Li Xu

Professor, Applied Computing & Computer Science
2023 CUES Distinguished Fellow
Photo of 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.

2023 CUES Distinguished Fellows