CyberTraining: Implementation: Small: Using Problem-Based Learning for Vocational Training in Cyberinfrastructure Security at Community Colleges

网络培训：实施：小型：使用基于问题的学习进行社区大学网络基础设施安全的职业培训

• 批准号: 2017337
• 负责人: Irfan Ahmed
• 金额: $ 25万
• 依托单位: Virginia Commonwealth 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: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2017337&HistoricalAwards=false
• 关键词: CyberTraining; Implementation; Small; Using; Problem

Professionals in the cybersecurity field are in high demand. Many sectors, including the research, military, civil law enforcement, corporate, and private sector communities, all benefit from a larger, highly skilled cybersecurity workforce, particularly considering the increasing number and sophistication of cyber attacks. Challenges for academia include producing diverse and high quality professionals, and unfortunately, the demand for cybersecurity professionals far exceeds the supply of students. Community colleges can play a crucial role in meeting the demand for cybersecurity professionals. This project uses problem based learning, an innovative approach to teaching cybersecurity, to bring community college students into the high rewarding cybersecurity field. The educational methods and products developed through the project will be broadly applicable, beyond community colleges, and will contribute to a better trained and more diverse cybersecurity and research workforce. Ultimately, the project will contribute to the health, safety, and economic well being of society by protecting the nation's cyberinfrastructure.The overall goal of the project is to provide vocational training in cyberinfrastructure security to community college students, to address the shortage of technical staff in cybersecurity. Community colleges have a significant student population of low income, diverse, first generation college students that have the potential for enabling a new stream of cybersecurity professionals. These colleges, however, face significant challenges to teaching advanced cybersecurity skills for cyberinfrastructure. To address these challenges, the project will develop vocational training modules on cyberinfrastructure security. Each module will consist of multiple micro-modules and target the skill sets required for entry level jobs in the cybersecurity field. Specifically, the approach involves three major tasks. The first task involves creating training modules on several offensive/defensive topics on cyberinfrastructure, including network penetration testing and digital forensics. The contents of the modules support problem based learning with a strong hands on components. The second task involves developing CRICE (Cyber Range Infrastructure for Cybersecurity Education) on NSFCloud to support problem based learning. NSFCloud is an NSF funded public cloud service available for research and training purposes. This will help community colleges to utilize the training modules effectively without requiring their own expensive computing infrastructure. The third task involves integrating the modules into the curriculum of two community colleges and evaluating the effectiveness of the problem based learning and CRICE in terms of cost, ease of adoption, student learning gain, and attitudinal survey on the students' experience. The project research contribution lies in exploring the effectiveness of problem based learning for vocational training in cybersecurity in the context of community colleges in the United States. The project will show that problem based learning is effective in providing both conceptual and practical understanding of cybersecurity topics. This project is funded by the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering. The Advanced Technological Education (ATE) program in NSF's Division of Undergraduate Education is providing co-funding for this project in recognition of its contribution to education in community colleges.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.

网络安全领域的专业人士需求很高。许多部门，包括研究，军事，民事执法，公司和私营部门社区，都受益于更大，高技能的网络安全劳动力，尤其是考虑到网络攻击的数量和复杂性。学术界的挑战包括生产多样化和高质量的专业人士，不幸的是，对网络安全专业人员的需求远远超过了学生的供应。社区大学可以在满足网络安全专业人员的需求中发挥关键作用。该项目使用基于问题的学习，一种创新的网络安全方法，将社区大学生带入高度奖励的网络安全领域。通过该项目开发的教育方法和产品将在社区大学之外广泛适用，并将为训练有素的网络安全和研究人员提供帮助。最终，该项目将通过保护国家网络基础设施来为社会的健康，安全和经济福祉做出贡献。该项目的总体目标是为社区大学生提供网络基础设施安全方面的职业培训，以解决网络安全技术人员的短缺。社区学院拥有低收入，多样化的第一代大学生的大量学生人口，他们有可能使新的网络安全专业人员流。但是，这些大学在教授网络基础设施的高级网络安全技能方面面临重大挑战。为了应对这些挑战，该项目将开发有关网络基础设施安全的职业培训模块。每个模块将由多个微型模块组成，并针对网络安全领域入门级作业所需的技能集。具体而言，该方法涉及三个主要任务。第一个任务涉及在网络基础设施的几个进攻/防守主题上创建训练模块，包括网络渗透测试和数字取证。模块的内容支持基于问题的学习，并强大的组成部分。第二个任务涉及在NSFCloud开发CRICE（网络安全教育的网络范围基础架构），以支持基于问题的学习。 NSFCloud是一项用于研究和培训目的的NSF​​资助的公共云服务。这将有助于社区大学有效地利用培训模块，而无需他们自己昂贵的计算基础架构。第三个任务涉及将模块集成到两所社区大学的课程中，并在成本，易于收养，学生学习收益以及对学生经验的态度调查方面评估基于问题的学习和CRICE的有效性。项目研究的贡献在于探索在美国社区大学的背景下，基于问题的学习对网络安全方面的职业培训的有效性。该项目将表明，基于问题的学习在提供网络安全主题的概念和实际理解方面有效。该项目由计算机和信息科学与工程局的高级网络基础设施办公室资助。 NSF本科教育部门的高级技术教育计划（ATE）计划正在为该项目提供共同的资金，以表彰其对社区大学教育的贡献。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来通过评估来支持的。

项目成果

Automated Waterloo Rubric for Concept Map Grading

用于概念图分级的自动滑铁卢评分标准

• DOI: 10.1109/access.2021.3124672
• 发表时间: 2021
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Bhatia, Shresht;Bhatia, Sajal;Ahmed, Irfan
• 通讯作者: Ahmed, Irfan

Cronus: An Automated Feedback Tool for Concept Maps

Cronus：概念图自动反馈工具

• DOI: 10.1109/access.2021.3106509
• 发表时间: 2021
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Dahir, Masrik A.;Qasim, Syed Ali;Ahmed, Irfan
• 通讯作者: Ahmed, Irfan