Although using machine learning for predicting which students are at risk of failing a course is indeed valuable, how can we identify which characteristics of individual students contribute to their being At-Risk? By characterising individual At-Risk students we could potentially advise on specific interventions or ways to reduce their probability…

Researchers agree that for children who attend early care and education programs, high-quality early learning experiences are critical for promoting academic, social-emotional, and executive function skills, particularly for children of color and children from families with low incomes. Rigorous research testing the effects of interventions to…

Despite popular myths related to the design and development of an online course, the endeavor is rather complicated. Universal Course Shell Templates (UCSTs) can alleviate teachers' workload, support teachers in taking pedagogically sound decisions, and assist students in their engagement with the course. The study begins with a review of the…

Proper institutional planning requires accurate enrollment forecasts. This is especially true in the community college context given open enrollment policies and reliance on public funds. Despite the importance of this task, enrollment forecasts are relatively disconnected from theoretical advances in the study of retention and enrollment. In this…

This paper, while conceptual in nature, is informed by both research and practice. Exploring the "engagement interface" as the site for student engagement (SE), we offer a conceptual contribution in engaging with the Kahu and Nelson (2018) model by bringing in a fuller understanding of SE grounded in the higher education context rather…

The context of this research aims to analyse the effects of entrepreneurial creativity (EC) empirically on entrepreneurial intention through structural equation modelling by proposing and testing the model that has been developed previously developed. The goal of this study is to understand some of the determinants of entrepreneurial intention…

In this digital ITEMS module, Dr. Stella Kim provides an overview of multidimensional item response theory (MIRT) equating. Traditional unidimensional item response theory (IRT) equating methods impose the sometimes untenable restriction on data that only a single ability is assessed. This module discusses potential sources of multidimensionality…

The research background rests on the shortcomings of existing electronic business development models. The main aspects of the framework for e-business development as a prerequisite for sustainable competitive advantage are based on an analysis of scientific literature on sustainable competitive advantage and electronic business development. The…

The standard model of particle physics is the most successful theory describing the behavior of matter and energy in the subatomic realm. However, success doesn't mean it is perfect, and a recent measurement of the mass of a particle called the W boson is puzzling, as it disagrees with theoretical predictions and earlier precise measurements. If…

Teaching upper division statistical physics can often be clouded by the theory and complex examples used. To better help students appreciate the fundamental statistical concepts and how they are connected to thermodynamic principles this paper suggests using a simple abstract model. Using Atkins' Model students can see these ideas clearly…

Mediation analysis is widely used to study whether the effect of an independent variable on an outcome is transmitted through a mediator. Bayesian methods have become increasingly popular for mediation analysis. However, limited research has been done on formal Bayesian hypothesis testing of mediation. Although hypothesis testing using Bayes…

Prediction of student performance in introductory programming courses can assist struggling students and improve their persistence. On the other hand, it is important for the prediction to be transparent for the instructor and students to effectively utilize the results of this prediction. Explainable Machine Learning models can effectively help…

Learning outcome modeling is a technical underpinning for the successful evaluation of learners' learning outcomes through computer-based assessments. In recent years, collaborative filtering approaches have gained popularity as a technique to model learners' item responses. However, how to model the temporal dependencies between item responses…

Current approaches used in educational research and practice to evaluate the quality of written arguments often rely on structural analysis. In such assessments, credit is awarded for the presence of structural elements of an argument, such as claims, evidence, and rebuttals. In this article, we discuss limitations of such approaches, including…

Researchers commonly use puppets in development science. Amongst other things, puppets are employed to reduce social hierarchies between child participants and adult experimenters akin to peer interactions. However, it remains controversial whether children treat puppets like real-world social partners in these settings. This study investigated…