Abstract
This article discusses an approach to analyzing performance assessments that identifies potential reasons for misfitting items and uses this information to improve on items and rubrics for these assessments. Specifically, the approach involves identifying psychometric features and qualitative features of items and rubrics that may possibly influence misfit; examining relations between these features and the fit statistic; conducting an analysis of student responses to a sample of misfitting items; and finally, based on the results of the previous analyses, modifying characteristics of the items or rubrics and reexamining fit. A mathematics performance assessment containing 53 constructed-response items scored on a holistic scale from 0 to 4 is used to illustrate the approach. The 2-parameter graded response model (Samejima, 1969) is used to calibrate the data. Implications of this method of data analysis for improving performance assessment items and rubrics are discussed as well as issues and limitations related to the use of the approach.
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