Psychological assessment method based on online learning process data
By using online learning process data-driven psychological assessment methods, the subjectivity and static nature of existing assessment methods are addressed, enabling personalized learning and emotion management, providing personalized intervention suggestions and long-term follow-up, and improving the overall effectiveness of learning and emotion management.
Patent Information
- Application Number
- CN202610401705.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-30
- Publication Date
- 2026-07-17
AI Technical Summary
Existing assessment methods for learning and emotion-related psychological qualities are mostly subjective questionnaires, which are easily influenced by self-perception biases and social desirability. They are also difficult to capture dynamic changes, cannot detect potential learning and psychological crises in a timely manner, and lack personalized intervention suggestions and long-term follow-up mechanisms.
By acquiring process data from online learning, converting it into a normal distribution and assigning scores, and using a Bayesian network model to construct a psychological assessment model, a psychological indicator score report and emotion warning are generated. Combined with group analysis and long-term tracking, this provides a foundation for personalized intervention.
It enables timely capture of changes in students' psychological state, provides personalized psychological intervention suggestions, improves learning and emotion management effectiveness, and forms a complete closed-loop solution.