Maximizing Student Engagement in Coding Education with Explanatory AI

This innovative practice paper presents a novel AI-powered approach to increasing student engagement in coding education. It involves providing students with real-time explanations of their code and compiler error messages while they code. The approach was implemented into the free online coding platform, Process Feedback, where students were given the options to ‘explain error’ and ‘explain code’ during their coding process. The platform was used by approximately two hundred students from an engineering college in Nepal and a research university in the United States, and these students participated in a post-usage survey. Analysis of the survey data indicates that students found the AI-generated explanations significantly beneficial for understanding and resolving coding issues. The availability of accessible explanations helped students navigate coding challenges and improved their understanding of code. The findings suggest that incorporating AI-driven explanatory tools into coding education can substantially enhance student engagement and learning outcomes. Furthermore, this approach can encourage self-reflection on students' coding practices and their use of AI. The implementation within Process Feedback is available for public use, offering a valuable resource for programming teachers and students.