Generative AI and Knowledge Mapping in Programming Education: Student Learning and Engagement

Abstract

This study examines how Generative AI and knowledge-mapping tools support student learning and engagement in programming education. A quasi-experimental design was conducted with 30 undergraduate students enrolled in an object-oriented programming course, where participants used both tools across a four-week intervention. Data were collected through task performance and learner perception surveys. The results indicate that students reported higher ease of use and immediate support when using Generative AI, while knowledge mapping was associated with stronger support for conceptual understanding and reflective learning in later stages. These findings suggest that the two approaches support different aspects of learning, with Generative AI facilitating rapid clarification and knowledge-mapping tools encouraging structured conceptual engagement. The study contributes to the e-learning field by providing empirical insight into how different forms of learning support function within the same instructional context. Rather than positioning the tools as direct alternatives, the findings highlight their complementary pedagogical roles and offer guidance for integrating adaptive AI support with structured learning approaches in programming education.