Papers with Socratic questioning
Socratic Question Generation: A Novel Dataset, Models, and Evaluation (2023.eacl-main)
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| Challenge: | Socratic questioning is a form of reflective inquiry often employed in education to encourage critical thinking in students. |
| Approach: | They present a first large dataset of 110K questions, context pairs for Socratic Question Generation. |
| Outcome: | The proposed model produces realistic, type-sensitive, human-like Socratic questions . authors show that the model can be used in counseling and coaching . |
MotivGraph-SoIQ: Integrating Motivational Knowledge Graphs and Socratic Dialogue for Enhanced LLM Ideation (2025.findings-emnlp)
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| Challenge: | Large Language Models (LLMs) have limitations in grounding ideas and mitigating confirmation bias during refinement. |
| Approach: | They propose a framework that integrates a Motivational Knowledge Graph with a Q-Driven Socratic Ideator to enhance LLM ideation. |
| Outcome: | The proposed framework enhances LLM ideation by integrating a Motivational Knowledge Graph with a Q-Driven Socratic Ideator. |
Automatic Generation of Socratic Subquestions for Teaching Math Word Problems (2022.emnlp-main)
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| Challenge: | We hypothesize that questioning can enhance human performance and assist solvers . |
| Approach: | They propose to use large language models to generate sequential questions for math word problem-solving . they propose to apply these models to a variety of math word problems . |
| Outcome: | The proposed model improves the performance of a math word problem solver by generating more questions than other models. |
Instruct, Not Assist: LLM-based Multi-Turn Planning and Hierarchical Questioning for Socratic Code Debugging (2024.findings-emnlp)
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| Challenge: | Current large language models often give away solutions directly, making them ineffective instructors. |
| Approach: | They propose to use a state space-based planning algorithm to build a question tree based on a student's knowledge state to help students independently identify and resolve errors. |
| Outcome: | The proposed model is able to debug code efficiently with minimal turns and highly Socratic questioning. |