Testing programs have explored the use of technology-enhanced items alongside traditional item types (e.g., multiple-choice and constructed-response items) as measurement evidence of latent constructs modeled with item response theory (IRT). In this report, we discuss considerations in applying IRT models to a particular type of adaptive testlet…

This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…

This study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent…

The sequential probability ratio test (SPRT) is a common method for terminating item response theory (IRT)-based adaptive classification tests. To decide whether a classification test should stop, the SPRT compares a simple log-likelihood ratio, based on the classification bound separating two categories, to prespecified critical values. As has…

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm…

Computerized adaptive testing (CAT) enables efficient and flexible measurement of latent constructs. The majority of educational and cognitive measurement constructs are based on dichotomous item response theory (IRT) models. An integral part of developing various components of a CAT system is conducting simulations using both known and empirical…

The use of new test administration technologies such as computerized adaptive testing in high-stakes educational and occupational assessments demands large item pools. Classic item construction processes and previous approaches to automatic item generation faced the problems of a considerable loss of items after the item calibration phase. In this…

The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…

In a test, the testing score would be closer to examinee's actual ability when careless mistakes were corrected. In CAT, however, changing the answer of one item in CAT might cause the following items no longer appropriate for estimating the examinee's ability. These inappropriate items in a reviewable CAT might in turn introduce bias in ability…

If classification in a limited number of categories is the purpose of testing, computerized adaptive tests (CATs) with algorithms based on sequential statistical testing perform better than estimation-based CATs (e.g., Eggen & Straetmans, 2000). In these computerized classification tests (CCTs), the Sequential Probability Ratio Test (SPRT) (Wald,…

This article extends the work by Armstrong and Shi on CUmulative SUM (CUSUM) person-fit methodology. The authors present new theoretical considerations concerning the use of CUSUM person-fit statistics based on likelihood ratios for the purpose of detecting cheating and random guessing by individual test takers. According to the Neyman-Pearson…

The generalized graded unfolding model (GGUM) has been recently developed to describe item responses to Likert items (agree-disagree) in attitude measurement. In this study, the authors (a) developed two item selection methods in computerized classification testing under the GGUM, the current estimate/ability confidence interval method and the cut…

This study investigates the effect of fitting a unidimensional IRT model to multidimensional data in content-balanced computerized adaptive testing (CAT). Unconstrained CAT with the maximum information item selection method is chosen as the baseline, and the performances of three content balancing procedures, the constrained CAT (CCAT), the…

Item response theory (IRT) and related latent variable models represent modern psychometric theory, the successor to classical test theory in psychological assessment. Although IRT has become prevalent in the measurement of ability and achievement, its contributions to clinical domains have been less extensive. Applications of IRT to clinical…

This study investigates measurement decision theory (MDT) as an underlying model for computer adaptive testing when the goal is to classify examinees into one of a finite number of groups. The first analysis compares MDT with a popular item response theory model and finds little difference in terms of the percentage of correct classifications. The…