EAGER: SaTC-EDU: Mathematically-grounded metaphors to teach AI-related cybersecurity

EAGER：SaTC-EDU：以数学为基础的隐喻来教授人工智能相关的网络安全

• 批准号: 2039616
• 负责人: Nicole Bannister Sinwell
• 金额: $ 30万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039616&HistoricalAwards=false
• 关键词: EAGER; SaTC; EDU; Mathematically; grounded

As the use of artificial intelligence (AI) becomes increasingly widespread in modern society, the need for children to learn cybersecurity practices that protect against the privacy and security risks created by digital systems is increasingly urgent. This project will address this need by developing and implementing a time- and teacher-friendly learning module that is geared towards middle school students. The learning module will be designed to integrate into existing middle school math curricula. There is a critical need to develop such educational materials, particularly for adolescents from minority groups that are underrepresented in STEM because they unduly experience harm from AI-related cybersecurity issues and are less likely to have school-based experiences that can inform their responses. The project seeks to empower middle school adolescents to manage their own digital identities and risk-taking in an increasingly AI-influenced world. This project will also support graduate students in computing and education to participate meaningfully and gain experience in collaborative, school-based, transdisciplinary research. The project will share materials developed to provide flexible, widespread access to the resources for middle school education stakeholders across the U.S.This project aims to improve middle school students’ use of security “best-practices” in their day-to-day online activities, while enhancing their fundamental understanding of the underlying security principles and math concepts that drive AI and cybersecurity technologies. To this end, the project team is developing a learning module that relies on the educational principle of “metaphors as reification” to teach AI-related cybersecurity. The innovation in this approach entails grounding these metaphors in their underlying mathematical principles. The project transcends research on “explainable AI” by giving end users a fundamental understanding of the mathematical principles behind AI, which constitutes a key advance in cybersecurity training. To investigate middle school students’ AI-related cybersecurity competencies relative to their mathematics knowledge and behaviors, the project team will use a mixed methods, exploratory research approach. A combination of pre- and post-tests of students’ cybersecurity knowledge, behavioral intention surveys, math affinity, observed decision-making in a “cybersecurity drill,” and module-specific test scores, will be used to evaluate the project. This project is supported by a special initiative of the Secure and Trustworthy Cyberspace (SaTC) program to foster new, previously unexplored, collaborations between the fields of cybersecurity, artificial intelligence, and education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.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.

随着人工智能(AI)在现代社会的使用日益广泛，儿童学习网络安全做法以防范数字系统造成的隐私和安全风险的需求日益迫切。该项目将通过开发和实施面向中学生的时间和教师友好型学习模块来满足这一需求。学习模块将被设计成整合到现有的中学数学课程中。迫切需要编写这种教育材料，特别是针对少数群体的青少年，这些群体在STEM中的代表性不足，因为他们不适当地经历了与人工智能相关的网络安全问题的伤害，不太可能拥有能够为他们的应对措施提供信息的在校经历。该项目旨在增强中学生在日益受到人工智能影响的世界中管理自己的数字身份和冒险行为的能力。该项目还将支持计算机和教育领域的研究生有意义地参与并获得合作、校本、跨学科研究的经验。该项目将共享开发的材料，为美国各地的中学教育利益相关者提供灵活、广泛的资源访问。该项目旨在改善中学生在日常在线活动中使用安全“最佳实践”的情况，同时增强他们对推动人工智能和网络安全技术的潜在安全原则和数学概念的基本理解。为此，项目组正在开发一种学习模块，该模块依托“隐喻为物化”的教育原则，教授与AI相关的网络安全。这种方法的创新需要将这些隐喻建立在其基本的数学原理上。该项目通过让最终用户对人工智能背后的数学原理有一个基本的了解，从而超越了对“可解释人工智能”的研究，这构成了网络安全培训的一个关键进步。为了调查中学生与人工智能相关的网络安全能力与他们的数学知识和行为的关系，项目组将使用混合方法、探索性研究方法。学生网络安全知识的前后测试、行为意向调查、数学亲和力、在“网络安全演习”中观察到的决策，以及特定模块的测试分数将被用来评估该项目。该项目得到了安全和值得信赖的网络空间(SATC)计划的一项特别倡议的支持，该计划旨在促进网络安全、人工智能和教育领域之间新的、以前从未探索过的合作。SATC计划与联邦网络安全研究和发展战略计划和国家隐私研究战略保持一致，以保护和维护网络系统日益增长的社会和经济效益，同时确保安全和隐私。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Trust the Teachers! Conducting School-Based Research in a Rural Middle School When Building Relationships Face-to-Face Is Not Possible

相信老师！

• 发表时间: 2022
• 期刊: Curriculum and Teaching Dialogue
• 作者: Singh, K.;Sidnam-Mauch, E.;Iqbal, S.;Khan, S.;Nelson, P.;Derrick, K.;Caine, K.;Knijnenburg, B.;Bannister, N.
• 通讯作者: Bannister, N.

Using Mathematically-Grounded Metaphors to Teach AI-Related Cybersecurity

使用基于数学的隐喻来教授人工智能相关的网络安全

• 发表时间: 2021
• 期刊: Canada
• 作者: Knijnenburg, Bart P.;Bannister, Nicole;Caine, Kelly
• 通讯作者: Caine, Kelly