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ERIC Number: ED520531
Record Type: Non-Journal
Publication Date: 2011-Apr
Pages: 62
Abstractor: As Provided
Reference Count: 15
ISBN: N/A
ISSN: N/A
The Feasibility of Using Cluster Analysis to Examine Log Data from Educational Video Games. CRESST Report 790
Kerr, Deirdre; Chung, Gregory K. W. K.; Iseli, Markus R.
National Center for Research on Evaluation, Standards, and Student Testing (CRESST)
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. Appendices include: (1) Cluster Analysis Basics; (2) Extracted Clusters by Level; (3) SPSS Syntax; (4) R Code; and (5) Percentage of Attempts in Each Cluster. (Contains 9 figures and 18 tables.)
National Center for Research on Evaluation, Standards, and Student Testing (CRESST). 300 Charles E Young Drive N, GSE&IS Building 3rd Floor, Mailbox 951522, Los Angeles, CA 90095-1522. Tel: 310-206-1532; Fax: 310-825-3883; Web site: http://www.cresst.org
Publication Type: Numerical/Quantitative Data; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: National Center for Research on Evaluation, Standards, and Student Testing