The COVID-19 pandemic, like past historical events such as the Vietnam War or 9/11, will shape a generation. Mathematics educators can seize this unprecedented opportunity to teach the principles of mathematical modeling in epidemiology. Compartmental epidemiological models, such as the SIR (susceptible-infected-recovered), are widely used by…

The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all units within the group are exposed to the treatment. However, the treatment is non-randomly assigned. COSs are common in both education and health services research. In…

This research explores the process of a Participatory Research (PR) project that brought together university researchers with museum practitioners to create reflective tools that can be used to better understand real practical challenges. This project followed Bourke's (2009) definition of PR, viewing the process as a collaborative endeavour…

As learning analytics use grows across U.S. colleges and universities, so does the need to discuss the plans, purposes, and paths for the data collected via learning analytics. More specifically, students, faculty, and others who are impacted by learning analytics use should have more information about their campus' learning analytics practices…

The purpose of this paper is to propose a framework to guide the study of classroom factors that promote student functioning and development within classroom settings. First, we describe a new framework, "Classroom Carrying Capacity," to categorize factors in the classroom as limiting or resource factors across four domains: external,…

Understanding software modelers' difficulties and evaluating their performance is crucial to Model-Driven Engineering (MDE) education. The software modeling process contains fine-grained information about the modelers' analysis and thought processes. However, existing research primarily focuses on identifying obvious issues in the software…

This paper presents a systematic literature review of using Machine Learning (ML) techniques in higher education career recommendation. Despite the growing interest in leveraging Artificial Intelligence (AI) for personalized academic guidance, no previous reviews have synthesized the diverse methodologies in this field. Following the Kitchenham…

In this article, we advocate for and propose a novel concept map driven knowledge tracing (CMKT) model, which utilizes educational concept map for learner modeling. This article particularly addresses the issue of learner data sparseness caused by the unwillingness to practice and irregular learning behaviors on the learner side. CMKT considers…

In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal…

Factor Score Regression (FSR) is increasingly employed as an alternative to structural equation modeling (SEM) in small samples. Despite its popularity in psychology, the performance of FSR in multigroup models with small samples remains relatively unknown. The goal of this study was to examine the performance of FSR, namely Croon's correction and…

Using a longitudinal national educational dataset, data science methods were applied to explain students' educational trajectories and determine the most predictive variables in STEM degree attainment. Challenging the notion of the STEM pipeline, an Alternative Pathways to STEM (APS) model was proposed. Using a foundation of Social Cognitive…

There are many important and interesting academic competitions that attract an increasing number of students. However, traditional student team building methods usually have strong randomness or involve only some first-class students. To choose more suitable students to compose a team and improve students' abilities overall, a competition-oriented…

Discussions of randomised controlled trials (RCTs) in education that do not show an impact regularly focus on the intervention and how it failed to impact on expected measures, with typologies identifying persistent critical points of failure. This paper uses one such RCT--the Integrating English programme--to exemplify the application of a new…

"Opportunity to learn" has evolved into an umbrella phrase for describing a large range of settings, resources, structures, and processes. The aim of this study is to develop a conceptual framework that can accommodate a wide range of opportunities to learn, not just those provided by teachers in classrooms. An inclusive framework can…

Data pooling is a powerful strategy in empirical research. However, combining multiple datasets often results in a large amount of missing data, as variables that are not present in some datasets effectively contain missing values for all participants in those datasets. Furthermore, data pooling typically leads to a mix of continuous and…