San Antonio, TX
March 2–6, 2015
Conference Website
APS annual meetings are attended by thousands of physicists, scientists, and journalists from around the world. They offer valuable opportunities for presenting research, sharing insights, and networking, as well as related workshops and activities for scientific discussion, professional development, improving education, and science advocacy.
Wednesday, March 4
Tracking student progress in a game-like physics learning environment with a Monte Carlo Bayesian knowledge tracing model
Gey-Hong Gweon (University of California-Santa Cruz), Hee-Sun Lee (University of California-Santa Cruz), Chad Dorsey, Robert Tinker, William Finzer & Daniel Damelin
3:06 PM–3:18 PM, Room 208
In tracking student learning in online learning systems, the Bayesian knowledge tracing (BKT) model is a popular model. However, the model has well-known problems such as the identifiability problem or the empirical degeneracy problem. Understanding of these problems remain unclear and solutions to them remain subjective. Here, we analyze the log data from an online physics learning program with our new model, a Monte Carlo BKT model. With our new approach, we are able to perform a completely unbiased analysis, which can then be used for classifying student learning patterns and performances. Furthermore, a theoretical analysis of the BKT model and our computational work shed new light on the nature of the aforementioned problems.