A Practical Study of Applying Generative Artificial Intelligence to Promote Programming Learning Engagement for Middle School Students

Programming education has gained prominence in the intelligent era, yet students frequently encounter coding errors and struggle with algorithm comprehension, which diminishes their learning engagement. Although generative AI has brought new vitality to programming instruction, its concrete impacts demand further exploration. This study developed three distinct AI-powered learning strategies - Inquiry Learning, Collaborative Learning and Dialogic Learning - to establish a Generative AI Programming Teaching Model specifically for junior high students. Using a quasi-experimental approach, the research compared the effectiveness of this AI teaching model against traditional methods by implementing them in separate seventh-grade classes at a Y City middle school. The results of the study show that (1) The holistic application of generative AI learning strategies significantly enhanced junior high school students' programming learning engagement. (2) Generative AI learning strategies can enhance middle school students' emotional engagement. (3) Generative AI learning strategies can enhance middle school students' cognitive engagement. (4) Generative AI learning strategies can enhance middle school students' behavioral engagement. The study makes recommendations for the experimental results in order to provide references for improving programming learning engagement.