Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…

In light of the widespread adoption of technology-enhanced learning and assessment platforms, there is a growing demand for innovative, high-quality, and diverse assessment questions. Automatic Question Generation (AQG) has emerged as a valuable solution, enabling educators and assessment developers to efficiently produce a large volume of test…

Presents a variation of a "greedy" algorithm that can be used in test-assembly problems. The algorithm, the normalized weighted absolute-deviation heuristic, selects items to have a locally optimal fit to a moving set of average criterion values. Demonstrates application of the model. (SLD)

A mathematical programming approach is presented for computer adaptive testing (CAT) with many constraints on the item and test attributes. Because mathematical programming problems have to be solved while the examinee waits for the next item, a fast implementation of the Branch-and-Bound algorithm is needed for this approach. Eight modifications…

Five approaches to writing test items with computer assistance are described. A model of knowledge using a set of structures and a system for implementing the scheme are outlined. The approaches include the author-supplied approach, replacement-set procedures, computer-supplied prototype items, subject-matter mapping, and discourse analysis. (TJH)

Two zero-one linear programing models for constructing tests using classical item and test parameters are given. These models are useful, for instance, when classical test theory must serve as an interface between an item response theory-based item banking system and a test constructor unfamiliar with the underlying theory. (TJH)

New items are being calibrated for the next generation of the computerized adaptive (CAT) version of the Armed Services Vocational Aptitude Battery (ASVAB) (Forms 5 and 6). The requirements that the items be "good" three-parameter logistic (3-PL) model items and typically "like" items in the previous CAT-ASVAB tests have…

A previously developed method of automatically selecting items for inclusion in a test subject to constraints on item content and statistical properties is applied to real data. Two tests are first assembled by experts in test construction who normally assemble such tests on a routine basis. Using the same pool of items and constraints articulated…

In constrained adaptive testing, the numbers of constraints needed to control the content of the tests can easily run into the hundreds. Proper initialization of the algorithm becomes a requirement because the presence of large numbers of constraints slows down the convergence of the ability estimator. In this paper, an empirical initialization of…

Proposes an algorithm that minimizes the asymptotic variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The criterion results in a closed-form expression that is easy to evaluate. Also shows how the algorithm can be modified if the interest is in a test with a "simple ability structure."…

Nine methods for automated test construction are described. All are based on the concepts of information from item response theory. Two general kinds of methods for the construction of parallel tests are presented: (1) sequential test design; and (2) simultaneous test design. Sequential design implies that the tests are constructed one after the…

A method of automatically selecting items for inclusion in a test with constraints on item content and statistical properties was applied to real data. Tests constructed manually from the same data and constraints were compared to tests constructed automatically. Results show areas in which automated assembly can improve test construction. (SLD)

Although computerized adaptive tests acquire their efficiency by successively selecting items that provide optimal measurement at each examinee's estimated level of ability, operational testing programs will typically consider additional factors in item selection. In practice, items are generally selected with regard to at least three, often…

When the network-flow algorithm (NFA) and the average growth approximation algorithm (AGAA) were used for automated test assembly with American College Test and Armed Services Vocational Aptitude Battery item banks, results indicate that reasonable error in item parameters is not harmful for test assembly using NFA or AGAA. (SLD)

A method is presented and illustrated for simultaneously generating multiple tests with similar characteristics from the item bank by using binary programing techniques. The parallel tests are created to match an existing seed test item for item and to match user-supplied taxonomic specifications. (SLD)