University dropout is a phenomenon of growing interest due to its negative consequences. Various variables have been studied in order to understand why this problem occurs. Satisfaction with the degree choice, self-regulation strategies and engagement within the university are some of the variables that have been studied in order to understand why…

This paper investigates the student dropout phenomenon in a technical Italian university from a time-to-event perspective. Shared frailty Cox time-dependent models are applied to analyse the careers of students enrolled in different engineering programs with the aim of identifying the determinants of student dropout through time, predicting the…

We examine the mechanisms explaining the dropout intentions of students with disabilities by integrating Tinto's model of student integration, the student attrition model, the composite persistence model, and insights from social stratification research. The resulting theoretical model posits that not only students' academic and social…

Study success in Higher Education is of primary importance in the European policy agenda. Yet, given the diverse educational landscape across countries and institutions, more coordinated action is needed to gain a more solid knowledge of the dropout phenomenon. This study aims to gain a better insight into students' dropout based on an integrated…

Based on the classic models developed by Spady and Tinto on the link between social and academic integration and dropout, we propose a refined model to explain dropout intentions--relating to dropout from higher education (HE) and dropout from a specific study programme--that more strongly emphasises individual background characteristics (e.g.…

Over 80,000 children in England were being looked after in Local Authority care in 2020 and a further 40,000 people were defined as 'care leavers'. Although a significant body of research highlights the prevalence of educational low achievement in the care experienced population, official government figures show that around 13% of care experienced…

The purpose of the present investigation is to shed light on the intraindividual (i.e., within-person) process of distancing from the goal of obtaining a PhD. Based on the motivational theory of action crisis, we assume that a lack of both individual (here: self-directed career management) and external (here: social support) resources may fuel…

The Institute of Medicine has found that barriers exist that directly contribute to the underrepresentation of racial and ethnic groups in health professional education. Yet, little research has been done to evaluate the barriers that affect athletic training students. An integrative review was conducted to identify barriers that affect students…

Early dropout of students is one of the bigger problems that universities face currently. Several machine learning techniques have been used for detecting students at risk of dropout. By using sociodemographic data and qualifications of the previous level, the accuracy of these predictive models is good enough for implementing retention programs.…

Purpose: The main purpose of this study is to evaluate the extent of dropout students and identify the relationship between risk factors of dropout and the survival time of students. Design/methodology/approach: The Kaplan-Meier estimator (KM), also known as the product-limit technique, is a nonparametric model function that is commonly used in…

Many educational institutions are using predictive models to leverage actionable insights using student data and drive student success. A common task has been predicting students at risk of dropping out for the necessary interventions to be made. However, issues of discrimination by these predictive models based on protected attributes of students…

The under-representation of women in male-dominated STEM fields is a worldwide concern. However, there are other academic fields, like some non-STEM degrees, where female students are over-represented. Previous research has identified five critical factors influencing student participation rates: career choice, satisfaction, self-esteem,…

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…

Course dropout is a concern in online higher education, mainly in first-year courses when different factors negatively influence the learners' engagement leading to an unsuccessful outcome or even dropping out from the university. The early identification of such potential at-risk learners is the key to intervening and trying to help them before…