Research has found that the "a"-stratified item selection strategy (STR) for computerized adaptive tests (CATs) may lead to insufficient use of high a items at later stages of the tests and thus to reduced measurement precision. A refined approach, unequal item selection across strata (USTR), effectively improves test precision over the…

Variable-length computerized adaptive testing (CAT) can provide examinees with tailored test lengths. With the fixed standard error of measurement ("SEM") termination rule, variable-length CAT can achieve predetermined measurement precision by using relatively shorter tests compared to fixed-length CAT. To explore the application of…

This article investigates several questions regarding the impact of different item formats on measurement characteristics. Constructed response (CR) items and multiple choice (MC) items obviously differ in their formats and in the resources needed to score them. As such, they have been the subject of considerable discussion regarding the impact of…

On a general level, the objective of diagnostic classifications models (DCMs) lies in a classification of individuals regarding multiple latent skills. In this article, the authors show that this objective can be achieved by multidimensional adaptive testing (MAT) as well. The authors discuss whether or not the restricted applicability of DCMs can…