Collaborative Research: CER: From Classroom to Career Readiness: Enhancing Undergraduate Computing Education Through Collaborative Research Experience in AI Security and Privacy
- Institution
- Rider University, NJ
- Principal investigator
- Zhengping J Luo
- Funding
- $218K
- Duration
- 2026–2029
Moonbase score
Still being scored
Abstract
Artificial Intelligence (AI) technologies are transforming daily life, but their rapid adoption has also introduced serious security and privacy challenges. Addressing these risks requires a workforce that can both advance AI innovation and safeguard its deployment. This project will help meet that need by strengthening undergraduate computing education through a curriculum-based research experience program that connects classroom learning with real world research experiences. The effort will integrate the latest AI security and privacy topics into existing computing courses while helping students build professional skills such as communication, teamwork, and leadership. By creating flexible learning modules that can be used across a range of undergraduate computing courses and institutions, the project will support workforce development and contribute to the secure, reliable, and responsible use of AI in society. The project will establish a curriculum-based undergraduate research experience program focused on AI security and privacy across partner institutions. The research team will design, implement, and evaluate flexible educational modules including labs, tutorials, assignments, and research activities in computer vision, speech and audio, and network systems. These modules will address vulnerabilities across the AI lifecycle and will be designed for seamless integration into undergraduate computing courses. The instructional materials will also be aligned with the NICE (National Initiative for Cybersecurity Education) Cybersecurity Workforce Framework to strengthen career-relevant competencies. In parallel, the research team will study educational approaches that embed research into coursework, including project-based and competition-based learning, and evaluate their effects on student engagement, success, technical growth, and professional skill development. The project will generate transferable resources and evidence-based practices that can be adopted more broadly in computing education and shared with academic and community audiences. 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.
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