Education DCL: EAGER: Generative AI-based Personalized Cybersecurity Tutor for Fourth Industrial Revolution

第四次工业革命（4 IR）系统的复杂性日益增加，使其极易受到网络攻击，因此有必要为4 IR员工提供网络安全培训。虽然在线课程具有高度可扩展性，是重新培训和提高现有员工技能的理想选择，但目前，它们不适合需要使用专用硬件的4 IR网络安全培训。此外，来自不同背景的学生有不同的学习风格，这取决于他们的成长，教育背景和动机。对于来自边缘化，代表性不足的社区的学生来说，成功完成课程尤其具有挑战性，因为在他们的成长期（学前/初中/高中）缺乏高质量教育的历史可能会阻碍他们的成功。为了应对这些挑战，该项目利用了基于生成人工智能的个性化网络安全导师（gAI-PCT），这是一个可扩展的在线学习框架，通过视频讲座和基于虚拟现实（VR）的网络安全实验室培训4 IR安全员工，通过生成人工智能个性化学生的学习需求，使用情感分析来评估学生的兴趣和知识理解。这项研究是亚利桑那大学和桑迪亚国家实验室的网络安全和教育研究人员之间的合作，研究团队将探索：1）一个基于Generative AI的交互式讲师，帮助和指导学生完成他们的在线课程; 2）基于虚拟现实的网络安全培训实验室，允许游戏化的4 IR网络安全培训，包括在不冒昂贵设备或人类生命危险的情况下进行极端情况下的培训; 3）基于transformer的机器学习方法，以衡量学生在学习活动中的情绪和知识理解; 4）基于生成式人工智能的方法，使用学生的情感和理解，结合布卢姆的分类法，根据学生的学习需求个性化课程; 5）衡量非规范性结果的方法，测量学生学习干预的有效性，同时为边缘化学生服务; 6）提高学生的归属感、学术成就和工程身份的方法，这将导致通过学位提高学术持久性。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

The increasing complexity of Fourth Industrial Revolution (4IR) systems makes them highly vulnerable to cyberattacks, justifying cybersecurity training for the 4IR workforce. Although online programs are highly scalable and ideal for reskilling and upskilling an existing workforce, currently, they are unsuitable for 4IR cybersecurity training which requires access to specialized hardware. In addition, students from different backgrounds have different learning styles depending on their upbringing, educational backgrounds, and motivations. Successful program completion is especially challenging for students from marginalized, underrepresented communities, as a historical lack of access to high-quality education during their formative years (pre/middle/high schools) can impede their success. To address these challenges, this project leverages a Generative AI based Personalized Cybersecurity Tutor (gAI-PCT), a scalable online learning framework that trains a 4IR security workforce through video lectures and virtual reality (VR) based cybersecurity labs, personalized to the students learning needs through generative AI, using sentiment analysis to evaluate student interest and knowledge comprehension. This research is a collaboration between cybersecurity and education researchers at the University of Arizona and Sandia National Labs.The research team will explore: 1) a Generative AI-based interactive instructor to assist and guide students through their online coursework; 2) Virtual Reality based cybersecurity training labs that allow gamified 4IR cybersecurity training, including training on extreme scenarios without risking expensive equipment or human life; 3) Transformer-based machine learning approach to gauge student sentiments and knowledge comprehension during learning activities; 4) Generative AI-based approach to use student sentiment, and comprehension, in combination with Bloom's Taxonomy, to personalize coursework according to student's learning needs; 5) An approach to gauge non-normative outcomes measuring the effectiveness of students learning interventions while serving marginalized students; 6) An approach to increasing student's sense of belonging, academic attainment, and engineering identity that will result in increased academic persistence through the degrees.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.