Exploring Problem-Solving Behavior in an Optics Game

Understanding player behavior in complex problem solving tasks is important for both assessing learning and for the design of content. Previous research has modeled studenttutor interactions as a complex network; researchers were able to use these networks to provide visualizations and automatically generated feedback. We collected data from 195 high school students playing an optics puzzle game, Quantum Spectre, and modeled their game play as an interaction network. We found that the networks were useful for visualization of student behavior, identifying areas of student misconceptions, and locating regions of the network where students become stuck.