Publications & Resources
The Feasibility of Using Cluster Analysis to Examine Log Data From Educational Video Games
Deirdre Kerr, Gregory K. W. K. Chung, and Markus R. Iseli
Analyzing log data from educational video games has proven to be a challenging endeavor. In this paper, we examine the feasibility of using cluster analysis to extract information from the log files that is interpretable in both the context of the game and the context of the subject area. If cluster analysis can be used to identify patterns of thought as students play through the game, this method may be able to provide the information necessary to diagnose mathematical misconceptions or to provide targeted remediation or tailored instruction.
Kerr, D., Chung, G. K. W. K., & Iseli, M. R. (2011). The feasibility of using cluster analysis to examine log data from educational video games (CRESST Report 790). Los Angeles: University of California, Los Angeles, National Center for Research on Evaluation, Standards, and Student Testing (CRESST).