This study examined the visual design processes and strategies used by design experts and non-design college students when composing an infographic. All participants created an infographic on a personal computer and were asked to think aloud as they performed the task. The goal was to identify differences in the strategies utilised to produce…

The development of metaknowledge about models (MKM) and metaknowledge about the modelling process (MKP) are important in pre-service science teachers (PSTs) education. MKM refers to knowledge about the model's entities and its purposes, while MKP refers to knowledge about the components and structure of the modelling process. Assessing MKM and MKP…

This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering…

In recent years, educators, administrators, policymakers, and measurement experts have called for assessments that support educators in making better instructional decisions. One promising approach to measurement to support instructional decision-making is diagnostic classification models (DCMs). DCMs are flexible psychometric models that…

Although the scholarship of teaching and learning (SoTL) has been described as the signature pedagogy of educational development (a professional field focused on support for teaching and learning in higher education), there is little systematic evidence of the scale and scope of the SoTL support practices that centers for teaching and learning…

Understanding complex physiological processes is a cornerstone of medical education, and one such fundamental concept is the regulation of the glomerular filtration rate (GFR) by Starling forces. Therefore, developing a physiologically sound educational model to demonstrate these forces can significantly enhance the learning experience for…

Simulation studies are needed to investigate how many score categories are sufficient to treat ordered categorical data as continuous, particularly for bifactor models. The current simulation study aims to address such needs by investigating the performance of estimation methods in the bifactor models with ordered categorical data. Results support…

Within the frequentist structural equation modeling (SEM) framework, adjudicating model quality through measures of fit has been an active area of methodological research. Complicating this conversation is research revealing that a higher quality measurement portion of a SEM can result in poorer estimates of overall model fit than lower quality…

Dynamic structural equation models (DSEM) are designed for time series analysis of latent structures. Inherent to the application of DSEM is model parameter estimation, which has to be addressed in many applications by a single time series. In this context, however, the methods currently available either lack estimation quality or are…

We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector using the matrix logarithm function. Bayesian inference about the unbounded vector is performed assuming a multivariate-normal likelihood, with a mean…

A practice that dates back centuries, apprenticeship is a workforce development model that has gained recent attention in the American higher education system. The researcher conducted a review of existing literature that included apprenticeships in higher education and other models of community college workforce development. Existing literature…

We explore ways in which statistics can be used to understand disease spread and support decision-making by governments. "Past performance does not guarantee future results"--we hope. We discuss and show examples from the National Science Foundation (NSF)-funded COVID-Inspired Data Science Education through Epidemiology (CIDSEE) project.…

Given the lack of cultural consideration of studies on digital natives, this study reports on a large-scale validation of the Digital Native Assessment Scale (DNAS) among university students from three regions of Greater China: Chinese mainland, Macau, and Taiwan, to examine measurement invariance and latent mean differences in the four constructs…

As evidence from evaluation and experimental studies continue to influence decision and policymaking, applied researchers and practitioners require tools to derive valid and credible inferences. Over the past several decades, research in causal inference has progressed with the development and application of propensity scores. Since their…

This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML outputs. In each of the experiments, participants were given the T and L task with T-shaped targets and…