Learning-by-teaching with ChatGPT: The effect of teachable ChatGPT agent on programming education
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Abstract (arXiv)
This study investigates the potential of using ChatGPT as a teachable agent to support students' learning by teaching process, specifically in programming education. While learning by teaching is an effective pedagogical strategy for promoting active learning, traditional teachable agents have limitations, particularly in facilitating natural language dialogue. Our research explored whether ChatGPT, with its ability to engage learners in natural conversations, can support this process. The findings reveal that interacting with ChatGPT improves students' knowledge gains and programming abilities, particularly in writing readable and logically sound code. However, it had limited impact on developing learners' error-correction skills, likely because ChatGPT tends to generate correct code, reducing opportunities for students to practice debugging. Additionally, students' self-regulated learning (SRL) abilities improved, suggesting that teaching ChatGPT fosters learners' higher self-efficacy and better implementation of SRL strategies. This study discussed the role of natural dialogue in fostering socialized learning by teaching, and explored ChatGPT's specific contributions in supporting students' SRL through the learning by teaching process. Overall, the study highlights ChatGPT's potential as a teachable agent, offering insights for future research on ChatGPT-supported education.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Dec 2024.
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Citing papers per year: 2025: 6; 2026: 3.
9 papers.
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- 2026What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AIcited by 2
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- 2025Chrysalis: A Unified System for Comparing Active Teaching and Passive Learning with AI Agents in Educationcited by 0
- 2026A Simulation-Based Method for Testing Collaborative Learning Scaffolds Using LLM-Based Multi-Agent Systemscited by 0
- 2026A Simulation-Based Method for Testing Collaborative Learning Scaffolds Using LLM-Based Multi-Agent Systems13 Apr 2026
- 2026Simulating Novice Students Using Machine Unlearning and Relearning in Large Language Models27 Mar 2026
- 2026What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI24 Feb 2026
- 2025Chrysalis: A Unified System for Comparing Active Teaching and Passive Learning with AI Agents in Education6 Oct 2025
- 2025A Meta-Analysis of LLM Effects on Students across Qualification, Socialisation, and Subjectification25 Sep 2025
- 2025Beyond Benchmarking: Scenario-Based Evaluation of Large Language Models for Personalized Learning2 Sep 2025
- 2025How Real Is AI Tutoring? Comparing Simulated and Human Dialogues in One-on-One Instruction2 Sep 2025
- 2025Conversational Education at Scale: A Multi-LLM Agent Workflow for Procedural Learning and Pedagogic Quality Assessment7 Jul 2025
- 2025LLM Agents for Education: Advances and Applications14 Mar 2025