Yeyu Wang 王烨宇

I recently earned my Ph.D. in Educational Psychology, with a specialization in the Learning Sciences, at the University of Wisconsin-Madison, where I had the privilege of working with Professor David Williamson Shaffer. My research focuses on developing interpretable computational methods that bridge human expertise and learning analytics to better understand learning and collaboration. In August 2026, I will join the University of Michigan, Ann Arbor as a MIDAS Postdoctoral Fellow , where I will work with Professor Vitaliy Popov and Professor Xu Wang. My current research explores virtual reality simulations in medical education, combining learning sciences, human-centered AI, and multimodal learning analytics to study teamwork, decision making, and learning in complex clinical environments.

Briefly, my academic journey began with a bachelor's degree in Educational Technology from Beijing Normal University, where Professor Jingjing Zhang first introduced me to educational research. I then earned a master's degree in Educational Technology and Applied Learning Sciences at the Human-Computer Interaction Institute, Carnegie Mellon University, where I worked with Professor Bruce M. McLaren on learning games and learner agency. After graduation, I joined the University of Pennsylvania and worked with Professor Ryan Baker, where I deepened my experience in machine learning for education before pursuing my Ph.D. at UW-Madison. Looking ahead, I am excited to continue this journey at the University of Michigan, exploring how emerging technologies can help us better understand and improve learning in authentic, collaborative settings.

• CV

News

🌟 09/01/2026 I will join the University of Michigan, Ann Arbor as a Postdoctoral Fellow at The Michigan Institute for Data and AI in Society (MIDAS), working with Professor Vitaliy Popov and Professor Xu Wang.
🎓 06/14/2026 I deposited my Ph.D. dissertation at ProQuest.
🌟 06/12/2026 I participated in the week-long Morgridge Entrepreneurship Bootcamp, where I developed and pitched a startup idea for a "Couch-to-5K for Productivity" that combines a mobile app with coaching from psychology and counseling students to help users build sustainable focus habits.
🎓 05/20/2026 I successfully defended my Ph.D. dissertation, Qualitative Parameter Triangulation, at the Department of Educational Psychology, University of Wisconsin-Madison.

Selected Publications

Wang, Y., Carpenter, Z., Swiecki, Z., & Shaffer, D. W. (2025, March). Qualitative Parameter Triangulation: A Conceptual and Methodological Framework for Event-Based Temporal Models. In Proceedings of the 15th International Learning Analytics and Knowledge Conference (pp. 537-546). [PDF]
Wang, Y., Shah, M., Jimenez, F. A., Wilson, C., Ashiq, M., Eagan, B., & Williamson Shaffer, D. (2023, October). Developing nursing students’ practice readiness with shadow health® digital clinical experiences tm: A transmodal analysis. In International conference on quantitative ethnography (pp. 365-380). Cham: Springer Nature Switzerland. [PDF]
Shaffer, D. W., Wang, Y., & Ruis, A. (2025). Transmodal Analysis. Journal of Learning Analytics, 12(1), 271-292. [PDF]
Borchers, C., Wang, Y., Karumbaiah, S., Ashiq, M., Shaffer, D. W., & Aleven, V. (2024, March). Revealing networks: Understanding effective teacher practices in AI-supported classrooms using transmodal ordered network analysis. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 371-381). [PDF]
Wang, Y., Ruis. A. R., Shaffer, D., (2021). Modeling Collaborative Discourse with ENA using a Probabilistic Function. Accepted by International Conference on Quantitative Ethnography, Denmark. [PDF]
Wang, Y., Swiecki, Z., Ruis, A. R., & Shaffer, D. W. (2021, February). Simplification of Epistemic Networks Using Parsimonious Removal with Interpretive Alignment. In proceedings of International Conference on Quantitative Ethnography (pp. 137-151). Springer, Cham. [PDF]
Wang, Y., Kai, S., & Baker, R. S. (2020, July). Early Detection of Wheel-Spinning in ASSISTments. In proceedings of International Conference on Artificial Intelligence in Education (pp. 574-585). Springer, Cham. [PDF]
Wang, Y., Nguyen, H., Harpstead, E., Stamper, J., & McLaren, B. M. (2019, June). How Does Order of Gameplay Impact Learning and Enjoyment in a Digital Learning Game?. In proceedings of International Conference on Artificial Intelligence in Education (pp. 518-531). Springer, Cham. [PDF]