With the breakthroughs of generative artificial intelligence in the fields of natural language processing and code generation, basic programming tasks can gradually be undertaken by large models, leading to the transformation of the programmer's role and challenges to traditional programming-related teaching content. Based on analyzing the reshaping of the programming workflow by large models, the transformation of the programmer's role, and the impacts and opportunities brought by large models to the core programming courses for engineering majors, this paper proposes comprehensive reform suggestions for the curriculum system, teaching concepts, and learning methods. By cultivating students' abilities in basic knowledge, logic, condensation and summary, and thinking in a more in-depth way, they can better use large models for programming and adapt to the needs of the era of artificial intelligence large models.

Lili Zhang, Wei Wei, Jing Li, Wentao Wu, Ge Wang. Analysis and Research on the Impact of Generative Artificial Intelligence on Engineering Programming Courses. Frontiers in Educational Research (2026), Vol. 9, Issue 6: 52-58. https://doi.org/10.25236/FER.2026.090607.

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