Burnout Intervention Mechanisms for Online Learning Processes Enabled by Predictive Learning Analytics

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A01=Wanxue Qi
A01=Xiaona Xia
adaptive intervention strategies
Author_Wanxue Qi
Author_Xiaona Xia
behavioural science in education
Burnout Intervention Mechanisms
burnout prevention in digital education
Category=JNC
Category=JNQ
Category=UYQ
educational data mining
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Massive online learning behavior instances
Online Learning Processes
Predictive Learning Analytics
risk prediction modelling
self-regulated learning
student engagement analysis

Product details

  • ISBN 9781041134084
  • Weight: 560g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Sep 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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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.

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.

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