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…

Cooperative education programs are usually based on a partnership between companies and universities. Dropouts have a particular impact here, for example the loss of junior staff in the companies. Most dropouts in cooperative education occur in the first academic year. In this multicausal dropout process, the influence of the cooperation partner…

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…

Student dropout is a significant concern for university administrators, students and other stakeholders. Dropout is recognised as highly complex due to its multi-causality, which is expressed in the existing relationship in its explanatory variables associated with students, their socio-economic and academic conditions, and the characteristics of…

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…

This quantitative correlational study explored the factors influencing graduate level student dropout intention across disciplines. Based on previous retention research that focused on undergraduate populations, this study attempted to investigate how that research could be applied to a graduate level student population in a private, non-profit,…

This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…

School dropout can be an ongoing process of academic failure and disengagement starting as early as elementary school. Given the importance of early identification of risk factors, the present study examines (a) whether early conduct problems and depressive symptoms predict a higher risk of school dropout, (b) whether depressive symptoms moderate…

Background/Context: There is a misalignment in contemporary society between the assumption that all high school graduates can and should attend college and the lack of funding and support to make that happen. This is especially apparent at community colleges that enroll disproportionally low-income students, who deal with a variety of obstacles…

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…

This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…

The true purpose of this study is to contribute to researchers' and practitioners' understanding of the power of Teacher-Student Relationships (TSRs) relative to at-risk students' graduation status. Much of the research surrounding dropouts focuses on root causes like attendance, retention, and families' economic status. However, minimal research…

Studies found that students from low socioeconomic backgrounds have higher odds of dropping out from higher education. Academic hardships were also identified as predictors. The current study utilizes data on 45,752 students who started their studies at The Hebrew University of Jerusalem (2003-2015). Descriptive statistics reveal that 18% of all…

The purpose of this investigation was to develop an ultra-short questionnaire that reliably predicted re-enrollment. Two binary stepwise logistic regressions were performed using re-enrollment status as the criterion. The first regression, conducted with a subsample of 4619 undergraduates, reduced 32 items drawn from the College Persistence…

Dropout remains a persistent challenge within high school education. In this paper, we present a case study on automatically detecting whether a student is at-risk of dropout within a diverse school district in Texas. We predict whether a student will drop out in a future school year from data on students' discipline, attendance, course-taking,…