicts the most frequently visited online modules by sessional teachers along with the online module descriptions.

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Table 1 Online module descriptions Designing learning Helping students learn Transitions

Why assess? Designing assessment Effective feedback

Focusses on ways to design effective learning experiences in order to optimize students’ deep engagement with learning Reflects on the diversity of the student cohort and explores teaching practices that facilitate inclusive learning environments Introduces theories, strategies, and practices that support students in their transitions into their first year of study, through their degree and out of higher education Enquires into the necessity to assess students in higher education. It reviews the purposes of formative, summative, and sustainable assessment Centers on designing effective assessment through engaging with the UOW Assessment and Feedback Principles and demonstrates successful assessment transformation through a local case study Promotes the importance of effective feedback. It explores how to design, implement, and use feedback practices that assist students to engage with learning and evaluate your own teaching practice

Source: From the authors

It is important that every online module looks and feels the same so that participants know what to expect (Delahunty et al. 2014). This assists in creating a sense of belonging in an online space (Thomas et al. 2014). Figure 1 is a screenshot of the online module Designing Learning. As shown, upon entering a module, the module title is featured with the Academic Development and Recognition image as the banner. A brief description provides instructions on how to use the module to highlight the flexibility of the space and ways it can be used differently for each person, stating: This module offers self-paced, practical strategies, theoretical underpinnings and further resources for you to engage with online. If you are seeking a more social experience which will complement the content in this module please check the LTC Events Calendar. As you move through this module, you may choose to engage with each section in sequential order or you can select only those sections that you think are relevant to your needs. The right-hand side of the webpage features a contact box, links to further professional development in the form of a teaching and learning portfolio, and details explaining the icons that appear in each module content book. Figure 2 shows these icons, their descriptions in detail. The icons are used to quickly inform the participant of resources (glasses icon), an activity (question mark icon), reflection on application of concept to practice (lightbulb icon), links to UOW policy (link icon), and exemplars of best practice (star icon). Five topic bars (shown in Fig. 1) draw participants into the module starting with an explanation for “how do I progress.” Within this section, two suggestions for note-taking, reflections, responding to activities, and future planning are suggested. The first is through downloading a Word document template, while the other suggests the use of an e-Portfolio through a free website platform such as wix.com or weebly.com. This prepares participant to engage with materials and activities in a way that records their reflections as they go. This also acts as a source of evidence to

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Fig. 1 Designing learning online interface

Fig. 2 Module icons

Using this module Icon

What’s this? When you see this icon you will discover a resource to help further your knowledge and practice in the topic area. When you see this icon you will be prompted to think about the topic through the use of reflective questions. When you see this icon you will be asked to consider how the concepts being presented might be integrated into your teaching practice. When you see this icon you will be find links to relevant UOW policy and other related documents.

When you see this icon you will find an exemplar of good practice related to the topic area.

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refer to when reflecting on practice, designing learning experiences, or collecting material for a teaching portfolio or award application. The second section introduces the Moodle book which encapsulates the content and activities related to the topic. It begins by pointing to the relevant UOW polices, frameworks, and guidelines. The Moodle book comprises text, images, videos, interactive games and quizzes, tables, figures, and links to resources and templates. These are clearly presented using subchapters (in the Moodle book) allowing the participant to browse the areas that they are most curious about. Each book in the module finishes with an activity to encourage reflection on the application of the concept to practice. Participants are encouraged to devise a plan for future teaching sessions using what they learned and to share these ideas with others. The third section comprises a list of relevant references and resources, with hyperlink for quick access. The fourth section asks participants for their feedback on the module. Feedback questions include what was liked most, what could be improved, suggestions or additions for the module (resources, concepts, case studies, etc.), and suggestions for other teaching and learning topics. The final section of the module acknowledges the collaborative process of the module design by recognizing its contributors to content and production support from across the university.

5.2

Case Study 2: Sessional Teacher’s Professional Development Program

Aligned with the suite of online modules above and recognizing the need to provide targeted support for sessional teaching staff, a semester-long program that draws teachers together during their teaching period is run each university semester. This program design could be seen as a “push” approach, where topics are selected, activities are pre-designed, and participation can build into a community of likeminded practitioners. The program has transformed over time for continuous improvement and to maintain strong links with the introduction of new resources. It was established as a yearlong, online course for sessional teachers in 2010 and called Flexi-ULT (see Dean et al. 2015, 2017). It emerged originally though as a teleconference version of the University Learning and Teaching (ULT) several years prior for academic staff at five remote campuses situated across the Southeast region of New South Wales. The University Learning and Teaching (ULT) program had ten face-to-face modules on university teaching and learning topics and was tailored to continuing new staff. Flexi-ULT transformed the modular design of the ULT workshop series and translated this into an online space to specifically meet the needs of sessional teachers at the University of Wollongong. In 2017, a revised casual academic teacher’s program was launched, maintaining the most effective components of Flexi-ULT and bringing the program forward to align with the suite of new online, asynchronous modules (see Sect. 5.1). Continuing with similar modules and activities in Flexi-ULT, Springboard into Teaching is a semester-long program (rather than yearlong) and facilitates conversation, sharing of

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experiences, exposure to resources, and cross-disciplinary networks that were the strengths of the precedent program. Similar to the online modules outlined in the first case study, Springboard into Teaching uses a Moodle platform to model possibilities and effective practices in the Moodle space for teachers to take back to their own contexts. Participants register and gain access to the Moodle site on a given date. The program has five modules, each becoming available for a set period (of around 3 weeks) during which time the module is facilitated daily and requires approximately 4 h to complete. The five modules are aligned to the main modules designed for all staff (outlined in the first case study) but have been developed at entry level in order to bring on board those sessional staff who, though they may have a great deal of industry or research knowledge and experience, may lack understanding of learning and teaching in higher education. Each module focusses on a specific content area related to teaching and learning. As outlined in Table 2, the five modules include designing learning, providing effective feedback, supporting assessment, facilitating inclusive classrooms, and Table 2 Springboard into Teaching modules Designing learning

Providing effective feedback

Supporting assessment

Facilitating inclusive classrooms

Gaining recognition for your teaching practice

Designing and supporting learning experiences that engage students and optimize deep learning and critical thinking requires an understanding of the complex nature of the learner. This module will explore how a learning experience is designed. [This topic is based on the all-staff, online module, Designing Learning.] The provision of effective feedback has a direct impact on student learning. This module focusses on the reasons for and means to provide timely, effective feedback to your students, through both formative and summative assessment tasks. [This topic is based on the all-staff, online module, Effective Feedback.] Recent research around assessment has foregrounded the importance of well-timed and constructed assessment as crucial to student learning and academic outcomes. This module investigates the purposes of formative, summative, and sustainable assessment.[This topic is based on the all-staff, online module, Why Assess?] Students come from diverse backgrounds, each with their own unique set of prior learning and personal experiences. This module explores the issues that students may experience as they navigate learning in higher education. [This topic is based on the all-staff, online module, Helping Students Learn.] At UOW, recognition of your teaching practice is available through the Continuing Professional Development (Learning and Teaching) Portfolio. This final module of the program focusses on developing your CPD (L&T) Portfolio by developing an understanding of the requirements for submission of such a portfolio through reflecting upon your teaching practice, unpacking “teaching evidence” and offering CPD (L&T) Portfolio exemplars. [This topic is based on the all-staff, online module, CPD Portfolio Development.]

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gaining recognition for your teaching practice. The program begins with a welcome segment in which the facilitator is introduced. From here, instructions on what to expect and how to navigate the modules are provided, including an outline of the five topics and the dates they will be open. Participants then engage in an ice-breaker activity, which takes place in a discussion forum. Participants are provided with the following guidance: 1. Start a new post to introduce yourself (in less than 200 words) – please include: (a) The area you are teaching in. (b) Why you’ve chosen to enrol in Springboard into Teaching. (c) What you hope to achieve by participating in this program. (d) Then pose a question for other participants to respond to, e.g., you might want to know Is anyone else juggling their teaching with PhD or Masters studies?, or Does anyone else teach in a subject with a high proportion of international students?, or Has anyone managed to find the best coffee on campus?. Try to think of a question that you’d genuinely like answered. 2. After introducing yourself to the forum, please read the posts of other participants and briefly respond to a few posts. You may need to return to the discussion forum over a few days as more people come in and introduce themselves. This activity will allow you to begin to form networks with people who may be able to support you (and vice versa) as you progress through this program and your career. This welcome section is designed to make expectations clear and for participants to start to get to know each other, in order to establish a safe learning environment. The facilitator remains active in this space to provide support, responds to any challenging questions that are posed with ideas or resources, and prompts participants in the discussion. The final module is connected to a process of accreditation for teaching staff at UOW that sits outside the program. The Continuing Professional Development (CPD) process for learning and teaching is a means by which teaching staff can gain recognition of their teaching through assembling a teaching portfolio (for more details, see Thomas et al. 2016, or go to http://www.uow.edu.au/dvca/ltc/teachdev/ cpd/index.html). Every staff member engaged in teaching at UOW is able and strongly encouraged to submit a portfolio for review and recognition at regular intervals during their teaching career. By participating in this final module in Springboard into Teaching, participants develop an understanding of the requirements for submission of a portfolio, through reflecting upon their teaching practice and what constitutes teaching for the portfolio. A central activity in this module is guidance to write a teaching philosophy. Sessional staff engaged in the program are introduced to the fundamental components of the portfolio however are not required to submit a portfolio to complete the program. Instead, program completion is through active participation in all modules, and a certificate is awarded at the end. The Springboard program has been designed to look like the online modules offered by the University’s Academic Development and Recognition team, using the same design elements – the banner, icons and, contact information explained in the

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first case study (see Figs. 1 and 2). This similarity across sites allows staff who has accessed other modules to quickly recognize its familiar layout. The content for the five segments is also built in Moodle books. Here, however, the Springboard segments begin to differ from the first case study’s modules due to their facilitated nature. In addition to the banner and icons on the entry page for the Moodle site, there is an additional html section on the righthand side of the site. This section, titled “comments,” provides a quick question and answer space for participants to ask questions as they occur. This can be a place to bring the facilitator into an issue with the site, e.g., where a link is broken within the content provided. It is also a space for the facilitator to provide extra information, for example, to act as an advertising space when there is an upcoming workshop that may be of interest to the participants. While the module content again points to the relevant UOW policies and context, and each topic contains text and images, videos, and links to resources and templates similar to the modules in case study 1, these are interspersed with activities that have been designed for facilitated use. Each module highlights three activities built around the main topic. Each activity requires participants to consider the content in and for their own teaching context, asking them to share their understandings and practices that align with the topic. Through the activities, participants are encouraged to plan for future change in their teaching practice related to their learning in the segment. Activities are based on real teaching situations and interactions and are timed in the program to occur alongside the semester timetable. For example, the feedback segment is facilitated around the same time that the first major assessment tasks are due to be handed in by participant teachers’ students. Finally, participants are asked to share their reflections, teaching activities, and experiences with their online peers. This practice sharing and future planning uses a variety of means, including Moodle discussion forums and the use of free online tools such as www. padlet.com. Participants are not only asked to share their ideas and practices but also to comment on others’ contributions. The facilitator also contributes to discussions and highlights key points in participants’ offerings as needed. While input to these discussions is asynchronous, “discussion” has been found to occur as participants return to particular discussion threads to contribute further. Each segment book concludes with an invitation, for those who have further time, to self-enrol in the all-staff modules for further content input. These, however, do not have further support provided by the facilitator. Participants are able to ask for further support via email, and they can also request a personal consultation at any time either in person for those at Wollongong campus or via phone or Skype for those working at regional campuses.

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Future Directions

With the higher education sector undergoing vast and wide-reaching change, it is imperative that those involved with supporting teaching staff consider the design and delivery of professional development activities that is inclusive of all within the varied nature of the academic workforce. The multiple iterations of a sessional

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teacher’s program not only support the notion that a program is essential and desired by sessional staff but speak to the need to continuously reflect on and improve the design of the program to fit with the fluidity of the university learning environment. Improvements to the programs presented in both cases continue. For example, we are looking into the possibility of a completion activity at the end of each online module to record participation. This will provide evidence of engagement for both the teacher and for our record keeping and evaluation processes, in addition to other learning analytics. In the sessional teacher’s program, feedback from participants had suggested the need for personal interaction with the facilitator and each other. A casual face-to-face “coffee catch-up” has been introduced for those working from Wollongong campus. This feature was deemed a success with a small number of staff attending in order to ask questions and meet with others undertaking the program. Participants come together to discuss their teaching contexts, problems they have during the teaching period and successes they experience using elements from the program. They engage each other in conversations around teaching and learning at the university, expanding their networks and toolkit of practical teaching strategies. This chapter has showcased two examples of how sessional teacher’s professional development can be supported through utilizing mobile technology. The design features of both cases are different yet complementary, enabling flexible spaces for engagement and sustainable opportunities that allow teachers to participant and seek information in a way that they are not disadvantaged because of provisional employment. Our research continues on the impact of these initiatives on student learning and teacher’s practice.

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Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Student Feedback in Mobile Teaching and Learning ▶ Tutors in Pockets for Economics

References Boud, D., and A. Brew. 2013. Reconceptualising academic work as professional practice: Implications for academic development. International Journal for Academic Development 18 (3): 208–221. Brown, N.R., J.-A. Kelder, B. Freeman, and A.R. Carr. 2013. A message from the chalk face – What casual teaching staff tell us they want to know, access and experience. Journal of University Teaching and Learning Practice 10 (3): 1–16. Brown, C., V.V. Vodeb, R. Slee, and M. Winchester. 2016. Professional development program to embed inclusive and explicit teaching practices in higher education first year units. Sydney: Office for Learning and Teaching. Dannin, E. 2003. Organizing contingent academics: The legal and practical barriers. Working USA 6 (4): 5–11.

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Dean, B., M. Zanko, and J. Turbill. 2015. Mobilizing PD: Professional development for sessional teachers through mobile technologies. In Handbook of mobile teaching and learning, ed. Y. Zhang, 165–182. Heidelberg: Springer. Dean, B.A., K. Harden-Thew, and L. Thomas. 2017. Building an online community to support the professional development of casual teachers. International Journal for Academic Development 22 (1): 31–42. Delahunty, J. 2012. ‘Who am I?’ Exploring identity in online discussion forums. International Journal of Educational Research 53: 407–420. Delahunty, J., I. Verenikina, and P. Jones. 2014. Socio-emotional connections: Identity, belonging and learning in online interactions. A literature review. Technology, Pedagogy and Education 23 (2): 243–265. Gilbert, A. 2017. Using activity theory to inform sessional teacher development: What lessons can be learned from tutor training models? International Journal for Academic Development 22 (1): 56–69. Gunson, J., E. Abery, L. Krassnitzer, I. Pricharsd, Christopher Barton, and E. Willia. 2016. Teaching in focus: The value of implementing a program-specific teaching support project for staff wellbeing and student success. Student Success 7 (2): 51–57. Harvey, M. 2017. Quality learning and teaching with sessional staff: Systematising good practice for academic development. International Journal for Academic Development 22 (1): 1–6. Harvey, M., K. Luzia, C. McCormack, N. Brown, J. McKenzie, and N. Parker. 2014. The BLASST report: Benchmarking leadership and advancement of standards for sessional teaching. Final report. Sydney: Office of Learning and Teaching. Hunt, L., and D. Chalmers. 2012. University teaching in focus. Camberwell: ACER Press. Johannes, C., J. Fendler, and T. Seidel. 2013. Teachers’ perceptions of the learning environment and their knowledge base in a training program for novice university teachers. International Journal for Academic Development 18 (2): 152–165. May, R., G. Strachan, and D. Peetz. 2013. Workforce development and renewal in Australian universities and the management of casual academic staff. Journal of University Teaching & Learning Practice 10 (3): 1–24. Myconos, G. 2005. Precarious employment: reflections from the semi-periphery. Just Policy: A Journal of Australian Social Policy 37 (1): 58–62. Percy, A., M. Scoufs, S. Parry, A. Goody, M. Hicks, I. Macdonald, N. Szorenyi-Reischl, Y. Ryan, S. Wills, and L. Sheridan. 2008. The red report: Recognition, enhancement, development. Sydney, Australia: Australian Learning and Teaching Council. Savage, J., and V. Pollard. 2016. Taking the long road: A faculty model for incremental change towards standards-based support for sessional teachers in higher education. Journal of University Teaching & Learning Practice 13 (5): 1–20. Shackleton-Jones, N. 2012. The importance of affective context: Push to pull learning. Global Focus: Workplace Learning 6 (1): 17–20. Thomas, L., J. Herbert, and M. Teras. 2014. A sense of belonging to enhance participation, success and retention in online programs. The International Journal of the First Year in Higher Education 5 (2): 69–80. Thomas, L., K. Harden-Thew, J. Delahunty, and B.A. Dean. 2016. A vision of you-topia: Personalising professional development of teaching in a diverse academic workforce. Journal of University Teaching & Learning Practice 13 (4): 1–13. Verenikina, I., P.T. Jones, and J. Delahunty. 2017. The guide to fostering asynchronous online discussion in higher education. From www.fold.org.au/docs/TheGuide_Final.pdf Williams, B., and B. Beovich. 2017. Experiences of sessional educators within an Australian undergraduate paramedic program. Journal of University Teaching & Learning Practice 14 (1): 1–12.

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Business Models for Mobile Learning and Teaching Cassey Lee

Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mobile Teaching and Learning: Concept and Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Business Models for Mobile Teaching and Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Evolution of Technology and Market Structure: Implications for Business Models in Mobile Teaching and Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Competing Mobile Device Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Network Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Distribution Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Mobile Broadband Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

E-commerce business models are important to ensure the financial feasibility of mobile teaching and learning services. Key elements of business models value propositions, revenue model, market opportunity, competitive environment, competitive advantage, market strategy, organizational development, and management team. Other considerations include competition between mobile device platforms, network effects, and mobile broadband pricing.

C. Lee (*) Institute of Southeast Asian Studies, Singapore, Singapore e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_46

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Introduction

The advent of the Internet has had a tremendous impact on how we access information and participate in educational and commercial activities. Teaching and learning have been transformed in the process. Students and teachers (and researchers) regularly access the Internet to gather information that are required to complete tasks and assignments. In most colleges and universities, instructors utilize the Internet-based platforms to distribute teaching materials, receive assignments, and grade student activities. The “public good” mature of information also ushered in the provision of free access to university course materials such as those available at the Massachusetts Institute of Technology’s (MIT) OpenCourseWare website. More recently, massive open online courses (MOOCs) have emerged. Setups such as Coursera, Udacity, and edX offer free online courses to thousands and millions of students globally. Aside from these developments, the medium of teaching and learning has also evolved. These changes have taken place partly due to technological change and infrastructure upgrades. In particular, broadband mobile has become increasingly important. The electronic communication and productivity devices have also evolved. These have interacted in a mutually reinforcing manner to provide more opportunities for mobile teaching and learning. Mobile learning (m-learning) can be defined as “the provision of education and learning on PDAs/palmtops/handhelds, smartphones and mobile phones” (Traxler 2009, p. 3). Mobile learning involves “learners who carry the mobile devices and move around with them,” while the term “mobile teaching” facilitates and supports mobile learning (Kukulska-Hulme and Traxler 2005, p. 25). Today, notebooks, smartphones, and tablets provide an improved platform for more effective mobile teaching and learning. An important issue that needs to be addressed in mobile teaching and learning is the commercial or business aspect of offering and accessing mobile teaching and learning services. The viability and sustainability of mobile teaching and learning services depend on the extent to which sufficient revenues can be generated to meet the cost of running these services. E-commerce business models can provide some insights into factors that are important for financially sustainable mobile teaching and learning services. This essay aims to provide a brief survey of e-commerce business models and, from this, draw some insights for mobile teaching and learning. The outline of the essay is as follows: Sect. 2 will briefly discuss the concept of mobile learning and teaching as well as the technology involved. Section 3 will survey the types of business models and discuss how they are related to mobile learning services. This will include a discussion of key factors that are likely to be important for financially sustainable delivery of mobile learning services. Section 4 concludes.

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Mobile Teaching and Learning: Concept and Technology

What are mobile teaching and learning services? From the learner’s perspective, mobile learning takes place when learners access knowledge through mobile devices. This can take place either through learning from mobile educational material (didactic learning) or through interactions with other mobile learners and teachers (discursive learning) (Kukulska-Hulme and Traxler 2005, p. 26). Mobile learning can be a substitute for face-to-face learning by replacing the physical classroom experience with learning through mobile devices at a distant location or at a different time (recorded instructions and documents). It could also complement face-to-face learning via the use of mobile devices to deliver content within a classroom lecture environment and when they are used to operationalize student project collaborations. In terms of technology, the most commonly used mobile devices include personal digital assistants (PDAs), e-book readers, mobile phones, smartphones, tablets, and laptops. One way to differentiate these mobile devices is in terms of their mobility and computational power (Table 1). The mobility of a device relates to the easy with which the device can be physically carried around. This will depend on its weight and size. Mobile phones are considerably smaller in size than tablets, but their smaller screen size also limits their usability for mobile learning to some extent. Note that a mobile learning device is sometimes defined in a way to include only handheld devices. This definition would exclude laptop, notebook, and netbook computers (Adkins 2011). Another dimension of mobility is access to the Internet – whether a device has Wi-Fi capabilities and/or broadband telephony capabilities (3G, 4G, plus). This dimension constraints learners’ access to the Internet which is a key component of mobile learning. Another dimension of mobile devices is computational power – defined by the computational capabilities of the processors in mobile devices. This is an important aspect of mobile devices as it determines the range, the size, and the speed at which tasks can be carried out by the devices. At the low end of the spectrum would be e-books which have possibly the lowest computational power among mobile learning devices with only basic functions – text display and Wi-Fi for downloading Table 1 Characteristics of mobile devices Low mobility

Medium mobility

Laptop

Tablet Netbook Notebook

Low computational power

Medium computational power High computational power Source: Author

High mobility Mobile phone E-book readers PDAs Smartphone

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e-books and documents. At the higher end would be applications that may require a minimum computational power such as those involving mathematical and statistical computation. To some extent, the computation-intensive routines can be carried out at a remote server linked to an application. Example includes the Wolfram Programming Cloud and the Wolfram Alpha. The quality of mobile processors can also impact power consumption. Thus, mobile processors and the capacities of batteries jointly determine the capability of a mobile device. This, in turn, is likely to affect the software and functionalities of mobile devices. The differences between the various types of mobile devices have been blurring over time. For example, there are hybrid products today combining tablet and notebook functions. This has been drive by technological improvements in both mobile processors and battery technology. These and other technological changes such as broadband mobile communications have the landscape for mobile learning services. The advent of 4G, for example, has meant that 4G-enabled mobile learning devices can access information at higher speeds albeit at a higher cost as well. Whether commercially feasible and sustainable mobile learning services are possible is explored next via a discussion of business models.

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Business Models for Mobile Teaching and Learning

What are business models and why are they important? Laudon and Traver (2010, pp. 2–4) define a business model as “a set of planned activities designed to result in a profit in a marketplace.” In the context of e-commerce, the business model would “use and leverage the unique qualities of the Internet and the World Wide Web” to achieve profitability (ibid, pp. 2–4). Thus, business models help ensure financial sustainability of e-commerce products and services. This is achieved by identifying key elements that are important for the success of a business. These factors include value propositions, revenue model, market opportunity, competitive environment, competitive advantage, market strategy, organizational development, and management team. How this can be applied to mobile teaching and learning services is summarized in Table 2. An exploration of the key elements of the business model relevant to mobile teaching and learning services clearly requires an understanding of the nature of such services as well as the technologies involved. We explore each of the elements and what they imply for mobile teaching and learning services. In terms of value proposition, mobility and convenience are clearly key selling points for mobile teaching and learning services. Mobile learning services can be delivered to learners (of which student is a subset) at their convenience. This is particularly convenient for learners who are unable to attend face-to-face lecture and tutorial sessions. For those able to attend face-to-face learning sessions, mobile learning services could provide complementary and supplementary learning services outside the classroom environment. The availability of high-speed mobile broadband services is likely to enhance the value of such services.

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Table 2 Key elements of e-commerce business model for mobile teaching and learning Elements Value proposition Revenue model Market opportunity Competitive environment Competitive advantage Market strategy Organizational development Management team

Key questions Why would students use and/or pay for mobile learning services? How can the seller generate sufficient revenues to ensure an acceptable rate of return on investment in mobile learning services? What is the market place for mobile learning services? Are there direct and indirect competing products in the market place? Are there any advantages that can be levied to make the mobile learning services competitive in the market? What plans can be made to promote the mobile learning services in the market? What type of organizational structures is useful to implement the business plan? Can a good set of executives with relevant experiences and qualities be identified and hired?

Source: Compiled by author-based framework provided in Laudon and Traver (2010)

A number of revenue models may be useful for developers and providers of mobile teaching and learning services. Potential revenue models include: • Advertising revenues – in which mobile learning services are distributed free of charge to learners in exchange for strategically placed advertisements in mobile teaching and learning spaces/sites and materials • Subscription – in which a fee is charged to learners who would like to access the contents of a given mobile teaching and learning service for a given period of time • Sales – in which a one-time fee is charged to learners interested in purchasing the mobile learning services. Such services could be unbundled which allows learners to purchase the set of learning services that are of particular interest to them Two or more of the above revenues could be used, resulting in the application of hybrid revenue models that help maximize revenues for the mobile learning service providers. An important consideration in selecting the optimal revenue model(s) is its/their impact on revenues over the product cycle. There are also risks associated with destruction of product cycles before service providers can maximize revenues from their mobile learning products. This is due to obsolescence arising from new and superior products introduced by competitors in the market. There are already significant market opportunities for mobile learning services. Most educational organizations and institutions have already incorporated some degree of e-learning services that are accessible through mobile devices. These range from basic approaches such as course websites and online course materials to more sophisticated distant learning programs. Publishers are already offering e-books that can be read with mobile devices. These services are being offered by

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companies such as Amazon.com either on a purchase or rental basis. There are clearly more market opportunities for mobile learning services with interactive activities. The competitive environment of mobile teaching and learning services is such that whichever type of services are offered there are bound to be competing services. If one were to design and promote a tablet application for the teaching and learning of a particular subject, its competitors would include other mobile learning services ranging from traditional e-books to more comprehensive learning portals offered by universities and textbook publishers. The set of competitors are also likely to change with technological changes in hardware and software for mobile teaching and learning. These changes are likely to be even more rapid than the traditional brick and mortar teaching and learning environment. Thus, the product life cycle of mobile teaching and learning services can be very short. Against this backdrop and in order to compete against these services, the competitive advantages of using mobile teaching and learning services need to be clearly identified. These include advantages arising from access to unique resources (knowledge, talent) that are not replicable by other firms. Such advantages translate into first-mover advantages by being the first to introduce the product in the market. However, digital products run the risk of being easily replicable by second movers in the market. One way to minimize such risks is by incorporating elements that cannot be easily replicable such as interactive communities above the critical mass, regular (content and system) updates, and large network effects. Converting competitive advantages into actions that maximize profits requires a market strategy. This will entail planning for market entry, service adoption, and market share expansion. For mobile teaching and learning services, there are many possible points of entry depending on which market is being pursued as well as the available technology for such services. For the student-consumer market, application (app) stores are likely to be an important approach to entering the market. The vertical integration between hardware market (e.g., iPhone) and software distribution market (e.g., iTunes) may narrow down available channels for the distribution of mobile learning devices. The successful implementation of the market strategy is, in turn, likely to depend on the quality of human resources (management team) and organization (organizational development). The various elements are in fact interdependent as the decisions on human resource and organizational development depend on the business strategies adopted (Baron and Hannan 2002).

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The Evolution of Technology and Market Structure: Implications for Business Models in Mobile Teaching and Learning

The markets for devices that are suitable for mobile teaching and learning have obviously undergone rapid and tremendous changes since they first appeared in the 1990s. Primarily driven by technological change, these changes are often

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reminiscent of Schumpeterian “creative-destructive” processes in which new products emerge to make obsolete and replace existing products in the market (McKnight et al. 2002). Such processes are particularly intense in markets driven by information technology. In assessing the business model of teaching and learning services, it is crucial to examine some of the market and industry factors that, though sometimes exogenous, have significant impact on the sustainability of these services. These factors include the competition between mobile device platforms, network effects, and mobile broadband pricing.

4.1

Competing Mobile Device Platforms

One issue that makes such the competition and market processes even more complex in the case of mobile teaching and learning devices is the coexistence of many competing operating system (OS) platforms for mobile device applications. At present, major mobile device platforms include iOS (Apple), Android, and Windows. The market share of the various mobile device platforms is important as it affects the market size or the number of potential users of mobile teaching and learning services. This is especially relevant if mobile teaching and learning service providers have to choose to deliver its services through a limited number of platforms. To put this in perspective, it is perhaps useful to examine the current market share for OS platforms for mobile devices such as smartphones, which is summarized in Table 3. Android-based smartphones have become increasingly dominant in the market since 2011. Today, the market share of Android-based smartphones has exceeded 80%. How do market shares affect mobile teaching and learning service providers? When such service providers can only offer their services using a given platform and to ensure maximum uptake of such services, developers of mobile teaching and learning applications will need to choose one or more of the dominant OS platform(s). In the case of smartphones, given the current market shares, this would be either Android or iOS. However, the market shares of OS platforms may be different for other types of mobile devices such as tablets (Table 4). While Android’s market share is still higher than iOS’s market share in the tablet market, the iOS is more dominant in niche markets such as the education sector. It has been reported that the iOS’s current Table 3 Market shares of smartphone OS, 2011–2014 (percent) OS platforms Android iOS Windows phone Blackberry Others

2011 Q2 36.1 18.3 1.2 13.6 30.8

2012 Q2 69.3 16.6 3.1 4.9 6.1

2013 Q2 79.6 13.0 3.4 2.8 1.2

Source: IDC, http://www.idc.com/prodserv/smartphone-os-market-share.jsp

2014 Q2 84.7 11.7 2.5 0.5 0.6

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Table 4 Market shares of tablet OS, 2012–2013 (percent) OS platforms Android iOS Windows phone Others

2012 45.8 52.8 1.0 [space] < Course_Code> e.g., Exam s12345678 AF101 where the student with ID s12345678 has requested the exam timetable for course AF101. This request and the reply received from the database are captured in Fig. 6. SMS Quiz Application This application is a two-way communication system designed to provide quiz in a form of questions having explicit answers. The quiz application is used for the following: (a) Short assessments – can take place either inside or outside classrooms or even be facilitated inside and outside classrooms in parallel, depending on the need.

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Fig. 5 Snapshot of the SMS block that a facilitator uses to send out SMS to the students

Fig. 6 A mobile screenshot of the SMS exam timetable application

(b) Receive on-the-spot student feedback in a classroom – the quiz can be opened to a class by the instructor to get just-in-time feedback on a recently taught concept by posing a few questions in class and letting the students attempt the quiz (Fig. 7).

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Fig. 7 A screenshot of the two-way SMS quiz application

Table 2 Mean ( x) and standard deviation (s) of student rating (1–5) for each service Services SMS notification SMS exam timetable SMS quiz

x 3.85 3.92 3.65

s 1.088 1.103 1.090

An online survey was conducted to rate each of these mLearning services in semester 2, 2015 with a total of 852 respondents on the 5-point Likert scale (very poor, poor, average, good, and excellent). The ratings of the mLearning services from 852 respondents were close to good (4). Table 2 shows the mean and standard deviation of students’ rating for each of the services.

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Web-Based Applications

USP decided to shift focus from SMS-based services to web-based services and mobile apps as a result of gradual increase of the use of smartphone as shown in Fig. 2. This focus was also backed by students’ feedback from a survey conducted in 2016 to take the pulse of students about what was most needed in mLearning at USP. From a total response of 2072 students, 90% wanted to have mobile-based app for the SMS-based services such as notifications, quizzes, and exam timetable. Keeping this in mind, USP has engaged in the development of responsive web applications and mobile apps for mobile devices. The responsive web design is important in eLearning since it optimizes the content for any mobile device. The following section discusses different web apps developed in USP:

3.3.1 Edutainments: Go Nuts Edutainment is a concept whereby educational activities have some form of entertainment, with the focus to make learning exciting and interactive thus keeping the learners engaged (Aksakal 2015). It can come in the form of television shows, theatrical plays, mathematics games, and game-based learning applications on computers and mobiles (Corona et al. 2013). A USP wide survey conducted in 2012 had showed that 89.6% (from 852 respondents) of students liked to use such game-based learning applications. Consequentially, a new edutainment module, named Go Nuts, was developed in-house. The Go Nuts edutainment module is a web-based game application (Fig. 8), built on the concept of the Hangman game, having a Pacific context and providing users with a number of questions to gauge the knowledge in a particular subject area, with three games developed: English Grammar, C++ Programming, and Get to Know Moodle. These games target a large number of students and help freshmen make a smoother transition into higher education. The Go Nuts has had 5176 hits since its launch in 2013. As shown in Fig. 9, the English Grammar and Get to Know Moodle were accessed by a large number of students. Go Nuts is accessible on: http://mlearn.usp.ac.fj/game/. 3.3.2 Course Finder A course finder app was created in-house in 2014 to assist existing and potential students search for information about courses offered by USP. The search feature allows filtering by course code, subject code, course title, or keywords of a course. Students can also browse courses based on the faculty and discipline. A screenshot of the app is provided in Fig. 10. This application is developed for Android users and web-based responsive application. For other operating systems, it can be assessed from anywhere via Internet connection. The URL of the web-based app is http://mlearn.usp.ac.fj/ coursefinder. 3.3.3 Exam Timetable Application Students sometimes turn to forget their exam timetable, venue, or seat number which easily panics them close to the exams. USP’s mLearning team shifted from SMS

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Fig. 8 Go Nuts game for English Grammar

Fig. 9 Hits for Go Nuts

2500

2061

2037

2000 1500

1078

1000 500

0

exam timetable application to responsive web application (exam timetable) where student search their exam detail using search filter “student ID.” The screenshot of the app with the result is shown in Fig. 11.

124 Fig. 10 Screenshot of the Course Finder App

Fig. 11 Screenshot of the web-based exam timetable App

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Tablet Learning Project

Teachers and facilitators have found the tablet devices as an effective platform for teaching and learning. Tablets have been used by them to connect their students to relevant online discussions. Since the course notes are already organized and available online, it presents the facilitators an opportunity to invest time in creating new, stimulating, and engaging learning activities for students (Pegrum et al. 2013). Enhancing learning inside and outside of classroom, tablets have given rise to the concept of “family learning” where students learn with their adult family members (see ▶ Chap. 9, “Parental Education: A Missing Part in Education”), and the learning outcomes are intended for both, contributing to a culture of learning in the family (Niace 2013; Sung and Blatchford 2014). With the apparent benefits, successful adaptation of tablet PC’s for learning and teaching is already proving to be phenomenal, with the future yet to unfold (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). In the Pacific, the higher education learning revolutionized when USP leveraged on ICT to introduce new teaching and learning pedagogies for its students based in the regional campuses. With improved technological developments, the university moved from print to online facilitation to provide flexible, more interactive, and quality learning to the distance students. Some of these ICT tools are provided in Sect. 2.3.” The ICT-enabled support services include video and audio conferencing, broadcasting and lecture capture, and communications through satellite, Moodle chat, YourTutor service, and eMentoring using Big Blue Button. Due to the fact that mobile devices such as tablets and smartphones were gaining popularity among students, USP integrated tablets for content delivery and effective facilitation of selected courses and programs in 2013 (Sharma et al. 2015; Reddy and Sharma 2015). Through such adaptive interventions, USP has been able to provide: (i) (ii) (iii) (iv) (v)

Accessibility to quality education to regional students Means to overcome digital divide Accessibility to learning support across the region Equitable and enriched learning environment Self-directed and self-paced learning

3.4.1 Current Deployment USP resumed the Tablet Learning Project (TLP) for its distance students in the region in 2017. After the success of the pilot TLP in 2013, the university approved free distribution of almost 700 tablets to selected students in selected USP regional campuses as shown in Table 3. STAP (Science Teachers Accelerated Program) is a new cohort-taught pedagogical model designed in USP to address the issue of qualified science teachers in the Pacific. The model provides a platform to upgrade the qualifications of underqualified teachers teaching science in secondary schools by providing an

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Table 3 Tablet distribution for TLP-2017 USP campus Samoa Tonga Kiribati Solomon Islands Vanuatu

# Tablets 80 160 70 200 100 90

Selection STAP cohort Face-to-face Science Program including STAP cohort All new first year students All new first year students STAP cohort Tablet training and spares

Fig. 12 A STAP II student receives USP tablet from Samoan Minister of Education, Sports and Culture Honorable Loau Solamalemalo Keneti Sio

intensive 2-year in-service program through mixed delivery modes and leveraging heavily on ICT tools and technologies, including tablets. The reader is referred to Sharma et al. (2018) for a detailed account of STAP. Moreover, instead of just being an electronic repository for course materials in TLP-2013, the TLP-2017 allows students to connect to the USP intranet and Internet through campus Wi-Fi and mobile data using SIM cards to access course materials, join and participate through discussion forums and chats, share information and create knowledge, and collaborate with peers and facilitators. The students are expected to utilize the tablets to garner the best learning experience. The distribution of tablets for TLP- 2017 in the Pacific region is shown in Figs. 12 and 13. It is also noted that in another new initiative, USP has issued tablets to all new first year degree students as part of the university’s new mobile platform for learning. This initiative has come keeping in mind the recent and future impacts of digital transformation of societies on universities. USP has re-calibrated its information and communication infrastructure and services for a better learning and teaching

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Fig. 13 Tongan students learn the features of new tablet during the tablet training workshop

experience, two priority areas captured in its 2013–2018 Strategic Plan (The University of the South Pacific 2013).

3.4.2 Student Feedback Feedbacks from students who are part of TLP-2017 were collected using questionnaires. A paper-based questionnaire was given to students prior to the tablet training workshop, and another online survey was conducted after its completion. Figure 14 shows the results from the Samoan and Tongan students who attended the preparatory workshops. From the sample, 96% (86 out of 89) of the students looked forward to engage in tablet learning (67% strongly agree and 29% agree). The highly positive response from the regional students could be that the preparatory workshops enhanced their digital skills and digital literacy which would come very useful for the distance and flexible learning. In addition, 94% (83 out of 89) of students had positive response toward the integration of tablet learning in their courses (51% strongly agree and 43% agree). Students appreciated USP for presenting them with easy-to-use tablets which assisted them in their studies. Compared to desktop computers, these tablets were light and portable making it ideal for use at anytime from anywhere. Students were also glad that they could take the tablets to their homes to use. Table 4 shows the calculated mean for the three questions taken from the survey. A higher mean for each question indicates a strong acceptance of tablet learning by the students in Samoa and Tonga. A similar response is expected from students of other selected campuses where tablets were distributed. Students were impressed with the features of the tablet especially the screen size. The tablet has 10.1 in. screen which allowed for better reading space for students. The other features include the leather case which helped protect the tablet from bumps, knocks, scratches, or any accidental damage and the dedicated keyboard which helped maximize the potential of the tablets by greatly assisting the students in faster typing of text compared to on-screen keyboard. Students also had more storage

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Fig. 14 Samoa and Tonga campus students’ response to the tablet learning

space with 32GB of internal storage and an additional 15GB of online storage through Google drive. The tablets also had a number of educational apps installed such as the customized Moodle Mobile, which is the official mobile app for Moodle (Moodle 2017). Tablet recipients were able to browse the content of their courses; attempt quizzes and post in forums even when offline; receive instant notifications of messages and other events; quickly find and contact their facilitators and friends doing the same course; upload images, audio, videos, and other files from their tablet; and view their course grades.

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Table 4 Samoa and Tonga campus students’ response to tablet learning

No. 1

2

3

Question Engage in tablet learning Integrate tablet learning in course Workshop has upskilled my knowledge on tablet learning

Strongly disagree (%) 0

Disagree (%) 1

Neutral (%) 2

Agree (%) 29

Strongly agree (%) 67

Mean 4.63

SD 1.45

0

3

3

43

51

4.40

1.17

0

2

6

42

51

4.40

1.15

Overall, these tablets helped reduce printing costs, provided flexible access to course materials, tracked student progress in their respective enrolled courses, and enhanced collaboration, engagement, and communication (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). Student Testimonials: The Tablet learning project 2017 has been really helpful for me this semester. It is easy and portable making it ideal to use at all times. I am so thankful for being part of this project and I would recommend it to anyone else. It is very useful in a sense that I don’t have to carry my books in school. I just carry the tablet with me to school, and as I get free time I use it to read the lesson notes. As a STAP student, I am working (teaching) and studying at the same, I am glad that I can take the tablet home and use the tablet offline to read the course notes, attempt quizzes and submit my assessments.

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Challenges in Adopting mLearning

The success and sustainability of mLearning tools in the Pacific region face strong technical, educational, social, and economic challenges. The Pacific region inherits an array of challenges and opportunities due to the geographic isolation, nonuniform secondary school education, English being the second or even third language, student diversity, digital divide and literacies, shoestring budgets, varying teaching resources, and lack of infrastructure to outline the major ones. Nonetheless, USP continually seeks efficient and cost-effective pedagogical tools and ICT technologies not only to drive innovations in the Pacific but to meet the expectations of its member countries.

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The challenges pertaining to mLearning among others include short battery life, smaller screen size, risk of obsolescence, limited memory, and maintenance of the mobile devices (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). In addition, there are device limitations since some types of mobile devices do not support viewing of different document formats. Reworking on the current eLearning materials to make it responsive on mobile devices is a huge challenge itself (Mehdipour and Zerehkafi 2013). Poor network reception, and the high costs associated with mobile data, is also a challenge especially in the Pacific region. Although the number of mobile subscribers is steeply increasing, not all people have mobile phones, and fewer have access to smartphones and broadband connections that make mLearning successful. Across Pacific and within the regional countries, inequity exists in terms of types of handsets, purchasing power of users, literacy levels of users, and mobile infrastructure. They further deepen the digital divide and digital inequality, which invariably affects the uptake and usefulness of mLearning in the Pacific. One of the challenges for the advancement of mLearning in USP is the availability of relevant, contextualized, and high-quality OERs. Unlocking and rendering OERs ubiquitous and responsive to new mobile devices will curtail costs, promote distance and flexible learning modes, and enable a greater accessibility to premium high-quality education especially in the developing countries. The other big challenge is the Pacific students’ readiness to mobile technology for learning. The universities and higher education institutes in the Pacific have begun to pilot and integrate mobile devices in the teaching and learning processes, but this opens up a number of concerns and questions about students. Are these students digital literate and have ICT competencies to use mobile technologies in higher education? What is their perception of mobile learning, and do they harbor positive attitude toward mobile learning? These are the questions which need to be addressed much before adaptive interventions related to ICT and mobile devices are implemented.

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Future Directions

To make education more accessible and flexible, USP is heavily leveraging on ICT. In USP’s ICT in education agenda, mLearning is seen to be an indispensable weapon in the ICT armory to help provide premium quality higher education to its students spread in 14 campuses and 11 centers around the Pacific. The mLearning initiative at USP is being achieved using a number of approaches and technologies, and while some technologies such as the SMS may be lesser used, the rise of smartphones and open-source software has brought greater opportunity for app development in higher education. The student surveys carried out in 2011–2017 have progressively indicated a significant increase in the percentage of smartphones; hence, work on web-based applications and Android versions have taken more liking and support in the university. The distribution of 3000 free tablets in 2017 to first year degree students and students in cohort-taught programs has further shown the university’s commitment to mLearning.

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Even though mobile learning has gradually permeated and proliferated in higher education, the transformations based on this new revolution of technology have been slow. There are many reasons, including the lack of resources; ICT infrastructure and competencies; attitude and perceptions of learners, facilitators, and institutions; digital literacies; and device diversity (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). The literature also points in the direction of the newer learning and teaching processes and pedagogies in higher education. Educators need to reconceptualize education, appropriately nourish with ICT tools and technologies, and make the shift from education at certain ages to lifelong learning (Brown 2005) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Stakeholders will have to work together to develop new educational models to cater for the new generations of learners who will be using mobile technologies that do not exist as yet. There is a dire need for the technological giants to work together with the educationists and look into how wearable and embedded technologies can be used to make learning more interactive, engaging, and productive (see ▶ Chap. 74, “Wearable Technologies as a Research Tool for Studying Learning”). Notwithstanding the above, there are pockets of excellence seen sprouting, for example, the embedded technology found some success in the medical field. Graduate medical education uses Google Glass to transfer live videos from classes to wearable devices, and it has enhanced the medical education and patient safety (Vallurupalli et al. 2013). VR and AR technologies have been proved to engage students in their learning too (see ▶ Chaps. 79, “VR and AR for Future Education” and ▶ 77, “Augmented Reality in Education”). The use of mLearning allows for greater collaboration; time is not wasted – students learn from any location; can cater well for all student learning styles (of course the course developers have to ensure that this happens – podcasts to listen to; videos for watching; researching and online activities); promotes lifelong and life-wide learning, and enables students to learn anytime – flexibility. Despite these apparent benefits, students who are too dependent on mobile devices for learning are most at risk for losing the face-to-face interactions and engagements with teachers and facilitators, or even their peers in the classes. While there are many points, such as digital literacy and ICT competencies, micro-learning, to consider before integrating mLearning in the various facets of learning and teaching, the universities need to embrace adaptive and personalized learning which can be complemented with LMS analytics when mLearning is already massified.

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Cross-References

▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ Parental Education: A Missing Part in Education ▶ Student Feedback in Mobile Teaching and Learning ▶ VR and AR for Future Education ▶ Wearable Technologies as a Research Tool for Studying Learning

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Parental Education: A Missing Part in Education Yu (Aimee) Zhang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The Importance of Parenting Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 The First Parenting Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 The Lack of Formal Parenting Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 The Reasons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Current Programs and Possible Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 The Study of Immigrated Family on Social Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Parenting Information and Resources for Immigrated Families . . . . . . . . . . . . . . . . . . . . . 3.2 Supporting Parents’ Groups on WeChat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Mobile Technology in Parenting Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Content Development and System Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Effective Learning with Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Combination with Off-Line Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A Survey on Chinese Background Families in Wollongong . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

136 137 140 140 141 142 143 143 149 149 150 151 151 152 152 153 158

Abstract

There is a positive relationship between the parents involvement and the students’ academic performance and achievement (García et al., The life-cycle benefits of an influential early childhood program. The National Bureau of Economic Research, Cambridge, MA, 2016; Gordon, Parent effectiveness training. Three Rivers Press, New York, 2000). Schools and teachers appreciate the contributions from parents’ comments, volunteering, and classroom support. Parents believe that the concepts they taught their child have a direct influence on the child’s Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_101

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personality, outlook on life, values, social skills, and attitude toward learning. Whatever the parents’ educational experiences, language they speak, or knowledge or skills, all parents begin this journey with their first baby. Parents spend about 75,000 h on average with their child. New parents usually get advice from parents, friends, community health professionals, and online resources. This chapter focuses on ways to help parents cope and learn better parenting skills. Mobile technology, with its unique advantages, has the potential to help parents with the complexity of parenting. Mobile technologies’ ability to personalize learning in real time can be a helpful parenting tool.

1

Introduction

A child’s first educational experience originates from the parents creating a home environment for their children to grow as a functioning person. “Men are what their mothers made them” Ralph Waldo Emerson (1860). Human beings transfer knowledge, experiences, and skills to the new generation through many methods such as expression, language, actions, and literacy. Research shows parent transfer of knowledge has positive relationship on a child’s development, behavior, and academic success (Russell and Lincoln 2017; Rowe et al. 2016; Lorber and Egeland 2009; Kim et al. 2014). Rowe et al. (2016) and Lorber and Egeland (2009) found that cold, harsh, or insentitive parenting can increase the children’s interpersonal violence and misbehavior later. The influences may last for a long period of time. Research demonstrates family factors have direct influence on the child’s educational performance than the quality of the school (de Zeeuw et al. 2016). Many new parents have little or no experience raising children. Some parents may study and learn from family members, medical professionals, books, or online resources (Gordon 2000). Parenting requires teaching childcare skills, such as safety knowledge, daily living, confidence building, communication, socialization, knowledge building, and nutrition. The content students learned from school are consistently and constantly changing with the development of new technologies and the changing requirements of the labor market (Rowe et al. 2016). Most parents rely on educators to teach their children, but a paradox exists when parents educate their children by responding to the needs of the child rather than educating based on research. Currently in Australia, many schools and local governments realized this parenting paradox and began offering involving the parents and community when designing new curriculum (Nicoletti and Rabe 2013; de Zeeuw et al. 2016). Parents play an important role in each stage of a child’s life (Gordon 2000). Parents provide nutrition for the child, a critical factor for successful learning when the child is young (Dunbar 2017). The lack of certain essential vitamins and minerals has a direct impact on a child’s ability to learn (Dunbar 2017). Parents provide socialization experiences for the child, often guiding them to certain children and selecting after-school class programs (Rowe et al. 2016). Research have shown 86%

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of Australian children enjoy the act of being read aloud at home (KFRR 2016). Communication between parents and teachers influenced the student’s academic performance (Hurst 2017). Upon graduation, students still rely on parents’ advice on finding a job, getting marriage, investing, and giving advice on childcare for the next generation (Rowe et al. 2016; Dunbar 2017). Parents have significant influence on a child’s personality, outlook on life, values, social skills, reading habits, and attitudes toward learning. Immigrant families often face more difficulties finding parenting support when their children study in a different cultural and language environment (Dunbar 2017; Russell and Lincoln 2017; Hurst 2017; KFRR 2016). To understand parents’ views on childhood education, a survey was designed and given to a group of parents (emigrating from China or using Chinese as mother language) in Australia. The results help to understand how parents support children living in a mix-culture community. Beside the traditional community and family support structures, mobile technology potentially can become an important tool in parenting education. The parents interviewed for the study said they relied on mobile technology for parental guidance and information (through WeChat, a Chinese social media mobile application). Generally, this occurred because of its convenience and efficient methods to get parenting information (Russell and Lincoln 2017; Mourshed et al. 2012) (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 33, “Mobile Education via Social Media: Case Study on WeChat”). Parents are eager to learn through mobile social media (Metzgar 2017; Zhang 2015b).

2

The Importance of Parenting Education

Many researchers and educators agreed parents play a far more important role in children education than just keeping the child safe and taking care of him/her (KFRR 2016; Russell and Lincoln 2017; Rowe et al. 2016; Gordon 2000). There are only formal educational programs in maternity departments in hospitals teaching new mothers how to breastfeed their baby or bath their baby and kids examination programs (voluntary) in community centers or clinic to help the new parents (Dunbar 2017; Gordon 2000). Research suggests minority families or less educated parents are less likely to seek parenting advice from medical professionals or their families (Rowe et al. 2016). New parents are usually too busy or frustrated to seek advice or search for information from professional sources (Gordon 2000). When problems occur (such as child’s illness), it is difficult for parents to keep calm and invulnerable (Gordon 2000). Actually, as depicted in Table 1 below, parenting time is much less than we though. A survey was conducted in this study to identify the hours a typical Australian parent spends with their child during their childhood. More parents work full time in Australia now than ten years ago. The parenting hours are reduced dramatically. The expected hours a parent spends with his/her child (including weekdays and weekends) were collected from the parents. The ranges of the children’s age were 0–1, 1–4 (childcare or preschool), 5–17 (primary or high school), 18–25 (adult), 26–40,

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Table 1 Estimated time a child spend with his/her parents (exclude sleeping hours and school hours) Age 0–1 1–4 5–17 18–25 26–40 40+

Hours per day 24 16 (24 in holiday) 16 (24 in holiday) 0 (24 in holiday) 0 0

Sleeping time 14 (average) 12 8 8 8 8

Hours per year 3,650 2,980 4,240 100–500 0–20 0–20

Total hours 3,650 11,920 55,120 800–4000 0–300 0–400

Source: From this study

and above 40 years old. The total amount of time the parents spend with their child in a typical Australian family can be calculated in the different aged groups. A qualitative interview with some of the surveyed parents was followed by the survey to identify the typical parental time and quality of parental time with kids for different aged kids group in Australia. As a result, 34 parents participated the mobile (online) survey (through WeChat social media public account), and 10 parents participated in the interviews for different kids aged groups. The study is limited by the number of interviewees and cases as well as location (only parents from Wollongong Chinese background parents were selected to attend the study). As shown in Table 1, the total amount of hours a child spend with his/her parents is around 75,000 h, which includes some after-school cares, long-day cares, casual classes, homework time, grandparents time, and playtime with friends. The real time a parent (two parents could take care of a child in turn) spends with their children could be much less than the estimated time. As the interviewed parents are parents who use Chinese at home, this study focused on small groups of families emigrated from China. The location of interview is ranged in Wollongong and Illawarra region in Australia. The number of interviews is limited. But the study proves that mobile technology could be used to conduct parent survey with the high penetration rate of mobile phones worldwide. The result shows that parental time with kids during different aged group is precious to both parents and children. A well-planned home education/play schedule could increase the quality of parental time dramatically, which should be taking into account in the children educational programs. The result also sheds a light on future design of parental education and community engagement programs for government and local schools. As shown in Fig. 1, a baby spends most of the time with his/her mother in the first year (up to 5% of the total time with his/her parents). Between 1 and 5 years old, with the join of childcare or preschool (in Australia), the time a child spend with his/her parents reduced dramatically. But this period still account for 16% of the child’s total time he/she spend with his/her parents. It is the most important period for the child’s personality, outlook on life, value, social skills, reading habits, and his/her attitude toward learning developments (Gordon 2000; Russell and Lincoln 2017). Parents play a vital role in these developments. After 5 years old, a student is usually enrolled in a formal primary (and later high) school in Australia. This is the longest accompany time the parents spend with their children during their lifetime (which accounts

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The parenting hours by age range

76%

0% 3%

1-5 6-17

0%

18-25

5% 0% 16%

0-1

25-40 40+

Fig. 1 The estimated parenting hours by age range with children (From this study)

for 76% of total parenting time as shown in Fig. 1). But due to the after-school care, casual classes, homework time, holiday plans, grandparents time, friends time, and so on, the total amount of hours the parents can spend with their children during this period could be much less than the estimated time. Majority of parents stopped reading to their children after they reached 9 years old as the children can read themselves (KFRR 2016). But research showed children like to be read aloud in both young and elder age because they like the special time with their parents (KFRR 2016). Parents played a vital role in developing the child’s reading habits (KFRR 2016). Figure 1 shows nearly 97% of the total parenting time is in the first 18 years. As indicated by some interviewed parents in this study, many family hours had been wasted when things are not going as they were planned (such as the child’s illness). The parents also agreed that mobile devices (such as iPad) plays more and more important role in kids home education and entertainment. Some parents showed their concern on the lack of outdoor time and potential health issues generated with the great amount of screen time the kids played at home. Schools in Australia are implemented BYOD (bring your own devices) programs too, which increased the total screen time for kids (KFRR 2016). Parents only spend around 75,000 h with their children in a typical Australian family as shown in Fig. 1. But these thousands of hours (especially the first 5 years in the child’s life) play an important role in a child’s education and his/her whole life (Gordon 2000). Most new parents struggle with many things with their first baby and ignored the efficiency of time spending with their child (Russell and Lincoln 2017). And some interviewed parents think there is no need to educate the kids after they reached the school age or went to job market, which is wrong. When the child became an adult and had his/her first baby, he/she is totally new for this new role without any experience or empirical skills. They relied on their parents’ advice and experience to learn the useful knowledge (Rowe et al. 2016). They needed encouragement just like when they were young. As discussed above, one reason for the lack of formal education for parents is the diversified needs from different families, cultures, regions, and religions (Rowe et al.

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2016). Mobile technology provides the personalized learning for different learners with its real-time communication function and powerful searching ability and location services (Zhang 2015a). The new data analysis and augment intelligence could provide value-added services to meet the special requirements from different families programs (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Combined with social media and online community services, mobile learning could provide more supports for families and parents (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). The interviews in this study also proved that parents are well connected by mobile devices and mobile social media. It could build the child’s or family profile to connect it with the family members from overseas or other places and pass on all the key and valuable knowledge for the whole family. The knowledge could benefit the future generations and community too.

2.1

The First Parenting Education

Dr. Thomas Gordon noticed the problem and started the first parenting workshop in 1962 (Gordon 2000), which benefited many parents in many years. However, the program was not very successful in China due to cultural differences. Study showed that families from different cultural background and ethnic groups may vary in family education and source of parenting information (Rowe et al. 2016). Immigrated families are facing more difficulties with less direct family supports and community supports when the parents were struggling with their income to support the family or language learning. The lack of confidence in a new environment may have negative influence on a child’s development and academic success too (Russell and Lincoln 2017).Most parents don’t know what to learn or where to learn in each stage of the child’s development. They only seek advice or search for information when they met a problem (such as the child’s sickness). With the fast development of technology and online communities, majority of new parents seeks advice online or through social media (Russell and Lincoln 2017). And many new parents were so exhausted and nervous when the child is sick; they may easily trust any online information (which could cause serious problems and delay the correct treatment). However, the quality of online information could be a problem for new parents who is lacking of experience to identify the usefulness and accuracy of these kind of information.

2.2

The Lack of Formal Parenting Programs

With the growth of child, there are less educational and supporting programs for parents. Parents are supposed to know everything with their kids, which is usually not the case. More and more parents are both employed with full-time or part-time jobs now, which left less family time for children. The reduction of family time and family education could have long-term influence on students’ life and even on the

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next generation. Most new parents got help from their own parents (the grandparents), relatives, and friends (Rowe et al. 2016). The knowledge was transferred through generation. There are many risks associated with the knowledge transfer, such as breakdown in generation (accidents or immigration) or inaccurateness of the online knowledge. For most parents with child in primary or secondary school, they do not know how they could support their child’s learning in school. Technology developed so fast the child has to learn different things from 20 years ago. Nevertheless, many families moved from their hometowns to other places or countries. They may speak different languages or have different cultures and educational experience. Therefore, the parents feel disconnected with local community or schools and are less confident in teaching their child in their learning process. There are different supporting programs for students with language and special problems in their learning in schools. There should be supporting programs for their parents in supervising their learning and living, which could significantly benefit the child’s learning as well as the whole family. If parental education is very important, why there is no formal program, system, curriculum, or regulation on it? There are several reasons for it.

2.3

The Reasons

The first reason for the missing part in parental education is the variety of needs from different families and different children. Each family has its own value, experience, local knowledge, and family traditions. For example, some big families in China have the family motto and lessons passed on for more than a thousand years (Zhang 2017). This valuable knowledge is accumulated by many generations and is unique it can hardly be copied from one family to another. Different countries and cities have very different environments, animals, plants, weathers, histories, and communities. The information is important for the people who live there but not necessary for the other people who had never lived there. Even people who live in the same city could have different religions and careers. It makes it difficult to ask every family to follow the same instruction in a parenting education. The second reason is the mobility of families and immigrations. More and more families now moved from their hometown to other cities or countries to live. The students have to learn new language, culture, and knowledge when they moved to a new place. The parents from immigrated families feel less confident in supporting their child in getting into learning in local school. Most parents feel confident in teaching their child when it comes to the knowledge or skills they are familiar with. The limited knowledge or skills of parents influence the child’s learning. However, there were several cases some very successful and famous people are taught by parents without any formal education background (e.g., Mengzi in China). The third reason is the different targets from school education and family education. To meet the educational requirement on curriculum teaching, school teachers focus more on meeting the goals in each year’s teaching and make sure all the students can keep up with their learning development. Parents, on the other

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side, educate their child to be safe, independent, and outstanding for their future career. The unmatched goals from school education and family education make it difficult for parents to understand and assist school learning process. Parents from different countries and cultures may have different views on education too. Economic background of a family influenced the student’s learning performance in school (Rowe et al. 2016). Last but not least, it varies in their educational backgrounds and experience; parents tend to try new things based on other parents/family members’ advice free before they invest their money or time on any formal education. Some resources with higher cost or higher time consumed are skipped by many parents. With the fast development of technology, parents tend to search information online and purchase resources or books online now (Russell and Lincoln 2017).Social media is a preferred source for parenting information and social supports now (Russell and Lincoln 2017), which will be discussed in the following section.

2.4

Current Programs and Possible Solutions

There had been a longtime argument on whether the formulated designed and structured curriculum could meet the needs for all the students (especially the gifted students and students with special needs). Parents play an important role in noticing those problems early as they spend more time with the student than any teacher. They have more significant influence on a child’s behavior and performance (Rowe et al. 2016; Russell and Lincoln 2017). To engage parents in students’ education and parents learning, Australian government released information-based mobile application – Learning Potentials (on Apple Store and Google Play). The information covers all parts of student’s development (from nutritious and balanced diet to learning in different stages). However, the articles are usually in English. Immigrated families may found the articles are too difficult to understand. On the other hand, the program is not promoted by all schools, which makes the penetration rate not very high in Australia. The Australian Parents Council is another source to access parenting information and links to trusted resources online. There are many educational programs from other online resources (e.g., ABC kids). But many parents still have concerns on the total number of screen time (including the screen time students using computers or iPad at school) and the gamification in such programs. Majority of parents seeks information online now with the fast development of new technology and new mobile devices, and some parents found the information are valuable (Russell and Lincoln 2017). Social media has been developed very fast in recent years. As shown in Fig. 2 below, almost every generation has their preferred social media platforms due to the timeline of different social media development. They communicate with others on social media and share photos and information. The development of social media was very fast in last decade. As a learning source, social media has played an important role in parenting education now. However, different groups of parents in different country (or even in a multicultural region in the same country) adopted different social media platforms. They have their own preferred sources to acquire parenting knowledge and resources

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1999: MSN,QQ, Bing

2003: Skype, LinkedIn

2005: YouTube, Renren

2010: Instgram

143

2004: Facebook, Flickr, Yelp

2006: Twitter, YouKu

2011: Google+, WeChat SnapChat

2009: Sina Weibo Whatsapp

2013: Yixin, Laiwang

Fig. 2 Timeline of social media markets (Revised from Zhang 2015b)

online too. Some immigrated families are facing more difficulties in getting supports and communicating with local schools with language and cultural barriers. They feel less confident to communicate with the teachers or other parents. The parents use different social media (e.g., Chinese parents adopted WeChat as all major social media in Western countries were blocked in China) to communicate and acquire news and resources (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”).

3

The Study of Immigrated Family on Social Media

As an immigrating country, Australia is proud of its multicultural and multi-language background community with more than half of its families are bilingual or multilanguage families. Wollongong is the ninth biggest city in Australia with many multicultural community groups. The number of Chinese background families increased dramatically in Wollongong from 2012 to 2017. However, new immigrated parents found it is difficult to get information from local community or schools. To understand better their preferred sources for information and resources as well as the family education for their children, a short survey was conducted in April, 2017. The results are discussed in the following section.

3.1

Parenting Information and Resources for Immigrated Families

A survey was designed and sent to Chinese background families in Wollongong to study their family education status in Australia and sources of information and

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resources for child education. As shown in Appendix A (in Chinese), there were 41 children’s parents participated in the survey. Majority of the Chinese background families in Wollongong had one child (54%), and only 6% of the families had three or more than three children, which shows the young and new immigrated families dominated in the survey. This is influenced by the one-child policy in China. Majority of the new parents were the first influenced generation under the one-child policy in China (from 1979 to 2015) and are the only child in their family. They have less experience and information in raising a child. They believe less child with high quality of education is more important (as promoted in one-child policy in China). As shown in Fig. 3, nearly half (48%) of the children were between 2 and 5 years old, followed by 34% of the children who were infants (0–2 years old), 14% of the children who were between 5 and 10 years old, and only 2% of the children who were more than 10 years old in this study. There were four different parent groups on WeChat for Wollongong Chinese background parents to share parenting information and resources on WeChat (0–2 years group, 2–5 years group, primary school-aged group, and grandparents group parents) (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). And the survey was sent to all of the groups on WeChat. In terms of choices for child education, nearly half (45%) of the families chose public education (preschools or schools) as shown in Fig. 4. A total of 38% of the families replied on family education (majority from under 2 years group). And 16% of the families chose private schools. Instead of sending the child to childcare very early (for most working parents in Australia), the Chinese background parents usually get supports from their parents (the child’s grandparents). Many of our surveyed families (Chinese background) in Wollongong had their children’s grandparents living with them for short or long visits. Family support is an important factor in Chinese culture, especially for new parents. So many Chinese background families kept the children educated at home (which are shown in the following question for early Chinese education choice) for their early ages. For the school-aged groups, 45% of the parents chose public education, while 16% of the parents chose Fig. 3 Ages groups of the surveyed Chinese background children in Wollongong (From the survey for this study)

Ages groups

0-2 years old 2-5 years old 5-10 years old 10+ years old

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private education. Education is one of the most important decisions for families in China. Parents usually pay for the child’s education for all ages, and the undergraduate students can focus on their studies instead of looking for part-time jobs during their studies in China (Zhang 2015c). There were an increasing number of international students from China in recent years in most of the countries, and many universities are taking Chinese market as one of their most important markets in the world now. To study the sources of educational information and resources, the first question is on the choice of Chinese language study. Chinese background families took Chinese language learning as an important part of their child’s education. Bilingual ability is identified as an important capability for the student not only in Australia but in many developed countries. Many well-educated families now took Chinese language as their first choice for the language study for their children taking the increasing importance of Chinese market and international trade in the world. As shown in Fig. 5, in this study, majority (61%) of the children were taught Chinese by their parents or grandparents (grandparents usually stay with their grandchildren for the first several years to help out the new parents in Chinese culture) at home. Some parents (12%) sent their children to formal Chinese language school. And 25% of the surveyed parents used English as communicating language at home and thought it is good enough for the child to understand simple Chinese in communication. One of the reasons is the lack of formal Chinese language education resources in Australia Fig. 4 Choices of child education of the surveyed Chinese background parents in Wollongong (From the survey for this study)

Child education

Public Education Familiy Education Private Education

Fig. 5 Choices of Chinese language education of the surveyed Chinese background parents in Wollongong (From the survey for this study)

Chinese langauge education

Family education by parents or grand parents Formal language school Not very important

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(majority of schools and high schools only have Japanese language or other languages taught formally in school). When it comes to the sources of educational information and resources, as shown in Fig. 6, majority of the Chinese background parents preferred searching online information (29%) or purchasing resources online from China (32%). Some parents (18%) chose borrow books or videos from local library. Only a small number of parents looked for online formal educational courses (5%), attend special online programs (6%), or find local private teachers for education (6%). Price is one of the major reasons for this result. One surveyed parent indicated the same book (same quality) is less than half the price in TaoBao (the most popular Chinese online shopping platform) than in Australian online shop. Another reason is most of the Chinese language resources can only be accessed through Chinese online shops. Nevertheless, there are more choices in the Chinese online shops for children’s products and educational products. Many grandparents or family members could bring those resources to the new parents when they came for a visit, which lowered the transportation costs. The new parents usually rely on family and friend suggestions when selecting educational resources. While majority (58%) of the parents spend more than 40 h per week with their child, the hours they invested in education (58%) were between 2 and 3 h only. Compared to other countries, Australian families took leisure time as higher priority than works. Parents in Australia spend longer time with their children compared to Fig. 6 Choices of educational information and resources of the surveyed Chinese background parents in Wollongong (From the survey for this study)

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parents in China. There were only 6% of parents who spend 10–20 h per week with their child only in the Chinese background parents in this study. A total of 22% of the parents spend 20–30 h per week, and 12% of the parents spend 30–40 h per week with their children. In terms of the invested education hours per week (besides school education), 58% of parents invested 2–3 h, 25% of parents invested 3–5 h, 6% of parents invested 5–8 h, 6% of parents invested 8–10 h, and 3% of parents invested more than 10 h. Living with grandparents had significant advantage on Chinese language education as discussed above. But there are disadvantages in family regulation and manner’s education. As shown in Fig. 7, majority (51%) of Chinese background parents felt strong needs to improve the ethics or manners in their child’s education. And there are 25% of parents who felt strong needs to improve the child’s social or communication skills. These are the two important capabilities for future job markets and social living in society (Hunt and Zhou 2017). Only a small number of parents expected improvement on knowledge education: 9% on math or science education (which Chinese background children usually do well than average in Australia), 6% on English learning, 3% on creative arts, and 3% on Chinese language. None of the Fig. 7 The most expected improvement on child’s education from the surveyed Chinese background parents in Wollongong (From the survey for this study)

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surveyed parents have higher expectation on dancing, sports (which Chinese background children are usually in disadvantages compared with local children), and other aspects of education. The strong focus on language, math, and science education in Chinese educational system (OECD 2016) had significant influence on the Chinese parents’ points of view. The other subjects were viewed as not as important subjects and were usually removed in high schools in some Chinese schools. In terms of school education, 35% of the Chinese background parents indicated they understood very well of the child’s progress and educational programs in school and had been study with them. A total of 32% of the surveyed parents indicated they had a good understanding of the child’s progress in school (often ask their child). There were 16% of parents agreed they often check their child’s homework. But there were 6% of parents who admitted they were too busy to ask or check their child’s progress in school, and 9% of parents felt less confident to help their children’s school education because of the lack of English ability. As shown in Fig. 8, a total of 22% of surveyed parents preferred local family programs for both parents and children to participate, followed by outdoor activity for same-aged group of kids (20%), after-school class for kids (15%), weekend outdoor family activities (13%), crafts or chess activities for kids (10%), sports activities for kids (9%), individual class (4%), and online class (3%). Adopted both the Chinese and Australian cultures, Chinese background parents in Australia Fig. 8 The most preferred local family activities or programs from the surveyed Chinese background parents in Wollongong (From the survey for this study)

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preferred more outdoor and family activities than online or individual class for kids. The results shed a light on local government supporting programs or community activities from local groups for those families. The study on Chinese background families in Wollongong, Australia shows the great difference and preferences of special cultural background groups of new families in Australia. The sources for educational information and resources as well as preferred local supporting programs and family activities should be taking into account when designing community activities or supporting programs.

3.2

Supporting Parents’ Groups on WeChat

As discussed above, many immigrated families are facing more difficulties in children’s education and communication with local community or schools. The parents seek advice and purchase educational resources from different sources. They communicated on different social media. There had been several established supporting WeChat groups for the Chinese background parents in Wollongong (Zhang 2015b), which combined both online communication and off-line family activities (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). Many new immigrated parents were benefited from those groups and felt involved and supported by local community. The groups supported not only the new parents but the grandparents (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). These are good examples of mobile technology in local parenting education and supports activities. But there are much more mobile technology can do to support parenting education and learning activities. They are going to be discussed in the next section.

4

Mobile Technology in Parenting Education

Mobile technology has been developed very fast in the last decade and has changed everyone’s life as well as their method of learning and communicating (Castro 2012; Zhang 2015a; Poore 2013; Alhassan 2016; Butoi et al. 2013; Demouy et al. 2015). As discussed in the sections above, there were several reasons for the lack of formal parenting education programs: special requirements, mobility of families, different perspectives from school education, and costs issues. One unique characteristic of mobile learning is the personalized learning design (Zhang 2015a; Hsu et al. 2013), which could greatly support special family education needs. Nevertheless, the profile or knowledge could even be shared and transferred between different family members or generations. This will provide a protection for valuable family memories and knowledge. The anytime and anywhere characteristics and instant communicating ability (Zhang 2015a) of mobile technology contributed to provide a good solution for parenting education. Although mobile devices are usually not cheap, the price of mobile devices and mobile carrier’s costs are decreasing gradually, and the costs of mobile devices are regarded as sunk costs (ITU 2016; Yousafzai et al. 2016). There

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was a fierce debate on children’s education on mobile devices, especially for younger kids (Qiu and McDougall 2013; Doug et al. 2009; Hwang and Chang 2016; Mishra 2013; Yousafzai et al. 2016). Mobile learning for parents to increase the efficiency of family education, therefore, opens another door for mobile education. A better support for parents through mobile technology could generate more benefits than knowledge education (e.g., children safety). To design and implement a good mobile parenting program, there are many issues to be taken into accounts, which will be discussed in the following section.

4.1

Content Development and System Design

To provide personalized design for family education, the contents must be dynamic and personalized. Some contents, such as family journals and photos, are valuable memories for each family and are important resources for the parents to share and store. As shown in Fig. 9, a cloud-based system with sharing function with family members and authorized person is an important part of the program. Security issues are important for family contents (and personal information). Therefore, firewalls and security software should be installed to prevent phishing or hostile online attack. The system should be compatible to different devices and platforms to suit the

DB Server

Data

Content Manager

Stream Server

Fire Wall User

Internet City1

User

Fire Wall

User

City2

User

WAP

User

PDA Base Station

Base Station Customer

Mobile Phone

Customer

WEMOSOFT Mobile Phone

Mobile Phone Mobile Phone

Fig. 9 The parenting education system enables access from different locations (Revised from WEMOSOFT GCCP design)

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different needs from different groups of people from different countries. A friendly and easy to use interface should be provided for parents with less technical skills and knowledge as well as the young and old generations. To reduce the influence of network connections, both online and off-line functions should be provided (see ▶ Chap. 27, “Tutors in Pockets for Economics”). As discussed above, different groups and generations have different preference in social media and communicating tools. Therefore, a good designed mobile supporting program should be linked with different social media platforms to provide supports to various groups of parents and grandparents (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Another important function of this system is the smart link to the trusted online information and resources. To provide convenient access to online information as well as reduce the influence of unauthorized or untrusted resources, a filter system to identify those sources of information is required. Like kids, parents need protection from online attacks. A good rating system by parents is helpful for parents to communicate and share good sources online with family and friends.

4.2

Effective Learning with Children

Parent, a special career for most of people, plays a vital role in human development. Given the importance of parenting education, there were less formal educational programs or supporting materials for parents. Many new parents struggled during the first 3–5 years of parenting and were relying on online information and resources, which are sometimes inaccurate or incorrect. What if the information are formally provided to all parents freely online and personalized on their mobile devices? What if the parents spend more efficient happy time with the children instead of worrying all the time and wasting a lot of times in their 75,000 h with their children? Empirical studies have found there are many effective learning techniques which can improve education, such as spacing and interleaving, self-testing, and explanatory questioning (Roediger and Pyc 2012). The friendly and warm parenting time with kids has a huge influence on the kids’ personality and influenced their life (Russell and Lincoln 2017; Kim et al. 2014). Some local government programs and trusted online educational programs provided useful advice on how to increase efficacy in family education (Dunbar 2017; Russell and Lincoln 2017; Rowe et al. 2016; Metzgar 2017; Becker et al. 2016). A little improvement in family education could play an important role in families and society if it is applied to many families. It generates prolong influence on human being when there are multiplier effects on family education.

4.3

Combination with Off-Line Activities

As concerned by most parents, the online activities had a huge influence on social and communicating abilities of the kids, which influence the social and communicating abilities of the parents (Ahn and Shin 2013; Primack et al.). Therefore, it is

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highly recommended the online education programs should be combined with off-line activities. As in the survey results from the local Chinese background parents in Wollongong, majority of the surveyed parents preferred family activities and weekend outdoor activities with the kids. This proved the parents have strong needs for off-line social activities when moving to a new environment and new community. On the other hand, the off-line activities generate online contents and online interactive for parents groups (Zhang 2015b) (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”).

5

Future Directions

As a sum, parents play an important role in child’s education and development. But there are less formal parents’ educational programs or supporting programs. There are strong needs for online communication and sharing of information for all aged parents. The immigrated parents are facing more difficulties in getting involved in local community programs or communicating with local schools. Majority of parents seeks information and resources online. Mobile technology, as a convenient personalized tool, has unique advantages in parenting education and family education. It opens a door for parenting education and family supports (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). The future design for parenting education should focus on cloud-based family support programs for parents. Online protection for personal information and family resources should be provided to all parents as well as for kids. The communication functions with local community and schools from different social media and platforms should be taken into considerations (for different groups of parents). Both online and off-line functions and different language supporting systems should be provided. The program should be combined with off-line outdoor activities to engage the parents and children in local community activities instead of online only communications. Some new technologies could be adopted in such programs (see ▶ Chap. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”). Given the importance of healthy family activities and education in a child’s development and learning, there should be more focus on the efficiency of family education in every country. All the parents (when they became parents for the first time) are new to the role. They need more supports from family and community. A little change can make huge influence in the future.

6

Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Tutors in Pockets for Economics

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Parental Education: A Missing Part in Education

Appendix A Survey on Chinese Background Families in Wollongong

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References Ahn, D., and D.-H. Shin. 2013. Is the social use of media for seeking connectedness or for avoiding social isolation? Mechanisms underlying media use and subjective well-being. Computers in Human Behavior 29: 2453. Alhassan, R. 2016. Mobile learning as a method of ubiquitous learning: Students’ attitudes, readiness, and possible barriers to implementation in higher education. Journal of Education and Learning 5: 176. Becker, A.S., A. F., C. Giesinger Hall, M. Cummins, and B. Yuhnke. 2016. NMC/CoSN horizon report: 2016 K-12 edition. Austin: The New Media Consortium. Butoi, A., N. Tomai, and L. Mocean. 2013. Cloud-based Mobile learning. Informatica Economica 17: 27–40. Castro, J.C. 2012. Learning and teaching art: Through social media. Studies in Art Education 53: 152–169.

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de Zeeuw, E.L., C.E.M. van Beijsterveldt, T.J. Glasner, E.J.C. de Geus, and D.I. Boomsma. 2016. Arithmetic, reading and writing performance has a strong genetic component: A study in primary school children. Learning and Individual Differences 47: 156–166. Demouy, V., A. Jones, K. Qian, A. Kukulska-Hulme, and A. Eardley. 2015. Why and how do distance learners use mobile devices for language learning? The EUROCALL Review 23: 10–24. Doug, V., K. David, and K. Ron Chi-Wai. 2009. Does using mobile device applications lead to learning? Journal of Interactive Learning Research 20: 469–485. Dunbar, F. 2017. 50 little things teachers, parents, and others can do to improve education. Accessed 28/2/2017 2017. Emerson, R.W. 1860. The conduct of life. Houghton: Mifflin and Co. García, J.L., Heckman, J.J., Leaf, D.E., Prados, M.J. 2016. The life-cycle benefits of an influential early childhood program. The National Bureau of Economic Research. 1–72. http://www.nber. org/papers/w22993.pdf. Gordon, T. 2000. Parent effectiveness training. New York: Three Rivers Press. Hsu, C.-K., G.-J. Hwang, and C.-K. Chang. 2013. A personalized recommendation-based mobile learning approach to improving the reading performance of EFL students. Computers & Education 63: 327–336. Hunt, E. and N. Zhou 2017. What does the future hold for students starting university today? The Guardian. https://www.theguardian.com/australia-news/2017/feb/20/what-does-the-futurehold-for-students-starting-university-today. Hurst, N. 2017. Students more likely to succeed if teachers have positive perceptions of parents. Missouri: University of Missouri. Hwang, G.-J., and S.-C. Chang. 2016. Effects of a peer competition-based mobile learning approach on students’ affective domain exhibition in social studies courses. British Journal of Educational Technology 47: 1217–1231. ITU. 2016. Measuring the information society report. ITU. https://www.itu.int/en/ITU-D/Statistics/ Documents/publications/misr2016/MISR2016-w4.pdf. KFRR. 2016. Australian kids & family reading report. KFRR. http://www.scholastic.com.au/ schools/ReadingLeaders/KFRR/assets/pdf/KFRR_AUS.pdf. Kim, J., S.J. Lee, S.A. Taylor, and N. Guterman. 2014. Dyadic profiles of parental disciplinary behavior and links with parenting context. Child Maltreatment 19: 79–91. Lorber, R.M., and B. Egeland. 2009. Infancy parenting and externalizing psychopathology from childhood through adulthood: Developmental trends. Developmental Psychology 45: 909–912. Metzgar, M. 2017. Community-focused versus market-driven education. Hybrid Pedagogy. http:// www.digitalpedagogylab.com/hybridped/community-focused-versus-market-driven-education/? utm_campaign=Feed%3A+HybridPed+%28Hybrid+Pedagogy%3A+a+digital+journal+of+learn ing%2C+teaching%2C+and+technology%29&utm_medium=feed&utm_source=feedburner. Mishra, S.K. 2013. Quality education for children, youth, and adults through Mobile learning. In Pedagogical applications and social effects of mobile technology integration, ed. J. Keengwe. Hershey: Information Science Reference. Mourshed, M., D. Farrell, and D. Barton 2012. Education to employment: Designing a system that works. McKinsey on Society. https://www.compromisorse.com/upload/estudios/000/222/Educa tion-to-Employment_FINAL.pdf. Nicoletti, C., and B. Rabe. 2013. Inequality in pupils’ test scores: How much do family, sibling type and neighbourhood matter? Economica 80: 197–218. OECD. 2016. Education in China a snapshot. Paris: OECD Publishing. Poore, M. 2013. Using social media in the classroom, a best practice guide. Los Angeles/London/ New Delhi/Singapore/Washington, DC: SAGE Publications. Primack, B. A., A. Shensa, J. E.Sidani, E. O.Whaite, L. Y. Lin, D. Rosen, J. B.Colditz, A. Radovic, and E. Miller. 2017. Social media use and perceived social isolation among young adults in the U.S. American Journal of Preventive Medicine, 53:(1)p1–8. Qiu, M., and D. McDougall. 2013. Foster strengths and circumvent weaknesses: Advantages and disadvantages of online versus face-to-face subgroup discourse. Computers & Education 67: 1–11.

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Roediger III, H.L., and M.A. Pyc. 2012. Inexpensive techniques to improve education: Applying cognitive psychology to enhance educational practice. Journal of Applied Research in Memory and Cognition 1: 242–248. Rowe, M.L., N. Denmark, B.J. Harden, and L.M. Staplenton. 2016. The role of parent education and parenting knowledge in children’s language and literacy skills among white, black, and latino families. Infant and Child Development 25: 198–220. Russell, B.S., and C.R. Lincoln. 2017. Reducing hostile parenting through computer-mediated parenting education. Children and Youth Services Review 73: 66–73. Yousafzai, A., C. Chang, A. Gani, and R.M. Noor. 2016. Multimedia augmented m-learning: Issues, trends and open challenges. International Journal of Information Management 36: 784–792. Zhang, Y. 2015a. Characteristics of mobile teaching and learning. In Handbook of mobile teaching and learning, ed. Y. Zhang. Australia: Springer. Zhang, Y. 2015b. Mobile education via social media – case study on WeChat. In Handbook of mobile teaching and learning, ed. Y. Zhang. Australia: Springer. Zhang, Y. 2015c. Student feedback in mobile teaching and learning. In Handbook of Mobile teaching and learning, ed. Y. Zhang. Australia: Springer. Zhang. 2017. The toleration motto from Zhang family [Online]. Zhang Xing Shi Zu. Available: http://www.zhangxingshizu.com/html/xwpd/hgwh/3588.html. Accessed 20 May 2017.

Design and Implementation of Chinese as Second Language Learning

10

Yu (Aimee) Zhang, Wangweilai Xiang, and Qifang Xue

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Design and Implementation of Chinese Language Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Students’ Backgrounds and Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Curriculum Design and Implementation for Junior Class . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Curriculum Design and Implementation for Senior Class . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Implementation of Mobile Learning and Designed Games . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Evaluation of Different Methods in Chinese Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Chinese language is one of the most difficult languages to learn as a second language. With the growing number of families emigrating from China to other countries, increasing business opportunities with Chinese companies, the demand to learn Chinese has dramatically increased for adults and school-age children. Often seen is a negative effect when learning Chinese; students lose interest to learn quickly without making a concerted effort to practice speaking and writing Chinese. This qualitative empirical study focused on a Chinese language school in Australia to analyze the different methods used to learn Chinese. Mobile technology applications were created to stimulate after school studies in conjunction with traditional face-to-face learning. The applications were shown to be Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] W. Xiang · Q. Xue Wollongong Chinese Language School, Wollongong, NSW, Australia e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_102

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effective tools to increase students’ interest in practicing writing skills and speaking with teachers, peers, and parents. The mobile learning applications and teaching materials developed by WEMOSOFT for this study could be used by other schools, educational institutions, and individuals.

1

Introduction

Chinese language is one of the most difficult languages to learn as a second language learner (Xu et al. 2004). With the increasing number of Chinese families immigrating to Australia and other western countries, there is a need for the children of those families to learn Chinese. A survey (conducted in Wollongong, Australia) among the Chinese families immigrating to Australia indicated a majority of parents (75%) think Chinese learning is important for their children and 25% indicated Chinese speaking and listening skills are important for their children (see ▶ Chap. 9, “Parental Education: A Missing Part in Education”). Communication (understanding of the Chinese language and the Chinese culture) is an important factor influencing the performances and results of international business collaboration between Australia and Chinese partners (Zhang 2012a). More Australian businesses are hiring employees with Chinese language skills as they increase their business with Chinese companies or providing services to Chinese customer. Most universities in Australia have Chinese language as an area of study, but Chinese language is not taught in most public primary or high schools in Australia. Only some private and selective schools have Chinese language as areas of study, creating a market for private language schools in Australian cities to meet the Chinese families’ demands for their children to learn to speak and write Chinese. Since 2015, the Chinese language after-school class has been active in Wollongong Public Schools. The class is taught 1 day per week (during school terms) from 3:15 to 5:15 pm in Wollongong Public School library. This study was conducted by two Wollongong Chinese Language Schoolteachers and one mobile learning program designer. Mobile technology has been adopted in many teaching and learning subjects because of its interactive capabilities (Alkhezzi and Al-Dousari 2016; Baage 2013; Demouy et al. 2015; Hsu et al. 2013; Kabugo et al. 2016; Koutropoulos et al. 2013) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). To increase the quality and efficiency of language teaching, a small class design was used (a teacherstudent ratio 1:6) to facilitate the teaching and engagement of the students. A mobile application was designed to support the learning and teaching by WEMOSOFT (see ▶ Chap. 28, “Development of Chinese Character-Writing Program for Mobile Devices”). A qualitative design was used to observe and interview the students and teachers. Several teaching programs and mobile technologies were applied and evaluated in the study. The design and implementation of these methods are going to be discussed in the following section.

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Design and Implementation of Chinese Language Learning

The exposure of the second language environment is vital for second language learning (Shu-Chun et al. 2017; Seo 2013). It is difficult for children living in a predominately English language environment to learn Chinese. Designing an effective teaching and learning program, to accommodate the students’ background and characteristics of the students, is an important first step for successful Chinese learning.

2.1

Students’ Backgrounds and Requirements

Australia is a country with a large immigrant population, comprising of several cultural and language communities from many countries. As shown in Fig. 1 (photo took at the end of year award ceremony in Wollongong Chinese Language School), in the last term of 2016, there were 12 students. There were seven Chinese students with one or two parents who emigrated from China or spoke Chinese at home, three Asian students who do not speak Chinese at home but use another language other

Fig. 1 The end of year award ceremony for Wollongong Chinese Language School. (Photo from this study)

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than English at home, and two students who are English speaking students learning Chinese as a second language. In the junior class, there were seven Chinese speaking students (one or two parents are speaking Chinese at home) and one teacher (Ms. Xue, one of the authors at the top right in Fig. 1). The parents’ expectations were high for their children to maintain a level of proficiency. Chinese education at home is a nonformal educational experience, conducted by parents or grandparents. The parents usually communicated with their child (between 0 and 3 years old) using Chinese and taught them some Chinese characters. The children had a Chinese foundation for listening and speaking (some of the students were able to read and write simple Chinese characters). Once the children entered primary school, the use of Chinese language decreased as the child got older. Parents believe formalized learning in a Chinese environment will increase their child’s interest to learn Chinese and their willingness to communicate with other Chinese speaking people. In the senior class, there were two students with English speaking parents and three Asian background students who speak another language other than English at home. The teacher was Ms. Xiang (one of the authors at the top left in Fig. 1). The two local students were self-motivated to learn Chinese. The Asian background students had grandparents from China, and the parents believed learning Chinese was important for their future endeavors. The initial levels of Chinese language skills for those students were lower than the junior class (Chinese speaking students). The major focus for the senior class was listening and speaking Chinese. Given the different cultural backgrounds, expectations, and entry levels of the students in the junior and senior classes, the curricula design and implementation of teaching were different for the two classes. Ms. Xue and Ms. Xiang, the two teachers for the junior and senior classes, implemented different teaching methods, which are going to be discussed in the following section.

2.2

Curriculum Design and Implementation for Junior Class

Based on a combination of environmental and practical factors in the Australian models to learn Chinese, it was a challenge to design curriculum for the younger students. Most of the students came to Chinese language school as a result of their parents’ desires for their children to learn Chinese, giving up their after-school rest and play time. So a goal was to guide and develop the students’ motivation to learn Chinese. Research suggests teachers’ perceptions of parents have positive influence on students’ performance in language learning environments (Hurst 2017). Robust communication and collaboration between teacher and parents are vital for successful second language learning (see ▶ Chap. 9, “Parental Education: A Missing Part in Education”). A teacher-parent communication channel was designed for each student through a WeChat (a Chinese social media with more than 800 million users) (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”) Chinese language class group. Teachers and parents communicated online and

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shared teaching resources. The channel allowed the students to communicate with other students about social events, creating a positive social interactive environment and a chance to use their language skills. The weekly students’ awards, printable teaching materials, mobile teaching application (see ▶ Chap. 28, “Development of Chinese Character-Writing Program for Mobile Devices”), and some educational kids’ crafts donated by WEMOSOFT (www.wemosoft.com) were valued by the teachers and students. Those resources significantly increased students’ motivation and engagement in class activities. To engage and increase students’ interests in learning Chinese, the teachers showed a passion about teaching Chinese and develop a bond with their students to increase their desire to learn Chinese. There are several methods demonstrating effective teaching and learning (RoedigerIII and Pyc 2012; Akamca et al. 2009; Zhang 2012b). Given the age and backgrounds of the students in the junior class, a combination of different teaching and learning methods were designed and implemented since every student has a unique response to a teaching method (O’day 2010). Weekly language learning (one class per week) was good for spacing learning (Roedigeriii and Pyc 2012). After a day of intensive school activities and studies, students are tired and found it difficult to focus on their Chinese studies. In such situations, holding the pen quietly in a written practice is not a suitable way to learn. The following teaching methods were adopted in the junior Chinese language class so students can maintain a relaxed and content mood in their learning.

2.2.1 Test-Enhanced Learning on Student Chinese Vocabulary Literacy and vocabulary are the foundation for Chinese learning. Empirical studies have shown frequently assessing students can improve learning (RoedigerIII and Pyc 2012). In the junior Chinese language class, the students were asked to “recognize,” “read,” and “write” the words in class. Chinese characters are similar to hieroglyphics, a set of phonetic and tabular text systems formed by the association of the shape, the sound, and its polymorphic structure, in order to enable students to learn Chinese characters, recalling Chinese characters, through writing each Chinese character using associative memory, and grouping them into different words or sentences. Both methods enhance character recognition and increase the capacity for using the characters in real cases. Games can play an important role in language learning (Dunbar 2017; Prensky 2001). A word game was designed for the junior class. The children used their imagination and initiative to recall Chinese characters. For example, students used their physical expressions or other descriptive sentences to describe the character without saying it directly, and another student would guess what the Chinese character was. Distribution of practices outside of the classroom has shown to be an effective learning method (RoedigerIII and Pyc 2012). However, the English-only speaking students have less practice opportunities once they leave the formal learning environment. Games were developed for junior and senior classes to engage the students outside of class (in Figs. 2 and 3). The games allowed the students to play individually or with others. The printable games combined with mobile learning improved

Fig. 2 Chinese word game developed for Wollongong Chinese Language School. (Photo from this study)

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Fig. 3 Chinese picture game developed for Wollongong Chinese Language School. (Photo from this study)

learning efficiency and long-term memory. As shown in previous empirical studies, practicing Chinese to solve real-world problems (games) enhances learning performance (Roediger and Pyc 2012; Dabbagh and Dass 2013; Van Merriënboer 2013; Sharples 2000).

2.2.2 Situational Learning and Role Playing English is the official language in Australia, a significant obstacle to learn Chinese because the students have minimal opportunities to practice Chinese once they leave the classroom A situational learning program was designed and implemented in the junior Chinese language class, linking the characters or words to real-world simulations. For example: in the “I go to school” lesson, a group of students were asked to introduce themselves to others and describe their school life. Throughout the role play, the students were more open and active in class activities. Personalized education has been a growing trend in language learning education (Hsu et al. 2013; Sun et al. 2016; Becker et al. 2016). Some students have a strong desire to show their level of expertise, while others are introverted. Role-playingdesigned activities allowed all the students to participate regardless of their personality traits. Role-playing included text-based reading competition and scene performances, letting each student to have opportunities to demonstrate their level of Chinese competency and knowledge.

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2.2.3 Learn from Open Questions, Discussion, and Reading Descriptive questions have shown to be effective in teaching and learning languages (RoedigerIII and Pyc 2012). The teaching materials used in each lesson included reading opportunities where the students were expected to read the material for content comprehension, allowing the teacher to assess the reading skill level of each student. To overcome the different reading levels, discussions occurred between the teacher and students. Each student understood the problem and brainstormed ways to improve his/her reading ability. For example, before the student reads the material, the teacher asked questions related to the reading. This questioning period allowed the students to have some basic understanding of the material before they independently read the passage. This process allows for improving their attention to and recalling detail. Through this practice, the students’ reading comprehension increased dramatically. This process to learn Chinese encouraged the students to work together to improve their understanding, judgment, reasoning of the material, and enhanced their social and communication skills. 2.2.4 Practicing Writing with Drawing and Mobile Assisting Tools The students in the junior class were primary students (Fig. 4). It was a difficult task for them to independently practice Chinese writing or finish a writing task, such as writing an article. The teachers began using pictures as visual cues to encourage proper writing practices (Connor 2009; Kabapinar 2005; Keogh and Naylor 1999; Zhang 2012b; Stephenson and Warwick 2002). Chinese characters were originally linked to oracle pictures. Students were asked to describe their understanding of the content from pictures, write stories, and participate in storytelling, to improve their writing abilities. Fig. 4 Two junior class students in Wollongong Chinese Language School. (Photo from this study)

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In the junior class, students became more confident in their abilities and their willingness to use Chinese and learn additional Chinese characters. These students valued drawing and painting and were encouraged to draw and describe their pictures, which were linked to the Chinese characters they learnt. For example, in the “bird free fly” lesson, students were encouraged to draw a picture with a description based on their readings. The students then shared their work with the other students, allowing their peers to not only see their artwork but gain a better understanding of the passage. In this way, the students learned to describe a scene and demonstrate their critical thinking skills. To encourage students in learning Chinese, the students were asked to act as the teacher’s assistant in a role play. The assisting student helped other students by repeating what the teacher did. Students built their confidence in this role-playing game. As a result, there was significant improvement in learning competence and behavioral self-control. To stimulate each child’s creativity, personalized teaching methods were adopted, so each child was allowed to independently express themselves intellectually and personally (Dabbagh and Kitsantas 2012). More open discussions lead to differences in learning, which required the teacher to find the child’s strengths and areas of improvement. Some children wrote well, some children responded quickly to questions, and some children read aloud. Today’s students are born in the age of digital and mobile devices (Prensky 2001; Zhang 2015), competing in a rapidly changing labor market where jobs are being replaced by machines and robots (Hunt and Zhou 2017). People will be required learn skills not presently taught in schools. To prepare students for digital world, mobile technology is increasingly used in teaching and learning environments (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). In the Chinese class, students and teachers used mobile technology to engage the students in one of the most difficult tasks in Chinese learning – writing practices. A writing showcase, practicing, and scoring application on mobile devices and online browsers were developed by WEMOSOFT in 2016 to support in-class and afterschool learning (see ▶ Chap. 28, “Development of Chinese Character-Writing Program for Mobile Devices”). The content was designed and developed to link to each week’s lesson so students could practice at home anytime and anywhere. Students were excited to participate in games in class, which increased their social skills and communication skills. The next stage of teaching will focus on using blended teaching methods and personalized teaching to enhance learning performance.

2.3

Curriculum Design and Implementation for Senior Class

Unlike the junior class students, the majority of the senior class students had not any Chinese background or knowledge before attending the Chinese Language School. They were from English speaking Australian families or Asian background families (with another native language). Every character or sentence in the textbook was new. The senior class focused on Chinese communication and cultural study to increase

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the students’ interests in Chinese learning. To improve the teaching methods, carry out new teaching design, and put the research results into practice, a “teachingresearch-practice-improvement-implementation” cycle that was adopted in the senior class. There were significant differences between students in their ages (from 4 to 11 years old), interests in learning, cultural backgrounds, and abilities (some students came during a term study). The textbook did not meet the students’ needs. The difficulties came from the students’ attitudes toward Chinese learning (some were self-motivated, and some were reluctant to join any learning activities) and the time requirements to learn Chinese.

2.3.1 Schulte Grid and Games in Learning To solve the problem, special teaching materials and games were developed and adopted. In digital teaching, the Chinese version of the Schulte grid (as in Tables 1 and 2) was used so the students could become familiar with the Chinese characters. Games were created to learn direction, time, family tree, and body parts. For example, in the body parts game, a human body was drawn on a white board. One student closed his/her eyes, while another student wiped off a part of the body and told the first student in Chinese where he/she erased. The first student was asked to complete the figure on the whiteboard according to his/her memory. In the textbooks, each lesson has a Chinese poem or song at the end of the learning unit. Chinese poems have a strong sense of rhythm. The students discovered it was similar to rap music and often preferring to use rap when recalling the content. Self-explanation in learning process (Roedigeriii and Pyc 2012) improved their critical thinking skills and innovative skills, which increased their self-motivated learning, teamwork, and interests in learning Chinese. 2.3.2 Chinese Cultural Study It is important to teach the contents in the textbook and support students to create a foundational Chinese language learning routine to build their interests in Chinese culture. The school created an environment for students to understand traditional Chinese culture by exposing them to Chinese calligraphy, Chinese traditional dancing, and Chinese crafts (Figs. 5 and 6). Students were engaged and practiced their Chinese writing, communicating skills, and social skills in class with the invited guests, teachers, and their classmates. Table 1 The Schulte grid in Wollongong Chinese Language School 一 七 二十五 十二 二十一 Source: From this study

十三 二十二 十一 二十三 二

六 二十四 三 二十 十四

十七 九 十八 十五 十九

十 五 十六 四 八

九十四 五十八 一 七十五 五十四 四十六 六十八 十 二十八 七

Source: From this study

十三 四十二 九十六 八十一 二十一 六十五 十七 八十四 三十一 四十五

五 三十七 六十六 三十 十二 一百 七十二 五十五 七十四 三十九

九十 八十五 四十七 九十八 八十二 二十四 九十三 十九 六十七 七十九

二十 七十八 四 五十二 三十五 九十七 三十二 六十四 十六 五十

Table 2 The 10*10 Schulte grid in Wollongong Chinese Language School 九十九 二十六 六十一 十八 五十七 四十四 六 八十六 八十九 七十一

八十三 七十六 三十三 七十三 四十八 九十二 三十八 六十九 二 二十五

五十一 九 八十 四十九 六十 十一 二十二 十五 四十 五十六

三十四 六十二 十四 八十八 三 七十七 八十七 三十六 五十三 二十九

五十九 二十三 九十五 四十三 二十七 四十一 六十三 九十一 八 七十

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Fig. 5 An invited teacher from China taught students Chinese calligraphy in Wollongong Chinese Language School. (Photo from this study)

2.3.3 Flash Cards and Stroke Cards Designed for Chinese Learning Chinese flash cards were made by senior class students (Fig. 7), and they used them to practice Chinese away from the classroom. The flash cards had Pin Yin (pronunciations) on them so the students were able to determine the pronunciations. A “pen stroke card” helped in Chinese writing. Each character was divided into strokes. Students were asked to find the corresponding order of the strokes and arrange them in the composition of the Chinese character. The idea came from a student’s parent, who designed the stroke game for the junior class. The card games enriched the Chinese language learning for those students without opportunities to practice Chinese outside the classroom. Students were usually tired when they came to class after a full day of regular school. To balance the study and relaxation time, teaching occurred into10-min units. Students were assigned a task in each of the 10-min units. They were allowed to relax and/or play games if they could finish their task early. The new characters and learning materials were assigned in the first two units, and the songs and games were assigned to later units. Reward chart and stickers were used to encourage the students to perform well in class. One student said: “I can do anything for just one more sticker.” But sticker incentives did not work for senior students. In order to improve their enthusiasm, teaching assistant strategy was adopted. This strategy is useful to solve the problems

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Fig. 6 Chinese traditional dancing in Wollongong Chinese Language School, Yifei Shi (left) and Dr. Aimee Yu Zhang (right). (Photo from this study)

Fig. 7 Chinese flash cards developed for Wollongong Chinese Language School. (From this study)

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for new students. Current students helped teach new students words which allowed the older students to practice their own knowledge. The students developed techniques suitable for students without any Chinese language background. For example, to learn “mouth,” “four,” “head,” and body parts, the new students tended to write the last character out of the word “mouth box” and then write the contents of the box inside. But this does not meet the Chinese writing stroke order (Chinese stroke writing order need to write vertical, and then cross, and then the contents of the word inside the box, and finally seal). Current students created their own rules to learn how to write; “you should build three walls first, then put things inside, and then close the door.” They developed useful formulas for Chinese learning individual, which helped the new students understand while enhancing their own learning processes. The case study demonstrated that problem-solving learning (Dabbagh and Dass 2013; Van Merriënboer 2013) could significantly increase learning efficiency as well as enhance long-term memory. Teaching 5000 years of Chinese culture into a weekly Chinese language school is a difficult challenge. Teachers and students worked together in their teaching and learning journals (the flexible curriculum created by the teacher and students together). The innovations in teaching and learning had positive effects in students’ learning performances and possible positive effects in their future endeavors. Mobile learning as a complementary teaching method engaged students in their Chinese learning, which is going to be discussed in detail in the following section.

2.4

Implementation of Mobile Learning and Designed Games

There were 95% of the world population covered by mobile cellular signals in 2016 (ITU 2016). Mobile learning caught the attention of educators, designers, developers, researchers, and policy makers (Alhassan 2016; Cheon et al. 2012; Hennig 2016; Zidoun et al. 2016; Wu et al. 2012). However, due to the limitation of mobile technology as well as the considerations for younger students using mobile learning in classroom, mobile learning is not designed to replace face-to-face teaching and learning in its current stage. Currently, mobile learning’s role is a complementary tool to face-to-face teaching and learning (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). For example, the economics teaching application (see ▶ Chap. 27, “Tutors in Pockets for Economics”). Writing is the most difficult part in Chinese learning, which requires a great deal of practice and patience. To support the writing practices in Wollongong Chinese Language School, a writing showing, practicing, and evaluating application on mobile devices and online browsers were designed and developed for the students by WEMOSOFT in 2016 (see ▶ Chap. 28, “Development of Chinese CharacterWriting Program for Mobile Devices”). The program was adopted as in-class group activity and after-school practice tool. Students were able to challenge other students (or even teachers) Chinese writing in class. They practiced at home or challenged their parents in writing. The researchers learned from this study that mobile technology could assist traditional teaching and learning in many ways just as any other

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Table 3 Evaluation of methods in Chinese learning in Wollongong Chinese Language School Methods Tests and self-tests

Advantages Enhanced memory

Situational role play

Increased interests and practices Enhanced critical thinking Enhanced focus Increased interests and practices Increased interests and practices Increased interests in learning Increased problem solving Increased practices

Open questions Schulte grid Flash cards

Mobile application Cultural studies Printable games Homework

Disadvantages Students are discouraged if they fail Students prefer certain roles

Comments (from students and parents) Students remembered to practice at home

Discussion may lose focus

Students are engaged in discussion

For short time only For short time games

Students feel accomplished in challenging games Students can practice with the cards at home

May be distracted by games Students are too excited sometimes Some are difficult for some students Sometimes are forgotten

Students asked for more practices at home

Students love them

Students learn not only Chinese language but cultures, which makes them interested in Chinese learning Students want more practices in this form

They usually forgot after class

Source: From this study

teaching tools. The evaluation methods adopted in Wollongong Chinese Language School, the advantages, disadvantages, and comments from students and parents are discussed in the following section.

3

Evaluation of Different Methods in Chinese Learning

As one of the most difficult adopted languages to learn in the world (Xu et al. 2004), Chinese is being taught in many educational departments, schools, and organizations. Wollongong Chinese Language School combined the traditional face-to-face language teaching with new technology. The innovative methods, programs, and resources used in Wollongong Chinese Language School were compared in Table 3. When facilitating students in their learning, it is important to identify and develop the students’ interests and abilities in different areas. The advantages, disadvantages, and students and parents’ comments are presented for future development of Chinese language learning programs in Australia and other countries in Table 3 below. As shown in the table, the majority of the methods used in the school had positive influences in students’ learning. But each student had his/her own advantages and

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disadvantages. They demonstrated interests in different teaching methods and materials. One method or program cannot help all students. Personalized learning is one of the most important characteristics in mobile learning (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”) and useful in learning languages.

4

Future Directions

Language learning should be a lifelong learning experience, motivated by self-study and interests. Continually practicing the language is important in second language learning but difficult to actualize. Teaching Chinese in a predominant Englishspeaking environment is difficult while trying to increase students’ interests in Chinese learning. This study focused on different methods, programs, and resources used in Chinese teaching and learning at the Wollongong Chinese Language School for different levels of students. Innovative teaching, mobile learning, and new teaching resources had positive influences on students’ demonstrated by students’ interest to learn Chinese increasing over time. Many students indicated they were interested in Chinese learning after 1 year of study at the Chinese Language School. The future directions of Chinese learning and teaching will be a combination of traditional face-to-face and new technology. A personalized learning approach should be designed and used in language learning complemented by mobile technology (see ▶ Chaps. 79, “VR and AR for Future Education” and ▶ 65, Advanced Image Retrieval Technology in Future Mobile Teaching and Learning).

5

Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning ▶ Design and Implementation of Chinese as Second Language Learning ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Parental Education: A Missing Part in Education ▶ Tutors in Pockets for Economics ▶ VR and AR for Future Education

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The Graduation Game: Leveraging Mobile Technologies to Reimagine Academic Advising in Higher Education

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Tressa M. Haderlie, Apoorva Chauhan, Whitney Lewis, and Breanne K. Litts

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Human-Centered Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Situative Learning Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 ARIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 The Graduation Game (TGG) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Game Development and Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Iterations of the Graduation Game (TGG) and Player Feedback . . . . . . . . . . . . . . . . . . . . 4 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 The Graduation Game: Current Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Collecting Evaluation Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Final Testing Before Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Email Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Orientation Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Evaluative Feedback on TGG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Designing Mobile Technology for Academic Advising in Higher Education . . . . . . . 5 Future Direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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T. M. Haderlie (*) The Department of Psychology, Utah State University, Logan, UT, USA e-mail: [email protected] A. Chauhan Department of Computer Science, Utah State University, Logan, UT, USA e-mail: [email protected] W. Lewis · B. K. Litts Instructional Teaching and Learning Sciences department, Utah State University, Logan, UT, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_98

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Abstract

Using the augmented reality features of a mobile game development platform, ARIS, the Utah State University’s psychology department designed a mobile application called The Graduation Game (TGG). TGG addresses issues with current student advising procedures and aims to make advising information and resources more readily available to students. The game seeks to provide an earlier and more meaningful connection between incoming students and their academic advisors and the institution. This chapter discusses the iterative development cycle of TGG describing a series of game design and play testing over the period of 8 months. We conclude with the affordances and constraints of TGG, lessons learned from using a game design approach for academic advising, and implications for leveraging mobile technologies to improve students’ advising experiences.

1

Introduction

Academic advising in higher education can have a large effect on students’ relationship with the institution. The connection students feel toward their school can have significant impacts on retention and students’ persistence through their academic career. Scholars have found how students judge the quality of their advising experiences is directly correlated to their loyalty to their school (Vianden and Barlow 2015). Moreover, researchers have demonstrated that students who are contacted earlier by their advisor are much more likely to persist in their education (Heyman 2010). Academic advisors can make a difference in students’ higher education experiences; however, forming strong student-advisor relationship is a challenge, especially at larger universities with hundreds of new students enrolling each semester. The National Academic Advising Association found the average case load of a full-time advisor is 1:260 for a public bachelor university (Carlstrom and Miller 2013). Hence, while academic advising can play a crucial role in students’ college experience, advisors face an unyielding demand of supporting hundreds of students simultaneously. In response to this tension, universities have implemented various technological solutions. In the 1980s, institutions began implementing “computer-assisted academic advisement programs” that electronically track student records and align them with degree requirements. These programs fundamentally shifted the burden placed on advisors and improved advising experiences overall (Spencer et al. 1983). In the 1990s, universities began exploring “expert advising systems,” computers which mimic the reasoning behavior of a typical human academic advisor. Expert advising systems provide students advisement opportunities anywhere, anytime, while offering more consistent guidance to students than human advisors (Wehrs 1992). Moving into the twenty-first century, these tools have become more commonplace along with email and telephone, yet there is minimal adoption of newer tools such as mobile technologies into academic advising practices (Steele 2016).

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In this chapter, the authors provide an illustrative case how advisors can use new technologies to reimagine academic advising. The authors share how The Graduation Game (TGG) was designed and implemented as a mobile technology advising experience for incoming freshmen at Utah State University (USU). This mobile game introduces students to their advisor and other resources even before stepping foot on campus and provides students just-in-time advising information about graduation requirements throughout their academic career. The overall goal of TGG is to offer accessible advising experiences that build early connections between students and their advisors. Students’ perceptions of how TGG impacted their connection with their advisor and the implications TGG design has for transforming academic advising more broadly will be discussed.

2

Context

Advising in higher education can look different depending on the institution. In general, academic advisors are responsible for helping students decide which classes to take, providing information about registration (major progression, registration deadlines, add/drop dates), and helping students with personal and professional goals (Elizabeth 2009). To receive this help, students are typically required to make a face-to-face appointment with their advisor through an online portal or by calling the advising office. There can be multiple barriers for students when making an appointment such as having to find who to contact and then needing to fit an appointment into an existing schedule. This is where a mobile advising experience can help augment face-to-face meeting with an advisor, when students can access the app irrespective of their physical locations, thus breaking down these barriers (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Utilizing mobile technology in higher education advising has great potential, but there is still a need to realize this potential. Findings from the National Academic Advising Association (NACADA) survey show 55.95% never used smartphones in their academic advising practices and 68.97% never used mobile applications in their academic practices (Pasquini and Steele 2016). However, Gonzalez and Perez have begun to explore the space of using mobile technology to provide advising services to their students by creating an advising dashboard, which encourages students to take control of their advising experience by providing them with course suggestions and a course roadmap (Gonzalez and Perez 2015). In this chapter, the authors explore how mobile technologies can help achieve an active and “intrusive advising” system in higher education by making earlier and more meaningful connections with incoming students, which could lead to higher rates of students completing their degree (Muraskin and Lee 2004). The authors will share findings of the USU psychology department’s experiments with integrating an augmented reality mobile advising experience providing students the ability to walk around campus virtually before they arrive physically.

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Human-Centered Design

Human-centered design (HCD) was used as the main design approach to develop TGG. In HCD, the designer starts with the users, which in this case are the students. By first focusing on the students and exploring their needs and problems, this mobile advising experience is informed by the people who will eventually be using and benefiting from it (Norman 2013). Students have been the focus throughout the development of TGG, so the mobile advising experience is solving the problems for advisors and the students.

2.2

Situative Learning Approach

The design of TGG is grounded in a situative perspective of learning, outlining the significance of learning in context through practice and participation (Brown et al. 1989; Lave and Wenger 1991). Mobile games have emerged as useful tools for situating learning in authentic ways (Gee 2004; Squire 2006, 2011). Mobile technologies bring learning opportunities to people who were previously unreachable because of their location or circumstance. Mobile learning is not a single, solitary, identified activity, but an experience is woven into our everyday activities (Traxler 2011) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). TGG leverages the affordances of mobile technologies by situating learning via augmented reality on a mobile device and making this experience more accessible to students at a distance (see ▶ Chap. 77, “Augmented Reality in Education”).

2.3

ARIS

To create TGG, the authors used augmented reality interactive storytelling (Holden et al. 2014), a platform to create mobile, location-based games and experiences. The ARIS platform has been used in both K-12 and higher education contexts to engage the learner with a place while learning (Dikkers et al. 2012; Holden et al. 2015). For example, designers of learning contexts have used ARIS for a range of goals including second language learning, historical thinking, ecological participation, and science education (Holden and Sykes 2012; Mathews and Squire 2009; Wagler and Mathews 2012; Bressler 2014; Gottlieb 2016; Bressler and Bodzin 2016). This location-based functionality works well with the type of information academic advisors have for their students.

2.4

The Graduation Game (TGG)

TGG was designed to (1) acquaint students with the institution (USU) and the psychology department’s program requirements and (2) form connection between students and their academic advisor. TGG aims to provide just-in-time resources for

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incoming students and a more personal and meaningful initial connection with their advisor. It provides the benefit of working (virtually) with an advisor in planning their coursework. The entire game experience was designed for USU, with the actual courses and the faculty members who teach them to mimic the real-life experience in graduating with the bachelors in psychology from USU. Players are presented with all the courses (situated on a map of USU’s Logan campus) they would need to complete during their freshman year. They can then click on each course and interact with information about the course through text and/or videos. After completing each course, an icon will disappear from the map, and the player will earn credits toward their degree. The goal of the game is for a player to complete all coursework for their freshman year. Since the initial target audience was incoming freshmen, the authors narrowed the scope of the game to cover the first academic year in USU’s psychology degree program with the option of expanding the game in the future.

3

Game Development and Design

Considering the cognitive overload students’ typically experience on orientation day, the first author explored designs to make the important information provided on that day more accessible and digestible. Below is the design story including every iteration of TGG and the way it evolved from a low-fidelity paper prototype to high-fidelity mobile application.

3.1

Iterations of the Graduation Game (TGG) and Player Feedback

3.1.1 First Phase: Idea Generation and Decision-Making The initial aim for the game was to have reachable goals en route to “graduation” to inform students of the nuances of degree requirements for the psychology program and provide a connection to their advisor and departmental faculty. The first step was to examine the degree requirements and explore different ways to separate them into a game. The authors attempted several paper prototypes. First, a monopoly-type board was developed, but it did not allow for differences in the successive trips around the board, which is required for each academic year of graduation. Then, wandering path was created with a graduation plaque at the end, but this paper design did not allow for achieving goals along the way. With these prototypes, it became evident the game should distinguish between the different types of courses (e.g., general education, major, minor, etc.) and provide a way to collect credits along the way (Figs. 1 and 2). Using spreadsheets, campus maps, and a working knowledge of the academic and campus data, two key design decisions were met. First, the game location would be the main campus of USU at Logan rather than drawing on fictional themes or narratives such as a treasure hunt or theme park. Second, ARIS affords both

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Fig. 1 Theme ideas and map

location-dependent (i.e., must be played in the specific physical location at all times) and location-independent options. Since the first advising contact with students happens through email, the authors opted to make TGG location independent so students can visit campus locations virtually. It was expected these decisions would better support students to connect their gameplay with their real-world context. Taking the psychology department’s current graduation requirements into consideration, we made TGG’s requirements as follows: Credits required to finish TGG (graduate) Credits from the major Credits from the minor Credits from general education Credits from electives

120 48 12 33 27

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Fig. 2 Theme ideas and map

To “graduate” in 4 years, students must complete 30 credits per year. The traditional class rankings of freshman, sophomore, junior, and senior are achieved after earning 30 more credits: 0–30 = freshman, 31–60 = sophomore, 61–90 = junior, and 91–120 = senior. In the game, we equate each ranking with a new game level unlocking new requirements as well as new course options. The game is designed to follow these guidelines and help students become familiar with the system they will be following in their academic careers. Freshman Year: Students will complete ten three-credit courses to complete this level. Freshman year will include beginning major coursework (General Psychology, Lifespan Development, Analysis of Behavior and Lab, Orientation to Psychology). Students will begin their general education requirements (English 1010, Stat 1040, Creative Arts, Life Science, Humanities). After successful completion of this year, students will be allowed to continue to the next year with sophomore standing. Sophomore Year: This level sees students beginning to explore with a minor exploration course and an elective course added to the general education and

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major courses. Major courses in this level are (Psychological Statistics and Abnormal Psychology). General requirement courses in this level are English 2010, Physical Science, American Institution, Social Science, Depth Humanities and Arts. Junior Year: Junior year sees students getting more involved in their minor coursework, with two minor courses included. They will explore more elective courses, three in all. Major coursework in this level are (Research Methods, Tests and Measurement, Neuroscience/Sensation and Perception, Advanced Analysis of Behavior/Cognitive Psychology, Psychology of Gender/Multicultural Psychology. Senior Year: Senior year will complete the major requirements (Social Psychology/ Personality Theory, two Psychology Specialization courses, Undergraduate Apprenticeship). The minor requirements will be completed with two minor courses. Two remaining elective courses and two remaining general courses will round out the credits at 120. A student as a player “takes a course” in the game, by selecting it, learning about the course, and responding to relevant questions. Each course provides information about its curriculum and the prerequisites, and a player must answer a yes/no or true/ false question. If the player answers the question correctly, she/he will earn credit for the course and will be able to move on to another course. If the player answers the question incorrectly, she/he will be shown the correct response.

3.1.2 Second Phase: Low-Fidelity Paper Prototype In the first paper prototype of the game, players are greeted by their advisor and are given some preliminary guidelines for playing the game. Players then are asked to choose the type of student: first generation, nontraditional, traditional, or high achiever. A first-generation student is a student whose parents did not attend college. A nontraditional student is a student older than a traditional college student or the one entering college after a delay—not straight out of high school. A traditional student is one who graduated from high school up to 1 year ago. A high achiever student is a student with transfer work, advanced placement course(s), and/or concurrent enrollment credits. The game then progresses on the basis of the student type. Afterplay testing this iteration with students, advisors, and faculty, the authors realized tracking students in the game resulted in confusing or ambiguous gameplay and reinforced certain higher education equity issues. Therefore, tracking was removed from the game. 3.1.3

Third Phase: Medium-Fidelity PowerPoint Prototype and Player Testing The authors created a medium-fidelity version of TGG on Microsoft PowerPoint. This digital prototype of the game allowed the game to be shared electronically through email and play test with a wider audience. Slides were created for the freshmen courses providing a brief introduction for each course (see Fig. 3). With

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Fig. 3 Screenshots from the PowerPoint version of TGG

this medium, the authors were not able to ask players questions or record their earned credits, which limited the scope of the prototype. Before this prototype development, the authors planned to use grades and overall GPA to determine players’ progress through the game. The technological limitations of PowerPoint revealed too much complexity using GPA as a metric, a much more complex formula which was needed to calculate the number of right and wrong answers and number of times each course was “taken.” It was decided to use the number of earned credits to measure the players’ success in the game. The authors play tested this version of the game with some of their personal contacts including family members and coworkers they contacted through email or in-person. Two of the students who play tested the game suggested using more graphics and videos to make the game more engaging, instead of relying on text. These suggestions were used to inform TGG’s current design, and confirmed by the survey results, video clips are the preferred type of interaction in the game. One of the play testers asked the authors to ensure introductory courses such as Psychology 1010 are listed as a prerequisite for all psychology courses. These nuanced requirements are important for students to understand as they register for courses and prepare their academic schedules. Such a requirement could be easily added into more sophisticated high-fidelity prototype using another platform (i.e., ARIS). Feedback from the other two play testers indicated the questions were appropriate and the concept of The Graduation Game is fantastic.

3.1.4 Fourth Phase: High-Fidelity ARIS Prototype and Player Testing To make TGG a mobile app, the authors explored different available mobile game platforms such as ARIS, Siftr, TaleBlazer, App Inventor, etc. ARIS was chosen for TGG because it allows both location-dependent and location-independent experiences and offers a range of training materials and tutorials to support non-programmers in their design and development. The training materials on the ARIS website were used, and the authors solicited assistance from other ARIS users to develop the experience as a single scene with several interactions and quests for each academic year. Similar to the first paper prototype, players are greeted by their advisor at the first scene, where she explains the rules and goals of the game.

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Advisor: “Hi there! I’ve been waiting to meet you. Are you ready to play the graduation game?” Student: “No” = Exit Game or “Yes” = Let’s get started. Advisor: “Great! This game is going to help you understand your requirements and give you an overview of what is required to earn a Bachelor’s degree in Psychology from Utah State University. The game is made up of four quests – freshman, sophomore, junior, and senior. You will earn three credits for each class you pass. You will need to earn 30 credits per quest to move on to the next quest and to have enough credits to graduate at the end of your senior year. Each class will teach you a little about the courses you will be taking as part of your degree. After each class review, you will be asked a true or false question to determine if you “pass” the course. You’ll also meet some different types of students along the way that can help you understand the university requirements better. Have fun!”

In this version of the game, the courses and years are separated into quests, one for each year. After play testing this version of game with students, advisors, and faculty, the authors decided to reorganize the goals of the game. The game was adapted to focus on the course requirements’ quests, which would span across in-game academic years, rather than class ranking, which would become separate levels. Specifically, the authors added four concurrent game quests: major, minor, general education, and electives. For example, if a player completes Psychology 1010 course, she/he will earn three credits toward his/her degree (120 credits are required to graduate) and earn three credits for the major (48 credits from the major are required to graduate). If the player takes another course, an elective, she/he will earn a total of six credits toward his/her degree and get three credits each in the major and the electives (see Fig. 4). With this new structure, players would progress through class ranking by tracking a total number of credits (30 credits per academic year) and meet specific degree program requirements for course types across major, minor, general education, and electives. The aim of the design decision is to teach students it is not just the number of earned credits allowing you to graduate but the type of credits and courses you completed. For early player testing of the ARIS version, the game was only for the first year and used the basic teaching material from previous iterations. After realizing the scale of the project, the authors decided to focus their development of TGG on freshmen year since their target audience are incoming freshmen.

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Implementation

4.1

The Graduation Game: Current Design

For implementation, the authors concentrated their development of TGG on completing the freshmen year and improving the app for a more engaging experience for incoming freshmen. To make the game experience more recognizable and connected to the identity of USU, more media was integrated. Icons were prepared for the game using the iconic Old Main building, the first building built on the USU Logan

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Fig. 4 Student’s progress toward his/her graduation

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Fig. 5 Program Icon for TGG

campus (see Fig. 5). Second, photos of the buildings were added, where the course is located on campus (see Fig. 7). The authors partnered with the faculty to add courserelated media for each course and recorded video clips of all first-level psychology courses being introduced by the professors who teach the course. The professors enjoyed the experience and developed their own dialog for their course. This made each clip unique focusing on diverse course information. The questions varied to make the game more engaging. Initially players view the image of Old Main building when they enter the game (see Fig. 6). They then are instructed to locate and select the “advisor greeting” on the map. This is the beginning of the game. Players are then prompted to continue to the advisor greeting screen, which explains the process for choosing classes. After completing the advisor greeting, players select any of the course icons located on the campus map and proceed with their courses. Once they select a course, they are prompted to read informational text followed by true/false questions or video clips. After answering a question correctly, players earn three degree credits and three credits in the specific area of the course, i.e., general education, psychology major, or elective. When a player does not answer the question correctly, she/he will have the option to retake the course. When the course is completed, its icon will disappear from the map. When the freshmen year is completed (30 overall credits), players will receive a freshman year certificate (see Fig. 8).

4.2

Collecting Evaluation Data

To collect players’ comments and feedback about the content and process of TGG, the authors created a Qualtrics evaluation survey. After 10 minutes of the game, players are prompted to either pick up or complete the survey. If they opt to pick up the survey, they can complete access it later. The survey’s goal is to capture players’

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Fig. 6 TGG home page

overall experience of the game and how they perceive their own comfort in contacting their advisor and doing course selection after playing the game. Aware not all players will complete the survey, the authors wanted to track the players of the game. The authors first attempted to monitor game play using the in-app metrics provided by ARIS, which tracks the popularity of the game. But this did not provide an accurate sense of who was playing the game. The authors added some JavaScript available on the ARIS forum to create a leaderboard to track who played the game. The leaderboard ranks players based on their earned credits as they work their way through the game.

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Fig. 7 Buildings for TGG

Fig. 8 TGG screenshots. (From left to right) TGG index, TGG map, TGG zoomed in map, and TGG leaderboard

4.3

Final Testing Before Distribution

Before making the game live to incoming freshmen, an additional round of play testing was completed. In this test, authors found several issues related to the media in the game. The game settings were improved so all the content is downloaded on the front end. Not only did this solve of the slow-loading graphics, but it allowed

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offline game play which takes significantly longer to download the game. Another issue arose when a play tester completed the entire freshmen level in less than the expected time and was not prompted to take the survey. The authors remedied this by setting the survey to appear after the participant completes 30 credits, eliminating a time requirement to complete the game. However, if the participant chose to delay completing the survey, a survey reminder will trigger every 120 seconds (2 minutes) after its initial introduction to the player.

4.4

Email Distribution

A series of email invitations to play TGG were sent to all the incoming pre-psychology major freshmen-level students who were slated to attend USU beginning in Fall 2017. In late March 2016, the authors invited 33 students in early April 2016. In mid-April 2016, another email invitation was sent to 30 new students (not included in previous invitations). A final invitation was sent to 67 (new) students. For a total of 172 email invitations, only five students completed TGG and responded to the survey. The authors realized access to and on-ramping to the ARIS platform can be limiting. For instance, one student replied to the email asking if the app could be downloaded on Android platform, but ARIS is iOS only. Another student mentioned it would be helpful if the user did not have to download a separate app and then have to set up an ARIS account to play TGG. Some students reported having difficulty accessing the survey. This was remedied by triggering the survey after completion of 21 credits (instead of 30), and if a student chose not to complete the survey, they will be reminded periodically the survey is waiting to be completed.

4.5

Orientation Distribution

Due to the low-response rate, the authors decided to use TGG during summer orientations with the incoming pre-psychology majors most of whom had already received the email invitation. Using the iPads from the computer lab in USU College of Education and Human Services, authors pre-installed the ARIS app on the iPads and created generic ARIS accounts for the students beforehand to minimize the on-ramping effort. Implementing TGG in this setting was more efficient for the authors to introduce the game and to observe any problems students faced while using the game. The first author conducted 11 orientation sessions with a total of 84 students. All the students who attended the orientation were presented with the game and the follow-up survey. The authors received 58 completed survey responses (response rate of nearly 70%). Some of the participants could not finish the game in the given time, so they did not reach the survey.

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Evaluative Feedback on TGG

The authors received 63 survey responses from both the email and orientation sessions. The survey responses provide a promising picture of the future for integrating mobile technologies in academic advising.

4.6.1 TGG Improved Comfort with USU Students were asked whether the authors met the goal in designing TGG, to make them feel more comfortable contacting their advisor. Most (80%) students reported TGG “definitely yes” or “probably yes” achieved this goal, which indicates a mobile app such as this one has potential to cultivate a connection between advisors and their students. Moreover, most (88.3%) students reported definitely or probably felt more comfortable navigating their course schedules after playing TGG. This suggests the mobile app may provide initial training to students to help them understand their program requirements toward graduation. 4.6.2 Game Design Tradeoffs All responders indicated they spent about 10 minutes playing the game through all of freshmen year. This indicates the mobile game approach appears to be a timeeffective method to deliver requirement information to students without an advisor needing to be present or use advising time to accomplish the task. When evaluating within game interactions, most (>50%) students ranked “video clips” as their first choice, followed by “true/false questions” and “text information, no follow-up.” These responses support play test feedback the authors received, players preferred videos as their primary form of interaction, and some students still requested more variety in question and interaction types. 4.6.3 Improving and Expanding the Game About 71% of students expressed at least moderate interest in completing all levels (i.e., sophomore, junior, and senior years), which suggests it may be worthwhile to complete the game to graduation. In open-ended responses, students offered recommendations such as adding subtitles to videos, providing headphones for gameplay, and diversifying interactions with more decision-making outcomes. Moreover, students expressed interest to know more about the professors including contact information and more information for each course. Two students requested advisors to provide recommendations for course sequencing.

4.7

Designing Mobile Technology for Academic Advising in Higher Education

In this section, the authors will discuss the technical considerations encountered during the design of TGG, the lessons learned from the game development process, and the process and importance of data collection.

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4.7.1 Technical Considerations When designing TGG on ARIS, several technical considerations were encountered that inform future iterations of TGG as well as other design of mobile technology for advising. Since ARIS games can only be played on iOS devices, TGG is limited to iOS. While this was a design decision the authors made for this context, it brings up key issues of access and equity in implementing mobile technologies in diverse contexts, which should be considered by designers early in the development process. To play an ARIS game, the player must download the app and create a login, requiring significantly more time and can be a barrier to entry. It was found integrating the game play into student orientations is an effective short-term solution; however, this would not be suitable for distance or online students who may never come to campus. For broader implementations, these particular technical considerations including requiring a mobile device at all are significant obstacles to ensure equitable access and on-ramping.

4.7.2 Lessons Learned Findings indicate TGG is a promising start for exploring new approaches for establishing early, meaningful connections between students and advisors. Students not only preferred videos of advisors and professors as a virtual introduction but desired more interaction and decision-making to make the game more engaging. This design story provides important context for distribution, and students were much more responsive to orientation distribution rather than email. Though a goal was to engage students as early as possible, the authors encountered a new design challenge for reaching students before orientation. In future iterations, the authors will further explore approaches to connect with students earlier, which is especially relevant to the distance and online students.

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Future Direction

Academic advising plays a critical role in how a student feels about their school and whether the student decides to persevere through their educational career. Implementing mobile experiences, like The Graduation Game, can potentially assist academic advisors by providing unique ways to build relationships with students and to make early contact with a large number of incoming students. By beginning the exploration of where academic advising and mobile technologies intersect, authors are only beginning the investigation of how and if mobile experiences like TGG can be effective tools for academic advisors to increase student retention helpful for academic advising. In the future, authors expect to extend TGG for graduate students as well.

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Cross-References

▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning

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Pasquini, L. A., and Steele, G. E. (2016). Technology in academic advising: Perceptions and practices in higher education. NACADA Technology in Advising Commission Sponsored Survey 2013. Spencer, Robert W., E.D. Peterson, and G.L. Kramer. 1983. Designing and implementing a computer-assisted academic advisement program. Journal of College Student Personnel 24 (6): 513–518. Squire, Kurt. 2006. From content to context: Videogames as designed experience. Educational Researcher 35 (8): 19–29. https://doi.org/10.3102/0013189X035008019. Squire, Kurt. 2011. Video games and learning: Teaching and participatory culture in the digital age. Technology, education–connections. New York: Teachers College Press https://eric.ed. gov/?id=ED523599. Steele, George. 2016. Technology and academic advising. In Beyond foundations: Developing as a master academic advisor, 305–326. Hoboken: Jossey-Bass http://www.wiley.com/WileyCDA/ WileyTitle/productCd-1118922891.html. Traxler, John. 2011. Learning in a mobile age, a more and more mobile age, 15–27. https://doi.org/ 10.4018/978-1-60960-481-3.ch002. Vianden, Jörg, and Patrick J. Barlow. 2015. Strengthen the bond: Relationships between academic advising quality and undergraduate student loyalty. NACADA Journal 35 (2): 15–27. https://doi. org/10.12930/NACADA-15-026. Wagler, Mark, and Jim Mathews. 2012. Up river: Place, ethnography, and design in the St. Louis River estuary. In Mobile media learning. Pittsburgh: ETC Press http://press.etc.cmu.edu/con tent/river-place-ethnography-and-design-st-louis-river-estuary. Wehrs, William E. 1992. Using an expert system to support academic advising. Journal of Research on Computing in Education 24 (4): 545–562.

Learning from Social Impact Games to Support Integration into Middle School Classrooms

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Renee E. Jackson and Emily Sheepy

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Theoretical Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Get Water! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Gameplay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Metagame Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Youth Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Instructional Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A:Youth Studies Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Section A: Interests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Section B: Video Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Section C: Get Water! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Video games known interchangeably as social justice, social impact, or social change games hold great potential for integration into classroom learning. They are promising particularly because they tend to be easy to play, are free or inexpensive, and, given that they address social justice-related issues in various R. E. Jackson (*) Temple University, Philadelphia, PA, USA e-mail: [email protected] E. Sheepy Concordia University, Montréal, Canada e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_117

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ways, can be more easily integrated with curricular goals for teachers who may not have much gaming experience. Drawing from two qualitative research projects, with female youth ages 11–14 (n = 74; n = 11), and centered around one particular game, Get Water!, guidelines are considered for game design intended for classroom use and informal learning, approaches toward assessment of learning, and suggestions for effective instructional practice. With girls at the middle school level in particular, building relationships with video games is important, as video games are considered by many scholars to be one way of developing or maintaining an interest and comfort with technology at a young age, in a world where technology and video game domains continue to be dominated by men. Informed by studies with girls, the purpose of this qualitative synthesis is to reflect on strategies for integrating casual games that can be played and understood reasonably quickly in learning contexts, yet are also in line with student-centered learning and goals related to the twenty-first-century learning trend, such as critical thinking, creativity, and collaboration.

1

Introduction

Social impact games intended to “serve as critical tools in humanitarian and educational efforts” (Games for Change Conference n.d.) have a potential role to play in classroom education. Within the broader area of game-based learning in the social sciences or related to social justice issues (as social justice issues are of concern across disciplinary boundaries), this chapter addresses the educational potential of social impact games – video games that are designed to increase awareness of important social and political processes and problems. Many of these games relate to social justice issues broadly defined as issues interfering with the distribution of wealth, opportunities, privileges, and safety. Social impact games, also referred to as social change games (SCG) (Whitson and Dormann 2011), form a smaller category of games within the broader serious games category, commonly defined according to Micheal and Chen (2006) as: “games in which education in its various forms is the primary goal, rather than entertainment.” Games for Change is a large-scale movement in support of social impact games, with a yearly conference that takes place in New York. The website partially functions as a game and related resource receptacle. As a general rule, most of the games are free or inexpensive to purchase, and similar to what are known as “casual games,” social impact games are quite accessible in terms of gaming skill required to play – a person who may not have much experience with gaming can generally play the games. The release of a MacArthur Foundation report, The Civic Potential of Video Games (Kahne et al. 2009), demonstrated a relationship between playing games which were high in civic content (i.e., which dealt with social/political processes) and positive citizenship outcomes such as political knowledge and volunteerism. Though there is not a lot of research demonstrating the impact of video games related to such positive change, this study provided some motivating evidence in this

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direction. Games are promising social educational tools (Squire 2011; Gee 2003). Kurt Squire (2004), for example, used Civilization III in a history class and found that the game was both engaging for students and supported development of complex skills related to civic learning, such as power negotiation and the capacity to understand history for various perspectives. James Gee (2003) has argued that good video games provide strong learning environments where players have agency, are able to take risks, and engage many complex learning skills including systems thinking. Yet teachers face persistent barriers when it comes to integrating gaming into the classroom. Challenges include difficulty finding games that are aligned with curricular goals, irrelevant content in commercial games, and demonstrating value to other stakeholders (Sheepy and Jackson 2015). Scholarly arguments advocating for the power of video games as learning tools (see Gee 2003; Squire 2011) typically revolve around complex, highly involved simulation games such as Civilization. Given the time constraints of the classroom and the challenge teachers face both vetting and understanding the direct connections between particular games and curriculum, simpler games related to social justice issues hold great promise for classroom use. In terms of time commitment and complexity, games like Get Water!, the primary subject of this chapter, are easier to integrate into everyday classroom activities and are more easily integrated into the daily lives of adult players as a facilitator of informal learning. Much research has taken place in relation to serious games more broadly (Connolly et al. 2012; Ma et al. 2011), where very little work has taken place in relation to the more specific category of social impact games (Dasgupta et al. 2012; Dahya 2008), particularly in relation to classroom integration. Though these games are made with the intention of enabling social change, research has yet to demonstrate that they have an impact in this way, and many game scholars remain skeptical (Whitson and Dormann 2011). Research related directly to the social impact of Get Water! has indicated that the game does not lead to substantial social impact. However, an unintended consequence of this research has led to a hypothesis that the use of social impact games in learning contexts can enable a symbiotic situation beneficial to both social change and student engagement. The capacity of the video game Get Water!, as a catalyst for social change, can be enhanced through the right pedagogical tactics. And student engagement can be enhanced in classrooms through gameplay. The larger question is whether or not relatively simple and largely narrative-driven casual games can be equally as successful at engaging students in social justice content and themes and providing meaningful learning opportunities. Accordingly, game-based education researchers have a role in exploring how learners benefit from social impact games and in establishing guidelines for effective instructional practice, assessment of learning, and game design. These three categories to research findings are applied below in order to further support integration of games into a classroom context. The strategies for integration are informed by research with girls ages 11–14, because listening to their responses to games will help to develop their relationships with video games. Video games are considered by many scholars to be one way of building an interest and comfort with technology at a young age (Walkerdine 2007; Harvey 2011; Baytak and Land 2011). Technology and video game domains

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continue to be dominated by men (Jenson et al. 2007, 2011). Misogynistic behaviors and attitudes continue to pervade (Delamere and Shaw 2008; Kain 2014). Offering learning opportunities related to this domain, in ways that work for girls, is needed. Balancing out the gender domination in the world of technology begins by offering opportunities for girls to work with technology in schools in a variety of ways from a young age.

1.1

Objectives

Drawing from a research project with female youth, related to one particular social impact game, Get Water!, guidelines are considered for game design intended for classroom use and informal learning, approaches toward assessment of learning, and suggestions for effective instructional practice. The purpose of this qualitative synthesis is to reflect on strategies for integrating casual games that can be played and understood reasonably quickly in learning contexts.

1.2

Theoretical Framework

Current recommendations for social science teaching and learning, including the National Council for the Social Studies standards (2010) and the twenty-first-century learning framework (P21 2011), emphasize the importance of social science curricula in promoting civic competence, enabling learners to apply their awareness of global issues, systems, and cultures in problem-solving and collaborative work (P21 2011). The twenty-first-century learning framework also promotes meaningful use of technology in the classroom (P21 2011). Though twenty-first-century learning can easily be considered a trend or fad within education, consideration is nevertheless important given that curricula have been evolving in this direction across North America (Brown n.d.; Boudreault et al. 2013; C21 Canada 2015; Education Sector Reports 2008; Knox 2006; Nehring and Szczesiul 2015; Newswire 2003; Pearlman 2006; Premier Technology Council (PTC) 2010; Salpeter 2008; Schwartz and Stolow 2006; Wilson 2006). Though twenty-first-century learning is a reasonably new term, it is situated in a progressive learning approach which places students at the center of learning (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Progressive education was popularized by John Dewey (1916, 1990, 1998) at the turn of the last century, yet, for a multitude of reasons, has never fully been integrated into mainstream education in North America. This pedagogical paradigm comes from a constructivist perspective where it is understood that people construct their own knowledge and that this happens primarily through hands-on, discussion-based learning situations, where students’ perspectives are taken seriously. Students are understood as having knowledge and skills that they bring to the learning situation in contrast to more traditional learning situations where the teacher is seen as the epitome of knowledge. Whereas learning in a traditional context is largely based on rote learning and memorization, and can easily be evaluated through testing, learning in a progressive context is more complex.

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Learning in this sense is based on the accomplishment of tasks involving collaboration, problem-solving (where there are multiple approaches to solving a problem and multiple answers), communication, creativity, and critical thinking. There are many definitions and positions related to twenty-first-century learning, most refer to these capacities (Romero et al. 2015). The research findings discussed in this chapter are situated in a progressive learning framework so as to inform student-centered learning which is aligned with the shift in curriculum toward twenty-first-century learning. Civic education is considered a “fundamental subject” within the twenty-firstcentury learning framework (P21 2011); however, civic education research and practice are contested areas; various syntheses of civic education goals and competency models have revealed a multiplicity of perspectives on what types of content and practices are endorsed (Brammer et al. 2012; Carnegie and CIRCLE 2003; Schulz et al. 2016). The critical citizenship education paradigm in civic education in particular emphasizes the promotion of a supranational common set of shared values such as tolerance, diversity, human rights, and democracy, as well as critical reflection on the past and future of social justice in diverse societies (Nussbaum 2002; Costandius et al. 2015; Johnson and Morris 2010). The primacy of such social justice values in the critical approaches to civic education contrasts somewhat from the aims of the development of the informed participant in democratic processes, where it is understood that citizens have a basic understanding of their political system, as well as an understanding of their own evolving interests and opinions and of the importance of collective deliberation and consent, prized within the American school of civic education and exemplified by Dewey’s work (Niemi and Junn 2005). Civic education curricula can serve to reproduce and enforce the agency of existing political structures in both what content is taught and how it is delivered (Kahne and Sporte 2008). Social impact games have the potential to play an important role in the development of the informed participant in democratic processes by enabling players to explore issues of global and public concern. These games are made with the intention of driving change in the world through the questioning and understanding social justice issues that exist as a result of political structures. Like any media, video games can reinforce and reproduce hegemonic structures, but they can also poke holes in such systems, enabling change: As markers of their times—the social, political, cultural and historical products that they are—digital games are well-positioned to allow insight into dominant ideologies as well as to provide the occasional space for challenging those ideologies. (Consalvo 2003, p. 8)

Social impact games, championed by the Games for Change movement, are curated and accessible through the website (http://www.gamesforchange.org/). The purpose of the movement is explained in the “about” section of the website: Founded in 2004, Games for Change empowers game creators and social innovators to drive real-world change using games that help people to learn, improve their communities, and contribute to make the world a better place. (Games for change n.d., retrieved March 6, 2018 from http://www.gamesforchange.org/who-we-are/)

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This positions such games as playing a promising role in civic education where the primary focus is engaged citizenry, but research in support of the classroom integration of social impact games is necessary.

2

Method

This qualitative synthesis draws together researcher experiences of two similar studies with youth who played the mobile game Get Water!. Relevant information from the data is culled to provide strategies toward assessment of learning and effective instructional practice, as well as initial reflections regarding guidelines for game design. The following is a list of instruments used for data collection (see “Appendices for Examples of Instrumentation”): • • • • • •

Post gameplay open-ended questionnaire Post gameplay structured questionnaire Follow-up questionnaire (2 weeks) Informal conversational interviews Focus group interviews and discussion Triangulation through correspondence with parents

3

Data Sources

The investigations drawn upon include two qualitative case studies about the mobile video game Get Water! conducted with adolescent girls (n = 74 and n = 11) in classroom environments using think-aloud procedures, observations, post gameplay open-ended responses, questionnaires, and focus group data. Below, we present a brief summary of the video game Get Water! and the studies conducted.

3.1

Get Water!

Get Water! (Decode Global 2012), until recently available through Sylvan play at http://www.sylvanlearning.com/resources/sylvanplay, is a water scarcitythemed casual game developed for mobile devices. The game was available for iOS, Android, and Windows devices. It was conceived through an industryuniversity partnership by a team of student interns and completed by industry professionals. The project was one of five winners of the 2012 Create United Nationals Alliance of Civilizations (UNAOC) Challenge in 2012 and received the “Power 2 Women!” World Summit Youth Award in 2013, an award supporting projects that target the United Nations Millennium Development Goals.

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Gameplay

Get Water! is a side-scrolling endless runner game. The protagonist, Maya, constantly moves horizontally through a 2D landscape, collecting water and other items and avoiding obstacles. The player guides Maya’s movements using their device’s touchscreen, drawing beneath her feet on the touchscreen with a finger. The game has evolved over time; our original research was conducted using version 1.0. Differences between versions 1.0 and 1.7, the current version, will be highlighted in this description. A brief animated vignette uses imagery without dialog to introduce Maya, an Indian girl approximately 12 years old. She is shown sitting with peers at desks in a classroom. A woman (Maya’s mother) appears in the door of the classroom. A speech bubble above the woman’s head presents a series of graphics that communicates Maya’s mother’s message: the water pump has broken, and Maya must leave to collect water. A brief tutorial demonstrating how to control Maya’s movements, after which Maya is shown standing outside of the schoolhouse, is ready to run. Maya’s exact location is never specified within the game itself, but the marketing materials for the game place Maya in India. Early versions of the game featured just one background depicting a slum area in India, with a developed urban area visible in the distance. The most recent version of the game also includes two additional backgrounds: one a rural area, with lush trees and bushes, and the other depicting ancient-looking ruins. The player’s aim is to accumulate target amounts of water as Maya runs and to collect special items such as mangoes for additional points. In the current version of the game, Maya can also collect jerrycans for bonus drops. The jerrycan is the symbol for the organization Charity: Water, which partnered with Decode Global in 2013 (Darabian 2013). The player must avoid various obstacles in the environment; if she hits an obstacle, her water vase breaks, and she returns to the beginning of the course to begin again. The obstacles include turtles that trip her, bouncing balls, peacocks, and monkeys that can damage her vase. If Maya collects dirty water (shown as red water drops), those droplets are subtracted from her collection. Maya can fend off peacocks and monkeys using a boomerang; the player launches a boomerang by tapping the screen. Throughout the game, special assignments or challenges are presented on a billboard where she begins running. These assignments run a certain distance without jumping or gathering a target number of mangoes. When these tasks are accomplished, Maya receives bonus drops at the end of her run (Fig. 1). There are ten “chapters” in total, which are brief animated storylets depicting events in Maya’s life. These chapters are unlocked to reward players as they accumulate target amounts of water. Each chapter comprises a vignette in which Maya figures out a new ability or “power-up” (Fig. 2). Power-ups appear as equippable items and are logged on a page displayed at the beginning of each run that describes the function of each skill and supply. These power-ups vary in terms of their relevance to real-world water gathering

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Fig. 1 Get Water! Water collection (Decode Global 2017)

Fig. 2 Get Water! Ten chapters (Decode Global 2017)

requirements; for example, in Chap. 3, Maya learns to jump over turtles to avoid breaking her vase, while in in Chap. 4, she learns to use a water filter that allows her to collect dirty water droplets without damage. In version 1.0 of Get Water!, Maya earned pencils that the player could exchange for power-up. This reward system was simplified in later versions of the game so that the special skills and supplies are automatically unlocked when the player completes chapters. Maya can use two skills and one supply per run, adding an element of resource management to the gameplay.

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Fig. 3 Get Water! Temple scene (Decode Global 2017)

Once the player has unlocked the tenth and final chapter, the player can continue to play the game but will acquire no more additional power-ups (Fig. 3).

3.3

Metagame Content

Much of the educational content of Get Water! is presented outside of gameplay, in what we call the “metagame” experience. This content includes both persuasive or value-laden messaging as well as factual information. Version 1.0 of the game presented quotes submitted by people of all ages from around the world, who shared their opinions about the importance of water and education. These quotes were presented to the player at the end of each run. The new iteration of the game still presents player-submitted quotes, but also includes quick facts about water scarcity, for example, “1 in 9 people are affected by water scarcity,” as well as tips about water and water conservation, for example, “Wash fruits and veggies in a bowl instead of running water from the tap.” In the new version of the game, there is an option on the main page to “learn more” on the main screen that Maya returns to after each run. If the player clicks on this icon, Maya’s teacher points to a bulletin board with three categories: “Why is water important?”; “Get involved”; and “About us.” Selecting “Why is water important?” invites player to share thoughts with Decode Global about the importance of water. “Get involved” invites players to organize a school campaign with Charity: Water and invites the player to learn more through their website. The “Get involved” page also has an icon that plays another animated vignette that tells the story about how Maya learned about Charity: Water. This aspect of the game application did not exist in any form in the original version.

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The game also had a Facebook community page as part of the metagame experience. Decode Global staff actively posted items of interest associated with global water issues and girls’ education, including articles, videos, and links to active campaigns. The game’s website (http://getwatergame.com) featured supplementary learning materials and weblog posts about recent projects and events.

3.4

Youth Studies

Jackson investigated learning with this game with a sample 85 girls from grades 6 to 8 (see Sheepy and Jackson 2015). The two case studies with young players were motivated by the ubiquity of this form of media: in 2015, global video game market revenue was in excess of $100 billion and recent estimates indicate that US children aged 13 years and older spend more than 6 h a week playing video games of various genres (Nielson 2014). This form of media arguably has the potential to influence more than others due to the interactive nature of the experience. The use of games in various ways within the classroom can enable critical engagement not only with game content, but with considerations of the medium itself and its role in our everyday lives. Just as it is important to critically consider more traditional media like books and films, it remains important to question the influence of video games on our perceptions about issues in ways unique to the medium itself. In the youth sample, the original intention of the research was to investigate the social impact of the game. Social impact was defined by the effect the game had on the players in terms of discussing the issue with others, being compelled to learn more by looking into the issue on a deeper level or by changing related behaviors such as deciding not to let the water run longer than necessary. Impact was assessed through open-ended responses immediately after gameplay, in order to provide insight into the immediate details about the game that struck the players. “Openended” in this context means without specific directions from the researcher beyond: “please share any reaction/response to the game on this page, in any way you would like. Feel free to write in any style, or to draw” (see Appendix A). This was followed by a more detailed questionnaire that addressed the general interests of the players in their everyday lives, their previous gameplay experience, their opinion of the game, their understanding of the game subject, and their thoughts about whether they may discuss the game or whether they were interested in knowing any more information related to the game. A questionnaire was also distributed 2 weeks after gameplay where participants were directly asked whether they played the game on their own time and about any actions or discussion that took place related to the game (see Appendix A for examples of the questionnaires). For the second sample group (n = 11), parents were also consulted to find out if participants discussed key issues at home. General responses to the game revealed that most students found the gameplay itself to be both “fun” (most popular descriptor word from the open-ended responses from both research groups, the word appears 38 times) and “addicting” (second most popular descriptor appearing 22 times), but few participants primarily viewed their

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gameplay experience as informative, though there were 16 comments overall that referred to the main theme in some way. Eleven of these comments came from one of the two grade 8 classes. This class of 17, as a group, was more reflective in various ways than the rest of the participants. This was evident not only through the tendency of their descriptors to allude to the game theme but also through more nuanced class discussion and through longer, more complex responses to the questionnaires. Overall, the driving element of play and interest in the game for most of the participants was the act of using your finger to guide the protagonist through the air to gather drops of water and to fend off peacocks with a boomerang. The deeper intentions of the game, and the element that is important to social impact – to inform players that some families do not have access to clean water and that this situation has a detrimental effect on girl’s education – were understood by most participants, but played a minor role in terms of what they chose to write about when invited to openly respond to the game. The intention of the game is to spread awareness of these interconnected issues related to water. Impact of the game as defined by the three elements described above (discussing related issues, searching for further information, taking action) was not significant for these youth. Though this approach to impact proved to be weak at best, focus groups conducted with the participants after the final questionnaire was complete were fruitful in terms of revealing opportunities for social learning afforded through playing and discussing the game.

3.4.1 Mobile Games in the Classroom Video games and mobile video games are an increasingly popular media. Media literacy scholars consider video games to be one form of text among many, where texts range from novels and comic books to television, film, and social media (Jenkins 1997). Video game-based learning and literacy isn’t necessarily a mightier pedagogical tool than any other forms of media-based learning and literacy, though some have argued that they may have a stronger impact, given their interactive nature (Brown 2008; Leonard 2003; Jansz and Martis 2007) (see also ▶ Chap. 18, “Mobile Learning and Education: Synthesis of Open-Access Research”). Regardless, given the popularity of games and the likelihood that the industry will continue to grow and evolve throughout our lifetime, it is important to create space for them in curriculum providing various types of learning opportunities by developing the skills to question, and to critique and engage with them, given that they are a significant form of communication in contemporary society. Although further research into the strength of social impact mobile games as an embedded learning tool in classrooms for youth is necessary, based on experience with the game Get Water!, the following recommendations can be made as a starting point. It is imperative that instructional practice and assessment of youth learners’ interactions with the learning tool take into account the facilitative role of the investigator, teacher, or parent, as appropriate. Merely playing these games in class is not the panacea for social science learning. However, employing such games as contemporary learning tools or catalysts for learning, through which to spawn potentially profound conversation about issues related to social justice, and key details related game design itself, holds great potential. Elaboration on these ideas

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through the development of guidelines related to instructional practice and assessment and provision of some preliminary reflections related to social impact game design for use in the classroom are provided below.

3.5

Instructional Practice

Casual games like Get Water! can engage younger students in gameplay, but in terms of learning, the game alone is not enough. As indicated in the literature concerning more complex games (Squire 2004; Bourgonjon et al. 2013), the role of teachers is the key in terms of integration into the classroom using approaches that are most effective. This same notion seems to hold true at least for this mobile game. However, in a catch-22-type situation, it is simultaneously a challenge for teachers to integrate games because some teachers do not have experience with gaming, and whether they do or do not, it remains a challenge to find appropriate games and to connect them to curricular demands (Kirriemuir and McFarlane 2004; Takeuchi and Vaala 2014). It is also often a challenge to justify game use to parents (Kirriemuir and McFarlane 2004), and teachers prefer using short games that students can complete within a single class period (Takeuchi and Vaala 2014). Social impact games designed as casual games meet these needs, because they are easier and quicker to play and because it often does not take long to develop a sense of the main argument or perspective shared through the game (Sheepy and Jackson 2015). To overcome these challenges, it makes sense to address the role of Get Water! in a classroom context. The game was most effective as a catalyst for discussion about issues related to water shortages. One student made the connection to a family trip to Mexico, where she realized that water was not as accessible as what she was used to in Canada (student participant interviewed by Renee Jackson, focus group, at a Middle School in Toronto, May 5, 2014). Another participant, who was an outlier in terms of her response to the game, was disturbed by the game and, during a 15 min gameplay focus group, stopped playing after 5 min. To her, it seemed contradictory to create a game made with the intention of depicting a very serious issue (this was explained during the gameplay session and reiterated in her questionnaire). From the results of the questionnaire administered immediately after gameplay and prior to any discussion related to the game, it is clear that most students understood, through gameplay alone, that the game was about global water shortage (57/85 or 65%), with a smaller percentage demonstrating an understanding of the deeper connections to the fact that water shortages create a barrier between girls and education (13/85 or 15%). The rest provided vague answers (i.e., water or India), or indirectly related issues (i.e., “girls in poverty”), or left this section blank. Further discussion is therefore required to bring participants to a more nuanced understanding of water collection as a barrier to education for girls. The questionnaire responses were not as rich or compelling as the focus group discussions that took place post gameplay (girls at this age generally prefer talking over writing) (B. Alexander, personal communication, April 1, 2015). Learning and critical thinking came

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through most strongly in focus group discussions where students collectively developed their knowledge and understanding of the issues. One key way this more nuanced understanding surfaced was through a question associated with game design. Prompted by “how would you change the game?”, grade 6 students commented on the real-world implications of the necessity of getting water for a family. Relating to the situation of the protagonist, Maya, one student explained that if young girls were out getting water, the task would become scarier as nighttime approached. She went on to explain that she would change the game by increasing the number of obstacles as time passed (Note: these students played version 1.0 of the game; the current version now includes more obstacles the longer the player runs) and by changing the lighting so that the screen would gradually darken. Another suggestion was to create various versions of the game depicting the way water situations differ across the globe. This observation opened the door to discussions about equity: who has access to water and why? Game design-related questions and activities can provide engaging learning opportunities and support for more complex twenty-first-century learning skills such as critical thinking and reflection. Inviting students to reconsider the game from their own perspective within the context of this research was a powerful and engaging way of inviting students to reveal their understanding, compared to more traditional approaches such as tests (Salen et al. 2011), or in this case, questionnaire 2, where they were directly asked to answer the question: what was the game about? Further analysis of the types of questions, which seemed to work best in relation to more complex learning outcomes, leads to the definition of essential questions as described by McTighe and Wiggins (2013). Essential questions can be applied to any subject area and are open-ended, thought-provoking questions that require reflection and can be answered in various ways. Essential questions are generally revisited over time and involve a gradual uncovering of depth and richness related to a topic (McTighe and Wiggins 2013). Essential questions provide meaningful learning opportunities, as defined by Ausubel (1966), by providing students with the opportunity to relate to the knowledge learned and to transfer learning into contexts beyond the classroom (McTighe and Wiggins 2013). Essential questions can be a starting point to discussion (e.g., “How would you change the game?”), but can also be a powerful strategy for providing the opportunity for deeper reflection based on the direction students take (e.g., “Who has access to water and why?”). The use of both game design-based inquiry and essential questions supports student-centered learning where the teacher/facilitator creates space for the ideas and perspectives of students while also attending to their responses and guiding them toward deeper levels of understanding and critical thinking.

3.6

Assessment

Inviting students not only to imagine how they would change a game but also to actually provide opportunities for game design and creation, whether they be digital

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or analogue, is also a newer area of research in terms of assessment (Salen et al. 2011; Q2L 2009). The research with Get Water!, and the reimagining of the game by participants triggered by the question “how would you change the game?”, is a micro-demonstration of the way game design could enable significant opportunities for assessment of learning. One could not, for example, create a game about key repercussions of water shortage in a particular country without knowing something about the issue and context. Taking the seed of an idea from the participants themselves, imagine providing the opportunity for students to actually create a digital- or paper-based game about the water situation in another part of the world. This challenge confronts the student with the need to understand such a situation while simultaneously providing a meaningful learning opportunity as students would be creating an actual game to be played, experienced, and for that matter witnessed by others in the real world. Too often classroom-based assignments are made strictly for assessment purposes and lack a practical role in the real world. Game design also requires other important twenty-first-century learning skills such as creativity, problem-solving, collaboration, and critical thinking.

3.6.1 Guidelines for Design A brief comparison to a study about both Get Water! and another social impact game called Ayiti: The Cost of Life (Jackson and Mandrona 2018) is useful as a starting point for parsing out game design suggestions because these games differ greatly by design. Working with a separate focus group of six 11-year-old girls who played both games, by contrast, indicated that the simplicity of the game mechanics in Get Water! made a difference in terms of accessing the main ideas embodied within the game. Ayiti: The Cost of Life is about poverty and the related barriers that can interfere with health. Participants’ reflections about the issues were initially clouded because they were distracted by the fact that they couldn’t “beat” the game. Players start off with a family of five, and they can become ill and die rather quickly. The game was nicknamed by one of the participants as “the impossible game to beat,” and for the most part, this nickname replaced the actual name of the game throughout the focus group session. Although this fact merits discussion value given that it is intentionally hard to “beat,” just as it is hard to emerge from cycles of poverty, these players generally associated winning as the primary goal for video games. This habitual goal, without further probing, can easily trump any deeper implications of a game. At least in this small sample group of students, players’ focus on winning diverted their attention from the deeper meaning of the game. Because these players were distracted by how quickly they lost the game, the hope that players could gain insight into the meaning of the game as a result of gameplay alone was certainly futile. As students develop the understanding that games can serve purposes beyond entertainment, it will perhaps become easier to recognize or consider deeper meaning on their own. However, typically the role of the teacher/parent in the facilitation of learning though video games is important, at least at this age. This finding was

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echoed in a recent study involving 1080 students in 46 classrooms in 10 different school contexts, playing “typical educational games” (simple games with transmission-based educational goals). This research by Clark et al. (2016, 2017) emphasizes the potential for such games as a valuable addition to curriculum yet emphasizes the importance of the role of the teacher and of further research in support of game integration in the classroom. The ease of gameplay in relation to Get Water!, as well as the fact that it addresses only two main ideas through gameplay, however, did make it easier for players to access the main learning, compared to Ayiti: The Cost of Life. This suggests that simplicity of game design can make learning more accessible. Simplicity of game design also supports the teachers’ capacity to integrate games into lessons or everyday learning situations (though this is not to say that more complex games should never be used).

3.6.2 Future Direction Based on unexpected evidence gleaned from these social impact studies, a symbiotic partnership between pedagogical practice and social impact games holds great promise. The results were surprising in the sense that the social impact was not strong within the parameters of how it was defined within the research (post gameplay discussion, inquiry, and behavior change related to water (i.e., not letting the water run)); however, other types of impact were observed. A deeper understanding of the underlying issues related to the game was revealed through answers to a question inviting students to imagine how they would change the game. Rich reflections and critical analysis of the game emerged during focus group discussion, prompted by essential questions. Building from the ideas brought forth from the focus groups themselves, opportunities for game design and game creation for assessment purposes would be a strategy of interest. This approach could conceivably be enriched by expanding the notion into a full game design-based challenge (paper or digital). Though assessment with and through games is not a new idea (Salen et al. 2011; Ruffo-Tepper 2015; Q2L 2009), further research is necessary for guiding and supporting this approach. Finally, the simplicity of gameplay enabled students to engage immediately with the game and is also a strategy that seems to prevent the impediment of the primary messaging embedded within the game. By inviting opportunities to reflect on social justice-related issues from various perspectives, as well as opportunities to articulate knowledge and understanding through creative means, these strategies support aspects of twenty-first-century learning, placing the locus of learning within the students.

4

Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Mobile Learning and Education: Synthesis of Open-Access Research

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Appendix A:Youth Studies Instrumentation

Post Gameplay: Open Response 1 This response is anonymous so please feel free to be as open and honest as you can so that we can learn from you! (please don’t include your name ☺) When you are finished playing the game, please share any reaction/response to the game on this page, in any way you would like. Feel free to write in any style or to draw. There are no right or wrong answers. When you are finished with this, please let me know, and I will collect it and give you a small questionnaire to fill in. Post Gameplay: Questionnaire 2 This questionnaire is anonymous so please feel free to be as open and honest as you can so that we can learn from you! (please don’t include your name ☺).

Section A: Interests 1. Tell me something about yourself – what are your top 3 interests in life, and what kinds of things do you most enjoy doing in your spare time?

Section B: Video Games 1. Do you play video games? (please circle) Yes No 2. If so what games do you play? 3. What do you think of video games? (please circle one of the following)

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love them

they’re okay

neutral

don’t really like them

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hate them

Feel free to add any thoughts about why you like or dislike video games

Section C: Get Water! 1. What are your general thoughts about the game Get Water!?

2. Would you have played the game longer? Yes No 3. Will you play the game again? Yes No 4. Would you play the game voluntarily if you came across it on your own? Yes No Why or why not?

5. How much would you pay for the game? $0

$0.25–$1.00

$5–$10

$15–$25

6. Where and when do you imagine you might play the game? (you can say nowhere if you don’t imagine playing it again.)

7. What do you think the game is about?

8. Did you learn anything from the game that you didn’t know or think about before? Yes No If yes what did you learn? 9. Do you think you will discuss anything about the game with others, if so what do you imagine you might discuss and with whom?

10. Are you interested in learning more about anything related to the game, if so what and why?

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Follow-Up Questionnaire 3

Outside of Class 1. Did you play the game Get Water! outside of class? If so, how much time do you think you spent doing so? Circle the most appropriate answer. 10 m–30 m

45 m–1 hr

1 hr–2 hrs

2 hrs–5 hrs

5+hrs

2. Did you tell anybody about the game? If so who did you tell? Why did you tell them?

3. Did you have any discussions that you think are a result of playing the game Get Water!? If so, please describe.

4. Did you do anything new as a result of playing the game Get Water!? If so, please describe.

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Design Considerations for Mobile Learning

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Jason Haag and Peter Berking

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 What is Mobile? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 What is Mobile Learning (mLearning)? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Performance Support in Curriculum and Instructional Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Learner-Centered Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 The Sense of Touch and Mobile Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Device Capabilities and Affordances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Learning Theories and Conceptual Frameworks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 A Framework for M-Learning Design Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 The Framework for the Rational Analysis of Mobile Education (FRAME) Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Park’s Pedagogical Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 The M-COPE Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Mobile Training Implementation Framework (MoTIF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Create, Convert, or Capitalize? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

For good reasons, the instructional design practices for classroom environments and e-Learning have been largely limited to the cognitive domain. With the increasingly widespread adoption of mobile technology, a paradigm shift is taking place, offering new opportunities for improving performance and augmenting skills (in addition to knowledge transfer). But how is curriculum design and instructional design for mobile learning any different? Traditional J. Haag (*) · P. Berking The Mobile Learning Research Team Advanced Distributed Learning (ADL) Initiative, Alexandria, VA, USA e-mail: [email protected]; [email protected]; [email protected]; peter.berking. [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_61

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course offerings replaced with or augmented by mobile technology may actually follow many of the same instructional design frameworks or processes in alignment with the widely accepted phases of ADDIE (Analysis, Design, Develop, Implement, Evaluate). But what other types of m-Learning can or should be considered during design? What are the current gaps in design knowledge for educators, instructors, and instructional designers? The answer to these important questions requires a solid understanding of mobile device affordances as well as considerations from two key domains of research and practice: Learning Sciences and Human-Computer Interaction (HCI). This chapter will cover these considerations with the goal of helping readers establish an informed design strategy for m-Learning, rather than relying solely on prior instructional design experience.

1

Introduction

As with many past technological innovations, instructional designers and educators have quickly adopted mobile technology with the inevitable benefit of understanding its pedagogical merits. With the growing popularity of interactive apps, engaging touchscreen interaction, and immediate access, it’s no surprise that mobile technology has ascended as a top priority of many education and training programs around the world. The mobile device and app platform model has undoubtedly created new opportunities for improving education, training, and performance in formal learning settings but has also drastically changed the way many people work and live on a daily basis. Instructors, educators, and instructional designers are quickly adopting mobile technology in their learning environments, but strategic design considerations and proven pedagogical practices have not been systematically documented. This misfortune can be attributed to the lack of a universal acceptance of what types of devices are agreed to be “mobile” as well as what types of activities are commonly understood and accepted as “mobile learning (m-Learning).”

1.1

What is Mobile?

When a popular technology like mobile receives so much public attention, development teams often begin with focusing too narrowly on the technology itself, rather than the requirements or learning needs. Ideally, the learning outcome should be the primary driver for making design decisions. However, being familiar with the capabilities of the different types of handheld devices that learners use may also introduce new ideas and might even help to appropriately narrow the scope of a mobile learning initiative. For now, there is no right or wrong answer for what types of devices are considered to be truly “mobile” as perceptions and technology will continue to change and evolve. The focus should be on how mobile technology can add the most value to the learning context. If there are no obvious benefits or justification for using mobile technology to enhance learning or performance, then

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it is conceivable that a business case analysis or cost-benefit analysis could be pursued. A cost savings benefit could possibly serve as a secondary driver for designing and developing a mobile solution. Mobile device screen sizes as well as several other form factors collectively introduce many considerations and implications for a mobile learning design strategy. Think about the minimum sizes of text and graphics for various mobile-device sizes, preferences for touching or interacting with different device types, designing for keyboard use, dealing with loss of connectivity, screen glare, and behaviors of smartphone users vs. tablet users. All of these concerns may influence how organizations determine what devices they will include or exclude from their list of targeted mobile device types. While there are success stories that leverage basic features such as text messaging, today’s mobile devices that have a touchscreen and advanced hardware capabilities seem to offer the most potential for rich mobile learning experiences. In addition, smartphones and tablets are becoming so prevalent because they are typically more affordable and portable than laptop computers. A survey conducted by the Advanced Distributed Learning (ADL) Initiative in 2013 asked 831 respondents from the education and training community which mobile device they use most often for learning (Berking et al. 2013). The results heavily implied a focus on smartphones and tablets for mobile learning, with the highest responses reported at 61% for tablets and 29% for smartphones. The education and training communities both have internally mixed opinions on whether a laptop should qualify as a mobile device. Laptops were once considered too heavy and not small enough to be truly mobile. However, the recent convergence of laptops with tablets into a hybrid device by some manufacturers could make this concern even more difficult to address. For example, designing learning content for a tablet has much more in common with a laptop or desktop computer than it does for a smartphone. However, the individual usage of these devices is much different. There is also an increasing number of design implications related to hardware expansion capability differences between mobile devices as the market continues to evolve. Nonetheless, the purpose and scope of this chapter will be focused on smartphones and tablets as the preferred types of mobile devices used for mobile learning.

1.2

What is Mobile Learning (mLearning)?

The true potential of mobile learning (hereafter referred to as “mLearning”) should not be merely described as learning content delivered or accessed on a mobile device. It should be viewed as a way to augment the learner by providing access to both learning content and support information, anytime and anywhere. Therefore, both the learners and devices of today as well as the future should be considered to provide a more flexible view of mLearning. Unlike other learning technologies, mLearning is unique in that it can accommodate both formal and informal learning in collaborative or individual learning modes, and within almost any context. Consider the following working definition of mLearning:

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Leveraging ubiquitous mobile technology for the adoption or augmentation of knowledge, behaviors, or skills through education, training, or performance support while the mobility of the learner may be independent of time, location, and space.

This definition allows for a growing number of mLearning scenarios as well as future device capabilities and types. This definition also lends itself to support both education and training in traditional learning environments as well as performance support scenarios. Mobile learning should not be merely viewed as a replacement, an alternative, or a new addition to existing education or training delivery methods. It should be thought of as a complementary way to augment or enhance environments that already support learning. There are many other macro-level implications and considerations for mLearning from a development, implementation, or evaluation perspective. It is beyond the scope of this chapter to describe or cover these. In this chapter, the focus is on answering the question, What unique considerations are relevant to the instructional design of mLearning? The chapter will begin with how the traditional views of curriculum and instructional design can be rethought to support the performance of the learner. Readers will learn about these critical considerations for mLearning design based on the aforementioned distinctions and descriptions the authors candidly provided for the terms “mobile” and “mobile learning (mLearning).”

2

Performance Support in Curriculum and Instructional Design

In formal learning environments around the world, the key tenets of “what should be learned” and “how it should be organized” are traditionally addressed through the processes of curriculum and instructional design. However, a prevailing uncertainty among educational technology researchers today is whether or not mLearning introduces a discontinuity in traditional design principles for curriculum and instructional designers. The 2013 ADL mLearning survey (Berking et al. 2013) of education and training professionals inquired whether the instructional design process for mLearning is any different from the instructional design process for traditional eLearning. Sixty-six percent of the respondents from this study agreed that it does offer some discontinuity. Perhaps the most significant impact of mLearning on overall curriculum and instructional design is a paradigm shift from planned instruction to performance support. Performance support is the discipline that harnesses informal learning and makes it intentional (Gottfredson and Mosher 2011). This is simply due to the “anytime, anywhere” nature of the mobile platform, where users can access information and support materials at the point of need. As MIT professor and artificial intelligence pioneer Seymour Papert (Motivateus.com 2014) said, “You can’t teach people everything they need to know. The best you can do is position them where they can find what they need to know when they need to know it.”

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Learners are no longer constantly tethered to their desktop or portable laptop computer to support learning but are more frequently turning to leveraging mobile devices for support and self-directed learning. A 2012 Pew Research survey (PEW 2012) found that 86% of smartphone owners have used their devices in the previous 30 days to perform at least one “just-in-time” or performance support activity. Performance support is now often used in education, training, and workplace settings when learning is complemented or enhanced by on-demand information assets and electronic aids. The previously mentioned survey on mLearning (Berking et al. 2013) revealed a high level of confidence in performance support as an optimal approach for delivering mLearning. Towards Maturity (2014) found in their 2013 survey that “accessing support at the point of need” was the top driver for mLearning (80% of respondents listed it as such, above such factors as “improving employee engagement” (79%) and “improving communication between individuals” (77%)). Mobile device use inherently increases the tendency for learners to engage in selfdirected learning and stimulate their cognitive curiosity beyond classroom walls (Traxler 2007). Self-directed learning is commonly understood as a universal goal of higher education. Determining the most effective conditions for improving the performance of the learners in both higher education and training environments is often considered by instructional designers and educators as one of the most critical yet challenging undertakings. The role and focus of performance support in education and training is generally increasing, and there is also a clear distinction in education when compared to its purpose in a training environment. The distinction is directly related to the intended outcome and whether it is supporting a workplace task or a formal learning task. Typical learning outcomes are commonly aligned with memorization, understanding principles or concepts, applying rules, or acquiring high-order cognitive skills or problem-solving abilities. These types of learning outcomes all require different forms of instructional support and strategic planning. There are two distinct types of performance support: one is designed to offer support for workplace tasks at the point of need (defined by time, place, and context); the other is designed to support the learning process itself, usually in an academic setting (i.e., electronic study aids for a class). The former is often blended with instruction (classroom or eLearning), and the latter is inherently blended. Performance support alone, or a blended version of it, has the potential to significantly alter curriculum design; what were once sequences of formal courses or modules can now be catalogs of performance support materials; what were once sequences of classroom activities can now be self-directed learning activities guided by on-demand information. In some cases, the classroom or online portion of a blended learning module is relegated to merely training on what performance support resources are available and how and when to use them. Assuming there is a clear value proposition for incorporating mobile technology, the teachers, instructors, or instructional designers need to determine if the learning activity is truly dependent upon the learner and device being mobile. If it is not, and the activity is only minimally enhanced by mobile technology, then it may not be necessary to tie it too closely to the learning objectives.

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Learner-Centered Design

A key factor in determining the utility and success of an mLearning solution is the ability of that solution to adequately satisfy its users. Instructional designers should consider establishing user experience goals for their solutions so the learners find them usable, engaging, and motivating. In both the mobile and web development professions, experience design and interaction design are often closely aligned to a usability philosophy of considering the quality of touchpoints and user engagement within a software application experience. Ironically, designers of interfaces for learning are often not instructional designers, but they should be encouraged to work closely together. User experience and interaction designers often apply principles of usability whereas the instructional designers apply theories of learning. These theories of learning should be conveyed to the interaction designer before they can be leveraged for mLearning design. Consequently, the principles of user experience and interaction design should be equally conveyed to the instructional designer. Often, the focus of a user-centered design is to support task completion, whereas effective learner-centered design will help to reconstruct the experience around the learner. Combinations of both user-centered and learner-centered practices are often required in order to design and develop a useful mLearning solution. Learner-centered strategies also usually target independent learners with a need to think critically and solve problems. As mentioned earlier, performance support is emerging as a key design strategy for mLearning but also supports learner-centered design strategies. In the higher education setting, this might take the form of the scenario mentioned in the previous section, where it complements the classroom experience or, in some cases, guides self-directed learning. For classrooms augmented by mobile technology, the design of the mLearning solution must integrate closely with the core texts, curriculum guide, class objectives, and other materials related to the class. Similarly, workplace performance support materials should align with existing training or workplace tasks. Ideally, a learner-centered design strategy must give the users a compelling reason to access the support materials. Quinn (2011), an author of several books and articles on mLearning design, presents performance support as a form of learning augmentation and provided the following items for consideration in a learner-centered design: 1. Motivational examples – presented before and after a formal course to reinforce the need to learn the material 2. Extending learning processes • Reconceptualization – providing new concept representations • Recontextualization – new contexts of application as examples • Reapplication – more practice 3. Connecting with feedback 4. Supporting learner preferences – presenting material in the medium, time, format, etc. preferred by the learner 5. Contextual opportunities – adding value by tailoring learning to specific locations or times

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What other factors could influence a learner-centered design strategy? To answer this question, consider thinking about how people touch, hold, perceive, and interact with their mobile devices. A deep understanding and analysis of the target audience’s usage patterns and the device affordances will heavily inform the design. These factors will be examined next.

3.1

The Sense of Touch and Mobile Behaviors

Mobile devices provide a context in which haptic interfaces are playing an increasingly important role (MacLean 2008). The emotional and social significance of touch for humans is undeniable. It is deeply rooted in early human physiological and psychological development from the time of embryo development all the way through adulthood (Nicholas 2010). Today’s mobile user typically expects full control over a mobile interface and receives sensory information prompts in a manner that is usable in his or her current context. Touchscreen and sensor-based inputs such as swipes, taps, pinches, screen rotation, and vibrations seem to increase motivation, engagement, and the authenticity of a simulated environment on mobile devices. However, there is little research on exactly why mobile touchscreen interfaces are so engaging and motivating in both collaborative and individual learning environments. According to the 2013 survey on mobile learning from ADL (Berking et al. 2013), touchscreen interaction was also selected as the top area of mLearning design that educators and training professionals were most interested in better understanding. What role does touch interaction play in tactile cognition and learning on mobile devices? Tactile learning is the process of acquiring new information through tactile exploration (Nicholas 2010). Research studies on tactile information processing in humans have revealed that people can actually be trained to absorb a large amount of information by using their sense of touch. There are also obvious benefits inherent in mobile apps that provide an optimized-for-touch experience. According to research on mLearning in the classroom (Ciampa 2014), materials, quizzes, and games made available via mobile apps also provide opportunities for exploration, repeated selfassessment, and instant feedback. The instant feedback to student responses was an appealing form of incentive compared to prior classroom practices of grading and providing feedback by hand, long after a concept had been taught and possibly forgotten. Neglecting to consider HCI and touch interaction behaviors when designing mLearning can actually lead to missed learning opportunities if users are subjected to poor interface and interaction design decisions. While high-quality content and instructional design are important, clean graphics and visual design help attract learners to interact with the interface and content. Fortunately, for the most part users are at the mercy of the mobile device manufacturers and operating systems (OS). They have already made many of the inherent user interface design decisions for apps to work within their mobile OS. However, there is still some responsibility for graphic design and interface elements in mLearning, leaving room for error, and

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even more so if mobile user behaviors are also not taken into consideration or tested for in advance. Past research on mobile behaviors has focused primarily on smartphones while educators and instructional designers have directed much of their focus to delivering mobile learning on tablets without a deep understanding of the ergonomics and behaviors of use. A recent survey report published by (Hoober and Shank 2014) titled “Making mLearning Usable: How We Use Mobile Devices” revealed how people hold and when they use mobile devices. The survey revealed the ways people use smartphones and large tablets are substantially different. People use phones almost entirely in several possible hand combinations, and largely on the move while standing or walking. People use tablets much more often while sitting, and with the device in a stand, attached to a keyboard, or set on a table. Users also often change the way they hold their smartphone or tablet, switching from one to two hands and changing the orientation, different for typing vs. reading. These findings have huge implications for readability and mLearning design (Fig. 1). These findings also point to the fact that the larger tablets with 9–11 in. screens are being used very similarly to laptops. In addition, the wide range of hand combinations when using smartphones is further increased if left-handed vs. righthanded use is taken into consideration. These insights reinforce the importance of HCI and learner-centered design considerations in an mLearning design strategy (Fig. 2). It may not be possible to address all of the attributes of both tablets and smartphones without encountering a substantial amount of distinct differences such as accommodating user interaction preferences, screen sizes, and user behaviors. These differences alone would require exponentially complex considerations for each device type and form factor. Therefore, it is imperative that organizations wisely decide on which devices should be part of their mobile strategy, and this decision should be informed by their learners’ behaviors but also by their access to and expectations of mobile technology.

Fig. 1 A tablet on a surface is much further from the user than smartphone in the hand so text and graphics must be much larger from Hoober and Shank (2014)

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Cradled

Held, Finger

One-hand, Low

One-hand, High

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Two Hands, Landscape

Two Hands, Portrait

Fig. 2 The way we hold our mobile devices from Hoober and Shank (2014)

3.2

Device Capabilities and Affordances

As a result of the excitement surrounding mLearning in recent years, many educators and instructional designers mistakenly ask “where do I start in deciding which mobile technology to use?” Faced with the overwhelming array of choices, many start in an arbitrary way, selecting a technology (especially a new one that has emerged as the flavor of the month) that seems to be a fit for their need and finding a way to make it work for them (e.g., augmented reality). A less risky approach is to define the problem to be solved and then examine mobile technologies systematically, pointing to specific device capabilities and affordances. This can be tricky, because most mobile technologies were not invented solely for learning and do not come with a manual of how to use them explicitly for learning. Psychologist James J. Gibson in his 1977 article “The Theory of Affordances” first introduced the term “affordance.” Gibson (1977) defined affordances as all “action possibilities” latent in the environment, objectively measurable and independent of the individual’s ability to recognize them but always in relation to agents and therefore dependent on their capabilities. An affordance in general terms is therefore a quality of an object, or an environment, which allows an individual to perform a specific action or ability. The term has been further evolved by Norman (1988) for use in the context of HCI to indicate the easy discoverability of perceived action possibilities. The key to understanding affordances is to identify the underlying capabilities and then describe the affordances those capabilities provide for learning applications, as an intermediary step to eventually identify the learning

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strategy to be employed. Raw capabilities of the device are therefore the enablers for affordances. However, learners may not always have equal access to the same capabilities depending upon their device type, connectivity, security, privacy, and other technological or environmental challenges. Equal access to specific device capabilities is a critical factor and consideration influencing the flexibility and richness of mLearning design options. These types of considerations should be identified during the analysis phase of an mLearning project so that they might be appropriately addressed during the design phase. Affordances are important to recognize for the design of mLearning because smartphones and tablets exhibit unique features and qualities that allow individuals to perform a specific action. Each affordance is enabled by the portability of the device, coupled with a specific capability of the device. In many cases the affordance is based on the combination of both hardware and software capabilities. For example, the camera is a capability of many smartphones and tablets. The hardware for the camera alone does not provide a unique capability. When the camera hardware is combined with a software application (App), then such affordances as capturing video and images, augmented reality, Quick Response (QR) code reading, or content image analysis are made possible. When thinking more deeply about capabilities and affordances for mLearning, consider the following table in Fig. 3 below.

3.2.1 Augmenting and Contextualizing Instructional designers and educators often lack clarity regarding the impact that a learner’s physical location has on his or her learning. An analysis of what parts of context are important for effective mLearning practices and how they can be used is of major importance. Augmenting and Contextualizing might possibly be two of the most powerful affordances to be considered for mLearning design. Mobile device capabilities such as the Global Positioning System (GPS) sensors, geolocation, and camera scanning provide mLearning designers with the ability to know the real-world geographic position as well as the physical place where learning can occur. Augmenting provides an enhanced view of the real world by overlaying sound, graphics, text, video, and GPS information. Contextualizing provides opportunities to improve learning through adding more meaning or contextual support. How can this impact mLearning design strategy? Consider situated learning (Lave and Wenger 1991), where such learning is situated in a specific context or takes place within a particular social and location-based environment. Situated learning is possible in mLearning today through the affordance of contextualizing. For example, consider the following examples: field trips, location-based guides, nature studies, museum tours, collaborative field activities, on-the-job training, and performance support. All of these types of learning scenarios are especially enhanced by improving nearby context information because they may depend on a specific location. Mobile augmented reality is one example of mLearning that sometimes combines the affordances of Augmenting and Contextualizing, providing designers with a way to enhance both the user’s context and real-world situation at the same time. This combination of augmenting and contextualizing might explain why augmented reality has grown substantially in recent years and penetrated other markets outside of the learning space.

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Affordance for Mobile Learning Accessing: On-demand access to information, courses, performance support or refresher knowledge. Examples: search knowledgebases, job aids, reference, dictionary, Wikipedia, courses, voice search, social media Augmenting: Overlaying still imagery, audio, or video over real world objects or setting in support of or during a contextual learning activity.

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Device Capabilities • • • •

touch screen internet browser connectivity microphone

• camera • GPS • internet connectivity

Example(s): augmented reality, scavenger hunt, museum tours, language learning Capturing (audio): Documenting or recording auditory content in support of or during a learning activity.

• microphone • speakers • digital storage

Capturing (imagery or video): Documenting or recording visual content relevant to learning activity.

• camera • microphone • digital storage

Communicating (messaging): One-way, two-way or group messaging as part of an informal or formal learning activity.

• • • •

SMS MMS chat apps microphone

• • • •

voice call voicemail speaker microphone

• • • • • •

Bluetooth GPS NFC RFID Wi-Fi camera

Examples: group collaboration, instructor/student discussion and chat Communicating (voice): Two-way, or group discussion as part of an informal or formal learning activity. Examples: group conference, meeting, focus group Contextualizing: Notifications and linked interactions sent by transmitters or tags attached to objects using proximity or location sensors to provide a context-aware or location-aware content in support of or as part of a learning activity. Examples: iBeacons, QR Codes, scavenger hunt, mobile tours, games, and interactive stories eReading: Accessing and reading documents on multiple devices anytime, anywhere in support of or as part of a learning activity.

• text zoom • text highlighting • notes

Media Playing: Accessing media anytime, anywhere in support of or as part of a learning activity.

• • • •

Example(s): YouTube, Kahn Academy, Webinars

Notifying / Reminding: Event triggers, instant reminders, and alerts that illicit immediate responses or deeper engagement with a learning activity. Examples: spaced repetition/learning, flash cards, language learning

Fig. 3 Affordances for mobile learning

image video audio internet connectivity

• connectivity • touch screen • push notification service • calendar

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3.2.2 Spaced Learning In addition to providing contextually relevant information or augmentation, mLearning is ideal for providing enhanced retention by leveraging Spaced Learning (aka spaced repetition). Spaced Learning is a learning technique that incorporates increasing intervals of time between subsequent reviews of previously learned material in order to exploit the psychological spacing effect. Spacing can involve a few repetitions or many repetitions. This is one of the examples provided in Fig. 3 above as a result of the notification/reminder affordance. Providing only textual and general information in mLearning without repetition, no matter how elegantly it is presented, will usually not result in long-term knowledge transfer or performance improvement for most learners. While repetitions are good for retention in learning, spaced repetitions have been proven to be the most effective. And longer spacings tend to produce more long-term retention than shorter ones (Thalheimer 2006). This spacing is effective both on the level of the initial content presentation as well as refresher/reminder education or training (to prevent knowledge decay of information that one seldom uses). Findings from Thalheimer (2006) reveal that the amount of practice and intervals in between depend on a number of factors including how complex is the skill, how often the opportunity occurs, and how important is competence or performance. Thalheimer, W. (2006) reports that The spacing effect is one of the most reliable findings in the learning research, but it is, unfortunately, one of the least utilized learning methods in the learning field.

Instructional designers have had this information for a long time – over 100 years, in fact. Hermann Ebbinghaus proved it in 1885 with what he called The Forgetting Curve. Figure 4 below is an adaptation of Spaced Learning to include practice and test depictions by Quinn, C. (2011).

100 Reactivation Curve 80

60

Spaced Learning Curve

Normal Learning Curve

Spaced Forgetting Curve

40

20 Practice

Normal Forgetting Curve

Test 0 Adapted from Thalheimer, W. (2006). Spacing Learning Events Over Time: What the Research Says. Work-Learning Research, Inc.

Fig. 4 Spaced practice by Quinn, C. (2011) (Adapted from Thalheimer 2006)

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This effect suggests that “cramming” (intense, last-minute studying) the night before an exam is not likely to be as effective as studying at intervals in a longer time frame. Repetitions at increased time intervals strengthen connections in the brain and counteract the process of forgetting. For improved retention, an mLearning solution could optionally provide repetitive practice to mastery to ensure that the facts, processes, and concepts are internalized for later recollection and use. Consider how spaced or timed, relevant learning could be beneficial to your learners. Mobile devices provide the capabilities that easily leverage the affordances of notifications and reminders that can harness the power of Spaced Learning.

4

Learning Theories and Conceptual Frameworks

As previously mentioned, mLearning does not simply amount to a different mechanism for delivering content to learners; it represents an emergent way of thinking that implies a paradigm shift and requires new design strategies informed by sound underlying learning theories. Although mLearning design does not necessarily require new models, the mobile devices and the learning theories they support are sufficiently unique that special considerations are warranted during the design process. Conceptual frameworks can also provide opportunities for these considerations by providing guidance for thinking about new concepts and approaches in the design context. Instructional design models such as ADDIE are generally focused on helping lead the designer, objectively, without premature bias toward a particular solution, to choosing the appropriate learning technology and instructional strategy. Robust ID models are intended to stand the test of time and are agnostic to particular technologies and design strategies. However, it is not unusual for instructional designers to combine existing process models with other models, frameworks, or theories. Learning theories are critical to mLearning design because they directly inform choices of learning strategies and can ultimately influence other steps in the ID process. Constructivism is generally recognized as one of three main schools of thought in learning theory, based on the work of Piaget and philosophers like Vygotsky. In the past, it has been underutilized in learning experience design because of limitations of the learning environment or technology. However, it is now enabled significantly by the mobile platform, occupying a potentially equal seat at the learning design table along with the two other traditionally relied-on learning theory schools of thought, Cognitivism and Behaviorism. Constructivism holds that learners “construct” knowledge and meaning from interactions with other people and their environment; meaning is therefore unique to each individual. New information is assimilated into the learner’s mental schema filtered through existing knowledge and experiences. Constructivist learning focuses on creating appropriate learning environments, with authentic representations of real challenges and tasks that learners can interact with and construct meaning from. This learning theory is especially relevant because mLearning enables learners to communicate, analyze problems, and participate in learning activities in a real-world

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context. In fact, learners can analyze problems on the spot in real time without having to return to the classroom. Constructivism is also often equated with informal learning. Depending on the definition of the latter, there is significant overlap, but they can be differentiated by the fact that informal learning connotes freedom of choice on the part of the learner to determine what activities they are going to engage in to meet the learning objectives; by contrast, constructivist learning environments (CLEs) may be constrained to a finite range of choices (i.e., learners “discover” the solution to a problem by examining the given options that are engineered into the system). There are no unique design considerations for mobile CLEs except that the affordances of the mobile device need to be taken into account; CLEs, more than behaviorist or cognitivist experiences, really can benefit the most from mobile technology, since they are often conducted in the field, leveraging the many different data capture and communication features of mobile devices. Conceptual mLearning design frameworks (as opposed to learning theories) might also be investigated during the analysis phase while developing an instructional strategy. However, they can inform mLearning design mostly only in indirect ways; they are meant to suggest a heuristically based intellectual orientation when approaching design problems. They are on the opposite end of the spectrum of algorithmic, cookbook-style design process models such as Dick et al. (2014). Although abstract and high level, these models can be used as an evaluation rubric for a given design, in terms of determining whether it adequately accounts for all aspects shown in the model. MLearning content and applications should be designed with special consideration for existing learning theories, and conceptual frameworks can be leveraged for stimulating creative thinking and planning. Several mLearning frameworks have been proposed, but many are uniquely aligned with a specific use case. The following frameworks are more generalized and might serve as a starting point for designers new to approaching design challenges in mLearning.

4.1

A Framework for M-Learning Design Requirements

This conceptual framework by Parsons et al. (2007) was conceived prior to the advent of modern smartphones and tablets, but it still provides a valuable resource on the systematic planning for mLearning experience design. The framework addresses generic mobile environment issues, context issues, learning experiences, and their individual or collective learning objectives (Fig. 5).

4.2

The Framework for the Rational Analysis of Mobile Education (FRAME) Model

Koole (2009) presents a model for describing mLearning as “a process resulting from the convergence of mobile technologies, human learning capacities, and social interaction.” It addresses contemporary pedagogical issues of information overload,

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Design Considerations for Mobile Learning

Generic mobile Mobile learning environment issues context issues Identity

Learning objectives

Organised contents Business rules, learning roles

Learner

Outcome and Feedback Test scores, leagues

Activity

Goals and objectives Skills and knowledge

Improved skills

Mobility

Mobile interface design Spatialtemporal

Facility Communication support

Collaboration

Representation or story Case studies, role plays Conflict, Competition, Challenge, Opposition Individual and team development Social Interaction Blogs,wikis, discussion groups, tests, teamwork

Social skills

Team skills

Collective learning

Media types

New skills

Individual learning

User role and profile

Learning experience

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Fig. 5 A framework for M-learning design requirements

knowledge navigation, and collaboration in learning.” Using this Venn diagram and the explanation Koole provides on each circle and intersection area, a high-level informal checklist can be generated to comprehensively guide one’s design thinking in these particular areas (Fig. 6).

4.3

Park’s Pedagogical Framework

Park (2011) used Moore’s (2007) transactional distance (TD) theory as the basis for a conceptual framework for mLearning. Transactional distance refers to the immediacy and structure of communication between instructors and learners. This led to his categorization of four types of mLearning by Park (2011): 1. 2. 3. 4.

High–transactional distance socialized m-learning High–transactional distance individualized m-learning Low–transactional distance socialized m-learning Low–transactional distance individualized m-learning (Fig. 7)

Park (2011) also discusses how this framework can be leveraged by instructional designers to understand how mobile technologies can be incorporated into their design strategy more effectively. The framework’s practical use would rely on categorizing the characteristics of desired learning activities as well as the inherent properties of a particular mobile technology and matching them to one of the four types.

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Fig. 6 The FRAME model (DL) Device Usability

(D) Device Aspect

(DS) Social Technology

(DLS) Mobile Learning

(L) Learner Aspect

(LS) Interaction Learning

Information Context

(S) Social Aspect

High Transactional Distance (TD) Mediated by Mobile Devices High TD Individual-based M-learning

Individualized Activity

High TD Group- based M-learning

Type 2

Type1 Type 3

Type 4 Low TD Individual-based M-learning

Socialized Activity

Low TD Group-based M-learning High TD Socialized Activity

Individualized Activity

Low Transactional Distance (TD)

Low TD

Fig. 7 Park’s pedagogical framework

4.4

The M-COPE Framework

This framework by Dennen and Hao (2014) provides a useful tool for encouraging educators to consider the requirements for incorporating mLearning into their instructional strategy. The M-COPE framework consists of five key elements: Mobile, Conditions, Outcomes, Pedagogy, and Ethics. Each of these elements provides a set of considerations to be made about a particular learning context. It was

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developed to help instructors make informed decisions during the design process when creating both new learning activities and applications or when incorporating mobile resources into existing nonmobile activities. The authors of this framework believe that instructors will benefit from this framework by prompting them to recognize learning needs and constraints while following established ID process models.

4.5

Mobile Training Implementation Framework (MoTIF)

This framework is focused on exploring the intersection of multiple design and research methods by following a Design-Based Research (DBR) approach. The framework suggests using an integrated master flowchart of processes, decisions, and considerations for the entire instructional design process, specifically including and highlighting elements that optimize it for mobile learning. The objective to define and refine a design decision support framework includes consideration of the motivational, contextual, pedagogical, and performance support aspects of mobile learning.

5

Create, Convert, or Capitalize?

Perhaps one of the least complicated mLearning decisions for educators and instructional designers is determining whether they need create something entirely new, convert existing learning materials, or capitalize on current mobile apps. Creating a new mLearning solution can quickly become costly and time consuming, and there are significant technical concerns when it comes to cross-platform development. Before rushing to create a new mLearning solution, designers might consider capitalizing on the popularity current App Store catalogs from Apple, Google, and Microsoft. The popular “there’s an App for that” slogan trademarked by Apple holds true for the other mobile platforms as well. Often, the mLearning need can be addressed by an existing app or a combination of apps. For example, several augmented reality browser apps are freely available today and are already being used to meet mLearning needs in education, training, and performance support. If existing apps or mLearning solutions can be leveraged, it might also be more cost effective to utilize them rather than creating a new capability from scratch. If existing apps don’t completely fulfill the mLearning requirements, then reviewing them might at least help expose educators and instructional designers to new design ideas. Alternatively, leveraging HTML and the web might provide another option for mLearning design for situations where learners might not have access to the same mobile platforms or apps. The one thing every mobile device has in common is that they all have web browsers that support HTML. While targeting a mobile web approach might address concerns with cross-platform access, it will limit mLearning design strategies that wish to target the advanced capabilities of mobile devices (e.g., sensors, camera, push notifications).

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In the case of revisiting instructional strategy due to a mobile conversion requirement, conceptual frameworks from Park (2011), Koole (2009), and Berking et al. (2014) that emphasize the analysis phase might also be considered. If the analysis phase is ignored, the learning or performance problem may never be addressed and money and resources might be wasted either on a problem that doesn’t exist or the wrong problem altogether. It is at this point in the process when appropriateness of mLearning as a solution should be justified. If existing learning materials are being converted to mLearning, the Analysis phase has presumably already been completed. However, in light of the unique design considerations for mLearning, an audit would be needed of the existing content and strategy, to ensure that the content and approach is still appropriate for mobile. Mobile conversion usually requires more than chunking the content down into much smaller units, accounting for the reduced screen size, etc. In fact, it often requires a careful analysis of existing learning materials or courses before converting them to a mobile format. It has been proposed that many designers and developers are creating new mobile content and converting existing courses by only resizing them to account for the smaller screen and user interface differences. Survey and interview respondents from ADL’s mobile learning survey report (Berking et al. 2013) agreed that this is often the case and results in poor usability and learning outcomes. An important consideration when addressing conversion to a mobile format is that the learning content should be reduced to much smaller discrete units than in a classroom or desktop eLearning course, with preferably 2–3 min for each unit or module. The attention span, readability (on a small screen), and previously mentioned mobile behaviors reinforce this advice. Where and how these design changes are to occur is also a primary concern in the analysis phase when following an instructional design model. Such questions as the following should be considered: • • • • •

6

Can the information be made more concise? Should information be sequenced in the same way? Should the students be assessed differently? Should objectives be reevaluated? Is the seat time too long for mobile instructional materials?

Future Directions

This chapter provides key considerations for the design of mLearning. It is difficult to design for all of the different characteristics of both smartphones and tablets. However, the scope was specifically limited to these devices as they offer the most potential for the rich, contextual, and contemporary mLearning design opportunities today. The contents of this chapter heavily relied on both the Learning Science and Human-Computer Interaction (HCI) domains in order to identify the unique considerations applicable to the instructional design of mLearning as well as describe potential gaps in general mobile design knowledge.

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When possible, it can be a powerful mLearning design strategy to incorporate performance support materials in both education and training settings. However, the most effective mLearning solutions often take both practice to mastery and performance support into account while focusing on how mobile technology can add the most value to the learning context. Learner-centered design considerations should be at the top of the list of any mLearning strategy. These considerations are often deeply connected to deeper aspects of user experience design, mobile behaviors, and access to mobile device affordances. The existence of learning theories and conceptual frameworks provides guidance and opportunities for leveraging mLearning epistemologies. Finally, most mLearning design decisions will eventually lead into production considerations of creating, converting, or leveraging existing materials. All of these aforementioned considerations are relevant to and will ultimately result in an informed set of design requirements for any mLearning strategy, whether it is for education, training, or human performance purposes.

References Berking, P., M. Birtwhistle, S. Gallagher, and J. Haag. 2013. Mobile learning survey report. Advanced Distributed Learning (ADL) MoTIF project. Retrieved from http://www.adlnet.gov/ wp-content/uploads/2013/09/MOTIF-SURVEY-REPORT-3.pdf Berking, P., M. Birtwhistle, S. Gallagher, and J. Haag. 2014. Mobile learning needs assessment report. Advanced Distributed Learning (ADL) MoTIF project. Retrieved from http://www. adlnet.gov/wp-content/uploads/2014/09/MOTIF-NEEDS-ASSESSMENT.pdf Ciampa, K. 2014. Learning in a mobile age: An investigation of student motivation. Journal of Computer Assisted Learning 30(1): 82–96. Dennen, V., and S. Hao. 2014. Intentionally mobile pedagogy: The M-COPE framework for mobile learning in higher education. Technology, Pedagogy and Education 23(3): 397–419. https://doi. org/10.1080/1475939X.2014.943278. Dick, W., L. Carey, and J. Carey. 2014. The systematic design of instruction. Upper Saddle River: Pearson Publishing. Gibson, J.J. (1977). The Theory of Affordances (pp. 67–82). In R. Shaw & J. Bransford (eds.). Perceiving, Acting, and Knowing: Toward an Ecological Psychology. Hillsdale, NJ: Lawrence Erlbaum. Gottfredson, C., and B. Mosher. 2011. Innovative performance support: Strategies and practices for learning in the workflow. New York: McGraw-Hill. Hoober, S., and P. Shank. 2014. Making mLearning usable: How we use mobile devices. The eLearning Guild Research Report. Retrieved 5 Apr 2014. Koole, M.L. 2009. A model for framing mobile learning. Mobile Learning: Transforming the Delivery of Education and Training 1(2): 25–47. Lave, J., and E. Wenger. 1991. Situated learning: Legitimate peripheral participation. Cambridge: Cambridge University Press. MacLean, K.E. 2008. Haptic interaction design for everyday interfaces. Reviews of Human Factors and Ergonomics 4(1): 149–194. Moore, M.G. 2007. The theory of transactional distance. In Handbook of distance education, ed. M.G. Moore, 89–105. Mahwah: Lawrence Erlbaum Associates. Motivateus.com. 2014. For leaders & teachers. Retrieved 25 Sept 2014 from http://www. motivateus.com/teach27.htm

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Nicholas, J. 2010. From active touch to tactile communication: What’s tactile cognition got to do with it? Aalborg: Danish Resource Centre on Congenital Deafblindness. Norman, Donald. 1988. The design of everyday things. New York: Basic Books. ISBN 978-0-46506710-7. Park, Y. 2011. A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types. The International Review of Research in Open and Distance Learning 12(2): 78–102. Parsons, D., H. Ryu, and M. Cranshaw. 2007. A design requirements framework for mobile learning environments. Journal of Computers 2(4): 1–8. PEW. 2012. Just-in-time information through mobile connections. Retrieved 10 Aug 2014 from http://www.pewinternet.org/2012/05/07/just-in-time-information-through-mobile-connections/ Quinn, C. 2011. Designing mLearning. San Francisco: Pfeiffer Publishing. Thalheimer, W. 2006. Spacing learning over time. Retrieved Apr 2012 from http://willthalheimer. typepad.com/files/spacing_learning_over_time_2006.pdf Traxler, J. 2007. Defining, discussing, and evaluating mobile learning. The International Review of Research in Open and Distance Learning 8(2): 1–12.

Mobile Learning and Engagement: Designing Effective Mobile Lessons

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 What is the Mobile Lesson? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 The Mobile Lesson Template . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Implementation of the Mobile Lesson: A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Faculty Learning Community on Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A: Mobile Lesson Template . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix B: Scavenger Hunt Mobile Lesson on Motivational Appeals for Persuasive Speaking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Goal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Learning Outcome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials/Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Instructions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deadline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Technology Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

As the world continues to move deeper into mobile, higher education classrooms (virtual and face to face) are positioned well for utilizing mobile learning to further enhance student engagement and learning. This is significant to today’s millennial learners who are tech savvy and have never known a world without the K. Vincent-Layton (*) Department of Communication, College of eLearning, Humboldt State University, Arcata, CA, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_62

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Internet. Connecting to this internet generation via mobile technologies creates relevance in the learning environment. Educause discusses the implications for teaching and learning in the May 2010 “7 Things You Should Know About Mobile Apps and Learning” and stresses that “. . . mobile devices support lifelong learning, and because the devices themselves are integrated into everyday life, they facilitate authentic learning” (Educause 2014). Yet one of the greatest challenges lies in the reality that there are few resources published that offer comprehensive mobile lessons and concrete methods to effectively implement mobile learning into the classroom. Educators need specific guidelines and model examples of mobile lessons to fully understand how to create the lesson, what to consider when developing, and how to successfully integrate it into the classroom. Having these essential components will change the ways in which learning takes place, breaking free of traditional pedagogical structures and finding new and relevant ways to engage the millennial learner. Christy Price, a psychology professor at Dalton State College, indicates that in order to reach this level of engagement, relevance is one of the greatest challenges in connecting learning outcomes and activities for the millennial learner (Price C, Why don’t my students think I’m groovy?: The new “R”s for engaging millennial learners, 2009). Educators can create relevance to learning using effective mobile design and implementation. The Mobile Lesson Template is a design guide that includes several elements for teachers to thoroughly examine when considering the ways in which mobile can support students’ learning (see Appendix A). As discovered in a semesterlong faculty learning community on mLearning, faculty were successful in utilizing the Mobile Lesson Template to create and implement mobile lessons into the classroom, allowing for reflection and evaluation of students’ learning. Educators worldwide can create significant connections between engagement and learning by incorporating mLearning strategies into teaching and learning design.

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Introduction

As students today continue to expand the use of mobile devices for everything from entertainment to social communication to news, educators can view this as competition for time-spent learning or take advantage of the ubiquitous nature of mLearning by integrating mobile lessons into course work that can further extend students’ learning beyond the walls of classroom space. In looking at both mobile learning and millennial characteristics, it is important to consider how the two intersect with respect to the learning environment. Mobile learning characteristics include “anytime and anywhere” and “flexible access,” which are key in understanding the scope of where the learning can reach. The boundaries are endless. Millennials, otherwise known as “Generation Y” or “Digital Natives” or “Net Generation,” are people who were born between 1981 and 1999, a quarter of the United States population and a significant part of the college base today. These learners have unique characteristics that include technological, goal-oriented,

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team-oriented, high achieving, pressured to succeed, sheltered by parents, and socially conscious (Howe and Strauss 2007). Millennials are creative and want learning to be a fun experience. The ways in which millennials impact teaching and learning are significant to the integration of mobile in today’s classrooms. In Price’s studies of millennial learners, the most important elements in a learning environment were found to be “interactive” and “participatory” (Price 2009). Millennial learners crave the technology and the interactive team aspects that flexible mobile learning environments support and allow the extension of the learning into the world beyond a physical space. This provides a very strong relationship between millennial learners and mobile, which is further enhanced by utilizing tangible methods and tools to support mobile learning and teaching practices. The Mobile Lesson Template is one such method/tool. The template allows the educator to tap into the millennial learner’s crave for technology and interactivity while considering a well-rounded look at all the necessary elements to consider when designing the lesson (see Appendix A). Creating a lesson is by nature a challenging and sometimes daunting task for an educator. Design takes precision, deep thought, and reflection. Add the persistent nature of mobile to the mix, and this can appear to add another layer of complexity. However, the Mobile Lesson Template creates a solid foundation for the design and development of a mobile assignment. The template begins with identifying the goal of the mobile lesson with respect to meeting the learning outcome(s). Additional template elements contribute to the creation of a well-rounded, thoughtful lesson. Looking at mobile as something that can be integrated, rather than as an extra step in the creation of in-class and/or online assignments, is a sound approach. In ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning,” it is noted that a blended learning environment is considered the preferred format with respect to mobile learning at this time. For this reason, mobile lesson design can be easily incorporated into existing lessons rather than starting from a blank slate. The Mobile Lesson Template guides the educator in recognizing a number of essential elements that should be considered in supporting successful outcomes of the mobile lesson. Elements such as allowing app and device freedom of choice and alternative assignments are some of the key mobile best practices because all students are included, regardless of ability and/or access. The elements take a close look at the crucial considerations when going mobile. In this chapter, mobile lesson will be defined, and key elements of the Mobile Lesson Template will be presented and discussed to support educators in successfully creating mobile lessons. A case study on the design and implementation of once such mobile lesson using the Mobile Lesson Template will also be shared. Lastly, a look at a semester-long Faculty Learning Community on mLearning will provide further evidence of the effectiveness of the Mobile Lesson Template as a model for designing mobile activities. As mobile technology expands and penetrates education at faster and deeper rates, educators can easily grasp and apply mobile methodologies and pedagogies to extend students’ learning outside the confines of the classroom.

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What is the Mobile Lesson?

The mobile lesson is an activity that may take place in a face-to-face classroom, in a virtual classroom, or out in the world. It allows the students to reach outside the walls of physical space and connect course concepts to a personalized learning experience. The personalized learning experience is meaningful and therefore encourages the individual to take charge of his/her own learning as it continues beyond the life of the course. One example of a mobile lesson is students adding and sharing voice data to various locations around the world by using a geolocation app, such as GeoGraffiti. Classmates (and others!) can “go” to these locations and find the data and add further information. Another example is students using a live-blogging tool, such as CoverItLive, to generate content during class or other learning sessions. In an online anthropology course, students might use mobile devices to capture observations using field notes and images to share in a course blog, wiki, or forum. Higher levels of learning skills that are used from these types of experiences include critical thinking, problem solving, and analysis (Atherton 2013). In order to achieve these higher levels of learning using mobile pedagogies, the Mobile Lesson Template becomes a useful guide in creating learning experiences that are designed to consider the knowledge and skills that create desired outcomes.

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The Mobile Lesson Template

There are several key elements of the mobile lesson that need to be considered in order for it to be effective in the classroom. The first step in designing the mobile lesson is to look at the goal and the outcomes. An effective mobile lesson can be created to meet the outcomes of an assignment by utilizing the Mobile Lesson Template, which includes core principles (goal, outcomes, instruction, assessment) of Wiggins and McTighe’s Understanding by Design (see Appendix A) (Wiggins and McTighe 2005). The first six elements of the Mobile Lesson Template create the foundation that is needed to build the lesson. Once these are defined, the template includes other elements that should be considered and also allows for flexibility in including only what is needed for the particular activity. Element 1: Assignment Name. It is important to include a name for the assignment and lesson concept that uses the word “mobile.” As with any lesson, providing a concise name draws the student into the lesson. For example, Scavenger Hunt Mobile Lesson on Motivational Appeals for Persuasive Speaking offers students a specific focus for the assignment while also including the mobile aspect (see Appendix B). Element 2: Goal. What experience will the lesson provide for the student? This is where the lesson overview is described to give the student an understanding of what is expected in the assignment. For example, “In order to be an effective speaker, it is important to consider the emotional impact on our audience, as well as relate our ideas to their emotions, needs, and values. We need to find out what is meaningful to

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our audience so we can relate to them in persuasive speaking. Work together as a team to discover and capture a variety of objects and/or visuals that include motivation appeals.” The student experience becomes the goal of the lesson, which is tied to larger assignment in this assignment (i.e., persuasive speech). Element 3: Learning Outcomes. The learning outcomes must be clearly stated in order to understand the expectations of the lesson and also to be able to evaluate the student’s performance. For example, “upon completion of this assignment, you will be able to evaluate at least five different objects and/or visuals that demonstrate motivational appeal.” This structure defines a specific measure ( five different objects and/or visuals. . .) for the student who is completing the work and for the teacher who will be evaluating the student’s work. Element 4: Materials/Resources. In this step of the template, the educator should consider what materials and/or resources are required in order for the student to complete the assignment. For example, students may be offered choices in the apps and devices used or even an alternative format, as long as the expected outcomes are met. This not only allows the student’s experience to be personalized, but it also creates a more inclusive learning environment. Element 5: Instructions. The instructions (including technical aspects) should be clear and broken down into detailed, concise steps in order for the student to successfully complete the lesson. Note in the Scavenger Hunt Mobile Lesson, the numerical instruction list serves as a simple, step-by-step guide for the student to follow. If there is any pre-lesson work that students need to complete, this should be stated as well. For example, if students are required to work in groups and use a specific type of mobile app, defining these ahead of time helps to prepare the students and reduce confusion during the activity. It is critical to map out a process that reduces student and teacher frustration while also increasing engagement. Element 6: Assessment. How will the students be evaluated? It is important to define the assessment process for both educator and student so that each knows exactly what is being asked in order to meet the outcome(s). For example, in the Scavenger Hunt Mobile Lesson, a rubric is used to define three criteria and point value for the associated expectations. Students can clearly identify for what an exemplary assignment includes and how it will be evaluated. Once these first six critical elements are defined, the mobile lesson is ready to further build using Elements 7–13 as appropriate. Not every mobile lesson will need to include all elements of the Mobile Lesson Template; however, each should be considered and modified as the design and development take shape. Element 7: Weighting of the Assignment. What percent of the student’s grade is reflected in this activity? It is important for the student to know how the grade for the lesson affects the overall class grade to give relevancy to the course. Element 8: Submitting Assignment for Evaluation. Assignment submission details that include how and where to submit should be included if the student is required to submit something. For example, in the Scavenger Hunt Mobile Lesson, the submission information is included in Element 4: Instructions, Step Four. In this example, the Mobile Lesson Template was modified to combine submission information with the detailed, step-by-step instructions.

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Element 9: Time Commitment. Students need to know the expected time commitment to complete the assignment in order to guide the process. In the Scavenger Hunt Mobile Lesson, students have 20 min to complete the mobile lesson during a class session, with face-to-face and online discussion following the lesson. Element 10: Deadline. A specific deadline should be given in order for students to successfully engage in the mobile lesson. In the Scavenger Hunt Mobile Lesson, students are required to submit the final lesson URL during the class period. Online discussion of other teams’ submissions is the final piece of the lesson due at the end of the week. Element 11: Feedback Expectations. When and how will students receive feedback on the assignment/activity? Feedback is an important part of the learning process because this is where the student reflects with information that can guide changes and improvements, i.e., learning! In the Scavenger Hunt Mobile Lesson, students receive three forms of feedback: classmates’ oral feedback, classmates’ written feedback in an online discussion forum, and instructor feedback in Moodle Gradebook. Element 12: Examples. If appropriate, examples of previous students’ work or an instructor example can provide a model for students to emulate, as well as get an understanding of what the lesson is asking. In the Scavenger Hunt Mobile Lesson, the instructor provides two sample video collages created with different mobile apps. These examples help to highlight the exact expectations and provide an exemplary example of the end product. Element 13: Technology Considerations (Challenges/Solutions). One of the final elements to address is potential technology challenges and solutions. What considerations are needed to identify challenges for both instructor and student? What potential solutions could solve these challenges? For example, is Wi-Fi access available? If not, will students have to use personal data service? Are there suggested, cross-platform mobile apps for varying devices? Some challenges in the Scavenger Hunt Mobile Lesson include student access to mobile devices and time used to select the mobile app and create accounts. Potential solutions include asking for student volunteers who are willing to provide a mobile device and selecting team leaders to choose and set up the mobile app prior to the activity. Thinking about potential technology issues in advance will help reduce barriers; however, it is not intended to create an experience that is constrained by structure. Instead, the educator should allow some “chaos” in the mobile learning experience, just as with any other learning activity (Yu 2008). It is these “chaotic” environments that allow the learner to reach beyond traditional knowledge models and create a personalized learning environment that can continue to grow throughout college and beyond. The Mobile Lesson Template becomes a guide for creating effective mobile assignments that include elements that allow for flexible design and implementation.

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Implementation of the Mobile Lesson: A Case Study

One such lesson that utilized the Mobile Lesson Template was the Scavenger Hunt Mobile Lesson on Motivational Appeals (Appendix B). The instructor created this lesson with the goal of improving students’ application of a concept that had not

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been met in previous lessons and assessments. To begin creating the lesson, each of the elements in the Mobile Lesson Template were addressed with the applicable information, with a particular focus on Element 11: technology considerations. In order to successfully integrate the lesson into the classroom, the instructor walked through the entire lesson and created examples to not only test the instructions, but also the various technologies. This step was critical in ensuring the student’s success in meeting the lesson outcomes. The activity included five parts: student prework to prepare for the activity, the activity itself, an in-class activity share, a discussionbased reflection activity focused on the outcomes of the activity and the process, and, finally, an online discussion post-activity. A final measure of students’ application of the learned concepts was evaluated in a culminating persuasive speech. The mobile lesson is now in the third year of successful implementation into the classroom. The mobile lesson was implemented into a section of Fundamentals of Communication (Public Speaking) at Humboldt State University, a required course to graduate from the California State University system. In previous semesters, students struggled with the concepts of motivational needs and values in persuasive speaking. The Scavenger Hunt on Motivational Appeals Mobile Lesson became a method to not only give students direct application with the concept, but also appeal to the millennial sense of teamwork and technology by using mobile to create personal connection with each other and the world around them. Student preparation before class included a chapter reading and an associated reading quiz based on values and Maslow’s hierarchy of needs. In class, the instructor facilitated a mini-lecture that incorporated student discussion related to the concepts of the reading and quiz. The mini-lecture also included a brief overview of mobile lesson examples for students to clearly understand what the final product may look like. Students were then divided into teams based on volunteers willing to use a smartphone for the mobile activity. This pre-class work was critical to the success of the lesson because students needed to come prepared with foundational understanding to build upon in order to successfully participate in the lesson during the class period. After student teams were formed, the mobile scavenger hunt began. (Note: a virtual scavenger hunt was also considered possible with this activity.) Student teams were seen all over the campus, searching for examples of images/ signs/other visuals that represent motivational needs and values. Examples included a restroom sign, appealing to a person’s survival needs; a sports team flyer, appealing to someone’s peripheral values; and a support group poster, appealing to a person’s belongingness needs. Excitement and energy filled the northwest side of campus as teams scurried to make the best use of 20 min capturing the visuals to support the idea of needs and values. Students returned to the classroom to finalize uploads using the team choice mobile app. These uploads took about 10 min and included a period of classroom chaos. The chaos was measured as a sign of deeper learning as students grappled and struggled with the technology, reached consensus over specific images and meanings, and worked together to accomplish the outcomes. The instructor facilitated some of the technological challenges, while also letting students wrestle to find solutions in a team-based environment. The learning and collaboration that unfolded during this “process” period created a sense of student ownership and accountability.

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Final video links were also uploaded to the course online discussion forum on the learning management system for reflection. The reflective component included: • Entire class watching each of the 30-s to 1-min videos. • Brief discussion period after each viewing. Student teams explained the specific needs and values addressed in the visuals while answering questions and receiving comments from classmates. • Class discussion about the mobile activity itself: • What worked well? Most students commented on the team element being the most valuable part of the scavenger hunt. • What was challenging? Some students confided that there was a period of confusion at the beginning of the lesson when it was not clear what was required. • How did the team work together to accomplish the objectives? Most to all teams stayed together during the scavenger hunt; one student would film and team members shared the search for visuals. • What could have been done differently? Some students reflected that a different mobile app might have worked better after viewing another classmates’ app selection. • How is individual understanding of appealing to needs and values improved by the activity? All students reported an increase in understanding after the activity, including students who performed well on the reading quiz. Some students reported that the collaborative component (team) improved learning. A final post-activity to culminate the lesson included students’ individual comments to other teams’ videos on the online discussion board. Comments required focus on the effectiveness or ineffectiveness of the images to persuade a target audience. Students were asked to post at least one online comment to another teams’ video before the next class period. A rubric that included individual and team participation was used to evaluate students’ work on the entire lesson. The formal assessment of the student application of these concepts was evaluated in the students’ persuasive speeches, which focused on the following outcomes: • Ability to apply strategies to motivate audience to adopt perspective or influence in specific direction • Ability to apply sound reasoning and evidence • Ability to apply motivational appeals and credibility Additional gains were made during this activity that were not included as formal outcomes of the mobile lesson. Students reported the feeling of a deep sense of camaraderie and satisfaction among the teams during the process of creating the

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video. Students had fun learning! Building community with classmates motivated student to reach beyond what the minimum requirements of the lesson asked. One semester, before students returned to the classroom at the end of the scavenger hunt, all teams did one extra video that was not required. All students stood in a long line “high-fiving” each other and jumping in the air, while a classmate captured it on video. The video was posted in the online discussion forum and viewed at the end of the video series in class. This final video gave evidence that students were able to use mobile to collaborate, create, and have fun while learning. Students truly engaged in a community of learning while improving individual understanding during the experience. This mobile lesson case study speaks to the value of both mobile learning itself and the use of the Mobile Lesson Template as a guide in creating a fully designed mobile activity. Students were able to meet the outcomes successfully and improve performance on the formal assessment following the lesson.

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Faculty Learning Community on Mobile Learning

The Faculty Learning Community (FLC) on mLearning was a personalized learning environment in which faculty used both collaborations to explore the “chaos” in mobile. The FLC included a small group of multidisciplinary faculty members engaging in the scholarship of teaching and learning with a semester-long, collaborative environment, structured to provide encouragement, support, and reflection. The FLC discussed pedagogical methods that could be enhanced through the use of mLearning. It was not designed to be just a “how to” class for technology but more as a space for sharing ideas and experiences and for the opportunity to develop an activity or unit that uses mobile to enhance student learning. The group members shared mobile lessons and experiences with the wider university community at a semiannual professional development event following the FLC. The goal of the FLC was to create a fun and safe environment to collaboratively explore, apply, and share mobile technologies and pedagogies to enhance student learning. The outcomes included: • • • • •

Understand how mLearning can support learning. Identify potential technology challenges and possible solutions. Create and apply a mobile learning lesson. Reflect on lesson implementation. Share findings with campus community.

During the semester, faculty participated in “mobile explorations” that utilized mobile apps as well as resources such as a Moodle course, a shared mobile apps wiki, a Twitter hashtag, a Tagboard feed for live collaboration, a Diigo group for web resources, Google Drive for peer collaboration, and asynchronous discussion forums for reflection.

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The faculty participated in further “mobile explorations” where collaboration, evaluation, and reflection were utilized to create and implement a mobile lesson in the classroom using the Mobile Lesson Template. Some “mobile explorations” that faculty engaged in included: • Looking for ways to explore the “flip the classroom” • Exploring the range of uses and develop a way to use a mobile device to increase student engagement • Looking for ways to stimulate students in large classes • Exploring ways that mLearning can support student-generated content (students apply the learning) • Looking for ways to teach beyond the classroom, i.e., virtual office hours, podcasts, and social media The majority of this faculty group added a mobile learning layer to an existing activity. This process allowed each to use a familiar lesson and explore the addition of a mobile component. The final portion of the FLC was to share mobile lessons at a campus-wide event. Faculty facilitated a discussion workshop, Exploring Mobile Learning to Support Students, where participants were asked to identify mobile strategies and/or techniques to integrate into future work as a result of workshop participation. Participants were also given a collection of mobile lessons created by FLC faculty that utilized the Mobile Lesson Template as a model for effective mobile design for higher education learning. This template served as a catalyst for educators, who needed a guide to begin harvesting personal connections that are created when the student’s mobile world becomes integrated into the learning of course concepts.

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Future Directions

The future of mobile learning is wide open. Educators can play a vital role in developing mobile lessons to support authentic learning with collaboration and critical thinking, as well as increasing student engagementthat allows the student to reach far beyond the limits of a classroom. Mobile opens the doors even wider for distance education students accessing all course resources from a learning environment that is free of physical space and time. Suddenly, the student’s personal world collides with the academic world in one of the most amazing learning disruptions ever. Possibilities such as advanced image retrieval technology and student opportunities to pursue relevant and personal learning experiences are just some of the many directions. Rick Oller, from the Marlboro College Graduate School, makes a clear connection to mobile learning potential by discussing its future in higher education in terms of traditional pedagogical structures being left behind and the need for teachers to “innovate, experiment, and be prepared to fail” (Oller 2012). It is this potential that gives educators opportunities to experiment with mobile in the classroom. Teachers

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can adapt existing lessons or create new lessons by using the Mobile Lesson Template as an effective roadmap for mobile lesson creation that provides relevance and personalized learning experiences for millennial students in a world that becomes the infinite classroom. Expanding mLearning to include collaboration across courses and curriculum with trends, such as augmented reality and learning implants, becomes a movement beyond the traditional pedagogies and technologies and into a whole new arena of reexamining and adapting in higher education.

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Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning ▶ How Irish Postgraduate Students Use Mobile Devices to Access Learning Resources

Appendix A: Mobile Lesson Template 1. Assignment Name [Provide a name that includes the lesson concept and the word “mobile.”] 2. Goal [What experience is this providing for the student?] 3. Learning Outcome(s) [By the end of this lesson, what will the student be able to do?] 4. Materials/Resources [Materials, handouts, software, special equipment needed.] 5. Instructions [Specific, concise, step-by-step details of the process that is expected to complete the assignment.] 6. Assessment/Rubric [How the assignment will be graded.] 7. Weighting of this Assignment [Percent of overall grade.] 8. Submitting Assignment for Evaluation [How/where to submit the assignment.] 9. Time Commitment [Expected time to complete the assignment.] 10. Deadline [When is the assignment due?] 11. Feedback Expectations [When/how will students receive feedback?] 12. Examples [Provide an exemplar example so students understand what you’re looking for.]

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13. Technology Considerations: Challenges/Solutions [What considerations are needed to identify challenges for both instructor and student? What potential solutions could solve these challenges?]

Kimberly Vincent-Layton 2013. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Appendix B: Scavenger Hunt Mobile Lesson on Motivational Appeals for Persuasive Speaking Kimberly Vincent-Layton, Department of Communication

Goal In order to be an effective speaker, it is important to consider the emotional impact on our audience, as well as relate our ideas to their emotions, needs, and values. We need to find out what is meaningful to our audience so we can relate to them in persuasive speaking. Work together as a team to discover and capture a variety of objects and/or visuals that include motivation appeals.

Learning Outcome Evaluate at least five different objects and/or visuals that demonstrate motivational appeal.

Materials/Resources • • • •

Smartphone with video or collage app of choice Account with app if needed (Animator, Vine, Flipagram, Instagram, etc.) Wi-Fi Classroom computer with projector to share final video/collage

Instructions You have 20 min to go on a team scavenger hunt, looking and capturing objects/ visuals around campus that appeal to needs and values (think: signage, posters, layout of structures, etc.).

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Include: • Needs – think Maslow’s hierarchy of needs (Maslow 1943) • Values – think general values (culture, family, social), core values, authority values, peripheral values Step One: Scour the campus looking for objects/visuals of any type that demonstrate appeals to needs and values (must include at least one example for need and one for value). Step Two: Use a mobile app, such as Vine, YouTube Capture, Animoto, Pic Stitch, and Photo Grid, to create a video or photo collage of no more than 1 minute; upload it to YouTube, Twitter, Facebook, Animoto, or any site where you can share with the class. Step Three: Think about the purpose and the target audience of your visuals. Answer these two questions in your video: 1. What values are appealed to in the object/visual? Identify the values. 2. What needs are appealed to in the object/visual? Identify the needs. Step Four: Upload your video/collage URL to the Share Your Scavenger Hunt Video Here forum on Moodle immediately following the scavenger hunt. Step Five: Reflection/share out – is the object/visual effective/persuasive to the target audience? What motivational appeal is it an example of?

Assessment mLesson rubric valued at total of 10 points will serve as participation points for this class session. Scavenger Hunt Rubric Criteria Contribution to group (3 points)

Needs and values (4 points) Final hunt results (video) (3 points)

Exceeds expectations Team accepted responsibilities for constructing the hunt and collaborating on the video Team included at least two examples of each: needs and values Video demonstrates an appeal to needs and values by answering all four questions

Meets expectations Team accepted some responsibility for constructing the hunt and some collaboration on the video Team included at least one example of each: needs and values Video demonstrates an appeal to needs and values by answering most questions

Below expectations Team made little contribution to constructing the hunt and/or collaborating on the video Team did not include at least one example of each: needs and values Video demonstrates an appeal to needs and values by answering few questions

Points

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Deadline URL submission due by April 21, 5:00 pm. Replies to classmates’ posts due by Sunday 11:00 pm of Week 12.

Feedback Students will receive classmates’ oral feedback during class share out, classmates’ written feedback in online discussion forum, and instructor feedback posted in Moodle Gradebook by Sunday of Week 13.

Examples Sample Video/Collage • See sample Vine on Moodle. • See sample Animoto on Moodle.

Technology Considerations Instructor will create sample video/collage to demonstrate the final product [Vine, Animoto]. Challenges Variety of devices and apps. Students may spend a lot of time just picking the app. Access to Wi-Fi could be intermittent in some areas. Need accounts created that could potentially take time. Time logging into accounts on classroom computer (to share video/collage). Solutions Ask students if they have a smartphone in class prior to activity. Assign team leaders to choose an app before next class session. If students are not using campus Wi-Fi, be sure to let them know that apps may require data usage on their plan. Have student leader create an account (if needed) before the mLesson.

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Kimberly Vincent-Layton 2013. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

References 7 Things You Should Know About Mobile Apps for Learning. n.d. EDUCAUSE homepage. Retrieved 28 June 2014 from http://www.educause.edu/library/resources/7-things-you-shouldknow-about-mobile-apps-learning Atherton, J.S. 2013. Learning and teaching; bloom’s taxonomy [On-line: UK]. Retrieved 22 July 2014 from http://www.learningandteaching.info/learning/bloomtax.htm Howe, N., and W. Strauss. 2007. Millennials go to college: Strategies for a new generation on campus: Recruiting and admissions, campus life, and the classroom, 2nd ed. Great Falls: LifeCourse Associates. Maslow, A. 1943. A theory of human motivation. Psychological Review 50: 370–396. Oller, Rick. 2012. The future of mobile learning. (Research Bulletin). Louisville: EDUCAUSE Center for Applied Research, 1 May 2012. Available from https://net.educause.edu/ir/library/ pdf/ERB1204.pdf Personalize Learning. n.d. Personalize learning. Retrieved 26 Aug 2014 from http://www.personali zelearning.com Price, C. 2009. Why don’t my students think I’m groovy?: The new “R”s for engaging millennial learners. Excellence in Teaching, June 2009 Wiggins, G.P., and J. McTighe. 2005. Understanding by design, Expanded 2nd ed. Alexandria: Association for Supervision and Curriculum Development. Yu, Calvin Y. 2008. Allowing for change: Chaos theory, learning organizations and the role of the educator. New Brunswick: Rutgers The State University of New Jersey, ProQuest, UMI Dissertations Publishing.

Framework for Design of Mobile Learning Strategies

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Oscar R. Boude Figueredo and Jairo A. Jimenez Villamizar

Contents 1 2 3 4 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Model Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Model Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bases of the Proposed Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Recognition Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Analysis Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Identification Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Bases Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Design Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Implementation Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

In the current peak of development and implementation of mobile applications in educational settings, it is becoming an urgent matter to propose pedagogical approaches that address the complex educational dynamics for mobile teaching and learning. Previous studies have suggested different models to implement mobile technologies in educational settings. However, few of them recognize the specific reality of an educational setting and the difficulties that must be assumed by teachers in mobile teaching design and implementation. Consequently, this O. R. B. Figueredo (*) Academy Technology Center, La Sabana University, Chia, Cundinamarca, Colombia e-mail: [email protected] J. A. J. Villamizar Katholieke Universiteit Leuven, Leuven, Belgium e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_87

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book chapter examines theoretical and empirical work of previous proposals in order to develop a framework of M-learning aimed at teachers who want to innovate their learning environments using mobile devices. To this end, a theoretical and empirical validation of the proposed model in order to design a framework that addresses practical aspects of the context of teachers without forgetting the pedagogical use of mobile technology was conducted. Finally, the results and conclusions of this proposed model are expected to contribute in the construction of an educational model for mobile technology integration.

1

Introduction

It is well known that since the last decade and thanks to the information and communications technology (ICT) revolution, society undergoes a transformational process that has modified the way we relate, work, organize, and learn (Marcelo 2001). It is a society characterized by its network structure (Castells 1997), plus the abundant and permanent circulating information, where knowledge is flexible, fluid, and in constant expansion and movement (Hargreaves 2003). But, above all, it is a society that demands citizens with new competences and skills. These can enable them to be active part of it, as well as to manipulate and update knowledge, to learn continuously, and to adequately choose data. In addition, this networking society also demands citizens capable of adapting to the quick social, cultural, and production transformations, whether material or knowledge type, highly based on ICT development and implementation in every daily sphere. In order to face the historical and social traits of each time, society has made education responsible for the formation of future citizens. However, different from preceding centuries, for the first time students have more abilities than their professors for accessing, manipulating, and transforming data. This situation is generating a school revolution and a rushed race in which many teachers have done their best for incorporating the most recent information and communications technologies for not appearing to be behind their pupils. Nevertheless, quite often they do not know how to do it, and many of them quit their attempts since they perceive the process is not as simple as it appeared to be in countless accessed blogs and websites. But the dilemma with this “race” is that the teaching exercise cannot be seen as such. It must not exist a tension among teacher, students, and resources. On the contrary, the relation between teacher and students should be seen as an aggregate of efforts in which the students’ skills are headed to a joint work. And the teacher becomes a strategist who sees his students’ potential and links it to the available resources according to an adequate strategy that serves defined goals. The students technological affinity makes them keen on teaching models that day by day involve more digital technologies and develop into useful means for innovating the teaching practice. Under this premise, the M-learning may be seen as a model of this joint work of ICT with teaching practice. M-learning includes the use of mobile devices – very popular among students – access possibilities, data management, and mobility

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that might broaden variety and the very same conception of activities that can be done by the teacher. In order to understand these possibilities and the practical reality of the M-learning, it is necessary to be thoroughly clear about its conception, implications, and implementation as learning framework. Hence, this chapter has done an analysis of different theoretical proposals (Sharples et al. 2005; Parsons et al. 2007; Liu et al. 2008; Mohammad et al. 2007; Nordin et al. 2010; Ozdamli 2012), in order to recognize the diverse factors and elements that must be accounted for when conceiving M-learning experiences. These proposals and their results provide an important basis of the present work for designing ICT-mediated learning environments. Additionally, they contribute to the analysis developed here to formulate a procedure that may be used by any teacher or education institution for designing more significant mobile learning strategies. The departure point is the theoretical frame of M-learning and its implications; secondly, the previous works presented by the authors are taken as reference frame. The next section presents the conceptual elements used and the proposed framework, to finish presenting some conclusions and proposals for future works.

2

Mobile Learning

In order to understand the implications of mobile learning, first of all it is necessary to acknowledge what the diverse authors who are working on this topic say about it. For some of them (Caudill 2007; Pinkwart et al. 2003; Mostakhdemin-Hosseini and Tuimala 2005; Georgiev et al. 2004; Keegan 2001), M-learning can be seen as an extension of the E-learning because it is an E-learning supported on mobile devices (Quinn 2000). For some other authors, it is a support of the in-classroom processes (Wang 2004; Mutlu et al. 2005; Walsh 2010). Nevertheless, for the present work M-learning is much more than the abovementioned, coinciding with Sharples et al. (2005), who proposes that in order to understand M-learning, it must be acknowledge that the learning process exceeds the physical frontiers of the classroom and the education institution. Likewise, it should be understood that students learn anytime, anywhere, when they go or are somewhere, taking an idea or resource from the context and relating or applying it to other contexts, or relating previously acquired knowledge to present processes (Sharples et al. 2005). Thus, designing M-learning experiences firstly implies the teacher awareness on the education process nature, based on mobile devices, and the identification of their limits as well as their multiple benefits (Parsons et al. 2007; Liu et al. 2008; Mohammad et al. 2007; Nordin et al. 2010). Finally, the teacher must reflect on his teaching practice and the learning experiences he wants to encourage in his or her students, plus the relationship among the benefits he hopes to acquire facing the effort he must do. In a nutshell the quid lies on acknowledging and understanding the weaknesses and strengths that may rise when incorporating mobile learning

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strategies (Motiwalla 2007; Ellis 2003) as the product generated from the permanent reflection on the educational practice of the teacher.

3

Model Design

The model here proposed is part of a research project focused on design mobile learning strategies. However, at the early stages of the project, it was necessary to formulate and validate a new model because the existing models, by themselves, did not respond to the needs of the project. Then, this is the followed process: First, a review of previous studies that have discussed and designed mobile learning strategies was conducted (Sharples et al. 2005; Parsons et al. 2007; Liu et al. 2008; Mohammad et al. 2007; Nordin et al. 2010; Ozdamli 2012). The conclusions of the review, in light of the project needs, pointed that although each of the proposed models contributes significantly to the process of designing M-learning strategies, those contributions are wide-ranging from a conceptual stand. Consequently, these models failed to connect with the particular necessities and expectations that can be found in different educational contexts. In other words, these models did not take into account that any teacher must be able to reflect on his pedagogical exercise that, in turn, generates a mobile learning strategy design significant for the educational context. Secondly, the process followed by the authors for designing ICT-mediated learning strategies and environments was contrasted against the processes proposed by Sharples et al. (2005), Parsons et al. (2007), Liu et al. (2008), Mohammad et al. (2007), and Nordin et al. (2010), for designing mobile learning strategies. This contrast’s findings evidenced that the present framework proposals as well as the designing process used by the authors were supplementary, so it was better to design a new unified framework. Next, a new model of mobile learning strategies that unifies the theories of the main proposed models was designed. Additionally, it offers teachers a clear process departing from recognizing the nature of M-learning and carrying it to the design of an M-learning strategy capable of supporting or supplementing his teaching practice. Afterwards, the framework was validated by a board of eight experts on integrating ICT to teaching processes attached to the Academy Technology Center of La Sabana University. The proposed framework was presented to these experts, and they were asked to assess it from the process they would follow when designing ICT-mediated learning strategies, as well as in light of their experience on integrating mobile devices in academic processes. This validation’s results were useful for adjusting some aspects of the framework regarding the elements that needed to be considered in each of the stages, as well as these stages’ names. Finally, based on the theoretical validation, a practical validation took place departing from three different scenarios. The first one was done through designing the mobile learning strategies that were used in the research with junior school students coming from two educational institutions of the municipality of Chía, Cundinamarca State, Colombia. The second one was the model used for university

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teacher training on designing mobile learning strategies, thus encouraging the proper use of these devices in academic processes. The last one was used for training students of master’s in computer science in mobile learning strategies design, as topic of the course Teaching and Learning in the Knowledge Society.

4

Model Background

For developing the present framework, a review of the previous proposals aimed at guiding the structural features of this framework, as well as assessing its range and relevance according to the M-learning concept presented in this chapter, was conducted. The final result was a grounded and updated proposal that includes an inductive analysis on the incorporation of mobile devices under a pedagogical strategy. The contribution is a detailed elaboration of the process that permits the reflection on the different stages of the M-learning project development from an educational and nontechnological perspective. It is important to highlight that the evolution of M-learning models has made their way from the technological problemsolving viewpoint more than from an educational perspective. Some proposed systems outline designs focused towards the technological process of information systems that allow sending data and the needed infrastructure for developing these processes like the models of Kinshuk (2004) and Barker et al. (2005), which in spite of it are taken into account due to significant technological implications. As described in detail by Maniar and Bennet (2007) and Yong et al. (2010), there still are several restrictions that must be accounted for with mobile devices when analyzing M-learning like screen size and resolution, storage, bandwidth, processing speed, and battery life, plus interoperational and standardization software aspects. In addition, there were found models focused on the adoption and attitude facing new technology, for example, Shih’s Mobile Learning Model (Shih and Mills 2007) that considers mobile devices as elements that may motivate students. This model is based on a motivational design under the use of collaborative discussions and interactions on mobile devices. The sequence is built as a cycle where activities are developed to generate motivation, relevance, satisfaction, and trust in the developed processes. Likewise the Technology Acceptance Model (Davis 1989), which has been accepted for diverse M-learning experiences (Ha et al. 2007; Yong et al. 2010; Liu et al. 2010; Suki and Suki 2011), is focused on technology adoption departing from considering some variables such as: perceived usefulness, perceived ease of use, attitude, behavioral intention, and actual usage, which are key points for learners adopting technology in a learning environment. Besides the motivational aspects, some other models are organized according to their function in the learning environment. As already mentioned, it could be taken as support of the learning activities. For Lan and Sie (2010), the M-learning is a learning model that enables students to obtain learning resources anywhere and anytime through communications, mobile devices, and the Internet. These authors claim to have found, in an experience review, diverse learning activities supported by mobile devices that include “(1) improve communication and collaborative

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interaction, (2) provide more learning opportunities for geographically dispersed persons and groups, (3) encourage active learning, (4) enhance learner’s feedback process, (5) emphasize time on task, and (6) acquire content quickly” (p. 723). However, beyond the particular aspects about using mobile devices in a learning environment, it is necessary to analyze an M-learning model in light of the very same teaching practice complexity, the generated interactions, and the institutions’, individuals’, and resources’ roles, as well as the distinctive features entailed by taking learning out of the classroom under the “anytime anywhere” learning model. Taking into account this characteristic, Parsons et al. (2007) designs a model that includes four perspectives: “generic mobile environment issues, learning contexts, learning experiences, and learning objectives” (p. 1). Taking this model into practice, it is able to evidence the significance of design and context when implementing an M-learning model and to describe in detail elements of each of the perspectives that must be observed when designing mobile learning environments in all their stages. In his proposal of generating an M-learning theory, Sharples et al. (2005) go a little deeper into the meaning and sense of the “coming to know” process, starting from analyzing the link learning – technology for which they depart from a reflection process that allows them to differentiate what is “special” in the mobile learning compared to other learning activities. This point turns out to be the core aspect to understand the need of generating an M-learning model as well as to assess time, space, communications, data, and technological interactions that go under changes in such a model. In addition, they ponder to consider the amount of learning processes that occur out of the formal educational scenarios. Particularly, focusing in those interactions where students engage with their surroundings to create impromptu learning spaces anywhere they are. This finally entails the need of a learning theory that takes into account the current practices that generate successful learning and that considers the ubiquitous use of technology. It ends up to be an M-learning theory based on the learning analysis “as a cultural-historical activity system, mediated by tools that both constrain and support the learners in their goals of transforming their knowledge and skills.” These developed aspects enable us to clarify some of the complexity associated with a learning process with mobile devices, aspects that turn to be the core element of the proposal developed in this chapter. The present framework attempts to approach more thoroughly the process of M-learning designing starting from the teaching practice. The main purpose is to clarify the theoretical relationship of learning models with mobile devices heading it to specific actions developed by teachers when designing learning environments and strategies.

5

Bases of the Proposed Framework

As can be seen in Fig. 1, the framework is divided into six stages: recognition, analysis, identification, bases, design, and implementation. Each of them has been designed as part of a process to be followed by the teacher and/or tutor to build

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Framework for Design of Mobile Learning Strategies

Recognition • M-learning Features • Users & Roles • Technical & Developmental Features • Communication Process

Analysis • M-learning Benefits • Inclusion scenarios • Educational Practice Analysis • Pedagogical Innovation

263

Identification

Bases

Design

• Supply • Support • New Educational Experience • U-learning Encouragement • Feedback Processes

• Coherence towards Established Pedagogical Bases • For new experiences: • Learning Goal • Context Features • Pedagogical Approaches

• Cognitive Processes • Context Features • Contents • Roles • Devices Features • Aims & Goals • Feedback • interaction

Implementation • Context Features • Needed Products • Devices Features • Educational Resources • Evaluation

Fig. 1 Framework for mobile learning strategies design

effective mobile integration strategies. This process aims mainly to respond to his educational context needs, although integration purpose in the strategy is rooted by broader society’s trends regarding ICT incorporation.

5.1

Recognition Stage

The first stage, recognition, suggests that for designing learning strategies supported or mediated by mobile devices (M-learning), as proposed by Parsons et al. (2007), Liu et al. (2008), and Mohammad et al. (2007), it should depart from what M-learning is in terms of its own features: Mobility: it enables the teacher as well as his students to be in touch when they are out of the conventional face-to-face communication spaces as the classroom or inside the educational institution. Ubiquity: it is the feature that enables learning process generation anywhere, anytime, thanks to the services available for these devices. Contextualized processes: it is the feature that allows designing and implementing learning strategies in which the context or scenario becomes an active and significant actor in students learning process. Active learning support: applications for mobile devices are designed for encouraging processes of communication, interaction, collaboration, and collective construction among devices’ users. Additionally, they also allow users to have a personalized experience that contributes to make them the center of the learning process. Diversity: it is the feature offered by mobile devices, in contrast with laptops or desktop computers, because they include a wide range of options in hardware and software resources for strategies designed by teachers. Augmented contents: it is the characteristic that enriches didactic contents, activities, and strategies implemented on these devices, thanks to the great diversity and services offered for them. Likewise, this first stage coincides with the ideas of Sharples et al. (2005), Parsons et al. (2007), Liu et al. (2008), Mohammad et al. (2007), and Nordin et al. (2010) regarding the recognition of the different users of these devices as well as

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their role in the learning process. It also coincides with Parsons et al. (2007) and Nordin et al.’s (2010) proposal on the recognition of technological needs and implications involved in the development like graphic interphase and adequate handling of audiovisual resources, even though they claim that there are many other aspects to bear in mind: Compatibility: because there is a huge diversity of devices and operational systems in the market that separately demand different hardware and software. Diverse operational systems: they, as well as their different versions, make some applications and services only available for some students. Connectivity: neither the teacher nor the students have the same network content access level, and it could generate difference regarding what students can or cannot do. Processing capacity: this feature, associated to memory capacity, implies that any teacher development will take longer execution or opening times of the demanded resources in some devices than in some others. Memory capacity: most devices have limited RAM capacities, making their execution of operations difficult, and simultaneously play videos and images. Finally, in accordance with Parsons et al. (2007), this stage proposes a careful thinking on the different aspects related to the communication process between teacher and students and among students.

5.2

Analysis Stage

This stage proposes the teacher to ponder about the students’ learning benefits of incorporating mobile learning strategies in his teaching practice. However, it is important to point out that this incorporation must coincide with a thoughtful position of the teacher about how, when, why, and what for they are included in his teaching practice as well as the possible changes which might occur as a result of mobile learning strategy integration. From this process, the teacher must reflect on his educational practice reality, i.e., on what learning is for him, his students’ characteristics and expectations, his own expectations, and the educational strategies and resources he is able to incorporate, plus the way of assessing his students’ learning (Colomina et al. 2001). It is worth mentioning that including M-learning is not an isolated process of teaching, and it is precisely in this thinking where the pivot lies in which the present teacher proposal and the M-learning strategy formulation spin around. In the end, after that careful thinking, the teacher must come to a decision on whether it is better to design a mobile learning strategy oriented towards supporting or supplying his didactic strategies or, on the contrary, to design an M-learning strategy oriented towards generating a pedagogical innovation. In this way, different from Nordin et al. (2010) proposal, the teacher is expected to understand the M-learning before deciding on his strategy core theories, and, based on that, to

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recognize its function in the educational context and pedagogical goals. Nevertheless, this proposal coincides on the importance of including, in any mobile learning strategy development model, the careful thinking on what is the most suitable learning theory for supporting the didactic strategies to be used.

5.3

Identification Stage

This stage proposes that the teacher, at this point, must decide if including M-learning will be done for supporting or supplying a didactic strategy already designed or if he is about to propose a new educational experience. In order to make that decision, the teacher must follow an analysis process that includes the general characteristics of the educational context, learning goals, appropriateness of changing his current strategy, benefits and drawbacks of doing a new intervention, and actions to be taken when deciding on one of the proposed ways, among others. However, aside from the decision made, the next issue to ponder about is whether the strategy about to be used is aimed at surpassing the traditional space frontiers of the educational process or if, on the contrary, it will be held inside the institutional area. The already mentioned decision is crucial because carrying on a ubiquitous education process or U-learning implies the teacher planning ahead diverse issues, for example, communication processes, geospatial location of resources, activities and contents, counseling process, query solving, and assessment, plus didactic sequencing plan to be followed over nontraditional spaces and its relationship with what is going on inside them, among others. Moreover, it is important that at this stage the teacher decides how to develop the feedback process by determining times, tools, and strategies to be used. For example, in order to pursue a feedback strategy where students were asked to propose a problem solution, it can be decided that this process would take place across pseudo-real time over an instant messaging application like WhatsApp. It can also be decided that feedback for all the students would be individual through a group created for that aim so all the students would learn through the process.

5.4

Bases Stage

The fourth stage, bases, proposes the teacher can follow two different ways based on the decision made at the identification stage. If the decision is supporting or supplying an already designed strategy, firstly its pedagogical bases should be revised for assuring that the devices’ activities or processes engaged are in agreement with these bases. The next stage consists in establishing a learning goal for these activities, activities that later should be formulated taking into account the targeted population features, as well as the context in which they will be held. For example, the type of relationship between context in which the experience takes place and the contents, resources, and activities that students will develop there must be decided. Likewise, the characteristics of the population must be established,

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Table 1 Mobile learning strategy bases Mobile learning strategy bases Learning Pedagogical strategies approaches

Population features

Environment features

Possible activities

like study level, technology uses, type of communication, and other elements that could be significant for the proposed activities. In contrast, if the teacher decision is to generate a new experience, the process must start by formulating one or more learning goals. In this point, the possible pedagogical approach or approaches that will be used for designing the mobile learning strategy must be decided. Also, general features of the population and the environment where the strategy will be held must be considered. Lastly, a list of possible activities that may be used is proposed. Moreover, in any of both scenarios, at the end of this stage, he must provide a table, as the one shown next, describing learning strategies, pedagogical approaches, possible activities, and the most relevant features of the population and environment where the strategy will be developed (Table 1).

5.5

Design Stage

This stage proposes the teacher to design, at this point, the mobile learning strategy. According to Parsons et al. (2007), Liu et al. (2008), and Nordin et al. (2010), it is necessary to decide and to organize the content to be used, the aims and goals to be reached, interaction processes and feedback processes, as well as the tools to be used, all aimed at achieving the purpose. Even though different from the proposals of Sharples et al. (2005), Parsons et al. (2007), Liu et al. (2008), Mohammad et al. (2007), Nordin et al. (2010), and Ozdamli (2012), this stage proposes the teacher to decide the cognitive processes he wants to encourage or strengthen along with the strategy, as well as the role of devices, students, and teacher. Next, each of these elements will be discussed: Cognitive processes: the significance on deciding and acknowledging the cognitive processes to be strengthened by means of a mobile learning strategy is grounded on two elements: first, where the teacher must establish a relationship between activities and student’s cognitive processes that he is interested on strengthening and, second, where the teacher must be able to contrast the cognitive development level of his students with the activity type he wants them to develop. Computer skills: the teacher should identify the computer skills among the population where the mobile learning strategy will be held. This diagnosis will ease the teacher decision on whether to undertake a training process prior to implementing the strategy. Contents: the teacher must decide on the content, resources, and their depth level in order to achieve the strategy objectives.

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Table 2 Mobile learning strategy design Mobile learning strategy design Learning goals Pedagogical approaches Population features Educational context features Needed cognitive processes Cognitive processes to reinforce Topics Computer skills Contents Resources Activity 1

Activity 2

Roles

Description Aim and goal Feedback Interaction Environmental features Description Aim and goal Feedback Interaction Environmental features Students Teacher

Devices

Roles: the teacher must decide his students, the mobile devices’ and additional tools’ roles, as well as his own role in the strategy. Aims and goals: the teacher must decide each of the learning aims and goals for each of the activities to be developed with the strategy. Feedback: as already mentioned, it is crucial that the teacher sets the mechanisms and tools he will use in order to do his student feedback process, as well as the time for it and the activities that will receive individual or group feedback. Interaction: lastly, it is necessary to decide how the interaction process will be held among students and between teacher and students, as well as the tools to be used for that purpose. At the end of this stage, as what happened in the previous stage, the teacher should have a chart with the following labels (Table 2):

5.6

Implementation Stage

This last stage proposes the teacher, before implementing the mobile learning strategy, must decide what are the educational resources demanded by the strategy. Accordingly, he must assess which of them are available on the net to be easily

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Table 3 Mobile learning resource implementation Resource 1

Resource 2

Product1

Tool 1

Description Activity Reusing Description Activity Reusing Description Activity Reusing Description Activity Reusing

Adapting

Producing

Adapting

Producing

Adapting

Producing

Adapting

Producing

reused or adapted and which of them must be produced. In the same way, it is necessary to establish what educational products, tools, applications, or materials are available to be used or which of them need to be adapted or produced for diverse platforms (Table 3). Lately, there has been an important movement that insists in a more collaborative work between teachers and promotes the use of resource repositories to share “reusable learning objects” or RLOs. However, recent research has raised questions regarding benefits in the reusability approach in teaching and learning (Sweet and Ellaway 2010). Accordingly, the assessment between creation and reuse of learning objects is a key factor for the following implementation. Unfortunately, the scope of this chapter is limited to the general implications of the stage and does not include the foundations for assessing or developing resources. But a careful examination of the potential impact of the decision taken in this stage is suggested, both from the pedagogical point of view and on the practical considerations for implementing the learning strategy. The foregoing is important because the context can play a significant role in shaping the experience with mobile devices. For instance, in some rural areas of Latin America, there is very low or no Internet connectivity, which can affect the intended use of some resources that rely on network access. Given these difficulties, a good learning experience could be transformed in a stressful experience for teachers and students. In a recent implementation with a group of 300 teachers of Fusagasugá (a small city in Colombia), this framework was validated. This stage was essential to analyze and modify educational resources according to the proposed strategy, the schedule to implement, and the infrastructure and connectivity available on every educational institution. In some cases, when the context has a strong impact on the effective implementation of the strategy, it is recommended to produce particular resources or, at least, make use of customizable resources that can be adapted to required situations. Finally, the last point of this stage is to encourage teachers to reflect on the evaluation process, responding to questions about what, when, and where to evaluate. The natural flexibility of mobile devices and a good learning design opens up

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new possibilities for learning and teaching. However, the final results depend on a consistent relation between the different stages of design and an adequate implementation.

6

Future Directions

This work has presented and discussed a theoretical frame for designing mobile learning strategies and has taken as its departure point those works done by diverse authors such as Sharples et al. (2005), Parsons et al. (2007), Liu et al. (2008), Mohammad et al. (2007), Nordin et al. (2010), and Ozdamli (2012). It has also taken into account the process followed by its authors as teachers when designing learning strategies mediated by ICTs. Nevertheless, different from the theoretical proposals presented by the mentioned authors, this work is oriented towards offering teachers and researchers interested on mobile learning theoretical and practical tools that enable them to design and implement mobile learning strategies that might support or supply their teaching practice. Likewise, it has been stated how important it is for designing significant mobile learning strategies that the teacher is aware of the educational process nature mediated by mobile devices, of its limitations and benefits. As a result, the teacher would be able to benefit from the current natural relationship between students and mobile devices. Similarly, three different ways of integrating mobile devices to teaching-learning processes have been introduced. The first one consists in doing it as supporting the ongoing process developed by the teacher by including new communication channels. The second one consists in using it as supplying the ongoing process developed by the teacher through activities that might not to be done in the classroom by the students and that supply their educational process. The third and last one is to incorporate a new learning strategy in such a way that the teacher innovates his teaching practice. It is worth mentioning that eight experts in ICT’s integration to educational processes, coming from the Technologies for the Academy Center of the University of La Sabana, firstly assessed the proposed framework; they requested some adjustments regarding the location of some of the framework components but not about including or suppressing any of them. However, the practical evaluation of it is being held by ten teachers in charge of different educational levels, who are also students of master’s in computer education at the University of La Sabana and who are members of the research area on designing learning environments mediated by ICTs. The results of this implementation will be published in a subsequent work. Likewise, the results of the present work are being used for designing an educational process oriented towards higher education teachers whose main goal is contributing to design mobile learning strategies as significant for the teacher as for his or her students. If the teacher departs from a deep understanding of M-learning, it will enable him or her to design mobile learning strategies that fit the needs of the population.

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Based on the results achieved in the mentioned processes, the framework will be adjusted and research projects will be designed for deciding how much the teacher understanding of M-learning contributes to designing significant mobile learning strategies for students and deciding on those processes that contribute to developing good practices by teachers.

7

Cross-References

▶ Adoption of Mobile Technology in Higher Education: An Introduction ▶ Characteristics of Mobile Teaching and Learning ▶ Design Considerations for Mobile Learning ▶ Design of Mobile Teaching and Learning in Higher Education: An Introduction ▶ Development of Mobile Application for Higher Education: An Introduction ▶ Evaluation of Mobile Teaching and Learning Projects: An Introduction ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts ▶ Mobile Learning and Engagement: Designing Effective Mobile Lessons ▶ Transformation of Traditional Face-to-Face Teaching to Mobile Teaching and Learning: Pedagogical Perspectives

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Foreign Language Teachers as Instructional Designers: Customizing Mobile-Assisted Language Learning Technology

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Michael Barcomb, Jennica Grimshaw, and Walcir Cardoso

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Input and Autonomous Learning in the FL Classroom via Text-to-Speech Synthesizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Levels of Teacher Involvement in Customizable MALL Materials . . . . . . . . . . . . . . . . . . . . . . 4 FL Teachers as Instructional Designers and Gamifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Customizing Mobile Technology to Increase TL Interaction: The Pedagogical Use of TTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Adapting Mobile TTS Materials: Level 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Modifying Mobile TTS Materials: Level 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Creating Mobile TTS Materials: Level 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

274 275 277 278 280 281 282 283 286 286 287

Abstract

In second or foreign language (L2) education, there is a dire need to increase student exposure and interaction with the target language (input) so that they can initiate or improve their learning (e.g., Ellis 1997). This is particularly true in foreign language environments in which students may not encounter the target language outside the classroom (Wang and Castro 2010). Mobile-assisted language learning (MALL) is gaining popularity for just this: it encourages learners to engage in learning without limitations of time and space (Miangah and Nezarat, Int J Distrib Parallel Syst 3(1):309–319, 2012). Although there exists an abundance of software applications for L2 learning, they are generally M. Barcomb (*) · J. Grimshaw · W. Cardoso Education, Concordia University, Montreal, QC, Canada e-mail: [email protected]; [email protected]; [email protected] © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_130

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pre-made and designed for the general population of teachers and learners without considering individual interests and abilities. To address this issue, a recent proposal by Barcomb, Grimshaw, and Cardoso (Language 2(3):8, 2017) categorizes three levels of teacher involvement in the development of MALL materials: (1) adapting pre-made resources, (2) modifying resources, and (3) creating resources. In this chapter, we illustrate the application of the abovementioned proposal within the framework of each level by exploring design options that teachers can make by using customizable text-to-speech technology to increase student interaction with the target L2 outside the classroom. The authors suggest that this approach has the potential to address some of the limitations that characterize the traditional L2 classroom, to encourage teachers to create relevant and enticing materials for their learners, and to motivate them to take control of their MALL-enhanced pedagogical experience.

1

Introduction

The modern foreign language (FL) teacher is often expected to be technologically minded, an expectation that places an added burden on teachers to implement cutting-edge, pedagogically sound language learning activities (Godwin-Jones 2015) (see also ▶ Chap. 49, “1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation”). Teachers are also often expected to facilitate outof-class practice, as FL students require additional access to target language input because the amount of in-class time is usually limited, particularly in the foreign language context (Munoz and Collins 2016). To address these two issues by exploring the role of teachers as mobile-assisted language learning (MALL) material designers and “engineers,” Barcomb et al. (2017) proposed three levels of teacher involvement with MALL technology, which enable instructors to customize and/or create material for their learners without prior programming experience. These three levels range from adapting pre-made materials at Level 1 to modifying pre-made materials at Level 2 and creating materials at Level 3. The goal of this chapter is to illustrate the implementation of this proposal in a MALL environment. As such, it positions FL teachers as instructional designers with knowledge to help them make appropriate decisions when using MALL resources. In order to avoid the misallocation of institutional resources on modern technology, it is imperative to understand that instructional design, not technology, is what is most important to help students achieve learning outcomes (e.g., Bernard et al. 2004) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Accordingly, this chapter explores how different paradigmatic approaches to L2 teaching may enable instructional designers to approach MALL technology at all three proposed levels, with multiple perspectives and rationales for customizing MALL materials. Due to the pedagogical orientation of this chapter, the proposed customized materials will be explored from a teacher-determined perspective (Brandl 2002), which positions the teacher as the individual responsible for pre-screening and implementing material in a mobile-assisted educational setting. To achieve these

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goals, a specific type of technology and its affordances are explored: text-to-speech (TTS or speech readers), a widely available technology that reads aloud written texts which may serve as a pronunciation model (see also Liakin et al. 2017, for a similar approach). As TTS can be made available at all three levels, this chapter examines how instructors can adapt and/or customize its use for their students and specific contexts. This chapter begins by discussing the importance of the L2 input for language acquisition, which serves to motivate the argument for teacher-generated resources to extend the FL classroom. Subsequently, the chapter will introduce Barcomb et al.’s (2017) proposal for the establishment of three levels of teacher involvement in MALL material customization and, within this approach, discuss the role of the teacher as an instructional designer and/or MALL engineer. Via the implementation of these three levels, the chapter then explores how FL instructors can adapt and/or customize available TTS software in a MALL setting to increase chances for exposure to FL input. The ultimate goal of the chapter is to help FL teachers approach customizable MALL design in a way that enables them to transform student interaction with the target language anytime anywhere, outside of the language classroom.

2

Input and Autonomous Learning in the FL Classroom via Text-to-Speech Synthesizers

According to Krashen (1985, 2003), exposure to target language (TL) input is essential for language development. In his input hypothesis, the author posits that language acquisition occurs primarily through the processing of the input that learners receive. As a consequence, language learners need a significant amount of exposure to the TL to develop their language skills. While Swain (2000) argues that language production, or output, is also essential in SLA, the ability to perceive sounds generally precedes the ability to produce them (Baker and Trofimovich 2001), although some studies suggest both perception and production develop simultaneously (e.g., Thomson 2012). Therefore, access to comprehensible input remains essential in the language learning process (Krashen 1985, 2003). Learners in foreign language settings often have limited exposure to the TL in their daily lives (Bione et al. in press; Collins and Muñoz 2016), which leaves students to their own devices to seek out opportunities to practice and develop their language skills. While there are numerous resources freely available online, Lai et al. (2016) found that language students often feel lost when attempting autonomous learning, as they do not know where to begin and where to find the information they need (see also ▶ Chap. 10, “Design and Implementation of Chinese as Second Language Learning”). Due to their unpreparedness for the task, their participants expressed interest in teacher guidance for out-of-class activities, as their teachers would presumably have the expertise to provide them with direction and assistance in choosing effective resources. In a teacher-determined approach to developing language materials online, the role of the instructor is to recommend resources and

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select activities that they feel their students would benefit from (Brandl 2002). Such an approach enables teachers to preselect materials for out-of-class interaction with the target language, without placing the burden on students to find or develop the materials themselves. While teachers have access to an endless supply of applications (apps henceforth) and computer programs for language learning, deciding on which ones to use with their students can be overwhelming (see also ▶ Chap. 26, “Development of Application to Learn Spanish as a Second Language: Lessons Learned”). One example of a readily available program and/or feature available on all computer platforms and in many apps is text-to-speech (TTS) software. Also known as text readers, TTS are computer programs that automatically transform written text into speech, thus enabling the computer to “talk” or “speak” to the user in different accents and voices representing speakers of different genders, age groups, etc. (see Handley 2009 and Liakin et al. 2017 for a discussion of TTS’s pedagogical affordances). As such, TTS can provide varied and customizable listening practice and pronunciation modelling that is easy for teachers to implement. In daily life, synthetic voices are often used to replace human speakers to automate or facilitate tasks (e.g., announcements in public transit systems, reading online texts to ease eyestrain, GPS systems). While the quality of synthetic voices has been negatively assessed in the past (e.g., Bossemeyer and Hardzinski 2001; Nusbaum et al. 1995), modern TTS voices have become significantly more natural and intelligible when compared with earlier voices (see Bione et al. in press for a current evaluation of TTS voices). These systems are also increasingly accessible as they are already built into many desktop software applications (e.g., Microsoft Word), apps (e.g., Quizlet), and mobile devices (e.g., smartphones, tablets); importantly, there are many free options available. A popular example of a free and multi-platform TTS system is Google Translate (https://translate.google.ca), available online and as a mobile app. Another freely available TTS system is Quizlet (https://quizlet.com), an app that offers teachers without programming experience an opportunity to create sets of online vocabulary flashcards that provide pictures and associated TTS-produced voices. By having access to TTS on mobile devices, language learners may gain even more access to the target language outside of the FL classroom (see also ▶ Chap. 34, “Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts”). With mobile technology becoming a permanent fixture in modern society, there are increasing opportunities for teachers to customize MALL experiences for their students. MALL may be particularly effective as it helps learners and teachers overcome the traditional roadblocks to language learning such as the limitations of time and space (Miangah and Nezarat 2012). As such, MALL materials can enable teachers to provide materials for their students for use on the go, thereby increasing learner’s access to input in the TL. However, increasing access to TL input through customizable, mobile TTS technology is contingent upon teachers being able to match their resources and abilities with the available technology to create mobile TL interaction opportunities for their students. The next section introduces three distinct levels of teacher involvement in customizable MALL materials that provide teachers

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without programming experience with an overview of how they can become involved in the development of mobile materials for their students.

3

Levels of Teacher Involvement in Customizable MALL Materials

While teachers have endless options for utilizing pre-made MALL software, it is possible that many are reluctant to take advantage of the technology because they are unaware that they can be easily customized, without the need for sophisticated expertise or programming skills. To encourage FL practitioners to work with the ever-expanding pool of customizable MALL materials and resources, Barcomb et al. (2017) proposed three levels of teacher involvement in MALL material creation, starting with adaptable pre-made materials (e.g., Duolingo), and moving toward customizable materials (e.g., Quizlet flashcards) and, finally, teacher-created materials (e.g., a customized Moodle course; see Table 1 for an illustrative overview of the three levels, where the gray cells show the novice-to-expert gradience nature of Barcomb et al.’s proposal). By introducing instructors to the three levels of teacher involvement in customizing MALL material, we aim to enable new “MALL engineers” to choose the level appropriate to their resources and skills (e.g., time, money, skills in the use of computer and smart devices) and, indirectly, their students. For example, MALL engineers do not have to work at Level 3 – the most complex level of teacher involvement – to create effective materials for their students. Conversely, although pre-made materials at Level 1 may seem too inflexible for customized learning, they can still offer students a great deal of interaction with the TL both inside and outside the classroom. To improve the development of computer-assisted language learning (CALL) materials, Caws and Hamel (2016) called on teachers to work as “CALL engineers,” applying a hard science approach to the development of L2 materials. Following their appeal, Barcomb et al. (2017) based the development of their three levels of

Table 1 Barcomb et al.’s (2017) three levels of teacher involvement using TTS Choose from pre-made content Modifying pre-made content Create own content Create own activities Examples using TTS

Level 1 Yes

Level 3 Yes (optional)

No

Level 2 Yes (optional) Yes

No

No

Yes

No

No

Yes

Duolingo, Google Translate, Natural Reader

Quizlet, Tinycards, Anki

TTS embedded in apps (e.g., Quizlet via Moodle)

Yes (optional)

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teacher involvement on activity theory (e.g., Engeström 2014), which enables teachers to isolate and examine different aspects of human-computer interaction to effectively link them together to create MALL resources. According to this theory, each aspect of an activity (e.g., the targeted language skill, the hardware, software, how students interact with the software or the activity) is vital to understanding how customizable technologies such as mobile TTS can help students achieve the desired learning outcome(s). As a MALL engineer, the teacher plays a central role in developing materials that their students can use online or via apps, within a spectrum that spans from teacherdetermined to student-determined materials (Brandl 2002). On the teacherdetermined end, the teacher selects the materials and bears the responsibility of developing the activity. Conversely, the amount of knowledge and expertise (e.g., developing comprehension assignments; Brandl 2002) required by students increases as approaches become more student-determined. While students desire guidance to locate worthwhile out-of-class materials (Lai et al. 2016), there are still opportunities for teachers to shift the responsibility of material creation to the students, so “the teacher’s roles vary from being a facilitator, designer, and guide to a resource person” (Brandl 2002, p. 89). As will be discussed, this approach lends itself to increasing opportunities for TL interactions in a mobile setting, ranging from more behaviorist to more constructivist activities across the three levels. Providing practitioners with a feel for how to approach material development may therefore enable them to apply specific pedagogical techniques to MALL technology at a level that matches their digital literacy, resources, and their student clientele’s needs and technological skills. FL teachers face an inherent pressure to have advanced technological knowledge; however, for actually building the materials, teachers are likely left to their own devices as they are not typically provided with up-to-date training (Godwin-Jones 2015). Even when provided with training and resources, teacher trainees do not always view themselves as future developers of CALL tasks (e.g., Kuure et al. 2016), as the role of the teacher as a CALL developer has not yet been clearly established. A teacher-determined approach at Level 1 may still be difficult for practitioners, as sifting through the available MALL software can be overwhelming; it is therefore essential to examine each element of a chosen software to determine its effectiveness as a learning tool. As teachers work across Barcomb et al.’s (2017) three levels, discussed above, they have more chances to enhance the digital environment around the object, which requires an increased awareness of how to use the available hardware and software to help students interact with TTS technology in an online classroom.

4

FL Teachers as Instructional Designers and Gamifiers

Instructional design is best described as a problem-solving activity (e.g., Carliner 2015), whereby the goal is to create materials that enhance a learner’s ability. Instructional design, while not bound to the use of educational technology, has an

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extensive history with technological advancements as, for example, the use of summative and formative assessment stemmed from attempting to make effective materials for World War II pilots (Reiser 2001). The military attempted to develop and implement complicated technology to gain an advantage, and as a result, effective training methods were a necessity (e.g., training to become a pilot). Educational technology in the form of instructional media during World War II and more recent uses of instructional television, computers, and the Internet are all technological advancements that have advanced the field of instructional design (Reiser 2001). In this way, technology has expanded design possibilities for instructional design, so the ways that learners can increase their abilities has also expanded. The approach that a teacher takes to educational technology is critical because, where a behaviorist may see an opportunity for operant conditioning, a constructivist may see a chance for students to take ownership in developing their own way to acquire new knowledge (Roblyer 2003). While a full discussion about paradigms is beyond the scope of this chapter, a basic discussion in relation to the design of effective MALL materials is warranted (see also ▶ Chap. 14, “Mobile Learning and Engagement: Designing Effective Mobile Lessons”). Ertmer and Newby (1993) pair behaviorism, cognitivism, and constructivism with three different levels of task knowledge (i.e., high, middle, low). In this way, as students become more proficient with task material, opportunities for more student-created materials become a possibility. This approach also pairs well with Brandl (2002), whose student-determined approach to material development requires students to have a high level of task knowledge. While working within a specific framework is central to helping learners achieve outcomes, paradigms do not need to be viewed as competing approaches to educational technology (e.g., Robinson et al. 2008; Bernard et al. 2004). Accordingly, this chapter focuses on designing mobile TTS activities that are behaviorist in nature but that also lend themselves to constructivist possibilities as students become more proficient with the material. Consequently, the proposed activities fulfill Roblyer’s (2003) recommendation in favor of hybrid approaches to technologyenhanced teaching. Even when teachers gain the ability to develop materials on a clear premise, students may not be motivated to use the materials consistently. One way of addressing this issue is via the use of gamified elements in pedagogy (see also ▶ Chap. 56, “Mobile-Assisted Language Learning: How Gamification Improves the Learning Experience”). While there is indeed a great deal of freedom in instructional design, gamification is a design choice that has become so common in educational technology that it can find a place in all of Barcomb et al.’s (2017) three levels. Video game elements have become prevalent in educational technology because they increase the enjoyment of learning experiences and encourage learners to spend extra time with the learning materials (Aldrich 2005). Bogost (2011) echoes this sentiment by explaining that video games can help learners to gain knowledge by interacting with and deliberately reviewing material to encourage deep learning instead of merely skimming in a unilateral direction. However, without having a clear view of how to develop the learning materials, the use of gamification and modern technology will at best seem like a gimmick (Sykes 2013). Consistent with

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having a clear approach to instructional design, Godwin-Jones (2014) points out that a key advantage to a self-developed game is that it is easier to track data to figure out how the game is being played, which reveals how outcomes correlate with actual game use. Such use of technology is beneficial as instructional designers must measure their results not only during the design process but also by understanding how effective the materials are after implementation, as it is only by following the process through implementation and ongoing maintenance that designers can ensure they have built effective materials (Carliner 2015).

5

Customizing Mobile Technology to Increase TL Interaction: The Pedagogical Use of TTS

This section demonstrates the implementation of the three levels of teacher involvement in customizing mobile TTS technology for pedagogical use, based on Barcomb et al.’s (2017) proposal. As described earlier, due to the teacher-oriented scope of the chapter, these activities will follow a teacher-determined design to materials development, as described in Brandl (2002). Within this approach, the teacher selects and pre-screens the materials, builds assignments, and then makes them available for students. This section also describes and explains the three levels proposed by Barcomb et al. (2017): Level 1 targets the adaptation of Duolingo, Level 2 targets modifying Quizlet TTS cards, and Level 3 targets the implementation of TTS cards into a Level 3 customized Moodle course with teacher-created content and gamified elements (see Fig. 1 for an illustration of the proposed activities using the three levels of teacher involvement in MALL customization). Gamified elements are considered at each level as they have proven to be pedagogically effective in FL research (e.g., Reinders and Wattana 2014; Figueroa Flores 2015).

Fig. 1 TTS, gamified elements, and related activities: three levels of teacher involvement with MALL resources (Barcomb et al. 2017)

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Adapting Mobile TTS Materials: Level 1

Duolingo (Duolingo, Inc., Pittsburgh, PA, USA, http://www.duolingo.com; freely available online as well as for Android and iOS devices) has gained popularity for offering a fun approach to autonomous language learning, particularly due to its pre-defined learning paths, user-friendly interface, and built-in gamified elements. Consistent with MALL software at Level 1, the normal Duolingo user interface does not allow language learners to choose which features to target. This, however, does not mean that Duolingo’s resources lack strengths, especially considering that they can introduce new vocabulary, provide comprehension activities, and motivate students with gamified elements within an aesthetically pleasing interface (see also ▶ Chap. 25, “Developing an Adaptive Mobile Tool to Scaffold the Communication and Vocabulary Acquisition of Language Learners”). To create a private learning space, teachers can create their own private Duolingo classroom via Duolingo for Schools (https://schools.duolingo.com) and distribute links to students in their class. Duolingo for Schools also enables teachers to keep track of data such as the last login and number of activities completed, all within a user-friendly dashboard for teachers. Duolingo offers a wide range of TTS materials that users can interact with outside of class. TTS activities in Duolingo include listening to a sentence and translating it, which affords the student the opportunity to respond to aural input with written output. Users may also be presented with a word or phrase, listen to a TTS pronunciation model, and then record themselves pronouncing the target word or phrase. In both cases, learners are provided with instant feedback on their ability to interact with TL (TTS-based) materials from a range of categories (e.g., adjectives, food vocabulary). The activities are structured in a way that vocabulary building and comprehension checks occur simultaneously through the use of both speaking and listening assignments (see Fig. 2 for the interface of a listening and speaking activity in Duolingo). This enables students to increase their interaction with the TL in the mobile setting, as the software helps learners to set goals, track progress, and interact with gamified elements such as experience points and levels in a way that promotes consistent practice. A full discussion about gamification will be detailed in Level 3, where gamification as a design choice becomes a more relevant topic. Teachers without programming skills, in this instance, can leverage pre-made content so that students can use mobile devices to create opportunities for students to interact with the TL outside of class. Level 1 was originally conceptualized as a way for the teacher to adapt pre-made materials to enhance out-of-class TL interaction, such as using the TTS voices offered by Google Translate as a pronunciation model. However, Duolingo for Schools contains a feature that encourages reconsideration of what it means to adapt pre-made materials. Duolingo for Schools has a “Classroom Activities” option which automatically generates questions consistent with user proficiency, based on the user logs and data from students in a particular course. While the activities in Duolingo are geared toward beginner language learners and are more behaviorist in nature (e.g., as defined in Roblyer 2003), they do provide unique opportunities for TL interaction on the go and, with the assistance of a teacher, could be

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Fig. 2 Duolingo TTS translation activity (left) and a TTS listen and repeat pronunciation activity (right) for French FL learners

complemented with more constructivist, in-class activities such as role playing and research projects. The design choices at Level 1 are predetermined, but there is still a variety of possibilities to adapt pre-made MALL technology to help students develop a consistent relationship with the TL outside of class, with activities that target their learning needs and interests.

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Modifying Mobile TTS Materials: Level 2

At Level 2, the teacher has the ability to modify TTS cards, but the activity types and gamified elements are still predetermined by the application. Quizlet (Quizlet, Inc., San Francisco, CA, USA, https://quizlet.com) is a flashcard-based app that affords teachers the freedom to modify TTS flashcards for their students (Fig. 3). Similar to Level 1, the predetermined gamified elements and activities offer the students a wide range of TL vocabulary activities in the mobile setting, which are made available to students via a class link. To make the cards, teachers type a target word in the TL and choose from over 150 languages for TTS pronunciation modelling. In addition to a database of images readily available to teachers to complement the cards, a paid account affords teachers the opportunity to upload their own images. This enables students to use mobile technology to swipe through cards, flip them to view a relevant image, and listen to target language pronunciation of each word or phrase. There are a number of predetermined activities that teachers can make available for their students to practice TL vocabulary with Quizlet. In the traditional flashcard mode, for example, students are able to see pictures, flip the card, read the word, and play the TTS model. In the “spell” mode, students can check their comprehension by taking a test that randomly generates questions that require learners to listen to a TTS voice, view the accompanying image, and then spell the word. To increase the level of difficulty, some items in “spell” do not contain an image – only the TTS pronunciation of the word or phrase. Similarly, timed matching games and writing tests are additional predetermined activities that students can play to practice target vocabulary. This offers students a number of ways to interact with TTS cards in the

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Fig. 3 Quizlet TTS card in Japanese (left) and the English definition on the back of the card (right) for Japanese as a FL learners

TL and consequently have access to comprehensible input outside of class, as recommended by Krashen (1985, 2003). In addition to the mobile setting, in classrooms where tablets are readily available, Quizlet Live includes competitive, in-class games that students can play against each other by syncing their tablets and working in groups to compete against other groups. A live scoreboard keeps track of student progress to encourage friendly competition between groups. Unfortunately, Quizlet Live is restricted to the in-class setting; nonetheless, it serves as an effective study companion to out-of-class interactions with TTS cards. While the differences between Levels 1 and 2 are subtle, the ability that teachers have to modify their own cards at Level 2 opens up a number of pedagogical possibilities. For example, teachers may like the way that their textbook presents grammar but remain dissatisfied with the amount and variety of vocabulary included in the book. In this case, teachers can use Quizlet as a mobile supplement to a traditional textbook to include the vocabulary they deem to be more relevant. For teachers who do not have the time or resources to create their own activities from scratch (such as those found at Level 3) but want to customize material, Level 2 offers modifiable TTS materials with effective predetermined activities and gamified elements. While the activities proposed are mostly behaviorist in nature (or directed, using Roblyer’s 2003 terminology), they provide an interactive way to practice new TL vocabulary. Level 3, as will be seen, gives teachers full control over adapting, modifying and, creating mobile TTS materials, comprehension activities, and gamified elements.

8

Creating Mobile TTS Materials: Level 3

At Level 3, teachers can take advantage of the adaptation and modification capabilities found at Levels 1 and 2 while also being able to create content and activities. As previously mentioned, one should not overlook the importance of learning how to program; however, Level 3 provides teachers with an advanced set of tools and design choices to help students increase interaction with the TL in the mobile setting without having to invest the time to learn advanced programming. Level 3 affords

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Fig. 4 Quizlet TTS food related vocabulary embedded in a Moodle course with predetermined study modes (left) and the associated points distributed to a Level Up! leaderboard (right)

MALL engineers the ability to peruse the robust supply of customizable resources, compile features they deem to increase TL interaction outside of the classroom (see also ▶ Chap. 71, “Mobile AR Trails and Games for Authentic Language Learning”), and implement those features into a customized course for their students (Barcomb et al. 2017). As such, this level focuses on creating activities and customizing gamified elements to encourage students to study the Quizlet cards created in Level 2 and combines them on a single platform (see Fig. 4 for an example using the course management system Moodle). At Level 3, teachers can also shift from behaviorist to more constructivist approaches (Roblyer 2003), so that students who are proficient with the material can have opportunities to create their own TTS cards or generate review quizzes for the other students to practice. This is also in line with Brandl (2002), who suggests that a shift from teacher-determined to studentdetermined material development places material creation in the hands of the students to encourage deeper learning. In short, there are several instructional design choices for practitioners to explore at Level 3. Moodle, an open-source course management system, which is commonly used on desktop computers, launched its mobile application in 2015, Moodle Mobile (for Android and iOS). Current versions such as Moodle 3.4 (November 2017) enable teachers to create mobile learning opportunities for tablets or smartphones. One of the strengths of Moodle is that teachers can design their own modules: series of activities that last for a specific duration such as 1 day, week, or month; a course is made up of a series of modules. Within a module, teachers can restrict student access to activities until specific conditions are met (e.g., passing a quiz), which is one of the ways that Moodle can resemble a game with levels (Pastor-Pina et al. 2015). Teacher-created multiple choice, fill-in-the-blank, and listening quizzes are all a possibility for comprehension checks, so pre-screening also becomes a process of creation in this instance. In addition to creating quizzes, there is an abundance of plugins in Moodle that can enable teachers to gamify their courses with badges, leaderboards, and progress bars. One of these plugins is Level Up!, a leaderboard module that rewards students with experience points for attempting assignments and

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reviewing material (see Fig. 4 for an illustration of Level Up! and its reward scheme). Teachers can set the amount of experience points students receive for each activity and the amount of points necessary to accumulate the badge for that level (e.g., Level 1 badge = 50 points; Level 2 badge = 100 points). This set of customizable tools gives teachers the ability to create MALL materials, fully equipped with TTS technology, comprehension checks, and motivational affordances. To create a gamified vocabulary course with activities and features similar to those found at Levels 1 and 2, teachers could start by embedding a set of Quizlet cards into a mobile Moodle course. To begin enhancing the environment around the cards, activity completion can be set up so that, once the student views the cards, the system automatically opens the next activity and distributes points to the user’s leaderboard account for attempting that activity. This proposed Level 3 activity is a culmination of all three levels, as adapting Moodle’s activity completion and restrict-access to mimic gamified elements enables teachers to embed modified TTS cards in an interactive environment they create through customization. To check for comprehension, teachers can create their own listening quizzes by using a combination of the quiz function and the PoodLL language recorder plugin, which enables teachers to create listening questions by making their own recordings; alternatively, students or instructors could make recordings using a TTS voice. Students could take a multiple-choice quiz that requires them to listen to a TL vocabulary word and either fill-in-the-blank or choose the L1 equivalent from a list. If students also receive experience points, badges, and recognitions on the leaderboard for practicing activities, then there is positive reinforcement for students to continue practicing the activities in a module, even after completing all the activities once. At Level 3, it is up to each teacher to create a course that targets the specific needs of their learners, yet they need to do this within their resources and abilities. Gamification, in addition to creating more enjoyable learning experiences, offers unique insights into instructional design choices and student usage patterns. One of the strengths of gamification is that it can enable students to work backward to review material (e.g., Bogost 2011) and focus on specific material that is worth more points. In this way, if a teacher looks at data logs and finds that students did not spend enough time reviewing the vocabulary cards, an appropriate design choice would be to make those cards worth more experience points to encourage students to focus on foundational knowledge before moving on to more difficult activities. As an example of the level of insight that gamification provides as a design choice, GodwinJones (2014) points out that a self-developed game is particularly effective for tracking data, a possibility that can also be found in Moodle via its user logs. To explore the pedagogical insights hidden in user logs, Barcomb and Sheepy (2017) applied a data mining algorithm to data logs from a gamified Moodle course targeting foreign language pronunciation. As a result of analyzing the observed patterns, they were able to better understand user tendencies, particularly in regard to how students behaved before communicating in video forums, where they recorded show-and-tells and responded to each other. The opportunities to customize MALL materials without programming skills enable teachers to create unique

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learning environments based on their own content and reward systems to motivate students to interact with the TL outside of class.

9

Future Directions

This chapter’s main goal was to provide L2 instructors with some guidance on how to implement the use of MALL in their classes, depending on their levels of technological expertise and needs. To achieve these goals, this chapter has demonstrated how the implementation of Barcomb et al.’s (2017) three levels for MALL material development can assist teachers in deciding which strategy or level is most appropriate for their students: adapting (level 1), modifying (level 2), or creating (Level 3) MALL material. Using TTS as a target tool, this chapter has also shown that, depending on teachers’ available resources and their technological skills and willingness to use them, they can easily adapt existing mobile technologies in order to increase their students’ exposure to the target language input, motivate meaningful interactions with the technology, reduce the place and time restrictions that affect the L2 classroom (Traxler 2007), and consequently encourage students to learn on their own, anytime, anywhere. It is only by enabling students to have increased interaction with the TL outside of class that students will truly have the input necessary to make gains in the foreign language context. The authors acknowledge, however, that the MALL implementation ideas discussed in this chapter require a long-term dedication to conceptualizing, creating, and revising materials and to understanding how to properly adapt/modify/create MALL materials into a learning experience: it involves a continuous cycle of designing, implementing, and (re-)evaluating (McKenney and Reeves 2012). Foreign language teachers are faced with a number of constraints, ranging from time limitations to using materials that are not motivating or relevant to students. The dual need for out-of-class interaction and relevant materials that can provide such interaction is a key reason that, for example, Blake (2013) highlights the potential for web-based language learning materials to replace the use of a static textbook. If paired with TTS technology, customizable MALL software shows promise in FL education as it affords teachers a feasible way to introduce materials that increase TL interaction outside of class. While there are numerous ways in which mobile technology can transform the amount and types of interactions that learners have with the TL, it is important to remember that instructional design, not the technology itself, is what leads to learning (e.g., Bernard et al. 2004; Reiser 2001) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”).

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Cross-References

▶ 1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation ▶ Characteristics of Mobile Teaching and Learning ▶ Design and Implementation of Chinese as Second Language Learning

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▶ Developing an Adaptive Mobile Tool to Scaffold the Communication and Vocabulary Acquisition of Language Learners ▶ Development of Application to Learn Spanish as a Second Language: Lessons Learned ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts ▶ Mobile-Assisted Language Learning: How Gamification Improves the Learning Experience ▶ Mobile AR Trails and Games for Authentic Language Learning ▶ Mobile Devices for Preschool-Aged Children ▶ Mobile Learning and Engagement: Designing Effective Mobile Lessons

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Deborah Silvis, Jeremiah Kalir, and Katie Headrick Taylor

Contents 1 Introduction: Mobile City Science and Smart and Connected Communities . . . . . . . . . . . . . . 1.1 Location-Aware and Mobile Technology in Research on Teaching and Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Smart and Connected Cities Initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 MCS Curriculum Design and Description of Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 MCS Curriculum Activities for Collecting Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Activities for Analyzing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Activities for Making Spatial Arguments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 MCS Research Collaborations and Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 MCS Curriculum Implementations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Key MCS Design Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Getting “Smart” with Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Getting “Connected” to Cities and Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions for the Design of Mobile Learning Curricula and Research . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter explores a relationship between learning across places and researching across places. Location-aware devices play an important role in research on teaching and learning as more learning settings incorporate mobile

D. Silvis (*) · K. H. Taylor Learning Sciences and Human Development, College of Education, University of Washington, Seattle, WA, USA e-mail: [email protected]; [email protected] J. Kalir Learning Design and Technology, School of Education and Human Development, University of Colorado Denver, Denver, CO, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_131

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technologies. However, collecting and managing the data produced by these technologies takes coordination, particularly when learning is happening at the scale of the neighborhood and when research sites are geographically distributed. This chapter examines the use of mobile and geolocative technologies in research on teaching and learning through a description of a novel approach called Mobile City Science (MCS). MCS is a project that brings together university-based researchers and youth-serving organizations (i.e., a science museum, after-school programs, and schools) in three US cities to support young people in developing locative literacies (Taylor 2017) through their study of local issues. By collecting, analyzing, and developing arguments with spatial data and mobile technologies, MCS participants learned what is involved in contributing to change processes at the city or neighborhood scale. These same data served to inform researchers about learning processes related to new spatial literacies, even when researchers and collaborators were located in geographically separate places. This chapter identifies a set of key design practices for studying and implementing MCS and then applies these to commonplace notions of smart and connected cities.

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Introduction: Mobile City Science and Smart and Connected Communities

This chapter explores a relationship between learning throughout a place and researching across places. Location-aware devices play a key role in research on teaching and learning as more learning settings incorporate mobile technologies (see ▶ Chap. 79, “VR and AR for Future Education”). However, collecting and managing the data produced by these technologies takes coordination, particularly when learning is happening at the scale of the neighborhood and when research sites are geographically distributed across different states. This chapter examines the use of mobile and geolocative technologies to research teaching and learning by describing Mobile City Science (MCS). MCS is a project that brought together university-based researchers and youth-serving organizations (i.e., a science museum, after-school programs, and schools) in three US cities to support young people in developing locative literacies (Taylor 2017) through their study of local issues. Participants used location-enabled mobile technologies like Garmin GPS devices, GPS-enabled action cameras, mobile phones, and mapping technologies to locate and re-present places of personal interest through their neighborhoods (see ▶ Chap. 77, “Augmented Reality in Education”). Implementing MCS in multiple cities required designing a suite of mobile learning activities while also encouraging local redesigns and novel uses of mobile technology that made sense within different neighborhoods. Collaborating participants and a team of researchers developed emergent practices and flexible tactics to effectively work with spatial data throughout the data collection, data sharing, and data analysis phases of the project. Such tactics resulted in key design practices that extend current ideas about “smart and

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connected” cities and communities. These design practices are foundational for studies of mobile learning that seek to engage participants in addressing neighborhood-scale issues. This is significant as the implementation of novel mobile teaching and learning projects increasingly involves geographically distributed research partnerships (Gallagher and Freeman 2011; Hannerz 2003) and geolocative data sources (Hall et al. 2015; Taylor 2017). This chapter describes how MCS has made promising contributions to a more robust and critical understanding of smart and connected cities. Specifically, MCS implementations have demonstrated how to support youth in imagining smarter cities through their own data collection and scientific inquiry practices. Through data collection, youth have been encouraged to notice their community assets and challenges, such as a lack of civic infrastructure (e.g., bicycle lanes, recreation centers). In this respect, youth are encouraged to propose data-driven solutions for smarter and more connected cities that are not merely technical but also require strengthening relationships among diverse citizens, stakeholders, and organizations. Insights from the MCS project suggest smarter cities are also more humane cities and that youth’s data-informed inquiry processes can be directed toward civically engaged sociotechnical development. MCS is guided by the idea that young people have valuable knowledge about places that can inform and enrich change processes at the scale of the city or neighborhood. On the one hand, a research project like MCS is predicated on the desire to create “smart and connected” communities by supporting new forms of youth civic engagement. On the other, MCS implementation across three cities expanded what it might mean to be “smart” or “connected” in today’s urban environments. This chapter explores these issues by examining the relationship between instantiations of mobile and location-based data during local, on-site implementation (of participating youth and facilitators within two city neighborhoods) and long distance, and online collaborations (between facilitators and researchers across three different cities) in the MCS project.

1.1

Location-Aware and Mobile Technology in Research on Teaching and Learning

Designing for – and in response to – mobility is increasingly a focus of research that attends to learning across settings, timescales, and cultural contexts (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Mobile learning approaches like MCS reorient curriculum activities around traditionally undervalued and underutilized learning resources. Research projects like MCS bring attention to the critical importance of the moving body and mobility in all learning (Hall et al. 2015; Streeck et al. 2011; Taylor and Hall 2013). MCS builds upon promising theoretical and curriculum advances in learning “on-the-move” (Taylor and Hall 2013; Taylor 2017) by using location-aware and wearable technologies to create place-based and mobile experiences for K-12 and postsecondary learners (e.g., Hall

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et al. 2015; Holden 2016; Kalir 2016; Rosner et al. 2015; Taylor and Hall 2013; Taylor 2017; Taylor and Silvis 2017). Mobile, location-based technologies not only augment the experience of learning in places, but they also focus attention on the place and social context in which learning occurs. Moreover, some scholars have argued that places are not transparently seen on maps or in locations; they are actively constructed by experiences in situ (Taylor and Phillips 2017). Methods of participatory mapping (i.e., Gordon et al. 2016; Taylor and Hall 2013) have been developed to address just this question of how experiences in and mobility through places contribute to “placemaking” (Taylor and Phillips 2017). These methods increasingly rely on interactive maps and GIS technologies, which enable narratives about places to be shared and edited across locations.

1.2

Smart and Connected Cities Initiatives

The research reported in this chapter was initially conceived and organized during a National Science Foundation-funded workshop titled Smart and Connected Communities for Learning: A Cyberlearning Innovation Lab. Both MCS and this workshop reflect a broader interest in the development of smart and connected cities and attendant issues for learning (Gianna and Divitini 2015). “City science” is an interdisciplinary field that sits at the nexus of urban planning and data science and aims to develop strategies and infrastructures for more efficient, equitable, and “smarter” cities. Smart and connected paradigms position state-of-the-art technology as the solution to global problems associated with urbanization (Angelidou 2015). Connecting more people, more goods, and more services to the grid is seen as a solution to historically unequal resource distribution, access, and opportunity. Ubiquitous mobile computing and large, rich data sets are essential components of smart and connected paradigms, which promise to improve all manner of urban systems from transit to environmental protection (Townsend 2013). While some are optimistic that having more people connected to urban infrastructures and collecting their own data (e.g., on air quality or mobility) will result in a collective ability to produce new ideas and engage in data-driven decision-making (Angelidou 2015), others are more circumspect about the nature of this data; user-generated data presents new questions about whose property the data will be, to what purposes it will be directed, and who stands to benefit from collecting and mobilizing city-scale data (Picon 2015). Questions about the participatory design of smart and connected cities are not new to the field of community planning and urban development (Gordon et al. 2016). Mapping sits at the intersection of this debate because location-based technologies are embedded in increasingly ubiquitous mobile devices, such as smartphones. Open Mapping Software such as Google Earth (Farman 2010) and Google Maps (Elwood and Leszczynsky 2013) and AR technology (Wilson 2011) make it more possible than ever for users to create cartographic content and make changes to map layers that can influence city planning and design of urban infrastructure. Moreover, today digital maps are accessed by people outside of traditional

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domains of city planning or civil engineering; maps are increasingly used to give spatially indexed accounts of everyday experiences and to address practical, “on the ground” needs (Taylor 2017). For youth and professionals, who are interested in addressing community-based issues and contributing to designs for smarter and more connected cities (Kingston 2007; Taylor and Hall 2013), location-based technologies and digital mapping applications present new avenues for advocacy.

2

MCS Curriculum Design and Description of Activities

Mobile City Science is a project, funded by the National Science Foundation (#1645102), that studied how two groups of urban youth collected, analyzed, and developed arguments with spatial data using mobile and location-aware technologies. One goal of the project was to support educators to better understand the places in which students live. Another intended outcome was for students to develop technical knowledge and capacities for civic engagement that can extend beyond the curriculum. In some cases, the data students gathered while participating in the project contributed to ongoing processes of change and urban planning in their neighborhoods. For example, in a midsouth city, where the MCS curriculum originated, participating youth brought the attention of city planners to the lack of youthoriented transit options in their neighborhood, and eventually a bike lane was installed in this “mobility desert” (Taylor and Hall 2013). While advocating for material changes to city infrastructures focusing on transit and mobility is not a requisite element of MCS, all participants have opportunities to gather data and form spatial arguments about their neighborhood through a series of learning activities.

2.1

MCS Curriculum Activities for Collecting Data

Because MCS emphasized moving around the city in order to understand the assets and opportunities in the local environs, learners’ early activities involved immersive fieldwork and data collection. Through a series of semi-structured, field-based inquiries using wearable cameras and geolocative devices – as well as paper maps and paperbased tools like trace paper and pencils – students gathered information about their neighborhood that could then be analyzed and organized into arguments for change. Before setting out, facilitators guided students through free recall mapping, an activity that introduces maps as a representational form (Hart 1977). Facilitators asked participants to produce a map of their neighborhood or community, a relatively open-ended prompt that allowed students interpretive and representational leeway. Participants went on to describe what they drew and the reasons for including these attributes (e.g., sidewalks, houses, gardens) on their maps. Next, in the walking audit, students used a paper map to navigate to several nearby locations of interest such as libraries, parks, faith-based sites, and other locally significant cultural institutions. The focus of this activity was on what might be missing on the map, or conversely, what might be depicted on the map

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Fig. 1 (a) Participants reconstruct the local Farmers’ Market on transparency film during the Historic Geocache activity in Seattle. (b) A question mark “walked” by participants in the GPS Drawing activity symbolizes change and uncertainty in the city

that was inconsistent with reality. While on site at these places, students discussed how they use or might use the space, and they also recalled previous experiences (if any) they may have had there. The historic geocache activity introduced participants to the use of digital maps for navigating to places, as they found their way to a number of preset waypoints that had been determined (typically, by facilitators) to have historical significance. While on site, participants produced some representation of the place using a variety of tools and media, such as mobile phones, paper and pens, transparency film, etc. (Fig. 1a). Depending on the location and local design of this activity, participants also interviewed experts at the site; local stakeholders’ institutional knowledge served as relevant data for students’ future analysis. A final data collection activity, GPS drawing, was an opportunity for students to then use the GPS devices to produce a personally meaningful symbol over a map of some nearby area (Lauriault and Wood 2009). Students first planned the shape they would draw on paper maps, making decisions about scale and route. They then set off through the neighborhood once again, using the device to create a set of GPS tracks that, when layered onto Google Maps, took the shape of their planned symbol (Fig. 1b). Walking the neighborhood in this way not only gave youth a new perspective on the map – as a representation collaboratively created by map-makers and users (Gordon et al. 2016; Taylor and Hall 2013) – it also introduced them to spatial ideas related to scale and the geometry of the built environment. GPS drawing allowed them to use the spatial arrangement of the environment and their own mobility as resources for learning (Taylor 2017).

2.2

Activities for Analyzing Data

As students returned from each field-based activity, and with the help of facilitators, they transferred their video and GPS files from cameras and Garmin devices to online file storage systems, making this data available for their own analysis. Each

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session between field trips was an opportunity to discuss observations from prior activities, troubleshoot technical difficulties, and debrief firsthand experiences in the neighborhood. These conversations functioned as early informal analyses that shaped how students conceived of local issues as they proceeded in the curriculum. Once they had some video and photographic data – from images collected during the walking audit, for example – students began creating an annotated map of their observations and ideas. This was facilitated through debriefing the field observations with an eye to what was missing, inconsistent, or problematic in terms of use or mobility but also with a focus on what was available to neighborhood residents and how (and if) people accessed such assets. This asset map – once populated with locally derived, on-the-move and on-site, youth-produced data – would inform their determination of what (if any) changes they might recommend in terms of local innovations or infrastructural improvements.

2.3

Activities for Making Spatial Arguments

Finally, facilitators supported youth to organize their analyses of mapped data into categories of issues that could be used to develop plans for change. Based on the kinds of observations students made, there may have been a particularly “live” problem that emerged from data analysis. Alternatively, individual students or groups might converge on a number of key issues salient to them. These then served as the grounds for producing counter-maps (e.g., Peluso 1995) of the neighborhood, which represented proposed changes and highlighted what students saw as missing places, assets, or features. The process of counter-mapping involved further analyzing or iterating on the asset map, toward the creation of a new map or spatiallyreferenced artifact that represented a youth perspective on proposed changes to the environment (Taylor 2013; Taylor and Hall 2013). These proposals were then made public in various ways. One approach was to organize a community meeting with stakeholders and decision-makers, and involved invited experts, such as urban planners, transit officials, or local public servants and elected officials. The purpose of this onetime meeting was to create the conditions for an active design charrette in which youth lead participating attendees through a process of redesign based on their findings from field work and their data analysis. Another approach was for a partner school to organize a final showcase event, which invited participation from professionals and other community members. This event could occur at school and may combine elements of both hands-on design work and a cumulative presentation. This type of event presented an opportunity for other students and educators from the partner school to learn about MCS activities and outcomes. Finally, it is also possible to present MCS programming at a standing community-based meeting, such as those organized by civic- or faith-based groups. This approach has the advantage of amplifying youth voice in settings that may (for various reasons) typically lack young people’s perspectives and brings youth into conversation with diverse stakeholder audiences.

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MCS Research Collaborations and Training

The project described in this chapter was a pilot study that emerged from a placebased, mobile teaching and learning social design experiment in a midsouth city. MCS was originally implemented in partnership with a youth-serving organization; the design team was led by this chapter’s third author (Taylor 2013, 2017; Taylor and Hall 2013). As an extension of this earlier research, the pilot study described in this chapter was organized as a collaboration among the University of Washington and researchers and organization leadership from the Digital Youth Network (DYN) and the New York Hall of Science (NYSCI). Under the auspices of designing and building capacity for smart and connected cities, this collaborative and cross-setting project was launched to pursue three interrelated goals. First, MCS partners sought to implement curriculum activities that positioned youth, their interests, and their data-driven argumentation as levers for smarter and more connected urban communities. Second, project partners would iterate MCS across multiple urban contexts to establish a smarter and more connected research community committed to the investigation of youth learning on-the-move with location-aware and mobile technologies. Third, the pilot was organized to establish connections across out-ofschool and in-school settings that would articulate how MCS could support placebased, mobile, and digitally mediated learning and thereby could be adapted by educators and organizations in other cities. Partnerships in this MCS pilot also engaged local secondary schools in both Chicago and New York City (The names of partner secondary schools – and their students and staff – in both Chicago, and Corona, Queens, are pseudonyms.). DYN’s MCS programming in a neighborhood on the southside of Chicago occurred through a partnership with Evergreen Academy, a public secondary school of approximately 200 students defined by a distinctive arts- and technology-infused curriculum. DYN facilitated MCS as an extension of the organization’s well-documented and highly successful digital media and learning programming (Barron et al. 2014). In a neighborhood in the borough of Queens, NYSCI partnered with Global Science Academy (GSA), a public secondary school of approximately 300 students affiliated with a larger network of international-themed schools primarily (though not exclusively) located in New York City. The partnership between NYSCI and GSA was rooted in the work of Queens 20/20, NYSCI’s initiative to engage young people and families from the neighborhood surrounding the museum in out-of-school STEM learning opportunities. For the purposes of describing university research collaborations with partner organizations in this chapter, staff and researchers at the partner organizations (i.e., DYN and NYSCI) and the university-based research coordinators are collectively referred to as the “research team.” Youth who participated in MCS at the secondary schools are referred to here as “participants,” although they were also considered “researchers.” For clarity, the three present authors are referred to in this chapter as “researchers.” In order, the authors were the Research Associate (RA), Program Evaluator (PE), and Principal Investigator (PI). The role of the RA was to coordinate the sharing of data, to manage the data repository, and to perform initial analysis of

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data as it was collected. The role of the PE was to visit sites during implementation, to observe and document ongoing implementation activities, and to review and assess culminating events and final program outcomes. The role of the PI was to train all facilitators and the research team to implement MCS activities, to oversee all research activities, and to generally keep the mobile learning and teaching environment moving. The roles of the staff and researchers at the partner organizations are described in more detail in Sect. 4. Prior to implementation at the partner sites, researchers hosted a training week for visiting members of the research team at their campus in Seattle. One member of the NYSCI team and two members of the DYN team attended the MCS Seattle training. There were several goals of this meeting. First, researchers intended to introduce team members across research sites to each other. Second, they introduced all team members to the MCS curriculum and presented an overview of how it had been designed and initially implemented. And third, they began planning for local implementations in Chicago and New York City. The primary task achieved during the Seattle training was to practice each of the MCS activities in some form, so that future facilitators had firsthand experience collecting, analyzing, and arguing from mobile and spatial data. Of course, this was somewhat abbreviated in the interest of time and team building. Nonetheless, and surprising even to us, salient local issues – such as gentrification and economic development – emerged as rich sources of analysis and conversation while practicing curriculum activities over the span of just days. Facilitators’ and researchers’ initial experiences of learning to “teach” MCS as mobile “learners” themselves were invaluable once local implementations in Chicago and New York were underway. Learning to collect and then analyze spatial data was an essential element of the Seattle training. In addition, the team established conventions for collaboratively managing data that would enable us to share and systematically analyze it across sites. Before summarizing what took place during local implementations of this mobile teaching and learning curriculum in Chicago and New York City, it is worth mentioning how the Seattle training set the stage for the more technical- and dataoriented aspects of the project which would become critical focal points for both researchers and youth participants. Data collection was primarily, though not exclusively, a responsibility of DYN and NYSCI as implementation and research partners; therefore, researchers worked to ensure they were comfortable using what, to some of us, were new technologies (e.g., GPS devices, point of view cameras), file formats (e.g., .mov, .gpx), and research methods (e.g., video recording, mobile mapping). Field notes from the Seattle training indicate how critical this part of the work was to the success of the partnership: When we were not out on the move getting to know each other and the city, we were inside downloading and discussing the data we had collected during MCS mapping activities. However, to get to the stage of downloading the data, literally hours of technical work had to be performed. . . Unpacking all the devices, setting them up to record data, learning how to operate new technologies, and making sure they were charged were ongoing activities on the way to making the data available to process and debrief (excerpt from fieldnotes).

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In the interest of transparency and to inform future implementations of MCS, it is worth noting that placing primary responsibility for data collection on DYN and NYSCI was a big ask. Once implementation commenced, the sociotechnical work of arranging for technologically mediated mobile learning was a heavy lift and required ongoing attention and troubleshooting. Nonetheless, the local benefits of the mobile learning curriculum outweighed these local challenges. The following section further describes the design and implementation of MCS at the two pilot sites and illustrates what was involved in learning and researching across places. This is followed by an elaboration of key practices that emerged from implementations.

4

MCS Curriculum Implementations

In this pilot study, the first MCS implementation took place in a south Chicago neighborhood in the fall of 2016. As most of the mobile, mapping activities in MCS happen outdoors, the climate of a particular location presents a wider or narrower window for implementation. With approximately 10 weeks of planned curriculum activities at Evergreen Academy, when DYN began facilitating MCS, they were rapidly approaching the cold weather season in a location known for harsh winters. In consultation with Evergreen’s principal, MCS was implemented in the first period of a Grade 9 science class and ran from October through December, 3 days per week, for all students enrolled in the class. In January through March of 2017, a subset of these students continued to coordinate a plan for the culminating design charrette. In Chicago, DYN’s facilitation team included three core researchers at their organization, Caitlin, Tene, and Elaina, and a team of three part-time facilitators, Jim, Dimress, and Asia, whose assistance depended on the nature of the MCS activity on any given day. For example, during field-based mobile mapping activities, four different facilitators each accompanied a group of three to four students who carried GoPro cameras, Garmin GPS devices, and paper maps around the neighborhood while they collected data. During these mobile activities, facilitators also served as data collectors, carrying or wearing cameras or later documenting field notes. Another role of the facilitators in this MCS program was to plan and organize curriculum activities before each class session, including transporting and distributing mobile tools and technologies, creating any necessary paper-based maps and instructions for students, and generally managing the roles and responsibilities of students in small groups. Much of this team’s planning for each class session also involved contacting local businesses, researching local points of interest, and coordinating the students’ visits to these sites beforehand (Fig. 2). At the end of DYN’s 5-month MCS implementation, students at Evergreen Academy defined and developed arguments to address a number of issues about their neighborhood. Students’ place-based inquiry identified a central problem: There was a lack of youth-oriented after-school opportunities in the neighborhood around their school. They tied this central problem to a lack of youth employment options, a lack of space for artistic production (i.e., studio space), and a lack of recreation centers. In some instances, participating youth also connected their lack of

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Fig. 2 (Clockwise from top left) Students on the Walking Audit photograph Popeye’s Chicken restaurant, which they report “brings lots of business to the neighborhood.” During the historic geocache, a group of students visits a local church’s free breakfast and meet with a clergyman who has coordinated this service since 1979. A slide excerpted from their final presentation depicting how they categorized assets and converged around a common hyperlocal problem. A collection of students’ plans for shapes they will “draw” by walking in park and a parking lot near Evergreen Academy

employment, artistic, and recreational opportunities to the troubling effects of Chicago’s well-documented struggles with gun violence (Gunderson 2017). The data they had collected while traveling around their neighborhood during MCS activities, talking to longtime business owners and religious leaders, and then creating asset maps of the area had given them a picture of the neighborhood as changing and gentrifying. They imagined what kinds of conditions and amenities might keep them in the neighborhood after school. Their design plan disclosed – from a youth perspective – how this could also serve as a place of potential renewal for people whose connections to places may have been severed by generations of social inequality, violence, and racism. About the same time, MCS activities wrapped up in Chicago, the pilot’s second iteration commenced in the New York City borough of Queens. NYSCI’s MCS implementation at GSA was unique in a variety of ways. First, participating students – like all students at GSA – had lived in the United States for no more than 4 years prior to their enrollment at the school; in other words, they were all recent immigrants. Second, the 12 students who participated in MCS did so voluntarily as an after-school elective associated with their school-wide health sciences curriculum. Third, the majority of students were in Grade 12, though several were in Grade 11, in contrast to the younger cohort in Chicago. NYSCI’s implementation of MCS at GSA

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Fig. 3 (Clockwise from top left) During the walking audit, a group of students collects transit data by tallying bus arrival times on a hand- drawn map and using Garmin GPS to navigate between stops. Students investigate the history of Corona as part of their planning of a historic walk that they organize with facilitators. One student shows her “perspective viewpoint” of the street where she lives and highlights an abandoned building that she and her friends say is a “haunted house.” Another student shows facilitators and peers his planned location for designing Friendship Park as a solution to a relevant hyperlocal issue

began in late March, 2017, and culminated in early June. Participants met for MCS activities twice a week, on Tuesday afternoons for an hour following school, and for five Saturday sessions that lasted for approximately 3 h each. One Tuesday afterschool session had to be canceled because of a snow storm that shut down New York City public schools for the day. There were three core NYSCI facilitators, Catherine and Anthony, who were present at most MCS sessions and, Andres, who was also co-Principal Investigator of the larger research project. In addition, GSA students’ social studies teacher, Ms. Julia, who was supervising the juniors and seniors taking this course as an elective, participated in some of the classroom-based activities. GSA’s principal accompanied the students on most of the field-based mobile activities outside of school. Facilitators ran the intensive field-based sessions on Saturdays, which gave more time (and more extensive mileage) to mobile data collection activities. However, holding sessions on the weekends sometimes resulted in low attendance, and not all participants were present for all activities because of their work and family commitments. In contrast to prior MCS curriculum iterations, NYSCI facilitators asked GSA students to select many of the neighborhood sites they visited, creating new sorts of challenges and opportunities for mobile mapping and learning about places (Fig. 3).

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The students at GSA developed their own sets of issues and arguments that emerged from what they learned while traveling around their neighborhood and locating themselves in its history. Rather than converging on a single theme, such as “transit/mobility” (as in the original MCS implementation), “change” (during the Seattle facilitator training), or “after-school opportunities” (DYN’s implementation in Chicago), the students at GSA identified a number of unique, personally relevant themes and built their spatial arguments around these topics. Some students worked individually, while others collaborated in pairs to construct evidence-based claims and then present these to local stakeholders at their culminating event. Given that GSA was planning graduation ceremonies for their first class of Grade 12 students at NYSCI in late June, it was easy to coordinate the museum hosting the final MCS event. During the final community presentation, one particularly vocal student, who was present at all MCS meetings and Saturday sessions, keyed into what he called a lack of “friendliness” and openness to meeting and talking with new people in his area of Queens, a neighborhood known for its ethnic diversity. His solution was to develop a nearby park into a “Friendship Park” designed for communion and conviviality in this dense and lively urban center. Other participant projects concerned youth-focused designs around mobility and recreation or common urban challenges such as local tourism and waste management. Given the strong diversity of international backgrounds and histories among GSA participants, it is not surprising that their inquiries led them to perceive such a wide range of challenges and opportunities in their neighborhood.

5

Key MCS Design Practices

For MCS participants – and for the researchers studying their learning – arriving at a set of arguments and articulating locally relevant issues involved a number of key design practices. During MCS curriculum activities, participants developed new knowledge by traveling around their neighborhoods, collecting geolocative data, and analyzing data through the lens of youth experiences. During all phases of MCS implementation, researchers’ methodological activities, organizational partnerships, and facilitation of the curriculum were likewise animated by these same activities. The remainder of this chapter discusses two principal design practices for MCS which were both relevant for researching across places and also for youth learning throughout places. These design practices represent important considerations for both researchers conducting this type of mobile learning research and for youth participating in mobile learning curricula. These design practices also contribute to new ways of conceptualizing – and building – smart and connected communities.

5.1

Getting “Smart” with Data

Establishing norms for data collection and exchange across people and places is part of any research project (Ribes 2014). This necessarily involves coming to a shared understanding (with collaborators or participants) about what the nature of data will

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be and how data will be used. In many multi-sited research projects, the collection and analysis of data are used primarily internally by researchers to understand participants’ activities or to engage in iterative design (e.g., Cole 2006). MCS was different in that youth participants used the data they generated to analyze problems and construct scientific claims of their own. The forms of these two instantiations of data (i.e., researchers’ and students’) were often the same (e.g., video recorded observations of students’ field work), though they served different purposes and were understood through different perspectives. Moreover, while some data served both researchers’ and students’ interests, other data were pertinent only to one constituency (Fig. 4). For example, one student who analyzed local bus schedules and routes as a problem for youth mobility in Queens determined that bus arrival times and frequencies were relevant for establishing future plans and recommendations. However, this data had no a priori importance for researchers; it was primarily relevant to students. Conversely, researchers were interested in the very perspectives and processes through which students came to use technology in the city and make sense of their location-based data. The sources of researcher-relevant data quickly proliferated as MCS implementation progressed in the two cities. However, youth were less interested in what researchers saw as valuable data, such as the video recordings researchers gathered about students’ perspectives on places and mobility during post-field work debriefs in class. Determining what data would consist of and how data would be used was a central task of both researchers and students. As students identified salient local issues and iterated on their design solutions, new forms of data emerged for them, and their notion of what counted as data evolved. Similarly, researchers planning for MCS implementation anticipated what kinds of data would be relevant to their own analyses, without necessarily knowing in advance what kinds of issues and places would become relevant to youth or how implementation would unfold. In both cases, what was required was developing new approaches to using data or getting smart Fig. 4 The overlap between researcher and student data

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with data (a note on the use of “smart” in 5.1.2). Two examples from the project serve to elaborate this key MCS design practice.

5.1.1 Data-Sharing Sustains Research Collaborations In order to lay the groundwork for what Loshin (2004) called the “semantic consistency” of data, the research team established a number of information management conventions. During initial research conversations at the Seattle training, researchers discussed file naming and storing conventions, a deceptively mundane part of the research process that obscures its larger implications for collaborative work in distributed knowledge projects (Turner et al. 2006). Figure 5 illustrates the

Fig. 5 The interrelated activities for MCS data management

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activities involved in managing and sharing data in MCS. While each technique is interrelated with others in making mobile and geolocative data available for analysis across sites, each also stands as a discreet example of how research methods were designed around emerging future uses of data. Establishing naming conventions is just one instance in the larger design practice of researchers’ “smart” uses of location-based data in MCS. As illustrated in Fig. 6, through a series of conversations begun at the Seattle training, the research team established file naming convention for all file types (i.e., video, photo, audio, GPS, etc.). Researchers’ planning for file naming conventions influenced MCS data management in several ways. First, by suggesting that the file name should include information about each file type (i.e., videos, photos, GPS track data), the research team set up an expectation that any and all of these forms of data would be collected (and could be relevant) in a given curriculum activity. Second, by including information about the individual who collected the data (i.e., student, researcher, person’s initials), the research team established each activity as a collective sociotechnical accomplishment. The broader process of getting smart with data – whether in terms of research methods or participants curriculum inquiry – could be considered a collective and distributed sociotechnical accomplishment (Turner et al. 2006). Third, through file naming conventions, the research team communicated the importance of methodological systematicity and shared data conventions for studying learning across places. This relieved facilitators of reinventing the wheel at each new implementation in order to share data across research sites. Notwithstanding the advantages of establishing such standardized data management procedures, file naming conventions were actively redefined during implementation depending on the local design of activities at partner sites. For example, in Chicago, the division of participants into small groups necessitated an additional field in the file name that differentiated by group. In New York City, where entire MCS activities were reinvented (e.g., the historic geocache evolved into a larger exploration of the history of Queens), the abbreviated reference simply to “HG” in the filename was insufficient to represent the contents of associated data to researchers across sites. In these cases, getting smart with data involved accommodating the ongoing exigencies of implementation and data collection and incorporating these in terms recognizable to remote collaborators. According to Loshin (2004), “a good naming Fig. 6 The elements of MCS file structure

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convention, when it accompanies a well-designed set of abstract data type definitions. . . will provide a means for easily defining new data objects while conveying semantic meaning to existing named objects” (p. 30). Facilitators distributed across locales were able to maintain coordinated data sharing despite local curriculum redesigns in part because they were scaffolded by an effective approach to data nomenclature. File naming conventions (and their iterations across research sites) were an example of using flexible approaches to data management to support multi-sited collaborative research.

5.1.2 Data Propel Mobile Learning Like the researchers studying youth learning, participants in MCS found that adopting a flexible approach to data supported their efforts. As an example, after mapping and visiting a number of local health clinics in their neighborhood, a pair of students considered what types of data might answer their emerging questions about these local assets. This conversation took place several weeks into the New York City implementation, after students had already engaged in several field-based activities and in-class sessions. Prior to this debrief in class, students had traveled in small groups with a facilitator to three neighborhood locations that were organized around a chosen theme. This particular group had settled on neighborhood health clinics as representative of the theme “physical health.” They had noticed a relatively large number of private clinics and medical offices in their neighborhood, including a large hospital, which they did not visit (though another group did). During their mobile mapping of these health clinics, the students began to wonder why most were closed on Saturdays when presumably many people would be off to work from their Monday through Friday jobs and might have time to make use of clinic services. During their walk, the students discussed how and when clinics were accessed by local residents, how people traveled there, clinic hours of operation, the appearance and signage of the facilities themselves, and the proximity of clinics relative to each other and to other neighborhood assets like markets and libraries. These on-the-move discussions were video recorded, and one student used a Garmin to navigate to different clinic locations. In the next MCS session, they returned to their questions with a focus on what kind of data they might collect to understand how clinics served the neighborhood. One student, Brittany, offered the idea that they could interview people who lived around the clinics or who frequented these businesses. She suggested that this would give them a different kind of information than they were able to glean from observing the locations. Her idea stood in contrast to the ways she and other students had talked about data prior to engaging in this activity. Their earlier conceptions of data were that they were “numerical,” that they consisted of “charts and graphs,” or that they were used as “proof” of something. Brittany’s new understanding of data was that it could also consist of the personally relevant interview-based responses of local stakeholders, whose opinions were valuable in defining the problem. New and emergent forms of data were offered as acceptable ways of illustrating problems that youth identified during mobile data collection.

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These emerging understandings about data point to how participants developed flexible approaches to data; in other words, they were “getting smart with data.” It is not so much that students learned how to collect data and so they “got smart.” Rather they broadened their understanding of how particular forms of data are effective tools for building an argument and advocating for something potentially transformative with other community stakeholders. Accordingly, the notion of “smart” that informs MCS is neither normative nor necessarily “taught” through traditional curriculum and pedagogy. Rather, it involved surfacing place-based knowledge about local issues that youth already have (or those they refined through fieldwork and analysis) and then reorienting this existing knowledge toward building an action-oriented argument. For both students and researchers, getting smart about collecting and using data took both careful planning and considerable flexibility. While the research team benefited from determining before implementation what data would consist of and how it would be managed, researchers also allowed for considering alternative forms and emerging uses of data in situ. For youth, the same key design practice involved recognizing the power of data to make an argument about a local problem, learning to collect representative data, and then harnessing this (or other forms of) data to make a compelling case to local stakeholders. These different forms of knowing or “smartness” were interrelated, with data collection, sharing, and analysis cutting across the work of participants, facilitators, and researchers – as well as across places.

5.2

Getting “Connected” to Cities and Sites

As a second design practice, MCS required forging connections at several different levels of activity. At an interpersonal level, connections among collaborators and participants included forming friendships in class, building relationships between facilitators and students, and even convening virtual research meetings. At a material level, technological connections (e.g., charging devices, maintaining a strong Wi-Fi connection) made it possible to implement a primarily wireless, mobile curriculum and to manage data collection efforts. Thirdly, and at a city scale, it was critical to develop connections to places in order to create conditions where youth-led inquiry and recommendations for change held meaning for participants (Taylor and Hall 2013). In this discussion, the focus is on this third level of connection to cities and sites, while recognizing that interpersonal and material connections were also implicated in how researchers and learners connected to and across places. As with the design practice of getting smart with data, two examples represent – from researcher and youth perspectives – how connections to cities and sites emerged in MCS.

5.2.1 Connecting Researchers to Remote Field Sites During the MCS Seattle training, after 2 days of intensively studying the neighborhood around the University of Washington campus, Catherine, a NYSCI research

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collaborator, commented that she felt more connected to the U District – the neighborhood under study during facilitator training – than to the neighborhood in Queens more than 2000 miles away, where she had worked for years and would eventually implement MCS. In her words, In 2 days I got to know this community [in Seattle], not like the back of my hand, but I feel like I sort of get a certain level, way more than a tourist. . . but I would say I know this community better than the community outside the doors of NYSCI. Better than... where [GSA] is. I see that [MCS] works. You can’t help but get connected to the community because you are talking to the store owners, and also interacting with people on the street. You’re learning about the history. It’s really very powerful.

She (and others) committed to getting out in the neighborhood on foot and learning about Queens, which was indeed the first thing she and her co-facilitator Anthony did when they prepared for implementation back in New York City. Catherine even proposed the idea of walking or running from her home, through Queens, to NYSCI in order to experience familiar routes and routines (i.e., commuting) and places in new ways. To do so, Catherine would have had to walk across a bridge between boroughs, a commute that typically involved taking the subway. The idea of “bridging connections” between personal itineraries and place-based teaching and learning presented an important moment in the project. Collectively, the MCS team recognized that moving around on foot through places was a critical means for connecting to the city and locally relevant issues (Rosner et al. 2015). While Catherine and other facilitators did make strong connections in and to their city neighborhoods, this design practice also served to inform remote research collaborators who were equally invested in getting to know the places under study. Off-site members of the research team relied on facilitators’ recordings of field work with students, the traces of their travels left in GPS tracks, and the records of local networking that materialized in curriculum documents to get to know the places students studied. This information served to “ground” youth-collected data and observations, which researchers accessed almost entirely remotely through files stored in the cloud, to the “on the ground” relationships youth were building in their local neighborhoods. MCS was configured as a multi-sited, multi-city research project, requiring what Hannerz (2003) called “translocal connections” (p. 206). Because placebased mobile teaching and learning were so central to MCS, it was vital to researchers to have collaborators on the ground who could forge connections to places (Gallagher and Freeman 2011). Therefore, facilitators were in key roles, articulating between connections to research partners and local connections on the ground. The former made it possible for researchers in Seattle and Denver to get connected to Chicago and Queens. The latter created the possibility that local youth would have mobile learning opportunities in their neighborhood that resonated with their own experiences in and of these places.

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5.2.2 Connecting Young People to Local Places The key practice of making connections to the urban environment is evident throughout curriculum implementations, because all of the MCS activities are in some way designed to connect participants to local places. In Chicago, during the historic geocache activity, a group of students visited a local barber. He spoke with them about the history and processes of gentrification in the area and changes to the neighborhood surrounding their school over the decades his shop had been in business. He highlighted the shifting demographics, commercial opportunities, local politics, and physical landscape of the neighborhood’s major thoroughfare, where his business is located. Students interviewed him and then shared these video recorded observations with other peer groups back in class. Debriefing the interview afterward with facilitators, the students who visited the barbershop were ambivalent about the nature of “progress” in the neighborhood. They made associations to similar transformations in the adjacent neighborhoods where they lived, citing personal stories of displacement and change. For this particular group of youth in Chicago, while they desired jobs and productive after-school activities, the larger problem that surfaced in their analysis of opportunity was a general lack of youth-oriented places in the neighborhood. Some students voiced concern about the prevalence of “gang-banging,” and one wrote on their hand-drawn free recall map of the community: “don’t shoot, I want to grow up.” Given this context – one unfortunately common in American cities (Gunderson 2017) – informal learning opportunities like MCS offer a critical, albeit provisional intervention that create conditions to repair relationships to place. An activity like visiting a barbershop and interviewing the owner opens up possibilities for forging much needed connections between youth and local cultural resources and institutions, which is a key component of building new digital literacies and supporting interest-driven learning (Barron et al. 2014; Ito et al. 2013). Facilitators played a critical role in the MCS design practice of making connections to cities and field sites. For youth as well as for their adult facilitators, becoming connected to the location under investigation played a role in how they viewed – and eventually advocated for – local issues. This was supported by mobile technology in data collection, analysis, and argumentation activities; however, mobile connectivity was only one aspect of getting youth out-of-school and experiencing their city’s past and present, to think about the/ir city’s future. To make connections to place, youth relied on their own experiences in and of places. Of course this was heavily supported by facilitators, who brokered connections between youth and local stakeholders. Likewise, for researchers, an understanding of the relevance of places and local issues was mediated by facilitators bridging connections for youth to find mobile learning opportunities in their neighborhoods.

6

Future Directions for the Design of Mobile Learning Curricula and Research

This chapter has described a mobile learning curriculum for youth living in urban settings that incorporates digital mapping and place-based pedagogies toward encouraging a form of youth participation and civic engagement. The partnership

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between researchers and youth-serving organizations required spatial and temporal coordination, as mobile and location-based data emerged and were spread across cities and over time. Because both researchers and participating youth used and managed data – and often for different, though sometimes shared, purposes – thinking about data demanded flexibility and an openness to emerging methods of collection or analysis. Moreover, because data collection and fieldwork were primarily the responsibility of members of the research team in Chicago and New York City, making connections to places was pivotal for researchers off-site so that they might make sense of curriculum implementations in these places. These connections were no less important for participating youth, for whom the curriculum was designed. Given these interrelated considerations, getting smart with data and getting connected to places were two key design practices for both MCS researchers and participants. In MCS, participants and researchers practiced ways of knowing and becoming connected to their local neighborhood. MCS was founded on the idea that young people are already smart about their surroundings and conceived as a means of harnessing new tools to support the unique knowledge they have of their neighborhoods and cities. However, youths’ ways of knowing were not aimed at or always entirely aligned with urban development agendas and the making of “smart cities” (Picon 2015). Furthermore, the MCS implementations reported in this chapter help to de-center discourse about “innovation” and “high technology” often associated with smart cities and reorient processes of change toward the local (and sometimes still paper-based) scale where MCS operates and innovates. This involved a process of participants learning how their data were useful, such as one student who described “seeing the neighborhood through new eyes,” or for developing spatial arguments about proposed infrastructure and community changes. In the process, students used mobility as a resource for learning and became more connected to the places where they live, attend school, and engage in everyday activities. A promising outcome of the research reported in this chapter is insight about youth’s interconnected perspectives on place, data, and data-driven decision-making. This is perhaps not surprising given that the research team anticipated the kinds of mobile and geolocative data youth would generate and planned for sharing these data across sites. What was unknown at the time of the Seattle training but emerged as a key practice for MCS throughout implementations was how the particularities of local issues would fuel flexible tactics for data collection, management, sharing, and analysis. The implication of this for future adaptations of MCS – and perhaps for other models of multi-sited research on mobile teaching and learning – is that in order to understand participants’ learning processes or processes of change at the city-scale, researchers need to also anticipate, and accommodate, changes at the level of curriculum design. That is, local MCS adaptations will be both influenced by data and will influence data and how data are used. Finally, these key MCS design practices contribute to more expansive conceptions of what it means to be (in) a “smart and connected” city or community. Connecting more vital services to the grid or networking cities’ communications is important, but future efforts and mandates ought to incorporate the perspectives – and data-driven arguments – of young people. The kind of personally relevant data

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that youth gathered and analyzed suggests a major gap in the ways city planners and officials tend to think about the problems they confront and solve – often without input from young people (Taylor 2013). With participatory action and sustainability among the goals of smart cities initiatives (Townsend 2013), supporting youth to connect with place, helping youth learn how to use mobile technologies, and advancing youth data-driven decision-making are critical components of developing such future capacities. Moreover, there is another lesson to be taken from the connections youth made throughout the reported MCS implementations: orienting urban design around innovations for cities of the future must be coupled with discovering and documenting the social contexts and personal histories in which these designs will be placed (e.g., Gordon et al. 2016; Taylor and Hall 2013). Connecting to places in this way will make it more likely that “connected places” of the future will respond to locally relevant needs and desires and that innovative ideas are ideally driven by today’s youth.

7

Cross-References

▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ VR and AR for Future Education

References Angelidou, Margarita. 2015. Smart cities: A conjuncture of four forces. Cities 47: 95–106. Barron, Brigid, Caitlin K. Martin, Kimberley Gomez, Nichole Pinkard, and Kimberly Austin. 2014. Creative learning ecologies by design: Insights from the Digital Youth Network. In The Digital Youth Network: Cultivating digital media citizenship in urban communities, ed. Brigid Barron, Kimberly Gomez, Nichole Pinkard, and Caitlin K. Martin. Cambridge, MA: The MIT Press. Cole, Michael. 2006. The Fifth Dimension: An after-school program built on diversity. New York: Russell Sage Foundation. Elwood, Sarah, and Agnieszka Leszczynsky. 2013. New spatial media, new knowledge politics. Transactions of the Institute of British Geographers 38: 544–559. Farman, Jason. 2010. Mapping the digital empire: Google Earth and the process of postmodern cartography. New Media and Society 12 (6): 870–888. Gallagher, Kathleen, and Barry Freeman. 2011. Multi-sited ethnography, hypermedia and the productive hazards of digital methods: A struggle for liveness. Ethnography and Education 6 (3): 357–373. Gianna, Fracesco, and Monica Divitini. 2015. Technology-enhanced smart city learning: A systematic mapping of the literature. Interaction Design and Architecture(s) Journal, N. 27: 28–43. Gordon, Elyse, Sarah Elwood, and Katharyne Mitchell. 2016. Critical spatial learning: Participatory mapping, spatial histories, and youth civic engagement. Children’s Geographies 26: 1–15. Gunderson, Anne. 2017. More questions than answers: A review of gun violence in Chicago. Chicago Policy Review. https://tinyurl.com/yd7nok8x. Accessed 8 Aug 2017. Hall, Rogers, Jasmine Ma, and Ricardo Nemirovsky. 2015. Re-scaling bodies in/as representational instruments in GPS Drawing. In Learning technologies and the body: Integration and Implementation, ed. Victor R. Lee, 112–131. New York: Routledge.

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Hannerz, Ulf. 2003. Being there...and there...and there! Reflections on multi-site ethnography. Ethnography 4 (2): 201–216. Hart, Roger. 1977. Children’s experience of place: A developmental study. New York: Irvington Publishers. Holden, Jeremiah. 2016. Mobile inquiry-as-play in mathematics teacher education. On the Horizon 24 (1): 71–81. Ito, Mizuko, Kris Gutierrez, Sonia Livingstone, Bill Penuel, Jean Rhodes, ..., S. Craig Watkins. 2013. Connected learning: An agenda for research and design. Irvine: Digital Media and Learning Research Hub. Kalir, Jeremiah. 2016. Preservice teacher mobile investigation and interpretation of everydaymathematics across settings. Journal of Technology and Teacher Education 24 (4): 415–442. Kingston, Richard. 2007. Public participation in local policy decision-making: The role of Web-based mapping. The Cartographic Journal 44 (2): 138–144. Lauriault, Racey P., and Jeremy Wood. 2009. GPS tracings-personal cartographies. The Cartographic Journal 46 (4): 360–365. Loshin, David. 2004. Naming conventions and semantic consistency. DM Review. Thomson Media. 14 (12). Peluso, Nancy. 1995. Whose woods are these? Counter-mapping forest territories in Kalimantan, Indonesia. Antipode 27 (4): 383–406. Picon, Antoine. 2015. Smart and connected cities: A spatialized intelligence. New York: Wiley. Ribes, David. 2014. Ethnography of scaling: Or, how to fit a national research infrastructure in the room. Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing, 158–170. Rosner, Daniela K., Hidekazu Saegusa, Jeremy Friedland, and Allison Chambliss. 2015. Walking by drawing. Proceedings of the 33rd annual ACM conference on human factors in computing systems, 397–406. Streeck, Jurgen, Charles Goodwin, and Curtis LeBaron. 2011. Embodied interaction in the material world: An introduction. In Embodied interaction: Language and body in the material world, ed. Jurgen Streeck, Charles Goodwin, and Curtis LeBaron. New York: Cambridge University Press. Taylor, K. H. 2013. Counter-mapping the neighborhood: A social design experiment for spatial justice (Doctoral dissertation). Vanderbilt University, Nashville, TN. Taylor, Katie H. 2017. Learning along lines: Locative literacies for reading and writing the city. Journal of the Learning Sciences. https://doi.org/10.1080/10508406.2017.1307198. Accessed 8 Aug 2017. Taylor, Katie H., and Rogers Hall. 2013. Counter-mapping the neighborhood on bicycles: Mobilizing youth to reimagine the city. Tech, Know, Learn 18: 65–93. Taylor, Katie H., and Nathan Phillips. 2017. Place-making. In Encyclopedia of out-of-school learning time, ed. Kylie Peppler. New York: SAGE. Taylor, Katie H., and Deborah Silvis 2017. Mobile City Science: Technology-supported collaborative learning at community scale. Philadelphia, PA: International Society of the Learning Sciences. Townsend, Anthony M. 2013. Smart cities: Big data, civic hackers, and the quest for a new utopia. New York: W.W. Norton and Company. Turner, William, Geoffrey Bowker, Les Gasser, and Manuel Zacklad. 2006. Information infrastructures for distributed collective practices. Computer Supported Cooperative Work 15: 93–110. Wilson, Matthew W. 2011. ‘Training the eye’: Formation of the geocoding subject. Social and Cultural Geography 12 (04): 357–376.

Mobile Learning and Education: Synthesis of Open-Access Research

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Teresa Cardoso and Renato Abreu

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Mobile Learning and Education: An Emergent Field of Research . . . . . . . . . . . . . . . . . . . . . . . . . 3 Mobile Learning and Education: Knowledge Systematization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Students’ Perceptions and Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Teachers’ Perceptions and Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Students and Teachers’ Perceptions and Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

In a global and mobile society characterized by the possibility of portability, mobile devices are no longer accessories, but they are rather resources that we cannot do without. In fact, nowadays no one seems willing to give up these tools recognizing its potential in various fields. For instance, they allow not only to shorten various distances but also to respond to different situations of our daily life, and also, of course, they provide moments of leisure and entertainment. T. Cardoso (*) LE@D, Elearning and Distance Education Lab, Department of Education and Distance Learning and Teaching, UID4372-FCT-MCTES, Universidade Aberta (Open University of Portugal), Lisbon, Portugal e-mail: [email protected]; [email protected] R. Abreu LE@D, Elearning and Distance Education Lab, UID4372-FCT-MCTES, Universidade Aberta (Open University of Portugal), Lisbon, Portugal Department of Laboratory Sciences and Community Health, Escola Superior de Tecnologia da Saúde de Lisboa, Instituto Politécnico de Lisboa, Lisbon, Portugal e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_85

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Thus, combining all these attributes, the benefit from them in education seems obvious. However, to what extent and how are mobile devices integrated in education? Is mobile learning or m-learning a reality? Or a fiction, instead? Therefore, the present study aims at clarifying these issues through a literature synthesis of research available in online databases. In this state of the art, m-learning is briefly characterized, namely, by describing some of its particular types and environments and also by a SWOT analysis (strengths, weaknesses, opportunities, and threats analysis). Students and teachers’ perceptions and practices on m-learning were also identified. We further identified determining factors that both students and teachers consider important in the use of mobile devices and in the acceptance of mobile learning. In short, the systematization of the analyzed literature summarizes experiences that promoted changes in both the alphabetization and digital literacy of the whole participating school communities. One can conclude that m-learning is a research area with a recent past, a dynamic present, and a promising future.

1

Introduction

The Horizon Report foresaw six emerging technologies that could revolutionize the current framework of the teaching of scientific research and the economy of countries until 2015 (New Media Consortium EDUCAUSE (Association) 2010). Among these emerging technologies and according to this report, mobile computing and open content were soon to reach the maximum point of use. As a result of the evolution of mobile technologies, education is entering in the so-called third wave technology called mobile learning (Sarrab and Elgamel 2013) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Thus, a new area of research arose to determine how these technologies can be used as learning tools (Kukulska-Hulme 2009), with the first projects emerging in the second half of the 1990s (Traxler 2005). There are evidences to suggest that mobile learning is growing in visibility and importance. Firstly, in the last decade, several studies have been developed on m-learning experiences, in formal and informal contexts, reporting positive results in the process of teaching and learning with relevant levels of adherence with regard to the acceptance of these technologies by the students (Attwell 2007). Secondly, we are witnessing an increase of workshops and conferences on the subject at all latitudes of the planet. As an example, there is the growing interest that mLearn conferences – Conferences on Mobile and Contextual Learning – are having within the scientific community, with successive meetings since 2002, being the last congress held in Istanbul. Thirdly, the community now has a peer-reviewed academic journal, the International Journal of Mobile and Blended Learning, as well as a professional research organization, the International Association for Mobile Learning.

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Hence, the mobile learning has gained clarity on the main issues, a well-defined research agenda, and a greater awareness of the need for the existence of guidelines and ethical frameworks. Nevertheless, it is still a field in which practice has not yet been standardized in terms of research, mainly in terms of methods and tools (Traxler 2005). Therefore, it is appropriate to summarize the current state of knowledge and research on the subject, so as to identify potentialities and constraints of this type of learning. In this text, the result of a literature review on m-learning is presented, considering documents available on the Internet at specialized electronic databases in education. A methodology focused on the criteria proposed by Rosenberg and Donald (1995) for the research of scientific evidence was adopted, thus claiming the comparability with the medical sciences, which have the largest collection of electronic databases on the Internet (McVeigh 2004). In addition, the selection of the analyzed publications was made in view of the recognition by experts in the field, their scientific committees, and, when possible, their impact factor as indicated in Table 1.

Table 1 Online databases searched for defining the corpus of this literature review. (Source: data collected for this study) Online journals and databases Educational Media International Revista de Educación a Distancia Journal of Educational Technology and Society eLearning Papers

Impact factor – – 0.824 –

Distance Education Computers and Education

0.725 2.630

Learning, Media and Technology RIED. Revista Iberoamericana de Educación a Distancia The International Review of Research in Open and Distance Learning Open Praxis

– –

Comunicar Informática na educação: teoria & prática The Internet and Higher Education

– –

American Journal of Distance Education Repositório Científico de Acesso Aberto de Portugal (RCAAP)

– –

– –

2.048

Uniform resource locator (URL) http://www.tandfonline.com http://www.um.es/ead/red/red.html http://www.ifets.info http://www.openeducationeuropa.eu/pt/ elearning_papers http://www.tandfonline.com http://www.journals.elsevier.com/ computers-and-education http://www.tandfonline.com http://ried.utpl.edu.ec http://www.irrodl.org/index.php/irrodl/ index http://openpraxis.org/index.php/ OpenPraxis/index http://www.revistacomunicar.com http://www.seer.ufrgs.br/index.php/ InfEducTeoriaPratica/index http://www.journals.elsevier.com/theinternet-and-higher-education http://www.tandfonline.com http://www.rcaap.pt/

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The last criterion considered to constitute the corpus of analysis for this study was the temporal filter defined between 2010 and 2014. This option was due primarily because of the speed of technological innovation when it comes to computers and therefore in the evolution of mobile devices and also so as to take into account the technical update and progress of m-learning.

2

Mobile Learning and Education: An Emergent Field of Research

M-learning is still an emerging research field (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). So, different actors and several factors are involved in conceptualizing it (Traxler 2007). This will determine the perceptions and expectations in its evolutionary process toward the future (Traxler 2009). Therefore, it is not surprising that various definitions arise, although one can already highlight the following attributes (cf. data collected for this study, namely, Traxler 2009): mobile learning is a “noisy” phenomenon, pervasive, and ubiquitous, creates new ways of commerce, changes the nature of work, promotes social change and at the same time is versatile in mobility, and navigates through “bite-sized” on a platform of mobile hardware. Thus, based on these attributes, m-learning can be defined as the connected, interactive, and personalized use of portable devices in classrooms, in collaborative learning, in fieldwork, and in advice and guidance for students (Traxler 2011). This definition means that mobile learning can include the following technological options: personal digital assistants (PDAs), mobile phones with SMS, smartphones, tablets, game consoles, iPods, and wireless infrastructures (Traxler 2005). However, this is still one characterization among others. It is, perhaps, technocentric and maybe unstable and focused on the set of hardware devices previously mentioned (Traxler 2005). It is therefore important to explore other approaches to this contemporary phenomenon. M-learning is also a reality in online education, and knowing the latter results from the evolution of e-learning, it is also important to note that online education is expanding at great speed in primary and secondary education as well as in higher education (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Most of the educational institutions are aware that change is a constant feature in the lives of students (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). That is why they continuously analyze ways to incorporate change in their practices. However, some traditional higher education institutions are hesitant to introduce e-learning in their teaching methodologies, like m-learning as well. Despite being innovative and technically achievable, incorporating pedagogical benefits, and currently knowing visibility and growing importance in higher education (Traxler 2007), m-learning may eventually have no possibility of institutional large-scale implementation in the near future (Traxler 2010) (see ▶ Chap. 6, “Micro-Credentialing in Mobile Learning: Implications for Impactful Design”). For m-learning in higher education to become a successful story, it is important to address the social, cultural, and organizational factors involved (see ▶ Chap. 59, “Adapting to Change: A Reflective History of Online Graduate Certificate and Its Implications for

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Teaching Geography”). These can be formal and explicit and tacit or informal and may vary greatly in all institutions and within each of them (Traxler 2009). Adding to this problem, most of the work done on m-learning in universities is still in a pilotphase testing, which points to considerable difficulties in the support and development of new teaching methodologies (Traxler 2009) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Another political action line for higher education institutions to equate is the desirable availability of open content to the world, that is, the higher education institutions’ repositories of open educational resources must adapt their characteristics, so that their contents (at the level of creation, publication, exploration, acquisition, access, use, and reuse of learning objects) can be accessed from mobile devices. This action line of opencontent democratization is reflected in the 2004 and 2010 Horizon Reports, which referred to, respectively, learning objects and open contents, predicting its short-term impact due to the current trend of availability of open contents, free of charge on the Internet, which can be viewed on mobile devices (Tabuenca et al. 2012). In fact, mobile devices produce almost a universal effect of connectivity between people, data, content, and media (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). So, we are watching changes and disruptions in learning that are launching the countries to emerge as a knowledge society oriented toward technology (see ▶ Chap. 34, “Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts”). The success of these societies depends on the ability to promote the acquisition of key skills and expand opportunities headed for more flexible and innovative ways of learning for all citizens, including non-formal education. Bearing in mind that in Asia almost everyone has a mobile phone or will soon have one, an Indian researcher argued that Asian countries can establish and use mobile networks for learning. The researcher proposed an “each-one-teach-one” mobile network project as a strategy to access to new knowledge, especially for the Asian countries and in general for all countries of the world. Mobile network proposals will work on the principle that those who want to teach and those who want to learn should have a free and open service to connect and share knowledge (Misra 2012). In addition, the development of m-learning has often been driven by educational need, technological innovation, and funding opportunities. M-learning should be characterized as a specific project within the education systems, and its strengths, weaknesses, opportunities, and threats (SWOT) are, generally, those shown in Fig. 1. As shown in Table 2, some information can be added, by further explaining the factors identified in Fig. 1.

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Mobile Learning and Education: Knowledge Systematization

As a result of scientific research, there is a vast repository of case studies, essays, and pilot studies publicly available, which enable to identify three main types of m-learning: personalized, situated, and authentic (Traxler 2007) (see also

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+ Generational change; Skills improvement; Sustainability (Cobcroft et al., 2006)

–Evidence and evaluation (Cobcroft et al., 2006)

+ Scale and generality (Farrow, 2003)

–Integration (Farrow, 2003)

M-learning SWOT Analysis √ Encourage learning “anywhere, anytime” √ Improve accessibility and 21st century social interactions √ Activate a personalized learning experience √ Integrate learning environments

! Change in Higher Education Learing ! Institutional changes ! Technological changes (Cobcroft et al., 2006)

Fig. 1 M-learning SWOT analysis. (Source: data collected for this study)

▶ Chap. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 27, “Tutors in Pockets for Economics”). The personalized m-learning is defined as the learning that resorts to different pedagogical approaches and that acknowledges social, cognitive, and physical differences and diversity in designing contents, interfaces, and mobile devices. The situated m-learning occurs during the learning activity, in rather specific contexts. Finally, the authentic m-learning is the learning that uses real-world problems and projects that are relevant and of interest to the student. This typology may be further differentiated, when instilled by the correct applicability of the available mobile technologies. This, in turn, enables constant changes of educational contexts or environments (Nash 2007), thus facilitating the integration by the student of the real world into the world of tools or devices and successfully showing achievement of the learning goals. Hence, it is possible to create different m-learning environments characterized by different aspects (Traxler 2009): Oriented technology – some innovations in mobile devices are implemented in the academic environment to determine the technical feasibility and the pedagogic features of such devices. Portable miniaturization of e-learning – learning using mobile technologies is much more flexible and replaces with great efficacy the static technologies of desktop computers, taking into account the privileged environment of e-learning. Connected classroom – the same technologies are used in the classroom to support collaborative learning, together with other technologies, such as interactive whiteboards.

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Table 2 Detailed m-learning SWOT analysis (Source: data collected for this study) Strengths(S)  Generational change: the identification in today’s young people of the desire to be creative, to collaborate, and thus to gain celebrity status is seen as belonging to the “Generation C.” This trend indicates a movement toward the DIY (do it yourself), which is presented as the creation of content and the dissemination of knowledge led by the users themselves (Cobcroft et al. 2006)  Skills improvement: the mobile devices can help improve literacy and numeracy skills; encourage independent and collaborative learning experiences; identify areas where students need assistance and support; mitigate resistance to change using ICT (information and communication technology); engage reluctant learners, allowing that they stay more focused for longer periods; and promote the self-confidence and self-esteem (Cobcroft et al. 2006)  Sustainability: the sustainability of m-learning pilot studies and experiences in educational settings tends to achieve a balance between costs, on the one hand, and the creation of financial profitability and social capital, on the other hand (Cobcroft et al. 2006)  Scale and generality: the m-learning community is excited to understand how some pilot studies, projects, and experiences in educational settings successfully can be applied on a larger scale in order to find the balance between the possible generality and the specificity (Farrow 2003) Opportunities (O) The opportunities commonly associated to m-learning are essentially the following: Encourage learning “anywhere, anytime” Improve accessibility and the twenty-first-century social interactions Activate a personalized learning experience Integrate learning environments However, the enthusiasm for the incredible potential of the mobile devices must be tempered by the functional, cognitive, and social considerable challenges, which are identified within m-learning (Farrow 2003)

Weaknesses(W) - Integration: the integration of mobile learning in other learning systems based on technology and institutional and organizational processes has not been a top priority (Farrow 2003) - Evidence and evaluation: the scientific community should give signs of greater relevance, meaning, and impact on the evaluation of m-learning, as it has presented more intrinsic problems than the evaluation of e-learning (Cobcroft et al. 2006)

Threats (T) ! Change in higher education learning: the predisposition for an increasing availability of mobile and wireless devices has direct implications on the blended learning environments, which combine physical and virtual strategies. These environments have in turn implications for students (learning experience) and teachers (practices) and for the planning of technology and sustainability. Thus, these are critical aspects in the implementation of m-learning in higher education institutions (Cobcroft et al. 2006) ! Institutional changes: the reference model to determine the most suitable technological choices in implementing m-learning should include criteria such as adequacy and access, easiness of use and reliability, costs, new trends in pedagogy, interactivity, organizational issues, innovation, speed, and alignment with the institutional goals. Consequently, the institutions should understand that the adoption of m-learning is in need of a strategic approach to risk management, with an assessment of the adequacy, quality, compatibility, and cost of the devices. Otherwise, it will be very difficult to keep the resources and minimize the change fatigue (Cobcroft et al. 2006) ! Technological changes: the wide availability of technology is essential, but by itself it is not enough for learning environments to be considered effective (Cobcroft et al. 2006)

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Additive technology – the mobile technologies are enhanced with additional functionalities, for instance, video capture, to improve the educational experience, which would otherwise be difficult or impossible to achieve. Just-in-time training – mobile devices are used to improve the productivity and efficiency of the workers in geographic mobility, providing just-in-time information and support. Environment and development – technologies are used to cope with challenges regarding environment and infrastructure, supporting conventional education, in places in which it would be difficult to implement e-learning technologies. In these educational scenarios, it is useful to analyze students and/or teachers’ perceptions and practices regarding m-learning and the ownership of mobile devices by either or both of them. This will be done in the following sections, on the basis of a synthesis of some of the examples included in the open access research corpus of this study.

3.1

Students’ Perceptions and Practices

Lowenthal (2010) carried out a study in which he analyzed the factors or determinants of the behavioral impact that explain the adhesion of students (51 men; 62 women) to m-learning at a university in the USA. These determinants included the expectation of performance and the expectation of the effort and selfmanagement of learning, all mediated by age, gender, or both. The regression coefficients showed strong significant relationship between the expected performance and the expected effort and behavioral willingness to use a mobile learning strategy. Researchers have shown also that the age and sex had no impact on mediation. Two years later, Firmin et al. (2012) reported on the results of a qualitative research study carried out with 3000 students of the American University, located in the Midwest, on their phenomenological perspectives (perceptions and motivations) with regard to using the BlackBerry. Three key aspects inductively emerged during the interview process: the students described the motivations that influenced their decisions of buying and using the BlackBerry, including the rather quick and convenient access to the e-mail and the Internet that these smartphones offer; all students compared their BlackBerry with the iPhone, valuing their mobile phones as only moderately “cool” and technologically less advanced; and students reported specific perceptions related to the use of the BlackBerry, which included a financial stigma and a stereotype of entrepreneur. More recently, Gikas and Grant (2013) studied not only the students’ perceptions regarding learning using mobile devices but also the role that these play in virtual communities. This qualitative research study focused on eight students of three universities of the USA. These students used the mobile devices on their courses for at least two semesters. The main data collection method used to assess the students’ perceptions was the focus group. Two specific themes emerged from the

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data of the interviews: benefits and frustrations regarding students’ learning related to the use of mobile devices. Participants in this study acknowledged the changes that occurred in learning, regardless of the limitations they identified, including the phobia of incorrect functioning of technologies, small keyboards that difficult typing, and the possible potential of distraction that these technologies offer. It is, however, important to mention that the participants that volunteered to share their experiences did so because they believed that mobile devices had an impact on their learning. Another study, both quantitative and of transversal observation nature, was carried out by researchers from a Dutch university with the participation of 3132 students. They answered an online survey on ownership and use of laptops, tablets, and smartphones, as part of a strategy by the university, called bring your own device (BYOD), to promote learning improvements resorting to mobile computational devices. The survey included the demographic characterization of the students, information about parents’ earnings (indicator of the socioeconomic status of the student), and questions regarding the usability of the mobile devices. The results showed that 96% of the students owned at least one mobile device (laptop, tablet, or smartphone). By using an econometric model, it was perceived that the students’ earnings, their family earnings, and typology, gender, and immigration have a statistically significant effect with regard to having a mobile device. The high percentages of mobile device ownership are, however, not associated by any means to the support given to the classes attended by the students. In this study, the students did not seem much enthusiastic to bring their mobile devices to the classes, choosing rather to leave their laptops at home. In general, the students only brought the laptop to the university once every 4 days, as they felt it was too heavy to carry. As a consequence, the students were not keen on the BYOD strategy despite the didactic benefits that this could provide to their education. Therefore, it seems that the strategy defined by that university was hampered (Kobus et al. 2013). In Spain, research was carried out to analyze the use and the concept of mobility of the information and communication technologies (ICT) of a group of 67 postgraduate students participating in an experiment of m-learning at the IL3 Institute for Life Long Learning of the University of Barcelona. During the online post-graduation course, designed from a traditional e-learning perspective, the students had access to a tablet (iPad) to work and for professional and private life use, as well. Before and after the course, an original survey was applied; it was designed to analyze the students’ attitudes, opinions, and habits. Trends in the use of mobile devices and the participants’ perceptions, from exams, goals, grading, as well as the integration with other technologies and genuine applications in the students’ personal, social, and professional life, were analyzed. The research aimed at answering five questions; the first question was “for what purposes do students usually use the Internet before and after the e-learning experience?” The authors concluded that the use of the Internet is mainly focused on the participation in social networks in order to produce information (and not necessarily only from a perspective of collecting information). The answers to the second question – “for what purpose do students use mobile devices in the framework of their formal/professional education before and after the

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m-learning experience?” – enabled them to state that the use of mobile devices changed significantly. Thus, the authors emphasize the students’ tendency to focus the attention on multifunction mobile devices and on using the tablet as an extension of the computer. Regarding the third and fourth questions (“what use is made of the mobile device in their daily life before and after the m-learning experience?” and “does your evaluation of the Internet and of the mobile devices change after the e-learning experience?”), the results show that the introduction of the iPad led to a change in the habits of connection and use of technology. This caused direct implications in the students’ daily, personal, and professional life, and a key change on the processes of accessing information was witnessed. Finally, with the sample of their study, the researchers were unable to prove that the Bernoff profiles were reproduced (Oró et al. 2013). In another Spanish research, Sevillano-Garcia and Vazquez-Cano (2015) evaluated the acceptance, the incidence, and the use of mobile devices (tablets and smartphones) among higher education students, with a sample of 419 students from three Spanish public universities. Through a quantitative methodology, the authors identified the factors that affect and promote the use of mobile devices in those universities. The results led to a holistic view of ICT innovation in three main areas: teaching model (blended learning/distance education), study aptitude, and general skills. Moreover, the results, according to the authors, can also be used as references to predict, explain, and improve the integration of mobile devices, in order to promote learning activities and general skills in higher education. In a different geographic context and with a higher sample, aiming at exploring the educational effectiveness of LMS for mobile devices, Han and Shin (2016) analyzed the demographic background (age and employment status) and reported psychological data (self-efficacy, innovation, ease of usage, and utility of LMS for mobile devices) of 1604 university students in South Korea. The results of linear regression analysis showed that age and employment status are significant factors in predicting the adoption of LMS for mobile devices and that there is potential connections between the use of LMS for mobile devices and students’ gender, age, and psychological characteristics. In addition, the study proved that the use of a LMS for mobile devices positively influenced the academic achievement of students. For Aish and Love (2013), the successful implementation of m-learning in higher education is essentially based upon the acceptance of the users. Hence, taking into account the unified theory of acceptance and use of technology (UTAUT), coined by Venkatesh, they proposed a model to identify the enhancing factors of m-learning acceptance. They also studied whether the previous experience with mobile devices affected the m-learning acceptance. A model of structural equations was used to analyze data gathered from 174 students of the Brunel University. The results indicated that the performance and effort expectation, the influence of the teachers, the quality of the service, and the capacity of personal innovation are significant factors that affect the behavioral intention of adhering to m-learning. With regard to previous experience with mobile devices, this was also considered an important factor in the behavioral intention.

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To summarize, it can be inferred that the determinant factors of the behavioral impact that explain why students adhere to m-learning are the following: • • • • • •

Expectation about performance, effort, and learning self-management. Influence of the teachers. Quality of the mobile service. Personal ability to innovate. Key changes on the processes of accessing information. Previous experience with mobile devices.

Summarizing now the factors regarding the use of mobile devices, the following two were perceived: rather quick and convenient access to the e-mail and the Internet and students’ earnings, their family earnings, and typology, gender, and immigration.

3.2

Teachers’ Perceptions and Practices

In this section some factors that determine the adhesion of teachers to m-learning and their attitude toward it are contextualized, as it is deemed important also to understand whether teachers define their mediated activities by mobile devices. Firstly, it is considered a study developed by four Spanish researchers who analyzed the feasibility of the incorporation of mobile technological support in educational practice, assessing the level of acceptance of this innovative measure. The sample of the surveyed population included 50 participants, grouped into 3 distinct sets: teachers of the University of Alcalá, specializing in technology; students who had their master’s in teacher education at the same university, in the school year 2011–2012; and former students. The results revealed a broad acceptance of the incorporation of mobile devices, as well as a high degree of awareness of some of its effects. Different levels of teachers’ former training needs were also perceived (Álvarez et al. 2013). In the same year, Mifsud et al. (2013) presented different perspectives on the role of the teacher equipped with PDAs (Palm IIIc and iPAQ PPPs) in the classroom, describing four studies in two countries (Norway and the USA). The general aim of those studies was to understand how teachers use the new tools in different educational contexts. The teachers of the Hedland Primary School (Norway) had no experience in the use of PDA in the classroom, but they revealed an assimilation of its functionalities aligned with the historical and chronological development of technology (books, a typewriter, and so on). In other words, teachers took advantage of this connectivity when resorting to the oldest and most familiar ways of planning the classroom activities, using the PDAs as a new form of book. This contrasts with the teachers’ attitude of the Midlands Intermediate School (USA), in which these types of mediated actions seem to be in regular use in the classroom. However, these teachers were more experienced in the use of PDA, as it was the fifth year of adoption of the PDA in the classroom, and revealed stronger opinions about the

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mediation of the PDAs. Finally, Mifsud et al. (2013) stated that it is not enough to introduce a new tool like the PDA in the classroom and wait for the teaching practice to change automatically. That is, teachers need to be aware of the new tool; they need to become proficient in their use, to realize their usefulness, and to be able to reflect on the advantages and restrictions of the tool in the context of learning, so as to take out all the benefits of its use in the classroom. More recently, again in the USA, O’Bannon and Thomas (2015) analyzed the perceptions of 245 teachers of Kentucky and Tennessee states about the advantages and disadvantages of using mobile phones in the classroom. The results indicated that almost half of the teachers (45%) approved the use of mobile phones in the classroom, while a quarter (25%) was against their use, and about one-third (30%) was uncertain. Teachers perceived the features/functions of mobile phones to be useful in the classroom, identifying the Internet access and the use of educational apps as an added value. These teachers discriminated cyberbullying and the access to inappropriate content as the main constraint to the use of mobile phones in the classroom. Another issue to bear in mind as far as the “digital teachers” or “technological teachers” are concerned is the fact that they can be recognized as online tutors. Indeed, Mathew and Sapsed (2012) suggest that in distance learning programs, both technology and pedagogy are crucial and mutually dependent elements and that the online tutors take on roles that go beyond the traditional scope of teaching. Besides, they are frequently forced to assume roles of adviser that fit more the skills of a counselor or of another professional from a different area. Of the analyzed studies, it may be suggested that the proactive attitude of teachers toward m-learning involves: • • • • •

Assuming the role of online tutors. Showing a wide acceptance in the use of mobile devices. Seeking prior training actions for different purposes. Becoming proficient in the use of mobile devices. Realizing the usefulness and reflecting on the advantages and constraints of mobile devices in the context of formal learning.

3.3

Students and Teachers’ Perceptions and Practices

Among the analyzed studies portraying different contexts, there are still those which refer to the m-learning perceptions and/or practices of both students and teachers. For example, studies on m-learning have also been developed in the field of health research, namely, in the area of self-efficacy, as the case of a research which took place in a nursing college in Canada. The aim of this research was to evaluate the teachers and students’ self-efficacy in the use of the full potential of mobile technology, in the process of teaching and learning in educational settings and in clinical practice. Within this transversal study, implemented in two education programs, 100 and 21 teachers and students were interviewed. The results showed a

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high level of ownership and use of mobile devices among them. The result of the median of the mobile self-efficacy was 75 on a scale of 100, indicating that both the teachers and the students were highly confident in the use of mobile technologies and prepared to engage themselves in mobile learning (Kenny et al. 2012). Another of the research focus on m-learning, as pointed out before, are the guidelines and practices regarding the use of the mobile phone by teachers and students. This goal was sought after by Obringer and Coffrey in their study, which took place in Obringer and Coffey 2007. For this purpose, a questionnaire was sent at random to 200 directors of US high schools, involving the 50 states. The response rate was 56% from all regions of the country. The main results are summarized to the following: – The majority of the schools presents guidelines on the use of mobile phones. – Parents generally support the use of mobile phones at school. – In the classroom the teachers use mostly their mobile phones to solve issues not related to the school subjects. – There is disciplinary action for inappropriate use of the mobile phone by the students, varying from a mild admonishment to the confiscation of the mobile phone in school. Seven years later, a different research had as its starting point the following question: “How can mobile phones be used to improve teaching and learning in science in secondary schools?” In this study, a group of teachers (5 men and 13 women) from Sri Lanka developed four lessons on household chemical products, functions and reactions of a voltaic cell, interactions between organisms and the environment, and the diversity of leaves. These lessons explored the features of mobile phone cameras, instead of its communication functions. A qualitative methodological approach was used to analyze the data collected, from the teachers’ planning to observations of lessons, and subsequently interviews were put forward with a number of students. The results showed that the use of images and videos captured by the students with their mobile phones allowed teachers to bring the outside world into the classroom and to provide unbiased data. These enhance the assessment of learning and also allow the teachers to clarify possible misconceptions of the students (Ekanayake and Wishart 2014). Still in the scope of the use of a mobile phone in an educational setting, more specifically in Portuguese primary and secondary schools, Carrega (2011) developed a case study on the representation of students and teachers of the 9th and the 12th grade. The results of the survey to 179 students and 88 teachers of these grades indicate that students and teachers have different representations, but the majority of them are not very receptive to using mobile phone in educational contexts. The students of the two grades stated that they were unable to indicate a situation in which teachers could teach better a subject by using a mobile phone. They could neither imagine a situation in which they could learn better a subject by using a mobile phone. As for teachers, a significant percentage of them did not recognize pedagogical advantages in using a mobile phone.

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A process that created great controversy in the past few years was a study on the impact of the efforts of m-learning implementation in the Estonian school system. The results showed different reactions by students, school leaders, and teachers. Although all of them have almost all the needed tools and skills, teachers showed an almost total lack of motivation on promoting mobile learning. Researchers presented some positive and negative scenarios and predicted huge problems if the teachers’ training remains unchanged and if the policies of Internet security (e-safety) are not adequately developed (Lorenz and Kikkas 2013). Nowadays, a growing number of teachers are beginning to use mobile devices and “clickers” (buttons which are physically attached to the PC) to evaluate the answers of students in the classroom in formative surveys such as quizzes. In such a context, Stowell (2015) compared the number of correct, incorrect, and missing answers of students who answered to survey questions in the classroom using mobile devices and clickers. In this exploratory research, students who used mobile devices had a greater number of missing answers and fewer correct answers than those who used clickers, but there was no difference in the final grades. In general, the attitude of students toward the use of mobile devices was favorable. However, 31% was unable to connect to the Internet “sometimes” or “most of the time.” Besides that, most (58%) reported “never” or “rarely” having been distracted by the misuse of the mobile device during the class.

4

Future Directions

The m-learning community has been focused on pedagogy and technology proving to be able to strengthen, broaden, enrich, and validate concepts of the learning activity itself, as well as to challenge and defy it, now and in the near future. However, the advances achieved in m-learning are not exempt from the risks of learning massification and industrialization (Traxler 2010) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). M-learning has the potential to convey the learning process to people, communities, and isolated countries, offering students the opportunity to take control of their learning experiences in a different way. Thus, students will have the ability to engage themselves in information and discussion activities, as part of real life, by becoming instruments of social policy. However, one cannot forget that mobile technologies used to teach may eventually turn out to be dysfunctional. This can be the case when they are vehicles of a certain culture or a spare and undesirable social luggage or just when they are empty containers loaded with unnecessary and inadequate expectations (Traxler and Kukulska-Hulme 2006). Research on m-learning should question and deepen wider learning theories that include new fields of knowledge such as cognitive psychology, bioinformatics, nanotechnology, and artificial intelligence. Research on motivation levels generated by m-learning should be further studied by the scientific community in order to become a universal truth, since to this date the evidence is scarce (Traxler 2011).

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In general it is possible to call m-learning to any form of learning through mobile devices, energetically autonomous and small enough to go along with people anywhere and anytime (Roschelle 2003). Currently students inhabit a social, cultural, and technological environment, where knowledge is built and shared, as part of a social process. Mobile technologies, managed effectively, can withstand constructivist approaches in learning and can be observed as tools to expand the discussion beyond the classroom and provide new ways for students to collaborate and communicate within their class or “around the world,” creating their own learning contents (Cobcroft et al. 2006). This reflects the need to validate a conceptual framework of m-learning to improve quality, increase flexibility, and customize and centralize the learning process on the student. This conceptual framework should be based on four fundamental principles (Cobcroft et al. 2006): engage students, recognize the context of learning, challenge students, and provide practical activity. The crucial factor to consider all integrating aspects of the m-learning development, including its conceptual framework, is the identification of the “turning point” in which the adoption of mobile and wireless technologies will gain a critical mass that will force the institutions to adopt effective and efficient plans and approaches in m-learning. M-learning has been presented throughout this text as an approach to teaching and learning that allows to acquire any user-desired knowledge (any content), regardless of time (at any time) and space (anywhere). Living with mobile devices is so intrinsic to current students that we would rather call them digital students, and so teaching without the use of such devices can be considered a waste. A prospective exercise, based on our literature review, results in systematized social habits, technological trends, and pedagogical solutions that m-learning will materialize in the short term or even that are already in progress. For example, with regard to the life cycle of SMS technology, it has reached a full maturity stage, as it is integrated in almost all the learning management systems, allowing better communication between all the people participating in education processes. Beyond what may be said as the massification of SMS, the ubiquitous learning (wearable technologies, biotechnology, and m-learning) will also be consolidated. In other words, the wearable technology and the biotechnology will become increasingly commercially viable, and the way for the integration of these technologies will be the m-learning, in a true ubiquitous learning, again resetting the e-learning in the educational agendas. Another pathway for the future of m-learning will, surely, be the mobile quizzes, as this type of testing has proven its effectiveness in improving learning strategies. Similarly, smartphones and tablets have become powerful devices due to the diversity of their user-friendly multimedia features. Being able to publish and share content anywhere through mobile devices, anytime and effortlessly, is an attribute of the current digital students. There are already several tools, applications, and technologies available to teachers and students. This will continue to enhance the increase in the use of multimedia materials in the learning activities with mobile devices. In this context, podcasts, vodcasts, screencasts, apps for m-learning, serious games, and augmented reality can be highlighted (Orlando 2016).

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We will certainly find a more comprehensive development of apps designed for m-learning, available to students and teachers at a low-cost or for free, enabling innovation in learning environments and reducing the gap between formal and informal learning through, for example, the Mobile Application Technology (MAT) (Khaddage et al. 2016). These applications are characterized by the variability and awareness of the context and the adaptation of the environments in which they are used. Current trends in the design of apps for teaching focus on four key aspects: (1) quality of content, (2) feedback and a good leveling of the learning stages, (3) richness of the interactions, and (4) ability of the applications to adapt themselves. With regard to the podcast, it is one of the tools with fastest growth in the context of distance education and e-learning, especially for the learning of languages (including English). Such applications make use of technology which is called adaptive for learning, i.e., allowing students to adapt to the proposed tasks. Despite the current development, it is expected that the advancement of technology, combined with low fees in data communications, the presence of wireless networks in most places, including public transport and buildings, as well as the wide dissemination and marketing of different mobile devices, namely, smartphones, will continue to be determining factors for the progressive use of podcasts in activities dedicated not only to the learning of foreign languages but also in different scientific areas like health sciences (Abreu 2017). These scientific areas have been further integrating serious games and augmented reality to foster collaboration and problem-solving-based learning and, at the same time, to increase the students’ performance and motivation. Nevertheless, the growth potential of those two technologies is still in an early stage. The possibilities and benefits of augmented reality have been a topic of recent studies, so there is a need for more research in this area (Chang et al. 2015) (see also ▶ Chaps. 75, “Augmented Reality and 3D Technologies: Mapping Case Studies in Education, ▶ 77, “Augmented Reality in Education” and ▶ 79, “VR and AR for Future Education”). By developing the research on this topic, as well as the growing of open-source software (and, thus, decreasing the costs involved), the integration of augmented reality in distance education and e-learning, and consequently in m-learning, could be massified. In addition, the mobile access to open educational resources (OER) will tend to be maximized by improving the direct interaction between the users or user groups and thus strengthen the link between the academic and the professional knowledge, toward an integration of learning environments: formal, informal, and non-formal and individual or collective. On the other hand, the Massive Open Online Course (MOOC), an example of distance education essentially based on online hosted learning courses in platforms of higher education institutions, faces the challenge of being accessible from mobile devices. Thus, despite the limitations in the mobile adaptation of MOOC platforms, which mainly affect their visibility, it is necessary to redefine the initial design process, in agreement with the principles of m-learning, in order to accommodate these courses for users in real mobile learning situations (González et al. 2016). Moreover, MOOC platforms should be designed to incorporate collaborative aspects and educational networks, enabling a clear distinction in

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pathways of learning and also of virtual learning environments (Teixeira et al. 2015). The motivational aspects should also be considered, in order to avoid the course dropouts and to promote learning. Hence, it is very important to consider some techniques of gamification to stimulate mobile learning. The Moodle platform is also facing the challenge of repositioning itself as a LMS that allows greater accessibility through mobile devices. This implies the existence of freer Android and iOS applications that allow the overall functionality of Moodle on smaller screens. In addition, Moodle has to uphold the ability of mobile devices to save image, audio, and video files in a more interactive way than the current MLE-Moodle extension. However, in the near future, it is desirable that higher education institutions produce themselves their own virtual learning environments and do not depend solely on already institutionalized environments (e.g., Moodle), because open, flexible, and innovative environments that integrate personal, social, and institutional environments are needed (Salinas 2016). In short, the development of m-learning in prospective terms will continue to be driven by educational needs, technological innovations, and funding opportunities. Therefore, m-learning should be, as for now, a specific development within the educational systems.

5

Cross-References

▶ Adapting to Change: A Reflective History of Online Graduate Certificate and Its Implications for Teaching Geography ▶ Augmented Reality and 3D Technologies: Mapping Case Studies in Education ▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ Micro-credentialing in Mobile Learning: Implications for Impactful Design ▶ Student Feedback in Mobile Teaching and Learning ▶ Tutors in Pockets for Economics ▶ VR and AR for Future Education

References Abreu, Renato Danton Sampaio Ribeiro de. 2017. Mobile learning e educação em sau´de: estudo de caso no ensino superior de práticas laboratoriais. Tese de Doutoramento, Universidade Aberta, Lisboa. https://repositorioaberto.uab.pt/handle/10400.2/6612. Abu-Al-Aish, Ahmad, and Steve Love. 2013. Factors influencing students’ acceptance of m-learning: An investigation in higher education. The International Review of Research in Open and Distance Learning 14 (5): 82–107. Álvarez, Salvia García, Estefanía Bleda Marco, Francisco Javier Castillo García, and Macarena Cuerva Jimeno. 2013. La opinión de profesionales sobre la incorporación de soportes tecnológicos portátiles en las aulas. RED. Revista de Educación a Distancia (39): 144–162. http://www.um.es/ead/red/39/.

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Attwell, Graham. 2007. Personal learning environments-the future of eLearning? eLearning Papers 2 (1): 1–8. Carrega, João António Marques da Costa Batista. 2011. A utilização do telemóvel em contexto educativo: um estudo de caso sobre as representações de alunos e de professores dos 9 e 12 anos de escolaridade. Dissertação de Mestrado, Universidade Aberta, Lisboa. http:// repositorioaberto.uab.pt/handle/10400.2/2043. Chang, Yu-Lien, Huei-Tse Hou, Chao-Yang Pan, Yao-Ting Sung, and Kuo-En Chang. 2015. Apply an augmented reality in a mobile guidance to increase sense of place for heritage places. Educational Technology & Society 18 (2): 166–178. Cobcroft, Rachel S., Stephen J. Towers, Judith E. Smith, and Axel Bruns. 2006. Mobile learning in review: Opportunities and challenges for learners, teachers, and institutions. In Proceedings Online Learning and Teaching (OLT) conference 2006, En. Brisbane, 21–30. http://eprints.qut.edu.au/5399. Ekanayake, Sakunthala Yatigammana, and Jocelyn Wishart. 2014. Mobile phone images and video in science teaching and learning. Learning, Media and Technology 39 (2): 229–249. https://doi. org/10.1080/17439884.2013.825628. Farrow, Robert. 2003. Mobile learning: A meta-ethical taxonomy. In IADIS International Conference, Mobile Learning 2011. Avila. http://oro.open.ac.uk/29149/. Firmin, Michael W., Ruth L. Firmin, Katlyn M. Orient, Anna J. Edwards, and Jennifer M. Cunliff. 2012. The Blackberry image: Self-identified perceptions and motivations associated with college student Blackberry use. Educational Media International 49 (1): 19–32. https://doi. org/10.1080/09523987.2012.662622. Gikas, Joanne, and Michael M. Grant. 2013. Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. The Internet and Higher Education 19: 18–26. https://doi.org/10.1016/j.iheduc.2013.06.002. González, Carina S., César A. Collazos, and Roberto García. 2016. Desafío En El Diseño de MOOCs: Incorporación de Aspectos Para La Colaboración y La Gamificación. Revista de Educación a Distancia (RED), no. 48 (January). https://doi.org/10.6018/red/48/7. Han, Insook, and Shin, Won Sug. 2016. The use of a mobile learning management system and academic achievement of online students. Computers & Education 102: 79–89. https://doi.org/ 10.1016/j.compedu.2016.07.003. Kenny, Richard F., Jocelyne M.C. Van Neste-Kenny, Pamela A. Burton, Caroline L. Burton, Caroline L. Park, and Adnan Qayyum. 2012. Using self-efficacy to assess the readiness of nursing educators and students for mobile learning. The International Review of Research in Open and Distance Learning 13 (3): 277–296. Khaddage, Ferial, Wolfgang Müller, and Kim Flintoff. 2016. Advancing mobile learning in formal and informal settings via mobile app technology: Where to from Here, and how? Journal of Educational Technology & Society 19 (3): 16. Kobus, Martijn B.W., Piet Rietveld, and Jos N. van Ommeren. 2013. Ownership versus on-campus use of mobile IT devices by university students. Computers & Education 68: 29–41. https://doi. org/10.1016/j.compedu.2013.04.003. Kukulska-Hulme, Agnes. 2009. Will mobile learning change language learning? ReCALL 21 (2): 157–165. https://doi.org/10.1017/S0958344009000202. Lorenz, Birgy, and Kaido Kikkas. 2013. Standing at the crossroads: Mobile learning and cloud computing at Estonian schools. eLearning Papers 32 (10 pages). December. http://openeduca tioneuropa.eu/en/article/Standing-at-the-Crossroads%3A-Mobile-Learning-and-Cloud-Comput ing-at-Estonian-Schools-?paper=122239. Lowenthal, Jeffrey N. 2010. Using mobile learning: Determinates impacting behavioral intention. American Journal of Distance Education 24 (4): 195–206. https://doi.org/10.1080/ 08923647.2010.519947. Mathew, David, and Susan Sapsed. 2012. Distance learning students: Should we use technology or pedagogy to overcome work and life obstacles? eLearning Papers 31 (4 pages). November. http://openeducationeuropa.eu/en/article/Distance-Learning-Students%3A-Should-we-useTechnology-or-Pedagogy-to-Overcome-Work-and-Life-Obstacles%3F?paper=122650.

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McVeigh, Marie. 2004. Open access journals in the ISI citation databases: Analysis of impact factors and citation patterns a citation study from Thomson Scientific. Philadelphia: Thomson Corporation. http://ip-science.thomsonreuters.com/m/pdfs/openaccesscitations2.pdf. Mifsud, Louise, Anders I. Mørch, and Sigmund Lieberg. 2013. An analysis of teacher-defined activities with mobile technologies: Predecessor and successor tool use in the classroom. Learning, Media and Technology 38 (1): 41–56. https://doi.org/10.1080/ 17439884.2012.655746. Misra, P.K. 2012. Each-one-teach-one mobile networks: An innovative strategy for knowledge access in Asian countries. Educational Media International 49 (2): 109–122. https://doi.org/ 10.1080/09523987.2012.683961. Nash, Susan Smith. 2007. Mobile learning, cognitive architecture and the study of literature. Issues in Informing Science & Information Technology 4: 811. New Media Consortium, and EDUCAUSE (Association). 2010. The horizon report. Austin/Boulder: The New Media Consortium/EDUCAUSE Learning Initiative. http://www.nmc.org/pdf/ 2010-Horizon-Report.pdf. O’Bannon, Blanche W., and Kevin M. Thomas. 2015. Mobile phones in the classroom: Preservice teachers answer the call. Computers & Education 85 (July): 110–122. https://doi.org/10.1016/j. compedu.2015.02.010. Obringer, S. John, and Kent Coffey. 2007. Cell phones in American high schools: A national survey. Journal of Technology Studies 33 (1): 41–47. Orlando, John. 2016. A comparison of text, voice, and screencasting feedback to online students. American Journal of Distance Education 30 (3): 156–166. https://doi.org/10.1080/ 08923647.2016.1187472. Oró, Mariona Grané, Lucrezia Crescenzi Lanna, and Karina Olmedo Casas. 2013. Cambios en el uso y la concepción de las TIC, implementando el Mobile Learning. Revista de Educación a Distancia (37): 1–19. http://www.um.es/ead/red/37/. Roschelle, Jeremy. 2003. Keynote paper: Unlocking the learning value of wireless mobile devices. Journal of Computer Assisted Learning 19 (3): 260–272. Rosenberg, W., and A. Donald. 1995. Evidence based medicine: An approach to clinical problemsolving. British Medical Journal 310 (6987): 1122–1126. Salinas, Jesús. 2016. La Investigación Ante Los Desafíos de Los Escenarios de Aprendizaje Futuros. Revista de Educación a Distancia (RED), no. 50 (July). https://doi.org/10.6018/red/ 50/13. Sarrab, Mohamed, and Laila Elgamel. 2013. Contextual m-learning system for higher education providers in Oman. World Applied Sciences Journal 22 (10): 1412–1419. Sevillano-Garcia, M. Luisa, and Esteban Vazquez-Cano. 2015. The impact of digital mobile devices in higher education. Educational Technology & Society 18 (1): 106–119. Stowell, Jeffrey R. 2015. Use of clickers vs. mobile devices for classroom polling. Computers & Education 82 (March): 329–334. https://doi.org/10.1016/j.compedu.2014.12.008. Tabuenca, Bernardo, Hendrik Drachsler, Stefaan Ternier, and Marcus Specht. 2012. OER in the mobile era: Content repositories’ features for mobile devices and future trends. eLearning Papers (32): 1–16. Teixeira, António, Antonio Garcia-Cabot, Eva Garcia-Lopez, José Mota, and Luis de-Marcos. 2015. A new competence-based approach for personalizing MOOCs in a mobile collaborative and networked environment / Un Nuevo Enfoque Basado En Competencias Para La Personalización de MOOC En Un Entorno Móvil Colaborativo En Red. RIED. Revista Iberoamericana de Educación a Distancia 19 (1): 143–160. https://doi.org/10.5944/ ried.19.1.14578. Traxler, John. 2005. Defining mobile learning. In Proceedings, IADIS international conference on mobile learning, Malta, 261–266. http://www.iadisportal.org/mobile-learning-2005proceedings. Traxler, John. 2007. Defining, discussing and evaluating mobile learning: The moving finger writes and having writ. The International Review of Research in Open and Distance Learning 8 (2): 1–12.

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Traxler, John. 2009. Current state of mobile learning. In Ally, Mohamed (ed.), Mobile Learning: Transforming the Delivery of Education and Training, 9–24. AU Press, Athabasca University. Traxler, John. 2010. Students and mobile devices. Alternatives Journal 18 (2): 149–160. https://doi. org/10.1080/09687769.2010.492847. Traxler, John. 2011. Aprendizagem Móvel e Recursos Educativos Digitais do Futuro. Cadernos SACAUSEF VII (7): 35–46. http://crie.min-edu.pt/index.php?section=402&module= navigationmodule. Traxler, John, and Agnes Kukulska-Hulme. 2006. The evaluation of next generation learning technologies: The case of mobile learning. In ALT-C 2006: The next generation research proceedings, Heriot-Watt University, 143–152. Oxford: The Association for Learning Technology. http://oro.open.ac.uk/12295/1/JT_AKH_ALT_Research_2006_forORO.pdf, https://www.academia.edu/189346/The_Evaluation_of_Next_Generation_Learning_Technolo gies_the_Case_of_Mobile_Learning.

Part II Development of Mobile Application for Teaching and Learning

Development of Mobile Application for Higher Education: An Introduction

19

Yu (Aimee) Zhang and Jun Hu

Abstract

Mobile technology plays an important role in the economic development of a country as well as in teaching and learning. The development of mobile teaching and learning programs includes the efforts from course designers, system designers, software developers, teachers, educators, and students. From the industry point of view, it also needs the efforts from many service providers and content providers to implement a good mobile teaching and learning experience (Zhang, An analysis of collaboration in the Australian and Chinese mobile telecommunication markets. Doctor of Philosophy (Economics), University of Wollongong, 2012). All of these elements are essential for a good mobile teaching and learning program. The people who either worked in the classroom or behind the scenes (such as technical support staff) are vital for a successful mobile teaching and learning program. This chapter introduces real cases, experiences, and theories in developing mobile teaching and learning programs in different countries. The technical barriers, difficulties, and solutions are introduced in the following chapters. These invaluable experiences and cases shed light on future mobile teaching and learning system design and development. It has long been recognized that there is a close link between the sophistication of a country’s telecommunications systems and its economic prosperity (Zhang 2012). Although the origins of telecommunications lie in services provided along fixed, terrestrial linkages, the future of telecommunications is increasingly linked to Y. A. Zhang WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] J. Hu (*) WEMOSOFT, Wollongong, NSW, Australia Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_15

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wireless. Mobile technologies have grown dramatically during the last decade. It changed the styles of learning as well as living. While today mobile devices are still used primarily for voice and text message communication, people increasingly also use them to take and send pictures, listen to music, record video, watch TV, play games, surf the Internet, check email, manage their schedules, browse and create documents, and more (Zhang 2012). The mobile device market is large and fast growing. Telecom service providers, including the application service provider (ASP), Internet service provider (ISP), managed service provider (MSP), and managed Internet service provider (MISP), provided various services and applications to their users. Content providers, including designers, developers, and educators, developed good curriculums and contents for learners all over the world. They all worked together to provide the best learning experience for learners. All of these elements are essential for implementing mobile teaching and learning. These people who either worked in the classroom or behind the scenes should be appreciated for their contributions to the social and economic development of the world. The fast growth of mobile telecommunications also brought great opportunities for educators to put their teaching materials online and provide personalized education to learners all over the world. It reduced the geographic location barriers, cultural barriers, religious barriers, and language barriers across nations. But it also brought challenges for educators to learn, understand, and adopt all these advanced and changing technologies in their teaching processes. It is widely accepted that mobile technology has changed human’s life in many dimensions. But there are always things that need to be improved, such as security of information, quality of signals, high costs of mobile devices and connections, and merging of new technologies in everyday life. The convergence of various technologies increases the level of service substitution in the mobile telecommunications market. The development of 3G (third-generation networks) and 4G (next-generation cellular wireless access standards) also brought new opportunities for teaching and learning. However, the different types of mobile devices, different protocols for telecommunication industries, different operation systems on mobile devices, different developing languages and various versions, different regulations and policies in different countries and institutions, different adoptions of mobile devices and mobile technology by learners, different environments in different places, and different skill levels of the designers and educators all limited the developing of mobile teaching and learning programs for individual learners. It is expected that the future technologies and collaborations will bring solutions to these problems step by step. To develop a functional and appropriate educational mobile application or program, it is important to understand from the initial needs of mobile learning from the students. It helps to design a viable structure for mobile learning in terms of curriculum, teaching materials, system structures, engaging students, adopting new products and technology, and the confidential information of users. The curriculum designer should work closely with the application developer to digitalize the teaching materials into mobile software or program properly. The teachers should be equipped with technology skills and knowledge and a strong understanding of the functions and design of mobile teaching and learning applications and programs.

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The interactive design of learners’ reflection and further improvement is important for a viable mobile learning program. Therefore, in mobile learning programs, designer, developer, teachers, and learner should work together to enhance the learning experience instead of a one-way knowledge transfer. Due to the lack of mobile signals in and the high cost for mobile data transfer in some communities, mobile learning anywhere and anytime is not fully achieved. Successful mobile learning programs and applications must complement face-to-face learning and not try to replace traditional learning experience. The chapters in this section introduce the mobile teaching and learning programs designed and developed in different countries and for different groups of learners. These cases are from variety of disciplines and different countries. Some of the leading-edge technology or products for education are also introduced in this section to predict the future trends of mobile educational application development. Educators and students benefited from these mobile learning programs. They also shed light on the future design of mobile educational programs for industry partners and educators from universities, businesses, and institutions. In ▶ Chap. 20, “A Novel Education Pattern Applied to Global Crowd of All Ages: Mobile Education,” Fosse Zhang from Tsinghua University in China proposed a program that adopted a novel education program for all ages from health disciplines. A mobile education framework was introduced in this chapter, which consists of two components: an offline summarization system and an online system. Mobile education has many advantages. It can be used for pervasive education, flexible education, efficient education, individualized education, and life-long education. But the performance of mobile learning is also influenced by mobile devices, usability, functions, and current mobile technologies. The different users, including educators, parents, and students, were discussed. The author believed that mobile education has a great pedagogical potential and has been recognized by educational researchers. It has an ability to exert interest in learning, expand the learning community, and be helpful to develop life-study enthusiasm in social. In ▶ Chap. 24, “Construction Safety Knowledge Sharing via Smartphone Apps and Technologies,” Dr. Rita Yi Man Li discussed the importance of safety knowledge in mobile educational programs. Construction accident rates are high in many places, leading to high compensation, loss in manpower, and extension of time. Accidents may happen due to complex equipment and tools, outdoor operations and fast-changing design, and poor workforce safety behaviors and attitudes on sites. Generation Y (born between 1982 and 1995) is also known as Generation Why, Generation Next, the www generation, the Millennium Generation, or Echo Boomers. They grow up in a media- and technological-saturated world and used Internet more than watching TV. They used more mobile technologies than any other age groups. The common types of mobile communication software they used are Line (in Korea), WeChat (in China), and WhatsApp (in Hong Kong). Two construction safety cases from Korea and one case from the USA are discussed. The author suggested that young construction workers should be educated using the latest mobile technologies in view of the case studies in the USA and Korea and the popularity of mobile technologies. This chapter introduced a negative influence from

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mobile knowledge safety issue for special group of learners. It shed light on future design of mobile learning program as well as mobile regulations and policies too. Dr. Sharon Rees, Dr. Clint Moloney, and Dr. Helen Farley presented how mobile technologies facilitate teaching and learning in a very traditional way learned by seeing and doing nursing education in ▶ Chap. 23, “Mobile Learning Initiatives in Nursing Education.” Mobile learning has changed nursing education, providing learning to nurses when and where they need it and in a manner that achieved positive learning outcomes. The authors argued that mobile learning through YouTube and augmented reality offers the best of the traditional ways of learning combined with time- and cost-efficient means of technology use and greater theoretical knowledge. SMS and online learning aided reaching nurses in rural and isolated communities. Nurses can learn at a time and place suitable for them. Many isolated trials have occurred in nursing education over the years with the use of PDAs. This chapter adopted a grounded theory approach and investigated nurse’s current use of mobile technology and their beliefs around mobile learning. The chapter explored how and when nurses are undertaking continuing education, with the discovery of how they personally designed their learning. The authors indicated that organizations should take into account the obstacles and privacy issues when adopting mobile learning in a workplace. Combined mobile technology with social media in mobile learning for health education was also discussed in the chapter. The authors indicated that artificial intelligence (AI) agents will play an important role in the future of mobile teaching and learning. Although there are still many concerns for adopting mobile devices and technologies for health education, such as privacy issues, costs of learning, and using mobile devices in clinic areas, the authors believe that mobile learning will start to be used more for nursing education. Some interactive applications assist learners from health discipline and help spread the knowledge to the public. Language learning is an essential part of education, and the demand of learning a foreign language is increasing globally as in Dr. Izabel Rego de Andrade’s ▶ Chap. 26, “Development of Application to Learn Spanish as a Second Language: Lessons Learned”; a multidisciplinary team of researchers from applied linguistics and computer science developed an application to help Brazilian university students learning Spanish as a foreign language in accordance with the contemporary context and needs of learners. The findings from this chapter shed light on other mobile language learning projects providing invaluable advice to designers, educators, and policy makers. In ▶ Chap. 25, “Developing an Adaptive Mobile Tool to Scaffold the Communication and Vocabulary Acquisition of Language Learners,” Carrie Demmans Epp demonstrated an artificial intelligence (AI) adaptive mobile learning tool to support English language learners. From the results of various evaluations of the AI mobile features, functionality and design, the author shares their findings of app elements that should be considered when trying to select and use mobile apps to support student learning. With the performance improvement of mobile devices and technology evolving, the development of AI is expected to play an important role in everyone’s life. AI has been used globally in manufactory, data analysis, services,

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health, and education. This chapter explained how AI could assist the English language learners in their learning. The results help future design and development of AI-empowered language learning system and provide useful suggestions for the designers, developers, educators, policy makers, and learners all over the world. Dr. Aimee Zhang and Jun Hu are able to design and build an HTML5 web-based interactive program with gamification feature to help students practice Chinese character writing on mobile devices and conventional computers via browsers without installing any package. ▶ Chap. 28, “Development of Chinese Character-Writing Program for Mobile Devices” provides the design and implementation of this program. Instead of developing mobile application for IOS and Android systems as in their Tutors in Pockets application (see ▶ Chap. 27, “Tutors in Pockets for Economics”), the newly designed and developed projects suit all mobile phones and computers, which meet the needs from primary students and parents. Empowered by the beauty of Chinese characters and algorithm of handwriting programs, the project provides a practicing platform for student and teaching assistant tools for in-class and after-class group activities for teachers with students, students with parents, and students with their peers. A viable mobile learning program should provide flexibility to teachers and educators that suits their teaching requirements and the needs of the students. The program provides a free endless practicing platform for all Chinese learners. In ▶ Chap. 22, “SmartLab Technologies,” Hu Yin extends the ability of mobile application from the device itself to Internet of Things (IoT)-enabled objects in Smart Lab. Mobile application is not a supplementary method for teaching and learning of the IoT technology but the essential part. The Smart Lab technologies introduced mobile technologies into lab design and implementation. Educators and students will benefit in their teaching and learning with those technologies in the lab. This chapter describes future smart design of classrooms and labs for schools and universities. The limitation of adopting mobile technologies and devices in teaching and learning is not with the technology itself but the imaginations of the designers and policy makers. Qiongjie Luo and Haiping Du discussed the possibility of applying networked teleoperation in mobile teaching in ▶ Chap. 21, “Study on Networked Teleoperation Applied in Mobile Teaching”; their eye-opening research broadens the mobile teaching from predominated two-dimensional screen-based to solid steel robotic arm. The technology is now widely adopted in many industries, including industry, health, and education. This chapter introduces how mobile technology could be adopted in teleoperation and assist teaching and learning. The findings provide possible solutions for future cross-country or long-distance education programs. Mobile technologies can assist teaching and learning from various industries and disciplines. The chapters described mobile learning projects in different parts of the world.

References Zhang, Y. 2012. An analysis of collaboration in the Australian and Chinese mobile telecommunication markets. Doctor of Philosophy (Economics), University of Wollongong.

A Novel Education Pattern Applied to Global Crowd of All Ages: Mobile Education

20

Fosse (Jing) Zhang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Overview of Mobile Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Mobile Education and Traditional Education Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Mobile Education Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Advantages of Mobile Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Factors Influencing Mobile Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Mobile Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Mobile Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Online and Offline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Users of Mobile Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Educators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Parents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conclusion and Future Research Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

342 342 342 343 346 348 348 349 350 350 353 353 354 354 355 356 357

Abstract

This chapter gives a detail that introduces about mobile education. Firstly, this chapter provides an overview of mobile education. Secondly, this chapter introduces the mobile education application framework in the education industry. At present, it is accepted and can be utilized in many ways in the education industry. Through the review of this chapter, these factors have prompted to further

F. J. Zhang (*) MADE IT Biotech (Beijing) Limited, North Gate of Tsinghua University of Power Plant, Beijing, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_50

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research due to its potential in making teaching and learning more attractive and promising. Further, the relation and differences between mobile education and traditional education are put forth. Finally, users of mobile education are also studied. This chapter reveals in mobile education that the need for usage of technologies increases day by day today when information and accession to information gain importance. In fact, mobile devices are smaller and smaller. Technologies of mobile education provide a chance of lifelong learning for people.

1

Introduction

Today, information technologies (IT) and mobile communication technologies develop rapidly and are increasingly impacting the whole world. Researchers and developers worldwide have put their efforts into the design, development, and use of information and communication technology to support teaching and learning (Lucke and Specht 2012). Mobile education is a component by pedagogical way, technological disciplines, and challenging ideas currently. As the characteristics of ubiquitous learning, we shall call it as pervasive education. The people are in a learning community now, and knowledge is not only acquired from teachers and learning materials but also the spread of knowledge comes more from the Internet. Learning is a social and collective outcome that is achieved through conversations, the spread of knowledge, and social networking. As the explosion of knowledge and education content change rapidly, lifelong education has become a requirement of modern society. The number of students outside the classroom of the traditional education is increased. In addition, the learning time and place these people have are not fixed (e.g., sales staff). Students also hope to acquire school notification and communication when they are on a holiday, go out, etc. These are difficult to realize in the current educational methods. Therefore, this chapter will describe mobile education as a relatively new tool in the pedagogical and a widely used teaching method. The development of computer technology to the communication bandwidth and computational power of mobile devices, the cost of wireless mobile devices, and its penetration rate will influence the development of mobile education, especially even more so in China.

2

Overview of Mobile Education

2.1

Mobile Education and Traditional Education Methods

In our age, with the development of computer technology, great changes have taken place in the traditional educational pattern. Distance education wins support among the people, people leave school, and many people who cannot receive formal education will choose this way of education. At the same time, the lifelong education

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is paid more and more attention. Mobile education has much more advantages than traditional education methods, and mobile education can be used to support traditional education as well as distance education (Bulun et al. 2004). For several years, the astonishing digital information technological advance changed our day-to-day life. We have seen that an increasing number of people have fully adopted it in adult education (Ceobanua and Boncub 2014). In education field, informatics technologies used have progressed rapidly and dependably, and this progress revealed the notion of mobile education. The most important advantage of mobile education is the access of the student to demanded information, and he/she is independent of time and environment. That is to say, the notion of mobile education also promotes traditional technological progress in education.

2.2

Mobile Education Framework

With information technologies and mobile communication technologies developing rapidly, mobile education system is a continuous improvement of systems engineering in Fig. 1. Previous mobile education system consists of four main parts: mobile communication network, the Internet, mobile equipment, and server. In the basic framework of mobile education, a variety of mobile education platform was built in

Fig. 1 Mobile education system model

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order to realize the diversification of mobile teaching and can also be a constructivist-mobile education environment. Zhang and Hu (2015) study a complemented mobile assist teaching application – tutors in pockets (TIPs) – which allows students to learn concepts within 5 min anywhere and anytime. Through the online survey, the results show that TIPs have a positive influence on students’ performances (Fig. 2). Guangbing Yang et al. (2013) study automatic text summarization for mobile education support. The overall system architecture of this mobile application is presented in Fig. 3. The entire application consists of two components: an offline summarization system, which implemented our summarization solution, and an online system, which was built as a portal to provide summaries as reading materials and questions to learners, collect learners’ answers, and record time used for these answers. This aims to assist learners to summarize learning content and improve the efficiency of learning. The research of Po-Han Wu et al. (2011) showed that conducting mobile learning activities for clinical nursing courses have the effectiveness and are helpful to students in improving their learning achievements. They study a repertory gridoriented clinical mobile learning system shown in Fig. 4, which is developed for a nursing training program with the assistance of the mobile learning system. Thus, the nursing school students are able to learn in an authentic learning scenario, in which they can physically face the target patients, with the personal guidance. It was found that most students showed favorable attitudes toward the usage of the mobile Training Provider

Data

DB Server

Designer

Content Manager

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Fig. 2 Sketch map of tutors in pockets (TIPs)

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Relevance model based summarization system

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Summarized Learning Contents & questions Web-based application Quiz answers

Summary repository Summaries

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Fig. 3 The overall system architecture of the mobile application (From Yang et al. (2013))

MINISTRY OF HEALTH (MOH)

CENTRAL ADMINISTRATOR (CM)

STATE-LEVEL ADMINISTRATOR (SA)

NEW DATA RESOURCE

ADMINISTRATOR (DBA)

IF AUTHORIZED

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1) PHARMACY

1) DOCTORS

2) RESEARCH LABS

2) NURSES

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AUTHORAZATION CHECK CENTER (ACC)

Fig. 4 Continuing mobile medical education architecture. BTS base trans receiving station, DBA database administrator

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learning system and their participation in the training program. The mobile learning system can guide the students to observe and identify the status of target patients in the real world with the help of wireless communication and mobile and sensing technologies. Students can reconstruct their knowledge and experiences via interactions with the learning environment and observations of the target patients in the real world and supplementary materials from the learning system to support them.

2.3

Advantages of Mobile Education

As a specific type of learning model, mobile learning is individual learning which is supported by various types of computer technologies. Mobile learning embraces many characteristics, but it is unique in terms of flexibility of time and location (Peters 2007; Zhang and Hu 2015). Mobile learning (m-learning) can also play a significant supplemental role within formal education (Cheon et al. 2012).

2.3.1 Pervasive Education Due to the rising popularity of mobile devices globally, the use of mobile education has become a pervasive phenomenon. The mobile education can help people of poverty area improve the literature addressing education inequality issues and efforts to fight illiteracy in order to promote the development of regional economy (Kima et al. 2008). Mobile education technology can promote the inclusion of students with various disabilities in education (Bjeki et al. 2014), such as autism (Emir Husni 2013). The pervasiveness of mobile education is not only reflected in user of mobile education but also in the space of mobile education, such as in some university which provides information for students or parents to visit their virtual campus (Pastiu 2013). 2.3.2 Flexible Education With the advancements in mobile technologies, many fields are affected especially in education area, which is no longer confined to classrooms and face to face. As long as they have the required hardware and network infrastructure, learners have the freedom to study at any time in different locations. M-education provides further flexibility for the learner to learn anytime and anywhere on the move (Cavus and Al-Momani 2011). Both educator and students expressed a positive attitude toward mobile education. Given the rise of the Internet and mobile devices, multiple new learning methods have been developed. Mobile education is no longer a concept, learning community is gradually created and advanced, and a knowledge community can be constructed by people of diverse backgrounds. By using mobile device and application, students can really personalize and diversify their learning processes, and all tasks can be rapidly completed in real time. 2.3.3 Efficient Education Learners will become more active in communication and learn much better when they own the learning tool as they consider it useful. Besides, it enables an

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educator who shares the information to contact more students who are independent of time and location with the usage of mobile devices in education (Korucu and Alkan 2011). In mobile education, practice courses are implemented as technology into tradition courses, comply with modern teaching methods, and increase the practice experience of students in an innovative learning environment; a practice learning approach is used that was originally adopted as a basic teaching strategy at schools. During the learning process, the students worked in teams to analyze and discuss by using tablet PCs. The instructor can timely guide students to complete their practice. Meanwhile, by using teamwork, the students make plans accordingly, collect the required information, and make decisions simultaneously.

2.3.4 Individualization Education In the modern society, the traditional fixed learning does not meet the needs of learners, but in a mobile education, learners can choose learning time, place, and content according to their own needs; learning progress can also be self-paced and depends on self-determination so as to realize the individualized learning. Although traditional in-class learning is a method of authentic learning, it is difficult for the teacher to provide full personalized learning support to every student, especially when a large number of students are gathered in the same class (Hwang et al. 2009). Pachler et al. (2009) pointed out that the individualization education has strong implications for autonomous learning. High levels of personalization would mean that the learner is able to enjoy an authentic learning, action learning, and experiential learning, leading to a strong sense of ownership. In independent learning environments, the teacher and students all could use the camera feature to record videos; the relevant documents and files were uploaded. Then, using the Internet enables each of the students to view shared information and rapid information searches; these both increase the level of interaction among students, making the learning process enjoyable because students can share information and communicate with each other. 2.3.5 Lifelong Education Along with the application and development of 3G mobile communication technology, mobile devices will become more and more popular, which will greatly expand the range of education, promote the development of the learning society, and provide a lifelong education. Indeed, as increasing numbers of learner take advantage of mobile education, the effect of mobile education to different education groups is an issue to be researched in order to provide lifelong learning. Modern society is a society of lifelong learning, and mobile education broadens the users of education, which improve the quality of the whole society. Traditional fixed learning also hindered the education opportunities, but mobile education will enable ubiquitous learning and open learning, and the learning is no longer a student’s patent.

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Factors Influencing Mobile Education

There are many factors influencing the application of mobile education. The influential factors were classified into four main categories: mobile device, mobile technology, Internet state, and cost.

3.1

Mobile Device

With the progress of mobile communication technologies and the facility of Internet connection almost everywhere, most of “smart” mobile devices are now capable of handling multimedia easily and effectively. Mobile devices such as personal digital assistant (PDA), mobile phone, and tablet PC are nowadays more convenient than before. They are coming with major improvement in memory storage, interactivity features, and high data transfer speed. A number of studies have found that function of mobile device impacts advantages of pedagogical perspectives (Chen et al. 2003; Denk et al. 2007; Zurita and Nussbaum 2004). Wu et al. (2011) have pointed out that convenient and practical mobile devices can complement the lack of a traditional learning environment, encouraging student confidence and active participation in the learning process. Characteristics of mobile device depend upon a number of factors, such as the following:

3.1.1 Usability From the usability aspect, mobile learning tools are small, light, and portable. For example, smartphones are combined devices and possess both computers’ abilities and mobile phones’ abilities. Smartphones’ sizes are between PDAs and mobile phones. Most of smartphones have touch screen and especially suitable for the elderly and children. Additionally, because of the progress of a new generation of large screen mobile phone, the mobile phone is more and more suitable for mobile learning. These features make the learners feel at ease as learning is no longer constrained in the classroom. 3.1.2 Functional Functionally, learners really need that the devices can provide instant and spontaneous information and can help learners to quickly search specific questions (Bidin and Ziden 2013). Another function is continuity of study. It is an important aspect that the learning is able to continue without the constraints of time and space. That is to say, learners may use their mobile devices to acquire information and learning material that they need, and they do not necessarily need to stop. Indeed, learners can communicate at various places. Learners can use the mobile phone, PDA, intelligent mobile phone, and other portable mobile devices to transmit information in a moving state video, data, and other information communication. Mobile learning makes the teaching and learning occur whenever and wherever possible, more convenient, and flexible.

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Mobile Technology

With the advancements in mobile technology, on the one hand, learning is no longer confined to classrooms. On the other hand, the teacher through the simulation of the actual environment makes the students into the teaching scene in order to improve their comprehension and achieve the desired learning outcomes. Mobile technology and wireless communication technology are closely linked. Several main technologies are introduced in the following.

3.2.1 Virtualization Technology Mobile education shows great potential for future teaching and learning in educational institutions. Virtualization technology is a kind of technology that is the fusion of mobile education and traditionally educational settings. On the one hand, on-site settings enriched with information technology allow for much tighter integration of online activities; on the other hand, virtual settings are sent back into the classroom and integrated with face-to-face activities. Indeed, virtualization technology has been integrated in the educational arena. For example, Chan et al. (2001) built a community-based network learning models to cope with issues related to the applications of networks in education. The virtual learning environments have been enabled teachers and students to communicate via networks. These environments can build and organize learning communities for distance education or for both on campus and distance education. In the future, virtualization technology will be in normal operation in mobile education. 3.2.2 Mobile Augmented Reality Application in Education The development and rapid increase in mobile device usage have made mobile augmented reality (MAR) became possible. Nowadays, MAR is in its infancy globally, and previous mobile augmented reality (MAR) is more focused mostly on games or simulation. MAR has potential and impact on mobile education as latest technologies. MAR can merge virtual and real worlds together in order to improve the quality of teaching and learning activity. Azuma (1997) argues that AR has three basic criteria: 1. Combination of real and virtual 2. Interactive in real time 3. 3D registration of virtual and real objects Today, a number of available MAR experiences and applications have been increasingly receiving attention. As MAR has a vast potential implications and benefits especially in learning environment, expect that there will be many more researches on MAR in the future.

3.2.3 Cloud Computing What is cloud computing? The generally accepted definition of cloud computing comes from the National Institute of Standards and Technology (NIST). Cloud

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computing is a broad term. Cloud computing has already gained a wide acceptance. It is currently the most new way of providing and consuming IT services as technological innovation since the advent of the Internet. Cloud computing has a potential to reduce the cost of economics of IT. In essence, cloud computing is able to quickly and automatically aggregate various cyber sources. In the mobile education building, data center infrastructure is a capital-intensive and expensive operation. However, cloud computing can easily recycle and repurpose resources to reduce costs. It is increasingly acknowledged that using cloud computing effectively in m-education is efficient for providing high-quality education, since cloud computing technologies can satisfy the users’ needs by collecting and analyzing users’ behavior. Cloud computing can rescue higher education institutes which are facing challenges associated with shrinking IT budgets and escalating IT needs. Evidently, the trend in m-learning sector is shifting toward cloud computing market. At present, cloud computing is divided into three types: software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) (Fig. 5) (Table 1).

3.3

Online and Offline

Many systems for mobile devices are an online/offline service that provides a training, learning, and evaluation methodology, supported by the most recent mobile technology. There are two kinds of status between mobile devices and servers, that is, the instant communication status and noncommunication status. The instant communication can also be called online status, and then there is a connection of mobile devices to a server. The learners can remote synchronous mobile learning, update data, and communicate whenever and wherever possible. Of course, another status is known as offline status; this status of mobile device is not connected to the network, so there is no communication cost, but in offline status, learners need to download the network learning resources that are temporarily stored in the mobile device in order to continue learning, which requires the mobile equipment to have enough storage space.

3.4

Cost

Mobile device purchase cost is a deciding factor for educational use. Nowadays, the price of laptop computers is lower than desktop computers, and they have much more features of being portable and plug and play than some desktop. Mobile phones are minicomputers, which offer a variety of features and functions that are beneficial to students and teachers in the classroom. Additionally, a recent report (Madden et al. 2013) indicates that 78% of teens and 91% of adults own a mobile phone. Mobile phones are mainly used to communicate vocally and send and receive messages. With the emergence of new generation communication technology (3G, WAP, GPRS, EDGE, SMS, etc.), mobile phones possess instant displays, videos, moving

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Fig. 5 Three types of cloud computing: SaaS, PaaS, and IaaS

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Content Collaboration

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Infrastructure Infrastructure as a Service (IaaS)

images, and communication via e-mail. With the popularization of 4G technology, the price of communication technology further reduces. At the same time, the rapid development of cloud computing further reduces the construction cost and improves the development speed of mobile education. According to a new report by Ambient Insight, global m-learning revenues will reach $14.5 billion by 2019, and China will be the top buying country beyond America by 2019. China and the USA combined will account for 31% of all mobile learning expenditures on the planet (Sam S. Adkins 2015).

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Table 1 The multiple comparisons of SaaS, PaaS, and IaaS SaaS SaaS is a business functionality that you can gain to use it

PaaS PaaS is an application/ framework that you can leverage to build something on

Characteristics

Web access to commercial software Software is managed from a central location Software delivered in a “one-to-many” model Users not required to handle software upgrades and patches Application programming interfaces (APIs) allow for integration between different pieces of software

Differential

SaaS applications are designed for end users, delivered over the web

Services to develop, test, deploy, host, and maintain applications in the same integrated development environment. All the varying services needed to fulfill the application development process Web-based user interface creation tools help to create, modify, test, and deploy different UI scenarios Multi-tenant architecture where multiple concurrent users utilize the same development application Built-in scalability of deployed software including load balancing and failover Integration with web services and databases via common standards Support for development team collaboration – some PaaS solutions include project planning and communication tools Tools to handle billing and subscription management PaaS is the set of tools and services designed to make coding and deploying those applications quick and efficient

Definition

IaaS IaaS is essentially a computer/server that you can remote desktop to the box and you manage everything else Resources are distributed as a service Allows for dynamic scaling Has a variable cost, utility pricing model Generally includes multiple users on a single piece of hardware

IaaS is the hardware and software that powers it all – servers, storage, networks, operating systems (continued)

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Table 1 (continued) Application area

SaaS E-mail, financial management, customer service, and expense management

PaaS A collaborative platform for software development A platform that allows for the creation of software utilizing proprietary data from an application Some examples of PaaS include Google App Engine, Microsoft Azure Services, and the Force.com platform

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Users of Mobile Education

4.1

Educators

IaaS Servers, storage, network, and operating systems

Educators are always looking for a new way to teach students. Mobile education is considered as having potential for pedagogical applications and not only has garnered much attention but also is becoming increasingly widespread. In mobile education, the teacher’s role is as a facilitator, coacher, and co-learner. Her/his responsibility is to help and guide learners throughout their knowledge acquisition and get their participation and feedback instantly, both in the classroom or at distance (Hamdani 2013). Today, teachers are facing growing pressure to interact with their students via network. All teachers, regardless of their age, need instructional models to effectively integrate new technologies (Ertmer 2005). Additionally, they need training on how to effectively use the technology to support student learning (Bitner and Bitner 2002). That is to say, even if educational application providers’ platform (EAPP) can help teachers easily apply new technology to build network learning communities and increase interaction frequency and quality both during and after class, the teacher also needs a lifelong learning involving new curriculum design, quality assurance and management, and pedagogical and administrative tasks. Not only have teachers always looked to adopt new technologies into their classroom to enhance student learning experience, but also teachers can increase communication and cooperation with parents through mobile technology. Thus, most educators consider mobile devices as important learning tools with a vast range of classroom applications, such as audio and video recorder, digital camera, the Internet, e-mail, educational apps, etc. (Johnson et al. 2012).

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Parents

In societies, education of family plays an important role in shaping the future of child’s life. The schools and other institutions of education are beneficial, supporting, and complementary for the family, because no other schools and institutions can give love, trust, confidence, morale, and warm family environment that are necessary for child’s development as much as her family. Undoubtedly, the parents know their children best, and they can give very useful information to the teacher. Thus, they can cooperate in solving the children’s problems (Genç 2005). Mobile education system can help establish a healthy interaction between teacher and parents, which will enable the children to become more easily recognizable; child-related problems encountered can be solved more easily. The conducted survey (Özdamlıa and Yıldız 2014) approved that majority of parents have mobile device and confirms that parent’s opinion on the usage of mobile devices in an educational purpose is generally positive. Parents stated that they can take education and information from concerned people of school with mobile technologies on child’s development and education. Also, they specified the necessity of communicating with mobile technologies to take school-family cooperation to an advanced level. Teachers can increase communication and cooperation with parents through mobile technology; thus, the children become more easily recognizable, because parents can give very useful information to the teacher. In addition, parents can be informed through mobile learning about the school-parent collaboration.

4.3

Students

Although traditional in-class learning is a method of authentic learning, it is difficult for the teacher to provide full personalized learning support to every student, especially when a large number of students are gathered in the same class (Hwang et al. 2009). Mobile education is becoming increasingly important from kindergarten to senior high school education. The teacher can add mobile education to the activities made by the students and thus can increase the student’s motivation. Mobile education offers students flexible and collaborative learning methods anytime and anywhere (Holotescu and Grosseck 2011). With the development of wireless networks and sensor technologies recently, researchers have been encouraged to develop computer-assisted learning environments or web-based learning environments. It is a learning environment with both authentic and virtual resources. The students can interact with the digital learning system outside the classroom and extend their learning experience to the authentic learning environment, and the learning system can detect and record the learning behaviors of the students in the real world (Hwang et al. 2009).

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Conclusion and Future Research Directions

Nowadays, the people can now whenever and wherever possible learn through the Internet, and numerous pieces of information are consolidated through the processes of discussion, communication, negotiation, sharing, and exchange. Cabrera and Cabrera (2005) pointed out that community members enhance their level of knowledge by sharing knowledge, that is to say, it is truly a knowledge sharing. Hendricks (1999) noted that knowledge sharing is a process of communication. When learning new information or sharing knowledge with others, a person must use the knowledge rebuilding process to achieve a meaningful learning experience. Nooteboom (2000) indicated that knowledge sharing can create value. The knowledge gathered through interaction can be beneficial, introducing novel elements to enhance the intellectual assets of an organization. Assimakopoulos and Yan (2006) noted that organizations must share knowledge to remain future oriented. The quality of human capital is crucial for the progress of society. China’ strategy puts a strong emphasis on education and training. The aim of modern education is to improve the quality of education and enlarge the scale of education. The rapid evolution of information technologies and mobile communication technologies has changed the traditional educational pattern; especially they have created new opportunities for improving the quality of teaching and learning experiences. Actually, a traditional method of education was face-to-face teaching. The teacher is responsible for all the arrangements and conveys learning activities (de Freitas et al. 2010). The integration of mobile technology and education has influenced and revolutionized the way we teach and learn. On the one hand, the teacher can provide an exciting, realistic, authentic, and extremely fun learning environment. On the other hand, there has been a tremendous increase on learner’s engagement and level in understanding the learning content. Moreover, mobile education also can enhance real-time interaction between the educator and learners, even between learners and learners. Mobile education indicates the use of mobile devices as a cognitive tool to promote higher-order thinking skills. Mobile device can identify the subject of information and extract important ideas from the discourse, which is helpful to gain a better comprehension to the learning materials. Ozdamli (2011) indicated that the teachers are willing to implement mobile education applications in support of the traditional education. As assistants or tutors, teachers can develop innovative pedagogies with mobile technologies, which enhance teaching and learning in higher education, especially in outdoor education such as campus, museums, or zoos and make further teaching staff professional development. Sohaib Ahmed’s (Ahmed and Parsons 2013) study proved that mobile education could boost students’ motivation and interest and could help them gain a better understanding. In conclusion, most of previous studies showed a positive impact and encouraging results; mobile education has a vast potential implications and benefits especially in life learning. The mobile education tremendously will impact the mode of all education globally over the next few years.

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With the development of wireless networks, one pedagogy model of communitybased learning has been established to enable teachers and students to communicate via networks, such as WebCT. As establishment of an education environment with both authentic and virtual resources, the students can interact with the digital learning system outside the classroom and extend their learning experience to the authentic learning environment (Hwang et al. 2008). Mobile education is an education method where the learner and teacher are not fixed or in a predetermined place or take advantage of learning and teaching opportunities offered by mobile technology. Mobile education supports a wide range of application field, but mobile education also has many challenges. Mobile devices have been integrated into daily education and show development in terms of portability and functionality, for example, PDA and smartphone are preferred by most of the people. Characteristics of mobile devices are perceived as helpful to support mobile education. Mobile devices have the features and properties such as portability, social interactivity, connectivity, context sensitivity, and individually summarized learning content (Huizenga et al. 2009). Although it has multiple benefits in using mobile devices such as cameras and recorders in the classroom, there are many barriers that must be overcome. For example, students encountering technical difficulties tend to stop using mobile devices. Today, as the highly fragmented mobile technology landscape and rapidly evolving standards, there is no single solution to make content working for every possible mobile device. It is not only both time-consuming and expensive, but also educators are forced to design new learning content or reformat existing learning materials for delivery on different types of mobile devices in the processing and delivery of learning content (Chang et al. 2011). Although the data shows that all aspects of the society have been carried out in various areas of mobile education, with technological progress, there is still a tremendous demand for further research and development. As technology progresses, the aim in mobile education is to inspire various interested people, including developers, educators, institution instructors, and mobile operators. Mobile education has a great pedagogical potential and has been recognized by educational researchers in terms of promoting the quality of teaching and learning activity. As mobile education is a new education way, the affordances and benefits to support learning were worth to discuss. Mobile education has an ability to excite interest in learning, expand the learning community, and develop life-study enthusiasm in society. The effectiveness of mobile education can be further extended when it combines with newly mobile device and innovative technology.

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Cross-References

▶ Tutors in Pockets for Economics

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Study on Networked Teleoperation Applied in Mobile Teaching

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Network-Based Teleoperation Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Bilateral Teleoperation Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Stability and Transparency Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Networked Teleoperation: Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 TCP and UDP Protocol Networked Systems Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Q. Luo Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia Macquarie University, Sydney, NSW, Australia e-mail: [email protected]; [email protected] H. Du Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] J. Hu (*) WEMOSOFT, Wollongong, NSW, Australia Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_56

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Abstract

In the last few decades, an increasing number of people began realizing that bilateral teleoperation plays an important role in the extension of human manipulation in fields such as space, underwater exploration, medical surgery, and hazardous environments. There is an untapped potential in applying bilateral teleoperation in mobile teaching especially networked scenarios. With the development of mobile technologies, education now focuses on the passing on of knowledge and the interaction between teacher and student. Increasing numbers of people are beneficial from mobile/distance education. But some remote students are in a disadvantage with some practicing subjects. Thus, with the better than better smartphones emerging, bilateral teleoperation-based mobile teaching will become a revelation to the existing education structure to help student learn and practice from a remote site. This chapter focuses on the control of bilateral teleoperation systems across the Internet which can be potentially applied in many mobile teaching applications. The authors designed a controller that focuses on the adaptability to time-varying asymmetric delays and stability with good transparency performance, appropriate Lyapunov–Krasovskii functionality, tighter bounding technology in cross terms and weighting matrix approach, and matrix inequalities solved by existing methods. We applied the controller to a linear system model with increasing forward and backward delays. An experimental validation of the developed theoretical methods was used to demonstrate the effectiveness of the proposed method, demonstrating that a criteria to improve the force tracking with less response time, less overshoot, and acceptable position error.

1

Introduction

1.1

Background

In the 1940s the first master–slave teleoperation system was built (Vertut and Coiffet 1985). Since then, a great deal of research has been conducted on the teleoperation systems that can be applied in areas such as aerospace, undersea exploration, medicine, and operations in hazardous environments (Anvari et al. 2005; Lichiardopol 2007). The teleoperation systems have great potential in solving the lack of practicing problems in remote learning. The development of the Internet and mobile technologies changed the way people are living, working, and learning (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Mobile devices and new human-machine interfaces were adopted in many places (ITU 2016; Hennig 2016; Butoi et al. 2013). Many new technologies and new algorithms were developed and implemented in teaching and learning (see ▶ Chap. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”). Social media played an important role in university teaching (see ▶ Chap. 27, “Tutors in Pockets for Economics”) (Haipinge 2013; Heatley and Lattimer 2013; Jenkins and Dillon 2013; Seo 2013; Wallace 2014) as well as community learning (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). Teleoperation across

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the global network has attracted attention in recent years and already proved its great value such as allowing doctors to operate surgeries from 400 km away (Anvari 2007). In such systems, the transmission time delay on the Internet has been considered the primary challenge as it can deteriorate system performance and even destabilize it. Many studies reported consider the transmission delay of teleoperation across the Internet. Some research projects that concern the controller design and experimental simulations are mostly focused on two kinds of time delays: constant time delay and time-varying delay. Since time-varying and asymmetric delays often occur in network-based bilateral teleoperation systems, designing an appropriate control system to maintain its stability has proved to be critical. A bilateral teleoperation system is typically composed of a human operator, a master (manipulator), a communication channel, a slave (manipulator), and an environment. The motion (position information and velocity information) and/or force information in a bilateral teleoperation system can be transmitted from both master to slave site and slave to master site so that the slave can try to mimic the behavior of the master which in turn takes into account the input forces from the slave. The bilateral teleoperation system has been extensively studied for decades, and it can be applied in many different areas such as space and underwater exploration, medical surgery, and any general tasks operated in hazardous environments (Anvari et al. 2005; Lichiardopol 2007). Initially, the first teleoperation application replaced human hands when handling hazardous materials (Lichiardopol 2007). Since then several applications were developed, such as Robonaut developed by the National Aeronautics and Space Administration’s (NASA) Johnson Space Center and the Defense Advanced Research Projects Agency (DARPA) (2012) to have the slave send information to the master through visual feedback, acoustical feedback, and tactile feedback. The information feedback is visual from a helmet, tactile from a pair of gloves, and positional from the tracker. The Robonaut brings site information to the operator and track detailed human hand operations. The goal of the Robonaut is to help humans extend ability to explore in space and assist or replace humans to construct and work in high-risk places. To meet increasing requirements for extravehicular activity (EVA) and dexterity on space works, the Robonaut has been developed based on mechanisms, computational architecture, and teleoperation control. It can be used as a validation tool for controller performance and mobility.

1.2

Problem Statement

There are two concerns from control point of view in designing a suitable controller for a teleoperation system: stability and transparency. Sufficient information must be transmitted between master site and slave site, while more information means more transmissions which results in large time delays in the communication channel. In terms of time delays in most communication channels, engineers are confronted with the delay-induced instability of bilateral teleoperation systems. In particular, a network (such as wired or wireless Internet) has been adopted as

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a communication medium where the delays will be time varying, irregular, and asymmetric (i.e., the time delays will be different in the forward and backward transmissions). The problem is to design a controller that can guarantee system stability while providing an acceptable transparency in a required environment.

1.3

Contributions

In this chapter, the study will primarily focus on developing effective control strategies for network-based bilateral teleoperation system so that the system stability and transparency performance can be guaranteed even when there are asymmetric time-varying delays across the network. The proposed research includes theoretical study and experimental investigation. This chapter makes the following contributions to both theoretical study and experimental investigation: 1. The author has developed an effective control strategy for a network-based bilateral teleoperation system with asymmetric time-varying delays. This new control strategy was developed by defining appropriate Lyapunov–Krasovskii (L-K) functionality and by applying tighter bounding technology for cross terms and free-weighting matrix approach. The developed control strategies guarantee system stability and transparency performance at the same time. The controller design procedure is completed by solving matrix inequalities and trial. 2. The authors built a network-based bilateral teleoperation system platform under the MATLAB environment. A HILINK microcontroller board and MATLAB/ Simulink are used to construct the real-time hardware in the loop control system. The built teleoperation platform can be easily used for different purposes. Under the MATLAB environment, different controllers can be easily implemented and validated. 3. This research has validated the developed control strategies numerically and experimentally through three main scenarios: simulation, one PC with two motors in a realistic communication-free environment, and two PCs with a networkbased teleoperation platform environment.

2

Network-Based Teleoperation Literature Review

2.1

Overview

Teleoperation systems have been developed for the last few decades, and many new novel technologies have been applied to the original system to enhance its performance. Numerous new applications have emerged which contribute to human life.

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In this chapter, we present background on bilateral teleoperation systems, design criteria, existing design methods, and applications.

2.2

Bilateral Teleoperation Introduction

Generally, a bilateral teleoperation system is composed of a local master site, which is driven by a human operator, and a remote slave site, which is in contact with the environment. In such a system, the slave follows the movement of the master and the master receives feedback information from the slave. With the development of computer networks, bilateral teleoperation systems operating over the Internet communication channel are becoming popular. However, the control of these systems is an open issue. A typical teleoperation system includes a human operator, a master operating stick at a human operator site, a slave operating stick at the environment site, a communication channel through which force and position information is transmitted between the master and slave, and visual feedback from his camera at the slave site and presented via the monitor at the master site. In this system, the control commands from the master to the slave and the feedback from the slave to the master can be transmitted electrically by wire, wire network, or wireless network. The control progress can be applied with one feedback or more feedbacks depending on different control strategies.

2.2.1 Bilateral Teleoperation Formulation Figure 1 shows the architecture of a bilateral teleoperation control system. The human operator sends an order to the master manipulator, after which it is transmitted over the communication channel. The order received by the slave is then subjected to forward delays. The slave then issues feedback to the master regarding its execution of the order, which is subjected to backward delays. In an ideal situation with no environment influences, both master and slave are in synchrony. However, in practice, this cannot be achieved. Hence, controllers are added to the

Master

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Master Controller

Master Manipulator

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Backward Delays

Fig. 1 The bilateral teleoperation control system. (Source: The author)

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master and slave sites. Their duty is to stabilize the system and help the slave track the master.

2.3

Stability and Transparency Analysis

There are two main design criteria used to assess the performance of teleoperation control systems: stability and transparency. Stability is one of the most important requirements for teleoperation systems. Theoretically, we can apply the Nyquist stability criterion, i.e., the number of characteristics roots of the closed-loop system on the right-hand plane to judge system stability (Ogata 2002). Practically, if the system input is bounded, the corresponding output should be eternally bounded (Zhu et al. 2011). Transparency is important performance requirement in teleoperation systems. It is an index that describes how realistic the operation is to the operator. Ideally, a good transparency would create a feeling that the operator is manipulating the remote object in person even when it is a virtual environment (Lichiardopol 2007).

2.3.1 Trade-Off Between Stability and Transparency Achieving perfect transparency requires constant feedback from the slave. This results in large feedback delays which in turn can eventually destabilize the system (Lawrence 1993; Polushin et al. 2008a). Hence, the two criteria are in conflict with each other and a trade-off solution must be reached (Hokayem and Spong 2006). The constraints on the physical communication media lead the trade-off between stability and transparency in a teleoperation system. Thus, researchers are faced with options either to focus on one or to compromise between the two. For space applications, Lawrence (Lawrence 1993) has explored the necessary levels of transparency for efficient task execution. While the optimal transparency depends on research objectives, higher transparency would significantly improve the maneuverability of teleoperation systems. Many studies have analyzed the trade-off between stability and transparency. In Polushin et al. (2008a), the authors propose a projection-based force reflection algorithm, which could arbitrarily decrease the feedback gain value when long delays result in high feedback gain. In this approach, the constraint of subsystem feedback gain is removed to ensure stability with good transparency under communication delays.

2.4

Networked Teleoperation: Introduction

Since the TCP/IP was proposed in 1974 (Zakon and The Internet Society 1997), the Internet has been consolidating its role as the central information media in the world. The teleoperation system using the Internet studies began in 1995 (Hokayem and Spong 2006). The bilateral teleoperation systems, information as force and position,

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are influenced by random uncertain delays based on Internet transmission. The fundamental networked teleoperation system is presented in Fig. 2. Packet-switched network is afflicted with time-varying delays and packet loss issues; if there is not a robust control strategy to the networked teleoperation system, destabilization will ensue.

2.5

TCP and UDP Protocol Networked Systems Analysis

In Lichiardopol (2007), a performance evaluation was performed between TCP (Transmission Control Protocol) and UDP (User Datagram Protocol) which are standard transmission protocols used in the Internet. TCP guarantees transmission quality but needs acknowledgment to continue transmission, while UDP is less timeconsuming to transmit because it does not need reception. Moreover, the state proposes three policies to deal with packet loss problems: null packet replacement, previous packet, and passive interpolation. Hokayem and Spong (2006) propose UDP as more suitable for real-time applications such as a teleoperation system based on the Internet. According to Fig. 3 (Kurose and Ross 2007), UDP is superior compared to TCP, because connection setup is not needed and there is no additional delay, no congestion control so it can transmit as fast as desired, and no connection state that needs to be kept at the sender and receiver.

2.6

Applications

Teleoperation systems are widely used in space, military/defense, security, underwater, forestry, mining, telesurgery, and nuclear industry (Lichiardopol 2007). The teleoperation “master and slave” model was developed in the 1940s to protect operators when handling radioactive materials (Vertut and Coiffet 1985).

Internet

Master TCP/UDP IP Physical Layer

Fig. 2 Networked teleoperation system. (Source: The author)

Slave TCP/UDP IP Physical Layer

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Fig. 3 TCP (upper) and UDP (lower) transmission. (Source: The author)

2.6.1 Space It is beneficial to use extravehicular activity (EVA) in developing bilateral teleoperation systems. Space walks are often required at the International Space Station. It is a high-risk task for an astronaut to stay outside the station and quite dangerous to deal with missions in unknown situations. Thus, bilateral teleoperation is the cornerstone of extending EVA and lowering the risk. R1 and R2 (Robonaut1 and Robonaut2) (Johnson Space Centre and the Defense Advanced Research Projects Agency 2012) have different abilities to help astronauts finish space missions. R1 can carry heavier objects, while R2 can move faster than R1. They both send sufficient visual and sense feedbacks to human operators.

2.6.2 Military/Defense Similar to space applications, unknown and high-risk tasks in military/defensive situations are putting teleoperation systems into practice. The most remarkable application is the unmanned combat air vehicle (URAV). The URAV enable air forces to detect and defend via air without an onboard pilot (Wired for War). It can be used to collect an enemy’s information such as geography, population, and weapons. It can attack an enemy after locating position and giving feedback to a pilot in a safe environment in real time. This teleoperation application avoids losing human life by substituting with an aerial vehicle. Figure 4 is the WZ-2000 URAV which was revealed by Guizhou Aviation Industry Group in the 2000 Zhuhai Air Show in the People’s Republic of China. The endurance of this URAV is 3 h, and the speed is 800 km/h which satisfies the needs of long-term missions.

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Fig. 4 The model of WZ-2000 URAV. (Source: The author)

2.6.3 Telesurgery It is commonly recognized that our society has dramatically changed by telecollaboration, and humans have made extraordinary progress in telesurgery specifically with the collaboration of a surgeon and a remote-manipulated “assistant.” In a real operating room, surgeons demand that the teleoperation system has enough feedback accuracy and speed. The challenges faced by this medical technology are as follows: the teleoperation system should be guaranteed stable under unexpected communication environments; sufficient information about the patient should be sent to and presented to the surgeon instantly; and sufficient information takes a long time to transmit, especially video feedback which is utilized in telesurgery. One of the advantages of telesurgery is the telerobotic remote surgical service (Anvari et al. 2005). The world’s first telerobotic remote surgical service was established in Canada. It is mainly used to help rural hospitals apply advanced laparoscopic surgery. In this application, the master and slave are located in two hospitals which are 400 km apart, and a commercial IP-VPN network with 15 Mbps was established. The 21 telesurgeries that have applied this system have helped patients in rural communities.

3

Future Directions

In this chapter, background information about teleoperation was introduced. And Internet environments and teleoperations based on Internet transmission were analyzed. Lastly, several popular applications based on bilateral teleoperation were introduced.

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The passivity-based method has been applied which guarantees stability to the design controller. More exactly, the PE scheme has been adopted in which position information is transmitted between the master site and the slave site to develop the controller. It is simple to apply and study. The Internet environment which has been chosen is UDP as no reception is required in this protocol. It is one of the most popular protocols, and since it is focusing on the control field, spending time on developing new transmission protocols suitable for teleoperation systems is not the research goal. Furthermore, facing the challenge of compatibility of software with hardware has been avoided. With passivity theory and UDP transmission in our system, it is guaranteed to be stable and less influenced by the Internet environment. Because of its compatibility, its potential can be used in many applications. Consequently, the updated controller is proofed with two HIL control platforms, and the results demonstrate the designed controller is suitable for practical use (Luo 2012). The system is suitable for training and learning courses. The advancing anytime and anywhere features of mobile technology have solved many teaching and learning problems in remote education. The mobility of the networked teleoperation system could play an important role in remote education and cross-country learning programs. With the fast-developed wearable technologies, this system provides more opportunities for future mobile learning with new devices (see ▶ Chap. 70, “VR, AR, and Wearable Technologies in Education: An Introduction”).

4

Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Tutors in Pockets for Economics ▶ VR, AR, and Wearable Technologies in Education: An Introduction

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Contents 1 Introduction: Why Students Need a Smart Laboratory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The SmartLab System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 IoT Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 SmartLab Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Mobile Apps for SmartLab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Courses for Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Benefits of Using the SmartLab System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Benefits for the University . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Benefits for Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Potential of the SmartLab System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile technologies have been developed very fast, and many new mobile devices have been released in the last decade, which changed the way people think and live, as well as the way of teaching and learning. They have been widely adopted in many countries and many industries in the world. Students of the new generation, who were born with all the new devices and technologies in their

H. Yin Beijing Oriental Caesar Ltd., Beijing, China e-mail: [email protected] J. Hu (*) WEMOSOFT, Wollongong, NSW, Australia Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_24

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daily life, are different from the old generations too. Therefore, education should be changing to accommodate these new technologies and meet these new requirements from the students and learners. A SmartLab system, based on a traditional IT laboratory, with additional Internet of Things (IoT) technology and mobile application technology, was developed using mobile application technologies and to provide a practice platform for university students learning IoT concepts and mobile application technology. The purpose of the SmartLab system (with both IoT and mobile application) is to provide a smart environment for a university to improve campus management in the Internet era, focusing on training and internship providers. The design and functions of SmartLab system are introduced in this chapter. SmartLab also has potential to solve other potential problems and combine with future technologies.

1

Introduction: Why Students Need a Smart Laboratory

With advances in computer science and Internet technologies, an increasing number of universities have established their own information technology (IT) institutes. Today, information technology is a basic skill required in many fields. Unlike in the 1980s, IT is no longer computer science based but focused on Internet technologies. With the evolution of Internet technologies, the concept of the computer has expanded to include small devices such as the mobile phone, which is now a high-performance computing and networking device (Zhang et al. 2009). Many new technologies and social media were adopted to assist mobile education (▶ Mobile Education via Social Media: Case Study on WeChat and ▶ Chap. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”) (Powers et al. 2012; Bredl and Bösche 2013; Castro 2012; Hwang and Chang 2016; Kabugo et al. 2016; ITU 2016). Millennial students appear to be affected by the growth of these new technologies and devices (OECD 2016; Hunt and Zhou 2017). These technologies have impacted their lives since they were born. Even though they have grown up with technology, they still need a formal university education to learn the professional technologies. Students who want to become professional software developers must have adequate practice in that work. Therefore, universities need to offer networked professional IT laboratories in addition to computer labs. With the correct equipment, environment, and courses, students can study and practice using these technologies, including TCP/IP stacks, different types of OS development, and Internet development based on B/S (browser/server) and C/S (client/server) architectures. In the past 20 years, a new concept, the Internet of Things (IoT) (Hennig 2016), was focusing on embedded and SOC (system on chip) technology which allows mobile devices to have a small and smart “brain,” making it possible for not only computers but most devices to comprise a network. Every device has its own identity and can be accessed by other entities in the network (▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). All of these devices can be the nodes of an IoT network which in turn impact our daily lives. For example, some software allows the

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user to use voice to control room lights or fans (Belkin International, Inc 2017) or press a button to order laundry powder from Amazon via Amazon Dash Button (Amazon.com, Inc 2017). Students in computer science major need to learn more computer languages and systems than the old generations. For IT students, programming embedded and mobile OS systems, such as iOS (the iPhone/iPad operating system (OS) of Apple, Inc.), Android (a popular smartphone OS from Google), and embedded Linux, have become an efficient way to improve their competitive strength (Zdziarshi 2009; see also ▶ Chap. 27, “Tutors in Pockets for Economics”). Also, the current exponential growth of wearable technologies and artificial intelligence is changing the needs of university education (Alkhezzi and Al-Dousari 2016; Becker et al. 2016; Yousafzai et al. 2016). To be impactful, a smart networked laboratory needs to provide several types of IoT nodes (e.g., smart devices with SOC or ARM cores that can communicate with each other by wireless technologies, such as Wi-Fi, ZigBee, and Bluetooth) and development platforms for students to learn at the highest levels. In a traditional network laboratory, PCs and network devices (such as routers, gateways, and so on) are provided for students only allowing students to learn and practice PC-based network programming. It is often difficult to convey to students the relationship between their programming practices and situations outside of the university. For example, one student asked why an iPhone app should be used to control lights and air conditioners in an office when it was easier to program with C/C++ or Java, and it was difficult to realize the control functions on a mobile phone. A smart laboratory provides students with opportunities to become familiar with and practice programming for an IoT network. While in the classroom, students acquire knowledge and some practice on the theory and usage of several concepts, including network construction and programming, wireless communication and programming, mobile platforms and programming, and IoT node management and programming. As universities become bigger, the management jobs become more complicated and difficult. A city may be established around one university. Managing the huge number of electrical systems and devices in a university has become a real problem (see ▶ Chap. 27, “Tutors in Pockets for Economics”). It may also bring a power saving issue for such big computer managing network (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). It is difficult to monitor all subsystems such as lighting, heating, and air-conditioning systems from the central managing computer. Different function zones of a university may be managed by different departments, which add to the complexity of energy management system design. How to control these subsystems remotely and efficiently is the problem to be solved by SmartLab. IoT technology is a proper method for resolving these problems. Smart mobile devices of the IoT is designed to replace some traditional devices (not connect to networks) so that subsystem devices will connect to each other to achieve the central control. With a certain set of communication protocols, a university can build a smart environment campus. UI (user interface) is designed to access and control those

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Table 1 Comparison between traditional and smart IoT labs Knowledge Computer network Internet structure Internet of Things (IoT) Network security Wireless technology Mobile platform (iOS/Android)

Traditional network lab ✔ ✔ ✔

Smart IOT lab ✔ ✔ ✔ ✔ ✔ ✔

remote smart devices. Mobile phones are the best equipment for running UI controlling software. The IoT network on campus will allow students to practice course experiments and self-designed IoT applications on any type of mobile phone platform, so that they can master the real application method of IoT. A SmartLab system is designed to provide a smart campus to a university and provide courses of IoT technology to students in a smart campus of a university. A comparison between a traditional network laboratory and a smart IoT laboratory is provided in Table 1. The SmartLab system is introduced in the following section.

2

The SmartLab System

The SmartLab system was designed for a university that provides courses in IoT technology via smart IoT laboratories. It was developed in 2010 and has been deployed in several universities in China. The system provides IoT node hardware and software for building smart IoT labs and including smart technology in other buildings in a university. The logic structure of SmartLab is illustrated in Fig. 1. In the intranet (or Internet) of a university, several subsystems of the campus are deployed by IoT nodes. The subsystems include the lighting, air conditioning, heating, audio/video, control switches, and security. Because an IoT node is actually an embedded computer device, it is programmable and network accessible. A smart control host device is used to communicate with all the nodes belonging to it. Because IPv4 is now the primary technology used for networks, smart control hosts must be used for management of the last 20 m of IoT nodes. In the future, however, when IPv6 becomes more popular, every IoT node will have its own IP address, and thus smart control hosts will be not necessary in a SmartLab system. A SmartLab service center serves as the database center and applications supporting center. Managers of a university will use a desktop utility or manage web pages to manage all subsystem devices and maintain different areas of the university. For students, the SmartLab environment provides dedicated workshop tools and a software library for programming self-designed IoT applications. Most of the applications will be developed on mobile platforms such as iOS and Android. These mobile platforms are the best choice for running IoT user interaction applications (▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 52, “Student Feedback in

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Education environment

Mobile application (practices)

Smart lab (students workshop)

IOT nodes

Smart control host

SmartLab service center

Manager

Smart control host

Manager Manager

IOT nodes

Subsystem: Lamp, Air condition, Heater, Curtain, Audio & Video, Switch, Security zone

Fig. 1 Logic structure of SmartLab. (Source: The author)

Mobile Teaching and Learning”). A university may build multiple smart laboratories, but only one SmartLab service center is necessary. The system is also applicable in training and teaching associations for skills teaching and other education.

2.1

IoT Nodes

The SmartLab system is designed for managing several types of subsystems of a university, including lighting, air conditioning, heating, audio/video, control switches, and security. IoT nodes are the key devices in those subsystems. One may wonder what the difference is between IoT nodes and traditional nodes. For example, the common light control in a house is illustrated in Fig. 2a. As shown in Fig. 2b, an IoT smart light panel has its own embedded CPU so that it is programmable. Based on the SOC system, it also supports wireless communication with other devices such as the smart control host. While the smart control host is connected into an IP network, the smart light panel can be accessed by any application through the IP network. Though a smart panel has a complex micro system inside, the panel has the same wiring interface as a common (traditional) light control panel. There is no necessity to destroy the original wires when updating a common lighting system to a smart lighting system. Wireless commands exchanging between a smart light panel and smart control host will operate the electrical switch inside the smart light panel to switch on and off the lights. With the same mechanism, every subsystem of a university can be supported by a SmartLab system with the appropriate IoT node device. As a gateway between IoT nodes and the intranet/Internet of a university, a smart control host is used to manage any IoT node device that belongs to it. A smart control

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a A common light panel

L

Lamp N L: Live N: Neutral

L Mechanical switch

b IOT smart light panel

L

Lamp N L: Live N: Neutral

L

Intranet/Internet

electrical switch System on chip RF communicate

Smart control host

Fig. 2 IoT nodes. (Source: The author)

Smart control host

Smart curtain control panel

Smart AC control panel Smart light control panel

Smart heater control panel IP camera Audio and Video

iPhone/iPad Apps Wire/Wireless security zone

Fig. 3 Smart control in a house. (Source: The author)

Sensor and trigger

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host is an embedded computer with various types of ports and wireless communication methods. One smart control host can arrange and manage numerous IoT nodes distributed throughout a building. Figure 3 illustrates a deployment in a house. Some IoT nodes, such as the curtain control panel, are almost the same as the smart light control panel in the SmartLab system. Smart air conditioning and heating control panels have their own embedded SOC, but unlike the lighting system, they use a RS485 bus to connect the building’s air conditioning and heating system with the smart control host, so air conditioning and heating control panels in a SmartLab are not wirelessly deployable. With the audio and video subsystems installed in university classrooms, teachers usually use IR (infrared ray) remote controllers to operate such devices as televisions, projectors, screens, DVD players, amplifiers, and so on. It is common to find more than three remote controllers in one classroom, and teachers may be confused by having to switch between several controllers. In a SmartLab system, an IoT device called an IR repeater is used to integrate all types of IR remote controllers together; so a teacher can control any audio/video devices just by using an application on a mobile phone. The IoT node IR repeater works as shown in Fig. 4. Other types of IoT node devices that use wireless technology, such as IR and RF (radiofrequency) technology, are IR detectors used for smart security zones and sensor/trigger areas. However, in this situation, IR technology is not used for remote control but for movement detection. Any valid motion detection will inform the smart control host by RF communication channel. Based on the various types of IoT nodes and powerful smart control hosts, the SmartLab was designed to construct a smart environment in a university and used by students to learn and practice IoT technology and applications. All IoT nodes in the

A/V device IR

A/V device

A/V device

IR

IR

Intranet/Internet IR transceiver RF System on chip RF communicate

Smart control host IR-repeater Fig. 4 SmartLab IR repeater. (Source: The author)

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SmartLab system, except the IR repeater, are read-writable, that is, they can be controlled remotely and automatically and current status can also be read remotely. For energy-sensitive subsystems such as lighting, air conditioning, and heating, it is especially important that the nodes can be read. With real-time read data from these subsystems, a SmartLab system allows them to run in an efficient way, thus saving energy.

2.2

SmartLab Management

In a SmartLab system, the IoT network and nodes are the main physical part of the system. The other essential part is the area configuration and management, which is the logical part of a SmartLab system. A large number of IoT nodes can be deployed in any part of a university campus. Each area of the university serves its own functionality and serves a specific part of the campus and manages numerous IoT nodes in its range. For example, public areas of campus has smart lighting, air conditioning, heating, and security zones, but a teaching building has more subsystems, such as audio/video, curtain, and sensor (trigger) systems. University managers need to learn that management utilities are needed to control a huge number of IoT nodes and designated areas. To meet this requirement from the university administrators and managers, a managing subsystem was designed. The SmartLab system has a powerful platform running in the background to provide multiple services for configuring and managing a complex IoT environment. As in Fig. 1, all of the IoT node data is saved in the core database of the SmartLab system. Managers can map any node to any area they want by using the SmartLab manager software running on a PC. Within this manager software, they can also manage (add, delete, and modify) user-defined areas of the campus, then fetch node data from the database, and map certain nodes into certain areas. The area defined by a manager may be an actual area on campus or can be a virtual area just for IoT courses. The managing subsystem is protected by authority functions and security system, by university administrators who are able to access the database and manager software system. Students never access this software and data directly.

2.3

Mobile Apps for SmartLab

With the fast growth of mobile technologies and devices, there is a strong need for mobile application use in the SmartLab. After configuring and arranging subsystems of SmartLab, campus users need convenient tools to operate IoT network objects. Though the managing software on a manager’s PC can remotely access IoT nodes, it is not safe or convenient. The SmartLab system provides a set of mobile applications and development libraries for university customers and students. As mentioned above, the mobile platform is now powerful enough to run multiple functions. It is the most suitable platform for running operating tools of an IoT network.

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Standard mobile applications are developed and released on the iOS platform. Campus users such as teachers and managers can download them freely from the iPhone/iPad App Store. The iOS application provides the users a convenient and easy way to use SmartLab. With corresponding authority, different members can operate only the IoT nodes in the area of which they are in charge. For example, a teacher using these apps can only operate IoT nodes in the classrooms where he or she lectures. However, a manager who maintains an office building will be allowed to operate all IoT nodes in the building. Of course, the management routines running in background of SmartLab will manage all the relationships. The iPhone App for SmartLab control is called “iSmartHome2” (BOCC 2012). It runs on iPhone and iPad, with iOS versions later than 5.0. Users can find and download the application from the Apple App Store. The UI of iSmartHome2 is shown in Fig. 5. There is also an iPad version of the utility called “iSmartControl” (BOCC 2010) available from the App Store (Fig. 6). These mobile applications can be used by the people who operate and manage IoT nodes in a university. Students usually will not use these utilities on their mobile phones. In fact, the SmartLab system has prepared a series of courses for students to learn how to design, manage, and program within an IoT environment. The SmartLab IoT developer library is part of these courses. The library can be used for students to program self-designed apps for an IoT network. Several types of mobile applications in a SmartLab-deployed university are illustrated in Fig. 7.

Fig. 5 iSmartHome2 user interface. (Source: The author)

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Fig. 6 iSmartControl for iPad. (Source: The author)

iSmartControl

Students: practices for IOT courses Smart laboratory

Students: practices for IOT courses Smart laboratory

Teacher: operating classroom devices Classroom

iSmartHome2 Managers: manage all around campus SmartLab deployed university

Fig. 7 University SmartLab. (Source: The author)

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Table 2 Content of SmartLab courses. (Source: The author) Content of SmartLab courses IoT nodes Wireless technology

Sensor IoT service

Network communication

User interface

Database Embedded front

RF communication RFID of IoT nodes IR repeater learning mode Wi-Fi network configuration Motion sensor and detector Gas sensor and detector TCP/IP program Client/server program Browser/server program Network protocol Data exchange (XML/JSON/etc.) IoT node management Scenario design and program iOS SDK program SmartLab app development

Students practice in the smart laboratory, where many IoT nodes are installed and managed by the SmartLab system. Through the IoT courses, students learn how to develop applications on a mobile platform using the SmartLab IoT developer library. Student-developed applications are allowed to operate and manage all IoT nodes only in the smart laboratory, so there will be no security problem created by students’ practice work. The safe environment in SmartLab provides more innovative creating spaces for student to design and develop their own works. The next step is to provide formal courses for student to learn gradually about the IoT nodes.

2.4

Courses for Students

To provide formal curriculum to student, the courses were designed and implemented in SmartLab. The SmartLab courses were designed particularly to provide practice with IoT technology. Coordinated with the lessons on IoT theory, the practice work helps students understand the key points of IoT theory. Table 2 lists the main content of SmartLab practice courses.

3

Benefits of Using the SmartLab System

3.1

Benefits for the University

The SmartLab offers many benefits to the universities. A SmartLab server running in IDC (Internet Data Center) provides data access and remote operating services to any manager in campus. It is a quick and convenient way to check or respond to any

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issues with devices on campus. The integrated desktop utilities allow managers to operate any devices remotely and immediately. The authority system is also secured with software and hardware protection, which provide a safe and secured environment for teaching and learning. Smart energy management benefits campus, by monitoring real-time power and user-definable auto running modes for IoT nodes that help managers at the university to learn to operate the campus in the most energy-efficient mode. It can also detect any problem in advance. The other important benefit of SmartLab is for teachers. It gives teachers a new way to keep their attention on the student learning instead of on operating devices in a classroom. For example, without SmartLab, if a teacher wants to begin a lecture by showing some PPT pages on a screen with projector, the teacher must stop the lecture, power on the projector, pull down the screen, connect the projector to the correct input video channel, and then show the PPT page on screen. But with SmartLab’s assistant, the teacher does not need to stop talking. He or she can just press one button (perhaps named “begin a PPT”) on his or her iPad screen then a series of actions on these devices will be executed automatically. The function of “begin a PPT” button is called a “scenario” in the SmartLab system. A scenario means a set of actions on a set of IoT nodes, so that one touch of a scenario button will cause a series of commands executing in order to get the current environment to reach a target status. Scenarios are user definable, so that in a complex IoT network, any number of scenarios can be defined and used to build a smart environment. There are some predefined scenarios in SmartLab to help teachers and managers work in a smart campus. For teachers, some predefined scenarios are listed in Table 3. For students, scenario design and programming are included in their practice.

Table 3 Scenarios and sequences. (Source: The author) Scenario name Begin a PPT

End a PPT Bright environment General environment

Power saving

Leave classroom

Commands sequence Power on projector Pull down screen Connect projector to AV1 channel Power on speakers Close nearby curtains of classroom Reverse steps of “begin a PPT” Switch on all lamps of the classroom Switch on half lamps Open all curtains Set AC to 26  C in summer/set heater to 20  C in winter Switch off all lamps Open all curtains Set AC to standby status Power saving scenario plus power off projector

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Benefits for Students

In a smart network laboratory managed by a SmartLab system, students are engaged more in their learning activities. They have opportunities to learn and practice most of the technology used in an IoT. Network structure and program practices allow students to gain important knowledge about the use of the Internet. Students will learn some key IoT concepts and technology, such as IoT node theory, wireless communication, sensors and triggers, and how to connect an IoT node to an IP network. There are many programming practices that can be done by students on a mobile platform. The iOS platform is now the primary platform recommended by SmartLab. Students enjoy using their imagination to construct their own visual area in the laboratory, composing smart and creative scenarios and creating their own mobile applications for using in their visual area. After SmartLab courses are completed, the teachers can compete for students to encourage them to try using more IoT technology with their original ideas. Combined with virtual reality, the system could provide more engaging programs to students.

4

Potential of the SmartLab System

With the development of IoT and mobile technologies, cities around the world will face or are facing a technological evolution. The computing capability will reach to the furthest corners of our living environment, as new mobile devices are being released with more abilities, which have changed the way people think and live. The new mobile technologies will bring a new generation of IT and will require more people to become familiar and creative with IoT. The SmartLab system is a platform that will generate future IoT engineers. Though SmartLab is currently deployed only in the university environment, it can also be used in any part of a city: a smart city, smart building, smart hotel, smart office, or smart home. The basic structure and configuration principle would be the same when using such a smart system in other parts of a city. SmartLab offers a powerful study and learning tool that helps students become developers of new IoT applications. For example, assume a student has already finished the SmartLab IoT courses and experiments and now wants to develop a smart home system. The aims of the smart home system include schedulable energy management, wireless management, one touch controlling, and automatic event responding. First, in a SmartLab laboratory, the student chooses a smart control host as the gateway of his or her smart home (a visual area). Then, his or her program via the SmartLab IoT development library can manage all of the IoT nodes managed by this host. Next, in the visual area, IoT nodes will be allocated to different parts of the smart home, such as the living room, bedroom, kitchen, and washroom. There are three types of IoT nodes in this smart home: lights, air conditioning, and triggers (IR). Every room has its own light and

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Table 4 Aim of smart home Schedulable energy management Wireless control One touch controlling

Event responding

0:00–9:00 am AC set to 26  C 9:00–5:00 pm AC standby (nobody in house) 5:00–0:00 pm AC set to 22  C Use mobile phone to control smart home devices Design serial of scenarios for living in smart home Leave home scenario: power off all lights and AC standby Back home scenario: AC set to 22  C, living room light on Sleep mode scenario: All lights off, AC set to 26  C Get up in night: bedroom light and washroom light on If somebody enters washroom, light auto switch on While no motion detected for 10 min, washroom light will auto switch off

Source: The author

AC panel; one motion detector (trigger) is assigned to the washroom. The list in Table 4 shows the aim of the smart home. The student’s program could read information for all lights, AC panels, and trigger objects (Kochan 2009). An iOS-based project would use Xcode (the official integrated development environment for iOS and Mac OS software programing) and plug-ins from the SmartLab IoT development library. It would include a proper header program, with the help of classes in Objective-C (the primary program language for iOS and Mac OS software development). Every IoT object has its own identity number that will be used in further access. According to the aims described in Table 4, timers and event delegate routine codes are programmed by the student. Using objects and methods provided by the SmartLab library, the student program can operate all the IoT objects in field. After the coding and testing work, an iOS application is made for this smart home. It will control the smart home environment automatically and in a user-friendly manner. It also illustrates that, with SmartLab’s help, it is easy to construct a new type of smart environment, not only on campus but in other environments utilizing other new technologies and devices.

5

Future Directions

IoT terminals, such as smart home devices and especially wireless accessible devices, are more popular than ever (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). These devices are called “smart” because they are clever than normal single-chip devices. They always have an ARM-based CPU inside. They can easily be connected to a network, and they are always programmable and accessible. For this reason, a SmartLab network laboratory is now a necessity for universities offering IT education. It could be adopted in training and skill education too.

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With the rapid development of IoT and mobile technologies, PC programming courses alone are not enough. A SmartLab course provides hardware and software tools that will help students construct a real IoT environment and develop in it safely and creatively. Without such a system, students may need several years to learn IoT concepts and master programming methods on different platforms. SmartLab could be adopted with other new technologies or devices, such as virtual reality, wearable technology, or artificial intelligence (Becker et al. 2016; Yang et al. 1998; Yousafzai et al. 2016; Alkhezzi and Al-Dousari 2016). The new emerged wearable technologies bring new opportunities and challenges too (see ▶ Chap. 70, “VR, AR, and Wearable Technologies in Education: An Introduction”). The future of education is open for any new smart solution or technology that could benefit both the educators and leaners.

6

Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Student Feedback in Mobile Teaching and Learning ▶ Tutors in Pockets for Economics ▶ VR, AR, and Wearable Technologies in Education: An Introduction

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Kabugo, D., P.B. Muyingda, F.M. Masagazi, M. Mugagga, and M.B. Mulumba. 2016. Tracking students’ eye-movements when reading learning objects on mobile phones: A discourse analysis of Luganda language teacher-trainees’ reflective observations. Journal of Learning for Development 3: 51–65. Kochan, S.G. 2009. Programming in objective-C 2.0. 2nd ed. Pearson. New Jersey, United States. 978-0-321-56615-7. OECD. 2016. Education in China a snapshot. Paris: OECD Publishing. Powers, L., R. Alhussain, C. Averbeck, and A. Warner. 2012. Perspectives on distance education and social media. The Quarterly Review of Distance Education 13 (241–245): 270–271. Yang, J., V. Honavar, L. Miller, and J. Wong. 1998. Intelligent mobile agents for information retrieval and knowledge discovery from distributed data and knowledge sources. Information Technology Conference, 99–102, IEEE, 1–3 Sept 1998. Yousafzai, A., C. Chang, A. Gani, and R.M. Noor. 2016. Multimedia augmented m-learning: Issues, trends and open challenges. International Journal of Information Management 36: 784–792. Zdziarshi, J. 2009. iPhone SDK application development. O’Reilly Media. Sebastopol, CA. 978-0596154059. Zhang, Y., A. Hodgkinson, and C. Harvie. 2009. Inter-firm collaboration in Chinese telecom market. The 6th SMEs in a global economy conference. Springer, China.

Mobile Learning Initiatives in Nursing Education

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Sharon Rees, Clint Moloney, and Helen Farley

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Background of Nursing Education and Value of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . 3 Mobile Learning in Nurse Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 E-Learning Using a Mobile Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Just-In-Time Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Contextual Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Mobile Apps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Social Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Context-Aware/Augmented Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Podcasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 SMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Future Possibilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Considerations for Introduction of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile learning is a very exciting approach to learning that has the possibility of changing nursing education, providing learning to nurses when and where they need it and in a manner that will achieve positive learning outcomes. Coming from an apprenticeship model in the military, nurses have traditionally learned by seeing and then doing. Mobile learning through means such as YouTube and S. Rees (*) · C. Moloney School of Nursing and Midwifery, University of Southern Queensland, Toowoomba, QLD, Australia e-mail: [email protected]; [email protected] H. Farley Digital Life Lab, University of Southern Queensland, Toowoomba, QLD, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_37

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augmented reality offers the best of this traditional way of learning combined with time- and cost-efficient means of technology use and greater theoretical knowledge. Reaching nurses in rural and isolated communities is also possible through these means. This is achieved through the use of SMS and online learning that is able to be used at a time and place suitable for the nurse, enabling them to include learning within their lives in a way that suits them. Many isolated trials have occurred in nursing education over the years, starting with the use of PDAs, and although many have shown success, there is not a great deal of research that has been conducted in the use of mobile education in nursing. Considering this, research was conducted using a grounded theory approach that investigated nurse’s current use of mobile technology and their beliefs around mobile learning. The study also explored how and when nurses are undertaking continuing education, with the discovery of how they personally resource their learning. When looking at trials of mobile learning within nursing education, it is apparent from these trials and the study that nurses are ready for mobile learning and that mobile learning shows great potential as a method for education within the nursing profession.

1

Introduction

Mobile learning initiatives have been trialed within nursing education. Although these small trials have been successful, the use of mobile learning within nursing education is not documented to be used widely. What appears in the literature, however, may not be accurate, as nurses are starting to investigate their own methods of learning through the availability of online education sites via the Internet and also the availability of mobile applications. To give context to mobile learning initiatives in nursing education, it is important to firstly review how nursing education has developed from a largely apprenticebased model where some learning still takes place toward a tertiary evidence-based model. This has required initiatives using various methods including the beginnings of mobile learning with the use of PDAs. The chapter will review mobile learning as it has been documented in the literature for use in undergraduate, postgraduate, and continuing nurse education and will also discuss initiatives observed by the authors in current clinical practice. It is difficult when reviewing mobile learning initiatives to look at them in total isolation to e-learning as the lines have blurred between what is considered as e-learning and what is m-learning. Therefore, some aspects of e-learning such as social media and YouTube, as well as the more traditional e-learning methods, will be discussed, as students and nurses will expect to be able to access these via a mobile device. Mobile learning should not be considered as the only method of education; however, it is a valuable adjunct to traditional learning methods. It provides the opportunity to improve pedagogy, while resources and time for learning are reducing

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within tertiary institutions and hospitals. The possibilities are exciting with such things as augmented reality offering the possibility of nurses being able to have a more authentic simulated experience with minimal continuing costs to the organization. These opportunities, however, also present challenges to the organization. Organizations, when introducing mobile technology into the workplace, will need to overcome obstacles to ensure its safe use for both the nurse and patient. Privacy and the potential for misuse are major considerations in health and therefore policies need to be developed to ensure the safe use of the technology.

2

Background of Nursing Education and Value of Mobile Learning

Over time as long as there have been nurses to care, there have also been nurse educators to train. Traditional methods of nurse training in Australia have stemmed from a militarian style where student nurses would earn their stripes as they learned on the job (Jolley 2007). With the evolution of standards for training and the desire for nursing to become a profession in the 1980s, hospital-based training made the transition to university training. Hence, the nursing degree was borne. This, however, never did dismiss the requirement for training nurses to have adequate clinical exposure (Bruni 1997). Tied to this evolution was the rapid progression of technology, the Internet, mobile phones, wireless technologies, telehealth, and the more recent smartphones and tablets (Robb and Shellenbarger 2012; Walton et al. 2005). The education and training of healthcare professionals has been apprised by advancements in information and communication technologies for several decades. Access to these technologies has meant that adult learners now have instant access to information flow (Billings 2005). Hence, a nurse as a lifelong learner now has access to instant evidence-based information on patient care processes and standards. When considering mobile technology literature and associated development, significant trends have emerged. Mobile technology appears turbulent, showing rapid and major developments. These include increased amalgamation of applications commonly called apps into a single mobile device, wider availability of wireless technology, and the reduction of connectivity problems (Neuman 2006; Ortega et al. 2011; Walton et al. 2005). Expectations from nurses and their learning needs are on the rise, and there is an expectation that academia and healthcare keep up with fast-paced technology evolution. Presently, however, there is evidence that healthcare are laggards when diffusing such technology (Moloney 2013; Moloney and Becarria 2009). At the same time, the technology has great potential to meet the needs of these students. The reason for the inability to keep up with the evolution of technology is correlated heavily to evidence utilization barriers. These include but are not limited to patient factors, social context, organizational effects, financial and political interference, communication breakdown, and the innovation itself. For every innovation, there appears to be noteworthy factors, including knowledge, skill, time, access to new evidence, and leadership (Moloney 2013).

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Ironically, the individual learning outside of the healthcare environment attaches importance to remote access learning resources and is already heavily using electronic learning resources on mobile devices (Yudkin 2012). Greater emphasis now needs to be placed on bridging the gap between external independent personal learning activities and those offered in the clinical environment (Whitehead and Lacey-Haun 2008). The university sector is well on its way to achieving this with many nursing programs like that found at the University of Southern Queensland offering external online undergraduate and post-graduate programs. These programs are particularly valuable for rural and remote nurses who without online programs are not able to advance their knowledge and qualifications. Gone are the days where nurses can afford time to attend classrooms. Nurses, therefore, now demand on the job and remote access to information for learning purposes. Universities are working toward developing resources around how and when nursing student’s access learning resources particularly to coincide with clinical practice (Ortega et al. 2011; Terry et al. 2016; USQ 2014). This growth of expertise will allow the use of the technology to be developed and refined to best cater for nurses in their learning pursuits (Gabbert 2007). M-learning is in need of interdisciplinary collaborative support in moving forward as a future in healthcare information and learning andragogy. There are various healthcare and non-healthcare groups who perceive m-learning development as integral to their role (Yudkin 2012). Software and hardware engineers, academics, and healthcare administrators are good examples. None of these groups can achieve in isolation or implement what is necessary to deliver m-learning. The responsibility lies with a collection of these groups working together to establish effective cooperative practices (Moloney and Becarria 2009; Yudkin 2012). As technology has evolved, the fears and anxieties associated with their use have dissipated. Research evidence as well as these authors’ findings reinforces that mobile technologies, specifically the mobile phone, are useful reference tools in the clinical setting, particularly for medication knowledge. It also demonstrates that nurses are using this technology for patient safety in conjunction with fellow health professionals and creates a cooperative learning community which enables support and knowledge acquisition (Johansson et al. 2012). The importance of mobile learning technology in healthcare continues to intensify with the arrival of electronic records now being introduced more widely. Healthcare educators can help nurses operate in this climate of change by providing access to mobile technologies now at the point of care. Clearly, the modern-day nurse graduate possesses a variety of technological readiness when entering today’s workforce, and modern-day educators in the hospital system now need to acknowledge the trend and seize the opportunity to embrace an education revolution (Johansson et al. 2012; Robb and Shellenbarger 2012; Walton et al. 2005). Mobile, wireless devices, m-learners, and m-learning require nurse educators to embrace change and revise curriculum structures (Whitehead and Lacey-Haun 2008). Changes are required in the entire cycle of a nurse’s lifelong learning including university programs and clinical practice experiences. Education that is responsive to m-learners will be compressed and accelerated. Modern-day nurses

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demand relevant content for practice, particularly advanced practice. The nurse educators of today need to evolve with the technology that is at their disposal in order to provide timely education in the workplace. The modern-day nurse now demands this, and it is no longer optional (Johansson et al. 2012; Robb and Shellenbarger 2012; Walton et al. 2005).

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Mobile Learning in Nurse Education

3.1

E-Learning Using a Mobile Device

A grounded theory study conducted in Australia has discovered how nurses view mobile learning and their experiences of mobile learning in the context of continuing education. The study found that nurses do not view e-learning and m-learning exclusively of each other. It also found that nurses generally were ready to, if not already using, mobile devices for learning. A study in the USA used perceived self-efficacy measures to determine if nursing students and faculty were ready for mobile learning. Their findings added weight to the assertion that students are ready for mobile learning. They found that both groups were ready to learn through mobile applications as generally their perceived self-efficacy in the use of mobile devices was high. It was found that students and faculty currently used their mobile devices to teach and learn informally and this is likely to increase (Kenny et al. 2012). This gives rise to the expectation by students and indeed people in general that if something is available via e-learning, they will be able to access it via their mobile device. This uses the affordance of learning via a mobile device being available at any time and in any location (Shippee and Keengwe 2014). The improvements in mobile devices over recent years have made for an improved experience when using mobile devices for e-learning. Issues still remain however in Australia as well as other countries for connectivity to the Internet for a true anytime and anywhere experience (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 30, “Mobile Learning in Southeast Asia: Opportunities and Challenges”). Nursing education in undergraduate, graduate, and workplace learning as with other professions has been increasingly moving toward e-learning (Neuman 2006). Therefore, developers of e-learning need to be designing the education to be available to students via a mobile device. When developing e-learning for use on a mobile device, the developer should ensure that the learning is firstly visible and workable on a mobile device, thus ensuring that the learning platform is appropriate and also the types of programs within the education are appropriate for mobile devices. The nurses within the study indicated they used their mobile devices or would like to use their mobile devices for learning in multiple environments, including while on transport or waiting for children or appointments or just in another location within their home or work. The learning therefore needs to be developed to allow this to occur. Developing the education in discernable smaller portions to enable the learner to complete portions of the education at a

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time and location suitable to them is one such measure. This enables the learner to allocate their personal resources to place education within their other life commitments. Mobile learning is facilitated by the portability of mobile devices, affording it a distinct advantage over e-learning. Portability is accomplished through devices being small enough to be carried with the learner and wireless and 3G/4G networks removing the need to physically connect to the Internet. This portability facilitates learning anywhere and anytime (Asabere 2012; Shippee and Keengwe 2014). To increase the portability of the learning, the learning modules should also be able to be saved onto the device as connectivity to the Internet cannot always be gained. This will enable the learning to continue as the student potentially moves in and out of Internet connection. The education also needs to be developed so it is not time critical, as in not needing to be synchronous learning. This is also due to the fact that the learner may be moving in and out of Internet connection within the session, have unreliable Internet access, or only be able to access the Internet within the workplace. The Australian study also found that many nurses are currently using their mobile device for just-in-time education in the workplace.

3.2

Just-In-Time Education

The most frequent use of mobile learning in nursing education is just-in-time education used in the clinical setting. The study found that nurses frequently use a mobile phone to check on practice. More specifically they use a mobile device to look up medications prior to administration. Mobile devices are ideal for justin-time education as their portability allows them to be easily accessible to the nurse when the education is needed. Just-in-time education is usually only small bites of information that is needed immediately to allow the nurse to be able to provide patients with a high standard of care at that particular time; however, it is also valuable for learning as they are able to then place that learning when it is needed at a later time. Nurses are also accessing best practice sites for their individual specialties through their mobile device within the workplace to determine best practice. This was also found with a US study where mobile devices were used by students to access professional information where they needed it, at the point of care. Students also believed that mobile technologies could improve communication with faculty when they were on clinical placements (Kenny et al. 2012). Just-in-time education within nursing education is also largely contextual.

3.3

Contextual Learning

The portability of mobile devices has enabled student learning to occur experientially with outside “real-life” experience. This experiential learning is achieved by learning being delivered in an environment where the students are able to directly

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apply their learning (Kukulska-Hulme et al. 2007). In a UK study, nurses viewed a video on their assessment under supervision. The nurses were able to access the learning at a time that suited them and then apply the knowledge when they next performed the procedure, consolidating what they had learned (Clay 2011). Class interaction can be improved through the use of mobile devices. In another study with nursing students in a UK university, teachers encouraged discussion around course-related YouTube videos shown in classes. The research found that the videos assisted the students with developing critical thinking skills, facilitated deep learning, and also increased their engagement (Clifton and Mann 2011). As has been demonstrated, videos obtained through channels such as iTunes U and YouTube can be valuable learning tools. A problem with YouTube, however, is that the origin of videos needs to be checked to ensure the video is accurate to best practice. This can be addressed by prescribing playlists for students, to enable them to access relevant quality information (Clay 2011; Clifton and Mann 2011; Cuddy 2010). Students unofficially access YouTube to improve their understanding of a procedure and therefore having playlists allows the educator some control of content. Ensuring students are given skills early in nursing programs to discern quality sources also allows the student to determine quality information.

3.4

Mobile Apps

Mobile applications or “apps” have brought about a huge change in how users interact with their mobile devices both at work and in their personal time. Apps are inexpensive to produce and relatively simple to use. They can be readily introduced into the market without being extensively trialed, making them also inexpensive to develop and sell (Johnson et al. 2012). Many apps are available for nurses; however, it is difficult to fully grasp how often these are being used, as data has not been collected. A search on the Internet, however, revealed that there are many apps that can assist the nurse with just-in-time information and with their continuing education in general. Apps have also been developed to be used in hospital communication, to assist the nurse in time management and in communication between health professionals, units within the hospital, and patients. It was reported by nurses in the study that nurses are using various apps within the workplace for just-in-time education and also at home mostly for scenario-based education. Educators within the study were also recommending apps to nurses for learning. Apps developed in the workplace to improve care were adopted in one aged care facility. Within that facility the apps were used by care staff to document patient care and were also used to provide staff with support in dealing with difficult situations. Another app within the facility allowed inexperienced staff to interact with dementia care scenarios that allowed them to gain experience and guidance within the situation without risk to themselves or the residents (Maiden et al. 2013).

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Social Media

Social media is a growing area for education; however, it is poorly documented in nursing education. A search through Twitter and on Facebook, however, presents with many opportunities for learning both for undergraduate and continuing nursing education. Nursing blogs have also become frequent on the Internet. Social media is a promising method of assisting nurses in communities of practice with nurses of similar interests and could also assist students in sharing of ideas and in supporting each other. Some hospitals are now using social media to advertise education opportunities and provide two-way communication between the educator and staff regarding these opportunities. Nurses reported that they liked these opportunities being brought to their attention as it saved them time from individually searching for their educational needs. Schmitt and Sims-Giddens (2012) take this further and suggest that social media is also important to give nurses a professional voice and that having a good understanding of social media will allow students to identify false information and also contribute to new sources of accurate information. Sarah Stewart discusses at length social media especially in regard to midwifery in her blog; she uses the blog to discuss not only personal aspects of her life but also to make comments on issues affecting midwives, with in particular technology. Sarah discusses in her blog the great value social media has as a communication tool and importantly also raises the issue of the need for policy in nursing around the use of social media. She raises an important consideration with the social media that will be discussed later in the chapter, that of the issue of maintenance of professional conduct (Stewart 2013).

3.6

Context-Aware/Augmented Reality

This is perhaps the most exciting opportunity for nursing education. It has long been an issue for nurses learning procedures for the first time, as they either need to practice on a human or with a simulation manikin. Both have issues in that with a human there is always risk of harm and a manikin although giving a nurse the experience does not have the same effect as a human by not being able to provide feedback or other supplementary materials (Wu et al. 2012). Augmented reality brings the experience closer to real life and therefore allows the nurse to problem solve and prioritize care. This was demonstrated by a university in Taiwan where students were able to use their mobile device to give realistic feedback when undertaking a respiratory assessment on a manikin. Through the use of a contextaware ubiquitous learning environment, the students were given guidance and feedback that assisted them with their learning (Wu et al. 2012). As the students approached the patient, they were given the patient’s history and presenting complaint via their mobile devices. The students then assessed the patient and when placing their mobile phones over the area to be assessed, the students heard the relevant lung sounds. Depending then on where their mobile device was placed depended on the information they received. From this they were then able to provide

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treatment to the patient. After they completed the assessment, they were then also given feedback on their current level of mastery (Wu et al. 2012). This study found that not only did this approach increase the number of practice opportunities in the same time for the students but also showed the levels of accuracy and smoothness of the procedure was improved in the student group undertaking this method of education compared to a control group using traditional methods (Wu et al. 2012).

3.7

Podcasts

Nurses report that podcasts allow the nurse or student nurse to access education while they are undertaking other activities, such as while driving, exercising, cleaning, or even mowing the lawn. As with all methods of education however, this method has its limitations. It has been shown by research conducted in a Sydney university with nursing and business students that although the podcast was able to shift the time needed, it was unable to make time (Kazlauskas and Robinson 2012). It should be noted that this was undergraduate students therefore possibly explaining the disparity between them and the postgraduate nurses who were undertaking this form of education while undertaking other activities and where it did in fact make extra time. This same research suggests that some students still prefer to attend lectures in person, rather than the more isolated experience of such methods as podcasts (Kazlauskas and Robinson 2012). Podcasts have been shown to improve nursing students’ knowledge and retention in a small study (Abate 2013) giving some evidence of value within nursing education. Given the variances in findings, this gives support to the idea that education should be provided to students using multiple modalities to enable them to use what is best suited to their needs and learning styles.

3.8

SMS

Some educators have used SMS messages to enhance students’ learning. A project using similar methods was used to teach pharmacology to nursing students. In this study, the students received two SMS messages per day regarding medication dosage and indications. It was found that the students receiving the messages had a greater knowledge of medications at the end of the 4 weeks and these results were statistically significant (Chuang and Tsao 2013). Edge et al. (2012) provided information through both audio and visual mediums via SMS/MMS and termed this mobile micro learning. They likened it to an improved flashcard system of teaching. Their study also proved that this style of learning enhanced retention and allowed students to access the materials at a time and location suitable to them. They found that learning was not impeded by distractions or movement of the learner (Edge et al. 2012). It is possible to distribute larger amounts of information to students through tablets such as iPads. In the Iheed report, Callan et al. (2011) report that one of the main barriers to improving health outcomes for people in developing countries is

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the lack of trained healthcare workers. In order to reach healthcare workers in remote areas of Africa, mobile technologies are being used as part of distance education programs. In this context, mobile phones are mainly used to send information to nurses and community health workers to supplement printed materials. Australia also has a large geographical area with many nurses being isolated from opportunities for continuing education. A study conducted by Kidd et al. (2012) confirms this, with nurses in the study stating they have a need for remote areaspecific education. Rural nurses need to have a great diversity of knowledge and skills in order to competently address the needs of the people they provide a service for. This can be difficult as they can receive education but not need to apply it until much later, making the details of procedures and processes difficult to recall (Kidd et al. 2012). An Australian study of nurse practitioners (NPs) found that the least favored method of receiving continuing education was through downloadable case studies for PDAs. It is not known if this discomfort would be translated to tablets or if these technologies would be more acceptable to these nurses. The most favored methods were receiving information via email or using interactive online case studies accessed via desktop or laptop computers (Newman et al. 2009). There have been considerable advances in mobile technologies over recent years and perceptions are changing toward them. Mobile technologies may now be more favored among nurses for the delivery of educational content as they are more likely to encounter these devices in their private lives. In 2009, Newman and colleagues found that NPs practicing in metropolitan areas were more likely to have broadband/network access at work than rural nurses (Newman et al. 2009). Access to broadband is likely to have increased in recent years, in both rural and metropolitan areas. However, the divide highlighted by Newman et al. (2009) is still likely to exist.

4

Future Possibilities

As mobile devices become even more integrated into everyday life, their use in nursing and nursing education is likely to also increase. Though they are often viewed with suspicion or dismissed as a fad by traditionalists, their enormous potential to deliver just-in-time information will ensure that their use in the workplace will increase rather than diminish. Recognizing this potential, education providers are beginning to create their own resources which can be housed on a secure server and accessed via mobile devices at the workplace. In a recent trial in Taiwan, resources such as assessment scales were made available, along with activities designed to develop critical thinking skills. In addition, communication channels were established to allow for learners to directly interact with educators and experts (Lai and Wu 2012). As mobile devices and associated technologies become more sophisticated, the resources available, levels of interactivity, and specificity of the information are likely to become more advanced. The advantage in these kinds of systems is that the quality of the information accessed and provided can be assured.

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Mobile applications or “apps” will continue to be popular with both students and professionals. Apps have the advantage that they are designed specifically for use on a mobile device and can leverage the features and hardware of the device including cameras, accelerometers, and speakers. Though apps are able to bring unparalleled levels of interactivity to information retrieval and learning, there are potential issues that need to be considered. In April 2014, a picture-sharing app for doctors and nurses received extensive media coverage. The app allowed practitioners to share photos of lesions with other practitioners and facilitated discussion to aid diagnosis. The app did contain some tools to help conceal the identity of the patient; however, there was no compulsion to use these (Smith 2014). With very little additional information, the patient could be identified from the pictures and many doctors and academics expressed dismay at the lack of guidelines to ensure patient privacy and confidentiality. In the near future, artificial intelligence (AI) agents may act as tutors or clinical experts, providing advice or up-to-date information as it becomes available. Many business and corporate enterprises are making increasing use of these AI agents to simulate the personal touch through services such as those provided by IBM’s Watson. This system, accessed through mobile devices, potentially can help nurses with treatment options and calculate the level of confidence in the options suggested (IBM 2014). These possibilities had been identified in the previous century (e.g., see Turley 1993), yet are only now being realized.

5

Considerations for Introduction of Mobile Learning

The students’ intention to adopt mobile learning is influenced by many things. Research undertaken in a university in the USA found that students who feel that mobile learning is easy to use are more likely to embrace learning through this medium. This led the researchers to recommend that when including mobile technologies in courses, educators should ensure that students are comfortable with the mobile learning tasks that are intended to be used. They suggested that more complicated mobile learning tasks should be implemented at a later time when students are comfortable with existing mobile learning tasks (Cheon et al. 2012). Taking this into account with the findings from the study, mobile learning would need to be introduced into organizations at a level that is acceptable to the nursing population and/or support given to enable nurses to undertake the education. Another concern of nurses is the cost of education. With mobile learning this also includes the cost of the device and the cost of Internet usage. This was also the findings in a study conducted in the USA. When students were asked about their willingness to participate in mobile learning, they were concerned about the potential costs associated with downloading materials (Kenny et al. 2012). If the student is in the university setting, this could be assisted by students being able to download at university and save the education onto their device; however, if the student is external, this is another cost of their education. Similarly in the workplace, allowing nurses to download information at work decreases the need for personal cost;

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however, it also opens the opportunity for misuse of download capability. Cost of the device is another concern and raises the need for education to be available in multiple formats, so as to not disadvantage those that are unable to purchase a mobile device. Concerns were also raised in the US study about infection-control issues with using mobile devices in the clinical setting (Kenny et al. 2012). This was also found in the Australian study; however, nurses also offered solutions to the issue of infection control. The concern is that the device will be taken into a patient’s room, used, and then taken to the next room and used without being cleaned. This is a valid concern; however, it is also an issue for other devices such as equipment for monitors, vital signs, and pens. Some units overcome these issues by having individual monitors for patients and also by having trolleys for the nurse to take to the outside of each room and attending to hand hygiene on entering and on leaving a room, therefore not contaminating the equipment. Infection control is also an issue that needs to be explored for the keeping of electronic records, which are currently being introduced within Australia as they have been overseas. Many nurses are concerned regarding the appearance of using a mobile device in the clinical area. Nursing historically continues to be a very active profession; therefore, if someone is using a mobile phone in a work area, people are uncertain if the nurse is using the mobile for work or for personal use. This is something that the workplace needs to be aware of and put strategies in place to both protect the nurse from being viewed unfavorably and ensure for the workplace that the nurse is actually working and not socializing. Possibilities for this would be to have mobile devices available at the workplace for nurses to use that only have accessibility to sites that are work orientated. Attitudes to mobile devices also need to change with both public perception and within the nursing community. In the authors’ research, nurses found access to knowledge at the point of care essential to nurses to ensure the best care is provided to the patient. Despite this, some organizations did not permit nurses to carry mobile phones thereby restricting access and potentially quality of care for the fear of misuse. These findings were supported by Mather, Gale, and Cummings (2017), who discuss that the benefits and issues need to be explored prior to implementation of mobile technologies to protect health outcomes and patient safety. Mobile technology at the bedside does have the potential to cause issues with patient privacy, especially with social media, and therefore needs proper governance to prevent the misuse of the technology (Maher et al. 2017; Stewart 2013). Policies are starting to be developed within nursing bodies and also health organizations to give guidance to the use of technology in the health environment, however need to be further developed to guide practice (Maher et al. 2017).

6

Future Directions

As can be identified throughout this chapter, mobile learning has great potential within nursing education. Isolated studies have proven that mobile learning is a useful tool in nursing education, and although the research is not numerous

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in nursing education itself, it is consistent with research in other areas indicating that the findings of these isolated studies are indeed valid. Coming from a largely apprentice-based model, nursing has held tight to that beginning despite moving into a university-based program, causing nursing to at times lag behind other professions in regard to technology. It is now time, however, that nurses are ready to change personally. Change is also eminent due to the change in the health environment requiring high knowledge levels in an ever-changing and cost-efficient environment. Nurses are using mobile devices in their personal lives and informally in their work lives already and so are ready to receive education via this method together with more traditional modes of education. Mobile learning is able to provide education to the nurse at a suitable time and place for the nurse to enable them to fit education into their life. Just-in-time learning is also important for nurses and the mobility of mobile devices allows this to occur. Just-in-time education is important in healthcare to check on best practice and is a very practical application for mobile devices that have the possibility of being readily available when required. Mobile devices are an ideal choice for contextual learning as it gives the nurse the opportunity to immediately put into practice what they have learned on the device and apply it in the clinical area, reducing the need for one-on-one support of beginning practitioners. One-on-one support is reduced when the beginning nurse is also able to use augmented reality to practice procedures and scenarios in an environment closer to reality than currently used in simulation and without risk to patients. Rural nurses although needing a broad range of skills and knowledge have found it difficult to access education, and mobile learning and e-learning have allowed them to access learning in their own community. This has the opportunity and necessity to be increased by improving access by developing education that does not necessitate constant Internet access, thereby allowing them the same potential to learn when and where they want and need to as their city counterparts. As various organizations and nursing bodies deal with the issues surrounding such issues as privacy, mobile learning will start to be used more for education within nursing. As hospitals move toward online records as in other countries, methods to maintain infection control will also be resolved, and mobile devices will become a commonplace within the healthcare system within Australia.

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Newman, Claire, Thomas Buckley, Sandra Dunn, and Andrew Cashin. 2009. Preferences for continuing education through existing electronic access for Australian nurse practitioners and its implication in prescribing potential. Collegian: Journal of the Royal College of Nursing Australia 16 (2): 79–83. Ortega, Luis De. Marcos, Roberto Barchino Plata, María Lourdes Jiménez Rodríguez, José Ramón Hilera González, José Javier Martínez Herráiz, José Antonio Gutiérrez De Mesa, José María Gutiérrez Martínez, and Salvador Otón Tortosa. 2011. Using m-learning on nursing courses to improve learning. CIN: Computers, Informatics, Nursing 29 (5): 311–317. Robb, Meigan, and Teresa Shellenbarger. 2012. Using technology to promote mobile learning: Engaging students with cell phones in the classroom. Nurse Educator 37 (6): 258–261. Schmitt, Terri L., and Susan S. Sims-Giddens. 2012. Social media use in nursing education. Online Journal of Issues in Nursing 17 (3): 1. Shippee, Micah, and Jared Keengwe. 2014. Mlearning: Anytime, anywhere learning transcending the boundaries of the educational box. Education and Information Technologies 19: 103–113. Smith, C. 2014. New picture-sharing app for doctors, medical students raises privacy concerns. ABC News. Stewart, S. 2013. Social media for midwives – Work of the devil or best thing since sliced bread? Social Media, Education, Life-Long Learning, Midwifery. http://sarah-stewart.blogspot.com.au/ . Accessed 21 Aug 2014. Terry, V.R., C. Moloney, L. Bowtell, and P.C. Terry. 2016. Online intravenous pump emulator: As effective as face-to-face simulation for training nursing students. Nurse Education Today 40: 198–203. Turley, J.T. 1993. The use of artificial intelligence in nursing information systems. Informatics in Healthcare Australia. USQ. 2014. Bachelor of nursing program external. Queensland Australia: University of Southern Queensland. Walton, G., S. Childs, and E. Blenkinsopp. 2005. Using mobile technologies to give health students access to learning resources in the UK community setting. Health Information & Libraries Journal 22: 51–65. Whitehead, T.D., and L. Lacey-Haun. 2008. Evolution of accreditation in continuing nursing education in America. Journal of Continuing Education in Nursing 39 (11): 493–499. Wu, P.-H., G.-J. Hwang, L.-H. Su, and Y.-M. Huang. 2012. A context-aware mobile learning system for supporting cognitive apprenticeships in nursing skills training. Educational Technology and Society 15 (1): 223–236. Yudkin, Roman. 2012. Thought leaders. Popularity of mobile devices brings risk. Health Management Technology 33 (4): 32.

Construction Safety Knowledge Sharing via Smartphone Apps and Technologies

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Rita Yi Man Li and Herru Ching Yu Li

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The Role of the Internet in Recent Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Knowledge: An Economic Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 A General Overview of Mobile Apps for Communication Used by Generation Y . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Construction accident rates are high in many places, leading to high compensation, a loss in manpower, and the extension of time. Numerous research sheds light on the causes of factors which lead to construction accidents, such as human error, hot summers, tight schedules, young age, and the lack of safety knowledge. As previous research has found, (1) more people from Generation Y sustain accidents, and (2) many people from this generation are expert users of mobile technology. With there being a lack of research on construction safety knowledge via various apps, this chapter aims at reviewing construction safety knowledge sharing via various mobile apps.

R. Y. M. Li (*) Real Estate and Economics Research Lab, Hong Kong Shue Yan University, Hong Kong, China Department of Economics and Finance, Hong Kong Shue Yan University, Hong Kong, China e-mail: [email protected]; [email protected] H. C. Y. Li School of Computer Science, University of St. Andrews, St. Andrews, UK © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_40

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Introduction

The construction industry is one of the most hazardous industries worldwide (Shin et al. 2014), and construction accident rates are high in many places. Many contractors have to pay high compensation costs. In Hong Kong, monetary compensation in 2006 alone reached HK$39,643,353. Construction accidents also lead to an extension of time due to the loss in manpower and the insurmountable paperwork. Nevertheless, accidents are not caused by any one dominant factor. Rather, it is often the view that construction safety is a complex issue with heaps of different factors under different circumstances, in different locations, and of a different occupational nature. Accidents may happen due to complex equipment and tools, outdoor operations, fast-changing designs, and poor workforce safety behaviors and attitudes on-site (Li and Poon 2007; Li 2012a, 2015) (Table 1). They may also occur when there is a lack of relevant information about the potential hazards on-site. As the construction method selection process on-site is based on individual knowledge, the construction industry needs to understand how to store, identify, obtain, share, and use knowledge (Ferrada and Serpell 2013). Le et al. (2014) and Mitropoulos et al. (2005) posited that a lack of safety knowledge is a major reason for high construction accident rates on-site. This is because some accidents occur due to the violation of prescribed defenses (Mitropoulos et al. 2005). Effective safety information and knowledge exchange, therefore, are important in lowering the dangerous occurrence of safety risks, accidents, and hazards. In South Korea, the safety information module (SIM), the safety semantic wiki tool (SSWT), and the safety knowledge module (SKM) are used to share construction knowledge. The SIM is a tool which was developed for construction engineers and other stakeholders to share accident and risky incident data. The SSWT is a tool to enhance collaboration between construction safety ontology technology and the semantic wiki web to allow users to (1) share safety knowledge and information and (2) classify them in a simple and easy way without the need for a computer background. In the SKM, accident information is examined and polished by domain experts. It provides users with an easy and convenient way in which to share information about the causes and prevention of accidents by communicating and uploading the relevant documents. On the other hand, some previous research has suggested that younger construction workers with relative shadow experience are more accident-prone than others. Moreover, to improve poor safety performance on-site, we need to learn from mistakes (Chua and Goh 2004). Thus, we may speculate that the higher chance of younger workers coming across accidents on-site is due to inadequate experience and knowledge accumulation with regard to safety issues on-site. Tsang et al. (2017) have built a forecasting model for construction accidents. The model has three variables: working conditions, environmental factors, and management actions. Other variables, including the number of vacancies and weather conditions such as lightning and typhoons, will cause construction accidents. One should use the latest technology, including neural nets, to analyze causation of construction accidents. Some previous research has constructed neural nets and

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Table 1 Factors which lead to construction accidents/affect safety performance. (Note: This table is an updated version of that of Li and Poon (2013)) Factors which lead to construction accidents Lack of safety knowledge Material handling Stress at work Young age Human error Lack of training Migrant workers Poor safety attitude Poor safety climate Poor relationship with the crew Fatigue Poor housekeeping Improper/inadequate protective equipment Structural failure On-site work complexity/unsafe working conditions Hot summer Hectic schedule High level of subcontracting Size of companies Separation of design and build in building project Legislation, regulations, and various aspects of legal system Usage of traditional methods in developing countries Workers’ salaries being paid by piece rate Low spending on safety issues Poor weather conditions

Supporting literature Li (2006), Atkinson et al. (2005), Mitropoulos et al. (2005), Le et al. (2014), and Li (2015) Irumba (2014) Irumba (2014) Li (2006) and Chi et al. (2005) Garrett and Teizer (2009) and Zhi et al. (2003) Chan et al. (2004), Debrah and Ofori (2001), and Liu et al. (2007) Debrah and Ofori (2001) Toole (2002), Teo et al. (2005), and Yu et al. (2014) Li (2015) Debrah and Ofori (2001) Chan (2011) Haslam et al. (2005), Toole (2002), and Hu et al. (2011) Toole (2002), Eliufoo (2007), Haslam et al. (2005), and Cheng and Wu (2013) Hintikka (2011) Choi et al. (2011), Chockalingam and Sornakumar (2011), and Shin et al. (2014) Hu et al. (2011), Chan (2011), and Navon and Kolton (2006) Debrah and Ofori (2001) Debrah and Ofori (2001), Rowlinson (1997), and Toole (2002) Lin and Mills (2001), Holmes (1999), and Lingard and Rowlinson (1994) Kongtip et al. (2008) and Arocena and Núñez (2010) Rowlinson (1997), Chockalingam and Sornakumar (2011), and Chan et al. (2004) Chun et al. (2012) Debrah and Ofori (2001) Debrah and Ofori (2001) Tsang et al. (2017)

found out that in both the USA and the Netherlands, the most common fatal accidents are caused by falls from a height, including a ceiling floor, ladder, and scaffolding (Hoła and Szóstak 2017). Generation Y, who were born between 1982 and 1995, have comparatively shadowed experience and knowledge and may easily become victims on-site (Li 2012a). Generation Y are also named Generation Why, Generation Next, the

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Millennium Generation, and Echo Boomers. They grow up in a media- and technology-saturated world and use the Internet more than they watch television. They also use more mobile technology than do any other generation (Li 2012a). They view, gather, and collect information from the Internet more than they read newspapers, books, and magazines and watch TV. They also use more mobile technology than do any other age group. The most common types of mobile communication software are Line in Japan, WeChat in China, and WhatsApp in Hong Kong. WeChat was launched by Tencent in January 2011. It is a kind of software which allows users to send pictures, voice messages, video quickly, and text via the mobile phone’s Internet and support group chat online. As of 15 January 2013, the number of WeChat users exceeded 300 million (Wei and Ke 2014). Many of them are Generation Y users. In fact, Li and Poon (2009) suggested that more Generation Y workers sustain accidents and end up in court. This generation is also called the www generation, as they know the use of the World Wide Web better than did their previous generations. The popularity of other mobile devices, such as smartphones, also increased Internet users substantially in places such as Hong Kong and Singapore. While traditional Internet users only access the Internet via heavy computers, Generation Y can access the Internet easily via mobile devices nowadays almost everywhere. As previous research on construction safety has mainly focused on the causes of construction accidents and various construction safety measures, few have studied safety knowledge sharing of this particular generation (Li 2012a). This book chapter aims to fill this gap in research.

2

The Role of the Internet in Recent Years

In recent years, cyberspace has interacted with urban space, disrupting and collapsing traditional enclosures. The popularity of a fixed Internet in the 1990s has enabled us to communicate, share, and receive knowledge via the World Wide Web. Moving from one place to another has become increasingly more virtual than physical. In the recent few years, the popularity of smartphones and mobile Internet has allowed us to communicate everywhere, e.g., public transportation, theaters, schools, shopping malls, and so on. The idea of mobile Internet combines two of the most important innovations in recent decades: mobile phones and the Internet. A combination of both not only provides much convenience to us in everyday activities but also powers economic growth and media transformations in the USA and South Korea (Li 2011, 2012a). The popularity of Samsung and LG products in South Korea, for example, has opened heaps of job opportunities in recent years. In the same vein, Apple Inc. in the USA offers lots of new positions, not only in the USA but also in places which sell the iPhone. Nowadays, almost 40% of adults use the Internet, e-mail, and instant messaging devices via mobile technology. They have used non-voice apps for mobile devices more in recent years, especially young adults between 30 and 49 years old. Young adults between 18 and 29 years old, in particular, are more likely to use their mobile

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phones for other mobile data applications, such as sending e-mails, taking photos, or surfing the Internet. As construction workers often work on different sites rather than in a fixed office, some workers may then be isolated from site safety information and knowledge. As safety information exists on-site at different stages, safety planning and management are usually kept in the site office. All of these imply that mobile safety knowledge sharing shall play an important role in the present day and in the near future (Li 2012a).

3

Knowledge: An Economic Perspective

Knowledge is a broad and abstract notion which has brought epistemological debate since the classical Greek era. Current knowledge management literature points out that researchers define knowledge from different perspectives. Knowledge can be regarded as a valuable commodity to an organization in a knowledge economy and can be manipulated externally (e.g., buy from outside) or internally (e.g., create within the organization) (Li and Zhang 2010). Alternatively, knowledge can be categorized into tacit and explicit. The former is complicated, as it is individual, nonconcrete, vibrant, and specific. On the other hand, explicit knowledge is a kind of codified guideline, hence being easily transferred and reusable in a consistent manner (Li 2012b). General knowledge is essential to an economy and social system. In Hayek’s paper with regard to knowledge in society, he rebuts the possibility of a centrally planned society in which relevant knowledge is concentrated in one place. New knowledge is obtained in two different ways: 1. Observing nature (whether by research or by less formal procedures) 2. Learning from others, which is subdivided into: (a) Intended learning (communication and education) (b) Inferring the knowledge of others by behavioral observation (Arrow 1994) The productivity of particular tasks and occupations depends on the knowledge that we have (Becker and Murphy 1992). As each individual holds a specific area of knowledge and there is a division of labor, the level of economic progress depends on technological and human capital growth. Apart from economic growth, the importance of knowledge to an economy is that it provides a rational economic order (Becker and Murphy 1992). Previous research has also linked the relationship between specialization and knowledge. For example, engineers in the early nineteenth century were not highly specialized. The growth of industries according to new technology and greater knowledge of science during the nineteenth and twentieth centuries led to the birth of many engineering specialties. The British Institute of Civil Engineering started their own society in 1818; mechanical engineers emerged in 1847; electrical engineers and automobile engineers began in 1871 and 1906, respectively. Chemical and other specialized societies have emerged in the past 90 years. The engineering and medical sector showcased much of the growth in

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specialization, emerging due to extraordinary growth in knowledge. Team sizes enlarge, workers become more specialized, and experts in a specific area of skill grow as human capital and technological knowledge increase. Adam Smith recognizes that there is a significant relationship between knowledge and specialization. He suggests that the division of labor flourishes in countries that enjoy the highest degree of development in industry and improvement. Although workers in modern economies are well equipped with complicated technology, a typical worker also commands a very small share as compared to the total sum of knowledge used by the economy. It is the extensive cooperation among these highly specialized workers that enables advanced economies to utilize a huge sum of knowledge. Nevertheless, the specialized knowledge of workers is not simply given, and acquisition depends on incentives. This is why Hayek emphasizes the role of markets and prices in combining the specialized knowledge of different workers efficiently in rich and complex economies. By means of a price system, the division of labor and coordinated resources based on knowledge have become possible (Becker and Murphy 1992). The “Jack of all trades” is less useful than specialists with advanced technology and skills. As growth in knowledge depends on investment in human capital, new technology, and basic research, the incentive to invest in knowledge depends on the level of task-specific skills as well as the degree of specialization. Therefore, there is a mutual relationship between knowledge and the division of labor. Greater knowledge increases through specialization benefits and, thus, the optimal division of labor in turn. This explains why workers become experts in narrow ranges of tasks as knowledge grows and countries progress. An increase in specialization, in turn, raises the benefits from knowledge investment, so growth in investment specialization in knowledge may nurture economic development (Becker and Murphy 1992). The peculiar character of the problem of a rational economic order is determined precisely based on the premise that knowledge never exists in a concentrated or integrated form, but as dispersed bits of incomplete and frequently contradictory knowledge which all separate individuals have – it is a problem of how to secure the best use of resources. It is a problem of how to utilize knowledge that is not given to anyone in its entirety, but is piecemeal, incomplete, and often contradictory (Hayek 1945). Asymmetric information suggests that we possess unequal sets of information. Information has to be transmitted from a knowledge holder to a receiver. Costs are sometimes paid by an information transmitter, e.g., postal costs. Therefore, information is often kept by an information holder who does not need the information but declines to transmit it to others who want to receive it. Knowledge holders are unwilling to share their information, and there is a lack of communication channels (Li 2012a). While it may be difficult to solve the first problem, tackling the second one is no longer a problem. Communication and computation technology breakthroughs allow innovative and flexible forms of learning and knowledge sharing via mobile devices, such as mobile phones and tablets, which allow users to send messages to others. Besides, electronic databases offer an excellent channel through which to share safety information. Furthermore, Generation Y often use mobile technology. They are experts in sharing knowledge via networks in mobile devices.

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Table 2 Details about Line, WhatsApp, and WeChat Types of communication tools Line (Line Corporation 2014)

Platforms Mobile: Android, BlackBerry, iPhone, Windows Phone, Nokia Asha, Firefox OS

PC computer: Windows, Mac OS

WhatsApp (2014)

iPhone, BlackBerry, Android, Windows Phone, and Nokia

Advantages 1. Exchange free instant messages with one-on-one or group chats. Line is available on all smartphone devices, e.g., iPhone, Android, Windows Phone, Blackberry, Nokia, and personal computers 2. Real-time video calls with friends are free 3. A wide range of emotions are available for users to express their feelings It allows users to share photos, voice messages, up-to-date information, knowledge, contacts, videos, and location information easily with friends (Line Corporation 2014) 1. Once it is downloaded, it is free to chat with 3G/EDGE or Wi-Fi 2. It allows users to send images, videos, and voice notes. It also makes group chats with friends and contacts possible 3. There is no marginal cost to send WhatsApp messages as long as they have WhatsApp Messenger installed 4. Usernames and passwords are not required. WhatsApp works with users’ phone numbers, which is similar to SMS, integrates flawlessly with the existing phone address book, and connects friends automatically 5. With push notifications, WhatsApp is always connected with users’ address book 6. WhatsApp saves messages offline, and users can retrieve them during the next application even if they miss the push notifications or turn off their phone 7. It shares the location, exchanges contacts, and customizes wallpaper. There are notification sounds, precise message time stamps, and e-mail chat history (APP Tomato Market 2014) (continued)

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Table 2 (continued) Types of communication tools WeChat (Tencent 2014)

Platforms iPhone, BlackBerry (OS5.0 or above, 10), Android, Windows Phone, NokiaS40, Symbian Keyboard, Symbian Touch

Advantages 1. There is a sticker gallery and voice and group chat 2. Users can invite friends to a WeChat group chat through a QR code 3. By selecting “Social” and then “People Nearby,” WeChat allows users to add people nearby as friends

For those who are interested in mobile apps, several safety apps are now available for them. Alternatively, they may learn safety information via e-books, which: 1. Substantially reduce the heavy weights of thick books. 2. Make keyword searches possible. Nevertheless, there are limitations to mobile technology. Many informationsharing methods rely on different input requirements as well as different output formats (Li 2012a).

4

A General Overview of Mobile Apps for Communication Used by Generation Y

Good development in the telecommunication sector is important for economic growth of a country (Khan 2010). The most common types of mobile communication software that they use are Line (in South Korea), WeChat (in China), and WhatsApp (in Hong Kong). WeChat was launched by Tencent in January 2011. It is a kind of chat software which allows users to send pictures, voice messages, video quickly, and text via the mobile phone’s Internet and support group chat online. As of 15 January 2013, the number of WeChat users had already exceeded 300 million (Wei and Ke 2014). Similar and popular software is WhatsApp. WhatsApp is a cross-platform mobile messaging application which allows users to exchange messages via smartphones. It utilizes an Internet data plan for web browsing and e-mail, and the marginal cost is zero when we use it to send messages. Furthermore, it allows us to chat as a group. Each of the typed conversations can be seen by others in the same group. WhatsApp users can also send audio and video media messages to contact people in different geographical areas (Li 2012a). Line is a South KoreanJapanese app for instant messaging on personal computers and smartphones to exchange video, text messages, audio, and graphics, hold free audio or video conferences, and make free VoIP calls (Line Corporation 2014). Line was launched in Japan in 2011 and had 200 million users only 6 months later (Lukman 2013) (Table 2).

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Table 3 Aims, objectives, and functions of the app (Perry 2014) Name of the apps Wireless Information System for Emergency Responders (WISER)

First aid by the American Red Cross

Easy Lift app

Monarch Construction Safety (Google, 2017)

Safety App (Google 2017)

Construction Safety Inspection (Google 2017)

Functions 1. It assists workers in handling hazardous material incidents 2. It provides useful occupational health and safety information on reactivity, explosive potential, PPE, fire procedures, storage, toxicity, environment, cleanup, chemical properties, treatment, carcinogens, health effects, occupational health and safety standards, and disposal 3. User profiles allow users to inform the app about their current situation, such that relevant information about incidents’ emergency responses can be provided 1. It integrates with 911, and workers can call EMS by using the app anytime 2. Simple step-by-step instructions guide workers through the procedures of first aid 3. Instant safety information access anytime in the absence of an Internet connection 1. By using a modified version of the NIOSH lifting equation, it provides the user with a maximum safe weight in various lifting scenarios by following the following three steps: It calculates the maximum safe lifting weight according to the NIOSH lifting equation in the absence of Wi-Fi It indicates where workers’ lift should begin It estimates the hours of lifting per day and the number of lifts per minute 1. It will record hazard assessment, site inspections, vehicle inspections, and corrective actions for each while on-site 2. It will automatically e-mail the forms to the corresponding person in charge (safety officer, head office) 1. It provides safety messages and promotes safety campaigns to different stakeholders, including workers and industry practitioners 2. It provides safety information and guidelines for workers to search 3. It has a video demonstration about health tips for workers 4. It promotes safety leadership to industry stakeholders 5. It will push notifications for weather warnings 1. It provides a customized inspection form for workers to fill in and report workplace hazards 2. The report will be sent to the person in charge via e-mail (continued)

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Table 3 (continued) Name of the apps AAT Training-Safety Handbook (Google 2017) Piping Engineering (Google 2017)

Job Safety Analysis (Google 2017) iAuditor-Safety Checklists (Google 2017) Zayfti (Google 2017)

EL CHARPP (Google 2017)

National Safety Stand-Down (Google 2017) CSS Safety 2.0 (Google 2017)

Safety First Associates (Google 2017)

Functions 1. It shows the latest regulations and safety tips for different workers, including heights, emergency responses, and forklift and construction safety 1. It covers different codes and standards, welding, inspection, design analysis, corrosion mechanisms, failure analysis, fitness-for-service, application, and value selection on piping engineering 2. It addresses the principles of materials, design, fabrication, and effects on system integration 1. It sets up a template to report working hazards with per-filling options and photo taking with GPS tags 1. It sets up an inspection form, and it will send reports to management with photo taking, automatic backup, and other functions 1. It provides an inspection form to keep track of risk assessments and reporting 2. It provides real-time alerts for workers nearby 3. Work alone check-in digitally 4. Record keeping, including worker profiles and hazard reports 5. Tracking of tool/vehicle inspections 1. It provides safety phrases, including text and voice translation in Spanish and Russian 2. Phrases can be saved and searched by keyword 1. It provides free resources such as talks and videos to raise awareness of working safety, including scaffolds 1. It can let users create and edit projects and upload photos with issues and hazards. Real-time tracking and e-mailing of safety issues to supervisors 2. It will provide the closest clinic in case of emergency 3. Delivers over 10,000 safety and practice questions 1. It provides a range of health and safety management services to different stakeholders, including the construction sector

Modern knowledge sharing via mobile apps has become possible. Knowledge can be shared via interactive apps in an interesting way. Furthermore, various mobile technologies, such as tablet PCs or iPads, allow apps that include computing Mobile System Analysis and Design to examine the level of satisfaction with regard to mobile learning (Hussin et al. 2012). In view of the above, mobile apps have been used to replace some of the traditional knowledge-sharing methods, including lectures, textbooks, and face-to-face interactions (Table 3).

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Tencent. 2014. Features. http://www.wechat.com/en Teo, E.A.L., F.Y.Y. Ling, and A.F.W. Chong. 2005. Framework for project managers to manage construction safety. International Journal of Project Management 23: 329–341. Toole, T.M. 2002. Construction site safety roles. Journal of Construction Engineering and Management 128: 203–210. Tsang, Y.T., I.W.H. Fung, V.W.Y. Tam, C.P. Sing, and C.T. Lu. 2017. Development of an accident modelling in the Hong Kong construction industry. International Journal of Construction Management 17 (2): 124–131. https://doi.org/10.1080/15623599.2016.1222664. Wei, H., and L. Ke 2014. New weapons of ideological and political education in Universities – WeChat. In: SHS Web of Conferences. Yu, Q.Z., L.Y. Ding, C. Zhou, and H.B. Luo. 2014. Analysis of factors influencing safety management for metro construction in China. Accident Analysis and Prevention 68: 131–138. Zhi, M., G.B. Hua, S.Q. Wang, and G. Ofori. 2003. Total factor productivity growth accounting in the construction industry of Singapore. Construction Management and Economics 21: 707–718.

Developing an Adaptive Mobile Tool to Scaffold the Communication and Vocabulary Acquisition of Language Learners

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Mobile-Assisted Language Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Exploring ELL Use of AAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Language-Learning Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Technology Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Application Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Adaptive MALL Development Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Application Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Developing Adaptive System Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Developing On-Demand Content Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Generating Appropriate Materials: Vocabulary Lists to Support Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Communicating the Meaning of Vocabulary Items . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Obtaining On-Demand Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Design Evaluation of a Hybrid AAC-MALL Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Language-Learning Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Technology Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Application Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Using and Selecting Adaptive Apps to Support Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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C. Demmans Epp (*) Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA EdTeKLA Research Group, Department of Computing Science, University of Alberta, Edmonton, PA, Canada e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_92

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Abstract

English language learners (ELLs) face many challenges. Among them are developing the ability to communicate with others and learning the vocabulary that is needed to enable language comprehension and production. The theories of languaging and extended mapping argue producing language and interacting with language supports learning (Carey, Daedalus Winter: 59–68, 2004; Lang Learn Dev 6(3): 184–205, 2010; Swain, Three functions of output in second language learning. In: Cook G, Seidlhofer B (ed) Principles and practice in applied linguistics. Oxford University Press, Oxford, 1995; Languaging, agency, and collaboration in advanced second language proficiency reading reflection. In: Byrnes H (ed) Advanced language learning: the contribution of Halliday and Vygotsky. Continuum, New York, 2006). However, the challenge of supporting ELL communication has received little attention from the educational technology community (Burston, CALICO J 31:103–125, 2014a; Wu, Comput Educ 59:817–827, 2012). The imbalance between the study of learner use of communication support tools and the potential for mobile devices to support ELLs presents an opportunity for research and development. To move this area forward, an adaptive mobile application was developed to support the communication and vocabulary acquisition of ELLs. This adaptive mobile learning tool was developed by iteratively refining upon an existing communication support tool following design-based research practices and the layered evaluation framework (Paramythis et al. User Model User-Adap Inter (UMUAI) 20:383–453, 2010). This framework was employed because it details how to build effective sociotechnical systems that employ artificial intelligence to adjust the learning experience to individual users. This chapter describes this design process and the changes that resulted from various evaluations of the mobile tools’ features, functionality, and design. The chapter concludes with a discussion of app elements that should be considered when trying to select and use mobile apps to support student learning.

1

Introduction

English language learners (ELLs) can find it difficult to communicate with others (Demmans Epp et al. 2015b; Gambino et al. 2014) as can many speakers of English as a first language. These first language speakers of English struggle with communicating on their own because of medical conditions rather than a lack of language proficiency. To overcome these barriers, they employ a collection of strategies and tools that are referred to as assistive and augmentative communication (AAC) (Todman et al. 2008). Existing AAC was designed to meet the specific needs of these English as a first language users (Bruce 2009), and commercial interests have recently made smartphone-based AAC available. This move to enable access to AAC through commodity devices means these supports are now available to ELLs who could employ them to scaffold their communication (Demmans Epp 2013).

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However, ELLs may have different needs that are linked to their limited understanding of English, and tools have yet to be developed that support their communication. As a result of these differences and the potential for AAC technologies to support ELL needs, an exploratory study (N = 12) was conducted to see how ELLs might use an AAC tool. Following this study, a new tool was developed to better meet ELL needs. The most important of which was the addition of on-demand content generation to support emergent communication and learning needs. This feature was validated through two studies (N = 16 and N = 202) before it was integrated into a new mobile-assisted language learning (MALL) tool. This hybrid MALL-AAC tool was then evaluated with a group of advanced ELLs (N = 8) to see how they integrated it into their activities. This evaluation showed the potential for these types of tools to support ELL communication and language-learning activities.

2

Mobile-Assisted Language Learning

MALL gets its name from the mobility of the learner or the tools learners use (Palalas 2011). MALL tools have become increasingly available (Beatty 2013) even if their use is still uncommon (Burston 2014a). Existing applications typically support a transmission-based model of learning (Beatty 2013; Burston 2014b; Stockwell 2012) that exposes learners to language by providing support resembling that of a dictionary (Demmans Epp et al. 2013; Procter-Legg et al. 2012) or by supporting vocabulary development (Duman et al. 2015; Veras et al. 2014; von Ahn 2013) through highly constrained memorization (Elmes and Fraser 2012; von Ahn 2013) or testing tasks (Garcia 2013; von Ahn 2013). These transmission-based systems are being expanded to include GPS-based features that situate learning (Dearman and Truong 2012; de Jong et al. 2010; Demouy and Kukulska-Hulme 2010) by delivering location-relevant content. The lack of adoption of applications that are dedicated to supporting language learning may result from the focus on transmission-based models and the mismatch between these models and the pedagogical approaches that are currently favored (Burston 2014b; Kukulska-Hulme 2013; Sweeney 2013). This preference for communicative and socio-collaborative approaches makes the use of MALL tools within and outside the classroom appropriate because smartphones can help learners realize their potential by adaptively responding to changes in learners or their environment (Hung and Zhang 2011; Traxler 2013). In spite of this capability, socio-collaborative learning activities and the types of effortful free-form language production (i.e., languaging) that are known to support learning (Robinson et al. 2012; Swain 2006) have not been enabled through MALL tools unless a teacher has repurposed a tool by having learners record and submit samples of their language production (Burston 2014b) or communicate through other media, such as mobile blogs or email (Beatty 2010; Stockwell 2012). Languaging has been minimally supported through dedicated MALL tools that require the learner to verbalize or respond to a specific prompt (von Ahn 2013; Demmans Epp 2017; Liu 2009), providing learners with

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rehearsal opportunities. However, these have not helped ELLs to transfer their knowledge to settings where they must interact with others. In contrast, AAC tools support the communication of proficient speakers of English who cannot communicate on their own (Todman et al. 2008). AAC has also shown its potential for scaffolding the learning of first language speakers who have limited comprehension of that language (Demmans Epp et al. 2015a). Therefore, AAC could support ELL needs by providing learning content or by scaffolding their communication. Given the potential usefulness of these tools and the lack of communication support provided by existing MALL tools, this research explores how AAC and MALL approaches can be improved to support ELL needs in English language environments. This exploration includes the development of a hybrid approach to MALL that is then evaluated.

3

Exploring ELL Use of AAC

To understand how to improve the support provided by AAC, it was first necessary to understand how ELLs would use this class of mobile tools. Given the exploratory nature of this work, a user-centered design perspective (Rogers et al. 2011) was chosen to investigate how ELLs would use a commercial AAC tool to support their needs. This meant giving the AAC tool to ELLs and collecting information about how they used that tool in real-world settings. Twelve learners (Table 1) were given training in how different AAC features worked but were not told how they should use those features to support their language learning or communication. This guidance ensured they were able to use the app while allowing their emergent practices to be identified. These learners used the initial release of a specific AAC tool, called MyVoice (2011), for a little over 3 weeks before reporting on their experiences. Table 1 Participant demographics: AAC study ELL Jian Arash Alba Ju Luis Dima Adora Ling Marco Mei Fan Shu a

Age 49 42 47 18 44 65 36 46 55 55 48 21

Sex M M F F M M F F M F M F

Mother tongue Chinese (C.) Farsi Spanish Chinese (C.) Spanish Bulgarian Spanish Chinese (M.) Spanish Chinese (M.) Chinese (M.) Chinese (M.)

English proficiencya CLB 1 40% (CLB 4) Good (CLB 2) Fluentb Poor (CLB 2) Bad (CLB 3) Poor (CLB 2) Good (CLB 4) Poor (CLB 2) Poor (CLB 4) Goodb Goodb

Language(s) spoken at home English Farsi Spanish and English Chinese (C.) Spanish Bulgarian and Russian Spanish Chinese (M.) Spanish Chinese (M.) Chinese (M.) Chinese (M.) and English

Self-reported Test scores were high enough to gain admission to an English language university, CLB (Canadian Language Benchmark) levels were verified, M. Mandarin, C. Cantonese

b

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The app they used is representative of the general approach taken by digital AAC tools. MyVoice resembles a visual dictionary: it displays vocabulary as image-word or image-phrase pairs that can be verbalized using text-to-speech (Fig. 1). These vocabulary entries are hierarchically organized within categories the user can browse but not search. The provided support materials can be modified through a separate web interface but cannot be modified through the mobile interface. Participant reports of how they used the app indicated these learners seemed to prefer receptive approaches to learning, which included their use of the AAC tool to support their study activities. This focus on using technology to support receptive learning activities was in conflict with learners’ concern over their ability to produce language.

3.1

Language-Learning Strategies

These learners were primarily concerned with their ability to communicate. Like so many learners before them, they used a collection of strategies to facilitate their communication and overcome barriers that were often the result of lacking vocabulary knowledge. Among these strategies was using cognates, using examples to

Fig. 1 A screenshot of one of the higher-level vocabulary categories (left) and the contents of the Tim’s category (right)

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illustrate what was meant until an interlocutor guessed the correct word, or seeking clarification. However, this primary concern was not evident in the majority of the activities learners performed. Rather learners tended to perform receptive learning activities. They sought and consumed authentic English media that included community newsletters and children’s books because these texts were at an appropriate reading level. ELLs consumed these materials to develop their reading and listening comprehension. Some of the more advanced learners would read the textbook from their courses to scaffold their aural comprehension within lectures. Others used music, movies, radio, and television to develop their listening comprehension (see Table 2). Ju’s listening practice also involved eavesdropping on others’ conversations. Like Ju, those who aimed to develop their language production used conversations to develop their listening skills. However, they went a step further by interacting with others using English. This choice forced them to produce language which was believed to benefit their learning. The general lack of activities that were dedicated to improving learner speaking ability appears to have resulted from a lack of opportunity to interact through English and a perception that speaking was the hardest aspect of language learning. Learners expressed a general sense of frustration because most people were not helpful or cooperative. This lack of cooperation led learners to rely on friends and family members when they needed to communicate orally, or they gave up on communicating orally. When they gave up on oral communication, either they resorted to preplanned written communication through letters, or they found someone who could communicate on their behalf.

3.2

Technology Use

As expected, participants used a variety of technologies to support their languagelearning needs with computers, television, and mobile phone use being widespread (Table 2). Smartphones were not widely adopted (only Arash owned one), which partially explains why few of the reported technologies were dedicated to enabling language learning. Participants had instead repurposed or appropriated technologies (Dourish 2003) to support their language-learning activities. One example of this appropriation is their use of subtitles to verify their understanding of program dialogue. Another is Ju’s use of Wikipedia instead of a dictionary to find definitions for words. Learners used paper and electronic dictionaries as well as electronic translators to support their communication (Table 2). None of them had used dedicated or adaptive language-learning software, and none had used communication support tools before.

3.3

Application Use

Like others (Demouy and Kukulska-Hulme 2010; Liu 2009), these participants welcomed the use of a mobile application to support their language-learning

Google Search

✓ ✓ ✓ ✓ ✓

✓ ✓

✓ ✓

Tapes/ CALL/ Electronic CD MALL Dictionaries

L2 learning tools

CALL computer-assisted language learning, L1 1st language, L2 2nd language

Mobile ELL Tool TV Radio Music Movies Computer Phone Jian 1 ✓ Arash 1 ✓ ✓ ✓ ✓ Ju 1 ✓ ✓ ✓ ✓ Luis 1 ✓ ✓ ✓ ✓ Dima 1 ✓ ✓ Adora 1 ✓ ✓ ✓ ✓ Mei 1 ✓ Fan 1 ✓ ✓ ✓ Shu 1 ✓ ✓ ✓ ✓

Everyday technology

Table 2 ELL technology use – AAC study

✓

✓

Paper Dictionaries (L1–L2) ✓

Paper Dictionaries (L2)

✓ ✓ ✓ ✓ ✓

Electronic Translators

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activities. No one reported problems with using the device or application, and learners expressed a desire and need for the type of vocabulary and communication support these tools provide. Their interest in accessing new and better tools seemed to be a primary motivator for learner participation. Like many other mobile applications (such as games or dictionaries) that deliver predetermined content, MyVoice was seen as a tool that delivered limited content with only one learner trying to improve that content. This behavior is consistent with a larger tendency to view apps as content delivery tools rather than content creation tools (Demmans Epp 2017). Participants’ belief that their limited vocabulary knowledge inhibited their language production and comprehension is evident in their application use across spaces: they spent most of their time studying and reviewing word meanings (Fig. 2). Like previous mobile learners (Demmans Epp 2010, 2017; Munteanu et al. 2013; Tsourounis and Demmans Epp 2016), these ELLs practiced their listening skills and their pronunciation in private spaces so as not to bother others or draw attention to themselves, which could be embarrassing. Participating ELLs further used the text-to-speech feature to assess their phonetic decoding skills and vocabulary knowledge by performing dictation tasks when they were alone. Application use in public spaces by Luis, Adora, Mei, and Arash typically involved silently reviewing vocabulary while commuting. The public use of the AAC tool occasionally involved showing the application to friends or using it to support communication. For example, learners would use the images as a visual support. They would scan through these images to find the one associated with a word they wanted to use. This allowed them to see the text, which reminded them of the English labels for objects so they could make requests. They also used the textto-speech feature to make requests when their accent impeded communication. Beyond the above uses, participants requested additional features that could help them. The ability to record samples of language use and see how words are used was

Fig. 2 ELL use of an AAC tool

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among these features. These results were consistent with prior findings (de Jong et al. 2010; Demouy and Kukulska-Hulme 2010). However, learners need to obtain new learning materials that are appropriate to their situations if they are to take full advantage of the opportunities afforded through mobile learning.

3.4

Summary

Learner experiences indicate it is not enough for these tools to provide a fixed set of support and learning materials. These materials need to be adjustable so emergent learner needs can be met. Keeping the limitations of the deployed communication support tool in mind, a new MALL tool that aimed to better support the communication and language-learning activities of ELLs was developed. This included the development of an on-demand content generation feature to support emergent learner needs.

4

Adaptive MALL Development Process

The design and validation of a new system was informed by user-centered design principles (Rogers et al. 2011) and the layered approach (Paramythis et al. 2010), which decomposes adaptive systems into the high-level stages that support adaptation. The layered approach also identifies appropriate methods for evaluating adaptive system components. In keeping with these two practices, the base features and visual design of the new mobile learning system were grounded in the evaluated AAC. However, several modifications were made because of how ELLs used that tool. This included changes to how support and learning materials were organized and presented as well as the ability to translate words and phrases, look up definitions of newly encountered vocabulary, share content, and import content that has been created by other learners. This also included the adaptive recommendation of learning materials and the ability to request new learning materials based on a user-identified need in a way that is similar to how one might perform a Google search when trying to learn about something new. The development and refinement of these new features and the learner-facing interface were conducted in parallel. To familiarize readers with the visible design components and increase familiarity with this new application, its design is discussed first. The adaptive system features are then explained. This explanation is followed by discussion of the methods used to create the on-demand content generation feature.

5

Application Design

Based on learner experiences, a number of elements from the tool they had used were adjusted. Following these adjustments, a variety of methods were employed to ensure system usability. The first was paper prototyping, which was followed by

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higher-fidelity (Hi-Fi) approaches. The Gestalt principles of visual design (Mullet and Sano 1995; Ware 2004) were applied to ensure the user’s visual attention was drawn to the appropriate interface elements. This resulted in several small changes to the color and spacing of interface elements. Nielson’s usability heuristics (Nielson 1994) were also applied: ten evaluators identified interface elements that were inconsistent with Nielson’s heuristics and those elements were refined accordingly. These types of evaluation methods were reapplied following modifications to ensure the design changes did not introduce new problems. In addition to the use of the above evaluation methods, café studies (Konno and Fong 2013) were employed to ensure system usability. Café studies are a type of brief case study where individuals who are in a coffee shop or other public location are approached and asked if they are willing to test a mobile application. Those who agree are asked to complete a highly constrained task, such as editing the sentence that is associated with a particular word. The designer watches how the person proceeds and notes the person’s behavior. The designer then modifies the application in an effort to improve people’s ability to complete the targeted tasks. This iterative, continual redesign process can be seen in Figs. 3 and 4, with Fig. 3 showing the process for the web-based client and Fig. 4 showing the process for the Android-based mobile client. In both cases, the initial designs that included random content were evaluated and then iteratively refined. In the case of the web-based client interface, the process of going from initial system mock-ups to a final prototype was faster with most of the changes being relatively minor adjustments to the visual design. An example of one of these adjustments was the change in the delete button’s color: it was changed from bright red to gray to reduce both its visual importance and its contrast with respect to the surrounding buttons. This change was made because the high-contrast red version of the button seemed to encourage people to click on the delete button, and while anything that was deleted could be easily recovered through a recycle-bin-like feature, deleting content was not an action that should have been encouraged. The relative size of various interface elements (e.g., the category labels and images) was also adjusted, paging was added to improve performance, and colloquial language was removed (e.g., trashed was changed to deleted). For the mobile interface, adjustments were made to accommodate learners’ existing cultures of use and differences in their individual learning behaviors. One of the features that was added to support these differences was the search feature. Learners were also given increased control over the audio features: they could choose when to use text-to-speech, record themselves, or record someone else saying something for later playback. They could also mute the audio should they want to. Another change was the addition of content recommendation and adjustments to the visual appearance of recommended materials so their addition was less obvious or jarring to users. Smaller design refinements included increasing the consistency in the visual representation and interactions used to engage different functions across platforms. This included changing the icon that was used to initiate content editing on the mobile client: it went from being a button with text that said “Edit This Term” to a button that looked like a pencil. The placement of certain functions was also

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Initial Mock-Ups

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Resulting Design

Heuristic & Design Evaluation

Heuristic & Design Evaluation

Hi-Fi Prototype

Fig. 3 The interface (re)design process for the web-based client

changed to ensure that the same action had the exact same meaning on each screen: in this case, the text-to-speech and recordings were changed so they could only be played from the screen where individual words were shown. This iterative redesign process was applied to both platforms. It enabled rapid improvement to the adaptive app. The use of these lightweight but powerful evaluation methods helped ensure the system, and its individual features were usable. However, the improvement of the aspects of the app learners see does not ensure the usefulness or effectiveness of the underlying computational methods. Concern over the computational methods employed is especially important in settings where the system uses complex procedures to make inferences, fulfill requests with limited

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Inspiration

Initial Mock-Ups Design Principles

User Feedback

New Features

Hi-Fi Prototype

Resulting Design

es

tudi

éS

Caf

Fig. 4 The interface (re)design process for the mobile-based client

information about user desires, or adapt elements of the system to a user. These types of adaptivity and adaptability require additional evaluation since they introduce complexity and uncertainty into the system.

6

Developing Adaptive System Features

The system’s adaptive and adaptable features were developed while the user interface was being refined. These features include adaptive testing, the recommendation of new learning content, and an on-demand content generation feature. This section will discuss the adaptive testing and content recommendation features. The development of on-demand content generation will be discussed later.

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The recommendation of new learning content within this app is based on specific situated learning theories: extended and fast mapping. These theories state people learn the meaning of new vocabulary items by encountering them in context (Carey 2010). When people encounter a new word in context, they begin to develop a sense of that word’s meaning, and their understanding of its meaning and usage increases with subsequent and varied encounters. This theory was used to reason over student actions and infer when they knew a word and were ready to see new related words (i.e., synonyms and near-synonyms). This reasoning process can be seen in Fig. 5. At the beginning, it is assumed the learner knows none of the vocabulary. The system then tracks each of the learner’s interactions with a vocabulary item (VCi) and infers a word is known when the learner has interacted with that word at least four times. At this point, the system shows the synonyms and near-synonyms (Si and SSi) of the word that is now, at least partially, known to the learner. The synonyms also show their synonyms. If the learner already knows a word with which the current vocabulary item is a synonym, then the first-degree synonyms (Si) of that vocabulary item are shown regardless of how many times the learner has interacted with that particular vocabulary item. An example of content recommendation can be seen in Fig. 6. In this example, the system believes the learner knows SUV so the system shows the synonyms and nearsynonyms (Si in Fig. 5) that are directly linked to SUV: vehicle and sport utility

Start / Reset VCi++ VCi++

VCi = 0, Si = 0/1, Ssi = 0

VCi < 4, Si = 0/1, Ssi = 0

VCi++

VCi++ VCi > = 4, Si = 1, Ssi = 1

VCi > = 4 Show Synonyms

Fig. 5 The state diagram describing the reasoning process for recommending new content for an individual content item (i). VCi = the number of times a learner has interacted with the vocabulary item, Si = the direct or first-degree synonyms and near-synonyms of an item, Ssi = the seconddegree synonyms and near-synonyms of an item

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Fig. 6 An example of content recommendation where the learner knows SUV so SUV shows its directly connected near-synonyms and those items show their directly connected synonyms. The arrows point to the synonyms shown by a word

SUV VC = 6

Truck VC = 3

Lorry VC = 1

Vehicle VC = 2

Van VC = 1

Sport Utility Vehicle VC = 0

Car VC = 1

vehicle. The system also shows the related vocabulary that is one level removed from the word it thinks the learner knows (SSi in Fig. 5). So, in this case, the vocabulary entry for vehicle will display truck, lorry, van, car, SUV, and sport utility vehicle as being related. Similarly, truck will show vehicle as a related word, but it will not show lorry because the word that the learner is believed to know is too far removed from that synonym. Since the adaptive provisioning of new learning content is based on the system’s ability to infer when a learner knows something, an adaptive testing feature was added. These adaptive tests had multiple purposes. The first was to allow the learner to test his or her knowledge. The second was to use the testing data to improve the underlying recommendation algorithm by adjusting its parameters using the results of learner tests. Reconfiguring the recommendation using thresholds that were empirically obtained based on evidence of each user’s knowledge allows the recommendation of new content to be more appropriately controlled: it would prevent those who take more time to learn new words from being overwhelmed by the recommendation of too many new learning materials and those who learn quickly would be less likely to become bored because the materials were too easy. As with all features not based on prior empirical results, this adaptive feature ran the risk of encountering what is generally referred to as the cold-start problem. The cold-start problem is similar to that of the chicken and the egg. In an adaptive system, a model of the learner is needed to adapt something to him or her, but the learner needs to have interacted with the system for the system to have a model that can drive this adaptivity. This means learners must have a history of interaction if

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the adaptive feature is to work appropriately, but a new learner cannot have this history. To overcome this problem, the developed mobile application used knowledge of the frequency of use of English words to select test items for newer users. It then transitioned to using the systems’ logs of which content the learner had interacted with to select test items. In both cases, learners are tested on frequent and infrequent items so that the test has some items where the learner should experience success and some that will challenge the learner. Selecting items that should have different levels of familiarity also provides information about how quickly the student learns these new words and can allow the system to adjust the processes represented in Figs. 5 and 6. This adjustment would be to the threshold used to infer learner knowledge: that threshold could be increased or lowered based on individual learner characteristics and histories. Alternatively, this information about individual learners could be used to adjust which activities are counted when determining whether the learner has met the threshold required to infer a word is known and thus receive recommendations for new learning materials. The full details of the recommendation process the system used can be seen in (Demmans Epp 2016).

7

Developing On-Demand Content Generation

As can be seen in Fig. 6, the content was reorganized using a graph structure so that it represented the multiple semantic relationships that exist among English phrases and words. This change from the simpler treelike structure that is commonly used in communication support tools added flexibility, and it enabled the scaffolded recommendation of new learning materials through the display of near synonyms. This change in data organization was made tractable through the addition of a search function that enabled users to find words by directly searching for them or by searching for all words belonging to a single category or set of categories. The application was also changed to allow users to see these categories alongside the words with which they were associated because the visibility of this information communicates content organization and can help improve vocabulary knowledge (Graves 2013; Wagner et al. 2007). To further support learners, the ability to obtain learning materials on an as-needed or on-demand basis was added. However, it is not possible to predict all user needs given the variety of situations and contexts in which language learners can find themselves. So, instead of trying to solve this incredibly difficult problem ahead of time by creating a glut of potentially useless content, a feature was developed to support user-identified needs. This feature could create content when the user requested it, provided the user could identify what his or her needs were. To enable both of these requirements, the search box was repurposed to allow users to translate a word from their mother tongue to English, which supported their ability to

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identify the appropriate context in English. They could then ask the system to find or create materials to support the need they had identified. If a user need could not be met with existing content, then computational methods could be used to meet emergent learner needs. This on-demand content generation feature augments existing materials by allowing the learner to request additional support when it is needed. The feature has two subcomponents. The first processes text-based corpora to generate vocabulary lists that are relevant to a learneridentified need. The second retrieves images that can communicate the meaning of vocabulary.

7.1

Generating Appropriate Materials: Vocabulary Lists to Support Communication

Different approaches to automatically creating lists of vocabulary that are specific to a particular context or topic were developed and evaluated (Demmans Epp et al. 2012). These approaches apply the same class of algorithms or computational processes (i.e., information retrieval) that search engines use to find relevant pages. These algorithms were used to process web-based corpora to generate a list of words or phrases and were evaluated (N = 16) for their ability to support communication through a discourse completion study. Those that provided the shortest list of items that effectively supported communication were integrated into the system. Please see (Demmans Epp 2016; Demmans Epp et al. 2012) for details. These computational approaches generated a minimally sufficient set of vocabulary, which was the first step in supporting emergent learner needs. The second was to provide additional scaffolding to support learner comprehension of the developed list. While the ability to retrieve the definitions of individual words in the list was added, this was not enough to support learners with lower levels of language proficiency, such as those in the above exploratory study. To better support these learners, automated methods of identifying appropriate visual scaffolds were explored.

7.2

Communicating the Meaning of Vocabulary Items

Four human-edited, open-source, web-based corpora (Table 3) were evaluated for their ability to provide images that represent a word or phrase’s meaning. The ability for images from these corpora to communicate the meaning of vocabulary entries was then evaluated in the hopes of determining which would best support learner comprehension of the automatically generated vocabulary lists. At least half of those who helped to evaluate the corpora (N = 202) rated several sets of images, with 4,754 ratings performed over 879 vocabulary items. See (Demmans Epp 2016) for details.

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Table 3 The evaluated image corpora Name PDClipArta Image-Net

a

Corpus http://www. pdclipart.org http://www. image-net.org

CAPL

http://capl. washjeff.edu

ESL Sitea

http://www. eslsite.com

Description This corpus contains over 25,000 cartoon-like images and continues to grow These images are typically photographic and are organized according to the WordNet hierarchy. This growing collection maps to over 21,000 synsets This community-generated collection of photographs provides a limited set of images that were taken in culturally authentic contexts These cartoon-like images were collected to support those who teach ELLs

Indicates a top-performing corpus

These ratings revealed the corpora whose images best communicated the meaning of vocabulary items were drawing-based rather than photographic, which may be tied to people expecting a more precise representation and therefore applying higher standards to photographs than sketches. It may also be due to the simpler nature of sketches which tended to include fewer background details that could contribute to ambiguity or confusion. It should be noted these top-performing corpora, some of which had even been designed to support learners, were merely sufficient. However, their use reduces the content creation burden that is common to learning systems and enables learners to receive support when they do not foresee their learning and communication needs. This need justifies integrating this content generation feature into the support tool so learners can request additional support from wherever they are when a need arises.

7.3

Obtaining On-Demand Support

Requests for on-demand support initiate a process where the system performs a series of operations to send support materials to learners as quickly as possible. The system first searches the existing vocabulary collections to see if there is one that is shared. When a collection exists, it is given to the learner immediately. In this situation, the learner only has to wait the length of time it takes for those materials to download before they can be used. When one does not exist, the automated approaches to generating these support materials are used, and they return the requested vocabulary list to learners. This requires a couple of minutes more than when a relevant collection of support materials already exists. However, once this has been done, these automatically created support materials are available for all learners, making it faster for others to get the same support. While these programmatically generated support materials can help learners, they can also be imperfect. A similar challenge arises when learners create their own

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support materials since they may make mistakes. To address this limitation, learners can modify the content of any vocabulary item they have imported. This allows them to fix the problems they find. They can then share the fixed materials so other learners can benefit from their efforts.

8

Design Evaluation of a Hybrid AAC-MALL Tool

An evaluation of this newly developed system was conducted from a user-centered design perspective to make sure the system supported ELLs’ communication and learning activities. This final stage was needed to ensure the system met its original goals before it could be evaluated for its effects on ELLs’ ability to achieve their communication goals or learn English. This evaluation, therefore, focuses on understanding how ELLs can use this tool to support their communication and languagelearning activities. This time, the English proficiency of all of the learners was high enough for them to gain admission to a Canadian postsecondary institution: their test scores were equivalent to or greater than an IELTS 6.0. They also shared many demographic attributes (see Table 4), with all of them pursuing postsecondary programs at English language institutions. These ELLs reported using varied learning strategies that integrated generalpurpose and dedicated language-learning technologies (Table 5). Their experiences foreground how dedicated MALL tools can be incorporated into ELLs’ existing learning strategies and expose occasions where using the developed tool extends the learning opportunities available to them.

8.1

Language-Learning Strategies

Participants relied on courses to develop their knowledge, and everyone used textbased media to support their study activities: some reviewed or practiced grammar rules, while others used dictionaries to explore word meanings and improve their Table 4 Participant demographics: ELL use of a hybrid MALL tool ELL Alda Ya Pio Zhen Gil Miao Ana Davi M. Mandarin

Age 22 27 23 24 21 24 21 23

Sex F F M F M F F M

Mother tongue Portuguese Chinese (M.) Portuguese Chinese (M.) Portuguese Chinese (M.) Portuguese Portuguese

Language spoken at home English Chinese (M.) Portuguese Chinese (M.) Portuguese Chinese (M.) Portuguese Portuguese

2 2 2 2 2 2 2 2

✓ ✓

✓ ✓ ✓

✓

✓

✓

✓

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

Tool Everyday technology TV Radio Music Movies Computer Mobile Phone

✓

✓ ✓

Google Search

✓

✓

✓

✓

L2 learning tools Tapes/ CALL/ CD MALL

CALL computer-assisted language learning, L1 1st language, L2 2nd language

Alda Ya Pio Zhen Gil Miao Ana Davi

ELL

Table 5 ELL technology use: hybrid MALL tool evaluation

✓

✓ ✓ ✓

✓

Electronic Dictionaries

✓

✓

✓

Paper Dictionaries (L1–L2)

✓ ✓ ✓

Paper Dictionaries (L2) ✓

Electronic Translators

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understanding of vocabulary (Table 5). Unlike those from the previous group, these learners pursued oral interaction to take advantage of languaging (Swain 2006), and they tried to improve their listening comprehension by watching TED talks.

8.2

Technology Use

Even though these learners used similar general-purpose technologies to those from the first study (Table 5), these ELLs exhibited greater comfort with technology. Learners increased their exposure to learning content by listening to their own English music and had integrated a diverse set of dictionary and translation tools into their communication and study habits. This included using Google search to verify word spellings (through its auto-suggest feature), Google image search to gist word meanings or Wikipedia articles to understand vocabulary. These participants also used applications that were dedicated to supporting language learning. The applications they had used targeted learner pronunciation or grammar rather than the higher-level tasks with which many learners need assistance (Demmans Epp 2017).

8.3

Application Use

Like MyVoice, this application was predominantly used in private spaces. Learners developed their vocabulary knowledge (Fig. 7) by studying vocabulary entries; using the sentences to model word usage; checking word spellings through the search function; and training their pronunciation by listening to the text-to-speech version of words, sentences, or definitions; recording themselves; and comparing the

Fig. 7 ELL use of the new tool to support their learning and communication goals

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two. Alda and Davi additionally used the application to help them complete their homework. Participants explained how images helped them to connect a familiar object or concept to its English label. Gil even admitted that he would only study materials that had images. Learners navigated the content by browsing and interacting with the synonyms that had been recommended to them. This behavior shows the potential usefulness of these types of subtle recommendation mechanisms. Participants also navigated the materials via the search feature. Learners would search through the available vocabulary or request new learning materials using the on-demand content features so they could find words that were of interest to them. They also used the on-demand content because they felt the default vocabulary was limited, and they expressed this feature provided meaningful collections of learning materials that occasionally included some noise. In one case, the term prenatal was included in the collection of vocabulary that was associated with a gym because it offered prenatal exercise classes. The male student could not understand why prenatal might be a word that is needed in that context, which demonstrates both a learning opportunity and an opportunity for adjusting learning materials based on the individual characteristics of learners rather than only using their behaviors and knowledge as a basis for informing adaptation. Learners enjoyed the additional control that the new design afforded them, with Alda, Gil, Ana, and Davi choosing when to use the recordings or text-to-speech feature to listen to pronunciation models. Alda, Gil, Miao, and Davi also compared recordings they had made of themselves to the system provided pronunciation models. They felt this feature was helpful because it allowed for self-monitoring and assessment, which are essential to improving learning when people are trying to learn on their own. While these types of audio features can support learning, they can also inhibit learner use of a mobile tool since using audio features can result in unwanted attention. Even with this potential social barrier, a subset of learners (Ya, Zhen, Miao, Ana, and Davi) used the application when they were in public spaces. These public spaces included the gym, a pub, a grocery store, their classroom, and a laboratory. Like in private settings, application use in public settings tended toward study-like activities. However, some learners felt comfortable using the application to support their communication. They would do this by using the text and images as prompts while trying to communicate. This prompting took the form of searching through images or words for the correct one and then using the information on the screen to remind them of the word that they needed or how it could be used in a sentence. For Zhen, this meant that she was able to buy the type of pumpkin she needed. Unlike those from the first study, these ELLs were more likely to develop the provided materials by further categorizing existing vocabulary (Pio, Zhen, Miao, Ana, and Davi). They also shared learning materials with one another. These behaviors indicate that enabling the creation and editing of materials through the mobile application was of use to learners. The increased range of behaviors observed in this study indicate the merging of AAC-based approaches with ELL-specific

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scaffolding enabled these learners to use the tool to support a wider range of learning activities.

9

Summary

This design-based work shows the general potential for adaptive mobile learning solutions when they take the users’ needs into account rather than providing prescriptive learning activities. This is shown through the multiple ways in which learners chose to use the tool. This early work expands on the more common study of tools that tend to support one specific learner need or the rehearsal of specific language skills. While the developed tool enables studying and the rehearsal of specific skills, it goes beyond these targets to support emergent learner needs including their ability to communicate with those in their surroundings. Providing this support was possible because a hybrid mobile tool was built using the tools that support the communication of clinical populations as inspiration. The newly developed tool was created following user-centered design principles to ensure it would meet language-learner needs. This process included the development, evaluation, and integration of adaptable features that support ELLs’ emergent communication needs (N = 16) and their ability to understand materials that are generated through computational methods (N = 202). The separate evaluation of different components of the system allowed for the understanding of the limitations of each component so the appropriate modifications could be made to support learner needs. The final design evaluation included all of these components to ensure they were compatible outside of laboratory settings so that the language learners who must use English to survive could benefit from a complete system rather than a set of poorly integrated support features. Both of the real-world evaluations revealed the potential usefulness of communication support tools for scaffolding language-learner activities, with the adaptive AAC-MALL hybrid tool supporting a greater range of ELL activities. Subsequent evaluations have shown the developed tool can support vocabulary learning and its use is associated with improvements in the communication of recent migrants (Demmans Epp 2016). However, the influence these tools have on ELL communication success or learning outcomes requires further study.

10

Using and Selecting Adaptive Apps to Support Learning

Based on learner experiences, it is appropriate to use this class of tools to support their cognition. In classroom settings, adaptive and other mobile tools can be used to provide local support to students at their desk, to prepare them for upcoming units through vocabulary review, or to expand their vocabulary through the recommendation of learning materials. In students’ everyday lives, these types of tools can be used to support communication by providing students with resources that enable

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them to get the help they need when they need it. When considered alongside the content recommendation feature, the use of such tools in students’ everyday lives holds the potential to connect what they are learning in the classroom with their lives outside of school. This connection could encourage the transfer of knowledge and help them to see the relevance of what they are learning, which could improve their motivation for learning. Using highly structured tasks is recommended when first integrating these tools. For example, have students complete worksheets to prepare them for upcoming classroom activities where specialized or new vocabulary is required. This can be done across domains, where the pre-review of vocabulary could help students to access and understand the information presented in a physics course. The types of activities being used can then be adjusted to gradually increase learner autonomy where they use the tool to support more self-directed study activities or projects. These projects could include documenting sample collection from a local stream for science or biology courses. When selecting tools, it is important to consider the level of alignment among the tools’ features, its underlying adaptive theory, and the pedagogical methods that are to be used in the classroom. Generally, a reasonable amount of alignment would be desired, but there may be cases when complementary approaches are wanted. For example, an app that uses a spaced-repetition approach might be valuable if considerable memorization is needed even though problem-based approaches are being used in the classroom. It is advisable to choose a tool or app that allows learners to log (e.g., type notes, record audio, or photograph) aspects of their learning experiences since this can allow them to reflect on their learning. It can also allow them to log learning opportunities for later study and exploration. Another aspect of the adaptivity that should be considered is the amount of control learners can exercise. To determine whether an app may or may not be appropriate, it is worth asking who should decide what the learner does: the learner, the teacher, the app, or some combination of these. In a similar vein, it is recommended that one investigates how recommendation errors are handled: can the user or teacher override an adaptive feature when it gets something wrong and what are the consequences of errors in the adaptive reasoning process? The answers to these and other questions about the appropriateness of any one mobile learning tool are rarely right or wrong. Rather they allow for someone to determine whether a tool can help meet the goals that have been set. Tools that can be used to help meet desired learning goals should be further analyzed to ensure they support both the experiences and outcomes that are desired. In short, it is important to know what evidence there is that any tool, whether adaptive or not, will support learner needs. That evidence can come from research exploring the use of the tool, the carefully documented development and evaluation of a tool, or a considered analysis of its features. Hopefully, this chapter has provided an example of the type of effort that should be invested in adaptive app development if these tools are to be used in educational settings as anything other than a supplement to support selfguided study.

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Future Directions

So far there has been limited study of adaptive mobile tools for supporting learning. Within language learning, these tools have tended to restrict adaptivity to that dependent on spaced-repetition algorithms designed to aid memorization or simple mechanisms that are tied to the learner’s location. This chapter presents the development of a tool that goes beyond these simple adaptive approaches to supporting learning. With the advancement of mobile device capabilities, there is considerable opportunity for integrating the types of deep adaptation that have been studied within computer-assisted learning (specifically within intelligent tutoring systems) into mobile contexts. However, the more complex and inconsistent nature of the learning environment requires the development of additional mechanisms for enabling the system or learner to overcome limitations in the recommendations made by the tool. In classroom settings, considerable work can be done with respect to learning activity design. There are several challenges that relate to ensuring similar learning outcomes and a similar quality of learning experience while using adaptive tools, especially ones learners can take with them or that adjust to the learner’s prior knowledge and context. In line with this is the need to develop tools or guidelines to aid instructors in evaluating potential apps. As a complement to these evaluation tools, additional tools could be developed to support curriculum planning so adaptive mobile tools can be incorporated while ensuring course and individual student goals are met.

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Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Development of Chinese Character-Writing Program for Mobile Devices ▶ Development of Application to Learn Spanish as a Second Language: Lessons Learned ▶ Enhancing Student Learning Experience with Practical Big Data Analytics Techniques ▶ Mobile-Assisted Language Learning: How Gamification Improves the Learning Experience ▶ M-Learning and U-Learning Environments to Enhance EFL Communicative Competence ▶ VR, AR, and Wearable Technologies in Education: An Introduction

References Beatty, Ken. 2010. Teaching and researching computer-assisted language learning, Applied linguistics in action. 2nd ed. Harlow: Longman. Beatty, Ken. 2013. Beyond the classroom: Mobile learning the wider world. Monterey: The International Research Foundation for English Language Education (TIRF). http://www. tirfonline.org/english-in-the-workforce/mobile-assisted-language-learning/beyond-the-class room-mobile-learning-the-wider-world/.

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Development of Application to Learn Spanish as a Second Language: Lessons Learned

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Theoretical Fundamentals of the Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Lessons Learned in Building Vecindario Prototype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Lessons Learned from User Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Learning a foreign language is a relevant demand in an increasingly globalized world. The dynamic routine of contemporary society and the ubiquitous situation of mobile devices increase the opportunities to learn foreign languages. However, the educational applications (apps) of foreign languages for mobile learning available nowadays are still not in accordance with the contemporary context and needs of learners. Research shows that it should contemplate multimodality (Kress and Van Leeuwen, Reading images: the grammar of visual design. Routledge, London, 2006), critical reading (Braga, Rev Latinoam Tecnología Educativa 9(2):63–76, 2010), situated learning (Cope and Kalantzis, Multiliteracies: Literacy learning and the design of social futures. Routledge, London, 2003), and the systemic-functional conception of communication (Halliday, Language as social semiotic. Edward Arnold, London, 1978), as presented in Andrade’s thesis (2017). To apply mobile digital technologies in

I. Rego de Andrade (*) Education Management, Serviço Nacional de Aprendizagem Industrial (SENAI-SP), São Paulo, SP, Brazil Campinas State University (Unicamp) – Campinas, São Paulo, SP, Brazil e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_122

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relevant manners to the learning of foreign languages, it is important to pay attention to how these technologies are used in educational contexts. To propose a coherent alternative to the scenario of a contemporary language education, it was designed an application for learning Spanish as a foreign language by Brazilian university students called Vecindario. The technical development was carried out by a multidisciplinary team of researchers in the fields of applied linguistics and computer science. This study examines the main lessons learned in the design process, prototyping and validation with volunteers, with the intention to help future projects that intend to develop educational applications for learning foreign languages like this one.

1

Introduction

Mobile devices represent the possibility of access to information for people who previously did not have other opportunities to connect to the Internet. This aspect is relevant because the Internet has become a privileged space for the exchange of information between people, institutions, and interest groups of the most diverse subjects. Through the net, you can also access educational content, previously restricted to physical school environments, such as classrooms and libraries. Mobile phones are the best-selling mobile devices in Brazil today. It has sold more devices than the population itself (around 280 million according to IBGE 2016). This widespread in recent years was mainly due to the cheapness of digital technologies, the expansion of 3G and 4G, and the expansion of free Wi-Fi networks. This scenario, represented by a range of different mobile devices, in which the flow of communication and interpersonal relationships permeate multiple screens and multiple platforms, sets up what has been called the mobility’s era. In a previous study, Andrade (2017) examined some of the applications available for learning Spanish language and concluded that there are gaps both in technological development and in the pedagogical design of such apps. In terms of technology, sophisticated features are used, such as user interaction interface with well-developed software, gamification features, and integration with social networks. In counterpart, the same applications consider a pedagogical point of view centered on language teaching out of specific contexts of use. The language assumption taken as reference for the development of some of these applications is usually related to out-of-date structuralist concepts, developed in the period of World War II, and the target language cutouts do not go beyond vocabulary and small sentences. The language assumption, who took prominence in behaviorist teaching tradition, is considered inefficient for learning nowadays. Contemporary ideas of language education consider relevant multimodality (Kress and Van Leeuwen 2006), critical reading (Braga 2010), situated learning (Cope and Kalantzis 2003), and systemic-functional design of the communication (Halliday 1978).

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Considering this gap between pedagogy and technology, a group of researchers from Campinas State University (Unicamp, Brazil) proposed the instructional design of a new application, called Vecindario, that includes such aspects of language and, at the same time, explores the technology resources available on mobile devices. The project was led by a Spanish teacher, with experience in e-learning, which was relevant to understand the main difficulties that teachers on their daily jobs have to develop innovative activities with mobile learning. This project reached a prototype developed technically and available at an application store. With the prototype, it was possible to apply user tests that indicated paths for the application improvement and highlights how the pedagogical strategies proposed were helpful to improve language learning. Business applications available on app stores such as Google Play and Apple Store are usually developed by specialized technical teams in programming for mobile. In education, however, the project design, instructional design, prototype, and pilot testing are not always familiar to teachers or other persons involved in the development of teaching materials for language teaching. Therefore, this chapter aims to share the main lessons learned to collaborate with the development of other applications for teaching languages that also have a concern to meet the needs of learner’s today. In this chapter, theoretical foundations of the applications’ design will be briefly presented at Sect. 2. Then, the most important lessons learned by designing and prototyping Vecindario will be presented in Sect. 3. Finally, lessons learned from the pilot test with volunteers will be presented in Sect. 4, followed by future directions to related projects.

2

Theoretical Fundamentals of the Project

Mobile-assisted language learning (MALL) differs from regular computerassisted language learning because of the use of personal and portable devices that “enables new ways of learning, emphasizing the continuity or spontaneity of access and interaction across different contexts of use” (Kukulska-Hulme and Shield 2008). Among the main characteristics of this modality, the following stand out: • Access to educational content anytime and anywhere, so the student has greater flexibility and autonomy to study. • The provision of technological resources for these devices allows the development of oral and written comprehension and expression skills, in an interactive and integrated way. • Democratization of access to these specific types of training, since the applications are often free or with very low cost in relation to traditional language learning courses.

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Within the universe of digital mobile devices, smartphones have some advantages over other mobile devices: they are light, easily portable, and largely used in society and have sophisticated technology resources. By these reasons, they are suited to the lifestyle of people and increase the possibilities of access to information by a larger group of users, who previously had no opportunity to learn foreign languages, whether in classroom or by e-learning. The design of contemporary language education that supports this proposal is based in current concepts of pedagogy and language which together can account for some of the learning needs of young university students who need to learn a foreign language. In this project, it was taken into consideration theoretical guidance on teaching and learning of languages in contexts mediated by mobile devices. The first aspect that supports this definition is related to the idea of text and context. According to the systemic-functional linguistic, initially proposed by Halliday’s studies (1978), text is the materialization of language. Within a universe of possible meanings, the text is formed by words chosen according to the context. So, language deduces the context and the context predicts the language. When teaching foreign language considering the text as a scope greater than isolated words and expressions, it is possible to use strategies for the student to learn how to make the proper sense of forecasts to social contexts where communication occurs, which includes also the different contexts of culture. Thus, according to this theoretical line, the minimum unit of meaning of human communication through language is the text, and the study of language structures should be focused on the construction of meaning in the text. Multimodality is another relevant topic for contemporary learning. Semiotics’ study highlights meaning making beyond the written text: image, sound, gesture, and space, among others. By integrating these modes, it is possible to compose new senses, unique and different from the previous ones, in texts called multimodal. In the current context of easy access to the digital technologies resources, these semiotic modes gain more prominence, increasingly present in the form of expression in digital media. These technologies enable the creation of new ways of representing and making meaning with the increasingly complex integration of different communicative modes available in the culture. It is important to note that communication in today’s world is being built, increasingly, as multimodality. The current scenario also demands that learners become increasingly autonomous in learning. This autonomy’s development can be exponentiated by digital literacy and the metacognitive reflection. Digital media available to young people are artifacts for cultural expressions, but there is resistance from them to use it for learning (Buckingham 2008). So, it is important to teach students how to use these new tools available for learning, so they can have more control over their own learning process in the foreign language. The metacognitive reflection can help bring the student to develop strategies to control their own cognitive processes and promote the analyzed language learning (Braga 2010), so that he can look for ways to fill gaps in prior knowledge and systematize knowledge he is acquiring in another language.

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Motivation is a relevant factor to promote language learning and can vary from one person to another, turning learning into a personalized and individual experience, although it has bases in the individual’s social context (Moura 2010). Motivation is a complex and multifaceted construct, involving intrinsic and extrinsic aspects of personality and combining the effort to the desire to achieve the learning goal (Gardner 1985). Therefore, to promote motivation is considered a relevant aspect in contemporary language education. In this contemporary scenario, mobile digital technologies, especially devices such as tablets and smartphones, are part of our daily activities, and it is present in displacements between home, work, school, and anywhere else. Considering this factor, the mobile learning modality was developed based on the quote “learning anytime, anywhere.” In this context, the central meaning of ubiquity is that the student can use short moments of time to learn, regardless of where she is. But researchers have noted that this is not always materialized, especially depending on the availability of Internet connection and the characteristics of the mobile devices (Zhang 2015). Ubiquity is a critical aspect that still demands technologically improvement that goes beyond educators’ efforts. To know and to consider which technology resources are available locally is an aspect that should be considered by instructional designers. As mentioned earlier, the aspects highlighted – text and context, multimodality, autonomy, motivation, and ubiquity – not always are considered by developers of mobile applications to language learning. To show how these important aspects can be integrated in a Spanish language app, the group of researchers designed the application Vecindario. To materialize Vecindario, first it was elaborated the instructional design by defining the curriculum, as well as content, activities, and assessment. This research was conducted as a case study (Gil 2009), which sought, rather than a definitive answer to the proposed problem, a more accurate view of the problem. The script of the application screens was organized in a storyboard, an instrument that, according to Filatro (2004), has the function of informing the contents to be presented visually and with technical indications for the production team. This script then was adapted by an expert in user experience, which signaled relevant aspects to be considered in relation to the design and application navigation, preventing how learners would interact with each screen. According to Von Saucken et al. (2013), the design for user experience (UX) focuses on the subjective perception and emotional response of an individual when using a product. This methodology allows to predict the reactions of users to interact with software and has been widely used to design applications for mobile devices. In the case of educational apps, this aspect is closely related to the motivation of the learners, engaging them in the tasks and favoring the access to the information that he may need. With the proposal to set design, the application of the prototype based on the storyboard was developed technically. The proposal was discussed with a multidisciplinary group of researchers from the Language Institute and the Computing Institute at Campinas State University (Unicamp), the last one collaborated in projecting the technical parameters of production and developing a prototype of Vecindario.

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Once the prototype was developed, it was performed the pilot test with eight volunteers representing the goals of the public: Brazilian university students. Considering the complexity of the development of empirical research and the need to analyze such a refined form of experience, it was developed different tools to collect and process data. Volunteers were invited by email and once accepted to join the project; they could choose between two modes of participation: • Group 1: Completion of the online course by their own mobile device, at the times and places of their convenience. • Group 2: In person, using the think-aloud methodology (Sanz et al. 2009; Bowles 2010), where the participant should verbalize his thoughts aloud while interacting with the application. Using the think-aloud (TA) methodology, it was possible to identify the perception of users regarding navigability, especially related to facility of use, and identification of information and understand the logic path chosen by the users, so as to make the app the most simple and intuitive. With this methodology, it was also possible to identify how students understood the tasks requested and if samples of the language offered were clear enough. In both groups, after the experience, volunteers were interviewed to have more concrete data about the application usability and the learning of the Spanish language by the participants. Google Analytics was used to track the subjects while navigating by the application. They were notified about the navigation tracking by agreeing to participate in the survey. This feature was of great relevance for the analysis of users’ browsing experience, as will be detailed below.

3

Lessons Learned in Building Vecindario Prototype

Distance learning courses differ from a traditional classroom, among other things, by the need to plan all educational activities, predicting assistance and the possible doubts and difficulties of students. Therefore, the planning stage is very relevant and should provide all kinds of support that a student may need when studying by himself. By designing Vecindario, the first decision made was to select the target audience in focus. In this case, the target audience was Brazilian university students who had not studied Spanish formally before. Only after setting this aspect, it was possible to propose language learning activities contextualized, considering the experiences and sociocultural environment of such public. The next step was to decide the best kind of mobile device to focus. This public has greater access to smartphone with Android operating system. It is given that a wide range of devices with this operating system with many brands, sizes, and technical capabilities exist. This aspect, until recently, was a factor that hindered the technical development of software applications, making necessary to choose only one device to focus. Currently, however, there are authoring software that allows developing APPs with a responsive design, which enables the adjustment

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of different screens (including adapting the same screen to smartphones, tablets, and computers). The choice of Android operating system was a very positive aspect of this experience, since it made the application accessible to most of the participants and the system proved to be quite stable. It was not reported bugs related to access or slowness. The login by Facebook made it easy to identify users for data analysis and to increase security by avoiding access by robots. Also, Facebook is related to sociocultural profile of the participants (college students). However, it is important to check in future projects whether this social networking option is more general for other user profiles or whether it restricts access for users in certain countries. After such settings, it was elaborated the curriculum of the course, based on references of the Common European Framework (Cervantes 2002), whereas a Brazilian apprentice with little previous knowledge in Spanish, given the proximity with the mother tongue, would be able to acquire skills within proficiency levels A1 and A2. The next step was to design an activity map that defined the name, content, and number of screens and resources of each activity inside each module. This activity map, however, did not bring enough information to design the interactions specifically, so it was designed a storyboard describing technically and pedagogically every screen of Vecindario. This resource was very productive for the technical team to produce the screens and the programming that integrates the different features. However, this is just one of the possibilities, and other alternative scripts might achieve similar results. This document was also used as a reference by the designer to prepare the screens based on usability principles (Fig. 1).

Fig. 1 Storyboard example. (Source: Andrade 2017)

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When performing the technical development of Vecindario, it was possible to identify the difficulties that a multidisciplinary team have when developing an innovative application to foreign language learning. Despite the availability of authoring tools for developing applications for mobile currently, these are still not sufficiently intuitive for a layman to create himself an application with innovative features that goes beyond the access features and allow to integrate various features into a single app. Therefore, the development of a software application with unprecedented activities still demands high investments in programming. There are some technical and time issue constraints regarding the development of the app. The gamification features, for example, given their complexity, were not developed and were rescheduled to the next stage of the project. To program gamification features such as scores, feedback, and ranking requires a reasonable investment in human resources. Regarding the design, modeling the screens for programming team did not reach the same aesthetic standard proposed by the user experience designer expert. The main lesson learned by these constraints was to initially focus on the development of some content modules and some of the functionality most relevant to the application. With a prototype, you can perform different tests that will guide the following steps of the development (Fig. 2). The management of the development work team facilitates the organization of technical production. The strategy adopted by this group was to organize every feature and every task as a goal and to arrange a schedule and a routine of development and validation between the different members of the team. The validation systematics occurred through a weekly routine with a delivery by the developer with subsequent validation by the instructional designer. For every new version of the application released, a file that was installed and tested in a smartphone was generated. The validation was performed identifying necessary adjustments that

Fig. 2 Example of Vecindario canvas drawing. (Source: Andrade 2017)

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were informed to the developer. After the implementation of the adjustments, it carried out a new validation and so on. For the management of the project, the team made use of file-sharing tools and tracking tasks (Trello 2017) by all their members. In this way, all the members could get a complete view of the progress of the project. Vecindario was produced using Android Studio software with integration of social networks such as Facebook (2017) and WhatsApp (2017) as well as YouTube (2017). Each screen of the app consists of two files: an XML file, responsible for the graphic part (such as the display of text, buttons, images, and menus), and a Java file, responsible for the logical part. The Java file responds to interactions made by the user on the screen, including the transition between screens using the touch movement. The source code has been generated in an XML file (Android Manifest) with essential information about the application, such as the Java package name, the permissions, and the minimum version of the API that it can be run in addition to the names of all Java files used. The app has been made available to the public through Google Play Store. When a user downloads Vecindario, it downloads most of the activities and videos, enabled to access it in offline mode. Some resources that require interaction with other participants and that require synchronization with database information were designed for exclusive use online. The user must log in her account on Facebook to access the app. This choice was taken because it is a social network with wide use by the target audience, so this login facilitates access by the participants, since the identification happens only once. For teachers and application administrators, this aspect helps to track their navigation route. In future stages of the development of Vecindario, this access can be used to create a community of participants in the social network. The access to the application is designed in an easy way to foster learner’s autonomy in the use of mobile digital technology. Google Analytics (2017) was used to track data of use of the app. When Vecindario was designed, it was defined in a certain way that it probably would be intuitively followed by users (as Fig. 3). By mapping data generated by Google Analytics, it was found that the route of users in real situation of use of the app does not always correspond to the expectations. In order to map this route, it was necessary to identify the log accesses of the user and track each action while interacting with Vecindario. This type of path trace data may be useful for the designer to raise more detailed hypotheses about the paths chosen by the users and evaluate advantages and disadvantages of access roads not foreseen initially. It is important to consider that these assumptions need to be checked more thoroughly because the user remote access does not allow the researcher to know if, once open the screen, the user is really interacting with the application or if she is also involved in parallel activities. Once launched on the Google Play app store, Vecindario application was installed and used by people from all over the world. This unexpected event escaped the control and initial proposal of the team of researchers and developers. This aspect brings a dimension of the reach of applications software to mobile

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Fig. 3 Activity diagram of the neighborhood application. (Source: Andrade 2017)

Fig. 4 Overview of Vecindario application. (Source: Google Analytics 2016)

devices. By using Google Analytics, it was possible to raise the number of people who used the application available online to the test situation (Fig. 4): The chart shows that 50 users downloaded the application. Disregarding the three project developers who also downloaded it for testing, it is possible to infer that 47 different people downloaded the app through Google Play. This number is higher than that of people who responded to the email invitation to join the survey, which shows that, once published in the app store, the developer no longer has full control over who will access it. It was recorded 294 sessions of access by the users. Each session lasted an average of 9 min and 20 s. It can be inferred from this information that this is the average time a user takes to perform an application topic.

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Despite the number of participants identified by Google Analytics, the next session will present the lessons learned in the validation test with volunteer participants who fit the target audience profile for which Vecindario was designed.

4

Lessons Learned from User Testing

Perform validation with users who represent the target audience segment is an important step for the technical development of an unprecedented software. It allows us to observe behaviors and reactions of the public and identify errors that can be resolved before spreading the access of the app for a larger audience. In the case of Vecindario, developed in the university environment and aimed at university students, the selection of users to prototype testing took place by inviting students who were interested to try it as volunteer. As presented earlier, volunteers who agreed to participate in the user test should initially choose one form of participation: online (Group 1) or in person (Group 2). Following, they should answer an online questionnaire aimed at identifying the previous experience to use smartphones to learn foreign languages. If they chose the online form, after answering the questionnaire, they should install the application on their mobile phone and start using it. After about 10 days, a phone interview was scheduled to raise data on its experience (opinion poll). If the volunteer chose Group 2, he should schedule dates and times for their participation in a meeting. In the test case, they were required to use the application applying the methodology of thinking aloud. At the end of the experiment, it was conducted an interview with the same survey questions answered by the Group 1. With this experience, it was possible to collect data that showed gains and losses in the development of the app prototype. The user test reveals technical problems that can only be observed in concrete situations of use. The most relevant technical problem was on the touchscreen technology, which is required in mobile applications for interaction through touch screen. For example, in a specific activity, the user was expected to drag the articles with his or her finger to position them in the empty space of the dialog. In the mobile screen that gesture demands a very high precision. This precision was not achieved in the prototype design. More specifically, to try to drag the word to the specified gap, the apprentice triggered other spaces on the screen, and the application automatically backed several previous pages. The recording of participants in Group 2 by think-aloud methodology allowed to find more specific details of the assessments collected retrospectively during the Group 1 interview. In educational applications, two practical problems may be caused by such difficulty: the student gives up the task or becomes insecure because he believes that it is his problem rather than the application’s bug. Data collected from users of the app also showed the need of improvement in instructional design. For example, as the digital screen has a different materiality than a printed content, it is important that the learner has some reference on the end of activities. In the original application’s design, it was predicted that at the end of the task, the student would be redirected to the Topics menu. However, it was

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not possible to implement that alternative in the prototype before the test. The data showed that this type of feature is important, because some users felt disoriented about when the task ended of (for lack of that information). Data test shows that users have expectations for this kind of resource. Some even made suggestions based on their experiences with educational APPs and games to improve the quality of Vecindario. Failures of functioning of some audio files were also identified in the tasks. For technical reasons, not detected before testing, some audio files stop working unexpectedly. This is a matter to be investigated in future technical research. Regarding the educational aspects, the test was crucial to identify the opinions of users, application aspects that require adjustments and increment. The lack of feedback that would guide the user about his linguistic performance interferes the participants in the task and in its motivation. This aspect was observed in both Group 1 and in Group 2, to perform the exercise called Acción. This also leads to other necessary adjustment: design a feature for the user to redo the exercise. It was also found that the learner feels the need to review aspects of the content when performing specific exercises and the fact that having to go back linearly interrupts the process of reflection in which it is immersed. This difficulty generates learner disengagement, which points to the need for a more dynamic access through a network structure or an easy menu access to allow return easily to specific points of the material. Design issues also interfere with the student’s learning process. The content reception conditions on a cell phone are different from those of a desktop. While watching videos, for example, as the screen is small, it presents problems to synchronize video information with a text box and the translation into Portuguese. Although the video has subtitles in Spanish, the reading condition in screen phone is difficult because of the font size. For this reason, it is expected that some participants had trouble reading the subtitles in Spanish because, besides being a new language, it appeared in a reduced form on the screen. One hypothesis is that this could have been overcome if the student had access to translation. For foreign language learners, the translation may be a necessary support especially for the less experienced. However, graphic design, the button that led to the translation of the legend, was shifted spatially from the video, which may have led users to not associate functionality with the activity of understanding the video. The visual appearance also interferes in the learning experience, as it affects the motivation of the user to interact with the application. Considering the small size of the mobile screen, the graphic design ends up being even more important than in other media, even by optimization issues of little available space. When the user accesses the application, he or she has an expectation about the graphics quality. This expectation is acquired by using other applications and games in which the visual aspect is highly attractive. This user expectations can interfere in the interaction with educational applications less visually appealing. This represents a problem for language teachers, as the domain of digital edition is not regularly part of their professional routine. Data showed that the motivation for application

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use can be enhanced or hindered by issues of design layout. If the layout is not attractive, the user’s needs or pedagogical innovation of the material must compensate this limitation. Some participants had difficulty understanding the videos of the Spanishspeaking students. Different explanations can be given to this issue in addition to the most obvious: the quality of the recording. It is possible that, for learners at an early stage, oral reception, given the speed of speech, makes it difficult to distinguish the word limit, since in the oral speech, the words suffer elisions, i.e., they are naturally linked. The reduced domain of vocabulary in the target language can make it difficult to identify these limits. Seen from a linguistic perspective, understanding oral language demands more automatic domain of the target language than reading because in this second case, the player controls the speed of the input. This aspect points out the need for greater care in the recording process and the inclusion of support resources that may be useful to less proficient learners. It can, for example, in addition to the transcript in Spanish video, be included a caption with the text translated into Portuguese, which allows the learner to read the text and check words that failed to identify when watched the video. Another possible feature of being thought would be to include in the application the possibility of a less accelerated version of the recording of the native speaker. Other support feature highlighted by the users was the need to access the videos without using the Internet (in the prototype, the videos were available on YouTube channel, and to watch them streaming, the user must be connected to the Internet). This question is relevant to the discussion of the mobility since the Internet, while it expands the possibilities of the study, restricts access to the material in places where Wi-Fi networks are not widely available to the population. The mobile learning literature often emphasize the wide Internet access as an aspect favoring the study in displacement, since it expands access to content such as virtual libraries. However, it is necessary to seek ways of adapting such literature to local conditions of access in other countries. In Brazil, Wi-Fi networks are not always available. During the test validation, it was also identified positive evaluations. In the pedagogical design, students evaluated positively the content, especially because of the context. Even with the inclusion of context, some participants pointed out the need to access more systematic language information. The language education point of view that guides this project shows that the metalinguistic reflection, together with the contextual content, can be a facilitator of learning. Learners in early stages use the translation as a support for learning. This aspect has been noted by several participants that pointed out the translation as a resource of important support at moments of difficulty of comprehension. In general, the usability problems that have arisen in the test situation point out guidelines for the future development of authoring tools. The tools currently available for the production of specific teaching materials to MALL offer no possibility of exploring more sophisticated proposals from a pedagogical point of view as designed for a course like Vecindario.

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Future Directions

Lessons learned, reported in this experience, represent a scenario found by language teachers to seek to innovate their practice to the development of applications for MALL. In summary, the main points learned in this project were: • To spend as much time and attention necessary to have a good planning. • To focus on a specific public to design the curriculum. • To use storyboard as a tool to develop screens and to dialog with the technical team. • To seek for partnership with technical experts. • To stablish a minimum of functionalities and tools to be developed primarily in the prototype (something like the minimum value project developed by startups). • To manage the team with virtual tools that can be shared and visualized by everybody. • To stablish a systematic to validate the prototype that involves technical and pedagogical teams. • To integrate social networks and other apps that can be useful to specific activities. • To analyze data monitored via Google analytics. • To validate the prototype with the goals of the public in different ways (i.e., applying think-aloud methodology, interviewing, etc.). • To focus on design and visual aspects in order to promote better user experience possible. • To prevent different forms of support to the user. In this case, translation was essential to beginners in Spanish language learning. • To allow offline access to as many activities as possible. This experience was important to detect the main difficulties that arise for the creative process of design of an educational application. Lessons learned can be a starting point for teachers and developers further the development of MALL projects.

6

Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Design Considerations for Mobile Learning ▶ Framework for Design of Mobile Learning Strategies ▶ Instructional Design Principles for Mobile Learning ▶ M-Learning and U-Learning Environments to Enhance EFL Communicative Competence

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References Andrade, I.R. 2017. Aprendizagem de língua assistida por dispositivos móveis (ALADIM): uma proposta alternativa para o ensino da língua espanhola. Doctoral thesis, Universidade Estadual de Campinas, Campinas. Bowles, M.A. 2010. The think-aloud controversy in second language research. New York: Routledge. Braga, D.B. 2010. Aprendizagem reflexiva de leitura em língua estrangeira: Questões relativas à construção de materiais digitais para acesso independente, Cáceres. Revista Latinoamericana de Tecnología Educativa 9 (2): 63–76. Buckingham, D. 2008. Defining digital literacy: What do young people need to know about digital media? In Digital literacies: Concepts, policies and practices, ed. C. Lankshear and M. Knobel, 73–89. New York: Peter Lang. Cervantes, I. 2002. Marco común europeo de referencia para las lenguas: aprendizaje, enseñanza, evaluación. http://cvc.cervantes.es/ensenanza/biblioteca_ele/marco/cvc_mer.pdf. Accessed 21 Mar 2017. Cope, B., and M. Kalantzis, eds. 2003. Multiliteracies: Literacy learning and the design of social futures. London: Routledge. Facebook. 2017. Facebook. http://www.facebook.com. Accessed 21 Mar 2017. Filatro, A. 2004. Design Instrucional Contextualizado. São Paulo: Senac. Gardner, R.C. 1985. Social psychology, and second language learning: The role of attitudes and motivation. London: Edward Arnold. Gil, A.C. 2009. Estudo de caso. São Paulo: Atlas. Google Analytics. 2017. Google analytics. http://www.analytics.google.com. Accessed 21 Mar 2017. Halliday, M.A.K. 1978. Language as social semiotic. London: Edward Arnold. IBGE. Instituto Brasileiro de Geografia e Estatística. 2016. Acesso à internet e à televisão e posse de telefone móvel celular para uso pessoal, 2014. Rio de Janeiro: IBGE. Kress, G., and T. Van Leeuwen. 2006. Reading images: The grammar of visual design. London: Routledge. Kukulska-Hulme, A., and L. Shield. 2008. An overview of mobile assisted language learning: From content delivery to supported collaboration and interaction. In ReCALL, vol. 20, 271–289. New York. Moura, A.M.C. 2010. Apropriação do Telemóvel como Ferramenta de Mediação em Mobile learning: Estudos de Caso em Contexto Educativo. Doctoral thesis, Universidade do Minho, Braga. Sanz, C., H.J. Lin, B. Lado, H.W. Bowden, and C.A. Stafford. 2009. Concurrent verbalizations, pedagogical conditions, and reactivity: Two CALL studies. Language Learning 59: 33–71. Trello. 2017. Trello. http://www.trello.com. Accessed 21 Mar 2017. Von Saucken, C., I. Michailidou, and U. Lindemann. 2013. How to design experiences. In Macro UX versus micro UX approach, ed. A. Marcus, 130–139. DUXU/HCII, Las Vegas, Nevada. Youtube. 2017. Youtube. http://www.youtube.com. Accessed 21 Mar 2017. Whatsapp. 2017. Whatsapp. http://www.whatsapp.com. Accessed 21 Mar 2017. Zhang, Yu Aimee. 2015. Handbook of mobile teaching and learning. Berlin: Springer.

Tutors in Pockets for Economics

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Yu (Aimee) Zhang and Jun Hu

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Design of TIPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Flexible Contents for Mobile Devices and FTF Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Application Design for Flexibility and Extendibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Results and Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Limitation and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A: Survey Results for TIPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile teaching has both advantages and disadvantages in higher education when compared to traditional teaching methods. Mobile applications (apps) provide a good solution as an assisting teaching tool to solve misconception problems. Tutors in Pockets (TIPs) is a mobile app designed and implemented in the University of Wollongong. It is designed as an assisting teaching and learning tool for economic content. The project is designed as a flexible framework for teaching materials, which can be expanded into other Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] J. Hu WEMOSOFT, Wollongong, NSW, Australia Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_1

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majors and subjects if needed. Any mobile device-supported multimedia materials can be used in this app, such as video, audio, picture, web-link, and text. This app is designed to be easily connected with existing e-learning systems and models as a value-added tool providing an equal access to those developed teaching materials for the students using other mobile devices and students without a mobile device; the teaching materials are also adopted in lectures and tutorials. Both face-to-face interviews and online surveys are adopted to collect students’ and staffs’ feedback on this project. The results show that the TIPs app has a positive influence on students’ learning efficiency, understanding of complex conceptions, long-term memories, correcting of some misconceptions, engaging in discussion with other students and teachers, and performances in subjects. Students also agree that it helps them to use small time period (such as waiting for a bus) to study at anytime and anywhere.

Highlights • Mobile apps can be used as good assisting tools in teaching for the new generation.

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• TIPs has a positive influence on students’ learning performances and engagements. • TIPs is a flexible app with more potentials.

1

Introduction

Mobile teaching and learning (m-learning) has been introduced into higher education for many years (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). It evolves from broadcast to podcast and now we believe it is “appcast” time. The release of iPod touch and iPad increased the adoption of mobile learning (Cumming et al. 2013). The fast growth of wearable mobile devices, virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), provided more opportunities for mobile learning (Alkhezzi and Al-Dousari 2016; Yousafzai et al. 2016; Hennig 2016) (see also ▶ Chap. 79, “VR and AR for Future Education”). However, the adoption of new technologies and mobile devices in education received both supports and concerns from many researchers, such as whether they are as efficient as the traditional face-to-face (FTF) teaching and how to assess the influences of remote teaching (Alhassan 2016; Alkhezzi and Al-Dousari 2016; Yousafzai et al. 2016; Qiu and McDougall 2013; Mishra 2013). M-learning has both advantages and disadvantages when compared to traditional FTF learning (Alhassan 2016) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Instead of using m-learning as a substitute for traditional teaching, this chapter presents the design, development, adoption, and evaluation of a mobile assist teaching app in economics teaching for higher education. To facilitate teaching, mobile devices should be regarded as teaching tools as normal blackboard and chalk that the teachers used in traditional teaching. Empirical studies showed that it takes a long time for some teachers to adopt the new technologies and devices and some teachers may have negative views in adopting them in their teaching and learning processes (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 49, “1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation”). The confidence and skills of new technologies and devices will encourage the teachers adopting the technology in their teaching and learning processes. Technologies are no different to traditional innovation in teaching tools. What makes it different are how the mobile devices and mobile technologies are utilized in teaching and learning. To understand better how mobile technologies can assist teaching, it is important to learn the characteristics of mobile technology (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). The first characteristic of mobile devices is anytime and anywhere (McCombs 2010; Peng et al. 2009; Cumming et al. 2013; Alkhezzi and Al-Dousari 2016). However, the reality is mobile learning cannot reach its expectation as learning anywhere and anytime yet with current technologies and barriers (Zidoun et al.

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2016). The second characteristic is flexible access (Mishra 2013; Rennie and Morrison 2013). Students use mobile phones in short time periods, such as waiting for friends or on a bus (5–10 min). How to make good use of these short timeframes? A well-designed app should fit into this gap and assist students’ learning using small time slices (Zidoun et al. 2016) (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 33, “Mobile Education via Social Media: Case Study on WeChat”). Furthermore, the interactive and communicate functions with its “natural user interface (NUI)” from the original of mobile technology also support learning process (Zhang 2012a; Alkhezzi and Al-Dousari 2016; Hennig 2016) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Mobile learning can also assist disabled students or students with special requirements in their learning, personal learning, efficiency learning, team collaboration in learning, in-class learning, self-regulated learning, lifelong learning, and learning with social media (Hennig 2016; Connor 2009; Fernández-López et al. 2013; Sharples 2000; Casey 2013; Heatley and Lattimer 2013; Rennie and Morrison 2013; Poellhuber and Anderson 2011; Mao 2014) (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 33, “Mobile Education via Social Media: Case Study on WeChat”). This chapter presents a flexible app, which allows students to learn concepts in 5 min at anywhere and anytime. Tutors in Pockets (TIPs) is a flexible designed mobile app in terms of both content and technology aspects. To study the influence of this app on students’ learning, both face-to-face interviews and online surveys are adopted in the teaching evaluation from 1st year to 3rd year students in University of Wollongong, Australia, and also potential students in China. The results show that TIPs has positive influence on students’ performances. Section 2 reviews mobile teaching and learning literature and empirical studies. The design and implementation of this application are introduced in Sect. 3. Section 4 presents the feedback and results of this project. The last section presents the findings of this project and proposes for future studies.

2

Mobile Learning

Students are different today compared to the students in 1990s (Alley 2009; Fraga 2012; Zidoun et al. 2016). Before 2000, the majority of students were local students in Australian and New Zealand universities (see ▶ Chap. 50, “Cross-Country University Collaboration Barriers and Solutions”). But the number of international students increased dramatically in recent years (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). In some subjects, 90% of students in a class can be international students (see ▶ Chap. 50, “Cross-Country University Collaboration Barriers and Solutions”). Today, students use their tablets, laptops, and smart phones as learning tools (Zidoun et al. 2016; Alhassan 2016). They search online for evidence and support in tutorial discussions using online resources (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). They share information, upload photos, discuss questions, and communicate with their

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classmates and friends online (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). They download lecture notes and finish their assessment online (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Does traditional face-to-face (FTF) teaching and learning still suit the new generation of students? FTF learning has some irreplaceable advantages, such as facial and body language in communication, emotional transfer, and active experience (Stewart 2011; Lewin 1948; Kolb 1984). Williams (2009) found m-learning reported lower performance (8% in average) compared with FTF learning. Empirical studies showed that m-learning still has many problems in terms of technology barriers, performance improvement, and adoption levels to technologies (Doug et al. 2009; McCombs 2010; Williams 2009). The lack of Internet access has been a major challenge for the overriding anytime and anywhere of m-learning (McCombs 2010). The reliability and costs for mobile telecommunication services limited the adoption of mobile learning in many countries (Qiu and McDougall 2013; Yousafzai et al. 2016; Zhang 2012a; Metzgar 2017). Some ethical, cultural, and political reasons are barriers for the implementation of mobile learning (Park 2013; Zhang 2012a; Gesteland 2012). Some researchers argued that the games and some contents on the Internet via mobile devices are not good for students (Prensky 2001; Alley 2009). Mobile learning should also be combined with a well-designed curriculum, so they can attract learners (Sung and Hwang 2013; Bredl and Bösche 2013). The percentage of the world’s population covered by a mobile cellular signal increased from 61% in 2003 to 95% in 2016, but there are still 40% of people who do not have mobile phones in 2016 (ITU 2011, 2016). Although both fixed broadband price and mobile broadband price dropped dramatically from 2013 to 2015, affordability is still a barrier for mobile adoption in many countries (ITU 2016). The capabilities of mobile devices are greatly enhanced (e.g., CPU speed, storage space, fast network connectivity support, screen size, batteries, and resolution). In September 2016, education apps were the third most popular category (after games and business), which shared 8.55% of all active apps on the Apple App Store (reduced by 2% compared with the data provided in 2013) (Statista 2016). And 140 billion apps were downloaded from the Apple App Store in 2016 (Statista 2016). Mobile devices are changing the style of living and the methods of learning (Zhang 2012a; Zidoun et al. 2016; Alkhezzi and Al-Dousari 2016; Alhassan 2016; Hennig 2016). Mobile technology has been part of the learning and teaching processes into higher education for many years. In 2012, there were 1.5 million educational programs on iPad in the USA (Cumming et al. 2013). Mobile learning can be described as components and communication style, mobility, and ubiquity (Kukulska-Hulme and Traxler 2005; Peng et al. 2009). Researchers believe that mobile learning effectively engages students (Martin and Ertzberger 2013); increases teaching and learning efficiency (Mishra 2013; Keengwe 2013); assists special education (Keengwe 2013; Kennedy et al. 2013; Cumming et al. 2013; Fernández-López et al. 2013); improves quality of teaching (Mishra 2013); improves lifelong learning, personalized learning, and self-motivated learning (Sha et al. 2012; Mishra 2013; Hsu et al. 2013; Sun et al. 2016); and increases learning performance (Sung and Hwang 2013; Hsu et al. 2013, Alkhezzi and Al-Dousari 2016).

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To achieve an “anywhere,” “anytime,” and flexible teaching app, it is important to design the system from an online and offline perspective (Zhang 2012b). Tutors in Pockets (TIPs) is a project designed to assist teaching and learning in higher education from a flexible perspective. Instead of competing m-teaching against traditional teaching method, TIPs is designed as an app that complements FTF teaching and assisting students learning process. This project is supported by University of Wollongong and external business partners. The app is flexibly designed in terms of both content and technology. The design and outcomes of this project are discussed in the following sections.

3

Design of TIPs

Students are different today from the 1990s (Fraga 2012; Zhang 2012b) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). They use less time in library but more time on mobile devices (Qiu and McDougall 2013). They search materials online and communicate online to facilitate their learning and finish an assessment. The characteristics of mobile access are short time usage (5–10 min) and ubiquity. The screen of mobile devices also fits better with specific content. Therefore, study materials with less complexity and specific content are preferred in mobile learning. As shown in the survey conducted in 2012 (in Appendix A), the majority (81%) of students who studied economic subjects before have problems of misconceptions or understanding some of the economic terms. International students suffered more from this problem (Zhang 2012b). This was the initial drive of the design for the TIPs project. To facilitate efficient learning, multimedia materials are developed for economics threshold concepts (Zhang 2012b). These teaching materials are designed for mobile app (with short contents and small file size). Problems in real cases engaged student learning (Dabbagh and Dass 2013) (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). It also helps students to increase their learning efficiency and understanding (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). To accomplish a flexible extension requirement, TIPs is designed with separated contents’ design and app design, which can be easily expanded into any other subject or discipline. The design of flexible contents and extendable application is introduced in the following sections.

3.1

Flexible Contents for Mobile Devices and FTF Teaching

Animated teaching materials have a significant positive influence on learning efficiency and understanding (Connor 2009; Stephenson and Warwick 2002; Zhang 2012b; Kennedy et al. 2013). They help break the “7-minute rule” of focus in class (Zhang 2012b). They engaged students into class discussions (Ostrom 2004) (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”) and help overcome the misconceptions (Akamca et al. 2009; Kabapinar 2005; Keogh and Naylor 1999). Multimedia materials increased learning efficiency (Zhang 2012b).

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Some interactive and communication functions of multimedia learning content are also attractive to students. Combined with external links, other game platforms, or social media, multimedia content can play important roles in teaching and learning (Bredl and Bösche 2013; Sung and Hwang 2013). To engage students in economics study and increase their learning efficiency, animated content in real-world cases was developed for TIPs. To facilitate the mobile access, all the developed animations are less than 1 MB in size, which makes them easier and faster to be accessed. The animated content is designed without long text or verbal explanation to remove the barriers for international students and students with disabilities. Mobile device platforms for multimedia content provide content with smaller screens but high calculation capabilities. Figure 1 provides an example of the developed cartoon. As shown in Fig. 1, this animation (view animated version in Tutors in Pockets application from Google Play) demonstrates that inflation is a fluid increase of goods prices with most goods and services. The price increase of one or several goods is not inflation. The price index in each country is usually calculated from the prices of house or accommodation, cars or transportation, foods and drinks, clothing, living materials, luxuries, and others. The price index is used to calculate inflation rate. All the key concepts are included in a simple animation (Zhang 2012b). The barriers of studying the difficult concepts are reduced by approachable and colorful cartoons. Students can learn as much as they want based on the given knowledge base. They can also extend the readings when they find it interesting. In the first version of TIPs, 80 animations were aligned to 200 economic concepts (Zhang 2012b) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). To provide equal access to the teaching materials, students can use any mobile device or access it without a mobile device; the teaching materials are adopted for lectures and tutorials. The animations can be used for class discussion or as part of exam questions that help students understand complex materials or processes. As Fig. 1 Developed cartoons for economics teaching. (Source: from Tutors in Pockets in this study)

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shown in Appendix A, students found these materials have positive influence on their learning, which corrected misconceptions, engaged them into discussion, engaged them in economic study, helped on better understanding, increased learning efficiency, increased long-term memory, and increased overall performance in the adopted subjects. Lecturers and tutors found the materials useful in their teaching, while students indicated the materials encouraged their interest in the content (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Designed in small file sizes, the materials are easy to be used in lectures slides, tutorials discussions, or exam questions as well as in mobile applications. Figure 2 displays a scenario of using these materials in lectures and tutorials. As shown in Fig. 2, the simple case study in the table above demonstrates a case study for four concepts in economics: substitutes, complements, change of demand, and change of supply. Tea is a substitute to coffee, which means the increasing consumption on tea will replace the consumption on coffee (for general person). On the other hand, sugar and milk are complements for coffee, which means the increase of consumption on coffee will increase the consumption of sugar and milk (ceteris paribus – if all the other things are the same). The table below shows the factors that will change the demand curve and supply curve of coffee. The simple case study helps students understand better how to solve questions in real cases or exams. This animation increased group discussion in class. Students replace the coffee, tea, sugar, and milk with any other goods and services that they are familiar with. They are interested in the subject and concepts instead of learning from written text or asked to

↑ ↑ ↑

Supply of X (Coffee) 1. Prices of related goods (produced) b. Substitutes (Tea) ↑ d. Complements (Coffee leaves) ↑ 2. Expected future prices 3. Prices of factors of production ↑ 4. Technology ↑

↑ 5. The number of suppliers ↑ ↑ 6. The state of nature ↑

↑

↑

5. Population ↑ 6. Preferences ↑

↑ ↑

Demand for X (Coffee) 1. Prices of related goods a. Substitutes (Tea) ↑ c. Complements (Milk) ↑ 2. Expected future prices ↑ 3. Income ↑ 4. Expected future income and credit ↑

Complements

↑

Substitutes

↑

Change effects

↑ ↑ ↑

Fig. 2 Using flexible materials in lectures and tutorials. (Source: from Tutors in Pockets in this study)

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remember all the possible factors. Students indicated the graphics and cartoons helped them understand the difficult conceptions more efficiently in their studies. The mobile learning methodology provided students a quick and easy way to link the knowledge with any searching website or engine with similar concepts or a case study. Some of the concepts in TIPs have links to authorized website, such as Reserve Bank of Australia (RBA) or Australian Bureau of Statistics (ABS). Videos and cartoons are also supported in TIPs. However, due to the size and speed issue in mobile teaching and learning and the high cost of video access without Wi-Fi connection (Zhang 2012a), videos are removed from the second version of TIPs (the function is still active if any video needs to be uploaded or linked in any concepts). All the developed animations are freely accessed by tutors and lecturers in economics. A total of 80 animated animations or figures were developed for 200 economic conceptions in the first version. The flexible design of these materials fits well in lectures, tutorials, and examinations and provides equal access by all students and staff. The IOS version with first TIPs is designed only with the online access. Student can access all the text contents in this mobile application. But for any figure or animated materials access, students need to link to the server. Students learn from the current knowledge lists or search any concept via searching function in the application. Some concepts have tables, animations, formulas, videos, and links to external specialists (such as Reserve Bank of Australia or Australian Bureau of Statistics websites). Students can update their knowledge database by clicking the “update” button in settings page. It is recommended the students have a Wi-Fi connection when they update the application or view videos because of the high costs of mobile connection (Zhang 2012a). Therefore, the first version of TIPs is limited by mobile signal and connection to server. This problem is solved in the second version on both IOS devices and Android devices. To achieve flexibility in terms of access anytime and anywhere and extending to other disciplines, the software application is designed in a flexible framework.

3.2

Application Design for Flexibility and Extendibility

Technology problems and wireless access are major problems facing mobile learning (Peng et al. 2009). All of the developed mobile learning applications are limited by the capability of mobile devices and network broadband (Alley 2009; Kwon and Lee 2010; Peter and Gina 2008; Lagos et al. 2007). This project was limited by current technology capability and wireless coverage in Australia and globally. Wireless coverage and broadband capabilities for the wireless connections are still a problem in some regions (Zhang 2012a). An application with only online or offline functions loses the advantages of flexibility and ubiquity for m-learning. To implement a stronger “anywhere” and “anytime” mobile learning system, both online and offline functions are important in the structural design. Therefore, TIPs 2 adopted both online and offline parts in its IOS and Android versions. This

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provided a switch between online (with wireless connection for download and update) study and offline (without wireless connection for study anytime and anywhere) study functions. As initial data was installed onto mobile devices, users can use the application without wireless connection. But the initial download file size was much bigger than the first version of TIPs. Students were recommended to have a Wi-Fi connection when they download TIPs from UOW server or Google Play online application store. Students could search, learn, and review any concepts in TIPs anytime without mobile signal or Internet connection after the download. This function secured learning anytime and anywhere. When there is an update for new content or a database, students needed to connect to the Internet to download the new database or content by clicking the update button in the settings page, which does not disrupt the students’ learning process anytime and anywhere. Figure 3 illustrates the project structural design for TIPs. Teachers and designers can access the system via Internet in any city or region. Students learn anywhere with Internet or mobile signal connection wherever the data and content servers are located. This design was adopted in both version 1 and version 2 for IOS and Android versions in TIPs project. The project was designed as a flexible framework for teaching materials, which is easily updated or expanded into other disciplines if needed. Any mobile devicesupported multimedia materials can be used in this application, such as video, audio, picture, web-link, and text. Structured conceptions are saved on a database Training Provider

Data

DB Server

Designer

Content Manager Stream Server

University

Fire Wall

Internet City 1

Student Fire Wall

Student

City 2 Teacher

Wireless

Tutor

PDA Base Station Student

Mobile Phone

Teacher

Base Station Mobile Phone

Mobile Phone Mobile Phone

Fig. 3 Designs of TIPs. (Source: from the author)

Student

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(DB) server and can be downloaded into mobile devices as stand-alone data source. The content manager is on a university web server. Data can be updated by editor anytime through Internet upload. The multimedia materials are saved on a stream server. The application also provides web access to external links (such as the Reserve Bank of Australia website) or online video providers (such as YouTube). End users can update their database by downloading new content from the servers anytime and anywhere. TIPs app is available for Apple mobile devices and Android mobile devices. More than 95% mobile users at the University of Wollongong use Apple or Android devices (Zhang 2012b). To facilitate 5 min of learning (efficient learning), functions and contents are designed in a simple format. Each conception in this program consists of definition, multimedia materials, formula, case studies, or external links that can be read within 5 min. Figure 4 shows the UI for conception list, learning page, and settings page for TIPs. Figure 4 shows the case of one important economic threshold concept – opportunity cost. This content is composed with a definition of opportunity cost; animation shows a scenario (Zhang 2012b) and an animation with a formula in a real case study to calculate opportunity cost. All of these materials can be learned within 5 min. Compared with the text case study in economic textbook, the efficiency of learning is greatly improved. Mobile devices have the advantage of “nature user interface (NUI),” which provides opportunities for many new learning methods (Hennig 2016). TIPs was designed with a friendly interface with a list of alphabetically ordered conceptions. The search function is very easy to use by users with any keyword input at the bottom of the main screen or scroll down by initial letters on the right side of the main screen. The update function is inside the settings page in the right-up corner of the application main screen, which shows the current version of software, current version of database (DB), and contributors’ information. The Apple application project was planned in four stages: course materials design and development (October 2011–January 2012), mobile application design and

Fig. 4 UI of TIPs. (Source: from Tutors in Pockets in this study)

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development (January 2012–June 2012), test and release (June 2012–October 2012), and feedback collection (October 2012). The second project on Android system was from February 2013 to October 2013 for development, testing, releasing, and dissemination with the internal and external teams. Each developing and implementing process of the project is conducted and finished successfully under the scheduled time length. As a result, a total of 110 animations for threshold economic conceptions are developed for TIPs 2. A total of 204 enhanced economic concepts and case studies are composed into designed database for mobile application. The mobile application was developed by an external partner (Beijing Oriental Caesar Technology Co., Ltd). Function tests and integration tests are conducted coordinately by the whole team. The application (Apple version) was released to students in August 2012. The application was introduced to Econ101 1st year Macroeconomics and Econ306 3rd year subjects. Interviews for students and teachers were conducted in February 2012 for the developed multimedia materials. Student survey on the mobile application was collected online from August to October 2012 (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). The results (in Appendix A) showed that nearly 2/3 of the surveyed students were using iPhones. An Android version of Tutors in Pockets was developed in February 2013 due to the strong requirement from Android users. The Apple version is available on UOW mobile application site (apps.uow.edu.au), and the Android version is available for free download from Google Play. The project achieved the “anytime” and “anywhere” objectives by introducing a combination of online and offline portions in the application. Students found the application had positive influence on their learning (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). The evaluations and results of this project are discussed in the following section.

4

Results and Feedback

To study the influence of this application on students’ learning, both face-to-face interviews and online surveys were adopted (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). Seventeen interviews were conducted in February 2012 to collect feedback about the application. Another online survey was conducted in October 2012. The results are shown in Appendix A. Initially, four out of five students claimed that they had some problems in understanding economic terms or conceptions in their studies. The majority of students (76% of the surveyed students) agreed that the animations helped them better understand some of the concepts or cases. More than half of the students agreed that these materials corrected their misconception problems and helped on long-term memory. Nearly half of the students agreed that the multimedia teaching materials increased their learning efficiency and made them feel interested in their studies.

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Majority of the students who used TIPs (84% as in Appendix A) agreed that this application increased their learning efficiency and helped them use the short time periods (such as waiting for bus) to study. More than half of the students agreed that they were engaged in discussions with others and it helped them study anywhere and helped for better understanding during the lectures and tutorials. The objective evaluation from students’ performances showed that TIPs and the multimedia materials adopted in class have a positive influence on tutorial marks, essay marks, final exam marks, and overall subject marks. Students’ groups with TIPs and multimedia materials in class have an average 4 marks higher than the groups without introducing TIPs. TIPs also has a positive influence on all the individual marks. Students also indicated that “I had no idea what economics is but now I am interested in economics” (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”), which was a major achievement from the project. Another reply from a disabled student shows the developed multimedia materials are also helpful for students with disabilities “As a RA student I strongly believe that these cartoons would help, as I learn more from visual examples than reading big words that mean nothing to me” (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). The result of this project has been presented to the Teaching Excellence Committee (UEC and LETs subcommittees), UOW TV, UOW media, economics school seminar in the University of Wollongong, and others who are interested in teaching and learning with new technologies and methods. In 2017, TIPs is still online for free in Google Play (for Android devices) and UOW App list (for IOS devices). Many students in an economic discipline and other business schools are benefited from this application. TIPs can be easily adopted for any discipline or subject area with its flexible function and database design.

5

Limitation and Future Directions

Mobile technology and device have made a dramatic impact on human life and influenced the ways to teach and learn (Alhassan 2016; Zidoun et al. 2016) (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). Mobile technology is a tool to assist teaching and learning, not to create inequality in learning. Therefore, to make the teaching materials accessible for all students, educators should consider a blended teaching or complimentary teaching method when adopting mobile learning in the course. The differences in cognitions, cultural backgrounds, and preferences should be taking into account when designing mobile teaching curriculum. This project was for economic teaching in one Australian university and teaching in other content areas. Data was collected with a small sample of students, so a larger sample size is needed to fully understand the application’s impact on student learning. One important advantage of mobile education is its ability to provide personalized learning (Becker et al. 2016; Harris et al. 2016; Hsu et al. 2013; Tsay et al. 2010). Personalized learning is regarded as the trend for future education. TIPs is a

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mobile teaching and learning application designed for university students. With the animated contents, it could benefit younger students. The future design will be focusing on personalized learning in economics.

6

Conclusions

TIPs is an application dedicated to complement economics teaching. It helped the 1st year students and international students solve common misconceptions and better understanding of economics content. It increased learning efficiency through an online and offline switching design, for “anytime” and “anywhere” learning (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 52, “Student Feedback in Mobile Teaching and Learning”). It allowed students to use short time periods for studying economic concepts. The application developed has received positive feedback from teachers and students. It is expected to increase learning efficiency, help on understanding of basic economic threshold concepts, engage students in discussion and economics study, and increase their studying performance (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). The evaluation for TIPs found it has positive influences on correcting misconceptions, increasing learning efficiency, enhancing understanding, improving longterm memory, engaging discussion and interests, and increasing performance in subjects (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). It also helps students with disabilities in their learning (Kennedy et al. 2013; Cumming et al. 2013; Zhang 2012b) (see ▶ Chap. 1, “Design of Mobile Teaching and Learning in Higher Education: An Introduction”). Further projects should focus on mobile communication for students and teachers. New technology or devices can also enhance the learning experiences on mobile devices (see ▶ Chap. 29, “Adoption of Mobile Technology in Higher Education: An Introduction” and ▶ Chap. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”). TIPs can be easily expanded into other disciplines due to its well-designed flexible and extendable structure.

7

Cross-References

▶ 1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation ▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning

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▶ Cross-Country University Collaboration Barriers and Solutions ▶ Design of Mobile Teaching and Learning in Higher Education: An Introduction ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Parental Education: A Missing Part in Education ▶ Student Feedback in Mobile Teaching and Learning ▶ VR and AR for Future Education

Appendix A: Survey Results for TIPs Did you have any difficulty or problem in understanding some economic concepts before? #

Answer

%

1

Yes

81%

2

No Total

19% 100%

Do you use mobile phones? #

Answer

%

1

Yes

94%

2

No Total

6% 100%

What mobile device(s) are you using? #

Answer

%

1

iPhone

61%

2

Android and others total

39% 100%

Is English your first language? #

Answer

%

1 2

Yes No

21% 79%

Total

100%

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Do you think the animations or cartoons in this subject have positive influences on the following aspects of your study? #

Answer

%

5

They corrected some of my misconceptions or misunderstandings They engaged me in a discussion with other students or teachers They engaged me in Economic study or make me feel interested in this subject They helped on better understanding of some concepts or cases They helped on long-term memory

6

They increased my learning efficiency

49%

7

They increased my performance in this subject

31%

1 2 3 4

53% 38% 42% 76% 51%

How did TIPs influence your study? #

Answer

%

1 It increased my learning efficiency

82%

2 It helped me study anywhere

64%

It helped me study utilizing the small time 3 slots (e.g. waiting for bus) 4 It helped my lecture/tutorial study 5 It made me feel interested in this subject It engaged me in a discussion with other students or teachers 7 It increased my performance in this subject 6

82% 64% 73% 55% 45%

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Development of Chinese Character-Writing Program for Mobile Devices

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Design of Chinese Character-Writing Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 User Interface Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Functions Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Development of Chinese Character-Writing Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Challenges of Developing Chinese Character-Writing Program . . . . . . . . . . . . . . . . . . . . . 3.2 Developing Chinese Character-Writing Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Adopting Chinese Character-Writing Program in Class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Test and Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Improvement of the Chinese Character-Writing Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

480 481 482 482 485 485 486 487 487 489 491 491 492

Abstract

Mobile technology has been adopted in the language education for many years. Mobile teaching has its own advantages and disadvantages and is adopted as a complementary teaching method to traditional teaching in many schools and universities. Mobile app provides a good solution as an assisting teaching tool to increase learning efficiency, engage students in learning, and enhance learning performances.

Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] J. Hu WEMOSOFT, Wollongong, NSW, Australia Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_103

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The Chinese character-writing program is a mobile application designed and implemented in ACF Wollongong School, which targets on writing practices and group works. It is designed as an assisting teaching and learning tool for in-class and after-class writing practices in Chinese learning. The project is designed for primary Chinese learners. To make it available to all teachers and parents, the program is implemented by HTML5 and can be easily accessed via web browser through almost any mobile phone or computer without download or installation. Basic functions, such as showing animation of the orders of strokes, marking handwritings, cleaning writing area, and changing characters based on unit lists, are designed to meet the requirement from the Chinese language class teaching. The application was adopted in Chinese class and promoted to the parents with printed notes. The results show that the application had positive influence on students’ learning efficiency, interests in Chinese learning, and engagement in-group works with other students, teachers, and parents in competition. The future design of the application is targeting on handwriting fonts selection and social communication online. Wearable devices could be a good extended area for writing practices too. The future of language learning will be open to all new technologies and devices.

1

Introduction

Knowledge is a scarce resource. Although there are large quantities of free information online that can be searched by different searching engines, the accuracy and safety of “knowledge” are a concern for educators and parents (ITU 2016). Empirical study found that students with their mobile devices accessing the Internet rarely use them in learning (Alhassan 2016; Hirsh-Pasek et al. 2015; Sana et al. 2013). The level and presentation of knowledge varies for different age groups and different students even in the same age group. Teachers are regarded as “door keepers” (to keep the information safe for the students and dangerous information away from students) for online information, but the current artificial intelligence (AI) firewalls (automatic content filter to stop some dangerous contents and keep the students’ confidential information safe) are still not good enough to identify some of the risks as human can do (Rennie and Morrison 2013; Yousafzai et al. 2016). A blended teaching method (with current technologies and devices) is still preferred (Rennie and Morrison 2012). One of the most important aims of education is to engage students in their learning and keep their interests in identifying problems, adopting critical thinking when searching for solutions, and seeking new knowledge in that area (Demouy et al. 2015, Sung and Hwang 2013). This will lead to a voluntary self-motivated learning and a lifelong learning (Sharples 2000; Mishra 2013). Increasing students’ interests and engaging them into self-motivated study is more important than knowledge transfer (Demouy et al. 2015). It is important in language learning (Alkhezzi and Al-Dousari 2016; Baage 2013; Demouy et al. 2015; Hsu et al. 2013). The learning efficiency and memories are much better when students are interested in the learning subject (Roediger and Pyc 2012). It reduces the barriers in learning (Alhassan 2016). When students find some difficult

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words, they are motivated to search the answer by themselves or raise a question. The self-motivated learner leads to better understanding and memories. This may lead to a lifelong learning in this subject. Learning through games may greatly increase the student’s interests in the subject. However, the games need to be designed and instructed by experienced educators, which should be linked closely to the knowledge points while avoiding too many gamifications. Language learning has been promoted by mobile technologies in many countries (Alkhezzi and Al-Dousari 2016; Demouy et al. 2015; Kabugo et al. 2016; Koutropoulos et al. 2013; Peter and Gina 2008; Zidoun et al. 2016). The adoptions of multimedia materials and personalized functions have been the highlights for those projects (Koutropoulos et al. 2013; Hsu et al. 2013; Alkhezzi and Al-Dousari 2016). Some empirical studies showed that mobile technologies enhanced students’ language learning efficiency and performances (Demouy et al. 2015; Peter and Gina 2008). From 2015, a Chinese language class was established in Wollongong Public School (see ▶ Chap. 10, “Design and Implementation of Chinese as Second Language Learning”). Students from local families without any Chinese language knowledge, from South Asia countries with more than two languages, and from Chinese background families who can communicate with others in Chinese fluently and can read or write several Chinese characters are all studied in the school. Language teaching for second language speakers is always challenging without practicing environments. Even for the students who speak Mandarin at home with their parents, it is still challenging for them to learn and practice their writing skills in the Chinese language school. To assist the teaching and learning in the school, a mobile and online writing practicing program was designed and developed by WEMOSOFT in 2016 and implemented in Chinese learning in class and after school. The design and development of the program are introduced in the following sections.

2

Design of Chinese Character-Writing Program

Mobile devices, like a pen or pencil, are just tools that can assist teaching and learning (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Technologies are just beautiful vases without being adopted and implemented in a well-designed educational program. Studies have found that most expensive educational programs or plans failed to reach their targets (Roediger and Pyc 2012). Different mobile technologies are adopted in different countries and associations all over the world (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Even if the technology or device is not suitable in its current iteration, that does not mean the technology or device is not “good” for a particular institution/ educational program. And the most expensive device/technology is not always the best. To design a good writing program for Chinese language class, it is important to understand the requirements from students and teachers first. Most of the students from ACF Wollongong School are Chinese background students, and some are from Asian background families and local families in Australia. Students are interested in practicing their reading and speaking in Chinese

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but have less incentive to practice their writing in Chinese. Chinese, regarded as one of the most difficult language to most language learners, is different from most of the other languages in its writing, characters, grammar, and pronunciation. The Chinese characters are formed by different strokes (Xu et al. 2004; Song et al. 2001). The writing, which came from the original abstract of drawing, is regarded as an art form (Dolinsky and Takagi 2007; Xu et al. 2004). To increase the students’ interest in Chinese calligraphy, we conducted several Chinese calligraphy practices in class (see ▶ Chap. 10, “Design and Implementation of Chinese as Second Language Learning”). However, students lack of incentives to finish their practices at home. To increase the in-class and after-school writing practices, a Chinese characterwriting program was designed and developed. Requirement analysis was conducted in term 4 of 2016. First, to meet the requirement of Chinese language class, the new characters taught each week should be categorized into each group for practice. Second, there should be showing of the order of the strokes (the order of writing is a learning goal in Chinese language writing) for each character. Third, to make students understand how well they had done or how much they had improved each time, an evaluation function is added to give a mark of the student’s writing. Students could use this function for group competition and other in-class group activities. Fourth, student could clean the writing anytime or restart the animation of order as they like or change to another character in the unit lists. To make it easy for students, parents, and teachers to access from any computer, mobile phone, or other devices, it is preferred to use an online form without installation requirement.

2.1

User Interface Design

To make the user interface (UI) friendly and easy to use for primary school students on both touchable and non-touchable devices, we designed the UI as simple as it can be with the required information on each page only. The welcome page listed all the ten units for the textbook. Figure 1 shows the welcome page with all units listed and the characters list for each unit page. Each unit has about ten new characters. Students are required to practice the writing of those new characters each week in class and after class. The graphical user interface (GUI) is touch screen friendly with large responsive blocks. The character pages with practicing functions (which is going to be discussed in the following section in details) are designed with more contents.

2.2

Functions Design

Figure 2 shows the design for a character page with the Pinyin (pronunciation of the character), character, number of strokes, order of strokes, showing of strokes, writing functions (change backgrounds scales or pen color), clearing function, saving

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Fig. 1 Welcome page and unit page for Chinese character-writing program. (Source: From this study by author) Fig. 2 Character page for Chinese character-writing program. (Source: From this study by author)

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Fig. 3 Recommended background scales difficulty levels. (Source: From this study by author)

function, restarting function (restart the animation showing of the order of strokes), and marking function. An animation is playing at the writing area with the standard character strokes order. Students can pause, resume, or restart the animation at any time by clicking the play control button. The writing area mimics the traditional Chinese character-writing practice book looking with bold red border to limit the writable area and dash back scales to help students locate the strokes’ position. Students can choose different types of grids according to their familiar levels or preferences. In general, the more indices, the easier to locate a stroke, and that’s why we recommend following difficulty order as Fig. 3 shows. “Score” button will compare the students’ writing with standard character by calculating the matching pixels. It is a concise algorithm but provides many gamelike stimuli to motivate students practicing and exploring more in Fig. 8. Our future improvement plan (new functions) includes stroke writing direction and order recognition, providing more accurate estimation score with these indicators and possible correcting suggestions. In order to encourage the students to share their practice results, we provide “Save” feature to export the students’ writing as images for their future reference. Those functions were implemented by WEMOSOFT and tested by ACF Wollongong School. The feedback and improvement of the functions are going to be discussed in the following section. The implementation and challenges during implementation of the application is discussed in the following section.

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3

Development of Chinese Character-Writing Program

3.1

Challenges of Developing Chinese Character-Writing Program

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The first challenge for the Chinese character-writing program is the order of strokes in Chinese characters. There are eight individual strokes, dot stroke, horizontal stroke, vertical stroke, left-falling stroke, right-falling stroke, turning stroke, hook stroke, and raising stroke (点、横、竖、撇、捺、折、钩、提), and many combined strokes in Chinese characters. Most Chinese dictionaries do not have the order of strokes for each character. Therefore, the order of strokes has to be inputted by the developer one by one. From calligraphy point of view, character with serif is more beautiful than non-serif one as Fig. 4 shows; but in our case, the serif is causing a lot of confusion to students when they try to follow the stroke and distracts the student’s focus from writing character to drawing a perfect serif. Therefore, we designed a semiautomatic algorithm to remove all the serifs from a character and use the sanserif character as our writing template. The second challenge for the Chinese character-writing program is to fit the screens on different mobile devices and computers. To make it easy to access from any devices (including mobile phone, iPad, and personal computers), the HTML5 program is running on web-based page instead of mobile App (which required purchase or download from an application marketplace, such as Apple App Store or Google Play). The initial welcome page is resized due to the browser, and it can be adjusted on mobile devices as required. Students can change the size of the screen to make it suitable and desirable for their own writing practices. They can change the background scales or writing colors that they feel comfortable with when practicing their writing. The third challenge for the Chinese character-writing program is the evaluation function. There are many algorithms in generating good or personalized Chinese

Fig. 4 Comparison of the same Chinese character Bai (Hundred) with serif (left one) and without serif (right one). (Source: From this study by author)

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character writing (Xu et al. 2004; Dolinsky and Takagi 2007; Song et al. 2001). However, it is hard to identify good handwriting as everyone has his/her own writing habits and skills. As the program’s users are primary school students (learning how to recognize and write Chinese character is the primary goal in their teaching and learning), the program helps to evaluate how much they write similar to the example (the formal Chinese character). This method met the requirement of primary school age writing practice and reduced the complexity of the evaluation function. To optimize the evaluation performance, we set up both canvas for writing layer and template layer with transparent background (where the alpha channel value for every pixel is 0). Then we only need to compare the alpha channel of all the pixels in both layers despite the color information to calculate the score S as Formula 1 shows.

S¼

l X i¼0

8
0 T i ½α > 0  _ , α ¼ 3 ^ ^ δðiÞ : 1, I i ½α > 0 T i ½α ¼ 0 I i ½α ¼ 0 T i ½α > 0

Formula 1. In score evaluation algorithm, I is the serial array of input pixels, T is the serial array of template pixels, l is the length of the serial array, and α is the index of alpha channel (in our case a pixel is represented by [red, green, blue, and alpha]).

3.2

Developing Chinese Character-Writing Program

To meet the requirements from the Chinese language school, the program was developed in term 4, 2016, by WEMOSOFT. It is released on WEMOSOFT website (free access through http://www.wemosoft.com/acf/). Teachers and students first test the program; some suggestions were adopted before the final release of the program. The first version (trail version) contained all the characters for the first lesson for the Chinese language school. The feedback was collected from the students for future improvement before all the lessons were released to students and teachers. To improve the program performance, we used a three-layer design as Fig. 5 shows to allocate different priorities to the await-rendering items. The top priority layer is Interactive Writing Layer, which captures the user finger/stylus pen movement and draws the trace; any tiny lag at this layer will affect user writing-experience severely. Dynamic Animation Layer is less important, and we will drop a few frames of animation if the computing resource is tight or the playing time is out-of-sync. As Static Display Layer names literal meaning, most of the items on this layer are static and only need update when required. Figure 6 shows the display of the order of strokes in the Chinese character-writing program. The writing area is still writable during the displaying time. Animations are preferred in mobile education as a multimedia tool to assist teaching and learning, which had many advantages (see ▶ Chap. 27, “Tutors in Pockets for Economics”). Students can write with their finger or stylus pen (can write on screens). They can press score to evaluate their writing with the marking function as shown in Fig. 7.

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Interactive Writing Layer

Dynamic Animation Layer for strokes order and background scales

Static Display Layer for information and buttons

Fig. 5 Three-layer design in Chinese character-writing program. (Source: From this study by author)

The program will calculate how similar the student’s writing is to the exampled character. This score can be compared with the other users’ scores too. With the evaluation function, student can learn how well they have done in writing or how much they have improved from last writing practice. Students can compete with each other on scores. Teachers can adopt the writing practice application in other in-class activities (such as team competition or games) to increase students’ social and communication skills. The program was adopted in ACF Wollongong School junior class in term 4 of 2016. Some amazing results and suggestions came from the teachers, students, and parents, which helped enhanced the program. The following section will discuss these practical “games” in detail.

4

Adopting Chinese Character-Writing Program in Class

4.1

Test and Feedback

First, the first unit with 11 characters was released to students and teachers to be tested in term 4, 2016, in Wollongong ACF School. Students were very excited to try the Chinese character-writing application in class. They soon got familiar with all the functions (they are designed to be easy to use). Students competed with each other in-class on higher score for each character. They finished all the characters very soon and asked for more. To avoid distraction from main class

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Fig. 6 Display of the order of strokes in Chinese characterwriting program. (Source: From this study by author)

teaching and learning, the teacher called for an end-on mobile practices and asked the students to practice their writing at home with any of their parents’ mobile device or computer (the link and notice were printed and given to each student in class). Students competed with their parents at home and tried to test the highest and lowest scores (test how the evaluation function works) too. The parents asked if there could be more units of the textbook characters added for the program (which were added to the list later). Figure 8 shows the tests for the lowest score using Chinese character-writing program by one of the talent students at home. Several teachers, students, and parents suggested some changes to the Chinese character-writing program. For example, one teacher suggested that the initial design of Chinese traditional handwriting characters with thick and thin parts in one stroke is very difficult for students to write with their finger. A parent suggested more units

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Fig. 7 Evaluation function in Chinese character-writing program. (Source: From this study by author)

with other characters should be added. Several students wanted to use the application on different screens. All of these suggestions were taken into account in the second version, which is discussed in the following section.

4.2

Improvement of the Chinese Character-Writing Program

To improve the Chinese character-writing program, several solutions were provided and adopted in the second version of the program. To solve the font problem, a new algorithm was adopted to remove all the handwriting thick and thin parts in the characters. The simplest is the best. To meet the requirement of primary school age users’ writing practices, the program was adjusted to use the simple fond with straight horizontal and vertical strokes. The strokes are easier to be written by primary aged students.

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Fig. 8 Tests for the lowest score in Chinese character-writing program. (Source: From this study by author)

All the characters were added into the program and put into different categories. Students can search and practice any character they like at anytime using a mobile device or a computer (they may use mouse to practice on computers). They can practice as many times as they like in class or at home. Research had found that parents play an important role in students’ learning performances and habit developments (KFRR 2016; Hurst 2017; Kim et al. 2014; Rowe et al. 2016) (see ▶ Chap. 9, “Parental Education: A Missing Part in Education”). Students love home reading mostly because this is a special time with parents (KFRR 2016). The Chinese writing program can create another opportunity for parents to play a competition game with their children in learning and practicing, which increased the children’s writing skills as well as family interactive time. Therefore, parents were encouraged to practice Chinese writing and assist students to finish their homework in the Wollongong ACF School. Third, the application was adopted in-class on the big projected touch screen. Students were playing with their writing practices and competing with each other in class. However, students were easily distracted from the writing practices with open access to computers too. The writing practice unit was called for an end after the practice. The program was used for home practicing.

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Future Directions

The next step of Chinese character-writing program is to combine with social media with font selection by students. Social media is not new to educators too. The writing program link is shared on WeChat, which most of the parents were using for Chinese language class parent group discussion. They are good social media to reach Chinese background parents too (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). Wearable technologies have attracted many researchers’ attention in recent years. They are convenient with their anywhere and anytime attributes. But some researchers argued that they are limited by their computing capability, screen size, battery power, distraction from core learning materials, and the issues with the confidentiality of the personal information. For younger kids, the protection of eyesight and health issues is considered when mobile devices are adopted in teaching and learning. Some educator argued that students are distracted from learning units or programs on mobile devices too. With increased development of mobile technologies, most of the limitations will be solved. As computing capabilities and batteries keep improving with new hardware and materials, mobile learning will become an essential part of the teaching and learning process. New technologies, such as VR and foldable screens, enabled higher resolution and more content on small screens. Mobile safety hardware and software, such as face recognition and finger print or voice recognition, are developed to provide better protection for mobile users. Eye-protecting technologies, such as blue ray protection screen and glasses, protect users’ eyes. Nevertheless, some social apps and location-based apps encouraged people to communicate more with friends and family as well as keep them healthy by encouraging them to reach daily exercise as suggested by health organizations. For example, one of the most famous mobile games in 2016, Pokémon Go, had increased users’ walking distance due to the report in the USA, thanks to all the companies and researchers working together to make mobile technologies better day by day. The future of language learning could be combined with new technologies (see ▶ Chap. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”) and new devices based on requirements from traditional classes.

6

Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning ▶ Design and Implementation of Chinese as Second Language Learning ▶ Parental Education: A Missing Part in Education ▶ Tutors in Pockets for Economics

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References Alhassan, R. 2016. Mobile learning as a method of ubiquitous learning: Students’ attitudes, readiness, and possible barriers to implementation in higher education. Journal of Education and Learning 5: 176. Alkhezzi, F., and W. Al-Dousari. 2016. The impact of mobile learning on ESP Learners’ performance. The Journal of Educators Online 13: 73–101. Baage, S.U. 2013. Using Wimba Voice Board to facilitate foreign language conversation course. In The plugged-in professor tips and techniques for teaching with social media, ed. S.P. Ferris and H.A. Wilder. Oxford: Chandos Publishing. Demouy, V., A. Jones, K. Qian, A. Kukulska-Hulme, and A. Eardley. 2015. Why and how do distance learners use mobile devices for language learning? The EUROCALL Review 23: 10–24. Dolinsky, J., and H. Takagi. 2007. Synthesizing handwritten characters using naturalness learning. In IEEE International onference on computational cybernetics, 19–21 Oct 2007. IEEE: Dolinsky and Takagi, Gammarth, Tunisia. Hirsh-Pasek, K., J.M. Zosh, R.M. Golinkoff, J.H. Gray, M.B. Robb, and J. Kaufman. 2015. Putting education in “Educational” apps: Lessons from the science of learning. Psychological Science in the Public Interest 16: 3–34. Hsu, C.-K., G.-J. Hwang, and C.-K. Chang. 2013. A personalized recommendation-based mobile learning approach to improving the reading performance of EFL students. Computers & Education 63: 327–336. Hurst, N. 2017. Students more likely to succeed if teachers have positive perceptions of parents. Missouri: University of Missouri. ITU. 2016. Measuring the information society report. ITU. Geneva, open access: https://www.itu. int/en/ITU-D/Statistics/Documents/publications/misr2016/MISR2016-w4.pdf. Kabugo, D., P.B. Muyingda, F.M. Masagazi, M. Mugagga, and M.B. Mulumba. 2016. Tracking students’ eye-movements when reading learning objects on mobile phones: A discourse analysis of luganda language teacher-trainees’ reflective observations. Journal of Learning for Development 3: 51–65. KFRR. 2016. Australian kids & family reading report. KFRR. Kim, J., S.J. Lee, S.A. Taylor, and N. Guterman. 2014. Dyadic profiles of parental disciplinary behavior and links with parenting context. Child Maltreatment 19: 79–91. Koutropoulos, A., D. Hattem, and R. Zelezny-Green. 2013. Mobile digital storytelling in the second language classroom. In The plugged-in professor tips and techniques for teaching with social media, ed. S.P. Ferris and H.A. Wilder. Oxford: Chandos Publishing. Mishra, S.K. 2013. Quality education for children, youth, and adults through mobile learning. In Pedagogical applications and social effects of mobile technology integration, ed. J. Keengwe. Hershey: Information Science Reference. Peter, E.D., and J.M. Gina. 2008. Working memory capacity and mobile multimedia learning environments: Individual differences in learning while mobile. Journal of Educational Multimedia and Hypermedia 17: 511–530. Rennie, F., and T. Morrison. 2012. e-Learning and social networking handbook: Resources for higher education. New York: Routledge. Rennie, F., and T. Morrison. 2013. e-Learning and social networking handbook, resources for higher education. New York: Routledge. Roediger, H.L., III, and M.A. Pyc. 2012. Inexpensive techniques to improve education: Applying cognitive psychology to enhance educational practice. Journal of Applied Research in Memory and Cognition 1: 242–248. Rowe, M.L., N. Denmark, B.J. Harden, and L.M. Staplenton. 2016. The role of parent education and parenting knowledge in children’s language and literacy skills among white, black, and Latino families. Infant and Child Development 25: 198–220. Sana, F., T. Weston, and N.J. Cepeda. 2013. Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Education 62: 24–31.

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Sharples, M. 2000. The design of personal mobile technologies for lifelong learning. Computers & Education 34: 177–193. Song, X., Y. Luo, A. Niwa, and E. Al. 2001. Stroke extraction as the preprocessing step for CJK outline font compression. In 8th International conference on neural information (ICONIP). Denver, Colorado Sung, H.-Y., and G.-J. Hwang. 2013. A collaborative game-based learning approach to improving students’ learning performance in science courses. Computers & Education 63: 43–51. Xu, S., F.C.M. Lau, K. Cheung, and Y. Pan. 2004. Automatic generation of artistic Chinese calligraphy. In National conference on artificial intelligence, San Jose, California 937–942. Yousafzai, A., C. Chang, A. Gani, and R.M. Noor. 2016. Multimedia augmented m-learning: Issues, trends and open challenges. International Journal of Information Management 36: 784–792. Zidoun, Y., F.E. Arroum, M. Talea, and R. Dehbi. 2016. Students’ perception about mobile learning in Morocco: Survey analysis. International Journal of Interactive Mobile Technologies, Zidoun, 10(4): 80–84.

Part III Adoption of Mobile Technology in Teaching and Learning

Adoption of Mobile Technology in Higher Education: An Introduction

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Abstract

With the evolution and upgrade of telecommunication infrastructure and end user’s devices, more and more students in higher education now possess their own Internet-connected mobile devices with moderate computing power. Mobile teaching and learning have flourished, allowing people to study anywhere at any time. Since 2000, the percentage of the world’s population covered by a mobile cellular signal has increased dramatically, and the number of users keeps growing at a fast rate. The capabilities of mobile devices have also been greatly enhanced. In January 2013, education apps accounted for 10.55% of all active apps on the Apple App Store, with 40 billion apps downloaded in early 2013. As of January 2017, 2.2 million mobile apps were available to download for various iOS devices, and 180 billion apps had been downloaded from Apple store (https://www.statista. com/statistics/263795/number-of-available-apps-in-the-apple-app-store/). There are barriers to the spread of mobile teaching and learning, such as the high cost of mobile data access and smart mobile devices, and there is debate about the efficiency comparison to the traditional face-to-face teaching, but it is widely acknowledged that mobile devices have changed the way we live and learn, especially for younger generations. As the use of mobile devices spreads among the new generation of students, a great need for mobile learning has emerged. From the early types of mobile devices to the smart phone, the adoption of mobile technologies in H.-J. Lee (*) Faculty of College of Education and Human Ecology, The Ohio State University at Lima, Lima, OH, USA e-mail: [email protected] J. Hu WEMOSOFT, Wollongong, NSW, Australia Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_4

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teaching and learning has now achieved over a decade of experience. Educators from universities, schools, and educational institutions, from many countries and various disciplines, have designed and adopted many different mobile educational models. This is an iterate life cycle with design, development, test, and improvement. All the current mobile applications have been through these processes and have been enhanced by the long journey. As a result, the adoption of mobile learning in teaching and learning has now matured from its initial stage and to the vast benefit of many students and learners in higher education and industry. Mobile teaching and learning (M-learning) was introduced into higher education many years ago. To improve the design and implementation of mobile teaching and learning, the experiences of prominent pioneers of this movement are collected in this volume. In the following chapters, M-learning educators and designers from around the world share their broad experience and practice, and its impact in different disciplines. Advantages and disadvantages and the critical issues of these programs are discussed, and solutions proposed. The findings from real practices shed light on the future design and adoption of different mobile learning programs. The adoption of high technology in education has been the subject of much debate. Is it as efficient as traditional face-to-face (FTF) teaching? There are many pros and cons. In its current stage, M-learning should complement, rather than substitute, traditional teaching. How does one assess the influences of remote teaching? Due to the current limitations and barriers of mobile technology and mobile devices (such as screen content, high cost of mobile data transfer, low signal quality, etc.), mobile learning is far from an adequate replacement to traditional learning methods. A blended-learning mode (which is combined with FTF learning and online or mobile learning) is a preferred learning mode for both educators and learners. To facilitate teaching, mobile learning should be used in the same way as the traditional blackboard and chalk: not for its own sake, but to serve the needs of teaching and learning. The advantages of mobile teaching and learning are many. They include (but are not limited to): access (not fully achieved, but constantly improving); flexibility; more efficient use of short time intervals for learning; cost saving; engaging in-class and after-class discussion with teachers and peers; supporting more interactive functions and contents; assisting special needs of students; increasing interest in learning; enhancing personal learning; engaging team collaboration in learning; improving self-regulated learning; engendering life-long learning; and learning through social media. Linda Robson introduces the challenge of making mobile learning accessible in the chapter ▶ Chap. 32, “Accessibility Challenges in Mobile Learning.” Although the use of mobile delivery opens up the educational experience to most learners, it is likely to be problematic for students with special needs. The chapter discusses the meaning of accessibility in M-learning and the types of challenges for designing resources, and how to maximize accessibility for mobile learning programs. Accessibility is defined as the extent to which a service or product is available to as wide a range of individuals as possible. Some challenges, including different educational settings, different mobile devices and screens, different cultural background,

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different environments, and different economic status, are discussed in the chapter. The author also encourages the readers to be aware of the range of challenges in student learning and the accessibility issues that affect students, not only those with special needs. Debra L. White sheds light from the educator’s perspective in ▶ Chap. 38, “Gatekeepers to Millennial Careers: Adoption of Technology in Education by Teachers.” Mobile technology brings greater access to good, as well as bad, resources to our students. The challenge therefore presents itself to the educator, of serving as gatekeeper for the generation born into the midst of such technology and mobile devices. Barriers to mobile teaching and learning still remain. The lack of universal Internet access, the lack of continuity of mobile data transfer between high buildings and the differing qualities of mobile signals in different areas are examples of technical barriers. The high cost of mobile data access and the high cost of smart mobile devices present economic problems for adopting mobile learning. Even in Australia, not all university students have mobile or smart mobile devices. To provide equal access to teaching materials and content, those students without a mobile phone should be taken into consideration. Dr. Helen Farley and Dr. Helena Song introduce a cross country mobile learning program in the ▶ Chap. 30, “Mobile Learning in Southeast Asia: Opportunities and Challenges.” Southeast Asia is a diverse region comprised of different countries, cultures, religions, politics, and languages. Mobile learning is well-documented in the UK, Europe, the USA, and Australia, but not many studies focus on mobile learning in Southeast Asia. This region contains both developed countries such as Singapore and developing countries including East Timor. At various levels of economic development, the extent of telecommunications technological penetration varies greatly. The infrastructure to support mobile and Internet networks may vary vastly, and the lack will inhibit the use of technology for learning. The chapter examines the mobile device market in the various countries of Southeast Asia and the particular demographics of those users. The impact of Internet censorship on mobile learning is also examined. The current policies, infrastructures, and mobile learning initiatives of mobile learning in a cross-section of East Timor, Indonesia, Malaysia, the Philippines, Singapore, and Thailand are examined separately. In the end of the chapter, the enablers and barriers to mobile learning in Southeast Asia are reviewed and proposals for future directions are made. The authors believe that in many areas of Southeast Asia, traditional modes of didactic delivery are still dominant. The findings of this chapter shed light on future international mobile learning design and development for educators. It is important to successfully implement mobile learning in an educational institution, but difficulties may present themselves on the way. Several experts in the field of mobile teaching and learning lead the way toward a better future in mobile teaching and learning design and implementation, by sharing the vast experience derived from their practice and classrooms. In the ▶ Chap. 34, “Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts,” Wendy Kraglund-Gauthier

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explores the philosophical frameworks that impact instructors’ approaches to teaching in post-secondary educational contexts. She shares her experience and findings in the practice of mobile teaching and learning. The findings also indicate future design of mobile teaching curriculum for mobile teaching and learning. The author argues that concepts of reflection-on-practice and reflection-in-practice, from the previous century, remain of prime importance. When the implications for teaching and learning in and outside the classroom with digital and mobile technologies are fully considered and addressed, a rich pedagogical experience can emerge. In ▶ Chap. 40, “Evidence-Based Teaching and Real-Time Assessment: Adoption of Mobile Interactive Apps,” Muztaba Fuad discusses the importance of evidencebased teaching and immediate assessment and feedback in class. The chapter proposes the use of mobile technology as a way to improve student engagement and problem-solving skills. It presents a sequence of steps needed to deploy a mobile response system and shares examples. In addition, the author shares some strategies and issues that instructors should be aware of in adopting mobile interactive activities. Providing real time feedback on students’ performance can improve student engagement and motivate them to learn better. As the author suggests, mobile-based in-class educational approaches should help faculty provide an evidence-driven teaching environment. This chapter discusses the theoretical background for such mobile-based approaches and its need in the classroom to provide both students and faculty with a real-time understanding about learning and to help students better engage into traditional lecturing. Additionally, the chapter discusses how such mobile-centric interactive systems could facilitate evidence-driven teaching. The chapter concludes with a discussion of issues that need to be considered for such adoption and it presents an example of a mobile-based system to facilitate evidencebased teaching. In ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat,” Dr. Aimee Zhang introduces the design of social media teaching and learning on WeChat. This chapter examines a new mobile social media platform – WeChat – which has more than 800 million users worldwide. Considering its relatively short history, the number of registered WeChat users has increased dramatically. Instead of using university teaching materials, this study composes teaching materials for public learners and compares the number of readings, reposts, and likes for different contents on three mobile educational social media public accounts: WollongongBaby, WEMOSOFT, and MobileClass. These designs provide learners with a new method of self-motivated learning. Different functions of WeChat and the WeChat public account allow for different expression of knowledge, sharing of knowledge, group discussion, and feedback collection, whereas the study found that content is the most critical component for social media teaching and learning. In ▶ Chap. 31, “The Development of Mobile Learning in China’s Universities,” Dr. Nan Ma, Xiaofen Zhang, and Dr. Yu Zhang shared various definitions of mobile learning used in the field, the characteristics of M-learning, M-learning application categories, and limitations of M-learning. In addition, the authors analyze their empirical studies on mobile teaching and learning at Beijing Union University,

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China. The findings showed that different programs suit different learning from different cultural backgrounds. Dr. Susan Crawford and Patricia Fitzpatrick propose a method for the adoption of mobile technologies and devices in physical education in ▶ Chap. 37, “Use of Mobile Digital Technology and iPod Touches in Physical Education.” They describe the widespread benefit of the program, which used iTouches and iPads in physical education initial teacher education. Mobile technology brought knowledge together and generated new innovations when it was adopted by cross-discipline designers and educators. In ▶ Chap. 36, “Tangible Objects and Mobile Technology: Interactive Learning Environments for Students with Learning Disabilities,” Elif Polat and colleagues define and describe the potential benefits of Interactive Tangible Technologies, a tangible mobile application for students with specific learning disabilities. The chapter also includes suggestions for future direction and implementation of the ITT mobile app. ▶ Chapter 39, “Trust/Distrust: Impact on Engaged Learning” focused on understanding why and where an individual’s trust/distrust is situated and how and why they choose to engage in online/digital spaces is a chapter in which Dr. Martha J. Hoff establishes the complex interrelatedness between experience, context, relationships, cognitive perspective, emotive states, and trust. Mobile learning and the online and classroom spaces provide powerful potential for collaboration, social connection, and distributed knowledge. Dr. Hoff explains how this diversity of engagement needs to be acknowledged in order to fully benefit from the mobile learning experience. Supportive government policies and regulations, as well as those of university administrations are imperative for the success of mobile learning. The matching goals of educators and institutions must be carefully coordinated to launch an effective mobile learning program. Professional development of designers, educators, and administrators in mobile curriculum design, mobile technology skills, and knowledge of mobile teaching and learning are key in this endeavor. The following chapters consider design features, professional development programs, and external supports needed for successful implementation and adoption of M-learning. In ▶ Chap. 41, “Instructional Design Principles for Mobile Learning,” Dr. Eun-Ok Baek and Eyda-Qi Guo point to the challenges of implementing mobile learning. These challenges include lack of instructional and infrastructure/technological support from institutional policy, as well as the instructors’ insufficient training, knowledge, and skills on mobile learning. The authors review ten studies and report on instructional design principles and frameworks for M-learning. The key features of mobile learning design are categorized in five areas: pedagogies and educational theories, platform and system design, technology acceptance, evaluation, and motivation and interaction. After reviewing previous studies, the authors share principles aiming to serve as guidelines for instructors who wish to design and develop mobile learning systems for each of the five categories.

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In ▶ Chap. 35, “Mobile Web 2.0 Tools and Applications in Online Training and Tutoring,” Dr. Zuzana Palkova introduces the use of mobile Web 2.0 tools and applications in online training and tutoring, through the outcomes of the Leonardo da Vinci project MobiVET 2.0. As Web 2.0 had been widely adopted in online teaching and learning, it has also been adopted in many mobile teaching and learning applications and programs. Online training and tutoring has quickly developed in professional development programs in many countries. The MobiVET 2.0 project aims to fill the online training gap between the self-directed learners and VET trainers by developing mobile E-learning 2.0 knowledge and skills of the trainers. The primary descriptive analysis was conducted to analyze the results from MOBIVET 2.0 students. The author also indicates that it is essential for educators to learn new technologies as they design and implement successful mobile learning programs. This chapter shares useful findings in the use of this technology for real online training programs. In these chapters, educators and teachers from around the world have shared the experiences and findings they encountered in real practice. Taken together, this collection of chapters gives a comprehensive perspective on mobile teaching and learning, with indispensable insight on how mobile technology may be adopted in the future for teaching and learning not only in universities but all schools and educational institutions, and for all public learners. The barriers and constraints that these authors have detailed in these chapters indicate specific directions for future improvement, design, and development of mobile learning. Institutional leaders and policy makers will also find these authoritative accounts of mobile learning and teaching invaluable in the creation of policy and regulations.

Mobile Learning in Southeast Asia: Opportunities and Challenges

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Contents 1 2 3 4 5 6 7

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Access to Internet and Mobile Internet in Southeast Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Internet Control and Censorship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ownership of Mobile Devices in South East Asia Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E-Learning and Mobile Learning in Southeast Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Technology Trends Impacting on Mobile Learning in Southeast Asia . . . . . . . . . . . . . . . . . . . Mobile Learning in Particular Southeast Asian Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 East Timor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 The Philippines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 Thailand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Future Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

504 504 506 506 508 509 511 511 512 512 513 514 514 515 516 517 517

Abstract

Mobile learning has been adopted to a varying extent across the countries of Southeast Asia. Though mobile learning initiatives in the UK, Europe, the USA, and Australia are well-documented, much less is known about mobile learning initiatives in Southeast Asia. This region is culturally and economically diverse, containing both developed countries such as Singapore and developing countries H. Farley (*) Digital Life Lab, University of Southern Queensland, Toowoomba, QLD, Australia e-mail: [email protected] H. Song Faculty of Creative Multimedia, Multimedia University, Malaysia, Cyberjaya, Selangor, Malaysia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_2

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including East Timor. This range of economic development means that the penetration of telecommunications technologies, including infrastructure to support mobile and internet networks, varies vastly, and the extent to which this technology is used for learning similarly varies. This chapter begins with an examination of the mobile device market penetration in the various countries of Southeast Asia and the particular demographics of those users. Internet censorship potentially will impact on mobile learning initiatives in some countries and this is examined briefly. The status of mobile learning in a cross-section of Southeast Asian countries will be examined, with a particular focus on government policies, critical infrastructure, and notable mobile learning initiatives. The chapter concludes with a review of the enablers and barriers to mobile learning in Southeast Asia and a look at future directions.

1

Introduction

Southeast Asia is a diverse region consisting of both developed countries and developing countries. It is not only economically diverse but also culturally diverse, shaped by extremes of climate, a diversity of religions, politics at both ends of the spectrum, and a multitude of languages. Southeast Asia incorporates the archipelagos of the Philippines, Malaysia, and Indonesia with East Timor, Singapore, Cambodia, Laos, Myanmar, Thailand, and Vietnam. Given this diversity, it is unsurprising that the levels of infrastructure available for information and communication technologies also varies between countries, even between neighboring countries. This chapter will first look at how access to internet and to mobile internet varies across the countries of Southeast Asia. Necessarily mobile learning requires access to mobile devices, so rates of ownership, affordability, and access across a number of countries in the region are detailed. Internet censorship is a significant factor, potentially impacting on mobile learning initiatives. How internet censorship varies between various Southeast Asian countries is briefly examined along with what is specifically censored in each case. The following part of the chapter focuses on a cross-section of Southeast Asian countries, looking at their own particular context and examining significant mobile learning initiatives that have been deployed. The chapter concludes with an examination of the barriers and enablers to mobile learning in Southeast Asia and a consideration of the future direction of mobile learning in the region.

2

Access to Internet and Mobile Internet in Southeast Asia

On May 16, 2011, the United Nations declared that access to the internet was a human right. That statement has implications for governments in terms of the provision of infrastructure, hardware, social access, and so on (La Rue 2011). In Southeast Asia, there are three distinct levels of broadband internet penetration

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(Deibert et al. 2012). In the first grouping are Brunei, Malaysia, and Singapore which have high levels of mobile, broadband, and computer penetration. The second group is made up of the middle-income countries, Indonesia, the Philippines, Thailand, and Vietnam. These countries have high levels of mobile penetration, but quite low levels of broadband internet and computer penetration. The third grouping includes Cambodia, Laos, and Myanmar, which have low levels of mobile, broadband internet, and computer penetration (Jeroschewski et al. 2013). Even though many do not have access to reliable broadband internet, the demand for internet and associated services is rapidly increasing (Jeroschewski et al. 2013). Counterintuitively, the number of internet users is growing more quickly than the number of internet subscriptions. Public access points, including internet cafes, account for this difference. For example, in Indonesia, around 7,500 “Warnets” short for “Warung Internets” supply affordable internet access to people in Java. Similarly, in the Philippines and Thailand, internet or cyber cafes provide affordable internet access to those who could not afford a connection in their home (Jeroschewski et al. 2013). Even with these constraints, the region has made remarkable progress in the last 10 years (So 2012). Broadband internet penetration is restricted in most countries within Southeast Asia due to the poor infrastructure. This is mostly attributable to a lack of private investment coupled with the severely limited capacity of the people to pay for services (Jeroschewski et al. 2013). Singapore and Malaysia are the significant exceptions to this technological deficit. New investors have focused their resources on providing infrastructure for mobiles rather than for broadband internet (Jeroschewski et al. 2013). In addition, a lack of access to electricity in Myanmar, Cambodia, and Laos necessarily limits the uptake of computer technologies. This is especially true in rural regions in these countries where the demand is not high and the disposable income of the residents is lower (Jeroschewski et al. 2013). In many developing countries, and those of Southeast Asia are no exception, mobile technologies have been adopted at greater rates, as compared to personal computers, also because tablets and smartphones are more affordable and easier to use (Zambrano et al. 2012). Even with the emphasis on supporting infrastructure for mobiles, there are three factors that hinder the penetration of mobile broadband. The first is lack of knowledge of potential users about the availability of mobile internet and the services it can facilitate (Jeroschewski et al. 2013). The second factor relates to affordability. The cost of buying a phone, a sim card, and any upfront fees associated with holding a mobile account can account for a large proportion of a person’s income (Jeroschewski et al. 2013). The third significant barrier is the lack of availability of internetenabled phones, particularly smartphones in some areas. In most areas, feature phones are still the main kind of phone available (Jeroschewski et al. 2013). In some areas this is rapidly changing and one in four people own a smartphone as they become more affordable (Jeroschewski et al. 2013). Southeast Asia benefits from its relative proximity to China where many unbranded, affordable smartphones are being manufactured (Jeroschewski et al. 2013) with some

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being used for mobile learning. Even so, in many countries in Southeast Asia, there is potentially a very large digital divide which often restricts access to education (Bandalaria 2005).

3

Internet Control and Censorship

Governments across Southeast Asia have to balance the increasing sophistication and availability of emerging ICTs on the one hand with social stability, cultural values, and security on the other (Deibert et al. 2012). In this region, there are some of the world’s most liberal societies and some of the world’s most restricted, all in close proximity (Deibert et al. 2012). Along with the growing dominance of mobile technologies in the marketplace, there is a corresponding increase in governments’ abilities to monitor and control access to the internet and all that can be retrieved with it. This monitoring generally manifests in the form of centralized filtering mechanisms, regulators to monitor content, and prosecutors to address transgressions (Deibert et al. 2012). Myanmar and Vietnam are among the most restrictive regimes with a particular focus on the restriction of independent media, material that could be considered to be politically sensitive, pertaining to human rights or political reform (Deibert et al. 2012). A report by the Berkman Centre of the Internet and Society (2006) revealed that Vietnam has sophisticated and effective filtering systems that resemble those of China. It is important for educators to understand the extent to which internet censorship may impact on mobile learning in Vietnam. Social networks, for example, are often used in mobile learning scenarios to encourage collaboration and sharing of information. In Vietnam, however, local authorities partially or wholly block access to sites such as Facebook (Subramanian 2012). Only a third (33%) of consumers in Vietnam over the age of 15 have a social media profile on a platform called Zing Me and 28% have an active Facebook profile (Nielsen 2011). Though a previous investigation of internet censorship showed no active censoring of information in Indonesia, more recent investigations suggest that pornography, select political and blasphemous content, and internet-tool-related content are censored. In Thailand, content related to politically sensitive events is filtered. In 2009, 44,000 websites were actively blocked by the nation’s government (Deibert et al. 2012). By way of contrast, Singapore only censors a relatively small number of sites, generally of a pornographic nature (Deibert et al. 2012). There is no evidence of filtering in Malaysia or the Philippines (Deibert et al. 2012).

4

Ownership of Mobile Devices in South East Asia Countries

Data suggests, that in some regions, mobile devices are being purchased instead of computers. In countries such as Cambodia and Laos, people won’t have access to a PC, but they will have access to a mobile phone (So 2012). This popularity of mobile devices is reflected in rates of mobile subscriptions as compared to the population.

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Commonly across Southeast Asian countries, there are more mobile phone subscriptions than people. The level of mobile phone subscriptions in Singapore is 153%, in Vietnam is 149%, in Malaysia is 141%, in Cambodia is 132%, in Thailand is 120%, in Indonesia is 115%, in Brunei is 114%, and in the Philippines is 107%. Even in a relatively economically disadvantaged country such as Laos, there are still roughly as many subscriptions as people (102%) (Greene 2013). Smartphones have more affordances to be leveraged for mobile learning, though levels of smartphone ownership as compared to feature phones remains relatively low across most of Southeast Asia. Of mobile phone users, the percentage of those who own smartphones are 15% in the Philippines, 23% in Indonesia, 49% in Thailand, 80% in Malaysia, and 87% in Singapore (Greene 2013). These figures are based on data collected by Nielsen Holdings who tend to concentrate their research on urban areas (Greene 2013). Those figures are generally lower for the countries overall. Data collected by Pew Research indicates that in Malaysia, 89% own a mobile and 31% own a smartphone; in Indonesia, 78% own a mobile and 11% own a smartphone; and in the Philippines, 71% own a mobile and 17% own a smartphone. Predictably, smartphone ownership tends to be higher in countries with higher per capita income (Pew Research Global Attitudes Project 2014). In addition, smartphones tend to be owned by people under 30 (Hussin et al. 2012). In Malaysia, 49% of 18–29 year olds own a smartphone, 30% of 30–49 year olds, 11% of 50+ year olds (Pew Research Global Attitudes Project 2014). In the Philippines, 24% of 18–29 year olds own a smartphone, 18% of 30–49 year olds, and 9% of 50+ year olds. In Indonesia, 18% of 18–29 year olds own a smartphone, 9% of 30–49 year olds, and 3% of 50+ year olds. This creates some opportunity for mobile learning with higher levels of smartphone ownership among the demographic that are most likely to engage in formal learning. Tablets are a low cost, flexible alternative to laptop and desktop computers, suitable for learning due to their ability to leverage mobile apps and their portability. They are suited to collaboration and are able to capture data (Johnson et al. 2012). Tablet ownership and penetration among mobile users in a cross section of Southeast Asian countries is rapidly increasing: there are 47% in Singapore, 42% in Malaysia, 16% in Thailand, 5% in Indonesia and 5% in the Philippines. These figures are as a percentage of mobile phone users in urban areas (Greene 2013). Though these figures are increasing, the overall penetration rates remain too low to leverage ownership for mobile learning. This would indicate that mobile learning initiatives designed for use in most Southeast Asian countries should be designed with smartphones in mind, and to ensure high levels of adoption, with feature phones in mind. In order to maximize the benefits of BYOD policies in educational institutions, any mobile learning intervention should leverage the affordances of mobile devices and users’ familiarity with those devices. It is therefore useful to consider how people in this region are using their mobile phones. The most popular use of mobile phones, after making phone calls, is texting (Pew Research Global Attitudes Project 2014). This is probably due to the very low cost of texting as compared to calling. In Malaysia, 89% own a mobile phone and 89% (of mobile phone owners) text, 51%

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take pictures or video, and 27% access social media. In Indonesia, 78% own a mobile phone, 96% of those people text, 46% take pictures or video, and 23% access social media. In the Philippines, 71% own a mobile phone, and of those 99% text, 54% take pictures or video, and 17% access social media (Pew Research Global Attitudes Project 2014). These figures should be kept in mind when designing mobile learning interventions. If the educator is going to ask students to use their phones in a way that is unfamiliar to them, sufficient training must be supplied in order to ensure the efficacy of the intervention.

5

E-Learning and Mobile Learning in Southeast Asia

Due to the poor access to broadband internet, and in some cases even electricity, there has been a marked lack of success with e-learning in many parts of Southeast Asia. Recent data suggests that prices for mobile phones and internet access have dropped substantially, opening the door for mobile learning initiatives in these poorer countries (So 2012). Even though mobile devices and subscriptions may still provide a significant cost for many people, mobile technologies are more affordable than both broadband internet and desktop or laptop computers. In addition, mobile learning provides study options to learners who are geographically remote from physical campuses and allowing them to fit study around their work or carer commitments (Chun and Tsui 2010). This flexibility is being demanded by learners, who want to learn wherever and whenever they want (Johnson et al. 2012). Mobile learning allows for both formal and informal learning (see ▶ Chap. 53, “Moving Towards the Effective Evaluation of Mobile Learning Initiatives in Higher Education Institutions”). In using their own devices, students are beginning to learn how to use their networks for more than just texting, allowing them to learn to “just in time” in response to emerging questions or problems. It also supports “discovered” learning where students discover the relevance of information for themselves, apt for their particular learning context (Johnson et al. 2012). There is also a move away from traditional didactic methods towards challenge-based and active learning, leveraging the affordances of mobile technologies to allow learning in real-world situations (Johnson et al. 2012). Mobile learning affords flexibility in open and distance learning institutions (Hussin et al. 2012), allowing those in rural areas greater access to education (Clothey 2010; So 2012; Jambulingam and Sorooshian 2013). Students are more and more wanting to use their own mobile technologies for learning. Mobile phones and tablets are viewed as an extension of an individual’s personality and learning style. Learners are familiar with using the devices in their personal lives and educators can leverage that familiarity to allow students to use these devices for learning (Valk et al. 2010; Johnson et al. 2012). For example, in 2010 researchers in Malaysia surveyed university students with some 84% of them wanting to participate in mobile learning activities. However, most did not want to incur data usage charges as part of that participation. Interestingly, less than half (46%) thought that their institution was ready for such a step (Hussin et al. 2012). In the Philippines, learners’

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familiarity with their own mobile devices was one of the reasons the University of the Philippines Open University decided to use mobile learning. No expensive training was required as people were already familiar with how to use their own devices (Bandalaria 2005). As a consequence, institutions are increasingly adopting BYOD (Bring Your Own Device) policies. Students can use their own devices for learning and well as in their personal lives (Johnson et al. 2012). By adopting these policies, institutions can spend less money on mobile learning overall. Though they do have to provide infrastructure to support a variety of devices, it is still less expensive than also buying the technology (Johnson et al. 2012). There is no longer any expectation for universities to provide technology directly to students. Since older students are likely to possess their own mobile devices, universities can take advantage of existing devices to encourage mobile learning activities, without having to purchase mobile devices for students (So 2012). Even though rates of mobile ownership are high in many parts of Asia (Chun and Tsui 2010), a survey of mobile learning articles in five prominent educational technology journals revealed that only one Southeast Asian country appeared in the list of the top 22 contributing countries – that country was Singapore (Hwang and Tsai 2011). Though there could be a number of reasons for this, including English not being the first language of educators, it is potentially indicative of the small numbers of mobile learning initiatives occurring in this region.

6

Technology Trends Impacting on Mobile Learning in Southeast Asia

There are a number of global technology trend that are also impacting on mobile learning in Southeast Asia. The impact of these trends are most evident in the more developed countries such as Singapore or Malaysia. These trends include cloud computing, social networking, and mobile applications or “apps.” In 2012, cloud computing was heralded by technology in education forecasters, the New Media Consortium (NMC), to be adopted within a year or two within K-12 in schools in Singapore. Though Singapore is a wealthy country with good access to both technology and ubiquitous connectivity, cloud computing is expected to make an impact in education on most countries across Southeast Asia. It allows for a shared pool of learning courses, digital assets, and resources to be accessed by educators and students. The cloud can be accessed via computers or laptops but also by a range of mobile devices (Teal et al. 2014). The learner is able to plug into this cloud anywhere and at any time using a mobile device (Teal et al. 2014). The cloud is especially useful in mobile learning as it removes the necessity for storing resources on the phone or tablet which have a necessarily restricted storage capacity. Social networking is increasingly being used by educators to promote interactivity in classrooms and to enhance collaborative opportunities. Interestingly, people in Southeast Asia are some of the world’s most frequent users of popular social networking sites such as Facebook and Twitter. In 2010, Indonesia, the Philippines,

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and Singapore were among the top ten Twitter users in the world. Similarly, the Philippines and Indonesia are among the top ten markets of unique Facebook users, ranking third and fourth respectively. Though these social networking sites are popular, they are not always accessed by mobile devices. Once people are online, they are very often using social media. In the Philippines, once online, 86% of people are using social media. In Indonesia, this number is 84% and in Malaysia, 76% (Jeroschewski et al. 2013). With these numbers, it allows the features of social networking such as discussion boards, the ability to broadcast announcements to select groups, share photos and videos, and so on to be leveraged for mobile learning. Anecdotal evidence would suggest that groups of students frequently form Facebook groups to offer mutual support and discussion opportunities in specific courses and programs. The use of web 2.0 tools to collaborate is becoming increasingly popular in Asia (Tsai and Hwang 2013), including Southeast Asia. In 2012, mobile apps or “applications” were predicted to be adopted in 1–2 years in Singapore. Mobile apps are low cost software extensions to smart phones that challenge the dominance of large, integrated software suites such as Microsoft Office (Johnson et al. 2012). Apps frequently have social functions that can allow sharing of content and discussion between users. Augmented reality apps can allow for exploration of historical sites with just-in-time information. Apps can also allow for creation of content, leveraging the features of the smartphone such as camera and sound recording features (Johnson et al. 2012). The literature indicates that discipline-specific mobile apps will become more popular. For example, there are large numbers of apps for foreign language students including dictionaries and flash cards. For almost every discipline, there are a number of apps available for both Android and iOS devices (Oz 2013). Electronic publishing is making a significant impact on education across the world, often through large publishing companies such as Pearson or Wiley. Publishing in this manner allows for infinite reproduction at low cost while incorporating rich media and publishing to a number of platforms, including mobile (Johnson et al. 2012). The distribution of electronic publications becomes particularly easy through distribution channels such as iTunesU. In 2012, it was said by the NMC to be adopted within 2–3 years in Singapore (Johnson et al. 2012). Enhanced electronic textbooks that can be accessed on mobile devices, particularly tablets, are being used instead of hard-copy textbooks in some countries. These electronic textbooks boast more interactivity and a range of multimedia (Johnson et al. 2012). Gamification is the incorporation of gaming or gaming elements into educational experiences. Games have been proven effective for learning skills and beneficial in cognitive development (Johnson et al. 2012), and are increasingly featuring in the literature pertaining to global education. Consequently, gamification has been used increasingly in education in Asia for the past 10 years (Tsai and Hwang 2013). Games used for learning across a variety of disciplines are generally goal-oriented, have strong social components, and simulate some real-world experience (Johnson et al. 2012). The NMC predicted in 2012 that gamification would be adopted in 2–3 years in K-12 education in Singapore (Johnson et al. 2012).

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As indicated earlier, the most common use of mobile phones, after making phone calls, is texting. There are numerous examples of mobile learning initiatives that have relied on text (Chun and Tsui 2010). Mobile learning initiatives that use texting are very useful as all phones as both smartphones and feature phones can be used for texting. Examples of this kind of learning would include SMS quizzes, where students would receive immediate feedback on their scores. Only in exceptional cases would students need to communicate directly with lecturers or teachers (Mohamad and Woollard 2010). The benefits of immediate feedback are welldocumented (e.g., see Peck et al. (2013)), encouraging students to become independent learners (Mohamad and Woollard 2010). Though this is hardly a new trend, texting being widely available for many years, it remains significant, particularly in the developing countries of Southeast Asia.

7

Mobile Learning in Particular Southeast Asian Countries

As previously indicated, the countries of Southeast Asia are economically, culturally, and politically diverse. The best way to explore this diversity and its impact on mobile learning is to investigate the status of mobile learning in a cross-section of countries, including government policy and particular mobile learning initiatives.

7.1

East Timor

It is very difficult to find information about mobile phone use and about mobile learning initiatives in East Timor. It is likely that this is in part with the amount of resources expended by East Timor to gain independence from Indonesia which finally occurred in 2002 (Marques et al. 2013). Now that independence has been achieved, the government can focus its efforts on reconstructing the country, particularly its struggling education system (Marques et al. 2013). One of the implications of independence from Indonesia was the resulting lack of teachers. Most teachers were Indonesian and subsequently returned to Indonesia after independence (Marques et al. 2013). It has been a struggle for the government and NGOs to make headway in a country where enrolment in school is just 70% of school age children and literacy rates remain very low (Marques et al. 2013). Only in recent times has the one-company monopoly over the supply of mobile phones been broken. Mobile phone ownership is now rapidly increasing (Cochrane 2012), though lags far behind other Southeast Asian countries. Though UNESCO has recommended that ICTs and in particular mobile technologies be employed (Capelo et al. 2014), there is little evidence that this has happened. A project whereby SMS messages were sent to new or expectant mothers to give them information about their particular stage of pregnancy or infant development appropriate to them has been trialed. If successful it will be rolled out more extensively (Cochrane 2012). This was the only mobile initiative that the authors could discover.

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Indonesia

There have been significant improvements to Indonesia’s education system over the past 40 years. The government has worked to decentralize education and thus improve access in rural areas and significant work has been done to improve teacher education (Suharti 2013). Indonesia’s population is spread across 13,000 islands, making the provision of education challenging (Bahar 2009). Consequently, much education is delivered at a distance (Soekartawi and Librero 2002). Originally, teacher education was the focus of distance education as most teachers, especially those in rural areas, had low levels of competency (Soekartawi and Librero 2002). High mobile phone penetration in Indonesia makes it an ideal place for mobile learning (Alamsyah and Ramantoko 2012). One of the issues with mobile learning in Indonesia is that reliability and quality of connection is frequently compromised due to too many concurrent users on the networks (Alamsyah and Ramantoko 2012). One way to overcome this would be to have students come to campus and access the university’s internet via Wi-Fi (Alamsyah and Ramantoko 2012). Though this will enable connectivity, it negates many of the positives associated with mobile learning such as access from geographically remote locations and the potential for contextual learning. In Indonesia, teachers’ participation in training is limited due to training location, time, cost, and opportunity (Yusri and Goodwin 2013). Despite various ICT training programs being conducted for teachers’ professional development, the ICT skill level of teachers in Indonesia is still quite low as shown by the National Examination of Teachers’ Competency which was conducted online in 2011 and 2012. Many failed simply because of their low basic ICT skill level. They did not know how to use a mouse and keyboard, how to open the examination applications, and how to answer the online examination (Yusri and Goodwin 2013). If teachers have low levels of competency in ICTs, it is nearly impossible for them to design and deliver mobile learning initiatives effectively. Much work remains to be done in this area.

7.3

Malaysia

High levels of ownership of mobile devices indicate that Malaysia may be ripe for mobile learning (Mohamad and Woollard 2010). Malaysians are also among the most prolific users of their smartphones, spending nearly 6½ h per week using them (NST-Business Times 2013). A number of mobile learning initiatives has been developed in Malaysia already, both in schools and in higher education settings (Mohamad and Woollard 2010). Other affirmative developments include the formation of the Mobile Learning Association of Malaysia (MLAM), which was officially registered on 21 January 2011; as well as the first International Conference on Mobile Learning, Application and Services (mobilcase2012) that was held in September 2012 (Song et al. 2013). In 2014, a Mobile Learning Symposium was held at the Multimedia University in Cyberjaya which attracted educators and postgraduate students from across Malaysia (Farley 2014).

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The National Higher Education Plan (PSPTN) developed by the Ministry of Higher Education is a document that indicates the direction of national higher education in Malaysia. Its purpose is to realize the country’s aspirations to become a developed, prosperous, and competitive nation. The implementation of the National Higher Education Plan is to be deployed in set phases and the Ministry of Higher Education has developed 21 Critical Agenda Projects to help achieve this. Mobile learning has been identified as one of the Critical Agenda Projects of the Ministry of Higher Education. The potential of mobile learning initiatives often remain unrealized in Malaysia due to a lack of access, bandwidth, and high cost to students (Embi et al. 2013). There are a number of groups in the Malaysian higher education sector who are actively implementing and researching mobile learning initiatives in Malaysia (Song et al. 2013). But even though mobile learning research has been steadily increasing in Malaysia, the deployment of mobile learning in higher education courses and programs has not been widespread (Embi and Nordin 2013).

7.4

The Philippines

It is difficult to implement distance education strategies in the Philippines due to the fact it is an archipelago of 7,107 islands which makes providing infrastructure difficult (Bandalaria 2005; Marques et al. 2013). Even so, there have been a number of successful mobile learning initiatives deployed in the last several years. By 2010, almost all of the courses and programs offered by the University of the Philippines Open University (UPOU) used some degree of mobile learning (Bandalaria 2005). The university has a mandate to provide high quality education to people no matter where they are and no matter what their circumstances. The university made a strategic decision to go fully online and in doing so inadvertently excluded large parts of the population from participating. The use of mobile learning helped to alleviate this disconnect to a certain extent (Bandalaria 2005). There are relatively high levels of mobile penetration in the Philippines and the population are enthusiastic texters, mostly because it is far less costly to text than to call (Bandalaria 2005). As people are using their mobile phones as part of their everyday lives, no expensive training was required in order to teach people how to use their mobile phones for learning (Bandalaria 2005; Clothey 2010). In addition, the learning became almost synchronous as educators could take a few moments to answer a student’s query whenever a text arrived. The educator could be traveling on public transport or waiting for an appointment (Bandalaria 2005). The UPOU used mobile phones for learning in a number of ways: to deliver short bites of course content to learners via their phones (in the early days, via feature phones); tutorial support or student consultation with educators; administrative support for learners; notification of results; and dissemination of information about other programs (Bandalaria 2005). The Text-2-Teach project in the Philippines is an example of a successful largescale project that used mobile technologies to deliver educational content to a

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diversity of schools. Since its launch in 2004, the Text-2-Teach project has provided schools with mobile learning resources in English, mathematics, and science (Natividad 2007). Students could readily download audio and video resources using their mobile phones. Teachers could also send SMS requests for educational resources to be delivered via satellite to a school television. The project was scaled up, reaching approximately 4,000 students in over 500 schools in the Philippines in 2011 (Ayala Foundation 2011). Similar projects have emerged elsewhere in the developing world where access to internet and computer technologies is limited.

7.5

Singapore

As one of the wealthiest countries in Southeast Asia, Singapore has systemic nationwide planning in ICT. The project FutureSchools@Singapore, launched in 2007, is the government’s initiative to build a new model for education by exploring innovative pedagogical approaches to the integration of ICT into school curricula (Koh and Lee 2008). Schools identified as “future schools” were awarded funding to transform their learning environments by deploying activities using ICT into the school’s curricula. The Singapore Ministry of Education expected to spread the pedagogical innovations developed in “future schools” to other nonparticipating schools in Singapore (Tsinakos 2013). While the use of mobile technology was not specifically mandated in the plan for FutureSchools@Singapore, some participating schools have already started exploring the potential of mobile learning through pilot projects. By way of example, Crescent Girls’ School, one of the original “future schools,” is making extensive use of tablets in the curriculum. All enrolled students have tablets preloaded with interactive digital textbooks. Nan Chiau Primary School, featured as a “future school” in 2011, has been trialing the deployment of mobile technologies into the curricula through various mobile learning initiatives since 2005 (So 2012).

7.6

Thailand

Students in Thai universities are ready and willing to trial mobile learning, yet mobile learning initiatives in these higher education institutions are relatively rare (Jairak et al. 2009). Research has shown that the price of mobile subscriptions, handset price, poor network coverage, and low disposable incomes of both educators and students hinder the uptake of mobile learning (Jiranantanagorn et al. 2012). There have been some mobile learning initiatives in Thai higher education institutions, however. A mobile learning initiative was deployed at King Mongkut’s Institute of Technology in North Bangkok. In this project, questions were displayed on a screen and the answers were texted using SMS (Librero et al. 2007). In this study, students were using feature phones with small screens and did express

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concern at trying to learn with such a small screen size (Valk et al. 2010). As smartphones gain more market share, this concern is likely to be less of a problem. Even so, 90% of the participating students owned their own mobile phones (Motlik 2008).

8

Future Trends

A noteworthy feature of mobile learning in Asia, and more particularly, Southeast Asia, is the movement toward designing learning environments that are future focused. These spaces are typically enriched by technology whereby some or the entirety of the learning experience takes place virtually. As would be expected, this move is more evident in wealthier countries with strong ICT infrastructure including Malaysia and Singapore. In these countries, the government’s focus is on designing technology-enhanced environments that satisfy the needs of contemporary, techsavvy learners. Mobile learning, while not specifically discussed at a policy level, is subsumed under broader ICT plans to build future learning environments (So 2012), and is likely to result in more, wide scale mobile learning initiatives. There are a number of special considerations that need to be kept in mind when designing mobile learning initiatives in Southeast Asia. The experience of participants with mobile learning or even with mobile phones may be highly variable; the access to and affordability of devices may be problematic; or internet searching, research, and access to social media may be impacted by internet censorship (Murphy et al. 2014). Pedagogical theories need to be re-examined and modified by educators, taking into account the devices used and their affordances. Linking theories to technology will enable educators to better leverage those affordances, allowing them to make best use of the technological context (Embi et al. 2013; Tsai and Hwang 2013). However, the pedagogy must remain the primary concern above the technology (Bandalaria 2005). Deploying mobile learning becomes a balance of leveraging the affordances of mobile devices while not disenfranchising those learners who are unable to afford the latest models. When designing mobile learning initiatives in developing countries, the rules and roles of the social relationships in the mobile learning space must be made explicit. Also, when designing mobile learning initiatives across cultural boundaries, special care must be taken to accommodate the cultural differences between designer and learner (Teal et al. 2014). Regional factors must be considered when designing for the learning behaviors of students. Each country has its own unique economic, political, and cultural context which may impact on how students can learn (Tsai and Hwang 2013). Instead of just using mobile devices for generic learning activities, as far as possible cultural learning and recognition must be incorporated into activities. For example, use mobile learning for cultural or social studies programs (Tsai and Hwang 2013). Cost remains a barrier and must be taken into account when designing and delivering mobile learning programs. There can be significant costs associated

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with buying a mobile device and then buying internet access or phone subscriptions (Bandalaria 2005). This is obviously going to be a more significant issue in those countries when the per capita income is lower (Tsinakos 2013). However, some consider mobile learning to alleviate the costs associated with some modes of study, face-to-face for example. Mobile learning enables learners to study remotely without the need to travel to a physical campus (Valk et al. 2010). Vigorous research is needed to establish the benefits of mobile learning in Southeast Asia. Large-scale initiatives need to be instigated so that good, reliable quantitative data can be collected to inform both future research and the future deployment of mobile learning (Tsai and Hwang 2013). There is an urgent need to measure the effectiveness and the efficiency of mobile learning systems (Bandalaria 2005). Additionally, good quality research can influence policy initiatives around technology-enhanced learning and inform the planning and resourcing of mobile learning initiatives (Hwang and Tsai 2011).

9

Future Directions

In 2012, UNESCO released a report which, among other things, looked at the enablers and barriers to mobile learning in Asia generally. The report named the following enablers: initiatives at the government and ministry levels; research in higher education institutions; and accessibility, connectivity, and affordability of mobile devices (So 2012). The governments of both Malaysia and Singapore have policy related to the deployment of ICTs in education which also includes mobile learning; it is unsurprising then, that a number of effective mobile learning initiatives have been deployed in those countries. Effective research is also being conducted in those countries. A number of academic groups are specifically researching mobile learning in Malaysia (Song et al. 2013); there are a significant numbers of academic papers being authored by Singaporean academics (Hwang and Tsai 2011). The same report also identified a number of barriers to the adoption of mobile learning. Some of these are fairly unsurprising including the cost of mobile devices and subscriptions. Others indicate a lack of available information about the affordances of mobile devices and the benefits of mobile learning, as well as general concerns around mobile phone use. These barriers include concerns about the misuse of mobile phones; teachers’ and parents’ mindsets and attitudes; health-related issues (especially fear of radiation); lack of teacher training and support; and lack of highquality educational content (So 2012). Lack of teacher support is often identified as a barrier to mobile learning and, for example, is the reason given for the low number of mobile learning initiatives in Indonesia (Yusri and Goodwin 2013). It follows then that critical success factors include: a high market penetration of mobile phones; adequate technological infrastructure (wireless network and mobile applications); and specific professional development on mobile learning for teachers (So 2012). Educators need to address the blending of formal and informal learning. In many areas of Southeast Asia, traditional modes of didactic delivery are still dominant (Johnson et al. 2012).

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Cross-References

▶ Moving Towards the Effective Evaluation of Mobile Learning Initiatives in Higher Education Institutions

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Soekartawi, A.H., and F. Librero. 2002. Greater learning opportunities through distance education: Experiences in Indonesia and the Philippines. Journal of Southeast Asian Education 3(2): 283–320. Song, H. S., A. Murphy, and H. Farley. 2013. Mobile devices for learning in Malaysia: Then and now. Paper presented at the proceedings of the 30th Australasian Society for Computers in Learning in Tertiary Education Conference (ASCILITE 2013), Sydney. Subramanian, R. 2012. The growth of global internet censorship and circumvention: A survey. Communications of the International Information Management Association (CIIMA). Advance online publication. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id= 2032098 Suharti. 2013. Trends in education in Indonesia. In Education in Indonesia, ed. D. Suryadarma and G.W. Jones, 15–52. Singapore: Institute of Southeast Asian Studies. Teal, E., M. Wang, V. Callaghan, and J.W.P. Ng. 2014. An exposition of current mobile learning design guidelines and frameworks. International Journal on E-Learning 13(1): 79–99. Tsai, C.-C., and G.-J. Hwang. 2013. Issues and challenges of educational technology research in Asia. The Asia-Pacific Education Researcher 22(2): 215–216. https://doi.org/10.1007/s40299-012-0038-9. Tsinakos, A. 2013. State of mobile learning around the world. In Global mobile learning implementation and trends. Beijing: China Central Radio/TV University Press. Valk, J.H., A.T. Rashid, and L. Elder. 2010. Using mobile phones to improve educational outcomes: An analysis of evidence from Asia. The International Review of Research in Open and Distance Learning 11(1): 117–140. Yusri, I.K., and R. Goodwin. 2013. Mobile learning for ICT training: Enhancing ICT skill of teachers in Indonesia. International Journal of e-Education, e-Business, e-Management and e-Learning 3(4): 293–296. https://doi.org/10.7763/IJEEEE.2013.V3.243. Zambrano, R., K. Seward, and S. Ludwig. 2012. Mobile technologies and empowerment: Enhancing human development through participation and innovation. United Nations Development Programme (UNDP). Retrieved from http://www.undp.org/content/undp/en/home/librarypage/ democratic-governance/access_to_informationande-governance/mobiletechnologiesprimer. html

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Nan Ma, Xiaofen Zhang, and Yu (Aimee) Zhang

Contents 1 Overview of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Definition of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Development Stages of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Characteristics and Content of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Characteristics of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 The Mobile Learning Mode of Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Application Prospect Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Core Strengths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Limitations Exist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Situation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Case Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Case Introduction: Campus Course Selection System Based on Mobile Terminal Platform in Beijing Union University . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 The Introduction of Software Development Environment, Design and Implementation, and Related Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 The Introduction to the Software’s Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 The Analysis of Difficulties and Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter is mainly about research on mobile learning, understanding the stages of its development in China and describing and analyzing its definition and characteristics and the mode of mobile learning. There are both advantages and disadvantages of mobile teaching and learning. It also describes the case of a campus course selection system based on a mobile terminal platform to show the characteristics of mobile learning.

1

Overview of Mobile Learning

1.1

Definition of Mobile Learning

Mobile learning is a way of learning in which mobile computing devices can help at any time and at any place (Alkhezzi and Al-Dousari 2016; Zidoun et al. 2016; Peng et al. 2009) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Mobile computing devices used for mobile learning must be able to effectively present content and provide two-way communication between teachers and students (Dye 2009). M-learning originated in the year 2000 at the University of California, Berkeley’s, “Mobile Education Research Project,” and it grew unexpectedly over the past 10 years. Desmond Keegan, an “International Distance Education” scientist, first introduced the concept of mobile learning into China in his academic report when he came to celebrate the 40th anniversary of the Shanghai TV University in 2000. Now, mobile learning has become an exciting topic in the field of education technology, attracting a large number of researchers into the field (Hennig 2016; Sun and Looi 2017). As in 2015, mobile learning does not have a clear, uniform definition, but many definitions from various angles describe it (Castro 2012; Kukulska-Hulme and Traxler 2005; Peng et al. 2009; MCCOMBS 2010). In this book, mobile learning is defined as learning through any devices from a wireless network connection or a distant learning source via mobile technologies (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Mobile teaching and learning have their own characteristics and advantages compared with the traditional face-to-face learning or online learning. But the current technology barriers and costs barriers are still obstacles for anytime and anywhere learning (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”).

1.2

Development Stages of Mobile Learning

China has a very different educational system (OECD 2016). In the next two decades in China, mobile learning will go through three stages: basic environmental construction, knowledge systematization construction, and learning services construction. The transition process among them is the iterative loop.

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During the first basic environment construction stage, it will form the basic environment adaptive to mobile learning with the development of wireless networks and resources and then, gradually, the network environment at national, regional, and organizational levels and a learning environment for thematic resources. This stage will last for 4–8 years, promoted mainly by mobile service providers and manufacturers. In the second (knowledge systematization construction stage), it will build a knowledge system based on the built mobile environment on a large scale, realizing the internalization and association between learning contents and compatibility and sharing the existing resources. The construction will be classified by and customized for different themes and needs. This stage will last for 5–10 years, promoted mainly by educational institutions and enterprises. In the third learning services (construction), it will be a new starting point for the socialization development of the comprehensive education process in China. Interactive environments for mobile learning processes will be recessive, and national learning service centers will be the social infrastructure, mobile learning will become a socialized form of education, and resource and systematic mergers and integration for resources will be conducted. This stage will last for 5–10 years, promoted mainly by the government.

2

Characteristics and Content of Mobile Learning

2.1

Characteristics of Mobile Learning

2.1.1 Form of Learning Mobility Students do not have to learn at a fixed time or place, but can learn at anytime and anywhere, and students and learning resources are mobile. Teachers can also upload the latest teaching materials from the Internet and update and modify teaching resources at libraries anywhere.

2.1.2 Implementation of Digital Learning and Networking Mobile learning has some characteristics with digital contents, mobile learning environment (network connections), interactive learning, and mobility of learning (Zhang 2015). In addition, most mobile learning models are based on wireless network systems with access to education through mobile devices, and the mobile learning is done online.

2.1.3 Interactive Learning Content Based on mobile computing technology and Internet technology namely, mobile Internet technology mobile learning technology has the characteristics of a two-way interaction (Alkhezzi and Al-Dousari 2016).

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2.1.4 High-Efficiency Study During the mobile learning process, the learning needs are first proposed by the student, and then questions are taken in the search for knowledge. Mobile communication devices may show the students multimedia learning resources. Students can also be real-time and network learning companions to explore issues, exchange ideas, and thus improve learning efficiency. 2.1.5 Personalized Learning Via the mobile learning mode, students arrange the time and place of learning according to their needs and at their own paces and have a free choice of learning content. 2.1.6 Correlation Learning Environment With features such as unique mobility, portability, and connectivity, mobile learning can access and respond to a particular location, environment, and time with corresponding real or virtual data, which can quickly and easily create personalized and diversified mobile scenarios. 2.1.7 Extensive Range of Education With the development of mobile communication technology, high-performance mobile devices emerge (e.g., smartphones), and these devices support faster downloading, greater capacity, and better computing capability. Students can use their mobile devices to listen to or watch from afar in real time, and they can communicate and have discussions with other students and teachers. This greatly broadens the range of the education, promoting lifelong learning and the educational process of democratization. 2.1.8 Assisted Learning Function Mobile learning is just a traditional classroom extension and expansion of education and cannot replace existing formal education; it can only be a supplement to conventional education (Zhang 2015; Rennie and Morrison 2012). 2.1.9 Learning in Smaller Time Slots Mobile learning has another characteristic. It usually takes less time than learning via personal computer or face-to-face. Students can use smaller time slots (such as waiting for bus or waiting for lunch) to learn. Therefore, the designed learning units should suit the learners to study in smaller time slots (such as 5–10 min). 2.1.10 The Goal of Universal Education The emergence and spread of smart mobile communication terminals enables people with a mobile communication terminal to use mobile learning and exchange, even in areas of traffic that can also be convenient to learn through the terminal. At the same time, learning resources according to the design and development of various objects can be quickly and easily obtained and updated, making the mobile learning mode universal.

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The Mobile Learning Mode of Learning

The mobile learning mode here means the learning curriculum designed for mobile learning in a higher educational institution. The major mobile learning application model in Beijing Union University is divided into the following categories.

2.2.1

Based on SMS (Short Messaging Service)/MMS (Multimedia Messaging Service) Mobile Learning Mode (Push-Based Mobile Learning Mode) Through mobile phones, students can send information to the Internet Teaching Server. The server can analyze the information it received and then send it back to the students. Using this mode of mobile learning, teaching activities can be achieved: teaching notices and relevant content release, students’ feedback on learning and teachers (teacher-student interaction), and online evaluation and information inquiries. Based on SMS and MMS, the mobile learning mode extends the media to expand the type of information techniques available, which can set voice, text, pictures, or animation to the maximum capacity of a single 100 kb message. Another low rate, highly convenient, and interactive characteristic, the phone is not required online at any time. Information management processes can be completed replying on the Internet, allowing interpersonal interaction for teachers and students. But the data communication is intermittent and not real time. It is difficult to achieve multimedia resources’ browsing and display. It is mostly image-based, relatively simple information texts. 2.2.2

Based on Wireless Network Connection Online Browsing Mobile Learning Mode Based on a wireless network connection online browsing mobile learning application model, students can use a wireless terminal, after the telecommunication gateway accesses the Internet, accesses the teaching server, and browses, queries, and has real-time interaction, similar to that of ordinary Internet users. Students and teachers can access teaching and learning resources via a mobile phone or other handheld devices at anytime and anywhere. Based on the wireless network connection to browse mobile learning application mode, students can get rid of the limitations of time and place, and necessary learning resources on the Internet can be searched, browsed, and downloaded. Moreover, the downloaded information can be stored in the mobile learning terminal for a long time. Then off-line students can also learn. The mobile learning application mode is suitable for all mobile students; it has the following forms of learning: 1. Based on WAP Web Mobile Learning This learning mode is the way to use mobile terminals to browse WAP Web for teaching information. Based on the traditional Internet http site protocol to access to various sites through computer browsers, a WAP site can be accessed through the mobile terminal browser. The mode can be set to include three functional modules,

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such as students, teachers, and administrators, remote network computers for secondary education to carry out registration, enrolment, teaching, assignments, answering questions, educational management, learning resources management, or user information management and other functional activities. 2. Based on Mobile Blog This mode is the way to use a mobile network platform, via e-mail, MMS, SMS, etc., which will be posted to the network through the WAP information logon, and can be edited at any time, viewing, logging, and information sharing for yourself or others, such as electronic lesson plans, electronic dictionaries, electronic answering, and Web courseware. It has immediacy, interactivity, openness, and personalization features. 3. Online Reading This mode is a way the student can read online and download either at professional terminals, by phone, or an e-reader. 4. Based on Streaming Media Mobile Learning Mode Streaming media refers to the application of streaming media files via the wireless network transmission technology (such as audio, video, and animation). There are two main forms: broadcast, and on-demand streaming media. Like traditional broadcasting, streaming media is broadcast to radio programs according to a fixed schedule. Using mobile phones and other mobile devices, students can download information from the Web server side edge to watch and listen without large storage space for entire stream media files, achieving even transfer and a real-time view. The on-demand streaming form is more flexible, and students can follow their wants according to the needs of educational programs on demand in the mobile terminal by just needing to build a streaming media repository to satisfy the search query. It features a large propagation range and receives real-time information, making an interactive, reusable media repository more perfect. 5. Based on the Podcast Mobile Learning Mode Based on the mobile learning mode, podcast students can use mobile phones to play audio or video files. Teachers use tools such as voice recorders or cameras in the classroom to record the teaching process and materials. The late editor generates the corresponding sound or video file, publishing it on the Web site for students to download. Students can use smartphones and other mobile tools to download these files and then study. With the continuous development of mobile communication technology, especially the improvement of 3G communication technology, network transmission speed continues to improve, and the phones become constantly more intelligent; the increase in the screen resolution becomes higher and higher, with

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these conditions based on podcast mobile learning creativity in favorable conditions. The mobile-based podcast student self-learning mode is suitable for studying teachers’ lectures. 6. Based on Virtual Reality Mobile Learning Mode In this mode, the entire mobile learning process is based on a virtual reality peripheral network environment or fixed-end mobile learning data transmission via a wireless communication network as well as the realization of mobile virtual reality interaction. Each student using mobile devices connects through a virtual reality port and virtual networks; each learner determines the forms of learning (self-learning, collaborative learning, etc.) through the role, the creation of learning scenarios, and then this virtual interactive scene. After the compressed data is transmitted via the wireless communication network to the mobile learning terminal end, students can download virtual scenes, and the use of certain interactive tools is completed, and there is interaction with other students, including visual, auditory, tactile, and other forms. In addition, various mobile learning terminals and fixed terminals and mobile resources can exchange data in order to achieve the virtual reality peripheral network environment and cooperation. 7. Based on the Expert System for Mobile Learning Mode Expert systems based on mobile learning systems use SOA (service-oriented architecture) and Web services as the interaction between the mobile terminal application and system data interface; in this way they establish a series of interactive expert system Web service client applications; direct students can download and install the expert system based on mobile learning system client software. They can operate Windows programs interacting with the expert system to complete the service. Students and interactive information systems are no longer required as an SMS-based mobile learning mode as the information manually coding but sending directly to the expert system. The expert system need not parse the information directly after receiving information of the mobile interactive interaction of students and returning the result to complete the interaction and the mobile system.

2.2.3

Based on the Campus Wireless Network Quasi-Mobile Learning Mode Mobile learning is the potential way that can be implemented in the local area (such as a campus, a building, an outdoor learning area, or a classroom). Students and teachers can use laptops to connect to the campus network via the campus wireless network access points. Learning can take place via wireless Internet, such as downloading learning content and sending the job contents to teachers. Teachers can provide guidance for students through the campus wireless network. Learning and teaching can take place by means of the campus network for learning and teaching evaluation as well. As an extension of the traditional

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classroom, the mobile learning will be individualized distance learning and the most promising mode.

2.2.4

Based on Mobile Devices, Books, Audio, Video, and Game Learning Mode Mobile devices basically support the txt format by e-book functions, such as prior teaching content downloaded via a computer to a mobile terminal (mobile phones, computers, machine learning, etc.); in this way, students can read while on the go. Audio, video, and other files can be downloaded via a computer to a mobile terminal, although some mobile terminals need to conduct a file format conversion. Downloadable audio can be used to practice listening and learning English pronunciation; video can create real situations to stimulate the students’ interest in learning, so that they obtain accurate knowledge of the scene rather than by traditional “rote” learning. However, this mobile learning mode is only suitable for self-study. On the one hand, learning can be conducted via downloading good resources, although resources are limited; on the other, the lack of this kind of functional interaction can help students obtain feedback in the learning process, but teachers cannot assess the students’ learning. However, this approach can be combined with other online mobile learning modes, and the outcome will be better.

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Application Prospect Analyses

3.1

Core Strengths

First, mobile learning in Beijing Union University can be conducted everywhere and at any time. This unique advantage is unmatched by other learning methods and greatly meets “general line” learning needs. It also establishes the important position of mobile learning in the future. Second, learning can be conducted in short time fragments. Mobile learning, with its unique characteristics of fragments, provides convenience for the students so that they can take advantage of small amounts of time to master relatively complete chunks of knowledge, in the face of seemingly haphazard knowledge fragments, after a long day of intake and accumulation points eventually enabling the completion of a jigsaw puzzle of knowledge. Third, it meets individual learning needs. Interactive mobile learning can achieve a two-way flow of information in a real-time manner, helping to train the student’s ability to communicate, inspire passion for the subject, develop the student’s personality, and help improve the students’ academic performance and confidence. Fourth, eliminate the psychological burden. From a psychological point of view, for those with introverted personalities or shyness, mobile learning can compensate for some of the traditional classroom and learning embarrassment of face-to-face encounters, making it easy to learn and exchange ideas and so on.

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Limitations Exist

3.2.1 Attention Control How to focus the students’ attention in mobile learning is a problem still to be solved. Because mobile learning resources are “flaky,” the learning environment and the addition of the noisy outdoor complex, there are many factors that interfere with learners that could cause the student not to concentrate and cannot fully enter the state of learning necessary to maintain long-term attention. In addition, mobile devices are generally small the size of the display screen and these factors also affect students’ attention. 3.2.2 Restriction Technologies Mobile terminals can transfer sound or image when teachers teach to the students, but can also provide online troubleshooting or online exams. However, when the mobile terminal device has poor network connectivity, network communication costs for expensive and complex man-machine interfaces will cause poor-quality video transmission in which the network is slow for browsing multimedia learning materials and results are unsatisfactory. Students in the normal learning process were interrupted, reducing the effect for students with learning difficulties. 3.2.3 Network Tariff Issues Currently, the focus on mobile learning in the media and the research community is not great, like the attention of educators. The reason for this is the high network tariffs. In general, students can afford a cell phone or PDA (personal digital assistant) and other mobile devices, but if one mentions the use of these devices online, it scares them away. Only if the network tariffs for mobile learning applications are lowered can there be. 3.2.4 Learning Resources Issues Students with mobile devices can move from one place to another. The designed learning resources or materials should also suit the requirements of mobile learning (mobility). The knowledge of students and teachers must be passed again finishing, processing, and refining, in the form of a complete system of moving students. In addition, mobile learning has resource scarcity and poor interactive courseware. Learning resources are scarce, the content is simple, and interactive courseware is poor, which directly affects the student’s motivation. 3.2.5 Limit for Mobile Devices Because of the lack of acceptance of mobile devices in terms of information and software, it has to limit the amount of information transmitted, thus affecting the effective interaction between teachers and students.

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Situation Analysis

3.3.1 Domestic In China, mobile education is still at a low-level stage. It has not been accepted as a real education mode in the university or as the pilot in the pilot schools. Conventional schools are still the traditional teaching mode. However, there have been some schools or educational institutions that made attempts at mobile learning. In 2007, Shanghai TV University made a great breakthrough in mobile learning, taking the first steps to real “mobile interactive teaching.” On the basis of the pilot project that year, the Foreign Language Department at Shanghai TV University and Lantop Technologies Co., Ltd. jointly developed a “Mobile English Learning System” that automatically sends English tests via SMS to students via a daily test and sends the answers and detailed notes the following day. 3.3.2 Foreign Mobile learning has already reached quite a high degree in developing foreign countries (Alhassan 2016; Alkhezzi and Al-Dousari 2016; Kabugo et al. 2016; Zidoun et al. 2016; Sun et al. 2016). It is a necessary teaching pattern in colleges and universities of some of the countries in Europe and America (Hennig 2016; Itu 2016). A lot of supporting software and hardware device has been developed in parallel (Alkhezzi and Al-Dousari 2016; Becker et al. 2016; Yousafzai et al. 2016).

4

Case Analysis

The cases provided in this section were selected from the Beijing Union University mobile learning modes. The designed mobile learning systems provide all the enrolled students an opportunity to learning through their mobile devices and communicate with teachers/course designers instantly. The functions and advantages are discussed in this section.

4.1

Case Introduction: Campus Course Selection System Based on Mobile Terminal Platform in Beijing Union University

4.1.1 Campus Course Selection System Status Most of the schools are now using the browser/server (B/S) mode, which is more convenient than the initial artificial course management. It no longer needs a lot of manpower, course selection for students is not crowded (too many students’ accessing at the same time can make the sever response very slow or sometimes even “frozen”) anymore, and it is not possible for students to delay the normal teaching task due to course selection. The browser/server (by moving most materials and computing tasks to server part, it reduces the working load on clients’ sides) mode of course selection only needs a browser to access the network. As long as the registration for the server can provide course selection,

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student status management, test scores, graduation design, and other business modules, students can use the function of the corresponding module management in the Windows client browser. Along with the development of the mobile Internet, this B/S mode course selection system has exposed many inadequacies; for example, for course selection operation, network access to the computer is necessary in order to get the notification about the courses’ setting and other information. Students who don’t often surf the Internet may miss a lot of useful information, and these defects can be addressed by the mobile terminal. With today’s popular smartphones, it can be used by a mobile terminal system, which will be accepted by students as new things, and at the same time will usher in a new trend. Compared with domestic development, universities’ software in foreign countries for teaching and scientific research are either early or mature because they generally have larger and more stable technical teams to provide service and technical support. The initial courses at universities in China are selected via the artificial mode, and now it is the online course selection system. With the great development of networks, course selection systems for mobile devices will open the new market demand.

4.1.2

The Development Prospects of a Mobile Terminal Course Selection System For most users, a course selection system is a simple, personal information query system, and students often don’t even know what they themselves are interested in or which courses are useful. This system is more practical and can play a guiding role in course selection. We believe that in the quickly developing era of science and technology, the system can provide users with a simple and practical course selection setting. Facing an enrolment expansion policy situation year by year, greater learning technology is a huge threat to helping students select courses effectively, so the informational course selection system seems to be the best solution to this problem. In general, the subfoundation determines the superstructure – a reasonably designed powerful course selection system as the basis of a school building, which will undoubtedly promote the overall development of the school. A good-quality university on a high level is the main driver of the development of the economy and people’s livelihoods. As we know, education is the lifeline of a country, so its development prospects and market demand are good. A campus course selection system, for course selection and a related teaching affairs management platform, also has some disadvantages such as the lack of resources and less emphasis. Based on the domestic and foreign university course selection system situation, combined with China’s education system, introducing the Taobao model of innovative ideas, the course selection mode from “filter” to “select” has been proposed. This mode includes course introduction, course evaluation, and a list of popular courses striving to give students a more convenient selection system and solving the current situation of students registering blindly, which reflects on them in personalized information management.

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4.1.3 Overview of the Software With the continuing development of the Internet and the reforms in higher education and teaching, the university’s course selection mode has been a shift from the traditional, paper-based way to online education. In the future, with the increasing popularity of mobile devices such as smartphones, mobile course selection will be another way to select courses following the Internet course. There is a greater selection of software for online courses, while special mobile course selection software is relatively less. The course selection system based on mobile terminal platforms is a supplement to the online course selection system based on the Web. The client of the system runs on the most popular smartphone operating system: Androids. Through a GPRS (general packet radio service) or WLAN (wireless local area network) and other wireless data transmission platforms, it has broken the limitation of geography, time, and traditional transmission means, establishing mobile terminal platforms for course selection for students in our school during intensive selection time, understanding the course information and querying the results, as well as selecting courses in a real-time, rapid, and accurate way. This software is intended to provide a fast and convenient course selection mode for masses of students, teachers, and educational administration personnel at any time and any place. Through preliminary study of the Android software development technology, the Java Servlet programming technology, and the analysis and research of the existing course system, combined with the characteristics of the mobile Internet, the main functions of the mobile course selection system have been summarized. The integrated plan, design, and performance can be conducted by using the method of information system development and other technological means. The system covers the user login, course selection, dropping the course, course selection information query, and other basic functions. Moreover, the system is divided into system login, course selection information, course selection, dropping the course, course selected query, etc. During the design and implementation of the mobile course selection system, the C/S architecture and http communication protocol have been adopted; the server can interact with the database through JDBC, and a mobile phone can receive the data from the Web server in the form of a stream.

4.2

The Introduction of Software Development Environment, Design and Implementation, and Related Technologies

4.2.1 Development Environment Application platform: Android platform Hardware environment: Millet 1 s phone (screen resolution: 854  480 pixels) Software environment: Eclipse Programming language: Java

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Design and Implementation

Overall Function Description Overall Implementation

This software using the related technologies manages the data of students, teachers, and educational administration personnel involved in course selection and provides a convenient way of course selection anytime and anywhere. The software implementation broke the limitation of the geographical, time, and traditional transmission means. It established a course selection system at the mobile terminal platform for the students to understand the course selection information, query course selection results, and select the courses in a real-time, rapid, and accurate way during concentrated selection time in the school. The course selection system based on mobile terminal platform includes notification management subsystems, user management subsystems, and course management subsystems. The overall functional analysis diagram is shown in Fig. 1:

System Permission

1. In the notification module, the system uses third-party services (the services are provided by another outsourcing company). The third-party service aurora push – pushes notification, which can only be sent by the educational administration personnel. 2. Three landing sites can be respectively logged into by a qualified person. 3. Only educational administration personnel can add or delete courses using this setting in order to prevent data loss or modification, so that data is protected.

Detailed Module Design Detailed Design Review

The task of a detailed design before programming is to analyze the logical management of algorithms, design all necessary processes in detail, and give clear expression to make it a coded basis. Fig. 1 Functional analysis of a course selection system

Course selection system basing on mobile terminal platform

Notification management subsystem

User management subsystem

Course management subsystem

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The Detailed Design of Software

1. General flow chart as shown in Fig. 2. The user management subsystem1 includes student information management module, teacher information management module, and academic staff management module. 2. The user management subsystem2 includes student information management module, teacher information management module, and educational administration personnel information management module, as shown in Fig. 3. The student information management module includes four functions: searching for courses, selecting courses, canceling courses. and evaluating courses, as shown in Fig. 4. The flow chart as shown in Fig. 5. Teacher information management module: Teachers can query the students’ information taught by them, as shown in Fig. 6. The flow chart as shown in Fig. 7, Educational administration personnel information management module, shown in Fig. 8. 3. The notification management subsystem includes the notification information management module and notification update module, as shown in Fig. 9: The notification information management module and notification update module are pushed notifications by educational administration personnel through the third-party service aurora push and send real-time notification on the welcome interface before the login system. Course selection information includes selection time, selective requirement, selection query result time, etc. 4. Course management subsystem includes course information management module and popular course information management module, as shown in Fig. 10: The popular course information management module is according to the notification interface. Students, teachers, and educational administration personnel can see the popular course list, and it will play a reference role for course selection and arrangement.

User management subsystem

student information management module

teacher information management module

Fig. 2 Analysis of a user management subsystem 1

academic staff information management module

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User management subsystem

Student information management module

Teacher information management module

Educational administration personnel information management module

Fig. 3 Analysis of a user management subsystem 2 Student information management module

The course of query

The course of selection

The course of cancellation

The course of evaluation

Fig. 4 Analysis of student information management module

Academic Staff Information Management module

The course of selection

The course of addition

The course of cancellation

Fig. 5 Analysis of academic staff information management module Fig. 6 Analysis of teacher information management module

Teacher Information Management module

Query the information of students

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Course management subsystem

popular course information management module

course information management module

Fig. 7 Analysis of course management subsystem

Fig. 8 Analysis of educational administration personnel information management module

Educational administration personnel information management module

The course of selection

The course of addition

Fig. 9 Analysis of notification management subsystem

Notification management subsystem

The notification of information management module

Fig. 10 Analysis figure of course management subsystem

The course of cancellation

The notification of update module

Course management subsystem

Course information management module

Popular course information management module

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Technical Introduction

Student Module After students log onto the main interface, the client side will retrieve the various classes of the selected course from the server, and the user will get this course when he clicks the corresponding item. Course Selection

Step 1: Get course information from the server The elective class is linked to the activity class. The students can obtain data from a server thread on the creating method. There is a thread to send the request to the server via Apache HttpClient Get way, after the Web server receives a request using the corresponding SQL statement MySQL database course traversing table and obtains return data to the client side. Step 2: The course information is displayed in the client side The returned data are stored in key-value pairs JSON data. The data are displayed in Listview in a specific form at the client side, using SimpleAdapter. Step 3: The Listview login is a corresponding click event monitor, and the client side will apply the server for the course information and display it when the user clicks the corresponding item. The client side will call up the relevant thread to complete the course when the user clicks the submit button. The interaction mainly sends the selected course information to the server through a request, and the server side should determine firstly whether the course margin is zero or not. The course selection will fail if it is zero; however, if it is not zero, the database will have one less than the number of courses and insert the data and user information into the table through SQL statements. After completing a series of operations, the server side will return a successful result. Withdrawal of Candidature

The client side will send a request to the server when the user clicks the “back” button. The server in the current elective course information table returns values selected by the client side user, and the returned data will display in the Listview control after the client side receives it. Meanwhile, the server side will delete the corresponding course selection information after the client side monitoring that the user clicks on the corresponding course and sends a request to the server. Teacher Module View Selected Student Information

After login, teachers can click to view current selected students’ information. The procedure for this feature is the client side sends the current user’s login account to the server with the http request. Then the server side extracts the students’ accounts from the received one and uses the connection to the database query to obtain student information and return it to the client.

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Adding Course Information

In the adding interface, teachers fill in the relevant information and click the “add” button on the client side, which will contain the information in the http request, adding to the database after the server receiving data in the course table. There is a “cou_audit” item on the list if the course table is empty (refers to an item that is not checked by administrator). Academic Administrator Module View Course

The principle of viewing the course is a feature in accordance with the course selection. Audit Courses

This interface lists all added but not audited courses. The administrator clicks on the corresponding course, and the user obtains the related prompt displayed in “dialog.” If the administrator chooses to audit by the client side, he will deal with the results sent to the server. If the audit is passed, the server will set the cou_check to “0,” and if the audit is not passed, this deletes the curriculum and elective courses in the table. Delete Courses

The server side will delete the syllabus and corresponding courses when it receives the request after the client side, obtaining all courses and the administrator selecting the courses needed to be deleted. List of Courses The database that have all students’ records will reduce to one after a student selected his/her courses. When the number in the accommodating database is reduced to zero, the course selection is finished. The current time stored in the table is then saved in the system. The server lists the courses from all the completed courses and returns to the client.

4.3

The Introduction to the Software’s Functions

Figure 11 is the notice page, which will send a push notification by using the thirdparty service aurora and send a notice on the welcome page. Students can start the course selection when they find the notification on the welcome interface. If not, the courses are unable to be selected, which can meanwhile avoid trouble and flaws in the dissemination of information resulting from the process. Figure 12 is the login selection page. There are three types of users in the course selection system students, teachers, and educational administration personnel. In order to facilitate various users’ use of the system, there are various buttons in the system. The setting of the list of popular courses is to provide selective views for students and to let teachers know students’ enrolment and interest situation.

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Fig. 11 The notice page

Fig. 12 The login selection page

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Figure 13 is the login page. The user can log in or quit his account on this page. As the system interacts with the server using the school and the school database holds all the user’s information, users can use their student number (job number) and password to log into the system to operate it. The users can log into the system when their names and passwords are both correct otherwise there will be a prompt notice of failing pass. Figure 14 is the course list page; it shows the number of students selected for this program on this interface. Figure 15 is the main page of students’ features. A student user can classify the course selection, query the course or its cancelation, and assess courses for operations on this page. The system is classified according to school selective status; the student user can clearly show the elective classes and click on the category after the “unselected” choice of courses in the selected category while avoiding all the users choosing the same type of course, which can cause system paralysis and allow users to choose their favorite courses real time. The selected course can be evaluated after being audited. Figure 16 shows courses for the students’ cancelation function page. The student user clicks the cancelation button after entering the page and then cancels the previously chosen course. Figure 17 is a student course evaluation function page with which students can evaluate the course after auditing it in order to provide advice for future students and avoid blind course selection. Figure 18 is the main page of educational management functions, which includes three functions: viewing the curriculum, adding courses, and deleting courses. Fig. 13 The logon page

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Fig. 14 The course list page

Fig. 15 The main students’ function page

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Fig. 17 The main page for evaluating courses to students

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Fig. 18 The page for educational facility managements’ functions

Educational administration personnel can take the corresponding operation after clicking the button. View course means to view selective courses, course information including the course category, course name, teacher information, and the time and place for the class. Adding courses is in line with the needs of teachers and students and adds some courses temporarily, which will complement the full course information; meanwhile, deleting courses is deleting those that cannot properly begin the program for various reasons. Figure 19 is a course display page. The educational administration personnel will enter the page when he clicks the “view course” button. This page shows the user all elective courses, including the course name, course category, teacher information, and time and place for class, all of which are convenient for the educational administration personnel to modify the course. Figure 20 is the page for adding courses. The educational administration personnel will enter the page when he clicks the “add course” button. They can add course names, course categories, teacher information, class times, and the number of students, based on the needs of teachers, and click on the “submit” button to save the information on the course. Figure 21 is the page for deleting courses to educational administration personnel. After entering the program page, the course can be deleted by clicking “delete.” Figure 22 is a teacher function page. There is only one function for teachers to query the information in the application. Teachers can view the students’ information about who selected his course.

544 Fig. 19 The page for checking courses by the educational administration personnel

Fig. 20 The page for adding courses by the educational administration personnel

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Fig. 21 The page for deleting courses to educational facility managements

Fig. 22 The page for teachers’ functions

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4.4

The Analysis of Difficulties and Characteristics

4.4.1

Difficulty Analysis

Module Integration The system provides different services for different users. This application consists of three modules: 1. Students can select the courses and cancel or query selected courses. 2. Teachers can view the students’ information, e.g., who selected their courses, in order to facilitate recording and understanding students’ information. 3. Educational administration personnel can view the course, making modifications and adjustments according to the teachers’ requests in order to do the overall planning. Networking Achievement The difficulty lies in the interaction of applications and servers, as well as the process of using the database. The educational administration personnel will modify the data directly in the process of adding and deleting courses. Meanwhile, it needs to keep the consistency and integrity of the data viewed by students and teachers. 1. After allocated the IP, using Get and Post HttpClient way, Android client program sends a requrest to the server. The server receives a client request and then requires the Tomcat Web project to respond. Using a combination of Tomcat and MySQL Web project technologies can make the corresponding operations on the database faster when responding to the server’s requests. 2. MySQL database on Chinese identification: the MySQL database default encoding form is Latin1, so this encoding cannot identify Chinese easily and lead the garbled condition of MySQL data. After modifying data, access to the MySQL database encoding is UTF-8, so it is possible to solve the problem of garbled Chinese.

4.4.2 Characteristic Analysis 1. More convenient. The users of the course selection system based on a mobile terminal platform can login to the system and select courses whether on the bus, at the mall, or at any place without computers, as long as the client carries an Android phone. It breaks the limitation of the geographical, time, and traditional transmission means. 2. More humanized. It issues notices on the welcome interface before the login system and avoids the trouble of information dissemination layer upon layer and information cracks caused by the process. 3. Versatility. The system provides the user with course descriptions, course evaluation, and a popular course list to give advice about course selection to the students. It can solve the present situation of blind selection, reflecting personalized management of courses for college students in the age of information.

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4. Enhance the user experience. It provides a simple interface, but meanwhile has a different page design in the UI design, and users can change the theme according to their interests. 5. Easier. The characteristics of the software are simple and direct, so that the user can save time on course selection and query. And the software can be classified by courses according to the school course requirements and make it easier for users to find their favorite courses.

5

Conclusion

Mobile technology has changed the way of teaching and learning (Doug et al. 2009; Zhang 2015). This chapter introduced the mobile learning platform designed and developed for students in Beijing Union University. The empirical study supports that mobile learning is more convenient, humanized, versatile, and easier to use and has enhanced the user experience. Mobile technologies and new devices have been released since 2015, which changed the mobile learning market dramatically. VR, AR, robotic technology, and wearable technology have been adopted in teaching and learning in many countries (Becker et al. 2016; Ahn and Shin 2013; Hennig 2016; Yousafzai et al. 2016; Alkhezzi and Al-Dousari 2016; Halpern 2007) (see also ▶ Chap. 79, “VR and AR for Future Education”). Students are different today, and they are facing different requirements and challenges tomorrow (Hunt and Zhou 2017; Dunbar 2017). Educators and schools should also make the changes to meet the new market requirements. The future of education is based on all the research, development, and improvement we have today with ever educator, designer, developer, policy maker, and student.

6

Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ VR and AR for Future Education

References Ahn, D., and D.-H. Shin. 2013. Is the social use of media for seeking connectedness or for avoiding social isolation? Mechanisms underlying media use and subjective well-being. Computers in Human Behavior 29: 2453–2462. Alhassan, R. 2016. Mobile learning as a method of ubiquitous learning: Students’ attitudes, readiness, and possible barriers to implementation in higher education. Journal of Education and Learning 5: 176–189. Alkhezzi, F., and W. Al-Dousari. 2016. The impact of mobile learning on ESP learners’ performance. The Journal of Educators Online 13: 73–101. Becker, A.S., A. Freeman, C. Giesinger Hall, M. Cummins, and B. Yuhnke. 2016. NMC/CoSN horizon report: 2016 K-12 edition. Austin: The New Media Consortium.

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Castro, J.C. 2012. Learning and teaching art: Through social media. Studies in Art Education 53: 152–169. Doug, V., K. David, and K. Ron Chi-Wai. 2009. Does using mobile device applications lead to learning? Journal of Interactive Learning Research 20: 469–485. Dunbar, F. 2017. 50 little things teachers, parents, and others can do to improve education. Accessed 28 Feb 2017. Dye, Aleksander. 2009. How can web 2.0 be used to improve cooperation between eLearners? A dissertation submitted in partial fulfilment of the requirement for the degree of Master of Science. http://www.dye.no/articles/how_can_web-2-0_be_used_to_improve_cooperation_ between_elearners.pdf Halpern, P. 2007. What science ever done for us: What the Simpsons can teach us about physics, robots, life, and the universe. Hoboken: Wiley. Hennig, N. 2016. Library technology reports. Chicago: American Library Association. Hunt, E., and N. Zhou 2017. What does the future hold for students starting university today? The Guardian. ITU. 2016. Measuring the information society report. Geneva: ITU. Kabugo, D., P.B. Muyingda, F.M. Masagazi, M. Mugagga, and M.B. Mulumba. 2016. Tracking students’ eye-movements when reading learning objects on mobile phones: A discourse analysis of Luganda language teacher-trainees’ reflective observations. Journal of Learning for Development 3: 51–65. Kukulska-Hulme, A., and J. Traxler. 2005. Mobile learning a handbook for educators and trainers. London/New York: Routledge. McCombs, S.W. 2010. Mobile learning: An analysis of student preferences and perceptions surrounding podcasting. Doctor Dissertation, University of Houston. OECD. 2016. Education in China a snapshot. Paris: OECD Publishing. Peng, H., Y.J. Su, C. Chou, and C.C. Tsai. 2009. Ubiquitous knowledge construction: Mobile learning re-defined and a conceptual framework. Innovations in Education and Teaching International 46: 171–183. Rennie, F., and T. Morrison. 2012. E-learning and social networking handbook: Resources for higher education. New York: Routledge. Sun, D., and C.K. Looi. 2017. Focusing a mobile science learning process: Difference in activity participation. Research and Practice in Technology Enhanced Learning 12 (3). Sun, D., C.K. Looi, L. Wu, and W. Xie. 2016. The innovative immersion of mobile learning into a science curriculum in Singapore: An exploratory study. Research in Science Education 46: 547–573. Yousafzai, A., C. Chang, A. Gani, and R.M. Noor. 2016. Multimedia augmented m-learning: Issues, trends and open challenges. International Journal of Information Management 36: 784–792. Zhang, Y. 2015. Characteristics of mobile teaching and learning. In Handbook of mobile teaching and learning, ed. Y. Zhang. Heidelberg: Springer. Zidoun, Y., F.E. Arroum, M. Talea, and R. Dehbi. 2016. Students’ perception about mobile learning in Morocco: Survey analysis. International Journal of Interactive Mobile Technologies 10: 80.

Accessibility Challenges in Mobile Learning

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Why Is Accessibility Important? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Devices and Interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 BYOD: Bring Your Own Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Device Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Text Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Content Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Touch Screens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Voice Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Study Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Collaborative Tasks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Text-Based Collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Multimedia Collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile learning opens up a wide variety of opportunities to deliver learning in new and exciting ways (▶ Chap. 29, “Adoption of Mobile Technology in Higher Education: An Introduction”). Making learning accessible is a challenge for educators regardless of the medium or platform with which they are working. This chapter looks at some of the accessibility challenges which educators face when moving to mobile delivery.

L. Robson (*) The Open University, Milton Keynes, UK e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_39

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In some situations the use of mobile delivery opens up the education experience to being far more accessible to a wide range of learners than more traditional delivery style. However, it is frequently seen that while adopting mobile delivery is beneficial to one group of learners, it may be problematic for another. This chapter briefly considers what accessibility means and why it is important in the wider context, before going on to consider the types of challenges which educational developers and teachers should be aware of when designing resources in order to maximize accessibility for students with disabilities. It does not attempt to address every single accessibility issue and potential adjustment but to encourage the reader to consider a range of issues their learners may face and to raise awareness of how particular delivery choices may affect potential learner engagement. There is also an acknowledgment that it may not be possible to cater to all learners using a single delivery solution. Where there is conflict between the needs of different groups, in terms of usability, it may be appropriate to offer multiple ways for students to engage with the learning, instead of attempting to make every activity fully accessible.

1

Introduction

Mobile technologies have been adopted by users worldwide at an enormous rate. In 2017 it is estimated that more than half the world’s population use a smartphone, and 50% of internet traffic comes from mobile phones (We Are Social 2017). Consequently, it is not surprising that educators have identified this as an opportunity to reach new audiences and to deliver educational material in new and enhanced ways. The adoption of mobile technologies within education has opened up many possibilities for engaging learners in a wide range of activities. However, at the same time as opening up new possibilities for engagement, the adoption of mobile technologies in learning also has the potential to exclude some individuals, particularly where developers have not considered a range of accessibility issues which particular learners may face. Before discussing accessibility challenges in mobile learning, some thought is needed regarding what the term accessibility means and why it matters. In its widest sense, accessibility could be defined as the extent to which a service or product is available to as wide a range of individuals as possible. This could include consideration of variation in a wide range of different factors, such as educational setting, cultural background, socioeconomic status, etc. More commonly, the term is used with a much narrower focus, to refer to designing products or services in order for them to be used by individuals with a disability. Although this chapter will focus on supporting students with disabilities, it is important for educational developers to be aware of the other access issues which may affect their students. Presumably, those developers harnessing mobile learning would have considered issues around bandwidth and connection reliability (▶ Chap. 13, “Design Considerations for Mobile Learning”), along with device

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availability and some consideration of cost, whether that is borne by the individual learner or the educational provider. Developers should also be encouraged to consider the characteristics of their target student group(s) and of any individuals which may be knowingly or inadvertently excluded. Pike (2010) studied the increasing digital divide for higher education (HE) students in prison and highlighted the increasing restrictions on accessible study programs for students due to increased uptake of Internet-based teaching. While it might be accepted that only a limited number of educational opportunities can be afforded to students in prison, the narrowing of accessible curriculum for this group may impact on the effectiveness of rehabilitation and have a negative impact on society. While the majority of educational developers will not be engaged in the development for the prison context, considering a broad range of environments can help the developer to think more creatively about the impact design decisions may have on accessibility. Historically, women have been disadvantaged in accessing the technology to be able to access online education. In the developed world, children are usually given priority access to Internet-enabled devices in order to support them in completing their school homework. Prior to mobile devices being widely available, men often got second priority regarding access to computers and the Internet, and women would be at the back of the queue. The increase of relatively cheap mobile devices has addressed this inequality to some extent, but women’s access still lags behind that of men. In many Western households, there are enough Internet-enabled devices available for the whole family to be accessing simultaneously. In 2017, reporting at the continent level, Internet usage in the Americas was reported to be higher among women than men, but in all other areas of the world, there was a 4–8% lower proportion of women with Internet access than men (Statista 2017). More detailed data will show variation at more local levels, be that by country, county, or region. Data from autumn 2017 shows mobile Internet access penetration over 75% for the United States, Spain, the United Kingdom, the Netherlands, Saudi Arabia, and the United Arab Emirates, while it is only 50% in China and 32% in India (Statista 2017). There is evidence that women in minority communities of the developed world still lag behind men in their digital literacy (Tolbert et al. 2007). In poor and rural areas of the world, there is still a significant gender-based digital divide (Elnaggar 2008; Al-Rababah and Abu-Shanab 2010), with women having much lower rates of access to the Internet and potential learning technologies. Table 1 shows the proportion of women and men with mobile Internet access in different countries. There is also a cultural dimension to accessibility of various educational opportunities. Some disciplines are seen as masculine and others as feminine which makes them more or less attractive to males and females accordingly. For individual learners, they may be attracted to a particular subject but feel excluded due to gender stereotyping of that discipline. Increasingly there is a concern about the educational provision for displaced peoples and refugees who are often in desperate need of educational opportunity, to support building new lives in new locations with limited resources. While not

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Table 1 Percentage of women and men with mobile Internet access in a selection of developing and developed countries in 2015. (Data adapted from Statista 2017) Country Ethiopia Uganda Pakistan Burkina Faso India Ukraine Japan France Germany United Kingdom

Women with mobile Internet access (%) 4 6 9 12 17 56 64 71 81 85

Men with mobile Internet access (%) 12 16 22 23 27 64 75 80 89 91

wanting to stifle innovation, it is important that developers are aware of the consequences of their decisions. Educators should work toward being inclusive whenever possible and be aware of the limitations where it is not possible. This preamble has considered some of the issues of accessibility in its widest definition. However, in many educational institutions, the term accessibility is used predominantly connected to issues of disability, and this is the area that we will now focus on. There are many different definitions available, but the remainder of this chapter will use the term accessibility defined as: designed to promote the inclusion and participation of individuals with disabilities.

1.1

Why Is Accessibility Important?

There are a number of answers to this question: There is a moral and ethical case for promoting inclusion and participation of all individuals in education, and more generally within mainstream society. Individuals who are integrated into society through effective education are able to realize their potential and become an asset to their communities. Education reduces poverty, improves health and promotes equality. (Global partnership for Education 2018) In many countries there are legal requirements for products and services to offer a minimum level of accessibility, for example, in the United Kingdom, the Disability Discrimination Act 1995 and the Special Educational Needs and Disability Act 2001, in the United States, Section 504 of the 1973 Workforce Rehabilitation Act and the Americans with Disabilities Act 1990, and in Australia, the Australian Disability Discrimination Act 1992.

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To promote technical efficiency, frequently accessible design is also more effective design for the general population. It is likely to be compatible with a wider range of devices allowing easier interoperability and updating. Interfaces which are designed for users with visual impairment are usually easier for everyone to interact with. This is a benefit to all students, regardless of whether or not they have disabilities. A significant number of students are likely to have disabilities, either declared or undeclared, and possibly unknown even to the student. Roughly 5% of UK students and 6% of US students in post-compulsory education declare a disability (Seale 2006), and there are likely to be more that do not declare. Around a quarter of students declare a disability-state dyslexia or a related specific learning disability, but this is commonly thought to be underreported. It is usually much cheaper to incorporate accessibility features into a learning program at the point of conception than to retrofit features when an individual learner with particular needs joins the program and identifies an issue. Designing for accessibility can often result in a superior outcome and improved user experience for all. While the utopian dream may be to have everything fully accessible to everyone, there are always funding limitations to consider, and compromises may have to be made. Too much emphasis on accessibility could lead to a danger of defaulting to an accessible specification which then degrades the experience for the majority and potentially stifles innovation. Developers may have to choose between access for one group and access for another. When making these decisions, it should be remembered that the focus should be on every individual having an opportunity to achieve the learning objectives. That does not necessarily mean that every activity should be fully accessible, and in some instances, it may be appropriate to provide alternative learning experiences which achieve the same learning outcomes. Just as providing balanced nutrition can be achieved through a variety of menus suited to different tastes, comprehensive education can be provided through activity options selected to cater to different needs and preferences. When providing alternative learning experiences, care should be taken to ensure that the students with disabilities are still embedded into the sociocultural aspects of the learning program. Ideally, the majority of the program should be accessible to all students with alternative learning activities provided just for discrete elements, so that all the students feel that they are following the same learning journey. It may also be appropriate to offer the alternative learning activity as an option for all students, not just those with disabilities, which allows for variation in preferred learning styles and reduces the risk of those students with disabilities feeling that they have been separated from the rest of the cohort. Importantly, the need to provide accessible learning materials should not prevent innovation by learning providers. While an attempt should be made to preempt potential issues with learning activities during the development phase, there may be occasions where an accessibility issue is not identified until a particular learner tries to engage. Where this situation occurs, learning providers will find that students with

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additional needs will be much more sympathetic toward the situation if their needs have been anticipated in other learning activities and they feel there has been an effort to include them in the majority of the learning experience. Within formally assessed programs, it is particularly important to ensure that students with disabilities are not penalized by design limitations which prevent them from fully engaging with the relevant activities. The remainder of this chapter is divided into three sections in which it will consider a number of features of mobile teaching technologies and highlight the positive and negative aspects of their use, related to accessibility issues. Accessibility and disability are very complex areas, and technology is evolving rapidly. Consequently, it is not possible to produce a comprehensive list of every issue and solution. Additionally, the individual nature of disability and its impact means that there is no “one-size-fits-all” solution to many of the challenges faced. However, by the conclusion of this chapter, the reader should be aware of a number of key concerns and have developed a mind-set to be able to identify the types of questions which tutors, learning designers, and academic developers need to be asking.

2

Devices and Interfaces

2.1

BYOD: Bring Your Own Device

If users are able to bring their own device to the learning environment, they are likely to solve some of their accessibility issues themselves. Familiarity with a particular device, which can be used for a number of different tasks, reduces the need for the student to invest time in learning basic functionality and operation. Individuals with disabilities face the same challenges in all aspects of their life, not just in learning. Therefore, they are likely to own devices which are particularly suited to their needs. Our allowing them to then bring their preferred mobile devices to the learning environment means they will already feel confident in their ability to use the technology. However, developers need to be aware of the range of devices which might be in use and the types of issues their content may cause. Developing for a range of devices increases the cost of development. Conversely, if educators specify a particular device must be used, it reduces compatibility problems. But it may be more challenging to cater to a range of accessibility issues. It may also increase cost to the student, if they have to buy a particular device for a specific study program.

2.2

Device Size

By definition, mobile devices need to be small and light enough to carry around. At one end of the scale are tiny screens just a couple of inches across, seen on some mobile phones, MP3 players, and smart watches. The screens get larger on

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smartphones, handheld gaming consoles, and PDAs. At the other end of the scale, tablets and iPads have much larger screens but are less mobile, no longer fitting into a pocket due to their increased size and weight. The manufacturers of mobile devices have increasingly blurred the lines between different types of devices with phones and tablets adopting each other’s functionalities and being available in a range of sizes. The size of the screen on the chosen device has a big impact on its accessibility of learning materials. A smaller screen means that either the content will be displayed smaller or less can be displayed on each page or both. Obviously there is a point at which content is displayed too small for any user, not just those with disabilities. But the issue is likely to be more acute for those who are visually impaired or have reading difficulties such as dyslexia. However, there is no direct correlation between screen size and ease of reading. Schneps et al. (2013) found that the reading comprehension of some dyslexic students increased when using electronic display with short line length. Visually impaired users suffering from tunnel vision may find a smaller screen easier to use as they are able to focus on the entire screen and do not lose anything which other users would be observing in their peripheral vision. The optimum screen size for interacting with a particular learning activity will be a personal issue depending on the particular student’s needs. Within the general population, we find that some users like to access digital content on a relatively small mobile phone, while others prefer the larger screen of a tablet device, despite the inconvenience of reduced portability. This preference may also vary according to the content which is being delivered. The ratio of text to images within a particular learning activity may influence a learner’s decision regarding the preferred device to use. This decision will also be affected by the type of engagement the learning activity is looking for. For example, an activity designed to promote students’ ability to critically analyze a painting, as part of an art history activity, would require much better resolution of the images, and potentially larger screen, than if the same image was used to accompany a historical narrative and provided to give context rather than to be studied in detail.

2.3

Text Considerations

Moving on from screen size, the text size and shape also have an impact on how effectively the user can interact with the learning activities. The ability to change the font can be particularly useful, and developers may wish to consider offering specific dyslexia friendly fonts, in addition to the standard, frequently used fonts which are available (O’Brien et al. 2005). If using specialist fonts, consideration needs to be given as to how they will render on different devices, if they are compatible with different versions and software packages and if the user would be required and able to alter local settings appropriately (Fig. 1). As fonts and text size are altered, it is important that formatting remains sensible for the particular device and content. For example, diagrams or images and

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Fig. 1 Examples of variation in text font, size, and color, including dyslexic friendly font OpenDyslexic (2014)

associated text descriptions need to be retained in close proximity. Equally, text embedded within diagrams and images needs to respond suitably to resizing.

2.4

Content Design

In some instances, it may be appropriate for some content, which is not critical to the message being delivered, to be removed to reduce clutter on small screens or when selecting larger fonts, although it could be argued that such content which could be removed is redundant and should not be present anyway. Similarly, color, brightness, and contrast affect the ease or difficulty with which a user can read from a screen. To some extent, users can usually customize displays using the standard device settings or through applying external overlays. An external film or overlay applied to a device’s screen can be used to alter the brightness or hue and reduce glare. It can be useful to also offer different color schemes within the learning activities to cater to individuals with a range of visual abilities. Some individuals find it difficult to read light-colored text on a dark background and vice versa. As technology evolves, devices may become more or less accessible. For example, the Kindle eReader has been popular with dyslexic readers due to the ability to easily manipulate the text size and the contrast. However, the Kindle Paperwhite and Kindle Fire are backlit, which is not so accessible for readers who experience visual stress or scotopic sensitivity. Some kindles also have embedded readout software which is useful for those who find interacting with text difficult, due to either visual impairments or dyslexia (Fig. 2).

2.5

Touch Screens

Almost all modern mobile devices are controlled through the use of a touch screen. For users with mobility problems, a mobile device which they can operate with a touch screen can often be more user-friendly than trying to access electronic materials using a PC or laptop. Mobile devices, by definition, can be brought to the user and are generally lightweight so can be easily manipulated. Where a user has limited manual dexterity, the use of touch screens, particularly if they are small, can be challenging. Both screen sensitivity and spacing of controls on

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Fig. 2 Kindle Fire, Kindle Paperwhite, and Kindle Wi-Fi showing text preference menus

the screen are important considerations to facilitate use by as wide a range of users as possible. The consistency of button position and function is useful for all users, but particularly so if users have difficulty locating controls. Consideration should also be given to the likelihood of accidently selecting the wrong button which can be very frustrating for users. It is a common misconception that visually impaired users will find the use of touch screen very difficult. In fact, provided there is consistency of control position and function, completely blind users can become very adept at using touch screen devices, when they are combined with audio responses. In some instances it may be useful to apply a tactile indicator to the touch screen to assist individuals in finding the correct locations (Rainger 2005; Arrigo 2010). Once the basic controls have been mastered, the ability of learners to interact with the learning activities in a touch screen environment depends on the type of activity

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which is presented to them. Using a touch screen to select items for display or to navigate through a selection of static pages is fairly straightforward. Activities which involve drag and drop may not be possible for students with visual impairment or manual dexterity problems. Small buttons can be problematic, particularly when arranged close together, and consideration should be given to how to arrange different functions on the screen, for example, putting significant space between “save” and “delete” buttons to reduce the possibility of selecting the wrong one.

2.6

Voice Recognition

So far, consideration has been given to interaction with material through a touch screen. Another option is to use voice recognition. Many mobile devices have some form of voice recognition as a standard feature, allowing basic controls. This feature can be harnessed for use with the learning activities that are being delivered. Apple devices incorporate Siri software and android devices Google Assistant both of which respond to voice commands. When asked for something that it doesn’t have, it will automatically search the Internet and give a suitable response. Although not infallible, it usually responds with something sensible. Unlike many voice recognition packages, Siri does not require training to a specific user. This advantage is timesaving for most users but may be a hindrance if an individual has significant difficulties around annunciation of their speech. If presenting users with learning activities which are to be controlled using voice recognition, consider if the required commands will be obvious to the user or if some training will be needed. Often there is a generation gap between the educational developers and the target learners and the possibility that the two groups use different vocabularies. Students who are studying in a non-native language may also use different word constructs, as well as having variation in pronunciation. There can be difficulty for some students in using voice commands. Those with speech impediments or who have difficulty enunciating, due to physical impairment or deafness, for example, may find voice recognition difficult to use. There also needs to be awareness that specialist words may not be known or understood prior to completing the particular learning activity. Both the student and the relevant software will need to learn specialist terms. In summary, the choice of device and design of the interface has a range of impacts on usability. A small, lightweight device offers the benefits of being very portable but with the challenges of small screen size. Larger devices are less portable but likely to offer increased functionality and allow greater complexity and resolution on the screen. Students with particular needs will have preferences regarding which devices best suit their needs. Ideally, developers will design learning activities which can be accessed on a range of devices and allow interaction in a variety of ways. Having multimodal interfaces which users can interact with in a variety of ways will allow the greatest number and range of users to access the learning (Arrigo 2010).

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Study Environment

Thinking about the study environment, there are two distinct reasons why educators might want to use mobile learning. One is to take the learning resources to the learner, and the other is to bring the learner to the resources (▶ Chap. 34, “Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts”). These two different reasons for utilizing mobile learning technologies present different challenges in relation to accessibility. When learning is being taken to a place of the learner’s convenience, this can be both an advantage and a disadvantage. For example, a student who suffers from fatigue or has limited mobility can access the learning without having to travel to a college campus or even from a hospital bed. However, the ability of the students to access their learning wherever they happen to be increases the likelihood that the environment will not be suitable for effective engagement with the materials. Students need to be able to concentrate on the learning materials, without distractions from other things in their immediate environment. Some may value the classroom environment to help them engage with the learning which is being presented. Going to the physical classroom is a clear signal to others that the individual is engaged in learning and should not be disturbed. A learner who is trying to engage from home may find that they are frequently interrupted by other family members or distracted by other demands. Conversely, some students may find the classroom environment challenging or display behavior which disrupts other learners. A learner with Tourette’s syndrome, for example, may be disruptive in a classroom setting but able to share an online learning environment without any difficulties. Students should be encouraged to be aware of the environment in which they choose to study and to take steps to select a place which will be effective for them. The most suitable place will vary from individual to individual, particularly where students have specific learning difficulties or concentration problems. For some individuals, complete silence will be the only way for them to be able to concentrate. Meanwhile, others find that some level of background noise is essential for them to be able to focus effectively and concentrate on what they are doing for extended periods of time. Coppin and Hockema (2009) give an interesting account of how an individual with dyslexia and ADHD (attention deficit hyperactivity disorder) organizes their workspace, using both physical distribution of artifacts within their immediate environment and background noise, to assist them in organizing thoughts and ideas. Other learners may find this type of environment too cluttered and distracting. Some mobile learning is used in order to take the learning experience to a particular place, situation, or artifact of relevance. This allows the student to contextualize the learning beyond what could be achieved in the classroom setting, for example, engaging in learning in a museum, a historic place, or an industrial setting. In these situations, there may be accessibility issues to do with physical access: Is its wheelchair accessible? What are the noise levels like? Are both the physical space and the learning activity navigable for a student with visual impairment?

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If the answer to any of these questions is no, this does not mean that no student should be given the opportunity to engage in this learning, because some are excluded. Educational developers should strive to overcome these barriers if possible. Can a different, more accessible, location be selected for the learning to take place? Or can the chosen location be made more accessible? For example, putting pressure on a museum to ensure that a particular artifact is positioned in a location which is wheelchair accessible will be of benefit not only to the students but also to the general public who are using wheelchairs or pushchairs. There is also the possibility that a museum may be able to access funding to improve their accessibility if they can show a number of users would benefit. However, where there are difficulties which cannot be overcome or while waiting the infrastructure to be changed, alternative arrangements need to be made for those who are unable to access. Where there are challenges which cannot be fully addressed, it is important that the student is made aware of any difficulties which they may face, preferably prior to starting the learning program, and the alternative support which will be provided. Ideally, information regarding accessibility should be available within the mobile learning environment so the students are aware of what to expect and what support has been put in place for them. In some instances, the use of GPS could be harnessed in order to assist students to navigate to particular places using more accessible routes (Arrigo 2010). Whether the learning takes place in the student’s choice of environment or situated in the context of the learning, consideration needs to be given to the student’s ability to engage effectively without distraction in order to achieve the learning outcomes. Students with dyslexia, fatigue, or concentration issues may find it difficult to focus on the learning if there are several other things going on in their immediate environment. It is likely they will also find it difficult to multitask, particularly where activities require both listening and writing at the same time. With the situated learning, it needs to be ensured that the students have enough time to engage with the environment and take notes or assimilate their learning. For some disabled students that may require extra time at the learning site compared with other students, they are able to complete activities more slowly or take breaks. This will vary by the student’s level of interest and conceptual understanding of the topic area, as well as the disability being a factor.

4

Scheduling

Although one of the key advantages of mobile learning is often that students have the freedom to study where and when they please, the issue of study scheduling still needs to be considered. Even self-paced study programs will have key milestones which students need to adhere to in order to make progress and gain credit for their studies. Consequently, students have to be able to pace their learning. While there is likely to be significant variation in the ways in which students manage their study time, it is imperative that they are all able to achieve the learning outcomes by the target date set either by themselves or by the institution. Some students will choose a

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steady trickle approach, while others may prefer longer more intensive blocks of study. This choice is related both to the students’ personal preferences and also to logistics of incorporating study into other aspects of life. This issue impacts all students, particularly in part-time study programs as they have to balance the study requirements with work and family commitments. Students with disabilities often have additional medical-related restrictions, along with scheduling of disabilityrelated appointments and support. All students may need assistance in identifying how to make best use of the time which they have available for study. While mobile learning opens up the possibility of studying in otherwise potentially wasted time periods, for example, waiting at the bus stop or 15 min on a tea break, there is a question to be asked about the quality of the study taking place. Some activities can be effectively fitted into short bursts of study, but many educators will argue that longer study periods are needed in order to fully engage with new concepts and ideas to achieve deep learning. There is a danger that because mobile learning offers the facility to fit study into these small study opportunities, students may not time-table longer study slots. When students have medical conditions which require regular healthcare appointments, mobile study programs may become something which is slotted in around other commitments and not given as high priority as more formally timetabled study might. However, it also offers the flexibility so that students attending medical appointments do not miss any teaching sessions. Self-scheduling of study may be particularly challenging for dyslexic students as one of the features of dyslexia is that individuals find organizing and managing their time challenging (Kirby et al. 2008). Consequently, dyslexic students may need support in managing the more flexible elements of their study programs, to ensure that they get them completed within a set study period. If the study program includes a number of different elements, they may also have difficulty in managing a number of discrete tasks, unless there is a clearly signposted pathway through. Students with physical or mental disabilities may have significant fluctuations in their health with a consequential impact on their ability to study over time. They will need support to ensure that they are able to utilize the opportunities they have to study while feeling well and manage the less effective or absent periods to have minimal impact on their overall progress. Where the mobile learning includes synchronous elements or has time-limited availability, consideration should be given to how this can be planned for maximum accessibility. Synchronous activities may be available at different times of the day so that students can select the most suitable time for their needs. Meanwhile the inclusion of time-limited activities should be planned with an awareness that some students may need to take a break or take longer than others to engage with the materials. This issue could often be addressed simply by removing the time limitations. Duncan (2015) reported that providing extra time in exams was of benefit to students with a specific learning difficulty but had no impact on the level of attainment for students without a declared specific learning disability. Therefore, educational developers should consider if there is adequate reason to place tight time

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limits on activities or if sufficient time for all students should automatically be available and the need for time adjustments removed. Many disabled students receive additional support to assist them in overcoming related difficulties in their studies. While this is very valuable, the extra support often requires the individual to spend additional time on their studies (Robson 2014). For example, students may need to use some of their study time learning to use assistive technology or working with a specialist study support tutor to improve their study skills and develop compensatory coping mechanisms. This additional support needs to be time-tabled around the standard study program which can be challenging. Where new technologies are introduced to facilitate mobile learning, there may be an additional difficulty if the study support tutors are not familiar with, or do not have access to, the mobile devices and content being used.

5

Collaborative Tasks

Many mobile learning programs involve students in completing collaborative tasks or discussing aspects of their learning with their peers. In both instances, students need to communicate with each other, and there are a variety of different tools which could be used to facilitate this. For synchronous communication, students could use instant messaging, voice calls, or video calls. For asynchronous communications forums, voice messages or video messages could be used. For students with disabilities, some of these will be more accessible than others, and the device they use for access may also impact on the ease of use.

5.1

Text-Based Collaboration

Any text-based form of communication requires a minimum screen size in order to be accessible to the general population as well as those with particular requirements. Individuals who find it difficult to type, particularly on a touch screen, may find themselves excluded from instant message discussions, as others are able to reply much quicker than they are and the conversation moves on too fast for them to be able to contribute meaningful comments. The ability to input text using voice recognition software can alleviate this issue. Voice recognition software can also be useful if individuals find text communication difficult due to limitations on their ability to spell. Some dyslexic students may feel very confident in a face-to-face group discussion using oral communication, but using text-based forums can be challenging because they are unable to express themselves so effectively in writing. Equally, there will be other individuals who feel quite shy in a face-to-face discussion and much more comfortable using a text-based online format. It is important that any text-based communication is also compatible with readout software. This will allow access by visually impaired users and may also be a preferred way of accessing by other individuals.

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5.2

Accessibility Challenges in Mobile Learning

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Multimedia Collaboration

Using voice and video communications is difficult for those with auditory and visual impairments. It may also be challenging for some with manual dexterity problems to capture video to the same standard as that of their peers. While the communications themselves may not be being assessed, it is important that the communication technologies chosen do not impede the student’s ability and enjoyment of communicating with each other. Frequently, students can be distracted by process when they are learning, particularly if they are attempting to use a process which they find is for some reason challenging or cumbersome.

6

Future Directions

This chapter has just scratched the surface of some of the issues of accessibility when utilizing mobile learning. Specific difficulties which may be faced depend on the particular mobile learning environment, learning activities and objectives, and the needs of individual students. When designing learning, mobile or otherwise, educational developers need to be aware that students are likely to bring a multitude of different accessibility challenges. Consideration of common issues should be included early on in the learning design process in order that accessibility features can be designed into the learning experiences. While educators cannot be expected to cater for every possible combination of additional requirements, they should take reasonable steps to accommodate common difficulties and to make their learning accessible to as many students as possible. For example, designing materials to allow users to manipulate the color scheme and text size, along with the compatibility for voice recognition and readout software, would fulfill the needs of many students with visual or auditory impairments, dyslexia, manual dexterity challenges, or fatigue. In addition to fulfilling any legal or ethical requirement to cater for disabled students, accessible learning design commonly produces a learning experience which is improved for all students. It is also sensible to try and anticipate needs as it is usually far more economical to design accessible learning at the point of course development than it is to retrofit accessibility features. Finally, there needs to be an awareness of the range of challenges and ways in which students may want to interact with materials. Making activities more accessible for one group may result in it being increasingly challenging for another. Put another way in terms of accessibility, as one door opens, another door closes.

7

Cross-References

▶ Adoption of Mobile Technology in Higher Education: An Introduction ▶ Characteristics of Mobile Teaching and Learning

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▶ Design Considerations for Mobile Learning ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts

References Al-Rababah, B.A., and E.A. Abu-Shanab. 2010. E-government and gender digital divide: The case of Jordan. International Journal of Electronic Business Management 8 (1): 1–8. Accessed 7 Mar 2014. Arrigo, M.C.G. 2010. Mobile learning for all. Journal of the Research Centre for Educational Technology 6 (1): 94–102. [Online]. http://www.rcetj.org/index.php/rcetj/article/view/78. Accessed 29 May 2014. Coppin, P., and S.A. Hockema. 2009. Learning from the information workspace of an information professional with dyslexia and ADHD. In IEEE Toronto international conference – Science and technology for humanity, ed. IEEE, 801–807. Toronto. Duncan, P. 2015. Equity or Advantage? The effect of receiving access arrangements in university exams on students with Specific Learning Difficulties (SpLD). Workshop at National Association of Disability Practitioners International Conference 20th–24th July 2015, Manchester. Elnaggar, A. 2008. Towards gender equal access to ICT. Information Technology for Development 14 (4): 280–293. Accessed 7 Mar 2014. Global Partnership for Education. 2018. Education. [Online] https://www.globalpartnership.org/ education. Accessed 11 May 2018. Kirby, J.R., R. Silvestri, B.H. Allingham, R. Parrila, and C.B. La Fave. 2008. Learning strategies and study approaches of postsecondary students with dyslexia. Journal of Learning Disabilities 41 (1): 85–96. [Online]. http://doi.org.libezproxy.open.ac.uk/10.1177/0022219407311040. Accessed 11 Nov 2013. O’Brien, B., J. Mansfield, and G. Legge. 2005. The effect of print size on reading speed in dyslexia. Journal of Research in Reading 28 (3): 332–349. [Online]. Accessed 25 Nov 2013. OpenDyslexic. 2014. OpenDyslexic free and open source dyslexia typeface [Online]. http:// opendyslexic.org/. Accessed 27 Apr 2014. Pike, A. 2010. Building bridges across the digital divide for HE students in prison. COLMSCT Final Report [Online]. http://curlew.open.ac.uk/opencetl/resources/details/detail.php?itemId= 4bd99ed8b28cd. Accessed 7 Mar 2014. Rainger, P. 2005. Accessibility and mobile learning. In Mobile learning – a handbook for educators and trainers, ed. A. Kukulaska-Hulme and J. Traxler, 57–69. Abingdon: Routledge. Robson, L. 2014. Additional help, additional problem – issues for supported dyslexic students. In Proceedings of HEA STEM annual conference, Edinburgh. Schneps, M.H., J.M. Thomson, C. Chen, G. Sonnert, and M. Pomplum. 2013. E-readers are more effective than paper for some with dyslexia. PLoS One 8 (9): 1–9. [Online]. http://ehis. ebscohost.com.libezproxy.open.ac.uk/eds/pdfviewer/pdfviewer?vid=5&sid=c1dd4adf-8dcf444b-a4c9-435479e1d468%40sessionmgr113&hid=106. Accessed 11 Nov 2013. Seale, J.K. 2006. E-learning and disability in higher education: Accessibility research and practice. Abingdon: Routledge. Stastista. 2017. Statistics and market data on Online Demographics & Use [Online]. https://www. statista.com/markets/424/topic/537/demographics-use/. Accessed 10 May 2018. Tolbert, C., K. Mossberger, B. King, and G. Miler. 2007. Are all American women making progress online? African Americans and Latinas. Information Technologies and International Development 4 (2): 61–88. Accessed 7 Mar 2014. We Are Social. 2017. Digital in 2017: Global overview [Online]. https://wearesocial.com/specialreports/digital-in-2017-global-overview. Accessed 15 Aug 2017.

Mobile Education via Social Media: Case Study on WeChat

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Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Development of Learning Through Social Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Combined with Mobile Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mobile Class on WeChat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Content Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Analysis on Reports to Improve Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Automatic Reply for Curriculum Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Message Management for Communications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Combined with Off-Line Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

566 567 569 571 572 576 578 579 582 584 585 585

Abstract

Social media has been developed very fast in recent years. Almost every generation has their preferred social media platforms. They communicate with others on social media, share photos and information through social media, search information through social media, and plan their future on social media. It had been adopted by young people and students very fast. It also attracted the attentions from educators. Some universities and schools have developed teaching curriculum for social media and adopted social media in teaching and learning. However, some academics have argued that the results of using social media in teaching and learning may be affected by some contents and games from the Internet. Some students cannot separate the good learning contents from the bad or fake ones that they may be used by criminals. Other researchers also argued that social media Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_67

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account is private, and the use of social media for teaching and learning may force the students to open their privacy to their teachers, which is a problem. Social media, as a tool for teaching and learning, is the same as chalks and pencils. It could have positive or negative influence on learning. When used properly, it can enhance learning performance dramatically. Combined with mobile technologies, social media provides better solution for teaching and learning. Mobile technology has its own advantages (e.g., anytime and anywhere) and disadvantages (e.g., small screen and calculation capability). Majority of social media teaching and learning studies focused on Twitter, Facebook, and Second Life platforms. This study examined a new mobile social media platform (original from China) – WeChat – which has more than 800 million users all over the world. Instead of using university teaching materials, this study is composed of teaching materials for public learners and compared the number of readings, reposts, and likes for different contents on mobile educational social media public accounts.

1

Introduction

The history of social media development has been more than 10 years. The previous definition of social media on Web 2.0 technology is already out of date (Kilpeläinen et al. 2011; Powers et al. 2012; Poellhuber and Anderson 2011). New social media on mobile devices has been growing fast since 2010 and expanded the definition of social media (Castro 2012; Mao 2014). Social media was adopted by new generation quickly now. They search information online, chat with their friends, share photos and information every day, make new friends from their friends’ circles, watch movies, listen to music, and plan their schedules via social media or mobile phones (Castro 2012; Wallace 2014; Powers et al. 2012). Educators also studied the use of social media as a platform for education purposes (Casey 2013; Dabbagh and Kitsantas 2012; Heatley and Lattimer 2013; Kilpeläinen et al. 2011; Zidoun et al. 2016; Alkhezzi and Al-Dousari 2016). Some of them shared teaching video on YouTube (Heatley and Lattimer 2013; Jenkins and Dillon 2013; Ferris and Wilder 2013; Koutropoulos et al. 2013). Some use game platforms to engage students to class discussion, tutorials, and consultations (Bredl and Bösche 2013; Oblinger and Oblinger 2005; SEO 2013). Some developed their own communication tools for education (Yuh-Shyan et al. 2004). Although there are still arguments on whether educator should be involved in the students’ social networks, schools and universities are using more social media as promotion channels, educational platforms, and community services now (Vogel et al. 2009). Social media is believed to play a more and more important role in future teaching and learning as well as people’s daily life (Castro 2012). Social media is also merged into mobile devices quickly because of the mobility and convenience characteristics of mobile devices (Mao 2014). Almost all popular social media have their mobile App version now. They are still lag behind their Web-based big brother on functions and page contents (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). But the usage of mobile version

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catches up very fast, and the providers are enhancing their mobile version continuously. WeChat is a new mobile social media from Tencent in China (Mao 2014). It developed very fast and chased most social media platforms within 3 years in terms of number of active subscribers. In the third quarter of 2016, WeChat had 846 million monthly active users (Statista 2017). With the new technologies been introduced into mobile social media and mobile education, it will bring more learners to the wireless environment and virtual worlds (see ▶ Chap. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”) (Mao 2014).

2

Development of Learning Through Social Media

Social media is not new to educators now. It has been developed very fast in recent years. Educators and educational organizations have designed and developed many practicing curriculums and courses on social media (Baage 2013; Britt 2013; Buffington 2013; Casey 2013; Haipinge 2013; Heatley and Lattimer 2013; Jenkins and Dillon 2013; Alkhezzi and Al-Dousari 2016; Zidoun et al. 2016). Some of them are multination or multidiscipline projects (McCombs 2010). However, the real effects or performances of these projects are influenced by the vision of the organizations, the design of curriculum, the chosen social media platform, and the readiness of teachers and students for that social media (Wallace 2014). Designers or teachers usually carefully select one or several social media that is suitable for the teaching disciplines, materials, and skills, such as Facebook (Ferris and Wilder 2013; Haipinge 2013; Kilburn 2013; Poore 2013; Rennie and Morrison 2013), Wimba (Baage 2013), Twitter (SEO 2013; Tyree 2013), Wikipedia (Britt 2013; Ferris and Wilder 2013; Kemp 2013; Poore 2013; SEO 2013), Pinterest (Buffington 2013), YouTube (Ferris and Wilder 2013; Heatley and Lattimer 2013; Jenkins and Dillon 2013; Koutropoulos et al. 2013; SEO 2013), Google+ (Heatley and Lattimer 2013), Google search or cloud computing (Heatley and Lattimer 2013; Mills 2013; Ostrom 2004), broadcasting (Castro 2012; Evans 2008), and the new mobile social media WeChat (Mao 2014). Not all social media suits all learners. The readiness of teachers and learners on social media usage and technical skills of using it is important (Poellhuber and Anderson 2011; Cheon et al. 2012; Cumming et al. 2013). If the vision of the organization that has mandated the use of social media or mobile learning is not coherent with the readiness from teachers or students, it usually brings unexpected results (Wallace 2014). Some researchers argued that the over-participation or addiction of students to social networking will lead to a negative impact on their academic performance (Kirschner and Karpinski 2010). Distraction is also a problem in mobile learning (Alkhezzi and Al-Dousari 2016). But other researchers argued that the performances from learning should be measured through different dimensions that adopting social media in learning increased students’ satisfactions on learning process (Al-Rahmi et al. 2014). Most educators believe that using social media in teaching and learning will facilitate learning, increase creativity in learning, and encourage share across time and space (Castro 2012; Howard-Jones 2002; Mao 2014). Some have proved that

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social media can help special students with disability or from a different cultural background (Baage 2013; Cumming et al. 2013; Koutropoulos et al. 2013; Castro 2012). Personalized learning or learning on demand becomes possible on social media and mobile devices (Dabbagh and Kitsantas 2012; Hsu et al. 2013; Sharples 2000; Tsay et al. 2010). Heatley and Lattimer (2013) argued that social media is the most cost-effective way to expand learning and break the limitation of a fixed classroom. With the development of wearable devices and development of “nature user interface (NUI)” (Alkhezzi and Al-Dousari 2016; Yousafzai et al. 2016; Hennig 2016), there will be more opportunities and forms of adoption of social media in mobile education. Figure 1 shows the timeline for the major social media market in China. Some old social media is not popular anymore or already quit the market. Some popular ones, such as LinkedIn, Facebook, and Skype, have been developed for more than 10 years. However, the new social media from China, Sina Weibo and WeChat, have only 5 and 3 years of history but more than 600 million and 800 million registered users in 2014. The difference between Weibo and WeChat is that the previous one started with online users, while the latter one started with mobile users only. Weibo and WeChat are the most popular social media in China. The users use Weibo and WeChat for different purposes. Figure 2 listed the differences between the usage of Weibo and WeChat. Most official departments and famous businesses/persons have their Weibo accounts. People share photos and information on Weibo. The repost rate is higher on Weibo. However, most users use WeChat for chat and connection. Mao (2014) studied the key factors of undergraduate students’

Fig. 1 Timeline of social media market in China. (Source: From this study by author)

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Mobile Education via Social Media: Case Study on WeChat

Wei bo

90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Status

Photos

Chat

Share

Reply

569

WeChat

Connect Discuss Repost

Others

Fig. 2 Differences on Weibo and WeChat. (Source: From this study by author)

WeChat usage and found the influence of friends is the major factor for them. Almost all students use WeChat every day and 18.8% of them use WeChat for more than 2 h per day. In a sum, social media has changed the way of teaching and learning. Students are no longer a message receiver that learns from teachers or books. Sometimes, they could possess more knowledge and skills than the teacher, equipped with online searching engines (such as Google), video guide (such as YouTube), and others’ experience (from professional groups). Therefore, teaching with social media should be different to traditional teaching. Students are more involved in communication with teachers, their peers, or maybe professional people online. They can contribute to not only the class participation or discussion but also the curriculum design and course development. The role of teacher is changed to facilitator to encourage students’ searching and sharing during class. But it is important for teachers to identify the usefulness of the knowledge online and quality of information from social media. Teachers can also encourage critical thinking and creative thinking during this process to lead the students on the right track. Social media, if combined with mobile technology, can be more powerful and attractive to learners.

3

Combined with Mobile Technology

Traditional social media starts from online platforms based on browsers on computers. They are designed for computer and Internet connections with more contents in the same screens and bigger size of photos or figures. Most social media have their own mobile applications for users now. They are available for users from application stores (Apple Store, Google Play, and others) for free. However, some are not suitable for mobile usage (such as big-sized pictures or large videos). As a result, the majority of users are still using computers to access them. WeChat is a social media born with mobile technology and users. The initial design of WeChat is only for free Chat and connection on mobile phone. The users’ interface and all materials on WeChat are designed in strict limited sizes. WeChat

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adopted fast micro-innovation life cycle to develop and try different new functions for its users. WeChat provides free group chat, voice and video messages, photo and text messages, “shake,” “look around,” “drift bottle,” and even “Facebook connect” functions, which are very attractive to young people (Mao 2014). Figure 3 shows its micro-innovations from version 1.0 in 2011 till 2014. The multiple free functions brought fast growth of registered users since January 2010. WeChat has 800 million users within 3 years, and the users are still growing fast in 2014. As indicated by Castro (2012), “If learning exists at multiple Scales, from cellular to cultural, then so does teaching.” As the fast-developing social media platform, many educators already focused on the use of WeChat in teaching, but most of them are in China (Mao 2014). The users’ growth is shown in Fig. 4. The trust levels between users are very high on WeChat. Most of them are family members or close friends. WeChat also provides very good analysis tools for users’ analysis. A WeChat public account is a special account which provides one to multiple methods for users to send group information, such as educational information. It also provides good users’ analysis tools and communication methods to engage users. Many authority departments or industry users already adopted WeChat public account to engage customers and users. This study will discuss the possibility of using WeChat public account in education.

Fig. 3 Micro-innovation of WeChat versions from 2011 to 2014. (Source: From this study by author)

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Mobile Education via Social Media: Case Study on WeChat

800 millions (160 millions overseas)

GROWTH OF TENCENT’S WECHAT SERVICE Unit: million users Source: Tencent Inc

millions

571

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300 250

200

200 150

100

100

50

50 0

Dec 2011

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Fig. 4 The growth of WeChat users by million from 2011 to 2016 (Statista 2017)

As one of the major social media in China, WeChat public account is popular for government, associations, and business promotions. WeChat public account has its own advantages and disadvantages as an educational channel compared to other social media and Weibo. The advantages and disadvantages of WeChat public account are discussed in Table 1.

4

Mobile Class on WeChat

The contents developed for Tutors in Pockets were targeting on higher education economic teaching and learning (see ▶ Chap. 27, “Tutors in Pockets for Economics”). This study expanded the use of those contents to a more general market to benefit the community and business users through a social media platform. Learners can be engaged and motivated from the real needs in their daily life. The curriculum can also be designed to suit different groups of learners. To examine the mobile education through new mobile social media – WeChat – three new public accounts were designed and developed on WeChat (“Mobile Class” or “口袋课堂”) by WEMOSOFT. All of them are registered in May 2013. As listed in Fig. 5, the first public account, WEMOSOFT, provides investment information and educational class to users (targeting on globe investors and visitors); the second one, Mobile Class, provides economic/food receipt/happiness mobile classes to users (target on well-educated learners); and the third one, Wollongongbaby, provides early childhood education activities and information (target on local community and parents with young kids).

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Table 1 Advantages and disadvantages of WeChat public account Advantages It is one to multiple push information on mobile phone with notice (like short message) The trust level between sender and receivers is usually higher (one forward leads to approximately ten reads) The edited contents can be saved, modified, and sent anytime and forwarded by others There are good analysis tools to analyze the users’ posts and messages easily

Disadvantages The reach is usually limited by close circles (hard to be forwarded by others and reach out) The editing system is not good enough (still has bugs) and is changed all the time Public account is not English friendly There are some bugs in the editing system

Source: From this study by author

Fig. 5 Three mobile educational public accounts on WeChat. (Source: From this study by author)

Each of them is targeting different user groups in different locations and education or age ranges. WEMOSOFT kept slow updating speed with one update per month or per week. It had 123 followers till 30 November 2014. Mobile Class was updated once per working day, and it had 45 followers till 30 November 2014. Wollongongbaby kept a once-a-day update since the opening of this account and had 135 followers till 30 November 2014. This public account is designed to be linked to a local community chatting group. Qualitative case study was adopted for this study. Each class (content) was reviewed with its report, user’s message, and keyword searching.

4.1

Content Development

The three WeChat public accounts were designed and developed with educational information for research. Take the Mobile Class as an example. A total of 80 classes

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were created for this public account (including 59 economic classes, 350 food receipts, and 12 happiness classes) before 2 March 2017. Figure 6 shows the list of the some economic classes (contents) for the Mobile Class public accounts. Each of the contents is composed of a title, front-page image, abstraction, main context with text and pictures (or animations) for economic teaching, and learning materials. All of them are in Chinese (expect some name in English). Most of them are related to some real-life case studies or historical stories linked to the economic conceptions. They are designed to help Chinese students in their economic subjects and better understand on how to use economic knowledge in real life. There are also some food receipt classes and happiness classes in this public account to give a break for learners from sole economic contents. The resources (animations and cartoons) for economic classes are from Tutors in Pockets (see ▶ Chap. 27, “Tutors in Pockets for Economics”; Zhang 2012), which are designed and developed for mobile devices and economic teaching and learning purpose. Each of these animations or cartoons is less than 1 MB in size, which is

Fig. 6 Contents for Mobile Class public account. (Source: From this study by author)

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suitable for mobile screens and mobile data transfer (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). But all of the contents are translated into Chinese and expanded. Some case studies in the Chinese markets or Chinese history are added to engage the Chinese learners. Figure 7 shows an example of how these contents are edited in the WeChat public account system. There are some limitations in the editing system by WeChat. Some functions are not working well for English systems or software, and the “Control + V” function is useful in the main context development. The size of pictures in the main context is also strictly limited to enhance the users’ experience on WeChat. There are many technical skills in using the WeChat public account editing system. Normal teachers or educators may find it difficult to use it for curriculum or teaching materials design and development. Some of the managers of WeChat public account have to seek advice from professional technical supports. As shown in Fig. 7, a class (content) is composed of a title, author, a front-page picture (required), abstract, and main content. Although the front-page picture size is not strictly limited, the smaller the picture, the less time learners open the content. This influenced the learners’ reading rate of each class. Animations play important

Fig. 7 Example of content in Mobile Class public account. (Source: From this study by author)

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roles in the economic classes on WeChat. The contents with animations have higher open rate than contents without animations. The title and abstract also have influence on the reading rate of each class. In general, an attractive title or introduction linked to real-life examples leads to higher reading rate. WeChat limited all the pictures in the main body by 300 kb (before November 2014) to enhance reader’s experience on their mobile devices. All audio files must be less than 1 min in time length and less than 5 MB in size (before June 2014). All video files must be less than 20 MB in size (before June 2014). All these limitations are designed for mobile users and greatly received users’ experience for learning. After the contents are designed and developed for WeChat Mobile Class. They can be sent in group message to all followers. Figure 8 shows the sent message by date. The message can be a text-only message (can be sent to all users by the manager’s mobile phone), one picture message (can be sent to all users by the manager’s mobile phone), an audio message (can be sent to all users by the manager’s mobile phone), a video message (can be sent to all users by the manager’s mobile phone), or a designed picture and text message (a designed class). We only adopted designed class in group message in this study as it is the best for teaching and learning purpose. But the other convenient messages from mobile devices are good for business promotion purpose or emergency information use. All the sent messages and their reach and reading can be viewed in the analysis reports provided by WeChat. This is also a powerful tool provided by WeChat,

Fig. 8 Sent message (class) from Mobile Class on WeChat. (Source: From this study by author)

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which is like the functions of Google Analytic tools. With a good use of these tools, designers and teachers can change their class contents and improve learner’s experience in learning easily. They are introduced in the following functions.

4.2

Analysis on Reports to Improve Teaching

The users’ reports and interactions can be viewed in the analysis pages provided by WeChat. As a result, the Wollongongbaby account had more followers and active users because of the supporting chatting group. Parents contributed to the curriculum design, information sharing, and suggestions every day. Mobile Class engaged more professional followers, and they provided some suggestions on how to improve the contents. WEMOSOFT public account had different performances on different contents due to the design of each material. WeChat provides content (class) analysis, users’ analysis, and message analysis. Each of them will be introduced below. As shown in Fig. 9, the contents are compared in the Mobile Class WeChat public account. The economic class 56 reached 41 people (who are followers of the public

Fig. 9 Mobile Class content analysis report from WeChat. (Source: From this study by author)

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account). It was opened by 20 people and 1 person saved or forwarded it to others. The food receipt class (target on female users with kids or family members living together) and happiness class (target on elder users or working groups with mental health issues) usually have more reads and forwards compared to economic class due to its readers’ age ranges and career backgrounds. For each class or content, WeChat also provides detail reports on its readers’ changes, trends, genders, locations, and mobile devices with their detail types. Figure 10 shows the detail learners’ report for one class/content in the listed mobile class. These data provided a good view on whether the content attracts more female learners or male learners, iPhone users or Android users, and users in mainland China (or some provinces in mainland China) or overseas users (marked as unknown in Fig. 10 report). The trend of the number of readers (who opened the content) and number of people who saved or forwarded it to others is also important. Some contents may be forwarded and reviewed several times after a certain period (e.g., the graphing data skill for students who will attend an examination that needs drawing a figure). Some contents have high readings and forwards in a certain day (e.g., the special event or activity on the day the content is sent).

Fig. 10 Details of learners for one class. (Source: From this study by author)

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All of these reports gave some good suggestions on how to improve future contents for class or time to send the class/content to learners. WeChat also provides group function to group users in special attributes. Different classes for different groups of users can be sent to special groups to increase the learners’ experience of learning. The functions are still under developing, and the future functions are expected to be enhanced to provide better experience for both designers and users. Another useful function for curriculum design on WeChat is the automatic reply functions. They are introduced in the following section.

4.3

Automatic Reply for Curriculum Design

The automatic reply functions are very good source of interactive functions to engage learners. With a well-designed logic, it can work like a dictionary, a robot to reply questions, or even a mobile game that leads learners to think and find the answers by themselves. As shown in Fig. 11, the automatic reply (from the Early Childhood Education public account) when a user is added to this public account is a welcome message that will be sent to any new follower. To engage users, a group chat address can be added to engage the users who want to learn from other peers and share their knowledge and experience with others. Figure 12 shows the automatic reply to users who are searching/sending information without using the keywords (which are already set up in this public account) from the Early Childhood Education public account. The designer can introduce the keywords to users to lead them to the correct information that they are searching. The teacher can also encourage learners to send questions or information back to this public account and review and reply questions in the message management. The automatic reply with keywords is a useful function for curriculum design. A good combination of keywords can make the learners feel like chatting with a real

Fig. 11 Welcome automatic replies. (Source: From this study by author)

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Fig. 12 Non-keyword automatic replies. (Source: From this study by author)

person (just like artificial intelligence robot on instant communication tools) or doing a game and searching for an answer. It can also be set by sorted names and numbers to facilitate the user’s searching for related contents or classes. English keywords, Chinese keywords, or numbers are accepted as keywords. But duplicated keywords can only be searched by the latest one. Figure 13 shows the automatic replies from the Mobile Class public account with different class names and numbers for searching.

4.4

Message Management for Communications

Message management provides a good communication and interactive interface with users or learners. But only the messages that the users sent to the public account within 5 days are available in the list. And if the manager of the public account did not reply the message (not including the automatic replies), the message cannot be replied manually. This is a disadvantage of WeChat public account. And the expected reply period in Australia and China is also different due to their cultural backgrounds. As shown in Fig. 14, the message management shows sender’s name, message body, and date and time of the message. The manager can save or reply the message manually. The keyword message is hidden from this message list, but the manager can open all messages by ticking the box of the hidden message function. The replied messages (either automatically or manually) are marked as “already replied” in red after the date and time of each message so the manager can focus on the messages that have not been replied. Like the content or users, the message analysis page also provides detail of reads, changes, trends, and numbers of messages per person. Figures 15 and 16 show the message analysis page for message report. They provide a good report on learner’s interactive with the public account and their

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Fig. 13 Keyword replies. (Source: From this study by author)

Fig. 14 Message management. (Source: From this study by author)

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Fig. 15 Message analysis page. (Source: From this study by author)

Fig. 16 Message analysis page 2. (Source: From this study by author)

interests of the class that had been sent. Another important report in the message analysis function is the keywords report. As shown in Fig. 17, the keywords report gives a good ranking on hot keywords searched by learners. The teacher can easily see where the major questions or concerns are. From this study, WeChat provides a very powerful platform for mobile teaching and learning, which includes design of curriculum, development of teaching

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Fig. 17 Keywords analysis. (Source: From this study by author)

materials, interaction with students, and communication or chat between users, and more than 800 potential learners are already on this platform. It provides very good analysis tools for designers and teachers in enhancing their teaching curriculum, doing innovation on their class, and conducting personal education to special groups of learners.

4.5

Combined with Off-Line Activities

Mobile technology has been proved to have many advantages in teaching and learning (Alhassan 2016; Alkhezzi and Al-Dousari 2016; Fernández-López et al. 2013; Evans 2008; Rennie and Morrison 2013; Qiu and McDougall 2013; Yousafzai et al. 2016). But there are many challenges facing mobile teaching and learning (Alkhezzi and Al-Dousari 2016; Yousafzai et al. 2016; Hennig 2016). One of them is the lack of social development and communication skills (Alhassan 2016; Bredl and Bösche 2013; Rennie and Morrison 2013). A blended teaching and learning method is preferred in the current stage. This section showed some successful examples of off-line activities combined with mobile learning through WeChat. The messages from users showed that the celebrating events or activities, humor content or title in class, beautiful photos or pictures (such as food), and personal information (linked to real-life example or real person) lead to more reads and forwards. A group activity is designed on the Wollongongbaby public account in collaboration with the Wollongong City Council for the annual festival in Wollongong – Viva La Gong. The Wollongongbaby group led the biggest group of people and prams in the parade in Viva La Gong. A total of 70 people registered

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for this activity on the Wollongongbaby group and more than 50 showed in the parade. Figure 18 shows the group parade on 8 November 2014 in Viva La Gong, Wollongong, NSW, Australia. As shown in Fig. 18, all the decorated posters (on the sides of prams) are printed and distributed to parents before the parade. An educational class was designed and made to teach people how to decorate themselves and the prams with these printed posters. All parents have showed great interests and did a great job to make it real. The grandmothers’ group performed in the following 2 years with Wollongongbaby group communicating and learning through WeChat group. Figure 19 shows the fan dancing group (grandmothers with average age 65 for Wollongongbaby) in Wollongong Chinese New Year celebration on 2nd of February, 2017. The group members actively shared and learned dancing and singing through WeChat contents. They also adopted WeChat as a communication tool and notice tool for weekly off-line activities. Some members also kept contact with the group Fig. 18 Viva La Gong Wollongongbaby group parade. (Source: From this study by author)

Fig. 19 The grandmothers’ fan dancing in Wollongong Chinese New Year. (Source: From this study by author)

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when they travel back to China and shared information with their Australian friends. Many audiences were impressed by their enthusiasm and attitude to life. The performance was highly appreciated by local government and communities. They were invited to many other celebrations and events. It is never too late to learn and to show others. This is a lesson the seniors taught us through their enthusiastic dancing and team work.

5

Future Directions

Social media has been developed and introduced into teaching and learning for many years. But the new mobile social media is a challenge for all previous social media. As a new social media born with mobile, WeChat developed very fast in terms of its registered users (800 million users within 3 years till 2014). WeChat targets on Chinese market and the Chinese community in other countries. The language and community support make it different from Facebook, Twitter, or LinkedIn for the community members in Australia and other countries. The convenient analyses and management tools provided by WeChat public account also attracted business and industry users. This study established three different WeChat public accounts for research and teaching purposes and collected qualitative results from all the analysis report, users’ feedback, and message report. The online activities were linked with off-line activities to make education connected with groups and benefit local communities. From this study, Mobile Class with social media is better to be linked with group chat and off-line activities. Group task generated best learning and communication on WeChat platform. The contents with educational information, humors, and celebrations attracted more interactions. WeChat provides very good analysis tools and users’ base for mobile education. The trust levels between users are high. Different functions of WeChat and WeChat public account are good for different expressions of knowledge, sharing of knowledge, group discussion, and feedback collection. WeChat can support subgroup of users for a public account. The manager can create different subgroups and put users into each group, such as group by gender, group by location, group by educational level, group by interests, or group by age. Educators can design, develop, and send different materials to different groups of learners to achieve personalized learning. This function is also useful for businesses if they want to target different groups of users. New technology and new social media provide many new innovative functions for teaching and learning. To make a good use of different tools, educators should keep studying the new skills and platforms as well as get involved in the learners’ preferred social media. Social media education is not a one-go class. It requires continuous promotion, enhancement, maintenance, and communication. Content is king for social media. So does for educational public accounts. The future use of WeChat for educational purpose can focus on curriculum design on logic combination, multimedia content development, subgroups to engage

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different groups of learners, and connection with off-line activities and group chat. It is identified as the future trend for learning and business.

6

Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning ▶ Tutors in Pockets for Economics

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Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Pedagogical Paradigms Impacting Teaching and Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Philosophical Underpinnings of Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Effective Instruction in Higher Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Reflective Thinking and Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 The Impact of Disruptive Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Digital Technologies in Higher Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Opportunities and Threats with Mobile Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Key Considerations for the Integration of Digital Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

In learner-centered, technologically enabled postsecondary classrooms, twentyfirst-century digital and mobile technologies provide avenues for flexible, personal learning for different groups in the same classroom and enable individual discovery. These same technologies also present risks and ethical dilemmas, including challenges to pedagogical processes and instructors’ academic identity in postsecondary teaching and learning contexts. In the current technologyenabled educational milieu of this century, this may mean instructors thinking differently about engrained, traditional pedagogical practices and exploring the interconnections between subject matter disciplines in a globally connected society. In this chapter, the author presents the argument that the past century’s concepts of reflection-on-practice and reflection-in-practice remain of prime W. L. Kraglund-Gauthier (*) St. Francis Xavier University, Antigonish, NS, Canada Faculty of Education, Yorkville University, Fredericton, NS, Canada e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_68

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importance, and when the implications for teaching and learning in and outside the classroom with digital and mobile technologies are considered and addressed, a rich pedagogical experience can emerge.

1

Introduction

Despite the ubiquitous nature of technology in our current twenty-first-century social milieu, its presence in postsecondary classrooms is still met with mixed opinions and varied degrees of effective use by instructors (Al-Emran et al. 2016). Via an extrapolation of Ardies et al. (2014) research on secondary students’ attitudes toward technology, understanding adults’ attitudes toward technology can contribute to the design of appropriate interventions and supports for those instructors who are open to exploring the ways mobile technologies can enhance their pedagogy. Specifically, as McKeachie and Svinicki (2014) argued, “the successful integration of technology entails careful consideration of course content, the capabilities of various technology tools, student access to and comfort with technology, and the instructor’s view of his or her role in the teaching and learning process” (p. 264). Moreover, as institutions learn to capitalize on their students’ seemingly constant access to mobile devices, more efficient and cost-effective ways to distribute information and complete administrative tasks related to student enrolment, fee payments, and academic advising can be realized. Since the first publication of this text, technology continues to dramatically change the way institutions conduct the business of education. As well, an ongoing scan of the literature reveals continued focus on the twenty-first-century learner and their skills and ways of learning in elementary and high school contexts. The education field is still flooded with examples of student learning activities that effectively incorporate technology to inspire engagement with the curriculum and to connect to the world beyond the physical classroom walls. What is less evident, however, is how the research field has continued to follow the twenty-first-century learner from their technology-infused K–12 classrooms to where they are now – postsecondary classrooms – many of which are steeped in traditional didactic, low-technology teaching methods. With the goal of improving students’ educative experiences, teaching practices have been researched and theorized extensively, especially in higher education classrooms of the latter half of the twentieth century (Chickering and Gamson 1999). There is an array of educational philosophies underpinning teaching practice, especially within the context of working with adult learners. There are far fewer parallel studies examining twenty-first-century postsecondary instructors in those same contexts. Writing and research that weave the business and process of student learning in higher education that involves technology with the required pedagogical approaches needed in classrooms enhanced with mobile technologies remain sparse (Gikas and Grant 2013). A noted exception is Herrington and Herrington’s observation that “the disruptive nature of the integration of new technologies in education

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often results in practitioners relying upon tried and proven pedagogical approaches, leading to ‘one step forward for technology and two steps back for pedagogy’” (as cited in Cochrane 2013, p. 247). In response, this chapter identifies key concepts of digital technologies as an ongoing disruptive force in higher education. But rather than a technical blueprint for implementation – a challenge because of the rapid evolution of technology itself and the myriad of applicable contexts – this chapter explores the philosophical frameworks that impact instructors’ approaches to teaching in postsecondary educational contexts. The goal is for readers to conceptualize and perhaps reconceptualize the pedagogical approaches that instructors use with their students. When pedagogical processes are at the forefront of course design and when instructors engage in reflective practice with the goal of improving teaching, learning that integrates digital technologies can be student-centered, engaging, and empowering for all.

2

Pedagogical Paradigms Impacting Teaching and Learning

Although difficult to define because of the individualized nature of teaching and learning, the term pedagogy is often used in reference to the instruction of children and encompasses the art and science of teaching. Adding to this, Loughran (2006) argued that pedagogical practice includes more than the transmission of information, but also includes the “relationship between teaching and learning and how together they lead to growth in knowledge and understanding through meaningful practice” (p. 2). In contrast, a more inclusive definition not bounded by age incorporates the term pedagogic setting to “denote any identifiable group. . .for whom teaching and learning are an explicit and overarching goal” (Leach and Moon 2007, p. 10). In this chapter, pedagogy carries a broad, inclusive meaning that encompasses teaching and learning in higher education – referred to here as postsecondary education or postsecondary learning – one borrowed from the Center for Instructional Development and Educational Research (CIDER 2009). According to CIDER, “pedagogy represents the creation of environments designed for learning.” In refining the concept of pedagogy even more specifically in terms of studentcentered activities that incorporate digital technologies, “Scholarly learner-centered pedagogy represents the conscious creation of environments designed to foster learning through a focus on learner autonomy, social engagement, and cognitive processing, based on principles of teaching and learning developed through theoretical and empirical research” (CIDER 2009). Such structured and analytical ways of thinking about beliefs and practice add foundational intentionality to teaching (Dewey 1959). In a milieu where the debate still rages over the purpose of postsecondary education, whether it be to gain the professional skills and knowledge associated with a career, to expose students to materials and to individuals that enlighten them and encourage engagement in critical thinking, or a rite of passage to adulthood, it remains

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that students who attend institutions of higher learning after the completion of their secondary education seek additional knowledge and skills from their instructors. The P21 Framework for 21st Century Learning (P21 Partnership for 21st Century Learning [P21] 2017) is an effective tool to conceptualize the twenty-first-century learning outcomes and support systems that instructors and administrators can consider as they work to address the pedagogical and career-building needs of the students who attend their institutions. As depicted in Fig. 1, the overarching aspects of student outcomes are supported by the foundations of standards and assessments, curriculum and instruction, professional development, and learning environments. It is within this foundation of critical systems where the application and implementation of digital technologies resides. By acknowledging and leveraging the digital technologies students bring into their learning environment, instructors can address the twenty-first-century teaching foci that P21 (2015) has identified: • Focus on twenty-first-century skills, content knowledge, and expertise. • Build understanding across and among key subjects as well as twenty-firstcentury interdisciplinary themes. • Emphasize deep understanding rather than shallow knowledge. • Engage students with the real-world data, tools, and experts they will encounter in college, on the job, and in life; students learn best when actively engaged in solving meaningful problems. • Allow for multiple measures of mastery.

Learning and Innovation Skills – 4Cs Critical thinking • Communication Collaboration • Creativity

Life and Career Skills

Key Subjects – 3Rs and 21st Century Themes

Information, Media, and Technology Skills

Standards and Assessments Curriculum and Instruction Professional Development Learning Environments © 2007 Partnership for 21st Century Learning (P21) www.P21.org/Framework

Fig. 1 P21 Partnership for 21st Century Learning Framework. (Used with permission)

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To do so, however, and to so with the explicit intention to embed within one’s instructional practice, those activities that help students develop and refine their skills and knowledge requires a deeply individualized examination of the philosophies of teaching that instructors bring to their practice within postsecondary classrooms.

2.1

Philosophical Underpinnings of Teaching

A developed educational philosophy of practice serves as “a tool to promote teachers’ ongoing personal development” (Beatty et al. 2009, p. 100) and informs the process by which instructors approach the inclusion of digital technologies into their design of student learning activities. A behaviorist philosophy of education serves to characterize instructors who concentrate on teaching skills that enable learners to function within society and who tend to focus on behavioral modification through positive and negative reinforcement (Elias and Merriam 1984; Merriam 2001). The behaviorist instructor is often authoritative and directive, and their teaching tends to be sequential in nature, with students having little to no involvement in determining learning outcomes or delivery methods (Elias and Merriam 1984). One can find behaviorists leading traditional elementary and secondary classrooms and delivering lectures in higher education classrooms and in skills labs. A progressive instructor acts as a guide to learning and is someone who creates opportunities for individuals to gain practical knowledge and skills that can be transferred to and from real-life experiences (Zinn 1999). Progressive instructors design learning experiences that enable students to reflect on experiences, evaluate the experiences, and, thus, gain a heightened awareness of the learning derived from those experiences (Lindeman 1926/1961). By making a connection between the material at hand and past material and experience, a student can bring a critical awareness to the new knowledge and experience. When individuals are participants in their learning, they are less passive and are better prepared to play an active role in society (Dewey 1959). In educational settings designed by humanistic instructors, discussion is encouraged, student input and self-direction are welcomed, and personal insight is sought. The instructor’s intent is to create opportunities for learners to delve into their own constructs of teaching and learning, perhaps challenging systemic and societal norms. Mutual trust and respect – a sense of community, as it were – are required. Constructivist instructors assert that students build and interpret reality based on how they perceive their experiences. In this learning paradigm, instructors consciously create opportunities for learners to engage actively with the course materials and with each other. Direct lecture is minimized, and the instructor functions as a facilitator, guiding students through interactive activities that build on their prior knowledge and understanding (Bangert 2004). In an early review of the effectiveness and efficiency of networked Internet communications technology in education commissioned by the Canadian Council of Ministers of Education and

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Industry Canada, “effectiveness of the technology seemed correlated with the extent of interactivity that the technology afforded the learners” (Ungerleider and Burns 2003, p. 30). By understanding philosophical underpinnings of teaching, an instructor can frame thinking and pedagogical intent. In doing so, instructors have the awareness and potential to make learning more meaningful for their students. Yet, in the drive to address the learning needs of twenty-first-century learners by incorporating digital technologies, it is important to “not lose sight of what matters in terms of quality pedagogy and learning experiences” (Kirkpatrick 2011, p. 24).

2.2

Effective Instruction in Higher Education

After collaborating with key scholars in the fields of higher education policy, administration, and economics, Chickering and Gamson (1999) released the document Seven Principles for Good Practice in Higher Education in 1987. They contended that the effective teaching of face-to-face postsecondary courses can be linked to the instructor who: • • • • • • •

Encourages student-faculty contact Encourages cooperation among students Encourages active learning Gives prompt feedback Emphasizes time on task Communicates high expectations Respects diverse talents and ways of learning (p. 76)

From a pedagogical standpoint almost two decades later, including these seven points into the design, delivery, and assessment of course outcomes is a prudent decision – one that has transferability to learning environments that include the application of digital technologies. Leach and Moon (2009) went so far as to attest that “Good teachers are intellectually curious about pedagogy” (p. 1). In consideration of the challenge in defining instructor effectiveness, Danielson’s (2007) four broad domains of teaching responsibility are appropriate considerations within the context of digital technologies in higher education because of the delineation of components: (a) planning and preparation, (b) the classroom environment, (c) instruction, and (d) professional responsibilities. Instructor effectiveness in terms of Domain 1: Planning and Preparation is derived from knowledge about six components, including among others, knowledge of content and pedagogy, resources, and instruction. Components of the “classroom environment” that may reveal teaching excellence include how the created environment enables interactions between facilitators and students that are respectful and understanding and are premised on a culture for learning. Other components of this domain involve classroom management of time, groups, tasks, and resources. Danielson’s third domain is “instruction,” which is comprised of five subcategories

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involving the ways in which instructors communicate with students about learning expectations and course content, engage students, use different assessment strategies, and be flexible and responsive to changing needs and situations. Regardless of definition, these dimensions are not mutually exclusive but rather are interlocking elements that, when combined, comprise a holistic concept of an effective instructor (Danielson 2007; Strong et al. 2011) who incorporates digital technologies effectively in ways that support student learning.

2.3

Reflective Thinking and Practice

One common thread throughout much of the literature about teaching is the importance of taking the time to examine the beliefs unpinning personal teaching practice, thus revealing personal philosophies of teaching and learning (Darkenwald and Merriam 1982). Schön (1983) differentiated between technological knowledge and “professional artistry” (p. vii) and urged instructors to use reflective practice to inform and develop their philosophies of teaching. Theorists have also acknowledged there is more than one framework from which to construct these personal philosophies (see, e.g., Brookfield 1990; Merriam and Caffarella 1999; Zinn 1999). Others, including Biggs (2002) and Flannery and Wislock (1991), have argued that a firm understanding of personal philosophies of teaching may enable instructors to make informed decisions on teaching methods and evaluations of student learning and reflections on practice. “Reflective thinking is the process of making informed and logical decisions on educational matters, then assessing the consequences of those decisions” (Taggart and Wilson 2005, p. 1). Reflective thinking is also a hierarchical construct, moving from the technical, to the contextual, to the dialectical, with each level building atop the other. The foundation of Taggart and Wilson’s (2005) reflective thinking pyramid is technical in nature, built from past experiences and the instructor’s ability to set learning objectives and to design activities in which learners are able to meet outcomes while using mobile technologies. It is at the technical level that instructors need to begin to identify teaching practices that help students achieve course objectives. A key component of this level is the honest assessment of the instructor’s own skills and knowledge of not only the mobile technology but also learner-centered pedagogical processes. In the technology-enabled educational milieu of this century, this may mean instructors thinking differently about engrained, traditional pedagogical practices and exploring the interconnections between subject matter disciplines in a globally connected society where learning is designed to “prepare young people for engaging in a complex and dynamic world deeply influenced by globalization and the revolution in digital technology” (Benade 2015, p. 42). It may also require shifting from instructor-focused didactic methods to a learner-centered model of exploration and inquiry that is made possible by devices that place knowledge in the hands of students to discover for themselves.

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In the twenty-first century, instructors must acknowledge the role science and technology has played in the transformation of higher education thinking and practice and of society itself. Most current postsecondary students have not known a world without the Internet, without mobile devices, and without digital media to shape their interactions and their learning. Students quite possibly may not “find what they learn at school to be important and relevant. . .without a transformation of the education practices and adoption of contemporary tools and information practices” (Churchill 2018, p. 67). Without, as Churchill (2018) has argued, “asking the fundamental question of what is learning and what to learn in the contemporary times” (p. 67), instructors may not be able to meet the learning needs of their students nor be able to prepare them for a world in which the speed and volume of information requires critical thinking and reflection-in-action (Schön 1983). This will, as Benade (2015) observed, require instructors and administrators to be “reflective about their core pedagogical values and beliefs. . .and the meaning of terms such as ‘education’ and ‘to be educated’” (p. 42). Reflective practice in teaching can be depicted concretely in terms of an ongoing cycle of thought and action (Mentis 2008; Mentor et al. 2011; Schön 1983, 1987). According to Mentor et al. (2011), this cycle begins with reflection and, from this, moves into planning and enacting changes. Then, the reflective instructor takes results from the process and analyzes them in terms of desired outcomes. The cycle begins again with reflection on the evaluation of the results. Through this conscious cycle, the reflective instructor engages in a conversation with practice itself, and: In this reflective conversation, the practitioner’s efforts to solve the reframed problem yields new discoveries which call for new reflection-in-action. The process spirals through stages of appreciation, action, and re-appreciation. The unique and uncertain situation comes to be understood through the attempt to change it, and changed though the attempt to understand it. (Schön 1983, p. 132)

Mentor et al. (2011) began with reflection; yet, some educators intentionally – and some, unintentionally – begin with incorporating mobile technologies, an action that is preceded by little reflection or inquiry into process, with evaluation and change then following a conscious reflection on that action. Linking back to Taggart and Wilson’s (2005) reflective thinking pyramid, “Selfreflection to interpret and inform practice and establish congruency between theory and practice would be indicative of functioning at a contextual level” (p. 4). Regardless of where that cycle begins, the process is a way in which instructors can develop an awareness of self and others in terms of teaching performance, its outcomes, and potential opportunities for further professional learning (Osterman and Kottkamp 1993). A growing self-awareness may lead to the recognition that teaching practices need to change because of changing circumstances – of content, of students, of delivery methods, or of institutional and societal pressures. Societal pressures can influence thoughts and actions (Osterman and Kottkamp 1993). In the traditional structures of higher education, the Socratic method of

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knowledge transmission is deeply rooted in common practice. Ironically, Osterman and Kottkamp (1993) questioned why instructors – who seek to improve their performance –are challenged to identify the specific thoughts and actions which prevent teaching success. This is particularly troublesome in light of the recommendation that in order to improve practice and to move from the contextual level to the dialectical level of reflection, instructors need to make time for collegial discussions and seek feedback from peers (Mentis 2008; Taggart and Wilson 2005). Currently, software and hardware have enabled collaboration and peer feedback regardless of geographic location and ready access to practice-based instructional tools and supports via the Internet. Yet, in the current postsecondary milieu of increasing workload demands and pressures to perform, finding adequate time to examine one’s practice can be difficult. As well, the very technologies that have been created to increase collaboration have served to decrease face-to-face interactions and erode academic identity (Kraglund-Gauthier 2014). An examination of actual practice brings meaning to an instructor’s underlying philosophy of teaching, but can also test assumptions (Benade 2015). Yet, by employing a rigorous strategy of reflective thinking to their course planning activities, instructors can identify how the current social contexts of twenty-first-century teaching and learning that incorporate digital technologies impact course design and delivery. When faced with potential changes to habitual thoughts and actions, it can be argued that only through reflection can instructors identify that to which they are resistant and why. This is certainly the case with learning to teach with digital technologies.

3

The Impact of Disruptive Technologies

In the mid-1990s, a time when computers and computing technologies were just establishing and place within educational contexts, Bower and Christensen (1995) realized the potential of emerging, user-friendly computing technologies to both disrupt and to yield opportunities. They identified an intersection between what consumers required from technology to improve performance and its overall trajectory as a performance-enhancing option in time. For Bower and Christensen (1995), “sustaining technologies tend to maintain a rate of improvement; that is, they give customers something more or better in the attributes they already value.” Disruptive technologies, on the other hand, have a flatter trajectory on the dimension of time because of their differences and the high switching costs for users. Included in these costs is the perception that the disruptive technology is no more effective than what is currently in use and familiar to users. Digital technologies, in particular, are sustaining and disrupting teaching, learning, and operations. For example, research by the Educause Center for Applied Research on mobile technologies in higher education has revealed that students are driving the adoption of mobile devices such as smartphones and tablet computers, with 67% of surveyed students believing that their mobile devices were important to their academic success and used them for academic purposes (Gikas and Grant

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2013). As MacLeod and Kraglund-Gauthier (2015) noted in research on infusing technology into preservice teacher education science courses, for their participants, “the notion of tablets and other mobile devices, Internet access, information accessibility, and ‘connecting’ are now part of daily personal activities and expectations of classroom learning” (p. 1). In traditional classrooms, “the receptivity and perceived legitimacy of new educational delivery modes is strongly related to the extent to which these instructional technologies reinforce or retain the central elements of the institutionalized and identity-enhancing classroom setting” (Jaffee 1998, p. 28). In 2006, the Berglund Summer Institute compiled a listing of eight conditions they felt contributed positively to the implementation of educational technology innovations. For the Institute, the presence of a particular “condition” was attributed, or “linked to,” a desired action or aspect of education that involved the implementation of technology (see Table 1). These conditions, which the Institute adapted from research done by Ely in the late 1990s, still hold true more than 10 years later (Al-Emran et al. 2016; MacLeod and Kraglund-Gauthier 2015; Niess and Gillow-Wiles 2016). Some argue institutionalized, traditional didactical structures of knowledge transmission have translated into a narrow concept of effective teaching, defined in terms of the cultural artifacts that embody its presence and function and that vary within the social context (Crawford 1996). These artifacts traditionally include lecture halls, Table 1 Conditions facilitating the implementation of educational technology Condition Dissatisfaction with the status quo Expertise

Description Feeling a need to change

Linked to. . . Leadership

Access to the knowledge and skills required by the user

Resources

Things needed to make it work – funding, hardware, software, tech support, infrastructure, etc. Prioritized allocation of time to make it work

Resources, rewards, and incentives; leadership; and commitment Commitment, leadership, and rewards and incentives

Time

Rewards or incentives

Internal and external motivators preceding and following adoption

Participation

Shared decision-making; full communication; good representation of interests Firm and visible evidence of continuing endorsement and support Competent and supportive leaders of project and larger organization

Commitment Leadership

Participation, commitment, leadership, and rewards and incentives Participation, resources, time, and dissatisfaction with the status quo Time, expertise, and rewards and incentives Leadership, time, resources, and rewards and incentives Participation, commitment, time, resources, and rewards and incentives

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desks, podiums, paper, and the physicality of an instructor and students (Friesen 2010). Furthermore, “actions and expectations around new teaching models alienated some staff, particularly those who saw themselves as guardians of the old ways” (Higgins and Northover 2011, p. 131). As Bailey (2002) proposed: For a large percentage of current teachers, the adoption of many educational technologies is a two part process involving 1) the reexamining of fundamental educational philosophy and pedagogy on the one hand, and 2) learning how to thoughtfully employ student-empowering applications of technology on the other.

This is still the case in our current educational contexts some 20 years later. For example, the scant research on mobile technologies and learning have focused on students’ access to content rather than an engagement with the content or the co-generation of content (Cochrane 2013). Yet, as support for learning that is enhanced by digital tools spreads throughout the academy, it is important to remain critically reflective on how “learning formats, pedagogical approaches and student achievement interact” (Lalonde 2011, p. 408). Furthermore, although an instinct may be to standardize practice in an attempt to reach a consistent quality, “shared practice does not entail uniformity, conformity, cooperation, or agreement, but it does entail a kind of diversity in which perspectives and identities are engaged with one another” (Wenger 1998, pp. 128–129).

3.1

Digital Technologies in Higher Education

Digital teaching and learning (or mobile, m-learning) has been a hot keyword in education in recent years because of the dramatically increasing penetration rate of mobile devices globally. Mobile devices have experienced very rapid changes from 2000 to 2014, with a reported 1.1 billion people using smartphones and tablets to access mobile Internet technologies (Manyika et al. 2013). This number has been estimated to be closer to more than 2.5 billion smartphone users in 2017, with China, India, and the United States as top usage countries (Richter 2018). By 2017, smartphones and tablet usage accounted for 70.7% of the total digital minutes used in the United States (Martin 2018). While mobile devices are currently used primarily for voice and text message communication, they are also used to send pictures, listen to music, record video, watch television, play games, surf the Internet, check email, manage schedules, browse and create documents, and more. Mobile technology and its complementary software applications and connections to real-time data via the Internet create opportunities for interaction, provide opportunities for collaboration, and enable students to engage in content creation and communication using social media and Web 3.0 tools (Dogtiev 2018; Gikas and Grant 2013; Mentis 2008). According to Manyika et al. (2013), “App downloads grew 150 percent in 2012, and . . .Time spent playing video games, emailing, and text messaging on mobile phones grew

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200 percent in the past four years” (p. 32). By 2017, the number of mobile app downloads had increased to 197 billion worldwide, up from 149.3 billion in 2016 (Statista 2018), and users spent an average of 2.3 hours on digital media each day (Dogtiev 2018).

3.2

Opportunities and Threats with Mobile Technologies

Mobile technologies, by their very nature, present both opportunities and threats for administrators and instructors to consider and mitigate, including, but not limited to, privacy, equitable access to technology, Internet access, and appropriate use. The pervasiveness of mobile technologies in higher education’s classrooms and educational spaces both on and off campus presents an opportunity for instructors to harness the power of these devices for learning. By recognizing the typical twenty-first-century student is connected to a network of peers and information, instructional strategies and learning activities both in an outside the classroom can become relevant, engaging, and responsive. It is inaccurate to assume, however, just because students seem to be technically savvy in their personal and social lives, that they are equally as savvy with using technology for learning (Ardies et al. 2014; MacLeod and Kraglund-Gauthier 2015; U.S. Department of Education 2015; Niess and Gillow-Wiles 2016). As Anders (2017) argued, digital tools can be used to create meaningful assessments for feedback or reflection, thus increasing versatility of formative and summative assessment strategies. For example, using mobile devices such as clickers and web-based polling are opportunities to engage students in real-time by providing responses to questions and to course content. Based on these responses, the instructor can modify teaching in real time. If most students respond with the correct answer to a problem in balancing a chemical equation, the instructor can move on to the next idea, while directing students with incorrect responses to additional learning resources. In a large class, the shy student who is reluctant to ask questions or volunteer comments out loud can contribute to the discussion electronically, thereby increasing engagement across and within the entire classroom community. In a Political Science class, the Internet can be used to stream live images of political uprisings as a conversation starter. A student can fact-check points quickly and unobtrusively before volunteering to contribute to a classroom conversation. Publishers and software engineers are also recognizing how connected students are to their mobile devices. Many course textbooks have available for purchase a PDF or e-text version, often at a substantially lower price. At Algonquin College, located in Ontario, Canada, for example, a campus-wide strategy to access only electronic textbooks from publishers or open access sites is expected to translate to student savings of over $2 million dollars by 2016 (K. MacDonald, November 26, 2014, personal communication). In addition, software companies now create mobile versions of software that address smaller screen sizes and bandwidth constraints. From a hardware perspective, if more students bring their own devices to campus (BYOD), demand for access to institutional-owned computers in student

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labs decreases. Moreover, incorporating learning management system tools and digital resources within course delivery methods also reduces paper and textbook costs, providing additional funds for long-term device purchases (Anders 2017). Overall, these opportunities translate to the potential of improving the student experience on campus, and customer satisfaction is crucial for financial success. The proliferation of mobile devices on and off higher education’s campuses does not come without threats. The lack of continuity of wireless data transfers between buildings and the different qualities of mobile signals in different areas are technical barriers to reach real anytime and anywhere mobile learning. On campuses with a high BYOD rate, investments in student computer labs are wasted. The unpredictability of the number of individuals wanting to access the intranet can cause system slowdowns and crashes. Besides this, the high costs of mobile data access and different mobile rates in different provinces and countries are also increasing the difficulties of adopting efficient mobile learning (Bridges and Traxler 2005). Institutions are at the mercy of data companies setting prices based on supply and demand. Ethical issues concerning mobile devices are abundant, and many of these issues translate to learning via a mobile device. With digital learning comes the issue of students located in countries other than in North America who wish to participate in classes within the continent. An ethical issue here is the different legal procedures and laws in general. In testing situations, mobile devices, especially wearable technologies, can be brought in the exam without being noticed. On a more personal level, with the ever-present mobile phone in campus dorms and other social spaces, the potential for privacy invasion is significant, as is cyberbullying. If an objectionable event goes viral, it is difficult to reverse a negative image of the institution as a whole. As with many new technologies, the biggest concern for users and also the most significant ethical dilemma is the security of sensitive information. Institutions of higher education collect a great deal of personal information about their students’ mobile technologies using unsecure Wi-Fi threaten to expose this sensitive information to anyone who may have the capability to gain access to the technology used to store and analyze information. With data becoming more mobile, the threat of security breaches increases (Kraglund-Gauthier and Young 2014) alongside the need to protect student information (Anders 2017). The privacy laws in the United States, for example, are different than the ones in Canada, and the institutions providing the course via mobile learning could be accessing information of students that is legal for them to do in Canada, but not legal in other locations across the globe. Students participating in a class from another country may not be aware of the ability and right of their institution of choice to access and use their personal data for any purposes they wish to use it for (Bridges and Traxler 2005). With challenges such as these creating wariness and mistrust, it is little wonder that mobile technologies have yet to be firmly established as legitimate and powerful tools of teaching and learning. Higher education stakeholders need to anticipate these threats and put into place privacy policies, rules regarding data storage and appropriate use.

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Key Considerations for the Integration of Digital Technologies

Specific departments within the institution have different functions and different technology needs; therefore, a variety of software programs and hardware must be purchased. Technology is a significant expense, and decisions for implementation must be proactively made that align with the institution’s overall academic and operational goals. The needs of instructors in one department need to be considered in relation to the needs of other departments, and key decision-makers will need to balance the distribution of desired technology with essential technology. These programs and technologies must also be chosen based on how long they will serve the institution’s needs and in consideration of hardware refresh rates and necessary software upgrades, and decision-makers must ensure that any investment made will be sustainable and that the selected technology is not anticipated to become obsolete too soon. As well, the potential impact of the technology must be assessed from various perspectives. Digital and mobile technologies provide avenues for flexible, personal learning for different groups in the same classroom and enable individual discovery (Anders 2017; Kukulska-Hulme and Traxler 2005). Additionally, mobile and data services offer potential for new methods of teaching and learning; for example, the emerging field of wearable technology has the potential to take learning anywhere. Real-time exchange rates, interactive management activities, synchronous communication, and global collaboration can also be brought into the classrooms at anytime and from anywhere. With digital technologies, students have access to a wealth of knowledge via their connections to campus libraries and to businesses that have a web presence. An important distinction here, though, is the difference between the formal use of technology for learning versus its informal use. In their research on student perspectives of learning with mobile devices, Gikas and Grant (2013) distinguished formal learning as occurring when students “are engaging with materials developed by a teacher to be used during a program of instruction in an educational environment, highly structured, institutionally sponsored, and generally recognized in terms of a certificate or a credit upon completion” (p. 19). In contrast, informal learning is less structured, but similarly intentional and contextualized, encompassing Internet searches, clicking highlighted links, and reading social media. In the higher education classroom, formal learning via a mobile device can, for example, include accessing resources and contributing to discussions in a course-based learning management system. It can also include using peripheral attachments on smartphones and tablets to collect magnified images of species and specimens during fieldwork, using data probes to collect temperature and air quality readings to import directly into a shared spreadsheet or database. Digital and mobile technologies and their associated applications cannot be successful in isolation. An engaging instructor and effective curriculum design with inspiring content are vital for a successful technology-enhanced learning program (Mentis 2008). When “problems are often seen as an indicator of incompetence and failure” (Osterman and Kottkamp 1993, p. 21), specific competencies in

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creating and displaying content requires a comprehensive understanding on different types of hardware and software as well as new developed technologies in telecommunication industry. Well-designed course content can include not just readings and discussions but also incorporate the interactive, communicative functions on mobile devices (Oblinger and Oblinger 2005). Functioning effectively in the media-rich classrooms of the twenty-first century requires a skillful and appropriate application of technology that is linked strongly to the curriculum. Students use mobile phones in smaller time slots, such as when waiting for friends or when traveling on public transport, to perform numerous tasks beyond merely texting and calling contacts. Students now use mobile devices in these time slots to engage in other social activities and to search for information and even work on assignments. A well-designed activity should make use of these smaller time slots, in particular in the form of micro-learning materials such as short instructional or review videos and reinforcing activities such as definition and concept reviews in the form of flashcards or quizzes. Because of technology and Moore’s law, students can carry hundreds of electronic books on one electronic device and access academic resources virtually instantaneously. Students and instructors alike can access virtual classroom space with personal mobile devices, and a volume of data is available at one’s fingertips. The smaller screen size and limited input options are key considerations, however. Mobile access has its limitation on the size of content, how it is designed to display on a screen, and how interaction is made. Videos can be valuable resources for learning but may be cumbersome and inefficient on mobile devices, and it may be hard to read subtitles. Similar to traditional learning environments, interactive functions and social communication are also effective ways to engage students and increase long-term memory. Discussion between students and communication with instructors help students to understand the materials and to apply their knowledge in real cases. Constructive feedback from students also helps improve instruction. As well, when designing an effective learning activity that incorporates mobile technologies, instructors must consider the different characteristics of mobile devices and of mobile learners themselves. Individuals’ past experiences, prior knowledge, and personal views and opinions tend to impact on the types of activities required for learning (Vygotsky 1978) and “their interpretations of the purposes or goals of an activity” (Crawford 1996, p. 44). Whether the learning tool requires the use of data and a reliable Internet connection and whether students have and can access data are other key considerations.

5

Future Directions

As higher education’s classrooms fill with twenty-first-century learners who are accustomed to learning with mobile devices, it is imperative that all stakeholders work to resolve the tension emerging from the mismatch of technological tools and platforms, instructional pedagogy, and the teaching and learning context of instructors and students. “Change is ubiquitous and relentless, forcing itself on us at every

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turn” (Fullan 1993, p. vii). It is imperative that stakeholders in higher education acknowledge and address the need for a focus on the art and craft of teaching – regardless of tools used – rather than a concentration on the technical mediums of content delivery and learning activities. Instructors with a vested interest in improving student learning “have to ride each new wave of technological innovation in an attempt to divert it from its more natural course of techno-hype, and drive it towards the quality agenda” (Laurillard 2005, p. 71). The issue is separating the hype from the demonstrable “best” practices. Instructors need to shift their own thinking about pedagogical processes to address the dynamic and shifting nature of teaching and learning in classroom milieu infused with students’ personal mobile devices. In order to thrive in the twenty-first century, all levels within institutions of higher education need to accept and leverage digital and mobile technologies to transform the way instructors engage with their students and how they provide innovative educational experiences and deliver content. Results from previous research (Kraglund-Gauthier 2014) indicated that the more experience participants have with technology, the more confidence they have in their own abilities to use that technology. Yet gaining more experience carries with it a commitment of time – a finite commodity for any instructor; furthermore, developing content matter knowledge tends to be prioritized over developing content delivery methods. Instructors who focus on constructivist pedagogical activities can efficiently maximize on students’ engagement and motivation, and, in turn, their students will feel a sense of connection with instructors and classmates. How instructors engage their students is due, in part, to the creation of spaces that are conducive to exploration and experimentation with mobile technologies that move beyond mobile technologies as “purely social tools for informal use into powerful tools for enabling student-generated content and collaboration within student-generated learning contexts” (Cochrane 2013, p. 255). It is through active reflection and engagement that an instructor can identify and attain high standards of teaching and develop expert knowledge that leads to self-efficacy and self-actualization for themselves and their students (Bandura 1993; Taggart and Wilson 2005). “The stronger the perceived self-efficacy, the higher the goal challenges people set for themselves and the firmer is their commitment to them” (Bandura 1993, p. 118). With self-efficacy and commitment established, the integration of mobile technologies is sustained. Clearly, it is incumbent on the instructor to think critically about the process of learning and the quality of desired learning outputs when making decisions on what technologies to incorporate into a course’s learning activities. “The adoption of an innovative technology brings into question the fundamental pedagogical beliefs, the technology is marginalized or rejected until it can either be incorporated into the educator’s existent pedagogical model, or until the model itself evolves” (Bailey 2002). Pedagogical processes, reflective thinking, and the frameworks of Bloom’s (1984) Taxonomy of Educational Objectives and Taggart and Wilson’s (2005) reflective thinking pyramid serve as guiding principles for designing learning activities, not only for students but also for instructors’ own acquisition of knowledge and applicable skills in teaching with mobile technologies. Reflection-on-

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practice has the potential to inform the types of goals instructors set for themselves when learning to incorporate mobile technologies and can reveal changes in perspective in the values, beliefs, and actions that form one’s pedagogical identity and shape practices. Mastering the techniques of teaching with digital technologies may not be an intuitive, simple process; furthermore, instructors “need to see learning to teach as an ongoing process with more challenging than easy answers” (Weimer 2010, p. 157) and to accept technology’s disruption of existing instructor-centered power relations. As in any professional industry, the higher education instructor’s skill in wielding the tools of the trade is one that improves over time with practice, developed and sustained through research and theory.

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 A Brief History of e-Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Key Trends in e-Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Web 2.0-Based Technologies and Tools for Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 The Technologies for Web 2.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Mobile Learning (M-Learning) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Mobile 2.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 How to Design M-Learning Using Web2.0 Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Creating Online Mobile Courses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Elements of Online Courses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Online Tests and Quizzes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 How to Make e-Learning Effective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Case Study: Mobile Web 2.0 e-Training for Vocational Education Trainers (Project MOBIVET 2.0) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Mobile Learning Course Preparation Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 MobiVET Mobile Learning Courses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Today, over six billion people have access to a connected mobile device and for every person who accesses the internet from a computer to do so from a mobile device as well. Mobile technology is changing the way we live and it is beginning to change the way we learn (UNESCO, Retrieved from http://www.unesco.org/ new/en/unesco/themes/icts/m4ed/, 2014).

Z. Palkova (*) Department of Electrical Engineering, Automation and Informatics (TF), Slovak University of Agriculture in Nitra, Nitra, Slovakia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_73

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Mobile Learning (m-learning), referred also as “anytime and anyplace learning,” has evolved with the introduction of mobile and hand-held devices, such as mobile phones, laptops, notebooks, and tablet PCs, in teaching and learning, together with broadband and wireless data transmission. This greater connectivity creates opportunities for flexible, collaborative modes of learning, while supporting stronger links between learning at work, in the home, at school, and in the community. As the main advantages of mobile technologies in education can be consider: • spontaneity – learning activities take place when the learner feels ready, or can be used to fill “dead time” • immediacy – learning becomes possible at the point of need, regardless of location • increased access – learning resources can be accessed from the workplace and in the field, while traveling, during classes and lectures • portability – communication with peers and tutors; and the capture, storage, and retrieval of information in multimedia formats are possible from one device at any location. This chapter aims to present the new trends for education – mobile learning, through the outcomes of the Leonardo da Vinci project MobiVET 2.0 – Mobile Web 2.0 e-Training for Vocational Education Trainers (MobiVET 2.0, Retrieved from www.mobivet2.eu, 2014). The MobiVET 2.0 project aimed at filling the online training gap between the self-directed learners and VET trainers by developing mobile e-learning 2.0 knowledge and skills of the trainers thus turning them from in-class trainers to skilled online tutors (etutors).

1

Introduction

From the last 10 years, e-learning technologies use interactive multimedia and allow user-interaction with controlling computer software programs and may be used effectively in education and training (Zhang 2015). Sophisticated computer hardware and software are available for the production of high-quality flexible training materials and at low cost. Interactive learning materials enhance the learning process; are enjoyable; and, using wireless networks, may be used anywhere, at any time, and by anyone. An individual has the freedom to learn at one’s own pace, to select the appropriate level, and to pick times for study so as to be able to study at work, at home, or in travel. The use of this forms of materials, if prepared carefully and comprehensively, can eliminate the need for face-to-face workshops, seminars, conferences,

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site visits, and attendance at technical fairs, saving time, travel, and fuels and so also reducing polluting emissions to air.

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A Brief History of e-Learning

In the last century, an effort to carry out educational process through new technologies occurred when, at the half of twentieth century, linear (Skinner 1954) or ramified (Crowder 1969) training programs were used within the program learning in order to increase the effectiveness of the educational process. In the coming years, this effort was supported by some philosophical theories, (Wiener 1961) characters of which became to be a basin for some programming languages (e.g., Prolog, Cobol). In a field of hardware, development carried over air-conditioned computer halls on to work tables in the form of PCs; however, at the turn of the 1970s–1980s, information and communication technologies occurred in the educational process without any complex conception. Attention was focused on the study of informatics or on programming as individual study subject. Start of multimedia computers provided more options for video and audio presentation. Requirement on training programs’ interactivity is highlighted and view on possibilities of ICT application in education significantly changed. A beginning of new millennium brings a necessity of lifelong learning, causing a development of distance learning based on principles of ICT exploitation in education. “Internetization” of all levels and forms of schooling is getting to be one of the main program objectives of the EU states’ national governments; various “information strategies” are being formed and virtual training centers interconnecting universities, libraries, research institutes, government, public, and commercial organizations are being created (e.g., Virtual Collaboration (Hossain 2004; Wainfan 2004)). Historically, educational and corporate training managers have always looked for ways to reduce the cost and improve the effectiveness of training programs and processes through the use of technological advances. Prior to 1980, in-class instructor-led training dominated, although some organizations used mainframe and interactive video approaches. By 1990, the delivery of CD-ROM content became possible. Since 1998, Internet-based approaches (e.g., Web Based Learning) have become the dominant delivery method for creating fast, scalable, low cost learning and corporate training (Fig. 1). Those methods usually follow the “classic” form of class-based learning, moving only the content from the paper book pages on to the computer screen. The participants in the process (teachers and students) still remain “tied” to the school LAN, which connects them to the learning content and the school Learning Management System (LMS). The “traditional” pen has been replaced by the keyboard and mouse. But, in most cases, these changes do not give the freedom that teacher’s and student’s “hands” may need – especially teaching and studying some specific subjects, such as art, drawing, design, and architecture.

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Fig. 1 Evolution of e-learning technologies

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Key Trends in e-Learning

During the last few years, e-learning has rapidly entered the educational sector and, as a result, more and more new learning tools are appearing. This changes the way how teachers and students work and interact, thus enabling a more effective learning process. Advances in ICT define the latest trends in the e-learning industry. New hardware devices and application programming interfaces (APIs) are shaping the present and future of how learning organizations will manage e-learning. In the present time, new technology developments are making their way into e-learning delivery. Some of the more significant trends in e-learning include (Learndash 2013): – Social Networking Services (SNSs): are virtual communities of practice constructed through SNSs enable learners to connect and collaborate on global platforms, transcending geographical boundaries (McCann 2009). – Massive Open Online Courses (MOOCs): It is possibly the most promising trend as more and more courses will be published online offering a free (open) access to the learners. – Gamification: learning (or “serious”) games and simulations (in 2D and 3D worlds) can be implemented quite easily into many e-learning courses and learning management systems (LMSs).

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– Mobile technology: includes devices like netbooks, e-book readers, tablets, smartphones, and Wi-Fi communication technology that are allowing e-learning to be on-the-move. – HTML5: This new web publishing standard offers better performance, multimedia, connectivity, and many other benefits for e-learning content design (W3 2014). – TinCan API: is the next generation of API software developed for the reporting of e-learning in LMSs used. TinCan API is expected to replace the old SCORM standard (Tincanapi 2014). – Responsive Web Design (RWD): focuses on mobile technology and it is intended that web content displays properly on all devices (no matter desktop or mobile). Good examples of using above-mentioned technologies can be found, for example, in: De Lima and Zorrilla 2017 – An Experimental Study of a Social MOOC Albayrak and Zahide 2015 – Facebook as a course management system Liyanagunawardena and William 2014 – Massive Open Online Courses on Health and Medicine (Palkova 2014) – Gamification.

3.1

Web 2.0-Based Technologies and Tools for Learning

By Tim O’Reilly (2007) who firstly has defined the term “Web 2.0,” it can includes online services such as blogs, wikis, podcasts, RSS feeds etc. These technologies facilitate a more socially connected Web where everyone is able to add and edit the information space. Main ideas of Web 2.0 change the key aspects of schools’ curricula and form of learning (Bartolomé 2008; JRC 2009): – NET technology as a platform oriented on multiple tools change the concept of the learning anytime and anywhere – Collective intelligence and wide experiences of users influence meaning of the expression “authority” in learning systems – Tags and RSS give opportunity to repeat browsing of traditional systems, organization of knowledge, and finding information – Lots of alternative tools used for the learning activities (tablet, smartphone, notebook, netbook, etc.) give the learners the possibility to learn anywhere and anytime – in cafeteria or library, waiting on the train, etc. Web 2.0 deletes the difference between time for study and other activities. Web 2.0 represents a new term for e-learning. What makes Web 2.0 so attractive for learners is that it is almost free, interactive in nature, and could be accessible from anywhere and via any mobile device. Because of the accessibility feature of Web 2.0 applications, learners are now able to interact in a virtual community and be exposed

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to sounds, images, moving pictures, colors, and text that are characterized to be ideal for the cognitively diverse classroom (Kelly 2011; Downes 2005). In this context, the Web 2.0 is the next level of the World Wide Web (W3 2014). The most basic characteristics of Web 2.0 include: – – – – – – – –

The read/write web The web as a platform Rich user experiences Data as the driving force An architecture of participation Harnessing collective intelligence A rich, interactive, user-friendly interface Leveraging of popular trends, including blogging, social tagging, wikis, and peerto- peer sharing – Inclusion of emerging web technologies like RSS, AJAX, APIs (and accompanying mashups), Ruby on Rails, and others – Open source or sharable/editable frameworks in the form of user-oriented “create your own” APIs New innovative learning methods require new training methodologies, as well as new ways to deliver the learning content to the target groups, considering the growing need of mobility, availability, information aggregation, and very fast response times among both students and adults in the labor market. Between up-to-date Web 2.0-based technologies and tools for e-learning we can include: – RSS Feeds (Rich Site Summary), which offer the ability to automatically fetch new content instead of having to search for it. By using special software called RSS aggregators, teachers or trainers can subscribe to multiple web pages that publish material relevant to the subject that they teach. This way, students can visit a single place that is constantly updated when new articles are published. Feed aggregation clients are available for all platforms, including mobile devices. – Audio/Video Conferencing refers to services and tools that allow conferencing events to be shared with remote locations. These are sometimes referred to as webinars or, for interactive conferences, online workshops. These tools can be used to record and share live events. The teacher/trainers can use them to cover a real-time event such as a lecture or a tutorial, to capture teaching resources, and, at the same time, to allow students to collaborate with their own responses. Example tools: Skype, BigBlueButton, Electa Live. – Online Presentation Tools give teachers or trainers the ability to share their presentations as well as enhance them with added functionality and taking advantage of user feedback to replace traditional desktop presentations. These tools have no software requirements since everything is done online through the web browser. The presentations can be embedded into websites, blogs, and wikis and can be used by students and teachers to collaborate remotely. Example tools: Voicethread, Prezi, Slideshare.

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– Social Media/Networking Applications offer users the ability to easily communicate and share resources. Most of them offer capabilities to create groups or communities so they can be used for specific courses or learning topics. The main advantage of these applications is that the students are already familiar with their use and are highly motivated to use them. Example tools: Facebook, Twitter, LinkedIn, Edmondo, Elgg. – Content Management Systems allow publishing, editing, and modifying content as well as maintenance from a central interface. Such systems of content management provide procedures to manage workflow in a collaborative environment. Furthermore, they can easily integrate most of the above technologies. Learning management systems are specialized for the needs of teachers offering a great set of tools for every aspect of the learning experience. Examples tools: WordPress, Drupal, Moodle, Schoology. More information can be found, e.g., in (Lee and McLoughlin 2010; Parusheva et al. 2018; Palková et al. 2014).

3.2

The Technologies for Web 2.0

Web 2.0 is not a new network technology but a network application (Anderson 2007) and the most used techniques that Web 2.0 website uses can be defined as follows: – Cascading Style Sheets (CSS), semantically valid XHTML markup, and microformats – Significant and clean URLs – Aggregation of RSS/ATOM data – Syndication of data in RSS/ATOM – REST or XML Webservice APIs – Some social networking aspects – Support posting to a weblog The base principles of Web 2.0 are creation of new relationships through electronic connections and social collaboration. Between main concepts that have been created for Web 2.0, we can include: – Mashups, which allow use of services from different users for creation of completely new service – Tagging, which are keywords represented by nonhierarchic metadata which allow to descript the content and find topic by browsing or searching – Folksonomie, very often referred as social tagging, allows users to tag their content, and enables other user to find and use it – Blogging is one of the most characteristic features of Web 2.0 and Tim O’Reilly’s (2014) basic form of blog defines just as a personal home page in diary format

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– Virtual worlds represent simulated 3D environments, usually gaming environments, which allow users a mutual interaction with the environment and between characters known as avatars (Palkova, an innovative virtual reality educational environment for school physics education: Slovakia Case, 2017), (Palkova and Vakhtina, Innovative learning: From multimedia to virtual worlds, 2015) Web 2.0 technologies offer new methods for learning delivery by providing teachers with new ways to engage students and even allow student’s participation on a global level. Web 2.0 tools are online and mostly free applications that can be used in innovative ways by teachers or tutors to support their teaching. Teachers have new ways to express their learning materials and share them with the students and other teachers, as well as allowing them to collaborate with their own ideas or resources. Audio and video sharing is easier than ever and allows learning sessions to take place online, instead of the classroom, in ways that can be more motivating and exciting for students. The vast amount of information available online can finally be organized by taking advantage of social bookmarking tools. Students, in a Web 2.0 classroom, are expected to collaborate and to interact only with one another and the content of the class. But by making a shift to a Web 2.0 classroom, teachers are creating a more open atmosphere where students are expected to stay engaged and participate in class discussions.

4

Mobile Learning (M-Learning)

Mobile Learning (m-learning), referred also as “anytime, anyplace learning” (Caudill 2007; El-Hussein 2010), has evolved with the introduction of mobile and hand-held devices, such as mobile phones, laptops, netbooks, and tablet PCs, in teaching and learning, together with broadband and wireless data transmission. This greater connectivity creates opportunities for flexible and collaborative modes of learning, while supporting stronger links between learning at work, in the home, at school, or in the community (Figueredo 2015). From this point of view, mobile learning allows truly anywhere and anytime, personalized learning, which through nonconventional devices and methods make traditional lessons or courses more attractive. Using mobile communication – for young people native forms of communication – helps learners and teachers to recognize and build on existing basic literacy skills and can help deliver and support literacy, numeracy, and language learning. At last but not least, mobile learning helps to combat resistance to the use of ICT by providing a bridge between mobile phone literacy and PC literacy. At present, a great variety of mobile computers and devices are available. Laptop computers outnumber desktop computers, while notebook computers, tablets, and cellular “smart” phones are considered to be the most important hardware items used for m-learning activities. Mobile devices can bring users the following advantages (Learning 2014):

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– Spontaneity – learning activities take place when the learner feels ready, or can be used to fill “dead time” – Immediacy – learning becomes possible at the point of need, regardless of location – Increased access – learning resources can be accessed from the workplace and in the field, while traveling, and during classes or lectures – Portability – communication with peers and tutors, and the capture, storage, and retrieval of information in multimedia formats are possible from one device at any location.

4.1

Mobile 2.0

Mobile 2.0 is considered to be the combination of the Web 2.0 philosophy with the mobile devices. Firstly, Mobile 2.0 is bringing the Web 2.0 to the user’s mobile device. In addition, Mobile 2.0 goes further in the adaptation of web content to the user’s mobile device and also the personalization of the content the user’s characteristics. Thus, a key point to Mobile 2.0 is leveraging Web 2.0 to take advantage of the strengths of user’s mobile device. Mobile Web 2.0 applications that are delivered to mobile devices need to be adapted to the characteristics of the mobile devices. Several years ago the big question was “Should we do mobile learning?” Today the question is “How should we do mobile learning?” TeachThought (2014) defines 12 principles of mobile learning: – – – – – – – – – – – –

Access (any time, any place) Learning metrics Cloud (content and learning delivery via cloud) Transparent Play (include serious games and gamification) Asynchronous learning mode Self-actuated (personalized: just in time, just enough, just for me) Diverse e-pedagogies Curation/learning management Blending different learning modes Always-on Authentic

4.2

How to Design M-Learning Using Web2.0 Technologies

Adopting a mobile-friendly content strategy enables many benefits that go far beyond delivering the right learning content to the right device at the right time – including collaboration via social networking platforms, multimedia (audio and video) enhancements, interactivity (quizzes, simulations and exercises), annotations to content, and much more.

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But what is the most efficient way to produce and deliver learning content optimized for the unique dimensions and firmware of every mobile device? How do the mobile learning designers enable the interactive features that make the content more than just a “page turning application”? These are just some of the questions that a mobile content strategy need to addresses. The instructional design is a systematic process for creating effective instructional solutions. This requires designers to analyze the desired outcomes and content and apply the appropriate design model to achieve the learning outcomes. The instructional design of m-learning solutions must first consider the fact that learner is not in a traditional classroom setting with a motivational and/or supervisorial instructor facilitating the learning process. Learner motivations, attention to learning content, understanding of the relevance of the subject matter, and ability to have social interaction with peers are not as easy to facilitate. The mobile learners can acquire learning content from the centralized shared resources and engage in anytimeanywhere context-aware learning via portable devices in wireless communication environment. E-learning design can only be generically applied to m-learning. Many of the current elements of m-learning are built upon a solid foundation of learner needs, learning outcomes, cognitive processes, and instructional strategies. Each of these foundational elements is critical for the creation of effective m-learning and involves a strong collaboration between instructional designers, educational technologists, graphic designers, web/software developers, educators, and students/users. However, m-learning instructional design as an emerging subject requires a more dynamic approach than traditional instructional design. Therefore, the need for more dynamics in instruction combined with the high demand for more m-learning solutions requires an evolution in m-learning design and a higher level of productivity. More use of current user-centered and evolutionary design methodologies like that of Agile design (Agilemodeling 2014), rapid prototyping, and successive approximation, instead of the antiquated and less iterative methodologies such as ADDIE model (ADDIE 2014), will allow m-learning designers to create more robust m-learning solutions rather than the typical unidimensional solutions currently being developed. In addition, in order to meet the need for increased productivity in m-learning, it is clear that there should be more use of rapid development applications. The reality is that creating m-learning solutions is more time consuming than traditional learning solutions; therefore, using software applications that do not keep up with the high demand for productivity does not allow the actual design to make it into production on regular basis. At present, it can be concluded that m-learning will continue to use some of the same software applications and more iterative instructional design methodologies in order to keep up with increased demand in the coming years.

4.3

Creating Online Mobile Courses

For creating mobile courses, there are a number of clear instructions that one needs to follow to make sure that the course is accepted more readily by the interested

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students. First and foremost, one needs to look at the content to determine what the aims and objectives of the course are, and what one envisages in the students to achieve once the course is finished. These aims and objectives should give the content provider a clear understanding of what to include or exclude in the course, as well as an indication of the most appropriate delivery mechanism of each of the objectives. Once this is established one needs to decide how to create appealing and interactive ways of delivering the content. A recent phenomenon is through the use of interactive applications and websites that are usually used online – such as interactive whiteboards which have facilitated and promoted the process further. On the other hand, one can see a number of e-learning tools today that are used individually on one’s own computer, smart phone, or tablet which facilitates individual learning. Whatever the medium used, the course designer should make sure that the content appeals to the target audience, and that the graphics and interactive tools used are neither too difficult nor too easy. There needs to be a balance between a challenge and extreme difficulty that may motivate or alienate the student. One should remember that a picture or a video speak a million words, so when possible one should provide the student with a graphic or picture, rather than a lot of text. However when using text, it is important to use appropriate, easy to read fonts and sizes as well as colors. Some fonts may be appealing to the eye but are hard to read. For instance, small fonts are usually used when a lot of text is concentrated in one page, deviating attention. Making it difficult to read colors or small fonts will put off anyone reading the text. When speaking about interactivity and graphics, one needs to keep in mind one very important factor. It is important to see whether the application/website can be accessed offline when the person doesn’t have internet facility. Another consideration that one needs to make is to see that the application/website looks and works well across all operating systems and on all devices. Finally, it is of utmost importance that the course content and tool in which this is embedded works smoothly and fast when accessed, since otherwise it would only frustrate the user and demotivate him/her. The first priority on the list when designing a course should be identifying the target audience. Anything proposed should be done so with that in mind and it should be easy to use, it should capture the attention of the user, and it should be motivating and intriguing. While different people have different concentration spans, others might have special needs to consider, such as cognitive conditions or physical difficulties. These specifications should be taken into consideration by the content provider who should make sure that all the kinds of people who are within the target audience bracket are able to access and use the course equally. These difficulties can be overcome by introducing blended learning, where the student may be able to focus on one method of learning which is more suitable to him/her. On the other hand, community e-learning, where groups can learn together online, is a form of peer teaching that can aid people with special needs to learn from different sources and with people who are similar to them. ICT tools can also be made in a way that can be adjusted according to who is using them, for e.g., with a lot of graphics for the hearing impaired or have a screen reader for the visually impaired and so on.

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Finally, in these cases where one is using ICT to teach, it is important that when there is an actual teacher who is physically facilitating the learning, the teacher is very fluent and competent in both the content and the media used to ensure that the students do not lose interest feeling that if the teacher can’t do it. On the other hand, these tools can always fail, hence a good 24/7 help desk should always be available for those users with difficulties and questions.

4.4

Elements of Online Courses

When creating an online course, a number of criteria must be met to ensure that students receive the benefits they signed up for. Below is a list of important ones:

4.4.1 Consistent Instructor Presence: The Value of Feedback The role of the instructor is very important in the e-learning process because it’s in his/her hands to encourage, inspire, and ensure that students do not feel as though they have embarked on this learning trip alone, and also because it will ensure that students will be tracked and given proper feedback which is very important throughout the learning process. To facilitate such a relationship, learning management systems offer options like instant messaging between peers, email, and other tools that ensure that the learner and professor are only a click away from each other. 4.4.2 A Streamlined and Well-Designed LMS When talking about the success of a LMS, we primarily mean that we want an e-learning site that is easy to navigate, is well-organized, and contains high quality material. Everyday tasks include the distribution of new materials and sending, receiving, and grading assignments. A well-designed LMS will ensure that those tasks are hassle-free and that its users can easily tap into the myriad of features that are an important part of the e-learning process. 4.4.3 Content that Is up to Par Apart from the ease and design of your LMS, the next most important thing to keep a student satisfied is the learning content. The role of the curriculum is to set the tone for an organization to design a successful course and offer both teachers and learners a set of guidelines. So while a system must be well-designed and efficient, the quality of the content must be on par with the impression you want the LMS to make in its entirety. 4.4.4 Tested Delivery Methods Let’s start with an example: you are running a course on astrophysics and you have found a very interesting video that you feel enhances the points made within the already existing content. Is adding the said video to the material the right move? As with any other website, application, or product, compatibility is always a delicate matter. We need to always be sure that the material we post for learners to use is compatible with all the possible web browsers or platforms being used. To avoid

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discouraging learners, keeping it simple is preferable over overextending ourselves and possibly hitting an incompatibility roadblock. All of these key elements have the ability to foster a supportive, effective e-learning environment. When all of these essential components are in place, online learning establishments have the ability to not only provide students with the skill sets and knowledge base that they are looking for, but a virtual education platform that helps to contribute to the future success of (and serves as a model of excellence for) the e-learning industry.

4.5

Online Tests and Quizzes

Despite the fact that e-learning lacks the element of physical presence, tests and quizzes are still essential parts of the educational process. Through online tests and quizzes an instructor is able to track the progress of students and assess the effectiveness of the curriculum, while at the same time giving students the ability to track their own progress and improve on their skills accordingly. Tests and Quizzes play an important role in e-learning and provide an array of benefits for both the learner and the instructor. Let’s first look at how they improve the experience of the instructor. Testing and quizzing can be made unique in a LMS by randomizing question and answer order. This is especially useful when a learner has to redo a test which he/she previously had poor performance on so that the test is not completed by memory, but rather by actually thinking through the correct solution once again. This feature is also useful to produce more variety by using a large pool of questions from which testing can be done, rather than recycling the same questions over and over.

4.5.1 Instant Grading and Feedback Grading and giving feedback is probably the most time consuming task for an instructor. It’s where the instructor has the ability to comment on the strengths and weaknesses of a learner and enable learning to actually take place! Feedback needs to be good. A LMS will usually allow the instructor to create dynamic feedback depending on the answer a learner will give to a specific question. For instance, in a multiple-choice test if the learner chooses answer B over the correct answer C, the appropriate feedback will be given back to the learner, indicating fault in the thought process or hints as to why another answer would be more appropriate. This complements point 1 above (i.e., “Less work to be done”) by the instructor because it allows the learner to get instant feedback on a correct/incorrect answer, and it saves time for the instructor who can take advantage of automated feedback. 4.5.2 In-Depth Analysis Readily Available Tests have to be gathered and graded, and feedback has to be written for the individual learner to take back and improve on particular areas. Learning management systems give the instructor even more thorough analysis. Through a reporting system, a LMS gives the instructor an overview of test scores, progress,

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and growth with graphical representation to make the analysis even easier to grasp especially when the class size is very large. That way, an instructor has the ability to analyze which students scored highest/lowest and which questions were hardest/ easiest for the majority of students. Reporting is a handy tool that allows the instructor to see trends and act upon them to improve the curriculum.

4.5.3 Self-Assessment Tool Testing and quizzing online will usually provide the user with results instantly. This is good for students because it allows them to know what they did wrong immediately, what they need to focus on, how to improve, and/or should they have to retake the test. 4.5.4 Keeps Learners Engaged Tests and quizzes have always been a motivator to study harder when students know that their progress will be judged upon an exam, a performance review, etc. It sets a deadline for when material is due to be learned and diligent students know they must adhere to that. 4.5.5 Further Considerations The use of different forms of testing, such as multiple choice tests, fill in the blanks, true or false, or essay questions can also be used to assess the progress of students with different learning styles. Catering to the needs of different learning styles is an important aspect of e-learning which gives it the edge over traditional learning models. It is a good idea to use different types of material and varying types of tests and quizzes to engage everyone in an online class. An important note to remember when creating online quizzes and tests is the ability of a learner to research the web for answers. If something is too hard and/or a little off topic in terms of the material taught, it is likely to be researched online. If the tests are too easy, they will be dismissed and passed over without much being learned. Thus tests should be structured in a way to encourage learners to think back to the material taught within the course rather than looking for answers elsewhere.

4.6

How to Make e-Learning Effective

Anyone may be able to create a simple online course. However creating an effective e-learning course is very different. An effective course takes a good deal of time, hard work, and commitment to high quality content to create. Here are some tips that can help you create a highly effective e-learning course regardless of the material or curriculum:

4.6.1 Know your Subject Material Well! There is no golden rule on how much time you need to put into creating the ideal content, but one thing is certain: you need to take your time to research material

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before making it available to your learners. The reasons are simple, you want to be prepared to backup any claims made within your course material, not all learners digest information the same way, and some may need more explanation through examples or further proof.

4.6.2 Online Courses Provided Should Appeal to all Learning Styles The design of the online course should take every learning style into consideration. For example, while one student may benefit from visual multimedia presentations of coursework and lessons, another student may be able to better absorb the information when it is presented in text form. An effective e-learning course always takes these various learning styles into account when the lessons are being created. 4.6.3 Facilitate Contact Students and teachers should be able to establish an open line of communication. Also, teachers should specify which means of communication they prefer and during which hours. This will ensure that expectations are met and that the student receives the help or support that they need. Also, students should have contact information for the systems’ IT support staff, and have access to a member of staff on a regular basis if needed. Examples of how students can communicate with their instructors are: discussion forums, social media, chats, email, video conferencing, and other VoIP technologies. 4.6.4 Platform Should Be Easy to Navigate and Fully Functional When designing the site and e-learning platform, the ease of navigation and functionality should be top priority. A well-organized and intuitive web-based learning platform enables students to focus on the coursework rather than having to sort out technical issues that may arise from poorly designed sites and systems. 4.6.5

Course Documents Should Be Available to every Student Enrolled Course documents like the syllabus must be available for students to view, particularly at the beginning of the term. This will ensure that the student knows which lessons will be covered throughout the course, and can use the syllabus as a guide throughout the entire course. It provides teachers with an effective road map as well, and helps structure their lesson plans. 4.6.6 The LMS Most people in the online course industry will tend to side with a LMS – especially when new to the scene – because it offers a large array of embedded tools that provide the administrator with the ability to create, curate, and enhance content in ways that are more cost-effective than using individual tools would be. Also, the benefits of using a LMS include the all-in-one element which enables the user to create the platform (website) and the content all in the same space without needing special network administration or website management skills. Another attractive

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feature is the ability of the system to automatically calculate exam results and generate reports which help both the instructor and learner.

4.6.7 Website Creation Platform There are a variety of free or low-cost website creation platforms online today. Even if you are not going to be offering strictly online courses, but are planning on providing CD-based courses, creating a high impact website that is easy to navigate and is aesthetically appealing can help you to promote your product. For those who are offering online courses, having a well-organized and intuitive website can hold the key to effective e-learning, online learning, experience for both teachers and students. There are also a myriad of companies that offer e-learning website design services if you simply do not have the time or know-how to create your own. 4.6.8 Course Design Tools Many companies now provide affordable course design tools which enable you to upload the content of your courses and then design effective presentations. There are even free platforms that you can use today; for example, Google now has an e-learning design platform that is free of charge. Even those who are not wellversed in coding or course design can now share their knowledge with the world. 4.6.9 Multimedia Production Tools The key to having a truly interactive and engaging e-learning course is by using the various multimedia resources that are available today. In our technological age, we now have access to instant streaming video, crystal clear recording capabilities, and instant chat support services. Moreover, you can rely upon a myriad of highly interactive multimedia production tools, such as design software and high definition cameras to record informative courses for your audience. There are even editing tools that give you the power to turn raw footage into a masterpiece in just a matter of minutes. 4.6.10 Blended Learning Blended learning is a combination of offline (face-to-face, traditional learning) and online learning in a way that the one compliments the other. It provides individuals with the opportunity to enjoy the best of both worlds. For example, a student might attend classes in a real-world classroom setting, and then supplement the lesson plan by completing online multimedia coursework. As such, the student would only have to physically attend class once a week and would be free to go at their own pace (and without worrying about scheduling issues). Blended learning is often also referred to as “hybrid” learning, and can take a variety of forms in online education environments. While some organizations may only use blended learning techniques on rare occasions, others might utilize it as a primary teaching method within their curriculum. There are two key principles commonly associated with blended learning (which are the “secrets” to its success): students who can share information and work with other students directly in a collaborative setting have a more enriched learning experience and collaboration

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between students can be improved upon if group activities rely on information gathered from online resources or lessons. It’s also been suggested that students who complete online coursework followed by interactive, face-to-face class activities have richer educational experiences. Tools and platforms that complement blended learning include LMSs and mobile devices such as tablets and smartphones.

4.6.11 Social and Collaborative Learning Collaborative learning is an e-learning approach where students are able to socially interact with other students, as well as instructors. In essence, learners work together in order to expand their knowledge of a particular subject or skill. In e-learning environments, this is typically done through live chats, message boards, or instant messaging. Collaborative learning is based upon the principle that students can enrich their learning experiences by interacting with others and benefit from each other’s strengths. In collaborative learning situations, students are responsible for each other’s actions and tasks which encourage teamwork.

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Case Study: Mobile Web 2.0 e-Training for Vocational Education Trainers (Project MOBIVET 2.0)

From 2012, seven organizations from Malta, Slovakia, Bulgaria, Germany, Greece, Romania, and Spain focused their joined efforts in implementing the project called “Mobile Web 2.0 e-Training for Vocational Education Trainers – MOBIVET 2.0.” This project aims to fill the online training gap between the self-directed learners and VET trainers by developing mobile e-learning 2.0 knowledge and skills of the trainers, thus turning them from in-class trainers to skilled online tutors (e-tutors). In this way the project offers a strong support for current and further development of innovative Web 2.0-based mobile learning methodologies, pedagogy approaches, and practices, thus improving vocational and lifelong learning in European Union. MOBIVET 2.0 project (MobiVET 2.0 2014) developed innovative learning methods, m-learning methodology, and m-learning materials as effective tools to improve the e-skills and competencies of European VET practitioners (teachers, trainers, and tutors) and helps develop adequate online training practices for effective distance tutoring of lifelong self-learning or vocational education activities at the workplace and while being mobile, without time and distance barriers.

5.1

Mobile Learning Course Preparation Methodology

During the preparation of educational materials for m-learning is necessary to consider the following: – Compose a mobile learning course – Tools to produce m-learning course – Form of learning – self-paced or instructor-led learning.

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Each m-learning course combines several main components: learning resources; trainer’s involvement like e-tutoring, e-coaching, e-mentoring, peer’s involvement; collaborative learning; and the environment where all is housed, a virtual classroom. As a base of m-learning course, simple learning resources can be considered, for example, non-interactive text documents, PowerPoint presentations, video, and/or audio files. The learners can read or watch content without being able to interact. Augmented part represents interactive content, which is created by a sequence of screens and can include text, graphics, audio, video, and interactive elements such as questions and feedback. The m-learning lessons can also recommend further reading, additional information, and links to online resources. Mobile courses can offer activities like simulations and games. Its aim is to offer real-world situations, ideally immersing the user in a simulated environment that responds and provides feedback in real time. They can emphasize on the informal aspects of the learning and provide educational element to the course. When starting to design any e-learning course, an analysis should be conducted to answer the following questions: – Is the training required to fill a gap in professional knowledge and skills? – Is the e-learning the best solution to deliver the training? Next step is to identify learners-related factors that will influence the course design: – Type of organization or institution in which learners work or study and their professional role(s) – Learners’ previous knowledge and expertise on the subject – Learners’ computer skills and previous experience with e-learning – The time that can be allocated to e-learning – The physical location where e-learning lessons will take place – at home, at work, or in a learning center – Connection speed and computer and software capabilities Content analysis is a critical step in the instructional design process. The course designer should include accurate and relevant content. Without this, even the best instructional methods and media will fail to transfer useful information to learners. Content identification and analysis can use the following methods: – Task analysis identifies the job tasks that learners should learn or improve and the knowledge and skills that need to be developed or reinforced. Mainly useful when preparing courses for specific job-related or interpersonal skills. – Topic analysis identifies and classifies the course content. Mainly suitable for broader educational objectives. – Definition of learning objectives, where the aim of any learning objective is acquisition of competences or capabilities by the learners. Objectives should be specified for the course as well as for the individual learning resources/activities.

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Learning objectives combine two main elements. First one is the expected level of performance and the second is learning content,. Both of them depend on the type of knowledge and/or skills that should be learned. Usually the course content is provided by experts in the training topic. Even existing materials can be adapted to a specific course. However, if the existing materials were designed for face-to-face training or paper, they should be transferred and adapted for m-learning. Lessons and presentations designed for face-to-face courses should be reworked to include all explanations that were delivered verbally. Longer texts should be cut into separate short “chunks” that will allow them to be easily mixed with visual, audio–video, and interactive content. Wherever a longer text is published, it has to be available in downloadable form – this will allow students to read it offline at most convenient time. The way how content is presented depends on the topic, content, target group, and, not last, creativity of the instructional designer. Due to all these variables, many different approaches exist: – Scenario-based content presentation: The content delivery follows a predefined scenario: often the learners are facing situations requiring answering questions and making choices. – Storytelling content presentation: This puts the information in certain environment and uses a narrative to gradually present the learning topics. There might be real or fictitious character(s) taking the role of a narrator and leading the students through the lesson. – Demonstration and practice content presentation: This is very suitable for practical tasks. The lesson demonstrates selected simple or more complex procedures and steps and then the learners are asked to repeat the learned lessons using the available interactive tools. – Toolkit content presentation: As the name suggests, the learners are presented with content divided into specific chunks forming a set of resources that can be studied independently of each other and without following a predefined path.

5.2

MobiVET Mobile Learning Courses

With the aim to evaluate developed methodology, seven m-learning courses on how to create and use mobile courses from both the teachers’ and the students’ perspectives were developed. These mobile courses are available at MobiVET2.0 platform http://mobivet2.eu/courses. Four of them were developed with the aim to introduce sample of m-courses for teachers: – – – –

Emotional Intelligence in the Workplace, Green Office, Intercultural Skills, Leadership Skills.

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The last three courses are targeted primarily to improving the skills of teachers/ trainers in the field of m-learning and developing of m-courses. The courses’ main objectives are to help teachers to understand Web 2.0 and support them to use in teaching/virtual classroom with the online and mobile training technologies and tools (Ionitescu 2014). During the pilot testing phase of the project, we collected the feedback from the VET students and their teachers. Results are presented in the following paragraphs. The primary descriptive analysis indicates that the fields of studies in which the MobiVET 2.0 students participated in the training course are mainly represented by theoretical studies in sciences as engineering, electronics, and telecommunications, but also by theoretical studies in humanities. The students could attend more than one course offered by MobiVET 2.0 training. As shown in Fig. 2, the majority – almost 90% of the population – that has studied the courses headed toward the Green Office course, followed by Emotional Intelligence in the Workplace (3%), Leadership Skills (3%) and Intercultural Skills (3%). As can be seen in Fig. 3, the availability of the courses was extended to different devices such as laptops (44%), desktop PCs (41%), and smartphones (16%) with Android (70%). As the survey was conducted in 2014, it would be interesting to verify how the target group was affected by the technological changes made over the last four years. The authors assume that the share of smartphones will grow significantly. From Fig. 4, it can be observed that more than 90% of the students indicated the fact that they didn’t need or needed only partial guidance from their teachers; contrariwise, the small proportion of students, 4%, needed full guidance. Regarding the need of guidance and considering the expectations of the students to the eventual study of the courses, an extension of the figures can be observed, indicating again the fact that self-learning is considered to be useful and efficient by the students. With a majority of 71%, students (Fig. 5) declared that future courses should continue being structured and contented in the same way the ones that they have

3% 3% 3%

Leadership Skills Intercultural Skills The Green Office 90%

Fig. 2 MobiVET 2.0 course(s) participation

Emotional Intelligence in the Workplace

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0% 16%

0%

41% computer laptop tablet smartphone

44%

other

Fig. 3 Devices used by students

partial guide of the teacher 48%

48% full guide of the teacher I did not need the guide of the teacher

4%

Fig. 4 The Need for Guidance during the course

0% 29%

to reduce course/courses by some information and videos/ multimedia to leave the course/courses as it is/as they are 71% to complete course/courses with additional information and videos/multimedia

Fig. 5 Students’ suggestions toward further development of the courses

studied did, meanwhile the other 29% suggested the extension of the courses with further information and additional materials and none of the respondents indicated that the courses should reduce their size or change the form. The second evaluation form created had the purpose to evaluate teachers’ overview about the utility of didactical aspects of the MobiVET 2.0 m-learning courses.

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The primary descriptive analysis indicated that the respondents are almost equally distributed by gender with ratios of 60% male and 40% female. Regarding the respondents’ age, it can be observed a majority of 80% of teachers are over 40 years old. As seen in Fig. 6, 60% of the teachers are teaching on the secondary grammar school and 40% that are teaching in upper secondary education – technology profile high-schools. In the didactic evaluation process of MobiVET 2.0 m-learning courses, teachers mostly used the prepared guides and manuals (MobiVET 2014a, b, c) (Fig. 7). The availability of the courses was extended to different devices such as desktop PCs, laptops, tablets, and smartphones. In the evaluation and testing of the courses, the most used devices were laptops, followed by tablets, and using smartphones with Android and iOS operating systems in the same portion, see Fig. 8. Regarding the form of the courses, the teachers indicated that the length and form of the courses is the exact one in order to complete the didactic requirements, and for the future courses they should be the same. 0% 0% 0%

secondary school

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post secondary (Higher Secondary / Junior College/ Church Post Secondary) Vocational School (ITS / MCAST) other type of secondary school

Fig. 6 Distribution of the educational levels in which the respondents are teaching

Online training and tutoring: methodology guidelines

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VET Teachers Manual e-Handbook: Guide to Using Web 2.0 Technologies in Training MobiVET2.0 VLE: Preparing and Publishing Learning Resources

Fig. 7 Training resources used by teachers in order to evaluate the courses

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0% 14%

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Fig. 8 Devices used by teachers

0% 20%

difficult to understand clear enough to understand 80%

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Fig. 9 Clarity of the course content

The perception of the teachers regarding the form of the courses is very important for the general feedback, revealing the following aspects (Fig. 9): 80% of the teachers evaluated that the content of the courses were clear enough to be understood, meanwhile 20% considered that the courses were very clear and easy to understand and none of the teachers found the courses difficult to understand. In order to complete the information about teachers’ evaluation over the MobiVET 2.0 courses that they have studied, the respondents were asked to give additional feedback and further suggestions in order to improve future m-learning courses. With a majority of 60%, teachers declared that future courses should be extended with further information or materials, meanwhile the other 40% suggested to leave the courses exactly the way as they are and none of the respondents indicated that the courses should reduce their size (Fig. 10). As can be seen in Fig. 11, the overall opinion after evaluating and implementing the utility of the courses indicates the fact that in proportion of 100%, the teachers found the MobiVET 2.0 training courses being valuable for their professional career and that they feel able to teach students using new methods and technologies.

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to leave the course/courses as it is/as they are 71% to complete course/courses with additional information and videos/multimedia

Fig. 10 Participants’ suggestions

0%

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Fig. 11 Teacher’s overall impression of the m-learning course(s)

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Future Directions

Today over six billion people have access to a connected mobile device and for every person who accesses the internet from a computer to do so from a mobile device as well. Mobile technology is changing the way we live and it is beginning to change the way we learn (UNESCO 2014). In the context of the MobiVET 2.0 project, is presented a way of how to fill the online training gap between self-directed learners and VET trainers by developing mobile learning 2.0 knowledge and skills of the trainers thus turning them from in-class trainers to skilled e-tutors. The results developed in the frame of this project help the tutors get familiar with various m-learning technologies and platforms and learn how they can be utilized in the learning processes.

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Presented study collects feedback from the students and teachers from different countries of Europe about the mobile learning and developed m-learning courses. Mobile technologies and concepts can supplement existing formal learning methods. Mobile learning is growing by leaps and bounds, and mobile learning devices are no longer restricted to the classroom. Most students, including young students, own or have access to cell phones, iPods, tablets, or other handheld devices – and educational administrators are quickly realizing that students can use those devices not only to access school websites, but used them for classroom assignments, and other educational resources from both school and home. But to be successful in designing and conducting mobile learning, the online educators have to learn some new techniques such as how to: – Create online classes with customizable and reusable content – Connect students with audio and video, while implementing interactive simulations to address a variety of learning modalities and styles – Incorporate video and applicable animation to simplify complicated topics – Save content as reusable templates and layouts for personal or system-wide use – Give quizzes and record and archive the results

References ADDIE. 2014, December 29. ADDIE model. Retrieved from http://www.instructionaldesign.org/ modelssssssss/addie.html Agilemodeling. 2014, December 29. Agilemodeling. Retrieved from http://agilemodeling.com/ essays/agileDesign.htm Albayrak, D., and Y. Zahide. 2015. Using social networking sites for teaching and learning: Students’ involvement in and acceptance of Facebook ® as a course management system. Journal of Educational Computing Research 52 (2): 155–179. Anderson, P. 2007. What is Web 2.0? Ideas, technologies and implications for education. JISC Technology and Standards Watch, Feb. 2007. Bristol: JISC. Retrieved from http://www.jisc.ac. uk/media/documents/techwatch/tsw0701b.pdf Bartolomé, A. 2008. Web 2.0 and new learning paradigms. elearning Papers 8: 1–10. Caudill, J.G. 2007. The growth of m-Learning and the growth of mobile computing: Parallel developments. The International Review of Research in Open and Distributed Learning, 8(2). https://doi.org/10.19173/irrodl.v8i2.348 Crowder, N. 1969. Automatic tutoring by intrinsic programming. Washington, DC: National Education Assn. De Lima, M., and M.E. Zorrilla. 2017. Social networks and the building of learning communities: An experimental study of a social MOOC. The International Review of Research in Open and Distributed Learning, 18(1). https://doi.org/10.19173/irrodl.v18i1.2630 Downes, S. 2005. E-learning 2.0. Retrieved from http://elearnmag.org/subpage.cfm?section=arti cles&article=29-1 El-Hussein, M.O. 2010. Defining mobile learning in the higher education landscape. Educational Technology & Society 13: 12–21. Figueredo, O.V. 2015. Framework for design of mobile learning strategies. In Zhang Y. (eds) Handbook of mobile teaching and learning. Springer, Berlin, Heidelberg. Hossain, L.W. 2004. ICT enabled virtual collaboration through trust. Journal of Computer-Mediated Communication 10 (1): JCMC1014. https://doi.org/10.1111/j.1083-6101.2004.tb00233.x.

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IDC. 2007. Retrieved from http://www.idc.com Ionitescu, S. 2014. Online platform and training methodology in Mobivet 2.0: The optimum tool for self-directed learners and trainers in vocational education and training. Scientific Papers. Series. Management, Economic Engineering in Agriculture and Rural Development 14: 351–357. JRC. 2009. Learning 2.0 – the impact of Web 2.0 innovations on education and training in Europe. Retrieved from ftp://ftp.jrc.es/pub/EURdoc/JRC55629.pdf Kelly, P. 2011. Web 2.0-based e-learning: Applying social informatics for tertiary teaching. The Journal of Open Learning, Distance and e-Learning 26 (3): 280–283. Learndash. 2013. Learndash. Retrieved from http://www.learndash.com/2013-hottest-e-learningtrends-infographic/ Learning, M. 2014. Mobile learning: Effective anytime, anywhere education. Retrieved from http:// www.eschoolnews.com/2012/03/26/mobile-learning-effective-anytime-anywhere-education/ Lee, M., and C. McLoughlin. 2010. Web 2.0-based E-learning: Applying social informatics for tertiary teaching. (pp. 1-483) https://doi.org/10.4018/978-1-60566-294-7. Publisher: IGI Global. Retrieved from www.scopus.com Liyanagunawardena, T.R., and S.A. William. 2014. Massive open online courses on health and medicine: Review. Journal of Medical Internet Research 16 (8): e191. McCann, K. H. 2009. Virtual communities for educators: An overview of supports and best practices. [Electronic version].In Proceedings from technology, colleges, and community conference, 137–142. Honolulu: University of Hawai’i at Manoa. MobiVET. 2014a. Retrieved from http://mobivet2.eu/VLE_files/teachers_manual/teachers_man ual.html MobiVET. 2014b. Retrieved from https://docs.google.com/presentation/d/1D8Y_DqJeIesNZQhJK GHU3zbxNWCIMh827u9gtd_LdFg/pub?start=false&loop=false&delayms=3000 MobiVET. 2014c. Retrieved from https://docs.google.com/presentation/d/1D8Y_DqJeIesNZQhJK GHU3zbxNWCIMh827u9gtd_LdFg/pub?start=false&loop=false&delayms=3000&slide=id.p13 MobiVET 2.0. 2014. Retrieved from www.mobivet2.eu O’Reilly, T. 2007. What is Web 2.0: Design patterns and business models for the next generation of software. Communications & Strategies. Retrieved from http://ssrn.com/abstract=1008839 O’Reilly, T.. 2014. What is Web 2.0? Retrieved from http://www.oreilly.com/pub/a/web2/archive/ what-is-web-20.html?page=3 Palkova, Z. 2014. Using virtual environments for vocational education: The Avares case.In DIVAI 2014, 147–153. Praha: Wolters Kluwer. Palkova, Z. (2017). An innovative virtual reality educational environment for school physics education: Slovakia case. In EDULEARN17 Proceedings, 7790–7797. Palkova, Z., and E. Vakhtina. 2015. Innovative learning: From multimedia to virtual worlds. In EDULEARN15 proceedings, 1590–1599. Palková, Z., A. Bandlerová, L. Schwarczová, and P. Bielik. 2014. WEB2.0 Technologies and their applications in online training. In INTED2014 proceedings, 4960–4966. Parusheva, S., et al. 2018. Use of social media in higher education. TEM Journal 7 (1): 171–181. Skinner, B. 1954. The science of learning and the art of teaching. Harvard Educational Review 24: 86. Teachthought. 2014. 12-principles-of-mobile-learning. Retrieved from http://www.teachthought. com/technology/12-principles-of-mobile-learning Tincanapi. 2014. Retrieved from http://tincanapi.com/ UNESCO. 2014. Retrieved from http://www.unesco.org/new/en/unesco/themes/icts/m4ed/ W3C. 2014. Retrieved from http://w3c.org Wainfan, L.P. 2004. Challenges in virtual collaboration: Videoconferencing, audioconferencing, and computer-mediated communications. Santa Monica: Rand Corporation. Wiener, N. 1961. Cybernetics: Or control and communication in the animal and the machine. Paris/ Cambridge, MA: Hermann & Cie/MIT Press. Zhang, Y. 2015. Characteristics of mobile teaching and learning. In Handbook of mobile teaching and learning. Springer.

Tangible Objects and Mobile Technology: Interactive Learning Environments for Students with Learning Disabilities

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Elif Polat, Kursat Cagiltay, and Necdet Karasu

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Potential Benefits of Tangible Technologies for Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Tangible Technologies and Specific Learning Disabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 A Tangible Mobile Application for Students with SLD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Parts of the Tangible Mobile Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Tangible Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Technical Aspects of Tangible Mobile Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Suggestions for Instructional Designers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Future Directions and Suggestions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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This chapter is based on corresponding author’s Ph.D dissertation. E. Polat (*) Faculty of Education, Computer Education and Instructional Technology Department, Istanbul University – Cerrahpasa, Istanbul, Turkey e-mail: [email protected] K. Cagiltay Faculty of Education, Computer Education and Instructional Technology Department, Middle East Technical University, Ankara, Turkey e-mail: [email protected] N. Karasu Faculty of Education, Special Education Department, Gazi University, Ankara, Turkey e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_119

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Abstract

In recent years, tangible mobile applications have been used in general and special educational settings. Providing multi-sensory interaction, physical engagement, accessibility, and collaboration, interactive tangible mobile applications have a potential to enrich learning experience of both normally developing students and students with specific learning disabilities (SLD). Despite the promising potential and agreement on the value of tangible technologies, few studies have yet revealed the use of interactive tangible technologies for students with SLD. Emerging research focus on supporting reading skills of students with SLD by developing tangible interfaces with different technologies. Moreover, related literature lacks both theoretical and empirical studies in relation with the use of tangible technologies for students with SLD. This chapter presents definition and potential benefits of tangible technologies, its use with SLD, description of a tangible mobile application for students with specific learning disabilities and future directions and suggestions. It is thought that design guidelines may be enlightening for instructional designers to design and develop interactive tangible mobile applications for students with SLD.

1

Introduction

In the fields of general and special education, interactive tangible mobile applications have an increasing importance and value. These applications have a promising role in enriching students’ learning experiences. O’Malley and Fraser (2004) emphasize that tangible technologies have a promising potential and the capacity for education with particular and innovative features. Providing multi-sensory interaction (Antle 2007), physical engagement (Manches and Price 2011), accessibility (Shaer and Hornecker 2010), and collaboration (Marshall 2007) can open a new learning way for both normally developing students and students with specific learning disabilities (SLD). Interactive tangible technologies aim to provide interaction with the physical and digital environment without using the traditional input and output devices such as monitor, mouse, and keyboard (Ullmer and Ishii 2000). Instead of pressing keyboard keys to interact with the computer, using gestures and physical actions make interaction closer to the real world (Jacob et al. 2008). Tangible technologies provide benefits to students for moving the physical world into the interface and they have a significant role in education in this way (Horn et al. 2009). In other words, tangible technologies enable students to understand real world in real world (Antle 2007). Fishkin (2004) states that the steps of interaction between tangible real world object and computer interface system are: (1) giving some inputs to computer system via physical movements (2) understanding the input by computer system and (3) giving feedback to the user taking input into account.

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Traditional computer-assisted materials offer learning opportunities for students with special needs. In this context, Eisenberg et al. (2003) underline that tangible technology does not reduce the value of educational technology used today. However, ensuring interaction with the real world object is difficult for computer-based educational systems. Decreasing the isolation between the virtual and concrete opens new doors for instructional designers to be able to make a more realistic design beyond computer-assisted materials. In this section, definitions of assistive technology, interactive technology, tangible tools, and interactive tangible technology will be given to better understand the chapter. Assistive technology is defined by Hersh and Johnson (2008, p. 196) as “. . . a generic or umbrella term that covers technologies, equipment, devices, apparatus, services, systems, processes and environmental modifications used by disabled and/or elderly people to overcome the social, infrastructural and other barriers to independence, full participation in society and carrying out activities safely and easily.” Interactive technology can be defined as providing a two-way flow of information between the student and the technology (IGI Dictionary Search 2018). Tangible tools are defined as technologies that offer students more natural and familiar interaction similar to real-life objects (Jacob et al. 2002; O’Malley and Fraser 2004). Finally, interactive tangible technology is a broader term which means two-way flow of information between the student and tangible technology that allows students bodily interacting with the tangible objects and the computational system can give immediate visual, auditory or haptic feedback to students for their actions (Shaer and Hornecker 2010).

1.1

Potential Benefits of Tangible Technologies for Learning

The classification below is made taking the characteristics of tangible technology into account and under the light of empirical and theoretical studies from the literature. In this context, physical interaction and manipulation, accessibility, and collaboration are mentioned.

1.1.1 Physical Interaction and Manipulation Physical activities play an important role in learning. As one of the benefits of tangible technology usage in learning, Marshall (2007) and O’Malley and Fraser (2004) emphasize that according to Piagetian developmental theory, manipulation of concrete physical objects can enhance thinking and learning. Employing visual, auditory, and touch as multiple senses helps students to construct knowledge in abstract problems (Zuckerman et al. 2005). Evidence indicates that there is some information that young children or adults cannot express verbally, however surprisingly they are physically able to express it with gestures (O’Malley and Fraser 2004). Tangible and spatial interaction can be gestural, haptic, full bodied, and spatial. Through these interactions, new learning opportunities can be proposed for students (Antle 2007). Different devices have different physical actions that can cause digital manipulations (Manches and Price 2011). Interaction in tangible technology is more

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natural and familiar compared to other types of interaction (Jacob et al. 2002). Touch-screen interaction is easier than mouse interaction. In parallel to this, interaction is easier with tangible objects that are similar to real-life objects (O’Malley and Fraser 2004).

1.1.2 Accessibility and Collaboration Tangible technologies make abstract information accessible to the application level regardless of the age level of abstract thinking and skills (Shaer and Hornecker 2010). Tangible technologies help to make abstract concepts concrete that are difficult to learn for different target audiences like students with learning disabilities (Zuckerman et al. 2005). Tangible interfaces provide both better manipulative access owing to multiple learners to manipulate many objects simultaneously and superior perceptual access. Hence, learners can understand topics easily (Horn et al. 2009). Interactive tangible technologies allow learners to collaborate with each other. Marshall (2007) states that numerous design-oriented studies emphasized appropriateness of tangible interface for collaboration. Tangible technology helps to ensure collaborative interaction in the shared space (Horn et al. 2009). In line with this, it also allows for group work (Zuckerman et al. 2005). Unlike traditional computer systems, which consist of mouse, keyboard, and a monitor, tangible interfaces provide simultaneous interaction by sharing control among students (Marshall 2007).

1.2

Tangible Technologies and Specific Learning Disabilities

In recent years, development of new technology has played an important role in meeting the needs of students with special needs. Educational technology offers learning opportunities for students with special needs. Hutinger (1996) emphasizes the positive impacts of technology on special education as being a facilitator for the inclusion, increasing social interaction and communication. Computer applications serve as an equalizer to make similar activities for both a child with special education need and a normally developing child. In line with this, Florian (2004) says that computer-assisted instruction is like a cognitive prosthesis by compensating difficulties which students faced, and also ensuring equal opportunities to learn. Moreover, children with learning disabilities seem to accept failure. However, no matter how many mistakes made by the child while interacting with a computer, the child does not face any criticism. Because computers are not being judgmental against the child, using computers has also an important role in special education. It is important to embrace this kind of strategy to prevent the child from learned helplessness (UNESCO 2000). The use of educational technology in special education encompasses tutorial software, exploratory learning environments such as simulation and virtual environments, drill and practice software, educational games, assessment and management tools and communicative tools (Florian 2004). Individualized learning program, in particular, is said to support students with special education needs. Integrated

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Learning Systems (ILS) are preferred in schools (Abbott 2007; Florian 2004). Although there exist different definitions of ILS, generally, they include diagnostic tools and a number of learning activities mostly related to literacy and numeracy (Abbott 2007). With the use of technology in education, exploratory learning environments including virtual environments emerged. These environments allow students to interact with materials and to have control of their own learning. In this regard, it is different from the tutor, drill, and practice (Florian 2004). Moreover, the use of technology in education allows the teachers to make the evaluation easier and faster and helps to diagnose learning disabilities, to prepare individualized education plans, and to monitor the progress of students (Florian 2004). Although computer-assisted instruction offers opportunities for facilitating learning for students with SLD, it remains limited especially in physical interaction. In line with this, Keay-Bright (2008) emphasizes that many positive outcomes have come out of using ICT in learning disabilities. However, technologies used in sensory action, that help to provide creative and flexible thinking as well as collaborative learning, are still few in number. An emerging area of research is the use of tangible technology to support special education (Shaer and Hornecker 2010). Falcão and Price (2010) stated that with the development of new technology, tangible technologies provide extending opportunities for multi-sensory interaction for students with learning disabilities. Moreover, tangible technologies make learning environment richer than a traditional graphical user interface system by offering opportunities in cognitive, social, and linguistic learning for special education (Shaer and Hornecker 2010). In the light of literature, the use of tangible technology in special education as well as general education is seen increasingly becoming important. However, few studies have yet revealed the use of tangible technologies for students with SLD. These research focus on supporting reading skills of students with SLD (Antle et al. 2015; Fan and Antle 2015; Pandey and Srivastava 2011a, 2011b). Pandey and Srivastava (2011a) developed a tangible interaction learning aid system named as SpellBound to teach the spelling of basic English words for students with dyslexia who are aged between 8 and 12 years (Fig. 1). A developmental study aimed at designing and developing an activity-based prototype by using tangible objects. As a conclusion, how the children interact with images, colors, and tangible objects was figured out. The numbers, basic arithmetic operations, and working on the shape of the letters will be incorporated to their future studies. Antle et al. (2015) developed a tangible system named as PhonoBlocks to support children with dyslexia who are aged between 5 and 8 years and have disabilities in decoding English sound-letter (Fig. 2). PhonoBlocks includes 3D tangible letters with colors as a cue providing help to distinguish the sounds of letters. In addition, it consists of a touch screen laptop, an input platform, and 27 tangible letters. It has been stated in the mentioned study that the authors will conduct a pretest-posttest experimental study to investigate the long-term use and its impacts on reading skills for students with dyslexia in follow-up studies.

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Fig. 1 SpellBound (Pandey and Srivastava 2011a)

Fig. 2 PhonoBlocks (Antle et al. 2015)

Cramer et al. (2016) investigated effectiveness of PhonoBlocks that was a tangible software system in terms of a dynamic color-coding scheme on students with dyslexia in 3rd–7th grades. They mainly focused on teaching to spell of the words that includes in one or double consonants and end with –le (cuddle, stable, topple etc.). They conducted a comparative study with four males and five female students. Five of the students were randomly assigned to Vowel Color Based on Design Principle Group (V-DP) and the rest assigned to Vowel Color Based on Identity (V-ID). The authors used red color for long vowels and yellow color for short vowels in V-DP group while they used different colors for each vowel in V-ID group. The study was carried out for 4 weeks. Students were given new two words in a 15 min practice session three times a week. As a result, even though there was no significant difference between two groups, improvement was seen for both groups. Fan and Antle (2015) developed a tangible tabletop system to help 5 and 6-yearold children with dyslexia who have disabilities in decoding English sound-letter

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Fig. 3 Tactile letters Letters (Fan and Antle 2015)

Fig. 4 Tiblo (Pandey and Srivastava 2011b)

(Fig. 3). It uses texture cues to promote learning letter-sound correspondence. In further studies, the authors are planning to conduct a user test to investigate prototype design and experimental studies to reveal the impact of tangible tabletop with texture cues in alphabetic learning. Pandey and Srivastava (2011b) developed a tangible user interface with color and sound cues named as Tiblo to help remembering and following sequential instructions in reading stories or words for students with dyslexia aged between 8 and 12 years (Fig. 4). Rapid ethnography to investigate emotional and psychical aspects and contextual enquiry were employed in this study. As a result, it was found out students had interest in using Tiblo.

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Kara et al. (2014a) designed and developed a computer application for supporting storytelling activities of preschool students. The authors carried out a usability study with 24 participants. The smart storytelling toy contains three parts which are background cards for showing stories, RFID (radio-frequency identification) system for transferring data to computer and a computer with Flash application. The system is based on the principle that “when the student put the toy on the receiver panel, Flash application displayed the stories on the screen.” As a result of this study, design principles in terms of usability, storytelling, visual design and interaction were revealed. Kara et al. (2014b) carried out a user study of StoryTech. Ninety preschool students from five different kindergartens were the participants of the study. Experimental design was employed in this study. The result of the study revealed that StoryTech exhibited rich experiences for storytelling particularly for five and sixyear-old students. Kara et al. (2013) investigated the impact of playing with a smart storytelling toy (StoryTech) on children’ narrative activities and creativity. As aforementioned, StoryTech contains three parts that are background cards for showing stories, RFID (radio-frequency identification) system for transferring data to computer and a computer with Flash application. Experimental design was used in the study. Ninety preschool students from five different kindergartens in Ankara participated in the study. Results showed that StoryTech contributed to narrative activities of preschool students and had a positive effect on creativity. Kara (2015) designed, developed and used a smart toy for preschool children. Design and development research method was used in the study. Results of the study showed that the participant pre-school teacher had positive thoughts about the appropriate use of technology in pre-school education. According to teachers, the content, the visual design and interaction components of the smart toys should be improved more. As a result of the study, the design principles covering content, visual design and interaction components were revealed. Results of the study indicated that 36 and 48 month old children demonstrated lower performance in completing cognitive activities of the smart toy when compared to 48 and 72 month olds. Teachers have also preferred to play with smart toys for collaborative activity. It can be inferred from the literature, there is an insufficient amount of theoretical and empirical studies about the usage of tangible technologies. A need for tangible technologies for various learning context for students with SLD has emerged. In this context, a tangible mobile application was designed and developed in order to facilitate learning of students with SLD. Tangible technologies could have a potential for students who have different disability types such as developmental, cognitive or physical. Parkes et al. (2008) used Tangible Kit called Topobo, for children with autism and Asperger’s syndrome. They reported that the Topobo enhance children’s engagement and motivation (Fig. 5). Cobb et al. (2007) employed Enlighten tangible system for students with multiple, severe and moderate learning difficulties. Tangible system has positive effects on students’ motivation, attention and communication skills (Fig. 6). Hengeveld et al. (2009) used LinguaBytes for toddlers with multiple disabilities to

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Fig. 5 An example for Topobo from Tangible Media Group, MIT Media Lab. (Parkes et al. 2008)

Fig. 6 An example of Enlighten from The University of Nottingham (Cobb et al. 2007)

help improve linguistic skills. They revealed that the tangible system could improve literacy skills of children (Fig. 7). Garzotto and Bordogna (2010) developed a tangible technology, Talking Paper to enhance linguistic, cognitive and motor skills of students with severe disabilities. They showed improvement in motor skills as well as linguistic skills (Fig. 8). Haro et al. (2012) developed an interactive tangible user interface to help children with Down syndrome for reading. The system improved reading process as well as enhanced attention and motivation of students. Jafri et al. (2017) developed a tangible system for visually impaired students to teach tactual shape perception and small-scale spatial awareness sub-concepts. Interview results with teachers showed that tangible system had a potential to meet these students’ need.

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Fig. 7 LinguaBytes (Hengeveld et al. 2009) Fig. 8 A scenario from Talking Paper (Garzotto and Bordogna 2010)

These systems developed for students with special needs can also be used for normally developing children taking age and characteristics into consideration. In this section, for general educators, some interactive tangible technologies which were developed for different age groups (from toddlers to undergraduate students) were provided without detail description. Arita et al. (2014) developed soft tangible objects work with a tablet for toddlers and prekindergartners to help color learning, engagement and enjoyment. Soft tangible objects have conductive materials. Also each one has unique surface. They tested their prototype on nine children (2–6 ages). Although the interaction pattern varies according to gender, overall families’ and children’s feedbacks are generally positive (Fig. 9a). Seo et al. (2015) developed a prototype called Stampies which have tangible objects made from different materials (wool, silicone etc.) works with a tablet. The purpose of the study was to investigate how 19 children aged 4–7 associate materiality and meanings. The study showed that materiality of objects associated with meanings through material essences by children. The authors also presented tangible design implications (Fig. 9b). Garcia-Sanjuan et al. (2018) developed both tactile and tangible gamified quiz system called Quizbot for students in primary education. Tactile version of

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Fig. 9 (a) Soft Tangible Objects with Tablet (Arita et al. 2014) (b) Stampies (Seo et al. 2015)

Fig. 10 (a) Tactile version of Quizbot (b) Tangible version of Quizbot (Garcia-Sanjuan et al. 2018)

collaborative gamified quiz system is on the tablet and elements are all digital while there are scattered tablets on the floor with tangible objects. The authors compared both tactile and tangible systems on eighty students in terms of user experience and quality of collaboration provided by systems (Fig. 10a, b). De Raffaele et al. (2017) developed and adapted a tangible tabletop system which aimed to teach object-oriented programming concepts for higher education. They investigated effectiveness of the tabletop on undergraduate students. The results of the study showed that tangible system could improve learning experience of students. In addition, tangible systems may have a potential to deliver complex concept to students effectively. Guerrero et al. (2016) combined tangible interface with virtual worlds to teach different geometrical concepts for secondary school students. A pilot study was conducted in a higher school. The results of the study showed that Virtual Touch enable students to learn more meaningful way. In addition, Virtual Touch system motivated them (Fig. 11).

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Fig. 11 The Virtual Touch system (Guerrero et al. 2016)

2

A Tangible Mobile Application for Students with SLD

An interactive tangible mobile application was developed by the authors of this chapter with the aim of improving achievement of students with SLD in 6th grade cell concept (Polat 2017).

2.1

Parts of the Tangible Mobile Application

The Learning Objective: Students will be able to compare animal and plant cells in terms of basic components and functions (6th grade cell concept). Scope of the Learning Objective: For the basic components of the cell, only the cell membrane, cytoplasm, and nucleus are given. Without giving detailed structures of cell organelles, students were only mentioned about the names and the main functions. Concepts: This study aims to equip students with SLD with the following concepts: “The cell, similarities and differences between plant and animal cells, name and function of the organelles, and basic components of the cell.” Target Audience: Target group consists of students with SLD selected from 6th–8th grade. The tangible mobile application includes a pretest-posttest, a trial screen, a tutorial and practice parts. Tangible objects are employed in all of these parts (Fig. 12). Firstly, there is a login (a nickname which selected by the researcher) screen in the application. Next, the pretest that includes criteria-based 22 questions in the tangible mobile application is presented. A trial screen is provided for the students to enable them get familiar with tangible objects as well as being able to use it easily. One of the main parts of the application is the “tutorial part,” which starts with an introduction and followed by an experimentation that is provided through a magnifying glass and a microscope. The next step consists of definitions and explanations about each concept. Each learning unit in the tutorial part is followed by a related practice. The posttest – the last part- is the same with pretest.

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Fig. 12 Screenshots of tangible mobile application

2.2

Tangible Objects

Eighteen tangible models (objects) were designed and developed (Fig. 13). In addition to holistic models of animal and plant cells, one microscope, one magnifying glass, six models that included the nucleus, the cytoplasm and the cell membrane of animal and plant cells and the cell wall were designed and developed. The remaining eight of them were the models of the organelles.

2.3

Technical Aspects of Tangible Mobile Application

The application was developed with Adobe Animate CC to use on Android Tablet. Tangible models were designed in 3D CAD programs and printed by a 3D printer (Fig. 14). During the development of the tangible objects, the researcher received feedback from a science education expert. Application works based on touch sensing principle, which could be used with stylus tips easily (Fig. 15). Every object has a unique stylus pattern so when a user puts the object on a tablet’s surface the system detects it through those stylus tips. It is thought that the findings of this study may be enlightening for instructional designers to design and develop tangible mobile applications for students with SLD. Instructional designers could use the guideline (model) (Fig. 16) to develop similar studies.

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Microscope

Mitochondria

Magnifying Glass

Lysosome

Plant Cell Membrane

Golgi Apparatus

Animal Cell Membrane

Ribosome

Plant Cell Cytoplasm

Endoplasmic Reticulum

Animal Cell Cytoplasm

Nucleus

Cell Wall

Vacuoles

Chloroplasts

Centrioles

Plant Cell

Animal Cell

Fig. 13 Screenshots of tangible models

Fig. 14 Working principle of the tangible mobile application

2.4

Suggestions for Instructional Designers

As seen from the Fig. 16, the guideline (model) consists of seven fundamental design and development steps and the three improvement steps. In the first step, “the educational subject” was determined. Next, “the educational scenario” was developed while also determining what kinds of tangible objects will be used as well as the features of the objects. The third step is “the development of the tangible objects” and working on the design and the nature of the objects. In the fourth step, a paperbased and a mobile device-based first prototype was developed, including the

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Fig. 15 The bottom of a tangible object (Black points are stylus tips)

sub-steps of “visual design, sound, educational content and coding.” Fifth step was developing the “low fidelity prototype” and the sixth step was developing the “high fidelity prototype.” Seventh step was the final version of the guideline (model). It should also be noted that after step four, each step was followed by improvements and the researcher made the necessary changes in line with views of experts, teachers and students as well the observations documented during the implementation. The right hand columns point the feedback taken from the stakeholders during the design and development phases. Special education experts’ views were taken into consideration in all the steps until the final version while science education experts’ views were taken in first five steps until the step of “high fidelity prototype.” Students’ views were also collected. In addition, students used in the steps of developing the first prototype and working on the “low and high fidelity prototypes.” As it can be seen on the left hand column, students were asked to use the application and all the steps were observed and documented from fourth step onwards. In broad, the iterative research and development process presented in the Fig. 16 is similar to other usual tool/technology developmental processes. However, what makes it different in order to serve students with special needs is in the details of the process. The source of data, expert advice, getting feedback from students with special needs and designing the prototypes for the target group make the process original.

3

Future Directions and Suggestions

One of the interventions to meet the needs of students with students with specific learning disabilities is utilizing innovative educational technology. Traditional computer-assisted instruction applications remain insufficient for providing physical engagement and multisensory interaction for this target group. With the new emerging technologies, tangible mobile applications have a potential to enrich learning experience of students with specific learning disabilities. Despite the promising

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Determine Educational Subject

Determine Educational Scenario Determine Tangible Objects

Develop Tangible Objects

Improvements

2. Sounds 3. Educational Content

Low Fidelity (Mobile Device Based)

Students, Views

Applying Prototypes to Students with SLD

4. Coding

Special Education Experts, Views

1. Visual Design

Science Education Experts, Views

First Prototype (Paper-Based Prototype & Mobile Device-Based Prototype)

Improvements

High Fidelity

Improvements

Final Version

Fig. 16 Design guidelines for developing tangible mobile application for students with SLD

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potential and value of tangible technologies, few studies have yet revealed the use of tangible technologies for students with SLD. Nascent research focus on dyslexia to support reading by developing a tangible interface with different technologies. Moreover, scholarship lacks both theoretical and empirical studies in relation with the use of tangible technologies for students with SLD in literature. There is an insufficient amount of theoretical and empirical studies about the usage of tangible technologies. There is a need for further research to identify which elements and features of tangible mobile applications are critical in learning environment. Besides, some tangible technologies for students with SLD have been developed to date; there is still an insufficient amount of empirical research. It is obvious that there is an emerging need to determine the design principles of tangible mobile application for students with SLD and to conduct empirical research. It is thought that the findings of this study may be enlightening for instructional designers to design and develop tangible mobile applications for students with SLD. Instructional designers could use the guideline (Fig. 16) to develop similar studies.

4

Cross-References

▶ Employing Virtual Reality to Teach Face-Based Emotion Recognition to Individuals with Autism Spectrum Disorder ▶ Characteristics of Mobile Teaching and Learning ▶ Design Considerations for Mobile Learning ▶ Instructional Design Principles for Mobile Learning ▶ Mobile Learning and Education: Synthesis of Open-Access Research ▶ Mobile Technologies for Teaching and Learning

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Use of Mobile Digital Technology and iPod Touches in Physical Education

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The Use of Interactive Multimedia in Physical Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Examining Mobile Digital Technology in General Education and in Physical Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The use of mobile digital technology as a teaching and learning medium in physical education is gaining momentum. This chapter opens with an introduction to mobile digital technology in general, in education, and in physical education. It proceeds to examine the use of iPod touches to enhance teaching and learning in a physical education setting. While anecdotal evidence exists as to its use, greater empirical evidence is required to establish the efficacy of the iPod touch from a teaching and learning context across all physical education settings and with different ages and abilities.

1

Introduction

Published empirical research to date indicates that information communication technology (ICT) has been used in higher education for a number of purposes. Information communication technology encourages the presentation of students’ work and experiences and also promotes reflective writing. ICT affords commentary S. Crawford (*) · P. Fitzpatrick Sports Studies and Physical Education, School of Education, University College Cork, Cork, Munster, Ireland e-mail: [email protected]; trishfi[email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_72

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on work presented and provides for peer learning and collaboration. It has also been used to establish communities of practice in particular settings (Papastergiou et al. 2011). According to Papastergiou (2010), information and communication technologies have become an integral component of physical education and sport science communities and professions. Mobile digital technology (MDT) is a core part of information communication technology. Mobile digital technology includes iPhones, personal digital assistants (PDAs), iPod touches, and other devices. Researchers indicate the benefits of mobile digital technology in areas of education and personal development (Lunsford 2010). In particular, Garrison (2011) identifies these technologies as having potential to create and sustain communities of learners. The immediacy of being able to post, share, and comment from in situ situations using mobile digital technology has instant appeal. This has been dealt with in detail in ▶ Chap. 45, “Mobile Technologies for Teaching and Learning.” Frohberg (2006) has explored the many different contexts of mobile digital learning. These he have identified to include free, formalized, digital, and indeed informal settings. Physical education can, and does, embrace all of these contexts at different times due to the potential for both online, in situ/practical, and classroom-based teaching and learning of the subject. When aspects of the digital learning context spill over into the physical environment, they impact students in a significant manner. This is known as “physical learning” (Engel et al. 2011). Similarly, in the world of informal lifelong learning, scholars have established the many benefits of mobile digital technology (Frohberg 2006; BeddallHill and Raper 2010). As physical education seeks to establish patterns of holistic healthy physical activity and physical learning across the life span, these are key aspects in considering its use. Frohberg highlights how the actual mobility of digital technology enhances this process as students of all ages and abilities can manage information wherever they are. Despite these obvious advantages for the use of mobile digital technology, Engel and Green (2011) indicate that second- and third-level institutes are still reticent about its use. This was initially thought to be due to physical limitations about size, shape, and ease of access. These issues are no longer pertinent in the current climate of variations in size and ease of availability of such technology. Herrington et al. (2009, p. 2) argue that the use of mobile digital technologies in thirdlevel education is “pedagogically conservative and regressive” and in the main are used to promote a teacher-centered rather than learner-centered environment. Researchers also indicate that concerns about academic integrity have been raised, but these can be and are addressed with clear guidelines on violators and student safety rules. Readers are directed toward the earlier chapter addressing ▶ Chap. 53, “Moving Towards the Effective Evaluation of Mobile Learning Initiatives in Higher Education Institutions” for a greater discourse on this topic at third level.

2

The Use of Interactive Multimedia in Physical Education

Sorrentino (2000) has established that software applications are used in physical education for a number of purposes. These include the evaluation of physical fitness, the collection of data on athletes’ performance (time, distance, rates, etc.), and the

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teaching of sports skills, tactics, and rules as well as exploring topics like health and related fitness. In relation to sport-specific software applications, Sorrentino (2000) tested the effectiveness of the use of the Internet in the teaching of motor and cognitive skills during swimming lessons. In her study, she examined the Internet as a means for enhancing skill acquisition, knowledge, and attitudes in school-based physical education. In the initial study, modeling delivered through progressive still photographs over a simulated Internet site was found to contribute to significant improvements in front crawl technique. No significant improvements were found for swimming knowledge, front crawl speed, back crawl speed, or back crawl technique that could be attributed to the Internet-based model delivery. A follow-up on the study examined the video and photographic modeling of front crawl and back crawl delivered using a simulated Internet site, compared to traditional swimming instruction. In this particular study, significant intervention effects were found for front crawl and back crawl stroke technique for the two Internet-enhanced groups. These changes were not found for the control group. However, no significant improvements were found for swimming speed or written knowledge. The use of video modeling was expected to lead to a higher frequency of self-instruction, analysis, and correction, resulting in better swimming performance; however, no significant differences were found between the two Internet-enhanced modeling groups. This indicates that both photographic models and video models were equally useful in enhancing front crawl and the acquisition of back crawl technique. In terms of student attitudes, all students of the Internet groups enjoyed the swimming lessons compared with three out of four in the control groups. Further, the majority of students in the Internet-enhanced groups would choose this method of instruction over the traditional one. Similarly, a computer-aided instruction for the teaching of a badminton skill was developed by Chu and Chen (2000). Everhart et al. (2002) examined the effects of high school physical education students interacting with a multimedia software program designed to provide nutritional and physical activity guidance. The study sought to investigate if by maintaining records of physical activity and eating, patterns using multimedia software would positively affect students’ behaviors in these areas. Findings indicated that the multimedia software had little effect on participation and nutritional behaviors. However, significant differences were revealed for all students for pre- and posttest scores in physical activity levels which justifies the importance of physical education in the school curriculum. The researchers in this study also surmised that if the intervention group had more frequent access to the multimedia software, there was potential for greater change occurring in the variables. In basketball, Antoniou et al. (2003) compared the use of multimedia computer programs, traditional methods of instruction, and a combination of the two in rule violation in basketball when teaching university students. Results indicated that all students increased their knowledge of rule violation in written tests, but only those in the traditional and combined approaches retained this knowledge. Total performance included the scores from the written test and a video test to assess that of basketball phases. Analysis of overall performance indicated that the traditional instruction group scored higher than the multimedia group, but the video test results were not retained. Hence, the researchers concluded

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that further research was needed to realistically establish the efficacy of multimedia computer programs. Vernadakis et al. (2008) applied specially designed software for the teaching of rules and ball-shooting skills in basketball, using a similar threegroup format. Posttest results indicated no significant differences between the groups in the written tests. However, attitude scores of the combined group were more favorable to the multimedia approach than the traditional method alone. In relation to the dance strand of the physical education curriculum, the majority of the published research projects that concentrate on the use of ICT in the teaching of dance focus either on the development of software or on the design of interactive learning platforms without empirically assessing their influence on actual dance performance in real time (Risner and Anderson 2008). Popat (2002) described the use of a dynamic website for teaching choreography in an international cooperation project between students from Britain, Portugal, and America. Cherry et al. (2003) showed how a digital video annotation tool can be used to teach dance composition. Kavakli et al. (2004) discussed the process in developing a virtual learning environment (WebDance) for teaching traditional Greek and English dances. Parrish (2007) considered how different types of technology have been used to enhance learning and teaching dance. However, in the words of Penrod (2005, p. 56): There is no formula or model that is going to fit every situation, including yours. If you believe there is a place for technology in the education of a dancer, you have to create an environment to make it flourish in your own place in your own time. Dance is the core, technology is the tool.

Embracing Penrod’s principle, Leijen et al. (2008) examined how dance students experienced learning in an international distance education program delivered in an eLearning format using a virtual learning environment platform. In order to organize the students’ experiences with the various learning assignments, the researchers focused on three learning tasks: individual writing assignments, collaborative assignments, and individual practical assignments. Data were collected using a questionnaire and group interviews. Regarding the eLearning format, the researchers found that the most crucial factor for carrying out all learning assignments was the teacher’s guidance and feedback on students’ work. With the use of the learning platform, findings indicated that carrying out practical assignments was the most limited with the available tools. Leijen et al. (p. 148) also felt: That besides developing physical skills and learning the domain-related knowledge, students should be encouraged to develop their individuality, reflect on their learning and enhance their creativity and critical-thinking skills.

Interestingly in many of these studies, most of the researchers did not find statistically significant differences between the experimental and the control groups. This was despite the fact that the pre- and post-performances of each group separately often proved statistically significant. Some of the issues identified are the small

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sample sizes, inadequacies of the technological devices, the cost of applications, or the low quality of their graphics. In relation to personnel, the lack of technology training for the physical education teachers and different users’ computer skills also proved problematic. In some studies, it was also impossible to control the time that the students actively engaged with the digital materials. Students participating in the studies with combined options preferred mixed teaching methods that combined interactive multimedia with instruction from the teacher than the use of the software applications alone. In some cases where researchers included interactive multimedia in their teaching practice, it has been found that their impact on the students’ motor skills and performance is either nonexistent or moderate compared with the traditional teaching methods. This leads us to conclude that technology can offer opportunities for personalized instruction, cooperation, communication, and feedback (Kwok-Wing Lai 2008; Leijen et al. 2008) as far as it is used with a focus on the improvement of instruction and the promotion of human movement and not its replacement.

3

Examining Mobile Digital Technology in General Education and in Physical Education

The use of video recording in education has been commonplace for many years. Video has been used to address teachers own teaching styles (Ammah and Hodge 2006; Calandra et al. 2008), to consider student learning (Blomqvist et al. 2000; Fiorentino and Castelli 2005; Foster 2004), and to provide invaluable feedback for students in situ. Scholars have also advocated this particular approach particularly in the teaching of motor skills (Boyce et al. 1996; Deakin and Proteau 2000; Martindale et al. 2001). The use of digital video recording (DVR) provides for this type of teaching and learning support in situ, especially in physical education. It is advocated in the sport of diving as reported by Chirico (2002). Banville and Polifko (2009) have found the use of a DVR to be effective in training gymnasts ranging in skill from novice boys in recreational classes to elite nationally ranked male and female athletes. These practitioners feel that because of the various learning environments and different teaching and learning styles, educators and students should be encouraged to develop their own way of implementing the described technology in their practice or class. DVR has also been advocated in the world of athletic training. Berry and Miller (2006) indicate its usefulness in training athletic trainers. The researchers also consider the benefits of DVR in physical educational settings where students find the use of videos stimulating and flexible. Digital video recording allows them to work at their own pace and limit passive observation associated with traditional videos. These researchers also comment on the benefits of streaming of videos to allow learners revisit clips and further enhance their learning. In their work, Klubacs Collins and Juliu (2009) advocate the use of the tablet PC in a similar fashion. Several academic institutions have conducted pilot projects to study tablet PCs as a teaching tool to deliver courses and to promote collaborative learning (Mock 2004). Tablet PCs have benefited faculty members in their teaching by

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facilitating (1) digital note-taking, (2) annotation of presentation materials, and (3) markup of students’ assignments (Wise et al. 2006). Such mobile digital technology is also excellent for collaborative and project-based learning experiences in the gymnasium (Gubacs 2004). The iPod touch is one such mobile digital device. The iPod touch is described as a multipurpose pocket-size electronic mobile device. It was designed and marketed by Apple. It has a user interface that is touch screen based. The iPod touch can be used as a music and video player, digital camera, handheld game device, and personal digital assistant (PDA). It connects to the Internet through Wi-Fi base stations. The iPod touch does not use cellular data and is therefore not a smartphone. The iPod touch has the added advantage of being small, lightweight, and easy to carry. It also has a longer battery life. The iPod touch was first released in 2001 and anecdotally is being actively used in many educational contexts for many purposes. Recent applications have improved the use of the iPod touch in many such settings: From kindergarten to college, in applications of all kinds, what was originally designed as a mere portable music player is on its way to becoming an essential educational tool. (Blaisdell 2006, p. 8)

The iPod touch contains easily accessible audio and visual content in what is a manageable size. Recent iPod touch models have become progressively more versatile with an increasing amount of content that can contribute to teaching and learning. In educational contexts, the use of the iPod touch to accommodate students of different ages and different abilities has been very successful. Patten and Craig (2007) have found that writing skills, vocabulary development, and comprehension skills improved as a result of the use of the iPod touch in the classroom. The use of iPod touch photo features has also been advocated for students with learning disabilities in classroom settings. Students can also record their own voice using iTalk (Griffin Technology iTalk 2009). This is a particularly useful feature as it can record notes which can be listened to at a later time and provides an alternative means of completing assignments. In the constantly changing environments of physical education, this can prove invaluable. Students with hearing and/or visual impairments can also benefit from using the iPod touch in an educational context. Broida (2009) identifies Sound AMP as a useful tool in this regard. This application turns an iPod touch into a hearing aid for individuals who have some hearing capabilities. With the built-in microphone, Sound AMP captures audio input and allows the user to adjust volume and tone to improve any hearing experience. There is also a “repeat” feature that replays the conversation over if needed. Students with severe impairments may benefit from the use of applications that teach sign language, e.g., iSign where each of the gestures is modeled with a 3D character and is completely animated. This application is beneficial in that it can help students learn to sign. Students with visual impairments can access book applications which allow users to customize text, color, and size. In a systematic review of studies that involved iPod touches, iPads, and iPhones in teaching programs for individuals

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with developmental disabilities, 15 studies covering academic, communication, employment, leisure, and transitioning across school settings, outcomes for 47 participants who ranged from 4 to 27 years of age and had a diagnosis of autism and/or intellectual disability were positive in supporting the use of iPod touches for this particular population (Kagohara et al. 2013). In the world of physical education, there is a dearth of empirical evidence for the use of actual iPod touches, despite anecdotal evidence from practitioners to the contrary. Physical education teachers and lecturers report the use of the iPod touch to capture video and audio clips in situ, to use as a teaching and learning aid in the classroom, and indeed to encourage and enhance students’ engagement in the physical education curriculum. In the Irish physical education context, one thirdlevel physical education teacher education provider indicates that the iPod touch has an integral role to play in the degree program. In the Bachelor of Education Sports Studies and Physical Education program in the University College Cork, the use of iPod touches are an integral part of many modules. The iPod touch has been used to record and inform the teaching and learning of motor skills in skill acquisition. In this module undergraduate physical education gains hands on experience designing and delivering skill acquisition programs to primary school children. Students are encouraged to video primary school children during program participation in action and to use this as a tool to reflect on their own teaching and learning practice. They are also encouraged to consider the children’s engagement throughout the session and reflect on this after using the iPod touch. Students are enabled to monitor progression of intervention programs addressing fundamental movement skill development from pre- and post-video/audio clips. The iPod touch can also be used to record their own and their peers’ reflections both in action during a session and on action after the session. In addition the iPod touches have been used to record the thoughts and views of participating primary pupils and their teachers on each session. Similarly, in the health stream of the Sports Studies and Physical Education Degree program the iPod touch has been used in a variety of modules. Views and participation of secondary school students, their teachers, community health workers, and undergraduate students are collated during workshops, symposia, and resource development. Again, video footage is also collated in all of these settings for the purposes of informing teaching and learning, module content, and workshop adaptation (Crawford 2015). In the health and aging module, the views of elderly participants are collated on a weekly basis and replayed to students to inform each session as the module progresses. This again has proven invaluable in relation to addressing approaches to teaching and learning and actual program content. In the sport, physical activity, and disability module, the views of participants with disabilities are similarly collated on a weekly basis and again guide the progression through the module (Crawford et al. 2012). This use of the iPod touch to enhance and inform teaching and learning throughout has proven very beneficial to all stakeholders and gives true meaning to the importance of participants’ voices informing the scholarship of teaching and learning in physical education degree programs. More recent studies are currently under peer review and will be published in due course (Crawford and Fitzpatrick 2015).

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Despite being viewed as advanced and innovative, the current conclusion of contemporary technological media and the use of digital multimedia and iPod touches is that they have not been incorporated in the classroom everyday learning practice yet. Both at third level and secondary and primary levels, teachers have difficulties with new technologies due to the lack of formal training to allow them to integrate these devices in their lessons. The cost of new software, together with its supporting systems and the limited access that a large percentage of the student population has to new technologies, is also prohibitive. There is also the continued fear and anxiety in the educational community about the safety of the use of such media. Teachers are anxious that this kind of instruction will discourage students from actively engaging and bodily practicing and experiencing the motor skills they are taught. However, students seem to be enthusiastic and motivated by some new teaching methods, especially if combined with the more traditional approaches (Leijen et al. 2009; Goulimaris et al. 2008). Another finding is that researchers seem to focus on the numbering of the learning results of each intervention, without checking and testing the cognitive processes and demands of the technologically supported instruction. Moreover, the evaluation of the newly suggested methods is confined either to the interpretive assessment of questionnaires and interviews or to the comparisons between one medium and another.

4

Future Directions

Although there are other devices available for teaching and learning in physical education, the iPod touch has the potential to become the preferred device based on its versatility and portability. It is critical to recognize that the selection and design of such a device must reflect a collaborative team approach and must include the student and staff familiar with the device. It is also essential that we remember that while technology can offer many opportunities for enhanced teaching and learning in a physical educational environment, we must use it with a complimentary focus as indicated earlier and not simply as a teaching aid in itself. Ongoing empirical studies are necessary in a sports studies and physical education context to establish its efficacy going forward.

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Beddall-Hill, N., and J. Raper. 2010. Mobile devices as “boundary objects” on field trips. Journal of the Research Center for Educational Technology 6(1): 28–46. Blaisdell, M. 2006. In iPod we trust. T.H.E Journal 33(8): 30–36. Blomqvist, M.T., P. Luhtanen, and L. Laakso. 2000. Validation of a video-based game: Understanding test procedure in badminton. Journal of Teaching in Physical Education 19: 325–337. Boyce, B.A., N.J. Markos, D.W. Jenkins, and J.R. Loftus. 1996. How should feedback be delivered? Journal of Physical Education, Recreation & Dance 67(1): 18–22. Broida, R. 2009. SoundAMP turns an iPhoneiPhone into a hearing aid. http://reviews.cnet.com/ 8301-19512_7-10281062-233.html. Accessed 13 July 2009. Calandra, B.D., R. Gurvitch, and J.L. Lund. 2008. An exploratory study of digital video editing as a tool for teacher preparation. Journal of Technology and Teacher Education (JTATE) 16(2): 137–153. Cherry, G., Fournier, J., and Stevens, R. 2003. Using a digital video annotation tool to teach dance composition. Interactive Multimedia Electronic Journal of Computer-Enhanced Learning 5(1). http://imej.wfu.edu/articles/2003/1/01/index.asp. Accessed 14 June 2007. Chirico, J. 2002. TiVo – The best innovation for diving since the cheese board. In Retrieved 12 May. Cited In Leight, Joanne, Dominique Banville, and Michael F. Polifko. 2009. Using digital video recorders in physical education. Journal of Physical Education, Recreation & Dance 80(1): 17–21. Chu, L., and Chen, W. 2000. Multimedia application to motor skill learning. Proceedings of ED-MEDIA, 2, 1257–1258. Montreal, USA. Crawford, S. 2015. Examining the process of University- School- Community collaboration in an Irish sports studies and physical education context. Irish Educational Studies. Accepted in press. Published on line 7th April 201256. 1–19. Crawford, S., and Fitzpatrick, T. 2015. Use of the iPod touch in skill acquisition programmes in a Sports Studies and Physical Education degree programme in Ireland. Study in progress. Crawford, S., R. O’Reilly, and S. Luttrell. 2012. Assessing the effects of integrating the reflective framework for teaching in physical education (RFTPE) on the teaching and learning of undergraduate sport studies and physical education students. Reflective Practice 13(1): 115–129 (15). Deakin, J.M., and L. Proteau. 2000. The role of scheduling in learning through observation. Journal of Motor Behavior 32: 268–276. Engel, G., and Green, T. 2011. Cell phones in the classroom: Are we dialling up disaster. Tech Trends 55(2):22–25. Engel, G., Palloff, R., Pratt, K. 2011. Using mobile technology to empower student learning. In 27th annual conference on distance teaching and learning, University of Winsconsin 1–4. Everhart, B.W., C. Harshaw, B.A. Everhart, M. Kernodle, and E. Stubblefield. 2002. The effect of physical education students using multimedia computers to improve physical activity patterns. The Physical Educator 59: 151–157. Fiorentino, L.H., and D. Castelli. 2005. Creating a virtual gymnasium. Journal of Physical Education, Recreation & Dance 76(4): 16–18. Foster, B. 2004. Video analysis of muscle motion. Strategies 17(4): 11–12. Frohberg, Dirk. 2006. Mobile learning is coming of age-what we have and what we still miss. DeLFI, Darmstadt, Germany. Garrison, D.R. 2011. Elearning in the 21st century, 2nd ed. New York: Routledge Falmer. Goulimaris, D., M. Koutsouba, and Y. Giosos. 2008. Organisation of a distance postgraduate dance programme and the participation of students specializing in dance. Turkish Online Journal of Distance Education 9(3): 59–73. Griffin technology: iTalk – A recording app for your iPhone or 2nd gen iPod Touch. http://www. griffintechnology.com/products/italk. Accessed 13 July 2009. Gubacs, K. 2004. Project-based learning: A student-centered approach to integrating technology into physical education teacher education. Journal of Physical Education, Recreation & Dance 75(7): 33–37. 43.

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Gubacs-Collins, K., and S. Juniu. 2009. The Mobile Gymnasium. Journal of Physical Education, Recreation and Dance 80(2): 24–31. Herrington, J., Herrington, A., Mantei, J., Olney, I., and Ferry, B. 2009. Using mobile technologies to develop new ways of teaching and learning. In New technologies, new pedagogies: Mobile learning in higher education, eds. Herrington, J., Mantei, J., Olney, I., Ferry, B., and Herrington, A., pp. 1–14. Wollongong: University of Wollongong. http://researchrepository.murdoch.edu.au/ 5227. Kagohara, D. M., van der Meer, L., Ramdoss, S., O’Reilly, M. F., Lancioni, G. E., Davis, T. N., Rispoli, M., Lang, R., Marschik, P. B., Sutherland, D., Green, V. A., Sigafoos, J. 2013. Using iPods( ®) and iPads( ®) in teaching programs for individuals with developmental disabilities: A systematic review. Research in Developmental Disabilities, Vol 34(1), pp 147–156. Kavakli, E., Bakogianni, S., Damianakis, A., Lamou, M., and Tsatsos, D. 2004. Traditional dance and elearning: The WebDance learning environment. http://www.aegear.gr/culturaltec/ webdance/publications.htm. Accessed 14 Feb 2015. Lai, K. W. 2008. ICT supporting the learning process: The premise, reality, and promise. In International handbook of information technology in primary and secondary education, eds. Voogt, J., and Knezek, G., Vol. 20, No. 3, 215–230. Berlin, Springer. Leijen, A., I. Lam, L. Wildschut, P. Robert-Jan Simons, and W. Admiraal. 2009. Streaming video to enhance students’ reflection in dance education. Computers & Education 52: 169–176. Leijen, Ä., W.F. Admiraal, E.M.M. Wildschut, and P.R.J. Simons. 2008. Students’ perspectives on e-learning and the use of a virtual learning environment in dance education. Research in Dance Education: Innovations in Arts Practice 9(2): 147–162. 16 p. Lunsford, J. 2010. Using handheld technologies for student support: A model. Journal of the Research Center for Educational Technology 6(1): 55–69. Martindale, T., S. Ryan, and S. Marzilli. 2001. Using digital cameras to assess motor learning. Journal of Physical Education, Recreation & Dance 72(8): 13–16, 18. Mock, K. 2004. Teaching with tablet PCs. Journal of Computing Sciences in Colleges 20(2): 17–27. Papastergiou, Marina. 2010. Enhancing physical education and sport science students’ self-efficacy and attitudes regarding information and communication technologies through a computer literacy course. Computers & Education 54(1): 298–308. Papastergiou, M., V. Gerodimos, and P. Antoniou. 2011. Multimedia blogging in physical education: Effects on student knowledge and ICT self-efficacy. Computers and Education 57(3): 1998–2010. Patten, K. B., and Craig, D. V. 2007. iPods and english-language learners: A great combination. Teacher Librarian 34(5): 40–44. Presented at the annual conference on innovation and technology in computer science education, Canterbury. Penrod. 2005. As cited in Äli Leijen, Wilfried Admiraal, Liesbeth Wildschut, and P. Robert-Jan Simons. 2008. Students’ perspectives on e-learning and the use of a virtual learning environment in dance education. Research in Dance Education 9(2): 147–162. https://doi.org/10.1080/ 14647890802087951. Popat, S. 2002. The TRIAD project: Using internet communications to challenge students’ understanding of choreography. Research in Dance Education 3(1): 21–34. Risner, D., and J. Anderson. 2008. Digital dance literacy: An integrated dance technology curriculum pilot project. Research in Dance Education 9(2): 111–126. Sorrentino, R. 2000. A simulation of internet enhanced motor learning. Phd thesis, University of Calgary, Canada. Vernadakis, N., E. Zetou, E. Tsitskari, M. Giannousi, and E. Kioumourtzoglou. 2008. Student attitude and learning outcomes of multimedia computer-assisted versus traditional instruction in basketball. Educational Information Technology 13(3): 167–183. Wise, John C., Roxanne Toto, and Kyu Yon Lim. 2006. Introducing tablet PCs: Initial results from the classroom. Frontiers in education conference, 36th annual. IEEE.

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The Mission of Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Administration and Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 IT Concerns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Digital Citizenship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Educator Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Professional Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Increased Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 “There’s an App for That!” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Classroom Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

As gatekeepers of the students’ futures, schools can no longer provide education that lacks the needed digital skills to excel in the twenty-first-century world. Teachers cannot fail to equip students with these skills without compromising the professional futures of their learners. Increasing digital literacy is the clearly stated goal for both International Society for Technology in Education (ISTE) and Common Core State Standards (CCSS). Yet, actual use of digital tools in schools remains inadequate, contributing to the digital divide. Slow-to-adopt districts and classrooms have typically cited IT security and bandwidth concerns, parental objections, lack of technological professional development, and difficulty accommodating access for all students, or “the digital divide.” Many of D. L. White (*) Liberty University, Lynchburg, VA, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_78

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these concerns are addressed through IT departments and communication with parents. However, teachers still need to be given more professional development training in education technology to help them integrate these tools into their educational practices and shift their teaching toward twenty-first-century culture. Teacher adoption of digital tools in lesson planning, implementation, and assessment can only happen after they have first learned these skills and practiced with the tools outside the classroom. This kind of professional development will help teachers model critical contemporary skills and become gatekeepers for students crossing the digital divide into millennial careers.

1

Introduction In times of drastic change, it is the learners who inherit the future. The learned usually find themselves beautifully equipped to live in a world that no longer exists. —Eric Hoffer

It is true that, in this day and age, change is taking place so rapidly that the world students enter upon graduation does not resemble the world as it was when they began learning. One way to stay abreast of change is through a primary agent of it in modern society: technology. Instruction and technology have walked hand in hand for decades now in ever-increasing degrees. Lou Yipling and his associates (2001) found statistically significant positive learning effects at all levels with computerassisted instruction in PK (mean E S = +0.55), all the way through adults in training situations (mean ES = +0.22) with scores for elementary, secondary, and college falling between. What was facilitated with computers 12 years ago has expanded greatly, and it is currently expressed in personal devices today. Due to lowered costs of these devices (such as tablets, laptops, and smart phones) and increased use for social media as well as information, the use of personal devices in everyday life is here to stay. This can be good news for schools as well, and harnessing their use in education is yielding higher engagement in learning as a potential cost-saving move across the nation. This is known as BYOD, or bring your own device. By making positive use of this technology, instead of discouraging it like a nuisance, such devices prove their purpose as educational tools in the classroom instead of mere social distraction. Implementing BYOD has special requirements for IT, administrators, instructors, and students alike if it is going to run successfully.

2

The Mission of Education

Education is always a mission whether overtly or quietly inherent. There is no knowledge that can be passed from one generation to the next devoid of a worldview or religion. The culture of education is not neutral. Followers of Jesus Christ have a clear calling for education to be infused with His truth and to hold impactful significance for the student’s worldview. If an instructor’s educational mission

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field is in the fields of Africa, they would learn African ways of doing things, talk their language, enter into their paradigm, find points shared in common, and so on. If it were in India, the educator would need to relate in these ways in Indian culture. There is no less of a mission in the field of US education and/or online learning. Mobile learning should include the positive employment of social media. Objections about social media and the Internet in education are not about its educational use. It is about its social misuse. This should not equate a banning of social media in education; instead it decries (profoundly) how necessary it is to educate students on the right use of it, missing how useful it could be. Picture a world entering the dawn of the Internet and social media where educators said, “Wow! This is really powerful; we should teach ourselves how to harness it and guide our children through it.” First, they learned how to secure data and kept this concept updated frequently and taught digital citizenship to all users. Second, they explored the possibilities with students finding out what could be done to research more fluently, publish more with impact, keep content discussions ongoing outside the classroom, help learning become more enjoyable, assess actual learning more regularly, go paperless, increase information for parents, enable data-driven decisions, reach more homebound students, create OERs (open educational resources) to share with the world, share culturally with other classes, adopt causes advocating to a global audience, collaborate with other teachers, help students collaborate more, develop lesson plans with sources all included, and increase student ownership of their learning. After all, the students are creating a digital footprint that could stick with them through college and careers.” This world is still possible through technology and mobile learning, and it is happening today. In mobile learning, bring your own device (BYOD) is a practice where schools must “get onboard or get run over.” So many staff and students are already bringing personal devices to school making its accommodation unavoidable and setting up security for it inevitable. When schools choose to harness this, personally owned devices become a valuable tool instead of a disciplinary problem. The BYOD movement is among the top ten trends in education technology (Becker 2013). Common Sense Media (2013) reports the rise of personal ownership of mobile devices and identifies that 75% of children have access to mobile devices at home. While a growing number of children utilize educational applications on mobile devices, Walling (2012) places on the importance of integrating classroom devices, the Internet, and personal devices to achieve academic excellence through technology in education. Best practices can be identified by lining them up within five categories of recommendations from the National Education Technology Standards (NETS) of the International Society for Technology in Education (ISTE). They are as follows: facilitate and inspire student learning and creativity, design and develop digital age learning experience and assessments, model digital age work and learning, promote and model digital citizenship and responsibility, and engage in professional growth and leadership. When it is realized that security, acceptable use, and professional development are not only achievable, but actually an asset, it becomes easier to sell this concept to your community and funding consortia, and then all stakeholders win.

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Technology for technology’s sake alone is not a worthy goal, and it can become a distraction or even detraction, from the goals of learning. Therefore, guiding education with technology, whether through assisting the instructor or the student, begins with the stated goals of the educator, the parent, the student, and the curriculum. Where technology enters into the picture is to further the communication between teacher and parents, teacher and students, students and one another, students and outside experts, and students and the course materials and to provide a platform of practice for their newly acquired skills in a style of differentiated instruction. Educational technology, through online computing, apps, and software, offers the greatest opportunity for both collaborative and individualized learning which hallmark current learning theory. Furthermore, “in order to be relevant in our present culture, we must respond to the growing body of knowledge in core subject matter and resources with content expectations that have grown exponentially. Language must now include the grammar of technology and the Internet (November, 2008). These things must be reflected in our mission of education. There are six standards for effective practice: 1. Students demonstrate creative thinking, construct knowledge, and develop innovative products and processes using technology. 2. Students use digital media and environments to communicate and work collaboratively, including at a distance, to support individual learning and contribute to the learning of others. 3. Students apply digital tools to gather, evaluate, and use information. 4. Students use critical thinking skills to plan and conduct research, manage projects, solve problems, and make informed decisions using appropriate digital tools and resources. 5. Students understand human, cultural, and societal issues related to technology and practice legal and ethical behavior. 6. Students demonstrate a sound understanding of technology concepts, systems, and operations (International Society for Technology in Education 2008).

3

Security

3.1

Administration and Policy

The ability of schools to meet the growing demand of integrating technology in the classroom is growing. By identifying the barriers and readiness of schools to implement the use of personal mobile devices into existing curriculum, schools face both challenges and innovative means to integrate a variety of mobile devices to enhance the learning experiences of digital natives of the twenty-first century. Exploring the results of successful implementations and failed BYOD programs helps prepare education technologists and teachers to brace themselves for a technology movement, which affects budgetary decisions for digital equipment, bandwidth allocations, firewalls, computer security, and classroom management.

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Administrators must come in ahead of adopting BYOD policies with full institutional commitment. Mobile phones, social media, blogs, Wikipedia, and so on are not inherently troublesome; only their misuse is. Blocking these things does not make the schools more secure, but it does limit the educational capacity of technology for teachers and students who are trained on how to use them. Therefore, it should be a priority in education to teach proper navigation of these tools that are already ingrained in our students’ lives. This is more effective than any filtering device that can be hacked through. “Educating is always more powerful than blocking” (McLeod 2012). Professional development, community awareness, security, and funding all fall under the leadership of school administration. Teachers, parents, IT staff, and consortia will only be positively involved if they are lead to be. Developing a school BYOD policy “may include how to manage (a) authorized use, (b) prohibited use, (c) systems management, (d) policy violations, (e) policy review, and (f) limitations of liability” (Emery 2012), but it also requires a great deal of encouragement and PR.

3.2

IT Concerns

BYOD is not possible without the hard work of involved IT staff. Wi-Fi and Web 2.0 tools are device neutral, which reduces the complexity of integrating a variety of devices into one location. A floor plan of all buildings, including the location of all cement and brick walls, is necessary to facilitate optimal bandwidth in all areas of access. It is consistently recommended to allow for far more bandwidth than initial needs assessments show because BYOD frequently yields many more devices coming in than anticipated (Xirrus 2012), plus its use gains momentum as more and more creativity gains progress. Quarantined network for students’ devices, up-to-date antivirus scanning programs, protecting data in the cloud, and tiered access separating school system data for IT, administration, teachers, students, and guests all guard against lost or altered data, as well as a host of other potential problems. Once the school is ready to adopt BYOD, listen to the plans of involved teaching staff and allow time to choose and develop standards, hardware, software, instruction, and networking so it can be established into the infrastructure (Ullman 2012). Just like over estimating bandwidth, leaving plenty of room for adjustment and growth is a must or the initial hard work will be outdated too soon. Many districts base as much of this as they can in cloud technology for more seamless expansion and growth.

3.3

Digital Citizenship

Students are eager to get onboard with BYOD, not only for social media but for social learning, ease of research, and collaboration. They are more than willing to gain the privilege by first learning and committing to good acceptable use policy and Internet safety. This is their role in security. Common Sense Media offers a

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curriculum to middle school-aged minors for gaining savvy in the digital world where knowledge increases safety. Their topics are as follows: Digital Life 101 (6–8), Strategic Searching (6–8), Scams and Schemes (6–8), Cyberbullying: Be Upstanding (6–8), and A Creator’s Rights (6–8) (www.commonsensemedia. org), covering everything from stranger danger to copyright law which goes far in satisfying Common Core technology goals and CIPA (Children’s Internet Protection Act) requirements. High school students can earn a DDL, or digital driver’s license, by passing sections of curriculum on digital etiquette and security, access, healthy communication, laws, rights and responsibilities, etc. (Swan and Park 2012–2013).

4

Educator Opportunities

4.1

Professional Development

Educational technologists are a bridge for the technology generation gap that resides between great, tenured teachers who did not have technology in their education and this generation of learners and a positive mentor for online students of all ages. It is important to continue learning to gain enough skill to lead them and help others continue to lead them and relate to students in their own online world. There are many effective ways for PD in technology to infiltrate school as educators and students begin to increase the use of technology in classrooms. Some schools have younger, more tech savvy teachers already using it who are encouraged to pass it on through their department, while others are simply providing tablets to ten teachers at a time and asking them to discover what can be done with it. ISTE reported that one district in Arizona is organizing a splashy show-and-tell conference for educational technologists and software designers to set up displays to inspire their local teachers and then break out into small groups for practice sessions. Why not propose CE credits for downloading or attending sessions from tech conferences and presenting it locally? Hiring educational technology specialists is always a worthy investment that can produce measurable results. Contact state professional organizations for education technology for information on their annual conference and subscribe to their newsletters for the teacher’s lounge. Always remember, though, to invest in only those things that serve the educational goals instead of having education serve technology. Technology offers a very flexible method of professional development through the use of communication suites like Adobe Connect. Teacher instruction, staff development, and leadership can be exercised in real time and asynchronistically, in small groups or as an entire staff, and attendance registries can assist in crediting continuing education. This increases opportunity for staff development by not requiring physical attendance on campus, especially for the support and management of online instructors.

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Increased Interaction

This is a vast mission field without any global boundary that can reach parts of every nation in the world accessible through the Internet. It affords nearly endless opportunities for interaction and helps to decide if it is positive or negative in nature. If this mission field is only cluttered with the accoutrements of the world, then it will serve to make the lost more lost. If the distractions are refined, harness the learning power of instantly ready information, and distill it to the students in an engaging manner, the online environment for this mission is captured . Students across the world are in the online environment all the time without their distinctly Christian influence for a significant part of their social and academic life. This is a mission field that spans the globe, and it envelopes our own children as well. It should not be abandoned to the non-Christian world. The strongest advice for teachers integrating technology into the classroom is to adopt a proactive teaching pedagogy that includes solid learning outcomes. Education can be more engaging through technology with its endless applications creating opportunity. Opportunity to vary teaching and learning style, to relate to students in their digital world, publishing opportunities, research opportunities, collaborative opportunities, and much more is possible. Teachers are blending and flipping their classrooms because it allows for more interaction, not less. This is through teacher to student, student to student, teacher to class, student to class, class to outside sources, and student to learning objects and course materials. They are drawing in less talkative students through text and class wikis, mainstreaming special needs of students through alternative communication modes, and using virtual field trips and lab projects for active class participation during lectures. When portions of instruction are prepared digitally through video, it can be assigned for homework outside of class time buying valuable time for projects and collaboration during class (this is what is commonly known as “flipping” the classroom because the lecture is at home, and the application or practice is done together in class) (Bergmann and Sams 2008). Virtual field trips, videos, and labs are all examples of learning objects which become more readily available for knowledge building and can be used again and again or shared between teachers (Cohen and Nycz 2006).

4.3

“There’s an App for That!”

All of these things, and more, are possible with the many websites and apps available online now. (Check out http://www.appsinclass.com/apps.html.) Publishing opportunities (audio, video, and written) and exploring the ICDL children’s digital library, student response systems, and Google Earth maps all are waiting to serve learning goals. Collaborative storage tools like Dropbox allow sharing between teachers, and Google Docs is perfect for student teamwork on projects. Social media is for conversations with experts and authors, flashcards skill builders, listening center activities, and formative assessment apps abound. Check out just a few school

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favorites from A–Z: Adobe, Alice, Audacity, audioBoom, Blackboard, Blogger, CamStudio, Camtasia, Discovery streaming, Dreamweaver, Dropbox, Edmodo, Engage LMS, Evernote, Flashcards Deluxe, GarageBand, Glogster, Google Apps for Education and the Teacher Dashboard, iMovie, iWork, Jing, Microsoft Office Suite, Moodle, MS OneNote, Poll Everywhere response system, Prezi, Quizlet, QR barcodes, Remind101, Sketchpad, SMART Boards, SMART Pens, Spaaze, TurningPoint, Twitter, Visual Basic, VoiceThread, Voki, WorldCat, YouTube, and Zangle. Edmodo has been nicknamed the “Facebook” of education. It provides a closed environment for the class created within it to communicate, collaborate, and follow links for assigned work. It helps parents, students, and teachers stay coordinated and provides a real time opportunity to communicate in between classes that are on campus. Edmodo is a great central hub to plug in other tools for your students and parents to use. Jing is a screen capture program that allows instructors to tutor through a video that shows their computer screen while voicing over instructions on how to complete an assignment or use a piece of software. Avatars are not only fun for presenting coursework but also provide a degree of anonymity in online work for underaged students, so it is a good practice to teach for when students launch out into other online endeavors. StudySync provides web-based educational content about literature across subject matters. It assigns peer to peer reviewing of written responses to literature and other assessment tools that can be customized or used as provided. LogMeIn Rescue is a free remote access program that will allow permission to access another person’s computer if they are struggling with technology and need assistance with using the virtual classroom. Fluency21 is a lesson plan generator. This site fosters more intentional planning to flexibly accommodate students anywhere within the digital divide to more actively engage twenty-first-century learning skills and includes a debriefing session for each lesson for future improvement. It also makes an open educational resource contribution to the global learning community at large. OERs, or open educational resources, are making an enormous impact in education by being available freely to all who can access the Internet.

4.4

Classroom Management

As instructors begin to rethink their presentations in class and incorporate new things, behavior management naturally comes to mind. Will BYOD be a “blessing or a bane?” Is it disruptive or does it truly make learning and use of time in class more efficacious? What does technology offer in contribution to behavior management? First of all, real-life application has shown that when engagement in class goes up, behavior issues decrease (Higgins 2011). Next, recognize that Rome was not built in a day and just slowly add in elements of instruction as they are learnt. This will avoid the loss of time and attention to awkward integration when the teacher is overwhelmed. Lastly, do not abdicate teaching to technology; it is only a tool and the teacher must still be actively in charge. Train classes in acceptable use and accountability, capitalizing on their desire to have these “cool tools.”

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Some teachers have captured the usefulness of the QR code to set the tone for each class immediately upon entering the room. A QR code is the black and white SKU code that can be scanned with phones and connect to the Internet message or link(s) it contains. At school the captured information that students scan might be “Watch this 5 min video and begin a five-sentence paragraph response.” Or, “Swap homework with your partner and correct each other’s answers; be prepared to show an example on the white board, one fact others may have also gotten wrong.” In this way, students entering the room know to come in ready to be engaged in the class right away. When the teacher is ready to speak or to get everyone involved in group learning, they then begin with, “Okay, place all devices on the upper right corner of your desk. . ..” Make it a class policy that devices are allowed as long as they remain in sight at all times and are turned on for educational use only. As they leave the room, text out any reminders for the next class through Remind101. Data input is another great reason to use technology as a teacher. Students can use devices for response systems during class discussion and have formative feedback immediately as they learn. This can also tabulate classroom behavior in the elementary to show earning (or losing) reward points as they go. One such reward program, ClassDojo, also has links to report great (or negative) behavior to parents right away. Keeping your data app available during class allows input to be calculated into grades in real time rather than the instructor having to calculate them later. Yet another advantage of BYOD is the increased ownership of learning as students search out information to apply to the lesson and accept responsibility for acceptable use policy. This is a good reflection of the educational trend of teachers becoming more like facilitators of learning rather than providers of information. The same sense of ownership is reflected in the inherent responsibility for taking care of the device. It has been shown that much greater care is taken if it is their own, than if it is a school-owned device. Encourage ownership of the AUP at school, as well, by having the students help set school-wide rules on the use of student-owned devices. Be sure to begin by establishing high classroom expectations for use and then let the learning roll.

4.5

Assessment

New concepts in assessment are growing out of educational technology, some that are mobile-learning friendly as well, that have potential to become new best practices. Online assessment is coming to schools by this year, 2015! As many educators consider the woes of assessments, their ability to effectively evaluate learning and teaching to the test, the development of online assessment has forged on. Mitch Fowler, in his article “Online Assessment: From Instant Access to Meaningful Decision Making” (2013), advocates for computer-adaptive assessment and immediate access to results for next-step decision making for teachers and professional development choices for administrators. Knowing sooner what weaknesses are being expressed in current classroom and campus dynamics allows for quicker intervention. In theory, this goes beyond teaching to the test and allows assessment

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to retake its proper role in guiding instruction. It will be interesting to track the impact of this technology to see if it, in fact, accomplishes this ideal or merely drives the current trend of the tail wagging the dog even faster than ever before. Many are hoping it achieves the desired improvement. Assessment ultimately occurs in the way that Internet use builds a digital footprint. Educators should help students cultivate a positive one. What about passing on this practice to secondary students? Elementary? Fontichiaro and Elkordy (2013) teach all about data-loaded badges that students of all ages can earn and keep in online backpacks that highlight interests, skills, and accomplishments in students’ lives not consistently represented on the traditional report card. A new online open-source framework called Open Badges Infrastructure coordinates the creation of badges and their ability to showcase in a positive way for students. It provides reinforcement for anywhere/anytime learning outside of school, and it is a great way to teach portfolio creation and positive cultivation of an online reputation. Michael and Amanda Szapkiw (2010), in their website for graduate classes on instructional design, state that authentic assessment includes live performance, demonstrations, projects, and portfolios, and they challenge teachers to find more. One final test of educational worth is employability. Google hiring practices provide an interesting case in point. J.R. Sowash, in his blog, The Electric Educator, posted the recent NY Times article on Google interviews and concluded, “Teaching (and learning) facts will not prepare students for success. Teaching them how to interpret, analyze, and evaluate and apply information will. Google is looking for critical and creative thinkers, not Jeopardy champions.” Reeves et al. (2002) call for several authentic online practices that place strong priority on “real-world relevance” and activities that “are seamlessly integrated with assessment.” This is called formative assessment which is a much better indicator for employers than the artificial assessment of static pencil tests with singular right answers. Take note of the following excerpts from that NY Times article Sowash shared: In Head-Hunting, Big Data May Not Be Such a Big Deal by Adam Bryant (2013). It was an interview with Laszlo Bock, senior vice president of people operations at Google, and he has a lot of valid points for educators to consider about tech integration and assessment! I think this will be a constraint to how big the data can get because it will always require an element of human insight. I don’t think you’ll ever replace human judgment and human inspiration and creativity. G.P.A.’s are worthless as a criteria for hiring, and test scores are worthless — no correlation at all except for brand-new college grads, where there’s a slight correlation. Google famously used to ask everyone for a transcript and G.P.A.’s and test scores, but we don’t anymore, unless you’re just a few years out of school. We found that they don’t predict anything. . . . academic environments are artificial environments. People who succeed there are sort of finely trained, they’re conditioned to succeed in that environment. One of my own frustrations when I was in college and grad school is that you knew the professor was looking for a specific answer. You could figure that out, but it’s much more interesting to solve problems where there isn’t an obvious answer. You want people who like figuring out stuff where there is no obvious answer.

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Future Directions

There are many worthwhile reasons to integrate mobile learning into the education of students. Furthermore, the ability to implement it continues to improve year by year. Administrators and IT can work together on realistic security and infrastructure options. All stakeholders can work together to develop effective AUP and classroom management strategies. Then the positive effects of increased engagement and interaction in learning combined with reduced behavioral problems can yield desired educational achievement. It is not only possible to implement BYOD; it is to everyone’s advantage to encourage and exercise positive digital citizenship with this generation of learners. According to the National School Board Association, these skills are among several that have been identified as crucial to future success: • • • • • •

Capacity for continued learning Cooperation and team building Precise communication in a variety of modes Problem solving with creativity and ingenuity Generation and organization of A LOT of technologically produced information Craftsmanship of products and ideas

In an educational community teachers are investing ideas and concepts into students and planting seeds that will last for years beyond any current school year. It is something that must be done intentionally and with integrity because of the potential to reach far into the lives of learners. Teachers are stewards of truth, knowledge, confidence, and direction. These skills are essential to communicating knowledge and skills. Collaborative, blended learning environments foster the development of them better than classes lacking the social media and technology infused in them. They open the gateways to millennial careers.

References 2009 Michigan Educational Technology Standards for Students. http://www.michigan.gov/docu ments/9-12_150927_7.pdf 2010–2015 Educational technology plan for Virginia. n.d. Retrieved from http://www.doe.virginia. gov/support/technology/edtech_plan/plan.pdf Bergmann, J., and A. Sams. 2008. Remixing chemistry class. Learning and Leading with Technology 36(4): 24–27. Bonk, C. n.d.. Retrieved from http://trainingshare.com/keynotes.php Bryant, Adam. June 19, 2013. In head-hunting, big data may not be such a big deal. Retrieved from http://www.nytimes.com/2013/06/20/business/in-head-hunting-big-data-may-not-be-such-a-bigdeal.html BYOD One Year Later. February, 2013. Technology & Learning 36–39. Retrieved http://www. schoolcio.com/section/feature-articles/109/page/1

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BYOD Strategies. February, 2012. Technology & Learning 32(7):34+. http://go.galegroup.com. ezproxy.liberty.edu:2048/ps/i.do?id=GALE%7CA279613035&v=2.1&u=vic_liberty&it=r& p=ITOF&sw=w Chambers, Bette, Philip Abrami, Bradley Tucker, Robert E. Slavin, Nancy A. Madden, Alan Cheung, and Richard Gifford. 2008. Computer-assisted tutoring in success for all: Reading outcomes for first graders. Journal of Research on Educational effectiveness 1(2): 120–137. https://doi.org/10.1080/19345740801941357. Cohen, E., and M. Nycz. 2006. Learning objects & e-learning: An informing science perspective. Retrieved on 23 Jan 2013 http://www.ijello.org/Volume2/v2p023-034Cohen32.pdf Dabner, N., N. Davis, and P. Zaka. 2012. Authentic project-based design of professional development for teachers studying online and blended teaching. Contemporary Issues in Technology and Teacher Education 12(1): 71–114. AACE. Retrieved from http://www.editlib.org/p/37659. Donald, N.M., and D.A. Kate. 2003. Evaluating the effectiveness of computer tutorials versus traditional lecturing in accounting topics. Journal of Engineering Education 92(2): 189–194. Retrieved at http://search.proquest.com/docview/217944177?accountid=12085. Dunn, R. April 12, 2013. Interview by D.L. White []. Technology Implementation planning. Emerging learning technologies. March, 2013. Retrieved from http://r685glossary.shutterfly.com/ Emery, S. July 17, 2012. Factors for consideration when developing a bring your own device (BYOD) strategy in higher education. Applied Information Management Master's Capstone Projects and Papers, University of Oregon. Retrieved: https://scholarsbank.uoregon.edu/xmlui/ handle/1794/12254 Fontichiaro, K., and A. Elkordy. 2013. Getting started with digital badges. MACUL Journal 34(1): 30–31. Fowler, M. 2013. Online assessment: From instant access to meaningful decision making. MACUL Journal 34(1): 18–19. Higgins, L. 2011. School’s radical flip gets results. Retrieved 11 Dec 2011 from: Detroit Free Press. 23 Oct. 2011. Introduction to technology and diversity. n.d. PowerPoint presentation. Liberty University. http:// bb7.liberty.edu/bbcswebdav/courses/EDUC629_D01_201320/module01_introduction/module 01_introduction_controller.swf ISTE|NETS Teacher Standards. 2008. International society for technology in education|home. N.p., 2007. Web. 2 May 2013. http://www.iste.org/standards/nets-for-students/nets-student-stan dards-2007.aspx Johnson, D. 2012. On board with BYOD. Educational Leadership 70(2): 84–85. McLeod, S. November 2, 2012. 27 talking points about internet safety. Retrieved http://www. schoolcio.com/cio-feature-articles/0109/27-talking-points-about-internet-safety/53145 Missouri Department of Elementary and Secondary Education. February 7, 2013. Six-step process in creating a technology plan. http://dese.mo.gov/divimprove/instrtech/techplan/gettingstarted. htm#GUIDINGQUESTIONS National School Board Association. n.d. Education leadership tool kit: Change and technology in America’s schools. http://www.nsba.org/sbot/toolkit/esskls.htm Presentation-Differentiated Instruction. PowerPoint presentation. Liberty University EDUC629. http://bb7.liberty.edu/bbcswebdav/pid-20098071-dt-coducationntent-rid-138714857_1/courses/ EDUC629_D01_201320/presentation_differentiated_instruction/presentation_differentiated_ instruction.swf Raths, David. 2012. Are you ready for BYOD? The Journal 39(4): 28–32. Reeves, T.C., J. Herrington, and R. Oliver. 2002. Authentic activities and online learning. In HERDSA 2002 quality conversations, Perth, 7–10 July 2002. Romiszowski, R.J. 2004. How’s the e-learning baby? Factors Leading to Success or Failure of an Educational Technology Innovation Educational Technology 44(1): 5–27. Simonson, M., S. Smaldino, M. Albright, and S. Zvacek. 2012. Teaching and learning at a distance: Foundations of distance education, 5th ed. Boston: Allyn & Bacon. ISBN 9780132487313.

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Sowash, J.R. 2013. The electric educator @Blogger google doesn’t care about grades or test scores. Spector, J., M. Merrill, J. Van Merrienboer, and M. Driscoll. 2008. Handbook of research on educational communications and technology, 3rd ed. New York: Routledge. Sprankle, B. May 2, 2012. A plan for technology integration. School CIO. NewBay Media. Retrieved: http://www.schoolcio.com/cio-feature-articles/0109/27-talking-points-about-inter net-safety/53145 Swan, G., and M. Park. 2012–2013. Students need a digital drivers license before they start their engines. Learning and Leading with Technology, ISTE 26–28 Szapkiw, Michael., and Amanda. 2010. http://www.amandaszapkiw.com/elearning/principles-ofdesign/module-4-2/types_of_assessments.html Thiele, H., E. Ullman, J. Salpeter, K. Hogan, and C. Weiser. 2012. The schoolcio leadership guide. Technology & Learning 33(4): 25–26, 28–30, 32, 34–36, 38, 40, 42–44. Retrieved http://search. proquest.com/docview/1243357115?accountid=12085. Ullman, E. 2012. BYOD and security: How do you protect students from themselves? School CIO Special Section, 32–36. New Bay Media, LLC. Retrieved www.schoolcio.com Violino, B. 2012. Education in your hand. Community College Journal 83(1): 38–41. Retrieved http://search.proquest.com/docview/1039556536?accountid=12085. Ward, M., T. Steeb, D. Tolliver, D. White, and J. Fleming. 2013. Mobile learning: BYODA literature review manuscript submitted for publication. Xirrus. 2012. Tablets in the enterprise: Considerations for managed device and BYOD strategies. Retrieved http://www.xirrus.com/cdn/pdf/xirrus_whitepaper_byod Yiping, L., P.C. Abrami, and S. d’Apollonia. 2001. Small group and individual learning with technology: A meta-analysis. Review of Educational Research 71(3):449–521. American Educational Research Association, Retrieved: Article Stable URL: http://www.jstor.org/stable/ 3516005

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Contents 1 Theoretical Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Defining Trust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Trust/Ditrust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 As a Continuum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 As Two Constructs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Trust and the Way We Behave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Trust: Social Networks and Online Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Cultural Influences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Positioning Trust in the Sphere of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Participatory Communities/Shared Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Moving Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Today’s youth experience life with and through their cell/smart phones. In researching the impact of mobile technology on literacy practices, I found that while access to phones and digital spaces was not a significant issue, trust was. Trust generalizes from social interactions and is positively associated with trusting of unknown others. Those who trust are comfortable engaging with others not previously known; they trust that others, through association, have similar interests and will behave in certain, predictable, positive ways. The willingness to be open to and actively engage with others is assumed. Prior experiences impact how we trust. While mobile technology can lead us to doors that open into new spaces and places, the how and why of one’s trust

M. J. Hoff (*) Department of Teaching and Curriculum, Warner School of Education and Human Development, University of Rochester, Rochester, NY, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_125

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determines not only if that door is opened but the type and level of engagement and interaction entered. When distrust is present, the ethos of participatory cultures (engage, participate, collaborate, cooperate, and disperse knowledge) is undermined. Distrust is different from low trust, with much stronger and deeper emotional roots. We cannot assume that because youth have technology and seemed to be constantly engaged with it means they are willing to participate, collaborate, cooperative in all places and spaces. Understanding why and where an individual’s trust/distrust is situated is important to understanding how and why they choose to engage in online/digital spaces. To realize the benefits of mobile learning and the online and classroom spaces characterized by collaboration, social connection, and distributed knowledge, we must acknowledge the diversity of engagement.

With mobile technology seemingly ubiquitous and youth actively engaged with those devices, we make the assumptions that youth are currently involved, ready, and willing to engage in a wide range of new online spaces. These spaces encourage individuals to engage, altering and broadening who, where, and how we interact. Digital spaces are built upon the concept of participatory cultures – a willingness to participate, cooperate, and collaborate with others not known to us in a physical sense (Jenkins 2006). In describing participatory cultures, Jenkins et al. (2009) suggest that “Not every member must contribute but all must believe they are free to contribute when ready and that what they contribute will be appropriately valued” (p. 7). To encourage and support this interactive culture, communities are created based on five foundational principles: (1) low barriers to expression/engagement are established, (2) a strong support for creating and sharing with others is provided, (3) an informal mentorship, (4) a belief that contributions matter, and (5) members feel some degree of social connection with each other (Jenkins 2006). Mobile technology, Wi-Fi connectivity, and a multitude of platforms provide opportunity to connect with others who share similar interests. In this world of online multiplayer games, fanfiction, blogs, social networking platforms, Snapchat, YouTube, and so on, youth have a multitude of options to engage with others, in new communities, in various ways, and on a seemingly infinite number of topics. We assume that once youth have reliable access (devices, affordable coverage, and connectivity), they will naturally seek out and actively engage in topics of interest or importance to them. Access provides opportunity but then what? Does opportunity plus interest translate into a desire to seek out and actively engage with others in participatory and collaborative ways? Participation is not a single entity and is best understood as a continuum ranging from no participation, watching, or guarded engagement to full active participation suggesting the overt desire to interact with others. These are individual choices and seem relatively clear cut. If you are interested, you engage; if not, you don’t. But what happens to the individual who has a strong desire to learn something that is only available to them in an online participatory community? Someone who can enter the space, but cannot take that

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next step, a participatory leap of faith, to post their question or engage with more informed others. It was this precise question that arose from my research into the impact of mobile technology on adolescent literacy practices. My six urban participants had smartphones, knew where and how to find free Wi-Fi, had a multitude of various interests, knew of online communities, went into online spaces for information, but could not take that next step. They knew that more knowledgeable others could be found in those spaces, but they felt that entry into that space was associated with more risk that they were interested in or willing to take on. To engage with unknown others required them to trust that people they did not know would act/behave in known and desired ways. Trust in others develops through lived experiences and is generalized to other places and spaces. For these urban adolescents, trust directly impacted participation and collaborative practices. “I don’t post anything. . .I mostly read. . .websites. . .Facebook” (DJ, interview) “no I don’t post stuff. . .I pretty much keep everything to myself.” (SW, Interview) “I just watch” (Cris, Interview) “I just don’t really conversate with people that I don’t know. It’s nice to meet new people but. . .at the same time. . .you have to be safe.” (DC, interview) “I would trust him. . .I know him. . .his experiences. . .in person. . .not the same online” (Cris, Interview) “I only go to places that I trust. . .people who know me. . .really know me” (Focus group) “I trust him. . .he knows stuff. . .but we know each other. . .that’s what’s important. . .knowing the person” (Focus group) Trust is the expectation that “cooperative behavior is based on commonly shared norms, within a community” (Fukuyama 1995, p. 2). This chapter explores the role of trust as it relates to engagement with online communities, and does not seek to address issues of trust related to cybersecurity, hardware, software, providers, platforms, hacking, or data mining. In this context, I explore how trust generalizes from social interactions and is positively associated with the trusting of unknown others. Trust forms the foundation of our behaviors, interactions, and communication styles. This trait, the willingness to be open to and actively engage with others, is assumed. Prior experiences profoundly impact how we trust. Mobile technology can lead us to and through doors that open into new spaces, places, thoughts, and ideas. The ability to interact with the world is literally at our fingertips. However, the degree to which one is willing to be open and trusting determines the levels of interaction. This propensity to trust is unique to each individual and develops from an accumulation of personal experiences. The ethos, or mindset, of participatory cultures is built upon a foundation of a community where any and all individuals can – and do, with relative ease – engage, participate, collaborate, cooperate, and disperse knowledge (Jenkins 2006; Lankshear and Knobel 2011). Understanding why and where an individual’s trust/ distrust is situated is important to understanding how and why they choose to

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engage, or not engage, in online/digital spaces. To realize the benefits of mobile learning that is characterized by collaboration, social connection, and distributed knowledge, we must acknowledge the diversity of engagement. It is imperative that educators know their individual students and realize, acknowledge, and develop learning strategies to meet the needs of every individual. To be trustful is not a universal human behavior. Distrust may not turn into trust, but openness to understanding students allows educators to better understand how and why students engage/disengage and succeed/flounder in classrooms. Ultimately, understanding the trust/distrust paradigm makes learning and success possible for all. If it were possible to define generally the mission of education, it could be said that its fundamental purpose is to ensure that all students benefit from learning in ways that allow them to participate fully in public, community, [Creative] and economic life. (Cope and Kalantzis 2000, p. 9)

But how can one expect all students to actively engage in diverse, dispersed online communities, when all they know of the others is a name and image. Is the “name” the real name, is the image/photo real, does the image align with the individual’s real name? These assumptions require a degree of trust, a belief that the others are and will behave as one would expect them to. What happens to that level of interaction when trust is low or nonexistent? Why should we believe in or trust in others without knowing who they are, what they represent, or what they might do with our thoughts and ideas? Trust is the bridge that allows you to move into spaces, into new and or different communities, into the unknown. Trust plays a critical role in the sharing of information as it is seemingly based on an implicit set of beliefs that others will behave in a dependable manner and not take advantage of the individual or situation (Hsu et al. 2007). Our initial information about the intentions or behaviors of others lays the foundation for how levels of trust are built. In this regard, trust refers to the attitudes, disposition or beliefs that we have about others whom we hope will be trustworthy. Trustworthiness refers to a property, personality trait, or characteristic of an individual whom we may trust (Cook et al. 2009). Trustworthiness is a precursor to trust and is a critical component in the sharing of information/knowledge. Online/virtual communities are implicitly designed to motivate individuals to engage. But Ridings et al. (2002) suggest that in these communities/spaces, member identity is invisible and communities do not/cannot guarantee that others will behave as they might be expected to. Hence, trust becomes a “crucial factor to sustain the continuity of the virtual community” (Hsu et al. 2007, p. 154). Engagement has become easier but also more complex. One of the greatest challenges in fostering and developing online/virtual interactive learning communities is the willingness of individuals to share knowledge with those known/not known. That willingness is representative of our predisposition to trust. Hsu et al. (2007) posit that personal cognition and social influence are critical elements of trusting others in online spaces. Individual behaviors are validated through considering the interactive influence of personal factors, environment, and behavior: Bandura’s triadic reciprocity (1986). Bandura does not suggest that the

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three elements make equal contributions, their influence is premised on which factor is strongest at a specific point in time. Individuals are agents who proactively engage in their own development, making things happen through their actions as well as those of the collective. To deepen our understanding of mobile learning and the twenty-first century engaged learner, we must explore more deeply how trust influences cooperative and collaborative behaviors among and between individuals, groups, and organizations, be they in physical or digital spaces.

1

Theoretical Framework

Glanville and Paxton (2007) suggest trust generalizes from social interactions and is positively associated with trusting of unknown individuals. Trust helps to simplify our decisions to act (Pearson et al. 2005), influences expectations about others, and affects behaviors in interdependent situations (Messick and Kramer 2001). Trust is a complex phenomenon around which there are many definitions and theories. There is no common understanding of what trust means across all disciplines (Brownlie and Howson 2005; Schoorman et al. 2007). Understanding the role and impact of trust on the engaged learner, both on and offline, requires broad and deep exploration of how an individual’s trust develops through experiences and across and within social communities. Educators must understand: (1) the role and development of trust developed within the individual (psychology), (2) how it influences interactions and communications, but also (3) how technology impacts, modifies, and challenges issues of trust developed in the physical world. What happens when interactions and engagement – whether they be of a social nature, knowledge seeking, an affinity space, or participatory community – move into the digital world? To best understand the role that trust plays within these new social paradigms requires an integration of perspectives (Heckscher 2015). This chapter takes an interdisciplinary perspective to explore how trust is defined across three disciplines: psychology, sociology, and computer science. Interdisciplinary exploration involves the combining of multiple academic disciplines in order to think about something in a new way; it crosses boundaries to better understand complex topics. This approach broadens understanding as it seeks to gain a greater sense of the whole, through multiple perspectives instead of just one. The term interdisciplinary is used intentionally here. A multidisciplinary approach, according to Klein (2010), seeks to foster a wider knowledge and understanding while keeping the disciplines separate. In this regard, each retains their original identity and no new knowledge is developed. In a multidisciplinary approach, the focus is premised on juxtaposition, sequencing, and coordinating. In contrast, an interdisciplinary approach focuses on integrating, interacting, linking, focusing, and blending (Klein), moving from a monistic to a pluralistic perspective. Deepening understanding of the importance of trust on engaged interaction and learning requires a perspective that incorporates the individual’s past and present experiences as well as the factors that influence them. To begin, we must examine trust as a social construct.

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Defining Trust

Trust is fundamental to human existence (Ess 2010) and functions as a way to reduce complexity within societies. It is a social construct that is the result of communication within and between social systems. Trust helps to simplify our decisions to act (Luhmann 1979; Pearson et al. 2005) and influences our expectations about another’s motives/actions with respect to oneself and affects behaviors in interdependent situations (Messick and Kramer 2001). Trust is an implicit set of beliefs that others will behave in a dependable manner and will not take advantage of the situation. It is a critical element of engagement that directly impacts the sharing of information. There is general agreement across disciplines that trust occurs under conditions of risk that require the trustor to develop favorable expectations regarding the intentions and behaviors of the trustee (the other party). This belief must be such that the trustor is willing to become vulnerable to the trustee’s future conduct (Mayer et al. 1995; McKnight et al. 1998). Communities, whether they are physical, virtual, or online are essentially groups of individuals drawn together for various reasons, but who trust each other. In this regard, trust is the confidence that others will act, in both present and future situations, in ways that we believe to be right (within the accepted norms of that group). Willingness to trust can be subdivided into trusting intentions and trusting beliefs. Trusting intentions the willingness to depend on another in each situation (McKnight et al. 1998). Trusting belief is a “generalized expectancy that the word, promise, or statement of another can be relied upon” (Rotter 1980, p. 1). Risk is a critical component of trust. How one assesses the level of risk directly impacts the degree of trust exhibited. Sociologists look at trust from the perspective of “a bet about the future contingent on the actions of the trustee” (Dumouchel 2005). Trust is explored through two perspectives, the individual and society. For the individual, the focus is on the willingness to be vulnerable to the trustee, a one-way, didactic relationship. Within social groups, trust is seen as the willingness of members to act in a consistent, expected, known manner. Experience shapes trust. In contrast, the psychological perspective is that trust is a state where the trustor risks being vulnerable to the trustee based on positive expectations of the trustee’s intentions and/or behaviors. To understand trust requires a more inward perspective that encompasses the cognitive, emotive, and behavioral aspects of the individual (Shercan et al. 2013). Consideration of trust in computer science is divided into two categories: user and system. The user notion of trust is derived from sociology and psychology (Marsh 1994). It is a subjective expectation regarding another’s future behavior. In this regard, trust is personal. In online spaces, trust is based on feedback from past interactions. Here trust is relational and develops as a result of previous experiences and interactions with others and in different spaces. Positive online user experiences deepen positive feelings of trust. However, while user experience is important, experiences in physical spaces also influence user trust. Trust may be context specific, but the propensity to trust develops deep within a broader set of experiences.

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It is worth noting that across these disciplines two characteristics associated with trust are evident: risk and interdependence. Here risk refers to the uncertainty associated with the intentions of others. Interdependence is based on the construct that a relationship exists between the parties and nothing can be achieved if they do not/cannot rely on each other. Both conditions must exist for trust to develop (Shercan et al. 2013). Trust is not a simple, single entity. In this chapter, we use the term to narrow our focus on the overall construct of trust but acknowledge that trust may take several forms. All forms have the same foundation of associated risk and interpersonal relationships: 1. Calculative trust: Here trust is defined a calculation made by the trustor whereby the individual weighs the possibility and consequences of loss against the degree of potential gain. In game theory, the “Prisoners Dilemma” is a good example of this model of trust and cooperation (Mayer et al. 1995; Jones and George 1998). 2. Relational trust: Trust develops over time and is based on personal and repeated interactions. Information available to the trustor from within the relationship informs the basis of this trust (Rousseau et al. 1998). 3. Cognitive trust: Cognitive trust is based on reason and rational behavior (Kuan and Bock 2005). Largely used in the field of psychology, cognitive trust precedes emotional trust (Möllering 2002). 4. Emotional trust: Trust is an outcome of a direct interpersonal relationship. Emotional trust influences the positive/negative perception of a relationship and is influenced by cognitive trust. This form of trust enables the individual to move beyond evidence, feel comfortable, and be assured that the risk of malevolence or misinformation is minimal (McKnight and Chervany 2001; Schoorman et al. 2004). 5. Dispositional trust: Dispositional trust develops over time. People develop generalized expectations about the trustworthiness of others. In a physical setting, dispositional trust may develop between individuals and/or groups of individuals. Because of the complexity of social networks, three types of dispositional trust exist: between members of the network, between member and online service, and between a member and the service provider (Shercan et al. 2013). 6. Context specific trust: Trust takes time to develop. A single high-impact event can eliminate trust and foster distrust (Schoorman et al. 2004). 7. Dynamic trust: Trust is not static. It will and can change with new experiences, interactions, and/or observations. New experiences are more important than old ones in the development/sustainability of trust. Trust is not innate (McKnight and Chervany 2001). 8. Associative trust: Trust/distrust along and across social connections and social networks allow individuals to form trusting relationships with those known to them through association. This can be problematic if the original information is incorrect or misleading (Jones and George 1998).

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9. Transitive trust: Generally, trust is not transitive (Yu and Singh 2000). For example, if Nicki trusts Sayed who trusts Joe, it is not implied that Nicki trusts Joe. 10. Self-reinforcing trust: Individuals act positivity with those with whom they trust. If that trust is low or nonexistent, it is unlikely that individuals will seek to engage with each other. This can lead to the development of distrust (Yu and Singh 2002). 11. Subjective trust: Personalized biases and preferences regarding the trustee have a direct impact on how one establishes the presence of trust/distrust. For example, Niesha believes that Shawn’s opinions are always good and trustworthy. Shawn gives a positive opinion about a movie. Based on Niesha’s belief about Shawn, she will trust his review. If Niesha thinks differently about Shawn’s opinions, she will not likely trust the review. 12. Asymmetrical trust: Trust is typically asymmetrical. One’s trust in other does not guarantee a reciprocal arrangement. Individual experiences and interpretations are unique to the person; shared experience does not equate with identical interpretations, risk assessment, or formation of trust. 13. Self-reinforcing: Individuals will act in a positive manner with those they trust. If trust is low, or distrust exists, it is unlikely that individuals will interact with each other (Yu and Singh 2002). The avoidance of interaction can/will directly impact collaborative and participatory events. 14. Disposition to trust: “Disposition to trust is general, not situation specific, an inclination to display faith in humanity and to adopt a trusting stance towards others” (Gefen 2000). Initial levels of trust do not start at zero but at a point that varies from person to person, based on past experiences and relationships, and is context specific (Kramer 1999). 15. Propensity to trust: An individual with a high propensity to trust will assume that most people are fair, honest, capable, and have good intentions. Those with low trust will tend to see others as selfish, devious, incompetent, or potentially dangerous (Mooradian et al. 2006). Reviewing these various types of trust highlights the interrelatedness between elements such as experience, context, relationships, cognitive perspective, emotive states, and trust. To understand trust requires a more complex approach than contemplating and exploring the impact of a single element in relation to trust. A broader approach such as an interdisciplinary approach is imperative as it affords a stronger and more realistic lens through which we can study and understand the role of trust within and across participatory communities. One of the most important debates on trust focuses on the treatment of trust and distrust. Are they a single construct, a continuum, or two distinct phenomena? Can distrust be turned into trust with support? A deeper understanding of the trust/distrust dynamic is paramount if we are genuinely interested in knowing how to best connect with others in participative and collaborative pursuits. Exploring trust/distrust deepens our understanding of student engagement within and across participatory communities, social networks, engaged learning, and mobile learning.

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Trust/Ditrust

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As a Continuum

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The traditional view of trust and distrust is that they form opposite ends of the same continuum. Within the continuum argument, low trust is equated with distrust, high trust is associated with low distrust, an either/or relationship (Schoorman et al. 2007). This common perspective is ingrained in how North Americans generally define trust as is evidenced by Webster’s Dictionary definition of distrust as the “lack of trust.” Others, such as Lewicki et al. (1998) define distrust as “confident negative expectations regarding another’s conduct. . .a desire to buffer one’s self from the effects of another’s conduct” (p. 493). Additionally, Lewicki et al. (1998) suggest that while trust and distrust are separate dimensions, they are linked. Trust and distrust may coexist – you may trust someone based on their professional credentials but distrust them as your child’s soccer coach. Trust and distrust are context specific.

2.2

As Two Constructs

In contrast to the continuum model, the two-construct model sees trust and distrust as being distinct, independent constructs and experiences, either or neither of which may be present but rarely do they coexist (Saunders et al. 2014). McKnight and Chervany (2001) note that trust and distrust are two separate concepts, functional equivalents, and opposites. In their view, to trust is to have faith in humanity; distrust is the suspicion of humanity. In seeing trust and distrust as separate constructs, they purport that these are very different experiences, requiring different and distinct coping strategies (McKnight and Chervany 2001). Dimoka’s (2010) brain imaging study demonstrated that trust and distrust reactions activate different regions of the brain, thus giving additional credence to the two distinct construct argument. In practice, this would suggest that providing additional support to a student who is hesitant to engage as a result of distrust, without understanding the cause of that distrust, will not be effective. To understand one’s distrust requires a deeper understanding of the individual and their experiences, past and present. In the presence of distrust, individual practices such as the smiling, nodding assurances, holding of hands, telling someone to be more trusting, and scaffolding are likely to be ineffective. Simple solutions are not realistic for such complex constructs.

3

Trust and the Way We Behave

Mayer et al.’s (1995) original model describes trust as dyadic (trustor and trustee), unidirectional, context specific, and contained by a relation-specific boundary. In 2007, Schoorman, Mayer, and Davis refined this model enveloping different views and perspectives. Their goal was to create a model that was generally applicable and useful across multiple disciplines. In this revised model, they broke with Rotter’s

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view of trust as being dispositional and trait-like, arguing instead that trust is an aspect of relationships and that it varies within and across relationships. While Schoorman et al.’s (2007) original model focused on a cognitive approach (perception of risk inherent in the actions/words of others considered in risk-taking decision), their latter work sought to illustrate how cognition and emotion impact trust. They believed that the propensity to trust plays a critical role, particularly in the early stages of a relationship as individuals have little knowledge/information from which to judge others (Mayer et al. 1995; McKnight et al. 2004). Online communities and spaces exacerbate this. Whom to trust and on what terms one is willing to engage, participate, and collaborate become more challenging. Trusting relationships cannot be assumed. Trust and propensity to trust are unique to each and every individual and vary across contexts. Trust, willing to take a risk by engaging with others unknown or poorly known, may not be the road some students are willing to travel. Disposition to trust is the willingness to be vulnerable accompanied by feelings of security. McKnight and Chervany’s (2001) study of websites found that viewing a website was seen as a low risk endeavor. Participants identified practices such as posting one’s thoughts, ideas, and opinions as risky. The higher the risk, the more that distrust influenced participation. Distrust is seen as more frantic and emotionally charged than trust – incorporating such things as fear, worry, doubt, panic, concern, and anger (McKnight and Chervany 2001). Distrust reflects the “emotionally charged human survival instinct” (McKnight and Chervany 2001, p. 884). Dispositions to trust or distrust are not static and may become more positive or negative over time as a direct result of life experiences. Jones and George (1998) found that to be an engaged learner, to effectively incorporate mobile technology into learning spaces requires the development of trust across the community of learners. “It is necessary to understand how trust in others is experienced psychologically before its impact on behavioral expectations and outcomes, such as the level of cooperation between people in an organization, can be adequately analyzed” (Jones and George 1998, p. 531). Educators must be cautious in making unrealistic assumptions regarding factors influencing levels of student engagement, as foundations of trust/distrust may differ within and across groups and vary according to activity. Jones and George (1998) acknowledge that the outcome of the trust/distrust interaction is influenced by one’s values, attitudes, and emotions as well as experiences. They conceptualize trust as “a changing or evolving experience, in which values, attitudes, and moods and emotions operate simultaneously to produce an overall state of trust or distrust” (Jones and George 1998, p. 534). Value systems that serve as guiding principles that individuals and communities use to determine the behaviors, situations, events, people, and spaces are deemed desirable or undesirable. Values create the propensity to trust: an individual’s inclination to believe others are trustworthy (Mayer 1995). In contrast, attitudes are object specific and are responsive to ongoing experiences and are evaluative in nature (Jones and George 1998). These include how we organize our beliefs, feelings, and behavioral tendencies toward people, places, and things (Hogg and Vaughan 2005). Affective states (moods and emotions) are feelings that provide information about one’s ongoing experiences and general state of being and directly

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689 BEHAVIORS

ENVIRONMENT

FAMILIARITY

in-person

risk

online

cooperation

context specific

collaboration

socio-cultural practices (alignment)

active/passive

engagement

in-person friend-of-friend

TRUST

unknown

Generalized/Int erpersonal

COMMUNICATION EXPERIENCES

THE INDIVIDUAL

lifelong

cognitive

context specific

affective

positive/negative

interest/motivation

within/between soical systems

risk

Fig. 1 Interdisciplinary trust model (Hoff 2016)

influence attitude. These constructs form the foundation of how trust is experienced. Trust is built upon expectations, that are, in part, emotionally driven (negative emotions can signal a violation of trust, the beginning of distrust). Affective states intermingle with values and attitudes to create a trust/distrust experience. Cognitive and affective constructs work in relation to each other, influencing how trust is used to influence and impact interactions and subsequent cooperative behaviors. To understand the role that trust plays in how, where, and with whom individuals are willing to engage, cooperate, and collaborate requires a framework that utilizes a variety of perspectives. Several factors influence how and where individuals choose to form relationships. Figure 1 is illustrative of an interdisciplinary approach, a consideration of multiple factors that contribute to an individual’s propensity to trust. Propensity to trust is directly influenced by the individual, their experiences, familiarity with others, and the environment. Whether one chooses trust or distrust determines behavioral patterns and communication pathways.

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Trust: Social Networks and Online Spaces

Communities are groups of people who trust each other (Fukuyama 1995). When trust is established, participants and/or members of a group feel confident that they know how the others within that community will act or behave, that there is a generally agreed-upon disposition to do the right thing. Mechanisms of socialization exist to ensure that all, who identify as members, play their part which facilitates a lowering of the risk or potential for hurt or harm.

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Communities that create an environment where members can share their thoughts, opinions, and experiences in an open and honest way without concerns about privacy and fear of being judged. These communities are built on authenticity, open sharing, like-mindedness and mutual respect. . .social trust provides an ideal foundation for building trust communities. Therefore, trust becomes an important aspect of social networks and online communities. (Shercan et al. 2013, p. 2)

Without trust, a heightened vulnerability is experienced regarding the safety of one’s thoughts, ideas, images, and identity, directly impacting engagement and participation. While many individuals have deep propensities to trust based on broad, positive experiences, there are those who are more cautious. The youth in my research resisted active engagement as a way to protect themselves and their ideas. “The other day I was searching fitness tips and so I’ll go to where people blogged about their different experiences. . .but I won’t really contribute to the conversation but I kinda. . .you know. . .just watch it. . .And see what other people have to say” [Cris, Interview] (Hoff 2014). Physical and digital/online spaces require willingness to trust the unknown. Physical spaces have the benefit of using visual images, intuition, and known affiliations to assess risk and verify trust. In the digital world, individual participants must rely heavily on the written word minus the facial expressions, gestures, inflections, and posture present in face-to-face interactions (Lowry et al. 2015). The tools available to assess the level of risk are significantly reduced and trust may be slow to develop. Engagement with others begins with the assumption of trust, which is influenced by one’s disposition to trust – the propensity to trust in addition to assumptions of trust are critically important in the initial stages of a relationship, where there is little or no specific information by which to judge others (Mayer et al. 1995; McKnight et al. 2002). In the digital world of online spaces, interactive communities, and networks, the individual must not only assess the risk on an interpersonal level but also at an institutional level (internet, website, and vendor). It is here where understanding an individual’s trusting stance may be helpful in assessing/understanding their willingness to explore, to engage, interact, participate, and collaborate (McKnight et al. 2004). The distribution of knowledge is built upon the assumption that others will behave and conduct themselves in specific ways, a true reflection of the individual’s practice.

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Cultural Influences

The twenty-first century is a time of change. Not only is technology providing us with access to many others, it supports us and provides avenues with which to engage. Historically, a community is a group of people who work together, built upon a shared sense of right. While access offers significant opportunity, issues such as whom to trust, on what terms is one willing to engage, practice, and collaborate, and how will one’s thoughts/ideas be used and/or integrated and distributed must be addressed before programs are initiated. Understanding whom to trust has never been more difficult.

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Cultural norms exert a powerful influence on how people think, feel, and act, and because educators are so immersed in their cultures, they often find it difficult to step outside of their traditions and assumptions to examine their conventional practices from a critical perspective. (DuFour et al. 2008, p. 90)

Putman (2000) suggests that it is relatively easy for most individuals to trust those who share the same backgrounds. Others have found that we are most likely to cooperate with those who share the same knowledge/perspective (Pinker et al. 2004). It is hardest to trust those different from us. In digital spaces, individuals and algorithms direct and lead us to spaces and communities of other like-minded people. The benefit is greater exposure to new and different ideas, and yet for some this is precisely the problem. For some, the desire to know may be trumped and negated by their inability to trust those they simply do not physically know. According to World Values Measures (Paxton 2007), certain regions of the world have higher levels of generalized social trust (Scandinavia) while others exhibit very low levels (Latin America). Regional differences also exist as evidenced by low levels of social trust in the southern United States and higher levels of general trust found in the northeast and the upper Midwest (Putnam 2000). Schoorman et al. (2007) found the variance in initial trust across cultures is related to the propensity to trust variable. “Task oriented cultures seem to have a higher initial trust of strangers and therefore a higher propensity, while relationship-oriented cultures need time to develop a relationship prior to working on a task” (Schoorman et al. 2007, p. 351). Additionally, the cultural variable of uncertainty avoidance is a well-established predictor of risk taking/aversion (Sully de Luque and Javidan 2004). While there certainly is a psychological component to trust, relationships are the bedrock of societies and those relationships are forged through shared cultural norms, values, and beliefs whose very foundations are built upon trust. Today the world, and many classrooms around the world, reflect a cultural mosaic and access and opportunity to engage with those different from ourselves and our local, physical community. As educators, we must not only understand the experiences of our students within the classroom but the foundations of trust developed through their experiences, prior and immediate surroundings, as well as culture.

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Positioning Trust in the Sphere of Mobile Learning

“Of the various challenges that schools presently face with mobile devices, trust is the one that looms largest – it is the one that does not have any simple or clear solutions or methods for attaining” (Ibrahim and Walid 2014, p. 432). Trust is one of the most significant factors in the acceptance of mobile applications/services (Kassin 2005), and the importance of trust in digitally mediated communications and interactions among educators and learners cannot be ignored. Mobile learning is premised upon the concept that one is willing to learn from others’ experiences and knowledge by joining a group, class, network, and/or community. Inherent in this learning is the assumption of trust based on the willingness to be vulnerable and

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open to others (Ibrahim and Walid 2014). Trust is based upon the positive expectation that others have something to give and their concerns, motives, and conduct are incontrovertible. Are those students who appear distrustful or disengaged generally disinterested or is something more profound occurring at the very foundation of engagement? How much is their propensity to trust/distrust impacting their educational experience? Educators immersed in or implementing participatory communities as part of mobile learning must be cognizant of students, as individuals as well as members of various groups. The willingness to engage in places and spaces is built over a lifetime of experiences. Assuming that all twenty-first-century youth easily and routinely engage in online spaces can/does lead educators down wrong paths, driven by perceptions but not necessarily facts. This assumption is increasingly problematic as we work to incorporate participatory communities and practices into digital learning spaces. This raises the question: What specific strategies are effective in addressing and understanding a student’s disposition to trust and, which ones are better suited for overcoming a disposition to distrust?

7

Participatory Communities/Shared Knowledge

The very essence of a participatory community is the willingness of participants to engage in collection, reflection, contribution, and distribution of ideas (Mackely 2013). Participatory communities are built upon the belief that there will be an equitable sharing of ideas; they invite us to value and respect common knowledge and to challenge current/traditional paradigms (Jenkins et al. 2009). Communities are a part of our nature as human beings and are essential in helping us to seek out and find both the meaning and significance in life. However, participation in such communities, and knowledge sharing in general, can be a demanding and uncertain process in which perceptions and feelings of conflict and vulnerability exist. To engage, to participate, requires one to evaluate the trustworthiness of others in that specific place/space: to build a level of interpersonal trust within and across relationships. This interpersonal trust, that is the willingness of one to be vulnerable to the actions of another, is the bedrock of knowledge. Trust impacts knowledge sharing not only through individuals but environments as well. Communities, be they physical spaces, digital spaces, or virtual worlds, are unique and specific. Interpersonal trust is a construct directly related to past experiences. Additionally, the propensity to trust is influenced by the cognitive and emotive constructs found within each and every individual. The willingness to trust/distrust others impacts both how and who is actively engaged in the sharing of knowledge through participation. While some individuals may choose to actively engage, energized by the exchange with others, known or not, others may choose to engage silently – watching, listening, and learning and still others will not be able to take that initial step (Nonnecke et al. 2004). “I just don’t really conversate with people that I don’t know. It’s nice to meet new people but. . .at the same time. . .you have to be safe” [DC, Interview] (Hoff 2014).

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Individuals have real and profound reasons for whom and why they trust. Trust is not trivial. Distrust may never be extinguished but a shift in the propensity to trust is possible through extensive positive experience over a period of time. Ultimately, an individual’s propensity to trust or distrust is their right. In education, acknowledgement of the role that trust/distrust plays in learning must be incorporated into teaching pedagogies and differentiated instruction. The twenty-first century offers many ways to engage; one size does not fit all.

8

Moving Forward

The participants in my study expressed deeply felt concern regarding interaction with unknown others in online spaces and communities. Trust was not implicit and their willingness to trust was premised on their personal experiences, familiarity, cognitive and affective states, as well as context and space. Their lived experiences required risk assessment; trust was not assumed. The willingness to take risks was constantly guarded: they minimized risk by placing trust only in those with whom they had a face-to-face history. Those findings align with previous research, which found that trust is important in fostering relationships and collaborative exploits (Chang and Fang 2013). “The key to ongoing social experience is producing trust” (Glanville et al. 2013). It is trust within a community that creates an environment in which people are inspired to share their thoughts, opinions, and experiences in an open and honest way (Nepal et al. 2012). Repeatedly, participants addressed the critical importance that knowing someone, face to face, and developing a level of trust were critical for them to engage with those individuals in online spaces. In the absence of trust, their behaviors were limited to not entering, communicating, or engaging with others in online spaces, even when they had a vested interest in the knowledge and experience that was available within that community or space. In some scenarios where trust was low, individuals would watch but not engage. Reasons given for such behaviors included not trusting those they didn’t know, an unwillingness to “conversate” with those unknown to them in a physical sense, and preference to watch when they knew no one in that space. Yamagishi refers to this as “default expectations of people’s trustworthiness” (2011, p. 28). Trust (high or low) and distrust are different constructs that can and do impact collaborative behavior differently, and in particular, how and where one chooses to engage in online spaces. If trust is a reflection of one’s general willingness to depend on or become vulnerable to others, then distrust is an unwillingness to depend on or become vulnerable. Chang and Fang (2013) put forth that online trust is a positive expectation characterized by reliance, confidence, and assurance. They describe distrust as negative expectations characterized by suspicion, wariness, and fear. These later elements are evident in my participants’ narratives as they consistently spoke about the need to be careful who they communicate and interact with, both online and in person (Hoff 2014, 2016). Wariness and lack of trust have a direct impact regarding where, how, why, and with whom they engaged.

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When distrust is present, this new learning ethos of engage, participate, collaborate, and disperse knowledge is undermined. Deeper insight regarding the role generalized trust plays in whether youth continue their digital media pursuits beyond piqued interest, “hanging out” (Ito et al. 2010), or fully engaged in mobile learning is needed. The elements discussed in this chapter should be used to inform the design and implementation of digital media production programs both in school and out, leading to more active participation and collaboration. Understanding why and where an individual’s disposition to trust/distrust is situated is important and critical to our understanding of how, with whom, where, and why youth choose to engage in online spaces and digital learning.

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Evidence-Based Teaching and Real-Time Assessment: Adoption of Mobile Interactive Apps

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Evidence-Based Teaching and Mobile Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Mobile Interactive Exercise for Evidence-Based Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Mobile Response System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Adoption Strategies and Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile-based in-class educational approaches should help faculty provide an evidence-driven teaching environment. This chapter is going to discuss the theoretical background for such mobile-based approaches and its need in the classroom to provide both students and faculty with a real-time understanding about learning and to help students engage more into traditional lecturing. Additionally, the chapter is going to discuss the way such mobile-centric interactive systems could facilitate more evidence-driven teaching. Finally, the chapter will discuss issues that need to be considered for such adoption and present an example of mobile-based system to facilitate evidence-based teaching.

M. Fuad (*) Department of Computer Science, Winston-Salem State University, Winston-Salem, NC, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_100

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Introduction

Lecturing is one of the most widespread forms of classroom instruction delivery technique (De Ridder-Symoens and Brockliss 1996). In this setting, communication between the faculty and the student is mostly unidirectional, from faculty to student. There is a lack of interaction with the students for many reasons (Costa et al. 2008), and a plethora of work (Derek 2012) has been performed to address this issue. It is found that the lack of interaction between the faculty and the student in a traditional lecturing environment has a detrimental effect on student learning and problemsolving skills (Perry 2000). Additionally, although traditional lecturing sessions are 60–75 min long, undergraduate students only have an attention span of 20 min (Perry 2000) at a time. This problem is exacerbated in recent years by the changing nature of the student body and the proliferation of mobile devices in the classroom. In this era of student’s constant urge for instant gratification and their lack of attention in the classroom, more evidence-driven teaching practices are needed that will provide a real-time indication of student learning. In the last couple of years, teaching methodology based on evidence-based practices from clinical psychology is gradually being used in academia to better assess student learning. Without a proper and real-time assessment of traditional pedagogical techniques, the faculty is left without evidence of student learning. Additionally, the lack of interactive activities in traditional pedagogy makes it harder to get a real-time evidence of student learning. The introduction of mobile devices in education has created enormous opportunities to assess student learning in a real-time fashion to have an evidence-based teaching and learning environment. The set of features in a current mobile device should allow us to provide students with interactive problemsolving in the classroom, as such interactive teaching strategies are necessary to make student learning more engaging and productive. It is considered that, in STEM courses, there is a need for students to actively perform problem-solving in a handson approach to better develop problem-solving and critical thinking skills. Since exams and quizzes are the most widely used assessment technique of student learning, such assessment techniques should be more interactive, engaging, and involving to better observe student’s learning in real-time to deliver an evidencebased pedagogy. The nature of undergraduate students is changing and today’s college students are not as engaged in the classroom as their predecessors (Babcock and Marks 2010). As they are dubbed “The Internet generation,” these students are comfortable using technologies in every aspect of life. The preexisting experience with computers, tablets, gaming console, and other technologies that students bring to the classroom, give them enough distractions during class time to lose focus on the class content. Since the form factor (size, weight, power requirement, computational capabilities, etc.) of such devices make it feasible to carry all the time and since the price has gone down drastically, mobile devices are a common occurrence in classrooms now a days. By having such a device all the time allows the students to deviate their concentration into something other than what the class is covering. By doing so only a fraction of the time, students can miss important aspects of the lecture, which will later hinder their problem-solving skills (Weimer 2018).

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One solution to this problem is to ban such computing devices during class time (Campbell 2006; Fang 2009). This should allow students to fully concentrate on the lecture and immerse themselves in the content. However, it is not a practical solution because most students do use mobile computing devices to take notes, browse lecture slides, and read electronic textbooks. Additionally, allowing students to utilize mobile computing devices and the Internet can facilitate the sharing of ideas and foster exciting discussion. Therefore, it would be wise to use those devices to elevate the class experience, instead of banning them from the class. Especially in a large class, where it is hard to interact with every student, these mobile devices can be utilized for our benefits to facilitate evidence-based active learning in the classroom. It is mostly accepted that in STEM disciplines, traditional pedagogical techniques are not enough to transfer critical knowledge to students (Katsioloudis and Fantz 2012; National Research Council 2015). If the faculty is only using lecturing during the class time, students will lose attention minutes after the class has begun and an effective level of student learning and engagement will not be achieved. An evidence-based teaching and learning technique, which provides real-time assessment and feedback, have to be implemented in our classes to improve student retention rates in the STEM disciplines. The feature set of a mobile device and student’s preference towards those devices makes it a preferred platform to facilitate such learning environment during class time. This chapter will discuss the theoretical underpinning for such mobile-based approaches, how they could facilitate more evidence-driven teaching, issues that need to be considered for such adoption, and an example mobile-based system to facilitate evidence-based teaching.

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Evidence-Based Teaching and Mobile Devices

In the last couple of years, evidence-based teaching and learning methods are brought into focus from the experience gained in clinical psychology and their use of evidence-based practices (EBP) (Biesta 2007; Perry 2000). Although EBP covers a multitude of meanings, historically it was defined as “the use of the best available evidence to bring about desirable outcomes both for the clients and society” (Kvernbekk 2015). Different authors have discussed (Fairweather 2008; Saville 2009; Mitchell 2010) the advantages of using evidence-based methods for teaching and learning. Evidence can be a student’s measurable learning (score or grade) after a treatment or student’s impression on learning and engagement after a new treatment is implemented. However, measuring the real-time impacts of traditional pedagogical approaches used in STEM disciplines are not easy. Additionally, faculty needs time to grade those manually, which in turn does not provide faculty an instant evidence about student learning. Classroom approaches where evidence can be gathered with real-time assessment and where the faculty is able to continuously improve the applied method with the help of evidence gathered is necessary to address student’s lack of attention in class.

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It is well believed that, in STEM courses, there is a need for students to actively perform problem-solving in a hands-on approach to better develop problem-solving and critical thinking skills (Katsioloudis and Fantz 2012; National Research Council 2015). Since exams and quizzes are the most widely used assessment technique of student learning, such assessment techniques should be more interactive, engaging and involving to better observe student’s learning in real-time to deliver an evidencebased pedagogy. In a traditional classroom setting, pen-and-paper based quizzes and exams are administered sparsely during the semester. Faculty normally takes static paper-based quizzes or exams in between few weeks of content covering. However, the problem with this approach is that, if the students had difficulty understanding the concept from the beginning, they might not do well when the quizzes and exams are given. This makes assessing student learning extremely difficult to synchronize with content coverage. By administering static quizzes and exams only in a course, faculty might not fully gauge student learning, cannot intervene early, and have any chance to improve student learning during the semester. Presenting these assessment items as interactive activities, where students can actively participate in different steps of the problem will definitely engage the student with the lecture content. Additionally, by administering them more frequently and by synchronizing such activities with the content covered, student’s critical thinking and problem-solving skills can be improved. However, this is impossible to achieve in traditional pen-andpaper approach and the era of mobile devices opens up a new horizon to facilitate such interactive problem solving for evidence-based teaching and learning. Mobile technology has brought incredible possibilities to enable and deliver learning activities in ways that could not have been imagined before. There is an increasing number of studies (Avery et al. 2010; Cometa 2011; Hao et al. 2017; Kim et al. 2011; Romney 2011) related to the research and development of learning environment intended for mobile computing devices. The problem-solving exercises can be made more visual and appealing to the students by converting them from traditional paper-based exercises to interactive mobile App exercises. This will also allow the students to realize the effects of interactions at the different stages of the exercise and allow them to self-reflect on their problem-solving skills. This will allow students to fully comprehend a concept and clarify any confusion by the virtue of visual presentation, active interaction, and hands-on nature through the use of mobile devices (Deb et al. 2018). To facilitate active teaching and learning, “clickers” were utilized in various ways (Caldwell 2007; Draper 2002; Fredericksen and Ames 2009; Knight and Wood 2005; Penuel et al. 2007; Roschelle et al. 2004). Although there are a lot of evidence that clickers can improve teaching and learning, they are not suitable for assessing multi-step and interactive problem-solving exercises. This makes their applicability limited in different assessment scenarios. The use of mobile devices become prominent in classroom teaching and learning in recent years and most researches in mobile learning reported positive educational outcomes (Wu et al. 2012). The ubiquitous availability of mobile devices and the interactivity and personalization they offer can be utilized to enhance the class experience and should minimize the limitations of “clickers.” There are several commercial products (E-Clicker 2017;

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Echo360 2017; iTestMe 2017; QuizCast 2017; Socrative 2017; Top Hat Monocle 2017) for different mobile platforms to create a more active, learner-centered environment while supporting various effective pedagogies. Many other approaches (DeWitt et al. 2014; Jones and Issroff 2007; Land and Zimmerman 2015; Mockus et al. 2011) also reported enhanced educational experiences when technology such as mobile devices has been adopted in the classroom. However, such efforts lack the support for interactive exercises and many do not support real-time assessment needed for evidence-based teaching and learning. To fill this gap, mobile-based learning environments, which support interactive problem solving and assessment, should be developed and deployed more into the classroom to increase student learning and engagement.

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Mobile Interactive Exercise for Evidence-Based Learning

In a face-to-face classroom setting, the faculty is in a dire need to assess whether the student has learned the concept or concepts that have been presented so far in the class. Traditionally, quizzes or exams are used to assess such scenarios, which give faculty a glimpse of how much the student is learning. There is two big problem associated with this approach. Firstly, this quizzes and exams need to be graded, which requires time and does not really gives faculty an instant evidence of student learning. Secondly, the faculty’s use of different teaching psychology makes it even harder to assess such student learning scenarios. Most of the lecture-oriented face-toface classroom setting is based on Objectivism (Vrasidas 2000), where learning happened when faculty transfers object knowledge to the student. This is extremely difficult to do and is limited in effectiveness. This also requires the student to be really attentive in listening for faculty lectures and use meta-recognition of the different facts the faculty is conveying and connect them together to understand the concept in a coherent manner. Students, especially in their early years in college is not accustomed to that and lacks the skills to learn well through such objective and stale lecture-oriented classrooms. Therefore, more dynamic and involving learning styles need to be employed in such a face-to-face classroom setting. Constructivism (Ertmer and Newby 1993) is one such approach where the assumption is that “the structure of the world is created in the mind through interaction with the world and is based on interpretation” (Vrasidas 2000, p. 446). According to constructivist learning theory, learning is defined as student engagement on an activity through the use of the content and the skills that the students are learning. Active learning (Bonwell and Eison 1991) is one of the constructivist learning approach, where students learn by actively engaging in building knowledge by interpreting facts and by utilizing skills through participation in different faculty-led on-class activities. Active learning not only allows faculty to assess student learning in real-time but also different studies (Braxton et al. 2008; Prince 2004) shows strong empirical evidence that active involvement in the learning process improves student’s critical thinking and problem-solving skills. This, in turn, contributes to student retention and program completion. Additionally, this facilitates faculty to engage students

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in higher-order thinking tasks (Anderson et al. 2001), which allows students to think what the class is about and what and how they are doing these activities to learn the content. Through the use of such active learning activities, faculty can get evidence of student learning instantly and steer the student learning process in the classroom towards a productive direction. Different algorithm visualization techniques have been used by computer science faculties over the years to explain difficult concepts to students with the help of simulations and animations. Although visualization might be effective in enhancing student’s perception, visualizations alone cannot improve student learning unless it allows active engagement of the students. Therefore, there is a need for constructive exercises, where students can simulate the steps of an algorithm by manipulating some user interface, and where an automated assessment of such exercises is possible. Different studies (Karavirta and Shaffer 2016; Myller et al. 2009; UrquizaFuentes and Velázquez-Iturbide 2009) have strengthened this argument by stating that such exercises may help to reach learning goals only if student’s performance can be monitored and feedback is given immediately. However, there are a few systems to support such interactive exercises, and even fewer to support the automated assessment of such activities (Deb et al. 2017). Since mobile devices are a common occurrence in current classrooms, these can be utilized to facilitate such interactive and visual problem-solving activities where real-time assessment and instant feedback can be provided for evidence-based student learning. An interactive problem-solving activity is defined as an Interactive Exercise (IE) (Fuad et al. 2016) with corresponding grading components and associated rubrics. It is called interactive because it is more involving than an active exercise and needs more engagement from the student’s side. Interactive exercises require students to directly work on a visual representation of a problem. The student then develops the answer by following a set of predefined steps guided by some particular algorithm or process. In each of these steps, students make key choices related to the problem, such as clicking a table entry or a particular array index for selection or swap, select an entry from a drop-down menu, etc. The choice a student makes in one step of the exercise will impact student’s next step of interaction in that problemsolving exercise. While the student is doing these interaction steps, they can traverse back and forth (by utilizing “Back” and “Next” button) to see the effect of their choice, which helps them understand the concept better. Interactive exercises can be offered to solve a problem from bottom-up or top-down fashion or solving certain steps of a particular problem in order to give students a different perspective on the problem and to assess their problem-solving skills. Having IE activities as mobile Apps encourage evidence-based teaching practices as discussed before. With the help of automated grading and instant feedback, mobile apps-based IE can help faculty conduct an evidence-based class. Research has shown that immediate feedback has a positive effect on students’ success, and by utilizing such multi-step interactive problem-solving approach in mobile devices, faculty can provide immediate and context-sensitive feedback to the students. Additionally, faculty can identify and correct common misconceptions and reinforce specific topics immediately on which students have not shown mastery. By monitoring and analyzing

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student device usage and interactions data (button clicks, steps traversed, time spent, navigation behavior etc.) while using these Apps, faculty can have a better understanding of student’s attitude, mental model, and barriers that they faced during problem-solving (Fuad et al. 2016).

4

Mobile Response System

Mobile Response System or MRS is a mobile learning environment that supports faculty to administer in-class interactive exercises and their real-time assessment using mobile devices (Deb et al. 2014, 2017; Fuad 2017; Fuad and Deb 2016; Fuad et al. 2014, 2016). MRS is a client-server software that allows faculty to prompt the students dynamically in their mobile devices with carefully designed IE Apps, synchronized with the lecture material being covered in the classroom. Students are then allowed to actively interact with the visual representation of the multi-step IE while recognizing the effect of their interactions visually at different stages of the problem and send their solution back to the faculty computer. MRS then enables grading of the answers by utilizing the faculty provided rubric. This formative assessment allows faculty to have real-time evidence of students’ comprehension of lecture materials on a particular class. Additionally, these types of assessment allow faculty to identify the concepts that need to be repeated or reinforced. Since MRS automates delivery, timekeeping, and grading of the IE Apps, faculty can use them more frequently in the classroom and students can actively participate in more exercises where they can receive real-time assessment and feedback. Faster and frequent feedbacks that the students receive using MRS reinforce student learning and help students to identify misconceptions and problem areas. This section will present how MRS can be deployed in class and how it facilitates interactive exercise and evidence-based practices. MRS comes with a set of IE apps that can be deployed in a variety of disciplines. However, in order to encourage broader adoption and dissemination, MRS is designed to be completely separate from the application logic of the IE apps. MRS is extensible to any discipline and therefore has the ability to render IE Apps created by any third-party developers (Fuad et al. 2016). Deploying MRS in the class involves a sequence of steps that the faculty needs to follow. (a) If the faculty wants to use one of the predeveloped IE apps that comes with MRS, there are two ways to create a new exercise for students. Each of the pre-developed IE apps has a new problem generator user interface (Fig. 1 shows an example), which allows the faculty to design a new exercise for the students and export it to a form that MRS will recognize. MRS uses a plain XML-based format to save exercises in the file, as shown in Fig. 2. Therefore, the second way to create a new exercise is to write a new XML definition of the exercise. However, this approach is comparatively harder than the first approach as faculty needs to know the format well enough to design the problem-solving exercise, and any error in the format will make it

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Fig. 1 User interface to define a new problem-solving exercise

Fig. 2 XML format of exercise definition file

unrecognizable by MRS. If the faculty wants to create a new IE app, there are standards and APIs, which are available to create a new IE app and to extend the feature of MRS into any discipline. (b) MRS needs student information to allow them to login to the in-class problemsolving sessions. To import the student information, a text file containing

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the required information must be created first. This must be saved in a space separated text file, where each line will have information about one student with the following format: last_name [space] first_name [space] user_name [space] password [space] e-mail Once the text file including the student’s information has been created, faculty needs to click the “Import Users” button under “User Management” tab to import student credentials as shown in Fig. 3. Most of the course management systems, like Blakboard, Moodle, etc., will allow faculty to export most of the student information in this format. However, in some instances, faculty needs to add any missing information to make it suitable for MRS usage. If the import is successful, the software will switch to “System Management” tab (Fig. 4), and faculty will be able to see any messages under “System Status.” To allow students to login and to broadcast interactive problems to students, the system needs to listen for student app invocations. Therefore, faculty needs to press the “Start Server” button under “System Management” tab (Fig. 4) so that students can login to the system. (c) Students will select the MRS client app in their mobile device and it will automatically locate the faculty computer in the network. Once student successfully logs in, they will be presented with the app’s home screen as shown in Fig. 5. On the faculty side, once students start logging in, their information will be shown under the “User Management” tab (Fig. 6), so that faculty can keep track of students.

Fig. 3 MRS user interface to import student information

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Fig. 4 MRS status window

Fig. 5 MRS student side app’s home screen

(d) Once all students have logged in, faculty can import questions (in the format as described in step a) and can start broadcasting them to student devices. Once questions are successfully imported, faculty can browse the questions on the pane next to the buttons on the “Question Management” tab (Fig. 7). Once

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Fig. 6 MRS student management screen

Fig. 7 Question management screen of MRS

a question is successfully broadcasted to all students, the software will automatically switch to “System Management” tab, where faculty can monitor which student has submitted their answer and then can process the student answers.

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The following example (taken from Deb et al. 2017) illustrates how students interact with an interactive problem-solving exercise in their mobile device. This IE app let students work on problems related to Prim’s algorithm. Prim’s algorithm is a greedy algorithm that finds a minimum spanning tree (MST) for a weighted undirected graph. Traditionally, we see students struggle with the concept of Prim’s algorithm and their performance on problem-solving related to that algorithm is not that good. Students usually trace pseudocode and draw intermediary diagrams with a pen to understand how the algorithm works for a particular graph. In the interactive mobile app version, the student can now interact with the nodes of the graph by touching them. Additionally, a table is provided as part of the visualization where students can keep track of the shortest distance to a non-tree vertex (via updating its parent and distance) every time the MST evolves. Therefore, the student interactions in this app are achieved by touching a graph node, selecting drop-down menu items in a table, and by touching navigation buttons. The problem-solving session is broken into multiple steps or screens that students can traverse. In step one (screen one), the student selects the starting node of the MST as instructed by the exercise by touching it and then the student selects the “Next” button. Figure 8a shows the app screen when a student selects node A (starting node) in the graph and is about to press “Next” to see the next interactive screen. It should be noted that when a node is included in the MST, the corresponding node in the graph and the entry in the table are marked green to signify that and their parent and distances can no longer be modified unless student utilizes the “Back” button. In each

Fig. 8 Sample IE app screens

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following step (screen), a student must perform three interaction in sequence. First, the student needs to work on the table to adjust parents and distances of non-tree vertices that are adjacent to the recently selected tree vertex. Figure 8b shows the app screen where a student is modifying node entries in the table that are adjacent to node “A.” Second, based on the information in the distance column of the table, the student then applies prim’s greedy strategy to find out the next node to be included in the MST and selects that node in the graph. Figure 8c shows the situation where the student decides to include node “D” next, correspondingly selects that node and is about to press “Next” to see the next interactive screen. Finally, once “Next” button is pressed, the app automatically adds the appropriate edge to the MST based on the student provided parent information of the recently chosen node in the table (Fig. 8d). The student will repeat the same procedure until all graph nodes become part of the MST. At any step, students can click “Back” button to undo the previous selection and repeat that particular step. Therefore, it is possible for a student to identify a mistake at the very last step and restart from scratch again by utilizing “Back” button multiple times (Deb et al. 2017). However, since the IE app itself cannot tell students about their answer being correct or not (which is done during grading at the faculty side); there is no way that students can game the system. (e) Once a question is broadcasted, and students have submitted their answers, MRS facilitate grading of those answers. Once the “process results” button on the “System Management” tab (Fig. 4) is pressed, MRS will ask the faculty (Fig. 9) to locate any custom grading component. If there is none, MRS will use a set of preexisting statistical tools and grading processes to grade the answers to that particular question. After the answers are graded, the faculty will have a number of options for displaying the results (Fig. 10) to the students, these include: • Grade Summary: Summarized statistical information about grade distribution. This gives the class an overall picture on student performance and allows student to self-reflect on their own performance compared to the rest of the class. • Grade Details: Details regarding class results, which might include partial grade information for each step of the exercise. This type of finer grained grading information will allow both faculty and students to see the part of the exercise where more focus need to be paid. • Time Taken: Displays the percent of the allotted time used by the students and/or time spent at individual steps of the exercise. By looking into different timing information, faculty can see in which part of the exercise students took longer or percent of time students spend on successfully solve the problem. • App Swap: Shows the number of times users swapped to a different application, while the problem-solving session was in motion. If students did not switch to other Apps during problem-solving sessions, it might mean that they are completely engaged in problem-solving and that they are not looking for answers on the internet.

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Fig. 9 Grading of student answers

Fig. 10 Post grading screen of MRS

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• Navigation: Shows the number of times a user pressed the “back” button to solve the problem. This might give faculty insight into whether students are checking their work and validating it before submitting. • Correct Answer: Displays the correct answer for that particular exercise question. Once the results have been processed, MRS allows the faculty the option to broadcast the results to all students through email. If faculty chose to send email notification of student’s results, each student receives an email with their grade on the question, their answer, and the correct answer of the question.

5

Adoption Strategies and Issues

Deploying such interactive exercises with the help of mobile devices need a thorough makeover of how faculty teaches a class. Faculty should put some extra time in each class to buffer any technological trouble or the extra discussion that will happen after such evidence-driven interactions. Usually, faculty should divide the class into periods, where multiple interactive problem-solving sessions will be administered. Each of the sessions should be in ascending order in the degree of difficulty with proper instructional scaffolding techniques incorporated to achieve the best student outcomes through the use of interactive mobile exercise. A typical class should have the following structure: • Faculty should spend the first half of the class to explain topic of interest and solve relevant examples. • Then students will be asked to solve first interactive exercise using mobile apps. Results are immediately available via email and visualization during class time. • The faculty then spends next few minutes to point out common mistakes and offer more clarification depending on the student performance on the first exercise. • Students then solve a second exercise with higher degree of difficulty. • Faculty then reinforces the topic and clarifies understanding in the next few minutes. • Depending on the length of the class and student’s command on that topic, faculty will continue this approach until he/she is satisfied with student’s comprehension of the topic. This approach allows the faculty to offer multiple interactive activities in students’ mobile devices, through which students can use the content being covered in the lecture and skills that are just been learned. This way, multiple interactive activity-based classrooms facilitates constructivist pedagogy and helps the student to engage more with the content. Since mobile devices are being used to deliver such activities and the current generation of students prefer that over other computing devices (Khalaf 2014), the effect of such interaction should be even more prominent. Faculty can adapt their teaching based on immediate assessment and tracking data and student feedback. This real-time assessment allows faculty to find evidence

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of student learning, which the faculty can use for continuous improvement of student learning and their own teaching methodology. The visual and interactive nature of this mobile app exercises should allow better comprehension of critical and hard to comprehend topics. By automating the delivery and grading of such activities, faculty will be able to offer more of those activities in the class, allowing more practices with feedback and instant correction of misconception should lead to improved student satisfaction. On the flip-side, developing such interactive apps might be time-consuming; however, once developed, by creating multiple question instances, student’s learning can be assessed repeatedly. Additionally, developing IEs require a well, thought-out plan for interaction and break down of the problem into smaller interactive entities. Faculty needs to consider different interaction scenarios that can occur because students might choose to interact in different ways and correspondingly various kinds of feedback that the application needs to provide to students. Another important issue that faculty needs to consider in such deployment is student’s anxiety on test/quiz taking as arguably testing is one of the most anxiety-provoking experience for students. The challenge for faculty is to strive to create such mobile problem-solving sessions as relaxing as possible such that rapport remains intact. To enhance learning and to improve rapport, faculty can ask students to study related materials before a deployment of mobile interactive problem-solving in the classroom.

6

Conclusions

In this chapter, we have discussed why evidence-based teaching and real-time assessment is necessary in the twenty-first era classroom and how interactive problem-solving using mobile devices can facilitate such methodology. With the help of the mobile interactive problem-solving and real-time formative assessment, faculty will have an evidence of student learnings and will help faculty to identify the concepts that need to be revisited. Table 1 summarizes evidence-based best practices for such deployment of mobile interactive problem-solving in the classroom (Fuad 2016, 2017), and Table 2 lists questions for future directions of such teaching methodology. With the list of features in any current mobile device and future trends in the development of such features, mobile devices will be used Table 1 Best practices Design class to include extra time for addressing technology-related issues because of the adoption of mobile interactive problem-solving. Interactive exercises should have multiple steps, where students can traverse back-and-forth to see effect of their interactions. Break the class into multiple interactive problem-solving sessions. Each session should have problems with higher-degree of difficulties than the previous session with proper instructional scaffolding techniques. Faculty should discuss common mistakes and offer more clarification depending on the student performance after each session.

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Table 2 Future directions Can the pedagogy based on mobile interactive problem-solving be generalized across different disciplines? What sort of adaptation and modification are needed to transport this approach to social sciences disciplines? What should be the granularity of steps for interactive-exercise? Should the same effect be achieved if interactive exercises are adopted through desktop devices instead of mobile devices? Is there an optimal number of interactive problem-solving sessions in a class? Is there any discipline specific effect on that?

more prominently in education in the future. Especially, mobile devices would be supporting more interactive and evidence-driven activities, which faculty will be increasingly incorporating into day-to-day classroom environment to improve not only student’s learning and engagement but also faculty’s own teaching methodology.

7

Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Design Considerations for Mobile Learning ▶ Mobile Learning and Engagement: Designing Effective Mobile Lessons

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Instructional Design Principles for Mobile Learning

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Eun-Ok Baek and Qi Guo

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Opportunities of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Learning Anytime and Everywhere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Differentiated Learning and Personalized Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Enhancing Student Retention and Achievement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Challenge of Mobile Learning in Higher Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Technical Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Lack of Support for Instructional Design, Institutional Policy, and Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Review of Design Guidelines and Frameworks for Mobile Learning . . . . . . . . . . . . . . . . . . . . . 4.1 Pedagogies and Educational Theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Platform and System Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Technology Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Motivation and Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Recommendations of Design Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Pedagogy and Education Theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Platform and System Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Technology Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Motivation and Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Case Study of a Mobile Learning Application: Visualize TOEFL Speaking (VTS) . . . . . . 7 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

With the exponential development of mobile devices and technologies, mobile learning has been in great use in higher education. This chapter will discuss the E.-O. Baek (*) · Q. Guo College of Education, California State University San Bernardino, San Bernardino, CA, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_111

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opportunities and challenges of mobile learning in higher education and review existing literature related to the design principles and frameworks for m-learning. Finally, this chapter will recommend comprehensive design principles with examples of mobile apps that closely applied the design principles.

1

Introduction

The number of mobile phone users worldwide in 2017 was expected to reach 4.7 billion, over 63% of the world’s population (The Statistics Portal 2017). Steadily, new technology functions are adding to mobile phone markets. Mobile phones serve not only as telephones but also as minicomputers, video and still cameras, PDA’s, audio recorders, GPS navigators, and smart and integrated Internet of Things using apps. The lightweight mobile technologies have opened a new horizon of disruptive technology within education. However, it also allows students to be engaged in ubiquitous formal and informal learning environments because students can access learning environments anytime and anywhere. This learning is referred to as mobile learning or m-learning (Dyson et al. 2009). There are different definitions of mobile learning. Specifically, for a higher education landscape, El-Hussein and Cronje (2010) define mobile learning as “any type of learning that takes place in learning environments and spaces that take account of the mobility of technology, mobility of learners and mobility of learning” (p. 20). The mobility of technology refers to functionality of further advanced smart telephones and wireless technology that allow dynamic content delivery for learning. The mobility of learners means that learners are not bounded by a physical location and time but can learn at any place and at any time. The mobility of learning signifies the capacity for supporting personalized, situated, and ubiquitous learning activities. Educational researchers and practitioners will need to deepen their insights into the best ways of developing and utilizing mobile learning. However, there is still only very limited research on the design principles that guide the effective design and development of m-learning which can harness the potential of mobile technologies and services. Thus, this chapter will discuss the opportunities and challenges of mobile learning in higher education and review existing literature related to the design principles and frameworks for m-learning. Finally, this chapter will recommend comprehensive design principles with examples of mobile apps that closely apply the design principles.

2

Opportunities of Mobile Learning

Mobile learning has supported both individual and collaborative learning by expanding the definition of formal learning as well as allowing some learning to be informal (Gikas and Grant 2013). Specifically, mobile learning has

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provided increased accessibility to learning, addressed differentiated learning, and enhanced student retention and achievement (Fozdar and Kumar 2007; Kukulska-Hulme et al. 2009).

2.1

Learning Anytime and Everywhere

“Learning anytime and everywhere” is the guiding statement adopted at by MLearn 2004, the international conference on mobile learning (El-Hussein and Cronje 2010). Mobile learning eliminates boundaries of time and geographical distance at the hands of learners (Awadhiya and Miglani 2016). When it is deployed strategically, mobile learning is an extension of e-learning and can generate added value to existing e-learning venues (Wang et al. 2009). M-learning reaches the otherwise unreachable. Learners can access course materials, take quizzes, participate in synchronous and asynchronous discussions, submit assignments and receive feedback all from a single device at their fingertips (Awadhiya and Miglani 2016; Cheon et al. 2012; Hashemi et al. 2011).

2.2

Differentiated Learning and Personalized Learning

Mobile learning has offered differentiated and personalized learning. Looi et al. (2009) suggest four ways that mobile learning facilitates personalized learning: “(a) allowing multiple entry points and learning pathways, (b) supporting multimodality, (c) enabling student improvisation in situ, and (d) supporting the sharing and creation of student artifacts on the move” (p. 1120). Even though this study was conducted at an elementary school, their findings resonant within higher education contexts. 3G and 4G networks enable the simultaneous use of talking and data services (Wang et al. 2009; Wang and Shen 2012). This will greatly be speeded up with upcoming 5G network. Educators can design course materials targeting multiple modalities for their courses using rich media. Students can choose a type of course material that best fits their own learning modalities. Along the same line, rich media offer diverse ways to support student interaction.

2.3

Enhancing Student Retention and Achievement

Many studies argue that mobile learning enhances student satisfaction, which results in higher retention and achievement rates in students (Fozdar and Kumar 2007; Hashemi et al. 2011; Wang et al. 2009). M-learning also increases students’ completion rate of courses. Hashemi et al. (2011) stated that newer mobile devices tended to increase learners’ engagement and motivation. In spite of the aforementioned potential of mobile learning, it has not been deployed to its fullest due to various challenging factors.

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Challenge of Mobile Learning in Higher Education

Opportunities and challenges are like two sides of a coin. While there are many opportunities that mobile learning offers (as discussed in the previous section), mobile learning also presents many challenges in education.

3.1

Technical Challenges

Mobile phones are relatively inexpensive, and many learners own them. However, mobile phones become obsolete quickly due to rapid advancements in mobile technology (Hashemi et al. 2011). Wang and Shen (2012) argue that it is also the wide range of mobile devices used in learning which results in mobile learning design challenges. In addition, 3G and 4G networks are expensive to build and maintain, and services are, at the time of this writing, not widely available outside of urban environments (Wang and Shen 2012).

3.2

Lack of Support for Instructional Design, Institutional Policy, and Infrastructure

While the readiness of learners to adopt mobile learning is high, few instructors have successfully implemented mobile learning (Blackwell et al. 2014; Lauricella et al. 2017). This is largely due to faculty’s lack of training, as well as their own internal and external pedagogical reasons (Ertmer et al. 2012). On the top of these, in a survey study conducted by Awadhiya and Miglani (2016) in universities in India, instructors selected “lack of support for instructional design for mobile learning,” “lack of institutional policy for mobile learning,” and “lack of infrastructure/technological support” as the top three challenges to implementing mobile learning. These findings confirm Panda and Mishra’s research (2007) about the important difficulties instructors encounter at open universities. The instructors’ insufficient training, knowledge about, and skills with mobile learning are listed as the important roadblocks for technology integration – as evidenced in previous research.

4

Review of Design Guidelines and Frameworks for Mobile Learning

The authors thoroughly reviewed academic articles and research regarding design principles of mobile learning. They selected ten articles and research which discuss design guidelines for mobile learning. These selected articles and research were classified by a framework with the following five categories: (1) pedagogies and educational theories, (2) platform and system design, (3) technology acceptance,

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(4) evaluation, and (5) motivation and interaction. This framework is suggested by Hsu and Ching (2015). As most of the articles contain principles that fall in more than one category, the authors analyzed and categorized the main goals and characteristics of the articles. Category Pedagogies and educational theories

Author Jalil, Beer, and Crowther Dillard

Platform and system design

Herrington, Herrington, and Mantei

Design Principles for Mobile Learning

Mayer

Ten Research-Based Principles of Multimedia Learning Universal Instructional Design Principles for Mobile Learning

Elias

Hockly

Technology acceptance

Title Pedagogical Requirements for Mobile Learning: A Review on MOBIlearn Task Model Mobile Instructional Design Principles for Adult Learners

Mobile Learning

Wang and Shen

Message Design for Mobile Learning: Learning Theories, Human Cognition and Design Principles Levene and Evaluation of Mobile Seabury Learning: Current Research and Implications for Instructional Designers

Evaluation

Motiwalla

Mobile Learning: A Framework and Evaluation

Motivation and interaction

Menkhoff and Bengtsson

Engaging Students in Higher Education Through Mobile Learning: Lessons Learnt in a Chinese Entrepreneurship Course

Year Principle/framework/module 2015 Address pedagogical requirements of mobile learning 2012 A guide of mobile learning principles to instructional designers 2009 The principles generated from New Technologies, and New Pedagogies Project that create and evaluate mobile pedagogies 2006 The multimedia learning principles that stem from Cognitive Loading Theory 2011 Apply the UID principles to facilitate the design of instructional and operating systems of mobile learning materials 2013 The SAMR Model for using technology to design mobile learning activities for ELT 2012 Principles and processes of m-learning message design

2015 An adapted conceptual framework, which combines the Framework for the Rational Analysis of Mobile Education (FRAME) and Transactional Distance Theory (TDT) 2007 A m-learning system was developed to evaluate students’ perception of m-learning 2012 A case study indicated that engagement mobile tool enables students in a meaningful and exciting classroom

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Pedagogies and Educational Theories

Jalil et al. (2015) reviewed the MOBIlearn Task Model and demonstrated that this framework plays a significant role in facilitating mobile instructional designers’ understanding of pedagogical goals and requirements. Their study also emphasized the following key factors that instructional designers need to pay attention to in supporting mobile activities: subject, object, control, context, and communication. In Dillard’s (2012) Annotated Bibliography, the pedagogy of mobile learning was defined to be the approach, skill, and manner of teaching applied by teachers to facilitate learning outside of the classroom. The author generated six principles from the annotated bibliography for guiding the pedagogical and content design of mobile learning. • • • • • •

Develop a simple and intuitive interface design Integrate interactive multimedia Build short, modular lessons and activities Design activities which are engaging and entertaining Design content that is contextual, relevant, and valuable to the learner Just-in-time delivery (p. 108)

To derive instructional design principles of mobile learning for higher education, Herrington et al. (2009) conducted design-based research named the New Technologies, New Pedagogies Project. The following 11 principles were extracted from the research: 1. Real World Relevance: Design mobile learning that can resolve real world problems 2. Mobile Contexts: Design the mobile contexts for learners on the move 3. Explore: Allow some time for learners to explore the features of mobile learning 4. Blended: Combine mobile and other forms of technologies 5. Whenever: Mobile learning can happen any time 6. Wherever: Mobile learning can happen anywhere, not exclusively in the classroom 7. Whomsoever: Anyone could learn through mobile learning, no matter individually or by group 8. Affordances: Explore other functions of mobile learning 9. Personalize: Compatibility of learner’s mobile device 10. Mediation: Mobile learning can facilitate knowledge acquisition 11. Produce: Learners can apply the knowledge they learned from mobile learning to generate new knowledge and share via social media. Mayer (2006) proposed six principles for multimedia learning based on Cognitive Load Theory, which are contiguity, modality, redundancy, coherence,

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personalization, segmenting, and pretraining principles. Mayer (2003) also pointed out that the same multimedia principles could be applied to different media. One of the attractions of mobile learning is, it is easy to incorporate multimedia in design, and multimedia is an indispensable element of mobile learning. By this, the multimedia design principles could be used to design mobile learning.

4.2

Platform and System Design

Mobile learning is easily connected with online learning or e-learning. Many researchers tried to explore the common points and differences between the two, and Elias (2011) is one of those researchers. In his study, he compared and illustrated the relevance of online and mobile learning. Then, he extended the eight Universal Instructional Design (UID) principles which were developed previously for online learning to mobile learning. The eight UID principles are: “Equitable use, Flexible use, Simple and intuitive, Perceptible information, Tolerance for error, Low physical and technical effort, Community of learners and support, and Instructional climate” (p. 147). The UID could guide instructors in designing the operating system and instructional materials of mobile learning. Hockly (2013) stated that mobile learning is not only suitable for informal learning outside the classroom but also suitable for formal learning inside the classroom. Her work provided a strong representation of using mobile technology for English language teachers (ELT). Further, she applied the Substitution Augmentation Modification Redefinition (SAMR) Model, which was developed by Puentedura (as cited in Hockly 2013), to ELT activities design. The SAMR Model identified technologies’ role in mobile learning system designed from the easily achieved Substitution to the complicated Redefinition. Instructors can use technology to backup and improve their traditional teaching (refer to Substitution and Augmentation). For advanced utilization of technology, instructors could innovatively redesign and create their teaching approach (refer to Modification and Redefinition).

4.3

Technology Acceptance

Wang and Shen (2012) synthesized research of mobile learning and explored principles of message design for mobile learning from cognitive theories, content, devices, and methodologies. There are four principles generated from devices and concept direction for message design, “(1) design for the least common denominator, (2) design for eLearning, adapt for mLearning, (3) design short and ‘condensed’ materials for smart phones, and (4) be creative when designing for mobile devices with 3G and 4G technologies” (p. 567). Additionally, they provided guidance and detailed information about message design, such as including audio, captioning, characters, icons, and colors.

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Evaluation

Evaluation is another key factor in designing mobile learning. Levene and Seabury (2015) utilized an adapted conceptual framework to evaluate mobile learning. It combines the Framework for the Rational Analysis of Mobile Education (FRAME) and Transactional Distance Theory (TDT). This emphasized how student achievement, usability, and student attitude are three aspects to evaluate the mobile learning success. Accordingly, the principles generated from the research to guide the design and evaluation of mobile learning are: (1) design should take students’ perception and attitudes into account, (2) the content should be usable and accessible, and (3) design should be aligned with the pedagogical goal. Another researcher Motiwalla (2007) applied a prototype Mobile Learning System (MLS) to 64 students in a university for two semesters. The goal was to evaluate the effectiveness of mobile learning. The MLS model included content and material delivery and included interactivity between instructor and learner functions. After the intervention, the author deployed a survey and conducted interviews about student usage, evaluating the system’s effectiveness through students’ perceptions about it. The result of the evaluation showed that most students were satisfied with MLS and believed MLS added value to their learning experiences. Similar with Levene and Seabury’s study, Motiwalla’s research also acknowledged the importance of learner’s perceptions, the interactions between learners and instructors, and the usability of the mobile learning system.

4.5

Motivation and Interaction

Many researchers emphasized the significance of motivation and interaction design of mobile learning. A case study of an entrepreneurship course at a university in Singapore conducted by Menkhoff and Bengtsson (2012) proved that a mobile learning approach including engagement tools such as photo-sharing websites, wikis, and podcasts brought excitement to online learning and supported students in a meaningful, collaborative learning environment.

5

Recommendations of Design Principles

After reviewing the studies and research done by previous scholars, the design principles have taken root in these authors’ thinking. It is time to share pedagogically driven guidelines for instructors to design and develop mobile learning systems. The principles will still follow the five categories which were generated from the review of the extant articles.

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Pedagogy and Education Theories

5.1.1 Principle 1: Align Learning Activities with Pedagogical Goals As defined by Ally and Prieto-Blázquez (2014), pedagogy is “the art or science of being a teacher” (p. 288). The pedagogy of mobile learning is to apply mobile technology in any teachers’ approach to facilitate learning both inside and outside of classroom (Dillard 2012). Filho and Barbosa (2013) propose the following learning aspects and criteria that adapt to pedagogical goals: just-in-time knowledge, separate views, content management, educational activities, and adaptation to the context. Park (2008) conducted research with 182 students at Buldang Middle School in Korea using personal digital assistants (PDA) in music classes. Teachers and students in this study utilized learning activities through mobile devices (PDA) such as text, images, graphics, multimedia, and sound to facilitate the teaching and learning process. Laine et al. (2010) designed four mobile games in 3 years which aimed to develop game-based mobile learning. They invited 343 players to test the mobile games. During the development of the four games, the researchers determined that the context should be adapted to the pedagogical requirements. The above studies demonstrated that identifying the pedagogical goals of mobile learning is a design precondition. All the learning activities should be designed in the aim of realizing pedagogical goals, otherwise, the direction of the mobile learning deviates. Therefore, it is significant to design mobile content, curricular and learning activities to conform to pedagogical goals.

5.1.2

Principle 2: Design Learning Activities Based on Educational Theories According to Ertmer and Newby (2013), learning theories provide sources and a foundation of instructional strategies. The three main learning theories are behaviorism, cognitivism, and constructivism. Behaviorism is how people learn from observable stimulus and response (Driscoll 2012). Teachers repeatedly stimulate students with positive or negative reinforcement until students form behavioral patterns. Cognitivism tries to explore the schema (organization) of the human brain and to figure out how memory is produced and processed in the human brain (Driscoll 2012). Under constructivist theory, teachers’ function as facilitators helping students to explore the outside world based on their previous knowledge and experiences (Christensen 2008). Learning occurs during this process. Many wellknown educational theories such as Cognitive Load Theory and Community of Inquiry stem from the three learning theories. Taylor et al. (2006) developed a task model for mobile learning under the guidance of a socio-cognitive engineering approach on a project of MOBIlearn funded by Europe. The socio-cognitive approach is derived from learning theory. They then examined two field studies and synthesized the relevant theories in

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analysis. Parsons and MacCallum (2017) assessed six learning theories using a rubric to evaluate mobile learning activities. The six learning theories are: 1. 2. 3. 4. 5. 6.

Behaviorism Constructivism Experiential learning Situated cognition Communities of practice Connectivism

They first applied the rubric to an existing 2-h development workshop formed by a large group of teachers. Then, based on the rubric and perspective learning theory, Parsons and MacCallum redesigned the learning tasks. Finally, they evaluated the improved learning tasks concluding that a learning theory rubric is a helpful guide to the cyclical design of mobile learning activities. The two examples demonstrated that the guidance of educational theories could help mobile learning designers to select the proper instructional strategies for targeted learners.

5.1.3 Principle 3: Conduct Learner, Instructor, and Content Analysis Learners and instructors have different styles and characteristics. Instructional designers should conduct research and analysis to identify the needs, skill levels, and expectations of their counterparts. The methods for analysis could include surveys, interviews, and observations. Hearing from multiple learners’ voices helps designers build a more robust and supportive learning system (Baek and Schwen 2006; Baek et al. 2008). Similarly, different learning contents require different teaching approaches. Never begin a design without analysis. During the analysis phase, learners’ needs, prerequisites, and entry skills should be collected. Also, learners, instructors, and content characteristics should be determined. Finally, course goals, objectives, and learning steps should be identified (Dick et al. 2015). Chetwynd (2017) designed a project named Virtual Learning Environment (VLE) to facilitate students in exploring additional examples outside the classroom. Before the design and development of the project, a structure analysis was conducted to evaluate learning and teaching styles. The structure analysis included two phases. The first phase occurred before the design and development, targeted to determine the topic areas and the desired key features of the VLE project. After the prototype was developed, the second phase of analysis was conducted to test and analyze the prototype. Inviting the same group of undergraduate students at Plymouth University, both phases of analysis were conducted through focus group interviews. The first analysis outlined a set of learner desired features, and most of them were implemented by Chetwynd into the VLE prototype. This study revealed that conducting learner, instructor, and content analysis could help instructional designers determine the characteristics of the target learners and instructors and further decide the desired contents and functions.

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5.2

727

Platform and System Design

5.2.1

Principle 4: Design Platform and System to Be Flexible with Content Format Lacking face to face communications, mobile learning systems need to increase interactions between learners and instructional materials to enhance learners’ initiative. Different content formats can mobilize students’ positive perspectives of learning. Multimedia is a good way to interpret and illustrate content in mobile learning systems. The mobile learning platform and system should be able to recognize and support different formats of files. For example, Parsons et al. (2006) highlight the significance of utilizing rich and proper media objects to support content in their m-learning framework project which was implemented in the United Kingdom. Jalil et al. (2015) also carried out a systematic review of the MOBIlearn task model framework and discovered that multimedia resources are one of the contributing factors for MOBIlearn to support educational purposes. Multimedia resources which include video, audio, images, text messages, web pages, presentations, and other interactive materials can improve users’ experiences of mobile learning. 5.2.2 Principle 5: Embed Online Support in the Platform or System The degree of satisfaction of mobile learning experiences depends on the users’ technological skills. According to Baek and Schwen’s (2006) research, technological problems are the major obstacle for users with limited skills. Online support could provide instant help to learners and, thus, meet participants’ needs. To discover the constraints of a Bring Your Own Device (BYOD) project, Song and Kong (2017) conducted a research study through observing and field notes of 17 teachers’ classes in the Hong Kong Institute of Education. They found that higher educational teachers needed technological assistance with operating the mobile devices as well as in designing the mobile learning activities. Peters’ (2007) research interviewed 29 business and education providers in Australia and discovered that providing customer service in mobile technologies could significantly increase the efficiencies in mobile learning.

5.3

Technology Acceptance

5.3.1 Principle 6: Access to Different Mobile Devices and Systems Unlike online learning, different mobile devices are designed based on different mobile operating systems. The two major mobile systems in the current market are Apple iOS and Google Android. Mobile learning applications need to be designed for at least two versions that use both operating systems. For instance, Dlab et al. (2017) led a design-based research study of math learning in an elementary school in Croatia. A mobile learning system named SCOLLAm (Seamless and Collaborative Mobile Learning) was developed. During the design phase, they stressed the importance of a mobile learning system that can adapt to the two major platforms and the

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different types of mobile devices. The mobile application would lose large numbers of users if not applicable in the two main mobile application markets.

5.3.2 Principle 7: Provide High Error Tolerance The mobile learning application needs to be simple enough for participants to use easily. However, it must also be complex enough to serve participants’ needs (Baek and Schwen 2006). Using an online study of Japanese university students, Lau et al. (2017) investigated users’ needs in mobile learning. The results showed that content display issues are barriers for most subjects in mobile learning. Users would quickly discard a mobile application when they frequently encountered system crashes. Instructional designers should test for edge and critical scenarios to increase the error tolerance of the system before going live. 5.3.3 Principle 8: Apply to Both High and Low Quality of Internet Due to the characteristics of mobile devices, mobile learning relies on a network. Occasionally, every user faces some time that the signal of a network is weak. For instance, people will be frustrated to find that they have free time to learn during their commuter time, but due to network on the transportation being weak, their mobile learning system cannot be used. Usually, the size of multimedia files is large and, thus, requires high Internet speed to download. Compressing the size of files in the system without reducing the quality of the files can help increase download speeds and perform better in low Internet speed areas. Designing mobile learning that functions properly, even in low quality of Internet areas, or provides background load processes will add power to the mobile learning application. Song and Kong’s (2017) research on 17 teachers reported that the unstable Internet connection and slow file transmitting speed were annoying to students and discouraged them from incorporating the BYOD in their classes, whereas some of the teachers who resolved the technological issues were able to explore more through this project. To sum, mobile learning must flex to different mobile devices, adapt to both iOS and Android mobile application platforms, and overcome technical constraints by increasing error tolerance and providing alternative solutions in slow Wi-Fi speed environments. When those issues are resolved, more and more teachers and students will accept and adapt to mobile learning.

5.4 5.4.1

Evaluation

Principle 9: Conduct Formative and Summative Evaluations During the Whole Process of Designing Mobile Learning Formative evaluations collect information during the design and development phases of the product, while summative evaluations collect information at the final stage of the design and development of the product. Both evaluation types assist in making decisions about whether the instruction meets original expectations

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(Dick et al. 2015). Why bother with two forms of evaluation, though? According to Dick et al. (2015), the previous scholars found that the performance of the designed learning products was not as good as expected and had limited effectiveness. In reviewing the scenarios, they expanded the concept of evaluation to include formative evaluation and summative evaluation. By conducting the two kinds of evaluations, reflections from learners are encouraged. This learner feedback then allows for timely revisions after each evaluation phase. Much design-based research follows a cyclical process with continual reflection and refinement. Dlab et al. (2017) used the process of modifying their SCOLLAm by first identifying learners’ and teachers’ requirements, then exploring their perceptions after using the product. Afterwards, they revised accordingly and then gathered information again to make continued improvements. Similarly, Chetwynd’s (2017) VLE project carried out at Plymouth University begins with analyzing learners’ and instructors’ desired topics. From there, it designs the prototype, investigates the results by evaluating users’ critiques about the strengths and weaknesses of the prototype. The researchers then evaluate users’ reflections and revises the product. Thus, evaluation not only encourages progress but also improves a mobile learning product.

5.5

Motivation and Interaction

5.5.1 Principle 10: Motivate Learners by Interactive Activities Learners may feel isolated in their learning experiences because of the asynchronous features of mobile learning. Strengthening the social component of mobile learning can increase its ability to establish individual and group relationships in virtual learning environments (Garrison 2009). It may also contribute to increased awareness of learners’ self-regulation. In a study conducted by Shen et al. (2009), researchers pointed out that a lack of interactivity in many Chinese online classes which provided only recorded lectures led to two consequences: distancing students and encouraging passive learning. Shen et al. (2009) developed a mobile learning system which provided customized live broadcasts of real-time classrooms together with real-time text message polls involving 562 students and instructors in the e-learning lab of Shanghai University. Through a survey, the researchers concluded that students may feel disconnected from their classes if interactivity is insufficient. They went on to conclude that providing more opportunities for students to work in study groups would increase interaction. Instructional designers could expand the communications tools in mobile learning design. Increasing learner-content interaction to the learning material would make learning become dynamic and attract learners’ attention. Increasing learner-learner and learner-instructor communication would help to create mobile learning communities and build an effective and efficient mobile learning environment. Mobile social media is one of the convenient and ready-to-use ways to increase learner-learner interaction and learner-instructor interaction.

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Case Study of a Mobile Learning Application: Visualize TOEFL Speaking (VTS)

Visualize TOEFL Speaking (VTS) is a mobile application, designed and developed by the Master of Arts in Instructional Technology Program Team at California State University, San Bernardino (CSUSB). The purpose of the VTS is to help learners practice English speaking skills for the TOEFL test. It is an interactive mobile learning platform, which incorporates various learning activities, such as watching lectures, viewing tutorial videos, uploading users’ voices for instructor feedback, and participating in online discussions. Figure 1 is a screenshot of the main functions of VTS. The pedagogical goal of this mobile application is that international students will improve their TOEFL speaking skills through a self-paced, mobile learning course. It aims to create an interactive learning experience through the following three aspects. First, this is a professionally designed learning course developed by a team of instructional designers including faculty and students, subject matter experts (SME’s) who have taught TOEFL courses for over 15 years, and a programmer. Second, the mobile app’s course content is based on the most current TOEFL speaking test. Finally, the mobile app’s third aspect is its in-time feedback. Instructors provide feedback within 24 h to each student’s oral practice through the mobile app. All of these elements are in accordance with Principle 1: Align Learning Activities with Pedagogical Goals. Figure 2 is the screenshot of a sample course. The learning activities are designed under the guidance of constructivism, which allow learners to watch the tutorial videos, upload their voice, receive feedback from instructors, orally practice more, and interact with other learners in the discussion forum. Teachers play the role Fig. 1 Main functions of VTS

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Fig. 2 Sample course

of facilitators in the mobile learning course. This guided feedback accords with Principle 2: Design Learning Activities Based on Educational Theories. Following the ADDIE (Analysis-Design-Development-Implementation-Evaluation) instructional design process, the development team conducted surveys and interviews with English language program students and instructors at CSUSB. With the learners and the instructor, the team performed content analysis by reviewing existing resources related to TOEFL. The content areas that most students and instructors identified as significant problem areas were selected to be main features of the application – speaking about a given topic and free topic. This is consistent with Principle 3: Conduct Learner, Instructor, and Content Analysis. Figures 3, 4, and 5 are screenshots of sample courses, which embed multimedia files. Except for the tutorial video demonstrated in Figs. 2, 3, and 4 are screenshots of the voice recording, reviewing, and saving processes. Figure 5 shows the discussion board, which allows learners to provide peer reviews and to communicate with instructors. The application provides multimedia to enhance learners’ initiative and learning. The rich format of content demonstrates Principle 4: Design Platform and System to Be Flexible with Content Format. There is a technical support function designed into the mobile app. Figure 6 shows a screenshot of technical support that also includes a user satisfaction survey. Both of these reflect Principle 5: Embed Online Support in the Platform or System. The designers already developed the Android version and are now working on the IOS version. After the IOS version is ready to use, the mobile application will fulfill Principle 6: Access to Different Mobile Devices and Systems. When designing the mobile app, the instructional designers keep it simple by focusing on only one area, speaking. This ensures participants’ ease of use. At the same time, the mobile app provides complex functions allowing learners to upload

732 Fig. 3 Record learner’s voice

Fig. 4 Review and save learner’s voice

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Fig. 5 Discussion board

Fig. 6 Technical support

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their voices and receive feedback from their instructors. This is an effective way to practice TOEFL speaking according to the instructor and learner analysis. While testing the mobile app, instructional designers received user feedback to improve the interface design and increase high error tolerance, thus fulfilling the requirement of Principle 7: Provide High Error Tolerance. The tutorial videos in the mobile app are externally connected through YouTube. The size of multimedia files is smaller than integrating the large size of video directly in the mobile app. This design compresses the size of system files without reducing multimedia quality. This also increases download speed, which aligns with Principle 8: Apply to Both High and Low Quality of Internet. Upon the above mentioned technical support function, after users proposed suggestions, the VTS will revise and update according to customers’ reflections, and a new version will be released for user download. This demonstrates Principle 9: Conduct Formative and Summative Evaluations During the Whole Process of Designing Mobile Learning. The functions of uploading learners’ voices, discussion boards, and instructors’ feedback are consistent with Principle 10: Motivate Learners by Interactive Activities. As presented in Figs. 2, 3, 4, and 5, learning activities deploy various multimedia which require students to be motivated and engaged in diverse interactions.

7

Future Directions

In this chapter, we recommended ten design principles through an in-depth literature review. The ten design principles are classified by a framework with the following five categories: (1) Pedagogies and Educational Theories • Principle 1: Align Learning Activities with Pedagogical Goals • Principle 2: Design Learning Activities Based on Educational Theories • Principle 3: Conduct Learner, Instructor, and Content Analysis (2) Platform and System Design • Principle 4: Design Platform and System to Be Flexible with Content Format • Principle 5: Embed Online Support in the Platform or System (3) Technology Acceptance • Principle 6: Access to Different Mobile Devices and Systems • Principle 7: Provide High Error Tolerance • Principle 8: Apply to Both High and Low Quality of Internet (4) Evaluation • Principle 9: Conduct Formative and Summative Evaluations During the Whole Process of Designing Mobile Learning (5) Motivation and Interaction • Principle 10: Motivate Learners by Interactive Activities

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The ten principles are chosen due to their importance in designing and developing mobile learning. As with any effective technology integration, designing mobile learning takes an alignment of the content knowledge with pedagogical and technical knowledge (Mishra and Koehler 2006; Koehler and Mishra 2008). The ten design principles are currently adopted within higher education to varying degrees. These principles serve as a comprehensive framework for the design and development of mobile learning, which allows educators and instructional designers to harness opportunities offered by mobile learning. Even though these principles are intended as guidelines when designing and developing mobile learning, these can also be utilized as an analytical framework when evaluating mobile learning. Future study is needed to utilize the above-mentioned principles to design a mobile learning system appropriate for formal learning in higher education. After a system is developed, action research must be conducted to evaluate the mobile learning system’s effectiveness. Considering the rapid development of mobile technology, systematic examinations of research about mobile learning will provide insights and help continue to revise and refine these principles.

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International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering 11 (10): 2320–2325. scholar.waset.org/1307-6892/10008028. Driscoll, Marcy P. 2012. Psychological foundations of instructional design. In Trends and issues in instructional design and technology, ed. Robert A. Reiser and John V. Dempsey, 4th ed., 52–60. New York: Pearson. Dyson, Laurel Evelyn, Andrew Litchfield, Ryszard Raban, and Jonathan Tyler. 2009. Interactive classroom mLearning and the experiential transactions between students and lecturer. In Proceeding of the 26th annual Ascilite international conference, Auckland (pp. 233–242). http:// www.ascilite.org/conferences/auckland09/procs/dyson.pdf. Accessed 1 Dec 2018. El-Hussein, Mohamed Osman M., and Johannes C. Cronje. 2010. Defining mobile learning in the higher education landscape. Educational Technology & Society 13 (3): 12–21. Elias, Tanya. 2011. Universal instructional design principles for mobile learning. The International Review of Research in Open and Distributed Learning 12 (2): 143–156. https://doi.org/ 10.19173/irrodl.v12i2.965. Ertmer, Peggy A., and Timothy J. Newby. 2013. Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly 26 (2): 43–71. https://doi.org/10.1002/piq.21143. Ertmer, Peggy A., Anne T. Ottenbreit-Leftwich, Olgun Sadik, Emine Sendurur, and Polat Sendurur. 2012. Teacher beliefs and technology integration practices: A critical relationship. Computers & Education 59 (2): 423–435. Filho, Nemésio, and Ellen Barbosa. 2013. A requirements catalog for mobile learning environments. In Proceedings of the 28th annual ACM symposium on applied computing (SAC 2013), Coimbra, 1266–1271. https://doi.org/10.1145/2480362.2480599. Fozdar, Bharat Inder, and Lalita S. Kumar. 2007. Mobile learning and student retention. International Review of Research in Open and Distance Learning 8 (2): 1–18. Garrison, D. Randy. 2009. Online community of inquiry review: Social, cognitive, and teaching presence issues. Journal of Asynchronous Learning Networks 11 (1): 61–72. https://eric.ed. gov/?q=EJ842688&id=EJ842688. Gikas, Joanne, and Michael M. Grant. 2013. Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. The Internet and Higher Education 19: 18–26. Hashemi, Masoud, Masound Azizinezhad, Vahid Najafi, and Ali Jamali Nesari. 2011. What is mobile learning? Challenges and capabilities. Procedia – Social and Behavioral Sciences 30: 2477–2481. https://doi.org/10.1016/j.sbspro.2011.10.483. Herrington, Anthony, Jan Herrington, and Jessica Mantei. 2009. Design principles for mobile learning. In New technologies, new pedagogies: Mobile learning in higher education, ed. Jan Herrington, Anthony Herrington, Jessica Mantei, Ian Olney, and Brian Ferry, 129–138. Wollongong: University of Wollongong. http://ro.uow.edu.au/. Hockly, Nicky. 2013. Mobile learning. ELT Journal 67 (1): 80–84. https://doi-org.libproxy.lib. csusb.edu/10.1093/elt/ccs064. Hsu, Yu-Chang, and Yu-Hui Ching. 2015. A review of models and frameworks for designing mobile learning experiences and environments. Canadian Journal of Learning and Technology 41 (3): 1–22. https://doi.org/10.21432/T2V616. Jalil, Abdurrahman, Martin Beer, and Paul Crowther. 2015. Pedagogical requirements for mobile learning: A review on MOBIlearn task model. Journal of Interactive Media in Education 2015 (1): 1–17. https://doi.org/10.5334/jime.ap. Koehler, Matthew, and Punya Mishra. 2008. Introducing TPCK. In Handbook of technological pedagogical content knowledge (TPCK) for educators, ed. AACTE Committee on Innovation and Technology, 3–29. Mahwah: Lawrence Erlbaum Associates. Kukulska-Hulme, Agnes, Mike Sharples, Marcelo Milrad, Inmaculada Arnedillo-Sánchez, and Giasemi Vavoula. 2009. Innovation in mobile learning: A European perspective. International Journal of Mobile and Blended Learning 1 (1): 13–35.

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Part IV Higher Education Partnerships with Nonprofit and Profit Organizations

Higher Education Partnerships with Nonprofit and Profit Organizations: An Introduction

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Abstract

Across the globe, institutions of higher education are positioned to generate and test innovative high-technology capabilities and lead their adoption in our STEMdriven worldwide market by investing in partnerships with nonprofit and profit organizations. Multifaceted collaborations among educational enterprises can support the design, implementation, and evaluation of learning using mobile devices and advocate concomitantly how best to change pedagogical practices in order to advance student learning. This introduction highlights scholarship around mobile learning within existing partnerships between higher education institutions and nonprofit and profit organizations. Partnerships include affiliations internal to higher education institutions, alliances crossing international boundaries, collaborations engaging P–12 school systems, and syndicates aligning organizations and companies within the educational marketplace. Examples from the current scholarship are highlighted in the Introduction and then unpacked by leading international researchers who authored the chapters that follow. A common recommendation underscores the need to prepare students for the STEM-focused global economy by utilizing the ubiquitous nature of mobile devices in both formal and informal learning environments. While this section addresses how to adopt and refine mobile technology in learning environments by harnessing the collective expertise from multiple organizations, leading international researchers also propose feasible opportunities for immediate action and evaluation that are guided by the needs of partnering entities.

B. Gimbert (*) Department of Educational Studies, Educational Administration, The Ohio State University, Columbus, OH, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_31

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A product of the new STEM democracy is the development of indigenous hightechnology capabilities. When effective mobile learning integrates with receptive learning environments, educators seize an opportunity to enhance teaching skills in order to advance student learning. Ubiquitousness of mobile devices in the STEMdriven global economy fuels opportunities for shared learning between teachers and students in both formal and informal learning contexts (Peng et al. 2009). Higher education partnerships with nonprofit and profit organizations afford relatively easy access to mobile-friendly resources that in turn enhance learners’ understanding and practical application of content knowledge seamlessly across learning environments. School systems strive to integrate mobile technology to connect students’ learning experiences beyond the classroom (Winslow et al. 2016). For elementary, secondary, and tertiary education students, mobile learning technology can “level the learning field” due to the relatively low cost and accessibility in most households and workplaces. Globally, adoption of research-based practices of mobile technology in learning environments is recognized as important to student learning by government legislation and international and national educational organizations across the globe. While the International Society for Technology in Education sets international standards for the use of technology in educational environments, international educational organizations, such as the International Council for Science (ICSU) and the American Educational Research Association (AERA), expect every student should be able to access age-appropriate curricula using technologically applicable tools. On the international stage, UNESCO (2014) advocates technology “can contribute to universal access to education, equity in education, the delivery of quality learning and teaching, teachers’ professional development and more efficient education management, governance and administration.” An example at the national legislative level is the Individuals with Disabilities Education Act, 20 U.S.C.§1400 (2004), in the United States that promotes the use of “assistive technology to increase, maintain, or improve functional capabilities of a child with a disability.” At the school level, coherent professional development experiences for educators can enhance administrators’ and classroom teachers’ knowledge and application of mobile learning skills in order to meet goals of equity and excellence for all students. In response, a digital multimedia medium supports mobile learning processes to purposefully accelerate how students synthesize and apply content knowledge in the context of a twenty-first-century classroom. Research-based best practices can help teachers engage students in hands-on activities using mobile-friendly digital resources to capture and sustain student interest for learning. Knowing how to incorporate technology into pedagogical practice and translate this into actions to enhance learning is therefore a vital shared responsibility of both for teachers and students. The chapters in this part, entitled “Higher Education Partnerships with Non-profit and Profit Organizations,” describe mobile learning applications, educational collaborations and partnerships, and programs that exemplify how learning can take place any time and anywhere. These range from early childhood classrooms to partnerships between higher education institutions and industry and include case

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studies of mobile learning. Work by leading mobile learning researchers across the globe suggests efficient and effective use of mobile technology in the current learning environments. Each chapter presents opportunities for future research within learning environments in profit and nonprofit organizations. In ▶ Chap. 43, “Trends in Mobile Learning: 2010–2017” Moonsun Choi and Dean Cristol explicate definitions of mobile learning and present a synopsis of theoretical frameworks recently applied to mobile learning research between 2010 and 2017. Drawing upon an existing analytical process used in the e-learning field (Shih et al. 2011; Wu et al. 2012); this systematic review is useful as an introductory reference for researchers as they formulate a design to evaluate mobile learning research. This chapter summarizes theoretical perspectives driving recent mobile learning studies’ purposes, questions, and methodologies. In ▶ Chap. 44, “P-16 Partnerships for Learning with Mobile Technologies: Design, Implement, and Evaluate,” Belinda Gimbert, Lauren Acree, Kui Xie, and Anika Ball Anthony discuss advancements in mobile technologies that hold promise for partnerships supporting teaching and learning in formal and informal educational settings. Across the globe, primary and secondary schools join with higher education institutions to design and implement mobile learning experiences for P-12 students and seek external funding to support such initiatives. This chapter describes a framework for advancing and sustaining m-learning initiatives in a P-16 partnership using a collaborative evaluation approach. Three key premises fortify the Partnership, Evaluation, Design, and Implementation (PEDI) framework: (1) partnership is the central driving force; (2) stakeholders and external experts determine processes of collaborative evaluation; and, (3) the relationship between the partnership, design, implementation, and evaluation needs to be both reciprocal and iterative. When evaluation moves beyond “a snapshot” of the initiative’s impact, stakeholders’ collective expertise and unique contributions are recognized. These authors draw on literature concerning educational technology design and implementation to advocate a partnership of higher education representatives (faculty, researchers, instructional designers, and software developers) and school-based educators (teachers, administrators, staff, and instructional technology coordinators) and adopt collaboratively evaluation practices in order to promote the most effective use of m-learning solutions in P-12 schools. In ▶ Chap. 45, “Mobile Technologies for Teaching and Learning,” Rajiv Ramnath and Ajay Kuriakose discuss how mobile information technologies can unshackle students from desks and classrooms and allow them to learn any time and in any place. Students explore and consume information, record their learning, and collaborate with mentors and peers. Because mobile devices know user location and identity, it is possible to both situate and personalize a user’s needs. Using the various theories and processes of learning as a lens, the authors project how the growing affordances of mobile technologies may influence student’s future learning. In ▶ Chap. 46, “Mobile Devices for Preschool-Aged Children,” Rachel Ralph and Stephen Petrina call for urgent attention to how to integrate media and technology and mobile devices most effectively in early childhood education, specifically in

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curriculum that is designed for preschool-aged children. Digital literacy affords and enhances multiple processes for children to communicate through speaking, symbol recognition, and the production of written language by using a touchscreen or keyboards. This chapter also explores the complexity of digital literacy, including the use of interactive media, such as software programs, applications (apps), broadcast and streaming media, television, eBooks, the Internet, and other content for young children. In particular, the research addresses the use of iPads with preschoolers. In ▶ Chap. 47, “Highs and Lows of Mobile Digital Technology Integration in Kindergarten,” the research team of Monica McGlynn-Stewart, Nicola Maguire, Emma Mogyorodi, Leah Brathwaite, and Lisa Hobman examined kindergarten teachers’ professional learning experiences when using open-ended tablet applications to support preschool and primary-aged children’s oral and visual literacy learning. The research team functioned as technical advisors, observers, and resource providers in order to ascertain educators’ levels of confidence, experience, and interests through regular interviews, questionnaires, and bi-weekly classroom visits. Over the 2-year partnership, participants experienced a series of highs and lows in response to particular contexts. With time and ongoing support, educators resolved a series of challenges to develop deeper understandings of the technical and pedagogical issues related to digital technology (DT) integration. This partnership illustrates how teacher learning in DT integration is complex and nonlinear, with different competencies and needs for support coming to the fore over time. In ▶ Chap. 48, “Role for Instructional Technology Leadership in K-12 Public Education” examines the role of instructional technology leadership in K-12 public schools. This author claims the role of an instructional technology leader (e.g., school superintendent, principal, technology director, technology coordinator, digital literacy coach, instructional coach, or classroom teacher) is to educate classroom teachers how to integrate technology into instructional practice and evaluate the ways teachers teach with technology. Indiana public school superintendents and teachers completed a survey where they were asked to rank the skills and experiences (completely essential, important, desirable-but-not-essential, not-at-all-important) that they believed were essential for an instructional technology leader. A comparison of mean scores indicated that both the superintendent and teacher groups tended to rank items similarly. However, an examination of participants’ conception of what defines instructional technology diverged markedly. Edelberg probes for an explanation about why both groups can find agreement about what instructional technology leaders should do, while unable to agree on a definition of instructional technology. In ▶ Chap. 49, “1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation,” Laura Eutsler frames the Concerns-Based Adoption Model (CBAM) to report the stages of concern and levels of one-to-one iPad use by a firstgrade teacher. A university researcher and a classroom teacher partnered to investigate technology integration strategies. Data from monthly video chats, text from a dialogue journal, and student work artifacts were analyzed. Findings show this teacher required 2 years to advance through the seven stages of concern, and it was during the management stage that the highest level of the concern was evidenced.

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In ▶ Chap. 50, “Cross-Country University Collaboration Barriers and Solutions”, Yongzheng Liu, Ziqui Zhang, and Yu (Aimee) Zhang maintain their premise that university collabo-ration generates enormous benefits. The majority of these joint outcomes, however, are not as productive as anticipated. Expanding student enrolment diversity, increasing knowledge exchange, and advancing opportunities for academic expertise for all partners are important considerations to grow and sustain global collaborations. China has been the major recruiting source of undergraduate and postgraduate overseas students for many universities. Many Australian and New Zealand universities have formalized relations with Chinese universities as international strategic partners. However, differences between Australian and Chinese policies, structures, and cultures create barriers for these collaborations. In this chapter, an analysis of the foremost obstacles highlights areas needing attention to ensure productive communication. To save transaction costs for appropriate collaborators and to increase the success rate in current collaborations, it is important to identify the key issues such university partnerships between Australia, New Zealand, and China encounter. This case study presents empirical evidence from observations conducted over the past 10 years of university collaborations, as well as face-to-face interviews with collaborators from three pioneering Chinese universities. Mobile technology can address communication challenges and potentially diminish misunderstanding between institutions. The chapter concludes with possible solutions and potential action steps for future cross-country university collaborations among universities and educational institutions. Collectively, the authors from this section both critique and celebrate how higher education partnerships with nonprofit and profit organizations can effectively integrate mobile learning within receptive learning environments in order to enhance teaching skills for the specific purpose of advancing preschool, elementary, secondary, and tertiary students’ learning. Continuing to grow “smart” higher education partnerships with both nonprofit and profit organizations afford further opportunities to harness the openness and power of globally available mobile technologies.

References Peng, H., Y.J. Su, and C.C. Tsai. 2009. Ubiquitous knowledge construction: Mobile learning redefined and a conceptual framework. Innovations in Education and Teaching International 46: 171–183. Shih, J.-L., H.-C. Chu, G.-J. Hwang, and Kinshuk. 2011. An investigation of attitudes of students and teachers about participating in a context-aware ubiquitous learning activity. British Journal of Educational Technology 42 (3): 373–394. UNESCO. 2014. United Nations decades of education for sustainable development 2005–2014: Draft international implementation scheme. Winslow, J., J. Dickerson, C. Weaver, and J. Fair. 2016. Iterative and event-based frameworks for university and school district technology professional development partnerships. TechTrends 60: 56–61. Wu, W.-H., Y.-C.J. Wu, C.-Y. Chen, H.-Y. Kao, C.-H. Lin, and S.-H. Huang. 2012. Review of trends from mobile learning studies: A meta-analysis. Computers & Education 59 (2): 817–827.

Trends in Mobile Learning: 2010–2017

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Definition of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Theoretical Frameworks Applicable to Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Sociocultural Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Activity Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Framework for the Rational Analysis of Mobile Education (FRAME) Model . . . . . . 4 Research Trends in Mobile Learning from 2010 to 2017: Research Purpose, Result, and Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Research Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Research Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Research Methods Used in the Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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This chapter discusses definitions of mobile learning and presents a synopsis of theoretical frameworks applied to mobile learning research from 2010 to 2017. Drawing upon an analytical process used in the e-learning field by Shih et al. (2011) and Wu et al. (2012), this systematic review is useful as an introductory

M. Choi (*) Center on Education and Training for Employment, The Ohio State University, Columbus, OH, USA e-mail: [email protected]; [email protected] D. Cristol Department of Teaching and Learning, The Ohio State University, Lima, OH, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_110

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reference for researchers as they design mobile learning research. This chapter summarizes current theoretical perspectives and identifies recent mobile learning research purposes, outcomes, and methodology.

1

Introduction

Recent studies identify mobile devices as important and effective pedagogical tools that provide students with learning opportunities and support individual and/or collective learning without constraints of time and space (Ahmed and Parsons 2013; Chiang et al. 2014) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Mobile technology use for teaching and learning appears to be an irrevocable trend in education. However, given findings from the current scholarship, it is difficult to answer the question, what does mobile learning means to students and teachers? Initially, scholars and practitioners paid attention to mobile devices such as PDAs (personal digital assistants), mobile/ smart phones, and tablet PCs (Cochrane 2013). The evidence from recent studies indicates how the design of mobile learning systems/applications may improve students’ achievement and increase learning opportunities (Boticki et al. 2015; Lee et al. 2016). Theoretical frameworks with constructs for modeling mobile learning that promotes student learning are in the embryonic stages of development (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). As models of learning that engage mobile technologies in formal settings emerge, researchers continue to investigate the effectiveness of practical applications of mobile technologies in informal educational settings (Charitonos et al. 2012; Chen et al. 2017; Jones et al. 2013). For example, Chen et al. (2017) developed and evaluated a mobile application system called iBeacon for students to explore information when they visit science museums. However, many K-12 schools now permit students to use their own mobile devices (bring your own devices or BYOD) in the classroom. These devices provide efficient access to information relating to the specific content areas and learning contexts in formal educational settings (Hwang et al. 2011; Shih et al. 2011; Wu et al. 2012). In order to explore definitions, theoretical frameworks, and methodologies applied to mobile learning in relation to secondary and tertiary students and teachers, Choi and Cristol synthesized mobile learning research from 2010 to 2017. Drawing on an analytical process used by Shih et al. (2011) and Wu et al. (2012), they identified articles that elucidated concepts of mobile learning and theories from Social Sciences Citation Index (SSCI) journals from 2010 to 2017. Journals were searched with high impact factors designated by the Institute for Scientific Information (ISI) Journal Citation Reports (Shih et al. 2011; Wu et al. 2012) including Computers and Education (CE), British Journal of Educational Technology (BJET), Innovations in Education and Teaching International (IETI), Educational Technology Research and Development (ETR&D), and Journal of Computer Assisted Learning (JCAL).

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This chapter discusses the definitions of mobile learning and theoretical frameworks that explicate mobile learning, participant selection, international learning contexts, learning domains (content), and mobile devices and highlights methodological issues evolving from the mobile learning research. Through a systematic review, this chapter presents trends of contemporary mobile learning research conducted between 2010 and 2017 and offers considerations when integrating mobile learning tools for promoting K-12 student learning, both inside and outside the classroom.

2

Definition of Mobile Learning

Although educators widely use the term “mobile learning,” there is no consensus for its definition (Crompton 2013a, b; Traxler 2009) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Since mobile learning first appeared in 2005 as a recognized term in a Google search (Crompton 2013a), a common practice by scholars and practitioners was to define mobile learning by comparing it with similar types of learning such as electronic learning (e-learning), distance learning (d-learning), and ubiquitous learning (u-learning). For example, a widely used definition of e-learning is “All forms of electronic learning and teaching, which are procedural in character and aim to effect the construction of knowledge with reference to individual experience, practice and knowledge of the learning. Information and communication systems, whether networked or not, serve as specific media to implement the learning process” (Tavangarian et al. 2004, p. 274). E-learning is framed by multiple types of media that deliver text, audio, images, and animations provided by electronic technologies/media/tools supporting individual learning. Students often use electronic technologies that are networked not centrally important to Tavangarian’s definition of e-learning which is “structured, media-rich, broadband, interactive, intelligent” (Traxler 2009, p. 14) information and communication systems. Distance learning (d-learning) challenges the traditional concepts of learning in school environments, where face-to-face interactions between teachers and students or students and students are important elements for learning to occur. Although d-learning differs from traditional types of learning in multiple ways, d-learning is similar to e-learning since electronic technologies enable students to learn in an informal educational setting (away from traditional classroom settings). For the purposes of this chapter, mobile learning encompasses the use of mobile devices within an e-learning context (see Fig. 1). Specific characteristics of mobile devices support access to the Internet, search for information, communicate/interact with others in real time, and meet employment responsibilities anytime-anywhere. Mobile learning is described as “personal, spontaneous, opportunistic, informal, pervasive, situated, private, context-aware, bite-sized, portable,” (Traxler 2009, p. 13) for “supporting flexible, accessible, personalized education” (Kukulska-Hulme 2010, p. 1).

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Fig. 1 Interconnectedness of e-learning, m-learning, u-learning, and d-learning. (Based on Crompton 2012b)

According to Traxler (2011), mobile learning further extends learner-centered learning in five ways: (1) contingent learning, changing experience students have by responding to the environment; (2) situated learning, in which learning occurs in the conditions applicable to the learning; (3) authentic learning connected to immediate learning goals; (4) context-aware learning, in which the environment and history affect learning; and (5) personalized learning, fitting into each peculiar student according to his/her interests and preferences.

3

Theoretical Frameworks Applicable to Mobile Learning

This section explains three commonly used theories applied to studies of mobile learning in the extant literature: sociocultural theory (Cole 1996; Rogoff 1995; Vygotsky 1978), activity theory (Engeström 2001; Liaw et al. 2010), and the FRAME model (Framework for the Rational Analysis of Mobile Education) (Koole 2009).

3.1

Sociocultural Theory

Sociocultural theory was the most commonly used theoretical framework (Charitonos et al. 2012; Kim et al. 2011; Pachler et al. 2013; Reynolds et al. 2010; Sandberg et al. 2011; Ting 2013). From a sociocultural perspective on learning (Cole 1996; Rogoff 1995; Vygotsky 1978), knowledge is a cultural product, “shaped by micro and macro-cultural influences and evolves through increasing participation within different communities of practice” (Windschitl 2002, p. 141).

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In contrast to a traditional acquisition-oriented learning model that emphasizes transmitting knowledge and skills, sociocultural approach conceptualizes learning as “a collective participatory process of active knowledge construction that underscores context, interaction, and situatedness” (Salomon and Perkins 1998, p. 2). Central to this theoretical perspective, participation in a social process of knowledge construction mediates an individual’s learning. Namely, people’s experiences within socialcultural contexts influence their thoughts, ideas, and understandings. In this way, m-learning closely connects to sociocultural perspectives in terms of context-aware and situated learning. Researchers regard mobile learning as an innovative approach for collaborating physically and virtually. Students participating in mobile learning, both in formal and informal learning situations, can interact with their peers and teachers in a live context via their mobile devices and through this multi-interaction construct their own knowledge.

3.2

Activity Theory

When integrating mobile technologies into learning processes, scholars (Crompton 2013b; Liaw et al. 2010; Moura and Carvalho 2013; Uden 2007) recognize activity theory as an appropriate lens to explain theoretically and conceptually processes of mobile learning. Uden (2007) investigated how mobile learning is socially mediated which is closely connected with features of activity theory developed by Engeström (2001). Essentially, subjects’ interactions mediate via tools, rules, community, and division of labor in an activity system. Learners (subjects) access mobile devices (tools), manage their learning (rules), create/select their learning environment (community), and select collaborative engagement (division of labor). Liaw et al. (2010) describe three components of activity theory and mobile learning. The control of learning relating rules in activity theory defines as selfmanagement or self-regulated learning in mobile learning. The context of learning referring community in activity theory views as the mobile learning system encouraging and enhancing learners’ use of mobile devices. Finally, the communication of learning in activity theory relates to the individual or collective activities of mobile learning (Fig. 2).

3.3

Framework for the Rational Analysis of Mobile Education (FRAME) Model

Koole (2009) proposed the FRAME model to illustrate mobile learning as “a process resulting from the convergence of mobile technologies, human learning capacities, and social interaction” (p. 25). The convergences interrelate and interlink to Vygotsky’s work. The FRAME model highlights the role of technology beyond simply an artifact of cultural-historic development, and demonstrates how the device, learner, and social aspects are interconnected entity within the mobile learning context. The device aspect(D) refers to “the physical, technical and

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Instruments

Object

Subject

Rules

(control of learning)

Community

(context of learning)

Outcome

Division of labour

(communication of learning)

Fig. 2 A framework for mobile learning based on activity theory. (Based on Liaw et al. 2010, p. 448)

functional characteristics of mobile devices.” The learner aspect (L) presents “the cognitive abilities, memory, prior knowledge, emotions and possible motivations” of the individual learner. The social aspect (S) constitutes “the process of interaction and cooperation.” In this model, users interact with a mobile device in order to mediate mobile learning social practices with information and to network with other users. In the FRAME model, knowledge is collaboratively constructed and shared in a mobile-friendly context that intersects interactions and mediates conversational technology. This framework describes the process learners undergo when they interact and construct knowledge through mobile learning (Fig. 3).

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Research Trends in Mobile Learning from 2010 to 2017: Research Purpose, Result, and Method

The search terms “mobile learning,” “m-learning,” “mobile devices,” or “mobile” with “learning” in five journals (BJET, CE, ETR&D, IETI, and JCAL) were included in the search. Each study met the criteria indicated in Table 1. Studies were then coded using these terms: (a) research purpose, (b) methodology, (c) participant (e.g., early childhood, primary, secondary, higher, or teacher), (d) country, (e) use of mobile devices/applications/programs, (f) learning content (e.g., language arts, mathematics, science, etc.), and (g) results (i.e., positive, negative, or limited).

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Fig. 3 The FRAME model (Koole 2009, p. 27) Table 1 The criteria for the inclusion in this analysis The criteria a. Must be empirical research a. Must be related to mobile learning b. Must use mobile devices or applications for the study c. Must identify student level d. Must have an educational purpose e. Must be published between January 2010 and May 2017

Of the more than 200 studies examined, 104 studies met the criteria (Appendix 1). Although findings from some studies indicating individuals’ perceptions of mobile learning offer important implications, these studies were not selected for analysis since mobile devices were not used, developed, and evaluated.

4.1

Research Purpose

According to Wingkvist and Ericsson (2011), research purposes fall into four categories: Describing, Developing, Understanding, and Evaluating. Describing illustrates “features of the portrayed environment, the technical implementation” and “actual results.” Developing defines “technical or theoretical frameworks” and

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provides “development and the presentation of solutions.” Understanding connects the results to theoretical framework providing “knowledge of a wider theoretical setting.” Evaluating assesses the effectiveness or usefulness of the research. These categories assist in classification of the early studies on mobile learning; however, they are too broad to apply to recent mobile learning studies. Only Describing the environment and technical implementation among four categories is not applied to the advanced studies conducted in recent years because this type of studies was already performed in the early years. So a refinement was made as follows: (1) Designing a mobile system/application/programs for their own research including the examination of its effectiveness; (2) Connecting theory with the result of research; (3) Evaluating the effectiveness for using mobile devices for learning; and (4) Describing how mobile learning has been implemented. The central difference between Designing and Evaluating is that evaluation investigates how much mobile devices improve individuals’ learning without creating new mobile system/application/program, while designing primarily develops an innovative mobile system/application/program and then evaluates its usefulness and effectiveness. As illustrated by Fig. 4, evaluating the effectiveness of mobile devices (43.3%) and designing a mobile system/application/program (41.3%) were the most common research purposes, followed by describing the current status of mobile learning (12.5%) and, lastly, connecting theory with the result of research (2.9%). This finding is in line with Wu et al. (2012) indicating that the most-cited research purpose is the evaluation of the effects of mobile learning, and the second was mobile learning system design. The authors concluded much of mobile learning research demonstrates new mobile learning system/application design and use in formal and informal learning environments. Since only three mobile learning studies provide a theoretical approach connecting mobile learning pedagogy with learning theories, a dearth of existing scholarship highlights the critical need for future studies.

Fig. 4 The types of research purposes in m-learning research from 2010 to 2017

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Fig. 5 The types of results in m-learning research from 2010 to 2017

4.2

Research Results

The majority of examined studies report that mobile learning generated positive outcomes (Fig. 5). For example, 75 studies (74%) showed that either student was more engaged in mobile learning activities or mobile learning improved student achievement and enhanced learning motivation. Research outcomes of 18 studies (17.3%) illustrated mobile learning had a limited impact on student learning performance. These studies indicated that mobile learning motivated students’ involvement in learning, but there was statistically no difference between mobile learning and traditional learning. For example, Engin (2015) concluded that teachers and students’ dialogic stance is more important than iPads per se for dialogic teaching. These correspond to findings by Wu et al. (2012) and other technology-assisted learning contexts in Ke (2009).

4.3

Research Methods Used in the Studies

This section illustrates the participants, countries, content areas (learning domains), mobile devices, types of research methods, and the methodological issues that emerged.

4.3.1 Participants The predominant types of participants were elementary school students (39.4%), followed by college/university students (33.7%), secondary school students (17.3%), early childhood students (4.8%), and, last, teachers (4.8%) (Fig. 6).This order suggests mobile learning studies in elementary school settings occurred because elementary students may have more interests in utilizing mobile devices (Sun and Jiang 2015) and were designed with tertiary students perhaps because the majority of these students own their own mobile devices. Furthermore, most studies explained how mobile learning influenced student learning with regard to motivation, achievement, and outcomes. There was a paucity

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Fig. 6 The types of participants selected in m-learning research from 2010 to 2017

of research on how teachers utilize mobile devices for instructional practices, how they instruct students in a mobile learning context, and how students and teachers consider the mobile learning environment. Therefore, it is important to explore the roles of teachers in a mobile learning environment in order to understand how mobile learning and teaching may promote student learning.

4.3.2 Countries The identified studies report Taiwan (23%) as the most active country participating in mobile learning research (Fig. 7). Between 2001 and 2005 (Hwang and Tsai 2011), the USA published the most articles than any country, but from 2006 to 2010, Taiwan overtook all other countries in publishing mobile learning research. This increase in Taiwan publication record may relate to an upsurge in the number of national e-learning projects. This trend continued from 2010 to 2017, suggesting that Taiwan remained the most productive country conducting mobile learning research. The results demonstrate that only a few countries dominate mobile learning research highlighting the need for a more global understanding of mobile learning. 4.3.3 Content Most of the content taught in these mobile learning studies was science (27.9%) and English as a second language (15.4%). Given that mathematics is a widely reported content area in many countries, it is surprising that mathematics was not a major focus for mobile learning research. A plausible explanation is that mathematics is viewed as difficult content area for integrating mobile devices in the learning process, especially designing effective learning applications (Fig. 8). 4.3.4 Mobile Devices Mobile/smart phones (46.1%) and tablet PCs (25%) were the primary devices used in mobile learning research followed by personal digital assistants (PDAs) (12.5%).

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* Leinonen et al. (2016) did not provide which countries were involved.

Fig. 7 Countries contributing to m-learning research from 2010 to 2017

Fig. 8 The types of subject selected for m-learning research from 2010 to 2017

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Fig. 9 The types of mobile devices used in m-learning research from 2010 to 2017

Some studies used multiple types of mobile devices (e.g., smart phones and PDAs or tablet PCs and smart phones in one study). Although some researchers applied the terms mobile phones and smart phones interchangeably, they described PDAs specifically as tools in both wireless and non-wireless environments. Some studies (12.5%) did not report the type of mobile devices used only mentioning the use of mobile devices. Some studies specifically described using iPads as their tablet device. Most studies described using tablets and did not specify the type of tablet (Fig. 9). Several studies did not emphasize the type of mobile devices used in the research, instead emphasized the study of specific mobile learning systems/application. It is clear from this study that the types of mobile devices are less important to a better understanding of specific mobile systems/applications’ effects on mobile learning.

4.3.5 Methodological Issues Based on the criteria drawn from Creswell’s (2002) classification of research design, this section presents eight research methods: narrative research, experimental research, survey research, grounded theory, case studies, phenomenological research, sequential mixed methods, and design-based research (Fig. 10). Figure 10 highlights the types of quantitative, qualitative, and mixed methods research used in these studies. Specifically, the most common methodology in mobile learning research was experimental research (56.7%). Most of the experimental research used surveys to evaluate outcomes, then sequential mix methodology (9.6%), and, last, survey and design-based research (7.7%). Researchers repeated experiments to find more in-depth results through design-based research. As research in mobile learning has expanded, there is an increase in the number of mixed methodology studies that apply a mixed methodology. Researcher employed qualitative methodologies to explore how and why students/teachers used mobile devices or learning systems/applications. Qualitative approaches such as grounded

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Fig. 10 The types of research methods in m-learning research from 2010 to 2017

theory and case study framed the methodology in 1.9% and 4.8% studies, respectively. Results reported by Wu et al. (2012) and Zawacki-Richter et al. (2009) affirm quantitative methodologies dominate mobile learning research. While experimental and survey studies may be useful for exploring the effectiveness of mobile learning and the impact of mobile learning on student learning outcomes, qualitative research may explicate how and why the daily use of mobile devices in and out of learning contexts influences student learning.

5

Future Directions

This study conducted a systematic literature review on mobile learning from 2010 to 2017 providing a comprehensive analysis of past studies and discussed the implications of new findings. The leading mobile learning research between 2010 and 2017 were short-term quantitative studies of elementary and university students’ use of mobile phones and tablet PCs equipped with mobile learning applications/systems. In summary, nine findings are reported: 1. The concept of mobile learning is closely connected with electronic learning, distance learning, and ubiquitous learning. 2. Sociocultural perspectives, activity theory, and the FRAME model can be a useful theoretical lens explaining m-learning. 3. The research purpose for most mobile learning studies focuses on valuating the effectiveness of using mobile devices, followed by designing mobile learning systems/applications. 4. Research outcomes in mobile learning studies tend to be significantly positive. 5. Elementary school students are the dominant type of participants, followed by students in higher education institutions.

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6. Researchers in Taiwan contribute the greatest number of published mobile learning articles. 7. Science and English as a second language were the content areas mostly researched. 8. Mobile phones and tablet PCs were the most commonly used devices for mobile learning research. 9. Experimental research and mixed methods are the preferred research methods. The information and technology revolution of the late twentieth and early twentyfirst century provides opportunities for learning to occur anywhere and anytime, specifically with mobile devices. The trends presented in this chapter offer researchers insights into how prevailing theoretical perspectives may explicate recent mobile learning research outcomes and propose new purposes and methodologies. Moreover, the findings signal that teachers and educators are striving to develop and implement curriculum enriched by mobile learning. Although findings from studies referenced in this chapter indicate mobile learning which can enhance students’ motivation for learning, further research should move beyond simply reporting users’ experiences and evaluating applications/programs/systems to exploring how mobile learning accelerates students’ academic success, specifically improves critical thinking (see ▶ Chaps. 77, “Augmented Reality in Education” and ▶ 79, “VR and AR for Future Education”). In this way, researchers may advance current knowledge about how to support practitioners integrate mobile devices into their daily pedagogical practices in order to boost student learning.

6

Cross-References

▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ VR and AR for Future Education

Reference Ahmed, S., and D. Parsons. 2013. Abductive science inquiry using mobile devices in the classroom. Comparative Education 63: 62–72. Charitonos, K., C. Blake, E. Scanlon, and A. Jones. 2012. Museum learning via social and mobile technologies: (How) can online interactions enhance the visitor experience? British Journal of Educational Technology 43 (5): 802–819. Cochrane, T. 2013. A summary and critique of m-learning research and practice. In Handbook of mobile learning, ed. Z.L. Berge and L.Y. Muilenburg, 25–34. New York: Routledge. Cole, M. 1996. Cultural psychology: A once and future discipline. Cambridge, MA: Harvard University Press. Creswell, J.W. 2002. Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Upper Saddle River: Pearson Education. Crompton, H. 2013a. A historical overview of m-learning: Toward learner-centered education. In Handbook of mobile learning, ed. Z.L. Berge and L.Y. Muilenburg, 3–14. New York: Routledge.

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Crompton, H. 2013b. Mobile learning: New approach, new theory. In Handbook of mobile learning, ed. Z.L. Berge and L.Y. Muilenburg, 47–57. New York: Routledge. Engeström, Y. 2001. Expansive learning at work: Towards an activity theory reconceptualisation. Journal of Education and Work 14: 133–156 Engin, M., and S. Donanci. 2015. Dialogic teaching and iPads in the EAP classroom. Comparative Education 88: 268–279. Hwang, G.-J., and C.-C. Tsai. 2011. Research trends in mobile and ubiquitous learning: A review of publications in selected journals from 2001 to 2010. British Journal of Educational Technology 42 (4): E65–E70. Hwang, G.-J., C.-H. Wu, C.R. Tseng, and I. Huang. 2011. Development of a ubiquitous learning platform based on a real-time help-seeking mechanism. British Journal of Educational Technology 42 (6): 992–1002. Ke, F. 2009. A qualitative meta-analysis of computer games as learning tools. In Handbook of research on effective electronic gaming in education, ed. R.E. Ferdig, 1–32. Hershey: Information Science Reference. Kim, P., T. Hagashi, L. Carillo, I. Gonzales, T. Makany, B. Lee, and A. Gàrate. 2011. Socioeconomic strata, mobile technology, and education: A comparative analysis. Educational Technology Research and Development 59 (4): 465–486. Koole, M.L. 2009. A model for framing mobile learning. In Mobile learning: Transforming the delivery of education & training, ed. A. Mohamed, 25–47. AU Press. Kukulska-Hulme, Agnes. 2010. Mobile learning for quality education and social inclusion. Moscow: UNESCO Institute for Information Technologies in Education. Russian Federation. Lee, H., D. Parsons, G. Kwon, J. Kim, K. Petrova, E. Jeong, and H. Ryu. 2016. Cooperation begins: Encouraging critical thinking skills through cooperative reciprocity using a mobile learning game. Comparative Education 97: 97–115. Leinonen, T., A. Keune, M. Veermans, and T. Toikkanen. 2016. Mobile apps for reflection in learning: A design research in K-12 education. British Journal of Educational Technology 47 (1): 184–202. Liaw, S.-S., M. Hatala, and H.-M. Huang. 2010. Investigating acceptance toward mobile learning to assist individual knowledge management: Based on activity theory approach. Comparative Education 54 (2): 446–454. Looi, C.-K., B. Zhang, W. Chen, P. Seow, G. Chia, et al. 2011. 1:1 mobile inquiry learning experience for primary science students: A study of learning effectiveness. Journal of Computer Assisted Learning 27 (3): 269–287. Moura, A., and A.A. Carvalho. 2013. Framework for mobile-learning integration into educational contexts. In Handbook of mobile learning, ed. Z.L. Berge and L.Y. Muilenburg, 58–69. New York: Routledge. Pachler, N., B. Bachmair, and J. Cook. 2013. A sociocultural ecological frame for mobile learning. In Handbook of mobile learning, ed. Z.L. Berge and L.Y. Muilenburg, 35–46. New York: Routledge. Reynolds, R., K. Walker, and C. Speight. 2010. Web-based museum trails on PDAs for universitylevel design students: Design and evaluation. Comparative Education 55 (3): 994–1003. Rogoff, B. 1995. Observing sociocultural activity on three planes: Participatory appropriation, guided participation, and apprenticeship. In Sociocultural studies of mind, ed. J.V. Wertsch, P. Del Rio, and A. Alvarez, 139–164. New York: Cambridge University Press. Salomon, G., and D.N. Perkins. 1998. Individual and social aspects of learning. In Review of research in education, ed. P.D. Pearson and A. Iran-Nejad, vol. 23, 1–24. Sandberg, J., M. Maris, and K. de Geus. 2011. Mobile English learning: An evidence-based study with fifth graders. Comparative Education 57 (1): 1334–1347. Shih, J.-L., H.-C. Chu, G.-J. Hwang, and Kinshuk. 2011. An investigation of attitudes of students and teachers about participating in a context-aware ubiquitous learning activity. British Journal of Educational Technology 42 (3): 373–394. Sun, Z., and Y. Jiang. 2015. How the young generation uses digital textbooks via mobile learning terminals: Measurement of elementary school students in China. British Journal of Educational Technology 46 (5): 961–964.

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Tavangarian, D., et al. 2004. Is e-learning the solution for individual learning? Electronic Journal of e-Learning 2 (2): 273–280. Ting, Y.-L. 2013. Using mobile technologies to create interwoven learning interactions: An intuitive design and its evaluation. Comparative Education 60 (1): 1–13. Traxler, J. 2009. Current state of mobile learning. In Mobile learning: Transforming the delivery of education & training, ed. A. Mohamed, 9–24. AU Press. Uden, L. 2007. Activity theory for designing mobile learning. International Journal of Mobile Learning and Organisation 1 (1):81–102. Vygotsky, L.S. 1978. Mind in society: The development of higher psychological processes (ed. M. Cole, V. John-Steiner, S. Scribner, and E. Souberman). Cambridge, MA: Harvard University Press. Windschitl, M. 2002. Framing constructivism in practice as the negotiation of dilemmas: an analysis of the conceptual, pedagogical, cultural, and political challenges facing teachers. Review of Educational Research 72 (2): 131–175. Wu, W.-H., Y.-C. Wu, C.-Y. Chen, H.-Y. Kao, C.-H. Lin, and S.-H. Huang. 2012. Review of trends from mobile learning studies: a meta-analysis. Comparative Education 59 (2): 817–827. Zawacki-Richter, O., E.M. Bäcker, and S. Vogt. 2009. Review of distance education research (2000 to 2008): Analysis of research areas, methods, and authorship patterns. International Review of Research in Open and Distance Learning 10 (6): 21–45.

P-16 Partnerships for Learning with Mobile Technologies: Design, Implement, and Evaluate

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Belinda Gimbert, Lauren Acree, Kui Xie, and Anika Ball Anthony

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The Partnership, Evaluation, Design, Implementation (PEDI) Framework . . . . . . . . . . . . . . . . 2.1 Partnership Is at the Center . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Stakeholders and External Experts Drive Collaborative Evaluation . . . . . . . . . . . . . . . . . 2.3 The Partnership, Design, Implementation, and Evaluation Are Reciprocal and Iterative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Rationale/Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Current State of M-Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Iterative Design of M-Learning by Stakeholders in P-16 Partnerships . . . . . . . . . . . . . . 3.3 Implementation of M-Learning by Stakeholders in P-16 Partnerships . . . . . . . . . . . . . . 3.4 Collaborative Evaluations by Stakeholders in P-16 Partnerships . . . . . . . . . . . . . . . . . . . . 4 Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Mobilizing National Educator Talent (mNET) Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 College Ready Ohio Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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B. Gimbert (*) · L. Acree · A. B. Anthony Department of Educational Studies, Educational Administration, The Ohio State University, Columbus, OH, USA e-mail: [email protected]; [email protected]; [email protected] K. Xie Department of Educational Studies, Learning Technologies, The Ohio State University, Columbus, OH, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_128

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Abstract

Advancements in mobile technologies hold promise for supporting teaching and learning in educational settings. Across the globe, primary and secondary schools join with higher education institutions to design and implement mobile learning experiences for P-12 students and seek external funding to support such initiatives. This chapter describes a framework for advancing and sustaining m-learning initiatives in a P-16 partnership using a collaborative evaluation approach. Three key premises fortify the Partnership, Evaluation, Design, and Implementation (PEDI) framework: (1) Partnership is the central driving force; (2) Stakeholders and external experts determine processes of collaborative evaluation; and (3) The relationship between the partnership, design, implementation, and evaluation needs to be both reciprocal and iterative. When evaluation moves beyond “a snapshot” of the initiative’s impact, stakeholders’ collective expertise and unique contributions are recognized. A partnership of higher education representatives, including faculty, researchers, instructional designers, and software developers, and school-based educators and personnel such as teachers, administrators, staff, and instructional technology coordinators should adopt collaboratively evaluation practices in order to promote the most effective use of m-learning solutions in P-12 schools.

1

Introduction

Mobile learning (m-learning) refers to the use of portable and wireless computing and communication devices to support teaching and learning (Quinn 2000). In light of rapid expansion of broadband subscriptions (International Telecommunication Union 2017; Sharples 2000; Sun and Looi 2017), m-learning nurtures a growing global appreciation for enhancing formal and informal learning experiences, enabling individuals of all ages to engage in interactive learning experiences anytime and anywhere (Fraga 2012; Hennig 2016; Johnson et al. 2013; Nordin et al. 2010; Preece et al. 2007). Increasingly, schools are adopting mobile devices such as laptops, digital tablets, netbooks, smart phones, and e-book readers to support P-12 education (Eisele-Dyrli 2011; Freeman et al. 2017; Robledo 2013). Researchers suggest m-learning assists students better understand concepts by participating in digital class discussions, offers a selection of learning modalities, facilitates interaction among participants of differing cultural backgrounds, and develops problem-solving skills (Bebell and O’Dwyer 2010; Kamarainen et al. 2013). Mobile technology also facilitates learning efficiency when students engage with content in regular short time slots (Zhang 2015). Students can use m-learning in the following ways: (1) discovery to assemble learning materials (van’t Hooft and Vahey 2007) and conduct Internet research, (2) computer-aided and computermediated instruction (e.g., tutorials and drill-and-practice applications) to reinforce basic skills and receive immediate feedback (Kirkpatrick and Cuban 1998),

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and (3) cloud computing to store and organize documents and files. Students can also use m-learning for daily planners, to access productivity software, and to communicate with teachers, parents, and classmates. While limitations, for example, costs of global accessibility and restricted size of content uploads by social media platforms, persist (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”), m-learning holds great promise for enriching teaching practice and extending teaching, learning, and classroom interactions across multiple locations by using communication networks (Baran 2014; Shuler 2009; Zhang 2015). For example, teachers can conduct formative and performance assessments while students use mobile devices to interact with real-world learning objects and historical landmarks beyond the classroom through virtual field trips (Kafai and Dede 2014) and augmented reality (Huang et al. 2016; Power et al. 2014). In the context of such experiences, teachers can encourage students to quickly access resources that connect the school to the broader community, to collaborate with others, and to engage in deep reflection, thus enhancing opportunities for teachers to encourage students’ social interaction and collaborative knowledge construction (Baran 2014). In light of increased affordability and accessibility of m-learning devices, P-12 administrators can allocate funds to purchase instructional resources that provide students with a familiar tool for reinforcing difficult learning concepts, as well as a mechanism to collaborate with teachers and peers, outside regular school hours (van’t Hooft and Vahey 2007). Further, m-learning can be used to record students’ interactions and responses which can be collected and analyzed by teachers and administrators through a desktop computer or mobile device to assess students’ learning outcomes. M-learning can also be used as a tool for teacher observation and evaluation, embedding evaluation rubrics, so data can be collected during classroom walkthroughs, maintained in a secure environment, and archived for subsequent analysis. An example includes the Pivot 5D+ application that was developed by the Center for Educational Leadership at the University of Washington and the Michigan Association of Secondary School Principals (Five-Start Technology Solutions 2014). Researchers advocate partnerships between higher education and P-12 schools, referred to as a P-16 partnership, as an effective strategy to address challenges in the ever-changing m-learning landscape (Anthony and Gimbert 2015; Dexter 2008; Leahy et al. 2016). A “smart partnership” is a relatively new term relating emergent technologies with education (Leahy et al. 2016). “Smart” implies “innovative and transformative changes driven by new technologies” designed to continuously improve “datadriven decisions, technology-enabled data sharing, communications and collaborations” (Leahy et al. 2016, p. 84). A “smart” partnership heralds powerful possibilities to advance P-12 student learning when professional growth opportunities intentionally align around a common goal of shifting educators’ mobile learning attitudes and growing their skills (Smolin and Lawless 2011; Winslow et al. 2016). Synergy between schools and universities/colleges can meet institutional needs to develop human capital in both contexts and positively influences students’ learning. Winslow et al. (2016) emphasize the potential for a reciprocal relationship between school districts and university partners. These researchers claim:

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Schools need expertise on how to implement technology-centric initiatives like blended learning, online learning, mobile learning, personalized learning, as well as strategic guidance on using Big Data to maximize student achievement with emerging learning analytics platforms. Universities will always seek school context to add authenticity and currency to their instructional technology curricula and services. In the evolving world of online learning where previous proprietary and territorial practices are obsolesced in favor of free-market consumerism, university-school partnerships have never been more important. School districts can shop for university partners to help them “do more with less.” Instructional technology programs must therefore recognize that in this new flattened competitive theatre, the links between university services and school district success are tenuous and replaceable without cultivated partnerships that demonstrate mutual value. (p. 60)

In addition to helping P-12 schools design m-learning applications, higher education partners can also contribute to efforts in P-12 schools to make design adjustments that facilitate adoption and adaptation for improvements in classroom instruction. Through working with P-12 educators, higher education partners can build on the expertise of these individuals to design and implement robust solutions to support teaching and learning. Higher education faculty and research centers are positioned to assist P-12 schools with securing funding for m-learning and can contribute to the m-learning knowledge-based and long-term adaptation through P-12 partnerships (see ▶ Chap. 49, “1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation”). Anthony and Gimbert (2015) present a conceptual framework that universities/colleges and P-12 educators can use to inform m-learning design and implementation through a shared decision-making model. Partners’ inputs may be explicitly evident in the design and implementation processes. However, the various ways in which a P-16 partnership contributes to the evaluation of an m-learning initiative are often overlooked (Intel Corporation 2013; Winslow et al. 2016). A gap in the existing literature warrants examining how stakeholders shape the design, implementation, and evaluation processes, thereby influencing both the success and sustainability of a technology partnership. This chapter proposes a collaborative evaluation approach described as the Partnership, Evaluation, Design, and Implementation (PEDI) framework for m-learning initiatives. This framework has three core premises: 1. Partnership is at the center. 2. Stakeholders with external experts drive collaborative evaluation. 3. The relationship between the partnership, design, implementation, and evaluation is reciprocal and iterative. A shift in perspective of evaluation influenced by a P-16 Partnership can shape technology-supported educational reforms for enhancing educators’ skills with mobile learning devices. Key concepts and practices illustrate the benefits, as well as challenges, of a collaborative approach in program evaluation framed by the partnership. In this chapter, we detail the PEDI with illustrative examples that provide readers with examples for future partnerships in m-learning.

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The Partnership, Evaluation, Design, Implementation (PEDI) Framework

The PEDI framework provides intra-linkages illustrating how stakeholders committed to a “smart” partnership (Charania and Davis 2016; Leahy et al. 2016) can organize and leverage collective efforts to evaluate, design, and implement m-learning programs in schools. Partners’ expertise can be harnessed and organizational resources maximized to sustain the impact of technology-enriched experiences for P-12 educators and students. The following subsections explain the three premises of this framework.

2.1

Partnership Is at the Center

Critical to this framework is the partnership between school district, school administration, teachers, university personnel, and external evaluators. Falloon (2015) describes an educational partnership as “a mutually satisfying relationship, which typically involves the free exchange of knowledge and ideas to the benefit of [all] parties” (p. 216). To advance this relationship, an economic state, explained as “Pareto efficiency” or “Pareto optimality,” requires efficient allocation of partnership resources in order to generate maximum satisfaction for all parties (Berthonnet and Delclite 2015). The partnership establishes with clear, agreed-upon goals that inform the evaluation, design, and implementation plan for the program. This could be through a series of informal or formal meetings or perhaps the formation of a memorandum of understanding. Within a “smart” partnership, stakeholders can apply data analytics using mobile technology to improve learning experiences for individual students (Clow 2013; Leahy et al. 2016) and provide timely evaluation feedback for corrections to enhance an intervention. While “smartness” can enhance partners’ decisions and actions and/or interventions by engaging “technology, communication, and communities” (Leahy et al. 2016, p. 85), it demands collaboration among its stakeholders. More importantly, when stakeholders exert collective expertise and propagate innovative ideas at differing decision-making levels within a partnership, a lasting impact of real-time mobile learning technologies to sustain the partnership becomes plausible. In their synthesis of previous researchers’ description of the characteristics of a “smart” partnership (Charania and Davis 2016), Leahy et al. (2016) claim partners should exhibit at least most of the following characteristics and behaviors: 1. Be multiple and diverse within and across educational institutions (educators, administrators, university personnel, researchers), government (e.g., local school district or county board of education, state department of education, US Department of Education, other federal government departments), business (e.g., ICT companies), communities (e.g., local not-for-profit and for-profit

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organizations), and nongovernmental organizations (e.g., nonprofit educational groups, NGOs). Own a common purpose including beliefs, ideas, and vision. Implement SMART goal(s) that are strategic, measureable, attainable, realistic, and timely. Recognize the work materializes, and at times is messy and necessarily fluid Advocate for change.

2.2

Stakeholders and External Experts Drive Collaborative Evaluation

After the partnership and its outcomes are established, stakeholders should collaboratively design a summative evaluation to assess the extent to which the program effectively attains preset goals (Campilan 2000; Kusunoki and Sarcevic 2013). Reversing from the goals and evaluation measures, the team should continue to collaboratively design the program, implement it, and devise formative processes to assess established benchmarks (Intel Corporation 2013). As the program moves from design to implementation, it is important to collect data continuously to inform changes to the program. When new needs emerge during the implementation phase, the team should be willing to revisit the summative evaluation to ensure it is serving the goals and needs of the program as a whole (Smolin and Lawless 2011).

2.3

The Partnership, Design, Implementation, and Evaluation Are Reciprocal and Iterative

Important to this framework is the dynamic nature of each part. While the goals and partnership direct the program’s evaluation, design, and implementation, the needs emerging from the latter should inform the partners’ decisions. Similarly, although planning the summative evaluation precedes and informs the program’s design and implementation, as needs change and new needs emerge, adjusting the summative evaluation becomes critically important. Within a mature P-16 partnership, each stakeholder’s perspective influences the degree to which a collaborative evaluation approach can iteratively shape the design and implementation of an m-learning initiative (Campilan 2000; Kusunoki and Sarcevic 2013). When evaluation moves beyond “a snapshot” of the initiative’s impact, partners’ collective expertise fully utilizes and overtly recognizes participants’ unique contributions. As this process unfolds, local knowledge analyzes, restructures, and recommends the dynamics of design and implementation activities (Campilan 2000; Smolin and Lawless 2011). Stakeholders can then better manage pressure from accountability, especially when resources are scarce

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(Intel Corporation 2013). Rather than predetermined by indicators often favored by a structured, often inflexible traditional evaluation method (Intel Corporation), classroom contexts and relationships among stakeholders are accommodated. “Insiders” conduct short-cycle iterative assessments and generate formative feedback for immediate, corrective actions of design and implementation activities. Such adjustments are necessary for enhancing end-of-project outcomes and other relevant program dimensions. In response, stakeholders can reflect on their own experiences and learn from the partnership’s efforts in order to capacitate educators to use mobile learning as a pedagogical practice to advance P-12 students’ academic success. In summary, stakeholders’ perception of partnership’s activities (Campilan 2000) and their interactions with each other anchor a collaborative evaluation framework for the design and implementation of a mobile learning project (Fig. 1).

Fig. 1 The PEDI framework

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Rationale/Background

3.1

Current State of M-Learning

The application of m-learning continuously reinvents itself, generating conceptual and logistical challenges to support P-12 students’ relevant learning opportunities and teachers’ instructional practices (Winslow et al. 2016). Challenges include difficulty with defining learning goals, aligning possibilities for novel teaching and learning approaches with traditional expectations for how schools function (Johnson et al. 2013), and ensuring adequate financial, professional development, and social support (Ng and Nicholas 2013). Although research concerning m-learning design, implementation, and effectiveness in P-12 education is still emerging (Manzo 2010), the aforementioned challenges are rooted in historical barriers associated with integrating information and communication technologies in P-12 schools (Cohen 1987; Cuban 1986; Cuban et al. 2001; Peng et al. 2009). Features such as ubiquity and flexibility (Cuban 1986) help address some of the challenges of m-learning implementation; however, in many settings, m-learning has not had a substantial impact on teaching and learning (Johnson et al. 2013) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). In response, m-learning is particularly ripe for nurturing P-16 partnership for at least two reasons. First, research shows that effective technology use and integration is highly context specific. The resources, culture, and leadership in a school shape the degree to which mobile devices are integrated effectively (Ertmer and Ottenbreit-Leftwich 2010; Groff and Mouza 2008). Ertmer and OttenbreitLeftwich (2010) report “technology innovation was less likely to be adopted if it deviates too greatly from the existing values, beliefs, and practices of the teachers and administrators in the school” (p. 264). Second, there are many types of barriers teachers face when adopting m-learning. Ertmer (1999) refers to these as first- and second-order barriers. First-order barriers are issues outside of a teacher’s control such as access to devices, insufficient bandwidth, or lack of training related to how to use the device (see technical barriers in ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Second-order barriers relate to internal issues a teacher might have related to his or her beliefs about the role of technology, the structure of teaching and learning, or the teacher’s openness to change (see ▶ Chap. 49, “1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation”). Knowing more about the specific challenge teachers are facing through, a collaborative evaluation in a P-16 partnership would enable school and district leaders to better address these needs.

3.2

Iterative Design of M-Learning by Stakeholders in P-16 Partnerships

Drawing on literature in instructional systems design and development (Morrison et al. 2007), faculty, researchers, and others in higher education settings can work

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with P-12 partners to design and develop m-learning applications for use in P-12 schools. Applications consider (1) end users and relevant content and level (e.g., administrators, teachers, students, early literacy, elementary mathematics, or secondary biology), (2) functionality to embed in a design (e.g., text-to-speech, speech recognition, hypertext, system assessment and feedback, and user control and customization), and (3) interface design (e.g., screen size and real estate, programming events to occur on touch or tap, tilt functionality, visual cues to indicate when a user can manipulate objects and icon placement). Higher education and P-12 partners can jointly form a design team, analyze needs m-learning addresses, design and develop applications, and conduct user testing and evaluation. In the context of a P-16 partnership, project managers, instructional designers, and researchers may have experience working in higher education settings. IT developers may work in higher education or may be industry partners. The P-12 side of the partnership should include representatives such as administrators, educational technologists, other education specialists, teachers, and students. Throughout the design process, P-12 education specialists can serve as subject matter experts, offering details on what is known about child development and learning processes, as well as teaching processes and instructional resources that can help support targeted learning outcomes. Education specialists, along with a sample of end users (e.g., teachers and students), can offer insights into issues encountered in actual teaching and learning environments. Education specialists, teachers, and students can also provide detailed information on the specific goal or need that the m-learning solution should address. Instructional designers and developers can then draw on such information to suggest instructional strategies, instructional messages, and technological functionality intended to address teaching and learning needs. Although it is important that teachers are included in the design process, the design team’s view toward teachers’ work and how the team envisages teachers’ future technology use has implications for the ways in which teachers are invited to participate as members of the design team. From insights related to sociology (Howard and Schneider 1984) and innovation research (von Hippel 2005), when the goal of m-learning replaces aspects of teacher practices and offers teachers little or no choice about practices will be automated, the design team holds a “technocentric” view toward instructional technology, meaning interests of making the research project efficient and technologically novel are a priority. Under such a view, teachers’ participation is potentially disruptive to the goals of the design team, and thus teacher participation should be minimal. However, when the design team holds an “organization-centered” view in which the goal of the m-learning uses technology to support teachers enhance practice, teachers are active agents in determining how technology integrates into their practice. Teachers’ participation in the design process is welcomed and vitally important for increasing teachers’ commitment to adoption because they have deep knowledge about their professional practice and are able to determine how best, and under which conditions, to use m-learning.

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Implementation of M-Learning by Stakeholders in P-16 Partnerships

Higher education faculty, P-12 administrators, practicing teachers, educational technologists, and education specialists solicit input on how new technologies may support their existing practices and how new goals for student learning, teaching practice, school policies, and structures for teaching and learning may be aligned in the context of m-learning initiatives in order to fully implement and sustain new technologies and practices. Higher education partners seeking to develop m-learning solutions for use in P-12 schools must understand factors impeding and/or supporting m-learning implementation, especially when effectiveness in the field is expected. It is important to distinguish between implementation of a technology program and effective integration of technology. Implementation refers to the degree to which a system executes its vision and plan for technology at the desired scale. Integration, on the other hand, refers to how teachers use that technology to support curricular and pedagogical goals in the classroom. When technological tools seamlessly connect teaching and learning activities, m-learning experiences shift from “add-on” or peripheral activities. To illustrate this distinction, consider a district that creates a technology program. After 2 years, they find that only 5% of teachers are using technology to support all aspects of teaching and learning. These few teachers have fully integrated technology into their classrooms, but the program has not successfully implemented district-wide. This chapter focuses on the success of implementation of m-learning programs where a critical mass of teachers and students regularly and effectively use mobile devices to improve and support teaching and learning. Many factors affect success of implementation. Clarity of vision, ownership, and roles (Sun et al. 2000); systems for continuous improvement (Demouy et al. 2015; Yasemin 2007); and distributed or shared leadership in the technology initiative (Dexter 2008; Printy et al. 2009) all contribute to the success of implementation of a technology program. However, important to note is the importance of the alignment between the vision and plan for technology at the district level and teacher practice. If the resources do not align to support teachers’ needs, it is unlikely that teachers fully or successfully integrate technology in their classrooms resulting in failed implementation of the program (Anthony 2012). Prepared with an understanding of contextual nuances and circumstances, higher education partners can support P-12 schools in addressing implementation barriers and developing conditions for sustainability. Some of the implementation supports specific to m-learning include the increased receptiveness of P-12 educators to online and hybrid learning, their increased use social media to connect with families and community members, increased access to open resources and cloud computing, and the decreased cost of technological devices (Johnson et al. 2013). According to Ng and Nicholas (2013), specific components sustain m-learning in P-12 education: (a) fiscal capability of the school with multiple channels of funding; (b) involvement of parents, political leaders, and business partners; (c) leadership and institutional policies for political sustainability; (d) decisions about which technologies serve

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institutional needs and goals over time; and (e) alignment between m-learning, teaching and learning practices, and peer collegiality for pedagogical sustainability. A shared decision-making model enables P-16 partners to discuss plans and improvements for m-learning design and implementation (Anthony 2012; Anthony and Gimbert 2015; Anthony and Patravanich 2014). Building on the work of Vroom and colleagues (Vroom and Jago 1998; Vroom and Yetton 1973), P-12 administrators or educational technologists alone do not have adequate knowledge to define content- or grade-specific teaching and learning problems, nor do they have sufficient knowledge or expertise to define solutions and chart out a course of action that teachers must then implement using m-learning. Because the use of m-learning to support education is a “group problem” that has the potential to affect multiple people (teachers, students, parents, educational technologists, administrators, other support staff), a shared decision-making model is ideal. Using such a model, team members share problems, generate alternatives, and devise solutions.

3.4

Collaborative Evaluations by Stakeholders in P-16 Partnerships

Conventionally, evaluation design holds program leaders accountable to attain objectives and meet the information needs of those who make decisions about the program’s future, including program directors, policy-makers, and officials from funding organizations (Intel Corporation 2013; Smolin and Lawless 2011). Evaluation can provide educational researchers with feedback to improve strategies for ensuring the adoption of mobile learning tools in P-12 classrooms, as well as inform program management decisions related to fiscal and personnel oversight. Typically, evaluators are people external to the program, objectives are preset, data collection instruments are based on predetermined criteria, and educators are viewed as “clients” and respondents. Accountability and transparency drive traditional approaches to evaluation. External experts collect, analyze, and use information to assess evidence for policy-makers, funders, and developers to determine whether a program has met its proposed objectives. However, given all stakeholders – program designers, advocates funders, and participants – want to know about the impact of the initiative, then a collaborative approach may recognize program beneficiaries as “contributors” to the evaluation process rather than only potential “users” of evaluation results (Kusunoki and Sarcevic 2013). Collaborative approaches such as “self-assessment, stakeholder evaluation, internal evaluations and joint evaluations” (Campilan 2000, p. 40) can support program learning and innovation” (p. 40). Key questions driving a collaborative approach to evaluation include the following: (1) For which stakeholder(s) is the evaluation process being conducted? (2) What can each stakeholder expect to learn from an evaluation? (3) What do the evaluation processes “sound and look like” from each stakeholders’ perspective? (4) What is the expected contribution of each stakeholder in the evaluation process/es? and (5) What is being evaluated? (Youth Policy Institute 2016).

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Inherent in a partnership’s success are challenges for how contextually appropriate evaluation processes apply to iteratively shape an initiative’s design and implementation activities. Hurdles may surface such as (1) matching stakeholders’ needs with prioritized issues requires formative evaluation with feedback loops for timesensitive corrective action, (2) involving different stakeholders in the scope of work generates additional complexity, and (3) requiring mutual agreement among users whose diverse perspectives drive and inform how, why, and when the project’s activities unfold. However, partners’ actions such as the following may counter impediments: (1) ensure technology initiative is on track to achieve its goals; (2) strive to improve the quality of both the short- and long-term outcomes of the project’s activities by sustaining more effective learning environments for all stakeholders; (3) generate stronger and longer-lasting learning effects for individual participants from deeper awareness through engagement and reflection; (4) intensify stakeholder relationships through shared responsibility of the project’s scope of work, and collegiality strengthen through struggle to impact P-12 students’ learning; and (5) enhance educators’ capacities to adopt and adapt mobile learning tools and assess attributions to their teaching and classroom practices (Anthony and Gimbert 2015; Intel Corporation 2013; Smolin and Lawless 2011). When collaborative evaluation forms the backbone for educators’ collective efforts to design and implement a mobile learning initiative in a partnership, program leaders and stakeholders (1) know what needs to be in place for the success of the initiative across “phases for the visioning, design, implementation and re-informing vision of the initiative” (Intel Corporation 2013, p. 3), (2) use formative evidence from short- and medium-term implementation indicators for continuous improvement through course corrections and provide opportunities for those stakeholders doing the core project activities to take responsibility for solving problems that arise, (3) initialize efforts to scale-up to broaden the initiative’s adaption and impact, and (4) reassess goals and reorganize the partnership’s structure in line with new contingencies to show progress or success of the initiative (Intel Corporation 2013). Shifting a partnership’s evaluation, design, and implementation activities from a lockstep procedural, time-bound operation to link reiteratively with feedback loops fosters benefits: (1) stakeholders offer holistic and realistic perspectives of the program and realize ownership which leads to greater buy-in and commitment to the project’s work – participants’ voices resonate; (2) validity of the results identified as “in action” benchmarks and “end-of-project” outcomes become more trustworthy and credible since data is mined from multiple sources and perspective; (3) assessment is considered ethical since the corrective actions are supportive by those directly affected by the measures. Stakeholders jointly develop indicators and measures, and program processes and outcomes receive equal evaluation attention when collaborative evaluation processes unfold (Falloon 2015; Smolin and Lawless 2011; Sun et al. 2000). As links between evaluation, design, and implementation become flexible and durable, stakeholders’ efforts to sustain the partnership’s technological innovations that nourish participants’ skills drive key outcomes. Core processes of a

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mobile learning partnership include (1) conducting a needs assessment of the partnership/operational context of the learners/participants, (2) adopting a flattened organizational structure supports flexible governance structure, (3) strategically designed elements to support the partnership engagement, (4) formative and iterative implementation processes, and (5) strategic summative evaluation of the partnership outcomes. Critical design points crafted over time allow for emergent evaluation criteria to guide and refine a productive partnership. Shared, symbiotic, and mutual benefits are the cornerstone of a healthy partnership. Key features of a partnership framework for evaluation, design, and implementation (PEDI) include: 1. Recognizes insiders’ (local educators, project staff, partner key personnel, and collaborating groups) and outsiders’ (external experts) contributions to both project processes and outcomes 2. Transpires in the practitioners’ arena and may be situation specific 3. Responds to contextual requirements 4. Iteratively generates collective outcomes driven by participants’ needs and insiders’ expertise 5. Provides multiple sources of innovation such that solutions to the problem may come from local knowledge and resources 6. Seeks to develop the capacity of stakeholders in systematic inquiry and action to enhance individual and organizational performance which in turns impacts the end-of-project outcomes 7. Acknowledges other internal and external environmental factors (social, political, physical) may confound efforts to develop capacity 8. “Considers innovation as a continuous learning process” (Campilan 2000, p. 47) and harnesses technology as a tool for innovating, not an innovation in of itself 9. “Views technology adoption, adaptation, integration, and rejection” (Campilan 2000, p. 47), rather than defining “adoption as the key criterion for assessing technological change” (Campilan 2000, p. 47) A team comprised of higher education faculty, staff, and researchers and school district personnel can serve an integral role in the design process by working closely with all partnership stakeholders to collect and analyze needs analysis data and to evaluate the usability and effectiveness of the m-learning solution. Drawing on evaluation findings, stakeholders can then work together to iteratively improve the functionality, usability, and content of the m-learning solution (Cobb et al. 2003). Design team members should expect adjustments to preliminary designs based on evaluation findings. For example, tweaks become necessary when the m-learning application for end-user customization to support teaching and learning results in too flexible customization options, thereby threatening fidelity of implementation across practice settings. In addition to using evaluation findings to improve the m-learning solution, a P-16 partnership’s researchers can disseminate findings to a wider audience to contribute to the growing m-learning research literature and to inform subsequent m-learning efforts.

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Case Studies

In order to illustrate the PEDI framework in action, this chapter presents two case studies of m-learning initiatives. Mobilizing National Educator Talent (mNET) addresses teacher pipeline issues by leveraging mobile technology. It leveraged a variety of partners to address a multifaceted problem nationwide. College Ready Ohio (CRO) involved partners at many levels of the education system in order to support schools as they built one-to-one computing programs designed to prepare students for college and career. Both of these programs leveraged the partnerships and relationships effectively, used data to inform the program, and enacted the PEDI framework to ensure program success.

4.1

Mobilizing National Educator Talent (mNET) Case Study

4.1.1 Context of the Case Study Well-prepared, technology-literate teachers are key to improved student learning in our schools. However, such teachers are often in short supply for students who need them the most. According to the National Comprehensive Center for Teacher Quality (2009), low-income and minority students in at-risk and hardto-staff schools consistently have teachers with little experience or marginal qualifications. This is particularly troubling given recent projections of teacher shortages over the next 5–10 years and beyond. Mobilizing National Educator Talent (mNET) is an interstate consortium of institutions higher education, nonprofit organizations, and P-12 school districts. It is designed to assist highneed local educational agencies (LEAs) which develop, enhance, or expand innovative programs to recruit, train, and retain technology-literate teachers for core content areas, particularly STEM fields (science, technology, engineering, and mathematics). Given mNET’s overarching goal of accelerating student academic success by mobilizing 1,565 talented new educators across the nation who demonstrate best practices in science, technology, engineering, and mathematics (STEM)-related pedagogy, three strands ground the stakeholders’ collective endeavor to advance m-learning: • Strategic Strand 1: Design and implement a virtual learning environment (VLE). By incorporating cloud technologies, mNET provided participants (teachers and school leaders) with open educational resources (OERs), including applications for mobile technology that offer e-content modules and e-coaching anywhere, anytime on any technology platform. • Strategic Strand 2: Expand e-learning approaches using cloud technologies to share interactive pedagogical practices between and among school leaders and classroom teachers. • Strategic Strand 3: Prioritize and implement strategies to recruit and support classroom teachers for underrepresented populations and offer e-STEM equity

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professional development using digital, open educational resources (OERs) that mitigate the identified barriers and institute systems and activities that remove the barriers. The key features of mNET are: • A virtual learning environment. An online asynchronous learning management system (LMS) uses a Moodlerooms environment and features research-based e-modules that are self-paced and cover a wide range of content areas, as well as principles of learning and teaching and effective pedagogical techniques. Selfassessment and testing components are included in each e-module to enhance each partner’s ability to prepare teachers to meet state certification and/or licensure requirements. • Online e-coaching and support for new teachers. mNET offers e-coaching sessions with expert teachers who provide targeted content and e-pedagogical supports for beginning teachers. Resources include a classroom support series that features research and advice on a wide range of topics and a teacher hotline where teachers can request guidance specific to a situation. • Online school leadership training and support. mNET offers a suite of mobilefriendly/online system of leadership-oriented resources, trainings, and targeted supports that help administrative staff in partner schools and districts to better support and prepare their novice teachers. Diverse partners contribute to mNET’s scope of work including 9 colleges/universities with education, mathematics and science, and engineering programs; 8 state departments of education; 157 school districts (known as local educational agencies); and 5 nonprofit educational partners. Each participating state meets the definition of high-need, and each public school district and charter school lists as high-need, hard-to-staff. Figure 2 lists partners and role in the program design, implementation, and evaluation. The mNET program is an ideal example of the PEDI framework in action as described below.

4.1.2 Partnership Is at the Center Key to the mNET project is the organization of the partners that guides the program. An organizational systems approach addresses the local staffing needs of its partners within and across 12 states (KS, NV, OH, TX, CO, LA, MS, NY, NC, OK, SC, and VA), one (1) territory (Puerto Rico), and the District of Columbia. High-need LEAs typically encounter a number of barriers to recruiting, selecting, and retaining highquality teachers. mNET partners assist school district personnel in overcoming these barriers to retain teachers and school leaders who were qualified to address how to improve student academic achievement and other school challenges. At monthly online meetings, mNET partners target needs, mutually agree to a set of collaborative evaluation strategies, and then design and implement through multiple iteration cycles new web 3.0 activities using cloud technologies to support

778 Design U.S, Department of Education and the Center on Education and Training for Employment, College of Education and Human Ecology (OSU)

B. Gimbert et al. Implementation The Ohio State University Partnering School Districts - 9 colleges/universities with Education, Mathematics and Science, and Engineering programs - 8 State Departments of Education - 157 school districts (known as local educational agencies) in Kansas, Nevada, Ohio, Texas, Colorado, Louisiana, Mississippi, New York, North Carolina, Oklahoma, South Carolina, Puerto Rico, Virginia, and Washington D.C. - 5 nonprofit educational partners – Educational Solutions LLC (VA) , National Association for State Directors of Special Education (VA), Association of Teacher Educators (VA), Thomas B. Fordham Institute (OH), and Youth Policy Institute (NY)

Evaluation Site-based stakeholders, Youth Policy Institute, and the Center on Education and Training for Employment, College of Education and Human Ecology (OSU)

Fig. 2 mNET partners

specific capacity-building strategies for the recruitment, preparation, placement, and retention of classroom teachers. Over the course of the project, partners have designed and tested, redesigned, and implemented (a) an online learning environment with research-based e-modules covering a wide range of content areas and accessible 24/7 by any computer and/or mobile device and (b) a system of online mobile-friendly e-coaching with targeted content and pedagogical supports for teachers.

4.1.3

Stakeholders with External Experts Drive Collaborative Evaluation As the conceptual framework illustrates, a system-based, collaborative evaluation model frames the design and implementation of this m-learning initiative. Teams of external experts, the YPI evaluators, and stakeholders are collectively responsible for identifying the factors and processes that most influence how and when core project objectives. Stakeholders determine core summative evaluation questions. These include the following: 1. Participating in the mNET partnership resulted in what changes in school policies and procedures, organizational structures, and resource allocation to support implementation? 2. What changes occur in teacher understanding and use with fidelity research-based mobile-friendly instructional practices? 3. Do PD/coaching staff present certain instructional strategies more effectively and with greater fidelity than others? Do implementation levels vary by school/ classroom/grade?

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Components of the Conceptual Design of mNET Evaluation

STATE, REGIONAL, & SCHOOL CONTEXTS State, District, and School Demographics State Certification Policies State and Local Professional Development Technical Assistance Systems Partnerships & Collaborative Agreements

INPUTS & RESOURCES

OPERATIONAL PRACTICES

IMPACTS

Online Learning Community

Project Governance

% of participants becoming teachers in high need schools

e-Coaching & Mentoring

Communications & Networking amoung Project Stakeholders

% of participants licensed within 3 years

Virtual Learning Environment (e-Modules) mNET online resources Implementation of Best Practices

Continuous PD & technical assistance for mNET partners & participants

% retained as teachers for 3 years in high need schools Improvement in TPACK Technological, Pedagogical and Content Knowledge

Local Hiring & Retention Practices

Fig. 3 Logic model for evaluation

4. To what extent are program effects among students (ELP, academic achievement, and behavior) comparable? To what extent are gains consistent across grade levels and demographic backgrounds (e.g., race/ethnicity, gender, and SES)? 5. Do the benefits of the mNET initiative accrue with increasing student exposure to the program? Do the benefits of mNET accrue with increasing teacher experience? 6. How do variations in implementation affect student outcomes? How do school contextual factors affect program implementation and student outcomes? The following logic model (see Fig. 3) and agreed-upon goals inform the collaborative evaluation approach. Formative evaluation provides objective and systematic data to stakeholders on project design and implementation, focusing on scope, quality, utility, and fidelity to proven strategies and practices. Formative assessment offers stakeholders timely feedback on each aspect of the evaluation, including the achievement of project milestones, short- and long-term formative measures, problems/solutions, and forecasts. The progress reports describe early (and ongoing) design and implementation results focusing on teaching development recruitment and rollout of effective PD and coaching services. mNET’s formative evaluation was guided by the critical process questions such as the following that were formed by consensus among the stakeholders: (1) Does mNET have the organizational structure, qualified staff, and

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detailed rollout plan with delineated responsibilities to effectively implement project activities? What problems are encountered during project development/refinement? How are they resolved? (2) Are project resources, services, and activities reaching the intended target audiences? (3) What factors are promoting or impeding quality implementation with fidelity? (4) How do classroom teachers, PD and coaching staff, instructional specialists, and administrators assess the quality and quantity of mNET services/activities and the project overall? Findings from the formative and summative phases of the evaluation are shared with each stakeholder, administrators and teachers, and project staff through a variety of communication channels including periodic meetings/briefings, annual evaluation reports, and a final evaluation report. The final report provides a comprehensive analysis of the expansion initiative, addressing all evaluation questions, including recommendations for future planning and decision-making.

4.1.4

The Relationship Between the Partnership’s Evaluation, Design, and Implementation Is Reciprocal and Iterative mNET partners iteratively evaluate, design, and implement new web 3.0 activities by expanding innovations and sharing solutions, strategic practices, and technology integrations. Partners use cloud technologies to support specific capacity-building strategies for the recruitment, preparation, placement, and retention of technologyproficient classroom teachers. The partnership’s collective expertise boosts mNET’s reputation for high-quality teacher preparation. In addition to supports by schoolbased partners, novice teachers are offered a range of mobile-friendly professional development opportunities designed to assist them integrate m-learning into their daily classroom practices. A variety of expansions and updates to the LMS provide digital content courses and mobile-friendly/online coaching across content areas. This includes modifications to content courses to update materials, to use branched technology to facilitate content mastery, and to make the majority of content resources mobile accessible. In addition, four new online content courses in education equity and STEM are available for teachers, and a spectrum of resources delivered to school leaders. A review of LMS use among all four cohorts over the past 4 years indicates that the percent of first-year teachers who accessed mobile-friendly content courses and online coaching at least once during the year was relatively constant over time. Moreover, after their first year of teaching, and even post-certification, a substantial number of teachers continue to access the LMS at least once a year. Each successive cohort of new teachers has rated the content courses more helpful, a reflection on mNET’s commitment to improvements and updates. Growth in ToR Instructional and Technology Skills: Teachers report their pedagogical skills increasingly benefited from their use of mobile-friendly, digital resources. At the end of their first year as teachers, 52% teachers describe an increase in their capacity to use technology to enhance instruction, compared to 64% of the second group of teachers, 66% of the third group, and 72% of final group. In addition, teachers in the final group report 70–82% growth in their preparedness to implement planning and instructional strategies using m-learning. An analysis of

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mean self-assessment scores across multiple pedagogical domains shows substantial growth over time for all teachers and an acceleration of the rapidity of this growth with each cohort. In addition, 40% of teachers reported that their content knowledge and pedagogical skills improved by over 20% from their first to third year of teaching. Access to mobile-friendly, digital resources is clearly associated with improved teaching skills. An increasing percentage of teachers each year report that use of these resources improved their understanding of instructional technology and content and pedagogical knowledge and helped them pass their licensure exams (both pedagogical and content). An analysis of change in skills over time indicates far greater growth in the pedagogical skills of teachers who made use of mobilefriendly, digital content courses and online coaching compared to those who did not use these resources, for both the first year and second year of teaching.

4.2

College Ready Ohio Case Study

4.2.1 Context of the Case Study The College Ready Ohio (CRO) project is a long-term large-scale K-12 technology integration project funded by the Straight A innovation grant program from the Ohio Department of Education. CRO aims to expand high school student college readiness via m-learning, open digital resources, and College Credit Plus opportunities through the creation of a statewide service model. College Ready Ohio provides 2-year-long professional development, mobile learning technology, and digital course materials to high school teachers that drive significantly more digital resources to classrooms to enhance student achievement and reduce operating costs. CRO works in high schools across ten districts and leverages a modified train-thetrainer model. Initially, partner schools identified two catalyst teachers per school who received high-quality professional development around mobile learning that they shared with colleagues in their “home-school.” By leveraging high-impact teachers, the program supported the learning of more than 10,000 students across the state of Ohio. There are four main components to CRO: 1. Professional development for technology integration: CRO provides highquality professional development through three different education service centers to one catalyst teacher per school. Schools identify catalyst teachers in a variety of ways and may have included principal identification, teacher volunteers, or an application process. 2. Technology enhancement: Schools were able to purchase mobile technology and digital materials as part of the CRO program. Many participating schools use the funds to start one-to-one computing programs that provide every student with a device. 3. Leadership development: Principals and district leaders participated in the “Leadership in a Digital Age Institute” at the start of the program and received

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ongoing support as they shifted school and district structures to support mobile learning in their schools. 4. Course development: Students complete college credit plus courses online from Ohio’s flagship university as part of CRO. In these courses, students receive mentoring from content experts at their schools, as well as web-based support from teachers across Ohio. CRO has five program goals: 1. Foster catalyst teachers’ knowledge and skills to lead digital-enhanced teaching and learning. 2. Ensure diffusion of innovation proposed by the project by scaling up the CRO models in the schools and districts. 3. Build leadership support from school principals, superintendents, and district key persons. 4. Ensure the effectiveness and efficiency of the digital-enhanced College Credit/ College Credit Plus programs that are able to continue and grow. 5. Ensure students leave an Ohio high school with enough knowledge and skills to succeed in college. These goals reflect the general vision and requirements of the Straight A program in the Ohio Department of Education.

4.2.2 Partnership Is at the Center The defining feature of CRO project is the collection of critical partners who each bring an important element to the program (see Fig. 4). The partnership lead is the Educational Service Center of Central Ohio (ESCCO) with the following partners: Design Office of Distance Education and eLearning (OSU)

Implementation Service Centers: ESCCO, GCESC, and OSLN Partnering Schools: - Berkshire High School; Berkshire Local Schools - Bio-Med Science Academy; Bio-Med Science Academy - Cardinal High School; Cardinal Local Schools - Dublin Coffman High School; Dublin City Schools - Global Impact STEM academy; Global Impact STEM academy - Innovative Learning Center; Hilliard City Schools - Kenstone High School; Kenston Local School - Metro High School; Metro Early College High School - Northland High School; Columbus Public Schools - Perkins High School; Perkins Local Schools

Fig. 4 CRO partners

Evaluation College of Education and Human Ecology (OSU)

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Geauga County ESC (GCESC), ten districts in five counties, the Ohio State University, and the Ohio STEM Learning Network (OSLN). The partnership is a shared service model with the project service provided by the Ohio State University Office of Distance Education and eLearning; implemented through ESCCO, GCESC, and OSLN to the ten schools districts; and evaluated by a research team in the College of Education and Human Ecology at the Ohio State University. The table below describes how the partners fit into the different aspects of the program. In each component of the project (i.e., design, implementation, and evaluation), all partners are involved in the decision-making process. The project team meets each month to report and discuss the design, implementation, and evaluation strategies and effort. These meetings are critical in maintaining trust, communication, and ensuring program fidelity and success. Additionally, each month, the partner teams send a newsletter to all partners, schools, and teachers to share information. It maintains constant communication, reiterates the importance of the relationships, and keeps the project goals at the fore. The CRO project involves a reciprocal relationship among the partnership between higher education and P-12 education partners. For example, the OSU partners design the project activities, such as professional development and digital technology implementation. The P-12 schools provide specific requirements and feedback to refine the project activities and contextualize them into the P-12 school settings. The OSU partners generate evaluation strategies, and the P-12 partners help to define the specifics for both the formative and summative evaluations. The design, implementation, and evaluation of the project involve collaboration among all of the partners reinforcing the fact that the partnership pilots the College Ready Ohio project.

4.2.3

Stakeholders with External Experts Drive Collaborative Evaluation The evaluation of College Ready Ohio has two components including the formative evaluation and the summative evaluation. The summative evaluation tracks longterm goals at three different levels: 1. School-level change: Cultural changes in schools 2. Classroom-level change: Classroom adaptation to digital curriculum and contents in teaching and learning (e.g., accessibility and usage of digital content in classrooms) 3. Student-level change: Student engagement in and performance change with digital curriculum implementation The formative evaluation supports the schools as they pinpoint specific errors and areas of improvement. This helps them ensure effectiveness and efficiency of the project. The formative evaluation unfolds extensively on the teacher professional development component of CRO. The evaluation uses a mixed-method approach gathering multiple resources in both qualitative and quantitative data that include pre /post-teacher surveys (engagement and attitude in PD, knowledge, and self-

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efficacy of digital content integration and instructional design), self-reflections, interviews, on-site observation, and system log data in the project portal. The formative evaluation is imperative for developing trust between the schools and the CRO partners. Annually, the evaluation team collects data and timely shares the findings with teachers and principals so that they could use it to improve their implementation. The fact that the evaluators participate consistently (as opposed to once at the start and once at the end as in traditional evaluation models) fosters trust with the school-based educators. The evaluators return annually to provide support and resources about the findings and to help inform the project moving forward which teachers found useful. This reinforces the partnership, builds trust, and helps ensure program success. Collective decisions of the CRO partnership drive both the formative and the summative evaluation efforts. For example, during the project period, the project design and implementation illuminated areas needing feedback and improvement; the formative evaluation team then collected data and offered suggestions addressing these areas. As for the summative evaluation, partners established the evaluation criteria for the project goals and outcomes. Discussion and mutual agreement ensured support for each evaluation strategy and the three level measures. The evaluation team collects and analyzes data from teachers following every professional development event. The professional development team receives feedback to improve the next event with teachers. In addition, the evaluation team amasses long-term evaluation data based on yearly summative evaluations of school-, classroom-, and student-level changes. The evaluation team then analyzes the data and visits each partnering school to review and discuss the findings with teachers and school leaders. Through this process, the findings become meaningful to all of the partners. School partners are able to reflect on their findings and make school-level policy decisions, and likewise, district partners do the same. The partners use this data during the monthly meetings to generate strategies for the following year and to ensure success. For example, in year 1 the evaluation team found that catalyst teachers gain knowledge related to the topics covered in professional development by participating in the CRO project. Some teacher leaders were also changing their own classroom practice. However, they were not successfully bringing the knowledge to other classroom teachers in their schools because they did not have the competencies and strategies to be able to do so. When the evaluation team presented findings to the partners, the team adjusted the program so that year 2 focused on teacher leadership and peer-to-peer coaching for the catalyst teachers.

4.2.4

The Relationship Between the Partnership, Design, Implementation, and Evaluation Is Reciprocal and Iterative The CRO project involves multiple iterative cycles of design, implementation, and evaluation. There are shorter cycles based upon the formative evaluations. In these cases, the evaluation team provides formative feedback to the partners who can use the data to prioritize needs for the participating schools, ask questions of the researchers, and redirect the focus of the evaluation.

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An example of this in action came after the first year of CRO. During year 1 the evaluation focused on evaluating the professional development. It assessed the quality and effectiveness of the training for teachers. However, schools and partners realized that this was insufficient and indicated instead that they wanted to measure student competency for college readiness. After analyzing feedback after the firstyear evaluation cycle, the evaluation team revisited the logic model and evaluation framework to include both cognitive and non-cognitive competencies that might help assess student readiness for college and career.

5

Future Directions

This chapter proposes a collaborative evaluation approach identified as the Partnership, Evaluation, Design, and Implementation (PEDI) framework for advancing and sustaining m-learning initiatives in a P-16 partnership. Three key premises fortify this framework: (1) Partnership is the central driving force; (2) stakeholders with external experts determine collaborative evaluation; and (3) the relationship between the partnership, design, implementation, and evaluation needs to be both reciprocal and iterative. Higher education representatives such as faculty, researchers, instructional designers, and IT developers with P-12 educators promote m-learning solutions for use in P-12 schools. M-learning helps students better understand concepts in P-12 education, increase their motivation, and improve problem-solving skills (Bebell and O’Dwyer 2010; Kamarainen et al. 2013). M-learning can also support educators and school administrators by adapting learning to occur anytime, anywhere. However, such a shift presents challenges and changes for educators addressed through a collaborative evaluation approach with thoughtful planning, use, and implementation. Using the PEDI framework to initiate and sustain m-learning programs can maximize the potential for P-12 student learning. One of the greatest challenges to attaining successful outcomes using the PEDI framework is how stakeholders understand the gap between evaluation, design, and use by stakeholders, educators, and learners. M-learning comprises three components: evaluation, design, and use. Evaluation is often the purview of external evaluation experts. Design often exists with private and public sector engineers and institutions of higher education and to some degree planning within P-12 schools. Use, however, falls to educators in P-12 classrooms. A disconnect between the processes that link these three components creates three types of problems. First, evaluators do not always understand context in which the initiative will unfold, or the vision of the program leaders, or know how to tap the expertise of insiders for evaluative purposes. Second, engineers and program designers tend to focus on functionality and user experience over rigor and pedagogy. This can lead to exciting programs that fail to support student higher-order thinking but receive much attention because adoption occurs in large part for their design and ease of use. Last, incompatibility results when tools have many possible productive applications, but educators use pedagogical practices that do not maximize potential for student learning.

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Conversely, many m-learning solutions and tools developed by educators have promising pedagogical actions and features, but fail to address user experience pitfalls, and thus are not widely adopted upon entering the market (Anthony and Gimbert 2015; Groff and Mouza 2008; Kafai and Dede 2014; Intel Corporation 2013). Uniquely positioned, institutions of higher education bridge these gaps. When a “smart” partnership is central to a collaborative evaluation approach of an m-learning initiative, higher education stakeholders can team with school leaders and teachers to design and plan for adoption of effective m-learning initiatives (Anthony 2012; Kusunoki and Sarcevic 2013). In doing so, the stakeholders can solve implementation dilemmas, build teacher capacity to use m-learning in the classrooms, and collectively design and conduct ongoing, formative research and evaluation. In this way, higher education representatives can work with P-12 partners through testing and implementation, helping to make first- and second-order changes that help ensure an m-learning solution aligns with visions of teaching, learning, and the organization of schools. Institutions of higher education not only have experts in engineering and design that can support m-learning and adoption, they also have evaluators, faculty who can support research and grant writing, and expertise in pedagogy and teacher training (Anthony & Gimbert). Such partnerships can address issues of ineffective use and ensure that m-learning programs are reaching their intended learning outcomes for P-12 students (Dexter 2008). Most m-learning studies focus on effectiveness, followed by design (Beauchamp et al. 2015; Fitts 2015; Holcomb 2009; Ifenthaler and Schweinbenz 2013; KukulskaHulme and Traxler 2007; Wu et al. 2012). Furthermore, existing studies have examined m-learning initiatives as short-term, externally funded projects (Kukulska-Hulme et al. 2009; Sharples et al. 2009; Inan and Lowther 2010). There is limited scholarship that conceptualizes the idea of collaborative evaluation of technology-enriched curriculum within a smart partnership (Charania and Davis 2016; Smolin and Lawless 2011; Spikol et al. 2008) for the purpose of sustaining teaching and learning with mobile devices in primary and secondary schools (Ng and Nicholas 2013; Sun et al. 2017). In future studies, P-16 partners should collect and analyze data to contribute to the testing and refinement of local m-learning solutions, and infuse collaborative evaluations across differing contexts, thereby informing the emerging m-learning scholarship. Such research can offer insights beyond the design of applications, the capabilities of mobile learning devices, or the effectiveness of m-learning by discussing the conditions of effective m-learning use. Findings may explain organizational and partnership factors that support m-learning implementation and ascribe how goals for m-learning can guide educators’ efforts to enhance P-12 student learning. Future benefits of m-learning partnerships include access to mobile-aided pedagogical approaches for widening learners’ participation (Chen et al. 2017) in formal learning spaces (e.g., classrooms and workplaces) and informal contexts (e.g., homes and community facilities) (Kukulska-Hulme et al. 2009). Another possibility offers mobile and ubiquitous learning strategies promoting learners’ activity across virtual and physical environments including differing types of learning, e.g., scenario-based learning (Andrews et al. 2015; Bates and Martin 2013). Diverse theoretical perspectives on mobile learning may promote

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professional learning communities aiming to learn about emerging forms of technology-mediated teaching practices and promote effective types of professional development provided to users (Aubusso et al. 2009).

6

Cross-References

▶ Adoption of Mobile Technology in Higher Education: An Introduction ▶ Characteristics of Mobile Teaching and Learning ▶ Higher Education Partnerships with Nonprofit and Profit Organizations: An Introduction ▶ 1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation ▶ Moving Towards the Effective Evaluation of Mobile Learning Initiatives in Higher Education Institutions

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Contents 1 Introduction: How Mobile Technologies Can Support the Teaching and Learning . . . . . . . 2 Applying a Theory-Supported Approach to Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Types of Learning and Learners and the Cognitive Processes of Learning . . . . . . . . . 2.2 Enabling Effective Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Assessing Teaching and Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Teaching Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Learners and Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Implications for Applying Mobile Technology to Learning . . . . . . . . . . . . . . . . . . . . . . . . . 3 The Current State of Mobile Teaching and Learning Technologies and Applications . . . . 3.1 Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Software Development Methodologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 State of the Research and Commercial Products for Mobile Learning . . . . . . . . . . . . . . 4 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile information technologies can unshackle learners from desks and classrooms and allow them to learn on the go. They can explore and consume information, record their learning, and collaborate with mentors and with each other at any time and in any place. A mobile device knows user location and identity, so learning can be location and situation based and personalized to the user. In this chapter, we describe current mobile computing technologies and their use in teaching and learning. We project how mobile technologies will evolve in

R. Ramnath (*) · A. Kuriakose Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_35

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the future and examine – using the various theories and processes of learning as a lens – how the growing affordances of these technologies may influence student learning and education in the future.

1

Introduction: How Mobile Technologies Can Support the Teaching and Learning

From blackboards to calculators to computers, technologies enable and enhance learning. Each new technology provides new and improved affordances that influence how we teach and how we consume educational material. However, when we explore how students learned by using technologies, it has become clear that naively applying technology is not enough, and we need frameworks for applying technologies. These frameworks come from learning theory. As Fischer and Scharff (1998) suggest, “New technologies and learning theories must together serve as catalysts for fundamentally rethinking what learning, working, and collaborating can be and should be in the next century.” This idea is the foundation for this chapter that begins with a discussion of a selection of the seminal learning theories, styles, taxonomies, and processes. Next, reasons how and why popular mobile technologies can advance teaching and learning are illustrated. Lastly, future application of these technologies is projected, and examined, through the lens of learning theory, in relation to how capabilities and affordances of mobile technologies can enrich and improve learning outcomes.

2

Applying a Theory-Supported Approach to Mobile Learning

Before discussing how mobile technologies may effectively assist learners, it is important to understand how learners learn, how they experience teaching episodes, and how assessment shapes teaching and learning. To that end, some foundational elements of learning theory first deserve reflection, followed by a discussion on how mobile technologies may support. This debate applies learning theory, teaching methods, and learning processes as its argument.

2.1

Types of Learning and Learners and the Cognitive Processes of Learning

Learning has been broadly classified as follows: • Learning-conscious or formalized learning (Rogers 2003): Formalized learning is “educative learning” rather than the accumulation of experience. Here, learning is

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a conscious process, with the intent that formalized knowledge will enhance and accelerate it. Task-conscious or acquisition learning (Rogers 2003): Acquisition learning is seen as going on all the time. It is “concrete, immediate and confined to a specific activity; it is not concerned with general principles.” Here, while the learners may not be conscious of learning, they are aware of the specific task in hand. Project-based courses, internships, and professional practice itself contribute to this kind of learning. In addition to categorizing learning, considerable research in education has focused on categorizing the types of learners – from conceptual learners, who prefer to learn using abstractions, to hands-on learners, who prefer to learn by doing. One commonly referenced body of work is Kolb’s Learning Style Inventory (LSI) (Kolb 1984). In this model, learners are categorized using two axes, namely, the active experimentation-reflective observation axis and the abstract conceptualization-concrete experience axis. Learners distribute to one of four quadrants, as follows: – Convergers, who believe in active experimentation as well as abstract conceptualization. For example, convergers may first think about things and then try out their ideas to see if they work in the real world or they could do the reverse, which is, experiment first and then generalize their experience into concepts. Convergers like to understand how things work. Convergers typically prefer to work by themselves, thinking carefully and acting independently. Computer-based learning tends to be effective with them. – Accommodators learn by active experimentation and through direct interaction and concrete experiences. Accommodators do rather than think and like to ask “what if?” and “why not?” rather than “how?” Unlike assimilators (see below), they are likely to reject approaches to learning that are routine. Accommodators prefer to learn by themselves than with other people and like hands-on and practical learning rather than lectures. – Divergers (reflective observation-concrete experience). Divergers take experiences, as well as instruction, and extrapolate and generalize learning in multiple directions. Divergers ask “why?” Divergers enjoy participating and working with others. While they like interactions with others, they like these to be calm and conversational and fret over conflicts. – Assimilators learn by reflective observation and abstract conceptualization. Assimilators think rather than act. They task, “what is there I can know?” They prefer lectures for learning, with demonstrations where possible, and respect the knowledge of experts. They will also learn through conversations, guided by a logical and thoughtful approach. The best way to teach an assimilator is with lectures and reading material that start with high-level concepts and then work through the details. Note that Kolb’s model of learner types is considered useful as a description of learning types; however, its use to analyze situations and provide solutions is unproven (Hunsaker 1981).

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An important aspect of all learning is “metacognition,” i.e., the process of reflecting on and directing one’s own thinking. Metacognition is the basis for two types of generalized learning, as follows: • Double-loop learning (Argyris and Schön 1978): This form of learning involves the detection and correction of error. In single-loop learning, the response when something goes wrong is to look for another strategy that will address and work within the existing governing variables. In other words, given or chosen goals, values, plans, and rules become operationalized, and more efficient, rather than questioned. An alternative response is to question the governing variables themselves. This is double- loop learning. Such learning may then lead to an alteration in the governing variables and, thus, a shift in the way strategies and consequences become aligned. • Reflective practice (Schon 1983, 1987): Reflective practice is a refinement of double-loop learning. The capacity to reflect on action to engage in a process of continuous learning is one of the defining characteristics of professional practice. The cultivation of the capacity to reflect in action (while doing something) and on action (after completion of the action) has become an important feature of professional training programs in many disciplines and encouraged as a particularly important aspect of educating the beginning professional. When trying to develop students’ metacognitive skills, making students’ thinking visible to both their teachers and themselves is very important. “Thinking aloud” is a common practice suggested to learners, in order to have them reveal their thinking and thought processes. While thinking aloud is effective (Baumann et al. 1992), Ericsson and Simon (1980) point out that “verbalizing information is shown to affect cognitive processes only if the instructions require verbalization of information that would not otherwise be attended to.” In other words, thinking aloud requirements need purposeful design.

2.2

Enabling Effective Learning

According to How People Learn (HPL) (Bransford et al. 2000), environments that best promote learning have all four of the interdependent characteristics described below: 1. They are learner centered: These learner-centered environments are those that pay careful attention to the knowledge, skills, attitudes, and beliefs that learners bring to the educational setting. New knowledge extends existing knowledge, and therefore teachers need to uncover any incomplete understandings, false beliefs, and naïve concepts that students may have. 2. They are knowledge centered: Knowledge-centered environments present knowledge in a well- organized approach, in order to support understanding and adaptive expertise building. Teachers have clear learning goals that capture

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exactly what knowledge students will be gaining and how they can use that knowledge. There is also emphasis put on developing a strong foundational structure of basic concepts on which to build further learning. 3. They are assessment centered: Assessment-centered environments provide frequent formal and informal opportunities for feedback focused on understanding and encourage and reward meaningful learning. In addition to grades on tests and essays that serve as summative assessments that occur at the end of projects, formative assessments provide students with opportunities to revise and improve the quality of their thinking and understanding. 4. They are community centered: Community-centered environments allow people to learn from one another, by collaboration, as well as by conflict. The HPL framework also has several recommendations for enabling effective learning, as follows: • Make thinking visible, of both students and experts, to enable metacognition. Thus, have students engage in activities that make visible the processes of their thinking, rather than merely the conclusions of their thinking. Model expert thinking to make explicit the strategies and techniques that are implicit in expert thinking. • Benchmark the knowledge level of students. The knowledge (and misconceptions) that students enter the class with will affect their learning. • Use contrasting cases as examples. Two examples whose differences highlight a particular point or set of points can illustrate particular points effectively. More so than novices, experts are likely to understand the contrast between two complex cases with many similarities. It is best, therefore, to start with simpler cases before moving to complexity as understanding deepens.

2.3

Assessing Teaching and Learning

As the HPL framework recommends, assessment is a key aspect of an effective learning environment. A well-known framework for assessment is Bloom’s taxonomy. The revised and updated version of this taxonomy is (Anderson et al. 2001), which categorizes the levels of learning as the following: • Remembering, that is, can the student recall or remember the information taught in (say) a class? Assessments for this level involve asking the learner to memorize and then define, duplicate, list, or even simply recall or repeat what was taught. • Understanding, that is, assessing that the student can explain ideas or concepts. Here, the learner is asked to classify, describe, discuss, explain, identify, translate, or paraphrase what was taught. • Applying, that is, assessing that the student can use the information. Here, the learner is asked to choose, employ, and demonstrate the use of the learning.

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• Analyzing and evaluating, that is, can the student distinguish between the different parts by appraising, comparing and contrasting, examining, and critiquing the information taught, or can the learner justify a stand or decision? • Creating, that is, assessing that the student can create a new information product or point of view. While Bloom’s taxonomy is intended to assess an individual’s learning, Kirkpatrick’s four levels of training (The Kirkpatrick Model 2015) are an orthogonal set of levels, primarily used for assessing knowledge delivery (i.e., the teaching or training). These four levels are as follows: • Level 1: Reaction – To what degree participants reacted favorably to the training • Level 2: Learning – To what degree trainees acquired the intended knowledge and skills from their participation in a training event • Level 3: Behavior – To what degree trainees could apply on the job what they learned during training • Level 4: Results – To what degree the appropriate outcomes (such as revenue growth, improved quality) occurred as a result of the training event In a sense, Bloom’s taxonomy is aimed at summative assessments (i.e., assessing the learner) as opposed to formative assessments (i.e., assessing the teaching or training), which is the target of Kirkpatrick’s four levels.

2.4

Teaching Techniques

Terrell (2005) delivered a simple way to categorize activities as essential elements of a learning system: auditory, which includes listening and speaking; visual, which includes seeing and reading; and kinesthetic, which incorporates “doing” in the teaching and learning process. The use of hybrid activities within a mobile learning system is exemplified in Tan and Liu (2004), where words are learned through matching with pictures (kinesthetic plus visual) and having the tool read out words (auditory). The “places” in which learning occurs is also a key characteristic of a learning system. Traditional lecture-based teaching typically takes place through lectures, interactions, and assessments in a specific room. Online systems remove constraints of location and distance. Thus, lectures stream as videos, assignments upload via email, and discussions may take place through online forums, such as chat rooms or wikis. Massive open online courses (MOOCs) are highly scaled up examples of online education systems. Hybrid systems consisting of place-based and online components deliver what is typically termed as blended learning (Meejaleurn et al. 2010). A (now) common example of blended education is done through what is known as a “flipped” or “inverted” classroom (Lage et al. 2000; Herold et al. 2012). The flipped classroom is widely regarded as an excellent approach to exploit

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affordances of online technologies to actively engage students and improve learning. Traditional lectures transform to online videos with class meetings being devoted to discussion and application of new ideas. The expectation is that this will help improve student achievement of course outcomes. The granularity of learning (and teaching) has also been the subject of educational research. A learning object (Wiley 2000; Gerard 1967) is “a collection of content items, practice items, and assessment items that are combined based on a single learning objective.” The main idea behind learning objects is to break educational content into small chunks, reusable in various learning environments.

2.5

Learners and Technology

Prensky (2001) makes the claim that learners today are “digital natives” who “think and process information fundamentally differently” because of the way they use technology in their daily lives, texting constantly to stay in touch, holding parallel conversations, used to playing deeply immersive games, rather than reading, and skilled at integrating information quickly, rather than synthesizing it deeply. His claim (that has considerable anecdotal support but, truth be told, insufficient experimental validation) is that learners today must be taught differently, in ways that take advantage of their multitasking, nonlinear skills.

2.6

Implications for Applying Mobile Technology to Learning

The aforementioned theory and practice afford significant implications on how mobile technology integrates with teaching and learning, as follows: • Support for task-conscious and learning-conscious learning: To begin with, mobile devices can support formalized, learning-conscious methods of teaching by presenting learning objects, or even just reading material, and streaming or podcasted audio and video lectures. Mobile devices can also support a wide and nuanced range of acquisition or task-based learning, for example, by having students take part in activities where they collect data in the field, and then analyze and present their findings. • Personalization: As personal devices, smartphones and tablets can identify, store, and apply intimate knowledge about the user. Programming can specifically match knowledge to a user’s learning type. A digital native can use today’s devices to access knowledge in chunks, in parallel by multitasking, and through Trojan Horse means, such as in games like “Where in the World is Carmen Sandiego” (Bernstein 1991), where the learning about geography, mathematics, and cultures, among other subjects, was hidden inside the game.

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• Support for single- and double-loop learning, reflection, metacognition, and learner visibility: At a micro level (selections, navigations, data entry, time of entry and exit, etc.), the smart device collects data as the user consumes educative material or practicing learned skills. This data can be mined and analyzed to provide detailed feedback to the user, so he can better apply what he has been taught (i.e., mobile technology can assist in single-loop learning). Further, mobile devices are programmed to identify lack of convergence toward a solution, compare one user’s process with another’s, perhaps someone who is an expert, and offer suggestions that direct the user toward double-loop learning as well. The device can facilitate active reflection; prompt the user to think aloud, to answer questions, and to probe engagement; as well as present quizzes or tests that assess learning and reveal problem-solving processes. • Creating rich learning environments: A smart device is a conduit to an individual’s learning environment. As mentioned previously, this environment may be learner centered through personalization, where the mobile device is collecting the data that enables this personalization. A smart mobile device can be programmed both to do explicit assessment (by presenting the learner with surveys and tests) and implicit or behind-the-scenes assessment, simply by observing the interactions between the user and the learning material. Finally, the mobile device serves as a means of connecting the learner with her learning community. • Assessment: Nuanced assessment to measure the learner’s level in accordance with Bloom’s taxonomy or explore a program’s quality with respect to Kirkpatrick’s four levels uses explicit pop-up surveys and tests or implicit behindthe-scenes data analysis, with the mobile device serving as the data collection device. • Support for auditory, visual, and kinesthetic models: The audio, video, and touch capabilities of the mobile device directly support these modalities, as well as hybrids of these modalities. Certainly, other electronic and physical means (such as paper forms) may achieve the above as well! However, mobile technology allows the learner to acquire knowledge through various modalities and practice this knowledge while collaborating with others free from the tethers of time and location. In the next section, then, we describe current mobile technologies and how these currently rich learning.

3

The Current State of Mobile Teaching and Learning Technologies and Applications

This section presents the current state of the computing technologies used in mobile teaching and learning applications and systems. This section then describes a selection of the teaching and learning applications and systems themselves. Applications for research and commercial applications are described.

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Technologies

Types of devices: Mobile computing devices integrated into teaching and learning range include smartphones, tablets and laptops, as well as specialized devices. Most devices fall into following categories: • iOS devices from Apple that include the various versions of the iPhone, the iPad, and the iPad mini. iOS devices have a share of approximately 33% of smartphone usage (Forbes 2017) while holding to approximately 15% of global market sales (IDC 2017). • Devices powered by the Android operating system from Google that make up roughly two-thirds of smartphone usage (and about 85% of global market sales) (IDC 2017). These include smartphones and tablets from a variety of manufacturers, such as Samsung, Google, and HTC, as well as the Kindle Fire from Amazon (which has transformed from an e-book reader to a tablet that can run apps). • Specialized devices such as the original Amazon Kindle Paperwhite, currently sold by Amazon, and the relatively new Amazon Alexa-based devices, namely, the Echo™ and the Dot™. Most of the general-purpose devices (i.e., outside of the specialized devices) have high-density displays. Thus, all mobile devices can present documents (text and PDF are the common formats supported), and most can support high-density video presentation. Rich interactive graphics are displayable (such as games). All can run special-purpose “apps.” Device capabilities: Apps on mobile devices can make use of a powerful set of built-in device capabilities. These include: • Display and graphics: The presentation capabilities mentioned above but also rich interactive graphics capabilities through touchscreens. • Storage: The ability to store increasingly large amounts of data – now up to multiple gigabytes (GB) for the more expensive and powerful devices (such as the Samsung Galaxy tablet, which has internal storage of up to 16GB) – with storage cards available that can store up to 128GB. Data can be stored as files as well in relational databases (such as SQLite [SQLite] that can run on the device). • Computation: The newer mobile devices are high-powered computing devices with multicore processors that can do complex mathematical calculations and render rich high-quality graphics in real time. • Sensing: These smart mobile devices come with a range of sensors that can sense magnetic fields, sound, light, and acceleration. A new sensor that is now found on many Android and iOS smartphones is a near field communication (or NFC) sensor. Together with the camera and audio recording capabilities, sensors are useful in creating active learning educational applications in which the device captures data in the field of physical phenomena.

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• Location sensing: Location sensing allows the smart device to not just know its GPS location but also its location hierarchy (e.g., which country it is in and within that, which state, which city, which street address, and so on). • Communication: A core feature of almost all mobile devices is the ability to communicate via the Internet through which apps can access information on the Web as well as send and receive emails and text messages, as well as communicate with each other. Devices also typically have a built-in short-range communications capability via a technology known as Bluetooth. This allows the device to connect to nearby devices such as displays and audio and video servers (like iTunes Plus that can stream content from the device to an audio system or the television). • Interactivity: Most recent smartphones and tablets allow users to interact with them using touch (operating as mouse clicks) and gestures. With the advent of Siri™ and Google speech recognition technology in Android devices, speech recognition is now a mainstream and (almost) reliable capability; therefore, users can interact with applications with their voice. • Built-in applications and app stores: Mobile devices come “factory installed” with several apps, such as a Web browser, a messaging app, a telephony app, a contacts app, and audio and video playback and recording apps. Thus, for example, an app that teaches biology has an experimental component where the learner in the field takes photos of various plants and uploads these as part of an assignment. A useful feature is that the services that these apps provide are callable from other apps. Thus, if a learning application needs to email results to a teacher for evaluation, it can simply use the built-in email app to send the email. The apps on a device are not predetermined and fixed. New apps can also be downloaded and installed from the appropriate “app store,” thus Android apps [are] downloadable downloadable from the Google Play store and iOS apps from the Apple Store. Software technologies: A large variety of software technologies build applications and systems for mobile devices, as follows: • The standard set of Web technologies such as HTML, Cascading Style Sheets (CSS), and JavaScript build Web-based apps for mobile devices. The advantage of building Web applications is that they are cheaper to build (because of the availability of programmers familiar with Web applications) and easy to install (because no installation is needed!). Note that a Web app is driven by a software component on a server, which may be written in a scripting language (such as Ruby on Rails, PHP, or Python) or in Java™or .NET™. Such a server component will also typically use a commercial-quality relational database, such as mySQL™ or SQLServer™. • Web applications have two disadvantages. They need to have constant and reliable access via the Internet to a server and (until recently) had limited capabilities with respect to a rich graphical user interface (or GUI). “Native”

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applications, which are essentially desktop applications that run on the mobile device, do not have the disadvantages Web applications have. Native applications for iOS devices (i.e., the iPhone or the iPad) develop into Objective-C using a “framework” called the iOS Framework, on an interactive development environment (IDE) called Xcode. Applications for the Android platform are developed in Java using the Android Framework, on an IDE called Eclipse (a more usable IDE called Android Studio has recently been released by Google). Apps for the Windows phone use a version of the .NET™ platform from Microsoft on an IDE called Visual Studio. • Cross-platform technologies: Native applications that need to run on more than one platform (i.e., iOS and Android) have to have a version developed for each platform. However, there are technologies that allow developers to develop an app once using one programming language and then have it automatically adapted by the IDE for all the platforms. Such technologies are called “crossplatform” technologies and include Sencha™, Titanium™, RhoMobile™, and Xamarin™. • Other relevant technologies: A mobile app may call upon data storage technologies to preserve user data or on data mining algorithms to extract insights from the data that the user is supplying. Data is typically stored on the device in files (which are often encrypted for security) or in relational databases (such as SQLite™) that run on the device itself (as opposed to on a server). Several open-source data mining and machine learning technologies exist in open source (enabling free use), such as Weka™.

3.2

Software Development Methodologies

In addition to the technologies used for building mobile apps, it is also important to briefly describe “best- practice” methodologies (or the engineering processes) used to develop these apps and systems. When developing apps for teaching and learning, it is important to be able to evolve an app quickly to meet the needs of diverse target populations. The methodologies and techniques described below enable software developers to develop software in a flexible manner: • Product line design: Product line design is an engineering design methodology used to develop a set of software-intensive systems that share a common, managed set of features. Typically, a family of systems satisfies the specific needs of a particular market segment or mission. These systems develop from a common set of reusable assets in a prescribed way. Using product line design greatly increases the efficiency and reduces the cost of developing apps that are all targeted for a specific domain (such as STEM teaching and learning). • Agile development: Agile development is a management practice and a set of programming techniques for software development that allows software to adapt rapidly to changing needs identified during its development cycle.

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State of the Research and Commercial Products for Mobile Learning

In this section, the “state of the art” in mobile teaching and learning first illustrates a selection of commercial products, followed by a selection of research projects in mobile teaching and learning.

3.3.1 Commercial Mobile Teaching and Learning Products There are several commercial teaching and learning products available commercially. A short list of products from Scholastic – well-known vendor of products – targeted at K-12 is shown below: • Read 180 (http://read180.scholastic.com): This is a reading intervention program from Scholastic that has a set of curriculum, instruction, assessment, and professional development programming. Read 180 has recently been made available on the iPad. Targeted at the Common Core State Standards. In the reading area, it provides reading comprehension material – articles and stories – integrated with embedded questions. Read 180 also provides writing assignments, which come with scaffolding material (such as bullet points outlining a suggested flow and content). • Math 180 (http://teacher.scholastic.com/products/math180): Math 180 is a mathematics intervention program to help students struggling with algebra. Math 180 is organized into nine blocks of instruction, each of which not only presents a related set of algebraic concepts but also tries to present its mathematical theme in the context of application stories and potential careers. • System 44 (http://system44.scholastic.com/): This is a reading program for reading-challenged readers in Grades 3–12+. It can be used as a standalone or as a supplement to Read 180. When combined with Read 180, System 44 is meant to bring students up to a level at which they can then use Read 180. • Grolier Online (http://teacher.scholastic.com/products/grolier/): Unlike the three products above, Grolier Online is not targeted at a specific skill. Rather, it serves as a resource of information, designed to be usable for learners in Grades 3 and higher. Resources include videos, links to world newspapers, and clickable maps that give detailed information about the places (including current events). Most commercially available products (like the above) simply use the ability of mobile devices to present and interact with information using native apps. The other capabilities of mobile devices – such as sensing, location, personalization, etc. – are not used. Commercial products will emerge that begin to use a richer set of mobile device capabilities. This prediction unfolds in Sect. 4.

3.3.2 State of the Research in Mobile Teaching and Learning As is to be expected, research in mobile teaching and learning has focused on answering research questions in mobile teaching and learning. Research has primarily looked at

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• The efficacy of specific learning modules when delivered on a mobile device (Yan et al. 2012; Tan and Liu 2004). • The adaption of students to mobile and online environments (Luo and Huang 2012) when they are asked to migrate away from the traditional classroom. In particular, (Terrell 2005) examines the effect of learning styles with respect to adapting to online and mobile instruction. • The combination, or blending, of mobile learning with traditional classroom learning, such as in (Meejaleurn et al. 2010). Note that most research focuses on applications that follow an acquisition of knowledge metaphor (AM). The participation (in activities) metaphor (PM) is so far mostly unexplored in the research, at least in any rich level. Incorporating rich activities in applications will be an area of deeper exploration in the future. To that end, an example of the authors’ research in mobile teaching and learning is presented. GeoGame: The GeoGame project is an ongoing collaboration between researchers in geography, physics education, and computer science (and receives ongoing support from the National Science Foundation through an NSF-IIS Award #1320259). The GeoGame project seeks to effect location-based learning (see Clough 2010) about the world through simulations built around online maps. Our first application (see Fig. 1) developed via this project, GeoGame–Green Revolution, turns digital world maps, similar to Google Earth and Bing maps, into a game board where any place in the world can be experienced firsthand through game-like simulations. The

Fig. 1 Game play in GeoGame – Green Revolution

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online game combines satellite images, geographic information, and game play to give users a microexperience of what life is like in other places of the world. In the first 2 years of this project, the team has developed and tested a prototype game about the Green Revolution in India. The data collected from user studies in university geography classes will help the team and the learning technology community to understand • What key components and functionality can help and guide others to develop similar learning technology • How educators can naturally integrate an online social game activity into the classroom • How a virtual microexperience can generate critical thinking and impact learning about a faraway place when the students can relate to what they experienced rather than what they have read Our first results (Ahlqvist et al. 2013, 2014; Mikula et al. 2013) demonstrate that many students who play the game increase their understanding from simple explanations to an awareness of the complexity of agriculture in the developing world. Continued research will seek to determine how that awareness is developed and how the technology can be used to take the students one step further to formulate explanations of what happens in the game. The technical innovations in GeoGame allow almost any type of board game played on top of a current or historic map of the world. In fact, the game can directly access and allow any known real-world information to affect the game play. Just imagine playing the popular game RISK with friends but in Google Earth on a current or historic map allowing real-world information on economy, population, and other conditions affect the game in real time or playing Farmville in a village close by or in a faraway Indian village, planting, buying supplies, fertilizing, irrigating, trading goods, and so on. The intent is for learners to have a lot of fun while learning about real-world facts and complex human-environment interactions. An edited book on geography-based games and learning (Ahlqvist and Schlieder, 2017) is scheduled to appear. Vector Training Module: The vector training module is an ongoing collaboration among researchers in physics education and computer science and engineering (Heckler and Mikula 2016; Mikula and Heckler 2017). It is a Web- and tabletbased quiz application that presents learners with questions on vector algebra and allows them to answer using a touch-based interface. This project is aimed at removing mathematical misconceptions with respect to vectors from high school students and first-year students in the undergraduate program. The basic framework of the vector training module can be extended to build quizzes on various topics (Fig. 2). Edgeo: The Edgeo application is another touch- and gesture-based Microsoft Windows application geared toward high school students learning geography. It is an application where teachers can present artifacts of geographic significance – such as the Three Gorges Dam – and present slides that provide various details about that

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Fig. 2 Example problem in the vector training module

artifact, such as its dimensions, its capacity, its economic and social impact, and so on. Finally, instructors can then pose questions for discussion as well as quizzes for students to answer. Finally, the system provides analytics on how the students interacted with the system and how they performed (Fig. 3).

4

Future Directions

This section considers where mobile technologies will go and where they will take learners. Mobile devices used by learners still suffer from several limitations – of high cost (the newest iPhone 7s costs upward of several hundred dollars), unreliable Internet connections and connections with low bandwidth, and limitations in screen size, storage, and raw computing power. In addition, market penetration of capable devices is slow. While the newer devices are much improved, not everyone has the latest iPhone, iPad, or Android tablet. In particular, the market with the highest need for mobile learning are students from underperforming schools, nontraditional students, and students in areas with poor information technology infrastructure.

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Fig. 3 Interacting with Edgeo, a touch- and gesture-based geography instruction application

However, these learners are the same who might not have the economic wherewithal to purchase the latest devices. However, as the cost of these powerful devices is diminishes, it is likely that sufficient market penetration will be achieved in 5–10 years. Thus, it is our belief that emerging research and commercial products should assume the wide availability to learners of powerful, well-connected devices. Given this, we now attempt to describe the future of mobile teaching and learning. On demand learning: Technology will enable mobile learning to achieve its promise of on-demand, anytime-and-anywhere learning. Learners will be able to seamlessly start a lesson in school, continue the lesson on the bus, and complete the learning at home. Students will be able to initiate learning at any time and place as well. Finally, location and context capabilities of mobile device render learning ubiquitous and seamless with the environment of the learner. Imagine driving by a state or federal park and exploring rich, interactive information about its flora and fauna that is delivered on your smartphone! Personalization: Since the mobile device will become the locus of all interaction between the user and the outside world, the device will have a rich awareness of context and a centralized and hence holistic and deep knowledge of the learner. Thus, mobile learning will adapt to the learning style of the learner. If the learner is an assimilator, the device will teach in an information-centric manner. If the learner likes to learn by doing, the device will suggest activities. Richer activity-based learning: Lastly, sensing capabilities of the device will be utilized in mobile learning. For example, learning modules will offer information to teach about micro-weather patterns through experiences that allow the learner to

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measure wind velocity, identify the existence of eddies, and correlate wind patterns with the humidity and quality of the air around him or her. A bright future lies ahead for mobile learning!

5

Cross-References

▶ Adoption of Mobile Technology in Higher Education: An Introduction ▶ Augmented Reality in Education ▶ SmartLab Technologies

References Ahlqvist, O., and C. Schlieder. 2017. Geogames and geoplay, game-based approaches to the analysis of geo-information. To appear 2017. Ahlqvist, O., R. Benkar, R. Ramnath, K. Vatev, A. Heckler, and B. Mikula. 2013. Online map games – playful interaction with geographical science tools. In Games + Learning + Society conference 9.0, Madison, June 2013. Ahlqvist, Ola, Zhaoyi Chen, Peixuan Jiang, and Rajiv Ramnath. 2014. Online map games – playful interaction with complex real-world issues. In AGILE conference on geographic information science, Castellon, 3 June 2014. Anderson, L.W., D.R. Krathwohl, et al. 2001. A taxonomy for learning, teaching and assessing: A revision of Bloom’s taxonomy of educational objectives. New York: Longman. Argyris, C., and D. Schön. 1978. Organizational learning: A theory of action perspective. Reading: Addison Wesley. Baumann, J.F., N. Seifert-Kessell, and L.A. Jones. 1992. Effect of think-aloud instruction on elementary students’ comprehension monitoring abilities. Journal of Literacy Research 24 (2): 143–172. https://doi.org/10.1080/10862969209547770. Bernstein, Sharon. 1991. PBS game show charts new territory. LA Times article, http://articles. latimes.com/1991-09-30/entertainment/ca-2396_1_carmen-sandiego. Bransford, John D., Ann L. Brown, and Rodney R. Cocking, eds. 2000. How people learn: Brain, mind, experience and school. 1st ed. Washington, DC: National Academies Press. Clough, G. 2010. Geolearners: Location-based informal learning with mobile and social technologies. IEEE Transactions on Learning Technologies 3 (1): 33–44. Ericsson, K.A., and H.A. Simon. 1980. Verbal reports as data. Psychological Review 87 (3): 215–251. https://doi.org/10.1037/0033-295X.87.3.215. Fischer, G., and E. Scharff. 1998. Learning technologies in support of self-directed learning. Interactive Media in Education 98(4). http://jime.open.ac.uk/98/4. Forbes. 2017. https://www.forbes.com/sites/johnkoetsier/2017/05/18/surprise-google-revealsapples-ios-market-share-is-65-to-230-bigger-than-we-thought/#615aab0b5890. Gerard, R.W. 1967. Shaping the mind: Computers in education. In Computer-assisted instruction: A book of readings, ed. R.C. Atkinson and H.A. Wilson. New York: Training & Development Journal. Heckler, A.F., and B.D. Mikula. 2016. Factors affecting learning of vector math from computerbased practice: Feedback complexity and prior knowledge. Physical Review Physics Education Research 12: 010134 Published 9 June 2016. Herold, M., T. Lynch, R. Ramnath, and J. Ramanathan. 2012. Student and instructor experiences in the inverted classroom. In Frontiers in Education Conference (FIE 2012), Seattle, Oct 2012.

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Hunsaker, Johanna Steggert. 1981. The experiential learning model and the learning style inventory: An assessment of current findings. Journal of Experiential Learning and Simulation 2: 145–152. IDC. 2017. Smartphone OS market share, 2017 Q1. http://www.idc.com/promo/smartphone-mar ket-share/os. Kolb, D.A. 1984. Experiential learning. Englewood Cliffs: Prentice-Hall. Lage, M.J., G.J. Platt, and M. Treglia. 2000. Inverting the classroom: A gateway to creating an inclusive learning environment. Journal of Economic Education 31 (1): 30–43. Luo, Shuanglan, and Xueqin Huang. 2012. A survey research on the online learning adaptation of the college students. In: 2nd international IEEE conference on Consumer Electronics, Communications and Networks (CECNet), Three Gorges, YiChang. Meejaleurn, S., A. Uratchanoprakorn, and S. Boonlue. 2010. The construction of the onlinelearning in a group activity using blended learning on the information communication and network system at Grade 9. In 2nd International Conference on Computer Technology and Development (ICCTD), 2–4 Nov 2010. Mikula, B., and A. Heckler. 2017. Framework and implementation for improving physics essential skills via computer-based practice: Vector math. Physical Review Physics Education Research 13: 010122 Published 8 May 2017. Mikula, B., A. Heckler, O. Ahlqvist, R. Benkar, R. Ramnath, and K. Vatev. 2013. GeoGame: An online geography game for learning about the green revolution. In Poster Paper, Games + Learning + Society conference 2013, Memorial Union, Madison, June 2013. Prensky, Marc. 2001. Digital natives, digital immigrants. On the Horizon (MCB University Press) 9 (5): 1–6. Rogers, A. 2003. What is the difference? A new critique of adult learning and teaching. The National Institute of Adult Continuing Education, England and Wales. ISBN 1 86201 184 2. https://learningandwork.org.uk/sites/niace_en/files/resources/WhatIsTheDifference.pdf Schon, D.A. 1983. The reflective practitioner. New York: Basic Books. Schon, D.A. 1987. Educating the reflective practitioner, Jossey-Bass Higher Education Series. San Francisco: Wiley. Tan, Tan-Hsu, and Tsung-Yu Liu. 2004. The mobile-based interactive learning environment (MOBILE) and a case study for assisting elementary school english learning. In ICALT’04 proceedings of the IEEE international conference on advanced learning technologies, 530–534, 2004. Terrell, S. 2005. Supporting different learning styles in an online learning environment. Online Journal of Distance Learning Administration VIII(II). Also at http://www.westga.edu/~dis tance/ojdla/summer82/terrell82.htm. The Kirkpatrick Model. 2015. http://www.kirkpatrickpartners.com/OurPhilosophy/TheKirkpa trickModel/tabid/302/Default.aspx. Wiley, D.A. 2000. Connecting learning objects to instructional design theory: A definition, a metaphor, and a taxonomy. In The instructional use of learning objects: Online Version. http://reusability.org/read/chapters/wiley.doc. Retrieved 07 June 2004. Yan, W., C. Li, J. Ma, S. Ma, and H. Truong. 2012. m-LTE: A mobile-based learning and teaching interactive environment. In IEEE international conference on Teaching, Assessment and Learning for Engineering (TALE), Hong Kong.

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Media and Technology: Increasing Use of Mobile Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Mobile Devices’ Use in Early Childhood Education (ECE) . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Digital Literacy and Multiliteracies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 iPads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Challenges with Mobile Devices in Preschool Education . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Why Do We Need Media and Technology in ECE? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conclusion and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Children are using mobile devices at home and in schools. This chapter discusses the use of media and technology with mobile devices in early childhood education (ECE) with preschool-aged children. Children under 5 years old spend almost 4 h per day interacting with mobile devices, and this time increases to over 7 h per day between the ages 5 and 10. Since average time spent on devices continues to grow, exploring any potential impact on children’s learning is important. Children can communicate through speaking, symbol recognition, and the production of written language including the use of a touchscreen or keyboards that have expanded traditional literacies in digital literacies. This chapter also explores the complexity of digital literacy including the use of

R. Ralph (*) · S. Petrina The University of British Columbia, Vancouver, BC, Canada e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_118

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interactive media, such as software programs, applications (apps), broadcast and streaming media, television, eBooks, the Internet, and other content for young children. This chapter focuses on the particular use of iPads, as the ubiquitous nature of these mobile devices warrants further exploration. It also discusses an urgent need to integrate media and technology and mobile devices in early childhood education. Additionally, this chapter portrays a pressing need for research with preschool-aged children and the use of mobile devices.

1

Introduction

Children are using mobile at home and more frequently in schools. In the United States (USA), over 4.5 million students are estimated to be using tablets every day (Etherington 2013). Several researchers associate negative effects resulting from overexposure to digital media and technology, such as attention deficits, cyberbullying, physical inactivity, and selfishness; there is also ample evidence of positive outcomes from uses of media and technology mobile devices, including deeper learning, increased motivation, more independent work, and increased confidence and curiosity (Flewitt et al. 2014; Gentile et al. 2014). Children under 5 years old spend almost 4 h per day interacting with devices, and this time increases to over 7 h per day between the ages 5 and 10 (Childwise 2016). Also over 73% of preschoolaged children use tablets (see Fig. 1) (Childwise 2016). Since average time spent on devices continues to grow, exploring any potential impact on children’s learning is important. This chapter focuses on the particular use of iPads, as the ubiquitous nature of these mobile devices warrants further exploration. In particular, the impact of iPads is substantial as there have been over 250 million iPads sold offering over 2.2 million apps and in particular over 300,000 for children (Apple 2017; Alper 2013; Hendela 2014). Recently, debates have arisen about the appropriate amount of screen time and other concerns regarding preschool-aged children using mobile devices. While these debates continue, the exposure and access to mobile devices for many children and families have become ubiquitous. Given the ubiquity of media and

Fig. 1 Preschool-aged children using an iPad

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technology and growing access to mobile devices in childhood, parents and teachers have pressing concerns with whether children are benefitting or suffering as a result. As media and technology are increasingly pervasive and studies’ findings about their influence on young children appear contradictory, researchers can explore the short- and long-term impacts of media, technology, and mobile devices on preschoolers’ learning. This chapter contributes to the knowledge of digital mobile devices and the implications in early childhood education (ECE) for parents and teachers. This chapter describes the role of media and technology and, in particular, mobile devices in preschool classrooms. In particular, it highlights digital literacies and the role of iPads, as well as challenges when using mobile devices with young children. The chapter concludes with why we need mobile devices in early childhood education.

2

Background

Previous research has explored how children learn using media, technology, and mobile devices (Alper 2013; Aronin and Floyd 2013; Beschorner and Hutchison 2013; Dennis 2016; Learmonth 2010; Muller and Perlmutter 1984; Plowman et al. 2012). In particular, Petrina et al. (2008) suggest that researchers describe how children can communicate with video, images, and text and express themselves and have become more interactive with media and technology. Their research, and other research, continues to explore how school-aged children, ages 5 and up, interact with mobile devices. Some researchers have begun to explore how preschool-aged children learn and interact with mobile devices (Flewitt et al. 2014; Lynch and Redpath 2014; McPake et al. 2013). However, more research needs to explore how preschool-aged children are accessing and learning with devices. This chapter focuses on how children under 5 years old learn to use mobile devices.

3

Media and Technology: Increasing Use of Mobile Devices

The increased use of mobile devices in classrooms has prompted a shift in the pedagogical approach to media and technology. In the early years of microcomputers, researchers found that children preferred working at a computer with another individual compared to working alone (Muller and Perlmutter 1984). At that time, researchers suggest computers provided a focus for social interaction and further encouraged cooperation likely because a limited number of computers were available in a neighborhood or classroom, which forced cooperative sharing. As media and technology gradually became ubiquitous in children’s lives, their interaction with mobile devices became much more independent. Recent research on screen time has also suggested that the growing access to digital devices hinders social interaction and can cause detrimental effects of attention deficit disorder and other

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Fig. 2 Children creating on the iPad together

negative effects (American Academy of Pediatrics (AAP) 2014; Adams and Thompson 2016; Jordan and Robinson 2008; van Geel et al. 2014). Children can communicate through speaking, symbol recognition, and the production of written language including the use of a touchscreen or keyboards that have expanded traditional literacies (see Fig. 2). As they begin to communicate, they may or may not understand and develop cultural conventions, such as politeness, taking turns, or other social behaviors. Learning to be literate, digitally and otherwise, and the development of behaviors include interpreting signs and sense-making (Rowsell and Harwood 2015). There are many mobile devices that children access; however touchpads or tablets, and in particular iPads, have become ubiquitous in the twenty-first-century classrooms. Devices have become more portable, affordable, efficient, and prominently used. In particular, iPads are used in education more than other tablets, dominating the market at 75% worldwide (Karsenti and Fievez 2013). iPads and other mobile devices encourage increased social learning, communication and collaboration, creativity, motivation, concentration, and independence for preschool-aged children (Flewitt et al. 2014; Lynch and Redpath 2014). Even though some preliminary research suggests banning the use of these devices, as described in more detail in this chapter, we need more research, as the pervasive nature of these devices is undeniable.

3.1

Mobile Devices’ Use in Early Childhood Education (ECE)

In many instances in the past, school computers were located in the low-traffic and removed-from-play areas, while in other instances laptops and devices preoccupy children and adults in all locations of the home. Additionally, the initial adoption of

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computers was impeded by the need for constant supervision to ensure no damage would occur to these expensive devices. As mobile devices have become more costeffective and mobile, the constant need for supervision or the storage of devices in secured locations has shifted and is significantly reduced; however, numerous other problems, such as cyberbullying, have arisen. The increase and shift of mobile devices’ infiltration into classrooms has prompted a shift in the pedagogical approach to media and technology. Mobile devices have seemingly enriched ECE classrooms, which perhaps is most pronounced in Montessori and Reggio Emilia programs; however fierce debates on distinctions between values of 3D physical objects and digital media and technology within ECE remain (MediaSmarts 2013; NAEYC 2012). Researchers need to explore further impacts of digital devices, especially as newer devices and software enter the market.

3.2

Digital Literacy and Multiliteracies

As media, technology, and the use of mobile devices increasingly influence curriculum and pedagogy, students develop digital literacies, albeit of various forms. Kang (2012) compiled two definitions from FutureLab’s Digital Literacy across the Curriculum handbook and the European Information Society: • To be digitally literate is to have access to a broad range of practices and cultural resources that you are able to apply to digital tools. It is the ability to make and share meaning in different modes and formats; to create, collaborate, and communicate effectively; and to understand how and when use of digital technologies is appropriate to support these processes. • Digital literacy is the awareness, attitude, and ability of individuals to appropriately use digital tools and facilities to identify, access, manage, integrate, evaluate, analyze, and synthesize digital resources, construct new knowledge, create media expressions, and communicate with others, in the context of specific life situations, in order to enable constructive social action and to reflect upon this process (p. 1067). Definitions of digital literacy tend to derive from Gilster (1997): “the ability to understand and use information in multiple formats from a wide range of sources when it is presented via computers” (p. 1). These definitions reveal the complexities in supporting learners to become digitally literate and the difficulties in achieving digital literacy. The complexity of digital literacy also includes the use of interactive media, such as software programs, applications (apps), broadcast and streaming media, television, eBooks, the Internet, and other content to “facilitate active and creative use by young children” (NAEYC 2012, 1). On mobile devices, an app is a software program designed for a particular purpose. Apps’ purposes range from social media to banking to maps to gaming to shopping and much more. Researchers note the slow pace at which expectations for

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digital literacy are driving core curricular outcomes in schools (Dennis 2016; Neuman and Neuman 2014). In particular, the use of iPads has and has been used to “facilitate the development of emergent literacy skills” in controversial ways (Neuman and Neuman 2014, 231). For example, Dennis (2016) tested an intervention to teach verbs using an iPad app, Book Writer, and the results indicated some positive gains in expressive vocabulary. Also, Neuman and Neuman (2014) described how some apps can support the pre-alphabetic stage of reading development by understanding the meaning from the icons or symbols on the touchscreens. Children are able to use iPads when they are in preliterate stages. Even if they cannot read text, children are able to derive meaning from the symbols or icons on the touchscreens as well as configure the devices themselves. For example, a young boy cannot read text, but he was able to recognize the graphics and logo of Disney’s Toy Story app and select it to play (Learmonth 2010). Multiliteracy expands upon traditional print literacy (Alper 2013; Beschorner and Hutchison 2013) and encompasses skills of multimodality and operational skills in communication and cultural conventions (McPake et al. 2013). Additionally, apps have been created to expand on these literacies such as letter names, sounds, phonological awareness, and early writing (Neuman and Neuman 2014). The literacy apps address some of the skills identified with digital literacy. Children also communicate through speaking, symbol recognition, and the production of written language including the use of touchscreens or keyboards. Learning to be literate include interpreting signs and sense-making (Rowsell and Harwood 2015). Devices, such as iPads, can encourage this sense-making as preschoolers will poke, touch, swipe, and pretend to demonstrate their emergent multiliterate behaviors (Roskos et al. 2012). Children are in a pre-digital literacy stage. Similar to a preliteracy stage when a child learns to hold and turn pages of a book or begins to recognize letters, attributes can be attributed to a pre-digital literacy stage, for example, learning to hold the iPad, touching, swiping, or tapping, and recognizing app symbols. However, sometimes a child’s use of a mobile device at home does not always reflect in schools and vice versa. Informal or home settings continue to outpace the learning of digital literacies in school (Aronin and Floyd 2013). By the time children are entering ECE, they have had access to a range of devices, such as mobile phones, smartphones, televisions, game consoles, DVD and MP3 players, tablets, iPods, iPads, as well as desktop and laptop computers (Aronin and Floyd 2013; Plowman et al. 2012). Many researchers have encouraged the continued education of practitioners to incorporate multiple devices into their classrooms (Flewitt et al. 2014; McPake et al. 2013). However, access to devices, lack of proper training, and negative perspectives on digital devices can still contribute to the lag of digital literacies’ entrance into schools. Some literature suggests that there are deeper learning, increased motivation, more independent work, and increased confidence and curiosity through enthusiastic use of media and technology (Flewitt et al. 2014; Lynch and Redpath 2014). Many of this research seems to focus on iPads in particular, and as suggested earlier being 75% of the worldwide education market, this chapter will explore the pervasiveness of iPads in classroom settings.

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iPads

There are many mobile devices that children access; however, tablets, and in particular iPads, have more recently infiltrated classroom settings. There are over 250 million iPads sold offering over 2.2 million apps and in particular over 300,000 for children (Apple 2017; Alper 2013; Hendela 2014). In the USA, 58% of parents claim to download apps for their children, making it not surprising to see preschool and toddler apps as the most popular category in the app store, monopolizing 72% of top paid apps (Common Sense Media 2013; Shuler et al. 2012). iPads have multiple uses that may be limited in other tablet devices (Crescenzi et al. 2014; Rowsell and Harwood 2015). The features of touch in iPads are important for young children. The iPad, in particular, allows for wider ranges, more touches, and more complex sequences for touch than other tablets on the market (Crescenzi et al. 2014). For example, multiple children can touch an iPad at the same time, which is restrictive in some apps and in other devices as well. Further, iPads have recently upgraded with more accurate finger tracing than other devices on the market. As touch is essential to young children’s development, iPads’ complex touch features are less constrained than other devices. Typically, digital devices influence audiovisual levels, watching with limited interaction; however, iPads allow for a haptic dimension. Touch interfaces influence cognitive abilities, as touch is a primary form of interaction for young children and it extends their understanding (Crescenzi et al. 2014; Neuman and Neuman 2014). Even though early touch interactions may be referring to physical contact with other people, the touch interaction with iPads is still an influential part of extending understanding. Moreover, haptic perception through tactile senses takes children beyond scanning and browsing into more interactive behaviors (Roskos et al. 2012). Preschool-aged children’s fine motor skills are less developed, but they are able to use their fingers in various apps (Moyer-Packenham et al. 2015). These apps continue to help refine children’s fine motor skills. iPad devices have become more portable, affordable, and efficient (Flewitt et al. 2014; Lynch and Redpath 2014). Since iPads entered the market less than a decade ago, and more recently in schools, research is quite new, but it is rapidly occurring. iPad devices allow for material, physical, and virtual productions, as well as multiple opportunities to blend these together (Rowsell and Harwood 2015). Additionally, iPads are one of the most “cutting-edge, culturally powerful yet enigmatic technological tools” for young learners that are available (Flewitt et al. 2014, 3). Based on market trends, the influence of iPads in the classroom continues to grow, and there are many benefits in choosing to integrate iPads into current curriculum, including increased social learning, communication and collaboration, creativity, motivation, concentration, and independence. Children’s social learning fostered by communication and collaboration advances cognitive growth through social interaction (Beschorner and Hutchison 2013; Plowman et al. 2012). Children can use various iPad apps to communicate digitally and virtually and collaborate face-to-face using shared devices or virtually online. The use of iPads fostered

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communication and collaboration with peers, but also between teachers and students (Karsenti and Fievez 2013; Roskos et al. 2012). Teachers can communicate with students inside and outside of the classroom with the mobility of these devices. Moreover, iPad integration supports multiple forms of communication through various modes of media that allow oral, written, and graphic communication that enable the majority of children to participate in multiple activities that may be restrictive in other devices or low-tech options (Flewitt et al. 2014; McPake et al. 2013). Photo and video capabilities are available with easy-to-use system. For example, iMovie has many capabilities but involved many drag-and-drop features with image directions supporting the written ones. The multimodal approach encourages creative endeavors. Children use a variety of apps to create multimedia products including voice recordings, video recordings, graphics, and text (McPake et al. 2013; Karsenti and Fievez 2013). The apps allow for some or all of these features. Creativity encourages independent thinking, and the ability to produce and think on an independent level is fostered through iPad use (Flewitt et al. 2014; Lynch and Redpath 2014). Educators can use iPads to allow learners to work at different paces and styles. Children become independent users much more quickly than they did with previous devices. iPad use further inspires increased motivation and concentration for students (Flewitt et al. 2014; Lynch and Redpath 2014). As many children can manage these devices individually, they can choose their favorite apps, which increases their motivation and concentration through their own interests. Children are able to make their own choices (Beschorner and Hutchison 2013), and they enjoy working beyond skill and drill apps. Additionally, children are highly motivated with heightened concentration that allows for more advanced literacy skills and information technology skills (Flewitt et al. 2014; Karsenti and Fievez 2013). Navigation on iPads, or more generally surface or touch devices, is easier than on other types of devices (Lynch and Redpath 2014). Typically, teachers provide technical assistance when using a desktop or laptop computer, as there are multiple access points and attachments. A “simple” computer has cords and a breakable mouse. Even a “simple” laptop has many keys that can malfunction or be more difficult for children with lower-level motor skills. Further, software capabilities are more complicated on desktops and laptops. With iPads, children are able to navigate through apps and the touchscreens with minimal scaffolding, much more quickly than other devices (Flewitt et al. 2014; Karsenti and Fievez 2013; Lynch and Redpath 2014). They can touch and swipe quite simply, without the need for fine motor skills. Children are able to use iPads more independently and require less help as iPads have simple operating systems (Lynch and Redpath 2014). The simplicity of closing the app and opening the app on the iPad often resolves the problem, an action that most children can do independently (Lynch and Redpath 2014). The ease of use supports competence and increases individual motivation for children. The interface and simplistic aesthetics of iPads are abundant that allow children to move more quickly toward their potential developmental level. iPads are replacing traditional large, standalone computers in classrooms. They are portable, light, and small, with minimal buttons and simple software. However, despite some of these capabilities, there continues to be challenges with mobile devices.

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Challenges with Mobile Devices in Preschool Education

Criticisms and critiques of mobile devices are complex. For instance, the webpage for the American Academy of Pediatrics (AAP) dedicated to media and children recommends that parents and pediatricians limit screen time for children and offer non-electronic formats of entertainment, such as paper books or board games. They suggest that screen time strongly influences health and academics, but also provides access to questionable media content (American Academy of Pediatrics (AAP) 2014). The AAP’s primary recommendation is screen-free zones and to limit children over the age of 2 to no more than 1 or 2 h a day. They also recommend that children under the age of 2 should not have exposure to any media and technology, as their brains are developing and learn best from personal interactions and not screens. The AAP (2014) describes the benefits of limiting TV time and even suggests hiding the remote. One major health concern in the USA is obesity linked to increased screen time. Many studies suggest that there is a direct relationship between obesity through lack of physical activity and increased screen time (Chavarro et al. 2005; Ham et al. 2013; Jordan and Robinson 2008). Lack of physical activity has increasingly become a concern, and there have been reports describing boys who were exposed to over 3 h of screen time per day also had higher body mass index and more fast-food consumption (Ham et al. 2013). Additionally, these children were more adverse toward exercise. Girls were experiencing similar situations; when screen time was increased, their body mass index also increased (Chavarro et al. 2005). Some studies also suggest that children whose media screen time exceeded 5 h a day had the highest body fat percentage and were at risk for obesity (Jordan and Robinson 2008). Lack of sleep relates to increased screen time. Researchers suggest that lack of sleep has detrimental effects on children’s activity levels and their ability to perform well in academic settings (Gentile et al. 2014; Magee et al. 2014). Children’s total device use was significantly associated with sleep duration (Magee et al. 2014). The more screen time, the less sleep. The less sleep, the lower the energy levels and the lower the performance in school. Low energy levels and low school performance can influence self-esteem that causes emotional and peer problems. Additionally, emotional problems and poorer family functioning intensify for each additional hour of screen time beyond the recommend two (Hinkley et al. 2014). Antisocial and aggressive behaviors of children and exposure to media violence were directly linked; more exposure to screens was equal to more antisocial and aggressive behavior (Gentile et al. 2014), including peer victimization, bullying, and cyberbullying (Adams 2012; Adams and Thompson 2016; Jordan and Robinson 2008; van Geel et al. 2014). Children are “in touch with their classmates and the world differently” through a digital wireless presence in their bedrooms rather than in a “relational community of the neighborhood playground and streets” (Adams 2012, 269). Turkle (2015) states that many of us have removed ourselves from the corporeal conversation and into a digital or virtual one. The projection into a digital or virtual community has led to a high level of anonymity and cyberbullying. Children’s access to the Internet makes it

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easier to become narcissistic, anxious, antisocial, or aggressive as the anonymity and addiction is prevalent (Edwards and Pye 2011; Rosen et al. 2013). Unfortunately, many subjects of peer victimization often ideated or attempted suicide (van Geel et al. 2014). As these detrimental side effects amass, many people are required to react. Multiple news reports continue to display the advice from the AAP and further perpetuate the potential detrimental effects. However, many families are making decisions based on their family values and circumstances rather than specified AAP recommendations (Plowman et al. 2010). In academic settings, many teachers believe that media and technology, and in particular iPads and other mobile devices, are overstimulating and distracting, take away from outside play time, focus on texting over talking, and are too fast-paced (Flewitt et al. 2014; Karsenti and Fievez 2013). Further, early use of media and technology in classrooms was only for play and without a pedagogical purpose (Morgado 2008). At this point, it is unclear whether, for children, the benefits of mobile devices outweigh the disadvantages (Edwards and Pye 2011). As mobile devices rapidly reach the market, researchers can explore potential benefits of mobile devices, especially within classroom settings and, more particular, in early childhood settings.

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Why Do We Need Media and Technology in ECE?

Even though some research suggests the detrimental effects of media and technology, especially on young children, a nuanced approach to media and technology mobile device integration is slowly becoming the consensus. In particular, the AAP has revised their statement on the initial ban of mobile devices. They do recommend parents to prioritize unplugged time for infants and toddlers, but recognize that “some media can have educational value for children. . .[and] that this be high quality programming” (American Academy of Pediatrics (AAP) 2016). They continue to make positive recommendations toward Sesame Workshop and Public Broadcasting Service (PBS) programming. The AAP, Sesame Workshop, and PBS ideas reflect digital literacy definitions of helping children understand what they are seeing and having those critically reflective discussions. Similarly, some theories and traditions of early childhood learning, such as Montessori and Waldorf, recommend cautious introductions of digital media and technology (Dunn 2000; Tosco 2015). Despite some research studies, the overall health effects of media and technology on children are unclear (Plowman et al. 2010). In particular, the research describing the detrimental effects of media and technology focuses on screen time, where children are passive observers rather than interactive participants in media and technology. The inclusion of media and technology and use of mobile devices has been integrated into ECE by referring to the National Association for the Education of Young Children (NAEYC) position statement on media and technology. The NAEYC and the Fred Rogers Center support the AAP in discouraging obsessive screen use under the age of 2 as early brain development occurs; however, they also understand there may be appropriate

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times for screen use at this young developmental age (Fred Rogers Center 2014;, American Academy of Pediatrics (AAP) 2016; 2014; NAEYC 2012). For example, appropriate screen time on a mobile device would be a Skype or FaceTime call with grandparents or trying an interactive app or watching Sesame Street and participating in a Sesame Workshop. The NAEYC has developed principles to guide the appropriate use of media and technology tools and interactive media on mobile devices in early childhood programs. The NAEYC and the Fred Rogers Center are aware of concerns and, in response, developed the following position statement: Technology and interactive media are tools that can promote effective learning and development when they are used intentionally by early childhood educators, within the framework of developmentally appropriate practice, to support learning goals established for individual children. (NAEYC 2012, 5). Researchers can explore how young children use and learn media and technology to understand any short- and long-term effects. One aspect to explore is the choice of apps. How to choose appropriate apps can be difficult and time-consuming, but this selection can be supported by using the four-pillar model of Hirsh-Pasek et al. (2015). They describe how: Humans learn best when they are actively involved (‘minds-on’), engaged with the learning materials and undistracted by peripheral elements, have meaningful experiences that relate to their lives, and socially interact with others in high-quality ways around new material, within a context that provides a clear learning goal. (p. 7). Another way of choosing apps can be grouped into two categories: open and closed (Flewitt et al. 2014). Open-ended apps encourage children to participate as creators or designers constructing activities often in a no-fail environment (Lynch and Redpath 2014; Neuman and Neuman 2014). These differ from closed apps, which play explicit roles in traditional print literacy and numeracy skills (Flewitt et al. 2014; Lynch and Redpath 2014). The open-ended apps allow children to make something which is more personalized (Lynch and Redpath 2014). Research is needed to determine how apps shape children’s cognitive abilities (Neuman and Neuman 2014). It is essential to select media and technology on mobile devices that “allow children opportunities to discover, make choices. . .to explore, imagine and problem-solve” (Beschorner and Hutchison 2013, 17). In ECE, these choices relate to preexisting program goals. The school goals and program styles are standard in each program. With the recent influx of mobile devices, a number of ECE centers are attempting to include media and technology into their programming. A variety of program styles exist that ECE centers follow, including HighScope, Reggio Emilia, Head Start, Child Care, Waldorf, and Montessori or a blended system using parts from several programs. These programs posit varying aspects of learning (Table 1). A pedagogical purpose to media and technology integration should align with ECE goals (Aronin and Floyd 2013; Morgado 2008). For example, Reggio Emilia practices include technology and distributed cognition that are integrated into play (Alper 2013). Other programs have many possible places for mobile device integration into their features. HighScope programs, for example, could integrate media and technology with mobile devices into their active learning goals, Waldorf could

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Table 1 ECE program features, teacher’s role, and theoretical base Program HighScope

Reggio Emilia

Child care

Head start

Main features • Plan-do-review teachinglearning cycle. • Emergent curriculum – Not planned in advance. • Children help determine curriculum. • Key experiences guide the curriculum in promoting children’s active learning. • Emergent curriculum – Not planned in advance. • Curriculum based on children’s interests and experiences. • Project-based curriculum. • Active learning. • Thousand languages of children – Symbolic representation of work and learning. • Atelier (art/design studio). • Comprehensive health, social, and educational services. • Program quality determined by each program. • Each program has its own curriculum. • Curriculum and program outcomes determined by performance standards. • Fully sponsored and funded. • Broad spectrum of comprehensive services, including health and nutrition, administrative support, and parent involvement. • Parents and the community play a key role in program operation. • No national curriculum – Created at a local level.

Teacher’s role • Plans activities based on children’s interests. • Facilitates learning through encouragement. • Engages in positive adultchild interaction strategies.

Theoretical base • Constructivist. • Piaget. • Dewey. • Vygotsky.

• Works collaboratively with other teachers. • Organizes rich in possibilities. • Acts as a recorder for the children, helping them trace and revisit their words and actions. • Atelierista (teacher trained in the arts).

• Constructivist. • Piaget. • Dewey. • Vygotsky.

• Provides care and education for the whole child. • Provides a safe and secure environment. • Collaborates with and involved families.

• Whole child. • Maturationist.

• Teaches and provides for all children’s developmental areas (social, emotional, physical, and cognitive). • Provides programs that support needs (socioeconomic, cultural, and individual). • Involves family and community in all parts of the program.

• Whole child. • Maturationist. • Intervention approach to addressing child and societal problems.

(continued)

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Table 1 (continued) Program Waldorf

Main features • Whole child – Head, heart, and hands – Is educated. • Arts integrated into all curriculum areas. • Study myths, lores, and fairy tales to promote imagination and multiculturalism. • Learning is doingmaking and doing. • Learning is noncompetitive. • Developmental phases of each child are followed.

Montessori

• Prepared environment supports, invites, and enables learning. • Children educate themselves (self-directed learning). • Sensory materials invite and promote learning. • Set curriculum regarding what children should learn (stay close to Montessori ideas). • Multi-age grouping. • Students learn by manipulative material and working with others. • Learning takes place through the senses.

Teacher’s role • Acts as a role model exhibiting Waldorf values. • Provides an intimate classroom atmosphere full of themes for caring about the community and the natural and living world. • Encourages children natural sense of wonder, belief in goodness, and love of beauty. • Creates a love of learning in each child. • Main teacher stays with the same class from childhood to adolescence. • Follows child’s interests and needs. • Prepares an environment that is educationally safe and interesting. • Direct unobtrusively as children engage in small group or self-directed activities. • Observes, analyzes, and provides materials and activities appropriate for the child. • Maintains regular communications with the parent.

Theoretical base • Anthroposophy. • Rudolf Steiner. • Whole child.

• Respect for children. • Whole child. • Active learning. • Absorbent mind.

Note: Adapted from Edwards (2002) and Morrison (2006)

incorporate media and technology with mobile devices into their doing-makingdoing ideals, and Head Start integration could be in teaching children of all developmental levels. These ECE programs have many options in aligning media and technology using mobile devices pedagogically with their key goals. Even though some parents reminisce and romanticize a “golden age” of childhood surrounded by inspiring, developmental, physical media and technology, this was never the reality for children in most countries of the world (Plowman et al. 2010). Children now enter schools within curricula and policies framed for the twenty-first-century learning (Beschorner and Hutchison 2013), and parents are striving to find a balance with all of these plugged in and unplugged activities.

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Conclusion and Future Directions

As concerns and fears regarding antisocial and aggressive behaviors and the influence of media and technology through increased mobile device use on young children accumulate, there is a need for future research. Research can provide findings and insights into attributes of media and technology in ECE. In particular, research can focus on the positive, or prosocial, behaviors associated with media and technology and mobile devices rather than the negative, aggressive, or antisocial behaviors. Research could focus on changes to policy and practice related to early childhood and the use of mobile devices. This chapter described children in their early states of socialization and learning in ECE classrooms. Notable is the rapid rate at which media and technology with mobile devices integrate into classrooms, especially with the emergence of tablets or iPads into the education market (Apple 2017; Childwise 2016; Common Sense Media 2013; Karsenti and Fievez 2013). Researchers do not have an adequate understanding of how new devices, such as iPads, shape behaviors. An empirically based understanding of how these elements interplay will have direct consequences for early intervention, education, and parenting.

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Monica McGlynn-Stewart, Nicola Maguire, Emma Mogyorodi, Leah Brathwaite, and Lisa Hobman

Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Pre-implementation High . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Early Reality Check . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Phase 3: Crawling Out of the Hole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Phase 4 Continued High: Exploring, Sharing, and Celebrating . . . . . . . . . . . . . . . . . . . . . . 4.5 Year-End Fatigue: What Now? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Flying High Again: Beginning of Year Two . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Cruising Along . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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M. McGlynn-Stewart (*) School of Early Childhood, George Brown College, Toronto, ON, Canada e-mail: [email protected] N. Maguire · L. Brathwaite · L. Hobman George Brown College, Toronto, ON, Canada e-mail: [email protected]; [email protected]; [email protected]; [email protected] E. Mogyorodi Ryerson University, Toronto, ON, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_121

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Abstract

This 2-year research study examined 27 kindergarten educators’ professional learning experiences using open-ended tablet applications to support children’s (aged 3–6 years) oral and visual literacy learning. In contrast to typical professional development initiatives, the educators in this study were treated like professionals with control over how the apps would be integrated into their daily pedagogical practice. The research team functioned as technical advisors, observers, and resource providers. Research team members ascertained educators’ levels of confidence, experience, and interests through regular interviews, questionnaires, and biweekly classroom visits. Annual workshops provided opportunities for educators to reflect and share insights. Over the 2 years, the educators experienced a series of highs and lows in response to their particular contexts. While they were initially confident about introducing the apps in their classrooms, technical and environmental challenges soon led to frustration. With time and ongoing support, educators worked through a series of challenges to develop deeper understandings of the technical and pedagogical issues related to digital technology (DT) integration. They came to appreciate the learning and teaching benefits of the apps, which provided them with additional tools to support children as they created, documented, and reflected on their learning. Moreover, the educators began to use the children’s digital work for assessment and planning purposes. This study illustrated how teacher learning in DT integration is complex and nonlinear, with different competencies and needs for support coming to the fore over time.

1

Introduction

It can be difficult for early childhood educators to know how and when to incorporate digital technology (DT) into their literacy programs for young children. They are faced with contradictory messages about DT use with young children. Some research reports that it can lead to children being solitary, sedentary, and passive (e.g., NAEYC 2012; Radesky et al. 2015; Council on Communication and Media 2016), but also that it can create opportunities for children to be creative problem solvers, to work collaboratively, and to be ready for our technology-driven society (e.g., Rowsell and Harwood 2015; Falloon and Khoo 2014). Educators are required to teach literacy in ways they did not experience as students and most likely did not learn about in teacher education programs (Chen et al. 2014; Darling-Hammond 2006a, b; Kirkwood 2009). Professional learning opportunities for early childhood educators in this area are limited. Educators learn little in their pre-service education programs, and the few opportunities for in-service learning are often brief and lack the in-depth knowledge and skills needed to integrate DT into their classroom programs successfully.

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This Canadian research study was funded by a federal research grant that focused on partnerships between colleges and social agencies (including public school districts) for the purpose of social innovation. Our college and a local school district began our partnership in 2015. The partnership came about due to a joint interest in investigating the learning possibilities of digital technology for young children. This study is an outgrowth of that partnership. This study proposed a flexible and responsive approach to teacher learning in DT. The research team was comprised of a professor in a local early childhood education pre-service program and her current and former students. The research team and the early childhood educators participating in the study, some of whom were graduates of the same program, worked together to design many aspects of the study. The early childhood educators working with kindergarten children in two school districts near the college were given iPads loaded with open-ended apps and ongoing support but were encouraged to use their professional judgment to guide their practice. The educators let the researcher know what types of supports they needed as the study unfolded. The research team was responsive to the needs of the children and teachers over a 2-year period, working with app developers, creating tip sheets, and providing learning opportunities as needed. The research team and the participants together discovered that teacher learning is complex and nonlinear, with different competencies and needs for support coming to the fore over time. This chapter reports on the first 2 years (2015/2016–2016/2017) of a 3-year research study examining the use of open-ended iPad apps to support young children’s literacy learning in 14 full-day kindergarten classrooms (ages 3–6) in Ontario, Canada. Literacy in this study is defined broadly, as meaning-making in multiple forms including visual, oral, print, and digital. Literacy activities in these classrooms are often social and collaborative in nature and integrated into play and content areas such as math and science. The curriculum for kindergarten in Ontario, The Kindergarten Program (Ontario Ministry of Education 2016), advocates a playbased approach to learning and teaching. It states: Play is a vehicle for learning and rests at the core of innovation and creativity. It provides opportunities for learning in a context in which children are at their most receptive. Play and academic learning are not distinct categories for young children, and learning and doing are also inextricably linked for them. It has long been acknowledged that there is a strong link between play and learning for young children. (Ontario Ministry of Education 2016, p. 18)

The classrooms in the study were situated in two large urban school boards in Ontario. The children come from families that are culturally, linguistically, and economically diverse. Children enter the kindergarten program in the year that they turn 4 and stay for 2 years. The iPad apps used in this study, 30 Hands and Explain Everything, are open-ended. They offer a range of visual recording options including drawing, photo, and video functions, as well as audio recording. There is no content other than a few background scenes, and the apps are not designed to teach any specific skills. These open-ended apps complement a play-based approach to learning and teaching. All children were able to explore and document their

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learning in ways that met their individual learning needs through the multimodal tools provided in the iPad apps. The research question that governed this study was: How do early childhood educators in a DT research project experience professional learning?

2

Literature Review

Several recent studies describe how mobile DT, such as smartphones and tablets, are being used to support young children’s literacy learning at home, to assess understanding, and to create a school-to-home link (Blagojevic et al. 2012; Neumann 2016; Radesky et al. 2015; Wong 2015). See ▶ Chaps. 46, “Mobile Devices for Preschool-Aged Children” and ▶ 49, “1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation.” While some studies have examined the use of eBooks, games, digital drawing pens (Lee et al. 2017), augmented reality toys (Yilmaz 2016), and learn-to-read apps, studies that report on the use of open-ended iPad apps in school environments are emerging (e.g., Fleer 2014; Herro 2015). In fact, several studies (e.g., Rowsell and Harwood 2015; Falloon and Khoo 2014) illustrate how literacy acquisition, expression, development, and consolidation are being redefined through DT. The increasing complexity of how we communicate as a global society means that we need highly skilled teachers who have a broad definition of literacy, can incorporate digital technologies (DT) into their learning programs, and recognize that literacy is rapidly evolving. However, currently pre-service and in-service professional learning offer little guidance on the appropriate use of DT in early childhood programs. As a result, many early childhood professionals report uncertainty about how and when to use DT in their early childhood classrooms (Beschorner and Hutchison 2013). For example, although there are hundreds of mobile applications claiming educational value, few reflect principles of constructivist learning necessary for young children (Goodwin and Highfield 2012). Without a secure foundation of knowledge to evaluate and integrate technologies, early childhood educators may struggle to incorporate DT. Early childhood educators need better support at both the pre-service and in-service stages. While the need for pre-service support has been identified (Darling-Hammond 2006b), little progress has been made to achieve that goal. Research offering pre-service guidance is not always delivered in an effective manner. Laffey (2004) found that even when pre-service early childhood teachers (ECTs) attended an educational institution with a mandate for integrating technology, they found little value or use for DT in their practice. However, when ECTs had practicum experiences involving successful DT use, they saw more potential for using the technologies with young children (Laffey 2004). By 2016, Brown et al. found that DT was more appealing to pre-service ECTs, but these educators continued to struggle with how to use DT in developmentally appropriate, child-centric ways. Without explicit guidance and practical experience, pre-service ECTs defaulted to using DT solely for documentation or “didactic

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instruction” (Brown et al. 2016, p. 179). The field needs further research to determine which supports effectively prepare pre-service early childhood professionals to use DT in their classrooms. There is also a growing recognition of the need for ongoing professional learning opportunities for in-service early childhood professionals. Parette et al. (2010) caution that failure to pursue DT-supported education may result in educators “missing the boat” (p. 335). While some institutions capitalize on the potential benefits of DT, they may only provide digital materials without accompanying pedagogical or technical support. Blackwell et al. (2014) highlight the need for further support, noting that “technology in and of itself may not have the inherent power to change teaching and learning practices” (p. 83). Ertmer and OttenbreitLeftwich (2013) likewise argue for the need to change the “focus from technology integration . . . to technology-enabled learning” (p. 175). Implemented alone, DT tools are insufficient; they must be accompanied by intentional strategies to be effective. Due to demand for DT support in early childhood settings, researchers have begun to experiment with different models of professional development. Keengwe and Onchwari (2009) designed an 8-week summer intensive, which involved a series of workshops to help early childhood teachers plan appropriate DT curriculum. While they found some improvements in the teachers’ planning abilities, none of the participants reached exemplary levels; this was possibly due to the brief nature of the program (Keengwe and Onchwari 2009). Chen and Chang (2006) tested a longer-term professional development program that aimed to support the “whole teacher” (para. 1), including their “attitudes, skills and knowledge, and practices” (para. 1). This approach was more effective than the short-term workshop experienced by the control group (Chen and Chang 2006). Fisher et al. (2012) also recommend long-term professional development opportunities that provide guidance for curriculum planning in addition to pedagogical implementation. Other researchers suggest that professional development models must target particular skills to be most effective. Blum et al. (2009) identified four competencies necessary for effective and sustainable technology practices in education: 1. The ability to use the technology (operational competence – how does the app work?) 2. The ability to apply the technology in the classroom (functional competence – storing, charging, displaying, class management, sharing) 3. An understanding of how the technology fits into the curriculum (curricular competence – how does it support learning?) 4. The ability to use effective instructional strategies (instructional competence – how do I teach with it?) (Blum et al. 2009) Educators demonstrate these competencies after participating in user groups supported by ongoing professional development (Parette et al. 2010; Keengwe and Onchwari 2009).

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While developmental skill-based models of professional development remain popular, other researchers note the limitations of this approach. Laffey (2004) explains that: Teachers’ adoption of technology has been most frequently treated as a linear movement from an entry level of developing awareness through appropriation and innovation, in which teaching roles and practices are transformed (CEO Forum 1999; Dwyer et al. 1991). The sociocultural framework suggests that the path is not simply linear and that tools may be mastered but not appropriated, appropriated for some roles in some contexts while not in others, and that it may be more useful to see appropriation as not simply a psychological or individual stance but rather a stance within a context. (Laffey 2004, p. 363)

Pacini-Ketchabaw et al. (2015) also challenge the assumptions made in traditional professional development, including the notions that it is a neutral, passive, and even “linear and sequential” (p. 67); that the educator is a stable, unchanging subject; and that change occurs solely in isolated and pre-planned increments. The current study offers an opportunity to both explore and challenge these models of professional development.

3

Methodology

This chapter reports on the first 2 years (2015/2016–2016/2017) of a 3-year study of 14 kindergarten classrooms in Ontario as they used open-ended tablet apps (30 Hands and, to a lesser extent, Explain Everything) in their play-based programs. Each classroom of participating teachers received three iPads used most often during open-ended activity time, outdoor play, and more focused literacy activities. Most classrooms had two educators (27 educators in year 1 in total and 25 educators in year 2 in total). The educators, registered early childhood educators (RECEs) and Ontario Certified Teachers (OCTs), participated in interviews before the study began to determine their experiences with DT and their attitudes toward using DT with young children. At the end of the first year, each teacher again participated in an interview to ascertain if their attitudes toward using DT with young children had changed and to learn about what they perceived to be challenges and benefits of using the tablet apps in their programs to support literacy learning. At the beginning of the second year, they completed a questionnaire on similar topics, and at the year’s conclusion, teachers participated in an interview for the last time. Interviews were recorded and transcribed. All educators attended a focus group/workshop each year. During the focus group/workshops, the educators were asked about the challenges and learning opportunities they and the students were experiencing. They then reviewed their students’ digital slideshows on their classroom iPads and shared their evaluation of them with their peers. Finally, they participated in technical and pedagogical challenges to increase their levels of comfort and familiarity with the apps. Detailed notes were taken during the focus groups. Members of the research team observed the teachers and children biweekly using participant observation. Research assistants (RAs) were all qualified early years

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educators or educators-in-training. Under the classroom teachers’ direction, RAs also worked with small groups of children during these biweekly visits to help with technical issues and to model supporting students as they used the apps. Students had individual accounts within the iPad apps where they could archive their slideshows. Samples of student digital slideshows were collected and analyzed. All children’s names are pseudonyms. The research design was emergent. While we gave the educators some basic training on the use of the apps, we did not train the educators on specific pedagogical strategies nor did we ask them to teach specific skills. We observed and listened to the educators and children in order to provide the support that they needed. For example, when the app 30 Hands proved problematic at first, we worked with the app developer to change the app to make it easier for young children to use. In addition, when the educators asked for specific technical or pedagogical information, we created and provided those resources.

4

Findings

4.1

Pre-implementation High

Interviews conducted with the educators prior to the implementation of the project revealed that there was an overall positive attitude toward using the open-ended iPad apps in their classrooms. When asked about the degree to which they felt DT has the potential to support literacy learning for young children, 96% of the educators responded that it had a “good” or “great” potential. When considering the ways DT may be useful as a classroom support, one educator stated: I think I would benefit from it immensely just in terms of my relationship with the kids, in being able to help them, being able to guide them, and keep them engaged in something that’s relevant in their world now. (Educator, Year One)

Evidence indicates that using DT in the classroom was pertinent to young children and educators through supporting their professional practice. Additionally, there was a high level of comfort among the educators when asked about their ability to implement DT effectively into their classroom teaching. Pre-implementation interviews illustrated that 73% of the educators in the study felt either comfortable or very comfortable using DT for teaching literacy to young children. They were eager to begin the project and expected that it would be quite straightforward, as illustrated in the following quote: Once they have access to them [the apps] and they’re free to do whatever they want and explore, they will become more confident and we can direct them with the right usage. They will be prepared to be alone with the device. (Educator, Year One)

Participants may have reported high self-efficacy due to their own use of, and proficiency with, DT in their personal and professional lives. Many of these

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educators were already using computers, iPads, digital projectors, and digital cameras in their classrooms. However, the use of these DT devices by their students was very limited. This prior experience and knowledge, coupled with the excitement related to having new devices and added classroom support from the researchers, contributed to their readiness and comfort to engage with a DT project in their kindergarten classrooms.

4.2

Early Reality Check

While this high level of self-efficacy was beneficial to the launch of the project, it was soon evident that both the educators and researchers underestimated the multiple and complex elements that implementing open-ended iPad apps in kindergarten classrooms entail. Many of the early challenges were related to technological issues, some of which were due to glitches in the free version of the first app that was first introduced, 30 Hands. Furthermore, the app had appeared simple upon the first glance; however some children required significant adult support while they became familiar with the various features and the multiple steps required to navigate within the app. In the context of a busy kindergarten classroom, the educators were not always able to dedicate the one-on-one time required for the type of support the children needed. While they were appreciative of the individual and small group support the research assistants were able to provide during biweekly classroom visits, it was apparent that many children required consistent and ongoing assistance to learn how to operate each of the features within the app before they were prepared to engage with it independently. It quickly became clear that routines to promote the integration of the iPads into the classrooms would be necessary to ensure sustained and positive experiences for the children and educators. Beyond trying to arrange for the one-on-one and small group support for the children, educators needed to consider how and when to charge the device batteries during a busy day and in classrooms with limited electrical outlets. Furthermore, educators identified social challenges related to the iPad apps. Children’s excitement and interest in the new digital tools contributed to disputes related to turn-taking and sharing with their peers. Children were enjoying taking photographs and drawing simple pictures on the iPads, and this made it challenging for them to hand the device over to another child at the end of their turn. Additionally, educators expressed worry that the novelty of the iPads meant some children were less likely to engage with the other materials in the classroom. Overall, these concerns, in addition to the time and planning required to support effective use of the iPad apps, created problematic situations for the educators. The educators’ self-efficacy, which had initially been quite high, was disrupted by the many challenges they faced. This led them to question themselves and the value of the technology itself. The researchers found that their role at this stage encompassed more troubleshooting than observing, as they worked with the educators to problemsolve the multifaceted issues.

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Fig. 1 Alicia’s drawing from this study

Drawing on the four competencies’ model of professional learning in DT presented by Blum et al. (2009), it became apparent that proficiency in each of the competencies (operational, functional, curricular, and instructional) encompassed a number of factors that were neither linear nor static. The initial excitement and desire to “get to work” that can often accompany a new project appeared to contribute to a simplistic view that it would be quick and easy to attain basic competency. The educators and researchers were unaware of the fluid and cyclical nature of the process of integrating DT into the classrooms. During the first 6 weeks, there were many unexpected challenges that arose for the educators, the children, and the research team. The primary focus during this time manifested in the operational and functional competencies identified by Blum et al. (2009). The need for immediate working knowledge of the apps and routines and procedures for introducing them into the classroom took precedence over a deeper examination of curricular and pedagogical issues. It became clear that the DT integration process was not as simple as it may have originally seemed. In spite of the challenges, the children were learning to use the open-ended app in basic ways such as drawing with a single color and taking photographs. In order to create the slide depicted below as in Fig. 1, Alicia (age 4) had to open the app, choose the blank slide option, choose the drawing tool, and create the drawing with a finger.

4.3

Phase 3: Crawling Out of the Hole

Despite the early hurdles in the first 2 months of the year, educators and the research team persisted and begun to devise strategies throughout the fall. To address structural challenges such as limited space to keep the iPads powered, educators were provided with cube-shaped outlet extensions, which allowed for charging multiple iPads concurrently. Charging stations (depicted in the photo above) helped educators to make the most of the limited space available in their classrooms. Educators also began formulating consistent routines to ensure that the iPads were

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Fig. 2 Teaching mobile devices

charged and ready for action. Locked storage spaces kept the devices safe when the educators were not present (Fig. 2). Technical glitches were an ongoing source of frustration for adults and children alike. These were met with a sense of determination and a willingness to problemsolve at this point. The research team took on the role of technical support, helping educators reboot the devices when there were minor glitches and frozen apps. As educators came to understand the apps more, they became more adept at navigating the many features provided without as much reliance on the research team. While social challenges were difficult at times, educators established routines around sharing and turn-taking to help the children self-regulate. For example, some educators divided the children into three groups corresponding to each of the class’ three iPads. Others set time limits to ensure all interested children could get a chance to use the iPad that day. Educators also helped children learn to ask permission before taking photos or videos of others. Another early challenge was children’s tendency to explore and draw over their peers’ files. To address this challenge, educators helped children to respect others’ digital work in the same way that they would respect a physical drawing. With the help from their educators, children quickly adapted to these expectations. One educator recalled: [Children] were actually really mature using the iPads, more than I expected. I was really nervous about them having the iPads to begin with. Like we talked about the rules. ‘Make sure you are careful.’ But you wouldn’t believe how responsible they actually were with the iPads. So they took ownership of their work when they were using them. They let other kids use it if they were having their turn. They would wait for their turn. There was no fighting, which I expected to happen. They knew their colour group. They knew if somebody was using it then they would ask for a turn, wait, and they were really excited about seeing other people’s work as much as their own. (Educator, Year One)

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As educators gained experience facilitating digital activities, their understanding of pedagogical strategies shifted in response. Many experimented with making the iPads easily accessible to children by strategically placing the devices near intriguing table activities. Furthermore, educators observed how children interacted with the iPads and used these observations to inform future curriculum planning. There were several factors contributing to the educators’ ability to strategize those early challenges. For one, educators had built enough operational and foundational competence (Blum et al. 2009) with the apps that they were able to increase their sense of self-confidence and self-efficacy. The research team’s biweekly visits also contributed to educators’ understanding, since educators were receiving frequent, ongoing support and modeling. Another factor was seeing firsthand how children were demonstrating deep literacy learning through their technology-facilitated explorations. Not only were children learning skills themselves, but they were also taking on leadership roles to support their peers. One educator remarked: [I]t was just really positive to see that they were so proud of what they could do. And the way that even the ones that at the beginning couldn’t even navigate it, couldn’t figure how to work the app they were just like figuring it out and then teaching other kids. So I really like to see the partnership and the teamwork that was happening, they were really supporting each other. (Educator, Year One)

Finally, educators were more motivated to strategize solutions when they saw the potential value of the apps and their pedagogical applications. Through discussions with the research team and observations of children in their own classes, educators developed an increased awareness of how technology supported literacy teaching and learning. While operational and functional competencies continued to be present at this stage, curricular and instructional competencies became more prominent (Blum et al. 2009).

4.4

Phase 4 Continued High: Exploring, Sharing, and Celebrating

The winter and early spring brought a period of excitement and more in-depth exploration of the apps. The slideshow above is an example of the more complex work the children were creating during this time. For this slide, Jaspreet (age 5) documented a structure he had made by photographing it and then labeling it using the tools in the app 30 Hands. He used phonetic spelling to describe what he had built, “Des is a letalcassol” [This is a little castle]. Documenting structures made during open-ended playtime was a popular use of the iPad apps during this period. This slide represents far more technical skills than the drawings the children were making earlier in the year, but also a more complex and detailed representation of the child’s thinking. The children in the project moved beyond experimenting with what the apps could do, to beginning to use the tools within the app to represent ideas and images that were important in their world (Fig. 3).

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Fig. 3 Slide made by students

A focus group/workshop in the early spring of the first year brought heightened enthusiasm for the project. Educators from multiple sites were brought together to share their joys and frustrations, which enabled collaborative sharing and learning. Educators helped each other problem-solve common issues from each of their sites, keeping an open mind and exercising patience in the face of challenges. The opportunity to share examples from their own classrooms contributed to an increased sense of pride on the part of each of the educator teams. As well, hearing about similar challenges from other sites helped educators realize that they were not alone in their struggles. They began to view challenges optimistically, realizing that it was simply part of the learning process for everyone. Within this community of learners, educators felt a sense of agency and collaboration. Looking back on this focus group/workshop 1 year later, an educator commented: I know the workshop was really good. Listening to how, and seeing how, other centres put the program to use is really neat, ‘cause all of our minds work differently, it’s kind of like the children. We all think differently, and seeing how they’re able to put the program to practice, and put it into use, then it’s – ideas that we can incorporate. (Educator, Year Two)

Factors influencing this high point in the project included the focus group/ workshop itself. It provided educators with time for support, learning, comfort, and reflection as they shared examples and worked together through challenges. Furthermore, the focus group/workshop gave the educators a chance to play and experiment with the technology in a concrete way, which inspired exploration of the device’s possibilities. While the educators were already creative, collaborative, and problem solvers in other areas of their programs, the focus group/workshop provided a safe environment for them to apply their professional knowledge and skills to the area of digital literacy learning.

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Year-End Fatigue: What Now?

The end of the school year in late spring brought some unexpected challenges. The novelty and initial excitement around the iPad apps appeared to have worn off. The educators and the children were less enthusiastic about the iPad apps, and the children were using them less frequently. When they did use them, the children seemed to have plateaued. Once they had discovered how to use the visual and auditory tools within the apps, they seemed to lose interest in continuing to use them as thinking tools, either leaving them sitting on the counter or using them in silly ways. This may have been due to end-of-year fatigue or uncertainty on the part of the educators and children about how to proceed once basic proficiency had been reached. Many children began trying to exit the open-ended apps to access other apps on the iPads that were more game-like (Fig. 4). During the interviews at the end of Year One, educators reported that they felt that they had needed some new programming ideas for the apps. Many said that they were comfortable supporting the children in the basic functions of the app, and in encouraging them to document their work, but they were ready to move on. As the educator below puts it, she had “gotten into a rut” and needed “creative ideas”: I definitely would like to move it from being a piece of furniture in my room to more of a vital part of my room. And I would like more support for creative ideas . . . because I kind of felt by the end I had gotten into a rut, like we just put it out and reminded them to document what they were doing. There’s got to be other things I could do with it, that I maybe hadn’t thought of. (Educator, Year One)

She recognized that the iPads, which had been a source of great excitement at the beginning of the year, had become merely “a piece of furniture.” Like the educator below, she recognized that she needed to try new strategies:

Fig. 4 Student’s work at the end of the year

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I think maybe I need next steps for it because I feel like we’ve gotten to the point of ‘let’s document and share it.’ I want to figure out another way that I can use the app besides maybe just documenting their projects, so if there are other suggestions of how to use it, that will be good. (Educator, Year One)

Both of these educators, and many others, asked for a workshop, technical tip sheets, and teaching ideas in the following year to help them to expand the use of the iPad apps in their programs. By the end of the first year, both the children and educators were feeling quite comfortable with the basic functions of the apps (operational competency) and the storing, charging, and sharing routines (functional competency). The educators reported that the apps were supporting the children’s literacy learning and development, particularly their oral literacy (curricular competency), but they sensed that the apps held a greater capacity to support their students’ learning than they had yet been able to realize. They recognized that what was needed next were resources to expand their repertoire of DT teaching strategies (instructional competency). Earlier in the year, the strategies that were in place (e.g., free exploration) were appropriate and sufficient for educators and children to learn how to use the apps, but now they needed more complex teaching strategies to support more complex use of the apps.

4.6

Flying High Again: Beginning of Year Two

At the beginning of the second year, the educators were very positive about the iPad apps for both teaching and learning. According to a questionnaire administered early in the year, 87.5% believed that they had the technical knowledge they needed to use the app 30 Hands in their kindergarten programs, and 75% reported that the app fits their image of “best practice” for literacy teaching and learning in kindergarten. However, in keeping with their interviews the previous spring, only 62.5% felt able to plan effective literacy activities with the app. In response to the educators’ request for more pedagogical leadership from the research team, early in the year, we held a half-day focus group/workshop. Whereas in the first year, the focus group/workshop was largely devoted to listening to the educators’ reflections on their students’ learning and their own learning and teaching, in the second year, we introduced technical guides, tip sheets, and teaching ideas for both indoor and outdoor learning experiences. In addition, we challenged the educators to work in teams to use a variety of tools within the apps to create their own slideshows. At this stage in the project, the children were broadening and deepening their use of the iPad apps. The following slide is an example of this more extended exploration. This visual is a slide Elia (age 5) made by choosing a space background and then adding her own planets and spaceship (Fig. 5). As she dramatically describes her creation in her voice-over narration, she becomes enthralled in her own story. The educators had asked for more teaching strategies (instructional competence) at the end of the first year, but in order to facilitate more complex use of the apps, they

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Fig. 5 Student’s work by Elia

needed to circle back and deepen their technical knowledge (operational competence). This, in turn, led to a more sophisticated understanding of how the apps could support student learning (curricular competence). To a lesser degree, they also modified their routines around turn-taking and the time they made the iPads available (functional competence) in response to the students’ increased comfort with the iPads. A number of factors led to the second year of the project beginning more smoothly than the previous year. First, educators had a year of experience under their belts. Second, half of their students were returning for the second year of the 2-year kindergarten program and could act as peer mentors to the new children. Finally, the focus group/workshop experience, including the technical and pedagogical resources they had requested, gave the educators new ideas and renewed enthusiasm for using DT in their programs.

4.7

Cruising Along

The second year continued to progress smoothly, with only a few minor challenges occasionally surfacing. When these obstacles did arise, it seemed the educators, children, and researchers experienced less anxiety. Their previous experience led them to be more open to experimenting with a range of strategies, both pedagogical and technological. The educators, children, and researchers were benefiting from renewed confidence and comfort in their roles. Many of the behavioral challenges observed earlier in the project lessened in the second year. With increased integration into the daily routines of the classroom, the children’s worry over getting a turn with the iPads reduced. Children appeared to view the iPads as another learning material. Sharing and turn-taking happened in more child-directed ways, with some children establishing and managing their own time-keeping systems and sign-up sheets. While some classrooms were still following the previously adult-determined methods for turn-taking, the use of timers and need for educators to police the equitable sharing of the iPads no longer appeared to

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Fig. 6 Student’s work by Omar

be a concern. Having time to become comfortable with the apps’ various tools, coupled with the educators’ deeper understanding of the curricular possibilities of this DT, contributed to the children producing more interesting and complex work. Many children had become comfortable with the basic features of the app and had moved beyond drawing simple pictures and taking photographs with the app. They were now producing drawings, videos, photographs, and audio recordings that included many forms of oral, visual, and print literacy. Some of these were represented by narratives the children had created, such as detailed documentation of classroom experiences (e.g., a series of photos documenting a melting snow that had been brought in from the playground and carefully choreographed and rehearsed dance videos) and short stop-motion animation videos. The two slideshows below illustrate the development of one child from the first year of the project to the second. In the first year, Omar (aged 4) created a simple drawing on one slide depicted below (Fig. 6). In the second year, he continued to explore drawing human figures but produced seven separate slides that when played together as a slideshow became a stop-motion animation video of two figures playing ball, depicted below. The researchers and educators had not realized that a stop-motion video could be produced this way and had certainly not taught the children how to do so. By the middle of the second year, Omar and many other children were planning and producing digital creations that went far beyond what was expected. This progress was recognized and appreciated by the educators, as one said: ‘Seeing their growth from that free exploration to making the videos, taking the pictures, documenting and even interviewing the other kids. It has been such a growth with leaps and bounds.’ (Educator, Year Two) Furthermore, children who were now in the second year of the project were able to support their younger peers who had just joined the class and who had less experience using the app (Fig. 7). This not only helped to alleviate some of the challenges related to one-on-one adult support but also provided valuable peerteaching opportunities for the older children. As one educator stated: They work in group sometimes, so the [older children] take the leadership to teach the [younger children] what they can do – instead of us. And I think getting that information from their peers is way more authentic than when they get it from us. (Educator, Year Two)

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Fig. 7 Student’s work by Omar in the second year

Of course individual children and educators were at different levels of interest and skill with respect to DT in the kindergarten programs. However, the open-ended nature of the apps supported the children, and the emergent design of the research project supported the educators in ways that were flexible and responsive to their needs. This had proved useful in meeting the operational and functional competencies that had been primary concerns in the first year and also in supporting curricular and instructional competencies as the project progressed. Interviews at the end of the second year provided an opportunity for reflection. One educator expressed it this way: I will be very honest. In the beginning . . . I would have never given the iPads to the kids if this project was not there. I would have been so hesitant and apprehensive. What if they press the wrong button? I think the support from [research assistants] made me feel like, ‘okay whatever happens they will be able to fix it. . .’ It was a learning curve for us as well. So now, I mean we are very comfortable using them. (Educator, Year Two)

The educators and researchers had become stronger in all four of the competencies and were once again experiencing high levels of self-efficacy. As a result, they were able to more clearly see the value of using these open-ended apps to support young children’s literacy learning in their classrooms (curricular competency). However, at the end of the second year interviews, they were asking for another focus group/workshop with more in-depth technical guidance and more curriculum ideas and teaching strategies. Once again, a greater appreciation for the curricular and instructional competencies required to more fully and meaningfully integrate DT into their programs was leading them back to a desire to strengthen their operational competency (Blum et al. 2009).

5

Discussion

The first 2 years of this study revealed the complexity of DT integration into kindergarten classrooms on many levels: technical, structural, social, and pedagogical. In keeping with results from recent research (e.g., Blackwell et al. 2014; Parette et al. 2010; Ertmer and Ottenbreit-Leftwich 2013), it was neither quick nor easy to navigate teaching and learning with DT for the children, the educators, or the researchers. Rather than moving through a series of steps to a predetermined goal,

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the amount and complexity of DT use were influenced by many contextual factors, and were enabled by the longitudinal nature of the study, as found in earlier studies (e.g., Chen and Chang 2006; Fisher et al. 2012). The four competencies in the model proposed by Blum et al. (2009) were clearly in evidence during the 2-year period of DT integration, but the educators’ movement through the competencies was neither linear nor sequential. Early in the project, the focus was on operational competency, ascertaining how this technology worked with functional competency, determining ways to store, charge, and manage the iPads within the classroom. At this early stage, a basic understanding of the literacy learning potential (curricular competency) and basic teaching strategies (instructional competency) was sufficient. As the educators and children became more proficient with the technology and the management of the technology over time, the educators witnessed the extent of the literacy learning potential of the openended apps. They expressed a desire to circle back to increase their operational competence (how the technology works) and instructional competence (teaching strategies) so that they could better support the curricular potential that they were seeing. This movement back and forth between the competencies happened multiple times and at different rates for different educators. This spiral rather than linear movement through the competencies was possible because of the responsive nature of the research project. Through observation, interviews, questionnaires, and focus group/workshops, the educators experienced opportunities to explore their students’ work and their own teaching and make plans based on those understandings. The research team was able to gain insight into the educators’ thinking and respond accordingly. The study also revealed the importance of a respectful and responsive approach to teacher learning in DT. This study did not incorporate a developmental, skill-based model of professional development, but one that sought to be responsive to the context and needs of the educators and children (Laffey 2004). The educators needed time and many kinds of support to purposefully integrate the open-ended apps into their classrooms and their pedagogy. The educators, in turn, gave the students time, resources, and support as needed. This responsive approach on the part of the research team and the educators led to far more widespread and innovative use of the DT by the children than was originally expected. This research represents a response to Pacini-Ketchabaw et al.’s (2015) call to challenge the assumptions of traditional professional development. As noted above, the professional development model in this research project was not linear or sequential (Pacini-Ketchabaw et al. 2015, p. 67). The challenges and new learning ebbed and flowed in response to technical issues, the time of year, and the interests of the children and educators. The goal of the research project was to respond to the educators’ understandings and needs as they integrated the openended apps into their kindergarten literacy programs. The educators themselves were not considered to be stable, unchanging subjects (Pacini-Ketchabaw et al. 2015, p. 67), but as knowledgeable and resourceful educators seeking to understand their students and improve their practice. They had a great deal of autonomy

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and agency in how they participated in the project. They chose when, how, and where to use the iPad apps in their programs. The project provided a loose structure by providing the iPads and apps, biweekly visits, and annual focus group/workshops and interviews, but within that structure, the educators used their professional judgment to guide their practice. Finally, change in the research project was complex and context-specific and did not occur in isolated or pre-planned increments. Each of the 14 classrooms developed their own routines and preferred ways of using the apps, and children within each classroom engaged with the apps in response to their particular contexts. Children influenced and inspired each other, and through the focus group/workshops, educators learned from and with each other.

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Future Directions

The findings from this study demonstrate the power of a responsive, open, and longitudinal approach to teacher learning. To effectively integrate DT into learning for young children, educators need responsive professional learning opportunities that are accepting of their varied levels of digital experience, interest, confidence, and competence. Responsive professional learning needs to be respectful of educators’ emotional, technical, and pedagogical needs and be flexible as those needs change over time and in different contexts. Furthermore, educators need to be able to exercise their professional judgment during their involvement in any professional learning program. Professional learning providers need to be empathetic and nonjudgmental as they support educators who are navigating the integration of DT into their programs. An important aspect of a responsive approach to professional learning is being open to changing roles and outcomes (see ▶ Chap. 46, “Mobile Devices for Preschool-Aged Children”). Professional learning providers need to be ready to shift from technical trainers to observers, to coaches, and to resource providers as requested by educators. Educators, in turn, need to be open to their students’ changing needs and interests with respect to DT. When educators, and students, experience freedom and support to explore DT at their own pace and in their own ways, there is a greater possibility of increased creativity, innovation, and confidence in teaching and learning. Providing a responsive and open approach to professional learning in DT takes time. A longitudinal approach to professional learning in DT, as in this study, provides the time to develop relationships between researchers and educators and for all parties to navigate the inevitable ebbs and flows of DT learning in a classroom environment. When educators or children encounter challenges, there is time to problem-solve and change direction as needed. Furthermore, a responsive, emergent, and longitudinal approach to professional learning supports educators and children to go beyond basic proficiency to explore a variety of DT teaching and learning applications that are meaningful in their particular contexts.

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Cross-References

▶ 1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation ▶ Foreign Language Teachers as Instructional Designers: Customizing MobileAssisted Language Learning Technology ▶ Gatekeepers to Millennial Careers: Adoption of Technology in Education by Teachers ▶ Mobile Devices for Preschool-Aged Children

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Goodwin, K., and K. Highfield. 2012. iTouch and iLearn: An examination of “educational” apps. In Paper presented at the Early education and technology for children conference. Salt Lake City. 14–16 Mar 2012. Herro, D. 2015. Sustainable innovations: Bringing digital media and emerging technologies to the classroom. Theory Into Practice 54: 117–127. https://doi.org/10.1080/00405841.2015. 1010834. Accessed 16 Nov 2017. Keengwe, J., and G. Onchwari. 2009. Technology and early childhood education: A technology integration professional development model for practicing teachers. Early Childhood Education Journal 37: 209–218. https://doi.org/10.1007/S10643-009-0341-0. Accessed 16 Nov 2017. Kirkwood, A. 2009. E-learning: You don’t always get what you hope for. Technology, Pedagogy and Education 18: 107–121. https://doi.org/10.1080/14759390902992576. Accessed 16 Nov 2017. Laffey, J. 2004. Appropriation, mastery and resistance to technology in early childhood preservice teacher education. Journal of Research on Technology in Education 36: 361–382. Lee, T.H., F.G. Wu, and H.T. Chen. 2017. Innovation & evaluation of tangible direct manipulation digital drawing pens for children. Applied Ergonomics 60: 207–219. National Association for the Education of Young Children and Fred Rogers Center for Early Learning and Children’s Media at Saint Vincent College. 2012. Technology and interactive media as tools in early childhood programs serving children from birth through age 8. Web pdf. http://www.naeyc.org/files/naeyc/PS_technology_WEB.pdf. Accessed 16 Nov 2017. Neumann, M.M. 2016. Young children’s use of touch screen tablets for writing and reading at home: Relationships with emergent literacy. Computers & Education 97: 61–68. https://doi.org/ 10.1016/j.compedu.2016.02.013. Accessed 16 Nov 2017. Ontario Ministry of Education. 2016. The kindergarten program 2016. Toronto: Ontario Ministry of Education. http://www.edu.gov.on.ca/eng/curriculum/elementary/kindergarten.html. Accessed 17 Nov 2017. Pacini-Ketchabaw, Veronica, et al. 2015. Journeys: Reconceptualizing early childhood practices through pedagogical narration. North York: University of Toronto Press. Parette, H., A. Quesenberry, and C. Blum. 2010. Missing the boat with technology usage in early childhood settings: A 21st century view of developmentally appropriate practice. Early Childhood Education Journal 37: 335–343. https://doi.org/10.1007/s10643-009-0352-x. Accessed 16 Nov 2017. Radesky, J.S., J. Schumacher, and B. Zuckerman. 2015. Mobile and interactive media use by young children: The good, the bad, and the unknown. Pediatrics 135: 1–3. https://doi.org/10.1542/ peds.2014-2251. Accessed 16 Nov 2017. Rowsell, J., and D. Harwood. 2015. “Let It Go”: Exploring the image of the child as a producer, consumer, and inventor. Theory Into Practice 54: 136–146. https://doi.org/10.1080/ 00405841.2015.1010847. Accessed 16 Nov 2017. Wong, S.S. 2015. Mobile digital devices and preschoolers’ home multiliteracy practices. Language and Literacy 17: 75–90. Yilmaz, R.M. 2016. Educational magic toys developed with augmented reality technology for early childhood education. Computers in Human Behavior 54: 240–248. https://doi.org/10.1016/j. chb.2015.07.040. Accessed 16 Nov 2017.

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Purpose of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Technology Leadership or Instructional Technology Leadership . . . . . . . . . . . . . . . . . . . . 2.2 Constructs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Research Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Survey Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Data Collection Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Findings/Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Ranked Mean Scores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Standard Deviation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Demographics: Alignment/Agreement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Demographics: Divergent/Disagreement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter examines the role of instructional technology leadership in K-12 public schools. Instructional technology leaders, as opposed to instructional leaders or technology leaders, educate teachers how to integrate technology into

T. Edelberg (*) Instructional Systems Technology, Indiana University, Bloomington, Bloomington, IN, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_127

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instructional practice and evaluate the ways teachers teach with technology. Although broadly defined (International Society for Technology in Education. ISTE Standards for Education Leaders. Retrieved from https://www.iste.org/ standards/for-education-leaders, 2018), instructional technology leaders can include school superintendents, principals, technology directors, technology coordinators, digital literacy coaches, instructional coaches, and of course teachers. To explore the function of instructional technology leadership, Indiana public school superintendents and teachers completed a survey where they were asked to rank the skills and experiences (completely essential, important, desirablebut-not-essential, not-at-all-important) that they believed were essential for an instructional technology leader. A comparison of mean scores indicated that both the superintendent and teacher groups tended to rank items similarly. However, an examination of group conception about instructional technology diverged markedly. In other words, how is it possible that both groups can find agreement about what instructional technology leaders should do despite being unable to agree about what instructional technology is? What other factors might explain the shared preferences between Indiana superintendents and teachers who otherwise differ in response to questions about instructional technology? Further research on these questions might help to explain why over 20 years of research on digital technologies in public school classrooms has not been able to show significant increases on student learning outcomes (OECD. Students, computers and learning: Making the connection. OECD Publishing, Paris. Retrieved from http://www.keepeek.com/ Digital-Asset-Management/oecd/education/students-computers-and-learning_978 9264239555-en, 2015; Player-Koro and Tallvid, Int J Med Technol Lifelong Learn 11:180–193, 2015).

1

Introduction

Integrating technology into K-12 schools has become an important task for school administrators, especially in regard to the high expectations associated with its potential to improve student performance (Faris and Selber 2013; Flanagan and Jacobsen 2003; OECD 2015; Staples et al. 2005). For this chapter, technology integration means implementing technology intentionally to promote instructional practices that achieve positive student learning outcomes (Davies and West 2014; Frick 1996; Yepes-Baraya 2002). The responsibility for fulfilling this task is broadly defined (ISTE 2018), which makes clarifying the role of a K-12 instructional technology leader difficult to define and which seems to be dependent on what a school or district decides to emphasize.

1.1

Purpose of the Study

The purpose of this study was to examine the types of skills and experiences K-12, public school superintendents and teachers consider important for instructional

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technology leadership. A survey of superintendents and teachers in Indiana captured what they prioritized as essential for instructional technology leaders. An analysis of overall results focused on school district demographics and the role of instructional technology leadership according to superintendent and teacher responses. The next section of the chapter reports on the findings followed by an interpretation of what these findings mean in the context of previous studies. The final section presents directions for future research in this area.

2

Literature Review

As the researcher of this study, the author intended initially to revalidate Brush and Bannon’s (1998) survey that sought to reveal what K-12 school administrators considered the primary role(s) of technology leaders. Although comparing similarities and differences between 1998 and 2015 superintendents’ responses about the skills each tended to emphasize as important for technology leaders would be interesting, the purpose of this study has changed. First, integrating digital technologies in K-12 classrooms has the potential to engage students in learning (ISTE 2018; OECD 2015). Hammond (2014) provides an excellent explanation for the pervasive implementation of technology devices in the British school system based on political assumptions about its inevitable impact on learning outcomes. Yet according to the 2015 OECD report, the implementation of digital technologies in K-12 classrooms has yet to show a significant increase in student learning outcomes. A concern is the current trend in K-12 public schools “to make room” to implement a digital computer infrastructure with the consequence that the current structures supporting student learning reduced functionally or removed entirely (US Department of Education 2016). Second, a way to understand how digital technologies enact in a classroom is to examine the role of public school superintendents whose primary function is managing school budgets and personnel (Flanagan and Jacobsen 2003; Virginia Department of Education 2008). However, technology integration involves more than selecting particular digital devices from a list of available products (e.g., SmartBoards, iPads, Dell laptops). To avoid absentmindedly championing digital devices as an essential element to a successful educational program (Hammond 2010) or presuming that simply installing a computer in a classroom will allow “magic” to happen (McLeod 2015, p. 56), school district superintendents must fully engage with the complexities involved to integrate digital technologies into a curriculum (Earthman 2013). Third, gaining knowledge from teachers as well as from superintendents about what constitutes technology integration sheds light on support K-12 teachers expect to receive. Teachers must not only interpret how to apply pedagogical content knowledge to facilitate the context of student learning (Chen et al. 2009; Shulman 1986); they must demonstrate technological knowledge as well (Davies and West 2014; Frick 1996). According to the National Center for Education Statistics (2010), over 80% of US K-12 teachers agree professional development related to technology supports their instructional goals; however, only 53% spent 8 h or less in such

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professional development in a 12-month period, 18% spent 16 h or less, 9% spent 32 h or less, and 7% spent 33 h or more. Finally, projections for the total cost for education in the US project increased dramatically in the following years (Wolff et al. 2014). The financial implications to a school compound the cost of building and maintaining a technological infrastructure throughout a school district (Hew and Brush 2007; Luschei 2014). Therefore, it seemed important to examine the background assumptions superintendents and teachers have about implementing technology in K-12 public schools and the expectation that simply implementing technology devices will increase student achievement (Cuban 2001; Ertmer 2005; Hammond 2014). The next section provides a background to the chapter by explaining the difference between technology leadership and instructional technology leadership. Gaps in the current literature point to a possible need to research further the different and sometimes competing responsibilities of instructional technology leaders in K-12 schools.

2.1

Technology Leadership or Instructional Technology Leadership

With regard to leading change vis-à-vis technology integration, the term technology leadership is defined broadly. Sometimes the technology leader is the school principal tasked with making technology decisions that positively influence teacher instruction (Technology Standards for School Administrators 2001; Virginia Department of Education 2008). Other times the technology leader is a school district technology director or coordinator who functions primarily to support a school principal and provide suggestions and guidance regarding technology integration (Gosmire and Grady 2007; Shattuck 2010; Sugar and Hollomon 2009). This guidance can be important in order to realize a technology affordance, which is a relation between the qualities of particular technologies and the people who perceive these qualities and conceive others (Hammond 2010). For example, as a child growing up in a household before smartphones, our family had telephone answering machine. Its explicit function was to audio record missed telephone calls to our home. However, its implicit function was to screen phone calls and avoid unwanted callers. In public K-12 schools, the task of utilizing such affordances from digital devices often falls to teachers (Chen et al. 2009; Ertmer 2005; Hew and Brush 2007) (see also ▶ Chap. 46, “Mobile Devices for Preschool-Aged Children”). Teachers can express difficulty applying lasting instructional strategies if there is confusion about how to merge subject content knowledge and computer technology knowledge into a coherent lesson plan (Hutchison et al. 2012; Mishra and Koehler 2006). It is possible when implementing technology devices in the school curriculum, unintended uses surface, for example, teachers who replace student work with a digital tool without redefining the instructional tasks that might realize possible affordances. Furthermore, not only are technology leaders expected to be literate about how to use technology and troubleshoot technical problems (Shattuck 2010; Sugar 2005);

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they often are expected to possess instructional and analytical skills in order to evaluate the ways teachers teach with technology (Gosmire and Grady 2007; ISTE 2018; Sugar and Hollomon 2009) (see also ▶ Chaps. 46, “Mobile Devices for Preschool-Aged Children” and ▶ 49, “1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation”). However, possessing a high degree of expertise regarding technology might create problems when communicating with teachers. Technological competency about an innovation without considering a client’s primary concern can risk creating conflict and problems with communication (Hulpia et al. 2011; Rogers 2003). Hew and Brush (2007) recommend that in addition to technological savvy, technology leaders need “technologysupported pedagogy skills” and “technology-related classroom management skills” (pp. 233–234). Moreover, without such in-depth knowledge of technology and pedagogy, the most accurate assessment about digital technology use in a classroom would be that it does not inhibit teaching, which is different from concluding the possibility that technology might provide affordances to enhance teaching (Faris and Selber 2013) (see also ▶ Chap. 46, “Mobile Devices for Preschool-Aged Children”). Overall, technology leaders are not considered classroom teachers hired to instruct students (Sugar 2005; Vavasseur and MacGregor 2008), nor do they manage a school in a way similar to school principals (Noeth and Volkov 2004; Sugar and Hollomon 2009; Tan 2010). Therefore, the extant literature suggests researchers explore the need for an instructional technology leader, a more refined role that assists teachers integrate technology into instructional practice in a classroom. To clarify the term, instructional technology leadership, what follows are the constructs that define this term.

2.2

Constructs

In a survey research, constructs define particular information that a researcher seeks to know (Groves et al. 2011, p. 41). In order to support technology integration in K-12 classrooms, public school superintendents have relied on support staff to assist teachers in blending instructional strategies with digital technologies (Earthman 2013; Frazier 2012; Vavasseur and MacGregor 2008). However, what are the essential experiences and skills that superintendents and teachers prefer from such staff? The following constructs were developed to aid in writing survey questions related to instructional technology leadership with the aim to discover from respondents what instructional technology leadership means to them. Technology integration will mean incorporating digital technologies intentionally into instructional practices in addition to classrooms in order to promote positive student learning outcomes (Davies and West 2014; Frick 1996; YepesBaraya 2002). • Question examples include asking if students are allowed to connect personal devices to the school district internet, if the district follows ISTE standards, and who specifically coordinates instructional technology decisions

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at the district level. Other sample questions include reference to providing instructional technology support and integrating technology into core curricular areas. Instruction will refer to the procedures and strategies K-12 teachers employ to deliver mandated school district curriculum content that positively influence student learning (Shulman 1986; Virginia Department of Education 2008; Zemelman et al. 2012). • Sample questions include reference to K-12 teaching credential, university teaching experience, providing instructional support, and helping teachers deliver instruction. Technology will refer to any computer-based teaching and learning materials, including desktop and tablet computers used to access Internet resources, run software applications, and communicate electronically (Baylor and Ritchie 2002; Brush and Bannon 1998; ISTE 2018). • Sample questions include reference to MS or apple certification, managing a computer systems network, computer troubleshooting and repair, and media center/library experiences. Instructional technology, in a K-12 context, will be any electronic, usually computerized or digital, device that teachers use to accomplish specific instructional tasks (Davies et al. 2013). • Sample questions include reference to advanced degree in instructional technology or related field, experience developing instructional technology workshops in K-12 setting, experience delivering K-12 instructional technology workshops, and experience helping teachers deliver instruction with technology. Leadership will refer to the transformational function that characterizes change agents, who influence clients to adopt an innovation and mediate their ability to adapt to it successfully (Leithwood and Jantzi 2006; Rogers 2003). • Sample questions include reference to K-12 administrative credential, K-12 administrative experience, experience evaluating instruction, and experience evaluating instruction with technology.

3

Research Method

The survey for this research was developed from Brush and Bannon’s (1998) study, which revealed what K-12 school administrators considered the primary role(s) of technology leaders. Examining which skills and experiences respondents prioritize over others can be one way to understand how technology integration realizes in K-12 classrooms.

3.1

Research Questions

The research questions aimed to determine the experience and skills K-12, public school district superintendents, and teachers consider essential for an instructional

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technology leader. Hew and Brush (2007) explained the importance to (a) address the needs of teachers and the context of their practice and (b) engage teachers in active learning that focuses on technological skills, technological pedagogical skills, and classroom management skills for integrating technology. Another way to consider the research questions follows: If technology leaders do not provide instructional support, and instructional leaders do not provide technology support, then who provides instructional technology support? RQ1: What skills and experiences do public school superintendents and teachers prioritize as essential for an instructional technology leader? RQ2: What do superintendents and teachers understand to be the primary role(s) of an instructional technology leader?

3.2

Survey Design

Designing surveys is deceptively simple. Fowler (1995) emphasized the importance of assessing the validity of survey questions and addressing whether the questions asked measured what was intended to be measured (pp. 139–140). The process involved for developing a survey instrument is about controlling for survey error, including errors in measurement, processing, coverage, sampling, nonresponse, and adjustments (Groves et al. 2011). However, survey respondents should be able to read questions, select answers, and understand instructions implicitly and easily without having to verify if the process they employed is appropriate (Fowler 1995). Survey designers must account for estimation and judgment questions, question construction, and response labels. This requires writing question items that not only invite potential respondents to answer but also to understand the intent of the questions asked. Groves et al. (2011) highlighted that attitude or judgment questions can create similar problems for respondents, especially when they have “vague impressions” or a “hazy sense of how often [they] have done something” (p. 236). Therefore, questions should ask respondents about their “general impression” and provide a “context-influenced estimate” (Tourangeau 2000, p. 146) in order to enable respondents to reference the middle value of the available response options and then adjust the value of their impression. Put another way, good survey items avoid unfamiliar language, complex concepts, and unnecessarily complicated grammar. The design for the instructional technology leadership survey aligned with the 62-item instrument used in the Brush and Bannon (1998) study. To facilitate the development of the survey design, an expert panel provided feedback on the question items. The panel comprised 30 participants, including current and former K-12, public school district superintendents, chief technology officers, building principals, and classroom teachers, as well as university faculty from departments of instructional design and technology and graduate students enrolled in a survey methodology course. To validate the content of the questions, the panel concerned itself with how respondents would interpret the questions asked. As mentioned

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earlier in the literature review, broad definitions of instructional technology do not support a uniform perspective. However, the panel agreed superintendents and teachers should agree to conceptual agreement. The survey aimed to explore respondents’ opinions about instructional technology, as well as how they perceived the role of an instructional technology leader. Another aspect the panel considered was the response options to the questions. Survey respondents tend to think that past events happened more often or carried greater significance than they originally thought (Fowler 1995). However, given the influence regarding the effects of scaled response labels, it was important to avoid including numbers, which do not carry meaning as well as clearly defined labels (Groves et al. 2011; Tourangeau 2000). Furthermore, labels allow respondents to answer within a generalized range; removing the restriction of having to choose a specific number makes responding to each question easier to do. The panel concluded that distinct terms without numbers would help respondents judge all the options available and attribute a level of importance. Labels applied not only to the demographic questions that asked about each respondent’s individual background, knowledge about digital technology in schools, and description of their school district. The labels identified the scaled response items that asked about the experience and skills related to instructional technology leadership. Each item began with a question stem followed by a list of responses items. Respondents were asked to rate the level of importance for each item using a five-point Likert response scale (1, completely essential; 2, important; 3, desirable but not essential; 4, not at all important; 5, not sure). See Figs. 1 and 2 for an example of how the survey items appeared online. According to Dillman et al. (2014), the visual layout of a survey should allow respondents with the least ability to complete them. For instance, respondents alone must determine how “to navigate the questionnaire” (p. 172). Clarity of the visual layout is similar to clarity of writing the questions; survey designers can help respondents to skip and scan through the survey without spending time reading instructions. Rather than ask respondents to slog through a long list of items, the 31 items were broken up into 3 groups or chunks of 10, 10, and 11 items, respectively. This decision allowed separate measurement of each chunk, which helped address reliability issues. This decision also allowed respondents to comprehend quickly what they should do to complete the survey. For example, Qualtrics, the cloud-based survey tool used to collect responses, provided statistics on the time each respondent took to complete the survey. All but one completed the survey in less than 9 min, and this one outlier took almost 1 h, which might indicate starting the survey and returning later to finish it. In addition, label headings helped respondents distinguish each chunk of items. These label headings included General Experience, Educational Experience, and K-12 Experience. To keep the response items in each chunk symmetrical, progressive tenses were modified to some items, for example, media center changed to managing a media center. Finally, the expert panel reviewed the scale of choices used for each of the 31 response items. The author developed scaled responses using the Oxford and Merriam-Webster dictionaries to unearth significant distinctions between the terms

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Fig. 1 Likert scale for survey items displayed in Qualtrics, for desktop and smartphone users

Fig. 2 Data visualization using a radar graph to display mean scores

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essential and important. The word important is a baseline term for “something of great significance,” while essential indicates a greater degree of importance as in “something that is indispensable.” Although crucial was considered, this word denotes important in the extreme, as in extremely important or critical. Clarifying the varying degrees of importance was “everything was acceptable,” but would respondents quickly recognize the subtle degrees of importance? Mindful of the target population and their sensibilities, overuse of important was avoided. To help respondents’ interpretation, the word completely is combined with essential to discriminate essential from important. The term desirable but not essential was used to indicate a lesser degree of importance. The expert panel confirmed that respondents would understand the distinction among the labeled choices.

3.3

Participants

With regard to participants, survey research requires clearly describing a target population from which to make inferences. The sampling frame describes the respondents with whom a researcher will have access (Groves et al. 2011, pp. 43–45). The purposeful sample consisted of currently employed K-12, public school district superintendents, and teachers in Indiana. Superintendents authorize decisions that set the condition for how digital technologies will influence instructional practice (Earthman 2013; Shuldman 2004), and teachers devise lesson plans for their own use in the classroom room (Davies and West 2014; Zemelman et al. 2012). One way to understand how digital technologies enact in classrooms is to examine what this population understands instructional technology leadership to mean.

3.4

Data Collection Procedure

The survey instrument collected data from superintendents and teachers. The executive director of the Indiana School Teachers Association (ISTA) and president of the Indiana American Federation of Teachers (AFT) received a Qualtrics link to the survey instrument. They forwarded the survey link to their respective members in their email distribution lists, which was followed up 2 weeks later by a second request to complete the survey. An informed consent letter was included at the beginning of the survey that indicated to respondents that they had the option to withdraw from the survey at any time. The online survey tool did not record identifying information apart from the IP address of the device used to complete the survey. An option at the end of the survey invited respondents to participate in a telephone interview. This option for an interview was excluded from the analysis section for this chapter. All identifying information for participants, district names, places, and regions were confidential and not included in the final report. A total of 94 superintendent responses and 111 teacher responses were received. A total of 89 superintendent responses and 101 teacher responses were included in

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the demographic section of the survey instrument, but a total of 88 superintendent responses and 96 teacher responses were included for all items in the instrument. This meant that 93.6% of the superintendent responses and 86.4% of the teacher responses were valid items that could be used to conduct a reliability test. IBM SPSS Statistics 24 for Microsoft Windows determined Cronbach’s alpha to ensure internal consistency of the 31 items in the response scale.

3.5

Limitations

Meaningful answers to questions, especially in survey research, require researchers to have a higher regard for the fundamentals of survey methodology vis-à-vis questionnaire design, which for this study included the types of questions asked, good question writing, estimation strategies, and visual design (Dillman et al. 2014; Groves et al. 2011). All questionnaires have problems, but the objective of survey design is to improve the capacity for respondents to answer as accurately as possible and thereby improve the accuracy of the responses collected. However, a brief comment about generalizability is important to address here. It is a simple enough task to write a statement explaining how “this study is not generalizable,” which too often is used as a boilerplate limitation. To do so here would reinforce the scientific, empirical model that subject-object concepts define in neutral terms across other, similar contexts. As an alternative, it is important to emphasize the central role subjects retain in their intentional relation to objects and indeed to other subjects. The task of this study is to reveal the subjects themselves and determine the principle traits that help to explain how and why they affect the world around them. In this sense, the superintendent and teacher respondents are not binary opposites regarding instructional technology leadership, but they are instead intersubjective agents whose different subject positions help to explain technology integration in K-12 instructional settings. Regarding the organization of the scaled response items, the expert panel could not agree unanimously on an objective method to determine which response items belonged to which label heading. For example, all panel members agreed that K-12 teaching experience belonged to the item group K-12 Experience and that managing websites did not belong under Educational Experience and Skills. However, it was not entirely clear whether providing instructional support or having experience modeling instruction with technology belonged to the item group Educational Experience and Skills or K-12 Experience and Skills. The panel even considered changing the value of the response items under each label heading, but they ultimately felt that doing so would blur the response choices. Rather than continue becoming “lost in the weeds,” the panel agreed that collecting responses to the survey items was more important than struggling to determine which label an item should belong. In the end, the goal was to work with the expert panel to achieve consensus. The analysis of this survey study focused on instruction and technology but not leadership. Only two response items explicitly addressed leadership: K-12

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administrative experience and state administration certification. Both items appeared among the five least important skills and experiences in the response to mean scores; however, making claims about these two leadership-related items might not be adequate to claim that leadership is not a priority for respondents. The next iteration of this survey instrument should include additional questions addressing leadership skills and experience more clearly, and the expert panel should review the quality of such questions.

4

Findings/Data

The data analysis included conducting a test for reliability to measure the variability in the scores collected, which indicate how consistent the respondents were in their responses (Fraenkel et al. 2012). One method for checking the scale of reliability, or internal consistency, is to use Cronbach’s alpha to measure the extent to which a given scale consistently measures a concept. The alpha coefficient values range from 0 to 1. An alpha score below 0.7 suggests the items are unrelated, but an alpha score higher than 0.95 indicates too many items are identical, which can occur in an extensive list of items (Loewenthal 2001; Pallant 2013). In order to address the limitation of unrelated or redundant items, the following step ensued: the 31 items were broken up into 3 chunks of 10, 10, and 11 items, respectively. This decision allowed a separate measurement for each chunk of items. Factor analysis supported the total scale, as well as the three “chunked” items within the scale for both superintendents and teachers. Both the chunked items and total items for each group of respondents showed excellent internal consistency (see Table 1). Initially, the mean scores for each of the response item were arranged in a table that would allow for a comparison to highlight similarities and differences between superintendents and teachers; however, analyzing the results in this format made it difficult to visualize this data (see Table 2). To facilitate an analysis regarding which skills and experiences superintendents and teachers tend to prioritize over others, it became necessary to arrange the mean scores in a manner that would make a comparison easier to do. The solution was to display the data using a Microsoft Excel feature called radar graph to display data visually (see Fig. 2). Every point on the continuous line Table 1 Cronbach’s alpha value for the 31-item responses, superintendents, and teachers Response items General experience and skills (10 items) Educational experience and skills (10 items) K-12 experience and skills (11 items) Total (31 items)

Superintendents Cronbach’s alpha = 0.834 Cronbach’s alpha = 0.808 Cronbach’s alpha = 0.880 Cronbach’s alpha = 0.868

Teachers Cronbach’s alpha = 0.888 Cronbach’s alpha = 0.836 Cronbach’s alpha = 898 Cronbach’s alpha = 0.934

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Table 2 Means of responses to items, superintendents, and teachers Rank Survey item description Means of responses to superintendent survey items 1 Developing technology goals/plans for the district 2 Providing instructional support 3 Integrating technology into core curricular areas (math, science, language...) 4 Experience helping teachers deliver instruction with technology 5 Experience modeling instruction with technology 6 Success using learning management systems (canvas, Moodle, etc...) 7 Curriculum or content specialist experience 8 Making purchasing decision 9 Experience evaluating instruction with technology 10 Managing social media (Facebook, Instagram, twitter, YouTube, etc.) 11 Experience delivering instructional technology workshops in a K-12 setting 12 K-12 teaching experience 13 Knowledge of windows or apple operating systems 14 Repairing or troubleshooting tech devices 15 Experience developing instructional technology workshops in a K-12 setting 16 Managing a computer system network 17 Managing databases 18 Success acquiring external funding (grant writing) 19 Teacher credential in your state 20 Managing websites 21 Installing a computer system network 22 Ability to teach classes to K-12 students 23 Advanced degree in instructional technology or a related field 24 Success using distance learning as a student or instructor 25 Developing educational software 26 Knowledge of computer-programming languages 27 K-12 administrative experience 28 Running a media center or school library 29 Administration certification in your state 30 Teaching university-level courses 31 Teaching outside a K-12 setting Means of responses to teacher survey items 1 Experience helping teachers deliver instruction with technology 2 Providing instructional support 3 Knowledge of windows or apple operating systems 4 Repairing or troubleshooting tech devices 5 Integrating technology into core curricular areas (math, science, language...) 6 Developing technology goals/plans for the district

Mean

SD

1.34 1.45 1.49

0.52 0.68 0.68

1.50 1.53 1.56 1.73 1.73 1.76 1.83 1.88

0.68 0.74 0.60 0.71 0.77 0.84 0.70 0.76

1.90 1.98 2.01 2.02

0.82 0.88 0.86 0.73

2.02 2.02 2.07 2.14 2.16 2.20 2.32 2.48 2.67 2.72 2.73 2.86 2.92 3.02 3.39 3.44

1.05 0.79 0.81 0.90 0.77 1.02 0.86 0.74 0.85 0.90 0.89 0.82 0.83 0.83 0.85 0.80

1.51 1.56 1.57 1.57 1.65

0.79 0.85 0.77 0.84 0.82

1.66

0.84

(continued)

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Table 2 (continued) Rank 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Survey item description Experience modeling instruction with technology Experience delivering instructional technology workshops in a K-12 setting Managing websites Managing a computer system network Experience developing instructional technology workshops in a K-12 setting Making purchasing decision Success using learning management systems (canvas, Moodle, etc...) K-12 teaching experience Managing databases Experience evaluating instruction with technology Installing a computer system network Ability to teach classes to K-12 students Success acquiring external funding (grant writing) Teacher credential in your state Advanced degree in instructional technology or a related field Managing social media (Facebook, Instagram, twitter, YouTube, etc.) Success using distance learning as a student or instructor Curriculum or content specialist experience Knowledge of computer-programming languages Running a media center or school library Developing educational software K-12 administrative experience Administrator credential in your state. Teaching university- level courses Teaching outside a K-12 setting

Mean 1.68 1.77

SD 0.80 0.78

1.77 1.80 1.92

0.91 1.11 0.91

1.94 1.95 1.98 1.98 2.02 2.02 2.03 2.07 2.17 2.20 2.33 2.38 2.48 2.52 2.55 2.61 3.06 3.14 3.30 3.39

0.98 1.08 0.92 1.12 1.00 1.13 0.94 1.00 1.02 0.92 1.09 0.94 0.96 1.19 1.04 0.97 0.96 0.95 0.95 0.96

indicates a mean score for each survey response item. The items with mean scores closer to the center represent experience and skills considered more essential. Items farther from the center identify as less essential. The red line represents the superintendent group and the blue line represents the teacher group. Although measuring the degree of difference between the lines could be useful, what stands out visually is the comparative similarity in responses between the superintendent and teacher groups.

4.1

Ranked Mean Scores

Comparing the ranked mean scores in Table 2 provides an indication of the similarity in responses regarding the experience and skills that superintendents and teachers consider essential for an instructional technology leader. However, this similarity or “sameness” in the mean scores becomes more apparent when the 31 items separate

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into 3 graphs representing the chunked items and compared to each other (see Fig. 3). For example, both superintendent and teacher respondents shared similar rankings when prioritizing the skills and experiences for K-12 administrative experience, media center/library experience, administration certification, teaching university-level courses, and teaching outside a K-12 setting. Additional differences include (a) superintendents tended to prioritize higher than teachers the items developing technology goals and having curriculum experience, while (b) teachers tended to prioritize higher than superintendents the item repairing or troubleshooting technology devices. Overall, both superintendents and teachers tend to indicate that instructional technology had more to do with technology expertise and less to do with an instructional expertise.

4.2

Standard Deviation

The radar graphs also help to visual the standard deviations for the response items (see Fig. 3). The superintendent graph is smaller and sits inside the teacher graph. For example, superintendent responses are concentrated more around their mean scores. There is less variation in the distribution of responses among superintendents than among teachers. This would indicate that superintendent responses as a group had less variation than teachers’ grouped responses (Fig. 4).

4.3

Demographics: Alignment/Agreement

An analysis of the survey demographics begins with a comparison about where superintendent and teacher respondents align in their answers (see Fig. 5). First, both respondents share a similar distribution in the years of experience. Second, both respondents indicated that more than half had greater than 15 years of experience as K-12 educators. Third, the range of descriptions regarding school location indicates that most respondents work in rural school districts, followed by suburban, and then urban. Fourth, the majority of superintendents and teachers indicated Yes to having a full-time person responsible for providing district-level instructional technology support. Overall, both groups of respondents share similar backgrounds and school districts locations, and most have full-time instructional technology support.

4.4

Demographics: Divergent/Disagreement

4.4.1 Instructional Technology Decision-Making Before beginning an analysis of the survey demographics where the comparison of superintendent and teacher respondents differs in their responses, it is important to point out that the majority of both respondents indicated that the district technology director coordinated all instructional technology decisions (see Fig. 6). As noted earlier, technology leaders do not typically participate with teachers to develop

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Fig. 3 Ranked mean scores

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Fig. 4 Standard deviations

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Fig. 5 Alignment/agreement in demographic responses

instructional strategies. This is not to claim that technology directors lack adequate pedagogical skills or knowledge, but rather their primary responsibilities are concerned more with digital technologies than with instruction. Moreover, about 20% of the respondents in both groups indicated the superintendent, 1–2% chose teacher, and none chose digital literacy coach. However, the remaining respondents differ: (a) 7% of superintendents and 0% of teachers chose instructional coach,

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Fig. 6 Who specifically coordinates instructional technology decisions at the district level?

Fig. 7 Are students allowed to connect personal devices to the school Internet?

(b) 9% of superintendent and 2% of teachers chose building principal, and (c) 1% of superintendents and 18% of teachers chose technology coordinator.

4.4.2 Students and Connecting to the Network Not surprising, superintendents are certain when students are permitted to connect to the district network (see Fig. 7). Only 1% of the superintendents indicated I don’t know, suggesting that superintendents understand clearly, compared to teachers, district policies regarding students’ personal devices. Network policy would fall under the purview of superintendents who should be aware of all school district policies (Earthman 2013). Teachers, on the other hand, were less certain about network policy, with most indicating that students could not connect their personal devices and the remaining 12% not knowing at all.

4.4.3 Level of Knowledge of ISTE Standards Interestingly, teachers indicated being much less aware about ISTE standards regarding technology in K-12 schools (see Fig. 8). Over 70% of teachers did not know anything about ISTE standards, while the remaining respondents split almost evenly between Yes and No. On the other hand, superintendents should know or at least aware of details related to the district technology infrastructure (Earthman 2013; Kowalski 2005). Their results indicate that 78% do know about ISTE standards, and almost half indicated that their district follows these standards.

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Fig. 8 Does your district follow International Society for Technology in Education (ISTE) standards?

Fig. 9 How would you describe your level of instructional technology?

4.4.4 Level of Knowledge of Instructional Technology Once again, superintendents indicated having a greater certainty compared to teachers of their level of instructional technology (see Fig. 9). Only 1% of superintendents indicated knowing very little about instructional technology versus 12% of teachers. Conversely, 7% of superintendents indicated expertise, while only 1% of teachers chose I am an expert. In addition, while the majority in both groups of respondents indicated having some knowledge of instructional technology, 45% of superintendents and 34% teachers chose I am very knowledgeable.

5

Discussion

It is clear from the demographic and item response data that not only do superintendents and teachers share similar background and school location, but they also prioritize the experience and skills of instructional technology leadership in similar ways. When asked who specifically coordinates instructional technology decisions, both superintendent and teacher respondents overwhelming indicated that instructional technology decisions rest with the technology director, who as mentioned earlier is not considered a pedagogical expert. Although 20% of superintendents and teachers tended to agree that the district superintendent was the instructional technology leader, what is striking is the lack of clear agreement among the remaining staff positions. Even the instructional and technology support staff, including

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instructional coach, other staff, and digital literacy coach, which neither group selected, seems to have a limited presence for coordinating instructional technology decisions. The irony is striking given that these support roles would seem to be the ideal staff assigned to work more directly and more often with teachers. Yet, teachers (18%) did indicate a preference for the technology coordinator, whereas superintendents (1%) hardly indicated this position at all. An analysis of the ranked mean scores from the scaled item responses indicates that both groups of respondents tended to emphasize more often the technology aspect of instructional technology leadership than the instructional aspect. For example, the response items ranked lowest in the means of responses include those having to do with instructional ability, either in K-12, post-secondary, or other teaching contexts. Interestingly, the leadership experience (administrative credential) ranked lower than instructional experience (teaching credential). On the other hand, superintendents tended to prioritize developing technology goals and curriculum experience, while teachers tended to prioritize troubleshooting technology devices, having knowledge of operating systems. Overall, superintendents and teachers tend to rank the majority of items in similar ways, with a few items ranked a few steps higher or lower. However, the demographic data also indicate some disagreement between groups related to a definition of instructional technology. The survey results reveal four distinct claims: (a) superintendents offer a narrower view of instructional technology leadership; (b) teachers emphasize technology aspects of instructional technology; (c) superintendents model a better understanding of instructional technology and district policy in districts that follow ISTE standards; and (d) both groups prioritize technology over instruction to integrate instructional technology into classroom practice. Although these results appear to confirm what the literature says about the role of technology leadership in K-12 public schools, the implication is that there remains a need for instructional pedagogy to make sense of digital technology (Cuban 2013; Davies and West 2014; Hammond 2014; Hew and Brush 2007; OECD 2015). The research literature on technology integration reveals that the transformative potential in education has less to do with emphasizing the digital tool itself and more to do with an ongoing discourse among educational stakeholders that shape how and where digital technologies should fit within the structure of education. Discourse among principals, teachers, and technology support staff brings forward pedagogical considerations to facilitate technology integration in classrooms.

6

Future Directions

The evolution of the information age has made school systems more complex, increasing school leaders’ responsibilities and confronting them often times with new and competing priorities (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 52, “Student Feedback in Mobile Teaching and Learning”). Political consequences can occur if a decision contradicts the sociopolitical context that surrounds public schools. For example, the US Department of Education, Office

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of Educational Technology (2016), frames how digital technologies be regarded in K-12 public schools, stating that district superintendents should be “rethinking the roles and responsibilities of existing staff members to support technology in learning” (p. 47). This is a broad mandate to integrate digital technologies into the school curriculum at the expense of other alternative educational supports regardless of whether such alternatives are as beneficial to support student learning. Future research should examine the ways the education system influences superintendent decision-making, as well as teacher preferences, regarding technology integration. For instance, this influence could stem from the system of education policy-making itself, namely, the State Department of Education, where the system influences the preferences that superintendents claim are essential skills and experiences. Banathy (1995) recommended examining the educational system in the context of multiple interactions that seeks understanding as a reflection of the larger society and then analyzes interactions, the behavior of the participants, over time. This raises a question about whether superintendents’ preferences are representative of their own individual agency or a reproduction of the educational system. Are such reproducible preferences in decision-making desirable, or are differences necessary to produce educational reform? If superintendents share the same preferences, attitudes, and habits despite their particular knowledge and experiences, it might be easy to replicate educational processes. One possible focus for future investigations into the tension between the educational system and individual agency could be to examine the decision-making processes that manifest learning spaces. For example, distributed leadership is a decentralized decision-making and shared leadership responsibility based on intentional cooperation from varying levels of school membership that seek to explore their normative understanding about a topic (Harris 2008; Hulpia et al. 2011; Spillane 2015). Distributive leadership practices can vary in scope and depth (Camburn et al. 2003; Spillane and Diamond 2007; Heller and Firestone 1995) depending on the size of a school district (e.g., urban, suburban, rural), the level of focus (e.g., district, building, classroom), and the stage at which schools are progressing along their strategic plan (Copland 2003; Spillane and Diamond 2007). However, evidence of any positive impact on student achievement remains an indirect relation (Hartley 2010). What is less examined from the literature on distributed leadership are “the political, economic and cultural conditions” (Hartley 2007, p. 203) that influence what the leadership role should be and who should lead. Such a study might contribute to a clearer understanding of the complexities and the necessary responsibilities required for integrating digital technologies in public school classrooms.

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Cross-References

▶ 1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation ▶ Characteristics of Mobile Teaching and Learning ▶ Mobile Devices for Preschool-Aged Children ▶ Student Feedback in Mobile Teaching and Learning

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Hammond, M. 2010. What is an affordance and can it help us understand the use of ICT in education? Education and Information Technologies 15 (3): 205–217. Hammond, M. 2014. Introducing ICT in schools in English: Rationale and consequences. British Journal of Educational Technology 45 (2): 191–201. Harris, A. 2008. Distributed leadership in schools: Developing the leaders of tomorrow. London: Routledge & Falme. Hartley, D. 2007. The emergence of distributed leadership in education: Why now? British Journal of Educational Studies 55 (2): 202–214. Hartley, D. 2010. Paradigms: How far does research in distributed leadership ‘Stretch’? Educational Management Administration & Leadership 38 (3): 271–285. Heller, M.F., and W.A. Firestone. 1995. Who’s in charge here? Sources of leadership for change in eight schools. Elementary School Journal 96 (1): 65–86. Hew, K.F., and T. Brush. 2007. Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Education Technology Research and Development 55: 223–252. https://doi.org/10.1007/s11423-006-9022-5. Hulpia, H., G. Devos, and H. Van Keer. 2011. The relation between school leadership from a distributed perspectiveand teachers’ organizational commitment: Examining the source of the leadership function. Educational Administration Quarterly 47 (5): 728–771. Hutchison, A., B. Beschorner, and D. Schmidt-Crawford. 2012. Exploring the use of the iPad for literacy learning. The Reading Teacher 66 (1): 15–23. https://doi.org/10.1002/TRTR.01090. International Society for Technology in Education (2018). ISTE Standards for Education Leaders Retrieved from https://www.iste.org/standards/for-education-leaders Kowalski, T.J. 2005. The school superintendent: Theory, practice, and cases. Northridge: SAGE. Leithwood, K., and D. Jantzi. 2006. Transformational school leadership for large-scale reform: Effects on students, teachers, and their classroom practices. School effectiveness and school improvement, 17 (2): 201–227. https://doi.org/10.1080/09243450600565829 Loewenthal, K.M. 2001. An introduction to psychological tests and scales. 2nd ed. London: Psychology Press. Luschei, T.F. 2014. Assessing the costs and benefits of educational technology. In Handbook of research on educational communications and technology, ed. J.M. Spector, M.D. Merrill, J. Elen, and M.J. Bishop, 239–248. New York: Springer. McLeod, S. 2015. The challenges of digital leadership. Independent School 74 (2): 50–56. Retrieved from https://eric.ed.gov/?id=EJ1062593. Mishra, P., and M.J. Koehler. 2006. Technological pedagogical content knowledge: A new framework for teacher knowledge. Teachers College Record. 108 (6): 1017–1054. Noeth, R.J., and B.B. Volkov. 2004. Evaluating the effectiveness of technology in our schools, ACT policy report, 2004. Iowa City. Retrieved from http://www.act.org/research/policymakers/pdf/ school_tech.pdf. Organisation for Economic Co-operation and Development (OECD). 2015. Students, computers and learning: Making the connection. Paris: OECD Publishing. Retrieved from http://www.keepeek.com/Digital-Asset-Management/oecd/education/students-computers-and-l earning_9789264239555-en. Pallant, J. 2013. SPSS survival manual. 5th ed. Maidenhead: McGraw-Hill Education. Player-Koro, C., and M. Tallvid. 2015. Title one laptop on each desk: Teaching methods in technology rich classrooms. International Journal of Media, Technology and Lifelong Learning 11 (3): 180–193. Rogers, E.M. 2003. Diffusion of innovations. New York: Free Press. Shattuck, G. 2010. Understanding school leaders’ role in teachers’ adoption of technology integration classroom practices. In Educational media and technology yearbook, ed. M. Orey, S.A. Jones, and R.M. Branch, vol. 35, 7–28. New York: Springer. https://doi.org/10.1007/ 978-1-4419-1516-0_2. Shuldman, M. 2004. Superintendent conceptions of institutional conditions that impact teacher technology integration. Journal of Research on Technology in Education 4 (36): 319–343.

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Shulman, L.S. 1986. Those who understand: Knowledge growth in teaching. Educational Researcher 15 (2): 4–14. https://doi.org/10.3102/0013189X015002004. Spillane, J.P. 2015. Leadership and learning: Conceptualizing relations between school administrative practice and instructional practice. Societies 5: 277–294. Spillane, J.P., and J.B. Diamond. 2007. Distributed leadership in practice. New York: Teachers College Press. Staples, A., M.C. Pugach, and D. Himes. 2005. Rethinking the technology integration challenge. Journal of Research on Technology in Education 37 (3): 285–311. https://doi.org/10.1080/ 15391523.2005.10782438. Sugar, W. 2005. Instructional technologist as a coach: Impact of a situated professional development program on teachers’ technology use. Journal of Technology and Teacher Education 13 (4): 547–571. Sugar, W., and H. Hollomon. 2009. Technology leaders wanted: Acknowledging the leadership role of a technology coordinator. TechTrends 53 (6): 66–75. https://doi.org/10.1007/s11528-0090346-y. Tan, S.C. 2010. School technology leadership: Lessons from empirical research. In Curriculum, technology & transformation for an unknown future. Proceedings ascilite Sydney 2010, ed. C.H. Steel, M.J. Keppell, P. Gerbic, and S. Housego, 896–906. Retrieved from http://www.ascilite.org.au/conferences/sydney10/procs/Seng_chee_tan-full.pdf. Technology Standards for School Administrators. 2001. Technology standards for school administrators collaborative. Eugene: International Society for Technology in Education. Retrieved from: http://www.kyepsb.net/documents/EduPrep/tssa.pdf. Tourangeau, R. 2000. The psychology of survey responses. New York: Cambridge University. U.S. Department of Education, National Center for Education Statistics. 2010. Teachers’ use of educational technology in U.S. Public Schools: 2009. Retrieved from http://files.eric.ed.gov/ fulltext/ED509514.pdf. U.S. Department of Education, Office of Educational Technology. 2016. Future ready learning: Reimagining the role of technology in education (National Educational Technology Plan). Retrieved from https://tech.ed.gov/netp/. Vavasseur, C.B., and S.K. MacGregor. 2008. Extending content-focused professional development through online communities of practice. Journal of Research on Technology in Education 40 (4): 517–536. Retrieved from http://files.eric.ed.gov/fulltext/EJ826089.pdf. Virginia Department of Education. 2008. Instructional technology resource teacher: Guidelines for teachers and administrators. Richmond. Retrieved from http://www.doe.virginia.gov/support/ technology/administrators_teachers_staff/teacher_guidelines.pdf. Wolff, E.N., W.J. Baumol, and A.N. Saini. 2014. A comparative analysis of education costs and outcomes: The United States vs. other OECD countries. Economics of Education Review 39: 1–21. Yepes-Baraya, M. 2002. Technology integration. In Assessing the impact of technology in teaching and learning, ed. J. Johnston and L.T. Barker, 139–160. Ann Arbor: Institute for Social Research, University of Michigan. Zemelman, S., H. Daniels, and A. Hyde. 2012. Best practices: Bringing standards to life in America’s classrooms. 4th ed. Portsmouth: Heinemann.

1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation

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Contents 1 Introduction: The Need to Study Teachers’ Technology Acceptance . . . . . . . . . . . . . . . . . . . . . . 1.1 Concerns-Based Adoption Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Stages of Concern with 1:1 iPads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Ms. Brown’s Stages of Concern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Levels of Use with 1:1 iPads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Ms. Brown’s Levels of Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 iPad Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Ms. Brown’s iPad Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 CBAM: A Final Reflection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

It is important to study technology acceptance of teachers to improve technology integration practices in the classroom. Framed by the Concerns-Based Adoption Model (CBAM), this chapter reports the stages of concern and levels of use to accept one-to-one iPads by a first-grade teacher. Described as an alternative choice school for the community, this charter school is located in the southeast area of the USA and operates within the public school district. The classroom teacher sought out a university researcher for assistance with technology integration strategies, which led to a 2-year partnership. Monthly video chats, text from a dialogue journal, and student work artifacts generated data. Analysis of data revealed findings that propose a classroom teacher needs 2 years to advance through the seven stages of concern. The greatest concern is shown during the L. Eutsler (*) University of North Texas, Denton, TX, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_132

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management stage. Additional data demonstrate barriers toward integrating the iPad, such as extensive time required to locate iPad applications. Strategies for moving across the CBAM are provided, along with apps the teacher found most useful. It is spring 2017 in Ms. Brown’s (all names are pseudonyms) first-grade classroom, and 18 students are hovered closely over their iPads, moving at their own pace to read and respond to literature. Lizzie is using the Book Creator app to audio and video record herself narrating her flip-book one page at a time. Jamaal is using PicCollage Kids to audio-record his personally crafted script for his digital picture book. Rosie is using ChatterPix to create a public service announcement about the importance of tree preservation to share on Twitter.

1

Introduction: The Need to Study Teachers’ Technology Acceptance

The vignette of Ms. Brown’s first-grade classroom shows how the iPad enables her students to access and use digital media tools in educational, engaging, and innovative ways. In the fall of 2015 during her third-year of teaching, Ms. Brown became a part of a 1:1 technology initiative. Through this initiative, each student received an iPad. Ms. Brown was eager for her students to use iPads, but limited technology integration training left her searching for guidance on how to use iPads to support learning. Concerned with her ability to integrate iPads into instruction, Ms. Brown contacted a university researcher for assistance, which established a partnership between the university researcher and classroom teacher. The purpose of this chapter is to describe the 2-year journey of Ms. Brown’s response to the 1:1 iPad initiative and demonstrate how her concerns influence iPad integration. The iPad was introduced in 2010. While the innovation remains relatively new, research has shown iPads in the classroom can increase learning outcomes for students (Haßler et al. 2016). Although iPads can be a useful educational tool, barriers to effective integration include acknowledging and responding to teachers’ attitudes toward technology (Aldunate and Nussbaum 2013) and providing pedagogical support for technology integration (Koehler and Mishra 2009; Cumming et al. 2013). Most research on iPads provides examples of use (Neumann 2016; Price et al. 2015), with limited examination of teachers’ iPad acceptance (Ifenthaler and Schweinbenz 2013). The policy brief to advance educational technology in teacher preparation released by the US Department of Education requests pre-service teachers be equipped with effective strategies for integrating technology into classroom instruction (Stokes-Beverley and Simoy 2016). For this reason, it is important to investigate technology concerns of teachers because it can reveal barriers that interfere with their ability to integrate successfully new technologies in the classroom. This chapter illustrates how one teacher progresses through all the stages of concern and levels of use during the first 2 years of iPad implementation. Since it

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took 2 years to advance through all seven stages of concern, this demonstrates how technology acceptance requires time and emphasizes commitment to technology integration efforts.

1.1

Concerns-Based Adoption Model

The Concerns-Based Adoption Model (CBAM, Hall et al. 1973), applied most commonly within educational contexts, is a research model that measures an individual’s reaction and acceptance to an innovation (e.g., when a new technology is introduced). Technology adoption models are research design frameworks used to provide insight into an individual’s thinking that is otherwise inaccessible. Applying the CBAM to understand teachers’ concerns with a new technology can provide schools with guidance to respond to individual teacher’s concerns associated with technological innovation. The framework of the CBAM consists of three main components that collectively explain the change process of a teacher’s acceptance of a new technology: stages of concern, levels of use, and innovation configuration. Stages of concern identify attitudes that describe how an individual reacts to an innovation, such as a new technology. Levels of use depict individual behaviors that illustrate the use of the innovation, like research and implementation efforts. Innovation is “any process or product that is new to a potential user” (Hall 1979, p. 203), such as using a technology (e.g., iPad) in new ways. Hall (1976) divided the developmental process of technology acceptance into seven incremental stages of concern, measured on a scale from 0 to 6 (Fig. 1): awareness (0), informational (1), personal (2), management (3), consequence (4), collaboration (5), and refocusing (6). Adapted to the context of this study, the first stage of concern, awareness, marks the moment a teacher acknowledges a new technology, such as the iPad. During the informational stage, the teacher searches for apps and learns how to operate the iPad. Personal concerns refer to self-assessment and reflection after iPad implementation. Management concerns address planning for instruction and Fig. 1 Stages of concern about the innovation (Hall 1976)

0 Awareness

I don’t know anything about it (the innovation).

1 Informational 2 Personal

I would like to know more about it. How will using it effect me?

3 Management

I seem to be spending all my time in getting material ready.

4 Consequence How is my use affecting kids? 5 Collaboration I am concerned about relating what I am doing with what other instructors are doing. 6 Refocusing

I would like to know of something that would work even better.

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whether new technology (e.g., iPad) influences routine use. Consequence occurs when the teacher inquires how iPads could influence their students’ learning. Collaboration depicts the phase when the teacher is comfortable connecting with a colleague to use the iPad together. Refocusing occurs after the teacher has moved through stages 0 to 5 and is searching for ways to improve pedagogy associated with technology. The second component of the CBAM focuses on an individual’s levels of use. Levels of use identify what the user is doing, such as orienting, managing, and integrating an innovation (Hall et al. 1975). There are eight stages associated with levels of use, measured by level 0 to level VI (Fig. 2): nonuse (0), orientation (I), preparation (II), mechanical use (III), routine (IV A), refinement (IV B), integration (V), and renewal (VI). The research proposes that CBAM’s levels of use are appropriate and align to this study. The nonuse stage does not apply to this study because the teacher had already began using iPads in her teaching at the time this partnership commenced. Orientation (I) refers to the decision to acquire iPads, which occurred among the school’s administration prior to this study. Preparation (II) occurs when the teacher becomes familiar with the iPad and available apps prior to using the device with students. Mechanical use (III) occurs when the teacher spends the majority of time organizing ways to use apps in an attempt to keep students smoothly operating the iPads. Routine (IV A) refers to the teacher’s regular use of the iPad. For example, the teacher may routinely allow students to choose from three identified apps to create digital storybooks. Integration (IV B) includes buy-in from multiple teachers, and teachers collaborate to plan their technology use. The final stage, renewal (VI), refers to a teacher’s reflection of iPads application during planning and implementation, with the intention to improve future use. The third and highest level of the CBAM, described as innovation configuration, reaches attainment when an individual surpasses all levels of self and task, which allows creative integration of the technology in ways that effect change. After implementing the innovation, the individual reverts to the earliest stages of concern and levels of use as they become familiar with the innovation. In this study, the innovation is the iPad, along with its app affordances.

2

Stages of Concern with 1:1 iPads

Examining an individual’s stages of concern can provide insight into perceptions that accompany accepting a new technology. Casey and Rakes (2002) applied the CBAM framework to unveil concerns of 659 preschool through high school teachers acceptance toward a new technology. Findings from the Stages of Concern Questionnaire revealed greatest concerns occurred at the personal (2) and collaboration (5) stages of concern. These concerns address how technology affects a user in personal ways and their desire to connect with other teachers to use technology.

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Level 0

NON-USE

Decision Point A Level I

ORIENTATION Decision Point B

Level II

PREPARATION

Decision Point C

Level III

MECHANICAL USE

Decision Point D-1 Level IVA

ROUTINE Decision Point D-2

Level IVB

REFINEMENT

Decision Point E Level V

INTEGRATION

Decision Point F

Level VI

RENEWAL

877

The individual has little or no knowledge and involvement toward the innovation, and is doing nothing toward becoming involved. Takes action to learn more detailed information about the innovation. The individual has or is acquiring information about the innovation and/or has explored its value orientation and required demands. Makes a decision to use the innovation by establishing a time to begin. The individual is preparing for the first use of the innovation. Begins first use of the innovation. The individual focuses most effort on the short-term, dayto-day use of the innovation with little time for reflection. Effort is primarily directed toward mastering tasks required to use the innovation. Use is often disjointed and superficial. Routine pattern of use is established. Use of the innovation is stabilized. Few, if any, changes are being made to ongoing use. Minimal efforts and thoughts are given to improve innovation use or its consequences. Changes use of the innovation based on formal or informal evaluation to improve expected benefits. The innovator varies the use of the innovation to increase the expected benefits within the immediate sphere of influence. Variations are based on knowledge of both short and long-term consequences and benefits. Initiates changes in use of innovation based on input from and in coordination with what colleagues are doing. The innovator is combining own efforts with related activities of colleagues to achieve a collective impact within the collective spheres of influence. Begins exploring alternatives or major modifications of the innovation presently in use. The user reevaluates the quality of use of the innovation, seeks major modifications of or alternatives to present innovation to achieve increased impact, examines new developments in the field, and explores new goals for self and others.

Fig. 2 Levels of use (adapted from Hall et al. 1975)

In another study, participants explored how iPads may support literacy instruction. Teacher concerns with iPad implementation were directly related to creative uses of the iPad (Hutchison et al. 2012). These studies draw attention to the complex nature of technology integration in the classroom. This case study contributes to existing literature by providing a longitudinal contribution to understanding integration and innovation with a new technology in an elementary classroom. The next section addresses Ms. Brown’s progression through the CBAM’s stages of concern.

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Ms. Brown’s Stages of Concern

Guided by the CBAM, this study addresses Ms. Brown’s stages of concern throughout her 2-year journey with the 1:1 iPad initiative. After receiving iPads in the fall of 2015, Ms. Brown’s level of concern was awareness (0) because she had no prior knowledge of the iPad. Further evidence to support she was at the awareness stage of concern was that she had not previously used an iPad as an educational technology tool. Upon receiving iPads, Ms. Brown’s greatest challenge was that she received minimal professional development on how to integrate this new technology into her instruction. She shared, “we have a K-6 technology specialist, she covers 30 classrooms, but she also teaches gifted. . .she’s so busy it’s really not effective, she’s running many different directions.” Navigating how to use iPads, she admitted, “I’m trying to implement way too much.” After 1 month of using iPads, Ms. Brown’s level of concern moved to informational (1). At this point, she wanted to learn more about how iPads could improve her students’ learning. At this moment, she took the initiative to contact the nearby university for guidance, “if I can see and hear what’s more effective, that’s what I would like to be using.” It was then that a partnership between Ms. Brown and the university researcher was established. The second month with iPads was challenging because Ms. Brown expended her available time on tasks related to researching and identifying appropriate apps. She confessed, “I’m not good with technology, I’m still learning.” At this point, Ms. Brown’s stage of concern had reached the management (3) stage because she was exerting extensive effort to prepare lessons using the iPad. She exhibited frustration associated with managing instruction with iPads, “I could do research all day.” Planning for instruction also felt burdensome, “I feel like I’m second-guessing my pedagogy, and I’m constantly wondering if my intention for using iPads will allow me to effectively meet the standards I’m trying to teach.” Over the next 6 months, Ms. Brown compared notes with the university researcher. Together they devised tactics for what technological and pedagogical strategies might help integrate technology and meet the learning standards. This reciprocal sharing of research allowed for an exchange of ideas found within articles about teaching with iPads. This open-ended non-threatening sharing of knowledge helped Ms. Brown become more confident and comfortable infusing iPads into her daily planning and instruction. The first year concluded with a sigh of relief, “This year has been a whirlwind and has required great dedication to learn new skills. Yet, iPads motivated my students and helped make learning much more interesting.” In the beginning of her second year with iPads, Ms. Brown went through a distinct change related to her perspective on technology integration. After reading technology integration literature, she began to wonder if using explicit instruction to introduce students to a new iPad app was an effective technique. Also during one of the video chats, the university researcher pointed out that Ms. Brown’s students might be more capable of navigating iPads than she had initially thought. The reasoning behind this belief was simple; some of Ms. Brown’s students had been using an iPad since they were born in 2010, the same year the iPad released to

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the public for purchase. Making connections between technology integration research and her individual students, she realized, “last year I did not allow my students’ time for much exploration.” Ms. Brown admitted that during her first year, “I had been overly concerned about excessively managing the iPads, feeling compelled to show the students exactly what to do and how to do it.” This realization marked Ms. Brown’s progression to the consequence (4) stage of concern. By the spring of 2017, with only a few months remaining in the study, Ms. Brown was still at the consequence (4) stage of concern. However, her concerns expanded to include collaboration (5). Some examples of collaboration, to be discussed in more detail later in this chapter, were that her students were creating digital books and sharing them with each other on the class Seesaw and Twitter pages. Students also participated in a FaceTime video conference with another elementary class to practice their mathematical learning together. At the end of the 2-year period with 1:1 iPads, Ms. Brown had reached the final stage of concern, refocusing (6). Evidence that Ms. Brown had reached the refocusing stage of concern was shown by her desire to identify new apps that could improve the digital storytelling experience. Using iPads to develop students’ literacy had become an important part of Ms. Brown’s teaching. “I have tested PicCollage and Chatterpix Kids. Book Creator will be next!” Following her experience with Book Creator, Ms. Brown raved about its innovation over previously implemented literacy instruction methods: With Book Creator my students are able to respond in ways they simply couldn’t with pencil and paper. With Book Creator my students are able to tell stories, demonstrate their understanding and share their learning with an audience. I have been given the gift of listening to student voices, capturing their thinking, understanding misconceptions, and I have gained a shareable product that documents their growth. For example, students create books to document their response to reading by using video reflections, text, voice recordings, pictures, and more! This has taken my formative assessments to the next level!

3

Levels of Use with 1:1 iPads

Technology use in the classroom connects to the teacher’s prior technological knowledge and attitude toward technology. Teachers who are early adopters of technology are more likely to use technology in their teaching (Aldunate and Nussbaum 2013). Following a 1:1 iPad initiative 1 year in five kindergarten classrooms, teachers concluded the following criteria should be considered when using individual iPads for learning in the classroom (Toppel 2014, p. 2): • “Structure, organization, and clear expectations are essential. • The more the merrier doesn’t apply to apps in the classroom – choose wisely. • Students like to talk, and iPads can be great ‘listeners’ by providing students with opportunities to record.”

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A review of 1:1 technology initiatives in K-12 classrooms show how a teacher’s own technology experiences influences students’ use, in combination with curriculum and instruction demands (Harper and Milman 2016). The next section of this case study documents how a teacher with no prior experience using iPads as an educational tool uses them in her first-grade classroom over a 2-year period.

3.1

Ms. Brown’s Levels of Use

After Ms. Brown connected with the university researcher for guidance to implement 1:1 iPads, she was encouraged to explore apps that could motivate her students and deepen their understanding of the curriculum and standards. Ms. Brown kept a journal of the apps she explored, documenting the purpose of each app and students’ perceptions of each app. When Ms. Brown first received iPads, orientation (I) described her level of use because she was actively seeking information and knowledge about how to use iPads. She admitted, “we use the iPads but not to where I want to be using them.” After about a month of reading educational technology blogs and articles on Common Sense Media, Ms. Brown moved to the preparation (II) level of use, as she learned the logistics of managing the iPads before implementation. She reflected on the importance of planning, “to get apps downloaded on the students’ iPads is not a quick process. I have to send the apps to my technology team, they must be approved, and then they work on pushing them through to all the first-grade iPads.” By the second month and until the end of the first year with iPads, Ms. Brown’s level of use was mechanical (III), evidenced by her short-term focus on implementing iPads. She explained: I want technology helping my students, not just serving as an extra assignment or something used to practice fluency skills. I know I need to think of the desired, end result when writing my lesson plans for the month. I feel like I struggle with coming up with the big picture and I tend to only focus on the right now.

Pre-service teachers learn to write a lesson plan by first identifying the learning standard. Based on this instructional design technique, the university researcher advised Ms. Brown to spend some time looking at her state standard and carefully develop teaching ideas using apps that could help her meet the learning standards. At the start of the second year with iPads, Ms. Brown’s level of use was refinement (IV B) because she wondered how to modify iPad use to enhance student learning. She emphasized iPad use would be purposeful and innovative in her classroom. “I don’t want my kids to get on ABCya and play games for 40 min. That’s just not the teacher I am and I never will be.” Instead, “I want them to be confident in creating things.” Interestingly, Ms. Brown did not appear to be at the routine (IV A) level of use, perhaps because during her first year she was busily experimenting new apps and searching for effective and creative approaches to

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increase her students’ motivation. “I really want my students to be excited about using technology to support their learning in my classroom.” As Ms. Brown progressed into her second year of having iPads in the classroom, her confidence with technology enabled her to collaborate with others, which indicated she had reached the integration (V) level of use. An example follows describing how Ms. Brown functioned at the integration level: We FaceTimed with another school today to play Mystery Number!! Each class picked a number from 0–120. They had to ask questions such as: Is your number even? Is your number odd? Does your number have 3 digits?...etc. So MUCH FUN!!! We ended our sessions with a game using Kahoot! We love Kahoot!!

Three months prior to the end of the 2-year study, Ms. Brown developed a routine for using iPads and had reached the routine (IVA) level of use. She was making only a few implementation changes such that her students felt comfortable using iPads in specific and repetitive ways. For example, to access “books from RAZ-KIDS, place them in book creator, record our voices, and finally push them out into Seesaw!” Seesaw is a digital portfolio, where students upload and share their digital creations, and the teacher and parents can view their child’s work. By the end of the 2-year study, Ms. Brown reflected on the quality of her routine practice with 1:1 iPads. By evaluating how iPads had improved her teaching, she had achieved iPad use at the renewal (VI) level of use. The biggest game changer for me is AUDIENCE!! My students LOVE coming to school each day to share their learning with more than just their teachers! The biggest turning point for me was when my shyest student asked to upload and record his finished writing project. Seesaw has given him a reason to be confident, bold, and proud of his learning.

In addition to being at the final level of use, renewal, Ms. Brown continued to search for new apps that could improve her current iPad use. In congruence with the CBAM, she had moved back to orientation (I), where she was acquiring information about apps to explore their value. She considered, “these are new applications I am looking into: Art Lab, Recap, Padlet, Tellagami, Popplet, Puppet Edu, Green Screen, Explain Everything.” Progressing through the levels of use allowed her to reflect on the complexity of integrating new technology, “I know I would have trouble implementing all of these so I have to research which applications would best suit my class and their purpose for using them.”

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iPad Use

Lu et al. (2017) examined four early childhood teachers with 1:1 iPads and discovered classroom teachers used iPads for children to practice basic literacy skills in center activities and to engage in child-centered digital production projects. As students advance to become critical and constructive users of technology, this

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requires a shift in teachers’ roles, such that teachers require “skills for guiding, questioning, and facilitating” (McKnight et al. 2016, p. 205). Research on students’ use of social media as a mechanism to expand innovative uses of technology is limited, yet this practice is becoming more common. Students in one second-grade classroom spent 8 weeks learning to use Twitter to share their literature experiences (Marich 2016). The teacher personally became familiar with using Twitter for a month before deciding on important media safe techniques: students could respond to learning using a shared classroom hashtag, identify themselves by first name only, and student viewing was limited to a predetermined classroom newsfeed. Others in the field have argued that social media (e.g., Twitter, Skype, Facebook, Instagram, YouTube) should harness students’ creativity and enhance learning by connecting socially (Krutka and Carpenter 2016). Although this prior research is important in recognizing the importance of using digital technology in creative and safe ways, this case study provides explicit examples of how Ms. Brown and her first graders use iPads to construct creative, digital representations of their learning while safely sharing their learning via social media.

4.1

Ms. Brown’s iPad Use

In January 2017, before students returned from a break and halfway through Ms. Brown’s second year with 1:1 iPads, she shared her enthusiasm for how she planned to use literacy apps to achieve learning innovation. “I’m going to have them create a Valentine’s greeting card using PicCollage Kids. We are then going to push that out into Chatter Pix Kids, allowing them to record their written message. . .then we will push that out into Seesaw!” Students’ experiences with these apps were positive, and students were engaged in their learning, writing their own books and practicing fluency skills. Even though Ms. Brown’s students had their own iPads since August 2016, it was not until March 2017 that students began to use the iPad in innovative ways. iPads became a mechanism for students to share their voices about literature with peers, parents, and the world. The next section provides detail on the apps Ms. Brown used to achieve innovation configuration (e.g., integrate a new technology in innovative ways) using iPads to develop her students’ literacy. Apps to achieve innovation configuration include Book Creator, Seesaw, PicCollage Kids, Chatter Pix Kids, and Twitter (Table 1). Book creator. After students create their own flip-books using paper and pencil, they record themselves retelling their stories using the Book Creator app (Fig. 3). Each page is video and audio-recorded, which allows the video viewer to read along with the book’s author. Seesaw. Seesaw is the app that enables Ms. Brown to “hear” her students’ thinking since each individual student publishes draft pieces of work to the class Seesaw page. Seesaw provides a collaborative space for students to publish and share work with peers, their teacher, and their caregivers. On the Seesaw classroom homepage, there is a scrolling class newsfeed on the left, which includes the

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Table 1 Literacy apps used to achieve innovation configuration during year two App Book Creator https://bookcreator.com/

SeeSaw https://web.seesaw.me/

PicCollage Kids https://pic-collage.com/

ChatterPix http://www.duckduckmoose. com/educational-iphone-itouchapps-for-kids/chatterpix/ Twitter https://twitter.com

Student use example One student transfers a flip-book, originally created on pencil and paper, and records himself reading the book one page at a time. Students share their creations (digital books) with their peers and parents on a password-protected digital portfolio. Students respond and react to visual media with their own narrative.

Students take a still image of a mouth and make it interactive by recording their own voice. The teacher shares examples of how her students respond to literature with the Twitter community.

Literacy skill Fluency (re-telling)

Publishing

Comprehension (oral retelling) Vocabulary (expanding vocabulary by exploring visual media) Fluency (re-telling)

Publishing

Fig. 3 Book Creator to create digital storybooks

student’s name and cartoon emoji, positioned next to the class list that shows each student’s name and the number of items each student has posted. To filter and view an individual student’s work in isolation, a teacher clicks on the individual student name.

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Seesaw allows for the following: • Students can upload and request to submit their own creations to the class newsfeed. • Students can view and like their peers’ published work in the class newsfeed. • The teacher can monitor the newsfeed as a formative assessment tool. • Parents and other family members may only view their child’s work. PicCollage Kids. When students want to respond to visual media by using pictures as the basis for storytelling, Ms. Brown’s students’ use the PicCollage Kids app. Jamaal narrates the story of a photo he encountered on one page of his book, “this is a person that made bees mad and all the bees stung them” (Fig. 4). PicCollage allows students to identify and respond to visual media that is important and appealing to them. ChatterPix. ChatterPix is a fun app to engage students in storytelling because it moves the mouth of any image. In Ms. Brown’s class, Rosabelle makes a public service announcement focused on saving the earth by reducing deforestation by moving the mouth of a butterfly to captivate the viewer. The moving mouth enhances the appeal of the visual image and attracts video viewers (Fig. 5). Twitter. While Ms. Brown’s students were not using personal Twitter accounts (for safety and privacy reasons), she allowed students to publish their work to her class Twitter page. In this instance, Twitter was used as a collaborative tool to share

Fig. 4 PicCollage to respond to visual media

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Fig. 5 ChatterPix enhances a public service announcement

student work with other educators, parents, researchers, and app developers, noted by the hashtags (e.g., #edtech, #literacy) and @ identifiers (e.g., @BookCreator, @SeeSaw). Ms. Brown reflected on the most useful app: Seesaw has proven to be my favorite tool. It has given my students a way to document their learning as it happens. I have witnessed Seesaw empower my students to think deeper and reflect. It has given me the opportunity to teach digital citizenship and twenty-first century skills. The most rewarding part about implementing Seesaw is creating a community around learning. I have been able to involve families in real time and we have taken student feedback to the next level.

4.2

CBAM: A Final Reflection

Out of concern for implementing 1:1 iPads into her first-grade classroom, Ms. Brown sought guidance from a university researcher to help her students learn to use iPads. This partnership blossomed into a 2-year case study where the university researcher guided Ms. Brown through the CBAM’s stages of concern and levels of use with iPads. The university researcher also provided training support and monitored how Ms. Brown’s concerns with acceptance of iPads changed over time.

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Throughout this case study experience learning to use iPads as a teaching tool, data show it took Ms. Brown 2 years to advance through the CBAM stages of concern and levels of use. The greatest concern occurred at the management (3) level of concern, where she incessantly searched for suitable apps. Ms. Brown’s ability to achieve technological innovation in her teaching demonstrates the importance of monitoring the developmental process that accompanies integrating a new technology. Acceptance of an innovation is a process that requires time, guidance by an expert, and dedication to acquire new skills. Findings from this study present evidence about how a teacher can creatively use a tool to reshape the learning landscape in the classroom. However, change does not actualize until the teacher embraces challenges that accompany the change process. Ms. Brown learned that effective iPad integration required she first address her own personal concerns. Then, she needed to conduct independent research to feel comfortable with the iPad’s functions. Finally, she had to adapt her instruction to the students’ growing technological knowledge. Perhaps most remarkable, Ms. Brown recognized that for students to innovate and demonstrate creativity in their learning, she had to trust her students by giving them freedom to explore the iPads. Although this study is limited to one teacher’s experience with the 1:1 iPad initiative, findings from this longitudinal data act as a starting point to understanding the complexity associated when teaching with a new technology. This study’s examination of a teacher’s technology acceptance can help school administrators effectively deploy resources and assist teachers in anticipating barriers and concerns with technology integration.

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Future Directions

Future research should investigate a larger sample size of teachers who are also part of the 1:1 initiative, assess their stages of concern and levels of use, and apply some of the strategies and practices used by Ms. Brown at each of her developmental processes. It would be prudent to document a timeline that shows when other teachers move through each stage of concern and level of use. This timeline could illustrate technology integration barriers that occur at each stage of concern and level of use within the CBAM. This research could lead to the development of a comprehensive technology integration guide that accompanies each CBAM construct by visibly documenting (with estimated timelines) an individual’s acceptance toward technology.

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Cross-References

▶ Adoption of Mobile Technology in Higher Education: An Introduction ▶ Highs and Lows of Mobile Digital Technology Integration in Kindergarten ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts ▶ Mobile Technologies for Teaching and Learning

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References Aldunate, Roberto, and Miguel Nussbaum. 2013. Teacher adoption of technology. Computers in Human Behavior 29: 519–524. https://doi.org/10.1016/j.chb.2012.10.017. Casey, H., and G. Rakes. 2002. An analysis of teacher concerns towards instructional technology. International Journal of Educational Technology 3 (1). http://ascilite.org/archived-journals/ijet/ v3n1/rakes/. Accessed 17 July 2017. Cumming, Therese, C.D. Rodrıguez, and I. Strnadová. 2013. Aligning iPad applications with evidence-based practices in inclusive and special education. In Assistive technologies: Concepts, methodologies, tools, and applications, 397–420. Hall, Gene. 1976. The study of individual teacher and professor concerns about innovations. Journal of Teacher Education 27 (1): 22–23. Hall, Gene. 1979. The concerns-based approach to facilitating change. Educational Horizons 57 (4): 202–208. Hall, Gene, Richard Wallace Jr., and William Dosset. 1973. A developmental conceptualization of the adoption process with educational institutions. Austin: Research and Development Center for Teacher Education, The University of Texas. Hall, Gene, Susan Loucks, William Rutherford, and Beulah Newlove. 1975. Levels of use of the innovation: A framework for analyzing innovation adoption. Journal of Teacher Education 26 (1): 52–56. Harper, Ben, and Natalie B. Milman. 2016. One-to-one technology in K–12 classrooms: A review of the literature from 2004 through 2014. Journal of Research on Technology in Education 48 (2): 129–142. Haßler, Bjoern, Louis Major, and Sara Hennessy. 2016. Tablet use in schools: A critical review of the evidence for learning outcomes. Journal of Computer Assisted Learning 32 (2): 139–156. Hutchison, Amy, Beth Beschorner, and Denise Schmidt-Crawford. 2012. Exploring the use of the iPad for literacy learning. The Reading Teacher 66 (1): 15–23. Ifenthaler, Dirk, and Volker Schweinbenz. 2013. The acceptance of tablet-PCs in classroom instruction: The teachers’ perspectives. Computers in Human Behavior 29 (3): 525–534. Koehler, Matthew, and Punya Mishra. 2009. What is technological pedagogical content knowledge (TPACK)? Contemporary Issues in Technology and Teacher Education 9 (1): 60–70. Krutka, Daniel G., and Jeffrey P. Carpenter. 2016. Why social media must have a place in schools. Kappa Delta Pi Record 52 (1): 6–10. Lu, Ya-Huei, Anne T. Ottenbreit-Leftwich, Ai-Chu Ding, and Krista Glazewski. 2017. Experienced iPad-using early childhood teachers: Practices in the one-to-one iPad classroom. Computers in the Schools 34 (1–2): 9–23. Marich, Holly. 2016. Twitter in the elementary classroom: A teacher’s journey. Language Arts 94 (1): 67. McKnight, Katherine, Kimberly O’Malley, Roxanne Ruzic, Maria Kelly Horsley, John J. Franey, and Katherine Bassett. 2016. Teaching in a digital age: How educators use technology to improve student learning. Journal of Research on Technology in Education 48 (3): 194–211. Neumann, Michelle M. 2016. Young children’s use of touch screen tablets for writing and reading at home: Relationships with emergent literacy. Computers & Education 97: 61–68. Price, Sara, Carey Jewitt, and Lucrezia Crescenzi. 2015. The role of iPads in pre-school children’s mark making development. Computers & Education 87: 131–141. Stokes-Beverley, Christine, and Ian Simoy. 2016. Advancing educational Technology in Teacher Preparation: Policy brief. Office of educational technology, US department of education. http:// tech.ed.gov/earlylearning. Accessed 17 July 2017. Toppel, Kathyrn. 2014. Accelerating learning: Making the most of iPads in kindergarten. IRA E-ssentials: 1–10. https://doi.org/10.1598/e-ssentials.8047.

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Yongzheng Liu, Ziqui Zhang, and Yu (Aimee) Zhang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 East China Jiao Tong University (Rank 240 in China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 University of Science and Technology of China (Rank 4 in China) . . . . . . . . . . . . . . . . . 3.3 Beijing Information Science & Technology University (Rank 370 in China) . . . . . . . 4 Barriers Between Chinese and Australian/New Zealand Universities . . . . . . . . . . . . . . . . . . . . . 4.1 Policy and Structural Difference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Different Expectations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Cultural Differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Communication Barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Suggested Solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Y. Liu New Zealand International Education Exchange and Trade Development and Immigration Services Co. Ltd, Levin, New Zealand e-mail: [email protected] Z. Zhang Beijing Information Science and Technology University, Beijing, China e-mail: [email protected] Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_64

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Abstract

University collaboration generates enormous benefits. However, the majority of these collaboration outcomes are far from satisfaction. Previous literature focused on the number of co-authored publications as a measure of successful collaboration. However, new student enrollment, increasing of knowledge share, and global influences for both partners are also important for global collaborations. China has been the major recruiting source of undergraduate and postgraduate overseas students for many universities. Many Australian and New Zealand universities have Chinese universities as international strategic partners. However, differences between Australian and Chinese policies, structures, and cultures create barriers for these collaborations. The majorities of intercountry university collaborations were time-consuming with a high demand of human resources and did not generate anticipated outcomes. In this chapter, an analysis of the foremost obstacles highlights areas needing attention to ensure productive communication. To save transaction costs for appropriate collaborators and to increase the success rate in current collaborations, it is important to identify the key issues such university partnerships between Australia, New Zealand, and China encounter. This case study presents empirical evidence from observations conducted over the past 10 years of university collaborations, as well as face-toface interviews with collaborators from three pioneering Chinese universities. Universities between Australia/New Zealand and China have many differences, and some of them are barriers for international university collaborations. Mobile technology can address many communication challenges and potentially diminish misunderstanding between institutions. Possible solutions are discussed toward the end of this chapter. The chapter concludes with insights and potential action steps for future cross-country university collaborations for universities and educational institutions.

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Introduction

University collaboration generates enormous benefits, such as co-authored publications (Mccombs 2010; Qiu and Mcdougall 2013); the sharing of knowledge or data (Mccombs 2010; Kennedy et al. 2013; Keengwe 2013); the generation of new ideas, tools, and other intellectual properties (Fernández-López et al. 2013; Collins and Hammond 1997; Coad and Teruel 2013); and greater efficiency (Hwang and Chang 2011; Butoi et al. 2013). China has a very different educational system with 260 million students and 15 million teachers (in 2014) (OECD 2016). Intercountry collaboration has also been one of the major sources of international student enrollment for some Australian universities (Park 2013) and universities in other countries. Some universities are replying on international students as major revenue sources. With more international students enrolled, the universities are learning by providing more cultural and language services. They also learn from their Chinese partners through the university collaborations. Unlike research

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collaborations, student exchange programs usually take many years from the initial discussion to successful stable collaboration. The outcomes are also influenced by different factors, such as trust, cultural difference, location, distance, shared goals, and mutual benefits (Fernández-López et al. 2013; Hwang and Chang 2011; Coad and Teruel 2013), and are also associated with high costs and risks (Mccombs 2010; Fernández-López et al. 2013). Furthermore, students are different today (Zhang 2015c; Hunt and Zhou 2017) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). They seek information and opportunities online instead of following the paths which were prepared by universities. They have more choices and know how to design their education better. Previous literature focused on the number of co-authored publications as a measurement of successful collaboration. However, new student enrollment is another benefit generated from university collaborations (Park 2013). China has been the major source of both undergraduate and postgraduate overseas students for many universities (Balaram 2010). Many Australian universities have Chinese universities as their strategic collaborators. The majority of cross-country university collaborations, which took great amounts of time and efforts, did not generate expected results (Park 2013). It is arguably possible that motives and risks for university collaborations are also different between Australian and Chinese universities, which may explain the high failure rate. Therefore, to save transaction costs in seeking for suitable collaborators and increase the success rate in current collaborations, it is important to identify the differences of university collaboration in Australia and China. This study identified the differences and barriers between Australian and Chinese university collaboration and proposed potential solutions by adopting mobile technology in cross-country communication and teaching. Some suggestions are given for future cross-country university collaborations. This chapter focuses on Australian, New Zealand, and Chinese universities’ collaborations.

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Literature Review

The literature on cross-country university collaborations is plentiful (Sana et al. 2013; Qiu and Mcdougall 2013; Cheon et al. 2012; Hsu et al. 2013; Liaw et al. 2010). The types of collaboration are diverse from research (Mccombs 2010; Collins and Hammond 1997; Dabbagh and Dass 2013) to teaching (Sana et al. 2013; Reich and Daccord 2008; Liaw et al. 2010). China has a different higher educational system with more than 80% of schools and universities supported by the government (Zhang et al. 2009; Su et al. 2009; Balaram 2010; OECD 2016). The targeting benefits are usually more political than academic in China. Cross-country university collaborations between Western universities and Chinese universities are usually required to go through an official interface of each university instead of through individuals or research centers. Many cross-country university collaborations with Chinese universities failed to reach their expectation because of the misunderstanding of the different educational and managerial systems. Adopting only the number of co-authored publication as a measurement of a successful university collaboration

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does not suit the situation in China. China has special expectation on international educational collaborations (MEPRC 2003). Chinese universities take other benefits (such as political benefits and visiting trips) as more important outcomes from university collaborations. The regulations published by the Chinese government (MEPRC 2003) and relationships between universities and different government departments are important for university collaborations and the source of support or grants from the government in China. With the fast development of technology and job markets, the requirements for graduated students are also changing (Hunt and Zhou 2017). It also influenced the future of university collaboration. There are more and more short-term student visiting groups (from other universities, high schools, and even primary schools) now, which shows significant increasing trends in Australia from 2012 to 2017. The ages of international students are younger, and the required time length and visiting programs are more flexible. Universities from other countries are preparing for more Chinese students now, which increased the global competition on international students. Australian universities and schools should be preparing for new changes and growth in the market demands soon. The Chinese universities and Australian universities have many differences in international university collaborations in terms of goals, collaborating types, expectations, and barriers. This study adopted both qualitative observations and face-toface interviews with high-ranking administrators in different departments in universities. A qualitative case study approach identifies current collaboration types, barriers, and key determinants for Chinese universities’ collaborations with international partners. Researchers conducted interviews with the international officers, vice presidents of the universities, dean of faculties, contact person for research and teaching collaborations, and directors of research centers in three Chinese universities. Insights related to the Australian and New Zealand universities’ collaboration with their Chinese partners suggest specific action steps. All authors in this study have been involved in different level of university collaborations as the key contact person between universities. The results will provide suggestions for both Chinese universities and Australian/New Zealand universities on their global collaboration strategies and current collaborations with each other. It also shed a light on developing future cross-country university collaborations between Chinese universities and universities from other countries.

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Case Study

Universities collaborate with global partners on various types of activities and programs, such as international conferences, visiting meetings, workshops and seminars, undergraduate and postgraduate exchange projects, teaching, and research collaborations. Most of the Chinese universities seek supplementary educational resources, good experience, and bilingual educators through international collaborations. They have been urged to connect with the global education level and quality. China has a very special educational system with more than 260 million students and 15 million teachers (OECD 2016). Chinese universities have both traditional

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Table 1 Interviewed universities and agents for international university collaboration Studied universities University of Science and Technology of China: Professor Wang Rongsen

Beijing Information Science &Technology University: Professors Ge Xinquan and Li Chen East China Jiao Tong University – VP Shi Huanping

Types of collaboration Guest professor, visiting professor, 3 + 1 + 1 student undergraduate + postgraduate programs, visiting research fellow, joint education for PhD, Microsoft-sponsored mobility study project, CSS scholarship, research collaboration Visiting research fellow, teachers training program, 3 + 1 or 2 + 2 undergraduate student program 2 + 2 undergraduate student program, 1 + 1 postgraduate, international conference, visiting trips

Collaborating partners America, Australia, the UK, Canada, Japan, Hong Kong, Taiwan, and Switzerland

America, Australia, Japan, and Ireland

America, the UK, Taiwan, and Russia

Source: Interview from this study

teaching system and open-minded collaboration programs after the educational reform in 2001 (OECD 2016). China has announced the global university collaboration policy for years. However, there are some problems with the implementation of the policy in practice. This study focused on the types, barriers, and key determinants for successful cross-country university collaboration between Australia/New Zealand and China. This study is an international collaboration study on three Chinese universities and Australian/New Zealand universities. To study the barriers for international university collaborations, personnel at three Chinese universities were interviewed for a case study, including university presidents, deans, heads of schools, international officers, professors, and managers, to understand the different opinions and expectations from different departments in universities. The universities, associated agents, and partners are listed in Table 1.

3.1

East China Jiao Tong University (Rank 240 in China)

The East China Jiao Tong University (ECJTU) was established in 1971. It is located in Nanchang, Jiangxi Province, China. ECJTU has 17 faculties and 60 undergraduate majors. It had more than 22,000 students and 1,600 staffs in 2013 (when the study was conducted). It also provides master and PhD degrees. ECJTU had collaboration with many international universities, such as universities from America, the UK, and Russia. ECJTU established a reciprocal relationship with the transportation department rather than local government (due to the history of this university). The interviews were conducted with the vice president, Professor Shi Huanping; associate dean of economics and management faculty, Professor Han Shizhuan; associate dean of international faculty, Professor Zhou Liping; dean

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of international faculty and international officer of ECJTU, Professor Fan Yong; and Professor Shang Yong and Professor Tang Bin from the international faculty in ECJTU. The different views and visions provide better answers to the research questions in this study. As the Chinese government requires 4% of GDP invested into higher education, ECJTU received four million RMB for lab and infrastructure projects. One third of the staff in transportation system was from the university. The faculty of economics and management in ECJTU has 10 undergraduate majors with about 500 undergraduate students and 200 postgraduate students. ECJTU had many collaborating projects with international universities. The types of collaboration include 2 + 2 undergraduate student program with the UK (approved by educational department from the government), 1 + 1 postgraduate with the USA (high expectation from students), international conference on transportation, and visiting National Taiwan University. ECJTU also planned for international collaboration on postgraduate studies. However, the high tuition fees and global reputation of the partner universities became barriers for enrollment. They took openness, action, and sharing as the key determinants for successful university collaboration. In terms of seeking for international partners, the research ranking and reputation of the vice chancellor of partner university and research centers are regarded as important selective factors.

3.2

University of Science and Technology of China (Rank 4 in China)

The University of Science and Technology of China (USTC) was established in 1958 in Beijing, China, and was chaired by Mr. MoruoGuo. It moved to Hefei, Anhui Province, in 1970. USTC has 15 faculties and 30 majors and master’s and PhD degrees. It had about 15,500 students and 1,572 staffs in 2013 (when the study was conducted). Ranked as top four universities in China, USTC is similar to highranking university in Western countries. USTC has established relationships with universities from America, Australia, the UK, Canada, Japan, Hong Kong, Taiwan, and Switzerland. Professor Wang Rongsen, Professor Lu Wei, and Professor Jin Hong accepted the interview of this study. The average publication on journals is seven per person per year in economics school in USTC. Personnel deeply understand the organizational structures and administrative processes of international universities. Most teachers and students either have experiences with a program of foreign study or an international research project. Professors and researchers were English language proficient. Currently, USTC collaborates with international universities on different projects, including guest professor, visiting professor, 3 + 1 + 1 student undergraduate and postgraduate programs (with Taiwan, American universities), visiting research fellow, joint education for PhD, international enterprises sponsored study project, CSS scholarship, and research collaboration.

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USTC also has many visiting professors from international universities. The medical insurance during visiting was problematic. They require the coverage from the partner universities. If the visiting professor is over 60 years old, the Chinese government now requires health report and insurance. Technically, extended stays in China for academic visitors over 65 do not receive approval. The understanding of the medical service in China is another problem facing the foreign visitors. USTC administrators believe the contact person is vital for success university collaboration. The quality of visiting researchers is important but often challenging to identify. The selection process for a visiting professor usually starts with the USTC sending an invitation to the dean of faculty or head of school at the partner university with a request to recommend a short list of potential visiting professors.

3.3

Beijing Information Science & Technology University (Rank 370 in China)

Beijing Information Science & Technology University (BISTU) was formed in 2008 by the combination of two institutions: Beijing Institute of Machinery (BIM) and Beijing Information Technology Institute (BITI, which was the second branch school of Peking University in 1978). It had approximately 15,000 students and 11 faculties in 2013 (when the study was conducted). The dean of commerce, Professor Ge Xinquan; dean of information management, Professor Li Chen; associate dean of arts, Professor He Shensi; vice president, Professor Xu Xiaoge; and previous international officer, Professor Fan Yutao, participated in the interviews of this study. Originated from the Computer Science College of Beijing University, BISTU has a strong background and national reputation in computer science studies and, historically, connects with the first generation of computer science human resources in China. It had collaborated with universities from America, Australia, Japan, and Ireland. The types of collaboration included visiting research fellow, teachers training program, and 3 + 1 and 2 + 2 undergraduate student program. BISTU had many projects sponsored by the Chinese government and Beijing local government. The policy change from close policy in educational collaboration to open policy that encouraging international collaboration in China affected the higher education collaboration (OECD 2016). Now, each program and associated visitors need to be approved through a process directed by the Chinese government. The Australian policy change on master programs (2 years now) also influenced collaboration. The master collaboration has been ceased since then. Another barrier for Australia-China university collaboration (not only for BISTU but also other Chinese universities) is the expectation from students and their families. Chinese families take education as top priority and spend more on education than families from other countries. They only target on top one universities of the world. The universities from the USA and UK have very high reputation in China. More than 80% of the students never considered other countries as overseas study destinations (Zhang 2015c).

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The interviewees in BISTU admitted there were only one or two students per year who exchanged their studies successfully with the University of Wollongong after the 2 + 2 student exchange program was established. With increasing global competition from other universities, how Australian universities compete in the internal student market is vital to increase global reputation and competitiveness. The interviewees in BISTU also agreed that the role of contact person is linchpin for international collaboration. “Sometimes, when the contact person left, the collaboration between two universities was closed (Interviewee).” Because language communication often hinders collaborative research efforts, advancing academic language development is crucial for international collaboration.

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Barriers Between Chinese and Australian/New Zealand Universities

The purpose of global educational collaboration targets utilizing different resources and advantages and teaching and educating composed of high-quality human resources with global educational background and different languages background. It can also increase and enhance teaching quality for students at both universities and allow the Chinese universities or institutions to learn from their global partners. To facilitate the global educational collaboration, the Chinese government published the “Chinese-Foreign Cooperation in Running Schools Regulation” (CFCRS Regulation) in 2003 (MEPRC 2003). The higher education community in China has experienced reform during the past three decades. However, obstacles still prevent international university collaboration between Chinese universities and Western universities. For example, based on more than 10-year observation on China and New Zealand/Australian university collaborations, barriers thwart university collaborations between Chinese universities and foreign universities. China and Australia/New Zealand have very different economic histories, structures, and performances (Zhang 2012). The educational system in China differs from the educational system in Australia and New Zealand (OECD 2016). Therefore, the goals and expectations for international university collaboration often misalign. The foreign collaboration regulations published by the Chinese government also indicate different expectations for global collaboration (MEPRC 2003). Major barriers universities encounter are summarized in the following table and explained in the next sections (Table 2).

4.1

Policy and Structural Difference

Early barriers for international university collaboration among Australian, New Zealand, and Chinese universities are policy and structural differences. Strict governance regulations and investigation requirements for foreign universities and educational institutions influence how global educational collaboration starts. The CFCRS Regulation limits the inclusion of foreign partners to universities or colleges

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Table 2 Barriers for international university collaborations Major barriers Policy and structural differences Different expectations Cultural differences Communication barriers

Risks Student exchange and visiting staff Cannot reach an agreement or expectation Misunderstanding Misunderstanding and delay

Source: Observation from this study

only. However, these collaborations usually include foreign enrollment, visa application, accommodation for students, evaluation on teaching materials from both sides, and teaching collaborations. Some students enroll in courses at different universities or faculties. Furthermore, the different legal systems, regulations, and policies in different countries influence peoples’ thinking, behavior, and custom. To increase efficiency and quality of services, the foreign universities usually contract some services to educational agents to sign contracts or negotiate collaboration with Chinese partners. They only follow the agreement to provide teaching services, an agreement that does not adhere to the CFCRS Regulation. Chinese universities are regarded as state-owned institutions, which is directed by government departments and regulations (OECD 2016). The advantages for such centralized system include (1) plentiful funds and resource supports from the government; (2) separate functions and regions in planned development; (3) resource relocation with administrative-level management for changes; and (4) quality assurance from province or central government level. However, the disadvantages from this governance include (1) limit to the number of international collaborations and visitors; (2) little differential development and enrollment; (3) widened inequity as over-allocated resources to top universities; and (4) delayed approvals due to bureaucracy. For example, personnel and researchers employed at Chinese universities (Chu Ji and above) are limited for their international traveling per year. Some policy changes may influence international university collaboration. For example, as aforementioned in this chapter, BISTU ceased collaboration around master’s programs with Australian partners due to the 2-year residency requirement in Australia. USTC also eliminated invitations for senior researchers over 65 years old, due to the new regulation by the Chinese government (considering the potential risks for health issues). As more than 80% educational institutions are supported by the government in China (OECD 2016), universities are regarded as not-for-profit institutions. The expectation on foreign collaboration is that the collaboration should be not-for-profit too (interviewee). However, this is not very attractive among Australian and New Zealand universities. This difference brought a problem for international collaboration when the drives for collaboration between the collaborating partners are mismatched. Australian government also requires the collaborating universities to maintain a formal representative agent in China. Australian universities rely on agents to enroll new students and provide visa, insurance, and consultation services. They pay

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commission fees to these agents for new enrolled students too. However, the number of approved agents in China is very limited due to the strict investigation and supervision in China. Many small agents have to collaborate with the approved agents by paying them “rental fees” for adopting their names. The quality of services provided by these agents varies dramatically. This type of collaboration lowered the average quality of service provided to Chinese students. The role of the international educational agents is deemed inappropriate in the Chinese market. In a global collaboration, Chinese universities usually avoid any agent’s name to appear in agreement or activities (interviewee). Another barrier toward international university collaboration is the structural difference in Australia/New Zealand and China. International university collaboration or program must go through a special department – international office in Chinese universities. Typically, a professor with international experience or educational background manages this office. They plan the visiting trip for all staff or teachers, send invitation to other partners, enroll and manage foreign teachers, sign agreements with international partners, and monitor the international projects. Any international project or visit requires approval by the international office. Therefore, the personal relationship with the managing professor in the international office is vital for any international collaboration. If the person in charge of the international office changed (e.g., retired), the collaboration would be substantially different. In Australia and New Zealand, international office is also important in each university. However, the detailed negotiation, credit certification, and teaching and research collaboration usually are regulated by different faculties, schools, research centers, or individual researchers. Similar research interests, publications, and grants application are usually the drives for collaboration between researchers. However, these types of collaboration are not regarded as formal collaboration in Chinese universities. The universities must sign an agreement at the “university level,” followed by agreement at the “faculty level,” before any collaboration is formally conducted by individuals. The different structures are barriers for international collaboration.

4.2

Different Expectations

The second barrier for international collaboration is different expectations. Universities, like firms, usually look for highly academically ranked partners in global collaboration. However, collaboration with similar level partner can reach better results (Zhang 2012). Chinese universities usually took the ranks of partner universities and quantity of collaborating countries/universities as political achievement. The global reputations of visitors and government-supported grants are also important results expected by Chinese universities. The universities in China evaluated the successful collaboration by a number of signed agreements and visiting programs and variety of collaborating types with their partners. Enrolled student numbers (the exchange programs are usually not equal for Chinese universities) and publications are usually value added for schools or individual researchers (not the universities).

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However, in Australia and New Zealand, universities usually collaborate with Chinese universities for their international students. They expect to enroll more students through 2 + 2 or 3 + 1 undergraduate program or 1 + 1 postgraduate program. The universities in Australia and New Zealand evaluated the success of their international university collaboration by enrolled student numbers (for student exchange programs) and published journal articles or grants (for research collaborations). The different goals for collaboration also brought problems for future collaboration. On the other hand, the different evaluation of journals and publications is another barrier toward international collaboration. Australia has its own evaluation system on journal publications. Only level A or A* journal publications are encouraged by faculties and universities now. This excludes many Chinese journals in China, which are regarded as high-ranking journals by Chinese universities. In China, many American journals are also ranked high by universities. Some level B or level C journals in Australia could be important publication journals in China. The different evaluation systems brought problems in international collaborations in terms of publication results. Teaching is a respected profession in China from its traditional education history (OECD 2016). There are many teaching professors in Chinese universities. Sometimes, a professor is not necessary to be a PhD. Therefore, they expected the visitors or collaborators to be a professor too. In Australia and New Zealand, not many professors in each university are usually busy with their research projects. The Chinese universities usually expect that the visiting group include the vice chancellor (top-level principal in a university), dean of collaborating faculty, and international officer. It is important to send the same level of managers to the meeting with visitors in China. However, this is usually difficult for Western universities. Some research projects only included one or two key researchers for visiting trips. The different expectations prohibit the success results of international university collaborations.

4.3

Cultural Differences

Cultural difference is a big topic in any international collaboration. It is vital for global collaboration (Zhang 2012; Grimm et al. 2016; OECD 2016). Australia and New Zealand have deal-focus culture (Gesteland 2012), which deal comes first. However, China has a relationship-focus culture (Gesteland 2012), which usually required the partner to be a friend to start any kind of collaboration. Contract is important in deal-oriented but not relationship-focus cultures. Any structured formal contract or presentation of lawyer in a meeting before the friendship establishment generates distrust in China. Dining is very much a part of establishing business relationships in China. There are many hidden rules in Chinese dining, and the Australian government published an article “doing business in China” to help business understand these cultural differences (Austrade 2013). However, it should be argued that the general rules may not suitable for different provinces or regions.

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Chinese people usually use indirect language in negotiation to “save face.” Expressive facial or body language and intense or firm eye contact in a meeting are not welcome in China (Gesteland 2012). “Sincerely” means “say it as it is” in Australia but “say it indirectly to help others” in China. The schedule is made 1 year early in Australian universities but 1 week to 1 month early in China. However, the expected responding time for email and message in China is usually within 1 day. All those important differences brought problems for international collaboration between Australian/New Zealand and Chinese universities. Another factor that plays an important role in business collaboration in China is business gifts. The studied Australian university had been sending their Chinese partner clocks as gifts for 5 years, which is regarded as “the end of life” in China. In China, white chrysanthemum (or blue or yellow flowers) are only used in funerals. However, they are usually used as gift for newborn or wedding in Australia. Clock/ watch (pronounced as end of life), comb or book (pronounced as lose), and handkerchief and cards written in red ink (means end of relationship) are not good gifts. A gift from the city or state that the Western university is located is usually a sign of friendship in collaboration. To reach a successful international collaboration, whether for business or university, great emphasis should be put on cultural differences.

4.4

Communication Barriers

Communication barriers are also important for international university collaboration between Australian/New Zealand and Chinese universities. Firstly, Australia and China have two to three time differences due to the time zone differences (Austrade 2013). Secondly, the social media in China is very different from the other countries (Zhang 2012, 2015b). Thirdly, the holidays are different in Australia and China, including school sessions and public holidays. The public holidays and cultural holidays in China include 1 January, New Year’s Day; late January/February, Spring Festival/Chinese New Year; 8 March, International Working Women’s Day; April, Qingming Festival (in lunar calendar); 1 May, Labor Day; 4 May, Youth Day; May, Duanwu Festival (in lunar calendar); 1 June, Children’s Day; 1 July, anniversary of the founding of the Communist Party of China; 1 August, People’s Liberation Army Day; and 1–2 October, National Day. The different holidays greatly influenced communications between universities. Table 3 showed the different holidays in China and Australia in 2014. There are many activities and events in universities in the start of a semester (for orientation, select subjects, and change tutorials in Australia) or end of a semester (for final exam, marking, and graduation); the best period for communication or visit in a year is from late May to early June or late October to early November. The delay of responses initiated barriers for collaboration and generated misunderstandings, e.g., an out-of-office auto-reply email from an Australian university is regarded as a refuse email for visiting a group in China, which caused the end of collaboration between both universities.

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Table 3 Different holidays in China and Australia

Month Jan Feb Mar Apr May Jun

China Autumn Semester 1-5 New year Holiday (25 Jan – 9 Feb) Spring Semester Qing Ming 4-6 Labor Day 1-7 Duanwu (31 May – 2 Jun)

Jul Aug Sep Oct

Holiday Holiday Mid-Autumn 6-8 National Day 1-7

Australia New year 1 Australia Day 26 Recess Autumn Semester Labour day 3 Easter 18-21 ANZAC 25 Autumn Semester Autumn Semester to 26 Jun, Queens’ birthday (different in QLD and WA) Recess Spring Semester starts 28 Jul Spring Semester, Labour Day first Monday in October Spring Semester to 20 Nov Holiday Christmas 25-30

Nov Autumn Semester Dec Autumn Semester Source: Observation from this study The boxes show the suitable communication period for the Chinese university and its foreign partner in a year

The Chinese universities will not respond emails or telephone call during holidays (or 2–3 days near holidays) because staffs usually take annual leave before or after holidays. In Australia, the deputy officer will answer emails in place of the leave manager. However, if the manager in charge is not available, the deputy officer in China will not answer emails to avoid any mistake. The technical problems are very common in Chinese universities, and sometimes the emails cannot reach the expected person in time. All of these barriers threaten international university collaboration. One problem could cause the end of collaboration or years of delay. To solve those problems, some suggestions are introduced in the following section. Mobile technology and solutions could greatly enhanced global collaboration for a better result. With the fast development of mobile technology and social media in recent years, Chinese social media communication markets are dominated by QQ and WeChat (see ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”), which are not very popular in most Western countries. The most popular social media in Australia and other Western countries, such as Facebook, Twitter, and LinkedIn, are not popular (or blocked) in Mainland China (Zhang et al. 2009). The survey among Chinese students indicated that majority of Chinese students use QQ and WeChat as communication tools (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Parents play an important role in students’ selection in China (see ▶ Chap. 9, “Parental Education: A Missing Part in Education”). Some universities in Australia have found the important role that Chinese social media plays in reaching potential Chinese students and their parents. They established WeiBo and WeChat (the most popular Chinese social media platforms) public accounts to promote their brand

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and attract potential students. They also collaborate with Chinese immigration and educational agents (more active on Chinese social media) to enroll new students. Mobile technology and instant communication tools made the information more transparent to students and parents. They also increased efficiency of enrollment processes.

4.5

Suggested Solutions

There are many factors that influenced successful cross-country university or business collaborations. Cultural and country differences are one of the most important factors. Showing respects to each other and following the rules and regulations in different countries are very important during global collaboration. A clear responsibility for each party in the global collaboration is also important. Chinese universities are usually responsible for enrollment and advertisement; teaching and management in China; assisting document accumulation for visa application for students; evaluation for students; management of students when they study abroad; and giving the graduation certifications. The third-party agents or representatives are responsible for visa application for students; services for students who study abroad; group visit and services from Chinese universities; communication between both universities; and problem-solving. Australian or New Zealand universities are responsible for teaching abroad; evaluation and assessment of students abroad; management and evaluation; and graduation certifications abroad. The roles can be changed in certain cases. However, responsibilities are usually written in an agreement or contract clearly before the start of global collaboration. Financial problems and costs issues are usually the most common problems during global university collaboration. A transparent financial design and instant communication are always required during global collaboration between universities. The third party between both universities is usually important for communication and problem-solving. They usually have very high trust level with both universities. Problem-solving procedures rely on trust and clear communication. To collaborate with Chinese universities under current regulations and rules, it is important to create innovative collaboration models for a successful collaboration. As listed in Table 4 below (some of them are already adopted and implemented by Chinese and foreign universities), there are usually many different collaboration models due to the real cases between universities. Some universities in this study have adopted collaboration models concurrently with different universities. The selection of collaboration model is based on the context of each university, the requirements from the policy and rules in each country, the quality and numbers of expected students, and the negotiation between both universities in a given period. Some suggestions for meetings and negotiations with Chinese partners include the following: (1) business professional attire should be worn when interacting with the Chinese universities; (2) produce a Chinese business card with Chinese characters (not all professors and staffs can read English); (3) exchange business

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Table 4 Collaborating between Chinese and foreign universities under regulation 1. Continuing education

2. Student exchange

3. Based on real collaborating projects

4. Hybrid overseas universities/ institutions

This is called “3 + 2” collaborating mode. Students need to finish 3-year vocational study in Chinese college and pass IELTS 6.0 to enroll into a 2-year course study in foreign university to get their bachelor’s degrees b. Vocational to This is called “3 + 3” collaborating mode. postgraduate degree Students need to finish 3-year vocational study in Chinese college and pass IELTS 6.5 to enroll into a 3-year (including 1-year prepared class, 1-year master’s course, and 1-year master’s degree study) master’s degree study c. Undergraduate to This is called “4 + 2” collaborating mode. postgraduate degree Students need to finish 4-year bachelor’s study and pass IELTS 6.5 to enroll into a 2-year (including 1-year master’s course and 1-year master’s degree study) master’s degree study d. Credit transfer This refers to the undergraduate or vocational for courses students in Chinese universities who pass IELTS 6.0 and want to study abroad. Their Chinese course credit can be transferred into the foreign courses if they passed the evaluation of the foreign university e. Continuing study All the previous collaborating modes have English language requirement (IELTS 6.0 for bachelor’s and 6.5 for master’s students) for new enrollment. If a student cannot get required IELTS score, he/she can also get conditional offer from foreign university. They can study a 3–12-month English course and pass IELTS test or similar test required by the university to continue his/her study there This collaborating mode is based on university visiting and investigation before they sign the formal “2 + 2” student exchange agreement. Both universities agree on each other’s course credit for their collaborating majors. Students need to finish a 2-year undergraduate study in the Chinese university and then finish another 2-year study in foreign university to get degrees from both universities. This collaborating mode is usually based on matured majors in both universities and can be extended to other collaborating modes later a. English training for Chinese staff b. Overseas teachers’ enrollment for Chinese university c. Teachers’ training (groups) in foreign university d. Foreign students’ enrollment for Chinese university e. Chinese high-level managers’ group visiting service f. Introducing foreign teaching curriculum and measures This collaborating mode is a newly registered educational institute which belongs to a university that is approved by NZQA (New Zealand Qualifications Authority) and its Chinese partner. The hybrid institute is usually small but has special characteristics. It can enroll both Chinese and foreign students and increase the global reputation of Chinese a. Vocational to undergraduate degree

(continued)

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Table 4 (continued)

5. Grants application and publications

partner. There are universities from Japan, Taiwan, and Mainland China who have opened their foreign college in New Zealand, for example, the Auckland Institute of Studies by the National Taiwan University and the Auckland College of Natural Medicine (for Chinese medical major and acupuncture major) by the Liaoning Chinese Medical University. The university from Liaoning, China, arranges visiting from China to New Zealand as well as from New Zealand college to China The different grants from governments are the bridge for international collaboration. There are many different government grants in China from different programs to support not-for-profit universities, and global experts are usually welcome in those programs. Collaboration on grants application and projects are usually popular in international collaboration between Chinese universities and researchers from other countries. It usually generated satisfied results (publications and reports) for both parties

Source: Observation from this study

card and gift with two hands; (4) attend dining to establish personal connections; (5) engage in personal chats before a professional meeting; (6) prepare a gift (avoid books, combs, clocks, or white flowers) that are representative of your country or city; (7) establish a communication chain with an appropriate individual who can facilitate and/or make decisions; (8) show respect to high status; (9) don’t use red ink when writing; and (10) avoid public holidays for business communications. It is important to have a personal communication number instead of using the formal university email in China. Chinese people usually have QQ and WeChat as instant communicate tools (Zhang 2015b). WeChat is a free mobile application that can be downloaded from the Apple Store or Google Play for free. It also has English version. The voice message or message can be preserved in their mobile phone for a convenient time to be read. Most of the famous communication tools and websites are blocked or half-blocked in China, such as Google, Facebook, and Twitter. There are sometimes technical issues with email communications too. Therefore, the instant communication tools in China are highly recommended for communication with Chinese universities. More and more international offices in Australian universities are hiring staff with Chinese background to communicate with Chinese partners now. They greatly increased communicating efficiency and reduced misunderstanding with Chinese partners. Mobile technology can also assist teaching and research projects (see ▶ Chaps. 27, “Tutors in Pockets for Economics” and ▶ 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”). An instant communication, interactive teaching, and multimedia contents can engage students better and reduce misunderstanding (Zhang 2015a). The examples of mobile teaching projects are introduced in other chapters (Zhang 2015a, b, c; Zhang and Hu 2015).

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Future Directions

University collaboration outcomes are usually far from satisfaction between Australian/New Zealand and Chinese universities. The reasons include political differences, structural differences, different expectations, cultural differences, and communication barriers. This study suggests some collaborating modes and solutions for successful international university collaboration between Chinese and foreign universities. To enhance the performance of international collaboration, mobile technology could be adopted in global university collaboration. It increased the response rate and efficiency in communications, reduced misunderstanding, and increased the performance for collaborating projects. It provides a supplement method for faceto-face communication and greatly reduced the communicating cost in collaboration. It also brought new potential collaborating types for international university collaborations such as video teaching and interactive teaching. The fast growth in the market demand of variety programs and age range for younger learners will drive the change in the global market. The more adaptive and flexible the universities and schools are, the more opportunities will open for them. In the future, mobile technology will bring new opportunities to university collaboration as well as the educational industry to provide more convenient learning materials and better learning experience and services to students and individuals. China has experienced fast economic growth and policy reforms in the past 10 years, and this will be the drive for new collaborations between Chinese universities and their global partners. Technology has been developed fast and changed many industries including education. The way people communicate with each other has been dramatically changed by technology and mobile phones. Communication and collaboration between universities are also changed. The future of collaboration will be more transparent, efficient, and convenient.

6

Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Parental Education: A Missing Part in Education ▶ Tutors in Pockets for Economics

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Part V Evaluation of Mobile Teaching and Learning Projects

Evaluation of Mobile Teaching and Learning Projects: An Introduction

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Abstract

The percentage of people who have access to technological devices has proliferated, which, in turn, has expanded the utility and accessibly of mobile devices for both noneducational and educational purposes. Despite the Joint Information Systems Committee’s (JISC 2011) call for systematic evaluations of mobile learning initiatives almost a decade ago, evaluation projects that take a systematic approach at determining the value of mobile learning are scarce. More knowledge is needed to better understand the organizational support needed for their successful deployment, how to operationalize fidelity of implementation when unintended consequences transpire, and how best to measure the impact of mobility on learning. The chapters in this part entitled “Evaluation of Mobile Teaching and Learning Projects” begin to tackle these issues by articulating the myriad of issues to consider when evaluating mobile learning initiatives in education. These evaluations are primarily positioned in higher education but also span K-12 and informal settings. Taken together, these chapters exhibit the necessity for evaluations to focus on the technology, the user, and the context. Also, the chapters accentuate evaluating the mobility of the person and the learning process, rather than the mobility of the device, per se. We live in an ever-evolving society, and technological advancements are a central reason for the increasing speed by which changes occur. Equally, the percentage of people who have access to technological devices has proliferated. A recent study conducted by ACT of college-bound, high school students in the USA, for example, found that almost all students (99%) had access to at least one technological device, R. Moore (*) ACT, Inc., Iowa City, IA, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_23

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85% of students had access to multiple devices (Moore et al. 2018), and the smartphone was the most prevalent (Moore 2018). Accessibility to technology is also a global trend (Bano et al. 2018; Crompton and Burke 2018; Crompton et al. 2017; Wu et al. 2012). Each generation of new mobile devices likewise has increasingly more sophisticated features like email, mp3 players, video, cameras, picture quality, and a stronger Wi-Fi connection. This, coupled with the affordability of owning a mobile device, has expanded the utility and accessibly of mobile devices for both noneducational and educational purposes. With most of the mobile device users of high school and collegiate ages (Pew Research Center 2017), it is not surprising that the field of education has integrated technological advancements in teaching and learning. A recent survey found that 73% of teachers had their students use smartphones to conduct internet searches and almost half of students reported using e-readers and tablets to complete in class assignments (Purcell et al. 2013). More recently, a survey of high school students (Moore and Vitale 2018) reported daily use of technological devices for schoolrelated activities including checking grades, emailing the teacher, researching information, and using school-related applications. Mobile devices – given their ubiquitous connectivity, portable nature, and sensitivity to context – have the potential to transform and redefine the teaching and learning experience. This is because mobile devices reflect the fluid and unrestricted nature of learning providing students with a personalized learning environment (Sharples et al. 2007) and anytime, anywhere support (Suarez et al. 2018). Mobile devices also provide students with experiences that allow them to be agents of their own learning instead of just consumers of information (Crompton and Burke 2018; Suarez et al. 2018) because teachers can more easily implement inquiry-based teaching methods (Bano et al. 2018). Research has shown that mobile learning improves educational outcomes. Mobile learning exposes students to collaborative problem-solving (Sung et al. 2016), improves critical thinking skills (Crompton et al. 2017), and advances academic achievement (Sung et al. 2016). On the other hand, research has also shown that students have a limited understanding of how to use mobile devices for learning purposes (Park 2011) and teachers have been reluctant to change their pedagogical beliefs to include mobile learning (Wang et al. 2009). Technological limitations like small screens, internet connectivity, and device-to-software capability have also muted their impact (Wu et al. 2012). Despite the Joint Information Systems Committee’s (JISC 2011) call for systematic evaluations of mobile learning initiatives almost a decade ago, evaluation projects that take a systematic approach at determining the value of mobile learning are scarce. More knowledge is needed to better understand the organizational support needed for their successful deployment, how to operationalize fidelity of implementation when unintended consequences transpire, and how best to measure the impact of mobility on learning. While some experts have developed evaluation frameworks that focus on an evaluation of the learning as opposed an exclusive analysis of the device (e.g., Eliasson et al. 2011; Levene and Seabury 2015; Motiwalla 2007; Sharples 2009; Vavoula and Sharples 2009), none have been comprehensive and

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rigorous enough to reflect the continuously changing technology, the pedagogical implications of mobile learning, and the intersection of theory, practice, and policy. The chapters in this part, entitled “Evaluation of Mobile Teaching and Learning Projects” articulate the myriad of issues to consider when evaluating mobile learning initiatives in education. These evaluations are primarily positioned in higher education but also span K-12 and informal settings. Taken together, these chapters exhibit the necessity for evaluations to focus on the technology, the user, and the context. Too, the chapters accentuate evaluating the mobility of the person and the learning process, rather than the mobility of the device, per se. In ▶ Chap. 53, “Moving Towards the Effective Evaluation of Mobile Learning Initiatives in Higher Education Institutions,” Helen Farley and colleagues focus on the practical and theoretical implications of implementing mobile learning initiatives in higher education. They begin with a description of current mobile learning uses and their intended pedagogical goals. They then move onto articulating how mobility shapes teaching and learning and stretches the imagination for how to apply this work to evaluation. Through a critical synthesis of existing frameworks for evaluating mobile learning, the authors posit their own evaluation framework. They integrate organizational, technical, and pedagogical considerations as well as indicators of technological readiness from data collected from a 3-year research project in an Australian regional university. Melissa Nursey-Bray and Rob Palmer, in ▶ Chap. 59, “Adapting to Change: A Reflective History of Online Graduate Certificate and Its Implications for Teaching Geography,” used critical reflection as a methodological approach for understanding how pedagogical limitations, institutional support, and workload realities can make or break the success of an online certificate program in geography. The program, a series of four online courses, grounded in problem-based learning (PBL) did not garner the level of student enthusiasm that was projected. The authors found that they overlooked the prerequisites needed for success, including detailed instructions for how to work the interactive PDFs, compatibility of devices and web browsers with the PDFs, and course cost comparisons, to name a few. In ▶ Chap. 54, “Internet-Based Peer-Assisted Learning: Current Models, Future Applications, and Potential” Tairan Kevin Huang, Jin Chi, Corinne Cortese, and Mathew Pepper present a compelling illustration of how emerging technology can be used for Peer Assisted Learning (PAL) . The authors posit an implementation structure of PAL that includes their use on campus, online/mobile, or in combination. This complexity, however, creates challenges for evaluation. While research has already shown the effectiveness of traditional face-to-face PAL programs, mobilebased PAL programs cannot be physically observed or recorded easily. Therefore, determining whether and how participation is related to academic performance must be reconfigured. The authors address these complexities and how evaluators can move forward. In ▶ Chap. 56, “Mobile-Assisted Language Learning: How Gamification Improves the Learning Experience,” Izabel Rego de Andrade engages students in the learning of a new language through gamification. She argues that mobile technology must promote the skills that traditional teaching cannot adequately

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address. Mobile technology, in general, and gamification, more specifically, provide an opportunity for students to talk with native speakers and learn about the culture of that language easier than in a traditional classroom setting. The use of gamification, however, must be done with pedagogy at the forefront. Therefore, the author outlines necessary elements for gamifications and then evaluates three gamification offerings based on these elements. The author provides a concrete set of criteria from which to determine whether gamification can improve educational outcomes. Melissa Nurse-Bray in ▶ Chap. 55, “Mobiles, Online Learning, and the Small Group Discovery Classroom: Reflections from South Australia” describes four scenarios in which mobile learning was integrated into small group investigations. Using interviews, survey responses, and reflective analysis, Nurse-Bray evaluates the effectiveness of using mobile devices from both the teacher and student perspectives. Managing student expectations of the technology, articulating how the technology should be used, and matching well the technology with the learning goals were a few of the lessons learned. Learning is mobile; exploring is mobile. It would only make sense that mobile devices would be used when students are out in the field working on service learning projects. Margaret Sass in ▶ Chap. 57, “Service-Learning Application in an M-Learning Course” succinctly makes this connection by summarizing the mobile learning and service learning literature. She then describes how social media sites (e.g., digital badges, Pinterest, YouTube, and Twitter) can be a catalyst for learning, especially since they are a platform with which students are already familiar. Yu (Aimee) Zhang in ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning” garners students’ perceptions of a mobile platform, Tutors in Pockets, a mobile learning assistance program that presents students with over 200 economic concepts via tables, animated cartoon, formulas, and/or case studies. Using a mixedmethods and a cross-cultural analysis, the author highlights the importance of investigating students’ technological expectations and how teaching styles should respond to these expectations. This interplay has cross-cultural implications, as Zhang stresses. Fariha Hayat Salman and David Riley in ▶ Chap. 58, “Technology-Mediated Assessment in Crossover Learning Assessment Design (CLAD): A Case from Sustainable Engineering Design Education” present the use of interactive usability cycles as means to improve technology-medicated assessments. In doing so, the authors first explain the differences between formal and informal learning and how these concepts overlay explanatory and experimental learning. They then make the argument for the use of CLAD as a pedagogical solution that includes both formal/ explanatory and informal/experimental learning. A framework is presented that the authors hope will be used by both educational researchers and practitioners to bridge the two concepts.

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References Bano, M., D. Zowgi, M. Kearney, S. Schuck, and P. Aubusson. 2018. Mobile learning for science and mathematics school education: A systematic review of empirical evidence. Computers & Education 121: 30–58. Crompton, H., and D. Burke. 2018. The use of mobile learning in higher education: A systematic review. Computers & Education 123: 53–64. Crompton, H., D. Burke, and K.H. Gregory. 2017. The use of mobile learning in PK-12 education: A systematic review. Computers & Education 110: 51–63. Eliasson, J., T. Pargman, J. Nouri, D. Spikol, and R. Ramberg. 2011. Mobile devices as support rather than distraction for mobile learners: Evaluating guidelines for design. International Journal of Mobile and Blended Learning 3 (2): 1–15. JISC InfoNet. 2011. Mobile learning infoKit. Retrieved from: https://2020research.files.wordpress. com/2011/07/mobile-learning-infokit.pdf Levene, J., and H. Seabury. 2015. Evaluation of mobile learning: Current research and implications for instructional designers. TechTrends 59 (6): 46–52. Moore, R. 2018. Smartphones and laptops are the most accessible technological devices students have at home. Iowa City: ACT. https://www.act.org/content/dam/act/unsecured/documents/ R1680-tech-devices-at-home-2018-05.pdf. Moore, R., and D. Vitale. 2018. High school students’ access to and use of technology at home and in school. Iowa City: ACT. https://www.act.org/content/dam/act/unsecured/documents/R1692tech-device-access-2018-07.pdf. Moore, R., D. Vitale, and N. Stawinoga. 2018. The digital divide and educational equity: A look at students with very limited access to electronic devices at home. Iowa City: ACT. Motiwalla, L.F. 2007. Mobile learning: A framework and evaluation. Computers & Education 49: 581–596. Park, Y. 2011. A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types. International Review of Research in Open and Distance Learning 12 (2): 78–102. Pew Research Center. 2017. Mobile fact sheet. https://www.pewinternet.org/fact-sheet/mobile/ Purcell, K., Al. Heaps, J. Buchanan, and L. Friedrich. 2013. How teachers are using technology at home and in their classrooms. Washington, DC: Pew Research Center. http://www.pewinternet. org/2013/02/28/how-teachers-are-using-technology-at-home-and-in-their-classrooms/. Sharples, M. 2009. Methods for evaluating mobile learning. In Researching mobile learning: Frameworks, tools, and research designs, ed. G.N. Vavoula, N. Pachler, and A. KukulskaHulme, 17–39. Oxford: Peter Lang Publishing Group. Sharples, M., J. Taylor, and G. Vavoula. 2007. A theory of learning for the mobile age. In The sage handbook of eLearning research, ed. R. Andrews and C. Haythronthwaite, 221–247. London: Sage. Suarez, A., M. Spechter, F. Prinsen, M. Kalz, and S. Ternier. 2018. A review of the types of mobile activities in mobile inquiry – Based learning. Computers & Education 118: 38–55. Sung, Y., K. Chang, and T. Liu. 2016. The effects of integrating mobile devices with teaching and learning on students’ eLearning performance: A meta-analysis and research synthesis. Computers & Education 94: 252–275. Vavoula, G., and M. Sharples. 2009. Meeting the challenges in evaluating mobile learning: A 3-level evaluation framework. International Journal of Mobile and Blended Learning 1 (2): 1–22. Wang, Y.S., M.C. Wu, and H.Y. Wang. 2009. Investigating the determinates and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology 40 (1): 92–118. Wu, W., Y.J. Wu, C. Chen, H. Kao, C. Lin, and S. Huang. 2012. Review of trends from mobile learning studies: A meta-analysis. Computers & Education 59: 817–827.

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Yu (Aimee) Zhang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Literature and Empirical Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Qualitative and Quantitative Study on Tutors in Pockets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Qualitative Interview for Multimedia Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Survey for TIPs IOS Version . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Survey for TIPs 2 (IOS and Android Versions) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Objective Evaluation for TIPs 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Comparative Evaluation on Australian and Chinese Students . . . . . . . . . . . . . . . . . . . . . . . 4 Compare the Differences from Australia and China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conclusion and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile learning is believed to be the trend for future education. It provides realtime, rich content, interactive, teamwork, and work-integrated learning to learners anytime and anywhere (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). It makes flexible personal learning available to meet the needs for new generation of students and students with special needs (e.g., disabled students or gifted students). It also gives opportunities for effective educators and important teaching materials to reach thousands of learners all over the world. However, mobile learning has also been criticized because it lacks personal contact, body and facial languages, and the ability to control the quality of teaching. Many empirical studies have focused on the differences between online or mobile learning and traditional learning methods, focusing on what can be Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_16

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enhanced for new developed blended learning or mobile learning programs. One such program is Tutors in Pockets, a mobile learning assistance program aimed to assist in student learning for economic subjects (see ▶ Chap. 27, “Tutors in Pockets for Economics”). This study collected primary data from both Australia and China to identify the students’ attitude toward mobile learning, their patterns of use, and learning patterns on mobile devices. In addition, the user experience and expected benefits from Tutors in Pockets were investigated. The first section of this chapter introduces mobile learning and its characteristics. Previous empirical findings are summarized in the second section by comparing the advantages and disadvantages for mobile learning to traditional learning methods. The third section discusses the design of this study and the mobile program implemented in a basic macroeconomics course – Tutors in Pockets. The fourth section presents the sample collected from Australia and China and how the data were analyzed. The last section summarizes the study’s findings and provides suggestions for future mobile teaching and learning programs.

1

Introduction

Mobile teaching and learning (m-learning) is believed to be the future for modern education (Alhassan 2016; Evans 2008; Mishra 2013; Hennig 2016; Metzgar 2017) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). It engages students in their subjects, assists the learning process, enhances personal learning, and increases discussion and performances (Mishra 2013; Bredl and Bösche 2013; Butoi et al. 2013; Evans 2008; Yousafzai et al. 2016). Some researchers have also found it helps people become lifelong learners (Liaw et al. 2010; Sharples 2000; Demouy et al. 2015; Mishra 2013) and benefits students with special needs (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”), such as disabled students (Cumming et al. 2013; Fernández-López et al. 2013; Metzgar 2017). Some authors, however, argue the negative influences brought by mobile devices, such as lose focus and addiction to mobile games instead of learning (Bredl and Bösche 2013; Alhassan 2016). To assist students’ learning process, a mobile app (application) “Tutors in Pockets” was designed and developed for economic subjects for IOS and Android devices (Zhang 2012b) (see also ▶ Chap. 27, “Tutors in Pockets for Economics”). It was introduced to undergraduate and postgraduate students and teachers in economics subjects from 2011 to 2013 at the University of Wollongong. Both qualitative interviews and quantitative online survey were conducted in Australia. The results showed that mobile learning had a positive influence on student’s learning process and performance. The mobile application was free for all students in Google Play (for Android devices) and UOW App list (for IOS devices) from 2011 to 2017. Universities and students also vary by country (Liu and Zhang 2015; Grimm et al. 2016) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning” and

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▶ 33, “Mobile Education via Social Media: Case Study on WeChat”). To understand the differences on mobile learning in different countries, another survey was conducted in three different universities in China in 2013. The results showed students from different countries and cultural backgrounds have very different expectations on mobile educational applications and different learning styles on mobile devices. Cross-country and cross-cultural educational mobile application designers should take into account these differences to reach their students and to benefit a larger audience.

2

Literature and Empirical Studies

The skills, knowledge, and expectations of students today are different from those of students 10 years ago (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning” and ▶ 50, “Cross-Country University Collaboration Barriers and Solutions”). Oblinger and Oblinger (2005) found millennials (students that were born after 1983) are very different from previous generations. They are multi-task learner. They prefer multimedia courseware than text. They prefer interactive and network in learning. They have shorter attention spans and poorer text literacy. They usually lack reflection skills and are unable to identify quality sources (Rennie and Morrison 2012; Vogel et al. 2009). Educators from preschool, school, and university are now at a crossroads on how to teach the students who were born with the devices and technology available to them. Most educators agreed that previous teaching methods need to change to suit a new situation so they can help new students in the learning process. The changes are needed, but how? Can mobile technology be part of the solution? Mobile technology has been introduced in education for several decades. As many other learning methods, mobile learning has its own advantages and disadvantages (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Mobile learning or distance learning was introduced to high education from the very traditional mobile devices with only black and white screens in the 1970s. But it grew very fast creating the new generation of mobile devices with high-speed data transferring capabilities and multimedia-supported functions provided by device providers, telecommunication operators, service providers, and content providers in the mobile telecommunication industry (Zhang 2012a) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Mobile learning is also adopted by educators in universities, schools, and educational associations. Many leading designers and educators adopted mobile learning or blend learning in their subjects in different disciplines (Bredl and Bösche 2013; Cumming et al. 2013; FernándezLópez et al. 2013). Multimedia, social media, new technologies, and new devices were adopted and developed too (Holotescu and Grosseck 2011; Yuh-Shyan et al. 2004; Wang and Zhang 2015; Alkhezzi and Al-Dousari 2016; Zidoun et al. 2016) (see also ▶ Chap. 33, “Mobile Education via Social Media: Case Study on WeChat”). Thousands of students have benefited from these projects with research showing positive influences on teaching and learning.

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Mobile learning has shown to correct misconceptions; increase learning efficiency; increase understanding (on complex concepts); facilitate learning from anywhere, anytime; increase communication between students with their peers and students with teachers; help students with special needs; engage students in their studies; enhance their final performance; help students understand the tasks in real world; enhance teamwork skills; and benefit students’ lifelong learning (Akamca et al. 2009; Evans 2008; Fernández-López et al. 2013; Oblinger and Oblinger 2005; Slavin 1980; Sung and Hwang 2013) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). There are many positive influences reported from empirical learning projects that are linked with multimedia learning and learning with social media (Collins et al. 2006; Kennedy et al. 2013; Vogel et al. 2009; Zhang 2012b; Alkhezzi and Al-Dousari 2016; Zidoun et al. 2016; Sun and Looi 2017). With new technologies and devices introduced into mobile learning, it is expected to bring more advantages to the students and learners (see ▶ Chaps. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning” and ▶ 79, “VR and AR for Future Education”). Although mobile learning had many advantages to educators and students compared to traditional learning methods, it is still limited by some technical and ethic barriers (Zhang 2012a; Alhassan 2016; ITU 2016). Current technologies still cannot fulfill a real “anytime” and “anywhere” learning due to the quality of signal connection, software and hardware barriers, wireless security issues, and high costs of wireless connections (Alhassan 2016; ITU 2016). The national security issues, political considerations, and monopoly power in telecommunication industries also influenced the adoption of mobile learning anywhere and anytime (Zhang 2012a). In addition, the high costs on smartphones and wireless data transfer are barriers for mobile learning. Some empirical studies also found that not all the students have smartphones or prefer mobile learning method (Peter and Gina 2008; McCombs 2010a; O’Day 2010; ITU 2016). There were concerns of a young child’s eye health with too many screens. Online learning and mobile learning are also criticized for its lack of facial and body languages and eye contacts during the teaching process as well as reducing the time for real face-to-face social communications (Qiu and McDougall 2013; Rennie and Morrison 2012). Mobile learning, as most of the other learning methods, does not satisfy the needs of everyone due to their current limitations and because of individual preferences. Given these barriers to technology, some educators have blended the two methods to capitalize on the benefits of both. This includes integrating mobile technology and social media into lesson plans (Casey 2013; Britt 2013; Heatley and Lattimer 2013; Jenkins and Dillon 2013; Powers et al. 2012; Wallace 2014; Tyree 2013). With new technologies and advanced devices developed, most of the technical issues for mobile learning today are expected to be solved in the future. However, there will continue to be cultural, language, and political barriers for international education (see ▶ Chap. 50, “Cross-Country University Collaboration Barriers and Solutions”). For example, social media differ across countries because of language, cultural, and political differences (Zhang 2012a), which create challenges for curriculum developers. To study these potential differences, this study collected data from Australia

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and China and compared their adoption of mobile learning and attitudes toward technology to the learning behaviors from these two countries. To bring the technology into one of the most traditional disciplines – economics, a mobile application was designed and developed for both IOS and Android versions. The mobile application, Tutors in Pockets, was introduced to 1st year and 3rd year undergraduate economics students and postgraduate students in the University of Wollongong from 2012 (the IOS version) to 2013 (the IOS and Android version). This project was expected to help students understand basic economic concepts, engage students in their economic studies, correct misconceptions, and improve subject performance at the University of Wollongong. The project was also greatly supported by a development team that consisted professionals both internal and external to the university, including experts in ad business. Each version was introduced to students for one session, and the evaluation was then released and collected through online surveys and face-to-face interviews at the end of the session. Both qualitative and quantitative studies were conducted to evaluate the result of this project to give a combined objective and subjective results on the TIPs evaluation. The project is also introduced to Chinese students to study the different learning attitudes and behaviors in China. The results showed interesting deviation from both student groups on their learning behaviors, study times, attitudes, and expectations on mobile learning. The results are expected to shed a light on future mobile learning system design and development. To study the different views on mobile learning from different countries, another survey was also conducted in three different universities in China. The compared results are given in the following sections.

3

Qualitative and Quantitative Study on Tutors in Pockets

3.1

Qualitative Interview for Multimedia Teaching

TIPs is designed to help reduce the learning barriers and enhance learning experience via multimedia teaching materials and mobile technology. Multimedia teaching materials with real case studies were developed first for 200 economic basic concepts. These materials are reviewed by students and staffs (lectures and tutors) from economic and other disciplines through face-to-face interviews. Table 1 below shows the interview results from this study.

3.2

Survey for TIPs IOS Version

TIPs (IOS version) was revised and released to all students in June 2012. To reduce the access barriers and collect quantitative survey from students, a QR code was adopted in this project. Students could easily scan this code from their IOS mobile devices (iPhone or iPad) and download TIPs from the UOW server automatically if

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Table 1 Interview results on multimedia teaching materials Interviewee RA student (undergraduate)

No. of students 1

International students (undergraduate) International students (postgraduate) Economic teachers and tutors

4

Teachers from other faculties

2

Total interviews

Feedback (examples) As a RA student, I strongly believe that these cartoons would help, as I learn more from visual examples than reading big words that mean nothing to me These cartoons are clear and easy to understand

6

It engaged students in class discussion

4

It is really good, and I would like to adopt some of them in my lectures I am sure it will touch a nerve with student’s lives I think it is good for engaging students It may be used in different subjects and may solve the performance problems of international students It is very impressive I wish I have the ability to develop such cartoons 10 examples of student responses

17

Suggestions The disability people should be part of the labor force

Add a link to RBA website for inflation cartoon would be helpful

2 suggestions

Source: Zhang (2012b)

they did not want to input the download link into the web browser of their mobile device. The first version (IOS version) was designed for online functionality only. A student could view all the text contents in the application. However, figures or animated materials required access to a mobile network connection to download. A total of 80 animated cartoons or figures were developed for 200 economic conceptions in the first version. Students could learn from the lists or search concepts in the application. Some concepts included tables, animated cartoons, formulas, and/or case studies. In addition, some animated cartoons included links to outside authorities (e.g., Reserve Bank of Australia or Australian statistics websites). The update function was also available for any new content added to the knowledge database. Students were encouraged to connect to a Wi-Fi connection when updating due to the high costs of 3G/4G mobile data transferring (Zhang 2012a). TIPs was introduced to the 1st year undergraduate, 3rd year undergraduate, and postgraduate economics subjects in 2012. More than 500 students got access to the application. However, not all students had IOS mobile devices (which was a requirement for the first TIPs version). The adoption rate was also limited by

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students’ personal preferences, class attendance, information sharing between students, and technology issues during download and first access. Figure 1 shows the first poster designed for TIPs IOS version release and collection of the quantitative survey from students (by QR code). The poster was introduced in class and also posted in campus to facilitate students’ access and feedback. This is greatly supported by ITS (Information and Technology Service) from the University of Wollongong (UOW). They have implemented an apps site for all the UOW teaching and learning apps, with TIPs on the list. The server space provided by ITS also helped on TIPs download and access. However, as the first version is required to be used as internal app, they are not allowed to be downloaded

TUTORS IN POCKETS (TIPs) For Economics

Study anywhere anytime!

Get It Now For Free! http://www.uow.edu.au/~dfs/tips/

Study is easy and fun!

Scan to feedback or email to [email protected] Fig. 1 TIPs poster for IOS devices in 2012. (Source: Developed by the author for TIPs)

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by public audience. Students or staffs from UOW must login with their university account to download this application to their mobile devices. A quantitative survey was conducted in August 2012 to collect the feedback from students. As a result, a total of 56 students completed the study online, including 22 male students and 25 female students. All of the surveyed students had mobile devices and 64% used an iPhone. A total of 79% of students who participated in the survey had difficulties in understanding some economic concepts before participating in the project. The majority of students indicated (strongly agreed or agreed) that TIPs had a positive influence on their learning efficiency (82%), increased their interest in economics (73%), assisted lectures and tutorials (64%), helped study anytime and anywhere (64%), engaged discussion with peers and teachers (55%), and enhanced subject performance (45%). In addition, most students (82%) like to study in their small time slots. Students also indicated on the survey that they would prefer the app be compatible with Android. Therefore, the second stage of the project, developed in 2013, integrated this into the design.

3.3

Survey for TIPs 2 (IOS and Android Versions)

The Android version of TIPs was developed and introduced into the economics classes in 2013. The IOS version of TIPs was also revised with some functions improved which included an adoption of an online-offline feature (to achieve a real anytime and anywhere study). More multimedia teaching materials were developed for TIPs 2 as well. Some suggestions from students and staffs were taken into account in the revision of TIPs IOS version and in the development of the Android version. Both online and offline functions were designed and developed in the second version to improve the learning anytime and anywhere experience. Students no longer needed access to a mobile signal connection to learn from their mobile devices. All text, figures, and animations were installed into the students’ mobile phone on the first download. The connection with the server via mobile Wi-Fi or cellular signal was only required when new content was added. The second version on Google Play is also accessible by all public audience for free. Figure 2 shows the poster for TIPs 2. To reduce the access barriers, two QR codes were adopted. Students could easily scan the codes from their mobile devices and download TIPs from the UOW server and from Google Play automatically. It was introduced in three tutorials in a 1st year undergraduate class to compare the differences of adopted and non-adopted groups. To make it available to more students (with other mobile devices or no mobile devices), the teaching materials were also adopted in class for these groups. Animations and figures were included in lecture slides. The evaluations of the use of animations were summarized in the following section. A survey was conducted to collect the students’ feedback for TIPs 2 in September 2013. A total of 54 students attended the study online, including 31 male students

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TUTORS IN POCKETS (TIPs) For Economics

Study anywhere anytime!

Get It Now For Free! For iOS http://www.uow.edu.au/~dfs/tips/

For Anroid https://play.google.com/store/ap ps/details?id=com.wemosoft.tips

Study is easy and fun!

Please email feedback to [email protected] Fig. 2 TIPs 2 poster for IOS and Android devices in 2013. (Source: Developed by the author for TIPs 2)

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and 23 female students. Most sample students have one or two smartphones, and only two students indicated that they have no smartphone. There were 74% students with IOS devices, followed by android devices (24%) and others (7% in total for Nokia, WinPhone, and Blackberry). As a result, students either agreed or strongly agreed that TIPs had a positive influence on their learning efficiency (38%), utilized small time slots (32%), increased their interest in economics (26%), assisted their understanding of material in lectures and tutorials (38%), helped them study anytime and anywhere (56%), assisted in their discussion with peers and teachers (9%), and enhanced their subject performance (26%). The results are different from the 1st year’s results, with the 1st year’s results being more positive. This might be because the 2nd year’s survey responders were 1st year undergraduate students only, whereas the 1st year survey responders included 1st year and 3rd year undergraduates as well as graduate students. These differences in survey responders might have been a contributing factor to their attitudes toward mobile learning.

3.4

Objective Evaluation for TIPs 2

To evaluate the objective results of adopted and non-adopted groups, the tutorial tests, essay assessment, and final exam results of each group (groups with TIPs and without TIPs) were also compared. The results are presented in Table 2. These results are from the 1st year macroeconomic students in the spring session, 2013. There were 446 students with all grades in 24 tutorials. The performances were evaluated in their average scores for tutorial preparation, in-class quiz, essay assessment, final exam, and overall marks for all the previous assessments. The higher the score, the better the student did on that assessment. Groups with TIPs being introduced were taught by the author, and groups without TIPs were taught by other tutors with traditional teaching methods. The results indicated that groups with TIPs adopted in class have higher performance in each of the individual assessments and overall marks. The average overall marks for groups with TIPs adopted were higher than those without TIPs adopted (taken from all students attending the same lectures). One of the students also indicated to another economic teacher “I had no idea what economics is but now I am interested in economics (after attending the tutorials with TIPs).” Students from the “TIPs” groups were engaged in more group discussions and provided more Table 2 Compare the average groups’ performance with and without TIPs Groups with TIPs adopted Groups without TIPs All groups Source: Author

Tutorial 13.96 13.36 13.41

Quiz 3.79 3.22 3.30

Essay 16.82 13.82 14.19

Final 46.02 45.60 45.57

Overall 63.72 59.48 59.93

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suggestions. They focus longer than the other groups. Some of them gave feedback during class and in the next class. Two students found small typographical errors in the mobile application. Their names were updated in the contributors’ list in the settings page of the application. It shows that TIPs has a very positive influence by improving students’ performances, increasing their understanding of key concepts, and developing an interest in the teaching material. There were also positive results from the tutorial class with animated lecture slides using the TIPs materials. Students were more engaged and indicated that the materials were very helpful to their studies. Although most materials are basic conceptions and case study on threshold concepts instead of solving difficult questions or practice questions for exams, students were very active in discussion. As in Table 2, the objective performance from tutorial marks, essay marks, and final marks is much higher than the groups that did not adopt these teaching materials, which shows the multimedia materials are not only useful on mobile devices but also helpful in normal class. Multimedia materials are one of the top figures in Tutors in Pockets, which play an important role in increasing learning efficiency and understanding (Zhang 2012b). During the interviews with individual students and staffs in 2012, some international students and staffs indicated that multimedia teaching materials and mobile learning methods can benefit international students and assist their learning with a non-native language. Figure 3 shows some multimedia cartoons adopted in the lecture slides and TIPs mobile application, which illustrate basic economic conceptions like inflation, demand curve, and monetary policies. Some misconception problems are also indicated in these figures. A picture is worth a thousand words (Larive 2008). One cartoon can present the basic conception, hypothesis of the situation, cases to help understanding, and formula for calculation in some cases. Other animated cases can be found in Tutors in Pockets application from Google Play.

3.5

Comparative Evaluation on Australian and Chinese Students

To understand better the different learning behaviors of Australian students and international students, another study was conducted in June to July 2013 in China to compare the Australian survey results. As the number of Chinese students in Australia increased dramatically in recent years, the survey was conducted in three different universities in China. They are East China Jiaotong University (in Jiangxi province, China), Beijing Information Science and Technology University (in Beijing, China), and University of Science and Technology of China (in Anhui province, China). Both undergraduate and postgraduate students are invited to attend this study. The result of this survey is compared with the Australian survey result collected for TIPs 2 to identify the different using patterns of mobile devices, mobile learning, and expectation of mobile learning applications from Australian and Chinese students. They are introduced in the next section.

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Fig. 3 Some animated cartoons and figures in Tutors in Pockets. (Source: From Tutors in Pockets developed by the author)

4

Compare the Differences from Australia and China

To study the influence of cultural differences on mobile learning, two surveys were conducted separately in China and Australia. China has a very different educational system compared with most of the developed countries (OECD 2016). The huge population base and high quality of students make it the most popular international students’ source for many foreign universities now. To study the differences from Chinese students and Australian students, a Chinese survey was collected from 183 postgraduate and undergraduate students from East China Jiaotong University, Beijing Information Science and Technology University, and University of Science and Technology of China in June and July 2013. The surveyed universities are located in Beijing, Anhui, and Jiangxi provinces, which are far from north to south of China. The results are believed to represent the most general university students’ groups in the Chinese universities. The Australian survey was collected from 54 1st year undergraduate economic students (majority of the students are local students) in the University of Wollongong in September 2013. Instead of evaluating TIPs only, this study focuses on the different views of students on mobile devices usage, how they learn on mobile, and what are their expectations on mobile educational applications. The last part of the questionnaire was designed to evaluate the results of TIPs. But some of the surveyed students did not have access to TIPs or were not using TIPs in their studies. The results show many differences from Australian and Chinese students, which also shed a light on future design and development of cross-country mobile teaching and learning systems and applications.

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Mobile devices in Australia

Mobile devices in China 40% 35% 30% 25% 20% 15% 10% 5% 0%

Android, Nokia 34% mobile devices, IOS, 24% 19%

Others, 18% Motorola , 5%

80%

IOS, 74%

70% 60% 50% 40%

Android, 24%

30% 20% 10%

Others, 2%

0% IOS

Android

Others

Fig. 4 Mobile devices used by learners in China and Australia. (Source: Author)

First, the market share of mobile devices in China is different from those in Australia due to the different choices of mobile devices available in the market, preferences from different cultural backgrounds, and different prices of mobile devices in different markets. Figure 4 shows the differences. The majority of Australian students (74%) were using Apple (IOS) mobile devices (iPhone or iPad). The Android mobile device (24%) and Apple mobile devices were used by 98% of the Australian students. In China, Android mobile devices had the biggest market share, which was 34%. A fewer percentage of students used Apple mobile devices (24%), Nokia mobile devices (19%), Motorola mobile devices (5%), and other devices (18%). Nearly half of the mobile devices in the Chinese market are not IOS or Android mobile devices, which should be taken into account when designing a mobile educational application for the global market. One possible reason for this is the price difference for iPhone and other mobile devices in the Chinese market. The variety of mobile devices that support Android system and the free mobile applications for Android devices are also factors that have improved their market share in China. Second, the usages of mobile phone in different location and scenarios are different in Australia and China. The different preferences, cultural backgrounds, and policies and rules in different countries are the major factors that influenced the usage. Figure 5 shows the differences. As shown in Fig. 5, the frequency of using mobile devices by Australian students was much higher than those of their Chinese peers. One possible reason is the strict restriction of mobile phone usage in classroom in China. Most Chinese students are not supposed to use their mobile phone either for play or search information in class. The use of mobile devices in class is regarded as disrespectful to the teacher or lecturer in China. Due to the cultural difference in universities and at home in different countries, the uses of mobile devices in class (restricted in most universities and schools in China) and during part-time jobs (Chinese students are not suggested

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The mobile phone usages in China and Australia 100% 80% 60% 40% 20% 0%

Chinese Australian At home or On the way In class library or waiting for bus

After class Doing part- Having Other time or having time job party with food my friends

Fig. 5 Mobile device usages by learners in China and Australia. (Source: Author)

Learning sources for Australian students Others

5%

Tutors in Pockets

27%

On-line news App stores

23% 16%

E-learning site

57%

Youtube Wikipedia

55% 34%

Google

91%

Fig. 6 Sources of mobile learning from Australian students. (Source: Author)

to do part-time jobs during study years) in China were very rare. Chinese students usually use their mobile devices in their spare time after class. As Chinese students usually live with their parents until they finished university studies, the use of mobile devices at home are also less than those of Australian students (due to the preference of the Chinese parents on mobile phone). Third, due to the cultural differences as discussed above, mobile learning was not adopted by majority of students in China. Only 9% of the surveyed Chinese students adopted mobile learning, and 61% of students adopted online learning (some are required by schools). Students still prefer traditional teaching methods or online learning methods. However, in Australia, students learned from variety of mobile and online sources. They are more active in searching information, downloading learning materials, and doing assessments on mobile devices compared to their Chinese peers. They also adopted different social media and platforms in their study. Figure 6 shows the percentage of students using different sources of online and mobile learning.

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Google is the first choice by 91% Australian students. e-Learning site by universities (57%, required by some universities or subjects), YouTube (55%), and Wikipedia (34%) are also popular for Australian students. However, YouTube, Facebook, Wikipedia, and Google are all blocked in mainland China. Instead, Chinese students usually use local social media platforms to communicate with friends and get information, such as Weibo, WeChat (Weixin), or Renren. The most popular video website in China is YouKu Tudou. There are also many different social media and video sites for different groups. For example, the 56.com video website is more popular in Chinese universities as it targets the young audience in China. Some of the on-site events, like the university filmmaking competition and mobile sharing rewards also increased their subscriber numbers from university students. The popular social media is expected to be different in different countries or even different regions. New replacement effect due to the development of new technology, new devices, and policies also influenced the penetration rate of mobile learning adoption in different countries. To suit the fast-changing rules and technologies, educational application designer for international market should also take these differences into account. Last but not least, the expectation of mobile learning is different in Australia and China. It could be different in other countries too. Figure 7 shows the differences in detail. Australian students appreciated more convenient functions that assist study anytime and anywhere, learning in class, and learning performances. Chinese students, on the other hand, preferred educational applications that assist learning in smaller time slots and increase learning efficiency. One possible reason for these differences is the usages in different scenarios in China and cultural preferences in the Chinese culture. Australian students focus more on efficiency and study in small time slots. Chinese students focus more on performance of the subject and learning

Expectations for mobile learning Others No difference to me Increase my performance Engage me in discussion with students… Chinese

Increase my interests in learning

Australian

Increase my searching and learning in class Utilise smaller time slots to study Study anywhere and anytime Increase learning efficiency 0%

20%

40%

60%

80%

100%

Fig. 7 Different expectations for mobile learning in Australia and China. (Source: Author)

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in class. Students in China have higher price elasticity to mobile applications and devices. In other words, when the price increased a small amount, more students will leave the customer group from using the mobile device or mobile applications compared to Australian students. Therefore, the designers and developers should also take into account these cultural differences in their cross-country educational system design. The results also shed a light on other commercial mobile application designs across countries. Although the major results are very different in Australia and China, there are some similar responses from Australian and Chinese respondents. The average learning time lengths per day on mobile devices were similar in Australia (40 min) and China (30 min), which were only 1/8 or 1/9 of the lengths of mobile usages per day in both countries. People usually get tired after focusing on a small mobile screen or holding a mobile device for half an hour. Mobile devices are not considered as a major source for study in current stage due to the technology, ethics, and high costs of mobile learning. But the situations are expected to change with more advanced mobile devices invented (like wearable mobile devices, new screen technology, or 3D technologies), more mobile educational application developed, and more university adopting mobile learning strategies. Mobile learning is regarded as a complimentary learning method to face-to-face learning than supplementary method in current stage. There are still technology, ethics, policy limits, and barriers for the adoption of pure mobile education in universities or schools. A blended learning method is still preferred by both educators and learners in current stage.

5

Conclusion and Future Directions

Mobile teaching and learning has been the trend for modern education (Alhassan 2016; Fraga 2012; Evans 2008; Hennig 2016) (see also ▶ Chap. 79, “VR and AR for Future Education”). Although it brings many benefits to students and educators, they are still limited by current technology and ethics issues to achieve a real “anytime” and “anywhere” (ITU 2016; Yousafzai et al. 2016). With the development of mobile technologies and globalization, these barriers will be diminishing in the near future. The qualitative and quantitative studies on mobile educational application for economics – Tutors in Pockets (TIPs) – showed very positive results for student’s learning process and performance. It corrected misconception problems, increased learning efficiency, increased understanding, increased in-class discussion and reflection, helped students with special needs, engaged students in economics, and enhanced students’ individual and final performances in the subject they studied. Staffs from economic school and other disciplines also gave high evaluations on TIPs. The positive results are also supported by many other mobile learning empirical studies (Evans 2008; Martin and Ertzberger 2013; Sun et al. 2016; Zidoun et al. 2016). There are some challenges facing mobile learning, such as the cost of telecommunication services and devices (McCombs 2010a; Mishra 2013; Oblinger and Oblinger 2005), computing

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capability and screen size for mobile devices (Alkhezzi and Al-Dousari 2016; Mishra 2013; Hennig 2016), broadband and stability of networks (ITU 2016; Park 2013), curriculum transfer and structure design (McCombs 2010b; Metzgar 2017; Prensky 2001), teachers’ training and adoption of technology in classroom (Powers et al. 2012; Johnson et al. 1998; Grimm et al. 2016), and safety and other issues (Peng et al. 2009; Yousafzai et al. 2016; Kemp 2013). Hopefully, most of these problems will be solved with the fast development of technologies and new policies. The developed multimedia materials can not only be adopted in mobile application but also tutorial discussion, lecture slides, and exam questions to help understanding, engage in-class discussion, and enhance students’ subject performances. Students also indicated that they were interested in the subject with all these materials adopted in class. The results from Australia and China studies showed that learners are different in terms of mobile device adoption, usage, pattern of mobile learning, and expectations for mobile educational applications in different countries. An international mobile educational application designer should take into account the cultural differences and political barriers to reach the global market and make a real international program (OECD 2016). The results from this study combined both qualitative and quantitative results to give a more reliable evaluation on mobile teaching and learning. It also studied the influence of cultural differences on mobile teaching and learning, which shed a light on cross-country mobile educational system design and development in the future. Students are different today with more technologies and ability to adopt mobile or online learning (Grimm et al. 2016). They are more creative, multi-task focusing, cross-cultural, global focused, and confident with technologies. With more and more international students traveling from one nation to another, the teaching system that focuses on providing human resources for local job market can hardly satisfy the potential employers and students. Universities and schools should also make the changes to meet the new requirements from students. Mobile learning could not be sustainable without digital curriculum system, proper structure design, positive policy support, and good technical training and support for teachers.

6

Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Characteristics of Mobile Teaching and Learning ▶ Cross-Country University Collaboration Barriers and Solutions ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Tutors in Pockets for Economics ▶ VR and AR for Future Education

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Moving Towards the Effective Evaluation of Mobile Learning Initiatives in Higher Education Institutions

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Helen Farley, Angela Murphy, Nicole Ann Todd, Michael Lane, Abdul Hafeez-Baig, Warren Midgley, and Chris Johnson

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 940 2 Influence of Mobile Learning Initiatives on Teaching and Learning Within Higher Education: Review of Current Use and Pedagogical Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 942 2.1 Altered Delivery of Content and Knowledge Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 943 H. Farley (*) Digital Life Lab, University of Southern Queensland, Toowoomba, QLD, Australia e-mail: [email protected] A. Murphy Australian Digital Futures Institute, University of Southern Queensland, Toowoomba, QLD, Australia e-mail: [email protected] N. A. Todd School of Linguistics, Adult and Specialist Education, University of Southern Queensland, Springfield Central, QLD, Australia e-mail: [email protected] M. Lane School of Management and Enterprise, University of Southern Queensland, Toowoomba, QLD, Australia e-mail: [email protected] A. Hafeez-Baig School of Management and Enterprise, University of Southern Queensland, Toowoomba, QLD, Australia e-mail: [email protected] W. Midgley School of Linguistics, Adult and Specialist Education, University of Southern Queensland, Toowoomba, QLD, Australia e-mail: [email protected] C. Johnson Research School of Computer Science, Australian National University, Canberra, ACT, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_17

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2.2 Portability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Creativity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Bridging the Knowledge and Application Gap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Interactivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Challenges in Evaluating Mobile Learning Initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Development of Frameworks for Evaluating Mobile Learning in Higher Education . . . . . 4.1 The Evaluation of Technologies Framework: Ng and Nicholas (2013) . . . . . . . . . . . . . 4.2 A Critical Analysis: Frohberg, Göth, and Schwabe (2009) . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 A Framework for Analyzing Mobile Learning: Sharples, Taylor, and Vavoula (2007) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Pedagogical Forms for Mobile Learning: Laurillard 2007 (Based on Work in 2002) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Developing a Mobile Learning Evaluation Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Stage 1: Development of the Mobile Learning Evaluation Criteria . . . . . . . . . . . . . . . . . 5.2 Stage 2: Validation of Evaluation Criteria and Development of Models and Frameworks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Stage 3: Finalization of the Mobile Learning Evaluation Framework . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Mobile learning is viewed by many institutional leaders as the solution for a student cohort that is demanding an increasing flexibility in study options. These students are fitting study around other aspects of their lives including work and caring responsibilities, or they are studying at a geographical location far removed from the university campus. With ubiquitous connectivity available in many parts of the world and with the incremental improvements in design and affordability of mobile devices, many students are using mobile technologies to access course materials and activities. Even so, there are relatively few formal mobile learning initiatives underway and even fewer evaluations of those initiatives. This is significant because without a rigorous evaluation of mobile learning, it is impossible to determine whether it provides a viable and cost-effective way of accessing courses for both the student and the institution. This chapter examines the broad groupings of uses for mobile devices for learning, before considering the evaluation frameworks that are currently in use. The characteristics, affordances, and issues of these frameworks are briefly discussed. A project to develop a Mobile Learning Evaluation Framework is introduced, which will consider evaluation from four aspects: (1) pedagogical learning, (2) pedagogical teaching, (3) technical, and (4) organizational.

1

Introduction

Mobile learning is an emerging area of interest for higher education institutions, but both the theoretical foundations and practical implications of mobile learning for those institutions are still being explored (Kearney et al. 2012). Until fairly recently, research into the impact of mobile learning initiatives on teaching and learning was

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still being undertaken on a fairly ad hoc basis within Australian universities. Mobile learning initiatives are frequently championed by individual practitioners with little buy-in from their institutions (Carter and Salyers 2013). Mobile learning is, however, being increasingly seen as a new and compelling way to engage students. Consequently, a number of higher education institutions in Australia have embraced the potential affordances of mobile technologies and implemented mobile learning initiatives of varying sizes. The University of Adelaide was one of the first Australian universities to provide mobile devices to students on a large scale. The university handed out free iPads to all students enrolling in a science degree in 2011, with the aim of providing students with flexible learning opportunities and teaching materials that were more accessible, more relevant, and more frequently updated (Murphy 2011). The University of Western Sydney (UWS) has more recently provided 11,000 iPads to all first year students and staff in 2013 to support learning and teaching innovation (Griffith 2012a). These programs have attracted extensive attention both within the mainstream media and in academic circles in relation to the potential pedagogical value of these initiatives. The National Tertiary Education Union has been highly critical of the UWS program, citing that the initiative arose at the expense of some language study courses which were abandoned. The university was also criticized for using expensive iPad technologies, rather than cheaper notebooks using Android systems, which would potentially be more useful for document processing and assignments (Griffith 2012b). These criticisms highlight the types of concerns that may discourage institutional leaders from considering the wide-scale implementation of mobile learning projects. These concerns indicate that the readiness of students, educators, and institutional leaders to effectively embrace the potential of mobile learning has yet to be fully be explored in Australian higher education institutions. There is also significant variation in the literature regarding the mobile technologies being used, the educational settings under investigation, and theoretical frameworks to support the sustainability of mobile learning initiatives (Ng and Nicholas 2013). Readiness is related to the concept of adoption phenomena. Readiness can be viewed as “behavioral readiness,” “perceived readiness,” “organizational readiness,” technical readiness,” and “environmental readiness.” For example, behavioral aspects can be directly borrowed from the previous adoption models of Fishbein and Ajzen’s Theory of Reasoned Action (TRA) (Fishbein and Ajzen 2010) in the context of intrinsic motivation (Davis et al. 1992) and affect toward use (Thompson et al. 1991; Venkatesh et al. 2003). Similarly, the concept of perceived readiness can be borrowed from a number of adoption, innovation, and diffusion theories (e.g., see Fishbein and Ajzen 1975; Davis et al. 1989; Rogers 2000). The greater use of mobile technologies for learning and teaching has a number of significant implications for higher education institutions at a pedagogical, infrastructural, and policy level (Dahlstrom 2012; see ▶ Chap. 15, “Framework for Design of Mobile Learning Strategies” by Boude Figueredo and Villamizar in this handbook). For example, prior to considering implementing these types of initiatives,

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universities need to consider whether they are ready, i.e., whether current wireless internet infrastructure should be upgraded or whether the format of current course materials is suitable for display on mobile devices. The implications of providing students with mobile technologies as opposed to encouraging students to bring their own device (BYOD) policies also require careful consideration. This chapter provides an overview of the potential practical and theoretical implications of implementing mobile learning initiatives at an institution-wide level. The chapter also presents an overview of current models used to assist higher education institutions in evaluating the potential impact and benefit of mobile learning initiatives.

2

Influence of Mobile Learning Initiatives on Teaching and Learning Within Higher Education: Review of Current Use and Pedagogical Goals

When considering whether or not to implement mobile learning initiatives in higher education institutions, it is easy for leaders and administrators to become fixated on the financial, logistical, or technological challenges or benefits. Cost, adaptability, and scalability are most frequently cited as the drivers encouraging the adoption of mobile technologies in specific learning environments (Patten et al. 2006), and frequently the potential pedagogical affordances of these devices are given less consideration. Educators and curriculum designers are faced with the challenge of identifying ways to use mobile technologies for more than simply practical purposes and need to do more than simply alter the presentation style of a traditional lecture or alter the physical locale of teaching and learning. Pedagogical change must accompany the adoption of mobile devices (Jeng et al. 2010), and educators are faced with the challenge of leveraging mobile devices in ways that are educationally appropriate rather than technologically complex (Roschelle 2003). Research also needs to move on from the usability and features of mobile devices to incorporate a broader pedagogical framework (Kissinger 2013). Five aspects of the use of mobile learning have emerged from the literature: (1) altered delivery of content and knowledge storage, (2) portability, (3) creativity, (4) bridging the knowledge and application gap, and (5) interactivity. Mobile learning allows for an alternate delivery of content and knowledge to the traditional lecture format with students sitting within a classroom passively listening to a knowledgeable person at the front of the room. This is related to the issue of portability of devices students use for learning. Portability also frees students from the traditional lecture situation and allows them to learn at a location remote from the campus. Mobile devices also allow for greater opportunities for developing creativity in students. Another positive aspect of mobile learning is the development of the link between the interests and experiences of students with higher education – bridging the knowledge and application gap. Finally, the aspect of interactivity also broadens the learning experiences of higher education students beyond the traditional passive learning situation. These five aspects will be explored in more detail below.

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Altered Delivery of Content and Knowledge Storage

In studies of iPads, particularly in higher education, these devices were found to be mainly used as repositories of content and portals to delivery mechanisms such as iTunes U for course materials (Cooper 2012; Murphy 2011). Further, students preferred the use of the iPad when the material was integrated with the curriculum (Manuguerra and Petocz 2011). Kissinger (2013) explored the learning experiences of students using eBooks in higher education as a replacement to traditional textbooks and other reference material and found students expressed feelings of competence and valued using the eBooks for their learning. Students appreciated the portability of eBooks. Though recently, doubt has been cast on whether students learn as effectively from eBooks as from printed materials (Flood 2014). Much work remains to be done in this space. In order to accommodate learning across a range of devices in a variety of contexts, course materials should be provided in a number of common file formats. Students typically use a variety of mobile devices using a range of operating systems (iOS, Android, Windows, Blackberry). For those students using laptop computers, materials should be provided as PDFs, or in the .doc, .xls, or .ppt formats (Murphy et al. 2014). To enable students to be able to annotate lecture slides (for face-to-face students) or to access notes when on the go or when grabbing portions of time opportunistically (face-to-face and distance students), notes should be provided in various formats that match the students’ study practices: not just in HTML, .doc, and .ppt but also PDFs which can be annotated with many apps and can be used across various platforms and with various applications (Murphy et al. 2014). Portability of information formats to different brands of device, and the creative tools currently available on them, is a major concern.

2.2

Portability

Devices such as iPads have also been used for student learning in the field, such as with paramedic students (Williams et al. 2011) making the most of physical portability of mobile devices. Podcasting also moves students from the traditional place of the lecture to a chosen location (Dyson et al. 2009; Gkatzidou and Pearson 2009). McGarr (2009) reviewed the literature and found that podcasting in higher education was most commonly used to provide recordings of otherwise conventional lectures. In addition, podcasting provided supplementary material to the lecture. A less common use of podcasting was student-generated, creative podcasts. It would not be helpful to record lectures as podcasts with those subjects that require complex formulae to be demonstrated or with strong visual elements necessary for understanding and so on, but for most courses, this would be useful. Podcasts allow students to make use of the time when they are on the go, moving between venues, while exercising, during a commute, and so on. Again, podcasts should be provided in multiple file formats to allow use on a wide range of devices.

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An educator does not necessarily need high-end hardware to record podcasts. Most smartphones have a voice recorder and this will produce recordings of a sufficient quality for most purposes (Murphy et al. 2014).

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Creativity

A greater use of mobile learning for creative purposes rather than simple replacement of the traditional learning environment is required. Eyadat and Eyadat (2010) named the connection between technology and creativity in higher education “the missing link.” These researchers found that there was a significant difference between the experimental (using technology) and control (receiving traditional teaching) groups of students in their creativity levels. A creative problem solving framework and mobile tool was employed by Wood and Bilsborow (2014) with higher education students, finding that students were more confident to generate solutions to problems and did, indeed, demonstrate greater creativity and divergence in their assignments. Similarly, Terkowsky and his colleagues found that students could work creatively in STEM (science, technology, engineering, and mathematics) subjects using ePortfolios, remote access laboratories, and learning environments accessed via mobile devices. The activities included facets that were known to promote creativity, namely, learning by doing, producing a product, and fostering self-reliance (Terkowsky et al. 2013). The sound and video recorders, cameras, and the ability to access web 2.0 tools for editing and sharing found in most modern mobile devices make it very easy for students to create and share content, wherever they are and whenever they want. These affordances of mobile devices, coupled with carefully designed activities, can foster creativity in students far beyond what is generally encountered in the traditional, didactic classroom.

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Bridging the Knowledge and Application Gap

Augmented reality mediated via mobile devices has been employed in order to better align student experiences and interests with higher education learning and the application of that learning, as well as encouraging creativity and novel solutions to problems. Augmented reality can facilitate problem solving via presentation of scenarios and gameplay (Herro et al. 2013; Squire and Klopfer 2007). It can help learners visualize complex structures, such as anatomical structures, by enabling them to virtually manipulate or walk around an object (Wu et al. 2013). Even so, using mobile devices for augmented reality gaming is not all positive as Hildmann and colleagues found in a multinational comparison study. There were more participants strongly opposed to the mandatory use of mobile devices in their higher education courses than were strongly supportive (Hildmann and Hildmann 2009). The authors note, however, that the results may not be

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representative of the wider university population. The five studies reported on included from 36 to 221 participants, a relatively small sample. Problems of connectivity are particularly heightened when using mobile devices for augmented reality and gaming (Herro et al. 2013; Hildmann and Hildmann 2009). Also, there can be issues when the mobile devices have to interface with other technologies or require ubiquitous connectivity for optimal performance (Wu et al. 2013). These technological difficulties can lead to students disengaging from the learning activity, frustrated at the time spent in troubleshooting issues, and diverting attention away from the learning.

2.5

Interactivity

The interactivity enabled by mobile devices has been explored in higher education with generally positive results (Franklin 2011). For example, the use of microblogging services such as Twitter and other social networking sites such as Facebook was incorporated into multiple higher education courses in New Zealand over a fouryear period with perceived success by students (Cochrane and Bateman 2010). Again, these authors said that integration of mobile learning into subjects requires a paradigm shift on behalf of the lecturers and this takes time. Cheung and Hew (2009) also noted that mobile devices were most commonly used as communication and multimedia access tools which have resulted in technology simply serving as a different means to the same instructional or learning goal. To effect real change, the affordances of mobile devices which enable interactivity must be leveraged. The levels of interactivity between lecturer and student have also been enhanced through the use of mobile devices for immediate assessment of student understanding (Cochrane and Bateman 2010). Using wireless technology and mobile devices such as iPod Touch and iPhone, for example, Stav and his colleagues were able to provide a more flexible and cheaper system than “clickers” for students to use in class (Stav et al. 2010). Using mobile devices in this way allows for more interactivity with the lecturer than just a questioning of students when only one student at a time can respond. It also allows for interaction by students who are normally too shy to respond in the classroom (Lam et al. 2011). Based on the research literature in the domain of wireless, handheld devices in an educational environment, mobile learning is not limited simply to retrieving information and resources. Mobile learning can be much more sophisticated. For example, mobile learning can involve interactively linking with other learners around the world, peer reviewing and learning in real time, and participating in a learning environment irrespective of the location. Hence, mobile learning provides the ability for participants to share resources in a live learning environment. Wireless, handheld devices in the higher education domain have enormous potential to improve learning and the educational experience of students, which is yet to be realized. However, these technologies and the evaluation of their use for learning pose some challenges.

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Challenges in Evaluating Mobile Learning Initiatives

With mobile learning, the focus is less on specific mobile devices and more on enabling students to engage in learning from any location and at any time, regardless of the type of technology in use. Mobile technologies have features and functionality that can be used to supplement and enhance both online and blended learning environments and therefore have the potential to deliver a wide variety of new outcomes for learners, lecturers, and the educational system. As a result, there is a need to determine the specific requirements when considering learning design in the context of mobile learning. Hence, it is necessary to validate the impact of mobile learning principles and initiatives on actual teaching and learning outcomes. A common problem encountered in evaluation models for educational technologies such as mobile devices is that many models focus only on isolated components of mobile learning. For example, models may single out the device, the user, or the institutional context with little consideration of how all of these may interact. These complex interactions need to be suitably expressed within any framework or model under consideration. After a thorough review of the literature, Ng and Nicholas (2013) indicated that there is currently no appropriate model of sustainable mobile learning in institutions. Fundamental to the evaluation of mobile learning is the need to conceptually define just what “mobile learning” is. John Traxler (2007), professor of mobile learning at Wolverhampton University, noted that “mobile” is far more than a mere qualification of the concept of learning. Instead, mobile learning has emerged as a distinct concept complementary to other emerging concepts such as the mobile workforce and a connected society. Traxler (2010) noted that initial attempts to define mobile learning focused exclusively on the mobile devices themselves, making particular reference to handheld or palmtop electronic devices. The next definitions showed an increased focus on mobility, but that focus was largely on the mobility of the technology. The following category shifted away from considering the technology to instead underscore the mobility of the learner and the learning process. Those definitions of mobile learning which only incorporate a description of the technology may become obsolete as mobile technologies and the emerging features of these technologies are changing quickly (Farley et al. 2013). There is a convergence of mobile technologies in single devices which can function as a phone, media player, multimedia, and wireless computer with GPS capability and sensor capability. Further, the explosion of mobile apps can potentially extend and leverage this growing list of multifunctional features (Sharples et al. 2007). Another equally important convergence that has also been occurring is personalized lifelong learning through the interplay between mobile devices and new ways of learning that are emerging (see Table 1). Table 1 provides examples of the interplay that can occur between new ways of learning and the current and increasingly expanding multifunctionality of mobile devices. It is worth noting that mobile apps further extend the ways which this multifunctionality can be leveraged for learning. Traxler (2007) makes a good point in

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Table 1 Interplay between new learning approaches and mobile technologies creating new learning opportunities (Adapted from Sharples et al. 2007) New learning 1. Personalized 2. Learner centered

Multifunctionality of mobile devices 1. Personal 2. User centered

3. Situated 4. Collaborative

3. Mobile 4. Networked

5. Ubiquitous

5. Ubiquitous

6. Lifelong

6. Durable

Examples Digital identity, contacts, calendar, photos, videos Learning can be contextualized to an individual’s preferences and technological capabilities of a mobile device Learning can be situated to a user’s location Learning activities and outcomes can be shared with others regardless of their location, as long as they have mobile broadband internet access, either synchronously or asynchronously Mobile technologies are readily accessible to all across a range of mobile devices and different types of networks with internet access Increasing mobile learning can be stored permanently as part of the digital footprint of users

this regard, in that there are also constraints involved with mobile learning facilitated by students using BYO mobile devices as not every student will have access to the latest mobile devices. The technological diversity and limitations of mobile devices such as mobile phones and tablets provide as many challenges as well as opportunities for academics and institutions wanting to embrace mobile learning in the delivery of the courses. Education and mobile learning are not at the forefront when these types of mobile devices are designed, manufactured, and marketed with corporate, retail, and recreational use in mind. Sharples et al. (2007) suggested that from a theoretical perspective, mobile learning must be tested against the following criteria: • Is it significantly different from current theories of classroom, workplace, or lifelong learning? • Does it account for the mobility of learners? • Does it cover both formal and informal learning? • Does it theorize learning as a constructive and social process? • Does it analyze learning as a personal and situated activity mediated by technology? A Mobile Learning Evaluation Framework needs to consider a number of key issues such as the technological support for mobile learning. Cochrane (2012) listed technological support as one of the critical success factors for mobile learning projects, suggesting a series of introductory technical workshops and intentional Communities of Practice during the planning and implementation of mobile learning initiatives (Cochrane 2012). Botcicki and colleagues (2011) recommended both technological and social scaffolding were necessary for students to fully participate

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in collaborative mobile learning opportunities. Technological support also needs to be considered in those instances where mobile learning is being deployed in developing countries where the technical infrastructure and support are likely to be limited. This aspect of mobile learning needs to be evaluated from the student, academic staff, and institutional level perspectives. Beyond investigating and describing the technological aspects of a mobile learning initiative, a number of other questions need to be asked and represented in a Mobile Learning Evaluation Framework: • Are there sufficient mobile learning opportunities that can be delivered to students and do these mobile learning opportunities leverage the multifunctionality of mobile devices such as smartphones and tablets as the technological boundaries of mobile learning are becoming blurred? • How do we accommodate the needs of students who do not have access to mobile devices and/or do not have access to mobile broadband internet? • How can institutions provide personalized mobile learning that accommodates the learning styles and needs of individuals and their technological capability? • How do we evaluate academic staff effectiveness in developing mobile learning opportunities which leverage the multifunctionality capability of mobile devices including always on connectivity? • How do we evaluate the effectiveness of mobile learning opportunities from a pedagogical perspective and are these in line with the broad aims and objectives of academic institutions? • Is institutional policy providing the impetus and support for academics to develop mobile learning opportunities for its students? • How do we accommodate the diversity of student populations in providing mobile learning opportunities?

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Development of Frameworks for Evaluating Mobile Learning in Higher Education

A Joint Information Systems Committee (JISC) eLearning program report, published in late 2010, stated that the most significant issue in mobile learning is the absence of full-scale evaluations of mobile technologies in the higher education sector (Wishart and Green 2010). The same report also bemoaned the lack of a stable model from which to effectively research the role, drivers, and impact of mobility on learning (Park 2011). There have been several attempts to theorize mobile learning, yet none have succeeded in ensuring a comprehensive and rigorous analysis of the swiftly developing landscape of mobile learning initiatives, networks, and technologies. Some models are emerging directly in response to the proliferation of mobile learning initiatives; others are adapted from existing evaluation frameworks for other technologies. The section below will provide a brief, critical overview of a few of the mobile learning frameworks and models identified in the research literature.

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The Evaluation of Technologies Framework: Ng and Nicholas (2013)

Ng and Nicholas 2013’s Evaluation of Technologies Framework is focused on mobile learning in primary and secondary schools, rather than in higher education institutions. Their research addressed how the interactions between stakeholders and between users and devices influence the sustainability of a mobile learning innovation in a particular institution. The emphasis is on how person-centered notions of sustainability are important for innovation. This Technology Evaluation Framework explains the interplay between a range of players or stakeholders and provides a holistic picture of mobile learning which considers the roles of the key stakeholders in the adoption of mobile learning (Ng and Nicholas 2013). Though useful, there are significant implications in applying this model to mobile learning in the higher education context. Individual educators are more likely to determine the successful adoption of any mobile learning initiative, and typically, universities are much larger orders of magnitude and complexity than individual schools. The Evaluation of Technologies Framework has emerged relatively recently and, as yet, has had limited impact on the planning and implementation of mobile learning initiatives in higher education. However, this may change given time.

4.2

A Critical Analysis: Frohberg, Göth, and Schwabe (2009)

Frohberg et al. (2009) critical analysis can’t really be considered a framework – no formal structure is proposed. However, the authors identify the central benefits and values of 102 mobile learning initiatives, before naming common pitfalls and making some recommendations. Frohberg and colleagues reviewed the literature using a methodology based on the work of Sharples et al. (2007). A weakness of this approach, by their own admission, is that this work is literature-based and not based on primary data. It is also possible that key literature was missed because key studies could have been published in journals of another discipline rather than in the educational technology or mobile learning journals (Frohberg et al. 2009). It was also formulated before the emergence of tablets and smartphones. However, this research makes an important point and concludes by saying that mobile learning is best used for learning in context, rather than just information delivery which can be done by other means. The researchers also suggest that advanced learners be targeted first (Frohberg et al. 2009). As the title suggests, this may indicate the future of mobile learning, yet very few educators are ready for such a nuanced and advanced view of mobile learning.

4.3

A Framework for Analyzing Mobile Learning: Sharples, Taylor, and Vavoula (2007)

Sharples et al. (2007) argue that conversation is the driving process of learning. This research builds on the work of Laurillard (2002) which previously built on the work of Pask (1975). This research is important as a foundational work which is specific to

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mobile learning. However, this research was conducted before tablets and smartphones become mainstream consumer devices, although it does refer to PDAs. This research provided some useful insights by looking into individual mobile learning initiatives which is appropriate given when it was written, well before the widespread adoption of mobile devices such as laptops, tablets, and smartphones.

4.4

Pedagogical Forms for Mobile Learning: Laurillard 2007 (Based on Work in 2002)

Laurillard’s (2007) Conversational Framework has gained considerable traction in educational technology research, but is not mobile specific. The basis of this framework in formal learning is that it rests on two levels: (1) a “discursive” level between student and teacher which accommodates theory, concepts, and description building and (2) an “experiential” level, also between student and teacher, but which focuses on practice, activity, and procedure building; both levels are interactive. Interestingly, this research also considers the importance of informal or unstructured learning which may be as important as formal learning in evaluating the effectiveness of mobile learning as a paradigm shift in learning in the higher education sector.

5

Developing a Mobile Learning Evaluation Framework

Over the previous decade, a number of studies have been conducted across sectors to investigate the role of mobile learning in learning and teaching (e.g., Elias 2011; Biggs and Justice 2011; Wong 2012). These studies consistently demonstrate that there are a significant number of difficulties that hinder the adoption of mobile learning, both at an institutional and at a user level, both educator and learner. Higher education leaders are wary about investing heavily in new mobile technologies because of the rate with which they become superseded. Consequently, only a small number of higher education institutions have deployed well-resourced mobile learning initiatives. Researchers at the University of Southern Queensland (USQ), in partnership with researchers at the Australian National University (ANU) and the University of South Australia (UniSA), are working to develop a Mobile Learning Evaluation Framework (MLEF). This is one of the five projects at USQ funded under the Australian Government’s Collaborative Research Network funding secured by the three partner institutions. The aim of the MLEF project is to support leaders and educators in higher education institutions to provide sustainable mobile learning opportunities to students. This project will result in three significant outcomes: 1. A standardized model to explore how mobile learning initiatives impact on learning and teaching in higher education 2. A review and analysis of the broad spectrum of pilot studies and initiatives that have been implemented in Australia and elsewhere and the kinds of approaches used to evaluate them

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3. A Mobile Learning Evaluation toolkit: a set of principles, procedures, and methods that can be used to promote the collection and review of information related to new mobile technologies, the objective evaluation of mobile learning initiatives, and prioritization of proposed investments in mobile learning within various learning contexts In order to measure the educative value of a particular educational technology, Quinton et al. (2010) recommended three areas of focus: pedagogical, technical, and organizational. For the purpose of this project, this model will be adapted by further breaking down the area of pedagogical to pedagogical (teaching) and pedagogical (learning), so that four primary themes will be explored during the data collection and analysis activities. The challenges, needs, and issues will be examined at each level when considering the implementation of mobile learning initiatives. Therefore, this project will focus on the following four areas: • Organizational: Clarification of the institutional policies and practices that currently support or hinder the implementation of mobile learning initiatives • Technical: Identification of the supporting technical infrastructure and technical support, as well as the priorities, standards, and protocols that will impact on the success of mobile learning initiatives • Pedagogical (teaching): Reflection on the strengths and inefficiencies of current mobile learning practices as well as the barriers and critical success factors that impact on the adoption of mobile learning initiatives • Pedagogical (learning): Exploration of the current expectations of mobile learning and insight into current formal or informal mobile learning practices to identify gaps in current services and student learning needs In addition to the four areas above, this research has identified that the “readiness” of the institution and the learning and teaching environment through the wireless handheld devices is a critical component for the successful implementation of mobile learning initiatives. “Readiness” is defined as the extent to which the educational institution is prepared to deploy and support mobile learning initiatives in terms of technology, organization, management, and learning and teaching resources. Figure 1 is a diagrammatic representation of the relationship between the various aspects of higher education impacting on mobile learning initiatives. The Mobile Learning Evaluation Framework project aims to create a flexible framework to fulfill the foreseeable needs of users, both educators and learners, in the deployment, support, and evaluation of mobile learning initiatives. An iterative approach will be employed, each phase incorporating the learnings from the preceding phase, allowing the inclusion of emerging innovations as the project progresses. Participatory monitoring and evaluation (PM&E) methods will be employed in the development of the project. This methodology has evolved through the broadening of participatory action research (PAR) into evaluation (Lennie 2006). It employs a holistic approach, accounting for the diverse perceptions and interpretations of project participants, collaboratively engaging them across all levels of the

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Pedagogical (Learning) Student perspective

R e a d i n e s s

Learning needs and desires Current and intended use Demographic and social context

Pedagogical (Teaching) Educator perspective Beliefs and pedagogies Critical success factors/barriers Context and learning objectives

Technical Processes and policies Organizational barriers Resourcing Technological context

Organizational Institutional strategy/vision Focus and commitment Leadership support Sector context

R e a d i n e s s

Fig. 1 The relationship between various aspects of higher education impacting on mobile learning initiatives

project (Estrella 2000). These methodological underpinnings of the project will confirm that the project outcomes are relevant across a wide range of real-world learning contexts.

5.1

Stage 1: Development of the Mobile Learning Evaluation Criteria

The focus of the first stage of the project will be on developing the preliminary evaluation criteria and framework. The following groups, representative of the four foci of the framework (pedagogical – teaching and learning – technical, and organizational), will be consulted to pinpoint the needs, expectations, and challenges when considering the deployment of mobile learning initiatives: 1. Pedagogical (learning): Students at each of the three partner institutions who are interested in mobile learning who will be able to contribute input on needs and preferences 2. Pedagogical (teaching): Educators from a variety of higher education institutions across the world who have attempted to implement mobile learning initiatives 3. Technical: ICT or learning systems that support representatives responsible for technical infrastructure, standards, and protocols 4. Organizational: Senior management at the partner institutions and higher education institutions across the world who have implemented pilot studies or institution-wide mobile learning initiatives

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As participatory action research forms a fundamental part of the project, participants will be invited to review and comment on research findings and deliverables. Social media channels established as part of this project and a project blog will be used to enable these interactions.

5.2

Stage 2: Validation of Evaluation Criteria and Development of Models and Frameworks

The evaluation criteria will be validated during second stage of the project. This stage also sees the confirmation and development of the framework. In order to ensure that the evaluation criteria are reliable and representative of the Australian higher education sector, a large-scale survey will be deployed. Four survey instruments will be developed, corresponding to each of the framework’s foci. Data collected during the first stage of the project will serve as the item pool for the surveys. These surveys will measure and describe institutional context, adoption drivers and barriers, user expectations and needs, pedagogical criteria, and the perceived impact of mobile learning initiatives. The draft instruments will be sent to the participants and a panel of experts for formal review. The first iteration of the survey instrument will be piloted on a sample of students and educators at one of the partner universities. The data collected will be analyzed using SPSS and the results will be used to refine the instruments. The data obtained from participants completing the refined surveys will be used to calculate reliability and validity of the instruments, validate the framework using techniques such as structural equation modeling (SEM), and obtain the normative data. The data will also be analyzed in order to segment and profile the differences in mobile learning by students and educators across various regions, demographics, age groups, and study fields.

5.3

Stage 3: Finalization of the Mobile Learning Evaluation Framework

During the final stage of the project, the finalized Mobile Learning Evaluation Framework and resources will be made available on the online website to be accessed freely by the education community. The toolkit will also act as a resource for the community that will enable the identification of mobile learning initiatives that have been demonstrated in pilot and experimental studies to contribute to highquality learning experiences and which can be reused and adapted across learning contexts. The project is currently in the first stage: development of the mobile learning evaluation criteria. This component of the research has included an extensive project management phase which involved developing the preliminary project website and blog and development of the project plan. During the initial stages of planning the research activities and conducting a literature review, it was identified that few

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researchers are in agreement about the definition, attributes, and affordances of mobile learning. This was a gap in the research identified by the project team that requires redress in order to develop a theoretically sound evaluation framework. Consequently, an online Delphi survey was developed to reach out to experts in the mobile learning research community in order to develop a consensus definition of mobile learning. The findings from the final phase of the Delphi technique will contribute to the foundation of the Mobile Learning Evaluation Framework. The project team is also currently recruiting and conducting focus groups and interviews with educators and students at the three universities (USQ, UniSA, and ANU). The interviews with mobile learning pioneers will be held in the form of webinars that will be available for participants of the mobile learning research community to attend. These webinars will also be made available as open educational resources on the project website to be used and accessed freely, accompanied by a case study about the project. Key learnings that have been identified during this phase are that educators and researchers have differing ideas about what mobile learning means and that this disparity in understanding often hinders adoption of mobile technologies for learning and teaching among educators. An additional learning is that sufficient time for effective project management and planning is a key consideration when developing large-scale research studies, and the amount of time required for these activities can be easily underestimated.

6

Future Directions

Mobile learning has surfaced as a new learning paradigm, becoming an intense focus of research as the technologies become ever more capable of supporting learning in both blended and mobile-only modes (Kukulska-Hulme et al. 2011; Engel et al. 2011). The ubiquitous connectivity of mobile technologies enables new ways of communicating, erases physical boundaries, and allows for the formation and support of distributed communities of learners (Garrison 2011, p.1). As the National Broadband Network (NBN) becomes more widely available in Australia, enabling ultrahigh-speed connectivity and unprecedented levels of access, education will shift from face-to-face and traditional distance education models to mobile models. This will enable educators to reach out to learners in regional, rural, and remote areas. Mobile devices provided and supported by the university make network and information administration manageable. But devices are expensive for the institution, and students typically already own one or more mobile devices such as smartphones, tablets, and laptops. These are devices that they bring to campus and expect to use directly in learning and in support activities. Allowing the practice of bring your own device (BYOD) enables the university to shift the costs of ownership and administration to the user from the institution but faces the administration of the university wireless access network with security risks from allowing a wide range of devices and systems access over its enterprise network, in common with other

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noneducational institutions (Godfrey 2013). These concerns typically lead to the university barring or restricting the use of some operating systems and applications that users normally rely on, turning the normally seamless device and services into something visibly patchy and possibly crippled. Ironically, these restrictions can mean that the learner may experience a worse mobile learning environment when on campus, despite being closer to the hub of face-to-face learning activities. For the institution to reduce these access barriers for the sake of mobile learning will mean an increased cost in network administration to maintain network security, undercutting the original promise of reduced cost from BYOD and mobility. However, slow institutions have been to adapt their provision of services and content; students are using their own portable devices. They choose between their devices for specific purposes, preferring smaller portable devices such as tablets for consumption (reading) and larger or more fixed devices (laptops and desktops) for creation of content (writing) (Dahlstrom 2012) – and choosing smartphones and tablets to support and manage their formal and informal learning activities, although possibly using different apps for social and academic purposes (e.g., see ▶ Chap. 27, “Tutors in Pockets for Economics” by Zhang et al. in this handbook). In reviewing the literature, five aspects of the use of mobile learning have emerged, namely, (1) altered delivery of content and knowledge storage, (2) portability, (3) creativity, (4) bridging the knowledge and application gap, and (5) interactivity. Given this diversity, it becomes imperative to evaluate mobile learning initiatives to ascertain their impact on learning and to ensure their sustainability allowing for the considerable investment of time, money, and resources. Though a number of evaluation frameworks exist, either emerging as a direct result of the increased emphasis on mobile learning or through the adaptation of other eLearning frameworks, none are sufficiently nuanced to address the issues and answer the challenges associated with deploying mobile learning initiatives across a wide range of higher education contexts. Consequently, the latter part of this chapter describes a project underway at the University of Southern Queensland, the Australian National University, and the University of South Australia that is more pragmatic in its approach. The project will develop a Mobile Learning Evaluation Framework that will aid in the selection and justification of mobile learning initiatives. Participatory monitoring and evaluation (PM&E) methods will be used to develop outcomes and deliverables. The resultant Mobile Learning Evaluation Framework will consider the issues and challenges associated with deploying and sustaining mobile learning initiatives from four distinct perspectives: (1) pedagogical learning, (2) pedagogical teaching, (3) technical, and (4) organizational.

7

Cross-References

▶ Framework for Design of Mobile Learning Strategies ▶ Tutors in Pockets for Economics

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Internet-Based Peer-Assisted Learning: Current Models, Future Applications, and Potential

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 The Philosophy of Peer-Assisted Learning (PAL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Face-to-Face PAL Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Internet-Based PAL Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Structure of PAL Program Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Evaluation of Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Development of Internet-Based PAL Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Peer-Assisted Learning (PAL) is recognized as an effective academic support program designed to assist students’ learning needs. At the tertiary level, universities in Western countries have developed and implemented various forms of PAL programs catering for students across disciplines, commonly targeting

T. K. Huang (*) School of Accounting and Finance, Faculty of Business, Justice and Behavioural Science, Charles Sturt University, Port Macquarie, NSW, Australia e-mail: [email protected] J. Cui · C. Cortese School of Accounting, Economics and Finance, Faculty of Business, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected]; [email protected]; [email protected] M. Pepper School of Management, Operations and Marketing, Faculty of Business, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_18

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transitional subjects which are perceived to be difficult. Studies have demonstrated that PAL programs positively contribute to better student performance and higher student retention rates. However, there has been relatively little discussion on how new technological trends can be applied to extend the PAL platform to suit the evolving student lifestyle and changes in learning behaviors. In this chapter, several models for Internet-based PAL are discussed and evaluated. The chapter also outlines some of the technological and other requirements for the establishment and maintenance of these Internet-based PAL programs. Finally, an evaluation of the potential outcomes is presented. The discussion highlights that Internet-based PAL programs can be used as an instructive complement to existing face-to-face PAL programs, further extending the benefits of student peer learning and social exchange with the convenience of mobile technology.

1

Introduction

Catering for students’ educational needs is a key success factor of higher education institutions (Wingate 2007; Molesworth et al. 2009; Stokes and Wilson 2011; Laurillard 2013; Entwistle and Ramsden 2015). For Western universities, the provision of learning and pastoral care to international students is even more important for the institutions’ financial and academic performance (Sawir 2005; Arkoudis and Tran 2010; Komlijenovic and Robertson 2016). Driven by the marketization of the education sector, universities are now facing challenging ethical dilemmas when safeguarding academic integrity while at the same time protecting their own managerial business interests (Hemsley-Brown and Oplatka 2006; Newman and Jahdi 2009; Ross et al. 2013; Komlijenovic and Robertson 2016). In other words, universities are faced with decisions regarding the amount, scope, and access to academic support to aid students in their study. As a result, providing high-quality supportive programs to students is an important step toward enhancing their learning experiences and addressing some of the pastoral issues that international students might experience in higher education institutions. Peer-Assisted Learning (PAL) is a student academic support program utilizing collaborative learning to enhance individual learning experiences and skills. PAL can be viewed as an alternative terminology (commonly found outside the USA) of the Supplemental Instruction (SI) model first developed by Dr. Martin at the University of Missouri-Kansas City (e.g., see Blanc et al. 1983; Arendale 1994). At present, various disseminations of PAL programs and models are implemented in higher education institutions across Western countries as an essential part of teaching and learning management, including the USA, Australia, Canada, the UK, and South Africa. Traditionally, PAL programs often use face-to-face study sessions/workshops as the main delivery channels. With advances in technology and evolving student lifestyles, some institutions have begun to develop and implement

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Internet-based PAL programs as supplements to face-to-face study sessions (e.g., UMKC’s Video-based Supplemental Instruction approach). For PAL program, this is a step forward to better suit the student learning needs in the digital age. This chapter provides a review of PAL programs and discusses some examples of Internet-based PAL models to extend the educational benefits of PAL programs. It aims to enrich the current understanding of PAL philosophy, highlighting some of the potential benefits and trade-offs that Internet-based and future mobile PAL programs could bring to the higher education sector. Case studies of both formal and informal Internet-based PAL programs are investigated, and evaluations of the pros and cons of possible models are provided.

2

Background

2.1

The Philosophy of Peer-Assisted Learning (PAL)

The PAL program utilizes a peer-led group to provide additional academic assistance for students to supplement formal face-to-face teaching hours (e.g., lectures, tutorials, workshops, or seminars), aiming to assist students achieving positive results. Facilitated by senior students (commonly referred to as leaders) who have excelled in the subject during previous semesters, PAL provides opportunities for participating students to strengthen their knowledge by actively being involved in group learning focused on material review and practical problem-solving (Sole et al. 2012). The recognized benefits of participating in the PAL program for students include better engagement with the university (van der Meer and Scott 2009), better connections with other students (van der Meer and Scott 2009; Longfellow et al. 2008), improved self-concept and enhanced learning behavior (Ginsburg-Block et al. 2006), and the notably observed improvement in academic performance (McCarthy et al. 1997; Parkinson 2009; Malm et al. 2011; Devine and Jolly 2011). The program hence benefits the institution facilitating the PAL program via positive impacts on student retention (Etter et al. 2001; Hensen and Shelly 2003; Dawson et al. 2014). PAL programs traditionally target challenging subjects, commonly observed in the discipline of Engineering (Malm et al. 2011), Mathematics and Chemistry (Parkinson 2009; Devine and Jolly 2011), and Medical Studies (Knobe et al. 2010; Yu et al. 2011; Sole et al. 2012). In current development, PAL has incorporated commerce subjects as the commerce subjects can be challenging for students (Minnaert et al. 2011; Zraa et al. 2011; Calkins 2012). For international students, the major benefits of participation in a PAL program include more opportunities for engaging and interacting with domestic student peers and consequently become more accustomed to the host country culture and learning environment (Leask 2009). The PAL philosophy draws from behavioral and social learning principles (e.g., Skinner’s radical behaviorism and Bandura’s social learning theory). For instance,

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Bandura’s social learning theory is used to explain the rationale that high-achieving peer students are used as PAL leaders in study sessions. Benefits of being a PAL program leader include enhanced academic knowledge, improving interpersonal qualities, development of leadership and teamwork skills, networking opportunities, and formal institutional recognitions in curriculum vitae. Student leaders in PAL program are very sought after by employers across many industrial sectors. PAL program participants are expected to imitate the leaders’ behavior in learning that may lead to favorable outcomes. Thus, engaging in close contact with a role model (face to face) is considered an important influence on new learners’ adoption of relevant learning behaviors and hence assists them to improve academic performance. However, Bandura (1977) states that observation of a live model is not always necessary for the behavior change stimuli to take place. Rather, verbal instruction and symbolic messages (including use of media and the Internet) can also be considered as vehicles for delivering modeling stimuli. As a result, a question arises as to whether the change from a face-to-face PAL model to a web-based noncontact PAL model will cause dilution of PAL programs’ educational benefits.

2.2

Face-to-Face PAL Models

2.2.1 Traditional Model Among the various dissemination forms of PAL programs implemented in higher education institutions, the most common model is face-to-face, regularly scheduled study sessions in which English is predominately used. In Australia, known universities which currently have implemented PAL (commonly referred to as PASS (peerassisted study sessions)) programs include the University of Wollongong, Monash University, Macquarie University, and University of Sydney. These programs can be both institutionally funded and implemented, where the PAL leaders are employed and remunerated, or based on altruistic activities where students are recruited as voluntary contributors. An archetypical PAL program is built on a peer-mentoring engagement between peer leaders and student participants. Using a “super group” approach, PAL study session aims to enhance students’ learning by integrating course content-focused study techniques and successful assessment/exam skills in a casual and relaxed atmosphere. The open dialogue engagement and social exchange between PAL leaders and students as well as between students studying in the same course are both influential factors to individual learning behavior change. The communication exchange between PAL leaders and participating students is considered to be less formal than in formal teaching contact hours; thus students commonly find themselves feeling more comfortable to interact and ask questions (Zaccagnini and Verenikina 2013). The PAL program provides opportunities for participating students to ask the questions they really want to get help on without the pressure of feeling their academic credibility is being put on the line. The intention is that students can work in a positive, supportive, and productive team environment which enhances their communication and critical and creative thinking abilities.

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Of course, these positive attributes can be carried into other aspects of students’ university life beyond PAL study sessions or even further into their future career workplace. However, it should be noted that the quality of actual academic content delivered in PAL study sessions is equally, if not more, important than the positive influences on learning behavior change. Students who have experienced PAL study sessions often comment that the revision of lecture and tutorial materials, recap of important theories/concepts, and more clarifications on assessment expectations make PAL programs very appealing to them. Although direct reteaching is not the purpose of PAL programs and PAL facilitators often emphasize that reteaching in PAL study sessions should be strictly avoided, it has been stated that sometimes reteaching cannot be avoided. In fact, in extreme circumstances, deliberate reteaching is needed to ensure the effectiveness of PAL programs (Cui et al. 2015).

2.2.2 Other Forms of Disseminations In addition to traditional PAL programs, there are also learning support programs which embrace PAL philosophies operating in higher education institutions. These different forms of dissemination of PAL programs may or may not explicitly include PAL as part of the programs’ title, but their management and operation are largely similar to traditional PAL programs. Cui et al. (2015) discuss a Bilingual Peer-Assisted Learning (B-PAL) program, which has been implemented in an Australian regional university to assist the teaching of Chinese international students. Under the B-PAL program, bilingual workshops using Mandarin and English conducted in the end of each session across more than 20 subjects including accounting, finance, economics, and management in business faculty. Unlike traditional PAL programs that strictly avoid reteaching, this B-PAL program deliberately includes reteaching of academic content covered in lectures and tutorials in the workshop. The use of Chinese students’ first language is an effective element that influences their learning, as the bilingual instruction can enhance students’ learning of academic content in a secondary language context by helping in conveying meanings (Cook 2001). It has other benefits including using first language to motivate students and scaffold learning (Turnbull and Arnett 2002), facilitating communicative features in group learning, and enhancing student/teacher interactions (Ghorbani 2011), as well as helping to establish constructive social relationships and communicating complex meanings (Littlewood and Yu 2011). The results of a qualitative analysis of Chinese students’ experiences of the B-PAL program show that in addition to the recognized benefits of traditional PAL programs on students’ learning, the bilingual approach provided extra value such as conveying meanings, sense making, and reducing exam/assessment anxieties (Cui et al. 2015). It should be noted that Cui et al. (2014) also reveal that students equally value the peer-teaching process and the actual academic content delivered in the B-PAL workshop, considering both as effective influential factors enhancing their learning experience and academic performance. In addition, the majority of Chinese student state that the academic content is extremely important. In fact, they prefer for teaching materials to be distributed online pre or after the workshop. However, they

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also acknowledge that the face-to-face contact and two-way communication are necessary for them to make better use of the materials and gain a better understanding of the subject. PAL programs were originally designed to target struggling subjects, not struggling students (Arendale 1994). However, there are also learning support programs that utilize the PAL model to provide educational support to students with genuine learning difficulties (also referred to as students-at-risk). As an example, the Australian Department of Education, Employment and Workplace Relations administrates and financially supports the Indigenous Tutorial Assistance Scheme (ITAS), which is a program providing supplementary tuition to support eligible Indigenous students to study university award level courses (2010). The purpose of the ITAS program is to accelerate education outcomes for Indigenous Australians beyond those which could reasonably be expected from the mainstream and the providers’ own financial resources alone. By offering regular face-to-face learning support delivered by a student leader, ITAS aims to improve the academic efficacy of Indigenous students in tertiary courses to the same levels as those for non-Indigenous Australians. Unlike traditional PAL programs where study sessions are often conducted in a one leader to many students format, ITAS programs generally rely on one-to-one peer teaching to achieve its objectives. In this sense, the level of direct face-to-face contact and engagement is more significant in the ITAS model.

2.2.3 Facilitating Learning Process or Providing Material? By examining both the traditional PAL model and the alternative forms of assisted study support, multiple benefits have been observed from different forms of PAL programs particularly on improving self-concept and learning behavior (Ginsburg-Block et al. 2006), hence notably improvement on academic performance (McCarthy et al. 1997; Parkinson 2009; Malm et al. 2011; Devine and Jolly 2011). Then it can be observed that a key question needs to be addressed before considering the development of an Internet-based PAL program. This question is what is more important/valuable/effective toward improving student academic performance, the peer-mentoring/teaching process or the actual content/materials distributed in PAL study sessions? An Internet-based PAL platform can have tangible advantages in connectivity and content distribution, but can Internet-based PAL programs offer similar environments for peer-to-peer communication and engagement which is needed for social learning to occur? Both the learning process and the material can be important motivations for students to participate in a PAL program. In addition to the engaging and collaborative learning environment, the distribution of PAL study session material should not be overlooked. Often there are some participants in the traditional PAL program who remain quiet during the session and have no engagement with leaders. The participants’ main motivation to join a PAL study session is to collect the teaching material distributed by the student leaders, rather than treat PAL program as an opportunity to interact with peers to enhance their knowledge and improve their individual study skills. Such passive learning behaviors result in the “silent group”

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which exists in PAL study sessions which merely follows the instruction of the PAL leader and seldom expresses their opinion or communicates with other student peers. In a face-to-face PAL session, these “silent group” sometime are forced by leaders to engage with others using various PAL teaching techniques. Now with the development of information technology, the Internet as an intermediate has been broadly used in higher education section with the implementation of students’ e-learning system, learning platform such as blackboard, and mass email system. These developments allow students to access their students’ profile and information at any time and any place when they connected to the Internet. PAL programs are under transition to Internet-based PAL program. However, the techniques PAL leader often use in face-to-face study sessions will be hard to apply online. The idea of using Internet-based PAL program to assist teaching is still appealing. Unlike the traditional PAL programs which are well developed and designed, Internet-based PAL programs are often implemented as a trial. Similar to the traditional PAL program that relies on face-to-face peer mentoring, the key features of successfully implementing an Internet-based PAL program are interactions and engagements of students. Then another question that should be asked is to what extent the interactions and engagements are sufficient? Distributions of material or illustrations of examples do not count for interactions or engagements, particularly in the online environment. For instance, if the leader would like to demonstrate a stepby-step solution, it would be easier through a face-to-face PAL session but difficult through an Internet-based PAL session. The interactions and engagements require in-depth communications and real-time feedbacks between leaders and participants. In face-to-face PAL sessions, it is relatively easy to maintain a friendly learning atmosphere through casual conversation among leaders and participants, using body languages or other teaching facilities like whiteboard or PowerPoint slides. It takes more time to for the participants and leaders to know each other and further build up a friendly learning environment over an Internet-based PAL session. This chapter goes on to discuss existing Internet-based PAL programs, identifying current trends and commonly found issues.

3

Internet-Based PAL Programs

A variety of terminologies have also been used to describe the Internet-based PAL programs, including PAL-Fleximode, Off-Campus PAL Program, or Online PAL Scheme. At present, Internet-based PAL programs are run on a much smaller scale compared to face-to-face PAL study sessions and considered in the testing or pilot phase of development. A number of studies have reported on the schemes, implementation, and preliminary results observed in pilot PAL programs (e.g., see Beaumont et al. 2012; Beckmann and Kilby 2008; Armstrong et al. 2011; Huijser et al. 2008). This section summarizes these findings and couches them in the context of how best to design and implement Internet-based PAL programs. Initially, to cater to the growing need of PAL programs from students off-campus or who are unable to attend scheduled PAL study sessions, video-based PAL

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programs are designed and implemented. For example, the University of MissouriKansas City (UMKC) initiated one of the earliest versions of Video-based Supplemental Instruction (VSI), which combines remote teaching of course content with Supplemental Instruction (SI) study sessions (UMKC n.d.). Teaching academics capture video recordings of their lectures. Trained facilitators, using the recorded lectures and the SI model, guide students through the learning process while emphasizing critical thinking and study skills. Assessments are provided by the academics keeping the facilitator in the role as a peer supporter and not an evaluator. Although for such video-based PAL programs the presence of a peer leader is still needed in a face-to-face learning environment, it opens up the possibility for PAL programs to be implemented online. Beaumont et al. (2012) establish some of the evaluation criteria for a successfully implemented Internet-based PAL program, including the suitability of synchronous communication, student interests, and whether the standard PAL principles and approaches can be carried and transferred online. Based on their case study of a pilot Internet-based PAL program implemented in an Australian university, there are observable benefits such as flexibility and convenience to attend a study session and higher students’ confidence to contribute in discussions and leader-student interactions. These benefits are essential for students who find it difficult to attend campus due to other commitments and perceive studies as their non-priority. Internet-based PAL program benefits these students by offering opportunity to access the same study information as those students on-campus. The Internet-based PAL program also provides a platform for those generally shy students to unveil themselves online without any concerns of embarrassment in a high-contact study sessions. In contrast, many drawbacks were experienced, such as poor content coverage, causing of distractions, and most importantly, leading to an impersonal nature of delivery which contradicts the philosophies of the PAL program. The software and connection lag issues lead to longer waiting processes when leaders are presenting the materials and providing feedback to participants. Finding also suggests that students procrastinated on completing class activities due to the lack of visual clues. It can be seen that online environment could actually hinder leaders’ ability to observe participants’ reactions (Beaumont et al. 2012). In addition, for international students who are from non-English-speaking countries, they are reluctant to express their opinion due to their lack of proficient language skills. It takes more time for them to post a response, which makes the student leader’s control of session time more difficult. The “invisible-to-each-other” relation between leaders and participants may also become a discouraging learning environment, as the communications are found to be impersonal, and it is difficult for the students and leaders to build trust and friendship. One of the benefits perceived in PAL program is that participants can observe or interact with role model students who have demonstrated their learning behavior through PAL program and are motivated through ego-enhancement. The effect of role models underpinned by the social learning theory can promulgate participants to model, imitate, and adopt the behavior themselves (Bandura 1977; Wenger 2010). Based on the limitation identified, the effectiveness of using peer

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leader as role models to influence students’ learning behavior may be reduced when programs are delivered online. Similarly, other studies also state that although student responses were generally positive on Internet-based PAL programs using online communication and collaboration tools (such as Google Docs, MSN Messenger, and virtual classrooms), researchers found that participation was hard to maintain and peer leaders often felt high pressure to moderate online group discussions (Beckmann and Kilby 2008; Armstrong et al. 2011; Huijser et al. 2008). Thus, the recruitment, training, and development of peer leader for Internet-based PAL programs are essential for the future success of such programs. The success of enabling students to gain multiple benefits from PAL programs depends on teachers’ own proficiency in languages, experiences, and cultures (Skalicky 2008; Cui et al. 2015). In addition to these qualities, other positive characteristics are expected from an effective online PAL program leader, such as the ability to remain an authoritative figure to regulate communications and discussions as well as good interpersonal skills to deal with unfavorable student online behaviors (such as causing distraction and inappropriate language use). In relation to the selection of online platform, it appears that the use of multi-people chatting software is not a favorable option as it is highly likely that participating students will start an irrelevant/distracting discussion. Use of discussion forums is a better alternative, as the leaders can keep better track of posted discussions and the program coordinators have an opportunity to study the communication process later to identify potential places for improvement. It needs to be clearly stated that the relatively low participation/attendance rate in Internet-based PAL programs recorded in the aforementioned studies is of significant concern. In earlier studies regarding PAL programs, results indicate that some PAL program participating students use the program as an alternative to formal teaching hours, hence causing the institutions and faculty members to express a certain degree of concern. At the same time, in many scenarios, the academics do consider that PAL programs provide the “last threshold” for some students who have very low study motivation and whose academic performance will likely drop even further without access to a PAL program. If a PAL programs’ switching from a face-to-face model to an online model causes lower attendance/participation, then the value of a PAL program will not be fully realized, and the students’ performances are at risk. Consequently, if an institution plans to establish an online PAL program, it is important that an enduring online learning community must be established and maintained among the faculty, PAL leaders, and students. The key features necessary to achieve such an online learning community identified in earlier studies include making learning interactive and collaborative, creating student-centered approaches, focusing on reflective thinking, and stimulating learner interest through the use of multimedia techniques (e.g., see Maor 2003; Wang et al. 2003; LaPointe and Reisetter 2008; Liu et al. 2010). In addition to the technological requirement, humanistic qualities in teaching and learning are also important criteria for building an online learning community and hence realizing the potential of Internet-based PAL programs.

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Structure of PAL Program Implementation

The implementation of traditional and Internet-based PAL programs in higher education institutions can have a number of structural arrangements. Figure 1 illustrates some of the arrangement that can be made to utilize an institution-based PAL program to enhance students’ learning. The use of online or mobile teaching and traditional on-campus PAL program to support formal contact teaching is well discussed in literature and other chapters of this book; this chapter focuses on discussing how Internet-based PAL programs can provide additional educational benefits to suit different student learning needs. The first possibility is to implement an online addition to the existing on-campus PAL programs to support formal teaching (A + B in Fig. 1). As discussed earlier, some students find attending on-campus PAL programs can be difficult due to timetabling issues or work conflict as these traditional PAL programs are often scheduled in regular school hours. In this scenario, including an online session

Fig. 1 Implementation structure of PAL programs

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will benefit these students, particularly the part-time students who also are employed. For the institution, integrating on-campus and online PAL programs offers learning potential for both the program coordinators and the PAL program leaders. This structure is suitable for large education institutions with its own PAL program coordinating unit that are interested in the research and development of PAL programs. What is important for the PAL program to identify is the transferability of the content and teaching style when the program is conducted online, actively seeking feedback from leaders and participating students to accumulate know-how and expertise. In contrast, for smaller campuses or satellite campus where it is less cost-efficient to establish on-campus PAL program, starting with an online PAL program can be a useful strategy to identify whether PAL approaches enhance students learning in a smaller campus environment and reduce the perceived learning gap between students in remote campuses and students in main campuses (D in Fig. 1). This implementation will be more useful when online teaching is the main education offered in these campus (lecture and tutorials are delivered through video conference or recorded media), as it is often found that remote campus students do require additional learning support due to less connectivity and engagement with teaching personnel in the main campus. Therefore, the Internet-based PAL programs used to support off-campus students or satellite campus students need to embrace effective online education pedagogies; ensure the program is relevant, interactive, and collaborative; and, most importantly, give learners the flexibility to control over their own learning (Bonk 2006).

5

Evaluation of Effectiveness

As discussed in the previous section, the application of Internet-based PAL program potentially enables higher education institutions to further narrow the learning quality gap between on-campus and online/off-campus students. However, the quality management and assurance of the online PAL programs can be a challenging issue, as the evaluation of online educational program effectiveness is more complicated than the already difficult process of evaluating on-campus programs. Studies concerning the effectiveness of traditional face-to-face PAL programs often focus on measuring the improvement of students’ performance, claiming that by participating in PAL programs, students generally perform better in struggling subjects (McCarthy et al. 1997; Parkinson 2009; Malm et al. 2011; Devine and Jolly 2011; Dawson et al. 2014). Similarly, Cui et al. (2014) also reveal that students who attended Bilingual PAL workshops obtained better average marks than those nonattenders. In addition, other studies use student feedback to reveal how their learning behavior changed under the positive influence of PAL programs. The impact of other factors (such as the subjects’ difficulty, students’ own learning efficacy, and selfselection bias) is yet to be comprehensively investigated to evaluate to what extent PAL programs alone can contribute to better students’ academic performance.

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Therefore, it is suggested that PAL programs are used as supplementary learning support rather than a stand-alone teaching delivery model. The evaluation of effectiveness for Internet-based PAL programs has additional challenges and difficulties. Unlike a face-to-face PAL study session, students’ attendance and participation in an Internet-based PAL program cannot be physically observed and recorded at ease. As a result, the correlation between program participation and academic performance may be misstated. Moreover, if the online PAL program focuses more on content distribution rather than teaching and learning engagement, issues such as spillovers may impact the program’s overall effectiveness evaluation as there will be difficulties in distinguishing the positive contribution resulting from content and from the learning process. It is hoped that with more technologies enabling better synchronized communication and visualization, there will be improved monitoring of students’ learning behavioral change during Internet-based PAL programs. The development of degree curricula, including teaching and assessment, will also impact the future of Internet-based PAL programs.

6

Future Development of Internet-Based PAL Programs

Although the current status of Internet-based PAL programs is far from being an effective learning support program due to the aforementioned issues, there is promising future development potential with the advancement of web communication technologies and applications. For instance, Friedrich et al. (2011) illustrate the characteristics and learning behavior of a student living in a not-so-far future year of 2020, stating that the student “can attend lectures, browse reading materials, do research, compare notes with classmates, and take exams – all from the comfort of his apartment”; all these functions are utilized through his primary digital device (PDD). The student in this story represents what the author refers to as “Generation C,” who is always “connected, communicating, content-centric, computerized, community-oriented and clicking” (Friedrich et al. 2011, p. 3). In the notso-distant future, Generation C will constitute the major cohort of service consumers, including education. At present, organizations like the Open Universities Australia offer more than 100 degrees for students to choose from; although in most cases the teaching is delivered through the Internet, students still must sit in formal exams in selected venues in order to complete subjects and degrees. What Friedrich et al. (2011) described can be considered as the next stage of virtual universities, where collaborative research and assessment can also be included in the online activities rather than just teaching content distribution. Another key feature associated with the “Generation C” cohort of students is their inseparable relationship with social media. In addition to sharing information, ideas, and things people discovered, social media platforms have also become the

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main broadcast channel by which many people learn about products and services (Anderson et al. 2011). Core elements such as community-based marketing and tailored applications are now widely used by both businesses and not-for-profit organizations to stay connected with customers to achieve higher sale expansion and customer retention. In previous studies, the issue of distraction is often observed when social media is used as a platform enabling online PAL sessions. However, it can be expected that in the future, more educational social media applications will be developed. Unlike an ordinary social media platform, PAL program-specific social media applications require more administrative and management effort to ensure that content sharing and communication are study related and meeting the required standard of teaching quality. Any form of distraction should be controlled and minimized to obtain better learning experience. Once again, this requires comprehensive training provided to leaders facilitating the Internet-based PAL programs, including how to introduce ground rules in the early stages of a program, establishing authority and clearly outlining students’ responsibilities during online PAL programs. Mutual respect between the online PAL program leaders and participants is necessary to achieve more teaching and learning outcomes from the online PAL program. Along with the development of web servers and broadband infrastructure, virtual worlds have now become widely used in education. The interactive nature and game-like characteristics of virtual worlds have strong appeal to students who are interested in online video gaming while, at the same time, capable of delivering rich and dynamic social interactions and collaborations between vast numbers of users (OECD 2011). Games such as Second Life have been used as a platform for online teaching, showing strong potential in the visualization of academic content and demonstrating its effectiveness (Burgess et al. 2010). Now with more than 200 universities establishing a presence in Second Life, a much larger scale of collaborative online teaching and learning program can be realized through the application of virtual worlds. However, other issues such as content ownership, privacy, as well as addiction must be taken into consideration. Furthermore, it has been observed that students (particularly for international students) often form their own online study group using social media platform/ software (Saw et al. 2013; Hrastinski and Aghaee 2012). For instance, the authors of this chapter have seen/engaged Chinese international students using the popular social media WeChat and have witnessed students voluntarily form online groups, often by the subjects they have enrolled in, to discuss course content, assessment requirement, and exam preparation among themselves. Quite often, some students acted the role of a “leader” in this kind of online discussion groups, frequently initialize topics, and facilitate communications. Institutions, in general, have relatively little information about what have been discussed by the students online. Recent reports (e.g., see McDonald 2014; Belot 2016) reveal a concerning situation that essay writing services (often referred to as ghost writers or essay farms) target students using social media tools; hence it calls for institutions to be

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aware of this kind of penetration in social media which causes negative impacts on students’ learning. As a possible remedy, online PAL program officially run and maintained by institution can be used to dilute this unfavorable situation, as students will expect to access information from online platforms led by trained, senior students, rather than left unmonitored in online discussions. The trained online PAL program leaders can also detect and report inappropriate communications in online discussion, so early warning and intervention can be given. To control and maintain the quality of online PAL learning and avoid issues such as digital data ownership and privacy, it is recommended that education institutions should maintain their own online PAL programs to complement their formal teaching and on-campus face-to-face PAL programs. As previously discussed, the two important criteria for successful implementation of online PAL programs are establishing an online learning community and training of online PAL leaders. If these conditions are met, the online PAL program can help enhance students’ learning, especially for those who have limited study time on-campus and need to access learning support via the Internet during self-study time. It is important for the institutions to see the benefit of providing Internetbased PAL programs, as the initial cost of technical requirements and leader training appears to be higher when compared to a face-to-face PAL program. However, if what Friedrich et al. (2011) described becomes reality in the near future, whereby online teaching and learning becomes the core function of education institutions, earlier investment in online programs can provide the institutions valuable experience and accumulation of both technical and human capital to provide effective online learning programs. To conclude, in this chapter, the philosophy of PAL programs and its current offline and online models are discussed, and the potential future development of Internet-based PAL programs is explored. Based on these discussions, successful implementation and effective use of an Internet-based PAL program require the establishment of a genuine and enduring online learning community and provision of online PAL leaders who are capable of regulating and facilitating online study that focused on peer communications and engagement. Lastly, a comprehensive framework is needed for evaluating the effectiveness of Internet-based PAL programs in improving students’ learning. The benefits of implementing an Internet-based PAL program seem less appealing at present with the identified technical and nontechnical issues such as causing distraction, lagged response times, and an inability to obtain real-time feedback, hindering the full potential of Internet-based PAL programs to be fully realized. However, with future technological advancement and evolving students’ online learning behavior, it is expected that the model can be further enhanced in order to cater the learning needs of “Generation C” students. Education institutions need to consider the associated cost and value contribution of implementing an Internetbased PAL program and must endeavor to better understand students’ attitudes with online teaching and learning in order to provide better support to their learning experience.

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Mobiles, Online Learning, and the Small Group Discovery Classroom: Reflections from South Australia

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Small Group Discovery at the University of Adelaide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Case Study 1: Environmental Impact Assessment (EIA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Case Study 2: Short Course – Indigenous Peoples and the Environment . . . . . . . . . . . 1.4 Case Study 3: Community Engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Case Study 4: Introduction to Urbanization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The use of mobile technologies is prevalent, and it is incumbent on tertiary teachers to move with the times and build curricula that use mobile themes. Yet in-depth learning and critical thinking are still key goals. This chapter explores not only the efficacy of mobile technologies in delivering online curricula but considers how the use of small group discovery techniques that utilize online tools can enhance face-to-face teaching. This chapter presents the argument that a combination of online with small group discovery delivery give students the focused attention they require, hence avoiding the overuse of mobile devices for online delivery. Careful tutoring and small group discovery together with the use of mobile devices enhances pedagogical outcomes.

M. Nursey-Bray (*) Department of Geography, Environment and Population, Faculty of Arts, University of Adelaide, Adelaide, SA, Australia e-mail: [email protected] © Her Majesty the Queen in Right of Australia 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_66

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Introduction

Working out how to ensure deep learning is becoming increasingly challenging in a world where students who wish to pursue further education but suffer from time constraints elect to study online over attending class (Hattle 2013). While many online programs are clever and are designed to facilitate learning, online platforms require mechanisms to ensure students are engaged with and use the material. Further, although online assessments may align with the course learning objectives, whether they have any pedagogical power per se is less clear. Yet, the use of mobile devices, whether they are laptops, tablets, iPads, or mobile phones, is on the rise and becoming entrenched in expectations of teaching practice: ownership rates for cell phones was at 95% in the USA, allowing unprecedented access by students to mobile learning (Dennen and Hao 2014). Unsurprisingly, e-Learning has burgeoned as a result, including the development of digital e-books and off-theshelf learning applications that encourage use of mobile devices in classrooms (Dennen and Hao 2014). Increasingly, those people teaching in higher education are under pressure to develop skills in “e” or online technologies to facilitate learning and ultimately improve graduate outcomes (see ▶ Chap. 2, Characteristics of Mobile Teaching and Learning). As early as 2000, results of a college student survey found that increasingly, students want interactive lectures and group-based activities and are, in general, nonresponsive to conventional modes of formal lecture and tutorial programs (Sander et al. 2000). In this context, e-Learning offers great capacity for building flexibility in the pace and distribution of learning (Chinyio and Morton 2006, p. 74). As such, multiple trials are taking place across the world in the development of online, hybrid, and blended learning programs (Rennie and Morrison 2012). Many mobile frameworks have evolved including the framework for the rational analysis of mobile education (FRAME) (Koole 2009), the m-learning framework (Motiwalla 2007), the mobile computersupported collaborative learning (CSCL) framework (Zurita and Nussbaum (2007), and the mobile affordances, conditions, outcomes, pedagogy, and ethics (M-COPE) framework (Dennen and Hao 2014). Ensuring that curricula are designed to be responsive to student needs is essential, as this will encourage the long-term sustainability of student learning (Castleford and Robinson 1998). However, interactive and e-delivery must be underpinned by pedagogical intent (Conole et al. 2004). As Alexander and McKenzie (1998) note, technology in and of itself does not result in improved quality or productivity of learning, what is most critical is the curriculum design of the student learning experience. Rich et al. (2000) argue this is an important gap, noting the “paucity of educational and pedagogic underpinnings of the developments made in the use of information and communications technology (ICT) to teach....” Building on this, Kirkwood and Price (2005) add: “although ICTs can enable new forms of teaching and learning to take place, they cannot ensure that effective and appropriate learning outcomes are achieved. It is not technologies but educational purposes and pedagogy that must provide the lead, with students understanding not only how to work with ICT but why it is of benefit for them to do so.” It is the

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exploitation of ICT for “rich pedagogical use” that will serve learners across multiple target groups and at various tertiary levels. Ensuring best practice in the use of educational technology can also ensure the versatility of teaching geography in higher education. Geography, in its investigation of the relationship between people and the environment, is by its very nature interdisciplinary and as such particularly suited to a suite of learning tools in curriculum delivery (Martin and Treves 2007). Indeed, as a discipline, geography “has always been considered a pioneering discipline in this regard” (Castleford and Robinson 1998, p. 377). As Lynch et al. (2008, p. 137) note of e-Learning in geography: “Using information technology effectively allows students to grapple with real-world problems, access appropriate information quickly and easily, share their ideas with fellow students. . .and construct new knowledge and meaning for themselves in a relevant interesting context.” How does this work in practice? In this context, the time is right to find ways of repositioning and reshaping disciplines such as geography and to embrace these new expectations by provision of new and innovative curriculum design (Enrique 2011; Rennie and Morrison 2012). Using a combination of peer and student evaluations, critical reflection of practice, and a basic strengths, weaknesses, opportunities, and threats (SWOT) analysis, this chapter presents the results of an evaluation of a comparative trial of students’ use of mobile devices within four different courses – (i) an environmental impact assessment course at third year; (ii) a face-to-face winter course on indigenous connection to the environment, within the discipline of geography; (iii) a postgraduate course in community engagement; and (iv) postgraduate course in urbanization. Specifically, this chapter explores how the use of small group discovery techniques, which are now embedded within the curricula structures at the University of Adelaide, can facilitate more effective use of e-Learning and mobile technologies.

1.1

Small Group Discovery at the University of Adelaide

The University of Adelaide, since 2014, has implemented the small group discovery experience. This is a teaching practice that actively tries to integrate and develop the teaching – research nexus – and delivers curricula in small groups, in ways that will enable learning or moments of “enlightenment.” This model is based on the Humboldt model, which emphasizes the importance of collaboration between students and researchers and working together in small groups to make new discoveries. Von Humboldt argued that education should be based on two principles: (i) Wissenschaft, which focuses on scholarly learning as a dynamic process of discovery, and (ii) Bildung, which asserts that education should be about the development of the individual rather than merely an employment training ground. Through its overall Beacon of Enlightenment strategy, the university invested in the centrality of small group learning. Today, all students are exposed to a small group discovery experience in at least one course, for every year of their degree.

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In the next section, four case studies of courses are discussed that were delivered solely by small group discovery mode; the use of mobile and e-Learning tools within each case study is explained followed by a reflection about how the use of mobile technologies enhanced face-to-face learning or the “small group discovery” experience.

1.2

Case Study 1: Environmental Impact Assessment (EIA)

EIA is an undergraduate course that takes students through the process of EIA via the use of case studies. This course introduces the methodology of environmental impact assessment as a vital tool for sound environmental decision-making. It introduces the concepts, methods, issues, and various stages of the EIA process. The various stages of the EIA process, such as screening, scoping, EIA document preparation, public involvement, review and assessment, monitoring and auditing, appeal rights, and decision-making, are examined. The course mainly focuses on EIA in Australia and draws on case studies from South Australia but also includes other EIA systems from other countries. The variability of EIA systems within Australia and other countries is highlighted. This course was not conducive to the traditional two lectures and one tutorial format; therefore, the course format was modified to include web components and small group instruction. A key component of the course involves trying to deepen student insight into the process via interrogation of real-life case studies and exercises. These are, in turn, constructively aligned with the assessment which requires students to simulate activities that practitioners might conceivably be asked to undertake in the field. For example, via case study instructions, students are asked to conduct a stakeholder analysis or to write a referral based on processes/activities currently in training.

1.2.1 The Trial To build the detail and simulate real experiences, this trial explored the ways in which the use of mobile technologies can be used in the classroom to develop deeper thinking, enhance critical reflection via group interaction of cases at hand, and enable on-the-spot interrogation of information supported by the teacher. Table 1 summarizes how this effort was invested. The same techniques were implemented over 6 tutorial classes of about 15 students each. Forty percent of the cohort came from the Faculty of Sciences with the remaining students from various disciplines within the Faculty of Humanities, Arts, and Social Sciences. There was roughly the same proportion of males to females. Students were then asked to reflect on the use/application of mobile devices as an aid to their learning. 1.2.2 Lessons Learned Student reflection results were surprising but created greater insights into using mobile learning activities as part of ongoing teaching practice. Firstly, it became

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Table 1 Summary of mobile device activities, environmental impact assessment Activity Develop student understanding of the EIA referral process

Ensure students become familiar with EIA documents

Students learn how to do stakeholder analysis/consultation on preset case study/ scenario

Example of interaction with mobile device Get students to access web site for referrals, read said referral documents, and discuss what/how their response would be if they were (i) a member of a community and/or (ii) federal government decision-maker Google and find an EIA in practice. Read documents, then in groups compare and contrast similarities and differences between different case study EIAs, and using a handout given on EIA flow, identify what stage of the EIA process the said examples are In groups get students to research, then allocate stakeholder roles for the scenario, then each student develops a stakeholder perspective in relation to the details of the case

clear that not all students have as much facility when accessing and using mobile devices as was first supposed. For example, a simple task, such as trying to find information about Sydney Airport EIS processes, seemed to cause concern among students. It emerged that it is not the facility with mobile media that is the issue but the capacity of students to do research that was problematic. Given they were undergraduates, the development of research capacity is yet nascent, so it put undue stress on students when they were asked to find bits of information. Further, it became clear that many students, apart from basic googling and accessing their many social media sites, were not actually familiar with the more sophisticated capacity of the various mobile devices they were using. Indeed, the following comment reflects this concern, on the topic of an in-class (during a tutorial) assessment that required use of the mobile device: “The mobile learning and online tasks were OK, but really if they are going to be worth 10% [of our grade], we should have had a lecture on how to do the online task.” Secondly, it also emerged that while all students appeared to own or have access to mobile devices, not all mobile devices were equal. Fashioning learning tasks that have pedagogical underpinnings and simultaneously engage students work well – when the device works too – but became an exercise in frustration if not. It is hard to predict how various programs, software glitches, and links that worked at first and suddenly don’t will affect in-class learning. Moreover, because these activities are in class, the frustration was witnessed by both the faculty and students in the class. In terms of active learning, the intent to use mobile devices did not meet their promise. Activities tended to have the (unintended) effect of stifling group interaction by closeting students off from each other as they each sought to engage with their devices rather than each other in the quest to obtain the information they needed to do the task. In many cases, time ran out before students could pool their information and then complete the task. Again, this mitigated against the pedagogical intent behind this trial.

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Feedback also indicated that students, in some cases, resented the use of mobile devices in class on the basis that they felt it was a “cop-out” by the lecturer, indicating laziness on his/her part, and showing a lack of willing to do “real teaching.” Set against ongoing institutional pressure for more mobile and technological-driven teaching, this was another surprising outcome – perhaps students do, after all, want traditional forms of information delivery and learning interaction. In this case, feedback highlighted that the attempt to use mobile devices in class made them feel less cherished and nurtured in their learning enterprises. Additional comments showed that a few students even felt this meant that the coordinator was not “across the subject.” In other words, students felt the coordinator was using activities designed around mobile devices to cover up the fact that the coordinator did not know the subject matter. Finally, it was not clear that deeper learning was achieved by using mobile devices in class. Surface learning, skimming over information, and trying to read dense information quickly emerged as characteristics of class behavior. Class discussions after group and mobile work highlighted that no real gain had been made via use of mobile devices in class activities. Neither was time saved since many students had to complete tasks after class they would normally have finished in class due to being distracted in using the device for information retrieval or analysis. Importantly this was also a function of the fact that students all read at different paces and further that roughly 30% of the cohort were English as second language (ESL) speakers. Cumulatively, all these factors mitigated against the potential benefits of a deliberative application of mobile device use in class to enhance pedagogical learning outcomes.

1.3

Case Study 2: Short Course – Indigenous Peoples and the Environment

The unit Indigenous peoples and the environment is a winter course, delivered in intense form over 3 weeks, at 12 h a week. It is part of the geography degree but also part of the major for Indigenous studies in the Faculty of Arts. Students tend to take this course as a “catch-up” one, to finish their degree early, or simply out of interest.

1.3.1 The Trial The course relies on an innovative application of aural and oral delivery techniques, largely delivered via mobile media. The major assessment piece is designed around a critique of a genre of Indigenous art and to explore the connection of art as an expression of connection to the environment. This assessment requires students to access, via their mobile devices, a wide range of materials about the various genres. Indigenous peoples have different ways of communicating and different world views, and this course attempts to introduce the students to some of these different cultural ways of thinking and doing. Given Indigenous cultures disseminate knowledge and learning via visual, oral, and aural means, the use of mobile and online technologies to implement learning is appropriate. Table 2 provides a summary of mobile device activities for this class.

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Table 2 Summary of mobile device activities, Indigenous peoples, and the environment Activity Develop student understanding of the history of colonization and its effect on indigenous connection to the environment

Ensure students become familiar with key narratives about indigenous peoples and the environment

Students learn how to critically analyze and think about indigenous ways of knowing and doing via interrogation of different genres of art

Example of interaction with mobile device Get students to view a series of documentaries written and directed and showing indigenous peoples experiences. Get students to access and then compare two mobile timelines, found on any mobile device (one colonial and one written by indigenous peoples) In both cases/tasks, provide a critical write-up of what they have learned Small group recount and activities based on the above Google and find narratives in practice Find indigenous examples of lessons learnt in class Write a profile of a key indigenous leader Small group recount and activities based on the above In pairs students research indigenous art genres They view different pieces on the web and bring to class examples on their mobiles and then share Write up a critical synthesis of how art reflects all the themes raised in the course. Necessitates student exposure via mobile devices and online learning of indigenous ways of knowing and doing Small group recount and activities based on the above

1.3.2 Lessons Learned In this case, the combination of targeted online technologies, used to enhance face-toface learning, worked really well. For example, the students were asked to do assessments around watching a series of videos, directed by Indigenous peoples that reflected key dimensions of the relationship between Indigenous peoples and the environment. Some films focused on colonization, others on environmental management, but all of them required students to synthesize their learning and then reproduce that in a written assessment task. While the use of technology in this instance was partly a function of time – in such a course, students and teachers are “pressed” for learning time; the use of mobile learning technologies, structured around specific learning task and outcomes, also meant that deeper learning occurred. Students also knew they would have to “share” that knowledge and learning in the small group activity afterward. Also, in this case, students were given their results and feedback for this task before they left the course. This instant feedback was appreciated by students, one of whom noted in the evaluations: “Knowing how I was going from my marks for the film tasks helped alot to work out what to do for the rest of the course assessments” and another student reflection statement said, “It motivated me to read more articles so I could try do better next time.”

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Implementation of this activity also provided useful insights into how to create learning without conventional lecture-student delivery. For example, another assessed activity asked students to compare two historical timelines on the web – one a history of Australia written by non-Indigenous peoples and another a timeline of Australia written by Indigenous groups. Previously, this information had been delivered in lecture form. Analysis of the ways in which students approached this task showed that they learned a lot from it and that it provided an excellent springboard for group discussion afterward. Student comments, such as “I had never thought about this before” or “I really liked the timeline exercise it opened my eyes,” reflect this learning. Class size also emerged as an important factor; as this was a winter course, the student cohort was also smaller. The smaller class size was an advantage to mobile delivery and use of the technology, as it helped develop an intimacy and familiarity with each other that built trust and enabled ongoing and fruitful use of the technologies. This has implications for use of mobile technologies in other courses, where structuring activities within certain class sizes will be useful. Finally, the use of mobile technologies, specifically oral/aural means, meant that students felt they were also gaining real insights into how Indigenous peoples communicate – which is primarily via the use of oral, online, and aural means. This was constructed as an explicit message within the course, and the application of mobile learning facilitated the storytelling characteristics that often dominate Indigenous learning styles and ways of knowing. In this case, application of mobile technologies for learning crated some potential to deliver decolonized curricula in appropriate ways.

1.4

Case Study 3: Community Engagement

Community engagement is a postgraduate course taught as part of a master’s degree in Environmental Policy and Management (MEPM) and the Masters of Planning (MPL). Taught within both of these degrees, the course usually attracts a cohort between 20 and 30 students, most of whom have prior or ongoing work experience, often in government. They conventionally are mature-aged students and at least 30% of the students are international. Thus, the class is often diverse. The course itself aims to teach students the theory and then practice of community engagement. Assessment is constructed around tasks that test students on their ability to apply and construct community engagement principles in practice.

1.4.1 The Trial Due to the diverse cultural nature of this class and the reality that many students are also working at the same time, mobile learning, using IT in class as well as constructing online tasks, was implemented. In the first case, to build motivation and understanding of the differences in community engagement in different cultures, a series of exercises were delivered throughout the course. Students were asked to break into groups and together google information on a series of questions around

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community engagement. Students were also instructed to view various YouTube clips (in class) of community engagement in practice and then reconvened in whole group to discuss their varying views on the different experiences they had viewed. The second element introduced into this class was the use of Articulate Storyline to facilitate a week of online learning. For this exercise, Articulate content was prepared beforehand and then uploaded in a week and necessitated students going online to go through the activities within it. This technique was employed to substitute for an entire week worth of face-to-face learning and instruction, with Articulate enabling students to (i) watch an online lecture, (ii) access various links/ clips, and (iii) complete exercises. 10% weighting of the total 100% was allocated to this assessment.

1.4.2 Lessons Learned The experience of combining mobile learning with online learning in the same course was instructive. Overall, students enjoyed undertaking the in-class mobile learning. Given the cultural diversity of the group, this aspect of the course not only enabled them to apply their learning within their own cultural contexts but also enabled a sharing of cultures and information that would have been difficult to achieve from lecture-type delivery alone. It also enabled a two-way interaction where students taught the instructor about new areas. Resoundingly, however, the online week using Articulate was a failure. Student feedback shows that they did not enjoy the experience and that, as it was timed for the week following mid-semester break (a 2-week period), it created disruption to class flow and cohesion. Two students simply refused to do the work, despite the fact it was worth 10% of their grade. Students who did complete the task nonetheless did not provide the level of detail or analysis that was expected. This is perhaps partly because student energy went into learning a new program, rather than focusing their learning on the content and assessment task itself. Student feedback also highlighted a preference for doing a field trip (even if self-directed) rather than the Articulate exercise. Further analysis indicates that the nature of the subject is relevant when considering how and when to use mobile learning and online-teaching techniques. In this case, where mobile in-class IT exercises help enhance learning, the online element was not suited to the subject matter. This experience highlighted not only the necessity of trialing different techniques in different courses but also the importance of ensuring one doesn’t make assumptions about the universal efficacy of mobile and online techniques unless they are tailored properly to content and the student cohort in each case.

1.5

Case Study 4: Introduction to Urbanization

Introduction to urbanization is another postgraduate course taught as part of the master’s degree in Environmental Policy and Management (MEPM) and the Masters of Planning (MPL). The course usually attracts a cohort of about 20 students, and most of these students are Chinese. Many have had prior or ongoing work

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experience, often in government. The course is constructed in three parts: (i) definitions and history of urbanization, (ii) drivers and impacts of urbanization, and (iii) responses to build sustainable urban regions. Assessment is constructed via a series of online activities (40% of their grade), a verbal presentation about an aspect of urbanization (30%), and a comparative impacts report (30%).

1.5.1 The Trial The second time this course was delivered, we tried implementing 40% of its content via online interactive mode. To do this, a series of weekly exercises were created on an online Blackboard platform called Canvas, and students were required to view all the links, stories, readings, and videos online and then create an e-portfolio of the answers. They then submitted all answers for the 5 weeks in one e-portfolio which was then assessed. In this part of the course, we deliberately aligned assessment with the online tasks, which were in turn linked to the key learning outcomes. The aim of consolidating content via online learning was to enable international students, enrolled in other online master’s, an additional option for taking this course. It was also designed to give students additional flexibility in attending class, so they could focus on developing in depth answers to the exercises and hence enhance their learning. The online content was supplemented by a 1-h, small group discovery class that explored in greater depth certain concepts in the class overall. 1.5.2 Lessons Learned The experience of combining online learning with small group discovery techniques was instructive. An analysis of the student evaluations showed that overall, students enjoyed undertaking the in-class learning and seemed to enjoy the online learning at the time. However, upon comparative analysis of the grades within the e-portfolios (versus similar but not online portfolio from the year before), it became clear that a number of the students, largely due to ESL issues, had misunderstood the assigned tasks and further had made only desultory attempts to answer them. For example, where it was expected, students would write an answer of 3–4 paragraphs, they might write one, and answers were brief, often in note form, and did not reflect the deeper learning that a representative answer from similar assessment from the year before had done. Linguistic expression moreover was often poor. Further, more often than not, information that was presented was rudimentary and clearly reflected a basic paraphrasing or sometimes cut and paste direct from the web. As such the web was used as a tool to get information, but the information itself was not used in any meaningful way. Another lesson lay in the fact that in constructing the course that way, students did not avail themselves of the readings provided unless absolutely instructed to do so. As such, in developing their assessments, they did not go to much effort to provide in-depth understanding of the concepts and learning aims, backed up by literature- or evidence-based case studies. A pattern emerged where it appeared that where tasks were constructed in web form, that students would only do what was asked and no more; hence reference to additional literature was not, from their perspective, needed. This had implications for later assessments – because students

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were not in the habit of reading or using literature, they did not then engage with the literature as they needed for later tasks. Overall, this weakened the quality of the overall assessments, which collectively were much lower in grade levels than the year before, despite the class being very similar in its social and cultural characteristics. Another insight from this course is that the use of online processes affected time management. Initially this course was structured as a 3-hour course, but in recognition of the fact that students had to undertake the online component, the face-to-face sessions were shortened to 2 h. However, on reflection, this was a mistake. The 2-hour time period was not enough to get through all the information needed and additionally guide the students through the online tasks – and teacher expectations of it. Future courses will revert to the 3-hour time period and cover in depth the requirements for the online task. In sum, in this case, while small group face-to-face activities enhanced learning, the online component let many students down: the online element did not offer the opportunity for the in-depth learning that the small group discovery experience is meant to develop. This is perhaps due to the types of tasks set rather than being a function of tasks being online, and future attempts to deliver this course will try new ways of delivering online content.

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Future Directions

So where to go from here? Creating conditions that enable versatility in teaching practice is a key process; the combination of small group discovery experience with online methods is one way forward in creating pathways to the implementation of e-Learning. However, lessons from these courses highlight that some important reform is needed in the use of mobile devices to enhance learning (Graham and McNeil 1999). Firstly, whether accessing mobile devices in class, encouraging mobile learning from mobile devices that is then shared in class, or using online assessments and interactions, students need to be taught how to do the exercises from a technological as well as a learning point of view. As one student (ironically) noted in a written evaluation: “If you are going to weight the courses so much towards online, we need face to face classes telling us how to do it!” It is thus suggested that future iterations of any courses like this also embed within them specific sessions that focus on online skills development as well as content delivery. Further, it is suggested that some time is dedicated to working face to face with students and uploading online examples of what is considered an excellent (and conversely a bad/fail answer) so they can understand what teacher expectations are. Second, it is necessary to find ways to develop interest and deep interaction between staff and students. The use of small group discovery techniques certainly helped to frame an efficient process for doing this overall. However, using online activities can create distance. There needs to be harmonious rather than frustrated use of technology to do exercises, especially where those exercises are assessed. One

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way of doing this is to work with the students at the beginning of each course to undertake a skills audit and also gain an understanding of how each student understands and is responsive to which type of mobile and online learning techniques. In this way, teachers will become better about to develop curricula and exercises tailored to each student cohort, their respective skills levels, and cultural interests. Third, teachers need to talk students through why they are using these technologies and for what purpose. This will help students understand that in fact such teachers are attempting to exercise innovation and need students help in making it work. For example, in this case, we started to formally articulate what the small group discovery model was and explained why, in each case, these technologies and online tools were being used. This is important also for students to understand that teachers are not using online tools to avoid what they may consider “proper” teaching. Developing mobile and online teaching and doing it well takes as much effort as teaching face to face, in some cases more, and it is important students know this, especially as they now, in most countries, pay a lot for the courses they take. This will also enhance group interaction (▶ Chap. 15, “Framework for Design of Mobile Learning Strategies”) and assert the utility of models for mobile learning that can be built to assist building reforms. Moreover, reforms can be tailored to selfdirected learning (▶ Chap. 13, “Design Considerations for Mobile Learning”). Further, while the use of mobile technologies can in theory democratize knowledge dissemination and learning, in practice this is not always the case. Indeed, it creates uncertainty in that students do not always feel confident that they are accessing the “correct” type of knowledge, yet simultaneously universities are no longer the only “holders” of knowledge. Hence, they not always seen as legitimate purveyors of it; there can also concurrently exist a reticence to consult the lecturer or course support person for advice. Finally, given the differential skills and abilities of student cohorts, learning and assessment tasks need to have boundaries; lecturers must manage expectations. Deeper learning can also be found in many other forms of delivery, and the use of mobile devices for deeper learning is more applicable to independent learning tasks, done out of the classroom in students’ own time. It is important to resist the temptation to overuse mobile devices. Further, as Alexander (2006) points out, the ongoing pressure to build technology into teaching also requires teachers to build their own technological capacities – this is a task that requires time and, on top of the effort already invested in curriculum development, should be supported and not ignored or belittled: “teachers need assistance to be effective at integrating mobile learning, and assistance involves not only learning how to operate the devices but also . . .plan mobile learning activities” (Dennen and Hao 2014, p. 399). Induction for both staff and students is an important step in the learning process and should be built in to the curricula in its own right. Nonetheless, the use of mobile devices and online platforms to enable students to develop their skills while also teaching in small groups and face-to-face has the potential to build interdisciplinarity and reshape discipline-based courses in productive ways (Sharpe and Beetham 2010; Whalley et al. 2011). As Cranford-Wesley and

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Kshama Pandey and Neetu Singh note, it is also important to develop multiple pathways in mobile learning design. The use of mobile devices in each case allows the creation of spaces for the discipline of geography to utilize the best that online technologies can offer. In particular, their visuality encourages students to “see and feel” the subject, especially important for environmental and sustainability disciplines such as geography, and given field trips and other experiential teaching opportunities are reducing with tighter fiscal conditions is an added bonus. Indeed a “self-paced virtual working environment” is “particularly suited to geography as a discipline” (Carr but cited in Lynch et al. 2008, p. 139). In sum, the use of mobile devices to enhance learning certainly has potential particularly in developing pedagogies around self-directed and self-regulated learning (Saks and Leijin 2014; Sha et al. 2011). It can integrate digital resources with authentic learning contexts (Hwang et al. 2013). However, it must not be overused, and teachers must not expect too much of such mechanisms. The effectiveness of class mobile learning-based exercises in small groups can foster group learning, peer interaction, and a sense of class identify, thus building graduate attributes as well as group cohesion and learning. Such approaches could also help facilitate inquiry-based or problem-based learning and overcome the overreliance on devices and online platforms, thus achieving a balance between the two. Ultimately, like good writing, good teaching does not need to be swamped by detail and complex jargon. Good teaching relies on simple direct techniques to relay complex ideas, and if we can find ways of utilizing mobile and online technologies to enhance learning in simple straightforward ways, the possibilities are endless.

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Cross-References

▶ Characteristics of Mobile Teaching and Learning

References Alexander, B. 2006. Web 2.0: a new wave of innovation for teaching and learning? Educause Review 41 (2): 32–44. Alexander, S., and J. McKenzie. 1998. An evaluation of information technology projects for university learning. Canberra: Department of Employment, Education, Training and Youth Affairs, AGPS. Castleford, J., and G. Robinson. 1998. Evaluating IT-based resources for supporting learning and teaching in geography: Some case studies. Journal of Geography in Higher Education 22 (3): 375–381. Chinyio, Ezekiel, and Nick Morton. 2006. The effectiveness of e-learning. Architectural Engineering and Design Management 2: 73–86. Conole, Grainne, Martin Dyke, and Jane Seale. 2004. Mapping pedagogy and tools for effective learning design. Computers & Education 43 (1–2): 17–33. Dennen, Vanessa, and Shunag Hao. 2014. Intentionally mobile pedagogy: The M-COPE framework for mobile learning in higher education. Technology, Pedagogy and Education 23 (3): 397–419.

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Enrique, Judith Guevarra. 2011. Tug-o-where: Situating mobilities of learning (t) here. Learning, Media and Technology 36 (1): 39–53. Graham, David, and Jane McNeil. 1999. Using the internet as part of directed learning in social geography: Developing web pages as an introduction to local social geography. Journal of Geography in Higher Education 23 (2): 181–194. Hattie, J. 2013. Visible learning: A synthesis of 800 meta-analyses relating to achievement. London: Routledge. Hwang, Gwo Jen, Po Han Wu, Ya. Yen Zhunag, and Yeuh Min Huang. 2013. Effects of the inquiry based mobile students. Interactive Learning Environment 21 (4): 338–354. Kirkwood, Aidan, and Linda Price. 2005. Learners and learning in the twenty-first century: What do we know about students’ attitudes towards and experiences of information and communication technologies that will help us design courses? Studies in Higher Education 30 (3): 257–274. Koole, M.L. 2009. A model for framing mobile learning. In Mobile learning: Transforming the delivery of education and training, ed. M. Ally, 25–47. Athabasca: Lawrence Endhaum Associates. Lynch, Kenneth, Bob Bednarz, James Boxail, Lex Chalmers, Derek France, and Julie Kesby. 2008. E-learning for geography’s teaching and learning spaces. Journal of Teaching Geography in Higher Education 32 (1): 135–149. Martin, David, and Richard Treves. 2007. Embedding e-learning in geographical practice. British Journal of Educational Technology 38 (5): 773–783. Motiwalla, L. 2007. Mobile learning: A framework and evaluation. Computers & Education 49: 581–596. Rennie, F., and T. Morrison. 2012. e-learning and social networking handbook: Resources for higher education. New York: Routledge. Rich, D.C., A.J. Pitman, and M.V. Gosper. 2000. Integrated IT-based geography teaching and learning: A Macquarie University case study. Journal of Geography in Higher Education 24 (1): 116–122. Saks, K., and A. Leijen. 2014. Distinguishing self-directed and self-regulated learning and measuring them in the e-learning context. Procedia – Social and Behavioral Sciences 112 (7): 190–198. Sander, P., K. Stevenson, M. King, and D. Coates. 2000. University students expectations of teaching. Studies in Higher Education 25: 309–323. Sha, Li., C.-K. Looi, Wenli Chen, and Bao Hai Zhang. 2011. Understanding mobile learning from perspective of self-regulated learning. Journal of Computer Assisted Learning 28: 366–378. Sharpe, Rona, and Helen Beetham. 2010. Rethinking learning for the digital age: How learners shape their own experiences. London: Routledge. Whalley, Brian, Angharad Saunders, Robin Lewis, Michaela Buenemann, and Paul Sutton. 2011. Curriculum development: Producing geographers for the 21st century. Journal of Geography in Higher Education 35 (3): 379–393. Zurita, G., and M. Nussbaum. 2007. A conceptual framework based on activity theory for mobile CSCL. British Journal of Educational Technology 38: 213–235.

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Mobile Learning in Foreign Language Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Gamification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Gamification Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Gamification in Teaching Languages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Language Learning Game . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Duolingo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 LingoBee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The learning process can be improved through the incorporation of evolving information and communication technologies. But it is not enough to use cuttingedge technology in teaching. The focus must be in promoting the development of skills that traditional teaching cannot adequately address. In this way, mobile devices, particularly smartphones and tablets, present exciting opportunities. These devices, largely used by students, allow access to information in a ubiquitous way – anytime, anywhere. This ubiquity, aligned with other mobile learning features – such as high memory capacity, built-in video cameras, voice recording capabilities, and geolocation capabilities, among others – addresses several I. Rego de Andrade (*) Education Management, Serviço Nacional de Aprendizagem Industrial (SENAI-SP), São Paulo, SP, Brazil Campinas State University (Unicamp) – Campinas, São Paulo, SP, Brazil e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_76

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foreign language learning needs, in the modality known as mobile-assisted language learning. Recently, games have been studied in a systematic way, where game elements are extracted and applied in different situations. In educational context, game strategies – known as gamification – are often used to enrich the student experience, fueling motivation and promoting meaningful learning. To achieve the best results, it is important for the teacher, or other learning experience designer, to be knowledgeable of gamification elements and their application when creating mobile-assisted language learning activities. This chapter highlights the main elements of gamification that can be exploited for teaching languages, and it examines three experiences of language teaching through mobile learning. It also analyzes how these experiences exploit gamification strategies to promote student engagement in the learning process. Understanding how gamification strategies improve student learning in these experiences is important in the advancement of pedagogical and technological research of mobile-assisted language learning.

1

Introduction

Learning a foreign language is increasingly in demand today as new technologies blur geographical boundaries and make access to information and people from remote locations possible. Even with the advanced development of tools that help in the translation of texts, such as Skype’s simultaneous translation tool (Skype Translator) or Google’s voice translator application, intrinsic human characteristics, such as the ability to critically analyze information, to grasp humor and irony, and to identify implicit meanings in a message, are necessary to extract meaning from language. While translation tools help, they do not replace the human need to learn to communicate in other languages. Mobile device technology can be a great ally if it is used to promote not only a more meaningful language learning experience for students but also to increase methodological efficiency by allowing access to education anywhere and at anytime. The mobile-assisted language learning (MALL) uses mobile devices to teach foreign languages. In this modality, the technology resources of mobile devices – such as video cameras, voice recorders, and Internet browsers – are exploited in individual or collaborative activities. Among the pedagogical resources used, game strategies – or gamification – are quite frequently employed to engage and motivate students. What is gamification? What elements can be exploited in language learning activities for mobile learning? How does gamification improve the learning of a foreign language? Understanding the answers to these questions is paramount to designing motivational activities and, at the same time, promoting meaningful learning of the language. In section 2 of this chapter, the concept of mobile language learning and the main features of language learning through this modality of education will be briefly discussed. Section 3 broaches gamification and the main

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elements explored in language teaching. Section 4 presents an analysis of the use of gamification in three foreign language teaching applications and evaluates these three uses of gamification based on effective components in gaming design summarized in Sect. 3. Section 5 is a conclusion, comprising a reflection of findings and a proposal for future studies.

2

Mobile Learning

Mobile learning (or m-learning) is a new teaching modality that follows the student’s current learning needs. This student is constantly moving from one place to another, and he is accompanied by mobile devices, such as smartphones and tablets, presenting opportunities to offer him educational activities so he can keep studying outside the formal classroom. It is possible to find different definitions of mobile learning in the academic literature. Some of the most comprehensive point of view about m-learning considers it a new educational paradigm based on the use of mobile technologies. The time and space parameters for learning are also changed, since it is possible to learn “anywhere and anytime” (Roschelle 2003; Trifonova and Ronchetti 2003; Moura 2010). Despite ease of access, it is important to consider that mobile learning efficiency depends on the development of teaching strategies appropriate to the learner, considering her learning style, background, and context (e.g., considering where she lives – socially and geographically). Following the current trend of fusion between classroom and distance learning, Zhang (2014) points out that the special characteristics of mobile devices and technologies should be taken into consideration before adopting mobile learning into any educational project. The author suggests that, rather than replacing classroom learning, mobile learning should be seen as a complement to traditional teaching. In the academic literature, the definition of mobile learning has evolved through three main phases: the first focused on the mobile device; the second turned the focus to learning outside the classroom; the third highlights the mobility of the student (Moura 2010). The main characteristics that define the last and current phase are the ability to continue learning beyond the time and geographical limits of formal education, the ability to use the student’s context to aid learning, and the ability to collaborate between peers. Students are no longer passive recipients of learning content, but instead exercise autonomy, creating and editing content and communicating with teachers and peers. Despite advances in mobile technology and in educational research, mobile learning initiatives do not always achieve this third phase – where the mobility of the student is focused – satisfactorily. McCombs (2010, cited Zhang 2014) argues that technical limitations and a lack of understanding of student needs by mobile learning project developers are still impediments to implementing true “anytime, anywhere” learning. Some technological barriers, such as lack of access to highspeed Internet on mobile devices, also hamper implementation. Even so, the sophistication and creativity of new applications is constantly improving, bringing real-

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world mobile learning closer to what researchers believe to be the ideal state of this modality, which is contextualized, collaborative, and ubiquitous. Among the relevant characteristics of mobile learning, learner mobility is considered by many authors (Peng 2009; Moura 2010; Sharples 2006; Traxler 2005) as its main feature. Other relevant features include the presence of a mobile technology device that, among various features, allows access to the Internet, access and ability to record audio and video, and file storage. Currently the most widely used devices are smartphones and tablets, but the early mobile learning research focused on PDAs (personal digital assistant), voice recorders, MP3 players, and regular mobile phones. Planning and developing m-learning activities may be challenging, but worth the effort as resources and learning activities can be shared anywhere and at anytime, allowing wider access to education and reaching remote locations and those with very limited financial resources. However, as explained below, technology and pedagogy both need to evolve so that mobile learning initiatives become more accessible and effective.

2.1

Mobile Learning in Foreign Language Learning

Learning a language is a long and continuous process. To encourage faster and more effective learning, it is necessary to expand the time and space limits of classroom, enabling the student to have contact with the foreign language at different moments of their daily life. Foreign language learning can work more effectively if the student could access learning content along his day. Therefore, as mentioned earlier, one of the areas of teaching that can largely benefit from mobile learning is foreign language learning. Some studies (KukulskaHulme and Shield 2008) demonstrate that mobility of the learner and mobile devices can provide great benefits for language learning. This form of education has been used in different contexts and with different teaching approaches, from the translation method to teaching based on experience. This is positive, since greater access to educational activities leads to higher benefits to learners of foreign languages. Some researchers call this area of knowledge MALL: mobile-assisted language learning (Kukulska-Hulme and Shield 2008). MALL offerings have changed as mobile device technologies have evolved. Initially, offerings focused on the use of voice recorders and of Palmtops (PDA). With the advent and adoption of the mobile phone, new offerings explored SMS (short message service or text message). As mobile phones gained more features and connection capabilities, MALL initiatives evolved to include native applications (installed on the device). Today, smartphones allow the use of native applications with Internet browsers, geolocators, video cameras, and audio recorders together in the same application, along with other features. However, even with many different technological features, many mobile language learning offerings still use very few technological resources. Translation and vocabulary exercises are the most widely available. Few offerings promoting collaboration, context exploration, and ubiquity (access anytime and anywhere) have

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been developed. In general, current offerings merely migrate the dynamics of traditional classroom teaching into mobile devices. Learner mobility and mobile devices can promote a more engaging and meaningful language learning experience. However, to advance foreign language mobile learning, teaching strategies that exploit technological resources and engage learners through experiences that are meaningful in their own context of use need to be developed. Game strategies can help. The following section is a reflection on the use of gamification to the teaching of foreign languages. The main elements of gamification will be presented, and three examples that exploit such resources for teaching languages will be analyzed.

3

Gamification

Games have been a part of human culture since ancient times. There are records of games being played as far back as 3000 BCE (Historic Games 2014). In addition to the playful and entertainment aspects, games can also be used to transmit knowledge from generation to generation. Therefore, playing can be a way of teaching and learning. Language, logic, motor coordination, spatial distribution, and a myriad of other cognitive skills can be taught and learned through games like chess, RPG (roleplaying game), video games, and others. In many cases, learning takes place intuitively and spontaneously while playing. Learning is not always the main goal of a game, but the result of engaging in the game’s tasks, of repetition, of engaging in trial and error, and of overcoming challenges. However, for educational purposes, it is possible to propose goals and to use gaming strategies to make learning challenging and engaging. Considering the ability to influence player behavior, Werbach (2014) proposes the use of the theories of persuasive design to show how a gamified activity can influence motivation and user ability. Building on Fogg’s theory (2009, cited Werbach 2014), which considers that motivation and ability lay in a continuum, the author considers it necessary to identify where the user is on this continuum to develop a trigger: “Game-like experiences can promote both motivation (by making activities feel more engaging) and ability (by promoting learning, achievement, and feelings of confidence)” (Werbach 2014). Even though, it is also necessary to consider that what motivates not always educates (Domínguez et al. 2013). When seeking a more critical orientation, it is necessary to reflect about these game strategies. To promote interventions that cause behavioral change, Werbach (2014) suggests that gamification should be seen as a process. Therefore, it is not necessary to classify whether a task is gamified or not nor to determine the degree of gamification of tasks. According to the author, to build this continuum leads designers to strive to enhance the strategies of the games. From another perspective, Kapp (2012) believes that gamification is the use of elements traditionally thought of as for a game or “fun” to promote learning, engagement, and problem-solving skill. In his book The Gamification of Learning

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and Instruction: Game-based Methods and Strategies for Training and Education, Kapp defines gamification and its components through an educational lens and presents strategies to bring gamification to the educational context, whether in the classroom or in a virtual learning environment. According to the author, “Game-based techniques, or gamification, when employed properly, have the power to engage, inform, and educate” (Kapp 2012). According to the author, the purpose of gamification in education is to create a system where participants engage in an abstract challenge, defined by rules, interactivity, and feedback resulting in a quantifiable product, ideally generating an emotional reaction. Kapp (2012) presents some game aspects that are essential for gamification in learning. Among them, the most relevant are: • Mechanics: with a schematic of points, rewards, and stages to be overcome. • Aesthetics: with great influence on the player’s engagement and her desire to participate in this experience. • Game thinking: converting an everyday experience into an activity that has elements of competition, cooperation, and storytelling. In the author’s view, these elements seek to promote engagement, which is essential for successful learning through a gamified experience. In the following section, these and other relevant elements necessary to create a gamified dynamic that positively impacts learning will be discussed.

3.1

Gamification Elements

There are a few ways to categorize gamification elements. One of the most widely used is to group them into three categories: dynamics, mechanics, and components (Werbach and Hunter 2012). Dynamics represent the highest level of abstraction of a game: constraints, emotions, narrative, progression, and relationships. Mechanics are basic processes leading to a sequence of actions that generate the player’s engagement: challenge, chance, competition, cooperation, feedback, resource acquisition, rewards, transactions, turns, and win states. Finally, components are the most easily observable elements by the player. The 15 most important pointed out by authors Werbach and Hunter (2012) are achievements, avatars, badges, boss fights, collections, combat, content unlocking, gifting, leaderboards, levels, points, quests, social graphs, teams, and virtual goods. This section will not exhaust all gamification elements, but will rather focus on those considered most relevant to the context of this discussion.

3.1.1 Goals When it comes to learning experiences, the definition of the learning objectives is the starting point. Without them, there is a risk of losing track along the route, resulting in a playful and motivating experience without concrete student learning results. In a game, victory is the goal. Reaching it means the end of the game. Therefore, it is

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customary to establish intermediate goals that lead to this ultimate goal. Thus, the student is motivated to move ahead and get feedback as she develops skills and overcomes challenges.

3.1.2 Mechanics Mechanics are systematized in rules and rules are the essence of a game. They dictate how the game will work, when it will end, and how the stated objectives will be achieved. There are different types of rules, grouped by Salen and Zimmerman (2004) as: operational rules (describing how the game is played), constitutive or foundational rules (formal structure that supports the functionality of the game), implicit rules or behavior rules (governing the social contract between two and more players; in other words, etiquette), and instructional rules (governing the learning process through the game). So, setting rules, it is an important step to define the game mechanics. 3.1.3 Aesthetics Aesthetics are of great importance in the participant’s engagement: “Appropriate and aligned visuals, attention to detail, simple contrasts, or colorful backdrops create an immersive environment that contribute to the overall game experience” (Kapp 2012). Consistency is the main factor to be considered in the aesthetics of a game. Therefore, it is very important to consider the audience for whom it is intended, taking care, for example, to not use childish aesthetics in a game designed for adults. 3.1.4 Game Thinking Game thinking converts everyday experiences, whether professional or educational, into more playful and dynamic activities. Werbach and Hunter (2012) define game thinking as a way to use all available resources to create an engaging experience that motivates the desired behaviors. Bringing this concept into education, it is important to observe teaching situations and identify opportunities to enrich them with the resources of gamification. This demands that the educator or designer get to know the repertoire of gamification strategies and elements that are available and critically look at teaching and learning experiences, identifying ways to make them more engaging and meaningful to the learner. 3.1.5 Collaboration There are several gamified learning experiences where students study and play by themselves, usually in a virtual environment. However, when thinking about mobile language learning activities, it should be considered that collaboration is a very important element in promoting collective knowledge building. Through the exchange of experiences and mutual help among peers, students have the opportunity to become more engaged with the challenge. Group work also increases commitment, helping to reduce evasion.

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3.1.6 Reward and Competition Reward structures involve but are not limited to scores, badges, and rewards. Behind these elements are driving forces of human development: motivation and competition. Kapp (2012) believes that conflict, competition, and cooperation are inherent parts of the game: The meaning of play in the context of conflict is to become a winner while avoiding a loss at the hands of an opponent. (. . .) Competition is where opponents are ‘constrained from impeding each other and instead devote the entirety of their attentions to optimizing their own performance’. (. . .) Cooperation is the act of working with others to achieve a mutually desirable and beneficial outcome.

Even if a reward is virtual, the possibility of winning something motivates the player to continue, seeking new badges and rewards. Competition can be exploited through simple game elements such as rankings, where players can view their position compared with opponents and feel motivated to improve their performance to achieve a higher rank. This monitoring of performance itself is an important way to promote metacognitive skills in the learner, allowing him to monitor his own learning. Kapp (2012) criticizes e-learning courses and classroom instruction which generally do not provide easily traceable progress reports in the formats of leaderboards, badges, or rewards. Reward structures can be regarded as a form of feedback, allowing the student to know her position in relation to the expected performance.

3.1.7 Feedback In games, feedback is constantly given. According to Kapp (2012), the frequency and intensity of the feedback is opposed to traditional teaching. According to the author, “Games provide informational feedback. Feedback in learning or playing game is designed to evoke the correct behavior, thoughts, or actions.” The author refers to two types of feedback. The first is more informational, showing the learner the degree of success or error of his behavior, thought, or action. The second is more educational, providing information to the learner to guide her toward the right end performance. The feedback does not need to look like a simple text message stating whether the student is right or wrong. In the words of Hunicke (2009 cited Kapp 2012), attractive and motivating feedback should be tactile (giving the player the feeling that the feedback is happening on real time), inviting (making it a moment desired by the player), repeatable (can be received several times when the player achieves objectives), coherent (related to the game context), continuous (the player does not need to wait for it, happening as a natural result of the interaction), emerging (flowing naturally in the game, giving the sensation of belonging to the game environment and not interrupting or distracting the player), balanced (the player knows he or she is getting feedback and reacts based on feedback), and fresh (it is a bit surprising, containing unexpected turns; it is interesting and inviting).

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Table 1 Gamification elements for mobile language learning Goals Educational Ludic

Narrative Rules Context Operational Behavioral Constitutive Instructional

Reward Feedback structure Educational Competition Informational Cooperation Collaboration

Progression degrees Narrative Ability Motivation

Graphic aspect Aesthetics Consistency

3.1.8 Progression in Levels Progression in levels is used to achieve three objectives (Kapp 2012). The first is to assist the evolution of the game narrative, presenting new information to sustain player engagement. The second objective is related to strengthening and developing skills, focusing on the development of the same skills in the later levels of the game, but requiring more speed and making them more challenging. The third objective is that the levels serve as motivation, as small victories by the player who moves from one stage to the next. Therefore, levels in the game are used to serialize the challenge and the narrative, increasing motivation and preventing the game from becoming boring and tiring. The challenge is to combine these elements so that the game does not become too easy or too hard. 3.1.9 Storytelling It is a big challenge for gamified learning designers to take into account the student’s context. One possible way is creating a narrative or storytelling, bringing relevance and meaning to experience. The name of the game, characters, and stages and some graphic elements are usually sufficient to activate the story that will unfold in the player’s imagination. According to Kapp (2012), stories bring meaning, context, and guide action. The main elements of the narrative used to develop games are the characters, events, tension, and solution. Considering the topics presented above, the most significant gamification elements for mobile language learning are summarized in Table 1. Learning tasks that employ gamification don’t always utilize all these elements. However, it is important to know them all and make conscious decisions about which elements to use. The main objective is not to transform learning activities into full games but to enrich the student’s experiences, motivate her, and make learning more meaningful. In the following section, three mobile language learning experiences will be analyzed from the perspective of gamification, highlighting strategies and elements used.

4

Gamification in Teaching Languages

The use of gamification strategies is widely used in the classroom teaching of foreign languages and can be seen in educational materials and activities that exploit recreation and competition to engage students in language learning. Currently, some mobile learning offerings also use game strategies for the teaching of foreign

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languages. Here, three foreign language mobile learning examples will be evaluated based on the gamification components presented above.

4.1

Language Learning Game

Sultana et al. (2012) present a collaborative game proposal for foreign language learning. Named LLG (language learning game), the tool is designed to help adult learners learn a foreign language using smartphones. Learners must already have some language knowledge to participate in the game. In terms of technology, a smartphone that runs Java and has access the Internet is needed. The authors presented an example of English language teaching. The game proposes that a small group of three to five participants collaboratively create a story in English. Each participant writes a sentence and submits it to the group. The other participants may suggest spelling and grammar corrections. The original and the corrected versions of the sentence are submitted to a vote by the group, which chooses the option that seems to be the most accurate. Then, another participant writes a sentence that follows the previous one. The process repeats until all students have written a sentence, which completes a cycle. The game runs for three to four cycles. In the end, a supervisor – someone with a high command of the language – assesses the story created and suggests corrections. Finally, everyone gets a version of the full story and a virtual flashcard with the supervisor’s corrections. An important aspect of LLG is anonymity: the participants do not know who is in their group. According to the authors, this prevents people from feeling intimidated, afraid of making mistakes. The authors also point out that competition can lead to a situation where students with greater language proficiency earn rewards and student with limited knowledge of the language gain nothing. Therefore, they believe that everyone benefits in collaborative offerings, where students are encouraged to create communities of mutual assistance: “Their critical thinking skills increase and their retention of information and interest in the subject matter improves. This in turn leads to higher self-esteem in all the participants, which is the goal of LLG. It is designed in such a way that all the participants need to communicate with each other frequently” (Sultana et al. 2012). In the paper presented by the authors, the following gamification elements are identified: • Objective: to promote the self-esteem of learners of a foreign language. • Mechanics: to write sentences that compound to a story. • Collaboration: to correct other participants’ sentences, to vote on the correct sentence among the different versions presented, and to write a sentence that will continue the story. • Feedback: participants correct the sentences for spelling and grammar; a supervisor reviews the story and points out corrections that students didn’t suggest.

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In addition to receiving the final version of the story the authors point out that the best writer and the best group should be rewarded, but not to name the reward so that students can’t discover the other participants of the game. It is noted that progression levels are not displayed. The authors note that, in the pilot, teachers who accompanied the game expressed interest in implementing LLG in their courses, demonstrating that it is a complementary activity to a wider teaching curriculum. Perhaps that is why there is no concern about levels of progression in the game. Although not explicit, it is possible that the complexity of the game increases as participants gain greater knowledge of the foreign language, which can make it more challenging for the whole group. The themes for the stories are not mentioned in Sultana’s article, but the group supervisor could suggest a theme or situation for the construction of the story, for example. Competition can stimulate student engagement in the game while being complementary to collaboration. On one hand, the anonymity of participants favors freedom from judgment in relation to making mistakes, but, on the other hand, recognition from peers promotes social engagement, which is important for collaboration.

4.2

Duolingo

A free and widely available foreign language learning application, Duolingo was analyzed by Petit and Santos (2013) from the point of view of language teaching methodology and gamification. The authors point out that the application uses quite old teaching methods and modern gamification strategies at the same time. Duolingo activities are based on the translation of texts (teaching methodology dating back to the nineteenth century) and teaching grammar and vocabulary in isolation (methodology that emerged in the mid-twentieth century). Petit and Santos (2013) believe that this methodological choice is made for economic reasons, since teaching vocabulary out of context excludes the need for human mediation. When a student starts learning a new language, the application presents vocabulary translation exercises, always regarding a language that can be the learner’s native language or another available language. One exercise, for example, has a word in the source language and four images with different words for the learner to choose the correct translation. By choosing one of the words, the application plays an audio recording of the chosen word. The same type of exercise is repeated for the translation of sentences. Sometimes images are available as translation support resources, but sometimes they are not, unlike the audio feature (which is always available). Even in early lessons, exercises are presented where the learner must write the translation of words and short foreign language sentences in the reference language. The system has some flexibility for accepting more than one translation option whenever possible, and words without orthographic accents, although drawing the user’s attention when he writes without accents. In the Spanish course for Portuguese speakers, 64 different lessons were identified. The names of the lessons are always

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topics of grammar or vocabulary such as plurals or colors. The initial lesson has 18 screens with different exercises, all centered around the translation of words and short sentences. The user begins the first lesson with four hearts, called “lives.” If she misses an activity, she loses a heart. If she loses the four, she will need to redo the lesson. At the end of each lesson, she receives a few points according to her performance. Among gamification strategies, Petit and Santos (2013) highlight the system of life, points, and competition. Competition takes place when the user adds other users to their list of friends. The system will notify the user about the performance of friends, encouraging them to reach the scores obtained by them. The most prominent gamification elements in the application are: • Mechanics: the rules are clear and presented as the user advances in the game. • Aesthetics: it is very intuitive and visual resources are exploited both for teaching the language (with images related to vocabulary) and to make the user experience more pleasant. • Feedback: the user receives feedback immediately when completing an exercise. The system also gives tips when orthographic accents are not used properly or when more than one answer is possible. • Levels of progress: the 64 lessons identified in the Spanish course, for example, are grouped into levels. To advance from one level to another, not all lessons need to be completed. If the user believes he has the required knowledge for that level, he can submit to a test called a “shortcut” to validate his knowledge and advance to the next level. Among the gamification elements that are not exploited, the lack of use of the student’s context and collaboration among peers stand out. From the point of view of language learning, the lack of use of the learner’s context in the design of the activities is a very important element. It would be necessary to further investigate if a learner who completed all the lessons will be a competent speaker, able to communicate in a foreign language. Regarding collaboration, the presence of friends serves as stimulus for competition, but a form of collaboration in solving tasks was not identified.

4.3

LingoBee

Going in the opposite direction, Procter-Legg et al. (2014) propose that learning should be a social activity that occurs inside a community of learners. To explore how these factors promote language learning, the researchers conducted a study in different countries to develop and test the application LingoBee, designed to support language learning on mobile devices. LingoBee is part of the SIMOLA (Situated Mobile Language Learning) project, created through a partnership between six countries (Simola 2012). The application supports six different European languages and Japanese. It is an open source app, developed for the Android OS.

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LingoBee’s objective is to develop knowledge of vocabulary in a context. The learner creates her own virtual flashcards with the words and phrases she is learning. In each flashcard, she describes the word and can link a picture, record the pronunciation of the word, or link a web link. The application has a text-to-speech feature to help with pronunciation. These flashcards are stored in the system repository and are shared among users who can view, edit, and vote on entries. This repository has search tools that facilitate the search for specific content. The authors identify LingoBee users as social networkers, since learners construct meaning together while creating the multiple inputs used to add and edit these entries. The application also allows users to create a social profile with a username and contact information, encouraging social interaction among peers. Although not presented as a game per se, it is possible to identify gamification elements in the LingoBee application: • Objective: the proposed objective is the dominance of vocabulary in a foreign language. • Collaboration: this element is crucial to motivate the engagement of the user in the application, since, by collaborating with peers, it is possible to validate if the entries presented are correct. • Feedback: occurs through interaction with peers, comments, edits, and voting on entries in the system. • Aesthetics: in Procter-Legg’s article, it is possible to identify some screenshots of the application and verify that the design is intuitive and functional. • Context: the application explores the learners place and time. He can, for example, take a picture of an object that is in front of him and create an entry with new vocabulary in the foreign language. The application is a great example of how to exploit context for teaching languages through mobile learning. Among the gamification elements neglected, game mechanics and rewards stand out. Regarding the mechanics, rules are not displayed. Also, no reward structure is evident besides the votes of fellow learners and the level of personal satisfaction achieved in learning. The authors propose that the social context promotes learning. They argue that social networks break down the barriers between formal and informal learning and are currently becoming a path sought by students. LingoBee explores gamification elements considering current concepts of teaching foreign languages, in particular the student’s context, and peer interaction, making it an interesting mobile language learning offering.

5

Future Directions

Considering the cases presented below, it is possible to conclude that learning foreign languages can be enhanced by mobile learning and by gamification strategies. Currently, studies on teaching approaches indicate that elements such as context and collaboration are very important when learning a foreign language

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(Telles 2009; Figueiredo 2006). According to Robison (2012), learning a language is interpersonal and contextualized. So, it can be favored by the mobile game scenarios. The challenge in using gamification elements in mobile language learning is to balance gamification and learning functions (Brophy 2015) and to go beyond activities focused on the acquisition of specific elements, such as vocabulary and translation of sentences, and expand the horizons to more complex offerings considering student’s context and the different forms of collaboration among peers. Future studies can perform deeper explorations on the language learning outcomes obtained by using gamification strategies. Another possible way is to research how to use gamification resources to develop contextualized and meaningful language learning activities with the use of gamification elements. One of the trends in the convergence of technologies for education is a blended format (Johnson et al. 2014), where educational activities will take place partly in person and partly online, both through computers and through mobile devices. This will lead designers to focus not only on technology devices, but specially on teaching strategies, considering the best resources to promote learning wherever the student is. In this sense, gamification strategies will be very important to engage and motivate students in learning beyond of the institutional limits of formal education, wherever they are and whenever they want to learn.

6

Cross-References

▶ Design Considerations for Mobile Learning ▶ Mobile Technologies for Teaching and Learning

References Brophy, Keith. 2015. Gamification and Mobile teaching/learning. Characteristics of mobile teaching and learning. In Handbook of mobile teaching and learning, ed. Y. Zhang. Berlin Heidelberg: Springer. Domínguez, Adrián, Joseba Saenz-de-Navarrete, Luis de-Marcos, Luis Fernández-Sanz, Carmen Pagés, and José-Javier Martinez-Herráiz. 2013. Gamifying learning experiences: Practical implications and outcomes. Computers & Education 63: 380–392. Figueiredo, F. 2006. A aprendizagem colaborativa de línguas. Goi^ania: UFG. Historic Games. 2014. History of games timeline. http://www.historicgames.com/gamestimeline. html. Accessed 15 Dec 2014. Hunicke, R. 2009. Wildflowers: The UX of game/play. UX Week. http://vimeo.com/6984481. Johnson, L., S. Adams Becker, V. Estrada, and A. Freeman. 2014. NMC horizon report: 2014 higher education edition. In The new media consortium. Austin. Kapp, Karl M. 2012. The gamification of learning and instruction: Game-based methods and strategies for training and education. San Francisco: Pfeiffer. Kukulska-Hulme, Agnes, and Lesley Shield. 2008. An overview of mobile assisted language learning: From content delivery to supported collaboration and interaction. ReCALL European Association for Computer Assisted Language Learning 20 (3): 271–289. Mccombs, S. W. 2010. Mobile learning: An analysis of student preferences and perceptions surrounding podcasting. United States – Texas, University of Houston. Ed.D.

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Moura, Adelina Maria Carreiro. 2010. Apropriação do Telemóvel como Ferramenta de Mediação em Mobile Learning: Estudos de Caso em Contexto Educativo. RepositóriUM. http://hdl. handle.net/1822/13183. Accessed 10 Oct 2014. Peng, H., et al. 2009. Ubiquitous knowledge construction: mobile learning re-defined and a conceptual framework. Innovations in Education and Teaching International 46(2): 171–183. Petit, Thomas, Santos, Gilberto Lacerda. 2013. A aprendizagem não formal da língua estrangeira usando o smartphone: por quê voltamos a metodologias do século XIX? Simpósio Hipertexto e Tecnologias na Educação. http://nehte.com.br/simposio/anais/simposio2013.html Accessed 21 Nov 2014. Procter-Legg, Emma, Annamaria Cacchione, Sobah Abbas Petersen, and Marcus Winter. 2014. Mobile language learners as social networkers: A study of Mobile language learners’ use of LingoBee. Digital Systems for Open Access to Formal and Informal Learning 1: 121–137. https://doi.org/10.1007/978-3-319-02264-2. Robison, David. 2012. Learning on location with AMI: The potentials and danges of mobile gaming for language learning. In Left to my own devices: Learner autonomy and mobile-assisted language learning, ed. Javier E. Díaz-Vera. Bingley: Emerald. Roschelle, J. 2003. Keynote paper: Unlocking the learning value of wireless mobile devices. Journal of Computer Assisted Learning 19 (3): 260–272. Salen, K., and E. Zimmerman. 2004. Rules of play: Games design fundamentals. Cambridge: MIT Press. Sharples, M. Ed. 2006. Big issues in mobile learning (Report of a workshop by the Kaleidoscope Network of Excellence Mobile Learning Initiative, pp. 14–19). Nottingham, UK: Learning Sciences Research Institute. Simola. 2012. About SIMOLA. http://itrg.brighton.ac.uk/simola.org/. Accessed 11 Dec 2014. Sultana, R., M. Feisst, and A. Christ. 2012. Collaborative language learning game as a device independent application. Towards Learning and Instruction in Web 3.0: Advances in Cognitive and Educational Psychology 1: 73–88. https://doi.org/10.1007/978-1-4614-1539-8. Telles, J. 2009. Teletandem: Um contexto virtual, autoˆnomo e colaborativo para aprendizagem de línguas estrangeiras no século XXI. Campinas: Pontes Editores. Traxler, J. 2005. Defining mobile learning. Paper presented at the IADIS International Conference Mobile Learning 2005, Qawra, Malta. Trifonova, A.; Ronchetti, M. 2003. A general architecture for mobile learning. Technical Report. https://www.researchgate.net/publication/2929880_A_General_Architecture_For_Mlearning. Werbach, Kevin. 2014. (Re)defining gamification: A process approach. PERSUASIVE 1: 266–272. https://doi.org/10.1007/978-3-319-07127-5. Werbach, Kevin, and Dan Hunter. 2012. For the win: How game thinking can revolutionize your business. Philadelphia: Wharton Digital Press. 148p. Zhang, Yu. 2014. Characteristics of mobile teaching and learning. In Handbook of Mobile teaching and learning, ed. Y. Zhang. Berlin Heidelberg: Springer.

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Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Service Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Social Media Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Digital Badges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Pinterest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Popplet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Blogs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Twitter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 YouTube . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Instagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 Snapchat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 Emaze . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Pros and Cons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Dos and Don’ts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

With the increasing popularity of smartphones, tablets, and laptops among college students, higher education institutions are beginning to implement these devices into the college curriculum. The academic community has realized that using mobile devices may encourage and increase academic intelligence. This troika relationship between the student, the mobile device, and the course is a form of m-learning, a method of teaching that is being practiced with increased M. Sass (*) Communication Department, College of Southern Idaho, Twin Falls, ID, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_86

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frequency throughout national and international campuses. Sharples et al. (Mobile learning. Springer, pp 233–249, 2009) state that “exploration is essentially mobile in that it either involves physical movement or movement through conceptual space, linking experiences and concepts into new knowledge” (p. 4). Education should be exploratory to the student, kindling a desire to learn more and do more. This chapter examines the pedagogy behind m-learning and discusses the relationship of m-learning with service-learning curriculum. The challenges of m-learning are discussed, as well as the ways to successfully implement social media tools into the college classroom when a service-learning project is of focus. The purpose of this chapter is to encourage instructors to consider using a form of m-learning in the classroom in collaboration with service learning as a way to engage the student in a familiar platform.

1

Introduction

Elementary-age children to elderly adults are carrying smartphones, living a life that revolves around mobile devices. Some are talking, texting, playing games, or surfing the web. In fact, it’s unusual to see students of all ages without a phone. Aware that the popularity of such devices will increase rather than decrease, some educators have added mobile devices to their curriculum (Stowell 2015; Graham 2017). With these smartphones, tablets, and laptops overwhelmingly popular among college students, learning through these devices is being implemented into the curriculum of traditional, hybrid, and online courses. The academic community has realized that using mobile devices to encourage academic and intellectual growth may be ideal (▶ Chaps. 34, “Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts” and ▶ 15, “Framework for Design of Mobile Learning Strategies”). This troika relationship between the student, the mobile device, and the course is a form of m-learning, a method of teaching that is being practiced more and more throughout national and international campuses. As Sharples et al. (2009) acknowledged, “exploration is essentially mobile in that it either involves physical movement or movement through conceptual space, linking experiences and concepts into new knowledge” (p. 4). The MoLeNET program defines mobile learning as “the exploitation of ubiquitous handheld technologies, together with wireless and mobile phone networks, to facilitate, support, enhance and extend the reach of teaching and learning” (MoLeNET 2014). They define mobile devices as “mobile phones, smartphones, PDAs, MP3/MP4 players (e.g., iPods), handheld gaming devices (e.g., Sony PSP, Nintendo DS), Ultramobile PCs (UMPCs), mini notebooks or netbooks, handheld GPS or voting devices and specialist portable technologies used in science labs, engineering workshops or for environmental or agricultural study” (MoLeNET 2014). This definition provides a beginning platform to describe what devices are considered mobile, but with such a rapid-changing technology industry, these

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devices will only improve and become more developed as with the websites and apps they are in sync with. This chapter examines the pedagogy behind m-learning and how it works in collaboration with service-learning curriculum. The challenges of m-learning are discussed, as well as the ways to successfully implement social media tools into the college classroom or a service-learning project. The purpose of this chapter is to encourage instructors to consider using a form of m-learning in the classroom in collaboration with a service-learning curriculum as a way to engage the student in a platform they are comfortable with.

2

Literature Review

One of the challenges of m-learning is compelling the student to be responsible for his/her learning experience. When a course instructor requires the use of mobile devices, they are considered more a “guide” than a lecturer. Educational content is still being transferred from instructor to student, but the method on how to do that is being reconfigured. This structure can be uncomfortable or unfamiliar to students due to their lack of exposure to student-centered learning in a much dominated teacher-centered world. When a course is online, students must self-regulate. Self-regulation is defined as “a student who is regulating his or her learning is able to set task-related, reasonable goals, take responsibility for his or her learning, and maintain motivation” (Heikkilä 2006, p. 101). Self-regulation pinpoints the need for the student to take responsibility of his/her own learning. It puts them in the driver seat, allowing them to have an interactive experience with the learning process. The instructor does not need to feed them the course content. The student experiences it through different mediums, including technology. However, this method of learning may be extremely difficult for students that do not have self-discipline or time management skills. Also, there is no classroom per se but usually an educational platform (Moodle, Blackboard, etc.) on the World Wide Web for academic and social interaction that students may be unaccustomed to when used in a course. There tends to be a lack of direct contact (aka “human touch”) found in a regular class (Shudgon and Higgins 2006). However, self-regulation in the classroom, mainly in learner-centered classrooms, can increase the skill set of students that a traditional lecture-based class may not offer. Students are required to manage their time to complete all assignments. They are required to organize the material that is provided in the classroom and analyze it intently for academic success, such as watching videos, reading articles, researching with search engines, or collaborating with peers that may be living in a completely different country. They become even more familiar with academic Internet tools, making them much savvier when they are ready for the workplace. In addition to self-regulation is technology-enhanced learning (TEL), the essence of m-learning. The University of Sheffield (2014) defines TEL as “e-learning, also known as online learning or technology enhanced learning (TEL) adheres to the basic tenets of face-to-face teaching, e.g., clear aims, specific learning outcomes,

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valid and reliable evaluation and assessment but with additional flexibility through the use of technology.” The University of Sheffield continues to emphasize that the educator needs to focus on the learning objectives and utilize technology, but not let technology be the main focus of the course. However, a lack of past use of technology may hinder some individuals when a course requires mobile devices. Traditional-aged students (18–22 years old) being born within the world of mobility could also encumber them, because their use of mobile devices may have only focused on entertaining activities. Opening a new world of opportunity with their mobile devices attributed to their learning brings value to their education. They are able to learn with devices that they are familiar with, making the transition from just playing games and surfing the net to learning about key educational concepts that will make them successful in school and in the workplace. The additional skill set is a definite advantage for students.

3

Service Learning

Service learning is a form of academic community engagement where service meets academia. Service learning started to receive more attention in the 1990s by the academic community as well as the federal government. It evolved from experiential learning, with the concept that “doing” is better than listening and taking notes. The concept of a more interactive education began with Dewey. He believed that “education must begin with psychological insight into the child’s capacities, interests, and habits” (Dewey and Small 1897, p. 6). Once those are acknowledged, students should apply their educational interests for further exploration, developing a desire to discover. By the 1980s, Dewey’s philosophy evolved into experiential learning, a concept defined by Kolb (1984) as “a perspective from which to approach these practical problems, suggesting a typology of different knowledge systems that results from the way the dialectic conflicts between adaptive modes of concrete experience and abstract conceptualization and the mode of active experimentation and reflective observation are characteristically resolved in different fields of inquiry” (pp. 37–38). Dewey and Kolb believed in student’s direct interaction with the environment, the main model of service learning. Bringle and Hatcher (1996) define service learning as “credit-bearing educational experience in which students participate in an organized service activity that meets identified community needs and reflect on the service activity in such a way as to gain further understanding of course content, a broader appreciation of the discipline, and an enhanced sense of civic responsibility” (p. 222). The idea concept behind service learning is that students are provided a powerful learning opportunity in a community environment. In order to reach that high level of learning, students must reflect upon their activities. Reflection can derive in the form of writing, group discussions, individual journals, and so on. Kaye (2004) describes service learning as employing four phases: preparation, action, reflection, and demonstration. In preparation, the student investigates the social problem and whether it is being resolved within the community. Once evaluated, the student

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(s) serve at a community nonprofit agency in order to assist them with that social concern. How they serve should coincide what the organization needs and what they are studying in the class. The third phase, reflection, is a significant aspect of service learning as it fosters students to think about their service and how it impacts them academically and personally. The last phase, demonstration, is the opportunity for students to display what he/she learned through the experience. This can be in the form of an essay, a presentation, or other creative formats. This phase is also the opportunity to include digital resources and technology to showcase what the student has learned. Service learning tends to be a supplement to a traditional course or an extra-credit project in a lecture-based class. However, with the new generation being born within a world of technology, it can be argued that service learning can be part of hybrid and online courses with the assistance of certain social media sites and mobile learning hardware such as a phone, tablet, or laptop. Many social media sites are ideal candidates to richly supplement service-learning curriculum as discussed below.

4

Social Media Sites

The Internet continues to progress so quickly that social media websites either build upon what they created or new sites are invented. Below are some of the social media sites that have some staying history; however, this chapter only touches upon the major Internet resources that are available at one’s fingertips (also see ▶ Chap. 27, “Tutors in Pockets for Economics”). These tools still serve many purposes that support teachers in enhancing their curriculum for more engaging material or assist students in learning the content better.

4.1

Digital Badges

Digital badges are increasing in popularity among younger students. It may seem similar to Boy Scout or Girl Scout badges, but in a digital form and utilized by adults. Once a person achieves this badge, he/she can post it in their Mozilla Backpack or showcase their accomplishment on their LinkedIn or Facebook site. Many universities and colleges have used digital badges in the classes as a new way to showcase student outcomes. “Digital badges have the potential to be the effective and flexible tools teachers have long sought to guide, recognize, assess, and spur learning. And they can recognize the soft skills not captured by standardized tests, such as critical or innovative thinking, teamwork, or effective communication” (Fontichiaro and Elkordy 2014, p. 13). Research shows that digital badges can also enhance student interaction with other students (Chou and He 2017), something that may be lacking in current online classes. The Center of Instructional Excellence at Purdue University has created a digital badge program for intercultural learning that is available for instructors and administrators. A major component of this passport is reflection, which occurs within the

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badge program by having students answer in-depth and prompted questions in order to meet the requirements of the badge. Not all digital badges available are based on education, but a vast majority exposes a student’s competencies to make them more marketable to graduate school and employers. Digital badges are a “flexible, inclusive ecosystem that connects formal and informal learning, skills and dispositions. . .” (Fontichiaro and Elkordy 2014, p. 15). A service-learning digital badge can be created for a course as a supplement or a project portfolio depending on the instructor’s desire. Most digital badge sites are free and accessible in which the instructor can develop very personable and contentspecific digital badges. A digital badge could work well in a service-learning course, because students can upload their reflection thoughts and essays or showcase the visual aspect of their project, something that is not always highlighted in a traditional resume.

4.2

Pinterest

Pinterest is an extremely popular visual platform that individuals and businesses are using by creating bulletin boards on a variety of subject matter. Though it’s most popular for personal collections and marketing endeavors, educators are seeing the value of using this site for educational purposes. One study showed that students enjoyed Pinterest and felt they learned more from the Pinterest assignment compared to other assignments (Joyce 2017). As a suggestion for a creative and visual assignment, use Pinterest as a weekly journal for students. Visual learners may be more enthusiastic about Pinterest, because of (1) the visual aspect, (2) the opportunity for creativity, and (3) the opportunity to do “work” at home. Each week students can create a new Pinterest page based on the chapter or discussion covered in the course that week. Have students search for ten visual pictures that represent that chapter and write at least three sentences on why and how the visual picture represents the chapter or topic of discussion. Students that are visual learners gravitate toward this type of project. This assignment is functional for all types of learners, because some learn by the visual choices they make, while others learn by writing about it. Overall, the assignment can develop a high level of critical thought, because they reflect on how visuals and words represent concepts. This same concept can be used in a service-learning course, and in fact, it has. Some K-12 schools and colleges based in the United States have created Pinterest sites for their service-learning projects as a way to visually show the service-learning project. On the Pinterest Board “Service Learning Projects,” some service-learning projects are highlighted. This works especially well for service-learning projects where the protected population they are serving cannot be shown on websites, presentations, etc. such as abused women in a shelter. Students can post a picture of a shelter or a picture that represents abuse without exposing the actual parties being affected. Students can then provide the “visual” aspect of service learning or volunteering and how their efforts are affecting social change or social knowledge.

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Students can then share their Pinterest pages with the world and allow others to “repin” their visual aids for their Pinterest sites.

4.3

Popplet

Popplet is a mind-mapping tool that can be operated by an individual or a group. This is a great visual brainstorming site that allows users to add information via pictures, videos, and text. This can be an abundant platform for students to collaborate on projects. Popplet is also an impressive tool for individual projects such as storytelling, managing a large social issue project, and building the visual connections or even as a way to describe a certain population, a certain organization, or even a certain class. Many service-learning projects are group based for several reasons. Reasons include logistics, creating a cohesive group of students, and similar interests among participants. Working in groups may ease the responsibility and the travel as well. Another benefit to service-learning groups is the group can make a greater impact than perhaps an individual. Service-learning groups can create a Popplet page as a collaborative space for brainstorming, organizing thoughts by all team members, and solidifying their activities geared toward the project. For example, a group working at a homeless shelter can share resources and research regarding homelessness. This mindmap can also show “connections” that group members may have not thought on their own. It also highlights the responsibilities of each member of the group and keeps them on task.

4.4

Blogs

Blogs, a form of writing on the Internet, are popular for the fact that people can write and reflect at a moment’s notice. In 2012, WordPress, a popular blog site, reported that over 100,000 new WordPress sites were created every day with 319 million people viewing 2.5 billion pages monthly (Chareonlarp 2012). Just 4 years later in 2016, WordPress published 24 blogs per second, averaging 2.13 million per day. The WordPress network had 22.17 billion page views per month (Schaferhoof 2016). Even though millions create and maintain a blog, this is not a novice concept. Blogging became prevalent in the 1990s (Williams and Jacobs 2014) and continues its popularity. Blogging may be seen as providing information about one’s thoughts and ideas, but it can also be a collaborative conversation with others in a classroom setting. Blogs utilized in higher education are also seen as a great benefit to students as it encourages more interaction among group members outside of walls of a classroom. By posting a blog, students can increase their writing capabilities and collaboration with other bloggers. Ferdig and Trammel (2004) add that blogs encourage critical thought, participation between students, and flexibility. Within the blogging realm, students have an opportunity to share information about certain classroom content, including service-learning projects. Students can

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write a weekly blog using Weebly, Blogger, or Blogspot and share their trials and tribulations of his/her service-learning project. They can follow others in the class and allow a more cooperative online relationship with peers. This instigates discussion beyond the classroom and a more flexible practicum for students with demanding responsibilities.

4.5

Twitter

Twitter is still an extremely popular social media site, especially for organizations and famous individuals. Political representatives have also been turning to Twitter to share their thoughts and encourage action. Though a fairly common tool for marketing and promotion as well, more and more educators are using this tool for interaction between themselves and the students. In fact, Twitter has 313 million monthly active users, 1 billion monthly visits to sites with embedded Tweets, and 82% of users are on mobile (Twitter 2017). Instructors can tweet articles, instructions, updates, etc. all through a Twitter feed. Also, students can follow each other and keep in contact. This may work better than email, because it’s instantaneous through texting, and the user is limited to 140 characters. In other words, being precise in your tweet is necessary to get your message across. As many popular social media sites, Twitter continues to grow with followers. Sometimes it is challenging to keep up with followers as well as manage your own posts. Twitter seems to attract a younger crowd than the more popular site Facebook (Fox et al. 2009). With Twitter being used more in education, research tends to follow. In fact, Junco et al. (2011) found that Twitter enhanced grade point averages. Another study involving 198 students using Twitter discovered that “most students. . .felt that Twitter could be utilized as a learning tool and that it allowed them to connect with others, share resources, and utilize their advocacy skills” (Anthony and Jewell 2017, p. 46).

4.5.1 Twitter Pilot Study Twitter can be a great tool for moments of reflection. In a pilot study in a communication course in a rural community college, students were required to sign up for Twitter during the second week of class, post their Twitter addresses on blackboard, and then follow the other students in the course. Students were encouraged to tweet with their “subgroups” which were smaller groups that they had a service-learning project with. Many students used Twitter as another way to interact with each other as well as group logistics (Anthony and Jewell 2017). This pilot study used a quasi-experimental, pre- and post-design. Students were required to complete a group service-learning project in their communication class while using Twitter and blogging as part of the service-learning project. All participants in this study were not self-selected, as they randomly enrolled in these communication courses without any knowledge of the class structure. A total of 26 students completed a survey at the fourth week of the semester and at the conclusion of the semester simultaneously. The semester was a 16-week class

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period. Students’ communication competency was measured with the Communicative Adaptability Scale (CAS). This assessment is known for its validity and reliability based on previous studies (Wheeless and Duran 1982; Duran 1983; Duran and Kelly 1988; Hullman 2007). The CAS assesses communication competence that measures flexibility and adaptability in social settings in an appropriate manner. The CAS subscales matched and measured the class objectives as interpersonal skills, social skills, presentation skills, and mass communication knowledge. Duran (1983) first created the instrument with a total of 20 items (Duran 1983) but then increased the instrument into a 30-item instrument (Duran and Kelly 1988) on a 5-point Likert-type scale from 5 = “always true of me” to = “never true of me” that measures 6 different items of communicative adaptability. A series of t-tests were used to see any significant change. The t-tests were conducted for each individual group comparing the pre- and posttest of the CAS. The test evaluated whether Twitter and blogging made any significant difference on any of the CAS subscales. A significant result on the articulation subscale of the CAS was found. The results show that Twitter and blogging improved students’ grammatical skills. By combining a service-learning project with Twitter and blogging, it stimulated student’s articulation skills. This may suggest that the additional form of writing through Twitter helps students’ articulation, and having a positive topic as service learning may enhance it further. The results encourage the implementation of service learning with Twitter into college curriculum as a motivating and intermingled network for students to reach class objectives. This pilot study raises many questions regarding the ability for students to use other social media tools in the classroom as well. This needs to be further explored in a larger group of participants with nontraditional students that struggle with Internet access or how to use them. This might encourage educators to investigate constructive ways to provide a technological aspect to classes easily accessible by all students.

4.6

YouTube

YouTube is one of the more popular social media sites instructors and teachers use due to its visual content, easy access, easy use, and flexibility to find almost anything at any time. YouTube boasts that it has over a billion users with hundreds of millions of hours watched on YouTube daily. Additionally, YouTube shares that it reaches people 18–24 and 18–49 more than any TV network in the United States alone (YouTube 2017). YouTube is also utilized internationally. In a study done in Thailand (Hayikaleng et al. 2017), researchers experimented with two groups of vocational students at a Thailand technical college. They discovered that the group being taught through YouTube showed significant achievement and higher levels of comprehension compared to the control group. YouTube is a valuable and accessible resource to share visual and audio information from instructor to student and vice versa. Instructors can video and post lectures. They can create these lectures right in the classroom or even a green room, if they have access to one. Green rooms can be created for around $100 if the

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instructor wants to create the green room in the classroom. Students can post academic videos and/or audio PowerPoints. YouTube has even created a new channel titled YouTube EDU which consists of channels created by universities and colleges (Snelson 2011). This format provides everyone access to free education. However, these videos can be private among the class or only to the user. These YouTube videos should be short (no more than 7 min) and entertaining. YouTube can also increase student engagement by conveying content in a different way that students find appealing. Clifton and Mann (2011) suggest that YouTube can “further stimulate deep learning students need to be encouraged to relate, compare, and analyse ideas. Through stimulated discussions students can recognize and evaluate alternative viewpoints and therefore the representation of multiple viewpoints provokes student critical thinking approaches” (p. 312). However, these videos should be used to supplement a lecture, not necessarily replace it (Kelly et al. 2009). YouTube can be very valuable for lifelong learners. Though not all videos have educational value, such as kittens playing with a paper bag, many people turn to YouTube for new and quick knowledge. For example, if a person wants to change a flat tire, he/she can probably find it on YouTube and watch it at the same time as he/she is changing the tire. If someone wants to watch a short video on American history, there is a strong possibility that many will be available within a quick search. Instructors can enhance the classroom lecture by supplementing it with a YouTube video or posting it as an assignment for discussion as homework or in an online course. YouTube can also be a great resource for service-learning projects. Students can vlog, a form of blogging via the video, right before or after a service-learning project. They can tape, with permission, the actual service-learning project, post it on YouTube, and show it in class as their final project presentation. Students can interview nonprofit volunteers, nonprofit agency staff, or those people who receive accommodations and services. For example, in one class, students taped themselves picking up food for a food drive and shared their experiences throughout the day. The advantage is seeing and reflecting on the perspective of others in the class. If students have different servicelearning projects, they can try and understand and learn from other students. If one group is working with the homeless, and another is working with veterans, then all students can be visually exposed about each other’s projects. Snelson (2011) mentions with the increased popularity of online education, professors and instructors should invest in developing stronger video production skill to attain higher-quality YouTube videos for their students. Also, to make it educationally productive for students, instructors must make sure that there is a teaching objective (s) and that the video is related to that objective (Thakore and McMahon 2006).

4.7

Instagram

There are over 500 million Instagrammers that post pictures to the very popular website Instagram (Instagram.com 2014). Forty billion pictures have been shared and 95 million photos and videos are shared daily (Instagram.com 2014). It seems

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natural that such a popular site would make its way into the education world. Hannah Hudson (2014) shares what teachers can do to promote Instagram in the classroom. She suggests that Instagram can be used for history lessons, field trips, and even showcasing favorite books. Additionally, there is great value for incorporating Instagram with service-learning projects. For example, if a service-learning project entails homelessness, students can snap pictures of what “homeless” means to them. Students could even snap photos through the eyes of a homeless person, trying to develop empathy and a new perspective on the people they are trying to assist. Students shouldn’t be limited to subject of homelessness but to explain other community service activities the instructor recommends or suggests. Many of those community service projects may include the elderly, animals, or even refugees. With the tool of their smartphone, students, for example, can take snapshots regarding the struggles elderly people go through on a daily basis and take pictures through the eyes of an 80-year-old woman or man. Opportunities are endless when telling a story or providing a snapshot of someone else’s perspective. Students can also provide their own perspective about some of the local community concerns, creating a bulletin board or a slideshow to share with other students. This can be abstract or provide realist evidence of the growing concerns people face within their communities.

4.8

Snapchat

Reported by the website Business Insider (Carson 2017), 158 million people use Snapchat daily, and users are spending 25–30 min on the app daily. So what is the interest in Snapchat? People, many of the younger generation, can take temporary pictures and share them, and then the pictures self-destruct. It seems that such an app would be disregarded in higher education, but in fact universities are beginning to use Snapchat. Sopho (2014) shares that schools can promote certain events and even endorse current activities on campus. One of her suggestions is that schools could use Snapchat for campus tours. Based on her comment, universities could promote community service opportunities that are active on campus, allowing students to see for a few seconds active community outreach. Students could then self-promote their own community engagement, possibly attracting other students to participate in these activities. Because the pictures disappear after a few seconds, it would be challenging to make Snapchat part of academic curriculum. However, snapping pictures of a noble cause such as a service-learning project may allure students that never participated in community service events in the past.

4.9

Emaze

Emaze, something similar to PowerPoint and Prezi, makes presentations more interesting and exciting for the viewing audience. As Bassa (2013) points out, “Emaze allows users to choose from a variety of templates with built in HTML5

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technology, ranging from PowerPoint style presentations, to 3-dimensional patterns, made possible by the advanced graphical capabilities of the system.” It’s common for students to present their service-learning projects as a final assignment which they are graded on by the instructor as well as their peers. With Emaze, students can still supply the presentation for academic evaluation but create something that is different and eye catching. With such interesting graphics and design, these service-learning projects presented on the Emaze platform may provide a more “live” experience of their service-learning projects. Educators could argue that such a presentation creates a more attention-grabbing scholarly experience.

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Pros and Cons

As most resources available to educators and administrators, there are positives and negatives associated with m-learning. Positive aspects of m-learning are providing creative ways of reflection and flexibility to students. Our world is 24/7, and this allows the student to be responsive whenever and wherever they may feel like it. Students may like this aspect, because they are not being confined to a time and space to complete assignments. They can be engaged anywhere at any time. The disadvantage of this is the accessibility 24 h a day, and there may not be a shut-off time for the student or for the instructor. This results in people always in the “on” mode, which does not offer a “down” time. Additional benefits that Corbeil and Valdes-Corbeil (2007) mention are that less barriers may exist between instructors and students, because students are comfortable with this type of medium. However, on the opposite side, there are students that may not be as comfortable with such devices, because (1) they never found a need to use it or (2) they haven’t had the financial means to keep up with up-to-date technology available. Additionally, certain technology products, websites, and apps evolve daily. Another negative aspect is that some students do not have access to the newest technology due to costs, old technology and/or hardware, or technological capability. When the instructor incorporates certain devices and websites for a class activity, he/she may need to change every semester just to keep up with all the technology changes. This can add additional frustration and time to an instructor’s already hectic schedule and overwhelming responsibilities. As mentioned, it is important to incorporate reflection in mobile activities, but this also has its challenges. Though students may be prompted to reflect and respond accordingly, it doesn’t necessarily create a deeper conception of the material. All the social media accessible to them distract students. They may be responding to a question on a YouTube clip, but then with constant emails, texts, and other tools showing on their phone, they may be distracted. Their concentration and commitment to the activity are then questionable.

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Dos and Don’ts

It’s important for the instructor to have some social presence on the Internet and in the virtual classroom. Without it, the student may feel some disconnection and not thrive in this environment. So how does a professor create a social presence in a social media network? Dunlap and Lowenthal (2014) offer some suggestions that can be introduced in most disciplines. One idea they suggest is having a student and a teacher bio but takes this bio a step further. They propose a prompt called “One Extra Hour.” They ask students what they would do if they had an extra hour a day to create interesting and engaging dialogue. This provides an opportunity for students to learn about their peer’s values, families, and work. They use VoiceThread to respond via a microphone or webcam to this extra-hour-a-day question. Microphones and webcams can be found on smartphones or other mobile devices such as laptops and tablets. Another interesting activity Dunlap and Lowenthal have interwoven in their curriculum is called “Soundtrack of Your Life.” They ask students to create a playlist of six songs: two that represent their past, two that represent their present, and two that represent the future. Many interesting and educational lessons can be found on an Internet search. The Internet and m-learning can be used asynchronously. However, it can be an excellent experiential world that increases successful collaborative student work. The principles are the same: the instructor needs to make sure there is continual communication with concrete objectives. Students should introduce themselves to each other through email or texts or face-to-face at the beginning of the project. Then, each student should have a defined role in the assignment, making sure each individual is responsible for being an active and supportive member of the group. Increasing motivation and accountability is necessary for group cohesiveness, which can occur through shared goals and rules that all group members must follow. Continual conversation should occur throughout the project, and the instructor should check to see the progression of the discussion. Suggesting or requiring specific goals to be met each week may be needed by the instructor or a group leader. The instructor needs to help his/her students to be efficient and organized within his/her group and for the class as a whole.

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Future Directions

Social media resources on the World Wide Web can be utilized to the advantage of instructors and professors. They can make great strides in engaging with their students and becoming more student-focused. However, they need to be intentional about their mobile assignments to increase academic growth and good reflective practice. Wi-Fi allows instructors to be more interactive with students, that is, not binding by classroom walls. M-learning also encourages students to collaborate and reflect together, allowing students to be more present when focusing on academic work. With service learning and m-learning being combined, the high educational

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impact can be limitless. With technology tools, websites, and apps changing at a high pace, so can the educational opportunities. The objective and goals of classes may stay the same, but the way to approach students and engage them can vary. Instructors and professors need to keep abreast of the changes that occur, so they encourage students’ productivity and interest in education. Additionally, more scholarly research needs to occur for theorists and educators to create conceptual frameworks in the world of education and technology (Antonenko 2015). With social media tools expanding and changing continuously, it is critical that educators see how technology can positive impact the classroom and their tech-savvy students.

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Cross-References

▶ Framework for Design of Mobile Learning Strategies ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts ▶ Tutors in Pockets for Economics

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Ferdig, R.E., and K.D. Trammell. 2004. Content delivery in the ‘blogosphere’. The Journal 31 (7): 12–20. Fontichiaro, K., and A. Elkordy. 2014. From starts to constellations: Digital badges can chart growth. Learning and Leading with Technology 41 (4): 13–15. Fox, S., K. Zickuhr, and A. Smith. 2009. Twitter and status updating, fall 2009. Pew Internet & American Life Project, 21 Oct 2009. Hayikaleng, N., S.M. Nair, and H.N. Krishnasamy. 2017. Using Youtube to improve EFL reading comprehension among vocation. Proceedings of the ICECRS 1 (1): 391. Heikkilä, A. 2006. Studying in higher education: Students’ approaches to learning, self-regulation, and cognitive strategies. Studies in Higher Education 31 (1): 99–117. Hudson, Hannah. 2014. We are teachers. http://www.weareteachers.com/blogs/post/2014/08/07/10ways-to-use-instagram-in-the-classroom. Accessed 1 Feb 2015. Hullman, G.A. 2007. Communicative adaptability scale: Evaluating its use as an ‘other-report’ measure. Communication Reports 20 (2): 51–74. Instagram. 2014. Instagram Press. http://instagram.com/press/. Accessed 31 Jan 2015. Joyce, A. 2017. I remember that from my pins!: Using Pinterest to encourage active learning. Psychology Learning & Teaching. https://doi.org/10.1177/1475725717710210. Junco, R., G. Heiberger, and E. Loken. 2011. The effect of Twitter on college student engagement and grades. Journal of Computer Assisted Learning 27 (2): 119–132. https://doi.org/10.1111/ j.1365-2729.2010.00387.x. Kaye, Cathryn Berger. 2004. The complete guide to service learning. Minneapolis: Free Spirit Publishing. Kelly, M., C. Lyng, M. McGrath, and G. Cannon. 2009. A multi-method study to determine the effectiveness of, and student attitudes to, online instructional videos for teaching clinical nursing skills. Nurse Education Today 29 (3): 292–300. Kolb, D.A. 1984. Experiential learning: Experience as the source of learning and development. Vol. 1. Englewood Cliffs: Prentice-Hall. MoLeNET. 2014. Molenet. http://www.molenet.org.uk. Accessed 10 May 2014. Schaferhoof, Nick. 2016, October 18 . Torque. https://torquemag.io/2016/10/13-surprisingwordpress-statistics-updated-2016/. Accessed 17 June 2017. Sharples, M., I. Arnedillo-Sánchez, M. Milrad, and G. Vavoula. 2009. Mobile learning, 233–249. Dordrecht: Springer Netherlands. Shudgon, W., and M. Higgins. 2006. Limitations of mobile phone learning. The Jalt Call Journal 2 (1): 3–14. Snelson, C. 2011. YouTube across the disciplines: A review of the literature. MERLOT Journal of Online Learning and Teaching 7:159–169. Sopho, Monthira. 2014. Using snapchat as a higher education tool. Multimedia Portfolio. http://sites. psu.edu/multimediaportfolio/2014/08/13/using-snapchat-as-a-higher-education-tool/. Accessed 3 Feb 2015. Stowell, J.R. 2015. Use of clickers vs. mobile devices for classroom polling. Computers & Education 82:329–334. Thakore, H., and T. McMahon. 2006. Virtually there: E-learning in medical education. The Clinical Teacher 3 (4): 225–228. Twitter Press. 2017. About. https://about.twitter.com. Accessed 15 Dec 2017. University of Sheffield. 2014. Learning and teaching services. http://www.shef.ac.uk/lets/toolkit/ teaching/e-learning/telon. Accessed 24 Dec 2014. Wheeless, V.E., and R.L. Duran. 1982. Gender orientation as a correlate of communicative competence. Southern Speech Communication Journal 48 (1): 51–64. Williams, J.B., and J. Jacobs. 2014. Exploring the use of blogs as learning spaces in the higher education sector. Australasian Journal of Educational Technology 20 (2): 232–247. YouTube Press. 2017. Statisics. https://www.youtube.com/yt/press/en-GB/statistics.html. Accessed 17 June 2017.

Technology-Mediated Assessment in Crossover Learning Assessment Design (CLAD): A Case from Sustainable Engineering Design Education

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Contents 1 2 3 4 5 6

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Formal and Informal Learning: A Brief Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . An Alternate View of Formal and Informal Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bridging Formal and Informal Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CLAD and Technology-Mediated Assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . GreenDesigners: A CLAD on Sustainable Engineering Design Education . . . . . . . . . . . . . . . 6.1 Overview of the Research Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Technology-Mediated Assessments in GreenDesigners: Design Framework . . . . . . . . . . . . 7.1 SPS and PFL Elements in Technology-Mediated Assessments . . . . . . . . . . . . . . . . . . . . . 8 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Crossover Learning Assessment Designs (CLADs) are unique in their coordination of formal and informal learning through technology-mediated assessment of curricular concepts. This chapter captures the research-based design of one CLAD that employed technology-mediated assessments driven by an augmented reality learning (ARL) platform to provide high school students an exposure to sustainable engineering design concepts. These assessments were embedded in the learning content that drew on the Next Generation Science Standards (NGSS) F. H. Salman (*) Learning and Performance Systems, College of Education, Pennsylvania State University, University Park, PA, USA e-mail: [email protected] D. R. Riley Architectural Engineering, College of Engineering, Pennsylvania State University, University Park, PA, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_120

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and spread across the real-world setting of a solar house. Learners interacted with the overlaid augmented content and assessments on their mobile devices as they physically navigated the GPS-marked locations across the solar house. Analytics on the learners’ performance on these assessments were secured on the ARL platform for further analyses. Data collected through iterative usability cycles helped improve the design of technology-mediated assessments that are essentially: (1) place-based, (2) curriculum-focused, and (3) technology-driven. Most importantly, the design of these assessments is deeply rooted in the conceptual distinction of informal and formal learning based on the emphasis on experiential and explanatory knowledge respectively. This chapter proposes CLAD as a pedagogical solution that coordinates explanatory (formal) and experiential (informal) learning through technologymediated assessments. The chapter also presents the design framework of technology-mediated assessments within a particular CLAD with the hope that educational researchers and practitioners will draw upon this framework in their efforts to bridge formal and informal learning experiences.

1

Introduction

Learning is fluid and unrestricted by boundaries, be it physical, spatial, or cognitive. Expanding on this perspective of learning, this chapter discusses Crossover Learning Assessment Design (henceforth CLAD) as a technology-driven, pedagogical solution to address disconnect between formal and informal learning. The unique contribution of CLAD is its coordination of formal and informal learning through technology-mediated assessment of curricular concepts. Conceptually rooted in ubiquitous learning (Cope and Kalantzis 2009), CLAD explores how formal and informal learning could be effectively coordinated. Hence, the chapter first takes a plunge into extant definitional perspectives on formal and informal learning. Moving forth, it invites educational designers, researchers, and practitioners to explore an alternate lens of differentiating formal and informal learning that is rooted in the emphasis on explanatory (formal) versus experiential (informal) knowledge. This differentiation forms the epistemic inspiration for the pedagogical solution of CLAD proposed in this chapter. Next, the chapter advances a detailed discussion on technology-mediated assessment as a unique aspect of CLAD. The chapter then attends to the design elements and implementation strategies of one CLAD called GreenDesigners where the technology-mediated assessments are geared towards sustainable engineering design education.

2

Formal and Informal Learning: A Brief Overview

Learning defies all boundaries. Some educational researchers acknowledge the fluidity of learning (e.g., Cook 2007; Sharples et al. 2015; Vahey et al. 2007) and lament the spatial divide where schools are responsible only for formal learning

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while outside school spaces are considered best suited for informal learning. In the absence of any agreement among educationists about what constitutes formality and informality (Dohn 2010), informal learning is conventionally characterized as the antithesis of formal learning – one that eludes structure in its design, expectations, and outcomes. Within the context of education, structure is usually determined by externally defined academic standards, formulated as curriculum. Learning designs that do not align with any standard curriculum are labeled as informal, nonformal, or extracurricular. For instance, museums and science centers conduct educational activities that are not curriculum-based, so are considered informal (Zimmerman et al. 2015). Such designs have made way for many researchers to view formal and informal learning along a continuum ranging from highly informal to highly formal (e.g., Plummer et al. 2015; Eraut 2004). Another popular definitional view dichotomizes formal and informal learning along the lines of teacher-centric and learnercentric design, respectively. This view also brings forth learners’ choice as an aspect that sets apart formal from informal learning as Falk (2005) emphasizes that “the operative issue is perceived choice and control by the learner” (p. 273). Beyond the pedagogic lens, a closer look at recent empirical excitement in informal learning affords deeper insights about this separation. While research on formal learning continues within the classroom space, research on informal learning probes into the design and impact of participatory learning experiences during fieldtrips (e.g., Lanir et al. 2017) and in spaces like transit stations (e.g., Cardiel et al. 2016), museums (e.g., Diamantopoulou and Christidou 2016; Rogers and Rock 2017), arboretums (e.g., Uzick and Patrick 2017; Salman et al. 2014), planetariums (e.g., Plummer et al. 2015), and nature centers (e.g., McClain and Zimmerman 2014). This helped popularize the term informal learning institutions or ILIs that has surfaced as a parallel force to the long-established classroom culture. This move away from spatial constraints of the classroom has encouraged research designs that support emergent curriculum for incidental learning (Eraut 2004), however, without an expressed focus on assessments or desired learning outcomes (Bybee 2013; Sahin et al. 2014). This has afforded much traction in innovative research areas like gamification (Chen and Hwang 2017; Klopfer and Perry 2014), social sites (e.g., Manca and Ranieri 2016), and fantasy sports (e.g., Newell 2017; Smith et al. 2006). It has also encouraged a bold and diversified disposition towards the use of technology (Hsu et al. 2012; Hwang and Tsai 2011) and multimodal analytical methods (Diamantopoulou and Christidou 2016; Salman et al. 2014).

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An Alternate View of Formal and Informal Learning

More recently, Kaser et al. (2017) and Arena and Schwartz (2014) added a new dimension to this definitional debate in observing that formal learning emphasizes explanatory knowledge while informal learning emphasizes experiential knowledge. Within the context of science learning, this lens invokes what was observed by Hofstein and Rosenfeld (1996) as the process of “hands-on experimentation” versus “minds-on reflection.” For instance, formal learning designs traditionally emphasize explanatory

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knowledge in the form of school lectures and whole-class relay of expository passages. This delivery mechanism is designed to provide declarative accounts of facts and procedures and is therefore constrained by time and space which is further reflected in the school assessments that test explanatory knowledge (Freeman et al. 2014) within the timed condition of a 40–50 min class duration. Contrastingly, informal learning with its focus on experiential knowledge is commonly packaged as guided discovery experiences and demonstrable concepts. Delivery mechanism is dynamic and ubiquitous across time and space which enables a learning experience comprised of rich narratives and multiple learning pathways. Students are involved in a process of personalized understanding that expands their prior learning experiences to help them acquire new experiential frames. However, this process remains mostly tacit due to the lack of school assessments that make the learning process visible (Davis and Singh 2015; Wardrip and Shapiro 2016). Unfortunately, school assessment of experiential knowledge is conducted through traditional formats that focus on explanatory knowledge instead of experiential knowledge gains. It is this lopsided emphasis on explanatory learning and assessment that perpetuates disconnect between classroom and real-world education. Crook (2002) notes that this disconnect results in the students’ experience of the informal and formal settings as silos or separate worlds. Moreover, Ito et al. (2013) warn that learners will continue to miss sustained connections between their informal and formal learning experiences due to dichotomies imposed by learning designs. Even if some schools venture to embed low tech, informal learning activities (e.g., field trips, etc.) in the school curriculum, their seriousness is compromised by the extant assessment regimes. This further devalues the learning potential of such informal spaces. Datoo and Chagani (2011) reflecting on their project of using street theatre as critical pedagogy in formal classroom settings emphasize that “strong formal structure of teaching and learning may initially make it difficult to be flexible and to adopt alternate ways of learning and expression.” (p. 28).

4

Bridging Formal and Informal Learning

These insights from the field reveal the epistemological and methodological limitations of applying the alternate view of formal and informal learning (see also ▶ Chap. 34, Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts). They further guide towards a proposal for coordinated learning designs. For example, Plummer et al. (2015) and Eraut (2004) explicitly recognize that formal and informal learning experiences should be perceived along a fluid spectrum rather than some rigid dichotomy. Particularly, Plummer et al. (2015) observe how variations in the content, audience, physical space, and the learning objectives should be designed to modulate the experience across this spectrum. Interestingly, while Hofstein and Rosenfeld (1996) proposed bridging the formal-informal separation through a “hybrid approach,” Arena and Schwartz (2014) assert that the bridged learning design should have a balanced emphasis on experiential and explanatory knowledge. This assertion reinforces the idea that designing for varied forms of knowledge expands learning opportunities for diverse learners. As such, recent research suggests that formal and informal learning should be bridged through technology-mediated learning designs

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(e.g., Salman and Riley 2016; Sharples et al. 2015; Wardrip and Shapiro 2016) with an emphasis on curriculum concepts (e.g., Bellocchi et al. 2016; Goff et al. 2018; Sun and Looi 2018). Motivated by these empirical insights, the National Research Council (2015) reports growing evidence that opportunities to learn outside of school directly affect what is possible inside classrooms, just as what happens in classrooms affects outof-school learning. Building on these recommendations, this research study advanced the pedagogic solution of Crossover Learning Assessment Design (CLAD) that coordinates technology-mediated learning designs and curriculum-based assessments to bridge formal (explanatory) and informal (experiential) learning. The next section elaborates on the conceptual design of CLAD and explains how technology-mediated assessments are operationalized within CLAD.

5

CLAD and Technology-Mediated Assessments

CLAD is based off the term crossover learning that has its roots in Sharples et al. (2015, p.1) who uses it to represent a pedagogical concept that bridges formal and informal learning set tings. It is illustrated by the design of the Museum Studies magnet program at Ortega Elementary in Jacksonville, USA (Sharples et al. 2015). This school partners with museums and integrates course subjects, so that students learn to create exhibits, to problem-solve and propose solutions based on content from math, science, social studies and other academic disciplines. In the crossover design of the Ortega program, students start a teacher-initiated investigation in class (i.e., a formal setting) then continue outdoors or at home (i.e., in informal setting), using mobile applications to collect data and evidence that are then shared and presented in class as student artifacts. The Ortega program elucidates three design principles: (1) interconnections across physical and/or digital settings; (2) curriculum-linked content; (3) technology- mediation through digital devices that help transfer information and experience across settings. To further emphasize the importance of this connection, Sharples et al. (2015) elaborate upon the nature of the connections These connections work in both directions. Learning in schools and colleges can be enriched by experiences from everyday life; informal learning can be deepened by adding questions and knowledge from the classroom. These connected experiences spark further interest and motivation to learn. (p. 3)

It is the bidirectional nature of the connection that uniquely defines crossover learning. It is important to note that Sharples et al. (2015) refer to the physical setting in their use of the terms formal and informal. Also, Sharples et al. (2015) present their big vision of crossover learning for coordinating formal and informal learning through examples of projects that illustrate the underlying principles. However, they do not specify the exact elements that form this coordination. It is in this context that CLAD is proposed as a direction for bridging formal and informal learning through technology-mediated assessments.

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The idea that propels this foregrounding of assessment is rooted in the importance that assessments have had in the context of education. Particularly, Kaser et al. (2017) observe that assessment influences what is taught, what should be taught, and what is discovered about how people learn. This is widely known as the washback effect where over a period of time, the assessment influences the school pedagogy and the curriculum. It is important to note that educational researchers (e.g., Bransford and Schwartz 1999) have long criticized school-based tests for their fixation on assessing declarative and procedural knowledge. In keeping with this argument, they discuss two types of assessments as measures of learning: sequestered problem solving (SPS) and preparation for learning (PFL). While, SPS designed to focus on explanatory knowledge, discourages use of information sources or scaffolds during the test, the design of PFL focused on experiential knowledge encourages students to use various information sources including their prior experiential knowledge. Bransford and Schwartz (1999) observe that SPS assessments that are mostly traditional, school-based tests discourage learning transfer- which is evidenced as the most significant indicator of sustained learning (Schwartz et al. 2005). In comparison, the construct of PFL assessments rely on the availability of information sources and could function well as a device for formative assessment within the informal dynamics of outside school settings. This typological comparison of SPS and PFL assessments is also helpful to understand the washback effect which essentially results from using ill-purposed tests. For example, if a school-based assessment designed to inform about declarative knowledge is used to evaluate what children have learnt from their experience within a videogame, the results will be misleading (National Resource Council 2012) and would eventually influence the pedagogical use of videogames in schools. Scholars also lament that most of the classroom-based test design is purposed towards measuring isolated skills for grading and academic placement whereby it is not indicative of the learner’s potential to perform in future learning settings. In a recent study, Kaser et al. (2017) assert that to effectively determine the measure of learning transfer both types of assessment, i.e., sequestered problem solving (SPS) and preparation for learning (PFL) should be employed. This recommendation holds significance both in terms of measuring for learning transfer and also for designing assessments that capture an inclusive palette of skills and resources. The CLAD design moves in this direction where components of SPS assessments are combined with those of PFL assessments through a technology-mediated platform that provides information about learners’ explanatory and experiential knowledge. The next section introduces the study to set the pace for the design framework of technology-mediated assessments in the exemplified CLAD of GreenDesigners.

6

GreenDesigners: A CLAD on Sustainable Engineering Design Education

With its focus on sustainable engineering design education within the broader scope of Science, Technology, Engineering and Math (STEM), GreenDesigners exemplifies a CLAD that integrates technology and engineering design

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curriculum across a place-based learning experience. The study marks a departure from previous research on technology-rich, outside-school learning experiences through a crossover learning design focused on STEM education-in and across- formal and informal learning. It is important to understand that the terms “formal” and “informal” within the context of CLAD predominantly refer to an emphasis on explanatory and experiential knowledge respectively.

6.1

Overview of the Research Design

The research design was located at the physical setting of the Pennsylvania State University’s solar house called MorningStar. Selected portions of the solar house were augmented with information about the design features that were deemed critical to youth’s conceptual understanding of sustainable engineering design. The curricular content was drawn from the High School Engineering Design standards of the Next Generation Science Standards (NGSS). Data was collected as ten high school students interacted with rich, augmented content and digital assessments on a mobile Augmented Reality Learning (ARL) platform while observing the sustainable design features onsite the solar house. The digitally augmented information and on-the spot assessments helped students notice the physical features as they toured the solar house (see also ▶ Chap. 71, “Mobile AR Trails and Games for Authentic Language Learning”). This in turn engaged the students in learning critical STEM concepts. This mobile learning experience culminated in a capstone design challenge where students designed prototype solutions based on their exposure to critical design concepts during their interactive tour of the solar house. Data was collected in the form of pre- and posttests, video and mobile screen recordings, learning analytics of all activities on the ARL platform and student generated artifacts and presentations. Data was analyzed using qualitative video-based interaction analysis and statistical testing of the pre-post-test responses. Research findings of this study are not discussed in this chapter since the focus is exclusively on the design framework of technology-mediated assessments which is discussed in the next section.

7

Technology-Mediated Assessments in GreenDesigners: Design Framework

This section presents the design framework of the technology-mediated assessments in GreenDesigners. The three design elements of technology-mediated assessments, i.e., place-based, technology-driven, and curriculum-focused (Fig. 1) draw upon the following design principles: 1. Assessments interface across formal and informal settings and the physical and digital mode, 2. Assessments are employed to enable crossover learning of curriculum concepts,

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3. Assessments are designed to make learning visible as both a process and an outcome of the learners’ performance to solve a real-world problem, 4. Assessments are balanced across Sequestered Problem Solving (SPS) and Preparation for Future Learning (PFL). It is important to emphasize that the design framework of technology-mediated assessments is geared towards bridging formal and informal learning experiences through a balanced focus on explanatory (SPS) and experiential (PFL) assessments. 1. Place-Based Within GreenDesigners, technology-mediated assessments were distributed across the real-world, physical space of a solar house layered with digital content. This allowed engagement with the embedded sustainable engineering design concepts, both physically and digitally. As such, the technology-mediated assessments reconfigured the space of the solar house into a place that generated experiences, interpretations, and meanings and provided insights into learner interactions. For example, the learners experienced the “space” in terms of varying temperature gradients, while the AR-driven place-based assessments invited their interpretations about temperature influenced by solar design strategies embedded in the design. As a physical “space,” the MorningStar solar house (Fig. 2) is 799 sq. ft. builtspace located at the 9-acre tract of the Penn State University’s Sustainability Experience Center. It features a residential, open-plan design with the combined living-dining space connected to a bedroom space with a fully-equipped kitchen and bathroom. There is a patio overlooking an outdoor grill area surrounded by community gardens. As a “place,” the solar house was represented by a GPS-GIS map with red location-markers within the Augmented Reality Learning (ARL) platform (Fig. 3).

Fig. 1 Design framework of technology-mediated assessments in GreenDesigners

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Fig. 2 MorningStar physical space

Fig. 3 MorningStar GPS-GIS map

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A digital map (Fig. 4) was created and utilized as representing the interior of the solar house with reconfiguration into a digital “place” through the augmented information overlaid on the physical “space.” Enriched by the AR information, the digitally reconfigured space of the solar house afforded learners hands-on interaction with the built environment. This aligns with the proposal to conceive buildings as 3D textbooks within the field of architectural engineering (Barr et al. 2011). The digital map (Fig. 4) functioned as a spatial reference for the learners to move in and out of the learning and assessment activities. The map served as the visual and spatial navigational tool for the technologically mediated assessments. This design element of “place-based” resonated with situated approaches to learning that typically involve situating students in real-world contexts that resemble the environment of disciplinary practice to solve real-world problems (Vos et al. 2011). Particularly, Wang et al. (2017) observe that problem-solving in authentic, real-world contexts affords analysis of new ideas while making connections to concepts acquired in situ which further helps in retaining concepts for later use to solve new problems. For example, in a museum-based study, Falk and Dierking (2000) observed that placespecific situatedness impacted and influenced how learners engaged with and constructed their understanding of new information. It is important to note here that Fig. 4 MorningStar interior “place”

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one criterion for effective STEM programs involves “first- hand experience with phenomenon and materials” (p. 16) that includes situated investigations in the real world (National Research Council 2015). Within this criterion, first-hand means providing learners direct engagement with questions, contexts, and data related to the STEM topic. The technologically mediated assessments with GreenDesigners were designed to expose learners to this first-hand STEM learning experience. 2. Technology-Driven This design element was accomplished through the Augmented Reality Learning (ARL) platform. This platform connected two separate technologies, a locationbased AR platform and a video-based learning analytics platform. This integration operationalized the place-based design of the assessments through a cohesive technological system that afforded rich information and generated learning analytics on the move. While the ARL platform provided the overall technological contextualization, the video content and assessments were aligned with the place dependent, physical features of the solar house. In this manner, place-based experience was achieved by these two platforms working in harmony to produce a holistic contextualized learning experience. As such, this AR integrated technological infrastructure enabled learner analytics as a method to monitor the assessments and evaluate STEM learning within GreenDesigners. Figure 5 uses the example of a design-concept “Conductors and Insulators” to illustrate the functioning of the ARL platform. This is an important and foundational design-focused concept in sustainable engineering design as it influences the choice of materials based on their capacity to conduct or insulate heat, especially for designing walls, windows and floors. Within GreenDesigners, this concept was digitally layered as a video hosted by the ARL platform on to the West wall of the solar house. Figure 5 shows how this concept and accompanying assessments were accessed by the learners on their tablets through the mobile app powered by the ARL platform. The learners accessed the default location Sustainability Experience Center (A) on the app which was powered by GPS-GIS. They were guided to the solar house (B) and prompted of the AR content geo-marked at the West Wall with a 1.5 m level of precision (C). On the digital, interior map (D) this specific content, namely, “conductors and insulators” was represented by the blue square. Learners were prompted of the design-focused content which was available as videos embedded with assessments (E). Within this scheme, (D) was the transition point denoting: (i) the integration of the two platforms, (ii) the augmentation of content, and (iii) the transition from physical to digital. This transition is indicated by a dotted connector in this Fig. 5. The augmented, video content allowed the learners to deepen their understanding of “heat conduction and insulation” while observing the concept in the physical design of the West Wall. Simultaneously, the learners responded to conceptual questions and contextualized design-focused questions while the platform generated learner analytics as an aggregate of student performance and a breakdown of each question. In this manner, the technologically contextualized assessments of design concepts afforded by the ARL platform in GreenDesigners supported the learners’ conceptual

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Fig. 5 ARL platform functioning

understanding that was later channelized towards their collaborative problemsolving in the design challenge phase. This experience echoes the National Research Council (2015) in its aspiration for learning designs that engage youth in a wide range of practices to investigate, model, and explain natural phenomena and the man-made world. 3. Curriculum-Focused Technology-mediated assessments in GreenDesigners leveraged the concept of buildings as teaching tools to contextualize sustainable engineering design concepts (Craig et al. 2012). This was achieved by overlaying portions of the solar house with selective design-focused concepts as a learning and assessment experience. Particularly, video-lessons embedded with assessments operationalized intentional connections to the location-based curriculum, i.e., the sustainable design features of the solar house and the subject-based curriculum of engineering design. For this, the overall assessment system was conceptualized on three specific Engineering Design standards from the Next Generation Science Standards (Lead States 2013) for high school grades organized across the process lens of analyze-design-evaluate. These standards were adapted and customized for GreenDesigners using Mclennan’s (2004) seminal work on green design methodology focused on built structures. The organizing lens of analyze-design-evaluate helped in the creation of designfocused videos and assessments and supported the culminating design challenge activity. Table 1 presents the NGSS engineering design standards organized by the process frames of analyze-design-evaluate for high school grades and the adapted standards using the four elements from green methodology by Mclennan (2004).

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Table 1 Adapted standards from NGSS/Engineering design standards NGSS Engineering Design Standards (NGSS Lead States 2013) HS-ETS1-1 Analyze a major global challenge to specify qualitative and quantitative criteria and constraints for solutions that account for societal needs and wants.

HS-ETS1-2 Design a solution to a complex real -world problem by breaking it down into smaller, more manageable problems that can be solved through engineering. HS-ETS1-3 Evaluate a solution to a complex real-world problem based on prioritized criteria and tradeoffs that account for a range of constraints, including cost, safety, reliability, and aesthetics as well as possible social, cultural, and environmental impacts.

Adapted Standards. GreenDesigners (Mclennan 2004) Analyze the global challenge of energy crisis through related information on renewable nonrenewable energy, fossil fuels, etc. Students analyze terminology, properties of materials and design strategies related to sustainable energy and solar strategies in built solar residential designs as one solution to the global challenge of energy crisis. Analysis employs the four elements frameworka. Design prototype of a built-solution based on solar design strategies by considering specific sustainable engineering concepts in design solutions using the four elements frameworka. Evaluate a built solution based on prioritized criteria and trade-offs specified by the four elements frameworka.

a

The four elements in green methodology (Mclennan 2004): 1. Understand climate and place [exemplified in solar house as geographical design considerations like position of sun and wind direction] 2. Load reduction [exemplified in solar house as modular construction/prefabrication. heat conduction and insulation, thermal mass in the choice of materials] 3. Using free energy [exemplified in solar house as regionally appropriate solutions] 4. Using the most efficient technology [exemplified in solar house as home owner behavior; active and passive solar strategies]

Based on these adapted curriculum standards, the technology-mediated assessments allowed learners an opportunity to study and analyze a solution (i.e., the solar house) to a real-world problem (energy crisis, environmental degradation). Learners were also provided an opportunity to design a prototype-solution (i.e., an artifact) and to present their design-evaluations to make their learning visible as recommended by Wardrip and Brahms (2015). Studies in sustainable architecture (Barr et al. 2011; Craig et al. 2012; Stephen et al. 2008) have recognized the importance of designing high-performing teaching tools that capture sustainable buildings as a design-focused solution to the contemporary environmental problems. Also, from the broader lens of science inquiry, tying curriculum standards to a realworld problem promises stronger contextualization of content that allows students to relate the content to problems and situations in their own lives and thus in the real world (Rivet and Krajcik 2008). In GreenDesigners, technology-mediated assessments were based on concepts explained through augmented videos that featured architectural engineers explaining

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the design-integration of those concepts. This resembled an apprenticeship pedagogy where a field expert explained the decisions and trade-offs that went into designing the solar house. For example, the concept of “heat conduction and insulation” was introduced through a video that was digitally overlaid on the “West and South walls” of the solar house. Learners were guided to observe this concept represented by two design features (integrated solar modules and structural insulated panels) at the solar house’s two walls. Formative assessments and reflective pauses embedded in the videos afforded a deeper understanding of how this concept functioned within the design considerations of sustainably engineered residential housing. Later when the learners returned to the classroom setting, this concept of “heat conduction and insulation” was one of the critical concepts that learners employed in designing a prototype solution. Being place-based, technology-driven, and curriculum-focused, the technologymediated assessments in GreenDesigners present a combination of sequestered problem solving (SPS) and preparation for future learning (PFL) elements as explained in the next section.

7.1

SPS and PFL Elements in Technology-Mediated Assessments

In terms of design, the technology-mediated assessments within GreenDesigners comprised a combination of elements that were purposed towards gauging learners’ explanatory knowledge (SPS) and experiential knowledge (PFL). This can be illustrated by the following example.

7.1.1 Example: Structural Insulated Panels (or SIPs) at the South Wall At the South wall, several design considerations related to “passive solar strategy” are introduced through an overlaid design-focused video that features an architectural engineer explaining design concepts, strategies and design trade-offs. One critical concept of wall insulation is explained through the design feature of Structural Insulated panels (SIPs). These are specially designed wall panels or bricks that are made of polyurethane foam. Learners are guided to observe the design-concept of “wall insulation” represented by the physical design feature of SIPs embedded in the South wall at the solar house. Since SIPs are concealed design-feature, learners are also provided access to a model of SIP. Combined with the SIP model, the overlaid video informs the learners about polyurethane foam’s thermal insulating properties, high resistance to water absorption, low moisture permeability, and reasonable mechanical strength. As learners watch this video while observing the SIPs in the physical space, assessments appear in the form of multiple choice questions (see Fig. 6a and b) and design prompts (Fig. 7) to afford a deeper understanding of how this concept functions within the design of sustainably engineered residential housing. Analyzing this example, the concepts and explanation of the SIPs comprise the explanatory or SPS elements that are assessed through multiple-choice questions focused on specific information. At another level, a probe into the design and functionality of SIPs required an interactive experience that was enabled by

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Fig. 6 (a) SIPs explanatory assessment. (b) SIPs sequestered problem solving

Fig. 7 SIPs experiential or PFL assessment

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experiential or PFL elements through the design-prompt where learners responded by assembling the SIP panels. This example of technology-mediated assessment indicates that the learners’ situated interaction of seeing the actual SIP bricks, holding them in their hands to feel the material and to stand in a house with walls made of SIPs enriched their understanding of the passive solar design. The combination of explanatory and experiential assessments inserted in the augmented video mediated their learning of the concept in its design dynamics.

8

Future Directions

This chapter proposes CLAD as a pedagogical solution that addresses disconnect between formal and informal learning experiences through technology-mediated assessments. Particularly, GreenDesigners as an example of CLAD combined explanatory (SPS) and experiential (PFL) elements through the three design elements, i.e., placebased, technology-driven, and curriculum-focused. As a future enterprise, this proposal could be further evaluated by designing and implementing CLADs in other subject disciplines, with other technologies and other standardized curricula. For example, a CLAD focused on a specific aspect in Math education is expected to operationalize and inform the design framework differently. Same would be true for a CLAD that lends itself to a different kind of mobile technology. With mobile technologies becoming more potent and efficient yet cost-effective, the technology-driven design frame can be operationalized through VR and more advanced three-dimensional Augmented Reality (see also ▶ Chap. 75, “Augmented Reality and 3D Technologies: Mapping Case Studies in Education”). Moreover, virtual or online CLADs can also be the future of architectural or engineering design education where 3D models of built and landscape architectural designs are used in lieu of the physical spaces. Such variations could offer further empirical insights on coordinating formal and informal learning experiences (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”).

9

Cross-References

▶ Augmented Reality and 3D Technologies: Mapping Case Studies in Education ▶ Characteristics of Mobile Teaching and Learning ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts ▶ Mobile AR Trails and Games for Authentic Language Learning

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Adapting to Change: A Reflective History of Online Graduate Certificate and Its Implications for Teaching Geography

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Historical Background to the Graduate Certificate in Climate Change Adaptation . . . . . 3 The Instructional Module: An Interactive PDF Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Postdelivery Reflections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 The Production of Content: The Interactive PDF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Institutional Support for Online Initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Workload Realities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 External Influencers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Those teaching in higher education are increasingly under pressure to develop skills in online technologies to facilitate learning and ultimately improve graduate outcomes. In so doing, multiple trials are occurring internationally to develop online, hybrid, and blended learning programs. Ensuring that curricula are designed to be responsive to student needs is essential, as this will encourage the long-term sustainability of student learning. The planet is also facing an environmental crisis of unprecedented proportions, and the development of appropriate curricula is an ongoing task for those in disciplines like geography, environmental science, and

M. Nursey-Bray (*) Department of Geography, Environment and Population, Faculty of Arts, University of Adelaide, Adelaide, SA, Australia e-mail: [email protected] R. Palmer Department of Media, Faculty of Arts, University of Adelaide, Adelaide, SA, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_99

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other disciplines. Graduates are needed who will be able to respond to the more recent and unprecedented environmental crises. This chapter provides a reflective history of the development of an online Graduate Certificate in Climate Change Adaptation, at the University of Adelaide in between 2010 and 2017, and its implications for teaching geography and other related disciplines in Australia. The chapter contends that there is a major place for online curricula and methods of teaching and learning but that it must be accompanied by institutional support, recognition of workload implications, and investment in skills development and be cognizant of wider political and social factors.

1

Introduction

Increasingly, people teaching in higher education are under pressure to develop skills in online and mobile technologies to facilitate learning and to improve graduate outcomes (Palloff and Pratt 2013) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Consequently, there is enormous growth in the number of courses and trials taking place across the world to develop and implement online, mobile, hybrid, and blended learning programs (Allen and Seamen 2016) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Ensuring that curricula are designed to be responsive to student needs is essential, as this will encourage the long-term sustainability of student learning. This observation is confirmed by a student survey that found that students want interactive lectures and group-based activities and are, in general, nonresponsive to conventional modes of formal lecture and tutorial programs (Sander 2000) (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). In this context, online learning offers great capacity for building flexibility in the pace and distribution of learning (Chinyio and Morton 2006, p. 74). By creating greater flexibility, some tertiary institutions also see online learning as a way of increasing student enrolment numbers, thereby maintaining and growing incomes at a time when governments around the world have reduced tax payer contributions to the sector (Bebbington 2017). However, interactive and online delivery must be underpinned by pedagogical intent (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). As Alexander and McKenzie (1998) note, technology in and of itself does not result in improved quality or productivity of learning, what is most critical is the curriculum design of the student learning experience. Rich et al. (2000, p. 264) argue this is an important gap noting the “paucity of educational and pedagogic underpinnings of the developments made in the use of [information and Communication Technologies] ICT to teach geography.” Building on this, Kirkwood and Price (2005, p. 257) add: Although ICTs can enable new forms of teaching and learning to take place, they cannot ensure that effective and appropriate learning outcomes are achieved. It is not technologies but educational purposes and pedagogy, that must provide the lead, with students understanding not only how to work with ICT but why itis of benefit for them to do so.

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From the perspective of teaching geography, these types of pedological concerns are enhanced by claims that online delivery also threatens the essence of what it means to be a geographer, that is, a professional who connects real people with real places (Ritter 2012). Therefore, it is the exploitation of ICT for “rich pedagogical use” that will serve both teachers and learners across multiple target groups and at various tertiary levels. Ensuring best practice in the use of educational technology will also ensure the versatility of teaching geography in higher education. Geography, in its investigation of the relationship between people and the environment, is by its very nature interdisciplinary and as such particularly suited to a suite of learning tools in curriculum delivery (Martin and Treves 2007). Indeed, as a discipline, geography “has always been considered a pioneering discipline in this regard” (Conceicao and Lehman 2010, p. 377). As Lynch et al. (2008, p. 137) note of online learning in geography: Using information technology effectively allows students to grapple with real-world problems, access appropriate information quickly and easily, share their ideas with fellow students. . .and construct new knowledge and meaning for themselves in a relevant interesting context.

Additionally, students studying geography at a tertiary level are often from diverse cultures and live across many different places. There is an increasing need to be inclusive of their different interests and capacities and to find ways of encouraging students to interact with each other despite this cultural and spatial differentiation (Joyce et al. 2014; Koenig 2000). Online learning moreover is often attractive due to the perception that it is “environmentally friendly” delivery. In this context, Lemke and Ritter (2000) said disciplines such as geography need to embrace these expectations by provision of new and innovative curriculum design. Or as Clark and Wilson (2017) note, online learning has huge potential to internationalize geography curricula. This challenge was the starting point of this chapter, to investigate if the online Graduate Certificate in Climate Change Adaptation delivered at the University of Adelaide, Australia, is a viable mechanism to deliver online, long-term, and sustainable learning environments in the discipline of geography generally. While the chapter draws on student feedback obtained via institutional evaluation mechanisms, and unsolicited peer feedback, the chapter is based on an application of critical reflection as a research method. This method is “an overall process of learning from experience, with the express aim of improving professional practice” (Fook 2011, p. 1). It allows teachers to actively reflect and build on their pedagogical practice as it evolves. It also uncovers deeply held assumptions and reveals any existing or embedded power and other relations between the practitioner, the student, and the curricula. In so doing, it becomes clearer what is working and what isn’t. This reflective process has added value when developing a course such as this one, which was characterized by small numbers and thus facilitated deeper engagement with the learners.

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Part of this engagement required application of the “art of noticing” or as Ash and Lombana (2012, p. 29) assert, a process where “increasingly reflective practitioners and teacher researchers, can learn to both ‘notice’ learners in new ways and respond to these learners with flexible scaffolding rather than with predetermined disciplinary content, scripts or standardized questions.” In this chapter, the aim of the critical reflective practice was to understand (i) whether mobile tools can assist geography educators to making learning enjoyable while complementing traditional modes of learning, (ii) whether online learning can operationalize problem-based learning effectively, and (iii) if online delivery can facilitate interdisciplinary learning. In concluding, reflections highlight that online delivery can become an integral component not just of the curriculum framework not only for wholly online courses but any geography course, whether it is hybrid, blended, or face-to-face.

2

Historical Background to the Graduate Certificate in Climate Change Adaptation

Climate change is a key public policy issue at multiple levels, including health, environment, and social planning (Gerber 2014). Governments are responding by establishing climate change departments, and local governments across Australia are implementing risk assessment and climate change adaptation planning frameworks (see Government of South Australia 2012 for an example of a climate change adaptation planning framework). Climate change is having impacts upon agriculture (Kingwell 2006), biodiversity, fisheries (Nursey-Bray et al. 2012; Pecl et al. 2009; Hobday et al. 2006), tourism (Turton et al. 2010; UNWTO 2008; Wilson and Turton 2009), mining, and ports and shipping (Nicholls et al. 2007; Nursey-Bray and Miller 2012) sectors in Australia. Many organizations have instituted climate change policies. Sea level rise is affecting residents across coastal settlements, both here in Australia and worldwide (CSIRO 2002; Gurran et al. 2008). In this context, professionals working in all of these areas are being required to develop climate change knowledge/expertise on the job. Further, as a career option, having a specialization in climate change adaptation will add value to the resume and improve the employability of graduates. However, in Australia in 2010 (This chapter offers an opportunity to see what happens to a program over time.), when the program was first mooted, there were very few options to formally qualify in climate change adaptation and management (as against climate change per se). Indeed, at the time of writing this chapter (2017), there is still only one other course in Australia that offers such a qualification. Due to this paucity, the authors of this chapter applied and were successful in obtaining funding from the Government of Australia, to develop climate change adaptation curricula for professionals. To understand fully what skills and knowledge professionals (especially in the fields outlined above) would need from such curricula, market research was conducted during 2011 to (i) obtain community feedback on desired content and (ii) seek community feedback on modes of delivery.

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Results showed high demand for a qualification in climate change adaptation, but a preference for online offerings due to the work commitments of potential students. The result was the development of a four-unit, 100% online Graduate Certificate in Climate Change Adaptation, a postgraduate qualification delivered through the discipline of geography, within the Faculty of Humanities and Social Sciences, University of Adelaide, Australia (see Table 1 for an outline of the course structure). The course commenced in mid-2013. All units are offered each semester, and they can be taken full or part time. After the first delivery to a cohort of student, each unit of study was formally evaluated by three stakeholder groups and a curriculum expert. The results of the evaluation were incorporated into an amended curriculum with the final instructional modules constructed as a series of interactive PDFs. The course has now been delivered for over 4 years (between mid-2013 and mid-2017). The mode of delivery has been 100% online with interactive pdfs.

3

The Instructional Module: An Interactive PDF Model

To date, although interactive PDFs are used in advertising and other contexts, like platforms for online magazines and newsletters, their deliberative use as part of curriculum design, or even as a technological tool, has been minimal, and there is very little to be found either in the literature or case studies about this. An interactive PDF is a virtual document that allows the user to “click” and be taken to other information sources simultaneously and concurrently with the document being read. For example, images, video, audio, and other information elements can be built into the document that encourages vibrancy to the user experience. For example, rather than citing a reading, an interactive PDF may have a photo of the author, and the student can “click” on the photo, and the relevant reading (by that author) will “pop” up in another window ready for the student to read. Unlike other interactive tools, such as “Activate,” an interactive PDF is not akin to a wiki or virtual web site. It can be uploaded to a platform like Blackboard and accessed online, but also, it can be downloaded directly to a student’s computer to read at other times offline. A tool interactive PDF encourages student-centered learning and offers important versatility for geography and sustainability courses (Lynch et al. 2008). Importantly, interactive PDFs enable the teacher to embed media such as video or audio in the actual document allowing the student to watch or listen to a prerecorded lecture – in which case, it can be viewed either in a new window, online via a link, or as a “talking head” within the PDF itself. For the Graduate Certificate in Climate Change Adaptation, there is an interactive PDF for each unit. The PDFs perform many functions, such as a study guide, by which students chart their progress, and enable students to undertake much of the learning independently. The PDFs include embedded links to online resources such as YouTube videos, a mini-lecture series recorded specifically for the course, sets of readings, case studies designed to enhance problem-based learning, and a series of interactive online activities. They allow integration of knowledge sets and data

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Table 1 The graduate certificate in climate change adaptation Unit name Introduction to climate change adaptation

Identifying risks and vulnerabilities

Adaptation options for management

Communication and evaluation of climate change adaptation

Description This unit introduces students to what climate change adaptation is, the legal and policy requirement for professionals working in the field, and the science underpinning it. The unit aims to develop student skills in accessing and synthesizing the most up-to-date information on law, policy, and science relevant to climate change adaptation. The unit will also equip students with an understanding of the concepts used in the field of climate change adaptation Conducting a vulnerability or risk assessment is a complex exercise, and usually, depending on the scale involved, one requires input from many fields of expertise. It is also an exercise that is conducted in many ways. Such assessments help to (i) identify specific areas of the community/sector that are vulnerable to climate change impacts and (ii) prioritize which of these are most important regarding management and (iii) therefore which adaptation option is the most appropriate. This unit aims, via a series of case studies and interactive assessments, to develop students skills in and knowledge about what types of decisions are needed and what types of processes must be implemented to assess risk and vulnerability to climate change An effective response to climate change includes mitigation and adaptation. This unit aims to introduce the student to the wide array of adaptation options that are being implemented globally. This includes mitigation programs as one end of the adaptation continuum, but the unit focuses on adaptation in the broader sense. Theoretical, technical, policy, sector-based, and many other types of adaptation are covered Developing communications strategies is a critical component of the adaptation debate. This will enhance the uptake of adaptation and acceptance of the need for mitigation. In this unit students will learn why communicating climate change is difficult and using case studies be able to describe the communication process, how to relate to target audiences and the key communication issues, and how to implement a six-step process to writing a communications plan. Finally, knowing if your chosen adaptation option is working, the communications program needs to need include an evaluation component. This unit will provide students with skills in using certain evaluation techniques

which also help to enhance different assessment strategies. For example, the online interactivity enables students to access different types of knowledge (e.g., Indigenous) as well as different ways of presenting climate knowledge (virtual, visual, aural, oral, etc.). In turn, this gives students a richer data base from which to

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complete and use in various assignments, as well as be creative in terms of how they present their learning. The modules enable students to move out of conventional essay and primarily written assessment modes. The interactive PDF also creates a visually appealing experience that aims to enhance the learning experience. Multimedia resources are proved to be efficient in online and mobile learning too (see ▶ Chap. 27, “Tutors in Pockets for Economics”). The interactive PDFs aim to extend beyond being a technological application, but to also enhance and be part of the overall curriculum design. Once students start using the PDF, all other learnings and interactions (via a diversity of fora) are also facilitated, including the minor and major assessments that are set as part of the course. While the aim was to adopt the PDFs as instructional tools to replace the conventional delivery receipt model of teaching and learning, it was intended that it would occur in a way that still required the student to invest in what would be the equivalent hours of learning per week if doing the course face-to-face. To do this, two strategies were implemented. The first was to chunk the interactive PDF into weekly releases, so instead of publishing it as a single virtual document at the start of the course, it was released in parts for the duration of the program. The second was to operationalize a problem-based learning (PBL) pedagogical framework for teaching climate change adaptation. In PBL the modules are constructed around problem scenarios rather than subjects or topics. In other words, the PDFs were used as a means by which to “involve the student in active learning” and therefore achieve “enhanced understanding” (Pawson et al. 2006). PBL is particularly suited to the discipline of geography as it is a way to construct curriculum in ways that confront students with real-life social and environmental problems from practice and thus are a stimulus to learning. Further, PBL is a technique that helps students learn how to learn. For example, in Unit 3 (Adaptation Options for Management), rather than deliver information about adaptation, students were presented a scenario where asocial sector or organization faces specific climate challenge management issues and then asked to solve these problems, by an application of knowledge. In Unit 2 (Identifying Risks and Vulnerabilities), students are set a scenario, with a series of challenges, which they are then asked to solve by conducting a risk assessment. PBL also allows for flexibility, where students can either choose a set scenario or work in a group or with the lecturer to refine a problem-based scenario that aligns with their work. Such exercises hone student problem-solving skills, but also demonstrate range and depth of understanding about adaptation. In using real-life scenarios, students are engaged with authentic situations. To date, results highlight that where students are full-time employed, the use of problem-solving and flexibility in choice of topic means many students actually apply their learning to current work issues/contexts, thus enhancing problem-solving in practice. One student, for example, developed a risk assessment for the port where she works. Through her analysis and approach to undertaking the assessment, she was able to build depth of knowledge about the climate change issues facing the port by learning how to apply risk techniques for that case study.

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Geography and climate change are both interdisciplinary topics and as such do not respect academic boundaries. Therefore by using PBL as the pedagogical construct of the PDFs, the graduate certificate also provides students with an opportunity to build collaboration across different disciplines and knowledge sets. Any of the exercises described above require students to go beyond their own disciplinary orientation to engage with others to solve problems. They do not need to be location based and can be undertaken by students anywhere in the world. As Pawson et al. (2006, pp. 105–106) note: “Such experiences are said to enhance means of managing or synthesising knowledge or of learning how to learn rather than attempting to assimilate content before employment”. For geography students the ability to learn as self-starters in new situations is clearly vital.

4

Postdelivery Reflections

Since its inception, only six students have completed all four units and graduated with the full graduate certificate. An additional 11 students have taken units of the course as an elective as part of either a Masters of Environmental Planning and Management or a Masters of Planning degree. This is a disappointing result for the work and consultation that was put into establishing it and necessitates deep reflection as to why this has happened. This begs the question of what and why did this course not take off given the market research indicated strong demand for it? Is it something to do with the subject matter and political changes to the issue of responding to climate change in Australia? Did the online format/content not work? Did the fact it was delivered via a university institution “put off” staff from some sectors we canvassed? Did the market research get it wrong? Or is it due to the costs of studying the graduate certificate at the University of Adelaide? In critically reflecting on this program, many insights were gained which provide lessons for the development and implementation of the online Graduate Certificate in Climate Change Adaptation. These lessons are instructional for other practitioners who may also be trying to develop and implement online learning pedagogies. The following sections provide a reflection of some of these lessons and include suggestions for what others can do to improve online learning as well as reflections on what was trialed within this program.

5

The Production of Content: The Interactive PDF

The first question to address is whether the course itself, in terms of content and delivery, has failed in some way. Upon review, overall, student feedback about the use of interactive PDFs as instructional tools has been very positive, most particularly because they have enabled students to (i) apply their own knowledge to familiar

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contexts and (ii) access a wide array of teaching and learning styles and information and (iii) by being constructed in a familiar PDF format are not seen as “too tricky” to use. In being able to download the PDF to use offline, students were also able to study on their own time, without web or the academic institution dependencies. However, they are not without challenges: interactive PDFs are often very “heavy” – their multi-megabytes mean that students cannot always download them depending on their allowed usage per month from their provider. In the initial stages, this was complicated by the fact that units were uploaded as just one PDF, and this was not only prohibitive for most students to download (i.e., it took so long to upload the computer that would time out), but also mitigated against effective learning. Further the multitude of programs, computers, and online devices students used to access the PDFs meant that a proportion of them found their systems to be incompatible with that of the university. This was a problem for the instructors, who had little control over the choice of device that students use. It remains an ongoing issue and one that needs to be resolved by building relationships internally, beyond disciplines, and with professional staff. Students also made a series of incorrect assumptions about the interactive PDFs and their purposes. For example, students tended to launch into the PDF without reading the initial introductions assuming it was more like a set of readings rather than the mechanism that operationalized the learning per se. This meant that students underestimated the work in the guide and then got behind later in the semester. Issues like this highlight the need to be more focused at the commencement of the graduate certificate to explicitly introduce each student to the purpose and workload contained within each interactive PDF. Consequently, an instructional lecture was recorded that told students how to use the interactive PDFs. Moreover, each PDF is now delivered via adaptive release and thus helps the students get more of a sense of the work each PDF entails and, importantly, how to pace their learning so it occurs continuously rather than in one rushed concentrated burst at the end. Further, while original deadlines for submission of the activities embedded within the guide were end of term, this was revised to be staggered over three dates during the whole term. Another lesson lies in the realization that instructions within the PDF about how to complete assessments were not clearly expressed. Students wanted more explicit instructions on how many words/sentences to write for each task. Similarly, amendments to the level of detail in each of the units PDF were undertaken to address concerns that students were getting too overwhelmed with the amount of information presented. Further, teaching strategies had to evolve to encourage a more balanced approach to study because in a flexible learning environment, it emerged that students often overdid and over worried about all the exercises, even if they were small and of less value to the overall successful completion of the certificate. In accessing different web links, different students could access them to different degrees, and not all students could access all links 100% of the time which impeded many elements of ongoing learning. This was due to links moving or disappearing altogether from the Internet or because different browsers provide varying degrees of user experiences. Therefore, before the release of an interactive PDF, each link to other resources had to be checked and changed where necessary. This process of link

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checking was also found to be useful for the teaching of climate change adaptation because the volume of new works produced on a yearly basis is immense and therefore enhanced the learning outcomes.

6

Institutional Support for Online Initiatives

Faculty support is another crucial element pivotal to the long-term success of online programs (Samuel 2016; Betts 2009). In this case, disconnection between the departmental operational delivery and the layers of institutional support and discourse about online learning occurred. For example, there was disconnection between the levels of IT support offered institutionally for “homegrown” initiatives such as this course. This was not deliberate, but was caused by role differentiation within university bureaucratic structures; IT staff focus on whether or not their online teaching (Blackboard/Canvas) system works; curriculum staff examine design issues. IT staff also focused on whether students can access the course, while the instructor focused on making the platform “look good” and support deep engagement with the curricula. Further the IT and the instructor focus modes are often mismatched. Therefore, finding support that would assist teachers to enhance the delivery of the course remains an ongoing challenge because staff who could help do not see support of the graduate certificate as part of their day-to-day responsibility. Another factor influencing the evolution of the program was the fact that the discourse around online learning and pedagogies at the University of Adelaide was incompatible with the type and design of the graduate certificate. This was due to two key factors. Firstly, in 2014, the University signed a contract with edX, an international online learning company, who then worked in partnership with high level decision-makers to design and then deliver a series of massive open online courses (MOOCs). MOOCs remain at the heart of how the University envisages itself as a leader in online technologies. This meant that unless the course itself became a MOOC of sorts, it would remain in the background, as it does not fulfill the criteria for the type of online learning programs that are being invested in. A second factor constraining the course is the pricing structure of the University. If a course is classified as 100% online, the price is much higher: one unit within the certificate is costed at over AU$3000, whereas most subjects in the same faculty delivered faceto-face are costed at approximately half of that. This had an impact on enrolments from the very beginning – from over 200 genuine enquiries, there were only 3 people in the first intake, and many prospective students sent emails expressing disappointment at the course price.

7

Workload Realities

The increase of enrolments by students in online courses has meant that staff are under increasing pressure to teach online (Allen and Seaman 2014). Ongoing workload tensions combined with specific role differentiation is another factor to

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consider when developing an online course. The pressure on academics to teach, and simultaneously learn the new skills required to teach in such different ways, means there is an ongoing tension between their teaching and practice, particularly in the context of demands to deliver innovative cutting-edge online curricula, whether for fully online courses or as part of hybrid, blended learning scenarios. Finding ways to recruit and then sustain staff involvement in online teaching is challenging (Green et al. 2009). Indeed: In order for online courses to be effective there needs to be appropriate training and support for both teachers and learners as they develop new strategies in response to new technologies for learning. (Westbrook 2006, p. 480)

As noted earlier, as high student numbers (rather than numbers of courses delivered) are what “counts” in current teaching regimes, it is simply not possible to constantly navigate the learning of new technology skills, manage the subsequent delivery of online courses, as well as deliver other face-to-face courses. In this case, the work required to maintain the units, combined with the small student numbers, meant that the workload on the staff was disproportionately heavy, and in fact they had to take on extra teaching to make sure they met their required work load and key performance indicators. Teaching the online units in this program was perceived as a “privilege” or indulgence in teaching a “vanity course,” a privilege moreover that had to be worked for, and was not recognized as a viable activity in and of itself. While, in this case, it was possible to initially resource a curriculum expert, who as an integral member of the team could build the PDFs, not everyone is so lucky. This begs the question of how teachers are to find the time, resources, and expertise to build imaginative online curricula within individual institutions. Staff need to be incentivized to participate, or as noted by Conceico and Lehman (2010, p. 7): “If instructors become aware of what it entails to teach online, from design to delivery, and try to prioritize their online teaching workload in relationship to their other activities, they can become more efficient and effective in their position and personal life.”

8

External Influencers

Given the course content, it is also worth reflecting on how wider political environments can impact student demand. This case study is illustrative as it took place in a period of intense political interest in the issue of climate change in Australia. In 2009, when the grant to develop the course was allocated, professional and political institutions, particularly local government, were actively seeking ways to build policy in this area and therefore were receptive to the idea of a qualification which would help them attain this goal. At the same time, the Australian government established the National Climate Change Adaptation Research Facility (NCCARF) and funded a series of climate change adaptation research networks in several sectors

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including infrastructure, health, and marine environments, to name a few. This was because Kevin Rudd, the then Prime Minister of Australia, viewed climate change as the “greatest moral issue of our time.” However, since then, the political environment in Australia has changed dramatically, and institutions, such as local governments, have “done it anyway.” For example, in South Australia, local governments have developed regional climate adaptation plans, and the State has developed an award-winning State-based adaptation framework. These factors might have impacted demand for the graduate certificate as there is less perceived need for further professional training. Further, other institutions, such as Oxford University, have entered the climate change adaptation education market, by offering face-to-face intensives in the UK and diluting the already reducing demand from potential students. Hence, it is suggested that the wider political context can actually have a big impact on the ongoing feasibility of online courses such as the graduate certificate.

9

Future Directions

This chapter provides a reflective history of the development of an online Graduate Certificate in Climate Change Adaptation and its implications for teaching geography and other related disciplines at the University of Adelaide, Australia. In assessing whether online delivery can become an integral or ancillary component of curricula, it is argued while there is an important place for online curricula and methods of teaching and learning that it must be accompanied by institutional support, recognition of workload implications, and investment in skills development and be cognizant of wider political and social factors. In terms of future directions, there is still an urgent need for delivery of interdisciplinary geography curricula such as the Graduate Certificate in Climate Change Adaptation that target and encourage students to engage with the challenges of the environmental crisis in a critically reflective yet positive manner. The approach to teaching and learning described in this chapter is informed by this principle. It consciously moved away from conventional “deliver receipt” models of teaching to a more iterative, collaborative, and problem-based learning style that encourages students to teach each other via online interaction, as well as learn as part of the journey of doing an online course. Developing appropriate and powerful online curricula is a pedagogical challenge that is ongoing, and with advancements in mobile technologies and devices, future directions in geography education have the potential to cut across the limits of time and location (see ▶ Chaps. 79, “VR and AR for Future Education” and ▶ 33, “Mobile Education via Social Media: Case Study on WeChat”). Future courses need to ensure that geography students not only learn the content they need but build lifelong learning skills that will support them in the challenges they will face when employed in the real-world and in the environmental problems they will be asked to solve.

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Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Student Feedback in Mobile Teaching and Learning ▶ Tutors in Pockets for Economics ▶ VR and AR for Future Education Acknowledgments We would like to acknowledge the Department of Climate Change for the initial funding to develop the curricula; staff at the Australian Maritime College, University of Tasmania; the DVC Teaching Professor Quester, University of Adelaide (UoA); and staff within the Discipline of Geography, Environment, and Population (UoA) for their ongoing support of this initiative and the opportunity to deliver it. We would also like to thank all the students who have completed units in the Graduate Certificate in Climate Change Adaptation.

References Alexander, S., and J. McKenzie. 1998. An evaluation of information technology projects for university learning. Canberra: Department of Employment, Education, Training and Youth Affairs, AGPS. Allen, I., and J. Seaman. 2014. Grade Change: Tracking Online Learning in the United States. Wellesley MA: Babson College/Sloan Foundation. Allen, E., and J. Seamen. 2016. Online report card: Tracking online education in the United States. Babson Park: Babson Survey Research Group from http://www.onlinelearningsurvey.com/ reports/onlinereportcard.pdf. Accessed on 6 July 20Ash. Bebbington, Warren. 2017. Is the traditional research university doomed to extinction in a digital age? Times Higher Education from https://www.timeshighereducation.com/features/traditionalresearch-university-doomed-extinction-digital-age. Accessed 6 Jul 2017. Betts, K. 2009. Online human touch (OHT) training & support: A conceptual framework to increase faculty engagement, connectivity, and retention in online education. Part 2. MERLOT Journal of Online Learning and Teaching 5 (1): 29–48. Chinyio, E., and N. Morton. 2006. The effectiveness of e-learning. Architectural Engineering and Design Management 2: 73–86. Clark, C., and B. Wilson. 2017. The potential for university collaboration and online learning to internationalise geography education. Journal of Geography in Higher Education 41 (4): 488–505. Conceicao, S., and R. Lehman. 2010. Faculty strategies for balancing workload when teaching online. In Presented to the 2010 midwest research to practice conference in adult, continuing and community education. Michigan State University, September 26–28 2010. CSIRO. 2002. Climate change and coastal communities. Victoria: CSIRO. Fook, J. 2011. Developing critical reflection as a research method. In Creative spaces for qualitative researching. Practice, education, work and society, ed. J. Higgs, A. Titchen, D. Horsfall, and D. Bridges, vol. 5. Rotterdam: Sense Publishers. Gerber, B. 2014. Climate change as a policy development and public management challenge: An introduction to key themes, risk, hazards & crisis. Public Policy 5 (2): 97–108. Government of South Australia. 2012. Prospering in a changing climate: A climate change adaptation framework for South Australia from https://www.nccarf.edu.au/localgov/ resources/prospering-changing-climate-climate-change-adaptation-framework-south-australiaaugust. Accessed 6 Jul 2017.

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Green, T., J. Alejandro, and A. Brown. 2009. The retention of experienced faculty in online distance education programs: Understanding factors that impact their involvement. The International Review of Research in Open and Distributed Learning 10 (3): 1–15. Gurran, N., E. Hami, and B. Norman. 2008. Planning for climate change: Leading practice principles and models for sea change communities in coastal Australia, National sea change task force report. Sydney: University of Sydney. Hobday, A.J., T.A. Okey, E.S. Poloczanska, T.J. Kunz, and A.J. Richardson. 2006. Impacts of climate change on Australian marine life, Report to the Australian Greenhouse Office. Canberra: CSIRO Marine and Atmospheric Research, September 2006. http://www.green house.gov.au/impacts/publications/marinelife.html. Visited 18 May 2013. Joyce, K., B. Boitshwarelob, S. Phinnc, G. Hilld, and G. Kelly. 2014. Interactive online tools for enhancing student learning experiences in remote sensing. Journal of Geography in Higher Education 38 (3): 431–439. https://doi.org/10.1080/03098265. Kingwell, R. 2006. Climate change in Australia: Agricultural impacts and adaptation. Australian Agricultural Review 14: 1442–6951. Kirkwood, A.T., and L. Price. 2005. Learners and learning in the twenty-first century: What do we know about students’ attitudes towards and experiences of information and communication technologies that will help us design courses? Studies in Higher Education 30 (3): 257–274. Koenig, G. 2000. Interactive education on the web – Experiences in development and application of a computer assisted training course for remote sensing. In International archives of photogrammetry and remote sensing. Vol. XXXIII, Supplement B6. Amsterdam. Lemke, K.A., and M.E. Ritter. 2000. Virtual geographies and the use of the internet for learning and teaching geography in higher education. Journal of Geography in Higher Education 24: 87–91. Lombana, J. 2012. Methodologies for reflective practice and museum educator research. In Putting theory into practice. New directions in mathematics and science education, ed. D. Ash, J. Rahm, and L.M. Melber, vol. 25. Rotterdam: Sense Publishers. Lynch, K., B. Bednarz, J. Boxail, L. Chalmers, D. France, and J. Kesby. 2008. E-learning for geography’s teaching and learning spaces. Journal of Teaching Geography in HigherEducation 32 (1): 135–149. Martin, D., and R. Treves. 2007. Embedding e-learning in geographical practice. British Journal of Educational Technology 38 (5): 773–783. Nicholls, R.J., S. Hanson, C. Herweijer, N. Patmore, S. Hallegatte, J. Corfee-Morlot, J. Ch^ateau, and R. Muir Wood. 2007. Ranking port cities with high exposure and vulnerability to climate extremes: Exposure estimates [online]. OECD environment working papers, no. 1, OECD Publishing. Available from: http://www.oecd-ilibrary.org Nursey-Bray, M., and T. Miller. 2012. Chapter 17: Ports and climate change: Building skills in climate change adaptation, Australia. In Climate change and the sustainable use of water resources, ed. W. Filho, 273–283. Heidelberg: Springer. Nursey-Bray, M., G. Pecl, S. Frusher, C. Gardner, M. Haward, A. Hobday, S. Jennings, A. Punt, H. Revill, and I. van Putten. 2012. Climate change risk perceptions colour a fisher’s world. Marine Policy 36: 753–759. Palloff, R., and K. Pratt. 2013. Lessons from the virtual classroom: The realities of online teaching. San Francisco: Wiley. Pawson, E., F. Fournier, M. Haigh, O. Muniz, J. Trafford, and S. Vajoczki. 2006. Problem-based learning in geography: Towards a critical assessment of its purposes, benefits and risks. Journal of Geography in Higher Education 30 (1): 103–116. Pecl, G., S. Frusher, C. Gardner, M. Haward, A. Hobday, S. Jennings, M. Nursey-Bray, A. Punt, H. Revill, and I. van Putten. 2009. The east coast Tasmanian rock lobster fishery – Vulnerability to climate change impacts and adaptation response options, Australia. Report to the Department of Climate Change. Canberra: Department of Climate Change. Rich, D., G. Robinson, and R. Bednarz. 2000. Collaboration and the successful use of information and communications technologies in teaching and learning geography in higher education. Journal of Teaching Geography in Higher Education 24 (2): 263–273.

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Ritter, M. 2012. Barriers to teaching introductory physical geography online. Review of International Geographical Education Online 2: 1. Samuel, A. 2016. Online faculty development: What works? Adult education research conference. http://newprairiepress.org/aerc/2016/papers/36 Sander, P. 2000. Researching our students for more effective university teaching. Electronic Journal of Research in Educational Psychology 5 (3): 113–130. Turton, S., T. Dickson, W. Hadwen, B. Jorgensen, T. Pham, D. Simmons, P. Tremblay, and R. Wilson. 2010. Developing an approach for tourism climate change assessment: Evidence from four contrasting Australian case studies. Journal of Sustainable Tourism 18: 429–447. UNWTO-UNEP. 2008. Climate change and tourism-responding to global challenges. Spain: World Tourism Organization and United Nations Environment Programme. Westbrook, V. 2006. The virtual learning future. Teaching in Higher Education 13 (4): 471–482. Wilson, R.F., and S.M. Turton. 2009. The impact of climate change on reef-based tourism in Cairns, Australia – adaptation and response strategies for a highly vulnerable destination. In Keys to the disappearing destinations: Climate change and the future challenges for coastal tourism, ed. A. Jones and M. Phillips. Wallingford: CABI.

Part VI Expectations from Future Technologies in Higher Education

Expectations from Future Technologies in Higher Education: An Introduction

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1061 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1065

Abstract

In the past few decades, the internationalization of higher education has become an increasingly popular trend across different parts of the globe. It can be observed that universities and colleges have been accommodating the innovative trends in teaching and learning to keep in mind the future prospects of higher education. They facilitate their learner to survive in this ever-changing world. They thoughtfully incorporate innovations and have faith in educational technologies – in curriculum and instruction, labs, assignment design, libraries, support services, and more. In this section, eight chapters have been incorporated. All the chapters reflect distinguish features of emerging trends and learning devices of teaching and learning. All the chapters advocate unique learning style as the need of the present hour and recommend engaging with the latest developments and how they shape the future of our children.

1

Introduction

Globalization and technological advancements present several social, economic, and environmental challenges. Together, these challenges offer countless expansive and innovative opportunities. Teachers can access classrooms through digital screens, K. Pandey (*) Department of B.Ed./M.Ed., Faculty of Education and Allied Sciences, MJP Rohilkhand University, Bareilly, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_30

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allowing accommodations for unique learning styles. Several technology and learning studies revealed that this integrated approach significantly enhances student achievement and teacher learning, but only if it is used appropriately (Dede 1998). The education network needs to collaborate with innovative technology to transform pedagogy and create such an environment, where students can learn by doing, receive feedback, and continually refine their understanding and build new knowledge (Barron et al. 1998; Bereiter and Scardamalia 1993; Hmelo and Williams 1998; Kafai 1995; Schwartz et al. 1999). Technology provides a means for student reflective thinking to construct their knowledge. To prepare students for twentyfirst century skills and raise demand of metacognitive skills interlaced with technology, higher education must be part of the solution. Technology-oriented learning tools are providing a foundation for creative and effective use of knowledge and digital competencies. In higher education, educators can inspire students to accept advance mobile devices as learning tools. To accomplish this vision, it is required to move away from traditional learning and replace it with needs based on reflective learning that encourages twenty-first century skills. Across the world, there are myriad of teaching and learning digital devices currently used. Educators need to implement innovative approaches, assisted by digital technologies. Mobile devices are a necessary learning tool that can change the concept of learning: when, where, and how to learn in higher education. Mobile learning incorporates numerous smart devices meeting learners’ expectations. This approach includes various wired and wireless devices offering ubiquitous systems so that learners can learn from multiple sources anywhere and at any time. Mobile learning allows for cloud teaching where access to people, resources, and information will float freely regardless of location (Sutch 2010). Several higher education organizations are increasing enrolment by implementing mobile technology to reach a broader range of students, for example, targeting different age groups who will be able to access course materials anywhere and anytime (Lowenthal 2010; Ally and Prieto-Blázquez 2014). Mobile learning has the capacity to facilitate equal opportunities for all students by permitting learning beyond the time, location, and learning style. Mobile learning can sustain quality in teaching and learning with in a structure of an interactive and hybrid global education model. In order to achieve the higher order interactivity, reflective engagement, and deep learning, it is essential to keep pace with emerging innovations in higher education. With higher education social, political, and academic support to adopt mobile learning interventions, mobile leaning has the potential to transform educational opportunities and outcomes for educators and learners. Mobile learning can transform higher education learning by acting as a catalyst for constructing significant transformation. In this part, “Expectations from Future Technologies in Higher Education” the author described learning through smart devices in hybrid learning environments. Mobile learning has the capability to enhance interactivity and deep learning to secure their place in the globally competitive economy. This learning approach can serve educational opportunities across the world and collapse classroom walls. Empirical studies, chronological evolution of technological learning devices,

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graphical presentation of technological evolution, mapping case studies, and emerging trends with technology make this section more relevant. The authors recommended emerging technologies such as image retrieval technology, u-learning, and big data analysis as future markers for educators, learners, administrators, and policymakers. ▶ Chapter 63, “Expectations from Future Technologies and E-Learning in Higher Education in Albania” by Nikaj focused on the role of government policies to generate a collaborative platform for all stakeholders. This study revealed the effect of Albanian network readiness in relation to socioeconomic and cultural aspects. The authors described the transformation of the Albanian Higher Education digital system. The chapter highlighted the future challenges facing Albanian Higher Education institutional autonomy and good governance of higher education institutions; the curriculum reformation in accordance with strategy of higher education and national priority; pledging quality assurance and a fair accreditation system as a guarantee to the service rendered to the society; integration of the teaching process via scientific research; preparing the conditions for lifelong learning; increasing student mobility and participation; and providing the higher education system better teaching and learning pedagogy through new technologies and e-learning. ▶ Chapter 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning” by Dr. Wang and Dr. Zhang introduced an emerging concept of advanced retrieval mobile teaching and learning technology. The authors suggested how this advanced technology improved learning efficacy. They suggested smart mobile devices could augment learning in various disciplines, i.e., content-based image retrieval has been used in outdoor ecology learning. Image retrieval technology usage is shifting from the traditional bag-of-features model to the more advanced deep learning model. Image retrieval technology can expand the scope of its applications in mobile teaching and learning increasing the quality of these applications to a new level of learning. ▶ Chapter 61, “M-Learning: Visible Approach for Invisible World” authored by Dr. Kshama Pandey reveals the status of marginalized Indian people waiting to acquire education. This often forgotten population is disconnected from the mainstream and not recognized as a part of society. The author discussed the educational status of higher education in India. Even though India has achieved almost 100% access to school for its children at the primary level, 40% of students drop-out at the elementary level. These students are members of the jobless population, with the majority having access to mobile phones. The chapter recommended mobile learning strategies, so these people can access education and improve their wellbeing and quality of life. In ▶ Chap. 64, “Mobile Technologies and Learning: Expectations, Myths, and Reality,” Lina Petrakieva discussed the myths and expectations of mobile learning. She describes the term “digital natives” as a myth, indicating there are more nuances in the skills, abilities, and attitudes of the learners. However, many institutions are equipping their teachers and students with advanced learning tools without understanding and utilizing the potential of these mobile devices. The author advocated the paradigms of mobile learning with reference to the learner, the educator, and the

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environmental perspectives by examining the learning taking place and the learner analytics. The researcher revealed that the learner analytics data could prove beneficial for institution and triggering intrinsic motivation for the learners. The chapter recommended that learning with mobile devices requires a more developmental pedagogical approach from the educators and more engagement and positive attitude from the learners. ▶ Chapter 68, “How Irish Postgraduate Students Use Mobile Devices to Access Learning Resources” is authored by Ann Marcus-Quinn and Yvonne Cleary. This chapter provided an analysis of the advantages and limitations of mobile learning in online and distance courses, and in a Virtual Learning Environment. The chapter explored how postgraduate students enroll in technical communication courses through hybrid environments, on-campus, and distance delivery modes exploiting mobile technologies. The results of this study indicated that there are mobile application needs and user gap between learners and instructors. Over half of the respondents accessed a variety of materials, in various ways, through mobile devices. The findings suggested an absence of policy for educators to ensure that delivery of materials matches learner expectations. ▶ Chapter 66, “Mobile Learning Beyond Tablets and Smartphones: How Mobile and Networked Devices Enable New Mobile Learning Scenarios” is authored by Stoller-Schai. This chapter presented emerging mobile and networked learning scenarios and a range of examples from schools, private sector, and public institutions. This chapter provided a description of the evolution of mobile and networked devices, which can be used to design, develop, and implement mobile learning scenarios in schools, businesses, and public institutions such as museums and libraries. The chapter illustrated the paradigm shift of mobile learning using a variety of mobile devices and present future possibilities beyond the devices currently used by educators and learners. ▶ Chapter 67, “M-Learning and U-Learning Environments to Enhance EFL Communicative Competence” is authored by Soraya Garcia-Sanchez1 and Carmen Lujan-Garcia. This chapter reflects the work of English as a foreign language (EFL) learners at the Universidad de Las Palmas de Gran Canaria. The authors hypothesized a unique design of mobile learning and u-learning. The authors integrated a context-aware ubiquitous learning environment with EFL communicative competence in two degree programs. The Doctor of Modern Languages (DML) degree focuses on developing student’s English communicative oral and written skills. In the Diploma of Telecommunications Engineering (DTE) degree, students learn English in the third year of their program. The data revealed the students’ written and oral expressions combined with the EFL skills improved in both degree programs by using the appropriate technology, content, and tasks. The outcomes revealed that the communicative competence and the foreign language skills improved by using the appropriate technology, content, and tasks that were especially adapted to digital students. ▶ Chapter 69, “Enhancing Student Learning Experience with Practical Big Data Analytics Techniques” is authored by Eric P. Jiang describing the design, implementation, and evaluation of two data analytics courses, “Introduction to Data

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Mining” and “Introduction to Artificial Neural Networks,” taken by students enrolled in the undergraduate computer science program at the University of San Diego (USD). Beginning in Spring of 2011, both courses were offered as upperdivision electives on a regular basis. The courses include data analytics concepts, principles, and applications, a unique student lecture series, programming projects, and research activities to engage students in active learning. A uniqueness of the courses is the ability for the students to have a data mining experience in a Chinese study abroad program. Guest lectures by data scientists from the host institutions and field trips to visit top information technology firms in China. The author’s experience demonstrated that big data analytics can be successfully taught to undergraduate students, enrolled in courses focusing on data analytics techniques applied to solve real-world problems. ▶ Chapter 62, “Problems and Challenges of Mobile Learning in Nigerian University System” is jointly written by Kayodo, Alabi, Sofoluwe, and Oduwaiye. The authors present a scenario of mobile learning in Nigeria. They discussed the features and benefits of mobile learning in the Nigerian university system. The authors focused on issues and challenges to teach students and educators the teaching and learning benefits of networks; like LinkedIn and Facebook, in a mobile learning context.

References Ally, M. and Prieto-Blázquez, J. 2014. Mobile Learning Applications in Higher Education [Special Section]. Revista de Universidad y Sociedad del Conocimiento (RUSC). 11(1): 142–151. https:// doi.org/10.7238/rusc.v11i1.2033 Barron, B.J., D.L. Schwartz, N.J. Vye, A. Moore, A. Petrosino, L. Zech, J.D. Bransford, and Cognition and Technology Group at Vanderbilt. 1998. Doing with understanding: Lessons from research on problem and project based learning. Journal of Learning Sciences 7(3-4): 271–312. Bereiter, C., and Scardamalia, M. 1993. Surpassing ourselves: An inquiry into the nature and implications of expertise. Chicago, IL: Open Court. Dede, C. 1998. Introduction. In Learning with technology, ed. C. Dede. Yearbook of the Association for Supervision and Curriculum Development (pp. v–x). Alexandria, VA: Association for Supervision and Curriculum Development. Hmelo, C., and Williams, S.M. (eds) 1998. Special issue: Learning through problem solving. The Journal of the Learning Sciences 7(3-4). Kafai, Y.B. 1995. Minds in play: Computer game design as a context for children’s learning. Hillsdale, NJ: Erlbaum. Lowenthal, J.N. 2010. Using mobile learning: determinates impacting behavioral intention. American Journal of Distance Education, 24(4): 195–206. https://doi.org/10.1080/08923647.2010. 519947. Schwartz, D.L., Lin, X., Brophy, S., and Bransford, J.D. 1999. Toward the development of flexibly adaptive instructional designs. In Instructional Design Theories and Models: Volume II, eds. C.M. Reigelut, 183–213. Hillsdale, NJ: Erlbaum. Sutch, D. 2010. Education futures, teachers and technology. Futurelab Report. http://www2. futurelab.org.uk/resources/documents/other_research_reports/Education_futures.pdf.

M-Learning: Visible Approach for Invisible World

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Educational Landscape in India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Dropouts: Invisible World Deprived from Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 M-Learning in Rural India: An Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Efficacy of M-Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Requisite of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 Principles of Designing Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 Mobile Learning Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 Features of Mobile Phone as a Learning Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 Digital Inclusion with M-Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Potential of Mobile Learning in Rural Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Suggestions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

With 16% of the world’s population, India is today the second largest populated country in the world. Future trends in global population growth could be significantly affected by improvements in both the quality and quantity of education, particularly female education. According to the UNESCO Report on Education in the twentyfirst century, higher education is the mandate to bridge the knowledge gap between countries and communities, enriching dialogues between people and culture, and international linking and networking of ideas, research, and technologies. On 2011 enrollment was only 207 lakhs for higher level. We can not supposed to education for K. Pandey (*) Department of B.Ed./M.Ed., Faculty of Education and Allied Sciences, MJP Rohilkhand University, Bareilly, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_26

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all because a huge population is still not able to reach basic education. Huge populations have mobile access in India. In India, total number of rural subscribers is 311.33 million in October 2014. Indian rural people are advanced in technology and there is a need to facilitate mobile as a learning tool. It has required a great motivation to achieve this target. In the future, we will witness mobile phones, computers, and various other computing/media devices (iPods, Digital Cameras, PDAs, etc.) we use converge into a single personal mobile computing device. At such a time, the differentiation between eLearning and m-learning will cease to exist; all learning will be electronic and mobile. Therefore, there is tremendous potential for the growth of mobile learning even in the invisible world.

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Introduction

Education is the prime mover of the society. It determines the role and approach for the modernization of society and the nation at large. Since “development” is the buzzword for the advancement of our nation, the quality of our education is of paramount importance along with access and equity to tap rich dividends from our demographic capital. We live in an ever-changing world. Higher education has to be assessed from a broader perspective in the context of various types of changes in the micro and macro environment. New technologies keep coming up and if you do not want to be left behind, you must keep up with the world that is moving fast. Integrating technology in education everyday helps students stay engaged. Today’s students love technology so they are sure to be interested in learning if they can use the tools they love. With technology, the classroom is a happier place. Students are excited about being able to use technology and therefore are more apt to learn. When mobile technology is readily available in the classroom, students are able to access the most up-to-date information quicker and easier than ever before.

1.1

Educational Landscape in India

With 16% of the world’s population, India is today the second largest populated country in the world. The world population is on the rise. In addition, America is working harder to maintain an educational system that ensures a proper education to every student, regardless of race or financial ability. Providing this education seems to be more difficult as time goes on, and there may be a direct correlation between the population growth and the educational difficulties. Future trends in global population growth could be significantly affected by improvements in both the quality and quantity of education, particularly female education. Education is essential for the growth and prosperity of both a nation and its society. Apart from primary and secondary education, higher education is the main instrument for development and transformation. Higher education has the omnipotent role of preparing future leaders for different spheres of life such as social,

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Table 1 Population census Year! Total population (in crore) Male Female

2001 102.80 53.20 49.65

2011 121.01 62.37 58.64

Source: MHRD, India (2011)

economic, political, cultural, scientific, and technological. According to the UNESCO Report on Education in the twenty-first century, higher education is the mandate to bridge the knowledge gap between countries and communities, enriching dialogues between people and culture, and international linking and networking of ideas, research, and technologies. Thus, higher education provides the competencies that are required in different spheres of human activity, ranging from administration to agriculture, business, industry, health, and communication, and extending to the arts and culture (Powar 2002, p. 74). In India, the growth of Indian higher educational system has undergone a remarkable transition from an elite system, having deep colonial roots, to an egalitarian system striving to meet the aspirations of a vibrant democracy. In India the growth of higher education is remarkable but there are still some gaps that deserve attention. We start from the total population of India as 121.01 crores (Table 1). It is evident from Table 2 that enrolment was only 1,356 lakhs for primary level, 594 lakhs for upper primary level, 482 lakhs for secondary level, and 207 lakhs for higher level. Census Data show that we can not supposed to education for all because a huge population is still not able to reach basic education.

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Dropouts: Invisible World Deprived from Learning

Dropout has been defined as the proportion of children that cease to remain enrolled in the schooling system. In 1993, 27 million children entered school in Class 1 in India but only 10 million (37%) of them reached Class 10 in 2003. Dropout rates peak in the transition between Class 1 and 2 and again in Classes 8, 9, and 10. Dropout rates have remained negative between Classes 4 and 5. The state of Pondicherry improved its performance concerning school dropouts from the fourth place in 1991 to the first in 2001, displacing Kerala as the best performing state. The states of Bihar, Jharkhand, Uttar Pradesh, and Arunachal Pradesh perform poorly in this ranking. India has seen a steady increase in primary school enrolment over the last decade – as of 2013, over 96% of rural Indian children of primary school age had enrolled in the schooling system, up from hovering around 80–85% in the early 2000s. However, many of these students leave – a UNESCO 2012 report shows that 13.54 million South Asian students leave school before completing their primary education. This problem presents in increasingly large proportions too – to take one

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Table 2 Level wise enrolment (in lakhs)

Year/level 1950–1951 1960–1961 1970–1971 1980–1981 1990–1991 2000–2001 2005–2006 2006–2007 2007–2008 2008–2009 (P) 2009–2010(P)

Primary (I–V) 192 350 570 738 974 1,138 1,321 1,337 1,355 1,345 1,356

Upper primary (VI–VIII) 31 67 133 207 340 428 522 544 572 554 594

Secondary/Sr. secondary (IX–XII) 15 34 76 110 191 276 384 398 445 455 482

Higher education 4 10 33 48 49 86 143 156 172 186 207

Source: MHRD, India (2011) P Provisional

state as an example, in 2013 over 14% of female students between the ages of 7 and 16 went missing from school in Maharashtra, as opposed to 11.7% in 2012. Thus, it seems that although the prevalent ethos and the legislation (including the Right to Education Act of 2008) in India nearly guarantees that every Indian student will start schooling, it does not yet have the abilities to ensure that the environment to actually attain an education exists. Dropping out of school is a worldwide phenomenon with drastic mental health consequences for children, families, and society. Every year, a large number of students drop out of school worldwide. A significant number of them go on to become unemployed, living in poverty, receiving public assistance, in prison, unhealthy, divorced, and single parents of children who are likely to repeat the cycle themselves. A huge number of our population is still invisible from main canvas. These marginalized students disappear from the real world and get involved with invisible world. We need to explore this world. Now the question arises that how these invisible people can access a quality education. The answer may be technology. We can adopt an advance cost effective technology for the education of this invisible world. Mobile learning would be the best solution for these marginalized students.

1.3

M-Learning in Rural India: An Overview

While scope of Mobile-learning is growing fast, it is imperative to address the problems of low level of literacy, limited understanding of English language in rural and semi-urban areas, and text-driven interface in order to reap the benefits of this technology.

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Table 3 Rural GSM subscriber Rural GSM subscriber figures, October 2014 1. Total number of rural subs as of October 2014 – 311.33 million 2. Rural subs net additions in October 2014 – 3.79 million with 1.23% increase from previous month 3. Maximum rural subs net additions in the month of October by Airtel – 1.66 million 4. Maximum rural subs addition in the month of October in Bihar – 0.79 million 5. Maximum rural subs – Airtel – 99.11 million 6. Maximum rural subs for the circle – UP (E) – 33.01 million Source: TRAI report (2014)

As per 2011 Census, India is recognized as one of the youngest nations with a majority of its youngsters entering the workforce by 2015. This has instigated the demand for a different kind of an education system that should be capable to fulfill the necessities of quality and quantity aspect of the education system. Hence it should such that increases the penetration of the education sector in remotest places and removes the barricades in quality education. It is evident from Table 3 that the total number of rural subscribers is 311.33 million in October 2014 and the number of subscribers has increased 1.23% from previous month. It shows that Indian rural people are advanced in technology and there is need to facilitate mobile as a learning tool. It has required a great motivation to achieve this target. The bull’s eye of completion for the different programs of Digital India is fiscal year 2016. The implementation of this program is a very rigorous process and seems very difficult to complete within duration. In these circumstances, mobile as a tool for learning is an easier and cheaper mode to educate millions of youth than a personal computer or laptop. According to Telecom Regulatory Authority of India (TRAI) Report and Census 2011, mobile dissemination in India is 76% in comparison to broadband, which is only two per cent. This further solidifies the view that mobile is more prime solution for intelligent young professional who wish to pursue education. However, meagerness of ICT infrastructure presents an enormous barricade. According to one of the estimates of TRAI during the coming year there will be an additional 200 million new mobile subscribers. This supports the research of wearesocial.net, that there are more than 898 million mobile subscribers in India, 292 million of these living in rural areas.

1.4

Efficacy of M-Learning

Mobile learning is not just a fashion. It is instead a transformative opportunity both for learning, and for the learning organization. Mobile learning supports formal learning, nonformal learning, and informal learning. Social learning is also enhanced by m-learning. The actual implementation of m-learning is growing faster in some capabilities than others. According to eLearning Guild research data collected from members

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worldwide, the use of m-learning for social networking and communication is more prevalent than it is for the development of custom applications, with 38.1% of organizations either implementing, designing, or building the business case for social networking and only 25.7% for custom application development. Of those who have conducted an m-learning implementation, 50% are seeing positive returns. Surpassing and increasing access to expanded educational opportunities for all students has long been an aspiration for policymakers, educators, and parents. In recent years, the government has emphasized the importance of mobile technology as a way for achieving this goal. Mobile technology can help connect teachers to students, parents, and free educational resources. Mobile technology also helps schools share classes, curricula, and other resources. The nation has made great strides toward connecting its educational infrastructure to high-speed internet, but the actual circumstances show that rural schools and communities have inadequate network coverage when compared with their nonrural counterparts. Inadequate connections for rural schools will become a growing problem for India if steps are not taken now – one fourth of all Indian students attend a rural school and in latest years rural enrolment growth has outpaced expansion in all other school locales. The availability of mobile network in the isolated area of the country enables to leverage the extensive use of technology through introducing modifications to the ecosystem of education sector through m-learning. Technology has only extended class room of urban schools, where it is again limited to computer labs and audiovisual rooms. With cultivating infrastructure, the Indian Education system is already making advances towards adopting the M-education (KPMG’s the Cloud: Changing the Business Ecosystem, 2011)

1.5

Requisite of Mobile Learning

Mobile is a powerful new tool for supporting organizational performance, including a wide-variety of learning opportunities including innovation, collaboration, research, and design. Mobile generates new products, services, and helps solve problems. Whether providing needed tools, augmenting learning, or connecting individuals, mobile devices are empowering individuals and organizations. M-learning solutions provide access to innovative teaching pedagogy to the educators which help to solve the training issue of undertrained educators. Engaging learners and enhancing the understanding of the learner demands customizing teaching styles according to the needs and preferences of each learner. This is impractical in traditional classroom environment. More interactive formats and content tailored to individual learning styles developed under the m-learning platform has the potential to increase engagement levels of students to understand better. In comparison to traditional time-consuming evaluation system, m-learning provides regular assessment system during the learning process which helps the teachers to understand and determine the specific learner requirement for conceptual clarity.

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Principles of Designing Mobile Learning

Mobile learning needs specific learning principles of design that is given in Fig. 1. Very initially, it is required to know the features of device and nature of target learners. Learning should be multifunctional and experience oriented. It is essential to explore the learner’s need and requirement so that it may be possible to connect the learner with this meticulous learning. It is very essential for the device to be simple in functioning. M-learning will be fruitful and beneficial if the learning will be provided on the bases of these principles. If a teacher will do it, then your target learners will appreciate an engaging, useful, and pleasant mobile experience.

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Mobile Learning Design

Content preparation is a beginning step for mobile learning design. Content should be focused on learners’ necessity. It may be fusion of traditional and innovative approach. In m-learning, learning material and content needs to be cast effective. Mobile learning should be required to follow some steps in organizing mobile learning design as given below: Steps of mobile learning design • • • • •

Content preparation A blended approach Magnitude of course file Mobile usability Device orientation

Fig. 1 Basic principle of m-learning Know the features of device and target learners. Multi functional and experience oriented Oriented towards learners need & requirement Simple in functioning

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(a) Content preparation As learners may choose to use short portions of m-learning at a time, they need to know how each learning nugget fits into a whole course or curriculum. The teacher should help them identify this by making the formation of the overall course clear when they access each learning nugget. A content preparation of the whole course at the beginning of each learning nugget would be a useful strategy for accomplishing this. Similarly, it is important to make the objectives for each learning nugget clear at the start, so that learners have an overall indication of what will be covered. (b) A blended approach Designing the course of m-learning should be learner centered. One of the major “mistakes” in designing m-learning is that too much content is inappropriately used for smartphones and tablets, resulting in a poor user experience. Instead of attempting to create whole eLearning courses for a small screen size, a different type of approach should be considered. Designer should be aware to produce relevant course material for small screen. We can adopt a blended approach for m-learning solution. For example, “justin-time” elements of m-learning such as revision modules that can be taken instantly before presentations or meetings, job aids and top tips can all be used along with traditional eLearning or instructor-led training in a blended approach. Learners can access these “learning nuggets” on their mobile device whenever and wherever they necessitate them. Resources such as these would sit well in a blended approach, perhaps alongside traditional eLearning, or instructor-led training. If the learners would like further information on a particular subject matter, then required to available them. Teacher could do this by directing them to other modules in the course, other aspects of the blended approach, or alternative resources, such as websites or supporting documents. (c) Magnitude of course file With the introduction of content being delivered with, bring your own device (BYOD), learners using their own mobile device for m-learning will be passionate to maintain their personal costs to a minimum. It should always be remembered that learners may not always have access to a Wi-Fi connection, and may be very unwilling to use their own data payment for learning content. Therefore, designer should require considering the overall file size of the course content. Another concern in m-learning design is that content should be available both online and offline. (d) Mobile usability Most users of mobile devices expect a good user experience. They expect applications to integrate well with their operating system, and do not expect to need to learn new navigation systems or unconventional gestures. Consider mobile usability heuristics to ensure that instructor is providing a positive useful experience for their learners. Aim to build content where users will not notice the usability experience. If they notice it, it is probably for the wrong reasons.

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(e) Device orientation In some instances, most mobile devices utilize both landscape and portrait orientation. Instructor should ensure that their learners are able to use both; otherwise, he should present content that is fixed to one orientation. Therefore, there really are many facets to consider when designing mobile learning. These will consistently change and advance over time and will depend on your customer’s specific need or requirement.

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Features of Mobile Phone as a Learning Tool

Mobile phones have the following features: (a) Voice Such phones with voice are the most basic phones, are still prevalent though being rapidly replaced. Only technology can be used to learn languages, literature, public speaking, writing, storytelling, and history amongst a whole range of topics. We have known that voice based learning works for millennia now. (b) SMS Widely used in India, literally billions of short text messages are sent over the phone networks. These messages can be written quickly and offer enormous learning opportunities. SMS can be used to provide just-in-time information of almost any type, like reminders (e.g., someone undergoing a formal mentoring process). SMS can be used for informational quizzes. There are also innovative games based around SMS that have strong learning potential. (c) Graphic displays Almost every mobile phone has a graphic display, even if it just shows signal and battery strength. Most phones today have far more graphic power and are able to display words, pictures, and animation. Such screens also allow for meaningful amounts of text to be displayed, supporting rapid serial presentation of contextappropriate information. You can use this type of displays for almost any sort of learning. Eventually these displays will render content that is today rendered on personal computers. (d) Downloadable programs With mobile phones that have memories, and can accept and install downloaded programs an entire new learning space is opened up on the phone. Almost any sort of learning content and interaction technology can be delivered to the phone using this method. (e) Mobile Internet Browsers Internet browsers are now built into an increasing number of phones, especially those that take advantage of 3G or enhanced data networks such as GPRS. Mobile should have browser that make it able to access learning resources like web browsing including Google, LMS applications, typical eLearning courseware, and other tools/applications.

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Digital Inclusion with M-Learning

These days, mobile devices are stylish. Children are carrying more technology to school in their pockets than we have been able to buy them over the last 30 years, says Shelly. However, for many of these cell phone users, mobile technology is the only way they can get online. Access to richer graphics and data, as well as superior tools, is still limited on many affordable mobiles. At the same time, many schools continue to demonize cell phone use during school, which may be an outdated policy. Not only are there an increasing number of educational applications for mobiles but, as Blake-Plock advocates, prohibiting phones now means “disconnecting the adolescent from what’s actually happening in most of our lives.” Digital exclusion remains a significant challenge in the India. A vast number of adults are offline. Within this group the elderly, the underprivileged, and those with lower incomes and less education are all disproportionately represented. This figure has been gradually falling, but there are substantial challenges ahead, because most of those with the desire to access online resources. Consequently, a significant mainstream of those still deprived to access online resources have no interest in moving to online resources. In particular, it argues for offering mobile devices for online resources that: • Come to the user and motivate for using mobile apps for educational purpose • Mobile features should be as simple as possible, to ease the skills challenge and to enable experimentation and also to inspire them for further usage. • Device should be vigorous, in the sense of easy to maintain and very easy for a beginning user. • Learner has to integrate, incorporating both equipment and connectivity. Moreover, the internet is increasingly a mobile phenomenon being accessed from mobile devices and the quantity of web content personalized for mobile browsing is on the increase. Over half of Indian adolescents use a smartphone or other mobile to get online resources. In the near future, internet exclusion will be exclusion from a medium primarily used via such devices. Governments must not underestimate the role mobile technology and networks have to play in bringing more and more people online. Mobile phone has attributes, which construct it highly valuable as a tool to deal with digital inclusion. Mobile phones with internet connectivity are simple to use and technically robust; need much lesser financial commitment than a PC with fixed broadband; are sound suited to passing individuals and those with in-home mobility challenges; and come with a range of integrated potential such as cameras which many PCs lack. As the task of helping people move online is becoming more challenging. Mobile phone is the best tool to help learners moving online and it will be the best option for an increasing number of individuals transitioning online. The nature of digital inclusion is changing increasingly. Those offline simply perceive a need to move online. Mobile has great potential as one such tool, and is currently underutilized.

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We believe the following steps could be valuable towards mobile meeting its potential in this context. • Availability of the devices • Accessibility of the technology at hand • Literacy cater

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Potential of Mobile Learning in Rural Areas

Without proper research evidences it is hard to express at the worth of the m-learning market in India, any projection is unfounded; and is also due to the improbability of being able to predict the rate of technological (read network) adoption and penetration. However, empirically, we are seeing an increasing interest in m-learning. Similar to India, it is hard to quantify adoption in more developed markets. It is well known that Asia and Europe are far ahead in terms of m-learning adoption compared to the North American market. The US market for Mobile Learning products and services is growing at a 5-year compound annual growth rate (CAGR) of 21.7% and revenues reached $538 million in 2007 (Chahal 2012). It would be fair to say that revenues in Europe and Asia will be equal to if not greater than the North American market. Almost every sector will benefit from the use of m-learning; however, we feel three primary areas that will feel the biggest impact: education, agriculture, and healthcare. Additionally, rural communities will benefit tremendously not just from m-learning, but the mobile technology as a whole. Mobile devices are far cheaper than personal computers and do not depend on a continuous power supply to function. There is a definite appeal in gaming for learning using mobile phones. Currently, several companies are experimenting with game-based learning technology for mobiles. However, the feasibility of such an approach depends on the cost of development and deployment of such applications, which are quite high at this time. With increasingly capable hardware and connectivity available and dropping costs, it is only a matter of time before learning games on mobile become commonplace. In the future, we will witness mobile phones, computers, and various other computing/media devices (iPods, Digital Cameras, PDAs, etc.) we use converge into a single personal mobile computing device. At such a time, the differentiation between eLearning and m-learning will cease to exist; all learning will be electronic and mobile. Finally, it seems relevant to examine the potential of mobile learning in rural areas. Fifty mobile users are selected for this short study from rural areas. They were aged between 16 and 20 years old. To achieve this objective, the investigator adopted SWOT (Strength, Weakness, Opportunities, and Threats) analysis framework. Table 4 exhibits the future promises and confronts of m-learning among the people of the invisible world.

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Table 4 SWOT analysis of m-learning Strengths • Convenience and flexibility • “Situated rather than simulated” and so it makes learning possible at the point of need • Mobile learning empowers learners to take the initiative and direct their own learning activities • Good use of “dead time” • Suitable for many different learning styles • Improves social learning • Encourages reflection • Easy evidence collection • Supported decision making • Easily digestible learning: avoids cognitive overload • Easily trackable via Wi-Fi • Cost-effective build • Context sensitive learning • The power of personalization

Opportunities • Mobile learning enables forgotten or mistakenly remembered information to be speedily accessed and redressed • Short nuggets of learning are offered on mobile devices, accessed prior to meetings or beginning tasks, improve learners’ confidence in their skills • Quick-fire knowledge or mobile assessments/quizzes, in between other kinds of training activities, keeps learning fresh and at the forefront of learners’ minds, making success more likely • Better planning for face-to-face sessions • Direct interaction with learning • With the integrated connection of mobile devices to the web, it opens up the possibility of tracking everything the user does, how they use the training, what questions they got right, and even their behaviors

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Weaknesses • Multitasking may not be best all time • Technology presents problems: Many students may be unable to load coursework and participate in mobile messaging discussions because their devices are not compatible with the class’s software and websites • Battery run-down can cause loss of data and applications • Back-up systems are required to restore configurations • Battery life decreases dramatically if add-on cards are used or life wireless communications are enabled • Stylus input is only suitable for short notes, simple diagrams, and selecting options on screen • Security of personal information is a major issue, particularly for medical and nursing education • They are easily damaged, lost, or stolen Threats • Mobile security is a serious problem • Hackers can compromise mobile devices by embedding malware into mobile apps • Hackers can steal private information from the device • Wi-Fi hijacking or Wi-Fi snooping is another threat • Hackers can also exploit vulnerabilities when Bluetooth connectivity is turned on • Cyber criminal • Lack of standards for learning on mobile and even general use of technology on mobiles • Multiple platforms and varied technical frameworks. Adds to complexity in terms of design and development, especially when the need is to build native apps, which can utilize the true potential of the mobile platform

Suggestions

(a) How to use mobile phone as a learning device? Data show that the realities in most rural Indian adolescents have mobile phones in their pockets. Findings of SWOT analysis for mobile learning show that it has great potential for future prospects instead of various weakness as well as threats. It is not looking good to perceive mobile phones as evil why not get these tools

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use them for leaning. Mobile phone can be used as revolutionary tool for education to invisible world. Here are some easy to employ strategies to use cell phones as learning device: • Recording lectures The learning material can be structured as a form of video recording. Teachers are required to record their lessons using video or audio, students are listening to that outside of class as the homework, and in class, they are completing the practice and the teacher serves as a guide, re-teaching as needed. Because of mobile phones, have features to restore data so that learner can use it and watch video of previous lessons of an appropriate clip on YouTube. • Instant response system With mobile device, a teacher can track instant answers from all students. Teacher can receive feedback for their improvement. In this regard, it may be an inspiring tool for teacher as well as learner. • Delivering materials In present days, curriculum materials are available in digital form and creative teachers are benefitted with delivering materials directly to students on their personal cell phones. This learning platform makes it possible for teachers and students to collaborate in discussion areas and chat with each other making blended learning a real possibility. (b) Common problems using cell phones in learning • Students lacking cell phones/smart phones Every student cannot afford mobile phone. It is also a big issue for mobile learning. The easiest way to work around this is to have students working in groups, collaborating and solving problems together. Therefore, we only need one cell phone to report out the group work. To get the solution of any problem we need to be creative. • Wireless access Wireless access might be another dilemma. Smart phone users will usually try to locate a wireless network instead of going through the provider signal. The network might be burdened and required material would be lost. • Maintenance & uses of cell phone When the class is started with mobile phone, it is the responsibly of instructor to make their class more interactive. Teacher should ensure that their students should be more convenient with m-learning rather than conventional learning. Teacher should make various efforts to reduce fear for using technology from regular routine. Instructors are needed to help students understand the consequences of things like cyber bullying, sexting, and posting things to social networking sites. (c) Awesome smart phone apps for teacher Presently, various smart phones are available in market with smart apps. These features make the life much smoother for professionals of all types. Therefore it should be inculcated among teachers. Here a list of smartphone apps that teachers can put to work in the classroom and beyond, creating a powerhouse of back-to-school mobile tools (Table 5).

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Table 5 List of smartphone apps for teachers Awesome smartphone apps for teacher Evernote Evernote is a web-based app that allows end users to capture, store, and synchronize text, image, and video files across multiple computing devices Attendance iPhone-enabled teachers adore this application allowing them to keep track of their students’ classroom habits and even learn their names via flashcard Grade Book for Professors Google Spreadsheets as a useful strategy for organizing and tracking student grades, either through the paid or free version Percent Calculatop Get grades done harder, better, faster, and stronger using this quick and easy calculator just for figuring out percentages E-Clicker Polling System Available on the iPhone, the eClicker Suite lets teachers poll their students about anything and everything during class Voice Recorder Perfect for Android users wanting to make permanent records of lectures for students who cannot make it to class for whatever reason i-talk Recorder It is a way to keep an audio record of classroom discussions using the iPhone Blackboard Mobile Learn Blackboard practically provides a classroom for an app, available on almost all smartphone and tablet platforms Course Smart Provide unlimited access to thousands of digital reads on their phones and tablet devices Teacher Aide Pro Lite Provide every specific organizational requirement educators need to succeed TeacherKit Provides a way to stay on top of grades, attendance, and any other factors they need to know Dropbox This simple, popular tool focuses mostly on transferring documents back and forth between different computers and smartphones alike RE.minder Educators with time management issues might want to consider downloading RE.minder, with a to-do list feature and handy alerts when tasks are almost due iAnnotate iAnnotate helps iPad-owning teachers edit, organizes, read, and annotate (of course) PDF files, making it an ideal tool for grading student projects Free Wi-Fi Finder It helps to know what nearby locales host free wireless service Instapaper Save pages from useful websites and blogs that you encounter for offline viewing and reading with this much-ballyhooed timesaver Documents To Go View and create PDFs and Microsoft Excel, Powerpoint, and Word documents from almost anywhere Bento Keep a database on contacts, projects, upcoming events, due dates, and more with one of the most acclaimed organization applications available Edmodo Connect with other teachers as well as students using Edmodo, which acts as a social media resource limited exclusively to the schooling sector (continued)

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Table 5 (continued) Awesome smartphone apps for teacher LinkedIn Access the ridiculously popular professional social media site and network with others in the education industry for ideas, inspirations, and information about how to improve your career iBlueSky (mindmapping) Get great ideas out there and in the open with this productivity app that means to push every user’s inherent potential forward Bump “Bumping” two enabled phones together automatically exchanges contact information – great for staying in touch with parents as well as other teachers and administrators from education events Twitter The ubiquitous microblog’s app covers every smartphone platform available, and offers a stellar way to share resources with other professionals as well as students and their parents Flashcards Create, share, and download flashcards on every subject imaginable – awesome for classroom use or staying current on changes within education and areas of inquiry Facebook It is a social networking apps as well as learning platform The Leadership Challenge Wiley Publishers provide a $4.99 resource packed with Mobile Tool information, inspiration, and a series of articles and activities meant to bolster general leadership acumen Pulse News Stay on top of the current news of the day by sticking with this Android app, which involves easy access to any online reads the user chooses. Pulse News makes for one of the best ways to remain relevant in the general education sector as well as any academic subjects taught Goodreads As a social network and personal library inventory system stands as solid proof Wolfram Alpha Turn a smartphone into the world’s most powerful reference tool, with extensive information about literally every academic subject imaginable packed into one stunning application Dictionary.com –Dictionary & Like the title states, this app from Dictionary.com combines Thesaurus, Free dictionary and thesaurus tools for quick vocabulary look-ups Wikipedia Read through and share articles from the world’s largest encyclopedia on every smartphone platform out there Wikipanion Wikipanion streamlines the Wikipedia experience even more, allowing for bookmarking, archiving visit dates, multilingual searches, and other amazing additions gratis How To Videos from Learn how to do just about anything using crowdsourced Howcasr.com videos, and even upload your own instructions to open up your classroom to the world Free Graphing Calculator It’s a free graphing calculator ASL Ultimate Teachers with hearing-impaired students will greatly appreciate having this resource around for advice on what to say and how to say it in ASL World Factbook Every year, the CIA releases its World Factbook to smartphone audiences and grants them access to detailed information about every nation on the planet (continued)

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Table 5 (continued) Awesome smartphone apps for teacher Google Search Google Search provides many more options than the web-based engine, and smartphone fans love taking advantage of how it sends returns based on photos and other multimedia input Kindle Available on every smartphone platform, Amazon’s popular ebook reader make free and for-profit digital literature easy to access during free moments TED TED provides an edifying way to pass the time, with hundreds of videos featuring experts lecturing on every topic imaginable Instagram In between pictures of cats and food, try posting some from the classroom and share ideas about decor, or host a digital art show for students Showyou Showyou curates the best of the best YouTube videos, and encourages others to share what they love most. The educational applications here ought to be readily apparent! Musee du Louvre Digitally walk the famous halls of the world-class art museum at the end of a stressful day and get lost in its glorious collections Foursquare Play fun, deal-seeking check-in games with friends or even draw some up for student scavenger hunts Cracked Reader Lite Cracked is so ridiculously hilarious, people sometimes forget it actually features some insightful and educational content on the reg Google Earth Fun with or without playing with it on an educational level, Google Earth inspires awe and wonder at our planet’s true complexities Source: Classroom aids: http://classroom-aid.com/author/classroomaid/

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Future Directions

Education is for people and its development is ultimately aimed at maximizing the capacity for achieving full welfare of the population. The educational planner as well as administrator is constantly engaged in activities for and with the people. The question arises: What are the demographic challenges facing educational planning today? Population growth results in significant variations in the age and sex compositions of the population besides the numerical increase. By 2030, India will be amongst the youngest nations in the world. With nearly 140 million people in the college-going age group, one in every four graduates in the world will be a product of the Indian education system. We have gross enrolment ratio of about 17.9% now, while an ambitious target of 25.2% has been envisaged by the end of 12th Plan. According to the latest report released by one of the universities in India, mobile internet users within the boundaries of India are estimated to go up to 160 million users by the end of 2015. An education sector especially remote area has not been left behind and do these internet mobile devices provide greatly exploring the opportunity. Currently, education sector in India including higher education has

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shortage of skilled human resources and quality facilities. This has resulted due to the lack of sociability among students. With introduction of technology, a greater opportunity has been provided to overcome such hurdles among students. This is because students can now use their mobile phones to navigate through the internet and join public chats on sites such as Facebook and Twitter. With the outburst in the number of educational apps, online courses, and smart phones in the hands of Indians young and old it may be possible to access education for the people belonging to the invisible world. According to Bruck, Motiwalla, and Foerster, mobile devices have now become the fastest growing technology in human history. He has cited numbers from the International Telecommunication Union. His “statistics shows more than 6 billion mobile phone connections existed at the end of 2011 worldwide and will grow to 12 billion by 2020 (ITU 2012 is cited in Moesser (2012)). Very soon mobiles will outnumber humans living on earth, presumably by 2013.” Rapid changes are taking place in both the technology and materials of mobile phones. Surprisingly, applications are being designed specifically for learning. Therefore, there is tremendous potential for the growth of mobile learning even invisible world.

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Cross-References

▶ Accessibility Challenges in Mobile Learning ▶ Mobile Learning in Southeast Asia: Opportunities and Challenges ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts

References Chahal, J. 2012. Modern trends of learning. International Journal of Behavioral Social and Movement Sciences 1(1) Moesser, J. 2012. Education: Is mobile learning actually effective? Retrieved from http:// momitforward.com/mobile-learning-effective#sthash.LR2x4OT9.dpuf. Powar, K.B. 2002. Indian higher education: A conglomerate of concepts, facts and practices. New Delhi: Concept Publishing Company.

Problems and Challenges of Mobile Learning in Nigerian University System

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David Jimoh Kayode, Afusat Titilayo Alabi, Abayomi Olumade Sofoluwe, and Rhoda Olape Oduwaiye

Contents 1 2 3 4 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Is Mobile Learning? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mobile Learning Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Benefit of Mobile Learning in Higher Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Issues and Challenges Toward the Implementation of Mobile Learning in Higher Education in Nigeria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Electricity Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Management and Maintenance of Mobile Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Acceptability by Both the Lecturers and the Student . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Affordability of Mobile Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Little Knowledge About Some of the Mobile Teaching Applications . . . . . . . . . . . . . . . . . . . 11 How to Address the Identified Issues and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The issue of access to university education due to low capacity of the universities to accommodate the qualified students into the university system has become a great concern for parents and the governments. The introduction of mobile learning will be a welcome development to reduce poor student access to the university. However, there are issues and challenges that are likely to create a barrier toward a successful implementation of mobile learning in universities in

D. J. Kayode (*) · A. T. Alabi · A. O. Sofoluwe · R. O. Oduwaiye Department of Educational Management, Faculty of Education, University of Ilorin, Ilorin, Kwara State, Nigeria e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_135

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Nigeria. This chapter therefore explains the concept of mobile teaching and learning, features and benefits of mobile learning in the university system, as well as the issues and challenges toward a successful implementation of mobile teaching and learning in universities in Nigeria. Some recommendations were suggested on how such issues and challenges can be addressed which include the training of both the students and the academic staffs on the benefits of some of the networking like LinkedIn, Facebook, etc., to enhance teaching and learning in higher education.

1

Introduction

As the world has become a global village because of the technological advancement in the world and Nigeria in particular (Alabi 2008; Kayode and Ojo 2011), mobile teaching and learning (m-learning) in recent years has become a valuable and real contribution to learning environment rather than what it used to be in previous years as a theory, academic exploration, and technological idea (Alzaza and Yaakub 2011). Mobile technology according to Premadasa and Meegama (2013) has become an “imperative technology that landed recently upon the arena of emerging educational technologies in the global academic sphere” (p. 106). Some scholarly observers of educational trends expect mobile learning to be the next significant innovation in higher education (Alexander 2004; Wagner 2005). Therefore, the role of the lecturers and the students are considered as a fundamental element in the learning situation. Even though mobile learning has advanced from testing stage to a new educational trend widely being used by countries like Britain, Denmark, Japan, and the USA (Osang et al. 2013), mobile learning is still very new and has not being fully implemented in most of the higher institutions in Nigeria. In a review of the literature on mobile learning as stressed by Croop (2008), the exact origin of mobile learning could not be pinpointed. However, according to Keegan (2000), the first extensive use of mobile learning as a label for learning through the use of mobile devices surfaced in several pan-European mobile learning projects that started in the late 1990s and the early 2000s. According to Osang et al. (2013), the University of Ibadan in partnership with Education Advancement Centre has also implemented it for the senior secondary students preparing for Joint Admission and Matriculation Board (JAMB UTME) in order to guarantee outstanding result in their exams. However, the University of Ilorin which is one of the federal universities in Nigeria, in an effort to implement mobile teaching and learning, has provided tablet PCs to over 20,000 students matriculated for 2013–2014, 2014–2015, 2015–2016, and 2016–2017 academic sessions. It therefore becomes pertinent to discuss how mobile teaching and learning can be successfully implemented as many schools, both private and public, are working toward mobile teaching and learning in their various schools. Currently, there is the introduction of google classroom in most of the postgraduate courses and

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some undergraduate courses where students are expected to interact with their colleagues and the lecturers in charge of the courses for assignment, quiz, and continuous assessment. The current young generation is growing up in a world dominated by communication with others and access to information through the use of cell phones and other mobile devices (Croop 2008). Conversing on the fly, text messaging, accessing media and information uninterrupted anywhere, and viewing text and other media on a small screen may be affecting the manner in which young students prefer, and possibly will need, to study and learn. Therefore, this chapter discussed the issues and challenges in the implementation of mobile learning in higher education in Nigeria and how such challenges can be addressed.

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What Is Mobile Learning?

Despite the fact that there is no single definition for mobile learning and Winters (2007) stressing that mobile learning has not yet been defined (Croop 2008), many researchers have put forth proposed definitions of the concept. Some of the authors who have suggested definitions have emphasized the mobile technologies that make nomadic learning possible (Aderinoye et al. 2007), while other researchers have chosen to focus on the experience of the learner in regard to the location and the type of learning activity encountered in mobile learning (Balasundaram and Ramadoss 2007). Mobile learning according to Alexander (2004) is often abbreviated as m-learning or mLearning. It is a concept that has “different meanings for different communities that refer to a subset of E-learning educational technology and distance education that focuses on learning across contexts as well as learning with mobile devices” (Mehdipour and Zerehkafi 2014, p. 93). It is a concept with different names which include m-learning (Alexander 2004), u-learning (Alexander 2004), personalized learning (Crompton 2013), learning while mobile, ubiquitous learning (Clark and Flaherty 2002), anytime/anywhere learning (Crescente and Lee 2011; Alzaza and Yaakub 2011), and handheld learning (Yusri and Goodwin 2013; Mehdipour and Zerehkafi 2014). Ozdamli and Cavus (2011) defined mobile learning as a mode of learning that allows learners to obtain learning materials anytime and anywhere using all sort of wireless handheld devices which include mobile phones, personal digital assistant (PDA), wireless laptop, personal computer (PC), and tablets. Also, Cobcroft et al. (2006) defined mobile learning as the type of learning that provides opportunity for learners using mobile devices to access learning resources anytime and anywhere. As argued by Mehdipour and Zerehkafi (2014), mobile learning is not just a mere conjunction of “mobile” and “learning” but has always absolutely meant “mobile E-learning” (p. 93). However, its history and development have to be understood as both a continuation of “conventional” E-learning and a reaction to this “conventional” E-learning inadequacies and limitations. In other words, it is the “mobile”

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that makes it to stand apart from other types of learning. Mobile learning has been described as a subdivision or subset of electronic learning (Peters 2007). Therefore, mobile learning focuses on the mobility of the learners, interacting with portable technologies and learning that reflects a focus on how society and its institutions can accommodate and support an increasingly mobile population. According to MOBIlearn (2003), mobile learning is seen as any sort of learning that happens when the learner is not at a fixed, predetermined location or learning that happens when the learner takes advantage of the learning opportunities offered by mobile technologies. This was further stressed by Aderinoye et al. (2007) when they defined mobile learning as any learning carried out with the employment of a wireless or mobile device. Fraga (2012) further defined mobile learning based on facilitating technologies (Traxler 2007; Richardson 2006), location and type of activity (O’Mailey et al. 2003; Balasundaram and Ramadoss 2007; Clark and Flaherty 2002), and in the context of research (Fraga 2012).

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Mobile Learning Devices

In the study conducted by Georgieva et al. (2005), mobile learning system was classified into seven components based on mobile devices and their capabilities which are communication technology used, access of services whether online or offline, communication between students and lecturers, information which comprise learning materials and administrative information, the location of learners, and E-learning standards whether supported or not (Rekkedal and Dye 2007). Mobile learning features according to Alzaza and Yaakub (2011) include WAPbased protocol; anywhere and anytime accessibility; wireless network; mobile network connectivity (GSM, GPRS, UMTS, or CDMA); mobile phone, smartphone, or PDA; and device size – very small screen size of a mobile phone has maximum of 480  640 pixels, while the common PDA has 240  320 pixels (p. 96). Riva and Villani (2005) enumerated specific devices for mobile learning which include cell phones, PDAs, web-enabled cell phones, wirelessly network-connected PDAs, wirelessly network-connected laptop computers, wirelessly network-connected tablet personal computers (tablet PCs), and the ultra-mobile personal computer (UMPC). This list was expanded by Alexander (2004) in his definition of mobile learning to include MP3 players or iPods, Bluetooth-enabled devices, handheld gaming devices, digital cameras, wireless access points, USB drivers, and radio frequency identification (RFID) tags. However, van’t Hooft coined the term highly mobile which further limited devices to ones operated with one hand (Croop 2008) which if considered will eliminate laptops and most tablet PCs from the list of devices considered as mobile learning devices or appliances. But, for the time being, the inclusion of laptops and tablet PCs as mobile learning devices is predominant in the relevant literature. As found in relevant literature according to Croop (2008), the usage of mobile device is illustrated in Table 1.

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Table 1 Examples of mobile devices and its usage Mobile devices Cell phone

PDA

Examples of mobile learning Using cell phones to teach English in Japan requiring students to, throughout a typical day, exchange text messages in English outside of class Employing PDAs to access PowerPoint and other course resources, participate in discussion boards, email other students and the instructor, and share work Relying upon SMS to pose questions to students and receive responses via cell phones in facilitating daily assessment of achieving learning objectives Utilizing PDAs to run class organization software

SMS

PDA Cell phone

Laptop, cell phones, PDAs,

Cell phones

Using cell phones to teach literature though multimedia messaging, web searching, mobile posting to blogs, and content-related gaming Distributing to students audio files that can be played on the learners’ portable media players to address false preconceptions and anxiety related to an information technology class Facilitating the polling of students, assessing comprehension, and fostering increased interactivity during a large business communications class with the help of students’ mobile phones

Source (s) Thornton and Houser (2005); Levy and Kennedy (2005) Ramsden (2005)

Balasundaram and Ramadoss (2007) Sharples et al. (2005) Shih and Mills (2007) Lee and Chan (2007)

Fisher and Baird (2006)

Source: Croop (2008)

4

Benefit of Mobile Learning in Higher Education

Access, context, collaboration, and appeal are considered to be the primary advantages of a mobile learning environment (MLE) compared to any other traditional classroom-based learning methods identified so far (Premadasa and Meegama 2013). However, to setup a reliable MLE, a number of important factors, such as contents of the learning material, learner’s mental ability, learning environment, space for the mobile learning, delivery method, technological aspects, and time for mobile learning, need to be considered (Laouris and Eteokleous 2005). Lecturers are busy in numerous academic activities which include preparing learning materials, assignments, quizzes, group discussions, and news forums to organize a better learning environment (Premadasa and Meegama 2013). Therefore, supporting the lecturers in their teaching activities is an indirect form of supporting a student’s learning ability (Gaudioso et al. 2009). As stressed by Bartlett-Bragg (2013), mobile learning is all about the learners experience and also about reframing traditional design and pedagogical frameworks to consider critical elements like time and place, relevance, collaboration, user control, and personalization (p. 25).

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According to Yusri and Goodwin (2013), mobile phones have more potential as a tool for mobile learning than any other handheld devices because it is available to everyone, has low-cost services, has wide coverage of the mobile network, and is a familiar device (Douch et al. 2010). According to technology time’s newspaper, out of the 167 million Nigerians, 63.9% of the population has access to mobile phones. Mobile phones have been seen as a sensible choice for educational investment (Williams 2006), and it is perceived as beneficial for both the learners and instructors in developing nations because of its cost-efficient method (Motlik 2008). As stated by Croop (2008), the impact upon higher education of a global society that is becoming more mobile can be seen in a 2005 survey of 1600 randomly selected University of Wisconsin-Madison students. The study reveals a quick abandoning of desktop computers in favor of laptops. This was also revealed in the study conducted by eMarketer in 2006 according to Oblinger (2006) that over 80% of college students have cell phones, 56% of college students own a laptop, and 75% of college cell phone owners use text messaging most often on their phones. According to Premadasa and Meegama (2013), mobile learning technology has improved the learning efficiency between the lecturers and the student as SMS has become one of the best communication technologies that can be used to bond the two roles, the lecturers and the student, for distributing information in the MLE. Therefore, the communication media as stressed by Rau et al. (2008) is an essential factor in the mobile learning environment (MLE) to increase intrinsic motivation without causing additional pressure in a demanding learning performance. As highlighted by Attewell (2005), mobile devices can help improve literacy and numeracy skills, encourage independent and collaborative learning experiences, identify areas where learners need assistance and support, mitigate resistance using ICTs, engage reluctant learners, enable learners to remain more focused for longer periods, and promote self-esteem and self-confidence (pp. 13–15). This was supported by Crompton (2013) in her discussion about the benefit of mobile learning to the students where she discusses five learning approaches using mobile devices; this is shown in Table 2. According to Croop (2008), the impact upon higher education of a global society that is becoming more mobile can be seen in a 2005 survey of 1600 randomly selected University of Wisconsin-Madison students. The study reveals a quick abandoning of desktop computers in favor of laptops. This was also revealed in the study conducted by eMarketer in 2006 according to Oblinger (2006) that over 80% of college students have cell phones, 56% of college students own a laptop, and 75% of college cell phone owners use text messaging most often on their phones. Furthermore, based on a survey of 107 students in Texas where all were owners of cell phones, Corbeil and Valdes-Corbeil (2007) proposed the first device that should be researched as a vehicle to implement mobile learning is the cell phone. Mehdipour and Kerehkafi (2014) heighted some applications of mobile phones which is shown in Table 3.

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Table 2 Learning approaches through mobile devices Learning types Contingent

Situated Authentic Contextaware Personalized

Description Students respond to the changes in environment and experiences

Students learn in an environment appropriate to their learning Tasks are directly related to the learning goals Students interact with the environment using the tools on their mobile devices Learning is customized to the preferences and needs of each student

Example A student can be walking down the street and may see a word on a billboard that interests him, so he looks it up then and there on his mobile device. Learning was not planned, but it happened Students listen to a podcast about erosion as they examine rocks in a quarry Students use the vibration meter app as they learn about earthquakes On a visit to a museum, a student scans a QR code to find out more about a warrior helmet she is looking at As the students in the class are watching a short video clip on their mobile devices, one student who is hard of hearing, realized his sound was too low. He stopped his video, turned up the volume, and then continued to watch the video

Source: Crompton (2013)

Fraga (2012) further highlighted the benefits of mobile leaning as follows: it is convenient and flexible (Peters 2007; Motiwalla 2007); mobile learning can be ubiquitous, localized, and personalized (Clark and Flaherty 2002; Alexander 2004; Keegan 2002; Peters 2007; Shih and Mills 2007); it is more portability at a lower cost (Kukulska-Hulme 2005; Motiwalla 2007; Balasundaram and Ramadoss 2007; Attewell 2005; Nyiri 2006); it increased learner motivation and engagement (Balasundaram and Ramadoss 2007; Kukulska-Hulme 2005); it increased collaboration (Brown 2005; Ramsden 2005; Oblinger and Oblinger 2005); mobile learning can complement other learning platforms (Traxler 2007; Aderinoye et al. 2007); mobile learning is student focused (Kukulska-Hulme and Traxler 2005; Kukulska-Hulme 2005; Fisher and Baird 2006); and mobile learning can contribute to the achievement of learning objectives (Shih and Mills 2007).

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Issues and Challenges Toward the Implementation of Mobile Learning in Higher Education in Nigeria

As stated by Traxler (2010), Corbeil and Valdes-Corbel (2007), implementing mobile learning in higher education is still challenging due to cultural, social, and organizational factors. Therefore, the first step toward a successful implementation of mobile teaching and learning in higher education is the understanding of factors that influence learners’ adoption of mobile learning.

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Table 3 Current capacities and application of mobile phones Subject Place Pedagogical change Instructor-student communication

Student-to-student communication

Feedback to student

• Assignment and test

• Presentations, exams, and assignment

M-learning • Learning anywhere, anytime • More voice, graphics, and animation-based instructions • Learning occurring in the field or while mobile • Instant delivery of email or SMS • Instant communication • Synchronous • Spontaneous • Flexible • Audio and video teleconference possible • 24/7 instantaneous messaging • No geographic boundaries • No travel time with wireless Internet connectivity • Flexible timing on 24/7 basis • Rich communication due to one-to-one communication, reduced inhibitions • One-to-one basis possible • Both asynchronous and synchronous • Customized instruction • Performance- and improvement-based grading • Real-life cases and on-the-site experiments • Less paper, less printing, lower cost • Any location • 24/7 instantaneous • Any amount of time possible • Individualized tests • Instant feedback possible • Flexible length/number of questions • Practical oriented exams direct on-site, hands-on based • Observe in the field and monitoring from remote location • One-to-one presentations with much richer communication • Automatic translation for delivery of instructions in many languages (possible) • Simultaneous collaborative group work • Electronic-based assignment delivery • e-delivery of assignment at any place and time • Instructor’s time used to offer individualized instructions and help

Source: Mehdipour and Zerehkafi (2014)

According to Mohamad et al. (2013), the challenges of introducing mobile learning in Malaysian schools are grouped into six key issues which are misuse, management and maintenance, current educational policy, digital divide, stakeholders’ attitude, and personal space invasion (p. 133). Therefore, some issues and challenges discussed in this chapter as pertinent to higher education in Nigeria include electricity supply, management and maintenance of mobile devices, acceptability by both the lecturers and the student, affordability of mobile device, and little knowledge about some of the mobile teaching applications.

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Electricity Supply

One of the utmost challenges to the development of Nigeria is electricity. Electricity supply was not in tune with the geometric increase in the population of the country, and because of that, some locations may not witness up to 5-h electric supply in a day, and that is a challenge to the use of mobile devices that requires constant electricity of at least 8 h in a day. This epileptic power supply in the country was further buttressed by Osang et al. (2013) in their study. It was reviewed that 64 out of the 80 locations required (education) identified power supply in the country as a major challenge to the implementation of mobile learning in Nigeria. According to Mohamad et al. (2013), change is difficult to introduce and implement because it sometimes disempowered than empower people, and causing them to learn new skills requires personal investment of time, effort, and sometimes finances. According to Mohamed et al. (2013), organization of mobile learning is time-consuming. It was further stated by Crompton (2013) that one of the issues of mobile learning implementation into the schools is that the lecturers have to change their everyday behaviors to incorporate technologies into tasks that they previously did without digital technology, and this has been perceived as a different change for many lecturers.

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Management and Maintenance of Mobile Devices

One of the perceived issues and challenges in the implementation of mobile learning in conventional universities in Nigeria is the issue of management and maintenance of mobile technologies. In the research conducted by Mohamad et al. (2013), it was revealed that the organization of mobile learning is timeconsuming and there is perceived cost in deploying mobile phones for teaching and learning. According to Naismith et al. (2004), as mobile devices encourage learning outside a classroom environment being managed by the lecturer, it is therefore necessary for the learners (students) to have some effective tools like MP3 and Webinars to record, organize, and reflect in their learning experiences. Therefore, the experience and epileptic nature of data connections in Nigeria would be a major challenge. For instance, out of the 38 federal universities in Nigeria, the University of Ilorin is still among the few universities that has a fiber-optic Internet connection, and up till now, it is the lecturers and the students that have to source for Internet connection for themselves in some of the universities in Nigeria. Therefore, the inability to rely on the devices and mobile network connections has made it difficult for mobile learning to move more quickly into mainstream education (Kukulska-Hulme 2005).

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Acceptability by Both the Lecturers and the Student

The success of mobile teaching and learning implementation lies on the lecturers’ and students’ readiness to use the new technology. Research has shown that large population of the lecturer does not really have the enthusiasm for teaching with technology as this will extend their workload through inclusion of course website, classroom technology, as well as learning the technology (Osang et al. 2013; Crompton 2013). It was also revealed that students prefer to be on net for social networking, online chatting, listening to music, and other social networking activities that distract their attention from studying rather than moving into the mobile space for their coursework. The researchers conducted a random sampling of 50 fresh students that were given a tablet PC in the University of Ilorin, and it was discovered that 31 (62%) of the students use it for social networking (Facebook, chatting, 2go, Skype, WhatsApp) rather than using it for studies, although it was explained by the students that social networking is less expensive on the tablet comparing it with the data bundle required when using it for educational purposes. This is also in line with the study conducted by Mohamad et al. (2013) where the respondents also believed that the stakeholders’ attitude might be a challenge to implement mobile learning in Malaysia. This challenge might arise from the students, teachers, parents, and the community.

9

Affordability of Mobile Device

The cost of mobile learning devices ranging from programs used for the development of the mobile-based system to the devices used to run the mobile application is one of the issues in the implementation of mobile teaching and learning. In an interview that was conducted among the students of the University of Ilorin, it was revealed that the model of a power determines the capacity of what the power can be used for, and according to them, not many of them have the financial resources to purchase a good mobile learning-compatible phone.

10

Little Knowledge About Some of the Mobile Teaching Applications

There is low awareness of mobile learning applications on the part of students and even lecturers. Fifty students and 10 lecturers were interviewed. Table 4 shows the types of the usage of some mobile learning applications the students and lecturers use and their purpose of being in that forum. As stressed by Croop (2008), the limitations of mobile learning implementation are classified as technical and pedagogical challenges. The technical challenges are in relations to the input and output functions of the mobile devices. According to Motiwalla (2007) and Ramsden (2005), entering text using the keyboards on mobile appliances is at times very difficult and represents dissuasion to using the devices in

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Table 4 Uses of mobile learning applications by samples from students and lecturers in the University of Ilorin Application usage Mobile learning applications Facebook LinkedIn SlideShare Skype WhatsApp

Usage of application by the students 42 21 3 16 39

Lecturers’ usage of the application 7 8 5 1 6

Academic usage Student Lecturer 3 1 3 7 1 5 – – – –

Connections/social networking usage Student Lecturer 39 6 21 4 – – 16 1 39 6

Source: Data collected for this study

learning activities, and also the small size of the viewing screen has been noticed as a limitation (Riva and Villani 2005; Fisher and Baird 2006). Fozdar and Kumar (2007) identified the difficulty that arises in reading from the mobile devices when in sunlight. Furthermore, Heath et al. (2005) wrote about the inability with many mobile devices for the learner to send output to a printer. However, the issue of limited bandwidth of wireless cellular, as well as the slow broadband network connections (Rekkedal and Dye 2007; Riva and Villani 2005), and small memory storage are the contributing factors to the slow nature of mobile device-facilitated learning activities (Kukulska-Hulme 2005, 2007). Other technical issues and challenges in mobile learning according to Croop (2008) include short or inadequate battery life (Corbeil and Valdes-Corbeil 2007; Kukulska-Hulme 2005; Riva and Villani 2005), difficult-to-use interfaces (Mottiwalla 2007), lack of a standard mobile operating platform and a risky security environment (Riva and Villani 2005), inability to mark text (Yarnall et al. 2007), and difficult or impossible cut-and-paste operations (Kukulska-Hulme 2005). Other issues and challenges in the implementation of mobile learning were highlighted by Croop (2008) which are the pedagogical issues which include the following: the use of text messaging by its nature may contribute to students not knowing and/or not caring how to spell (Attewell and Savill-Smith 2004); the students might be overwhelmed with information overload (Motiwalla 2007); it may be easier to cheat (Corbeil and Valdes-Corbeil 2007); and according to Fozdar and Kumar (2007), if not used properly, mobile learning can be counterproductive, and there is the possibility of misuse via MMS, Bluetooth, and cyberbullying.

11

How to Address the Identified Issues and Challenges

In order to address the above highlighted challenges toward the implementation of mobile learning in universities in Nigeria, the following measures are suggested: 1. The school leader should create an encourage atmosphere to both the students and the staffs in order to arose their willingness toward mobile learning through seminars and workshops on the values and usage of some of the educational

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social networking like LinkedIn, Facebook, SlideShare, etc. so that the students can see them as a way of improving their learning rather than using it for social connection and other illegal activities. The school leaders should also provide strong Internet facilities to the students especially when on campus. The school management can also encourage the university community by providing them their desired mobile device, for them to be paying it back on installment basis depending on the school capabilities. The lectures should encourage the learners by creating an educational page in some of the networking forums like Facebook, and they should encourage one another in joining some of the professional LinkedIn group on the Internet to improve themselves and discussing any challenge faced in their process of lecture delivery of professional growth. It is also suggested that mobile phones that have parental features to control students through limiting the phone functionality will be necessary. The government needs to amend some of its policies regarding ICT usage in higher education. The school should have industrial-university collaboration with some of this mobile device manufacturer to discuss the specifications of mobile device they need as well as organizing workshops for both the lecturers and the students on the usage of those devices to build self-confidence in them. The collaboration will also help in terms of getting those devices secure as each device will be customized with the users’ detail to avoid theft.

12

Future Directions

The role of mobile learning in reducing the rate of low access to university education by Nigerian student will be a welcomed development in responding to inadequate lecture rooms, personnel, and other facilities needed by the schools to accommodate more students. As students are more used to mobile devices, if such tools are being converted as learning device, it will increase their enthusiasm toward learning. However, for successful implementation of mobile learning especially in conventional universities in Nigeria, the students, the school leaders, the parents, and the government have a role to play in addressing the likely challenges of mobile learning.

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Expectations from Future Technologies and E-Learning in Higher Education in Albania

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Process and Systems in Change and New Model of Learning . . . . . . . . . . . . . . . . . . . . . . 1.2 Development of Supporting Tools in Learning Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Background. Development based on Information and Communications Technology (ITC) is the future of Albanian economy and society to ensure sustainable development and reduction of poverty. Higher Albanian education has an important role to realize this development. Efforts for harmonizing the pathways of the progress of higher education in Albania have recognized achievements and developments that need to be considered when assessing the qualitative growth of ICT and the contribution of higher education institutions to the formation of the generations that are able not only to use these new ideas but also to influence the spreading of the new ideas, developing and transforming Albanian society. Subject and Methods. In this chapter, we are focused in examination of technology development strategies, the role of government policies to create a collaborative platform of actors, and the changes that have taken places in Albanian higher education in general, and in particular the gender changes and the role of women in social change this past years. To realize this aim, we

I. Nikaj (*) Faculty of Education and Philology, “Fan S. Noli” University of Korça, Korca, Albania e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_43

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are relying on quantitative and qualitative methods from foreign and domestic literature, comparing outward and inward trends, the changes that have emerged in Albanian society and in higher education and to present progressive perspectives on E-learning and future technologies in our country. Conclusions. The evolution of Mobile Learning in Higher Education in Albania should take the following direction: the existing Mobile Learning environments participate in future mobile learning as content repositories, but the active part of learning process covered by the personal learning environment, where the students, using their favourite e-services and e-tools, will construct their knowledge in constant collaboration, just a click away from the knowledge, from the services, from a complex social life.

Abbreviations

Generation Y

Generation Z

HEI ICT i-mode INSTAT MIAP M-Learning Net-gen

NR NRI

Web

The generation born between 1982 and 1995, is also known as Generation Why, Generation Next, the www generation, the Millennium Generation, or Echo Boomers Defined as people born from the mid-1990s to the early 2000s who have used the Internet since a young age and are comfortable with technology and social media Higher education institutions Information and communication technology A customized packet-based mobile service Institute of Statistics Albania Ministry of Innovation and Public Administration in Albania Mobile learning or m-learning is the learning activity on mobile devices or learning anytime and anywhere The Net-Generation is the cohort of young people born between 1982 and 1991 who have grown up in an environment in which they are constantly exposed to computer-based technology. It has been suggested that their methods of learning are different from those of previous generations Networked readiness is a key indicator of how countries are doing in the digital world Network Readiness Index measures how well an economy is using information and communications technologies to boost competitiveness and well-being. An Internet-based hypertext system

“Everything is particles, everything is fields, and third, everything is information.” J. A. Wheeler

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Introduction

The Government of Albania, along with education stakeholders applied the “Net - Gen” strategy and is now facing the challenge of further institutionalizing some of the early achievements and reforms in the education sector in Albania. In particular, according to the 2014–2020 National Strategy for Development and Integration (NSDI) and the 2014–2020 Pre-University Education Development Strategy (PUEDS), educational reforms including curriculum modernization, promotion of European principles, social inclusion, expanding Information and Communication Technology (ICT) in education, standards for teachers, and improving student achievement are among Albania’s top priorities (Ministry of Education, Sports and Youth. 2015). The Education Policy Review (EPR) report is intended as a strategic tool that can assist the Government of Albania in realizing these policy priorities. At the Digital Agenda of Albania 2015–2020, we find this statement: We live in a time of Technological Changes and progress around the global world and in Albanian society. Albania is a country in the South of Europe with economic potential, with natural resources and a young age population. This human capital tends to be educated and seeks opportunities to improve their economic, social, and cultural status through study and training in various areas of knowledge. Based on many research studies we can highlight that there are some features in the developing society from the point of view of sustainable development that condition the way they approach scientific and technological achievements. In addition, the government adopts this framework of action about the development of the economy. In this context, developments in Albania are stable, not at high rates, but continually keep an upward trend. Technology is the future of world economic development. Our mission is to use it as a tool to ensure good governance and to create development opportunities for the next generation. By the Digital Agenda Strategy 2015–2020, we define our vision and will to become a member of the European Union (Ministry of Innovation and Public Administration at Council of Ministers, Albania 2015). It is clear that the Albanian Government thinks that ICT must be seen as a tool that changes everyday life, transforms our work, organizations, and changes the existing markets by creating new opportunities and businesses, changes participation, cooperation, and interaction models, but first, to transform the Public Administration to open and transparent governance. Usually, as we know, the generations are differentiated by periods of 20–25 years, whereas the evolution of technology differentiates the generations of people for periods of about 10 years. The problem is that this group of relatively young generations are absolutely different within themselves, and we must understand the difference and similarities of this group because some of them are part of an academic staff and the younger are students. The development perspective is thus technological and social. The ICT and digitalization processes support modernization of a society as follows:

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Economic processes through the improvement of production capacities based on the ICT, knowledge economy, and establishments of start-ups, development of innovative and intelligent activities in cities and communities, production growth in agriculture, social enterprises, etc. Social processes through the improvement of services provided to the community and that of joint goods production, stimulation and facilitation of social innovation, joint establishment and utilization of resources and financing (known as “crowd sourcing” and “crowd funding”), etc. Institutional and administrative processes through the e-government services, digital identity, facilitation of inter-institutional interaction, simplification of institutional and administrative procedures, delivery of online auxiliary assistance, participation of citizens and businesses in the decision-making process (Ministry of Innovation and Public Administration 2015). Changes are part of the way ICT and its various forms of application have entered the lives of individuals, supporting social life, employment, facilitating work, and so on. If we look at the domestic and international sources, we can better understand what has changed over recent years in Albania with regard to ICT and developments related to it, but also even the prospects for change, trends, and areas where it is possible that this change is displayed. The Fourth Industrial Revolution represents a transition to a new set of systems, bringing together digital, biological, and physical technologies in new and powerful combinations. The mechanisms that drive human resources and human capital in general are shown below as a complexity of collaboration of network readiness, also as drivers and impact. We have chosen this figure because networked readiness depends on the drivers necessary for digital technologies to meet their potential and how these technologies are impacting the economy and society today and in the future. Thus, Fig. 1 helps us to better understand the forces that push the development of economies, the mechanisms that drive economic potentials, and the changes that the economy brings to the standard of living, the socioeconomic and cultural status of the individual and the groups. Table 1 and Fig. 2 show the changes from 2015 to 2016 in the Networked Readiness Index Albania, explained by a range of pillars. The Networked Readiness Index (NRI) is a key indicator that poses the digital development of a country or society in the world. In addition, the NRI measures how well an economy is using information and communications technologies to boost competitiveness and wellbeing. The Networked Readiness Index changed from the rank 92 (of 147) in 2015 to the rank 84 (of 139) in 2016. The respective change in values is from 3.7 in 2015 to 3.9 in 2016. Specifically, the NRI for each pillar has changed as in the following table. From Fig. 2, it seems clear that the increase in NRI is explained by the respective increase of NRI in infrastructure, affordability, and skills.

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IMPACT

Environment Infrastructure

Affordability

Skills

Economic

Individual

Business

Government

Social

Readiness

Usage

Fig. 1 The Networked Readiness Framework. (Reprinted from World Economic Forum 2016)

Table 1 Networked Readiness Index in detail for 2015 and 2016

Pillars 1. Political and regulatory environment 2. Business and innovation environment 3. Infrastructure 4. Affordability 5. Skills 6. Individual usage 7. Business usage 8. Government usage 9. Economic impacts 10. Social impacts

2015 Rank (of 143) 113

Value (1–7) 3.1

2016 Rank (of 143) 109

Value (1–7) 3.2

69

4.3

61

4.4

84 92 65 79 103 78 125 82

3.5 4.5 5.2 3.6 3.3 3.7 2.5 3.8

75 92 29 83 93 76 121 76

4.1 4.7 5.7 3.6 3.4 3.7 2.6 4

Source: World Economic Forum 2015, 2016

1.1

Process and Systems in Change and New Model of Learning

The higher education system is by nature a consistent system, but based on the Bologna Process, Digital Agenda, and UNESCO, Albanian higher education faces changes, which are even deeper because of the use of new technologies inside and outside the learning environment (National Information and Communication Technologies Strategy for Albania, 2003, 2008). It is happen because one of the immediate important problems of Albanian society is that a mass of graduates is not equipped with the proper skills, knowledge, and dispositions that allow them to be functionally productive within the context of Albanian economy. We, as society and its education institutions, want to survive in the digital era, and we are changing and must continue to change deeply and

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Fig. 2 Networked Readiness Index

rapidly. We think that higher education in Albania, as in all developed countries, is considered a public service and a public good, and therefore, one of its main goals is to maintain the basic principles of this education such as the principle of equal opportunities, the principle of free competition, and, above all, being a public service, to which all have access on the basis of merit (Nikaj 2015). The following changes are seen in our environment: First, from 2013 until now (2019), some conditions for the development of mobile networks and technology have changed rapidly in Albania, despite the fact that in quantitative terms, there are a small number of users with relatively limited applications, although the network offers many opportunities for applications. Second, among the innovations that we can highlight is a more flexible response of the governing institutions, especially the Ministry of Innovation and Public Administration (MIAP), which has led an intensive e-agenda during the past 4 years to make changes in the way we approach and use technology in everyday life, to receive and provide/create services. Third, the general trends in ICT and Mobil Learning, which have impacted the Albanian Higher Education Institutions, are shown here:

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Micro-learning is a short, focused learning chunk of information on a topic that is designed to fulfil a specific learning objective. App-based learning includes effective implementation of micro-learning, simulation and game-based learning, extensive control on tracking and learning management, and offline performance support applications anywhere and anytime. Mobile Learning is a trend and a rising need with an increasing number of mobile users across the globe, delivering their training to them on their devices, in addition to tablets and computers. That is one reason why mobile learning will continue to attract the attention of learners today. With more content going online, learners can access information across different devices based on their location or needs. Video Learning: if we think about the popularity of You Tube, we can easily understand the importance of this in training courses. In fact, our brain processes video about 60.000 times faster than text, so that more videos are more engaging for learners. Recent studies revealed that courses with videos have a 51% completion rate whereas those without videos have as low as 36%. Social learning is a concept that is not new but certainly is on the rise in our environment because social learning or informal learning takes place through e-learning; collaborating and connecting with others who are taking the course benefits them while they interact. Gamification as the application of typical elements of game playing is taking place because it is a source of motivation, promises to make hard tasks or duties fun. Thus, creating possibilities for offering incentives, certificates, or badges upon completion of courses encourages students/learners to complete their courses in a competitive manner, to motivate participation, engagement, and loyalty. Adaptive Learning is programming that focuses on learner requirements and their current understanding of the matter. This procedure helps them progress at a faster pace in the subject with which they are familiar. In addition, adaptive learning has been of great importance for mobilizing Mobile Learning to its full potential, because it pays attention to the points of interest of learners through more personalized training. Augmented Reality is yet to be implemented on a large scale, especially in highrisk occupations. Virtual reality has the potential to change the overall landscape of the e-Learning area via the immersive experience it provides to the learners. The changes are visible in Table 2 and Fig. 3, which show quantity and quality data for Internet users in Albania in 2016 and in a period of time from 2000 to 2016. The findings in the table show that during the past 3 years, the percentage of the population using the Internet and technology is greater than 60%, and with a trend to increase in future years. The data and the graphs show a growing trend in the percentage of Internet users in the Albania population, reaching the value of 62.8% in 2016. Considering that the number of Internet users in the world in 2016 was 3,424,971,237, the share of Internet users in Albania, of the world Internet users, is only 0.1%.

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Table 2 Extent of Internet users in Albania in years 2000–2016

Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Total population 3,121,965 3,124,093 3,123,112 3,117,045 3,103,758 3,082,172 3,050,741 3,010,849 2,968,026 2,929,886 2,901,883 2,886,010 2,880,667 2,883,281 2,889,676 2,896,679 2,903,700

Internet users 3,562 10,178 12,183 30,295 75,123 186,283 293,176 452,715 708,171 1,207,113 1,305,847 1,414,145 1,574,456 1,649,237 1,736,695 1,794,798 1,823,233

Penetration (percent of population, %) 0.11 0.33 0.39 0.97 2.42 6.04 9.61 15.04 23.86 41.20 45.00 49.00 54.66 57.20 60.10 61.96 62.79

One-year (1Y) user change (%) 40.40 185.74 19.70 148.67 147.97 147.97 57.38 54.42 56.43 70.46 8.18 8.29 11.34 4.75 5.30 3.35 1.58

Population change (%) 0.23 0.07 0.03 0.19 0.43 0.70 1.02 1.31 1.42 1.29 0.96 0.55 0.19 0.09 0.22 0.24 0.24

Source: Internet Live Stats 2016

Fig. 3 Albanian Internet users by years

The ICT is already a mass phenomenon that has involved most of the population, not only urban dwellers but also the rural population. Albania represents today a society with a steadily growing trend of ITC and the incentives that it gives to economic development.

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1.2

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Development of Supporting Tools in Learning Process

1.2.1 Role of the Lector We are sure that the traditional learning process and resources, chalkboard and master classes, no longer present the reality of professional life to students. Certainly, the class depended entirely on the teacher, who could get very close to the auditor. Visual methods with slides and transparencies provided support and have endured for many years. Flip charts have been very useful in small classes but are useless in classes with a large number of attendees. Television and video were used mainly to play movies, documentaries taken on the matter. The revolution came with the video projector. The lector can bring all the material, selected and prepared previously. Smart or interactive whiteboards create possibilities for the student to participate actively in classes or in the learning process, and also can test the student’s knowledge on the subject, but the lector/instructor will be encouraging creativity, will be an organizer of knowledge and skills, and will be managing the student’s time. 1.2.2 Role of the Student Technological development creates a new reality for students, because they have changed from taking handwritten notes of all subjects to active learning. This development has led to a change that allows them to pay more attention to the explanations, not to focus on taking notes, and thereby to participate more actively in classes. The dynamism of the classes makes it easier to capture a student’s attention: working in a group can train the students in horizontal skills as important as teamwork. Classrooms are getting smaller, and modern classrooms are flat. This reduction in size is aimed to accommodate a smaller group of students to enable them to perform collaborative learning and project-based learning. Today the classrooms have a configuration that is not teacher oriented, with a round table and the whole space with screens on all four walls. 1.2.3 The Learning Process The learning process has changed rapidly. Collaborative learning, supported by the availability of learning materials consulted by students, has created greater interaction between the lector and the student. It required much more preparation by the lector, but allowed students to collaborate more efficiently with the lector and the entire group of students. The project-based learning tries to place the student in a situation similar to that of the workplace, and thus to create conditions to learn in a personal manner, individually or in groups. As well, network resources have had a great impact on active learning. 1.2.4 Gender, ICT, and Mobile Learning As all aspects of human interaction, ICT are gendered. ICT contributes broadly to readjusting social rules for interaction, offering new channels for establishing and accessing connections and relationships. Globally, ICT transforms the way production is organized and information is shared. ICT offers flexibility of time and space, a

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way out of isolation, and potentially increased access to knowledge and productive resources, even in remote locations. But ICT may also contribute to discrimination and reinforce existing inequalities. Considering the manifestations of gender inequalities in the access, use, and control of information and communication technologies and how those inequalities can be erased, at the same time, it is shown how ICT can provide opportunities for women to improve their incomes, gain awareness of their rights, and improve their own and their families’ well-being, the so-called quiet gender revolution. The data of women who study at universities and use ICT emphasize the possibilities for women’s empowerment through ICT. In national and international reports, the trend of the number of women attending bachelor, master, and postgraduate studies has steadily increased. In Albania, the numbers of women who are studying are larger than those of men, a trend that has not changed during the transition years (1990–2017), despite the external and internal migration rates, wage inequality between men and women, gender discrimination, high unemployment among women, and difficulties within an emerging but still very uneven society. Even in our study, female students are significantly higher than male students, showing exactly the trend that is observed in Albanian higher education in general (total of 106,077/66,124 females in academic year 2016–2017) [source: Institute of Statistics (INSTAT)].

1.2.5 Subject and Methods The basis of the Universe may be not energy or matter, nor information. The Digital Revolution strongly influenced the children born at the end of the twentieth century and in the first decade of the twenty-first century. These children are found in different studies named with the Y and Z definitions and represent social groups with close links with personal computers, computer games, WEB (an Internet-based hypertext system), and all the data tables and gadgets available. For this reason, in the framework of our research study, a survey of the students from the Faculty of Economics (Branch of Marketing and Management) and Education and Philology (Master of Science in Primary Education) has taken place. The aim of this survey was to collect data for the use of technology and mobile learning from the students in their everyday learning and life. We believe that there are two different profiles among the students interviewed: one dynamic and one less dynamic, which are correlated to the content of their study program. A questionnaire was prepared for the purpose of this survey. The questions intended to collect data about the use of mobile phones, use of different web applications, and the duration, purpose, and influence of these devices in mobile learning, utilizing 52 valid interviewers. We analyzed the data by different social groups related to gender, origin and residence of each student, and by mobile type as well. The data collected for each question group are summarized and visualized in the following tables and figures, respectively: 1. What mobile phone are you using? (Table 3, Figs. 4 and 5) 2. Which application or Web sites usually are used for studying? (Table 4, Fig. 6)

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Table 3 Use of mobile phone Female, city Female, country Male, city Male, country Totals

iPhone 4 6 2 1 13

Telephone mobile 5 5 7 6 23

iPod 0 0 0 0 0

Other 4 9 0 3 16

Total 13 20 9 10 52

Fig. 4 Use of different types of mobile phones by different groups

3. Where do you usually use your mobile devices? (Table 5, Fig. 7) 4. How long are you using your mobile phone to study per day? (Table 6, Fig. 8) 5. What are the thoughts about positive influence of mobile learning? (Table 7, Fig. 9) In the following we display these results for each group of questions. 1. What mobile phone you are using? 1. iPhone 2. Mobile device 3. iPod 4. Other Figure 4 shows that for both genders, the use of the mobile phone by students living in villages is greater than that of students living in the cities. Change seems to be greater for females. According to the foregoing graph, 64% of mobile users are female and most of them live in the country.

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Fig. 5 Overall use of mobile phones by different groups Table 4 Application use for study purposes

Female, city Female, country Male, city Male, country

Learning Internet Web pages of Google Wikipedia YouTube universities 12 9 2 4

iTunes U or Google Play 1

Online news 4

Instructions package 1

Other 0

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2. Which application or websites are usually used for studying? 1. Google 2. Wikipedia 3. YouTube 4. Learning Internet-web pages of universities 5. Applications on iTunes U or Google Play 6. Online news 7. Instructions package 8. Other Most of the students who use applications for study purposes are females who live in the country. iTunes U and Google Play are the applications most used.

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Fig. 6 Application use for study purposes Table 5 Use of mobile for different purposes

Female, city Female, country Male, city Male, country

Lectures and assignments 8

Meeting friends 5

Reception 1

Walking or on transportation 6

Ordering food 2

At work 2

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3. When do you usually use your mobile devices? 1. Lectures and assignments 2. Friends’ meetings 3. Reception 4. Walking and transport 5. Ordering food 6. At work An interesting result noted on Fig. 7 is that the females who lives in the country use their mobile phone more for the purpose of meeting with friends. 4. How long do you use your mobile phone to study per day? 1. 2 h minimum 2. 6 h maximum 3. 4 h on the average

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Fig. 7 Use of mobiles for different purposes

Table 6 Daily usage of mobile phone for study purposes Female, city Female, country Male, city Male, country

Minimum, 2 h 13 19 0 5

Maximum, 6 h 0 0 3 0

On average, 4 h 0 1 6 5

Fig. 8 Daily usage of mobile phone for study purposes by gender and rural/urban dwellers

From Fig. 8, it is clear that although the number of females using the mobile phone is greater than the number of males, on a daily basis, they use it less than do boys.

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Table 7 Positive influences of mobile tools used for learning in total (number of responses)

Female, city Female, country Male, city Male, country

Use any time or Study Enhances anywhere interval for learning and efficiency anytime studying

Increases Increases my quality of interest learning for learning hours

Possibility of discussions with students and pedagogues

Quality of my preparation in education subjects

There is no existing role for me Other

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Fig. 9 Positive influences of mobile tools used for learning in total

5. What do you think about the positive influences of mobile learning? 1. Enhances learning efficiency 2. Can study anywhere and at any time 3. Can use any time interval for studying 4. Increases the opportunity to request and learn during learning hours 5. Increases my interest for learning 6. Gives the possibility to be involved in discussions with students and pedagogues 7. Increases the quality of my presentation, preparation, and disciplines in education subjects 8. There is no existing role onto me 9. Other

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According to Fig. 9, mobile learning helps the students to study more, anywhere and anytime, and to discuss their work with other students and pedagogues.

2

Discussion

We have presented, in this chapter, the results of our survey of which the purpose was the use of technology and mobile learning in the everyday life of students in different study programs. In general, the data show an increase in the number of students who use mobile learning more often and in everyday life, both female and male students, in a broader spectrum of uses. The basis of our view is that technology is used intensively and that this phenomenon certainly affects each of these students, but also the economy, culture, and quality of life of the population of the country. We work and live in a “knowledge society,” and its mission is to create, share, and use knowledge for the prosperity and well-being of its people. Thus, the evolution of Mobile Learning in Higher Education in Albania should take the following direction: the existing mobile learning environments participating in future mobile learning as content repositories, but the active part of the learning process covered by a personal learning environment, in which the students, using their favourite i-services and i-tools, for example, i-mode, will construct their knowledge in constant collaboration, just a click away from the knowledge, from the services, from a complex social life. This was a descriptive study based on the data collected. Comparative research and a study on the possible factors that can influence the use of mobiles and technology will be subjects of our future work.

References Internet Live Stats. 2016. Albania internet users. http://www.internetlivestats.com/internet-users/ albania/. Accessed 29 Aug 2017. Ministry of Education, Sports and Youth. 2015. The law of higher education in Republic of Albania, No. 80/2015. https://arsimi.gov.al/ligj-nr-802015-per-arsimin-e-larte-dhe-kerkimin-shkencorne-institucionet-e-arsimit-te-larte-ne-republiken-e-shqiperise/. Accessed 29 Aug 2017. Ministry of Innovation and Public Administration at Council of Ministers. 2015. Cross-cutting strategy, digital agenda of Albania 2015–2020. http://akshi.gov.al/wp-content/uploads/2018/03/ Digital_Agenda_Strategy_2015_-_2020.pdf. Accessed 29 Aug 2017. National Information and Communication Technologies Strategy for Albania, 2003, 2008. http:// www.ictd.org.al/strategy/strategy_en.pdf. Accessed 29 Aug 2017. Nikaj, I. 2015. Expectation from future technologies and e-learning in higher education in Albania. In Handbook of mobile teaching and learning, 1–28. Berlin/Heidelberg: Springer. World Economic Forum. 2015. The global information technology report 2015. http://www3. weforum.org/docs/WEF_Global_IT_Report_2015.pdf. Accessed 11 Sept 2017 World Economic Forum. 2016. The global information technology report 2016. http://www3. weforum.org/docs/GITR2016/WEF_GITR_Full_Report.pdf. Accessed 11 Sept 2017

Mobile Technologies and Learning: Expectations, Myths, and Reality

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Myths and Expectations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Technical Side . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 The M-Learning Paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Learning and Learner Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Learning Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Learner Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 M-Learning Trade-Off Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

M-learning is often approached as an innovative method to teach, but quite often without the proper planning of the actual learning process and proper understanding of the implications on the pedagogy of the learning process in such a setting. Because of the multiple stakeholders in the process – the institution, the learners,

L. Petrakieva (*) Learning Development Centre / School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK e-mail: [email protected] D. McArthur Learning Development Centre / School of Computing, Engineering, and the Built Environment, Glasgow Caledonian University, Glasgow, UK e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_28

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the educators, the policy-makers, etc. – it is very difficult to encourage educators to engage with something so different that will require a rethink of their teaching practices. In addition, with so many different technical elements and challenges, it is often simply just too daunting a prospect. It is also unfortunate that m-learning is often only limited to simply mobile access. A good m-pedagogy will not just transfer the learning process to a mobile device but incorporate the very nature of mobile, flexible, user-guided, bite-sized learning. The recent rise of learning and learner analytics has also highlighted the issue of how students engage with university systems and the ethical consideration of such data being collected and used. Real m-learning needs to have a real purpose, and the stakeholders need to see the value in it for it to have a chance to be a success. Having all the correct m-pedagogy in place and if both educators and learners see the value of engagement, m-learning can bring real benefits – flexibility of access and freedom of engagement therefore allow a real meaningful tailoring of the learning process. Only very recently have real attempts been made to motivate progression toward adaptive learning. Incorporation of pedagogy and AI (artificial intelligence) methods seems to be pointing to a future of real, adaptive, and effective m-learning.

1

Introduction

With the development of the humble mobiles from a cordless phone that can be carried around to a supercomputer that can do almost anything imaginable that a piece of technology is capable of, the excitement of the potential use for education has grown exponentially (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). As new generations of learners become seemingly more digitally literate, the drive to engage more with technology-enhanced learning is being driven mostly by learners (because they are used to it) and by the management (seeing it as a cost-saving exercise and promotion opportunity). However, the full understanding of the pedagogy in relation to the use of technology, the understanding of the real level of digital literacy of the learners, the fast pace of technological development, as well as the sometimes resistant-tochange educators or CAVEs – colleagues against virtually everything – have to be taken into account when any technology-enhanced learning and especially mobile learning solution are being implemented (see ▶ Chap. 49, “1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation”). The term educators will be used in this chapter for lecturers, teachers, and many others involved in teaching in one way or another, bearing in mind that not all involved in mobile learning will be lecturers; there will be tutors, learning technologists, teaching fellows, and others.

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Mobile Technologies and Learning: Expectations, Myths, and Reality

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Myths and Expectations

There is an expectation from learners that when they come to university or college, they will be given Wi-Fi access and access to technology, as well as provided with training of how to use it in an education setting. The Digital Student project (JISC 2014) shows that although the expectations vary greatly, some are quite widespread. According to Beetham (2014), some of the common are (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”): • Robust and ubiquitous Wi-Fi across campus locations • Easy to connect their own devices to the university network and access personal/ social web services • Continued access to institutional devices, especially desktop computers with relevant software for their use And while the students have some clear expectations in terms of the technology and connectivity, when it comes to the role of technology in their education and especially in terms of their chosen course and future career, the students are unclear (Beetham 2014). This is where the role of an educator comes in, and it is important to understand that this role comes with big responsibility. The information and communications technology (ICT) confidence of the teaching staff has a strong impact on the students and their own use of technology. From an institutional point of view, “digital natives”(Prensky 2001) are an increasing proportion of the new learners, so they are not supposed to need so much support and training, apart from access to technology. Although a number of subsequent studies (Bennett and Maton 2010; Margaryan et al. 2011) have shown that the “digital natives” are a myth and there is much more variety and nuances in the skills, abilities, and attitudes of the learners, the institutions seem to cling on to that notion that learners use technology all the time and are able to learn how to use it on their own (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). With the ubiquitous access to mobile devices now, most institutions are also keen to implement a BYOD (bring your own device) strategy, as this is usually seen as a very cost-effective way to reduce the money spent on technology. However, the Digital Student project’s (JISC 2014) most recent findings published clearly state that students “don’t want technology to be a substitute for ‘the real people, in the same place, learning together” (Beetham 2014). That means that the institutions are still expected to maintain access to computer labs, printers, etc. and with the increased diversity of devices brought in as a result of BYOD, the technical and support staff actually have an increased workload, so overall the idea of using BYOD for cost-saving reasons for the institution ends up costing more to the staff (Keyes 2013). Most of the universities and colleges have included the notion of creating digitally literate graduates in their policies, mostly with emphasis on employability, but the strategy to achieve that is usually simply relying on the teaching staff to be able to do that as part of their subject teaching and not recognizing the need for

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specialist on digital literacy to teach both the educators and the learners. Most of the time, the institutions will be keen to promote and show that they are implementing technology-enhanced learning or blended learning and have the attitude that all learning is suitable to be carried out using technology, even if that means simply putting up your lecture slides in the institutional virtual learning environment (VLE). Using VLE for every module is one easy way of showing that the institution is using “blended learning.” Providing electronic feedback is another common use of technology that often justifies the use of the term “blended learning.” However, there is a big difference between providing access electronically to teaching material and true blended learning and m-learning (Littlejohn 2007). Universities, colleges, and schools have all tried to modify and adapt the teaching to incorporate mobile technology, and almost all support departments are scrambling to create apps, so they can get to the learners quicker and closer. A quick search in the App Store and Google Play with almost any higher education institution’s name will show at least one app created. A lot of institutions are also using generic apps to get access to their resources like library (LibAnywhere, BorrowBox Library, etc.) and VLE (Blackboard Learn, Moodle Mobile, etc.). However, a lot of them are still struggling to understand and utilize the potential of true mobile learning, not just mobile access or mobile services. What is usually lacking is a proper m-learning and m-teaching strategy, with support for both educators and learners to fully benefit from m-learning.

3

Reality

3.1

Technical Side

The use of mobile devices in a learning and teaching setting also has technical limitations that need to be taken into account. Some of the issues of using mobile devices to access information are discussed by Petrakieva (2012, p. 159), and although the mobile device features are constantly improving, the majority of issues are still present simply due to the nature of the devices (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Some of the main ones are: • Access to technology – educators can design good m-learning only if they are familiar with the particular technology, and this means having access to it. It also means that in order to make sure that everything will work on the learners’ devices, the institutions will have to either issue the devices to every learners, thus ensuring parity, or make sure that anything created is rigorously tested on all popular systems (iOS, Android, etc. devices; see figure below) while also offering borrowing options for those without a smart mobile device. The mobile operating systems market is converging at the moment with the main considerations focused on only two systems – Android and iOS – however, this could vary depending on the country and access to technology, so an overview of the particular context is still advisable (Fig. 1).

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Mobile Operang Systems Sales shares for Q1 of 2016

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Mobile Operang Systems Sales shares for Q1 of 2017

Android

Android

iOS

iOS

Other OS

Other OS

Fig. 1 Mobile operating systems new sales shares, first quarter of 2016 and 2017 (Gartner 2017)

• Wi-Fi and mobile Internet access – if the m-learning is to be part of a class, access to the Internet due to buildings that were built before Wi-Fi was available and simply the lack of bandwidth to support large classes are common problems. The same problems exist with the mobile network coverage, and not all learners will have mobile phone contracts that will allow them Internet access, or they may simply not wish to use a personal device and contract in class nor should they be expected to. • Software access – most of the m-learning solutions will involve specialist software, either ready to buy or custom made. In both cases there is the issue that most free versions have severe limitation and thus limited application or a license needs to be purchased which usually involves preparing a business case by the educator so the institution can justify spending the resources. The required know-how in choosing the right software; the skill set involved in using the software, potentially having to write a business case; and the time required are great deterring factors for educators not to pioneer m-learning in their institutions.

When m-learning is concerned, it also should not be forgotten that the situation in the developing countries is very different in terms of access to technology, access to the Internet, etc. Although the difference between the availability of mobile technologies in the different parts of the world is narrowing, it is going to have an impact on the way m-learning is being used for some time yet. In a recent report by UNESCO (West and Ei 2014), it is very clearly shown how simple basic access to mobile reading makes a big difference to the people in the developing countries; however, simply having access is not enough. “People who think that literacy can be achieved by mere proximity to reading material should be reminded that it took the most talented linguists on the planet over a thousand years to decipher Egyptian hieroglyphs. The challenge wasn’t access to hieroglyphs; it was figuring out what they communicated. Humans may have a language instinct, but there is nothing

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natural about reading; it is a skill that needs to be taught and practiced, again and again and again” (West and Ei 2014). Similarly, there is nothing natural in using technology for learning either. Simply providing access to it to educators and learners will have a very minimal and limited effect. That is why a development strategy, support structure, communication, and willingness to change and develop are some of the major other components of a successful implementation of m-learning that are often forgotten or ignored. For now, the focus will be on the developed markets where the mobile technology penetration is much higher and the m-learning can be considered as a viable option to go into the mainstream education. And although developed countries are assumed to be uniformly well-off, there are big differences within them. There is a big drive in a lot of countries for widening access and participation. “Across the world, higher education has turned from a privilege available to an elite few into a mass expectation”(David et al. 2012). All learners are assumed to have access to technology (PC/laptop at home, smartphone with Internet access, tablet); however, as mentioned earlier, access doesn’t equate skills to use the technology for educational purposes. The digital divide is still very much alive, and although there seems to be a shift from knowledge gap to usage gap (van Deursen and van Dijk 2013), there should not be an assumption that all learners will have access to mobile technologies to an extent of using them for m-learning.

3.2

The M-Learning Paradigm

Before any m-learning is implemented, a clear investigation of the particular needs of the learners and educators and the underlying pedagogical reasons is necessary. Implementing m-learning for the sake of doing it is a common reason why it fails to deliver on the expectations. Taking into account the universal instructional design (UID) principles for mobile learning suggested by Elias (2011) with an emphasis on solid pedagogical approach can be the key to a successful m-learning application. The major stakeholders in the process – the learners and the educators – have to see the need and the value in investing in a potentially difficult new approach. Without this full investment in the process, after the initial novelty effect has worn off, the learners will simply revert to the familiar study patterns. Following Maslow’s idea (1943) of hierarchy of needs, going from basic (deficiency) needs to growth (self-actualization) needs, the m-learning could be viewed in a similar way, taking into account the slight differences of the two main stakeholders: learners and educators (see Fig. 2). Although a real m-learning can only be achieved when all layers are present, so it should be outside, encompassing all, it has been put in the center, as a pearl in a shell that can only develop fully when the shell is complete and strong and surrounding environment is fertile.

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Fig. 2 M-learning requirements hierarchy

3.2.1 The Learner Perspective The most basic requirement to achieve real m-learning is to make sure that the learner has access to a smart mobile device. This may be taken for granted in most developed countries; however, that cannot be simply assumed when the learning is taking place in a developing country, for example And it is not so much the mobile device itself but their ubiquitous access to the Internet that makes the difference to what people use their devices for. And although in most universities there is free Wi-Fi access, the m-learning idea is to make the learning accessible anytime anywhere and that means learners having ready Internet access. Very few institutions yet are providing the mobile devices to their learners, and that means that most mobile devices are for personal use as well as for study. The influence of the ICT self-efficacy to the adoption of m-learning (Callum and Jeffrey 2013) should also be considered. When the learner is faced with using new technology, the real and perceived lack of ICT skills may be a barrier to the engagement. The appropriate support in place is crucial for overcoming such problems. Nurturing a positive attitude to the process is key to the success of the process, as even with all the technology setup and with all the skills necessary, if learners don’t want to engage, the implementation and use of m-learning will not be a success.

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3.2.2 The Educators’ Perspective Access to technology is even more crucial for educators as they need to be able to set up the m-learning to work with any mobile device that the learners can use or make sure that one is issued to them. Most of the time, this requires either a lot of resources (in the cases when devices are issued to the learners) or specialist technical knowledge, usually from technical staff in the institutions (in the cases when the m-learning has to be compatible with all devices). Because of this, most of the time, the educators end up simply setting everything up just through web access, and because all mobile devices now ubiquitously have this capability, this approach ensures that all learners can access it. But this ends up no different than the e-learning that educators are used to, and it becomes too easy for them to fall into the pattern of producing just e-learning materials and not really adapting the approach for a real m-learning. Providing the educators with the technology and the necessary training to use this technology is important for allowing them to adopt fully m-learning and to concentrate on best using the technology to support the pedagogy. There is also a need to re-evaluate the pedagogical approach when using m-learning (Clark 2014) and not just add on technology or “mobile access” and claim that that is m-learning. The fundamental difference of using mobile devices, with their limited screens, limited creativity tools, and limited Internet access, does also provide an opportunity to develop a more natural, bite-sized delivery that is not just linear, but interlinked, thus allowing good educators to deliver a better learning process and achieve better learning outcomes by providing flexibility and allowing the learner to incorporate the learning into their life. Once the m-learning pedagogy is thought through and properly planned and with the technology in place, the educators’ ICT skills will play a crucial role in translating the pedagogy in a real m-learning experience for the learners. If the educators have low self-efficacy in ICT, that will have an impact on the perceived difficulty of engaging with m-learning by the learners (Mac Callum and Jeffrey 2014). The expectation that educators will have adequate ICT skills to implement m-learning can be one of the major reasons for the educators not to get involved in m-learning as they feel they don’t have the skills and they will not be offered support to develop those skills (Aubusson et al. 2009). Another one of the main features of the m-learning approach is flexibility. Allowing the learner to dictate how, when, and what they access is paramount, and in order to create an m-learning process that can accommodate that, and even more, to use this as its main advantage, means that the educator has to have an approach and attitude flexibility. Change should become an intrinsic part of the process, and thus the expectation that things will happen according to plan is tenuous. So flexible attitude is needed – plans will change, technology may fail, and learners will not behave as expected – and that should be taken as an opportunity to develop a better, more flexible, and more robust approach to m-learning and not as a sign of an impossible task. That flexibility and preparedness for change should be a vital part of the attitude of the educator to make the m-learning a success story. One of the outcomes of the Jisc Digital Capabilities project (JISC 2017a), which investigated the different strands of what it means to be digitally capable, has been

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Fig. 3 Jisc Digital Capabilities framework (JISC 2017a)

the framework illustrated in Fig. 3. It shows the ICT skills at the center since they are fundamental for any digital endeavor; however, they are not the only required element to be a digitally capable educator, especially if a more advanced approach is being used such as m-learning. The recent pilot of a Jisc Discovery Tool for evaluating digital capabilities highlighted in its feedback how much academic staff valued the discussion created around the subject and the opportunity for targeted development (Beetham 2017). Combined with the fact that only 36% followed up with the resources suggested for developing further their digital capabilities clearly still indicates how difficult it is to engage staff in developmental work, even when they are aware of their need for that development.

3.2.3 The Environment The m-learning process can only really succeed when there is a need to implement it and both sides of the process – the educators and the learners – see the value in doing so. If the m-learning is used just as a box-ticking exercise to show that the institution is engaging with new technology and approaches, the process will inherently start off with the incorrect premise, and neither the educator nor the learners will have the impetus to engage with it. Both main stakeholders will have to see the need and the value in using m-learning and thus will be invested in making it a success. Valuable outcomes from effective m-learning are of a bifold nature: Firstly, successful student learning and motivation to engage with their studies, and with the technology used, can both be improved. This outcome forms an integral part of any learning process and pedagogy.

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Secondly, the use of m-learning allows for the collection of data regarding the engagement with the learning process itself. This type of data has recently been identified as a major area of focus for most Institutions, as it can be used to identify potential problems and issue in the future. Learning and learner analytics are seen as effective ways to predict and better guide interventions. Depending on how the gathered data is viewed and utilized, different types of analytics exist. The data analysis perspective also differs when looking at either learning or learner analytics.

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Learning and Learner Analytics

4.1

Learning Analytics

Higher education institutions have become fixated with the concept of data gathering and the possibility of using such data to measure the educational contributions of online learning resources and applications. The use of virtual learning environment (VLE) such as Moodle, Blackboard, Canvas, etc. provides effective online platforms and interfaces through which learners access their course materials and interact with their programs of study. Each VLE provides a plethora of data streams regarding the accessing of study modules, and interaction with resources therein, highlighting student engagement with their respective modules. The inclusion of third-party and in-built tools for assessment is frequently used by institutions to generate coursework, online tests, and written assessments through which the student learning pattern is monitored. The data harvested through these systems is analyzed through dashboards to identify student engagement and activity to predict student’s potential for success and to identify those who are at risk of failing to achieve their imaginable outcomes within their modules of study. There is a widespread interest in this type of analytical approach, and some good examples of practice, including Manchester Metropolitan University, the University of Bedfordshire, and the London South Bank University’s partnership with IBM, have used such systems. The Open University have also utilized their AnywhereApp to the same effect (De Quincey et al. 2016). Students do not, however, limit themselves to learning only via university-based systems, e.g., VLE, etc. Utilizing their own mobile technologies and home-based computing systems allows for a wider and varied repertoire of research and learning options to be accessed (see ▶ Chap. 52, “Student Feedback in Mobile Teaching and Learning”). Social media feeds such as Twitter and Facebook groups, blogs, wikis, and other social and/or informal learning contribute to student learning and are completely outwith any scope of measurement by university-based monitoring systems. These learning pathways, and the associated knowledge garnered, cannot be tracked nor analyzed, by university systems, leaving a considerable amount of

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learning data potentially missing, which could lead to misinterpretation and misguided interventions planned on incomplete data. An analysis of student engagement through dashboards and VLE data feedback does form a relatively effective overview of student learning from the teacher/ lecturer perspective; however, the student’s view of learning analytics as a motivator is not necessarily the same.

4.2

Learner Analytics

The main focus of research in this field has largely fallen upon learning analytics, where the information is used to guide improvements and interventions to the learning process. When this data is used to monitor progress and guide interventions regarding the learner, the focus falls upon the learner engagement, and the overall analysis perspective changes. However, this raises potential ethical questions regarding how data is collected and the purposes for which it is used. This is still very much an open debate within the educational community. The educational community is very much concentrating on the learning analytics and only seeing the learner analytics as a side aspect of it and thus avoiding the focus on it. The recently agreed JISC Learning Analytics Services terms and conditions state: “If Learning Analytics Services are agreed, Personal Data will be analysed to provide learner level information, and combined to provide grouped information, for example at a course or module level”(JISC 2017b), which clearly indicates the educational sector’s approach of using the term learning analytics for all aspects of data collection and analysis even when the data is used at a learner level and for learner intervention. Very few studies exist regarding student’s views and interpretation of learning analytics and how the use of such data can work as a motivator for improving their overall experience and learning outcomes. A study carried out by Keele University on a group of their own computer science students (De Quincey et al. 2016) revealed that their perceptions of the IT systems used for analysis were limited in their output with regard to student motivation. Suggestions formulated by students for effective “learner analytics” and motivators for increased engagement included VLE dashboards to present data elements such as attendance and assessment tracking, engagement, activity, and progress meters. National student surveys (NSS) carried out annually within the UK regarding programs of study within higher education institution offer final year students the opportunity to give their opinion and feedback regarding their experiences of their course of study. The outcomes of this survey are looked upon with great interest and importance by all institutions. Each year, for many institutions, the returned feedback from the NSS highlights the student’s need for improved “feedback” from their module and programs of study. Maybe it is time to implement the student perspective, provide visual learner analytic data that motivates positive study activities, and reap what mutually beneficial rewards appear.

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The access to the learner analytics data for learners themselves could prove to be even more beneficial than the institutional use of it, as it may trigger more intrinsic motivation for the learners themselves.

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M-Learning Trade-Off Issues

Educational pedagogy would generally dictate that, when using an online resource for information delivery and incorporating interactivity, when input is required, it is necessary to retain the context of the input requirement visible to the user. That however becomes a major issue when designing for small screen m-learning. Some compromises therefore need to be incorporated into the m-learning pedagogy to allow for effective small screen m-learning development. One example of a system, developed as a learning object with varied device uses in mind, is a pilot project within Glasgow Caledonian University. The Pre ICT Induction (PICTI) (Petrakieva and McArthur 2017) is based upon many years of experience delivering ICT Induction to new students. The information delivered via the resource was designed to be viewed on medium to larger screen sizes; however the information could also be read on smaller handset devices. Issues for designing for smaller screen delivery became apparent when interactivity with the resource required students to input information. The moment a screen keyboard appears, the screen real estate available on small handheld devices reduced significantly from an already limited screen space as illustrated in Fig. 4. Development of PICTI version 2 will look to creating an adaptable format to compensate for the issues discovered with the pilot project. This may require rethinking how user input is presented on screen. Utilizing multiple-choice answer responses instead of typed answers in some cases will eliminate some issues; however pedagogically, this may be too much of a sacrifice to retain screen real estate (Fig. 5).

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Future Directions

The communication side of the mobile devices was probably the first one to go mainstream – texting in class, texting announcements, expectation that learners will receive their email on their phone, etc. However, deeper learning with mobile devices requires more developmental pedagogical approach from the educators’ perspective and more engagement and correct attitude from the learners. Having a more flexible approach to m-learning and acknowledging that it is also an individual tool for note-taking and collating information, quick access to info may be the use of mobile technology that should be encouraged and supported more, as this will develop some of the skills that will be used in the real world of work. So instead of trying to adapt the teaching to be delivered to mobile devices at all cost, it should be acknowledged that sometimes having a mixed approach to teaching – traditional,

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Fig. 4 Different views of the Pre ICT Induction (PICTI) on a mobile screen and the same screen with the keyboard visible for entering data

Fig. 5 Pros and cons of using multiple-choice questions in m-learning

Advantages

Dissadvantages

•Bigger screen visible •The context of the input required is visible

•No deep learning testing •Limited overview of the learning process

location, and time set learning with the addition of using technology and specifically mobile devices – may be a more practical approach for the time being. Until the m-learning becomes a more adaptive learning, the process of setting it up may be a bit too complicated for most, hence the limited adoption (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Recent attempts to develop adaptive learning by the Edinburgh-based company CogBooks that uses AI (artificial intelligence) techniques to learn from the learner’s behavior and to guide them to the most pedagogically sound next step may be the most appropriate stage in the

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development of m-learning. Then the educators can concentrate on developing the m-pedagogy and using a unified system to deliver the m-learning itself.

7

Cross-References

▶ 1:1 iPads in First Grade: Case Study of a Teacher’s Concerns and Implementation ▶ Characteristics of Mobile Teaching and Learning ▶ Student Feedback in Mobile Teaching and Learning

References Aubusson, P., S. Schuck, and K. Burden. 2009. Mobile learning for teacher professional learning: Benefits, obstacles and issues. Alternatives Journal 17 (3): 233–247. https://doi.org/10.1080/ 09687760903247641. Beetham, H. 2014. Students’ experiences and expectations of the digital environment | Jisc, 23-062014. http://www.jisc.ac.uk/blog/students-experiences-and-expectations-of-the-digital-environ ment-23-jun-2014. Accessed 3 May 2018. Beetham, H. 2017. Discovery tool – what we learned and where we go next. https:// digitalcapability.jiscinvolve.org/wp/2017/08/31/discovery-tool-what-we-learned-and-wherewe-go-next/. Accessed 3 May 2018. Bennett, S., and K. Maton. 2010. Beyond the “digital natives” debate: Towards a more nuanced understanding of students’ technology experiences. Journal of Computer Assisted Learning 26 (5): 321–331. https://doi.org/10.1111/j.1365-2729.2010.00360.x. Callum, K. Mac, and L. Jeffrey. 2013. The influence of students’ ICT skills and their adoption of mobile learning. Australasian Journal of Educational Technology 29 (3): 303–314. Clark, D. 2014. ‘Keynote speech, iTech 2014’. http://youtu.be/bO0W-2Kl_zQ David, M. et al. 2012. Widening participation in higher education. https://doi.org/10.1057/ 9781137283412. De Quincey, E. et al. 2016. Learner analytics; The need for user-centred design in learning analytics. 3(9): 6–9. https://doi.org/10.4108/eai.23-8-2016.151643. Elias, T. 2011. Principles for mobile learning. International Review of Research in Open and Distance Learning 12: 143–156. Gartner. 2017. Gartner says worldwide sales of smartphones grew 9 percent in first quarter of 2017. http://www.gartner.com/newsroom/id/3725117%0A. Accessed 3 May 2018. JISC. 2014. Digital student project | Jisc, 2014. http://www.jisc.ac.uk/research/projects/digitalstudent. Accessed 3 May 2018. JISC. 2017a. Building digital capability. https://www.jisc.ac.uk/rd/projects/building-digital-capability. Accessed 3 May 2018. JISC. 2017b. JISC Learning_analytics_report.pdf, JISC Learning analytics services appendix terms and conditions. https://analytics.jiscinvolve.org/wp/files/2017/07/Jisc-Learning-Analyt ics-Service-TCs_20170725_Final.pdf. Accessed 3 May 2018. Keyes, J. 2013. Bring your own devices (BYOD) survival guide. Boca Raton: CRC Press, Taylor & Francis Group. Littlejohn, A. 2007. Preparing for blended e-learning. London: Routledge. Mac Callum, K., and L. Jeffrey. 2014. Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Computers in Human Behavior 39: 8–19. https://doi.org/10.1016/j. chb.2014.05.024. Elsevier Ltd.

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Margaryan, A., A. Littlejohn, and G. Vojt. 2011. Are digital natives a myth or reality? University students’ use of digital technologies. Computers & Education 56 (2): 429–440. https://doi.org/ 10.1016/j.compedu.2010.09.004. Elsevier Ltd. Maslow, A. 1943. A theory of human motivation. Psychological Review 50: 370–396. https://doi. org/10.1037/h0054346. Petrakieva, L. 2012. The shift to mobile devices. In User studies for digital library development, ed. M. Dobreva, A. O’Dwyer, and P. Feliciati, 159–165. London: Facet Publishing. Petrakieva, L., and D. McArthur. 2017. Pre ICT induction – PICTI. https://goo.gl/HW8CTA. Accessed 3 May 2018. Prensky, M. 2001. Digital natives, digital immigrants part 1. On the horizon 9 (5): 1–6. http://www. marcprensky.com/writing/Prensky–DigitalNativesDigitalImmigrants–Part1.pdf. Accessed 3 May 2018. van Deursen, A.J., and J.A. van Dijk. 2013. The digital divide shifts to differences in usage. New Media & Society 16 (3): 507–526. https://doi.org/10.1177/1461444813487959. West, M., and C. Ei. 2014. Reading in the mobile era: a study of mobile reading in developing countries. http://unesdoc.unesco.org/images/0022/002274/227436E.pdf. Accessed 3 May 2018.

Advanced Image Retrieval Technology in Future Mobile Teaching and Learning

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Lei Wang and Yu (Aimee) Zhang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Literature and Empirical Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Advanced Image Retrieval Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Advantages and Disadvantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Advanced image retrieval technology has been widely adopted in many academic and industrial institutions. Mobile technology has been adopted in teaching and learning in various disciplines. Image retrieval technology can improve learning efficiency, enhance memory by providing similar learning content, and engage students in learning. However, mobile technology presents a number of software and hardware barriers, such as computing capability, screen size, and the quality of wireless connections (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). It is believed the adoption of the advanced image retrieval technology will enhance the capability of visual content search and the teaching and learning experience of educators and students. The advanced image retrieval technology will play an important role in future mobile teaching and learning and higher education.

L. Wang (*) Faculty of Engineering and Computer Science, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] Y. A. Zhang WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_53

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Introduction

For the last two decades, the development of image retrieval technology in business and industry has opened a new dimension to conveniently and efficiently access visual information (Yang et al. 1998; Yuh-Shyan et al. 2004; Datta et al. 2008; Picard et al. 2008). However, the adoption of image retrieval technology in education has lagged behind and still in its prototype stage. Some educators have designed and implemented mobile learning applications with image retrieval technology to help leaners identify the names and types of birds and butterflies (Yuh-Shyan et al. 2004), provide augmented learning contents (Han et al.), or enhance the learning of second language (Starostenko et al. 2009). The evaluation of these projects demonstrates significant results in the learning process and the engagement of learners. The use of image retrieval technology in learning is not limited to some specific areas. It can be widely applied to health, creative arts, design, teaching and learning, data analysis, and many other disciplines. It is regarded as one of the important trends in future mobile teaching and learning. The following section reviewed the literature on mobile learning. Section 3 introduced the latest image retrieval technology and some of its applications to mobile learning. Section 4 discussed the advantages and disadvantages of the application of image retrieval to education. The last section summarized the findings of this chapter and shed a light on the future image retrieval technology in mobile teaching and learning.

2

Literature and Empirical Studies

The mobile telecommunication industry has evolved rapidly in the last decade, with 95% of the global population covered by mobile cellular signals (Zhang 2012a; ITU 2016). The traditional mobile voice communicating service has been expanded into various multimedia services and social communicating services, such as taking and sending image or video, listening music, watching TV, playing games, checking emails, managing personal schedules, and surfing the Internet (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). The growth of the telecommunications not only provides users with a method to communicate but brings significant profits for the value-added services including learning anytime and anywhere (Vogel et al. 2009; Zhang 2012a; Qiu and McDougall 2013). The development of 3G (third-generation networks) and 4G (next-generation cellular wireless access standards) creates new markets and opportunities (Zhang 2012a). New mobile devices and wearable devices, such as Apple Watch, led the market trends, which opened a new area of mobile learning (Hennig 2016) (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning and ▶ 79, “VR and AR for Future Education”). Combined with virtual reality and augmented reality technologies, they brought new opportunities to mobile education (Alkhezzi and Al-Dousari 2016; Hennig 2016; Yousafzai et al. 2016; Metzgar 2017; Sun and Looi 2017) (see ▶ Chaps. 79, “VR and AR for Future Education” and ▶ 77, “Augmented Reality in Education”).

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Nonetheless, surveys of mobile phone users demonstrate that consumers view the benefits of mobile sectors as saving money, saving time, and providing useful information (Evans 2008; Zhang 2012a; Alkhezzi and Al-Dousari 2016; Zidoun et al. 2016). There is a continuing discussion concerning the advantages and disadvantages of mobile learning compared to traditional face-to-face teaching (Evans 2008; Mishra 2013; Qiu and McDougall 2013; Rennie and Morrison 2013; Alhassan 2016; Yousafzai et al. 2016). There are many challenges for mobile learning, such as small screen size, limited computing capability, short batteries life, high cost for telecommunication services, low bandwidth, reliability of networks connection, the design of learning functions, distraction from learning, and physiological issues (Mishra 2013; Rennie and Morrison 2013; Alkhezzi and Al-Dousari 2016; Hwang and Chang 2016; Yousafzai et al. 2016). With the growth of new technologies and mobile devices, these limitations will be reduced (Hennig 2016). Many designers, educators, and developers have worked together to bring new technologies into universities, high schools, and primary schools (Alley 2009; Cheon et al. 2012; Fraga 2012). In 2016, the education applications were the third most popular category in Apple store and shared 8.55% of all apps (Statista 2016). By 2016, there were more than 130 billion apps downloaded in Apple Store, including more than 11 billion educational apps. They benefited teachers and students all over the world. The growth of touch screens, wearable technologies, and 3D technologies brought opportunities for mobile learning to benefit learners of all abilities (Alkhezzi and Al-Dousari 2016; Hennig 2016; Yousafzai et al. 2016). The adoption of mobile technology in education increased self-learning and lifelong learning (Sharples 2000; Demouy et al. 2015). With the new growth in technologies and industries, the requirements of job markets changed, posing more challenges to universities and educational institutions (Hunt and Zhou 2017). With the focus on personal abilities, technology and environment, and international and communication, mobile learning is playing an important role in the future of education (Zhang 2015; Metzgar 2017).

3

Advanced Image Retrieval Technology

Image retrieval finds images from large databases to meet the requirements set by a user (Smeulders et al. 2000; Datta et al. 2008; Zheng et al. 2017). This technology becomes important and indispensable with the wide use of images, because users need to have efficient access of the visual information in image databases, as well as searching for a specific image. The application of image retrieval in mobile teaching and learning can be intuitively understood, because visual aids such as graphs, diagrams, illustrations, and pictures have become an essential component of modern teaching and learning. And the use of these visual aids is becoming more extensive with the popularity of multimedia tools, wireless communication networks, and mobile computing platforms (Fig. 1).

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Fig. 1 An illustration of an image retrieval system. (Source: From the author)

Image retrieval systems can be categorized into text-based image retrieval (TBIR) systems or content-based image retrieval (CBIR) systems. These two kinds of systems can be differentiated through the queries they accept. In a retrieval system, a user submits queries to the system via an interface to express the information need. A query can usually be submitted in two different formats. The first format, which is commonly used, is in the form of free text queries. It consists of a small number of keywords or textual description about the images to retrieve. A system working with text-based queries is often called a TBIR system. In such a system, each image in the database has been associated with keywords or textual annotation. The relevance of an image to a given query is measured by the similarity between its textual annotation and the query. In this case, image retrieval that is essentially converted to text retrieval has been well investigated (Roediger and Pyc 2012; Rattanarungrot et al. 2014). The second query format provides an example of image to retrieve. A system accepting such a query is often called CBIR system. In this case, the relevance of an image to a given query is measured by the similarity of visual content of the two images, for example, the similarity of their color, texture, or shape information. Since its early days, image retrieval has been treated as an application of text retrieval, and an image retrieval system is often developed within database management system. This leads to the TBIR system. Until now, most of the commercial image retrieval systems are still based on TBIR due to the success and usability of the database management and information retrieval techniques. CBIR started attracting attention in the 1990s. As the digital imaging equipment use increases, the volume of image databases becomes increasingly large. As a result, it is time-consuming and laborintensive for annotators to manually add keywords for each image. Simply using a small number of keywords is difficult to provide an accurate and comprehensive description for an image, which is especially true for the images in a broad domain such as the Internet. Due to the issue of human perception subjectivity, people may have dissimilar descriptions about the same image. As a result, the keywords given by annotators may not be the same as the queries given by users. In this case, it becomes difficult to retrieve relevant images by using text-based image retrieval.

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CBIR has been intensively researched during the past two decades (Yuh-Shyan et al. 2004; Picard et al. 2008). CBIR does not need human annotators but instead uses computers to extract visual features to represent an image. The visual features are based on the color, texture, or shape of an image. In this way, each image associates with a set of visual features, which are conceptually comparable to the text annotation used in TBIR. The similarity of two images is evaluated by comparing the associated visual features. Two images having similar visual features are deemed relevant images. CBIR can effectively address the three issues previously mentioned. CBIR suffers from a critical issue called “semantic gap.” As human beings, we describe image content with high-level concepts such as “desk,” “car,” or “airplane.” However, when describing image content, computers only use low-level visual features. The semantic gap leads to two semantically related images not containing similar visual features, and vice versa. In addition, the TBIR and CBIR approaches are not contradictory but complementary to each other. As long as images have been annotated with textual information, the two approaches can be integrated to effectively improve retrieval performance. The applications of image retrieval can be categorized as narrow-domain-based and broad-domain-based applications. In the former, the images in a database are related to a specific application or restricted to a specific scope, and they often have less diverse image content. For example, the search of medical images, trademark images, or astronomical photos frequently belongs to a narrow-domain-based image retrieval system. Comparatively, the latter case has little or no restrictions on image content, and the images in a database can relate to arbitrary topics, scopes, and applications, resulting in very diverse image content. Searching for images on the Internet is a good example of broad-domain-based retrieval. Both types of image retrieval can find their applications in mobile teaching and learning. As previously mentioned, TBIR only deals with text-based queries. Comparatively, CBIR can handle more flexible query modes. The most common query mode in CBIR is query by example; users can directly submit to the system an example of the images to be retrieved and can delineate a region of an image to request the system to search for the images having this specific region. In some CBIR systems, users are allowed to submit a line sketch or color composition to search for images (Kumar et al. 2010). In addition to the query modes, advanced image retrieval systems allow users to interact with the systems to improve retrieval performance, which is called “relevance feedback.” The relevance feedback mechanism was originally used in TBIR. In the 1990s, it was introduced into CBIR and has received much attention. Through this mechanism, users can label retrieved images as relevant or irrelevant and feed this evaluation back to the system. By analyzing user’s feedback, the system will refine the retrieval in the next iteration. Making use of this mechanism can effectively improve retrieval performance. This mechanism is an effective means to deal with the notorious “semantic gap” problem by introducing human users into the loop of image retrieval. These flexible query modes and the interactive relevance feedback mechanism can bring benefits to the users of mobile teaching and learning to acquire information and knowledge.

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Many image retrieval systems have been developed in the past decades. The query by image content (QBIC) is among the earliest content-based image retrieval systems, developed by IBM in the mid-1990s. This system allows users to find images from a large database to meet their information needs in terms of color, shape, texture, etc. It accepts the queries including example images, sketches and drawings, and designated color or texture patterns. In addition to QBIC, famous pioneering image retrieval systems include the VisualSEEk and WebSEEk systems by Columbia University and Photobook and PicHunter systems developed by MIT. Recently, the developments of new companies focus on image retrieval such as TinEye and Kooaba. CBIR was initially focused on developing effective visual descriptors to describe image content, for example, its color, texture, or shape information. Typical visual descriptors are found in the MPEG-7 visual standard for content description (Sikora 2001). During the last two decades, with the advance of computer vision and machine learning technology, more sophisticated visual descriptors and retrieval algorithms have been designed, significantly boosting the performance of content-based retrieval. The state-of-the-art retrieval algorithms are built upon the convolutional neural networks developed in the field of deep learning. This approach describes an image with unprecedentedly effective feature representations. Upon these representations, simple Euclidean distance can be used to measure image similarity, achieving groundbreaking image retrieval performance (Razavian et al. 2014). As previously mentioned, this retrieval approach is built upon deep learning technology. In the past several years, deep learning technology has received intensive attention due to its record-breaking performance in many pattern recognition and machine learning tasks, including image retrieval. Deep learning is realized through deep neural networks or artificial neural networks (ANNs) with many layers. ANNs were intensively researched several decades ago. Its resurgence in the past several years is attributed to the following changes: (1) more powerful computers, (2) larger-scale datasets, and (3) more advanced algorithms to train neural networks. Benefiting from these changes, deep neural networks can now directly learn feature representations from raw images, which are far better than those representations empirically designed via prior knowledge or domain theories. These directly learned feature representations yield significant improvement to image retrieval and change the techniques used in the state-of-the-art retrieval systems. Compared with the previous bag-of-features model commonly used a decade ago, the image retrieval is relatively easier and simpler to use (Fig. 2). To obtain feature representation, each image is presented to a deep convolutional neural network. This neural network is pre-trained on a large-scale image dataset, for example, the ImageNet dataset collected by researchers at Stanford University (Deng et al. 2009). Because the training dataset contains a large number of images, the obtained neural network can produce feature representations to effectively characterize generic images. Instead of designing features to describe the color, texture, or shape of an image, the state-of-the-art approach employs a pre-trained deep network as a feature extractor. This considerably simplifies the feature extraction process, achieving better image retrieval performance. A typical content-based image retrieval system built upon deep learning technology is illustrated in Fig. 3.

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Pre-trained Deep Convolutional Neural Network

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Feature representation

Fig. 2 Extracting feature representation for an image by using a pre-trained convolutional neural network. (Source: From the author)

Image Database

Retrieve images

Pre-trained Deep Convolutional Neural Network

Image representation

Construct Indexes

Post-processing of feature representation

Fig. 3 Illustration of an image retrieval system based on deep learning technology. (Source: From the author)

Given an image database, each image will be fed into a pre-trained deep convolutional neural network to extract its feature representation. Post-processing operations are conducted to further improve the feature representation. In doing so, each image in the database is characterized by a high-dimensional vector. Once a query image is submitted, its feature representation will be extracted in the same manner. Since each image is now associated with a vector, image retrieval can be carried out by evaluating the similarity of the associated vectors. To speed up retrieval process, an indexing structure is often employed. This deep learningbased retrieval approach is able to achieve excellent retrieval performance. During the past several years, a number of advanced variants of this approach have been developed to improve retrieval accuracy and computational efficiency further. A successful implementation of this system requires sufficient hardware and software support. This retrieval system consists of a server and a group of clients. The image database, pre-trained deep neural network model, feature

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representations of the images in a database, and the indexing structure are stored on the server side. When conducting retrieval, a client needs to send the query information to the server and then receive retrieval result. In this case, the computational power of a mobile platform, as a client, and the bandwidth between client and server become critical. When a query image is submitted, a straightforward way is to send this query image to the server and process it there (e.g., extracting feature representation). This leads to low computational requirement for the client and is important for mobile platforms. At the same time, this approach puts excessive requirements on the bandwidth between the server and clients and the computational capability of the server. Another way is to process the query image, as much as possible, on the client side and minimize the information to be sent to the server. Although this can reduce the requirement on bandwidth and remove burden from the server, more computational capability will occur for the client. This becomes an issue for low-end mobile platforms, especially when the latest deep learning-based retrieval approach is used because the extracting feature representation with deep neural networks involves significant computation. The above two ways correspond to the “centralized” and “decentralized” approaches commonly encountered in distributed computing systems. Selecting a specific mobile image retrieval system must be evaluated by way of considering all the factors related to the system. With the development and popularity of mobile computing platforms, image retrieval has been applied to mobile teaching and learning tasks. The following part shows three examples in the fields of medical practice, outdoor ecology learning, and archival research, respectively. Image plays an important role in medical teaching and training (White et al. 2014; Matzke et al. 2017) inspiring the development of mobile medical image retrieval system called MedSearch Mobile (Duc et al. 2011). It is a mobile search system built upon an existing MedSearch system. This system is a web-based working on a variety of mobile platforms focusing on the iPhone and iPad, as shown in Fig. 4. It retrieves text- and contentbased medical images from medical open access literature. Users are allowed to type in free text queries or take pictures with phone’s camera to conduct retrieval. In addition, this system tests different screen layouts to investigate utilizing the display space in the most efficient manner. This is an important issue for mobile image retrieval systems, because mobile computing platforms usually have limited space for users to interact with the system. By addressing potential issues, such a system will be able to provide efficient access to medical information and expect to improve the performance of medical teaching and learning. Content-based image retrieval has been used in outdoor ecology learning (Yuh-Shyan et al. 2004). Taking advantage of wireless transmission technology and handheld devices, a mobile firefly-watching learning system was developed (Yu et al. 2004). This system allows students to take pictures of the firefly in an outdoor environment and transfer the picture to the server side. The picture is matched with images in a database and similar ones are retrieved. By crossreferencing the retrieved images and the captured image, students will be able to identify their commonness and differences on site and access textual information associated with the retrieved images. With such a system, students will have

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Fig. 4 The MedSearch mobile system on iPhone and iPad. (Source: Duc et al. 2011)

opportunities to perform independent learning and are less constrained by time and place. Fig. 5 shows the interface of this image retrieval system. The left panel displays the query image and the right panel displays the retrieval result. Image retrieval has been used to retrieve photos from archival photographic collections. Most of existing archival photo search systems are based on text annotation and use text-based image retrieval to find relevant photos. However, with the increasing volume of archival photo collections, text-based retrieval becomes less efficient due to the need of manual annotation and the limited expressive power of keywords. Taking advantage of content-based retrieval techniques, a system was developed to reduce the dependence on text annotation and provide public users with efficient access to visual information to conduct research, teaching, and learning. This system was previously built upon the bag-of-features model for image retrieval, and it has now been upgraded by employing the state-ofthe-art deep learning-based approach. Fig. 6 displays a snapshot of this system. When a user is interested in an archival photo, he/she can click the photo. The photo will be displayed at the top as query, and the system will retrieve relevant photos from the database and display them on the screen. In this manner, all the information associated with the retrieved photos could be passed to the user and can be extended to mobile platforms.

4

Advantages and Disadvantages

The advantages of image retrieval technology in education are to improve learning efficiency, enhance memory by providing similar learning contents, and engage students in learning. Some prototype products and their evaluation demonstrated

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Fig. 5 A mobile fireflywatching learning system. (Source: From Yu et al. 2004)

the image retrieval technology helped students in their learning and increased their interests in learning and discussion (Yuh-Shyan et al. 2004; Datta et al. 2008). A picture is worth a thousand words (Larive 2008). Ten or twenty similar pictures benefit students more. The searching ability, linked memory (Zhang 2012b), and group discussion enhance not only learning but lead to lifelong learning (Sharples 2000; Mishra 2013). Although several studies (Yuh-Shyan et al. 2004; Datta et al. 2008; Picard et al. 2008) indicated image retrieval technology in mobile learning had a positive influence on the learning process and positive evaluation in qualitative analysis as discussed above, there are some disadvantages or barriers for this technology that should be taken into consideration for future design and development. Mobile devices, compared to personal computers, have limited computing capability and battery life due to the limitation of their hardware (Rennie and Morrison 2013; Alhassan 2016; Yousafzai et al. 2016). Although the gaps are decreasing, mobile devices still have lower computing capability. Therefore, image retrieval applications should fit into mobile devices by employing better algorithms to speed up the process. Mobile devices are limited by their screen size and image resolution (Mishra 2013; Alkhezzi and Al-Dousari 2016). Images with details or small-sized words are not suitable for mobile devices. High-resolution images take more time to load and transfer. Small-sized images with simple content are a better fit for mobile devices. The network connection via 3G is costly and not reliable on mobile devices (Zhang 2012b; Alhassan 2016; Yousafzai et al. 2016; Metzgar 2017). Although both fixed broadband prices and mobile broadband prices dropped dramatically from 2013 to 2016, affordability is still the major barrier for mobile adoption in many developing countries (ITU 2016). Some mobile devices make it easier to transfer the Wi-Fi connection to 3G anytime, which increase the costs to the customers. For example, in Australia, a video transfer via 3G connection may cost 200 AUD per hour. Therefore, the image retrieval technology should focus on reducing the size of transferred files and messages.

Advanced Image Retrieval Technology in Future Mobile Teaching and Learning

Fig. 6 A retrieval example of archival photo search system. (Source: From the author)

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Mobile device users are willing to learn with smaller time slots instead of watching mobile devices for more than 1 h (Qiu and McDougall 2013; Alkhezzi and Al-Dousari 2016). They are interested in applications with convenient and simple functions, more colors and interactions, or social communication functions. Distraction from other mobile applications is another problem in mobile learning (Peter and Gina 2008; Sana et al. 2013; Alhassan 2016). A well-designed mobile application should meet these requirements (Hennig 2016).

5

Conclusion

Mobile teaching and learning is a growing trend in higher education. The advanced image retrieval technology can add value to this field due to the wide use of image and video in teaching and learning. With the development of image retrieval technology in the last two decades, image retrieval is not a simple extension of text retrieval anymore but has opened a new dimension for conveniently and efficiently accessing visual information. This is important for mobile teaching and learning advocates who expect free, flexible, and efficient ways to acquire knowledge. The extensive use of image retrieval technology in areas related to mobile teaching and learning can be expected in the very near future. At the same time, there are still a variety of issues needing to be resolved to make mobile image retrieval more reliable and efficient. One is related to the computational capability of mobile computing platforms. With the increasing application of mobile image retrieval systems, more sophisticated imageprocessing algorithms and graphical user interfaces could be implemented at the client side leading to more computational overhead and memory and storage usage. In this case, it may not be effective to pursue high-end mobile platforms but, instead, design better systems and create algorithms and communication protocols to make mobile image retrieval a cost-effective system. This is important for making mobile teaching and learning affordable for everyone in the era of big data and deep learning. Another critical issue is the development of image retrieval technology. Although content-based image retrieval has made significant progress, its performance still needs more research and development. The effectiveness of image retrieval depends on the development of image understanding, a central issue in computer science and artificial intelligence. As previously described, this field has witnessed increased growth from the traditional bag-of-features model to the more advanced deep learning model. The latter has achieved remarkable performance in the area of image understanding and still has significant potential to be exploited. The advance of image retrieval technology will not only expand the scope of its applications to mobile teaching and learning but help improve the quality of these applications.

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Cross-References

▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ VR and AR for Future Education

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Mobile Learning Beyond Tablets and Smartphones: How Mobile and Networked Devices Enable New Mobile Learning Scenarios

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Five Decades of Learning Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 First Decade: 1975 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Second Decade: 1985 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Third Decade: 1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Fourth Decade: 2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Fifth Decade: 2015 and Beyond . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Learning Beyond Tablets and Smartphones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 The Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 The Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

There is a growing set of mobile and networked devices, which can be used to design, develop, and implement mobile learning scenarios in schools, enterprises, and public institutions such a museums and libraries. Networked objects with iBeacon, radio-frequency identification (RFID), Bluetooth, and other technologies are located in buildings and communicate with users who approach them. This chapter will give an introduction to this new possibility to create mobile and networked learning scenarios and present a range of examples from schools, enterprises, and public institutions. The chapter is a first glimpse into new applications and

D. Stoller-Schai (*) CREALOGIX Digital Learning, Zurich, Switzerland e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_71

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possibilities of mobile learning based on an extended understanding, which goes beyond tablets and smartphones. Some ideas are still sketches and basic descriptions. The goal is to encourage one’s own experience and to explore new ways of teaching and learning with mobile technologies.

1

Introduction

Mobile learning will expand to other devices, which become part of the daily life. Tablets and smartphones will remain key devices for mobile learning, since they have a display to present information, connectivity to networks, computing power to execute calculations, games and other tasks, and a broad variety of sensors to gather contextual information. However, part of these functions will drift to other devices such as watches, bracelets, clothes, and glasses or become components of buildings, cars, public institutions, stores, etc. Mobile learning will be a commodity the more the Internet of Things becomes a reality. This is good news for educators in public schools and trainers in small or large enterprises. They can design learning scenarios, which are situated in the learning and working context of their pupils and employees. Learning takes part outside of formal settings and becomes an experience with light bulb moments.

2

Five Decades of Learning Technologies

For the last 40 years, different types of personal computer technology have been developed and evolved which could be used not only for working or leisure time but always also for learning purposes. Over five decades, computers became always smaller, more connected, and more mobile (Campbell-Kelly et al. 2013; Ceruzzi 2012). They moved from the computing center to the palm, which is not just the basis for mobile computing but also for mobile learning. In order to understand the past development and predict and anticipate the future development, the five decades are briefly described and summed up with a short conclusion regarding the relevance for mobile learning (for more details, see (Crompton 2013)).

2.1

First Decade: 1975

When the first personal computer was invented in the mid-1970s, the usage was focused on the built-in features and functions of the machine; it was a stand-alone – almost immobile – engine. It has been used mainly for programming, hardware bricolage, gaming, and certain low-level office tasks (Fig. 1).

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Fig. 1 First decade: personal computers, e.g., Commodore 64. (Source: Flickr, Author: Blake Patterson, URL http:// bit.ly/dss_mobilelearning_ fig1, Retrieve data Nov. 11, 2014, Copyright: Creative Commons BY)

2.1.1 Significance for Mobile Learning Actually, computers were isolated machines, at least for people outside the universities. Computers could be used to teach programming techniques and to learn with stand-alone programs and early versions of computer-based training (CBT) on floppy disks and later on compact disk read-only memory (CD-ROM). Mediabased learning could not be considered as “mobile.”

2.2

Second Decade: 1985

With a standardized connection to the Internet in the mid-1980s, computers became a “window” into a huge world of information and communication, but this possibility was still limited to a small group of people, who knew how to use acoustic couplers, mailbox systems, use groups or Internet Relay Chat (IRC), etc. (Fig. 2). Before the continuous connection to the Internet, the users were mainly satisfied with the local functions of their desktop computers. Now, the focus moved slightly away from the machine to the net, and computers became “access points” to the connected world.

2.2.1 Significance for Mobile Learning With the first laptop computers, it was possible to change location. In reality, this happened not really a lot since the first laptop computers weighed still a couple of kilos or pounds and were not very “mobile friendly.”

2.3

Third Decade: 1995

With the built-in connection to the Internet and the invention of the Hypertext Transfer Protocol (HTTP) and the World Wide Web (www) after 1995, the next big leap occurred. Now, the access to website, online games, and communication with others was in the focus. All of a sudden, thousands of web servers with interesting content were reachable (Fig. 3).

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Fig. 2 Second decade: personal computers, e.g., IBM PC. (Source: Flickr, Author MarcinWichary, URL http:// bit.ly/dss_mobilelearning_ fig2, Retrieve data Nov. 11, 2014, Copyright: Creative Commons BY)

Fig. 3 Third decade: connected computers, e.g., iMac. (Source: Flickr, Author Carl Berkeley, URL http://bit. ly/dss_mobilelearning_fig3, Retrieve data Nov. 11, 2014, Copyright: Creative Commons BY-ND)

2.3.1 Significance for Mobile Learning In the 1990s, mobile computers and first tablets were available (such as the Apple Newton, which was never a real success). It was possible to gain first experiences since computers left the desktop and could be carried around. Additionally, the first mobile telephones and the Wireless Application Protocol (WAP) interface allowed limited access to the Internet from a personal mobile device. Mobile learning became an important topic as a research topic in universities and as a new opportunity for corporate training programs in enterprises and public institutions.

2.4

Fourth Decade: 2005

The fourth decade was mainly characterized by two evolutions (Fig. 4): First, with the Web 2.0, the behavior, how the Internet is being used, changed again. Now, self-presentation, exchanging personal information, building relations,

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Fig. 4 Fourth decade: mobile computers, e.g., iPhone. (Source: Flickr, Author William Hook, URL http://bit. ly/dss_mobilelearning_fig4, Retrieve data Nov. 11, 2014, Copyright: Creative Commons BY-SA)

watching movies, shopping online, etc. became the main reason to start a computer. A disconnected computer from the Internet was almost worthless. It could not serve its main purpose anymore to be the entry point into the “digital world.” Actually, not the computer was important anymore, but the access to a connected information space. Second, the invention of smartphones with touch screens in the mid-2005s made almost the same processing power as a desktop computer available in a mobile device. The window to the connected information space became smaller and could be carried around. Access to everything from everywhere at anytime became a reality – as long as there was a paid connection with a network provider and a charged storage battery available.

2.4.1 Significance for Mobile Learning The fourth decade is the birth of mobile learning in the pure meaning of the word. With smartphones and touch screens and a broad range of apps, learning became mobile and available for almost everybody. In addition, the understanding of learning expanded from “formal learning” (e.g., in a classroom or a seminar room) to “informal learning,” which happens on the road, at the workplace, or even in the personal spare time – with no syllabus, lecturer, or teachers. In that sense, mobile devices expanded our understanding how learning occurs, as a small percentage of formal learning and a large percentage of informal learning, triggered by the needs, the interest, and the curiosity of the learners: With smartphones, it is possible for the first time to answer almost any questions just right away. Especially for rural regions, this is a very important source for education and teaching (UNESCO 2014).

2.5

Fifth Decade: 2015 and Beyond

After computers left our desktops, they will also leave our palms in the fifth decade (Fig. 5). The Internet becomes part of everyday objects and is being integrated into daily commodities. Our mobile devices can communicate with the “Internet of

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Fig. 5 Fifth decade: wearable computers, e.g., Google Glasses. (Source: Flickr, Author Ted Eytan, URL http:// bit.ly/dss_mobilelearning_ fig5, Retrieve data Nov. 11, 2014, Copyright: Creative Commons BY-SA)

Things” (Madisetti and Bahga 2014), and new displays such as watches, glasses, and lenses are currently being invented. A lot of “things” are collecting or transmitting data without any or just reduced displays such as “wearables” (computers, which are integrated into bracelets, necklace, and rings or which are parts of clothes and shoes). This personalized data gives us information about a lot of parameters about our daily routine: Where have I been? How many calories did I burn? When did my heart rate go up? How was my sleep?

2.5.1 Significance for Mobile Learning With the “Internet of Things,” not only computing but also learning becomes ubiquitous. Mobile learning allows situating learning into the daily life of a person. With new displays in glasses, lenses, and watches and with a broad range of devices that collect and deliver information, new learning scenarios are possible. Some of them will be described in the following chapters. As an overview, the five decades of computer development and learning are depicted in Fig. 6.

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Learning Beyond Tablets and Smartphones

Although mobile learning is still in its infancy and in many schools and enterprises not yet developed, it is already possible to piloting the next generation of mobile learning scenarios, which deal with smart objects (e.g., indoor positioning systems, wearable, or activity trackers). However, this does not mean that mobile learning takes place without smartphones and tablets, since a display and processing and communication power are still needed. But mobile learning, which is integrated into the daily life and smartphones or tablets that interact with additional external devices, generates the possibility to create situated learning situations (Lave and Wenger 1991) or “situated mobile learning” (Pfeiffer et al. 2009).

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Fig. 6 Five decades of computer technology: from immobile to mobile to ubiquitous. (Source: Author Daniel Stoller-Schai)

To create new situated mobile learning scenarios, a two-folded approach is needed. The Device First, it is crucial to know the range of available and future devices that can interact with a smartphone or a tablet. Based on this knowledge, teachers, trainers, and learning professionals have to gain their own personal experiences, before they can design situated mobile learning scenarios. The Setting Second, a pedagogical attitude is needed to generate a curiosity in learning processes and asking new questions about the personal world of the learner. If a learner has no questions to ask, all the connected learning scenarios are useless, because there is nobody to be interested in the answers. Learning professionals and education designers have the duty to design a setting, which creates new questions and offers the setup to answer them. Connected mobile device offers a broad toolbox of opportunities to cover both aspects.

3.1

The Device

The situated setting of mobile learning technology beyond smartphones and tablets has to be divided into four components (Fig. 7): The first component is the display. Normally, the built-in displays of smartphones or tablets are used to read, to hear, or to watch any kind of information. Actually, there are many more displays available, which are built-in in other devices.

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Fig. 7 The device: four components to build the technological ecosystem. (Source: Author Daniel Stoller-Schai)

The second component is the external source. In addition to web servers, which remain one of the main sources of information, it could be an activity tracker, indoor positioning system, etc. The third component is the communication connection between the source and the display. If the source is inside the device, the connection is hardwired. If the source is outside the device, the connection must be wireless. The fourth and last component is the sensor. Sensors are very important for mobile devices and an important factor for their commercial success. Sensors can be part of the device (e.g., a smartphone) or part of an external source (e.g., the wind sensor of a Wireless Fidelity (Wi-Fi)-enabled weather station).

3.1.1 Display First, in addition to the standard touch screen displays of smartphones and tablets, there is a broad range of new displays available (Table 1).

3.1.2 Source Second, the information to feed the devices comes from a variety of sources, which are on or around a person (Table 2).

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Table 1 Range of new displays Display 1. Glasses

Definition Special glasses with an optical head-mounted display (OHMD). It can display information in a smartphone-like format

2. 3D glasses

Open or closed glasses with a display to produce 3D images

3. Lenses

Contact lens with builtin light-emitting diode (LED) arrays

4. Watches

A small display integrated into a watch to communicate with other mobile devices

5. Indicators

A device, which has no visual display but sends signal by vibrations or LEDs

6. Projector

A device, which projects the display on a surface, e.g., the arm bed

Purpose Display information to execute tasks directly to the retina. The main benefit that glasses allow is a hand-free handling, which allows using hands for other tasks Virtual reality headset for 3D gaming or exploring 3D architecture models. Together with data gloves, it is possible to manipulate objects in the 3D world Display information to execute tasks directly on the retina. With LED array lenses, the computing power which is available for the user becomes invisible to another person Reduction of the display and its integration into a watch free up again both hands for other tasks Collect personal activity data, e.g., heart rate, blood pressure, etc., and inform wearer about past, current, or anticipated status Displays personal activity data, e.g., heart rate, blood pressure, etc., directly on any surface

Examples Google Glasses DigiLens VuzixWrap iOptik (Innovega)

Oculus Rift ARCHOS VR Glasses Samsung Gear VR Durovis Dive Zeiss Cinemizer Epson Moverio

There are several research projects in progress (Parviz 2009), but no commercial product is yet on the market

Apple iWatch Motorola’s Moto 360 Samsung Gear Live LG G Watch Pebble Steel Withings Pulse Fitbit Flex Garmin vivofit Basis Carbon Steel Misfit Shine Cicret Bracelet

Note: The examples in the fourth column for this and the following subchapters are based on the market situation at the end of 2014 and can change quite rapidly. The purpose to mention concrete products is to give the reader of the chapter the opportunity to continue their own research

3.1.3 Connection Third, there are different technologies and communication protocols to connect an external source with a mobile device. The most important ones are presented in Table 3.

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Table 2 Different sources to acquire information Source 1. Wearable

2. Activity tracker

3. Indoor positioning system

Definition “Wearable technology (. . .) are clothing and accessories incorporating computer and advanced electronic technologies.” (Wikipedia 2014d) “A device or application for monitoring and tracking fitness-related metrics such as distance walked or run, calorie consumption, and in some cases heartbeat.” (Wikipedia 2014a) “An indoor positioning system (IPS) is a solution to locate objects or people inside a building using radio waves, magnetic fields, acoustic signals, or other sensory information collected by mobile devices.” (Wikipedia 2014b)

Examples Motion Recognition Clothing/Medibotics Hexoskin See activity trackers above

iBeacon, Apple IndoorAtlas sensewhere Other applications (Mautz 2012)

Table 3 Connection technologies and protocols Technology 1. Bluetooth 2. Wi-Fi 3. Infrared 4. RFID

Purpose Used to connect mobile devices with audio components and television and to set up indoor positioning systems Basic technology to gain access to the Internet Basic technology for remote controls “Radio-frequency identification (RFID) is the wireless use of electromagnetic fields to transfer data, for the purposes of automatically identifying and tracking tags attached to objects. The tags contain electronically stored information.” (Wikipedia 2014c)

3.1.4 Sensor Finally, with each generation of new smartphones or tablets, the range of available sensors is being expanded. For special purposes, more accuracy or flexibility, a lot of specialized sensors are made as stand-alone products (Table 4).

3.2

The Setting

3.2.1 Pedagogical Starting Point Before discussing different learning scenarios, it is important to mention that the new learning possibilities are related to the fact whether teachers or trainers as well as pupils or corporate learners are interested about their environment and are able to formulate learning-related questions. If there are no creative, reflective, and critical questions, all new mobile learning channels are useless (The Critical Thinking Community 2014). Therefore, it is important as teachers or trainers to arouse first the interest of pupils and corporate

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Table 4 Overview of sensors Sensor 1. Ambient light 2. Optical proximity 3. Microphone 4. Capacitive touch 5. Temperature 6. Accelerometer 7. Atmospheric pressure 8. Digital compass 9. Gyroscope 10. Humidity 11. Image 12. Gesture

Purpose Measures the intensity of light in the environment Measures the distance between an object and the device Records sound from an external source Notices pressure on a touch-sensitive surface Measures the temperature of any material Measures the movement of an object Measures the atmospheric pressure for weather forecasts Indicates the direction of the four cardinal points Measures the position of the device in a 3D space Measures the humidity of any material Captures images or movies from a camera Visually detects gestures to trigger an action

learners toward their specific world. If there is an interest, learning becomes an ongoing activity, and mobile devices and other objects are powerful tools to design effective learning scenarios, which answer those questions. A mobile device can become a tool to proof our personal scientific hypotheses about our world. With multisensored and connected mobile devices, it is possible to design an experienced-based education as intended by the German physicist and pedagogue Martin Wagenschein. His goal was to reconnect science teaching with both the developing child and nature. He saw the detrimental effects of theory-based instruction and rote learning that informs so much of science education today. He developed an experience-based approach to science education. For him science classes should be first and foremost an exploration of concrete phenomena – students thereby learn science as a process of inquiry rather than as a body of set facts and theories (The Nature Institute 2014; Wagenschein 2013; Udell 2013). The setting consists of six steps (Fig. 8): 1. Question: Starting point for a situated mobile learning scenario. 2. Setup: Design of the pedagogical experiment to answer the questions. 3. Experiment: Execution of different actions to go through the defined steps of the pedagogical experiment. 4. Reflection: Personal reflection of the results and observations. 5. Discussion: Social learning activity by discussing and arguing the results with peers or teachers and trainers. 6. Report: Formulate the answer to the question in the first steps. Archive learning results and transfer solution into the daily practice. In the following chapter, this setting or part of the setting is being applied to basic and advanced teaching scenarios for pupils and employees (Table 5).

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Fig. 8 The setting: six steps for situated mobile learning. (Source: Author Daniel Stoller-Schai)

Table 5 Overview of teaching and learning scenarios Pupils Basic teaching scenarios for pupils in schools Advanced teaching scenarios for pupils in schools

Employees Basic learning scenarios for employees in enterprises Advanced learning scenarios for employees in enterprises

3.2.2 Basic Teaching Scenarios for Pupils in Schools After discussing and introducing the different components of a situated mobile learning scenario, a couple of concrete examples will be presented to demonstrate how these possibilities can expand learning scenarios in a classroom (Table 6). 3.2.3 Basic Learning Scenarios for Employees in Enterprises Another couple of examples describe different basic (informal) learning scenarios for employees in enterprises (Table 7). 3.2.4 Advanced Teaching Scenarios for Pupils in Schools In addition to the basic scenarios, there are more advanced teaching scenarios for pupils in schools (Table 8). Network, Example 1: A Quest Through an Old “Ch^ateau” With an indoor positioning system such as iBeacon and with a platform provider who delivers the appropriate development package (application programming

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Table 6 Basic teaching scenarios for pupils in schools Learning question How cold is water when it turns to ice?

Setup Temperature measurement with smartphone and thermometer (e.g., Kinsa, Thermodo, etc.)

How loud is my music speaker? When does the music volume become unhealthy?

Loudness measurement with internal or external microphone and decibel app (e.g., apps like dB Volume Meter, TooLoud?, DeCibel, etc.)

How far is it from my home to school? What is actually the shortest way?

Distance measurement with GPS/maps and activity tracker app (e.g., apps like Moves, Argus, Endomondo Sports Tracker, FitBit, etc.) Camera: take pictures every 30 s (or less, or more) with a stop motion app (e.g., StopMotion Recorder, Stop Animator, Frameographer– Stop Motion & Time-Lapse, iMotion HD, etc.) Camera: take pictures with a slow motion app (e.g., Coach’s Eye, PotPlayer full HD media player, Slow Motion PRO, Slow Motion Video, etc.) and analyze it

How fast does a flower open its blossom?

How do I jump over a hurdle?

Experience Cool down water in a bucket and continuously measure the temperature until ice building starts Let one group play their favorite music on their preferred volume level. Let another group measure the decibel and compare it with references for ear protecting Start with estimating certain distances and suggestions for shortest way. Proof these hypotheses by walking the defined route Put a camera on a tripod and activate the app to take pictures with a predefined frequency

Put a camera on a tripod and activate the app to take a movie. Analyze and compare style, accuracy, etc. of different people

Note: The example will start with the question; describe briefly the setup and end up with a sketch of the experience. Other steps like reflection, discussion, and reporting cannot be described, since they are part of a concrete learning process. The examples are just starting points to trigger own teaching scenarios Again, product examples reflect the market situation at the end of 2014 and can change quite rapidly. The purpose to mention concrete products is to give the reader of the chapter the opportunity to continue their own research Note: A couple of the described scenarios require special equipment or a special environment. Both may not be available for a specific school class. In this case, it is often enough just to use the built-in technologies and sensor of a standard mobile device

interface, API; software development kit, SDK; content development network, CDN; web panel and admin. app, e.g., from Kontakt.io), it is possible to build your own quest through a museum, a shopping mall, or a school building. The following example shows part of a quest through an old “Ch^ateau” – the “Schloss Birlinghoven” in Sankt Augustin, Germany – which is the headquarter of the “Fraunhofer Institute for Applied Information Technology FIT” (FIT 2014). The quest was part of a conference to demonstrate current and future mobile technologies, which took place in October 2014 (Fig. 9).

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Table 7 Basic learning scenarios for employees in enterprises Question How can I stay in contact with my colleagues/ customers?

Setup Solution approach: see who is currently in your neighborhood with an app, e.g., Swarm by Foursquare

Who knows what and who can help me to solve a problem?

Solution approach: Intelligent networks which connect people, competences, and location, e.g., Starmind. “Starmind matches your questions with real solutions from direct human input. Give your team access to know-how that is stored inside a corporate brain. Always up-to-date, always in real time.” (Starmind International AG 2015)

Experience Especially in projects where all the members of a team are dispersed geographically, a visual map of all the locations can help to solve ad hoc problems and foster informal learning The learning organization as described by Peter Senge (1990) is based on human interactions and networks. To access this “corporate brain” is now possible with technology and apps, which are integrated in personal smartphones and tablets

Table 8 Advanced teaching scenarios for pupils in schools Network Example 1 A quest through an old “Ch^ateau”

Equipment Example 2 A personal weather station

Body Example 3 Body measurement

Perception Example 4 Augmented reality

As users walk through the rooms of the “Ch^ateau,” they see on a map their position and get information about the rooms and the objects on their tablet. It is even possible to place an iBeacon on a specific person. If a user is in the neighborhood of the equipped person, the appropriate information is displayed again on the tablet. Since the application can be expanded, it is possible to add own comments and photos and share them with a community. In a collaborative action, a dense net of information about the “Ch^ateau” can be weaved together.

Equipment, Example 2: A Personal Weather Station A second advanced example covers the analysis of weather data and challenges the weather forecast on television. With a weather station, a weather app, and the transfer of weather data to a social community (Fig. 10), it is possible to create a weather observatory to answer questions as the following: What is the saturation of O2 and CO2 in our classroom (when the windows are closed or opened)? How fast is the wind currently blowing? How much did it rain since yesterday?

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Fig. 9 Example of a quest on an iBeacon platform. (Source: Author Daniel Stoller-Schai)

The collected weather data can be shared on a community platform. As in the example before, these data are again a contribution to a dense net of information about the weather situation in the region or in other parts of the world.

Body, Example 3: Body Measurement A similar example can be built up with activity trackers, apps, and webpages to answer these questions: How does my heart rate go up when I step up a stair? How many calories do I burn if I walk on a hill? How do I collect personal data (big data awareness) with activity trackers?

Perception, Example 4: Augmented Reality (AR) In case that a class can afford the purchase of 3D glasses for 3D visualization and tackles the challenge of programming a 3D environment, it is possible to explore historical facts about a building or a city with a head-mounted display or an AR Browser.

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Fig. 10 Example of a weather observatory based on a weather station platform. (Source: Author Daniel Stoller-Schai)

Table 9 Advanced learning scenarios for employees in enterprises Network Example 5 Onboarding learning path with iBeacon

Equipment Example 6 Onboarding learning path with action camera

3.2.5 Advanced Learning Scenarios for Employees in Enterprises There are some advanced learning scenarios for employees in enterprises (Table 9).

Network, Example 5: Onboarding Learning Path with iBeacon Newly hired employees get a tablet and explore on their own the main building and the campus of their new enterprise. Similar to the example above (“Network, Example 1: A Quest Through an Old ‘Ch^ateau’”), there are a series of iBeacons dispersed in rooms, on persons, and in the environment of the main building which trigger information and tasks on the tablets of the employee. With this approach, the employee follows a journey (learning path) and gathers personal information about people, processes, and products.

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Equipment, Example 6: Onboarding Learning Path with Action Camera Another way for new employees to explore their enterprise, the people, processes, and products is to film the personal way of the first 1 or 2 weeks. For this purpose, an action camera (e.g., GoPro Camera) is attached to the clothes or the back bag of the employee, and he/she decides when to start/stop the camera. This source material is the basis for a personal onboarding diary. Multimedia producer has to give assistance on how to cut, to assemble, and to finish such a movie.

3.2.6 Tips and Tricks How to Start In order to start situated mobile learning scenarios, it could help to follow the suggested steps: 1. Personal curiosity: If a teacher or a trainer does not ask questions, the pupils or employees won’t. Teacher and trainers should train themselves how to ask questions about the world. 2. Particular experience: It starts with personal experience such as the following: To download a couple of interesting apps To buy some activity trackers or other devices and test them in the daily life To start equip a home, a school, or a building with an indoor positioning system and play around with the new possibilities 3. Collaboration with others: Teachers or trainers should collaborate with institutes and students from their neighbor university to set up more advanced mobile learning scenarios, which require programming effort, webpages, or even the integration of a content development network (CDN) partner. 4. Available devices: It is not necessary to wait until special devices or the subscription of an expensive service is affordable. The built-in sensors and functions of a smartphone or a tablet are already a good starting point. 5. Best practice sharing: As soon as some personal experiences are gathered, these personal insights and related questions should be shared with a community. A lot of trainers, teachers, and researchers have the same questions and problems. A person, who starts to share, will often get back a multiple.

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Future Directions

The sixth decade will bring a lot of smart objects, which can communicate with a person who triggers the communication or autonomously with other objects. Mobile learning is and will become the main manner on how we learn with media. Every media-based learning scenario has to start with a “mobile-first” approach. Typical eLearning scenarios such as learning with a web-based training, which is stored on a learning management system (LMS) and proofs your knowledge by conducting an eTest, will slowly fade out. Media-based learning must be situated in our daily life.

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Since the “Internet of Things” is a growing topic, which affects every part of our life, it is obvious that situated mobile learning scenarios will be an integrated part of teaching and learning in school or training in enterprises. Computers will leave not only our desktop, but also our palms and will be part of other equipment such as glasses, clothes, and watches. The next future steps are to integrate devices into our bodies. The LED array lenses are just first steps. Authors like Bruce Sterling (1986) and William Gibson (1986) have foreseen this development since a long time. As William Gibson once pointed out, “The future is already here – it is just unevenly distributed” (Wikiquote 2014).

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Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Augmented Reality and 3D Technologies: Mapping Case Studies in Education ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts

References Campbell-Kelly, Martin, and William Spray. 2013. Computer: A History of the Information Machine (The Sloan Technology Series) 3rd ed. Boulder: Westview Press. Ceruzzi, Paul E. 2012. Computing: A concise history. Boston: MIT Press Essential Knowledge. Crompton, Helene. 2013. A historical overview of mobile learning: Toward learner-centered education. In Handbook of mobile learning, ed. Z.L. Berge and L.Y. Muilenburg, 3–14. New York: Routledge. FIT. 2014. “Fuelbands”, “Smart Watches”, “Glasses” and Co. = Next Gen Smart Phones? Demo-Workshop über Nutzungs-Szenerien von Wearables als Türöffner zu neuen Endgerätegenerationen. St. Augustin: Fraunhofer Institute for Applied Information Technology FIT. Gibson, William. 1986. Neuromancer. New York: Ace/Penguin Books. Lave, J., and E. Wenger. 1991. Situated learning: Legitimate peripheral participation. New York: Cambridge University Press. Madisetti, Vijay, and Arshdeep Bahga. 2014. Internet of things – A hands-on-approach. 1st ed. Atlanta: VPT. Mautz, Rainer. 2012. Indoor positioning technologies. Zürich: ETH, Habilitation, Department of Civil, Environmental and Geomatic Engineering, Institute of Geodesy and Photogrammetry. Parviz, Babak A. 2009. A new generation of contact lenses built with very small circuits and LEDs promises bionic eyesight. In Augmented reality in a contact lens – IEEE spectrum. http:// spectrum.ieee.org/biomedical/bionics/augmented-reality-in-a-contact-lens. Accessed 14 Dec 2014. Pfeiffer, Vanessa D.I., Sven Gemballa, Halszka Jarodzka, Katharina Scheiter, and Peter Gerjets. 2009. Situated learning in the mobile age: Mobile devices on a field trip to the sea. ALT-J: Research in Learning Technology 11: 187–199. Senge, Peter. 1990. The fifth discipline: The art and practice of the learning organization. New York: Doubleday/Currency. Starmind International AG. 2015. Starmind: A human solution. https://www.starmind.com. Accessed 02 Feb 2015. Sterling, Bruce. 1986. Schismatrix. New York: Penguin.

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The Critical Thinking Community. 2014. The role of questions in teaching, thinking and learning. http://www.criticalthinking.org/pages/the-role-of-questions-in-teaching-thinking-and-learning/ 524. Accessed 13 Nov 2014. The Nature Institute. 2014. Experience-based science education: The work of Martin Wagenschein. http://natureinstitute.org/txt/mw/. Accessed 14 Nov 2014. Udell, Chat. 2013. The seventh sense: Using haptics, light sensors, accelerometers, barometers, and more to create innovative learning solutions. In Employing mobile device sensors for enhanced learning experiences | Float mobile learning. http://floatlearning.com/2013/08/employingmobile-device-sensors-for-enhanced-learning-experiences/. Accessed 12 Dec 2014. UNESCO. 2014. Mobile learning | United Nations Educational, Scientific and Cultural Organization. Edited by ICT in Education. http://www.unesco.org/new/en/unesco/themes/icts/ m4ed/. Accessed 14 Nov 2014. Wagenschein, Martin. 2013. Verstehen lehren. Genetisch, Sokratisch, Exemplarisch. Weinheim: Beltz. Wikipedia. 2014a. Activity tracker. http://en.wikipedia.org/wiki/Activity_tracker. Accessed 30 Dec 2014. Wikipedia. 2014b. Indoor positioning systems. http://en.wikipedia.org/wiki/Indoor_positioning_ system. Accessed 30 Dec 2014. Wikipedia. 2014c. Photodetector. http://en.wikipedia.org/wiki/Radio-frequency_identification. Accessed 30 Dec 2014. Wikipedia. 2014d. Wearable technology. http://en.wikipedia.org/wiki/Wearable_technology. Accessed 30 Dec 2014. Wikiquote. 2014. Wikiquote. http://en.wikiquote.org/wiki/William_Gibson. Accessed 14 Nov 2014.

M-Learning and U-Learning Environments to Enhance EFL Communicative Competence

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Higher Education Participation in M-Learning and U-Learning Approaches . . . . . . 2 Communication and EFL Knowledge Building . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Expressing Themselves by Means of Written and Oral Tasks . . . . . . . . . . . . . . . . . . . . . . 3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 The EFL U-Learning Environment with Mobile Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Level B1 and English . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Expressing Themselves by Means of Written and Oral Tasks . . . . . . . . . . . . . . . . . . . . . . 4.2 Autonomy, Responsibility, and Collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Today mobile learning and ubiquitous learning are hand in hand when planning higher education courses. On the one hand, m-learning implies that learners have access to digital information by using any mobile device such as their tablets or smartphones. On the other hand, u-learning suggests that the walls of the traditional classroom are extended to more open spaces that facilitate not only the access to information but also to participation anywhere and at any time. Moreover, tasks can be designed having in mind either an individual or cooperative learning approach, in which the interaction between learners is the key to succeed

S. Garcia-Sanchez (*) · C. Lujan-Garcia Department of Modern Philology, Translation and Interpreting, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_74

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in their learning process. U-learning activities such as online glossaries, discussion forums, and interactive digital exercises allow today’s English as a foreign language (EFL) student to effectively enhance and perform their communicative language competence in the foreign language. Thanks to technology, current higher education students can improve the key skills of a foreign language (use of English, vocabulary, reading, listening, writing, and even speaking with other participants) using mobile devices and a u-learning approach. This chapter aims to demonstrate the work EFL tertiary learners have produced by using both m-learning and u-learning environments. The outcomes reveal that the communicative competence and the foreign language skills are being improved by using the appropriate technology, content, and tasks that are especially adapted to today’s digital students.

1

Introduction

Technology has been a revolution in today’s population. It has improved different community sectors, and as a result, educational institutions have positively benefited from implementing e-learning tools in their courses. From b-learning (blended learning) scenarios that combined face-to-face instruction with e-learning practice, technology keeps modifying ways of learning in order to adapt education to students’ needs. This approach to learning implies a proactive attitude by students and, therefore, a greater autonomy, more responsibility, and some more engaging and relevant tasks that are linked to interaction. Two of the main functions of using a smartphone are interaction and communication, which allows participants to be connected in various multitasks while on the go (Anshari et al. 2017; Schuck et al. 2017). Mobile phones are more sophisticated every day to answer the most demanding twenty-first-century citizens. Equally, learners carry either their phones or their tablets to actively participate in their learning process anywhere and at anytime. Mobile learning (m-learning) is a current methodology in education, “supported by situated learning, personalized learning, collaborative learning, ubiquitous learning, and lifelong learning” (Castillo and Ayala 2012). As Graf and Kinshuk (2012, p. 878) state, personalized learning systems consider the individual differences of learners and tailor their learning experience to their current situation, characteristics, and needs. This adaptation increases learners’ progress and outcomes and enables learners to learn with less effort and a higher motivation. Mobile and wireless technologies have produced new ways of interacting with the world, away from the limitations of desktop computers. These devices present design opportunities for multiple kinds of collaboration and to support different aspects of the learning process (Abachi and Muhammad 2014; Banerjee 2018; García-Sánchez and Burbules 2017; Milrad and Ulrich Hoppe 2012). The students participating in mobiquitous learning environments (m-learning and u-learning) actively not only decide, but they also select the resources that are best adapted to

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their context so that they can flexibly access the material (Abu-Al-Aish and Love 2013; Cope and Kalantzis 2010; Marrero et al. 2013; Luján-García and GarcíaSánchez 2012, p. 10). M-learning and u-learning environments contribute to the successful educational practices of continuity, autonomy, and interaction promoted by the European Higher Education Area (Aljohani et al. 2012; García-Sánchez 2014, p. 13). A mobile learning environment is defined as an approach that connects learning with moving or traveling, by means of a mobile device that has Internet connection. If e-learning implies accessing a computer or a laptop and typing information or clicking various links once connected, mobile learning deals with touching the device to continue on the go of learning (MoLeNET 2007; The eLearning Guild 2014). Moreover, the adequate application and thorough evaluation of m-learning environments imply moving the spheres of the classroom to new external spaces that require of the use of IT communication as highlighted by D. Stoller-Schai and M. J. Nursey-Bray in the corresponding chapters of this handbook (▶ Chaps. 66, “Mobile Learning Beyond Tablets and Smartphones: How Mobile and Networked Devices Enable New Mobile Learning Scenarios” and ▶ 55, “Mobiles, Online Learning, and the Small Group Discovery Classroom: Reflections from South Australia”). With an appropriate Internet connection, the possibilities for facilitating, supporting, enhancing, and extending the user’s knowledge are massive (MoLeNet). Ubiquitous learning goes beyond any time and place restrictions in order to provide learners with the real learning context they need at a specific time (Burbules 2012; Chen et al. 2013, p. 1; Kalantzis and Cope 2012). In their study, García-Sánchez and Luján-García (2016) proposed a ubiquitous learning context with both cognitive and practical experiences to foster EFL learning affordances in higher education. Mobile devices present design opportunities for multiple kinds of collaboration that satisfactorily support different aspects of the learning process (Milrad and Ulrich Hoppe 2012). Nowadays, u-learning occurs in everyday scenarios that are constructive, individual, cooperative, and collaborative (Bomsdorf 2005, p. 2; García-Sánchez 2012, p. 95). If m-learning and u-learning approaches are intertwined, the skills of a foreign language can be positively enhanced. It is a fact that the main purpose of learning a foreign language is to communicate with others via written or oral expression. Currently, communication quite often takes place on one’s mobile phone, not only by means of having a conversation with others but also by accessing instant messaging, social networks, and video chats with common software such as WhatsApp, Facebook, and Skype, which require Internet connection. Moreover, free apps for iPhone and Android have recently become quite useful when learning a foreign language. Some learners more often approach you by commenting on a new app that is suitable for the specific content they are learning. Some even prefer posting these useful apps that respond to their immediate needs on the course forum so that it is shared with others, as it was the case of the Cambridge UP phrasal verbs app. A smartphone is a complementary tool for learners, and although they mostly use it for personal communication, the mobile phone is becoming the most useful device to access instant information while walking or while traveling on the bus, for instance.

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This study is based on the communicative approach to teaching and learning English as a foreign language (EFL) at a renowned university in Spain using mobiquitous learning environments. The authors will focus on the written and oral expression of students of EFL while working in m-learning and u-learning environments. The following key questions will be addressed: 1. Can m-learning and u-learning environments improve individual and cooperative abilities in EFL? 2. Are the various EFL skills being constantly enhanced by our learners by especially accessing m-learning and u-learning environments? 3. What u-learning activities are successful to express written and oral forms of communication?

1.1

Higher Education Participation in M-Learning and U-Learning Approaches

A Spanish university has participated in innovative projects which have contributed to the creation of digital material in order to support our students’ learning process. Some teaching staff, devoted to the area of English as a foreign language (EFL), has elaborated videos of a different purpose in order to consolidate essential skills in this foreign language. Those videos were often supported by a number of interactive exercises of different types (e.g., gap fill or multiple choice), which learners could do and revise instantly. The type of material created for EFL was classified according to level B1 or level B2 on the Prometeo and the OCW platforms. Prometeo was the initial innovative project that especially promoted the creation of short videos of specific content teachers could upload on the platform. This project, presented in January 2008, was addressed to our educational community since participants were required to have a username and a password to have access to the digital material. Prometeo was also beneficial for the teachers of this project because they could use the flipped class methodology (Bergmann and Sams 2012), which implied that some instructive videos were designed as an integrative part of the course for students to watch outside the classroom (as homework), so that more face-to-face sessions could be devoted to practice communicative skills in English. Guerra-Artal et al. (2012) have demonstrated that digital tools such as the whiteboard Picasst can be effective for teachers who would record their animated flipped classes using their PCs or mobile devices and Internet connection. This project was closed in August 2012. In February 2011, this higher education institution launched its OpenCourseWare (OCW) platform, which followed the initiative launched by MIT (Massachusetts Institute of Technology) of publishing free online lectures and learning material. MIT started making public their first 50 pilot courses in 2002. Now the educational content, which was previously limited to the learning community with a username and password, is open and free for anyone to use anywhere and at any time. More recently, another tertiary education project by García-Sánchez and Burbules (2017) engaged 90 foreign language preservice instructors, enrolled in an official Master’s

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Fig. 1 University OCW platform

Degree in Secondary Education, in producing flipped classes that were set in a mobile and ubiquitous learning environment. The results were satisfactory since these preservice teachers dealt with pedagogical and ICT strategies at the time of producing their own videos and addressing a variety of learning styles for younger twenty-first-century learners (Fig. 1). After having participated in these innovative projects, which contributed to creating some useful digital content for EFL and other subjects of the institution, a group of innovative education researchers (Grupo de InnovaciónEducativa) produced the multilingual web Ubilingua, which has also a channel on YouTube with the videos recorded by its members. Ubilingua is currently opening their space in other languages such as Arabian, Chinese, French, German, and English and also in consecutive translation (Spanish–English and Spanish–German). Anyone can access these foreign language courses for free by simply registering on the website. These courses at Ubilingua do not have a unique learning pathway, but learners can choose the level, the skill, or the topic they would like to improve at a specific time (Figs. 2 and 3).

2

Communication and EFL Knowledge Building

Learners are not always engaged in the communication process of a foreign language, especially if they are studying a university degree. A vast number of Spanish EFL learners do not feel confident enough to speak in public, even less if they have

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Fig. 2 YouTube channel of Ubilingua

Fig. 3 Ubilingua interface based on Moodle

to do it in English. Several scholars have highlighted that motivation plays an important role at the time of learning any skill or content (Dörnyei 1997, 2001; Huiping and Hornby 2014; Kim and Pekrun 2014; Pintrich 2003; Sears and Pai 2013; Vizoso and Clara 2013; Wu et al. 2011). Some of the common characteristics that prevent our students from performing their communicative competence in English have to do with interpersonal fear (Sappington 1984, p. 24). They fear

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to be called upon for active participation in front of the class. Some are also embarrassed when talking in English because they may not feel confident when using their verbal language. When different language levels happen in the same group, which is quite common, it is frequent to observe that learners may be apprehensive by others criticizing their contributions in EFL. Is this fear of public speaking in EFL a cultural characteristic commonly shared by the Spanish population? Have Spanish children or adolescents been practicing their public speaking and question making from an early age? Without a doubt, most Spanish citizens have not been trained for active participation and therefore for public speaking. Active participation used to be penalized by the majority of past instructors. The lessons were more teacher centered, and learners were used to receiving information and instructions quietly. Now, it seems that teenagers tend to be more active participants. The learning environment in Spanish educational institutions seems to be changing to a positive lifelong learning context that trains EFL learners to speak up with appropriate presentations and questions from an early stage. Research on this area is essential in order to adapt the most efficient learning process to present-day students’ needs in Spanish higher education. These needs aim to combine the proper use of ICT with the improvement of EFL to its highest communicative competency, especially if the young population is immersed in an adequate foreign language environment from an early age (Luján-García 2011, p. 18). One of the research questions proposed in this chapter corresponds with the possibility of performing the communicative competence when working in m-learning and u-learning environments. In fact, it is believed that thanks to technology the communicative competence, which implies using words and correct grammatical structures in the foreign language, together with the appropriate use of the language and correct use of communication strategies (Canale and Swain 1980), is performed by EFL students at a distinguished university in Spain not only in the classrooms but anywhere else and at any other time, out of the academic schedule. This implies that current students are constantly performing their communicative competence when watching videos on their mobile phones or when responding to forum topics from their tablets. This study aims to focus only on one part of the communicative competence: learners’ spoken and written expression.

2.1

Expressing Themselves by Means of Written and Oral Tasks

The written and oral expression of EFL learners can only be improved if students are based on an interactive learning environment (ILE) that allows them to exchange messages in English. According to J. Psotka (2012): An interactive learning environment (ILE) is a system built in software and sometimes with specialized hardware designed to support teaching and learning in education. The interaction in the system can be between the learner and the system, the teacher and the system, or between teachers and learners with each other using the system.

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ILE can be easily combined with technology nowadays having as a result mobiquitous learning scenarios that facilitate communication and interaction among students. In this line, written and spoken forms can be integrated in their learning routines and adapted to their specific needs successfully.

3

Methodology

3.1

The EFL U-Learning Environment with Mobile Devices

This research integrates a context-aware ubiquitous learning environment with the enhancement of the EFL communicative competence, using mobile devices in higher education. Two degrees have been selected for this study. The first is the Degree in Modern Languages (DML), in which students are highly motivated to improve their communicative oral and written expression in English. The second is the Degree in Telecommunications Engineering (DTE), in which students are not given the possibility of choosing the English subject in the third year of their course because it is compulsory. Although English is obligatory in both cases, it is understood that students of DML have preferred to study languages so that they are motivated to improve their language skills, while in DTE, students have no other option rather than studying a six-credit subject during the second semester of the third year of their degree. A deductive qualitative methodology has been applied for this research, based on describing the phases, the task-based learning approach, and the consequent results achieved when using m-learning and u-learning scenarios. This investigation has also focused on a descriptive–comparative approach that aims to observe the EFL learning progress of our students by implementing u-learning environments in both degrees, DML and DTE, during three consecutive years (2011–2012/2012–2013/ 2013–2014). The stages are shown below: First phase: Register the m-learning EFL material that was needed for learners to follow the English courses in DML and in DTE. Once this m-learning material was selected, it was posted on the courses platforms. The m-learning material created by the EFL staff was posted on the OCW platform, on the Ubilingua website, and on the YouTube channel. Here different approaches that combine the flipped classroom with u-learning environments are considered. Second phase: Design and collect the type of digital activities created by students of DML and DTE that resulted in enhancing their communicative competence by means of m-learning and u-learning environments: Online glossaries, discussion forums, and interactive digital exercises. Here the instructions, the tools, the skill especially performed, and whether the activity is performed individually or in groups would be of consideration. Third phase: Analyze the activities together with the results and assessment for these communicative tasks. Assess if these m-learning environments satisfied students.

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Procedure

As mentioned before, this study was conducted during 3 consecutive academic years in a 15-week semester for each university program. During these 3 years, the study groups were asked to participate in a variety of learning approaches depending on the task or the content studied. On some occasions, students watched video lectures individually and outside the classroom (flipped classroom) in order to allow the physical space for tasks devoted to practice their written and oral expression. On other occasions, students were interacting with others while posting their comments on discussion forums or while elaborating glossaries on the course platforms (u-learning). Ultimately, they also delivered group oral presentations and individual written assignments that required the u-learning context-aware environment and the m-learning approach of using their mobile devices anywhere and anytime to do some research and to elaborate their tasks. The following Table 1 shows the activities designed for these students to demonstrate their oral and written skills in the EFL courses.

3.3

Level B1 and English

In Spanish higher education, it is essential to obtain a diploma that certifies a minimum of B1 level in English, according to the Common European Framework of Reference for Languages (CEFRL) in order to be graduated in any degree. Students are given the possibility to obtain this B1 level in English by means of one or several subjects in EFL they have to attend throughout their degrees. In the specific cases of the two university degrees analyzed in this chapter, DML and DTE, students have different subjects that provide the adequate conditions for them to obtain this B1 level. In DML, students may obtain a B1 level by attending their first two subjects in EFL (English I and English II), both of them taught in their first year at university. Table 1 Activities to improve written and oral expression in EFL EFL communicative activities focused on written and oral expression Degree in telecommunications Degree in modern languages engineering 2011–2012 Discussion forums, group oral Discussion forums, individual oral presentations using visuals, written presentations using visuals, written assignments assignments, online glossaries 2012–2013 Discussion forums, group oral Online glossaries, discussion forums, presentations using visuals, written in-class debates, group oral assignments presentations using visuals, written assignments, online glossaries 2013–2014 Discussion forums, group oral Online glossaries, discussion forums, presentations using visuals, written in-class debates, group oral assignments, in-class debate presentations using visuals, written assignments, online glossaries

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However, those students will be future experts in foreign languages, so they are required a higher level (C1) that they will achieve by attending four more compulsory subjects in EFL (English III, English IV, English V, and English VI) taught throughout their second and third years of degree. By contrast, students of Telecommunications Engineering are required a B1 level in English, and they have two compulsory subjects, English and Communicative Competences in English, which are taught in the last 2 years of DTE. Despite the obvious differences between both degrees in terms of demand of English, all the students are required a B1 level in EFL, and that is the level this chapter has addressed. The adequate design of tasks that correspond with the soft skills to perform level B1 in EFL will improve the written and oral competencies that follow:

3.3.1 Written Expression The main goal as regards this skill within level B1 is to be able to write wellstructured texts about daily life topics and related to the academic and professional fields. The competencies to be developed will be, first, the capacity to tell and describe feelings and experiences through simple written texts and to write real and imaginary short stories and, second, the ability to summarize information related to students’ specialties and express their opinions in brief written texts. 3.3.2 Oral Expression The main objective that students have to achieve is to describe in a simple and organized way a set of topics related to daily life. The specific competencies to be developed by students are, first, to be able to describe experiences and tell stories and events; second, to express opinions, plans, and actions; and, third, to present a topic, following an academic format, in front of an audience. The next section provides some examples of specific activities that students completed in order to achieve the abovementioned competencies set for level B1 regarding the oral and written expression. The tasks that were created using m-learning and u-learning methodologies are especially classified.

4

Results and Discussion

The outcomes reveal that the written and oral expressions together with the rest of EFL skills have been improved in both degrees by using the appropriate technology, content, and tasks that were especially adapted to these digital students. The authors have attempted to adjust their courses to the learners’ context. In this line, this section will be classified according to the following pairs of activities that happened in a mobiquitous learning environment: written or oral task and individual or cooperative work.

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Expressing Themselves by Means of Written and Oral Tasks

4.1.1 Written Tasks The written expression had a similar plan in both the DML and DTE courses. Students practiced the process of writing: how to generate ideas; how to narrow the topics; how to outline their essays, the paragraph structure, the essay structure, the appropriate use of linking words, and the passive voice for formal context; and how to include their opinions in the most objective and formal possible way as part of their writing sessions. These learners did various peer-to-peer exercises in class and online. They not only received constructive feedback from their teachers but also from their peers, who, following the evaluation criteria posted on the platform, provided suggestions to improve their written expression. It was an input–output exercise that they especially enjoyed. Moreover, these learners also received feedback and suggestions to improve from their teachers, not only once the first assignment was marked but during the writing tasks they posted on the forums or glossaries, for instance. Previous to the final written assignment, which was done in class in exam condition, these EFL learners had to express themselves, share their written work, offer feedback to other peers, and receive the suggestions provided in a constructive way with the intention of improving their writing skills. Students’ written expression was mostly assessed individually once the first essay was handed in and once the final essay was written in class in exam condition following the rubric they had already been using in this u-learning environment. The teachers also provided students with some feedback on the most common mistakes made by them during a class session with the whole group. Students generally discovered and recognized their own mistakes. Some DML students also wrote mini-sagas or stories in 50 words. They had to choose a topic they liked and write a mini-story by using only 50 words. It means that they had to carefully summarize the contents of their stories with the most appropriate words. Once they wrote their mini-sagas, they posted them on the virtual platform to share their anecdotes with their classmates. Students felt proud of seeing their creations posted, and they could vote for the best mini-saga. One more activity students in DML had to accomplish was the appropriate structure of an email with its opening, body, and closing paragraphs and the specific features of this kind of writing activity (informal language, abbreviations/contractions, and so on). Students were asked to write an email to an old friend they had found on Facebook. This task was sent to another classmate and to the teacher. Each student received an email from a classmate. They had to correct each other considering the conventions worked in class. The discussion forum was the most regular activity posted on these DML and DTE platforms. They did not only respond to the topics suggested by their teachers, but they even invited classmates to follow up the discussion with new welcoming conversations. The motivation level when participating in forums was generally high, and even the shiest student had the opportunity of speaking up and having a say

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on the topics proposed. Furthermore, the discussion forum remains one of the most useful activities to promote informal discussions in EFL for the improvement of lexis, grammar, and written expression. Learners are more often used to interacting by means of posting m-learning messages that can be read from their mobile devices. Another u-learning activity planned to improve their written structures was the digital glossary. The online glossary is based on Moodle, and it allows learners to create a group glossary with the most useful new terms studied in the course. Once students were presented some definition structures, they followed these instructions to add terms in the glossary created by the group. Each glossary differs each academic year since it is adapted to the specific needs of the learners participating in the course. This implies that the final glossary depends on the educational community participating in the course. This task was not only useful but successful at the time of creating correct definitions and sentences with the terms in a context applied to students. Although this tool could be printed out, most learners accessed this resource from their laptops (less frequent was the PC), their tablets, and their mobile phones.

4.1.2 Oral Tasks The EFL courses of this study planned for DML and DTE implied that students were immersed in an EFL scenario 24/7, when attending and interacting in face-to-face sessions or when accessing m-learning content. So, they could practice their written and oral expression together with their listening and reading comprehension, the lexis, and the use of English studied in these courses. The concluding oral tasks that formed part of their assessment criteria were the group oral presentation and the debates, both delivered in class. The oral presentations and the debates required that students created their groups in order to organize their work and assign roles to each group participant. These two oral tasks were founded on a collaborative learning approach that “was designed in order to highlight social and affective skills that would improve students’ confidence in the foreign language and the performance of various language skills” (GarcíaSánchez 2014, p. 7). The findings demonstrate that these tasks were positively accepted by students who mostly enjoyed the procedure of actively creating their speeches, either for a debate or for an oral presentation purpose. The cooperative approach was positively accepted by these learners who understood the level of decision-making and group compromise needed to fulfill these tasks. The intention, the format, the rules, and some expressions were explained at the end of one session so that students could do some research for homework. Initially, students were told that the class would be divided into three groups: the group in favor, the group against, and the audience. One member of the class, if possible a volunteer, would be the moderator who runs the debate controlling the time and the turns when speaking. Once the form of the debate was explained, students were told the topic of the discussion for them to do some research that could support their positive or negative arguments. Making some questions for the positive and the negative team was also suggested since they could also be assigned the role of the audience. Nobody would know which role they would have in the debate until the

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date planned for it. So, it is expected that everyone is well informed to contribute in either of the two teams or as part of the audience, which would also interact at the end of the discussion with some questions, comments, and/or suggestions. The rules and the steps for students to prepare the debate were also provided, together with some polite language they could use when introducing the topic or when expressing disagreement, for instance. In the DML group, this activity was done only in the second year of this study, while in the DTE, the debate had its place during the 2 years of this research, but it was only in 2013–2014 when the two classes (Group A and Group B) together with their teachers were joined in one common session to start the debate. The figures below show some of the slides presented in class during the last explanation of a debate (Fig. 4). Regarding the oral presentations, they were organized in groups of four or five students, and they had absolute freedom to choose a topic related to their field of expertise or a topic seen in class. Each student needed to present a section of their group speech and demonstrate coordination among the group members. Groups had to design their presentations following a set of guidelines presented by the teacher. On the day of their presentations in class, the rest of the students were required to be proactive, asking questions, saying comments or suggestions, and so on. It means that each presentation took around 20 min followed by 10 min of discussion. Obviously, students freely prepared this activity with various resources available to support their presentation such as music, videos, PowerPoint or Prezi, and disguises. Once the instructions for the delivery of the oral presentation were given (Fig. 5), learners could access the evaluation criteria on Moodle. They could understand which factors and percentage would be given to their work. The following figure shows an example of the rubric for one of the subjects in the DML. Students could understand the expectations of their work and the final grading. This rubric did not include the levels of quality (from poor to excellent or from 1 to 5, for instance), but the top standards for each evaluation category were given for students to peer assess (only in DML) each other and for teachers to evaluate their students’ work. In one of the subjects of the DML, peer-to-peer assessment was implemented during students’ presentation. While two groups delivered their speeches, the rest of the class followed their presentation and were welcome to make contributions or questions. Once their oral presentations were finished, one member of a group assessed another member of the other group (20%), while the teacher was assessing everyone (80%). In addition, each student was asked to write individually a few lines to state the mark they considered fair for their performance. Then, they handed in this piece of paper to the teacher. The final mark was summative and included both the students’ and the teachers’ feedback on the students’ goals. As E. Silva (2009) has suggested, current learning methodologies put “[a]n emphasis on what students can do with knowledge, rather than what units of knowledge they have” (Fig. 6). The results demonstrate that the oral presentation and the debate were the most satisfactory activities for students. In the organization of these activities, students had to establish clear roles that depended on each other to have a concluding product: the oral presentation. At the same time, preparing their oral presentation implied that

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“The IMPACT of TELEVISION on Society” TWO TEAMS: 1. POSITIVE: team agreeing with the topic 2. NEGATIVE: team opposing the topic – Each team argues its position within the framework of the debate.

Remember to have a moderator + audience and to use polite language

Debate week 10 Be ready to participate Do some research and read as much as you can about The impact of TV on Society (+ & -) On the debate day you will be given a specific role –(agree team/disagree team/audience/moderator)

Think about expressions and vocabulary that you should use when debating Check the debate rules as well –speaking time/turn…

Soraya García-Sánchez, ULPGC

Steps to prepare a debate 1. The debate begins with the presentation of a topic. –Good resolutions have two sides –Two teams are assigned opposing sides

2. Convince people 3. Give reasons and examples to support your arguments

Soraya García-Sánchez, ULPGC

Soraya García-Sánchez, ULPGC

Remember the rules set in a debate You are the only one allowed to speak Everyone else has to listen to you You will be given time limit (60 seconds) to speak When it is someone else's turn to speak you can't say anything, you have to write down notes that you might want to say and wait your turn to say it Soraya García-Sánchez, ULPGC

Fig. 4 Slides explaining the structure and rules of the debate

Fig. 5 Slides showing some tips students should follow to prepare their oral presentations

they used the vocabulary, appropriate structures, and other important aspects such as body language, visual contact, voice projection, and suitable design of their PPT presentations, for their talks to be formed successfully. They also had to divide the participatory interactions among the group members. Delivering a group oral presentation was a necessary requirement to pass these subjects. The vast majority of groups in both DML and DTE were actively motivated

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Fig. 6 Example of a rubric for oral presentations posted on Moodle

in participating in their oral presentations (85%). Although some students initially were frightened of this particular oral task, they finally succeeded and felt satisfied with their group and individual contributions. Even the less motivated students were immersed in providing similar responses to their class peers with the elaboration of their work, and therefore, they put a special effort in speaking up and letting their voices be heard by the classmates. Both the organization and elaboration of either the debate or the oral presentation allowed this tertiary educational community to participate in u-learning and m-learning environments. Students were given the instructions, the tools, and the evaluation criteria to accomplish these two oral tasks, which implied adapting their speeches to the specific context of the course and the students’ needs. Likewise, learners had to access flipped classrooms (“how to deliver an oral presentation” and “discourse markers,” for instance) and other u-learning spaces (“linking words,” “polite language,” and other web references) for their research and knowledge creation in EFL. García-Sánchez (2017) has demonstrated that today this knowledge creation implies combining formal and informal learning, individual and collaborative learning, mobile and ubiquitous learning. These individual and cooperative preparatory exercises were mostly done outside the classroom with no schedule limitations, which implied performing individual and group tasks.

4.2

Autonomy, Responsibility, and Collaboration

K. Yujaroen has previously highlighted in this handbook how necessary learners’ autonomy is when learning a foreign language in m-learning environments. The design of the exercises and tasks students had to accomplish in this study was planned having in mind an individual learning approach together with a collaborative learning approach. This proposal establishes a logical dialogue between two terms: autonomy and collaboration. Under the sphere of a learning environment,

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responsibility is the key concept behind a successful learning approach that should combine individual and teamwork. Normally, a citizen that is aware of their daily tasks has a positive impact on the rest of coworkers or family and friends. The same would happen in a learning environment. If a learner understands his or her goals in a responsible way, they cannot only be successful lifelong independent learners, but they can also contribute with other peers in team tasks that require that same level of compromise. When this responsibility takes place in both spheres, the final result is successful learning. The individual tasks planned for these EFL courses were especially designed to improve learners’ vocabulary, use of English, written expression, reading comprehension, and listening skills. The collaborative tasks, on the contrary, implied more peer-to-peer interactive actions that contributed to oral communication practice either by means of daily conversations in class and online discussion forums or by means of debates and oral presentations. While participating in these collaborative tasks, learners were also involved in enhancing other skills of EFL since they had to do other secondary actions such as reading, watching videos, writing, and supporting ideas in addition to using the vocabulary, for instance, to finally share and create the oral presentation and the debate. In this line, the current study demonstrates that both the individual and team activities were established in a communicative learning approach that promoted active participation by means of adding ubiquitous and mobile learning environments that go beyond the time and space limitations of the classroom.

5

Future Directions

Nowadays, it is doubtless that learning English as a foreign language (EFL) implies constant interaction between students and teachers and regular access to information by means of mobile devices. Learners of EFL in higher education are more often used to actively participate in the performance of exercises that focus on the skills of the foreign language: use of English, vocabulary, reading, listening, writing, and even speaking with other participants. U-learning suggests that knowledge and information are context aware and available anywhere and anytime. The written and oral exercises performed in class and online were carefully planned having in mind u-learning and m-learning environments, in order to allow these tertiary education students to be prepared for life and for professional purposes. Due to adapting these EFL students to current methodologies that included more participation, resourcefulness, and interaction, these learners were positively improving their written and oral expression in English since they were frequently involved in wireless systems of communication that not necessarily happened inside the classroom (Liu and Hwang 2010). Although some of the students’ final written and oral tasks were presented in class, it is assumed that their knowledge building occurred partly outside the classroom (individually and cooperatively) and by means of accessing u-learning spaces that contributed to EFL acquisition and production.

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From an empirical viewpoint, it is not new to affirm that this type of EFL lessons demands to be regularly innovating learning plans and assessment criteria that can be especially adapted to students’ needs. Depending on the contents, the number of learners, the number of weeks, and the u-learning tools, teachers can propose a u-learning environment that can be combined with a m-learning approach in order to promote anywhere and anytime self-determination for learning. In doing so, teachers can be closer to students’ reality. Consequently, current citizens’ needs are not being ignored. This study suggests that some EFL current instructors and learners are moving forward when accessing flipped classes or when creating interactive online glossaries and cooperative wikis. It is true, though, that only by means of proper training and continuous revision of goals can educational institutions contribute in the achievement of successful learning (Rudd II and Rudd 2014, p. 6). Deepening in this kind of approach to learning EFL by using m-learning and u-learning environments is a challenge for committed educators. Future prospects could be related to doing some rigorous research that can assess learners’ performance when they are participating in these u-learning environments that more frequently add the use of apps (Kim et al. 2013) or multi-synchronous language learning environments (Mellati et al. 2018) and other open-access tools students individually discover and share with their educational community.

6

Cross-References

▶ Mobile Learning Beyond Tablets and Smartphones: How Mobile and Networked Devices Enable New Mobile Learning Scenarios

References Abachi, Hamid R., and Ghulam Muhammad. 2014. The impact of m-learning technology on students and educators. Computers in Human Behavior 30: 491–496. https://doi.org/10.1016/ j.chb.2013.06.018. Abu-Al-Aish, Ahmad, and Steve Love. 2013. Factors influencing students’ acceptance of m-learning: An investigation in higher education. International Review of Research in Open and Distance Learning 14 (5): 82–107. Aljohani, NaifRadi, Hugh C. Davis, and Seng W. Loke. 2012. A comparison between mobile and ubiquitous learning from the perspective of human-computer interaction. International Journal of Mobile Learning and Organization 6 (3–4): 218–231. Anshari, Muhammad, et al. 2017. Smartphones usage in the classrooms. Learning aid or interference? Education and Information Technologies 22 (6): 3063–3079. Banerjee, Kamalika. 2018. How to incorporate open educational resources (OER) into the infrastructure and pedagogy for promoting ubiquitous learning. In Innovations in open and flexible education, 177–184. Singapore: Springer. Bergmann, Jonathan, and Aaron Sams. 2012. Flip your classroom: Reach every student in every class every day. Eugene: ISTE. Bomsdorf, B. 2005. Adaptation of learning spaces: Supporting ubiquitous learning in higher distance education. In Mobile Computing and Ambient Intelligence, Germany.

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Burbules, Nicholas C. 2012. El aprendizaje ubicuo y el futuro de la enseñanza. Encounters 13: 3–14. Canale, Michael, and Merrill Swain. 1980. Theoretical bases of communicative approaches to second language teaching and testing. Applied Linguistics 1: 1–47. Castillo, Sergio, and Gerardo Ayala. 2012. Mobile learning. In Encyclopedia of the sciences of learning, ed. Norbert M. Seel, 2293–2295. Berlin/Heidelberg: Springer. Chen, Da-Ren, Mu-Yen Chen, Tien-Chi Huang, and Weng-Pao Hsu. 2013. Developing a mobile learning system in augmented reality context. International Journal of Distributed Sensor Networks 2013: 1–7. https://doi.org/10.1155/2013/594627. Cope, Bill, and Mary Kalantzis, eds. 2010. Ubiquitous learning: Exploring the anywhere/anytime possibilities for learning in the age of digital media. Urbana-Champaign: University of Illinois. Dörnyei, Zoltán. 1997. Psychological processes in cooperative language learning: Group dynamics and motivation. The Modern Language Journal 81: 482–493. Dörnyei, Zoltán. 2001. Motivational strategies in the language classroom. Cambridge: Cambridge University Press. García-Sánchez, Soraya. 2012. English in class and on the go: Multimodal u-learning. The Eurocall Review 20 (2): 94–102. García-Sánchez, Soraya. 2014. Knowledge creation and digital collaboration in higher education. In Collaborative learning: Theory, strategies and educational benefits, ed. Stephen Rutherford, 1–14. New York: Nova. García-Sánchez, Soraya. 2017. Collaborative ubiquitous learning: A 21st-century approach to (in) formal scenarios. In Informal learning: Perspectives, challenges and opportunities, ed. Stephen Rutherford, 57–71. New York: Nova. García-Sánchez, Soraya, and Nicholas C. Burbules. 2017. A revision of activity theory to foster communicative 21st century skills. The International Journal of Learning: Annual Review 24 (1): 1–12. García-Sánchez, Soraya, and Carmen Luján-García. 2016. Ubiquitous knowledge and experiences to foster EFL learning affordances. Computer Assisted Language Learning Journal 29 (7): 1169–1180. Graf, Sabine, and Kinshuk. 2012. Personalized learning systems. In Encyclopedia of the sciences of learning, ed. Norbert Seel, 878. Berlin/Heidelberg: Springer. Guerra-Artal, Cayetano, Soraya García-Sánchez, and María Dolores Afonso-Suárez. 2012. Picasst: An innovative web-based tool for recording classes. Ubiquitous Learning: An International Journal 4 (3): 73–84. Huiping, Ning, and Garry Hornby. 2014. The impact of cooperative learning on tertiary EFL learners’ motivation. Educational Review 66 (1): 108–124. https://doi.org/10.1080/ 00131911.2013.853169. Kalantzis, Mary, and Bill Cope. 2012. New learning: Elements of a science of education. 2nd ed. Cambridge: Cambridge University Press. Kim, ChanHin, and Reinhard Pekrun. 2014. Emotions and motivation in learning and performance. In Handbook of research on educational communications and technology, ed. J. Michael Spector, M. David Merrill, Jan Elen, and M.J. Bishop, 65–75. New York: Springer. Kim, Eunice, Jhih-Syuan Lin, and Yongjun Sung. 2013. To app or not to app: Engaging consumers via branded mobile apps. Journal of Interactive Advertising 13 (1): 53–65. Liu, Gi-Zen, and Gwo-Jen Hwang. 2010. A key step to understanding paradigm shifts in e-learning: Towards context-aware ubiquitous learning. British Journal of Educational Technology 41 (2): E1–E9. https://doi.org/10.1111/j.1467-8535.2009.00976.x. Luján-García, Carmen. 2011. The impact of English on Spanish daily life and some pedagogical implications. Nordic Journal of English Studies 11 (1): 1–21. Luján-García, Carmen, and Soraya García-Sánchez. 2012. M-learning: Transforming present education and designing future education. Frontiers of Language and Teaching 3: 1–12. Marrero, Darias, Soraya García-Sánchez Agustín, and Ana Ruth Vidal Luengo. 2013. Aprendizaje móvil, ubicuo y autónomo de lenguas extranjeras en la ULPGC. Cuadernos de InnovaciónEducativa 1: 11–35.

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Mellati, Morteza, Marzieh Khademi, and Majid Abolhassani. 2018. Creative interaction in social networks: Multi-synchronous language learning environments. Education and Information Technologies: 1–19. Milrad, Marcello, and H. Ulrich Hoppe. 2012. Learning with collaborative mobile technologies. In Encyclopedia of the sciences of learning, ed. Norbert Seel, 684. Berlin/Heidelberg: Springer. MoLeNET: The mobile learning network. 2007. http://www.molenet.org.uk/. Accessed 10 Nov 2014. Pintrich, Paul R. 2003. A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology 95 (4): 667–686. Psotka, Joe. 2012. Interactive learning environments. In Encyclopedia of the sciences of learning, ed. Norbert Seel, 1604–1606. Berlin/Heidelberg: Springer. Rudd, Denis P., II, and Denis P. Rudd. 2014. The value of video in online education. Journal of Instruction Pedagogy 13: 1–7 http://www.aabri.com/manuscripts/131760.pdf. Accessed 28 Oct 2014. Sappington, Thomas E. 1984. Creating learning environments conducive to change: The role of fear/safety in the adult learning process. Innovative Higher Education 9 (1): 19–29. Schuck, Sandy, Matthew Kearney, and Kevin Burden. 2017. Exploring mobile learning in the third space. Technology, Pedagogy and Education 26 (2): 121–137. Sears, David A., and Hui-Hua Pai. 2013. Effects of cooperative versus individual study on learning and motivation after reward-removal. The Journal of Experimental Education 80: 246–262. Silva, Elena. 2009. Measuring skills for 21st century learning. Phi Delta Kappan 80 (9): 630–634 http://216.78.200.159/RandD/Phi%20Delta%20Kappan/Measuring%20Skills%20for%2021st %20Century%20-%20Silva.pdf. Accessed 29 Oct 2014. The e-Learning Guild: Community and resources for eLearning professionals. 2014. http://www. elearningguild.com/. Accessed 5 Nov 2014. Vizoso, Martín, and María, Clara. 2013. Los MOOCs un estilo de educación 3.0. In Scopeo informe n 2. Mooc: estado de la situación actual, posibilidades, retos y futuro, 239–261. http://scopeo. usal.es/wp-content/uploads/2013/06/scopeoi002.pdf. Accessed 21 Oct 2014. Wu, Wen-Chi Vivian, Ling Ling Yen, and Michael Marek. 2011. Using online EFL interaction to increase confidence, motivation, and ability. Educational Technology and Society 14 (3): 118–129.

How Irish Postgraduate Students Use Mobile Devices to Access Learning Resources

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Advantages and Challenges of M-learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Using M-learning in Online and Distance Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 M-learning and the Virtual Learning Environment (VLE) . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Research Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

For almost 20 years, the University of Limerick has run programs in technical communication. These programs have evolved over time to encompass online delivery techniques. More recently, the suite of learning materials includes discrete learning objects and podcasts. These delivery strategies facilitate increased personalization of learning including through mobile devices. This chapter discusses how learning resources, deployed through a virtual learning environment (VLE), are used by postgraduate technical communication students A. Marcus-Quinn (*) · Y. Cleary School of Languages, Literature, Culture and Communication, University of Limerick, Limerick, Ireland e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_29

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(including a cohort of distance learners) in a personalized manner. Eighteen students completed a short survey about their uses of mobile devices to access learning resources. The findings indicate that over half the respondents regularly access a variety of materials, in various ways, through mobile devices. The findings also imply that, in the absence of policy, educators need to be vigilant to ensure that delivery of materials matches learner expectations.

1

Introduction

Use of mobile technologies is rapidly overtaking use of other computing devices and fixed-line computing. Wohlsen and Marcus (2010) have predicted the end of the PC era, following a worldwide drop in sales of 10% last year alone. The home market share is dropping rapidly because of increases in tablet and smartphone sales, while in emerging markets many consumers have entirely skipped the PC era in favor of mobile computing devices (IDC 2014). Recent reports (IDC 2014; Gartner 2014) forecast that tablet sales will surpass PC sales by the end of 2015. IDC note that “the transition toward mobile and cloud-based computing is unstoppable.” Because mobile devices are becoming ubiquitous, they have enormous potential to be harnessed to deliver many types of personalized educational materials to learners, though that potential may not always be harnessed effectively (Traxler 2010a). Mobile learning is not an entirely new paradigm; rather it builds on theories of traditional and online learning but has a strong emphasis on accessibility and personalization. These are especially important features for higher-level students and for online learners (Betts and Lynch 2009). Many chapters in this handbook examine the use of m-learning with students. For example, Zhang explores student feedback in mobile teaching and learning. The objective of this chapter is to examine how postgraduate students taking technical communication courses through a mix of on-campus and distance delivery modes exploit mobile technologies in their learning. This chapter reports on a survey of postgraduate technical communication students about their use of mobile devices to access learning materials. The chapter begins by exploring the background to m-learning, focusing on its advantages and potential disadvantages, its use in online and distance courses, and its use with a VLE. It then describes the parameters of the study. The next section of the chapter reports the findings followed by an interpretation of what these findings mean in the context of previous studies. The final section presents directions for future research in this area.

2

Literature Review

This literature review provides a background to the chapter by examining the advantages and disadvantages of m-learning, discussing its use in online and distance education, and exploring m-learning in the context of a university VLE.

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Advantages and Challenges of M-learning

ICT in education is one of UNESCO’s themes, and mobile learning is a prominent strand within that theme. UNESCO (2013) notes the benefits of mobile learning: “It presents unique attributes compared to conventional e-learning: personal, portable, collaborative, interactive, contextual and situated, it emphasizes ‘just-in-time-learning’ as instruction can be delivered anywhere and at anytime through it.” This accessibility has carryover benefits for all students. JISC (2013) notes that “learning with mobile devices can bring many inclusion benefits, enabling learners to access content wherever and whenever they choose, and using a device they know they can operate.” Personalization of education is becoming increasingly important, as learning happens among myriad other activities in learners’ busy lives (Evans 2008). Mobile learning is a form of personalized learning, enabling a means of pursuing “meaningful curriculum engagement with students’ diverse life experiences, life projects and life-long learning” (Hargreaves and Shirley 2011, pp. 16–17). M-learning, furthermore, has the potential to increase self-regulation and ultimately should result in improved learning outcomes for students (de Marcos et al. 2010). There are, of course, also challenges associated with m-learning as a new paradigm. At the level of the student, a digital divide appears to be emerging, between those users who have access to mobile devices and have the confidence to use them and those who do not. One of UNESCO’s policy guidelines for m-learning (2013) is to “develop strategies to provide equal access [to mobile devices] for all.” No learner should be left behind because of lack of access or confidence. While older users may find adapting to m-learning more of a struggle than traditional learners, a study by Santos et al. (2013) shows that a “collaborative and participative approach” combined with meaningful activities helps engage older learners. A recurrent theme in the literature is that m-learning should not be the exclusive means of delivering educational materials but ideally should be blended with more formal and structured delivery mechanisms (de Marcos et al. 2010). This strategy helps to ensure that those learners who do not have access to mobile devices are not denied learning opportunities. At the level of content, m-learning materials must be accessible to all users. Responsive design is essential for accessible content (W3C 2013). The corollary is that content is equally accessible to learners who do not use or have access to mobile devices. De Marcos et al. (2010) advocate “granularity” where small blocks of content are made available to students to support learning of discrete topics. At the level of policy, several researchers and organizations outline the need for local (institutional), national, and international strategies to support and manage m-learning. UNESCO has developed policy guidelines for m-learning in a context where “[t]he ever-increasing availability of mobile technologies requires policy-makers to revisit and rethink the potentials of ICT in education” (UNESCO 2013, p. 7). A report from the Web Accessibility Initiative (W3C 2013) notes the convergence of web accessibility issues with the need for harmonization of design standards for mobile devices. These challenges, and potential solutions, interact with one another. For example, the type of content an instructor develops will be influenced by the institutional policies and supports, including the VLE and its adaptability to mobile delivery.

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Using M-learning in Online and Distance Programs

Online and distance learning programs are becoming more popular as student demographics and lifestyles change. Geith and Vignare (2008, p. 7) explain that “[o]ne of the key benefits of online learning is that it can be offered free of time and geographic constraints, thereby increasing the accessibility of higher education.” According to the Irish Higher Education Authority (HEA), over 43,000 part-time students had college places in Ireland in 2013. The HEA (2013) aims to increase access for all types of students: Achieving full equality of access to higher education is a national priority, for people with disabilities, mature students who previously had not the opportunity to access higher education, those facing social and economic barriers, and minority groups, including the Traveller community.

The HEA Strategic Plan posits open and distance learning programs as potential interventions which could increase access for underrepresented groups within the population. Because most adults “are not in a position to put their lives and commitments on hold for 3–4 years while they pursue full-time study” (MacKeogh and Fox 2008, p. 1), e-learning, m-learning, and flexible access to educational resources are a potential means of enabling such students to participate. Even among the more traditional cohort of 18–22-year-olds, part-time work is common. Darmody and Smyth (2008, p. 353) report that 60% of Irish full-time higher education students they surveyed work “at least to some extent, during term time.” These students value, and may even expect, more flexible and personalized educational arrangements. Betts and Lynch (2009) show that “the long-term sustainability of online degree programs is highly dependent upon student engagement and retention. Therefore, with increasing numbers of non-traditional students returning to higher education through online programs, it’s critical that institutions personalize the online experience and develop strategies to bring the campus to this growing student market.” According to Lee and Chan (2007, p. 202), m-learning is a “natural match” for distance learning programs because it enables learners “to undertake learning in conjunction with other tasks, or when on the move for extended periods of time, such as during business trips. Many of them are ‘continuously connected’ by mobile phones, laptops and hand-held devices.” Making materials, including podcasts, readings, and presentations, available to users of mobile devices helps to meet the expectations of distance learning students who need to be able to access materials any time and any place and who have the technology to enable them to do so.

2.3

M-learning and the Virtual Learning Environment (VLE)

AVLE has become an essential tool for educators in higher education, and especially in online courses, since it can support constructivist and self-regulated learning (Betts and Lynch 2009). Through the VLE, students have access to learning resources (such as

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podcasts, presentations, syllabi, and readings), as well as collaboration tools (discussion forums, online chat tools, and group forums) and organizational tools (a course schedule, university handbook, and links to the university library, for example). Accessing the VLE through mobile devices takes personalization to a new level, because students are now able to read lecture materials and supporting documents, listen to podcasts, contribute to conversations via discussion forums and online chats, and find organizational supports, from any place at any time (assuming that the technological infrastructure is in place), all on a mobile device. They are not tied to the campus nor to a fixedline computer (Traxler 2010b). Using the VLE in this way effectively does what Betts and Lynch (2009) indicate the need for: it “brings the campus to the student” rather than the converse. There are two postgraduate programs in technical communication at the University of Limerick (UL), an MA in Technical Communication and E-Learning and a Graduate Certificate in Technical Writing by distance learning. The latter program is delivered entirely online through the university VLE. Students on both programs share courses, and they all have access to VLE resources such as readings, presentations, and podcasts, as well as shared online discussions and chats. The mode of deployment may influence the perception and usability of a VLE in a mobile environment. The UL VLE is Sakai (called Sulis at UL), an open-source “full featured system supporting technology-enabled teaching, learning, research and collaboration for education” (Sakai 2014). This is a web-based VLE deployed using a responsive web design for mobile delivery. The site resizes to fit the – likely smaller – mobile device screen (see Fig. 1), and a mobile version of the site is also available (see Fig. 2). Students accessing the VLE through a mobile device expect a stable deployment. According to one study (Cho et al. 2014), students using smartphones to access a VLE rated reliability as twice as important as students using desktop computers. The authors take the view that m-learning is an extension of e-learning and do not seek to replace traditional teaching strategies but rather to take a blended approach that exploits m-learning’s potential for personalization, access, and flexibility, to augment the learning experience, for both on-campus and online learners. Within this framework, the study seeks to examine whether and how postgraduate students on technical communication programs at the University of Limerick access the university VLE using mobile devices, and their satisfaction with the experience. The next section outlines the methodological approach.

3

Methodology

The expectations and learning environment has changed rapidly over the last few years, particularly with the influx of open educational resources; it is important to recognize that student needs and expectations have also changed. There is a lot of anecdotal-based work available in the literature describing the benefits of mobile learning, but there are fewer evidence-based cases available (Hew 2013). Even the recently circulated roadmap for building digital capacity in Irish higher education (2014) does not provide any detail

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Fig. 1 Full site via mobile presentation

on the current state of mobile learning in Ireland. It merely states, “The proliferation of mobile devices such as tablets and smartphones is one area that is impacting on the technological infrastructure. This is evidenced in the huge growth in demand for Wi-Fi that is being reported across the sector” (p. 15).

3.1

Research Design

In order to ascertain questions to ask to capture to what extent, if any, existing teaching and learning materials were being used to accommodate some aspect of mobile learning, the authors conducted a manual electronic search of the literature

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Fig. 2 Mobile site

across the available academic databases including Applied Science and Technology Source and the Web of Science. These databases are highly regarded by other investigators in their search for empirical articles (Hung and Zhang 2011). The databases were used to search for articles using an open-ended search period (up till December 15, 2013). The terms used for the search strategy are listed in Table 1. The first author read the abstracts of the studies initially identified by the databases, and relevant studies were then selected for review. The articles included case studies which discussed the impact of using Web 2.0 technologies on teaching and learning. Where the studies included questionnaires, some of the more frequently occurring questions were adapted for this survey (Chen and Denoyelles 2013). Studies where the participants of the studies were either in elementary/ primary or secondary/postprimary schools were excluded.

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Table 1 Search strategy keywords

Sequence 1 2 3 4 5

Keyword Mobile learning M learning Mobile education Web 2.0 and education Virtual learning environment (VLE)

The two aims/objectives of the study were • To determine the effectiveness of learning resources as a personalized learning solution • To determine which learning materials are used in “mobile” ways In order to answer these questions, students were surveyed to get feedback on the learning resources and ascertain if any of the resources were being used to facilitate mobile learning. This strategy also sought to elicit the students’ opinions on types of resources that they found of most value.

3.2

Participants

There were two groups involved in the study: students undertaking the Graduate Certificate in Technical Writing by distance and students on the MA in Technical Communication & E-Learning. A total of 36 students were invited to participate in a survey to explore to what extent they use mobile devices to access learning resources on the institutional VLE. This group were of a wide range of ages and experiences, and at least half of the group were in part-time employment.

3.3

Instruments

An online tool (SurveyMonkey) was employed to ensure that their responses remained anonymous. The students were not under any obligation to respond to the survey. However, the invitation did state that feedback would be noted and where applicable, comments and recommendations would influence the future development of teaching materials for online delivery. The questionnaire included questions pertaining to the use of the VLE by each student. Questions sought to capture data on frequency and location of accessibility and the perceived suitability of the learning resources. The questionnaire had a total of ten questions drawing on the pertinent literature.

3.4

Procedure

After successfully completing the first 13 week semester of their respective courses, all 36 students were invited to respond to the survey. A total of 18 responded to the

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survey giving a response rate of 50%. Over the last number of decades, there are trends of decreasing response rates around the world (Fan and Yan 2010). The nonresponse bias for this survey could be attributed to many students reporting survey fatigue during the autumn semester. This was a self-reported questionnaire on students’ interaction with the available learning resources over the first 13 weeks of the academic year 2013/2014. The questionnaire was accessible via a secure website, and students that responded had their IP address captured, as well as how long they spent completing the questionnaire. The questionnaire consisted of questions relevant to the type of mobile device used by the students, frequency of student visits to the VLE, and the preferred location of the students for accessing and/or using the resources. Two additional items were relevant to the learning resources, asking students to rate the teaching materials (seven-point scale). There were three comment boxes prompting students to explain their ratings and asking for detail on what teaching materials were the most and least successful.

3.5

Limitations

The authors presumed that the entire student cohort had a mobile phone or access to a mobile device, but prior to collecting the survey, there was no evidence to this effect. It is also important to note that while all respondents to the survey claimed that they owned a mobile device, not all of the students responded to the survey; the response rate was 50%. Therefore, there may be a significant minority who do not own a mobile device that are not represented in the study. The authors did not differentiate between the full-time and the distance students taking the survey nor observe the students using the resources. The data collected is from a self-reported questionnaire. This study does not claim to be exhaustive on the use of mobile technology by this cohort.

4

Results

The intention of this study was to invite students to participate in a survey to explore to what extent they use mobile devices to access learning resources on the institutional VLE. However, given some of the responses, it would seem that the survey was considered by some as a course evaluation. This is not unexpected for two reasons. Firstly, many of the questions could be found in a course evaluation questionnaire, and secondly, the survey was circulated to students during the final 2 weeks of the semester. Participants were aware that feedback would be noted and where applicable, comments and recommendations would influence the future development of teaching materials for online delivery. The survey response rate was 50% 18 out of the potential 36 completed the survey. The respondents to the survey engaged with the questions and responded with considered and meaningful replies, taking on average 9½ min to complete the

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survey. There was no evidence of the “asdf” problem nor did students enter nonsense words as responses (Müller et al. 2014). This constructive feedback may be attributed to the fact that the surveyed group comprised only graduate students. Table 2 illustrates the many devices used by this cohort to access the learning materials online. While the use of a laptop is unsurprisingly the top choice, a large number also use their smartphones/iPhones and/or tablets. One would expect that if the survey were conducted with a cohort of students in the academic year 2014/2015, the use of tablets would be even greater as there have been new releases of many tablets and they have become more affordable. It is worth noting that none of the respondents reported using a Blackberry device given that this device was one of the market leaders until 2011. The survey did not explore which specific learning resources the 12 students who reported using either a smartphone or an iPhone accessed. It would be worth conducting further study to see if students using a mobile phone device contributed to the discussion for a using the mobile phone. It is striking that so many of the respondents reported using the full site in preference to the mobile site given that so many accessed the resources using a mobile phone (see Table 3). It is worth noting that the Help documentation provided for Sulis by the University of Limerick provides no information on accessing the mobile version of the site. This may account for students not choosing the mobile site when using a mobile device. When asked how many times a week they visited the Sulis site, the average response was 8.3 times; the highest number of self-reported visits was 20 and the lowest was 4. Interestingly, the data stored for the Sulis site reports an average of 14 visits a week per unique visitor. However, the survey results reflect the reality that there are some very active users of the site and some that engage with the VLE to a much lesser extent. The study aimed to establish how students were storing the material from the VLE. The majority (12) reported that they downloaded the material locally while a significant number (8) chose to download the materials multiple times. This finding may suggest that they were using multiple mobile devices to access the materials. This study did not explore the use of many mobile devices, and this topic would merit further investigation. If learning materials are to be adapted for the most effective and appropriate mobile delivery, then it is crucial to understand where the materials are being accessed and used. To this end, students were asked where they usually accessed

Table 2 Mobile devices used by students Device Percent Number

Smart phone 47.06% 8

iPhone 29.41% 5

Tablet 52.94% 9

Music player 0 0

Laptop 64.71% 11

I didn’t know there was a mobile option 1

Both 3

Table 3 Breakdown of use: full site or mobile site Full site 13

Mobile site 1

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the teaching materials. Table 4 details the locations where students reported using the materials. All of the respondents accessed the materials at home. The survey did not explore whether they used a desktop at home or not. It is a safe assumption that those accessing the materials in an “extramural,” informal, or “other” setting were much more likely to have used a mobile device to do so. Therefore, at least 9 (possibly 15) of the 18 respondents used the teaching materials in a mobile manner. Students were asked to rate the teaching materials (using a seven-point scale). The purpose of this question was to try to gauge the perception of mobile devices for academic purposes and to capture how the students were using the teaching materials to achieve some level of personalized learning. None of the statements resulted in any distinctive polarization, as illustrated in Table 5. When asked to comment on what they had found to be the most useful of the teaching materials, many reported that the lecture slides were the most useful. Table 4 Locations at time of use reported by students Institutional: formal setting e.g., school classroom/university 16.67% 3

Home 100.00% 18

“Extra-mural”: e.g., library, school playground, excursion site, museum 22.22% 4

Informal: e.g., cafe, public transport 27.78% 5

Other 33.33% 6

Table 5 Student response to “mobile devices for academic purposes” Comment

1

2

Improve my quality of work Make it easier to access my coursework Make it easier to complete my coursework Increase my knowledge in my field of study Increase my motivation towards completing my coursework Increase communication with other students Increase communication with my instructor

16.67% 33.33% 3 6 22.2% 4 16.67% 3

4

5

6

11.11% 2 11.11% 2

27.78% 5 11.11% 2

0% 0

5.56% 1 5.56% 1 18

5.56% 1 11.11% 2

22.2% 4 18

4.17

16.67% 3

22.2% 4 11.11% 2

16.67% 3

11.11% 2

5.56% 1 18

4.44

16.67% 3

5.56% 1 22.2% 4 5.56% 1 22.2% 4 16.67% 3

11.11% 2

18

3.94

11.11% 2

5.56% 1 16.67% 3

5.56% 1 11.11% 2

18

3.83

18

3.28

18

3.33

5.56% 1 11.11% 2

11.11% 2

16.67% 3

5.56% 1 16.67% 3

33.33% 6

16.67% 3

7

Average Total ranking

3

22.2% 4 22.2% 4

5.56% 1 22.2% 4 5.56% 1 5.56% 1 22.2% 4 27.78% 5

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The podcasts were also recognized as effective. It was useful to capture how students tended to use the lecture slides and podcasts. A significant number reported listening to the podcasts in tandem with the lecture slides in the first instance and then referring to the lecture slides on their own at a later date. This strategy could be considered as mimicking the traditional lecture whereby students attend the lecture and receive face-to-face instruction from the lecturer and take notes. They only receive this “performance” once. They then access the slides and their personal notes from the slides any number of times. Knowing that many students may only listen to the podcasts once may change how the audio is delivered in the future. It may be better to lock the audio into the presentation so that students will be presented with audio whenever they try to access the slides. Although not immediately considered a “teaching material,” the discussion forum was also rated quite highly among respondents. Two of the respondents were critical of the teaching materials but did not recommend or suggest anything else that would better accommodate mobile learning. Remarkably, none of the comments suggested that video would be advantageous for mobile learning. Some of the student responses are provided below: “(I) saved slides as word documents and used them as a basis for better understanding the lecture through use of ‘other’ (resources), i.e., textbooks.” “Easy access to materials mentioned in class was excellent for referring back. The discussion forums are an excellent source of information and help both from lecturer and other students.” “[I]I Found lecture slides most useful.” “A concise and quickly accessible summary is most useful.” “The podcasts are very useful.” “I would rank them all [lecture slides, podcasts and discussion] as quite high as used together you get a great experience as a distance student”. “The discussion forum and teaching materials are a bit weak, so I’m supplementing with library stuff.” “Lecture slides contained a lot of very valuable information and could be accessed often, very quickly. I always used them along with the podcast in the first instance but then went through them again a couple of times on their own.” “It [The Discussion forum] was useful to bounce ideas around and hear other people’s responses. [I] could learn from what others wrote there.” “[The lecture slides] Contained information I could research. I would have put the top 3 [slides, podcasts and discussion forum] together as they all were useful for different things.” “Lecture slides can be easily referred to when needed, give structure to the podcasts.” “[The lecture slides were] Easily accessible visually. They provide an excellent basis.”

When asked to comment on what teaching materials (if any) were not successful, many reported that the combination of resources had worked quite well but that in isolation the teaching materials were less effective. There was very little criticism of either the teaching materials or the manner in which they were presented. What did emerge from the qualitative comments was that small changes could potentially have a positive impact on mobile learning. One student stated that they would appreciate if they could be notified when new topics were posted to the discussion forum. Both

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the instructor and the student must activate this feature. This is a very small task that may improve the mobile learners’ experience. The students also appreciated some of the recommended text being made available electronically. A small number of distance students were critical of the lab sheets provided to guide them through the software applications that are covered on the graduate program. While every effort is made to try and provide support for the delivery of this content, it remains challenging, particularly for distance students. Over the next semester, possible alternatives for the delivery of this content for distance students will be considered.

5

Discussion

This study set out to determine the effectiveness of learning resources as a personalized learning solution and to determine which learning materials are used in “mobile” ways. The learning materials accessed by the students participating in this study were not specifically designed for mobile delivery. The purpose behind the materials was to try and enhance the learning experience for all students, both traditional and distance. Creating podcasts and directing learners to online supplementary material including multimedia was a natural development to enhance traditional lecture slides. The results of this study suggest that there is a gap between students using mobile devices and instructors requiring students to use mobile devices. If instructors were more aware of the devices and mobile applications that students are currently using to engage in mobile learning, then perhaps mobile learning could be exploited to a greater degree. The current situation is that instructors cannot assume that students have mobile devices or that they are comfortable using them to access educational materials. According to Kearney et al. (2012, p. 9), personalization “has become a corner stone of e-learning. Key features associated with personalization include learner choice, agency and self-regulation as well as customization.” Appropriately designed mobile learning/teaching materials can afford learners a better learning experience (Pachler et al. 2009). Mobile learning can be customized at a number of levels: the actual teaching materials created/provided by the instructor, how these teaching materials are presented (intended use), and the actual manner in which they are used. As learners are accessing the materials on their personal mobile devices, they are able to engage with the material in a more autonomous manner (Lee and Chan 2007). Learners can choose how often they wish to visit the VLE and where and how they want to store the teaching materials (Betts and Lynch 2009). This level of autonomy is evident in this study. Students accessed the materials in nontraditional educational settings, they chose where and how to store content, and they also actively chose how they would use the lecture slides (in tandem with the podcasts or not). Instructors are encouraged to foster and promote autonomous learning. The teaching materials and course content are provided. Traditionally, the educational institutions have provided the technology and access to that technology. Now,

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however, a sea change is emerging in that it is the students who are assuming the responsibility for the technology (UNESCO 2013). In providing their own devices, they are changing the system (Hargreaves and Shirley 2011). As Traxler (2010a, p. 151) states, “The institutions traditionally procure, provide and control the technology for learning but now students are acquiring their own personal technologies for learning and institutions are challenged to keep pace.” These devices enable students to assume autonomy over the content that is provided to them in terms of how they store, transmit, and consume information: “this potentially realises the educators’ dream but for institutions is potentially a nightmare, one of loss of control and loss of the quality, consistency, uniformity and stability that delivered the dreams of equity, access and participation” (Traxler 2010a, p. 149). Traxler, among others, observes that using desktop technology takes place in a “bubble” – in committed times and locations where the user ignores the world for a considerable and possibly planned episode, whereas interaction with mobile technologies is “woven into all times and places of students’ lives” (Traxler 2010b, p. 150). Mobile devices create potential learning environments in every conceivable space. Mobile learning has the potential to redefine the very notion of a learning space (Melhuish and Falloon 2010). However, what if the space is not an appropriate learning space? Educators no longer have the power to dictate or suggest where materials are to be accessed or where work is to be completed. This small-scale survey has shown that mobile learning is happening anyway and students will continue to use their own technology to engage in mobile learning. This finding implies that both students and instructors need a policy at an institutional and national level to better facilitate mobile learning. Without a policy, student expectations may be unrealistic and cause frustration when they are not met. Furthermore, instructors will not have any level of support in terms of what and how they offer their mobile and traditional learners.

6

Future Directions

This study indicates that use of mobile devices to access learning resources is widespread among respondents. Nevertheless, educators have an imperative to continue to provide learning materials that can be accessed by students with various types of technology, not only mobile devices. This study also indicates that, in the absence of policy surrounding m-learning, educators must work to ensure they use engaging and appropriate content delivery strategies. Most respondents in the study used multiple resources in tandem with one another and found each useful for different purposes. Indeed, the granular approach to content delivery that has emerged organically in practice – providing readings, a podcast, lecture notes, and other materials to cover a topic – finds favor among the respondents and in the literature (see, e.g., de Marcos et al. 2010). The authors believe that future investigation is merited in areas such as whether students use mobile phones to contribute to discussion forums and whether students

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use multiple resources to access learning materials. The findings also highlight the need to ensure that respondents understand that their responses are anonymous and not related to a course evaluation. Follow-up surveys with students on the same programs in future years will enable us to track whether dependence on mobile delivery of learning materials is increasing, as implied anecdotally and in the literature.

7

Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Design of Mobile Teaching and Learning in Higher Education: An Introduction ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts ▶ M-Learning: Visible Approach for Invisible World

References Betts, Kristen, and William Lynch. 2009. Online education: Meeting educational and workforce needs through flexible and quality degree programs. iJournal: Insight into Student Services 24. http://ijournalccc.com/articles/issue_24/betts-lynch.html Chen, Baiyun, and Aimee Denoyelles. 2013. Exploring students’ mobile learning practices in higher education. http://www.educause.edu/ero/article/exploring-students-mobile-learning-prac tices-higher-education. Accessed 8 June 2014. Cho, Wooje, Yoonhyuk Jung, and Jin-Hyouk Im. 2014. Students’ evaluation of learning management systems in the personal computer and smartphone computing environments. International Journal of Mobile Communications 12(2): 142–159. Darmody, Merike, and Emer Smyth. 2008. Full-time students: Term-time employment among higher education students in Ireland. Journal of Education and Work 21(4): 349–362. de Marcos, Luis, José Ramón Hilera, Roberto Barchino, Loudes Jiménez, José Javier Martínez, José Antonio Gutiérrez, José Maria Gutiérrez, and Salvador Otón. 2010. An experiment for improving students performance in secondary and tertiary education by means of m-learning autoassessment. Computers and Education 55(3): 1069–1079. Evans, Chris. 2008. The effectiveness of m-learning in the form of podcast revision lectures in higher education. Computers and Education 50(2): 491–498. Fan, Weimiao, and Zheng Yan. 2010. Factors affecting response rates of the web survey: A systematic review. Computers in Human Behavior 26(2): 132–139. Gartner. 2014. Gartner says worldwide PC shipments in the First quarter of 2014 declined 1.7 percent. http://www.gartner.com/newsroom/id/2705117. Accessed 17 July 2014. Geith, Christine, and Karen Vignare. 2008. Access to education with online learning and open educational resources: Can they close the gap? Journal of Asynchronous Learning Networks 12 (1): 1–22. Hargreaves, Andy, and Dennis Shirley. 2011. The far side of educational reform. Report commissioned by the Canadian Teachers’ Federation. http://www.ctf-fce.ca/Research-Library/Report_ EducationReform2012_EN_web.pdf. Accessed 17 July 2014. Hew, Khe-Foon. 2013. Use of web 2.0 technologies in k-12 and higher education: The search for evidence-based practice. Educational Research Review 9: 47–64. Higher Education Authority (HEA). 2013. Equal access: Access to higher education for all. http:// www.hea.ie/en/news/equal-access-leaflet. Accessed 17 July 2014.

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Hung, Jui-Long, and Ke. Zhang. 2011. Examining mobile learning trends 2003–2008: A categorical meta-trend analysis using text mining techniques. Journal of Computing in Higher Education 24(1): 1–17. International Data Corporation (IDC). 2014. IDC expects PC shipments to fall by 6 % in 2014 and decline through 2018. http://www.idc.com/getdoc.jsp?containerId=prUS24700314. Accessed 17 July 2014. JISC. 2013. “Upwardly mobile,” Online, Available: http://upwardlymobile.jisctechdis.ac.uk/. Accessed 17 July 2014. Kearney, Mathew, Sandra Schuck, Kevin Burden, and Peter Aubusson. 2012. Viewing mobile learning from a pedagogical perspective. Research in Learning Technology 20: 14406. https://doi.org/10.3402/rlt.v20i0/14406. Lee, Mark J.W., and Anthony Chan. 2007. Pervasive, lifestyle-integrated mobile learning for distance learners: An analysis and unexpected results from a podcasting study. Open Learning 22(3): 201–218. MacKeogh, Kay, and Seamus Fox. 2008. Opening access to higher education to all? What motivates academic staff in traditional universities to adopt e-learning? In European Distance & eLearning Network 5th research conference: researching and promoting access to education and training, Paris, 20–22 Oct 2008. http://doras.dcu.ie/2099/1/eden_2008.pdf. Accessed 17 July 2014. Melhuish, Karen, and Gary Falloon. 2010. Looking to the future: M-learning with the iPad. Computers in New Zealand Schools 22(3): 1–16. Müller, Hendrik, Aaron Sedley, and Elizabeth Ferrall-Nunge. 2014. Survey research in HCI. Ways of knowing in HCI. In Ways of knowing in HCI, ed. Judith Olson and Wendy Kellogg, 229–266. New York: Springer. Pachler, Norbert, Ben Bachmair, and John Cook. 2009. Mobile learning: Structures, agency, practices. New York: Springer. Sakai Project. 2014. Features: Sakai. http://sakaiproject.org/features. Accessed 17 July 2014. Santos, Patricia, Mara Balestrini, Valeria Righi, Josep Bla, and Davinia Hernández-Leo. 2013. Not interested in ICT? A case study to explore how a meaningful m-learning activity fosters engagement among older users. In Scaling up learning for sustained impact, 328–342. Berlin/ Heidelberg: Springer. Traxler, John. 2010a. Students and mobile devices. In Research in learning technology, North America. http://www.researchinlearningtechnology.net/index.php/rlt/article/view/10759. Accessed 30 June 2014. Traxler, John. 2010b. Will student devices deliver innovation, inclusion and transformation? Journal of the Research Centre for Educational Technologies 6(1):3–15. UNESCO. 2013. Policy guidelines for mobile learning. http://unesdoc.unesco.org/images/0021/ 002196/219641e.pdf?utm_source=Mobile+Learning+Week+2013_v3_CfP&utm_campaign= 8885b82361-UNESCO_Mobile_Learning3_28_2013&utm_medium=email. Accessed 17 July 2014. Wohlsen, Marcus. 2010. The PC’s death might also mean the web’s demise. Wired Magazine. http:// www.wired.com/2014/01/death-pc-also-mean-end-web/. Accessed 17 July 2014. World Wide Web Consortium (W3C). 2013. Research report on mobile web accessibility. http:// www.w3.org/WAI/RD/2012/mobile/note/ED-mobile. Accessed 17 July 2014.

Enhancing Student Learning Experience with Practical Big Data Analytics Techniques

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Eric P. Jiang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Course Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Major Topics Covered . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Assignments and Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 A Student Lecture Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Final Research Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Unique International Experience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

With the enormous growing volumes and varieties of consumer data, generated by various desktop, mobile, and Internet of Things applications, e-commerce, and other resources, and the recent advances of computational processing and data storage technologies, big data analytics has become an increasingly important tool of transforming large quantities of digital data into meaningful insight and decisions (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). The concept of big data has been around for decades, but it has only become a hot buzzword in the last few years, and its broad applications nowadays have been enthusiastically embraced by financial service providers, retailers, insurers, manufacturers, healthcare organizations, universities, and other enterprises. To meet the great demand for data scientists and engineers from almost every sector of E. P. Jiang (*) Department of Computer Science, Shiley Marcos School of Engineering, University of San Diego, San Diego, CA, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_116

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industry, business, and government, several universities have recently started graduate programs in data science or data analytics. However, the number of undergraduate programs that have integrated big data analytics courses into their curricula still remains very small. In this chapter, the author describes the design, implementation, and evaluation of two data analytics courses, Introduction to Data Mining and Introduction to Artificial Neural Networks, which have been developed and included in the undergraduate computer science program at the University of San Diego (USD). Since the spring of 2011, both courses have been offered as upper-division electives on a regular basis, and it has been a very successful learning experience for both the instructor and the students. The courses include, in addition to the coverage on key data analytics concepts, principles, and applications, a unique student lecture series, programming projects, and research activities to engage students in active learning. The author has also recently been offering the data mining course as a study abroad program in China, integrated with additional guest lectures by data scientists from the host institutions and field trips to visit top information technology firms in the host country. The author’s experience has shown that big data analytics can be successfully taught at the undergraduate level, and in fact, students enrolled in the courses have learned a great deal of data analytics techniques and have been able to apply them to solve many real-world problems.

1

Introduction

Big data analytics is the process of analyzing and identifying hidden patterns embedded in large amounts of data by using various methodologies from multiple areas such as machine learning, pattern recognition, artificial intelligence, and statistical theories and principles. With the rapid proliferation of the Internet, the pervasive use of mobile devices and e-commerce services, and the advances of computing and data storage technology, big data analytics has become an increasingly important tool of transforming reams of digital data into meaningful predictions and decisions, and, just over the past decade or so, it has widely been applied to many areas ranging from business and finance, healthcare, and telecommunication, to science and engineering, to defense and higher education. To meet the urgent and great demand for data scientists and engineers from almost every sector of industry, business, and government, several universities have recently started their graduate programs in data science or data analytics. However, the number of undergraduate programs that have integrated big data analytics courses into their curricula still remains very small. Over the recent years, the author has developed two big data analytics courses, namely, Introduction to Data Mining and Introduction to Artificial Neural Networks, as undergraduate upper-division computer science electives at the University of San Diego, and, more specifically, he offered the artificial neural networks course to the

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program for the first time back in the fall of 2003 and the data mining course in the spring of 2011, respectively. A preliminary overview of developing the latter course was reported in Jiang (2016). Although during the course development process the author has encountered a number of challenges, this particular curricular development work has been a very rewarding experience. There were several key motivations for proposing and developing the big data analytics courses. First, as aforementioned, data mining has become an increasingly important interdisciplinary field of computer science, and it has been broadly used in so many areas in business and society, as both the quantity and variety of data from various resources have been accumulated at an exponentially growing rate and the tremendous number-crunching power of modern computers and the affordable data storage have become a reality (see ▶ Chap. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”). As one of the most promising machine learning paradigms and data analytics tools, artificial neural networks aim to model information processing and storing forms observed in human brains and have demonstrated their great potential to learn very complicated patterns from reams of data. In fact, neural networks systems with multiple hidden layers represent the current state-of-the-art deep learning technology in the areas that include image identification, speech recognition, and language translation. Both general data mining technology and neural networks as a specific machine learning approach have been the important areas of active research and development, and they have also been among the top fields of employment opportunities. The courses that present big data analytics concepts, principles, and applications should help prepare computer science graduates to be succeeded in their continuing studies in graduate programs such as data science, artificial intelligence, and bioinformatics or in pursuing a professional career in data analytics or other related fields. Second, since big data analytics has been serving as a primary tool of transforming data into knowledge to help make meaningful predictions and decisions and delivering solutions to many real-world problems, integrating data analytics courses into a computer science program should help promote undergraduate student research. There are so many data-driven problems surrounding us today that can be formulated into appropriate undergraduate research projects, which can be included in a computer science upper-division class, in an independent study, or as a summer student research project. In fact, over the past few years, the author has worked with more than 40 students in various research projects in information retrieval and filtering, off-topic information search, neural networks, and Web link analysis and mining. Some of the projects have also led to research presentations at professional conferences and publications at computer science journals (e.g., Davis and Jiang 2007). It should be noted that such projects usually require the participated students to have an adequate background in data analytics concepts, principles, and skills, and the data analytics courses can help fill the needed background gap. Furthermore, USD’s computer science program nowadays requires all graduating seniors to do a capstone project, and having the data analytics courses offered on a regular basis in the program, the students can choose to take one of them or both courses if they are interested in the area and plan/do a data analytic-related senior project.

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Finally, a well-designed data analytics course could also provide students with a good integration opportunity where they can reflect and apply what they have learned from other courses, such as calculus, data structures, algorithms, and database management, in learning data analytics algorithms. For instance, the students in the neural networks class should learn how to use the chain rule from differential calculus to devise the popular steepest descent methods for the delta learning rule used in pattern classification and association and to formulate the underlying core learning algorithm for the backpropagation networks. For the data mining course, when discussing the general market basket transactions or association analysis, the students would be able to apply the knowledge they have learned from algorithm complexity analysis to help understand why the number of candidate itemsets, used in association rule mining algorithms, needs to be reduced. Along the same lines, the students could also use their data structure knowledge to appreciate the idea of partitioning and storing candidate itemsets in some efficient data structures such as a hash tree. Just like developing any other new courses, the author encountered a few challenges in planning the undergraduate data analytics courses, in particular for a small program and also for a student body that has quite diverse backgrounds. The primary goals he planned to achieve were (1) to create practically useful courses to introduce students to the big data analytics field as well as its broad applications and (2) to provide students with the opportunities where they can apply and reinforce the academic knowledge and skills they have learned elsewhere. After some extensive curricular research and literature review, the author developed course objectives for both courses. For the data mining course, they are as follows: • Explain fundamental concepts and techniques of data mining. • Identify a broad range of data mining applications in business, science, and engineering. • Develop a foundation of problem solving through data analytics and data modeling. • Develop skills for using modern data mining software and techniques to solve practical problems in a variety of disciplines. • Gain experience doing independent study and research. • Explain the importance of privacy preserving data mining and the professional and ethical responsibilities of a (data mining) practitioner. For the neural networks course, the course objectives are: • Describe the connection between biological and artificial neural networks. • Identify a broad range of neural networks applications in business, science, and engineering. • Explain and implement the architectures and learning algorithms of standard neural networks. • Discuss the main factors involved in achieving both good training and generalization performance in neural networks. • Evaluate the practical considerations in applying neural networks to real-world problems.

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Since USD’s computer science program is relatively small, the author needed to set a reasonable but somewhat marginal prerequisite for the courses in order to have enough students enrolled in the courses. Traditionally, an artificial neural networks class would require the enrolled students to have some background in vector calculus and linear algebra, while a data mining class would require some knowledge of probability and statistics. But unfortunately, these requirements might not be practical due to program size. As a compromise, the author decided to have a minimal prerequisite for both courses, and, as a remedy, the instructor needs to integrate some required background material into class lectures as a way to support those students who have not yet exposed of the material. For both data analytics courses, the author placed the data structure and algorithm analysis course and the integral calculus course; both are typically completed by USD computer science students during their sophomore year, as the prerequisite. When the author offered his first neural networks class for the program in the fall of 2003, there were 11 computer science majors enrolled in the class. When he offered his first data mining class in the spring of 2011, there were also 11 students registered for it, and, among them, there were 8 majors, 2 minors, and 1 foreign exchange computer science student from Argentina. Over the years, the enrollment numbers of these two courses have been varied, and, in general, they have been pretty proportional to the student headcounts of the program. However, there seems to be an enrollment uptrend for the courses in recent years, and, for instance, there were 20 students enrolled in the neural networks class in the fall of 2015. Selecting good textbooks for the courses was another challenge the author faced in the course development process. The author had searched and reviewed a good number of available books in the areas, but unfortunately most of them were not suitable for the proposed courses. Specifically, they either targeted toward graduate students, scientists, or practitioners and required a strong background in mathematics or were written just for a general or nontechnical audience such as business managers and analysts and simply did not contain an adequate amount of technical content for the courses. This was especially true for books in artificial neural networks. After careful selection, the author settled on the book written by Fausett (1994) for the neural networks course. Relatively speaking, the book offers a gentle introduction to artificial neural networks, and it covers fundamental ideas, architectures, and algorithms of multiple popularly used neural networks. As far as the author knows, it is still a popular textbook for an academic undergraduate course in this area due to its relative accessibility to undergraduate students. In addition to the Fausett’s book as the required textbook, a few reference books have been included in the course syllabus, and the latest research and development and products in artificial neural networks have also been integrated into the course lectures. For the data mining course, the author decided to use the book written by Tan et al. (2006). This book has a modest prerequisite in statistics or mathematics, and it also provides a comprehensive introduction to data mining. The major chapters on classification, association analysis, and clustering of the book are self-contained, and the order to be covered is also quite flexible. In addition, the exercises at the end of its chapters are handy and can be used as student homework assignments. Of course, the author has been continuing to search and review latest published books in the big data analytics area and may adopt adequate ones for the courses.

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Related Work

Over the past one and a half decade, there are only a few research papers on developing data analytics, machine learning, and artificial intelligence courses for undergraduate students that have been reported in literature. A data analytics course based on the Weka data mining package and the Weka book (Witten and Frank 2005) was discussed in Lopez and Ludwig (2001), and the course emphasized on hands-on experience with various data mining algorithms provided by Weka. An NSF-funded project that developed a set of hands-on semester-long student assignments for an introductory artificial intelligence course was outlined in Russell et al. (2005). Another interesting data mining course for undergraduates was discussed in Musicant (2006), and it used a collection of data mining research publications as the primary course reading material. It appears that one primary advantage of this approach would be to help students gain better understanding of data mining research and the intricacies of data mining algorithms. But the strategy may or may not work well for a student body with considerably diverse backgrounds. There are also some other papers that proposed data analytics or artificial intelligence courses for both undergraduate and graduate students (Sequer 2007; Chawla 2005; Venayagamoorthy 2005). These courses were designed to adequately accommodate and balance the needs and backgrounds of two different student groups. The big data analytics courses, artificial neural networks, and data mining, described in this chapter, have focused on motivating and engaging students in learning data analytics and machine learning methodologies and applications. The courses have multiple learning components. By encouraging and requiring students to read relevant course material and research papers, present their findings in a student lecture series, implement some of the important data analytics and machine learning algorithms, learn many real-world big data analytics applications by talking with data scientists and practitioners and visiting top information technology firms that develop advanced data science products and services, and complete a research project, the author believes that, through all of these, the students have a good understanding of big data analytics ideas, approaches, and applications and are able to identify data analytics problems and apply practical data mining or machine learning algorithms to solve them. This has been reflected by student work in course assignments, their answers to exam questions, and, in particular, their accomplishments in the final research project.

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Course Structure

Both the neural networks course and the data mining course that the author has developed are three-unit computer science upper-division electives in the USD computer science program. The courses have typical class lectures on key ideas, algorithms, and applications of artificial neural networks or data mining, homework and programming assignments, in-class quizzes, a midterm exam, and a final research project. In addition, the data mining class includes a semester-long student

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lecture series on some selected supplemental material. Other course learning activities include invited guest lectures by data scientists and practitioners and field trips to visit top information technology companies to learn their latest development and products in data science, machine learning, and artificial intelligence.

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Major Topics Covered

In this subsection, the major lecture topics covered in the artificial neural networks class and the data mining class are described, respectively.

3.1.1 Artificial Neural Networks Artificial neural networks are computer systems that are inspired by the structure and functional aspects of biological neural systems (brains). The systems learn to perform computational tasks by large amounts of data and represent today’s best performing artificial intelligence technology in many areas, from autonomous driving and flying and image identification, to speech recognition, and to language translation. More specifically, artificial neural networks are a collection of simple information processing units or neurons that are regularly and densely interconnected and arranged into layers, and the learning process is essentially an iterative loop that manages to pass the informational signals between connected neurons and can either strengthen or weaken the connections, represented by changes on connecting weights. With recent development of the concept of deep learning (Goodfellow et al. 2016), which is typically performed by an artificial neural networks system with multiple hidden layers, and recent remarkable successes of deep learning in computer vision, speech recognition, and human games, there is a resurgent interest in learning and using artificial neural networks to solve many complex tasks such as medical diagnostics, natural language processing, drug discovery, and bioinformatics and to address a number of other significant social and business problems. For this introductory class, the instructor decided to focus on fundamental neural networks for pattern classification, pattern association, and also the networks based on competition. For each of the network types, its primary architectures, features, learning algorithms, and applications are covered. Overview of Machine Learning, Artificial Intelligence, and Applications For the course, an overview of machine learning, artificial intelligence, and their latest development and applications is provided. It is followed by an introduction to major machine learning paradigms: supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. The deep learning concept, approaches, and many latest successful applications are also introduced and discussed. In addition to a number of fundamental concepts, the course focuses on the broad applications of machine learning to stimulate student interest in this important subfield of computer science.

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Introduction to Artificial Neural Networks In this part, artificial neural networks are introduced with a number of interesting questions being raised and discussed. The questions include: What are artificial neural networks? What is the relationship between artificial neural networks and biological neural networks? Why neural networks and why now? Where are neural networks being used? In terms of approach, capability, and applicability, neural networks are also compared with conventional software systems. It seems that conventional software industry has significantly slowed its growth rate, while the development of machine learning software has still been growing very rapidly. The brief but fascinating history of neural networks is also covered. Finally, a review of vector calculus and linear algebra, which serve as the perquisites for learning many neural networks algorithms, is provided. Neural Networks for Pattern Classification In this first major chapter on neural networks learning systems, several simple networks for pattern classification tasks are discussed, and they include the Hebb net, the Perceptron net, the Adaline net, and variants. The instructor uses a number of simple examples to demonstrate stepwise how each of the neural networks could take a sample of data as input, how to apply a learning algorithm to adjust connecting weights between neurons, and then how to generate final classification outcomes. When introducing the Perceptron networks, the instructor also illustrates, by integrating multiple learning processes that human beings often use in real life to learn a new thing, how the Perceptron learning algorithm can be derived very naturally from the Hebb rule. Neural Networks for Pattern Association The next chapter covered is neural networks used for pattern association. Learning itself is closely related to patterns association, and, to a certain extent, it would be considered a process of forming association between related patterns. In this chapter, several auto-associative networks are discussed where each output pattern is the same as the corresponding input pattern with which it is associated, and then the well-known Hopfield network system and applications are covered in detail. The instructor also discusses several hetero-associative networks where the associated output pattern is different from the input pattern and covers in detail the BAM (bidirectional associative memory) networks and applications. Neural Networks Based on Competition Neural networks for pattern classification and pattern association are learning models that effectively perform a mapping from a given input space to a related output space. They are supervised machine learning systems. But in the real world, there are many other types of problems where training samples contain only input values and the embedded patterns and knowledge within the input data need to be discovered. In this chapter, several related unsupervised learning paradigms are discussed, namely, clustering, vector quantization, and general competitive neural networks using learning rules based on dot product and the Euclidean distance.

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Some other neural networks in this area as well as their applications are also covered that include the Max net, the Mexican Hat net, the Hamming net, the Kohonen SOM (self-organizing map) net, the learning vector quantization net, and the counterpropagation nets. Backpropagation Neural Networks and Other Learning Systems The backpropagation network system is one of the most powerful and most widely used artificial neural networks, and it has many successful applications. Its core idea is to achieve a good balance between the memorization (the ability to respond correctly to the training patterns) and generalization (the ability to respond reasonably to the new input data that are similar but not identical to the training samples) abilities of the system. The backpropagation networks, their variations, and practical implementation issues as well as their popular applications are discussed in detail. When time permits, some fixed-weight neural networks are also covered that can be used to solve many interesting constrained optimization problems such as the famous traveling salesman problem.

3.1.2 Data Mining Data mining or data analytics is a very broad multidisciplinary field that straddles several areas of computer science, and hence it has a very rich collection of learning algorithms. For this introductory data mining course, a comprehensive coverage of data mining topics is designed that include general data processing, manipulation and storing, data mining algorithms for different types of problems, and many realworld applications. Overview of Data Mining, Data, and Data Processing The course begins with an overview of big data analytics concepts, tasks, challenges, and applications, with an emphasis on the importance and relevance of data mining to many practical problems in business, finance, healthcare, science, and engineering. Then, the latest development and applications of big data analytics and a number of future social and business problems that can potentially be addressed by data analytics technology are discussed. This comprehensive introduction aims to motivate students to learn the course contents and to help them connect many potential applications with individual data-based learning approaches that are to be covered later in the class. In addition, the course also covers the concepts and properties of data, as well as general procedures for processing, manipulating, analyzing, and visualizing data.

3.1.3 Data Mining for Classification Classification, a task of assigning objects to one of the predefined categories, is a pervasive problem that encompasses many diverse applications. For this data mining domain, decision tree induction algorithms, nearest neighbor classifiers, and the naïve Bayes classifier are discussed in detail. The well-known Perceptron neural networks and support vector machines are also introduced. The course typically spends a great deal of time at discussing the construction of decision trees that

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includes several impurity measures for selecting the best split of data in a tree node. This topic is quite appropriate for undergraduate students with a background of tree data structures. The naïve Bayes approach is another classification method covered extensively in the class. It is a probabilistic learning model that can be implemented very efficiently with a linear complexity. It should be pointed out that most of the students that have completed this data mining class didn’t know much about probability and never heard of the Bayes theorem beforehand. In order to present the naïve Bayes approach in an accessible way to students, the instructor first reviews fundamental probability concepts and rules and then gently introduces the famous Bayes theorem. As it is the case with the naïve Bayes classifier, the naïve theorem has many other practical applications. Hence, the time spent for covering this particular probabilistic modeling tool is worthwhile to many computer science students as this could be the only opportunity for them to learn one of the most widely used probability theorems.

3.1.4 Data Mining for Clustering Clustering or cluster analysis partitions data into inherent and meaningful groups and has been widely applied in biology, business, psychology, medicine, climate research, and other areas. The course covers clustering algorithms of both partitional and hierarchical clustering with an emphasis on the former type. That includes the most famous k-means algorithm and its several variants such as bisecting k-means, basic agglomerative hierarchical clustering algorithms, and a representative densitybased algorithm (DBSCAN). 3.1.5 Data Mining for Association Analysis Association analysis, also known as market basket analysis, is a methodology for discovering interesting relationships that are usually hidden in large transactional datasets. As an introduction, the instructor discusses a few examples of association rules and also a variety of business-related applications in marketing promotions, inventory management, and customer relationship management (CRM). The primary association analysis algorithm covered for the course is the most popular Apriori algorithm. This fundamental association analysis approach is also well connected to several standard data structures (e.g., trees, hashing tables), and a good understanding of the Apriori approach also requires some basic knowledge of algorithm complexity analysis. 3.1.6 Data Mining for Anomaly Detection The primary goal of anomaly (or outlier) detection is to find data objects that are different from most other ones. It can be used in many areas including fraud detection in finance, intrusion detection in network system security, healthcare management, medical diagnosis, and drug development. There is a good variety of anomaly detection approaches, and for the course, an overview of several popular anomaly detection approaches that are statistics based, proximity based, and model based is provided.

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Assignments and Tests

To help students better understand course material, there are several course assignments: homework, reading, and programming projects. Homework problems that are closely tied to data analytics concepts, procedures, and learning algorithms are assigned on a regular basis during a semester. All the homework assignments were collected and graded by the instructor. Reading assignments are regularly announced and assigned in class every week. Programming projects that implement some of neural networks or data mining algorithms are also required, and they are designed to help students learn the intricacies and functionalities of the algorithms. For the data mining class, the instructor usually assigns a set of programming projects that include the k-nearest neighbor classifier and the bisecting k-means clustering algorithm. The projects are required to apply some real-world datasets from the popular UCI Machine Learning Repository (UCI MLR) for model training and testing. For the neural networks class, the assigned programming projects typically include the Perceptron net, the Hopfield net, and the counter-propagation neural net. For all programming projects in the class, students are also expected to perform some extensive data-based experiments. For both classes, students could use any modern programming languages of their choice to do the projects. Several selected research papers have been used in the courses as additional reading assignments in order to help students expose to data analytics and machine learning research. For instance, a paper that applies neural networks and association rules to classify medical images for tumor detection (Antonie et al. 2001) was assigned for both courses as a supplemental reading material. The paper is quite readable to undergraduate students who have gone through some basic training in data analytics. An additional reading assignment designed for the data mining class is a supplemental book, Super Crunchers, and will be described in detail in the next subsection. Like many other computer science courses, a number of in-class quizzes and one midterm exam are arranged that intend to evaluate student’s learning on covered course material, in particular student knowledge of fundamental ideas and structures of various data analytics and machine learning algorithms.

3.3

A Student Lecture Series

The author has developed a unique student lecture series for the data mining course. It was aiming to achieve three goals: (1) stimulating student learning interest, (2) sharing data analytics ideas and applications with peers, and (3) motivating students to learn course contents. For the series, the course has been using a New York Times bestseller, Super Crunchers (Ayres 2008), as the primary reading material. In the beginning of the semester, the instructor partitions the book chapters among the enrolled students with one or two students being assigned to a chapter, depending upon the length of the coverage. Each student or each student team is then expected to be very familiar with his or their chapter’s coverage, by reading the

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chapter and researching on their own to acquire additional relevant information (through online documents, papers and videos, etc.), and to prepare and present a formal mini lecture on the topics covered in the assigned chapter to the class. The course usually has one student lecture session each week, and each session takes about 15 min, including a quick Q&A session. Super Crunchers is a great book about data mining and statistical analysis. Although the book does not cover complex data mining techniques, it successfully introduces the basic ideas behind data mining for a general audience. In particular, the book presents many small yet very fascinating real stories and examples about data crunching, and it beautifully demonstrates how data analytics can really help people make intelligent and accurate decisions and perform various tasks both efficiently and effectively. This student lecture series, specifically designed for the data mining course, has been a very successful active learning experience for all students, and their feedback on this learning component has been very positive. By studying and researching some supplemental course material on their own and presenting their findings to class as guest speakers, students are expected to develop a broad interest in learning data analytics technology and a deep understanding of many real-world data analytics applications. In addition, it offers students a unique opportunity of practicing their technical communication skills. The author plans to adopt the student lecture series in the neural networks class as well in the near future.

3.4

Final Research Project

In lieu of a final exam, a final research project is required for both data mining and neural network classes. For the project, students propose to either develop a data analytical tool, solve a real-world problem using data mining or neural networks technology, implement an interested learning algorithm from a recently published research paper and demonstrate its effectiveness, or participate in a relevant big data analytics competition and formulate a final submitted solution using any machine learning approaches. Students may choose to do it as solo project or as a team project of two members. Since these courses are counted as computer science upper-division electives, some programming implementation is highly expected in this final project, and it can be done in any programming languages of student choice. In addition, students are required to present the project to the class at the end of the semester. This final research project is a very important learning component to students. First, it serves as an integration module for the courses. Students will design, implement, and complete a significant software project, and students are expected to apply the knowledge and skills they have learned from the respective class and integrate them to perform various tasks toward the completion of a project. Second, this requirement serves as a valuable research activity where students can gain better understanding of the course content, hands-on research experience, and deeper insights into the challenges faced by data scientists and machine learning

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professionals. Finally, because of the project presentation requirement, it also provides a great opportunity to students for learning from each other about the latest development and advances in data analytics research and applications that may or may not have been covered in class lectures. Below are some of the student’s proposed and completed final research projects from the first neural networks class offered by the author back in the fall of 2003: Facial Recognition Using Neural Networks Breast Cancer Diagnosis – An Application of Neural Networks Speech Recognition Based on Neural Networks Neural Networks to Predict 3-D Protein Structures The student’s proposed and completed final research projects from the first data mining class offered by the author in the spring of 2011 include: Multidimensional Scaling for Data Visualization Participation in Data Mining Cup 2011 – Developing an E-commerce Recommendation System Mining Web Navigation Patterns with a Path Traversal Graph Improved Probabilistic C-Means Clustering Algorithms Spam Email Detection and Text Classification Data Mining for Public Education Funding Decisions It should be noted that two students from the spring of 2011 data mining class decided to do their final research project by participating in the Data Mining Cup (DMC) competition 2011 (DMC 2011). DMC is an annual event that aims to promote intelligent big data analytics, and it has attracted college student teams from many countries in the world. The challenge of that particular year was to develop an efficient and accurate product recommendation system, based on a dataset over 9.5 million customer transactional records that is capable of predicting the products customers would likely be interested in. For the given task, the two students were able to successfully apply their learned knowledge and skills in association analysis, perform numerous number-crunching procedures, and finally achieved the second place in this international contest. The students also won a monetary award and were invited to Germany later for a winner presentation in the summer of 2011.

4

Unique International Experience

In the last few years, the author has also started to offer the data mining course in a faculty-led study abroad program in China. More specifically, the course has been offered to all USD computer science students in a summer, and typically it lasts about 3 weeks. It has become a popular study abroad course among computer

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science majors, and the course has offered them a fine opportunity of gaining academic experience within a unique international learning environment. Over the past two decades, China has successfully produced a large number of qualified scientists and engineers and has also been one the most popular outsourcing locations for many top US high-tech firms. Silicon Valley has long been the world’s technology capital. But China’s tech industry, particularly in mobile applications, has in some way pulled ahead very recently, and Western companies such Facebook and Uber are looking there for new ideas. Already, for instance, more people in China use mobile devices to watch videos and find dates than anywhere else in the world, and mobile payments in China have surpassed those in the USA in 2015 (New York Times 2016). It is relevant to teach a data mining course in China. China has been investing heavily in universities and research institutions, and according to an article in UK Telegraph (2010), China will likely be producing more scientific research papers than any other country by 2020. Over the last decade, the growth in big data analytics, machine learning, and artificial intelligence technology in China has been particularly strong in terms of research publications and applications in economic development (Cheng et al. 2007). For this study abroad version of the course, in addition to the regular course contents, a number of academic activities have been arranged that include guest lectures on data analytics technology and applications in China, given by some experts from universities or high-tech firms in China. The activities also include visits to a top university in China, for meeting with Chinese computer science students to learn more about China’s higher education system in general and science and engineering education in particular, and visits to one of the top information technology leaders in China such as Baidu (which is often called the Google of China and a pioneer in artificial intelligence and other related fields), for learning the latest big data analytics-based products and services they have developed and the potential of data analytics to reshape the world in which we all live and work. Another noticeable advantage for US students taking a study abroad program is to learn potential career opportunities offered in the host country. This is particularly meaningful to those studying in computer science or related disciplines as technological innovations and development have gone beyond geographical boundaries. For the study abroad data mining course, an additional meeting with human resources executives from a technology leading firm has been arranged by the instructor so the participated students can learn job opportunities offered by the firm, both in China and at its overseas research and development centers in the USA, and the details as to how to apply for them.

5

Future Direction

The author has presented his academic experience of developing two big data analytics courses, and data mining, for undergraduate students at the University of San Diego. Since the fall of 2003 and the spring of 2011, respectively, the artificial

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neural networks course and the data mining course have been offered multiple times as computer science upper-division electives in the computer science program. The courses have several unique features. They combine lectures on key big data analytics concepts, principles, algorithms, and applications, a student lecture series (for the data mining course), programming projects, research activities, and additional international learning experience (for the data mining course) to engage students in active learning. The experience has shown that, with carefully planned learning outcomes, course material, and learning activities, data mining and artificial neural networks can be taught successfully at the undergraduate level. In fact, students can learn a great deal of big data analytics techniques and skills from these courses and also are capable of applying them to solve many real-world problems. All of these have been shown by student achievements in various course assignments and especially in their final course research project. The participated students also have found these courses very interesting and practically useful as described by the comments from three students from a recent neural networks class offered in the fall of 2017: “Most useful CS class.” “To realize what the neural networks could actually do was pretty cool.” “I have really enjoyed learning all of our different net architectures, from perceptron, to Hopfield to back propagation. I feel I have learned skills this semester that will really benefit me in my future career.” As the number of jobs in data science, machine learning, artificial intelligence, and other related fields has been continuing to grow a remarkably fast pace, developing some appropriate big data analytics courses and integrating them into computer science undergraduate programs can definitely be beneficial to computer science graduates in terms of preparing them to have the necessary knowledge and practical skills in data science for many great career opportunities and for solving many exciting yet very challenging data intensive social and business problems (see also ▶ Chaps. 77, “Augmented Reality in Education” and ▶ 79, “VR and AR for Future Education”).

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Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ VR and AR for Future Education

References Antonie M., O. Zaiane, and A. Coman. 2001. Application of data mining techniques for medical image classification. Paper presented at the 2nd International Workshop on Multimedia Data Mining. Ayres, I. 2008. Super crunchers. New York: Random House. Chawla, N. 2005. Teaching data mining by coalescing theory and applications. Paper presented at the 35th ASEE/IEEE Frontiers in Education Conference.

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Cheng, S., et al. 2007. Research on data mining and knowledge management and its applications in Chinese economic development: Significance and trend. International Journal of Information Technology & Decision Making 5 (4): 585–596. Davis, D., and P.E. Jiang. 2007. Exploring content and linkage structures for searching relevant web pages. Lecture Notes in Artificial Intelligence 4632: 15–22. DMC – Data Mining Cup. 2011. http://www.data-mining-cup.de/en/dmc-competition/ Fausett, L. 1994. Fundamentals of neural networks: Architectures, algorithms and applications. Englewood Cliffs: Prentice Hall. Goodfellow, I., Y. Bengio, and Courville. 2016. Deep learning. Cambridge, MA: MIT Press. Jiang, P.E. 2016. Exploring practical data mining techniques at undergraduate level. International Journal of Computers 1: 78–82. Lopez, D., and L. Ludwig. 2001. Data mining at the undergraduate level. Paper presented at the Midwest Instruction and Computing Symposium, Cedar Falls. Moore, M. 2010. China to lead world scientific research by 2020. The Telegraph. Retrieved from http://www.telegraph.co.uk/news/worldnews/asia/china/7075698/China-to-lead-world-scien tific-research-by-2020.html Mozur, P. 2016. China, not Silicon Valley, is cutting edge in mobile tech. The New York Times. Retrieved from https://www.nytimes.com/2016/08/03/technology/china-mobile-tech-innova tion-silicon-valley.html Musicant, D. 2006. A data mining course for computer science: Primary sources and implementations. Paper presented at the annual conference of Special Interest Group on Computer Science Education. Russell, I., Z. Markov, T. Neller, and S. Coleman. 2005. Enhancing undergraduate AI courses through machine learning projects. Paper presented at the 35th ASEE/IEEE Frontiers in Education Conference, Indianapolis. Sequer, J. 2007. A data mining course for computer science and non-computer science students. Journal of Computer Sciences in Colleges 22 (4): 109–114. Tan, P., M. Steinbach, and V. Kumar. 2006. Introduction to data mining. Boston: Addison Wesley. University of California at Irvine Machine Learning Repository. http://archive.ics.uci.edu/ml/ Venayagamoorthy, G. 2005. Development of a computational intelligence course for undergraduate and graduate students. Paper presented at the Annual Conference of American Society for Engineering Education, Portland. Witten, I., and E. Frank. 2005. Data mining: Practical machine learning tools and techniques. 2nd ed. San Francisco: Morgan Kaufmann.

Part VII VR, AR, and Wearable Technologies in Education

VR, AR, and Wearable Technologies in Education: An Introduction

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Abstract

The primary role of an educator is to create an environment, within a given context, that encourages learner engagement to build connections between what is being learned and their personal experiences. Educators may adopt various tools such as textbooks, computers, handheld devices, and/or other electronic devices to engage with their learners and encourage active learning. However, the choice of learning innovation is very much dependent on the access to the various technologies and their availability to both educators and their learners. It is also true that world-class education and training is not always available everywhere. There has always been a disparity in the level of quality of education and training across different regions of the world, which is why there is a great need for innovative solutions to help reach those deprived areas. Virtual reality (VR) and augmented reality (AR) in education aim to positively affect conventional learning processes. VR and AR introduce new engaging methods of teaching and learning that have the potential of being completely location agnostic and they enable educators to simultaneously reach many learners across the globe using a virtual environment and still be as effective as if they were all in the same physical space. AR can be described as a technology that overlays computer-generated information on to a virtual environment that can be experienced by people. AR is already being used in recent years to enhance learning experiences. However, such AR-based applications require specialized teams with specific skills in software development to create and maintain learning content within AR. The following chapters attempt to Y. Jing (*) Coventry University, Coventry, UK e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_109

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address some of these challenges and introduce new ideas to support educators in better engaging with their learners using cutting-edge technology. In ▶ Chap. 75, “Augmented Reality and 3D Technologies: Mapping Case Studies in Education,” Teresa Cardoso, Teresa Coimbra, and Artur Mateus from the Open University of Portugal introduce a mapping for three-dimensional augmented reality to enhance the teaching content for mathematics in higher education. The authors’ mapping shows that the application of AR to educational situations has benefited from the technological development and in particular for those using mobile devices and m-learning approaches. The authors assessed the mathematical content using tangible (3D printing) and intangible (AR) technologies and found that it can enhance learner engagement and support active learning. This case was especially true for blind students, who were part of the experiments that engaged well with the 3D printed learning materials. In ▶ Chap. 78, “Mobile-Based Virtual Reality: Why and How Does It Support Learning,” Karen Ladendorf, Danielle Schneider, and Ying Xie from Northern Illinois University explain how the use of VR can stimulate the cognitive functions within the brain and how it can activate the long-term memory and by bypassing the working memory learners can learn more quickly, speeding up the learning process. The authors explain the impact of immersive virtual reality has on the brain and body using the theory of hypothetical model of immersive cognition (HMIC) . The authors explain the need for further considerations to be taken into account such as cognitive and physical overload when developing software for VR technologies. The authors provide guidance to instructions and instructional designers when structuring their instructions when embedding VR technologies in their teaching without losing focus on learning. In ▶ Chap. 79, “VR and AR for Future Education,” Ken Kencevski and Yu (Aimee) Zhang from Australia readdress the experimental learning theory, first introduced by David Kolb, and describe how recent advances in AR and VR can help engage students in their learning for the future. The authors explain how the fast pace of technological development and the decreasing cost of telecommunications in recent years pave the way for VR and AR adoption. They explain as more applications are being developed more industries are being influenced which will also encourage educators to new ways of teaching. The authors present the Kolb software, which is not just simply focused on introducing the education sector to VR but instead combines Kolb’s experimental theory in achieving the best results for students. The chapter contains evidence of benefits of merging Kolb theory with technology and gamification as it proves to be beneficial for the learning process. The chapter touches upon what the future holds for AR and VR in learning and teaching and how it will have an impact on the wider society. The chapter also explains some of the negative side effects on user’s health and some of the precautions one should consider before adopting AR and VR technology. In ▶ Chap. 73, “Location and Place: Two Design Dimensions of Augmented Reality in Mobile Technologies,” Apoorva Chauhan, Whitney Lewis, and Breanne K. Litts from Utah State University propose a quadrant-based framework that focuses on AR in learning by introducing “location” and “place” as two key design

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principles for AR mobile learning. The authors present a mobile application for each quadrant to illustrate how the proposed framework informs and contextualizes the designs and developments in mobile technologies. The chapter demonstrates the significance of the two dimensions and their importance in AR applications. The chapter describes how the technology has a place outside of the classroom which can benefit learners. The authors provide evidence to support their claim that AR and mobile experiences are location independent and engage learners with their location, providing the best experience for situated learning or learning that can take place in a social context. In the chapter ▶ “Review of Virtual Reality Hardware Employed in K-20 Science Education,” the authors describe how VR technology can promote learning and enhance the user’s virtual experience using haptic feedback. The chapter includes many examples to support its claims of enhancing learning experiences using VR-assisted technologies. By further improving the immersive experience for learners such as by adding a head-mounted display or a holographic display and/or VRE hardware can enhance user engagement and increase their learning. The chapter describes the use of high fidelity, photorealistic image mimicking interactions to stimulate multiple senses such as sight, touch, and sound to enhance the user’s learning experience. The chapter summarizes some of the benefits of VRE technology and how it can be accessible to a wider audience while supporting and enhancing traditional pedagogical processes in teaching and learning. In ▶ Chap. 76, “Employing Virtual Reality to Teach Face-Based Emotion Recognition to Individuals with Autism Spectrum Disorder,” the authors describe the use of VR technology to provide a modern approach to helping individuals with autism develop their social skills. In particular, the chapter explains how current interventions for Emotion Recognition (ER) can be enhanced using VR technology to provide a virtual experience to stimulate responses from virtual emotional expressions. The chapter refers to the inventors of NimStim who have collected hundreds of pictures of facial expressions and various emotions to help categories and label the data for experimental purposes. The chapter describes some of the challenges in evaluating emotional recognition (ER) for autism spectrum disorder (ASD) and how individuals may respond to emotional stimuli using facial expressions by comparing brain responses as a primary measure. The chapter makes a strong case for exploring emerging technologies such as VR to help aid in providing individuals with ASD with multiple valid social stimuli within a safe environment. The chapter refers to many studies that have used VR to engage their users effectively to help develop their social skills in emotional recognition. In ▶ Chap. 77, “Augmented Reality in Education,” Joseph M. Reilly and Chris Dede from Harvard Graduate School of Education describe how augmented reality can be used to enhance learning and uses examples to illustrate how educators can employ AR as a means to transform their teaching and better engage with their learners more effectively. The chapter highlights how problem-solving activities such as inquiry-based problems can be solved using interactive, dynamic learning experiences. The authors explain the two broad categories in AR are location-based

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and vision-based and how these concepts are implemented within AR. The chapter explains how AR can be used in both formal and informal learning settings and across multiple disciplines. The chapter also describes some of the advantages, challenges, and limitations for implementing the technology in education. The chapter describes AR as an emerging technology and illustrates some of the trends in publications such as the Gartner Hype Cycle for Emerging Technologies. The application of AR technology in teaching is still in its infancy; however, this chapter provides evidence from a case study on how AR technology can positively enhance the learning experience. In ▶ Chap. 71, “Mobile AR Trails and Games for Authentic Language Learning,” Mark Pegrum from The University of Western Australia presents AR learning using mobile-assisted language learning environments and gamification to help engage learners. The chapter explains how many AR learning trials have language and literacy learning skills as the main or auxiliary focus. The chapter describes how to maximize the pedagogical potential of mobile learning by encompassing three levels of mobility, and these traits are found in AR-enabled gamified learning trials. The chapter covers a wide range of ideas and projects that have been able to experiment and gain insightful knowledge in harnessing the benefits of AR technology in adapting pedagogical approaches in teaching and learning languages across the world. The chapter links the advances in the use of AR technology with practices in traditional pedagogy and explains how early research in educational advantages of mobile AR is now beginning to be underpinned empirically. The chapter makes references to Apple and Facebook CEOs, who have endorsed the value of using AR technology. Finally, the chapter makes references to global interests and projects that have recognized the benefits of AR and are putting the technology through its paces in educational settings, especially in learning languages. In ▶ Chap. 74, “Wearable Technologies as a Research Tool for Studying Learning” Jimmy Jaldemark, Sofia Bergström-Eriksson, Hugo von Zeipel, and Anna-Karin Westman from Sweden University describe the use of AR in mobile learning through wearable devices such as superimposing computer-generated information or graphics on a user’s view of the real-world using spy glasses. The chapter touches upon a wide range of topics within teaching and learning and adopting mobile and wearable technology in schools. The chapter demonstrates the growing interest in experimental studies in adopting new technologies to gain support and enhance learning. The chapter mentions some of the advantages and disadvantages of using wearable spy glasses and also explains some of the ethical issues surrounding the use or misuse of the technology. The chapter draws information from recent advances in wearable technology and demonstrates how it can be applied to traditional pedagogical approaches to enhancing learning. The chapter refers to several studies that have experimented with wearable technology such as Norooz et al. (2015) that studied biometric sensing in an elementary school. The chapter also describes the use of spy glasses as a data collection tool and refers to research carried out in Sweden that has experimented with the technology in compulsory school and children at grade nine between the ages of 15 and 16 participated in the study.

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VR, AR, and Wearable Technologies in Education: An Introduction

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In ▶ Chap. 72, “Virtual Reality and Its Applications in Vocational Education and Training,” Zuzana Palkova and Ioannis Hatzilygeroudis from Slovak University of Agriculture in Nitra present three examples of how VR technology is being used to help engage learners and make learning more attractive to the young generation. The chapter explains how some of the key types of VR technologies are being used and in what context – such as head-mounted displays for an immersive learning experience and telepresence using remote sensors and controls such as teleconferencing and virtual worlds where learners can explore a virtual space and interact with objects within it. The chapter uses games such as World of Warcraft to describe how this technology is being used already for pleasure. The chapter continues to explain under the heading “Educational potential of 3D virtual worlds” how 3D virtual worlds offer a new learning delivery channel for experimental and or simulated learning. The chapter presents a range of example of VR technologies being used effectively in vocational education and training. The authors demonstrate how well traditional methods of pedagogical processes can be enhanced through the use of carefully crafted teaching material designed for leveraging the benefits of VR technology. Engagement is a key challenge for educators; VR, AR, and wearable technologies provided an innovative method to address this issue among others. The introduction of AR and VR technologies to education is still relatively new; there are still obstacles such as lack of powerful headset and wearable devices that support VR and AR; the wireless internet bandwidth still hinder the widespread use of VR and AR technology. However, the chapters in this sector have provided many useful, good case studies; it is the author’s belief that VR, AR, and wearable technologies will change the way educators teach and learners engage with new knowledge. The revolution has just started.

References Norooz, L., Mauriello, M.L., Jorgensen, A., McNally, B., and J.E. Froehlich. 2015. BodyVis: A new approach to body learning through wearable sensing and visualization. In Proceedings of the 33rd annual ACM conference on human factors in computing systems, 1025–1034. ACM. CHI 2015, April 18–23 2015, Seoul, Republic of Korea. https://doi.org/10.1145/2702123. 2702299, http://www.cs.umd.edu/~jonf/publications/Norooz_BodyVis-ANewApproachToBody LearningThroughWearableSensingAndVisualization_CHI2015.pdf

Mobile AR Trails and Games for Authentic Language Learning

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Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Levels of Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mobile AR Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mobile AR Learning Around the World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Heritage Trails in Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 TIEs in Hong Kong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Mega Trails in Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Fukuchiyama Castle Rally in Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Today’s proliferation of mobile, and especially smart, devices opens up new educational opportunities. This chapter explores the benefits of pedagogically rich mobile learning (m-learning) designs where the devices, the learners, and the learning experience are all mobile; where the constructs of personalization, collaboration, and authenticity are all foregrounded; and where weak interaction is complemented by strong interaction. Many of the best examples of such designs can be found in mobile augmented reality (AR) learning trails and games. The chapter showcases language and literacy learning on gamified AR learning trails, some of which have a mobile-assisted language learning (MALL) focus, and some of which have a more general learning focus, but all of which incorporate elements of language and literacy education. Following a brief M. Pegrum (*) The Graduate School of Education, The University of Western Australia, Crawley, Perth, WA, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_89

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overview of significant examples from around the world, the chapter focuses on recent trails in Asia, including the Singaporean Heritage Trails, the Hong Kong TIEs (Trails of Integrity and Ethics), the Indonesian Mega Trails, and the Japanese Fukuchiyama Castle Rally. On such trails, students typically learn collaboratively in real-world settings while practicing language, developing digital literacies and twenty-first-century skills, and often exploring culture at the same time. The chapter outlines how these gamified trails are structured to enable students to draw the greatest learning benefits from digitally supported, authentic, situated interactions. It is suggested that successful mobile AR learning designs depend fundamentally on a willingness to view mobile devices not as screens which separate people from the world, but as lenses which connect people with the world and which focus attention on new ways of implementing teaching and learning experiences outside the regular spaces and times of education.

1

Introduction

When the second generation of the web, or Web 2.0, began to emerge around the year 2000, it opened up the possibility of promoting personalized but collaborative learning. A new generation of mobile context-aware technologies has since appeared, building on Web 2.0 but going beyond it and creating opportunities for foregrounding authentic learning in everyday contexts. Contextual learning is shaping up as the next generation of mobile learning (Traxler and Kukulska-Hulme 2016a) and the “successor of [the] Web 2.0 paradigm” (Kinshuk 2015, p. 1). To capitalize on the potential inherent in contextual approaches, it is essential for educators to develop appropriate mobile learning designs. Many of today’s most pedagogically rich designs involve three levels of mobility, pertaining to the devices, the learners, and the learning experience (Pegrum 2014, 2016); they involve a balance between the three constructs of personalization, collaboration, and authenticity (Burden and Kearney 2017; Kearney et al. 2012); and they involve strong interaction alongside weak interaction (Clandfield and Hadfield 2017). Such designs often take the form of gamified mobile AR learning trails, many of which have language and literacy learning either as a main or an auxiliary focus.

2

The Levels of Mobile Learning

At the first level of mobile learning, the devices are mobile, but the learners and the learning experience are not; a typical example might involve students sitting at their desks using tablets to conduct Internet research or engage in app-based exercises (Pegrum 2016). Cost and flexibility benefits notwithstanding, this kind of m-learning amounts to little more than pedagogically traditional e-learning on shrunken screens.

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The iPAC framework, based on the Mobile Pedagogical Framework (Burden and Kearney 2017; Kearney et al. 2012), highlights the three distinctive constructs of personalization, collaboration, and authenticity that can underpin m-learning; with reference to this framework, it can be seen that there is scope for personalization of the technology (through the choice of hardware and the selection of software settings, possibly with scope for further personalization through inbuilt learning analytics) and the learning (through the exercise of a degree of agency and autonomy), but there is typically rather less scope for collaboration (although some online networking may be possible) or authenticity (although online access to authentic materials, or online viewing of real-world scenarios, may also be possible). With reference to Clandfield and Hadfield’s (2017) work on online interaction, it can be seen that there is scope for weak interaction (i.e., where students interact with their devices), but there is typically rather less scope for strong interaction (where students interact, through their devices, with other people), notwithstanding the online networking possibilities mentioned above. At the second level of mobile learning, the devices and the learners are mobile, but the learning experience is not. One type of learning at this level involves students circulating with their devices as they interact with each other – working in groups to share their learning or to engage cooperatively with apps – in an educational space such as a classroom or the grounds of a learning institution. In terms of the iPAC framework, such learning goes beyond personalization to incorporate collaboration between students, but authenticity is typically not as strongly foregrounded. In terms of Clandfield and Hadfield’s online interaction model, it may involve both weak and strong interaction, with the latter often occurring around the devices (that is, offline) as much as through them (that is, online); the possibility of interaction prompted by devices but occurring around instead of through them represents an extension of the original model, but is nonetheless clearly a case of strong interaction (Lindsay Clandfield and Jill Hadfield, personal communication 2017). Ultimately, this type of learning is a pedagogically richer extension of learning at the first level, making room for more active, collaborative, constructivist approaches. Another type of learning at the second level involves learners who, while outside the classroom, can access online learning materials and potentially engage with geographically scattered fellow learners, from a variety of locations and, not infrequently, while actually on the move in a variety of modes of transport (such as studying via an app or a mobile learning platform while taking the bus or train to or from work). Again, in terms of the iPAC framework, elements of collaboration may be layered over the personalization of the hardware, software, and learning; and in terms of the online interaction model, both weak and strong interaction may be involved, with the latter occurring mainly through, rather than around, the devices. At the third level of mobile learning, the devices, the learners, and the learning experience are all mobile. That is to say, the learning experience is dynamically shaped and informed by the learners’ movement through changing spaces and contexts; for instance, students might be directed to record examples of languagein-action derived from real-world exchanges before analyzing them and compiling them into an annotated class database. It is at this level that mobile learning offers

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the greatest possibilities for pedagogical transformation, opening up space for inquiry-based or problem-based participatory approaches anchored in “user-generated contexts” for learning (Cook 2010). At the first two levels of mobile learning, there is some limited potential for mobile devices to function as lenses directing attention from the classroom to the wider world outside or directing attention from the wider world into the (online) classroom, but, to a large extent, they function as screens on which students focus their attention while wholly or partly turning their backs on the real world. At the third level, however, mobile devices truly come into their own as lenses. At this level, they can serve as lenses to focus students’ attention on the learning possibilities in their real-world settings (Dunleavy 2014), providing them with the information channels to inform their experiences and the communication channels to record, share, revisit, and consolidate these experiences. In this way, the educational benefits of personalization and collaboration can be enriched by the integration of elements of authenticity drawn from everyday environments; and, as at the second level of mobile learning, pedagogically traditional learning involving weak interaction can continue to be enriched by the integration of more contemporary approaches involving strong interaction, with the latter very likely occurring both through and around the mobile devices. The growing pedagogical sophistication that emerges in moving from the first to the third level of mobile learning involves, in part, differences of degree; but such differences of degree can accumulate to enable transformative learning possibilities at the third level. In short, to maximize the pedagogical potential of mobile learning, the optimal underlying designs should involve activities encompassing all three levels of mobility; the three constructs of personalization, collaboration, and authenticity; and both weak and strong interaction, with the latter occurring online, offline, or both. Many of the most effective examples of such designs are to be found in today’s AR-enabled gamified learning trails, where mobile devices are employed as lenses on learning.

3

Mobile AR Learning

According to a conceptual definition, AR involves a dynamic presentation of contextually relevant information and communication channels in a real-world setting, usually via a mobile device which can be easily moved between settings; according to a technocentric definition, which effectively represents a subset of the conceptual definition, AR involves a visual superimposition of these channels on a view of a real-world setting, such as on the screen of a smartphone (e.g., Bacca et al. 2014; FitzGerald et al. 2012). The broader definition is more useful in many ways (Chow et al. 2015; Pegrum 2014), certainly educationally, as it allows consideration of a wider range of channels with similar learning implications. Nonetheless, the visual displays associated with the narrower definition are likely to become the dominant AR interfaces of the next few years (most likely complemented by auditory and haptic elements) as the transition from smartphones to smart glasses gets underway (Scoble and Israel 2017), possibly to be followed at a later stage by

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a shift to smart contact lenses. It is worth noting that AR is sometimes also referred to as mixed reality (MR), given the mixing of the real and the virtual, especially in visual AR interfaces. Mobile AR is widely seen as a technology with considerable promise. In 2016, when asked about virtual reality (VR), Apple’s CEO Tim Cook responded that he considers AR to be a larger development and “probably by far” because of the way it allows users to be “very present” while engaging with each other (Kastrenakes 2016). The key difference is that unlike VR, AR does not require simulation of an entire world, but rather situates users in the real world overlaid with and informed by digital data. In 2017, Facebook’s CEO Mark Zuckerberg also endorsed the value of AR, referring to the coming generations of devices: “We want to get to this world in the future where you eventually have glasses or contact lenses where you can mix digital or physical objects in the digital world” (Isaac 2017). There is already intense educational interest in AR. Early research on the educational advantages of mobile AR is now underpinned by a growing empirical base. This research has drawn heavily on pedagogical approaches such as (social) constructivism (Vygotsky 1978) and its offshoots like inquiry-based, problem-based, and task-based learning, explicitly or implicitly linking these approaches with AR activities that are built around (collaborative) construction of knowledge (e.g., Dunleavy and Dede 2014; FitzGerald et al. 2012; Lee et al. 2016). Similarly, the research has drawn on situated/contextual learning (Comas-Quinn et al. 2009; Huang et al. 2016; Lave and Wenger 1991), emphasizing the connection with AR activities that involve the construction of understanding emerging from the interplay between people, objects, and activities located in everyday settings (e.g., FitzGerald et al. 2012; Johnson et al. 2016; Kinshuk 2015; Sharples et al. 2015; Traxler and Kukulska-Hulme 2016a). There would also appear to be possible links, as yet rarely considered, between situated or contextualized AR and the emerging concept of place-based/place-conscious pedagogy (Comber 2016; Demarest 2015), which is grounded in the premise that learning should be tailored to local contexts and framed within a broad social justice agenda that helps students to engage in active, meaningful learning in those contexts while contributing to their local communities. In addition, the research has drawn on the notion of informal learning (ComasQuinn et al. 2009; Livingstone 2001), explicitly or implicitly highlighting the connection with AR activities that foreground the extensive and often unanticipated incidental learning possibilities present in everyday surroundings (e.g., FitzGerald et al. 2012; Read et al. 2016; Traxler and Kukulska-Hulme 2016a). Furthermore, the research has drawn on the idea of embodied learning/cognition (Gee 2015; Sharples et al. 2015), which has gained currency as a way of beginning to overcome the Cartesian mind-body dualism and the limitations of disembodied learning, with the research emphasizing its relevance for AR learning that foregrounds the relationship between the mind, the body, and the context or environment (e.g., FitzGerald et al. 2012; Pegrum 2014; Radu 2014). Given the extensive links that have been recognized between AR learning and widely endorsed contemporary pedagogical approaches and frameworks, it is unsurprising that a number of studies report that mobile AR can lead to learning gains (e.g., Bacca et al. 2014; Johnson et al. 2016; Radu 2014; Schmitz et al. 2012),

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although there is certainly a need for more empirical and comparative work in this area. As might also be expected, numerous studies report motivational gains, especially though not exclusively when AR intersects with gaming approaches (e.g., Antonaci et al. 2015; Bacca et al. 2014; Dunleavy and Dede 2014; Radu 2014; Schmitz et al. 2012). Moreover, additional learning benefits might be expected to accrue from AR games, given recent research suggesting the potential of various kinds of gaming and gamification to promote the development of twentyfirst-century skills (e.g., Qian and Clark 2016; Sourmelis et al. 2017). Indeed, perceptions of both the learning benefits and the motivational benefits of mobile AR gaming were boosted globally with the release of the world’s first widely popular AR game, Niantic’s 2016 Pokémon GO, with educators taking to the web to extol its advantages (e.g., Conlan 2016; Gorman 2016). Within the rapidly broadening field of contextualized and often gamified mobile AR learning, it is possible to trace a trajectory from initiatives where students are relatively passive learners, observers, or consumers, to those where they become more actively involved in generating their own learning (Traxler and KukulskaHulme 2016b), for example, through annotating their environments and/or creating contextualized multimedia artifacts (FitzGerald et al. 2012). In more passive educational scenarios, students’ mobile devices might act primarily as lenses on learning to make the invisible visible (Dunleavy 2014) and highlight learning opportunities to them, though this could in turn prompt certain interactions with the environment and the people within it. In more active scenarios, students might help to turn their peers’, teachers’, or the wider public’s mobile devices into lenses on learning. Both the more passive and more active aspects of mobile AR – especially when intertwined, as is often the case – may have a role to play in the transformation of learning, helping to promote a shift away from traditional teacher-centered pedagogies toward more constructivist learning enveloped in twenty-first-century skills like communication, collaboration, critical thinking, and creativity (Gee 2013; NCTE 2013; P21 n.d.). This is about much more than a quantitative increase in the educational opportunities available; it amounts to a qualitative shift: we need to consider how new technologies might offer the potential for qualitative change in our relationship with reality: imagine a learner leaving a ‘video note’ for her peers at a historical point of interest; viewing a geographical site as it would have looked in the ice age; or collecting audio-visual notes of her observations. Such experiences transform reality into a multi-modal social text . . . (FitzGerald et al. 2012, p. 3)

In short, this educational potential inheres in well-designed mobile AR learning where, as noted in the earlier discussion of levels of mobile learning, there is mobility of the devices, the learners, and the learning experience; where there is scope for personalization, collaboration, and authenticity; and where strong interaction, whether through or around the devices, complements weak interaction. In the not-too-distant future, the possibilities will regularly be enhanced in learning designs linking mobility with big data tracking and learning analytics (Chan et al. 2015; Traxler and Kukulska-Hulme 2016b), which can further magnify the power of mobile devices as personalized lenses on learning.

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Mobile AR Learning Around the World

Recent years have seen a number of successful mobile AR learning projects, many involving some kind of game-based design. Early US educational experiments with GPS-enabled handheld devices included the Alien Contact! game (Pegrum 2014; Potter 2011), where students collected digital data, interacted with virtual characters, and completed literacy and mathematics puzzles in their quest to determine why aliens had landed on their campus, and the Environmental Detectives game (Klopfer and Squire 2008), where students also collected digital data and interviewed virtual characters on their mission to investigate the cause of a toxin found in campus groundwater and to propose solutions. In the more recent New Zealand Kiwi Mobile game for Android devices (Lee et al. 2016), players were tasked with collecting digital data in a variety of real-world locations as they investigated the problems facing a fictional mobile phone company. It has been suggested that there is considerable potential for promoting AR-enhanced language learning: “Mixing realities has meaningful implementations in the short term, and it seems this could be a new frontier in language education and learning in general” (Hawkinson et al. 2017, p. 31). Well-known projects with a specific MALL focus have included the US Mentira game (Holden and Sykes 2011; Pegrum 2014), where students of Spanish engaged in online and offline interactions – with the latter including a visit to a local Spanish-speaking neighborhood – in the search for clues to solve a historical murder mystery. Meanwhile, the European MASELTOV project (Kukulska-Hulme et al. 2015; Kukulska-Hulme and Pegrum 2018) involved the creation of a context-aware Android app to support recent migrants to Europe in leveraging their everyday environments to reinforce their language learning, with help of a suite of tools tied together by a recommendation engine and a serious game. There have also been many innovative initiatives to emerge in the Asian region. The remainder of this chapter outlines four cutting-edge projects, from Singapore, Hong Kong, Indonesia, and Japan, respectively. The first two are large-scale educational projects, one with a historical and cultural focus and the other with an academic integrity and ethics focus, both of which also incorporate language and literacy learning elements. The last two are more narrowly targeted MALL projects, one with a focus on learning Indonesian and the other with a focus on learning English. In all of these projects, students straddle the virtual-real divide, accessing and/or creating digital data in real-world settings and often engaging in both collaboration and competition with other learners at the same time.

4.1

Heritage Trails in Singapore

Since 2008, the Singaporean company LDR has been developing mobile AR learning trails which have now found their way into schools, colleges and universities, cultural institutions, corporations, and even the military (Pegrum 2014, 2016), with approximately 241,000 people having participated in these trails as of

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September 2017. The trails support content learning in formats ranging from orientation tours for new students through cultural tours for travelers to wartime history tours for army recruits. At the same time, they promote skills development in areas ranging from team building to leadership training, and encompassing twentyfirst-century skills along with associated digital literacies. Among the 192 trails created by LDR to date, there are 39 heritage trails commissioned by the Ministry of Education and designed as part of the social studies syllabus to assist school students in learning about Singaporean history and culture via the medium of the Singaporean lingua franca, English, or the mother tongue languages Mandarin, Malay, and Tamil. Students work in groups, using Android or Apple mobile devices to access the Pocket Trips app, which employs GPS, Bluetooth, and image recognition technology to overlay information and tasks on their surroundings. They thus have the opportunity to learn from the app, the environment, and each other in immersive activities. At each station on a learning trail, multimedia information is pushed to students to help contextualize their understanding. A first layer of quiz questions then typically requires them to seek factual answers in the setting in which they find themselves, after which they receive immediate, automated feedback on whether they are correct; for example, students might be asked to identify a historical figure depicted in a statue or find out the construction date of a building. Following this, a second layer of tasks engages them in local inquiries and collaborative construction of multimodal responses; for example, they might be asked to interview passersby or owners of nearby businesses about a historical event and then, while still in situ, to reenact a key conversation they imagine taking place during that event, filming it and uploading it to the app for later review and commentary by peers and teachers. While students collaborate in groups, those groups may compete against each other as to how quickly and effectively they can complete a given learning trail, thus adding a motivating game-like element into the mix. These trails clearly involve mobility of the devices, the learners, and the learning experience; they offer scope for personalized and collaborative responses constructed in authentic settings relevant to the learning; and they demand strong interaction both around and through the technology. From a language learning point of view, students may be seen as engaging in a situated kind of content and language integrated learning (CLIL), in this case practicing language while they learn about history and culture; and they may also find themselves engaging in codeswitching, as multilingual teams collaboratively seek out information in different ethnic neighborhoods before generating a group response in a matrix language like English or Mandarin. Not only can students teach their peers and the wider community through the multimodal artifacts they produce, but they can teach each other in a more structured way by creating learning stations and indeed entire learning trails for their peers using the Pocket Trips software. The approach of having students create their own customized, inquiry- or problem-based, and sometimes gamified learning trails – one also espoused by another well-known Singaporean company, Rockmoon, through its Trail Shuttle software – is designed to maximize the emphasis on active, constructivist learning.

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TIEs in Hong Kong

Since 2015, mobile AR learning trails have been designed, piloted, and deployed as part of the project Reinforcing the Importance of Academic Integrity and Ethics in Students with Blended Learning – A Deployment of Augmented Reality Applications, funded by the University Grants Committee of Hong Kong from 2014 to 2017 and led by Hong Kong Baptist University in cooperation with the Chinese University of Hong Kong, the Education University of Hong Kong, and the Hong Kong Polytechnic University (Chow et al. 2015; Kukulska-Hulme and Pegrum 2018; Wong et al. 2016). As of late 2017, 8 main trails had been developed, some with different versions for implementation on different campuses, and more than 3000 students had taken part in them. Known as the Trails of Integrity and Ethics (TIEs), these are not intended primarily to promote language learning or literacy acquisition, but have nevertheless been found to offer considerable support for both. Rather than learning about academic integrity and ethics in a formal classroom context, first-year students arriving for their university orientation are requested to download the AR-Learn app – customized and enhanced for use in this project by the Singaporean developer, Impact Media Inc. – onto their own Android or Apple mobile devices. Working in groups, they follow a version of the TIE-General trail tailored to their particular campus. This takes them to learning stations where ethical dilemmas ranging from intellectual property to data falsification issues might arise, as revealed at each location through some combination of GPS, Bluetooth, and image recognition (including QR scanning) technology. The dilemmas are contextualized in a multimedia storyline involving local Hong Kong university students conversing about the issues in question in colloquial English through platforms like WhatsApp. After learning about and discussing each dilemma, the first-years are asked to select what they believe to be the most appropriate response, on which they subsequently receive feedback. They thus have the opportunity to co-construct understandings as they connect theoretical guidelines with pertinent real-life contexts, applying their learning to possible everyday scenarios. From a language learning point of view, it is important to note that most students taking such a trail are native speakers of Chinese (Cantonese or Mandarin), not of English, and that for some this is the first time in their lives that they have attended an English-medium institution; the colloquial language they encounter incidentally in these stories exposes them to linguistic resources they can draw on in their everyday lives on campus over coming years, especially as they interact with the increasing numbers of international students. There is also a peripheral multilingual element, with some cohorts of students who take TIE-General being given the option to use either English or Chinese in their pre-trail and post-trail online discussions, resulting in digital conversations that flow naturally back and forth between the languages preferred by these largely biliterate, trilingual students. Going beyond such general language learning, the trails can play an even more significant role in helping students develop field-specific language, as seen in the case of TIE-SR, a 30-station trail focusing on integrity and ethics in the area of Sports and Recreation. Dilemmas are presented in bilingual videos, generally voiced

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in Cantonese but subtitled in English, and framed by English-language response options and feedback. Comparisons of students’ pre-trail and post-trail online discussions of integrity and ethics have revealed increased post-trail usage of highly appropriate, subject-specific, English language lexis related to sporting ethics. Although these students are mostly not native speakers of English, they are studying sports and recreation in English and therefore need to acquire the appropriate disciplinary vocabulary. It is particularly noteworthy that the TIE-SR learning stations were constructed not by lecturers but by students and alumni who were tasked with conceptualizing, presenting, and asking questions about genuinely relevant and challenging sports dilemmas in an engaging, multimodal manner; the materials were created using Microsoft PowerPoint and the iSpring Suite and then converted into HTML5 files. Student surveys have indicated a high level of engagement in these situated learning activities, where the devices, the learners, and the learning experience are all mobile; where students are invited to collaborate on their responses to personally relevant scenarios in authentic settings; where strong forms of interaction around the devices (complemented by strong interactions through other devices in the pre- and post-trail discussions) are dominant; and where motivation is enhanced by game-like elements such as competitions between teams or overarching puzzle structures where students collect clues at each station to obtain an overall message or meaning. Finally, having students construct their own learning scenarios for their peers capitalizes on the potential for active, constructivist learning; this is a strategy which, having been demonstrated successfully on TIE-SR, has now become the norm for all other learning trails being built as part of this project.

4.3

Mega Trails in Indonesia

Since 2016, work has been underway on building mobile AR trails with a specific language focus for learners of Indonesian. Developed by Language Mega using LDR’s Pocket Trips platform, the trails are being designed and trialed first in Singapore, with a view to eventual deployment in Indonesia for language learners who visit that country. Created initially for Apple’s operating system, iOS, the plan is to release an Android version at a later date. After downloading the Language Mega app to an Apple device, a student can follow a trail through Kampong Glam, the traditional Malay area of Singapore, with a combination of GPS, Bluetooth, and image recognition being used to reveal information and tasks at each learning station. The tasks relate directly to language learned in the preceding section of the app. For instance, when students have been learning lexis relevant to food and beverages, they are asked to visit a shop and buy a famous Indonesian tea; following the option to watch an advertisement for this product from Indonesian television, they are invited to take a “selfie” with their purchase and post it to the class Facebook group. Or when students have been learning the names of fruit and vegetables, they are asked to launch the AR interface in the fresh produce section of a supermarket, identify the tagged fruit and

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vegetables, and send audio recordings to their teacher of themselves pronouncing the names in Indonesian. After each activity, students are requested to seek out a particular sign or object in the setting in which they find themselves, scanning it to unlock the next level of the learning quest. The trails can lend themselves either to independent learning or joint learning, with individuals or teams of students potentially competing against each other in terms of speed and accuracy. These trails encompass mobile devices, mobile learners, and a mobile learning experience. Personalized responses are required from students who take the trails alone, though the products they generate in various media – photos, audio recordings, or video recordings – are often shared with peers on the social media platform Facebook. Collaborative responses are of course more natural on occasions when students work in groups to follow the trails. In either case, the central emphasis is on situated learning in authentic contexts, as indicated by Haneef Khee, the CEO of Language Mega, who points out that the trails are specifically conceptualized to transport learners into environments “where they can experience first-hand the culture and hear and speak in real situations as the language is used on a daily basis” (personal communication, 2017). These trails powerfully exploit the potential of mobile devices to prompt language learning activities in the real-world contexts where the language is naturally spoken, as well as their capacity to record these learning activities for later evaluation by teachers, commentary by peers, and reflection by the learners themselves.

4.4

Fukuchiyama Castle Rally in Japan

In 2017, as part of the ARientation project, which aims to establish design principles and best practices for informal AR learning, 220 participants took part in the Fukuchiyama AR Rally, organized by the Mixed, Augmented and Virtual Realities in Learning (MAVR) research group in the Japanese city of Fukuchiyama. The goals were to orientate new University of Fukuchiyama students to the city, create an atmosphere conducive to building relationships, and connect students with the community. The four learning trails were presented to students as “missions,” all of them conducted in English. One of these missions, the Fukuchiyama Castle Rally, which was taken by 37 participants, focused specifically on helping the Japanese students to improve their English through an AR vocabulary activity (Hawkinson 2017; Mehran and Alizadeh 2017). Working in groups of nine to ten participants in four separate rounds, students began by downloading the Blippar AR app to their personal mobile devices. Scanning an AR card at the entrance to Fukuchiyama Castle revealed a video briefing them on the nature of their mission, which involved locating ten AR cards containing key vocabulary – in each case accompanied by the pronunciation, a definition, and an example – relating to the history of the building and location, and obtaining secret codes from these cards which would be needed to unlock a box at the conclusion of the mission. Following a vocabulary pre-quiz, students were exposed to a second video presenting all of the key vocabulary in the context

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of a historical description of the castle. They then set out on their mission to find the vocabulary cards which, wherever possible, were placed next to relevant objects, so that, for instance, the card for the word “helmet” was located next to a display of armor which included helmets. After a vocabulary posttest, students were able to use the codes they had obtained from the cards to unlock the box, revealing “mission accomplished” signs, which they then held up as they posed for a final group photograph. As will be detailed in a future publication, average scores in the posttests were close to one point higher than in the pretests (though a t-test revealed this result not to be significant); it would be interesting to see whether future trials with bigger vocabulary sets, longer activities, or larger cohorts might lead to more significant gains. The game-like framing of the learning activity as a mission certainly appears to have increased students’ engagement, which could perhaps be further heightened in future iterations of this project by having student teams compete with each other to complete the mission in the shortest time. This trail involved mobile devices, mobile learners, and a mobile learning experience. Collaboration within teams, including strong interaction around the devices, was promoted, and there was an emphasis on rendering the experience as authentic as possible by having students encounter the vocabulary in a real-world setting where it had immediate relevance – and where, for example, it might be spoken by a tour guide or documentary presenter and heard by tourists or viewers. Operating on a smaller scale than the sets of trails discussed in the Singaporean, Hong Kong, and Indonesian examples, the significance of this activity is in demonstrating the feasibility of mobile AR learning trails in the form of targeted interventions focused on particular areas of language learning (in this case, vocabulary) as motivating, situated learning supplements to in-class learning. Armed with some basic technological knowledge, and with the confidence that these activities can motivate students, teachers could design a number of such learning experiences scattered across nearby locations and interwoven throughout a class schedule – and, once such trails have been modeled for students, teachers could promote an even more active, constructivist approach by inviting students to design their own customized trails for their peers.

5

Future Directions

There are various senses in which mobile devices might be considered lenses on learning, but there are particularly compelling reasons for viewing AR-enabled devices as lenses on learning (and teaching) in the world outside the classroom. Transformative pedagogical possibilities arise when the devices, the learners, and the learning experience are all mobile; when there is a combined emphasis on personalization, collaboration, and especially authenticity; and when strong interaction, whether through or around the devices, is present. The resultant learning activities can be framed pedagogically with reference to social constructivism and its offshoots, as well as situated and place-based learning, informal learning, and embodied learning. Early research suggests that there are strong motivational benefits as

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well as some learning gains for students – as seen for instance in the Hong Kong and Japanese cases discussed above – though there is a pressing need for more empirical work to demonstrate this across subjects and levels, as well as helping to further distil mobile AR design principles. In order to promote further implementation of AR, there is also a need to pay greater attention to teacher development in the use of emerging technologies, not only entailing technological training and pedagogical framing but targeting a shift of mindset. The last of these requires teachers to orchestrate and facilitate more student-centered approaches where learners take on greater responsibility for their own learning; at the near end of the spectrum, that might simply mean students learning informally outside of class beyond the direct supervision of the teacher, and at the far end of the spectrum, it might mean empowering students to themselves become designers of learning experiences for their peers. In the latter case, students can effectively help turn their classmates’ mobile devices into lenses that focus their attention on the learning possibilities in real-world settings, spur them to interact with their settings, and invite them to construct multimodal responses geotagged to those settings, which can later be visited by their peers, their teachers, or the wider public. In time, smartphones are likely to be edged out by more flexible AR glasses and perhaps even AR contact lenses. At that point, mobile devices will be much more than metaphorical lenses; they will have become actual lenses. To the extent that educators have already become accustomed to considering mobile devices as lenses, this is a future development which they should welcome and for which they will be pedagogically prepared.

6

Cross-References

▶ Augmented Reality and 3D Technologies: Mapping Case Studies in Education ▶ Augmented Reality in Education ▶ Location and Place: Two Design Dimensions of Augmented Reality in Mobile Technologies ▶ VR, AR, and Wearable Technologies in Education: An Introduction

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Types of Virtual Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Concepts and Background of Virtual Worlds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Software and Hardware for Virtual Worlds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Educational Potential of 3D Virtual Worlds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Working with Students/Trainees in 3D Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Drafting a VR Island of Research (Stoyanov et al. 2016) . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Campus Plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Forming Working Teams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 AVARES Case (Hatzilygeroudis et al. 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Hybrid Educational Platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 The Virtual Learning Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 The AVARES Virtual World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 The Virtual World Facilities/Constructions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Connecting the Virtual World with the VLE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Beyond the AVARES: VR4STEM Case and World of Physics . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 VR4STEM: Virtual Reality for STEM Entrepreneurship Training . . . . . . . . . . . . . . . . . 4.2 WoP: World of Physics Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Z. Palkova (*) Department of Electrical Engineering, Automation and Informat- ics (TF), Slovak University of Agriculture in Nitra, Nitra, Slovakia e-mail: [email protected] I. Hatzilygeroudis University of Patras, Patras, Greece e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_88

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Abstract

The main aim of the chapter is to present how virtual reality is used in activities for making education more attractive to young generations. This chapter presents three projects supported by the European Commission under the program Erasmus+ (or predecessor), namely, AVARES – “Enhance attractiveness of renewable energy training by virtual reality,” VR4STEM – “Virtual Reality for STEM Entrepreneurship Training,” and World of Physics – “An innovative virtual reality educational environment for school physics education,” which focus on the implementation of Virtual Reality and 3D Virtual Worlds for different types of education and training. The AVARES project integrates a developed virtual world with a traditional Learning Management System (LMS), represented by Moodle, for more attractive learning in the challenging field of Renewable Energy Sources (RES). The hybrid educational platform developed in AVARES project combines traditional online learning procedures offered to students via Moodle, acting as a Virtual Learning Environment (VLE), with learning procedures delivered to students in 3D Virtual World. The Virtual World is developed in Open Simulator (OpenSim), an open source platform for creating multi user 3D Virtual Worlds. VLE focuses on the management of the learning material processes, whereas the Virtual World environment offers students the ability to interact and experiment with items and constructs in a similar way they would do in real world. The VR4STEM project aims to assist young people to gain entrepreneurship skill in STEM domain and the related ICT industry. The project’s main aim is to offer an educational environment for teaching/learning STEM entrepreneurship aspects that uses advanced ICT-based educational methods, like 3D virtual reality-based ones. This leads to more attractive ways of teaching, through the Virtual 3D World that is developed, and hence to more effective ICT-based teaching and training. The VR4STEM project offers to young people the chance to improve understanding and skills on STEM entrepreneurship, using augmented technologies and contributes in improving the quality of learning. The World of Physics project aims to assist students in studying physics domain with the utilization of innovative technologies like virtual reality. Specifically, a 3D virtual reality educational environment is developed possessing innovative educational infrastructure, offering immersive and efficient learning opportunities, engaging students in various educational activities, learning scenarios, and offering students an attractive, entertaining and efficient way to learn various topics of the challenging domain of physics. The students have the ability to virtually visit laboratories, perform experiments, explore procedures, and examine the ways that are conducted. The virtual educational environment and the laboratories are designed in a way that supports students to create appropriate mental models of the involved concepts. This is achieved by offering visualizations of phenomena and processes in the form of interactive virtual representations of them. This contributes in more effective ICT-based teaching and training and also offers new, more attractive ways of teaching, through the Virtual 3D

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World that is developed. Students can improve their understanding and skills on physics with the use of advanced ICT (like virtual reality technology), thus improving the quality of education and learning.

1

Introduction

The virtual reality concept appeared much earlier than the modern computers (Ainge 1995). In the middle of the twentieth century, Morton Heilig suggested the creation of the Sensorama (IJsselsteijn 2005), a theater experience designed to stimulate the senses of the audience – vision, sound, balance, smell, even touch (via wind) – and so draw them more effectively into the productions (www.Itleadership.org, 2010). The digitally generated world has entered our life more than three decades ago; however, many of the ideas used to build it already existed for much longer. They can be found in well-established social technologies, such as books, theater, film, music. The idea of a virtual world where people negotiate space as a psychological apparatus, rather than a physical reality, has been exploited for centuries and can be traced as back as to the ancient Greek mythology. The concept of virtuality is far wider and encompasses much more than the computer mediated communities. So, the digital virtual worlds can be considered as an extension of other older forms of virtuality. The virtual reality (VR) simulators developed for military and aerospace purposes are the granddads of the virtual worlds. Virtual reality as a term applies to computersimulated environments that can simulate physical presence in places in the real and in imaginary worlds. The term virtual reality itself was proposed and popularized in the 1980s by Jaron Lanier, a researcher and engineer who contributed to several products to the emerging VR industry. Today virtual reality is used to describe a wide variety of applications commonly associated with immersive, highly visual, 3D environments. Most of the current VR environments are displayed via a computer screen or special stereoscopic displays and rely mainly on visual stimulus; however, there are simulations include additional sensory information, such as sound and force feedback (tactile information). In near future, remote communication environments will become available (see ▶ Chap. 21, “Study on Networked Teleoperation Applied in Mobile Teaching”). They will provide users with virtual presence (telepresence and telexistence) and will use either standard input devices such as a keyboard and mouse or multimodal devices like wired gloves and omnidirectional treadmills. The simulated realities in such environments can be like the real world and provide lifelike experience (combat training, pilot simulators) or can differ significantly from reality (VR games). The origin of virtual worlds on personal computers can be traced back to early games such as Maze War (Tachi et al. 2012), which was developed in the early 1970s at NASA. In this game images of eyeballs were used to represented avatars, there were maps showing the levels, and it was played over networks. In 1986, LucasFilm

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Games developed Habitat (Habitat: http://www.youtube.com/watch?v= VVpulhO3jyc), mostly two-dimensional environment that included humanoid avatars, and users could access the game through online service on their computers. When World Wide Web started to spread in the mid-1990s, many online virtual worlds started to appear, and some experts predicted that these 3D views would become the standard way to browse the web. One of the earliest, the Active Worlds (Active Words: http://www.activeworlds.com/) platform, allowed people to join for free or pay a monthly fee for premium features. However, the first virtual worlds did not reach the expected level of popularity mainly because the hardware and bandwidth requirements were much higher than the average at the time. The 1990s have witnessed appearance of several VR-focused products – the EyePhone by VPL research, Nintendo’s Virtual Boy, Sega VR. The main reason they failed to reach popularity was the technology limitations in computing power resulted in high costs and lack of realism. However, VR progressed in other directions – car manufacturers started using it to design cars and test user experience; medical scientists used it to study or treat wide range of medical conditions – from physical to physiological. The governments, military, and NASA developed ways to incorporate VR into training. Fast forward several years: in September 2012 Oculus (Oculus: https://www. oculus.com) closes its Kickstarter campaign after raising two million dollars, in March 2014 it is bought by Facebook. In 2015 VR become affordable for a first time: Google cardboard headsets were presented which converted any smartphone into a head-mounted display (see ▶ Chap. 73, “Location and Place: Two Design Dimensions of Augmented Reality in Mobile Technologies”). Various magazines delivered ready cardboard headsets to their subscribers. Instructions were published online how to create such headsets at home, DIY style, requiring only a plan, cardboard, and a smartphone. The big question is whether the trend be sustained in 2016 and beyond. Will after the initial hype the industry manage to provide content to exploit the existing, already powerful and affordable hardware: games, education materials and ultimately movies? (Virtual reality in 2016: The 10 biggest trends to watch: http:// www.techrepublic.com/article/virtual-reality-in-2016-the-10-biggest-trends-to-watch/) According to a study by Accuray Research LLP, published in March 2016, the Global AR and VR Market is poised to grow at around 16.7% in the next 5 years to reach approximately $2.95 billion by 2020 (Global Augmented Reality and Virtual Reality Market Analysis & Trends – Industry Forecast to 2020 http://www. reportlinker.com/p03622000-summary/Global-Augmented-Reality-and-Virtual-Real ity-Market-Analysis-Trends-Industry-Forecast-to.html).

1.1

Types of Virtual Reality

1.1.1 Immersive Completely involves the user’s personal viewpoint in the virtual world. The user experiences immersion or the feeling of being a part of that world. Usually a HMD

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(Head Mounted Display) is used, a helmet or face mask that holds the visual and auditory displays. A large projection displays are used to create a virtual background such as a room.

1.1.2 Nonimmersive Text-based VR: The reader of a certain text forms a mental model of a virtual world in his mind (Curtis 1992). Augmented VR: The idea of taking what is real and adding to it in some way so the user obtains more information from their environment, where can be included: – Window on world (or Desktop VR) (Li et al. 2003) – Systems that use conventional computer monitor to display visual world

1.1.3 Tele-Presence Systems link the remote sensors with the senses of human operator in real world. Popular applications include teleconferencing and operating remote controlled vehicles (see ▶ Chap. 21, “Study on Networked Teleoperation Applied in Mobile Teaching”). 1.1.4 Mixed Reality Mixed reality merges Tele-presence and Virtual Reality systems. The user can see and hear a virtual world and can operate with the world using Tele-presence. 1.1.5 Virtual Worlds “Virtual World” term is used to describe digital spaces that can be explored from within, where users can navigate through, interact with objects, other users and AI bots. Users can exchange information via text, audio, still images, animation, and video. Usually the user’s presence takes is facilitated by an “avatar” – a digital 3D object that is used to represent the user. This representation is chosen by the user who may choose if his virtual identity has any real-world resemblance (Miah and Jones 2011). The currently popular virtual worlds are three-dimensional (3D) computer rendered environments which can be accessed over a network, usually via Internet, populated by users in form of avatars who interact with the simulated environment and other users (Ma et al. 2014; Grivokostopoulou et al. 2015). These virtual worlds had moved beyond gaming and chat environments and transforming into powerful communication and education tools. The sensory immersion and the way of communication with other users make them a feasible alternative approach to tasks as distance learning and training, worldwide communication, and collaboration (Fominykh and Prasolova-Forland 2012). The number of private and public virtual world users grows steadily, from 300 million users worldwide in 2008 to forecasted 1 billion users in 2017 (Strategy Analytics: http://www.strategyanalytics.com/default. aspx?mod=PressReleaseViewer&a0=39830, populating existing and new virtual worlds that are constantly being developed. According to Gartner Research (http://www.gartner.com) statement dated 2008: “Public virtual worlds, which are suffering from disillusionment after their peak of

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hype in 2007, will in the long term represent an important media channel to support and build broader communities of interest (Hype Cycle for Emerging Technologies, Gartner Research, August 2008, http://www.gartner.com/it/page.jsp? id=739613).” Forrester Research (http://www.forrester.com) predicted: “Within five years, the 3D Internet will be as important for work as the Web is today. Information and knowledge management professionals should begin to investigate and experiment with virtual worlds (Getting Real Work Done In Virtual Worlds, Forrester Research, January 2008, http://www.forrester.com/Getting+Real+Work+Done+In+Virtual +Worlds/fulltext/-/E-RES43450?objectid=RES43450).” Virtual worlds are becoming a major technology for teaching, learning, research, and collaboration. Virtual worlds constitute a growing online space for collaborative play, learning, edutainment, and work.

1.2

Concepts and Background of Virtual Worlds

Virtual worlds rely on developing the centuries old human desire to get free from the boundaries of the real world. In 3D cyberspace users can interact with the virtual environment in a more life-like manner which can lead to development of new forms of human-machine interaction (HMI). Interaction with a computer by using a keyboard and mouse which became prevalent in the last 30 years is unnatural to humans and forces people to adapt to the existing technology. Ideally a virtual environment would allow users to fully immerse in a highly convincing world which they can explore by means of all senses and interact naturally using new forms of communication and understanding (De Freitas et al. 2010).

1.2.1 Real Life in Virtual Life A virtual world can offer freedom from real life constraints and besides mimicking the real world experience allow the users to: – Move though by walking, running, flying to explore the open spaces and threedimensional objects (e.g., buildings) – Interact with objects and perform virtual operations (open doors, access computer terminals, watch movies, etc.) – Interact and communicate with other world residents (e.g., write to, talk, play, attend events) – Take part in activities (e.g., training sessions, presentations, seminars) All these and many more activities taking place in a 3D environment replicate real-life experiences but without real-life constraints and with some degree of anonymity.

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1.2.2 Categories of 3D Virtual Worlds The contemporary virtual worlds can be categorized as follows: – Role plays – multiplayer role play online games (World of Warcraft (http://www. worldofwarcraft.com), Everquest (http://everquest.station.sony.com), Guild Wars (http://www.guildwards.com)) – Social – open-ended exploratory immersive worlds (Second Life (http://www. secondlife.com), OpenSimulator (http://opensimulator.org), CyWorld (http://us. cyworld.com), ActiveWorlds (http://www.activeworlds.com/edu/awedu.asp)) – Work-related – corporate and business 3D spaces (Project Wonderland (https:// lg3d-wonderland.dev.java.net), IBM’s Metaverse (http://eightbar.co.uk/2007/05/ 08/the-ibm-innovate-quick-internal-metaverse-project)) – Training – 3D training simulations and serious games (Forterra’s OLIVE platform (http://www.forterrainc.com/products.php)) – Mirror worlds – using geo-spatial databases and mapping services (Google Earth (http://earth.google.com), Planet Earth (http://www.planet-earth.org), Unype (http://www.unype.com)) The above categorization of virtual worlds is neither exhaustive nor definitive; it can be used as a starting point for exploring the wide range of applications that are currently available (Sara de Freitas, Serious Virtual Worlds, JISC, http://www.jisc. ac.uk/media/documents/publications/seriousvirtualworldsv1.pdf; http://arianeb. com/more3Dworlds.htm). Some of the application domains of 3D virtual worlds today (Virtual world, Wikipedia, http://en.wikipedia.org/wiki/Virtual_world): – – – – – – – –

Education and training Social communication, networking, and interaction Commercial (business and e-commerce) Medical Industrial design Entertainment (single- and multiplayer games) Tourism Media publishing, etc.

1.3

Software and Hardware for Virtual Worlds

1.3.1 Choosing a Platform The easier option to quickly create a virtual world is by using dedicated virtual world platforms. These platforms can already be online, offered as services allow users to connect and create own content (e.g., Secondlife (http://secondlife.com), Kitely (https://www.kitely.com)) or offered as software that user can install on his/her own machine as a server process, where client users will connect to.

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1.3.2 Proprietary Platforms Propriety platforms, like SecondLife or Kitely, are much easier to start with. The providers of these platforms run servers and hosting all the virtual worlds. This also allows focusing on creating and managing content and building virtual world, avoiding complex installation, configuration, and maintenance of software and hardware. Furthermore, this kind of virtual world will be part of a great grid of other worlds, sharing resources and assets. This makes it much easier for audience that already use Virtual Worlds, to find and visit other virtual world. Adequate support is offered, while there are usually corresponding marketplaces where users can find material that can use. The main drawback is apparently the cost of purchasing and maintaining land; however, in case of limited needs (e.g., user do not have own server), it could be less expensive than the alternative options. Additionally, the disadvantage of having own 3D World hosted is that user has less options for custom configurations, especially if he or she is an advanced user. 1.3.3 Open-Source Platform Open-source platforms like Opensim give user the freedom of running own server hosting his/her Virtual Worlds (Fishwick 2009, Allison et al. 2012). It is offered for free and allows user to have as many Worlds as want without land limitations. Every aspect of the Virtual World can be configured and since it is open source software, advanced users with programming skills can even implement their own, custom ideas and extensions. There is a community of existing users that can help beginners, and some distributions are available that require minimum amount of configuration. Even with preconfigured distributions, user needs to have some basic ICT knowledge, like networking and server management. Furthermore, this Virtual World will probably be somewhat secluded from other Worlds online (e.g., existing Virtual World users may have to create a new avatar to use in other Worlds). There are configuration options that allow linking another world to existing grids; however, they require additional time and skills to achieve.

2

Educational Potential of 3D Virtual Worlds

In the recent years, the 3D virtual worlds started to attract attention as platforms for learning (see ▶ Chap. 79, “VR and AR for Future Education”). They offer new learning delivery channels through which training organizations can provide experiential or simulated learning and group activities in a shared space. A virtual world can provide a perfect multidimensional/sensory environment and a host of tools for informal learning, coaching, brainstorming sessions allowing real time sharing and exchange and also recording and capturing the ongoing activities (Mikropoulos and Natsis 2011). Nowadays the existing 3D virtual worlds provide immersive learning delivery platform that can be adapted to different training scenarios (3D Learning and Virtual Worlds, Xerox white paper, 2009, http://www.xerox.com/businessservices):

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– Discovery learning by clicking on objects with associated information – Reinforcement learning by offering a knowledge repository, tools, etc., associated with objects in 3D – Collaborative workspaces, such as 3D classrooms and informal sites for discussion, encouraging school-style study and research – Traditional instructor-led learning through a distance delivery method – Simulated learning by modeling a process or interaction that closely resembles the real world in terms of fidelity and outcomes 3D virtual environments possess several significant advantages over other training approaches: – – – – – – – –

The experience can be much more engaging than a typical page-turning course. The learner can learn by doing. Expensive videoconferencing is not required for real-time online activity. A user’s learning experience can be designed to fit specific task needs with a flexibility and immediacy that is impossible in real life. Exploration and discovery are encouraged. Fantasy and imagination can be unleashed. Virtual 3D spaces often allow full recording of any activity, interaction, or exchange, enabling past events to be re-experienced or re-used. Creed, skin color, look, and status within the organization do not count much in virtual spaces. Further, people with major physical handicaps appear as capable and as beautiful as anyone else, reducing discrimination.

2.1

Working with Students/Trainees in 3D Environments

Setting up teaching places will help to organize the lessons. Theoretically, training activities can be realized anywhere; however, the students have to know where to come so even if teaching outdoors landmark is necessary – a big standalone tree, rock, or lake, for example. A proper auditorium will provide a more formal atmosphere for training activities and can make students realize that however fun (Fig. 21), the virtual world training is still training and has to be approached seriously (Liu et al. 2010).

2.1.1 Defining Training Goals To avoid a chaotic build-up as a starting point, the outline how virtual island will look like is recommended before it is actually created. In order to start designing the virtual island, the user’s tasks as goals and actions definitions are expected. Once users land on the island, they won’t necessarily immediately perform the actions expected. The task of teacher/trainer is to create an environment that will guide them towards the tasks that have to be achieved.

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2.1.2 User Pathways Specific sequences of actions have to lead visitors through the island as they try to accomplish their tasks. The goal of teacher/trainer is to define users’ paths – the flows that take users from their entry spot toward the places of interest (Fig. 17). Without the pathways, like the “yellow brick road” in the Baum’s Wizard of Oz, the visitors can get easily lost or distracted. 2.1.3 How to Optimize the Users’ Experience Jim Ramsey (2007) has written for web experience to virtual reality: – Have clear goals for users that help them understand where they are going and each step they will take to get there. – Provide immediate feedback – whether users click on a button or navigate from one location to another – tell them how they are doing, and what is going on. – Maximize efficiency – once users become familiar with the island, they will want to start using it more efficiently. When they are experiencing flow, users want to work more quickly and want the place to feel more responsive. We should avoid any annoying, repetitive tasks. – Allow for discovery – once a user has begun to work with maximum efficiency, there is a chance that they will feel less engaged and grow bored with their experience on the island. In order to avoid this, we should make content and features available for discovery. A prediction of students’ behavior can be described via three possible scenarios after landing in the virtual world (Fig. 1). Scenarios 2 and 3 can be changed at any point – the users may decide to use teleport, to skip following signs if he sees the place he wants to go in the distance and just fly there, or to stop flying when feeling lost and a signpost is in view. User Lands Reads the welcome information sign

Reads the welcome information sign

Ignores the welcome information sign

Selects location from list

Follows directional signs and maps

Explores the island freely

Teleports to destination

Reaches destination on foot

Sees the destination

Reaches destination on foot or flying

Fig. 1 Scenarios of students’ behavior in virtual world

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There are numerous possible combinations. Each scenario/combination of scenarios requires taking specific measures to provide smooth user experience. Scenario 1 – the list should be visible on landing, not hidden behind objects; the text should be easily readable – not obtrusively large, just large enough. It should be clear that each sign is interactive and offers a teleport. Scenario 2 – the directional signs should be visible on landing (Fig. 16). There should be strategically positioned direction posts and maps showing where user is located on the map. Paths or at least the directions should be easy to follow. Scenario 3 – all places of interest should have specific characteristics that distinguish them. The more “weight” given place has the more prominent and easy to spot it should be. Architecture should give visual clues to the purpose of each building/open area and hint what information it contains. In order to “tease” the users and increase their interest, certain activities may not be easy to spot and may be difficult to find. There are no signs leading to them, of if there are signs they are of the riddle type. The structures themselves can be hidden – behind buildings, land masses, vegetation, under the water, high up in the sky.

2.1.4 The Element of Discovery In order to “tease” the users and increase their interest, certain activities may not be easy to spot and may be difficult to find. There are no signs leading to them, of if there are signs they are of the riddle type. The structures themselves can be hidden – behind buildings, land masses, vegetation, under the water, high up in the sky. Some of these hidden “extras” may be unlocked after students achieve certain goals. As an example, the island of AVARES project (http://avares.org) had hot air balloon and solar-power vehicles (Fig. 6), which could be put in motion only after entering passwords. 2.1.5 Layered Approach The overall aim of the island design should be that the island appeals to new users and experienced users alike. The island should provide “layered” user experience so all types of users find the place enjoyable. New users should orientate easily, and experienced users should have places to discover or just to hang out with friends. This layered approach should be applied not only in spatial but in time dimension. There should be new movies in the cinema, new books in library, new training sessions. And not forgetting the edutainment: simple changes as new drinks in the bar, new boats in the bay, new roaming animals, new vehicles to drive, and complex changes as new games and quests.

2.2

Drafting a VR Island of Research (Stoyanov et al. 2016)

The geography of the Island of Research (Fig. 2) was created by Dr. Ernest Marburg, from the University of Michigan with the assistance of Elaine Stallman, and the artistic rendition of William Brudon. The original appeared in American Scientist, 54: 470, December 1966. The map is both serious and humorous (http://cancerres. aacrjournals.org/content/40/12/local/front-matter.pdf). The geography of the Island

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Fig. 2 Island of Research, first published in 1966, prepared by Dr. Ernest Harburg (University of Michigan) and Elaine Stallman, and drawn by William Brudon

of Research was created by Dr. Ernest Marburg, from the University of Michigan with the assistance of Elaine Stallman, and the artistic rendition of William Brudon. The original appeared in American Scientist, 54: 470, December 1966. The map is both serious and humorous. This island can be used also as a blueprint for design of other virtual worlds. A first question: an island or several islands – an archipelago? A choice should depend on whether the training topics will be very varied or not. If varied – perhaps it is a good idea to assign an island to each topic. If not, all the activities can be kept on one island. In order to add a discovering, game-like element, there may be an island for games and auxiliary resources, e.g., a small island, visible from the main one. Before going into detailed execution, the design of the island should start with a very rough plan of the island and position the key points of interest – the arrival (landing) spot, the place that will hold the main bulk of resources (a library), teaching spaces, informal meeting spaces, etc. This way teacher/trainer/island designer can plan the users’ paths and make sure that all main points of interest will be easily accessible. A hierarchy of places has to be established so the more important a place is – the more visible it is to the user on arrival. Following this logic can be “hidden” the places that host games and other surprise objects.

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2.2.1 The Island Atmosphere Before starting to create Island can run a survey among the students or other target groups, to see what expectations and preferences they have: urban, trendy, futuristic, adventurous, close to nature, etc. This will help designing a place the users can associate with. The design process should start from the grounds up – first terraforming, than urban planning and the architectural style(s), embellishments – vegetation, animals, and vehicles coming last. A good approach is to sketch ideas first – to keep the initial thought “fresh.” Designer can keep these initial sketches as a reference to come back to and check how far he/she progressed and if wandered off too much from the original idea or if to forgot something. How the island will look is limited only by designer imagination and the training topic. A tropical paradise can offer a break from the grey daily routine to visitors and offers great “Survival” style settings. A medieval castle can offer a lot in terms of gamification of history lessons. A remote island off the Irish coast could offer fitting environment for climate lessons. And a colony on Mars is ideal for courses on terraforming and science in general. Lessons do not need to be available only in the library or the auditorium – different lesson parts can be scattered around the island, one part leading to another and making users search for answers. Take full advantage of the created world and mix it with the learning materials until surrounding and training content blend to provide captivating learning experience. However, when organizing a trainer-led session, it is a good idea to inform the students beforehand when and where the training will take place.

2.3

Campus Plans

A campus layout may depend on several factors and wishes to emulate an existing real world campus, a historical location or sci-fi settings. Whatever option is selected, designer has to be sure that it is working well with the predefined students’ paths and all key zones of learning – auditoriums, libraries, exhibition areas, cinemas, and experimentation areas are easily accessible.

2.3.1 Suggested Virtual Island Campus Plan A crescent shaped bay with amphitheatrically terraced places. Why such approach? This way most places will be positioned within a short distance, not scattered around a flat surface. Thus, not only the important places will be well presented and easy to access, but we can avoid situations when elements disappear because of the distance. The campus should be made attractive and inviting. The bay itself can host floating cafes and other meeting venues. The library and the main amphitheatric auditorium can offer nice views to the bay. By clustering the training zones in one area, the rest of the island can be left relatively “wild.”

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2.3.2 Preparing the Training Content All the content that will be published in the VR world has to be organized by delivery media. Depending on the content type, the place of delivery can be selected: a library, a cinema, an exhibition area, a gaming club, etc., whichever is the optimal based on storyboards. Major task here is to keep the consistency of the topics. All major topics should bear an individual substyle that will distinguish them regardless of the media and place of delivery. Color coding of topics (assigning a different color to each topic) would be a good approach. If you wish to learn more about color coding in public spaces you can research the international standard ISO 22324: Societal security – Emergency management – Guidelines for color-coded alerts and supplementary information. Carefully placed links among the resources can save time and simplify the learning paths. Placing temporary teleport links between a meeting place and different resources, while conducting training session is a viable option. A way to motivate and empower the users is to offer areas/sections where they can contribute so they are not only passive but active learners. You can prepare showrooms for displaying users’ generated content – animations, videos, 3D objects, and spaces in libraries for resources written by the students. You can plan competitions and virtual fairs and much more.

2.4

Forming Working Teams

To organize the development of virtual worlds, several working teams specialized in certain areas are necessary: – Content transfer team tasks focus on create storyboards, optimize delivery of training resources in VR: what will work best as text, video, interactive games/ lessons, etc. The team check what are the file formats of the available learning resources and if needed convert the files for “in-world” use. – Engineers’ team tasks are oriented on server setup, test server, and client (s) programs. – “Scavengers” team finds best practices and collect free or CC-licensed resources that can be “re-cycled” while building the island. – Crowd management team designs the spatial learning pathways, optimize students flow among resources. – Terra-forming team creates the island: shape, topography, defining rocks, soils, and vegetation. – Architects team designs how the island will look: urban planning, architecture, info points. It is important that all teams establish good communication and keep track of the overall progress. To give some examples: Architects have to know what will be the island’s topography, what will be training pathways, and how the different resources

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will be displayed. Both architects and the content transfer team should be aware of the “Scavengers” finds to avoid producing resources that are already available. Engineers have to keep track of any bugs or problems the other teams may experience and offer timely solutions. Each team should develop a set of guidelines to be used during the implementation phase. Some of these guidelines will be used internally, some, for example, the engineers’ team guidelines for client programs and firewalls setup will be written for the end user.

3

AVARES Case (Hatzilygeroudis et al. 2013)

The aim of the AVARES Project (www.avares.org) was to establish a 3D virtual learning environment and multimedia learning materials for vocational education and training in the field of Renewable Energy Sources (RES). More specifically, the project aimed to develop a Virtual Reality environment, created innovative Virtual Reality learning methodologies, and integrated them with traditional learning for teaching more efficiently the challenging field of RES. The AVARES project and its outcomes offered a transition from the traditional book/textbook learning approaches to a new way of more interactive and efficient learning. Indeed, virtual reality offers a new, attractive, and efficient way of learning where learners can have a feeling of natural presence and also learn through experimenting and interacting scenarios in the virtual world.

3.1

Hybrid Educational Platform

The Hybrid Educational Platform developed in AVARES project for teaching RES domain combines traditional learning procedures offered to students via Learning Management System Moodle with learning procedures delivered to students in 3D virtual world. The AVARES virtual world uses Open-Source platform Open Simulator (OpenSim). LMS Moodle focuses on the management of the learning processes and helps the tutors with the course organization and administration. Virtual learning environment helps also the student to get the proper theoretical background on the domain of RES. In the AVARES virtual world, students have the ability to interact and experiment with items and constructions in a similar way they could in real world. In this way, students can get a deeper understanding of the functionality of special items such as energy machines, solar collectors, wind turbines. The 3D models of such items in the virtual world will present in an interactive way the parts they consist of and how they function. A student can explore the RES domain through five online courses: Solar Energy, Water Energy, Wind Energy, Geothermal Energy, and Energy of Biomass. The curriculum of each one of the e-courses combines traditional learning approaches with proper learning scenarios in the 3D virtual world.

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The Virtual Learning Environment

A Virtual Learning Environment (VLE) has been developed based on the Moodle VLE. Moodle platform was selected because of its popularity and wide-use and also because of its open-source nature. Selecting and using Moodle as a VLE has many pros. A main advantage is that Moodle is an open source environment which is developed and supported by an international community which has more than 1,000,000 members. Also, the Moodle LMS environment has been translated to more than 75 languages and has been used with great success in different institutions all over the world. Moreover, it includes a web service layer that opens it to new technologies and also gives Moodle the ability to be integrated with service-oriented architectures. Moodle VLE focuses on the management of the learning processes and can help the tutors with the course organization and administration and also the supervision of the students’ performance. Moreover, it can help students to get the proper theoretical background on the domain of RES. Students can explore and learn about RES domain through five courses available in the Moodle VLE environment: Solar Energy, Water Energy, Wind Energy, Geothermal Energy, and Energy of Biomass. Also, an introductory course on Green Energy is planned to be offered to the students. In Fig. 3, a few examples of the courses available in VLE are illustrated. In the AVARES VLE are available following courses: – Solar Energy Course: Introduces students to the basic theoretical concepts regarding solar energy production. The students learn how solar energy can be generated and how radiant light heat from the sun is harnessed using a range of ever-evolving technologies such as solar heating, solar photovoltaic, solar thermal electricity, solar architecture, and artificial photosynthesis (Figs. 4, 5, 6, and 7). – Water Energy Course: Hydroelectricity is the term referring to electricity generated by hydropower, the production of electrical power through the use of the gravitational force of falling or flowing water. The Water Energy course provides students the proper theoretical background of how hydropower generation systems operate and how hydropower energy is produced (Figs. 8, 9 and 10). – Wind Energy Course: During this course, the students learn how wind power is generated. More specifically, they learn how the wind is converted into a useful form of energy, and also the way this is made by using, for example, wind

Fig. 3 Virtual learning environment combines the advantages of LMS Moodle and virtual reality

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Fig. 4 Solar Energy Island

Fig. 5 Learning materials in VLE

Fig. 6 Solar-power vehicle

turbines to make electrical power, windmills for mechanical power, wind pumps for water pumping or drainage, or sails to propel ships (Figs. 11, 12, and 13). – Geothermal Energy Course: The course provides a student the knowledge about a thermal energy generated and stored in the Earth and that determines the temperature of matter (Figs. 14, 15, 16, and 17).

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Fig. 7 Interactive 3D animation

Fig. 8 Water Energy Island

Fig. 9 Learning materials in VLE and interactive 3D animation

– Energy of Biomass Course: Students are familiarize with the biomass as renewable energy source that can either be used directly via combustion to produce heat, or indirectly after converting it to various forms of biofuel. Course provides information about a conversion of biomass to biofuel, different methods that help to achieve it and are broadly classified into: thermal, chemical, and biochemical methods (Figs. 18, 19, 20, and 21).

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Fig. 10 Assignment in the AVARES VLE

Fig. 11 Wind Energy Island

Fig. 12 Interactive 3D animation

A student can register to the VLE platform and create a personal account. After that, he/she can anytime assess the platform with his/her credentials. In the VLE developed, the student can register and participate in any course he/she wants and gain access to the course’s educational content. The course material mainly consists

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Fig. 13 Interactive 3D animations

Fig. 14 Geothermal Energy Island

Fig. 15 Interactive 3D animations

of presentations that the student can download and study on his/her own pace. Learning material also includes textbooks, web-pages, animations, and videos. During a course the students are requested to fulfill different assignments. The assignments consist of different type of exercises such as fill-in-the-blank exercises, multiple choice exercises, and open answer ones (Fig. 12). The student after having answered their assignments can submit their answers for grading. Finally, the VLE platform offers various ways of communication between trainers and trainees

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Fig. 16 Landing place at GE Island

Fig. 17 Adventure pathway at GE Island

Fig. 18 Biomass Energy Island

including News and Announcements, Discussion Forum, Instant Messaging/Chat, Files Sharing. As mentioned above, the aim of the courses offered by the Moodle VLE is to help the students get the proper theoretical background on course’s concepts. After a student has covered the basic theoretical topics, he/she can access the Virtual World, where he/she can get the proper practical training thought different learning scenarios.

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Fig. 19 Powerpoint presentation displayed in the VLE

Fig. 20 Interactive 3D animations

Fig. 21 Outdoor auditorium

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The AVARES Virtual World

As technology evolves, it changes the human society. Over the past decades, technology has changed the education domain as well. Indeed, the way that learning procedures are structured and delivered to students has changed completely, shifting from traditional blackboard approaches to more engaging and interactive ones. Recent approaches for more efficient and intensive learning are via digital, 3D Virtual Reality environments. A Virtual World environment offers to the student the ability to interact and experiment with items and constructions in a similar way he/she would do in the real world. The main objective of the AVARES Virtual World is to present the learning material for each learning course stored in the VLE, in corresponding areas inside the world. It offers 3D models of the presented machineries and devices that will help students understand the way they function. Furthermore, it offers more assessment possibilities by tracking the avatar interactions in the Virtual World and also more ways for communication of trainers and trainees (Figs. 22, 23, 24, 25, 26, and 27). Inside the virtual world, trainers and trainees can communicate with instant messages. It is possible for teachers to create groups and invite their students to create working groups. However, the OpenSim can also embed suitable communication software, such as the FreeSWITCH server, to allow voice communication. This communication can be in the form of the trainer speaking and being heard by any avatars that are near to him, or in the form of private calls with selected avatars or groups in the world. Fig. 22 An overview of an area in the Virtual Word

Fig. 23 Main landing point

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Fig. 24 Learn how to use AVARES Virtual World

Fig. 25 An auditorium in the Virtual Word

Fig. 26 One of the informal meeting points in the AVARES Virtual Word

3.4

The Virtual World Facilities/Constructions

The Avares Virtual Word is proposed to consist of: – The 3D Auditorium: Trainers giving lectures in the 3D Auditorium will be able to load specific presentations from the VLE or even upload their own slides (Fig. 25).

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Fig. 27 Library in the AVARES Virtual Word – additional reading sources

– Sub-Areas dedicated to each course: For each one of the five main learning topics, there are designated areas inside the world. Each area hosts the corresponding training material along with interactive 3D models that will help them comprehend the presented topics (Figs. 4, 8, 10, 14, and 18). – Classrooms/ Meeting Rooms: These rooms can serve both as meeting areas for project partners and as classrooms for small groups of students (Figs. 21, 25, and 26).

3.5

Connecting the Virtual World with the VLE

The learning materials stored in the VLE are also available in the Virtual World. More specifically by visiting the 3D Library (Fig. 27), users have access to the textbooks and have the option of opening them in browser windows inside the Virtual World or following external links to the VLE. Specific textbooks and presentations are visible as posters or boards, at various areas of the Virtual World (Figs. 5, 11, and 19). For example, inside the 3D Virtual Park, adjacent to 3D models representing biogas systems (Fig. 20), users will be able to read the corresponding learning material from the VLE. Trainers giving lectures in the 3D Auditorium are able to load specific presentations from the VLE or even upload their own slides (Fig. 25). SLOODLE (https://www.sloodle.org) is a Moodle plug-in that has been developed to facilitate the integration of Moodle with Seconlife or Opensim (Kemp et al. 2009). Using SLOODLE avatars are able to participate in the exercises stored in the VLE by sitting on corresponding “test chairs.” Their answers are automatically evaluated by the VLE and as well their communications inside the virtual world are stored. A Scoreboard connected with the VLE can present their assessment in the AVARES Virtual World. It is also possible to use “enrolment booths” in the AVARES Virtual World to automatically register and enroll users in the VLE. The enrolment is also necessary to connect a student account in the VLE with the corresponding avatar. OpenSim embed suitable software such as Wi-Fi for offering an avatar account management system. This allows users to create and manage an avatar account for the virtual world. The administrator of the system can also use this tool to remotely manage avatar accounts and groups of avatars, to assign specific

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roles and grant permissions. It also allows using a number of default avatars (e.g., male, female) for users to select during the avatar creation. This system can finally be used in parallel with the Moodle registration module to allow the automatic creation of the avatar during the registration of the user in the VLE.

4

Beyond the AVARES: VR4STEM Case and World of Physics

Two projects – VR4STEM and WoP – follow experiences obtained in the AVARES project (AVARES Case) and outcomes of these projects will be available in 2018, respectively 2019.

4.1

VR4STEM: Virtual Reality for STEM Entrepreneurship Training

Youth entrepreneurship is vital for creating employment and sustainable growth and has become a priority in the EU policy agenda as a tool to combat unemployment and social exclusion as well as stimulating innovation among young people. According to Eurostat, the youth unemployment rates are much higher than unemployment rates for all ages. Particularly, unemployment rate among young people (18–24 years old) in Slovakia reached in March 2015 26.5%, in Romania 21.7%, and even in Greece 49.8%. In spite of high unemployment rates not only in mentioned but in many Member States, there is evidence of skills shortages in STEM (Science, Technology, Engineering, and Mathematics) fields. The Erasmus+ project “VR4STEM – Virtual Reality for STEM Entrepreneurship Training (www.vr4stem.ro),” which runs from February 2016 till January 2018 and aims to assist young people to gain entrepreneurship skill in STEM domain and the related ICT industry. The project main aim is to offer an educational environment for teaching/learning STEM entrepreneurship aspects that uses advanced ICT-based educational methods, like 3D virtual reality. This can lead to more effective ICT-based teaching and training and also offer new and more attractive ways of teaching, through the Virtual 3D World. Moreover, the VR4STEM project offer to young people the chance to improve understanding and skills on STEM entrepreneurship, through the use of augmented technologies, and will contribute to improve the quality of learning. The project brings together partners from Romania, Slovakia, Greece, and Germany. Over 24 months the partnership plans to achieve the following key deliverables: 1. Report on practices and competences in STEM Entrepreneurship Training and 3D Virtual Worlds – the study identifies the suitable techniques and learning approaches that are used in the 3D course, focusing on the requirements for efficiently training young people through virtual simulations and learning activities.

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2. STEM Entrepreneurship curriculum design – the aim of this output is to design a curriculum for STEM Entrepreneurship Training based on the Report on practices and competences in STEM Entrepreneurship and taking into account the reports about the state of the art and the capabilities of Virtual Worlds. 3. Open Learning Resources – specialized content on entrepreneurship in STEM sector is designed and implemented on the multimedia-based learning materials and related pedagogics. 4. Virtual 3D World – the 3D World hosts all developed STEM Entrepreneurship learning material (textbooks, presentations, multimedia, 3D objects, and constructions) as well as the learning scenarios. Furthermore, it includes functionality for carrying out virtual sessions, like conferences and seminars, a media library, and other learning activities. At the end of the VR4STEM project, Course Curriculum and Open Learning Resources will be available in five languages (English, Romanian, Greek, German, and Slovak) and will include: – Text/Presentation files (in Google Documents format) – Interactive multimedia files/animations – 3D Objects and constructions Based on the findings from the Report on practices and competences in STEM Entrepreneurship Training, course curriculum comprises five modules and covers following: – Three technological topics Information and Communication Technologies Drones Photooptics Two core theoretical topics: Innovation and start-ups Sot skills The learning platform and VR4STEM Virtual World will be freely available for young people to visit and use for self-learning purposes. Moreover, trainers will be encouraged to participate and extend the courses offered while improving their ICT skills.

4.2

WoP: World of Physics Case

The main aim of WoP project is to develop an educational environment developed innovative educational infrastructure and offer immersive and efficient learning opportunities, engaging students in various educational activities, learning scenarios and offering students an attractive, entertaining and efficient way to learn various

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topics of the challenging domain of physics. The virtual educational environment and the laboratories are designed in a way that support students to form appropriate mental models of involved concepts, by visualizing them and allowing interactions with the virtual phenomena and processes. Based on the findings in the report “Physics Education in Secondary Education Schools around Europe,” the WoP 3D World has three different regions, each one dedicated to one principal topic of Physics: – Mechanics – Properties of matter – Electricity and magnetism Each region contains a variety of different learning resources, both static (text, images, videos) and interactive (3D objects, puzzles and quizzes, talking characters, etc.). The learning experience follows the necessary pedagogical methods focusing on gamification and learning-by-doing ideas. More specifically the students are guided by Non Playable Characters (NPC) to follow certain quests inside the 3D World. Each quest has a clear learning goal and requires that the student: 1. Reads the relevant theory 2. Applies the concepts in experiments/laboratories 3. Completes assessment tests to receive a reward The tests are a simple quiz of multiple-choice questions or a simulated scenario where the student needs to apply the theory to solve a situation. Each region also has areas that support the teacher (logged in as an avatar) to give lectures to the students or test their progress. Finally, special areas where students are able to design their own material and the teachers can organize special assignments that can test the students in a highly creative and imaginative spirit are available. The learning materials include many different formats depending on the learning topic being taught such as text, images, multimedia, and 3D Objects.

5

Conclusions

In the recent years, the 3D virtual worlds started to attract attention as platforms for learning. They offer new learning delivery channels through which training organizations can provide experiential or simulated learning and group activities in a shared space. A virtual world can provide a perfect multidimensional/sensory environment and a host of tools for informal learning, coaching, brainstorming sessions allowing real time sharing and exchange and also recording and capturing the ongoing activities. Virtual worlds are becoming a major technology for teaching, learning, research, and collaboration (see ▶ Chap. 79, “VR and AR for Future

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Education”). Virtual worlds constitute a growing online space for collaborative play, learning, edutainment, and work. This chapter presents how virtual reality is used in activities for making education more attractive to young generations via presenting three project supported by the European Commission under the program Erasmus + (or predecessor), namely, AVARES – “Enhance attractiveness of renewable energy training by virtual reality,” VR4STEM – “Virtual Reality for STEM Entrepreneurship Training,” and World of Physics – “An innovative virtual reality educational environment for school physics education,” which focus on the implementation of Virtual reality and 3D Virtual worlds for different types of education and training.

6

Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Location and Place: Two Design Dimensions of Augmented Reality in Mobile Technologies ▶ Study on Networked Teleoperation Applied in Mobile Teaching ▶ VR and AR for Future Education

References Ainge, D. 1995. Virtual reality in Australia. VR in the Schools 1 (1): 3. Allison, C., A. Campbell, C.J. Davies, L. Dow, S. Kennedy, J.P. McCaffery, and G.I.U.S. Perera. 2012. Growing the use of virtual worlds in education: An OpenSim perspective. In Proceedings of the 2nd European Immersive Education Summit, 1–13. Curtis, P. 1992. Mudding: Social phenomena in text-based virtual realities. In High noon on the electronic frontier: Conceptual issues in cyberspace, 347–374. Cambridge, MA: MIT Press. De Freitas, S., G. Rebolledo-Mendez, F. Liarokapis, G. Magoulas, and A. Poulovassilis. 2010. Learning as immersive experiences: Using the four-dimensional framework for designing and evaluating immersive learning experiences in a virtual world. British Journal of Educational Technology 41 (1): 69–85. Fishwick, Paul A. 2009. An introduction to OpenSimulator and virtual environment agent-based M&S applications. In Simulation Conference (WSC), Proceedings of the 2009 Winter. IEEE, 177–183. Fominykh, M., and E. Prasolova-Førland. 2012. Educational visualizations in 3D collaborative virtual environments: A methodology. Interactive Technology and Smart Education 9 (1): 33–45. Grivokostopoulou, F., I. Perikos, K. Kovas, and Hatzilygeroudis, I. 2015. Teaching renewable energy sources using 3D virtual world technology. In Proceedings of the 2015 IEEE 15th International Conference on Advanced Learning Technologies, 472–474. Hatzilygeroudis, I., B. Stoyanov, Z. Palkova, F. Grivokostopoulou, K. Kovas, I. Perikos, D. Popovici, and S. Ionitescu. 2013. Developing a hybrid educational platform based on virtual world learning for teaching renewable energy domain. https://pdfs.semanticscholar.org/46e1/ 43b5f3c59e58ee5f8c72975b5ea2f286e8b3.pdf IJsselsteijn, W.A., 2005. History of Telepresence. In Schreer, O., P. Kauff, and T. Sikora (Eds). 3D Videocommunication: Algorithms, Concepts and Real-Time Systems in Human Centred Communication, John Wiley & Sons, 7-21.

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Kemp, J., D. Livingstone, and P. Bloomfield. 2009. SLOODLE: Connecting VLE tools with emergent teaching practice in Second Life. British Journal of Educational Technology 40 (3): 551–555. Li, J.R., L.P. Khoo, and S.B. Tor. 2003. Desktop virtual reality for maintenance training: an object oriented prototype system (V-REALISM). Computers in Industry 52 (2): 109–125. Liu, H., M. Bowman, R. Adams, J. Hurliman, and D. Lake. 2010. Scaling virtual worlds: Simulation requirements and challenges. In Simulation Conference (WSC), Proceedings of the 2010 Winter. IEEE, 778–790. Ma, T., X. Xiao, W. Wee, C.Y. Han, and X. Zhou. 2014. A 3D virtual learning system for STEM education. In Virtual, augmented and mixed reality. Applications of virtual and augmented reality, 63–72. Cham: Springer International Publishing. Miah, A., and J. Jones. 2011. Virtual worlds. In Encyclopedia of social networks, ed. G. Barnett. Sage. http://www.andymiah.net/wp-content/uploads/2011/09/MiahJones2011 VirtualWorldsSAGE.pdf. Mikropoulos, T.A., and A. Natsis. 2011. Educational virtual environments: A ten-year review of empirical research (1999–2009). Computers & Education 56 (3): 769–780. Ramsey, Jim. 2007. Designing for flow, December 04. Published in http://alistapart.com/ Stoyanov, B., I. Hatzilygeroudis, and K. Kovas. 2016. User guide: Setting up virtual worlds for training. VR4STEM project. http://vr4stem.ro/images/outputs/O1_User_guide_Setting_up_vir tual_worlds_final_2.pdf Tachi, S., K. Minamizawa, M. Furukawa, and C.L. Fernando. 2012. Telexistence – From 1980 to 2012. In Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, IEEE, 5440–5441.

Location and Place: Two Design Dimensions of Augmented Reality in Mobile Technologies

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 The Concept of Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 AR in Mobile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Place . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Two Design Dimensions of Mobile Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Place . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Game Illustrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Sky Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Field Trip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Google Expeditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Google Earth VR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 The Climb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 The Blu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Pokémon Go . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 Landlord Real Estate Tycoon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Intersection of Location and Place . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Quadrant I: Both Location and Place (True AR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Quadrant II: Only Place . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Quadrant III: Neither Location nor Place (True VR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Quadrant IV: Only Location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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A. Chauhan (*) Department of Computer Science, Utah State University, Logan, UT, USA e-mail: [email protected] W. Lewis · B. K. Litts Instructional Teaching and Learning Sciences Department, Utah State University, Logan, UT, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_104

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6 Significance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Augmented reality (AR) integrates virtual objects in real environments in real time. It is becoming widely adopted in education, entertainment, and beyond. In this chapter, authors introduce “location” and “place” as two key design dimensions for designing AR-based mobile technologies for learning. “Location” is defined as the user’s physical location, and “place” is defined as the user’s engagement with the physical location she/he is in. Authors further operationalize “location” and “place” as independent constructs and map out their intersection using a quadrant-based framework. In each quadrant, a mobile application is presented to illustrate how this framework informs and contextualizes designs and developments in mobile technologies. The framework introduced in this work aims to highlight the importance of “location” and “place” when designing AR-based educational technologies.

1

Introduction

The ubiquity of smartphones and low-budget tools such as Google Cardboard provides an easy access to experience augmented reality (AR) and virtual reality (VR) (see ▶ Chap. 79, “VR and AR for Future Education”). This proliferation has fundamentally shifted the conversation around learning with technology both in and out of classrooms. The use of AR in mobile technologies has immense potential for educational purposes. AR bridges formal and informal learning by enabling learning in ubiquitous, collaborative, situated, and immersive environments and helping visualize the invisible in 3D perspectives (Squire and Jan 2007; Squire and Klopfer 2011; Wu et al. 2013) (see ▶ Chaps. 75, “Augmented Reality and 3D Technologies: Mapping Case Studies in Education” and ▶ 77, “Augmented Reality in Education”). This new type of teaching and learning afforded by AR has shown to improve and/or increase learning performance, learning motivation, student engagement, and positive attitudes (Bacca et al. 2014). When transitioning toward designing AR learning experiences, it is important to consider the design trade-offs of these experiences to ensure that researchers, designers, and educators effectively and efficiently leverage its affordances to support learning. Past studies show that there are three primary issues, namely, technological, pedagogical, and learning, when implementing AR in education (Wu et al. 2013). Technological issues comprise of cumbersome and expensive design (e.g., head-mounted displays), improper interfacing and/or integration between multiple devices (leading to issues while navigating between reality and fantasy), device failure, and trade-off between location dependency-ones that

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Table 1 Location and place – the two design dimensions for AR-based learning technologies Design dimensions Location Place

Definition User’s physical location User’s engagement with his/her physical location

provide new meanings to familiar locations and location independency-ones that are portable, flexible, and could save cost on transportation (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Pedagogical issues comprise of constraints from schools and resistance among teachers and instructional design (i.e., the distribution and flow of information between two realities and multiple devices). Learning issue includes cognitive overload, when applying and synthesizing multiple complex skills in spatial navigation, collaboration, problem solving, technological manipulation, and mathematical estimation (Wu et al. 2013). Designers of AR should make efforts to minimize these issues and maximize the use of capabilities of mobile technologies (such as GPS capabilities). The aim of this chapter is to present a new set of design dimensions necessary for designing AR experiences for education. Overall goal is to consider the locative and place-based features of AR-based mobile technology in the context of learning theory and present a framework to inform future learning designs and applications of mobile technology. Lave and Wenger (1991) define “learning” as something, i.e., is situated in learner’s everyday experiences and the social settings she/he experiences. Therefore, designers must carefully choose the different types of contextual engagements to support their design. Hence, this chapter introduces “location” and “place” as two design dimensions for designing AR-based learning experiences (see Table 1). These two design dimensions make up four quadrants, which any educational app can map onto. This framework complements Wu et al.’s (2013) claim that AR could enable more situated learning. The goal of this framework is to aid educational app designers by helping them leverage the fullest potential of AR technologies. This framework helps understand the two dimensions of AR, location and place in detail, and analyze the affordances when considering either of the one or both of them as parameter(s) for learning technologies.

1.1

Motivation

This chapter is built on the work of Litts and colleagues, who identified five dimensions of mobile technologies that connect theory and practice: place, embodiment, narrative, identity, and design (Litts et al. 2013). The goal of this chapter is to explore the “place” dimension of mobile technologies in depth and conceptualize “location” and “place” as two separate and independent entities. This is important as there is a significant difference between being at a location and being engaged with that location. The expansion of the “place” design dimension also informs the design of mobile technologies for situative learning (ones that engages learners with their physical location) contexts using AR.

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Context

Affordances offered by mobile technologies, such as portability, context sensitivity, connectivity, and ubiquity, make them as ideal learning tools (Klopfer 2008). To make full use of these affordances, mobile technologies have evolved from basic phones to smartphones to smart kits, such as MS HoloLens, Oculus Rift, HTC Vive, etc. (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). In this section, authors first discuss the concept of reality, a continuum that stretches from real environment to a virtual environment. Further, they discuss the use of AR in mobile and the importance of location and place in designing learning technologies.

2.1

The Concept of Reality

Virtuality continuum, as shown in Fig. 1, has real environment (completely real) on its one end and virtual environment (completely fictional) at the other end. In the middle of the real and the virtual environment lies augmented reality (AR) and augmented virtuality (AV) (Milgram and Kishino 1994). AR is when the display of real world is augmented by means of virtual objects, whereas AV is when the display of virtual world is augmented by the means of real objects. Mixed reality (MR) is a subclass of virtual reality (VR) that merges the real and the virtual environments (Milgram and Kishino 1994). The focus of this chapter is on the AR. AR is when the 3D virtual objects are integrated into a real environment in real time (Azuma 1997). Applications of AR include medical, manufacturing and repair, annotation and visualization, robot path planning, entertainment, military aircraft, etc. (Azuma 1997). In this chapter, authors explore the use of “location” and “place” dimensions of AR in learning.

2.2

AR in Mobile

Leveraging smartphone affordances, such as GPS, camera, object recognition and tracking, voice and motion detection, etc., is crucial for supporting learning. The best use of mobile affordances will create immersive learning experiences that will enable learners to see the world around them in new ways. Immersion in digital environments enhances learning by allowing multiple perspectives within a specific context (situated learning) (Dunleavy and Dede 2014). Fig. 1 Virtuality continuum (Milgram and Kishino 1994)

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Location and Place: Two Design Dimensions of Augmented Reality in Mobile. . .

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Location

Past studies have often used “location” and “place” interchangeably. However, in this chapter, these parameters are used as two distinct entities, one (location) as the learner’s physical location and the other (place) as the learner’s engagement with his/her physical location, respectively.

2.4

Place

Gruenewald (2003) refers “place” as a “community” with the perceptual, sociological, ideological, political, and ecological dimensions. Smith and Sobel (2010) also describe place as something inseparably intertwined with the community. Definition of “place” for this work is also somewhat congruent with the above definitions, where authors define “place” as the learner’s engagement with his/her physical location and not merely his/her physical location.

3

Two Design Dimensions of Mobile Technologies

“Location” and “place” are two of the many dimensions for designing mobile technologies. Definitions of “location” and “place” on the continuums and their usefulness in learning are discussed in the following subsections.

3.1

Location

“Location” is defined as the user’s physical location. In reference to this definition, one end of the “location” spectrum consists of “location agnostic” apps, while the other end consists of “location-dependent” apps (see Fig. 2). Location agnostic apps are the apps that do not make use of user’s physical location. Examples of location agnostic apps include Google Expeditions (an app that allows users to take virtual trips all over the world), Google Earth VR (an app that allows users to explore world in VR environments), The Climb (an app that allows users to climb in VR environments), and The Blu (an app that allows users to explore oceanic lives in VR environments). Though the location agnostic apps give users the flexibility of using them from anywhere, the downside is that they disconnect or distract the users from their surroundings. Location-dependent apps are the apps that require users to be at a designated location to access the app. Examples of locationdependent apps include Sky Map (an app that shows the names of celestial bodies present over user’s head), Field Trip (an app that notifies users about interesting nearby locations), Pokémon Go (a popular mobile AR game in 2016), and Landlord Real Estate Tycoon (an AR app that allows users to buy, sell, and trade real-world properties). All these apps require users’ physical location. Though the locationdependent apps take users out to particular locations, they may or may not always

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Fig. 2 Location continuum

Fig. 3 Place continuum

connect users with those locations. For example, in Pokémon Go, players go to poke stops but do not really engage or learn about those locations. Learner’s physical location is useful in learning as it provides gateway to real world, such as under the sky, on the busy streets, in the botanical garden, etc.

3.2

Place

“Place” is defined as the user’s engagement with his/her physical location. Therefore, while one end of the “place” spectrum has “no engagement with place,” the other end of the spectrum has “engagement with place” (see Fig. 3). Apps that fall under “no engagement with place” criteria are the apps that do not engage users with their physical location. Examples of such apps include The Climb, The Blu, Pokémon Go, and Landlord Real Estate Tycoon. Apps that fall under “engagement with place” are the ones that engage users with their location. Examples of such apps include Sky Map, Field Trip, Google Expeditions, and Google Earth VR. It should be noted that the apps that cause engagement with place don’t really require users to

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be at specific locations. For example, Google Expeditions teach users about a high rise in Dubai, without requiring them to be physically present in Dubai or in that building. Place is an important factor to consider, when designing AR applications for learning. Based on the extent a learner is engaged with, his/her surroundings affect his/her learning motivation. Place also plays a key role in designing immersive experiences, one where the learner is immersed into the application.

4

Game Illustrations

To demonstrate the use of mobile technologies in influencing learning, authors present eight apps outlined in Fig. 4. These eight apps fit into one of the four quadrants that depict the intersection of the “location” and “place” dimensions of mobile technologies. Each quadrant has two examples. Quadrant I includes Sky Map and Field Trips, apps that engage users with their physical location. Quadrant II includes Google Expeditions and Google Earth VR, apps that educate users of distant places. Quadrant III includes The Climb and The Blu, apps that take users into a virtual environment. Quadrant IV includes Pokémon Go and Landlord Real Estate Tycoon, games that take users to a specific location but don’t really engage them with that location. Details of these apps and why they fit into a particular quadrant are given below.

4.1

Sky Map

Sky Map (see Fig. 5) is a handheld planetarium for Android devices (https://play. google.com/store/apps/details?id=com.google.android.stardroid&hl=en#details-re views). On pointing an Android device such as a mobile phone or tablet toward the Fig. 4 Two-dimensional framework of location and place

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Fig. 5 Sky Map icon

Fig. 6 Field Trip icon

sky, Sky Map shows the names of the stars, planets, and other celestial bodies present over users’ head. The app was developed by Google in 2009 but was open sourced in 2012. Sky Map doesn’t require Internet connection, except when putting one’s location. This can be done without Internet, by adding the latitude and longitude of the user’s location. Sky Map is free of charge and is available on Google Play. It is a fit for Quadrant I because (1) it is sensitive of user’s physical location and (2) it engages the users with the physical location they are in. The app influences learning by educating users about the part of the universe above their head.

4.2

Field Trip

Field Trip (see Fig. 6) is available for android and apple devices and glass (https://www.fieldtripper.com/). The app runs in the background of the users’ phone and notifies them as they get close to an architecture, historic place and events, lifestyle, offers and deals, food drinks and fun, movie locations, outdoor art, and obscure places of interest. In addition to notifying users about an interesting nearby location, it gives users an option to read more about that location. When the app is used in conjunction with a Bluetooth or headset, it can also read aloud that information for the users. This is ideal even while the user is driving. Users can also

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Fig. 7 Google Cardboard viewer

share their travel experiences using Field Trip through email and social networks. Field Trip is a fit for Quadrant I because (1) it is sensitive of user’s physical location and (2) it engages the users with the physical location they are in. The app influences learning by informing users about the interesting things near them.

4.3

Google Expeditions

Google Expeditions (see Fig. 7) allows users to lead or join immersive virtual trips all over the world by putting their phones into a Google Cardboard viewer or using their mobile devices in a 2D magic window mode (https://edu.google.com/expedi tions/#about). The app allows users to explore historical landmarks, dive underwater with sharks, or visit outer space. It connects the devices on the same Wi-Fi network, though if an expedition is pre-downloaded, no Internet connection is required to run it. The app is free of cost and is available in multiple languages. It is a fit for Quadrant II because (1) it works irrespective of user’s physical location and (2) it engages users with a remote “real” location. The app influences learning by educating users about different places.

4.4

Google Earth VR

Google Earth VR (see Fig. 8) is available for Oculus Rift and HTC Vive (https://vr. google.com/earth/). It is free of cost but requires VR headset. The app puts the whole world in front of users, letting them explore whatever part of earth they are interested in. Google Earth VR is a fit for Quadrant II because (1) it works irrespective of user’s physical location and (2) it engages users with a remote “real” location. The app influences learning by allowing users to see 360 views of the places and geographical features all around the world.

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Fig. 8 360 views of Space Needle, Seattle, USA

Fig. 9 The Climb

4.5

The Climb

The Climb (see Fig. 9) lets users do rock climbing in VR environments. The app is developed by Crytek and is built on the CRYENGINE (http://www.theclimbgame. com/). It is built for Oculus Rift and costs $49.99. The app features include solo climbing, racing with other players, and bouldering. The Climb has four immersive environments by day and night. It has a tourist mode, a simplified version which is ideal for introducing to beginners. The app does not require Internet connection but requires the Oculus head gear to enjoy the experience. The Climb is a fit for Quadrant III because (1) it works irrespective of user’s physical location and (2) it engages users with an “unreal” location they are virtually in. The app influences learning by exposing users to the simulations of rock climbing, where they can learn and/or practice climbing skills without the fear of falling.

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Fig. 10 The Blu

Fig. 11 Pokémon Go icon

4.6

The Blu

The Blu (see Fig. 10) is an immersive VR series that allows users to experience the ocean through different habitats (https://www.oculus.com/experiences/rift/9842940 25016007/). The app is available on Oculus Rift and costs $9.99. The app doesn’t require Internet connection but does require Oculus Rift to get the under-ocean experience. The Blu is a fit for Quadrant III because (1) it works irrespective of user’s physical location and (2) it engages users with an “unreal” location they are virtually in. The app influences learning by exposing users to the ocean life without a risk of getting harmed.

4.7

Pokémon Go

Pokémon Go (see Fig. 11) is an app designed for android and apple platforms (http://www.pokemongo.com/). It is free of cost but requires Internet connection. Pokémon Go requires users to visit poke stops to find Pokémons. The app is built in such a way that your device would notify you as you get closer to a Pokémon. Users can catch, hatch, evolve, and fight Pokémons. Pokémon Go is a fit for Quadrant IV

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Fig. 12 Landlord Real Estate Tycoon icon

because (1) it is sensitive to user’s physical location and (2) it engages users with the “unreal” objects located at the location they are in. The app influences learning by teaching users the skills of navigation.

4.8

Landlord Real Estate Tycoon

Landlord Real Estate Tycoon (see Fig. 12) is an AR property game that lets users buy venues as they visit there and then earn rent as people check in at those properties in real time (https://landlordgame.com/#Home). The app allows users to buy, sell, and trade famous properties, such as San Francisco’s Golden Gate Bridge. It is free of cost but requires Internet connection. Landlord is a fit for Quadrant IV because (1) it is sensitive to user’s physical location and (2) it engages users with the “unreal” aspects of the location they are in. The app teaches users the skills of navigation, decision making, negotiation, money, and real estate.

5

Intersection of Location and Place

“Location” and “place” are two separate entities that may or may not simultaneously exist. Based on this understanding, we depict the relationship of “location” and “place” using a quadrant-based framework.

5.1

Quadrant I: Both Location and Place (True AR)

The first quadrant utilizes both the “location” and “place” aspects of mobile technologies. Apps in this quadrant include “Sky Map” and “Field Trip.” Both these apps engage the users with their physical locations. For example, “Sky Map” takes users outside under-sky and engages them with the sky above their head. Similarly, in “Field Trip” users need to be at a location to learn about it. Quadrant I is an example of AR, where the virtual objects supplement the real environment. Apps in this quadrant make users aware of their surroundings.

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Quadrant II: Only Place

The second quadrant educates users about their virtual location. Examples of the second quadrant include “Google Expeditions” and “Google Earth VR.” Both these apps facilitate remote learning. For example, using “Google Expeditions” users can learn about different landmarks without visiting to those locations physically. Similarly, in “Google Earth VR,” users can learn about all the continents and geographical features remotely.

5.3

Quadrant III: Neither Location nor Place (True VR)

Apps in the third quadrant neither require users to be at specific physical locations nor educate users about their physical location. This quadrant is a perfect example of VR, where users are taken away from their real surroundings to an imaginary world. Example apps in this quadrant include The Climb and The Blu. The Climb lets users climb the imaginary mountains, the ones inspired from real mountains. Similarly, The Blu takes users to a journey in the ocean, where they virtually dive deep to explore whales and other ocean life. The experiences users have from these apps are designed and not real. Therefore, the learning they have here is about fictional (which mimics or is inspired by real, but not real) objects and not real things.

5.4

Quadrant IV: Only Location

The fourth quadrant requires users to be at a particular physical location, but doesn’t really engage them to that location. Apps in this quadrant include Pokémon Go and Landlord Real Estate Tycoon. Both these apps require users to be at specific locations, but instead of letting them engage with those locations, these apps force users to interact with the virtual objects present there.

6

Significance

“Location” and “place” can play a very important role in the future of educational AR applications, but these two dimensions must work together to create better learning experiences, “location” being the requirement that a learner must be in a specific area to experience the app and “place” being the engagement the learner has with the location she/he is in. Designing experiences with both “location” and “place” in mind can result in designs that build mobile interactions that include more situated learning, or learning in learner’s specific context, in the activities she/he is already in. The first quadrant of our framework outlines games of this nature. Moreover, the full use of the first quadrant, which uses both the “location” and “place” design dimensions, can produce AR games that are more situated. This situatedness comes when AR supplements the real world by overlaying digital

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objects on it, thus providing users just-in-time information about their surroundings, also enabling them to experience their surrounding in a way they have never done before. While the other quadrants may provide opportunities for learning, this learning is not in the learners’ real, daily contexts. This framework aims to help designers see the AR possibilities outside-the-classroom.

7

Conclusion

To aid designers in creating AR experiences that better support situated learning, authors here presented a framework made up of two design dimensions: location and place, location being the learner’s physical location and place being the learner’s engagement with that location. These two design dimensions make up four quadrants of a plane. Location is the x-axis that goes from location-agnostic to location-dependent, and place is the y-axis that goes from engagement with location to no engagement with location. Every AR mobile experience can be mapped onto this framework to determine how the design employs these design dimensions. It can be easy to fall into the idea that learning occurs only in formal learning environments like the classroom, but this framework presents two design dimensions to show designers the possibilities of AR outside of the classroom. AR can facilitate situated learning wherever the learner is like it has never been done before. Authors, in this chapter, argue that the AR and mobile experiences that are location-dependent and engage learners with their location provide the best experiences for this situated learning or learning that can take place in the social context it applies to. This is because, only when a mobile experience requires learners to be in a specific location, and engage with that location through AR, they are truly taking part in a situated experience that results in being in that place, not just in that location. As AR technology grows in education, future researchers must not forget about situated opportunities simply because the technology now makes it easier to access virtual locations in the classroom. On the flipside, designers must also not forget the importance of place just because technology can now overlay new worlds on top of our real world. Future research should continue to explore the intersection of location and place in AR as a way to make situated learning a learner’s reality.

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Cross-References

▶ Augmented Reality and 3D Technologies: Mapping Case Studies in Education ▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ VR and AR for Future Education

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References Azuma, Ronald T. 1997. A survey of augmented reality. Presence: Teleoperators and Virtual Environments 6 (4): 355–385. Bacca, Jorge, Silvia Baldiris, Ramon Fabregat, Sabine Graf, and Kinshuk. 2014. Augmented reality trends in education: A systematic review of research and applications. Educational Technology & Society 17 (4): 133–149. Dunleavy, Matt, and Chris Dede. 2014. Augmented reality teaching and learning. In Handbook of research on educational communications and technology, 735–745. New York: Springer. https://doi.org/10.1007/978-1-4614-3185-5_59. Gruenewald, David A. 2003. Foundations of place: A multidisciplinary framework for placeconscious education. American Educational Research Journal 40 (3): 619–654. Klopfer, Eric. 2008. Augmented learning: Research and design of mobile educational games. Cambridge, MA: The MIT Press. https://doi.org/10.7551/mitpress/9780262113151.001.0001. Lave, Jean, and Etienne Wenger. 1991. Situated learning: Legitimate peripheral participation. Cambridge, UK: Cambridge University Press. https://books.google.com/books/about/Situated_ Learning.html?id=CAVIOrW3vYAC. Litts, B. K., Smith, G., Gagnon, D., Martin, J., Mathews, J. 2013. Situated learning and mobile technologies: Connecting theory to design. In C. Willaims, A. Ochsner, J. Deitmeier, & C. Steinkuehler (Eds), Proceedings of the ninth annual Games+Learning+Society Conference (pp. 210–215). ETC Press: Pittsburgh, PA. Milgram, Paul, and Fumio Kishino. 1994. A taxonomy of mixed reality visual displays. IEICE Transactions on Information and Systems 77 (12): 1321–1329. Smith, G.A., and D. Sobel. 2010. Place-and community-based education in schools. New York: Routledge. Squire, Kurt, and Mingfong Jan. 2007. Mad city mystery: Developing scientific argumentation skills with a place-based augmented reality game on handheld computers. Journal of Science Education and Technology 16 (1): 5–29. Squire, Kurt, and Eric Klopfer. 2011. Augmented reality simulations on handheld computers. Journal of the Learning Sciences 16 (3): 371–413. https://doi.org/10.1080/105084007 01413435. Wu, Hsin-Kai, Silvia Wen-Yu Lee, Hsin-Yi Chang, and Jyh-Chong Liang. 2013. Current status, opportunities and challenges of augmented reality in education. Computers & Education 62 (March): 41–49. https://doi.org/10.1016/j.compedu.2012.10.024.

Wearable Technologies as a Research Tool for Studying Learning

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Jimmy Jaldemark, Sofia Bergström-Eriksson, Hugo von Zeipel, and Anna-Karin Westman

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Spy Glasses as a Tool for Data-Collection: Two Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 The Lab-Work Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 The Excursion Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Lessons Learned . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Ethics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Technology and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Selection and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter discusses the potential that wearable technologies have for studying and understanding how people learn. In particular, the focus is on how spy glasses can be used as a tool for collecting data from educational situations. The chapter reports on two different cases investigated by the authors in which spy glasses were used, including considerations made from a methodological point of view. From the first case a conclusion drawn is that spy-glass recording made it possible to closely follow teaching and learning during science lab work and identify specific elements not found in video data from ordinary video cameras. The second case reports on valuable information about how the motivation to learn

J. Jaldemark (*) · S. Bergström-Eriksson · H. von Zeipel · A.-K. Westman Mid Sweden University, Sundsvall, Sweden e-mail: [email protected]; sofi[email protected]; [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_105

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works in young children. Drawing further on these studies, the chapter elaborates on themes that arise as central to video research: ethics, technology and methodology, as well as selection and analysis. The chapter discusses a transformation in how childhood is considered in relation to new technology. Here children are seen as being more active and participatory in the shaping of their own childhoods. This can also result in developing new research methods in order to understand and visualise the child’s perspective, and using wearable technologies could certainly be one of these areas. In other words, it is a unique perspective when participants are co-creators of research studies. This suggests that important work awaits future research, developing and applying wearable technologies for education and educational research.

1

Introduction

As a result of technological developments, mobile devices have become a part of many people’s everyday life. This has led to lifestyles where such devices are integrated into human existence. This development has had an impact on many aspects of such lifestyles, and the technology’s impact also bears a relationship to learning processes. This relationship between mobile devices and learning is linked to participation in learning tasks in formal or non-formal educational settings as well as informally emerging learning that occurs during the performance of everyday activities or while working. The relationship is conceptualised and studied under various terms, such as augmented learning, mobile learning, technology-enhanced learning and ubiquitous learning. In this chapter, it is discussed in terms of mobile learning. The field of mobile learning has emerged since the dawn of the millennium and is focused on how mobile devices relate to learning as a communicative process that is inseparable from content, context, social group, and physical location (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Moreover, these aspects also relate to learning as a phenomenon that is dispersed over time (Kukulska-Hulme et al. 2011). Nevertheless, the study of mobile learning as a field remains immature (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). This is particularly true with respect to rapid technological development, including a such a rate in the introduction of new devices and applications (see ▶ Chaps. 79, “VR and AR for Future Education” and ▶ 77, “Augmented Reality in Education”). This rapid development also points to a need to develop methods to study the impact of mobile devices on human learning. So far, only a few publications have focused on methodological aspects of researching the impact of mobile devices on learning (e.g. Pachler et al. 2011; Vavoula et al. 2009). Examples of devices that have been used as a tool to enhance learning are handheld devices such as smartphones and tablets and various wearable devices, e.g. smartglasses or smart watches. While smartphones and tablets have received some attention over the years, wearable devices have received less. However, following the rapid development

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of the field of Internet of Things (IoT), scholars are just starting to understand the potential of such devices (see ▶ Chap. 22, “SmartLab Technologies”). A wearable is a device that is a “fully functional, self-powered, self-contained computer that is worn on the body ... (and) provides access to information, and interaction with information, anywhere and at anytime” (Barfield and Caudell 2001, 6). However, since the study by Barfield and Caudell, the concept of computers has evolved. It should be interpreted as a “shift from computers as detached tools to technologies as embodied companions that become extensions of self” (Bower and Sturman 2015, 344). From this definition it follows that wearables have at least three inter-related capabilities. First, such devices have the ability to observe physical surroundings, in other words, they are sensible. Second, these devices can analyse observations. Finally, they have the ability to send information about the analysed observations to other devices and applications (Atzori et al. 2010). These capabilities of wearable technologies present an opportunity to anchor scientific studies in everyday life while applications of wearable technologies have the “potential to support situated, embodied learning in real-world contexts” (Pegrum 2016, 415). This is an argument for the theme this chapter deals with: The study of learning with the help of mobile and wearable devices. At least two different deployments of wearables in research settings focused on learning are identified as enhancing learning and supporting the study of learning. The first one deals with how wearables could be used as an enhancement of learning (Barbee 2017). Studies of wearables in terms of enhancing learning have applied at least two different types of wearables, so-called fitness trackers and various kinds of glasses. Fitness trackers embrace technologies such as smart watches and digital wristbands and digital clothes. This type includes small mobile devices that usually deploy Bluetooth to sync information to other smart devices. An example of a wearable study in an elementary school setting includes smart clothes in the form of an e-textile shirt that helps children understand human anatomy by applying wearable visualisation and biometric sensing (Norooz et al. 2015). In a smart watch study scholars designed a wearable app that supported informal science learning for children between 8 and 11 years old. The smart WatchApp captured real-life stories from children by drawing from the children’s embodied experiences. A third example is taken from a higher education study in Japan (Ueda and Ikeda 2016). To meet societal demands on higher education in a situation with declining birth rate and an ageing population this study focused on developing a stimulation method for student learning. In the study, advancements within the field of IoT were integrated to measure the real-time status of students. The design included applications such as a learning management system (Moodle), wristbands, smartphones and tablets. The second type includes various kinds of glasses, e.g. smart glasses and spy glasses. Smart glasses augment reality by imposing digital information on a user’s view in real-world settings. A Swedish study included higher educational students designing smart-glasses applications for young pupils. The study explored the integration of learning expeditions in formal educational settings as a new way of enhancing learning, including students working on an open-ended problem-based task while being on the move (Jahnke et al. 2016). So-called spy glasses,

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also discussed in terms of point-of-view video glasses, may be less technologically developed than smart glasses but have built-in functionalities such as the recording of audio and video and in some cases also sensors to detect motion. Such wearables were used in a project that studied clinical training of nursing students. The study analysed the introduction of such technologies in laboratory settings (Metcalfe et al. 2015). The second deployment concerns how wearables could support data collection. However, few studies on this topic have been reported. Some of the studies focused on applications of spy glasses in formal educational settings. In the Swedish SONAT project, such deployment involves capturing communication between students and teachers in science classrooms (e.g. Eliasson et al. 2016; Sund 2016). Another study included an investigation of how teacher educators supported pre-service teachers analysing classroom communication (Estapa and Amador 2016). Overall, these studies produced promising results of supporting understanding of communicative aspects of learning from a participant’s point of view. A prominent feature of applying wearables as a research tool is the role of a participant’s agency. In particular, this is relevant in light of the state-of-the-art view of research on childhood (Esser et al. 2016). James (2009) points out that the origin of the understanding of children’s agency can be traced back to the 1970s. Up till then the view of childhood as a preparatory period for adulthood had gone unchanged, and children were seen as dependent receivers of the actions of adults. The new paradigm embraces children as being social actors who both create and are created by the circumstances they encounter. According to Corsaro (2011), a big change in childhood sociology is that children are seen as active and participatory in shaping and changing the reproduction of the childhood in which they participate. With the development of childhood as a social structural period, research on child and childhood also advanced (Lange and Mierendorff 2009; Qvortrup 2009). Further, research methods have been developed to try to understand and visualise the child’s perspective (Esser et al. 2016). The two cases in this chapter include children as co-producing agents of results, in terms of their actions recorded by wearables located on their bodies. The agency of the participants in the two cases differs regarding the design of the educational setting. One of the cases represents a classroom setting in terms of lab work, while the other case takes place in an outdoor educational setting during an excursion. The classroom setting affords less movement than the outdoor setting. Together these two cases afford a wider picture of how wearables can be used as a research tool. To sum up: this chapter deals with wearable technologies and the potential such applications have for understanding learning. The chapter focuses in particular on how wearables, specifically, spy glasses could be used as a tool for collecting data. Two different projects are reported as subcases. The chapter introduces the two cases, including critical illustrations from a methodological point of view. The chapter continues with lessons learned in these research projects. Finally, concluding remarks are made and suggestions given for future development. Before moving on to the two cases, a section about spy glasses immediately follows.

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Spy Glasses as a Tool for Data-Collection: Two Cases

The spy glasses used in both cases resembled normal glasses. The frame was black and slightly thicker than on normal glasses and it had room for a small memory card. On the bridge between the eyes were a camera and a microphone. Recordings were started and stopped by pressing a button on one of the sidepieces. Moreover, both models also allowed one to capture images. In the excursion case, the model used also included motion detection and could be used as a webcam. In both cases video and audio recordings were implemented. Both models of spy glasses required a USB cable to download the recordings onto a computer. The same cable was used for charging the built-in battery. Depending on the model, the battery could be used for 30–60 min of video recording. MicroSD-cards are used to store recordings (Fig. 1).

2.1

The Lab-Work Case

This case took place during a research project conducted in the period 2013–2016 with a focus on the relation between trends found in large-scale studies and how teaching and learning are constituted within science classrooms. Swedish students have shown declining results in large-scale studies such as PISA (OECD 2014) and TIMSS (Martin et al. 2012) since the turn of the millennium, and the aim of the project was to understand the declining results in classroom teaching and learning. All data in the project were collected during science lessons in grade 9 in a Swedish compulsory school; students were 15 or 16 years old. Data were collected in the form of two kinds of video recording: as recordings from cameras that capture the entire classroom situation from two corners of the room and from spy glasses worn by three or four students during lessons. The study presented in this chapter focused on student discussions during lab work and so used both types of recording. The project gathered a total of approximately 80 recorded lessons.

Fig. 1 Images of spy glasses used in both cases. Left: glasses used in the lab-work case; right: glasses used in the excursion

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In previous research, lab work in science education was questioned with respect to its contribution to learning (Hofstein and Lunetta 2004). The study presented here aimed to analyse two aspects of lab-work situations. First, an analysis was done regarding the guidance designed by the teacher, and this included oral and written components. Secondly, we analysed what the students focus on in their discussions during the lab work. Against a background of findings from previous research (Hofstein and Lunetta 2004; Jenkins 1999; Wellington 1998) we constructed three general categories for teacher guidance and student negotiations: scientific ideas, laboratory skills and knowledge of the scientific method. Data collection was designed to effectively capture these situations, and the spy glasses contributed to this end in a valuable way. For the analysis, we studied both classroom views and the spy-glass recordings in search of situations where students negotiated the contents of lessons, but we quickly came to the realisation that the spy glasses were more effective. The spy glasses were checked to make sure they had fully charged batteries and enough space on the memory card for collecting data. Such preparation was simple but absolutely necessary. The researchers had also made dry-run recordings with the spy glasses prior to data collection. Prior to data collection, on an earlier occasion, the students received information about how the recordings were planned to take place, that they would be asked to carry the glasses and that the glasses recorded both picture and sound. A typical lesson that included lab work started with an introduction from the teacher. The introductions ended when the teachers told the students to move on with their own lab work. At this stage, the spy glasses were distributed among the students on a voluntary basis. Depending on how many students volunteered, the glasses were distributed to as many lab groups as possible. Usually, two or three students did the lab work together, and in the vast majority of cases, there were enough volunteers to distribute three or four glasses to different lab groups. All students that participated in the study had given their consent prior to data collection. The students who declined participation conducted their lab work out of sight of the camera, and no one in their lab group carried spy glasses. The recordings from the spy glasses made it possible to follow students while they carried out their lab work. The spy glasses also made it possible to follow the interplay among students, with their teachers and with the material, both the physical laboratory equipment as well as the literature. Our main focus was on those occasions when students posed questions about the lab work to peers or teachers. We consider those occasions to be moments of potential learning, and in the analysis, we grouped the content of the talk into three categories: scientific ideas, laboratory skills and knowledge of the scientific method. The recordings from the spy glasses made it possible to identify when the students were engaged in discussions with peers or teachers. It was also possible to follow how students sometimes consulted the literature to solve a question that arose during lab work. From these recordings we were able to conclude that students discussed the categories laboratory skills and scientific ideas to a greater extent than knowledge of the scientific method. The fact that teachers emphasised scientific ideas

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connected to the lab work was no guarantee that the students would discuss the same idea among themselves. We also found that the chances of such a discussion increased if the students had encountered the ideas prior to the lab work or if the lab assistant asked for an explanation of the observed phenomena. Compared to camera recording, it was possible not only to pick out more details (audio and video) but in some instances, the spy-glass recordings actually gave completely different angles on what was taking place. For instance, in one lab work situation, one participant (not wearing spy glasses himself) was moving constantly among the other students, talking and laughing, from the video camera recordings appearing to act mostly as disturbance and not taking the teaching situation seriously. However, from the spy-glass recordings it became clear that he was at the same time leading his lab group and communicating (scientifically) with other groups. In another example, one student was talking with the teacher about how to answer some study questions. The recording on the spy glasses made it possible to follow what the teacher said and see the student’s interpretation of the teacher’s words in the answer the student wrote and in the list of follow-up questions the student came up with for the teacher. The recordings made it possible to follow the whole course of events and allowed the researchers to follow how teaching and learning in science education could occur.

2.2

The Excursion Case

In the summer of 2016, the use of the game Pokémon GO, a location-based game, exploded, and it would go on to be a bigger success than anyone had ever imagined. In the first week, the game became the most downloaded app ever, and the breakthrough is unprecedented. In the game, players move on a real-world map, with houses, roads and water correctly indicated. On the map, Pokémon pops up to be captured by players throwing virtual balls on them. Players must therefore move physically to places where monsters exist, and the game also encourages long walks. The Pokémon GO study aims at describing how the implementation of mobile technology in elementary schools could support learning processes regardless of the classroom’s physical constraints. Today, research is conducted on how physical settings interface with children’s learning and development in schools, and learning situations are not seen as something that happens between pupils and teachers and as interplay between individuals and physical space. To the didactic questions “what?,” “how?” and “why?” should be added “where?”. One rarely asks the question of where learning will happen. The room is often seen as something obvious, but today more and more demands are being place on teachers to design learning situations (Kress and Selander 2012). Szczepanski and Andersson (2015) write that the more memory systems that are activated in memorisation and learning, the more support the learning has. An outdoor setting may, the authors assert, have this complementary role in teaching.

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They argue that “it is in the body-related place in time and space that knowledge can be transformed and acquire new dimensions that in turn can open new perspectives on things that seem to be obvious” (2015, 145). This project originated in an interest in what happens in the interplay between the individual and the environment when a mobile device is featured as a mediating artefact. In what way do children discover the opportunities that exist in the real physical world while simultaneously discovering possibilities through the mobile phone as an artefact? There was also an interest in how schools can use and utilise what children are interested in during their spare time in order to spur motivation to learn traditional subjects using the mobile devices that the children use. In autumn 2016, two meetings were held to meet teachers at a primary school in a smaller municipality in Sweden. The teachers were informed of our interest in studying the use of mobile technology in school. It was decided to implement the study in two classes, a fifth-grade and a sixth-grade class. The teachers were instructed to plan a lesson in subjects social science and mathematics, where the students were expected to be outdoors and use mobile phones and play Pokémon GO. By “outdoors” is meant the physical setting in the school’s vicinity. At a meeting at the school, parents were informed of the project and about the need to have their signed permission for their children to participate in the project and be filmed. Each class was then divided into groups of three to four students. The lessons that would form the basis for the data collection were planned to occur during a walking tour in the vicinity. The walks included Pokémon stops where the teachers planned to teach. Each group went on two walks together with a teacher. Each walk took about 30 min to complete. The teacher and students played Pokémon GO while following the walk planned in advance by the teacher. Before the start of the walk, the children were informed of the purpose of the study and what would happen over the course the study, and they were told why they should wear the glasses. They were then shown the spy glasses and were allowed to examine them before putting them on. Before the glasses were passed out, the wearers were filmed with the pair of glasses they would wear because each pair of spy glasses was coded so as to be able to associate it with its wearer. Class photos of the groups were also used to ensure that a particular pair of glasses could paired with the right individual. In addition to the students’ use of the spy glasses, the teacher also used a pair of spy glasses to try to capture data based on a given person’s perspective. Using these glasses allows the wearer to capture documents and communication from the perspective of both students and teachers. In combination with the spy glasses, a simple handheld camera was also used to obtain a complete picture of the multiple perspectives captured by the spy glasses. The video material from the observations and lesson plans enabled a description of what students and teachers actually did when they played Pokémon GO during the outdoor-based lesson. Student and teacher reflections were captured using interviewing techniques. This also enabled us to describe how teachers and students perceive the implementation of mobile technology in teaching.

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Each student group were eqipped with one or two smartphones. The purpose of having only one or two smartphones per group was to stimulate collaboration among students. The direction and length of the walks were planned in advance by the teacher, so at the start of the walk the teacher instructed about the direction of the excursion. A researcher participated in the walk and filmed the group using a handheld camera. When the student group arrived at the planned stop, the teacher tried to draw the students’ attention to something, and the recorded material from the spy glasses shows them looking at what the teacher is talking about. The empirical evidence also shows how some students found it difficult to focus on the game and instead looked at the phone instead of looking up and paying attention to what the teacher was saying. In the discussion of what creates motivation and how to customise lessons to individual students’ specific needs, recorded material with spy glasses can provide valuable information and knowledge about how motivation to learn functions. Immediately in connection with each walk, group interviews were conducted with the student groups to capture their experiences and perceptions of the previous activity: what they thought of the walk, what they believed they had learned and what they liked about wearing the spy glasses. When all the groups had completed their walks, the teacher followed up the outdoor lesson with a lesson in the classroom for the entire class. This happened a few days after the walk. At the follow-up session, the teacher wore spy glasses while the researchers took field notes and made a recording with the handheld camcorder. The teacher then discussed with the students the contents of the outdoor activity. Teachers’ perceptions and experiences were followed up by interviews with teachers.

3

Lessons Learned

The experiences from the two cases yielded some general lessons. In what follows, these experiences are grouped under four headings following a suggestion in an article written by a group of video researchers (Derry et al. 2010). The article discusses how communication about research results can be enhanced if researchers can agree upon central challenges that need to be addressed in a transparent way. They suggest four themes they hold to be central in the area of video research: ethics, technology, selection and analysis. These themes can be applied to studies with spy glasses as well as other studies including other types of video material. The experiences connected to these themes from the two spy-glass studies in this chapter will be presented in what follows.

3.1

Ethics

Lange and Mierendorff (2009) emphasise that children’s perspective on various phenomena constitutes a new paradigm in research on children and childhood.

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Children’s perspective, however, is a manifold concept of great rhetorical capacity, and the concepts of children’s perspective and childhood should be further refined. The difference between these two expressions of speaking about children and their perspectives lies in distinguishing who formulates the perspective, the children themselves or someone who represents them. That difference defines the difference between the concepts. A child’s perspective is thus created by adults in their quest to pay attention to children’s perceptions, experiences and actions (Kampmann 2004; Mayall 2002). Sommer et al. (2013) argue that a child’s perspective represents children’s perceptions, experiences and understanding of their world. In relation to the discrepancy between children’s perspective and a child’s perspective, the two examples in this chapter are based on children’s perspective. Lange and Mierendorff (2009) argue that in the research on children’s perspective, the researcher tries to understand and visualise children’s actions and statements. The fact that participants themselves wear spy glasses that capture audio and images from where the participants target their focus is an exciting and unique way to collect data. Earlier it was discussed whether the number of microphones and camera angles could increase the possibilities of doing studies based on children’s perspective (Aarsand and Forsberg 2010; Silverman 2013). Spy glasses as a technique/method in a research context provide unique data that naturally represent children’s perspective. However, several methodological issues need to be discussed to develop a complete approach, which is what this chapter aims at. While the two cases discussed represent studies of children, the ethical issue is applicable in a more general sense. The application of spy glasses gives a perspective from the participant’s point of view. With the increased use of video recordings in research contexts, the Swedish Research Council has adapted how individual protection can be satisfied with the use of video in order to contribute to good practice (HSRF 1996). Still, the four research ethical principles are based on an information requirement, consent requirement, confidentiality requirement and utility requirement, which are HSFR’s generally formulated ethical principles. When using spy glasses as a research method, special attention must be paid to the consent requirement. When children wear these glasses and control what and on whom the camera will focus, there is little opportunity for the researcher to wrest control over the camera away from individuals who are not allowed to participate in the research. This difficulty in this type of data collection has been resolved in the present studies mainly by creating contexts where children who cannot be seen in the films do not participate and by retrospectively deleting sequences of children during editing of the recordings. However, there are occasions in our examples when children chose to leave the classroom to avoid being unintentionally filmed against their will. The children were better able to prepare for a recording when they knew in advance how and when the recordings were to take place. This issue is an aspect worth considering and discussing critically, but it is also important to continue developing and disseminating methods and approaches that meet these challenges.

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Technology and Methodology

In both these cases, advantages were found from using spy-glass recordings over video cameras, and these benefits are related to the kind of data collected. Spy glasses have the obvious advantage of closely following the wearer, which is very helpful since people tend to move around during excursions and lab work. The glasses record all actions from the viewpoint of the participant. On the other hand, the recording can become rather unstable and unpredictable. Head movements are more frequent and erratic than one might expect. Further, once the glasses are on, the researcher has no control over the situations recorded. The cases reported in this chapter were able to follow a few participants closely, but other people sometimes left one recording only to show up in another one later on. The data produced from spy glasses are not always easy to describe, compile and analyse. When several spy glasses are in use, it is possible to use different recordings, together with the overview of a recording, to patch up and reconstruct events and conversations. But this is very time-consuming and does not always capture the whole situation anyway. Some aspects of data collection are different once the researcher relinquishes control over the recording equipment. Preparation is obviously crucial, but no matter how meticulously one prepares, unexpected elements and events will arise in the data obtained from wearable technologies. Typically on wearable recording equipment, such as spy glasses, there is limited possibilities for controling the content during recording while there is no interface to interpret the ongoing recording. Hence, it is necessary to perform careful tests in advance. How long will the batteries last? What kind of data files will be produced? How do the glasses indicate record mode? How are they switched on and off? How easily can they be unintentionally switched off? In both cases discussed in this chapter, there were occasions when no data were obtained because the equipment were turned off prematurely. Another aspect of preparation is advance instruction to participants. Once the equipment is turned on and the session starts, the researcher has limited possibilities to control what is recorded and how. Researchers need to make as sure as possible that the equipment will stay on and follow participants actually taking part in the activities of interest. It is also necessary to know where in the recording space the glasses will move around; the researcher might want to assure that the recording equipment in use is evenly spread out during recording. Participants should be interviewed and instructed calmly and safely prior to recording. The time and effort spent choosing and preparing participants will be repaid in the form of increased chances of obtaining high-quality data. Further, habituation needs to be taken into account. Most people will be more aware of the glasses initially and then gradually start acting increasingly normal. An inevitable implication of spy glasses is the messiness of the recordings. Audio and video data will not always be easy to interpret. A pilot study will tell researchers more about what kind of data there will be and what kind of steps they can take to prevent loss of useful data collections. A complete overview of a situation is hard to come by from a set of individual spy-glass recordings. For complementary overviews from a video camera, recordings have proven to be very valuable.

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Selection and Analysis

Video material tends to be extensive; one lesson filmed from different angles produces twice or three times the length of material. This requires a well-defined methodology for selection. In cases where lab work is studied (in the excursion study the materials were not analysed by the time of writing), parts were selected where students discussed the lab work task and how to solve problems related to the performance of the task. It did not take long before the discovery was made that recordings from spy glasses told much more than recordings from cameras in the corners of the classroom. The analysis of the students’ discussion was performed with the support of computer-assisted qualitative data analysis software (CAQDAS), e.g. Atlas.ti or InVivo. Using CAQDAS the first selection of interesting parts in the recordings was made, and after this first selection, a more detailed analysis was made of the interesting parts. The discussions were categorised by codes for different content such as discussions about scientific ideas, about lab work skills or about knowledge of the scientific method. A method to enhance selection is in our opinion almost necessary since video material quickly becomes extensive. Using a first, rough selection of quotes with interesting content that can address the research questions, it is possible to analyse those quotes in a much more detailed manner.

4

Discussion

As indicated in the introduction to this chapter, a transformation is taking place in our understanding of childhood. This change consists of a new way to see children as being more active and participatory in the shaping of their own childhoods (Esser et al. 2016). In turn, this has resulted in the development of research methods in order to try to understand and visualise the child’s perspective, where the use of wearables is one method. The use of participatory tools can entail new positions and different relations between researchers and participants in a research study (Waller and Bitou 2011). In the two cases discussed in this chapter, it is described how children become co-producing agents of results since their actions are recorded by wearables located on their bodies. Despite the desirable aim of eliciting different perspectives, a few aspects are worth mentioning. The first is the question of controlling and owning the data. Another is the issue of how participatory research empowers children. Both of these aspects shed light on the issue of roles, that of the researcher and that of participants. It is about the power relations that exist and are created between researcher and researched (Christensen and James 2008). The use of spy glasses as a research method deconstructs the boundaries between seeing and being seen, and wearing spy glasses transforms the wearer into both observer and observed. Another dilemma of power is that this research method requires researchers to deal with the fact that they do not really have control over the material being collected. In particular, if the participants are children, there might be different opinions about what activities and actions are and are not meaningful. However,

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this demands of the researcher openness and respect for various individual perspectives (Emond 2005). Such demands are a prerequisite for a researcher that aims at taking advantage of the potential spy glasses could bring to their studies. Waller and Bitou (2011) critically pose the question of whether participatory research really empowers children. This chapter ends by concluding that a participatory approach entails further dilemmas in connection with ethics and power that need to be raised, discussed and addressed. What follows is a concluding discussion of possible future directions of using wearables as a research tool.

5

Future Directions

Wearables represent a field undergoing rapid development. This is particularly true in relation to developments in the field of Internet of Things. Such developments will probably lead to new functionalities incorporated within the current glass technology. Smart glasses and spy glasses will probably converge into one device. Current devices within the smart-glass field suffer from being too expensive and too physically conspicuous, which makes it hard to use them as tools for collecting data. Spy glasses are cheap and easier to use than smart glasses but have limited functionality. Their further development will probably make them economically affordable, lighter and easier to use with even better functionality. Ideas about their development borrowed from other wearables, such as wristbands, will probably find their way to smart glasses. In the end, these two categories of glasses, together with functionalities from other wearables, will intersect and afford new possibilities for research on participant perspectives. Subsequently, the unique situation where participants are co-creators of research studies will imply important future work (see ▶ Chaps. 77, “Augmented Reality in Education” and ▶ 79, “VR and AR for Future Education”). This will probably have a significant impact on the understanding of the concept of mobility and its relationship to learning as well as on research in many other fields and disciplines.

6

Cross-References

▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ SmartLab Technologies ▶ VR and AR for Future Education

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Augmented Reality and 3D Technologies: Mapping Case Studies in Education

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Teresa Cardoso, Teresa Coimbra, and Artur Mateus

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Augmented Reality and Its Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Augmented Reality in Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Learning anywhere, any time is becoming ever more a daily routine, due to the increasingly and recent growth of information and communication technologies (ICT). The key characteristic of ICT, namely, in the use of mobile equipment and software, has been their portability, mobility, and network access. The technological development, including software applications available for the implementation of three-dimensional contents, has been following this trend. Hence, it is important to know whether and how these three-dimensional contents are being T. Cardoso (*) LE@D, Elearning and Distance Education Lab, Department of Education and Distance Learning and Teaching, UID4372-FCT-MCTES, Universidade Aberta (Open University of Portugal), Lisbon, Portugal e-mail: [email protected]; [email protected] T. Coimbra LE@D, Elearning and Distance Education Lab, UID4372-FCT-MCTES, Universidade Aberta (Open University of Portugal), Lisbon, Portugal e-mail: [email protected]; [email protected] A. Mateus CDRsp – Centre for Rapid and Sustainable Product Development, Polytechnic Institute of Leiria, Marinha Grande, Portugal e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_84

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integrated in educational situations, namely, regarding augmented reality and mobile learning. Thus, a synthesis of Portuguese and international research works and case studies related to the use of three-dimensional augmented reality is presented, from a chronological perspective on the evolution of the information and communication technologies. The main goal of this knowledge mapping is to contribute to the state of the art in three-dimensional augmented reality technologies in education. In addition, it is aimed to frame the creation and implementation of three-dimensional content in higher education, specifically in the field of mathematics.

1

Introduction

Three-dimensional (3D) technologies, based either on tangible perception, such as the case of 3D printing, or on intangible perception, such as augmented reality (AR), are mature enough to be accessibly and efficiently applied and put to advantage in the field of education. Combining 3D technologies with information and communication technologies (ICT) increases the flexibility of their on-site or remote access and use. We are thus part of an ecosystem with optimal conditions for advancing teaching and learning through the development of contents that leverage resources currently available to us. In this regard, there is a great international exploratory momentum with the development of several research projects, which is also beginning to grow in Portugal. This chapter aims at mapping the evolution of 3D technology, particularly in the application of AR and 3D contents to teaching, and presents a synthesis of practical cases. Therefore, it begins by setting the context for the insertion of (intangible) three-dimensional technologies across the society. Then, some international and Portuguese works being developed using 3D technologies, mainly in education and teaching, are described. To this end, and in line with Cardoso et al. (2007, 2010, 2013), a thorough literature research was conducted, with a focus on recent years (between 2010 and 2017), with regard to the application to education, although the technological framework includes some facts and milestones from the last 80 years. Finally, part of the research work on intangible three-dimensional technologies, in particular the implementation of AR, is described, as well as how these technologies can be capitalized on on-site and remote educational situations. For this study, Google was searched using keywords and Boolean markers, including terms such as “augmented reality,” “tridimensional,” “teaching,” “mathematics,” and “m-learning.” Using the same descriptors, the literature search was complemented with a more focused search on b-on, the Online Knowledge Library, where the journals Computers and Education, Computers in Human Behavior, Journal of Systems and Software, Computer Science, Advances in Engineering Software, and Social Behavior Sciences were consulted. Furthermore, these sources are completed with a selection from ResearchGate automatic notifications, as well as from international scientific meetings on education technology using the same filters

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and descriptors. Searches were conducted during 2013 and 2014 and were updated at the end of 2016 and in June 2017. It should be noted that this study presents a chronological perspective of technological evolution of equipment and software, which currently translates into unique conditions for the effective implementation of three-dimensional technologies supported by AR and by ICT in the field of education. Therefore, the selected works, mainly published in papers, were conducted from the 1990s and reflect the developments from 1961 to the present. In addition, the search was not restricted to research work in Portugal, in part because the first finding of the mapping is that there is a reduced amount of work in this field being implemented in Portugal, although this trend has changed between 2014 and 2017. A corpus of 44 references was therefore created, mostly composed of international peer-reviewed scientific journals, giving priority to papers presenting a chronological evolution of augmented reality technologies, their relations with the evolution of ICT and, finally, to studies of three-dimensional content implementation of AR in higher education, in particular in mathematics courses.

2

Augmented Reality and Its Evolution

When talking about three-dimensional technologies, such as the ability to print three-dimensionally (3D printing), to capture 3D shapes (3D scanning), and to integrate virtual elements (AR) into the real world, it becomes apparent that 3D technologies advance alongside technological computer developments and are linked to the integration of ICT in our daily lives. An analysis of computer development will show some similarities to 3D technology development, as can be seen below. Intangible content 3D technologies, such as AR, are closely linked to computer capacity and calculation, and thus their availability is related to the development of personal computers. AR is defined as the integration of virtual images into the real world; this integration is performed using ICT. The reality is augmented with virtual elements: a mobile device with a camera, such as a tablet, a cell phone with Android or iOS operating system, or a computer enables anyone to access AR contents. The development of AR contents has been following computer and ICT technological developments. Figure 1 presents a chronological summary of the main events that contributed to the current state of the art in these areas (see also Table 1). For example, in 1961, the cinematographer Morton Heilig registered the patent of an innovative system, the Sensorama, which allowed the user to experience an immersive cinematic session. In 1968, Ivan Sutherland developed a computercontrolled immersive helmet (Carmigniani et al. 2011; Sutherland 1968). This was the first virtual and augmented reality, which was developed at Harvard University in Utah, USA. In the 1970s, this technology became known as Artificial Reality (Zhao 2009). Later, Myron Kruger, at the University of Connecticut, developed the Videoplace, which consisted of a living room for human-computer interaction. This

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Fig. 1 Historical evolution of AR and technological evolution milestones in computers, ICT, and image display systems. (Source: Data collected for this study)

system used information from a camera and transmitted to a computer and then projected on a screen, allowing interaction with Artificial Reality (Nagler 1994). In 1993, Feiner and collaborators published the first paper in the field of AR. The application they developed, named KARMA, was validated in technical staff training for printer maintenance. Two years earlier, Feiner (1991) had concluded that AR-based content would have an important role in training and that increasing its use only required a reduction in display system sizes and a more flexible usability (cf. Feiner et al. 1993). Indeed, viewing/display systems were relatively large, inflexible, and uncomfortable at that time. Research and development into this new perspective of the real world continued, mainly in military applications of NASA (National Aeronautics and Space Administration) for the training of pilots, astronauts, and military and in the medical field. Many innovations and developments in Artificial Reality never came to be applied successfully until Zimmerman and Lanier introduced the “dataglove,” a more user-friendly way to interact with the virtual environment (Sturman and Zeltzer 1994) in which users could manipulate objects in the virtual world through a glove. In 1989, Jaron Lanier coined the term virtual reality and was the first to bring the technology to the public, selling “datagloves” as a way into the virtual world (Zhao 2009). In 1990, the designation “augmented reality” was attributed to Tom Caudell, who created the term while working for Boeing to develop a head-mounted display system to help with wiring instructions for planes via the projection of plane schematics on boards at the factory (Vaughan-Nichols 2009). In 1994, this juxtaposition of virtual and real objects was explained by Milgram et al. as a continuum between real and virtual environments (see also Milgram 2006), as can be seen in Fig. 2. In 1997, Ronald Azuma (1997) wrote a report defining the scope of AR and listed three important criteria to define it, separating AR from “artificial and virtual realities.” Therefore, Azuma’s three criteria to define AT are combining the real

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Table 1 Historical evolution of AR and technological evolution milestones in computers, ICT, and image display systems. (Source: Data collected for this study) Year 1946 1961 1968 1970 1979 1981 1982 1985

1989 1990 1992 1993 1994

1997 1999 2000 2001 2002

2005 2007

2008 2009 2010 2013

2014

Iconic letter (cf. Fig. 1) – milestones E – 1st Computer: ENIAC S – Heilig invents a system that enables immersion in a virtual world through images: SENSORAMA h – Ivan Sutherland invents the 1st image display helmet m – Cooper develops the 1st mobile phone n – NTT opens a mobile phone network in Tokyo c – The 1st cellular phone system in the world is implemented in Denmark, Finland, Norway, and Sweden N – Nokia introduces car phones a – NASA develops multisensory systems for pilots and astronauts v – Myron Krueger develops a computer-controlled interactive laboratory without helmet mediation r – Jaron Lanier creates the term virtual reality; his company, VLP Research Inc., becomes the pioneer in the virtual reality market p – Personal computers (PC) become widespread A – Tom Caudell establishes the term augmented reality (AR) f – L. B. Rosenberg creates “virtual fixtures” K – The 1st paper on the application of AR in training, through the KARMA application, is published e – Milgram puts forward a continuum relating real and virtual environments, positioning AR as a mixture of reality and virtuality in the continuum Z – Zimmerman and Lanier develop a digital glove, thus introducing an easier way to interact with the virtual world D – Azuma describes the differences between virtual reality and AR, underpinning the latter’s main characteristics: it combines the real and the virtual, interactive in real time, registered in 3D H – Hirokazu Kato develops the ARToolKit I – Desktop Internet becomes widespread i – The iPod is launched b – Bruce Thomas launches the 1st outdoor game in AR: AR Quake F – Steven Feiner publishes “Augmented Reality: A New Way of Seeing,” in which he predicts how AR will be used in the future and says that “computer scientists are developing systems that can enhance and enrich a user’s view of the world” R – Prediction of the New Media Consortium (2005), in the Horizon Report, on the great impact that AR will have on teaching s – Smartphones are launched (1st iPhone) M – First marketing applications in AR P – Application of AR in medicine; use of helmets with AR content in the treatment of Parkinson’s patients W – Wikitude develops AR browsers for Android mobile phones: Wikitude AR Travel Guides L – Layar, a Danish company, introduces an AR-based browser for mobile phones = a turning point that allowed AR to reach the general public t – Mobile Internet becomes widespread; tablets are launched (1st iPad) g – Google Glass is launched 6 – The MIT Media Lab introduces the “Sixth Sense” 3 – The future of AR education: textbooks containing high 3D interaction AR contents G – Google markets AR glasses j – Jeff Powers and his team develop the Structure Sensor, which allows for the recognition of real-world shapes in AR

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Mixed Reality (MR)

Real Environment

Augmented Reality (AR)

Augmented Virtuality (AV)

Virtual Environment

Reality-Virtuality (RV) Continuum Fig. 2 Virtual reality continuum. (Source: Milgram et al. 1994)

and the virtual worlds, real-time interaction, and 3D presentation. From this moment, the development of AR grew and in 2002 the first AR outdoor game, called “Quake,” was presented (Thomas et al. 2002). In 2005, the Horizon Report described AR as a key technology to develop applications until 2010. In fact, the popularity and the development of smartphones have brought AR to users. At that time, two different AR forms were identified and defined: AR based on geographic location and AR based on marks or patterns. In the case of location-based AR, the use of the mobile’s GPS determines the location, and thus a layer of information is added on top of what we are seeing with the camera (Billinghurst 2011; Carmigniani et al. 2011). Two examples of applications working in this way are the Wikitude application, released in 2008, and the Layar application, released in 2009. Both are available for mobile devices. In AR based on marks or patterns, the mobile device (mobile phone, tablet or laptop camera) recognizes markers that give information or three-dimensional elements. The HITLab in New Zealand was the first to create AR markers on newspapers, which, for instance, would advertise the Wellington zoo. As soon as readers recorded the marker with their mobile device, a 3D animal appeared on the page (Schmalstieg et al. 2011). Another example of technological advancement is Google Glass, which appeared in 2012 for testing and was released to the public in 2013, when they began to be marketed in the United States. In 2017, a second version became available. Although the patent has been registered by Google, other applications have already been developed by other companies or are emerging and preparing to appear on the market. The incorporation of virtual elements into the real world now gains a new dimension. One example is the integration of technologies such as AR and threedimensional noncontact scanning, which enabled Jeff Powers and his team to develop a system which, in addition to allow viewing the real world through the “window” of a tablet, can scan the same real world so that the geometric boundaries of real-world elements are recognized in real time by overlapping AR virtual elements. An example of the integration of noncontact scanning technology with virtual content, namely, a sensor visual field scan identifying objects and their forms, can be found in http://structure.io, whereas an example of an application of the integration of noncontact scanning technology with virtual content can be seen on video on the Internet in http://youtu.be/39v5OoBJFDk. This new feature opens an even greater field of applications and ways of displaying contents. It represents the

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interaction between a set of balls that fall on a bench and its surroundings (Occipital 2013). In this case, the effect of gravity and of object borders is apparent. Many different applications are being developed with the expansion of ICT and accessibility to mobile devices. The potential application areas of AR cross all subjects. Several examples of these applications are presented below, especially those in education.

3

Augmented Reality in Education

Three-dimensional technologies are still at a very early stage of application in teaching and learning. Nonetheless, there are several fields of knowledge in which they have been implemented and studied by several authors (among others: Bujak et al. 2013; Fonseca et al. 2014; Kamarainen et al. 2013; Wojciechowski and Cellary 2013; Wu et al. 2013; Di Serio et al. 2013; Martin-Gutierrez et al. 2012; Nee et al. 2012; Kaufmann and Schmalstieg 2003). However, for a historical and broader perspective of the application of AR contents and technologies in education, training, and teaching, some studies and applications since the 1990s are presented. The abovementioned case of Feiner and collaborators is resumed: as stated, in 1993, they implemented the application KARMA to speed up the training process in laser printer maintenance. In the late 1990s, Kancherla et al. (1995) described the application of virtual reality and AR technologies to the kinematic and dynamic analysis of body motion applied to anatomy seminars. In 1997, Inkpen presented a study in which specific contents were developed to stimulate learning via a computer. These contents were not developed in AR, but they served as precursors in analyzing the effect of technology-based learning. In addition to the specific development of applications and software to stimulate learning, Inkpen (1997) examined the possibility of simultaneously working on computers with two mice. The results showed that motivation and learning were increased with group work in comparison with the individual use by each child. In 1999, Lu, Shpitalni and Gadh (1999) presented a study at the opening session of the CIRP (Collège International pour la Recherche en Productique), a major worldwide engineering academy, in which he stressed the importance of AR in the development and manufacture of products. In 2000, Weidenbach (2000) and his team developed a system with AR content for the medical field, in particular for training two-dimensional echocardiography analysis. One year later, Taxen and his collaborators developed virtual environments by immersing an AVATAR (graphical self-representation of the Internet user intended for virtual environments), to teach mathematics, in the context of learning content. Still in 2001, Billinghurst, Katob and Poupyrev (2001) also developed mathematics content displayed in AR under the name “MagicBook.” In 2003, also in mathematics, Kaufmann and collaborators described the implementation of the “Construct3D” system. This allowed an evaluation of the importance and flexibility of AR even in collaborative environments, as well as underlining the importance of such environments in student-student and student-teacher interaction. This system

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Fig. 3 Construct3D system for collaborative learning (a) face-to-face and (b) remote. (Source: Kaufmann and Schmalstieg 2003)

consists of three-dimensional mathematical contents supported by display equipment and collaborative work, either on-site or remote – see Fig. 3a, b, respectively. In other areas, and still following a chronological evolution, Liarokapis et al. (2004) and Nee et al. (2012) studied the implementation of AR in manufacturing projects and processes in engineering. Moreover, Quirós et al. (2008) and Maier et al. (2009) developed chemistry-oriented applications, thus enhancing the visualization of atoms and molecules as well as that of chemical reactions. MartinGutierrez et al. (2012) studied the application of AR in teaching and in the spatial perception of mechanical engineering students. Later, in 2012, they analyzed the applicability of AR to electrical technical engineering, while Fonseca et al. (2014) examined its applicability to architecture. In the same year, Salinas et al. (2013) developed specific software for three-dimensional modeling of mathematical functions and conducted a study highlighting the important role of these technologies in group motivation and in reinforcing collaborative work. Some interesting advantages of AR application were observed in the works that were analyzed. In the study of Martin-Gutierrez et al. (2012), the increase in students’ self-learning ability was highlighted, giving teachers more time to focus on explaining more complex issues. The study of Fonseca et al. (2014) outlines the advantages of AR tools for increasing spatial perception, providing in situ views of hypothetical scenarios for future construction, thus allowing an exploration and analysis of several solutions. In an earlier study, on m-learning systems, Ismail et al. (2010) described a high user satisfaction with additional mobile learning tools. The users felt supported and motivated to use mobile applications with an accessible language. Indeed, systems usually used in m-learning, such as these mobile communication systems, can enhance field observations and explorations when including AR content, because observed reality can be explained with the (augmented) addition of virtual content (explanatory videos, schematics, and three-dimensional designs, among others). This interaction contributes to greater autonomy in the learning process. It should be borne in mind that content made available and developed using AR technology can be accessed anywhere from m-learning support systems, such as mobile phones or tablets.

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Fig. 4 Three-dimensional representation of mathematical functions in a mathematical analysis seminar of the ESTG-IPL. (Source: Teresa Coimbra©)

AR enables the development of conventional contents (e.g., books, lecture notes, presentations), but adds specifically programmed graphics which are recognized by an AR application and then activate additional explanations when displayed (such as three-dimensional files, explanatory videos, and/or images). Figure 4 represents an example developed in AR to support the teaching of mathematics, within the work of Coimbra et al. (2015). The contents of teaching and learning, in this case mathematics, can be designed as usual based on an explanation on paper and complemented with a description of equations based on two-dimensional images. Contents such as 3D files, videos, and explanations of intermediate steps can be added to these standard elements. This provides an integration between a traditional mode of visualization of content on paper and the use of a complementary AR technology. Augmented reality allows the addition of digital information to the real world, not only to what is defined on 2D sheets of paper, such as the inclusion of layers of 3D virtual contents over physical paper contents, but also to include digital and virtual information on three-dimensional real objects (that works as the target). These can be produced by 3D printing. Virtual perception can be complemented by tangible touch given by tangible objects. For those who are blind, AR will be useless, and 3D printing appears as an interesting alternative, allowing a tactile perception of the three-dimensionality of what may exist only for some, in digital data. The existence of “real, physical targets” contents allows AR to add layers of virtual information on elements that may have been produced via 3D printing. With the 3D printing massification, classrooms can make available three-dimensional models of diverse elements in different subjects, including mathematics, as the examples shown below (see Fig. 5). Another example is the mathematical description in contours of a terrain topography. In such cases, in addition to the virtual perception that we can achieve with the AR today, 3D physical (or real) models can quickly be printed and made available for tangible perception. As these 3D models can be described digitally, the access to the three-dimensional printing of objects

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Fig. 5 (a, b, c) Three-dimensional elements: model printed in 3D for a tangible complementary perception of mathematical functions. (Source: CDRSP, Centre for Rapid and Sustainable Product Development©)

becomes easy and inclusive, i.e., available for everybody. In other words, digital data can easily be downloaded anywhere and converted by 3D printing in real objects. Therefore, real objects can be accessed anywhere, anytime, by anyone. These models, printed in 3D, might be a first experience, namely, a real and tactile perception, which can be complemented by more information. In order to do so, we only need to direct a mobile device with an application to them. On the other hand, the complementarity of technologies is such that it allows a broad range of the population to access them, as is the case of blind people, previously referred to. Thus, the combination of these technologies is the basis for the democratization of access to all perception of digital three-dimensionality, which, in the case of 3D printing, becomes tangible. As mentioned above, AR facilitates the integration between the real world and the virtual world, allowing the simulation and visualization of contexts and situations that could not be implemented otherwise. There are many areas of study and learning in which AR technology can be useful. Furthermore, AR technology brings a significant added value to areas that involve hands-on and experimental practice, such as science and engineering courses. Besides the integration between the real world and virtual contents in the classroom, it is also possible to create contents combining several other environments. In addition to the most common environments (at home, at the office, in the living room), AR facilitates the development of contents in various contexts and environments for everyone. This enhances the interaction between in situ observation of the real world and the addition of theoretical and explanatory contents. The flexibility of AR tools allows for further experimentation and exploration of the real world by introducing real-time virtual explanations. One example is the project “EcoMobile,” described by Kamarainen et al. (2013). This project assessed the implementation of AR to learning by using mobile devices in contexts in which students are exposed to real situations. In this case study, the influence of AR contents was assessed during study visits, and it was concluded that students showed an increase in interpretation flexibility when exposed to real situations and obtained explanations about their actual, real-time

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observation. Here, learning is focused on the individual, and each one can have access to explanations and support in the form of differentiated AR content when learning takes place. In recent years, there has been a growing interest in applying AR to create unique educational configurations. Bacca et al. (2014) argued that there are few review studies focusing on research factors such as uses, advantages, limitations, efficacy, challenges, and characteristics of AR in an educational environment. Another growing area of interest is using AR in customization to promote inclusive learning. This chapter presents a systematic literature review on AR in an educational environment, considering the abovementioned factors. In total, the authors analyzed 32 studies published between 2003 and 2013 in 6 indexed journals. Furthermore, future trends and visions are discussed, as well as opportunities for new research in AR in an educational context. In 2015, Maia-Lima, Silva, and Duarte (2015) presented a paper describing a learning experiment in a classroom using smartphones and QR code readers. These have proven invaluable in problem-solving and exploration of research tasks because of the motivation they triggered in students. This project was conducted in 2014/2015 at the curricular unit of geometry from the 2nd year of the degree in basic education from the School of Education of the Polytechnic Institute of Porto, Portugal. The group consisted of 76 students and took place in 3 classes for a total of 5 h in the presence of the observer. Every pair had a smartphone, a computer, or a tablet and a QR code reader in every equipment. During the learning experience, students have been very enthusiastic about completing each step, and curiosity was important in fulfilling the main task objectives. From the workgroup’s positive feedback on the task and resources, motivation for learning triggered by curiosity in finding what was behind each code was found to be the main factor for the project’s success. Also in higher education, Jorge (2016) conducted a research on AR in a virtual decision-making simulator in the Health School of the Polytechnic Institute of Leiria (IPL), Portugal. This aimed at analyzing whether AR would foster clinical decision-making skills in diagnosis and chronic wound treatment by increasing student motivation, as well as the usability of a virtual simulator, e-FER. In the 3rd Meeting on Games and Mobile Learning, Gomes et al. (2016) analyzed the introduction of gamification strategies in formal learning using technological learning objects mediated by augmented books, suggesting a symbiotic partnership between traditional paper books and a teaching approach updated by incorporating videogame mechanisms. The main objective of this study was to validate the hypothesis that teaching would profit from including such artifacts and strategies as fruitful teaching tools. One of the conclusions from this research is that the satisfaction degree and internal learner motivation is comparatively higher when education based on technological learning objects using gamification strategies is used, either in the classroom as a formal learning environment or in informal learning processes. In 2017, Almenara (2017) published a monograph in the EDMETIC – Revista de Educación Mediática y TIC entitled “Presentación: Aplicaciones de la Realidad Aumentada en educación,” in which recent papers were reviewed to explore the

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potential of AR in education. This work was based on nine papers describing experiences including AR in different levels and educational contexts in several countries, including Spain. The first paper, “Realidad Aumentada: Una revolución educativa,” was published in November 2016 and showed the investment on this domain in recent years. In fact, this (r)evolution has been strengthening further, with other studies published in the first semester of 2017 alone, namely, the following five: Almenara and Marin (2017), Erdem (2017), Hung et al. (2017), Martinez (2017), and Salinas and González-Mendívil (2017). Again on AR applied to mathematics and considering our study (Coimbra 2017), our observations during the research described below, including results from teacher interviews and student questionnaires, as well as data provided by the academic services of the Management School (ESTG) of the Polytechnic Institute of Leiria (IPL), lead us to believe that AR has a positive effect in furthering mathematics contents. Together with studies in similar environments (cf. Domingos 2003), it can be concluded that the advantages outweigh the limitations, i.e., that tridimensional technologies have a relevant role. More recently, Oliveira (2016) aimed at widening the understanding on the potential application of AR to support teaching courses through mobile devices, in this case in the field of information technology. He concluded that AR has a strong potential as an auxiliary tool for teaching information technology courses, therefore promoting interaction and collaboration among stakeholders. Let us refocus on mathematics, in the curricular unit (CU) of mathematical analysis (MA): considering aspects such as the difficulty students find in abstract contents, the versatility teachers identify in their methodologies, and the scarcity of three-dimensional, intangible contents using mobile devices, we found that threedimensional technologies such as AR can play an important role in this scenario. From the students’ point of view, including mobile devices, which they regularly use, may have a very positive impact, even though they are mostly unfamiliar with their potential in learning mathematical concepts and using AR. Teaching practices are attempting to use three-dimensional, albeit somewhat more conservative technologies, to promote an effective interaction of students with the contents. As some teachers are open to technological methodologies, AR could prove to be an alternative to some instruments, not only because it facilitates achieving the goals, but also because a structured integration would facilitate lesson preparation and streamlining their implementation in a classroom, taking advantage of time to improve the understanding of concepts. The potentials of implementing 3D technologies in teaching and learning mathematics are almost unanimously acknowledged. From these, the most relevant are autonomy in acquiring new skills, motivation, connection between theory and reality, as well as an increased perception of abstract contents, use of resources outside the classroom, and better communication between teacher and student. Group dynamics are another potential advantage of integrating these technologies. From the limitations teachers pointed out to technology integration, one of the most frequents is the lack of teaching time, since the priority is completing the

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curricular program. According to some teachers, one of the strategies to integrate these technologies could be redefining both the CU program and the number of students per class. Inevitably, it would be crucial to provide teachers and students with classroom conditions to accurately implement such technologies and to optimize time, both to complete the CU goals and to use time in exploring more complex concepts. Another strategy suggested by teachers to facilitate integration is the possibility of including 3D contents, including AR, to review, consolidate, and highlight abstract concepts. A potential distraction factor is another limitation pointed out by some of our respondents, both students and teachers, although not consensually. Teachers proposed some strategies to overcome this limitation, including moderate use, adequate and timely planning, establishing rules of conduct in the classroom, and an adequate choice of contents according to the CU goals. Teachers’ expectations regarding the use of 3D technologies in MA teaching were also identified, including an improved acquisition of mathematical concepts due to viewing objects from another perspective, as well as an increased understanding of formal, abstract mathematical concepts. Other expectations on the potential implementation of these technological instruments in MA classes were motivation and an increased connection between concepts and reality. Some students found that the integration of these technologies could promote motivation in clarifying specific MA contents, although not all have an opinion on the issue. Greater student autonomy is widely referred as an expectation by teachers and students, and it was suggested that these resources could be used outside the classroom. Another expectable factor in a technological (r)evolution in education, including in Mathematics in higher education, is an increased, more effective, and bidirectional communication.

4

Future Directions

The short chronological-historical mapping above shows that AR, as well as mobile learning, is a breeding ground for education. The mapping also shows that application of AR to educational situations has benefited from technological development, in particular mobile devices and m-learning. Therefore, it is believed that threedimensional technologies, more specifically intangible technologies (such as AR), will continue to be included on the educational agenda. Finally, part of the joint work developed in mathematics in higher education is presented. Among other goals, this work aimed at assessing content produced through three-dimensional, tangible (3D printing), and intangible (AR) technologies. This work is included in a project from the Portuguese Open University in cooperation with the Polytechnic Institute of Leiria, which resulted, for example, in a PhD thesis in education, in the specialty of distance education and e-learning. The abovementioned broader, international project, 3D4εDU – ThreeDimensional Interactive Contents in Higher Education – is a strong challenge and a strong commitment to create three-dimensional content that can be democratized and made accessible. Besides including intangible 3D content accessible through

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Fig. 6 (a, b) Implementation of 3D AR content in a mathematical analysis seminar of the ESTGIPL. (Source: Teresa Coimbra©)

AR, the project also focuses on the democratization of low-cost 3D printing to provide blind students with a three-dimensional perception of even more abstract concepts like mathematical functions. This is an example of inclusion which could take place in other sectors of society. In general, contact with new technologies during a student’s training will allow them to learn to apply similar technologies to different sectors and moments in their future professional and personal life, in a lifelong learning rationale. The 3D4εDU project intends to develop contents in other areas beyond mathematics, such as chemistry, life sciences, and optoelectronics. Furthermore, the work on mathematics in Portuguese higher education (Coimbra 2017) could be extended to other disciplinary and international situations, with the involvement of researchers and collaborators from Brazil, China, England, India, and Thailand. Involving different intervention areas and locations will boost the internationalization of teaching in Portugal in terms of defining, implementing, and assessing three-dimensional contents applied to learning. The abovementioned innovative research work (three-dimensional technologies as a contribution to the learning of mathematics in higher education) (Coimbra 2017), including an experimental and analytical branch, has been methodologically supported by the design-based research (DBR). Therefore, the second iteration of content deployment took place during the 1st semester of the academic year 2014–2015, and a system was implemented to provide 3D AR content in the cloud (unlike tangible content, which can be provided in the classroom). This implementation was subject to previous validation, both remotely and on-site, during an exploratory phase which took place in the second semester of the academic year 2013–2014. The creation of 3D contents in AR involved MA teachers from the ESTG of the IPL, who have used them to complement mathematics teaching, namely, in engineering courses. Figure 6 illustrates a validation moment in the classroom during the first DBR iteration. Technical constraints were solved, although they did not compromise the excellent reactivity of students who accessed and tested this 3D AR content.

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The second DBR iteration was initiated when creating AR contents and data collection tools, such as the survey questionnaire for teachers and the survey questionnaire for students. This stage involved several procedures, including contacting educational agents directly involved in the implementation of AR contents: the Director of the ESTG of IPL, the coordinators of engineering courses of the IPL, the Coordinator of the Mathematics Department, the Director of the Distance Learning Unit of the IPL, and teachers of MA. This stage ended with the implementation of contents in a classroom and teacher interviews. Throughout this period, AR contents were being systematically built, tested, and updated using various applications and tools, including programming with instructions in AR, three-dimensional edition, and access in query phase. The editing stage includes the first three phases (I, II, and III), i.e., the procedures to create and prepare AR contents. Phase IV corresponds to the end-user query. The first phase (I) consisted in 3D element development, which in our case has been created using different applications/softwares. We began by creating 3D elements using mathematics software (such as the K3Dsurf and the Graphing Calculator) to convert three-dimensional functions in neutral files (typically, in ASCII – American Standard Code for Information Interchange) containing a 3D function description. Consequently, several neutral format files comprised of polygon meshes defined by the exterior normal were created using the mathematics applications. STL (Standard Tessellation Language), OBJ (object, developed by Wavefront Technologies), and PLY (Polygon File Format) formats were tested. STL only translates geometry, whereas the remaining two translate geometry and color. However, the STL format was chosen for the simplicity of its structure, allowing for a simple and effective manipulation. The three-dimensional representation of mathematical functions in STL format was completed with other three-dimensional elements and 3D design applications. These elements were obtained in CAD (computer-aided design) applications and were merged into an application capable of defining actions and animations. In our case, the 3D StudioMAX application was used. From this application, neutral format files were exported: OBJ, FBX, and CAE (COLLAborative Design Activity). In OBJ and CAE formats, three-dimensional models are described in meshes without animation, but with color description. In most contents, animations activated by actions were used. These animations were recorded in FBX (Filmbox), an openstructure format developed by Kaydara and owned by Autodesk since 2006. Thus, phase I resulted in three-dimensional files containing animations and color. These 3D files, mostly in FBX format, are used in the RA application for programming contents. The application was Metaio, developed by Metaio, a Munich-based company. On May 28, 2015, the company was acquired by Apple Inc. Since then, it has ceased to provide licenses and discontinued their products. When we started this work, we evaluated several competing applications, as, for example, the BuildAR, but we chose Metaio because it offered many programming options that fulfilled our needs. Currently, there are many options available for the same purpose, with the advantage of being Open Source, including the ARToolKit or Argon. The applications available include or allow installing readers. Besides this, other elements can be added when importing 3D, such as audio or video.

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In Metaio, actions associated with each exercise of mathematics in the handbook were programmed. The programming work has had several iterations to optimize subsequent stages of publication and query. Providing elements of good graphic quality resulted in an increase in the AR application size with three-dimensional contents to support learning mathematics. The size of information had to be dealt with by providing deliveries in packages (on demand). This allowed us to obtain an excellent graphic and action quality, facilitating access via medium-/low-range mobile devices. At the end of phase III, the application is ready for publishing. Publishing can be implemented in three different, albeit complementary forms, each with advantages and disadvantages, as shown further on. The programming in Metaio could result in query applications for mobile devices (Android and iOS tablets), query applications for computers (B), and direct access applications to a channel with cloud query (C). Applications (A) designed for Android and iOS systems (cf. App Store or Google Play) allow these devices to work offline, with the advantage of circumventing the need for an Internet connection. However, these applications do not communicate with the editor/author/owner of the application and require new facilities in case the user needs to be updated; the same goes for desktop applications. In order to publish the application in the cloud, users need to install an AR content player. For the handbook we have created, the reader was Junaio, a free application. Publishing is implemented with access rules and may be disseminated by social media, with or without password protection. Hosting and publishing in the cloud requires the user to have Internet available at the moment, a limitation which is overcome by allowing constant application updates with real-time user access. Moreover, content use can be tracked with tools such as Google Analytics. This way, access can be globally monitored, and details such as location, time, device type, access time, and access number can be analyzed. As a result of phase III, contents were published and were subsequently ready to be used and queried. As mentioned above, contents can be queried through mobile or desktop devices. In either case, it is necessary to use a handbook on paper or PDF for AR content activation. Several levels of interaction can be expected; in the mathematics handbook, these included a detailed interaction with three-dimensional elements of functions with on-demand access and the ability to interact with the activation of resolution steps. In previous studies supporting the implementation in MA, projects were specifically developed to introduce new technologies and contents at different levels of vocational education and training (primary education, secondary education, higher education, continuous training, and advanced training). The results were evaluated, particularly their advantages and disadvantages, to define best practices for a proper implementation. Therefore, as explained above, contents were developed in the Metaio application, which can be accessed through the Junaio application, available on several mobile devices. These contents have been created for an exploratory analysis of the visualization of medicine and biology elements (see Figs. 7 and 8).

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Fig. 7 Three-dimensional representation of a human heart. (Source: CDRSP©)

Fig. 8 Three-dimensional representation of the DNA double helix. (Source: CDRSP©)

Besides the cases described and analyzed above, these two case studies also support that AR technologies can integrate both theoretical knowledge into real situations and real contexts into theoretical presentation forms. Bringing together and integrating both information formats can provide important leverage if contents are appropriately developed. In short, the value of integrating and using AR-based applications for content development, including formal access, is also confirmed in mathematics, as stated above, at a time which is conducive to the democratization of increasingly portable, more personal, and more social technology.

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Cross-References

▶ Adoption of Mobile Technology in Higher Education: An Introduction ▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Development of Mobile Application for Higher Education: An Introduction

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▶ Expectations from Future Technologies in Higher Education: An Introduction ▶ Framework for Design of Mobile Learning Strategies ▶ Learning to Teach Using Digital Technologies: Pedagogical Implications for Postsecondary Contexts ▶ Mobile Learning and Education: Synthesis of Open-Access Research

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Employing Virtual Reality to Teach FaceBased Emotion Recognition to Individuals with Autism Spectrum Disorder

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Rebecca Hite, Wesley Dotson, and Rebecca Beights

Contents 1 2 3 4 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Current Interventions for ER in Individuals with ASD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The NimStim Inventory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Additional Challenges in ER for Students with ASD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Using VR Technology to Teach Adaptive (Behavioral) Skills (BST) for Students with ASD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Using VR Technology to Teach ER for Students with ASD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 A Case Study of Virtual Social Reality in BST and ER for Students with Autism . . . . . . . 8 Future Direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Students with autism spectrum disorders (ASD) have difficulty recognizing emotion in facial expressions. This ability is important, as it supports students’ skills in empathy and socialization, so they may have more natural interactions with peers and adults. Multiple methods have been utilized to improve facial emotion recognition (ER), including sessions with trained therapists, actors, and facial stimuli. The latter, the NimStim (a 2D photographic battery of 646 facial expressions), has been used to help students identify emotions. However, emotion is a dynamic and nuanced process,

R. Hite (*) Curriculum and Instruction, Texas Tech University, Lubbock, TX, USA e-mail: [email protected] W. Dotson · R. Beights Texas Tech University, Lubbock, TX, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_124

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hence not readily captured and examined in static, single frame images. Other practices for improving ER are less reliable, sustainable, and technologically advanced in providing low-cost, naturalistic, and effective treatment. This chapter promotes the concept of leveraging 3D virtual reality (VR), using the valid and reliable data from the NimStim, to aid in facial ER for students with ASD. A case using the virtual social reality (VSR) of Second Life for ER training is presented and critiqued. The unique affordances of VR technology in apparent realism, zooming and rotation, without social and safety issues of VSR, may provide users a socially vetted and personalized interaction with facial images to build their skills of facial ER.

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Introduction

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that impacts adaptive functioning across the lifespan. Observed challenges and targets for intervention in ASD are classified under two domains: (1) reciprocal social communication and (2) restricted, repetitive behaviors (American Psychiatric Association [APA] 2013). Reciprocal social communication describes the spontaneous use of verbal and nonverbal strategies to initiate and respond to social interaction opportunities. Social communication begins with joint attention, which involves recognizing and then directing the eye gaze, facial expressions, and gestures with others to places and things in the environment. Development of reciprocal social communication then moves to theory of mind skills (BaronCohen 1995) and increased awareness of salient or important features in the environment in order to further interpret, respond, and direct the attention and behaviors of self and others (Van Hecke et al. 2016). Restricted, repetitive behaviors refer to stereotyped and/or unusual interests and preoccupations that may be characterized as being resistant to change and atypical in focus or intensity (APA 2013). Although presentation and level of functioning vary greatly, individuals with ASD exhibit skill deficits and limitations in these two domains across their lifespan. Emotion recognition (ER), and subsequent interpretation and response to emotional behavior, is one area of notable limitation for children, adolescents, and adults with ASD (Kouo and Egel 2016; Sucksmith et al. 2013; Uljarevic and Hamilton 2013). Per Berggren et al. (2017), “ER plays an important role in social communication. The ability to attend to socioemotional cues (e.g., facial expressions, tone of voice, and body language), interpret them correctly and respond to them appropriately is vital for successful everyday social interaction” (p. 1). Therefore, ER significantly affects successful social engagement and overall understanding of social contexts for individuals with ASD; therefore, it is a meaningful target for intervention and education.

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Current Interventions for ER in Individuals with ASD

Interventions for ER focus on simple identification or matching of an emotion label to a facial expression, as well as more complex interpretation of emotional experiences (e.g., potential antecedents or causes of an emotion and consequences or recommended responses to an emotional experience). Theoretical bases for interventions aimed at ER often use cognitive and/or behavioral perspectives to conceptualize the nature of ER deficits in individuals with ASD to provide more effective and evidence-based treatment strategies. From a cognitive orientation, the nature of ER deficits reflects impairment in the development of theory of mind and social information processing of the thoughts, feelings, and experiences of others (Uljarevic and Hamilton 2013). Behavioral accounts for ER difficulties in ASD suggest that decreased social motivation and limited learning histories of the salience and potential reinforcing properties of emotion and social interaction lead to challenges with labeling, matching, understanding, and responding to others’ emotions. Interventions for ER have largely focused on labeling and/or matching static, two-dimensional images of faces only without more dynamic, personally relevant, or interactive stimuli (Berggren et al. 2017; Kouo and Egel 2016; Uljarevic and Hamilton 2013).

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The NimStim Inventory

One primary challenge in teaching ER to children with ASD involves the inherent variability of emotional expression across human models. Also, when evaluating the mastery of particular emotions being recognized, few studies have addressed that even neurotypical peers are not perfect at recognizing emotions in others. Even neurotypical peers are only accurate at recognizing emotions in others 60–70% of the time (Tottenham et al. 2009). To more systematically disentangle deficits in ER from inherent ambiguity in varied facial stimuli being used as models, the NimStim database was created. This is a database of several hundred pictures of faces showing various emotions. The creator (Tottenham n.d.) hired an entire graduate theater department (43 male and female actors of varying ethnicities) to each model 16 various facial emotions (e.g., happy, sad, surprised, bored, etc.) including a neutral pose as a baseline. After the pictures of the faces were gathered, they were shown to 81 participants (raters) who attempted to identify the emotion in each picture to validate the set (Tottenham et al. 2009). At the end of the process, the database contained a score for each face representing its ease of identification and overall accuracy from raters. For example, some happy faces were recognized as happy by more than 90% of raters, while others were recognized as happy by less than 60% of raters. This method of analysis created a pool of ER stimuli that can be easily used to offer more or less ambiguous exemplars of each emotion for experimental and therapeutic purposes. For the therapeutic teaching of emotion, the NimStim database would allow therapists to initially teach ER using high-clarity stimuli (those identified correctly over 90% of the time) before moving on to progressively more ambiguous examples.

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Additional Challenges in ER for Students with ASD

Another challenge in evaluating ER in ASD includes how these learners respond to emotional stimuli in common experimental preparations. For example, in the majority of neuroimaging studies of emotional response in people with ASD, the experimenters compare brain response to visual stimuli as the primary measure. An experimenter, for example, will show a participant a picture of a fearful person and then look to see if the participant shows a fear response. Yet, participants with ASD rarely show a fear response to pictures of fearful faces. This has previously been explained as representing an abnormal response to fearful stimuli in individuals with ASD, but this explanation is incomplete. When individuals with ASD are presented with nonsocial fearful stimuli (e.g., pictures of objects they fear such as spiders, or stimuli associated with aversive events), their neurological fear response is not significantly different than their neurotypical peers (Uljarevic and Hamilton 2013). This suggests that abnormal responses to fearful faces are most likely the result of not perceiving the fear in the faces, rather than not feeling fear in the same way as their peers.

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Using VR Technology to Teach Adaptive (Behavioral) Skills (BST) for Students with ASD

Prior work using technology to teach students with ASD is through behavioral interventions called Behavioral Skills Training (BST). BST emphasizes teaching skills in a structured manner to develop more adaptive functioning across a variety of skill domains. Adaptive functioning is a measure of how well a student with ASD is “coping with the demands of the everyday environment” (Liss et al. 2001, p. 219), compared to neurotypical individuals of a similar age and background. Often BST requires direct and hands-on instruction with paid actors and psychologists as research suggests that “children may need to have at least some intervention directly within the generalization environments (i.e., the environments in which the children actually need to demonstrate these skills) if the children are going to demonstrate the skills learned” (Rosenberg et al. 2015, p. 213). Yet technology-enhanced learning environments have taught BST-based adaptive skills when traditional training is dangerous or problematic, like traffic safety (Honsberger 2015). Virtual reality (VR) provides rich immersive and interactive environments, creating a visual illusion of objects having depth and realistic qualities, to replicate the real world (Dalgarno and Lee 2010). VR’s inherent purpose of striving to replicate the real world corresponds directly with the importance of skills training in realistic environment for greater generalization. There is a potential for, as Ruzic (1999) described, “individualized, interactive and realistic learning that makes virtual reality a tool for apprenticeship training, providing a unique opportunity for situated learning” (p. 188). Twenty years ago, Strickland (1997) discussed how VR may aid students with ASD through controllable input or sensory stimuli, modification of

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environments for greater generalization, providing a safer learning situation, provision of a primarily visual/auditory environment, ability to provide individualized treatment, as well as varied user interactions, including head and body tracking (pp. 82–83). As VR has grown in popularity, it has been employed for BST for students with ASD. In a study by Goldsmith (2008) using VR for traffic safety, results indicated the naturalistic movements in the VR world (e.g., moving their head left and right vs. moving a joystick) influenced real-world generalization for participants with ASD. Yet, BST is different than ER training, and research suggests individuals with ASD may benefit from ER training; yet, transfer or generalization of training or to real-world settings is lacking (Fletcher-Watson et al. 2014) likely due to poor social reciprocity (i.e., social conversation and interaction), a core criterion for ASD diagnosis (Backer van Ommeren et al. 2017). The key for students in ER, as with the NimStim, is the ability to discriminate which is done through multiple exemplars and trials which are costly due to the human capital needed the inherent reciprocity required to facilitate these, albeit training, experiences.

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Using VR Technology to Teach ER for Students with ASD

A critical component of ER education is that students need multiple valid and reliable social stimuli, within a naturalistic environment, with multiple exposures to exemplars (Berggren et al. 2017; Kouo and Egel 2016; Uljarevic and Hamilton 2013). VR technologies can provide such a setting; the unique affordances of VR environments may aid students with ASD not only in BST but also in ER recognition (faces), developing emergent social reciprocity (Lorenzo et al. 2016). Students with ASD require concrete experiences in understanding ER facial features so they may develop more salient understandings of face-based emotion. Using VR, students may use zooming tools to closely examine aspects of the human face (e.g., eyes and mouth) to determine what facial features constitute a given emotion. This is supported by research using robots for ER that use exaggerated features and expressions to convey face-based emotion, aided in facial recognition and transfer (Boucenna et al. 2014; Chuah et al. 2014). Often cartoon faces are used, in lieu of robots, to eliminate extraneous facial information in order to improve recognition, which may not transfer or generalize to real-life social interaction (Rosset et al. 2008). Alternatively, VR may employ natural faces where students can zoom to fully explore the face; thus, the learner may determine which features are salient to understanding ER. This is possible as the realistic face in VR does not tire or begin to emote differently (as compared to an actor) over time, nor requires the student to negotiate reciprocity with a live person. Using VR and the 3D affordance of the technology, including the ability to rotate and change perspective, is superior to 2D representations of the same real faces (i.e., NimStim). 3D movement and dynamic, user-directed interactions may provide more durable learning aiding the student in negotiating global ER interactions (like interfacing with a virtual teacher or students in a VR classroom) and other relevant social situations. Overall, VR shows promise as an approach to ER teaching by providing dynamic, realistic, and

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customizable intervention features (Uljarevic and Hamilton 2013) vital to ER education. Kouo and Egel (2016) described for further research the use of VR as a realistic approach that could be customized to provide continual maintenance probes and/or relevant scenarios for generalization and maintenance, and VR may be a more interactive approach by highlighting personally relevant scenarios, enhancing opportunities for generalization (Berggren et al. 2017). Current research using VR for ER has evidenced improved ER skills in a safe and socially non-threatening environment (Didehbani et al. 2016). Yet, generalizability is an omnipresent concern in ER education (Berggren et al. 2017), in which the apparent realism of the VR environment is paramount to facilitate transfer to real-world contexts. There are calls for ongoing research exploring students with ASD perceptions of veridicality when using VR (Parsons 2016).

7

A Case Study of Virtual Social Reality in BST and ER for Students with Autism

One example of the potential impact of virtual environments to enhance and support the development of ER and social relationship skills in individuals with ASD is the reaction of some people with ASD to the online community Second Life. Second Life (2018) is an online, multiple-user community setup to allow participants to craft an individualized “avatar” and to interact with other users in a 3D, virtual environment filled with communities and open to user modification. Founded in 2003, Second Life has become an active and controversial social environment for individuals with ASD, with the opportunity to interact anonymously and using imaginary identities hailed as both an advantage and a risk to individuals who might choose virtual interaction over a more stressful face-to-face conversation (Danilovic 2009; Stendal and Balandin 2015). Individuals with ASD participating in Second Life activities describe advantages such as the freedom to self-define their personalities and methods of expression through their avatars (Danilovic 2009) and the ability to explore and express emotion through written text and textual cues rather than having to rely on face-to-face interactions (Stendal and Balandin 2015). Participants across both studies reported feeling safer and more willing to engage socially in new ways within the virtual environment of Second Life. While the potential benefits of a virtual social environment such as Second Life suggest that virtual environments are engaging and less intimidating for individuals with ASD, these environments have notable shortcomings due to lack of evidencebased, socially normed instruction and feedback systems that can be offered through BST approaches. An online, multiple-user interface like Second Life has potentially serious limitations as a vehicle to teach ER and social skills to individuals with ASD. First, avatars within Second Life are limited in emotional expressiveness and do not respond in real time to the content of user conversation. This limits the ability of the avatar to help an individual with ASD learn to recognize and pair physical signals of emotional state with the content of the conversation with a

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partner. Also, while the virtual environment is “safer” in regard to the potential social consequences of ER failures during interactions, the other conversational partners are neither teachers nor coaches, and users are not guaranteed to receive any social feedback about their ER decisions in real time – whether correct (i.e., socially normative and/or appropriate) or incorrect. Users who find the individual with ASD awkward in Second Life are as likely to shun or ridicule the individual as people in real-world settings. Finally, while Second Life offers many opportunities with varied partners to engage in social interactions requiring ER, these opportunities are not structured for best learning, scaffolded to the individual’s current level of ER skills, and do not provide sufficient, immediate feedback with the opportunity to correct and re-practice the missed ER discrimination that is characterized by the most successful ER programs with individuals with ASD. Last, these social platforms of virtual social reality, where users in VR interact with other people with the environment (Heeter 1992), may present additional challenges in social-based addiction (Weisel 2015), threats to privacy and autonomy (O’Brolcháin et al. 2016), as well as social exclusion and porting poor social behaviors to the real world (Papagiannidis et al. 2008). A systematic and rigorous VR instructional program that takes advantages of many of the design and interface characteristics of the Second Life experience (e.g., personalization of avatars, opportunity to interact with many different people, a “safer” interaction modality) that also incorporates the precision of stimuli using socially vetted, more scripted interaction and individualized feedback mechanism of BST-based ER instruction may represent an exciting direction for future ER intervention using VR technology. VR presents notable strengths of limitless socially interactive, teaching scenarios and individualized details within a potentially preferred, technology-based framework. Thus, addressing notable concerns related to structure and safety through a collaborative design of BST-based education with VR technology could greatly improve ER education and social engagement to be generalizable more successful real-world experiences and use of online platforms like Second Life.

8

Future Direction

Current estimates indicate that between 1% and 2% of the global population present ASD characteristics (APA 2013; Baron-Cohen et al. 2009), and students with ASD diagnoses are rising in the United States (Christensen et al. 2016) and globally (Berggren et al. 2017). As this population grows, traditional methods of ER training will be impractical or impossible due to issues of cost and access. Because of the importance of authentic contexts for ER education, computer or multimedia education is less effective as compared to hands-on, in-person instruction. Therefore, it is critical to explore emergent technologies like VR that replicates the real world in a virtual setting, to be employed in ER education for students with ASD. Further research requires assessment of VR environments for veridicality (Parsons 2016) and design to accommodate the physical and cognitive limitations of students

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with ASD (Lorenzo et al. 2016) (see also ▶ Chaps. 78, “Mobile-Based Virtual Reality: Why and How Does It Support Learning”, ▶ 72, “Virtual Reality and Its Applications in Vocational Education and Training,” and ▶ 79, “VR and AR for Future Education”).

9

Cross-References

▶ Mobile-Based Virtual Reality: Why and How Does It Support Learning ▶ Virtual Reality and Its Applications in Vocational Education and Training ▶ VR and AR for Future Education

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Augmented Reality in Education

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Theoretical Foundations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Social Constructivism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Situated Learning Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Affordances and Challenges of Augmented Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Affordances and Advantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Challenges and Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Case Study: EcoMOBILE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Current Trends in AR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Augmented reality (AR) allows users to superimpose digital information on the physical world by means of mobile devices. As a form of mixed reality, AR aligns with social constructivist and situated learning theories, in which knowledge is collaboratively co-created in real-world contexts using authentic disciplinary processes. Compared to fully virtual environments such as virtual reality (VR), educational AR affords location-specific information, just-in-time instruction and scaffolding, increased self-efficacy and tenacity, and greater ease of collaboration and of authoring. Rather than problem-solving activities in decontextualized settings, learners can engage in inquiry-based problem finding through an interactive, dynamic, contextualized learning experience that fosters near-transfer to later activities in the real world. This chapter summarizes illustrative research J. M. Reilly (*) · C. Dede Graduate School of Education, Harvard University, Cambridge, MA, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_126

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findings on uses of AR in formal and informal learning settings across multiple disciplines and age ranges. Based on these findings and on likely short-term advances in immersive media, ways that educators can best utilize AR as a means of transforming their teaching are discussed.

1

Introduction

Augmented reality supplements and enhances the real world by inserting or overlaying digital information that seems to exist in the same space as the physical world. Azuma et al. (2001) define an AR system as a combination of real and virtual objects based in a real environment that align with each other interactively and in real time. These virtual objects can take the form of text, still images, videos, 3D models, audio, or any other digital media. AR is a type of mixed reality, existing along a spectrum between a fully real environment and an entirely virtual environment (Milgram and Kishino 1994). The proportion of real and virtual objects in the environment varies in different mixed experiences, but all are grounded in the real world. Two broad categories of AR experience are location-based and vision-based (Cheng and Tsai 2013). In a typical vision-based activity, specific labels or fiducial markers are set in the physical world to register the position of virtual objects. An image such as a QR code is recognized by a digital camera and can trigger the appearance of digital information. Advances in computer vision and mobile hardware are quickly reducing the need for specific markers, instead relying on image recognition algorithms to pair virtual and physical objects (Peddie 2017) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). In contrast, location-based AR activities use positional data from a wireless network or GPS to trigger virtual content when users are at specific locations. Not all mobile and wearable devices are GPS-enabled or capable of location-based activities, but all can carry out vision-based content. Many AR applications involve complex heads-up displays in stationary devices or static projectors, but this chapter will focus on uses of AR involving mobile devices that can operate without being paired with other equipment or tethered to a desktop computer. In implementing AR, wearable technologies such as glasses and headsets will be discussed, as well as the use of mobile broadband devices (MBDs) such as tablets and smartphones. At a bare minimum, all a device needs to be capable of AR is a front-facing camera and a rear-facing screen (Peddie 2017). Thus, a wide range of devices are AR-capable, potentially lowering the cost of implementation for educational uses. In currently published literature on the use of AR in education, approximately 51% of studies focused on K-12 uses of the activities, with 29% of the corpus focused on higher education (Akçayır and Akçayır 2017). This chapter will explore case studies from a wide range of educational fields and age ranges but will focus the discussion on implications for higher education, in keeping with the theme of

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this volume. A comprehensive history of the origins and evolution of the technology is not presented here but can be found in this handbook (see ▶ “Augmented Reality and 3D Technologies: Mapping Case Studies in Education” by Cardoso et al., this volume; Dunleavy and Dede 2014). This chapter first explains two central theoretical underpinnings of AR for educational purposes: social constructivism and situated learning theory. Major affordances of AR in educational settings are discussed next, drawing from seminal papers in the field, literature reviews, and current work. Notable challenges that have been encountered are also delineated. Next, to add depth and specificity, a case study of how an ecosystem science mobile AR activity was designed and implemented will be described. Finally, a discussion of notable recent advances in AR-related technology and potential future directions of the relevant technologies will suggest strategies for incorporating AR in educational settings to facilitate transformative teaching and learning.

2

Theoretical Foundations

2.1

Social Constructivism

Learning does not occur in a vacuum. New knowledge builds on prior knowledge gained in other formal and informal learning settings, as well as on the lived experiences of the learners (Vygotsky 1978; Bruner 1966). Within classes or groups, individuals cannot be considered in isolation; the relationships between participants interacting with each other and the setting must be explored and examined (Greeno 1998). Instead of learning traveling in one direction from instructor to pupil, social learning theory (Bandura 1997) suggests that people learn from each other by observing what others do and seeing the resultant outcomes of their actions. This type of social learning requires attention to what is being modeled, retention of cause and effect, the ability to accurately reproduce what was modeled, and motivation to do so. In contrast to fully virtual environments that isolate the participant from others, these types of social interactions are currently easier to do in the mixed reality format of AR, allowing users to collaborate and interact in accustomed ways. Instruction that embraces social learning theory can provide rich, open-ended learning opportunities but can still include sufficient scaffolding and facilitation in the form of authentic resources and tools embedded in the physical world (Squire and Jan 2007).

2.2

Situated Learning Theory

All learning takes place in a physical context as well as a social one, and learning can be thought of as an interaction between everything within and relative to that context. Brown et al. (1989) call for a cognitive apprenticeship model that “supports learning in a domain by enabling students to acquire, develop, and use cognitive

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tools in authentic domain activity” (p. 39). This is similar to Lave and Wenger’s call for knowledge to be presented in authentic contexts and, to facilitate novice-expert shifts, for learners to join in communities of practice that mimic those of experts (1991). These theories also build on Vygotsky’s learning through social development (1978). Situating learning in this way is valuable due to the high degree of difficulty in transferring knowledge learned in one context and applying it to a novel situation or context (Mestre 2002). Instead of learning in a sequestered context, then being assessed on a learner’s ability to apply skills to a real-world problem, situating the learning in the real world with the types of scaffolding AR provides can “turn transfer inside-out” (Grotzer et al. 2015, p. 44). Mobile AR hardware that functions in field settings can increase the salience of information in otherwise confusing learning environments by highlighting certain contextual features and providing opportunities to apply knowledge in authentic settings. Situated learning requires only near-transfer to related problems, instead of the much more difficult far-transfer to different contexts with unlike semantics (Perkins and Salomon 1992).

3

Affordances and Challenges of Augmented Reality

Illustrative research findings from uses of AR in formal and informal learning settings across multiple disciplines and age ranges are presented here as a highlevel overview of how this technology can effectively be used to facilitate transformative educational experiences. In addition, commonly reported challenges and problems that have appeared in the literature are summarized. As with any rapidly evolving emerging technology, advances in hardware will address some of these issues but also raise new difficulties.

3.1

Affordances and Advantages

AR activities offer opportunities for groups of learners to collaborate and work together to solve problems using role-based approaches. Different members of the group can have specialized tasks or information available to them, with success being dependent on each member bringing their specialty to bear on the task in a jigsaw fashion (Dunleavy et al. 2009; Klopfer and Squire 2008). Knowledge is distributed among group members, who are therefore interdependent. Shared meaning can be built within groups, common ground can be established, and argumentation and negotiation can be more easily carried out (Morrison et al. 2009). The use of roles is also valuable in shaping epistemologically authentic inquiry tasks in which learners carry out activities much like experts in that field (Chinn and Malhotra 2002). The scaffolding and supports that AR can provide facilitate these types of tasks without constant instructor supervision and guidance. This just-in-time instruction and scaffolding possible in AR activities acts as intelligence

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amplification (Brooks 1996), allowing students to draw more effectively on these dynamic resources when compared to textbooks or traditional instruction. Within different types of technological interventions, evidence shows that AR lessons can direct student attention to deeper learning, whereas students using a similar PC program were more distracted by surface features (Lindgren and Michael Moshell 2011). This improvement is likely not due solely to the virtual elements of the program; work by Quarles et al. (2008) has shown an increased ability to transfer knowledge to real world situations in AR versus a similar VR intervention in medical training. Chiang et al. (2014) found that AR activities provide immediate and relevant information to learners without the need to spend time searching for it, increasing learning motivation and potentially reducing cognitive load. These findings hold in informal educational settings as well, where learners interacting with digitally augmented museum exhibits consistently demonstrate higher knowledge gains than their peers in unaugmented conditions by making unseen forces such as airflow around a ball visible (Yoon et al. 2017). It is possible that AR and other interventions in the mixed reality spectrum may offer the best of both the physical and virtual worlds, finding an optimal balance between the two that maximizes learning gains (see ▶ Chap. 79, “VR and AR for Future Education”). Many studies note high levels of engagement and motivation in their population beyond what would be expected with a novel technological intervention (Dunleavy and Simmons 2011; Chang et al. 2014). In one study, students even rated an AR computer-assisted design program as more satisfying to use despite also rating the overall usability of the AR program lower than a PC-based version (Kaufmann and Dünser 2007). While the authentic and interesting tasks that AR facilitates can account for some of this effect, an additional source of engagement comes from the learners’ immersion in the AR activity. Immersive virtual media have been shown to be highly engaging (Dede 2009), but unlike in a fully virtual world, less suspension of disbelief is required of AR activities due to the ever-present physical layer. Immersion typically requires high visual quality of a display or projector, good sound quality, and intuitive interactions through a user interface (Peddie 2017). There are tradeoffs between wearable head-mounted displays (HMDs) using either optical or video see-through and MBDs limited solely to video see-through on small screens (Rolland and Fuchs 2000). While HMDs may offer more immersion, they are also costly and less widely available in many educational settings. AR experiences can be easier to author than fully virtual environments by virtue of being based in physical space. Instructors and developers can place select digital information in the world to enhance learning opportunities without having to create an entire immersive environment from scratch. Fewer original art assets are required, and AR experiences can be created as simply as printing QR codes or placing markers on a digital map in a browser-based editor. Dunleavy and Dede (2014) list numerous stand-alone AR development platforms that do not require programming experience. Making AR platforms usable by nontechnical audiences increases adoption of the technology and empowers both teachers and learners to use AR actively as content creators rather than as passive consumers.

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Challenges and Limitations

A recent literature review and a meta-review of AR in education (Akçayır and Akçayır 2017; Radu 2014) have highlighted several issues common to many implementations of these types of activities. As with all emerging technologies, technical problems have unexpectedly developed in studies, and multiple facilitators may be necessary to successfully implement complex AR activities (Dunleavy et al. 2009; Dunleavy and Simmons 2011) (see also ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). In addition, time required to set up and implement activities can be increased by the addition of AR components. Gavish et al. (2015) report that users in an AR training group required much longer mean training times than their non-AR using peers, due to the lack of familiarity with the technology. Successfully implementing mobile AR lessons in formal educational settings requires highly skilled teachers who can rethink the role of mobile technology from something to be banned to something to be leveraged (O’Shea et al. 2009). All these issues will recede as AR becomes more robust and commonplace. In addition to technical and capacity hurdles, alignment of AR activities with mandated standards and assessments has proven challenging for designers and teachers. Many teachers feel pressured to “teach to the test” and cover the breadth of material that will be on the summative high-stakes assessments their pupils take, resorting to assimilative methods of instruction rather than exploratory, inquirybased activities (Clarke-Midura et al. 2011). This pressure is common in K-12 settings but also appears in medical and legal education where accrediting bodies with large amounts of power exert influence on how courses are taught or structured. These issues surrounding mismatches between AR activities and business as usual activities are similar to what teachers report when trying to incorporate field trips in their curricula: they are one-time experiences that require effort to arrange but have limited connection to the regular classroom curriculum (Kamarainen et al. 2013). While advances in immersive technology-based assessment may change the nature of high-stakes tests, this conflict will remain in play for many instructors in formal educational settings where teacher accountability is tied to summative assessments of their learners. Conflicting reports of increased and decreased cognitive load in AR activities can be seen in the literature (Akçayır and Akçayır 2017). At times, preventing student cognitive overload has been a frequently reported limitation in the development of AR for education. AR activities involve complex tasks, and the volume of material (especially written material) may overwhelm learners (Dunleavy et al. 2009; Cheng and Tsai 2013). Restructuring activities with this in mind can reduce cognitive overload, and replacing text with audio can diminish the effect that literacy might have on efficacy of the activity (Perry et al. 2008). By starting with simpler, linearly structured activities and more explicitly scaffolding activities at each step (Klopfer and Squire 2008), students can get accustomed to the technology and ease into the activity without being overwhelmed.

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Case Study: EcoMOBILE

EcoMOBILE was a set of related middle-school ecosystem science AR experiences delivered to students via MBDs. Developed between 2011 and 2015, these activities aimed to extend ecosystem science learning to field settings, connecting abstract concepts learned in the classroom to the reality of learners’ local watersheds. Based on Next Generation Science Standards and the Massachusetts Comprehensive Assessment System (MCAS) and designed in free, open-source software, the EcoMOBILE activities were freely released online for teachers anywhere to use in their curricula. Findings from two studies on EcoMOBILE activities are discussed here with a focus on teachers’ reactions and aspects of the work that are relevant to developers and practitioners. Additional details regarding learning gains and methods can be found in the original studies. An activity titled “Water Quality Measurements” was designed and implemented to help students to use probeware to authentically gather water quality data in local ponds (Kamarainen et al. 2013). Several sixth grade classes worked in pairs to measure dissolved oxygen concentrations, turbidity, pH, and water temperature using the probeware, while an AR activity guided them through the data collection and analysis. This activity used a mix of location-based triggers when students approached predetermined coordinates, as well as vision-based information about their watershed accessible through scanning QR codes. Students in the pilot activity showed positive shifts in their attitudes about their ability to understand scientific topics and carry out science-related skills. Students reported generally enjoying the field trip, and technology-rich components of the activity earned the highest ratings of motivation. Teachers reported high levels of student engagement and productivity, with pairs being able to work at their own pace independent of direct teacher supervision. As one instructor put it, “I felt like it gave them a different ownership over the experience than if there had been just one teacher voice and a crowd of kids” (Kamarainen et al. 2013, p. 553). By freeing the instructors and facilitators to move around and work with groups individually, the activity empowered studentcentered learning through sufficient but not overbearing scaffolding. Teachers also noted that students were more easily able to consider the unseen molecules at work in the ecosystem as well as factors at a distance from the pond such as features of their local watershed. The AR scaffolding allowed these nonobvious causal factors to compete with obvious ones, reducing the attractiveness of distractions and increasing the salience of nonobvious causes. Another instructor mentioned the value of giving authentic tools to students from traditionally underserved communities, indicating a benefit in combining AR with authentic scientific methods. Despite initial skepticism from teachers that the technology would overwhelm students and detract from the experience of being in the field, students were still aware of the physical layer of the activity and did not focus solely on the embedded virtual information presented to them. The hybrid nature of mixed reality experiences such as AR lends itself well to field work in

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which fully physical environments are confusing and chaotic, but fully virtual simulacra would lack the local context and value of being at a real pond carrying out authentic investigations. Two other EcoMOBILE lessons were designed to explore the importance of contextualization on mobile AR activities. Within AR activities, two different axes of contextualization can be considered by designers: social and physical. Social contextualization involves how much teamwork and collaboration is required and to what degree this socialization is mediated by the mobile technology, while physical contextualization is a spectrum of how place-dependent an activity is (Kamarainen et al. 2015). An activity called “Take a Tour” was designed to be highly physically and socially contextually dependent, with content being tied to one specific watershed and success requiring effective collaboration within groups and communication between groups. Another activity dubbed “Follow the Flow” was designed with opposite contextual goals in mind: it was place-agnostic and could be done in any watershed by an individual learner. These two activities were implemented with eight classes of middle school students and were followed by interviews and focus groups about their experiences. Few differences in student comments were found between groups in the different activities, indicating that place-agnostic designs may function as well as placedependent ones while being able to scale and be used in different learning environments more easily. Even without specific links to features of their environment, a well-designed place-independent activity can still engender feelings of a physically contextualized experience. On the social contextualization axis, few discernable differences were found on questions regarding community or collaboration, but students in the “Take a Tour” collaborative condition mentioned being confused more frequently in focus groups. This indicates that working in small groups does not inherently make activities easier and that the addition of layers such as roles and jigsaw pedagogy must be tempered by the risk of increased frustration and difficulty. In both implementations, mobile AR was a transformative technology that allowed instructors to use pedagogical approaches otherwise difficult or impossible to use in the field. By guiding learners through the use of probeware at a real pond, “Water Quality Measurements” was a student-centered activity that was a scaffolded, but authentic representation of how ecosystem scientists gather and make sense of data in real settings. The implications from “Take a Tour” and “Follow the Flow” indicate the ability of placeagnostic activities to nonetheless cause feelings of connection to local issues. Chang et al.’s (2013) work in AR activities related to socioscientific issues around the Fukushima power plant disaster also speaks to the power of context in instruction, which may make learning more meaningful or enduring than traditional instruction.

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Current Trends in AR

Several recent developments in mobile technology and shifts in public awareness of AR have led to a surge of interest in developing and marketing AR applications to the general public. AR was placed in the “trough of disillusionment” in the most

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recent Gartner Hype Cycle for Emerging Technologies (Panetta 2017) after recent failures of highly hyped wearables, but it is poised to move up the “slope of enlightenment.” While many of these advances have not yet been leveraged in formal studies or in educational settings, these trends provide a glimpse of the likely evolutionary path of the technology. The recent spike in popularity of mobile AR can be largely attributed to two sources: the popularity of Pokémon GO (a popular location-based mobile game) and the adoption of AR by social media applications. Developed by Niantic, formerly a part of Google, Pokémon GO boasted 65 million users 1 week after release (Bogost 2016). Based on a previous science fiction game by Niantic called Ingress, by overlaying virtual representations of Pokémon on users’ neighborhoods, it encouraged users to explore their local areas hunting for creatures to capture. While not an educational game, increasing children and adults’ familiarity with the concepts of location-based AR and virtual information overlay may reduce the barriers to adopting the technology in other applications. Niantic has announced another AR game based on the Harry Potter intellectual property to be released in 2018 (Hanke 2017). While educational applications of AR will never have the same viral appeal as popular entertainment franchise, the potential for mass market uses of AR for learning is now being realized. Several social media applications have been at the forefront of bringing AR to the typical MBD user. Snapchat “world lenses” allow virtual objects (such as emoji) to be placed in physical spaces along with text bubbles. Unlike similar AR applications available on older platforms like the Nintendo 3DS, Snapchat does not utilize QR codes or fiducial markers. The live camera feed of the MBD is used to register the virtual objects in the users’ surroundings in real time. While initially no customization options were available, users can now place their customized 3D Bitmoji in messages sent to their contacts, and advertisers have started to pay for branded world lenses. Facebook has followed suit by announcing the Camera Effects developer platform with the intention for it to be the first “mainstream augmented reality platform” that will work with future HMDs as well as phones and tablets (Constine 2017). With hundreds of millions of daily active users, the influx of AR in students’ everyday digital lives via social media will allow designers to leverage similar techniques for education. The successes of these smartphone apps doing vision-based AR without external references highlight recent advances in computer vision and image recognition software, as well as improvements to cameras in MBDs. Registration problems reported in early AR literature have largely been solved by simultaneous localization and mapping (SLAM) technology (Peddie 2017). Deep learning and neural nets have revolutionized the ability for AR hardware to recognize objects in surroundings and coordinate this information with accelerometers and onboard sensors in the device. In addition to software improvements, stereo cameras and Kinect-like depth and facial recognition sensors are becoming more common in mobile electronics. Developers and researchers will need to keep these advances in mind when basing work on extant AR literature. These advances make vision-based activities easier to implement and may result in more hybrid activities in which students are guided

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to certain locations via GPS coordinates, and then vision-based activities take over at those locations with no prior setup of markers or symbols. More generally, advances in machine learning on mobile devices have consequences for AR that reach far beyond image recognition. Whereas previous implementations of mobile machine learning depended on MBDs communicating with far away clusters of powerful computers, modern devices can train and utilize machine learning models using onboard hardware. ARKit (an AR development platform) and Core ML (a mobile machine learning platform) were both announced simultaneously by Apple and can work together to bring novel functionality to AR activities. As a proof of concept, the Magic Sudoku app uses an iPhone camera to scan an unsolved Sudoku puzzle, a machine learning model to solve it, and computer vision to overlay the solutions virtually on the puzzle through the device’s screen (Dwyer 2017). Another app that exemplifies this synergy allows users to place virtual artwork or pictures on walls, modify it via a neural net to match any other artistic style, and then overlay brush strokes on the new style to give the appearance of three dimensionality (Laan 2017). While work similar to this has been done previously with desktop devices, the ability to do similar activities in real time on a mobile device on top of a physical space is revolutionary. In addition to the aforementioned ARKit, ARCore from Google, Facebook’s Camera Effects platform, Amazon’s Sumerian, and PTC’s ThingWorx Studio all now offer the option to author AR experiences with a minimum of programming experience. These platforms are similar in that they have a “low floor” where users can use place freely available 3D resources in the physical world with a drag-anddrop interface while having a “high ceiling” of integrating with Unity, Unreal, and other high performance traditional development tools for experienced programmers. AR platforms are incorporating more features of the ideal development platform outlined by Dunleavy and Dede (2014), such as simple multimedia embedding, leveraging existing multimedia content, social networking, and robust location-based as well as vision-based embedding. Evidence suggests that student authoring of AR experiences would also be beneficial (Bower et al. 2014; Klopfer and Sheldon 2010), and these platforms are well-suited to entry-level authors. Despite such clear advances in MBD-based AR, the future for consumer wearables is unclear. Both Google Glass and Snapchat Spectacles failed to deliver on lofty promises of permeating the consumer market. While many industrial uses of wearable AR are well-documented (Peddie 2017), many consumers are engaging with AR solely through handheld devices, if at all. While higher levels of engagement and immersion are likely possible with wearable devices that position over the eyes, the technology is currently expensive and limited in what it can do when compared to a MBD. Headsets are not as likely to blend unobtrusively into everyday life (Azuma et al. 2001) and may not be as comfortable to wear routinely. These barriers and prejudices may change over time as manufacturers advance wearable technology development. Currently, the cost of HMDs is high for educational institutions that may already have iPads or sufficient hardware through a bringyour-own-device strategy. Microsoft’s growth of Hololens and their push for

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developers to create mixed reality platforms indicates a strong desire to capture the consumer market, and time will tell when consumers are ready to adopt HMDs at scale. Privacy concerns are an essential part of any conversation regarding a new technology that will be studied with protected populations. Similar to issues that have been raised with Alexa and Google Home, AR hardware requires near-constant recording and monitoring of one’s surroundings to properly register virtual aspects of the experience. Privacy concerns exist for users as well, where advertisements or disturbing imagery may be overlaid on their physical world without their consent and unwanted applications may compete for the users’ attention (Roesner et al. 2014). Conflicts have already begun to arise over Snapchat’s virtual art installations in public spaces, resulting in Jeff Koons’ AR artwork being “vandalized” by artists who disagreed with corporations being able to place whatever content they see fit over Central Park (Matney 2017). Who owns the virtual space and dictates what content gets displayed to users in a certain physical area? Who can place this data, and is there any restriction on what data can be overlaid? These are important conversations to have as the technology proliferates.

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Future Directions

Interest in AR and mixed reality is rapidly expanding beyond military and engineering markets. Experts at Goldman Sachs estimate approximately $300 million in educational VR/AR software revenue by 2020 and $700 million by 2025, predicting 8 million new users in educational VR/AR in that timespan (2016). Moving forward, methods of interfacing and interacting with AR will become standardized and familiar, much as smart phones now utilize regular patterns of swiping, tapping, and pinching to navigate interfaces. Students who have increasingly more experience with AR for entertainment or social networking will be able to utilize AR activities more easily than in past studies. Additionally, easier to use authoring tools and large amounts of freely available 3D assets will empower educators to create and modify activities to suit their needs. Professional development and training on the implementation and authoring of AR activities will facilitate this empowerment. Design principles for AR activities need to be codified to address the conflicting reports in the literature of cognitive overload. Additional virtual information overlaid on the physical world can help learners see more deeply and highlight important or otherwise unseen aspects of the world, but too much information can lead to a deluge of data that overwhelms rather than augments. Additionally, AR activities need to be better incorporated into existing curricula and should be implemented by unaided teachers, rather than studied as interventions led by external teams of researchers. The content of activities needs to align with the goals of educators and local governing bodies that dictate standards for certain subjects or ages. While many AR in education studies take place in science or medical education, more work in other subjects in the humanities and social sciences must be explored to see how AR’s affordances might help learn other material.

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Also, assessing student performance in AR activities is a challenge, particularly in educational experiences that are standard-based and use high-stakes assessments. Incorporating formative assessments in AR activities is possible and desirable, but learning gains in current studies are typically determined by paper-based pre- and posttests. A commonly underutilized aspect of AR activities is the large amount of process and log file data generated as students move physically through the world and interact with virtual information. In the EcoMOBILE activities, time-stamped log file data documented each group’s physical movements, when certain triggers were met, and what content was viewed in what order. These data were used to determine how far each group progressed through the field trip and to elucidate how the content they did or did not view may have shaped their explanations of data variability (Reilly et al. 2017). Additional work must also be done on the social nature of AR and how groups of learners can jointly navigate mixed reality activities. One potential way to explore these collaborations is through the use of multimodal learning analytics (MMLA) as pioneered by Blikstein (2013). Collecting data on students’ gaze, body movement, speech, and arousal can enhance understanding of how collaboration manifests in AR activities and how they may differ from traditional activities in terms of conversational turn taking, use of gestures and nonverbal behavior, and joint visual attention (Schneider and Blikstein 2015). More details on how AR alters social interactions may reveal additional affordances of the technology that can be leveraged by authors of activities. With a solid initial foundation of literature findings and major advances in hardware and software resolving many reported issues with the emerging technology, mobile AR is now poised to move from an experimental intervention to an instructional approach instructors can utilize in their own classes. While future developments in wearable technologies may lower their cost without sacrificing quality, many near-future educational AR implementations will likely use devices learners bring to the classrooms themselves and are already familiar with such as phones and tablets. Leveraging the combination of AI and AR now possible on such devices will allow creation of mobile AR activities far more complex than what was feasible with the last generation of MBDs. Future study is needed on the impact and efficacy of AR activities on students with learning differences and traditionally underserved populations. Further work and more extensive implementations of educational AR will test findings of engagement and motivation to see if they are robust once novelty effects are reduced.

7

Cross-References

▶ Augmented Reality and 3D Technologies: Mapping Case Studies in Education ▶ Characteristics of Mobile Teaching and Learning ▶ Mobile AR Trails and Games for Authentic Language Learning ▶ VR and AR for Future Education ▶ VR, AR, and Wearable Technologies in Education: An Introduction

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Mobile-Based Virtual Reality: Why and How Does It Support Learning

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Theoretical Foundations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 A Hypothetical Model of Immersive Cognition (HMIC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Definition and Explanation of the HMIC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Cognitive Overload and Physical Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Instructional Design Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Authentic Experience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Design and Instructional Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Virtual reality has rapidly evolved from desktop applications to mobile devices with headsets, creating an immersive environment. Learning institutions at both the K-12 and higher education levels have begun to purchase virtual reality kits consisting of mobile devices and virtual reality headsets. The purpose of including the virtual reality kits in instruction is to positively impact learning by streamlining the cognitive pathway of information from sensory input to working memory. A plausible explanation for this learning phenomenon is the Hypothetical Model of Immersive Cognition (HMIC), a combination of the cognitive features of the information processing theory with the inclusion of the body from embodied cognition. As immersive virtual reality (IVR) stimuli are presented to the brain, the sensory register filters the stimuli, creates a sense of K. Ladendorf (*) · D. E. Schneider · Y. Xie Educational Technology, Research and Assessment, Northern Illinois University, DeKalb, IL, USA e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_133

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presence, and immediately activates long-term memory, bypassing working memory. While the process can streamline the cognitive pathway, it also has the potential to cause cognitive and physical overload, possibly resulting in cognitive loss, dizziness, falls, and sickness for even the healthiest of learners. Software developers need to take cognitive and physical overload into consideration when developing new mobile immersive applications. Furthermore, instructors and instructional designers need to structure their instruction by embedding immersive virtual reality without losing sight of the main focus of the learning. Instructors and designers should take into account the established curriculum, design of the mobile immersive app, and setup of the physical environment. Future research should be conducted to determine the long-term impact immersive virtual reality has on the brain, body, and learning in general.

1

Introduction

Virtual reality has become increasingly popular in recent years. In the traditional sense, virtual reality is defined as a virtual environment that gives the user the nearphysical experience of being somewhere other than his or her location (Xie 2010). It simulates the real world, current or past, to allow the user the ability to view and experience an environment that is not the present reality (see ▶ Chap. 70, “VR, AR, and Wearable Technologies in Education: An Introduction”). This advanced form of communication has the goal to create as real of an experience for the user as possible (Riva et al. 2004). With the rapid change in technology, many of the experts and creators of virtual reality technologies are still at odds with its nomenclature. However, what is agreed upon is that each of these terms now reflects much more specificity. Xie (2010) differentiated virtual reality (VR) from virtual worlds (VW): VW is a virtual space simulated by computers where users are represented as avatars and can virtually interact with other avatars. In contrast, VR replaces the real world with a simulated one or a replica of the real world, providing users with visual, auditory, and tactile senses of the simulation so as to create a sense of reality. Another common VR is mixed or augmented reality (AR). This is when elements of the physical, real-world environment are augmented by computer-generated sensory input using a live-direct or indirect view (Carmigniani and Furht 2011). Although AR is not discussed in this chapter (see ▶ Chap. 79, “VR and AR for Future Education”), the potential, authentic nature of this powerful tool was found to increase its motivational appeal and in turn supports learning outcomes (Harley et al. 2016). VR as seen and most widely used in instructional institutions began with desktop applications, providing users with a virtual view or simulation of reality on the computer screen. Early application such as Google Earth gave users not just a virtual view of real places around the globe, but also simulations of real occurrences that cannot be brought into the physical learning environment. Learners were able to explore the surface of the moon, see the rotation and axis of the Earth, and explore

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the outer reaches of the solar system from a desktop computer in the school building. Access to live streaming cameras further provided learners and instructors the ability to virtually visit a location without physically leaving the classroom. As technology has grown, so have VR options. The emergence of mobile learning devices gives developers the flexibility to create new and interactive VR applications. Learners can now utilize 3D VR viewers to view the same VR content as before. The 3D viewer creates an immersive environment, taking the traditional desktop application to a deeper level of experience. This emerging technology is immersive VR (IVR): a 3D mobile-based, virtual environment that simulates a realistic environment while simulating a physical feeling of being in an authentic location or situation. IVR offers the learner a visuospatial perspective, or the ability to view the world from another perspective, which evokes a sensory immersion connecting the digital world to the entire sensory system (Bailey et al. 2016; Baumgartner et al. 2008; Ehinger et al. 2014; Pavone et al. 2016). This experience presents the user with an illusion that they have been transported through space and time. The more popular applications, such as Google Expeditions and YouTube 360, are nearly or fully immersive with 3D view, 360-degree access, and at times, audio input. Educational institutions at all levels and individuals, for both educational and personal use, are purchasing VR viewers on a daily basis (see ▶ Chap. 80, “Review of Virtual Reality Hardware Employed in K-20 Science Education”). The viewers can be found in school technology catalogs and electronic stores in abundance. Due to the increasing popularity of this new technology, it is imperative to provide a framework built on theory and research for incorporating it into any learning environment, thus ensuring the investment is worthwhile and learnerfocused (see ▶ Chap. 74, “Wearable Technologies as a Research Tool for Studying Learning”).

2

Theoretical Foundations

Despite the young age of this technology, immersive VR has its foundations in multiple theoretical concepts. • The information processing model was put forth by Atkinson and Shiffrin (1968) in efforts to explain how sensory input is brought in and consequently dealt with and stored as memory, through an organized process. Once the sensory input enters, it is processed through the sensory register. Sensory that is important continues to flow to the working/short-term memory and then to the long-term memory. There are points for cognitive loss due to overload on the sensory register and working memory. There are also points of additional access to long-term memory recall, as no memories are truly lost, though some may “decay” if not accessed over time (Bailey et al. 2016; Foxe and Snyder 2011; Xie and Zhang 2017). • The embodied cognition theory is grounded in the construct that cognition itself is determined by and based in bodily experiences (Black 2010; Johnson and Lakoff

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2002; Thompson 2010; Varela et al. 2016). The mind and the body are not contingently linked; they are inexorably linked, as they have evolved together (Clark 1998; Varela et al. 2016). As each experience is indexed, the components of our environment, emotions, tactile, and vision are established within our memories. It is then, through those indexes, that we are able to experience the phenomena of embodied cognition (Clark 1998; Varela et al. 2016). When compared to the traditional view of cognition presented in the information processing model, embodied cognition views the entire environment as stimuli with the capability to activate multiple channels within the brain for connections and long-term learning. Sensory stimuli come from multiple places, including the environment, and impact more than the brain. The impact on the body cannot be ignored and must be taken as an equal to the impact on the brain. The body and the environment impact the brain’s ability to create representations (Shapiro 2007). Where information processing theory relies heavily on visual stimuli to trigger the brain and create symbolic representations, embodied cognition creates the representations from the environment’s impact on the body, not the brain alone. Visual stimuli are impacted by physical movement and vice versa and therefore, can create physical stimuli (Shapiro 2007).

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A Hypothetical Model of Immersive Cognition (HMIC)

How does experiencing learning through IVR become different than learning through non-immersive media such as video and print? Blending the foundational theories in the past section with the impacts of VR on the human mind establishes the Hypothetical Model of Immersive Cognition (HMIC).

3.1

Definition and Explanation of the HMIC

The HMIC relies on the foundation of the information processing theory. Taking into account knowledge of the impact of experience on the body and learning, the HMIC seeks to marry the processes via a theoretical framework that stimulates not just the brain but also the body. In this section, the HMIC is discussed with a blend of research to further explain and substantiate the model (Fig. 1). Atkinson and Shiffrin’s (1968) argument about the main input into the sensory register being visual is not disputed. However, the impact the sensory register has on the brain and the body combined can no longer be ignored. In the HMIC model, visual stimuli still have a large impact on the brain and learning process. The brain continues to process visual stimuli in the natural sense of the information processing theory. There are four fundamental differences in learning within IVR as compared to traditional learning (see ▶ Chap. 64, “Mobile Technologies and Learning: Expectations, Myths, and Reality”).

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Fig. 1 Hypothetical Model of Immersive Cognition (HMIC)

First, since the visual stimuli are lifelike, the 3D IVR activates visual and motor channels and creates a simulation of physical stimuli (Garbarini and Adenzato 2004). In essence, the 3D IVR environment, while not able to provide physical stimuli, tricks the brain into believing physical stimuli is present and activates the physical and motor channels in the brain. When combined with limited live movements of the learner, the brain can be altered and impacted in a positive manner, as was seen in the case of stroke patients using 3D IVR for enhanced physical therapy (Mayr et al. 2006). Pan et al.’s (2017) findings about the IVR environment further support this notion: motion provided sensory input, which helps establishing embodied memories. These embodied memories, combined with external cueing, can create additional layers of immersion and add to the immersive sense of presence (Ahn et al. 2014, 2016). Studies conducted on patients experiencing virtual reality with brain scans indicate that the IVR did not impact a structural MRI scan (Hoffman et al. 2003) but did create a measured sense of presence. The higher levels of presence can correlate with medial prefrontal cortex alpha-band oscillations (Lenggenhager et al. 2011). Studies such as these indicate that intense visual stimuli in an immersive environment can trigger a physical stimuli and sensation without the necessary need to physically move. Furthermore, this sensation does not have an impact on the structure of the brain.

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The second difference between the HMIC and the information processing theory is how the visual input is processed when it enters the sensory register. The IVR can possibly directly access embodied memories stored in the LTM (Pan et al. 2017). The LTM components have been previously indexed through life experience (Lenggenhager et al. 2011; Pan et al. 2017; Pavone et al. 2016; Thompson 2010). This access to embodied memories simplifies the pathway for immersion and establishes an immediate sense of presence, so that the brain is deceived into believing the learner is in a lifelike and realistic environment (Riva 2008). This capability of the brain offers designers the opportunity to create simulated, emotional, and abstract stimuli that cannot be replicated outside an IVR environment. The brain can predict potential physical feelings and impact on the body from the audio and visual stimuli based on embodied memories. Using this prediction, the brain can be led into believing it is physically experiencing a virtual environment. Even if the learner knows and acknowledges that the environment is not real, the brain can still predict a physical, and possibly emotional, stimulus and react as though the body is physically experiencing the real environment (Schuemie et al. 2001). While a strong sense of presence can assist the brain with activating and transferring stimuli to the working memory, the power in the HMIC is the immediate activation of the long-term memory (LTM). The information processing model sees the working memory (WM) as an active place of continuously scanning stimuli from the sensory register against information from the LTM. In a traditional cognitive sense, the WM reviews visual stimuli more in-depth and makes determinations on what transfers to the LTM and what decays. If information does not transfer to the LTM, it was not rehearsed or coded, as the WM did not see a need for the stimuli from the sensory register (Atkinson and Shiffrin 1968). The HMIC identifies the direct interaction between access of embodied memories in LTM and the sensory registers, which then creates a bypass of the WM. The LTM is more likely to be activated if the sense of presence is very realistic and familiar (Xie and Zhang 2017) and will place less demand on the WM (Marsh et al. 2013). A third difference is explained by Holmes and Spence (2004) in their article, “The body schema and multisensory representation(s) of peripersonal space.” They argued that objects within a person’s peripersonal space, or the space immediately surrounding the body, could be represented differently from objects in extrapersonal space or too far away for the body to directly interact with. In a human’s schema, the objects perceived realistically are scored in more modalities of sensory information. Objects at a distance as well as those represented in unrealistic formats such as on paper or a screen are in the extrapersonal space and can only be perceived through a limited number of senses. However, the objects in a person’s peripersonal space are processed in a more thorough and complex manner (Holmes and Spence 2004). A 3D IVR could dramatically reduce the perceived distance of the objects due to the realism of these objects and strong sense of presence. IVR can also stimulate the neural circuitry in the brain to activate the schema in multiple sensory so as to streamline the cognitive path and deepen the learning experience. Studies with results that indicate IVR triggered physical or emotional stimuli in the brain with learning outcomes are reviewed later in this chapter.

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The fourth difference is that the HMIC model indicates a portion of the sensory register is muffled, blocking some sensory stimuli from accessing the brain. As per the embodied cognition theory, all stimuli are indexed with the components of the environment, including vision, audio, smell, touch, and emotion (Varela et al. 2016). In real life, location and stimuli enter the sensory register in a complete package of indexes, all of which signal to the brain that the person is in a live situation. However, some elements of the package in 3D IVR may be missing as simulations often consist of visual stimuli with limited physical input. When auditory, olfactory, and/or tactile indexes fail to accompany the lifelike visual stimuli, the brain and body can become disoriented. Gibson (1967) maintains, “perception of this environment is then accompanied by an awareness of the perceiver’s existence in the environment” (p. 85). Pretto and Chatziastros (2006) found how different environmental factors affected driving speeds in an IVR environment. By varying other environmental inputs in the IVR with reduced visibility, drivers were able to alter their behavior when presented with limited visual cues. Vision is, therefore, a partial bridge between environmental visual input and the other components of 3D movement that exists, as the learner perceives the world around him (Varela et al. 2016).

3.2

Cognitive Overload and Physical Challenges

The 3D IVR creates a sense of presence and at the same time a potential adverse effect due to visual and cognitive overload (Bailey et al. 2016; Barrouillet et al. 2010; Ehinger et al. 2014; Foxe and Snyder 2011; Heinz and Johnson 2017; Pavone et al. 2016, Xie and Zhang 2017). Therefore, the HMIC has kept intact overflow points to allow for the release of extraneous information that cannot be retained. Since the virtual stimuli are impacting the sensory register with information at a fast speed, the register cannot handle all the information at once, causing some stimuli to immediately bounce off. Many mobile IVR applications are asking the brain to perform two tasks at once: maintain a live physical balance while also processing a virtual scene (Chiarovano et al. 2015). The multitasking can create an immediate cognitive overload in the sensory register, causing even more stimuli to continue to miss the register. Barrouillet et al. (2010) identified that while WM was able to be simultaneously processed and maintained with limited stress, yet, under time constraints, increasing cognitive load could have a detrimental effect to learning. Interestingly, however, Xie and Zhang (2017) demonstrated how familiarity sped up the ability to make short-term memory gains through accessing familiar visual cues. Through multiple studies with immersion and load, Bailey et al. (2012, 2016) identified that a higher visual load or cognitive load, respectively, harmed learning. In one study, participants viewed a pro-environmental message and were taught multiple environmental friendly strategies in 3D IVR and then given multiple tasks in the physical world. Participants from the IVR group performed worse than their video counterparts on teaching tasks and strategies to other participants, writing as many tasks as they could remember and matching the tasks to the examples (Bailey 2012). Therefore, the output has the greatest potential to suffer if visual load is not

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properly moderated. As learning tools are designed to access this stimulus pathway, it is imperative that the IVR experience aligns to the vestibular system in order to ensure the brain truly accepts the illusion (Deroualle et al. 2015) and avoid motion sickness, dizziness, or physical falls from any user (Chiarovano et al. 2015).

4

Instructional Design Recommendations

IVR offers a learning environment that can transport learners to places that were previously inaccessible such as locations around the globe, historical events, and the outer reaches of space. However, the exposure to IVR could also cause the learner to experience both physical and cognitive overload. Due to these potential drawbacks, the instructor must identify which components of the IVR impact their populations and address them as needed. Quality IVR learning is supported when there is a proper mix between VR immersion and instruction (see also ▶ Chap. 14, “Mobile Learning and Engagement: Designing Effective Mobile Lessons”). This blend also ensures both the possible physical and cognitive reactions are taken into account to ensure optimal learning for the student. The following instructional recommendations are drawn from the HMIC model described above and relevant research studies about IVR learning experiences (see ▶ Chap.3, “Transformation of Traditional Faceto-Face Teaching to Mobile Teaching and Learning: Pedagogical Perspectives”).

4.1

Authentic Experience

The 3D immersive experience simulates real life to provide the learner with an authentic, semi-concrete experience. The HMIC takes embodied cognition into consideration and emphasizes the importance of including the body’s reaction to the IVR environment in the learning process (Shapiro 2007). The IVR experience must be as realistic as possible to create a strong sense of presence and activate the LTM. While traditional VR can provide cognitive stimuli, the stimuli are not strong enough to create the sense of presence, which leads to a weaker learning experience. Brown et al. (1989) stated, “. . .but it is nonetheless full-blooded, authentic activity that can be deeply informative - in a way that textbooks examples and declarative explanations are not. . .” (p. 34). The immersive experience is crucial to the learning process because it stimulates the body and the mind, involving the senses and simulating physical touch and placement. The emphasis on the immersive experience correlates to the HMIC theory, providing multiple stimuli to activate multiple channels, resulting in a strong sense of presence and activation of the LTM. A strong sense of presence is vital for two reasons. First, a sense of presence is necessary to better ensure the activation of the LTM. Recalling from the HMIC, virtual stimuli can immediately escape the sensory register. The 3D IVR environment must utilize all stimuli to create as realistic of a sense of presence as possible in order to activate the LTM and begin the learning process. Without this sense of

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presence, the brain and body do not connect, and the learning either does not occur or is not as effective as desired. Second, sense of presence can empower the learner. Riva et al. (2004) indicated that presence could have a positive impact on rehabilitation in neuropsychology. Virtual reality environments can create a safe place for patients to feel free to explore, necessary for patients who suffer from extreme fears or traumatic brain issues. The 3D IVR environment is safe, sheltered, and allows for warranted explorations of the abstract or semi-concrete issues at hand for the patients (Riva et al. 2004). While presence in this sense is focused on neurological patients, the same can be said for learners at all levels. The brain and body may react as though the VR is real, knowing that the experience is virtual and could end or be paused at any time. This two-way road between reality and virtual experience provides learners with the opportunity to be in an abstract or impossible situation while knowing the body and brain are physically safe. The learner should also be given the freedom and opportunities to leave the IVR environment at any moment for mental breaks, feelings of safety, and to alleviate physical feelings of dizziness, motion sickness, and balance. This also gives the learner a sense of control that can last beyond the experience with the 3D IVR (Ahn et al. 2014) and allow for deeper understanding of the content or topic at hand.

4.2

Design and Instructional Considerations

While IVR can provide an authentic experience that empowers learners, it can also have drawbacks to learning. As indicated in earlier sections, drawbacks include cognitive overload and physical reactions. This is possible due to the sensory register’s muting of or overreaction to some the IVR stimuli; it can also be due to a lack of accommodations built into the instructional plan. Instructors, instructional designers, software designers, and curriculum developers should consider the HMIC with both positive outcomes and possible drawbacks of IVR and provide both technological and instructional accommodations that will meet the cognitive and physical needs of the learner. The following sections indicate both potential drawbacks and accommodations for each drawback to ensure learners can experience the IVR while also mastering the learning goal.

4.2.1 Limit the Scope of VR While a heightened sense of presence can engage learners, it can also impede the learning process (Rupp et al. 2016). Learning can be negatively impacted when large amounts of stimuli and information are presented utilizing 3D IVR (Andersen et al. 2016). In a study utilizing 360Video and three delivery modes of IVR, Rupp et al. (2016) found that the greater the sensory input was, the less likely subjects were able to learn with the IVR. Subjects viewed a guided tour of the International Space Station from the point of view of the astronaut. When asked to list as many details and aspects of the station as possible, participants from the less realistic and less presence-inducing experiences outperformed their peers in the high-presence IVR

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experience. Subjects in the high-presence IVR group reported that they were often so busy interacting and absorbing the IVR environment that they were often distracted and unable to learn. Lee et al. (2017) found similar results when comparing Google Cardboard usage against viewing content on a 2D screen. While the 3D IVR stimuli can make it through the sensory registers, establish a sense of presence, and activate the LTM, information can still be lost between the transfer from the LTM back to the WM. The IVR can access and activate schemas (Flannery and Walles 2003). However, too many schemas activated at once can also cause overload (Bailey et al. 2016). A richer, more stimulating IVR experience can require additional mental effort and higher levels of attention, causing overload (Rupp et al. 2016). In other words, information overload in an extremely vivid learning environment, whether it be virtual or live, can be too much for the brain to handle and can drain mental capacity (Heinz and Johnson 2017). To avoid cognitive overload, it is recommended that 3D IVR environments should be very detailed but limited in scope. The smaller the virtual environment, the more likely learners are to explore the area and activate the LTM (Carter and Potter 2016). The smaller environment can also help to physically balance and center the user. Less movement and smaller environments can lead to more physically balanced learners, making it less likely they will fall (Chiarovano et al. 2015). Instructors should strive to choose mobile applications that are not overly robust and limited in the space learners can explore. The younger the learner, the more limited the space should be. Furthermore, it is recommended that learners are guided to focus on specific details or individual topics. Learners should not be utilizing IVR for the purpose of remembering as much content information as possible. The cognitive overload will lead to a loss in information, making the instruction with IVR unsuccessful (Bailey et al. 2016; Rupp et al. 2016).

4.2.2 Properly Sequence the Instruction While studies indicate an overly immersive experience that causes cognitive overload, learners in these same studies indicated an exceptionally positive interaction with the IVR experience. Learners expressed enjoyment and contentment from the IVR, noting the difference from traditional instruction (Lee et al. 2017; Rupp et al. 2016). Reflecting on the HMIC, these studies suggest that learners enjoy the sense of presence, even if the LTM is not activated (Lee et al. 2017; Rupp et al. 2016). However, the HMIC indicates that the LTM must be activated in order to start the learning process. The enjoyment of the sense of presence must be built upon by providing learners with the proper curricular supports and scaffolding to ensure learning happens. To activate the LTM with the sense of presence, the IVR experience must be embedded within an instructional structure. IVR cannot be a stand-alone instruction, nor would it be appropriate. Having learners simply looking at the IVR environment without providing enough depth of content is the equivalent of bringing a 3D movie into the physical learning environment. More important are the instructional strategies utilized to embed the 3D IVR within the learning. The IVR application is a tool, but not the form of instruction. Looking specifically at structures and theories,

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learning should be within the context of an authentic activity and environment. IVR provides this through a situated cognition experience. Within situated cognition, learning happens in an authentic activity but not necessarily an authentic environment (Brown et al. 1989). IVR goes beyond the authentic activity to provide the nearly authentic environment. The semi-concrete experience gives the learner the sense of being in the authentic environment without leaving the physical learning environment. Through the use of situated cognition in combination with the HMIC, the instructor has the ability to facilitate learning in not only an authentic context but also an authentic virtual environment. Lin et al. (2017) recommended to keep in mind three elements for embedding IVR: (a) full immersion into the 3D IVR environment and the learning itself; (b) interaction between the virtual experience, the live physical space, and other learners in the class; and (c) activating imagination, emotion, and abstract thoughts. The following steps can accomplish this: • The instructor should first determine the learning goals and a structure to utilize, for example, problem-based learning. • The instructor prepares learners for the virtual experience. • The instructor provides learners with the IVR experience directly connected to the content and context. The 3D IVR experience is realistic and believable, stimulating the brain and the body. • The instructor provides guidance throughout the time learners will be experiencing the IVR environment. • The instructor should pause learners and remove them from the virtual experience to collaborate with each other on extensions and reflection. • The learners should be encouraged to leave the environment for any physical or emotional needs such as dizziness, balance, or fear. • The experience provides learners with a means of reflection and gaining new understanding and knowledge. This can lead to further authentic 3D IVR experiences to continue to deepen the learning through brain and body stimuli. These steps were seen in Ahn et al.’s (2014) study of paper consumption knowledge and IVR. The researchers prepared the IVR experimental group by first explaining the purpose of the study, the setup of the IVR experience, a wide space for physical movement, and reflection after the study. Results indicated the IVR experience was successful, as noted later in this section (Ahn et al. 2014). When designing the overall content of the IVR lesson, instructors must begin with content preview and engaging discussion. Depending on the age of the learners, this can be a few minutes or an entire session. This mental preparation is essential for the brain to ready itself for LTM access. In addition, instructors cannot overlook the importance of pre-teaching the behavioral expectations when using and physical manipulation of the IVR technology. It cannot be assumed that learners know what they are supposed to do. It is during this time that instructors implicitly discuss how all materials are to be utilized, from the IVR technology to any assessment tools to be collected. Assuming the learners know what to do can be the failure of the wellcrafted lesson.

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Guidance is necessary immediately after the learners have entered the IVR environment. Instructors can provide a guided tour of the environment, mentioning specific details to search for. As mentioned before, often, if learners are overly immersed, learning can be lost, so it is important that learners are continuously connecting the visual experience with the content to continue to activate the LTM (Bailey et al. 2012; Rupp et al. 2016). Having learners engage in conversation with peers, the instructor, or through a question and response within the IVR, can also provide the guidance and scaffold support needed to activate schemas in the LTM. Having the learners pause their experience, remove themselves from the VR environment, and physically write responses allows for optimal learning to occur (Bailey et al. 2012; Rupp et al. 2016). The instructor should also provide opportunities for reflection through purposeful questioning and guidance, allowing the instructor to take a step away from “giver of information” and move toward guide and facilitator. This facilitation gives the learner the opportunity to form his or her own understandings and connections. Lin et al. (2017) also noted that reflection could encourage learners to participate more, increasing motivation for learning in the physical learning environment.

4.2.3 Be Mindful of Learning Goals As a versatile learning tool, IVR can provide many gateways to learning. However, it does not replace real, hands-on learning, when available. Additionally, instructors must not confuse the tool with the curriculum. This robust technology, while engaging for the learner, can also prove to be a sideway learning tool at times. When students are extremely excited and overstimulated by this IVR environment, the technology can become detrimental to the learning process (Bailey et al. 2012; Rupp et al. 2016). Furthermore, the learning outcomes must be for an authentic purpose such as research or empathy. Rote memorization with IVR will not yield positive results, no matter how realistic or impossible the IVR location is (Rupp et al. 2016). If the IVR technology is provided to learners without the effectual academic learning standards built around it, there will be a lack of support for any basis for its’ use as an educational learning tool. There is a push at all educational levels to include problem-based learning (PBL) experiences, STEM initiatives, and specifically at the K-12 level, the Next Generation Science Standards (National Research Council 2012). Learners today are expected to interact at a more engaged level than in years past. K-12 students are now asked to observe and provide evidence they gather on the changes in the Earth’s surface, movement and gravitational force in space, and energy flow in ecosystems from around the globe (National Research Council 2012). It is nearly impossible to transport an entire class to a location on the opposite side of the world. IVR can assist with meeting these new twenty-first-century standards but only when the standards are at the forefront of and the center of the purpose of the IVR experience. Instructors must be mindful to steer clear of didactic learning, evaluation tools, and activities such as memory/recall that are widely implemented as educational pedagogy moves toward skilled performance that can transfer to a real-world setting (National Research Council 2012). Similar can be said to higher

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education and adult learning. As higher education institutions and corporations look for adults who possess collaborative, problem-solving characteristics, it is imperative that the use of immersive VR enhances these characteristics and does not simply support memory or recall (see ▶ Chap. 72, “Virtual Reality and Its Applications in Vocational Education and Training”). Furthermore, the shift in instructional standards toward an exploratory- and inquiry-based approach can greatly benefit from IVR. Hu et al. (2016) studied collegiate students who experienced a creative thinking instruction versus traditional instruction in a general education course. Students who experienced the creative thinking instruction had higher levels of sensitivity and fluency in their creative thinking skills. When IVR was added, the students in the creative thinking instruction grew even higher in fluency and sensitivity as compared to their traditional instruction peers (Hu et al. 2016). Lin et al. (2017) had similar results when comparing collegiate students in traditional instruction classes to students in exploratory education courses and IVR. While the two groups both grew in their attitudes and motivation to learn, adding the IVR to the experimental exploratory group saw higher levels of learning attitudes and motivation to continue to change their behaviors. This also indicated that the learners were possibly more willing to leave their comfort zones and challenge their own boundaries of learning (Lin et al. 2017). As indicated by these studies and the HMIC, the IVR allowed for deeper exploration and development of learning skills. In addition, utilizing the IVR tools as a connection to social-emotional skills should not be overlooked. Multiple studies with embodied cognition identified that subjects in a given IVR environment with additional haptic input experienced a heightened sense of realism and showed the greatest behavioral impact response both for the immediate and long term (Ahn et al. 2013, 2014, 2016). IVR helped to increase emotional connectedness, understanding toward another person or situation, and elicit empathy in the IVR user (Ahn et al. 2013, 2014, 2016; Passig et al. 2007; Passig 2011). Ahn et al. (2014) conducted two studies and placed adults in an IVR environment limited in scope to a large tree in a forest. The participants used a virtual chainsaw to cut down the tree, experiencing audio, visual, and physical stimulation in the form of the chainsaw vibrating and resistance from the tree. When compared to the participants who experienced a print telling of the tree cutting process in the first experiment and a video telling in the second experiment, the IVR group indicated higher levels of locus of control and higher self-reported environmental friendly behaviors 1 week after the second experiment. Ahn et al. (2016) saw similar results in a study of adults utilizing IVR and developing a sense of involvement in environmental risks. Three separate studies were conducted to find which stimuli created the strongest sense of presence and compared it to the learners’ emotional growth. Users were placed in an IVR environment from the point of view of animals including a cow and a coral reef. The experiences that involved point of view and physical stimulation led to a stronger sense of presence and a higher acknowledgment that environmental risk was happening. The users also had a greater feeling of involvement with environmental risk (Ahn et al. 2016). Each of these studies placed users in an abstract situation that could not be done in real life

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such as cutting down a tree or experiencing environmental risk from the view of an animal. Both first-person simulation studies indicated that subjects were more likely to connect and be empathetic after experiencing the immersive VR when compared to traditional video and print instruction on an abstract topic (Ahn et al. 2014, 2016). The physical stimuli and point-of-view perspectives allowed for the sensory register to access embodied memories in the LTM and apply them directly to the IVR experience at the moment. The emotional connections do not stop at abstract ideas such as the point of view of the environment. Ahn et al. (2013) conducted a series of three studies involving IVR and the experience of color-blind individuals. Three IVR groups experienced a virtual environment as a color-blind individual. The results indicated the IVR group had a longer-lasting empathetic impact of 24 hours versus the video presentation group. Furthermore, the IVR group felt they had merged with and truly experienced the world of a color-blind individual, leading to a higher rate of helping behavior outside the IVR environment (Ahn et al. 2013). Passig et al. (2007) had similar results with middle school students developing empathy and understanding toward immigrant students after experiencing a VR environment from the viewpoint of the immigrant in a social-emotional learning lesson. Middle school students were placed in an IVR environment and asked to perform tasks while experiencing language and cultural barriers common to immigrants as well as negative feedback from digital representations of people, while a second group watched a video from the point of view of an immigrant teen. While both groups grew in their understanding of the social experiences of an immigrant, the IVR group experienced higher levels of emotional intensity. The video group had limited emotional growth (Passig et al. 2007). Nearly similar results were also seen in a study of teachers experiencing the world and cognitive demands of a dyslexic student in a professional development setting (Passig 2011). Forty teachers were placed in an IVR environment from the point of view of a dyslexic student and given the opportunity to view the dyslexic students’ world and cognitive experiences. When compared to their 40 colleagues who watched a video on dyslexic students, the IVR group was able to answer more questions about dyslexic students’ experiences correctly and indicate a better understanding of the students’ world (Passig 2011). These studies indicate that while VR has the potential to impact learning, it can also have a positive impact on socialemotional intelligence, a set of standards being adapted by multiple State Departments of Education. IVR can provide the instructor and learners with an abstract point of view. In each of these studies, the sense of presence was very realistic and pulled both cognitive and embodied memories on the user. The physical feelings allowed the user to be transported and have a deeper learning experience, as indicated in the HMIC. Instructors should take into account applications and methodologies that support learning outcomes at higher levels of thinking when choosing specific VR experiences to embed. Utilizing Bloom’s revised taxonomy can provide instructors with guidance in this regard (Anderson et al. 2001). Bloom’s revised taxonomy emphasizes a cognitive difference between lower levels of remember, understand, and apply and higher levels of analyze, evaluate, and create. Immersive VR has the

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potential to assist learners in the levels of remember, understand, and apply (Passig 2011). Furthermore, the VR experience, when combined with a strong structure and facilitative approach to the instruction, can provide learners the opportunity to analyze, evaluate, and create new understandings on abstract concepts (Passig et al. 2007). To assist with this, the chosen application should also be engaging and provide opportunities for above the line learning as based upon the SAMR model (Puentedura 2017). Puentedura’s (2017) model can provide instructors and designers with a guide for embedding mobile VR technology, ensuring the technology is an important part of the instruction, but not the driving force behind the lesson (Romrell et al. 2014).

4.2.4 VR Classroom Design It is imperative that the live learning environment setup is thought through to match the learner population, including ensuring learner safety. The HMIC indicates not all stimuli enter the sensory register, creating an impaired experience for learners. A strong learning environment design plan must be mindful of this. Flexible seating allows instructors to change the environment to meet the lesson and learners’ specific needs (Perks et al. 2016). It should be noted: simply having flexible furniture in the live learning space will not automatically lead to student engagement in the VR activity. The setting is only as powerful as the instruction that was created (Perks et al. 2016). For safety, learners should stay seated throughout the VR experience. This is imperative for younger learners. Immersive VR does not require, but can inspire, physical movement. Learners should be able to swing their arms without touching another individual or object, but not walk while not able to view the physical environment. The live learning environment should be clear of obstacles to allow learners the freedom to turn and move without causing injury, if a learner does begin making large movements or start walking.

5

Future Directions

Based on the foundation of the information processing theory, the Hypothetical Model of Immersive Cognition (HMIC) connects multiple stimuli across the sensory register, activates cross-channel connections, and fully immerses the learner in a 3D world. This creates a sense of presence other than the current location. That sense of presence activates the long-term memory, bypassing working memory, to connect the brain and body in a deeper learning experience. HMIC brings together traditional cognitive learning theories and body-centered theories to create a brain-body bridge for a deeper acquisition of knowledge and transfer to the long-term store. Instructors and designers should keep the HMIC at the forefront of the instruction. By understanding, and taking the HMIC into consideration, instructors and designers can better ensure learning occurs with immersive VR technologies and the possibility of cognitive overload diminished. The HMIC provides a guide for planning instruction, setting up the physical environment, and selecting mobile applications to meet learners’ needs.

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Looking forward, the multiple research opportunities present themselves in various applications of the HMIC for laboratory research as well as educational implementation. As educational institutions become more accustomed to this technology, the increased rate of immersion will generate greater proficiency by learners within immersive VR applications, which will ultimately lead to higher levels of learning (Glaser 1990). Through a comprehensive understanding of neuropsychological and cognitive theories combined in the HMIC, designers and instructors can prepare themselves and the learners they serve for this evolving technology. Immersive VR technology will continue to grow in popularity and educational use (see ▶ Chap. 79, “VR and AR for Future Education”). Research studies are needed to further solidify the assumptions and foundation of the model. Connecting studies on the brain-body and the HMIC can also potentially provide the support for implementing immersive VR in the learning environment. Future research should be conducted utilizing the HMIC to verify its validity. Researchers should also study the long-term impact immersive VR has on the brain-body connections. By looking at the HMIC model over short and long periods of time, the field may gain a clearer picture of the impact this technology has on the brain and the body. Varying and comparing the VR applications, headset devices, and including AR will also test the validity of the HMIC and its impact on the learning process.

6

Cross-References

▶ Characteristics of Mobile Teaching and Learning ▶ Mobile Learning and Engagement: Designing Effective Mobile Lessons ▶ Mobile Technologies and Learning: Expectations, Myths, and Reality ▶ Transformation of Traditional Face-to-Face Teaching to Mobile Teaching and Learning: Pedagogical Perspectives ▶ Review of Virtual Reality Hardware Employed in K-20 Science Education ▶ Student Feedback in Mobile Teaching and Learning ▶ Virtual Reality and Its Applications in Vocational Education and Training ▶ VR and AR for Future Education ▶ VR, AR, and Wearable Technologies in Education: An Introduction ▶ Wearable Technologies as a Research Tool for Studying Learning

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Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 VR and AR in Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Designing and Implementation of Kolb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 VR or AR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Design Process and Reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 The Expectation of Kolb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

VR (virtual reality) and AR (augmented reality) have been introduced in education for many decades. VR and AR have been adopted in a wide range of educational programs, including astronomy, medical education, engineering, physics, geology, biology, chemistry, mathematics, geometry, language learning, arts, interactive books, training for new teachers, and many other disciplines. It was widely adopted in industries, such as tour guides, industrial design and maintenance, museum, laboratory simulation, and the most popular games. These technologies enabled educators to break the limitation of location and/or time in education and bring a totally new experience to learners. Many empirical studies indicate adoption of VR and/or AR in education had several positive influences on students’ learning engagement, understanding, process, K. Kencevski Devika World, Smart Building, University of Wollongong, Wollongong, NSW, Australia e-mail: [email protected] Y. A. Zhang (*) WEMOSOFT, Wollongong, NSW, Australia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_136

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and outcome. However, there are still challenges in adopting such technologies in a wide range of educational programs due to some barriers, such as high cost of devices, high cost for content development for educational purpose, training for academic professionals and educators to introduce these technologies in their teaching methodologies, etc. There are arguments for further investigation on design, development, and evaluation of VR and/or AR in education. When VR is combined with experiential learning theory, KOLB (a learning program combined with traditional Kolb theory and emerging technologies) brought a new experience to students and learners. The design and development process for KOLB is introduced in this chapter. With the increasing number of mobile technologies and decreasing costs on telecommunication consumption in recent years, VR and AR technologies are introduced in more applications and programs, which have influenced many industries. These technologies will lead education into a new phase and link current teaching and learning with future world.

1

Introduction

VR (virtual reality) and AR (augmented reality) have been introduced in education for many decades. VR is defined as computer-generated simulation of a real or imagined environment or world (VREL 2007), which is majorly based on virtually designed computer world (Fernandez 2017). AR is defined as a combined world of real and virtual in real time with a registration in 3D (Azuma 1997). VR and AR have been adopted in a wide range of educational programs, including astronomy (Fernandez 2017), health and medical education (Fernandez 2017; White et al. 2014; Yiasemidou et al. 2017; Sankaranarayanan et al. 2016; Elby et al. 2017), engineering (Sankaranarayanan et al. 2016; Alhalabi 2016), physics (Enyedy et al. 2015), geology (Virvou and Katsionis 2008), biology (Fernandez 2017), chemistry (Fernandez 2017), mathematics (Fernandez 2017; Lee 2012), geometry (Ainge 1995; Virvou and Katsionis 2008), language learning (Alkhezzi and Al-Dousari 2016; Shu-Chun et al. 2017; Hennig 2016; Ramya and Madhumathi 2017), arts and creativity (Castro 2012; Fernandez 2017; Rattanarungrot et al. 2014), interactive books (Fernandez 2017), and training for new teachers (Nissim and Weissblueth 2017; Fernandez 2017; Lee 2012; Kim et al. 2017). These technologies were adopted in industries, such as tour guide (Fernandez 2017; Kloepper et al. 2010; Lee 2012), industrial design and maintenance (Fernandez 2017) (see ▶ Chap. 21, “Study on Networked Teleoperation Applied in Mobile Teaching”), museum introduction (Hennig 2016; Lee 2012), laboratory simulation (Sankaranarayanan et al. 2016; Kloepper et al. 2010; Matzke et al. 2017), training (Lee 2012; Nissim and Weissblueth 2017; Griffith 2013) (see ▶ Chap. 72, “Virtual Reality and Its Applications in Vocational Education and Training”), and the most popular games (Statista 2016; Bredl and Bösche 2013) (see ▶ Chap. 71, “Mobile AR Trails and Games for Authentic Language Learning”). These technologies enabled educators to break the

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limitation of location or time in education and bring a new experience to learners (Lee 2012; Fernandez 2017; Rattanarungrot et al. 2014). Many empirical studies indicate adoption of VR and/or AR in education had positive influences on students’ learning processes and outcomes (Alkhezzi and Al-Dousari 2016; Fernandez 2017; D’Agustino 2013; Virvou and Katsionis 2008; Sun et al. 2016; Alhalabi 2016) (see ▶ Chaps. 78, “Mobile-Based Virtual Reality: Why and How Does It Support Learning” and ▶ 77, “Augmented Reality in Education”). Students are different and more prepared for mobile, VR, or AR education with their digital natives (Prensky 2001) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). But there are still challenges in adopting such technologies in a wide range of educational programs because of barriers, such as high costs of devices, high costs for content development for educational purpose, training for academic professionals and educators to introduce these technologies in their teaching methodologies, limitation of processing capability of hardware, broadband, seamlessness of mobile networks, and some political and ethical barriers (Fernandez 2017; Vogel et al. 2009; Nissim and Weissblueth 2017; Yousafzai et al. 2016; Alhassan 2016; Zhang 2012) (see ▶ Chaps. 2, “Characteristics of Mobile Teaching and Learning,” ▶ 80, “Review of Virtual Reality Hardware Employed in K-20 Science Education,” and ▶ 33, “Mobile Education via Social Media: Case Study on WeChat”). There are discussions whether VR and/or AR can help solve the current problems in education for different learners (Lee 2012; Våpenstad et al. 2017; Chen 2006). As the mobile technologies’ development increased and costs on telecommunication decreased dramatically in recent years, VR and AR technologies are being introduced in more applications and programs, which influenced many industries including education. Combined with traditional learning theory and emerging technologies and devices, VR and AR will lead education into a new phase and link current teaching and learning with future world.

2

VR and AR in Education

VR and AR play an important role in teaching and learning (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). The new VR and AR technologies and mobile devices should be combined with many other important factors, such as a well-designed digital curriculum, supportive faculty and policies, welldesigned digital teaching materials, hardware and software supports, trained and confident educators, and prepared learners to assist improving learning experience, process, and performances. The most expensive educational programs or plans do not necessarily generate satisfied outcomes (Roedigeriii and Pyc 2012; Enyedy et al. 2015). Mobile technologies and devices are adopted differently in different countries or associations (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). The best mobile teaching and learning solutions meet the requirements of students and teachers in their class. The complete immersion experience in VR and the

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Concrete Experience

Observations and reflections

Testing implication of concepts in new situation

Formation of abstract concepts and generalization

Fig. 1 KOLB’s four-stage cyclical experiential learning theory (Kolb 1984)

interactive connection with physical world in AR provided different opportunities in education (Fernandez 2017). VR and AR brought opportunities to traditional learning theories or emerging computing technologies or devices. As shown in Fig. 1, KOLB’s experiential learning theory is a four-stage cyclical experiential learning theory, which combines experience, observation, cognition, and testing (Kolb 1984). This theory has been adopted by many empirical studies and learning processes. It is expanded and combined with emerging technologies (Vogel et al. 2009; Kabugo et al. 2016). Devika (an education company based in Wollongong, Australia) builds experiences using emerging technologies, such as AR and VR. Devika provides workshops equipping students with in-demand skills in technology through hands-on and gamified approach and is dedicated to move students from content consumers to content creators. In doing so, Devika is building digital experiences combined with KOLB’s theory and emerging technologies. Noticing the gaps in the teaching and supporting of technology in schools, Devika Learning collaborated with schools to facilitate their current schooling (help school teaching system evolve so students receive as much support as possible when it comes to tech education). Given the expected growth in STEM careers, Devika aimed to encourage young Australians to be technologically empowered. On the other hand, the traditional methods of learning (such as textbook) need to be improved when connecting to millennial students. Devika introduced virtual and augmented reality (VR and AR) applications to schools to meet the gap. The new VR and/or AR learning systems engage students in an immersive learning experience and support schools with emerging technologies. Targeting the changing roles of students from content consumers to content creators, Devika Learning brought the hands-on approach to modern education in a supportive environment. It equipped the students with relevant technology skills through the guidance of current industry professionals to set them up with transferrable skills for the future. Devika Learning is dedicated to driving transformable

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change through conveying to students a mindset and thought process which promotes adventure and discovery. These skills are expected to generate an impact on their daily lives, their families, and their community. Devika has a background in software development in the realm of emerging technologies with a current focus on both VR and AR. Through utilizing these skills and technological capabilities Devika is pursuing a new venture called Kolb, which is a project focused on the creation of products for the education sector. Kolb involves a software application providing experiential learning scenarios delivered in VR and AR. Each setup is extracurricular and mapped to the Department of Education’s High School curriculum. This new approach has engaged students through gamification and the use of emerging technologies. Kolb software takes its name from KOLB’s experiential learning theory (Kolb 1984). Kolb theory works on two levels with the utilizing of a four-stage learning cycle of learning and four separate learning styles. Considering the current gap with technology and education industries, KOLB merged Kolb’s theory with immersive technology to create a new dimension of experiential learning, especially with the present developments of VR. The idea of VR has existed on the periphery of industries since the 1950s (Ainge 1995; VREL 2007); however, hardware and software limitations have prevented it from achieving mainstream application until recently (Fernandez 2017; Nissim and Weissblueth 2017; Yiasemidou et al. 2017; Zhang 2012) (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Historically, VR has been connected to the entertainment industry, but the various possible applications for this technology far exceed use in this sphere alone. The application of both VR and AR has merit for industries in areas such as healthcare (Sankaranarayanan et al. 2016; Våpenstad et al. 2017; White et al. 2014), data visualization (Fernandez 2017; Rattanarungrot et al. 2014), public safety (Fernandez 2017), entertainment (Bredl and Bösche 2013; Fernandez 2017; Virvou and Katsionis 2008), sport (Rattanarungrot et al. 2014), and design (Fernandez 2017). Educators are most interested in education (Chen 2006; Matzke et al. 2017; Yiasemidou et al. 2017; Fernandez 2017; Alhalabi 2016; Ainge 1995; Cochrane 2016; Nissim and Weissblueth 2017). They aim to make advancements in how technology is incorporated and experienced in the learning space. A significant asset to education is mixed reality (MR) and its support of the flipped classroom method (Shu-Chun et al. 2017; Fernandez 2017; Vogel et al. 2009). This method encourages students to view lectures at home, so classroom time can be utilized to expand on concepts students learned at home. An example of this is the Google Expeditions software that allows students to travel to exotic locations adding context to previous history and geography lessons and homework. While this example highlights how mixed reality encompasses mostly passive experiences, Kolb software uses dynamic storytelling to create active experiences to allow students to engage with their subject material while harnessing the Kolb method. As shown in Fig. 2, one example of Kolb learning is interactive learning in a virtual environment. There is always a trade-off in selecting the most suitable technologies when designing educational systems. VR and AR provide different experiences in teaching

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Fig. 2 Kolb virtual learning experience. (From the author)

and learning. Educators are always confused with the selection of new technologies and devices. Industry partners provide consultation to support them. The design and implementation of Kolb learning program are introduced in the following section, benefitting the policymakers, educational associations, educators, and teachers.

3

Designing and Implementation of Kolb

3.1

VR or AR

Devika and other companies, who use emerging technologies to create immersive experiences, encounter the challenge of choosing the right type of technology to best suit the situations at hand. When trying to find the most suitable technology, it is important to look at VR and AR. Selecting AR or VR technology is dependent when considering what works best for students. Factors such as available hardware, development trends, and the Kolb method are all integral to deciding the type of technology to incorporate. There are a variety of platforms supporting AR and VR such as SteamVR and the Microsoft Store. Devika will be working with application stores approved by the Board of Education stating the platform provides positive contributions to the education ecosystem. Microsoft Store’s hardware has strong potential for educational software. This can be seen by the Microsoft HoloLens, which is the first mainstream AR headset already supporting a small range of educational software. Adding to this, the Microsoft Store has recently released a series of collaborations with companies such as Dell, Acer, Asus, HP, Samsung, and Lenovo, demonstrating how Microsoft and its platform were built focusing on the education sector.

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When it comes to the creation of applications for VR, hardware does not play a major factor as Devika, or for Kolb, as the developers practiced a technologically agnostic model. This means an unbiased approach toward both hardware and software is taken when using different technologies and creating products. The developers believe in building cutting-edge software used on the newest platforms and hardware. It is important for them to design experiences not limited to a specific type of hardware, but with the desired outcomes in mind and how to use current software capabilities to achieve the desired outcomes. Regarding AR and VR, Kolb does not make software to fit only one type of hardware, but rather adapts to what is needed from the hardware and considers other aspects such as accessibility and cost, an important part of the decision-making process. Due to hardware requirements, AR and VR can be separate pieces of hardware. Although companies such as Microsoft and Meta intend to merge the two technologies into one set of hardware, for now AR primarily exists with the HoloLens and Meta headsets, while VR is available through hardware such as the HTC Vive, Oculus Rift, and the Microsoft Mixed Reality headsets. No hardware on the market currently offers both. Therefore, the outlook Mixed Reality headset will be a merger of the two types. A headset capable of blocking out the real world for a virtual experience and a transparent background can provide an augmented experience. As shown in Fig. 3, this difference of hardware plays a large factor in deciding between AR and VR for development. Growth for AR and VR is going in different directions. VR work is primarily done on desktop-based hardware, whereas AR development is mobile driven. However, new advancement is happening within the space. For example, after building the Westpac (Australian Bank) AR applications on what “the future of banking will look like with holograms,” only months later was the public release of

Fig. 3 Example in Kolb. (From the author)

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Apple’s ARKit and Google’s ARCore. The conversation from physically large firstgeneration headsets to mass-market mobile-ready application was the topic. Desktop hardware for VR is more sophisticated than it is for AR, which has led to continued VR development with desktop rather than mobile hardware. The preference between mobile and desktop hardware advancement is a factor when comparing the two as they have vastly different capabilities and functionalities. The main difference is six degrees of freedom, which the mobile does not currently support, referring to the freedom of movement in three-dimensional space. Taking these factors into account, Devika believes VR is currently the most consumer-ready and appropriate format for combining the Kolb method with immersive software in order to create experiential learning for students. This is more effective to create an immersive experience as it blocks out students from the real world. This is achieved by using captivating visuals and sounds engrossing users in their own worlds and holds their attention. The desktop VR experience provides six degrees of freedom, which is very important in the creation of an engaging experience as it allows movement of a rigid body in three-dimensional space. This entails the body (arms and legs) freedom to change position from forward/backward, up/down, and left/right through transitions of three perpendicular axes. This adds a high level of engagement to the virtual world and helps capture a student’s focus, which allows for a better application of the Kolb method. Desktop programming compared to mobile programming must be evaluated. As mentioned above, desktop VR is increasing in volume, whereas AR is trending toward mobile. It is very important that experiential learning scenarios are simulated on desktop platform and not mobile platforms at the moment. Since it offers motion tracking and the ability to interact with the environment, the desktop platform makes interactions more immersive. Therefore, desktop platforms are more effective for the application of the Kolb method and its experiential learning. In regard to desktop advancements, VR has more sophisticated hardware and development avenues due to being on the market longer. Unfortunately, AR is yet to have these desktop improvements in its hardware capabilities and is reliant on mobile. Due to this, VR is a better tool for the Kolb method and education at this time. Lastly, VR has more available hardware at a more affordable price than AR at the moment. Therefore, considering the accessibility and scalability of the business model, VR devices are more cost-efficient for current learning programs. To give as many students as possible an access to the educational software without sacrificing quality, Devika decided to begin with the computer-based VR for Kolb.

3.2

Design Process and Reasoning

The design process of Kolb software heavily applies the Kolb method of experiential learning (Kolb 1984). As mentioned above, the method involves a four-stage cycle of learning with importance given to the student experience at each part of the cycle. The four stages are:

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1. Concrete Experience: A new or reinterpreted situation is experienced by the student. 2. Reflective Observation: A chance to look for any gaps between experience and understanding. 3. Abstract Conceptualization: The creation of new ideas or the changing of an existing concept. 4. Active Experimentation: The student applies these thoughts and sees the results. David Kolb views learning as an integrated process with each stage mutually supporting the other. Students can enter the sequence at any stage and follow it through to completion. However, Kolb software places students in a more controlled environment taking them from stage one to stage four in sequential order to enhance their experience. The design process for Kolb expanded Kolb theory and combined it with emerging technologies as shown in Fig. 4. A key part of Kolb’s work outlines the different learning styles exhibited by students. This part is adopted by Kolb software. These styles are broken down into four types: 1. Diverging: These students prefer passive experiences over active ones. They possess a strong imagination. Doing well in groups, being open minded, and enjoying feedback are part of this style of student. They have broad interests and are artistic.

Fig. 4 Design process for Kolb. (From the author)

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2. Assimilating: These students prefer clarity in their learning environment. They enjoy logic and analytics. They are conceptualizers. 3. Converging: These are students who are problem-solvers. They put their lessons into practice. New ideas and practical tasks are enjoyed by these students. 4. Accommodating: Consists of students who prefer active experiences involving several practical exercises. They enjoy using intuition to solve problems and experimentation. The Kolb method provides the education sector with the opportunity to develop more appropriate learning opportunities. By allowing students to engage in ways deemed best for their individual learning styles, the Kolb concept encourages better education. Kolb believes VR and AR are the next logical steps in offering experiential learning. These diverse ranges of learning styles mean it is not possible to serve all students equally with one product. However, VR does hold the capabilities to create different experiences for each student to suit their needs and provide personalized learning experience (Hsu et al. 2013; Becker et al. 2016; Sun et al. 2016). It can be argued VR allows for different learning styles to benefit from experiential learning. For diverging learning styles, VR can provide a passive experience where they can watch and study different cultures as well as allowing them to be artistic. Students who have an assimilating learning style can have access to data visualization, making it quicker for them to comprehend analytics. Converging students can experience learning situations presented through problem-solving scenarios allowing them to learn while completing the task. And for accommodating students, they can use VR to have active experiences and engage with surroundings to optimize their learning. There is much potential in VR education. Combined with Kolb theory, it can help construct the design process for all of the Kolb scenarios. As shown in Fig. 2, the goal of the exampled software in Fig. 2 is to use experiential learning to teach students about penguins and Antarctica by placing them in a VR experience. The software provides a series of tasks such as photographing penguins with the aid of a narrator. It is not about giving the students a tutorial for taking the photos but rather about positioning the narrator as a guide providing encouragement, so the student must work out the tasks for themselves in an active and engaging manner. This method is more useful for the converging and accommodating learning styles, but this experience can be adapted. For example, it can be made into a more passive experience for diverging learning styles and include data visualization for assimilating learning styles. Using VR as a tool for the Kolb method will add new dimensions in experiential learning. By situating the student in a world of six degrees of freedom, the Kolb software is designed to optimize each student’s learning potential. The students will experience a new type of experiential learning that has not been made available before. The software can put students in almost any interactive situation to enhance their learning process. The Kolb software provides the opportunity for students to discover new skills and learn in situations best suited for them while ensuring all four

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stages of the experiential learning cycle are completed. It can maximize the education experience by providing a contemporary platform designed for a range of students and learning styles. Another key aspect to the design process for Kolb software is delivering the Kolb method through gamification of VR and AR. This will increase engagement in students and better target their learning styles. By using video game elements such as design, progress mechanics, storytelling, feedback, scaffolded learning, and collaboration, it will optimize participation and enjoyment for students within an immersive learning environment. This leads to students retaining knowledge at a higher rate and increasing their desire to take initiative by working on meaningful learning tasks. This form of education is important for students as it gives them ownership of their own learning and the opportunity to work on things such as identity, differentiated instructions, and discovering intrinsic motivators for education. These aspects are achieved by giving the students the opportunity to try and fail numerous times in a safe controlled environment. The combination of gamifying the Kolb method through AR and VR not only targets the four different learning styles but has the potential to help students who struggle with their learning (Cumming et al. 2013; Fernández-López et al. 2013). Issues such as dyslexia or attention deficit disorders can prove difficult for traditional teaching styles; however, Kolb’s software captures students’ engagement levels in a various amount of ways.

4

The Expectation of Kolb

The Kolb software is not focused on introducing the education sector to VR. It combined VR with Kolb’s experiential learning theory to achieve the best results for students. This presence of VR can be seen by the early adoption of the technology by disciplines such as biology, anatomy, geology, and astronomy. Other areas of education such as architecture, history, literature, and economics are now incorporating it into their practices in a myriad of ways. Kolb software is expected to gain higher retention rates of knowledge among participants. This will be achieved by encouraging active thinking and learning through gamification. The merging of the Kolb theory with technology and gamification is demonstrating a new form of educating the next generation of students. Students who try Kolb indicated they were more engaged and felt they would retain the information they just learnt easier because they enjoyed their experiences. With VR and AR being relatively new mainstream technologies, there is no reason to think development and hardware will not continue to improve. Combined with higher adoption rates by education institutions and mainstream society and an increase in student accessibility rates, VR and AR will become more popular and effective in the education sector. With the potential for VR training to become more prevalent in multiple industries, students will be using VR in school and in their personal and professional lives. This makes early involvement in VR training

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Fig. 5 Future education with VR and AR. (From the author)

valuable for students. As shown in Fig. 5, students are not limited by physical location or classroom anymore with VR and AR technologies. In conclusion, the Kolb theory is a highly effective method providing students with experiential learning. Emerging technologies such as AR and VR is the best platform to apply the concept. Through integrating the method with the gamification of the content, Kolb software is believed to provide meaningful learning experiences to a diverse range of students. It will allow students to retain a higher amount of information through active learning.

5

Future Directions

In recent years, VR and AR technologies have attracted researchers’ attention. Even though VR and AR technologies are not new in education, their success at transforming education has only minimal benefit to students in their learning processes and outcomes (Ainge 1995; Lee 2012; Nissim and Weissblueth 2017; White et al. 2014). Combined with traditional learning theories, VR and AR technologies can bring new learning experiences of engagement for students. But some researchers argue they are limited by hardware capability, wireless signal connections, and confidentiality of the personal information (see ▶ Chap. 2, “Characteristics of Mobile Teaching and Learning”). Some researchers argue they may create social isolation (Fernandez 2017; Ahn and Shin 2013; Primack et al. 2017). For younger

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kids, the protections of eye sight and health issues are a concern. Advanced technologies in materials and hardware, MVR (mobile virtual reality), and MAR (mobile augmented reality) enabled higher resolution and more content on mobile devices. Face recognition and fingerprint or voice recognition now provide better protection for mobile security. Blue ray protection screen and glasses are protecting the users’ eyes for health concerns. Nevertheless, there are more apps and programs developed to encourage people to communicate more with friends and family. Some educational programs encouraged leaners to collaborate or communicate when learning (Kloepper et al. 2010; Sung and Hwang 2013; Tsay et al. 2010; Enyedy et al. 2015) (see ▶ Chap. 65, “Advanced Image Retrieval Technology in Future Mobile Teaching and Learning”). Mobile technologies and devices are changing frequently. Most of the barriers facing VR, AR, and mobile education will be solved in the near future. Combined with mobile technologies, VR and AR will lead education into a new phase of virtual learning and link current teaching and learning into the future. This future will allow students who are limited by location or time the ability to learn at higher efficiency. Students can get access to tangible items too. For example they could investigate the smallest atom to the biggest star. They could travel through time to experience the history or future technology. They could play with extinct animals and learn about the future. They are not only learners but creators of their own learning space and world. Educators are not only knowledge deliverers but collaborators and learners with students to create, learn, experience, assist, and play with the students in their learning process. Dynamic and flexible curriculum will become very important to achieve the future learning goals and support these learning processes. With the collaboration among industry partners, educators, associations, educational departments, parents, and students, the emerging devices and technologies are changing the way people are living and learning. The possibilities are only limited by imaginations.

6

Cross-References

▶ Advanced Image Retrieval Technology in Future Mobile Teaching and Learning ▶ Augmented Reality in Education ▶ Characteristics of Mobile Teaching and Learning ▶ Design and Implementation of Chinese as Second Language Learning ▶ Mobile AR Trails and Games for Authentic Language Learning ▶ Mobile Education via Social Media: Case Study on WeChat ▶ Mobile-Based Virtual Reality: Why and How Does It Support Learning ▶ Parental Education: A Missing Part in Education ▶ Review of Virtual Reality Hardware Employed in K-20 Science Education ▶ Study on Networked Teleoperation Applied in Mobile Teaching ▶ Tutors in Pockets for Economics ▶ Virtual Reality and Its Applications in Vocational Education and Training

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Review of Virtual Reality Hardware Employed in K-20 Science Education

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Rebecca Hite, Gina Childers, and M. Gail Jones

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Defining Virtual Presence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Virtual Presence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 The Importance of Hardware for Virtual Presence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Use of VRE Hardware in K-20 Science Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Since the 1990s, virtual reality (VR) technology has been promoted to revolutionize learning in K-20 science education. This attribution has been largely focused on the affordances of VR software for scaffolding technical information and providing skill-building opportunities that are not readily available for learners in traditional classrooms. Moreover, VR hardware plays an important role in facilitating robust and memorable virtual learning experiences. Per experts in the field, there are three hardware categories that create VR environments (VREs): desktop, head-mounted displays, and projection systems. Within each of these three groupings, VR technologies have expanded to include both R. Hite (*) Curriculum and Instruction, Texas Tech University, Lubbock, TX, USA e-mail: [email protected] G. Childers Teacher Education, University of North Georgia, Dahlonega, GA, USA e-mail: [email protected] M. G. Jones Department of STEM Education, North Carolina State University, Raleigh, NC, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7_123

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three-dimensional (3D) capabilities and haptic feedback to enhance the virtual experience, immersion, and involvement (i.e., virtual presence) for the user. Current educational research suggests that each VR variety has distinct advantages and disadvantages, each with different efficacies and affordances for different learners. This chapter will explore the historical and current literature on VR hardware, including the incorporation of 3D and haptic-enabled elements, to enhance virtual presence and to promote the learning of science. This includes a discussion on the affordances and challenges of using VR technologies in science education within formal, K-20 science contexts.

1

Introduction

Virtual reality (VR) technologies enable K-20 students to investigate science by employing photorealistic images and sensory features (e.g., touch, sight, and sound) mimicking reality (Hite 2016) (see ▶ Chaps. 79, “VR and AR for Future Education” and ▶ 78, “Mobile-Based Virtual Reality: Why and How does it Support Learning”). These virtual reality environments (VREs), also known as educational virtual environments (EVEs) or virtual learning environment (VLEs) (Mikropoulos and Natsis 2011), provide students a unique learning experience through realistic opportunities to support motivation, interest, and learning in science. To promote realistic learning encounters in VREs, attention to how the students perceive virtual presence (how realistic the VRE appears to the user) is paramount. Designing VREs for the teaching of science concepts must support sensory and realism factors (e.g., immersions, vividness, touch, sight, sound) while decreasing distraction factors (comfortability of head-mounted gear, 3D glasses) and mediating control factors (sensor and tracking movement) of K-20 students during learning experiences. Both software and hardware contribute to users’ perceptions of presence when using VREs for student learning of science concepts, yet there is a dearth of research in the area of hardware capabilities. The topic of VRE hardware is important as these technologies have great potential in supporting student learning through immersive learning, increasing student interest, and understanding of science content and process skills. This chapter reviews research on virtual presence perception of the hardware to create VREs, specifically focusing on virtual reality, 3D, and haptics, and their use in science education. Exploring both the affordances and challenges provides insight into the benefits and limitations of VRE use in K-20 science education.

2

Defining Virtual Presence

A unique aspect of VREs is that they employ high-fidelity, photorealistic images mimicking interactions (e.g., sight, touch, sound) the user would experience in reality. This type of virtual environment conveys a rich and robust experience that

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is compelling (Wouters et al. 2013), natural (Mikropoulos et al. 1998), and engaging to the user (Graesser et al. 2014). The user characteristically experiences, to some degree, a psychological phenomenon described as a diminished sense of one’s immediate surroundings (Bulu 2012) along with a sensation of physical transportation to a simulated realm where the virtual experience feels authentic and real (McCreery et al. 2013). This construct is known as virtual presence (Fowler 2015). The term presence is an expression that describes the realness of a user’s experience within a virtual environment. Because presence is a construct that spans many academic disciplines, there are many definitions and descriptions for the concept, which is often connected to other related constructs such as telepresence (Lombard and Ditton 1997; Lee 2004; Ma and Nickerson 2006; Sheridan 1992). Presence has been described as the user’s sense of being physically present with engaged senses through the use of a remote technologies or a communicated medium (Sheridan 1992). Lombard and Ditton (1997) stated that presence is composed of several elements including realism, immersion, transportation, medium, social richness, and social actor. Furthermore, Witmer and Singer’s Conditions of Presence (1998) described the construct of presence as the level of immersion, involvement, and focus of a user in a virtual environment as governed by distractions, sensory information, realness of the virtual environment, and the perceived level of control within a virtual environment. Specifically, virtual presence describes the degree to which a user is unable to differentiate the sensory information from a hardware-mediated environment from that of reality, interpreting the virtual input as though it were from the real world (Chertoff et al. 2008). The efficacy of VREs as an instructional medium hinges on their ability to induce perceptions of presence (Mikropoulos and Natsis 2011). Most research in this area explored how the design or usability of virtual environments plays a role in inducing presence (Childers 2014; Childers and Jones 2014, 2015, 2017; Fowler 2015; Papachristos et al. 2014; Seo and Kim 2002; Tromp et al. 2003; Whitelock et al. 2000). Jones et al. (2015, 2016) documented middle school teachers’ and students’ perceived virtual presence in a VRE used to learn science content (human heart and electrical circuits). They found students reported more presence, interest, and preference to learn science in the VRE, confirming prior research indicating VREs supported students’ motivation and interest to learn science (Mikropoulos and Bellou 2006). These technologies are ever evolving and unique tools that can provide students with vivid learning experiences (Mikropoulos and Strouboulis 2004); therefore, designing immersive, present learning experiences is key to support science learning in K-20 classrooms.

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Virtual Presence

Designing and facilitating science learning experiences that promote a high degree of virtual presence and garner student motivation and interest is often connected to software applications. Specifically focusing on Witmer and Singer’s (1998)

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Conditions of Presence, software has been at the forefront of research in user’s experiences while engaged in a science learning activity (Jones et al. 2015, 2016; Childers and Jones 2015, 2017). The Conditions of Presence assessment is divided into four domains that indicate how users’ experiences may translate to virtual presence:(1) control factors (how well the user can control or regulate the actions in the software program), (2) sensory factors (how well the user can interpret sight and sound from a software program), (3) realism factors (to what extent the user can be immersed in a software application), and (4) distraction factors (to what extent the user is distracted or diverted during a learning experience caused by problematic issues with the software or external environmental issues) (Witmer and Singer 1998). However, major advancements in hardware design of VREs could help support participants’ perceptions of presence along with the effective use of the software program (Hite 2016). Hardware can also facilitate interactions that mimic reality between the user, software, and the virtual learning environment experience. To support a vivid and immersive learning environment, the hardware associated with VRE technologies can provide realistic sensory feedback to create elements of apparent realism and presence. Conversely, elements of distraction (e.g., hindering, cumbersome, or confining headgear) and perceived control factors (e.g., tracking systems not aligned) may need to be limited in providing a realistic, immersive learning experience. In designing VRE for use in science education, special attention needs to be focused on aligning well-designed hardware (and software) that limit technological and external environmental distractions while simultaneously supporting a vivid, immersive learning environment that is realistic to the user.

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The Importance of Hardware for Virtual Presence

In Dalgarno and Lee’s (2010) model of learning in VREs, there are two key characteristics for facilitating presence, the quality and authenticity of the display (representational fidelity) coupled with precise user actions (learner interaction). Representational fidelity refers to the quality of the display to produce realistic or photorealistic images (Zeltzer 1992) as well as creating a visual illusion of objects having depth and realistic qualities (Wann and Mon-Williams 1996). A hallmark of VREs is the use of 3D images (Dalgarno and Lee 2010) for user immersion and interaction (Trindade et al. 2002), creating a rich and robust experience that is both compelling (Wouters et al. 2013) and engaging to the user (Graesser et al. 2014). Hence, the 3D effect extends beyond the visual quality of the display, but also to the consistency of an object’s behavior through the learner interactions in the VRE (Fowler 2015). In addition to visual modalities, VREs may also incorporate force generating technologies, called haptics (Srinivasan 1995). Haptic-enabled technologies provide touch-based sensory feedback to the user through a hardware interface, such as a grip, vest, or stylus, that provides various tactile sensations (e.g., force or vibrations) to simulate texture, pressure, resistance, weight, or speed (Minogue

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and Jones 2006; Jones et al. 2014). Among the senses, visual information may most strongly influence presence (Witmer and Singer 1998), yet research into haptics has found that body interactions yielded an increased sense of presence for the user (Mikropoulos 2006; Slater and Steed 2000). Early studies assessing presence found using multiple sensory inputs (e.g., 3D coupled with head tracking) were associated with higher presence ratings (Arsenault and Ware 2004). Haptic feedback has been shown to provide a more immersive experience for the user (Jones et al. 2006) and more broadly that “augmented experiences that include sight, sound, movement, and haptics all contribute to a more realistic virtual environment” (Jones et al. 2015, p. 2). Provided presence is a psychological product of multiple sensory inputs (Witmer and Singer 1994), touch, and other sensory technologies that may play an important and promising role in inducing or sustaining presence in VREs (Witmer and Singer 1998). To create hardware to support 3D and haptic-enabled VREs, we review three distinct types of hardware strategies each with advantages and disadvantages: desktop, head-mounted displays, and projection systems (Limniou et al. 2008). Desktop Systems. Desktop computer systems use a cathode ray tube (CRT) monitor to produce a 3D-like (or 2.5D) effect, as limitations in the hardware have made full 3D cost prohibitive (Peled et al. 2013). User interaction is typically through a mouse and keyboard, relying heavily on the software to provide presence (Lee et al. 2010) and providing a less expensive yet less expressive environment for user immersion (Lee et al. 2013). Desktop systems that combine haptic elements and robust 3D visualization have been evidenced to be particularly powerful in promoting presence; a study by 6th and 9th grade students by Hite et al. (2017) found students had significant improvement in understanding cardiac anatomy and function, citing the affordances of visualizing a 3D heart beating in real time through a haptic-enabled stylus. Although these displays generally supported only a single view using some form of head-tracking technology (Greenwald et al. 2017), they do provide a unique opportunity for constructivist collaboration (Dede 1995). Although presence is reduced with a second user, dyadic interactions (between one user and one follower) may foster rich peer-to-peer collaboration (Bower et al. 2017). Head-Mounted Displays. Head-mounted displays (HMDs), first developed by Clark (1976), require the user to wear a combination of headgear or goggles to create the VRE. Inside, display screens produce imaginary scenery before the viewer (Shibata 2002). Early research suggested desktop and HMDs were indistinguishable in quality to the user (Peli 1998), yet a clear advantage of HMD that has emerged is their ability to create 3D stereoscopic (as compared to 2D or monoscopic) displays. There are desktop-based stereoscopic displays that provide the viewer two different images of the same object within a CRT screen, positioned for each eye to receive visual information for (binocular-based vision) depth and perception. Preference toward 3D stereoscopic viewing is based upon prior research where users reported improved performance (60%) on tasks, especially (67%) tasks of spatial

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manipulation, as compared to monoscopic viewing (McIntire et al. 2014). A study by Price et al. (2015) provided 2D and 3D stereoscopic images of the Milky Way galaxy to museum visitors and assessed their knowledge of its structure and function. Controlling for demographics between both groups, results indicated there were short-term learning gains in both the 2D and stereoscopic groups; however only the stereoscopic group exhibited long-term learning gains. Yet there are concerns with HMD use, provided it hinders the perception of oneself and others (Greenwald et al. 2017) and the headset itself can become cumbersome for the user over extended periods of time (Lee et al. 2004), facilitating visual fatigue (e.g., headaches, sore eyes) (Shibata et al. 2011) and VR sickness (e.g., nausea) (Kim and Park 2017). This is not insignificant, “although there is little evidence that viewing stereoscopic images causes irreversible damage to health, there is also no evidence that contradicts this contention” (Ukai and Howarth 2008, p.114). In a meta-analysis by Sharples et al. (2008) comparing the virtual reality-induced symptoms and effects (VRISE) among CRT, HMD, and PT systems, they found participants reported more VR sickness (60–70%) in HMD as compared to desktop VREs and greater visual fatigue in HMD as compared to projection technology systems. Higher levels of symptoms were reported from individuals who were passively viewing versus actively using the VRE interface. If users are uncomfortable wearing or using the hardware, users’ immersion and involvement in the virtual environment will diminish considerably, affecting users’ perceptions of presence. Research suggests even modest modifications in visual angles can significantly decrease VR sickness in HMDs (Tanaka and Takagi 2004), showing promise in modifying hardware to ameliorate VRE-related health issues. Projection or Holographic Displays. Projection technology (PT) systems use holograms projected on surfaces to create a VRE that may be shared with more than one user at a time (Lucente 1997). Cave automatic virtual environment (CAVE) systems employ theater settings with rear and down-facing projection screens (CruzNeira et al. 1993) to create an immersive VRE. In a study by Jung et al. (2016), they found that PT-based VREs in museums and public spaces had limitations in interaction and immersive stereoscopic viewing, yet overcame many restrictions of HMD by incorporating users into real surroundings with virtual and real objects, where users with lighter hardware may use their bodies and other users in the same virtual experience. PT displays offer opportunities for peer collaboration and recognition of oneself within the VRE. Also, body language and gestures may serve as a proxy for hardware interfaces (mouse, stylus, etc.) for more naturalistic interactions in the VRE (Salzmann et al. 2009). Although collaborative, it does “not support embodied interaction and head-tracked egocentric viewing” (Greenwald et al. 2017, p. 720). To combat reduced perceptions of presence, prior research has incorporated the use of several displays to offer improved individual user presence (Mulder and Boscker 2004) at the expense of the size of the collaboration space (Greenwald et al. 2017). Perspective projection and head-tracking hardware (Amir et al. 2016) and haptic-enabled props (Cheng et al. 2015) have been used to also improve presence, although accuracy between the user and virtual objects requires more

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research (Salzmann et al. 2009). Overall, PT systems require advanced hardware and large dedicated spaces that are costly and immobile (Roussou 1999).

5

Use of VRE Hardware in K-20 Science Education

Selection of appropriate VRE hardware in K-20 science education should both reflect the learning goal and learning context. For example, students in a study by Mikropoulos (2006) reported that HMDs were easier to use for the learning task as compared to PT systems. Research indicates that desktop VRE types were preferred by learners when the learning goal was to explore a 3D object only without any outside or peer interaction (Adamo-Villani and Wilbur 2008; Mikropoulos 2006). This may explain the expanded use of desktop systems to teach universitylevel astronomy (Eriksson et al. 2014) and chemistry (Limniou et al. 2008; Merchant et al. 2013; Stull et al. 2013). In a study by Huang et al. (2016), results showed medical students prefer desktop and PT systems in their medical training compared to traditional methods of instruction. This and research by Hite (2016) suggest age, as well as spatial ability, plays a role in the affordances of the VRE to augment science teaching and learning. In a meta-analysis by Krange et al. (2002), findings suggest few VRE specifically designed for K-12 students. A few studies have explored the learning experiences of K-12 science learners with VREs; some examples include middle graders in engineering (Klahr et al. 2007), secondary students in biology (Hite et al. 2017), and elementary students in earth science (Sun et al. 2010).

6

Future Direction

A meta-analysis by Brinson (2015) comparing learning outcomes of virtual technologies to traditional science (hands-on activities) revealed that the majority of studies (89%) found virtual technologies improved students’ outcomes in knowledge and understanding as well as skills in scientific inquiry, science procedures, and scientific communication. Clearly, the future of VRE hardware in science education is secured and will continue to expand in primary and secondary grades and with diverse learners. Research is split among scholars as to the learning affordances of VREs among users with lower spatial abilities; some argue it lowers their performance (Barrett and Hegarty 2014; Modjeska and Chignell 2003; Osberg 1997) and others suggesting VREs aid these users by reducing cognitive load (Lee and Wong 2014). Related research has also explored VREs as powerful tools for teaching students with autism (Parsons and Cobb 2011; Parsons and Mitchell 2002), with special considerations in hardware that is accommodating for persons with physical and cognitive disabilities (Newbutt et al. 2016) (see also ▶ Chaps. 70, “VR, AR, and Wearable Technologies in Education: An Introduction,” and ▶ 79, “VR and AR for Future Education”).

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Cross-References

▶ Mobile-Based Virtual Reality: Why and How does it Support Learning ▶ VR, AR, and Wearable Technologies in Education: An Introduction ▶ VR and AR for Future Education

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Index

A Accessibility, 552–554 challenges in mobile learning (see Mobile learning) definition, 552 legislation, 552 Accommodators, 793 Acquisition learning, 793 Active learning, 701 Activity, 244, 246, 249 Adaptive learning, 1107 Adaptive MALL development process, 425 application design, 425–428 on-demand content generation, 431–432 on-demand support, 433–434 system features, 428–431 vocabulary lists, 432 vocabulary meaning, 432–433 Advanced image retrieval technology advantages and disadvantages, 1141–1142, 1144 archival photo search system, 1143 CBIR, 1136, 1137 content-based image retrieval, 1140 deep convolutional neural network, 1138 deep learning technology, 1139 MedSearch Mobile system, on iPhone and iPad, 1140, 1141 mobile firefly-watching learning system, 1142 QBIC, 1138 TBIR, 1136, 1137 Affordances, 229, 233 Albania, ICT, and digitalization processes economic processes, 1104 institutional and administrative processes, 1104 Internet users, 1108

learning model, 1105–1108 Networked Readiness Index, 1106 social processes, 1104 supporting tools in learning process, 1109–1116 Albanian Higher Education digital system, 1063 Amazon Kindle Paperwhite, 799 Analysis, Design, Develop, Implement, and Evaluate (ADDIE) framework, 7 Android, 373 mobile client, 426, 428 mobile devices, China, 930 smartphone, 115 App-based learning, 1107 Apple application project, 471 Apple mobile devices, Australian students, 930 Apprentice-based model, 388 Apps, 876, 878, 881 Book Creator, 882 ChatterPix, 884 Kahoot, 881 PicCollage Kids, 884 Seesaw, 882–884 Twitter, 884–885 Archetypical peer assisted learning program, 962 ARKit, 1346 Artificial intelligence (AI), 338, 1211 Artificial neural networks (ANNs), 1138, 1211 Assessment-centered environments, 795 Assimilators, 793 Assistive and augmentative communication description, 418 English language learners’ use of, 420–421 tools, 420 Assistive technology, 637 Audio/ video conferencing, 614

© Springer Nature Singapore Pte Ltd. 2019 Y. A. Zhang, D. Cristol (eds.), Handbook of Mobile Teaching and Learning, https://doi.org/10.1007/978-981-13-2766-7

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1402 Augmented reality (AR), 394, 1107, 1224, 1354 advantages of, 1314 affordances and advantages, 1340–1341 challenges, 1317, 1342 characteristics, 1317 Construct3D system, 1313, 1314 definition, 1374 design dimensions of, 1224 dimensions of, 1277 3D printing, 1315, 1316 and 3D technologies, 1224 EcoMobile, 1316, 1343 in education, 1225, 1276, 1375–1378 and evolution, 1309–1313 future research in education, 1347–1348 implementation of, 1314, 1321 Junaio, 1322 limitations, 1342 in location, 1279 mathematical analysis, 1320 mathematical functions, three-dimensional representation of, 1315 Metaio, 1321 in mobile, 1276, 1278 in place, 1279 significance, 1287 situated learning theory, 1339–1340 social constructivism, 1339 Sky Map, 1281 trends in, 1344–1347 trials and games for language learning, 1226 virtuality continuum, 1278 wearable technologies, 1226 Augmented reality (AR) learning Fukuchiyama Rally in Japan, 1239–1240 future research, 1240–1241 heritage trails in Singapore, 1235–1236 Mega Trials in Indonesia, 1238–1239 mobile, 1232–1234 TIEs in Hong Kong, 1236–1238 trails, 1235–1240 Augmented reality interactive storytelling (ARIS), 182, 183, 187 Augmented Reality Learning (ARL) platform, 1029, 1030, 1033, 1038 Australian parents, 137 Authenticity, 1231 Authoring tools and methods, 262, 265, 266, 268 Autism spectrum disorder (ASD) behavioral skills training for students with, 1330

Index challenges in emotion recognition, 1330 description, 1328 emotion recognition for students with, 1331 interventions for emotion recognition, 1329 NIMStim Inventory, 1329 second life activities, 1332 skill deficits and limitations, 1328 AVARES Project, 1259 Avatar, 1248, 1249, 1252, 1267, 1269, 1272

B Behavioral skills training, 1330–1331 Beijing Information Science & Technology University (BISTU), 895 Beijing Union University, 500 Beijing Union University mobile learning attention control, 529 campus course selection system, 530–531 campus wireless network, 527 characteristics analysis, 546–547 expert system, 527 learning resources issues, 529 mobile blog, 526 mobile devices, books, audio, video and game learning mode, 528 mobile devices, limit for, 529 mobile terminal course selection system, 531 module integration, 546 networking achievement, 546 network tariff issues, 529 online reading, 526 podcast, 526–527 restriction technologies, 529 situation analysis, 530 SMS and MMS, 525 software (see Software) streaming media, 526 virtual reality, 527 WAP web, 525–526 Big data analysis, 1063, 1065 Big data analytics courses, 1207 description, 1206 primary goals, 1208 Bilateral teleoperation, 361, 363–364 Bilingual peer assisted learning (B-PAL) program, 963 Blended learning, 26, 624–625, 1120 mode, 498

Index B1 level, in EFL, 1177–1178 oral expression, 1178 written expression, 1178 Blogs/Blogging, 615, 1013 Bloom’s taxonomy, 795 The Blu, 1285 Book Creator, 882 Book Writer, 814 Bring your own device (BYOD), 321, 554 project, 727 strategy, 1119 British Institute of Civil Engineering, 407 Broadband, 504 Business model, e-commerce, see E-commerce business models C Café studies, 426 Career development, 669, 670 Cartoons for economics teaching, 467 Cave automatic virtual environment (CAVE) systems, 1394 ChatterPix, 884 Child care program, 820 Chinese and Australian/New Zealand Universities, 902 communication barriers, 900 cultural differences, 899 different expectations, 898 policy and structural difference, 896 Chinese character-writing program challenges for, 485–486 development, 486–487 functions design, 482–484 improvement of, 489–490 test and feedback, 487–489 user interface design, 482 Chinese language education, 145 Chinese language learning cultural study, 170–173 curriculum design and implementation for junior class, 164–169 of mobile learning and designed games, 174–175 for senior class, 169–174 evaluation of methods, 175–176 flash cards and stroke cards, 172–174 future research, 176 learn from questions, discussion, and reading, 168 literacy and vocabulary, 165–167

1403 practicing writing with drawing and mobile assisting tools, 168–169 schulte grid and games in learning, 170 situational learning and role playing, 167 students’ backgrounds and" requirements, 163–164 Chinese writing, 9 Classroom integration, 201, 204 Classroom practice, 881 The Climb, 1284 Closed apps, 819 Cloud computing, 349 Coherent professional development, 742 Collaboration multimedia, 563 text based, 562 Collaborative learning, 94, 95, 625, 1109 College Ready Ohio (CRO) project, 781–785 Common European Framework of Reference for Languages (CEFRL), 1177 Communication, 1156 Communicative Adaptability Scale (CAS), 1015 Communicative competence, EFL, see English as a foreign language (EFL) Community engagement, 984 Community of learners, 37, 44 Competency-based approach (CBA), 82 Computer-assisted academic advisement programs, 180 Computer-assisted language learning (CALL), 277, 278 Computer-supported collaborative learning (CSCL) framework, 978 Concerns-based adoption model (CBAM), 744, 875–876, 881, 885–886 Connection technologies, 1158 Construction safety, 404, 406 Content and language integrated learning (CLIL), 1236 Content-based image retrieval (CBIR), 1136, 1137 Content management systems, 615 Content providers, 336 Content recommendation, 426, 428, 430 Continuing education, 391, 393, 396 Continuing professional development (CPD), 60 Continuous learning, 794 Convergers, 793 CoreML, 1346 Course design tools, 624

1404 Course finder app, 122 Critical citizenship education, 203 Critical reflective practice, 1046 Cross-country university collaboration, 745, 891–892, 902–904 BISTU, 895–896 communication barriers, 900–902 cultural differences, 899–900 different expectations, 898–899 ECJTU, 893 policy and structural difference, 896–898 universities and agents, 893 USTC, 894–895 Crossover learning assessment design (CLAD), 914 Curricular unit (CU), 1318, 1319 Curriculum design, 225 D Data mining for anomaly detection, 1214 for association analysis, 1214 for classification, 1213–1214 for clustering, 1214 course, 1208 definition, 1213 Degree in modern languages (DML), 1176, 1177, 1179, 1181, 1182 Degree in telecommunications engineering (DTE), 1176, 1177, 1179, 1182 Design, 224, 245, 246, 249, 250 learner-centered, 226–233 Design-based research (DBR), 1320, 1321 Design practices, MCS, see Mobile City Science (MCS) Digital Agenda of Albania 2015–2020, 1103 Digital badges, 1011 Digital badging, 81 Digital divide, 74, 75, 672, 1122 Digital inclusion, M-Learning, 1076, 1077 Digital learning, 671, 674 Digital literacy, 744, 1118, 1120 Digital natives, 1119 Digital revolution, 1110 Digital technology(ies) (DT), 591, 592, 827 application, 594 context of, 594 design, 593 in higher education, 599–600 integration, 744 literacy programs, 826 research assistants (RAs), 830 teaching with, 605

Index Digital Youth Network (DYN), 296, 298 Disability, 550, 552, 555, 560, 562 Display, 1155 Distance learning, 112, 1192 Distrust definition, 682 development to, 686 treatment of, 686 vs. trust, 687 Divergers, 793 D-learning, 750 Dot™, 799 Double-loop learning, 794 Duolingo, 280–282 3D virtual world categories of, 1251–1252 educational potential of, 1252–1259 STEM entrepreneurship training and, 1270 Dynamic animation layer, 486 Dyslexia, 553, 555, 556, 559, 561, 563 E Early childhood education mobile device use in, 812–813 program features, teacher’s role, and theoretical base, 820–821 Early childhood educators, 826, 827 East China Jiao Tong University (ECJTU), 893–894 Echo™, 799 Eclipse, 801 E-commerce business models, 66, 68, 69, 74 competitive advantages, 70 competitive environment, 70 market opportunities, 69 market strategy, 70 revenue models, 69 value proposition, 68 EcoMOBILE, 1343–1344 Economic threshold concept, 471 Edgeo application, 804 Education, 222, 225, 232, 237, 239 Educational application(s), 932 Educational application providers’ platform (EAPP), 353 Educational technology, 224 VRE hardware (see Virtual reality environments (VREs)) Educational virtual environments (EVEs), see Virtual reality Environments (VREs) Education apps, 465 Education Policy Review (EPR) report, 1103

Index Education technology, 667, 670 Edutainment, 122 EFL communicative competence, see English as a foreign language (EFL) e-government services, 1104 e-Learning, 225, 238, 948, 978, 1087 in Albania, 1106, 1107 definition, 749 in geography, 979 implementation of, 987 interconnectedness of, 750 use of mobile and, 980 e-learning 2.0, 625 Elementary classroom, 877 Emaze, 1017–1018 Embodied learning/cognition, 1233 Emotion recognition (ER), 1225 Engaged learner, 683, 686, 688 Engagement, student, 250 English as a foreign language (EFL) autonomy, responsibility and collaboration, 1183–1184 communication and knowledge building, 1173–1176 communicative activities, 1177 higher education participation in, 1172–1173 level B1 in, 1177–1178 oral tasks, 1180–1183 with mobile devices, 1176 written tasks, 1179–1180 English language learners (ELL), 418 application use, 422–425 technology use, 422 Entrepreneurship, STEM training, 1270–1271 Environmental Detectives game, 1235 Environmental impact assessment (EIA), 980–982 Evidence-based teaching, 500 and mobile devices, 699–701 mobile interactive exercise for, 701–703 Exam timetable application, 122–124 Excursion, 1294, 1295, 1297, 1301 Experience-based learning, 1159, 1161 Experience design, 226, 233, 234, 239 Experiential learning, 392, 1010 Explicit knowledge, 407 Extravehicular activity (EVA), 366 F Face-to-face (FTF) learning, 15, 465 Face-to-face (FTF) teaching, 5, 36, 40, 498 Facial emotion recognition, 1331

1405 Field trip, 1282 First-generation student, 186 Flexibility, 1193 Flexible learning, 112 Flipped classroom, 94, 101–102, 796 Flipping the test, 102, 104 Folksonomie, 615 Foreign language (FL) teachers, 274 constraints, 286 as instructional designers and gamifiers, 278–280 MALL materials, TTS software in (see Textto-speech (TTS), MALL materials) Formal and informal learning, 1024 bridging, 1026–1027 overview of, 1024–1025 view of, 1025–1026 Formalized learning, 792 Formal teaching, 968 Framework, 260, 262, 269 Framework for the rational analysis of mobile education (FRAME), 724, 978 G 4G, 336 Gamification, 612, 914, 995, 1107 aesthetics, 996, 997 collaboration, 997 Duolingo, 1001–1002 feedback, 998 game thinking, 996, 997 goals, 996 LingoBee, 1002–1003 LLG, 1000 mechanics, 996, 997 progression in levels, 999 reward and competition, 998 storytelling, 999 Gender, 202, 551 Generation Y, 337, 405, 406 Line, 409, 410 WeChat, 410 WhatsApp, 409, 410 GeoGame project, 803 Geography, 1045 Geolocative data, 291, 301, 304, 309 Gestalt principles of visual design, 426 Global Science Academy (GSA), 296, 299, 300 Google, 932 Google Earth VR, 1283 Google Expeditions, 1283

1406 Graphic users interface (GUI), 482 Grolier Online, 802 Grounded theory study, in Australia, 391 H Haptics, 1392 Head mounted displays (HMDs), 1341, 1393 Head start program, 820 High/scope programs, 820 Higher education, 250, 513, 894, 896 See also Mobile learning, higher education Higher-fidelity (Hi-Fi) approach, 426 HILINK microcontroller board, 362 HTML5, 485, 613 web based interactive program, 339 Human centered design, 182 Human-computer interaction (HCI), 227, 229, 238 Hybrid AAC-MALL tool application use, 436–438 design evaluation, 434 language-learning strategies, 436 technology use, 436 Hypothetical model of immersive cognition (HMIC), 1224, 1367 cognitive overload and physical challenges, 1359–1360 definition, 1356–1359 I Image retrieval technology, 1063, 1135–1143 adoption of, 1134 advantages and disadvantages, 1141–1144 development of, 1134 use of, 1134 Image search, 1135, 1137 Immersive environment, 1355, 1357 Immersive virtual reality (IVR), 1355 authentic experience, 1360–1361 design and instructional considerations, 1361–1367 embodied cognition theory, 1355 HMIC (see Hypothetical model of immersive cognition (HMIC)) information processing model, 1355 India, 1063 Indiana public school superintendents and teachers, instructional technology leadership, see Instructional technology leadership, in K-12 public schools

Index Indigenous tutorial assistance scheme (ITAS), 964 Informal learning, 1233 Information and communication technology (ICT), 110, 321, 1103, 1308, 1309, 1311, 1313 government and non-government organization initiatives, 113 mobile devices in education, 113–114 mobile devices in Pacific, 114–116 universities initiatives, 113 usage in pacific island countries, 112–113 use in education, 111–112 Information processing theory, 1358 Infrastructure as a service (IaaS), 352 Innovation, 875 Instagram, 1016 Institutional evaluation mechanisms, 1045 Instructional design, 222, 224–225, 234, 235 Instructional technology leadership, in K-12 public schools, 848, 850–851 alignment/agreement, in demographic responses, 861 data analysis, 858 data collection procedure, 856–857 data visualization, 855 decision-making, 861–865 digital technologies, in K-12 classrooms, 849 instruction, 852 level of knowledge, 866 limitations, 857–858 participants, 856 professional development, K-12 teachers, 849 ranked mean scores, 860–861 research questions, 852–853 standard deviation, 861 students, network connection, 865 survey design, 853–856 technology integration, 851 Intellectual property (IP), 4 Interaction, 1170, 1175, 1182, 1184 Interactive exercise, 702–704 mobile, evidence-based learning, 701 mobile response system, 703 Interactive learning environment (ILE), 1175, 1176 Interactive problem-solving activity, 702 Interactive tangible technology, 637 Interactive technology, 637 International Society for Technology in Education (ISTE) standards, 865

Index Internet, 1009, 1011, 1013, 1015, 1019 control and censorship, 506 mobile, 504, 506 role of, 406–407 Internet-based PAL programs, 965–967 See also Peer assisted learning (PAL) Internet-based peer assisted learning, 913 Internet censorship, 499 Internet of Things (IoT), 339, 372, 1150, 1153, 1166 network, 374 nodes, 375–378 technology, 373 traditional laboratory vs. smart laboratory, 374 Internet usage, 110 Inverted classroom, 796 Invisible world, 1069 iPAC framework, 1231 iPad apps, 815–816, 827, 828, 831, 832, 835, 837, 838, 843 iPhone/iPad operating system (OS), 379, 383, 384 iPod touch applications, 660 description, 660 uses, 661 IPv4, 374 iSmartControl, 379, 380 iSmartHome2, 379 J Just-in-time education, 392 K K-12 instructional technology leaders, 744 Kiwi Mobile game, 1235 Knowledge-centered environments, 794 Knowledge mapping, three-dimensional augmented reality technologies, see Augmented reality (AR) Knowledge sharing, Generation Y, see Generation Y Knowledge systematization, 317–326 Kolb method design process and reasoning, 1380–1383 future education with VR and AR, 1383–1384 virtual/augmented reality, 1378–1380 Kolb’s experimental theory, 1224 Kolb’s learning style inventory (LSI), 793

1407 Kolb theory, 1382 K-20 science education, VREs hardware, see Virtual reality environments (VREs) L Labwork, 1294, 1297, 1302 Landlord Real Estate Tycoon, 1286 Language learning, 338, 481 features of, 992 foreign, 994–995 gamification (see Gamification) strategies, 421–422 Language learning game (LLG), 1000–1001 Language Mega app, 1238 Language teaching, 993, 1000, 1001 Learner-centered environments, 794 Learning acquisition, 793 analytics, 1126–1128 assessment, 795–796 design, 233 enabling effective, 794–795 formalized, 792 granularity of, 797 in MCS (see Mobile City Science (MCS)) mobile, 242 process, 1109 sciences user interface design, 227 theory, 38, 39 Learning 2.0, 632 Learning-conscious learning, 792 Learning management systems (LMS), 112 Learning technology, 233 five decades of, 1150–1154 Lesson, mobile, 244–246, 249 Lifelong learning, 347, 353 Line, 409 Location, 1279 Long-term memory (LTM), 1358, 1360, 1362, 1363 Lyapunov–Krasovskii (L-K) functionality, 362 M Machine learning, 1211 Manual dexterity, 556, 563 MASELTOV project, 1235 Mashups, 615 Massive open online courses (MOOCs), 112, 328, 612, 796, 1052 Math 180, 802

1408 Mathematical analysis (MA), 1318, 1320, 1322 MATLAB, 362 MCS curriculum design, see Mobile City Science (MCS) MedSearch Mobile system, 1140, 1141 Message management, 579 Micro-credentialing challenges, 83–84 context, 79–80 device mobility, 85–86 disaggregation/re-aggregation, 82–83 implications for practice, 87–88 learner mobility, 84–85 methodology, 79 micro-credential mobility, 86–87 micro-rewards, 81–82 and mobile learning, 84–87 principles of, 78 rationale for, 80–81 Micro-learning, 1107 Micro-rewards, 81 Microsoft Store, 1378 Ministry of Innovation and Public Administration (MIAP), 1106 Mixed reality (MR), 1278 Mobile, 242, 243 broadband devices, 1338 broadband prices, 73–74 digital technology, 659, 662 lesson, 244–246, 249 Mobile affordances, Conditions, Outcomes, Pedagogy and Ethics (M-COPE) framework, 978 Mobile application, 187, 194, 227, 237 design, 18 for economics students (see Tutors in Pockets) nursing education, 393 Mobile Application Technology (MAT), 328 Mobile apps for communication, Generation Y aims, objectives and functions, 411 Line, 409, 410 WeChat, 410 WhatsApp, 409, 410 MOBIlearn Task Model, 722 Mobile assisted language learning (MALL), 9, 419–420, 447, 1235 adaptive development (see Adaptive MALL development process) gamification (see Gamification) initiatives, 994 TTS software in (see Text-to-speech (TTS), MALL materials)

Index Mobile augmented reality (MAR), 349 Mobile-based virtual reality, see Virtual reality (VR) Mobile City Science (MCS), 290–291 curriculum implementations, 298–301 data analysis, activities for, 294–295 data collection, curriculum activities for, 293–294 design practices, 301–308 location-aware and mobile technology, 291–292 research collaborations and training, 296–298 smart and connected cities initiatives, 292–293 spatial arguments, activities for, 295 Mobile City Science (MCS) project, 9 Mobile device, 590, 597, 599, 603, 667, 668, 944, 947 characteristics, 603 functional, 348 mobile technology, 349–350 penetration, 505, 513 usability, 348 Mobile education cost, 350–351 educators, 353 efficient education, 346–347 flexible education, 346 framework, 337 individualization education, 347 lifelong education, 347 medical education architecture, 345 mobile device, 348 online and off-line, 350 overall system architecture, 344, 345 parents, 354 pervasive education, 346 students, 354 system model, 343 traditional education, 342–343 tutors in pockets, 344 Mobile information technologies, 743 Mobile learning (m-learning), 78, 182, 222–224, 249, 250, 259–260, 464–466, 748, 750, 751, 978, 980, 984, 1019, 1062, 1063, 1107, 1121, 1122, 1190, 1191, 1193, 1200, 1202, 1292, 1314, 1319 activity theory, 751 advanced image retrieval technology (see Advanced image retrieval technology)

Index advantages and disadvantages, 1018 applications, 742 assisted learning function, 524 in Beijing Union University (see Beijing Union University mobile learning) benefits in higher education, 1089–1091 BYOD, 554 challenges in adopting, 129–130 challenges of, 1009 cloud computing, 509 contemporary, 749 content design, 556–557 correlation learning environment, 524 definition, 110, 316, 522, 718, 749, 993, 1008, 1087–1088 design, 1073, 1075 design guidelines and frameworks, 720–724 design process, 224, 233, 234 development stages, 522–523 devices, 1088 device size, 554–555 differentiated and personalized, 719 digital inclusion, 1076, 1077 digital learning and networking, implementation of, 523 digital multimedia medium, 742 educators’ perspective, 1124–1125 efficacy, 1071, 1072 EFL (see English as a foreign language (EFL)) and e-learning, 508–509 electronic publishing, 510 extensive range of education, 524 features, 994 flexibility, 1124 in foreign language learning, 994 form of, 523 future research, 1128 gamification, 510 high-efficiency study, 524 in higher education, 720 higher education institutions, 317 image retrieval technology, 1063 implementation in Chinese learning, 174 interactive learning content, 523 internet control and censorship, 506 learner-centered learning in, 750 learner perspective, 1123 learning analytics, 1126, 1127 as learning tool, 1075 levels of, 1230–1232 methodology, 625

1409 mobile and networked devices, 1064 multimedia collaboration, 563 myths and expectations of, 1063 in Nigerian university system, 1065 off-line activities, 582 in online and distance courses, 1064 online databases, 315 opportunities of, 718–719 personalized learning, 149, 524 potential, 1077, 1082 pre-school-aged children, 744 principles, 1073 problems of, 567 processes of, 751 recommendations, 724–729 in relation to secondary and tertiary students, 748 requirements hierarchy, 1122, 1123 requisite, 1072 research trends in, 743 in rural India, 1070, 1071 scheduling, 560–562 self-regulated learning in, 751 service-learning curriculum, social media tools (see Social media) short message service gateway, in USP, 118–121 in smaller time slots, 524 smartphone ownership, 506–508 social networking, 509, 510 sociocultural theory, 750–751 Southeast Asia, 511, 515 study environment, 559–560 SWOT analysis, 317 text based collaboration, 562 text considerations, 555–556 theoretical models, 233, 239 touchscreens, 556–558 trade-off issues, 1128 and U-learning, 1064 universal education, goal of, 524 visualize TOEFL speaking (VTS), 730–734 voice recognition, 558 web 2.0, 616–625 Mobile learning and education, 327 additive technology, 320 connected classroom, 318 environment and development, 320 just-in-time training, 320 oriented technology, 318 portable miniaturization of e-learning, 318 students and teachers’ perceptions and practices, 324–326

1410 Mobile learning and education (cont.) students’ perceptions and practices, 320–323 teachers’ perceptions and practices, 323–324 Mobile learning, higher education content and knowledge storage, 943 creativity, 944 evaluation models, 946, 948 framework, 948, 954 interactivity, 945 knowledge and application gap, 943 Mobile micro learning, 395 Mobile phone(s), 446, 1090 capacities and application, 1092 usage, 1111 Mobile response system (MRS), 703–711 Mobiles for development, 512 Mobile teaching advanced image retrieval technology (see Advanced image retrieval technology) networked teleoperation (see Networkbased teleoperation) Mobile teaching and learning, 3, 10, 14–16, 463–464, 918 accessibility in, 498 advantages of, 5, 498 Australian vs. Chinese students, 929–933 Australian mobile devices market share, 21 barriers, 6, 497, 499 challenges for, 6 Chinese mobile devices market share, 21 commercial products, 802 cost of, 18, 19 design and implementation of, 498 design for, 24–26 design structure, 336 development of mobile technologies, 16 disadvantages, 5 3D VR technology, adoption of, 17 Edgeo application, 804 essential elements for implementation, 336 evidence-based teaching, 500 expectation and benefits, 22, 24 GeoGame project, 803–804 government policies and regulations, 501 in higher education in Nigeria, 1091–1096 implications for applying, 797–798 initiatives in higher education, 913

Index internet censorship, 499 length of mobile learning time per day, 23 limitations, 6 literature and empirical studies, 919–921 mobile learning curricula, 4 mobile teaching curriculum, 500 networked teleoperation, 339 nursing education, 338 scenarios of, 19 and service learning, 914 SMS, 6 social media, 500 software development methodologies, 801 sources of mobile learning, in Australia, 23 student feedback, 914 SWOT analysis, 6 technologies, 792, 799–801 usages of mobile devices, Australian and Chinese students, 22 vector training module, 804 Mobile technology, 3, 4, 14, 24, 26, 261, 262, 266, 290–292, 296, 308, 310, 481, 613, 891, 901, 904, 905 advantages, 582 applications of, 1277 AR in, 1276 cloud computing, 349–350 dimensions of, 1277 mobile augmented reality application in, 349 virtualization technology, 349 Mobile TTS materials, MALL, see Text-tospeech (TTS), MALL materials Mobilizing National Educator Talent (mNET), 776–781 features, 777 goals, 776 logic model for evaluation, 778–779 partners, 777–778 ToR Instructional and Technology Skills, 780–781 MobiVET 2.0 project, 502 MobiVET mobile learning courses, 627, 628 MoLeNET program, 114, 1008 Montessori program, 821 Moodle, 280, 284, 285 MOODLE learning management system, 6 Multimedia messaging service (MMS), 525 Multimedia production tools, 624

Index Multimedia teaching, qualitative interview for, 921 Multimodality, 448 Multi-touch applications, 639, 649 MyVoice, 420, 424 N National Climate Change Adaptation Research Facility (NCCARF), 1053 National Strategy for Development and Integration (NSDI), 1103 Nature user interface (NUI), 471 Near field communication sensor, 799 Network-based teleoperation bilateral teleoperation, 363 fundamental, 365 military/defense, 366–367 space, 366 stability and transparency analysis, 364 TCP and UDP protocol networked systems analysis, 365–366 telesurgery, 367 Networked Readiness Framework, 1105 Network effects, 72–73 Neural networks based on competition, 1212 course, 1208 for pattern association, 1212 for pattern classification, 1212 New York Hall of Science (NYSCI), 296, 297, 299, 300, 306, 307 Next Generation Science Standards (NGSS), 1029, 1034, 1035 Nigeria cost of mobile device, 1094 electricity supply, 1093 lecturers and students readiness to use technology, 1094 management and maintenance of mobile devices, 1093 measures for mobile learning issues and challenges, 1095–1096 mobile learning applications, 1094–1095 Non-traditional student, 186 Nursing education, 388 artificial intelligence agents, 397 augmented reality, 394–395 background of, 399 considerations for mobile learning, 397–398 contextual learning, 392–393

1411 e-learning, mobile device, 391–392 just-in-time education, 392 mobile apps, 393 mobile learning, 391–396 podcasts, 395 SMS, 395–396 social media, 394 O Objective-C, 384 One-to-one iPads (1:1 iPads), 744 Book Creator, 882 ChatterPix, 884 levels of use, 879–881 PicCollage Kids, 882, 884 Seesaw, 882 stages of concern, 876–879 teachers’ technology acceptance, 874–875 Twitter, 882, 884 Online graduate certificate in climate change adaptation, 1045–1047 external influencers, 1053–1054 future research, 1054 institutional support, 1052 interactive PDF model, 1047–1050 post-delivery reflections, 1050 production of content, 1050–1052 workload realities, 1052–1053 Online learning, 40, 52, 54 Online presentation tools, 614 Online professional learning, for sessional teachers accessibility, 53 BLASST model, 51 context independency, 53 Flexi-ULT, 58 formal courses, 52 online design pedagogical principles, 53 online modules, 55–58 practice relevancy, 53 ‘push’ or pull’ delivery models, 51 The RED Report, 51 Springboard into Teaching, 59, 60 teaching support and development practices, 51–52 temporal proximity, 53 ULT program, 58 Open access research, 320 Open-Book-Open-Web (OBOW) approach, 94 OpenCourseWare (OCW), 1172–1173

1412 Open educational resources (OER), 328 Open-ended apps, 819 Open University, 6

P Paper-prototyping, 425 Parental education content development and system design, 150–151 effective learning with children, 151 first, 140 future design, 152 immigrated family on social media, 143–149 importance of, 137–140 lack of formal parenting programs, 140–141 mobile technology in, 149–152 off-line activities, 151 programs and solution, 142–143 reasons for missing, 141–142 survey on Chinese background families in Wollongong, 153 Parents learning, 150 Participant’s perspective, 1294, 1297, 1301, 1303 Participatory communities, 680, 683, 686, 692–693 Partnership, evaluation, design, and implementation (PEDI) framework, 743, 767–769 Pattern classification tasks, 1212 Pedagogical approach, 942, 951, 952 Pedagogy, 38–40 definition, 591 educational purposes and, 978 instructional, 603 knowledge of content and, 594 and learning experiences, 594 Peer assisted learning (PAL), 913 aims, 961 bilingual, 963 description, 960 effectiveness evaluation, 969–970 face-to-face models, 962–965 future development, 970–972 implementation structure, 968–969 internet based programs, 965 philosophy of, 961–962 teaching materials, 964 traditional model, 962 Pen stroke card, 172

Index Performance support, 224–225 Personal digital assistants (PDAs), 316, 323, 324 Personalized learning, 1191, 1196, 1199 Philosophies of teaching, 593, 595 Physical education interactive multimedia, 656, 659 mobile digital technology, 659, 662 PicCollage Kids, 884 Pinterest, 1012 Place, 1280 Platform as a service (PaaS), 352 Player testing high-fidelity ARIS prototype and, 187–188 medium-fidelity powerpoint prototype, 186–187 Pocket Trips app, 1236 Podcast mobile learning, 526 Podcasts, 395 Point of view video glasses, 1294 Pokémon GO, 1285, 1345 PoodLL language, 285 Popplet, 1013 Postgraduate accounting course, 94, 105 P-16 partnerships, 765 evaluation design, 773–775 implementation of M-learning by stakeholders in, 772–773 iterative design of M-learning by stakeholders, 770–771 Pre ICT Induction (PICTI) on a mobile screen, 1129 Preschool-aged children challenges with mobile devices in, 817–818 digital literacy and multiliteracies, 813–814 iPads, 815–816 media and technology, 811–812 Pre-University Education Development Strategy (PUEDS), 1103 Principle investigator (PI), 296 Prison/prison students, 551 Problem-based learning, 913 Process models, 233, 234, 237 Professional development, 50, 52–54, 669, 670 Professional learning, for sessional teachers, see Online professional learning, for sessional teachers Program evaluator (PE), 296 Progressive education, 202 Projection technology (PT) systems, 1394 Prometeo, 1172 Public broadcasting service (PBS) programming, 818

Index Q Quadrant-based framework, 1224 Query by image content (QBIC), 1138 Quizlet, 280, 282, 285 R Rational Analysis of Mobile Education (FRAME) model, 751–752 Read 180, 802 Real-time assessment, 699, 701, 703, 712 Reflection, 596, 597, 604 Reflective practice, 794 Reggio Emilia program, 820 Representational fidelity, 1392 Research associate (RA), 296 Responsive web design (RWD), 613 Revenue models, 69 RSS feeds, 614 S Safety information module (SIM), 404 Safety knowledge in mobile educational programs, 337 Safety knowledge module (SKM), 404 Safety semantic wiki tool (SSWT), 404 SchoolNet, 113 Science education, VREs hardware, see Virtual reality environments (VREs) Science Teachers Accelerated Program, 125 Screen size, 555, 558, 562 Second language learning, 163 See also Chinese language learning Seesaw, 882 Sense of presence, 1357, 1362, 1365, 1367 Sensor, 1156, 1158 Service learning, 914, 1011 definition, 1010 social media sites, service-learning curriculum (see Social media) Sessional teachers, online professional learning, see Online professional learning, for sessional teachers Short message notification service (SMS), 6 Short messaging service (SMS), 525 Simultaneous localization and mapping (SLAM) technology, 1345 Situated/contextual learning, 1233 Situated learning theory, 1339 Situated mobile learning, 1154 components of, 1160 steps for, 1160 Situative learning approach, 182

1413 Sky Map, 1281 Small group discovery, 979 Smart glasses, 1293 SmartLab system, 339 benefits for students, 383 benefits for university, 381–382 courses for students, 381 future research, 384–385 IR repeater, 377 logic structure, 374 management, 378 mobile apps for, 378–381 potential of, 383–384 Smart partnership, 765 Snapchat, 1017 Social change games (SCG), 200 Social constructivism, 1233, 1339 Social impact games, 200, 201, 203, 210, 213 Social justice, 200, 201, 203, 209, 213 Social learning, 1107 Social media, 137, 140, 143, 394, 491 blog, 1013–1014 in China, 568 development, 566 digital badges, 1011–1012 Emaze, 1017–1018 Instagram, 1016–1017 learning through, 567 networking applications, 615 Pinterest, 1012–1013 platform for education purpose, 566 Popplet, 1013 Snapchat, 1017 in teaching and learning, 567 Twitter, 1014–1015 WeChat, 569 YouTube, 1015–1016 Social networking services (SNSs), 612 Social science, 200, 202, 209 Software, 532 academic administrator module, 538 adding courses, educational administration personnel, 544 checking courses, educational administration personnel, 544 course list page, 541 deleting courses, educational facility managements, 545 detailed design of, 533–539 development environment, 532 educational facility managements’ functions, 543 list of courses, 538

1414 Software (cont.) login selection page, 539 logon page, 540 overall implementation, 533 student course evaluation function page, 540 student module, 537 students’ cancellation page, 542 students’ functions page, 541 system permission, 533 teacher function page, 543 teacher module, 537–538 Software as a service (SaaS), 350–352 Source, 1156 Southeast Asia e-learning and mobile learning, 508–509 mobile device ownership, 506–508 mobile internet, 504–506 mobile learning East Timor, 511 Indonesia, 512 Philippines, 513–514 Singapore, 514 Thailand, 514–515 technology trend, 509–511 Spaced learning, 232–233 Spaced repetition, see Spaced learning Spanish, 338 Spanish language learning, 446 Specific learning disabilities (SLD), 636 tangible technology, 638 Spy glasses, 1226, 1293, 1294 in classrooms, 1298 for data-collection, 1295–1299 lab group, 1296 recorded material, 1299 SQLite™, 801 Standard Language Tessellation, 1321 SteamVR, 1378 STEM education, 1029 Streaming media, 526 Strengths, weaknesses, opportunities, and threats (SWOT) analysis, 6, 318 Student orientations, 195 Students and teachers’ perceptions and practices, 324 Study environment, 559–560 Substitution Augmentation Modification Redefinition (SAMR) model, 723 Sustainable engineering design, 1024 CLAD on, 1028–1029 System 44, 802 Systemic functional linguistics, 448

Index T Tablet learning project, 125 deployment, 125–127 student feedback, 127–129 Tablets for Students, 113 Tacit knowledge, 407 Tagging, 615 Tangible mobile application, 647 working principle of, 648 Tangible models, 648 Tangible objects, 639, 644, 648 Tangible technology accessibility, 638 characteristics of, 637 collaboration, 638 interaction in, 637 and specific learning disabilities, 638 students with SLD, 646 Tangible tools, 637 Target language (TL), 275, 276, 280 Task-conscious learning, 793 Teacher-parent communication channel, 164 Teaching, 243 and learning, 661 and learning strategies, 268 methods, 590 nature of, 591 philosophical underpinnings of, 593–594 Technology acceptance, 874, 886 Technology enhanced learning (TEL), 1009, 1250, 1267, 1272 Technology mediated assessments, 1024, 1027 CLAD and, 1027–1028 in GreenDesigners, 1029–1036 SPS and PFL elements in, 1036–1038 Technology oriented learning tools, 1062 Teleoperation, network-based, see Networkbased teleoperation Text-based image retrieval (TBIR), 1136, 1137 Text-to-speech (TTS), MALL materials, 277–278, 286 adaptation, 281–282 creation, 283–286 customization, pedagogical use, 280 input and autonomous learning, in FL classroom, 275–277 modification, 282–283 The Graduation Game (TGG) data collection, 190–191 design, 182–183, 188–190 email distribution, 193 evaluative feedback on, 194

Index future research, 195 iterations of, 183–188 mobile technology for academic advising in higher education, 194–195 orientation distribution, 193 testing before distribution, 192–193 Three-dimensional augmented reality technologies, see Augmented reality (AR) Time delay, 361 Timetabling, 561, 562 TinCan API, 613 Tool development, 439 Touchscreen, 227, 556–558, 562 Toy Story app, 814 Traditional education, 342, 355 Traditional lecture-based teaching, 796 Traditional student, 186 Trails of integrity and ethics (TIEs), 1237 Transactional Distance Theory (TDT), 724 Transmission Control Protocol (TCP), 365 Trust associative, 685 asymmetrical, 686 calculative, 685 cognitive, 685 context specific, 685 definition, 683, 684 disposition to, 685, 686, 688 dynamic, 685 emotional, 685 information sharing, 682 interpersonal, 692 in others, 681 propensity to, 686, 690 relational, 685 self-reinforcing, 686 social, 691 subjective, 686 traditional view, 687 transitive, 686 urban adolescents, 681 Tutors in pockets (TIPs), 344, 464, 681, 918 application design for flexibility and extendibility, 469–472 comparative evaluation, Australian and Chinese students, 927 design, 466 flexible contents for mobile devices and FTF teaching, 466–469 limitations and future research, 473 multimedia materials, 927 objective evaluation, 926–927

1415 qualitative interview for multimedia teaching, 921 survey for IOS and Android version, 924–926 survey for IOS version, 921–924 survey results for, 475 Twenty-first century learning, 203 Twitter, 884, 1014 U Ubilingua, 1173–1174, 1176 Ubiquitous computing, 1154, 1155 UCI Machine Learning Repository (UCI MLR), 1215 U-learning, 750, 1063, 1064 U-learning, EFL higher education participation in, 1172 with mobile devices, 1176 Ultra-mobile personal computer (UMPC), 1088 Unified theory of acceptance and use of technology (UTAUT), 322 Universal instructional design (UID) principles, 723, 1122 University collaboration, cross-country, see Cross-country university collaboration University Learning and Teaching (ULT) program, 58 University of Science and Technology of China (USTC), 894 University of the South Pacific (USP), 116 mobile learning, 118–121 short message service gateway, 118–121 tablet learning project, 125–129 USPNet, 117 web-based services, 122–123 Unmanned combat air vehicle (URAV), 366 Urbanisation, 985 User Datagram Protocol (UDP), 365, 368 User testing, 455–458 USPNet, 117 V Vecindario, 450–455 Vector training module, 804 Video-based supplemental instruction (VSI), 966 Video games, 200 impact of, 200 and mobile video games, 209–210 power of, 201

1416 Video learning, 1107 Virtuality continuum, 1278 Virtualization technology, 349 Virtual learning environment (VLE), 1126, 1190–1193, 1260 Virtual presence, 1390 definition, 1390–1391 importance of hardware for, 1391–1395 Virtual reality (VR), 1224, 1390, 1394 autism spectrum disorder, 1225 behavioral skills training, students with autism spectrum disorders, 1330 classroom design, 1367 concept, 1247 definition, 1247, 1354, 1374 in education, 1376 embodied cognition theory, 1355 emotion recognition, students with autism spectrum disorders, 1331–1332 environments, 1267 Google Earth, 1279 hardware affordances and challenges, 1225 HMIC (see Hypothetical model of immersive cognition (HMIC)) information processing model, 1355 LMS Moodle and, 1260 mixed reality, 1278 mobile learning, 527 scope of, 1361–1362 simulators, 1247 for STEM entrepreneurship training, 1270 types of, 1248–1250 in vocational education and training, 1227 VREs (see Virtual reality Environments (VREs)) Virtual reality environments (VREs), 1390 desktop systems, 1393 efficacy of, 1391 haptics, 1392 HMDs, 1393–1394 in K-20 science education, 1395 learner interactions in, 1392 projection/holographic displays, 1394–1395 representational fidelity, 1392

Index Virtual worlds (VW), 616, 1354 Visual impairment, 553, 556, 558, 559, 563 Visual Studio, 801 VLE, see Virtual learning environment (VLE) Vocational education and training, 625 Voice recognition, 558 W Waldorf program, 821 WAP-based protocol, 1088 Wearable devices, 1292 Wearable technologies applications, 1294 capabilities of, 1293 Web 2.0, 613–616, 628 Web applications, 800 Web-based client interface, 426 Website creation platforms, 624 WeChat, 410, 491, 500, 567, 569 mobile class on, 571 usage, 569 users, 570 vs. Weibo, 569 WeChat groups for Chinese parents, 149 Weibo, 568 WEMOSOFT, 165 WhatsApp, 409, 410 Wi-Fi, 17, 18 Women, 551–552 WordPress, 1013 Working memory (WM), 1358, 1362 X Xcode, 384, 801 Y YouKu Tudou, 932 Youth in online spaces, 692 and social communities, 680 YouTube, 1015