Multidimensional achievement tests are recently gaining more importance in educational and psychological measurements. For example, multidimensional diagnostic tests can help students to determine which particular domain of knowledge they need to improve for better performance. To estimate the characteristics of candidate items (calibration) for…

Most existing diagnostic models are developed to detect whether students have mastered a set of skills of interest, but few have focused on identifying what scientific misconceptions students possess. This article developed a general dual-purpose model for simultaneously estimating students' overall ability and the presence and absence of…

This study proposed Gibbs sampling algorithms for variable selection in a latent regression model under a unidimensional two-parameter logistic item response theory model. Three types of shrinkage priors were employed to obtain shrinkage estimates: double-exponential (i.e., Laplace), horseshoe, and horseshoe+ priors. These shrinkage priors were…

In this paper, we develop a mixed stochastic approximation expectation-maximization (MSAEM) algorithm coupled with a Gibbs sampler to compute the marginalized maximum a posteriori estimate (MMAPE) of a confirmatory multidimensional four-parameter normal ogive (M4PNO) model. The proposed MSAEM algorithm not only has the computational advantages of…

In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…

Two strategies for assessing item bias are discussed: methods comparing item difficulties unconditional on ability and methods comparing probabilities of response conditional on ability. Results suggest that the iterative logit method is an improvement on the noniterative one and is efficient in detecting biased and unbiased items. (Author/DWH)

This study introduces the individual consistency index (ICI), which measures the extent to which patterns of responses to parallel sets of items remain consistent over time. ICI is used as an error diagnostic tool to detect aberrant response patterns resulting from the consistent application of erroneous rules of operation. (Author/PN)

The outcomes of two scoring methods (one based on an error analysis and the second on a conventional method) on free-response tests, compared in terms of reliability and dimensionality, indicates the conventional method is inferior in both aspects. (Author/PN)

A newly introduced approach, rule space, can represent large numbers of erroneous rules of arithmetic operations quantitatively and can predict the likelihood of each erroneous rule. The new model challenges the credibility of the traditional right-or-wrong scoring procedure. (Author/PN)

Empirical results from two studies--a simulation study and an experimental one--indicated that, in achievement data of the problem-solving type where a specific subject matter area is being tested, the greater the variety of the algorithms used, the higher the dimensionality of the test data. (Author/PN)

A scoring algorithm for performance assessments is described that is based on expert judgments but requires the rating of only a sample of performances. A regression-based policy capturing procedure was implemented for clinicians evaluating skills of 280 medical students. Results demonstrate the usefulness of the algorithm. (SLD)