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Giada Spaccapanico Proietti; Mariagiulia Matteucci; Stefania Mignani; Bernard P. Veldkamp – Journal of Educational and Behavioral Statistics, 2024
Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…
Descriptors: Automation, Computer Assisted Testing, Ambiguity (Context), Item Response Theory
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van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob R. – Applied Psychological Measurement, 2002
Compared the nominal and empirical null distributions of the standardized log-likelihood statistic for polytomous items for paper-and-pencil (P&P) and computerized adaptive tests (CATs). Results show that the empirical distribution of the statistic differed from the assumed standard normal distribution for both P&P tests and CATs. Also…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Response Theory, Statistical Distributions
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van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob – Applied Psychological Measurement, 1999
Theoretical null distributions of several fit statistic have been derived for paper-and-pencil tests. Examined whether these distributions also hold for computerized adaptive tests through simulation. Rates for two statistics studied were found to be similar in most cases. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Goodness of Fit, Item Response Theory
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Nering, Michael L. – Applied Psychological Measurement, 1997
Evaluated the distribution of person fit within the computerized-adaptive testing (CAT) environment through simulation. Found that, within the CAT environment, these indexes tend not to follow a standard normal distribution. Person fit indexes had means and standard deviations that were quite different from the expected. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Error of Measurement, Item Response Theory
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Dodd, Barbara G.; Koch, William R. – Educational and Psychological Measurement, 1994
Simulated data were used to investigate the impact of characteristics of threshold values (number, symmetry, and distance between adjacent threshold values) and delta values on the distribution of item information in the successive intervals Rasch model. Implications for computerized adaptive attitude measurement are discussed. (SLD)
Descriptors: Adaptive Testing, Attitude Measures, Computer Assisted Testing, Item Response Theory
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Hankins, Janette A. – Educational and Psychological Measurement, 1990
The effects of a fixed and variable entry procedure on bias and information of a Bayesian adaptive test were compared. Neither procedure produced biased ability estimates on the average. Bias at the distribution extremes, efficiency curves, item subsets generated for administration, and items required to reach termination are discussed. (TJH)
Descriptors: Adaptive Testing, Aptitude Tests, Bayesian Statistics, Comparative Analysis
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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
Ito, Kyoko; Sykes, Robert C. – 1994
Responses to previously calibrated items administered in a computerized adaptive testing (CAT) mode may be used to recalibrate the items. This live-data simulation study investigated the possibility, and limitations, of on-line adaptive recalibration of precalibrated items. Responses to items of a Rasch-based paper-and-pencil licensure examination…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Difficulty Level
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Cohen, Allan S.; And Others – Journal of Educational Measurement, 1991
Detecting differential item functioning (DIF) on test items constructed to favor 1 group over another was investigated on parameter estimates from 2 item response theory-based computer programs--BILOG and LOGIST--using data for 1,000 White and 1,000 Black college students. Use of prior distributions and marginal-maximum a posteriori estimation is…
Descriptors: Black Students, College Students, Computer Assisted Testing, Equations (Mathematics)