Developing Students' Computational Thinking through Project-Based Learning Empowered by Generative AI: A Practical Study
Pingzhang Gou, Xuanyu Ren · 2025
Generative artificial intelligence shows broad application potential in the field of education, as the core thinking of the foundation of human intelligence, computational thinking urgently needs to proactively adapt to the development trend of generative artificial intelligence, and to promote the in-depth transformation of teaching methods. Taking the development of computational thinking ability as the goal, we construct a ternary teaching model that covers the empowerment layer, teaching layer and target layer, and integrates generative artificial intelligence and project-based teaching method. Taking the course of Python Programming as an example, the teaching practice is carried out. The findings demonstrate that the approach considerably enhances students' overall computational thinking skills, particularly in task decomposition, algorithm design, and assessment reflection, and lessens the complexity of problem comprehension and program development. Meanwhile, further optimization strategies for teaching are proposed to provide practical paths and theoretical references for promoting curriculum integration and teaching innovation in the context of artificial intelligence.