Educational testing has been criticized for its disconnect from modern cognitive science and its limited role in improving instruction and student learning. Reform efforts emphasize the need for testing to provide specific diagnostic insights into students' skills and knowledge. Cognitive diagnosis (CD), an emerging paradigm in educational…

Much research has been devoted to identification of differential item functioning (DIF), which occurs when the item responses for individuals from two groups differ after they are conditioned on the latent trait being measured by the scale. There has been less work examining differential step functioning (DSF), which is present for polytomous…

Estimation of parameters for the many-facets Rasch model requires that conditional on the values of the facets, such as person ability, item difficulty, and rater severity, the observed responses within each facet are independent. This requirement has often been discussed for the Rasch models and 2PL and 3PL models, but it becomes more complex…

This article presents the performance of item response theory (IRT) models when double ratings are used as item scores over single ratings when rater effects are present. Study 1 examined the influence of the number of ratings on the accuracy of proficiency estimation in the generalized partial credit model (GPCM). Study 2 compared the accuracy of…

Testing item fit is central in item response theory (IRT) modeling, since a good fit is necessary to draw valid inferences from estimated model parameters. "Infit" and "outfit" fit statistics, widespread indices for detecting deviations from the Rasch model, are affected by data factors, such as sample size. Consequently, the…

In applications of item response theory (IRT) models, it is known that empirical violations of the local independence (LI) assumption can significantly bias parameter estimates. To address this issue, we propose a threshold-autoregressive item response theory (TAR-IRT) model that additionally accounts for order dependence among the item responses…

The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…

Mixture IRT models address the heterogeneity in a population by extracting latent classes and allowing item parameters to vary between latent classes. Once the latent classes are extracted, they need to be further examined to be characterized. Some approaches have been adopted in the literature for this purpose. These approaches examine either the…

Multiple choice results are inherently probabilistic outcomes, as correct responses reflect a combination of knowledge and guessing, while incorrect responses additionally reflect blunder, a confidently committed mistake. To objectively resolve knowledge from responses in an MC test structure, we evaluated probabilistic models that explicitly…

Assessments built on a theory of learning progressions are promising formative tools to support learning and teaching. The quality and usefulness of those assessments depend, in large part, on the validity of the theory-informed inferences about student learning made from the assessment results. In this study, we introduced an approach to address…

Unmotivated test takers using rapid guessing in item responses can affect validity studies and teacher and institution performance evaluation negatively, making it critical to identify these test takers. The authors propose a new nonparametric method for finding response-time thresholds for flagging item responses that result from rapid-guessing…

The usefulness of item response theory (IRT) models depends, in large part, on the accuracy of item and person parameter estimates. For the standard 3 parameter logistic model, for example, these parameters include the item parameters of difficulty, discrimination, and pseudo-chance, as well as the person ability parameter. Several factors impact…

Current procedures for equating number-correct scores using traditional item response theory (IRT) methods assume local independence. However, when tests are constructed using testlets, one concern is the violation of the local item independence assumption. The testlet response theory (TRT) model is one way to accommodate local item dependence.…

Applications of traditional unidimensional item response theory models to passage-based reading comprehension assessment data have been criticized based on potential violations of local independence. However, simple rules for determining dependency, such as including all items associated with a particular passage, may overestimate the dependency…

This study compared several exposure control procedures for CAT systems based on the three-parameter logistic testlet response theory model (Wang, Bradlow, & Wainer, 2002) and Masters' (1982) partial credit model when applied to a pool consisting entirely of testlets. The exposure control procedures studied were the modified within 0.10 logits…