A Simulation Study to Compare CAT Strategies for Cognitive Diagnosis
Xueli Xu, Hua‐Hua Chang · 2003
This paper demonstrates the performance of two possible CAT selection strategies for cognitive diagnosis. One is based on Shannon entropy and the other is based on Kullback-Leibler information. The performances of these two test construction methods are compared with random item selection. The cognitive diagnosis model used in this study is a simplified version of the Fusion model. Item banks are constructed for the purpose of simulation. The major result is that the Shannon entropy procedure outperforms the procedure based on Kullback-Leibler information in terms of correct classification rates. However, Kullback-Leibler has slightly smaller item exposure rates than the Shannon entropy procedure. This study shows that the Shannon entropy procedure is a promising CAT criterion, but modification might be required to control the exposure rate.