生成式人工智能在程序设计课程教学中的应用研究

Research on the Application of Generative Artificial Intelligence in Programming Course Teaching

摘要: 针对《Python程序设计》课程学生基础差异明显的问题，本文探讨生成式人工智能融入课程教学的路径。在方法上，综合采用文献研究、案例分析与设计研究方法，构建由自适应学习路径、实时互动问答、智能项目评估与协作编程支持四个模块构成的教学模型，进而提出实施路径、风险治理与准实验评估方案。该设计从支撑高阶能力培养、个性化学习路径、产业案例库与师资平台四个层面推进课程改革，并借助学术诚信、技术依赖、数字鸿沟与数据安全四类机制实施风险控制。预期成效通过项目完成质量、代码纠错能力、学习参与度、创新思维与课程满意度五项指标进行观测，可为本科院校《Python程序设计》课程改革提供参考。

Abstract: Aiming at the problem of obvious differences in students’ foundations in the “Python Programming” course, this paper discusses the path of integrating generative artificial intelligence into course teaching. In terms of methods, this paper comprehensively adopts literature research, case analysis and design research methods to construct a teaching model composed of four modules: adaptive learning path, real-time interactive Q&A, intelligent project evaluation and collaborative programming support, and then propose implementation paths, risk governance and quasi-experimental evaluation schemes. The design promotes curriculum reform from four levels: supporting high-order ability cultivation, personalized learning paths, industrial case databases and teacher platforms, and implements risk control through four mechanisms: academic integrity, technical dependence, digital divide and data security. The expected results are observed through five indicators: project completion quality, code error correction ability, learning participation, innovative thinking and course satisfaction, which can provide reference for the reform of “Python Programming” courses in undergraduate colleges.