随着人工智能技术的快速发展,编程教育正从传统的语法讲授向计算思维与实际问题解决能力培养转型。Python作为广泛采用的编程语言,其教学方式亟需创新。项目式教学虽契合编程教学的内在需求,但在实践中仍面临项目选题单一、学生认知负荷高、评价方式单一等挑战。生成式人工智能的出现为解决上述问题提供了新的路径。以DeepSeek为例,系统构建了生成式人工智能赋能下的Python项目式教学模式,围绕“项目引入—活动探究—成果展示”三大阶段,详细阐述了在“选定项目、制定计划、活动探究、作品制作、成果交流、活动评价”六个环节中,教师、学生与GenAI的协同作用机制,为生成式人工智能支持下的Python项目式教学提供系统的理论框架与教学设计参考,为后续实证研究与实践探索奠定基础。

With the rapid development of Artificial Intelligence technology, programming education is transforming from traditional grammar instruction to cultivating computational thinking and practical problem-solving abilities. Python, as a widely adopted programming language, urgently needs innovative teaching methods. While project-based learning aligns with the inherent needs of programming education, it still faces challenges in practice, such as limited project selection, high student cognitive load, and simplistic evaluation methods. The emergence of Generative Artificial Intelligence offers a new path to address these issues. Take DeepSeek as an example, this paper systematically constructs a Python project-based teaching model empowered by Generative Artificial Intelligence. Focusing on three stages—project introduction, activity exploration, and results presentation—it elaborates on the collaborative mechanism between teachers, students, and GenAI in six stages: project selection, planning, activity exploration, project creation, results sharing, and activity evaluation. It provides a systematic theoretical framework and instructional design reference for Python project-based teaching supported by generative artificial intelligence, laying the foundation for subsequent empirical research and practical exploration.