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Glas, Cees A. W.; Vos, Hans J. – 1998
A version of sequential mastery testing is studied in which response behavior is modeled by an item response theory (IRT) model. First, a general theoretical framework is sketched that is based on a combination of Bayesian sequential decision theory and item response theory. A discussion follows on how IRT based sequential mastery testing can be…
Descriptors: Adaptive Testing, Bayesian Statistics, Item Response Theory, Mastery Tests
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Green, Bert F. – 2002
Maximum likelihood and Bayesian estimates of proficiency, typically used in adaptive testing, use item weights that depend on test taker proficiency to estimate test taker proficiency. In this study, several methods were explored through computer simulation using fixed item weights, which depend mainly on the items difficulty. The simpler scores…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Computer Simulation
Weiss, David J.; Suhadolnik, Debra – 1982
The present monte carlo simulation study was designed to examine the effects of multidimensionality during the administration of computerized adaptive testing (CAT). It was assumed that multidimensionality existed in the individuals to whom test items were being administered, i.e., that the correct or incorrect responses given by an individual…
Descriptors: Adaptive Testing, Computer Assisted Testing, Factor Structure, Latent Trait Theory
Rizavi, Saba; Way, Walter D.; Lu, Ying; Pitoniak, Mary; Steffen, Manfred – Online Submission, 2004
The purpose of this study was to use realistically simulated data to evaluate various CAT designs for use with the verbal reasoning measure of the Medical College Admissions Test (MCAT). Factors such as item pool depth, content constraints, and item formats often cause repeated adaptive administrations of an item at ability levels that are not…
Descriptors: Test Items, Test Bias, Item Banks, College Admission