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He, Wei; Reckase, Mark D. – Educational and Psychological Measurement, 2014
For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution…
Descriptors: Item Banks, Test Length, Computer Assisted Testing, Adaptive Testing
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van der Linden, Wim J. – Journal of Educational and Behavioral Statistics, 1999
Proposes an algorithm that minimizes the asymptotic variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The criterion results in a closed-form expression that is easy to evaluate. Also shows how the algorithm can be modified if the interest is in a test with a "simple ability structure."…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
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
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Ban, Jae-Chun; Hanson, Bradley A.; Yi, Qing; Harris, Deborah J. – Journal of Educational Measurement, 2002
Compared three online pretest calibration scaling methods through simulation: (1) marginal maximum likelihood with one expectation maximization (EM) cycle (OEM) method; (2) marginal maximum likelihood with multiple EM cycles (MEM); and (3) M. Stocking's method B. MEM produced the smallest average total error in parameter estimation; OEM yielded…
Descriptors: Computer Assisted Testing, Error of Measurement, Maximum Likelihood Statistics, Online Systems
Glas, Cees A. W.; van der Linden, Wim J. – 2001
To reduce the cost of item writing and to enhance the flexibility of item presentation, items can be generated by item-cloning techniques. An important consequence of cloning is that it may cause variability on the item parameters. Therefore, a multilevel item response model is presented in which it is assumed that the item parameters of a…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Costs
Shermis, Mark D.; And Others – 1992
The reliability of four branching algorithms commonly used in computer adaptive testing (CAT) was examined. These algorithms were: (1) maximum likelihood (MLE); (2) Bayesian; (3) modal Bayesian; and (4) crossover. Sixty-eight undergraduate college students were randomly assigned to one of the four conditions using the HyperCard-based CAT program,…
Descriptors: Adaptive Testing, Algorithms, Bayesian Statistics, Comparative Analysis
Maurelli, Vincent A.; Weiss, David J. – 1981
A monte carlo simulation was conducted to assess the effects in an adaptive testing strategy for test batteries of varying subtest order, subtest termination criterion, and variable versus fixed entry on the psychometric properties of an existent achievement test battery. Comparisons were made among conventionally administered tests and adaptive…
Descriptors: Achievement Tests, Adaptive Testing, Computer Assisted Testing, Latent Trait Theory
Xiao, Beiling – 1990
Dichotomous search strategies (DSSs) for computerized adaptive testing are similar to golden section search strategies (GSSSs). Each middle point of successive search regions is a testing point. After each item is administered, the subject's obtained score is compared with the expected score at successive testing points. If the subject's obtained…
Descriptors: Ability Identification, Adaptive Testing, Computer Assisted Testing, Equations (Mathematics)
Patience, Wayne M.; Reckase, Mark D. – 1979
An experiment was performed with computer-generated data to investigate some of the operational characteristics of tailored testing as they are related to various provisions of the computer program and item pool. With respect to the computer program, two characteristics were varied: the size of the step of increase or decrease in item difficulty…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Error of Measurement