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Belov, 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
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Penfield, Randall D. – Applied Measurement in Education, 2006
This study applied the maximum expected information (MEI) and the maximum posterior-weighted information (MPI) approaches of computer adaptive testing item selection to the case of a test using polytomous items following the partial credit model. The MEI and MPI approaches are described. A simulation study compared the efficiency of ability…
Descriptors: Bayesian Statistics, Adaptive Testing, Computer Assisted Testing, Test Items
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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
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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
Lam, Tit-Loong; Foong, Yoke-Yeen – 1991
This simulation study involved the design of two two-stage tests in which the routing tests and the second-stage measurement testlets took the form of a multidimensional knapsack problem with prespecified target informations and constraints to be enumerated using the algorithm of E. Balas. Two conventional tests of similar length to the two-stage…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Computer Simulation
Reshetar, Rosemary A.; And Others – 1992
This study examined performance of a simulated computerized adaptive test that was designed to help direct the development of a medical recertification examination. The item pool consisted of 229 single-best-answer items from a random sample of 3,000 examinees, calibrated using the two-parameter logistic model. Examinees' responses were known. For…
Descriptors: Adaptive Testing, Classification, Computer Assisted Testing, Computer Simulation
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
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Liu, Chao-Lin – Educational Technology & Society, 2005
The author analyzes properties of mutual information between dichotomous concepts and test items. The properties generalize some common intuitions about item comparison, and provide principled foundations for designing item-selection heuristics for student assessment in computer-assisted educational systems. The proposed item-selection strategies…
Descriptors: Test Items, Heuristics, Classification, Item Analysis