arXiv cs.AI· Mykhailo Kopytskyi, Jianhua Yang, Mir Seyedebrahimi·· 3 天前AI 评分27
SocraticRepair：规划引导的苏格拉底式辅导框架，用于程序调试与错误概念修复
SocraticRepair: Planning-Guided Socratic Tutoring for Program Debugging and Misconception Repair
AI 导读
SocraticRepair 是一个规划引导的苏格拉底式辅导框架，用于程序调试与错误概念修复，通过在四个预处理编程数据集构建的合成多轮辅导对话上微调 Qwen2.5-Coder-7B-Instruct 实现。实验显示，该框架在逐步引导和提问质量上得分更高，并大幅减少过早泄露答案的情况，但可靠的教学计划生成仍是待解难题。
正文 · 原文
Abstract:Large language models are increasingly used in computer science education. However, the teaching abilities of even the most powerful LLMs are limited: they tend to reveal the solution prematurely and may lose focus on the learner's current debugging objective. To address this, we introduce SocraticRepair, a planning-guided Socratic tutoring framework for program debugging and miscon- ception repair that adapts prior planning-guided tutoring work (Li et al., 2026b). The framework is instantiated in the Python programming domain by fine-tuning Qwen2.5-Coder-7B-Instruct on synthetic multi-turn tutoring dialogues constructed from four preprocessed programming datasets. The system is evaluated using a predefined set of independent metrics and benchmarked against a general-purpose LLM. The experiments show that SocraticRepair achieves higher scores on stepwise scaffolding and question quality while also substantially reducing premature solution disclosure. The results also identify reliable pedagogical plan generation as an important remaining challenge.
| Subjects: | Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.15204 [cs.AI] |
| (or arXiv:2610.15204v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.15204 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Mykhailo Kopytskyi [view email]
[v1]
Sat, 10 Oct 2026 22:28:56 UTC (60 KB)
来源：arXiv cs.AI · arxiv.org