Ke Yang
@EmpathYang
1 Following 491 Followers
Building AI tutors requires feedback from students, but real learner studies are slow and hard to scale. 📈
Just in: StudentSim (Microsoft×UIUC) trains personalized AI student simulators 🤖 from real learner 🧑🎓 records and evaluates whether they both match a specific student’s behavior and can respond to tutor guidance.
✏️ Across three learning domains, StudentSim outperforms strong student simulator baselines, including GPT-5.4. In a chess tutor RL study, using StudentSim as guidance helpfulness feedback led to tutor guidance that human experts rated higher in accuracy, guidance quality, and personalization.
📄 Arxiv: 2609.01591
💻 Code: microsoft/StudentSim
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