模拟学生会犯真实错误，助AI导师更快学习
原标题：Simulated students that make realistic mistakes help AI tutors learn faster
AI 摘要
微软与伊利诺伊大学的研究团队提出 StudentSim 系统，通过有限数据为每个学生构建能复现其典型错误、并能根据导师提示修正答案的数字孪生。该系统以阿里 Qwen3-4B-Instruct 为基础模型，采用两阶段训练，在国际象棋、英语和数学三个科目上表现优于被提示扮演学生的 GPT-5.4。研究者还用学生副本训练国际象棋导师，其解释质量和适应性评分最高，但强调这只是概念验证，代码已在 GitHub 公开。
正文节选
Simulated students that make realistic mistakes help AI tutors learn faster A new system from Microsoft and the University of Illinois builds realistic replicas of individual students from limited data. These replicas provide rapid feedback when getting it from real students would be too expensive and slow, helping researchers improve AI tutors. AI tutors work best when they adapt to each student's strengths and weaknesses. But finding out which guidance works for each student takes time and mon