Description

This skill aims to truly transform smart courses from simply "building" them into "using and improving them." It is designed for university teachers who have already implemented courses and possess data on grades, assignments, evaluation rubrics, classroom interactions, or learning platforms. After teachers upload their teaching data, the system will automatically complete the following: 1. Data integrity check; 2. Overall class learning analysis; 3. Identification of knowledge points and weaknesses in skills; 4. Student stratification and learning warnings; 5. Differentiated practice and differentiated teaching interventions; 6. Quality analysis of assignments, projects, and works; 7. Analysis of course objective achievement; 8. Design of teaching data visualization solutions; 9. Attribution of teaching problems; 10. Continuous improvement plan for the next round of courses. It is applicable to various data sources, including grade sheets, assignment grading sheets, project evaluation rubrics, classroom interaction records, learning platform data, student work evaluations, and AI dialogue records. This skill does not involve redesigning the entire course; rather, based on real teaching results, it helps teachers answer three questions: How well have students learned? Where exactly are the problems? How should we teach, practice, and improve next?