# Learning-by-teaching with ChatGPT: The effect of teachable ChatGPT agent on programming education

arXiv: https://arxiv.org/abs/2412.15226 · HTML: https://mlsanity.com/paper/2412.15226/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Dec 2024.

## Built on by (most cited first, 9 of 9)

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- [Simulating Novice Students Using Machine Unlearning and Relearning in Large Language Models](https://mlsanity.com/paper/2603.26142/) (2026)
- [How Real Is AI Tutoring? Comparing Simulated and Human Dialogues in One-on-One Instruction](https://mlsanity.com/paper/2509.01914/) (2025)
- [A Meta-Analysis of LLM Effects on Students across Qualification, Socialisation, and Subjectification](https://mlsanity.com/paper/2509.22725/) (2025)
- [What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI](https://mlsanity.com/paper/2602.20547/) (2026)
- [Beyond Benchmarking: Scenario-Based Evaluation of Large Language Models for Personalized Learning](https://mlsanity.com/paper/2509.05346/) (2025)
- [Chrysalis: A Unified System for Comparing Active Teaching and Passive Learning with AI Agents in Education](https://mlsanity.com/paper/2510.05271/) (2025)
- [A Simulation-Based Method for Testing Collaborative Learning Scaffolds Using LLM-Based Multi-Agent Systems](https://mlsanity.com/paper/2604.11161/) (2026)

## 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.