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…

The multimedia simulation teaching mode introduces students into virtual scenes for learning. Whether it is enhancing students' interest in learning or enhancing their physical fitness, it is a new teaching mode. This article discusses the establishment of a BP neural network model to study the prediction of students' physical fitness and conducts…

This report provides advice to policymakers and school leaders on the use of assessment centres as part of a teacher selection approach. It discusses the relationship between assessment centre scores prior to joining teaching, and teacher effectiveness over a six-year period. It draws from various stages of a wider research project, the overall…

Wildfires pose significant environmental threats in Australia, impacting ecosystems, human lives, and property. This review article provides a comprehensive analysis of various empirical and dynamic wildfire simulators alongside machine learning (ML) techniques employed for wildfire prediction in Australia. The study examines the effectiveness of…

Symmetry considerations are important in science, and Group Theory is a theory of symmetry. Classical Measurement Theory is the most used measurement theory in the social and behavioral sciences. In this article, the author uses Matrix Lie (Lee) group theory to formulate a measurement model. Symmetry is defined and illustrated using symmetries of…

Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not…

Digital technology is profoundly transforming various aspects of life, thus highlighting the need to enhance digital literacy on a national scale. In primary and secondary schools, artificial intelligence (AI) education plays a pivotal role in fostering digital literacy. To comprehensively investigate the variables influencing AI education in…

Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…

The computational model of school achievement represents a novel approach to theorizing school achievement, conceptualizing educational interventions as modifications to students' learning curves. By modeling the process and products of educational achievement simultaneously, this tool addresses several unresolved questions in educational…

In this thesis, I use a combination of simulations and empirical data to demonstrate that a small set of structural and functional principles - the basic tenets of predictive coding theory - succinctly accounts for a very wide range of properties in the language processing system. Predictive coding approximates hierarchical Bayesian inference via…

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

This study tested the feasibility and efficacy of a Virtual Reality (VR) social prediction training (VR-Spirit) specifically designed for patients with congenital cerebellar malformation. The study is a randomised controlled trial in which 28 cerebellar patients aged 7-25 yo were randomly allocated to the VR-Spirit or to a control intervention in…

In this research, it was aimed to determine the effect of Simulation-Supported Prediction Observation Explanation (SSPOE) activities related to solid and liquid pressure on the conceptions of learning physics of 10th grade students. In the research, a quasi-experimental design with pretest-posttest control group, which is one of the quantitative…

With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…

The Beer-Lambert law is a fundamental relationship in chemistry that helps connect macroscopic experimental observations (i.e., the amount of light exiting a solution sample) to a symbolic model composed of system-level parameters (e.g., concentration values). Despite the wide use of the Beer-Lambert law in the undergraduate chemistry curriculum…