Rosie Le Xiu

Rosie Le Xiu (she/her/hers) is a Ph.D. student in Educational Psychology at the University of Southern California (USC) Rossier School of Education, where she serves as a research assistant at the Center for Generative AI & Society under the guidance of Dr. Stephen Aguilar and Dr. Erika Patall. She is concurrently pursuing a Graduate Certificate in Applied Data Science at the USC Viterbi School of Engineering. She also teaches graduate coursework on AI and learning technologies in USC Rossier's Master of Education in Learning Design and Technology (MLDT) program.

Her research centers on international comparisons of how K-12 teachers understand, adopt, and reason about generative AI in their classrooms. She has led statistical analyses of large-scale teacher surveys and has co-authored peer-reviewed publications and policy reports on AI in education. Her broader interests include AI literacy development, learning analytics, bilingual learners, and digital equity. Building on her training in applied data science, she aims to extend this work into educational data science, using computational and data-intensive methods to study teaching and learning at scale.

Xiu received her M.A. in Human Development and Psychology from the University of California, Los Angeles (UCLA), where she completed a mixed-methods thesis on bilingual students' approaches to learning in online mathematics classrooms, and her B.A. in Creative Writing and Education from the University of Washington. Before her doctoral studies, she taught competition mathematics to upper-elementary students, an experience that grounds her research in teachers' perspectives and continues to inform her interest in connecting research with classroom practice.

Internal Research Funds Grant, USC Rossier School of Education (2025–2026)

• Xiu, R. L., Aguilar, S. J., Macías, A. J., Xing, Y., Al-Sulaiti, R., Junjunia, M., & Jebril, S. T. (2026). An Exploratory Cross-National Study of K–12 Teachers’ Generative AI Literacy and Classroom Enactment. Education Sciences, 16(5), 811. https://doi.org/10.3390/educsci16050811
• Aguilar, S., Xiu, R. L., Junjunia, M., Al-Sulaiti, R., & Talha-Jebril, S. (2025). PERCEPTIONS AND PATHWAYS TO AI INTEGRATION. https://www.wise-qatar.org/app/uploads/2025/11/wise-x-usc-perceptions-and-pathways-final.pdf 
• Aguilar, S. J., Nye, B., Swartout, W., Macias, A., Xing, Y., & Xiu, R. L. (2025, August 21). How Students and Teachers Worldwide Are Adapting to AI. https://doi.org/10.35542/osf.io/wr6n3_v1
• Xiu, L. (2025, March). Analyses of Online Learning Behaviour Based on Linear Regression Algorithm. In 2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE) (pp. 1333-1338). IEEE.
• Xiu, L. (2024). The Challenges and Approaches of Generative Artificial Intelligence (GenAI) to promote Educational Innovation. International Journal of Computer Science and Information Technology, 4(3), 400-407. https://doi.org/10.62051/ijcsit.v4n3.45