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Learning analytics in open and distributed learning : potential and challenges / Paul Prinsloo, Sharon Slade, Mohammad Khalil, editors

Contributor(s): Prinsloo, Paul | Slade, Sharon | Khalil, MohammadMaterial type: TextTextSeries: Publisher: Singapore : Springer, 2022Description: 1 online resource (vii, 126 pages) : illustrations (some color)ISBN: 9789811907852; 9789811907852; 9789811907852; 9789811907852Subject(s): Education | Education | Education, HigherDDC classification: LB1028.5 .L43 2022 Online resources: Click here to access online | Click here to access online | Click here to access online
Contents:
Foreword -- Introduction -- Chapter 1: The Potential of Learning Analytics for Intervention in ODL; Billy Wong -- Chapter 2: A Global South perspective on learning analytics in an Open Distance e-Learning (ODeL) institution; Angelo Fynn, Jaroslaw Adamiak & Kelly Young -- Chapter 3: Learning analytics in open and distance higher education: The case of the Open University UK; Avinash Boroowa; Christothea Herodotou -- Chapter 4: Mobile Multimodal Learning Analytics Conceptual Framework to Support Student Self-Regulated Learning (MOLAM); Mohammad Khalil -- Chapter 5: Designing a Social Learning Analytics Tool for Open Annotation and Collaborative Learning; Jeremiah H. Kalir -- Chapter 6: Situating Learning Analytics for Course Design in online secondary contexts; Joshua Quick & Rebecca C. Itow -- Chapter7: Ethical considerations of artificial intelligence in learning analytics in distance education contexts; Leona Ungerer & Sharon Slade -- Chapter 8: Conclusion
Summary: This book explores and further expands on the rich history of theoretical and empirical research in open and distributed learning, and addresses the impact of the "data revolution" and the emergence of learning analytics on this increasingly diverse form of educational delivery. Following an introductory chapter that maps the book's conceptual rationale, the book discusses the potential, challenges and practices of learning analytics in various open and distributed contexts. A concluding chapter briefly summarises the chapters before providing a tentative future research agenda for learning analytics in open and distributed environments
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Holdings
Item type Current library Call number Status Date due Barcode
Books Books Gabriel Afolabi Ojo Central Library (Headquarters).
LB1028.5 .L43 2022 (Browse shelf(Opens below)) Available 0194468
Books Books Gabriel Afolabi Ojo Central Library (Headquarters).
LB1028.5 .L43 2022 (Browse shelf(Opens below)) Available 0194467
Books Books Gabriel Afolabi Ojo Central Library (Headquarters).
LB1028.5 .L43 2022 (Browse shelf(Opens below)) Available 0194469

Foreword -- Introduction -- Chapter 1: The Potential of Learning Analytics for Intervention in ODL; Billy Wong -- Chapter 2: A Global South perspective on learning analytics in an Open Distance e-Learning (ODeL) institution; Angelo Fynn, Jaroslaw Adamiak & Kelly Young -- Chapter 3: Learning analytics in open and distance higher education: The case of the Open University UK; Avinash Boroowa; Christothea Herodotou -- Chapter 4: Mobile Multimodal Learning Analytics Conceptual Framework to Support Student Self-Regulated Learning (MOLAM); Mohammad Khalil -- Chapter 5: Designing a Social Learning Analytics Tool for Open Annotation and Collaborative Learning; Jeremiah H. Kalir -- Chapter 6: Situating Learning Analytics for Course Design in online secondary contexts; Joshua Quick & Rebecca C. Itow -- Chapter7: Ethical considerations of artificial intelligence in learning analytics in distance education contexts; Leona Ungerer & Sharon Slade -- Chapter 8: Conclusion

This book explores and further expands on the rich history of theoretical and empirical research in open and distributed learning, and addresses the impact of the "data revolution" and the emergence of learning analytics on this increasingly diverse form of educational delivery. Following an introductory chapter that maps the book's conceptual rationale, the book discusses the potential, challenges and practices of learning analytics in various open and distributed contexts. A concluding chapter briefly summarises the chapters before providing a tentative future research agenda for learning analytics in open and distributed environments

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