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Xiao Hu

Associate Professor, Information Science
2026 CUES Distinguished Fellow
Headshot of Xiao Hu

Note: Titles and affiliations appear as they were at time of award.


Illuminating Student Writing in the Age of Generative AI

For many reasons, honing students’ academic writing remains an essential and valuable aspect of university education. The surge of generative artificial intelligence (AI), however, has fundamentally changed how students write, creating both challenges and opportunities for improving students’ writing and understanding its value. Grounded in self-regulated learning theory, this project aims to use learning analytics—an approach to measuring, collecting, and analyzing learning data—to 1) help students regulate their writing process more effectively, thereby ensuring meaningful learning rather than mere text production, and 2) empower instructors to guide ethical AI integration while providing timely feedback and upholding academic standards. This project supports the CUES mission by advancing research and evidence-based practice in AI-integrated writing education, enabling broader adoption across disciplines, and informing institutional policy frameworks.

2026 CUES Distinguished Fellows