Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

We propose a novel approach to address the issue of college student attrition by developing a hybrid model that combines a structural neural network with a piecewise exponential model. This hybrid model not only shows the potential to robustly identify students who are at high risk of dropout, but also provides insights into which factors are most…

Using data from 11 institutions, the authors investigate enrollments in intermediate microeconomics to determine characteristics of successful and unsuccessful students and follow the retake behavior of unsuccessful students. Successful students are significantly different from unsuccessful ones, and unsuccessful students differ by type…

This study reports on two key aspects relating to the use of the Online Learning Readiness Self-Check (OLRSC) survey, which has been proposed as identifying non-traditional students' readiness for online learning, and their strengths and weaknesses in six key areas. The first aspect validates the use of the instrument based on data from 199…

This study examined the persistence of first-year engineering students at a Hispanic-Serving Institution (HSI) and a Historically Black College and University (HBCU) pre- and mid-COVID-19 interruptions and whether their characteristics (race/ethnicity, financial need status, first-generation status, SAT scores) predicted their persistence. Using…

This article investigates to what extent disrupted schooling due to the COVID-19 pandemic has affected pre-primary-age children's school readiness in Ethiopia. We use data on early numeracy of 2,640 children collected before and after the eight-month school closure to assess their learning progress in the context of COVID-19. We find that children…