Socratic Tutoring

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9 papers1 paper in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

SocraticRepair: Planning-Guided Socratic Tutoring for Program Debugging and Misconception Repair
Oct 10, 2026Mykhailo Kopytskyi, Jianhua Yang, Mir SeyedebrahimiSocratic Tutoring Intelligent Tutoring Systems
University of Warwick · Warwick Manufacturing Group
ToST: A Tree-of-Thought Socratic Teaching Framework for Multi-Path Guidance and Parallel Thinking
Aug 26, 2026Feng Ling, Heng YuSocratic Tutoring Intelligent Tutoring Systems
Beijing Normal University
Beyond Direct Answering: Aligning Educational LLMs as Socratic Guides via Heuristic Reinforcement Learning
Jul 25, 2026Xiaokun Wang, Siyu Song, Wentao Liu +1LLM Alignment Intelligent Tutoring Systems
East China Normal University, Shanghai, China · Shanghai Chuangjie Situo Information Technology Co., Ltd., Shanghai, China · Shanghai Normal University, Shanghai, China +1
Reflective Dialogue or Prompt Refinement? Effects of Tutor Scaffolding on Students' Independent LLM Use for Programming
Jul 3, 2026Jerome Brender, Laila El-Hamamsy, Kim Uittenhove +4Intelligent Tutoring Systems LLM Prompting
MOBOTS & LEARN, EPFL, Switzerland · University of Teacher Education (Haute École Pédagogique) Vaud, Switzerland · Center for Digital Education & LEARN, EPFL, Switzerland
Hey Chat, Can You Teach Me? Structuring Socratic Dialogue for Human Learning in the Wild
Jun 10, 2026Sidney Tio, Arunesh Sinha, Pradeep VarakanthamIntelligent Tutoring Systems AI in Education
School of Computing and Information Systems Singapore Management University · Department of Management Science and Information Systems Rutgers Business School
SocraticPO: Policy Optimization via Interactive Guidance
Jun 3, 2026Zirui Liu, Jie Ouyang, Qi Liu +8RL for Language Model Reasoning LLM-Guided RL
State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China · iFLYTEK AI Research (Central China), iFLYTEK Co., Ltd
PEARL: Training Socratic Tutors with Pedagogically Aligned Reinforcement Learning
May 28, 2026Qikai Chang, Zhenrong Zhang, Linbo Chen +4Multi-Objective Reinforcement Learning Intelligent Tutoring Systems
University of Science and Technology of China · iFLYTEK Research
Retrieval-Augmented Tutoring for Algorithm Tracing and Problem-Solving in AI Education
May 13, 2026Mragisha Jain, Tirth Bhatt, Griffin Pitts +6Retrieval-Augmented Generation Intelligent Tutoring Systems
North Carolina State University · University of Pittsburgh · University of California, Berkeley +1
From Surface Learning to Deep Understanding: A Grounded AI Tutoring System for Moodle
May 7, 2026Anna Ostrowska, Michał Kukla, Gabriela Majstrak +4Intelligent Tutoring Systems AI in Education
Faculty of Mathematics and Information Sciences, Warsaw University of Technology, Warsaw, Poland

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SocraticRepair: Planning-Guided Socratic Tutoring for Program Debugging and Misconception Repair

Mykhailo Kopytskyi, Jianhua Yang, Mir Seyedebrahimi

University of Warwick · Warwick Manufacturing Group

Socratic Tutoring Intelligent Tutoring Systems Code Language Models

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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.