Presents a constrained computerized adaptive testing (CAT) algorithm that can be used to equate CAT number-correct scores to a reference test. Used an item bank from the Law School Admission Test to compare results of the algorithm with those for equipercentile observed-score equating. Discusses advantages of the approach. (SLD)

Considers computerized adaptive testing from the perspective of graphical modeling (GM). GM provides methods for making inferences about multifaceted skills and knowledge and for extracting data from complex performances. Provides examples from language-proficiency assessment. (SLD)

Evaluates a method for item selection in adaptive testing that is based on Kullback-Leibler information (KLI) (T. Cover and J. Thomas, 1991). Simulation study results show that testing algorithms using KLI-based item selection perform better than or as well as those using Fisher information item selection. (SLD)

Chang and Zhang (2002, 2003) proposed several baseline criteria for assessing the severity of possible test security violations for computerized tests with high-stakes outcomes. However, these criteria were obtained from theoretical derivations that assumed uniformly randomized item selection. The current study investigated potential damage caused…

If examinees are permitted to choose to answer a subset of the questions on a test, just knowing which questions were chosen can provide a measure of proficiency that may be as reliable as would have been obtained from the test graded traditionally. This new method of scoring is much less time consuming and expensive for both the examinee and the…

An alternative item-selection procedure for use with Owen's Bayesian adaptive testing strategy is proposed. This procedure is, by design, faster than Owen's original procedure because it searches only part of the total item pool. Item selections are, however, identical for both methods. After a conceptual development of the rapid-search procedure,…

This paper presents an approach to item pool design that has the potential to improve on the quality of current item pools in educational and psychological testing and thus to increase both measurement precision and validity. The approach consists of the application of mathematical programming techniques to calculate optimal blueprints for item…

Several methods have been developed for use on constrained adaptive testing. Item pool partitioning, multistage testing, and testlet-based adaptive testing are methods that perform well for specific cases of adaptive testing. The weighted deviation model and the Shadow Test approach can be more generally applied. These methods are based on…

Preventing items in adaptive testing from being over- or underexposed is one of the main problems in computerized adaptive testing. Though the problem of overexposed items can be solved using a probabilistic item-exposure control method, such methods are unable to deal with the problem of underexposed items. Using a system of rotating item pools,…

This report contains a review of procedures for computerized assembly of linear, sequential, and adaptive tests. The common approach to these test assembly problems is to view them as instances of constrained combinatorial optimization. For each testing format, several potentially useful objective functions and types of constraints are discussed.…

Most large-scale testing programs facing computerized adaptive testing (CAT) must face the challenge of maintaining extensive content requirements, but content constraints in computerized adaptive testing (CAT) can compromise the precision and efficiency that could be achieved by a pure maximum information adaptive testing algorithm. This…

To satisfy the security requirements of computerized adaptive tests (CATs), efforts have been made to control the exposure rates of optimal items directly by incorporating statistical methods into the item selection procedure. Since differences are likely to occur between the exposure control parameter derivation stage and the operational CAT…

In computerized adaptive testing, updating item parameter estimates using adaptive testing data is often called online calibration. This study investigated how to evaluate whether the adaptive testing data used for online calibration sufficiently fit the item response model used. Three approaches were investigated, based on a Lagrange multiplier…

Information based item selection methods in computerized adaptive tests (CATs) tend to choose the item that provides maximum information at an examinee's estimated trait level. As a result, these methods can yield extremely skewed item exposure distributions in which items with high "a" values may be overexposed, while those with low…

The purpose of this study was to compare a proposed revised a-stratified, or alpha-stratified, USTR method of test item selection with the original alpha-stratified multistage computerized adaptive testing approach (STR) and the use of maximum Fisher information (FSH) with respect to test efficiency and item pool usage using simulated computerized…