EAGER: SaTC-EDU: A Case- and Play-Based Learning Module for Cybersecurity and Artificial Intelligence Education for Early Teen Learners

EAGER：SaTC-EDU：针对早期青少年学习者的网络安全和人工智能教育的基于案例和游戏的学习模块

• 批准号: 2113803
• 负责人: Shuchi Grover
• 金额: $ 30万
• 依托单位: Looking Glass Ventures, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-15 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2113803&HistoricalAwards=false
• 关键词: EAGER; SaTC; EDU; Case; Play

Artificial intelligence (AI) and machine learning (ML) are expanding into more aspects of our daily lives as well as key infrastructure. As a result, understanding these concepts and their relationship with cybersecurity is becoming increasingly important both for all students and the nation’s workforce. Providing engaging learning experiences for K-12 learners around cybersecurity and AI education is critical, especially during the early teen years when individuals are developing career aspirations and interests. This is beneficial at the level of both individuals and the nation, as it contributes to the development of the nation’s future STEM workforce and citizenry. Current K-12 cybersecurity education is largely accomplished through ‘digital literacy’ activities in classrooms or out-of-school initiatives with few authentic programming elements for younger learners. Moreover, AI/ML do not feature in these curricula even though AI efforts in K-12 schools are separately garnering attention. This case- and play-based learning (CAPABLE) module for cybersecurity and AI education project will address this gap in cybersecurity and AI/ML education for K-12 learners. The project will develop an authentic, engaging learning experience that will introduce students in grades 8-10 to the fundamentals of cybersecurity and its interplay with AI. The proposed effort will innovate in the areas of curriculum and pedagogy to systematically integrate ideas from cybersecurity, AI, and ML. These topics are typically taught separately, if at all, and providing integrated learning experiences in these critical computer science (CS) topics will empower learners in their early teen years. The project will involve development and empirical investigation of a 40-hour learning module—AI & Cybersecurity for Teens (ACT)—to motivate and engage students aged 13-15. The ACT module will be made available for use in cybersecurity camps and/or as an extension to CS and/or AI curricula in school classrooms. The curriculum and pedagogy will utilize collaborative board or card games to orient students to cybersecurity concepts. It will also include an innovative collection of authentic, real-world ‘cases’ related to cybersecurity issues (such as cyberfraud, cyberbullying, hacking, phishing) with which young teens can identify. These will be paired with related, transformative programming exercises in the NetsBlox programming environment and involving AI/ML, which will help build student understanding of ML models and AI/ML techniques including text classification, neural networks and generative adversarial networks. The project team will also design a Cybersecurity Scenario-Based Assessment to assess understanding of cybersecurity and AI/ML concepts.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.

人工智能 (AI) 和机器学习 (ML) 正在扩展到我们日常生活以及关键基础设施的更多方面，因此，了解这些概念及其与网络安全的关系对于所有学生和国家劳动力来说变得越来越重要。为 K-12 学习者提供有关网络安全和人工智能教育的引人入胜的学习体验至关重要，尤其是在个人发展职业抱负和兴趣的青少年时期，这对个人和国家都是有益的，因为它有助于促进发展。民族的未来发展目前的 K-12 网络安全教育主要是通过课堂上的“数字素养”活动或校外活动来完成，很少有针对年轻学习者的真实编程元素，而且，人工智能/机器学习甚至没有出现在这些课程中。尽管 K-12 学校的人工智能工作正在单独引起关注，但这个用于网络安全和人工智能教育项目的基于案例和游戏的学习（CAPABLE）模块将解决 K-12 学习者在网络安全和人工智能/机器学习教育方面的这一差距。将开发出一种真实的、引人入胜的向 8 至 10 年级的学生介绍网络安全的基础知识及其与人工智能的相互作用。拟议的工作将在课程和教学法领域进行创新，以系统地整合网络安全、人工智能和机器学习的思想。单独授课（如果有的话），并提供这些关键计算机科学 (CS) 主题的综合学习经验，将为青少年时期的学习者提供帮助。该项目将涉及 40 小时学习模块——人工智能和网络安全的开发和实证研究。青少年(ACT)——激励和吸引 13-15 岁的学生。ACT 模块将用于网络安全训练营和/或作为学校课堂中计算机科学和/或人工智能课程的延伸。课程和教学法将采用协作方式。它还将包括与网络安全问题（例如网络欺诈、网络欺凌、黑客攻击、网络钓鱼）相关的真实、真实“案例”的创新集合，青少年可以通过棋盘或纸牌游戏引导学生了解网络安全概念。这些将与 NetsBlox 编程环境中涉及 AI/ML 的相关变革性编程练习相结合，这将有助于学生理解 ML 模型和 AI/ML 技术，包括文本分类、神经网络和生成对抗网络。团队还将设计基于网络安全场景的评估，以评估对网络安全和人工智能/机器学习概念的理解。该项目得到安全可信网络空间 (SaTC) 计划特别倡议的支持，旨在培育新的、以前未探索过的、 SaTC 计划与联邦网络安全研究与发展战略计划和国家隐私研究战略相一致，旨在保护和维护网络系统不断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价值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

Beyond Black-Boxing: Building Intuitions of Complex Machine Learning Ideas Through Interactives and Levels of Abstraction

超越黑盒：通过交互和抽象层次建立复杂机器学习思想的直觉

• DOI: 10.1145/3501709.3544273
• 发表时间: 2022-08
• 期刊: The 2022 ACM Conference on International Computing Education Research V.2 (ICER ’22
• 作者: Broll, Brian;Grover, Shuchi;Babb, Derek
• 通讯作者: Babb, Derek

Beyond black-boxes: teaching complex machine learning ideas through scaffolded interactive activities

超越黑盒：通过支架式互动活动教授复杂的机器学习思想

• 发表时间: 2023-01
• 期刊: The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23
• 作者: Broll, Brian;Grover, Shuchi
• 通讯作者: Grover, Shuchi

Cybersecurity Education in the Age of AI: Integrating AI Learning into Cybersecurity High School Curricula

人工智能时代的网络安全教育：将人工智能学习融入网络安全高中课程

• DOI: 10.1145/3545945.3569750
• 发表时间: 2023-03
• 期刊: 54th ACM Technical Symposium on Computer Science Education
• 作者: Grover, Shuchi;Broll, Brian;Babb, Derek
• 通讯作者: Babb, Derek