Dominance analysis (DA) is a very useful tool for ordering independent variables in a regression model based on their relative importance in explaining variance in the dependent variable. This approach, which was originally described by Budescu, has recently been extended to use with structural equation models examining relationships among latent…

This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemented in particular in the popular intercept-and-slope model as well as in more general models containing it as a component, such as longitudinal…

Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e.,…

Background: Structural Equation Modeling (SEM) is a powerful and broadly utilized statistical framework. Researchers employ these models to dissect relationships into direct, indirect, and total effects (Bollen, 1989). These models unpack the "black box" issues within cause-and-effect studies by examining the underlying theoretical…

Research on computing in higher education research has been dominated by studies on "things that work" (or not). While useful, the field now needs more research on authentic tech-related problems of practice and viable solutions that resolve them. This article describes one such approach: Educational Design Research (EDR). It begins with…

Unlike previous studies on fixed logistics nodes, this research explored how consumer distribution impacts store selection and inventory balance, integrating the "ship-from-store" strategy to increase fulfillment within multiperiod sales plans. Specifically, omnichannel retailers (O-tailer) must sequentially decide on inventory…

This concept paper proposes a way of mapping educational landscapes to clarify the practice of experiential programming. It initially reviews how experiential education has been defined and suggestions for better definitional clarity. It then examines a recent initiative commissioned by the Society for Experiential Education to update its…

This article focuses on describing a systematic model for constructing, describing, and interpreting logarithmic diagrams as a graphical method for representing redox chemical equilibria. This model considers concepts such as electron potential (p[subscript e]), the chemical equilibrium constant (K[subscript d]), and the standard reduction…

We perform an asymptotic static analysis on a simple two degrees of freedom structure, made up of a highly stiff bar and two springs, which shows two different linear behaviours and different finite stiffness depending on the magnitude of an applied static force. Both regimes as well as the non-linear transition between them occur in the framework…

Research into statistical learning, the ability to learn structured patterns in the environment, faces a theory crisis. Specifically, three challenges must be addressed: a lack of robust phenomena to constrain theories, issues with construct validity, and challenges with establishing causality. Here, we describe and discuss each issue in relation…

In the dynamic landscape of tertiary education, fostering innovation, adaptability, and enhanced institutional performance hinges on the effective management of knowledge. Responding to this challenge, this study introduces a novel model, the DNA model of a tertiary education institution, for systematically advancing knowledge management practices…

The use of structural equation models for causal inference from panel data is critiqued in the causal inference literature for unnecessarily relying on a large number of parametric assumptions, and alternative methods originating from the potential outcomes framework have been recommended, such as inverse probability weighting (IPW) estimation of…

A linear model is often used to find the effect of a binary treatment D on a noncontinuous outcome Y with covariates X. Particularly, a binary Y gives the popular "linear probability model (LPM)," but the linear model is untenable if X contains a continuous regressor. This raises the question: what kind of treatment effect does the…

The study investigated the structural equation modelling of nine variables consisting of research undertaking, digi-tech construct (digital nativity, category of adoption of digital technologies, digital literacy, digital citizenship, statistical software anxiety, self-efficacy and knowledge) and researcher statistical software skills in the…

In this study, which focuses on selecting the material and predicting its mechanical behaviors in materials science, an Artificial Neural Network (ANN) was used to predict and simulate the low-speed impact effects of hybrid nano-doped aramid composites. There are not enough studies about open education practices in this field. Since error values…