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Moothedath, Shana; Chaporkar, Prasanna; Belur, Madhu N. – Perspectives in Education, 2016
In recent years, the computerised adaptive test (CAT) has gained popularity over conventional exams in evaluating student capabilities with desired accuracy. However, the key limitation of CAT is that it requires a large pool of pre-calibrated questions. In the absence of such a pre-calibrated question bank, offline exams with uncalibrated…
Descriptors: Guessing (Tests), Computer Assisted Testing, Adaptive Testing, Maximum Likelihood Statistics
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Choi, Seung W.; Grady, Matthew W.; Dodd, Barbara G. – Educational and Psychological Measurement, 2011
The goal of the current study was to introduce a new stopping rule for computerized adaptive testing (CAT). The predicted standard error reduction (PSER) stopping rule uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Evaluation Methods
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Makransky, Guido; Glas, Cees A. W. – International Journal of Testing, 2013
Cognitive ability tests are widely used in organizations around the world because they have high predictive validity in selection contexts. Although these tests typically measure several subdomains, testing is usually carried out for a single subdomain at a time. This can be ineffective when the subdomains assessed are highly correlated. This…
Descriptors: Foreign Countries, Cognitive Ability, Adaptive Testing, Feedback (Response)
Kim, Jiseon – ProQuest LLC, 2010
Classification testing has been widely used to make categorical decisions by determining whether an examinee has a certain degree of ability required by established standards. As computer technologies have developed, classification testing has become more computerized. Several approaches have been proposed and investigated in the context of…
Descriptors: Test Length, Computer Assisted Testing, Classification, Probability
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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
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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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Lei, Pui-Wa; Chen, Shu-Ying; Yu, Lan – Journal of Educational Measurement, 2006
Mantel-Haenszel and SIBTEST, which have known difficulty in detecting non-unidirectional differential item functioning (DIF), have been adapted with some success for computerized adaptive testing (CAT). This study adapts logistic regression (LR) and the item-response-theory-likelihood-ratio test (IRT-LRT), capable of detecting both unidirectional…
Descriptors: Evaluation Methods, Test Bias, Computer Assisted Testing, Multiple Regression Analysis
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Hutton, Jerry B.; And Others – School Psychology Review, 1992
A mail survey about the use of instruments in 9 assessment areas was answered by 389 school psychologists. Comparison with a similar survey 10 years earlier suggests no decline in assessment overall, although emphasis is switching away from intelligence testing, toward achievement testing, behavior rating, and adaptive measurements. (SLD)
Descriptors: Achievement Tests, Adaptive Testing, Behavior Rating Scales, Comparative Analysis