Stratified Item Selection Methods in Cognitive Diagnosis Computerized Adaptive Testing.

ABSTRACT: Cognitive diagnostic computerized adaptive testing (CD-CAT) aims to obtain more useful diagnostic information by taking advantages of computerized adaptive testing (CAT). Cognitive diagnosis models (CDMs) have been developed to classify examinees into the correct proficiency classes so as to get more efficient remediation, whereas CAT tailors optimal items to the examinee's mastery profile. The item selection method is the key factor of the CD-CAT procedure. In recent years, a large number of parametric/nonparametric item selection methods have been proposed. In this article, the authors proposed a series of stratified item selection methods in CD-CAT, which are combined with posterior-weighted Kullback-Leibler (PWKL), nonparametric item selection (NPS), and weighted nonparametric item sel

SUBMITTER: Yang J 

PROVIDER: S-EPMC7433381 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature