石家庄学院学报

随着人工智能（AI）技术快速发展，高校教学面临内容滞后、与产业脱节等问题。为应对这一挑战，针对软件工程课程教学，构建并实践了“案例驱动+项目导向”的AI赋能教学模式。该模式重构教学内容，将自然语言处理、机器学习等AI工具深度融入软件开发生命周期各阶段，并在实践阶段以真实产业项目为载体，形成“预习—研讨—实践—智能评估—复盘”的闭环教学流程。同时，构建了融合过程性、结果性与创新性的智能化多元评价体系。实证结果表明：该教学模式成效显著，学生综合成绩显著提升，低分现象得到消除，学生能力分化程度减小。问卷调查结果显示，学生在AI工具应用、复杂问题解决等维度自评得分较高，课程满意度达97.7%。综上，该教学模式有效提升了学生的工程实践与创新能力，为软件工程教学改革提供了可复制、有数据支撑的实践方案。

With the rapid development of artificial intelligence(AI) technologies, higher education is confronted with challenges such as outdated teaching content and disconnection from industry practices. To address these issues, an AI-empowered teaching model featuring "case-driven learning plus project-oriented practice" has been constructed and implemented for software engineering courses. This model reconstructs the teaching content by deeply integrating AI tools including natural language processing and machine learning into all phases of the software development life cycle. In practical teaching, real industrial projects are adopted as core carriers, forming a closed-loop teaching process: preview, discussion, practice, intelligent assessment, and retrospective review.Meanwhile, an intelligent and diversified evaluation system has been established, combining process-based,outcome-based and innovation-based assessment. Empirical results demonstrate that the teaching model achieves remarkable effects: students' overall academic performance has been significantly improved, the occurrence of low grades has been eliminated, and the gap in students' competency levels has narrowed. Questionnaire surveys reveal that students score highly in self-evaluations of AI tool application and complex problem-solving, with a course satisfaction rate reaching 97.7%. In summary, this teaching model effectively enhances students' engineering practice and innovative capabilities, providing a replicable and data-supported practical solution for the reform of software engineering education.