AdaTutor: Adaptive Tutoring through Pedagogical Strategy Selection
Overview & Synopsis
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.
Indexed from repository: arXiv
(
arxiv.org)
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Document Information
| Document Title | AdaTutor: Adaptive Tutoring through Pedagogical Strategy Selection |
|---|---|
| Author / Organization | Rajeev Bhatt Ambati, Shashank Srivastava, Snigdha Chaturvedi |
| Subject & Discipline | cs.AI |
| Categories | Computer Science & Mathematics |
| Publication Year | 2026 |
| License / Rights | arXiv Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
arXiv
(arxiv.org)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-6144 |
| Original Source Link | Visit Source Page on arxiv.org » |