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Ersen, Rabia Karatoprak; Lee, Won-Chan – Journal of Educational Measurement, 2023
The purpose of this study was to compare calibration and linking methods for placing pretest item parameter estimates on the item pool scale in a 1-3 computerized multistage adaptive testing design in terms of item parameter recovery. Two models were used: embedded-section, in which pretest items were administered within a separate module, and…
Descriptors: Pretesting, Test Items, Computer Assisted Testing, Adaptive Testing
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Kang, Hyeon-Ah; Zhang, Susu; Chang, Hua-Hua – Journal of Educational Measurement, 2017
The development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Test Items
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Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry – ETS Research Report Series, 2015
The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…
Descriptors: Item Response Theory, Computation, Statistical Bias, Error of Measurement
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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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Samejima, Fumiko – Applied Psychological Measurement, 1994
The reliability coefficient is predicted from the test information function (TIF) or two modified TIF formulas and a specific trait distribution. Examples illustrate the variability of the reliability coefficient across different trait distributions, and results are compared with empirical reliability coefficients. (SLD)
Descriptors: Adaptive Testing, Error of Measurement, Estimation (Mathematics), Reliability
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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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Berger, Martijn P. F. – Applied Psychological Measurement, 1994
This paper focuses on similarities of optimal design of fixed-form tests, adaptive tests, and testlets within the framework of the general theory of optimal designs. A sequential design procedure is proposed that uses these similarities to obtain consistent estimates for the trait level distribution. (SLD)
Descriptors: Achievement Tests, Adaptive Testing, Algorithms, Estimation (Mathematics)
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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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Lin, Miao-Hsiang; Hsiung, Chao A. – Psychometrika, 1994
Two simple empirical approximate Bayes estimators are introduced for estimating domain scores under binomial and hypergeometric distributions respectively. Criteria are established regarding use of these functions over maximum likelihood estimation counterparts. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computation, Equations (Mathematics)
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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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Wainer, Howard; And Others – Journal of Educational Measurement, 1992
Computer simulations were run to measure the relationship between testlet validity and factors of item pool size and testlet length for both adaptive and linearly constructed testlets. Making a testlet adaptive yields only modest increases in aggregate validity because of the peakedness of the typical proficiency distribution. (Author/SLD)
Descriptors: Adaptive Testing, Comparative Testing, Computer Assisted Testing, Computer Simulation
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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