Hello, my academic friends!

I am a fifth-year PhD student in Epistemic Analytics Lab at University of Wisconsin-Madison. I am working with Professor David Williamson Shaffer. My research focus on developing methodologies in learning analytics and quantitative ethnography to better represent, understand, and diagnose learning processes. My two major projects include: (1) Trans-Modal analysis, a conceptual and methodological framework to address data fusion issue in multimodal learning analytics, (2) Qualitative Parameter Triangulation, a principled approach to translate qualitative heuristics into quantitative representation for high fidelity learning analytics models. (I am currently preparing my dissertation proposal, which is 78.23% enjoyment and 21.77% suffering. )

Brief intro about my trajectory:
For my bachelor degree, I studied educational technology in Beijing Normal University, China. Professor Jingjing Zhang kindly introduced me to the world of research. Then, I obtained a Master of Educational Technology and Applied Learning Sciences at Human-Computer Interaction Institute, Carnegie Mellon University. I took various human-computer interaction courses, and worked with Professor Bruce M. McLaren to explore how agency plays a role in learning games. After graduating from CMU, I worked with Professor Ryan Baker at the University of Pennsylvania. I mastered machine learning techniques used in educational domains and was determined to pursue a PhD degree in education. In 2019, I was admitted to a PhD program in Department of Educational Psychology, at University of Wisconsin-Madison. I am fortunate to work with Professor David Williamson Shaffer and went on an adventure of research in Quantitative Ethnography.

Selected Publications

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]