This simulation study examines the measurement precision, item exposure rates, and the depth of the MAP® Growth™ item pools under various grade-level restrictions. Unlike most summative assessments, MAP Growth allows examinees to see items from any grade level, regardless of the examinee's actual grade level. It does not limit the test to items…

Imposed time limits on computer adaptive tests (CATs) can result in examinees having difficulty completing all items, thus compromising the validity and reliability of ability estimates. In this study, the effects of speededness were explored in a simulated CAT environment by varying examinee response patterns to end-of-test items. Expectedly,…

In adaptive testing, item selection is sequentially optimized during the test. Since the optimization takes place over a pool of items calibrated with estimation error, capitalization on these errors is likely to occur. How serious the consequences of this phenomenon are depends not only on the distribution of the estimation errors in the pool or…

This paper examines some characteristics of the statistics associated with the sampling distribution of the proficiency level estimate when the Rasch model is used. These characteristics allow the judgment of the meaning to be given to the proficiency level estimate obtained in adaptive testing, and as a consequence, they can illustrate the…

Error indices (bias, standard error of estimation, and root mean square error) obtained on different scales of measurement under different test termination rules in a computerized adaptive test (CAT) context were examined. Four ability estimation methods were studied: (1) maximum likelihood estimation (MLE); (2) weighted likelihood estimation…

R. J. Owen (1975) proposed an approximate empirical Bayes procedure for item selection in adaptive testing. The procedure replaces the true posterior by a normal approximation with closed-form expressions for its first two moments. This approximation was necessary to minimize the computational complexity involved in a fully Bayesian approach, but…

Replenishing item pools for on-line ability testing requires innovative and efficient data collection. A method is proposed to collect test item calibration data in an on-line testing environment sequentially using locally D-optimum designs, thereby achieving high Fisher information for the item parameters. (SLD)

A broad-range tailored test of verbal ability, appropriate at any level from fifth grade upwards, is briefly described. The test score places persons at all levels directly on the same score scale. (Author/RC)

Effects of altering test difficulty on examinee ability measures and test length in a computer adaptive test were studied for 225 medical technology students in 3 test difficulty conditions. Results suggest that, with an item pool of sufficient depth and breadth, acceptable targeting to test difficulty is possible. (SLD)