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Parshall, Cynthia G.; Kromrey, Jeffrey D.; Harmes, J. Christine; Sentovich, Christina – 2001
Computerized adaptive tests (CATs) are efficient because of their optimal item selection procedures that target maximally informative items at each estimated ability level. However, operational administration of these optimal CATs results in a relatively small subset of items given to examinees too often, while another portion of the item pool is…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Estimation (Mathematics)
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Wang, Shudong; Wang, Tianyou – Applied Psychological Measurement, 2001
Evaluated the relative accuracy of the weighted likelihood estimate (WLE) of T. Warm (1989) compared to the maximum likelihood estimate (MLE), expected a posteriori estimate, and maximum a posteriori estimate. Results of the Monte Carlo study, which show the relative advantages of each approach, suggest that the test termination rule has more…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Estimation (Mathematics)
Chang, Shun-Wen; Twu, Bor-Yaun – 1998
This study investigated and compared the properties of five methods of item exposure control within the purview of estimating examinees' abilities in a computerized adaptive testing (CAT) context. Each of the exposure control algorithms was incorporated into the item selection procedure and the adaptive testing progressed based on the CAT design…
Descriptors: Adaptive Testing, Algorithms, Comparative Analysis, Computer Assisted Testing
Bejar, Isaac I. – 1996
Generative response modeling is an approach to test development and response modeling that calls for the creation of items in such a way that the parameters of the items on some response model can be anticipated through knowledge of the psychological processes and knowledge required to respond to the item. That is, the computer would not merely…
Descriptors: Ability, Computer Assisted Testing, Cost Effectiveness, Estimation (Mathematics)
Kim, Haeok; Plake, Barbara S. – 1993
A two-stage testing strategy is one method of adapting the difficulty of a test to an individual's ability level in an effort to achieve more precise measurement. A routing test provides an initial estimate of ability level, and a second-stage measurement test then evaluates the examinee further. The measurement accuracy and efficiency of item…
Descriptors: Ability, Adaptive Testing, Comparative Testing, Computer Assisted Testing
Vale, C. David; Gialluca, Kathleen A. – 1985
ASCAL is a microcomputer-based program for calibrating items according to the three-parameter logistic model of item response theory. It uses a modified multivariate Newton-Raphson procedure for estimating item parameters. This study evaluated this procedure using Monte Carlo Simulation Techniques. The current version of ASCAL was then compared to…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Computer Simulation
Kirisci, Levent; Hsu, Tse-Chi – 1992
A predictive adaptive testing (PAT) strategy was developed based on statistical predictive analysis, and its feasibility was studied by comparing PAT performance to those of the Flexilevel, Bayesian modal, and expected a posteriori (EAP) strategies in a simulated environment. The proposed adaptive test is based on the idea of using item difficulty…
Descriptors: Adaptive Testing, Bayesian Statistics, Comparative Analysis, Computer Assisted Testing
Xiao, Beiling – 1990
Dichotomous search strategies (DSSs) for computerized adaptive testing are similar to golden section search strategies (GSSSs). Each middle point of successive search regions is a testing point. After each item is administered, the subject's obtained score is compared with the expected score at successive testing points. If the subject's obtained…
Descriptors: Ability Identification, Adaptive Testing, Computer Assisted Testing, Equations (Mathematics)