In a typical study comparing the relative efficiency of two item selection rules in computerized adaptive testing, the common result is that they simultaneously differ in accuracy and security, making it difficult to reach a conclusion on which is the more appropriate rule. This study proposes a strategy to conduct a global comparison of two or…

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…

Item selection methods in computerized adaptive testing (CAT) can yield extremely skewed item exposure distribution in which items with high "a" values may be over-exposed while those with low "a" values may never be selected. H. Chang and Z. Ying (1999) proposed the a-stratified design (ASTR) that attempts to equalize item…

Demonstrates mathematically that if every item in an item pool has an equal possibility to be selected from the pool in a fixed-length computerized adaptive test, the number of overlapping items among an alpha randomly sampled examinees follows the hypergeometric distribution family for alpha greater than or equal to 1. (SLD)

Proposes two new methods for item-exposure control, the Progressive method and the Restricted Maximum Information method. Compares both methods with six other item-selection methods. Discusses advantages of the two new methods and the usefulness of combining them. (SLD)

Compared five item selection rules with respect to the efficiency and precision of trait (theta) estimation at the early stages of computerized adaptive testing (CAT). The Fisher interval information, Fisher information with a posterior distribution, Kullback-Leibler information, and Kullback-Leibler information with a posterior distribution…

Provides an overview of computerized adaptive testing (CAT) and introduces contributions to this special issue. CAT elements discussed include item selection, estimation of the latent trait, item exposure, measurement precision, and item-bank development. (SLD)

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…

This paper applies specific information item selection using a method developed by T. Davey and M. Fan (2000) to a multiple-choice passage-based reading test that is being developed for computer administration. Data used to calibrate the multidimensional item parameters for the simulation study consisted of item responses from randomly equivalent…

The multistage alpha-stratified computerized adaptive testing (CAT) design advocated a new philosophy of pool management and item selection using low discriminating items first. It has been demonstrated through simulation studies to be effective both in reducing item overlap rate and enhancing pool utilization with certain pool types. Based on…

The average Kullback-Keibler (K-L) information index (H. Chang and Z. Ying, in press) is a newly proposed statistic in Computerized Adaptive Testing (CAT) item selection based on the global information function. The objectives of this study were to improve understanding of the K-L index with various parameters and to compare the performance of the…

When items are selected during a computerized adaptive test (CAT) solely with regard to their measurement properties, it is commonly found that certain items are administered to nearly every examinee, and that a small number of the available items will account for a large proportion of the item administrations. This presents a clear security risk…

The purpose of many certification or licensure tests is to identify candidates who possess some level of minimum competence to practice their profession. In general, this type of test is referred to as classification testing. When this type of test is administered with a computer, the test is a computerized classification test (CCT). This paper…

This study investigated the efficiency of item selection in a computerized adaptive test (CAT), where efficiency was defined in terms of the accumulated test information at an examinee's true ability level. A simulation methodology compared the efficiency of 2 item selection procedures with 5 ability estimation procedures for CATs of 5, 10, 15,…

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)