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的更多方面以及关键基础设施。因此，理解这些概念及其与网络安全的关系对所有学生和国家的劳动力都变得越来越重要。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，特别是在青少年早期，当个人发展职业抱负和兴趣时。 这在个人和国家层面都是有益的，因为它有助于国家未来STEM劳动力和公民的发展。目前的K-12网络安全教育主要是通过课堂上的“数字扫盲”活动或校外活动来完成的，几乎没有真正的编程 年轻学习者的元素。此外，AI/ML并没有出现在这些课程中，尽管K-12学校的AI工作正在单独获得关注。这个基于案例和游戏的学习（CAPABLE）模块的网络安全和人工智能教育项目将解决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。该项目将开发一个真实的，引人入胜的学习体验，将向8-10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。拟议的努力将在课程和教学领域进行创新，以系统地整合网络安全，人工智能和ML的思想。这些主题通常是单独教授的（如果有的话），并且在这些关键的计算机科学（CS）主题中提供综合的学习体验将使青少年早期的学习者能够获得能力。该项目将涉及40小时学习模块的开发和实证调查-青少年人工智能网络安全（ACT）-以激励和吸引13-15岁的学生。ACT模块将用于网络安全营地和/或作为学校教室中CS和/或AI课程的扩展。课程和教学方法将利用协作棋盘或纸牌游戏，引导学生了解网络安全概念。它还将包括与网络安全问题（如网络欺诈，网络欺凌，黑客攻击，网络钓鱼）相关的真实，真实世界的“案例”的创新集合，青少年可以识别。这些将与NetsBlox编程环境中的相关变革性编程练习以及涉及AI/ML的练习相结合，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。项目团队还将设计一个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。该项目得到安全和可信网络空间（SaTC）计划的特别倡议的支持，以促进网络安全，人工智能和教育领域之间新的，以前未探索的合作。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知识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

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
• 期刊: 54th ACM Technical Symposium on Computer Science Education
• 作者: Grover, Shuchi;Broll, Brian;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
• 期刊: The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23
• 作者: Broll, Brian;Grover, Shuchi
• 通讯作者: Grover, Shuchi

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
• 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