Fr. 235.00

Burnout Intervention Mechanisms for Online Learning Processes - Enabled By Predictive Learning Analytic

English · Hardback

Will be released 29.09.2025

Description

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This title aims to fully demonstrate the burnout of students 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.


List of contents










1. Introduction 2. Key Burnout Feature selection and association prediction of learning behaviors 3. Learning Behavior Reasoning and Critical Path Fusion for Burnout Based on Multi Entity Association 4. Predicting Burnout States and Guiding Learning Behaviors driven by knowledge Graph Propagation 5. Adaptive Positioning of Temporal intervals for key interventions and Burnout Tracking 6. Risk Prediction and Early Warning Routing Formation of Burnout State Propagation 7. 8. Conclusion


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 theory. His research interests include educational big data, moral education, etc.


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