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Kerr, Deirdre; Chung, Gregory K. W. K. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
Student mathematical errors are rarely random and often occur because students are applying procedures that they believe to be accurate. Traditional approaches often view such errors as indicators of students' failure to understand the construct in question, but some theorists view errors as opportunities for students to expand their mental model…
Descriptors: Educational Games, Video Games, Mathematics, Misconceptions
Kerr, Deirdre – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2014
Educational video games provide an opportunity for students to interact with and explore complex representations of academic content and allow for the examination of problem-solving strategies and mistakes that can be difficult to capture in more traditional environments. However, data from such games are notoriously difficult to analyze. This…
Descriptors: Identification, Misconceptions, Scoring Rubrics, Educational Games
Kerr, Deirdre; Chung, Gregory K. W. K.; Iseli, Markus R. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2011
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…
Descriptors: Video Games, Multivariate Analysis, Data Analysis, Context Effect