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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
Peer reviewed Peer reviewed
Millman, Jason; Westman, Ronald S. – Journal of Educational Measurement, 1989
Five approaches to writing test items with computer assistance are described. A model of knowledge using a set of structures and a system for implementing the scheme are outlined. The approaches include the author-supplied approach, replacement-set procedures, computer-supplied prototype items, subject-matter mapping, and discourse analysis. (TJH)
Descriptors: Achievement Tests, Algorithms, Computer Assisted Testing, Test Construction
Peer reviewed Peer reviewed
van der Linden, Wim J. – Applied Psychological Measurement, 2001
Presents a constrained computerized adaptive testing (CAT) algorithm that can be used to equate CAT number-correct scores to a reference test. Used an item bank from the Law School Admission Test to compare results of the algorithm with those for equipercentile observed-score equating. Discusses advantages of the approach. (SLD)
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Equated Scores
Peer reviewed Peer reviewed
Eggen, T. J. H. M. – Applied Psychological Measurement, 1999
Evaluates a method for item selection in adaptive testing that is based on Kullback-Leibler information (KLI) (T. Cover and J. Thomas, 1991). Simulation study results show that testing algorithms using KLI-based item selection perform better than or as well as those using Fisher information item selection. (SLD)
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Selection
Chang, Shun-Wen; Ansley, Timothy N.; Lin, Sieh-Hwa – 2000
This study examined the effectiveness of the Sympson and Hetter conditional procedure (SHC), a modification of the Sympson and Hetter (1985) algorithm, in controlling the exposure rates of items in a computerized adaptive testing (CAT) environment. The properties of the procedure were compared with those of the Davey and Parshall (1995) and the…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
Lau, C. Allen; Wang, Tianyou – 1999
A study was conducted to extend the sequential probability ratio testing (SPRT) procedure with the polytomous model under some practical constraints in computerized classification testing (CCT), such as methods to control item exposure rate, and to study the effects of other variables, including item information algorithms, test difficulties, item…
Descriptors: Algorithms, Computer Assisted Testing, Difficulty Level, Item Banks
Stocking, Martha L.; And Others – 1991
A previously developed method of automatically selecting items for inclusion in a test subject to constraints on item content and statistical properties is applied to real data. Two tests are first assembled by experts in test construction who normally assemble such tests on a routine basis. Using the same pool of items and constraints articulated…
Descriptors: Algorithms, Automation, Coding, 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
Macready, George B.; Dayton, C. Mitchell – Psychometrika, 1992
An adaptive testing algorithm is presented based on an alternative modeling framework, and its effectiveness is investigated in a simulation based on real data. The algorithm uses a latent class modeling framework in which assessed latent attributes are assumed to be categorical variables. (SLD)
Descriptors: Adaptive Testing, Algorithms, Bayesian Statistics, Classification
Peer reviewed Peer reviewed
Stocking, Martha L.; And Others – Applied Psychological Measurement, 1993
A method of automatically selecting items for inclusion in a test with constraints on item content and statistical properties was applied to real data. Tests constructed manually from the same data and constraints were compared to tests constructed automatically. Results show areas in which automated assembly can improve test construction. (SLD)
Descriptors: Algorithms, Automation, Comparative Testing, Computer Assisted Testing
Gershon, Richard; Bergstrom, Betty – 1995
When examinees are allowed to review responses on an adaptive test, can they "cheat" the adaptive algorithm in order to take an easier test and improve their performance? Theoretically, deliberately answering items incorrectly will lower the examinee ability estimate and easy test items will be administered. If review is then allowed,…
Descriptors: Adaptive Testing, Algorithms, Cheating, 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.; Boekkooi-Timminga, Ellen – 1986
In order to estimate the classical coefficient of test reliability, parallel measurements are needed. H. Gulliksen's matched random subtests method, which is a graphical method for splitting a test into parallel test halves, has practical relevance because it maximizes the alpha coefficient as a lower bound of the classical test reliability…
Descriptors: Algorithms, Computer Assisted Testing, Computer Software, Difficulty Level
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