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…

This chapter addresses the psychometric challenges in assessing English language learners (ELLs) and students with disabilities (SWDs). The first section addresses some general considerations in the assessment of ELLs and SWDs, including the prevalence of ELLs and SWDs in the student population, federal and state legislation that requires the…

Cognitive ability tests are widely used in organizations around the world because they have high predictive validity in selection contexts. Although these tests typically measure several subdomains, testing is usually carried out for a single subdomain at a time. This can be ineffective when the subdomains assessed are highly correlated. This…

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…

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…