High school Chinese classical Chinese teaching method and system
By employing a three-tiered progressive framework and a three-dimensional dynamic knowledge graph, combined with an emotion-cognition dual engine, the problem of low interest, fragmented knowledge, and insufficient personalization in traditional high school Chinese language teaching has been solved. This has enabled highly efficient teaching that is personalized, emotionally aligned, and achieves a closed-loop learning process, thereby improving students' academic performance and interest.
Patent Information
- Application Number
- CN202610195132.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-11
- Publication Date
- 2026-05-26
AI Technical Summary
Traditional high school Chinese language teaching suffers from problems such as low learning interest, fragmented knowledge, lack of personalization, neglect of emotions, delayed teaching feedback, and a lack of a closed loop for ability development. Existing tools have failed to effectively solve these problems.
It adopts a three-tiered progressive framework, integrates a three-dimensional dynamic knowledge graph with an emotion-cognition dual engine, constructs a three-dimensional dynamic knowledge graph of "text-language-Tao" and introduces a dynamic weight adjustment algorithm. Combined with micro-expression data and learning behavior, it realizes personalized teaching and emotional adaptation, forming a complete closed loop for ability cultivation.
This resulted in an 88% increase in student learning interest and satisfaction, a 60% reduction in anxiety, a 24.2% increase in classical Chinese test scores, an increase in the completion rate of creative tasks from 41% to 85%, more precise teaching feedback, and a 42% reduction in teachers' lesson preparation time.