Polynomial algorithms are presented that are used to solve selected problems in test theory, and computational results from sample problems with several hundred decision variables are provided that demonstrate the benefits of these algorithms. The algorithms are based on optimization theory in networks (graphs). (SLD)

The second response conditional probability model of decision-making strategies used by examinees answering multiple choice test items was revised. Increasing the number of distractors or providing distractors giving examinees (N=106) the option to follow the model improved results and gave a good fit to data for 29 of 30 items. (SLD)

It has previously been shown by M. Beller (1990) that an additive tree (Addtree, a hierarchical tree representation of similarity data developed by S. Sattath and A. Tversky in 1977), may be useful for representing the structure between tests and items through the similarity among them as measured by their intercorrelations. In this study, the…

Four discussions of test construction based on item response theory (IRT) are presented. The first discussion, "Test Design as Model Building in Mathematical Programming" (T. J. J. M. Theunissen), presents test design as a decision process under certainty. A natural way of modeling this process leads to mathematical programming. General…

Mastery tests are analyzed in terms of the number of skills to be mastered and the number of items per skill, in order that correct decisions of mastery or nonmastery will be made to a desired degree of probability. It is assumed that a random sample of skills will be selected for measurement, that each skill will be measured by the same number of…