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…

Understanding student engagement with the institution from the first day of classes to the end of the semester would help inform the institution of the potential risk that a student will drop out of a class or of the school. Learning Management Systems (LMS) record student interactions with the system and might be able to be used to identify…

Students' perception of excessive difficulty in STEM degrees lowers their motivation and, therefore, affects their performance. According to prior research, the use of gamification techniques promote engagement, motivation, and fun when learning. Badges, which are a distinction that is given as a reward to students, are a well-known gamification…

In the United States, doctoral students have a fifty percent chance of graduating from their institutions with a doctoral degree (Berelson, 1960; Bowen & Rudenstein, 1992; Lovitts, 2001; Sowell et al., 2015); however, this percentage decreases when race and ethnicity are included (Lovitts, 2001; Nettles & Millett, 2006). Research indicates…

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.…

In this study, an early warning system predicting first-year undergraduate student academic performance is developed for higher education institutions. The significant factors that affect first-year student success are derived and discussed such that they can be used for policy developments by related bodies. The dataset used in experimental…

At a community college in the state of Florida, student retention has become a critical concern because more than half of the first-year first-generation students fail to graduate. That rate is four times higher than for other first-year students. Guided by Tinto's Student Integration Model as the conceptual framework, this intrinsic qualitative…

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…

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…

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…