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…

This article sets out to share the experience of a Cork Education and Training Board (CETB) Further Education and Training (FET) Guidance Counsellor on collaborating with FET Literacy and Apprenticeship Services colleagues to support young male early school leavers who had achieved less than the required five passes in their Junior Certificate to…

Purpose: Unemployment has a conflicting influence on Higher Education (HE) dropout, decreasing both opportunity costs and expected benefits of studying. Herein, we aim to distinguish these two effects, by using the unemployment rate of individuals with secondary education for measuring the first effect and the unemployment rates of HE recent…

In many countries with apprenticeship-based vocational education and training (VET), dropout from apprenticeship training is a major concern. Leaving an apprenticeship early can be problematic, particularly for young people who do not continue their training at another company or in another occupation, and drop out of the education system without…

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…

The majority of adolescents communicate via text-based messaging, particularly through WhatsApp, a widely used free communication application. Written content on WhatsApp has the methodological potential to provide rich qualitative interview data. This study compares data collected using text-based WhatsApp versus face-to-face interview…

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…

Most students who begin at a community college do not complete their desired credential. Many students fail to graduate due to various barriers other than their academic performance. To encourage previously successful non-completers to re-enroll and eventually graduate, a growing number of community colleges have implemented re-enrollment…

Since the expansion of higher education began, student motivation and institutional choice have been widely studied, yet the reasons behind high dropout rates in public institutions in Central and Eastern Europe remain poorly understood. In our research, we sought to answer the question of what subjective and objective factors predict an increased…

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…

Students with high incidence disabilities are dropping out of high school at alarming rates. Compared with other demographic groups, students with disabilities have the lowest graduation rates of any group in the nation. The substandard graduation rates have remained stagnant for two decades, indicating that programmatic attempts to address the…

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.…

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:…