Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time,…

Enzymes are nature's catalysts, mediating chemical processes in living systems. The study of enzyme function and mechanism includes defining the maximum catalytic rate and affinity for substrate/s (among other factors), referred to as enzyme kinetics. Enzyme kinetics is a staple of biochemistry curricula and other disciplines, from molecular and…

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…

Virtual Reality has proven to be highly promising within the field of learning. Most VR learning methods do not effectively implement pedagogical models or adapt to the individual's learning style. This research aims to bridge this gap by integrating Fuzzy Cognitive Maps (FCMs), Flow Theory and Gamification within an educational Virtual Reality…

The objectives of this research are (1) to study and synthesise the conceptual framework of the imagineering learning model with inquiry-based learning via augmented reality to enhance creative products and digital empathy, (2) to develop the imagineering learning model with inquiry-based learning via augmented reality to enhance creative products…

The Open University is a university that has been around for a long time, so that it is able to develop a learning process that demands the development of science and technology, both online and offline independently. Therefore, this study aims to describe and analyze the process and results of the development of a virtual science laboratory to…

Many studies show that augmented reality (AR) provides multiple benefits to science education, including learning gains, motivation to learn, and collaborative learning. However, while using AR largely depends on the teachers' willingness, existing literature lacks studies that identify teachers' intentions to use this technology. This study…

As the number of STEM opportunities and the need for a scientifically literate society increases, educators in STEM fields require tools that help support these needs. Chemistry is one STEM content area that would benefit from exploring educational technology that supports conceptual understanding. An action research study was conducted to…

This study examined whether athletic training students in a four-year undergraduate entry-level accredited athletic training program in a postsecondary institution perceived the PEARLS model as effective in providing feedback. Although students look to the feedback process to help them better understand their skill and performance level when…

We discuss analysis of 5-grade Likert type data in the two-sample case. Analysis using two-sample "t" tests, nonparametric Wilcoxon tests, and ordinal regression methods, are compared using simulated data based on an ordinal regression paradigm. One thousand pairs of samples of size "n"=10 and "n"=30 were generated,…

Computational modeling and thinking skill sets were previously relegated to computer scientists and programmers. As a result, computational tools are largely unfamiliar to K-12 science teachers and students. Using Mathematical and Computational Thinking and Developing and Using Models were included in the "Next Generation Science…

Inferential reasoning is an integral part of science and civic society, but research shows that it is a problematic domain for many people. One possibility for a more accessible approach to inferential reasoning is to use randomization tests via computer simulations. A case study was conducted with primary preservice teachers after they had passed…

Item Response Theory (IRT) models are a popular analytic method for self report data. We show how traditional IRT models can be vulnerable to specific kinds of asymmetric measurement error (AME) in self-report data, because the models spread the error to all estimates -- even those of items that do not contribute error. We quantify the impact of…

Causal-formative indicators are often used in social science research. To achieve identification in causal-formative indicator modeling, constraints need to be applied. A conventional method is to constrain the weight of a formative indicator to be 1. The selection of which indicator to have the fixed weight, however, may influence statistical…

However, although existing models for evaluating the effectiveness of universities provide a large number of modeling solutions, it is difficult to objectively evaluate dynamic coefficients based on the differences in precision ideological and political work systems of different types of universities in the evaluation process of innovative paths…