一种基于人机协同交互过程数据的学习者认知状态判定方法及系统
By collecting human-computer collaborative interaction data and processing it using long short-term memory neural networks, the problem of the inability to monitor learners' cognitive state in real time in existing technologies has been solved, enabling accurate assessment of learners' cognitive state and behavioral differentiation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN NORMAL UNIVERSITY
- Filing Date
- 2026-05-06
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies cannot monitor learners' cognitive states in real time and lack the ability to uncover subtle features in the human-computer collaborative learning process. This results in an inability to distinguish between deep task-oriented thinking and cognitive overload, and the assessment methods are lagging and prone to creating the illusion of high scores but low abilities.
By collecting timestamp data, text content data, and copy-paste operation data during human-computer collaborative interaction, and using a long short-term memory neural network to process the three-dimensional temporal feature tensor, the learner's cognitive state is determined to be either content reuse or reconstruction.
It achieves seamless and accurate assessment of learners' cognitive states, improves the real-time performance and accuracy of cognitive engagement state recognition, and can distinguish between content reuse and reconstruction behaviors.
Smart Images
Figure CN122132556B_ABST