Performed a simulation study to demonstrate the dramatic impact of capitalization on estimation errors on ability estimation in adaptive testing. Discusses four different strategies to minimize the likelihood of capitalization in computerized adaptive testing. (SLD)

A new computerized mastery test is described that builds on the Lewis and Sheehan procedure (sequential testlets) (1990), but uses fuzzy set decision theory to determine stopping rules and the Rasch model to calibrate items and estimate abilities. Differences between fuzzy set and Bayesian methods are illustrated through an example. (SLD)

Effects of self-adapted testing (SAT), in which examinees choose the difficulty of items themselves, on ability estimates, precision, and efficiency, mechanisms of SAT effects, and examinee reactions to SAT are reviewed. SAT, which is less efficient than computer-adapted testing, is more efficient than fixed-item testing. (SLD)

A study involving 1,000 simulated examinees compared the partial credit and graded response models in computerized adaptive testing (CAT). The graded response model fit the data well and provided slightly more accurate ability estimates than those of the partial credit model. Benefits of polytomous model-based CATs are discussed. (SLD)

Vocabulary fixed-item (FIT), computerized-adaptive (CAT), and self-adapted (SAT) tests were compared with 121 college students. CAT was more precise and efficient than SAT, which was more precise and efficient than FIT. SAT also yielded higher ability estimates for individuals with lower verbal self-concepts. (SLD)

A model-testing approach for evaluating the stability of item response theory item parameter estimates (IPEs) in a pretest-posttest design is illustrated. Nineteen items from the Head Start Measures Battery were used. A moderately high degree of stability in the IPEs for 5,510 children assessed on 2 occasions was found. (TJH)