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…

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…

In this article, we pursue two points of discussion. First, a new illustration is presented of the person-oriented tenet according to which it can be hazardous to generalize to the individual results that are based on the analysis of aggregated data. Second, it is illustrated that taking into account serial dependence information can result in not…

Resident assistants who serve as peer leaders to other students are consistently considered crucial in creating a positive on-campus experience. Despite the demonstrated benefits these peer leaders bring to their communities and the significant monetary resources invested in them, there is a significant lack of research about their selection,…

Dynamic Item Response Models extend the standard Item Response Theory (IRT) to capture temporal dynamics in learner ability. While these models have the potential to allow instructional systems to actively monitor the evolution of learner proficiency in real time, existing dynamic item response models rely on expensive inference algorithms that…

In recent years, online learning methods have gradually been accepted by more and more people. A large number of online teaching courses and other resources (MOOCs) have also followed. To attract students' interest in learning, many scholars have built recommendation systems for MOOCs. However, students need a variety of different learning…

The literature on cognitive processing and strategic processing is murky with regard to how these types of processing influence learning. One reason for this is that the frameworks used to investigate these relations have separately focused on different aspects related to cognitive processing with little integration between them. To address these…

Group model building is a participatory workshop technique used in system dynamics for developing community consensus to address complex problems by consensus building on individual assumptions. This study examines changes in individual mental models of the complex problem of childhood obesity following participation in group model building (GMB),…

This study examined high school chemistry students' understandings of big ideas--matter and energy, how these understandings are related to macro and submicro representations and fine-grained distinguishing characteristics of students' explanations. The study was conducted in the context of computer-based models and model-based assessments.…

Each day people make decisions about complex topics such as health and personal finances. Causal models of these domains have been created to aid decisions, but the resulting models are often complex and it is not known whether people can use them successfully. We investigate the trade-off between simplicity and complexity in decision making,…

In this article we address the historical and epistemological study of infinity as a mathematical concept, focusing on identifying difficulties, counter-intuitive ideas and paradoxes that constituted implicit, unconscious models faced by mathematicians at different times in history, representing obstacles in the rigorous formalization process of…

Agility is a contemporary approach to IT project management, which we can also use in education. Students learn through the gradual implementation of iterative projects with information exchange between team members. Agility is above all a mindset. Being agile is quite simply being able to adapt to an environment that changes. Furthermore, various…