Generative Artificial Intelligence Supported Programming Learning: Learning Effectiveness and Core Competence

The programming curriculum is crucial in today’s digital age, but a common issue is its focus on technical training while neglecting essential skills enhancement. Teachers lack structured and practical guidance on instructional methods, and the wide range of students’ foundational abilities makes it difficult to cater to personalized learning needs. The advent of Generative Artificial Intelligence (GAI) technology has brought significant changes to education, with its personalized dialogue features offering effective technical support to address these challenges in programming education. This study develops a GAI-supported programming learning approach, applied in a programming course at a vocational school in China, to investigate the effects of various learning approaches on students’ learning outcomes, motivation, self-efficacy, and 5C competencies among different learning styles. The study involved 46 learners in the experimental group using GAI-assisted learning and 46 in the control group using traditional methods. Results showed that the experimental group significantly outperformed the control group in learning outcomes, motivation, self-efficacy, and 5C competencies. Moreover, students with a diverging learning style in the experimental group showed notably higher motivation than others. Additionally, creativity levels among students with diverging and assimilating learning styles in the experimental group were substantially greater than those in the control group.