ICAT: An Adaptive Testing Procedure for the Identification of Idiosyncratic Knowledge Patterns

Abstract

Traditional adaptive tests provide an efficient method for estimating student achievements levels, by adjusting the characteristics of the test questions to match the performance of each student. These traditional adaptive tests are not designed to identify idiosyncratic knowledge patterns. As students move through their education, they learn content in any number of different ways related to their learning style and cognitive development. This may result in a student having different achievement levels from one content area to another within a domain of content. This study investigates whether such idiosyncratic knowledge patterns exist. It discusses the differences between idiosyncratic knowledge patterns and multidimensionality. Finally, it proposes an adaptive testing procedure that can be used to identify a student’s areas of strength and weakness more efficiently than current adaptive testing approaches. The findings of the study indicate that a fairly large number of students may have test results that are influenced by their idiosyncratic knowledge patterns. The findings suggest that these patterns persist across time for a large number of students, and that the differences in student performance between content areas within a subject domain are large enough to allow them to be useful in instruction. Given the existence of idiosyncratic patterns of knowledge, the proposed testing procedure may enable us to provide more useful information to teachers. It should also allow us to differentiate between idiosyncratic patterns or knowledge, and important mutidimensionality in the testing data.