Immersive virtual reality (i-VR) is a powerful tool that can be used to explore virtual models in three dimensions. It could therefore be a valuable tool to supplement anatomical teaching by providing opportunities to explore spatial anatomical relationships in a virtual environment. However, there is a lack of consensus in the literature as to…

A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…

The virtual interactive learning model using imagineering process as a tool to promote happy learning for digital age learners. The concept is based on the combination of virtual learning environment and metaverse in order to create learning experience via virtual community. The objectives of this research are (1) to study and synthesise the…

In this article, I present a new multivariate regression model for analyzing outcomes with network dependence. The model is capable to account for two types of outcome dependence including the mean dependence that allows the outcome to depend on selected features of a known dependence network and the error dependence that allows the outcome to be…

Virtual reality (VR) is an increasingly available resource with numerous applications to medical education, and as a teaching tool has been widely validated in the literature. Photogrammetry, the process of overlapping two-dimensional (2D) photographic images of three-dimensional (3D) objects to create a 3D image or "model," can be used…

Science museums have demonstrated over time, and through various academic researches, to be a favorable environment to awaken the desire to learn more about scientific content, bringing visitors closer to artifacts and concepts in a different way than any other media can offer. In this research, we investigate how the public interacts with the…

Recent developments have enabled the modeling of longitudinal assessment data in a diagnostic classification model (DCM) framework. These longitudinal DCMs were developed to provide measures of student growth on a discrete scale in the form of attribute mastery transitions, thereby supporting categorical and criterion-referenced interpretations of…

The concept of computational thinking (CT) has become more prevalent across the engineering education research and teaching landscape. Yet much of the research to date has been more definitional and has not offered many ways to convert CT theory to practice. One prominent set of tools used across engineering disciplines is modeling and simulation,…

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…

Moderated multiple regression (MMR) has become a fundamental tool for applied researchers, since many effects are expected to vary based on other variables. However, the inherent complexity of MMR creates formidable challenges for adequately performing power analysis on interaction effects to ensure reliable and replicable research results. Prior…

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…

This paper describes how students conceptualize real-life phenomena in which two or more quantities are covarying in an augmented reality environment. With this technology, real-world phenomena and virtual representations may be connected simultaneously. We aim to investigate how students connect elements of the two worlds when conceptualizing…

A standard assumption of latent class (LC) analysis is conditional independence, that is the items of the LC are independent of the covariates given the LCs. Several approaches have been proposed for identifying violations of this assumption. The recently proposed likelihood ratio approach is compared to residual statistics (bivariate residuals…

The recognition memory receiver operating characteristic (ROC) is typically asymmetric with a characteristic elevation of the left-hand portion. Whereas the unequal variance signal detection model (uvsd) assumes the asymmetry results because old item evidence is noisier than new item evidence, the dual process signal detection model (dpsd) assumes…

The focus of this paper is on the empirical relationship between item difficulty and item discrimination. Two studies--an empirical investigation and a simulation study--were conducted to examine the association between item difficulty and item discrimination under classical test theory and item response theory (IRT), and the effects of the…