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Tan, Qingrong; Cai, Yan; Luo, Fen; Tu, Dongbo – Journal of Educational and Behavioral Statistics, 2023
To improve the calibration accuracy and calibration efficiency of cognitive diagnostic computerized adaptive testing (CD-CAT) for new items and, ultimately, contribute to the widespread application of CD-CAT in practice, the current article proposed a Gini-based online calibration method that can simultaneously calibrate the Q-matrix and item…
Descriptors: Cognitive Tests, Computer Assisted Testing, Adaptive Testing, Accuracy
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Li, Yan; Huang, Chao; Liu, Jia – Journal of Educational and Behavioral Statistics, 2023
Cognitive diagnostic computerized adaptive testing (CD-CAT) is a cutting-edge technology in educational measurement that targets at providing feedback on examinees' strengths and weaknesses while increasing test accuracy and efficiency. To date, most CD-CAT studies have made methodological progress under simulated conditions, but little has…
Descriptors: Computer Assisted Testing, Cognitive Tests, Diagnostic Tests, Reading Tests
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Kang, Hyeon-Ah; Zheng, Yi; Chang, Hua-Hua – Journal of Educational and Behavioral Statistics, 2020
With the widespread use of computers in modern assessment, online calibration has become increasingly popular as a way of replenishing an item pool. The present study discusses online calibration strategies for a joint model of responses and response times. The study proposes likelihood inference methods for item paramter estimation and evaluates…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Response Theory, Reaction Time
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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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Andrich, David; Marais, Ida; Humphry, Stephen – Journal of Educational and Behavioral Statistics, 2012
Andersen (1995, 2002) proves a theorem relating variances of parameter estimates from samples and subsamples and shows its use as an adjunct to standard statistical analyses. The authors show an application where the theorem is central to the hypothesis tested, namely, whether random guessing to multiple choice items affects their estimates in the…
Descriptors: Test Items, Item Response Theory, Multiple Choice Tests, Guessing (Tests)
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Doong, Shing H. – Journal of Educational and Behavioral Statistics, 2009
The purpose of this study is to investigate a functional relation between item exposure parameters (IEPs) and item parameters (IPs) over parallel pools. This functional relation is approximated by a well-known tool in machine learning. Let P and Q be parallel item pools and suppose IEPs for P have been obtained via a Sympson and Hetter-type…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Simulation
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Armstrong, Ronald D.; Jones, Douglas H.; Wang, Zhaobo – Journal of Educational and Behavioral Statistics, 1998
Generating a test from an item bank using a criterion based on classical test theory parameters poses considerable problems. A mathematical model is formulated that maximizes the reliability coefficient alpha, subject to logical constraints on the choice of items. Theorems ensuring appropriate application of the Lagragian relation techniques are…
Descriptors: Item Banks, Mathematical Models, Reliability, Test Construction
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Stocking, Martha L.; Lewis, Charles – Journal of Educational and Behavioral Statistics, 1998
Ensuring item and pool security in a continuous testing environment is explored through a new method of controlling exposure rate of items conditional on ability level in computerized testing. Properties of this conditional control on exposure rate, when used in conjunction with a particular adaptive testing algorithm, are explored using simulated…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Difficulty Level
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van der Linden, Wim J.; Ariel, Adelaide; Veldkamp, Bernard P. – Journal of Educational and Behavioral Statistics, 2006
Test-item writing efforts typically results in item pools with an undesirable correlational structure between the content attributes of the items and their statistical information. If such pools are used in computerized adaptive testing (CAT), the algorithm may be forced to select items with less than optimal information, that violate the content…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Item Banks
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Revuelta, Javier – Journal of Educational and Behavioral Statistics, 2004
This article presents a psychometric model for estimating ability and item-selection strategies in self-adapted testing. In contrast to computer adaptive testing, in self-adapted testing the examinees are allowed to select the difficulty of the items. The item-selection strategy is defined as the distribution of difficulty conditional on the…
Descriptors: Psychometrics, Adaptive Testing, Test Items, Evaluation Methods