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PDF pending restorationVale, C. David; Weiss, David J. – 1977
An alternative item-selection procedure for use with Owen's Bayesian adaptive testing strategy is proposed. This procedure is, by design, faster than Owen's original procedure because it searches only part of the total item pool. Item selections are, however, identical for both methods. After a conceptual development of the rapid-search procedure,…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Programs, Item Banks
Download full textGeorge, Archie A. – 1979
The appropriateness of the use of the standardized residual (SR) to assess congruence between sample test item responses and the one parameter latent trait (Rasch) item characteristic curve is investigated. Latent trait theory is reviewed, as well as theory of the SR, the apparent error in calculating the expected distribution of the SR, and…
Descriptors: Academic Ability, Computer Programs, Difficulty Level, Goodness of Fit
PDF pending restorationCivil Service Commission, Washington, DC. Personnel Research and Development Center. – 1976
This pamphlet reprints three papers and an invited discussion of them, read at a Division 5 Symposium at the 1975 American Psychological Association Convention. The first paper describes a Bayesian tailored testing process and shows how it demonstrates the importance of using test items with high discrimination, low guessing probability, and a…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Oriented Programs, Computer Programs
Patience, Wayne M.; Reckase, Mark D. – 1979
Simulated tailored tests were used to investigate the relationships between characteristics of the item pool and the computer program, and the reliability and bias of the resulting ability estimates. The computer program was varied to provide for various step sizes (differences in difficulty between successive steps) and different acceptance…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Programs, Educational Testing
Cliff, Norman; And Others – 1977
TAILOR is a computer program that uses the implied orders concept as the basis for computerized adaptive testing. The basic characteristics of TAILOR, which does not involve pretesting, are reviewed here and two studies of it are reported. One is a Monte Carlo simulation based on the four-parameter Birnbaum model and the other uses a matrix of…
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Programs, Difficulty Level
