Educational scenarios on the ground implementation program
Key steps in building an intelligent tutoring system:
- domain qualification: Use
Prompt TemplateLimit the range of responses, e.g."你是一名初中数学老师，请用15岁学生能理解的方式解释..." - Error analysis function: Additional instructions when entering student's incorrect answers
"请分析以下错误原因，并给出三种解题思路" - Difficulty Adaptation: Add in the cue word
"知识深度：小学/初中/高中"Parameters control the output complexity
Systems Integration Program:
- Development of Flask/Django middleware to handle pre-processing of student questions and post-processing of results
- Enhance knowledge accuracy by incorporating RAG technology and connecting to textbook PDF/EPUB repositories
- For teaching programming, enable
code_interpreterExample of mode auto-execution code
Note: Education scenarios are recommended to be turned onsafe_mode=True(custom implementations required), filter inappropriate content; regularly test model performance with EDU-CAT assessment set
This answer comes from the articleQwen3-8B-BitNet: an open source language model for efficient compressionThe
May not be reproduced without permission:AI productivity tools " How to apply Qwen3-8B-BitNet for personalized learning tutoring in educational scenarios?
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