This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback-Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions. When item separation was…

In the human sciences, a common assumption is that latent traits have a hierarchical structure. Higher order item response theory models have been developed to account for this hierarchy. In this study, computerized adaptive testing (CAT) algorithms based on these kinds of models were implemented, and their performance under a variety of…

This study examined the performance of the maximum Fisher's information, the maximum posterior weighted information, and the minimum expected posterior variance methods for selecting items in a computerized adaptive testing system when the items were grouped in testlets. A simulation study compared the efficiency of ability estimation among the…

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…

Item selection is a core component in computerized adaptive testing (CAT). Several studies have evaluated new and classical selection methods; however, the few that have applied such methods to the use of polytomous items have reported conflicting results. To clarify these discrepancies and further investigate selection method properties, six…

Assessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC…

Criteria had been proposed for assessing the severity of possible test security violations for computerized tests with high-stakes outcomes. However, these criteria resulted from theoretical derivations that assumed uniformly randomized item selection. This study investigated potential damage caused by organized item theft in computerized adaptive…

Computerized adaptive testing is subject to security problems, as the item bank content remains operative over long periods and administration time is flexible for examinees. Spreading the content of a part of the item bank could lead to an overestimation of the examinees' trait level. The most common way of reducing this risk is to impose a…

Content balancing is an important issue in the design and implementation of computerized adaptive testing (CAT). Content-balancing techniques that have been applied in fixed content balancing, where the number of items from each content area is fixed, include constrained CAT (CCAT), the modified multinomial model (MMM), modified constrained CAT…

Item exposure control, test-overlap minimization, and the efficient use of item pool are some of the important issues in computerized adaptive testing (CAT) designs. The overexposure of some items and high test-overlap rate may cause both item and test security problems. Previously these problems associated with the maximum information (Max-I)…

In the present study, a procedure that has been used to select dichotomous items in computerized adaptive testing was applied to polytomous items. This procedure was designed to select the item with maximum weighted information. In a simulation study, the item information function was integrated over a fixed interval of ability values and the item…

Computerized adaptive tests (CATs) are individualized tests that, from a measurement point of view, are optimal for each individual, possibly under some practical conditions. In the present study, it is shown that maximum information item selection in CATs using an item bank that is calibrated with the one- or the two-parameter logistic model…

Multidimensional adaptive testing (MAT) procedures are proposed for the measurement of several latent traits by a single examination. Bayesian latent trait estimation and adaptive item selection are derived. Simulations were conducted to compare the measurement efficiency of MAT with those of unidimensional adaptive testing and random…

A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level ([theta]) estimation and vice versa. When discrepancies exist between an examinee's estimated and true [theta] levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with…

To determine which produced the most accurate item parameter estimates, four methods of item response theory were evaluated: (1) heuristic estimates; (2) the ANCILLES program; (3) the LOGIST program; and (4) the ASCAL program. LOGIST and ASCAL produced estimates of superior and essentially equivalent accuracy. (SLD)