Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

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…

Human ratings are ubiquitous in creativity research. Yet, the process of rating responses to creativity tasks -- typically several hundred or thousands of responses, per rater -- is often time-consuming and expensive. Planned missing data designs, where raters only rate a subset of the total number of responses, have been recently proposed as one…

Methods for optimal factor rotation of two-facet loading matrices have recently been proposed. However, the problem of the correct number of factors to retain for rotation of two-facet loading matrices has rarely been addressed in the context of exploratory factor analysis. Most previous studies were based on the observation that two-facet loading…

Manually determining concepts present in a group of questions is a challenging and time-consuming process. However, the process is an essential step while modeling a virtual learning environment since a mapping between concepts and questions using mastery level assessment and recommendation engines is required. In this article, we investigated…

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…

All cognitive diagnostic models that evaluate educational test data require a Q-matrix that combines every item in a test with the required cognitive skills for each item to be answered correctly. Generally, the Q-matrix is constructed by education experts' judgment, leading to some uncertainty in its elements. Various statistical methods are…

Cognitive diagnosis models (CDMs) are latent class multidimensional statistical models that help classify people accurately by using a set of discrete latent variables, commonly referred to as attributes. These models require a Q-matrix that indicates the attributes involved in each item. A potential problem is that the Q-matrix construction…

Network models of the WAIS-IV based on regularized partial correlation matrices have been reported to outperform latent variable models based on uncorrected correlation matrices. The present study sought to compare network and latent variable models using both partial and uncorrected correlation matrices with both types of models. The results show…

Raven's Standard Progressive Matrices (SPM) test and related matrix-based tests are widely applied measures of cognitive ability. Using Bayesian Item Response Theory (IRT) models, I reanalyzed data of an SPM short form proposed by Myszkowski and Storme (2018) and, at the same time, illustrate the application of these models. Results indicate that…

Feedback is a powerful instructional tool for motivating learning. But effective feedback, requires that instructors have accurate information about their students' current knowledge status and their learning progress. In modern educational measurement, two major theoretical perspectives on student ability and proficiency can be distinguished.…

Exploratory cognitive diagnosis models (CDMs) estimate the Q matrix, which is a binary matrix that indicates the attributes needed for affirmative responses to each item. Estimation of Q is an important next step for improving classifications and broadening application of CDMs. Prior research primarily focused on an exploratory version of the…

Operations and Supply Chain Management (OSCM) courses may cover supply chain strategies, supply chain classification, and supply chain performance. Familiarity with various manufacturing and logistics firms would help students to better understand such topics. Information on the Dow Jones Industrial Average indexed firms and top 50 supply chain…

Lagrange multiplier (LM) or score tests have seen renewed interest for the purpose of diagnosing misspecification in item response theory (IRT) models. LM tests can also be used to test whether parameters differ from a fixed value. We argue that the utility of LM tests depends on both the method used to compute the test and the degree of…

Multidimensional item response theory (MIRT) models use data from individual item responses to estimate multiple latent traits of interest, making them useful in educational and psychological measurement, among other areas. When MIRT models are applied in practice, it is not uncommon to see that some items are designed to measure all latent traits…