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…

Previous work showing that revised parallel analysis can be effective with dichotomous items has used a two-parameter model and normally distributed abilities. In this study, both two- and three-parameter models were used with normally distributed and skewed ability distributions. Relatively minor skew and kurtosis in the underlying ability…

It is demonstrated that the popular three-parameter logistic model can lead to markedly inaccurate individual ability level estimates for mixture populations. A theoretically and empirically important setting is initially considered where (a) in one of two subpopulations (latent classes) the two-parameter logistic model holds for each item in a…

In real-world situations, multidimensional data may appear on large-scale tests or attitudinal surveys. A simple structure, multidimensional model may be used to evaluate the items, ignoring the cross-loading of some items on the secondary dimension. The purpose of this study was to investigate the influence of structure complexity magnitude of…

The development of assessments as part of the funded LOCUS project is described. The assessments measure students' conceptual understanding of statistics as outlined in the GAISE PreK-12 Framework. Results are reported from a large-scale administration to 3,430 students in grades 6 through 12 in the United States. Items were designed to assess…

From the complex dynamic systems theory perspective, evaluating CALL pedagogy involves miscellaneous variables. It seems the ecosystem of the CALL environment necessitates an array of extralinguistic (Ecolinguistically situated) issues to be considered in any appraisal of the CALL milieu. To this end, this paper aims to develop and validate a…

Undergraduate genetics courses have historically focused on simple genetic models, rather than taking a more multifactorial approach where students explore how traits are influenced by a combination of genes, the environment, and gene-by-environment interactions. While a focus on simple genetic models can provide straightforward examples to…

The "extended Rasch modeling" (eRm) package in R provides users with a comprehensive set of tools for Rasch modeling for scale evaluation and general modeling. We provide a brief introduction to Rasch modeling followed by a review of literature that utilizes the eRm package. Then, the key features of the eRm package for scale evaluation…

In dichotomous item response theory (IRT) framework, the asymptotic standard error (ASE) is the most common statistic to evaluate the precision of various ability estimators. Easy-to-use ASE formulas are readily available; however, the accuracy of some of these formulas was recently questioned and new ASE formulas were derived from a general…

Written inquiries, which are more frequent and have less of a focus on complex thinking, are issues at school. Students are not taught how to respond to questions found in High-Level Thinking Skills (HOTS) tests, hence, their thinking abilities are generally weak. The issue for teachers is that neither they nor anyone else has been able to create…

The current study compared the model fit indices, skill mastery probabilities, and classification accuracy of six Diagnostic Classification Models (DCMs): a general model (G-DINA) against five specific models (LLM, RRUM, ACDM, DINA, and DINO). To do so, the response data to the grammar and vocabulary sections of a General English Achievement Test,…

Process Analysis is an emerging approach to discover meaningful knowledge from temporal educational data. The study presented in this paper shows how we used Process Analysis methods on the National Assessment of Educational Progress (NAEP) test data for modeling and predicting student test-taking behavior. Our process-oriented data exploration…

For surveys of complex issues that entail multiple steps, multiple reference points, and nongradient attributes (e.g., social inequality), this study proposes a new multiprocess model that integrates ideal-point and dominance approaches into a treelike structure (IDtree). In the IDtree, an ideal-point approach describes an individual's attitude…

Mixture item response theory (MixIRT) models combine IRT models with latent class model and assume that there exist latent subpopulations in the data. Identification of latent subpopulations via MixIRT models produces more detailed information. Detailed information about the response processing of examinees provides a better understanding of the…

Most of the existing classification accuracy indices of attribute patterns lose effectiveness when the response data is absent in diagnostic testing. To handle this issue, this article proposes new indices to predict the correct classification rate of a diagnostic test before administering the test under the deterministic noise input…