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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
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
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
Knol, Dirk L. – 1989
Two iterative procedures for constructing Rasch scales are presented. A log-likelihood ratio test based on a quasi-loglinear formulation of the Rasch model is given by which one item at a time can be deleted from or added to an initial item set. In the so-called "top-down" algorithm, items are stepwise deleted from a relatively large…
Descriptors: Algorithms, Item Banks, Latent Trait Theory, Mathematical Models
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