Combining Cognitive Diagnostic Computerized Adaptive Testing With Multidimensional Item Response Theory

Abstract

The new generation of tests not only focuses on the general ability but also the process of finer-grained skills. Under the guidance of this thought, researchers have developed a dual-purpose CD-CAT (Dual-CAT). In the existing Dual-CAT, the models used in overall ability estimation are unidimensional IRT models, which cannot apply to the multidimensional tests. This article intends to develop a multidimensional Dual-CAT to improve its applicability. To achieve this goal, this article firstly proposes some item selection methods for the multidimensional Dual-CAT, and then verifies the estimation accuracy and exposure rate of these methods through both simulation study and a real item bank study. The results show that the established multidimensional Dual-CAT is effective and the new proposed methods outperform the traditional methods. Finally, this article discusses the future direction of the Dual-CAT.