当AI学会“仿真思维”，教师才能回归育人本质——从“工具效率”到“认知理解”，教育AI进入深水区
Merged summary
TL;DR - Tianli Qiming introduced an education-AI framework that models students’ cognitive states rather than merely recommending content, aiming to support personalized instruction while returning teachers’ focus to mentorship.
- Its LAM feedback loop uses student behavior to infer conceptual or reasoning gaps and plan tailored learning paths.
- The “one student, one plan” system automates diagnostics, resource matching, exercise selection, and class-level analytics.
- The company reports deployment across 150+ schools, serving over 300,000 teachers and students.
- A proposed “cognitive sovereignty” framework treats inferred student mental-state data as protected information.
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当AI学会“仿真思维”，教师才能回归育人本质——从“工具效率”到“认知理解”，教育AI进入深水区
TL;DR - Tianli Qiming introduced an education-AI framework that models students’ cognitive states rather than merely recommending content, aiming to support personalized instruction while returning teachers’ focus to mentorship.
- Its LAM feedback loop uses student behavior to infer conceptual or reasoning gaps and plan tailored learning paths.
- The “one student, one plan” system automates diagnostics, resource matching, exercise selection, and class-level analytics.
- The company reports deployment across 150+ schools, serving over 300,000 teachers and students.
- A proposed “cognitive sovereignty” framework treats inferred student mental-state data as protected information.