One of the central components of cognitive diagnostic assessment is the Q-matrix, which is an essential loading indicator matrix and is typically constructed by subject matter experts. Nonetheless, to a large extent, the construction of Q-matrix remains a subjective process and might lead to misspecifications. Many researchers have recognized the…

This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…

Recent research in multidimensional item response theory has introduced within-item interaction effects between latent dimensions in the prediction of item responses. The objective of this study was to extend this research to bifactor models to include an interaction effect between the general and specific latent variables measured by an item.…

The common practice for testing measurement invariance is to constrain parameters to be equal over groups, and then evaluate the model-data fit to reject or fail to reject the restrictive model. Posterior predictive checking (PPC) provides an alternative approach to evaluating model-data discrepancy. This paper explores the utility of PPC in…

We review the GIDNA and CDM packages in R for fitting cognitive diagnosis/diagnostic classification models. We first provide a summary of their core capabilities and then use both simulated and real data to compare their functionalities in practice. We found that the most relevant routines in the two packages appear to be more similar than…

In general, newer educational assessments are deemed more demanding challenges than students are currently prepared to face. Two types of factors may contribute to the test scores: (1) factors or dimensions that are of primary interest to the construct or test domain; and, (2) factors or dimensions that are irrelevant to the construct, causing…

María Oliveri, and Saad Khan write that the article: "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" provided helpful illustrations regarding the implementation of evidence-centered assessment design (Mislevy & Haertel, 2006; Mislevy, Steinberg, & Almond, 1999) with games and simulations.…

In his commentary on "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" by Almond et al., Mike Timms writes that his own research has involved the use of embedded assessments using simulations in interactive learning environments, and the Evidence Centered Design (ECD) approach has provided a solid…

This article summarizes assessment of cognitive skills through collaborative tasks, using field test results from the Assessment and Teaching of 21st Century Skills (ATC21S) project. This project, sponsored by Cisco, Intel, and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and…

One of the key ideas of evidence-centered assessment design (ECD) is that task features can be deliberately manipulated to change the psychometric properties of items. ECD identifies a number of roles that task-feature variables can play, including determining the focus of evidence, guiding form creation, determining item difficulty and…

This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…

Testlets, or groups of related items, are commonly included in educational assessments due to their many logistical and conceptual advantages. Despite their advantages, testlets introduce complications into the theory and practice of educational measurement. Responses to items within a testlet tend to be correlated even after controlling for…

The importance of subscores in educational and psychological assessments is undeniable. Subscores yield diagnostic information that can be used for determining how each examinee's abilities/skills vary over different content domains. One of the most common criticisms about reporting and using subscores is insufficient reliability of subscores.…

This dissertation proposes two modified cognitive diagnostic models (CDMs), the deterministic, inputs, noisy, "and" gate with hierarchy (DINA-H) model and the deterministic, inputs, noisy, "or" gate with hierarchy (DINO-H) model. Both models incorporate the hierarchical structures of the cognitive skills in the model estimation…

The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having…