Intelligent Systems and Learning Data Analytics in Online Education

1st Edition - June 15, 2021
Editors: Santi Caballé, Stavros N. Demetriadis, Eduardo Gómez-Sánchez, Pantelis M. Papadopoulos, Armin Weinberger
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 2 3 4 1 0 - 5
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 2 3 1 2 7 - 2

Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning.… Read more

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Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general.

This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply.

Cover image
Title page
Table of Contents
Copyright
Dedication
List of contributors
Foreword
Preface
Final words
Acknowledgments
Conversational agents in MOOCs: reflections on first outcomes of the colMOOC project
1 Introduction
2 Background
3 The colMOOC project
4 “Computational Thinking” MOOC
5 “Programming for non-programmers” MOOC
6 “Educational technology for the classroom” MOOC
7 “Educational technologies in support for collaboration and evaluation in virtual learning environments” MOOC
8 Discussion and conclusions
Acknowledgments and disclaimer
Further reading
Part I: Intelligent Agent Systems and Learning Data Analytics
Chapter 1. Artificial Intelligence (AI)-enabled remote learning and teaching using Pedagogical Conversational Agents and Learning Analytics
Abstract
1.1 Introduction
1.2 Literature review
1.3 Our experience with Pedagogical Conversational Agents
1.4 Results and analysis
1.5 Discussion
1.6 Future trends and conclusion
References
Chapter 2. Integrating a conversational pedagogical agent into the instructional activities of a Massive Open Online Course
Abstract
2.1 Introduction
2.2 Literature review
2.3 Research methodology
2.4 Results and discussion
2.5 Conclusions and future work
References
Chapter 3. Improving MOOCs experience using Learning Analytics and Intelligent Conversational Agent
Abstract
3.1 Introduction
3.2 Online learning and MOOCs
3.3 Methodology
3.4 LAICA integration in MOOCs: framework
3.5 LAICA integration in MOOCs: example implementation
3.6 LAICA integration in MOOC: impact analysis
3.7 LAICA integration in MOOC: findings and discussion
3.8 Conclusion
References
Further reading
Chapter 4. Sequential engagement-based online learning analytics and prediction
Abstract
4.1 Introduction
4.2 Related work
4.3 Sequential engagement-based academic performance prediction network
4.4 Experiments and evaluation
4.5 Conclusions and future work
Acknowledgment
References
Chapter 5. An intelligent system to support planning interactive learning segments in online education
Abstract
5.1 Introduction
5.2 Theoretical backgrounds of intelligent systems in active learning systems
5.3 Methodology of implementation and target group
5.4 Results and discussion
5.5 Conclusion
References
Part II: Artificial Intelligence Systems in Online Education
Chapter 6. A literature review on artificial intelligence and ethics in online learning
Abstract
6.1 Introduction and motivations
6.2 Artificial intelligence in online learning
6.3 Ethics in online learning
6.4 Ethics in artificial intelligence
6.5 Limitations of ethics by design and how moral systems can overcome them
6.6 Reflections and guidelines for an ethical use of artificial intelligence in online learning
6.7 Concluding remarks and future work
Acknowledgments
References
Chapter 7. Transfer learning techniques for cross-domain analysis of posts in massive educational forums
Abstract
7.1 Introduction
7.2 Related works
7.3 Text categorization model
7.4 Transfer learning strategy
7.5 Experiments and evaluation
7.6 Conclusions and further work
References
Chapter 8. Assisted education: Using predictive model to avoid school dropout in e-learning systems
Abstract
8.1 Introduction
8.2 Background
8.3 Related work
8.4 PRIOR Ensemble Architecture
8.5 DPE-PRIOR: Dropout predictive Ensemble Model
8.6 Final remarks
Acknowledgment
References
Chapter 9. Adaptive task selection in automated educational software: a comparative study
Abstract
9.1 Introduction
9.2 The pedagogical implications of personalized learning systems
9.3 Overview of the different adaptation schemes
9.4 Methodology and research approach
9.5 Simulation results
9.6 Discussion
9.7 Conclusions
References
Appendix A
Chapter 10. Actor’s knowledge massive identification in the learning management system
Abstract
10.1 Introduction
10.2 Diagnosis of higher education in Morocco and contribution of e-learning
10.3 Machine learning evaluation tools
10.4 E-learning massive data
10.5 Conclusion
References
Part III: Applications of Intelligent Systems for Online Education
Chapter 11. Assessing students’ social and emotional competencies through graph analysis of emotional-enriched sociograms
Abstract
11.1 Introduction
11.2 State-of-the-art analysis
11.3 Socioemotional graph analysis
11.4 Application domains
11.5 Conclusions and open research areas
References
Chapter 12. An intelligent distance learning framework: assessment-driven approach
Abstract
12.1 Introduction
12.2 Sketch of intelligent distance teaching and learning framework
12.3 Three-layered distance teaching and learning platform
12.4 Learning assessment and feedback
12.5 Analytics: mining from learning graph and assessment graph
12.6 Simulation result
12.7 Concluding remarks
References
Chapter 13. Personalizing alternatives for diverse learner groups: readability tools
Abstract
13.1 Introduction
13.2 Personalization in online education: trends, systems, and approaches
13.3 Implementing readability tools: general steps and suggestions
13.4 Discussion
13.5 Conclusion
References
Chapter 14. Human computation for learning and teaching or collaborative tracking of learners’ misconceptions
Abstract
14.1 Introduction
14.2 Related work
14.3 Results from preliminary studies
14.4 System architecture
14.5 Conclusion
References
Index

Santi Caballé

Santi Caballé is a full professor at the Universitat Oberta de Catalunya (UOC) based in Barcelona, Spain. He holds a PhD, Master's, and Bachelor’s in computing engineering from the UOC where he teaches on-line courses on software engineering and conducts research activity on the interdisciplinary field of learning engineering by combining e-learning, artificial intelligence, software engineering and distributed computing. He has over 250 peer-reviewed publications, including 15 books, 60 papers in indexed journals, and 150 conference papers. Professor Caballé has led and participated in over 30 national and international research projects and has been involved in the organization of many international research events. He also serves as editor for books and special issues of leading international journals.

Affiliations and expertise

Professor, Faculty of Computer Science, Multimedia and Telecommunications, Universitat Oberta de Catalunya, Barcelona, Spain

Stavros N. Demetriadis

Dr. Stavros N. Demetriadis holds a BSc degree in Physics, MSc in Electronic Physics, and PhD in Multimedia educational technology from AUTh. He teaches courses and conducts research in the broader area of technology- enhanced learning with emphasis on Computer-supported collaborative learning (CSCL), Adaptive hypermedia systems for learning, Educational robotics and Tangible interfaces for programming, Conversational agents, Multimedia learning, Cognitive training technologies. Dr. Demetriadis has published more than 150 research papers either in international scientific journals (with IF) or in international/national conference proceedings (more than 2500 third party citations and h-index: 25 reported in Google Scholar). He is member of the scientific committee in several top-ranking international Conferences each year (such as IEEE ICALT, ECTEL, CSEDU, etc.). Since 1995 he has participated in many AUTH research projects and has been project leader in some of them. Dr. Demetriadis is currently the coordinator of the ongoing research project "colMOOC" funded by the European Commission devoted to the integration of conversational agents and learning analytics in online education.

Affiliations and expertise

Professor, School of Informatics, Aristotle University of Thessaloniki, Greece

Eduardo Gómez-Sánchez

Eduardo Gómez-Sánchez received his PhD degree in Telecommunications Engineering in 2001. He is currently professor of Telematics Engineering at the University of Valladolid in Valladolid, Spain. His main research interests include the design and evaluation of software systems to support collaborative learning, both in formal and informal settings. He has published more than 40 papers in indexed journals and has a Google Scholar reported h-index of 27.

Affiliations and expertise

Professor, School of Telecommunications Engineering, Universidad de Valladolid, Valladolid, Spain

Pantelis M. Papadopoulos

Dr. Pantelis Papadopoulos holds a BSc in Informatics, and MSc and PhD in Information and Communication Technologies in Education from the School of Informatics at Aristotle University of Thessaloniki. His research interests include Educational Technology, Game-Based Learning, Computer-Supported Collaborative Learning, Innovation and Entrepreneurship Education, and Open and Distance Education. His work is published in more than 45 top ranking international peer-reviewed journals and conferences. Dr. Papadopoulos is an Associate Editor and chief-editor of research journals and books. He is a member of the scientific committee in several top-ranking international conferences and reviewer to major journals in his domain as well as a member of the Institute of Electrical and Electronics Engineers (IEEE), the International Society of the Learning Sciences (ISLS), and the Association for the Advancement of Computing in Education (AACE).

Affiliations and expertise

Associate Professor, Department of Instructional Technology, University of Twente, Enschede, The Netherlands

Armin Weinberger

Prof. Armin Weinberger is head of the Department of Educational Technology and Knowledge Management at Saarland University in Saarland, Germany. His main research interests are educational technology, technology-enhanced learning, computer-supported collaboration scripts, argumentative knowledge construction, crosscultural education, and methodological issues in small group learning. He is on the editorial board of ijCSCL (International Journal of Computer Supported Collaborative Learning), one the two premier journals of the Learning Sciences field, and has extensively published in this and many other leading research journals, obtaining award-winning articles in reputed journals, such as Computers in Human Behavior and Instructional Science.

Affiliations and expertise

Professor, Department of Educational Technology and Knowledge Management, Saarland University, Saarland, Germany

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Intelligent Systems and Learning Data Analytics in Online Education

Purchase options

Institutional subscription on ScienceDirect

Santi Caballé

Stavros N. Demetriadis

Eduardo Gómez-Sánchez

Pantelis M. Papadopoulos

Armin Weinberger