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Han, Kyung T.; Dimitrov, Dimiter M.; Al-Mashary, Faisal – Educational and Psychological Measurement, 2019
The "D"-scoring method for scoring and equating tests with binary items proposed by Dimitrov offers some of the advantages of item response theory, such as item-level difficulty information and score computation that reflects the item difficulties, while retaining the merits of classical test theory such as the simplicity of number…
Descriptors: Test Construction, Scoring, Test Items, Adaptive Testing
Barnard, John J. – Practical Assessment, Research & Evaluation, 2018
Measurement specialists strive to shorten assessment time without compromising precision of scores. Computerized Adaptive Testing (CAT) has rapidly gained ground over the past decades to fulfill this goal. However, parameters for implementation of CATs need to be explored in simulations before implementation so that it can be determined whether…
Descriptors: Computer Assisted Testing, Adaptive Testing, Simulation, Multiple Choice Tests
Chen, Ping – Journal of Educational and Behavioral Statistics, 2017
Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…
Descriptors: Test Items, Item Response Theory, Test Construction, Adaptive Testing
Wei, Hua; Lin, Jie – International Journal of Testing, 2015
Out-of-level testing refers to the practice of assessing a student with a test that is intended for students at a higher or lower grade level. Although the appropriateness of out-of-level testing for accountability purposes has been questioned by educators and policymakers, incorporating out-of-level items in formative assessments for accurate…
Descriptors: Test Items, Computer Assisted Testing, Adaptive Testing, Instructional Program Divisions
Seo, Dong Gi; Weiss, David J. – Educational and Psychological Measurement, 2015
Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm…
Descriptors: Computer Assisted Testing, Adaptive Testing, Accuracy, Fidelity
Yang, Xiangdong; Poggio, John C.; Glasnapp, Douglas R. – Educational and Psychological Measurement, 2006
The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory-based adaptive classification procedure on multiple categories were studied via simulations. The following…
Descriptors: Classification, Computation, Simulation, Item Response Theory
Parshall, Cynthia G.; Davey, Tim; Nering, Mike L. – 1998
When items are selected during a computerized adaptive test (CAT) solely with regard to their measurement properties, it is commonly found that certain items are administered to nearly every examinee, and that a small number of the available items will account for a large proportion of the item administrations. This presents a clear security risk…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Efficiency
Davey, Tim; Parshall, Cynthia G. – 1995
Although computerized adaptive tests acquire their efficiency by successively selecting items that provide optimal measurement at each examinee's estimated level of ability, operational testing programs will typically consider additional factors in item selection. In practice, items are generally selected with regard to at least three, often…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
A Feedback Control Strategy for Enhancing Item Selection Efficiency in Computerized Adaptive Testing
Weissman, Alexander – Applied Psychological Measurement, 2006
A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level ([theta]) estimation and vice versa. When discrepancies exist between an examinee's estimated and true [theta] levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with…
Descriptors: Item Response Theory, Feedback, Adaptive Testing, Computer Assisted Testing
Kalisch, Stanley James, Jr. – 1974
The four purposes of this study were: (1) To compare two versions of a tailored testing model similar to one suggested by Kalisch (1974); (2) To identify levels of the variables within the two versions, which produce an efficient tailored testing procedures; (3) To compare, within each version, the results obtained when employing relatively small…
Descriptors: Ability, Adaptive Testing, Branching, Comparative Analysis
Kalisch, Stanley James, Jr. – 1975
Two tailored testing models, specifying procedures by which the correctness of examinees' responses to a fixed number of test items are predicted by presenting as few items as possible to the examinee, were compared for their efficiency. The models differ in that one requires reconsideration of each prediction whenever additional information is…
Descriptors: Ability, Adaptive Testing, Branching, Comparative Analysis