arXiv:2502.15357cs.CYcs.AI2025-02被引 18

将生成式AI融入网络安全教学,提升学生批判性思维与实践能力。

Integrating Generative AI in Cybersecurity Education: Case Study Insights on Pedagogical Strategies, Critical Thinking, and Responsible AI Use

  • 通过教程与测评双阶段嵌入GenAI,训练学生生成并优化安全策略。
  • 学生在评估中显著提升风险分析与理论实践结合能力,但存在依赖过强问题。
  • 适合关注AI教育应用、培养未来安全人才的高校教师与课程设计者。

生成式人工智能(GenAI)的快速发展为高等教育带来了新机遇,尤其在需要分析推理与合规性的领域如网络安全管理中。本研究提出一种结构化框架,将GenAI工具融入网络安全教育,展示其在培养批判性思维、解决实际问题及增强合规意识方面的作用。实施采用两阶段策略:在教程中让学生生成、评估并改进由AI辅助的安全政策;在考核中要求将AI输出应用于真实场景,确保符合行业标准与法规要求。结果显示,借助AI学习的学生在政策评估、风险分析与理论实践衔接方面能力明显提升。学生反馈与教师观察表明,分析参与度提高,但存在对AI过度依赖、数字素养差异及内容情境局限等问题。通过有指导的干预与持续优化,学生逐渐认识到AI作为生成工具的优势及其需人工监督的本质。研究强调,在网络安全教育中必须平衡自动化与专家判断,以培养具备实战能力的专业人才。未来研究应探讨长期使用AI学习对安全能力的影响,以及自适应AI测评在个性化教学中的潜力。

原文摘要 · Abstract (English)

The rapid advancement of Generative Artificial Intelligence (GenAI) has introduced new opportunities for transforming higher education, particularly in fields that require analytical reasoning and regulatory compliance, such as cybersecurity management. This study presents a structured framework for integrating GenAI tools into cybersecurity education, demonstrating their role in fostering critical thinking, real-world problem-solving, and regulatory awareness. The implementation strategy followed a two-stage approach, embedding GenAI within tutorial exercises and assessment tasks. Tutorials enabled students to generate, critique, and refine AI-assisted cybersecurity policies, while assessments required them to apply AI-generated outputs to real-world scenarios, ensuring alignment with industry standards and regulatory requirements. Findings indicate that AI-assisted learning significantly enhanced students' ability to evaluate security policies, refine risk assessments, and bridge theoretical knowledge with practical application. Student reflections and instructor observations revealed improvements in analytical engagement, yet challenges emerged regarding AI over-reliance, variability in AI literacy, and the contextual limitations of AI-generated content. Through structured intervention and research-driven refinement, students were able to recognize AI strengths as a generative tool while acknowledging its need for human oversight. This study further highlights the broader implications of AI adoption in cybersecurity education, emphasizing the necessity of balancing automation with expert judgment to cultivate industry-ready professionals. Future research should explore the long-term impact of AI-driven learning on cybersecurity competency, as well as the potential for adaptive AI-assisted assessments to further personalize and enhance educational outcomes.

生成式AI网络安全教育创新

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