In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…

Formulates optimal sequential rules for mastery testing using an approach derived from Bayesian sequential decision theory to consider both threshold and linear loss structures. Adopts the binomial probability distribution as the psychometric model. Provides an empirical example for concept-learning in medicine. (SLD)

During the last decade the use of Bayesian statistical method has become quite prevalent in the educational community. Yet, like most statistical techniques, little has been written concerning the application of these methods to the classroom setting. The purpose of this paper is to help correct such a deficiency in the literature by developing a…

In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)

A coherent system of decision making is described that may be incorporated into an instructional sequence to provide a supplement to the experience-based judgment of the classroom teacher. The elements of this decision process incorporate prior information such as a teacher's past experience, experimental results such as a test score, and…

Several Bayesian approaches to the simultaneous estimation of the means of k binomial populations are discussed. This has particular applicability to criterion-referenced or mastery testing. (Author/JKS)

A version of sequential mastery testing is studied in which response behavior is modeled by an item response theory (IRT) model. First, a general theoretical framework is sketched that is based on a combination of Bayesian sequential decision theory and item response theory. A discussion follows on how IRT based sequential mastery testing can be…

A Bayesian framework for making mastery/nonmastery decisions based on multivariate test data is described. Overall, mastery is granted if the posterion expected loss associated with such action is smaller than the one incurred by denying mastery. (Author/JKS)

A general framework for making mastery/nonmastery decisions based on multivariate test data is described in this study. Over all, mastery is granted (or denied) if the posterior expected loss associated with such action is smaller than the one incurred by the denial (or grant) of mastery. An explicit form for the cutting contour which separates…

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)

False-positive and false-negative decisions are the two possible errors committed with a mastery test; yet the estimation of the likelihood of committing these errors has not been investigated. Two methods of this type of estimation are presented and discussed. (Author/JKS)

The Bayesian approach to setting passing points on credentialing examinations in the health fields is considered in the context of the Normal model, and examples are given to demonstrate the procedure. An application to a credentialing examination, to determine a rational passing point, is presented. (Author/MH)

The Libby-Novick class of three-parameter generalized beta distributions is shown to provide a rich class of prior distributions for the binomial model that removes some restrictions of the standard beta class. A numerical example indicates the desirability of using these wider classes of densities for binomial models. (Author/BW)

The purpose of this paper is to formulate optimal sequential rules for mastery tests. The framework for this approach is derived from empirical Bayesian decision theory. Both a threshold and linear loss structure are considered. The binomial probability distribution is adopted as the psychometric model involved. Conditions sufficient for…

This paper focuses on a version of sequential mastery testing (i.e., classifying students as a master/nonmaster or continuing testing and administering another item or testlet) in which response behavior is modeled by a multidimensional item response theory (IRT) model. First, a general theoretical framework is outlined that is based on a…