The case of adaptive testing under a multidimensional logistic response model is addressed. An adaptive algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The item selection criterion is a simple expression in closed form. In addition, it is…

The designing of tests has been a source of concern for test developers over the past decade. Various kinds of test forms have been applied. Among these are the fixed-form test, the adaptive test, and the testlet. Each of these forms has its own design. In this paper, the construction of test forms is placed within the general framework of optimal…

An item-selection algorithm to neutralize the differential effects of time limits on scores on computerized adaptive tests is proposed. The method is based on a statistical model for the response-time distributions of the examinees on items in the pool that is updated each time a new item has been administered. Predictions from the model are used…

A model for constrained computerized adaptive testing is proposed in which the information in the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum information at the current ability estimate fixing…

In this study some alternative item selection criteria for adaptive testing are proposed. These criteria take into account the uncertainty of the ability estimates. A general weighted information criterion is suggested of which the usual maximum information criterion and the suggested alternative criteria are special cases. A simulation study was…