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.
1. Intelligent Systems and Learning Data Analytics in Online Education - p. ii 2. Cover - p. ii 3. Title Page - p. ii 4. Copyright Page - p. iii 5. Table of Contents - p. iii 6. Dedication - p. iv 7. List of Contributors - p. xvii 8. Foreword - p. xxi 9. Preface - p. xxv 10. Acknowledgments - p. xxxv 11. Chapter 1 Artificial Intelligence (AI)-enabled remote learning and teaching using Pedagogical Conversational Agents and Learning Analytics - p. 3 12. Chapter 2 Integrating a conversational pedagogical agent into the instructional activities of a Massive Open Online Course - p. 31 13. Chapter 3 Improving MOOCs experience using Learning Analytics and Intelligent Conversational Agent - p. 47 14. Chapter 4 Sequential engagement-based online learning analytics and prediction - p. 71 15. Chapter 5 An intelligent system to support planning interactive learning segments in online education - p. 91 16. Chapter 6 A literature review on artificial intelligence and ethics in online learning - p. 111 17. Chapter 7 Transfer learning techniques for cross-domain analysis of posts in massive educational forums - p. 133 18. Chapter 8 Assisted education: Using predictive model to avoid school dropout in e-learning systems - p. 153 19. Chapter 9 Adaptive task selection in automated educational software: a comparative study - p. 179 20. Chapter 10 Actor’s knowledge massive identification in the learning management system - p. 205 21. Chapter 11 Assessing students’ social and emotional competencies through graph analysis of emotional-enriched sociograms - p. 239 22. Chapter 12 An intelligent distance learning framework: assessment-driven approach - p. 273 23. Chapter 13 Personalizing alternatives for diverse learner groups: readability tools - p. 301 24. Chapter 14 Human computation for learning and teaching or collaborative tracking of learners’ misconceptions - p. 323 25. Index - p. 345
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.
1. Intelligent Systems and Learning Data Analytics in Online Education - p. ii 2. Cover - p. ii 3. Title Page - p. ii 4. Copyright Page - p. iii 5. Table of Contents - p. iii 6. Dedication - p. iv 7. List of Contributors - p. xvii 8. Foreword - p. xxi 9. Preface - p. xxv 10. Acknowledgments - p. xxxv 11. Chapter 1 Artificial Intelligence (AI)-enabled remote learning and teaching using Pedagogical Conversational Agents and Learning Analytics - p. 3 12. Chapter 2 Integrating a conversational pedagogical agent into the instructional activities of a Massive Open Online Course - p. 31 13. Chapter 3 Improving MOOCs experience using Learning Analytics and Intelligent Conversational Agent - p. 47 14. Chapter 4 Sequential engagement-based online learning analytics and prediction - p. 71 15. Chapter 5 An intelligent system to support planning interactive learning segments in online education - p. 91 16. Chapter 6 A literature review on artificial intelligence and ethics in online learning - p. 111 17. Chapter 7 Transfer learning techniques for cross-domain analysis of posts in massive educational forums - p. 133 18. Chapter 8 Assisted education: Using predictive model to avoid school dropout in e-learning systems - p. 153 19. Chapter 9 Adaptive task selection in automated educational software: a comparative study - p. 179 20. Chapter 10 Actor’s knowledge massive identification in the learning management system - p. 205 21. Chapter 11 Assessing students’ social and emotional competencies through graph analysis of emotional-enriched sociograms - p. 239 22. Chapter 12 An intelligent distance learning framework: assessment-driven approach - p. 273 23. Chapter 13 Personalizing alternatives for diverse learner groups: readability tools - p. 301 24. Chapter 14 Human computation for learning and teaching or collaborative tracking of learners’ misconceptions - p. 323 25. Index - p. 345
