生成式人工智能赋能师范院校程序设计课程教学模式构建研究

Research on the Teaching Model of Programming Courses in Normal Universities Empowered by Generative Artificial Intelligence

摘要: 生成式人工智能正在影响程序设计学习和软件开发实践，也为师范院校程序设计课程改革带来新的可能。当前课程中，学生编程基础差异较大，教学案例与教育应用场景联系不够紧密，实践指导和过程评价仍显不足。围绕师范生数字素养与程序设计实践能力培养，本文构建了由目标重构、任务驱动、人机协同、过程评价和反思改进组成的课程教学模式。该模式将AI工具嵌入课前导学、课堂实践、课后拓展和课程评价过程，通过教育场景化任务、代码分析支持和学习过程证据，引导学生从语法模仿转向问题分析、代码审查、调试优化和教育应用迁移。以2023级软件工程专业1、2班90名学生为对象的课程试用表明，该模式能够提高学习反馈的及时性，促进学生关注代码理解、AI使用规范和程序设计的教育应用价值，可为师范院校程序设计课程智能化改革提供参考。

Abstract: Generative artificial intelligence is influencing programming learning and software development practice, bringing new possibilities for the reform of programming courses in normal universities. At present, such courses still face problems such as considerable differences in students’ programming foundations, insufficient connection between teaching cases and educational application scenarios, inadequate practical guidance, and weak process evaluation. Focusing on the cultivation of normal university students’ digital literacy and programming practice ability, this paper constructs a teaching model consisting of goal reconstruction, task-driven learning, human-AI collaboration, process evaluation, and reflective improvement. The model embeds AI tools into pre-class guidance, classroom practice, after-class extension, and course evaluation. Through educational scenario-based tasks, code analysis support, and learning process evidence, it guides students to shift from grammar imitation to problem analysis, code review, debugging and optimization, and educational application transfer. A course trial involving 90 students from Classes 1 and 2 of the 2023 Software Engineering major shows that the model can improve the timeliness of learning feedback and promote students’ attention to code understanding, AI usage norms, and the educational application value of programming. This study provides a reference for the intelligent reform of programming courses in normal universities.