Burnout Intervention Mechanisms for Online Learning Processes Enabled by Predictive Learning Analytics
Language: English
Published by Taylor and Francis Ltd, GB, 2025
- Hardcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
£ 250.45
Quantity: Over 20 available
Add to basketItem description from seller
This book aims to fully demonstrate the burnout of learners in online learning processes. The authors propose a series of feasible and reliable solutions to sufficiently obtain and analyze massive instances of online learning behavior.In order to flexibly perceive and intervene in the "burnout state" and improve online learning processes and learning effectiveness, the authors design and construct various novel data analysis models and decision prediction methods using technological means and data-driven learning strategies. Their innovative methods, techniques, and decisions would benefit autonomous learning behavior tracking and stimulate the learning interest of online learning processes enabled by predictive learning analytics. By employing behavioral science research strategies, they build adaptive prediction and optimization measures for positive online learning patterns, improve learning behaviors, optimize learning states, and establish dynamic and sustainable knowledge tracing paths and behavior scheduling methods, enabling users to achieve self-organization and self-mobilization in their overall learning processes.The book will appeal to scholars and learners in Europe, North America, and Asia, especially those majoring in educational statistics and measurement, educational big data, learning analytics, educational psychology, artificial intelligence in education, computer science, and online collaborative learning.…
Seller Inventory # LU-9781041134084
- Title
- Burnout Intervention Mechanisms for Online Learning Processes Enabled by Predictive Learning Analytics
- Author
- Xiaona Xia, Wanxue Qi
- Publisher
- Taylor and Francis Ltd, GB
- Publication year
- 2025
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 1041134088
- ISBN 13
- 9781041134084
- Item weight
- 520 grams
This book aims to fully demonstrate the burnout of learners in online learning processes. The authors propose a series of feasible and reliable solutions to sufficiently obtain and analyze massive instances of online learning behavior.
In order to flexibly perceive and intervene in the "burnout state" and improve online learning processes and learning effectiveness, the authors design and construct various novel data analysis models and decision prediction methods using technological means and data-driven learning strategies. Their innovative methods, techniques, and decisions would benefit autonomous learning behavior tracking and stimulate the learning interest of online learning processes enabled by predictive learning analytics. By employing behavioral science research strategies, they build adaptive prediction and optimization measures for positive online learning patterns, improve learning behaviors, optimize learning states, and establish dynamic and sustainable knowledge tracing paths and behavior scheduling methods, enabling users to achieve self-organization and self-mobilization in their overall learning processes.
The book will appeal to scholars and learners in Europe, North America, and Asia, especially those majoring in educational statistics and measurement, educational big data, learning analytics, educational psychology, artificial intelligence in education, computer science, and online collaborative learning.
"Synopsis" may belong to another edition of this title.
About the Author
Xiaona Xia is a professor at Qufu Normal University. She is a member of Institute of Electrical and Electronics Engineers and China Computer Federation. Her research interests include learning analytics, interactive learning environments, collaborative learning, educational big data, educational statistics, data mining, service computing, etc.
Wanxue Qi is a professor at Qufu Normal University. He is an established educational expert in higher education and moral education. His research interests include educational big data, moral education, etc.
"About the title" may belong to another edition of this title.
Rarewaves.com USA
London, London, United Kingdom
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