Fostering Student Engagement and Learning Perception Through Socratic Dialogue with ChatGPT: A Case Study in Physics Education

Abstract

This classroom-based case study examines how an AI-mediated Socratic dialogue, implemented through ChatGPT, can support students’ engagement and perceived learning in undergraduate thermodynamics. Conducted in a first-year engineering physics course at a private university in northern Mexico, the activity invited small student groups to interact with structured prompts designed to promote inquiry, collaboration, and reflective reasoning about the adiabatic process. Rather than functioning as a source of answers, ChatGPT was intentionally positioned as a mediating scaffold for Socratic questioning, prompting students to articulate, examine, and refine their reasoning. A mixed-methods approach was employed, combining a 10-item Likert-scale survey with construct-level statistical analysis of two focal dimensions: perception of learning and engagement, including an exploratory comparison by gender. Results indicated consistently high levels of perceived learning and engagement across the cohort, with average scores above 4.5 out of 5. At the construct level, no statistically significant gender differences were observed, although a single item revealed higher perceived learning among female students. Overall, the findings suggest that the educational value of ChatGPT in this context emerged from its integration within a Socratic, inquiry-oriented pedagogical design, rather than from the technology alone. These results contribute to ongoing discussions on the responsible and pedagogically grounded integration of generative AI in physics education and align with Sustainable Development Goal 4 (Quality Education).

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