Li Xu
Note: Title was current at time of award and may have changed.
Using cybersecurity data sets to enhance course design and online student learning
This project aims to explore, refine and assess best practices for engaging online students in learning Computational Thinking (CT) and Statistical Thinking (ST). The project is grounded on a design that leverages domain-specific rather than discipline agnostic data contexts. Aiming to fill a knowledge gap and contribute to a still small body of empirical studies on teaching interventions using cybersecurity data, this study investigates: (1) which cybersecurity data sets are relevant and effective for engaging students in learning CT and ST; and (2) how the use of cybersecurity data impacts the development of students’ knowledge, skills, self-efficacy, and learning engagement in CT and ST. Ultimately, project findings will aim to inform the design of more effective and engaging methods for teaching and learning data thinking in cybersecurity.
Publications
Xu, L. (Accepted/Forthcoming). Trends in US healthcare data breaches (Paper Presentation). IEEE International Conference on AI and Data Analytics (ICAD 2025), Tufts University, Medford, MA.
Xu, L. (2025). Designing Assignments in an Online CURE to Advance Data Thinking and AI Literacy in Healthcare Breaches. In R. Jake Cohen (Ed.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 1017-1022). Orlando, FL, USA: Association for the Advancement of Computing in Education (AACE).
Presentations
JUN 2025: Trends in US Healthcare Data Breaches, IEEE International Conference on AI and Data Analytics (ICAD 2025), Tufts University School of Engineering, Medford, MA.
MAR 2025: Designing Assignments in an Online CURE to Advance Data Thinking and AI Literacy in Healthcare Breaches, 36th International Conference of the Society for Information Technology and Teacher Education (SITE), University of Central Florida’s Rosen College of Hospitality Management, Orlando, FL.