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…

University dropout is a serious problem in higher education that is increasingly gaining importance, as it is essential to understand its causes and search for public and institutional policies that can help reduce it. This research uses conventional and extended Cox survival models to analyze the factors behind dropout rates at a co-financed…

To address three issues identified in previous research this study proposes a clustering-based MOOC dropout identification method and an early prediction model based on deep learning. The MOOC learning behavior of self-paced students was analyzed, and two well-known MOOC datasets were used for analysis and validation. The findings are as follows:…

This study captures the stories of adult Black men from an urban area plagued by generational poverty and low educational attainment. Narrative semi-structured interviews were employed to examine their stories, the factors that contributed to their identities as students, and their decision to drop out of school. Using the cool pose theory (Major…

What happens to our students when they do not complete their studies and drop out of school? Perhaps this question is probably not something that we reflect on as educators. This study seeks to amplify three students' voices and explore their unique experiences and the challenges they faced after they did not complete their high school studies.…

This article analyses the main reasons for dropping out of Spanish Intermediate Vocational Education (IVET) and the link to personal (sex, ethnicity, age), family (parents' educational level) and financial sociodemographic characteristics, as well as academic background (repeating or expulsion). To do this, a cohort of IVET students was monitored…

Contribution: This study proposes a student dropout prediction model, named image convolutional and bi-directional temporal convolutional network (IC-BTCN), which makes dropout prediction for learners based on the learning clickstream data of students in massive open online courses (MOOCs) courses. Background: The MOOCs learning platform attracts…

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…

Success for 4-year universities is often measured by graduation and retention rates; however, gaps exist in understanding nonreturning students at private institutions. Recent research is helping to build the lexicon of drop-outs, stop-outs, opt-outs, and transfer-outs to inform strategic retention initiatives. Using an action research method, we…

Students who drop out of university cite various reasons for their decision. Female enrolment has significantly increased over the past few decades and is now higher than male enrolment. In terms of performance, it is recognised that women perform better than males do, and fewer women drop out of university than men do. However, the relationship…

Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…

Policy research established that it is possible to predict a student will drop out of school based on academic, attendance, behavior indicators. Little is known about the processes that put Early Warning Systems (EWS) in place. This case study of the Montana EWS describes the characteristics of a statewide implementation, the efficiency of the EWS…

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.…

Understanding the drivers of student dropout from higher education has been a policy concern for several decades. However, the contributing role of certain factors--including student mental health--remains poorly understood. Furthermore, existing studies linking student mental health and university dropout are limited in both methodology and…

Background: Although most engineering graduate students are funded and usually complete their degrees faster than other disciplines, attrition remains a problem in engineering. Existing research has explored the psychological and sociological factors contributing to attrition but not the structural factors impacting attrition. Purpose/Hypothesis:…