arXiv cs.AI· Rajeev Bhatt Ambati, Shashank Srivastava, Snigdha Chaturvedi·· 12 小时前AI 评分31
AdaTutor：通过教学策略选择实现自适应辅导
AdaTutor: Adaptive Tutoring through Pedagogical Strategy Selection
AI 导读
AdaTutor 提出 Comparative Pedagogical Supervision（CPS）训练框架，让辅导模型学会针对学生错误选择最优教学策略与反馈。在数学与科学推理数据集上，经过五轮辅导后 CPS 优于最强的固定策略基线。学到的辅导能力可跨数据集迁移，其策略选择还能为另一个基于 API 的辅导模型提供指导。
正文
Abstract:Effective tutoring requires determining not only what information to provide, but also which form of assistance to deliver. A tutor may address the same student error using various pedagogical strategies, adapting its approach as the interaction progresses. We introduce Comparative Pedagogical Supervision (CPS), a training framework to learn to select the optimal strategy and feedback for student learning. We evaluate CPS on math and science reasoning datasets. After five tutoring turns, CPS outperforms the strongest fixed-strategy baselines. The learned tutor transfers across datasets, and its strategy selection can also inform a separate API-based tutor.
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.34659 [cs.AI] |
| (or arXiv:2610.34659v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.34659 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Rajeev Bhatt Ambati [view email]
[v1]
Mon, 26 Oct 2026 00:44:29 UTC (8,941 KB)
来源：arXiv cs.AI · arxiv.org