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Yuan, Lu; Huang, Yingshi; Li, Shuhang; Chen, Ping – Journal of Educational Measurement, 2023
Online calibration is a key technology for item calibration in computerized adaptive testing (CAT) and has been widely used in various forms of CAT, including unidimensional CAT, multidimensional CAT (MCAT), CAT with polytomously scored items, and cognitive diagnostic CAT. However, as multidimensional and polytomous assessment data become more…
Descriptors: Computer Assisted Testing, Adaptive Testing, Computation, Test Items
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Sahin Kursad, Merve; Cokluk Bokeoglu, Omay; Cikrikci, Rahime Nukhet – International Journal of Assessment Tools in Education, 2022
Item parameter drift (IPD) is the systematic differentiation of parameter values of items over time due to various reasons. If it occurs in computer adaptive tests (CAT), it causes errors in the estimation of item and ability parameters. Identification of the underlying conditions of this situation in CAT is important for estimating item and…
Descriptors: Item Analysis, Computer Assisted Testing, Test Items, Error of Measurement
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Kárász, Judit T.; Széll, Krisztián; Takács, Szabolcs – Quality Assurance in Education: An International Perspective, 2023
Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…
Descriptors: Test Length, Probability, Comparative Analysis, Difficulty Level
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Chen, Ping – Journal of Educational and Behavioral Statistics, 2017
Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…
Descriptors: Test Items, Item Response Theory, Test Construction, Adaptive Testing
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Sahin, Alper; Weiss, David J. – Educational Sciences: Theory and Practice, 2015
This study aimed to investigate the effects of calibration sample size and item bank size on examinee ability estimation in computerized adaptive testing (CAT). For this purpose, a 500-item bank pre-calibrated using the three-parameter logistic model with 10,000 examinees was simulated. Calibration samples of varying sizes (150, 250, 350, 500,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Sample Size, Item Banks
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Wu, Huey-Min; Kuo, Bor-Chen; Yang, Jinn-Min – Educational Technology & Society, 2012
In recent years, many computerized test systems have been developed for diagnosing students' learning profiles. Nevertheless, it remains a challenging issue to find an adaptive testing algorithm to both shorten testing time and precisely diagnose the knowledge status of students. In order to find a suitable algorithm, four adaptive testing…
Descriptors: Adaptive Testing, Test Items, Computer Assisted Testing, Mathematics
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Zhang, Mo; Breyer, F. Jay; Lorenz, Florian – ETS Research Report Series, 2013
In this research, we investigated the suitability of implementing "e-rater"® automated essay scoring in a high-stakes large-scale English language testing program. We examined the effectiveness of generic scoring and 2 variants of prompt-based scoring approaches. Effectiveness was evaluated on a number of dimensions, including agreement…
Descriptors: Computer Assisted Testing, Computer Software, Scoring, Language Tests
Roussos, Louis; Nandakumar, Ratna; Cwikla, Julie – 2000
CATSIB is a differential item functioning (DIF) assessment methodology for computerized adaptive test (CAT) data. Kernel smoothing (KS) is a technique for nonparametric estimation of item response functions. In this study an attempt has been made to develop a more efficient DIF procedure for CAT data, KS-CATSIB, by combining CATSIB with kernel…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Bias, Item Response Theory
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Koch, William R.; Dodd, Barbara G. – Educational and Psychological Measurement, 1995
Basic procedures for performing computerized adaptive testing based on the successive intervals (SI) Rasch model were evaluated. The SI model was applied to simulated and real attitude data sets. Item pools as small as 30 items performed well, and the model appeared practical for Likert-type data. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Item Response Theory
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Chuah, Siang Chee; Drasgow, Fritz; Luecht, Richard – Applied Measurement in Education, 2006
Adaptive tests offer the advantages of reduced test length and increased accuracy in ability estimation. However, adaptive tests require large pools of precalibrated items. This study looks at the development of an item pool for 1 type of adaptive administration: the computer-adaptive sequential test. An important issue is the sample size required…
Descriptors: Test Length, Sample Size, Adaptive Testing, Item Response Theory
Zwick, Rebecca – 1995
This paper describes a study, now in progress, of new methods for representing the sampling variability of Mantel-Haenszel differential item functioning (DIF) results, based on the system for categorizing the severity of DIF that is now in place at the Educational Testing Service. The methods, which involve a Bayesian elaboration of procedures…
Descriptors: Adaptive Testing, Bayesian Statistics, Classification, Computer Assisted Testing
De Ayala, R. J. – 1995
This study extended item parameter recovery studies in item response theory to the nominal response model (NRM). The NRM may be used with computerized adaptive testing, testlets, demographic items, and items whose alternatives provide educational diagnostic information. Moreover, with the increasing popularity of performance-based assessment, the…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Educational Diagnosis
De Champlain, Andre; Gessaroli, Marc E. – 1996
The use of indices and statistics based on nonlinear factor analysis (NLFA) has become increasingly popular as a means of assessing the dimensionality of an item response matrix. Although the indices and statistics currently available to the practitioner have been shown to be useful and accurate in many testing situations, few studies have…
Descriptors: Adaptive Testing, Chi Square, Computer Assisted Testing, Factor Analysis
Ree, Malcom James; Jensen, Harald E. – 1980
By means of computer simulation of test responses, the reliability of item analysis data and the accuracy of equating were examined for hypothetical samples of 250, 500, 1000, and 2000 subjects for two tests with 20 equating items plus 60 additional items on the same scale. Birnbaum's three-parameter logistic model was used for the simulation. The…
Descriptors: Computer Assisted Testing, Equated Scores, Error of Measurement, Item Analysis
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Lei, Pui-Wa; Chen, Shu-Ying; Yu, Lan – Journal of Educational Measurement, 2006
Mantel-Haenszel and SIBTEST, which have known difficulty in detecting non-unidirectional differential item functioning (DIF), have been adapted with some success for computerized adaptive testing (CAT). This study adapts logistic regression (LR) and the item-response-theory-likelihood-ratio test (IRT-LRT), capable of detecting both unidirectional…
Descriptors: Evaluation Methods, Test Bias, Computer Assisted Testing, Multiple Regression Analysis
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