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Barrada, Juan Ramon; Olea, Julio; Ponsoda, Vicente; Abad, Francisco Jose – Applied Psychological Measurement, 2010
In a typical study comparing the relative efficiency of two item selection rules in computerized adaptive testing, the common result is that they simultaneously differ in accuracy and security, making it difficult to reach a conclusion on which is the more appropriate rule. This study proposes a strategy to conduct a global comparison of two or…
Descriptors: Test Items, Simulation, Adaptive Testing, Item Analysis
Leung, Chi-Keung; Chang, Hua-Hua; Hau, Kit-Tai – 2000
Information based item selection methods in computerized adaptive tests (CATs) tend to choose the item that provides maximum information at an examinee's estimated trait level. As a result, these methods can yield extremely skewed item exposure distributions in which items with high "a" values may be overexposed, while those with low…
Descriptors: Adaptive Testing, Computer Assisted Testing, Selection, Simulation
Leung, Chi-Keung; Chang, Hua-Hua; Hau, Kit-Tai – 2000
Item selection methods in computerized adaptive testing (CAT) can yield extremely skewed item exposure distribution in which items with high "a" values may be over-exposed while those with low "a" values may never be selected. H. Chang and Z. Ying (1999) proposed the a-stratified design (ASTR) that attempts to equalize item…
Descriptors: Adaptive Testing, Computer Assisted Testing, Selection, Test Construction
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Chang, Hua-Hua; Zhang, Jinming – Psychometrika, 2002
Demonstrates mathematically that if every item in an item pool has an equal possibility to be selected from the pool in a fixed-length computerized adaptive test, the number of overlapping items among an alpha randomly sampled examinees follows the hypergeometric distribution family for alpha greater than or equal to 1. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Selection
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Revuelta, Javier; Ponsoda, Vicente – Journal of Educational Measurement, 1998
Proposes two new methods for item-exposure control, the Progressive method and the Restricted Maximum Information method. Compares both methods with six other item-selection methods. Discusses advantages of the two new methods and the usefulness of combining them. (SLD)
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Selection
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Chen, Shu-Ying; Ankenmann, Robert D.; Chang, Hua-Hua – Applied Psychological Measurement, 2000
Compared five item selection rules with respect to the efficiency and precision of trait (theta) estimation at the early stages of computerized adaptive testing (CAT). The Fisher interval information, Fisher information with a posterior distribution, Kullback-Leibler information, and Kullback-Leibler information with a posterior distribution…
Descriptors: Adaptive Testing, Computer Assisted Testing, Estimation (Mathematics), Selection
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Meijer, Rob R.; Nering, Michael L. – Applied Psychological Measurement, 1999
Provides an overview of computerized adaptive testing (CAT) and introduces contributions to this special issue. CAT elements discussed include item selection, estimation of the latent trait, item exposure, measurement precision, and item-bank development. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Selection
Thompson, Tony D.; Davey, Tim – 2000
This paper applies specific information item selection using a method developed by T. Davey and M. Fan (2000) to a multiple-choice passage-based reading test that is being developed for computer administration. Data used to calibrate the multidimensional item parameters for the simulation study consisted of item responses from randomly equivalent…
Descriptors: Adaptive Testing, Computer Assisted Testing, Reading Tests, Selection
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Schnipke, Deborah L.; Green, Bert F. – Journal of Educational Measurement, 1995
Two item selection algorithms, one based on maximal differentiation between examinees and one based on item response theory and maximum information for each examinee, were compared in simulated linear and adaptive tests of cognitive ability. Adaptive tests based on maximum information were clearly superior. (SLD)
Descriptors: Adaptive Testing, Algorithms, Comparative Analysis, Item Response Theory
Leung, Chi-Keung; Chang, Hua-Hua; Hau, Kit-Tai – 2001
The multistage alpha-stratified computerized adaptive testing (CAT) design advocated a new philosophy of pool management and item selection using low discriminating items first. It has been demonstrated through simulation studies to be effective both in reducing item overlap rate and enhancing pool utilization with certain pool types. Based on…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Selection
Tang, K. Linda – 1996
The average Kullback-Keibler (K-L) information index (H. Chang and Z. Ying, in press) is a newly proposed statistic in Computerized Adaptive Testing (CAT) item selection based on the global information function. The objectives of this study were to improve understanding of the K-L index with various parameters and to compare the performance of the…
Descriptors: Ability, Adaptive Testing, Comparative Analysis, Computer Assisted Testing
Berger, Martijn P. F.; Veerkamp, Wim J. J. – 1994
The designing of tests has been a source of concern for test developers over the past decade. Various kinds of test forms have been applied. Among these are the fixed-form test, the adaptive test, and the testlet. Each of these forms has its own design. In this paper, the construction of test forms is placed within the general framework of optimal…
Descriptors: Adaptive Testing, Foreign Countries, Research Design, Selection
Parshall, Cynthia G.; Davey, Tim; Nering, Mike L. – 1998
When items are selected during a computerized adaptive test (CAT) solely with regard to their measurement properties, it is commonly found that certain items are administered to nearly every examinee, and that a small number of the available items will account for a large proportion of the item administrations. This presents a clear security risk…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Efficiency
Weissman, Alexander – 2003
This study investigated the efficiency of item selection in a computerized adaptive test (CAT), where efficiency was defined in terms of the accumulated test information at an examinee's true ability level. A simulation methodology compared the efficiency of 2 item selection procedures with 5 ability estimation procedures for CATs of 5, 10, 15,…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Maximum Likelihood Statistics
Stocking, Martha L.; Lewis, Charles – 1995
In the periodic testing environment associated with conventional paper-and-pencil tests, the frequency with which items are seen by test-takers is tightly controlled in advance of testing by policies that regulate both the reuse of test forms and the frequency with which candidates may take the test. In the continuous testing environment…
Descriptors: Adaptive Testing, Computer Assisted Testing, Selection, Test Construction
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