A decision-theoretic procedure is outlined which provides a framework within which Bayesian statistical methods can be employed with criterion-referenced tests to improve the quality of decision making in objectives based instructional programs. (Author/DEP)

This paper describes two procedures for making binary classification decisions using tailored testing: the sequential probability ratio test (SPRT) and a Bayesian decision procedure. The first procedure described, the SPRT, was developed by Wald for quality control work. It has not been widely applied for testing applications because the…

The issues of treatment assignment is ordinarily dealt with within the framework of testing aptitude treatment interaction (ATI) hypothesis. ATI research mostly uses linear regression techniques, and an ATI exists when the aptitude treatment (AT) regression lines cross each other within the relevant interval of the aptitude variable. Consistent…

The philosophy and assumptions of the Multi-Attribute Utility-Bayesian Decision Theoretic model (MAUT-Bayesian model) are presented. The evaluator uses the MAUT-Bayesian model along with the knowledge of the decision-maker's, and perhaps the evaluator's own values to decide what data should be collected. Appropriate data are presented to the…

A computer simulation of Bayes' Theorem was conducted in order to determine the probability that an examinee was a master conditional upon his test score. The inputs were: number of mastery states assumed, test length, prior expectation of masters in the examinee population, and conditional probability of a master getting a randomly selected test…

The economic utility of the following 5 weighting methods for evaluating consumer loan applications was determined using a sample of 443 loans: (1) unit; (2) weighted application blank; (3) chi square; (4) Bayes; and (5) regression. The unit and weighted application blank procedures were the best approaches. (SLD)

We consider human performance on an optimal stopping problem where people are presented with a list of numbers independently chosen from a uniform distribution. People are told how many numbers are in the list, and how they were chosen. People are then shown the numbers one at a time, and are instructed to choose the maximum, subject to the…

Differences between traditional linear regression and a Bayesian approach to classification are discussed. Classification consists of assigning subjects to one of several available treatments on the basis of their test scores when the success of each treatment is measured by a different criterion. Formulating this problem as an empirical Bayes…

This research follows up a study conducted in 1998 by the National Foundation for Educational Research (NFER) to investigate teachers' and students' views on the factors affecting students' choices of whether or not to apply to Oxford and Cambridge universities. It identifies what has changed since 1998 and areas in which the universities could…

The decision making processes of children in a probabilistic environment were studied within the context of the theory of signal detection (TSD). The relationship between the age of the child and his ability to revise decision criteria was examined, as well as the appropriateness of TSD measures and methodology with children. It was hypothesized…

The assumptions of the Criterion-Referenced Test (CRT) model proposed by Kriewall are compared to those of Emrick and Adam's Mastery-Learning (ML) model. Testing, in the context of instructional management, serves three general purposes: performance evaluation (achievement of objectives), placement (classification of students for instruction), and…

A Markov model for predicting performance on criterion-referenced tests is presented,. The model is expressed mathematically as a function of transition matrix, a current state vector, and a future state vector. The matrix is defined in terms of conditional probabilities, i.e., the probability of making a transition to a specific future…

Comments are made on the review papers presented by six Dutch psychometricians: Ivo Molenaar, Wim van der Linden, Ed Roskam, Arnold Van den Wollenberg, Gideon Mellenbergh, and Dato de Gruijter. Molenaar has embraced a pragmatic viewpoint on Bayesian methods, using both empirical and pure approaches to solve educational research problems. Molenaar…

This project is concerned with the development and implementation of some new statistical techniques that will facilitate a continuing input of information about the student to the instructional manager so that individualization of instruction can be managed effectively. The source of this informational input is typically a short…

The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Four basic decision problems are distinguished: (1) selection; (2) mastery; (3) placement; and (4) classification, the situation where each treatment has its own criterion. Each type of decision can be identified as a specific configuration of one or…