Proficiency Scaling Based on Conditional Probability Functions for Attributes
Final rept. Apr 89-Aug 93,
EDUCATIONAL TESTING SERVICE PRINCETON NJ
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This study introduces procedures for constructing a proficiency scale for a large-scale test by applying Tatsuokas Rule Space Model. The SAT mathematics SAT M, Section II, is used for illustrating the process and the results. A task analysis is summarized in a mapping sentence, and then 14 processess and content attributes are identified for explaining the underlying cognitive aspects of the examinees performance on the SAT M. Analysis results show that almost 98 of 2,334 examinees are successfully classified into one of 468 cognitive states. The cognitive states are characterized by mastery or non- mastery of the 14 attributes. Attribute Characteristic Curves, which are conditional probability functions defined on the SAT Scale, are introduced and used for interpreting an examinees proficiency. Prototypes of a students performance report and a group performance report are given as examples of possible ways for summarizing the analysis results.
- Statistics and Probability