New SocraticRepair framework improves LLM programming tutoring

Researchers have developed SocraticRepair, a new framework designed to improve the Socratic tutoring capabilities of large language models for program debugging. This framework addresses the common issue of LLMs revealing solutions too quickly by employing a planning-guided approach. SocraticRepair was implemented by fine-tuning the Qwen2.5-Coder-7B-Instruct model on synthetic dialogues within the Python programming domain. Evaluations indicate that SocraticRepair offers superior stepwise scaffolding and question quality while significantly reducing premature solution disclosure, though challenges remain in reliable pedagogical plan generation. AI

IMPACT This research could lead to more effective AI tutors for programming, improving educational outcomes by guiding students without giving away answers.

RANK_REASON The cluster contains an academic paper detailing a new framework and model fine-tuning for AI-assisted education. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• Hugging Face
• Li et al., 2026b
• Python
• Qwen2.5-Coder-7B-Instruct
• SocraticRepair

• paper
• model release

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