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…

The relationship between engagement and the intention to drop out was the focus of this research. Following an empirical-analytical approach, a sample of 1,122 university students responded to a questionnaire designed to measure the engagement and the intention to drop out of school. The results confirmed that undergraduates who considered…

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…

Practitioners of the statistics course embedded in a computer science programme at a fully online university were concerned with the high dropout rate. In the academic year 2018-19, they decided to carry out a two-phase project in order to address this issue. In the first phase, an early classifier to identify students at risk of dropping out of…

Dropout rates in engineering degree programmes at universities are high, and skilled workers are needed. Universities try to prevent dropouts with different offers one of which is attending bridging courses. Research on the effects of these programmes is rare, especially in subject-specific programmes and study formats like cooperative education.…

Early Warning Systems (EWS) in higher education accommodate student counsellors by identifying at-risk students and allow them to intervene in a timely manner to prevent student dropout. This study evaluates an EWS that shares student-specific risk information with student counsellors, which was implemented at a large Dutch university. A…

Dropout is one of the major problems online higher education faces. Early identification of the dropout risk level and an intervention mechanism to revert the potential risk have been proved as the key answers to solving the challenge. Predictive modeling has been extensively studied on course dropout. However, intervention practices are scarce,…

Despite a high primary school enrollment in India, the overall learning levels have been low, and the dropout level in secondary school and beyond has been high. One reason for low learning levels and high drop-out rates is the student's lack of motivation to learn in the classroom. We suggest that curiosity may be a useful tool to improve student…

Early school leaving is an outcome of complex and long-term processes comprising personal, institutional, and systemic factors. Studies on individuals in Hungary have identified a connection between early school leaving and teaching practices at schools. The creation of supportive learning environments in turn can contribute to preventing early…

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:…

Early leaving studies demonstrate it is possible to improve young people's opportunities through education and training. The current research evidence has yet to agree a definitive answer as to where the primary policy focus to improve their life chances should be. That is, which risk factors are the most impactful for minimising early school…

Within OECD countries, 20% of university students continue no further than the first year. The objective of this research is to analyse the antecedents of student commitment, so as to design action plans for reducing dropout rates within higher education. Educational engagement, student--university identification and perception of performance were…

Inefficient targeting of students at risk of dropping out might explain why dropout-reducing efforts often have no or mixed effects. In this study, we present a new method which uses a series of machine learning algorithms to efficiently identify students at risk and makes the sensitivity/precision trade-off inherent in targeting students for…

In recent years, initiatives and the resulting application of precision education have been applied with increasing frequency in Taiwan; the accompanying discourse has focused on identifying potential applications for artificial intelligence and how to use learning analytics to improve teaching quality and learning outcomes. This study used the…

We investigated changes in youths' intentions to quit school after following a group-based cognitive behaviour therapy (CBT) based intervention for depressed adolescents in upper secondary school: the Adolescent Coping with Depression Course (ACDC). Data were collected from 228 youths, 133 of whom received the 14-week ACDC intervention and 95 who…