Collaborative Research: Towards Engaged, Personalized and Transferable Learning of Secure Programming by Leveraging Real-World Security Vulnerabilities

Virginia Commonwealth University, Richmond VA

Investigators

Abstract

This project aims to serve the national interest by building personalized secure programming projects motivated by real world security vulnerabilities. A number of educators have introduced concepts in secure programming into a series of introductory computer science courses. Students, however, still have difficulty in applying knowledge to new programming tasks in real world scenarios. Students may either have low intrinsic motivations or have few practical examples so that there is limited transfer of skills and competencies across tasks. The proposed project intends to provide additional opportunities for continued learning and real-world applications of secure programming. The project has the potential to prepare a capable workforce with strong secure programming skills. The project would potentially contribute to a competent workforce to safeguard the nation's information technology infrastructure. The project team plans to conduct three activities: 1) mapping between secure programming topics in the curriculum and categories of real-world vulnerabilities, 2) building easy-to-use learning projects from selected real-world vulnerabilities, and 3) developing a personalized project delivery mechanism based on different task contexts. The proposed work intends to establish a learner-centered competency-based model for secure programming and to build a supporting community of learners, educators, and researchers. The project results will be disseminated on the project website, and through computing related conferences, open-source repositories, and mailing lists. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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.