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Thompson, Nathan A. – Practical Assessment, Research & Evaluation, 2011
Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Classification, Probability
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Vuk, Jasna; Morse, David T. – Research in the Schools, 2009
In this study we observed college students' behavior on two self-tailored, multiple-choice exams. Self-tailoring was defined as an option to omit up to five items from being scored on an exam. Participants, 80 undergraduate college students enrolled in two sections of an educational psychology course, statistically significantly improved their…
Descriptors: College Students, Educational Psychology, Academic Achievement, Correlation
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Eggen, Theo J. H. M.; Verschoor, Angela J. – Applied Psychological Measurement, 2006
Computerized adaptive tests (CATs) are individualized tests that, from a measurement point of view, are optimal for each individual, possibly under some practical conditions. In the present study, it is shown that maximum information item selection in CATs using an item bank that is calibrated with the one- or the two-parameter logistic model…
Descriptors: Adaptive Testing, Difficulty Level, Test Items, Item Response Theory
Zhu, Daming; Fan, Meichu – 1999
The convention for selecting starting points (that is, initial items) on a computerized adaptive test (CAT) is to choose as starting points items of medium difficulty for all examinees. Selecting a starting point based on prior information about an individual's ability was first suggested many years ago, but has been believed unimportant provided…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Difficulty Level
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Stocking, Martha L. – Journal of Educational and Behavioral Statistics, 1996
An alternative method for scoring adaptive tests, based on number-correct scores, is explored and compared with a method that relies more directly on item response theory. Using the number-correct score with necessary adjustment for intentional differences in adaptive test difficulty is a statistically viable scoring method. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Item Response Theory
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
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Vispoel, Walter P.; Clough, Sara J.; Bleiler, Timothy – Journal of Educational Measurement, 2005
Recent studies have shown that restricting review and answer change opportunities on computerized adaptive tests (CATs) to items within successive blocks reduces time spent in review, satisfies most examinees' desires for review, and controls against distortion in proficiency estimates resulting from intentional incorrect answering of items prior…
Descriptors: Mathematics, Item Analysis, Adaptive Testing, Computer Assisted Testing
Stocking, Martha L. – 1994
Modern applications of computerized adaptive testing (CAT) are typically grounded in item response theory (IRT; Lord, 1980). While the IRT foundations of adaptive testing provide a number of approaches to adaptive test scoring that may seem natural and efficient to psychometricians, these approaches may be more demanding for test takers, test…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Equated Scores
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Bridgeman, Brent; Cline, Frederick – Journal of Educational Measurement, 2004
Time limits on some computer-adaptive tests (CATs) are such that many examinees have difficulty finishing, and some examinees may be administered tests with more time-consuming items than others. Results from over 100,000 examinees suggested that about half of the examinees must guess on the final six questions of the analytical section of the…
Descriptors: Guessing (Tests), Timed Tests, Adaptive Testing, Computer Assisted Testing
De Ayala, R. J. – 1990
The effect of dimensionality on an adaptive test's ability estimation was examined. Two-dimensional data sets, which differed from one another in the interdimensional ability association, the correlation among the difficulty parameters, and whether the item discriminations were or were not confounded with item difficulty, were generated for 1,600…
Descriptors: Ability Identification, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
Kim, Seock-Ho; Cohen, Allan S. – 1996
Applications of item response theory to practical testing problems including equating, differential item functioning, and computerized adaptive testing, require that item parameter estimates be placed onto a common metric. In this study, three methods for developing a common metric under item response theory are compared: (1) linking separate…
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Difficulty Level
Gershon, Richard C.; And Others – 1994
A 1992 study by R. Gershon found discrepancies when comparing the theoretical Rasch item characteristic curve with the average empirical curve for 1,304 vocabulary items administered to 7,711 students. When person-item mismatches were deleted (for any person-item interaction where the ability of the person was much higher or much lower than the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Elementary Education
Sykes, Robert C.; Ito, Kyoko – 1995
Whether the presence of bidimensionality has any effect on the adaptive recalibration of test items was studied through live-data simulation of computer adaptive testing (CAT) forms. The source data were examinee responses to the 298 scored multiple choice items of a licensure examination in a health care profession. Three 75-item part-forms,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Estimation (Mathematics)
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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Dodd, Barbara G.; And Others – Educational and Psychological Measurement, 1993
Effects of the following variables on performance of computerized adaptive testing (CAT) procedures for the partial credit model (PCM) were studied: (1) stopping rule for terminating CAT; (2) item pool size; and (3) distribution of item difficulties. Implications of findings for CAT systems based on the PCM are discussed. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Simulation, Difficulty Level
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