Visions and Concepts for Education 4.0: Proceedings of the 9th International Conference on Interactive Collaborative and Blended Learning (ICBL2020) ... in Intelligent Systems and Computing, 1314) 3030672085, 9783030672089

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Advances in Intelligent Systems and Computing 1314

Michael E. Auer Dan Centea   Editors

Visions and Concepts for Education 4.0 Proceedings of the 9th International Conference on Interactive Collaborative and Blended Learning (ICBL2020)

Advances in Intelligent Systems and Computing Volume 1314

Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Advisory Editors Nikhil R. Pal, Indian Statistical Institute, Kolkata, India Rafael Bello Perez, Faculty of Mathematics, Physics and Computing, Universidad Central de Las Villas, Santa Clara, Cuba Emilio S. Corchado, University of Salamanca, Salamanca, Spain Hani Hagras, School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK László T. Kóczy, Department of Automation, Széchenyi István University, Gyor, Hungary Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA Chin-Teng Lin, Department of Electrical Engineering, National Chiao Tung University, Hsinchu, Taiwan Jie Lu, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia Patricia Melin, Graduate Program of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico Nadia Nedjah, Department of Electronics Engineering, University of Rio de Janeiro, Rio de Janeiro, Brazil Ngoc Thanh Nguyen , Faculty of Computer Science and Management, Wrocław University of Technology, Wrocław, Poland Jun Wang, Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

The series “Advances in Intelligent Systems and Computing” contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the areas of modern intelligent systems and computing such as: computational intelligence, soft computing including neural networks, fuzzy systems, evolutionary computing and the fusion of these paradigms, social intelligence, ambient intelligence, computational neuroscience, artificial life, virtual worlds and society, cognitive science and systems, Perception and Vision, DNA and immune based systems, self-organizing and adaptive systems, e-Learning and teaching, human-centered and human-centric computing, recommender systems, intelligent control, robotics and mechatronics including human-machine teaming, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, Web intelligence and multimedia. The publications within “Advances in Intelligent Systems and Computing” are primarily proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results. Indexed by SCOPUS, DBLP, EI Compendex, INSPEC, WTI Frankfurt eG, zbMATH, Japanese Science and Technology Agency (JST), SCImago. All books published in the series are submitted for consideration in Web of Science.

More information about this series at http://www.springer.com/series/11156

Michael E. Auer Dan Centea •

Editors

Visions and Concepts for Education 4.0 Proceedings of the 9th International Conference on Interactive Collaborative and Blended Learning (ICBL2020)

123

Editors Michael E. Auer Carinthia University of Applied Sciences Villach, Austria

Dan Centea McMaster University Hamilton, ON, Canada

ISSN 2194-5357 ISSN 2194-5365 (electronic) Advances in Intelligent Systems and Computing ISBN 978-3-030-67208-9 ISBN 978-3-030-67209-6 (eBook) https://doi.org/10.1007/978-3-030-67209-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021, corrected publication 2021 This work is subject to copyright. All rights are solely and exclusively licensed 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, expressed 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 Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

ICBL2020 was the 9th edition of the International Conference on Interactive Collaborative and Blended Learning. The conference focused on the fundamentals, experiences, and applications in blended learning and related new technologies, including topics in interactive, collaborative, and blended learning; technology-supported learning; pedagogical and psychological issues; and real-world experiences. Other objectives of the conference were to discuss guidelines and new concepts for engineering education in higher education institutions, including emerging technologies in learning; to debate new conference format in worldwide pandemic and post-pandemic conditions, and to discuss new technology-based tools and resources that drive the education in non-traditional ways such as Education 4.0. ICBL2020 has been organized as a virtual event by McMaster University in Hamilton, Ontario, and Canada, between October 14 and 15, 2020. This year’s theme of the conference was “Vision and Concepts for Education 4.0”. The following outstanding educators and researchers from around the world accepted the invitation to deliver keynote speeches: • Uriel Rubén Cukierman, Director of the Center for Educational Research and Innovation at the Universidad Tecnológica Nacional (UTN) in Argentina, and President of the Argentinean Section of the International Society for Engineering Pedagogy (IGIP). Title of the keynote address: A Perfect Storm for Higher Education • Rocael Hernandez Rizzardini, Director Galileo Educational System, Universidad Galileo, Guatemala. Title of the keynote address: The 4th Industrial Revolution: Challenges and Opportunities • Dominik May, Assistant Professor in the Engineering Education Transformation Institute, Athens, GA, USA, Vice President of the International Association of Online Engineering (IAOE). Title of the keynote address: How Cross Reality Technology is changing Engineering Education

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Preface

• Yevgeniya Sulema, Associated Professor and Vice-Dean at the School of Applied Mathematics of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine. Title of the keynote address: Digital Twins Technology for Education 4.0 An exciting workshop was held: “Lessons learned from teaching a large introductory psychology course: What works and what doesn’t, and what isn’t worth the effort”. Facilitator: Joe Kim, PhD, Associate Professor, Department of Psychology, Neuroscience and Behavior, Faculty of Science, McMaster University, Canada. We would like to thank the organizers of the following special sessions: • Digital Technology in Sports (DTiS) Session Chair: Thrasyvoulos Tsiatsos, Aristotle University of Thessaloniki, Thessaloniki, Greece • Experiences in rapid transition to remote learning: Challenges in delivery and assessment during contingency Session Chair: Omar H. Karam, British University in Egypt (BUE) and Mohamed Samir El-Seoud, The British University in Egypt (BUE) The following were the main themes of the technical sessions: • • • •

Interactive, Collaborative, and Blended Learning Technology-Supported Learning Education 4.0 Pedagogical and Psychological Issues

The following types of submission have been accepted for publication in the proceedings: • full paper and short paper • work in progress • special sessions All contributions were subject to a double-blind review. The review process was very competitive. A team of about 81 reviewers had to assess more than 140 submissions. Our special thanks go to all of them. Following a critical review, 61 submissions were accepted for presentation. The online conference had 80 online participants from 24 countries from all continents. Our special thanks go to Kostas Apostolou and Seshasai Srinivasan from McMaster University, Andreas Pester from the British University in Egypt, and Christian Guetl from Graz University, Austria, who co-chaired the conference. We thank Sebastian Schreiter for the technical editing of this proceedings. Michael E. Auer Steering Committee Chair Dan Centea ICBL2020 Chair

Organization

Committees Steering Committee Chair Michael E. Auer

CTI, Frankfurt/Main, Germany

General Conference Chair Andreas Pester

The British University in Egypt, El Sherouk City, Egypt

ICBL2020 Chairs Dan Centea Christian Guetl

McMaster University, Hamilton, Canada TU Graz, Austria

International Chairs Samir A. El-Seoud Xiao-Guang Yue Alexander Kist Doru Ursutiu Jorge Membrillo Hernández David Guralnick

The British University in Egypt (Africa) Wuhan University, China (Asia) University of Southern Queensland, Australia (Australia/Oceania) University Transylvania Brasov, Romania (Europe) Tecnológico de Monterrey, México (Latin America) Kaleidoscope Learning, New York, USA (North America)

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Organization

Technical Program Chairs Seshasai Srinivasan Kostas Apostolou Sebastian Schreiter

McMaster University, Hamilton, Canada McMaster University, Hamilton, Canada IAOE, France

Workshop, Tutorial and Special Sessions Chair Ishwar Singh

McMaster University, Hamilton, Canada

Publication Chair Sebastian Schreiter

IAOE, France

Local Organization Chair Kostas Apostolou

McMaster University, Hamilton, Canada

Local Organization Committee Members Dan Centea Ishwar Singh Kostas Apostolou Moein Mehrtash Nasim Muhammad

McMaster McMaster McMaster McMaster McMaster

University, University, University, University, University,

Hamilton, Hamilton, Hamilton, Hamilton, Hamilton,

Canada Canada Canada Canada Canada

Program Committee Members Aadil Merali Abul Azad Apostolos Gkamas Barbara Kerr Bekim Fetaji Christos Douligeris Dan Centea Daphne Economou Demetrios Sampson Despo Ktoridou Dieter Wuttke Doru Ursutiu George Ioannidis Pedro Isaias

McMaster University, Hamilton, Canada Northern Illinois University, USA University Ecclesiastical Academy of Vella of Ioannina, Greece Ottawa University, Canada University Mother Teresa, Macedonia University of Piraeus, Greece McMaster University, Hamilton, Canada University of Westminster, UK University of Pireaus, Greece University of Nicosia, Cyprus Technical University Ilmenau, Germany University Transylvania Brasov, Romania Patras University, Greece The University of Queensland, Australia

Organization

George Magoulas Golberi S. Ferreira Joanne Kehoe Kostas Apostolou Maiga Chang Manuel Castro Matthew Minnick Minjuan Wang

Moein Mehrtash Mo Elbestawi Mohamed Bakr Monica Divitini Mostafa Soliman Prashant Mhaskar Santi Caballé Seshasai Srinivasan Tom Doyle Zhen Gao

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Birkbeck College, UK CEFET/SC, Brazil McMaster University, Hamilton, Canada McMaster University, Hamilton, Canada Athabasca University, Canada Universidad Nacional de Educación a Distancia, Spain McMaster University, Hamilton, Canada Shanghai International Studies University (Oriental Scholar); San Diego State University, USA McMaster University, Hamilton, Canada McMaster University, Hamilton, Canada McMaster University, Hamilton, Canada Norwegian University of Science and Technology, Norway McMaster University, Hamilton, Canada McMaster University, Hamilton, Canada Open University of Catalonia, Spain McMaster University, Hamilton, Canada McMaster University, Hamilton, Canada McMaster University, Hamilton, Canada

Contents

Education 4.0 Devising a Prototype Model for Assessing Digital Competencies Based on the DigComp Proficiency Levels . . . . . . . . . . . . . . . . . . . . . . . Xhelal Jashari, Bekim Fetaji, Alexander Nussbaumer, and Christian Guetl

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Low Cost and User Friendly IoT Laboratory: Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mostafa M. Soliman and Ishwar Singh

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Curriculum Based Accessible Learning for Schools Using ICT Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rani P. Venkitakrishnan

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An Assessment of the Pedagogical Style of Online Software Courses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ishwar Singh and Jeff Fortuna

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The Role of Competency Development in the Implementation of Portfolio-Based Education in Higher Education . . . . . . . . . . . . . . . . . Vilmos Vass and Ferenc Kiss

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Education 4.0: Remote Learning and Experimenting in Laboratory for Automation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hasan Smajic, Abdulkadir Sanli, and Niels Wessel

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Developing Workforce Skills for Industry 4.0 . . . . . . . . . . . . . . . . . . . . Andrii Karpenko, Hanna Zasorina, and Natalia Karpenko Work-in-Progress: Gamification and Design Thinking–A Motivational Analysis of an International, Interdisciplinary, Team-Based University Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . David Kessing and Manuel Löwer

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Collaborative Learning Environments Multimodal Access to Scientific Experiments Through the RIALE Platform - Main Steps of Bioinformatics Analysis . . . . . . . . . . . . . . . . . Carole Salis, Davide Zedda, Federica Isidori, Roberto Cusano, Francesco Cabras, Marie Florence Wilson, Federico Cau, and Lucio Davide Spano New Approaches for Understanding Some Concepts from History Using Engineering Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Silviu Butnariu Work in Progress: “Embedding Graduate Skills in Online Courses” . . . Swapneel Thite, Jayashri Ravishankar, Eliathamby Ambikairajah, and Araceli Martinez Ortiz

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Genetic Algorithms to Generate Data for a Social Learning Recommendation Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Sonia Souabi, Asmaâ Retbi, Mohammed Khalidi Idrissi, and Samir Bennani The Learning Factory: Self-directed Project-Based Education . . . . . . . . 114 Joshua Lawrence, Benjamin Dimashkie, Dan Centea, and Ishwar Singh Enhancing Practical Learning in Undergraduate Chemical Engineering Courses via Integration of Commercial Process Modelling Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Ryan J. LaRue, Isabella Monaco, and David R. Latulippe Self-directed Learning Compared to Traditional Engineering Approach: Case Studies in Developing Machine Learning Capabilities to Solve Practical Problems . . . . . . . . . . . . . . . . . . . . . . . . 132 Yih-Chyuan Hsiao, Sohaib Al-emara, Anoop Singh Gadhrri, Ishwar Singh, and Zhen Gao Introduction of IDEEA (International Design and Engineering Education Association) Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Kwanju Kim, Manuel Löwer, and Pedro Orta Castañón Online Teaching and Learning in India During Lockdown and Its Impact on Teaching Practices . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Sherine Akkara and Mallikarjuna Sastry Mallampalli The Role of Educational Neuroscience in Distance Learning. Knowledge Transformation Opportunities . . . . . . . . . . . . . . . . . . . . . . . 159 Spyridon Doukakis and Evita C. Alexopoulos

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Interdisciplinary Megaprojects in Blended Problem-Based Learning Environments: Student Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Henrik Worm Routhe, Lykke Brogaard Bertel, Maiken Winther, Anette Kolmos, Patrick Münzberger, and Jesper Andersen Collaboration with Industry in the Development and Assessment of a PBL Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Dan Centea and Seshasai Srinivasan Padlet in IDEEA Global Course and Project . . . . . . . . . . . . . . . . . . . . . 189 Pedro Orta, Kwanju Kim, Manuel Löwer, Gabriela Mendez-Carrera, Pedro D. Urbina Coronado, and Horacio Ahuett-Garza Low Cost Simulation Lab for Teaching Control Theory Concepts . . . . . 200 Timber Yuen Work-in-Progress: Blended Learning in Engineering Education in Peru. A Systematic Review of University Theses . . . . . . . . . . . . . . . . 206 Osbaldo Turpo-Gebera, Juan Zarate-Yepez, Francisco García-Peñalvo, and Fernando Pari-Tito Innovation and Issues in Education Student Perceptions of Screencast Video Feedback for Summative Project Assessment Tasks in an Engineering Technology Management Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Allan MacKenzie Knowledge Building Processes Between Interaction and Collaboration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230 Giorgio Poletti, Anita Gramigna, and Marco Righetti Problem Based Learning in Finite Element Analysis . . . . . . . . . . . . . . . 240 Seshasai Srinivasan and Dan Centea Recursion Versus Iteration: A Comparative Approach for Algorithm Comprehension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Francesco Maiorana, Andrew Csizmadia, Gretchen Richards, and Charles Riedesel Integrated Thinking - A Cross-Disciplinary Project-Based Engineering Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260 Steven Bogoslowski, Fei Geng, Zhen Gao, Amin Reza Rajabzadeh, and Seshasai Srinivasan A Flipped Design of Learning Resources for a Course on Algorithms and Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268 Francesco Maiorana

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Adaptation to On-Line Teaching with the Access of Social Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 Marcelo Augusto Leal Alves Work-in-Progress: Using the PerFECt Framework to Design and Implement Blended Learning Activities to Introduce the Binary System in Primary School Students . . . . . . . . . . . . . . . . . . . 288 Nektarios Moumoutzis, Nikolaos Apostolos Rigas, Chara Xanthaki, Yiannis Maragkoudakis, Christina Christodoulakis, Desislava Paneva-Marinova, and Lilia Pavlova Technology Based Collaborative Learning Measuring Student Confidence in the Intercultural, Cooperative Teaching of Ancient Greek via Semiotic Feedback . . . . . . . . . . . . . . . . . 299 Despina D. Lazaropoulou and George S. Ypsilandis Transition from In-Class to Online Lectures During a Pandemic . . . . . 307 Nasim Muhammad and Seshasai Srinivasan Providing On-Demand Feedback for Improved Learning of Logical Reasoning in Computer Science and Software Engineering . . . . . . . . . . 315 Wolfram Kahl Open Educational Resources for Environmental Education . . . . . . . . . . 327 Dana Perniu, Ileana Manciulea, Cristina Salca Rotaru, and Camelia Draghici Cloud-Based Education: Why Corporate Educational Platforms Lead Total Distance Learning Shift? . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 Ekaterina Beresneva, Mariia Gordenko, Olga Maksimenkova, and Alexey Neznanov Multimodal Environment for Studying the Behavior of Autonomous Vehicles in Traffic Situations . . . . . . . . . . . . . . . . . . . . . 347 Csaba Antonya and Ioana Diana Buzdugan A Low Cost Simulation to Replace a Physical Demo for Teaching Vibration Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 Timber Yuen Poster: Efficient Analysis of Frequency Demodulation in Remote Laboratory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362 Narasimhamurthy Kyathsandra Chandrashekar, Amrutha Muddappa, Bindu Tavakadahalli Shivakumar, Vismitha Tumkur Abhinandana, and Suchitra Vankalkunti

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Practical Experiences in Blended Learning Examining the Effects of Privacy-Aware Blended Learning Scenarios in Executive Training for Policymakers and Government Officials . . . . 373 Maria Gaci, Juan Carlos Farah, Isabelle Vonèche Cardia, Geneviève Féraud, and Denis Gillet How National and Institutional Policies Facilitate Academic Resilience and E-Learning in the Unprecedented Time? . . . . . . . . . . . . 385 Yang Gao, Ke Fu, and Xiaoyi Tao Shared Remote Lab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 Marjan Alavi The Impact of a Gamified E-Learning Environment in Students Attitude: A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 Marcos M. Tenório, Francisco Reinaldo, Vitor Gonçalves, Eliana C. Ishikawa, Lourival A. Góis, and Guataçara dos Santos Jr Lessons Learned from Sudden Transition to On-line Learning . . . . . . . 411 Dana Perniu, Ileana Manciulea, Codruta Jaliu, Liviu Perniu, Anca Vasilescu, and Camelia Draghici Evaluation of Challenge Based Learning Experiences in Engineering Programs: The Case of the Tecnologico de Monterrey, Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419 Patricia Caratozzolo and Jorge Membrillo-Hernández A Timed Discussion Forum for Novice Users and Self-learners of Spoken Tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 Kannan M. Moudgalya, Nancy Varkey, Vishnu K. Raj, and K. Sanmugasundaram Experiences in Rapid Transition to Remote Learning Integrated Online Wind Tunnel Experiments and Assessment for Contingency Scenario: Case Study at the British University in Egypt (BUE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 Ahmed Aboelezz, Peter Makeen, and Hani Ghali Online Implementation of Structural Analysis Tool for Remote Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447 Ghada El-Mahdy and Amany Micheal Work in Progress: The Effectiveness of Using Blended Learning on Developing Egyptian EFL Learners’ Language Skills . . . . . . . . . . . . 456 Wesam Khairy Morsi

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Effectiveness of E-Assessment in Quantitative Modules, COVID-19 Consequences: A Case Study by the British University in Egypt . . . . . . 466 Wafaa Salah, Mohamed Ramadan, and Hossameldin Ahmed A Framework for Harnessing Analytics to Augment the Development of Academic Action Plans . . . . . . . . . . . . . . . . . . . . . . 478 Ashraf S. Hussein and Omar H. Karam The Effectiveness of Using Collaborative Learning Systems to Prevent Spread of Coronavirus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 488 Hosam F. El-Sofany and M. Samir Abou El-Seoud A Remotely Accessible in-Door C-Band Solar Simulator for PV Cells Characterization: Educational Technology Case Study in the British University in Egypt (BUE) . . . . . . . . . . . . . . . . . . . . . . . . 495 Sameh O. Abdellatif and Hani Ghali A Concept Extraction System with Rich Multimedia Learning Resources for Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503 Somaya Al-Maadeed, Batoul M. S. Khalifa, Moutaz Saleh, Jezia Zakraoui, Jihad M. Alja’am, and M. Samir Abou El-Seoud Visualizing Children Stories with Generated Image Sequences . . . . . . . 512 Jezia Zakraoui, Moutaz Saleh, Somaya Al-Maadeed, Jihad M. Alja’am, and M. Samir Abou El-Seoud Image Steganography Using Auto Encoder-Decoder Based Deep Learning Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 520 Nandhini Subramanian, Omar Elharrouss, Somaya Al-Maadeed, and M. Samir Abou El-Seoud Digital Technology in Sports Gamified Educational Mobile Application to Support Healthy Lifestyle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 533 Karypidou Kyriaki and Thrasyvoulos Tsiatsos Utilising Virtual Communities of Practice to Facilitate Clean Sport Education in Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541 Lambros Lazuras, Antonia Ypsilanti, Vasilios Barkoukis, Despoina Ourda, Nikolaos Politopoulos, and Thrasyvoulos Tsiatsos Evaluating a Serious Game for Anti-doping on Adolescents . . . . . . . . . 547 Agisilaos Chaldogeridis, Lampros Karavidas, Nikolaos Politopoulos, Georgia Karakoula, Lambros Lazuras, Vasilios Barkoukis, and Thrasyvoulos Tsiatsos

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Design and Expert Evaluation of a Serious Game for Halting Harassment and Abuse in Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555 Thrasyvoulos Tsiatsos, Stella Douka, Lampros Karavidas, Kyriaki Karypidou, Monica Shiakou, and Andreas Avgerinos Correction to: The Impact of a Gamified E-Learning Environment in Students Attitude: A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marcos M. Tenório, Francisco Reinaldo, Vitor Gonçalves, Eliana C. Ishikawa, Lourival A. Góis, and Guataçara dos Santos Jr

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Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 563

Education 4.0

Devising a Prototype Model for Assessing Digital Competencies Based on the DigComp Proficiency Levels Xhelal Jashari1(&), Bekim Fetaji2, Alexander Nussbaumer1, and Christian Guetl1 1 Graz University of Technology, Graz, Austria [email protected], {alexander.nussbaumer,c.guetl}@tugraz.at 2 Mother Teresa University, Skopje, North Macedonia [email protected]

Abstract. The assessment of the current situation of digital skills and competencies in a given group is a fundamental issue nowadays. Hence, the purpose of the research study is to address this issue. The research methodology is quantitative, including also a case study experiment and pre and post-questionnaires. To obtain and make use of digital resources, one should own the necessary skills and digital competencies to do so. To specify the key elements of digital competence and the ways to assess it, the European Commission developed a Digital Competence Framework for Citizens – DigComp. The European Computer Driving Licence (ECDL), modules back up all competencies and areas of DigComp, which facilitate the structure in the digital skills area. Based on a developed prototype model which has been evaluated by an expert group, an experiment to assess the digital skills and competencies of high school and undergraduate students was conducted in the context of the ECDL Base modules. The experts examined the procedure and the list of selected categories, skill sets, and task items included in the prototype model, and assessed if they comply with the word processing syllabus. After the experiment, we used the statistical analyses to find cross-tabulation of self-evaluation questions within the level of education from tasks devised. The experiment revealed digital literacy levels of students and pointed out the areas that require improvement. It also compared the self-evaluated levels and the actual task experiment results of the students. This comparison showed that self-evaluation is not a proper way to evaluate the digital skills and competences of individuals in general. The study proved that there is a high discrepancy between the selfevaluation and actual evaluation results of the assessment groups. Keywords: Digital skills
Digital competencies ECDL modules
Prototype model
Assessment


DigComp competencies


1 Introduction In this modern era of the globalized world, there has been digitalization of data, information, and knowledge to make it easily accessed by almost everyone. According to Global Digital Overview, in 2020, there are more than 4.5 billion internet users, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 3–14, 2021. https://doi.org/10.1007/978-3-030-67209-6_1

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including 3.8 billion active social media users, with an increase of 7% from the previous year [1]. Most of the governmental administrative services and other services from other arenas are digitized. Nowadays, the functioning of the new digitized society is dependent on the skills and digital competencies of the people as its main driving force to its full implementation and proper usage. Therefore, the assessment of the level of digital competencies will become a necessity in the new digital society and a new digitized era that is rapidly evolving. Having insufficient digital skills is likely to harm people’s employability and life quality. According to the Organisation for Economic Co-operation and Development (OECD), Information and communications technology (ICT) in the workplace is now required in all but two occupations: dishwashing and food cooking. Furthermore, Digital Economy and Society Index (DESI) 2017 EU data shows that 169 million Europeans (44%) and 86 million people in the EU labour force (37%) have insufficient digital skills. However, according to (DESI) 2019, there has been a progress, where the number of people who does not have at least basic digital skills required in most jobs decreased by 2%, respectively to 35% [2]. To obtain and adequately make use of digital resources, one must possess the necessary skills and digital competencies. In order to understand what the key elements of digital competence are and how to assess it, the European Commission developed a Digital Competence Framework for Citizens–DigComp. It describes the skills and competencies needed to use digital technologies in a confident, critical, collaborative, and creative way, thus accomplishing the goals related to work, learning and leisure in digital society [3]. Besides all, DigComp framework is considered to be a general, highlevel description of the set of competencies relevant for users of digital technology. On the other hand, European Computer Driving License (ECDL) Foundation [4] has been an active stakeholder in all stages of DigComp ECDL, offering specific solutions in this area. The ECDL modules support all competencies and areas of DigComp, which help to provide structure in the digital skills area and assist individuals and organizations in understanding the competencies that they need now and in the future. The purpose of this research study is to create a prototype model to assess the proficiency level of high school and university students from a different perspective, with a specific focus on the area of Digital Content Creation. Furthermore, the assessment is carried on through self-conducted methods prepared based on the first insights from experts obtained from the preliminary study. The structure of the paper is as follows: it begins with an introductory section, then Sect. 2 provides information about the relation between the Digital Competency Framework and ECDL Module. Section 3 describes the prototype model developed to assess digital competencies. Section 4 illustrates the research study conducted on a task-based instructional strategy and investigates the derived results from the compiled data. Finally, in Sect. 5, the conclusion is presented., the conclusion is presented.

2 Background and Related Work This section summarizes information regarding the history and different aspects of the Digital Competence Framework concerning ECDL modules.

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According to [5], an increasingly higher number of governmental and nongovernmental organizations and companies are creating different frameworks that serve to describe, categorize, and enhance digital skills, literacy, and competencies. In order to understand what the key elements of digital competence are and how to assess it, a Digital Competence Framework for Citizens–DigComp is developed [3]. As a framework, DigComp was first introduced in 2013 by the European Commission’s Joint Research Centre (JRC). In the meantime, in 2016, it went through the first phase of update where its focus was the conceptual reference model [6]. The second phase of the update was held in 2017 and included eight proficiency levels, and the examples to use them [7]. According to [8], the ECDL Foundation has provided inputs on the content and conducted an exercise of mapping out the ECDL programme to DigComp framework. The details of the mapping are presented in the table below. Table 1. Digital competencies and ECDL modules [8] Digital competence area 1. Information and data literacy

Competencies

1.1 Browsing, searching and filtering data, information and digital content 1.2 Evaluating data, information and digital content 1.3 Managing data, information and digital content 2. Communication and 2.1 Interacting through digital collaboration technologies 2.2 Sharing through digital technologies 2.3 Engaging in citizenship through digital technologies 2.4 Collaborating through digital technologies 2.5 Netiquette 2.6 Managing digital identity 3. Digital content 3.1 Developing digital content creation 3.2 Integrating and re-elaborating digital content 3.3 Copyright and licenses 3.4 Programming

ECDL modules Computer Essentials Information Literacy

Online Essentials Online Collaboration ICT in Education

Word Processing, Spreadsheets, Presentation, Using Databases, Advanced Word Processing, Advanced Spreadsheets, Web Editing, Image Editing, Project Planning, 2D CAD, Advanced Database, Advanced Presentation (continued)

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X. Jashari et al. Table 1. (continued)

Digital competence area 4. Safety

Competencies

ECDL modules

IT 4.1 Protecting devices Security 4.2 Protecting personal data and privacy 4.3 Protecting health and well-being 4.4 Protecting the environment Computing 5. Problem solving 5.1 Solving technical ICT problems Troubleshooting 5.2 Identifying needs and technological responses 5.3 Creatively using digital technologies 5.4 Identifying digital competence gaps “Note: Some modules may support more than one competence area - for example, Computing relates to Programming in Digital Content Creation, as well as Problem Solving; Computer Essentials and Online Essentials both include issues relating to Safety” [8].

As can be seen from the Table 1, the DigComp framework has five specific areas, whereby our research complies with the third one, which is about digital content creation and ECDL Module Word Processing Application (Table 3). 2.1

Digital Skills’ Proficiency Levels

This section incorporates the eight proficiency levels for each of the 21 competencies of DigComp Framework. Moreover, the table below illustrates the knowledge, skills, and attitudes that depict each level of each competence (Table 2). Table 2. Eight proficiency levels in DigComp 2.1 [7] Level

Complexity of tasks

Autonomy

L1 L2

Simple tasks Simple tasks

L3

Well-defined and routine tasks and straightforward problems Tasks, and well-defined and non-routine problems Different tasks and problems Most appropriate tasks

With guidance Autonomy and with guidance where needed On my own

L4 L5 L6

Independent and according to my needs Guiding others Able to adapt to others in a complex context

Cognitive domain Remembering Remembering Understanding

Understanding Applying Evaluating (continued)

Devising a Prototype Model for Assessing Digital Competencies

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Table 2. (continued) Level

Complexity of tasks

Autonomy

L7

Resolve complex problems with limited solutions

L8

Resolve complex problems with many interacting factors

Integrate to contribute to the professional practice and to guide others Propose new ideas and processes to the field

Cognitive domain Creating

Creating

These proficiency levels also help our instrument to assess the digital skills and competences of the targeted groups of high school and university students.

3 Devising a Prototype Model This section presents a developed prototype model for assessing digital competencies. As it is seen from the previous chapter, ECDL Foundation has been an active stakeholder in all stages of DigComp development, and it has mapped the ECDL modules with DigComp areas. Furthermore, for the development of this model, we have been focused on the third Digital competence area, which is Digital content creation, specifically competence 3.1 Developing digital content and ECDL module Word Processing. After having analyzed the latest Word Processing Syllabus [9] which describes, through learning outcomes, the knowledge and skills that a candidate for the Word Processing module should possess, we have managed to select the working categories and skill sets for the experiment. Whereby we have selected four categories out of 6, and 6 skillsets out of 11 ones. In the experiment, we have also picked up several task items from the syllabus related to the selected categories and skill sets, as can be seen in the table below. Table 3. List of selected categories, skill sets, and task items for the prototype model Category 1. Using the application

Skill set 1.1 Working with Document

2. Document creation

2.1 Enter Text

3. Formatting

3.1 Text

Task item 1.1.1 Open, close a word processing application. Open, close document(s) 1.1.3 Save a document to a location on a local, online drive. Save a document under another name to a location on a local, online drive 1.1.4 Save a document as another file type like: text file, pdf, software specific file extension 2.1.3 Enter text into a document 2.1.4 Insert symbols or special characters like: ©, ®, ™. 3.1.1 Apply text formatting: font size, font type (continued)

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Category

4. Objects

Skill set

3.2 Paragraphs 4.1 Table Creation 4.2 Table Formatting

Task item 3.1.2 3.1.7 3.2.4 4.1.1 4.1.2 4.2.3

Apply text formatting: bold, italic, underline Insert, edit, remove a hyperlink Align text: left, centre, right, justified Create, delete a table Insert, edit data in a table Apply shading/background colour to cell(s)

The created prototype model was tested by a focus group of three ECDL experts, who are currently working in high school and our target universities. One of the experts is a female working as an informatics professor in high school with up to 10 years of professional experience. Furthermore, the other two experts are working as professors in two different universities with 13, respectively, 15 years of experience in ECDL. The experts were part of one of the most significant ECDL projects in Kosovo, which aimed to train teachers in using ECDL modules. The experts were informed about the task and procedure, and asked to participate in the qualitative assessment of the prototype model. They analyzed the list of selected categories, skill sets, and task items included in the prototype model, and evaluate if they comply with the word processing syllabus. According to the responses, 2 out of 3 experts strongly agreed with the selected categories for the prototype model, while one of them thought the selected categories were appropriate. All of them agreed that these categories are sufficient for the experiment. Besides, 2 out of 3 experts strongly agreed with the selected skill sets and task items, and the 3rd one approved of the decision. The experts agree that the selected task items and skills set are sufficient to fulfill the purpose of the intended experiment. After analyzing and evaluating the prototype model, the experts were asked to offer their opinion on the approach used in the model. Specifically, the main concern was to know if the same approach is suitable to work out for both the students of high school and university. According to them, using the same approach for both of the groups was not something preferable, but in general, they agreed that this type of integrated approach would work well for both of the groups. In conclusion, the overall opinion of the experts about this prototype model for assessing digital skills is that it is a supporting, innovative, and a well-organized method to assess the digital skills of the intended groups.

4 Assessing Digital Competencies Based on the DigComp Proficiency Levels This research study is based on a task-based instructional strategy and aims to collect data from high school and university students about their proficiency levels and digital competencies.

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In addition, it can be considered as part of a scope of an integrated focus group and experiment with primary quantitative data mainly collected from exercises particularly designed for this research, which were distributed to the experiment’s participants. 4.1

Study Design

The focus of this research study is to create a prototype model to assess the proficiency levels of high school and university students with a specific focus on the area of Digital Content Creation. Input data from the user’s impressions and experiences realizing the task will be collected using pre and post questionnaires. Experts tested the prototype model that is created through a focus group before conducting the experiment with the students. Furthermore, the assessment is carried on through self-conducted methods prepared based on the first insights obtained from the preliminary study and primary qualitative and quantitative data. Research Questions: 1) What are the digital competencies and skills required to use a word processing application? 2) What are the target groups? (high school and university students) 3) How can we measure their proficiency levels on the digital competencies? 4) Can we integrate the model into the existing e-learning platform Google Classroom? The methodology used to design this study was based on a task-based assessment, accompanied by pre and post-task questionnaires with closed-end and open-ended questions addressing target groups. 4.2

Setting and Instruments

The instruments used in this research study are the pre and post-task questionnaires consisting of 11 questions in the first questionnaire and 10 in the second one. The questionnaires are divided into three sections (introductory questions, general questions related to the task, and questions regarding the self-evaluation of the digital skills of students based on proficiency levels). Between the pre and post questionnaires, the students were asked to perform a task concerning the word processing application. 4.3

Procedure

The study was designed and organized based on the Word Processing Syllabus and the feedback of ECDL experts. The participants attended the study online through Google Classroom, where they accessed the task, pre and post questionnaires, and received the instructions in zoom video and text formats beforehand. During the experiment, the behaviors of students were monitored and tracked through the MS Word macro recording, whereby the duration of the experiment in total, including the questionnaires, was 30 min. At the very end, they had to submit the questionnaires and upload the task as an assignment.

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Study Participants

The target groups of our study were high school and undergraduate students selected randomly by their professors. During the research, 60 students managed to complete the requirement and provide valid responses appropriately. Regarding the level of education of the participants, 30 of them were high school students and 30 undergraduates. Amongst the high school students, 70% of them were in their second year of study in order to do so., while amongst the undergraduate group, the majority of them were third-year students, respectively 63.3% of them, however in total, 46.7% of all participants were second-year students. The gender perspective between the number of males and females that attended the study was equal. However, when compared to the level of education, high school students were represented by 70% females as opposed to 30% males. On the other hand, the opposite representation occurred at the undergraduate level. The average age of high school students was 16.5, while 20.7 was the average age of undergraduate students. 4.5

Results and Discussion

This section includes the results of the study research based on the frequency and crosstab analysis of students’ skills in word processing applications. In regard to the general questions related to the task and questions about the self-evaluation in compliance with the responses in the pre and post-task questionnaires, the results are discussed below: In terms of the usage frequency of the word application in their studies, 38.3% responded that they use it for once a week, followed by 26.7% using it three times a week and 16.7% of them using it more than five times a week. Self-evaluation Questions The cross-tabulation of self-evaluation questions analyzes the data here within the level of education in pre and post-task questionnaires, compare to actual task assessment results. The skills of students are assessed in word processing application, which complies with the first category of the syllabus, Using the Application, where 56.7% of high school students evaluated themselves as very good, while the results from the task experiment showed that 36.7% of students belong to the satisfactory level (see Table 4).

Table 4. How would you self-evaluate your skills in word processing application? Education * High School

Pre questionnaire Task experiment Post questionnaire

How would you self-evaluate your skills in word processing application? Unsatisfactory Satisfactory Good Very Good Count 2 % within Edu. 6.7% Count 8 % within Edu. 26.7% Count 0 % within Edu. 0.0%

3 10.0% 11 36.7% 5 16.7%

6 20.0% 3 10.0% 8 26.7%

17 56.7% 5 16.7% 10 33.3%

Total Outstanding 2 6.7% 3 10.0% 7 23.3%

30 100.0% 30 100.0% 30 100.0%

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When the high school students were asked the same question after the task experiment, according to the responses, 33.3% of them evaluated themselves as very good. Here it is seen that self-evaluation is always higher than the actual results, even though the percentage of self-evaluation after the task dropped from 56.7% to 33.3%. In the pre questionnaire, 40.0% of undergraduate students self-evaluated themselves as good in word processing application, while the results of the task assessment showed that 43.3% of them performed very good. After the task, the self-evaluation of the students shows that 35.0% evaluated themselves as satisfactory. As it is shown in Table 5, in general, the self-evaluation results and actual task results of the undergraduate students are closer, compare to high school students. Table 5. How would you self-evaluate your skills in word processing application? Education * Undergraduate

Pre questionnaire Task experiment Post questionnaire

How would you self-evaluate your skills in word processing application? Unsatisfactory Satisfactory Good Very Good Count 1 % within Edu. 3.3% Count 3 % within Edu. 10.0% Count 10 % within Edu. 16.7%

4 13.3% 4 13.3% 21 35.0%

12 40.0% 5 16.7% 20 33.3%

11 36.7% 13 43.3% 9 15.0%

Total Outstanding 2 6.7% 5 16.7% 10 16.7%

30 100.0% 30 100.0% 30 100.0%

Both of the groups of students were also asked to assess their skills in Document Creation and Text Formatting as part of the second and third categories of Word Processing Syllabus, respectively Document Creation and Formatting. The questions were designed based on the proficiency levels of the DigComp Framework. As shown in Table 6, the results were as follows, high school students with 33.3% evaluated themselves to belong to Level 5. In contrast, according to actual task results, 40% of them belong to the second level. In the post-task questionnaire, they evaluated themselves in third and sixth levels with 20% in each of them. There is a high discrepancy between the self-evaluated and actual results. Table 6. How would you self-evaluate the level of your skills in Document Creation and Text Formatting in word processing application? Education * High School

*How would you self-evaluate the level of your skills in Document Creation and Text Formatting in word processing application? L1

Pre questionnaire

Count 3 % within Edu. 10.0% Task experiment Count 2 % within Edu. 6.7% Post questionnaire Count 0 % within Edu. 0.0%

Total

L2

L3

L4

L5

L6

L7

L8

1 3.3% 12 40.0% 4 13.3%

2 6.7% 8 26.7% 6 20.0%

5 16.7% 5 16.7% 3 10.0%

10 33.3% 0 0.0% 4 13.3%

5 16.7% 1 3.3% 6 20.0%

4 13.3% 2 6.7% 5 16.7%

0 30 0.0% 100.0% 30 0.0% 100.0% 2 30 6.7% 100.0%

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As it can be seen in Table 7, when the undergraduate students were asked the same questions, 23.3% of students considered themselves to belong to the third level, while the actual results illustrate that they belong to the third and fourth levels with 23.3% in each of them. After the experiment, undergraduate students self-evaluated themselves 26.7% to belong to the second level. Table 7. How would you self-evaluate the level of your skills in Document Creation and Text Formatting in word processing application? Education * Undergraduate

*How would you self-evaluate the level of your skills in Document Creation and Text Formatting in word processing application? L1

Pre questionnaire

Count 5 % within Edu. 16.7% Task Count 2 % within Edu. 6.7% Post questionnaire Count 2 % within Edu. 6.7%

L2

L3

L4

L5

L6

L7

L8

3 10.0% 6 20.0% 8 26.7%

7 23.3% 7 23.3% 6 20.0%

1 3.3% 7 23.3% 1 3.3%

7 23.3% 4 13.3% 5 16.7%

5 16.7% 1 3.3% 4 13.3%

0 0.0% 3 10.0% 3 10.0%

2 6.7% 0 0.0% 1 3.3%

Total

30 100.0% 30 100.0% 30 100.0%

When considering the level of their skills in Table Creation and Formatting, 30% of high school students self-evaluated themselves in the sixth level, whereby according to the results of the actual assessment, they belong to the third level with 30%. After the task, students evaluated themselves with 20% in the eighth level, which appears to be far away from the real results (see Table 8).

Table 8. How would you self-evaluate the level of your skills in Table Creation and Table Formatting in word processing application? Education * High School

* How would you self-evaluate the level of your skills in Table Creation and Table Formatting in word processing application? L1

Pre questionnaire

Count 3 % within Edu. 10.0% Task experiment Count 3 % within Edu. 10.0% Post questionnaire Count 1 % within Edu. 3.3%

Total

L2

L3

L4

L5

L6

L7

L8

4 13.3% 7 23.3% 3 10.0%

3 10.0% 9 30.0% 4 13.3%

3 10.0% 1 3.3% 2 6.7%

5 16.7% 5 16.7% 5 16.7%

9 30.0% 4 13.3% 5 16.7%

2 6.7% 1 3.3% 4 13.3%

1 3.3% 0 0.0% 6 20.0%

30 100.0% 30 100.0% 30 100.0%

On the other hand, in the same category, undergraduate students considered themselves to belong to the third and sixth levels with 20% in each of them, where the actual results depict that they belong with 23.3% in the sixth level. Post task questionnaire results showed that 23.3% of undergraduate students belong to the third level, as Table 9 indicates.

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Table 9. How would you self-evaluate the level of your skills in Table Creation and Table Formatting in word processing application? Education * Undergraduate

* How would you self-evaluate the level of your skills in Table Creation and Table Formatting in word processing application? L1

Pre questionnaire

Count 4 % within Edu. 13.3% Task Count 2 % within Edu. 6.7% Post questionnaire Count 4 % within Edu. 13.3%

Total

L2

L3

L4

L5

L6

L7

L8

5 16.7% 5 16.7% 5 16.7%

6 20.0% 6 20.0% 7 23.3%

3 10.0% 3 10.0% 4 13.3%

5 16.7% 3 10.0% 4 13.3%

6 20.0% 7 23.3% 3 10.0%

0 0.0% 4 13.3% 1 3.3%

1 3.3% 0 0.0% 2 6.7%

30 100.0% 30 100.0% 30 100.0%

The final part of the post questionnaire consisted of general questions related to the task. In the question regarding the willingness of students to receive additional training after completing the task, the percentage of high school students willing to receive the training is 40%, smaller compared to the percentage of undergraduate students, which is 60%, ready to receive the training. When the students were asked if they agreed with the testing method, the majority of them agreed significantly with the method used in the experiment. Students were also made to evaluate the complexity of the task. Where the majority of them evaluated it to be amongst the 4th and 5th levels of difficulty. Cross tabulation data shows that 63.3% of high school students and 50% of undergraduate students evaluated the utilization of Interactive e-learning platform Google Classroom as very good. Considering the overall satisfaction of the students, 53.3% of high school students and 46.7% of students considered it very good. At the very end of the post questionnaire, students had the opportunity to offer their opinions and feedback on the questionnaires and the task. The majority of them did not have any suggestions, while some of them evaluated the experiment as innovative and educational. There were also some students willing to further improve their skills by asking for more assignments and tasks, while for some of the students, the usage of macro was something new and a little challenging.

5 Conclusion In conclusion, the experiment proved that self-assessment methods are not effective and correct methods to evaluate the digital skills and competencies of individuals. In the results obtained from the experiment, there is a significant discrepancy between the self-evaluated results of the students and the actual results obtained from the task experiment. The study experiment was conducted by a devised prototype model for the assessment of digital competencies based on the eight DigComp proficiency levels. Before conducting the experiment, the experts examined the model and the list of selected ECDL module categories, skill sets and task items included in the prototype model. They evaluated their compliance with the word processing syllabus.

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The experiment measured the digital literacy levels of students and identified the areas that need improvement. Through the experiment, we also managed to compare the self-evaluated results of the students and the actual one obtained from the task experiment. The study evidenced that a high discrepancy between the self-evaluation and actual evaluation results of the assessment groups exists. Also, the level of education proved to be an important factor for students in their ability to self-evaluate their proficiency level, where undergraduate students performed better compared to high school students.

References 1. Kemp, S.: Digital 2020: Global Digital Overview. Datareportal.com (2020). https:// datareportal.com/reports/digital-2020-global-digital-overview. Accessed 30 Jan 2020 2. The Digital Economy and Society Index (DESI) (2019) 3. Ferrari, A.: DIGCOMP: A Framework for Developing and Understanding Digital Competence in Europe. Publications Office of the European Union, Luxembourg (2013). https://doi. org/10.2788/52966 4. ECDL Foundation, The Fallacy of the ‘Digital Native’. www.icdl.org 5. Jashari, X., Fetaji, B., Nussbaumer, A., Gütl, C.: (Accepted/In press). Assessing digital skills and competencies for different groups and devising a conceptual model to support teaching and training. In: Proceedings of ICBL 2019 Springer (2019) 6. Vuorikari, R., Punie, Y., Gomez, S., Van Den Brande, G., et al.: DIGCOMP 2.0: The Digital Competence Framework for Citizens. Update Phase 1: The Conceptual Reference Model. Publications Office of the European Union, Luxembourg (2016). https://doi.org/10.2791/ 11517 7. Carretero, S., Vuorikari, R., Punie, Y., et al.: DigComp 2.1: The Digital Competence Framework for Citizens with Eight Proficiency Levels and Examples of Use. Joint Research Centre. Publications Office of the European Union, Luxembourg (2017). https://publications. jrc.ec.europa.eu/repository/bitstream/JRC106281/web-digcomp2.1pdf_(online).pdf 8. ECDL Foundation, ECDL and DigComp–Describing, Developing and Certifying Digital Competence. https://icdleurope.org/policy-and-publications/icdl-and-digcomp. Accessed 10 May 2020 9. ECDL Foundation, WORD PROCESSING Syllabus 6.0 Syllabus Document. https://icdl. sharefile.com/share/view/sf48c8f169a14846b. Accessed 15 May 2020

Low Cost and User Friendly IoT Laboratory: Design and Implementation Mostafa M. Soliman(&) and Ishwar Singh McMaster University, Hamilton, ON L8S 0A3, Canada {solimm12,isingh}@mcmaster.ca

Abstract. The Internet of things (IoT) is the main technology enabling the fourth industrial revolution. Huge demand for engineers with strong IoT skills and competencies is expected in the near future. There is an urgent need to teach the foundation of IoT technologies in the undergraduate engineering curriculum using experiential and project-based learning methods with significant use of hardware, software, and cloud platforms. This paper proposes a low cost and easy to use IoT laboratory that introduces the challenging and multidisciplinary subject of Cloud Computing and IoT to engineering students with minimal prerequisites. Widely available software and cloud platforms are exploited to enhance teaching an introductory IoT course. Furthermore, a blended teaching approach that includes lectures, instructor-led labs, and project-based learning is described. The labs were used to teach third-year students of the Automation Engineering Technology program at McMaster University. Relevant student course evaluation results are provided to show student response to the learning experience. Keywords: Internet of Things (IoT)


Cloud
MQTT
LabVIEW
Arduino

1 Introduction The industry is just beginning to scratch the surface of what is imaginable through Industry 4.0. This new paradigm advocates the use of advanced technologies such as artificial intelligence (AI), IoT and industrial IoT (IIoT), big data and data analytics, and additive manufacturing to produce novel products and services [1]. It is predicted that the worldwide IoT market will reach $14.4 trillion by 2022 [2], and that there will be between 50 to 100 billion IoT devices by the end of 2020 [3]. The engineering education is witnessing revolutionary changes in response to the huge demand for engineers with high industry 4.0 competencies. Engineering graduates will need to learn IoT and IIoT as the foundation for implementing Industry 4.0 concepts in industrial operations [2]. Designing and teaching an introductory IoT course within the undergraduate engineering curriculum is a challenging task. First, IoT is a multidisciplinary engineering discipline that requires background knowledge of electronics, software, computer engineering, and information and network technologies. This background is usually not fully established, especially, for intermediate-level students. Furthermore, IoT is a very applied subject that requires hands-on learning using labs and/or projects. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 15–23, 2021. https://doi.org/10.1007/978-3-030-67209-6_2

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Preparing an IoT lab can be expensive and cost prohibitive. The recent pandemic (COVID-19) outbreak poses extra challenges for lab teaching. Different approaches for implementing and teaching IoT labs were proposed in the literature. The design of real-time IoT system course, laboratory experiments and term projects is described in [4], where Adafruit cloud platform and ESP8266 microcontrollers are used. Smart IoT laboratory system is proposed in [5] to remotely monitor and control small appliances. In [6], project based learning is suggested in a lab environment to teach IoT. In this approach, students are required to choose the hardware and software of their projects. The use of Arduino microcontrollers to teach IoT labs is described in [7]. The use of Arduino Uno with Ethernet shield to act as an IoT gateway is described in [8]. HTTP requests are used to transfer the data to the cloud server: data.sparkfun.com server, where this data is stored and displayed in a simple database. This paper describes the design and implementation of a low-cost IoT laboratory that gently introduces cloud computing and IoT to engineering students with minimal pre-requisites. Furthermore, a blended approach for teaching IoT that relies on using lectures, instructor-led labs, and project-based learning is described. The proposed IoT labs offer several advantages compared to the ones existing in the literature. They use inexpensive Commercial off-the-shelf (COTS) components that can be purchased by students. The software required to perform the labs is either free or provided by the university. The labs can be fully performed off-campus. Graphical programming languages are mostly used through the labs, thus allowing the students to focus on problem solving instead of writing hundreds of lines of code with different programming languages such as C, python, JavaScript, Node.JS, etc. This paper is organized as follows. An overview of the introductory IoT course is provided in Sect. 2. The proposed hardware and software architecture for the introductory IoT lab is discussed in Sect. 3. Details of the IoT labs and students’ projects are provided in Sect. 4. The student learning experience is discussed in Sect. 5; and Sect. 6 concludes the paper.

2 Introductory IoT Course Overview 2.1

Integration of IoT and Industry 4.0 in the Engineering Curriculum

The school of Engineering Practice and Technology (SEPT) at McMaster University has recently made huge effort to integrate IoT, IIoT and Industry 4.0 in the undergraduate and graduate curriculum. In the undergraduate Automation Engineering bachelor of technology offered by SEPT, a new smart systems specialization is introduced in the fourth year, where the offered courses focus on IoT. A new introductory IoT course (SMRTTECH 3CC3) was developed and offered for the first time at the 3A level in the fall of 2019. Another effort by SEPT is the formation of a CyberPhysical Systems Learning Centre that focuses on implementing Industry 4.0 concepts for teaching, training, and research at McMaster University [9, 10]. The Centre includes a series of specialized learning labs and the SEPT Learning Factory that allow the development various theoretical and technical skills needed for product production.

Low Cost and User Friendly IoT Laboratory

2.2

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Course Description

The IoT course is a three-credit course offered to intermediate-level (3A) undergraduate automation students. The required prerequisites are basic knowledge of programming and electronics. It includes three hours lecturing and three hours lab every week. One of the main course goals is to teach the main skills required to implement an IoT application that involves sensors, actuators, networks, and cloud platforms. The course topics are summarized in Table 1. Experiential and project-based learning (PBL) are implemented in the course. Students are required to complete ten Instructor-led labs and a project. Details of these labs and the project are provided in Sect. 4.1 and Sect. 4.2. Table 1. Introductory IoT course-content and time provided for each subject.

(1) (2) (3) (4) (5) (6)

(7)

Subject

Content

General view of IoT Introduction to digital systems Sensors technologies Actuators technologies Data acquisition

Introduction to IoT concepts, basic IoT architecture, Industrial applications of IoT Decimal, Binary, and Hexadecimal Number Systems. Binary number mathematics Sensor specifications, position, speed, acceleration, force sensors, interacting DC motors, stepper motors, solenoids, pumps, valves, actuator interfacing ADC, DAC, sampling and quantization, Nyquist frequency, signal conditioning Fundamentals of serial communication, UART, I2C, SPI protocols, MQTT protocol, TCP/IP and HTTP fundamentals Cloud Computing concepts, fundamentals of data analytics, IBM Watson IoT platform

IoT communication protocols Cloud computing

Time (%) 14% 9% 18% 18% 18% 14%

9%

3 Introductory IoT Lab Design Designing an IoT lab, choosing its architecture, hardware and software can be a daunting task for the instructor. A typical IoT architecture includes smart devices (things), IoT gateways, and a cloud platform. IoT devices are typically equipped with sensors, actuators, microcontroller or microprocessors, and network connectivity. The proposed lab setup is shown in Fig. 1. Due to its popularity and low cost, the Arduino Uno is used as an IoT device. The Arduino Uno is connected to the student’s computer using a USB cable. The computer is connected to the internet using Ethernet or WiFi and it will act as the IoT gateway. The HiveMQ MQTT public broker is used to exchange data between the gateway and the Cloud.

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MQTT over Ethernet or WiFi

Serial

HiveMQ MQTT broker

Actuators Arduino Uno - Lynx firmware

Computer - LabVIEW

IBM Cloud - node-RED - Cloudant DB - AnalyƟcs

Off-campus lab setup

Fig. 1. Proposed introductory IoT lab setup.

The IBM cloud is chosen as the cloud platform. A recent report selected IBM Cloud as the most significant industrial IoT software platform with the strongest strategy [11]. Furthermore, IBM Cloud natively supports Node-RED which is a graphical tool that allows to configure and program cloud applications. The lab setup is done off-campus. The students are required to have their own kits. An Arduino starter kit costs around 50$. Other electronic components that are required for the labs costs another 50$. The required software is either free or provided by the school. Thus, the total cost of the lab is less than 100$ for every student. LabVIEW is used as the main programming language for the IoT devices. It is a graphical programming language, with lots of built-in functions, known as VIs, and libraries. In contrast with the Arduino IDE, LabVIEW allows code debugging and visualization. Another major advantage of using LabVIEW is the fast creation of powerful graphical user interfaces (GUI). A sample LabVIEW GUI is shown in Fig. 2 (a) and (b). The programming can be done by dragging and dropping VIs in the block diagram as shown in Fig. 2 (c). Finally, LabVIEW programming is widely used in the industry. To interface LabVIEW to Arduino, the freely available library, LINX, is used. With this library, the Arduino board acts as a remote I/O or a data acquisition module with all its peripherals accessible using LaVIEW VIs.

(a)

(b) Fig. 2. LabVIEW programming.

(c)

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Node-RED is used to program and configure the cloud application. It is a graphic‐ based tool that facilitates the implementation of different IoT tasks. Figure 3 shows a flow that requests weather data from the OpenWeatherMap website, stores it into a cloud database and displays the current temperature on a web app using a dashboard.

Fig. 3. Node-RED programming.

4 IoT Lab and Project Implementation 4.1

Instructor-Led Labs

The introductory IoT course requires the successful completion of 10 experiments and a term project. Table 2 shows a sample of 4 labs and their objectives. The weight of all the labs is 15% of the total course grade. Table 2. IoT labs. (1)

Experiment title Temperature sensing and Introduction to LabVIEW

(7)

Introduction to Stepper Motors

(8)

Connecting to the Cloud using MQTT

(9)

Cloud-based gardening

Objectives • Interface a thermocouple to an Arduino • Understand the role of signal conditioning • Implement basic LabVIEW block diagram and GUI elements • Wire and control the speed, direction, and position of a stepper using a LabVIEW GUI • Use LabVIEW Mathscript and case structures • Use IBM cloud to display Ultrasonic sensor data on and control an LED from a Dashboard • Use MQTT protocol to transfer data between a LabVIEW Client and public broker • Use Node-RED to transfer data between a web-based Dashboard and a public broker • Create a cloud-based gardening system using a soil moisture sensor and a solenoid • Send email alerts when soil moisture is less then certain threshold • Storing sensor data into a database and interact with webservices such as openweathermap

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For the sake of illustration, details of lab 8 is discussed. The main objectives of this lab are to build a web-app that displays the measurements of an ultrasonic distance sensor, and allows the control of an LED. In the first part of the lab, students will exchange data between their computer (LabVIEW) and the cloud (Node-RED). This will be done using HiveMQ MQTT broker [12], a freely available LabVIEW MQTT library, and a Node-RED flow. In the second part of the lab, students are required to construct a circuit with an ultrasonic distance sensor and an LED as shown in Fig. 4, modify the program of part 1 to display the sensor data on a chart and control the LED as shown in Fig. 5. Addition of these features can be easily achieved due to the multithreading and parallel programming capabilities of LabVIEW.

Fig. 4. Ultrasonic and LED circuit wiring.

Once the students can locally control and monitor the system using LabVIEW, the final task for this lab is to perform cloud-based control and monitoring using a dashboard. The final outcome is the dashboard shown in Fig. 6. The students are also required to test the web-app using their cell phones. 4.2

Lab Project

Project based learning (PBL) is used in the course to encourage students’ creativity, increase students’ motivation, and strengthen team work skills [13]. Students are required to work in teams to design and implement a prototype for an IoT system of their choice. The project weight is 15% of the total course grade. The project starts in Week 8 and it should be completed within four weeks. To limit the project scope a maximum number of sensors and actuators is allowed. The project proposal must also be approved by the lab instructor. The project must contain all the concepts that were covered in the course including sensors, actuators, Local LabVIEW GUI, MQTT, webapp, and cloud functionalities. Examples of projects from the fall of 2019 are home security system, skittle color sorter, path following car.

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Fig. 5. LabVIEW GUI for lab 8.

Fig. 6. Lab 8 web-app with a chart and controls.

5 Students Learning Experience In the fall of 2019, only eight labs were used in the first eight weeks of the semester, followed by the lab project which spanned the remaining 4 weeks. The labs were performed on-campus in a lab facility containing all the electronic components as well as standard lab instruments such as multimeters and power supplies. The standard course evaluation includes the following two questions on student satisfaction: (1) how do you rate the value of this course compared with others you have taken at McMaster University and (2) independent critical judgment was encouraged. Figure 7 shows the students’ response for the two questions. Both results indicate the student appreciation of the course. In the course evaluation, many of the students positively commented on the handson approach utilized for learning the course concepts and the lab component. Some suggestions for improvement that were received are: to introduce IoT and cloud concepts earlier in the labs, and to improve the synchronization between the lectures and the labs. Both comments will be addressed in the coming offerings of the course. One major change that will be implemented in the coming course offerings is to perform the labs off-campus using students’ owned kits. This will allow to perform all the labs of Sect. 4.1 as well as executing the lab project in parallel with the last two labs.

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Fig. 7. Students feedback. (score is from 1 to 5, 1: very poor and 5: excellent).

6 Conclusion This paper details the design and implementation of a smart IoT laboratory that allows the student to monitor the environment via sensors, influence the outside world using actuators, and store and visualize data using cloud technologies. Compared to existing approaches in the literature, the proposed laboratories use low-cost and widely available hardware, LabVIEW graphical programming, and it enable students to easily and quickly create powerful IoT applications. This approach allows the students to be gently introduced to the challenging multidisciplinary field of Internet of Things and Cloud Computing. Furthermore, IoT teaching using a blended instructor-led labs and project-based learning is described.

References 1. Veneri, G., Capasso, A.: Hands-On Industrial Internet of Things: Create a Powerful Industrial IoT Infrastructure Using Industry 4.0. Packt Publishing, United Kingdom (2018) 2. Puri, I.: Tomorrow’s engineers need to learn IoT (2017). https://www.design-engineering. com/features/tomorrows-engineers-iot/ 3. Jeong, G.M., Truong, P.H., Lee, T.Y., Choi, J.W., Lee, M.: Course design for Internet of Things using lab of things of microsoft research. In: Proceedings-Frontiers in Education Conference, FIE (2016) 4. Kucuk, K., Bayilmi, C., Msongaleli, D.L.: Designing real-time IoT system course: prototyping with cloud platforms, laboratory experiments and term project. Int. J. Electr. Eng. Educ. (2019) 5. Poongothai, M., Subramanian, P.M., Rajeswari, A.: Design and implementation of IoT based smart laboratory. In: 2018 5th International Conference on Industrial Engineering and Applications (ICIEA), pp. 169–173 (2018) 6. Rout, K.K., Mishra, S., Routray, A.: Development of an Internet of Things (IoT) based introductory laboratory for under graduate engineering students. In: Proceedings-2017 International Conference on Information Technology, ICIT 2017, pp. 113–118, Bhubaneswar, Odisha, India (2017)

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7. Guerra, J.G., Perez, A.F.: Implementation of a robotics and IoT laboratory for undergraduate research in computer science courses. In: Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, p. 369, Arequipa, Peru (2016) 8. Bhadoriya, R., Chattopadhyay, M.K., Dandekar, P.W.: Low cost IoT for laboratory environment. In: 2016 Symposium on Colossal Data Analysis and Networking, CDAN 2016, Indore, Madhya Pradesh, India (2016) 9. Centea, D., Singh, I., Elbestawi, M.: Framework for the Development of a Cyber-Physical Systems Learning Centre BT-Online Engineering & Internet of Things. Presented at the (2018) 10. Elbestawi, M., Centea, D., Singh, I., Wanyama, T.: SEPT learning factory for industry 4.0 education and applied research. Procedia Manuf. 23, 249–254 (2018). https://doi.org/10. 1016/j.promfg.2018.04.025 11. Wave, F.: The forrester wave industrial IoT software platforms, Q3 2018 (2018) 12. HiveMQ Homepage. https://www.hivemq.com/public-mqtt-broker/ 13. Nelson, N.: Achieving graduate attributes through project-based learning. Proc. Can. Eng. Educ. Assoc. 1–7 (2015). https://doi.org/10.24908/pceea.v0i0.5923

Curriculum Based Accessible Learning for Schools Using ICT Methods Rani P. Venkitakrishnan(&) TCS Lab, Spoken Tutorial Project, Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India [email protected]

Abstract. The ability to read with ease and to understand the meaning of sentences is essential for students. India has 22 official languages which are spoken in the various states. Children of migrant laborers face the task of adapting to a different language other than their mother tongue, which is an uphill task. The absence of structured language learning materials and affordable inter-language dictionaries results in a knowledge gap and adversely affects the academic performance. Online education adopted by schools, due to recent pandemic or other natural disasters, add to difficulties. To mitigate these effects, construction of curriculum based language learning materials is proposed. Currently, the learning resources aligned to the curriculum, to mitigate language barrier, are not available for student use. Due to the widespread use of smartphones, a majority of students are familiar with the use of web-browser, online navigation, playing videos, and listening to audio clips. Since the textbooks are available online, learning resources that require knowledge of basic phone use can be designed and created. Construction of highlighted reading videos of textbook chapters, glossary and language dictionary for chapters for vocabulary building, audios, concept maps, interactive simulation, and learning games is proposed. Short videos were created on creating glossary, language-dictionary and online thesaurus, which can be practiced side-by-side by the learner. This can be achieved with the existing technology of computers or smartphones and 4G data. Keywords: Highlighted text reading tutorials


Language learning
Spoken video

1 Introduction 1.1

Language Barriers Affecting Reading Skills

Skill to read and write is essential for students to progress to higher education in any field. Language, phonetics, and word meanings are required for this. According to Lyon et al. [1], reading is not a natural process. Gough et al. [2] have further added that, to read fluently, readers need extensive practice. In India, about a quarter of a billion students are of school-going age. Many schools in rural communities lack adequate availability of the internet, computers, and trained teaching staff. Teachers are pegged as the source to develop students reading habits [3, 4] and responsibility of curriculum performance is also varied [5]. Children of migrant labourers also face a lack of knowledge of the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 24–31, 2021. https://doi.org/10.1007/978-3-030-67209-6_3

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medium of instruction in the schools due to numerous languages (22), which are geographically demarcated. Students have to assimilate learning in new and different languages from their mother tongue. Most state board schools follow a three language system with English, Hindi and the local languages to follow. Since, language is the foundation of understanding and concept forming, the student’s ability to read and understand in the language is important. Without a good understanding of the language, the lessons do not reach the desired potential. When applied to the world scene, this problem is more compounded with a greater number of languages to consider. Students having to overcome the language and communication barrier to advance their learning. There are various online learning resources, learning methods, studies, and analysis to improve upon them [6–11]. Online education is also adopted by an in-creasing number of schools in recent months due to the Covid-19 pandemic, wild-fires, earthquake, war, or refugee crisis, to name a few. Currently, ICT methods are used in a limited capacity. Instances of multiple resources for a study chapter Video lessons, the Zoom app, and the Google classroom being the most popular. This does not address the language gap to mitigate learning or ability to understand. Many students also lack ICT skills to use the resources. The blended modes of online training are not accessible for many students. Mostly, learning resources are also categorized by the concept under study. For a novice struggling with many aspects of learning, this can be an overwhelming task [12]. The vocabulary, language, and concept, have to be learned together by the students in a short period and assimilate. This two-pronged dart, cause severe disruptions in learning. In this work, construction of (i) language-oriented curriculum based learning resources for the students and (ii) software skills based on open-source software to construct such resources are discussed. 1.2

Skill Sets for Online Learning and Resource Creation

Students familiar with the usage of ICT technologies for learning can fare better [13–15]. If onboarding and a learning curve is needed to use the resource, language and concept learning difficulty may not be mitigated. Thus one needs to identify, the ICT skills students are familiar with, for using the re-source. The silver lining to this problem is the widespread usage of phones and smartphones coupled with the breadth of 4G network in India and its availability at very cheap prices (for less than $4 per month). Most students know to surf the web, navigate, and locate files. For example, download pictures, songs, play video and audio and know to play a variety of games. Teachers need an additional set of skills to create the resources. Teachers who wish to create appropriate resources may lack the ICT skills required to do such a creation. This article demonstrates, techniques strung together to create the resources and the skills used to create them. A smartphone and data or a computer with open source software can be used to construct the learning materials for student use. Inability to read by themselves or the lack of availability of textbooks is the major bottleneck. When learning materials are divided into sections, students tends to show familiarity with the lesson from the school classes or notes. A highlighted video of the textbook can be created to deliver visual learning. The videos can be played on the mobile platform, which the students know to use. This is particularly useful, in developing a reading habit, of the text-book, albeit via video.

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Short step-by-step videos were created, to build skills with resource construction. The videos demonstrate the creation of (i) glossary of words from text (ii) Language dictionary (iii) using online thesaurus website and (iv) to make an annotated illustration for early learners [16, 17]. The side-by-side learning method has been efficiently used to train about 3 million students by the Spoken tutorial project, which is funded by Ministry of Human Resource Development (MHRD), Government of India. More information on this project can be found at this website [18]. Glossary or word list can be created using Worditout or Vocagrabber websites. A language dictionary can be built from the glossary, using popular search engines such as Google. The videos can be practiced as a side-by-side guide for learning re-quired skill set. The short videos can be used by anyone, who is interested to create the resource or who want to learn the process. They can use a file template to create the learning materials.

2 Methodology Demonstration video for (i) glossary (wordlist), (ii) language dictionary creation, and (iii) highlighted textbook video were recorded using screencast software Kazam on Ubuntu Linux 16.04 OS. Only open-source software was employed in this study. Audio was recorded and edited with Audacity and Libreoffice was used for spreadsheet construction. The videos were edited using Kdenlive video editor and compressed using the ffmpeg2theora codec. Table 1 lists the problems we want to address, a solution within the premises of the curriculum, and the expected result. Two highlighted videos were created from the Class IX English language textbook chapters. They are Sound of Music from NCERT board (National Council for Educational Research and Training) and the chapter Bang the Drum from the Kerala State board. Short videos, outlining step by step process to create a glossary of words and language dictionary is created. They can be practiced with a smartphone. Ease of share and ability to form group studies are possible with social media. The highlighted textbook video in English is for demonstration purposes. A similar resource can be made for the various languages for visual reading.

3 Discussion The learning cone principle, described by which Dale [19] was employed in this study. Word highlighted video provides visual guided reading, familiarity with the word, phonics, and alphabets. Audio lessons form a learning resource when a student lacks fluency in reading. Interactive simulation and game-based learning identified are listed in Table 2. Visual, hands-on practice and listening form the base of the learning pyramid. Since most of the audience of this article would lack knowledge of Indian languages, English is used for example construction of highlighted reading learning resources for demonstration purposes. A paragraph from the chapter, Sound of music, from class IX NCERT English textbook is used for highlighted reading demonstration, wordlist, and dictionary creation. English-Malayalam dictionary was constructed, since Malayalam is one of the Indian official languages. The same can be extended to the

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Table 1. Issues in learning, possible solutions, and the likely outcome. Problem Language barrier within India for migrant children

Solution Construction of language-language dictionaries for curriculum Vocabulary and language building using pictures Aid ICT skill creation Create short videos which can be to build the language practiced side by side, to aid in resource creation resource Identify and create a glossary using Creating the online sites curriculum based Create annotated illustration or/and language resources storybook for language building Lack of reading skills Create a video of highlighted reading of curriculum chapter Break the sentences into words and phrases Audio learning Audio file of chapters for listening resource for selfstudy learning Lack of hands-on Identify Interactive simulations for examples for study use Subject learning aids Create downloadable games, which can be played on phones and distribute to students Identify web sites that allow them to create downloadable games for learning

Effect 14 Aids in building vocabulary. point, bold

Builds skill set to create the resource Helps to understand word meaning in student mother tongue language Helps to associate word, phonetics and pronunciation Student can hear the lesson in the absence of smart-phone Builds student familiarity Create learning games and distribute them to the students

Indian languages with ease using ICT, since the fonts are available for these languages. Illustrative highlighted video for reading is given in Video1.ogv. Learners can enhance reading skills, by practicing along with the video, enhancing their self-learning efficiency. Figure 1 shows an example of the glossary or wordlist obtained from online wordlist creation tools. Example wordlist (glossary) and English-language dictionary created using methods demonstrated in Video2.ogv and Video3.ogv files are given in Supportfile1.pdf and Fig. 1. A pilot assessment was conducted using the Kerala State board English textbook. The poem, Bang the Drum from their Unit I section was used to create Class IX English highlighted reading (Video5.mp4), dictionary(supportfile2.pdf) and glossary image. At the time of writing this article, classes are conducted in online mode only due to the Covid-19 lockdown. Class IX students of PTMSS school received the materials,

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Fig. 1. A) and (B) are two wordlist or glossary for students obtained for illustration from worditout website for the chapter on “Sound of Music” in English NCERT class IX textbook. figure caption is always placed below the illustration.

in the Whatsapp app on their phones. Some students were unable to open the compressed ogv format video file on their phones. The duration of the video, is approximately 7 min. MPEG-4 (mp4) was the preferred format for the video, along with pdf document for the language dictionary and context meaning. More than 90% of the students found the highlighted reading useful, while about 7% of the students watched the video more than once. Reading skill is essential for education and development [20–22]. Table 2 lists the website and the resources available for interactive simulation, game construction, skill video training, concept map construction, offline dictionary, and NCERT based educational materials. The video file resources, can be practiced side-by-side to develop the skills to create few learning resources. Concept maps [23] and the use of interactive simulation [24] is also helpful for students. Learning games keeps up the interest and engages the students. Wisc-online.com allows creation of several types of games which can be freely downloaded. By providing curriculum-based material as an open resource, students can access to the class lessons on which their examinations will be based on. When the student miss school days or don’t understand a lesson, they can listen and read the chapter, with a text highlighted video. Such highlighted videos for students in the languages will help in the learning process. Online sites, such as TTSreader can also create highlighted reading. A drawback is that the whole sentence is highlighted and read together, instead of breaking it up to shorter phrases. The language dictionaries could help to improve comprehension in the language. The initial effort would be to construct the materials for each grade. Since the school curriculum and textbooks are unified for educational boards, the construction of the resources is well defined. Students come in varied abilities. Some hear better, others watch and observe better, yet another set, may grasp the concepts with interactive simulations or games. Thus, the student is presented with a choice of methods, which will help to mitigate the various issues. The learning resources can be populated on a website for student access. A teacher, an academic coordinator, parents can also be given the resource links. Students can be easily guided, to access an audio or video file using the phone, at any time.

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Table 2. List of tools to create language resources, along with websites that provide interactive simulations, curriculum content MCQs, and allow construction of games free-of cost to students. Website https://worditout.com/ https://www.visualthesaurus.com/ vocabgrabber/ https://www.sequencepublishing.com/1/ Video2 and Video3 (Files, Video2.ogv and Video3.ogv) Video4 (File, Video4.ogv) Video1 and Video5 (Files Video1.ogv and Video5.mp4) https://www.wisc-online.com/ https://phet.colorado.edu/_m/ https://www.ekshiksha.org.in/

https://www.freeplane.org/wiki/index.php/ Home https://spoken-tutorial.org/tutorial-search/? search_foss=Freeplane&search_language=

Available resources Create glossary and thesaurus using online tools

Offline dictionary and thesaurus, with synonyms, antonyms Skill video with an example output file, for Creation of language dictionary and an online thesaurus Skill video to annotate pictures, to create the language resource for vocabulary building Example highlighted text of textbook video for reading aid Interactive simulations and Learning games construction for download Interactive simulations Curriculum content MCQ for NCERT, Interactive simulations and Question bank for student aid Download site for Freeplane software, for mind map/concept map construction Link for the skill video to learn Freeplane software, to create a concept map

Many LMS/CMS (Learning/Course Management System) encourage students to participate in online group studies. This encourages their resolve to reach out, seek answers to questions, clarify concepts and increase self-learning ability. Mitigation of the language barrier enables better academic performance, improving society benefits, lessen crimes and help people adjust better with the surroundings. This also allows us to provide the same quality of learning resources to all students, since the State board education and/or examinations are unified. Even when there is a non-availability of teachers, students will have direct access to curriculum-based subject lessons. By making the learning resource directly to the students, a lack of computer and internet issues can be solved in rural areas. By increasing the ability to understand and learn local languages also, student retention, completion of high school, reduction in dropout numbers, better academic performance, and integration of migrants with the local surroundings can be achieved. At present, displacement due to war, or violence is also a reason for hurdles in education in several parts of the world. Several years are spent in refugee camps or shelters add to the instability and continued propagation of violence. A YouTube channel or app-based development is also possible in this method. In the Indian state of Kerala, e-centres called Akshay Kendra in every panchayat, which helps students with many tasks for a nominal fee. This popular “go-to” place for students may also be

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roped in for storing the resources. If the students have difficulty in connecting to the internet, they could approach the e-centre to get a copy of the learning resource. If the students do not shy away from asking questions on the forums, an online user forum or establishing local study groups could clear doubts from students. Teachers from each school can be identified with the task of answering online student questions. Thus, by using the phone, 4G network, and curriculum based learning resource availability, the goal to provide, improve and mitigate few of the learning difficulties can be achieved. Acknowledgement. This work was supported by the grant to Prof. K. Mougdalya, IIT-Bombay, from MHRD, Government of India. Demonstration Video File Links 1. Video1.ogv: This is an illustrative text highlighted video guide to aid students in reading the textbook material.Link: https://drive.google.com/file/d/1bUKJovp8Hm-eOo7K5Y_Rw2qaaCwvFkX/view?usp=sharing 2. Video2.ogv: Short video to practice side-by-side to make a language dictionary. Link: https://drive.google.com/file/d/1WOUo_Bex04jzfU6gizDVw1hGd0cAy8Z4/view?usp=sharing 3. Video3.ogv: Short video to practice side-by-side. This video aids to create glossary (wordlist) and thesaurus from text, using the websites, https://worditout.com/ and https://www. visualthesaurus.com/vocabgrabber/. Link: https://drive.google.com/file/d/1-qtxfYFQXL15UD3l41O7WFW1vj5-ZUlE/view?usp=sharing 4. Video4.ogv: Illustrative example for visual language study by using a picture that can be shared with students. English, Hindi, and Tamil languages are used for illustration. Link: https:// drive.google.com/file/d/1TPabpc70kDfF6Lw4dz3ONofloUDThTyU/view?usp=sharing 5. Video5.mp4: Highlighted video of Bang the Drum poem from the Class IX Keala State board English textbook. Link: https://drive.google.com/file/d/1LIr0_7wE_cTmlRzCgCjtCvOEBS9kP9W/view?usp=sharing

References 1. Lyon, G.R.: Why Reading Is Not a Natural Process. http://www.ldonline.org/article/6396/ 2. Gough, P.B.: How children learn to read and why they fail. Ann. Dyslexia 46, 3–20 (1996) 3. Jose, G.R., Raja, W.D.: Teachers’ role in fostering reading skill: effective and successful reading i-manager’s. J. English Lang. Teach. 1(4), 1–10 (2011) 4. Rupley, W.H., Blair, T.R., Nichols, W.D.: Effective reading instruction for struggling readers: the role of direct/explicit teaching. J. Read. Writ. Q. 25(2–3), 125–138 (2009) 5. Sanzo, K., Clayton, J., Sherman, W.: Students with special needs, reading education, and principals bridging the divide through instructional leadership. Int. J. Educ. Leadersh. Prep. 6 (1), 1–20 (2011) 6. Anwer, F.: Activity-based teaching, student motivation and academic achievement. J. Educ. Educ. Dev. 6(1), 154–170 (2019) 7. Eagle, S.: Learning in the early years: Social interactions around picturebooks, puzzles and digital technologies. Comput. Educ. 59(1), 38–49 (2012) 8. Gibson, D., Baek, Y.K.: Digital simulations for improving education: learning through artificial teaching environments. IGI Glob. Chap. 2, 25–51 (2009) 9. Sandanayake, T.C.: Promoting open educational resources-based blended learning. Sandanayake Int. J. Educ. Technol. High. Educ. 16, 3 (2019)

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10. Radianti, J., Majchrzak, T.A., Fromm, J., Wohlgenannt, I.: A systematic review of immersive virtual reality applications for higher education: design elements, lessons learned, and research agenda. Comput. Educ. 147, 103778 (2020) 11. Kumar, K.L.: Educational Technology. New Age International Publishers, New Delhi (1997) 12. Yousef, A.M.F., Chatti, M.A., Schroeder, U.: The state of video-based learning: a review and future perspectives. Int. J. Adv. Life Sci. 6(3–4), 122–135 (2014) 13. Dunlosky, J., Rawson, K.A., Marsh, E.J., Nathan, M.J., Willingham, D.T.: Improving students’ learning with effective learning techniques: promising directions from cognitive and educational psychology. Psychol. Sci. Public Interest 14(1), 4–58 (2013) 14. Serena, M., Nino-Zarazua, M.: What works to improve the quality of student learning in developing countries? Int. J. Educ. Dev. 48, 53–65 (2016) 15. Voogt, J., Fisser, P., Roblin, N.P., Tondeur, J., Braak, J.V.: Technological pedagogical content knowledge – a review of the literature. J. Comput. Assist. Learn. 29, 109–121 (2013) 16. Wood, K.D., Josefina, T.: Using pictures to teach content to second language learners. Res. Pract. Middle Sch. J. 33, 11495331 (2003) 17. Drobot, I.A.: Foreign language learning: the use of images and the visual sense. Int. J. Manage. Appl. Sci. 1(9), 2394–7926 (2015) 18. The Spoken-tutorial home page. https://www.spoken-tutorial.org, Average Daily Unique Visits 14.1 K 19. Dale, E.: Audiovisual Methods in Teaching, Dryden Press: Holt, Rinehart & Winston, (3rd Edition), NY, (1969) 20. Delgadova, D.: Reading literacy as one of the most significant academic competencies for the university students. Proc. Soc. Behav. Sci. 178, 48–53 (2015) 21. Genlott, A.A., Grönlun, A.: Improving literacy skills through learning reading by writing: the iWTR method presented and tested. Comput. Educ. 67, 98–104 (2013) 22. Kucukoglu, H.: Improving reading skills through effective reading strategies. Proc. Soc. Behav. Sci. 70, 709–714 (2013) 23. Phantharakphong, P., Pothitha, S.: Development of English reading comprehension by using concept maps. Proc. Soc. Behav. Sci. 116, 497–501 (2014) 24. Sadykov, T., Čtrnáctová, H.: Application interactive methods and technologies of teaching chemistry. Chem. Teach. Int. 20180031, 1–7 (2019)

An Assessment of the Pedagogical Style of Online Software Courses Ishwar Singh and Jeff Fortuna(&) McMaster University, Hamilton, ON L8S 0A3, Canada [email protected]

Abstract. It is projected that software development positions in the US will increase by 21% from 2018 to 2028 an increase from 14% in 2014. Other economies have experienced similar type of growth as well. To meet the challenge of supplying a large number of graduates with the software engineering skills many universities have added on-line courses and degree in this field. In this paper, we will present a survey of approaches that have been used to design and deliver online courses with content that is software centric. We will compare these approaches with respect to each other, with respect to faceto-face courses and, specifically, with respect to our entirely online software program at McMaster University in Ontario, Canada. The course dimensions that will be compared include content, assignments, tests and exams and outcomes. A number of pedagogical styles may have been used for each of the course dimensions. All of this information will be gathered for the study Keywords: Online


Software
Pedagogy

1 Background Recently there has been increased interest in delivering content in an online format [1]. Courses on computing would seem to be naturally amenable to computer–based delivery. Interestingly, however, there has been a limited amount of research which surveys and compares approaches. This study is intended to help fill that gap by providing some guidance for instructors/course developers that are looking to re-design their course to be delivered in a fully online modality. Additionally, this study was intended to determine how much of a variation has occurred in the aforementioned course dimensions when comparing face-to-face vs online modalities. Small variation would indicate that online courses tend to look similar to their face-to-face counterparts. We were interested in determining whether or not there is more variation in pedagogical approaches within face-to-face courses and online courses. This observation will provide insight into whether course developers feel constrained by the technology in online courses thus limiting their pedagogical choices when designing the course. This will also show whether or not instructors of face-to-face courses are utilizing varied pedagogical approaches in their course designs.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 32–41, 2021. https://doi.org/10.1007/978-3-030-67209-6_4

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2 Method A number of courses will be selected and qualitative descriptions of the course content, assignments, tests/exams and outcomes will be examined. This selection of courses will include both online courses and face-to-face courses. These courses will be compared in the context of the online software program we implemented at McMaster University starting in 2016 [4]. As mentioned above, a key goal is to determine whether or not the online courses are quite similar to the face-to-face offerings. To accomplish this, we will work with a relatively large pool of courses. As a result, we will not organize the courses by content. We will be working with only two discrete groups–face-to-face and online. This will provide a larger sample size for each group, thus making the similarities or differences between the groups more significant. We are considering 2 elements of variability–within-group and between group. The within-group variation will provide an indication of the flexibility that course designers feel that they have when developing courses for either face-to-face or online delivery. The between group variation will give an indication of whether or not online course developers have deviated significantly from their face-to-face corresponds Additionally, qualitative summaries of the courses will be compared for the purpose of providing a reference to those that are looking to convert a face-to-face course to one that is online. In doing so, we will provide some insight gained from a number of years’ experience with the seventeen software courses that we have developed. Our program at McMaster uses a particular pedagogical approach which will be described in the paper. This approach was designed to ensure that the online course was very similar to a face-to-face offering. Our approach has been quite successful in terms of student feedback, student outcomes, and future enrolment. However, the aforementioned variation within groups shows that many options for online course design exist and this paper will detail some of the other options as well.

3 Results We surveyed 6 different courses in this work. The courses are typical courses that are offered in computing disciplines studied at a university level. These courses included Data Structures and Algorithms, Parallel Programming, Software Design, Discrete Math, Real-Time Systems and Machine Learning/Artificial Intelligence. These courses came from a variety of universities across Canada and, in one case, from a university in the United States. Generally, these were chosen based on the availability of full course outlines which allowed us to gather enough information about the course to allow us to gather data for 4 dimensions of the course – content, assignments, tests and exams and

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outcomes. There is little reason for us to believe that Canadian university course design is significantly different from designs from other countries. Therefore, these results should be applicable for other countries in the world. The universities surveyed for face-to-face courses included McMaster, Western, Carleton, University of Winnipeg, Queens and the University of British Columbia. For online courses, we surveyed McMaster, Athabasca, Thompson River, MIT, Ryerson and the University of Colorado at Boulder. The qualitative results that we obtained for all of the courses over all of the universities and all of the course dimensions are summarized in Tables 1, 2, 3, 4, 5, 6, 7 and 8. 3.1

Within-Group Variation for Face-to-Face Courses

With respect to course content, interestingly, there was very little variation in the delivery modality of the content. All of the courses utilized a live lecture to deliver the majority of the content. While there has been a lot of interest in the idea of a flipped classroom, clearly we did not observe this in our sample. The courses observed used a very traditional methodology to disseminate the course content. Out of the 18 face-to-face courses sampled, 11 courses followed a textbook to some extent. The remaining courses relied on course notes, custom course notes or selected readings to provide content. Although not directly noted in the tables, most of the courses provided links to external content in the form of web pages, videos, etc. Again, this is a relatively traditional way to deliver content to students. With respect to assignments, 5 courses opted not to include assignments as part of student assessment. For the purposes of this survey, as assignment was assessed as such based on how the student task was indicated on the course outline. These are thus differentiated from quizzes or projects based on the instructor’s delineation. The average number of assignments assigned per course (among courses that chose to use assignments) was 3. There were 5 courses that opted to use quizzes. With respect to tests and exams, the most common choice was to use a single midterm and final exam, conducted in person. 10 courses utilized this evaluation methodology. 4 courses chose to have only a final exam. 3 courses chose to not have any exams, and 1 course used two midterms and a final exam. Therefore, there was quite a bit of variability in the assessment, although the use of in-person exams was by far the preferred evaluation choice. In comparing outcomes, we opted to determine the average level of the course with respect to Bloom’s taxonomy. At the bottom (level 1), outcomes centered around “remembering” content are placed in this category. Level 2 includes outcomes based around the idea of “understanding”. Level 3 has outcomes expecting that students can “apply” course concepts. Level 4 outcomes include “analysis”. Level 5 in Bloom’s taxonomy is centered around “evaluation”. Finally, at the top level (Level 6), we have “create/design”. While there is some amount of subjectivity when trying to decide which outcomes fit into which Bloom’s level, we have tried to use words in describing

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the outcome as written in the course outline such that the Bloom’s taxonomy level is relatively easy to determine. The results are shown in Table 9. Generally we can see substantial variation in the level of each of the courses. 3.2

Within-Group Variation for Online Courses

With respect to course content, only McMaster’s B.Tech. program opted to use a traditional live lecture. This was 6 out of the 18 courses that we surveyed. Of course, this is heavily weighted in favor of live lectures, because we included our own program as part of the study. In general, this methodology was not popular. It appears that other universities designed online courses favoring offline content delivery. Out of the 18 face-to-face courses sampled, 8 courses followed a textbook to some extent. Interestingly, there seemed to be less dependency on traditional material as delivered from a textbook. This is likely because the online modality encourages the use of content from a wide variety of sources. With respect to assignments, only one course opted not to use assignments. The average number of assignments assigned per course (among courses that chose to use assignments) was 3.33. There were 7 courses that opted to use quizzes. From this, it seems that assignments and quizzes were quite commonly used by most courses. With respect to tests and exams, Interestingly, only 3 courses did not chose to use exams as part of the course evaluation. The most common choice was to use a single midterm and final exam, conducted in person, through the use of an examination center, or in person at the host university. Overall, there was not all that much variability in the assessment. With respect to the level of the online courses, the results are shown in Table 10. Generally we can see substantial variation in the level of each of the courses. 3.3

Between-Group Variation

Overall, we did not observe notable or significant differences in the methodologies employed between face-to-face and online modalities in all but the content delivery. Only our McMaster program utilized a live lecture for online delivery. The other online courses delivered content in an asynchronous mode. Other than that, however, the faceto-face delivery and the online delivery is strikingly similar for most courses. Particularly noteworthy is the fact that the online delivery mode used a traditional in-person exam. This is likely due to the difficulty in invigilation for a purely online exam. Even the level of the courses, as measured by Bloom’s Taxonomy, was similar. The average level was 3.32 for face-to-face courses and 3.56 for online courses.

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I. Singh and J. Fortuna Table 1. Face to Face–content and assignments

Table 2. Face to Face–tests & exams and outcome

An Assessment of the Pedagogical Style of Online Software Courses Table 3. Face to Face–content and assignments

Table 4. Face to Face–tests & exams and outcomes

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I. Singh and J. Fortuna Table 5. Online–content and assignments

Table 6. Online–tests & exams and outcomes

An Assessment of the Pedagogical Style of Online Software Courses Table 7. Online–content and assignments

Table 8. Online–tests & exams and outcomes

39

40

I. Singh and J. Fortuna Table 9. Face-to-face, average Bloom’s taxonomy level Course University Data structures and algorithms Western Carleton University Parallel programming Western Carleton University Software design Western Carleton University Discrete math Western Carleton Queens Real-time systems Western McMaster University Machine learning/AI Western Carleton Queens

of

of

of

of

Average Bloom’s level 4.67 2.50 Winnipeg 4.00 3.33 2.33 Winnipeg 2.67 1.33 4.00 Winnipeg 4.00 4.00 3.50 3.50 3.67 4.67 British Columbia 4.33 2.67 2.67 2.00

Table 10. Online, average Bloom’s Taxonomy level Course University Data structures and algorithms Western Carleton University Parallel programming Western Carleton University Software design Western Carleton University Discrete math Western Carleton Queens Real-time systems Western McMaster University Machine learning/AI Western Carleton Queens

of

of

of

of

Average Bloom’s level 5.00 5.00 Winnipeg 2.60 3.75 3.40 Winnipeg 4.00 4.50 2.67 Winnipeg 2.25 4.00 2.00 3.75 3.25 4.00 British Columbia 3.50 4.50 2.25 3.67

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4 Conclusions Our study has provided an assessment of the variation in the pedagogical approaches used in both face-to-face and online courses. In summary, we found that: 1. Most online courses employed a different content delivery mechanism, relying on an asynchronous delivery mode. McMaster’s B.Tech. courses were an exception. This program relies on live lectures, in order to replicate the in-class experience. 2. There was little difference in the use of textbooks between face-to-face and online courses. Online courses relied on textbooks less often, because of the integration of material available from the internet. 3. Assignments were equally utilized by face-to-face and online approaches. 4. Assessment via in-person tests and exams was applied almost universally between face-to-face and online courses. Overall, we can conclude that there are far more similarities than differences between face-to-face and online delivery modalities. The amount of variation within each group was also similar. There was slightly more variation in the content delivery mechanism in online courses, as mentioned above, simply because less instructors opted to use a textbook and there were many other convenient sources of content available from the internet. This study provides some interesting observations from a number of face-to-face and online offerings of computing courses and hopefully this will be helpful for instructors that are considering online offerings of courses.

References 1. Duncan, H.E., Young, S.: Online pedagogy and practice: challenges and strategies. The Researcher 22(1), 17–32 (2009) 2. Kelly, H.F., Ponton, M.K., Rovai, A.P.: A comparison of student evaluations of teaching between online and face-to-face courses. Internet High. Educ. 10(2), 89–101 (2007) 3. Gressman, P.: Engaging Students Through Technology Symposium 2015 Presentation by Phillip Gressman, 01 October 2015. http://repository.upenn.edu/showcase_videos/97 4. Fortuna, J., Srinivasan, S.: Course conversion from face-to-face to online for technical courses. In: Auer, M., Zutin, D. (eds.) Advances in Intelligent Systems and Computing-IMCL 2018 Proceedings, Springer, Cham (2018)

The Role of Competency Development in the Implementation of Portfolio-Based Education in Higher Education Vilmos Vass(&) and Ferenc Kiss Budapest Metropolitan University, Budapest, Hungary {vvass,fkiss}@metropolitan.hu

Abstract. The context of the study is the challenge of “skill gap”, which is growing fast in the Age of the 4th Industrial Revolution connected to the relationship between innovation and rethinking higher education. Higher education is under pressure to change all over the world. Globalization and internationalization, growing competition in the international higher education arena and the prioritizing of world class universities require the renewal of the concept of competency development from theoretical and strategic perspectives in HE. The purpose of the study is to introduce some results of portfolio-based education research, especially typology work, career and learning portfolios and the trends and processes of implementation of portfolio-based education in higher education. This study provides some important steps in the implementation of portfolio-based education in higher education, especially some pragmatic experience such as: formulating teams and learning communities, making and using competency standards in curriculum development and revision, changing innovation mindsets via implementation at individual and organizational levels. Keywords: Competency development
Innovation
Portfolio-based education

1 Context In the 21st century higher education is facing the challenge of a rapidly changing world, especially from cultural, social, demographic, technological, scientific and economic perspectives. Globalization and internationalization have an enormous impact on rethinking and reforming the higher education (HE) sector and for finding adequate answers to the above-mentioned challenges, especially focusing on creative and innovative higher education institutions. Under the umbrella of hard accountability systems, the tendency towards standardization is becoming stronger and higher education systems are not uniform and homogeneous (Maringe and Foskett 2012; De Witt, H., Gacel-Ávila, J., Jones, E. and Jooste, N. 2017). In fact, the main trends are based on personalization, which means a growing need for differentiated education. These are mainly cultural, psychololgical and social differences, but from the educational perspective, the driving force behing stronger personalization is the global market. Turning to the knowledge economy means a closer relationship between the market and higher education (Vass 2020). Quality of knowledge is undoubtedly key for © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 42–48, 2021. https://doi.org/10.1007/978-3-030-67209-6_5

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economic growth and competitiveness in a given country. (Hanushek and Woessmann 2009, Hanushek and Woessmann 2015a, 2016, Hanushek 2019). Hanushek and Woessmann hypothesise that there is strong relationship between the quality of cognitive skills, basic skills, learning outcomes and economic productivity (Hanushek, E. A. and Woessmann, L. 2015b). Another strong connection can be found between the growing knowledge economy and a changing set of competencies. The reason for this is that 57% of students, who enter the school system today will work in professions that do not yet exist (Davidson 2011). Soffel structured 21st century skills into three domains and 16 areas: Foundational Literacies (literacy, numeracy, scientific, ICT, financial, cultural and civic), Competencies (critical thinking/problemsolving, creativity, communication, collaboration) and Character Qualities (curiosity, iniative, persistence/grit, adaptability, leadership, social and cultural awareness) (Soffel 2016). Because of the growing need to adapt to a fast changing world, the model of fourdimensional education contains knowledge, skills, character and meta-learning domains (Fadel, Bialik and Trilling 2015) Focusing on the areas of competency, parallel to these structures, Jacob’s 4 C model emphasizes the growing importance of creativity and innovation, critical thinking and problemsolving, communication and collaboration, which have become a significant part of the new competency set (Jacobs 2010) Turning to non-cognitive skills, the Big Five model contains the dominant domains, namely openness, conscientiousness, extraversion, agreeableness and neuroticism. For instance, in the openness domain you can find some non-cognitive skills: creativity, curiosity, global awareness, positive mentality, fantasy, innovative skill, tolerance (Fazekas 2017). To summarise, the process of internationalisation has an enormous impact on developing creative, innovative personalized learning via cognitive and non-cognitive processes at personal and organisational levels in higher education as well (Smith, M.K. and Vass, V. 2017).

2 Competency-Based Education in Higher Education On the basis of this above-mentioned contextual background, competency-based education has become prominent. Firstly, competency-based education focuses on key competencies in structured areas (knowledge, skills and attitudes) of life, work and literacy, namely communication, mathematical, scientific and technological competence, digital competence, enterpreneurship, learn to learn, civic competence and cultural awareness. In fact, the OECD DeSeCo project defined four key areas of competence: acting autonomously, functioning in heterogenous groups, using tools interactively and reflective thinking (OECD 2005; Vass 2006). Secondly, key competencies such as metaphor of change, the way of thinking about how students learn in the 21st century and the future of schooling with some competencies, for instance, analytical and imaginative thinking (Hipkins, Bolstad, Boyd and McDowall 2014). Understanding the growing needs and complexities of key competencies includes some challenging transformational steps at individual and organizational levels in HE. Traditionally, higher educational institutions have focused on declarative, disciplinary knowledge from a teaching- and teacher-centered paradigm strengthening academic, cognitive areas in education. No doubt, competency-based education resulted in a

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dramatic paradigm change in education, especially focusing on the process of different levels of understanding, the growing importance of applied knowledge and knowledge transfer. Turning back to the first competency area of the OECD DeSeCo, acting autonomously, from the perspective of competency-based education, requires promoting lifelong learning, especially developing self-directed learning. This is the learning and learner-centered paradigm in HE and it has resulted in significant changes at the levels of curriculum development, learning and teaching methodology and assessment. In this paper, we will focus on assessment for learning, especially portfolio-based education. Nowadays, using portfolios under the umbrella of competency-based education in HE is spreading all over the world. Basically, the concept of student portfolio has been widely accepted and implemented in HE in some forms, namely learning,career and teaching portfolio. According to Zubizarreta, learning portfolio are now mainstream in higher education (Zubizaretta 2009). The learning portfolio focuses on student’s learning emphaisizing reflective thinking. As Satterthwaite and D’Orsi stated, career portfolio is “a collection of documents and other easily portable artifacts that people can use validity claims they make about themselves.” (Satterthwaite and D’Orsi 2008. 3-4.). Focusing on a career portfolio draws attention to the most important information related to personal performance, future opportunities and building confidence. The career portfolio generally contains personal characteristics, experience, accomplishments, knowledge and skills (Satterthwaite and D’Orsi 2008). A teaching portfolio contains the collection of evidence on quality of teaching. In other words, a dossier of evidence of good teaching practice (lesson and project plans, presentations, trainings, rewards, evaluation tools, reflective essays. To summarise, these types of portfolio (learning, career and teaching) have some similar characteristics. Each type of portfolio is based on self-evaluation and selfreflection, competency standards and learning/teaching outcomes in order to become more self-aware and self-reliant. Strengthening self-reflection has an enormous impact on innovative strategies and education in higher education (Wright, Knight, and Pomerleau 1999). In the next part of our paper, we would like to give a case of the implementation of portfolio-based education, especially career-portfolios at Budapest Metropolitan University (METU).

3 Implementation of Portfolio-Based Education (A Case Study) At Budapest Metropolitan University, the Academic Strategy is focusing on developing a career university, where the curriculum is relevant and up-do date, teachers have industry experience and connections and the knowledge is immediately applicable. The focus is on preparing students’ path into the labour market, as well as improving students’ and teachers’ creativity and innovation. In order to reach these goals, we implemented portfolio-based education 3 years ago, which is called MyBrand Program. All of this takes place in a very international environment where Hungarian and international students and teachers work together and can learn from each other. What are the expected outcomes of portfolio-based education at Budapest Metropolitan University?

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• The career portfolio helps students to learn from the academic knowledge of their professional field in an integrated way and to use their knowledge, skills, attitudes and intrinsic motivation for lifelong learning entering the labour market more successfully. • The competitive advantage of portfolio-based education is developing a pragmatic, practice-oriented mindset changing learning and teaching methodological culture increasing the reputation of METU as an innovative higher educational institution. • MyBrand Program means conscious and continuous career planning for our students during their academic years. They build their own brand presenting and reflecting their progression and competency development via collecting evidence and products. • Portfolio-based education has an impact on more qualitative curriculum development based on a revised Bloom-taxonomy, expected learning outcomes, METU competency standards and professional competencies, interdisciplinary curricular content, students’ and teachers’ tasks, tools and assessment (diagnostic, formative and summative) Turning to the last point, the algorythm of planning is (i) defining the aims of the course focusing on learning outcomes and competency areas, (ii) short content description with key concepts and interdisciplinary approach, (iii) planning students’ and teachers’ activities, which are based on interaction and cooperative learning strenghthening methodological culture and learn to learn competence, (iv) planning diagnostic, formative and summative assessment. To sum, MyBrand-based curriculum development focuses on learning putting competencies and learning outcomes at the center of planning. In order to reach these aims and expected outcomes promoting a MyBrand-based curriculum planning, learning and teaching methodology and assessment, we developed METU competency standards, namely • Communication competency will be developed through individual and group work creating complex situations, so students can observe the function and operation of communication. They develop further competence through new exercises set by themselves and practice presentation skills and collaborative assessment. • Creative competency is based on divergent thinking by finding and solving a problem from different aspects and to combine apparently incompatible elements creating something new and valuable. During problemsolving students are allowed to be open to different and multiple ideas and points of view. • Complex problemsolving means dealing with real life problems and tasks by involving external partners in the education. Problemsolving progresses often in groups which requires cooperation with students and teachers via project-based courses. • Critical thinking: Information gained through observation, thinking and communication will be analysed and synthesized in problem-based tasks. Through this way of critical thinking and debating, the students can be trained in their own experience, arguments and thoughts. • Cooperation means working togetherin an effective way. The students bring their own ideas and interests to the project set together with the teacher to discuss the

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aims, expected outcomes and collaborative tasks. Social and civic competencies are significant in this process. • Decision making will be developed through a large number of discussions, alternative tasks and different ways of thinking for potential solutions and by setting goals and defining the current conditions • Digital competence means competent use of ICT tools with a high level of information processing, selection, construction and creative knowledge transfer. • Self-knowledge and self-improvement can promote students to enhance their selfknowledge and to help in self-understanding. Through self-improvement the students can recognise their strengths and weaknesses by collecting evidence for their career portfolio. On the basis of the MyBrand-based curriculum planning, we are developing a mentoring system for the teachers in order to change the methodological culture at METU. The priorities are strengthening cooperative learning, project-based courses, developing interdisciplinary and pragmatic mindsets in the implementation process. “Learning by doing” was our basic principle using numerous interactions and creative tasks. We selected relevant teachers (8) from our staff on the basis of their experience and students’ feedback. Our mentoring programs contain in the first phase of the implementation to give professional trainings for the teachers on cooperative learning, project-methods, reflective thinking, formative assessment, problem-based learning and experience-based learning. Around 1/3 of our staff took part in these trainings. Via classroom observation, we discuss the MyBrand-based methodology in practice in order to evaluate teachers’ work and the implementation process. The criteria of the classroom observation are based on the MyBrand strategy. The most innovative methods are: making mind maps, brainstorming, visual association, place mat, interpretation quotes, advertising text writing, questioning, story telling, field studies, case studies, the fishbone model, problem-focused essays and analysis, reflexions and dilemmas, conversation circles, mosaic methods, database usage, reference research, CV, motivation letters, self-reflective questionnaires. The implementation process of MyBrand program has three Phases, which started in 2018 with extensive discussion and sharing ideas in order to strengthen mutual undestanding about career portfolio and portfolio-based education. Phase 1: First trainings and workshop for the students and teachers, e.g. curriculum planning (2018/2019) Phase 2: Developing Guide Book for the teachers, second trainings and workshop for the students and teachers focusing on assessment and online learning (2019/2020) Phase 3: Evaluating the implementation of the curriculum planning and mentoring program, developing synergies among the professionals, academic areas, developing assessment criteria on the portfolio-based exams.

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4 Conclusion Implementing portfolio-based education in higher education is a challenging process. At the system level, the contextual background of the implementation requires strong adaptability, problemsolving and handling changes. The internationalization and globalization in HE include the future characteristics of greater volatility, uncertainty, complexity and ambiguity, called VUCA-world. At the institutional level, implementation of competency and portfolio-based education has changed the students’ and teachers’ mindset focusing on innovation and creativity and turning to a learning- and learner-centered paradgm. Creating opportunities for discussions, sharing information, collaboration and mentoring has resulted in professional learning communities on the basis of different developmental teams for curriculum planning, learning and teaching methods and changing assessment culture. At the individual level, one of the strongest impacts on implementation of competency- and portfolio-based education is growing conscsiousness on self-reflection and self-assessment. This case is only the start of the professional and challenging road towards reaching our goals and expected outcomes. One of the most critical points is lack of relevant evidence for the students’ and teachers’ portfolio, but a systematic view of implementation and mutual trust can help to solve every problem in this process.

References Davidson, C.N.: Now You See It: How Technology and Brain Science Will Transform Schools and Business for the 21st Century. Penguin Books (2011) De Witt, H., Gacel-Ávila, J., Jones, E., Jooste, N. (eds.): The Globalization of Internationalisation, Routledge, London (2017) Fadel, C., Bialik, M., Trilling, B.: Four-Dimensional Education. Center for Curriculum Redesign, Boston, MA (2015) Károly, F.: Nem kognitív készségek kereslete és kínálata a munkaerőpiacon. Magyar Tudományos Akadémia Közgazdaság- és Regionális Tudományi Kutatóközpont Közgazdaságtudományi Intézet, Budapest (2017) Hanushek, E.A., Woessmann, L.: Do Better Schools Lead to More Growth? Cognitive Skills, Economic Outcomes, and Causation. Working Paper No. 14633. Cambridge, MA. National Bureau of Economic Research (2009) Hanushek, E.A.: The Economic Value of Improved Schools. Hoover Institution, Stanford University (2019) Hanushek, E.A., Woessmann, L.: The Knowledge Capital of Nations: Education and the Economics of Growth. MIT Press, Cambridge (2015a) Hanushek, E.A., Woessmann, L.: Knowledge capital, growth, and the East Asian miracle. Science, 351(6271), 22 January 2016 Hanushek, E.A., Woessmann, L.: Universal Basic Skills: What Countries Stand to Gain. OECD Publishing, Paris (2015b) Hipkins, R., Bolstad, R., Boyd, S., McDowall, S.: Key Competen Cies for the Future. NZCER Press, Wellington (2014) Jacobs, H.H. (ed).: Curriculum 21. ASCD, Alexandria, VA (2010)

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Maringe, F., Foskett, N.: Introduction: globalization and universities. In: Maringe, F., Foskett, N. (eds.) Globalization and Internationalisation in Higher Education, pp. 1–15. Continuum International Publishing Group, London (2012) Maringe, F.: The meanings of globalization and internationalization in HE: findings from a world study. In: Maringe, F., Foskett, N. (eds.) Globalization and Internationalisation in Higher Education, pp. 17–34. Continuum International Publishing Group, London (2012) OECD: The Definition and Election of Key Competencies. Executive Summary. OECD, Paris (2006) Satterthwaite, F., D’Orsi, G.: The Career Portfoilo Workbook McGraw-Hill, New York NY (2008) Smith, M.K., Vass, V.: The relationship between internationalisation, creativity and transformation: a case study of higher education in Hungary. Transform. High. Educ. 2, 1–9 (2017) Soffel, J.: What are the 21st-century skills every student needs? World Economic Forum, 10 March 2016. https://www.weforum.org/agenda/2016/03/21st-century-skills-future-jobsstudents/ Vass, V.: Kompetenciafejlesztés a 21. században (értékteremtés és megújulás) Selye János Egyetem Tanárképző Kara, Komárom (2017) Vass, V.: A tudásgazdaság és a 21. századi kompetenciák összefüggései. Új Munkaügyi Szemle 1(1), 30–37 Wright, W.A., Knight, P.T., Pomerleau, N.: Portfolio peopleteaching and learning dossiers and innovation in higher education. Innov. High. Educ. 24(2), 89–103 (1999) Zubizaretta, J.: The Learning Portfolio Jossey-Bass A Wiley Imprint. San Francisco, CA (2009)

Education 4.0: Remote Learning and Experimenting in Laboratory for Automation Hasan Smajic1(&), Abdulkadir Sanli2, and Niels Wessel3 1

2

Technology Arts Science TH Koln/Faculty of Vehicle Systems and Production, Cologne, Germany [email protected] Department for Mechatronics, Turkish German University in Istanbul, Istanbul, Turkey 3 Schnedier Electric GmbH, Ratingen, Germany

Abstract. Experimental laboratory equipment for automation technology and mechatronics is always associated with high costs. The reason for the high investments are the costs for different intelligent devices within an automation solution and the costs for extensive engineering. Beyond the costs, the number of workstations usually does not correspond to the required number of students to be trained. In this case, the same exercises have to be repeated several times, which also leads to increased personnel costs. Web-based laboratories are a very cost-effective solution to these problems. This paper describes how this goal can be achieved by implementing a WBT server (WBT - Web-Based Training Server) and a Java-based client-server architecture. The idea behind a remote controlled laboratory is to use web technologies and the Internet as communication infrastructure to perform an experimental part of the training with programmable automation devices. First of all, a detailed requirement profile for the laboratory was developed. Primarily technical, didactical and organizational requirements are concerned. In addition, the laboratory is to improve the education of the students by interactive, problem-oriented learning on real industrial automation components. The aim of the training is to learn suitable working methods for the design (engineering) of complete automation solutions starting from simple to medium complex machines and plants. There are 20 workstations available with the following automation components:

• • • • • • •

Sensors, detectors, encoders and RFID switches for data detection Programmable logic control (PLC) for data processing Human Machine Interface Velocity speed driver and Motion driver Smart meter for energy efficiency Ethernet Network and CANOpen as machine bus Programming and SCADA software

Keywords: Automation


Industry 4.0
Remote education

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 49–55, 2021. https://doi.org/10.1007/978-3-030-67209-6_6

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1 Training in Real and Virtual Environment The currently most widespread model for knowledge transfer at European universities is still characterized by passive lectures and exercises. However, such knowledge transfer through theoretical input in engineering courses always suffers from a low recall rate. At the Faculty of Vehicle Systems and Production, application-oriented teaching is provided with the support of practical exercises and group work. Although the recall rate with this approach is as high as 32% after three months, the number of dropouts is still too high. One of the main reasons for this dropout rate is an excessively high level of abstraction in the transfer of knowledge in mechatronic modules. This problem makes it increasingly difficult to find candidates who can carry out internal project work in the form of individual projects, interdisciplinary projects and master projects. The current shortage of skilled workers in Germany is also intensifying the competition between universities and industry, since even the few existing candidates with specialist knowledge prefer to write their theses in industry (Fig. 1).

Fig. 1. Various training opportunities in higher education

The main focus of this project is the development of teaching content with a high practical relevance for areas of automation technology. The previous rather passive and theoretical learning should be supplemented by the experience in the practical environment and would lead to essentially better and more efficient learning results. For this purpose, technical workstations have been developed which enable active experience and experimentation. Such an approach can make the level of abstraction of complex programming tasks much more comprehensible through personal experience with all sensory organs and through cooperation and communication with others. It can even increase the above-mentioned recall rate to 65% and thus lead to significantly better learning outcomes.

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2 Building of a Working Unit for Automation Training Depending on the complexity of the process, the spectrum of automation concepts used to control production plants ranges from individual PLCs to complex decentralized multiprocessor systems [1]. For the control tasks of simple machines, which predominantly require binary signal processing in the form of a logic or sequence control, central programmable logic controllers are still used. While a few years ago the trend towards more complex, more powerful central PLC systems in production engineering was still noticeable, this development is reversed by decentralized structures [2]. Increasingly, a displacement of large, complex central controls by several small, decentralized programmable logic controllers on the machine [6] can be observed. These are usually medium-sized controls or also intelligent sensors and drives directly at the machine or plant, which are networked with each other via corresponding field buses. With the aim of providing students with a modern education in automation technology, the Technical University of Cologne, together with an industrial partner, has designed equipment according to its own requirements. Attention was paid to the use of as many innovative automation technologies from industry as possible. Due to investment security, the selected components should not be older than two years on the market. A simple integration of the equipment into the lecture content is another criterion. The new developed workstation with implemented automation technologies is shown in figure 2nologies is shown in Fig. 2.

Fig. 2. Description of a workstation

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Inductive and capacitive sensors, optical encoders and radio frequency identification sensors (RFID) are provided for the acquisition of binary and analog process signals. They are connected to the programmable logic controller (PLC). A modern mid-range PLC with numerous external modules was selected for processing of the process signals. The PLC is a digitally operating electronic system for use in an industrial environment with a programmable memory for implementing specific functions such as logic control, sequence control, timing, counting and arithmetic functions. By programming digital or analog input and output signals, various types of machines or processes can be controlled. The signal processing of the PLC mainly uses the principle of cyclic program execution, i.e. the sensor values from the process are read into the PLC-internal process image, linked via the application program and processed sequentially. The program results are then transferred to the actuators which can influence the process. For the tasks “operating and monitoring”, advanced HMI touch panels with color display are used. Each station is equipped with modern electronic drive components. A velocity speed driver is used to practice right rotation, left rotation and commands for constant speeds and constant torque. A linear axis with servo motor and servo controller can be used to perform various tasks with positioning control. All components are networked via CANOpen field bus. Profibus DP is also available as an option. In this way, students can configure field buses and learn about their communication protocols. A new generation of decentralized controllers is significantly influenced by the spread of Industrial Ethernet and web technologies (IoT). By consistently integrating these technologies, various problems of existing fieldbuses, such as openness and manufacturer independence, can be solved [3, 4]. Up to the control level, these protocols have been consistently and successfully introduced at all workstations. All stations are networked via Ethernet TCP/IP, so that access to web servers of individual components is independent of location. The Cologne University of Applied Sciences is one of the first universities in Germany that aims to sensitize its students to the efficient use of energy resources within the framework of university teaching. For this purpose, appropriate measuring devices were installed at each station, which are used to continuously record and store all energy data of three consumers. The data is then evaluated and analyzed by the students. After the analysis, proposals for measures to be introduced to save energy will be developed. In order to increase the students’ motivation for training in the field of automation technology even more, technologies were also procured with which young people today can identify more easily. Thus, it is possible for students to complete certain exercise parts using Java Apps from their own smartphones. In addition to the hardware, corresponding site licenses for the complete engineering (programming, visualization with SCADA, simulation, etc.) were provided. The entire apparatus equipment of the Laboratory for Automation Technology at the Cologne University of Applied Sciences comprises 20 modern workstations of identical design. A large number of practical exercises can be carried out in the teaching environment. The training of students in the areas of control, drive and communication technology is thus decisively improved and made much more understandable.

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53

3 IoT Architecture for Remote Education The concept presented above was built identically at 20 workstations in the laboratory. At each station, two students work in a team, so the capacity for training is 40 participants. In order to use the potential of the equipment also outside, the approach of IoT was implemented. At each workstation 10 global IP addresses were implemented. A WBT server manages an Ethernet network of more than 200 addresses. The Internetbased architecture allows remote access to the automation technology modules for exercises and practical training. The resources of the laboratory can be used as “Distance Learning” for location-independent training. This technology offers an enormous advantage, especially in the global pandemic period due to COVID-19. Students do not have to be present at the university, but are able to carry out their automation tasks (programming, visualization, parameterization etc.) online via remote access. The equipment is also available to our external partners from industry and other universities. In the middle of the remote architecture is a server that manages the entire information content of the individual stations. The server controls remote access and routing to individual workstations as well as authentication (user name and password) of the users. Various SQL databases for archiving access protocols are implemented on the server. Remote access from the global network is established via a VPN connection. In this step the external computer becomes part of the laboratory network and is assigned an IP address via the DHCP server (Fig. 3).

Fig. 3. IoT architecture for practical exercises

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In the next step, a connection to a virtual computer from the computer pool is created by establishing a remote desktop connection according to previously defined rules. This computer provides a working environment with all software components required for programming. After a “user name and password” query, access is gained to all programming software for PLC, HMI and drives. The user can observe the downloading and testing of the programs written on the automation components via a standard webcam. Once a student has logged on to a remote computer, he can use all of Toll’s software to program the platforms. In Fig. 4 on the left side is the software for configuring and programming the PLC. Five different languages (LD, FBD, SFC, IL, ST) according to IEC 61131-3 are available for programming the tasks. When the tasks have been programmed, the participant can test and validate his solutions in a debugging process before the project is remotely transferred to the hardware. Tools for diagnostics and online services are then also available. Following a similar pattern, students also use the software to create the screens on the HMI device. Objects are defined in a graphic editor and linked to control variables.

Fig. 4. Software tools, testing and validation of programs remotely

HMI software uses Ethernet TCP/IP connectivity and is therefore able to support decentralized WEB gate access as well as the exchange of application data between terminals, the transfer of recipes and protocols for variables and much more. For the developed application, a simulation of the PLC variables (I/O, internal bits and words) and the graphical application can be performed with a RunTimer, before downloading the application to the device. This creates a condition window (top right) where all the exercise programs are validated. A webcam (bottom left) shows all activities on the unit.

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4 Conclusion and Future Challenge The COVID-19 pandemic confronts universities with great challenges to maintain research and teaching activities with as little contact as possible. Lecturers currently have to migrate to Internet teaching. In most cases, e-learning and digital tools are used to continue online courses to replace classroom teaching. But current approaches are limited to just lectures and theoretical mathematical exercises. In this paper it was shown how practical exercises can be carried out remotely via internet in a real technical environment. The first experiences have shown that the interest and motivation of students for the tasks of automation engineering has increased significantly. Varied exercises reduce the degree of abstraction in programming tasks significantly and lead to a significant improvement of the examination results. The developed internet-based architecture with its WEB server provides a good basis for location-independent access to all resources of the laboratory. The challenges of digitization in teaching is another focus of current research at the faculty. Research projects include, for example, the development of innovative assistance systems for evaluating learning progress based on artificial intelligence approaches and the introduction of an automatized booking service (Scheduler Tools). The resources of the laboratory are currently also being used by partners from industry and partners from universities as “Distance Learning”.

References 1. Wuttke, H.-D., Hamann, M., Henke, K.: Integration of remote and virtual laboratories in the educational process. In: Proceedings: 12th International Conference on Remote Engineering and Virtual Instrumentation (REV), pp. 157–162 (2015) 2. Meier, H. (ed.) Embedded Online Service - Internetbasierte Dienstleistungsplattform für Produktionsbetriebe 2004, 184 Seiten, VDMA Verlag, Frankfurt/Main (2004). ISBN: 3-81630477 3. Smajic, H., Wessel, N., Hammermeister, T.: Modernes Webfähiges Labor für Automatisierungstechnik, Eine Kooperation zwischen Hochschule und Industrie in Lehre und Ausbildung, AALE Konferenz für angewandte Automatisierungstechnik in Lehre und Entwicklung, Regensburg 8–9 Mai 2014 (2014) 4. Restivo, M.T., et al.: A Remote Laboratory in Engineering Measurement, vol. 56, no. 12, pp. 4836–4843, Dezembro 2009 (2009) 5. Wuttke, H.-D., Henke, K., Hutschenreuter, R.: Digital twins in remote labs. In: 16th International Conference on Remote Engineering and Virtual Instrumentation (REV 2019), 03–06 February 2019, B.M.S.College of Engineering, Bengaluru, India, p. 1 (2019) 6. Falkman, P., Helander, E., Andersson, M.: Automatic generation: a way of ensuring PLC and HMI standards. In: IEEE 16th Conference on Emerging Technologies and Factory Automation, ETFA 2011, Toulouse, 5–9 September 2011 (2011)

Developing Workforce Skills for Industry 4.0 Andrii Karpenko(&)

, Hanna Zasorina

, and Natalia Karpenko

National University «Zaporizhzhia Polytechnic», 64 Zhukovskogo Str., Zaporizhzhia, Ukraine [email protected], [email protected], [email protected]

Abstract. The article considers the main trends in the development of the Fourth Industrial Revolution, which will lead to changes in the workplace, business and human resource requirements. The aim of the article is to analyze global changes in the field of employment and job changes and to identify key skills that are in demand for the development of the Ukrainian economy. The study showed that Ukrainian companies do not have a clear vision of the needs of professionals and the necessary skills they must have. This is due to the fact that companies do not engage in strategic planning and do not develop scenarios for their business development. The heads of Ukrainian companies indicate the unwillingness of graduates to perform professional tasks in the workplace. There is a significant gap between the desired skills (on the part of employers) and the skills that young people have. Therefore, the paper substantiates the need to stimulate the integration of business and education, which will allow Ukraine to create new form of cooperation or to develop existing ones. These results can be used in universities, schools or other educational institutions and organizations to develop curricula as well as in business for the formation of training programs and adaptation of new employees. Keywords: Future workplace


Future skills
Drivers of change

1 Drivers of Change: Future Workplace and Employee Skills 1.1

Influence of the Industry 4.0 Revolution on Workplace Change

Already, we can observe cardinal changes in the structure of economic processes and national economies. They occur under the influence of new technologies, which also shorten the life cycle of professions and make significant social changes. These changes require greater adaptability on the part of the workforce and the entire labor market. Accordingly, a huge role in this process is given to educational institutions, which should provide the maximum necessary level of preparation of students for the requirements of future work. The transition to industry 4.0 implies increasing labor productivity, improving the quality and quantity of products, economic growth at the micro, meso and macro levels, but at the same time, imbalance in the global economy can be expected in the short term, which will lead to greater inequality among workers and increase global unemployment. It should be noted that most processes will be automated or disappear. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 56–64, 2021. https://doi.org/10.1007/978-3-030-67209-6_7

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Specialists of the future will face new challenges that require creative thinking, the ability to interact with people and artificial intelligence, readiness for changes in their professions or changes in the sphere of activity, and high adaptability. Now it’s hard to assess and predict the impact of the fourth industrial revolution, but it’s already clear that the future lies in automation, robotization, the development of digital technologies, artificial intelligence and biotechnology. It is worth noting that the modern industrial revolution is significantly different from the previous ones. If they developed linearly and the environment had enough time to adapt to changes before, the industrial revolution is developing exponentially now [1]. We believe, accordingly, that this will also lead to a discrepancy: the educational system to future challenges (pace and level of its development for the formation of necessary skills among employees); systems of policies and state mechanisms for regulating education; supply and demand on the labor market, ways of doing business. The fourth industrial revolution is associated with a significant influence of the mobile Internet, cloud technology, an increase in the computing power of computers and other equipment, the use of big data, new energy sources and other technologies [2], which implies an increase in labor productivity, the number of products, which will lead to economic growth [3]. As a result, the increase in the use of digital technologies gives rise to the so-called cyber-physical production systems [4]. But, at the same time, increased use and full transition of some sectors of the economy to new technologies will lead to automation of jobs [5], as a result, there will be a massive retrenchment of workers. Also, in the short term, this can lead to an imbalance in the global economy and, possibly, increase unemployment [3]. In addition, due to automation, digitalization and the introduction of many new technologies, jobs will be modified, which will lead to the disappearance of most professions [6]. An overview of the main trends that will change the workplace in the future and their comparison are presented in Table 1. It is worth noting that the above studies evaluate only potentially automated professions, and not the number of automated jobs [5]. That is, now it’s quite difficult to give accurate forecasts of the number of workstations and the number of unemployed, since the duration and speed of automation in countries is very different [4]. Despite all the positive forecasts regarding the growth of labor productivity, Deloitte research confirms that the impact of new technologies negatively affects the employee’s condition and productivity: more frequent burnout due to information load and round-the-clock contact, low employee involvement [7]. All the trends shown in Table 1 are of a general global nature, but their level of manifestation will determine the future development of each country in different ways. A special role in this is played by technological and economic development, the level of readiness of the transition of industry to industry 4.0. Apart from the positive factors, these trends, globalization and integration of the world labor market will widen the gap between countries. 1.2

Skills that Will Be Required in the Years 2020–2030

As stated above, most jobs will be automated and digitized. But along with this, radically new professions that cannot be replaced by robots will appear on the labor market. And those places that remain will require certain new skills and knowledge

58

A. Karpenko et al. Table 1. Trends that affect the future workplace and the necessary skills for work

Resource Skills of the future: What you need to know and be able to in a new complex world [3]

Future work skills 2020 [8]

Employment in 2030 [9]

Drivers of change Digitalization, automation, globalization (economic, cultural, technological), greening, demographic changes, formation of a network society, accelerating Increased longevity, development of smart machines and systems, computational world, new media ecology, superstructured organization, globally connected world Technological change, globalization, demographic change, environmental sustainability, urbanization, increasing inequality, political uncertainty

from employees, which until recently were not required. Already now, when analyzing vacancies on job sites and conducting studies that are related to the requirements for an employee, many employers point to a significant gap between the skills that the applicant has and the skills that the employer needs. At the moment, there is no single classification of the demanded skills of the future and their expanded significance. Some scientists divide them into hard (professional) and soft skills (additional knowledge, skills, personal qualities), and the other into cognitive, non-cognitive (social) and technical ones. Examples of future skills are shown in Table 2. Analyzing the given skills of the future, it is worth noting that each scientist and company has its own list of necessary skills. They have similar skills as well as skills that are different. Our assumption that this is connected with a different kind of activity of people: each profession and position has its own list of skills, which is somewhat different and has different priorities in use due to the difference in work processes. Therefore, these lists are generalized. It is also worth noting that the difference in the list of skills also differs from the country, its economic position and growth. This affects the relevance of these skills. In addition, we determined that some companies and researchers presented a more generalized version of the skills without revealing their essence, others were described in detail, and still others represented the skills as full-fledged (the skill “People management” implies the ability to motivate, manage conflicts, create and coordinate teams, etc.). Studies have revealed that the fourth industrial revolution will lead to a high demand for technological skills. Employees will be required to understand the technologies, with which they work, the ability to develop, implement and adapt innovations [12]. Along with this, the demand for digital skills will increase, as industry 4.0 is closely linked to the digital economy. The EU claims that “there is a need for digital skills for almost all jobs where technology complements existing tasks” [11].

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Table 2. Skills needed for the future Resource The 4th Industrial Revolution & The future of jobs [2]

Future work skills 2020 [8]

Global education futures [10]

The 10 skills you need to thrive in the Fourth Industrial Revolution [11]

Skills list Integrated problem solving, critical thinking, creativity, people management, coordination with others, emotional intelligence, judgment and decision making, service orientation, negotiation, cognitive flexibility Sense-making, social intelligence, novel and adaptive thinking, cross-cultural competency, computational thinking, new-media literacy, transdisciplinaity, design mindset, cognitive load management, virtual collaboration Cognitive skills: self-development, organization, managerial skills, achievement of results, solution of non-standard tasks, adaptability; Sociobehavioral skills: communication, interpersonal skills, intercultural interaction; digital skills, systems building, information management Complex problem solving, critical thinking, creativity, people management, co-ordinating with others, emotional intelligence, judgment and decision-making, service orientation, negotiation, cognitive flexibility

Inevitable automation and robotization in the future will lead to an increase in the need for skills that cannot be delegated to machines or technologies. Therefore, modern employers are increasing the need for soft skills. That is, the employee needs to have “finely tuned social and emotional skills” [12]. Increased demand for higher cognitive skills is expected: creativity, critical thinking. As the emergence of new products, technologies and ways of working, people must become more creative in order to benefit from these changes and help their business stay afloat, attracting more and more consumers of their products [11]. Transformational changes in the world economy are determined today by the intellectual activity of individuals, large and small companies and states, which ensure the production of new ideas that are commercialized in innovation. Indisputable is the priority place of man in the system of modern socio-economic development. Today the substantiation of expediency of identification and separation in the structure of human potential of that part of it which is characterized by maximum productivity, determines the probability of future capitalization, provides added value and on this basis determines the current and strategic level of competitiveness at micro and macro level. Intellectual assets of human potential as a set of cognitive, creative, emotional competencies of economically active population are defined [13]. The boundaries between disciplines, such as science and computer science, will become more blurred. Technology cooperation can disrupt existing business models, but also create completely new markets and new areas of application [14].

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2 Skills of the Future for Ukraine Currently, there is not enough literature, summaries, scientific publications or analytical notes, as well as instruments or methods for integrating into 4.0 Industry in Ukraine. Also, there are practically no initiatives to motivate students to get the appropriate specialties at the state level, the levels of analytical centers or commercial organizations. At the same time, large companies and IT-companies are engaged in the search and recognition of human talents; build a strategy for the struggle for talents and their retention [15]. The general resumes that now exist are focused on countries with a high level of economic development and technological development that do not meet the real needs and possibilities of education, business, technological and innovative development, and a balanced labor market in Ukraine. The results of these studies are not universal, but only provide an approximate guideline and an opportunity to understand the vector of future development for Ukraine. Therefore, it is now relevant to determine the current level of development and the desired result, to do gap analyze. Although Ukraine (Table 3) belongs to countries with an income below the average, it is worth noting that its human development indicators tend to unity, rather than to zero like other countries in this category. Having a high level of education of the population, the country has deterioration in living standards, a low level of economic development and labor productivity [20]. It is also worth noting that Ukraine has a fairly low level of competitiveness. We believe that, to a greater extent, these low indicators are the consequences of the absence and slow pace of reforms regarding labor market regulation, business support and the development of business infrastructure, innovative enterprises, lack of trust and communication between the educational institution, business and government representatives, low student motivation to knowledge, formalization of obtaining a diploma, low standard of living (not meeting the needs of the population and the implementation of their needs) etc. The modern interaction of business and the university is at a critically low level. Most employers, especially small businesses, do not interact and do not make adjustments to training programs. Therefore, universities are divorced from reality thereby training specialists without the necessary skills that are not required in the realtime labor market, which has a detrimental effect both on business (additional costs for staff retraining) and on the university (knowledge obsolescence, valuation of the education system). As a rule, high-quality professional education prevents a decrease in productivity at the workplace, an increase in losses, loss of customers and innovative opportunities, and an increase in resources (temporary, monetary, human) for the search and selection of personnel. Close interaction between educational institutions and business allows developed countries to quickly advance scientific developments in the real sector of the economy, which is accompanied by a high level of training at universities, where students are more motivated due to a number of restrictions (high entry requirements, high cost, etc.). In Ukraine, as reality shows, the situation is different. Most students go to universities with poor results and often with low motivation to obtain specific knowledge. This is confirmed by a study conducted in 2016 by the CEDOS Analytical

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Table 3. Dynamics of GDP per capita and international indices in the studied countries 2017

United States

2018

2019

GDP per capita

GCI

HDI

Happiness Index

GDP per capita

GCI

HDI

Happiness Index

GDP per capita

GCI

HDI

Happiness Index

53,5

84,8

0,924

6,89

–

85,6

0,920

6,89

–

83,7

0,924

6,94

Canada

43,2

80

0,926

7,33

–

79,9

0,922

7,28

–

79,6

0,926

7,23

Germany

40,7

82,6

0,936

6,97

41,1

82,8

0,939

6,99

–

81,8

0,936

7,08

Poland

25,3

68

0,865

6,12

26,5

68,2

0,872

6,18

–

68,9

0,865

6,19

Lithuania

29,3

66,4

0,858

5,95

30,5

67,1

0,869

6,15

–

68,4

0,858

6,22

Latvia

26,8

64,8

0,847

5,93

28,2

66,2

0,854

5,94

–

67,0

0,847

5,95

Estonia

28,9

–

0,871

5,74

30,0

70,8

0,882

5,89

–

70,9

0,871

6,02

Rep. Korea

–

70

0,903

5,88

–

78,8

0,906

5,89

–

79,6

0,903

5,87

Japan

–

81,6

0,909

5,92

–

82,5

0,915

5,89

–

82,3

0,909

4,56

Ukraine

15,9

53,9

0,751

4,10

–

57,0

0,750

4,33

–

57,0

0,751

4,56

Reference [16–19]

Center together with Gfk Ukraine as part of the Academic Integrity in Ukraine Project (SAIUP), supported by the US Embassy in Ukraine. It was found out that from 4% to 23% respondents choose a specialty due to the fact that it allows them to go on a budget; from 4% to 27% would not choose their specialty a second time; more than 20–30% of students choose their specialty because of the opportunity to receive free tuition at the expense of the state. This confirms that despite the high level of education, the population of Ukraine is forced to receive higher education based on their financial capabilities. Accordingly, 13–32% of Ukrainian students, regardless of educational institution, are employed, combining work and full-time education. In general, this is good, because the student can consolidate his theoretical knowledge in practice, but most students do not work in the field of study. This increases the workload of the student and decreases his involvement in the educational process [21]. In addition, the lack of a real choice of disciplines by students, as well as clear criteria for their assessment, leveling the higher education system in society does not contribute to the high motivation of young people to obtain real knowledge. On the other hand, there is a problem on the part of employers. Most companies do not know what kind of employees they will need in the near future and what skills they should possess. This confirms that companies do not carry out strategic planning and do not develop business development scenarios, do not follow HR trends [22]. This negatively affects both the labor market and the development of individual companies and overall economic growth. One of the most negative influences is the situational nature of decisions and actions. That is, due to a lack of understanding of the future need for personnel (and their skills), information about the necessary skills and knowledge simply does not have time to reach the educational institution. As a result, future participants in the labor market do not have time to obtain the necessary knowledge. Consequently, the business has to increase expenses not only for the qualitative adaptation of the new employee, but also for his training or retraining (financial expenses, time costs).

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A. Karpenko et al. Table 4. Comparison of research results on the necessary skills for the future

Resource Skills for a modern Ukraine [20]

CSR-Ukraine [23]

Skills list Sociability responsibility, sales skills, learning ability, stress resistance, knowledge of markets and products, organization of working time, self-organization, knowledge of analytical methods, analytical abilities, purposefulness, knowledge of specialized software, knowledge of foreign languages, teamwork, knowledge of legislation, versatility, negotiation, web programming, critical thinking, organization, design, problem solving, professionalism, driving, decision making, teamwork, basic computer skills Emotional intelligence, ability to work in a team, solving complex problems, ability to learn quickly, adaptability/flexibility, analytical thinking, critical thinking, project management, strategic thinking, initiative/change management

The studies (Table 4) of the World Bank and the Center for the Development of Corporate Social Responsibility (Center for CSR Development) showed that young people are not ready to fulfill their tasks in the workplace. According to Ukrainian employers, graduates have the best knowledge of the following skills: IT literacy, initiative, communication skills, competent writing and speaking, teamwork, fast learning, good adaptability; and worst knowledge about the professional skills are as follows: the ability to negotiate, speak oratory, project management, solving complex problems and strategic thinking [23]. According to the graduates themselves, they are able to learn, know how to work in a team, are good at coordinating with others and listening, proactive, responsible and sociable. At the beginning of their work, they lacked public speaking skills, the ability to comprehend and make decisions, lacked IT literacy skills, experienced stress resilience, and conflict management and negotiation [22].

3 Conclusion The study proved that in the near future the pace of inevitable automation of all spheres of human life will increase. People will gradually be crowded out by robots from many modern activities. They will be more and more popular in new conditions, where it is impossible to automate processes and creativity, the use of logic, etc. are needed. All this will lead to the formation of new requests for human skills, increasing inequality, unemployment, etc. Significant visible changes are already taking place, which are manifested in the organization of labor, in the requirements for new employees and their skills. Many companies lack knowledge and skills among employees. This forces them to train and retrain staff for their own purposes independently (as reflected in low level of knowledge and willingness to work in a real economy). Currently, educational institutions continue to train employees for the rapidly departing system of the global economy. This situation is especially acute in developing countries or countries with a

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low level of economic development. Such systems do not have sufficient funds and the necessary competencies to be included in the economy of the future, and they simply may not have such a role in the world of high-performance automated production. Ukraine, in principle, can also be attributed to this type, which now has every chance to move from low-tech production to high-tech. Already, there is a high level of development in the field of computer technology and the sphere of IT services. But along with this, it is necessary to create and develop mechanical engineering, electrical equipment, biotechnology, pharmaceuticals and much more to facilitate the integration of business and education. As our study shows, in Ukraine there are enough problems that affect the determination of the necessary skills and their development among employees. Summing up the above, it can be argued that the problem of skills development lies in the low level of interaction between the educational institution and business, the construction of ineffective business models, and the low motivation of staff and students to acquire knowledge. Therefore, modern Ukrainian companies must create and adapt their employment plans and business development strategies to ensure compliance with the requirements of future skills. Already, HR managers need to use new methods of searching and testing skills of candidates for selecting talents, creating new opportunities for their development and retention. On the part of the government, it is necessary to respond in a timely manner to changing conditions, making education a national priority. Indeed, in order to maintain the competitiveness of enterprises and satisfy their needs in the workforce, representatives of educational services must take into account the full range of skills that will be needed in the labor market. Educational institutions need to adapt to the new conditions of reality, to show more activity in the formation of cooperative ties with business. This will make the educational process closer to the real economy and create more opportunities for students to gain practical experience and develop the necessary skills. It is important to focus on developing the skills that are most in demand today and will be needed in the future among young people: critical thinking, analytical skills, high adaptability, ability to work productively in a team, creativity, etc.

References 1. Solving future skills challenges. Universities UK (2018) 2. Van Dam, N.H.M.: The 4th Industrial Revolution & the Future of Jobs, 1st edn. (2017) 3. Loshkareva, E., Luksha, P., Ninenko, I., Smagin, I., Sudakov, D.: Skills of the future: What you need to know and be able to in a new complex world. https://worldskills.ru/assets/docs/ media/WSdoklad_12_okt_rus.pdf 4. Whitepaper Summary: Skill Development for Industry 4.0. BRICS Skill Development Working Group. https://rda.worldskills.ru/storage/app/media/Reports/2016_BRICS%20Skills%20Development%20for%20Industry%204.0/2016_BRICS_Skill-development-forindustry-4.0_report.pdf

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5. Bakhshia, H., Downingb, J.M., Osborneb, M.A., Schneiderd P.: The Future of Skills: Employment in 2030. https://www.robots.ox.ac.uk/*mosb/public/pdf/2864/Bakhshi%20et %20al.%20-%202017%20-%20The%20future%20of%20skills%20employment%20in% 202030.pdf 6. The 2030 Skills Scorecard Bridging business, education, and the future of work. Global Business Coalition for Education and the Education Commission. https://gbc-education.org/ wp-content/uploads/2019/09/GBC-Education-2030-Skills-Scorecard.pdf 7. Deloitte Insights. Human Capital Trends 2020 (2020) 8. Davies, A., Fidler, D., Gorbis, M.: Future Work Skills 2020. http://www.iftf.org/uploads/ media/SR-1382A_UPRI_future_work_skills_sm.pdf 9. Employment in 2030. https://futureskills.pearson.com/research/assets/pdfs/media-pack.pdf 10. Global Education Futures. https://globaledufutures.org 11. The 10 skills you need to thrive in the Fourth Industrial Revolution. https://www.weforum. org/agenda/2016/01/the-10-skills-you-need-to-thrive-in-the-fourth-industrial-revolution 12. Skill shift: Automation and the future of the workforce. McKinsey Global Institute (2018) 13. Karpenko, A.V.: The Development of Intellectual Assets of Human Potential: theory and practice. Monograph. Zaporizhzhia (2018) 14. The Future of Work Jobs and Skills in 2030. Z_punkt The Foresight Company, The Centre for Research in Futures and Innovation. Wath-upon-Dearne, UKCES, England (2014) 15. Karpenko, A., Basenko, K.: Highly effective corporate culture as an instrument of talents’ attracting and retaining. Baltic J. Econ. Stud. 3(4), 101–106 (2017) 16. State service of statistics of Ukraine. Statistical yearbook. LLC “Beech-Print”, Zhytomyr (2018) 17. The Global Competitiveness Index. https://www.weforum.org 18. Human Development Index. http://hdr.undp.org 19. The World Happiness Report. https://worldhappiness.report 20. Del Carpio, X., Kupets, O., Muller, N., Olefir, A.: Skills for a modern Ukraine (English). Washington, D.C.: World Bank Group (2017). http://documents.worldbank.org/curated/en/ 809811483684795777/Skills-for-a-modern-Ukraine 21. Motivation of students to study as a defining condition of academic integrity (RESEARCH). https://saiup.org.ua/resursy/motyvatsiya-studentiv-navchannya-yak-vyznachalna-umovaakademichnoyi-dobrochesnosti-doslidzhennya 22. Zinchenko, A.G., Saprykina, M.A.: Skills for Ukraine 2030: a view of business. LLC “Publishing House”YUSTON, Kyiv (2016) 23. CSR-Ukraine. https://csr-ukraine.org/pro-nas

Work-in-Progress: Gamification and Design Thinking–A Motivational Analysis of an International, Interdisciplinary, Team-Based University Course David Kessing(&) and Manuel Löwer Bergische Universität Wuppertal, Gaußstraße 20, 42119 Wuppertal, Germany [email protected]

Abstract. Design Thinking gains more and more importance as a modern method for structured innovation and already found its way into many different business contexts. Hence, it is important to teach students this method early on during their studies. An effective way to teach development processes is to simulate realistic teamwork. The IDEEA (International Design and Engineering Education Association) is a growing association of currently 23 universities worldwide, which offer this course concept every year since 2019 by building international and interdisciplinary teams with the task to develop a product by using the Design Thinking process. During the first IDEEA class in 2019 motivational problems could be observed across most of the teams. Especially decision making and constant progress of the team was increasingly problematic during the semester. While the results of the teams in the final presentation were above average, the commitment of the students to the teams and the course decreased throughout the semester. In order to increase students’ motivation in the upcoming IDEEA class/course a systematic field study based on established gamification frameworks is implemented. The goal of this research is to compare different motivational strategies to foster collaboration and team success. Keywords: Gamification


Design thinking
Motivation

1 Introduction The International Design and Engineering Education Association (IDEEA) is a growing cooperation of currently 23 universities worldwide. The IDEEA is the successor of the PACE Partners for the Advancement of Collaborative Engineering Education) program which started in 1999. The goal of the IDEEA is to teach students modern aspects of design engineering work like international teamwork, intercultural communication and interdisciplinary collaboration. As a framework the Design Thinking process is used, which also is the educational content of the course [1]. In the first successful semester of IDEEA in 2019, the students developed detailed drones for many different well-researched use cases. The drones were presented on the final symposium at Monterrey Tec University in Mexico. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 65–73, 2021. https://doi.org/10.1007/978-3-030-67209-6_8

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While the quality of the team results was above average compared to other student projects, the motivation of the team members decreased during the project as many of the participants reported to the lecturers. The reasons mentioned were communication and decision difficulties as well as a general lack of commitment to the project and the team. To address this problem, it is planned to integrate different motivational aspects, based on the gamification concept, to teams in 2020’s IDEEA semester.

2 Literature Review The term gamification first appeared in research of management consultant Nick Pelling in 2002 and has been gaining attention over time. A first scientific conference on the topic was held in 2011 [2, 3]. Hence, gamification is a relatively young approach, which started in the field of software development. Meanwhile, gamification methods are already successfully used in many companies [4, 5]. Different frameworks try to structure gamification techniques by their addressed motivational driver and different “player types”. Relevant approaches are Bartle’s “Player Type”, “How to gamify” from Morschheuser, Hamari et al. and “Actionable Gamification” from Chou [6–8]. Chou observes in “Actionable Gamification” eight motivational gamification Core Drives of video games, structured in the so-called Octalysis framework: • Positive: Epic Meaning and Calling, Development and Accomplishment, Empowerment of Creativity and Feedback • Neutral: Ownership and Possession, Social Influence and Relatedness • Negative: Scarcity and Impatience, Unpredictability and Curiosity, Loss and Avoidance A context which is analyzed with the Octalysis framework regarding the fulfillment of the Core Drives can be visualized in an octagon graph as in Fig. 5. Richard Bartle defined four general video game “player types” in his research “Hearts, Clubs, Diamonds and Spades – Player who suit MUDs”, which are: achiever, socializer, explorer and killer. These player types are the first approach to cluster people regarding their main motivational drive with the axis of activity (acting$interacting) and activity object (world$players). These relations are visualized in Fig. 1.

Fig. 1. Bartle’s four player types model

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• Achievers play to “win” and therefore act on the world. They are searching for accomplishment and rewards. • Explorers interact with the world. They want to discover the story and the phenomena. • Socializers interact with other players. Communication and social influence are the most important drives. • Killers act on other players. They try to dominate people by physical or psychological violence. To find out the player type, a so-called Bartle test can be conducted. The Bartle test consists of 40 questions where participants have to decide between options which are tendencies to the player types. For example, one question of the Bartle test is: Would you rather have: 1) A spell to damage other players 2) A spell that increases the rate at which you gain experience points In this case, answer 1 will give a tendency to the killer type while answer 2 is meant to be the achiever type. The final Bartle quotient has a total amount of 200% with each player type maximum having an amount of 100%. Thus, participants can be a combination of multiple player types as this is more realistic than being only one player type. Bartle gives an estimation in his research that about 80% of all players are socializers, while 10% each are achievers and explorers. Only a minority of less than 1% are killers. In following research Bartle developed a more detailed profile. He mentioned that the four player types are not sufficient to represent reality comprehensively, especially in gamification applications [9, 10]. Hence, Bartle added the axis implicit and explicit to each of his player types which resulted in the following model with eight player types (Fig. 2):

Fig. 2. Bartle’s eight player types model

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No established test for Bartle’s eight player type-model exists today. Also, Bartle’s player types were not meant to be used outside of Game Design, but it was frequently used in gamification business as it helps to cluster people regarding their activity and suitable rewards. Morschheuser, Hamari et al. compared 41 different approaches for gamification implementation in their literature review “How to gamify” and developed the framework based on the Design Thinking process shown in Fig. 3.

Fig. 3. Gamification process “How to gamify” from Morschheuser, Hamari et al.

The process includes seven phases, from preparation of the development, environment analysis, idea generation, mechanics design, technique implementation, success evaluation and monitoring, which can be performed iteratively according to the Design Thinking approach, if required. This process will be used in the following research for the analysis and development of suitable gamification strategies for the teams of the 2020’s IDEEA class. Bartle’s “eight player types”-approach offers a well-established model and therefor is used in this research for user analysis [11]. As there is no test for this model yet, a new approach on how to use the existing “four player”-Bartle test is proposed. The Octalysis framework of Chou offers an intuitive visualization tool and a high amount of gathered gamification techniques and thus, will be used for technique ideation and success evaluation.

3 Approach Starting with the defined objective of the implementation, a user analysis will be conducted by classifying the students into Bartle’s Player Types. On the basis of Chou’s gamification technique catalogue from Actionable Gamification, fitting gamification techniques will be identified in the Ideation Phase. After designing the techniques, the two strategies of “supporting existing motivational factors” (positive) and “balancing less represented motivational factors” (negative) will each be implemented in one team. Two other teams will form the control group for this field study. Analysis and evaluation of the students’ motivational status will be conducted using online surveys on the fulfillment of the eight Octalysis Core Drives as a multi-item-measurement

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(see Fig. 5). The overall success of the gamification strategy will be evaluated and adopted in the following semesters of the IDEEA course. From the described field study design three research hypothesis derive (Fig. 4):

Fig. 4. Field study design (unfactorial, 3 independent variables, 1 dependent variable with 8 formative indicators)

• H1: Positive gamification in comparison to no gamification positively influences the motivational status of the team members • H2: Negative gamification in comparison to no gamification positively influences the motivational status of the team members • H3: Positive gamification in comparison to negative gamification positively influences the motivational status of the team members The standard Bartle test is adapted for the application case of this field study to build a more realistic test scenario. Therefor, the questions are changed from gaming related content to study related content. Also, as there is no established test for Bartle’s eight player types, the standard Bartle test will be used with an extension of the analysis algorithm. Each question of the standard Bartle-test implicates a tendency to one of the four standard player types. With the introduction of the implicit/explicit axis, the analysis of the questions of the standard Bartle test are also assigned to be implicit or explicit. Hence, all eight player types can be identified with the standard Bartle test. The exemplary question from Sect. 2 is now changed to: Your group is doing mediocre in the project. Due to a mistake of the professor you get information on the final exam. Would you rather: 1) Give false information to the better teams 2) Try to outpace the better teams with the information The answer possibilities are considered implicit as they are long term orientated. Thus, this question now indicates the implicit killer type politician or the implicit achiever type planner. The survey on the fulfilment of the Octalysis Core Drives consists of one question for each of the eight Core Drives. The questions are also aligned with the course scenario. As an example, the question for the Ownership is: “I was able to integrate my own ideas of the drone into the project.”, the question for Scarcity is: “I really want to move on to the next phase of the project, but we are not ready yet.”

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4 Preliminary Results The results of the Bartle test with 19 participants are shown in Table 1. Table 1. Results of Bartle test (N = 19) Bartle player types Hacker (implicit Explorer) Scientist (explicit Explorer) Friend (implicit Socializer) Planner (implicit Achiever) Griefer (explicit Killer) Networker (explicit Socializer) Opportunist (explicit Achiever) Politician (implicit Killer)

% of answers given 20,78 17,41 16,46 12,15 12,15 10,66 5,94 4,45

The results show that the most present player type is the explorer in general. The answers relating to the implicit hacker have the most consent along the participating students. Bartle’s definition of the hacker and scientist player type are summarized in Table 2. Table 2. Definition of the hacker and scientist player types by Richard Bartle Hackers are implicit explorers They experiment to reveal meaning They have an intuitive understanding of the virtual world, with no need to test their ideas They go where fancy takes them They seek to discover new phenomena

Scientists are explicit explorers They experiment to form theories They use these theories predictively to test them They are methodical in their acquisition of knowledge They seek to explain phenomena

The assumption that most of the IDEEA students have an explorer mindset is a solid basis for this course as the main objective is to design a drone independently. The requirements for successful participation in this course is the motivation to “explore” solutions for the chosen drone use case by using design thinking. Chou comments Bartle’s Player Types in Actionable Gamification and mentions that “Explorers continuously use their creativity to find new ways to test every boundary that constraints them, and when they succeed, they are fulfilled by a sense of accomplishment.” [8] Hence, the development of gamification strategies will consider “giving constraints” as negative motivation and “enhancing accomplishment” as positive gamification. The results of the survey regarding the motivational Core Drives are shown in Fig. 5. This survey was conducted before the mid-term presentation, hence without implemented gamification strategies. This survey shows the status quo of the students’

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motivation which is used as a reference for the second part of the survey which will examine the influence of the gamification strategies on the teams’ motivation.

Fig. 5. Visualization of the survey results on the Octalysis Core Drive fulfillment

The results of this survey show the highest agreement to the Core Drives Meaning and Social Influence. This fits to the expectations as the international cooperation between the universities creates a higher relevance compared to other courses. The international teamwork strengthens the Social Influence factor. The Core Drives Accomplishment, Empowerment, Ownership and Unpredictability are also at a high level. As the survey was conducted during the start of the semester, the motivation was generally at a high level. This is expected to decrease during the ongoing semester based on last year’s students’ course evaluation from last year. As mentioned before, two gamification approaches are developed from this analysis: 1. Supporting existing motivational factors by enhancing accomplishment feeling (positive motivation) and 2. balancing less represented motivational factors by enforcing constraints (negative motivation) Each approach is implemented to one team after the mid-term presentation on May 4th. Two other teams without integrated gamification mechanics will be used as a reference. Gamification approach 1 is implemented as a weekly positive supporting e-mail, which specifically addresses the Accomplishment Core Drives. The first e-mail after the mid-term presentation included phrases like “Congratulations for this awesome midterm presentation! You did a really good job! We already finished Research, Definition and a big part of the Ideation phase.” The gamification approach 2 is realized with a countdown timer implemented to the background of the mentor during the online meetings. With the constant visualization

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of the deadline until the final presentation, the urgency feeling of the team members is addressed. The implemented countdown background is visualized in Fig. 6.

Fig. 6. Countdown-Timer background for negative gamification in online-meetings

5 Expected Results Regarding the gamification process of Morschheuser and Hamari introduced in Sect. 2, this research is currently in phase 6 – Implementation. For completing this study, the survey on the success of the gamification approaches has to conducted and analyzed in order to evaluate the stated hypotheses. Many different studies in gamification already have proven a positive influence on motivation in different contexts. Thus, this research expects a confirmation of the Hypothesis H1 and H2. This will be measured by regular online surveys with the team members until the end of the semester. Also, it is mentioned that positive gamification has a higher influence on motivation compared to negative gamification. Therefore, this research expects a confirmation of H3. Hence, a difference between the gamified teams in the online surveys can be observed. As mentioned in different frameworks, positive gamification has a long-lasting effect on engagement while negative gamification creates urgency. Hence, as motivation might be high in both “gamified” teams, the quality of the delivered results might differ.

References 1. IDEEA. https://ideea.network/. Accessed 27 May 2020 2. Marczewski, A.: Gamification – A simple Introduction (2013). ISBN:1471798666 3. Gamification Summit 2011 (2011). http://gamification.de/2011/04/24/gamification-summit2011/. Accessed 27 May 2020 4. Ellenberger, T., Harder, D., Brechbühler Pešková, M.: Gamification in Unternehmen. In: Schellinger, J., Tokarski, K.O., Kissling-Näf, I.: Digitale Transformation und Unternehmensführung: Trends und Perspektiven für die Praxis, pp. 55–81. Springer Fachmedie, Wiesbaden (2020) 5. Reiners, T., Wood, L.C.: Gamification in Education and Business. Springer, Cham (2015). ISBN 978-3-319-10207-8 6. Hearts, Clubs, Diamonds and Spades – Player who suit MUDs, Richard Bartle. http://mud. co.uk/richard/hcds.htm/. Accessed 27 May 2020

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7. Morschheuser, B., Hamari, J., Werder, K., Abe, J.: How to gamify? A method for designing gamification. In: Proceedings of the 50th Hawaii International Conference on System Sciences (2017). https://doi.org/10.24251/HICSS.2017.155 8. Chou, Y.: Actionable Gamification. Octalysis Media, Milpitas (2016) 9. Bartle, R.: A Game Designer’s View of Gamification. http://aom.jku.at/archiv/cmc/text/ bartle.90/mud.co.uk/richard/GamificationSummit.pdf. Accessed 27 May 2020 10. GSummit SF 2012: Richard Bartle - A Game Designer’s View of Gamification. https:// www.youtube.com/watch?v=raj2SBU3PW4. Accessed 27 May 2020 11. Hamari, J., Tuunanen, J.: Player types. Meta-synthesis of player typologies. In: Proceedings of DiGRA Nordic 2012 Conference: Local and Global–Games in Culture and Society (2012)

Collaborative Learning Environments

Multimodal Access to Scientific Experiments Through the RIALE Platform - Main Steps of Bioinformatics Analysis Carole Salis1(&), Davide Zedda1, Federica Isidori2, Roberto Cusano1, Francesco Cabras1, Marie Florence Wilson1, Federico Cau3, and Lucio Davide Spano3 1

2

CRS4, Loc.Piscina Manna, Ed. 1, 09050 Pula (CA), Italy [email protected] Laboratorio di Genetica Medica, Policlinico S.Orsola-Malpighi, Bologna, Italy 3 Dipartimento di Informatica e Matematica, Università di Cagliari, Cagliari, Italy

Abstract. RIALE (Remote Intelligent Access to Lab Experiment) is a concept designed to supplement school science laboratories. Its multifunctional platform for innovative learning applications offers a multimodal approach of science. During Lab experiments Internet of Things (IoT) devices collect data, while an Artificial Intelligence (AI) tool is trained to recognize the tools, identify procedures and protocol phases, highlight the results of quantitative observations and tag collected data in a Timeline enriched with tagged additional educational contents (videos, external links, etc.). After remotely witnessing live the Lab experiment, students will access all educational contents from the platform to go deeper into single aspects of the experiment. A second AI tool will explore students’ approaches to learning, enabling us, in the long term, to obtain a userfriendly tool that will give information on students’ learning styles and help adapt teaching to their learning needs and styles. The first RIALE experiment deals with bioinformatics analysis. The educational scenario deals with exome sequencing and related scientific concepts (family tree, inheritance, genes…). Keywords: Artificial Intelligence labs
Scientific experiments


Next Generation Sequencing
Remote

1 Context The Center for advanced studies, research and development in Sardinia (CRS4) is an interdisciplinary Research Center with a research line on Educational Technology (EduTech). Their objective is to identify effective ways to integrate innovation in the school curriculum. EduTech’s latest project focuses on teachers wishing to use more effectively specific technologies in their teaching practice: the Innovazione Didattica E Apprendimento - IDEA project (i.e. Innovation, Didactics and Learning) [1]. IDEA developed a new concept and its related platform: the RIALE approach, designed to supplement traditional Lab activities, by offering students remote access to Research labs to view experiments that schools cannot offer. As Heradio et Al. say, “virtual, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 77–85, 2021. https://doi.org/10.1007/978-3-030-67209-6_9

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remote and hands-on labs are not exclusive alternatives, but valuable educational resources that can be combined in one integral and complementary learning unit” [2]. The experiment is video recorded live and processed to obtain a high resolution video. Procedures, instruments, quantitative observations data, etc. are tagged with an AI tool and put in a Timeline (TL) enriched with other educational objects (videos, texts, links, self-evaluation tests, etc. (see Fig. 1)), because we believe that visual and auditory strategies have a positive impact on knowledge [3]. The enriched TL is then uploaded on the RIALE Platform to be shared and reused by teachers, and to be accessed on demand by students who wish to deepen what was seen in the live session.

Fig. 1. Enriched timeline.

2 Objectives The RIALE approach wants to foster the understanding of complex scientific experimentations that cannot be addressed in schools Labs. The specificity of an experiment lies in its structure. The conditions in which the researcher operates influence the success of the step he is working on, and the possibility to go on to the next step. To understand how an experiment unfolds, students must be able to identify the variables involved in moving from one step to the next. The more innovative is the technology used in Labs, the more costly is the experimentation. This fact prevents students from becoming aware of new scientific approaches. Despite having scientific Labs, schools often lack the resources to meet reagents and maintenance costs. Digitizing the hardware components of a Lab is complex and costly. This is why we wish to promote remote access to real Labs and why, for the first RIALE experiment, we gave access to CRS4 NGS platform (next.crs4.it) to four scientific secondary schools classes.

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3 Motivation Since the 17th century, experimental research pioneers worked on observing and reproducing natural facts. Fact analysis lead to experimental practice and to scientific disciplines, focusing more on “why” than on “how”. Kalali traces the changes in secondary schools science programs and shows how since the 1970s simple instruments were introduced to engage students [4]. Experimentation have two complementary dimensions. 1) “the practical dimension with objects, phenomena, processes, procedures, socio-technical roles of scientific and technological activity; 2) the dimension of conceptual processing, models and theories”. They allow, “the development of critical thinking to cope with social, ethical problems related to scientific progress”. However, as Gruson mentioned [5], this progress undermines school science programme contents that cannot compete with scientific research using ever more sophisticated equipment. To bridge the gap, virtual online Labs are often used. They are important virtual resources for physics or chemistry, usually accompanied by tutorials. Developing tutorials scenarios require much energy and time (chemcollective. org, phet.colorado.edu or www.golabz.eu). Although they show action-reaction processes, they do not replicate the whole experience of a researcher using state of the art tools and implementing world-wide validated procedures: contingencies or measurement errors are not addressed. Yet, Lab operators need to resolve such situations. This important part of the learning process is lost in the over‐idealized virtual world. Video recording allows students to view the experiment but engages them passively. Bossewitch and Preston [6] explain the pedagogical interest of annotating videos when used to highlight recorded behaviors and technical gestures. Video editing using tools like Firefogg improves active engagement but the content still unfolds from A to Z. Additional data cannot concurrently be included, yet, they are critical to understand the true Lab flow. We might want to investigate simultaneously different measures (e.g. temperature and cell density) taken by a researcher manipulating a cell. With the RIALE platform, both measures can be acquired, uploaded and displayed synchronously on a single Timeline thus obtaining an interesting pedagogical tool.

4 RIALE Value Added and Strategy Some of the technologies used in the RIALE approach are listed below: 1. Video registrations of the experiment with low and high resolution cameras. The first to interact live with the researcher; the latter to show details of the procedures. 2. IDEA platform to acquire data from the experiment devices using IoT data channels. Data are linked to the specific phase of the experiment. IoT is also used to automate the video registration (cameras’ positions, movements, zooming etc.). 3. AI tools to tag key aspects of the experiment (procedures, tools, phases, quantitative observations, etc.) and to categorize students’ learning profiles and styles. 4. TeacherTube and YouTube can offer valuable videos. 5. Interactive online simulations related to the topic. 6. Additional learning objects annotated by the teacher on the Timeline.

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None is a novelty, but combining the different data flows, we obtain a dynamic tool in which users are free, thanks to the tags and the AI tool, to hop from one educational object to another (a new approach to complex scientific experiments). The RIALE platform, built on cloud SaaS infrastructures, leverages the scalability, reliability and power of serverless computing systems for fast and efficient setup of various experiments and their unconstrained remote distribution. Using a pay-per-use computing resource helps keeping the operating costs down, ensuring performance level. The Timeline, made with new generation responsive web-application, allows easy access to all resources and displays all acquired data at a glance. Users can for example, keep the focus on IoT telemetry and view the video capture synchronized with the incoming data on the system.

5 Hypothesis of Impact into Learning Procedure Tracking students’ navigation data will allow us to: collect the data needed to categorize the learning profiles; sketch and analyze navigation habits that best lead to a complete exploration of the Timeline (TL). We will also identify cases where students enact a single behavior (accessing videos only, go to the end of the procedure without viewing other phases of the experiment, etc.). This will help us guide teachers on how to empower the Timeline and improve the teaching of scientific experiments. Tracking the path followed by a single student is useful for instructional guidance as the teacher can quickly validate the strategies used by the student or redirect him/her toward suitable strategies [7]. Teachers might also consider rethinking their practice or Didactical design if a large number of students make inadequate use of the TL. For these reasons, an adequately fed Timeline enriched by the teacher with suitable educational resources, can become an innovative and strategic tool to promote the knowledge building necessary to understand a scientific Lab.

6 The AI Video Tagging Recognition and understanding video content is a challenge for many applications (monitoring, recommendation, personal assistance, question answering, smart homes and task video analysis). Many networks deal with image detection and image recognition, (Inception [8], MobileNetV2 [9]). When it comes to activity recognition in videos, we can cite learnable pooling with context gating [10], NeXtVLAD network architecture [11] and Cross-Class Relevance learning approach [12]. The AI tagging procedure has two steps: object detection and activity recognition. A first AI block identifies the equipment from the experiment video. The data is collected through camcorders registering the whole session; generating videos from which to extract the labeled images for model training. Then, images and their labels are fed to the MobileNetV2 network [9] to start the training phase for instrument detection and tracking. The second AI block consists in a model like [11] and [12], to recognize video segments corresponding to a specific experimental step. The recorded videos are leveraged to extract audio/video features to label each segment of the

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experiment in progress, which are the data used to train the AI. The two blocks work in parallel: one tags the objects of interest, the other tags the name of the procedure that is happening in the current experiment Timeline. During the training phase, to cut down on label assignment and location tracking of operators inside the Lab, inertial sensors will be attached to the instruments. The data collected by the sensors and a model of the sequence of tasks will give a first labeling iteration that will be reviewed to provide the ground truth for the final classification technique.

7 The 1st RIALE Experiment - Exome Sequencing Through NGS A real case was needed to refine the RIALE concepts. Since CRS4 hosts one of the largest NGS platforms in Italy, for the first RIALE experiment we chose the educational scenario of a family needing to investigate the genetic risk for a specific disease. This means identifying the genetic cause of a rare disease through DNA sequencing and addressing school curriculum educational contents (phases of DNA sequencing, concepts of genetic inheritance, alleles, genes, statistics, etc.). Since each run requires about €20,000.00 of reagents, it is a good example of lab activity that schools cannot afford and a perfect candidate for the RIALE approach. In Europe, a disease is defined “rare” when it affects less than 1/2000 people (www.orpha.net/) so, rare genetic diseases impact a significant slice of the world’s population. Now, technological advances, allow a better understanding of rare disorders [13]: NGS technology can sequence simultaneously thousands of millions of DNA molecules. Clinical diagnostics and research use it extensively [14]. Its capacity to generate huge amounts of sequencing data in a short time, at an affordable cost is leading to the discovery of a growing number of genes linked to inherited disorders and to the understanding of the molecular basis of complex diseases [15]. All NGS platforms for routine diagnostic applications use massively parallel sequencing of clonally amplified DNA molecules spatially separated in a flow cell. They generate hundreds of megabases to gigabases of nucleotide sequence output in a single run, based on the platform and the experiment [16]. Therefore, NGS is a powerful diagnostic tool that allows identification of disease associated variants [17]. Nowadays, three main NGS-based tests are used in rare disease research. They include: 1) parallel sequencing of coding sequences (exons) of groups of genes related by similar or overlapping phenotypes (gene panels); 2) Whole-Exome Sequencing (WES), in which all known coding regions of the human genome are sequenced; and 3) Whole-Genome Sequencing (WGS), which analyzes the entire human genome. In recent years, WES has become the test mostly used: it covers 1% of the human genome yet approximately 85% of the mutations causing diseases are found in these coding regions [18]. While exome sequencing is mainly performed on Illumina devices (NextSeq 550, HiSeq 2500 and HiSeq 3000), the preliminary library preparation can be done using various protocols. Nextera Flex (Illumina) for example, is a fast library preparation protocol with minimal hands-on time, and it works with small quantities of input DNA [19]. Nextera Flex protocol is based on enzymatic fragmentation of the DNA with trasposomes conjugated directly to beads and on exome capture using pools

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of biotinylated oligonucleotide probes specific for target regions [19]. The data gained from the exome sequencing, need to be analyzed, filtered and prioritized using computational and theoretical approaches which take into account the model of disease inheritance, the potential functional impact and relevance of variants. Since NGS technologies are a powerful tool to identify the causal variant(s) of a genetic disease, during the first RIALE experiment, we will simulate the diagnostic process to detect a pathogenic mutation, from DNA sequencing (WES), applied to 3 family members (parents and an affected child) till the main steps of bioinformatics analysis. During the live remote experimental session, students will witness once, from their classroom, the experiment carried out by the researcher. DNA sequencing is the process of determining the nucleic acid sequence of a DNA strand. This allows us to verify if the genetic sequence in the patient is “normal” (by comparison with a known human reference sequence representative of human genome without mutations) or if the analyzed gene carries a variant that causes the specific disease.

8 Characteristics of CRS4 NGS Core Laboratory CRS4 NGS Core facility is a modern Lab. sustaining high throughput, low cost, production-scale sequencing experiments, coupled with a data-intensive computational infrastructure that provides specialized capabilities for tracking all-data procedures and biodata provenance, managing complex analysis workflows and results. Our researchers have long experience with Illumina NGS technology in a broad range of applications including whole-genome, whole-exome and transcriptome sequencing, analysis of DNA binding sites, targeted resequencing. The laboratory is equipped with the most up-to-date Illumina sequencing technology (MiSeq, HiSeq 2500 and HiSeq 3000), a liquid handler for the management of large number of samples and all the instruments necessary for the quality control of biological samples.

9 What Do Teachers and Students Do After Live Remote Access? After the live session teachers will tag the main aspects of the recorded experiment with the AI tool, and to reinforce concepts, upload additional educational learning objects that give extra information on tools, reagents, procedures; as well as exercises, or students self-assessment tests. The end product is an enriched Timeline available on our platform to be shared and reused by other teachers. It will also be accessible to students on demand. Below a few examples of aspects of NGS procedure that teachers can tag and enrich with Additional Learning Objects (ALO). Tag 1: Introduction to NGS method. The ALO could be: 1) Glossary of terms used by the researcher; 2) Illustrated list of tools used, with explanation; 3) Nucleotide images; 4) DNA molecular structure videos; 5) IoT data from indoor positioning systems based on BLE Beacons to detect the use of Lab. instruments; 6) IoT data from indoor

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positioning systems based on Ultra Wide Broadband technology to track the researcher’s position in the Lab; 7) IoT data from thermocycler. Tag 2: Library preparation. The ALO could be: 1) Video explaining what a NGS library is (see Fig. 2); 2) Video on DNA fragmentation; 3) Link to scientific articles explaining NGS library fragmentation; 4) Data on DNA libraries from Bioanalyzer giving information on library quantification and fragment size information (fragment size - x-axis; concentration - y-axis); 5) IoT data from indoor positioning systems based on Bluetooth Low Energy (BLE) Beacons to detect laboratory instruments used; 6) IoT data from indoor positioning systems based on Ultra Wide Broadband technology to track the researcher’s position in the Lab.

Fig. 2. NGS library preparation, sample quality control

Tag 3: Issues from the sequencing data analysis. The ALO could be: 1) Link to Integrative Genomics Viewer (IGV) (igv.org/app) - a visualization tool for interactive exploration of genomic data; 2) IGV tutorial; 3) Reference file of Human genomic sequence; 4) ClinVar file (known genomic variations and its relationship to human health); 5) NGS sequencing data. At their own leisure students can access the platform through their computer or mobile device and choose to view the whole experiment or part of it. They can choose to go deeper into a specific aspect by exploring the additional educational objects etc. They can carry on the analysis of the data obtained through the IoT channels, check their self-understanding with evaluation tests the teacher may have uploaded before.

10 The Future As described in “Context”, RIALE is part of a larger project called IDEA. The latter involves the inclusion of platforms and the educational scenarios associated with them. We plan to develop a general purpose platform so that we can present different types of scientific experiments. The post-experimental analysis of the data collected will allow us to build both a model of development of multimodal resources and a crosspedagogical model that respect the multiple capabilities of RIALE.

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Acknowledgements. The authors gratefully acknowledge the “Servizio Istruzione of Direzione Generale della Pubblica Istruzione of Assessorato della Pubblica Istruzione, Beni Culturali, Informazione, Spettacolo e Sport of RAS” and “Sardegna Ricerche”.

References 1. Salis, C., Zedda, D., et al.: Teacher coaching program – the IDEA linea B3 project. In: 2nd International Conference on Advanced Research in Education, Diamond Scientific Pub., Paris (2019) 2. Heradio, R., de la Torre, L., Galan, D., Cabrerizo, F.J., et al.: Virtual and remote labs in education: a bibliometric analysis. Comput. Educ. 98(Issue C), 14–38 (2016) 3. Chen, G., Fu, X.: Effects of multimodal information on learning performance and judgment of learning. J. Educ. Comput. Res. 29(3), 349–362 (2003) 4. Kalali, F.: L’enseignement des Sciences expérimentales, ou le débat récurrent du culturel versus utilitaire: quels problèmes? SPIRALE - Revue des Recherches en Education 42, 183– 194 (2008) 5. Gruson, C.: L’expérimentation scientifique permet-elle le développement de l’esprit critique de l’élève? Education, Hal Id. dumas-00750748 (2012) 6. Bossewitch, J., Preston, M.D.: Teaching and learning with video annotations. In: Learning Through Digital Media Experiments in Technology and Pedagogy, vol. 19, pp. 175–184. The Institute for Distributed Creativity, R.T. Scholz Editor, New York, NY, USA (2011) 7. Van Der Maren, J.M., Salis, C., Gardina, M., Froissart, B.: Profil d’utilisation d’adjuvants didactiques en mode hypertexte par des étudiants universitaires, in: Apprendre à l’université “tête bien faite….tête bien pleine”. In: actes du congrès de l’Association Internationale de Pédagogie Universitaire, pp. 205–214. AIPU, Sainte-Foy, Laval, Canada (1992) 8. Szegedy, C., et al.: Going deeper with convolutions. In: 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, pp. 1–9 (2015) 9. Sandler, M., Howard, A., Zhu, M., Zhmoginov A., Chen, L.: MobileNetV2: inverted residuals and linear bottlenecks. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, Salt Lake City, UT, USA, pp. 4510–4520 (2018) 10. Miech, A., Laptev, I., Sivic, J.: Learnable pooling with Context Gating for video classification (2018). arXiv:1706.06905v2. Accessed 31 Mar 2020 11. Lin, R., Xiao, J., Fan, J.: NeXtVLAD: An Efficient Neural Network to Aggregate Framelevel Features for Large-scale Video Classification (2018). arXiv:1811.05014v1. Accessed 31 Mar 2020 12. Ma, J., Gorti, S.K., Volkovs, M., et al.: Cross-Class Relevance Learning for Temporal Concept Localization (2019). arXiv:1911.08548v1. Accessed 31 Mar 2020 13. Fernández-Marmiesse, A., Gouveia, S., et al.: NGS technologies as a turning point in rare disease research, diagnosis and treatment. Curr. Med. Chem. 25, 404–432 (2018) 14. Vrijenhoek, T., Kraaijeveld, K., Elferink, M., et al.: Next-generation sequencing based genome diagnostics across clinical genetics centers: implementation choices and their effects. Eur. J. Hum. Genet. 1142–1150. Nature Publishing Group (2015) 15. Coonrod, E.M., Durtschi, J.D., Margraf, R.L., et al.: Developing genome and exome sequencing for candidate gene identification in inherited disorders: an integrated technical and bioinformatics approach. Arch. Pathol. Lab. Med. 137, 415–433 (2013) 16. Voelkerding, K.V., Dames, S.A., Durtschi. J.D.: Next-generation sequencing: from basic research to diagnostics. Clin. Chem. 55, 641–658 (2009)

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17. Hardy, J., Singleton, A.: Genome wide association studies and human disease. N. Engl. J. Med. 360, 1759–1768 (2009) 18. Cooper, D.N., Krawczak, M., Antonorakis, S.E.: The nature and mechanisms of human gene mutation. In: The Metabolic and Molecular Bases of Inherited Disease, 7th edn., pp. 259– 291. McGraw-Hill Education, USA, (2019) 19. Bruinsma, S., Burgess, J., Schlingman, D.: Bead-linked transposomes enable a normalization-free workflow for NGS library preparation. BMC Genom. 19, 722 (2018)

New Approaches for Understanding Some Concepts from History Using Engineering Techniques Silviu Butnariu(&) Transilvania University from Brasov, 500036 Brasov, Romania [email protected]

Abstract. The concept of Blended Learning has emerged as a natural byproduct as a result of the development of the digital domain and which complements traditional methods in the real environment for various reasons. This learning method can be applied with different degrees of compatibility in the educational process. Even if some disciplines are better suited to these new methods, for example the technical ones, the question arises whether it is possible to use this concept in the humanities disciplines (literature, philosophy, history, psychology, etc.). The present paper aims to provide a new tool for increasing the visibility and accessibility to some components of the cultural heritage, especially to those artifacts that could not be kept in the original form but for which we have information and evidence regarding their characteristics and properties. This study is part of the author’s concerns to identify and to develop a methodology for the identification, evaluation, virtual reconstruction of artifacts, analysis and simulation of their functionality using new technologies and software engineering tools (3D reconstruction, new 3D visualization techniques, haptic systems, Finite Element Analysis, Multi Body Systems). Keywords: Blended learning


eHeritage
Engineering heritage

1 Introduction In 100% online learning activities, due to the lack of social interaction, some students need additional motivation to solve the imposed tasks. It is necessary to create a compromise between conventional face-to-face sessions and online learning. Some researchers in this field admit the reality of this concept only through the existence of real elements that will be intervened with the help of digital technologies. It is considered the identification of flexible activities that lead to the interaction between student and moderator not only accessing information through digital methods. An initial definition of blended learning included the need for an efficient combination of different teaching modes and learning styles. It was considered that the definition of this concept could be changed or there was ways for improvement [1]. Blended Learning is a combination of different teaching modes, teaching models and learning styles designed to streamline the transfer of knowledge between teacher © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 86–97, 2021. https://doi.org/10.1007/978-3-030-67209-6_10

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and student, using classical and modern teaching methods. This definition is more comprehensive, adding the dimensions of teaching and learning styles [1]. In the general sense, blended learning is a mixture of online and face-to-face learning. As digital and social media become more widespread in students’ lives, it was only a matter of time before learning became “mixed” with necessity. [2] According to current definitions, Blended Learning involves [2]: 1. Courses that integrate online with face-to-face activities 2. Courses that are taught both in the classroom (face-to-face) and at distance 3. Mixing or combining instructional technology with actual job task, in order to create a harmonious effect of learning and working 4. Combining computers with traditional teaching. It’s also referred to as reverse teaching, flip teaching, backwards classroom, or reverse instruction (Table 1) Table 1. Models of blended learnings [2, 3] Blended learning models Station rotation Lab rotation Remote (Enriched Virtual) Flex

Flipped classroom

Individual rotation A La Carte

Explanations

Similarity

Based on a fixed schedule, students can rotate through stations. At least one of the stations is an online learning station Students rotate through stations on a fixed schedule in a dedicated computer lab Students complete the majority of coursework online at home or outside of school, but attend school for required face-to-face learning sessions with a teacher Students move on fluid schedules among learning activities according to their needs. Online learning is the most important thing in this model This model flips the traditional relationship between class time and homework. Students learn at home via online coursework and lectures, and teachers use class time for teacher-guided practice or projects Students rotate through stations, but on individual schedules set by a teacher or software algorithm. Students take an online course with an online teacher of record _in addition_ to other face-toface courses, which often provides students with more flexibility over their schedules

Lab rotation

Station rotation A mix of self-directed, flex, flipped classroom

Remote, inside-out blended learning Remote blended learning

Mastery-based

In addition to the established models of blended learning, other sub-models have been identified, each with new and old features, some appearing following the technological evolution of recent years [3]. Various types have been proposed, as follows [2]:

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• Project-Based. The students use both online learning—either in the form of courses and face-to-face instruction and collaboration to design a project; • Self-Directed. This model is a combination of online and face-to-face learning, guiding the investigation of students, advised by the teacher; • Inside-Out/Out-side-In. Students design projects in non-academic physical and digital environments but complete them within a classroom; • Supplemental. Students complete either entirely online work to supplement their day-to-day face-to-face learning, or entirely face-to-face learning experiences to supplement the learning gained in online courses and activities; • Mastery-Based. The ability to use face-to-face and digital assessment tools is either powerful or complicated depending on the mindset of the learning designer. Analyzing the above, we can consider that the proposal in this article is within the description of this learning concept because: it uses face-to-face and online learning methods; presupposes the existence of real or very well described elements (artifacts); involves traditional analysis of artifacts; involves the use of new technologies to establish the physical/chemical/mechanical/functional characteristics of artifacts. Thus, I can say that my proposal falls into one of the Flipped Classroom or Remote (Virtual Enriched) types, having the characteristics of these typologies.

2 A Proposed Method for Blended Learning in History 2.1

History Discipline [4]

Some of the most important ideas presented in the Curriculum of the History discipline 11th grade, high school, in Romania have been detailed below. Two of the general competencies of the History discipline taught in the 11th grade of high school, aim at applying the appropriate principles and methods in approaching historical sources for information, documentation and research as well as using resources that support lifelong learning. As a result, the general and specific competencies that have to be formed through the teaching-learning process of the History discipline must be taken into account, among others, the following values and attitudes: • Consistency and rigor in thinking and action. • Critical and flexible thinking. • Training prospective thinking by understanding the role of history in the present life and as a factor in predicting change. From the point of view of the teaching methodology, we can see an interference of some well-established approaches at academic level, which promote an integrative, critical and self-reflexive knowledge but also a soft approach, “learning history through research”, learning strategy used more widely in non-formal educational contexts. These new elements encourages students to use a variety of sources, to use contemporary testimonies, to compile projects and to argue the approach used.

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Thus, the roles of the two partners of the educational process are rethought: what they have in mind: • for the teacher: facilitating learning, encouraging students to formulate personal points of view, collaborating with students in achieving the teaching approach; • for the student: cooperative learning, learning in formal and non-formal contexts, learning transfer. Assuming new roles involves didactic approaches based on learning through discovery, simulation, and analysis of historical sources, debate, role-play, and project. They have the advantage of allowing the alternation of forms of activity and favor the highlighting of the holistic dimension of learning. Previous learning experiences can thus be correlated with new learning [4]. The training of skills related to the analysis of historical sources is an important teaching objective because the value of sources for historical interpretation is very different, and the analysis tools of different sources are very diverse. The key concept that should be in the teacher’s attention is that of multiple perspectives, meaning “A way of thinking, selecting, examining and using evidence from different sources to clarify the complexity of a situation and to discover what is happened and why” [5]. A didactic approach focused on understanding multiple perspectives means helping students to practice ways of analyzing historical facts/processes in order to understand what has happened in the past and why. Critical thinking is considered a key factor in effective learning. The use of investigation as a didactic approach favors: the practice of intellectual work techniques and the method of learning through discovery, corroborating historical sources and their interpretation, cultivating the interest for research, learning the stages of designing a historical investigation. The stages of an investigative approach include identifying the topic, formulating questions related to the field of interest, establishing the objectives of the investigation, identifying sources of information, making a plan, collecting information/data, analyzing and processing information, presenting results. The integration of new information technologies in the teaching-learning process (including the Internet) is becoming essential in the conditions of multiplying the sources of information and communication [4]. 2.2

Scientific Context

The main meanings of the notion of heritage are (i) the evidence of the past, such as historical sites, buildings, and the unspoilt natural environment, considered collectively as the inheritance of present-day society or (ii) anything that has been transmitted from the past or handed down by tradition [6]. According to the definitions of [7], the notion of cultural heritage represents the inheritance of the physical artifacts and the intangible attributes of a group or society that are inherited from the past generations, currently maintained and given to the benefit of future generations. Objects are important for the study of human history, because they provide a concrete basis for ideas and can validate them. Their preservation demonstrates the recognition of the necessity of the past and of the things that tell its story. The preserved

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objects also validate the memories; and the actuality of the object, as opposed to a reproduction or a surrogate, attracts people and offers them a literal way to reach the past. Unfortunately, this is a danger, because places and things are damaged by the hands of tourists, the light needed to display them and other risks of making an object known and available. The passing of time, natural or human-made disasters, neglect, and inadequate conservation are the main reasons for the disappearance of cultural heritage. Lately, the protection and promotion of cultural heritage, in various forms (monuments, historical sites, artifacts, and cultural expressions) has become a central topic of European and international cultural policy. In the last decade, there have been concerns about the recovery of the intangible cultural heritage. However, there are also a number of elements of cultural heritage that have not been analyzed at the same level as the others, and here we refer to some artifacts that have not been kept in proper conditions or even at all.

3 Case Studies 3.1

Examples - Completed Case Studies Used so Far

The universal cultural heritage is composed, according to the specialized definitions, of tangible elements (buildings, artefacts, archaeological sites) and intangible elements (legends, traditions, dances, etc.). Between these two types of elements are the artifacts for which there is no tangible evidence but there is quality historical information in various forms. An example is the Dacian flag (wolf’s head). There are many representations of it on Trajan’s Column or references in the historical writings of the time (Arrianus), but there is no tangible artifact [8]. Therefore, it is very important to find a reconstruction method, in order to determine its shape and functionality. Of course, digital reconstruction is a much cheaper and faster variant, with spectacular results than real reconstruction. The proposed method will contain some very important steps: (i) identification and classification of the artifacts that can be analyzed with the proposed engineering techniques; (ii) identification of the visualization methods for each type of reconstructed artifact; (iii) identifying the types of analyzes and simulations to be performed on the virtual model; (iv) validation of the method. The method thus developed will be able to be implemented with minimum costs to the direct beneficiaries of this type of activity: museums, research centers in history, educational units of profile. A very large percentage of the research papers published in recent years focus on the digital reconstructions of some buildings, artifacts or archaeological sites. In order to develop this new proposed method with new characteristics of digital model so we can ask ourselves the following questions: 1. 3D virtual reconstruction it is enough to describe an artifact? 2. What kind of elements should be added to this approach in order to extend the information on it?

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3. How can we add the mass, structure, equilibrium of elements in the virtual environment? 4. What can be done with this new information to the geometric model? Can it demonstrate the functionality of the reconstructed objects, their characteristics? In carrying out the whole study, the main objective is to develop and making available to researchers new methods of study of artifacts. This objective can be achieved by creating a method of study that will contain elements of digital reconstruction, analysis, simulation, visualization of the digital model that will be made available to researchers for the study of special types of artifacts. However, there are some concerns in this direction internationally: digital reconstruction and simulation of the functioning of ancient musical instruments [9], identification of sounds from archaeological sites of sanctuary type [10], churches [11], use computer games (Serious Games) for presenting and learning history [12].

Fig. 1. Previous achievements (a) haptic bow; (b) Dacian Dracon – battle flag; (c) 3d interactive book with 3D representation; (d) 3D viewing system for ancient buildings.

In order to achieve this objective, there will be created databases with artifacts, classified according to certain rules that will be established during the development of the study. Depending on the classification, dedicated methodologies for analysis and simulation will be developed and proposals will be made regarding the equipment for viewing digital models that can be displayed in museums. The figures above are some examples that can be exposed, made in our research centre.

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As shown in the examples presented above (Fig. 1), which is part of the outputs of our work, the proposed study is perfectly feasible. The disparate components were realized within individual researches, following that in this study a generalization and structuring of the actions will be realized. The studied artifacts belong to several categories (constructions, tools, weapons, statues), so the objectives pursued were different. However, a common line of these studies is the additional amount of information that has been added to existing knowledge. The usefulness of some tools and the functional limitations of others [13], the confirmations or non-confirmations of some legendary facts [14], or the complex study of some elements (buildings, books, statues) in 3D virtual digital format [15, 16] could be demonstrated. Thus, the information received in the classes from the History discipline could become more detailed, more precise, bringing an extra scientific rigor and, at the same time, they became more attractive compared to the classic teaching/learning methods.

4 New Case Study – the Hypocaust Historical Data About the Hypocaust According the Oxford Classical Dictionary, the hypocaust (ὑpόjatrsom; hypocaustum) is a raised floor heated from below by a furnace (Fig. 2). Elementary types are found in some Hellenistic baths (Gortys in Arcadia; Gela in Sicily) but the fully developed system originated in central Italy and is already found in Pompeii (Stabian baths) and in private houses by the later 1st century [17].

Fig. 2. The hypocaust heating system

Interesting is the way of using this heating system used by the Romans, in areas with different climates, either in the central areas of the Empire or in the extreme areas, newly conquered. The Romans are recognized for their ingenuity, for the quality of their

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engineers and the skill of the workers. This system has been identified in many places, having the role of heating in cold areas: England [18, 19], Korea [20], or equipping public bathrooms or individual houses in warmer areas, Turkey [21]. Also, the hypocaust can work in reverse mode, respectively cooling the upper chamber during the hot season by ensuring a continuous flow of fresh air into the lower chamber [22, 23]. The structure of the underfloor heating system is used efficiently even today. The only thing changed is the heat source, being used pipes with thermal agent embedded in the floor. Hypocaust Function In the studies carried out on this type of construction, it was established that the flows and modes of heat transfer are performed as follows [24–27]: (i) by forced convection in the basement (the fire is positioned in one part of the room, and in the opposite parts there are the chimneys); (ii) conduction through the ceiling/floor; (iii) free convection in the upper chamber (Fig. 3).

Fig. 3. Heat transfer in a hypocaust

Speaking of the hypocaust, depending on the areas where they were built, the materials used are diverse, but the aim was to comply with certain technical characteristics: thermal insulation material for walls, conductive material for the floor, material with high heat retention characteristics [28, 29]. Some researchers have raised the issue of heat transfer but also the consumption of wood fuel, reaching remarkable results on the quantities of wood used for heating [29–31]. Study of Thermal Transfer Using Finite Element Analysis In order to visualize the operation and demonstrate the technical characteristics of the hypocaust, analyzes based on the Finite Element Method were performed using ANSYS software (https://www.ansys.com/). Fluid Flow (Fluent) module were used to determine heat transfers based on free or forced convection, as well as Steady-State Thermal for heat transfer through conduction.

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Fig. 4. Geometric model of the studied hypocaust

A simple geometric model was created, with a combustion chamber and a heated chamber above, a furnace and a chimney, as well as a single pillar (Fig. 4). The analysis consisted in simulating a heating process, creating a high temperature point (100 °C) at the entrance to the combustion chamber and creating a flow of hot air with a speed of about 5 m/s, having the exit from the combustion chamber on the opposite wall., to the chimneys. The aim was to identify the heat fluxes in the combustion chamber, as well as the heating modes of the floor and the upper chamber.

Fig. 5. Temperature flow in underfloor chamber (a) and heat distribution in the floor (b)

Using the Fluid Flow (Fluent) module, data were obtained on the hot air circuit in the combustion chamber as well as details on the influence of the chamber geometry, the number and the positioning of the pilars, the positioning of the chimney (Fig. 5). It was possible to obtain suggestive images but also animations, which are much more conclusive, being able to simulate with modified input data. Using the Steady-State Thermal module, it is possible to follow the temperature variation on the entire floor thickness, the analysis taking into account the material and its thermal and mechanical properties (Fig. 6a). Simulations can be made with different materials or with different layers of different material.

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The distribution of temperatures in the upper room, based on the phenomenon of free convection, having as heat source the floor, can be observed in Fig. 6b.

Fig. 6. Heat transfer by conduction in floor (a) and the temperature gradient in the upper chamber due to free convection (b)

All these analyzes can be followed in the form of captures of images or animated films, with the possibility of modifying the initial data: construction geometry, materials used, temperature and speed of air flow, floor thickness, etc. Students have the opportunity to modify all this data according to the historical data which they have and which require the existence of local architectures and materials.

5 Conclusions This paper presents a new methodology for studying artifacts, in order to discover some qualities and characteristics that we could not observe otherwise. The proposed procedure adds value to the classical classes held in the History discipline. Within the Blended Learning methods, a place has been identified where this procedure fits well. To reinforce what has been explained theoretically, a custom case study will be presented. We agreed in chapter 1 the types of Blended Learning that can be applied to the classes in the History discipline, respectively Flipped Classroom or Remote types. In order to carry out these hours, it is necessary to respect a plan for carrying out the activities, as well as the presence of an engineering specialist who can make the necessary simulations. The plan involves the following steps, respecting the requirements of the types of Blended Learning mentioned: 1. Positioning the problem to be studied in the temporal and technical framework of the History discipline (responsible - history teacher), the activity carried out either classically or online. 2. Students receive for individual study a research topic on an artifact, weapon, installation, equipment (responsible - students), activity carried out at home. 3. Free discussions student - history teacher regarding the need to exemplify a certain phenomenon through digital simulations (responsible - history teacher). 4. Preparation of the simulation (specialist engineer)

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5. Demonstration - virtual simulation (responsible - specialist engineer), online activity. Here is the need for another teacher, an engineer by profession, who will help the tenured history teacher. The main challenge is to identify, classify, and create new procedures and instructions for the use of technologies in mechanical engineering and Virtual Reality, in order to use them for the detailed study of artifacts. The proposed theme comes with an innovative idea, which adds value to the 3D models of the artifacts: physical and mechanical characteristics, mode of operation and use, simulation and analysis of phenomena. These issues were rarely discussed in the articles in the specialized journals. The use of this procedure in history classes requires some specialized knowledge from teachers but dedicated, simplified modules can be made, which do not require high-level engineering skills.

References 1. Heinze, A., Procter, C.: Reflections on the use of blended learning. In: Extract from: Education in a Changing Environment 13th–14th September 2004, Conference Proceedings (2004). http://usir.salford.ac.uk/1658/ 2. Of The Most Common Types Of Blended Learning, by TeachThought Staff, 21 June 2019, in Learning. https://www.teachthought.com/learning/12-types-of-blended-learning/. Accessed 24 May 2020 3. Blended Learning Models. https://www.blendedlearning.org/models/. Accessed 24 May 2020 4. School Program for History, 11th grade, High School, Ministry of Education, Re-search and Innovation from Romania, http://oldsite.edu.ro/index.php/articles/12814. Accessed 25 May 2020 5. Stradling, R.: Teaching 20th-century European History, vol. 257, Collection Education, Council of Europe, ISBN 9287144664 (2001) 6. Collins Dictionary: Definition of Heritage. https://www.collinsdictionary.com/dictionary/ english/heritage. Accessed 10 May 2020 7. UNESCO: Tangible Cultural Heritage. http://www.unesco.org/new/en/cairo/culture/tangiblecultural-heritage/. Accessed 10 May 2020 8. Wheeler, E.L.: The Occasion of Arrian’s Tactica. Duke University, Durham (1978) 9. Avanzini, F., et al.: Archaeology and virtual acoustics. A pan flute from ancient Egypt. In: Proceedings of the 12th International Conference on Sound and Music Computing (SMC-15), Maynooth, Ireland, 30, 31 July (2015) 10. Till, R.: Songs of the stones: the acoustics of Stonehenge. In: Banfield, S. (ed.) The Sounds of Stonehenge, pp. 17–39. Archaeopress, Oxford (2009) 11. Suárez, R., Alonso, A., Sendra, J.J.: Archaeoacoustics of intangible cultural heritage: the sound of the Maior Ecclesia of Cluny. J. Cult. Heritag. 19, 567–572 (2016). ISSN 12962074 12. Mortara, M., et al.: ReviewLearning cultural heritage by serious games. J. Cult. Heritag. 15, 318–325 (2014)

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13. Butnariu, S., Duguleana, M., Brondi, R., Gîrbacia, F., Postelnicu, C.C., Carrozzino, M.: An interactive haptic system for experiencing traditional archery. Acta Polytech. Hung. 2018 (15), 185–208 (2018) 14. Butnariu, S.: Engineering eHeritage—A New Approach for Study of Intangible Cultural Heritage. Case Study: The Analysis of the Noise Produced by the Dacian Dracon. Sustainability 2019 11, 2226 (2019) 15. Duguleană, M., Postelnicu, C.: Towards preserving Transylvanian fortified churches. In: Proceeding of VRTCH 2018, 1st International Conference on VR Technologies in Cultural Heritage, Brasov (Romania), 29–30 May 2018 (2018) 16. Lorenzini, C., Evangelista, C., Carrozzino, M., Postelnicu, C., Maltese, M.: An interactive digital storytelling approach to explore books in virtual environments. Informatica 40, 317– 321 (2016). Special Issue: Virtual Reality in Cultural Heritage (ISSN 0350-5596) 17. DeLaine, J.: Hypocaust, Oxford Classical Dictionary, Roman Material Culture, December 2015. https://oxfordre.com/classics/view/10.1093/acrefore/9780199381135.001.0001/acrefore-97801 99381135-e-3202. Accessed 10 May 2020 18. Roman Central Heating. https://www.romanobritain.org/12_innovations/inv_central_ heating.php. Accessed 29 May 2020 19. Black, E.W.: Hypocaust heating in domestic rooms in Roman Britain. Oxford J. Archaeol. 4 (1), 77–92 (1985). https://doi.org/10.1111/j.1468-0092.1985.tb00232.x 20. Cowan, H.J.: A note on the Roman Hypocaust, the Korean On-dol, and the Chinese Kang. Arch. Sci. Rev. 30(4), 123–127 (1987). https://doi.org/10.1080/00038628.1987.9696614 21. Disli, G., Celik, N.: Heating system evaluation of an ancient turkish bath: the bath of suleymaniye hospital. In: Papers presented to the 12th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Costa de Sol, Spain on 11–13 July 2016 (2016). http://hdl.handle.net/2263/61834 22. Bansal, N.K.: India: characteristic parameters of a hypocaust construction. Build. Environ. 34(3), 305–318 (1998). https://doi.org/10.1016/s0360-1323(98)00018-3 23. Bansal, N.K., Bhandari, M.S.: Evaluation of hypocaust heating of buildings. Int. J. Ambient Energy 20(2), 67–78 (1999).. https://doi.org/10.1080/01430750.1999.9675321 24. Lehar, H.: The Roman hypocaust heating system. In: Calculations and Thoughts About Construction, Performance and Function, Proceedings of the 17th International Conference on Cultural Heritage and New Technologies 2012 (2012) 25. Gagliano, A., Liuzzo, M., Margani, G., Pettinato, W.: Thermohygrometric behaviour of Roman thermal buildings: the “Indirizzo” Baths of Catania (Sicily). Energy Build. (2016). https://doi.org/10.1016/j.enbuild.2016.12.011 26. Oetelaar, T., Johnston, C., Wood, D., Hughes, L., Humphrey, J.: A computational investigation of a room heated by subcutaneous convection—a case study of a replica Roman bath. Energy Build. 63, 59–66 (2013). https://doi.org/10.1016/j.enbuild.2013.03.049 27. Heinz, W.: An engineer studies heating systems in baths. Hans-Christian Grassmann, die funktion von hypokausten und tubuli in antiken römischen bauten, insbesondere in thermen. erklärungen und berechnungen. J. Roman Archaeol. 26, 721–722 (2013). https://doi.org/10. 1017/s1047759413000652 28. Kroos, K.A.: Central heating for caligula’s pleasure ship. Int. J. Hist. Eng. Technol. 81(2), 291–299 (2011). https://doi.org/10.1179/175812111x13033852943471 29. Douglas, J.: The development of ground floor constructions: part 7 (underfloor heating). Struct. Surv. 17(2), 74–81 (1999). https://doi.org/10.1108/02630809910273730 30. Basaran, T., Ilken, Z.: Thermal analysis of the heating system of the Small Bath in ancient Phaselis. Energy Build. 27(1), 1–11 (1998). https://doi.org/10.1016/s0378-7788(97)00013-3 31. Rook, T.: Problems in Estimating Fuels Consumed in Buildings: Fuel Requirements of Hypocausted Baths. (2019). https://doi.org/10.17863/CAM.46329

Work in Progress: “Embedding Graduate Skills in Online Courses” Swapneel Thite1(&) , Jayashri Ravishankar1, Eliathamby Ambikairajah1, and Araceli Martinez Ortiz2 1

The University of New South Wales, Sydney, Australia [email protected] 2 Texas State University, Texas, USA

Abstract. In the age of digital revolution, technology plays a vital role in transforming education practices. Online courses are gaining a lot of attention and demand in recent times as universities try to manage resources and cope with increasing number of student enrolments. In this study, an existing electrical safety course comprising of various activities like Virtual Reality, Case Study Presentations and having face to face (f2f) collaborative lectures was converted to be offered completely online. Team activity like case study presentations enhance student’s teamwork, leadership and communication skills which are extremely important for the industry. Safety at workplace is taken very seriously in Australia and this knowledge is widely required in most industries. With a fore sight of offering this course as a training module in the industry, efforts were made to convert this course online. An evidence-based approach was taken to develop various online teaching methods validated by learning theories. Several challenges were faced while incorporating existing teamwork activities and building an online community. COVID 19 helped test the efficacy of these strategies on learning outcomes of the students that were overseas. Keywords: Online courses Teamwork skills


Online learning theories
Graduate skills


1 Introduction 1.1

Literature Review

Engineering education is under tremendous pressure from the evolving Industry 4.0 to transform its teaching methods during the prevalent technological revolution. Education 4.0 is the buzzword for this futuristic way of teaching and learning which requires graduates to possess self-regulated learning, critical thinking and collaborative and teamwork skills supported by digital expertise to perform at the highest level to meet demands of Industry 4.0 [1, 2]. COVID 19 has further triggered this push towards online education [3]. The goal of any educational institution is to prepare employable graduates that possess technical as well as professional skills. However, research suggests there exists a skill gap between university students and fresh graduates in the industry [4]. A recent © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 98–105, 2021. https://doi.org/10.1007/978-3-030-67209-6_11

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study by Christine [5], discusses methods to bridge this gap. Junaid’s study mentions KSAVE framework created by top companies in the industry that predicts the top five most important skillset required for electrical and computer engineers for the next decade that includes innovation, critical thinking, metacognition, teamwork, collaboration and communication skills [6]. Teamwork and communication skills are currently highly valued by industry professionals all over the world [7]. Online learning has been proven to be as effective as classroom teaching in terms of student performance [8]. Online courses have the power to cross geographical barriers and reach students all over the globe, incorporate large student enrolments and provide flexibility. However, a complete shift to online courses opens a new set of challenges to maintain the quality of education, student engagement and develop teamwork skills [9]. This leads into the research problem investigated in this study on how to embed graduate skills in an online course. The goal of this study is to embed the graduate skills such as teamwork, leadership, and communication in an online environment, using efficient online teaching methods which are validated by learning theories. This paper discusses strategies implemented in an online course to boost these graduate attributes.

2 Electrical Safety Course 2.1

Background

The course under consideration is an elective course called Electrical Safety. It usually has large enrollments up to 200 students. Traditionally, run as face-to-face (f2f), in 2019, there were regular topical one-hour lectures followed by two-hours of f2f collaborative teamwork session led by student mentors. This course has a strong presence of industry partners. Teaching techniques and assessments included in prior offerings were web-based virtual reality (VR) simulations, Case study presentation (CSP), tutorial, formative quizzes, oral Q&A, teamwork assessment and a written final exam. 2.2

Course Plan 2020

This course is run completely online in 2020 and all the activities were redesigned to suit an online model. The current course is structured into seven modules as shown in Table 1. Each module has its own VR simulation and a follow up VR quiz. The modules 1,2 and 3 comprise of the core mandatory topics and the rest 4 modules are electives. Students have the option of choosing any 2 out of the 4 electives. The course commenced in June 2020 and closes in the first week of August. One-hour overview online lecture in is run by the lecturer followed by one hour of online collaborative team work session run by mentors in Microsoft teams every week.

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Elective modules Choose two from the below list Module M1: Electricity & Human body Module E1: Power line safety Module M2: Earthing Module E2: Emerging energy sources Module M3: Hazardous area Module E3: Safety against OV, ELV, RV – Module E4: Electrical safety in hospitals

3 Community of Inquiry Framework Redesigning any course and shifting it into an online environment needs to be based on strong foundations of learning theories [10]. Selection of learning theory is based on the learning outcomes of the course. Teamwork, leadership, and communication skills are targeted graduate attributes of this course. Furthermore, learner engagement is extremely crucial in any successful online course [11]. The most popular and effective online learning model in literature that targets the above attributes and engagement is the constructivist theory-based Community of Inquiry framework (COI) [12]. Heilporn tested this framework and found high internal consistencies between the three main factors of cognitive, social, and teaching presence, which reinforces the fact that this structure is reliable [13]. This framework was created in the 2003 by Garrison, D. Erson and T.Archer, Walter [14] which aims to create meaningful educational learning experience. Cognitive presence reflects the ability of an educational setting to construct meaning through sustained communication. Social presence is signified by the ability of students to project their personal characteristics in the framework. Teaching presence has a twofold function 1. Design and development of learning activities and assessment. Primary presentation, selection and organization of the course content. 2. Bearing responsibility of teaching and sharing the load among other mentors. Accommodating these three components, cognitive, social and teaching presence, gives rise to a community of inquiry in the course [12]. Holly’s review paper suggested recommendations for all three aspects of this framework [12]. Based on these guidelines, we executed the following to ensure the framework is successfully implemented: 1. Course Discussion forum was setup for general questions, Q&A section and CSP Q&A. 2. Teams have their private channel on Microsoft Teams to interact and work collaboratively throughout the CSP project cycle. 3. Teaching presence is maintained regularly via synchronous lectures, course discussions and collaborative sessions run on Microsoft Teams by the mentors. 4. Mentors based overseas were selected to cater for students all over the world living in different time zones. The synchronous sessions could then be completed without inconvenience to either mentors or students. 5. Regular specific feedbacks are provided to the groups and students based on their performance.

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6. Team activities involve ice breakers, mini games, brainstorming, reflection, and integration required for the final CSP submission. 7. Additionally, student shall be mandated to ask minimum three questions on any three other CSP submissions and answer three questions on their video submission. This activity shall count towards successful completion of the CSP and shall boost student online engagement.

4 Teamwork Training Modules Incorporating teamwork activities in large online courses pose a lot of challenges. Group sizes impact the level of learning throughout the activity. Larger groups lead to lower quality of learning [18]. However, lower group sizes increase the number of groups and hence the need for increased teaching assistance. The team of teaching assistance requires training and needs to be trained to ensure students are getting consistent advice [19]. The implemented module addresses the above challenges. Literature on teamwork has documented various successful teaching methodologies that support development of teamwork skills like Project Based Learning, Team Based Learning and gamification [15]. While these were initially meant for f2f classes, online implementation has been piloted with decent results. The general approach in the above techniques is that students understand teamwork by carrying out a team project. However, students tend to divide tasks instead of collaborating and use trial and error to find what works best for the team [16]. Therefore, a more direct approach to teamwork training like experiential training modules is a better option where course structure has flexibility to achieve learning outcomes combining technical and teamwork concepts in one project [17]. 4.1

Implemented Modules

The teamwork component in the course is case study presentation which accounts for 30% of the course mark. Each team picks a real-life electrical safety incident and prepares a presentation on their analysis and solutions to the neglected electrical safety issue. Instead of running a live f2f presentation for the peers and the industry guest, implemented asynchronous version requires teams to submit a presentation video on Moodle which shall be assessed by the industry guests. Teams of five were created on Microsoft teams considering geographical time differences. Every team has a mentor assigned to them. With a total of six mentors in the course, each mentor has 30 students (i.e., 6 teams) under their supervision. In the first lecture, a brief introduction was given on why teamwork is important and how the collaborative activities will be run throughout the course. A short survey was conducted on the first lecture aiming to find the initial understanding of teamwork that students possess. The same survey will be run at the last lecture to check the difference in understanding [18]. Training modules for eight weeks of the course were created based on reliable experiential models conducted in literature [16, 17]. The framework by Lydia on proactively ensuring teams success (PETS), was used as the basis for our model [19]. Each group has a

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synchronous collaborative session run with the mentors where every group would carry out the activities and discussions included in the leaflet provided to them prior to class. Each week along with technical queries and discussions, a new concept of teamwork is explored which shall be accompanied by a small activity. Leaders are assigned to the marked weeks 3–7 such that all students get an opportunity to lead. Their responsibilities include checking on progress with team members, checking if the project is on track, encouraging team members to achieve and push for weekly milestones, holding members accountable for their roles, formulating milestones for the following week, and submitting a summary of reflection of main takeaways of the collaborative session. A sample leaflet is shown in Fig. 1.

Fig. 1. Sample leaflet

Mentors role in these teamwork activities is crucial for its success [20]. Students who had completed the course and those who had already mentored in previous offerings were chosen. Equity and diversity were ensured with an equal balance of male and female mentors. A special training session was run for the mentors before the start of the classes in the first week to explain mentor responsibilities and instructions on how to conduct the collaborative sessions. To ensure fidelity, all the mentors catch up every week for half an hour discussing progress, response and challenges faced with their teams. These mentor meetings are ensuring a consistent method of guidance and training across all groups. The teamwork plan for the 8 weeks is as shown in Table 2.

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Table 2. Teamwork plan Period Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8

4.2

Teamwork plan Introductions & Overview Concept plan & Role Assignments Leadership (Marked) Communication (Marked) Accountability & Trust (Marked) Conflict management (Marked) Application of teamwork and performing (Marked) Reflections

Teamwork Assessment Rubric

An assessment method created by the American association of colleges and universities called “VALUE” was based to create the UNSW Teamwork skills development framework shown in Fig. 2 [21, 22]. It has six criteria and four levels of performance:

Fig. 2. UNSW teamwork skill marking rubric [21, 22]

Students are individually marked with this rubric from week 3 to week 7. A marking method produced by peerassesspro will be utilized to calculate the student’s normalized personalized result [23]. The rubric translates to the following steps: – Each team gets a mark for the video submission which is the team result (TR) – Each student gets individually marked from weeks 3–7 based on the VALUE rubric. There are six criteria each comprising of maximum four marks based on the four levels of the VALUE rubric. This accounts to maximum 24 marks per student per week.

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– Sum up all five weeks and convert to 100. This is the Team Based Learning Index (TBLI). – Indexed Personal Result, IPR = TR  TBLI (max 100) – Take average IPR for the team. This is called AIPR. – The final step is to obtain the Normalized Personal Result, NPR = TR + (IPR – AIPR). This NPR shall be then converted to 20% and the rest of the 10% is assigned to an individual oral examination, which shall be conducted in week 9 and 10 run by the mentors based on the questions received from the industry guests and the course content. This assessment method was briefed to the students in the first introductory class. Team marks affect the marks of the individual student and shall promote peer motivation and support.

5 Expected Outcomes The structured teamwork training model is being piloted in the current term. COI framework is being implemented by the team of mentors and the lecturer. The above implementation is expected to boost teamwork, leadership and communication skills required for industrial experience, improve student engagement and performance of students, and reflect high student satisfaction rates for the online course. The term runs until the middle of August 2020 and results of this implementation will be available after this time.

6 Conclusion An existing f2f course was re-designed to be offered completely online. This online offering is modeled on the online learning theory-Community of Inquiry framework. An experiential module-based teamwork training was run in conjunction with the case study activity of the course. A combination of synchronous collaboration sessions and asynchronous assessment methods are being used to run the proposed teamwork model to potentially enhance teamwork, leadership, and communication skills in the course effectively improving graduate employability.

References 1. Lea, Q.T.: Orientation for an education 4.0: a new vision for future education in Vietnam (2020) 2. Hussin, A.A.: Education 4.0 made simple: ideas for teaching. Int. J. Educ. Literacy Stud. 6, 92–98 (2018) 3. Verawardina, U., Asnur, L., Lubis, A.L., Hendriyani, Y., Ramadhani, D., Dewi, I.P., Darni, R., Betri, T.J., Susanti, W., Sriwahyuni, T.: Reviewing online learning facing the Covid-19 outbreak. J. Talent Dev. Excellence 12, 385–392 (2020)

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4. Singh, M., Sharma, M.: Bridging the skills gap: strategies and solutions. IUP J. Soft Skills 8, 27 (2014) 5. Winberg, C., Bramhall, M., Greenfield, D., Johnson, P., Rowlett, P., Lewis, O., Waldock, J., Wolff, K.: Developing employability in engineering education: a systematic review of the literature. Eur. J. Eng. Educ. 45, 165–180 (2020) 6. Qadir, J., Yau, K.-L.A., Imran, M.A., Al-Fuqaha, A.: Engineering education, moving into 2020s: essential competencies for effective 21st century electrical and computer engineers (2020) 7. Pham, T., Saito, E.: Teaching towards graduate attributes. Innovate Higher Education to Enhance Graduate Employability: Rethinking the Possibilities, p. 109. (2019) 8. LaMeres, B.J., Plumb, C.: Comparing online to face-to-face delivery of undergraduate digital circuits content. IEEE Trans. Educ. 57, 99–106 (2013) 9. Stone, C.: Online learning in Australian higher education: opportunities, challenges and transformations. Student Success 10, 1 (2019) 10. Fasihuddin, H.A., Skinner, G.D., Athauda, R.I.: Boosting the opportunities of open learning (MOOCs) through learning theories. GSTF J. Comput. (JoC) 3, 1–6 (2013) 11. Brieger, E., Arghode, V., McLean, G.: Connecting theory and practice: reviewing six learning theories to inform online instruction. Eur. J. Train. Dev. (2020) 12. Fiock, H.: Designing a community of inquiry in online courses. Int. Rev. Res. Open Distrib. Learn. 21, 134–152 (2020) 13. Heilporn, G., Lakhal, S.: Investigating the reliability and validity of the community of inquiry framework: an analysis of categories within each presence. Comput. Educ. 145, 103712 (2020) 14. Garrison, D., Erson, T., Archer, W.: A theory of critical inquiry in online distance education. Handb. Distance Educ. 1, 113–127 (2003) 15. Hrynchak, P., Batty, H.: The educational theory basis of team-based learning. Med. Teach. 34, 796–801 (2012) 16. Hurst, A., Jobidon, E., Prier, A., Khaniyev, T., Rennick, C., Al-Hammoud, R., Hulls, C., Grove, J., Mohamed, S., Johnson, S.: Towards a multidisciplinary teamwork training series for undergraduate engineering students: development and assessment of two first-year workshops. Proc. Am. Assoc. Eng. Educ. (ASEE), 18 (Year) 17. Al-Hammoud, R., Hurst, A., Prier, A., Mostafapour, M., Rennick, C., Hulls, C., Jobidon, E., Li, E., Grove, J., Bedi, S.: Teamwork for engineering students: Improving skills through experiential teaching modules. Proc. Can. Eng. Educ. Assoc. (CEEA) (2017) 18. Kavanagh, L.: Instructor’s Manual: Proactively Ensuring Team Success (PETS Process). The University of Queensland, Australia (2018) 19. Kavanagh, L., Steer, J.: A process for proactively ensuring student team success: perceptions of students and lecturers. In: 17th Annual Conference, Australasian Association for Engineering Education, Melbourne, Australia. (Year) 20. Iacob, C., Faily, S.: The impact of undergraduate mentorship on student satisfaction and engagement, teamwork performance, and team dysfunction in a software engineering group project. In: Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Portland, OR, USA, pp. 128–134. Association for Computing Machinery (2020) 21. McConnell, K.D., Horan, E.M., Zimmerman, B., Rhodes, T.L.: We Have a Rubric for That: The Value Approach to Assessment. ERIC (2019) 22. Association of American Colleges and Universities (AAAC). https://www.aacu.org/sites/ default/files/files/VALUE/Teamwork.pdf 23. Peer Assess Pro. https://www.peerassesspro.com/individual-grade-determination/#

Genetic Algorithms to Generate Data for a Social Learning Recommendation Approach Sonia Souabi(&), Asmaâ Retbi, Mohammed Khalidi Idrissi, and Samir Bennani RIME TEAM-Networking, Modeling and E-Learning Team- MASI Laboratory- ENGINEERING.3S Research Center, Mohammadia School of Engineers (EMI), Mohammed V University, Rabat, Morocco [email protected], {retbi,khalidi,sbennani}@emi.ac.ma

Abstract. The genetic algorithm is regarded as one of the foremost evolutionary algorithms, especially in optimization problems. In addition to optimization problems, genetic algorithms can contribute to solving other problems. In the context of social learning, particularly recommendation systems, researchers are usually faced with a problem of lack of data when testing their approaches. This is where the genetic algorithm can intervene to generate additional simulation data from an already existing database. In this article, we will outline how we can apply the genetic algorithm to address the lack of data, particularly in our context of recommendation systems within social learning. Keywords: Genetic algorithms


Social learning
Recommendation system

1 Introduction Nowadays, distance learning has enabled learners to acquire a wealth of online knowledge without the necessity to go anywhere. Given the significant value of elearning in education, researchers are increasingly turning their attention to this field and are carrying out studies to analyze the performance of distance learning [1–3]. However, in order to perform these studies, data are required for the reliability of the study. It is in this respect that the problem arises. Lack of data in the field of distance learning, particularly social learning, can pose major difficulties, above all with regard to recommendation systems. Many researchers have relied on MovieLens databases for the sole reason that learning data were not available [4]. When it is deemed necessary to evaluate a recommendation approach at the learning level, for example, it is important to have the appropriate data to perform this evaluation and to show the performance of the recommendation system. Our work is a further extension of our proposed social learning recommendation system and proposes genetic algorithms to solve the problem of missing data. In the literature, genetic algorithms have been extensively used in optimization problems, particularly in several areas. These algorithms have been found to solve several problems, including maximization and © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 106–113, 2021. https://doi.org/10.1007/978-3-030-67209-6_12

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minimization. In our context, we intend to explore the use of genetic algorithms not for optimization, but to generate additional data from existing data. Based on some real learning data, we can generate additional simulation data by applying the different steps of the genetic algorithms. In case the data are limited, we can thus expand our database to test our recommendation approach and make the tests performed more reliable. Our paper is structured as follows: in the first part, we will introduce genetic algorithms and their steps as well as their applications in e-learning. In the second part, we will apply the genetic algorithms in our context and present the results and the ensuing discussion of the results. Finally, in the last part, we will report the conclusion of the work.

2 Background 2.1

Genetic Algorithms

Genetic algorithms are part of evolutionary algorithms. The purpose of their exploitation is to obtain approximate solutions to optimization problems, especially when there are no exact solutions or when the solution does not already exist. Thus, the genetic algorithm goes through several steps that are deemed crucial for its correct functioning [5]. Selection. This step consists of selecting the optimal individuals likely to give the best results during reproduction. Candidates are selected based on their fitness function according to the weighted wheel [6]. Crossover. The second step is to generate new individuals from the individuals selected in the first stage of selection. Each cross is made from each pair of individuals. The genes of the children created are produced from the genes of the parents, and those produced by using recombination to form the new chromosomes [7]. Mutation. This last step consists in mutating the values, i.e. transforming 0 into 1 or 1 into 0 [8]. As we noticed, the genetic algorithm goes through several steps that can be summarized as selection, crossing and mutation. It is important to note that a stopping criterion must be defined, such as the execution time or the number of iterations. 2.2

Genetic Algorithms in E-Learning and Recommendation Systems

In addition to several application areas, e-learning and recommendation systems are considered very prominent areas for application of genetic algorithms. Table 2 illustrates some work carried out in terms of e-learning and recommendation systems.

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Paper [9]

[10]

[11] [12]

Overview This study deals with an important problem, which is the scheduling of classes. Genetic algorithms are thus considered in order to solve the problem of presentation of the course timetable This paper provides a state of the art on the use of evolutionary algorithms in distance learning. The study also shows the relevance of genetic algorithms in the personalization of the learning path This paper proposes the evaluation of genetic algorithms in the construction of a learning path that is optimal and beneficial for learners This study allows the usage of genetic algorithms to generate an optimal path through the identification of the level of difficulty of online courses and the courses that correspond to the learners’ needs

Table 2. Initial data related to two events performed by learners. Learners [A1, A2, A3, A4, A5, A6, A7, A8, A9, A10]

Data [(6, 4), (3, 4), (6, 3), (5, 5), (3, 6), (4, 3), (2, 0), (1, 1), (6, 1), (5, 4)]

3 Genetic Algorithms Implementation 3.1

The Developed Approach

As we have already mentioned, we will harness genetic algorithms not for the optimization problem, but rather for the data gap problem. We will generate data from existing data. For this purpose, we are going to perform the same steps except that at the first step, which is the selection step, we will assume that the basic data are those already selected. Therefore, we are proceeding to directly apply the next two steps, which are the crossing and the mutation. Our primary objective underlying the harnessing of genetic algorithms is to expand our database so that we can test and demonstrate the relevance of our recommendation system. Through a considerable database, it will be possible to test and measure the performance of the system. We will consider an example that falls within our field of application: social learning. We are going to examine a set of 10 learners, and for each learner, the occurrence of two events are regarded for a duration t, for example: • E1 : The amount of learners’ interactions toward the different contents. • E2 : The amount of interaction between learners. The data will therefore be presented as follows: A1 (E1 , E2 ). Table 2 outlines the data on which the genetic algorithms will be applied. From this data, we will generate a number of additional data: =45 pairs

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M is the amount of new data generated. N is the amount of initial data. 3.2

Results and Discussion

Selection. As mentioned above, this step is considered to be already done since we are not going to select data from the initial database. However, we will convert the decimal data into binary data in Table 3. Crossover. This step consists of cross-referencing every two data pairs. To start this step, it is necessary to divide the data into two parts: the first one concerning the first event and the second one concerning the second event. The aim is in fact to process each type of data separately and to be able to apply the genetic algorithms on each separate event. At the end, we will be able to link the learners’ data together after running the genetic algorithms. In what follows, we will illustrate an example of the crossover operation with respect to the learner data. 6

0110

0111

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Mutation. This step thus consists in exchanging one of the bits obtained from the previous step, which is the crossing step. We choose in our context to exchange the last bit of each number: 0110 0111. After applying the two steps of crossover and mutation on the basis of initial data, especially on the two events, each event separately, we obtain the following results: 90 simulated learners from 10 initial learners. The final database will therefore contain 90 + 10 = 100 learners. The latest results obtained are shown in Table 3. Table 3. Results obtained after genetic algorithms execution. Learner A11 A12 A13 A14 A15 A16 A17 A18 A19 A20 A21

Data (3, 5) (7, 3) (5, 4) (5, 7) (5, 3) (3, 1) (1, 1) (7, 1) (5, 5) (6, 3) (6, 4) (continued)

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Data (2, 7) (4, 3) (3, 1) (0, 1) (6, 1) (6, 5) (5, 6) (3, 6) (5, 2) (3, 0) (1, 0) (7, 0) (5, 4) (0, 6) (5, 0) (2, 0) (0, 0) (6, 0) (4, 5) (4, 3) (3, 3) (0, 1) (6, 1) (6, 5) (1, 0) (1, 0) (7, 0) (4, 4) (1,0) (7, 0) (5, 5) (6, 1) (4, 4) (5, 4) (6, 5) (7, 4) (6, 5) (3, 5) (7, 4) (7, 5) (continued)

Genetic Algorithms to Generate Data Table 3. (continued) Learner A62 A63 A64 A65 A66 A67 A68 A69 A70 A71 A72 A73 A74 A75 A76 A77 A78 A79 A80 A81 A82 A83 A84 A85 A86 A87 A88 A89 A90 A91 A92 A93 A94 A95 A96 A97 A98 A99 A100

Data (2, 4) (7, 4) (6, 5) (3, 4) (0, 5) (2, 5) (3, 4) (2, 5) (2, 4) (3, 4) (0, 5) (6, 0) (6, 3) (7, 2) (7, 3) (6, 2) (7, 2) (6, 3) (6, 5) (46) (5, 5) (4, 4) (5, 4) (4, 4) (3, 6) (2, 5) (2, 6) (3, 6) (0, 7) (7, 3) (4, 2) (5, 2) (5, 3) (2, 1) (3, 1) (2, 1) (1, 1) (0, 1) (6, 1)

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Performance of the Approach. To show the performance of genetic algorithms at the level of data generation, we choose to measure the average of the generated data and compare it to the initial data. For the first event E1 , we obtain an average of 4,044 compared to 4,1 of the initial database. For the second event E2 ; we achieve an average of 3,122 against an average of 3,1 in the initial database. We can notice that values are quite equal, which explains the efficiency and performance of genetic algorithms in generating data. We were thus apt to generate data for 90 learners with similar behaviour as the original learners. The reason for adopting genetic algorithms in recommendation systems is mainly to test our recommendation approach. Indeed, in order to prove the performance of our recommendation system, it is a prerequisite to have a considerable amount of data in hand in the first place. Data required to test the recommendation approach will hence be generated by genetic algorithms. Typically, in most research, genetic algorithms are involved in optimization problems. In our case, genetic algorithms have been leveraged to generate data in order to enhance the robustness of the database.

4 Conclusion In our context of recommendation systems within social learning networks, our approach consists in providing a solution regarding scarcity of data, as the e-learning area generally suffers from this problem. To this extent, we have exploited genetic algorithms to generate data from available data. The major intent of using genetic algorithms is to expand our database in order to test and demonstrate the relevance of our recommendation system. We examined an illustrative example of data coming from 10 learners, out of which we generated data concerning another 90 learners. This attests that genetic algorithms have the potential to become a very substantial part of solving the problem of scarce data. In our future work, we intend further to: • Test the genetic algorithms on a database of real learners. • Introduce genetic algorithms into our approach to recommending social learning.

References 1. Durak, G., Cankay, S., Yunkul, E., Ozturk, G.: The Effects of A Social Learning Network On Students’ Performances And Attitudes, Zenodo, févr. 2017. https://doi.org/10.5281/ zenodo.292951 2. Somayeh, M., Dehghani, M., Mozaffari, F., Ghasemnegad, S.M., Hakimi, H., Samaneh, B.: The effectiveness of E- learning in learning: A review of the literature, 6 3. Chou, C.-H.,. Shih-Ming, Pi.: The Effectiveness of Facebook Groups for e-Learning, IJIET, 5(7), 477–482, (2015). https://doi.org/10.7763/ijiet.2015.v5.553 4. Bobadilla, J., Serradilla, F., Hernando, A.: Collaborative filtering adapted to recommender systems of e-learning, Knowl.-Based Syst. 22(4), 261–265, mai (2009). https://doi.org/10. 1016/j.knosys.2009.01.008 5. Saad, I., Tangour, F., Borne, P.: Application des algorithmes génétiques aux problèmes d’optimisation, 7 (2009)

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6. Hassanat, A., Almohammadi, K, Alkafaween, E. Abunawas, E., Hammouri, A., Prasath, V. B.S.: Choosing Mutation and Crossover Ratios for Genetic Algorithms—A Review with a New Dynamic Approach, Information, 10(12), 390, Décember 2019. https://doi.org/10. 3390/info10120390 7. Walchand College of Engineering, U. A.J., S. P.D., and Government College of Engineering, Karad, Crossover Operators In Genetic Algorithms: A Review, IJSC, vol. 06, no 01, pp. 1083–1092, October 2015. https://doi.org/10.21917/ijsc.2015.0150 8. Jebari, K., Madiafi, M.: Selection Methods for Genetic Algorithms, p. 13 9. Ahmed Hamdi, A.A., Al-Sayegh, S.W.: E-learning Timetable Gen-erator Using Genetic Algorithms 10. Gavrilović, N., Šibalija, T.: The application of evolutionary algorithms. In: E-Learning System, The 9th International Conference on eLearning (eLearning-2018) 11. Zaporozhko, V., Bolodurina, I.P.: A genetic-algorithm approach for forming individual educational trajectories for listeners of online courses, p. 8 12. Akure, O.S., Nige-ria, O. C., Agbonifo, O.A.: Obolo Department of Computer Science, Federal University of Technology, Genetic Algorithm-based Curriculum Sequencing Model For Personalised E-Learning System, IJMECS, vol. 10, no 5, p. 27–35, mai (2018). https:// doi.org/10.5815/ijmecs.2018.05.04

The Learning Factory: Self-directed Project-Based Education Joshua Lawrence(&), Benjamin Dimashkie, Dan Centea, and Ishwar Singh McMaster University, Hamilton, ON L8S 0A3, Canada [email protected]

Abstract. Self-directed learning, project-based learning, and mentorship are the components which construct the pedagogy invoked in McMaster University’s SEPT Learning Factory. This approach to learning provides students with the opportunity to investigate new concepts through self-led inquiry by working towards engaging real-world project goals. This process facilitates a higher level of student engagement, material retention, as well as a multitude of other benefits to the student’s learning experience. This paper aims to explore the benefits of self-directed learning, project-based learning, as well as the incorporation of guided mentorship into the student-led project development process. The outcomes indicated by research into the individual benefits of each of these components provide an insight into the effect of this learning process as a whole. Furthermore, anecdotal evidence is provided to discuss the benefits of the confluence of these methods, presented in one pedagogy. These findings suggest a possible value to implementing a self-directed, project-based learning system with mentorship within a higher education environment in order to support student learning. Keywords: Self-directed


Project-Based learning
Learning factory

1 Introduction The SEPT Learning Factory (LF) is a state-of-the-art facility which simulates the factory of the future to provide students, industry professionals, and researchers a space to learn Industry 4.0 concepts through hands-on methods [1]. Within this facility each year, students are employed through the undergraduate co-op program to participate in research-focused projects to develop the LF to further the integration of concepts such as the Industrial Internet of Things (IIOT) and Cyber Physical Systems. Students who work in the LF undergo a unique learning experience which is characterized by selfdirected learning, project-based learning, and access to mentor support. Students are assigned broadly structured projects with technical goals and specifications, then provided the opportunity to work towards these project goals with open access to technical and educational resources. The assigned projects include a learning curve, and students are encouraged to apply self-directed learning to understand all the necessary core concepts, and then come to a solution which fits the project specifications on their own. If students are unable to achieve a project goal, direction is openly © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 114–122, 2021. https://doi.org/10.1007/978-3-030-67209-6_13

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available from mentors knowledgeable in the project’s technical domain and available to advise the student. This learning pedagogy offers many benefits to student learning as compared to traditional didactics implemented today. Before exploring the benefits to this methodology, it is important to define the components which make up this structure. With respect to project-based learning, it can be defined as the following: “a pedagogical approach that enables students to learn while engaging actively with meaningful problems. Students are given the opportunities to problem-solve in a collaborative setting, create mental models for learning, and form self-directed learning habits through practice and reflection” [2]. Within the LF, this concept is materialized through tasks assigned to the students being in the form of large-scale projects. When it comes to self-directed learning, there are many differing definitions of the term. One definition prescribed by Zimmerman is the following: “[students] who have an understanding of their own approach to learning and how best to maximize their learning in the most efficient ways; are motivated to take responsibility for their learning; and are able to work with others to enhance the depth and breadth of their learning” [3]. Another commonly quoted definition is that of Malcolm Knowles, who has defined it as a process where “the students take initiative with or without the help of others, assess their learning needs, formulate goals with implementation of appropriate strategies and evaluate learning outcomes” [4]. This definition captures the self-directed learning applied within the LF, as it is the responsibility of the student to define their gaps of knowledge and develop strategies to address these topics to ultimately complete their projects. Finally, mentorship is a broad term which can be applied in multiple contexts. In the Oxford Dictionary it is defined as the following: “guidance provided by a mentor, especially an experienced person in a company or educational institution” [5]. In the context of this paper, mentorship refers to the guidance provided to students by instructors, peers and mentors who possess a greater level of understanding in relevant technical areas. Informed by individual experiences in the LF as well as in traditional education, insight into the potential inherent advantages of the pedagogy displayed in the LF can be explored, with the driving purpose being to facilitate higher quality learning. The self-directed, project-based, mentor-guided system proposed in this paper provides numerous benefits regarding student learning and should be considered for feasibility in supplementing traditional education methods implemented today. Some of the benefits explored in this paper include improved learning efficiency due to individualized learning paths, which consider the students’ preliminary knowledge and avoids a one size fits all strategy. Furthermore, project-based learning provides a platform which contextualizes and applies knowledge as well as strengthens organizational skills, and mentorship compliments the aforementioned system by providing necessary guidance to students when challenges are encountered in the project development process. In short, student-led, self-directed projects with mentor guidance facilitate higher quality learning in undergraduate engineering students.

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2 Purpose The purpose of this paper is to explore the effectiveness of the learning methods implemented in the LF. The LF facilitates a confluence of a multitude of factors which define it as a pedagogy. Self-directed learning produces greater student learning initiative, individualized learning efficiency, and generally better student outcomes, including student well-being. Facilitating this method of learning through a project development process contributes hands-on relevance and memorability to learning, prepares students to work on tasks where prior knowledge is not sufficient for the project goals, and reinforces organizational skills. Mentorship and knowledgeable feedback serve as an invaluable addition to student learning through self-directed projects. Teachers, mentors, and peers are very beneficial for learning technical information directly, adapting the student’s learning path dynamically, and in mitigating problems encountered during the learning process and project development. The aim of this paper is to explore the aforementioned system of learning and to address its effectiveness in facilitating an environment which fosters learning for undergraduate students.

3 Approach With respect to the approach to this paper, there are two primary methods for collecting evidence, those being through informational interviews with individuals who have experienced the learning process within the LF, as well as a comprehensive analysis of academic literature on the subject at hand. Four individuals were interviewed to understand their perspectives on how the LF affected their learning in the classroom and beyond. The following individuals were interviewed: Simran Nijjar, B. Tech 2018, Manufacturing Controls Engineer, Tesla Anoop Ghadrri, B. Eng Electrical 2020, Entrepreneur, Research Software Lead Josh Lawrence, B. Tech 2021, Research Assistant Learning Factory Ben Dimashkie, B. Tech 2021, Research Assistant Learning Factory During the interviews, questions were asked in a structured format with questions formulated pre-interview. These questions were created to provide open-ended opportunities for the interviewee to offer their perspective regarding the topic at hand. Evidence was also gathered through the use of reputable research papers and cited appropriately.

4 Outcomes The pedagogy employed by the LF is intended to provide students with an open-ended and experiential learning opportunity. This structure can be described as a confluence of self-directed learning, project-based learning, and mentorship. The benefits to student learning from each of these elements are multidimensional and descriptive of the LF undergraduate co-op program as a whole.

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Self-directed Learning. With regards to self-directed learning, a key benefit is in developing student engagement and initiative in their own learning. Active research and information seeking through a wide range of learning resources is facilitated, and in doing so familiarizes students with active engagement of online research material, a skill which can be transferred to other domains. For instance, “self-directed learning has significant and direct impacts on the cognitive presence of students in the blended learning setting” [6]. Greater engagement with educational material is obtained through repeated self-directed discoveries with a variety of learning resources, as one student stated regarding learning a new technology, “in terms of how to learn the associated theory I would use many resources, for example: online searches, instruction manuals, and watching videos” [7]. Furthermore, learning time is used more efficiently, as it is directed at the individual’s gaps of knowledge specifically. This directionality in the student’s learning is an asset because “on the cognitive side, self-directed learning allows individuals to focus effort on useful information they do not yet possess, can expose information that is inaccessible via passive observation, and may enhance the encoding and retention of materials” [8]. Student-led inquiry can make learning experiences more memorable, and self-directed learning skills are common and beneficial within higher education. It can be seen that “undergraduate students have selfdirected learning skills and these skills are related to lifelong learning” [9]. Additionally, independent learning skills are both essential for success in higher education, as well as promoting of student wellness. An article regarding this relation between independent learning, student autonomy, and well-being states the following regarding students entering university without independent learning skills: “[students] are impeded in terms of successfully transitioning to effective and efficient tertiary learning practices. This can hamper their learning and understanding of discipline knowledge, skills and attitudes” [10]. Moreover, the article identifies that “curriculum initiatives that promote independent student learning should be understood as wellness promoting activities, as well as learning activities” [10]. This further illuminates the various psychological and learning benefits of self-directed learning. Through experiences in a self-directed environment, students acquire learning skills which can be universally applied to a multitude of situations. Through experience learning a complex technical concept called the robot operating system (ROS), a student states that “through my experiences in a self-led environment learning ROS, I’ve acquired the ability to identify the subcomponents required to achieve my project goals. Through reframing my focus to learning the subcomponents independently, I’ve attained the ability to approach a certainly daunting task through a simplification process I’ve acquired through my self-teaching” [11]. Figure 1 outlines a hierarchical map of the ROS learning path explored by this student in the LF. This map outlines how through self-directed learning students acquire the ability to understand the highlevel structure of an advanced topic by dividing the subject into easy to learn subcomponents.

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Fig. 1. Hierarchical learning path of robot operating system

One challenge imposed by a self-directed learning system is regarding learning a complex topic such as the ROS, as the lack of structure provided is sometimes difficult for students to manage. In the traditional classroom, students are provided with a structured curriculum with a specified learning path. Though a challenge, it is an undeniably integral skill to be able to self-identify one’s own learning path, a proficiency valuable in any context. During discussion, a student said regarding overcoming this obstacle, that “through practice, learning how to overcome the initial intimidation of a project by subdividing it into its components has helped me improve my self-teaching ability. This process has allowed me to accelerate at learning a variety of concepts and will prove essential for my future learning” [11]. Being an essential component to selfdirected learning, defining the required learning path is an important skill and is best promoted in students by facilitating a self-directed learning environment. Project-Based Learning. The second component that informs the LF pedagogy is project-based learning. Projects apply theoretical content in a relevant and hands-on way, increasing student understanding by continuously relating new information to a practical body of work. This distinctly influences student outcomes, for instance, it has been demonstrated that with respect to traditionally taught groups, “students who participated in the IT‐enhanced [project-based learning] performed significantly better than their control classmates” [12]. A key benefit stemming from a project-based structure is in adding context, strengthening the ability for students to approach technical challenges with limited prior knowledge in the area. This effect is evidenced by the student experience of project-based learning, in that “students strongly feel that this is a better method for “learning” and believe that the projects provide a more realistic environment for applying the principles of engineering, science and mathematics towards solving practical problems” [13]. Another benefit of project-based learning is that it reinforces project management and organizational skills. This impact includes an “improvement in the students’ ability to set goals and identify and organize activities to best accomplish those goals” [14]. This effect is described by a student as the ability to “break things down into the barebone components you need to learn, then learning the

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components independently” [15]. In this context it can be seen that increased ability to structure one’s own learning is the result of repeatedly disassembling complex projects in their constituent components. The project-based learning process is a clear asset to student understanding regarding the technical concept being studied in particular, as well as in strengthening the student’s ability to apply the project development and research process in other technical domains. An example of this is provided by a student in their development of an online energy-monitoring dashboard for the LF. The goal of developing this project necessarily required the self-directed learning of many other technical areas, such as Node-RED, the web-based visual programming tool used to display the energy data, the programming language Python, and the relational database management system, MySQL [16]. To apply these individual tools towards the final project goal, they were researched independently by leveraging a multitude of educational resources, including regular consultation with individuals knowledgeable in each respective area. Conceptual understanding of topics including coding with Python, using Python libraries, SQL queries, and working with Web APIs was built-out naturally from project goals [16]. Newly acquired and diverse technical knowledge is then immediately applied in a relevant application. Learning is contextualized by linking tasks to learning goals, then intrinsically demonstrating the value of that knowledge by completing the project goals. Lastly, the project development process is paralleled later in education, and in the workforce, especially commonly within engineering. The organizational and goalsetting skills strengthened by project work are universally valuable to the student, being applicable in more varied environments than the direct benefits of increased technical skill. Mentorship. It should be noted that self-directed learning is not a solitudinous effort. Instructors, peers, and mentors are essential informational resources for a self-directed learner to leverage. Regular guidance from experienced individuals in self-directed learning can have a positive effect on developing technical skill, due to increased practice, as demonstrated in a study on surgical residents [17]. Beyond direct informational assistance, open access to mentorship provides students with continual guidance and correction in learning paths, making the experience more efficient and adaptable. Moreover, mistakes can be mitigated in a project environment by consulting more experienced individuals. Cultivating an environment with regular communication channels to mentorship results in a system conducive to rapid learning, continuous adaptation of the student’s learning path, and successful project completion. Within the practical implementation of a mentorship system in the LF, students are provided support from peers and mentors to help facilitate their self-directed learning. This system provides students the necessary support to facilitate a rapid self-learning environment. With regards to the effect of mentorship on a student’s learning experience, a student stated: “during my self-directed learning with ROS, one of the largest barriers to success was defining an appropriate learning path to become an expert on this topic. The mentorship from my peers was integral to my success in this journey, having someone to turn to who was an expert on this subject helped me troubleshoot errors and fast track my learning process” [11]. The benefits of a self-directed, projectbased learning are heavily accentuated by the inclusion of a mentorship support system.

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Structural Comparisons

The LF structure integrates the positive attributes of self-directed learning, projectbased learning, and mentor guidance in order to create a practical and memorable compliment to traditional education. The LF structure allows students to gain strong comprehension of academic theory through project goals which necessitate discovery of more foundational knowledge. Self-directed learning goals are developed by the student and are explored with a variety of resources, including mentorship, and then applied directly to the project, thus contextualizing and reinforcing the material. This principle is described by a student in that, “hands on experience really connects the dots” and that regarding the LF structure, “the theory would be project research and actually doing it would be the application portion where you connect all the dots together” [7]. This process is distinct from lecture-style learning where a universal learning path is conveyed to all students without direct application of the theory learned. To draw a quantitative comparison between traditional lecturing and active learning, a meta-analysis into the performance of undergraduate students in science, technology, engineering, and math indicates “active learning as the preferred, empirically validated teaching practice in regular classrooms” [18]. Further, student experience in the LF indicates the potential value of pairing traditional education with selfdirect, project-based, and mentor-guided learning programs. Self-directed, project-based learning can be compared to a lab work structure. Hands-on application of course material is often implemented with regular lab sessions. Courses paired with lab sessions offer the advantage to students of a practical, relevant, and memorable learning experience. Alternatively, self-directed projects give students a practical understanding of academic material, while also supporting a dynamic learning process which is not restricted to the segmented topics found in lab sessions. When asked to compare project-based learning to lab work, a student stated that “labs are so structured in what’s provided to students with direct instructions of what to do and when, […] students miss out on a lot of the learning. The self paced projects in LF were phenomenal because I had the freedom to explore all of my options with how to approach a problem” [15]. A self-directed project will incorporate many technical concepts together, and in doing so, provide a more realistic application of the content, and equip students with the ability to repeat the project development and learning process elsewhere, including the workplace. The Learning Factory structure intrinsically prepares students entering the workforce due to the similarity in learning methodology to the learning process increasingly found in the workplace. As addressed by an interviewee referencing their experience of joining the workforce with regards to self directed learning, “my experience at Tesla has been exactly that, a lot of self-directed learning. […] When I came to Tesla my manager introduced me to a new platform, I had no experience with and mentioned he wanted me to use it in my work. Right then and there, during the first week I was there, that was when self-directed learning comes into play” [7]. Students are prepared with a process with which to take on unfamiliar technical concepts, self-validate their understanding, and actively apply themselves to develop their understanding further. Furthermore, this structure shares parallels and distinctly prepares students for a project-based work environment, especially in an engineering context. When prompted

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about how the methodology implemented in the LF affected their experience in the workforce, the interviewee stated that it “has definitely had a positive effect, since everything I do at Tesla is project based. Not all of my co-workers know the correct approach or correct steps and that’s when it’s up to me to explore it myself with selfdirected learning. I would definitely say that the LF experience along with other experiences have all come together to provide me with my understanding and knowledge to apply to the projects I work on today” [7].

5 Conclusion In conclusion, the pedagogy materialized in McMaster University’s SEPT Learning Factory provides a unique approach to education which offers many benefits to student learning. Self-directed, project-based learning with mentor guidance produces graduates who are ultimately better prepared for the workplace. The method proposed contrasts traditional labs, suggesting an avenue for improvement. The self-directed component facilitates an individualized method of learning for the student, which facilitates higher student engagement, as well as providing better academic and wellbeing outcomes. With a project-based approach, students experience hands-on learning in a manner which replicates the workforce, exploring new concepts with repeated contextualization. This is implemented for the purpose of improving memorability of content and providing students with the opportunity to learn how to approach technical challenges where they possess limited foundational knowledge. Finally, these methods of learning are tied together with the informational support of mentorship, which complements the self-directed learning process, as well as providing students with the support they require when challenges are encountered in the learning process. With regards to implementing this strategy in a classroom environment, it would be advisable to modify hands-on components such as labs with self-directed projects which can provide a more all-encompassing implementation of the theory taught traditionally. Self-directed projects can be implemented in a multitude of manners, though it is essential to provide students with the opportunity to explore new concepts through student-led inquiry. It is essential to supplement the theory taught in the classroom with hands-on experiences which foster an understanding of the core theoretical concepts taught in the classroom.

References 1. Elbestawi, M., Centea, D., Singh, I., Wanyama, T.: SEPT learning factory for industry 4.0 education and applied research. Procedia Manufact. 23, 249–254 (2018) 2. Yew, E.H.J., Goh, K.: Problem-based learning: an overview of its process and impact on learning. Health Prof. Educ. 2(3), 75–79 (2016) 3. Zimmerman, B.J.: Becoming a self-regulated learner: which are the key subprocesses. Contemp. Educ. Psychol. 11(4), 307–313 (1986) 4. Knowles, M.S.: The Making of an Adult Educator: an Autobiographical Journey. JosseyBass, San Francisco, CA (1989)

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5. Definition of Mentorship, Lexico Dictionaries. https://www.lexico.com/en/definition/ mentorship. Accessed 28 May 2020 6. Geng, S., Law, K.M.Y., Niu, B.: Investigating self-directed learning and technology readiness in a blending learning environment. Int. J. Educ. Technol. High. Educ. 16(17), 1–2 (2019) 7. Nijjar, S.: (Learning Factory Alumni), interview by Lawrence, J., Dimashkie, B.: 20th May 2020 8. Gureckis, T.M., Markant, D.B.: Self-directed learning: a cognitive and computational perspective. Sage J. 7(5), 464–481 (2012) 9. Aşkin, İ., Demirel, M.: An investigation of self-directed learning skills of undergraduate students. Front. Psychol. 9(1), 2324 (2018) 10. Field, R., Duffy, J., Huggins, A.: Teaching independent learning skills in the first year: a positive psychology strategy for promoting law student well-being. J. L. Des. 8(2), 4 (2015) 11. Lawrence, J.: (Learning Factory Research Assistant), interview by Dimashkie, B., 20th May 2020 12. Barak, M., Dori, Y.J.: Enhancing undergraduate students’ chemistry understanding through project-based learning in an IT environment. Sci. Educ. 89(1), 118 (2004) 13. Savage, R., Chen, K., Vanasupa, L.: Integrating project-based learning throughout the undergraduate engineering curriculum. J. STEM Educ. 37(1), 1 (2009) 14. Walters, R.C., Sirotiak, T.: Assessing the effect of project based learning on leadership abilities and communication skills. Semantic Scholar (2011) 15. Ghadrri, A.: (Learning Factory Software Lead), interview by Lawrence, J., and Dimashkie, B., 25th May 2020 16. Dimashkie, B. (Learning Factory Research Assistant), interview by J. Lawrence, May 20th 2020 17. Aho, J.M., Ruparel, R.K., Graham, E., Zendejas-Mummert, B., Heller, S.F., Farley, D.R., Bingener, J.: Mentor-guided self-directed learning affects resident practice. J. Surg. Educ. 72 (4), 674–679 (2015) 18. Freeman, S., Eddy, S.L., McDonough, M., Smith, M.K., Okoroafor, N., Jordt, H., Wenderoth, M.P.: Active learning increases student performance in science, engineering, and mathematics. PNAS 111(23), 1 (2014)

Enhancing Practical Learning in Undergraduate Chemical Engineering Courses via Integration of Commercial Process Modelling Software Ryan J. LaRue(&), Isabella Monaco, and David R. Latulippe Department of Chemical Engineering, McMaster University, Hamilton, ON L8S 4L7, Canada {laruerj,monacoi,latulippe}@mcmaster.ca

Abstract. Integrating commercial software packages into undergraduate engineering courses is seen as a beneficial pedagogical approach for students in two ways. First, it facilitates an active learning environment; second, it gives students access to modern technical tools. Here, we present the key outcomes from the incorporation of software packages in two chemical engineering courses: a commercial hydraulic modelling software (PIPE-FLO; Engineered Software) was used in a Fluid Mechanics course, and a freely-available water treatment design software (WAVE; DuPont) was used in a Separations course. For each software package, a set of self-guided tutorials were created with step-by-step instructions (including screenshots/diagrams) and both closed- and open-ended practice problems that were designed to improve the learning outcomes. Also, a set of supplementary workshops were given to demonstrate the practicality of the software. This approach was expected to promote a greater understanding of course material by creating a low-risk environment where the students can explore and expand their knowledge. Over the past five years of integrating PIPE-FLO into the Fluid Mechanics course, the responses from the students have been overwhelmingly positive. Our approach has led to the successful internalization of course content, as evidenced by accreditation metrics. We anticipate that continually refining these course materials—especially with regards to the WAVE software—will see students develop a greater understanding of the course content. Keywords: Software package Engineering education


Fluid mechanics
Separations science


1 Introduction and Background Traditionally, undergraduate engineering courses have students develop their skills by the manual application of fundamental theory and governing equations. This approach can limit the students to solving relatively simple, closed-ended problems whereas the problems encountered in graduate school and industry are complex and open-ended, requiring well-developed critical thinking skills. Furthermore, it is often the case that only a superficial understanding of the concepts is developed [1]. The integration of © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 123–131, 2021. https://doi.org/10.1007/978-3-030-67209-6_14

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commercial software packages into engineering courses is seen as a beneficial pedagogical approach [2–5] which promotes active/deep learning and allows the students to use ‘state-of-the-art’ tools. Towler and Sinnott give a strong recommendation for this approach in the preface of their textbook Chemical Engineering Design where they “strongly recommend that students be introduced to commercial software at as early a stage in their education as possible. The use of academic design and costing software should be discouraged. Academic programs usually lack the quality control and support required by industry, and the student is unlikely to use such software after graduation” [6]. Furthermore, the approach of integrating these software tools is expected to promote a deeper understanding of the course material by creating a low-risk environment where the students can explore and expand their knowledge. The added benefit to this approach of using commercial software in engineering courses is that it directly satisfies many of the ‘indicators’ that were developed by the Canadian Engineering Accreditation Board (CEAB) for program accreditation. Accredited programs are required to measure and compile a large group of these indicators on an annual basis in order to assess the program effectiveness and identify possible areas for improvement. To this end, we have integrated commercial process modelling software into two courses in the Department of Chemical Engineering at McMaster University. We present the development of educational tools and compare the results which were gleaned from many semesters of using PIPE-FLO in a Fluid Mechanics course and the recent introduction of WAVE in a Separations course. These two typical chemical engineering courses do not traditionally involve a software component.

2 Methodology 2.1

Introduction to Fluid Mechanics and PIPE-FLO

The “Introduction to Fluid Mechanics” course is a mandatory second-year course with a typical enrollment of between 150 and 180 students. A hydraulic modelling software (PIPE-FLO; Engineered Software) was first introduced in the 2013/2014 academic year. PIPE-FLO is one of many software packages that can be used to design and analyze systems of pipes, pumps, tanks, and other fluid handling equipment; other packages include AFT Fathom and FluidFlow. As PIPE-FLO is a commercial software product, it is not freely available. However, a sufficient number of educational licenses were generously provided by the software manufacturer so that the students could use the software at on-campus computer labs or download it onto their own PCs. We created a courseware booklet consisting of ten self-guided tutorials which could be purchased for a nominal amount at the campus bookstore or could be downloaded for free from the course website. The tutorials were designed to build in complexity: from software basics to the simulation of complex piping networks. The students were taught the software with relevant examples in fluid mechanics using step-by-step instructions, screenshots, and diagrams. Closed-ended practice problems were included at the end of each tutorial to help the students explore topics in-depth and improve learning outcomes. On an annual basis, the PIPE-FLO materials were given minor revisions and

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technical staff installed the latest version of the software onto the computer lab servers. Prior to the 2016/2017 academic year, the courseware was given a full overhaul, featuring new examples, practice problems and in-depth discussions relating course material to the software features. A summative tutorial which guided the students in modelling the engine system of a classic Saturn V rocket was included, incorporating many of the topics discussed in previous chapters. Notably, PIPE-FLO was not just used as a single element within the course, but examples using the software were incorporated into the lectures, on assignments, and even in the final exam. The students were first taught the fundamental theory such that they could perform calculations manually and use their results to make informed engineering decisions. However, they were then instructed to use the software to (a) verify their by-hand calculations (and vice-versa) and (b) to solve systems which would be far too onerous to calculate manually. As one example, an assignment problem evaluated in the 2016/2017 academic year asked students to calculate and control the flow rate of a model system containing liquefied propane gas (LPG) which is piped from a dockside storage tank into an empty LPG tanker ship. This problem is shown in Fig. 1. As another example, a final exam question asked students to consider a printout of a complex PIPE-FLO flowsheet which modelled a sap collection network in a hypothetical maple syrup facility, and then use the PIPE-FLO results to verify the sap production rate.

Fig. 1. A) Schematic of the process for transporting LPG from a storage tank to a tanker ship. B) Completed PIPE-FLO simulation of the problem.

2.2

Industrial Separation Processes and WAVE

Building upon the lessons we learned from integrating PIPE-FLO, another software tool was adopted in a separate “Industrial Separations Processes” course to teach students how to design and optimize the performance of membrane-based processes for water treatment. This fourth-year elective course has a typical enrollment of between 50 and 60 students. The commercial process design software package for membrane separations (WAVE; DuPont) was first introduced to the students in the 2019/2020 academic year. WAVE is one of a few software packages that can be used to design and analyze water treatment processes, however, it is freely-available and students can download the package onto their individual PCs. Another courseware was created, consisting of three chapters containing detailed instructions on how to use the software as well as exploration questions designed to help the students obtain a deeper

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understanding of the course material. The courseware features an overarching example involving the use of membrane technologies to purify a saline wastewater stream from a mining operation. A sample of one of the courseware screenshots is shown in Fig. 2. The three chapters build upon each other, beginning with an introduction to the software (easy), then a discussion on ultrafiltration processes (medium), and finally a tutorial on reverse osmosis membranes (more challenging). An interpretation of the simulation warnings and errors that are triggered by the software is also included. By the end of the courseware, a comprehensive system for treating the mining wastewater is modelled; a block-flow diagram of the system is shown in Fig. 3. Building upon our knowledge gained from the years of using PIPE-FLO, open-ended problems were included at the end of each chapter to encourage the students to identify critical process parameters in the operation of membrane systems.

Fig. 2. Screenshot from the WAVE interface from the courseware, instructing students how to add a “concentrate recycle stream” to their reverse osmosis process.

Fig. 3. Block-flow diagram illustrating ultrafiltration and reverse osmosis processes used to treat saline mine wastewater. Detailed process parameters are accessed in each of the “blocks”.

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3 Results and Discussion 3.1

Designing Practice Problems in PIPE-FLO and WAVE

Based on the knowledge gained during the six years of teaching PIPE-FLO in the Fluid Mechanics course, we have solidified our approach to include both open-ended and closed-ended questions to allow students to learn the course material. “Typical” PIPEFLO end-of-chapter questions ask for a specific value to be calculated. For example, a theoretical fire truck draws water from a water tank to feed a structural fire. Asking “What is the flow rate of water produced by the pump?” proves to be valuable for verifying knowledge/understanding, while exploratory problems such as “What is the effect of varying the water temperature (i.e. as the seasons change)?” provide students with the opportunity to obtain a deeper understanding of the factors that affect the design and operation of real-life piping systems. This mix of question formats is valuable for teaching critical engineering concepts to the second-year students. The WAVE courseware is tailored to the fourth-year students and thus features a greater number of inquiry-type problems which require them to integrate knowledge from other courses (e.g. fluid mechanics, engineering economics, etc.) to investigate the design and operation of membrane systems. For example, in a membrane process combining the use of ultrafiltration and reverse osmosis technologies, the students were asked to investigate “the effect of adding or removing a stage or pass on the separation” (i.e. on the produced water quality, recovery, number of pressure vessels, etc.) and if “changing the membrane element type can improve the quality of the permeate stream, with all else equal”. 3.2

Accreditation Metrics

One of the CEAB indicators to be assessed is “the ability to use modern/state-of-the-art tools”. In the Fluid Mechanics course1, the ability of students to effectively use a hydraulic analysis software package like PIPE-FLO to calculate design parameters (e.g. pressure drops, flow rates) for specific piping configurations containing various types of fittings, connections, and valves served as an excellent assessment for this indicator. A PIPE-FLO question modelling a simple home bathroom piping system was included each year on a homework assignment to assess this indicator; a description of the problem can be found elsewhere [5]. The evaluation criterion for the “Meets Expectations” category is that the “question was completed with all correct values for the design parameters”. A breakdown of the annual success rate is found in Table 1. In 2017/2018, a significant fraction of students did not meet our expectations on that assessment. As such, we hypothesized that the students would benefit from some structured practice with building flowsheets and solving problems using PIPE-FLO.

1

Metrics are not available for the Separations course because it is an elective course and thus is not evaluated by the CEAB.

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Table 1. Percentage of students in the “Meets Expectations” category for the CEAB indicator “the ability to use modern/state-of-the-art tools”, by academic year. Students not attempting the problem were not included in the analysis. 2017/2018 2018/2019 2019/2020 32% 65% 83%

3.3

Using Supplementary Workshops to Enhance the Learning of PIPE-FLO

In order to address the low percentage of students that were performing in the “Meets Expectation” category, we decided to offer two supplementary PIPE-FLO workshops to demonstrate the practicality of the software and to serve as a “starting point” for those less familiar with the software at the time. These workshops were run in one of the campus computer labs in the evening and thus were completely optional. Students were encouraged to work independently on a given problem following the steps laid out on a workshop handout. Input was given from the instructor who would also periodically demonstrate the steps to the correct solution. The workshops featured industriallyrelevant problems. For example, as shown in Fig. 4, the one problem challenged the students with the purification of a virus-based cancer therapeutic. With reference to Table 1, in the 2019/2020 academic year, over 80% of the students achieved the “Meets Expectations” category which we believe is attributable to the improved delivery of the PIPE-FLO material in the course, such as through the new supplementary workshops and the better integration of software into the lectures. In Sect. 3.5, samples of student feedback are shown, which reiterate the value of judiciously using PIPE-FLO in the Fluid Mechanics course.

Fig. 4. A) Schematic of a purification process for a virus-based cancer therapeutic. B) Completed PIPE-FLO simulation of the problem.

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Using Supplementary Workshops to Enhance the Learning of WAVE

Given the success associated with integrating the supplementary tutorials in the Fluid Mechanics course, a similar approach was taken for teaching the students in the Separations course on how to use WAVE. A supplementary two-hour workshop was given to help the students get acquainted with the software; the overarching example from the courseware on treating mine wastewater was demonstrated while the students worked on the problem on their own computers in parallel. Furthermore, ample time was given for the students to explore the open-ended problems in the courseware. We felt that this approach greatly reduced the ‘barrier-to-entry’ that some students might experience in attempting to navigate the complex nature of the WAVE software. 3.5

Student Feedback

For the 2019/2020 offering of the Fluid Mechanics course, 43% of the students who completed the optional course evaluation form mentioned PIPE-FLO in the section “list aspects of this course that you found valuable and should be continued”. Overall, the comments were largely positive or constructive including the following: • “The software pipe-flo was a nice way to apply the course to industry” • “Extra tutorials for PIPEFLO helped me feel more confident about working with the software” • “The PIPE-FLO tutorials that were held this semester were also very useful to me” • “It is awesome that after taking this course, one could say they have a working background and understanding in such a useful program” • “I think that the PIPEFLO tutorials should be continued because it allowed for students to apply the knowledge in a tutorial setting” • “If possible integrate pipe flo into the course/tutorials even more”. Students seemed to particularly enjoy the optional PIPE-FLO workshops with some students asking for increased seating capacity so that additional students could benefit from the hands-on learning environment and so that students could develop greater confidence when using these tools. There were few mentions of WAVE in the evaluations for the Separations course; this is likely due to the fact that it was implemented at the very end of the course. However, one student specifically acknowledged how “a lot of work [was spent] developing course material, such as the Wave tutorial”, while another suggested “[moving] the WAVE tutorial closer to the middle of the Term” so that students could fully take advantage. Future iterations of the course should provide additional constructive feedback for the WAVE materials. 3.6

Future Directions with PIPE-FLO and WAVE

The deployment of PIPE-FLO within the context of the Fluid Mechanics course is mature; that is, the materials are well-integrated within the course. However, work continues to be done in (a) updating the courseware such that it matches the everchanging versions of software that PIPE-FLO produces, (b) developing new and

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interesting real-life problems for end-of-chapter exercises, assignments, and evaluations, and (c) periodically refining the material to better suit the needs of the students. A substantial update of the courseware is currently being undertaken in the summer of 2020, considering the three aforementioned points. A brand-new initiative is currently being pursued to exploit a recent feature in the PIPE-FLO software which allows parallel fluid mechanics and heat transfer calculations. Thus, there exists the possibility of using PIPE-FLO in subsequent Heat Transfer courses. Finally, the PIPE-FLO resources will be made available online so that other instructors and students can take advantage of them. With regards to the Separations course, the WAVE materials are currently undergoing a significant revision for the 2020/2021 academic year; funding for this initiative was generously provided by the North American Membrane Society (NAMS) in the form of an Education Innovation Fellowship. The future modules will still contain instructions on how to use the software, but will also feature a variety of prescient industrial examples (e.g. seawater desalination, wastewater treatment), practice problems, and questions which could be used for homework assignments. An exciting outcome of this initiative is that the modules will also be posted on the “education” section of the NAMS website and thus will be available to a wide audience.

4 Conclusions The lessons learned from years of PIPE-FLO experience in the Fluid Mechanics course (such as the need for open-ended exploration problems) has laid the groundwork for the incorporation of the WAVE software in the Separations course. As expected, the software tools in the chemical engineering courses have been well-received by the students. The development of high-quality software-based tutorials, workshops, and assessment questions appears to have led to successful internalization of the course materials, as evidenced by the most recent accreditation metrics. It is anticipated that continuous refinement of the WAVE materials will see students develop a better understanding of the course content and a good appreciation for the utility of the software. Acknowledgements. The authors acknowledge Engineered Software Inc. for generously providing the PIPE-FLO licenses and DuPont for their technical support in this initiative. For their funding support, we thank the North American Membrane Society (in the form of an Education Innovation Fellowship) and the MacPherson Institute at McMaster University (in the form of a Teaching and Learning Grant). Also from McMaster University, we thank Mike Clarke and the University Technology Services team for their help in maintaining the software in the campus computer labs.

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References 1. Keith, J.,

Silverstein, D., Visco, D.: Ideas to consider for chemical engineering educators teaching a new ‘old’ course: freshman and sophomore level courses. In: Proceedings of the 2008 American Society for Engineering Education Annual Conference & Exposition, vol. 1147 (2008) 2. Georgiev, H., Ivanov, A.: Active learning in mechanical engineering education using innovative software tool integrated in solidworks. In: 18th International Conference on Information Technology Based Higher Education and Training (ITHET), Germany, pp. 1–5. IEEE (2019) 3. Akkoyun, O.: New simulation tool for teaching–learning processes in engineering education. Comput. Appl. Eng. Educ. 25(3), 404–410 (2017) 4. Shaikh, F.U.A.: Role of commercial software in teaching finite element analysis at undergraduate level: a case study. Eng. Educ. 7(2), 2–6 (2012) 5. Campbell, S., Latulippe, D.R.: Towards improved learning of fluid mechanics via integration of a commercial software package into an undergraduate course. In: Proceedings of the Canadian Engineering Education Association (CEEA) (2015) 6. Towler, G., Sinnott, R.: Chemical Engineering Design: Principles, Practice and Economics of Plant and Process Design, 1st edn. Elsevier, New York (2008)

Self-directed Learning Compared to Traditional Engineering Approach: Case Studies in Developing Machine Learning Capabilities to Solve Practical Problems Yih-Chyuan Hsiao, Sohaib Al-emara, Anoop Singh Gadhrri(&), Ishwar Singh, and Zhen Gao McMaster University, Hamilton, ON L8S 0A3, Canada [email protected]

Abstract. In this work, the authors present the study from personal experience to gain some insight into the different aspects of efficient self-directed learning. Two case studies regarding the self-directed learning approach and process are conducted and elaborated. The first is more focused on how learning objectives are achieved based on the implementation of detailed plans via concrete steps. The second one is more focused on the online learning of Reinforcement Learning. This work also provides insight from the perspective and teaching experience of AI/ML instructors. Overall, the proposed approach of self-directed learning is an individual initiative, which involves consultation with mentors/professors, formulation of learning goals, comprehension of knowledge, assessment of knowledge, monitoring of minds-on and hands-on training, identification of resources, planning of learning roadmaps, and evaluation of learning outcomes. The proposed approach is also applicable for self-directed learning of other engineering and computer science courses. Keywords: Self-directed learning
Engineering education approach
Machine learning

1 Introduction In recent years, the approaches to teaching and learning have undergone dramatic changes. As we enter the digitally connected age of humanity, accessibility to highquality educational resource materials has been increasing exponentially. With the recent explosion in Machine Learning (ML) and Artificial Intelligence (AI), supplemented by the digital resources on the internet, it is easier than ever before to begin a journey as a data scientist. From open source software to online course materials curated by many prestigious institutions, there are tremendous opportunities for selfdirected learning. Academic institutions play a pivotal role in one’s development and self-discovery. The foundation of their credibility and importance lies partly on their merits - fostering the next generation of forerunners from all walks of life. As such, it is important for academic institutions to always evaluate and explore new mediums of education. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 132–144, 2021. https://doi.org/10.1007/978-3-030-67209-6_15

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Institutionalized learning is a two-way street between the student and instructor. These classically defined roles are slowly being challenged by the modern, changing pedagogic ideologies surrounding academia. With technological advancements, students are becoming ever more self-sufficient in their quest for knowledge. Yet there is often an unrepresented group-the disadvantaged. In the restructuring of a course, we should not only be concerned with the implications for the labour market as Ranson et al. (1996) describes, but with all the individuals involved [1]. What we must understand are the effects of structural transformations that will ultimately disrupt the human experience [1]. Academic institutions often have many on-site resources and services such as libraries and technology labs which may assist or supplement a student’s education. For disadvantaged students who do not have access to cyberspace or computing devices, self-directed learning with regards to engineering and computer science courses may prove to be a challenge. As well, there is another group of students who may be overlooked - first year students just entering a university. In a paper written by Field, Duffy, and Huggins (2014), students at Australian universities were experiencing high levels of psychological distress which began during their first year [2]. Since first years are introduced into a new pedagogical structure, some may lack the self-sufficiency and skills necessary to ease their transitioning process. As Field et al. (2014) indicates, explicit faculty-based support should be provided to develop the independent learning skills of students [2]. We should not neglect the disadvantaged students and incoming undergraduates, and must act with due diligence to help those in need without any prejudice. Even students who are considered more skillful than their peers do not achieve optimal performances due to the omission of self-regulation [3]. As students progress through the various levels of academia, the more crucial self-directed learning becomes. Having online courses introduces the fundamental concept of selfgovernance. The student may choose whenever they wish to study the material, and supplement if necessary. They must enforce their schedule and study habits upon themselves in order to learn independently and effectively. In a study conducted by Freeman et al. (2014), they compared student performance in STEM courses with a limited exposure to active learning, versus the traditional lecturing methodologies [4]. This active approach was compared with passive, traditional learning - where a student simply receives information from an instructor. The results concluded that students in traditional lecture courses were 1.5 times more likely to fail [4]. However, self-directed or independent learning is not a learning method free of any curricula or oversight. It should be emphasized that independent learning can be facilitating meaningful discussion amongst peers, supplementing learning with other credible resources, and reaching out to instructors and teaching assistants. It is about the ability to self-govern and make sound decisions regarding their academic learning. With the vast amount of resources available, it becomes difficult to separate meaningful content from the noise, and focus on what is most important to the learning process. Even after the first problem is solved and we have good, quality content laid out for us, we are met with an even bigger obstacle: the ability to self-discipline and self-direct towards an educational goal - in our case - the goal of becoming an ML

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expert. Throughout this paper, we hope to present our study from a personal experience point of view and share our perspective watching others go through the same process, gaining insight into the different aspects of efficient self-directed learning. In this work, we will also provide insight from the perspective and teaching experience of AI/ML instructors. It is believed that even in a self-directed learning environment, the instructors still contribute to the students’ learning experience. On the other hand, since the areas of AI/ML are evolving frequently for both development tools and state-of-theart techniques, AI/ML instructors should practice self-directed learning to update their theoretical and practical skills as well. Our approach was simple: We surveyed ourselves in our learning process to determine what was effective and what was not through individual initiative, discussions with our mentors and professors (who are part of this study), formulating learning goals, understanding the prerequisite knowledge, assessing our current knowledge, identifying resources for learning, planning our learning strategies, and evaluating the learning outcomes. We also observed how the online/self-directed learning process can be different from the typical learning process taught in universities. In the case of ML, these steps were used to achieve the goals of self-directed projects.

2 Case Study #1-Self-directed Learning of Machine Learning and Deep Learning In the following subsections, Student A, as one of the coauthors, will elaborate on how learning objectives are achieved by implementing concrete plans. 2.1

Motivation

The objective for Student A was to attain the skills and knowledge required to create a machine learning model which could take an image/video as input, and output numerical data representing the context of the image. For example, classification data which would allow the categorization of items within the image, and bounding box data which would allow the localization of an object. This is important because when vision-focused AI is incorporated into conventional products, it not only improves the underlying system, but also reduces costs drastically. The student began a project meant to help monitor traffic flow (pedestrian and vehicle) from a CCTV camera. This project served as an excellent opportunity to learn about the AI vision field in depth. The student later landed on the subtopic of ML known as Deep Learning and eventually decided to focus on CNNs (convolutional neural networks). CNNs are a deep and repetitive matrix multiplication of trained weights with input data. These deep learning architectures are specific to vision related tasks and in the student’s case, the specific input data are images. 2.2

Resource Gathering

The first step was to conduct research. The goal was to access the landscape to see what resources existed and which of these resources would provide the biggest ROI (return

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on investment). The main sources were Google, YouTube and various blogs. While Google and YouTube served as the most convenient sources for finding content, the student found that blogs possessed the highest quality of information. Through these sources, the student was able to find dozens of individuals who had gone on a similar path and documented their learning experience; hence, there was no need to reinvent the wheel. Reading through as many blogs as possible helped to determine which methods worked and which did not. This blog-focused research also allowed the student to identify common learning materials that most individuals used. After finding a specific course, book, or tutorial series, the student would use Google and YouTube to research the materials and find reviews. In the end, the student was able to develop a solid course of action for learning. 2.3

Planning

For this specific case, the plan was straightforward and split into phases. These phases were structured in sequence. Each phase had a very specific assessment metric, as well as a direct and focused learning objective. A first principles approach to learning was adopted, combined with practical exercises. Hence, the first phase of learning was to master the fundamental mathematical concepts. Phase 1 would be done through CS231n, which is an open source course by Stanford University, developed by Andrej Karpathy [5]. Supplementation of mathematical theory-based learning was done through a book called Deep Learning by Ian Goodfellow [6]. In Phase 2, the student began to focus on the more practical aspects and to implement theory-based learning. Phase 3 was the phase where there was a main focus on a cumulative project that would require a combination of all previous learning along with new learning to complete an objective. This final phase shows how the student went about quickly redoing the learning process for Unreal Engine to create synthetic data to solve their problem of having a lack of data. In the end, the student had a complete pipeline of deep learning, from data creation, to model training, to inference and scaling. 2.4

Phase 1-Fundamental Learning

The strict objective for Phase 1 was to learn the mathematical concepts underlying all neural network based models. This phase would require the most self-discipline as it is arguably the most unexciting; However, it is very crucial to the overall learning objective. The student was able to follow through the CS-231n course fairly easily as the video lectures were very clear and concise [5]. The lessons began with very basic fundamentals surrounding matrix algebra, forward passes, back propagation, and even more complex topics such as the choice between FP32 vs FP16 operations. As mentioned before, this was a very complex phase and it was found that the best way to keep focused and stay interested was to implement each mathematical concept into something very practical. For example, for each mathematical concept there was a practical test performed in Python to experiment with the concept. This not only helped the student to stay engaged, but also helped them understand the concepts on a deeper level such that they were easier to remember and apply. By the end of this phase, the student had a very strong understanding of the mathematical concepts that underlie all neural

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networks, rather than just CNNs. At this point it was clear that in the next phase, there would be a need to begin focusing more on vision-related neural networks and increase the amount of practical learning. 2.5

Phase 2-Practical Experience

As was briefly mentioned earlier, the main objective of this phase was to begin specializing the learning towards strictly vision-based neural networks. These are almost always based on the concepts of CNNs. Convolutional neural networks maintain the spatial patterns in the input data which proved to be very necessary and beneficial in the case of image analysis. For this phase, the learning began by looking at the practical assignments offered in CS231-n that strictly focused on vision [5]. Then, various resources were referenced in order to complete these assignments, varying from classification of animals to classification of letters and digits. These references led to other courses as well as tutorial series. A notable course was Deep Learning Specialization by Andrew Ng [7]. A lot of the material was covering the fundamentals and later began to focus around the CNNs. The student - due to previous experience - was able to skip the fundamentals and skim through the CNN content. At this point, there was no need to sit through every component of the teaching material, as enough fundamental knowledge had been established to be able to skim through and find the things that were needed to fill the gaps of the student’s skillset. After learning some more theory focused around CNNs, more time was allocated towards practical projects. The objective was to read through papers that presented state of the art models and recreate these in Python programming. The student began with the most basic model LeNet developed by Yann LeCun in 1988. The model was very simple and straightforward; However, in order to maintain efficiency there was a need to learn a framework that was suitable for the task. PyTorch by Facebook was chosen, and learning the fundamentals were done by following through the documentation presented on the main website. To really solidify the learning in this phase, the student began to recreate a lot of other models as well, which became progressively more complex. This not only strengthened the student’s fundamental understanding, but also his ability to write efficient Python code for PyTorch-based models. At the end of this phase, the student had a very strong understanding of CNNs. Namely, he understood that they act as feature extractors, taking an image and turning it into feature maps that - in some abstract way - represent the contents of the pictures. 2.6

Phase 3-Independent Project

In the semi-final phase of the learning process, the entire focus was on creating a fullfledged model for a very particular purpose. A big project would not only strengthen theoretical learning of the fundamentals, but also teach the principles of creating and deploying a model from a concept to a final production-ready version. The student had the flexibility to choose what project they wanted to focus on. This simple fact is important as it allows a more passionate learning experience. In this case, the student set about creating a system for traffic monitoring using strictly vision. This would require a few things: lots of data, a classification model, and the mathematical

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transformations for a bird’s eye perspective. At this stage of learning, it was very difficult to find any course or tutorial on the matter, mainly due to the complexity of the task. The most helpful resource in this phase was GitHub, as it was easy to find hundreds of similar projects as well as papers associated with them. The student was able to go through these projects and dissect the code to learn the “bigger picture” components. This project was split into its three fundamental components: 1) Data: A method of creating data would be mandatory to train our deep learning model. 2) Model: A suitable model would be needed for performing detection and classification of cars and pedestrians. 3) Transforms: Mathematical transformations would be needed to predict location of objects precisely. 2.7

Data Creation

Since traffic monitoring requires a CCTV camera, it was challenging to find an open source dataset to train a neural network model. Also, creating a big enough dataset using a real camera is not possible by an independent learner. A new learning experience had to be introduced. Unreal Engine 4 (UE4) is a gaming engine that is used to create a photo realistic gaming environment, as shown in Fig. 1. Using Google and YouTube, the student was able to gain the expertise to design an environment with AI moving pedestrians and vehicles.

Fig. 1. Creation of realistic gaming environment

The next step was finding a way to prepare the dataset from the simulation, in which the UE4 plugin NVIDIA Deep Learning Dataset Synthesizer (NDDS) was used to create the dataset [8]. This plugin exports high-quality synthetic images with a 3D bounding box, pose, segmentation, and depth, as shown in Fig. 2. This plugin also gives the ability to randomize the scenery, lighting, camera position, poses, textures, and distractors.

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Fig. 2. Synthetic images with 3D bounding

The dataset consisted of 71,500 unique frames and was used to accelerate the project in detection and pose estimation of pedestrians and vehicles, as well as depth estimation and segmentation. 2.8

Deep Learning Model

The next component of this phase was the model aspect. The student created a classification model based on a “Faster RCNN” framework. For feature extraction (Fig. 3), the student created a custom ResNet-50 model and combined it with the detection head given by “Faster RCNN”. In the end, the model showed to be efficient enough for the students’ computational needs and accurate enough for the task at hand.

Fig. 3. Feature extraction based on a custom ResNet-50 model created by the student

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Perspective Transformation

The final component of this project was a perspective transformation that would allow the student to estimate the location of the objects detected by the deep learning model. This transformation was done using camera intrinsic and extrinsic properties, as explained below [9]:

ð1Þ

A typical camera model consists of the above Eq. (1). This shows the transformation from world coordinates to camera frame coordinates. To go in the opposite direction, [X, Y, Z, 1] must be solved. Due to the loss of depth dimension, it is required to constrain the extrinsic properties to a 3  3 condition. Setting the Z-coordinate to zero performs a homogeneous transformation from a real world flat plane to our camera frame, resulting in the inverse matrix of the 3  3 matrix which is used to solve [X, Y, 1]. The end result is shown in Fig. 4., where the left image is a regular view, and the right image is the perspective transformation. From this result, localization of the output of a detection in real world space was made possible.

Fig. 4. Result of perspective transformation

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Summary of Case Study #1

Learning is an ongoing process, and there is no particular right or wrong approach; However, there were a lot of key points that helped the student to learn more efficiently. The most valuable aspect of this learning experience is that it was very hands-on. Even though the learning was very theoretical - filled with mathematical concepts - Student A was able to find a way to have some sort of physical and objective task. This was sometimes as simple as testing dot products, and other times as complex as recreating a back propagation library. Another factor that really helped in this learning was the in-depth research Student A did before starting. One key point to consider is

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that during the entire process, Student A tried to make sure that the created plan was effective and efficient. Finally, the last notable factor is that Student A found a way to keep the bigger end-goal in mind. When things got bland, the student took the time to step back and remember the reasons why learning vision-focused AI was important in the first place, which resulted in continued motivation, focus, and passion (Fig. 5).

3 Case Study #2 - Self-directed Learning of Reinforcement Learning In the following subsections, Student B, as one of the coauthors, will elaborate on a particular online resource for Reinforcement Learning, and will focus on the comparison between in-person and self-directed learning. 3.1

Motivation

Student B has always been fascinated by games of all shades. From games thousands of years old, such as Chess and Go, to modern day, real-time strategy (RTS) games such as StarCraft and Dota. The student has taken part in these games and enjoys them greatly. In the last decade, there has been tremendous leaps of progress in AI technology, with many companies partaking in these games and the challenges that surround them. With Dota 2, there was OpenAI’s OpenAI Five. In Go, there’s DeepMind’s AlphaGo, and subsequently AlphaZero which encompassed the games of Go, Chess, and Shogi. By watching and following the events surrounding these events, the student developed a deeper fascination for Reinforcement Learning (RL). 3.2

Online Resource

To go about learning RL, the student decided to look for courses from online learning platforms such as Coursera, Udacity, and edX. They looked into these courses due to their partnerships with industry professionals and experts in academia. To elaborate, a lot of these platforms work with people who are renown in their respective fields, as well as with academic institutions such as universities. These platforms offer a structured learning approach to topics that anyone can enroll in. Some courses offered on these platforms are paid, while others are free. The University of Alberta and the Alberta Machine Intelligence Institute (amii) partnered together to offer a specialization course on RL [11]. The course introduces the very fundamental concepts of RL, such as the differences between supervised, unsupervised, and reinforcement learning. After covering the main ideas of modern RL systems, the course takes the student through a journey where they ultimately implement their own neural network learning system - solving an infinite state control task. The course itself is broken into four weeks and allows the student to take a selfdirected approach and pace themselves accordingly. Students are encouraged to watch the videos of the instructors explaining high-level concepts, while supplementary reading is provided. In fact, it is encouraged for students to do the required reading before watching the videos, as the concepts taught in the textbook are further

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elaborated on in the videos. In this course specifically, the supplementary reading involves the textbook, Reinforcement Learning [11]. This mimics an in-person style teaching, where the student follows along reading material provided by their instructor.

Fig. 5. Agent-environment relation in a Markov decision process [11]

There are interactive modules that the course offers, such as examples regarding how a learning agent would act. For example, during an in-person lecture, the instructor may ask “Now imagine yourselves as an agent. What are the choices that an agent will make in this situation?” Depending on a student’s understanding, their conceptualization may or may not be correct. The interactive modules provided a clear, concise example as to what an agent - in this case, the student interacting with the module would do in a given situation. This is not the same as if a professor walked through an example of an agent choosing a situation, because it takes away the key importance of having the student do the heavy-lifting in the agent’s decision making. 3.3

Online Learning

With online learning, lectures are always available so long as they remain hosted. This allows for an iterative learning approach if students need to go back and review concepts shown in the videos. This normally wouldn’t be an option with in-person lectures. Furthermore, there are options to control playback speed. This is crucial for lecturers who tend to talk slow. On the other side of that coin - for in-person teaching if a student’s professor had a tendency to speak fast, they may or may not be able to fully grasp the concepts properly. One thing to note is that the video lectures in general are not very long. This helps with concentration and content absorption. Students may find sitting through hour-long lectures to be difficult. Another difference is that if a student wasn’t able to understand a concept and needed to consult other resources, they would be able to do so easily by pausing the video lecture and supplement their learning elsewhere. During in-person lectures, a student isn’t able to do this as effectively, as the lecturer will continue speaking, thus resulting in the student missing information. There are discussion forums on Coursera that aim to facilitate meaningful discussions between the student users and the instructors. With in-person learning, students

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may feel uncomfortable speaking or asking a question in a face-to-face environment. Online discussion boards help distance this feeling. At the end of each week, there are quizzes and assignments to probe the student’s understanding. The programming assignments are done in Coursera’s Jupyter notebook an open source web application document that contains live code - allowing for the student’s code to be tested and verified, resulting in a numeric grade for the course. Some may argue that this puts a restrictive element to the creative process, but oftentimes, the assignments are well constrained in their delivery and approach. 3.4

Summary of Case Study #2

In conclusion, online content delivery can most certainly fill the gaps of in-person teaching - especially with regards to software courses - so long as the quality of education remains prudent. The type of medium used in the videos is most definitely a factor. The video could be a recording of the professor in front of a whiteboard in their room, a screen recording of a slideshow with voiceover, or a professionally edited video. Based on the medium, the effectiveness ultimately varies. Learning has, and will always consist of some form of self-governance. However, instruction and guidance will alleviate some burden in the process of a student’s learning – only if course designers and instructors do their due diligence in conveying that accommodation.

4 The Instructor’s Role for Self-directed Learning For the self-directed learning of students, course instructors are still expected to play an important role in improving the learning experiences of the students. As shown in the following figure (Fig. 6), there are a variety of factors such as self-motivation, the establishment of long/short term study goals, the proper approach in gathering information, good learning habits and self-discipline, adequate exposure in minds-on and hands-on practices, and so forth. These will all affect a student’s learning objectives and can be reinforced from a student’s interaction, consultation, and communication with their instructors. As the fields of machine learning, deep learning, and reinforcement learning become more dynamic in recent years, along with the emergence of various development tools, instructors must update their theoretical and practical skill base. Therefore, in a self-directed learning environment, there is a mutual influence between students and instructors, resulting in a positive feedback loop. In some scenarios, students may even present much faster learning progress due to physiological or intellectual advantages, complementing an instructor’s higher level vision and experience.

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Fig. 6. Role of the course instructor in terms of learning outcomes of students in self-guided learning environments

5 Conclusions This paper emphasizes the straightforward approaches of self-guided learning, which are mainly initiated by students themselves. It is noticeable that the areas of machine learning, deep learning, and reinforcement learning are progressing and changing. We must consider that each student has their own learning curves and habits. In a traditional learning environment, the instructor has to consider the needs of the majority to design course materials and manage the pace of content delivery; Therefore, it is not as flexible as a student tailoring everything to achieve equivalent or even better learning outcomes, so long as the student is competent in their self-governance. There are various factors that greatly affect the performance of self-directed learning, and they must be taken into account. Overall, this research is focused on two case studies which were conducted by students. The projects which were implemented by the students themselves prove the real world problem-solving skills gained through the self-directed learning approach. The proposed methods are also feasible for other engineering and computer science courses.

References 1. Ranson, S., Martin, J., Nixon, J., McKeown, P.: Towards a theory of learning. Br. J. Educ. Stud. 44(1), 9–26 (1996) 2. Field, R., Duffy, J., Huggins, A.: Independent learning skills, self-determination theory and psychological well-being: strategies for supporting the first year university experience. In: Creagh, T. (ed.) Proceedings of the 17th International First Year in Higher Education Conference, pp. 1–10. Queensland University of Technology (2014) 3. Zimmerman, B.J.: Becoming a self-regulated learner: which are the key subprocesses? Contemp. Educ. Psychol. 11(4), 307–313 (1986)

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4. Freeman, S., Eddy, S.L., McDonough, M., Smith, M.K., Okoroafor, N., Jordt, H., Wenderoth, M.P.: Active learning increases student performance in science, engineering, and mathematics. Proc. Natl. Acad. Sci. 111(23), 8410–8415 (2014) 5. CS231n: Convolutional Neural Networks for Visual Recognition. http://cs231n.stanford. edu/ 6. Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, United States (2016) 7. Deep Learning Specialization. https://www.coursera.org/specializations/deep-learning 8. NVIDIA Deep learning Dataset Synthesizer. https://github.com/NVIDIA/Dataset_Synthesizer 9. Gartia, A.: Project 3: Camera Calibration and Fundamental Matrix Estimation with RANSAC. https://www.cc.gatech.edu/classes/AY2016/cs4476_fall/results/proj3/html/agartia3/index.html 10. Reinforcement Learning Specialization. https://www.coursera.org/specializations/reinforce ment-learning 11. Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction, 2nd edn. MIT Press, United States (2015)

Introduction of IDEEA (International Design and Engineering Education Association) Program Kwanju Kim1(&), Manuel Löwer2, and Pedro Orta Castañón3 1

3

Hongik University, Wausan-ro, Mapo, Seoul 04066, Korea [email protected] 2 University of Wuppertal, Gaußstraße 20, 42119 Wuppertal, Germany ITESM, Av. Eugenio Garza Sada, 64849 Monterrey, Nuevo Leon, Mexico

Abstract. IDEEA program was launched in January 2019 by the universities worldwide to succeed PACE (Partners for the Advancement of Collaborative Engineering Education) program operated by General Motors from 1999 to 2018. IDEEA program provides a platform for academia and industry to meet, exchange ideas, foster collaboration and make new friendships. Scientific presentations on leading-edge research and education build an essential part of the IDEEA Forum. But an even more important aspect is the event to showcase the outcome and process of the global engineering-design collaborative project. International and interdisciplinary student teams present their product concepts – virtually and physically. They are provided a pre-conference workshop to work together in labs and to meet after several months of online collaboration. Each year, the global forum takes place at a different member institution. In 2019, the IDEEA Forum was held at Tec de Monterrey in Mexico. This year meeting will be hosted by the University of Wuppertal in Germany and takes place from July 20–23, 2020 if Covid-19 pandemic situation is resolved completely. More than 20 universities worldwide team up to create a unique educational experience for engineering and design students. Despite the issues of the time zone difference, language barrier, and differences in academic calendars, participating students have been satisfied with the program by understanding the mindset of other majors, and embracing the interests and background of students from different countries. The number of participating schools and students have been increasing over the years. Building a systematic approach to vitalize this program is a future challenge. Keywords: Engineering design Multidisciplinary


International collaboration


1 Outline of IDEEA Program IDEEA program was launched in January 2019 by the universities worldwide to succeed PACE (Partners for the Advancement of Collaborative Engineering Education) program [1] operated by General Motors from 1999 to 2018. IDEEA program [2] provides a platform for academia and industry to meet, exchange ideas, foster collaboration and © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 145–150, 2021. https://doi.org/10.1007/978-3-030-67209-6_16

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make new friendships. The 2020 project is the design of civilian drones, and a series of processes for the development of transportation vehicles, i. e. marketing-designengineering-manufacturing, has been carried out. 162 design and engineering students from 9 countries, 16 universities, 31 faculty members are participating this year and the list of universities participating is shown in Table 1. In order to systematically educate students’ engineering design ability, design thinking lectures are offered by Prof. Dresselhaus of Portland State University via YouTube [3]. After a two-week team-byteam workshop at Wuppertal University in Germany, where the Global Forum is held, the final presentation and mock-up exhibition will be conducted. However, due to the current Covid19 situation, we are also considering the final announcement online.

2 IDEEA2020 Program The main theme of this year’s project is “developing a smart modular drone concept”, and the objective of this project is to design, model, and mockup a new and innovative drone design and engineering concept based upon a selected specific drone application category. 2.1

Program Schedule of IDEEA2020

In November of last year, the program was launched with a general announcement of this year’s assignments. Figure 1 shows the timeline of this year’s drone projects. In December, we will team up with participating students with the support of universities that are willing to participate. In order to provide the knowledge of engineering design process, the design thinking course conducted by Professor Dresselhaus was provided to the students via YouTube In January 2020. In February, the entire student team formation was completed. During “the team collaboration phase 1”, from February 23rd to May 4th, when all universities around the world are offering classes, it was easier for students to conduct drone assignments without interfering with other external factors such as summer internships. The teams have usually executed empathic contextual and discovery research to define real-world application needs within their drone application category. They will then develop ideas and define concepts for the drone design that will meet their identified key category of human needs. The midterm presentation took place on May 4. The purpose of this midterm presentation was to determine the degree of collaborative activity of teams. Since then, until fourth week of July, when the final announcement is expected, is “the team collaboration phase 2”. Students finalize the engineering specifications and develop a “soft” precision mockup and a CAD model of their final drone solution concept design. They will present a series of development processes and their mockup drones on the final presentation, scheduled to be on the fourth week of July. The description stipulated so far is shown in the following figure.

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Table 1. List of participating universities in alphabetical order 1 2 3 4 5 6 7 8 9 10 11 12 13 14

2019 IDEEA Forum Hongik University, South Korea Instituto Maua de Tecnololgia, Brazil IPN ESIME Ticoman, Mexico McMaster University, Canada Shanghai Jiao Tong University, China Technologico de Monterrey, CEM, Mexico Technologico de Monterrey, Monterrey, Mexico Technologico de Monterrey, Puebla, Mexico Technologico de Monterrey, Toluca, Mexico Tongji University, China TU Darmstadt, Germany Tuskeegee University, USA University of Wuppertal, Germany

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2020 IDEEA Forum Hongik University, South Korea Instituto Maua de Tecnololgia, Brazil IPN ESIME Ticoman, Mexico Jilin University, China JSSSTU MYSORE, India McMaster University, Canada Technologico de Monterrey, Monterrey, Mexico Technologico de Monterrey, Puebla, Mexico Technologico de Monterrey, Toluca, Mexico Tongji University, China Transilvania University of Brasov, Romania TU Darmstadt, Germany University of Cincinnati, USA University of Ontario Institute of Technology, Canada UPRM, USA University of Wuppertal, Germany

Fig. 1. IDEEA 2020 Project Schedule

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Issues for Success of the Programs

The IDEEA program faces many challenges due to the diversity of the participating universities. Organizationally, different curriculum contents, semester starting dates, and media restrictions in different countries should be managed. Deliberate caution is required for the smooth operation of the program. Issues to consider during the project are listed as follows:

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Select an Adequate Topic. It is important to consider the following aspects to select the appropriate program theme: • Participating mentors’ suggestions, interests, and/or knowledge • Topics that require both design and engineering • Products that are neither too simple nor too complicated, expecting each team consists of approximately 10 participants for better communication • Technology which can be available in the next two or three years. Teaming Up. Although there was a lot of interest from participating schools, it was not easy to get a list of all the schools at the beginning of the assignment. The items considered during team configuration are as follows: • Each team will include engineering and design students. • As much as possible, students on all continent will be included in a team Role of the Mentors. The role of mentors is important to the progress of the project. This year, 13 teams are formed with two mentors for each team. Mentors usually supervise weekly meetings with their teams. Milestones for Checking Up Team Progress. In order to make sure that teams are working corporately, the midterm presentation was held on May 4th. They have presented their progress for five minutes. The same topic has been going on for two years to different students, this year’s contents seemed to be in better quality than those of last year. 2.3

The Performance of the IDEEA Program and Outcome

Last year, the IDEEA program involved 150 students from six countries, 13 universities, and 25 professors. The development of drones was carried out through multidisciplinary collaboration, and the drone was designed, produced, and tested. The final presentation and mock-up exhibition were held at the Global Forum at ITESM University in Monterey, Mexico. This year, we are working on the same drone topic as last. The final presentation and mock-up exhibition will be held at Wuppertal University in Germany. However, due to the Covid19 incident, we are also considering a final online announcement. Anticipated Outcome. The purpose of the project is for students to find solutions of innovative designs or strategies as potential answers to a given set of requirements. Students can have an opportunity to experience and advance the collaborative work of engineers and designers in developing real world products. They should go through the typical design thinking process, i. e. research – definition – ideation – making - testing [3]. During the research phase, if necessary, marketing research could be conducted and learn how many kinds of drones there are in the world now. The divergent phase and the convergent phase are conducted to define the desired drone for each team. After students decide their drone type, they deal with activities such as comparing, investigating, analyzing, and selecting among ideas from the pool in order to fulfill their own drone’s performance[4]. While fabricating their prototype, fulfilling the team’s ideas,

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Fig. 2. A rendering drawing and its idea sketch of a delivery drone presented last year forum.

they have the opportunity to use various modern manufacturing tools. The following figure shows the one example of drones presented last year (Fig. 2).

3 Conclusion The IDEEA project was initiated in 2019 by the universities which had actively participated in the GM PACE program, and the IDEEA2019 Forum was successfully held at Tec de Monterrey in Mexico. This year’s meeting will be hosted by the University of Wuppertal in Germany and takes place from July 20–23, 2020. More than 20 universities worldwide team up to create a unique educational experience for engineering and design students. The online collaboration part started in March 2020 and teams have already presented the first results of their work. The IDEEA course may face some challenges due to the diversity of the participating universities. Organizationally, different curriculum contents, semester starting dates, and media restrictions in the different countries should be managed. At the same time, the challenges of the student teams form the basis for an important teaching content of the course: the independent organization of project work in a team, across the boundaries of time zones, working culture, and language barriers. This program can provide a guideline for implementing an international, multidisciplinary collaboration course. Based on the experience from the last two years, a structured approach will be documented regarding the organization and project design, the team initiation, teaching concept, and the project outcome in terms of quality of the delivered results as well as the learning success for the students. Acknowledgements. This program was partly supported by the 2020 Hongik University Research Fund.

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References 1. 2. 3. 4.

PACE program homepage. https://www.pacepartners.org. IDEEA program homepage. https://www.ideea.network. Professor Dresselhaus’ Design Thinking homepage. https://billdresselhaus.fatcow.com. Larsen, P., Fernandes, J., et al.: A multidisciplinary engineering summer school in an industrial setting. European Journal of Engineering Education 34(6), 511–526 (2009)

Online Teaching and Learning in India During Lockdown and Its Impact on Teaching Practices Sherine Akkara(&) and Mallikarjuna Sastry Mallampalli Hindustan Institute of Technology and Science, Padur, Chennai, India [email protected]

Abstract. COVID-19 has a disruptive impact globally on every aspect of human life and Higher Education is no exception. It has thrown a challenge to the existing e-learning infrastructure in India in reaching out to the students in different areas, completing the syllabus and assessing students’ performance. The present research aimed at studying a) the efficacy of the existing infrastructure facilities for providing online collaborative learning for engineering undergraduate students in both urban and rural areas, b) faculty capability in adapting to online teaching and assessing, c) students’ readiness for online collaborative learning and d) the performance of the students in online class tasks. Different Learning Management Systems like MS Teams, Moodle and Google Classroom and video conferencing platforms like WebEx, Zoom, Google meet, Google hangouts and WhatsApp were used to conduct the online classes during the pandemic. The data for the study was collected from students and faculty from both urban and rural areas through mixed methods approach. The results indicated that most participants used mobiles for attending online classes. Connectivity was a major issue among others in infrastructure facilities. It also revealed a significantly greater impact on the teaching practices of urban teachers than on teachers from rural areas. However, students from both the areas showed greater interest in attending online classes. Keywords: Computer supported learning
Online collaborative learning Blended learning
Interactive learning
Learning during pandemic




1 Introduction National lockdown in India during COVID-19 thrust upon online learning on 35 million higher education students [1] across the country leading to a paradigm shift in the second largest higher education system in the world. Before presenting how the students and faculty from both urban and rural areas responded to the crisis and continued their efforts despite many technological, psychological and pedagogical issues, it is essential to understand higher education facilities in the country, information and communication technology (ICT) initiatives in higher education, and the existing internet infrastructure in urban and rural areas.

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Higher Education Scenario in India

With more than 53,600 higher education institutions, 35 million students and 1.4 million teachers, India’s higher education stands second in the world [1]. According to the Department of Higher Education, Government of India, there are 993 universities, 41,901 colleges and 10,726 standalone institutions. Out of these more than 60% colleges are situated in rural areas [2]. 1.2

E-Learning Facilities in Higher Education

Digital India campaign of Government of India aims at providing access to quality educational resources through several platforms for the disadvantaged sections of people. People with a digital device and internet connection can access rich learning resources like: i) National Digital Library of India with 38 million books in more than 200 languages, and millions of educational resources at all levels; ii) Swayam, a national online learning portal with many MOOCs for high school and college students; iii) National Program on Technology Enhanced Learning (NPTEL), the most subscribed educational channel on You Tube with more than 1.5 million subscribers and more than 54,000 h of video content and a number of MOOCs for engineering students; and iv) Virtual labs for engineering students and Spoken tutorials for developing technical skills [4]. 1.3

Existing Internet Infrastructure in India

India is the second largest online market with over 560 million internet users and it is estimated to reach 650 million users by 2023. Though the country has large internet base, the internet penetration stands around 50% in 2020 [5]. India is also the second largest market for e-learning after the United States and it is expected to grow rapidly [6].

2 Purpose of the Study The present research aimed at studying a) the efficacy of the existing infrastructure facilities for providing e- learning for engineering undergraduate students in both urban and rural areas, b) faculty capability in adapting to online teaching and assessments, c) students’ readiness for online collaborative learning and d) the performance of the students in online classes and internal assessments. It focuses on the real life experiences of instructors and learners while addressing the above research questions.

3 Literature Review This brief literature review presents a relevant definition of online learning for the present context, stakeholders, current theories of online learning, and the most crucial factors for success in online learning. The definition of e-learning undergoes a revision with the evolution of technologies (from Web 0 to Web 4.0). E-learning can be defined as the development of knowledge

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and skills through the use of information and communication technologies (ICTs), particularly to support interactions for learning, interactions with content, learning activities and tools and other people [8]. For the purpose of the present paper, online learning and e-learning have been used synonymously. Blended Learning (BL) is defined as the combination of traditional face-to-face teaching methods with authentic online learning activities [9]. BL may not be the most appropriate term for the current study as face-to-face and online teaching did not happen simultaneously as online teaching was thrust upon the system as an alternative method by the pandemic. Literature suggests various parties that constitute the world of e-learning as stakeholders. Anyone who is a constituent part of an organization is a stakeholder [10]. Broadly, four stakeholders can be identified in the world of e-learning. They are: a) learners, b) instructors, c) designers and d) implementers [7]. Education institutes and employers come under implementers. Most of the learning theories focus on the learners’ needs and some on the learner and instructor together. E-learning programs can be more effective if the program is designed and implemented keeping the interest of the learner and his learning style in mind. Instructional strategies and the choice of technology play a vital role in learning [11]. Many learning theories insist on a three-dimensional interaction of learner with the course content, co-learners and the instructor [12]. From the literature on e-learning theories, it is observed that the concept of learning is associated not only with the aspects of cognition but also various psychological, environmental and technical aspects which have a profound influence on the world of digital learning [13]. The present study investigates whether the essential requirements for online teaching and learning exist for an immediate switch over from face-to-face classroom teaching to online teaching in a vast country like India where the access to Higher Education is unequal in spite of the best efforts of the government. Providing infrastructure to support online classes is analogous to building a new physical campus. Online teaching and learning requires similar support system both for teachers and learners as well. If these infrastructure considerations are not addressed properly, the success of the entire learning process will be jeopardized [14]. There is little research on how the higher education institutions respond to a deepening crisis like the COVID19 and how the institutions, teachers and learners respond and adapt to the new ways of online learning and teaching in the absence of previous experience.

4 Approach For the purpose of the present study two reputed engineering institutions accredited by National Assessment and Accreditation Council (NAAC) and National Board of Accreditation (NBA) were selected from two different parts of the country. One is located in Chennai city and the other at a small town located in Andhra Pradesh. The participants were the first year students of four year engineering course in different branches of engineering. They were taught the prescribed subjects of their curriculum which included technical writing skills, report writing in English and along with the core subjects. Mixed methods approach was adopted and two instruments were used: a) questionnaire to 200 students from each institution and b) semi-structured interviews

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with 30 faculty members (15 from urban and 15 from rural areas) teaching different subjects. Efforts were made to obtain data even from the people who did not have the internet connection to attend the online classes and the same was recorded. The fourquadrant framework of India’s biggest online learning platform Swayam [4] was taken as a model for analysing the online courses design and delivery during the pandemic. The quadrants of the course design include: a) e-tutorial (video), b) e-content (etextbook, PDF, illustrations, documents), c) Assessments (problem/solution, MCQs, assignments, and Quizzes and d) Discussion. Instructors and learners were interviewed on how they felt and experienced the online teaching and learning during the pandemic.

5 Results This section presents the results of the study in the order of research questions that were studied. The first research question addresses efficacy of the internet infrastructure in the country. Figure 1 presents how the learners from urban and rural areas attended online classes during the lockdown period in the order of the device, platform and the internet connection they used. Smartphone was the most widely used device both in rural and urban areas making online learning experience accessible to the majority of the students. Learners studying in the urban college were provided with a Learning Management System (LMS), Microsoft Teams whereas rural students attended the online classes through different video conferencing applications chosen by their respective instructors. Most students used mobile hotspot (urban 74.4% and rural 66%). There was only 2% of difference in the use of broadband between urban and rural areas. This indicates the spread of BSNL broadband services in villages and small towns.

Fig. 1. Device, Platform, and mode of internet connection used by students

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The second research question aims at understanding how the instructors responded and adapted to online teaching. Instructors responded positively to the call of the nation and used different platforms for online teaching. As shown Fig. 2, the previous online teaching experience was a bit higher in the case of faculty from urban areas (40%) than it was in the rural areas (13.33%). Instructors from urban areas were at an advantage as they encountered fewer connectivity issues and were provided with an LMS for delivering the lessons. Urban faculty used collaborative tools better (86.66%) than the faculty in rural areas (33.33%). Lack of training in using the collaborative online teaching tools and the absence of an LMS were reported as the major factors badly impacting their teaching in addition to the poor connectivity and frequent breakdown in the internet connection. The faculty at urban areas easily adapted to online teaching whereas faculty from rural areas found it challenging. They shared their presentations through Whatsapp and email. The third research question about students’ readiness for online collaborative learning received equally positive response. Students from both urban and rural areas attended the online classes regularly, completed collaborative tasks and assignments successfully, and the attendance was above 75% to most of the classes in the urban areas. The frequent interruptions in the connectivity had a negative impact on the rural students’ attendance to the online classes but they answered all the questions in the asynchronous mode and completed the assignments. More than 84% of students from both the areas were satisfied with the syllabus completion and received learning resources from their respective faculty. As shown in the Fig. 1 in the results section, majority of urban students were taught on a Learning Management System, whereas, most rural students received lecture notes, power point presentations and links to You Tube videos through WhatsApp groups and email.

Fig. 2. Instructors’ online teaching experiences and preferences

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The fourth research question is related to the performance of the participants in the online classes and internal assessments. More than 93% of urban students completed all the quizzes and assignments in time and nearly 77% students from rural areas completed the internal examinations. The teachers from both the areas reported almost the same level of performance in the internal examinations. The end semester examinations were not yet completed in any part of the country during the period of the present study.

6 Discussion The success of online learning depends on the contribution of the four stakeholders: learners, instructors, designers and implementers. All the stakeholders have a vital role to play in making the collaborative effort successful. While the learners are responsible for their learning, instructors play a crucial role in sustaining the motivation and autonomy of learners. Ensuring the right and reliable technology is the key responsibility of the implementers. It requires not only equipment and training, but also enormous amount of planning and anticipation of needs. However, in the present situation, online learning has been thrust upon the nation with the abrupt closure of educational institutions across the country during the pandemic. Even though the potential of global delivery of e-learning is emphasised, the real potential of e-learning much depends on the local conditions [15]. In a country like India, which is as diverse as Europe, the environment for e-learning differs from place to place. Indian internet infrastructure is not fully equipped for a paradigm shift to online learning necessitated by the pandemic situation, and connectivity and signal issues are the most prevailing problems as reported by Quacquarelli Symonds (QS) [16]. The present study revealed that the gap between the engineering institutions located in urban and rural areas. Better broadband connectivity in the urban areas, Learning Management Systems (LMS) provided by the institutions have kept the students in urban areas at a greater advantage than the students in rural areas. Within a few weeks, the country witnessed a flurry of online teaching activity using whatever means of communication that was available to the teachers to reach out to the students and complete the syllabus and internal assessment. There were a series of Faculty Development Programmes (FDP) on online teaching and learning and the use of collaborative tools like Google Drive, Google documents and Moodle software for creating online learning management system. Majority of faculty from both the areas reported keen interest in learning online teaching and learning and using the LMS effectively. Instructors from rural areas were asked to complete the pending syllabus and conduct internal assessment tests using whatever communication channel they could use. Instructors in the urban areas were provided with an LMS and they had little difficulty in delivering the courses and interacting with the students in a systematic way, whereas instructors from rural areas created WhatsApp groups for communication and shared learning resources. There were many pedagogical and psychological challenges the instructors from rural areas had to face with the lack of support systems. The instructors had to take the entire responsibility of instructional design, technical

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issues while delivering the lessons with unreliable network connectivity. More than 66% faculty from rural areas could not avail any other applications except email and WhatsApp for sharing learning materials and links to You Tube videos. 21 out of 30 (70%) instructors both from rural and urban areas felt they were teaching in a vacuum when they could not see the faces of the learners on their screen due to the issues of bandwidth. The quality of online programmes depends on the professional development of the faculty and the timely response to the needs of online teachers [17]. Delayed responses from implementers and technicians had a negative impact on the pedagogical practices of the instructors. However, from the interviews with the teachers, teachers from the urban areas showed greater resilience and flexibility in adapting to online teaching in the midst of ongoing crisis than teachers from rural areas, From the results of the study it is evident that students from both the areas showed equal levels interest and performance in spite of poor connectivity problems. One of the striking features of online classes and all the webinars during the pandemic was the muting of both the video and audio functions of the video conferencing tools of the participants and only the presenter was allowed to use the video because of the bandwidth issues. Connectivity issues led to frequent interruptions and abrupt closure of classes and rescheduling of the classes resulting in loss of motivation. The severity of the problem was worse in rural areas where more than 85% respondents relied on mobile internet. The frequent interruptions in the network resulted in the loss of interest in the classes and have a negative impact on the anxiety of the learners. Some learners needed to be counselled and their doubts were clarified in separate individual sessions, which resulted in teachers sticking to the computers or mobile phones most of the time. Interactivity is cited as single most important factor critical for success in e-learning. Synchronous learning has facilitated immediate clarification of doubts. However, rural students missed that opportunity due to the frequent network issues and they had to rely on asynchronous mode of communication. Engaging the learner and sustaining motivation is a critical factor of online learning and teaching and it remained a distant dream for many teachers from rural areas. However, when asked about their preferences after COVID-19, more than 66% students preferred blended courses to direct classroom and complete online courses. Though most of the (more than 89%) students from the areas were complete the given assignments and quizzes, they expressed unwillingness in taking the semester end examinations as the system was not foolproof from dishonest practices while writing the examinations.

7 Conclusion E-learning with its proven benefits of flexibility, accessibility and low cost could be the most preferred choice for many in higher education, especially in a country like India it has great potential in offering quality education for all. As discussed in the paper, elearning is a collaborative effort of all the stakeholders and it demands a holistic approach to make it successful. Exposure to online learning was one of the beneficial impacts of COVID-19. Online education has leapfrogged during the pandemic from face to face to classroom teaching to direct online teaching and learning. Many Indian

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educationists consider blended courses as a suitable model and it amply reflected in the recent decision of the University Grants Commission (UGC) in making 25% of the syllabus completion online, leading the way for blended learning experience in the country. In addition, equipping the institutions with LMS, training the faculty in using LMS and online teaching, and integrating the existing MOOCs of NPTEL and Swayam with the regular courses will be a game changer in online education in the country.

References 1. Linney, S.: How Will Changes in India Affect Inbound and Outbound Student Mobility?. QS. https://www.qs.com/india-become-higher-education-force/ Accessed 28 May 2020 2. Aishe.gov.in. 2020. MHRD Dashboard. http://aishe.gov.in/MHRDDashboard/home Accessed 25 May 2020 3. Mhrd.gov.in. 2020. Technology Enabled Learning | Government of India, Ministry of Human Resource Development. https://mhrd.gov.in/ict-initiatives Accessed 20 May 2020 4. Swayam.gov.in. 2020. Swayam Central. https://swayam.gov.in/nc_details/NPTEL Accessed 25 May 2020 5. Statista. 2020. Topic: Internet Usage In India. https://www.statista.com/topics/2157/internetusage-in-india/ Accessed 25 May 2020 6. Ibef.org. 2020. Education & Training Sector In India: Education System, Growth & Market Size | IBEF. https://www.ibef.org/industry/education-sector-india.aspx Accessed 20 May 2020 7. Choudhury, S., Pattnaik, S.: Emerging themes in e-learning: a review from the stakeholders’ perspective. Comput. Educ. 144, 103657 (2020) 8. Tîrziu, A.M., Vrabie, C.: Education 2.0: e-learning methods. Procedia Social Behav. Sci. 186, 376–380 (2015) 9. Davis, H.C., Fill, K.: Embedding blended learning in a university’s teaching culture: experiences and reflections. Br. J. Educ. Technol. 38(5), 817–828 (2007) 10. Wagner, N., Hassanein, K., Head, M.: Who is responsible for e-learning success in higher education? a stakeholder’s analysis. Educ. Technol. Soc. 11(3), 26–36 (2008) 11. Clark, R.E.: Media will never influence learning. Educ. Technol. Res. Develop. 42(2), 21–29 (1994) 12. Mayer, R.E., Moreno, R.: Nine ways to reduce cognitive load in multimedia learning. Educ. Psychol. 38(1), 43–52 (2003) 13. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Quarterly, pp. 425–478 (2003) 14. Schroeder, R.: Institutional support infrastructure for online classes. Metropolitan Universities 12(1), 35–40 (2001) 15. Ali, G.E., Magalhaes, R.: Barriers to implementing e-learning: a kuwaiti case study. Int. J. Train. Develop. 12(1), 36–53 (2008) 16. QS. 2020. How Universities Are Embracing Online Learning During The Coronavirus Outbreak - QS. https://www.qs.com/how-universities-are-embracing-online-learning-duringthe-coronavirus-outbreak/ Accessed 24 May 2020 17. Baran, E., Correia, A.: A professional development framework for online teaching. Techtrends Tech Trends 58, 95–101 (2014). https://doi.org/10.1007/s11528-014-0791-0

The Role of Educational Neuroscience in Distance Learning. Knowledge Transformation Opportunities Spyridon Doukakis1(&) and Evita C. Alexopoulos2 1

Department of Informatics, Ionian University, Corfu, Greece [email protected] 2 Pierce-The American College of Greece, Athens, Greece [email protected]

Abstract. Educational neuroscience is an interdisciplinary field that brings together researchers from neuroscience, cognitive science, psychology, and education as well as teachers of all disciplines with the purpose of identifying methods and techniques, using experiential, social and biological evidence to modify education. In this paper, an attempt is made to find connections between educational neuroscience and distance education so that a) student engagement is increased, b) formative assessment for learning is enhanced, c) student mistakes are exploited to a greater degree and d) to incorporate approaches that enhance opportunities of multiple representations for the benefit of both students and teachers. Furthermore, reducing speed in order to promote creativity along with collaboration among students can transform teachers’ perspective with the goal of increasing activities in all four sectors. The article ends with suggestions regarding the professional development of teachers in distance education and educational neuroscience, according to the Technological Pedagogical Content Knowledge. Keywords: Distance learning


Educational neuroscience
TPACK

1 Introduction For many decades now, research in the field of cognitive science, psychology and education has offered substantial findings in the areas of perception, memory, language, and attention, all of which affect the educational process. In the last two decades, neuroeducation has advanced these findings as it attempted to delve into the function of the brain and the mind [1]. In particular, the use of brain imaging techniques such as electroencephalography (EEG), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) has further advanced the understanding of neural mechanisms of human development and learning. It is as a result of these findings and the impact they had on education that the new, interdisciplinary research field of neuroeducation has been founded. Neuroscientists, educationists from various disciplines, and cognitive scientists collaborate in order to investigate and subsequently apply neuroscientific findings in educational contexts [2]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 159–168, 2021. https://doi.org/10.1007/978-3-030-67209-6_18

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One of these educational contexts is distance learning. Within this context, there is a physical separation between students/learners and educators/teachers [3]. Furthermore, in order to establish and facilitate communication between learners and teachers in distance learning, a variety of technological tools are used. The particular characteristics of distance learning have led to the development of educational programmes, which prepare teachers so that the latter can acquire the necessary background to teach and enhance their students’ learning. Even though initially distance learning targeted specific groups of students (working students, students living in isolated areas, students with physical handicaps), over the past few years, it has developed to such a degree that it has either been included in a growing number of traditional educational contexts or offered as a separate unit, independent of other educational types (as complementary asynchronous or synchronous distance learning). During the academic year 2019–2020, educational systems around the world were affected by the COVID-19 pandemic and, as a result, governments everywhere had to seek alternative modes of education as the existing school/university buildings could not be used. According to data provided by UNESCO, on the 4th of April 2020, 1,598,099,008 learners in 194 countries, that is 91.3% of the total number of enrolled learners internationally were not able to be to the existing school/university buildings by the pandemic (pre-primary, primary, lower-secondary, upper-secondary, tertiary education levels) [4]. This was the day with the highest percentage of potentially inactive learners in a traditional educational setup, if there was no access to distance learning. Thus, it can safely be claimed that distance learning played a crucial role in the operation of schools during the period of the pandemic. It can also be assumed, however, that in many cases of transitioning from traditional to distance learning, the systematic training and education of teachers in the pedagogy and methodology of distance learning was absent. Therefore, teachers carried out their teaching based on their own experience or did one of the following: a) formed learning communities and exploited their experience; b) attended synchronous meetings on distance learning; c) took the initiative to attend MOOCs and other professional development courses. All these actions enhanced yet another mode, that of emergency remote teaching in relation to distance learning/ education. In this article, an attempt will be made to relate the research findings of educational neuroscience with issues pertaining to distance learning, with the ultimate goal of reinforcing and facilitating student learning. Therefore, in the next section, research findings from educational neuroscience that can enhance distance learning will be outlined. Subsequently, a proposal will be put forward for the reinforcement of teachers so that they can select appropriate technological tools in distance learning as these are defined by the principles of educational neuroscience. Finally, future research topics will be suggested aiming at the transformation of teacher knowledge concerning educational neuroscience and distance learning.

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2 Educational Neuroscience and Distance Learning Educational neuroscience is an interdisciplinary field that brings together researchers from neuroscience, cognitive science, psychology, and education as well as teachers of all disciplines with the purpose of identifying methods and techniques, using experiential, social and biological evidence to modify education. In recent years, it has been integrated into teacher training with the aim of transforming educational practices, strengthening the operating framework of the classroom (physical or virtual), and, above all, improving learning [5]. 2.1

Brain and Learning

Education is carried out in a school environment, but learning is achieved in the learning systems of the brain. More specifically, one of these systems, is the brain’s hippocampus which rapidly alters its connections and produces episodic or autobiographical memory by recording snapshots [6]. Furthermore, within the cortex, the brain identifies patterns (spatial and temporal), the so-called concepts and learns associations between motor responses and perceptual information. Certain associations between stimulus and response are unconscious and contain emotional structures that are found in the human brain. Additionally, the brain is trained to control content-specific systems in the posterior cortex so as to integrate planning with emotion. At the same time, another reward-based system allows our brain to concentrate on actions that will produce desirable outcomes and avoid unpleasant situations. Furthermore, a procedural system exists that permits activities we frequently repeat, such as how to read, how to drive, how to swim, to form part of our memory. Apart from continuous practice, the learning of these automatic skills requires the looping outer-to-inner circuits which connect the cortex to the thalamus, through the basal ganglia and back again as well as the cerebellum [7]. Moreover, the brain can exploit existing widespread circuits for perception and understanding so as to acquire/learn skills by observing others and modelling their behaviours/actions. Finally, the brain can also exploit widespread circuits to formulate new concepts and new structures through instruction. Most of the activity above can be carried out within seconds or minutes, while some will require a lot more time. All of the above-mentioned systems operate in a unified manner and respond differently over time as well as to different instructional frameworks/styles. Furthermore, their function can be influenced by other factors such as the motivational and emotional state of the individual/learner. Educational neuroscience seeks to enhance the ability, the motivation, and the attention of the learners/students so that the latter can achieve the desired learning outcomes as these are defined within a specific teaching and learning framework/in each teaching and learning situation/context. Researcher Howard-Jones, and his colleagues focus on three issues: student involvement, scaffolding/ building knowledge and knowledge consolidation so that it is permanent, accessible and useful [8]. Within the context of online teaching, teachers need to be aware of the ways the above three goals can be achieved so that learning can be successful.

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Brain and Distance Learning

A key element in the achievement of these goals is the plasticity of the brain and its capacity to develop through pathways [9]. A student’s brain is affected not only by the environment and its ongoing activities but also by genetic factors. Distance education environments offer multiple opportunities for a variety of activities that can enhance student involvement. In particular, the teacher can make use of such tools as the private chat, the group chat, the shared whiteboard in such ways that students are actively involved and building knowledge. For instance, the teacher can give students a question or a problem to research/explore/investigate/reflect on for a few minutes and ask them to send him/her a message through the private chat. This way a) all students engage in the activity since the teacher has asked for a response; b) if a student sends a wrong answer, through the private chat again the teacher can prompt him/her to try again; c) students do not ‘expose’ themselves to the group but only to the teacher; and d) all students have to submit an answer and cannot ‘agree with the previous answer,’ a common practice in the physical classroom, as students do not have access to each other’s answers. Another method/technique is using the group chat for a similar problem-solving activity. This time though the teacher asks students to use the group chat but asks them not to send their answer until they are told to do so. This way, a) and d) from above are accomplished as all students are involved in and must complete the activity independently. A third approach is the use of multiple shared whiteboards. More specifically, each student works on their own whiteboard, drafting their own answer and receiving differentiated support suitable for their specific needs. This way, total student participation is achieved without exposure to the group. What is more, neural pathways and connections can be developed while opportunities for the acquisition of experience and the building of new knowledge is provided through ‘Think’, ‘Practice’, ‘Interpret’, ‘Apply’, ‘Evaluate’, and ‘Create’. Furthermore, the teacher can take advantage of tools for diagnostic, formative, and summative assessment in order to establish his/her students’ prior knowledge and their development as learners. According to findings from neuroeducational research, assessment can play a key role in determining a person’s knowledge, as well as in shaping this knowledge [10]. Through the exploitation of tools for diagnostic, formative, and summative assessment and the use of frequent and non-threatening assessment, along with feedback on the understanding of an idea or concept, the teacher can identify both prior knowledge and pre-requisite (possibly informal) knowledge and keep track of his/her students’ development. Assessment plays an essential part in memory consolidation and could be proven to be a suitable methodology for the storage of important, new information in the student’s memory during the educational process. In the context of distance education, the teacher has a variety of tools at his/her disposal so as to assess students’ prior knowledge and pre-requisite (possibly informal) knowledge as well as observe their development. The use of polling during the lesson with the use of True/False questions and the option of creating multiple choice or matching-sentences quizzes during the lesson or for the assessment of students after the lesson provide students with opportunities to enhance their

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memory, reflect on what they have comprehended as well as on what they need to work on further and much else. At the same time, the option of assessing through gaming, always taking into consideration students’ abilities, allows for more student involvement and lesson differentiation. For instance, a quick polling test where only the teacher sees the answers of all students, introduces an element of fun (who will get the most correct answers in the fastest). Besides, posing questions that can take more than one correct answer will motivate students. Following such a process, the teacher can create new student working groups, according to the answers given in the poll, as well as redefine his/her teaching practice responding to his/her students’ needs. These processes can be tried out within the framework of lesson planning and may include challenging and non-trivial questions while the score students will receive will not be of primary importance but will be used exclusively for their formative assessment. From an educational perspective, brain development can also be enhanced through the exploitation of mistakes. Within the context of distance learning, exploiting student mistakes that might have been made while they were engaging in a learning activity or observed while they were assessed for learning can positively contribute to the learning experience. For this positive outcome to be achieved during distance learning, teacher and students discuss and review their mistakes or work on specific obstacles that cause misunderstandings [11]. Individually or in groups, students identify their mistakes, communicate with their teacher through the private chat and in a more fun way, asking questions like: “How many mistakes can you spot and subsequently correct?” identify all of the mistakes in a sentence, a solution, an approach and move on to correcting them [12]. This way, the teacher can carry out a simultaneous assessment of all students or students can create their own artefact to illustrate the way in which they worked so as to highlight their strategies. Over the past few decades, special emphasis has been given to students’ learning styles and the need to facilitate learners by presenting new knowledge in their preferred learning style. Nevertheless, current research in neuroeducation and learning has demonstrated the idea that “individuals learn better when they receive information in their preferred learning style (e.g. auditory, visual, kinesthetic)” to be a neuromyth while what is the case is that “individual learners show preferences for the mode in which they receive information (e.g. visual, auditory, kinesthetic)” [13]. From this perspective then, and according to the research findings in the field of neuroscience, neural pathways and learning are optimized when the learner has the opportunity to consider a concept or idea using a multidimensional approach, as different areas of the brain are activated depending on the activity one engages in as well as on the way the learner carries out this activity. Within the context of distance education, a multidimensional approach can be attempted through a variety of approaches of teaching and learning. It is essential for lesson planning to incorporate an array of activities with a range of exploratory and problem-solving, both open and closed type, strategies. This way, students will carry out activities using a variety of approaches. For instance, it is interesting for students to approach and solve the same problem in different ways: a) using mathematics, b) using diagrams, c) using algorithms (coding) and at the same time to write a story about this problem or to create an image/ picture, a video or an artefact [14].

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From all the above, it is obvious that within the context of distance learning, the teacher must pay attention to: a) the involvement of the student in the learning process, b) the manner in which s/he will incorporate assessment in the learning process, c) the exploitation of teaching obstacles/student mistakes, and d) the multidimensional approach of presenting and working with a new concept. These four principles of distance learning need to operate in an appropriately designed working environment, the properties of which will be discussed in the next section. 2.3

Distance Learning and Working Environment

The real framework for distance education to take place according to the four principles discussed above inevitably leads to two more issues. The first issue relates to the ‘speed’ with which an online class operates. The role of speed is definitive with regard to: a) creativity and flexibility and b) how students learn from working together in class. According to current research findings in the field of neuroeducation, working under pressure causes a) anxiety and b) the impression that “my mind has stopped working.” On the contrary, it appears that learning is enhanced when students approach concepts and ideas with creativity and flexibility [15, 16]. Consequently, the working environment in distance education must operate in such a way that students are provided the time they need in order to be creative. Additionally, speed affects learning and the brain. According to the research, when learning is attempted at a fast pace, existing neural pathways may be boosted and new neural pathways may be created, but these may be easily lost as the four principles presented in the previous section cannot be applied. For this reason, in distance education, working time needs to be granted without a request for information reproduction or speed of action since the development of neural pathways and synapses is a slow process. The second issue concerns student collaboration. In the online class, collaboration among students is significant for two reasons: a) it allows them to share their concerns, ideas and, finally, to successfully study the problem they have been given and b) it helps them understand and recognize how others function. In particular, within the context of learners’ learning development, collaboration among students helps each one individually recognize that others too have some or many difficulties in learning. Students, therefore, will be in a position to think critically about their own learning and to keep in mind that learning is a procedure where students come up against similar or identical problems/obstacles which they are called upon to overcome. At the same time, though, students are given the opportunity to make connections between ideas and to formulate opinions. In other words, instead of students recalling knowledge, they are given the chance to explore ideas and collaborate so as to solve problems. This type of framework is common in the physical classroom, too. Findings in the field of neuroscience have proven that when people collaborate, the medial orbitofrontal cortex and frontoparietal network are activated and, as a result, the development of executive functions is promoted [17, 18]. This is why these regions of the brain are also referred to as ‘social brain’ and demonstrate the value of the sociocultural approach to learning [19] and the need to provide students with such opportunities in multiple ways. Collaboration, therefore, is a complicated task which plays a crucial role in learning, in

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goal accomplishment, and in the development of the brain. Distance education offers the context for such collaboration as it allows for the assignment of students to separate rooms through the use of modern learning tools, decision-making within a team, and presentation of the teams’ results to the entire class.

3 Discussion Distance education in secondary and tertiary education, especially during the pandemic, was defined as a practical and effective solution so that students in both sectors would not be left outside the educational process. According to a recent study in the European Union, for two thirds out of the approximately 5000 teacher-respondents this was their first experience of distance education [20]. In the same research, teachers appear concerned about whether students, especially the disadvantaged and the young ones, will stay engaged and continue participating in online classes. Within this context, it is of crucial importance for teachers to be prepared adequately so that they are able to work according to the principles of a) educational neuroscience and b) distance education, making the right use of the available digital tools. Due to the characteristics of distance education and the mediating role digital tools play, taking advantage of the Technological Pedagogical Content Knowledge (TPACK) framework might contribute to the enhancement and professional development of teachers so they can work online (Fig. 1). The framework is an attempt to assist teachers to promote effective pedagogical practice in technology enhanced environments [21].

Fig. 1. TPACK Framework.

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According to the TPACK framework, apart from the content-knowledge teachers are called on to teach, they need to have pedagogical competence in distance education and in the principles of educational neuroscience as well as in the use of technological tools necessary in their teaching. Special significance is attributed to the overlapping sectors of the cycles where new types of knowledge appear (Pedagogical Content Knowledge, Technological Content Knowledge, Technological Pedagogical Knowledge) and the Technological Pedagogical Content Knowledge (TPACK) of the teacher forming in the overlap among the three cycles. As a result, incorporating the principles and tools of distance education in teachers’ professional development, the teacher is given the opportunity to acquire Technological Pedagogical Content Knowledge in Distance Learning. In conclusion, it could be argued that because of the nature of distance education, it is important for teachers’ professional development to be oriented towards: a) knowledge in relation to technological tools necessary for the online teaching of specific content and b) knowledge in relation to educational neuroscience so that they can exploit effective teaching practices and manage their online class optimally.

4 Conclusion In this article, an attempt has been made to show that educational neuroscience with its principles and the existing research findings can enhance distance education considerably. Four important sectors have been defined which, according to the findings in educational neuroscience, can promote learning in distance education. Initially, the focus was given to the plasticity of the brain and its capacity to develop through pathways. Within this context, student involvement in the learning process plays a definitive role in the development of the brain. Then, the value of diagnostic, formative and summative assessment was established; through these types of assessment, the teacher has the chance to explore the prior knowledge of his/her students as well as their learning development, with the ultimate goal of assessing for learning as well as of learning itself. Furthermore, the importance of exploiting mistakes and obstacles in learning was pointed out as mistakes can activate certain areas of the brain and assist in the memory retention. The fourth sector is the multidimensional approach of concepts and activities. This approach allows students to become involved with various reproductive models and thus to operate different areas of the brain. Crucial in the activation of the four sectors are two factors: speed and collaboration. More specifically, it was found that in the context of distance education, working time needs to be granted without a request for information reproduction or speed of action since the development of neural pathways and synapses is a slow process. Moreover, it was obvious that collaboration is a complex task and plays a crucial role in learning, in the achievement of goals and in the brain’s development.

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Finally, it seems that the significant findings in educational neuroscience research demand that teachers are appropriately trained. Within this framework, the development of training programmes according to the TPACK framework may contribute to the preparation of teachers to teach in distance education structures according to the principles of educational neuroscience.

References 1. Ansari, D., Coch, D., De Smedt, B.: Connecting education and cognitive neuroscience: where will the journey take us? Educ. Phil. Theory 43(1), 37–42 (2011) 2. Nouri, A.: The basic principles of research in neuroeducation studies. Int. J. Cogn. Res. Sci. Eng. Educ. 4(1), 59 (2016) 3. Moore, M.G., Resta, P., Rumble, G., Tait, A., Zaparovanny, Y.: Open and distance learning: Trends, policy and strategy considerations. UNESCO (2002) 4. https://en.unesco.org/covid19/educationresponse Accessed 29 May 2020 5. Howard-Jones, P.A.: A multiperspective approach to neuroeducational research. Educ. Phil. Theory 43(1), 24–30 (2011) 6. Thomas, M.S., Ansari, D., Knowland, V.C.: Annual research review: educational neuroscience: progress and prospects. J. Child Psychol. Psychiatry 60(4), 477–492 (2019) 7. Rosenberg, M.D., Martinez, S.A., Rapuano, K.M., Conley, M.I., Cohen, A.O., Cornejo, M. D., Hagler, D.J., Anderson, K.M., Wager, T.D., Feczko, E., Earl, E.: Behavioral and neural signatures of working memory in childhood. J. Neurosci. 40(26), 5090–5104 (2019) 8. Howard-Jones, P., Ioannou, K., Bailey, R., Prior, J., Yau, S.H., Jay, T.: Applying the science of learning in the classroom. Profession 18, 19 (2018) 9. Rees, P., Booth, R., Jones, A.: The emergence of neuroscientific evidence on brain plasticity: Implications for educational practice. Educ. Child Psychol. 33(1), 8–19 (2016) 10. Hwang, G.J., Chang, H.F.: A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students. Comput. Educ. 56(4), 1023– 1031 (2011) 11. Moser, J.S., Schroder, H.S., Heeter, C., Moran, T.P., Lee, Y.H.: Mind your errors: Evidence for a neural mechanism linking growth mind-set to adaptive posterror adjustments. Psychol. Sci. 22(12), 1484–1489 (2011) 12. Nottingham, J.: The learning challenge: How to guide your students through the learning pit to achieve deeper understanding. Sage Publications, London (2017) 13. Newton, P.M., Miah, M.: Evidence-based higher education–is the learning styles ‘myth’important?. Front. Psychol. 8, 444 (2017) 14. Boaler, J.: Urban success: a multidimensional mathematics approach with equitable outcomes. Phi Delta Kappan 87(5), 364–369 (2006) 15. Ferguson, M.A., Anderson, J.S., Spreng, R.N.: Fluid and flexible minds: Intelligence reflects synchrony in the brain’s intrinsic network architecture. Network Neurosci. 1(2), 192–207 (2017) 16. Novick, J.M., Bunting, M.F., Engle, R.W., Dougherty, M.R. (eds.): Cognitive and Working Memory Training: Perspectives from Psychology, Neuroscience, and Human Development. Oxford University Press, USA (2019) 17. Lu, K., Xue, H., Nozawa, T., Hao, N.: Cooperation makes a group be more creative. Cereb. Cortex 29(8), 3457–3470 (2019)

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18. Decety, J., Jackson, P.L., Sommerville, J.A., Chaminade, T., Meltzoff, A.N.: The neural bases of cooperation and competition: an fMRI investigation. Neuroimage 23(2), 744–751 (2004) 19. Wertsch, J.V., Toma, C.: Discourse and learning in the classroom: a sociocultural approach. In: Constructivism in education, pp. 177–192 (2012) 20. https://www.schooleducationgateway.eu/en/pub/viewpoints/surveys/survey-on-onlineteaching.htm Accessed 29 May 2020 21. Koehler, M.J., Mishra, P., Yahya, K.: Tracing the development of teacher knowledge in a design seminar: Integrating content, pedagogy and technology. Comput. Educ. 49(3), 740– 762 (2007)

Interdisciplinary Megaprojects in Blended Problem-Based Learning Environments: Student Perspectives Henrik Worm Routhe1, Lykke Brogaard Bertel1(&) , Maiken Winther1, Anette Kolmos1 , Patrick Münzberger2, and Jesper Andersen1 1

Aalborg University, Aalborg, Denmark {routhe,lykke}@plan.aau.dk 2 Aalborg, Denmark

Abstract. This paper presents research and initial findings on the launch and first two rounds of educational megaprojects at Aalborg University, i.e. largescale interdisciplinary projects designed to address highly complex problems and grand societal challenges such as the Covid-19 pandemic or the UN Sustainable Development Goals. Based on data collected through observations of blended, collaborative learning activities as well as student interviews, the paper identifies and discusses potentials and challenges related to the implementation of interdisciplinary collaborative learning in blended problem-based learning environments, with a particular focus on students’ experiences and perspectives. The concept of high and low distinctiveness and responsiveness within ‘educational adhocracies’ is introduced as a framework for analyzing interdependencies and barriers for collaboration within current running megaprojects. Based on these preliminary findings, specific collaborative learning activities are proposed as ways to facilitate higher degrees of both distinctiveness and responsiveness in future megaprojects, particularly in the early stages of the project to ensure higher interdependency and thus motivation for interaction and collaboration. Keywords: Megaprojects


PBL
Blended learning
Interdisciplinarity

1 Introduction With the growing need for solutions to address increasingly complex and diverse societal problems follows a need for more advanced skills and competences for the future. Competences, not only within one field or discipline but collaborative and transversal skills and competences across programs and paradigms as well. Educational institutions are employing different strategies to support students in developing such competences both in online and blended learning environments; one such strategy being the implementation of large scale and interdisciplinary student projects, or educational megaprojects [7]. The purpose of educational megaprojects is to address highly complex problems and grand societal challenges such as the Covid-19 pandemic or the UN Sustainable Development Goals (SDGs) and offer students a possibility to © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 169–180, 2021. https://doi.org/10.1007/978-3-030-67209-6_19

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integrate interdisciplinary and digitally supported collaborative learning into semester projects while still meeting learning objectives of the formal curriculum. This paper reports initial findings from research on the first two rounds of educational megaprojects at Aalborg University (AAU), launched in the fall of 2019 and spring 2020 to identify and discuss potentials and challenges related to the development and implementation of megaprojects in blended problem-based learning environments. Based on the theoretical concepts of adhocracies and loosely coupled systems, this research reports empirical findings related to structures, platforms and project processes in large-scale interdisciplinary interactive collaborative learning, with a particular focus on students’ experiences and perspectives. 1.1

Project-Oriented PBL: Revisiting Models and Methods

Whereas problem-based learning (PBL) originates as far back as the late 1960s at McMaster University with the success of a completely new medical school and curriculum [13, 17] quickly spreading to other institutions with variations such as projectoriented PBL [2, 4], resent research shows that the majority of PBL is still mostly implemented at course level [3]. At Aalborg University (AAU) though, a systems approach has been applied since its beginning in 1974, with problem-based project work typically accounting for half the students’ time at each semester (15 ECTS). At AAU, a specific focus is put on student-centered problem identification and analysis as point of departure for project work organized in smaller groups of 3–7 students, supported by courses and supervision and involving collaboration with external stakeholders [1]. This approach has been shown to improve students’ collaborative skills and project-oriented competences, particularly within their own discipline [8]. However, whereas project-oriented PBL provide students with expert knowledge and skills, the single-discipline team approach does not necessarily resemble real-world project work nor is it able to fully capture and address the complexity of grand societal challenges such as the SDGs. Thus, a larger variation in project-oriented PBL has been proposed as an approach to facilitate student reflection on both the contributions and limitations of their own discipline as well as varying levels of complexity in interactive collaborative learning e.g. through interdisciplinary collaboration in student projects, particularly within engineering programs [7]. In recent years this approach has been further expanded with the aim of collectively addressing sustainability issues and in the fall of 2019, AAU launched AAU Megaprojects providing students across all faculties the opportunity to work together on complex problems particularly related to the SDGs [18]. 1.2

AAU Megaprojects

AAU Megaprojects are umbrella projects running for a duration of 2–3 years focusing on one or more related SDGs, inviting a variety of student groups across semesters and programs to work together to solve related real-world challenges. The structure of a megaproject is scalable in nature (see Fig. 1) with a complex societal problem at the top, branching out in up to three focus areas, each with two subsequent challenges. Each focus area represents a theme within the overall frame of the megaproject

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specified further into challenges possible for students to engage in. Each challenge has the potential to hold a large number of clusters, each containing up to five groups of between 2–7 students per group (at the moment single-student ‘teams’ are only allowed for graduating master students). In the initial phases of the megaproject, each group of students choose a challenge of interest and based on initial project descriptions are distributed into interdisciplinary clusters, all of which contribute with problem analyses, designs and solutions related to the megaproject [18].

Fig. 1.

Example of AAU Megaproject structure

Initially, each megaproject theme is proposed by an interdisciplinary group of faculty members and further developed in collaboration with private and public stakeholders to ensure that themes, focus areas and challenges are authentic and relevant. It is a requirement, that the megaprojects are relevant for at least four faculties, whereas focus areas must be relevant for at least three faculties. Challenges must be relevant for at least two faculties, one in addition to the faculty hosting the particular megaproject. Joining a megaproject is not a requirement and thus considered extra curricula for participating students, however the majority of megaproject activities work in tandem with program specific activities and are fully credited in semester projects. Through this structure, it is possible for students to take part in interdisciplinary and large-scale collaborative work while still maintaining the timeframe and learning outcomes given within specific semesters and programs. 1.3

Collaboration Structures in AAU Megaprojects

During a megaproject period, a number of collaborative products and activities are organized to facilitate collaboration particularly within each cluster of groups but also across clusters, challenges and focus areas (see Fig. 2). These include a minimum of two student-organized seminars in each cluster (Midterm and Endterm), with the aim of sharing and synthesizing problem analyses and preliminary findings, as well as four deliverables from each student group, designed to help facilitate ongoing reflection and knowledge sharing in the clusters. At the end of each semester, a megaproject conference is organized for project participants, invited researchers and stakeholder representatives as well as potential future project participants and facilitators to present

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current state-of-the-art and solutions from all project clusters in each megaproject and to inspire interested students to join future megaprojects in the coming semesters.

Fig. 2.

Project timeline in an AAU Megaproject semester

To encourage megaproject groups to engage and communicate throughout the project period, each cluster is offered a digital space for online collaboration (Moodle in the fall of 2019, Microsoft Teams in Spring 2020). External stakeholders are also invited to use the platform and required to provide students with information and knowledge needed, particularly in the problem identification and analysis phases.

2 Megaprojects: Towards Educational Adhocracies? Recent research has compared project-oriented PBL with new emerging ways of organizational collaboration, one key comparison being that of small-group PBL work and flexible organization or ‘adhocracies’ [12]; a term coined as far back as 1970 [15] and further elaborated in the late 70’s and early 80’s, arguing that a highly organic structure as well as informal and mutually adjusted ways of working are considered particularly suitable to address complex, ill-structured problems [9, 10]. Compared to traditional hierarchical organizational structures, adhocracies are organized in networks shaped by the project it is addressing and with distributed management in project units inside the network. Engeström expands this teamwork metaphor further by describing it as a net with strands and knots created and connected as needed, changing the tension and shape of the entire network [5]. By this, knotwork (i.e. the distributed and partially improvised orchestration of collaborative performance between otherwise loosely connected actors and activity systems) is characterized by processes of tying, untying and retying together seemingly separate threads of activity’ [5]. Spinuzzi adds to this the ICT-enabled possibilities of extending adhocracies to large distributed networks, or so-called all-edge teams, working on the same project, where coordination and mutual adjustment depends on the availability of efficient and affordable ICT infrastructure [14]. However, whereas adhocracies are needed for solving complex problems, a hierarchical structure is often more effective for implementation and routine shaped tasks [9], which poses a particular challenge when applying this approach to educational megaprojects.

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Open, Closed and Loosely Coupled Systems

When considering the interfacing of and interactions within educational adhocracies, we argue it is beneficial to consider these ‘all edge teams’ as loosely coupled systems [11, 16]. From this perspective, organizations or knots or all-edge teams can be both opened and closed, but exist in separate locations: the closed system usually considered the rational, determinate technical core eliminating uncertainty; or the open indeterminate system, handling uncertainty and allowing for ‘intrusion of variables penetrating from the outside’ with a managerial layer mediating between the two [16]. A loosely coupled system, on the other hand, is a system that contains both rationality and indeterminacy in the same entity or the same location, i.e. is simultaneously open and closed, indeterminate and rational [11]. Here, coupling in the system happens in two dimensions: responsiveness (the degree to which elements in the organization are influenced by and interdependent of each other) and distinctiveness (the degree to which elements differ from each other e.g. regarding competencies, specialization etc.) [11], resulting in four different couplings (see Table 1). Table 1. Orton and Weick’s four different couplings Low responsiveness High responsiveness Low distinctiveness Non-coupled system Tightly coupled system High distinctiveness Decoupled system Loosely coupled system

We argue that this framework is a relevant approach when exploring the interaction and interdependencies within an educational megaproject, i.e. the level of distinctiveness and responsiveness within groups, clusters and challenges to understand whether the megaproject constitutes an actual system, and to which degree the system, or adhocracy, distinctive and responsive, i.e. decoupled, loosely or tightly coupled. 2.2

Team Interdependency in Interdisciplinarity

As argued earlier, solving complex and ill-structured problems requires new interdisciplinary skills, thus the character of the problem and the composition of the team organization define the degree to which a project is interdisciplinary [7]. The driver for this interdisciplinarity will be exogenous, i.e. the complexity of the problem defines whether it is possible to find solutions by connecting people with different disciplines in – multidisciplinary (juxta positioned) – teams, or whether disciplines much merge or entirely new disciplines emerge [6]. Thus, whereas an important outcome of a complex project such as a megaproject can be new disciplines emerging from the field in between existing disciplines, developing new interdisciplinary skills requires groups from different disciplines (high distinctiveness) to work together in close coordination (high responsiveness), which is exactly what characterizes the loosely coupled system.

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3 Research Design and Methods The empirical data for this research has been collected in the period from January to April 2020 (see Fig. 2) with approximately 50 students participating in total. Data from the first round of megaprojects in 2019 includes observations from the face-to-face endterms and physical Megaproject Conference (February 2020) as well as focus group and individual follow-up interviews with participating students, who have experienced a full semester participating in all activities related to a megaproject, including assessment and exams. For the second round of megaprojects, data include observations of meetings with facilitators and stakeholders as well as observations of midterms in April 2020, all conducted online on MS Teams due to the Covid-19 pandemic. Thus, while the two Megaproject periods are similar in nature and comparable in terms of goals and purpose of activities, they are fundamentally different in practice and not necessarily directly comparable. Due to Covid-19, the megaproject activities in spring 2020 have been fully virtual, (using MS Teams) whereas the setting in fall 2019 was inperson and blended (using physical meetings and Moodle). The intention of this paper is not to compare these platforms or modes of support, but to elaborate on possibilities, challenges and significant differences in the way physical and online learning environments support interactive collaborative learning in megaprojects, providing insights into opportunities for new blended and large-scale collaborative settings. A total of seven clusters of student groups (two in 2019 and five in 2020) have participated so far, divided between two megaprojects; ‘Simplifying Sustainable Living’ and ‘The Circular Region’. In each cluster, up to four groups have collaborated represented from all faculties at the university, except health science. However, the diversity in each cluster have been fairly limited in these first two rounds, as onboarding of students have been voluntary so far, with several groups from similar programs and scientific paradigms such as Communication and Digital Media and Sociology working on the same topic. Additional data include documents such as the project deliverables, syntheses and conference posters as well as weekly meetings with the AAU Megaproject administrative manager. Covid-19 forcing the students to meet and interact online only has made it possible for researchers to observe most interaction among student groups in the clusters, with challenge facilitators and organizers, however with limited means of interacting directly with the students for in-situ interviews in these settings. 3.1

Researching Ever-Evolving Practice

As the aim of this research has been to explore contextually embedded potentials and challenges and propose practical improvements in the platforms and structural processes specifically related to megaprojects at AAU, this research process has been inductive in nature, letting data indicate patterns and guide topics of interest, providing a bottom-up approach to conducting the data analysis. However, this inductive approach in combination with the conceptual framework presented earlier, have provided general findings and indicators of experiences and knowledge relevant to other institutions working with PBL and/or planning to implement large-scale interdisciplinary and interactive collaborative learning in blended learning environments as well.

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4 Findings In the following section, we will present and discuss findings from these first two rounds of megaprojects at AAU with specific focus on the megaproject as a bureaucracy vs. adhocracy, on ways to facilitate high distinctiveness and responsiveness within educational megaprojects as well as the role of ICT and blended learning spaces in large-scale interactive collaborative learning. 4.1

Educational Megaprojects: Bureaucracy vs. Adhocracy

As mentioned, megaprojects at AAU are defined by interdisciplinary groups of faculty members with an appointed challenge facilitator, and a central administrative project organization is responsible for the overall coordination of the megaproject, including communication (e.g. on the website, deliverable requirements and templates etc.) and planning related to formal activities (e.g. midterm, endterm and the megaproject conference). This organization is established to ensure that megaprojects are aligned with formal requirements of the AAU PBL model and strategy, while still encouraging students to take ownership of the megaproject processes, particularly in relation to collaboration in the clusters. Whereas this central organization is vital to the overall documentation and progression of the educational megaproject since ‘adhocracies’ are not, as Mintzberg stated, efficient for routine shaped tasks; it is a challenge balancing the built-in bureaucracy of static operational administrative management and the wish for a more fluid organization of the student group ‘adhocracies’ in the clusters. For instance, clusters cannot emerge ‘organically’ or be organized by the students themselves, but are composed and created centrally according to the megaproject guidelines (with at least two faculties represented in each challenge) based on the project descriptions in deliverable 1. This means students sometimes have a hard time finding how their projects are interconnected, and that they often have to consult the collaboration guidelines e.g. during midterms simply because collaboration is not a ‘need’ as much as it is a requirement. Thus, whereas a centrally organized structure of clusters is beneficial in the start-up phases of large-scale collaborative megaprojects, particularly in relation to ensuring the distribution of discipline in the participating groups (high distinctiveness), based on the following findings we do expect and recommend that groups and clusters will eventually collaborate more as ‘knots in networks’ that can be tied and untied dynamically in response to the motivations and needs within the project. 4.2

Mutual Alignment and Responsiveness

Even with a systemic PBL model and approach, semester projects are practiced with many variations across departments and programs at AAU [7]. Perhaps most distinctive, is the difference in project timelines across faculties. For instance, engineering and science programs will often form groups right at the beginning of a semester and students will work on problem analysis and definition approximately the first 8 weeks of the semester. For many programs in social science and humanities, on the other hand, group formations occurs 3–4 weeks into the semester or even later, which can be a challenge when attempting to align megaproject specific activities such as

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deliverables and midterm with projects in individual programs. As Mintzberg emphasizes, alignment or ‘mutual adjustment’ is a key coordinating mechanism in adhocracies and without a common problem or shared objectives, collaboration becomes ‘unnecessary’ and the adhocracy tend to act as a non-coupled or de-coupled system with limited interaction, rather than a loosely coupled system. Thus, the slight offset in project initiation poses a particular challenge to the ‘coupling’ or interdependency within megaprojects, which is supported by observations during endterm and midterms. With the exception of one cluster, the midterm is the first activity where the groups meet to share input and findings within the cluster, with the purpose of writing a shared deliverable providing new perspectives and interdisciplinary aspects to incorporate into the megaproject. However, whereas most students find the midterm helpful for facilitating knowledge sharing in the cluster, the offset timeline of individual projects makes it difficult to incorporate these findings across projects. Some students explicitly stated they did not feel ‘ready’ to share findings yet, while others were already set on a specific problem statement and method, making it difficult to adjust individual projects in relation to input from other groups. In this sense, the midterm becomes more of a debriefing and a distribution of online resources and literature, rather than an interactive collaborative activity and a mutual alignment of problem statements and project objectives. Some students explicitly stated it was difficult both listening to inputs from other groups and working on a joined contribution. Several clusters therefore agreed to schedule a second midterm, giving each group more time to reflect on inputs from the previous midterm and especially one cluster succeeded in this and engaged collaboratively in the joint deliverable, sharing problem formulations and thoughts on interdisciplinarity in their cluster as well as articulating similarities and differences between their projects. The one exception was an early meet-up in one cluster prior to the midterm, that had been initiated by the challenge facilitator, and this had a positive effect on the students’ confidence in sharing preliminary results as well as their ability and motivation to relate to the literature and initial findings presented by other groups. This in turn made the midterm more interactive, collaborative and interdisciplinary in nature. These findings point to a need for actively facilitating interdependency within the clusters, particularly in the early stages of the projects to ensure high responsiveness. The challenge here is to balance bureaucratic and ‘adhocratic’ approaches to this facilitation, i.e. whether interdependency is facilitated centrally e.g. by organizing early collaborative problem-focused workshops and require shared project objectives; or by encouraging more student-initiation and involvement in the definition of challenges and allowing for more flexibility in the distribution of groups and clusters. 4.3

High Distinctiveness in Interdisciplinarity

Whether an educational adhocracy evolve to become a loosely coupled system, depend on both high responsiveness and high distinctiveness, i.e. the level of interaction and interdependency among the groups in the megaprojects. In relation to this, particularly students in the first round of megaprojects in the fall 2019 highlight the challenge of ensuring interdisciplinary input in the projects without much variation in the group structure. Some students propose a more deliberate push for interdisciplinarity by

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mixing students across different study programs or semesters in the groups. This is based on the assumption that working in interdisciplinary groups creates more awareness of the contribution of one’s own discipline to the project, and that older students are more capable of defining their own contribution compared to e.g. first year students (i.e. incorporate higher distinctiveness). This is supported by observations showing that master level students were ascribed a certain credibility during interactive collaborative activities such as mid- and endterm, often taking the lead with the other groups valuing their viewpoints. This points to a potential in leveraging master level students’ competences e.g. in administrative project management processes within clusters and challenges but also points to the potential bias that younger students have less to contribute. Some students suggest more frequent, interdisciplinary events such as the megaproject conference to provide the opportunity to engage with other clusters and challenges, which is supported by observations from both rounds of megaprojects suggesting that students’ awareness of the contribution and limitations of their own discipline, i.e. high distinctiveness, increased in groups organizing an ‘extra’ second midterm. For instance, in a cluster discussing sustainable consumer behavior from the perspective of both digital communication and business perspectives, humorously agreed they were ‘missing a group from psychology!’. Organizing a second midterm also helped students set clear goals not defined centrally, which seemed to increase motivation for the second meeting, where the students decided to compare problem statements to identify similarities and contributions related to the overall framing of the megaproject. Through this, the students became more aware of the interdependency of projects within the cluster, and a certain chronology in the proposed research questions with groups depending on each other’s findings. The students also explicitly discussed the meaning of the joint deliverables, even if it was still early for the students to clarify their individual contribution. Particularly in the early launching phases of educational megaprojects, high distinctiveness might be difficult to obtain, simply because the number of group participating is still low with many groups from the same or similar programs and scientific paradigms. However, we argue that high distinctiveness in interactive collaborative activities such as one problem-focused workshop, one midterm for dissemination, and another for collaboration on a joint deliverable, can help facilitate both high distinctiveness and high responsiveness in the clusters. Finally, creating more interdependency within the challenges, e.g. by ensuring that projects are somewhat dependent on each other or by having the students work on shared interdisciplinary products or ‘boundary objects’ making collaboration necessary for the project groups to succeed, is another way to facilitate both high distinctiveness and responsiveness in educational adhocracies. 4.4

Large-Scale Collaboration in Blended Learning Spaces

As Spinuzzi states, ICT is a prerequisite in modern adhocracies and all-edge teams, and this has been the case for AAU megaprojects as well, particularly in the spring of 2020 due to the Covid-19 pandemic. In the fall of 2019, the central project administration had been using Moodle to communicate with students in the megaprojects, however

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found this to be limiting particularly in relation to facilitating interaction and collaboration among the clusters. In spring 2020, MS Teams was used for all communication to and between students in clusters, since students were prevented from meeting physically on-campus until early June. Whereas this makes the comparison of interactive collaborative activities such as midterm and endterm in 2019 and 2020 difficult, it did provide an opportunity to observe collaboration in both blended settings with Moodle and co-located seminars in 2019 and fully online collaboration with MS Teams in 2020. The use of a digital platform particularly in spring 2020 provided the students a forum for sharing documents and planning activities and for meeting each other virtually despite being distributed across many different locations. Midterms and meetings with facilitators and external stakeholders have been organized through MS Teams, providing students different additional digital tools to use, although observations show variations in the extent to which the students made use of such tools. Some students shared their screen while presenting power points and some groups used shared online writing tools through Sharepoint for syntheses and documentation, whereas others did not. During one midterm, a student asked for the others to turn on their camera to enable more ‘face to face’ interaction, stating ‘I don’t even know how you all look’, however this was not possible for all participants, since a webcam was not a requirement to participate in a megaproject. In interactive collaborative activities where some students had their webcam on and others did not, we observed a difference in the extent to which student engaged, with ‘visible’ students being visibly more interactive, more often asking questions and making comments or taking the lead in discussions. In one midterm, though, the students were waiting for someone to take lead until finally the challenge facilitator who was present took charge. Group composition and students’ motivation and personality obviously affect the dynamics during these online collaborative activities and thus difficult to generalize across megaprojects, however the findings point to a need for more awareness on how online tools and virtual meetings both enable and inhibit students in taking part in large-scale interactive collaborative learning. A technical platform such as MS Teams provide just that - a platform - for communication and collaboration. It does not, in of itself, ensure good communication, and facilitation and management of meetings is just as important virtually as it is in face-to-face physical settings, which students could ideally be encouraged to reflect upon as part of developing and documenting complex PBL competences in project work. Whereas MS Teams seemed to be a useful platform for sharing documents, minutes from meetings and joint deliverables, we observed little activity on the platform in between or after organized activities, with groups often not responding to questions and suggestions for additional meetings posted by other groups. The question here again is whether to increase the level of bureaucracy and ‘require’ the students to engage more online and provide guidelines for such engagement or whether to focus on increasing interdependency within the adhocracy to facilitate a natural need for ‘knots’ to form in the network, i.e. moving from a decoupled system to a loosely coupled one.

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5 Conclusions and Future Work In this paper, we have presented findings from the launch and first two rounds of educational megaprojects at Aalborg University and based on theory on adhocracy and loosely coupled systems, we have identified potentials and challenges particularly related to ‘bureaucratic’ versus ‘adhocratic’ approaches to ensuring high distinctiveness and responsiveness in large-scale collaborative megaprojects. We have identified a need to move from ‘required coordination’ in decoupled systems to ‘meaningful collaboration’ in loosely coupled systems of knots in teams, and suggest facilitating more interdependency particularly in the early stages of the project as a way of doing so. This includes early problem-focused workshops and ongoing interactive and collaborative activities leveraging both blended and online learning spaces, as well as through a general increase in student involvement in the definitions of megaproject themes and distribution of clusters and challenges. Participating in megaprojects both requires and facilitates the development of new student competences. Thus, future work includes research on how to assess students’ complex problem-solving and PBL competences in megaprojects, both from the perspective of facilitators and supervisors and by leveraging online tool and emerging technologies such as AI and learning analytics. Furthermore, future work includes exploring and analyzing organizational structures and barriers affecting the scale-up of educational megaprojects both in levels of interdisciplinarity and complexity as well as in terms of project size, distribution of disciplines and global impact.

References 1. Askehave, I., Prehn, H.L., Pedersen, J., Pedersen, M.T. (eds.): PBL: Problem-Based Learning. Aalborg University, Aalborg (2015) 2. de Graff, E., Kolmos, A.: History of problem-based and project-based learning. In: de Graff, E., Kolmos, A. (eds.) Management of Change, 1-8. Sense Publishers Rotterdam, Netherlands (2007) 3. Chen, J., Kolmos, A., Du, X.: Forms of implementation and challenges of PBL in engineering education: a review of literature. Euro. J. Eng. Educ. 1–26 (2020). https://doi. org/10.1080/03043797.2020.1718615 4. Du, X., de Graff, E., Kolmos, A.: PBL – diversity in research questions and methodologies. In: Du, X., de Graf, E., Kolmos, A. (eds.) Research on PBL Practice in Engineering Education. Sense Publishers, Rotterdam (2009) 5. Engeström, Y.: From Teams to Knots: Activity-Theoretical Studies of Collaboration and Learning at Work, 1st edn. Cambridge University Press, USA (2008) 6. Klein, J.T.: A taxonomy of interdisciplinarity. In: Julie Thompson Klein & Carl Mitcham (eds.). The Oxford Handbook of Interdisciplinarity. Oxford University Press (2010) 7. Kolmos, A., Brogaard, L.B., Egelund, J.H., Routhe, H.W.: Project Types and Complex Problem-Solving Competencies: Towards a Conceptual Framework. IRSPBL2020 (2020) 8. Kolmos, A., de Graaff, E.: Problem-based and project-based learning in engineering education. Cambridge handbook of engineering education research, pp. 141–161 (2014) 9. Mintzberg, H.: The Structuring of Organizations, 1st edn. Prentice-Hall, New York (1979)

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10. Mintzberg, H.: Structures in Fives. Designing Effective Organizations. 1st edn. Prentice Hall, Englewood Cliffs, New Jersey, USA (1983) 11. Orton, J.D., Weick, K.E.: Loosely coupled systems: a reconceptualization. Acad. Manage. Rev. 15(2), 203–223 (1990) 12. Ryberg, T., Sørensen, M.T., Davidsen, J.: Student groups as ‘adhocracies’ – challenging our understanding of PBL, collaboration and technology use. In: Wang, S., Kolmos, A., Guerra, A., Qiao, W., (Eds.), 7th International Research Symposium on PBL: Innovation, PBL and Competences in Engineering Education, pp. 106–115. IRSPBL 2018. Aalborg Universitetsforlag (2018) 13. Spaulding, W.P.: The undergraduate medical curriculum model: McMaster University. Can. Med. Assoc. J. 100, 659–664 (1969) 14. Spinuzzi, C.: All edge: Inside the new workplace networks, 1st edn. The University of Chicago Press, Chicago (2015) 15. Toffler, A.: Future Shocks. Random House, USA (1970) 16. Thompson, J.: Organizations in Action. Social Science Bases of Administrative Theory. McCraw-Hill Book Company, USA (1967) 17. Woods, D.: How to gain most from Problem Based Learning. McMaster University Press, Hamilton (1994) 18. AAU Megaprojects, https://www.megaprojects.aau.dk/ Accessed 19 May 2020

Collaboration with Industry in the Development and Assessment of a PBL Course Dan Centea(&) and Seshasai Srinivasan McMaster University, 1280 Main Street West, Hamilton, ON L8S 0A3, Canada {centeadn,ssriniv}@mcmaster.ca

Abstract. The automotive industry brings to market continuously improved electric and hybrid electric vehicles, and each new vehicle includes improved autonomous features. The automotive companies are constantly looking for specialists to design, implement and test the new features and technical solutions, including university graduates with competencies needed for current and future developments in the automotive industry. The approach taken at McMaster University in the School of Engineering Practice and Technology to prepare students who possess the competencies needed by the fast-evolving automotive industry is presented. The ways in which the expected competencies are conveyed from the technical experts engaged in the automotive industry to academia are shown. The Problem-Based Learning (PBL) teaching method that allows to deliver a constantly evolving course content related to the design and electrical and hybrid electric vehicles is presented. The collaboration between industry experts and academia through input in course development, annual course revisions, and assessment and feedback of final projects is described. Keywords: Problem based learning
PBL
Industry-university collaboration
Conceptual design of electric vehicles
Conceptual design of hybrid electric vehicles

1 Introduction To address the needs of the automotive industry for new employees with competencies in the design of new electric and hybrid electric vehicles with more autonomous features, the academia needs to provide graduates with competencies that match the expectations of the industry. The traditional automotive curriculum needs to include basic science, engineering fundamentals and tools, robust design skills, deep knowledge of automotive engineering, expertise in using solid modelling tools, expertise with various modelling and simulation software tools, and a fast-evolving knowledge related to the design solutions for electrified vehicles with autonomous features. Although most of the competencies that result from this curriculum can be delivered with traditional course delivery approaches, the part of the curriculum that evolves fast needs to be updated every year. This part of the curriculum can be accomplished through research, through the published literature, and through a cooperation between experts from the automotive industry involved in the development of future vehicles and academia. This paper focuses on the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 181–188, 2021. https://doi.org/10.1007/978-3-030-67209-6_20

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cooperation between industry and academia for the development and constant updating of a course related to the conceptual design of electric and hybrid electric vehicles offered in Canada at McMaster University. The university–industry collaboration, within the particular context of education‐ related partnerships reported in several papers [1–6]. This interaction within engineering curricula is recommended as it allows the development of engineering competencies while solving real industrial interdisciplinary problems [7], or allows students to develop both cognitive and non-cognitive skills through project-based learning [8]. One of the outcomes of the collaboration between industry and academia in the education of the university graduates is a list of competencies that the graduates are expected to have. However, preparing graduates for the fast-evolving automotive industry is a difficult task because the large content encompassing the past, present and potential future engineering solutions cannot be taught in a single course using a traditional lecture-intensive approach. Furthermore, modern engineering education should be organized according to an interdisciplinary and transdisciplinary approach [9]. To address these challenges, the course delivery method taken for the fourth-year students enrolled in the Automotive and Vehicle Engineering Technology Program at McMaster University is PBL. This course delivery method provides an opportunity for students to connect abstract multidisciplinary principles from to mechanical, electrical, computer and mechatronics engineering with real life situations, an approach that increases students’ motivation to learn and apply their knowledge and skills to real-life applications. The use of PBL in the delivery of courses that integrate different areas of knowledge, while solving real industrial problems is reported by [7]. The transfer of knowledge between industry and academia can be facilitated by using PBL to address unsolved problems from industry [10]. PBL can be combined with other active learning strategies that involve industry-university cooperation to develop educational programs [11]. Several companies have reported gaps between industry expectation and students’ skill set level. PBL provides the means for the students to enrich their knowledge and skills and reduce the bridge between industries and engineering education [12]. Evidence suggests that industry demand for professional skills is one of the primary drivers behind the adoption of PBL at many institutions [13]. Although PBL has been adopted in many engineering institutions because its effectiveness in developing student’s competencies, the forms of implementations and challenges of PBL in engineering education vary between course level, cross-course level, curriculum level, and projects level [14]. PBL has been successfully implemented for capstone projects, one example being the development of several components of electric vehicles reported by [15]. The paper presents the forms of collaboration in education between experts in the automotive and manufacturing industry and the School of Engineering Practice and Technology at McMaster University for a capstone course related to the conceptual design of electric and hybrid electric vehicles. The course is offered to upper year automotive engineering technology students, and it’s the first PBL course in their studies. The method of applying PBL in this course is presented in Sect. 2. Several types of cooperation between industry and academia for the development and constant updating of the curriculum of this course is discussed in detail in Sect. 3. The conclusions of the paper are presented in Sect. 4.

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2 Problem Based Learning The modern tools currently used in the automotive industry for designing, prototyping, testing, and manufacturing have significantly reduced the lead time to introduce a new vehicle into the market. Furthermore, most of the car manufacturers currently offer at least one electric or hybrid electric vehicle, and adopt new solutions every year to improve their existing designs. To encourage students to master the art of self-learning to keep up with the rapidly evolving automotive industry, students are required to participate in many inquiry-based problem-solving activities. PBL is a platform in which students are required to use engineering design and analysis methods that have been taught in previous courses to perform a variety of problem-solving activities. In doing so, they are expected to search, identify and read relevant published research related to the design of modern vehicles, and are required to be aware of the current trends in the automotive industry. PBL, pioneered in Canada at McMaster University’s Medical School in 1969 [16], is a pedagogical approach in which students master a subject by applying fundamental concepts to solve problems [17]. PBL facilitates the development of self-directed learning skills by working in groups through a structured problem-solving strategy. After understanding the problem and identifying the concepts that are applicable to solve the problem, students work to evolve their knowledge and understanding to solve the problem in hand. The defining characteristic of PBL is that it is a student-centric learning approach where the instructors play a role of facilitators. The instructor must design good problems whose solution will adequately demonstrate that the learning objectives are met. Such open-ended problems tend to have multiple solutions. Students are expected to consider several possible solutions, evaluate the merits and demerits of each, and propose an optimal solution. The problems serve as a stimulus for the students to identify the topics of interests to them and draw an outline of the way they want to study the topics. In doing so, the students take control of their education by defining their learning needs, planning classroom activity/discussions, and assessing their progress as well as that of their peers. The course described in this paper is Conceptual Design of Electric and Hybrid Electric Vehicles, and is delivered to full-time students enrolled in the last semester of an automotive program. Students have acquired considerable automotive engineering and management knowledge and gained relevant industrial experience through 12 months of full-time co-op employment. By employing the principles of PBL, students use previously taught knowledge, investigate various forms of published information, use problem solving activities, identify relevant design approaches and distinguish between acceptable and non-acceptable solutions, and assess the applicability of innovative ideas. At the end of this course the students have a good understanding of the state-of-the art in the field of automotive engineering. Group of students are asked to prepare open ended projects that combine engineering solutions with an associated business model for electric or hybrid electric vehicles with autonomous features that are expected to be used in 3 years for car-sharing applications. Descriptions of different elements of the course are presented in [18–21].

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3 Cooperation Between Industry and Academia The cooperation between industry and academia for the initial development and continuous updating of the course described in this paper was and is accomplished through (i) an initial curriculum development committee; (ii) input from a program advisory committee; (iii) employment of students in automotive companies; (iv) assessment of student projects; and (v) feedback and suggestions for the next iteration of the course. These five types of cooperation are discussed in the following sections. 3.1

Initial Curriculum Development

The curriculum of the Automotive Engineering Technology program has been initially developed in 2006 through a partnership between McMaster University and Mohawk College by a committee that included experts from both academic institutions and specialists from the automotive and manufacturing industry. The curriculum has been modeled based on similar automotive engineering programs and covers the academic requirements of a university degree. The industry representatives suggested a curriculum with significant experiential learning activities materialized through substantial lab components for each course. Furthermore, to ensure the industry-related knowledge and skills upon graduation, a mandatory 12-months employment has been included in program graduation requirements. A shift of the automotive industry towards electric propulsion systems became clear after the inception of the automotive program. Various forecasts [22, 23] indicated an increase in the number of electric and hybrid electric vehicles produced my most automotive companies in most industrialized countries. The shift towards teaching the fundamentals of electrified vehicles has been suggested by the amount of research carried out in this field and by the industry experts through a Program Advisory Committee. 3.2

Input from the Program Advisory Committee

The constantly evolving needs of the industry are annually discussed in a Program Advisory Committee that include members of academia, researchers in automobile electrification, and engineering managers from automotive-related industries. The committee provides advice on the changes carried out in the curriculum, and suggests changes to the curricula that are expected to align the competencies of the graduates with the anticipated changes in vehicle design and production. Examples of suggestions that have been implemented in the program included increasing education in electric vehicles, providing opportunities for international engineering cooperation and competitions, an increased focus on electric and electronics systems for vehicles, and more recently an increased emphasis on the development of autonomous features. 3.3

Co-op Employment in Automotive Companies

Work placements of the students has been proven beneficial for students [24]. Many employers prefer to hire graduates of engineering programs that have co-op

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employment experience. The students enrolled in the automotive program described in this paper have a mandatory one-year co-op employment requirement for graduation. Many of the employment opportunities are in the automotive and manufacturing industries. Students are often hired due to their design skills, and often these skills are related to using complex solid-modeling software packages that differ between companies. The feedback from the industry employers allowed the management of the automotive program to include in the curriculum the four CAD software packages that are most used in the automotive industry. During employment, many students improve their attitude towards work, strengthen their technical knowledge and skills, and become aware of the trends in the automotive industry. They apply the knowledge and skills in their open-ended project, and are encouraged to include in the projects advanced but realistic solutions based on the realities of the automotive industry. 3.4

Industry Assessment of Student Projects

The external evaluation of the final project is a very important assessment of the course. The capstone project is a final product of a series of courses related to automotive engineering, electric and hybrid vehicles, engineering design, combined with business and management elements. The external assessment is performed by a panel of judges that includes engineering managers from major automotive related companies, and faculty members whose main research is related to electric and hybrid vehicles. Presenting their designs in front of possible future managers gives students an opportunity to showcase their accomplishments to relevant people in the industry, but at the same time also creates a certain level of anxiety as they expect to be questioned by knowledgeable people in this field. Being fully aware of this type of assessment throughout the course keeps the students motivated to prepare good conceptual designs. The external judges are provided score cards that allow them to assess the level of technical knowledge in the fields covered in the course and the students’ skills in proposing an innovative business concept and describing a business model. Students need to convince the judges that the combination of technical solutions and a business model can be implemented in industry within 3 years. The judges, assuming the roles of automotive manufacturers, need to be able to convince vehicle car-sharing providers to buy their vehicles and use the suggested business model for profit. 3.5

Feedback and Suggestion for the Next Iteration of the Course

Score cards are used by the judges to provide detailed feedback on different aspects of the projects. The score is an important measure of achievements of the learning outcomes, while the verbal and written feedback help students to understand the expectations that their employers will have after graduation while analysing their solutions. The development, implementation, and evaluation of PBL activities carried out in partnership with industry representative allow new course implementations every year [25]. Each iteration of the course presented in this paper is expected to include every year new approaches and features, most of them being suggested by the external judging panel. Examples of suggestions include a significantly increased market

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research and business model, the use of a given vehicle frame on which students are required to conceptually design elements related to vehicle electrification. The several layers of industry input improve the outcomes of the course and ensure that the graduates of the course will have many of the required competencies in the design, manufacturing, and testing of new electric and hybrid electric vehicles and increases their chances to be successful in finding relevant employment in the automotive-related industry.

4 Conclusions The paper presents a course aimed to address the modern trends in the fast-evolving automotive industry. Students are expected to prepare the conceptual design of a future electric or hybrid electric vehicle and to create a business case of an associated carsharing service. The PBL approach used in this course encourages students to read relevant published literature, identify the current trends in increasing the electric range and autonomous levels, perform problem-solving activities, and improves their technical, business-related, engineering collaborative and managerial skills. Students prepare open ended projects that combine engineering solutions with a business model for a vehicle with the autonomous features that are expected to be available in 3 years. The curriculum of the automotive engineering technology program has been initially developed by a committee that included experts from academia and specialists from the automotive and manufacturing industry. The curriculum covers the academic requirements of a university degree and includes a significant number of experiential learning activities that provide the competencies needed for employment in the automotive and manufacturing industry. The constantly evolving needs of the industry are annually discussed in program advisory committee that include academia and engineering managers from the relevant industries. The students enrolled in the automotive program have a mandatory one-year co-op employment requirement for graduation, and many of the employment opportunities are in the automotive and manufacturing industries. During employment, many students strengthen their design skills and are made aware of the trends in the automotive industry. They apply these knowledge and skills in their open-ended project for the course presented in this paper. Students are encouraged to include in their project advanced but realistic solutions that combine an innovative business model with modern technical specifications. A panel of industry managers who are in charge with future developments in the automotive industry and university researchers in automobile electrification are assessing these projects and provide valuable feedback both to the group pf students and to the course instructor for suggested changes in the future iterations of the course. The approach of delivering a course using the PBL approach and using several layers of industry input to improve the outcomes of the course described in this paper ensures that the graduates of the course will have many of the required competencies in the design, manufacturing, and testing of new electric and hybrid electric vehicles and increases their chances to be successful in finding their dreamed employment.

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Padlet in IDEEA Global Course and Project Pedro Orta1(&) , Kwanju Kim2, Manuel Löwer3, Gabriela Mendez-Carrera1, Pedro D. Urbina Coronado1, and Horacio Ahuett-Garza1 1

Tecnologico de Monterrey, 64849 Monterrey, NL, Mexico [email protected] 2 Hongik University, Seoul 04066, Korea 3 Wuppertal University, 42119 Wuppertal, Germany

Abstract. In this work, it is presented a brief history of IDEEA and how it was created. A global course and project are presented and explain how it has developed and evolved. The Padlet online tool as an icebreaker activity is explained. Global competences are presented. Also, it is discussed how Covid19 has changed the project. Results from a survey conducted to the students from the global course and project are presented. It is concluded that the icebreaker activity with the Padlet helped the students to start working with their teams. Global competences have been developed by students by working in this type of project. Keywords: Global teams


Padlet
Multicultural competencies

1 Introduction In 1999 the PACE Partners for Advancement CAD/CAM Education) organization was created by General Motors. Over the years, PACE changed the name to Partners for the Advancement of Collaborative Engineering Education [1]. In the spring of 2017, it was officially announced that in 2018 the organization would end operations. At that moment, twenty-five companies support the organization with more than sixty academic institutions from around the world. PACE organized global projects where global collaboration was promoted. The organization created two-year projects where students were able to develop and present their work Teams of five or six different institutions were created, with more than 30 students involved in the project for a team. Also, a competition was organized each year during PACE Forum. In this forum, the teams presented their results and prototypes. Since PACE officially announced the conclusion of the program. In the spring of 2017, a group of faculty from different institutions start working and having meetings to conceive a new organization. During the PACE Annual Forum in the summer, around 30 institutions agree to participate in this organization. During 2018, the IDEEA (International Design and Engineering Education Association) was conceived and created by academic institutions. At the moment, only universities are part of IDEEA; it is also planned in the future to involved companies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 189–199, 2021. https://doi.org/10.1007/978-3-030-67209-6_21

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The primary mission of IDEEA is to develop education and research of upcoming technologies relevant to mobility, product development, and industry 4.0 and also to promote collaborative design and engineering education in global teams. And the main objective of IDEEA is to develop the engineers and designers of the future in upcoming technologies relevant to mobility, product development, and industry 4.0. In the Fall of 2018, it was decided to create a Global course to develop a project with multicultural teams. One of the objectives of this course is to promote multicultural competencies in the students. In 2019 was decided to do a second iteration of this course where Padlet tool was used. This paper will focus on the second iteration of the course, and results from a survey applied to students are presented.

2 Literature Review Following a literature review about global collaboration is presented. Jesiek et al. [2] report results from a literature review related to the challenges engineers had when they work globally. Responding to these challenges, he presents competences that engineers need to have to work in global companies, where they present three dimensions of global competencies. The following are the competencies: technical coordination, engineering cultures, and ethics, standards, and regulations. Grandin and Hirleman [3] present a report on a set of recommendations called “The Newport Declaration To Global US Engineering Education. In this declaration, they say that US engineering educators must adopt a global environment. Parkinson [4], in this work, addressed three questions regarding global competence in engineering education: Why is it needed? What does it mean? and What is the most important? In this work, he presents results from a survey done to industry and academia, where it evaluates thirteen competencies that engineering graduates need to have. The most important competencies were: appreciate other cultures, teamwork, and communication. In Streiner et al. [5] in their study, they present results from a survey applied to 200 engineering students. From these results, they do cluster maps were present seven clusters related to global competences. Motschnig and Güver [6] in their work present, they conclude that it is vital to communicate and have social skills. A critical ability to is work in multicultural teams. In this, they present a survey done to students with questions related to communication skills. Literature review regarding the Padlet is presented. Fisher [7] presents a review of how the Padlet can this be used to engage students in a class and promote collaboration. Deni and Izat [8] give an academic exploration in the use of Padlet to develop Communication skills. Haris et al. [9] the effectiveness of using Padlet in the classroom is presented. In this work, Padlet was used in an English Class, where 30 students participate. Reka Ramachandiran and Mahmud [10] present how they develop 21stcentury learning skills (4Cs) that consist of the development of creativity, critical thinking, collaboration, and communication by using the Padlet. The students that use the Padlet develop better performance in the 4C skills. Collaboration and communication skills are also global competences.

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3 The Course and Project For the two courses, it was decided to have a Global Course on Design Thinking Methodology and develop as a project a smart modular drone. All Institutions that were part of IDEEA or PACE were invited to get involved in this initiative. Due to the different time zones, it was decided that lectures explaining the design thinking process were recorded in videos that placed in a password-protected web site and YouTube. The videos could be played at any time by anyone participating. Also, in the web site, presentation slides and other documents were available. Figure 1 shows the design thinking methodology. For the 2019 project, fifteen teams were created with around ten students per team and at least one mentor. In each team, the mentor is expected to give guidance to the students in the development of the project.

Fig. 1. Design thinking process

In 2020 it was decided to repeat the same project. Once more, PACE institutions were invited; this time, we had 18 institutions from around the world. One of the institutions invited a university from Romania. It was decided to use the same material and videos already developed. Some changes were made for this second iteration of the course: – – – – –

Moodle Learning Platform was implemented for all teams. Design thinking evaluation questioners were implemented in Moodle. All the videos were available in Moodle and the website. An Icebreaker activity was implemented using Padlet. It was decided to have a larger number of students per team and least two mentors per team.

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4 Padlet Padlet [9] is an online tool that works like a bulletin board where the users could post text, pictures, or videos. Anyone who has the web link of the Padlet can post or read the messages on the Padlet board. The creator of the digital bulletin board has control over the content, design, layout, and privacy of the board. For the 2020 global course, it was decided to do an Icebreaker activity by using Padlet. This tool is being used by the Global Classroom form Vice-Rectory for Internationalization of Tecnologico de Monterrey. A space for each team was created in the Padlet, also for each student, the name and school were defined, so each student had his own space to post information about themselves, so they also could post pictures of videos of them. In the Padlet, instructions to students were placed. It was asked the students to introduce themselves to the team, to talk about their country, university, family, hobbies; also, we ask the students to replay other posts. All the students in a team had the opportunity to read and replay the post of the other students. With the icebreaker activity, it was expected the help the students develop global competencies. Global competencies are an essential part of the global course and global project. In Fig. 2, it is presented a part of a Padlet from Team 1 icebreaker activity.

Fig. 2. Padlet example of Team 1

5 Project Development and Covid19 For the two generations of the project, the challenge was the same, to develop a Smart Modular Drone Concept. Both groups of the students need to follow the design thinking methodology from the video lectures. For all the students, the first step was to find a specific application and market for the Drone. The main differences in how the project was developed and affected were the Global disease (COVID-19) Pandemic [10]. In the 2019 generation, the students had the opportunity to work locally together, to do research, find, and interact with possible

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users developing empathy for the user. In the development of the 2020 project, all schools were closed around the world, classes move to be online, and worked at home. Due to the social distancing guidelines, local meetings were not possible. Usually, local students meet at their schools, but with this pandemic, this was not possible. Regardless of this problem, team global meetings take place every week. Students worked at home, and instead of face to face research, they did online research. At the midterm moment, the results from both generations were very similar. In 2019, the students did physical prototypes that were presented during the IDEEA annual Meeting. Also, the competition was organized, and a final presentation was done during this meeting. An Online Competition took place at the end of July 2020. For the 2020 project, it was expected more virtual results; it was complicated to develop a physical prototype by the teams, due to the pandemic will be difficult for students to get together. Likewise, physical tests with users were difficult to perform. Some testing was done by doing FEA simulations or rendering simulations. Student motivation is another challenging problem; some teams are having problems maintaining all the students involved.

6 Global Competences Global Competencies are skills expected to be developed by students during the development of the projects by working in global teams. The competences are divided into five that are de following: – Multicultural Communication competence is related to the knowledge and ability to communicate. This is the ability to speak, read, write, and listen in a common language used by the team. It most of the teams, the common language is English. Some students have problems communicating and understanding. Some students say that there is a huge language barrier in some teams. – Multicultural involvement competence could be defined as cross-cultural attitudes and beliefs. Meaning the students have an appreciation for other cultures, openness to understand other cultures, and be flexible in understanding how to work with other cultures. Develop skills like empathy, have a sense of cultural equality and global citizenship. Students need to have the desire to understand and explore other cultures. – Multicultural knowledge this competence is the skill of understanding the world in terms of values, geography, religion, language, culture, political and economic systems, including current and historical world events. Understanding how the team member manages time is part of each countries culture. During the project, some countries change of time zone due to daylight savings and meetings change. – Effective Global Teams competence is the ability to work in a global team toward having a common goal, using tools to manage the different tasks the teams need to do. – Engineering and Design Collaboration is a key competence. It is related to how engineers and designers communicate, share information, and understanding of the influence of culture on the engineering or design profession and engineering practices.

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7 Survey and Results A ten questions survey was applied after the mid-term presentation of the 2020. To the survey, only 69 students responded. Not all the questions are presented in this work. In Fig. 3, we ask the students from witch team they were. At least one member of each team answered the survey. Some teams like A or C, almost all the team members answered the survey.

Fig. 3. Team membership

For Fig. 4, it was asked if they used the Padlet in the Icebreaker Activity. 90% of the answers were positive in doing the activity; only 10% did not use the Padlet.

Fig. 4. Participation in the Padlet Icebreaker activity

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In Fig. 5, it was asked to the students if this activity help to start working on the project. 70% of the students answer positive and 30% negative. From the previews question, 10% did not use the Padlet, and probably these students are in the 30%.

Fig. 5. Did the Padlet activity help start working?

In Fig. 6, it was asked to the students what tools they were using to communicate with their teammates. Most of the students say they are WhatsApp 50%, Zoom 45%, and Skype 43% also, they mention other tools like Trello for project management. Communication in teams has been critical.

Fig. 6. What tools were used to communicate?

Figure 7 has a critical question; this was an open question about if everybody is working in the teams. As the question was open, we received different answers, and they were categorized in positive (teams that do not have problems with their teammates) and negatives (teams that are having problems). 46.51% answers were positives, 51.16% were negative, and 2.33% were categorized as others.

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From the negative answers, most of the students complain of teammates that do not do their job or simply they are lost and do not answer emails or other communications. In past experiences, many students get lost when they finish the course where they were enrolled, or they have lost interest and motivation.

Fig. 7. EveryoneTeam actively participating?

In Fig. 8, it was asked to the students what global competence was developed by doing the Icebreaker. Communication got 50%, then Multicultural Involvement 19% Multicultural Knowledge 14% and last Engineering collaboration skills 1.7%.

Fig. 8. Competence developed by students doing the Icebreaker activity

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Figure 9, it was asked to the students if they reviewed the videos of the Design Thinking course. This year we give them two options one was the instructor web site, and the second was the Moodle web site, where also the videos were placed. 83% of the students say they were checking the videos, and only 17% say they don´t see them. We can conclude that most of the students are reviewing the videos.

Fig. 9. Review design thinking videos

In Fig. 10, it was asked to the students to rank by importance the global competencies they had developed in the project. For this ranking, a score was calculated depending on the number of people and the importance they give. Multicultural

Fig. 10. Global competence importance score by students

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communication got a 3.75 score, meaning that this is the most important competence the student think they had developed. The second competence was Multicultural involvement with a 3.15 score. The third competence was Multicultural Knowledge with a 2.79 score. Students had developed all global competencies through project development. It is challenging for students to work, communicate, and do teamwork with people from other countries; sometimes, they only see their faces in the web meeting.

8 Conclusions From the survey’s results, it can be concluded that most students use the Padlet in the icebreaker activity. Also, most of the students think that this activity helped start working with their team. Students believe that Padlet helps them developed communication competence with their team. In the survey, it can be observed that students had developed global competencies through the development of the global project. For students, it is challenging to learn, communicate, and do teamwork with people from other countries; sometimes, they only see their faces in the web meeting. At the mid-term presentation, it was announced that the IDEEA Forum would be online due to the COVID 19 pandemic. This affected student motivation to work on the project in many teams. From the survey, it was appreciated that some teams had motivation problems. Teams had problems keeping all their team members in the project. For many students, the motivation was to travel. For others, the motivation was the grade of the course where the students were enrolled. For many schools, the semester ended before, and they have got their grade. The mentors were another factor that was key to maintain the team together is also how the mentors are involved and motivated their team students. By developing this type of project, students have learned the following: – – – – –

Collaborate in an international, interdisciplinary environment Apply knowledge from their area of expertise in a global team Structure and organize global teams and their tasks. Develop communication skills in a global environment. Learned about other cultures and how they work.

Finally, it can be concluded that the Global course and project help students developed global competences. The COVID 19 pandemic has made it more difficult and challenging for mentors and students. All Teams presented their work with good quality and content during the mid-term and final presentation, although not all students end the project.

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Acknowledgments. The authors acknowledge the support for the Padlet from the Vicerectoria de Interacionalizacion of Tecnologico de Monterrey. Additional support was provided by Tecnologico de Monterrey and the Research Focus Group of the Automotive Consortium in Cyber-Physical Systems.

References 1. PACE|Partners for the Advancement of Collaborative Engineering Education. http:// pacepartners.org/ 2. Jesiek, B.K., Zhu, Q., Woo, S.E., Thompson, J., Mazzurco, A.: Online J. Glob. Eng. Educ. Competency Context Situations Behav. 8 (2014) 3. Grandin, J.M., Hirleman, E.D.: Educating engineers as global citizens: a call for action/a report of the national summit meeting on the globalization of engineering education. Online J. Glob. Eng. Educ. 4, 1–28 (2009) 4. Parkinson, A.: The rationale for developing global competence. Online J. Glob. Eng. Educ. 4, 2 (2009) 5. Streiner, S., Vila-Parrish, A., Lunsford, P.: Using concept mapping to investigate engineering students’ global workforce perceptions. Online J. Glob. Eng. Educ. 9, 1 (2016) 6. Motschnig, R., Güver, S.: Improving communication in multicultural teams - A web-based model and its application in project management education. In: Proceedings - Frontiers Educational Conference FIE, October 1–9 2017 7. Fisher, C.D.: Padlet: an online tool for learner engagement and collaboration. Acad. Manag. Learn. Educ. 16, 163–175 (2017). https://Padlet.com 8. Md Deni, A.R., Zainal, Z.I.: Padlet as an educational tool: Pedagogical considerations and lessons learnt. In: ACM International Conference Proceeding Series, pp. 156–162 (2018) 9. Haris, M., Yunus, M., Badusah, J.: The effectiveness of using Padlet in Esl classroom. Int. J. Adv. Res. 5, 783–788 (2017) 10. Ramachandiran, C.R., Mahmud, M.M.: Padlet: A Technology Tool for the 21st Century Students Skills Assessment, pp. 101–117 (2018) 11. Padlet is the easiest way to create and collaborate in the world. https://padlet.com/ 12. Coronavirus disease 2019. https://www.who.int/emergencies/diseases/novel-coronavirus2019

Low Cost Simulation Lab for Teaching Control Theory Concepts Timber Yuen(&) Automotive and Vehicle Engineering Technology, School of Engineering Practice and Technology, Faculty of Engineering, McMaster University, 200 Longwood Road S. MARC 270, Hamilton, ON L8P 0A6, Canada [email protected]

Abstract. Physical lab experiments, provide concrete experience to students, are considered an integral part of engineering education. In April 2020, Canadian universities were under quarantine due to the COVID-19 pandemic. Due to the need for social distancing and other uncertainties caused by the virus, instructors needed to convert their courses and labs in preparation for online delivery in September 2020. The author is responsible for a Control Theory course in Level 3 of an Engineering Technology Program at McMaster University. There are six faceto-face labs in this course. The conversion and implementation of one of these physical labs into a simulation lab for online delivery is the focus of this study. The drawbacks and benefits of using Excel simulations for teaching control theory concepts are also discussed. Keywords: PID tuning


Simulations
Experiential learning

1 Introduction 1.1

Background

Traditionally, physical lab experiments are considered an integral part of engineering education. Students are scheduled to use a piece of equipment which is designed to achieve certain learning objectives. However, due to the COVID-19 pandemic in 2020, students were asked to stay at home and most of the face-to-face experiments had to be converted into online learning sessions. One way to provide online learning is to use simulation tools. Well-designed simulation tool can be used to demonstrate abstract concepts and provide feedback to the users instantly [1]. Flight simulators, for example, are commonly used to train pilots. However, due to the large numbers of physical lab experiments to be converted and the limited budget provided by the school, low cost simulation tool is the idea here. This paper focuses on the design and implementation of a low cost simulation tool to teach control theory concepts. The pros and cons of a simulation tool designed using Microsoft Excel is discussed. The concept of using spread sheet to develop simulation tool has been discussed by other researchers [2]. There are many advantages in using simulation tools. They can be easily developed and modified. Also, students can use the tools to learn regardless of © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 200–205, 2021. https://doi.org/10.1007/978-3-030-67209-6_22

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time and place. To illustrate the procedure used to develop these simulation tools, an example is presented here. 1.2

Learning Objectives of the Original Lab Experiment

Fig. 1. Servo motor control experiment hardware

The original lab equipment (Fig. 1) is a DC Motor Trainer manufactured by Quanser Engineering Inc. A plastic ruler has been added onto the equipment to make it look more interesting to the students. With the plastic ruler, the system is changed from a rotating disk into a one link flexible robot, and the oscillation of the ruler is more obvious. The system is a classical single-input-single-output system. The learning objectives of this lab experiment include the following: (1) To provide a PID controller tuning experience (2) To study the effects of the Kp, Ki and Kd gains (proportional, integral and derivative gains) (Fig. 2), and (3) To study the system transient response and steady state response. In the original lab, the input type is limited to a unit step input (effects of sinusoidal inputs are to be investigated in another experiment). The students can dynamically change the system parameters and immediately observe their effects on the system behavior – both physically from the single axis flexible link robot and the plot on the screen.

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Fig. 2. Graphical User Interface (GUI) used in the original experiment

2 Development of the Excel Simulation To develop the Excel simulation, the single axis flexible link robot is first modelled as 2nd order mass, damper and spring system. The model is then converted into a transfer function in the Laplace S-domain. Subsequently, the PID controller is added onto the system and the closed-loop system block diagram is shown in the Fig. 3 below.

Fig. 3. PID control loop block diagram

After simplifying the block diagram into a single block, the system is converted back to the time domain to develop the Excel simulation. The Excel simulation follows the original lab and uses a unit step as an input. The output is plotted right on the Excel sheet. In order to study the effects of each of the Kp, Ki and Kd gain terms on the transient and steady state response, the students is asked to change each of the gains one at a time. A sample output of the Excel simulation is shown in Fig. 4 below.

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Fig. 4. PID control excel simulation output (stable system)

3 Drawbacks of the Excel Simulation and Potential Solutions 3.1

Drawback #1 – Missing Concrete Experience

It has been pointed by Bread [4] that “the more senses we use in an activity, the more memorable the learning experience is going to be”. For example, in the original lab equipment, students could change the gains and get a motor completely out of control and sense the severe mechanical vibration. However, this type of “concrete experience” as described by Klob [3] as essential for learning, is missing in an Excel simulation. One potential solution to this issue is to introduce the Excel simulation lab with a Youtube video showing how a poorly tuned motor would behave. This could compensate for the missing visual and audial stimulation in the Excel simulation. 3.2

Drawback #2 – Missing Trouble Shooting Experience

A hands-on lab with actual equipment would provide trouble shooting opportunities on mechanical and electrical hardware. However, in an Excel simulation lab, these problem solving opportunities are missing. Although the trouble shooting opportunity is missing, this could be considered a major benefit of a simulation lab because the student can stay focus on learning the expected outcomes of changing the PID gains. 3.3

Drawback #3 – Missing Team Work Experience

While the physical lab would encourage a group of two students to work on the equipment together, the main reason for developing the Excel simulation is to allow students to use the tool at home individually. The sense of partnership and team work is missing in the learning process using the Excel simulation.

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To compensate for this, the instructor could assign two students per group to work on the simulation in a “breakout room”. Some online platforms such as Zoom would have this feature available.

4 Major Benefits of the Excel Simulation 4.1

Benefit #1 – Infinite Input Range

Since there is no fear of damaging the equipment or creating safety issues, students could have the freedom of entering parameters into the simulation that is considered to be “outside the scope” or even “dangerous” to the original equipment. For example, as shown in Fig. 5 below, a set of PID gains which caused the simulation system to become unstable was able to be entered and implemented in the Excel simulation. However, in the original experiment, in order to protect the equipment and the students, these PID gains would not even be accepted by the GUI.

Fig. 5. PID control excel simulation output (unstable system)

4.2

Benefit #2 – Unlimited # of Use

Instead of limited to the 2–3 h scheduled for the physical lab, the Excel simulation is available to the students even after the lab period. This is a major benefit for the students because they can run the simulation over and over again at home to review concepts especially before the final exam for reviews.

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Benefit #3 – Easy to Expand and Maintain

Since it costs almost nothing to increase the number of sets of simulation worksheets as the class size increases, the Excel simulation allows an easy adaptation to class size expansion. Also, the simulation can be updated quickly and there is no hardware to maintain.

5 Conclusions In conclusion, a low cost Excel simulation lab experiment has been developed for a Control Theory course. The simulation lab meets the original learning objectives of the original PID controller tuning lab. Also, the pros and cons of the simulation lab and some potential solutions have been discussed.

References 1. Lateef, F.: Simulation-based learning: just like the real thing. J. Emergencies Trauma Shock 3 (4), 348 (2010) 2. Aliane, N.: Spreadsheet-based control system analysis and design. IEEE Control Syst. Mag. 108–113 (2008) 3. Beard, C.: The Experiential Learning Toolkit: Blending Practice with Concepts, vol. 129. Kogan Press, London (2010) 4. Kolb, D.: Experiential Learning as the Source of Learning and Development, vol. 31. Prentice Hall, Englewood Cliffs, NJ (1984) 5. Beard, C.: Transforming the Student Learning Experience: A Pedagogic Model for Everyday Practice, Hospitality, Leisure, Sport and Tourism Network: Enhancing Series: Student Centred Learning (2009)

Work-in-Progress: Blended Learning in Engineering Education in Peru. A Systematic Review of University Theses Osbaldo Turpo-Gebera1 , Juan Zarate-Yepez1(&) , Francisco García-Peñalvo2 , and Fernando Pari-Tito1 1

Universidad Nacional de San Agustín, Arequipa, Peru {oturpo,jzaratey,fpari}@unsa.edu.pe 2 Universidad de Salamanca, Salamanca, Spain [email protected]

Abstract. Blended Learning is established as a standard modality in the training of engineers in Peruvian universities, establishing objects of study that show its transcendence and potential. In this sense, the theses reports presented to the universities have been systematically reviewed. Eight thesis reports were recovered from the Repositorio Nacional de Trabajos de Investigación (RENATI). The results show a growing research interest in areas and fields of teaching rather than management; high concentration of research in postgraduate rather than undergraduate studies; and centrality of knowledge in the capital (Lima) instead of the provinces, more in public than in private universities as well as emphasis on quantitative studies and techno-pedagogical orientations combined with convergent models. Such dynamics bring Latin American contexts closer, and places them far from other realities. Keywords: Blended learning


University theses
Systematic review
Perú

1 Introduction Information and Communication Technologies (ICT) bring about changes in personal and social interaction, inducing changes in the ways we relate to the subjects, processes and spaces of pedagogical interactivity. The paradigmatic turns are propitiating adaptations that contribute to the improvement of the formative process [1]. In this perspective, Blended Learning (BL) is instituted and consolidated as a “standardized” modality [2], which facilitates increasing access to learning opportunities, as well as collaborative interactivity, among other potentialities [3]. Essentially, BL favors the techno-pedagogical confluence, connecting worlds that are artifactually “separated,” so that knowledge flows on multiple platforms, sharing resources, spaces, etc., that strengthen the relationship mediated between teachers and students [4]. BL as a training modality incorporates an array of technological tools, and pedagogical approaches and methods [5, 6] to generate more active and adapted learning in a flexible and personalized didactic context [7]. In BL, a high level of acceptance is obtained among students and professionals, who affirm that BL led them to achieve © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 206–216, 2021. https://doi.org/10.1007/978-3-030-67209-6_23

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satisfactory results. The role of the teacher-tutor acquires relevance [8] by relating the conceptual and practical aspects, the diversity of learning styles, and directing it towards the improvement of the educational quality. The construction of knowledge in BL involves greater tutorial intervention, as well as feedback and continuity of critical debates, bringing together computer-mediated collaborative learning (CMC) with factual relationships (face-to-face), along with other complementary activities (workshops, laboratories, etc.) that contribute to the amplification and enhancement of learning [9, 10]. The operation of BL allows the use of techno-pedagogical devices (teleconferences, forums, etc.) together with a series of didactic strategies (Flipped Classroom, Serious Games, etc.), configuring a technopedagogical ecosystem that recovers the social presence and educational participation in the pedagogical dynamics, institutional management and technological infrastructure [11, 12]. In BL, quality is defined by perceptions and emotions, motivation and learning styles, integration of experiences and ideas, as well as instructional design, altruism, participation and interaction [13]. These components make BL a viable alternative, where it is not necessary to share the same spatial context, but rather a learning one which involves the use of technological tools and group discussions. BL goes beyond the integration of training spaces; it involves the concurrence of learning strategies [14] and the indistinct confluence of the face-to-face and virtual modes. In this way, the students advance towards autonomy, overcoming the in person-virtual dichotomy, immersing themselves in the convergence and techno-pedagogical continuity [4, 6, 15]. In the transition of BL, the formative processes are beneficial, collaborative, flexible and motivating; likewise, they induce new forms of teaching and learning, beyond the spatial-temporal coordinates [13, 16]. BL has transformed the traditional educational spaces causing an efficient use of technology [17], moving toward an intense social interaction and generation of positive feelings, by achieving greater effectiveness in problem solving [18]. The emergence of new learning devices, such as augmented reality and others, has led BL into new scenarios [19], which implies a new vision and renewed teaching practice, intensely creative and prone to more realistic scenarios, with enriched, safe and controlled environments. The technological, institutional, educational, and other changes in BL, raise the need to investigate the research dynamics of those who choose them as objects of study. Reviewing the Latin American context, through research published in scientific journals, we discover the thematic contexts, methodological orientations, etc. that point to the prevalence of descriptive studies without empirical references, oriented towards disciplinary areas such as psychology, education, economics, and computer science [20]. On the other hand, by studying the same spatial context, the multiple denominations of BL (mixed, hybrid, semi-presential, virtual distance) become evident as a paradigm that mixes or hybridizes, maintaining the presential-virtual duality [21]. In other studies, the evolution and techno-pedagogical transitions of BL are analyzed: from the combination to the convergence of mediations and resources, through the integration of environments [4, 21]. Reviewing the trends and impact of BL in Latin America, we find that didactic interaction has generated positive results, as well as the development of cognitive skills and critical and constructive thinking for problem solving [22]. Analyzing university

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theses in Peru, it was found that BL is applied to the training in different professional fields. The results help us recognize differences in theoretical and methodological approaches and emphasis on training areas [23, 24]. The different studies provide a global understanding of BL in teaching; there is no specific research on BL in Peru in training by profession, except for the field of Communication for Development [25]. Hence, this research, due to its particularity on the specialized knowledge of engineering education, brings specific situations to the considerations assumed of the university reality of Peru. Having provided an overview of what BL is and its trends and impact in Latin America, the second section will describe how the study was carried out, to finally mention the results of the study that focus on the situation and evolution of university research of BL in engineering education in Peru, the fields and sub-fields of knowledge of BL in engineering education, the infrastructure supporting the activities of BL in engineering training, the findings of the research on BL in engineering education, and BL models in engineering training with techno-pedagogical mediation systems.

2 Method In order to determine the production of knowledge about BL training in engineering, eight thesis reports have been recovered from the National Research Work Repository (RENATI), managed by the National Superintendence of Higher University Education (SUNEDU): http://renati.sunedu.gob.pe/. The documents come from Peruvian universities, which voluntarily allow access to the theses of their graduates and the theses defended in foreign universities and deposited for the purpose of degree recognition (Resolution No. 033-2016-SUNEDU/CD). The research questions that guided the review are: – RQ1. How has university research on BL evolved in engineering education, according to degree, geographic region and university ownership regime? – RQ2. What are the fields and sub-fields of knowledge of BL in engineering education addressed in Peruvian university theses? – RQ3. What significant findings are evident in Peruvian university theses when investigating BL in engineering education? The following inclusion criteria were taken into account for the selection of thesis reports: – Search term: “Blended Learning”, “Semi-presential”, “Engineering” and “Technology”. – Scope. Tertiary education (university and technological institutes). – Period of publication of university theses (last 5 years): 2015–2019. – Full access to the thesis report. – Research work of empirical nature.

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The search was carried out between February and March 2020. The determination of the analyzed theses followed the sequence of analysis below:

Fig. 1. Study sample determination sequence.

Fig. 2. Theses according to university of origin

These 14 theses constitute the corpus of analysis used in the development of the aspects that define BL in engineering education in Peruvian universities.

3 Results Considering the systematized information, arguments to answer the research questions (RQ) were formulated from the comparison, contrast and qualitative analysis of the sorted data [26].

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Situation and Evolution of University Research of BL in Engineering Education in Peru In terms of the theses that investigate BL in engineering education in Peru, the last 5 years demonstrate its presence as an object of study. Seventy-nine percent of the theses correspond to graduate studies (5 master’s and 6 doctorate), 21% corresponds to undergraduate studies in different areas of engineering and technology.

Fig. 3. Evolution of university research of BL in engineering education.

In the first years of the study period, the majority of the theses related to engineering education in Peru are for graduate (Master’s degrees and doctorates) works, with a low incidence of undergraduate works; whereas in the last years, both graduate and undergraduate levels share interest in these kinds of studies. The evolution shows the growing interest in the research of BL in engineering education. BL as a study modality represents a topic of growing interest in different areas of professional training, with a little lower incidence in engineering and technology [23], yet its importance is tangible today, given that the country is moving rapidly through a process of change in university education towards greater virtualization.

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Fig. 4. Universities where BL theses in engineering education were defended.

In Peru, private universities outnumber public universities in terms of enrollment and coverage. The largest scientific production of BL in engineering education is concentrated in public universities (in 7 of the 10 universities). In the national repository there is a thesis from a foreign university, which was deposited for the purpose of recognizing the foreign degree in the country (homologation). It is noticeable that out of the 10 universities that researched BL in engineering education, only one is located in the capital (Lima), the rest are located in the provinces, in the periphery of knowledge. Fields and Sub-fields of Knowledge of BL in Engineering Education The determination of the fields responds to the nature of the studies, some of which are directed to the development and academic strengthening through the subjects that compose the curricula of the engineering careers, namely general studies (GS) and specialized studies (SS), and others related to the management of the institution and study platform. Table 1. Fields and subfields of BL in engineering education addressed in university theses. Knowledge field Sub-knowledge field Teaching Mathematics (GS) (86%) Physics (GS) Systems dynamics (SS) Humanities (GS) Communication (GS) Management Mentoring support (14%) Social responsibility Total

2015 2016 2017 2018 1 1 2 1 1 1 1 1 1 1 1 3 6 1 2

2019 Total 1 4 1 1 3 1 3 1 1 2 14

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The field of knowledge prioritized in universities that conduct research on BL in engineering is teaching (86%), with an emphasis on the GS (79%) rather than the SS (7%). An even interest is observed on both science and humanities-related subjects due to the emphasis of the current University Law on a wholistic education that includes general and specialized students as a graduation requirement. Another field addressed in the research is related to management (14%) in two areas or subfields complementary to university training. Infrastructure Supporting BL Activities in Engineering Training In BL, the infrastructure includes both virtual and face-to-face formats, which are employed according to the techno-pedagogical development of each institution. The thesis reports point out the access and capacity gaps. Various resources are recognized (not always cutting-edge ones), while attendance is marked exclusively by being physically present at classes at the university.

Fig. 5. Supporting infrastructure

In the experiences researched, the support infrastructure is far from the avant-garde conceptions and resources typical of other realities. In the Peruvian universities, in terms of virtuality only 75% of public universities and 25% of private universities have virtual platforms. Universities resort to various digitalized resources such as the use of USBs, CDs or printed books for virtual interactivity, more frequently in public universities than in private ones. In terms of attendance, universities in general consider the classroom as the only setting for physical work meetings. None of the research considered other possibilities, such as synchronous attendance or visits to other training scenarios. Findings of the Research on BL in Engineering Education The educational aspects declared in the research, as evidence favorable to the formation of students are considered achievements; while the limitations are given by the aspects that hinder academic progress.

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Fig. 6. Achievements and limitations of BL in engineering education

The academic achievements identified in BL’s theses in engineering education have been classified in four domains: 1) cognitive-epistemic: breadth of knowledge and critical thinking, 2) social: confidence and autonomy, 3) formative: tutorial accompaniment, responsibility, time management and autonomy, and 4) technological: digital literacy and interactivity. Although the boundaries between them are blurred, certain predominance can be expressed. Among the limitations are those of a didactic nature, directly related to the teaching of faculty members, in most cases, where teachers are in turn tutors. The role of teacher tutors ends up overloading the training activity, since the teachers need to both prepare content and accompany the process [27]. BL Models in Engineering Training with Techno-Pedagogical Mediation Systems In the different realities, experiences that express the changes of BL are described. These experiences explain the diverse techno-pedagogical transitions that refer to a normalized modality, that is to say, transitions with an own identity. Among the evolutions we can recognize: i) separate or combined systems, which distinguish moments of presence and virtuality, ii) mixed or integrated systems of hybridization of training scenarios, and iii) expansive or convergent systems, where the boundaries are diluted and continuity prevails [4, 27–29].

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Fig. 7. Pedagogical-technological mediation systems

The referents assumed by those who investigate BL in engineering education are basically the combined systems, where the virtual and face-to-face moments are defined and separated, which places it in its beginnings. Only one study refers to an integrated model of hybridization of components and training moments.

4 Conclusions The review of the scientific production of BL in engineering training in Peruvian universities, from the theses analyzed, reveals its emergence as an object of study and growing interest. The last five years have revealed the need to adapt the training models to the greater virtualization that the country is experiencing, and to accelerate the changes brought about by the university law. The research analyzed reveals the shift in the centrality of the knowledge generated from the capital to the provinces given that more universities in the regions are researching BL in engineering training, more in the public universities than in the private ones, more in the field of teaching than management, more in general studies subjects than in specialized ones. The infrastructure supporting BL in engineering training expresses the delays with respect to other realities, since there is no greater innovation, and resources that are far from the vanguard are used. Among the significant results referred to in the theses, a greater distinction is made between those of a cognitive and formative nature, among others that are equally important; while the limitations are more of a teaching nature. The research reviewed, when contrasted with the techno-pedagogical mediation systems, refer us to the dawn of BL because they prioritize the combinatorial systems of separation of components.

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In essence, the analysis of the uniqueness of Peruvian university research reveals continuities and disparities with respect to global dynamics [30]. Research on BL in Peru is currently in its third transitional phase (2010–2013), which is to “talk about the experiences of students or teachers regarding the implementation, application and results obtained” [31]. This is a stage that coincides with the dynamics experienced by Latin American countries, and is far from the experiences of European countries, which are increasingly innovative. The path of the review reveals proximities and routes of advances and perspectives of the transformations assumed in the development of BL [17].

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Innovation and Issues in Education

Student Perceptions of Screencast Video Feedback for Summative Project Assessment Tasks in an Engineering Technology Management Course Allan MacKenzie(&) McMaster University, Hamilton, ON, Canada [email protected]

Abstract. The paper examines the use of screencast video software for student project feedback in an undergraduate engineering technology management course. The course utilizes two team-based project summative assessments in the form of presentation slide decks containing detailed notes during the term. These assessments integrate and scaffold into a final presentation and comprehensive written project report due at the end of the course. The challenge was how to provide detailed, high-quality and specific feedback for a project that scaffolds across the entire term to enhance student learning and future performance. In fall 2019, non-traditional, screencast video software was utilized for instructor-student feedback. Preliminary findings indicated that students appreciated this method of input because it was good quality; was easier to understand; had more depth, and was more personal than written feedback. From the faculty’s perspective, this method allowed for more comprehensive comments on the student’s work in less time per assessment compared with using written feedback. The paper also presents a research design for a more deliberate evaluation of using screencast technology in the next course iteration. Keywords: Screencast video feedback Summative assessment feedback


Engineering management


1 Introduction The objective of this paper is to share the experience of using screencast technology in an undergraduate engineering technology management course, Entrepreneurial Thinking and Innovation, that has an extensive group project that requires comprehensive instructor feedback multiple times throughout the term. The research on the perspectives of providing high-quality and specific feedback for students in higher education is surveyed. The perception of students, along with the operational factors of using screencast technology, is discussed within the context of the particular course. Lastly, the paper will present a research design for a more deliberate evaluation of using screencast technology for feedback on the summative assessment tasks in a future iteration of the course.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 219–229, 2021. https://doi.org/10.1007/978-3-030-67209-6_24

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Let’s begin, however, with an explanation of screencast technology, and the use within the parameters of his study. Snagit, a third-party screen-capture software, was used to provide asynchronous visual annotation combined with audio commentary on student presentation slide decks for feedback purposes at various milestones in the course. The screencast technology records what is happening on the user’s screen, along with comments spoken into a microphone. After the screencast feedback was recorded, it was exported as a.mp4 file and uploaded to the course LMS dropbox assignment folder. When students open their team’s screencast, they see their original slide deck, along with the instructor’s cursor movements, and narrative feedback about their presentation. The members of the student project team can watch the screen capture recording and listen to the instructor’s personalized comments about specific elements of their presentation either as a group or individually.

2 Assessment Feedback Perspectives It is commonly recognized that assessments are essential to student learning in higher education, with feedback being a central aspect of the assessment process in terms of elevating student performance and achievement [1–6]. Further, good quality and timely feedback are critical features for supporting effective student learning processes and in developing the student-instructor relationship [7, 8]. Gibbs and Simpson [4] specify seven conditions for successful feedback: a) sufficient in terms of quality and quantity, b) relevant to students’ performance rather than their personalities or characteristics, c) timely; addressing present and future issues related to students’ learning, d) appropriate to the purpose of the assessment and its criteria, e) understandable; so that students comprehend what to do next, f) available to students, and g) useful and related to future work. In the end, feedback aims to promote cognitive and analytical competencies that enable the student to assess their progress and apply a critically reflective approach to academic work and professional practice [9]. Despite the literature agreeing on the importance of assessment feedback as part of the learning process, the same body of research also points out that many students do not value feedback comments [10–13]. In some cases, the students do not even bother to read feedback once their work has been assessed, preferring only to know their grades [14]. Yet if students do read the feedback, some researchers have argued that they do little with it [12]. A qualitative study by Young [15] suggests, it is the student’s level of self-esteem that affects the messages they receive—both positive and negative. “Those with low self-esteem tend to view all feedback as a judgement of ability, while those with high self-esteem do not. High and medium self-esteem students tended to see feedback as something they were able to act on and make use of; students with low self-esteem are more likely to feel defeated and may even consider withdrawing from the course” [15]. Sadler [16] argued that to learn from feedback students need a) to have a concept of the reference level they are aiming for, b) an ability to compare their current standard of work with a reference level and c) to be able to engage in appropriate behaviour that enables closure of the gap between the reference level and their current level.

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Research has correspondingly demonstrated the method by which students receive information may influence their ability to assimilate it [17]. There is evidence that students are undertaking less reading for pleasure [18], which can lead to students becoming less comfortable in processing written information. Combined with the visual, aural, and kinesthetic learning styles that dominate students enrolled in STEM programs, alternative forms of feedback delivery may be more efficacious [19]. In addition to the challenges associated with feedback comprehension, most educators find that providing quality feedback to students is very time-consuming [7, 20]. There are also concerns about the lack of student engagement with the feedback process even when timely and good quality feedback is provided [14]. In response to these criticisms, alternative feedback approaches such as audio, video and screencasts are being explored and adopted by some educators [1]. These alternative feedback modes can offer more productive inputs for students and also have the benefit of being more personalized by addressing the individual needs, strengths and weaknesses of the students [21]. For example, Harper et al. [22] identified several benefits of spoken feedback compared with written feedback that has emerged across the research: • It is more engaging due to variation in the tone of voice and expression. • It is easier to understand since it is more nuanced through intonation, potentially helping students to discern what is essential within the comments. • It has more depth due to the instructor being able to say more than in written feedback. • It is personal, with students feeling as if the instructor is engaged more with their work and cares about them to a higher degree. • It increases the sense of instructor presence: students feel as if the instructor is there with them as they listen to their feedback. Screencasting technology takes this to the next level by incorporating all the benefits of oral input, in combination with visual annotation tools to spotlight focus areas within the particular assignment. Research suggests that screencast technology is a logical approach for feedback in higher education due to its numerous benefits for students and instructors [23–27]: • It is easy to follow and provides students with more information on their assignments than written corrective feedback. • It potentially improves students’ listening skills. • With the auditory and visual combination, screencasting better supports a variety of learning styles. • It reduces time devoted to giving written feedback and allows the instructor to invest time in providing high-quality feedback. • Due to its conversational character, it can increase rapport between instructors and students. • It is suitable for individual or group student feedback and readily supports either blended or fully online learning modalities. • It is available 24/7, and students can easily access videos across time zones. • It gives students the flexibility to pause, rewind, and watch the screencast more than once.

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• It is multimodal, supporting the idea of using more than one semiotic mode, such as print, sound, and imagery to contribute to conveying the meaning of the instructor comments. Feedback through screencasting technology aims to improve students’ future assessment performance, increases the nuance of the input, and allows for enriched clarity to make revisions based on the comments provided. It generally enhances student engagement with assessment deliverables, better accommodates different learning styles, and usually improves the quality of the input supplied by the instructor [28, 29].

3 The Study and Results 3.1

The Course Setting

The undergraduate engineering technology programs within McMaster’s University W Booth School of Engineering Practice and Technology integrate technical comprehension with cross-boundary skills in business and management. The study occurred in the fall of 2019 within a mandatory third-year Entrepreneurial Thinking and Innovation course with the students enrolled across the program streams of Automotive and Vehicle Engineering Technology, Biotechnology, and Automation Engineering Technology. The course introduces students to the interrelationship of entrepreneurial thinking and innovation at both the industrial and individual level. The structure of the course follows the fundamental building blocks of an enterprise-level business case. The Business Case Project is the main deliverable, worth 45% of the overall course grade. Self-selected small student teams develop a robust case that would potentially allow them to secure resources and the allocation funds for a “real-world” new product opportunity, or a unique capability or significant product extension within an enterprise. The Business Case Project is delivered across multiple phases that scaffold into a final presentation and comprehensive written project report due in the last week of the course. • Phase 1: Idea Screen Presentation (5%): This deliverable is due in week four and consists of a 10-min presentation supported with an accompanying deck of a maximum of eight slides. The presentation focuses on defining a real-life organizational problem or opportunity the team intends to solve, along with business objectives and metrics relating to the identified opportunity. • Phase 2: Scope Screen Presentation (10%): This deliverable is due in week seven and consists of a 15-min presentation with an accompanying slide deck. The presentation includes amended material from the Idea Screen phase, along with a thorough Environmental Scan, Stakeholder Analysis, Risk Impact and Assumptions, along with three or more viable Solution Alternatives. Required within the notes section of the slide deck is detailed written comments, including citations that thoroughly explain all the critical areas of the team’s business case.

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• Phase 3a: Final Business Case Presentation (10%): This deliverable is due in either week 11 or 12 near the endterm and consists of a 20-min presentation directed at the executive team level with accompanying slide deck encapsulating the team’s entire Business Case. • Phase 3b: Business Case Written Report (20%): This final report deliverable includes all the sections of the business case, including revisions based on the instructor feedback, from the earlier Idea and Scope Screen Presentations. It consists of the identified opportunity, external and internal influences, solution alternatives, feasibility and impact analysis, stakeholder and risk analysis, detailed and accurate estimated financial metrics and return on investment spreadsheets, implementation plan, and any relevant supporting documentation or evidence. 3.2

The Instructor Experience

The challenge faced by the author/instructor was how to provide detailed, high-quality and specific feedback for the Business Case Project that scaffolds across the entire term to enhance student learning and future performance. In fall 2019, 85 students were enrolled across two sections of the course, translating into a total of 17 project teams. An essential task for the instructor is providing quick assessment turn-around so the students can assimilate the feedback to improve their performance before the next phase of the project. The author adopted TechSmith’s screencast video software, Snagit, to provide instructor-student feedback. The technology allowed for the screen recording of student PowerPoint slides, accompanied by a narrative that was exported as a.mp4 file and uploaded to the course LMS to be viewed by the student project team. The technology also allowed the instructor to spotlight specific areas within the slides using the cursor to draw attention to which elements were being discussed during the narrative. Each of the screencast feedback recordings ranged from five to eight minutes, accompanied by a word document rubric highlighting the grades received on the required presentation elements. The total instructor administration time needed to read and review the student presentation, complete a screencast feedback recording, finalize the rubric and upload these files to the course LMS averaged around 45 min per team for the Phase-One Presentations. There was a modest increase in administration time for the Phase-Two Presentation, averaging approximately 60 min for each team’s feedback. Compare to previous offerings of the course, this was a substantial reduction of time required by the instructor to grade and provide feedback. In earlier offerings of the course, the author utilized the review functionality within Microsoft’s PowerPoint to type feedback comments on individual slides, as well as summary comments on the rubric form. The time required for this approach ranged from 90 to 150 min for each presentation.

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Unfortunately, many times, students could not find the feedback within their slides due to the small size of the comment box symbol in PowerPoint. This resulted in students overlooking vital feedback and not comprehending their assigned grades. The built-in default positioning for the comment function in PowerPoint locates a tiny comment box at the top of a particular slide. This constraint led to the instructor having to write detailed descriptive comments to orientate the students about which specific item on the slide was being addressed. Using this method of feedback resulted in the instructor having to spend more time writing as well as meeting in-person with teams during office hours to help guide the students through their project feedback. Employing screencast technology to provide student assessment feedback led to substantial instructor efficiencies in time and effort. There was no writing involved other than typing the team presentation grade on the rubric form. The screencast technology also records cursor movements, which allowed the instructor to point or circle a particular item on the slide, so students could identify precisely what the instructor was discussing. Lastly, the Snagit platform was easy to deploy, and the learning curve for the instructor was minimal as the software does not require extensive technical expertise. 3.3

The Student Experience

At the end of the term, students were invited to complete a short online questionnaire to explore their perceptions about the use of screencast technology for feedback on PhaseOne and Phase-Two of their Business Case Project. The survey was entirely anonymous, and participation was optional. The questionnaire consisted of eight closedended question items, using a five-point Likert scale, ranging from (1) as strongly disagree, (2) disagree, (3) neutral, (4) agree, and (5) strongly agree, along with not applicable option. There were 85 students enrolled across two sections that the author taught. The overall participation rate was 44.7%, with 38(n) students completing the survey. The questionnaire results indicated that students overwhelmingly supported using screencast technology for feedback about their Business Case Project. The eight statements were divided into two sections. The first section focused on the quality of screencast. Whereas, the second related to the helpfulness of the screencast feedback for the students. Figure 1 graphically depicts the four items that dealt with the quality of screencast feedback. The students generally perceived the quality of the provided feedback positively. Students thought the screencast was easy to understand and more in-depth than written feedback, with 87% of them either agreed or strongly agreed with that particular statement. Eighty-four percent perceived video feedback as more personal. The majority of the students, 82%, indicated the screencast feedback felt more supportive and caring than receiving written feedback.

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Fig. 1. Descriptive survey results for the quality of the screencast feedback

Figure 2 graphically depicts the second section items related to the helpfulness of the screencast feedback for the students. The majority of the students, 87% believed the screencast delivered helpful suggestions for how to improve, rather than just identifying problems. Just over three-quarters of the students felt the tone, expression, and emphasis of the screencast feedback added to the depth of the communication with their team. The screencast feedback also helped 82% of the students to more fully understand the expected standards for the course assignments. Lastly, 84% agreed or strongly agreed that the screencast feedback was easy to comprehend and take action to improve the future stages of their business case project.

Fig. 2. Descriptive survey results for the helpfulness of the screencast feedback

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For the students participating in this study, screencast feedback was viewed as beneficial due to it’s perceived higher quality and more in-depth analysis of their assignment performance. The students indicated they were given significantly more individualized and personalized explanations than they believed they would receive through text-based feedback. The screencast feedback helped them have greater insight into any mistakes they made, which enabled them to make improvements on future phases of the Business Case Project.

4 Future Research Design The fall 2019 study, as described, had several limitations. First is its small scope, with only 38 students surveyed and one instructor. The small sample limits the study’s transferability, and the positive impact of the screencast feedback could be linked to the instructor’s familiarity with the students, along with the instructor unconsciously advocating for screencast feedback. Another limitation of research conducted was its reliance on only eight closed-ended participant-reported questionnaire statements that primarily focused on the quality and helpfulness of the screencast feedback. Finally, the screencast approach used in this study was a recording of the instructor’s computer screen that captured cursor movements and scrolling, along with simultaneous audio narration. The screencast method used did not enable the computer’s video camera to provide a physical representation of the instructor in combination with the screen capture and audio narration. In fall 2020, a more deliberate research design will be applied to evaluate the use of screencast technology for feedback within the Entrepreneurial Thinking and Innovation course assessment phases of the Business Case Project. The instructor will continue to utilize the Snagit screencast video software to provide feedback to student project teams after each assessment. The scope of the study will expand to include students from all sections of the course, approximately 185 third-year undergraduates. A university research ethics approved end-of-term survey, and confidential focusgroups will be employed to evaluate the student experience. The questionnaire will identify student demographic items, such as gender, age, specific program stream and status as either domestic or international learners. An anonymous online Likert-style survey questionnaire will examine five themes, a) students’ responses to the benefits of receiving feedback through screencast videos, b) perceptions towards the appropriateness of sound, time, and language of the video feedback, c) perception towards the quality of the provided feedback, d) challenges encountered in receiving the input through the screencast, and e) gauging students’ attitudes towards screencast videos. The students will also be invited to participate in confidential focus-groups facilitated by educational developers from the university’s institute for leadership, innovation and excellence in teaching. Through this forum, students can further express their attitudes and perspectives towards the screencasting feedback approach. The responses to the open-ended questions will be transcribed, categorized and summarized into the respective five theme areas. While students appreciated the ability to hear their instructor voice in the screencast in the 2019 study, some researchers indicate this type of screencast could be considered

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deficient [1]. Klappa [30] suggests using ‘combination-type’ screencasts, which enables a small video recording of the instructor to be displayed within a screencast— thus providing a physical representation of the instructor in concert with the screen capture and audio narration of a traditional screencast. The Snagit screencast software can record a computer camera, in combination with the screen capture and audio. This type of combination screencast enables a range of nonverbal cues, for instance, facial expressions and body language that have been identified as constituting the richness of video feedback [31]. Anson et al. [32] found that students repeatedly described combination type screencast feedback as conversational and reminiscent of a face-to-face meeting with their instructors. Interestingly, students refer to combination type screencasts as being more conversational, even though no actual conversation or dialogue takes place. A possible explanation is that video component reduces the perceived distance between the instructor and student, leading to the increased use of phatics, speech that serves a social function rather than conveying information, salutations and compliments [33]. Due to the COVID-19 global pandemic crisis, the university has mandated all undergraduate courses to be delivered remotely during the fall 2020 term. Given this further separation between the students and instructor, the combination type screencast method will be deployed as part of the new research design to explore whether it improves the instructor-student relationships within the remote learning environment.

5 Conclusion Specifics were shared about the experience of using screencast technology in an undergraduate engineering technology management course. Using the screencast video approach for the delivery of feedback had a positive impact on the student’s learning experience. Students in this study demonstrated a positive attitude towards the screencast feedback approach and perceived it to be in-depth, multimodal, personal, and helpful. From the instructor’s perspective, the method allowed for a more detailed analysis of the student’s work in less time per assessment compared with using textbased feedback. Although the screencast feedback remains asynchronous, it establishes a learning dialogue between student and instructor that has the potential to be extended beyond the assignment. This particular benefit is even more appropriate as the higher education learning environment pivots to the modality of remote learning during the global pandemic crisis. There will undoubtedly be other elements not considered that educators may need to consider before adopting screencast video feedback. Factors such as field of study, assessment type (formative or summative), assessment format (visual, aural, written), the class size, the student type (age, local or international; visual/hearing impaired), and finally, resources (software, hardware, digital storage) [1]. However, the screencast video feedback method can be beneficial in STEM-based education programs because it can provide a detailed analysis of student performance for tasks that are mainly visual-based, like the summative assignments presented in this paper.

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22. Harper, F., Green, H., Fernandez-Toro, M.: Evaluating the integration of Jing® screencasts in feedback on written assignments. In: 15th International Conference on Interactive Collaborative Learning (ICL), Villach, pp. 1–7 (2012) 23. Hoyer, J.: Enhancing the “Show and Tell” aspects of class engagement using Camtasia, a low-cost video screen capture replay technology. In: 9th Annual Instructional Technology Conference: Transforming the Learning Environment, University of Colorado, Boulder, Colorado (2004) 24. Kerr, W., Mclaughlin, P.: The benefit of screen recorded summaries in feedback for work submitted electronically. In: 12th CAA International Computer Assisted Assessment Conference: Proceedings of the Conference pp. 153–168. Loughborough: Loughborough University (2008) 25. Warnock, S.: Responding to student writing with audio-visual feedback. In: Carter, T., Clayton, M.A. (eds.) Writing and the iGeneration: Composition in the Computer-Mediated Classroom, pp. 201–227. Fountainhead Press, Southlake, TX (2008) 26. Thompson, R., Lee, M.: Talking with students through screencasting: experimentations with video feedback to improve student learning. J. Interact. Technol. Pedagogy 1, 1–16 (2012) 27. Silva, M.: Camtasia in the classroom: student attitudes and preferences for video commentary or Microsoft Word comments during the revision process. Comput. Compos. 29(1), 1–22 (2012) 28. Cunningham, M.: Using audio screencast for feedback on short written essays (Doctoral dissertation). ProQuest Dissertation & Theses: Full Text (2015) 29. Ali, A.D.: Effectiveness of using screencast feedback on EFL students’ writing and perception. Engl. Lang. Teach. 9(8), 106–121 (2016) 30. Klappa, P.: Innovative Pedagogies Series: Videos for Learning and Teaching. Higher Education Academy. https://www.heacademy.ac.uk/sites/default/files/peter_klappa_final2. pdf. Accessed 23 May 2020 31. Borup, J., Graham, C.R., Velasquez, A.: The use of asynchronous video communication to improve instructor immediacy and social presence in a blended learning environment. In: Kitchenham, A. (ed.) Blended Learning Across Disciplines: Models for Implementation, pp. 38–57. Hershey, IGI Global (2011) 32. Anson, C.M., Dannels, D.P., Laboy, J.I., Carneiro, L.: Students’ perceptions of oral screencast responses to their writing: exploring digitally mediated identities. J. Bus. Tech. Commun. 30(3), 378–411 (2016) 33. Thomas, R.A., West, R.E., Borup, J.: An analysis of instructor social presence in online text and asynchronous video feedback comments. Internet High. Educ. 33, 61–73 (2017)

Knowledge Building Processes Between Interaction and Collaboration Cognitive Fields and Learning Processes Giorgio Poletti1(&)

, Anita Gramigna1

, and Marco Righetti2

1

2

University of Ferrara, Ferrara via Ludovico Ariosto, 35, Ferrara, Italy [email protected] Laboratory of Education Epistemology of University of Ferrara, Ferrara via Paradiso 12, Ferrara, Italy

Abstract. Knowledge building processes are involved in epochal changes that affect society. It was deemed necessary to start a study on the effects of these changes and processes on training practices and their models, also considering the consequences, not always explicit, that both of them have towards behaviors and values. The work also starts from the consideration, which many researches have highlighted, of how communication technologies and society are factors of great influence on learning-teaching processes. The learning-teaching processes are often integrated by blended methodologies and technologies certainly increase the factors of connection and interaction between the actors of the formal, non-formal and informal training processes. A balanced and preparatory analysis of effective practices is based on knowledge of learning processes and cognitive practices. The work describes the first phase of the research, an exploratory research on teachers’ perception on the relationship between cognitive styles, learning and technologies integrated in the learning-teaching processes. The first part of the research started from the investigation of the teachers’ thoughts, from their “feeling” of how the world of technologies and their pervasive use influenced cognitive styles and, in any case, students with school skills and attitudes secondary, regarding learning processes. From the result obtained, the second part of the research was developed which investigates the processes of building knowledge and which the situation of Pandemic has prevented from carrying out in the expected times. For this reason, the first phase of the research and the theoretical structure of the next phase are presented, in terms of methods and objectives. Keywords: Cognitive styles
Learning
Interactive technologies
Knowledge

1 The Research Project 1.1

Purpose of the Research Project

The research project that has developed started to detect teacher’s thoughts, from their “feeling” of how the world of technologies and their pervasive use has influenced cognitive styles, and in any case on students’ skills and attitudes, relatively to learning processes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 230–239, 2021. https://doi.org/10.1007/978-3-030-67209-6_25

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The aim was to detect teachers’ thinking in relation to the “assessment of cognitive trends” in order to be able to reach pedagogical models to detect and optimize cognitive processes. A further aim, pursued with a research-action on didactic processes. This phase was intended to respond to a challenge of education in the digital age. The challenge is to combine the growing availability of technologies with the activation of new skills, and respond to new educational needs by knowing the cognitive styles. The intended contribution is to indicate through which technology, in a broad sense, integration into the learning-teaching processes is possible. It was intended to clarify that technology is not only an aid for a “better” or “less tiring” learning path. Technology changes the approach to cognitive processes, people’s approach to the reality around them, to understand it and interact with it. In short, it can be said that it pushes us to understand how each of us builds knowledge. This project intends to focus on the problems related to the analysis of cognitive fields. Two aspects will be considered: • the critical issues found in the cognitive approaches of adolescents (difficulty of concentration, attention, abstraction, motivation, synthesis, solipsistic behaviors); • how a conscious use of cognitive approaches helps teachers analyses the cognitive habits and therefore the difficulties and strengths of their students, as well as to activate a metacognitive approach to school knowledge. The practical impact is to include technologies in teaching and not to have a classroom for technologies, a method that has proven useful for increasing the level of learning. 1.2

Methodological Approach

The aim of the project, which started with an initial exploratory research, is to propose a school that aims to enhance the talents of both teachers and students. The research project has a qualitative imprint and began, with the exploratory action to detect teachers’ thoughts, their “feeling” of how the world of technologies and their pervasive use has influenced cognitive styles, and however on the skills and attitudes of students, in relation to learning processes. We chose to use questionnaires that use Likert scales, in order to have a first feedback in relation to the focus of the research project, substantially placing some statements to the evaluation of the teachers with respect to their opinions on cognitive trends. The questionnaires also collect information on the profile of teachers to frame opinions also in relation to training and therefore to their cognitive styles. The sample of teachers can be defined as random, the distribution reproduces a “realistic” situation; for example, to make a comparison with a certain figure in Italy, according to an OECD estimate 83% of teachers are women, which is comparable with 80.9% of the sample, as well as the relationship between the different disciplinary areas.

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The second phase of the research made use of survey questionnaires on the use and results of technologies in training processes. The teachers used observation sheets and the students filled in the questionnaires. The data analysis was done both from an interpretative point of view, as regards the impressions of the teachers on cognitive styles and from an interpretative point of view as regards the results obtained with the students. The data and analyses, including tests with Cronbach’s Alpha, highlight the repeatability of the learning improvement in relation to use of technologies, understanding of the construction of knowledge and definition of cognitive styles. In the final phase of the research, we will analyses the critical issues found in the cognitive approaches of adolescents and it will be shown as a conscious use of cognitive approaches. In this, we will analyses, in a systemic perspective, fundamental elements that characterize the structure of a cognitive field: 1. ability to identify the relationships between the part and the whole of a context; 2. proposal of exercises that have a clear metacognitive depth; 3. ability to identify the virtuous relationship between training needs and school proposals. The approach will still be qualitative: the relationships between data and information will be analyzed from a systemic perspective. However, the numerical and statistical aspects of data and information will also be analyzed. 1.3

The Analysis of Cognitive Fields

This phase of the project intends to focus on the problems related to the analysis of cognitive fields and cognitive modifiability. Habits, in fact, are “cognitive paths” [1], experimented models of behavior with which we relate to the world, are learning patterns that presuppose points of view. These paths draw the limits and potential of the cognitive field. However, it is also true that they are likely to change, expand, interconnect, restructure or disappear with the activation of other fundamental knowledge. In fact, the basic, basic knowledge that the school builds with its protagonists makes sense if all the subjects involved in the training game are aware that, while building knowledge, they activate a series of acquisitions that they will use, at least in part, in other contexts. These are metacognitive learning. When we talk about cognitive functions, we refer to basic cognitive and coordination processes. Among the basic cognitive processes, we consider the following: perception, emotion, attention, memory, language (amplitude and plurality of vocabularies, mastery and precision), and empathy. Among those of coordination, we consider the following: plurality of linguistic styles and interaction, visual-spatial and topographical orientation, operativeness and praxis, abstract thinking, intuition, creativity, cognitive awareness of oneself. The goal that this phase of the research project has is to give answers to what are considered fundamental questions in relation to the study and cognitive fields, in their definition and determination.

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The questions that are considered fundamental and to which you intend to answer, in summary, are: • What are the well-developed cognitive functions and what are they lacking based on standard paradigms recognized by the literature? • What are the emotional problems that hinder the execution of a task or learning? • What processes facilitate it? • What strategies for potential cognitive functions? • What is the extent of the improvement that we can expect? • What are the linguistic and relational assumptions that can trigger change? The definition of these questions is also functional to what you intend to do and that is: • analyze the criticalities found in the cognitive approaches of adolescents (difficulty of concentration, attention, abstraction, motivation, synthesis, solipsistic behaviors); • showing the conscious use of cognitive approaches helps teachers analyze the cognitive habits and therefore the difficulties and strengths of their students, as well as to activate a meta-cognitive approach to school knowledge. The research phase foresees a preliminary bibliographic survey on the international debate, where the following fundamental elements that characterize the structure of a cognitive field will be analyzed in a systemic perspective: • ability to identify the relationships between the part and the whole of a context; • proposal of exercises that have a clear metacognitive depth, or that do not aim exclusively at the training of specific functions, but rather that, at the same time, develop similar or close functions, that is, which activate a structural change in the boy; • ability to identify the virtuous relationship between training needs and school proposals. To this end, cards, questionnaires, structured and semi-structured interviews will be prepared to be submitted to a significant sample of teachers and students. The disciplines involved are: • pedagogy, in its epistemological and experimental aspects; • philosophy of education. Research Method. A qualitative approach was chosen based on the purpose and scope of the research, an approach for analyzing the relationships between data and information in a systemic perspective. However, the numerical and statistical aspects of data and information will also be analyzed. We are convinced that an intelligent consideration of quantitative data leads to qualitative considerations and hypotheses, but the opposite is also true. Research Strategies. The strategy applied is that of the analysis of notable cases and the collection, cataloging, analysis of experiences, data and information. Action rich with teachers and students. The internalized action that is accompanied by the competent guide of the teacher becomes a mental operation. The boy learns the procedural

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sense as well as the different strategies that, in other contexts, this procedure can activate. This event shows us that it is possible, on the one hand, to study the directions of a cognitive field, on the other, to improve its mental abilities. The metallization of a procedure, of an operative choice, of a strategy aimed at solving a problem, implies the competence of the teacher in guiding the reflection on the evidences, on the gestures, on the operations. In this way, it is possible to correct the structure of cognitive functioning, rework the action plans, and improve their critical issues. In a word: increase learning potential. The teacher learns about the cognitive habits of his students, identifies their resources with weak points, and uses error as a concrete opportunity for strategic rethinking. Reference Epistemology. The reference epistemology refers to interpretative pedagogy [2], narrative pedagogy, and hermeneutics. This knowledge is not based on the possibility of an exchange, of their mutual help and therefore on the synergistic action of different styles of thinking, cognitive approaches, intelligences. The unity of meaning, the epistemic link, the eidetic structure is the RELATIONSHIP. The epistemic values adopted establish and elaborate a hierarchy of criteria aimed at justification, that is, at the consequentiality of our knowledge theory in relation both to its applications and to the theoretical and methodological premises. From the above, an epistemological perspective of a hermeneutic character emerges. The network of structures is organized in an elastic, dynamic, highly integrated and, at the same time, open hierarchy. It is an organizational framework of knowledge with which we interpret and build knowledge, it therefore has an active and concrete tension. Active, because it acts on reality and regards both the processes, the acquisition, the construction and the organization of cognitive data. And it is concrete, because it refers to the way we see the world, to the questions we ask ourselves when we act and that direct our conduct, it concerns the hypotheses of our research and its processes. Check and Evaluation. The verification of our project requires a rigorous procedural analysis of the following fields according to the criterion of their mutual coherence as well as the coherence between methods, activities, tools, epistemology and objectives. The fields of verification and analysis, specifically are: • the processes of construction, organization, dissemination and trans-formation of knowledge; • the methods, the contexts of meaning and the conditions of their construction; • conditions, in turn, pose the problem of verifiability of these constructions (for example: when and to what extent does knowledge have criteria of truth, certainty and efficacy?). • the choice of information that experience suggests to us, their interpretation and their placement within our system of knowledge; • the relationship of these processes with our cognitive self, or with the conscious and non-conscious perception that we have both of our cognitive field and of our potential for acquisition, elaboration, invention; • specific language of the disciplinary approaches involved, field of study and application, peculiarities of the contents, method, procedures, theoretical

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background, consequentiality, verifications, tools and coherence of the meaning and procedural relationships that exist between them. The evaluation criteria will take into account the following points: • the parameters on the basis of which we evaluate the impact that these problems have on the present; • epistemological assumptions, including implicit procedures; • methodological consistency with these assumptions; • the conceptual tools, the theoretical background in the international debate; • the reference theories; • the criteria for a constant revision of the model and its strategies; • the means of observation, collection, cataloging and documentation; • the tools for verifying and evaluating the results of our research in relation to the objectives, assumptions and means that we have been able to use; The consistency between all these elements and the possibility of their rearrangement.

2 Cognitiveness and Teachers: What They Think 2.1

Research Environment

The research started from the survey of teacher’s thoughts, from their “feeling” of how the world of technologies and their pervasive use influenced cognitive styles, and in any case on students of secondary school skills and attitudes, regarding learning processes. It was decided to use a scale based on a Likert scale, in order to have a first response in relation to the focus of the research project by substantially placing some statements with respect to their evaluation of cognitive trends to the teachers’ evaluation [3]. It was decided to use an “online” system for the administration of the questionnaires and specifically, through the school managers, the link to fill in the questionnaire was disseminated. On the one hand, the choice was dictated by the need to have rapid feedback and on the other by the reflection that in order to refine a more in-depth questionnaire and the development of teaching strategies to experiment, it would be significant to gather opinions without posing a segmentation problem. The focus was on secondary school teachers, even if vertical plexuses were also contacted, and questionnaires were obtained from teachers of primary and secondary level. The questionnaire, which was accompanied by a letter of introduction, declared the purpose of the project, of which it was the starting action, namely an analysis and a subsequent pedagogical proposal for a school that values the talents of all those who live there. The questionnaire was divided into three sections and was intended for a brief but meaningful compilation.

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The first section was the compilation of data relating to the compiler in relation to the educational qualification, area of study, gender and age. The second section collected data related to teaching and the order and grade of the school and the disciplinary area, together with the survey of the length of service (how many years have you been teaching?). The last section is the fundamental one “ASSESSMENT OF COGNITIVE TRENDS” for the detection of teacher’s thinking and to be able to continue with the structuring of the project to define pedagogical models to detect and optimize cognitive processes. This section consists of three questions, two closed and one open to collect suggestions and feelings from the teachers. The first question is “In recent years, young people have been the subject of a bombing of information and very rapid stimuli, which seems to have made it difficult, if not annoying, to experience situations that require slow rhythms”. Thinking back to his experience as a teacher of the last few years, how much do you agree with the following statements?”; in relation to this question possible answers are given that complete the statement The students have worsened the capacity of…, and the statements are: • • • • • • • •

identify the differences (ANALYSIS) classify the identified differences elaborate integrations between different elements (SUMMARY) to establish sets of elements based on the principle of affinity or congruence encode and decode a message, a language, a code, an instruction, a program… identify key words that connote an event or process to identify the relationships between the part and the whole of a context activate collaborative and supportive social behavior

And for each statement you are asked to choose between the options of a Likert scale: Totally agree Partially agree Neither in agreement nor in disagreement Partially disagree Totally disagree Similarly, the next question, which contains a single statement; the question is Overall, considering his experience, to what extent do you agree with the following statement? and the statement to “evaluate with the same Likert scale seen above is: The massive attendance towards technological apparatuses by children and young people has played a main role in changing their approach to learning in the dimensions identified in the previous table of affirmations. The collected questionnaires are 204.

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Search Results

Analyzing, from a percentage point of view, the data once again the sample seems to be always satisfactory with a view to reliably analyzing the sensations with respect to the learning trends and being able to prepare design and analysis tools to continue the project.

Table 1 Data collected in the third section of the questionnaire STUDENTS HAVE DROPPED THE ABILITY OF…

A 54 69 108

B 108 102 75

C 24 21 12

D 15 9 6

E 3 3 3

… identify the differences (ANALYSIS) … classify the identified differences … elaborate integrations between different elements (SUMMARY) … to establish sets of elements based on the principle of 66 87 33 12 6 affinity or congruence … codify and decode a message, a language, a code, an 87 81 21 12 3 instruction, a program … identify key words that connote an event or a process 48 93 27 33 3 … to identify the relationships between the part and the 78 81 30 12 3 whole of a context … activate collaborative and supportive social behavior 48 78 36 27 15 A: Totally agree - B: Partially agree - C: Neither in agreement nor in disagreement - D: Partially disagree - E: Totally disagree

The data relating to section three are the central ones that led to a first reflection and a first confirmation of the feeling that one had in the various contacts with the schools. In summary, see Table 1, the data collected in the third section with the reflections that they led. A first overall reading of this table shows the detection by teachers of a deterioration of certain skills; in fact, if we add the totally with the partially in agreement, we can see that there is an evident detection of this deterioration. There is an almost total concordance in detecting a diminished or worsened capacity for synthesis where there is an 89.7% of interviewees completely or partially in agreement with the statement. Similarly, there appears to be evidence of progressive deficiencies in the ability to classify differences (83.8% Totally + Partially in agreement). Of interest is to note that a very high percentage 82.1% (Totally + Partially agree) shows a diminished ability to encode and decode a message, a language, a code, an instruction, a program, where undoubtedly today the relationship with technologies is privileged and the technologies themselves are pervasive. This is certainly a first indicator of where to continue an investigation, because this result highlights how technologies become memory substitutes and information cataloging, also explaining the need for schools to push for coding, for the development of computational intelligence.

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The aspect of coding and the development of computational thinking, as well as emerging need in the school explains why, in the analyzed questionnaires there is a strong correlation between those who disagree, partial or total, with the statements and their membership by training or teaching area for the technological areas. Probably in this case it is evident that technology and technology are too often confused and that the ability to use tools is “confused” with new learning styles, which in some way displace the previous ones. A separate discussion and of interest also for the relational area are the “reactions” to the affirmation the students have worsened the ability to activate collaborative and supportive social behaviors where 61.5% agree completely or partially but disagree total or partial there is a 20.6% and a percentage of neutrals of 17%. This is interesting because it reveals what is the influence of social networks that are judged on the one hand a source of isolation, and even more serious problems such as cyber-bullying and on the other hand to increase socialization and all those collaborative stimuli useful not only in new social processes but also in learning processes [4]. On the other hand, there is a clear indication from the analysis of the reactions from the last statement. The massive attendance towards technological apparatuses by children and young people has played a main role in changing their approach to learning in the dimensions identified in the previous table of affirmations, relating to the question Overall, when thinking about your experience, to what extent do you agree with the following statement? This result, even in all the facets seen in the individual reactions to the other statements, confirms that the pervasiveness of “intelligent” technologies and tools is felt as a “cause” not only of social and relational changes but also in the way in which individuals they relate to the construction of knowledge and the same cognitive styles. The project therefore encouraged by the observation that what were “sensations” are strong evolutionary impulses even within the school and that these thrusts sometimes generate problems that must be tackled in a structural manner. We work and study to be able to say with the philosopher William James, “The greatest discovery of my generation is that human beings can change their lives by changing their mental habits”.

3 Conclusions, Results and Perspective A first overall reading of the data collected in the first phase of the research highlights the detection by the teachers of a deterioration in certain skills; in fact, if you add up the totally with partially the agreement it shows how there is a clear detection of this worsening. There is an almost total agreement in detecting a decrease or worsened synthesis capacity. A very evident interest 82.1% (Totally + Partially agree) shows a decrease in the ability to encode and decode a message, a language, a code, an instruction, a program, where without doubt the relationship with the technologies are preferred and the technologies themselves are pervasive. The data collected from the second phase of the experiment, the results obtained and the evaluations of the documents have meant that, otherwise necessary additional

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experiments are needed in this regard, that the technologies thus used and tested in this work help to improve the capacity of the SYNTHESIS… elaborated integrations between the different elements (SUMMARY) that had been identified, from the initial research among teachers, as a lack generated by a pervasive use of technologies. It can be said that the use of interactive technologies and content creation processes in formal learning processes increases the ability to synthesize and metabolize knowledge together with the facilitation of inclusion processes, which develop the development of collaborative and cooperative collaborative skills. The results in summary can be said that the technologies have proven useful in two specific directions: the pursuit of the structure of knowledge for better understanding and the use of technologies for experimentation, but at the end of the methods of solving problems, learn to learn. From the last phase of the research we expect to define the aspects again, also seeing the change in a period like this, where the pandemic has increased the abuse of technologies in a social and relationship context devastated. Talking about learning-teaching means paying attention, as has been done in research, to the learning processes, focusing on the student and his dynamics with which he relates to learning. The teaching and learning processes cannot be separated from the knowledge of the mdi with which the mind builds knowledge and which are still cognitive that are used. Error learning, the construction of methodologies that is not only a diversified technology but also a different knowledge, there is the information of which the research results have highlighted the possibility and the integration of technologies in the learning procedures- teach how to enhance and improve cognitive anchors. An efficacy that has among the strengths of the theoretical basis of the observation of cognitive anchors and learning methods. The technologies, whether they are software or hardware, which allow the development of analytical knowledge tools or the strengthening of proactive approaches to knowledge, are the key to a training that becomes the students’ ability to be in continuous training. Research, therefore, compared to the factual situation has shown the importance of knowing the other student’s cognitive and how it is possible to increase the ability to learn with the use of technologies guided by a methodology that has an unavoidable basis in the knowledge of cognitive fields.

References 1. Coussin, C.: The Bonsai School. D & S Books, Hamburg (2002) 2. Piaget, S.: Psicologia ed epistemologia. Per una teoria della conoscenza, Loescher, Torino (1971) 3. Nind, M., Curtin, A., Hall, K.: Research Methods for Pedagogy. Bloomsbury Academic, London (2016) 4. Thomas, M.: Digital Education: Opportunities for Social Collaboration. Palgrave Macmillan, London (2016)

Problem Based Learning in Finite Element Analysis Seshasai Srinivasan(&) and Dan Centea McMaster University, Hamilton, ON L8S4L8, Canada {ssriniv,centeadn}@mcmaster.ca

Abstract. With the advancement in computing power and the evolution of different engineering software, a lot of engineering design and development uses computational modeling. Finite element analysis is one of the most popular computational approaches to engineering design and assessment. At the W Booth School of Engineering Practice and Technology’s Automotive and Vehicle Engineering Technology program, a course in Finite Element Analysis is taught in the 3rd year of a four-year Bachelor’s program. In this work, we present the problem-based learning (PBL) approach that we use in this course to teach the principles of finite element analysis and applying them to two realworld engineering problems. For these problems, the students are taught ANSYS software, which is popular in the industry. In a PBL setting using a constructivist environment, we are able to engage the students and successfully deliver the concepts. Keywords: Problem-based learning


Finite element analysis

1 Introduction As part of their engineering education, students typically take anywhere between five to six courses every term. Through the course of their engineering degree, the students end up taking well over 40 courses. The exact number of courses depends upon the stream they are majoring in. With an emphasis on engineering practice, most of these courses have a lecture component as well as a lab component. While the former is aimed at delivering the theoretical principles, the latter is used to inculcate practical skills that the student will need to have as operating engineering in their discipline. In addition to these curriculum-based training, in several engineering programs, students are also required to undertake some paid industrial internships as part of their education. These could be anywhere between six months to a year of practical training in the industry related to their degree. In this stringent regiment of training that the students undergo as part of their undergraduate education, an immense amount of material is to be mastered by them to emerge as capable and qualified engineers who can be employed by the industry. As a result, there is an enormous emphasis on teaching and learning pedagogies that are best suited to help students master the material. There is a large body of research focused on developing techniques that propose a variety of methods depending upon the subject. Some of the pedagogical approaches proposed in the literature include co-operative and © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 240–246, 2021. https://doi.org/10.1007/978-3-030-67209-6_26

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small group learning [1–3], challenge-based learning [4], undergraduate research-based learning [5], inquiry-based learning [6, 7], problem-based learning [8–14] and active learning [15–20]. In this research, we present a problem-based learning approach for teaching the principles of finite element analysis to the students in the third year of an undergraduate engineering degree in Automotive and Vehicle Engineering Technology at McMaster University’s W Booth School of Engineering Practice and Technology. The main objective of this work is to describe the implementation details of a problem-solving based approach to study real-world engineering applications in the area of thermal analysis using ANSYS. We chose a problem-based learning (PBL) approach because we believe that this is an appropriate method for the students in this program who are naturally disposed to simulated and active learning. Specifically, students enrolling in our programs have a stronger inclination for more hands-on learning than the traditional engineering programs. In fact, unlike the other engineering programs, in almost every course that the students take in this school, the students take the same number of lab hours as the lecture hours for a particular subject. While PBL has been employed, the manner in which the learning happens has been structured so as to include elements of the constructivist theory of learning [21, 22]. Constructivism is grounded on the principle that knowledge results from the constructive activity of each individual. With their unique individual experience and response to a certain stimulus environment, the learner develops his/her understanding of the concepts. As pointed out by others, the constructivist learning environment is characterized by the following [23]: personal constructions of reality, simulated authentic learning environments, multiple representations of data, active learning, and collaboration. In this work, we create an environment inside the class that emulates an authentic learning environment where students interact, discuss and deliberate with peers and the instructor, and try to solve two real-world engineering problems using ANSYS in addition to solving theoretical problems in collaboration with their peers. The ANSYS problems are formulated such that students are required to think and determine an explanation for the solution. In the ensuing sections, we describe the materials and methods that we adopt in this course, the data collection to assess the outcome, and present a detailed discussion on the result of this approach to learning. We end the work with our conclusions from the path we have adopted to teach finite element analysis to students.

2 Materials and Methods As mentioned in the Introduction section, PBL was employed in the third-year undergraduate course of Finite Element Analysis. A total of about 80 students spread over two sections took the course in the fall term. The class typically meets once every week for a 3-hour duration. The entire course was taught over a period of thirteen weeks. The typical lecture is divided into an hour and a half of theory followed by an

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hour and a half of lab work in which problems are also solved using ANSYS, thereby teaching students this software. 2.1

Course Design

As part of the course, the following topics are taught to the students through the term: (i) Fundamentals of finite element analysis including the basic steps, generic solution approaches, and verification of solutions, (ii) Structural analysis of trusses, beams, and frames, and (iii) Thermal analysis. While problems in one and two dimensions are taught to be solved using theoretical principles, a finite element analysis software is also introduced in the course to solve problems in one, two, and three dimensions. Specifically, in addition to the theoretical principles, students are also trained in using ANSYS because it is a critical finite element analysis software that is used in the industry. As part of training students in using ANSYS software, six different labs are included in the course. These labs focus on teaching them how to set up the problem, apply boundary conditions, solve the problem, and interpret the data using ANSYS. It must be clarified that these six labs are not aimed to incorporate intense ANSYS training into the curriculum. On the contrary, the objective is to introduce the software to the students and demonstrate how it could be used in an industrial environment to solve engineering problems. 2.2

Procedure

Each week, in the first half of the lecture, the theoretical principles are taught and the concepts are illustrated with examples to elucidate the concepts. This is followed by a problem-solving session in which the students are given a set of problems and are encouraged to solve them in a specified amount of time. In doing so, they are allowed to communicate with their peers and the instructor. The questions posed in these active learning sessions were on topics that were either from the current topic or from material taught in the previous weeks. Thus, the students are required to repeatedly recall the concepts and apply them to solve the problems. This weekly spacing of problems, recalling, and application of the concepts helps reinforce the material [19]. Several of these problems are quite involved, and students often engage in detailed discussions with their peers, helping each other solve the problems by sharing their thoughts/ideas. By solving these problems, the students master the concepts and are aware of the underlying engine that operates the ANSYS software. Since very complex problems cannot be solved via such calculations, in the second half of the lecture, real-world problems are introduced, and students are guided to set up the problem and solve it using ANSYS. Each problem is part of a lab for which there is a grade assigned. As part of employing problem-based learning to teach concepts the finite element analysis concepts, two specific problems that we would like to present in this work are the following: (i) Thermal Analysis: Designing an aircraft panel with different materials and doing a thermal analysis to determine energy efficiency.

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(ii) Structural Analysis: Crash testing of two types of vehicles, namely, a sedan and a van. Thermal Analysis Problem: In this problem, the students would investigate the temperature distribution across a composite material that is used to design the aircraft fuselage (c.f. Fig. 1).

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11cm k=0.06 W/m.K

Tcabin=22°C

k=0.03W/m.K

1cm

5

Fig. 1. Aircraft fuselage made of composite material.

In doing so, they would consider three cases: (i) Baseline Case: Here, the thermal conductivity of the panels is shown in Figure 1. ANSYS is used to set up this problem and understand the temperature distribution across the composite material. (ii) Case A: One way of minimizing operating costs is to improve the insulation material quality, i.e., reduce the values of the thermal conductivity in the central layer. So, in this case, the students investigate the effect of lowering the value of k in the central panel. (iii) Case B: Another way of savings is to use cheaper material, resulting in lower manufacturing costs. However, this might be at the cost of the quality of insulation, i.e., a lower value of k. The students study the temperature distribution using this scenario. In all cases, the students set up the problem in ANSYS, study the temperature distribution, and present arguments for prescribing a specific solution to the above question. In doing so, the students collaborate and discuss the outcomes and debate the

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solutions they prescribe. This entire exercise allows them an excellent opportunity to study a real-world engineering problem using the principles of finite element analysis via software that is used in the industry. Structural Analysis Problem: In this problem too, the students investigate multiple cases: (i) Case A: In this case, simulating an impact of a collision, the effect of a specific applied pressure on the stress distribution and the deformation of the two vehicles is studied. (ii) Case B: In this case, converting the same vehicles into an armor grade, the simulation of crash testing is repeated. More precisely, with a complete metal enclosure without any windows, the driver is assumed to be able to drive from inside a virtual steel cage. It is believed that such futuristic vehicles would have mounted cameras and screens inside the vehicle for the driver and operators to see the outside terrain. Once again, simulating the crash testing using ANSYS, the students can evaluate the impact on the deformation and stress distribution, and discuss their solutions along with the pros and cons of either type of vehicle. Thus, they are once again able to study a real-world engineering application using industry-relevant software.

3 Discussion The PBL approach used to master the principles of finite element analysis and to study the problems theoretically as well as using ANSYS has resonated very well with the students. The key aspect of PBL was to introduce active collaboration and discussion inside the classroom. While theoretical problems that the students undertook had no grade associated with them, the students had to submit a short report of the case studies that they undertook using ANSYS for which a numerical grade was assigned. In the instances when grades are not assigned for the practice problems that we addressed in the first half of the lecture, the students were focused on learning. The learning environment was characterized by a significant amount of discussion and exchange of ideas. As a result, by the end of the first part of the lecture, almost every student in the class had a good understanding of the concepts. In the case studies using ANSYS, since there is a report that is eventually due, there is always a risk of student shifting their focus from learning to finishing the work for a final grade. With this shift in focus, there is inadvertently a loss of appetite for learning and an urgency to meet the submission deadline with adequate data. To mitigate this risk, students were given adequate time to complete the report. Specifically, the deadline for a report was usually set on Sunday midnight. As a result of this, students engaged in discussions and deliberations with their peers inside the class, sharing their ideas and findings with them. We believe that the constructivist learning environment in the classroom was extremely beneficial to the students. Such engagement inside the classroom to solve the problems aided in the mental construction of the concepts, and students developed an

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excellent understanding of the subject. Their fruitful exchange of ideas enabled cement the principles of finite element analysis. We conclude this based on the performance of the students in the two reports that they submitted as part of their findings and recommendations for each problem solved by ANSYS. We also noted that at the end of the classroom sessions, students were interested in pursuing the subject beyond the curriculum.

4 Conclusion In this work, we present a problem-based learning approach to teaching the principles of finite element analysis from an industry-centric perspective. Specifically, in addition to teaching regular theoretical principles and engaging the students in problem-solving sessions during one part of the lecture, students were also taught to use ANSYS software to solve more complex and real-world problems, typical in the industry. Here we present two such applied problems that students undertake during the course. While there was no grade for the problem-solving sessions in which the students had to solve theoretical problems, they had to submit a report on their findings for the two applied problems. It was found that by setting up a constructivist learning environment, the students invested a lot of time in discussions and deliberations with their peers to solve the problem. In these deliberations, there was a healthy exchange of ideas and constructive criticism of the solutions that were pitched by the peers. An important action to avoid students falling prey to the anxiety of grades and shifting their focus from understanding the application of principles to meeting a deadline for grades was done by giving students ample time to submit the report. This ensured that students were more geared towards understanding and applying the principles to solve the problem rather than simply getting a final answer. The rich exchange of ideas and thoughts helped create impressions in their minds that ultimately fostered learning.

References 1. Wage, K.E., Buck, J.R., Wright, C.H.G., Welch, T.B.: The signals and systems concept inventory. IEEE Trans. Educ. 48, 448–461 (2005) 2. Prince, M.: Does active learning work? a review of the research. J. Eng. Educ. 93, 223–231 (2004) 3. Hake, R.R.: Interactive-engagement versus traditional methods: a six-thousand-student survey of mechanics test data for introductory physics courses. Am. J. Phys. 66, 64–74 (1998) 4. Roselli, R.J., Brophy, S.P.: Effectiveness of challenge-based instruction in biomechanics. J. Eng. Educ. 95, 311–324 (2006) 5. Srinivasan, S., Rajabzadeh, A.R., Centea, D.A.: Project-centric learning strategy in biotechnology. In: Auer, M., Hortsch, H., Sethakul, P. (eds.) The Impact of the 4th Industrial Revolution on Engineering Education. ICL 2019. Advances in Intelligent Systems and Computing, vol 1134 pp 830-838. Springer, Cham (2020)

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6. Farrell, J.J., Moog, R.S., Spencer, J.N.: A guided-inquiry general chemistry course. J. Chem. Educ. 76, 570 (1999) 7. Lewis, S.E., Lewis, J.E.: Departing from lectures: an evaluation of a peer-led guided inquiry alternative. J. Chem. Educ. 82, 135 (2005) 8. Capon, N., Kuhn, D.: What’s so good about problem-based learning? Cogn. Instr. 22, 61–79 (2004) 9. Kolb, D.A.: Experiential learning: experience as the source of learning and development. In: 2nd ed., Pearson Education Inc., (2015) 10. Dochy, F., Segers, M., Van den Bossche, P., Gijbels, D.: Effects of problem-based learning: a meta-analysis. Learn. Instr. 13, 533–568 (2003) 11. Centea, D., Srinivasan, S.: Assessment methodology in a PBL environment. Int. J. Innov. Res. Educ. Sci. 6(6), 364–372 (2016) 12. Sidhu, G., Srinivasan, S., Centea, D.: Implementation of a problem based learning environment for first year engineering mathematics. In: Guerra, A., Rodriguez, F.J., Kolmos, A., Reyes, I.P. (eds.) PBL, Social Progress and Sustainability, Aalborg: Aalborg Universitetsforlag. (International Research Symposium on PBL), pp. 201–208 (2017) 13. Centea, D., Srinivasan, S.: Enhancing student learning through problem based learning. In: Guerra, A., Rodriguez, F.J., Kolmos, A., Reyes, I.P. (eds.) PBL, Social Progress and Sustainability, Aalborg: Aalborg Universitetsforlag. (International Research Symposium on PBL), pp. 376–385 (2017) 14. Muhammad, N., Srinivasan, S.: A problem solving based approach to learn engineering mathematics. In: Auer M., Hortsch H., Sethakul P. (eds) The Impact of the 4th Industrial Revolution on Engineering Education. ICL 2019. Advances in Intelligent Systems and Computing, vol. 1134, pp. 839–848 (2020) 15. Beichner, R.: The Student-Centered Activities for Large Enrollment Undergraduate Programs (SCALE-UP) Project (2007) 16. Burrowes, P.A.: A student-centered approach to teaching general biology that really works: lord’s constructivist model put to a test. Am. Biol. Teach. 65, 491–502 (2003) 17. Cummings, K., Marx, J., Ronald, T., Dennis, K.: Evaluating innovation in studio physics. Am. J. Phys. 67, S38–S44 (1999) 18. Sidhu, G., Srinivasan, S.: An intervention-based active-learning strategy to enhance student performance in mathematics. Int. J. Pedagog. Teach. Educ. 2, 277–288 (2018) 19. Srinivasan, S., Centea, D.: Applicability of principles of cognitive science in active learning pedagogies. In: Proceedings of the 13th International Workshop Active Learning in Engineering. (1 ed.) Aalborg Universitetsforlagpp, pp. 99–104 (2015) 20. Srinivasan S., Centea D.: An active learning strategy for programming courses. In: Auer, M., Tsiatsos, T. (eds.) Mobile Technologies and Applications for the Internet of Things. IMCL 2018. Advances in Intelligent Systems and Computing, vol. 909, pp. 327–336 (2019) 21. Olusegun, B.S.: Constructivism learning theory: a paradigm for teaching and learning. ISOR J. Res. Method Educ. 5(6), 66–70 (2015) 22. Srinivasan, S., Muhammad, N.: Implementation of a course in computational modeling of biological systems in an undergraduate engineering program. Int. J. Eng. Educ. 36(3), 857– 864 (2020) 23. Maor, D.: Teachers-as-learners: the role of a multimedia professional development program in changing classroom practice. Aust. Sci. Teachers J. 45(3), 45–51 (1999)

Recursion Versus Iteration: A Comparative Approach for Algorithm Comprehension Francesco Maiorana1,2(&), Andrew Csizmadia3, Gretchen Richards4, and Charles Riedesel5 1

University of Urbino, Italia, 61029 Urbino, Italy [email protected] 2 Kansas State University, Manhattan, KS, USA 3 Newman University, Birmingham, UK [email protected] 4 Jacksonville State University, Jacksonville, FL, USA [email protected] 5 University of Nebraska’s-Lincoln, Nebraska, NE, USA [email protected]

Abstract. There is a worldwide effort for incorporating computing as a basic literacy in addition to reading, writing and arithmetic, and sustaining its learning from kindergarten to higher education. This work focuses on comparing recursion with iteration as they are perceived by learners in a first computing course. It also attempts to identify when is the best time to teach recursion and compare both iterative and recursive design techniques. As a case study, the authors utilised an attitude survey to be completed by the participants to determine their perception of both recursion and iteration implementation for both Bubble and Merge sorts, and a module which focused on recursion compared with iteration. In addition, we report on the design and development of animations for both the Merge and Bubble sort algorithms to illustrate and illuminate these algorithms. Three different formative assessment tools are introduced that can be used to sustain and guide students throughout a self-explanation of the two algorithms. A first run of the formative assessment tools have been administered to students in a first computing course: the first with 15/16-year-old high school students and the second with undergraduate students majoring in humanistic studies in their final year before graduation. By using both animations and an inquiry-based approach the work aims at investigating the most appropriate time and way to teach sorting algorithms using both recursion and iterative algorithms. The long-term aim is to design an effective learning trajectory. In a future study, longitudinal concept retention will be investigated. Keywords: Recursion
Iteration
Inquiry-based pedagogy algorithms
Bubble sort
Merge sort


Sorting

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 247–259, 2021. https://doi.org/10.1007/978-3-030-67209-6_27

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1 Introduction The importance of exposing all students to computing has been recognized worldwide and, consequently, a strong effort has been put in place to expose both computing majors and non-majors to rigorous computer science concepts. Ways to make the content more accessible and relevant to all have been explored. In this direction, many tools such as block-based languages have been developed to facilitate the first exposure of students to computing concepts both in a first CS course such as CS0 or CS1 courses and more advanced one such as CS2 courses. Block-based languages such as Edgy [1] and Blocks4ds [2] are used in Data Structures courses both for elective high school studies and in undergraduate courses for both non-majors and majors. Even in advanced courses like CS2 courses which usually focus on algorithms and data structure, recursion is considered one of the most difficult topics in these courses since it is essential in most advanced data structures that students will encounter [3]. For these reasons we advocate for an introduction of recursion as early as possible, even in a first computing course for both major and non-major students. In a recent survey, Rinderknecht [4] summarizes curricular approaches, including the textbooks employing them, that focus on overcoming student difficulties, and conducted a research review on the recursion problem solution strategies such as starting with the base case and addressing induction, and in updating concrete approaches to teaching recursion such as visualization, animation, games, and use of multimedia environments. McCauley et al.’s review [5] focuses on effective practices to introduce recursion such as using different contexts, and the best learning trajectories as suggested in the literature, noting how these may prefer either teaching iteration before recursion or vice versa. Studies related to recursion discuss topics related to the following: 1. How students trace recursive programs [6], namely simulating execution, dynamic programming, accumulating pending calculations, and predicting the result. 2. Mental models of recursion are studied [7, 8] in order to understand how students depict recursion so as to avoid misconceptions and improve teaching. In particular they suggest showing to students a variety of recursive problems, from mathematically based to graphical recursive function; focus on the backtrack process, and give them sufficient practice in designing recursive functions, and finally using algorithm animation as a means to enhance students’ understanding of recursion. Differences in students’ comprehension of iterative and recursive programs is investigated by McCauley et al. [9]. 3. Students’ difficulties with data structures and recursion [3, 10]. 4. Interaction, visualization and animation of a recursive program [11, 12]. 5. Concept inventories from the design to the validation process. [13, 14]. 6. Student preference of iterative and recursive approaches with evidence of better performance in terms of correctness of iterative solutions [9, 15]. 7. Use of educational games to introduce recursion in both high school and university courses. [16, 17].

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Following up on the previous related work, previously summarized, our intent is to answer the following research questions: 1. Is there any perceived difference between an iterative or recursive approach by first time learners in a computing course? 2. Which is the best learning trajectory to support the teaching recursion? We will present: 1. An attitude survey that, by using a language agnostic approach, will ask students to trace recursive functions expressed in natural language and to design and develop recursive programs that produce a given result. 2. A module to introduce recursion showing the learning trajectories that can be used in relation to context and curricula, suggesting resources, pedagogical approaches, and technologies useful in different contexts according to the age and students’ previous experience. 3. Present the main pedagogical approach used which relies on a flipped learning approach [18]. In designing the learning material instead of starting from presenting the main concepts to students, we preferred starting by asking the students to explain using natural language what they see in the animations. The reflections, with an inquiry-based approach, are guided by formative assessments scaffolding the students in their learning process. This approach has been applied in many different context [19, 20]. 4. Present, as a case study, the above-mentioned pedagogical approach with two different group of students, namely: a. undergraduate students majoring in humanities, during their first computing course in their final year before graduation. b. a class of high school students, in their last year of compulsory education, at the beginning of their second course in computing, but with no previous experience of being formally taught recursion. Both groups have been exposed to two animations of the bubble sort and the merge sort and have been exposed to three different formative assessments tests. An incremental approach, guide students in scaffolding their solution of the sorting algorithms they have been asked to investigate. A discussion and further study section will complete the work.

2 Attitude Survey There exist computing attitude surveys that span the learning cycle from middle school [21, 23] through to higher education. We have developed an attitude survey that, according to McCauley et al. [5] tests the students’ attitude, first to evaluate and trace recursion, and then to write recursive functions that reproduce a given pattern. The attitude survey questions are programming language independent with all the questions, including those related to tracing, are expressed in natural language. Some examples of the tracing questions used are reported in Table 1 and Table 2.

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In the following board if the x represents the Global Positioning System (GPS) location of JoCS, how many different cellss will JoCS touch? Will JoCS stay inside the grid after executing the movements? List the different squares touched by JoCS in order of time after executing the movements in a). If a square is touched more than one time, list it every time it is touched. List only the squares inside the grid. Separate the squares by a comma without spaces. In writing the square list the letter then the number, e.g. A1.

a. 1 step to the right b. Call Help (3) Where Help (N) is: If N > 0 then Go one square left Go one square down Call Help (N -1)

a) Tail recursion

Call Help2 (4) Where Help2 (N) executes If N > 0 then Call Help2 (N -1) Go 1 square down Go 1 square right Go 1 square down b) Head recursion

Call Help3 (3) Where Help3 (N) executes If N > 0 then Go one square right Call Help3 (N -1) Go one square down Call Help3 (N -2) c) Tree recursion

The questions can be used as a pretest before the module on recursion and how it relates to iteration is delivered and as post-test at the end of the same module and at the end of the course itself. If used at the beginning of the studies, for example at the beginning of the undergraduate studies, then it should be used in conjunction with an attitude survey [24] such as Computing Programming Aptitude Test developed by the University of Kent that focuses on logical thinking and problem solving, pattern and syntax recognition, and ability to follow complex procedures. The questions proposed in Table 1 and Table 2 belong to the last category. The attitude survey and the following discussion allow us to present different ways to repeat actions within programs, from using loops which allow code to be iterated a fixed number of times, when either a condition is met, or until a condition is met, or recursive functions that call themselves until a base case is reached. With a similar approach it is possible to ask the students to reproduce a drawing by designing either a recursive or an iterative program. Such type of activities has been effectively implemented within a blended learning approach to extend the educational activities beyond the time and space class limit.

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3 The Recursive Module: Content, Technologies, and Learning Trajectories We designed a module for teaching recursion module that was inspired by the following design principles: 1. Using an inquiry-based approach to design the module with a flipped learning approach, which started with a scaffolding formative test soliciting student reflection on key concepts. This test was used as a pre-test for this investigation. Example of activities that can be used with an inquiry-based approach are: a. The attitude survey, which is presented in Sect. 3. b. Animations, which are discussed in Sect. 6 used along with formative test guiding students in correct descriptions of what they have seen in the animation. Ensure that the content is as accessible as possible in order to use at the beginning of the course. This provides students with an opportunity for a longer self-reflection period and provides them with multiple possibilities to practice, developing in parallel both the recursive and the iterative solution to the problem they are presented with. These are examples of the positive effect of introducing recursion and there are others in literature such as [25]. Table 2. Examples of tracing iterative algorithms: a) repeating a fixed number of times; b) repeat until condition, and c) use function with repetitions.

In the following board (similar to the one used in Table 1) assuming that the x represents the Global Positioning System (GPS) of JoCS, in which cell JoCS arrives after executing the following movements?

b)

c)

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The taught module has been experimented with both visual block-based programming languages, for example App Inventor, as reported in the case study, and with textual programming languages, for example Python and Java, within an online course on data structures and algorithms for non-major [18] students. 3.1

The Content

We designed and developed a teaching module to be developed as part of a data structures and algorithms course. The authors recommend a two-week schedule for the whole content. The content of this module is outlined below: 1. Introduction: recap on iteration: a. Repeat a fixed number of times b. Loops and conditions at the head or at the tail c. Repeat while a condition is met d. Repeat until a condition is met e. Repeat for all the elements of a list 2. What is recursion? 3. Some examples: a. draw a square and generalize it to a regular polygon b. invert a sequence of characters 4. Implementing recursion: a. LIFO function call order 5. The structure of a recursive program: a. The factorial b. recursive version of the algorithm to find the max and the min of N number c. recursive merge of two ordered lists. d. Project: a recursive calculator using only assignment to zero, increment and decrement 6. When it is not worth using recursion: a. the Fibonacci numbers b. naïve implementation 7. Solving recurrence equations a. Time complexity of the Fibonacci number: 8. How to improve recursion: memoization a. Fibonacci performance improvements. b. Retake of the recursive calculator with performance improvements 9. When recursion is worth using a. The tower of Hanoi 10. Transforming a recursive program into an iterative program

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4 Case Study Strategies for teaching and learning computing have been considered by the authors from many different points of view [26] and different learning trajectories have been explored for a first computer science course [27]. One approach investigated relies on animations of algorithms to facilitate the understanding of algorithms [28]. Animation has been integrated into programming environments for program visualization [29]. This work describes an experience relating to the design of animations for both bubble sort and merge sort algorithms and the design of formative assessment tools rooted in previous experiences [30, 31] that an inquiry-based approach [32–37] can sustain students in their learning of the algorithms and the underling technique, i.e. iteration and recursion, during a first Computer Science (CS) course. Animations and formative assessment tools will be used to investigate the following two research questions: 1. Is recursion perceived, by students in a first CS course, more difficult to grasp than iteration? 2. Is an active learning approach where students first explain the steps within an algorithm just from observing its animation and then are exposed to a detailed explanation more effective than simply exposing students to the algorithm explanation from the onset? In order to validate the animations and the formative assessment tools, we collected data from an investigation with one group of 15-16 year old high school students and data from another investigation involving undergraduate students majoring in humanistic studies. Both two groups were engaged in their first computing.

5 Animation Design To design and implement animations, many approaches can be followed: from using a visual block-based programming language such as Snap! [38] or App Inventor [39], to a text-based language with an object-oriented capability such as Python or Java. A block-based programming language allows students to focus on semantics rather than syntax. Furthermore, according to constructionism [40], it is possible to ask students to read the source code and use it as a reference point for developing their animations. Since the animations are designed to be used both within a first programming course and within a more advanced course where data structures are presented, then the respective audiences’ needs need to be carefully considered at the design stage for each animation. Each animation must be explicit, clear, and precise, and still retain sufficient details necessary to avoid any misconceptions, such as showing the swapping process. Efficiency issues must be avoided for the sake of clarity of each animation.

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6 Design of the Formative Assessment Tool We designed three formative assessment tools to be used with each algorithm. Through a sequence of open scaffold questions, with a different level of insight, aims at guiding students, using active learning activities [41], to obtain insight into each of the two algorithms. In particular, the three sequences of formative tests are outlined below. The first sequence of tests asks the individual student to describe what the animations do and how they work. Then students rate the perceived level of difficulty and a comparison of the two algorithms in terms of simplicity to grasp, learn and code is also asked. These ratings are asked at the end of each sequence of tests. The second sequence of test presented to each student concerns the recursive algorithms: 1. To identify the number of phases, i.e. recursive division and union of the two ordered halves. 2. To describe in natural language each of them. 3. To aggregate the operations during the merge phase in order to identify repetitions. 4. To count the number of operations in the union phase. Then individual students are asked about the iterative algorithm in order to facilitate the individuations of nested loops: 1. To identify and describe the swapping process. 2. To identify, describe and count the repeating operations. 3. To identify the halting conditions. The third sequence of tests presented to individual students asks them for the recursive algorithms; with the focus shifting from the merge phase to that of recursive division: 1. To describe the recursive division process and its backtrack. 2. To write the instructions for the merging phase, using a scaffold approach. For the iterative algorithms, students demonstrate a deeper understanding of the nested loop by writing the instructions for the merging phase. The three tests could be administered in different ways, such as at the beginning of the course to establish a baseline, in the middle to measure instruction, and at the end of the course to evaluate students’ progression inside the course, and/or for a final comparison of the two algorithms. To evaluate longitudinal retention, a test could be administered at the beginning of a second computing course, such as a CS2 course. There is also an opportunity to administer a third longitudinal evaluation within a first software development course. This is usually delivered after CS2 where recursion, sorting, searching and all the major recursive data structures have been covered, and could complete the longitudinal study on recursion, searching and sorting.

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7 Preliminary Field Test The formative assessment tools presented were used in a first CS course for both: a) final year undergraduate students majoring in humanistic studies; b) 15–16-year-old high school students in the second year of their studies. Each animation was shown twice to each group. At the end of the second view, the associated formative assessment test was administered. The animation for merge sort algorithm was shown first, then the bubble sort animation was shown next. Prior to the participants completing the final comparison test, the two animations were shown in reverse order. 7.1

Finding for the Field Test with Undergraduate Students

Out of the fifty students (n = 50) participating in the study, for the majority (95%) of them it was the first CS course in their learning career. In the test administered at the beginning of the course 50 students, (90% were female) completed the tests for the iterative, the recursive algorithm and the comparison. The merge sort algorithm was perceived as the easiest to grasp (60%), to learn (62%), and to code (62%). Overall, at the beginning of the course, it was preferred by 62% of students. Figure 1 reports the students’ ratings of simplicity, using a 10-point scale (1 lowest simplicity, 10 highest simplicity) regarding technical details related to Merge Sort and Bubble Sort.

Fig. 1. Perceived simplicity of Merge a) and Bubble sort b) by the undergraduate students

These percentages remained almost steady till the end of the course. A preliminary analysis of the open questions reveals a fair grasp of the concepts underpinning the two algorithms and the necessity for a deeper scaffolding related to complexity issues. 7.2

Finding for the Field Test with High School Students

The tests were administered to a second-year class of 15–16-year-old high school students studying at a technical high school at the end of their second month of the delivery of that class. For the students, this was their first exposure to sorting algorithms. None of the authors were involved in teaching these students. Ten students out of 20 volunteered to complete the test. The merge sort algorithm was perceived as the easiest to grasp (80%), to learn (70%), and to code (50%). Overall, it was preferred by 70% of the participating students. Figure 2 shows the perceived simplicity of the two

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algorithms. In this case the Merge sort algorithm was perceived simpler by 80% of the students and it was the preferred algorithm in terms of facility to learn and code.

Fig. 2. Preferred algorithm in terms of facility to learn a) and code b) by the high school student

8 Conclusions and Further Work This work reports a preliminary experience on designing, developing and field testing of animations for both a bubble sort and a merge sort, and three formative tests to obtain an insight into the perceived difficulties of recursion by students in their first CS courses. The main conclusion that can be drawn from this study is that the students’ perceived difficulty of recursion and recursive algorithms is not too high, compared to similar iterative algorithms. Thus, the data sustain the hypothesis that recursion can be introduced as early as possible within a computing curriculum as a vehicle to assist students understand and comprehend how algorithms can be constructed. Not only that, but both iterative and recursive algorithms for a similar task can be taught parallel, allowing for these algorithms to be compared for similarities and contrasted for differences. An initial analysis of the data indicates that students perceived the Bubble Sort to be more complex than the Merge Sort and therefore alternative approaches to explain the concept of a Bubble Sort are required, such as a unplugged activity [42] coupled with sound pedagogical approaches such as Peer Instruction [36, 37, 43]. This hypothesis will be evaluated in further studies as well as the analysis of the students’ open-ended responses will be analyzed and reported on. In further studies, the animations with the formative assessment tools will be used to study the effectiveness of a student-centered approach to teaching sorting algorithms by means of scaffolding formative assessment compared to a more traditional style of knowledge transmission within formal lesson settings. These further studies will allow us to validate the protocol and compare different models for teaching and learning sorting algorithms using both recursion and iteration. Further activities involving recursion with engaging games and using real life dataset such as the one proposed in [44] will be explored. Additionally, longitudinal studies across a sequence of CS courses could also be undertaken to obtain an insight into the students’ cognitive process as they fully understand and master recursion. We anticipate that participants in this longitudinal study would have a starting point of a CS0 course, continue to participate through studying CS1, CS2 and conclude their involvement by completing a first software development course.

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Integrated Thinking - A Cross-Disciplinary Project-Based Engineering Education Steven Bogoslowski, Fei Geng(&), Zhen Gao, Amin Reza Rajabzadeh, and Seshasai Srinivasan McMaster University, Hamilton, ON L8S 4L8, Canada {bogoslsr,gengf,gaozhen,rajaba,ssriniv}@mcmaster.ca

Abstract. A new model for engineering education is implemented to introduce the professional practice and simulate a work environment in post-secondary undergraduate education. More precisely, cross-disciplinary project-based learning has been introduced into the curriculum of three undergraduate engineering programs, namely, Biotechnology, Automotive and Vehicle Technology, and Automation Engineering Technology. In this, students from the three streams undertake a collaborative effort to design an in-house electrochemical biosensor device that can be used in a series of disjoint experiments performed by the student participants of this study. An open-ended research project was issued to the students for evaluation of the course. To ensure continuous progress by the students, weekly reports, regular presentations, assignments, and lab reports were submitted towards a final grade. The entire exercise implements Bloom’s taxonomy on learning in a top-down approach, leading to a more challenging but extremely satisfying learning experience that will promote the retention of the concepts for a longer duration. By offering the students an opportunity to expand on innovative ideas that scaffold technical development through the use of experimental research and design, the project-based learning methodology will enhance the engineering learning environment for postsecondary education Keywords: Engineering education
Project-based learning practice
Cross-disciplinary
Electrochemical biosensor


Professional

1 Introduction Undergraduate engineering education is currently based on a new paradigm in which engineering education is delivered through experiential learning. Industry-related stakeholders and accreditation boards across the globe are continually reaching out to academic institutions in ways to improve the preparation of engineering students before graduation [1–4]. In essence, post-secondary institutions aim to produce engineers who are competent to participate in the development, the role of an engineer is redefined from being a developer of technology to be a participant in the real-world experience and the process through which technology shapes the real world. The approach to innovation and improvement of professional practice in engineering stems from an active digital learning environment [4, 5], the collaboration of © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 260–267, 2021. https://doi.org/10.1007/978-3-030-67209-6_28

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cross-disciplinary groupwork [6, 7], and the development of establishing the theoretical framework for engineering pedagogy [8]. These critical points in education can be established through teaching styles centered around project-based learning [9–13]. Implementing the shift from a lecture, content-driven material approach to an application in practice approach is done to provide students an opportunity to participate in real-world and personally meaningful research projects, preparing them for integration into the workplace. With this educational reform, students will develop in-depth content knowledge, foster critical thinking, engage in collaboration, promote creativity, and harbor management and soft communication skills. In this paper, students from an undergraduate engineering technology program are assessed to document the outcomes of implementing a cross-disciplinary, project-based learning environment into the curricula. By executing a top-down Bloom’s Taxonomy approach [14, 15], the students are tasked to research a topic and design an experimental procedure for using a novel biosensor. As such, the program offers a new approach to engineering pedagogy through integrated thinking, thus dawns the name of the program – iThink. The scope of the project has drawn much support from the work done at MIT in the NEET project [16]. In this work, implementation of the iThink course is presented as a cross-disciplinary, project-based program that has allowed faculty to simulate a workplace environment in the curriculum. The students participating in the iThink program are from the Automotive & Vehicle Technology and the Biotechnology streams. In addition to the faculty members, qualified teaching assistants from the Biotechnology and Electrical Engineering programs also assist the students in their projects. Periodic qualitative evaluation of the evolution of the project has been implemented to assess the progress of the students. In the ensuing sections, the implementation of this initiative is presented in greater detail.

2 Bio-sensing – Preparation of the Pilot iThink Project 2.1

Biosensing System Design

The objective of this project was to develop a novel, open-source, biosensor capable of electroanalytical measurements. In a test cycle, to see the feasibility of accomplishing this during a term, a group of four co-op students from the Biotechnology and Electrical Engineering programs at McMaster University were tasked to develop the biosensor. The components of the biosensor system were a Rodeostat open source potentiostat purchased from IO Rodeo Smart Lab Technology, a gold coated screen-printed electrode, and a laptop with software for generating data output. The potentiostat, primarily capable of measuring voltage and current, was programmed to conduct Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) tests of organic samples on the screen-printed electrodes. These tests were primarily used to observe the hybridization between a probe DNA strand and its complementary on the electrode surface. The majority of the computer programmed designed in Python was programmed using sample code made available online via the IO Rodeo website. In order to facilitate straightforward use of the software program, the Python GUI application was used to archive the graphical data and store it in an online database for access to all

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group members. The GUI application was designed to allow students to input different parameter values for each test specific to the student’s project. Testing was done at different stages of DNA incubation to see the changes in surface characterization. Graphs from the CV and DPV testing were displayed in Microsoft Excel spreadsheets with the corresponding data set values to compare area and peak current values between the different stages of testing. An example of one of the tests is shown in Fig. 1.

Fig. 1. Sample result of a Cyclic Voltammetry (CV) test on the DNA probe.

During the following school year, the design was further optimized to make it a more user-friendly system. The laptop equipped with software for the biosensor system was replaced by a Raspberry Pi computer for processing. The GUI application software was installed on the Raspberry Pi and tested to ensure reproducibility. Figure 2 shows the potentiostat to used by students in the iThink project. 2.2

Graphical User Interface for the Bio-sensing Project

The overall design principle of Graphical User Interface (GUI) is: 1) Easy to be utilized by students with little programming experience; 2) Easy to be maintained by a follow-up developer; 3) Easy for cross-platform application and can be used in Windows, iOS, and Linux systems; 4) Easy to be interpreted based on the straightforward instruction and documentation. Figure 3 shows the GUI that has been developed for this project and that satisfies the above requirements.

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Fig. 2. The in-house IO Rodeostat: potentiostat for the biosensing system.

Fig. 3. Graphical User Interface for running electroanalytical measurements: Cyclic Voltammetry; Constant Voltage Voltammetry; Differential Pulse Voltammetry.

In operating the GUI, if one decides to administer the cyclic voltammetry test, the user has to click on the corresponding button and will be guided through additional screens that prompt the user on the next steps.

3 Implementation of the Pilot Project 3.1

Approach

The iThink project-based learning course ran throughout the entire academic year of Fall 2019 to Winter 2020. In the first term they design the system and the subsequent term they develop the system. Students from the level two Biotechnology program

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were allowed to register for the iThink project substituting the traditional labs offered in the program. In doing so, each term, the students would be required to attend 15 h of laboratory instructional type of learning, as required by the curriculum. In the iThink program, the weekly 3 h lab period consisted of a 1-hour tutorial where the teaching assistant would engage in discussion-based lecture, discussing theoretical content of the biosensor system and the experimental design research process. The remaining 2 h of the lab period were used for active learning sessions in which students perform the experiments. Once they had learned all foundational lab techniques, towards the middle of the Winter semester, students were required to dedicate the whole 3 h lab period to experimental performance. Through the entire process, students were required to choose a research project topic of their interest, research and design an experimental procedure to detect their biomarker using the novel biosensor system. Students would design their protocol by researching online papers, learning the necessary lab techniques required for experimentation, compiling the material lists of reagents. As a step beyond the traditional labs, the students would also reach-out to distributors for product pricing and information, and examine material Safety Data Sheets (SDS) for proper handling and storage of hazardous chemicals. The instructors and the TA were always present during the lab session and were available for any student inquiries regarding their project. Dryrun experiments harbored basic cell biology lab techniques to prepare students. Respective lab techniques, relevant to content taught in the classroom, are performed in-line to ensure a complete understanding of the experimental concepts. This method ensures students gain technical experience through active learning before conducting their own research project. Assessment of progress consisted of bi-weekly presentations, assignments, experimental design milestones, and a final lab-report. 3.2

Assessment/Procedure

The projects were to be done by students in pairs, and the assessments were developed accordingly. The students were given the opportunity to select their partners. One instructor, one lab instructor/course development co-op student, and one TA were collectively involved in mentoring the students. With some general guidelines on the complexity of the project, during the Fall term, students were required to identify a research topic pertaining to the area of biosensors. An outline of expectations and resource/equipment availability was given to the students so that their research topic choice would be feasible. Additional content was provided by the instructors to help students get started on their research. In the initial few weeks, students are required to submit a draft of the overview of the topic. Additionally, they are also required to do a short 5-minute presentation to justify the choice for their topic and the background information on developing a biosensor. The presentations were held in the form of a group discussion, allowing them to discuss and deliberate ideas, enabling eachother to learn and improvise their design. This constructivist environment [17, 18] of learning was maintained through the duration of the course. By creating a discussion-based environment during the presentations, an atmosphere for active learning was created to help in communication

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and group work skills [19–24]. These were formally implemented as 1-hour discussionbased tutorials outlining concepts on biosensors and 2-hour dry-run experiments involving curriculum-related lab experiments to practice and understand technical and theoretical concepts. For the Fall term, a final report was submitted at the end of the term, carrying the majority of weight to their grade. This report contained all of the dry-run experiments performed in the lab with a focus on how these apply on their own research project. The specific techniques learned by the students during the Fall term are as follows; bacterial media preparation, plasmid DNA purification and transformation of pcDNA 3.1 into E. Coli cells, bacteria plate streaking methods – plate to plate, liquid to plate, and agar slants, cell lysis, and gel electrophoresis. In the same term, the group of students enrolled in the Automotive & Vehicle Technology stream was tasked to optimize the housing unit adapter for the biosensor system. The adapter connector port purchased from IO Rodeo was not very accurate and generated inconsistent readings and background noise on the data application. The students in the Automotive stream collaborated with their peers in the Biotechnology program to upgrade and produce a better adapter. The purpose of these meetings was for brainstorming, exchange ideas, transfer knowledge, and understand the needs and constraints of the two disciplines. Thus, the collaboration helped the Automotive students develop an adapter that supported a more appropriate connection. In the Winter term, students focused on executing their experimental designs from the Fall term while continuing to learn new lab techniques. This term was identical in format of the Fall term in terms of allocation of lab period time. Towards the middle of the term, students would be performing experiments through the entire lab period. A month into the semester, students had initiated the first steps in implementing their research topic, procuring the specific plasmid encoding DNA. The next steps involved finalizing the experimental protocol for their research project and conducting experiments simultaneously. Students fully developed their research protocol and executed up to the point of protein purification before closures. As in the Fall term, student progress was monitored via weekly presentations, group discussions, the experimental design of their research project, and a final report submitted at the end of the term. A list of techniques learned throughout the Winter term are as follows; genetic engineering, small scale protein synthesis, cell lysis concentration for biosensor protein purification, and spin column-based protein chromatography specific to each student’s topic. Evaluation of the course was made through a series of course, instructor, and peer-to-peer evaluations. Subject areas in the aforementioned evaluations consisted of feedback for each category to improve the iThink course overall. A student selfreflection was also conducted individually to asses the impact of project-based learning, and also to evaluate the students strengths/weaknesses. A few comments, re-iterated for use, made by the students stated that the openended projects influenced their academic experience in a positive way, evidence of a strong correlation between the information researched online to the skills preformed in-lab, and that the students were satisfied having the freedom to choose their own topic, leaving a more personally, inspirational academic experience. Skills learned by the students engaging in project-based learning are listed; groupwork, communication skills from doing the presentations, time

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management and project planning from setting milestones to complete their experimental research project, and the technical application of biotechnology-related lab skills as mentioned above.

4 Conclusion A cross-disciplinary project-based learning approach has been introduced into the undergraduate engineering curriculum of the W Booth School of Engineering Practice and Technology (SEPT) at McMaster University. In this work, implementation of Bloom’s taxonomy in a top-down approach wherein students identify and device a research project based on some prescribed guidelines. In implementing the project, the learning outcomes are met more satisfactorily than the traditional labs in which students learn skills via disjoint experiments but are unable to apply them collectively to a single large project. The students would complete their training on a full spectrum of biotechnology techniques. An informal evaluation of the learning experience from the students highlighted the following: better knowledge of the theoretical framework, a sound understanding of the concepts from a research-based reading and experiments, development of critical thinking abilities, improvement in the soft skills, ability to integrate and work in a multidisciplinary group setting. Overall the students found this form of learning very valuable. A curriculum based on active learning through the use of regularly scheduled presentations and reports creates a right constructivist environment for learning. By promotion open-ended active learning, offering flexibility in topic selection, and to strategically place the students in an advantageous position for future projects like the Capstone Project in senior year, the levels of engagement increased. In conclusion, the approach taken by us helps promote a more in-depth knowledge, foster critical thinking, engage in collaboration, encourage creativity, and improve the soft skills needed to work in a multidisciplinary environment.

References 1. Case, J.M., Light, G.: Emerging research methodologies in engineering education research. J. Eng. Educ. 100(1), 186–210 (2011) 2. Splitt, F.G.: The Challenge to change: on realizing the new paradigm for engineering education. J. Eng. Educ. 92(2), 181–187 (2003) 3. Williams, J.M.: Transformations in technical communication pedagogy: engineering, writing, and the ABET engineering criteria 2000. Tech. Commun. Q. 10(2), 149–167 (2001) 4. Lima, R.M., Andersson, P.H., Saalman, E.: Active learning in engineering education: a (re) introduction. Eur. J. Eng. Educ. 42(1), 1–4 (2017) 5. Lacuesta, R., Palacios, G., Fernández, L.: Active learning through problem based learning methodology in engineering education. In: 39th IEEE Frontiers in Education Conference, pp. 1–6 (2009) 6. Borrego, M., Newswander, L.K.: Characteristics of successful cross-disciplinary engineering education collaborations. J. Eng. Educ. 97, 123–134 (2008) 7. Fruchter, R.: Dimensions of teamwork education. Int. J. Eng. Educ. 17(4/5), 426–430 (2001)

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8. Mishra, P., Koehler, M.J.: Technological pedagogical content knowledge: a framework for teacher knowledge. Teachers College Record 108(6), 1017–1054 (2006) 9. Edström, K., Kolmos, A.: PBL and CDIO: complementary models for engineering education development. Eur. J. Eng. Educ. 39(5), 539–555 (2014) 10. Helle, L., Tynjälä, P., Olkinuora, E.: Project-based learning in post-secondary education – theory, practice and rubber sling Shots. High. Educ. 51, 287–314 (2006) 11. Savery, J., Duffy, T.: Problem based learning: an instructional model and its constructivist framework. Educ. Technol. 35(5), 31–38 (1995) 12. Blumenfeld, P.C., Soloway, E., Marx, R.W., Krajcik, J.S., Guzdial, M., Palincsar, A.: Motivating project-based learning: sustaining the doing supporting the learning. Educ. Psychol. 26(3–4), 369–398 (1991) 13. Srinivasan, S., Rajabzadeh, A.R., Centea, D.: A project-centric learning strategy in biotechnology. In: Auer, M.E., Hortsch, H., Sethakul, P. (eds.) ICL 2019. AISC, vol. 1134, pp. 830–838. Springer, Cham (2020) 14. Fruhling, Z.: Bloom’s taxonomy: bottom-up or top-down?. Resilient educator (2018). https:// resilienteducator.com/instructional-design/blooms-taxonomy-bottom-up-or-top-down/. Accessed 28 May 2020 15. Wright, S.: Flipping bloom’s taxonomy. powerful learning practice (2012). https:// plpnetwork.com/2012/05/15/flipping-blooms-taxonomy/. Accessed 28 May 2020 16. Crawley, E.F., Hosoi, A., Long, G.L., Kassis, T., Dickson, W., Mitra, A.B.: Moving forward with the new engineering education transformation (NEET) program at MIT - building community, developing projects, and connecting with industry. In: ASEE Annual Conference & Exposition (2019) 17. Srinivasan, S., Muhammad, N.: Implementation of a course in computational modeling of biological systems in an undergraduate engineering program. Int. J. Eng. Educ. 36(3), 857– 864 (2020) 18. Olusegun, B.S.: Constructivism learning theory: a paradigm for teaching and learning. ISOR J. Res. Method. Educ. 5(6), 66–70 (2015) 19. Beichner, R.: The student-centered activities for large enrollment undergraduate programs (SCALE-UP) project (2007) 20. Sidhu, G., Srinivasan, S.: An intervention-based active-learning strategy to enhance student performance in mathematics. Int. J. Pedagog. Teach. Educ. 2, 277–288 (2018) 21. Burrowes, P.A.: A student-centered approach to teaching general biology that really works: lord’s constructivist model put to a test. Am. Biol. Teach. 65, 491–502 (2003) 22. Cummings, K., Marx, J., Ronald, T., Dennis, K.: Evaluating innovation in studio physics. Am. J. Phys. 67, S38–S44 (1999) 23. Srinivasan, S., Centea, D.: Applicability of principles of cognitive science in active learning pedagogies. In: Proceedings of the 13th International Workshop Active Learning in Engineering. (1 edn.) Aalborg Universitetsforlagpp, pp. 99–104 (2015) 24. Srinivasan S., Centea D.: An active learning strategy for programming courses. In: Auer, M., Tsiatsos, T. (eds.) Mobile Technologies and Applications for the Internet of Things. IMCL 2018. Advances in Intelligent Systems and Computing, vol. 909, pp. 327–336 (2019)

A Flipped Design of Learning Resources for a Course on Algorithms and Data Structures Francesco Maiorana1,2(&) 1

University of Urbino, 61029 Urbino, Italia, Italy [email protected] 2 Kansas State University, Manhattan, KS, USA

Abstract. There is a worldwide effort to introduce Computer Science (CS) to students from primary school level through higher education, and this effort has been sustained by the whole education community from teachers to researchers. The paper describes the design decisions and development processes of accessible and inclusive learning resources (LR) suitable for infusing computational thinking (CT) and computing into the STE(A)M, i.e. Science, Technology, Engineering, Mathematics, and All other disciplines. The developed curriculum supports quality education for all. The developed learning resources have been used in an online course on algorithms and data structures for undergraduate students not majoring in Computer Science. Content, Pedagogies, and technologies will be discussed along with a comparison and a contrast of different learning trajectories. Keywords: Online education


Algorithms
Data structures

1 Introduction One of UNESCO’s sustainable goals is quality education for all [1, 2]. The paramount importance of education is clearly stated by others [3]. Quality education allowed for “an integrated approach” with mutual sustainment among different activities pursuing different goals. This international effort for quality education is comprehensive, incorporating the infusing of computing knowledge among all citizens, involving all educators, using all levels of education, extending inside all types of educational systems, and considering all stages of life. It is recognized that this effort must be pursued from early development [4] and has been the focus of the Computer Science education community during its whole life span. This quality education for all must be maintained as much as possible, in times of crisis too [5–8]. The online learning approach must be sustained, according to the TPCK framework [9–11], by: 1) Adequate content design and development [12–15]. This requires attention to the content itself that should contain cutting edges, variegated and real-life applications and to the presentation that should follow multimedia design principles rooted in © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 268–279, 2021. https://doi.org/10.1007/978-3-030-67209-6_29

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solid research evidence. The online content requires a design that must be simple. The content must be delivered according to accessibility guidelines. 2) Suitable online pedagogies [16, 17]. Proven sound and beneficial pedagogical methodologies based on an inquiry, student centered approach should be sought and adapted to the online setting. 3) Supporting technologies allowing to maximize opportunities and overcome difficulties arising from the distance learning environments in an accessible environment [18, 19]. The technologies should offer support ranging from teacher awareness of students in synchronous activities to collaborative work and should offer accessibility in all the tools used from the learning management platform to the Integrated Development Environment. In this work, by leveraging on previous experiences [20–24] we will consider and address the following challenges faced in designing and developing a fully online course for undergraduate students not majoring in Computer Science: 1. How to deliver a fully online course 2. How to design the content so it is suitable for students not majoring in computing Ideas and thoughts will be shared on: 1. How to integrate different approaches like unplugged activities, puzzle-based, and coding activities into Algorithms and Data-Structures (A&DS). How this variety of design and implementation tools can serve learners with different learning styles. 2. What activities, tools, and pedagogies are best suited for a formative assessment approach to A&DS education. 3. How A&DS can be used to teach core CS ideas and 21st-century skills with an interdisciplinary approach that can serve students, teachers, and researchers with different backgrounds, interests, expertise, and experiences. 4. How to use A&DS to expose students to different areas with new and quickly changing domains.

2 How to Address Online Learning The main strategy used in designing the course was a focus on supporting studentcontent interaction. The content was provided by means of an online book supported by an Open Online Course with video lessons, assessments, and coding activities. Student-content interaction is supported by means of: 1) Animations and assessment activities supporting student self-reflection 2) A flipped approach to the content development: start from the formative assessment, proceed with the content and assessment solutions Online learning in this time of crisis due to the presence of COVID-19 has become a focus of learning communities. The course is the third one in the program and, according to modern Human Computer Interaction design principles, the choice was

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made to use a consistent look and feel across the whole program. Regarding online learning, the following suggestions and lessons learned are shared: 1. The course was designed for an expected audience of more than 50 students. For this reason, the decision was made to use asynchronous delivery of lectures. In this respect, asynchronous lectures give more freedom to students to follow the course at their own pace. To mitigate the effect of students’ procrastination, it is advisable to decrease the course load at end of the term and give tighter deadlines at the beginning, releasing this deadline at the end. This coupled with other interventions [25] can contribute to students’ success in projects. 2. The course was designed to be fully online. Office hours were held, using synchronous Zoom sessions. Teaching assistants were available, according to students’ requests, for face-to-face meetings. Our suggestion is to offer, whenever possible, face-to face session with students coupled with on-campus day-long activities to be attended by students on a voluntary basis. 3. The assessment in all its forms, from formative to summative, covers an important part of the course. The formative assessment was designed with open and closed responses. The summative assessment was project-based with the grading of students’ projects performed using an auto-grader to ensure scalability. Coupling the auto-grader with human review allows for better learning experiences, allowing students to benefit from the feedback. Organizing synchronous online sessions for students’ projects presentations in front of all classmates, divided in groups where necessary, offers an invaluable means for students to improve their communications skills, receive feedback from peers, and from the instructors.

3 How to Address Students not Majoring in Computing The importance of involving non-majors in computing education has been exposed in [26]. The approach used to introduce computing to non-majors has been explored for several decades. In [27–29] several approaches based on engaging practices and by considering different populations of learners addressing their learning goals and exposing them to the communities of practices they are more interested in have been presented. The approach taken for the course followed by non-major students was to: 1. Offer the core algorithm and data structure content in a rigorous way 2. Add diversity offering a rich set of activities and projects, such as application of the algorithms and data structures in different domains, adding applications in a modular way. The diversity must span both the application domain and the technologies used, offering a first insight into advanced topics such as parallel programming in the simplest and most accurate way possible. Allowing for students’ contributions and project proposals is a suggested approach for their involvement. 3. Use of data and real-life datasets in different domains with an insight into the techniques used to analyze data in different domains: text and humanities, numbers

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in Science, Technology, Engineering and Mathematics (STEM), audio, images and multimedia as engaging activities.

4 Course Content The course on Algorithm and Data Structure was designed and developed inside the Computational Core certificate1 at the Kansas State University as the first course of two focusing on the topic. It is the third course in the program after two courses on covering an introduction to programming, the first one, and a second course on algorithm and programming. In designing the content, the priority was given to favoring studentcontent interaction. This interaction must be coupled with peer interaction and studentinstructor interaction. The content of this course must cover basic linear data structures leaving more advanced non-linear data structures to the successive course, the second on data structures and algorithms, the fourth in the program. A fifth mandatory course should cover software design principles with a capstone project. Elective courses can be selected by the students among a set of available ones, covering databases, data science and other topics. The author was not directly involved in the design of the whole program and details on this will be shared in a successive work. The basic concepts of object design and programming are presented, after reviewing, and consolidating the key concepts of imperative and procedural programming, from the very first lesson through examples and simple applications. The concepts presented are applied through the book guiding students, with an incremental approach, in realizing software projects with increasing difficulty and complexity that require the use of multiple classes in relation to each other and one or more objects of each class. According to modern software development approaches, the incremental approach allows for the building of a working application at the end of the first module which will be further developed along with several modules, adding functionalities, and refactoring i.e. modifying the code structure without modifying the program behavior in order to make it easier to read and extend. The presentation of data structures is done both by introducing the properties and the operations allowed by each data structure, in order to make the reader able to implement the data structure, and through the use of the developed data structures by applying them in projects requiring their use. Some projects will also require a starting use of library and Application Programming Interfaces. Algorithm design techniques have been presented through puzzle-based activities [30]. Collaborations with other initiatives were actively pursued to sustain the effort in developing the book. Elective activities have been presented by proposing projects with an interdisciplinary context. Other activities will be added in further developments of the course for a successive use in further classes.

1

https://core.cs.ksu.edu/authors/.

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5 Pedagogies The main pedagogical approaches adopted are: 1. Active learning and inquiry-based approach 2. Incremental learning at all stages from design to project development and assessment 3. Use of animation to scaffold students’ self-reflection 4. Facilitate students’ engagement though offering a broad range of activities in different domains The pedagogical approach is based, according to modern active pedagogies, on an inquiry-based approach. Leveraging on the author’s experience [21, 31] students’ engagement has been pursued through formative assessment activities to be completed before content presentations to implement a flipped book centered on a cycle of activities starting from student self-reflection. The incremental approach in the formative assessment has been pursued to scaffold student self-reflection on new concepts, guiding them through a deeper level of insight and technical detail. The formative assessment activities have been scaffolded by animations extensively used to display algorithms and data structures operations. The approach used was to let the students watch the animations and then answer the assessment activities. The same incremental approach has been used in project development supported by design, code, test, debug, and document activities. Examples in this direction are: 1. a scientific calculator that started from the basic arithmetic operations implemented using assignment to zero, increment and decrement by one, coupled with the control instructions (conditions and loops). The project was then refactored using functions, adding other operations ranging from power to factorization and primality, designed in an object-oriented fashion, implemented recursively and extending some operations like division with decimal using non-linear data structures such as Finite State Machine (FSA). 2. Object-oriented design (OOD) and Object-Oriented Programming methodologies [32] applied to the development of a management of a collection of objects. An example in this direction is reported in Fig. 3. 3. Use of recursion as early as possible and use of recursive approaches to implement operations of the studied data structures as well as use of stack to understand implementations details of function calls and recursive programs.

6 Technologies The technologies used were chosen to support the design choices and the pedagogical approaches: • For online content delivery: Canvas [33] for its support of classroom activities and learning management system capabilities.

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• For online programming Environment Codio: for allowing a programming environment accessible from any device without requiring system level abilities to install development environments and tools. • For online project assessment: an auto-grader, constructed in-house. • For design of algorithms: Flowcharts [34] for their versatility supporting automatic translation into many programming languages among which the two course chosen languages: Java and Python. Flowcharts are also used in Object Oriented Programming as a way to design method. Raptor has some functionalities for this [35]. • For Object-Oriented Design (OOD) the Unified Modelling Language (UML) software the reader can use ArgoUML a free open source software suggested by Free Open Source Software or StarUML [36]. • For creating animations: Edgy coupled with Java and Python Turtle libraries used to extend each data structure class with drawing functionalities used to animate its operations.

7 Outcomes The content has been developed in 12 modules suitable for a course on algorithms and data structures covering the major linear data structures, namely stacks, queues, lists, hash tables and the applications of these data structures to implement sets, dictionaries and finite state machines. Recursion is presented at the beginning of the course in order to allow students to familiarize themselves with this difficult concept. In order to build a bridge toward the planned successive course on hierarchical data structures, the discussion of Finite State Machine and their implementation with adjacency matrix and adjacency list have been used to anticipate and introduce the representation of graphs and trees. The basis for elective activities has been laid for further development in the successive course. Figure 1 summarizes the planned content.

Fig. 1. The course contents

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The content has been used for a first edition of the course, named Computational Core 310, at the Kansas State University and is available online2. For describing data structures, the same approach was used. Students were exposed to the underlying properties and operations allowed in each data structure. Figure 2 shows the concept map summarizing the approach used for data structures.

Fig. 2. Couse data structures overview

To facilitate the use in different contexts, the libraries available in the two main programming languages used in the course, namely Java and Python, were presented and applied to solve problems in different domains. Figure 3 shows the approach used to present and apply language specific data structure libraries for the Python language.

Fig. 3. Python libraries overview

2

https://core.cs.ksu.edu/3-cc310/.

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A similar approach was used for Java libraries. For presenting the object-oriented approach, a methodology presented in [32] was used coupled with an incremental approach: as a recap, a class, with attributes and methods, presenting issues related to information hiding, was introduced. After this, inheritance was presented by adding to the project subclasses. The relation with information hiding as well as multiple inheritance and related issues were addressed. The following steps consisted in presenting hierarchies such as composition, avoiding, at a first stage, to point out advanced distinctions with aggregation, followed by use relationships and associations. Figure 4 shows an example of a completed project proposed to students with the above described incremental approach.

Fig. 4. An example of Object-Oriented project

The use of activity diagrams could be suggested as an elective activity and to assist students facing difficulties in following the flow of execution and object interactions. The whole course syllabus is reported in Table 1 with sample activities and project suggested as mandatory or as elective. According to the design principle above mentioned, reading material such as [37] should be suggested to the students as well as many resources as possible in order to gave them the ability to choose the projects they like the most and contribute with their projects to forming a shared memory of resources developed by the students inside the class.

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F. Maiorana Table 1. Course content, tools, and activities for each module

Mod. 1

Content Review of imperative programming

Tools Flowgorithm [34]

2

Review of Objectoriented programming

Flowgorithm, Raptor [35], StarUML [36]

3

Programming by Contract & Introduction to Performance

4

Data structures and Algorithms

Python and Java libraries supporting programming by contract, e.g.a Edgy

5

Stacks

6

Recursion

7

Searching and Sorting

8 9

Queues Lists

10

11

Hash table and Dictionary: properties and implementations

Edgy. Java and Python turtle libraries Flowgorithm, Animations, CargoBot [38, 39] Flowgorithm, Animations Animations, Edgy Animations, Edgy Animations, Edgy

Sets: property and Animations, Edgy, implementations Flowgorithm Animations, Edgy, 12 Finite State Automata: Flowgorithm Property and implementation. Data structure comparisons a Python programming by contract libraries

Activity Computing calculator (Calc) with assignment to zero, increment and decrement Refactor computing calculator using OOD. Implement the project in Fig. 3 Find pre, post and invariant conditions of algorithms, e.g. the computing calculator Implement a brute-force technique to solve a strategy game Extend Calc to handle expression Refactor the recursive calculator Sorting and searching applications Priority queues management Set and set operations on real-life datasets Translation service. and WordNet usage Dictionary implementations using data structures Set implementations using data structures Extend the CC calculator to handle decimal divisions. Design and implement an augmented data structure

The course content is summarized in Table 1 where the tools and suggested activities, either mandatory, or elective, are detailed. Giving a recap and a broad overview on data structures at the beginning of the course allows for easier acquaintance with the new material. Having a broad overview allows for a more proactive student role. The design process should be sustained at all levels coupled by offering different possibilities to approach the content from puzzlebased activities to the use of block-based languages for fast prototyping.

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Regarding the learning trajectory, anticipating recursion at the beginning of the curriculum had the benefit of covering an important topic earlier, allowing more time for students’ reflections, sustained by continuous use of a recursive approach in the course module, and avoiding student cognitive overload. Use of recursion, complexity analysis and invariant identification should be applied transversally along all the modules of interest. According to [31], these analyses should help the students reach the learning goal of selecting and comparing different data structures and analyzing the complexity of the algorithms used.

8 Conclusions The proposed approach sustains the presentation of different aspects both through giving a foundation on theoretical and design aspects and through practical applications in the form of lab activities. These laboratory activities are structured in guided exercises that highlight and apply the theoretical concepts presented and guide students through the development of projects. The author has maintained a balance between design and implementation aspects. The design concepts presented are applied by referencing and comparing different programming languages, e.g. Python and Java. The laboratory activity has stimulated students to create software products of growing difficulty with a project-based approach. As a further study, we plan to add functional programming topics, to expand the puzzle-based section of the curriculum, expand the assessment sections [40], to expand the interdisciplinary real-life project section, and compare to other curricula [41]. Moreover, we plan to compare the result of the course delivery, and student engagement with the previous years and explore ways to engage every student with the curriculum [42] leveraging on students’ communities of practice.

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Adaptation to On-Line Teaching with the Access of Social Networks Marcelo Augusto Leal Alves(&) Escola Politécnica, University of São Paulo, Av. Professor Mello Moraes, 2231, São Paulo, SP 05508-970, Brazil [email protected]

Abstract. Due to the COVID-19 pandemic, all courses at the University of São Paulo had to switch to online teaching. Several digital and online resources were applied (Zoom, Google classroom, among others); however, to keep closer contact with the students and provided additional material the use of Social Networks was adopted in line with a previous experience carried-out since 2015 to keep students engaged during the time out of class. The idea is to make use of the students' participation and extensive use of social networks and provide them with additional material related to the classes to increase interest and engage the students with the subject. The experience that started on the introductory class on manufacturing was extended to the machine elements Keywords: Social network


Student engagement
On-line teaching

1 Introduction The COVID-19 crisis presented a series of challenges to higher education. Around the world, several countries were affected, and despite different reactions in each country, the general rule was the suspension of on-campus lecturing and the adoption of online teaching. Another critical issue was keeping students engaged during a period in which many of them returned to their hometowns. With classes suspended and the campus in lockdown, student engagement was essential to the success of the new teaching methodologies that were implemented. Per engagement, we understand student interest in the subjects, following the class schedule, keeping contact with the instructor, and developing further interest in the taught subjects. The adopted strategy was to use social networks to contact the students and present additional material in parallel with the instruction. It is understood that social media is a new tool for communication that became widespread during the last decade. The use of “smartphones” as well as other mobile communication devices allow access to such networks, a permanent activity with alerts of new postings, as well as the option to comment and providing feedback to what is published. Following previous experience with the use of a social network as a student engagement tool, applied to the introductory course of manufacturing processes, the same approach was used in the classes of machine elements during the COVID-19 pandemic. The author created two pages on a popular social network (“Facebook”), © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 280–287, 2021. https://doi.org/10.1007/978-3-030-67209-6_30

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and this article presents the results of such experience as a way to engage students. Similar experiences were tried by [1, 2], and [3] in different subjects and environments. The author evaluates as positive the addition of social network interaction with the students. It certainly is not a replacement for the traditional lectures and other techniques like Project-Based Learning, but it can be a useful auxiliary tool to keep the students engaged when there is a competition to the students' time and attention.

2 Methodology The initial idea of using social networks came after the first class on the Introduction to Manufacturing Processes course in which a survey performed with the students at the first day of classes demonstrated that for that group of students the subject was considered less relevant than others and that they were not familiar with the subject. Just as a background, the Mechanical Engineering Degree Program at Escola Politécnica at the University of São Paulo has ten semesters in total, and every year 80 news students are admitted after their participation at the University of São Paulo entry exams that are open to every student that finished high school. Introduction to Manufacturing Processes is offered in the first semester of the second year, and its syllabus comprises traditional manufacturing processes such as forming, machining, polymers processing, as well as assembly and current trends in manufacturing, such as additive manufacturing. It is a 60 h course (4 h per week, 15 weeks plus three weeks for exams) mandatory to all mechanical engineering students. This first experiment with social networks was tried in 2017, and it has been repeated ever since for this particular course. Table 1 summarizes the initial survey results. At this first year, 50 students participated (62,5% of the full class)—all of them taking this course for the first time. The survey results were initially considered a challenge to the instructor that had to turn an unknown and not much exciting subject into something of relevance to the students. However, previous course evaluation had shown that students had difficulties in visualizing and understanding some of the manufacturing processes, and they wanted to see how the manufacturing-related other fields such as economy, business, and environmental protection. Table 1 also presents the data for the same survey until 2020 (for this year, the survey distribution was before the COVID-19 crisis). On all occasions, the survey was passed on the first day of class. Only students who had not attended the course before had to reply. With lecturing time entirely dedicated to the contents and other pre-established objectives, the idea was to use the off-class time to engage the students on the subject. According to national statistics [4], Brazil had, in 2017, 126.3 million internet users, and among the age group of the students, 88,1% had an internet connection. According to press reports [5] and [6], Brazilians ranked second in social network engagement, among users around the globe, with an average of 3h45m of daily use in 2019. This amount of time was consistent with observations by the author regarding the student behavior as well as with the instructor heard during informal conversations with students.

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M. A. L. Alves Table 1. Initial survey results.

Question “What is your knowledge of manufacturing processes?”

“Do you think that manufacturing is a high technology field?” “Do you think that knowing about manufacturing will be important for your career as an engineer.” “Have you heard of ‘industry 4.0’”? “What is your primary source of information (generic)?”

“For your studies, what is the primary source of information.”

Total number of respondents

Answers None Basic (knows a few processes) Fundamental (knows a few processes and their main features and applications Advanced (has previous technological training in manufacturing) I have no idea Not much It has some new technology Yes No Never thought about it

2017 52% 18%

2018 54% 16%

2019 55% 15%

2020 53% 12%

20%

16%

18%

23%

10%

14%

12%

12%

62% 28% 10%

66% 20% 14%

75% 15% 10%

74% 14% 12%

15% 10% 75%

8% 13% 79%

12% 7% 83%

12% 21% 67%

Yes No Internet TV Radio Newspapers Other Textbooks Classroom notes Internet articles Videos Others

12% 88% 90% 4% 2% 2% 2% 50% 30% 10% 8% 2% 50

13% 87% 88% 11% 1% 52% 27% 8% 8% 5% 63

37% 63% 83% 8% 3% 2% 3% 48% 23% 3% 18% 8% 60

56% 44% 88% 5% 4% 2% 1% 53% 12% 10% 25% 57

Based on the survey results, it was proposed the use of the social network as a way to engage the students. Another objective was to provide additional information and context to the lessons. Another reason for this choice was to use something closer to the students' reality. The initial idea was to have a page dedicated to the course. It was agreed with the students that Facebook would be the network. In order to define the page use the following basic principles were established: • Non-mandatory following • The information posted on the page will not be used on exams

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• Comments and questions were to be replied as quickly as possible • Material on the page will be relevant to provide context to the subjects taught. The page was created, and since then, its following is about 90% of the students, as seen in Table 2, considering a class size of 80 students. Engagement varies with the posting subjects, with an average of 47 views per posting. Posted articles were mostly videos related to the subjects or articles related to news in manufacturing (Fig. 1).

Fig. 1. Screen capture of the social network page.

After the first semester finished, the regular course evaluation was performed, and in all forms (45) that had a written comment, the social network page was regarded as a positive aspect. For the instructor, one positive point of the page was the possibility to measure user interaction with each posting. The social network provides data on the popularity of each posting, how many times the page was viewed, among other data. One issue that was difficult to initiate was debate regarding the information added to the page. The social network is not meant for an in-depth discussion of topics. However, more questions were posed in class related to material posted on the social network. After the initial experience in 2017, the page was kept active for the new classes. The page response was about the same given statistics provided by Facebook. The page engagement and reaction to posts were almost unchanged, as shown in Table 2. The number of participants decreased by a small margin, and on the course evaluation results from 2019, three comments (in 58 replies) pointed that since they did not were Facebook users, then the page was of no use to them. This experience was expanded during the COVID-19 crisis in other courses. However, with different purposes, more associated with the mandatory separation and isolation between students and instructors.

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M. A. L. Alves Table 2. Basic social network page statistics. Page engagement indicator Number of new users Average number of page views per day Average number of comments per post Total number of postings per semester

2017 73 30 2 45

2018 77 41 2 58

2019 74 39 1 50

2020 71 35 1 49

From March 15, 2020, the University of São Paulo suspended all classes. Teaching had to be moved to online sessions using videoconferencing software such as ZOOM™, or Google Meets™. This transition demanded the instructor and students to undergo a learning period on how to use the videoconference as a useful lecture tool. Giving this learning period, effective use of class time was not optimal to present the subjects according to the class schedule. One course that was affected was Machine Elements II, taught at the 1st semester of the 3rd year of the mechanical engineering degree program. This courses' main objective is the application of solid mechanics, both theoretical and numerical methods, to verify strength, stiffness, and stability of mechanical components such as joints (bolted, riveted, welded, bonded), power transmission elements, couplings, bearings among others. It is a second course after the first one that is taught during the previous semester in which the theoretical foundations such as the presentation of strength criteria and their application to power shafts, springs, and spur gears. Both courses have a duration of 60 h, during 15 weeks of classes, and three weeks dedicated to exams during the semester. The two are mandatory for mechanical engineering students. This semester Machine Elements II had 92 students enrolled. This number includes students attending for the first time as well as a group of students that had failed in previous semesters. One of the methodologies adopted for in-depth discussion and problem solving that goes beyond the traditional textbook exercises is the use of case studies, in particular, accident and failure reports of equipment such as airplanes. The students are presented to the failure case and have to research the fundamentals, run simulations (FEM), and have to present their analysis on how and why the failure happened. The cases discussions happen in a four hours session held before the final week of exams. One purpose of the case discussions is to provide background and context to the subjects. As explained before, during the COVID-19 crisis, the class time had to be devoted solely to the syllabus content, discussion of practical cases had to be taken out of the schedule. Since this group of students had been presented to the social network page experience in manufacturing (in 2018), the idea was to use the same tool to either present and discuss the additional material. Similar to what was to in Introduction to Manufacturing, a similar page was set up on the same social network. Another particular reason for setting up this page was difficulties in accessing the e-learning tools provided by the university. The Moodle platform is the base for this system, but due to the sudden excessive data traffic during

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the pandemic, this system became unstable. Another point is the difficulty of accessing the system using mobile devices such as smartphones and tablets. The page had the same layout as the one used for Introduction to Manufacturing. The page had 87 users; a high number considered that 92 students enrolled in Machine Elements II and that following the page was not mandatory because the introduction of the social network page as an experiment and should not interfere with the activities to be accounted on the students’ grades. One difference to the initial experience in manufacturing was the idea to discuss the material posted on the page and not only the presentation of additional material to supplement what was taught during the lectures. The material shared included not only videos but the case reports that helped to the application of the contents but provided a more advanced application that the content provided on textbooks. The first example of the social network application was the presentation and discussion of the loosening of bolted joints. Several videos of the Junker Testing, such as [7, 8] were presented, and students were asked to research and summarize at least two recent (from the last ten years) journal papers on these subjects. This exercise was not the typical one done in the classroom where the instructor normally explains what is the current practice on this subject without further reference on research. The references were uploaded on the social network, and students were able to compare and select which ones they would use to write their report in which they had to describe and explain how the bolted joint can fail by loosening. As one example, one of the cases for in-depth discussion was the accident with the British Airways flight 5390 in which the windscreen detached from the cockpit structure. The cause of this failure was the use of the wrong (shorter) bolts, without the proper initial loading. The Air Accidents Investigation Branch (AAIB) from the United Kingdom investigated the event. The incident is famous for the bizarre situation of the pilot being sucked from the flight deck and held by other crewmembers. He managed to survive, and this fact led this incident to be fully documented by the press. As for the class, two materials were posted on the page: a video report of the accident [9] and the investigation report [10]. To further explore the case, the instructor proposed an exercise in which students had to estimate the load applied to the windshield, the bolts, and explain the failure mechanism. The case study was done out of the class hours, and the social network was used to discuss the matters and share information on the theoretical and numerical models. No grade points were assigned to this work since following the page was not mandatory. The students were encouraged to discuss the models they were developing. They could use whatever communication tools they wanted, but at least part of the discussion had to be done on the social network. This point was significant to enable the instructor to follow the process the students were using to solve the task. This process observation is an improvement compared to see the final results when the students present their reports. It also leaves the possibility for the instructor to interfere with the discussion being more proactive instead of waiting for questions being sent by the students. On two occasions, the instructor interfered by providing clarification on how to identify errors in the finite element analysis of the bolted joints and how to obtain material properties data for aluminum alloys that are not of everyday use.

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The other subject studied was related to riveted joints. It must be noticed that this point is normally limited in the textbooks of machine elements such as [11] and [12]. The case was also related to an aircraft accident, the Japan Airlines flight 123, in which a wrong design of a repaired riveted joint led to the failure of the pressure bulkhead and damage to the tail surfaces of the aircraft that finally crashed. As on the previous case, a video [13] and the investigation report [14] were used. One important point of this second example was to show that there is no ``trivial'' topic and that some decision making during the design phase can lead to unforeseen consequences.

3 Conclusions After the development of the activities, the participants had to provide some feedback regarding the activities. One point that came up was the possibility to discuss the matters out of the class hours and engage with the other colleagues. This discussion was one of the main reasons to implement the social network page to keep students talking about the class subject after they left the classroom. Another raised point was to the elimination of the misconception that even some topics of the syllabus were less critical than others. Real-life examples helped to show that the theory can be applied and further developed in order to understand complex situations. The experience helped to keep the students engaged during the time of the pandemic and led them to study further, going beyond the textbook. A significant point was the possibility to follow more closely how the students react and discuss the subjects. By following the exchanges on the social network page, the instructor was able to understand better how the students understood the proposed cases, how the theoretical and numerical models were developed as well as what sort of discussion and interactions the students had. It must be noticed that without access to the social network by instructor and students, the instructor would not be aware of the content of such conversations and debate between students. This point is an added benefit to the traditional way in which the evaluation tends to be focused on the final deliverables presented by the students, usually a report or a presentation. The possibility of monitoring almost in real-time students working in collaboration can be an essential way to check how teamwork is progressing and how each student work with their colleagues. It is recognized that the experience still needs to be further developed and integrated into the course. It was decided not to include the activities on the grading since there was no planning ahead of time for such use of social networks, and students were not required to join it as a mandatory requirement for the class.

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References 1. Munoz, C., Towner, T.: Opening Facebook: how to use Facebook in the college classroom. In: Gibson, I., Weber, R., McFerrin, K., Carlsen, R., Willis, D. (eds.), Proceedings of SITE 2009–Society for Information Technology & Teacher Education International Conference, pp. 2623–2627. Association for the Advancement of Computing in Education (AACE), Charleston, SC, USA (2009). https://www.learntechlib.org/primary/p/31031/. Accessed 8 June 2020 2. Grant, N.: On the usage of social networking software technologies in distance learning education. In: McFerrin, K., Weber, R., Carlsen, R., Willis, D. (eds.), Proceedings of SITE 2008–Society for Information Technology & Teacher Education International Conference, pp. 3755–3759. Association for the Advancement of Computing in Education (AACE), Las Vegas, Nevada, USA (2008). https://www.learntechlib.org/primary/p/27833/. Accessed 8 June 2020 3. Saunders, S.: The Role of Social Networking Sites in Teacher Education Programs: A Qualitative Exploration. In: McFerrin, K., Weber, R., Carlsen, R., Willis, D. (eds.), Proceedings of SITE 2008–Society for Information Technology & Teacher Education International Conference, pp. 2223–2228. Association for the Advancement of Computing in Education (AACE), Las Vegas, Nevada, USA (2008) 7 June 2020 https://www. learntechlib.org/primary/p/27538/ 4. Instituto Brasileiro de Geografia e Estatística – IBGE, Acesso à internet e à televisão e posse de telefone móvel celular para uso pessoal – 2017. Pesquisa Nacional por Amostra Domiciliar – PNAD, Internet Document. https://biblioteca.ibge.gov.br/vizualizacao/livros/ liv101631_informativo.pdf. Accessed 1 Jun 2020 5. Ribeiro, C.: Conheça as redes sociais mais usadas no Brasil e no Mundo em 2018, on line article. https://www.techtudo.com.br/noticias/2019/02/conheca-as-redes-sociais-maisusadas-no-brasil-e-no-mundo-em-2018.ghtml. Accessed 8 Jun 2020 6. Politi, C.: Quanto tempo os brasileiros gastam em redes sociais? https://www.tracto.com.br/ quanto-tempo-os-brasileiros-gastam-em-redes-sociais/. Accessed 8 Jun 2020 7. Friction Factors – Fastening Theory part 2, Youtube video. https://youtu.be/fN9b3ByRh7A. Accessed 1 Jun 2020 8. VU Junker test demonstration, Youtube video. https://youtu.be/ssr8jMpv-Ao. Accessed 1 Jun 2020 9. Pilot Sucked Out In Flight | British Blowout | British Airways Flight 5390, Youtube video. https://youtu.be/3AeWKIKmCBQ. Accessed 1 Jun 2020 10. AAIB, Report on the accident to BAC One-Eleven, G-B JRT over Didcot, Oxfordshire on 10 June 1990, PDF Internet file. https://reports.aviation-safety.net/1990/19900610-1_BA11_GBJRT.pdf. Accessed 1 Jun 2020 11. Norton, R. L. Machine Design, 4th Edition, Prentice Hall, New Jersey (2011) 12. Budynas, R.G., Nisbett, J.K.: Shigley’s Mechanical Engineering Design, 8th edn. Tata McGraw-Hill Publishing Company Limited, New Delhi (2008) 13. Segundos Fatais - Queda incontrolável no Japão, Youtube vídeo. https://youtu.be/ jORmYQ5-2D8. Accessed 1 Jun 2020 14. FAA, Lessons Learned JAL 123, Internet Document. https://lessonslearned.faa.gov/ Japan123/JAL123_Acc_Report.pdf. Accessed 1 Jun 2020

Work-in-Progress: Using the PerFECt Framework to Design and Implement Blended Learning Activities to Introduce the Binary System in Primary School Students Nektarios Moumoutzis1,2(&), Nikolaos Apostolos Rigas1, Chara Xanthaki3, Yiannis Maragkoudakis1, Christina Christodoulakis4, Desislava Paneva-Marinova2, and Lilia Pavlova5 1

Laboratory of Distributed Multimedia Information Systems and Applications, School of Electrical and Computer Engineering, Technical University of Crete, 73100 Chania, Crete, Greece {nektar,imarag}@ced.tuc.gr, [email protected] 2 Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria [email protected] 3 Directorate of Secondary Education, Chania, Crete, Greece [email protected] 4 Department of Computer Science, University of Toronto, Toronto, Canada [email protected] 5 Laboratory of Telematics, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria [email protected]

Abstract. This paper presents how the PerFECt framework is employed to enable innovative teaching and learning mathematics in schools using dramabased approaches. The topic addressed lies in the cross-section between mathematics and computer science: teaching and learning the binary system of arithmetic that constitutes the basis of modern computing. The work builds on previous research efforts targeting gamification of mathematics and is seen under new light offered by the Theatre in Mathematics (TIM) Methodology. The result is an engaging game to teach the binary system to children using their bodies and simple rules for interacting with each other. Following these simple rules the participants enact the operation of a calculator that is able to transform integers into their binary representations and compute the result of the four arithmetic operations (addition, subtraction, multiplication and division). The game can be combined with online activities using a simulator of the game, so that learners can explore it for themselves and discover how the arithmetic operations are done, even when they are not in the same physical space with their peers. This way, an effective blended learning approach is ultimately offered combining face-to-face and online activities. Keywords: Theatre system


Mathematics
Computer science principles
Binary

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 288–295, 2021. https://doi.org/10.1007/978-3-030-67209-6_31

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1 Introduction People learn and create within certain social contexts, in environments, physical or virtual, within which other people are engaged as well, possibly with different roles but common goals and expectations to create or learn. In this respect, the central concept of community is employed to signify the social context within which human creativity is exercised or learning happens. The proliferation of digital technologies, opens us new opportunities, especially when digital systems can be realized by the composition of elementary components and be put to work by end users, eventually facilitated by IT engineers that play the role of catalysts of change and evolution of those systems towards directions that could not be initially foreseen [1]. Cabitza et al. [2] emphasize the fact that end users are becoming “producers” of contents and functionalities. On the other hand, the term expert user is suggested to signify an expert in a particular domain with main goal to develop appropriate technological capabilities. An expert user engages in creative/authoring activities without being a professional software developer. Usually the role of end user and that of an expert user are played by different people that may also belong to different communities. Furthermore, Cabitza et al. [2] suggest the role of meta-designer to describe the work done by professionals who create the socio-technical conditions for empowering end users in acting as active contributors of contents and functionalities. A metadesigner creates open systems that can be further developed by their users acting as codesigners. However, apart from the technical conditions necessary to set up such environments, there is a need to effectively create the social conditions that will allow expert users to build and adapt the artifacts to be used by end users. In respond to this need, a special user role is specified: maieuta-designers. A maieuta-designer creates the necessary preconditions for facilitating expert users appropriate the design culture and technical notions necessary for the meta-task of artifact development and involving as many end users as possible in the process of continuous refinement of the artifact, by improving participation. The user of the term “maieuta” directly references the Socratic method of getting people acquire notions, motivations and self-confidence. All above concepts are defined in the PerFECt framework [3]. The next sections describe how this framework supports the development of a Community of Practice in teaching and learning mathematics employing theatrical approaches. In particular, the work presented here adheres to an important topic in the cross-section between mathematics and computer science: teaching and learning the binary system of arithmetic. The structure of the paper is as follows: Sect. 2 presents previous work done with respect to the gamification of mathematics as a way to make mathematics teaching and learning more engaging and meaningful for children. Section 3 presents the Theatre in Mathematics (TIM) Methodology on how theatre can be employed to support playful learning in mathematics employing the concepts of the PerFECt framework. Section 4 presents the overall design of the theatrical game to teach the binary system to children employing theatrical techniques. Section 5 concludes and presents plans for future work.

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2 Previous Work The previous work that constitutes the starting point for the work in progress presented in this paper is GamifyMaths [4]. GamifyMaths offers a conceptual framework for amplifying and enhancing mathematics learning that is taking place in the classroom by adopting inquiry-based learning, gamification strategies and the flipped classroom model for engaging students in immersive and interactive mathematics resources and processes realized both out-of-the classroom (online) and in-class for involving students into higher-order inquiry-based learning in mathematics. Solving mathematical problems necessitates knowledge, skills, creativity and resilience. To simplify the process of acquiring such skills, GamifyMaths propose an architecture that combines play, learning, motivation, participation and engagement. However, there is a need to address the role of the teachers and the set of skills that they need to develop in order to have the full control of the pedagogical process and be able to support their students appropriately. This need was identified by GamifyMaths that stressed the necessity for the establishment of a Community of Practice to support the teachers through learning materials and scenarios, a social network to promote their close collaboration and exchange of experiences and ideas. Several existing platforms and initiatives can serve as hosting infrastructures for such community building process such as the Coursevo Platform [5] that is employed in the work described in this paper (see next section).

3 TIM Project Methodology and Community of Practice The purpose of “TIM - Theatre in Mathematics” project is to face the main obstacles in the way of teaching and learning mathematics at EU level. It aims to contribute to the ways to improve mathematics teaching and learning, in particular providing a new methodology - TIM Methodology - to teach mathematics using drama. The project develops the TIM methodology by deepening and combining two existing approaches: “Mathemart – Playing with mathematics in the theatre workshop” and “Process Drama - change of roles, perspectives, and role aspects in teaching mathematics”. Mathemart addresses teaching mathematics through Social and Community Theatre (SCT) methodology to get students involved in the game of mathematics by means of theatrical games and activities: an overall approach that includes mind and body, inborn creativity and engagement. To establish a Community of Practice for TIM, following the principles and concepts offered by the PerFECt framework, the Coursevo Platform [5], offering diverse services within activity spaces, is used. Coursevo enables communication between tutors/trainers and trainees, cooperation among trainees and access to coursework information and learning resources. It can combine traditional classroom-based lessons and practical sessions, with self-study and eLearning. The figure below depicts how the PerFECt framework enables a co-evolution process around the four user roles (end users, expert users, meta-designers and maieutadesigners) presented in Sect. 1. This process is represented by three homocentric cycles: action-interpretation cycle at the lower level, task-object cycle at the middle

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level and community-technology cycle at the upper level. In the center of this process is the idea of universality of objects, i.e. the idea that objects can be better understood if they comply to deterministic rules (cause-effect relationships) as it is the case for digital objects of any kind as well as for humans following certain rules, as it is the case for the Human Calculator theatrical game that is presented in the next section. The idea of performativity is also important to emphasize the fact that technology essentially offers new affordances (i.e. new action and interaction possibilities) encapsulated in the properties for performative artifacts (pArtifacts) [3]. In the case of the Human Calculator game, these new affordances rely on drama-based interactions (Fig. 1).

Fig. 1. The main components of the PerFECt framework

4 The Human Calculator Theatrical Game The Human Calculator is a theatrical game to learn computing principles in a way that promotes development of embodied knowledge and active exploration of strategies (algorithms) to find the binary representation of numbers and perform the four arithmetic operations (addition, subtraction, multiplication and division). It employs no special equipment, just the body of the participants. To play this game, very simple rules are given to the participants to create a binary calculator using their bodies. To start the game, participants are split into two groups: One group (the actors) enacts the Human Calculator while the other group (the audience) observes the operation of the Human Calculator, explores its properties and reflects on the phenomena observed. To enable the active participation of all, the participants alternate between the group of the actors and the audience. Each participant in the group that enacts the Human Calculator represents a bit that can be in state 0 or state 1 as shown in Fig. 2. To create n-bit numbers, n participants

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are organized in a row, one behind the other, as depicted in Fig. 3 where 8 participants are organized in a row. All of them follow the same rule to alternate between states 0 and 1: “Stand up, raise your hand and touch the shoulder of the child in front of you. Whenever somebody touches you, lower your hand. If somebody touches you again, raise your hand and touch the shoulder of the child in front of you. Continue this way forever”. State changes can be triggered either by touches from the child immediately behind in the row, or by touches made by the “operator” of the Human Calculator who is able to touch anyone in the row.

Fig. 2. The Human Calculator theatrical game distinguishes between two states: When in state 0, the participant raises one hand to touch the next participant (left). When in state 1, the participant is standing up without touching anybody (right).

Following the rule, it is possible to find the binary representation of a number and perform additions and multiplications. Figure 3 depicts how this is possible. The Human Calculator is initialized with all participants in state 0. Then, if any participant is touched by the “operator” it moves from state 0 to state 1, due to the common rule followed by all participants. Consequently, if the rightmost child is touched once, the corresponding binary represented will be 1. If the rightmost child is touched again, it will move from state 1 to state 0, thus touching the next child that will change from state 0 to state 1. In general, whenever a child that is already in state 1, is touched, it will move back to state 0 and trigger a state change to the next child to the left by touching it. This is essentially the mechanism that puts the Human Calculator in action by chaining together state changes. Adding two numbers n and m can be naively performed if the Human Calculator is initialized and the operator touches the rightmost child n times to “load” the first number and then m times more to accumulate the value of the second number. A faster way to make the addition, if the operator has mastered the binary representation of numbers, is by directly setting (i.e. touching) the bits that correspond to the binary representation of n and then adding the bits that correspond to the binary representation of m. Finally, multiplication can be performed as a series of additions. For subtraction and division, as well as for the representation of negative numbers in two’s complement notation, the participants are invited to follow a slightly different rule: “Whenever somebody stops touching you, lower your hand (stop touching the child in front of you). If somebody stops touching you again, raise your hand to touch

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Fig. 3. The Human Calculator theatrical game in action: Eight children, one behind the other, are organized initially in state 0, i.e. touching the child in front of them (top). Note that the leftmost child does not touch anyone else. If an “operator” touches the rightmost child four time, the rule of the game ensures that the participants will correctly change states to represent numbers 1, 2, 3 and 4, one after the other.

the child in front of you. Continue this way forever”. State changes are triggered when a child feels that somebody stops touching it. Due to space limitations, we do not elaborate more on the details of this part of the game inviting the interested reader to explore using the simulator at https://scratch.mit.edu/projects/410832633/. It is important to note here that the Human Calculator game is designed to be explored in episodes, following the principles of the PerFECt framework, in a way that promotes the gradual transition of learners from being an end users (just observing the operation of the Human Calculator) to becoming expert users (able to perform arithmetic operations). This gradual transition is supported by the teacher-facilitator, the maieutadesigner in the terminology used by the PerFECt framework. Participants learn the rules of the game by enacting them, observe how the rules trigger certain behavior, and explore the phenomena that emerge by using the Human Calculator as operators (expert users). To enable this active exploration when not in the classroom, a simulator of the game has been developed in the Scratch programming environment [6] and is available at https://scratch.mit.edu/projects/410832633/. Using this simulator, the face-to-face

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activities can be combined with online activities so that learners can explore the game for themselves and discover how arithmetic operations are done, even when they are not in the same physical space with their peers. This blended-learning approach can also support flipped teaching strategies [4].

5 Concluding Remarks and Future Work The PerFECt framework addresses issues related to the establishment and support of rich socio-technical contexts where engaging learning experiences can take place and human creativity can be effectively expressed. It was initially developed to capture design principles suitable for the development of open learning environments [7] to effectively support collaborative learning [8] that emphasizes the need to link learning to effective social structures. As a concrete example of how this framework can be put in action, this paper presents the how the TIM project builds a Community of Practice in teaching mathematics using drama-based approaches, exemplified by a theatrical game for creatively exploring the binary system. Future work will evaluate the learning effectiveness of using this theatrical game in schools. The overall evaluation approach employs a number of tools that have already been used in previous evaluation efforts related to the use of theatrical approaches in learning [9]. Future work will also develop alternative representations of binary numbers in the form of a board game resembling an abacus. This alternative representation will facilitate a deeper understanding on the internals of arithmetic operations. Finally, future plans include the application of the PerFECt framework in facilitating content creation and community management in schools [10] and in analysis of serious games [11], cultural heritage systems [12] and learning personalization [13]. Acknowledgements. The development of the PerFECt framework is a work partly supported by the Bulgarian Ministry of Education and Science under the National Research Programme “Cultural heritage, national memory and development of society” approved by DCM №577/17.08.2018. The TIM project (project nr. 2018-1-IT02-KA201-048139) is funded by the Erasmus + programme.

References 1. Cabitza, F., Simone, C.: Building socially embedded technologies: implications about design. In: Wulf, V., Schmidt, K., Randall, D. (eds.) Designing Socially Embedded Technologies in the Real-world, pp. 217–270. Springer, London (2015) 2. Cabitza, F., Fogli, D., Piccinno, A.: Cultivating a culture of participation for the co-evolution of users and systems. In: CoPDA@ AVI, pp. 1–6. (2014) 3. Moumoutzis, N., Koukis, A., Christoulakis, M., Maragkoudakis, I., Christodoulakis, S., Paneva-Marinova, D.: PerFECt: a performative framework to establish and sustain onlife communities and its use to design a mobile app to extend a digital storytelling platform with new capabilities. In: International Conference on Interactive Mobile Communication Technologies and Learning (IMCL), Thessaloniki, Greece (2019)

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4. Lameras, P., Moumoutzis, N.: Towards the gamification of inquiry-based flipped teaching of mathematics a conceptual analysis and framework. In: 2015 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL) (2015) 5. Pappas, N., Arapi, P., Moumoutzis, N., Christodoulakis, S.: Supporting learning communities and communities of practice with coursevo. In: 2017 IEEE Global Engineering Education Conf. (EDUCON), pp. 297–306. Athens, Greece (2017) 6. Maloney, J., Resnick, M., Rusk, N., Silverman, B., Eastmond, E.: The scratch programming language and environment. ACM Trans. Comput. Educ. (TOCE) 10(4), 1–15 (2010) 7. Mylonakis, M., Arapi, P., Pappas, N., Moumoutzis, N., Christodoulakis, S.: Metadata management and sharing in multimedia open learning environment (MOLE). In: Research Conference on Metadata and Semantic Research, pp. 275–286. Springer, Berlin (2011) 8. Stylianakis, G., Moumoutzis, N., Arapi, P., Mylonakis, M., Christodoulakis, S.: COLearn and open discovery space portal alignment: a case of enriching open learning Infrastructures with collaborative learning capabilities. In: 2014 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL2014), pp. 252–256. IEEE (2014) 9. Moumoutzis, N, Gioldasis, N., Anestis, G., Christoulakis, M., Stylianakis, G., Christodoulakis, S.: Employing theatrical interactions and audience engagement to enable creative learning experiences in formal and informal learning. In: Auer, M., Tsiatsos, T. (eds.) Interactive Mobile Communication, Technologies and Learning, pp. 142–154. Springer, Cham (2017) 10. Yoshinov, R., Kotseva, M.: Vision for the engagement of the e-facilitator in school in the inspiring science education environment. Serdica J. Comput. 9, (3–4) (2016). IMI-BAS, 2016, ISSN:ISSN 1312-6555 11. Márkus, Z.L., Kaposi, G., Veres, M., Weisz, Z., Szántó, G., Szkaliczki, T., PanevaMarinova, D., Pavlov, R., Luchev, D., Goynov, M., Pavlova, L.: Interactive Game Development to Assist Cultural Heritage. Digital Presentation Preserv. Cult. Sci. Heritage 8, 71–82 (2018). ISSN 1314-4006 (Print), eISSN 2535-0366 (Online) (2018) 12. Dochev, D., Pavlov, R., Paneva-Marinova, D., Pavlova, L.: Towards modeling of digital ecosystems for cultural heritage. digital presentation and preservation of cultural and scientific heritage 9, 77–88 (2019). ISSN 1314–4006 (Print), eISSN 2535–0366 (Online) (2019) 13. Arapi, P., Moumoutzis, N., Mylonakis, M., Theodorakis, G., Christodoulakis, S.: A pedagogy-driven personalization framework to support automatic construction of adaptive learning experiences. In: Leung, H., Li, F., Lau, R., Li, Q. (eds.) International Conference on Web-Based Learning, pp. 55–65. Springer, Berlin (2007)

Technology Based Collaborative Learning

Measuring Student Confidence in the Intercultural, Cooperative Teaching of Ancient Greek via Semiotic Feedback Despina D. Lazaropoulou(&) and George S. Ypsilandis Department of Italian Language and Literature, Aristotle University of Thessaloniki, Thessaloniki, Greece [email protected], [email protected]

Abstract. Collaborative learning is on the rise and this goes hand in hand with the developments in modern technology. Research projects promoting intercultural communication through electronic collaboration between learners are now being considered provided that there is a common tool of interaction, a common language. This study, conducted with the approval of the Greek Ministry of Education, forms an alternative distance, digital and interculturally cooperative learning environment, promoting exchange of knowledge in a made-up discourse setup with relevance to the teaching of Ancient Greek (AG). Participants completed grammar exercises corrected by their peers on the other side in pairs. An invented, semiotic language was used by participants for them to communicate. Short- and long-term confidence of subjects was measured using a Vougiouklis and Vougiouklis (2008) ravdos [4]. It was hypothesized that this innovative approach would increase not only a) student performance, [8], but also b) student confidence, regarding the accuracy of their responses in the test. The results analyzed, showed a statistically improved score in student confidence in post-test 1 (after an hour) and a positive tendency in post-test 2 (after a week). The learning experience of the participants, tested as an independent variable, did not prove to statistically affect test results in either of the two post-tests. Positive results favor the tested treatment being beneficial and having a positive impact to all learners (Greeks and Italians), independent of their learning experience in the subject. Keywords: Collaborative language learning feedback


Confidence
Corrective

1 Introduction The teaching of Ancient Greek (AG) has been and continues to be approached through the traditional grammar translation method, it being a method that owed its origin to the teaching of classical languages. Although current language teaching methodology has moved to more learner-centered and task-oriented approaches, focusing on communication and the productive skills (speaking and writing), the methodology of teaching classical languages has not been affected by this development.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 299–306, 2021. https://doi.org/10.1007/978-3-030-67209-6_32

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Nowadays, reports on collaborative learning and peer assessment, by definition learner centered approaches, have revealed it to promote positive effects on language learning [8, 13, 17], which in many cases is measured through learner performance in after treatment tests. Peer assessment, as a collaborative technique, aims to engage the learner in the process as an active participant, and thereon to increase his/her performance; an approach that challenges teaching and learning that contains a more passive reception of the correct/expected usually linguistic structure, typically provided by a teacher or an electronic device. Such a passive approach does not always bring about the desired results, in terms of consolidation, as there are cases in which the error is constantly repeated even when the student has studied the grammatical phenomenon [7]. On the other hand, activating students, and making them identify the error and correct it themselves, is a method much more compatible with the learning objectives set by the teacher [2]. In this direction, student performance (learning outcome) was examined [8] after collaborative intercultural peer-correction treatment or observing the learning benefit of using the feedback provided by their peers [9], through the medium of a semiotic made-up language. Questions related to the influence such methods have on learner psychology [12] may need to be examined and more specifically those that impact on learner self-confidence. Self-confidence is the dependent variable examined in the present study and learning experience the only independent variable explored. The impact of students’ learning experience, measured in months, was recorded to explore the research target (self-confidence) through a statistical Pearson correlation test. The following alternative research hypotheses were tested: • H1. Cooperative learning through semiotic (sign process) corrective feedback among peers, of different nationalities, working in pairs via the Internet has a significant positive impact on student stated self-confidence in the learning of AG. • H2. Initial statement of confidence remains after a week, so revealing a long-term achievement.

2 Confidence and Learning Performance The usefulness of gathering confidence in empirical research, and its integration as a measurable variable in learning analyses, is significant as this factor is more than a selfstatement related only to learner personality. It is an indirect statement of a) the degree of explicit knowledge possessed by the individual, and b) a tool of awakening and activating peripheral implicit knowledge and strategies to reach learning goals [10]. The relationship between confidence and student performance becomes evident by observing learners’ tendency to change their initial answer, when completing a Multiple-Choice (MC) test. This self-monitoring tactic is calculated by measuring students’ confidence after each response to a test by using different tools (see, next chapter). It is suggested that learners with higher performance tend to perceive their abilities better [11] and it would be expected that when students improve their monitoring skills, higher test performance be reached.

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Moreover, an attempt becomes possible to link students’ tendency to change their initial response to a psychological factor [1] that would incorporate the confidence question. In more detail, research attempted to investigate this issue in closed-ended tests, by registering learner perceptions as well as by identifying what leads them to adopt this tactic and how this relates to the effectiveness of change. The suggestion is that when learners are aware of the reason they proceed with this change, this strategy is successful and positively influences their performance, and thus changing a response could be beneficial [1]. Another study [6] reached similar conclusions and showed positive results, although not all learners seem to have benefited equally. This inconsistency, to a degree, may restrict the possibility of drawing unambiguous conclusions about the effects of this tactic on all learners, particularly when the specific characteristics of each candidate in a language test have been ignored [16]. Moreover, it is not so possible to identify the ability of each learner to distinguish between the wrong initial answers and those that do not require corrective action [3]. Finally, it is not clear whether changing initial responses is the result of a conscious choice rather than of a psychological function, which is shaped by the conditions under which a language test is performed [1]. Whatever the reason, though, ‘guessing’ is seen as an unwelcome tactic that does not bring the desired results [14]. On the contrary, it has been advocated that this tactic is a) automatically activated in the human brain, when learners do not possess the correct option, and b) based on informed selections by activating implicit knowledge on the subject [15]. Hence, it is proclaimed that inferencing would need to be encouraged either by providing additional test time for testees to check their responses or be recommended by the examiner-teacher. 2.1

Confidence Measurement

The measuring students’ certainty as a qualitative variable would also need to be discussed. Most researchers traditionally use Likert scales, despite the various disadvantages surrounding their implementation when measuring fuzzy variables, such as this one here. The problem concentrates in the structure of the instrument that does not provide clear distinctions between the points of the scale, which are subject to subjectivity and general ambiguity. It is doubted whether vague concepts such as confidence can be effectively depicted on a scale the form of which is standardized and predetermined by the researcher. It is stated that this standardized form influences participants’ way of thinking, thus affecting also their final answers [5]. Alternatively, the use of a ravdos (bar) is suggested, with values ranging from 0 to 1 where 0 represents a totally negative statement and 1 a totally positive. Its ideal length was set at 6.2 cm, the Golden Ratio of 10, instead of 10 cm that was originally suggested. This particular choice is based on the fact that the human eye is accustomed to distinguishing and dividing a 10 cm segment into its individual parts. That way, the new bar design and the new length helped prevent any segmentation that may result from the natural human tendency, thus inadvertently leading to data that will be a result of an uncontrolled process [5].

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Nevertheless, the Golden Ratio of 10 was not adopted in all cases. The 10 cm confidence bar has also been integrated in the methodological approach to measure candidates’ confidence in each of the queries of the linguistic tests, so that the variable of confidence can be better statistically processed and analyzed [10].

3 Method 3.1

Subjects

A total of 70 students, 35 learning AG from the 1st High School of Thessaloniki and another 35 from the Liceo Classico Gentileschi of Naples were involved in the study. 3.2

Design and Procedure

Two similar multiple-choice grammar exercises were initially prepared, one for each of the two phases of the research. All grammatical phenomena examined had been taught in the classroom before the experiment, and teachers from both sides did not provide any extra feedback on the examined linguistic phenomena during treatment. Participants were asked to cooperate in pairs (one from each school), each correcting the other and providing feedback through a communication model (made-up language) based on semiotics. The procedure was deployed in three steps [8]: 1. Participants answered the closed-ended questions of the first test individually, which appeared in the Google Docs tool (doc-version 1), and marked their level of confidence on the ravdos for each question. 2. In pairs they compared their answers and provided cooperatively corrective feedback to each other through the made-up language (on the same doc-version 2). 3. Immediately after that, subjects were tested again individually with the same test and stated their level of confidence (short-term confidence). 4. A week later they were re-tested through the use of a similar test (test two) on the same grammatical phenomena and stated their level of confidence (long-term confidence). 3.3

Tools

The following tools were used: a) the semiotic-sign language with interpretations translated into Greek and Italian. Through the use of a combination of signs, participants were able to provide grammatical metaliguistic feedback, b) two tests, one used before treatment and the other after treatment, c) a 10 cm ravdos for participants to record their confidence [4].

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4 Analysis 4.1

Frequencies of the Independent Variable

The crosstabulation Table 1 below depicts the frequencies concerning the experience of all subjects in the learning of AG; the independent variable. Table 1. Frequencies of the independent variable Italy

Greece Total

Experience 12 months 31.4% 0.0% 15.7% 21 months 68.6% 0.0% 34.3% 30 months 0.0% 100.0% 50% Total 100.0% 100.0% 100.0%

11 of the Italian subjects had been taught AG for 12 months (15.7%), while 24 declared that they had 21 months (34.3%) learning experience in Ancient Greek. 35 Greeks (50%) had 30 months experience and thus, they were significantly more experienced in AG learning. 4.2

Confidence

Scores of declared confidence in relation to H1 The values that arose from the subjects’ statement of confidence, during each research phase, for each one of the questions, are shown in Table 2. The first column offers the statistics of students’ confidence before treatment (confidence in initial test), while the next two columns depict the scores right after treatment (short-term) and after a week, respectively.

Table 2. Scores of confidence in relation to H1 Confidence in initial test Short-term confidence Long-term confidence Valid 70 70 70 Missing 0 0 0 Mean 57.805 69.805 69.145 Median 57.070 73.715 73.355 56.00a 60.29a Mode 31.43a Std. Deviation 18.369 16.601 14.917 Minimum 8.00 19.14 15.57 Maximum 100.00 93.71 94.14 a Multiple modes exist. The smallest value is shown

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It is apparent that all descriptive measurements of student confidence after treatment (mean, median, mode) increased. Notice that, rise of the mean value after treatment (short-term) does not ensure an even greater increase in the long-term measurement, but it does at least maintain initial gains made. Standard deviation (showing how much participants of this group differ from the mean value for the group) lessens from the first value of r = 18.3 to r = 16.6 and later at r = 14.9 which shows that values become more concentrated around the mean of the group. Notice also that, while the mean value increases, the standard deviation is dropping which shows that when confidence among members is growing, the mean value becomes more reliable. Results from Paired Samples T test: Comparison between means of confidence. A paired samples t test was used (Table 3) to compare the means of both groups in twos, between the two measurements on the same continuous, dependent variable (confidence). Table 3. Paired differences Mean Std. Deviation Std. Error mean T Sig. (2-tailed) Initial-short term −11.99943 17.39164 2.07870 −5.773 .000 Initial-long term −11.33929 12.57737 1.50328 −7.543 .000

The results show that increase in confidence is statistically significant at p < 0.05 level of significance (t = 5.773; p = .001) between initial test and in the short term after treatment and this is maintained in the long-term (t = 7,543; p = .001). This means that subjects stated they feel more confident after treatment and this level of confidence remained in the second test. Correlations between Experience in Learning AG and Confidence at Initial Test. Further, correlations between the independent variable (learning experience in AG) and the dependent variable (confidence) were investigated. In this case the Spearman’s rho test was employed, as the dependent variable did not have a canonical distribution. A statistically significant association is registered at p < 0.05 level of significance (2-tailed significance level = 0.048) (Table 4). Table 4. Correlations

Spearman’s rho

Experience of AG learning in months

Correlation coefficient Sig. (2-tailed) N Confidence at the Initial Correlation test Coefficient Sig. (2-tailed) N *Correlation is significant at the 0.05 level (2-tailed)

Experience of AG 1.000

Initial confidence .237*

. 70 .237*

.048 70 1.000

.048 70

. 70

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This shows that when learning experience in AG increases, stated confidence grows as well. Results from Paired Samples Statistics: Learning Experience and Confidence. Change in students’ confidence, in the three stages of the study, was also explored. Table 5 below illustrates the mean of confidence for all three groups depending on stated experience in the learning of AG. Despite the registered increase of students’ confidence in all the three groups, this trend was not statistically significant. This may be explained by the fact that the experiment was executed only once, and participants did not have the opportunity to record statistically significant benefits. Finally, the group that benefits more is the one with 21 months of experience in the subject. Table 5. Paired samples statistics

Mean: Certainty in initial test Mean: Certainty after treatment Mean: Certainty after a week Difference between initial confidence and confidence after treatment Difference between confidence after treatment and confidence after a week

12 months 56.73 67.68 72.96 10.95

21 months 52.02 70.69 70.70 18.67

30 months 62.10 69.86 66.87 7.76

5.28

0.01

−2.99

5 Conclusions and Discussion The evidence confirms the hypotheses. Cooperative, distance learning corrective-signfeedback between peers, proved to be beneficial for the registered confidence for all subjects, irrespective of their experience in the learning of AG. In addition, the construct of confidence seems to be parallel to learning experience, i.e. when learning experience increases, confidence grows as well, and its growth is maintained after a week in all groups, which is a promising outcome for the design and conduct of future experiments. Learning experience of the participants on the subject (despite its unbalanced distribution) had an parallel positive effect on stated confidence. Among the shortcomings of this present research are the low external validity of the experiment (small group of subjects not representative of the population) and the short period of treatment. In this light, although conclusions are not generalizable (low external validity), this research may be perceived as being a promising pilot study in a research path on the subject, to be repeated at a second phase with a larger sample following exactly the same cooperative learning procedure. Furthermore, this was an alternating experiment in which all groups follow the exact same treatment and there was not a control group used for comparisons, i.e. a group treated with a more traditional corrective feedback method provided by the teacher. Finally, positive results may be attributed to the effect of novelty aspect of the experiment on participants, i.e. an experiment enthusiasm which may fade out as time passes.

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This tested initial reconnaissance approach, may become a new route for a global qualitative cooperation between educational institutions and students, in which the teaching of AG is included in their syllabi, in a systematic way, at an international level. In addition to the hypotheses already tested here, further research may extend to measuring confidence at the tertiary level of education with the inclusion of a control group.

References 1. Al-Hamly, M., Coombe, C.: To change or not to change: Investigating the value of MCQ answer changing for Gulf Arab students. Lang. Test. 22(4), 509–531 (2005) 2. Corder, S.P.: The significance of learner’s errors. IRAL-Int. Rev. Appl. Linguist. Lang. Teach. 5(1–4), 161–170 (1967) 3. Higham, P.A., Gerrard, C.: Not all errors are created equal: metacognition and changing answers on multiple-choice tests. Canadian J. Exp. Psychol. Revue Can. de Psychol. expérimentale 59(1), 28 (2005) 4. Kambaki-Vougioukli, P., Vougiouklis, T.: Bar instead of scale. Ratio Sociol. 3, 49–56 (2008) 5. Kambaki-Vougioukli, P., Karakos, A., Lygeros, N., Vougiouklis, T.: Fuzzy instead of discrete. Ann. Fuzzy Math. Informatics (AFMI) 2(1), 81–89 (2011) 6. Kruger, J., Wirtz, D., Miller, D.T.: Counterfactual thinking and the first instinct fallacy. J. Pers. Soc. Psychol. 88(5), 725 (2005) 7. Lalande, J.F.: Reducing composition errors: an experiment. Mod. Lang. J. 66(2), 140–149 (1982) 8. Lazaropoulou, D.D., Ypsilandis, G.S.: Cooperative learning via semiotic feedback in ancient Greek teaching: a case study in Greek and Italian schools. eClassica 5, 89–101 (2019) 9. Loewen, S., Erlam, R.: Corrective feedback in the chatroom: An experimental study. Comput. Assist. Lang. Learn. 19(1), 1–14 (2006) 10. Mouti, A.: Investigating Cognitive Style as a Factor Affecting language Test Performance and Confidence (No. GRI-2012-8001) (in Greek). Aristotle University of Thessaloniki (2011) 11. Nietfeld, J.L., Cao, L., Osborne, J.W.: Metacognitive monitoring accuracy and student performance in the postsecondary classroom. J. Exp. Educ. 74(1), 7–28 (2005) 12. Papinczak, T., Young, L., Groves, M.: Peer assessment in problem-based learning: A qualitative study. Adv. Health Sci. Educ. 12(2), 169–186 (2007) 13. Race, P., Brown, S., Smith, B.: 500 Tips on Assessment, 2nd edn. Routledge, London (2005) 14. Shatz, M.A., Best, J.B.: Students’ reasons for changing answers on objective tests. Teach. Psychol. 14(4), 241–242 (1987) 15. Tsopanoglou, A., Ypsilandis, G.S., Mouti, A.: Piloting a polychotomous partial-credit scoring procedure in a multiple-choice test. Lang. Learn. High. Educ. 4(1), 43–58 (2014) 16. van der Linden, W.J., Jeon, M., Ferrara, S.: A paradox in the study of the benefits of testitem review. J. Educ. Meas. 48(4), 380–398 (2011) 17. Zhang, Y.: Cooperative language learning and foreign language learning and teaching. J. Lang. Teach. Res. 1(1), 81–83 (2010)

Transition from In-Class to Online Lectures During a Pandemic Nasim Muhammad and Seshasai Srinivasan(&) McMaster University, Hamilton, ON L8S4L8, Canada {nasimm,ssriniv}@mcmaster.ca

Abstract. A global pandemic is underway that has required an overwhelming number of universities and educational institutions across the world to stop all in-person classes. This has mostly been implemented following social distancing guidelines by various governments, some of whom have enforced a complete lockdown of the affected areas. The universities are facing a situation wherein it is believed that this pandemic will eventually be overcome, but if the classes are not conducted and curriculum not completed, the students' career progress will be severely disrupted. In a bid to address this, classes were abruptly shifted to an online format, and the transition happened with a span of 2–4 days. In this work, we present an approach that has been followed to implement this transition. Keywords: Virtual classroom


Online lectures
Online assessments

1 Introduction Towards the end of 2019 and early part of 2020, with the absence of travel restrictions and social distancing norms, the Novel Coronavirus spread to numerous countries, resulting in a pandemic. In a bid to arrest the spread of the virus and curb the loss of lives, several businesses and organizations stopped operating. Educational institutions were not immune to this havoc wrecked by the pandemic. While every company has its challenges, the difficulties for the educational institutions are of its own kind. By the time the pandemic was declared, McMaster University was well into the winter term with just about four weeks of school remaining, followed by an examination session. The choice was to stop operations at the university or determine an alternative approach where we could continue operations but in a remote manner. The former implied disrupting the education cycle that students are following, delaying graduation, thwarting employment offers, halting research that is critical for a university, thesis presentations, etc. As in other businesses, the price to be paid is immense. On the other hand, keeping a remote environment of education continuing, the students would have a chance to finish the rest of the term, albeit with some attenuations, enabling them to progress into the next levels. However, this abrupt transition is easier said than done, and instructors, as well as students, had to adapt to a development almost overnight. Through the course of an undergraduate engineering degree, students typically take anywhere between six to eight courses in an academic year. While the courses are nearly the same across the disciplines in the first year of education, the students would take more specialized courses in the upper years. Two such courses that the students at © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 307–314, 2021. https://doi.org/10.1007/978-3-030-67209-6_33

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the W Booth School of Engineering Practice and Technology at McMaster University take and that are pertinent to this work include a second-year undergraduate course in Mathematics, and a first-year undergraduate course in Object Oriented Programming. In this work, we present the details of the transition and operations that we employed in these two courses. In both courses, we transformed the in-person classes to a synchronous online format. In particular, the last three weeks of the content in either course were taught in an online setting. The topics covered in these three weeks are critical because they are advanced concepts that are relevant to the subsequent courses in the upper years. Further, the students' understanding of these topics is evaluated only during the final exam. While there are numerous pedagogical techniques such as active learning [1–6], cooperative and small group learning [7, 8], undergraduate research-based learning [9], inquiry-based learning [10, 11], and problem-based learning [12–18], we adopted an active learning setting based on the principles of constructivist learning theory [19, 20] to conduct our courses. Additionally, in this work, we also describe the toolsets that we used to deliver the material and the assessments that were administered. We also share the methodology that we are likely to adopt in the upcoming fall term, where the entire course will be offered through an online medium. In doing so, we identify the challenges associated with online education and propose possible solutions.

2 Materials and Methods The pedagogical transformation was performed for two undergraduate courses. The first course is on the topics related to signals and systems in the second year of an undergraduate engineering program. The second course is in Objected-Oriented Programming (OOP) taught to students entering the third year of an engineering degree program after a three-year college diploma. While the former was originally designed to be offered in person with in-class assessments, the course on OOP was designed to be offered in an online format but with in person assessments. The students enrolling in these courses are eventually majoring in one of the following three disciplines: Automotive Engineering Technology, Automation Engineering Technology, Biotechnology, or Software Engineering Technology. A total of approximately 120 students spread over two cohorts took the course in Mathematics, and approximately 55 students took the course in OOP. 2.1

Course Design - Mathematics.

This course is offered to second-year undergraduate students in Automotive and Vehicle Engineering Technology and Automation Engineering Technology. The main purpose of the course is to provide the foundation to upper-year courses, especially the Control Theory course in the 3rd year of the program. The specific topics covered in the course are (a) Continuous-time signals and systems (b) Convolution (c) Laplace transform (d) Fourier series and transform and (e) Discrete-time signals and systems. In the original plan at the beginning of the term, the entire contents of the course were to be delivered in face-to-face class settings over a duration of 13 weeks. Two

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classes per week were scheduled, each for a duration of two hours, where students interact with the instructor. Various assessment components have been included in the course to access the student's understanding of the course. These components include weekly assignments, two tests, and a comprehensive final exam. 2.2

Course Design – Object Oriented Programming

The principles of foundational programming concepts, as well as OOP were taught over a period of 13 weeks. The specific topics covered in the course included the following: (a) introduction to programming logic, (b) variables and arithmetic operations, (c) control structures, (d) file input/output (e) strings (f) classes (g) inheritance, and (h) polymorphism. Since python was the chosen programming language for this course, additional topics that were covered included lists, tuples, sets, and dictionaries. As mentioned earlier, the entire course was offered in an online format as part of the Software Engineering Technology degree. The class met once a week for 3 h in an online setting. However, two assessments, namely, the midterm and the final exam, were initially planned to be administered in-person. Due to the closure of the university, the final exam had to be changed into an online format. 2.3

Online Operation – Mathematics

The course was originally designed to be delivered in a face-to-face setting. However, all in-person classes were suspended in the 9th week of the semester until further notice. We resumed our classes online after a delay of one week. We followed the same class schedule, but the lectures were delivered virtually via zoom. During these sessions, we attempted to simulate the in-person learning environment to the best of our abilities. Lecture notes in a pdf document were provided ahead of the class. These notes include definitions, relevant explanation of the topic, some solved examples as well as unsolved problems. Thus, while screen-sharing the file during the live lectures, the students were able to follow and relate to all the annotations that the instructor was making. At the end of the lecture, the examples solved in online sessions were also shared with the students via the online course management platform. While it serves as a good review for the students who attended the class, it also helps those students who were unable to attend the lecture access the classroom material. In creating an active learning environment, numerous questions were posed to the students during these sessions. Further, unlike the regular in-class sessions, the intensity and frequency of such interactions were deliberated increased by the instructor. 2.4

Online Operation – Object Oriented Programming.

In this course, the lecture topics were introduced via PowerPoint slides that were shared with the students before the beginning of the class. The typical lecture would include an introduction to the theoretical principles/concepts, followed by some sample programming examples. The programming examples were coded via python. Live coding was an integral part of lecturing to enable students to gain hands-on experience with programming, demonstrate the errors and the debugging techniques, show the

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implementation options for the desired execution of the program. For the live coding examples, the questions were available during the lecture on the PowerPoint slides, and the instructor would demonstrate the implementation using python. In general, for each concept, depending upon the complexity of the topic, numerous examples were introduced inside the class, ranging from a simple program to a fairly complex program. After demonstrating a couple of programs for the students, practice questions were posted for the students to code. Thus, a typical three-hour lecture will introduce about 8–10 example programs, and give students an opportunity to develop their own programs with about 3–5 additional questions. This live coding with examples and debugging exercises enable a healthy exchange of ideas and solutions among the students.

3 Assessments 3.1

Mathematics

The course contains various assessment strategies, formal and informal, to access the learning and understanding of the students. There is no grade associated with informal assessment, while formal assessments are graded. The graded assessments include weekly assignments, two tests, and a comprehensive final exam. Each assignment is based on the topic covered in the corresponding week. They are allowed to collaborate with their peers and seek help from the instructor and the teaching assistant. The assessment after each topic helps the instructor gauge the level of understanding of the students and act accordingly. If needed, the instructor gets a chance to review the concept in the next class. The two tests are conducted in the 5th and 10th weeks of the term to measure students' understanding. The 1st test contains the topics covered in the first four weeks of the term, and the 2nd test includes the material covered in weeks 5 through 9. The final exam is comprehensive and scheduled by the Registrar's office. We were able to conduct only one test before the university suspended all in-person activities. As a result, the second term test and the final exam were administered online. It was not possible to offer these assessments as a closed book format and therefore students were allowed to access all resources. To minimize the collaboration during the test and the exam, we did the following: A question bank consisting of three pools was created for the 2nd test. Each pool had four different questions from a specific topic but at the same level of difficulty. During the test, each student receives three random questions, one from each pool. They were given one and a half hours to write their solutions on paper. An additional 15 min were assigned to take pictures of the answers, compile a pdf document, and upload it in a dropbox. The dropbox was set with time restrictions so that no one would be able to upload the file after the time expires. The final exam followed the same procedure except that we created four question pools with three questions in each pool.

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Object Oriented Programming

A variety of assessments have been pursued in this course to determine and evaluate the students' understanding. These include formal as well as informal approaches. The informal assessments were for the instructor to understand the overall level of comfort of the students with the topics, and for the students to gauge their depth of understanding for each topic. There was no grade associated with this form of assessment. Students participated actively in these classroom discussions. While a vast majority shared their solutions, those who had difficulty solving the problems engaged in discussions with the instructor and peers to understand the answers. Three types of formal assessments were included in the course, namely, quizzes, exams, and a project. The quizzes were administered through the university's online course management platform once every two weeks and would contain multiple-choice and true-false type questions. The quiz is supposed to be taken by an individual without any collaboration. We prevented collaborations by creating a question bank, and for each student, the quiz populated with a random set of questions from this database. Further, all the students had to appear for the quiz at a specific interval of time. This was usually at the end of the class. Thus, with a timed quiz containing random questions, we expect the collaboration to be minimal. The mid-term exam was a paper-based exam, and students appeared for the exam in person. The exam had a combination of multiple-choice, short answer, debugging as well as programming questions. For this in-person exam, students did not have access to notes or computers. The same set of questions were given to every student. With the shut down of university due to COVID-19, we could no longer hold an in-person final exam. As a result, a new format was devised for the final exam. In this format, the students had to appear for an individual exam in which each student was given a set of 5 questions from a random pool of 15 questions. All questions required students to write a program or alter a given program. With stringent time limitation, simultaneous examination duration, and randomization of the questions, the collaboration was mitigated. Another assessment that the students underwent was the development of a substantial project that incorporates the principles of OOP. With this cohort, the students were given an option of one of the following two projects: the development of comprehensive tax software or the development of a robotic vacuum cleaner that cleans a room. The submission was individual, and each student developed their own program.

4 Discussion Pedagogical Approach. In both courses, we imbibed a constructivist approach to learning to introduce the concepts [19–21]. Specifically, the classroom environment in the online setting was transformed into a session with discussions and debates. Here, after introducing a concept, problems were posed that were solved by the students via active participation. The rich discussions allow for a variety of experiences for the students that result in a strong mental construction of the concepts. We believe that

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with exposure to a variety of experiences in such an active learning environment, cognition is initiated by fitting new information together with the already known facts. In our opinion, the informal assessments are more effective in engaging students in online classes. We found that by not associating every assessment with grades, and engaging in informal assessment via sample questions inside the classroom, the anxiety to perform was taken away, and students focused all their energy on learning. Thus, a student who did not understand the concept was more interested in learning how to solve the problem as opposed to getting the right answer. Similarly, when there were a variety of solutions, students engaged in discussion showcasing their viewpoint, trying to learn the alternative approaches to solving the problem. All these foster a good mental construction of the concepts, and students begin to understand the nuances of the subject. Assessment Challenges. The assessments that were outside the class was largely based on an element of trust. The informal assessments inside the classroom give us a measure of the preparedness and learning of the cohort. With formal assessments that are devoid of any form of proctoring, there is always a scope for collaboration. We made an attempt to avoid any kind of peer collaboration with random question sets for assessments and introducing a short window for testing. Subsequent evaluation of the tests submitted by the students did not show any glaring evidence of collaboration. Therefore, at this time, we present random sets administered in a short window of time as the most optimal way to assess students. The other options that are currently under consideration for the online classes in the Fall term include the following: (i) Enlisting the services of a proctoring company that will use video conferencing as a tool to ensure the integrity of an assessment. (ii) Conduct personal interviews of students via video conferencing to evaluate their comprehension of the topics. However, there are several challenges with an interviewbased examination, such as the inefficiency of the process for large classes, recording requirements to re-evaluate a student appeal, etc. Technical Challenges. There is an investment in technology that is needed to deliver online classes. This could be in the form of tablets, cameras, microphones, headsets, etc. Additional requirements could include the need for recording services, closed captioning, etc. Thus, there is potentially a large financial commitment to set up the infrastructure. In some situations, we might need to set up recording stations on campus that could be shared by faculty members to develop content for online delivery of the lectures. This adds to the cost of infrastructure. Loss of internet connection during a lecture or poor connectivity can result in an ineffective learning environment for the student. Pre-recording key examples and making them available as supplementary material, and providing lecture notes prior to the class can help with the quality of the course. Additionally, making the recording of lectures available to the students for review outside the class is beneficial. However, providing recordings of the lecture could result in poor attendance. This can be marginally addressed by introducing quizzes during the lectures.

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5 Conclusion In this work, we present the approach that we took to transform and offer two courses in an online format in the last three weeks of the Winter 2020 term, in the wake of the pandemic. The two courses were a second-year undergraduate engineering math course and a third-year programming course in OOP in the Bachelor of Technology programs in the W Booth School of Engineering Practice and Technology at McMaster University. For content delivery, the zoom platform was used, and the content itself was a combination of PowerPoint slides with annotations. Additionally, a programming platform was used for the OOP course. While the transition was not that challenging, assessments had to be changed. In person assessments were transformed, and timed tests with random questions appearing from a question pool were administered via the online course management platform. Students had to submit the scanned version of the answers written on paper to an online dropbox. In summary, challenges in simultaneously offering numerous courses across a university are immense: (i) There would be a need to invest in technology-related infrastructure to create material for online content, deliver it, and perhaps record it with closed captioning. (ii) Assessments might need to hire services of a proctoring company to conduct tests without any collaboration. (iii) There would be a need to ensure that the quality of the learning environment is not lost with issues such as disruption of classes due to internet issues, or diminished active learning components.

References 1. Beichner, R.: The student-centered activities for large enrollment undergraduate programs (SCALE-UP) project. Res. Based Reform Univ. Phys. 1(1), 2–39 (2007) 2. Burrowes, P.A.: A student-centered approach to teaching general biology that really works: lord’s constructivist model put to a test. Am. Biol. Teach. 65, 491–502 (2003) 3. Srinivasan S., Centea D.: An active learning strategy for programming courses. In: Auer M., Tsiatsos, T. (eds.) Mobile Technologies and Applications for the Internet of Things. IMCL 2018. Advances in Intelligent Systems and Computing, vol. 909, pp. 327–336 (2019) 4. Cummings, K., Marx, J., Ronald, T., Dennis, K.: Evaluating innovation in studio physics. Am. J. Phys. 67, S38–S44 (1999) 5. Sidhu, G., Srinivasan, S.: An intervention-based active-learning strategy to enhance student performance in mathematics. Int. J. Pedagog. Teach. Educ. 2, 277–288 (2018) 6. Srinivasan, S., Centea, D.: Applicability of principles of cognitive science in active learning pedagogies. In: Proceedings of the 13th International Workshop Active Learning in Engineering. (1ed.) Aalborg Universitetsforlag, pp. 99–104 (2015) 7. Wage, K.E., Buck, J.R., Wright, C.H.G., Welch, T.B.: The signals and systems concept inventory. IEEE Trans. Educ. 48, 448–461 (2005) 8. Prince, M.: Does active learning work? a review of the research. J. Eng. Educ. 93, 223–231 (2004) 9. Srinivasan, S., Rajabzadeh, A.R., Centea, D.: A project-centric learning strategy in biotechnology. In: Auer, M., Hortsch, H., Sethakul, P. (eds.) The Impact of the 4th Industrial Revolution on Engineering Education, ICL 2019, Advances in Intelligent Systems and Computing, vol. 1134, pp. 830–838. Springer, Cham (2020)

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10. Farrell, J.J., Moog, R.S., Spencer, J.N.: A Guided-inquiry general chemistry course. J. Chem. Educ. 76, 570 (1999) 11. Lewis, S.E., Lewis, J.E.: Departing from lectures: an evaluation of a peer-led guided inquiry alternative. J. Chem. Educ. 82, 135 (2005) 12. Capon, N., Kuhn, D.: What’s so good about problem-based learning? Cogn. Instr. 22, 61–79 (2004) 13. Kolb, D.A.: Experiential Learning: Experience as the Source of Learning and Development, 2nd ed., Pearson Education Inc. New Jersey (2015). 14. Centea, D., Srinivasan, S.: Enhancing student learning through problem based learning. In: Guerra, A., Rodriguez, F.J., Kolmos, A., Reyes, I.P. (eds.) PBL, Social Progress and Sustainability, Aalborg: Aalborg Universitetsforlag. (International Research Symposium on PBL), pp. 376–385 (2017) 15. Dochy, F., Segers, M., Van den Bossche, P., Gijbels, D.: Effects of problem-based learning: a meta-analysis. Learn. Instr. 13, 533–568 (2003) 16. Centea, D., Srinivasan, S.: Assessment methodology in a PBL environment. Int. J. Innov. Res. Educ. Sci. 6(6), 364–372 (2016) 17. Sidhu, G., Srinivasan, S., Centea, D.: Implementation of a problem based learning environment for first year engineering mathematics. In: Guerra, A., Rodriguez, F.J., Kolmos, A., Reyes, I.P. (eds.) PBL, Social Progress and Sustainability, Aalborg: Aalborg Universitetsforlag. (International Research Symposium on PBL), pp. 201–208 (2017) 18. Muhammad, N., Srinivasan, S.: A problem solving based approach to learn engineering mathematics. In: Auer, M., Hortsch, H., Sethakul, P. (eds.) The Impact of the 4th Industrial Revolution on Engineering Education. ICL 2019. Advances in Intelligent Systems and Computing, vol. 1134, pp. 839–848 (2020) 19. Olusegun, B.S.: Constructivism learning theory: a paradigm for teaching and learning. ISOR J. Res. Method Educ. 5(6), 66–70 (2015) 20. Tam, M.: Constructivism, instructional design, and technology: implications for transforming distance learning. Educ. Technol. Soc. 3(2), 50–60 (2000) 21. Srinivasan, S., Muhammad, N.: Implementation of a course in computational modeling of biological systems in an undergraduate engineering program. Int. J. Eng. Educ. 36(3), 857– 864 (2020)

Providing On-Demand Feedback for Improved Learning of Logical Reasoning in Computer Science and Software Engineering Wolfram Kahl(B) McMaster University, Hamilton, ON L8S 4K1, Canada [email protected] http://www.cas.mcmaster.ca/∼kahl/ Abstract. For teaching introductory courses on logics and discrete mathematics for computer science students, there have been several attempts to use support by existing established “professional” proof assistants. In contrast, we have developed a proof checker the feature set of which is motivated by the educational application. Students access our system via a web-app, which they use to write proofs in the rigorous but mostly-conventional mathematical language of the textbook, and obtain fine-grained on-demand feedback on the correctness of their proof attempts. Keywords: Proof checker science education

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· Theorem proving components in computer

Introduction

An introductory logics and discrete mathematics course prepares students of Computer Science and of Software Engineering for later courses, where they will need to be able to read and write logical formulae in the context of software specifications, including loop and class invariants. They will also need to have experience proving theorems of propositional and predicate logic, for example for the purpose of proving equivalence of different formulations of the same invariant, and for proving (or at least solidly arguing) correctness of programs. In short, they need fluency in applied logic, and acquiring this is similar to acquiring foreign language skills: Practice is essential for developing competence and confidence. However, in the context of large university classes, opportunities for feedback in lectures and tutorials are limited, and in traditional pen-and-paper mathematics classes with large class sizes, feedback on assignments typically becomes available only week(s) after the student worked on them. After adopting as textbook the classic “A Logical Approach to Discrete Math” (LADM) of Gries and Schneider (1993) which focusses on a rigorous proof style as vehicle to familiarise students with using logics as a tool in the context of discrete mathematics, a frequent question from students was: “How do I know whether my proofs are good?” Although the direct answer to that c The Author(s), under exclusive license to Springer Nature Switzerland AG 2021  M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 315–326, 2021. https://doi.org/10.1007/978-3-030-67209-6_34

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would be “you check carefully whether you applied the rules correctly in each step”, the precision required for that is exactly one of the central learning objectives of the course. However, since the rigorous proof style of the textbook very closely approaches fully formal proof (in a presentation optimised for human readability), answering the students’ question is within reach of mechanisation. Through development of a custom proof checker for the proof style of the course textbook, and making this proof checker accessible via a web application, students now can ask that proof checker whether their proofs are good, at any time of the day, and as often as they like. Students access this proof checker in their web browser, where it presents a “notebook” interface somewhat similar to that of Project Jupyter1 . Each notebook is presented as a document with interspersed vertically-split “code cells”. In the left part of these code cells, theory content (in particular theorems with proofs) is entered, and, upon request, server-generated feedback is displayed to the right, as shown in Fig. 1.

Fig. 1. Proof checker interaction in web browser: Plain-text entry to the left, automatically-generated feedback to the right 1

https://jupyter.org.

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Arriving at this net-based learning system for LADM-based courses required the development of three distinct components: 1. The “CALCCHECK language” is essentially a recognisable formalisation of the calculational proof language of LADM and the underlying calculational logic of Gries (1997). It includes also syntax for structured proofs which LADM only introduces briefly (in Sect. 4) and hardly ever actually uses in later chapters. 2. The CALCCHECK proof checker processes “theories” written in the CALCCHECK language and provides detailed feedback in the shape of annotated versions of the provided proof attempts. Many aspects of the proof checking and of the feedback generation are configurable; there is also a mode for automated grading. The CALCCHECK proof checker provides individual feedback for each proof step, and certain summary information for subproofs. 3. The web application CALCCHECKWeb provides an on-line interface for interacting with notebooks that have been set up with particular theory and proof checking configurations. This is used not only for ungraded exercises, but also for graded assignments and exams; the screenshot in Fig. 1 is what a student will have seen during a second midterm exam (after possibly having overlooked the hint about “A straight-forward equivalence calculation” at the top of the picture, and attempted a proof by mutual implication instead. . . ). The current paper discusses the design choices that make this net-based proof checker a useful learning tool for students in a first logics and discrete mathematics course in computer science and/or software engineering. We briefly discuss the formalisation of the proof language of the textbook in Sect. 2. We then explain the role of the net-based learning tool in the course context in Sect. 3, and summarise the features of the web interface in Sect. 4. Some features of the server-side checking mechanisms are explained in Sect. 5. The principles used for automated grading are presented in Sect. 6.

2

Brief Notes on the CALCCHECK Language

Previous publications (Kahl 2018a; 2018b; 2020) contain more detailed explanations of the theory and proof languages of CALCCHECK. Here we only give a quick impression, concentrating on the closeness of the formal CALCCHECK language to the rigorous but informal language of LADM. A key requirement for the CALCCHECK language is that it should recognisably “be” the language of LADM. Some small liberties have been taken; perhaps the most striking is that for the sake of reducing potential ambiguity, theorem names are always delimited by “pretty” double quotes in CALCCHECK, and almost all lexemes need to be separated by spaces. Apart from such minor changes, it is easy to make calculations in CALCCHECK look almost the same as in LADM. For example, LADM p. 198 shows (up to only minor typographical differences):

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(11.5) S = {x x ∈ S : x} . According to axiom Extensionality (11.4), it suffices to prove that x ∈ S : x }, for arbitrary v . We have, v ∈ S ≡ v ∈ {x x ∈ S : x} v ∈ {x  Definition of membership (11.3)  (∃x x ∈ S : v = x) =  Trading (9.19), twice  (∃x x = v : x ∈ S) =  One-point rule (8.14)  v ∈S

=

The last seven lines of this are called a “calculation”: The delimiters “. . .” are called hint brackets and enclose a hint that is expected to provide justification for the statement resulting from the application of the associated calculation operator (here always “=”) to the two surrounding expressions. In CALCCHECK, where some theorem names have been changed (mostly for the sake of disambiguation for human readers and writers), the following can be entered:

The most notable difference is that in the CALCCHECK version, the outer proof structure which LADM expresses in prose has been formalised into the explicit “Using” and “For any” structures. (A minor difference is that for the concrete syntax of quantifications and set comprehensions, CALCCHECK follows the lead of the Z notation (Spivey 1989) and uses “ • ” where LADM uses a colon to introduce the body expression.) A CALCCHECK module is a “literate theory document” (in the sense of literate programming) consisting of a sequence of “top-level items” (TLIs) and document fragments (encoded in Pandoc’s MarkDown). The CALCCHECK language is layoutsensitive; most substructures have to be indented at least two spaces beyond the start of their parent structure; calculation operators have to be aligned, and calculation expressions need to be indented at least two spaces further. The CALCCHECK language differs from LADM “only as much as needed”; the fact that proof structures like those above have a formally defined syntax that mixes well with the calculational style has the advantage that structured proofs become much more natural and straight-forward to produce. Even though

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LADM advocates formalised proof, in cases of comparable complexity it still frequently reverts to conventional mathematical prose for the proof structures, as for example for (11.5) as shown above—we believe that having mechanised support such as that provided by CALCCHECK can be a real game changer in terms of getting students used to producing rigorous proofs.

3

The Role of the Net-Based Learning Environment

Providing a proof checker over a proof assistant was chosen since proof assistants are designed to increase the productivity of users who already know what a proof is, who have experience in finding proofs, and have a large vocabulary of proof strategies, while students in a first course on logic and discrete mathematics need to learn all that. What our proof checker does provide is feedback on the correctness of individual proof steps, for proofs entered in a language that is clearly recognisable as the language of the textbook LADM (with minor alterations to make it fully formal). LADM takes a proof-centered approach to discrete mathematics, and mastery of proof development in the style of the textbook is also the declared goal of the course: We tell students from the beginning of the course that they need to be able to do the proofs not only on the system, but also with pen on paper, in particular in case the network or other infrastructure fails during an exam. While the course so far has been delivered in a standard lecture-centered manner, with occasional demonstration in class of interaction with the proof checker and of ways to deal with new concepts, the main use of our tool is for student learning: Every week, the following notebooks are made available: – Exercise notebooks, parts of which are discussed in small-group tutorials, where most students bring their laptop computers and therefore can work with the system during the tutorial. – Assignment notebooks (two or three almost every week) that take up the topics from the exercise notebooks. – Since 2018, after about every second lecture, a homework notebook (or two) is posted, due before the next lecture, or after two days. Doing this has become feasible due to the fact that our system includes a useful autograder that assigns part marks in a way that students accept as sufficiently fair. Exams are also conducted on the system, so far invigilated in computer labs; the first midterm exam is conducted with proof checking disabled and only syntax checking enabled; later midterms and the final exam are now conducted with proof checking enabled.

4

The CALCCHECKWeb Interface

Students access CALCCHECK exclusively via the CALCCHECKWeb web-app, which presents a “notebook”-style interface where the formal content is presented in

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paired boxes as visible in Fig. 1. The left box is a text input area that should contain one or more “top-level items” (TLIs) in the CALCCHECK language, which is intentionally restricted to Unicode plain text, without any additional markup, and therefore no two-dimensional features (such as exponents or limits) beyond the layout sensitivity mentioned above. Symbols are input via escape sequences starting with backslash (frequently the corresponding LATEX macros are one alternative), with menu and completion support. The right box is initially empty; typing Ctrl-Alt-Enter in the left box (or a menu action) sends the content of the left box together with all preceding code boxes to the server for checking, and then populates the corresponding right boxes with the feedback returned by the server. Authoring a notebook for use by students involves producing a CALCCHECK module that has contains a “Prefix end” marker delimiting the setup part from the part visible to the students. The latter cannot contain any import declaration, nor any grading configuration. At the “Prefix end”, suffix settings can be added, which influence functionality of the notebook interface the students use, including: – The limit of the number of items in a single hint—this is usually set to 1 in the first month, and later to 4, which seems to be a reasonable value for avoiding “spaghetti hints” while still allowing larger steps. – Availability of hint language features such as Evaluation or Monotonicity. – Whether proof checking is disabled—with this setting, when students trigger proof checking, only syntax checking is performed. In recent years, at least the first midterm exam has always been written with proof checking disabled, but syntax checking still enabled. To practice this (or to obtain faster feedback), students can always use Ctrl-Enter to request only syntax checking. – Information reporting: In the feedback box in Fig. 1, there are two report lines below the theorem statement: The first documents that CALCCHECK recognized variable S as a metavariable inside which none of the bound variables of the theorem statement can occur; the second presents the same information in the shape of a ¬occurs “proviso” as LADM states them for (most) theorems involving metavariables—CALCCHECK derives these provisos automatically, but students need to be aware of them when applying such theorems. The display of these two lines can be enabled and disabled separately. Similarly, display of the inferred types of the theorem variables can be enabled. In addition the system also detects cycles in calculations, and “trivial calculations” that (attempt to) prove goals of shapes such as “P ⇒ true” in more than one step—these frequently arise from working with implications “in the wrong direction”. Reporting these can be enabled; this is normally disabled while students are working on notebooks, and enabled in the autograder.

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Any import declarations (or direct theory content) before “Prefix end” make operator declarations and theorems available for use in the suffix. For convenience, and for reducing the danger of typos, CALCCHECKWeb offers theorem name completion: After an opening double quote (which can be plain) followed by at least three characters, the TAB key activates theorem name completion, again supported by a menu (and automatically fixing the opening double quote). Theorem name completion offers only the theorems brought in by the prefix, and those stated in the suffix in preceding code boxes. Some further special-purpose editing support is available, for example for block (un-)indentation. However, menu-driven syntax refinement, for example, is intentionally not provided, to ensure mastery of the proof formats: This is explained to the students by stressing that they need to be able to write proofs in exams also using pen and paper, in particular in case the computing or network infrastructure breaks down during or before the exam.

5

Parser and Proof Checker

Parse errors have the potential to invalidate a whole cell, which, for graded material, could mean that significant opportunities for part marks could be lost due to what may be considered a tiny error. Fortunately, the layout rules of the CALCCHECK language frequently make it possible to resume parsing after the current block ends; for this reason, the internal proof representation includes error nodes that replace the construct that failed to parse and save the parse error message for inclusion in the feedback. This includes hints and calculation expressions, which are frequently left unfinished when their calculation is abandoned in the hectic of an exam. Deactivated features and hints with too many items are still parsed, but are annotated with error messages even if proof checking is disabled. Students need to be trained to actually read the parse error messages— LADM assigns ∧ and ∨ the same precedence, so that in mixed expressions, parentheses are always needed; if such parentheses are missing, the parse error message points this out explicitly. In the internal proof representation, proof structures and calculation steps all have space for accommodating “reports” that will ultimately make up the feedback; in addition they also carry a “conjecture status” which records, for locally correct proof (steps), which theorems they use directly. This information is used to report when a locally-correct proof depends on not-yet-proven earlier theorems. Proof checking starts with type-checking the expressions involved in the proof; type errors contribute reports (there is one of these in Fig. 1) and set the conjecture status to “unproven”. Proof goals that involve type-incorrect expressions are not attempted by the proof checker—this gives rise to the “Unknown goal” message that can also be seen in Fig. 1.

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The central component of the proof checker attempts to confirm that a goal is justified by a hint, and for the most general mechanism for doing this, CALCCHECK translates the goal into a set of equivalent equations, translates the hint into a set of equational term rewriting functions, and applies these breadth-first to both sides of the goal equations until a common reduct is found, or either the search space or the maximum depth or the time-out are exhausted. For this term rewriting, expressions are converted into an internal term representation that uses special data structures for operators with activated associativity and/or commutativity properties, using an adaptation of the AC-matching algorithm of Contejean (2004). Activated transitivity rules as well as registration for equality and equivalence operators are used to check whether a calculation justifies its goal, and to derive the result “goal” from a calculation that has no goal imposed on it from the outside, such as the calculation inside the “Assuming” subproof in Fig. 1.

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The Autograder

If enabled, registered users can save (“submit”) CALCCHECKWeb notebooks to the server. Automated grading of CALCCHECKWeb notebook submissions refers to a reference solution that defines which theorems were expected to be proven. If in the sequence of expected proofs, the proof of an earlier theorem is not completed, later proofs are still allowed to use that theorem without penalty. However, if students add lemmas without providing a complete proof, the theorems using these lemmas cannot obtain full marks. Occasionally, students postulate additional axioms that make the expected proofs much easier; the CALCCHECK autograder rejects these as “unwarranted additional axiom”. The basis for analysing these issues is the conjecture status information mentioned in Sect. 5. For each theorem, the size of the proof in the reference solution determines the maximum number of marks available, and this can be reached only via a correct proof. Incomplete proofs potentially earn marks with locally correct steps, and are penalised for unjustified or invalid steps. Cycles, unless needed for example for proving equivalences via a cyclic implication chain, do not earn any positive marks, and the “trivial calculations” mentioned in Sect. 4 earn at most one. The reference solution is a CALCCHECK module that may contain additional grading configuration attached to individual theorems, including listing forbidden or expected theorems for use in hints. A special mode is available for “fillin-the-blanks” questions where occurrences of “?1 ” have to be replaced with a single hint item. As the grading system has improved over the recent years, it appears to have become quite rare that students do “busy steps” in the hope of earning marks for essentially doing nothing on questions they cannot solve. The fact that part marks are given (in a probably still somewhat generous way) appears to be key to acceptance of autograding by the students.

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Outcomes of Learning with CALCCHECK

Students tend to appreciate already by the first tutorial that the problem is not interaction with the proof-checking system, but their main problem is finding the proofs. Having the proof checker available makes this drastically clear already before the submission of assignments, while in a pen-and-paper course, students will learn about their mistakes only when the assignment is returned. Strong students tend to take very positively to this; weak students who want to pass the course are effectively forced to learn. All students tend to appreciate the availability of immediate feedback. Especially since the introduction of homework, it is noticeable that by the second midterm, all students have considerable confidence in their ability with syntax and simpler proof steps, and many spend quite long times working on harder proofs without triggering checks by the system. In the four years that the current wep-application has been in use, the grade distribution has been more top-heavy than previously. After the introduction of homework, which succeeds keeping most student active on the course more continuously, the top-heaviness of the grade distribution has become even more pronounced, and this development is also reflected correspondingly in the learning outcomes measurements. Instructors of several third-year courses also noted that the skills the students acquire with our proof checker make a noticable difference in student preparation for their courses.

8

Related Work

Using computer support for teaching logic has quite a long history. For example, Cater and Johnstone jr (1975) report on a language and system called LOGOL implementing decision procedures for validity of propositional logic and monadic predicate logic, and emphasise the usefulness of fault-tolerant parsing that still produces error messages, but increases turn-around and feedback experience in their batch-processing context. We are not aware of any previous tool support for the logic of LADM; the “structured derivations” of Back (2010) are a different approach to calculational proof presentation that shares with CALCCHECK the possibility of nested calculations. Initial tool support for this appears to have been the MathEdit system by Back et al. (2007). There appears to be no active development of tool support for structured derivations. Apart from this, tools targeting proof presentation intended for human consumption tend to concentrate on conventional mathematical prose proofs. For example, Lurch by Carter and Monks (2017) trains the writing of mathematical prose, which can be checked due to markup that is added to the embedded formulae and specifies their rˆ oles in the mathematical development–a residual risk remains that the mark-up does not quite correspond to the meaning of the natural language of the prose, and therefore the formal proof that Lurch

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checks is not necessarily a precise formalisation of the prose proof that a reader of the typeset version reads. The EPGY Theorem Proving Environment (Sommer and Nuckols 2004) “aim[s] to imitate ordinary practice as best possible, while adhering to a level of formalism sufficient for computer-verified proofs.” Proof development proceeds by selecting, from menus, “steps” like “expand definition”, “universally generalize”, “instantiate”, or “strategies” like “By contradiction”, “By cases”, “By Math Induction”. The generated proofs are in a somewhat idiosyncratic format, apparently essentially Hilbert-style proofs rendered in a way that gives some appearance of conventional mathematical prose fragments. Theorema 2 Buchberger et al. (2016) is intended primarily as “a computer assistant for the working mathematician”; for the predecessor system, an educational front-end was developed by Mayrhofer et al. (2007); proving in this system is essentially a dialog-based interaction where the user provides guidance to the Theorema prover, and the resulting proof is then displayed in a human-readable, apparently-informal format. More remotely related are the many tools that target proof development directly in the kind of proof systems typically considered in introductions to the theory of logic (as opposed to the use of logic as a tool, which is the approach taken by LADM). For example, Gasquet et al. (2011) present a graphicallyinteractive tool for construction of natural deduction proofs in inference-tree presentation. The interactive tutoring systems of Lodder, Heeren and Jeuring (Lodder et al. 2016; 2017) build on ITS infrastructure by Heeren and Jeuring (2014) and also appear to present mostly menu-driven interaction for navigating the natural deduction proof space.

9

Conclusion

CALCCHECK has been designed to help students develop skills in calculational proof throughout a one-term course based on textbook classic LADM. This required the design of a proof language that includes and accommodates the calculational presentation format, includes also sufficient proof structuring mechanisms to make it possible to formalise also those proofs for which LADM encodes the top-level structure in prose. The key feature of CALCCHECK is instant feedback on proof correctness, which is delivered via the web-app CALCCHECKWeb . A useful convenience, especially for the large (200 to 300 students) classes we have been teaching recently, is the presence of an autograder that appears to grade quite sensibly. Even without aiming for the interactive guidance of an ITS (intelligent tutoring system), the educational focus for the system has imposed requirements that are quite different from those for a conventional proof assistant the users of which already know what a proof is, and will spend most of their time working with the system after they mastered it. CALCCHECK, however, is designed for student who need to learn what a proof is, and most of the time they work with the system while learning about proof and about the formalised topics of discrete

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mathematics. Nevertheless, by the end of the term, these students are a completely different kind of users than they were at the beginning of the term, and the system has “knobs and dials” to successfully adjust to that. The fact that the language of our proof checker is recognisable as the language of the textbook, the fact that pen-and-paper proof skills are expected at least for the case of system failure in an exam, and the fact that they hear that the learnt skills are used in later courses all help letting students realise that what they learn with CALCCHECK is not a special-purpose system skill, but a general skill that translates into different settings. Altogether, frequent homework and assignments appear to help students achieve significant language acquisition achievement in the language of logic and discrete mathematics. Now that the CALCCHECK system is becoming more feature-complete, systematic studies investigating its influence on student learning are on our agenda. From the student reactions we received so far, students appear to strongly appreciate the immediate feedback, and the increasing challenges as the material progresses over the course of the term.

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Kahl, W.: CALCCHECK: A proof checker for teaching the “Logical Approach to Discrete Math. In: Avigad, J., Mahboubi, A. (eds.) ITP 2018. LNCS, vol. 10895, pp. 324–341. Springer, Cham (2018a). https://doi.org/10.1007/978-3-319-94821-8 19 Kahl, W.: Calculational relation-algebraic proofs in the teaching tool CALCCHECK. In: Desharnais, J., Guttmann, W., Joosten, S. (eds.) RAMiCS 2018. LNCS, vol. 11194, pp. 366–384. Springer, Cham (2018b). https://doi.org/10.1007/978-3-03002149-8 22 Kahl, W.: Calculational relation-algebraic proofs in the teaching tool. J. Logic. Algebr. Methods Program. 1–43 (2020, to appear) Lodder, J., Heeren, B., Jeuring, J.: A domain reasoner for propositional logic. J. Univ. Comput. Sci. 22(8), 1097–1122 (2016). https://doi.org/10.3217/jucs-022-08-1097 Lodder, J., Heeren, B., Jeuring, J.: Generating hints and feedback for Hilbert-style axiomatic proofs. In: Proceedings of 2017 ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2017, New York, NY, USA, pp. 387–392. ACM (2017). https://doi.org/10.1145/3017680.3017736. https://doi-org.libaccess. lib.mcmaster.ca/10.1145/3017680.3017736 Mayrhofer, G., Saminger, S., Windsteiger, W.: CreaComp: Experimental formal mathematics for the classroom. In: Li, S., Wang, D., Zhang, J.-Z. (eds.) Symbolic Computation and Education, Singapore, New Jersey, pp. 94–114 (2007). World Scientific Publishing Co. http://www.worldscibooks.com/socialsci/6642.html Sommer, R., Nuckols, G.: A proof environment for teaching mathematics. J. Autom. Reason. 32, 227–258 (2004) Spivey, J.M.: The Z Notation: A Reference Manual. Prentice Hall International Series in Computer Science. Prentice Hall (1989)

Open Educational Resources for Environmental Education Dana Perniu, Ileana Manciulea, Cristina Salca Rotaru, and Camelia Draghici(&) Transilvania University of Brasov, 500036 Brasov, Romania {d.perniu,c.draghici}@unitbv.ro

Abstract. Although Open Educational Resources (OERs) and Massive Open On-line Courses (MOOCs) are more and more developed and available in European educational systems, there is a lack of MOOCs in the field of toxicology and environmental sciences. Starting from this fact, the “Learning Toxicology through Open Educational Resources – TOX-OER” project was granted and run between 2015 and 2018. Seven European High Education Institutions shared knowledge and skills and created seven toxicology-related OERs. The challenges and the experience gained during development of these OERs, especially the video presentations, supporting texts, additional documentation, and evaluation tests, are presented in the present paper. Our outstanding experience gathered during TOX-OER project, contributed to the decision to extend our initiative to a subsequent project, “Environmental Education – OERs for Rural Citizens” (EnvEdu – OERs). The new project aims to develop new OERs targeting rural citizens’ life-long learning focusing on environmental quality. The lessons learned from the TOX-OER project are presented not only for an effective transfer to the new EnvEdu – OER project, and for an efficient rural community acceptance, but also for other audience facing similar challenges and experience in creating OERs. Keywords: Environmental education open online courses


Open educational resources
Massive

1 Introduction The first publication on Massive Open Online Course (MOOC) (Fini, 2009) announced that in 2008 a new concept emerged in the already crowded e-learning landscape: MOOC. Elite universities started to offer their own MOOCs, video based course, free of charge, credit-less and massively available to learners from all over, so that 2012 was declared The Year of the MOOC (Pappano, 2012). Reviews are available in the literature, pointing out the growing interest in MOOCs, highlighting the large increase in the number of publications on the subject, publications evaluated during 2008–2017 period. Almost half of the studies were firstly presented at conferences, then published in conference proceedings, while the other half were published in journals (Yousef et al., 2014; Zancanaro, 2017; Mahmod et al., 2018; Shettar et al., 2019). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 327–334, 2021. https://doi.org/10.1007/978-3-030-67209-6_35

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Of interest to our study are the publications presenting Open Educational Resources (OERs) and MOOCs developed in Romania, most of them published as conference papers, as well: a set of publications presenting the first initiatives of OERs and MOOCs in Romania (Mihaescu et al., 2014; Holotescu et al., 2014; Holotescu and Pepler, 2014; Vasiu and Andone, 2014; Mihaescu and Vasiu, 2015; Grosseck and Malita, 2015, MOOC for business education (Onete et al., 2014), a parallel presenting MOOCs in Romania and in Bulgaria (Grosseck et al., 2015), health care MOOCs for palliative care and zoonoses, project based developed, with funds from the Erasmus Program (Colibaba et al., 2015; Colibaba et al., 2019), open education initiatives and strategy in Romania (Holotescu and Grosseck, 2018). This is to underline that in 2014 Politehnica University of Timisoara started the development of the first Romanian MOOC, UniCampus, as a Moodle based learning management system (LMS) (Andone et al., 2017). Another direction of MOOCs development, of interest for our study, is the one for environmental education (EnvEdu) as presented in Table 1., most of these MOOCs being developed in Europe. Figure 1A. and B. shows the evolution and distribution of MOOCs development in Europe until 2015. Table 1. Developed MOOCs for environmental education. MOOC title (host university) Greening the Economy: Lessons from Scandinavia (Lund University, Sweden) Environment, computer science and society (Hochschule für Technik und Wirtschaft, Berlin, Germany) Sustainable Energy in Education (University of Helsinki, Finland) Environmental Education: Transdisciplinary Approaches to Addressing Wicked Problems (Cornell University, USA) Marine Litter (University of Madrid, Spain) Environmental Sustainability of Organizations in the Circular Economy (Universidad San Jorge, Zaragoza, Spain)

Ref. Leire et al., 2016 Fuchs-Kittowski, 2017 Kaul et al., 2018 Krasny et al., 2018 Tabuenca et al., 2019 Loste et al., 2020

Fig. 1. Developed MOOCs distribution in Europe: updated on 10.01.2014 (A.); updated on 30.11.2015 (B.); TOX-OER and EnvEdu-OERs contributions to MOOCs in Europe (C.).

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Taking into account this evolution, as well as the lack of toxicology related MOOCs, a partnership of universities from seven EU countries implemented the project Learning Toxicology through Open Educational Resources (TOX-OER) between 2015–2017, having as main target groups the students from higher education institutions (Fig. 1C.). Our outstanding experience gathered developing OERs during the TOX-OER project, as well as the lack of EnvEdu related MOOCs contributed to the extension of our initiatives to a second project, Environmental Education – OERs for Rural Citizens (EnvEdu – OERs). The project aims to develop new environmentally related OERs, enlarging the target groups for adults education (mainly active in rural communities), as lifelong learning opportunity (Fig. 1C.). The goal of this paper is to present part of our experience in creating OERs, based on TOX-OER project and to underline the lessons learned from this project to a better implementation of the OERs developed under the EnvEdu – OER project.

2 Experience in Open Education Resources Development in the Framework of TOX-OER Project The partnership of the TOX-OER project was formed by University of Salamanca (Spain) as coordinator, and six European partners: Space Research and Technology Institute (Bulgaria), Charles University, Prague (Czech Republic), South-Eastern Finland University of Applied Sciences (Finland), University of Bologna (Italy), University of Porto (Portugal), and Transilvania University of Brasov (Romania). Seven OERs (modules – M) were developed, having as main target group the students from diverse study programs: M1: General Concepts; M2: Pharmaco-Toxicokinetics; M3: Principal Groups of Xenobiotics – Prescription Drugs and Drugs of Abuse; M4: Environmental Pollutants; M5: Target Organ Toxicity and Biomarkers; M6: Environmental Toxicology; M7: Patents and Patent Application. The created OERs are available on the TOX-OER MOOC platform (https://toxoer.com/). For each agreed module/ topic, and for each ECTS (28 conventional hours), the OERs authors produced a series of courses contents: video presentations, supporting text contents and additional readings (papers, book chapters), tests for self-evaluation and final tests. As a novelty of TOX-OER MOOC, it was agreed that all the videos, texts and tests will be produced in English and then translated in all seven native languages of the seven partners (Bulgarian, Czech, Finish, Italian, Portuguese, Romanian and Spanish), being thus available in eight languages (Manciulea et al., 2019). Our team, from Transilvania University of Brasov (UNITBV) was only involved in OERs production, and not in the MOOC development. Therefore, the actual communication will only focus on presenting the students perception on OERs created for the pollutants related topics, parts of M4, developed by the group from UNITBV: 4.1 Environmental Pollutants – Gaseous Pollutants (1 ECTS); and 4.3 Environmental Pollutants – Persistent Organic Pollutants (1 ECTS). For this purpose, we lunched a survey on Google Forms, for our actual and former students from the Environmental Engineering bachelor and master programs. The survey comprises questions related to:

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– general information about the students and their actual online courses experience; – the TOX-OER topics 4.1 and 4.3; – final comments and recommendations. The survey was completed by 50 respondents, as follows: bachelor students (29), master students (9), bachelor degree graduates (9), and master degree graduates (3). From the cohort of respondents, 88% of the students declared their openness towards online courses, but their experience until now is only based on the courses on the elearning platform of the university and/or of the TOX-OER platform. The OERs for topic 4.1 (Gaseous Pollutants) was taken by 64% of the students and 80% took the topic 4.3 Persistent Organic Pollutants. Most of them took the Romanian version, but 20% also followed the English version of the OERs. Two sets of questions were organized in order to verify the perception of the students on the OERs: (i) their interest to the OERs contents, videos, texts, additional documents, tests (Fig. 2A.), (ii) and the perceived usefulness of the OERs (Fig. 2B.).

Fig. 2. Survey results after following the OERs for Module 4, topics 4.1 (Gaseous Pollutants) and 4.3 (Persistent Organic Pollutants): set of questions (1–5) related to the type of OERs followed by the students (A); set of questions (1–8) related to the perception of the students on the quality and usefulness of the OERs (B); legends for the two sets of questions/answers, see text.

The sets of answers to the questions related to the TOX-OER topics 4.1 and 4.3 are summarized in Fig. 2, where the following legends were used: a. for questions A.: 1 – followed the video presentations; 2 – followed the supporting texts; 3 – followed additional documentation; 4 – solved the intermediary tests (selfevaluation); 5 – solved the final test (evaluation); b. for questions B.: 1 – the scientific content of the OERs was accessible; 2 – OERs contributed to acquiring knowledge about pollutants as xenobiotics; 3 – the information was well structured; 4 – the course presentation was attractive; 5 – the video presentation was useful to understand the course content; 6 – the supporting texts were useful to better understand the subject; 7 – the self-evaluation tests helped with

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fixing the information; 8 – the final test was easy after following all the OERs materials and the self-evaluation tests; c. for answers B., on a scale from V-I: V – very high level, IV – high level, III – moderate level, II – very low level, I – low level. Most of the students followed the video presentations (85%) and the supporting texts (78%); only 48–50 also followed additional documentation. This shows either that the available video and related texts are of high quality and well-structured for an adequate acquisition of new knowledge, or the low interest of the students for complementary information. For the evaluation, most of them solved the intermediary tests, 85% for topic 4.1, respectively 90% for topic 4.3, before the final tests (Fig. 2A.). The students’ appreciation on topics 4.1 and 4.3 revealed that the great majority of them evaluated the usefulness of the OERs with “very high level” (V on scale) and “high level” (IV on scale), in terms of accessibility, scientific content, attractiveness and efficiency, as shown in Fig. 2B. The “very low level” (II on scale) and “low level” (I on scale) answers were not selected. The survey results about the students’ perception on the OERs quality and usefulness are valuable feedbacks, and will be of great help to the developing team in their future activity to improve the OERs or create new ones, by providing contents that suit their students’ needs (as also mentioned by Aharony and Bar-Ilan, 2016). No relevant final comments were registered, except general appreciations on the OERs quality and usefulness. As recommendations, for the question “Which are your recommendations for future development of new OERs in the domain of environmental protection” we selected individual answers, considered to be relevant for our future intentions to produce more OERs: a. OERs on the chemical and technical (best available practices – BAT) background needed for better understanding of the anthropogenic pollution phenomenon; b. OERs on sustainable development and on strategies and techniques for the pollutants impact reduction; c. OERs on the socio-economic aspects of the environmental protection; d. OERs on how to write a project for companies or local authorities to receive financial support from different sources, envisaging environmental related activities; e. OERs on the transposition of the EU environmental legislation to the EU member states, for a better understanding of the mechanism of environmental legislation dynamic development, and consequently, its transposition; f. the OERs should be correlated and completed with the adequate environmental regulations, case studies, and good practice examples in our country as well as in other countries.

3 OERs for Environmental Education There were two particular findings that determined us to propose a new project to be granted, aiming to develop new OERs for environmental education:

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1. the requests formulated by the local authorities from rural area about their needs on environmental education (general aspects, legislation on waste management, writing projects to receive financial support to improve the environmental quality in their community); 2. our perception about the fact that citizens are not aware about the pollutants effects on their life and the environmental related consequences; this lack is mostly correlated with their legal access to the public debates with different occasions, like an environmental impact assessment report (EIA) presentation, but not being educated for such actions/ decisions. Starting with the limited MOOCs available on environmental education (Table 1), with the identified needs for new OERs subjects, and also based on the previous TOXOER experience, EnvEdu – OERs project was proposed, is already selected to be granted, and started in November 2020. The novelties of this project are: – we enlarged the group of specialists in EnvEdu, a new consortium of High Education Institutions (HEIs), with Transilvania University of Brasov (UNITBV, Romania) as coordinator, and three more HEIs: Reykjavik University (RU, Iceland), Bucharest University of Economic Studies (BUES, Romania) and Gheorghe Asachi Technical University of Iasi (TUIASI, Romania), as also presented in Fig. 1C.); – we will develop a new MOOC, on the university Moodle platform, as Moodle is one of the most popular learning management system (LMS) available today, also implemented at UNITBV level; – we will develop new OERs for continuous training in EnvEdu, enlarging the target group to rural citizens, and non-academics; by this, we will also answer to the need of opening the MOOCs and OERs to socio-economically disadvantaged learners. The new OERs (course modules – M) proposed to be produced during this project, as well as the HEIs responsible for their development, are: – – – – – –

M1. M2. M3. M4. M5. M6.

Sustainable Communities and Social Communication (UNITBV); Environment Quality (UNITBV); Environmental Management, Impact and Risk Assessment (TUIASI); Waste Management in Rural Communities (TUIASI); Water Resources and Water Balance for Sustainable Community (RU); Environmental Projects Management (BUES).

The development of the OERs in eight languages, in the framework of the TOXOER project, seemed to be beneficial for the initial target groups, our students, from universities in different EU member states. In time, we can appreciate that this turned out to be a disadvantage, because any revision or amendment of the OERs will involve, once again, that all the project groups, will translate any OER content modifications (video, texts, and tests) in their native language. This was one of the lessons learned from the previous project, and one of the reasons why the EnvEdu – OERs will only be developed in two languages: Romanian, being useful for the majority of the future learners, and English, Icelandic language not being compulsory, as concluded by the RU representatives in the project.

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4 Conclusions We presented, at first, some general information about MOOCs and OERs and their reflection in specialized publications, especially those developed in Romania and those dedicated to environmental education. Part of our experience in creating OERs, based on Learning Toxicology through Open Educational Resources – TOX-OER project, a short description of the developed OERs by our project team, as well as some perceptions of our students after taking the TOX-OER modules were also presented. We showed how we transferred the TOX-OER project experience to extend our initiative to a second project, “Environmental Education – OERs for Rural Citizens” (EnvEdu – OERs). In the end, we are pleased to identify that now, after the EnvEdu – OERs project was selected to be granted, the recommendations collected from our students, future practitioners, were quite similar to the new OERs that were proposed to be developed on the new MOOC platform. The lessons learned from the TOX-OER project will be valuable inputs for the new EnvEdu – OER project outcomes, both for an efficient rural community acceptance of the environmental education through open educational sources, and for other audience facing similar challenges and experiences in creating OERs. Acknowledgements. Project “Learning Toxicology Through Open Educational Resources” (TOX-OER), with Financial Support from the European Erasmus + Programme, KA2, Strategic Partnership, Project Code 2015-1-ES01-KA203-015957 and project “Environmental Education – OERs for Rural Citizens (EnvEdu – OERs)” with financial support from the European Economic Area (EEA) Financial Mechanism 2014-2021, Cooperation Projects in the Higher Education area, project code 19-COP-0038.

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Cloud-Based Education: Why Corporate Educational Platforms Lead Total Distance Learning Shift? Ekaterina Beresneva(&), Mariia Gordenko, Olga Maksimenkova(&), and Alexey Neznanov National Research University Higher School of Economics, Moscow, Russia {eberesneva,mgordenko,omaksimenkova,aneznanov}@hse.ru

Abstract. Recently the World faced force push to distant learning caused by COVID-19 disease. Statistical numbers show a notable increasing number of users of corporate educational solutions utilizing cloud architecture. However, non-cloud-based learning tools do not meet this growth. In this work the authors consider the causes of that contradictory behaviour and present an explanation based on differences between two types of these educational systems. Also, the authors formulate an interpretation giving a list of extracted technologies or product features that allow corporate solutions to quickly gain popularity among educational society. In addition, clear examples of their connection to learning methods that can improve teaching, learning, and the last, but not the least a user’s experience are provided. And finally, the authors highlight a significant role of integration and interoperability standards supporting easy components replacement and scaling. Keywords: Collaborative learning
Cloud-based education software
Cloud educational solutions
Cloud platforms


Educational

1 Introduction It is common knowledge that educational software is purposed to make the learning process more effective and efficient. In last decades people have an evidence of four technological paradigm shifts in educational technologies [1]. Let us briefly outline these generations, examining them in detail later. The first one is characterized by growing number of personal computers that can be used in educational process, while the second paradigm happened due to the integration of these devices initially into local networks and then into global internet. With the advent of cloud computing technology, it became possible to get inexpensive access to a single computing environment for most people and the third transition took place [2]. This phase provides us with the “Bring Your Own Device” paradigm for mobile client devices and the first mentioning of Educational Technology knows as EdTech. So, online learning systems and interactive collaborative learning tools started their growth. And the fourth transition will be completed when all learning tools transform to intelligent and adaptive systems powered by artificial intelligence (AI). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 335–346, 2021. https://doi.org/10.1007/978-3-030-67209-6_36

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In this work the authors concentrate on cloud-based learning systems, which forms the third educational generation type, because of their significance and transformative potential. In addition, according to the educator survey [3], cloud-based lesson planning and delivery tools top the list of technologies expected to see the biggest growth in the next 1–3 years. The recent COVID-19 pandemic provokes wide and quick ad hoc adoption of various learning tools from different generations, platforms, and vendors. Due to decease, lists of recommended EdTech tools were published by different governments and international organization [4, 5]. It should be highlighted that they mostly consist of isolated solutions from the first or the second generations while the third type tools are not widely counseled. Nevertheless, statistics demonstrates that a lot of cloud-based educational solutions supported by corporate companies met a dramatic increase in the number of new users after a pandemic had pushed education to distance [6]. On the contrast, authors could not find an evidence of significant users increase in standalone (non-corporate) specialized educational tools. This situation is contradictory. So, the main purpose of this research is to provide an exploratory analysis on reasons explaining why cloud-based corporate educational platforms lead total distance learning shift.

2 Historical Overview of Educational Software Generations To make the context of the paper clear this section introduces educational generations and explains the significant ideological differences between cloud-based solutions and previous non-cloud-based generations for supporting learning and teaching. It also overviews a notable increasing number of users of corporate educational solutions utilizing cloud architecture. Over the past 50 years the global educational community welcomed four generations of educational software. The first generation of learning software is associated with the era of widespread off-the-shelf personal computers (PCs) which began with the microcomputer revolution of the 1970s. That time matched well with the John W. Mauchly’s statement “There is no reason to suppose the average boy or girl cannot be master of a personal computer” [7]. Starting with the creation of affordable devices by Apple and Commodore, and people could buy and use the computer at home. PC’s users could break up with the dependence on large-sized machines mostly located in universities as the PCs were priced less than one thousand dollars. It changed the software engineering sphere in general and its application to educational field in particular. From that moment the expenses on software distribution dramatically reduced and business specialized in educational software started it growth. The companies like The Learning Company and Broderbund (which is now the part of the previous one) gave way to the first standalone educational tools purposed to make the educational process more effective and efficient. While the first generation is characterized by increase of PCs that can be used in educational process, the forthcoming of the second generation happened owing to the integration of these devices initially into local networks and then into global Internet. Due to the market competitiveness (for example, Commodore/Atari price war) the retail prices on client hardware systematically decreased making devices more affordable.

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In parallel the invention and advancement of mobile technology provoked the development of handheld devices having wireless access to the network. These technological innovations escalated the new principles of learning and gave a way to international government programs aimed at mass usage of personal computers in education to provide the learners with laptops, handhelds, smartphones or tablets having access to the World Wide Web. For instance, advanced countries introduced the one-to-one computing initiative [8], later they help developing countries to start One Laptop Per Child program [9]. Along with these initiatives and a general trend on wearable technologies, the concept of Bring Your Own Device (BYOD) introduced by [10] came into being and was highly adopted in education sphere, allowing teachers and learners to keep the context and to use personalized environments. The third generation of learning software is associated with cloud computing technology. The first references to cloud computing originated in the 1950s, when the idea of simultaneous connection to one processor by several employees appeared which was the first formed factor. It was impossible to buy computers for all staff members, since they were extremely expensive. However, this model lost its relevance in the 1980s when cheap personal computers came into being. The second important factor that influenced modern clouds was the global network connection. The third significant factor in the history of cloud technologies was virtualization: users needed digital systems that were independent of specific equipment and allow them to start and stop work at any time. Thus, the mutual penetration of telecommunication technologies and the simultaneous adoption of virtualized server hardware and software and centralized management lead us to consolidated cloud infrastructure with benefits in total cost of ownership (TCO), durability and scalability. This technology in its modern modification started its ascendant in the 2010s. According to the NIST [11], the cloud computing technology has the following required specificity: – on-demand self-service – a pay-as-you-go system is applied for necessary volume of resources, so the use of remote resources allows organizations to avoid spending on up-to-date hardware infrastructure and other equipment; – broad network access – it is a fundamental principle of technology having all computations on a server side: users can get access to services from anywhere in the world without any necessity to set up software; – resource pooling and rapid elasticity lead to the optimal use of software and hardware, hence increasing the level of availability and reduce risks of inoperability; – measured service, which is determined automatically by chosen service model. Initially, there are three main types of service models described by NIST [11]: – Software as a Service (SaaS), which is fully managed by cloud providers who host the software and core infrastructure and do all maintenance, including software updates and security patches. End users connect to the application over the Internet, usually using a web browser on their device. It should be noted that most of the software used for educational purposes belong to the SaaS, e.g. Zoom, Microsoft Teams, Skype, G Suite.

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– Platform as a Service (PaaS) provide an on-demand environment for developing, testing, delivering, and managing software applications, e.g. Microsoft Azure and Google App Engine. PaaS makes it easy for developers to quickly build web or mobile applications without having to deal with the basic infrastructure of servers, storage, networks, and databases needed for development. – Infrastructure as a Service (IaaS) allows to rent IT infrastructure (servers, virtual machines, storage, networks, and operating systems) from a cloud provider and is mostly managed by sysadmins. Amazon EC2 and Amazon S3 are two leading examples of IaaS. Along with abovementioned service models, there is one more type, which is practically used by educators. It is Desktop as a Service that enables organizations to deliver virtual desktops hosted in the cloud to any device from anywhere, e.g. Amazon WorkSpaces, Citrix Managed Desktops. The list of key benefits of cloud-based educational software is: – cloud computing technology overcomes issues of previous generation software and provides an incredible cost reduction. It allows educational software tools to become even more affordable and applicable to online learning processes; – cloud-based educational software can be quickly configured and deployed; thus, it meets scalable demands [12]; – perspective immersive distance learning spaces based on VR/AR/MR/XR technologies are very computer-intensive and partly constructed owing to cloudsupported Big Data computing [13]; – clouds allow implementing interactive collaborative learning methodology based on ideas firstly proposed by Engelbart [14, 15]; – one of the main advantages of clouds for education is omnichannel communication which provides continuous learning with device and location independence; – cloud computing development eliminated the main drawback of BYOD – the data loss after the device is changed. Nowadays, the presence of a mobile phone and interfaces using two-factor authentication allows a person to make his/her own context in any information environment. So, the use of virtualization technology makes possible to save the educational context by keeping it in the cloud. It means that all cloud-based software is committed to BYOD concept, however, not all BYODs are always based on cloud computing technology. Moreover, with the advent of virtualization, homogeneity was replaced by heterogeneity, which ensured the possibility of complex structured software development and its integration. So, the learning platforms which were specially created for the two-side interaction of teachers and students started their growth. In this context, the question arises – is it better to choose one big platform or several standalone tools for education purposes? The universality of the platform has its strengths and weaknesses. On the one hand, multifunctionality and inclusiveness are the main characteristics that attract users who prefer to get different kinds of sources in one place. However, on the other hand, it can be very easy for users to get confused in functions, and developers have to constantly change the product architecture in pursuit of customer wishes. To avoid the universality trap, the information systems’ area has several ‘tips’ like teaching user

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stories, short courses, etc. With this context it becomes clearer that up-to-date infrastructures have to ensure integration and interoperability of subsystems to support easy components adjunction and replacement. There are cloud-based educational solutions, such as Google G Suite for Education, Microsoft Office 365 Education which are designed around universal corporate collaboration spaces, extended by omnichannel communication and supported Learning Tools Interoperability (LTI) standards. Thus, modern interoperability standards and guidelines, for example, from IMS Global (LTI and QTI APIP), go to the front-line. Recently, a new trend in intelligent educational software emerged. These systems powered by artificial intelligence originate as another one actor in the educational process, which undertook some part of the content management in the educational process. So, the transition to the fourth generation will take place when cloud-based learning tools transform to adaptive systems. To sum up, let us take three axes into consideration: the first one is an educational software generation in its historical order, the second and the third axes are universal antagonistic attributes such as cost and functionality. By the cost is meant the expenses spent on learning software construction from developers’ side and its purchasing, deployment and maintenance from users’ side. The functionality is understood as the quality of the solution to the pedagogical problem. We assume these problems are connected with a software adaptiveness to special forms of learning (interactive/collaborative/blended/adaptive activities) in educational process; and they are linked with the ways of directional pair interaction (teacher ! student, student ! teacher, student ! student). Overall, we can observe a general trend – the generation change leads to the significant total cost decrease and total functionality increase (expanding) promoting a more productive learning environment.

3 Coronavirus Impact on Corporate Solutions Usage Increase Statistics demonstrates that a lot of corporative cloud-based solutions met a dramatic increase in the number of new users after a pandemic had pushed education to distance [6]. It should be mentioned that this booming is mostly connected with the cloud-based nature of this product. For instance, Jordan Catling, Associate Director of Client Technology at the University of Sydney, mentioned that “Zoom’s cloud-based design and baked-in scalability has ensured it could handle these increases in demand and usage without any infrastructure changes or added management” [16]. It should be noted that MOOC’s vendors faced an enlargement of their audience (mostly in already connected schools and universities), however, distance learning newcomers commonly select corporate solutions with special “COVID-license” (see Table 1).

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Product Zoom

Webex

Discord

Microsoft teams

Microsoft skype

Amazon AWS educate

Google G Suite

GitHub

Impact Many classes began being conducted via videotelephony software. Consequently, Eric Yuan, CEO of Zoom Video Communications Inc., said that more than 300 million people joined Zoom meetings on April 21, up 50% from the beginning of the month [17] and up 300% from a year earlier [18]. In May company announced the guide on hosting graduation ceremonies over Zoom, this activity became a new use case for educators during this unprecedented time [19] Cisco’s Webex saw a surge in usage as well. In February Cisco noticed that the amount of network traffic per second in China increased its normal level in 22 times [20]. Later company made a point that they hosted 50 million meetings by the 26th of March, and they expected to host at least 23 million more in the final five days of the month [18] This messenger with video conferencing support is used not only by gamers, but also by pupils, students and business. Covid-19 pandemic caused start of having virtual classrooms or remote working using this service. Discord met a significant growth in daily voice users: it was 50% in the USA, nearly 150% in France and Italy and just under 250% in Italy [21]. In March 2020, the company temporarily increased the maximum number of participants in a video chat from 10 to 50 users [22] Microsoft saw a 500% increase in usage of Teams meetings, calling, and conferences and a 200% increase in Teams usage on mobile devices [23]. Also, a 775% bump in Teams’ calling and meeting monthly users from Italy in March is highlighted Another Microsoft’s product – telecommunication application Skype – saw a flood of interest as well. The company said 40 million people used Skype daily in end of March, up 70% from just a month ago [24] Amazon Wed Services (AWS) did not explicitly comment about increased cloud-computing usage. However, AWS provided free access to AWS Educate program, Amazon Chime, Amazon Connect и Amazon WorkSpaces that are useful for educator needs during the outbreak [25] Google expanded basic subscriptions in G Suite for Education platform to allow virtual meetings with up to 250 people and live streams with up to 100,000 viewers for free in order to support huge surge of new users [26] Paying attention to computer science instructors, GitHub offered free access to developer tools through the GitHub Teacher Toolbox, along with free access to auto-grading with GitHub Classroom [27]

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4 Cloud-Based Educational Solutions Features and Educational Perspectives To support the declared goal, the authors gather two major types of data described in authority sources. The first one is dedicated to software engineers’ reviews on how to develop cloud-based educational software like the work by Ahmeds [28], Wang and Xing [29], Hendradi et al. [30] and Shukur et al. [31]. This kind of data allow to elicit developers’ understanding of learning requirements, demands and their considerations about omnichannel communication, hardware and software compatibility, cyber security, software transparency, data management, and the others. While the second one is addressed to practical use cases of cloud-based solutions from the end users’ side (e.g. teachers, tutors, learners, instructional administrators) and the effectiveness of such tools in application to modern teaching strategies and teacher-with-student and student-with-student interaction. Here, we base on survey by Almajalid [2] and a review by Al-Samarraie and Saeed [32]. 4.1

Features of Corporate Software Solutions

Before we move on to the corporate educational software, we need to highlight essential characteristics of mature corporate solutions. Due to a modern technological basis (see Fig. 1 for our representation), authority sources [2, 28–32] give accents to the key points, which are presented in Table 2 coupled with our comments.

Collaborative services and workspaces

Administrative tools

Analytics tools

Editors of std. artifact types

Storage UI and dashboards

Low-code automatization

Sharing and publishing

Connectors API

External connectors

Open platform API Versioning subsystem

Scheduling and notifications

Directory Service

Authentication /authorization

Durable distributed storage + computational resources

Fig. 1. Modern cloud platform (logical view).

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Characteristic Load robustness

Interoperability

Omnichannel communication

Separation of access

Multi-platform and crossplatform software

Localization and internationalization

Safety and cyber security

Explanations Foremost, corporations need to satisfy the needs of hundreds of thousands of employees, so the software is designed for high load and many incoming users in advance. Corporations have a sufficiently large and reliable storage owe to their own data centers or rented hardware infrastructure from reliable cloud providers Due to high complexity of enterprise software ecosystem, a need in integration with other corporate systems arises. So, the corporate software is compatible with other standardscompliant applications through the API Corporations adhere to the BYOD principle so that employees can quickly connect to their workstation even when they are out of office and continue working from where you left off. That is why the demand in software, which supports omnichannel communication and keeps the working context, appears The specificity of working in large companies leads to the variety of existing job positions with different privilege levels. Thus, it is necessary to have a software system which allows to configure user roles and their access level and information access in order to support restriction policies and prevent information overload Corporations have to follow modern technologies, otherwise they will not survive in the innovator’s dilemma. Now on the market there is a tendency towards multi-platform and crossplatform software which is greatly supported via compatible with the latest browsers and operating systems web applications Global companies evidently have employees who are from different countries. So, enterprise software solutions are initially designed to be adapted to various languages and regions Safety, security and use and administration reliability are prioritized as key processes by corporate companies. Thus, software is aligned with state-of-the-art security technologies and appropriate standards to limit exposure to liability in all areas of financial, physical, and personal risk

The features are selected for a reason as they are highly important for educators and students. Thus, load robustness and scalability allow handling dramatic increases in demand. Multi-platform and cross-platform software with omnichannel communication support ensure easy access to learning materials from anytime, anywhere, from any client device. Interoperability is vital for gathering the personal learning spaces. Separation for access support roles used in basic educational process. Software having

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built-in localization and internationalization automatically covers globally wide learning audience. And finally, paying attention to safety and cyber security allows to prevent leaks of personal data and intellectual property (IP) and keeps from uncontrolled copying. 4.2

Educational Cloud Software

First ideas and common discussions about utilizing of cloud solutions in education began immediately after cloud-computing wide spreading in early 2010s. These solutions allowed online collaborative activities and supported end-to-end integration and demanded from educator types of acting inside habitual way of life. Thus, the paper [33] is a good example because it describes a cloud computing service for programming education, but at the presented use-case diagram one can see the old way of teaching and learning processes understanding. Surely, mentioned paper reflects the way of understanding mostly connected with that collaborative learning spaces was underdevelopment and educators only become get used to them. For today, the World educational society more and more often reacts on effects of educational cloud systems penetration like digital transformation and the authors of this paper share the position that it is significant to rethink present teaching, learning and management processes. So, we suggest the use-case diagram (see Fig. 2), which takes into consideration active learning techniques delivered in blended or distance format through a cloud platform for two user roles: a student and a teacher. We state that a modern educational software should have the following components and features that ensure students have 21st-century skills they need to succeed in the global information society, as it is discussed in detail in [33] and [34]: – content management system, which is used to provide and organize a collaborative space for processes of creating, editing, managing, and sharing content supported such required formats as video, audio, HTML, PDF, PowerPoint, Word, etc.; – omnichannel communication system that combine teaching communication and feedback via synchronous chats/meetings and asynchronous forums/messengers with integrated tags, comments, and notifications; – learning management system integration (curricula, courses, lesson plans, student groups); – evaluation services for manage student assessments and gradebooks; – the ability to conduct, record, and stream teleconferences and webinars; – support of gamification elements; – the ability to combine courses into various personal learning paths, including intelligent assistance for adaptive learning. Corporate solutions are designed to support very complex and weighty business processes in the face of changing infrastructure and organizational structure. On the contrary, organizational structure in education does not change so quickly, because the basic education processes are covered by student, teacher, and administrator roles. So, this scheme can be easily supported by corporate tools since they are initially aimed at supporting a complex organizational structure. In this context, the main responsibility of enterprise software solutions is to make tools joining which is possible due to

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Fig. 2. Active and blended-learning use-cases in cloud-based platform.

platform and data transfer technologies that give flexibility and simplify integration with external services.

5 Conclusion The authors explode the role of solutions implemented in corporate cloud educational infrastructures which ensure their leading positions in pressing migration to distance learning this year. To support their stable position in current educational process, authors introduce and explain the significant ideological differences between cloudbased solutions and previous non-cloud-based generation for supporting interactive collaborative learning. And as a result, authors erase the boundaries between intangible cloud-based educational technologies, classical standalone learning software and the ways of rethinking their adoption by teachers and learners. It became clear that students to have relevant and time-bound knowledge should be taught in up-to-date infrastructures, which ensure integration and interoperability of subsystems to support easy components’ replacement. Hence, standards and guidelines for them are especially important, as well as a group of standards on the interaction with promising intelligent systems. In turn vendors of corporate cloud platforms continue as adding connectors

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suitable for education (like IMS LTI) as integrating and adopting main learning/ teaching scenarios into universal communication use cases. As a result of analysis, the authors give a list of extracted technologies or product features that allowed corporate solutions to quickly gain popularity among educational society. Therefore, authors present findings which might have important implications to solve the problem of undervaluation of cloud-based tools and prove the fact that cloud developments are revolutionizing the way educators manage schools and conduct lessons. Therefore, corporations that have already moved to a new level of software tools are able to instantly meet education challenges and refine the existing system by adapting it for pedagogical purposes for a fairly short time. Acknowledgement. The article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project “5–100”.

References 1. Chomal, V., Saini, J.: A study and analysis of paradigm shifts in education triggered by technology. Int. J. Res. Econ. Soc. Sci. 3(1), 14–28 (2013) 2. Almajalid, R.: A Survey on the Adoption of Cloud Computing in Education Sector. arXiv: 1706.01136 (2017) 3. Promethean: The State of Technology in Education 2019/20 Report (2019) 4. UNESCO: Distance learning solutions. http://en.unesco.org/covid19/educationresponse/ solutions. Accessed 09 Apr 2020 5. The World Bank: How countries are using edtech (including online learning, radio, television, texting) to support access to remote learning during the COVID-19 pandemic. http://www.worldbank.org/en/topic/edutech/brief/how-countries-are-using-edtech-tosupport-remote-learning-during-the-covid-19-pandemic. Accessed 11 Apr 2020 6. Vox: Microsoft, Google, and Zoom are trying to keep up with demand for their now free workfrom-home software. http://www.vox.com/recode/2020/3/11/21173449/microsoft-googlezoom-slack-increased-demand-free-work-from-home-software. Accessed 22 Apr 2020 7. Mauchly, J.W.: Pocket Computer May Replace Shopping List, The New York Times (1962) 8. Penuel, W.R.: Implementation and effects of one-to-one computing initiatives: a research synthesis. J. Res. Technol. Educ. 38(3), 329–348 (2006) 9. OLPC, Inc: One Laptop per Child. http://one.laptop.org. Accessed 05 Apr 2020 10. Ballagas, R., Rohs, M., Sheridan, J.G., Borchers, J.: Byod: Bring your own device. In: Proceedings of the Workshop on Ubiquitous Display Environments. Ubicomp (2004) 11. National Institute of Standards and Technology: The NIST Definition of Cloud Computing. http://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-145.pdf. Accessed 02 May 2020 12. Mhouti, A., Erradi, M., Nasseh, A.: Using cloud computing services in e-learning process: benefits and challenges. Educ. Inform. Technol. 23(2), 893–909 (2018) 13. Assunção, M.D., Calheiros, R.N., Bianchi, S., Netto, M., Buyya, R.: Big data computing and clouds: trends and future directions. J. Parallel Distrib. Comput. 79(80), 3–15 (2015) 14. Endelbart, D.: Knowledge-domain interoperability and an open hyperdocument system. In: Proceedings of the Conference on Computer-Supported Work. Los Angeles (1990)

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15. Engelbart, D.: Toward high-performance organizations: a strategic role for groupware. In: Proceedings of the GroupWare 1992 San Jose (1992) 16. Zoom Video Communications Inc: University of Sydney Leverages Zoom as It Faces Unique Challenges During COVID-19. http://blog.zoom.us/wordpress/2020/06/01/university-ofsydney-leverages-zoom-unique-challenges-covid-19/. Accessed 01 June 2020 17. Zoom Video Communications Inc: Ask Eric Anything. http://www.youtube.com/watch?v= OGQpawfDRcA. Accessed 22 Apr 2020 18. MarketWatch: Zoom, Microsoft Teams usage are rocketing during coronavirus pandemic, new data show. http://www.marketwatch.com/story/zoom-microsoft-cloud-usage-are-rocketingduring-coronavirus-pandemic-new-data-show-2020-03-30. Accessed 22 May 2020 19. Zoom Video Communications Inc: Tips for Hosting Your Zoom Graduation. http://blog. zoom.us/wordpress/2020/05/27/tips-for-hosting-your-zoom-graduation/. Accessed 28 May 2020 20. CNBC: Cisco says Webex video-calling service is seeing record usage too, even as competitor Zoom draws all the attention. http://www.cnbc.com/2020/03/17/cisco-webexsees-record-usage-during-coronavirus-expansion-like-zoom.html. Accessed 15 May 2020 21. Discord, Talking to each other during COVID-19. http://blog.discord.com/talking-to-eachother-during-covid-19-6ca471fbe5ac. Accessed 26 May 2020 22. Discord: Helping out where we can. http://blog.discord.com/helping-out-where-we-can3a5fb7bac77a. Accessed 22 May 2020 23. Microsoft: Our commitment to customers during COVID-19. http://www.microsoft.com/enus/microsoft-365/blog/2020/03/05/our-commitment-to-customers-during-covid-19/. Accessed 22 Apr 2020 24. Microsoft: Introducing the new Microsoft 365 Personal and Family subscriptions. http:// www.microsoft.com/en-us/microsoft-365/blog/2020/03/30/introducing-new-microsoft-365personal-family-subscriptions/. Accessed 22 Apr 2020 25. AWS: AWS Educate. http://aws.amazon.com/education/awseducate/. Accessed 25 May 2020 26. Google: COVID-19 support resources: Google for Education. http://edu.google.com/latestnews/covid-19-support-resources/. Accessed 22 Apr 2020 27. GitHub, Inc: Engaged students are the result of using real-world tools - GitHub Education, 2020. http://education.github.com. Accessed 01 Apr 2020 28. Ahmed, E., Ahmed, H.: A proposed model for education system using cloud computing. In: 2018 3rd International Conference on Emerging Trends in Engineering, Sciences and Technology (ICEEST), pp. 1–4. Karachi (2018) 29. Wang, B., Xing, B.: The application of cloud computing in education informatization. In: 2011 International Conference on Computer Science and Service System (CSSS), pp. 2673– 2676. Nanjing (2011) 30. Hendradi, P., Khanapi, M., Mahfuzah, S.N.: Cloud computing-based e-learning system architecture in education 4.0. J. Phys. Conf. Series 1196(1), 012038 (2019) 31. Shukur, B.S., Ghani, M.K.A., Burhasnuddin, M.A.: A cloud computing framework for higher education institutes in developing countries (CCF_HEI_DC). Intell. Interact. Comput. Lect. Notes Netw. Syst. 67, 397–409 (2019) 32. Al-Samarraie, H., Saeed, N.: A systematic review of cloud computing tools for collaborative learning: opportunities and challenges to the blended-learning environment. Comput. Educ. 124, 77–91 (2018) 33. Elamir, A., Jailani, N., Bakar, M.: Framework and architecture for programming education environments as a cloud computing service. In: Procedia Technology, 11 (2013) 34. Intel: The Education Cloud: Delivering Education as a Service. http://virtucom.com/wpcontent/uploads/2016/05/Intel-ITDM_education_cloud_final1.pdf. Accessed 15 May 2020

Multimodal Environment for Studying the Behavior of Autonomous Vehicles in Traffic Situations Csaba Antonya(&)

and Ioana Diana Buzdugan

Transilvania University of Brasov, Blvd. Eroilor 29, 500036 Brasov, Romania [email protected]

Abstract. The paper is proposing an advanced simulation tool for evaluating the behavior of semi and fully autonomous vehicles in the presence of the actions and decisions of the drivers (acquired and automated competencies). The vehicle simulator is built on a hexapod platform, the driver is interacting with steering wheel and pedals with the virtual vehicle. The selected traffic scenario is a roundabout with several vehicles. The behavior of these vehicles is imposed by computing their speed with a deterministic finite state automaton while maintaining the imposed path. These vehicles have simplified kinematic models (the acceleration is controlled) and they are obeying traffic rules. The driver will negotiate the roundabout while studying and evaluating the behavior of the other vehicles. The outcome of this simulation environment will be a new humanmachine interaction evaluation introduced through a real-time simulation system in which the semi and fully autonomous vehicles’ behavior is evaluated. The assessment of the driving experience of the vehicles in the new age of the autonomous vehicle is an important step in the algorithm development for autonomous decision-making systems and will contribute to safety analysis and the fidelity of the simulation models. Keywords: Autonomous vehicle Decision evaluation


Driving simulator
Rule-Based decision


1 Introduction Autonomous vehicles could completely change mobility in the coming years. As the autonomous vehicles are still under development and gathering essential data for further analysis, existing studies mainly applied models and simulations to assess their impact on traffic [1]. One of the major challenges that autonomous vehicles are facing today is driving in urban environments. A driver is expected to react based on his experience in different tracks and environmental conditions. Also, in the traffic scenarios, the behaviors of the autonomous vehicles will be based on a set of rules, and the actions of the user will trigger the response of other vehicles in the framework of these rules. According to [2], autonomous vehicles, which operate in different dynamic environments, have the ability to acquire methods to respond to unpredictable situations in a timely manner in order to reach human-level reliability. Driving scenarios have been © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 347–355, 2021. https://doi.org/10.1007/978-3-030-67209-6_37

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developed in several papers, some of them consider that the vehicles are making the decisions with fuzzy logic, deep learning, reinforcement learning [3, 4]. Automation of a vehicle can vary from a human-operated semi-autonomous vehicle to a self-driving vehicle. In a multimodal driving environment, the users can be exposed to easily adaptable driving scenarios, it has the advantage of being safe and easy to repeat. The simulator can evaluate the driver, but also can deliver information regarding the safety and the performance of the simulation scene. Blended learning environments create the possibility for every user to experience precisely the learning needs. Blended learning refers to the blending of two or more methods related to documentation and testing. According to [5, 6], in the blended learning context, the combination of traditional information technology and testing can create infinite possibilities in education to reflect the highest level of education. This study aims to explore the effect of applying blended creativity teaching to increase the level of knowledge of the user. We also want to cultivate the user’s skills in independent thinking, novelty, and flexibility through testing and understanding the proposed driving scene. The user will have the ability to provide feedback and to contribute with ideas that will help us to improve the project. The contribution of this study therefore can be summarized as: we are in the process of studying several aspects of planning and decision-making of autonomous vehicles by using a simulator and typical algorithms. For this, we are proposing a multimodal environment based on a vehicle simulator for studying the behavior of autonomous vehicles in a traffic situation. The first part of this paper will present the design of a driving scenario. Section 3 is presenting the simulator, followed by the description of the testing scenario.

2 The Simulation Environment The simulation environment consists of a typical situation in which the user is going through a roundabout where the other vehicle’s behaviors are defined by imposed rules. The rules are regarding the distance between two vehicles, velocity and acceleration limits, delays in response, the path to follow, etc. At the end of the simulation, the user will give feedback regarding the autonomous vehicle’s performance. The users are not informed about the rules imposed by us; they have to observe them during the simulation and compare them to their prior experiences in similar traffic situation. To perform modeling and simulation in the multimodal virtual environment, we need models of the environment (road, infrastructure, scenery) and of dynamic entities (other vehicles, pedestrians and their behavior). Other vehicle behaviors are following typical rules for the chosen traffic situation. Driving simulators are providing the user realistic feedback regarding the required visual, auditory, haptic, and kinesthetic information. A multimodal virtual environment can be used to experience the presence of autonomous vehicles. The proposed multimodal environment is composed of a hexapod platform on which a driving seat is mounted. This setup permits inertial feedback for the driver in six directions and

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visualization on a multi-screen display. The driver can interact with the vehicle with steering wheel and pedals. 2.1

The Environment

The environment in which the testing of the vehicle’s behavior rule takes place can be divided into two domains: computation of the vehicle’s movement to reflect the imposed behaviors, and experiments by negotiating the roundabout using the vehicle simulator. Roundabouts, defined as a channelized intersection as replacements for signalized intersections, have grown in popularity and has multiple advantages regarding safety and access management. In a roundabout, several roads converge towards a central island form different directions. Each road includes predefined entry and exit points for each lane connected to it. The capacity of a roundabout is measured by the distribution of time between consecutive vehicles. This model is based on the gap-acceptance theory [7, 8]. During the negotiation of a roundabout, the driver must be aware of the presence of the crossing pedestrians at entrance and exit, bicycles merging into the traffic, and must choose an acceptable gap in which to enter [9]. Figure 1 shows the test track used for the traffic experiments created in Driving Scenario Designer in Matlab [10]. The main characteristics of this roundabout are:

Fig. 1. The roundabout design

• The width of the roundabout is 12.15 m. • It has four entrances/exits, 8.15 m wide each. • The roundabout has two lanes inside, 4 m each. The geometric design of a roundabout is governed by the requirements of the design vehicle and its velocity. The size of a roundabout is determined by many design objectives: design speed, path alignment, design vehicles etc. The design speed of a

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roundabout depends on the theoretical speed that drivers could achieve through the roundabout. For single-lane roundabouts, the maximum theoretical speeds recommended are 30 to 40 km/h, for multilane roundabouts the theoretical speed recommended is 40 to 50 km/h and for mini-roundabouts, the maximum theoretical speed is 20 to 30 km/h [9]. 2.2

The Actors

The actors of the simulation scenario are several autonomous vehicles and one humancontrolled vehicle. In this paper, we model the vehicle-to-vehicle interaction at a roundabout in the cruising directions indicated by the red arrows. A human, who is testing the behavior of the other vehicles, is in control of one vehicle - the ego vehicle (represented by the blue box in Fig. 1,a) without cameras or radars/lidars - and is focusing on the behavior of the other actors (represented by the red, green, yellow, cyan box in Fig. 1,a). Driving in a roundabout requires the individual actors to decide to merge, to follow the front car, change lanes based on the movement of other interacting actors. The human driver is assumed to act selfishly, making decisions depending on the traffic situation. In this approach, human actions are not going to influence the autonomous vehicle’s behavior. The traffic flow on a roundabout must be continuous, this means they do not allow for vehicles to stop for a long time or reverse whilst they are still on them. The actors follow the imposed path, represented by the red, green, yellow, and cyan points, along the curved traffic lanes. The velocity of the actors is imposed according to the behavior rules, by controlling the accelerations of the vehicles. 2.3

The Roundabout Negotiation Rules

Autonomous driving in the roundabout has to achieve the levels of human driving competence. The drivers are making decisions on three levels: strategic level (path planning), maneuvering level for short-term path control, and operational level for direct control of the acceleration, braking, and steering of the vehicle [11]. The driver model has to include emotional states and risk management (risk-threshold, riskcompensation models, or risk-avoidance models [11]). Usually, the vehicle speed decreases when approaching a roundabout. Just before entering a roundabout, or inside it, the speed is low, or even the vehicle is stopped. All the information, such as position inside a lane of all the actors that participate in this driving scenario, traffic lights or signs, pedestrians are determining the behavior of the ego vehicle through the human-machine interaction interface. We considered the following characteristics and rules for our driving scenario: – Approaching a roundabout: vehicles entering a roundabout must give way to any vehicle already in the roundabout. If the distance between the vehicle which wants to enter in the roundabout and the vehicle which is already in it is less than 4 m (measured on the left side of the vehicle), then the vehicle which wants to enter will

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slow down. If the distance between these two vehicles is less than 2 m the vehicle which wants to enter in roundabout will stop (gap acceptance parameters). – In the roundabout: the vehicles will follow the front car and will change lane before exiting. – Exiting a roundabout: the vehicle will slow down when approaching an exit of a roundabout or will follow the front vehicle, followed by speeding up until it will reach the maximum velocity. – The maximum speed for the vehicles in the roundabout is 40 km/h, and 50 km/h outside of it. The motion control of autonomous vehicles is using a deterministic finite state automaton. The states are the different constant velocities and accelerations of the vehicles in different phases of negotiation of the roundabout: stop state, constant velocity state, accelerating and deaccelerating state. Acceleration states contain the stay-in-the-lane acceleration, acceleration during a lane change and the target gap acceleration (at entering and during the choice of a target gap) [8]. These motion controllers are computing the required velocities of the actors, while they are following the impose trajectories.

3 The Multimodal Environment of the Driving Simulator Our vehicle simulator is a driving seat on top of a Moog hexapod system (Fig. 2). The user is interacting with the vehicle through the pedals and steering wheel. The vehicle dynamic model is developed in Matlab, together with the filtering and motion cueing algorithm which transforms the computed inertial forces of the driver into displacement command of the hexapod system in three directions (surge, sway and heave) and three rotations (roll, pitch and yaw) [12]. The visualization of the driving simulation is based on the Epic Games Unreal simulation environment (Fig. 3) and is shown on three displays in front of the user. This graphical game engine provides visual development tools to increase the level of details of the environment to add realism to the driving experience. The user is able to select different viewpoints and the car dynamics are synchronized with the hexapod motion.

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Fig. 2. The vehicle simulator

Fig. 3. The rendered scene of the roundabout with vehicles

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4 Testing Scenarios In the testing scenario the subject is driving in the vehicle simulator through a roundabout in which the other participants are autonomous vehicles with rule-based imposed behavior. The presence of the vehicles in the roundabout and their behaviors are directly influencing the drivers’ decisions. The observation point of the driver is from the cockpit and permits a good view of the other vehicle’s movement (Fig. 4). The set of states that will provoke a collision or an accident is known in the literature by capture set, the inevitable collision states, the region of an inevitable collision, or the target set [13].

Fig. 4. The rendered scene of the roundabout with vehicles

To model the traffic participants (actors), a starting point is a finite decision set (turning, changing lane, overtaking). According to the target lane choice, the vehicle stays in the current lane or is changing to either the right or the left lane. The decision to change lanes is conditioned by the adjacent gap in the target lane (the clear spacing between lead and lag vehicles) [8]. This will determine the possible path of the vehicles at the center of the lanes. In our model, the paths of vehicles are predefined in and around the roundabout (Fig. 5, a). The velocity of the actors is computed with a deterministic finite state automaton using a Stateflow chart [10]. The states are for the kinematic model: accelerating (decelerating), cruising with constant velocity and the stop state. This kinematic model of the cars is a simplified model with steerable front wheels and no lateral velocity. The transition between the states is computed according to the relative positions of the actors. The vehicles slow down before the roundabout, they have the imposed constant speed in the roundabout or they are following the front vehicle. Figure 5,b is showing the ego view during the design phase. Autonomous vehicles generally aim to follow the imposed path by a motion planning process with a high degree of precision [14], but errors can occur during the

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movement of them. After performing the simulation, we will take into account the feedback that is given to us by the driver of the vehicle simulator regarding the behavior of the autonomous vehicle based on the imposed rules (Sect. 2.3). Based on the driver’s feedback will be analyzed individual characteristics of the vehicle’s aggressive behavior, reaction time, safe operation. The aggressive driving behaviors of the autonomous vehicle include severe acceleration and braking, high frequency of braking followed by acceleration, steering wheel angle speed and harsh high speed turning, driving too close to the car in front, not respecting traffic regulations or improper lane. The velocity of the actors is imposed according to the behavior rules. Each vehicle has a different velocity profile on the same path controlled by the state’s characteristics (imposed by the value of accelerations and velocity, distance to the front vehicle): passive, normal or aggressive. The human driver must detect the difference between the three modes of operation of the actors. The safe operation of an autonomous vehicle means situation risk assessment [15]. The human driver must observe if the actors can identify possible actions for a dangerous situation, such as unexpected changes and actions in turning left or right, moving faster or slower and non-compliance with traffic rules of the actors. Another task for the driver is to observe the simulation scenario’s faithfulness.

(a) Bird-eye’s view

(b) The ego vehicle view Fig. 5. Simulation viewpoints

5 Conclusions Users have a significant role to play in the development of autonomous intelligent vehicles. By using the proposed simulation tool, they will understand the behavior of the autonomous vehicle in a certain driving scenario in a safe environment. The presence of the rules is defining the behavior of autonomous vehicles and will be identified and evaluated by users. This will enable us to improve and further develop the rule-based behavior. A driving simulator with realistic interaction, operating

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environment and feedback eliminates the difficulties of the road test, and allows the understanding of driving behavior, testing driver assistant systems and traffic research. The proposed multimodal environment enables us to make user-studies upon the rulebased behavior of autonomous vehicles. Understanding of vehicle behavior and the decision-making process can significantly contribute to safety analysis and the fidelity of the simulation models. A high desire for knowledge makes every user to autonomously investigate the project activity, so they can actively consult with experts to gain professional knowledge. After the simulation, the user is able to obtain an in-depth understanding of the activity topic. In future work a user study will be conducted with participants familiar with the vehicle simulator.

References 1. Katrakazas, C., Quddus, M., Chen, W.H., Deka, L.: Real-time motion planning methods for autonomous on-road driving: state-of-the-art and future research directions. Transp. Res. Part C: Emerg. Technol. 60, 416–444 (2015) 2. Schwarting, W., Alonso-Mora, J., Rus, D.: Planning and decision-making for autonomous vehicles. Annu. Rev. Control Robot. Auton. Syst. 1, 187–210 (2018) 3. Tian, R., Li, N., Kolmanovsky, I., Girard, A, Yildiz, Y.: Adaptive game-theoretic decision making for autonomous vehicle control at roundabouts. In: 2018 IEEE Conference on Decision and Control (CDC), pp. 321–326 (2018) 4. Rastelli, J.P., Penas, M.S.: Fuzzy logic steering control of autonomous vehicles inside roundabouts. Appl. Soft Comput. 35, 662–669 (2015) 5. Ting, Y., Tai, Y.: Using technology in students’ daily life to teach science. Int. J. Technol. Eng. Educ. 9(1), 21–29 (2012) 6. Chung, C., Dzan, W., Shih, R., Tsai, H., Lou, S.: Creativity learning through blended teaching for designing amphibious vehicle. Int. J. Technol. Eng. Educ. 9(1), 34–38 (2012) 7. Dahl, J., Lee, C.: Empirical estimation of capacity for roundabouts using adjusted gapacceptance parameters for trucks. Transp. Res. Rec. 2312(1), 34–45 (2012) 8. Toledo, T., Koutsopoulos, H.N., Ben-Akiva, M.: Integrated driving behavior modeling. Transp. Res. Part C: Emerg. Technol. 15(2), 96–112 (2007) 9. U.S. Department of Transportation Federal Highway Administration: Roundabouts, 3–10 (2010) 10. Matlab, Simulink, Mathworks Inc Homepage. https://www.mathworks.com/products.html. Accessed 27 May 2020 11. Michon, J.A.: A critical view of driver behavior models: what do we know, what should we do. In: Human Behavior and Traffic Safety, pp. 485–524. Springer, Boston (1985) 12. Antonya, C., Carabulea, L., Pauna, C.: Predictive actuation of a driving simulator. In: Burnete, N., Varga, B. (eds.) International Congress of Automotive and Transport Engineering 2018, pp. 128–135. Springer, Cham (2018) 13. Schwarting, W., Alonso-Mora, J., Paull, L., Karaman, S., Rus, D.: Safe nonlinear trajectory generation for parallel autonomy with a dynamic vehicle model. IEEE Trans. Intell. Transp. Syst. 19(9), 2994–3008 (2017) 14. Petrovskaya, A., Thrun, S.: Model based vehicle detection and tracking for autonomous urban driving. Auton. Robots 26(2–3), 129–139 (2009) 15. Wardzinski, A.: Dynamic risk assessment in autonomous vehicles motion planning. In: 1st IEEE International Conference on Information Technology, pp. 1–4 (2008)

A Low Cost Simulation to Replace a Physical Demo for Teaching Vibration Concepts Timber Yuen(&) Automotive and Vehicle Engineering Technology, School of Engineering Practice and Technology, McMaster University, Faculty of Engineering, 200 Longwood Road S. MARC 270, Hamilton, ON L8P 0A6, Canada [email protected]

Abstract. Physical demo tools providing concrete experience to students can enhance the learning experience in an engineering lecture. In April 2020, Canadian universities were under quarantine due to the COVID-19 pandemic. Due to the need for social distancing and other uncertainties caused by the virus, instructors were asked to convert their lectures and labs in preparation for online delivery in September 2020. The author was responsible for a Mechanical Vibrations course in Level 3 of an Engineering Technology Program at McMaster University. Over the years, many physical demo tools have been developed for this course [1]. The conversion of one of these demo tools into a low cost Excel simulation demo for online delivery is the focus of this study. Keywords: Vibration control demos
Excel simulation
Experiential learning

1 Introduction 1.1

Background

A primary concern in the teaching of an engineering curriculum is to deliver interesting contents to keep the students engaged in a lecture. Traditionally, physical demo tools could be used in a lecture to allow students to see, hear and feel the physical problem at hand. In the case of vibration control, a physical demo could create the visual and audial effects that draw the students’ focus onto the vibration problem at hand. However, due to the COVID-19 pandemic in 2020, students were asked to stay at home and instructors were forced to deliver their courses online. How could physical demos used in face-to-face lectures be converted into simulations for online delivery? What are the roles of the instructors in the delivery of online simulated demos? In this paper, the conversion of a physical demo tool for a mechanical vibration course will be used as an example to demonstrate the process (Fig. 1).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 356–361, 2021. https://doi.org/10.1007/978-3-030-67209-6_38

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Learning Objectives of the Original Demo

Fig. 1. Physical demo tool for vibration absorber design [2]

To demonstrate the implementation of a vibration absorber, a physical demo tool designed to be used in a face-to-face lecture is to be converted into a simulation. The demo equipment was built as a vertical cantilever beam to model a tall building. A DC fan with a rotating unbalance was attached to the bottom of the structure to provide a continuous sinusoidal input. Typically, the demo would be used in a classroom with around 80 students. The demonstration would start with the system oscillating without the vibration absorber. The rotating unbalance in the DC fan would create a significant amount of vibration. The sound level created would make a huge impression in the minds of the students. After mounting a dynamic vibration absorber [3] on the oscillating structure, the vibration of the structure could be greatly reduced. This demo enhances the students learning by providing a real world “concrete experience” as described by Klob in his work in experiential learning. [4]. It is important to understand the learning objectives of this demo tool before we can convert it into an Excel simulation for online delivery. The learning objectives include the following: (1) To provide a real life vibration control experience (2) To demonstrate the effects of a well-designed vibration absorber The vibration amplitude versus time graphs of the system before and after the vibration absorber is implemented are shown in Fig. 2 below.

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Fig. 2. Actual system response - “before and after” absorber implementation

2 Demo Simulation Design 2.1

Demo Simulation Graphical User Interface

Before the conversion of the physical demo tool into an Excel simulation, one should consider the role of the simulation in the students’ learning process. When the physical demo tool is used in the classroom, the students would perceive (i.e. hear, look and feel) the behavior of the demo and construct the mathematical and physical concepts in their minds directly, Fig. 3(a). However, with the introduction of the Excel Simulation, it acts like a “filter of knowledge” for the students, Fig. 3(b). Typically, a filter would remove the “unwanted material” from a process, as in the case of a coffee filter. However, a poorly designed demo simulation could become an obstacle for the learning process.

Fig. 3. Demo simulation as a “filter of knowledge”

To make it easier for the students to interact with the Excel simulation, a simple Graphical User Interface has been designed (Fig. 4). The input fields are all heighted in yellow and the output plots are shown within the field of view of the students.

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Fig. 4. Demo simulation graphical user interface

2.2

Excel Demo Simulation Implementation – Role of the Instructor

As pointed out by Morris & Finnegan [5], for a successful online delivery, it is critical for the instructor to be involved in the delivery process such as directing students to important contents and providing feedback on participation. A few interesting observations from the simulation results can be used to illustrate the important role of the instructor in delivering online contents in this case. (1) The simulation assumes that the system parameters are known perfectly; therefore, in an ideal case, the system vibration will be cancelled completely by the vibration absorber, as shown in Fig. 5.

Fig. 5. Vibration absorber physics explained

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(2) However, if the amplitude or the frequency of the designed vibration absorber is slightly off, as in real life implementation, some residual oscillation will remain. When implemented with a 5% error in the absorber designed frequency, the simulated output plot (Fig. 6) resembles the actual system output quite well.

Fig. 6. Simulated system response – “after” absorber with 5% error

(3) The phenomenon of “beating” [6], when two signals with similar oscillation frequencies are added together, is more obvious in the simulated results (Fig. 6). Although not very obvious, “beating” is also visible in the actual system response (Fig. 2). The smaller “beating” amplitude in the actual response graph indicates that the absorber implementation error is probably due to a simultaneous amplitude and frequency mismatch. During the demonstration, it is important for the instructor to provide insights such as the three observations mentioned above. By actively showing the students how to use the demo simulation online synchronously, the instructor could highlight the implementation issues of vibration absorbers. The involvement of the instructor would help engage the students and increase their sense of belonging to the course.

3 Conclusions Based on a physical demo for the implementation of a vibration absorber, an Excel simulation has been developed to meet the original learning objectives. Since a simulated demo tool is only a mathematical representation of the actual system, it can never replace the actual system. It is suggested that before the simulated demo tool is used in an online lecture, a video of the original physical demo should be used to introduce the learning objectives to the students. Then the data collected from the physical demo should be presented. After seeing the actual data plots, the students would have a better idea on what to expect from the Excel simulation. It is also important to point out that the instructor should play an active role throughout this

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demonstration process to guide the students. The discrepancies between the response from the Excel simulation and the actual response from the physical model should be clearly explained by the instructor, so the students would understand the benefits and limitations of the simulation.

References 1. Yuen, T., Balan, L., Mehrtash, M.: The Design and Implementation of a low-cost demo tool to teach dynamics in the IOT Era. In: Mobile Technologies and Applications for the Internet of Things, Springer Nature Switzerland AG, pp. 228 – 234 (2019) 2. Yuen, T., Balan, L., Mehrtash, M.: – Implementation of an absorber design for vibration control in automation systems. Proc. Manufact. 32, 578–584 (2019) 3. Preumont, A., Alaluf, D., Bastaits, R.: Hybrid mass damper: a tutorial example. Active and Passive Vibration Control of Structures, pp. 179–212. Springer, Berlin (2014) 4. Kolb, D.: Experiential learning as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall, 31 (1984) 5. Morris, L.V., Finnegan, C.L.: Best practices in predicting and encouraging student persistence and achievement online. J. Coll. Student Retention 10(1), 55–64 (2008) 6. Rao, S., Mechanical Vibrations, 5th Edition, Prentice Hall, 267–269 (2011)

Poster: Efficient Analysis of Frequency Demodulation in Remote Laboratory Narasimhamurthy Kyathsandra Chandrashekar(&), Amrutha Muddappa, Bindu Tavakadahalli Shivakumar, Vismitha Tumkur Abhinandana, and Suchitra Vankalkunti Siddaganga Institute of Technology, Tumkur, India {kcnmurthy,suchitrav}@sit.ac.in, [email protected], [email protected], [email protected]

Abstract. In this paper, performance analysis of Frequency demodulation using remote laboratory is presented. Remote laboratory system has the option of selecting nine different combination of Frequency demodulation circuit. It is possible to perform frequency demodulation experiments with three different capacitors and three different resistor values. This will enable the user to analyze the frequency demodulation performance thoroughly. User can see the time response as well as frequency response during the conduction of experiment. The free running frequency, lock and capture can also be measured. Remote laboratory system for oscillations is built using Aurdino ATMEGA-2560, National instruments (NI) Analog discovery kit and indigenously developed Printed Circuit Board. User has the freedom to conduct the experiment any number of times from anywhere with anyone. Keywords: Phase locked loop
Analog Discovery Remote laboratory
Loop filter time constant


FM demodulation


1 Introduction Engineering education is all about learning by doing. In undergraduate, most of the electronics engineering related courses are design oriented. Many courses deal with Analog electronic circuits. Concepts of these courses will be better understood by visualizing the concepts. Most of such courses will have associated laboratory and nowadays SPICE simulations are also used to solidify the theoretical concepts. However, many times it’s not possible to synchronize the lab experiments with concepts discussed in classroom. In many instances the instructors for theory classes and laboratory classes would be different. In such cases students find it difficult to understand the concepts discussed in the classroom. Experiential learning using Remote laboratory is used as a platform to bridge the gap between the theory and laboratory classes [1–8]. In this paper an innovative approach of Remote laboratory for experiential learning of one of the important concept of frequency demodulation using the phase locked loop is discussed.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 362–369, 2021. https://doi.org/10.1007/978-3-030-67209-6_39

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Economic pressures on universities and the emergence of new technologies have spurred the creation of new systems for developing engineering laboratories, in particular simulations and remote-access laboratory systems. These laboratories are similar to simulation techniques in which they require minimal space and time, because the experiments can be rapidly configured and run over the Internet from any place of the world. While accessing the virtual laboratory, the authorized user can select the desired circuit, vary the available parameters and observe the stimulated output. The simulated output is obtained as per the models files that are being used in the simulators and most of the cases the output differs from the real time outputs. This is because the models of the circuit components may not be representing many real time parameters. Analog communication is one of the important basic courses at under graduation level of Electronics Engineering. It’s necessary to visualize the concepts of analog modulation and demodulation processes for better understanding. In the conventional labs due to time constraints, complexity of the circuit and lack of experience, the important phase of learning: analysis of many modulation and demodulation circuits are not carried out. As an effort towards experiential learning, demodulation of Frequency modulated (FM) signal using Phase Locked Loop (PLL) IC565 is being implemented as one of the Remote laboratory experiments. In this paper, details of the implementation of FM demodulation in Remote lab with access to key parameters of the circuits, response of the circuit for those parametric variations are presented. In Sect. 2 the description of development of FM demodulation circuit for remote laboratory access is discussed. In further section the results are discussed and finally the paper is concluded.

2 Development of FM Demodulation Circuit for Remote Laboratory System The process of extracting the information signal from the carrier is termed as demodulation. Generally in demodulation, the challenge is to design a circuit (or algorithm) that will achieve this task optimally in the presence of noise, interference and varying signal strength, frequency and phase, whilst being compact, power efficient and cheap. In any radio that is designed to receive frequency modulated signals there is some form of FM demodulator or detector. Therefore it’s necessary to know the working of FM demodulator and its analysis. Demodulation of FM signal using PLL happens to be nightmare experiment for students sometimes even for faculty also due to many conceptual design parameters involved in the circuit. The main difficulty during the conduction of PLL based FM demodulation experiment are identification “LOCK and CAPTURE range” of PLL, adjustment of loop filter time constant, modulation depth of FM signal as well as the strength of the FM input signal. The theme of the paper is to explain how to fix these issues and to provide all possible options to vary key components of the circuit and enable the user to measure all essential parameters. Most importantly the purpose of including this in remote laboratory is to give confidence to the user, by step by step process of demodulation of FM signal using PLL. Each step is linked to the theoretical concepts, so that user finds it interesting in conducting the complex experiments.

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The block diagram of remote laboratory system is shown in Fig. 1. Authorized user can login to remote laboratory and perform experiments on the circuits at anytime from anywhere. The remote laboratory system can be accessed using computer or Smartphone and it doesn’t require any special software for accessing.

Fig. 1. Block diagram of Remote Laboratory System

2.1

Implementation of FM Demodulation Circuit

To realize the FM demodulation, most popular PLL based circuit is utilized, as it has good controllability and observability in analyzing the concepts. Figure 2a shows the conceptual set-up, Fig. 2b shows the pin details of PLL IC 565 used in the FM demodulation circuit and Fig. 2c shows the FM demodulation circuit diagram using PLL IC 565. Observation of Fig, 2a and b revels that the phase detector shown in Fig. 2a is completely implemented in 565 monolithic IC. However, to realize VCO and loop filter, external components required. The data sheet of PLL IC LM565 is thoroughly studied and found that it’s possible to modify the free running frequency of Voltage Controlled Oscillator (VCO) and loop filter time constant by varying corresponding resistor and capacitors. More interestingly, Lock and Capture range of the PLL can be easily estimated by plotting the Bode plots. The complete FM demodulation circuit shown in Fig. 2c consists of RT and CT for deciding the free running frequency of the VCO as given in the Eq. (1). CF along with internal resistor of 3.6 KΩ will decide the loop filter time constant. Loop filter time constant will decide the Lock and Capture range of PLL circuit. Free running frequency ¼

0:3 RT CT

ð1Þ

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Fig. 2. (a) Block diagram of FM demodulation (b) PLL monolithic IC 565 details (c) FM demodulation circuit diagram

The FM demodulation circuit in Fig. 3 has six switches, three each for RT and CF. These six switches enable user to vary VCO frequency through S1, S2 and S3 and the loop filter time constant by selecting S4, S5 and S6. The remote laboratory system provides options for the user to select three free running frequencies and three loop filter time constants. In total user will have nine different combinations of PLL circuitry for FM demodulation.

Fig. 3. PLL based FM demodulation circuit implemented in Remote Laboratory

Figure 3 shows the sequence of selections in Remote lab system during the conduction of FM demodulation. User has the option to view Bode plot to know the LOCK and CAPTURE rage of PLL and the final demodulated output. In order to understand all these concepts, conduction of experiment on FM demodulation can be classified into 3 stages. 1. Selection of the VCO free running frequency through RT. 2. Observing the Lock and Capture range of the PLL using Bode plot. 3. Applying FM signal and observing the demodulated waveform.

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In first stage, external variable timing resistor RT and fixed CT will decide the free running frequency of VCO as per Eq. (1). Second stage involves observing the Lock and Capture of the PLL circuit for the selected value of CF, this can be observed on the Network option of Analog Discovery kit. This observation helps user to realize the dependency of Lock and Capture range on the time constant of the loop filter. Finally the demodulation process is carried out by setting the carrier frequency and depth of modulation as per the selection of RT, CT and CF in stage 1 and 2. Figure 4 shows the Waveform tool screenshot showing the specifications of FM signal. In this stage user will understand the requirements of FM demodulation process. Firstly, in order to demodulate the FM signal, the carrier frequency must match with VCO free running frequency and secondly, the swing in the carrier frequency due to modulation must be within the Lock and Capture range of PLL observed in stage 2. Table 1 shows the selection of timing resistor RT and loop filter capacitance CF and their effect on the performance of the FM demodulation process. By varying the depth of modulation of FM signal it’s possible to carryout number of FM demodulation analysis with nine combination of RT and CF. That is for the selected RT and CF it’s possible to apply FM signal with carrier frequency same as that of free running frequency but with different depth of modulation and analyze the output. Table 1. Values of RT and CF and their impact on PLL operation Sl no RT kΩ 1 2.2 2 3 4 3.3 5 6 7 4.7 8 9

CF µF 0.1 0.02 0.01 0.1 0.02 0.01 0.1 0.02 0.01

Free running frequency Lock/Capture range Highest

High

Lowest

Least Less More Least Less More Least Less More

All the above discussed analysis can be carried out in the Remote laboratory system who’s GUI is being developed using Python. Various configurations of the PLL circuit can be realized by switching S1 to S6 appropriately. These switches are triggered using Arduino board. The input FM signals is applied and the corresponding outputs are observed using Analog Discovery Kit.

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Remote Laboratory System Access

Figure 4 shows the sequence of steps involved in the conduction of FM demodulation experiment. The authorized user can start accessing the Remote laboratory experiments using the “Welcome” page. In step 2, user need to select “Demodulation” option from the list of experiments, later must select FM demodulation. Next is the process of deciding the VCO frequency of the PLL from the available three options with VCO1 being the highest free running frequency. Soon after that the loop filter time constant needs to be selected from one of the LOCK time constant. Lock 1 being the button for highest time constant meaning the least Lock and Capture range. At this stage it is possible to measure the free running frequency and Lock and Capture range of PLL by selecting the “Network” option as shown in step 6 and then click on the conduct button. To perform FM demodulation, first the FM signal is applied using AD kit with suitable carrier frequency and depth of modulation. To observe the demodulated signal the button “Demodulation” is selected and click on the conduction button. This will result in demodulated signal same as that of modulating signal on the Scope of Waveform tool. Demodulated output will be distorted, if the depth of modulation results in carrier frequency deviation going beyond the capture range of PLL.

Step 4:Select the Step 5: Select loop Step 6: Select Bode Step 3:Select plot or demodulation free running filter capacitor FM output frequency demodulation

Step 1: Start Remote lab

Step 2: Select demodulations

Step 7: experiment.

Conduct

Fig. 4. Sequence of steps to perform FM demodulation experiment

3 Results and Discussion Conduction of PLL based FM demodulation experiment in Remote laboratory system has resulted in visualization of following theoretical concepts. 1. The Free running frequency of VCO is modified using three timing resistors (Using switches S1, S2 and S3). 2. The Lock and Capture range of the PLL is modified using three loop filter capacitors (Using switches S4, S5 and S6). 3. It’s observed that, circuit with least time constant for loop filters (CF = 0.01 µF) can demodulate the FM signal with maximum modulation index. As the time constant (CF = 0.1 µF) increases, the range of modulation index of the FM signal that can be demodulated will also reduce.

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The oscilloscope views obtained during the conduction of FM demodulation experiment will give confidence to the remote user about the working of the PLL based FM demodulation circuit. Figure 5 shows the response of the PLL based circuit by selecting the RT and CF as 2.2 kΩ and 0.01µF respectively. Figure 5a shows the Bode plot response of the circuit by sweeping the input signal from 80 kHz to 250 kHz. Flat response in the magnitude plot shows the lock region of the PLL.

Fig. 5. Response of FM demodulation circuit under different conditions, a) Bode plot to know the capture and lock range b) Demodulated output signal (Blue), input FM signal (Yellow) for modulation index 20% c) Slightly distorted Demodulated output signal for 75% modulation index, d) Fully distorted output signal due to large modulation index 80%.

Table 2. Various RT and CF and the corresponding circuit response. Sl No RT CF kΩ µF 1. 2. 3. 4. 5. 6. 7. 8. 9.

2.2 3.3 4.7 2.2 3.3 4.7 2.2 3.3 4.7

VCO KHz

0.01 132.98 0.01 89.143 0.01 64.071 0.02 130.92 0.02 89.022 0.02 64.749 0.1 126.47 0.1 89.01 0.1 64.008

Capture/Lock range KHz Min Max 108.38 217.53 65.128 151.35 44.358 63.959 107.91 128.92 71.99 88.341 49.534 63.36 113.69 133.01 76.575 92.28 43.987 63.578

Max. modulation index 70 75 68 60 57 56 30 28 32

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Similar type of analysis is carried out on the circuit by selecting different combinations of VCO frequency and Lock and Capture ranges by selecting RT and CF. For every selected component values, VCO frequency, lock and capture range are measured. Then the FM signal of various modulation indexes was applied and the maximum modulation index for which the circuit gives proper demodulated signal is observed. Table 2 shows the summary of the responses of the FM demodulation process. It may be noted the VCO frequency decreases with increase in RT and the lock and capture ranges decreases as the CF value increases. The readings will give confidence to the user as the theoretical concepts are visualized by conducting the experiment with various parametric variations quickly and correctly in the Remote laboratory system.

4 Conclusion This paper explains an innovative approach to visualize the PLL based FM demodulation circuit in an effective way using the remote laboratory system. The implementation of the FM demodulation circuit is done effectively by providing remote access to vary key parameters that have impact on the output. It also provides many variations to visualize the theoretical concepts of FM demodulation. It’s possible to view and measure various parameters for analysis. This way its possible to effectively analyze the concepts. This FM demodulation circuit can be accessed by any authorized users from anywhere and at anytime. This is aimed at giving confidence to students during the learning process by all possible visualization of the theoretical concepts. Acknowledgment. Authors of this paper express their gratitude for all those who helped in developing the Remote Laboratory system. We also thank officials of Siddaganga Institute of Technology (SIT), Tumakuru, the Management, Director, CEO and Principal for their support in establishing Remote Laboratory system.

References 1. http://vlab.co.in/ 2. Hesselink, L., Rizal, D., Bjornson, E., Paik, S., Batra, R., Catrysse, P., Savage, D., Wong, A.: Stanford cyberlab: internet assisted laboratories. Int. J. Distance Educ. Technol. (2003) 3. http://www.uml.edu/IT/Services/vLabs/ 4. de la Torre, L., Guinaldo, M., Heradio, R., Dormido, S.: The ball and beam system: a case study of virtual and remote lab enhancement with moodle. IEEE Trans. Industr. Inf. 11(4), 934–945 (2015) 5. de la Torre, L., Sanchez, J.P., Dormido, S.: What remote labs can do for you. Phys. Today 69, 48–53 (2016) 6. Sanchez-Herrera, M.R.S., Mejias, A., Marquez, M., Andujar, J.M.: A fully integrated open solution for the remote operation of pilot plants. IEEE Trans. Ind. Inf. 1–1 (2018) 7. Heradio, R., de la Torre, L., Dormido, S.: Virtual and remote labs in control education: a survey. Ann. Rev. Control 42, 1–10 (2016) 8. IEEE Std 1876–2019, IEEE Standard for Networked Smart Learning Objects for Online Laboratories (2019)

Practical Experiences in Blended Learning

Examining the Effects of Privacy-Aware Blended Learning Scenarios in Executive Training for Policymakers and Government Officials Maria Gaci1(B) , Juan Carlos Farah1 , Isabelle Von`eche Cardia1 , Genevi`eve F´eraud2 , and Denis Gillet1 ´ Ecole Polytechnique F´ed´erale de Lausanne, Lausanne, Switzerland [email protected] United Nations Conference on Trade and Development, Geneva, Switzerland 1

2

Abstract. Enabling blended learning scenarios that foster participation and interaction is an important consideration in the design of executive training programs. To investigate this design process, our study focuses on two aspects that are present in such scenarios, namely (1) participant engagement and (2) privacy expectations. This paper presents the pilot deployment of a digital tool within a blended learning scenario implemented by UNCTAD for an executive training program aimed at policymakers and government officials. Our main contribution is a detailed analysis of insights gathered through an observational study with participants from Latin America and the Caribbean. By interpolating data from digital logs, questionnaires, observations, and interviews, our results show that the two aspects investigated play a significant role in fostering interaction among participants. As an outcome of this study, we formulate two hypotheses regarding the design of privacy-preserving blended learning scenarios for validation in future work. Keywords: Blended learning · Digital intervention Digitalization · Executive training

1

· Privacy ·

Introduction

Science, technology, and innovation (STI) are expected to play a major role in achieving the Sustainable Development Goals defined by the United Nations, particularly Goal 8 (“Decent Work and Economic Growth”), Goal 9 (“Industry, Innovation, and Infrastructure”) and Goal 17 (“Strengthen the Means of Implementation and Revitalize the Global Partnership for Sustainable Development”). Nonetheless, gaps persist in terms of STI adoption in several regions of the world, especially developing and in transition regions [8]. To provide developing and in transition regions with access to the benefits of STI, the United Nations Conference for Trade and Development (UNCTAD), c The Author(s), under exclusive license to Springer Nature Switzerland AG 2021  M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 373–384, 2021. https://doi.org/10.1007/978-3-030-67209-6_40

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which is an intergovernmental body of 195 member states established by the United Nations General Assembly, has been promoting technologies that help transform economies [15]. Digitalization, however, requires knowledge transfer and digital capacity building, in addition to the adoption of technology. To address this, UNCTAD delivers e-learning programs to train individuals within specific subjects [13], as well as capacity building programs for policymakers and government officials in the framework of a course on Key Issues on the International Economic Agenda, also known as “Paragraph 166” (P166) [14]. The course is organized for developing regions and economies in transition, and provides beneficiaries with state-of-the-art economic and policy knowledge based on UNCTAD research. Since 2016, UNCTAD and the Swiss Federal Institute of Technology in Lausanne (EPFL) are collaborating to investigate alternative blended learning scenarios that rely on innovative digital tools. Blended learning has been defined by many authors [2,11] and in the context of the present study, refers to the mix of face-to-face and digital activities (e.g., discussions, quizzes) to enhance participation and enrich interaction among participants [3]. Often, a digital tool that acts as a computer-mediated communication channel needs to be deployed in a blended learning scenario [6]. As the introduction of technology may give rise to potential privacy risks and pose important ethical questions, these risks should be considered and appropriately managed [15]. Thus, SpeakUp [12], a digital communication tool ensuring the privacy of participants, was selected for this study. This paper presents an observational study conducted by UNCTAD and EPFL to investigate the impact of the introduction of a digital tool in the framework of an executive regional course. To frame our study, two potential aspects that might affect participation during training were identified: (i) participant engagement, and (ii) privacy expectations. We present the results of our quantitative and qualitative analyses conducted on data gathered from digital logs, questionnaires, observations, and interviews. Our results guide the formulation of two hypotheses concerning the design of privacy-preserving blended learning scenarios, which we propose to be validated in future work.

2

Motivation

Blended learning has been demonstrated to foster interaction between participants [16] and previous studies have shown that social interaction is conditio sine qua non for learning [5]. According to [9], interactions must not be taken for granted, but intentionally designed into the instruction to occur and be meaningful. However, to the best of our knowledge, no studies have been conducted on proposing strategies for increasing interactions (and, as a result, learning) in training programs for policymakers and government officials, hereafter referred to as participants. Thus, this unique collaboration aims to propose strategies that foster face-to-face and digital interactions in such programs. In recent years, several studies have been conducted to identify aspects that need to be considered when designing digital and/or blended learning scenarios

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in executive education for Master in Business Administration students [4,10,17]. According to [17], asynchronous communication in online platforms should be synchronized with synchronous face-to-face communication to increase participant engagement. Studies conducted by [10] suggest that the dichotomy of humility and hubris should be managed in blended learning scenarios to deliver effective executive education. Performance expectancy, effort expectancy, and hedonic motivation have further proved to be the best predictors of the intention to use blended learning in executive training [4]. In the design of blended learning scenarios for policymakers and government officials, one should consider that participants are representing their respective governments and can be held accountable for their actions and interventions [1]. This translates to specific challenges and requires special consideration. Anonymization due to privacy measures might need to be balanced with the expectation of recognition due to networking goals. Furthermore, the fact that training is contained to three-week periods might help mitigate the risk of dealing with potentially sensitive content by imposing temporal limits on data retention, but might hinder long-term networking possibilities by prematurely closing communication channels for the sake of risk management. Hence, anonymous tools offering different data retention options were introduced in the present executive training program. Taking into account the trends highlighted in the literature, as well as the specific nature of our participants—as presented above—the design process for the learning scenarios addressed in this paper focuses on two main aspects: Participant Engagement (A1) and Privacy Expectations (A2). Concentrating on these two aspects allows us to formulate hypotheses regarding the factors that could contribute to increased face-to-face and digital interactions among participants. Testing these hypotheses will then provide a baseline for implementing and validating effective blended learning scenarios for executive training aimed at participants of future studies. Previous studies have been conducted between UNCTAD and EPFL on implementing blended learning scenarios for capacity building for policymakers and government officials [7]. Those studies were concerned exclusively with analyzing data collected from logs generated by the digital tools. However, due to the small sample of participants involved in those previous scenarios, quantitative analyses performed on the logs proved to be insufficient to draw general conclusions. Although the digital logs provided insights into the activity of participants in the digital channel, there was a lack of data regarding face-to-face interaction. To tackle the problems encountered during our previous studies, this paper presents an observational study interpolating different sources of data, comprising digital logs, questionnaires, observations, and interviews.

3

Methods

In this section, we first describe the scenario in which the observational study took place. We then introduce SpeakUp. Finally, we outline the different sources from which we were able to gather our data.

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Use Case

Our study was conducted in Medellin, Colombia, in July 2019 during the P166 regional course for economies in Latin America and the Caribbean [8]. The study lasted three days and was organized as a part of Module I of the training program, titled “Development, Development Policies, and the Role of International Trade and Finance in a Globalized World”. A total of 35 individuals were present in the module: 26 participants (11 female & 15 male), 3 instructors (1 female & 2 male), 3 experts (2 female & 1 male) and 3 researchers (1 female & 2 male). The module was taught by three different instructors. Sessions were organized with the instructors prior to the beginning of the module to introduce them to SpeakUp and discuss the digital intervention strategy. Each session was held privately and face-to-face with each instructor, and lasted for approximately one hour. The research team from EPFL and one of the experts from UNCTAD were present at each session. Participants were introduced to SpeakUp through a one-hour briefing session after the opening ceremony. During the briefing, a 20-min presentation was held, describing the objectives of the observational study and briefly explaining SpeakUp’s main features. Participants then had the opportunity to practice using the digital tool and ask questions. Throughout the training, participants were seated in a horseshoe/modifiedU arrangement composed of two rows in a conference room. All participants had at least one digital device (mobile phone, laptop, and/or tablet) to connect to SpeakUp. The official languages of the training material were English and Spanish. During training, researchers from EPFL were present to observe the digital interaction and provide technical assistance. 3.2

Digital Tool

Virtual interaction during training was enabled through the use of SpeakUp, a digital chatroom designed to foster social interaction and collaboration of participants co-located in physical spaces. In a typical scenario, the instructor creates a chatroom before the start of the presentation, and participants can join (without registration or login), post messages, vote on existing messages using the like/dislike button, and answer multiple-choice questions (Fig. 1). The absence of authentication enables participants to start using the tool with little friction while maximizing their anonymity. To manage the privacy of the content generated in the chatroom, SpeakUp offers chatroom creators the option of configuring two features: Nicknames and Here & Now. The former defines the anonymity of participants and the latter the persistence of the data generated during the sessions. Thus, privacy in the current context is defined in terms of these two features. More specifically, it is defined by the requirement of nicknames (or lack thereof) and the duration for which the chatroom will remain accessible, respectively. The two options available regarding anonymity are anonymous and nicknames, while the two options for data retention are temporary (24 h) and permanent (or until manually

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Fig. 1. Two screenshots of SpeakUp. Left: Instructors can create new chatrooms. Right: Participants can join, post messages, vote, and answer multiple-choice questions.

deleted by the chatroom administrator). The most privacy-aware case is implied to be the anonymous and temporary chatroom, and the least privacy-aware one is implied to be the pseudonymous and permanent chatroom. In the context of this study, only temporary chatrooms were assessed. The configurations of the chatrooms created during the training were the following: – Anonymous & Temporary (Days 1 and 3) – Pseudonymous (Nicknames) & Temporary (Day 2) 3.3

Data Collection

A mixed-methods approach was employed to gather data, combining quantitative and qualitative methods using four techniques: log file analysis obtained from SpeakUp (T1), questionnaires (T2), observations (T3), and interviews (T4). Data gathered was interpolated to enrich the evaluation process and provide insights into the digital interaction (T1), the face-to-face interaction (T3), and both (T2, T4). Table 1 provides a detailed chronological overview of the data collected during the study. Log files were extracted automatically using SpeakUp’s administrator privileges. The activity of the participants and the instructors in the chatroom was exported at the end of each session in the form of a comma-separated (CSV) file. Each log file contained information regarding the number of messages written in the online chatroom along with the content, timestamp, nickname (if applicable), likes, and comments per message. Non-participant observations were conducted during the three-day training by one of the researchers of the EPFL team to record the face-to-face interac-

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M. Gaci et al. Table 1. Chronological Overview of the Activities Activity

# Individuals Techniques Aspects

Briefing session w/ participants 26

–

A2

Pre-questionnaire

26

T2

A2

Session 1

26

Interviews with participants

2

Session 2

26

Session 3

26

Interviews with participants Post-questionnaire

T1, T3

A1

T4

A1, A2

T1, T3

A1

T1, T3

A1

3

T4

A1, A2

26

T2

A2

tions. As participants were sitting on pre-assigned seats throughout the duration of the training, a unique random code was allocated to each of them. The observer would then note down in a confidential notebook the code of the participant interacting at each moment, along with the type of interaction (e.g.., “asking a question”, “providing an answer”, “clarifying”). Two separate questionnaires were distributed to participants at the beginning (pre) and at the end (post) of the module (n = 26). Five-level Likert questions following a scale from “Strongly Disagree” to “Strongly Agree” were included to evaluate how participants perceived privacy, as well as their intended (pre) and actual (post) behavior in the chatrooms. Open-ended questions were included at the end of the questionnaires for the participants to share their expectations and to gather comments, feedback, and queries. Finally, face-to-face unstructured interviews were organized individually with five of the participants. Each interview lasted between 20 and 30 min. A narrative analysis approach was selected to review the individual responses of each participant regarding the effective design of privacy-aware blended learning scenarios to highlight critical points and find common patterns.

4

Results

The various qualitative and quantitative sources detailed in Sect. 3 were analyzed and triangulated to address the two aspects presented in Sect. 2. One-sample Wilcoxon signed-rank tests were performed on the data obtained through the two questionnaires to test for significant divergence from the expected median Likert score of three. The results of the analysis are presented below, organized by aspect. 4.1

Participant Engagement (A1)

Face-to-face interaction was analyzed for each of the three sessions. During each session, 18, 9 and 18 participants, respectively, asked/provided face-to-face questions/answers (Table 2). In total, five participants asked face-to-face questions

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in all sessions, 12 participants in any two of the three sessions, 10 participants in only one session, and two participants did not ask any face-to-face questions at all. Digital interaction was also analyzed for each of the three sessions (Table 2). If the number of participants attending the training (n = 26) is compared to the number of registered users on SpeakUp—50, 38, and 25 for each session, respectively—it may be inferred that almost everyone used the digital channel, even though the utilization was not compulsory. The higher number of registered users in the chatroom is a result of participants utilizing multiple devices during the training. This was evident when inspecting the number of nicknames during the second session, when despite the fact that 38 users were registered, only 26 unique nicknames were recorded. Overall, 46%, 39%, and 28% of the participants who joined the digital room in each session posted at least one message, while 22%, 37%, and 20% of the participants in each session voted at least once. Table 2. Face-to-face vs digital interaction Interaction

Interaction type

Face-to-Face

Question posed by instructor

4

2

5

Question posed by participant

7

8

17

Comment/Opinion Digital

Session 1

Session 2

Session 3

27

4

19

Clarification

2

0

10

Poll created by instructor

4

0

1

30

37

5

2

16

6

Vote Question posed by participant Comment

28

6

0

Other (e.g., Greeting, Technical support)

15

5

1

According to three participants, questions that were not urgent and required the opinion of a broader audience were typically posted in the digital chatroom, as opposed to questions that required immediate clarification from the instructor. We observed that 22% of the questions were asked to clarify content presented in the slides, such as several graphs and equations. Participants expressed a positive attitude towards the use of digital tools to get a diverse range of opinions from peers, especially as it did not interrupt the flow of the presentation and they could continue the discussion online after the training. Furthermore, we observed that the tool was highly utilized by participants speaking a different native language than the one used during the presentation. Participants would post messages in the digital chatroom in either of the two languages and other participants would volunteer to translate them into the other language. In total, 14, 5, and 3 of the messages posted in the digital chatroom were translated for each session, respectively. Contrary to the results of previous studies conducted in higher education settings [12], spamming was neither an issue in the fully anonymous scenarios nor the pseudonymous scenario. Zero spam messages were recorded in the chatrooms and participants pointed out that spamming was not relevant in the current context as it was a professional setting predominantly focused on learning.

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Privacy Expectations (A2)

Several questions were included in the pre- and post-questionnaires to gain insight into the participants’ perception of privacy. In the pre-questionnaire, participants stated that ensuring privacy would result in higher participation in the digital chatrooms (mean Likert score x ¯ = 4.15, SD = 0.95, Z = 29.0, p < 0.001). Participants also considered full anonymity to be an important way of ensuring privacy (¯ x = 3.85, SD = 1.03, Z = 18.0, p < 0.001). In the pre-questionnaire, participants expressed that they would participate more if the digital tool was fully anonymous (¯ x = 3.52, SD = 0.8, Z = 13.0, p < 0.01) and if posts were deleted automatically after some time (¯ x = 3.37, SD = 0.97, Z = 18.0, p < 0.05). In the post-questionnaire, participants were asked to reflect on their behavior and identify if anonymity (¯ x = 2.76, SD = 0.97, Z = 40.0, p = 0.23) and ephemerality of data (¯ x = 2.71, SD = 0.95, Z = 31.0, p = 0.15) affected the rate of digital interaction (Table 3). Participants were also asked if knowing the identity of participants affected the trust on the messages posted in the virtual chatroom and a mean Likert score of x ¯ = 3.52 (SD = 0.89, Z = 21.0, p = 0.01) was obtained. During the interviews, participants were indirectly posed questions regarding their behavior in the virtual chatroom. A group of them mentioned that they considered themselves introverts and the availability of a digital channel enabled them to prepare questions in advance, formulate them correctly, and feel less anxious about expressing their opinions. Furthermore, anonymity was considered to be important, as it enabled participants to express themselves without the risk of encountering negative verbal and nonverbal reactions from their peers and instructors. Participants were asked if the quality of the posts on the digital chatroom would be higher if participants posted anonymously and the mean Likert score was x ¯ = 3.48 (SD = 0.80, Z = 24.0, p < 0.01). Three participants mentioned that anonymous digital channels could be extremely useful in scenarios where people can be judged depending on their hierarchical status and position, yet they were not necessary for training. They suggested that knowing the identity of the participants is necessary to build connections, and as policymakers and government officials, they are trained to overcome the fear of public speaking. When participants were asked about the importance of knowing the identity of other participants to build connections, the mean Likert score was x ¯ = 3.48 (SD = 0.89, Z = 33.0, p < 0.05). Table 3. Questions repeated in the pre- and post-questionnaires On a scale from 1 (Strongly Disagree) to 5 (Strongly Agree),

Pre

how would you rate the following statements?

x ¯

SD

Post x ¯

SD

I am/was concerned about privacy when posting on SpeakUp.

3.44

1.22

2.52

1.19

I will/did participate more if I am/was anonymous.

3.52

0.80

2.76

0.97

I will/did participate more if posts are/were temporary.

3.37

0.97

2.70

0.95

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To better understand the effect of pseudonymity, we performed an analysis of the nicknames selected by the participants during the second session. Before the start of the session, participants were informed about two options when choosing a nickname: (a) use of their real names or initials, so that they would be identifiable, and (b) use of a fictional name, so that they would be unidentifiable. The nicknames selected were as follows. Two participants used their first name, four participants used the initials of their full names and 20 participants selected objects, fictional characters, professional titles, or other unidentifiable names. In the post-questionnaire, participants were asked to select the chatroom settings that they would prefer for two different use cases: (i) if they were the creators of the chatroom and were going to use the tool as an instructor and (ii) if they were users of the chatroom (Fig. 2). A total of 64% of participants selected the same settings in both use cases and 68% of the participants preferred temporary chatrooms either as creators or users. Approximately 52% preferred the fully anonymous setting as users of the chatroom, but only 40% preferred the fully anonymous setting as creators of the chatroom. The most preferred combination of settings in both scenarios was “temporary chatroom with pseudonymity”. Participants stated that the preferred settings would differ according to the context of each scenario, as sometimes it is of high importance to have access to the content of a meeting (hence, permanent chatrooms were desired) and sometimes it is of high importance to ensure that everyone has participated and shared their opinion (hence, anonymity was not highly favorable).

Fig. 2. Difference in preferred chatroom privacy settings when considering the perspective of a chatroom user or a chatroom creator/administrator.

Before the intervention, participants were neutral about the statement “I will be concerned about privacy when posting on a SpeakUp chatroom” (¯ x = 3.44, SD = 1.22, Z = 82.5, p = 0.08). However, at the end of the module, the mean Likert score dropped to x ¯ = 2.52 (SD = 1.19, Z = 68.0, p < 0.05), suggesting that participants were slightly less concerned about their privacy after being exposed to the tool. Nonetheless, despite its privacy-preserving features, participants did not indicate a preference to use SpeakUp over asking face-toface questions (¯ x = 3.02, SD = 0.98, Z = 49.0, p = 0.82). Feedback from the interviews and observations during the training revealed that privacy remained the participants’ main concern (Table 3), but this was mainly attributed to the setup of the training and not the use of SpeakUp, as summarized below.

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Firstly, due to the layout of the room, participants sitting in the second row could observe the screen of the participants sitting in the first row. Secondly, participants could deduce who was the author of the message by matching the person typing and the messages posted at a specific time due to the small group size. Thirdly, in the case of pseudonymous chatrooms, participants could read their neighbors’ nicknames, as the physical distance between adjacent participants was relatively small. Moreover, as participants knew each other in a professional context, they claimed that they could sometimes identify patterns in the posts due to keywords or due to the structure of the language used. Lastly, nicknames were mentioned to create differences between the participants, as some nicknames were referred to as being more favorable and prompting, thus affecting the rate of comments and likes.

5

Discussion

This observational study aimed to investigate two aspects of blended learning scenarios for training for policymakers and government officials in Latin America and the Caribbean: participant engagement (A1) and privacy expectations (A2). By interpolating quantitative and qualitative data gathered from four different sources, we can summarize our findings per aspect as follows. A1. The addition of a computer-mediated communication channel can encourage participant interaction in bilingual settings. Furthermore, different communication channels can be used to interact with instructors depending on the perceived urgency of a question. A2. Although enforcing digital privacy is essential, it is not sufficient to encourage user participation in training. Failing to take into account physical privacy in small co-located group settings, as well as the desire of participants to have a digital identity that exposes their participation, could be detrimental to fostering participant interaction. The combination of the two findings in this paper suggests that a correlation exists between participants’ engagement and privacy expectations. Therefore, two hypotheses can be formulated for future investigation. – A computer-mediated communication channel that takes into consideration the urgency of a question will result in increased participant interaction in blended learning scenarios for executive training programs. (H1) – A computer-mediated communication channel that provides privacy options at the interaction level—rather than at the user level—will foster participant engagement in blended learning scenarios for executive training programs. (H2) Validation of these two hypotheses in future studies will contribute to the ultimate goal of the collaboration between UNCTAD and EPFL. That is, proposing best practices for blended learning scenarios for executive training for policymakers and government officials that encourage both face-to-face and digital interactions.

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Conclusion

This study analyzed the use of a privacy-aware digital tool in a blended learning scenario comprising the three instructors and 26 participants of a UNCTAD regional course in Latin America and the Caribbean. In particular, two aspects faced in such a framework (participant engagement and privacy expectations) were explored. The results of this study suggest that the two factors should be taken into consideration when designing blended learning scenarios for executive training for policymakers and government officials. Our findings reveal that digital tools could complement face-to-face interaction by providing new means of collecting a wide range of opinions during training. Furthermore, results show that in the current context, privacy ensured by the digital tool was not sufficient to increase digital interactions, as participants realized that their privacy could be compromised by the physical setting of the scenario. Thus, even though the two aspects investigated play an important role in fostering interaction among participants, their correlation could not be determined. Instead, two hypotheses (H1, H2) were formulated to be addressed in future work. To conclude, this paper describes the initial experience of deploying a digital tool in executive training for policymakers and government officials. Despite the limitations of a small sample size and a specific use case, our findings have practical implications that could support future research on the impact of novel digital tools in blended learning scenarios aimed at policymakers and government officials. Acknowledgment. This research has been co-funded by the European Union’s Horizon 2020 research and innovation program in the context of the Next-Lab Innovation Action and the Marie Sklodowska-Curie Action (grant agreement nos. 754354 and 731685).

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How National and Institutional Policies Facilitate Academic Resilience and E-Learning in the Unprecedented Time? Yang Gao(&)

, Ke Fu, and Xiaoyi Tao

Dalian Maritime University, Dalian 116026, LN, China [email protected]

Abstract. The fierce COVID-19 has been widely spreading across the globe since the beginning of 2020, which has caused the majority of schooling, higher education in particular, to move online. Consequently, different national and institutional policies have been issued to assist academic resilience during this unprecedented time. In the study which has been conducted in a typical research-based university in Northeast China, we explored how national and institutional policies have informed pedagogical decisions about designing and implementing online courses and helped maintain a successful transition from face-to-face classrooms to online ones during the pandemic times. Keywords: COVID-19 resilience
E-learning


National policies
Institutional policies
Academic

1 Introduction The fierce COVID-19 has been widely spreading across the globe since the beginning of 2020. By May 23, 2020, the global statistics have reached 5.4 million for the confirmed cases, 2.17 million for the recovered cases, and 345,000 for the deaths. One of the severe consequences that COVID-19 has caused is the majority of schooling, higher education in particular, to move online. In response to the emergency, different national and institutional policies have been issued to assist academic resilience during this unprecedented time. In the study which has been conducted in a typical research-based university in Northeast China, we traced the policies and documents from the beginning of February 2020 when the government decided to close campuses all across the country to the late of May 2020 when the university as the research site officially announced the returnees of their first group of students. We then explored how national and institutional policies during the unprecedented time have informed pedagogical decisions about designing and implementing online courses.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 385–391, 2021. https://doi.org/10.1007/978-3-030-67209-6_41

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2 Literature Review 2.1

Redefining the Academic Resilience

The concept of resilience originated from a psychological construct which defines students or learners’ ability to deal with stress or pressure [1, 2]. However, the recent decade has witnessed a shift from individual learners or students to educational contexts or institutes [3]. While there seems no consensus, academic or educational resilience in this redefined orientation presents the likelihood of operational success of schools or academic institutes despite environmental or contextual adversities brought about by emergencies or conditions [3, 4]. In this study, we chose to adopt the redefinition of the academic resilience and studied how a specific academic context, i.e. the university, had responded to the policies and maintained successful online instruction during the COVID-19 period. 2.2

E-Learning in the Emergency or Disaster Times

Even prior to this COVID-19, human beings have already suffered from different pandemics including SARS or H1N1 in the history forcing their schooling to suspend or move online as an alternative. Circumstances as such then guide scholars to conduct research on e-learning in the emergency or disaster times. For example, Meyer and Wilson [5] studied whether and how online or distance learning had been included in the institutions’ emergency plans as solutions to emergencies such as H1N1. Likewise, Mackey, Gilmore, Dabner, Breeze, and Buckley [3] presented how blended learning helped cope with the immediate post-earthquake challenges of redesigning courses and met the instructional needs in the emergency time.

3 Research Methodology 3.1

Approach

We used policy analysis as the methodology for the study [6], in order to study how general policies inform alternatives and consequences during a certain time [7]. With that methodological framework, we traced the issuing of official policies and documents from both national and institutional levels and made analyses on these policies and documents from both macro and micro perspectives. Our macro analysis delved into connections and tensions between national and institutional policies and how the policies were delivered in a hierarchical and timely order. Our micro analysis then explored how these policies and also subsidiary policies emerging from these policies helped maintain the operation of online courses during the time. 3.2

Data Collection and Analysis

We collected official documents from governmental conference press, the Ministry of Education (MOE), institutional policies and notices, and school policies and mapped out these documents in different categories. Specifically, we created a chart by listing

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all the documents from each source. The following table gives a summary of all these documents (see Table 1). Table 1. A Synopsis on the Documents Number 1 2 3 4 5 6 7 8

Source of documents Governmental Conference Press MOE Provincial and Municipal Governments General Affairs Office Academic Affairs Office Human Resource Office Security Office Development Planning and Quality Management Office

Number of documents 1 2 2 14 12 15 7 1

4 Findings 4.1

Hierarchical Delivery of Policies

In a typical collectivist culture, political and institutional policies mandated teachers to uniform their designs and practices. In this study, we found that policies went through a hierarchal process from the governments, either national or local, to the institutes, and then to the individual school or departments. Specifically, it was the governmental conference press that had announced national decision or notice about how people in different fields should work hard together to handle the emergency from this pandemic time. Then, all the fields were required to make specific plans or decisions and implement these plans or decisions. In academia, then it was MOE that had made the paramount guiding principle or decision to all levels of schooling, higher education included. The official notice from MOE “campus closed; classes continue (CCCC)” served as a starting point and signal for different subsidiaries to take action. The decision then went forward to provincial or municipal government, typically to the bureau or hall which was in charge of the educational affairs. Next, these local governments, bureaus, or city halls would inform their local institutes or schools of specific decisions they had made, including ways to conduct instruction and dates to close or return to school during this unprecedented time. However, for some institutes, if they were affiliated directly to state-level ministries, they may have some wiggle room to directly respond to the ministry-level decisions instead of local decisions. In this study, for example, the institute selected did not go strictly with this hierarchy, due to its administrative affiliation to a certain ministry. It was thus directly responding to the decision from MOE or other ministries. The feature of the hierarchical delivery also lies within an institute and university. In this study, for example, the decisions to handle the emergency and make general guidance for instruction and research came foremost from the General Affairs Office (GAO) in which sits the presidential board of the university. Then all the other affiliated

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offices made specific guidance accordingly. The following Fig. 1 provides a general picture of how these policies were distributed in a hierarchical order.

Fig. 1. Hierarchical Delivery of the Policies

4.2

Co-existence of Multiple, Cooperative Policies and Decisions

In this study, we found different administrative offices in the university worked together to make plans for online instructions during the pandemic time. Particularly, under the overarching GAO, there were four different administrative departments or offices highly involved in the whole process of smoothing over difficulties or challenges and ensuring the instructional practices.

Fig. 2. Cooperative Policies from Different, Institutional Offices

These offices include Academic Affairs Office, Human Resource Office, Development Planning and Quality Management Office, and Security Office. Specifically, Academic Affairs Office took charge of the overall instruction across the campus; Human Resource Office, in which Faculty & Teacher Development Center (FTDC)

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was embedded, provided different online training to all the teachers, particularly in the pandemic time. Security Office, to which IT & Network Support Center (ITNSC) was affiliated, offered timely IT support to faculties and teachers when meeting with technical issues in their instruction. Development Planning and Quality Management Office, in which Teaching Quality Assurance Team (TQAT) was located, monitored and evaluated the instructional practices during the pandemic times. These four offices and/or centers followed the general guidance from the General Affairs Office and cosupported each other to aid teachers and ensure the quality of the instructional practice during the pandemic times (see Fig. 2) 4.3

Adequate Training to Facilitate Online Instruction

University Training. One of the key offices to ensure the operation of all courses is FTDC from the Human Resources Office. From the beginning of February 2020 when the official announcement from GAO had made in response to CCCC, till the middle of May when the university officially had announced to reopen the campus for the first group of student returnees, FTDC held 14 online training sessions to all the faculty members and instructors during the pandemic times. These sessions fell into four major categories, including online teaching techniques, online teaching beliefs, online teaching devices, and online teaching case studies (see Fig. 3). All these categories cooperated with each other and facilitated the instructors to smooth over challenges and difficulties in their instructional practices.

Fig. 3. Different Categories of University Training

School/Departmental Training. We took one sampled school in the study to further explore how policies from different institutional offices help relieve the academic resilience and offer e-learning support during the pandemic times. The school included four individual departments but one overall administrative school office. The school administrative office delivered the dean’s announcements and notices and helped monitor the operation of these departments. In the study, prior to the spring semester which was scheduled at the beginning of March, the office set up two different temporary support teams through social media apps to facilitate the instructions. These teams included the instructional design and development team and the instructional

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technological support team. The former team included all the teacher leaders and departmental chairs who may provide timely instructional techniques, online pedagogy, and real-life experience on how they had designed and delivered the lectures; the latter team included not only teacher leaders but also student representatives who may support the departments and the school from different perspectives. 4.4

Timely Technology Support

Another key office that plays a crucial role in supporting online instruction during the pandemic times is from Security Office to which ITNSC was affiliated. From the beginning of February to the end of May, when the university had officially announced the return of the first group students on campus, ITNSC offered continued help and support to all the teachers across disciplines online. It guaranteed a smooth online context for the teachers to design and implement their curricula and lesson plans. It also supported FTDC to give lectures or training on how different technologies and techniques may support online instruction during the pandemic times. 4.5

Assurance of Teaching Quality

With all the policies, training, and support from different offices and centers, another team worked to ensure the quality of teaching during the pandemic times is the Development Planning and Quality Management Office, in which TQAT was located. TQAT monitored and evaluated the instructional practices during the pandemic times, typically in the mid- and final-term. TQAT assigned the monitoring and evaluative tasks to different teaching supervisors and set up evaluative rubrics for instructors’ performance. With the rubric, supervisors evaluated instructors’ performance and gave timely feedback and responses to the instructors.

5 Discussion We presented how national and institutional policies have facilitated the online instruction during the pandemic times in the sampled university. A further analysis of these policies and how they were delivered leads us to the following four points that would maximize the operation and implementation of online courses during an unprecedented time, typically in the university. The first one is the efficiency of delivering the policies. Regardless of the national level or the institutional level, governments or administrators in the study attempted to issue and forward the emergency policies or decisions directly and promptly during the pandemic times. Responding to these policies and decisions was mandated but rest assured that schooling would be continued. Second, the cooperation among different offices and schools across the campus is another key to ensure regular operation of online instruction. It is not the power of a single unit but the cooperation from different units that plays a crucial role in sustaining the operation and implementation of courses. Third, the sufficiency of technological and pedagogical training appeased faculty members and teachers physically and mentally, which is also crucial to the successful

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operation of online courses during the unprecedented times. Teachers in the study, typically for those who are technophobia, got adequate training from the institute and school which helped them design and implement the online courses. Also, the effectiveness of technological support is extremely important in the roughly four months. In addition to the technical support during the regular class hours, technical staff worked shift to solve technical issues, if any, during the unexpected times. Last but not least, appropriateness of monitoring guaranteed the teaching quality and rest assured that all instructors and teachers had been on the right track for their class instruction and student performance.

6 Conclusion In this study, we mapped out different policies and documents from national and institutional levels during the approximately four-month period when COVID-19 were fiercely spreading across China. We presented our findings on how these hierarchal policies helped maintain a transition when teachers in the sampled university successfully conducted their online instruction. Our discussion indicated the efficiency of delivering the policies, the cooperation across the campus, the sufficiency of technological and pedagogical training, the effectiveness of technological support, and the appropriateness of monitoring were five primary factors that have contributed to the successful operation of the online instruction during the pandemic time. With the limited time and sampled research site, our findings may not be generalizable to all the contexts but at least may contribute to a point which can be adapted or referenced to in studying e-learning and academic resilience during disaster times in the future.

References 1. Masten, A.S.: Resilience in Children at-Risk. CAREI 5, 6 (1997) 2. Rutter, M.: Psychosocial resilience and protective mechanisms. In: Rolf, J., Masten, A., Cicchetti, D., Neuchterlein, K., Weintraub, S. (eds.) Risk and Protective Factors in Development of Psychopathology, Cambridge University Press (1990) 3. Mackey, J., Gilmore, F., Dabner, N., Breeze, D., Buckley, P.: Blended learning for academic resilience in times of disaster or crisis. J. Online Learn. Teach. 8, 122–135 (2012) 4. Waxman, H.C., Gray, J.P., Padron, Y.N.: Review of research on educational resilience (11). (Center for Research on Education Diversity and Excellence, University of California), California (2003) 5. Meyer, K.A., Wilson, J.L.: The role of online learning in the emergency plans of flagship institutions. Online J. Distance Learn. Adm. 14 (2011) 6. MacRae, D.: Concepts and methods of policy analysis. Society 16, 17–23 (1979) 7. Walker, W.E., Europe, R.: Policy analysis: a systematic approach to supporting policymaking in the public sector. J. Multi-Crit. Decis. Anal. 9, 11–27 (2000)

Shared Remote Lab Marjan Alavi(B) McMaster University, 1280 Main St. W, Hamilton, ON L8S 4L8, Canada [email protected] https://www.eng.mcmaster.ca/sept/people/faculty/marjan-alavi

Abstract. During COVID-19 pandemic, a rapid change from in-person to online classes was required in the middle of the semester. This paper presents a remote lab which offers experiential learning experiment to the students in online classes. The students share one smart hardware which is located at the instructor’s home. The control and communication is via Node-red and MQTT protocol. Samples of experiments and data collected is presented in this paper. Keywords: IoT · Smart lab · Remote lab Education innovation · COVID-19

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· Blended learning ·

Introduction

On 13th March 2020 it was announced that no in-person classes would be held on campus due to COVID-19 pandemic. We were looking for a solution to run the IoT lab experiments from home and save the semester. We could manage to share some hardware among all students of the class and conduct some lab experiments at home while supervising by the instructor via Zoom. For some other labs, the devices were not portable, or the number of devices were not enough to be distributed to every student. There were also some safety concerns for high voltage labs. This paper presents a remote lab which was used in the online class to enable the students to share a single set of hardware which was located at the instructor’s home and run different experiments remotely. The paper is structured in 5 sections. Section 2 reviews the background and existing alternatives to the in-person labs. Section 3 describes the implementation of the proposed remote lab. Examples of lab experiments are presented in Sect. 4. Section 5 concludes the paper.

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Background

Traditionally, the engineering labs are offered in a space in the schools where educational- or industrial-scale measurement instruments are available. The students will learn different skills such as lab safety, setting-up the devices, collaboration with groupmates, working with real instruments, and data collection. c The Author(s), under exclusive license to Springer Nature Switzerland AG 2021  M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 392–399, 2021. https://doi.org/10.1007/978-3-030-67209-6_42

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They will see errors, noises, disturbances, and imperfections while performing the lab and collecting data. Engineering labs are an inevitable part of engineering education. However, they are usually expensive, have high start-up costs, need special safety requirements, and enforce scheduling constraints. Hence, several groups have been working on alternatives ways to offer engineering labs. The literature on virtual and remote labs from its beginnings to 2015 are analyzed in [3]. 2.1

Remote Lab

Remote laboratory refers to the labs where the system-under-test and the scientist are located in separate geographical locations, and the experiment is conducted using telecommunication technologies. In [6] an inverted pendulum remote lab was implemented by LabVIEW web publishing tool and web server. The hardware was an embedded system based on Arduino UNO micro-controller to control the inverted pendulum. The students could watch the a video stream of the process in real-time using a webcam. Recently, a remote lab based on MQTT communication protocol is reported in [10]. The proposed lab relies on iLab Shared Architecture (ISA) [2]. In general Web-based control of laboratory experiments proved to be an advantageous teaching method [6] because of the flexibility it provides to the students to do the lab at their own pace. A deeper students engagement in the remote labs is reported in comparison to simulation [8]. Remote labs reduce startup costs of laboratories and increase lab safety. The main purpose of remote labs in universities like MIT [5] was to make expensive or dangerous labs accessible for users across the globe. The focus of our work is to offer a free, rapid, flexible, and worldwide accessible remote lab for the time of COVID-19 which would be under full control by the lab instructor. 2.2

Simulation Lab

There exist several simulation tools for engineering labs. MATLAB, for example, provides a variety of libraries for simulating engineering labs. Most of such software are not free, and require installation, and subscription. The data collected in a simulation lab is clean, while real data collected from a physical lab is not. So, the students miss the opportunity to deal with real world data. The lab results are often in the form of animation, text, or numbers, and the students cannot see the actual hardware. A better solution would be using MATLAB Hardware-in-loop, where a combination of simulation and experiment can be used simultaneously. Qbot [4] is an example of such educational devices. 2.3

Virtual Lab

In virtual labs, there is no real hardware. Data collected form these labs are like what can be obtained from simulation. The difference is in the virtual lab,

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the lab environment is also modeled and the students can see the lab as animations. UbiSim [9] is an example of virtual labs that provides a training platform for nurses. The students practice on a virtual patient in virtual environment. Quanser [7] recently released QLabs Controls which interactions with virtual hardware. Detailed models and animations provide a realistic experience. The accuracy of the experiments depends on the accuracy of the models used for virtual hardware. Another type of virtual labs are based on pre-recorded labs. Hence, the data collected from these labs are real while offline. Beyond Labz [1] is an example of virtual labs which covers science courses such as chemistry, biology, and physics. In these laboratories, students find themselves in a virtual environment in front of a virtual bench where they can explore different material and process and see the resulting consequences. 2.4

Mobile Lab

For battery operated electronic labs where the components are not bulky, and the working voltage and current is low, the students can carry out the experiments, and do the experiments individually at home under instructor’s supervision through Zoom. For these labs, the student collaboration is a challenge. Multiple sets of hardware components is needed, which adds a significant cost to the lab.

3

Implementation

The proposed remote lab consists of a single set of smart hardware which is located in the lab, and two Node-red flows for lab and user computers. Node-red is a flow-based programming based on a network of nodes. The system architecture is shown in Fig. 1.

Fig. 1. Remote lab architecture.

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Hardware

The only hardware needed in the student side is a laptop, desktop, or smartdevice which capable or running Node-red. A laptop, desktop, or RPi in the lab side with Wifi connection is also needed. We also need a smart lab device which can be connected to Wifi and controlled via Node-red. In these experiments due to the limited access to the labs and components in the COVID-19 situation, we used home appliances such as hair-dryer, fan, and a wall lamp as systems-under-test. An off-the-shelf smart plug (TP-Link HS-110) was used to control the hardware. The smart plug comes with internal voltage, current, and power sensors and a binary actuator to control on/off state of the device connected to it. The measurements were sent to the lab computer via Wifi connection and sent to MQTT broker through the Node-reed flow which was running on the lab computer. The laptop camera was used to display real-time results to the students. 3.2

Software

The software consists of two flows; The first one runs on the lab computer (Fig. 2), and the second flow (Fig. 3) runs on the student computers. The flows are stored using JSON which can be easily imported in Node-red and shared with others. They can be customized for each lab.

Fig. 2. Node-red flow running on the lab computer.

Figure 3 shows the user flow. In the beginning of the lab, the students enter their student ID in the ID box of Fig. 3a. The template provides two period of a square wave with pulsewidth of 50% and period of 100 ms. The students can modify the parameters of this flow to send their desired waveform. The measurement responses from the lab device are sent to the MQTT broker. All the user flows would receive the messages. The CheckID box in Fig. 3b would filter the responses, and keep only the measurements which are a response to the particular student who originally sent the command to the hardware. The flow which is running on the lab computer is shown in Fig. 2. When a message is

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(a) User command along with student ID are being sent to the MQTT broker from student’s computer.

(b) Measurements from the remote lab hardware are received via MQTT broker by student’s computer.

Fig. 3. Node-red flow running on the students’ computers.

received from the MQTT broker, the student ID is extracted from the message, and saved locally. The message will then be sent to the smart switch (TP1) to turn it on or off. Consequently, a measurement request is being sent to the smart plug to measure real-time current, voltage, and power. The student ID which was saved locally, would then be attached to the measurement value and sent to the MQTT broker. 3.3

System Setup

The smart device needs to set up once by connecting to the Wifi and computer. After each experiment is finished by an student, the hardware automatically goes to its initial stage via clean session request. It will make the shared hardware ready for the next user. Using the static IP for the smart device, the lab can be run without the presence of a lab technician. The event poll interval of the smart plug TP-link HS-110 is 500 ms–3000 ms. This is good enough for a variety of mechanical and mechatronic experiments where sampling rate of 2 KHz is acceptable. If we have n students in the class, in the worst case scenario the wait time for a user would be T × (n − 1), where T is the length of each test (around a few seconds). In reality, the students have different pace, and they start the actual experiment in different time slots in the class, so the wait time is even less. We can also include lab questions, video, readings, and lab experiments in different orders in a lab session. It will reduce the probability that multiple users need to access the

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device at exactly same time, hence reduces the wait time. The other solution to reduce the wait time is to reduce the length of each experiment. For this purpose, we need a higher sampling rate device. In the next session some examples of experiments which were conducted by this set-up are described.

4

Sample Experiments

In this section, a few experiments which were run with this set-up are described. The emphasis is on observation of the phenomenon which cannot be experienced in the simulation. It includes system identification, observation of outliers, and step response of a fan. More complex experiments can be conducted based on the requirements of each lab session. 4.1

System Identification

The hardware used for this experiment is a hair drier. The hair dryer have two control switches; upper switch (U) which controls the heat and has three states, and lower switch (L) which controls the air flow and have two states. The combination of the switches gives us six different modes of operation.

(a) U1L1.

(b) U3L2.

Fig. 4. Data collected remotely from different modes operation of the hair dryer.

The students can send different on/off patterns to the hair dryer and collect electrical data remotely. Figure 4 show the current response for two modes of operation. In this experiment, the on/off duration of the switch was 10 s. After all students collected the data for all modes of operation, the lab instructor would set the dryer on a mode of operation which is not revealed to the students. They will run the experiments to identify the mode of operation. Similar types of classification experiments can be used for remote lab exams.

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Cleaning Data

Here, an example of a lab experiment is shown where students can observe outliers from a current measurement of the hair dryer (Fig. 5).

Fig. 5. Observation of outliers in the data collected form current measurement of hair dryer in mode U1L1.

In a real lab experiment, outliers may be observed due to several reasons including measurement errors, or ambient noises and disturbances. This is an advantage of using a remote lab instead on simulations. The students will collect and work with real data. They might need to repeat the experiments or use statistical skills to clean the data. 4.3

Step Response

In another experiment, a fan was controlled remotely, and the current, voltage, and power measurements were collected. Figure 6 shows the step response of the fan. The student can measure the time constant in this type of experiments.

Fig. 6. Remote observation of step response of a fan from measurement of current.

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Conclusion

In this paper a remote lab was presented which could address the physical lab access challenge during COVID-19 pandemic. The lab was originally designed in an IoT course, and can be extended to other subjects. The students of a class share a single set-of hardware which is located in the remote lab. Examples of data collected remotely was presented in the paper. The proposed remote lab runs on several operating systems. It is free, thanks to Node-red open source access, and free MQTT brokers. The lab is very flexible, and can be modified by the students or lab instructors from different backgrounds to fit their experiments. The lab is globally accessible, no special access to the school VPN or network is required. A post class survey revealed 71% of student prefer remote lab with integrated physical components over pure simulation.

References 1. Beyond Labz. https://www.beyondlabz.com/ visited on 30 May 2020 2. Harward, V.J., et al.: The iLab shared architecture: a web services in- frastructure to build communities of internet accessible laboratories. Proc. IEEE 96(6), 931–950 (2008) 3. Heradio, R., et al.: Virtual and remote labs in education: a bibliometric analysis. Comput. Educ. 98, pp. 14–38 (2016). https://doi.org/10.1016/j.compedu.2016.03. 010. http://www.sciencedirect.com/science/article/pii/S0360131516300677. ISSN: 0360-1315 4. Huq, R., et al.: QBOT: an educational mobile robot controlled in MATLAB Simulink environment. In: 2009 Canadian Conference on Electrical and Computer Engineering, pp. 350–353 (2009) 5. iLabs. http://icampus.mit.edu/projects/ilabs/.Visited on 30 May 2020 6. Issa, A., et al.: Remote computer based learning system for inverted pendulum lab experiment. In: 2018 International Conference on Promising Electronic Technologies (ICPET), pp. 113–117 (2018) 7. Quanser Interactive Labs. https://www.quanser.com/digital/quanser-interactivelabs/. Visited on 30 May 2020 8. Sauter, M., et al.: Getting real: the authenticity of remote labs and sim- ulations for science learning. Distance Educ. 34(1), pp. 37– 47 (2013). https://doi.org/10. 1080/01587919.2013.770431. 9. UbiSim. https://www.ubisimvr.com/. Visited on 30 May 2020 10. Uhlmann, T.S., et al.: ELSA-SP – Through-the-cloud subscribe-publish scheme for interactive remote experimentation under iLab Shared Architecture and its application to an educational PID control plant. In: 2019 5th Experiment International Conference (exp.at 2019), pp. 58–62 (2019)

The Impact of a Gamified E-Learning Environment in Students Attitude: A Case Study Marcos M. Tenório1(&) , Francisco Reinaldo1 , Vitor Gonçalves2 , Eliana C. Ishikawa1 , Lourival A. Góis1 and Guataçara dos Santos Jr1 1

,

Federal University of Technology - Paraná, Curitiba, Brazil [email protected] 2 Polytechnic Institute of Bragança, Bragança, Portugal

Abstract. E-learning conditions underpin the teaching and learning procedure and plan to involve students in their insight development process. Notwithstanding, including them during this procedure requires a high level of inspiration. Gamification is one of the methodologies that address this challenge and proposes that on-line situations are going to be a plus from it. On the other hand, Statistics is a field that can be supported by these learning methodologies. These days, with the use of massive data, the information holds a critical worth and to process this information into valuable data empowers the statistics field as a basic subject. This paper expects to feature a replacement point of view over the teaching and learning process offering a gamified e-learning condition to support the statistics field in the class. To research and portray the increases of this system, we refine a contextual investigation strategy to a Probability and Statistics lecture of an undergraduate Engineering course. With a descriptive study, we decide to comprehend the students’ attitudes once they face the proposed gamified e-learning condition. The results indicate that were some changes on students’ attitude when they use the gamified approach and suggest that we can be on the right track regarding the application of innovative learning formats, especially in the use of ICT. Keywords: Gamification


E-learning
Attitude towards statistics

1 Introduction E-learning environments support collaborative activities between teachers and students. This implies plenty of methods to build and oversee instructive exercises [1]. Instructive techniques, built over levels, conjure students in their insight development. In any case, involve them into this process it is still a challenge [2], gamification seems The original version of this chapter was revised: The author’s name has been corrected to “Gonçalves V.”. The correction to this chapter is available at https://doi.org/10.1007/978-3-030-67209-6_61 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021, corrected publication 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 400–410, 2021. https://doi.org/10.1007/978-3-030-67209-6_43

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to be having support for that. Thus, gamification is a technique that may improve elearning situations. Likewise, it is highlighted to promote the use of game design elements in non-game settings. Consequently, gamification contributes to learners’ involvement during their use [3]. Hence, an e-learning proposition with those highlights has risen, as introduced in [4]. e-Class platform emerges in this paper as an instructional e-learning environment to encourage students’ participation in a virtual class. Using gamification elements gathered from the literature [5], e-Class was modeled with the property of virtualizing genuine instructing and learning situations as well as to settle on choices about student yields. In this research, we choose the Probability and Statistics scenario in Higher Education since it is hard to be virtualized, as indicated by [6]. Nowadays, the information holds a significant value in society and this conventional study hall course has become a significant apparatus for a few fields, supporting its appropriation. In this vein, e-Class was applied during a full academic semester. The primary objective is to gather students’ behavior data such as participation, motivation, engagement, incentive, and others that allow us to identify the effects of positive or negative discipline behavior in terms of student’s attitude. Thus, the SATS instrument (Survey of Attitude Towards Statistics) [7] told us the best way to line up students’ attitudes with the subject in question and how these factors allow the adoption of strategies to increase the efficiency of teaching Probability and Statistics [8]. This paper describes the e-Class platform as an e-learning environment which as built over Gamification concepts and provided by a huge Probability and Statistics students’ behavior data in Higher Education. The article additionally discusses one of the primary commitments of the environment, considering the adjustment in attitude that can generate in the students associated with this methodology.

2 eClass The e-Class platform is a user-friendly web-based system hosted at estatistica.ipb.pt. This platform was carefully modelled over three main modules, such as (i) Content Management, (ii) Student Interactions, and (iii) Learning Activities. On this first module, students access the course content provided by the teachers, such as class notes, plans, study guides, textbooks, and others. The second module provides resources for interaction among students. Thus, students exchange information and experiences in forums and also share documents. The last module is the core of the gamification approach. Teachers inject questions to students come in to solve them when performing activity tests. In each virtual activity test, students may choose the content and set the range of skill parameter (from easy to difficult). After that, a set of randomly selected questions is provided (Fig. 1). Unlimited trials are allowed, however, limited resources induce students to explore different contents and parameters. Additionally, this approach uses a ‘sandbox-style’ game, signing there is no linear narrative structure [9]. At the end of the virtual activity test, instant feedback is provided with the performance results. Here, gamification aims to involve students in such activities and guide them in an appropriate pedagogical sequence.

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Fig. 1. Learning Activities module during use

In the eClass, the feedback is not limited to students. On the teachers’ side, each students action are reported like forums, content, interactions and activity tests. Teachers access all activity test attempts and may identify issues and routes chosen by each student. This feature allows professors to make decisions and act based on these reports. They may use this tool to provide formative or summative assessments in runtime. Ultimately, the e-Class also suggests a final score based on students’ performance. 2.1

A Gamified Structure

Gamification offers mechanisms to reach a game-like approach. In e-Class, we implemented Experience Points (EXP), Badges, and Virtual Coins (eCoins). All these three engines have the role of encouraging users during virtual class. There are also other elements to virtualize the real student environment, such as timeline, progress bar, limited resources, time restrictions, exchanges, feedback, and others. However, the elements were addressed mainly to the Learning Activities module, this means students are guided during the set of parameter choices that implies in rewards. The Experience Points (EXP) engine controls numerical values, like a score, that each student collects through the EXPi sum function. Mainly on the Learning Activities module, EXPi is earned when an activity test is performed, Eq. (1).

ð1Þ

Where j is the number of attempts within a parameter set and performance is the score (0–100) result of the activity test. Here, the EXPi value decreases when the same

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parameters are chosen. In general, the EXP is a broad measure of success on assessments, at the same time guide the students on the parameters choices. In addition, some authors suggest that students are motivated when use this element and this can increase the users’ involvement [10, 11]. Virtual Coins also follow the EXP principle but changes the earnings according to the chosen difficulty, Eq. (2). eCoin ¼ ðEXPi=10Þ  dif

ð2Þ

Where, dif is the difficulty parameter chosen by the student (1–3). The eCoin is a virtual asset that can be exchanged in easiness on future activity tests. Although this element is underreported in the literature it is useful when students see it as a reward and progress measure [12]. On the other hand, Badges are well explored in gamified environments and usually accredit attitude or behavior [13]. Here, they were designed to recognize and accredit experiences and actions in each module (Table 1). Table 1. Badges Module

Actions

Layout

Access

a) Loggin in frequently

Forum

a) Publish b) Generate comments

a)

b)

Extra Content

a) Publish b) Generate downloads

a)

b)

Activity

a) Perform activity without trades b) Explore difficulty 1 activities c) Explore difficulty 2 activities d) Explore difficulty 3 activities

a)

b)

c)

d)

a)

Each rightful action results in a badge and more repetition improves this badge. This implies smaller goals within each action. High-level badges represent higher value with different layout and colors replacing previous ones. Badges are shown to students as soon as they earn them, then they are shown in the profile crediting their experiences and actions [14].

3 Attitude Towards Statistics Attitude is characterized as the individual’s predisposition while responding favorable or unfavorable to objects, circumstances, facts, individuals, or propositions [15]. Attitude is not behavior nor motivation, although it is characteristically identified with them.

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Some authors recommend that this inclination is conceivable to be altered, given the way that it endures impacts and changes with circumstances or environment [16, 17]. Inside instructing and learning environments, the students’ attitude is mainly expressed through feelings of engagement, participation, motivation, and others. These feelings are driven to the course or class content. The comprehension of these issues permits us to adopt methodologies to impact positive attitudes and increase efficiency in the instructing and learning conditions [16]. To gather the students’ attitudes information inside the Statistics field, we have chosen the Survey of Attitudes Toward Statistics (SATS). This because of the most grounded confirmation about form authenticity and inside consistency [7]. This review grants us to assess students’ replies going up against a situation where they need to utilize the learned statistical content [18]. The SATS, introduced in Table 2, is composed of 28 Likert-type scale items that assess each of the four dimensions of students’ viewpoints. Those dimensions cover attitudes, such as (a) Affect – students’ positive and negative feelings concerning statistics, (b) Cognitive Competence - attitudes about intellectual knowledge and skills when applied to statistics, (c) Value - attitudes about the usefulness, relevance, and worth of statistics in personal and professional life, and (d) Difficulty - attitudes about the difficulty of statistics as a subject [7]. Table 2. SATS Affect 1. I will like statistics. 2.* I will feel insecure when I have to do statistics problems. 11.* I will get frustrated going over statistics tests in class. 14.* I will be under stress during statistics classes. 15. I will enjoy taking statistics courses. 21.* I am scared by statistics. Cognitive Competence 3.* I will have trouble understanding statistics because of how I think. 9.* I will have no idea of what's going on in statistics. 20.* I will make a lot of math errors in statistics. 23. I can learn statistics. 24. I will understand statistics equations. 27.* I will find it difficult to understand statistics concepts.

Value 5. Statistics is worthless. 7. Statistics should be a required part of my professional training. 8.* Statistical skills will make me more employable. 10.* Statistics is not useful to the typical professional. 12.* Statistical thinking is not applicable in my life outside my job. 13. I use statistics in my everyday life. 16.* Statistics conclusions are rarely presented in everyday life. 19.* I will have no application for statistics in my profession. 25.* Statistics is irrelevant in my life. Difficulty 4. Statistics formulas are easy to understand. 6.* Statistics is a complicated subject. 17. Statistics is a subject quickly learned by most people. 18.* Learning statistics requires a great deal of discipline. 22.* Statistics involves massive computations. 26.* Statistics is highly technical. 28.* Most people have to learn a new way of thinking to do statistics

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This scale ranges from 1 (“Strongly disagree”) to 7 (“Strongly agree”), yet 4 (“Neither disagree nor agree”) is the center term. All reaches, with higher evaluations, show a progressively uplifting order. The items comprising each attitude dimension are averaged to yield the score for that dimension and some specific items (*) have reversed the responses to the negatively worded items. In the end, it is possible to evaluate students’ responses when confronting a circumstance where they should utilize the learned statistical content. In such cases, the attitude can turn into a facilitator or a snag to students learning. Thus, it is important to understand these issues to promote positive attitudes in students [16–18]. In [18] several similar studies with SATS are compared and the author verifies that, normally, there is a direction to reduce attitude values during the course, since the students become aware of the discipline in time. In the Statistics context, [19] demonstrate unfavorable attitudes in the difficulty dimension, however a general reduction in attitude indexes in the posttest. The general reduction trend was found even in the scale validation [7]. Subsequently, the same author reports that in most favorable results, a new method or innovative learning format was applied [18].

4 Method To research and portray the increases of this system, we refine a contextual investigation strategy to a Probability and Statistics lecture of an undergraduate Engineering course. A descriptive study was chosen to understand the students’ attitudes since they face the proposed gamified e-learning condition. The study was approved by the Research Ethics Committee (CEP - UTFPR) under process number 00976418.6.0000.5547, being both ethically and methodologically adequate regarding the researches with human beings. The students of Probability and Statistics were participants to this research during a semester of an engineering course at the Federal University of Technology - Paraná (UTFPR), Brazil. From the beginning of the semester, the students have logged to the system, receiving initially instructions about how to use the modules and concerning its general functioning. The statistics analysis was performed using the SATS instrument described before (Table 2). All positive and negative statements regarded in Statistics about the four dimensions of the attitude were made. When collecting students’ attitudes, [7] recommends two application moments, the pretest and posttest. So as to grasp the attitude differentiation when the e-learning is applied, as suggested by Schau [7], the pretest was applied at the first three weeks of the semester and the posttest one week before the final exams. There were 45 students responding the questionnaire, however 37 students answered both the pretest and the posttest. Here, only the 37 students who participated in both moments were considered for analysis. To proceed with the statistical analysis, first the internal consistency of the scale was measured using Cronbach’s alpha (ac). Reduced ac values may suggest inadequate interpretations of the questions, impairing a dimension consistency. Table 3 shows the collected values.

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Items 6 6 9 7

ac pretest 0.81 0.81 0.62 0.42

ac posttest 0.70 0.75 0.77 0.67

ac suggested 0.80 a 0.89 0.77 a 0.88 0.74 a 0.90 0.64 a 0.81

To adjust the dimension ac to suit Schau’s recommendation, or at least reach the ac recommended for Likert scale questionnaires (ac > 0.7), it is possible to remove some items that most harms the results. Here, items that would significantly increase reliability were identified and removed: Statement 15 and 26. Table 4 shows the ac final values. Table 4. Adjusted Cronbach Alpha Attitude dimensions Affect Cognitive Competence Value Difficulty

Items 5 6 9 6

ac pretest 0.83 0.81 0.62 0.61

ac posttest 0.75 0.75 0.77 0.69

ac suggested 0.80 a 0.89 0.77 a 0.88 0.74 a 0.90 0.64 a 0.81

Finally, after the items removal, we reach an acceptable ac value to Likert-type questionnaires to the majority of dimensions. Further removals was not favoring the internal consistency of the scale. Then, statistical analysis was performed.

5 Results Table 5 presents the descriptive statistics of the values collected from the pretest and posttest. Here, each dimension presents a value between 1 and 7, meaning higher the value, more positive the students’ attitude towards this dimension. Table 5. Descriptive Statistics of Attitude Towards Statistics Affect

Average (M) 1º Quartile Median (MD) 3º Quartile Standard Deviation (s) Coefficient of Variation (CV)

pre 4.71 3.60 5.00 5.40 1.31 0.28

post 4.78 4.00 4.80 6.00 1.15 0.24

Cognitive Competence pre post 4.91 4.88 4.00 4.17 5.17 4.83 5.67 5.83 1.04 1.00 0.21 0.21

Value pre 6.21 5.89 6.11 6.67 0.55 0.09

Difficulty post 6.07 5.67 6.22 6.67 0.67 0.11

pre 3.71 3.17 3.67 4.33 0.87 0.24

post 4.02 3.33 4.00 4.33 0.97 0.24

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A boxplot graph was built to explain another perspective, including the dimensions and intervals (quartiles), Fig. 2.

Fig. 2. Boxplot of Attitudes Towards Statistics

The statistical results bring some significant contemplations concerning the connection between the attitude measurements and the eClass environment. Initially, the Affect dimension showed attitudes with a slight negative trend, especially in the pretest. In the posttest, the boxplot suggests an apparent improvement in the indices, with less variation. To measure this difference, a Hypothesis Test was performed, using the t-test statistic with 95% confidence level (a = 0.05). The Hypothesis Test shows that there were no significant difference for this dimension between the pre and the posttest (p = 0.72). Still, two statements in this dimension proven a significant change: Statement 2 (p = 0.04) and 14 (p = 0.02). Statement 2 showed the lowest average on pretest (Mi2-pre = 3.9), proving that students felt insecure when studying statistics. In the posttest, there is a statistically significative increase (Mi2-pos = 4.5), meaning that students did not feel so insecure afterwards. Statement 14 also shows a significant increase in the posttest (Mi14-pre = 5.2 to Mi14pos = 5.9), demonstrating that students were not so tense with the discipline afterwards. In the Cognitive Competence dimension, most students scored average values close to 5. The Hypothesis Test shows that, with 95% confidence, there was no significant difference from the pretest to the posttest (p = 0.87). Besides, inside this dimension no item showed a significant difference, even so, in the item 20 presented a lower average in both tests (Mi20-pre = 4.1 and Mi20-pos = 3.8), stating that they make math errors when doing the statistical calculations. In the Value dimension, students showed the best attitudes (MVALUE-pre = 6.2 and MVALUE-pos = 6.1) and low variation (CVVALUE-pre = 0.09 and CVVALUE-pos = 0.11). It is also worth to noted that the posttest shows attitudes with a slight reduction when compared to the pretest. The Hypothesis Test demonstrated, with 95% confidence, that there was no significant difference in this dimension (p = 0.08). Several items of this dimension showed the same values in the posttest (items 5, 7, 8 and 25). Items 12, 13, 16 and 19 showed a small reduction, with item 13 having the lowest average in both tests (Mi13-pre = 5.0 and Mi13-pos = 4.7). It is worth mentioning that the values of

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attitude towards this dimension are still high, and students continue to have positive attitudes towards the value of statistics. The Difficulty dimension had the lowest rates of attitudes in the pretest. However, the posttest shows an increase. The Hypothesis Test shows that, with 95% confidence, there is a significant difference in this dimension (p = 0.03). Items 18 and 17 in the pretest showed the lowest averages (Mi18-pre = 2.9 and Mi17pre = 3.3), where they considered that to learn statistics it is necessary to have a great deal of discipline and it is hard to be learned by most of people. In the posttest, all items showed improvement and items 4 and 6 reached a higher average (Mi4-pos = 4.9 and Mi6-pos = 4.6). This suggests that, in the posttest, the students found it easier to understand the statistical formulas and that the subject later presented itself as less complicated.

6 Conclusions The results analysis collected through SATS with the eClass bring some important considerations especially in Attitude dimension. Initially, the feeling of affection, during the affect dimension was raised from pre to posttest, increasing the average, and reducing the standard deviation. In any case, a Hypothesis Test showed no significant difference between pre and posttest, only just two items that accomplished noteworthy improvement and show students losing their fear of the discipline. By allowing constant connection with the discipline, one of the main goals of eClass planning, students end up losing the fear of the discipline and felt more secure. In the Cognitive Competence dimension, it is hard to establish a causal relationship, as there was no significant difference. The interesting point here is the student’s difficulty reported in mathematical calculations and statistical concepts. This is a signal to the eClass and the discipline, they must pay attention at the students’ difficulty with such issues and work with this. In the Value dimension, there were higher attitudes on both tests and no significative distinction. The items related to the statistics usage outside the academic environment present reduction in posttest. This suggests that, after advancing the specific contents, students became more aware of the discipline content, rethink their responses and reduce the value of the statistic regarding workplace and everyday life. In the Difficulty dimension, students initially presented a negative perception about it. The Hypothesis Tests show a significant difference on the posttest. This improvement exhibit that students change their opinion on the discipline difficulty, showing that now it is easier to understand statistics formula and believing that it is possible to learn this subject. As noted in the Affect dimension, the use of eClass may have facilitated the process of understanding statistics and changed students’ perception of their difficulty. The results expressed in this study comes to reinforce Schau’s theoretical consideration, suggesting that a innovative teaching environment, apart from traditional ones, involves the student in a new learning format, favoring the attitude.

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When considering that e-Class usage may favored the students’ attitudes, it is possible to consider that several factors may also be positively influenced, especially in Probability and Statistics learning. Although it is out this work bounds, there are some literature studies that draw this comparison and states that even academic performance can be favored by attitude [16, 17, 19]. There are obviously changes in the eClass, or even in the discipline structure, which can further improve attitude rates. Even so, what we have so far is a strong evidence that we can be on the right path regarding the innovative learning formats.

References 1. Prensky, M.: Digital natives, digital immigrants Part 1. On The Horizon 9, 1–6 (2001) 2. Valente, L., Moreira, P., Dias, P.: Moodle: Moda, Mania ou Inovação na Formação? In: Moodle: estratégias pedagógicas e estudo de caso, pp. 35–54 (Universidade do Estado da Bahia (2009) 3. Deterding, S., Khaled, R., Nacke, L., Dixon, D.: Gamification: toward a definition. In: CHI 2011 Gamification Workshop Proceedings, pp. 12–15 (2011) 4. Tenório, M.M., Lopes, R.P., Góis, L.A., dos Santos, G.: Design and evaluation of a gamified e-learning system for statistics learning activities. Literacy Inf. Comput. Educ. J. 10, 8 (2019) 5. Tenório, M.M., Reinaldo, F.A.F., Góis, L.A., Lopes, R.P., dos Santos, G.: Elements of gamification in virtual learning environments. In: Auer, M.E., Guralnick, D., Simonics, I.: Teaching and Learning in a Digital World, pp. 86–96. Springer, Cham (2018) 6. Moura, G.M., Samá, S.: Blended learning potencializando a aprendizagem da estatística no ensino superior. Inform. Educ. 20 (2017) 7. Schau, C., Stevens, J., Dauphinee, T.L., Vecchio, A.D.: The development and validation of the survey of antitudes toward statistics. Educ. Psychol. Measure. 55, 868–875 (1995) 8. Singh, K., Granville, M., Dika, S.: Mathematics and science achievement: effects of motivation, interest, and academic engagement. J. Educ. Res. 95, 323–332 (2002) 9. Cipollone, M., Schifter, C.C., Moffat, R.A.: Minecraft as a creative tool: a case study. Int. J. Game-Based Learn. 4, 1–14 (2014) 10. Attali, Y., Arieli-Attali, M.: Gamification in assessment: do points affect test performance? Comput. Educ. 83, 57–63 (2015) 11. Hew, K.F., Huang, B., Chu, K.W.S., Chiu, D.K.W.: Engaging Asian students through game mechanics: findings from two experiment studies. Comput. Educ. 92–93, 221–236 (2016) 12. Robinson, D., Bellotti, V.: A preliminary taxonomy of gamification elements for varying anticipated commitment. In: Proceedings of ACM CHI 2013 Workshop on Desining Gamification: Creating Gameful and Playful Experiences, ACM (2013) 13. Abramovich, S., Schunn, C., Higashi, R.M.: Are badges useful in education?: it depends upon the type of badge and expertise of learner. Educ. Technol. Res. Dev. 61, 217–232 (2013) 14. Dominguez, A., et al.: Gamifying learning experiences: practical implications and outcomes. Comput. Educ. 63, 380–392 (2013) 15. Guilford, J.P.: Psychometric Methods, McGraw-Hill (1954) 16. Gal, I., Ginsburg, L., Schau, C.: Monitoring attitudes and beliefs in statistics education. In: The Assessment Challenge in Statistics Education, pp. 37–51. IOS Press (1997)

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17. Chiesi, F., Primi, C.: Assessing statistics attitudes among college students: Psychometric properties of the Italian version of the Survey of Attitudes toward Statistics (SATS). Learn. Individual Differences 19, 309–313 (2009) 18. Schau, C.: Students’ attitudes: the “other” important outcome in statistics education (2003) 19. Mantovani, D.M.N., Viana, A.B.N.: Atitudes dos alunos de Administração com relação à Estatística: um estudo comparativo entre antes e depois de uma disciplina de graduação. Revista de Gestão 15, 35–52 (2008)

Lessons Learned from Sudden Transition to On-line Learning Dana Perniu, Ileana Manciulea, Codruta Jaliu, Liviu Perniu, Anca Vasilescu, and Camelia Draghici(&) Transilvaia University of Brasov, 500036 Brasov, Romania {d.perniu,c.draghici}@unitbv.ro

Abstract. The sudden shift from the lecture theatres and laboratories to a laptop or smart phone screen due to the restrictions caused by the pandemic 2020 crisis, changes the students’ way of working in the academic environment. The present paper investigated the engineering students’ perception of the changes occurred during this period. The investigation was based on a questionnaire, aiming to point out evidences on premises which can be used in designing new learning environment in the future. Promising premises regarding students’ willingness for learning in on-line environment exist, and this can push the on-line learning to become a consistent part of the curriculum. There will be necessary a special focus on courses design and also on remedial consultancy for students for their personal development. Keywords: On-line learning during coronavirus crisis learning


Transition to on-line

1 Introduction The 2020 global pandemic event due to the spread of the new COVID-19, caused unprecedented changes and challenges in all sectors of the socio-economic system, affecting everyday life aspects [1]. The educational system is facing the transition to on-line activity, no matter if it was or not prepared for this shift, the main challenges being the access to technical infrastructure, competence and pedagogies for on-line learning and the requirements of specific fields of study [2]. At the same time, the forced transition offers opportunities to propose more flexible learning possibilities and to explore blended learning [2]. From the mechanism of change theory in organization, is known that growth is tied with the crisis. The change is expected to occur when the positive forces act as drivers and the negative ones are counterbalanced [3]. The systems theory explains the steps a system passes when a disruptive event takes place. When a disruptive event acts on a system existing in its original state, the system enters in disrupted state, characterized by vulnerability and survivability actions. In response, a recovery action takes place enabling the system to recover, by re-establishing its structure and relations to enter in a stable recovered state [4]. When these assumptions are translated to the educational system during and after the pandemic crisis, it is assumed that the system, after the crisis will be recovered and © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 411–418, 2021. https://doi.org/10.1007/978-3-030-67209-6_44

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brought to a new stable state. Compared with the initial state, the new one might represent growth if the internal structure and relationships are exploited as positive forces to drive the change. The recovery is complex, it involves both top-down and bottom up approaches, and is under debate at international level [5]. Considering that students are the main actors in the educational system, and each action is taken need to be based on evidences [6] and addressed from their perspective [7], the investigation was conducted to explore the students’ view on the experience they went through the pandemic crisis, as basis for designing transition to digitalization of the higher education, as desideratum, at least at the local level.

2 Data Collection and Interpretation 2.1

The Questionnaire Development

To investigate the engineering students’ opinion on the factors influencing their own learning in the forced on-line environment, a questionnaire was developed and applied. The questionnaire, based on Likert-scale items, comprises 25 statements, clustered in six groups: 1. The use of computers as a habit and the equipment availability. The general term of “computer” was used to denote the electronic learning environment; 2. The personal motivation for studies (personal satisfaction, perceived usefulness of the studies in socio-economic system, and learning willingness), as premises for learning efficiently; 3. The perception of the sudden transition for the on-line learning, as developing negative emotions and feelings; 4. The perception of the on-line learning as new, accepted behavior, after the (almost) one-semester experiencing; 5. The students’ insights regarding the educational approach, the “student-centered approach” versus “teaching-centered approach” as premise for the on-line learning; 6. The students’ willingness to be involved in future on-line learning experiences. The target group for the study consists of undergraduate students, involved in engineering (e.g. mechanical engineering, industrial engineering, environmental engineering, electrical engineering, and also computer sciences) study programs. Students’ opinion on each statement was quantified (−2 for strongly disagree - SD, −1 for disagree - D, 0 for neutral - N, +1 for agree - A, and +2 for strongly agree - SA) and average value for each item (or group of items) was calculated and/or represented in graphical format. The Google Forms application was used for development of the questionnaire and data collection. 2.2

Students’ Responses Interpretation

As it has been mentioned, the investigation targeted the students following engineering studies, including computer sciences, in Transilvania University of Brasov, Romania, after experiencing on-line learning using the Moodle platform implemented at the

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university. The questionnaire was distributed after the official restrictions period ended (i.e. mid of May, 2020), and it was available for responses during one week. A total number of 257 students responses was registered, from which 131 are involved in computer sciences studies (CS) and 126 in other engineering studies (ENG) running the university.

% of responses

The Use of Computer as a Habit. A basic premise of the on-line learning is the use computers as a habit, since now-a-days students belong to the “digital native” generation [8]. It is known that the technology become an indivisible part of the higher education landscape, even the system is still anchored in traditional learning approach. From Fig. 1 can be depicted the information that the majority of the students highly appreciate the use of computers both for their studies (statement G_1) and for general purpose (statement G_2). During the period involved in the study, the students were not in the university campus, therefore, the lack of equipment (computer/internet connection) was reported as restriction by some students from the ENG group (statement G_3). This lack of equipment may have negative consequences in accepting/practicing the on-line learning.

70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 G_1 SA

G_2 A

N

D

G_3 SD

Fig. 1. Students’ habits in computer use: G_1 - The use of the computer was a habit, for information in the field of study; G_2 - The use of the computer was a habit, for communication, e-mail, social platforms; G_3 - During the online learning period I had difficulties generated by the lack of equipment (laptop, internet).

Premises for Learning Efficiency. As premises for efficient learning (in general and also in on-line environment) were considered the motivational factors as learning willingness, perception of the studies utility in socio-economic environment, students’ satisfactions towards their studies and also the habit of using computers in learning context. It was registered a general positive appreciation of this issue, (1.22 as general average value), the students involved in Computer science studies having a more positive perception (1.55 as general average value) than the engineers’ ones (Fig. 2).

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average score

2 1.5 1 0.5 0 P_1

P_2

P_3

CS students

all students

P_4

Fig. 2. Premises for learning efficacy: P_1 - I am satisfied with the chosen field of study, I feel that it suits me; P_2 - I am confident that the chosen field of study is important for the socioeconomic environment; P_3 - I have always enjoyed learning from any event I have attended, either inside or outside the school; P_4 - The use of the computer was a habit, for information in the field of study

The Perception of Sudden Transition to On-Line Learning. The crisis situation caused by the Coronavirus diseases was governed by negative emotions, feelings, influencing the daily activity [1]. The general students’ opinion can be generally described as being a slightly intriguing situation demonstrated by the general average score of 0.44. The value is in fact obtained from very different values between the two groups of students. The general score for the CS students was −0.01, reflecting a quite balanced perception, coming both from positive and negative opinions. The average general score of 0.91 registered for the ENG students, reflects the negative perception of the sudden transition to the on-line learning. The scores for each statement are presented in Fig. 3. A detailed examination of the answers was done for the statement S_4, to have a deeper understanding of the group of students who declared the working load as overwhelming. In this respect, the students’ who rated S4 with “strongly agree” (score 2), were identified as not frequent computer users, those who perceived the transition like a shock (average score 1.09), declared negative feelings (score 0.9) and physical discomfort (score 1.22). The Habit in On-line Learning. Even for a short time, and during “forced” conditions, on general average, the students are getting used with the on-line learning. The general score was 0.39, but with significant differences between the two students groups: 0.08 average score for ENG students and 0.39 for CS students. As Fig. 4 reveals, both groups agreed that they are getting used with the on-line working, but, as result of working load, the free time is differently perceived (statements H_2 and H_3). The CS students declared their involvement in activities others than those related for the faculty and also for enjoyable ones, which would be necessary to cope the COVID19 associated negative feelings [1]. Contrary, the ENG students declared a lower

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involvement in such activities, fact that can be corroborated with the negative emotions and feelings (statement S_2), Fig. 3.

S_4 S_3 S_2 S_1 -0.50

0.00

0.50 average score

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1.00

1.50

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Fig. 3. Students’ perception of the sudden transition: S_1 - The sudden transition to online education I felt like a shock; S_2 -The sudden transition to online education caused me negative feelings (anxiety, sadness, fear); S_3 - Practicing online education during the state of emergency caused me physical discomfort (back pain, eye problems, etc.); S_4 - The workload for covering the study tasks seemed overwhelming

H_3 H_2 H_1 -0.5

0

0.5

1

1.5

average score CS students

ENG students

Fig. 4. Students’ perception on the habitude to use on-line learning: H_1: During the two months of teaching-learning online, I got used to the way I work; H_2: During the two months of learning online, I had time to carry out other activities that I enjoy; H_3: During the two months of learning online, I had time to carry out other activities, for which I have obligations, in addition to those related to the faculty.

Educational Approach. Students’ perception on educational approach followed two directions: (a) the perception of own behaviors during the envisaged period, to get the impression about the premises of a leaner – centered approach of the educational

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process (statements EA_1 – EA_4), and (b) the perception of the teachers’ role (statements EA_5 – EA_7). As general remark, the students declared a low level of experiencing behaviors that fit into the student-centered learning approach, with slight differences between the two groups: the average score of 0.19 for all respondents and 0.25 for the CS group and 0.12 for the ENG one. In the case of statement EA_2 (Fig. 5), where the time management ability was put into discussion, all students (on average) registered a slight negative score. This value can be corroborated with their high perception of overwhelming due to work load (statement S_4), with the perception of low involvement in different activities (statements H_2 and H_3), and also with perception of on-line learning as providing a flexible learning opportunity (statement EA_4).

EA_7 EA_6 EA_5 EA_4 EA_3 EA_2 EA_1 -1.00

-0.50

0.00

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CS_students

0.50

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Fig. 5. Students’ responses regarding the perception of the educational approach during the online learning: EA_1: During the two months of learning online, I learned to be more responsible for my own learning; EA_2: During the two months of online learning, I learned to better organize my study time; EA_3: During the two months of learning in the online system I had moments of reflection, of self-knowledge; EA_4: In general, I believe that the great advantage of learning online is that I can (or could) learn at my own pace, without being constrained by a certain time interval; EA_5: I received feedback from most teachers when I had tasks to solve, and this helped me in learning; EA_6: After the online learning experience I realized that the teacher can offer me support for learning in different ways, not just through face-to-face activities; EA_7: After the experience of online learning, I realized that the teacher is the only one who can tell me what to learn

For the CS students a higher level of on-line learning appreciation as learning in own pace opportunity was registered, compared with the ENG students. This significant difference might be caused by the pedagogical approach of the courses they attended.

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Considering the teachers’ role perception, differences between the two respondents groups are registered. All students appreciate the role of the teacher in supporting the learning process (Fig. 5, statement EA_6). The CS group of students are more independent in learning, as they had significant lower level of assessment of the statement focusing on the teacher-centered approach of the instructional process (EA_7). A value close to the neutrality was registered for the students form the ENG group, but this came from the balanced distribution of the scoring, revealing differences between students’ opinion, most probably caused by the different experiences they faced. For the ENG group the role of feedback for the teacher was highly appreciated (statement EA_5, Fig. 5), which reveal the appreciation of the supportive role of the teacher. The Perception of Future Teaching and Learning Approach. Considering the students’ experience during the crisis situation, their opinion about valuing this experience was assessed. The general opinion is that the on-line learning might be an option (general average score of 0.73 for all respondents, with 0.58 and 0.87 registered for ENG and CS groups). In Fig. 6 scores for each statement are presented, and it can be concluded that premises for transition to (partial) on-line activity exists, even though slight differences are registered between the two groups of students.

N_3 N_2 N_1 0.00

0.20

0.40

0.60

0.80

1.00

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average score CS_students

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Fig. 6. Students’ opinion about the future teaching and learning approach: N_1 I would like to participate in online learning activities, but combined with face-to-face learning activities; N_2 The experience gained during this period can be used in the future, during studies, for online learning; N_3 The experience gained during this period can be used in the future, after graduation, for online learning

3 Conclusions The present paper addressed the sudden transition to the on-line learning, in engineering studies at undergraduate level. The study focused on the students’ perception regarding their experience during the pandemic restrictions, which should be

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understood, improved, developed in order to bring an improving step in transition to on-line learning in the future. The majority of the students appreciate the on-line activity, which can be an option for further learning activities, both in the university and in life-long learning context. They possess the basic motivational drivers, such as learning willingness, computer use skills, satisfaction towards studies and a general positive perception of the applicability of their studies in the socio-economic environment. If transition to on-line learning is targeted, it should include the blendedlearning option, since the traditional role of the teacher is still appreciated by the engineering students. The computer-science students proved to be more autonomous in learning than the engineering ones, and this issue must be utilized in new instructional design. The negative feelings related to forced on-line experience were identified, but the scores were not very high, driving the idea to propose remedial, supportive activities for students to cope this type of feelings. The results are promising, and the lessons learned from this research will be further used as starting point in investigating perception of actors (as teachers, managerial staff) in order to develop coherent, evidence-based strategy for transition to on-line learning both at course level and faculty level.

References 1. Polizzi, C., Lynn, S.J., Perry, A.: Stress and coping in the time of COVID-19: pathways to to resilience and recovery. Clin. Neuropsychiatry 17(2), 59–62 (2020) 2. Marinoni, G., van’t Land, H., Jensen, T.: The impact of COVID-19 on Higher Education Around the World. IAU Global Survey Report. https://www.iau-aiu.net/IMG/pdf/iau_ covid19_and_he_survey_report_final_may_2020.pdf. Accessed 29 May 2020 3. Martin, A.: Mechanisms of dialectical change. Manage. Revue 20(2), 149–157 (2009) 4. Dessavre, D.G., Ramirez-Marquez, J.E., Barker, K.: Multidimensional approach to complex system resilience analysis. Reliab. Eng. Syst. Safety 149, 34–43 (2016) 5. COVID-19 and higher education: Today and Tomorrow. http://www.iesalc.unesco.org/en/wpcontent/uploads/2020/04/COVID-19-EN-090420-2.pdf. Accessed 28 May 2020 6. Curriculum design: Thematic Peer Group Report. https://eua.eu/resources/publications/919: curriculum-design.html. Accessed 28 May 2020 7. Evidence-based approaches to learning and teaching. Thematic Peer Group Report. https:// eua.eu/resources/publications/922:evidence-based-approaches-to-learning-and-teachingthematic-peer-group-report.html. Accessed 28 May 2020 8. Skok, K.: No teacher without a student…a theoretical analysis and practical implications of educational changes in the era of digital natives. In: Kowalczuk-Waledziak, M., KorzenieckaBondar, A., Danilewicz, W., Lauwers, G. (eds.) Rethinking Teacher Education for the 21st Century. Trends, Challenges and New Directions, Verlag Barbara Budrich, pp. 111–126, (2019)

Evaluation of Challenge Based Learning Experiences in Engineering Programs: The Case of the Tecnologico de Monterrey, Mexico Patricia Caratozzolo1 and Jorge Membrillo-Hernández1,2(&) 1

Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Monterrey, Mexico {pcaratozzolo,jmembrillo}@tec.mx 2 Writing Lab, TecLabs, Vicerrectoría de Investigación y Transferencia de Tecnología, Tecnológico de Monterrey, Eugenio Garza Sada 2501, 64849 Monterrey, NL, Mexico

Abstract. The Tecnologico de Monterrey has implemented the Tec21 Educational Model, based on four fundamental pillars: Challenge-based learning (CBL), Flexibility, inspiring trained teachers and a comprehensive educational experience that makes it memorable. To be successful, there must be flexibility in curricular programs, which requires that instruction take place in settings within and outside the boundaries of the university campus. Our project was based on the design, development and implementation of a university-industry collaboration in CBL experiences, with Sustainable Development Engineering students in a week exercise called i-week, where students were subjected to the Energy Management in Intelligent Electric Networks challenge in conjunction with an external training partner. Our results indicate that students gain more knowledge using CBL, however, teachers require an appropriate training program and a prior design of the competency assessment instruments. The role of training partners is essential to increase the degree of uncertainty of the challenges that are to be solved in the development of this ambitious program promoted by CBL. Finally, it is clear that every semester a comprehensive evaluation of the application of this model must be made to adapt it to the circumstances of the world’s educational reality. We propose a series of evaluation instruments to determine the development of competencies that can be used for other CBL experiences. Keywords: Challenge-based learning skills
Higher education


Educational innovation
Engineering

1 Introduction 1.1

The New Educational Model Tec21

Since the summer of 2013, the Tecnológico de Monterrey, one of the best universities in Latin America (158th in the world and second in Mexico, according to the 2020 QS rankings) started the implementation of the Tec21 Educational Model, with the aim of preparing the students with a comprehensive education, which allows them to face the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 419–428, 2021. https://doi.org/10.1007/978-3-030-67209-6_45

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challenges that a changing, global and uncertain world demands and guarantee the international competitiveness of graduates [1, 2]. The Tec21 model is based on four fundamental pillars: 1) Challenge-based learning (CBL), 2) Flexibility, 3) Inspired trained teachers and 4) a comprehensive experience of the university environment that makes the student’s stay a memorable event for their lifetime. In this model, there are two categories of competences to be developed: Disciplinary and Transversal, the first refers to all that knowledge, skills, attitudes and values that are considered necessary for professional practice and the second to all that attitudinal, cultural and values necessary for the comprehensive training of a professional person [3–6]. Modern educational models must allow students to become leaders capable of facing challenges and opportunities in the 21st century and, to be successful, seek to improve competitiveness by developing the skills and abilities required in various professional fields. Both types of skills are fundamental to face today’s challenges and, in turn, they must develop comprehensive transversal skills such as critical thinking, understood as a tool to evaluate information and ideas and solve complex problems in a non-routine way. Additionally, the importance of social engineering skills, especially the aforementioned critical thinking and creativity, has been studied for many years by academic researchers. However, it was not until very recently, since first-year students belong almost 100% to Generation Z, that it was seen the need to introduce innovative approaches so that these competences are developed in an effective and lasting way. taking into account the particular characteristics of Generation Z engineers [7, 8] Both employers and international accreditation agencies are most interested in having these competencies formally considered in engineering programs. Challenge Based Learning shares characteristics with Project Based Learning. Both approaches engage students in real-world problems and make them participants in developing specific solutions. However, these strategies differ in that instead of presenting students with a problem to solve, Challenge Based Learning offers open-ended general questions on which students will determine the challenge they will tackle [9, 10]. On the other hand, challenge-based learning also has similarities to problem-based learning. The latter is a collaborative learning teaching technique in which a problematic situation related to the physical or social environment is presented. A fundamental difference between the two approaches is that Problem Based Learning often uses fictional case scenarios; For CBL, the objective is not to solve the problem itself, but to use it for the development of learning, competencies, the final product, it can be tangible or, a proposal for a solution to the challenge [11]. In a previous article we described the differences between them [12]. Here we report on the results of an exercises for the implementation of the Tec21 Educational Model in engineering programs, during the last two years, where flexible courses and challenging experiences were analyzed. 1.2

Challenge Based Learning Theory

Some of the essential conditions to promote effective experimental learning in a CBL experience are [13]:

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• Learning experiences should include activities of reflection, critical analysis and synthesis. • Learning experiences should be structured in a way that promotes decision making and student responsibility for results. • Students must participate actively and creatively in the approach and solution of the problem. • The experience must involve all participants not only intellectually but also emotionally and socially. • The instructor and students may experience success, failure, uncertainty, and risk taking, because the results of the experience may not be entirely predictable. • The instructor recognizes and promotes spontaneous learning opportunities. • The instructor has among its functions the declaration of the problem, the establishment of limits, facilitating the learning process, supporting the students, as well as ensuring the physical and emotional integrity of the students. • The learning outcomes are personal and are the foundation of future experience and learning. • The experience should promote students’ self-awareness, empathy with their peers and a greater knowledge of the environment and other cultures. CBL is an approach to andragogy that has been successfully incorporated into engineering curricula because it achieves a real-world perspective and considers student learning to be “doing” about a topic of study. This approach offers a studentcentered learning framework that emulates real work experiences in industry and corporations: CBL builds on student interest in giving practical meaning to education, while developing key competencies observed by organizations international: leadership and social influence; Emotional intelligence; Reasoning, problem solving and ideation; and Analysis and evaluation of the system. In their latest reports, both the Organization for Economic Cooperation and Development (OECD) and the World Economic Forum (WEF) presented a comparison of current skills with those required by future professionals to face the challenges of the Fourth Industrial Revolution [14, 15]. Table 1 shows the skills that are expected to trend by 2022. CBL is based on theories of experimental learning, the fundamental principle of which is that students learn better when they actively participate in open learning experiences, than when they passively participate in instructor-led activities or teacherled conferences. Implementing challenge-based learning in higher education curricula enables students to apply what they learn in real situations, face complex problems, design and test creative solutions; and most importantly: interact with other students to develop skills and abilities as a team.

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P. Caratozzolo and J. Membrillo-Hernández Table 1. World Economic Forum report [15| Increasing skill demand (2022) 1 2 3 4 5 6 7 8 9 10

Analytical thinking and innovation Active learning and learning strategies Creativity, originality, and initiative Technology design and programming Critical thinking and analysis Complex problem-solving Leadership and social influence Emotional intelligence Reasoning, problem-solving and ideation System analysis and evaluation

2 Experimental Settings 2.1

i-Week as a Model for Challenge Based Learning Teaching Technique

The general purpose of this research was to investigate the first results of the implementation of the Tec21 educational model. Specifically, a specific case of an exercise called Semana i (i-week) was analyzed. Every year now, for a specific week, all students The general purpose of this research was to investigate the first results of the implementation of the Tec21 educational model. Specifically, a specific case of an exercise called i-Week (Semana i in Spanish) was analyzed. Every year now, for a specific week, all students from the twenty-six campuses of Tecnológico de Monterrey stop their courses to enroll in challenging activities designed by different teams of teachers. The challenges designed by the teachers can be developed on campus, off campus or in conjunction with an external training partner that can be a company, industry, or social organization [13]. The main pedagogical theory to be developed is CBL and, for five days, the students are exposed to real situations to develop a solution strategy. Firstly, the groups of participating teachers in this experience were trained in the design of competency assessment tools to verify their development [16] and, secondly, they were also trained to change their teaching style and transformed from content teachers to CBL. In addition, they were taught to apply different digital technological tools such as CANVAS©, eLUMEN©, PADLET© and REMIND©. Finally, evaluation instruments were also designed and applied to review the content of the courses. Various assessment instruments were used during the CBL experiences [17–20]. Specific skill assessments were conducted, each based on rubrics, checklists, knowledge tests, or learning assessments based on challenge resolution through written progress reports and oral presentations [21, 22]. These assessments covered the development of challenge solutions and the development of competency skills, such as oral and written expression, teamwork (collaboration), ethics, critical thinking, abstract thinking, and problem solving skills. In addition, student satisfaction surveys and anonymous opinion polls were conducted to evaluate all courses. Surveys were also established for teachers to evaluate their transformation process towards CBL.

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3 Results and Discussion 3.1

CBL i-Week: Energy Management in Intelligent Electric Networks

The experience of management and monitoring of electrical energy efficiency in smart microgrids was carried out during the 2017, 2018 and 2019 fall semesters, in collaboration with an expert company in the industry (external training partner). In a previous paper we have discussed the importance of world leading companies as training partners [13]. This educational exercise was designed for third and fourth year students of the Sustainable Development Engineering undergraduate program at the Tecnologico de Monterrey. Every year, students from different semesters grouped into two different teams to carry out the activity, which was divided into four stages: 1) Theoretical training and training, 2) Visit the site, 3) Work sessions, 4) Final presentation. This CBL project placed students in direct contact with industry participants to address the energy needs of a real customer, allowing them to become familiar with concepts and activities that would be relegated to the secondary plane, if not entirely omitted in a traditional teaching environment. These activities include the delivery of preliminary energy diagnoses, the recognition of industrial equipment in real electrical installations and the analysis of data for energy efficiency, which involve preliminary correlations with variables of commercial operation such as site occupation, scheduling of operations, local weather conditions and the geographical location of the sites. Site visits also helped students become familiar with customer-specific operating protocols. In addition, soft skills such as teamwork and leadership were developed, as students had to work as a team, not necessarily with peers from the same semesters. Students were required to present their findings and recommendations based on data in a final presentation to jurors from both the energy company and Tecnológico de Monterrey, which helped further develop the required communication skills in a real industry context. As the experiences of CBL were in different years (2017, 2018, 2019), the challenge was always different every time, which is one of the characteristics of CBL: the level of uncertainty. Therefore, a challenge should not be repeated year after year, because it would become a practical or a problem or a project rather than a CBL educational model. The project described in this document was intended to help students develop the skills required in a real industry environment as perceived by a new company based on real technology, such as a power company. While additional assessments should be applied to assess the level of development of each of those skills in future iterations of the activity, students were encouraged to use specific skills that may be required by the external training partner. These needs are listed and related to the Energy Efficiency Management and Monitoring experience in Table 2.

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P. Caratozzolo and J. Membrillo-Hernández Table 2. Required Competencies for this CBL experience

Industry specific required skill Capabilities in analysis, communication, facilitation and software development

Create things from scratch by taking advantage of the latest technology and knowledge available

Commitment to leaving behind a better world by being persistent, hungry, motivated and curious

3.2

Relation to the CBL learning experience Students were encouraged to select the best software alternative and data analysis tool to deliver the expected result as part of the activity Although the data was delivered to students in a flat format, participants were successful in presenting a data-driven presentation with specific recommendations made to a business customer, even under the time and information constraints inherent in the activity format Students had to act in a curious and autonomous way to achieve the desired result in a context of limited information and uncertainty about the result

CBL i-Week Evaluation

The objective of this research is not only limited to the implementation of a CBL exercise but also to the establishment of an evaluation system that can measure the development of competences. Nowadays, there is a need of an assessment method that could be objective, sensible, fair and that students feel satisfied with their rating. Different Assessment Instruments have been used, but apparently none have been unique to assess competencies derived from a CBL experience. In this i-week we evaluated the following two transversal competences and one disciplinary competences using the following criteria: Competency 1: Problem Solving: The student identifies the problem and analyzes the elements that make up the purpose of designing and implementing strategic actions that specify an effective solution to it. Indicators for the development of the competency: A) Intentionally and organized application of techniques or methods for the identification and analysis of problems. B) Investigate, collect, analyze, contrast and evaluate data and information related to the problem, from diverse, reliable and relevant sources. C) Poses various alternatives for the solution of a problem and, through an evaluation, chooses the one with the best chance of success. D) Evaluate the way in which the solution to the problem was defined and implemented, as well as the specific results and identify the aspects that need to be improved. Competency 2: Collaborative Work: The student is integrated into work groups to work together on a common goal, ensuring the participation and learning of himself and his peers. Actively participate and create evidence of it.

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Indicators for the development of the competency: A) Communicate effectively and respectfully his ideas or proposals to the group. B) Participate in each of the phases of the group work and make sure that the final product or the task meets all the requested requirements and is delivered with quality and in a timely manner. The following disciplinary competency was evaluated: Competency 3: Disciplinary Competence of Engineering in Sustainable Development: The student generates proposals for solutions to multidisciplinary problems related to the sustainable use of natural resources, with various energy sources and their social, economic and environmental impacts. Indicators for the development of the competency: A) The student is capable of proposing alternative solutions to problems related to the areas of energy generation and efficient use of electromechanical components, validating models based on the process of research, innovation, design and improvement of technological projects. B) The student can make the selection and evaluation of economic techniques for energy projects. C) The student is capable of evaluating and proposing improvements to processes related to the use of electrical energy, various energy sources, and savings models. Five different Evaluation Instruments were used for each moment of the experience: Diagnostic, Formative and Summative assessments (The day of the week, the evaluators and the competencies evaluated are indicated): Diagnostic Evaluation Instrument: Online questionnaire (Google Forms) Moment: Monday Indicators: Competency 1 A) Evaluator: University Professors Expert Interview Instrument: Observation Guide, Interviews Moment: Wednesday Indicators: Competency 1 B) Evaluator: Expert of the training partner and University Professors Executive Summary Instrument: Observation Guide Moment: Thursday Indicators: Competencies 1 B) and 2 A) Evaluator: Peer evaluation

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Oral Presentation Instrument: Training Partner Rubric Moment: Friday, during oral presentations Indicators: Competencies 3 A), 3 B) and 3 C) Evaluator: Experts of the External Training Partner and University Professors Instrument: Teacher Rubric Moment: Friday, at the end of the activities Indicators: 1 D) and 2B) Evaluator: Experts of the External Training Partner and University Professors 3.3

Satisfaction Surveys

When carrying out a satisfaction survey, during the three consecutive years that this exercise was carried out, it was evident that the students appreciated (greater than 80%) that the Challenge Based Learning didactic strategy is a method where they test their abilities, their knowledge, his resistance to frustration and his teamwork. The students, on the other hand, expressed their satisfaction with the evaluation instruments, especially appreciating that the evaluators were both internal (university professors) and expert engineers from the training partner company. The opinions expressed by the students about the level of challenge was high. Finally, the teachers expressed that the transformation from being a blackboard teacher to a teacher where teamwork with other experts is required and where uncertainty is high, requires special training in the use of digital technologies and in a way, the role of a teacher was being a coach rather than just a transmitter of theoretical knowledge. 3.4

Conclusions

The results of this CBL exercise in what we call i-week for three consecutive years indicate that adequate teacher training and a prior design of the competency assessment instruments are required. Adequate and precise use of technology tools such as REMIND, ZOOM or CANVAS and other platforms is necessary to increase efficiency in developing a CBL experience with a training partner. The role of training partners is essential to increase the degree of uncertainty of the challenges that must be resolved in the development of this program promoted by CBL. Finally, it is clear that every semester an exhaustive evaluation of the application of this model must be carried out to adapt it to the circumstances of the educational reality of the world. An important task is to improve an evaluation methodology appropriate for the challenge-based learning technique, it is difficult to have a single form of evaluation and this is complicated when there are training partners involved in the teaching process. Compliance and development of both cross-disciplinary and disciplinary competences is necessary, so developing a methodology that can collect evidence in this regard is a task that is constantly developing, here we discuss some proposals that will surely be useful for other CBL exercises. Other authors have reported the use of deliverables, such as written reports, exams by training partners, or skills tests. However, the application of CBL at the undergraduate level is still under development and implementation.

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Acknowledgements. The authors would like to acknowledge the financial and technical support of Writing Lab, TecLabs, Tecnologico de Monterrey, Mexico, in the production of this work. The authors acknowledge the NOVUS Programs grants with PEP no. PHHT032- 192200006-05001 and PEP no. PHHT090-19ZZ00008 in support of this work.

References 1. Free document. https://observatory.itesm.mx/tec21/. Accessed 22 April 2019 2. ITESM: Strategic Plan 2020. http://sitios.itesm.mx/webtools/planestrategico2020/publico/ EN/inex.html. Accessed 13 Jan 201 3. Nichols, M., Cator K.: Challenge Based Learning. White Paper. Apple, Inc, California (2008) 4. Nichols, M., Cator, K., Torres, M.: Challenge Based Learners User Guide. Digital Promise, Redwood City (2016) 5. Johnson, L.F., Smith, R.S., Smythe, J.T., Varon, R.K.: Challenge-Based Learning: An Approach for Our Time. The New Media Consortium, Austin (2009) 6. Giorgio, T.D., Brophy, S.P.: Challenge Based learning in biomedical engineering: a legacy cycle for biotechnology. In: ASEE, pp. 2701–2711. (2001) 7. Mohr, K.A.: Understanding Generation Z students to promote a contemporary learning environment. J. Empower. Teach. Excell. 1(1), 9 (2017) 8. Caratozzolo, P., Alvarez-Delgado, A., Hosseini, S.: Strengthening critical thinking in engineering students. Int. J. Inter. Des. Manuf. (IJIDeM) 13(3), 995–1012 (2019). https://doi. org/10.1007/s12008-019-00559-6 9. Membrillo-Hernández, J., de J. Ramírez-Cadena, M., Caballero-Valdés, C., Ganem-Corvera, R., Bustamante-Bello, R., Benjamín-Ordoñez, J.A., Elizalde-Siller, H.: Challenge based learning: the case of sustainable development engineering at the Tecnologico de Monterrey, Mexico City Campus. In: Auer, M.E., Guralnick, D., Simonics, I. (eds.) ICL 2017. AISC, vol. 715, pp. 908–914. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-73210-7_103 10. Membrillo-Hernández, J., Muñoz-Soto, R.B., Rodríguez-Sánchez, A.C., Castillo-Reyna, J., Vázquez-Villegas, P., Díaz-Quiñonez, J.A., Ramírez-Medrano, A.: Student engagement outside the classroom: analysis of a challenge-based learning strategy in biotechnology engineering. In: Proceedings of the EDUCON 2019. IEEE Global Engineering Education Conference, EDUCON April-2019, pp. 617–621 (2019). Art no. 8725246 11. Caratozzolo, P., Alvarez-Delgado, A., Hosseini, S.: Fostering specific dispositions of critical thinking for student engagement in engineering. In: Proceedings of the EDUCON 2019. IEEE Global Engineering Education Conference EDUCON April-2019, pp. 221–226 (2019) 12. Membrillo-Hernández, J., J. Ramírez-Cadena, M., Martínez-Acosta, M., Cruz-Gómez, E., Muñoz-Díaz, E., Elizalde, H.: Challenge based learning: the importance of world-leading companies as training partners. Int. J. Inter. Des. Manuf. (IJIDeM) 13(3), 1103–1113 (2019). https://doi.org/10.1007/s12008-019-00569-4 13. Membrillo-Hernández, J., Ramírez-Cadena, M.J., Caballero-Valdés, C., Ganem-Corvera, R., Bustamante-Bello, R., Benjamín-Ordoñez, J.A., Elizalde-Siller, H.: Challenge based learning: the case of sustainable development engineering at the Tecnologico de Monterrey, Mexico City Campus. Int. J. Eng. Pedagogy 8, 137–144 (2018). https://doi.org/10.3991/ijep. v8i3.8007

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14. Reyna-González, J.M., Ramírez-Medrano, A., Membrillo-Hernández, J.: Challenge based learning in the 4IR: results on the application of the Tec21 educational model in an energetic efficiency improvement to a rustic industry. In: Advances in Intelligent Systems and Computing, AISC, vol. 1134, pp. 760–769 (2020) 15. World Economic Forum: Centre for the New Economy and Society Boston Consulting Group (BCG). Towards a reskilling revolution: industry-led action for the future of work. World Economic Forum, Geneva, Switzerland (2019) 16. Agüero-Pérez, M.M., López-Fraile, L.A., Pérez-Expósito, J.: Challenge based learning as a professional learning model. Universidad Europea and Comunica +A program case study. Vivat Academia Rev. Comm. 149, 1–24 (2020). https://doi.org/10.15178/va.2019.149.1-24 17. Membrillo-Hernández, J., Molina-Solís, E.G., Lara-Prieto, V., García-García, R.M.: Designing the curriculum for the 4IR: working the case of biology and sustainable development in bioengineering courses. In: Advances in Intelligent Systems and Computing, AISC, vol. 1135, pp. 306–315 (2020) 18. Arrambide-Leal, E.J., Lara-Prieto, V., Garcia-Garcia, R.M., Membrillo-Hernandez, J.: Impact of active and challenge based learning with first year engineering students: mini drag race challenge. In: Proceedings of the 2019 IEEE 11th International Conference on Engineering Education, ICEED 2019, pp. 20–25 (2019). art. no. 8994939 19. Lara-Prieto, V., Arrambide-Leal, E.J., Garcia-Garcia, R.M., Membrillo-Hernandez, J. Challenge based learning: competencies development through the design of a cable transportation system prototype. In: Proceedings of the 2019 IEEE 11th International Conference on Engineering Education, ICEED 2019, pp. 11–15 (2019). art. no. 8994958 20. Eraña-Rojas, I.E., López Cabrera, M.V., Ríos Barrientos, E., Membrillo-Hernández, J.: A challenge based learning experience in forensic medicine. J. Forensic Legal Med. 68, 101873 (2019) 21. Allen, M.J.: Using rubrics to grade, assess, and improve student learning. strengthening our roots: quality, opportunity & success professional development day, pp. 34–35 (2014) 22. Value Rubrics: Association of American Colleges & Universities. https://www.aacu.org/ value-rubrics. Accessed 26 Apr 2020

A Timed Discussion Forum for Novice Users and Self-learners of Spoken Tutorials Kannan M. Moudgalya(B) , Nancy Varkey, Vishnu K. Raj, and K. Sanmugasundaram Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India [email protected]

Abstract. Spoken Tutorials are an instructional methodology to train students on IT topics at a national level through self learning. Problems that beginner users face in accessing information from online resources are explained. A timed online discussion forum, through which users of Spoken Tutorials can ask their questions, and also learn from previous discussions, is presented. In this Timed Question and Answer Forum, learners access information by pinpointing the exact time of the Spoken Tutorial at which one may have questions. This forum is helpful not only to the beginners, but also to other learners who participate in massive distributed workshops as well. Discussions in this forum double as document/FAQ for the software. Keywords: Discussion forum for beginners · Question and answer forum · Collaborative content generation · Learner Centric MOOCs

1

Introduction

Employability of students is very low in India [7]. This can be partly addressed if we can tackle the problem of low computer programming competency [9]. The Spoken Tutorial project was started to help improve programming skills of students [6,14–16]. Spoken Tutorials are a series of audio-video tutorials of 10 min duration each. As many students in India do not have access to good education, self learnability is accorded the maximum priority in the creation of Spoken Tutorials. To achieve this goal, video tutorials are created using scripts that pass a novice check, as shown in Fig. 1. Some other steps undertaken to make Spoken Tutorials accessible to the disadvantaged student community are: (1) Audio is dubbed into all 22 official languages of India, keeping videos in English - this helps students who are not fluent in English, without sacrificing employment opportunities (2) Facilitating offline use by providing a zip file of tutorials on one or more topics (3) Focusing only on open source software, which obviates the need to buy c The Author(s), under exclusive license to Springer Nature Switzerland AG 2021  M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 429–437, 2021. https://doi.org/10.1007/978-3-030-67209-6_46

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commercial software (4) Releasing the Spoken Tutorials under the CC-BY-SA license. There are a total of about 1,100 Spoken Tutorials, covering about 75 topics. Including dubbing, there are about 11,000 Spoken Tutorials. Using Spoken Tutorials, more than 6 million college students have been trained during the past 6–7 years [16,24]. Students trained through this self learning method have been performing well [17,19]. Given the great potential that Spoken Tutorial has [6], it is important to provide an online forum for the target audience to interact, and to clear their doubts. This work presents some difficulties that beginners face in using forums in Sect. 2, and our solution in Sect. 3. Unexpected benefits of this forum to other segments of the population are explained in Sect. 4.

Create/improve Script

No

Can a beginner understand it?

Yes

Record a video using the script

Fig. 1. Novice check of script helps in self learning of Spoken Tutorials

2

Desired Features of Forums from Beginners’ Perspective

1. Friendliness: Most Internet forums demand certain netiquettes. While some forums are tolerant, others are not, and may result in nasty responses [25]. To a beginner, learning to use Free and Open Source Software (FOSS), this is a formidable challenge. Usage of FOSS requires a higher competence or having a community that is willing to help beginners without being rude [21]. The need to keep forums friendly as a long-term survival strategy has been articulated, however [8]. 2. Reading before posting: Forums also ask the user to search before asking a new question. Sadly, forums become overwhelming and confusing for users to navigate, especially for low Internet efficacy users. Students with high Internet efficacy learn to do this better, however [1]. Novices behave differently from experts, and they need help to locate the information available on the Internet [12,13]. Unfortunately, however, they don’t necessarily get helped, as Internet users are more rude online than they are in person [2]. If they don’t use the forums well, beginners lose out [20].

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3. Constructing useful content out of online collaboration: The popular forum StackOverflow has been suggested by many as a useful learning tool [4]. Nevertheless, the main weakness of online tutorials, manuals, FAQs, wikis, bulletin boards, and weblogs that form the documentation for FOSS, is that they are incoherent, unorganised, and incomplete [11,21]. The problem of documentation cannot be solved on a technological level, but by using different methods of storing and retrieving information, in a way consistent with cultural practices [21]. Microlearning is proposed as a way to learn FOSS, and to acquire knowledge in small steps to construct a broad and deep knowledge eventually [21]. Ten minute long Spoken Tutorials, which are in a sense a documentation to open source software, are a step in this direction. It will be interesting if we can organise discussions that happen in a carefully designed forums to produce useful content. Collaboratively created documentation for Scilab is available through the Textbook Companion project [3].

3

Implementation of a Forum with Desired Features

Keeping the requirements stated in the previous section, we have designed and implemented a forum to provide answers to questions, on the basis of the time of occurrence in the Spoken Tutorial [22]. We will refer to it as the Timed Questionand-Answer (QnA) Forum. Django, MySQL database, Bootstrap, HTML 5, CSS 3 were the technologies used to create the Timed QnA Forum. As the Spoken Tutorial website [23] is in Django, one could log into it and the Forum through a single sign on with a common user login. The ST video ID is mapped with each Forum question. So the questions can be fetched accurately in both online and offline playback. Fetching of questions is done through AJAX calls, wherein the Spoken Tutorial website [23] acts as an API that feeds the tutorial names into the Post Question form. Whenever a question is posted, all contributors/authors of the Spoken Tutorial are notified. Subsequently, follow-up mails are also sent as reminders to the authors. The learner who posted the question is also notified when the question is answered. The same is also visible immediately online on the Forum. On the Timed QnA Forum webpage, a slider displays all the software series in graphic form. By clicking on any one of these, one can access all the previously asked questions posted in Forums, till date, for that particular software series. On the homepage, the 10 most recently posted questions are displayed and these are arranged in achronological order, with the most recent question appearing first. The columns are sortable in ascending and descending order. A typical set of questions asked on the forum is displayed in Fig. 2 (Left). Magnifying glass icons are provided below the software series name and tutorial name. Clicking on the magnifying glass icon below the software series name, shows a list of all the tutorial names on which questions were posted, in alphabetical order. Clicking on the magnifying glass icon below the tutorial name,

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Fig. 2. A typical set of questions as it appears on the Timed QnA Forum (left) and the result when the lens next to Moodle is clicked (right)

shows a list of all the questions posted. For example, on clicking the lens next to Moodle in Fig. 2 (left), we obtain the figure on the right. On clicking the lens next to a tutorial name, one can see all the questions posted on it. For example on clicking the lens next to Getting Ready in Fig. 2, we obtain Fig. 3 (left). Now, one can sort the questions in chronological order. By clicking the Mins (Minutes) button in Fig. 3 (left), one can sort the questions in ascending minutes, as shown in Fig. 3 (right).

Fig. 3. On clicking the lens symbol next to Getting Ready in Fig. 2, we obtain the figure on the left, which displays the questions on this tutorial only. On clicking Mins (Minutes) in this figure, questions get arranged chronologically (right).

As all the questions get sorted chronologically, it is easy to locate them on the basis of the time. One can also see all different questions asked at a particular time. One can click on the title of a question to read the full question and the answers posted - a sample is provided in Fig. 5. One can join any of the discussions by asking more related questions. One can also answer questions that are previoulsy asked. One can see that all the requirements of the previous section have been met:

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1. As the method of posting is easily understood, and easy to follow, even a novice can post questions without making mistakes. As a result, one can say that this Timed QnA Forum is a friendly one that conveys to every user how to post the questions. 2. Next, the sorting method explained above can be used to easily locate the previously asked questions, and one does not have to be an expert to do this. 3. Finally, the above explained method of organising the previous discussion helps produce useful content. In addition to the above, additional help is provided to answer seekers, as we explain how. While posting questions on the Timed QnA Forum, as one begins typing the text of the Title of the question, we are prompted to view similar previously posted questions on Forum. Clicking on the previous questions link opens a pop-up box with the previous questions listed therein. Clicking on the hyperlinked questions, redirects us to another webpage where we can read the question and the associated answers. In most cases, these could satisfy the learner’s query. If not, one can always go ahead and post the new question. This feature is useful and helpful in limiting the repetition of questions. The flow in using the Timed QnA Forum by a Spoken Tutorial user is illustrated in Fig. 4.

Fig. 4. Flow in using the Timed QnA Forum

4

Timed QnA Forum Benefits the General Audience

We already saw in the previous section that the three desired features of a forum are available in the Timed QnA Forum presented in this work. We will now present a few additional benefits. With this Timed QnA Forum, it is possible to effectively and efficiently answer the questions of the participants of large workshops [10]. Questions and answers happen silently, without disturbing others present in the workshop. Once a question is answered, this discussion becomes available to everyone. Participants of a large LATEX workshop, who were forced to use the Timed QnA Forum, gave a positive feedback [10]: They found the forum helpful, as they normally

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hesitated to ask questions in a large class, and as they usually missed details of discussion in a live class. They felt that their doubts were answered a lot faster than in a large class. They also felt that they did not have to wait to get their doubts cleared. Their answering pattern also indicated a high level of satisfaction. The Timed QnA Forum discussed here also helps a lot in distributed settings. The authors’ team has organised massive blended workshops for as many as 5,000 simultaneous participants, attending the workshop in 200+ locations [18]. If conventional methods are followed, one would need an expert at every location to clear the doubts. With the method adopted in the Timed QnA Forum, it is possible for a few experts to answer the doubts of several thousand participants. We should also point out that there will not be many duplicate questions, because of the way the forum is organised, as explained in the previous section. During the COVID-19 pandemic, most workshops have participants from different locations. About 200 participants of a recently conducted DWSIM beginner level workshop [5], from as many locations, found the Timed QnA Forum very effective. When asked to give their feedback about the forum approach, answers of the following type were obtained: questions were answered immediately, answers were cleared, it really helped in solving problems, most of the doubts were cleared in the forum itself, most of the common questions are already answered, and this platform is easily accessible to clear the doubts. Finally, the Timed QnA Forum is helpful to address the changes due to versioning of software. It is possible that an open source software may be changing frequently, especially at initial stages of development. Unfortunately, Spoken Tutorials cannot keep pace with the software releases, as it takes a long time to create, because of the novice check requirement explained in Fig. 1. Whenever a feature changes in the software, one can immediately post it on the Timed QnA Forum at the appropriate location. In Fig. 5, one can see how the change in a software DWSIM is addressed.

Fig. 5. Addressing difficulties due to version changes through the Timed QnA Forum

Timed QnA Forum

5

435

Discussion and Conclusions

The Timed QnA Forum presented in this work makes it easy for beginners to access previously happened discussions. It also makes it easy for them to ask new questions at appropriate locations. This forum also promotes peer-to-peer learning: even though the person answering a question may not be an expert, they may have sufficient expertise on the issue asked. If used constructively, the Timed QnA Forum can form a basis for creating FAQs. It is a type of on-the-fly documentation and with a little moderation by subject-matter-experts, has the capacity to help create useful content. The forum provides networking opportunities, and access to expertise from a wide range of ages, backgrounds and geographies. It offers shy and more reticent learners the opportunity to participate in forum discussions more easily than in face-to-face sessions. When the learners take the lead role of answering a question posted on the forum, they themselves become independent learners. One shortcoming of this approach is that this forum is tightly coupled with the underlying Spoken Tutorial, which itself may undergo version changes. We believe, however, that this problem can be tackled through a version-control type technology. There is also a difficulty in using the discussion in the Timed QnA Forum directly as additional content, given that most beneficiaries are beginners, and certain amount of curation is required. Acknowledgement. Generous funding to the Spoken Tutorial project from the National Mission on Education through ICT, Ministry of Education, Govt. of India, is acknowledged. Enthusiastic supported provided by the members of FOSSEE and Spoken Tutorial teams is appreciated.

References 1. Balaji, M.S., Chakrabarti, D.: Student interactions in online discussion forum: empirical research from ‘Media Richness Theory’ perspective. J. Int. Online Learning 9(1), 1–22 (2010) 2. Betkowski, B.: Why are we so rude on social media? https://www.folio.ca/whyare-we-so-rude-on-social-media/. Accessed 30 Aug 2020 3. Braatz, R.D.: Scilab textbook companions. IEEE Cont. Syst. Mag. 76 (2014) 4. Dondio, P., Shaheen, S.: Is stackoverflow an effective complement to gaining practical knowledge compared to traditional computer science learning? In: Proceedings 11th International Conference on Edition Technology and Computers, ICETC, pp. 132–138. ACM (2019) 5. DWSIM-Team: DWSIM Beginner Workshop. https://www.it.iitb.ac.in/ nmeict/workshopContent.html?workshopid=xuto7xzB6T7kJRpHW1GLqA& category=UubpVTjA3FS-DQx8uW4rlA. Accessed 30 Aug 2020 6. Eranki, K.L.N., Moudgalya, K.M.: Comparing the effectiveness of self-learning Java workshops with traditional classrooms. Educ. Technol. Soc. 19(4), 310–331 (2016) 7. Farrell, D., Kaka, N., Sturze, S.: Ensuring India’s offshoring future. The McKinsey Quarterly 2005 special edition: Fulfilling India’s promise, pp. 75–83 (2005)

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8. Fogel, K.: Producing Open Source Software: How to Run a Successful FreeSoftware Project. https://unglueit-files.s3.amazonaws.com/ebf/0689f7b5c08743c29ffbfc194b d03179.pdf. Accessed 30 Aug 2020 9. Gadgets-Now: 95% of engineers in India unfit for software development jobs, claims report. Communications of the ACM (2017). https://cacm.acm.org/ careers/216143-95-of-engineers-in-india-nfit-for-software-development-jobsclaims-report/ 10. Ganguly, S., Eranki, K.L.N., Moudgalya, K.M.: Assessing the efficacy of a large, self-learning, silent, LATEX workshop. In: IEEE International Conference on Technology for Education (T4E). IEEE, IIT Bombay (2016) 11. Levesque, M.: Fundamental issues with open source software development. First Monday (2005). http://firstmonday.org/article/view/1484/1399 12. Lu, Y., Hsiao, I.: Seeking programming-related information from large scaled discussion forums, help or harm? In: International Conference on Educational Data Mining (EDM). International Edition Data Mining Society (2016). https://eric.ed. gov/?id=ED592724. Accessed 31 Aug 2020 13. Lu, Y., Hsiao, I., Li, Q.: Exploring online programming-related information seeking behaviors via discussion forums. In: 2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT), pp. 283–287 (2016) 14. Moudgalya, K.M.: Spoken Tutorial: A Collaborative and Scalable Education Technology. CSI Commun. 35(6), 10–12 (2011). http://spoken-tutorial.org/CSI.pdf, Accessed 17 Sep 2020 15. Moudgalya, K.M.: Pedagogical and Organisational Issues in the Campaign for IT Literacy Through Spoken Tutorials. In: Huang, R., Kinshuk, N.S.C. (eds.) The New Development of Technology Enhanced Learning, chap. 13, pp. 223–244. SpringerVerlag, Berlin Heidelberg (2014) 16. Moudgalya, K.M.: IT Skills Training through spoken tutorials for education and employment: reaching the unreached. CEC J. Digit. Educ. 1(1), 19–62 (2017). http://spoken-tutorial.org/media/CEC.pdf 17. Moudgalya, K.M.: Crowdsourced information technology content for education and employment. In: 18th IEEE International Conference on Advanced Learning Technologies (ICALT 2018), pp. 39–41. IIT Bombay (2018) 18. Moudgalya, K.M.: Simultaneous training of 10,000 teachers through weapons of mass instruction. Pan Commonwealth Forum 9, Edinburgh (2019). http://oasis. col.org/handle/11599/3404 19. Moudgalya, K.M., Viswanathan, U., Ghavri, V.: Fossee fellowship 2019: results of crowdsourcing and performance based selection. In: 2019 IEEE Tenth International Conference on Technology for Education (T4E), pp. 94–101. T4E. IEEE, Goa (2019) 20. Nandi, D., Hamilton, M., Harland, J., Warburton, G.: How active are students in online discussion forums? In: Hamer, J., de Raadt, M. (eds.) Proceedings Australasian Computing Education Conference (ACE 2011), pp. 125–134 (2011). https://crpit.scem.westernsydney.edu.au/confpapers/CRPITV114Nandi. pdf, Accessed 31 Aug 2020 21. Sch¨ afer, M.T., Krazlm¨ uller, P.: RTFM! Teach Yourself Culture in Open Source Software Projects. In: Hug, T. (ed.) Didactics of Microlearning, pp. 324–337. Waxmann Verlag, Munster (2007). http://mtschaefer.net/entry/rtfm-teach-yourselfculture-open-source-software-projects/ 22. Spoken-Tutorial-Team: Spoken tutorial forum. http://forums.spoken-tutorial.org/. Accessed 17 Sep 2020

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23. Spoken-Tutorial-Team: Spoken Tutorial Website. https://spoken-tutorial.org 24. Spoken-Tutorial-Team: Workshop/training statistics. http://spoken-tutorial.org/ statistics/training/. Accessed 17 Sep 2020 25. Wikipedia: Posting Style. https://en.wikipedia.org/wiki/Posting style, Accessed 30 Aug 2020

Experiences in Rapid Transition to Remote Learning

Integrated Online Wind Tunnel Experiments and Assessment for Contingency Scenario: Case Study at the British University in Egypt (BUE) Ahmed Aboelezz1 1

, Peter Makeen1,2(&)

, and Hani Ghali1,2

Centre for Emerging Learning Technologies (CELT), The British University in Egypt (BUE), Cairo, Egypt [email protected] 2 Electrical Engineering Department, Faculty of Engineering, The British University in Egypt (BUE), Cairo, Egypt

Abstract. This paper presents an effort towards the development and the implementation of an integrated remote experimentation facility along with corresponding assessment for deployment in online contingency scenario. A sample real-time aerodynamics experiment has been developed to operate, fully remotely, along with corresponding real-time visualization. Although in the case of a remotely controlled experiment only single user will be able to access the setup at time, the instructor and other students will be meeting, virtually, during the lab session providing real-time technical support for the experiment’s operation, faster collaboration among students, and real-time feedback. The use of standard virtual meeting platforms during the lab session provides an enhanced students’ engagement for the remote experimentation exercise. The proposed operation scenario fits within the synchronous learning activities, with the biggest advantage of human connections. On the other hand, to match the on-campus lab session, two extra online tasks have been added within the allocated experiment’s time slot; these are pre-lab activities and postlab assessment. The use of the two online tasks, besides the real-time testing task will allow more students to operate simultaneously in each lab session. The experiment has been fully designed and implemented using NI LabView software and NI cDAQ platform to conduct the real-time experiments with corresponding controls. Students will be able to run, remotely, the experiment using the free NI LabView run-time engine software. The pre-lab and the post-lab tasks will be performed using Google Forms, thus converting the complete lab session to an integrated online environment. Keywords: Wind tunnel experiments
Remote aerodynamics experiment Online testing
NI LabView
NI cDAQ
Synchronous leaning activities

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 441–446, 2021. https://doi.org/10.1007/978-3-030-67209-6_47




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1 Introduction: Challenges Serving wide range of specializations ranging from architecture, civil, mechanical and electrical, the wind tunnel experiments are commonly used to test everything from buildings, aircraft, and automotive designs. During a test, the used model is placed inside the test section of the wind tunnel and air is forced to flow around and past the model. Mainly, there are four types of wind tunnel experiments: aerodynamic forces upon the model, pressure distribution of the wind force on the object, the spatial variation of the wind speed around the model, and, finally, visualization of air flow around the model to provide useful aerodynamics information about the model. In standard on-campus situation, students perform these experiments to acquire the required measured data and verify their understanding of the theoretical background behind the obtained results. However, in contingency situation, where the on-campus facilities are very limited, or eventually not allowed, the understanding of key aerodynamics concepts remains a challenging task. Simulation based experiments, or more precisely virtual experiments have been proposed as a ready replacement for real situation. However, the engagement and interaction of students with the software tool remains limited with very little understanding of related key concepts. In [1], a virtual aerospace laboratory has been proposed, where real-life examples have been used as movies of low-speed and supersonic flows, generation of lift, and various flight maneuvers. The main problem with this method is the absence of the interaction between students and the experiment. Remote experimentation emerges as an attractive alternative, where students can, remotely, control a real-time physical experiment setup and associated equipment and sensors, and in the same time visualize its operation. Technologies have supported the implementation of such scenario through different options. One of the very commonly used technique is the use of NI LabView software tool to build the experiment’s user interface (UI) which includes; control knobs, sliders, indicators and charting/graphing options, integrated with a data acquisition system to perform the electronic control on the real-time experiment’s setup. In [2, 3], a web-based, interactive laboratory experiment in turbomachine aerodynamics has been proposed. Using an existing laboratory, control units as well as some motors have been added in addition to two video cameras, and NI LabView has been used to build a user interface so that students can run the experiment, fully remotely. A survey on students’ feedback on both the on-campus lab and the remote labs shows significant advantages for the use of remote labs. This paper presents a case study, that is currently being in its final stage for full implementation, of an aerodynamics experiment on pressure distribution on object inside the test section of the wind tunnel. Additional online tasks have been added to the experimentation task, mainly pre-lab activity and post experiment assessment to ensure the implementation of the full delivery of lab sessions that matches the standard operation in normal on-campus conditions.

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2 Aerodynamics Experiment: Pressure Distribution The implemented experiment represents one of the most important aerodynamics testing in wind tunnel. The main objective of the experiment is to investigate the pressure distribution, and hence calculate the coefficient of pressure, on a sample object placed inside the test section of the wind tunnel. The used object is a hollow cylinder of diameter 11 cm, and height equals to the height of the test section as shown in Fig. 1. The experiment setup consists of a subsonic wind tunnel at the British University in Egypt (BUE) with test section of cross section area of 1 m x 1 m, length of 2.2 m powered with a 3-Phase 30 kW axial flow fan with an Airflow of 93,000 m3/hr. The 3Phase fan is connected to the AC speed drive, Schneider Altivar 61, 30 kW – 40 HP 380/480 V to provide variable speed control to generate variable wind speed up to 25 m/s inside the test section. The control on the fan speed has been achieved using LabView software with NI cDAQ-9189 platform and NI 9263, NI 9472, NI 9215 modules. On the other hand, 13 uniformly distributed holes have been made along the circumference of the cylinder and are connected to 13 pressure sensors AMS2710–0020-D & AMS2710–0050-D with 5000 Pa range through pressure tubes as shown in Fig. 2. The set of sensors are connected to NI module NI 9205 which is used to acquire the signals from the pressure sensors with 1000 samples per second.

Fig. 1. Cylindrical object placed inside the Fig. 2. Pressure sensors connected to the test section of the wind tunnel. holes via pressure tubes.

Aerodynamic forces such as Lift (L) and Drag (D) could be calculated by dividing the surface into small elements. Once these values have been obtained for each element, integration over the surface is performed to obtain the L and D coefficients for the immersed body. This can be conducted by measuring the pressure at different points along the body surface. An important term used in these calculations is defined as the pressure coefficient (Cp). Cp equals the difference in the local pressure and a reference pressure divided by the reference dynamic pressure, where the reference is the freestream air in this case as given by:

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Cp ¼

p  preference qreference

ð1Þ

The Drag coefficient could be determined by integrating the pressure distribution over the overall body surfaces using the following equation: Cd ¼

1 2

Z

2pi

C p coshdh

ð2Þ

0

Using the pervious equations along with the measured pressures values at different locations on the cylinder surface, the drag coefficient is determined on the cylinder at certain wind speed. Figure 3 shows the obtained experimental results at wind speed 12 m/s, compared with the ideal case given by: C p ¼ 1  4  sin2 ð180  hÞ

ð3Þ

Fig. 3. Comparison between experimental and ideal data

2.1

Experiment’s User Interface

LabView software has been used to design the user’s interface (UI) control panel as shown in Fig. 4. The user “student” has full access to control the speed of the fan, and consequently the generated wind speed. On the other hand, the user “student” will get the instantaneous values of the pressure distribution along the 13 sensors, which could be saved for processing. In addition, the user “student” can select any point among those 13 holes along the cylinder and get the coefficient of pressure as a function of time at a certain wind speed. This could be easily extended to plot the coefficient of pressure at any desired location, along the cylinder, as a function of the wind speed.

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a) Pressure along the cylinder

b) Cp at point 5

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c) Wind speed control

Fig. 4. Experiment’s user interface (UI)

2.2

Pre-lab Activities

The pre-lab activities have been created using a google form, where each student should answer the questions within 20 min. The pre-lab activities have been categorized into three main sections; the first section focuses on the fundamental concepts of the experiment, the second section explores the student’s understanding of the mathematical model of the experiment, and the third section ensures the student’s ability to interpret and understand the data which will be obtained from the experimental setup as shown in Fig. 5. Once the student submits the form, an email will be automatically sent to the student to proceed with the next step of the experiment. In addition, the instructor will be able to send instantaneous feedback to the students to ensure the proper operation of the following experimental task. 2.3

Post-lab Assessment

The last step of the online experiment is the post-lab assessment, which has been also created by another google form as shown in Fig. 6. Each student should answer all questions within 20 min to finish the online assessment task. The target of the assessment is to ensure that the students have acquired the experiment’s Intended Learning Outcomes (ILOs) where, the assessment consists of a multiple-choice section with the result of this section immediately marked after the submission. It also provides the instructor with personalized feedback on the performance and understanding of each student. Finally, it will be used, along with the other two tasks, for grading the student’s lab exercise.

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Fig. 5. Experiment’s google forms for step (1): pre-lab activities.

Fig. 6. Experiment’s google forms for step (3): post-lab assessment.

3 Conclusions A fully integrated remotely accessible real-time experimentation facility with associated pre-lab activities and post-lab assessment is proposed for implementation in contingency situation. The proposed real-time experiments have been developed using NI LabView software with cDAQ platform to perform the required controls on the experiment’s setup. Google forms have also been used for the pre-lab activities as well as for the post-lab assessment. In addition, meeting using standard virtual meeting platforms is recommended to be used during the experimentation task for instantaneous feedback, thus enhancing students’ performance and understanding. The proposed scenario fits within the synchronous learning activities having great added value regarding students’ collaboration and human connections.

References 1. Higuchi, H., Henning, G.A.: Development of a virtual aerospace laboratory for undergraduate education. Comput. Appl. Eng. Educ. 4(1), 19–26 (1996) 2. Cranston, G., Lock, G.: Techniques to encourage interactive student learning in a laboratory setting. Eng. Educ. 7(1), 2–10 (2012) 3. Navarathna, N., et al.: Web-based, interactive laboratory experiment in turbomachine aerodynamics. J. Turbomachinery 132(1) (2010)

Online Implementation of Structural Analysis Tool for Remote Learning Ghada El-Mahdy(&)

and Amany Micheal

British University in Egypt (BUE), El-Sherouk City 11837, Cairo, Egypt [email protected]

Abstract. The delivery of a structural analysis module to architectural or civil engineering students needs the visualization of certain diagrams, such as the internal force diagrams and the elastic line. These diagrams are difficult to grasp for students new to structural analysis and need a lot of practice to become proficient in drawing them. Current structural analysis textbooks with electronic platforms do not include tools to draw the internal force diagrams or deflection. This has led to the initiative of creating an online structural analysis tool to enable the student to easily apply different loadings on different statical systems to draw the internal force diagram or the elastic line. The online tool is easy to navigate, using dropdown menus to choose the structural system and sliders to specify the parameters. It can be implemented during online lectures to demonstrate diagrams to the students and in assessments where students can easily apply the tool to visualize the required diagram and check their calculations. Other smart questions can be adopted by the teacher which need a lot of manual calculations that are not practical during the assessment’s limited time. This smart assessment is now doable using the structural analysis tool. This tool has further been extended as a mobile application which can be used offline. The tool can be enlarged to accommodate more complicated structures and loading conditions. The tool’s effectiveness over that of software packages is the simultaneous interaction in the user interface. Keywords: Mobile applications Structural analysis


Virtual education
Online structural hub


1 Introduction: Challenges Interactive tools have become imperative in any teaching environment, whether distant learning is required or not. In engineering disciplines, the transition to interactive eBooks with electronic platforms has become the trend. This is needed for ordinary inperson teaching, and even more, for distant learning, as has been dictated by the outbreak of the Covid-19 pandemic. The current Covid-19 pandemic has led to a race in the development and implementation of more electronic tools to assist in the distant learning process. Structural analysis is used by practically all disciplines in engineering, and, in particular, students of architecture and civil engineering. It is a basic requirement to start the process of design of sections in reinforced concrete and steel structures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 447–455, 2021. https://doi.org/10.1007/978-3-030-67209-6_48

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The first step in any structural design is to find the internal forces and deflections of the structure subjected to certain applied loads. This leads to many challenges for students new to this process. The first challenge is the visualization of internal force diagrams like the bending moment diagram (BMD), the shear force diagram (SFD), and the normal force diagram (NFD). Visualizing the internal force diagrams has proven difficult for students beginning their journey of learning in structural analysis. There are so many statical systems and loading conditions for the student to deal with. Although the student is taught to use the method of sections to find the internal forces, the resulting internal force diagrams is somewhat a myth to the student. For this reason, developing an interactive tool to draw the BMD and SFD for 1D systems such as statically determinate beams, and the BMD, SFD, and NFD for 2D systems such as statically determinate frames has been an attractive objective for any structural analysis module. In fact, current structural analysis electronic textbooks or platforms [1, 2] do not include this as a coaching activity. The second challenge is the visualization of deflections. Often, after two or three lectures on deflections, I find students asking me what is the deflection of a beam? The aim, therefore, is to introduce the student to an interactive dynamic example of the deflection of a beam from the first lecture, so that they have a tool to play with while studying the theoretical aspects of calculating deflections. The tedious methods of calculating deflections (double integration method, moment-area method, conjugatebeam method, or virtual work method) are taught in vain if the student has not grasped the concept of deflections from the first lecture. Interactive deflection tools cannot be found in the coaching activities of current electronic platforms for structural analysis textbooks [1, 2]. Although these textbooks contain coaching tools for simple load deformation problems of mechanics of materials, no interaction deflection tools have been developed or included. This has led to the urgent need to develop in-house interactive tools for complementing the delivery of any structural analysis module.

2 Structural Analysis Tool Three phases of a structural analysis tool have been developed by the Center for Emerging Learning Technologies (CELT) at the British University in Egypt (BUE) [3]. These are, the drawing of the internal forces for statically determinate beams, the drawing of the internal forces for statically determinate frames, and the drawing of the elastic line for simply supported beams and cantilevers. 2.1

Internal Forces for Statically Determinate Beams

The interactive tool for structural analysis of statically determinate structures under static loads is an effective approach to introduce the concept of drawing a diagram that includes all internal forces acting on any section in a structure to a year one student in engineering schools. As a matter of fact, presenting these diagrams for particularly architectural students is a major challenge. These students usually have the perspective that such topics are irrelevant to their studies. The major challenge in teaching such

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topics to architectural students is to link theoretical modules to their interest in architectural design and to emphasize on the fact that structural analysis is a crucial module to help them estimate the dimensions of sections they design architecturally. Developing an interactive tool specially if it is in the form of a mobile application will gamify these tough modules for architectural students. The first tool is a simple beam with an overhanging part. The loading conditions include a partially uniformly distributed load with intensity w (kN/m) and length a (m) and point load P (kN) on both beam and overhanging part. The variables are introduced in the form of sliders to describe geometry and loads as shown in Fig. 1.

Fig. 1. Simple beam with an overhang part – loading cases.

Fig. 2. Simple beam with an overhanging part loading Case (1) – concentrated load.

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The solution provides the student with the reactions at the beam supports and the BMD and SFD. To present the merit of the developed tool, let us consider Case 1 of a concentrated load presented in Fig. 2. The output is easy to interpret as the loading case is simple, but for a case with a more complicated loading regime it is better to partition the load into simpler cases which can be displayed separately and when superimposed the resulting diagrams are easier to interpret. An example for the above learning technique is given in Fig. 3, showing a beam subjected to all loading cases together and the diagrams for the combined case are displayed.

Fig. 3. Simple beam with an overhanging part - combined loading case.

2.2

Internal Forces for Statically Determinate Frames

The second developed tool is a 2D statically determinate frame under static load. The frame span is L (m) and the column height is H (m). The loading cases are distributed load of value w (kN/m) and point load P (kN), on either the columns or the beam or simultaneously. The output includes reactions at supports in addition to the normal force diagram (NFD), shear force diagram (SFD) and bending moment diagram (BMD) as shown in Fig. 4. Complete shots for the different loading cases are given in Fig. 5.

Online Implementation of Structural Analysis Tool

Fig. 4. Statically determinate frame loading case (1).

Fig. 5. Statically determinate frame loading cases.

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Elastic Line for Simply Supported Beams and Cantilevers

The interactive tool for deflections was meant to introduce the concept of deformations of simply supported beams and cantilevers under a point load. The tool allows the student to develop an in-depth understanding of the behavior of deflections of simply supported beams and cantilevers under a point load and to determine the value of the deflection at any point along the beam. The equations for the elastic line were developed using the double integration method, by integrating the expression for the moment and applying the relative boundary conditions and continuity conditions to find the constants of integration. This was done for the case of a simply supported beam and a cantilever beam subjected to a single concentrated load. A drop-down menu was defined to choose between the case of a simply supported beam and a cantilever beam. Three parameters were defined, the span of the beam or the length of the cantilever L (m), the magnitude of the concentrated load P (kN), and the position of the concentrated load along the span a (m). These parameters were programmed to be input using a slider as shown in Figs. 6 and 7. The deflection curve was hence, drawn graphically along the span as shown in Figs. 6 and 7, and the exact value of the deflection could be shown by holding the pointer on a specific point on the curve.

Fig. 6. Interactive tool for determining the deflection of a simply supported beam under a single concentrated force.

Fig. 7. Interactive tool for determining the deflection of a cantilever beam under a single concentrated force.

This application may seem simple in appearance and easy to navigate, but it gives the deflection values of a much more complicated process of integration. It gives the student a visualization of the deflection curve and enables them to check their selfcomputed values. This tool has proved to be appealing to the student and worthy of future extensions for more loading conditions and statical systems. The only drawback

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in the deflection tool is the length of the process of integration and algebraic substitutions as the loading conditions and statical systems get more complicated. However, as the final product is a simple and effective tool for students of structural analysis the effort is worth making.

3 Implementation of the Tool in Teaching Activities The above-mentioned tools for both structural analysis of beams and frames and deflection calculation can be adopted as a teaching tool during class by introducing a certain problem to students; trying to solve it using first principals and then giving them the opportunity to check their answer using the mobile app. Such interactive classes, even for online classes, gives the class a dynamic ambient. Furthermore, as a dynamic interactive tool, it can be implemented to deliver certain concepts visually by giving the students the opportunity to try different loading values, structural dimensions, and to discuss how each parameter affects the output diagrams. As an example, if we consider the beam in Fig. 8 subject to a combined loading, Case (1) and Case (3), the student can try different combinations of load values and positions so that the beam reaction at the left support reduces to zero or even becomes inverted which means the beam transforms to a seesaw structure. Implementing this case on the tool is shown in Fig. 8. This cannot be achieved using conventional manual analysis methods as it needs many trials with a lot of calculations, while in the present tool it only needs the movement of the slider to see how the reactions are affected.

Fig. 8. Seesaw effect of inverting reactions.

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4 Deployment of the Tool in Assessments One of the characteristics of structural analysis course assessments is that the student may get a final answer of a certain problem which does not make sense due to lack of experience. In some cases, it needs a lot of calculations to check for the validity of the answer, which needs extra time that is allocated to other parts of the assessment. This is one of the big merits of such a tool. The student can use conventional ways to solve a problem and then check their answer using the mobile app. This approach gives the student a self-assessment tool without interference from the facilitator and will enhance the ability of the student to deal with different tasks at the same time, hence gives time allocation proficiency. One of the major challenges for online teaching is the risk of plagiarism due to lack of supervision. The developed tool can serve effectively to resolve this issue. The solution is to give each student a unique problem. This can be achieved by linking some of the problem parameters with the student ID. For marking the assessment, the teacher only needs to use the tool once for each student to get the model answer and mark accordingly. Other smart questions can be adopted by the teacher which need a lot of manual calculations which is not practical during the limited time of the assessment. This smart assessment is now feasible using the structural analysis tool. The advantage of such an online tool over the structural analysis software packages like SAP, ETABS, STAAD and others is the simplicity in using it, and the simultaneous response of the tool while changing parameters without the need to change an input file and running the program.

5 Conclusions and Recommendations Interactive tools have become imperative in the delivery of structural analysis modules. They are needed whether the teaching is in person or online as in the case of the implementation of the contingency plan for the Covid-19 pandemic. There is currently a gap in interactive tools for drawing internal forces and elastic lines in available interactive eBooks, which leads to the need to develop in-house applications. The advantages of having an available structural analysis tool both online and offline in the form of a mobile application is obvious in the delivery of lectures and tutorials, as well as the delivery of assessments. The dynamic nature of the tool enables easy visualization of the problem and facilitates the checking of hand-calculated answers. The future of the delivery of structural analysis modules is definitely heading for the need and use of such online structural analysis tools. Acknowledgements. The authors would like to express their gratitude to the Center of Emerging Technologies (CELT) at the British University in Egypt (BUE) for programming these online tools and making them available to the students and faculty of the university.

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References 1. Hibbeler, R.C.: Structural Analysis in SI Units, 10th edn. Pearson/Prentice-Hall, Upper Saddle Rive (2020) 2. Hibbeler, R.C.: Mechanics of Materials in SI Units, 10th edn. Pearson Education, Upper Saddle Rive (2018) 3. Center for Emerging Learning Technologies (CELT). https://celt-bue.netlify.app/#!/

Work in Progress: The Effectiveness of Using Blended Learning on Developing Egyptian EFL Learners’ Language Skills Wesam Khairy Morsi(&) The British University in Egypt, Cairo, Egypt [email protected]

Abstract. Blended learning (BL) is the integration of traditional classroom instruction with computer-mediated instruction. It has become a common approach in educational systems all over the world, and recently it has become a matter of considerable interest in teaching English as a foreign language (EFL). As opposed to online learning, BL complements face to face instruction with a wide variety of technologies that makes learning easier in the 21st century. This paper investigates the effectiveness of the BL approach on the learning outcomes and satisfaction of undergraduate students, taking an English language course in a private university in Egypt. A quasi-experimental research design will be implemented and sixty students will be chosen as the sample of participants. All students will receive the same instructional topics with regards to the reading and writing skills; forty students represent the study groups who receive BL through the flipped classroom method, e-learning and the use of an interactive e-book, while twenty students represent the control group who will only receive face to face instruction. The effectiveness of the BL approach will be measured by examining the development of the students’ reading and writing skills. The study groups will fill out a 21-item likert scale satisfaction questionnaire to evaluate the content of the course, the usefulness of e-learning, the instructor and interaction. Data of students’ pre-test and posttest will be analyzed, and a t-test will be used to find out the significant differences of the learning outcomes between the study groups and the control group. The t-test will also be conducted to identify learners’ satisfaction of the BL environment. Keywords: Blended learning


English language teaching
e-learning

1 Introduction The outbreak of the pandemic COVID-19 through the world has given the global community a hard time. The international academic calendar has been thrown into a state of disarray; all human endeavors have been affected on the social, political, and academic levels. According to the World Bank Reports (2020), closure of schools and universities has become a critical pillar of the social distancing tools to mitigate the spread of the disease. It was recommended in the early months of 2020 that governments should put contingency plans to prevent loss of learning, and hence stakeholders and management of higher educational institutions have immediately turned to online © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 456–465, 2021. https://doi.org/10.1007/978-3-030-67209-6_49

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learning tools for the continuation of academic activities across all schools worldwide (Demuyakor 2020). Education has long been challenged with the integration of technology to create more interactive learning conditions inside and outside the classroom (Brown 1994; 2006). Researchers have given several definitions to what technology integration means. Ruthven and Brindley (2005) argue that the way instructors use technology to reshape and make familiar classroom activities more effective is a definition of technology integration (cf. Ahmadi 2018). Dockstader (1999) adds that integration of technology should enhance the learning environment and provide opportunities for students to use computer programs to do their assignments instead of the paper and pen. Thus, the use of technology has become a must to support curricula design in all fields. However, during the lockdown of schools and higher educational institutions, technology has even become more involved in delivering lectures and tutorials virtually. Consequently, several challenges appeared since professional training was needed for instructors to master the use of different options of different online platforms and to customize materials and assessments that could be delivered to online audience. In addition, not all students have the digital literacy and skills to accommodate with the new learning environment; no doubt they have diverse needs and learning independently without a face to face support can be a challenge. As the new academic year 2020–2021 approaches with a no definite answer to the question when life would return back to normal, stakeholders and leaders of many institutions are considering BL as an attempt to minimize the drawbacks of a solely online learning. In Egypt, for instance, the Ministry of Higher Education would probably adopt BL in curriculum design all over the country to improve the instructional progression of learning by using technology. Because there is less literature on the “functional effectiveness” of the BL approach rather than on how to implement it (Tomlinson and Whittaker 2013 as cited in Rahim 2019), many researchers argue that its benefits in teaching and learning should be explored (Fakir 2015). Therefore, the purpose of this paper is to investigate how a BL format of an English language course affects freshmen’s development of language skills and academic performance compared to students in the traditional face to face environment. The study will also look into whether students are satisfied with the BL approach in learning the English language.

2 Literature Review 2.1

Blended Learning

Blended Learning has been defined and interpreted differently by researchers and educators. Thorne (2003) defined it as the best means of developing learning materials that suit the needs of students by using innovative, technological advances. Garrison and Vaughan (2007) argue that BL, “the thoughtful fusion of face-to-face and online learning experiences… Such that the strengths of each are blended into a unique learning experience. It is a fundamental redesign that transforms the structure of, and approach to, teaching and learning” (p. 5).

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On the other hand, Littlejohn and Peglar (2008) suggest the idea of the ‘strong’ and ‘weak’ blends on a continuum in which there is a range of a very small amount of e-learning to significant amount of e-learning. Therefore, there is no specific definition or explanation of BL (Picciano 2009). Timilson and Whittaker (2019) illustrate that a consensus definition of BL has not been reached because it is sometimes referred to as ‘e-learning’, ‘hybrid’ or ‘mixed’ in which online activities replace traditional learning 45% or ‘fully online’ in which 80% of activities are conducted online (p. 12). However, they believe that, many of the terms are synonymous and that in English Language Teaching (ELT) ‘blended learning’ is the term most commonly used to refer to any combination of face-to-face teaching with computer technology; or a combination of physical environment with virtual environment in which web-based technology is used. (Picciano 2009; Chen and Chiou 2014; Ma’arop and Embi 2016; Wichadee 2018). 2.2

Blended Learning and English Language Teaching

Over the past few years, “blended learning (BL) has been a popular topic in English language teaching (ELT) but it has expanded in many other academic subjects due to its usefulness.” (Lungu 2012, p. 470). It has become an indispensable teaching approach because it aligns with the current demands of education globally. It best suits the needs of the 21st century learners and matches their learning style. It makes both the teaching and learning process more effective and convenient (Wichadee 2018, p. 26; Ju and Mei 2018). As an exceptional mixture of the face to face instruction mode and online learning, BL offers more valuable opportunities for interaction that can be anywhere or anytime because of using computer-mediated tools and social media. For instance, students can participate in forum discussions to share ideas or exchange opinions; do online interactive quizzes; and submit assignments electronically (Dabbagh and Bannan-Ritland 2005). No doubt the quality of education provided to students can significantly improve if they are offered opportunities for collaboration and use of interesting technological tools (Starkie 2007). Such advantages of BL have caught the attention of many educators and syllabus designers because the remarkable connection that usually occurs between blended teaching techniques and students’ learning experiences can bring about high achievements in students’ language learning outcomes (Wichadee 2018). However, it is worth noting that adoption of such an approach in an EFL context requires further research for two main reasons. First, it takes time and commitment, and second it is a complete shift in the educational environment from a traditional face to face method to one in which BL is integrated. Thus, implementation of BL should be thoroughly examined when it comes to learning foreign languages (Rahim 2019). 2.3

Review of Previous Research

BL has become revolutionary in teaching foreign languages because the conventional teaching methods are usually unfair in the language teaching context (Albiladi and Alshareef 2019; Rahim 2019). Hybrid courses are considered a flexible platform for language learning that promotes student-centred education, engages learners in collaborative tasks and endorses better academic achievements. Students experience

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computer assisted language learning (CALL) within this environment. At least 30% of the course content is delivered through e-learning activities such as quizzes and synchronous and asynchronous discussion which complements a carefully planned face to face teaching (Neurmeier 2005). In 2006, Banados conducted a study of a communicative English course offered in a BL environment to improve learners’ language skills. Data were collected from 39 EFL undergraduate students who did a diagnostic test and a perception questionnaire. Findings showed that students were highly satisfied with the blended format of the course and that their linguistic skills had significantly improved. Results also implied that BL was an effective solution for language instruction. Kizil’s study in 2014 showed that 68 EFL students enrolled in Firat University School of Foreign Language in Turkey were significantly satisfied with the delivery of the English course, using the Moodle platform and face to face teaching. Students filled out a survey that focused on their engagement, learning and overall satisfaction of the course content, and delivery. Results showed that in-class teaching combined with “technology assisted language instruction” could create efficient language environments (p. 175). Another case study in a university in Moscow investigated BL versus traditional learning in foreign language teaching (Nazarenko 2015). Data were collected using two surveys from 32 (year 2015 students) and 31 (year 2014 students) of the second year. The survey addressed questions about new features of the blended course, using the flipped method in delivery, the virtual learning environment, the new leaning activities and the scoring/rating system of assessment. Findings revealed that 96% of the students were positive about BL; and 96% appreciated the user-friendly virtual learning environment that was supported by e-learning. However, there was a high percentage of non-favorable opinions about the extensive use of technology. For instance, using the ‘Flipped Classroom’ approach was the most ambiguous for a large number of students. The concept of the approach and the idea of self-study was not quite accepted by the students; and the online annotating and discussion activities were not popular because of their novelty. The author concluded that young students were sensitive and responsive to technology; yet, they needed professional and creative teachers to achieve success. AlKhaleel (2019) investigated the advantages of using BL in teaching 60 EFL female Prep. Year Program learners enrolled at the Medical Faculty in the University of Tabuk, Saudi Arabia. They filled out a 6-item likert scale questionnaire to evaluate how the participants perceived the influence of BL on improving their English Language skills. Findings revealed that the proficiency level of 84% of students were improved compared to the ones in the traditional method. Similar findings were found by Wichadee (2018). Wichadee examined students’ learning performance, satisfaction, attitudes, work load and digital literacy towards BL. She also investigated how learners perceived the quality of online learning and the face to face support. The participants were 149 students taking an English course that integrated listening, speaking, reading and writing in a private university in Thailand. Results showed that students had positive attitude towards learning with regards to convenience, freedom and being more responsible for their learning. They also perceived the quality of online learning tools and face to face support at a high level. The students learning performance was positively correlated with the digital literacy and face to face support, while their

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satisfaction was correlated with digital literacy, quality of online tools, workload management and attitudes towards BL. It was concluded that digital literacy and face to face support and attitudes towards BL were factors that should be thoroughly considered when designing blended courses. In conclusion, BL can effectively develop upheld and practical learning environments in which learning is merged with collaborations and innovations (Starkie 2007). Therefore, face to face support, students’ attitudes and user-friendly online tools should be considered by teachers and curricula designers because of their impact on the course success. The present study will not only investigate the effect of the BL environment of an English course on undergraduates’ academic achievement and development of their language skills, but it will also reveal whether students are satisfied with the course blended format or not.

3 Research Questions This study aims at answering the following research questions: 3:1. Does the BL environment have a positive effect on students’ learning outcomes with regards to their reading and writing skills? 3:2. What are the students’ satisfaction levels of the BL environment? Accordingly, the following research hypotheses are investigated: Hypothesis 1: There is no difference in students’ learning outcomes achieved in the two modes of instruction: face to face and blended learning. Hypothesis 2: There is no difference in students’ satisfaction with the two learning environments: traditional face to face and blended learning.

4 Research Methodology 4.1

Participants

Participants in the study are 60 freshmen who are enrolled in the faculty of informatics and computer science in a private university in Egypt. The students’ age ranges from 18–20 years. This sample of participants is drawn according to the convenient sampling procedures (Cohen et al. 2000). Their proficiency level in the English language will be measured by the APTIS placement test developed by the British Council language testers. The students’ proficiency levels are either upper intermediate or advanced. In semester 1, they take English for Academic Purposes course (EAP). The main aim of the course is to develop students’ English language and academic skills necessary to meet the demands of undergraduate courses in an English-speaking academic environment. The module focuses on listening/lecture note-taking, reading strategies, academic writing and speaking (group discussions and oral presentations). Due to time constraints in the study, only two skills (reading and writing) will be foregrounded by the researcher to measure the effectiveness of BL on students’ academic achievements

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and satisfaction. It is preferable to practice active listening/note-taking skills and speaking in class during specific time so that students are well trained for the final assessments. To assess students’ reading and writing skills, they will be taking a test with the same writing genre and types of reading questions in the first week of the semester (pre-test). 4.2

Integration of Blended Learning in the EAP Course

For the purpose of the BL environment, e-learning, the flipped method of delivery, and an interactive e-book: College Writing Skills with Readings (10th edition) will be used (Langan and Albright 2019). The e-book and the flipped method of delivery will be provided via e-learning. Instructors will meet the students twice a week for two hours. The e-learning pages are used for uploading material, videos, internet links, and interactive quizzes, posting forums, announcements and submission of assignments. The flipped method (which is another form of BL) will be adopted to further enhance students’ independent learning. Both BL and the flipped method have the same learning objectives which aims at providing a flexible, interactive, and motivating teaching and learning environment that caters for learners’ individual differences (Nazarenko 2015; Zhang and Zhu 2018). In a flipped classroom, students use technology to learn at their own pace about concepts and check their understanding by doing interactive quizzes before coming to class. The e-learning page is divided into a number of weeks. Each week is divided into three sections: pre-class, in-class and afterclass. In the ‘pre-class section’, educational videos and interactive quizzes will be provided for students to learn about concepts and test their knowledge. Both the students and instructors can view the grades of the pre-class quizzes. Students can watch the videos and attempt the quizzes several times. In class, time is dedicated for discussion and in-class practice. In the ‘in-class section’, there are handouts for activities and material to be covered face to face. The ‘after-class section’ is for assignments and extra practice uploaded for students. Two graded activities will be assigned to students from the interactive book each week. To further strengthen the BL strategies used in the EAP course, instructors can use the book to tailor material and activities for the face to face session; they can also assign students to do extra interactive practice as it provides instant feedback and tutorial videos to help students improve their language skills. 4.3

Procedures

There will be three groups in the study: two study groups (40 students) and one control group (20 students). In the first week, students are introduced to the course and are given introduction on how to use e-learning and the e-book. Students in both conditions of instruction will receive identical topics during the two scheduled sessions delivered each week; each session takes 100 min. The study will take place over 7 weeks. Delivery of lessons will be given by the same instructor. In week 1, after having an orientation session of the course, students will take the pre-test (reading and writing test). Students will be asked to write an essay and answer critical reading questions developed for an article.

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In the following weeks, students are introduced to the concepts of reading and genre of writing they will be practicing. In week 2, they are given one writing topic to work on it for the next 4 weeks, and they are given feedback on each step of the writing process. They also discuss two reading articles in class and answer critical reading questions. In week 5, students submit the final writing assignment individually. In week 6 a reading quiz will be conducted and students will also receive individual and generic feedback on their performance in the reading quiz and the writing assignment. In week 7, students will take the posttest (in-class reading and writing test). The study groups will use all the previous options of e-learning, flipped classroom method and the e-book. However, the control group will only be introduced to the materials in the face to face sessions. Concepts will be discussed only in class. The reading and writing practice will only be carried out in class, using handouts. The preclass content on e-learning will be deactivated for the control group and will be given in class. Students cannot watch the videos or the power points a second time unless they ask for it. Instructor prepares CDs with the videos for students to borrow (Chen and Chiou’s 2014). In Chen and Chiou’s study (2014), the teachers prepared a teaching live recording of course and all power points on CD – Rom formats and students were allowed to borrow them when needed. Unlike the study groups, students will not be assigned to do interactive reading or writing exercises in the e-book. They will do them at home, using handouts and bring it to class the next session. Feedback on the steps of the writing process or home assignments will be given face to face to the control group. Students will discuss their ideas and outlines for the writing assignment during class time. The instructor monitors them and group leaders will submit a hard copy progress report. Similarly, the two reading articles will be discussed in class. On the other hand, the study groups will be introduced to the concepts before class, following the flipped classroom approach. Class time will be dedicated for practicing these concepts. Students’ preparation and discussion of the writing assignment or reading strategies with their instructor will be done mostly virtually using e-learning discussion forums. They will exchange ideas and share their writing with their peers. The study group progress reports will be posted on e-learning to be checked by the instructor. Teacher gives the study group feedback on the writing assignment online via e-learning. In week 5, both groups submit the individual writing assignment and take the reading quiz. They will also fill out the ‘Student Satisfaction Questionnaire’ adapted from Kizil (2014) and Wichadee (2018) about their BL experience (See Appendix). In week 6, they receive feedback. A conference will be held in class for the control group where students receive a course feedback form filled out by the instructor, while the study groups will receive the generic feedback in class and the individual feedback will be posted on e-learning for each student. In week 7, students take the reading/writing in class test (posttest). 4.4

Measurement and Analysis

This is a quasi-experimental research design. It will be examining students’ satisfaction and academic achievement in two kinds of instructional environments: BL environment

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and traditional classroom environment. The grades of the in-class reading and writing tests will be counted as students’ academic achievement. Learning satisfaction will be evaluated using ‘Student Satisfaction Questionnaire’ adapted from (Kizil 2014; Wichadee 2018). The questionnaire has brief information about the research purpose and a note that the data collected will remain confidential. The questionnaire is divided into four sections: blended course content, e-learning, instructor and interaction. Students will respond to 21 questions provided in a five rating scale (1 = strongly disagree to 5 = strongly agree). The questionnaire ends with three-open ended questions that are adapted from Yapici (2016), asking students about the benefits and drawbacks of the BL environment in developing their language skills and about the aspects they would like to improve about the course if they were to take the course again. Results from this questionnaire will show students’ levels of satisfaction of the delivery of EAP course, following the BL approach. Finally, independent samples t-test will be conducted to find out the differences between the pre-test scores and the posttest scores of the reading and writing tests among the study groups and the control group. The t-test will also be used to reveal the relationship between students’ learning satisfaction in the study groups and the control group.

Appendix Student Satisfaction Questionnaire of Blended Learning A. Students’ Satisfaction with Blended Course Content 1. The course content delivered in the face-to-face sessions is suitable for me to learn. 2. I understand the concept of the flipped classroom method and find it effective in learning and improving my language skills. 3. The materials designed in the flipped mode (Pre-class quizzes) and after class (interactive quizzes) are appropriate and relevant to the course content. 4. The assessment criteria for each assignment are clear. 5. Duration of doing each assignment is appropriate. 6. The use of e-learning allows me to participate at times that are convenient for me. 7. The ability to access course information and content through e-learning is important. 8. In terms of technology, I feel comfortable using e-learning. 9. Using e-learning has been difficult for me. 10. Using an interactive e-book is very effective to improve my skills. 11. Using the interactive e-book is not necessary in this course. 12. In terms of technology, an interactive e-book is difficult for me to use. 13. The use of e-learning provides me with options that meet my learning needs and learning style.

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B. Satisfaction with instructor 14. The instructor is able to explain the content clearly. 15. The supplementary interactive quizzes provided in the e-book are clear and helps in reinforcing the course content. 16. Classroom assignments are clearly communicated to me. 17. Feedback on assignments is given in a timely manner. 18. The instructor is able to use blended learning technology. C. Satisfaction with interactivity 19. Teacher-student interaction is appropriately maintained in online and face to face sessions. 20. I am satisfied in the way I interact with other students in online and face to face sessions. 21. I am satisfied with my peer collaboration in groups to complete assigned tasks. D. Please answer the following questions: 1. What do you think are the benefits of teaching the EAP course using the blended learning environment?. .......................................................................... 2. What do you think are the disadvantages of teaching the EAP course using the blended learning environment?............................................................................. 3. What are your suggestions for improvement of the EAP course?.........................

References Ahmadi, M.: The use of technology in English language learning: a literature review. Int. J. Engl. Res. Engl. Educ. 3(2), 116–125 (2018) Albiladi, S., Alshareef, W.: Blended learning in English teaching and learning: a review of the current literature. J. Lang. Teach. Res. 10(2), 232 (2019) AlKhaleel, A.: The advantages of using blended learning in studying English as a foreign language in the University of Tabuk. Mod. Lang. J. Lang. Teach. Methods 9, 1–7 (2019) Banados, E.: A blended-learning pedagogical model for teaching and learning EFL successfully through an online interactive multimedia environment. CALICO J. 23(3), 533–550 (2006) Brown, D.: Teaching by Principles: An Interactive Approach to Language Pedagogy. Prentice Hall Regents, Englewood Cliffs (1994) Brown, D.: Principles of Language Teaching and Learning, 5th edn. Pearson Education, Upper Saddle River (2006) Chang-Tik, C.: Impact of leaning styles on the community of inquiry presences in multidisciplinary blended learning environments. Interact. Learn. Environ. 26(6), 827–838 (2018) Chen, B., Chiou, H.: Learning style, sense of community and learning effectiveness in hybrid learning environment. Interact. Learn. Environ. 22(4), 485–496 (2014) Cohen, L., Manion, L., Morrison, K.: Research Methods in Education, 5th edn. Routledge Falmer, London (2000) Dabbagh, N., Bannan-Ritland, B.: Online Learning: Concepts, Strategies, and Application. Pearson Education Inc., New Jersey (2005)

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Demuyakor, J.: Coronovirus (COVID-19) and online learning in higher institutions of education: a survey of the perceptions of Ghanaian international students in China. Online J. Commun. Media Technol. 10(3), 1–9 (2020) Dockstader, J.: Teachers of 21st century know the what, why and how of technology integration. Technol. Horiz. Educ. 26(6), 73–74 (1999) Fakhir, Z.: The impact of blended learning on the achievement of English language students; and their attitudes towards it (Master’s thesis). Middle East University (2015) Garrison, D., Vaughan, N.: Blended learning in higher education: framework, principles, and guidelines. Jossey-Bass, San Francisco (2007) Ju, S., Mei, S.: Perceptions and practices of blended learning in foreign language at USIM. Eur. J. Soc. Sci. Educ. Res. 12(1), 170–176 (2018) Kizil, A.: Blended instruction for EFL learners: engagement, learning and course satisfaction. JALT CALL J. 10, 175–188 (2014) Lungu, I.: The increasing need of blended learning models in courses of English for specific ppurposes. Procedia Soc. Behav. Sci. 70(2013), 470 (2012) Littlejohn, A., Peglar, C.: Preparing for blended e-learning. Br. J. Edu. Technol. 39(4), 749–469 (2008) Ma’arop, A., Embi, M.: Implementation of blended learning in higher learning institutions: a review of literature. Int. Educ. Stud. 9(3), 41–52 (2016) Langan, J., Albright, Z.: College Writing Skills with Readings, 10th edn. Mc-Grew-Hill Connect (2019) Nazarenko, A.: Blended learning versus traditional learning: what works? (A case study research). Procedia Soc. Behav. Sci. 200(2015), 77–82 (2015) Neumeier, P.: A closer look at blended learning: parameters for designing a blended learning environment for language teaching and learning. Recall 17(2), 163–178 (2005) Thorne, K.: Blended learning: How to integrate online and traditional learning. Kogan Page, London (2003) Picciano, A.: Blending with purpose: the multimodal model. J. Asynchronous Learn. Netw. 13 (1), 7–18 (2009) Rahim, M.: The use of blended learning approach in EFL education. Int. J. Eng. Adv. Technol. 8 (5), 2249–8958 (2019) Thyer, B.: Quasi Experimental Research Designs. Oxford University Press, New York (2012) Tomlinson, B., Whittaker, C.: Blended Learning in English Language Teaching: Course Design and Implementation. British Council, London (2013) Wichadee, S.: Significant predictors for blended learning effectiveness in a language course. JALT CALL J. 14(1), 25–42 (2018) Yapici, I.: Effectiveness of blended cooperative learning environment in biology teaching: classroom community sense, academic achievement and satisfaction. J. Educ. Train. 4(4), 269–280 (2016) Zhang, W., Zhu, C.: Comparing learning outcomes of blended learning and traditional face-toface learning of university students in ESL courses. Int. J. E-Learn. 17(2), 251–273 (2018)

Effectiveness of E-Assessment in Quantitative Modules, COVID-19 Consequences: A Case Study by the British University in Egypt Wafaa Salah(&) , Mohamed Ramadan and Hossameldin Ahmed

,

The British University of Egypt, Cairo, Egypt {Wafaa.Salah,Mohamed.Ramadan, Hossameldin.Ahmed}@bue.edu.eg

Abstract. The Covid-19 pandemic has globally influenced higher education, prompting the closure of thousands of universities as a key strategy for social distancing. Therefore, universities faced a new set of challenges; on top of them was the unprecedented request for e-assessments, instead of on-CAMPUS assessments. This paper presents the findings of a case study conducted at the Faculty of Business Administration, Economics and Political Science (BAEPS) at the British University in Egypt (BUE) over the second semester of the academic year 2019–2020. The case-study aimed to assess the fast BAEPS response to the challenges of the new assessment mechanism, which have been conducted using various interactive educational platforms. Additionally, this paper aims to examine the degree to which the results of the e-assessment conducted during the pandemic are consistent with traditional paper assessment. The first conclusion was the existence of a significant difference between eassessment and paper assessment, which may very well be due to the open-book nature of e-assessments. However, the paper concluded that the value of uniqueness and time factors in the design of e-assessment shrink the results gap between both types. The evidence showed the ability of e-assessment to overcome the main threat, which is external support to students, through the proper assessment design. Moreover, the paper concluded the efficiency of e-assessments to significantly reflect actual students’ capabilities and achievements in quantitative modules. Finally, the authors emphasized that e-assessment has noticeably become mandatory for the future of education in the fourth industrial revolution. Keywords: Online exam
E-assessments
COVID-19
Education revolution
Digital transformation
Higher educational
Egypt

1 Introduction The world has experienced a global crisis arising from the rapid spread of COVID-19, which has impacted higher education, by the start of 2020. Most educational institutions locked down their doors and students returned home for quarantine. UNESCO [1] announced that 1,576,873,546 students were affected, representing 90.1% of all students registered in 190 countries, at all levels of education. The academic year © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 466–477, 2021. https://doi.org/10.1007/978-3-030-67209-6_50

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2019/2020 was a significant challenge for universities worldwide, and the magnitude of this crisis varied from one university to another, due to differences in technological advances and educational platforms. In fact, in a very limited time period, thousands of universities enforced online learning. Online learning can be defined as a learning experience, which is used for studying and connecting virtually from almost anywhere with teachers and other students, through a wide variety of devices; including laptops and mobiles, in synchronous or asynchronous environments [2]. In Egypt, as a result of the crisis, the Egyptian supreme council of universities declared temporary suspension of on-campus classes, and replaced all written and oral assessments scheduled for the second semester of the academic year 2019/2020 with projects and e-assessments. As a response, BUE decided to continue teaching its various curricula entirely online. Prior to COVID-19, modules were designed for face-to-face learning and oncampus examinations. The Learning Management Information System (LMIS) platform was essentially utilized to post information and supporting material for students, ungraded assignments, and facilitate contact with students. As a result of the suspension, LMIS was used for online learning, e-assessments, and projects to relate the assessment of the module to the expected Intended Learning Objectives (ILOs). LMIS is a web-based assignment and assessment tool for students to interact with their coursework and make it more effective to evaluate students’ performance. The analytical reports furnished allowed the university to meet the requirements decreed by its British partner university, that required a thorough analysis of student performance, in particular of assessments representing the achievement of the ILOs. BAEPS worthily deserves the credit for professionally taking the initiative to conduct e-assessments for more than 2000 Students through LMIS. The assessments are conducted after the students completed the curriculum through online learning. The students are allowed to solve exam questions and problems based on the covered content to make sure that learning results are achieved [3]. Module leaders were required to construct pools of algorithmic examination questions, with varying difficulty levels, to have different versions of exams for cheating reduction. In addition, the students were familiar with the exam time limit and system functionality through mock exams created by their module leaders. A zoom session was created during the examination process to provide real-time responsive technical assistance to the students. Nowadays online classrooms and assessments are increasingly in demand, particularly after the COVID-19 pandemic. The results of various studies indicate that in an adequate technical environment and support, online learning can be used successfully in education [4–6]. According to UNESCO [1] technology will reshape universities by 2030 and the relatively new online education system will be as those based on universities. The Egyptian supreme council of universities is encouraging educational institutions to implement hybrid teaching and learning plans starting from the academic year 2020/2021. In addition, a collaboration agreement for the creation of an e-assessment program for universities was signedby both the Ministryof Higher Education andScientific Research andthe Ministryof Communications and Information Technology. However, adopting online learning system requires significant planning, reliable infrastructure and investments [7]. It is important to track, develop, and enhance the best methods and practices of delivery to ensure high quality education and a suitable

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student learning experience. Besides, university management and educators need to feel confident that using digital technologies in student assessments and online classes will guarantee the desired outcomes to ensure a successful experience for their students and themselves. In fact, educators need to be confident that online student performance is similar to traditional on-campus interaction. Along this thought, Toquero [8] argues that further studies are needed to track the impact of the Covid-19 pandemic on the educational system. Ultimately, changes in university assessments and teaching methods should always be accompanied by rigorous studies which investigate both the strengths and weaknesses of each new or old approach in relation to learning outcomes. The reviewed literature, which will be explored in detail in the second section, has produced mixed findings for the effectiveness of e-assessments, which may prevent the use of e-assessments by learners. Thus, the objective of this study is to add to the body of literature investigating performance differences between paper-based and electronic assessments during the COVID-19. The following research questions have been developed accordingly: RQ1: To what extent are the results of the e-assessment mechanism homogeneous with traditional paper assessment? RQ2: To what extent could the e-Assessment mechanism efficiently evaluate the true performance of students in quantitative modules? The results of this study may be of interest to university management and administrators seeking to determine how use of digital technology will achieve the desired learning outcomes and the required decisions, concerning the implementation of online learning programs, in the event of any potential sudden closure, due to health emergencies. Notably as well, the findings may be useful to educators who may gradually realize the importance of online learning and assessment as a means of enhancing their teaching, intellectual, and time management skills. The present study can considerably assist them in developing and delivering remote e-assessments. This study contributes to the literature by revealing the difference between traditional paper exams and e-assessments. To elaborate, the findings may be of great value to educational authorities who will propose transforming education through the incorporation of e-assessments and online classes into current traditional teaching and learning. The rest of the paper is organized as follows: Sect. 2 presents the literature review. Section 3 displays the data and research method, followed by the results and discussions, and finally the conclusion.

2 Literature Review Since the 1840s, online learning has taken root in distance learning and was organized via the Internet by unlimited Massive Open Online Training (MOOCs). This has continues to grow in recent decades, and played a growing role in higher education. The enrollment’s growth rate in online courses reached 9% annually [9], with several major universities; including Harvard, Peking, and Oxford, gradually changing their curricula online and reducing on-campus delivery [7]. The aforementioned universities have started providing unlimited access to Massive Open Online Training (MOOCs)

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through various providers, including Coursera, Khan academy, Edx, and Edraak. However, online learning has often faced opposition from institutions and even students themselves, but the widespread of the COVID-19 pandemic and the uncertainty surrounding the return of on-campus classrooms may put an end to such resistance. Supporters of the phenomenon point out that online learning has several advantages for students, university administrators, and educators. Students who find it hard to meet a timetable on campus are granted more flexibility in their online classes. They are likely to learn effectively from online classes because they tend to be better coordinated, study without close supervision, and have greater control over their studies [5, 6]. Educators can reduce cheating by creating algorithmic question pools, and then use randomized functions that distribute different versions of exams among students [10]. Although the above arguments endorse online learning and assessments, it should be noted that the counter arguments are, naturally, not so supportive. For instance, Werhner [6] mentions that online classes lack social interaction, motivation and teacher support. Students are sometimes found lacking equipment, internet connection, or motivation, and find difficulty in online learning. Earlier work by Cavanaugh and Jacquemin [9] shows that students with low GPAs are suffering in online classes in contrast to those on campus. Zhu and Liu [11] add that universities are in need of a high margin of investment in professional development, secure digital infrastructure, and networks, as well as comprehensive online teaching and learning quality assurance systems. In a similar vein, Ali [12] addresses several online learning deficiencies; such as confusion and dispute regarding online learning strategies, teacher inexperience, information gap, teaching environment, and complex home environment. In response to the pandemic, the faculty of BAEPS subverted traditional paper assessments into digital assessments for quantitative modules. The LMIS tool was used utilized to design and conduct the e-assessments. Some literature finds that students have exhibited a positive perception towards e-assessments in a Decision Support System Course et al. Bayt University. In a similar vein, Elmehdi and Ibrahem [10] have found that students were more supportive of e-assessments on issues concerning the added value and benefits of online examinations, particularly logistical assessments and the improvement of teaching and learning. In accordance with these findings, there was no significant difference in students’ perception of the level of cheating in online classrooms, versus face-to-face classrooms [13, 14]. An interesting study conducted by Still and Still [14], comparing students' learning results with traditional paper assessments, in comparison with e-assessment shows that the desired results between the two types of assessments have no significant variations.

3 Methodology The proposed methodology in this paper is to merge the qualitative and quantitative analysis techniques for the purpose of analyzing the under-focus case study. The proposed methodology is based on the case of the Statistics Module that had been taught to Preparatory-Year Students in the BUE during the spring semester of the academic year 2019–2020. To answer the main research questions in this paper, it is important to investigate two dimensions; first is the stability of the e-assessment results

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of this module, Statistics Module (in 2019–2020), in comparison with the paper assessment results of the same module, Statistics Module in the previous academic year (2018–2019). This comparison, indeed, means that the stability of the module results is under investigation across time, which examines different specimens, without paying attention to the factor of the students’ capabilities. In other words, the sample can be considered to be non-stochastic, where the students' feature doesn’t dramatically vary from one specimen to another. Therefore, another analytical dimension between the Statistics Module (in 2019–2020) and a similar module for the same subject under investigation should be introduced to trace to what extent the e-assessment converged to reflect the true specimen’s capabilities and academic achievement. Accordingly, the Mathematics Module has been chosen for contrast. This module was taught during the same academic year (2019–2020), but during the fall semester. This indicates two visible advantages of using the Mathematics Module. First, both modules not only belong to the general quantitative modules, but they also belong to a very tight category of specialization in statistics and mathematics. Second, these modules represent a situation before and after the COVID-19 pandemic, which not only means that one of them was traditional paper assessment and the second is e-assessment, but also, they showcase to what extent was the education system after COVID-19 successful in continuing as it did before the pandemic. Along with the analysis, there will be extensive use of inferential statistics to test the proposed research questions, which are hypothesized. Moreover, the analysis attempts to employ the SWOT analysis, as one of the qualitative techniques, to support and interpret the results of the used quantitative techniques.

4 Results and Discussions This part was devoted to providing sufficient evidence on the proposed research questions, which were mentioned in the introduction part. To provide a comprehensive analysis and answer the research questions, the authors decided to follow the casestudy analysis approach. The selected case is the Statistics Module in the Business School, which is being introduced to Preparatory-Year Students. The main force-power behind this case was the COVID-19 lockdown, which forced educational systems worldwide to search for more suitable alternative assessments in the era of social distancing. Accordingly, BUE decided to acclimate its alternative assessment techniques, based on two factors: the nature of the module, as well as the Intendent Learning Objectives (ILOs). However, as a direct consequence of the COVID-19 pandemic, there was an urgent need to re-engineer the assessment methodology in the selected module, Statistics in Business, to be an e-assessment, based on one of the common interactive platforms, instead of traditional on-CAMPUS paper assessment. Through the analysis of this case study, as mentioned in the methodology section, the SWOT analysis will be the higher-level frame of the analytical approach, while the second detailed level will depend, mainly, on the quantitative techniques. The importance of such a methodological approach is to understand the results of the comparison between e-assessments and paper assessments. This paper does not investigate whether or not there is a difference between both approaches, as much as it

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investigates the reasons, or the circumstances, that could lead to minimizing the deviation of the results that have been extracted from e-assessments in relation to the expected results that should be extracted from effective assessment, which could easily be achieved through the traditional on-CAMPUS paper assessment. The first dimension of analyzing this case study, which could be thought as one of the important strengths, is “To Be Ready”. In fact, nothing could be worse than implementing a new system without making sure that all relevant stakeholders are well trained, and ready to efficiently use this system. Therefore, the first step was to train the module team and the students by exposing both sides to the real simulated situation, which helped them to identify the pros and cons of such a new experience. For the module team, it was important, indeed, to make sure that this sort of assessments would allow them to perform the relevant effective assessment, which could efficiently assess the Module’s ILOs, or what could be ultimately described as the pedagogical side of the assessment. Of course, the module team will also have kept in mind the other side of the assessment process, which is more relevant to the logistics. On the contrary side, it was also important for the students to train themselves on such alternative assessment approaches, to avoid any sort of shock or unpreparedness because of not being aware of the optimal requirements for such assessment techniques. There is no doubt that any e-assessment is considered a digitalized version of openbook assessments. This point is the second dimension of analyzing the proposed casestudy. Various types of open-book assessments are mostly characterized by somehow biased curves toward the highest grade. Off course, this curve could be controlled through the assessment criteria to avoid any inflation. Accordingly, the most important hazard in any kind of open-book assessments is inflated grades, either because of the lack of appropriate difficulty level, or the lack of uniqueness that facilitates plagiarism and cheating among students. To analyze the case-study from the second perspective, the authors brought two results for the Statistics module, one after the COVID-19 semester (Spring 2019– 2020), which means that it was carried out by using e-assessment, and another one came from the previous academic year (2018–2019), which indicates utilization of the traditional paper assessment approach. The distributions of both Statistics modules show that the final results are approximately symmetric for both academic years. However, the comparison of the two averages showed that there is a significant increase in the average during the post-COVID-19 period, versus the pre COVID-19 period. The average of the Statistics Module recorded a highly significant increase from 54.8% for students that experienced the paper assessment to about 63.1% for students that experienced the e-assessment. In addition to that, due to the certain presence of outliers, median will be less sensitive to them than the arithmetic mean, where the median mark for the Statistics module has notably increased from 57.5% in the traditional paper assessment in 2018–2019 to 65.0% in the e-assessment in 2019–2020. The second note on the distribution relates to the dispersion of students' distributions. The standard deviation showed that the scores achieved by students that experienced the e-assessment were much tight in comparison to the scores of the students that experienced the paper assessment. This observation could rely on the scarcity of low scores in the e-assessment, which could be translated into a lesser failure rate in e-assessment in comparison to previous paper assessments. As Figs. 1 and 2

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Fig. 1. The histogram for the final results of the Statistics Module in the academic year 2019–2020.

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summarize the observations on the scores of the two modules, they present more symmetric and homogeneous scores in e-assessments, in comparison with paper assessments, and a more flattening distribution, that covers most of the scores' range in paper assessments compared to e-assessments. The above analysis of the differences between e-assessments and paper assessments in the case of the Statistics Module for Preparatory-Year students in the BUE, could lead to deduce that e-assessment is more biased toward higher grades, which is to be expected, as mentioned earlier, due to the fundamental nature of open-book assessments, which contributes to less failure rate. It is worthwhile to mention that the failure rate in paper assessments was 19.8%, which decreased to about 5.8% in e-assessments. This finding could be thought of as one of the main threats that face e-assessments. Defiantly, the phenomenon of inflated grades is one of the ultimately crucial threats of any sort of assessment, especially e-assessments, because a significant part of the assessment process is not carried out under proper academic proctoring. “Uniqueness”… This word could be the miracle that will give the module team the power to prevent many kinds of support to the enrolled students during the assessment process, thence, controlling the final grades. Therefore, the question is how to design your e-assessment to be unique?… There are some features that could build the uniqueness of the e-assessment, which start with the algorithmic feature. In the algorithmic feature, the questions are designed to generate random givens and inputs to the students in any quantitative module, thence, the final results, and maybe the steps, will vary across students. This feature may limit students from resorting to each other, but it will not, indeed, prevent students to at least share the steps. Therefore, the pooling feature is considered a very important compliment to the algorithmic feature. The pooling feature is to design a set of questions, as a pool, that some of its questions will be randomly dedicated to each student. Each pool should consist of homogeneous questions, to guarantee fairness. The idea of pooling is to more and more guarantee the student assessment uniqueness, through providing each student with a semi set of unique questions. The third way to achieve a more unique assessment is the scrambling feature, which scrambles the order of questions over the system per each student. Thereby, due to these three features, students would ideally have a very low probability to face the same questions and/or the same numeric assumptions, which, indeed, illustrates the uniqueness of the assessment.

Fig. 2. The histogram for the final results of the Statistics Module in the academic year 2018–2019.

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Table 1. Descriptive statistics for the proposed three modules. Measure Mean Median Standard deviation 95% confidence interval

Statistics (2019– 2020) 63.1 65.0 15.5 61.7: 64.5

Mathematics (2019– 2020) 55.2 58.0 22.4 53.1: 57.2

Statistics (2018– 2019) 54.8 57.5 21.3 52.7: 56.8

Is Uniqueness sufficient to prohibit the phenomenon of inflated grades?… Unfortunately, the answer is NO. Subsequently, the importance of time factor is, thus, being spotted. There is no meaning to giving students a short unique assessment, as they will tend to resort to each other. Thereby, the optimal adjusting of the revision time during the assessment is an important determinant to avoid any casual time during the assessment. This factor has a sociological impact on members who are considered as achievers within the student-body, who are considered as the main source of expected support to other students, because it will decrease their level of generous support. Moreover, more pressure on time means less tendency to research solutions or similar ideas over the internet. To wrap-up this threat, the uniqueness and time factors are very important in designing any e-assessment, which has been introduced in the online version of the Statistics Module. As a direct result of the implementation of these features on the module, the average of the final results, as mentioned earlier, only increased about 10 marks, compared to the paper version of this module. Although this increment in the overall average between the two approaches, which is very important of course, demonstrates the good point of the existence of variability of scores, i.e. there is a good shape for score distribution that guarantees distinction between different students' achievements. The third dimension in analyzing this case study is the assessment of the feasibility of the e-assessment as an effective mode of assessment. In this regard, and to answer this question, it is imperative to understand how the e-assessment of the Statistics Module was able to reflect the actual performance of students and their academic achievements. Thereby, this paper utilized the advantage of having another module, the Mathematics Module, which had been taught to the same students, but during the fall semester of the same academic year, i.e. before the spread of COVID-19. Hence, the following section will be devoted to analyzing the relationship between both the Statistics and Mathematics Modules in the academic year 2019–2020. Before comparing the Mathematics Module with the Statistics Module in the academic year 2019–2020, it is worthwhile to compare between Mathematics Module in (2019–2020) and the Statistics Module in (2018–2019). The conclusion that the authors were able to extract from comparing both modules is the similarity in pattern and features of the final results in both modules. For instance, Table 1 and Figs. 2 and 3

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show the highly significant convergence1 between the two modules’ final results, either in average, or in coverage for different grades. The purpose of this comparison is to conclude that the final results of both Mathematics (2019–2020) and Statistics (2018– 2019) are belonging to the same family of the paper assessment method. Therefore, the analysis of the relationship between the Statistics and Mathematics Modules (2019– 2020) investigates two main dimensions: the effectiveness of the e-assessment to reflect students' capabilities in quantitative modules, especially that both modules had been taught to the same students and in the same academic year; as well as it could be thought of as another validation for the e-assessment approach through comparison with the paper assessment (Fig. 4). In the comparison between both modules, two types of correlation measures were introduced; Pearson and Spearman correlation coefficients, as each of them will test a specific argument. Starting with Pearson’s Correlation Coefficient, which hit 52.6%, and was highly significant (p-value < 0.001). Accordingly, the correlation coefficient showed the existence of a moderate association relationship between the final results of both the Statistics and Mathematics Modules (2019–2020). It is important to emphasize again that these two modules were taught to the same students in one academic year, but the Mathematics Module was taught during the fall semester, meaning pre-COVID19, thus it was a paper assessment, while the Statistics Module was taught in the spring semester, meaning post-COVID-19, thus it was an e-assessment. The results of the Pearson Correlation Coefficient could lead to deducing the highly significant correlation between the achieved score, as a value, for the same student through both modules.

1

The Independent Samples T-Test was performed under the condition of equal variance between the Mathematics Module (2019–2020), which was taught during the fall semester, and the Statistics Module (2018–2019), which means that both were paper assessments, as they were before COVID19. The test statistics were insignificant, because the p-value > 0.1 was at a significance level of 5%. Therefore, the null hypothesis that the difference between the two means is insignificant was not rejected, which means that it could conclude the existence of a statistical insignificancy between the means of both modules' final results.

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Sometimes it is not the values of two random variables that are in the focus, because more important focus should be devoted to the rational position of the sampled subjects between those two random variables. This is could be the thought in this case. The modules are within the same family because both are quantitative modules, as well as mathematics and statistics are much too related, but this does not detract from the fact that the comparison is for two different modules. Therefore, Spearman’s Correlation Coefficient will be used to test the association between the ranks of the students in both modules2. The results showed another evidence of the moderate association between the students’ rank/position within the final results of the two assessments. Accordingly, the two previous results showed that the students’ scores, as well as their ranks in both assessments, have a moderate relationship. In addition to the introduced correlation coefficients, the results of the regression analysis between the Statistics Module, as an endogenous variable, and the Mathematics Module, as an exogenous variable, were introduced. Therefore, leads to the question of to what extend could the Mathematics Module be efficient to explain the variations in the final results of the Statistics Module. The regression equation showed that Mathematics results of this specimen could explain about 27.5% (adjusted Rsquare) of the variations in the Statistics results of the same specimen. Although this explanation of power is not that strong, it is highly significant (ANOVA Pvalue < 0.01). The unexplained percent of the variations in the results of the Statistics Module could rely on various factors, such as the experience that the students concluded from the Mathematics Module, as well as the increased familiarity with the university system, especially the assessment mechanism and criteria…etc. However, the authors were still able to conclude that the e-assessment for the Statistics Module (2019–2020) was able to capture students’ achievements. The previous analysis was mainly focused on the evaluation dimension of the assessment process. On the complement side, there are other dimensions that should be investigated. For instance, the logistics dimension, which is an extensive time and cost consuming dimension. The academic staff in education institutes knows well the burden of time that is being consumed to mark assignments, quizzes, as well as assessments. This factor is being visibly minimized in e-assessments, especially in the case of using professional e-assessment platforms. Moreover, this sort of e-assessments is probably thought of as less costly in comparison to traditional paper assessments, as well as it is environment-friendly because of its paperless feature. This is, of course, one of the strengths for digitalizing the assessment system in any educational institution. However, the untrained staff or students on e-assessment mechanisms are still the most important weak point in this regard. The final part of the analysis section is to highlight the opportunity, which is the last part of the SWOT analysis. During the last two decades, developed countries have started a real digitalization process, which was a matter of increasing countries' efficiency and competitiveness. However, after the COVID-19 pandemic, the whole world now believes in the new-normal. Accordingly, digitalization has become more mandatory, which

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The data was divided into deciles to be more categorized, then the Spearman’s Correlation Coefficient was applied to the categorized data.

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stressed the decisions of various stakeholders all over the world. Therefore, the opportunity, from the authors' point of view, is still valid for rapidly digitalizing education systems to attach to the current worldwide revolution in education.

5 Conclusion Due to the unexpected sudden existence of COVID-19 and its unpredictable time frame to end, educational institutions have accordingly become forced to reconsider their strategy and mechanisms for teaching and delivery. COVID-19 has generously granted educational institutions worldwide a very good opportunity to adopt serious implementation for new technologies and methodologies to meet their pre-determined objectives for teaching and learning. The adoption of these new strategies should be executed in the frame of both effective planning and timely manner in decision making which are stemmed from clear vision for online communicative classrooms and eassessing systems. Through the performed analysis, the proposed paper concluded to a generic framework of SWOT for e-assessment mechanisms. Starting with the strengths, the analysis showed the significant success of e-assessments to reflect real students’ achievements fairly and efficiently. This convergence was not completely achieved because of the main threat that faces any e-assessment, which basically points at external support that students may have from whatever human or non-human sources. In this regard, the e-assessment design, basically the features of algorithms, pooling and scrambling, as well as the time factor, are all considered determinant factors for maximizing the uniqueness of the student’s assessment and minimizing students' willingness to search for any kind of external support. As a result of that, taking these features into consideration has led to very high similarity in the outputs between both paper and e-assessments. In addition to that, module teams and students must live the experience of real assessments, such as a training simulating experiments, to extract all actual and potential drawbacks before the actual assessment. On the other hand, raising awareness among academic staff of the importance of following clear guidelines for creating effective unique e-assessments that are completely different from paper-based examinations has become a mandatory step to avoid potential inconsistency in assessment preparation. There is a current opportunity for any education system/institute to join the running education revolution, which is basically a part of the fourth industrial revolution. Thereby, digitalizing the whole education system in general, and the assessment mechanism in particular, has become a must, and no longer could be thought of as an auxiliary strategy. Despite that, other factors should be developed soon, such as designing and activating effective proctoring systems. Other modules from different faculties and universities can be included in the sample of study as well. Moreover, future investigations in this field may also include the perceptions of faculty members as well. Future studies need to demonstrate the effective response of education institutions to another potential epidemic or circumstance. In addition, future studies need to focus on the methods to be implemented in online learning such as online training practices, implementation, and the design of online curriculum.

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References 1. UNESCO. Global Monitoring of School Closures caused by COVID-19 (2020). https://en. unesco.org/covid19/educationresponse. Accessed 16 2020 2. Singh, V., Thurman, A.: How many ways can we define online learning? A systematic literature review of definitions of online learning (1988–2018). Am. J. Distance Educ. 33(4), 289–306 (2019) 3. Garrison, C., Ehringhaus, M.: Formative and summative assessments in the classroom (2007) 4. Basilaia, G., Kvavadze, D.: Transition to online education in schools during a SARS-CoV-2 coronavirus (COVID-19) pandemic in Georgia. Pedagogical Res. 5(4), 1–9 (2020) 5. Wang, H., Pi, Z., Hu, W.: The instructor’s gaze guidance in video lectures improves learning. J. Comput. Assisted Learn. 35(1), 42–50 (2019) 6. Werhner, M.J.: A comparison of the performance of online versus traditional on-campus earth science students on identical exams. J. Geosci. Educ. 58(5), 310–312 (2010) 7. Bao, W.: COVID-19 and online teaching in higher education: a case study of Peking University. Hum. Behav. Emerg. Technol. 2(2), 113–115 (2020) 8. Toquero, C.M.: Challenges and opportunities for higher education amid the COVID-19 pandemic: the philippine context. Pedagogical Res. 5(4), em0063 (2020) 9. Cavanaugh, J.K., Jacquemin, S.J.: A large sample comparison of grade based student learning outcomes in online vs. face-to-face courses. Online Learn. 19(2), n2 (2015) 10. Elmehdi, H.M., Ibrahem A.-M.: Online summative assessment and its impact on students’ academic performance, perception and attitude towards online exams: University of Sharjah Study Case. In: Creative Business and Social Innovations for a Sustainable Future, pp. 211– 218. Springer, Cham (2019) 11. Education in and after Covid-19: immediate responses and long-term visions. Sci. Edu. 1–5 (2020) 12. Ali, W.: Online and remote learning in higher education institutes: a necessity in light of COVID-19 pandemic. High. Educ. 10(3) (2020) 13. Spaulding, M.: Perceptions of academic honesty in online vs. face-to-face classrooms. J. Interact. Online Learn. 8(3) (2009) 14. Still, M.L., Still, J.D.: Contrasting traditional in-class exams with frequent online testing. J. Teach. Learn. Technol. 4(2), 30–40 (2015)

A Framework for Harnessing Analytics to Augment the Development of Academic Action Plans Ashraf S. Hussein1(&) 1

and Omar H. Karam2

King Salman International University, Sharm El-Sheikh, South Sinai, Egypt [email protected] 2 British University in Egypt, Cairo 11837, Egypt [email protected]

Abstract. Faculties usually develop Academic Action Plans (AAP) in response to reports from the Faculty Review Panels. A Faculty designs the AAP to help identify, refine, and discuss the main goals for the upcoming semesters, and the changes it will make to improve its academic standing. Nowadays, the technologies adopted in higher education organizations provide volumes of data at high velocity and with greater variety in educational contexts. Such big data leads to relevant insights, which help in answering the AAP questions to have effectual actions. Besides, those insights support advancing better outcomes ranging from improving student success to forming optimal strategies that can maximize organizational and foundational relationships. In the same context, data analytics helps in making better decisions to attain organizational goals. Coupling the state-of-the-art analytical methods with a focused approach to how and when we engage our data leads to better decisions. This paper outlines a proposed framework for harnessing academic data to support the development of AAP in the context of enhancing student success. This framework enables better insights and intervention strategies for organizations and faculty members in addition to the students themselves. The framework also helps guide the data strategy by establishing a common understanding of the vocabulary employed towards the data-driven decision-making process. The present framework can support academic leadership to keep up with their ongoing challenges, as it provides a big picture of the trends and patterns needed to evaluate and streamline processes, create efficiencies, and improve the overall student experience and success. Keywords: Academic action plan
Improving the quality and value of higher education
Digital transformation in higher education
Data analytics
Datadriven decision making

1 Introduction Answers to questions necessary to achieve an effectual action plan need evidence-based responses and recommendations, ‘SMART’ objectives and actions, responsibilities, progress indicators, expected outcomes, and success criteria and indicators. Therefore, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 478–487, 2021. https://doi.org/10.1007/978-3-030-67209-6_51

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data and data analytics would be cornerstones in answering questions, proposing recommendations, forecasting the future, and making data-informed decisions. Data-informed decision-making is therefore the spearhead of digital transformation in higher education, as it can contribute positively to student success and organizational effectiveness [1]. In this context, data and analytics have become one of the fundamental pillars in most of the 2020 Top 10 Information Technology (IT) issues in higher education [2]. Focusing on academic and learning analytics, the main objectives of deploying the various types of big data analytics can be summarized as follows [3]: • • • • • • •

Improve student experience and success. Enhance student progression and retention. Increase graduation rates and reduce the graduation periods. Optimize administrative load on faculty members. Reduce the cost of education – optimize resource utilization. Create a “learning organization” – use data for a better future. Establish a culture of data-informed decision making.

The aim of this paper is to propose a framework that utilizes academic data to support the development of AAP in the context of satisfying the above objectives. The breakdown of this paper is as follows. Section 2 of this paper presents an overview of the previous work in academic data analytics. The framework for harnessing data analytics to augment the preparation of the academic action plan is discussed in Sect. 3. A case study on how data analytics could serve to decide on academic actions and their objectives are discussed in Sect. 4. Finally, conclusions and future work ideas are presented in Sect. 5.

2 Previous Work The key trends and challenges accelerating technology adoption in higher education are surveyed in [4]. This survey reflects how the academic and learning analytics and their related topics represent a major theme for various pioneering studies, events and projects, governmental and corporate initiatives, institutional agendas, and strategic plans related to smart universities. Learning, and academic analytics are therefore generally considered one of the main pillars of digital transformation in higher education, an essential component in smarter universities. A comprehensive review of educational data mining and learning analytics in higher education was conducted in [5]. It revealed that the application of educational data mining and learning analytics can provide significant benefits, and therefore it urges higher education organizations to adopt them. Viberga et al. [6] analyzed more than 250 papers on learning analytics in higher education, published between 2012 and 2018, in an attempt to answer the question: What is the current scientific knowledge about the application of learning analytics in higher education? The focus was on research approaches, methods, and evidence for learning analytics concerning (a) improving learning outcomes, (b) supporting learning and teaching, (c) wide deployment, and (d) ethical usage. Their results revealed improvements of 10% in students’ learning outcomes, 35% in learning support, and 35% in teaching. Also, evidence was

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found for improvement in deployment (6%) and ethical usage (18%) respectively. Their analysis indicated that, in the presence of learning analytics, there is a shift towards a deeper understanding of students’ learning experiences. Data analytics needs to be combined with higher education business processes to improve course structure and delivery to help students who have struggled to stay in a course by identifying their engagement and correlation. However, universities are struggling to understand how to lower dropout rates and keep students on track during their study program. In this regard, Jha et al. [7] have discussed how data analytics can be harnessed in higher education business processes. They investigated the core business processes of learning and teaching and defined a re-engineered higher education business process model. From the resource-based perspective, Shuijing [8] summarized the factors that influenced organizations’ motivation to use data analytics, which includes technical capacity, environmental pressure, expected earnings, data resources, and data quality [8]. All these factors should not be considered as decoupled concepts, as they are all interconnected. These factors and their relationships with each other entail that analyzing the adoption of big data from a systematic perspective could yield convincing results [9]. The discussion of the current state-of-the-art on how higher education organizations are using data analytics reflects the collaborative effort of the three higher-education pillars, which are organizational research, student affairs, and information technology. Together, their functions are prioritizing the importance of measuring student outcomes and advocating the use of appropriate student data, specifically qualitative data, to enhance student success [10].

3 Framework Harnessing data analytics to prepare effectual AAP is considered a four-way split between people, process, data, and technology as shown in Fig. 1. Starting from the top-middle of this figure, the focus should be centered on the students and their departments’ capability to create optimized learning approaches and processes. This cannot be done without adopting agility and advancing knowledge more iteratively to ensure work is in the right direction. Valuing when and where data is required to support the effective process creation, and offer a digital value is mandatory, as we start to look at data as a currency. This entails moving towards a more technology integrated approach to delivering information to the places that are most valued. Finally, we anticipate the new needed skills with the onset of new technology and tools to support the successful adoption of data analytics. This should result in data becoming more of a mindset than a theory or an individual tactic.

A Framework for Harnessing Analytics

People

Process

Student Centric Capability

Mindset

DA

New Skills

Agility

Data Driven

Integrate

Technology

481

Digital Value

Data

Fig. 1. The main four pillars of harnessing data analytics for AAP preparation.

The proposed framework offers various levels of services to augment the development of AAP as shown in Fig. 2. These include dealing with the straight query and reporting that are mandatory to enable organizations to understand what is happening, drilling down to where the problem is, and interfering to enhance performance. The next levels facilitate understanding why things happen, predicting the impacts of current events, and reorganizing all these items together to optimize outcomes, which mainly focus on student success.

Start with an academic issue

Feedback into the Process of Addressing Academic Issues

Find/Collect the Appropriate Data Related to that Issue

Development of an Academic Action Plan Decide on the Proper Action to be Taken to Address the Academic Issue

Analyze that Data with an Eye toward Prediction and Insight Formulate and Present in Ways that are Understandable and Actionable

Fig. 2. A framework of harnessing data analytics for AAP preparation

The proposed framework comprises several components for preliminary data reports, including business intelligence, reporting with visuals, and dashboards, which are utilized using IBM Cognos Analytics [11]. The framework also includes other components for data analytics, including modeling, forecasting, and data mining, which

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are offered through IBM Watson Studio [12]. Nevertheless, adopting data analytics in higher education involves a series of harmonized culture, workforce, and technology paradigm shifts, as those shifts enable the changes to the value proposition of the organization. The academic data analytics framework offers several paths of analysis, including tracking and analyzing Key Academic Performance Indicators (KPIs), and the factors influencing those indicators. It also includes studying students’ progression and retention and identifying at-risk students and how to support them. Several AI-based modeling techniques were utilized to model various KPIs. Also, the framework uses text analytics to analyze the different aspects of students’ feedback on the offered modules. Also, the text analytics is the main component in analyzing the reports received from the Faculty review panel, the external examiner(s), and the academic reviewers. The proposed framework can support academic leadership to keep up with their ongoing challenges using the right data, as it consolidates information to provide a big picture of trends and patterns. It can help to evaluate and streamline processes, create efficiencies, and improve the overall student experience and success.

4 Results As a case study of utilizing data analytics to augment the development of AAP, we considered the data of the Information Technology and Computing Program (ITC) at the Arab Open University, which offers the program amongst nine Arab countries and adopts Blended Learning [13]. We conducted a study over several years, from 2013 to 2019, to see how the data related to the students’ academic performance as well as to the performance of the program delivery trended overtime. Also, we investigated the semester-wise students and faculty member feedback, the previous Faculty review panel, and the external examiner reports for the same period. Students’ dropout, engagement, the pass rate at the module level are common issues amongst AAPs as well as the performance of the module delivery. Other issues, such as at-risk-students and students’ progression and retention are continuous organizational matters. We developed key academic performance indicators for the Information Technology and Computing (ITC) Program courses, and then monitored trends and investigated contributing factors using IBM Cognos Analytics [11]. The focus was on the students’ engagement as one of the critical academic performance indicators. Business Intelligence was utilized to examine the semester-wise average students’ engagement, as shown in Fig. 3. We noticed that after adopting the new curriculum in Fall 2017, the trend of the engagement rate is slightly decreasing, especially for the introductory and level-one modules. By unveiling insights, we confirmed this observation, as shown in Fig. 4. Insights revealed that starting from the Spring of 2017, level-one Modules exhibited engagement rates below the general average throughout the considered period. It was a clear academic issue, and it needed proper action and effective intervention.

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Fig. 3. Semester-wise average students’ engagement

Fig. 4. Unveiling insights of the semester-wise average student’s engagement

To decide on the proper action(s), we must study the factors and actors behind the student engagement. Initially, IBM Cognos Analytics was utilized to find out the key drivers that influence the engagement rate, as shown in Fig. 5. Focusing on the independent drivers, we saw that Module Level, Module Code, University Country campus, Average Students per Class, Full-Time Tutors, Part-Time Tutors are important drivers behind the engagement rate. However, conducting further investigations was warranted to be able to decide on the actions that target the pain points.

Fig. 5. Relationship diagram, emphasizing the key drivers of the engagement rate

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In this way, we modeled the engagement rate using IBM SPSS [14]. Several algorithms were utilized such as Random Forest [15], CHAID [16], QUEST [16], Bayes Net [17], MLP Neural Network [18], and Logistic Regression [19]. The accuracy of the developed models to reproduce the training data is depicted in Table 1. Random Forest and CHAID models exhibited the best accuracy, and both identified the Average Students per Class, number of Full-Time Tutors, number of Part-Time tutors, Module Code, Country, and Module Level as the dominant drivers behind the students’ Engagement Rate. To design proper actions, we must drill down deeper in some of those drivers.

Table 1. Accuracy of engagement rate modeling Model Random Forest CHAID QUEST Bays Net NN-MLP Logistic Regression

Correct records Wrong records 2,645 98.95% 28 1.05% 2,469 92.37% 204 7.63% 2,388 89.34% 285 10.66% 2,301 86.08% 372 13.92% 2,385 89.23% 288 10.77% 2,357 88.18% 316 11.82%

Throughout the considered period, we identified the modules that exhibited an average engagement rate of less than 90% and a pass rate of less than 80%, as shown in Fig. 6. We found that all of them are introductory and level-one modules which is in full agreement with the preliminary investigations. We then identified those modules and their codes. Further, an investigation was conducted for the collected student feedback to unveil the insights related to the modules under consideration which might influence student engagement. Text analytics were conducted via two different approaches. The first approach utilized Text Link Analysis to identify positive and negative sentiments for various concepts, as shown in Fig. 7. It is a fast approach, and it is useful to identify negative feedback, which might directly influence the students’ engagement.

Fig. 6. Engagement rate versus pass rate

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Fig. 7. Text link analysis of students’ feedback

We also used Text Mining using IBM SPSS [14] to unveil more insights from students’ feedback. The Multi-aspect Sentiment Classification technique was applied [20]. The results show the various aspects (categories), and what is positive or negative in each category, as shown in Fig. 8. It is interesting to point out that text analytics revealed that the module material is inappropriate for the modules that exhibited a lower engagement rate. Besides, the students requested to increase the practical sessions in most of the levelone modules, and they preferred to have formative assessments with personalized feedback from the concerned tutors to enhance their level of understanding. After drilling down in all the dominant players regarding students’ engagement, we decided on the actions to be: 1. Increase the ratio of full-time to part-time tutors. 2. Keep the number of students per class at the optimum value of 25 students. 3. Switch from the traditional pdf content to interactive books, adopting AI and adaptive learning for some modules and MOOCs for others in addition to recording the lectures and providing them through the Learning Management System (LMS). 4. Provide more practical sessions. 5. Tutors should adopt formative assessments and provide students with personalized feedback. We also recommended the collection of all the weak points across the cohort and reporting them anonymously with the tutor feedback and making this report available to students through the LMS.

Fig. 8. Text mining on students’ feedback

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5 Conclusion and Future Work The journey of adopting data analytics in higher education starts by the drivers behind the use of data analytics. One of the key drivers is the questions and issues raised within the AAP. The proposed framework, in this paper, starts with those strategic/academic questions and utilizes data analytics through a well-identified and systematic lifecycle to reach mature decisions on the proper actions to be taken to either answer the AAP questions or to find solutions to academic issues. The proposed framework comprises several components including business intelligence and business analytics. Those components utilize state-of-the-art artificial intelligence techniques. This paper demonstrated how this framework has been utilized to decide on the proper actions to enhance the students’ engagement. The future work will focus on predictive analytics and how to automate the generation of possible actions.

References 1. Bariff, M., Norton, J.: Unlocking the true potential of data in education. In: Industry and Campus-Led Session, EDUCAUSE Annual Conference (2019) 2. 2020 Top 10 IT Issues. https://www.educause.edu/research-and-publications/research/top10-it-issues-technologies-and-trends/2020. Accessed 30 July 2020 3. Hussein, A., Khan, H.: Students’ performance tracking in distributed open education using big data analytics. In: Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing, Article No.: 75, pp. 1–8 (2017). https://doi.org/10.1145/ 3018896.3018975 4. Eugenia, S.: Smart university in smart society – some trends. In: Smyrnova-Trybulska, E. (ed.) E-learning and Smart Learning Environment for the Preparation of New Generation Specialists, pp. 65–80. Studio Noa, Katowice (2018) 5. Aldowaha, H., Al-Samarraiea, H., Fauzyb, W.: Educational data mining and learning analytics for 21st century higher education: a review and synthesis. Telematics Inform. 37, 13–49 (2019) 6. Viberga, O., Hatakkab, M., Bältera, O., Mavroudia, A.: The current landscape of learning analytics in higher education. Comput. Hum. Behav. 89, 98–110 (2018) 7. Jha, M., Jha, S., O’Brien, L.: Re-engineering higher education learning and teaching business processes for big data analytics. In: Abramowicz, W., Corchuelo, R. (eds.) BIS 2019. LNBIP, vol. 354, pp. 233–244 (2019). Lecture Notes in Business Information Processing, 22nd International Conference, BIS 2019 Seville, Spain, 26–28 June 2019 Proceedings, Part II (2019) 8. Shuijing, H.: Affecting factors on firms. Acquisition intention for big data analytics technology based on RBV. Inf. Sci. 5, 148–152 (2016) 9. Wang, L., Yang, M., Pathan, Z., Salam, S., Shahzad, K., Zeng, J.: Analysis of influencing factors of big data adoption in Chinese enterprises using DANP technique. Sustainability 10 (3956) (2018). https://doi.org/10.3390/su10113956 10. Parnell, A., Jones, D., Wesaw, A., Brooks, D.: Institutions’ use of data and analytics for student success, results from a national landscape analysis. National Association of Student Personnel Administrators, Inc. (2018)

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11. Cognos Analytics Homepage. https://www.ibm.com/products/cognos-analytics. Accessed 30 July 2020 12. Watson Studio Homepage. https://cloud.ibm.com/catalog/services/watson-studio. Accessed 30 July 2020 13. Arab Open University Homepage. https://www.arabou.edu.kw. Accessed 20 May 2020 14. SPSS Homepage. https://ibm.com/analytics/spss-statistics-software. Accessed 30 July 2020 15. Davies, A., Ghahramani, Z.: The Random Forest Kernel and other kernels for big data from random partitions. arXiv:1402.4293 [stat.ML] (2014) 16. Lin, C., Fan, C.: Evaluation of CART, CHAID, and QUEST algorithms: a case study of construction defects in Taiwan. J. Asian Archit. Build. Eng. 18(6), 539–553 (2019). https:// doi.org/10.1080/13467581.2019.1696203 17. Scanagatta, M., de Campos, C., Corani, G., Zaffalon, M.: Learning Bayesian networks with thousands of variables. In: Cortes, C., Lawrence, N., Lee, D., Sugiyama, M., Garnett, R. (eds.) Advances in Neural Information Processing Systems 28, pp. 1855–1863 (2015) 18. Collobert, R., Bengio, S.: Links between perceptrons, MLPs and SVMs. In: Proceedings of the 21st International Conference on Machine Learning (2004). https://doi.org/10.1145/ 1015330.1015415 19. Harrell, E.: Regression modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. Springer, New York (2010). ISBN 978-1-4419-2918-1 20. Lu, B., Ott, M., Cardie, C., Tsou, B.: Multi-aspect sentiment analysis with topic models. In: Proceedings of the IEEE 11th International Conference on Data Mining Workshops, Vancouver, BC, pp. 81–88 (2011). https://doi.org/10.1109/ICDMW.2011.125

The Effectiveness of Using Collaborative Learning Systems to Prevent Spread of Coronavirus Hosam F. El-Sofany1,2(&) and M. Samir Abou El-Seoud3 1

2

3

King Khalid University, Abha, Kingdom of Saudi Arabia [email protected] Cairo Higher Institute for Engineering, Computer Science and Management, Cairo, Egypt Faculty of Informatics and Computer Science, The British University in Egypt (BUE), El Shorouk City, Cairo, Egypt [email protected]

Abstract. Collaborative Learning (C-learning) is applied as an effective way to develop students’ proficiency such as collaboration, communication, and critical thinking. The spread of the new coronavirus disease (COVID-19) around the world resulted in shutting universities globally. The education sector has changed with the distinctive rise of full E-learning, whereby teaching is undertaken remotely through Collaborative and interactive classrooms using Elearning platform such as Blackboard collaborate ultra-system. As a result, most professors and students found themselves forced to use C-learning for teaching and learning. The paper discusses the basic concepts of C-learning and presents the impact of applying this technology to support the C-learning environment. The paper aims to present the benefits, and challenges by transforming learning in King Khalid University and the British University in Egypt into full Clearning, due to the spread of COVID-19. The study analyzed the factors affecting the use of students to C-learning while performing learning activities and assignments such as short tests, forums, projects, essays, and presentations. The paper shows that students have positive behaviors towards using C-learning to perform their activities. The researchers used the Unified Theory of Acceptance and Use of Technology (UTAUT) model to evaluate the strength of students’ responses to accept C-learning to facilitate the continuity of Collaborative and interactive learning and prevent the spread of coronavirus. Keywords: Collaborative learning Higher education
UTAUT


E-learning
COVID-19
Coronavirus


1 Introduction Recently, a significant increase in the use of collaborative and interactive learning in higher education [1]. This correlates to the increased use of student-centered learning approaches used in higher education including in traditional lectures [2, 3]. The utilization of collaborative learning tools has had a significant impact on teaching [4]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 488–494, 2021. https://doi.org/10.1007/978-3-030-67209-6_52

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These tools are an excellent way of promoting student satisfaction and, in particular, Millennials’ or digital natives’ desire for interactivity. Management and business educators have also found that collaborative learning and interactive teaching tools have enhanced higher level thinking, communication, and problem-solving competencies [5]. In this paper, the authors provide the features of Blackboard Collaborate Ultra for collaborative E-learning lectures, seminars, and tutorials. These studies are based on undergraduate courses, which supports students from a variety of different programmers. This study uses the UTAUT model introduced by Venkatesh et al. [7]. The UTAUT model focuses on the analysis and evaluation of users’ feedback regarding the use of new systems. The UTAUT principles state that there are four main factors affecting this evaluation, which include performance expectancy, effort expectancy, social influence, and facilitating conditions. The first three factors focus on the intention and behavior of the individuals that use the system, while the fourth factor focuses on their behavior. The UTAUT factors mentioned are affected by gender, age, experience, and voluntariness of use to the system.

2 Collaborative Learning via Blackboard Collaborate Ultra System Blackboard collaborate ultra-system provides an online room for your course that stays open for the life of your course (by default, the room is given your course name). Ultra is the new, browser-based version of Blackboard Collaborate. It allows instructors to host remote, synchronous sessions within an existing Blackboard course site. BB Collaborate Ultra is a real-time audio/video conferencing tool designed specifically for education and allows to conduct interactive sessions with multiple users and share content, such as files or individual applications/screen view. It allows to perform quick polls and accommodates group work in break-out private group spaces. Collaborate sessions can be recorded, with the recordings becoming available in BB. As a result, Collaborate Ultra allows instructors to audio/video conference, chat, use a whiteboard, share applications and documents, and guide students through websites. Instructors can designate students as presenters (moderators) and allow them to take control of the session and make presentations. Collaborate Ultra is an alternative Web conference tool which can be used in place of (or in addition to) the original Collaborate Classic. Instructors will want to consult with an Instructional Designer to decide if Collaborate Ultra or Collaborate Classic will work better for them.

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3 King Khalid University’s Plan to Collaborative Learning Transformation Starting from 1 March 2020, King Khalid University (KKU) changed the learning and assessment methodologies due to the spread of coronavirus in the world. The following are the new teaching strategies for the lectures: 1. 2. 3. 4.

The current full E-learning courses remain unchanged on the Blackboard platform. The partial E-learning courses are replaced with full virtual classes at the same time. The traditional courses are replaced with virtual classes at the same time. Duties and activities: All traditional duties and activities are transformed into electronic duties and activities provided through the Blackboard Collaborate Ultra platform. 5. Type of assessments: The new student evaluation method in each course includes short tests, projects, forum, essay, and live activities (presentation, oral evaluation) through virtual classes.

4 Contingency Plan for Teaching and Collaborative Learning at the British University in Egypt (BUE) Currently the campus is closed to students, both graduate and undergraduate. The government has ordered this as a response to COVID-19, to protect the health of the BUE community. Although there will be no face-to-face classes on campus, learning and teaching will continue online. Academic staff, Teaching Assistants and Administration will enter the campus and their offices as necessary in order to ensure that teaching continues online. Clearly it is unfortunate that the campus must close. We quite understand that this is troubling to students. But this is clearly necessary and BUE is committed to supporting students in continuing their studies. It will do so as described below, applying its Contingency Plan for Maintaining Effective Teaching and Learning during Unscheduled Campus Closure. Student Must 1. Be well aware that this is not a holiday. 2. Respond immediately to the communication sent to you via the eLearning site by the Module Leader or staff member teaching the module. 3. Access the eLearning system to find instructions not only about your modules, but also on the site for your program. 4. Access the eLearning website for each of your modules and work through the content and other material it contains. 5. Complete all exercises on the eLearning website which have been set on material to be covered during the closure. 6. Submit electronically and on time all assignments set for the period of closure.

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Academic Staff Must 1. Respond to the direction of the Dean and Head of Department who are required to send all team members an email regarding ongoing arrangements for closure. 2. Module Leaders must communicate immediately with others teaching the module with instructions, monitoring on an ongoing basis that instructions are followed. 3. Communicate immediately via the eLearning site with all students taking the module indicating what they are required to do. (See Student Must) 4. Communicate regularly with the students during closure, individually or as a group, through a news item on the module site on the eLearning system. 5. Where appropriate, include a number of additional exercises in the eLearning system which the student should take and which will help reinforce the material that has been covered. 6. Continue to expand significantly material currently held on the eLearning system, including full lecture notes and teaching aids.

5 Methodology Online questionnaires were conducted among 600 students enrolled in different courses in the Computer Science Department using the purposive sampling method. The researchers aimed to study students’ behavior towards the use of collaborative learning to facilitate the continuity of interactive learning in the university and to help in preventing the spread of coronavirus among students.

6 Research Model The proposed study sought to analyze and evaluate the strength and effectiveness of the following factors: performance expectancy-PE, effort expectancy-EE, social influenceSI, facilitating conditions-FC, and behavioral intentions-BI on students’ intention to accept the use of C-learning systems for learning and communication, during the spread of the COVID-19 epidemic around the world [7]. The UTAUT model is used with four external variables and two internal variables, excluding the moderating variables from this study. Figure 1 illustrates the proposed UTAUT model that shows the effective factors in the students’ acceptance to use Clearning system for learning and communication, during the spread of COVID-19. As a result, the researchers proposed the hypotheses H1 to H5 as shown in Fig. 1:

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Fig. 1. The proposed UTAUT model for C-learning

7 Research Experiments and Data Analysis A total of 600 online questionnaires were circulated in the selected classes with a response rate of 99.2%. Table 1 shows the demographics of the selected respondents. 85.0% of the students use C-learning for full interactive E-learning and communication once or more a day, while 12.5% of the students use C-learning once a week. 1.3% and 0.8% of the respondents use C-learning once and twice a month, respectively. Table 1. Respondents of the demographic data (n = 600) Character Gender Age Student Level

Frequency Percent Male Female Under 20 20–23 Level-1 Level-2 Level-3 Level-4 Level-5

300 300 200 400 100 120 100 120 160

50.0 50.0 33.3 66.7 16.7 20 16.7 20 26.7 (continued)

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Table 1. (continued) Character The use of collaborative learning for learning and Communication

Frequency Percent Once or more a 510 day Once a week 75 Twice a month 8 Once a month 5 Never 2

85.0 12.5 1.3 0.8 0.3

8 Results Analysis and Discussion The participants of the study are students at KKU. KKU uses Blackboard LMS as an essential tool for the U-learning process across the university. The examples in this paper are based on courses taught during the Spring semester of the academic year 2019-2020. The courses have been conducted as Collaborative Learning courses through the spread of COVID-19. This research study aims to explain the advantage of Collaborative Learning for learning and communication and present its impact on

Fig. 2. UTAUT indicator analysis for the use of U-learning through the spread of COVID-19

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students’ skills and experiences. Web-based questionnaires were distributed among 600 students in seven courses with different levels in the Computer Science Department, created through the “survey” assignment tool in the Blackboard system (Fig. 2).

9 Conclusion This paper presents the benefits, challenges, and barriers caused by replacing traditional learning by full U-learning, due to the spread of COVID-19 in KSA and Egypt. The study analyzed the factors affecting the use of students to Collaborative Learning while performing learning activities and assignments such as forum, essay, project, presentation, laboratory, short tests, and final exam. The research study has shown that students have positive behaviors for using Collaborative Learning to perform their activities through this stage. The UTAUT model was used to evaluate the predictors’ strength for students’ intention to accept the use of Collaborative Learning system for learning and communication, during the spread of COVID-19. The results have shown that the total average of students that accept the transformation process of education to Collaborative Learning is 88.95%, and the total average of students who disagree is 7.13%, while the total average of students who neither agree nor disagree is 3.92%. Acknowledgment. The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through research groups program under grant number (R.G.P.1-185/41).

References 1. Wdowik, S.: Using a synchronous online learning environment to promote and enhance transactional engagement beyond the classroom. Campus Wide Inf. Syst. 31(4), 264–275 (2014) 2. Plush, S.E., Kehrwald, B.A.: Supporting new academics’ use of student centred strategies in traditional university teaching. J. Univ. Teach. Learn. Pract. 11(1), 1–14 (2014) 3. Baeten, M., Dochy, F., Struyven, K., Parmentier, E., Vanderbruggen, A.: Student- centred learning environments: an investigation into student teachers’ instructional preferences and approaches to learning. Learn. Environ. Res. 19(1), 43–62 (2016) 4. Hussein, E.M.H.: The effect of blackboard collaborate-based instruction on pre- service teachers’ achievement in the EFL teaching methods course at faculties of education for girls. Eng. Lang. Teach. 9(3), 49–67 (2016) 5. Politis, J., Politis, D.: The relationship between an online synchronous learning environment and knowledge acquisition skills and traits: the blackboard collaborate experience. Electron. J. e-Learn. 14(3), 196–222 (2016) 6. Becker, S.A, Cummins, M., Davis, A., Freeman, A., Giesinger, C.H, Ananthanarayanan, V.: NMC Horizon Report: 2017 Higher Education Edition. The New Media Consortium, Austin (2017) 7. Venkatesh, V., Morris, M., Davis, G., Davis, F.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)

A Remotely Accessible in-Door C-Band Solar Simulator for PV Cells Characterization: Educational Technology Case Study in the British University in Egypt (BUE) Sameh O. Abdellatif1,2(&) 1

2

and Hani Ghali1,2

FabLab, Centre for Emerging Learning Technologies (CELT), British University in Egypt (BUE), Cairo, Egypt {sameh.osama,Hani.amin}@bue.edu.eg Electrical Engineering Department, Faculty of Engineering, The British University in Egypt (BUE), Cairo, Egypt

Abstract. This paper surveys how the characterization process for a Photovoltaic (PV) cell is implemented to serve in introductory undergraduate/postgraduate courses and research purposes. The characterizer has the capability of measuring the I-V characteristic curve of the PV cell attached to the system with indicating the solar irradiance that is sensed during the measurement. The use of the NI Environment facilitates the Internet publication opportunity where users can access the setup remotely. The remote accessibility is considered as a significant credit in integrating the setup as a demonstration tool in teaching modules as well as student accessibility. Keywords: Photovoltaic


E-lab
Remote accessing
Hardware experiment

1 Introduction: Challenges Solar power generates electricity with no global warming pollution, no fuel costs, and no risks of fuel price spikes, and has the potential to help move the country toward cleaner, reliable, and affordable sources of electricity. In developing countries, especially in Egypt, the replacement of the ordinary fuel based electricity sources by renewable sources became an obligatory step toward better environment. Toward that, new programs targeting renewable energy in both undergraduate and postgraduate levels have been lunched. These programs should be accomplished by the desired Lab facilities for gaining more practical experience as well as better understanding of fundamental topics. Toward this aim, many techniques have been investigated in literature for implementing a robust remotely accessed experiment dealing with different renewable energy systems. These techniques were implemented and improved during the previous decades. The following paragraphs are dedicated for criticizing theses work and glowing the attributed contribution of our proposed experiment. In 1998, Stuart Bowden and Christiana Honsberg, work at the Solar Power Labs at ASU [1], lunched the first online resources for photovoltaic education [2]. The website © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 495–502, 2021. https://doi.org/10.1007/978-3-030-67209-6_53

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provides the users with basics theoretical examples demonstrating the main theory of operation for PV cells and its performance at different conditions. However, this contribution was limited to theoretical examples with no experimental assets. After that, new technologies such as virtual reality Labs were enrolled in developing PV experiment as in [3]. A remote triggered photovoltaic solar cell experiment is presented to study the fundamental characteristics of photovoltaic solar cells where lake of hardware experimental work is also observed [3]. More toward theoretical modeling experiments, a mathematical model based on Matlab platform was implemented in [4]. The model allows the student to plot the I-V and the P-V curves at different environmental conditions for various PV module types. However the provided model was limited to be offline use where no friendly user interface was provided. Besides understanding the PV operation, information about solar irradiance should be provided especially for non-horizontal surfaces. Therefore a remote accessed virtual laboratory based on Matlab is presented in [5]. The work demonstrates the solar irradiance at different tilting angle while no study for a full PV system was provided within the experiment. Another trial was made in [6] to simulate the sun paths and irradiance. This work enables students to study the performance of the sun and its effect on the PV module behavior. Hardware based remote experiments start to appear in Mexico, where there is a high need for replacing the ordinary sources of energy by renewable one, targeting well educated student in this field. A mobile PV system for educational purposes is implemented [7]. The prototype is consisted of four PV module associated with Data acquisition system. The systems showed a good performance, however its sustainability was not granted. Approaching better hardware environment, a remotely accessible solar energy laboratory has been developed, aiming at representing a small photovoltaic (PV) system, including two PV cells, batteries, a charge controller and a dummy load [8]. In this work, A Raspberry PI microcontroller enables to control the different inputs, measures the voltages and the currents in the circuit and provides a remote access through the web. The system is built very well but it missed the student evaluation and the student’s feedback. Another technique based on NI equipment [9] was attached for data acquiring and controlling as in [10]. The PV system, with attached charging batteries unit, was controlled with the instrumentation software LabVIEW. A double axial tracking system, includes two motors to track the sun radiation, was also controlled using LabVIEW. This study focused on the battery charging voltage and current at different temperature and angle of incidence with less interest on the PV performance and characterization. Still using LabVIEW, the work in [11] focused on the maximum power point tracking algorithms through implementing a remote distance learning LabVIEW platform and enables the student to access, monitor and control the experiment remotely. However, lake of accurate measurement was observed from the results leading to some uncertainties. Another LabVIEW trails were published in [12, 13]. A virtual environment was emulated to show the main principles of PVs and its characteristics. The experiment implemented for both industrial as well as academic use, but no experimental work was demonstrated. In this work, a low cost, PV characterization experiment is introduced. The setup is consisting of LED source, Keithley 2401 source/meter and a UV-Vis spectrometer is

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employed to analyze the produced spectrum. A calibrated solar cell, 91150-KG3 from Newport, is used to validate the utility of the designed array of LEDs to operate as a standard solar simulator. An isolated chamber with temperature sensor and distance controller is implemented. Moreover, Keithley source/meter 2401 is used for I-V characterization. The proposed system will enable the extraction of all necessary data required in analyzing PV cells. A LabVIEW-NXG front panel is designed showing the solar irradiance, module temperature and the I-V characteristic curves. The use of NI environment enables the publishing of the experiment front panel through the internet which provide the remote access to students to perform the experiment 24/7. The innovation in this paper is not only attributed to the constructed setup but also in the robustness of the experiment setup and the accuracy of results. In addition, the low cost and repeatability of the experiment makes it easy for any other developing university to implement such an educational platform.

2 Learning Approaches and Outcomes Renewable energy became a critical strategic country’s objective as an alternative, inevitable, source for electricity required for the economic and social development of the country. Among the different renewable energy sources, the solar energy occupies an advanced position as promising candidates in both local as well as international markets. The possible achievement of such strategic objective requires, besides other components, professional engineers and technicians specialized in the field of renewable energy and capable to understand and handle current as well as future related advanced technologies in such domain. Consequently, different Egyptian universities and higher education institutions have established “Renewable Energy Engineering” programmes at both the undergraduate engineering level as well as at the postgraduate engineering level aiming at graduating professional engineers and technicians with appropriate skills and capabilities. Most of Egyptian universities face the problem of overcrowded classes and laboratories which affects the quality of delivered materials, either in classroom or in laboratories leading to a negative effect on the level of graduate. On the other hand, existing newly developed renewable energy programs, either for the undergraduate or for the postgraduate levels, also suffer from the lack of up-to-date specialized interactive experiments in such field due to; unaffordable cost required to build a typical renewable energy unit, lack of required space for installation and operation and lack of localized multi-disciplines expertise, within each institution, capable to design, implement and operate such new type of multi-disciplines experiments. This paper addresses the implementation of a remotely accessed Photovoltaic characterization experiment. The experiment aims at providing an improved education quality in the field of renewable energy engineering through the development and implementation of new form of internet based practical activities, e-experiments, to support teaching and learning of corresponding courses delivered in renewable energy programs. The wider scope of the experiment outcomes focuses along the country’s national priorities for the improvement of higher education and learning quality through the development of new learning and teaching tools. This will be achieved

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through the efficient utilization and deployment of available advanced biological tools and corresponding facilities for the development of multi-platform e-experiments, which will be fully accessible and operational through the internet using any browser, providing a flexible learning tool and environment for both students and teachers. This new facilities will provide students with an unprecedented opportunity to use the available online e-experiment environment for enhancing their understanding of key concepts related to their study which will significantly improve their learning outcomes. In addition, the developed e-experiments will provide students with new nonconventional interactive techniques for learning and understanding fundamental as well as advanced topics in the field of renewable energy through remote experimentation, which will be available and accessible 24/7. Besides that, these e-experiments will provide an optimum low cost solution based on the fact that different students from different universities and institutions can share the same platform, in other words not every university and every institution will be required to purchase separate specialized laboratories and test equipment. In a specific manner, this experiment has been performed as a part of postgraduate courses in the British University in Egypt (BUE). The students enrolled in these courses practiced the experiment and evaluate it according to a given evaluation form, more details are found in the next sections.

3 Experiment Implementation and Testing Solar cells must be characterized under standard conditions using solar simulators. In principal, the high uniformity, temporal stability, and spectrum matching are the three main parameters that distinguish solar simulators from other low-cost sources [14]. However, commonly used low-cost light sources can still be used for characterizing PV cells, while taking the mismatching factors in consideration. Herein, a customized LED array is used [15]. Ocean Optics Red Tide USB650 Fiberoptic Spectrometer has been used to optically characterize the used light source. The spectrometer readings have been calibrated by using a reference sample to give readings in Watts/unit area. Figure 1 shows the UV-Vis-IR spectrum for the used low-cost light source. The optical mismatching was calculated based on Fig. 1 with respect to the standard solar irradiance given in AM1.5G [16]. This mismatching factor is considered in calculating the solar cells efficiency in the results discussion section. Regarding the temporal stability, the selected source showed an acceptable stability with time reaching an overall variation less than 0.1% across five continuous hours of operation. Finally, to minimize the uniformity mismatching errors, a solar cell under test with small are x 20 mm) is selected where the used light source is assumed to be uniform within this area.

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Fig. 1. LED spectral mismatching with respect to AM1.5G

Both the light source and the solar cell were put inside an isolated cabinet in this experiment to take advantage of wall reflections, and both were aligned on the same vertical line (see Fig. 2). The light source was supplied by an external power source. The solar cell temperature was measured to be in the range 28–33 °C during all experiments. In the first part of this experiment, the light source was fixed on top of a metallic lifter rod and the solar cell is fixed on the moving part of this lifter rod. The distance between the light source and solar cell was changed using the moving part of the lifter from 3 cm to 37 cm with a step of 2 cm. At each step, a voltage was applied on this solar cell from 0 V to 10 V with a step of 0.1 V and the output current was recorded using Keithley 2401 device. The IV curve points were recorded on an excel file for each cell placement using LabVIEW-NXG, see Fig. 3. The proposed setup has been extensively tested in our previous work in [15, 17–21]

Fig. 2. Experimental setup for I-V easements

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Fig. 3. Labview-NXG Interface

4 Feedback Gathering Student evaluations were conducted from February to December 2019, with the 15 postgraduate students in the British University in Egypt who had used the experiment. One postgraduate course was selected, REN 616, under the renewable energy track in the postgraduate level. Ten of these students had an electrical engineering (EE) major, and five had a mechanical engineering (ME) major. They also differed in their levels of knowledge of photovoltaic systems: three EE graduate students and two ME students

Fig. 4. Student survey for feedback gathering

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had limited experience on PV characterization, whereas seven EE graduate students were familiar with PV characterization. The authors administered the surveys after teaching the students the main concepts of PVs, as going over some solved examples. Then the students started to evaluate the experiment using the suggested template snapped in Fig. 4. A statistical analysis is then performed on the student’s survey results. It can be observed from the statistical analysis that, regardless the student major study field or experience, almost all the students can perform the experiment smoothly with no need for external instructions or guidance. On the other hand, 85% of the student agrees on the utility and beneficially of the experiment for a postgraduate level, while the remaining percentage indicated that it still needs some updates. Finally, some students’ comments on the experiment interface, targeting better friendly interfacing with more help options, and the authors considered these comments to be implemented in the future version.

5 Conclusions Based on LabVIEWTM, a remote instrumental system that measures the characteristics of PV cells is designed and implemented in this study. The system can be used to measure irradiation, open-circuit voltage, short-circuit current, I-V curve, and output voltage/current/power under different conditions for educational purposes. The developed technique can be used to monitor and collect data for PV generation system with an advantage of being low cost. A possible future application of this work is upgrading the PV system to study the charging and discharging of the batteries as backup system of the PV. The objective of this experiment is the applicability to execute on different renewable energy source as wind energy and bio-mass. Building like these systems on different renewable energy application will lead to improvement in the education process in both undergraduate and post graduate studies related to renewable energy fields

References 1. Lab, S.P.: ASU 2. Koseler, R., et al.: Work in progress: evaluation of an online education portal from the user’s perspective: an empirical investigation of a photovoltaics (PV) Engineering Learning Portal, pveducation.org. In: Frontiers in Education Conference (FIE), Seattle, WA (2012) 3. Freeman, J., et al.: Remote triggered photovoltaic solar cell lab: effective implementation strategies for virtual labs. In: Technology Enhanced Education (ICTEE), Kerala (2012) 4. Erdema, Z., Erdemb, M.B.: A proposed model of photovoltaic module in Matlab/Simulink for distance education. In: 13th International Educational Technology Conference. Elsevier Ltd (2013) 5. Rus-Casas, C., et al.: Virtual laboratory for the training and learning of the subject solar resource. In: IEEE (2014) 6. Jacques, S., et al.: An innovative solar production simulator to better teach the foundations of photovoltaic energy to students. WSEAS Trans. Adv. Eng. Educ. 10, 11–20 (2014)

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7. Dolores, M., et al.: Design of a mobile photovoltaic module system for demonstration and experimentation. J. Energy Power Eng. 8, 1568–1574 (2014) 8. Assante, D., Tronconi, M.: A remotely accessible photovoltaic system as didactic laboratory for electrical engineering courses. In: IEEE Global Engineering Education Conference (EDUCON), Tallinn, Estonia (2015) 9. Instrument, N, NI 10. Faria, N., et al.: Photovoltaic panels LabView™ Controlled œ a platform for educational purposes. In: International Conference on Renewable Energies and Power Quality ((ICREPQ 2008) (2008) 11. Bauer, P., Ionel, R.: Distance laboratory for programming maximum power point tracking of a photovoltaic module. In: e-Learning in Industrial Electronics, IEEE (2013) 12. Huang, W.-T., et al.: A labwiew based photovoltaic cells virtualinstrumental system for educational purpose. ICIC Express Lett. 8(2), 613–619 (2014) 13. Mastny, P., et al.: Operational characteristics of photovoltaic systems. In: IEEE (2014) 14. Domínguez, C., Antón, I., Sala, G.: Solar simulator for concentrator photovoltaic systems. Opt. Express 16(19), 14894–14901 (2008) 15. Hassan, M.M., et al.: Toward low-cost, stable, and uniform high-power LED array for solar cells characterization. In: New Concepts in Solar and Thermal Radiation Conversion III. 2020. International Society for Optics and Photonics (2020) 16. Bremner, S., Levy, M., Honsberg, C.B.: Analysis of tandem solar cell efficiencies under AM1. 5G spectrum using a rapid flux calculation method. Progress Photovol. Res. Appl. 16 (3), 225–233 (2008) 17. Abdellatif, S., et al.: Refractive index and scattering of porous TiO2 films. Microporous Mesoporous Mater. 264, 84–91 (2018) 18. Sanad, M.F., Abdellatif, S.O., Ghali, H.A.: Enhancing the performance of photovoltaic operating under harsh conditions using carbon-nanotube thermoelectric harvesters. J. Mater. Sci.: Mater. Electron. 30(22), 20029–20036 (2019) 19. Hassan, M.M., et al.: Investigating the parasitic resistance of mesoporous-based solar cells with respect to thin-film and conventional solar cells. In: Organic, Hybrid, and Perovskite Photovoltaics XXI. 2020. International Society for Optics and Photonics (2020) 20. Ahmed, A.K., Abdellatif, S.O.E.: Modelling and simulating the spectral and spatial interference in LED array. In: Optical Modeling and Performance Predictions XI. 2020. International Society for Optics and Photonics (2020) 21. Abdellatif, M.M., Maher, S.M., Ghazal, M.: Implementation of a low cost, solar charged RF modem for underwater wireless sensor networks (2020)

A Concept Extraction System with Rich Multimedia Learning Resources for Children Somaya Al-Maadeed1, Batoul M. S. Khalifa1, Moutaz Saleh1, Jezia Zakraoui1(&), Jihad M. Alja’am1, and M. Samir Abou El-Seoud2 1

Qatar University, Doha, Qatar {s_alali,batoul,moutaz.saleh,jaam}@qu.edu.qa, [email protected] 2 British University in Cairo, Cairo, Egypt [email protected]

Abstract. COVID-19 pandemic imposed a new way of teaching children. Distance education through the Internet will then be adopted in many countries as the main source of education. The whole world is transformed from physical teaching in schools’ premises to virtual teaching through the web by using software like ZOOM or Microsoft team. These software connect people to discuss and share documents, however, they do not generate contents. Instructors need digital materials to deliver effectively through and explain concepts. They cannot prepare them by themselves as they get used to rely on printed textbooks in their schools. The objective of this work is to propose and implement a new online learning platform that uses multimedia in teaching. It focuses on teaching the Arabic language through simple stories for children and none-Arabic speakers in Qatar University. The platform receives as input the story script, automatically extract the main concepts, and associate them with images. A multimodal text-image corpus is built with structured contents allowing the instructors to find the most representative visual concepts associated with keywords. The corpus can be enriched with additional stories and images. Search engines are used to retrieve these images that the instructor need to approve them to be used in education. The platform opens a new era of distance education and improve the education process during the COVID-19 pandemic. Keywords: Distance education


Text-Image corpus
Concepts extraction

1 Introduction The school closures and the social distancing bring many changes and new challenges for parents and their children. Consequently, many schools offer Distance Education (DE) courses to address the diverse educational needs of students and to stay up to date with advancing technology in online and blended learning. Students, parents, and teachers are seeking new and alternative course resources to support DE. However, supporting education for children with special educational needs and disabilities can be very challenging and difficult. Children with special needs have major difficulties to © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 503–511, 2021. https://doi.org/10.1007/978-3-030-67209-6_54

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understand vocabulary in text [7] in any setting, other children may have health conditions that mean it wouldn’t be safe for them to attend school at the moment, or they may need to stay at home to help protect other family members. Although, online communities are the great way to connect with other parents while staying at home, online tools and systems lack however, the need for dynamic, reliable, and personalized contents. Teaching through raw text distantly is not effective and difficult. Images can be used in teaching as they may have direct effect on children understanding. Online tools use mainly google images search engines to establish a careful combination of vocabulary and images. However, selecting images relevant to vocabulary in text and placing them at suitable contextual locations within it is a challenging problem for automated content generation systems. In fact, word to word matching can give wrong or irrelevant images. The semantic aspect of the matching should be considered along with the shapes of objects in the retrieved images. In this paper, we propose a new system for distance education based on a domainoriented architecture to analyze raw text and generate the best images representative images. We use several natural language processing techniques [2, 3, 11] to extract keywords from text and we link them images fetched from search engine [4]. We build a huge corpus that contains thousands of vocabularies and images used in animal domain to generate content on demand during learning session. The remaining of the paper is organized as follows: Sect. 2 discusses some previous works; Sect. 3 shows the system components; Sect. 4 presents the proposed approach; Sect. 5 concludes the paper.

2 Related Works 2.1

Understanding of Stories Through Images

Shize et al. [8] proposed an approach that generates image-text timelines for news events based on evolutionary image-text summarization. Alternatively, Dhiraj et al. [6] presented an approach that automates story picturing based on the mutual reinforcement principle. In their work, semantic keywords are extracted from the story text and an annotated image database is searched to form an initial picture pool. While most of the existing work relies on translating the whole text to relevant images, this work selects the most important sentences in the domain of discourse, identifies the semantic relationships between entities with highest weights, and link them with images. 2.2

Image Retrieval and Validation

Image search and retrieval is becoming an important feature to assess the quality of search engines. Many people rely on search engines to retrieve images corresponding to keywords. Therefore, search engines with high satisfactory results will become the most used tools for image retrieval. Google, Yahoo and Baidu have recently launched keyword-search-image feature, which is still under assessment and improvement. They mainly retrieve annotated or tagged images through matching their captions with the keywords. However, millions of images are upload on the web, but they are untagged

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or wrongly captioned. Therefore, matching keywords with images captions can lead to ambiguous and noisy results [11]. In fact, similarity between images’ captions and keywords used in queries are not the only features that should be considered to associate the image with the keywords. The semantic of the image caption plays an important role to describe the image and link with the keywords. In addition, the shape of objects in an image should be considered to give more accuracy to image retrieval. Open source tools package (Java caliphemir) is used to annotated images along with the perceptual hash algorithm for image analysis. Experts in the domain of discourse should check the retrieved images and validate their usage in education for children based on their background and cultures. In fact, images with different culture and traditions should be eliminated even they match the keywords. For instance, in Fig. 1, the following queries “Camel lives in desert” addressed to Google can generate thousands of images and clips. – Camel lives in desert

Camel in desert

Camel sits on sand

Camel eats herbs

Fig. 1. Images retrieved with updatable captions.

The instructor can select and validate some of the retrieved images and update their captions. She/he can rank the images based on their importance in the domain of discourse and get additional images with high similarity to the best representative images. In fact, by a simple click on an image k, the system can search and retrieve m images with a high similarity to k. Therefore, every instructor can add new learning resources to the system at any time and from any location. We can think to build a web platform involving volunteers’ instructors to collect images, rectify their captions and submit them to our system for insertion the multimedia corpus. We can then have the best learning resources that can be used locally and internationally for distance education. In addition, we can build corpora on different domain (i.e., transportation, medical, monetary, etc.). 2.3

Representative Sentences Selection

Every story contains many sentences while many of them are irrelevant or redundant. Instructors teaching online will not have enough time to repeatedly explain the same vocabulary several time while teaching. In addition, several words in sentences are not important to be considered. Instructors needs then to find the most significant sentences representing the story so they can allocate more time to explain their vocabularies [1]. We focus then on identifying these sentences based on their vocabularies weight and

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highlight them to the instructors. They can start to read these sentences and explain their vocabularies to the children through images fetched from a corpus. Whenever, the instructors have more time, they can focus on the less important sentences.

3 System Components 3.1

Corpus of Vocabularies

We build a corpus of vocabularies extracted from text of stories in the animal domain for children. It contains thousands of vocabularies with their weights representing their importance in the domain of discourse. Whenever a new story is processed, the vocabularies weights are recalculated and updated automatically. Images are retrieved from the web through search engines API (i.e., Google). One of the tools available to build a rich corpus of vocabularies is Sketch Engine SE. It allows to create a corpus of texts on the domain of discourse, extract keywords and terms, calculate and updated the frequency of every entity and tag them (verb, noun, adverb, etc.). The instructor can get additional materials by selecting a list of keywords from the domain of discourse Lk and submitting it to SE which will address queries to the search engine Bing and fetch website pages based on these keywords in Lk. The instructor should check and validate the content, eliminate keywords, and text (Fig 2).

Fig. 2. Snapshot of Sketch Engine to build a corpus based on a list of keywords Lk

3.2

Assessment for Learning Vocabularies in Different Contexts

The objective of building our corpus is to know the most important vocabularies used in the domain of discourse so the instructors can focus mainly on their meaning, prepare extra materials to explain them. In fact, once the children understand very well the meaning of these vocabularies in different circumstance, they can improve largely their communication skills and they can reply to themselves in reading new stories. The instructors can assess the children based on the vocabularies with the highest frequencies. In fact, a list of these vocabularies can be produced with a list of representative images. Students will then be asked to match these words with the images and to

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put a red circle on words which they forgot their meanings. Whenever, the instructors found many red circles on students’ responses, they must reexplain these words through additional representative images. The instructors can assess the learners of Arabic language by generating a list of vocabularies in context using MonoConc software. In fact, the same vocabulary can have different meaning in different contexts. The students can be asked to form simple sentence using vocabularies in different context. 3.3

Story Visualization

Every important vocabulary in the domain of discourse is linked with a list of representative images stored the corpus. We can also create a clips-based corpus and link these highly ranked vocabularies with these video-clips. The instructor can click on the vocab and the system will propose a list of corresponding images to select from. In the case, no images are retrieved for a given vocabulary v the system will automatically address a query to a search engine (e.g., Google, Yahoo, Bing) to find images related to v. As irrelevant images can be proposed, we have developed a filtering algorithm to eliminate them automatically and return only those judged as relevant. The instructor can work independently alone and prepare the images to be presented during the online learning sessions. We can think to build a corpus of chunks (e.g., short sentences) with their representative images and clips so that the generation of multimedia tutorials will be faster. Learning through images will increase the understanding of children [5, 9, 10]. In fact, there is a saying that “An image is worth a thousand words”. The whole story can then be visualized offline and presented online to children. The system can store the story and its images to be accessible after the end of the learning session. 3.4

Queries Modes

The instructor can address different modes of search to retrieve the desired images and illustration. The best results can be obtained once the corpus of vocabularies and images is completed and covers well the domain of discourse. Experts play an important role to fine tuning the quality of the corpus. They can index the images manually by adding a list of representative keywords, tags, captions, or a short description. They can use a thesaurus to link these keywords with their synonyms. The search will then focus on similarities matching between the user keywords and these elements. However, this work is time consuming but leads to the best results. The system offers different modes of search, based on text, example images, concepts, and sketches. The instructors can click on a word, a short sentence (i.e., a concept) or an image, submit her query to the system and get back the results as shown in Fig. 3 below.

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Text Based: Oryx Example Images

Concept Plant Desert Fig. 3. Different modes of search: by keywords, by concepts, and by example images.

4 Our Approach This approach is divided into two parts: (a) Automatic creation of domain-term indexing: building a domain-oriented dataset along with methods of feeding it. (b) Story text processing and multimedia mapping: using a sentence ranking and selection algorithm, and image retrieval techniques. 4.1

Sentence Ranking Algorithm

The text of the story can sometimes be long and contains many sentences that can simply be ignored. The online teaching time is very limited, and the instructors are unable to explain every word in the text. It is therefore highly important to determine the most important sentences in the story so the instructor can focus on their vocabularies. We have already developed a ranking algorithm for text sentences that we describe briefly here [15]: Step-1: Input d = {v1,v2…,vn,} Dd = Domain of discourse Step-2: 8 vi 2 d calculate weight (v,d,Dd) Step-3: Calculate term frequency tf (vi, di) for nouns and verbs, calculate (DW) Step-4: Calculate wi combination of di = {w1, w2,…,wn}, Wi = tf (vi, di) * DW(vi, D d) A commonly used term weighting method is the normalized document frequency, which consists of assigning a high weight to a term if it occurs frequently throughout the document. Additionally, a none stop word term that occurs in nearly all documents within the specific domain has more power and will be given a greater weight. Before calculating the normalized document frequency weight of a term in a domain, it necessary to know: (1) how many documents are available in the domain (n = number of documents); and (2) how many documents of the collection the term occurs in (the document frequency = DF). The following formula is then applied: DW ¼ 1 þ DF = n

ð1Þ

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Matching Relationships and Tagged Images

Fetch an image I with R

Similarity Matching R C

Extract Features C

Corpus

I

Discard I

Fig. 4. Images fetching and matching with text.

The following algorithm 1 eliminates irrelevant images retrieved from search engines (e.g., Google or Yahoo). Only annotated images are considered while requested during learning sessions. We extract R from text, fetch an image I and match them. Whenever, a good similarity S is found between R and I, the image is relevant and will be added temporarily to the corpus. Otherwise, the image is simply discarded. We are not considering it as relevant. The instructor should validate the retrieved images and decide whether to add it to the multimedia corpus or not (Fig 4). Algorithm 1: Matching relationships and tagged images Input: (R::, , ), k) Output: Best k images Begin 1- ListImages [k], i = 0, j = 0 2- Retrieve k images from search engine based on R ListImages[k] 3- While (i < 5 && j 45 1 Educational level Size MSc Graduate 5 PhD Graduate 1 Female Male

Percentage (%) 0.0 100.0 Percentage (%) 66.6 16.6 16.6 Percentage (%) 83.3 16.6

The process of evaluating the game was simple enough as the experts played the game lone enough to have a clear image about it and afterwards completed a questionnaire based on the 10 heuristic rules (rows 1 to 10) of the Table 2. Table 2, also, contains the severity (“S” columns) and the frequency (“F” columns) that a problem emerged related to each of these rules. Each expert (columns E1 to E6) also made some comments to highlight some bad practices that should be fixed and treated better in future projects and versions of the game. Table 2. Heuristic evaluation results

E1 Νο. 1 2 3 4 5 6 7 8 9 10

E2

E3

E4

E5

E6

Heuristic rule Aesthetic and minimalist design Match between system and the real world Recognition rather than recall Consistency and standards Visibility of system status User control and freedom Flexibility and efficiency of use Help users recognize, diagnose, and recover from errors

S

F

S

F

S

F

S

F

S

F

S

F

2

0

0

0

1

0

1

1

0

0

2

1

3

0

0

0

0

0

0

0

0

0

1

0

3

2

0

0

1

3

0

0

0

0

1

1

2

0

0

0

0

0

0

0

0

0

0

0

3

0

0

0

1

2

0

0

3

1

1

1

4

0

0

0

1

1

0

0

0

0

3

2

2

0

0

0

2

3

0

0

0

0

0

2

4

0

0

0

1

3

0

0

0

0

0

0

Error prevention Help and documentation

3

0

1

0

0

0

0

0

0

0

2

2

2

0

4

3

0

4

0

0

2

1

2

4

Design and Expert Evaluation of a Serious Game

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Some problems that emerged of the evaluation process was the lack of a helping manual and of an indication where to click on the location map. Moreover, the first reviewer pointed out that the player should remember the characters’ names in order to successfully play the last scenario and some warnings by the sixth one were made about the verbosity of the dialogues and the fact that some dialogues were repeated without an important reason as well as that he was not able to go to a previous question in the scenario. All in all, the good practices outnumbered the bad ones which were mostly focused on the help and documentation rule as seen in the table above. 3.2

Face Validity

The term of face validity refers to the extent to which a test appears to measure what it is intended to measure. A test in which most people would agree that the test items appear to measure what the test is intended to measure would have strong face validity. Participants: 13 specialists from the field of education and sports were invited, with high academic and professional qualifications. Procedure: A personal invitation letter was sent to all, via e-mail, with specific instructions. Within ten days they should send a 200−300 words evaluation report. The 11 experts responded promptly to the invitation and sent a corresponding number of evaluations. In the face evaluation of the HALT game, experts were initially asked to play the whole game following the relevant scenarios gradually. Next, they should evaluate the extent to which the content: 1. Agrees with the meaning and dimensions of abuse and harassment in sports, and 2. whether the content is appropriate for informing and raising awareness among adolescents. Results: The analyses of the reports showed the unanimity of the evaluators in the following: 1. The game is interesting with characteristic and essential behaviors in its scripts, through which young people learn to recognize as problematic. 2. What makes the game useful and important is that it puts the user to think and judge behaviors that until now s/he considered normal or that s/he thought were considered acceptable by everyone. 3. The game aptly covers some of the likely incidents of abuse and harassment in sports. 4. Each aspect of the problem and every type of stakeholder have been taken into account (such as coach, athlete, staff, and parents) concerning various areas of harassment and abuse. 5. The content meets the purpose of its creation, while some improvements in the selection of answers and in its design would make it even more useful and attractive.

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4 Concluding Remarks This paper presents a serious game designed and developed in the context of HALT [6] Erasmus + Sport project. Main aim of this game is to support younf athletes to recognize harassment and abuse in sports. In addition, this paper presents the expert evaluation results in terms of usability and face validity. In general, the experts have a positive opinion about the game in both its usability and content. These results are very important for the design of similar serious games for similar target groups (adolescents). The main suggestions of the experts concern the integration of a user manual and help functionality. Based on these comments, the project team will create the next version of the game that will be evaluated by the target groups in the next phase of the project. Acknowledgment. This research has been funded with support from the European Commission. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein. The authors of this research would like to thank HALT [6] Erasmus + Sport (Project No: 603479-EPP-1-2018-1-EL-SPO-SCP) project team who generously shared their time, experience, and materials for the purposes of this paper.

References 1. Maffulli, N.: Human rights in youth sport. Br. J. Sports Med. 41(1), 59–60 (2007) 2. Alexander, S.L.: The experiences of children participating in organised sport. NSPCC, London (2011) 3. Toftegaard, N.J.: The forbidden zone: intimacy, sexual relations and misconduct in the relationship between coaches and athletes. Int. Rev. Sociol. Sport 36(2), 165–182 (2001) 4. Blumberg, F.C., Almonte, D.E., Anthony, J.S., Hashimoto, N.: Serious games: what are they? What do they do? Why should we play them. The Oxford handbook of media psychology, pp. 334–351 (2013) 5. Nielsen, J.: 10 usability heuristics for user interface design. Nielsen Norman Group, 1(1). (1995) 6. HALT (Halting Harassment and Abuse in Sports using Learning Technologies) project website, http://halt.phed.auth.gr/. Accessed 15 Sep 2020

Correction to: The Impact of a Gamified E-Learning Environment in Students Attitude: A Case Study Marcos M. Tenório , Francisco Reinaldo , Vitor Gonçalves Eliana C. Ishikawa , Lourival A. Góis , and Guataçara dos Santos Jr

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Correction to: Chapter “The Impact of a Gamified E-Learning Environment in Students Attitude: A Case Study” in: M. E. Auer and D. Centea (Eds.): Visions and Concepts for Education 4.0, AISC 1314, https://doi.org/10.1007/978-3-030-67209-6_43

In the original version of the book, the following belated correction has been incorporated: In Chapter 43, the author’s name has been changed from “Vitor Goçalves” to “Vitor Gonçalves”

The updated version of this chapter can be found at https://doi.org/10.1007/978-3-030-67209-6_43 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, p. C1, 2021. https://doi.org/10.1007/978-3-030-67209-6_61

Author Index

A Abdellatif, Sameh O., 495 Aboelezz, Ahmed, 441 Abou El-Seoud, M. Samir, 488, 503, 512, 520 Ahmed, Hossameldin, 466 Ahuett-Garza, Horacio, 189 Abhinandana, Vismitha Tumkur, 362 Akkara, Sherine, 151 Alavi, Marjan, 392 Al-emara, Sohaib, 132 Alexopoulos, Evita C., 159 Alja’am, Jihad M., 503, 512 Al-Maadeed, Somaya, 503, 512, 520 Alves, Marcelo Augusto Leal, 280 Ambikairajah, Eliathamby, 98 Andersen, Jesper, 169 Antonya, Csaba, 347 Avgerinos, Andreas, 555 B Barkoukis, Vasilios, 541, 547 Bennani, Samir, 106 Beresneva, Ekaterina, 335 Bertel, Lykke Brogaard, 169 Bogoslowski, Steven, 260 Butnariu, Silviu, 86 Buzdugan, Ioana Diana, 347 C Cabras, Francesco, 77 Caratozzolo, Patricia, 419 Castañón, Pedro Orta, 145 Cau, Federico, 77 Centea, Dan, 114, 181, 240 Chaldogeridis, Agisilaos, 547

Christodoulakis, Christina, 288 Chandrashekar, Narasimhamurthy Kyathsandra, 362 Csizmadia, Andrew, 247 Cusano, Roberto, 77 D Dimashkie, Benjamin, 114 dos Santos Jr, Guataçara, 400 Douka, Stella, 555 Doukakis, Spyridon, 159 Draghici, Camelia, 327, 411 E Elharrouss, Omar, 520 El-Mahdy, Ghada, 447 El-Sofany, Hosam F., 488 F Farah, Juan Carlos, 373 Féraud, Geneviève, 373 Fetaji, Bekim, 3 Fortuna, Jeff, 32 Fu, Ke, 385 G Gaci, Maria, 373 Gadhrri, Anoop Singh, 132 Gao, Yang, 385 Gao, Zhen, 132, 260 García-Peñalvo, Francisco, 206 Geng, Fei, 260 Ghali, Hani, 441, 495 Gillet, Denis, 373 Góis, Lourival A., 400

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. E. Auer and D. Centea (Eds.): ICBL 2020, AISC 1314, pp. 563–565, 2021. https://doi.org/10.1007/978-3-030-67209-6

564 Gonçalves, Vitor, 400 Gordenko, Mariia, 335 Gramigna, Anita, 230 Guetl, Christian, 3 H Hsiao, Yih-Chyuan, 132 Hussein, Ashraf S., 478 I Idrissi, Mohammed Khalidi, 106 Ishikawa, Eliana C., 400 Isidori, Federica, 77 J Jaliu, Codruta, 411 Jashari, Xhelal, 3 K Kahl, Wolfram, 315 Karakoula, Georgia, 547 Karam, Omar H., 478 Karavidas, Lampros, 547, 555 Karpenko, Andrii, 56 Karpenko, Natalia, 56 Karypidou, Kyriaki, 555 Kessing, David, 65 Khalifa, Batoul M. S., 503 Kim, Kwanju, 145, 189 Kiss, Ferenc, 42 Kolmos, Anette, 169 Kyriaki, Karypidou, 533 L LaRue, Ryan J., 123 Latulippe, David R., 123 Lawrence, Joshua, 114 Lazaropoulou, Despina D., 299 Lazuras, Lambros, 541, 547 Löwer, Manuel, 65, 145, 189 M MacKenzie, Allan, 219 Maiorana, Francesco, 247, 268 Makeen, Peter, 441 Maksimenkova, Olga, 335 Mallampalli, Mallikarjuna Sastry, 151 Manciulea, Ileana, 327, 411 Maragkoudakis, Yiannis, 288 Membrillo-Hernández, Jorge, 419 Mendez-Carrera, Gabriela, 189 Micheal, Amany, 447 Monaco, Isabella, 123 Morsi, Wesam Khairy, 456

Author Index Moudgalya, Kannan M., 429 Moumoutzis, Nektarios, 288 Muddappa, Amrutha, 362 Muhammad, Nasim, 307 Münzberger, Patrick, 169 N Neznanov, Alexey, 335 Nussbaumer, Alexander, 3 O Orta, Pedro, 189 Ortiz, Araceli Martinez, 98 Ourda, Despoina, 541 P Paneva-Marinova, Desislava, 288 Pari-Tito, Fernando, 206 Pavlova, Lilia, 288 Perniu, Dana, 327, 411 Perniu, Liviu, 411 Poletti, Giorgio, 230 Politopoulos, Nikolaos, 541, 547 R Raj, Vishnu K., 429 Rajabzadeh, Amin Reza, 260 Ramadan, Mohamed, 466 Ravishankar, Jayashri, 98 Reinaldo, Francisco, 400 Retbi, Asmaâ, 106 Richards, Gretchen, 247 Riedesel, Charles, 247 Rigas, Nikolaos Apostolos, 288 Righetti, Marco, 230 Rotaru, Cristina Salca, 327 Routhe, Henrik Worm, 169 S Salah, Wafaa, 466 Saleh, Moutaz, 503, 512 Salis, Carole, 77 Sanli, Abdulkadir, 49 Sanmugasundaram, K., 429 Shiakou, Monica, 555 Singh, Ishwar, 15, 32, 114, 132 Shivakumar, Bindu Tavakadahalli, 362 Smajic, Hasan, 49 Soliman, Mostafa M., 15 Souabi, Sonia, 106 Spano, Lucio Davide, 77 Srinivasan, Seshasai, 181, 240, 260, 307 Subramanian, Nandhini, 520

Author Index T Tao, Xiaoyi, 385 Tenório, Marcos M., 400 Thite, Swapneel, 98 Tsiatsos, Thrasyvoulos, 533, 541, 547, 555 Turpo-Gebera, Osbaldo, 206 U Urbina Coronado, Pedro D., 189 V Vankalkunti, Suchitra, 362 Varkey, Nancy, 429 Vasilescu, Anca, 411 Vass, Vilmos, 42 Venkitakrishnan, Rani P., 24 Vonèche Cardia, Isabelle, 373

565 W Wessel, Niels, 49 Wilson, Marie Florence, 77 Winther, Maiken, 169 X Xanthaki, Chara, 288 Y Ypsilandis, George S., 299 Ypsilanti, Antonia, 541 Yuen, Timber, 200, 356 Z Zakraoui, Jezia, 503, 512 Zarate-Yepez, Juan, 206 Zasorina, Hanna, 56 Zedda, Davide, 77