This study examined three statistical methods for selecting items for mastery tests. One is the pretest-posttest method due to Cox and Vargas (1966); it is computationally simple, but has a number of serious limitations. The second is a latent trait method recommended by van der Linden (1981); it is computationally complex, but has a number of…

The study compared two promising item response theory (IRT) item-selection methods, optimal and content-optimal, with two non-IRT item selection methods, random and classical, for use in fixed-length certification exams. The four methods were used to construct 20-item exams from a pool of approximately 250 items taken from a 1985 certification…

This paper presents an introduction to the use of latent trait models for the estimation of domain scores. It was shown that these models provided an advantage over classical test theory and binomial error models in that unbiased estimates of true domain scores could be obtained even when items were not randomly selected from a universe of items.…

Four discrimination indices were compared, using score distributions which were normal, bimodal, and negatively skewed. The score distributions were systematically varied to represent the common circumstances of a military training situation using criterion-referenced mastery tests. Three 20-item tests were administered to 110 simulated subjects.…

This meta-analysis of 49 comparative studies shows that mastery testing has positive effects on student learning, but the size of effect depends on the stringency of the criterion used and the degree of experimental control. The effects of instructional time, student attitudes, and differences in ability levels are also addressed. (Author/LRW)

The sequential probability ratio test (SPRT), developed by Abraham Wald, is one statistical model available for making mastery decisions during computer-based criterion referenced tests. The predictive validity of the SPRT was empirically investigated with two different and relatively large item pools with heterogeneous item parameters. Graduate…