Biography
Doy Kim is a Quantitative Learning Scientist who came from mathematics education. He studies the cognitive science of how students come to understand mathematics, how instruction can be built from that understanding, and how to tell whether it actually worked. He has been pursuing those three questions in every role he has held, beginning as an undergraduate.
As an educational content researcher at the Korea Educational Broadcasting System, he wrote evidence-based instruction plans for mathematics video and animation programming. As general manager of a center for in-service teacher education, he built professional development programs reaching more than 7,000 teachers. During his master’s at Seoul National University, he designed and ran a study of how digital environments shape elementary students’ understanding of mathematical concepts.
Now an Arvil S. Barr Fellow and Ph.D. candidate in the Learning Sciences area of the Department of Educational Psychology at UW–Madison, he brings the same questions to technologies for mathematics learning. His dissertation examines geometric reasoning in virtual reality. At the Wisconsin Center for Education Research he studies the same problems through action-based technologies, from motion-capture games to interactive whiteboards. As a Quantitative Methods Intern at WestEd’s Center for Teaching and Learning, he worked on large-scale school evaluations of mathematics programs and technologies.
As an educator and mentor, Doy has taught EDPSYCH 301: How People Learn as instructor of record, and he is a founder and a proud leader of a research team of eight graduate and undergraduate researchers.
Education
Ph.D. candidate, Educational Psychology – Learning Sciences, University of Wisconsin–Madison.
- Minor: Quantitative Educational Research.
- Advisor: Mitchell J. Nathan.
M.Sc., Educational Psychology – Learning Sciences, University of Wisconsin–Madison, 2022.
M.Sc., Mathematics Education, Seoul National University, 2019.
B.Sc., Mathematics Education, Seoul National University, 2016.
Research Interests
Doy studies what makes a learning technology work for mathematics: which features of a tool change how learners reason, for whom, and through what process. He is drawn in particular to geometry and mathematical proof, to the role of physical action and gesture in abstract reasoning, and to virtual and extended reality (VR/XR) as a setting where action can be designed rather than only observed.
His dissertation approaches these questions from two directions. GRAID (Geometric Reasoning Analysis through Integrated Datasets) synthesizes a series of independent experiments to model how physical actions and gestures relate to valid geometric reasoning. iGRASP (Immersive Geometric Reasoning through Action and Spatial Performance) is a randomized experiment developed in partnership with Curio, a virtual reality learning app for geometry. It asks whether the conceptual fit of an action matters apart from how much physical effort it demands.
Methodologically he pairs close qualitative analysis of gesture, speech, and classroom video with systemic quantitative measurement, modeling, and causal inference. Across all of it, he designs measures for student reasoning that conventional instruments do not capture.