人工智能赋能三螺旋模型驱动的网络攻防课程思政改革研究

Research on Ideological-Political Reform in Network Offense and Defense Course Driven by AI-Empowered Triple Helix Model

摘要: 网络攻防技术课程兼具技术敏感性与伦理敏感性，其课程思政建设长期面临思政元素与专业内容融合不畅的困境。大语言模型的快速发展为破解这一难题提供了新的技术路径。本文在三螺旋理论基础上，引入AI作为贯穿“专业能力–思政素养–创新素质”的赋能轴，构建了“三螺旋 + AI”融合模式。该模式将AI安全与大语言模型伦理纳入教学内容，利用AI驱动实现思政案例的精准匹配与动态生成，借助自然语言处理技术对学生反思日志进行思政素养的多模态评估。同时，本文分析AI评估中的隐私、数据安全和算法偏见风险，并讨论该模式在师资、技术与资源方面的推广局限。教学实践表明，该模式有效提升了学生的专业认同感、思政获得感与创新参与度。

Abstract: The course on Network Attack and Defense Technologies possesses both technical sensitivity and ethical sensitivity, and its ideological-political education construction has long faced the difficulty of poor integration between ideological-political elements and professional content. The rapid development of large language models offers a new technological pathway to address this challenge. Building on the Triple Helix theory, this paper introduces AI as an empowering axis that runs through “professional competence - ideological-political literacy - innovative qualities,” and constructs a “Triple Helix + AI” integration model. This model incorporates AI security and large-model ethics into the teaching content, utilizes AI-driven approaches to achieve precise matching and dynamic generation of ideological-political cases, and employs natural language processing techniques to conduct multimodal assessment of students’ ideological-political literacy based on their reflective journals. This paper analyzes the risks of privacy, data security, and algorithmic bias in AI assessment, and discusses the limitations of scaling up this model in terms of faculty, technology, and resources. Teaching practice demonstrates that this model effectively enhances students’ professional identity, ideological-political attainment, and innovative engagement.