Effects of ChatGPT-Based Human–Computer Dialogic Interaction Programming Activities on Student Engagement

This study seeks to deepen the understanding of the direct and indirect effects of human–computer dialogic interaction programming activities, facilitated by ChatGPT, on student engagement. Data were collected from 109 Chinese high school students who engaged in programming tasks using either ChatGPT-driven dialogic interaction or traditional pair programming. A quasi-experimental analysis revealed that ChatGPT-based programming activities remarkably boost student engagement, outperforming pair programming in behavioral, cognitive, and emotional dimensions. Results demonstrated that such activities help minimize off-task behaviors, promote higher-order cognitive skills, and foster greater interest in programming. Additionally, these interactions enhance students’ self-efficacy and reduce learning anxiety. The findings underscore the potential of ChatGPT-driven dialogic interaction in programming education. This study offers practical recommendations to enhance student engagement in programming learning.