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Passos, Valeria Lima; Berger, Martijn P. F.; Tan, Frans E. S. – Journal of Educational and Behavioral Statistics, 2008
During the early stage of computerized adaptive testing (CAT), item selection criteria based on Fisher"s information often produce less stable latent trait estimates than the Kullback-Leibler global information criterion. Robustness against early stage instability has been reported for the D-optimality criterion in a polytomous CAT with the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Evaluation Criteria, Item Analysis
Frey, Andreas; Carstensen, Claus H. – Measurement: Interdisciplinary Research and Perspectives, 2009
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…
Descriptors: Adaptive Testing, Test Items, Classification, Psychometrics
Xu, Xueli; Douglas, Jeff – Psychometrika, 2006
Nonparametric item response models have been developed as alternatives to the relatively inflexible parametric item response models. An open question is whether it is possible and practical to administer computerized adaptive testing with nonparametric models. This paper explores the possibility of computerized adaptive testing when using…
Descriptors: Simulation, Nonparametric Statistics, Item Analysis, Item Response Theory
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
Revuelta, Javier – Journal of Educational and Behavioral Statistics, 2004
This article presents a psychometric model for estimating ability and item-selection strategies in self-adapted testing. In contrast to computer adaptive testing, in self-adapted testing the examinees are allowed to select the difficulty of the items. The item-selection strategy is defined as the distribution of difficulty conditional on the…
Descriptors: Psychometrics, Adaptive Testing, Test Items, Evaluation Methods
McArthur, David L.; Choppin, Bruce H. – 1983
This paper examines the history of approaches to diagnosis in education and in medicine--a profession with concentrated attention to the conceptual and mathematical underpinnings of diagnosis. Presented is a comprehensive model of diagnostic testing in education and a summary of the results of four studies, one from each of four separate…
Descriptors: Adaptive Testing, Computer Assisted Testing, Diagnostic Tests, Educational Diagnosis
Kalisch, Stanley J. – Journal of Computer-Based Instruction, 1974
A tailored testing model employing the beta distribution, whose mean equals the difficulty of an item and whose variance is approximately equal to the sampling variance of the item difficulty, and employing conditional item difficulties, is proposed. (Author)
Descriptors: Adaptive Testing, Computer Assisted Testing, Evaluation Methods, Item Analysis
Rizavi, Saba; Way, Walter D.; Davey, Tim; Herbert, Erin – Educational Testing Service, 2004
Item parameter estimates vary for a variety of reasons, including estimation error, characteristics of the examinee samples, and context effects (e.g., item location effects, section location effects, etc.). Although we expect variation based on theory, there is reason to believe that observed variation in item parameter estimates exceeds what…
Descriptors: Adaptive Testing, Test Items, Computation, Context Effect
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