Bayesian Computerized Adaptive Testing Page 1 Bayesian Computerized Adaptive Testing
Bernard P. Veldkamp* Mariagiulia Matteucci** Abstract Computerized adaptive testing (CAT) …

Background: Item response theory (IRT; Lord & Novick, 1968) is a psychometric framework
that can be used to model the likelihood that an individual will respond correctly to an item …

Item response theory parameters have to be estimated, and because of the estimation
process, they do have uncertainty in them. In most large-scale testing programs, the …

In an expert knowledge elicitation exercise, experts face a carefully constructed list of
questions that they answer according to their knowledge. The elicitation process concludes …

A major goal in computerized learning systems is to optimize learning, while in
computerized adaptive tests (CAT) efficient measurement of the proficiency of students is the …

This study assesses the parameter recovery accuracy of MML and two MCMC methods,
Gibbs and HMC, under the four-parameter unidimensional binary item response function …

In testing, item response theory models are widely used in order to estimate item parameters
and individual abilities. However, even unidimensional models require a considerable …

High-stakes tests often consist of sets of questions (ie, items) grouped around a common
stimulus. Such grou**s of items are often called testlets. A basic assumption of item …

Testing has existed for thousands of years and has evolved from all examinees receiving the
same test to adaptive testing, in which the test is tailored to the individual examinee. These …

The aim of the paper is to propose the introduction of power prior distributions in the ability
estimation of item response theory (IRT) models. In the literature, power priors have been …