The recent literature on computerized adaptive testing (CAT) has developed methods for creating CAT item pools from a large master pool. Each CAT pool is designed as a set of nonoverlapping forms reflecting the skill levels of an assumed population of test takers. This article presents a Monte Carlo method to obtain these CAT pools and discusses…

Item-exposure control in computerized adaptive testing is implemented by imposing item-ineligibility constraints on the assembly process of the shadow tests. The method resembles Sympson and Hetter's (1985) method of item-exposure control in that the decisions to impose the constraints are probabilistic. The method does not, however, require…

Developed a multilevel item response (IRT) model that allows for differences between the distributions of item parameters of families of item clones. Results from simulation studies based on an item pool from the Law School Admission Test illustrate the accuracy of the item pool calibration and adaptive testing procedures based on the model. (SLD)

The Sympson and Hetter (SH; J. Sympson and R. Hetter; 1985; 1997) method is a method of probabilistic item exposure control in computerized adaptive testing. Setting its control parameters to admissible values requires an iterative process of computer simulations that has been found to be time consuming, particularly if the parameters have to be…

Item-exposure control in computerized adaptive testing is implemented by imposing item-ineligibility constraints on the assembly process of the shadow tests. The method resembles J. Sympson and R. Hetter's (1985) method of item-exposure control in that the decisions to impose the constraints are probabilistic. However, the method does not require…

In the context of examining the feasibility and advisability of computerizing the Law School Admission Test (LSAT), a review of current literature was conducted with the following goals: (1) determining the skills that are most important in good legal reasoning according to the literature; (2) determining the extent to which existing LSAT item…

Test-item writing efforts typically results in item pools with an undesirable correlational structure between the content attributes of the items and their statistical information. If such pools are used in computerized adaptive testing (CAT), the algorithm may be forced to select items with less than optimal information, that violate the content…

Multidimensionality is known to affect the accuracy of item parameter and ability estimations, which subsequently influences the computation of item characteristic curves (ICCs) and true scores. By judiciously combining sections of a Law School Admission Test (LSAT), 11 sections of varying degrees of uni- and multidimensional structures 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…

With the increased use of computerized adaptive testing, which allows for continuous testing, new concerns about test security have evolved, one being the assurance that items in an item pool are safeguarded from theft. In this paper, the risk of score inflation and procedures to detect test takers using item preknowledge are explored. When test…

The availability of item response times made possible by computerized testing represents an entirely new type of information about test items. This study explores the issue of how to represent response-time information in item banks. Empirical response-time distribution functions can be fit with statistical distribution functions with known…