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Cheng, Philip E.; Liou, Michelle – Applied Psychological Measurement, 2000
Reviewed methods of estimating theta suitable for computerized adaptive testing (CAT) and discussed the differences between Fisher and Kullback-Leibler information criteria for selecting items. Examined the accuracy of different CAT algorithms using samples from the National Assessment of Educational Progress. Results show when correcting for…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
Stocking, Martha L.; Lewis, Charles – 1995
The interest in the application of large-scale adaptive testing for secure tests has served to focus attention on issues that arise when theoretical advances are made operational. Many such issues in the application of large-scale adaptive testing for secure tests have more to do with changes in testing conditions than with testing paradigms. One…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
Krass, Iosif A. – 1998
In the process of item calibration for a computerized adaptive test (CAT), many well-established calibrating packages show weakness in the estimation of item parameters. This paper introduces an on-line calibration algorithm based on the convexity of likelihood functions. This package consists of: (1) an algorithm that estimates examinee ability…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
van der Linden, Wim J. – 1997
In constrained adaptive testing, the numbers of constraints needed to control the content of the tests can easily run into the hundreds. Proper initialization of the algorithm becomes a requirement because the presence of large numbers of constraints slows down the convergence of the ability estimator. In this paper, an empirical initialization of…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
van der Linden, Wim J. – 1997
The case of adaptive testing under a multidimensional logistic response model is addressed. An adaptive algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The item selection criterion is a simple expression in closed form. In addition, it is…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
Peer reviewed Peer reviewed
van der Linden, Wim J. – Journal of Educational and Behavioral Statistics, 1999
Proposes an algorithm that minimizes the asymptotic variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The criterion results in a closed-form expression that is easy to evaluate. Also shows how the algorithm can be modified if the interest is in a test with a "simple ability structure."…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
Bergstrom, Betty A.; Lunz, Mary E. – 1991
The equivalence of pencil and paper Rasch item calibrations when used in a computer adaptive test administration was explored in this study. Items (n=726) were precalibarted with the pencil and paper test administrations. A computer adaptive test was administered to 321 medical technology students using the pencil and paper precalibrations in the…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
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
van der Linden, Wim J. – 1999
A constrained computerized adaptive testing (CAT) algorithm is presented that automatically equates the number-correct scores on adaptive tests. The algorithm can be used to equate number-correct scores across different administrations of the same adaptive test as well as to an external reference test. The constraints are derived from a set of…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
Schnipke, Deborah L.; Reese, Lynda M. – 1997
Two-stage and multistage test designs provide a way of roughly adapting item difficulty to test-taker ability. All test takers take a parallel stage-one test, and, based on their scores, they are routed to tests of different difficulty levels in subsequent stages. These designs provide some of the benefits of standard computerized adaptive testing…
Descriptors: Ability, Adaptive Testing, Algorithms, Comparative Analysis
Veerkamp, Wim J. J.; Berger, Martijn P. F. – 1994
Items with the highest discrimination parameter values in a logistic item response theory (IRT) model do not necessarily give maximum information. This paper shows which discrimination parameter values (as a function of the guessing parameter and the distance between person ability and item difficulty) give maximum information for the…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
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Vale, C. David; Weiss, David J. – 1977
Twenty multiple-choice vocabulary items and 20 free-response vocabulary items were administered to 660 college students. The free-response items consisted of the stem words of the multiple-choice items. Testees were asked to respond to the free-response items with synonyms. A computer algorithm was developed to transform the numerous…
Descriptors: Ability, Adaptive Testing, Algorithms, Aptitude Tests