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…

Background: Education plays a pivotal role in empowering individuals with the knowledge and skills needed for careers, economic progress, and societal engagement. Dropping out of school before achieving a qualification undermines these opportunities and has an impact on individuals and society (Audit Commission, 2010; OECD, 2023). International…

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…

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…

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.…

Every year around 1.2 million students drop out of school in the US. According to a UNICEF report enrollment in educational institutions in Lebanon dropped from 60% in 2020-2021 to 43% in 2021-2022. The National Dropout Prevention Center (NDPC) at Clemson University has identified an extensive set of risk factors organized into four domains:…

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:…

The increased availability of technology in higher education has led to the growth of online learning platforms. However, a significant concern exists regarding dropout rates in online higher education (OHE). In this ever-evolving landscape, student attrition poses a complex challenge that demands careful investigation. This systematic literature…

Evidence on the extent to which dropout intention can serve as a valid predictor of dropout decisions remains scarce. This study first presents the results of a systematic literature review of 14 studies examining the relationship between dropout intention and actual dropout in post-secondary education (vocational education and training [VET] or…

This research explores who is at risk of dropping out of high school and how collaborative Student Support Teams can contribute to students staying on track to graduate high school. The issue of student success is important because graduation is positively correlated with important life outcomes and ability to earn an adequate income in the labor…

While open and distance education gains growing recognition over time, it also faces increasing drop-out rates. Consequently, the development of predictive models for early identification of students at-risk for drop-out could be critical to promote ongoing engagement. This study aims to gain insights into the dropout prediction problem in a…

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…

E-learning students have a tendency to get demotivated and easily dropout from online courses. Refining the learners' involvement and reducing dropout rates in these e-learning based scenarios is the main drive of this study. This study also shares the results obtained and crafts a comparison with new and emerging commercial solutions. In a…

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…

Student drop-out is one of the most burning issues in STEM higher education, which induces considerable social and economic costs. Using machine learning tools for the early identification of students at risk of dropping out has gained a lot of interest recently. However, there has been little discussion on dropout prediction using interpretable…