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Direct linkBelov, Dmitry I.; Armstrong, Ronald D.; Weissman, Alexander – Applied Psychological Measurement, 2008
This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the…
Descriptors: Test Items, Monte Carlo Methods, Law Schools, Adaptive Testing
Gorin, Joanna; Dodd, Barbara; Fitzpatrick, Steven; Shieh, Yann – Applied Psychological Measurement, 2005
The primary purpose of this research is to examine the impact of estimation methods, actual latent trait distributions, and item pool characteristics on the performance of a simulated computerized adaptive testing (CAT) system. In this study, three estimation procedures are compared for accuracy of estimation: maximum likelihood estimation (MLE),…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computation, Test Items
Li, Yuan H.; Schafer, William D. – Applied Psychological Measurement, 2005
Under a multidimensional item response theory (MIRT) computerized adaptive testing (CAT) testing scenario, a trait estimate (theta) in one dimension will provide clues for subsequently seeking a solution in other dimensions. This feature may enhance the efficiency of MIRT CAT's item selection and its scoring algorithms compared with its…
Descriptors: Adaptive Testing, Item Banks, Computation, Psychological Studies
