Learning-by-teaching with ChatGPT: The effect of teachable ChatGPT agent on programming education
This research addresses programming education for students by exploring an incremental application of ChatGPT to overcome limitations in traditional teachable agents.
This study tackled the problem of enhancing programming education by using ChatGPT as a teachable agent to support learning-by-teaching, finding that it improved students' knowledge gains, programming abilities in writing readable and logical code, and self-regulated learning, though it had limited impact on error-correction skills.
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.