Concept categorization analysis: verbal and written data sources*
Dyan McBride and Dean A. Zollman
Department of Physics, Kansas State University
Our current project, which focuses on how students construct an understanding of wavefront aberrometry, has produced a significant amount of both verbal data from interviews and written data from student worksheets. Using concept categorization techniques, we present an analysis of both types of data; in particular, we focus on comparing the two data types for use with concept categorization analysis and present both advantages and disadvantages of this method for each type of data.
*Supported by National Science Foundation grant DUE 04-27645
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