My research is to support more people learn in effective ways. I draw techniques and theories from Human-Computer Interaction, Learning Sciences, and Artificial Intelligence to develop computational methods and systems to support scalable teaching and learning. There are several directions in my research that draw on data science techniques and also contribute to interdisciplinary data science research, 1) data-driven authoring techniques of intelligent tutoring systems, with application domains in UX education and data science education 2) AI-augmented instructional design and the use Human-AI collaborative techniques in instructional design.
Xu Wang
Assistant Professor, Computer Science and Engineering
AI in Education, Data Science Education, Human-Computer Interaction, learning at scale
