Dropout rates in higher education (HE) are particularly high for non-traditional students which may be due to unadjusted educational policies. Considering as non-traditional the students who are employed at the enrolment moment and using a longitudinal database containing information on 5351 students from a Portuguese HE institution, an event…

Despite the robust literature on the effects of financial aid, the effects of financial aid loss remain largely understudied. We employ a regression discontinuity design, leveraging a minimum GPA scholarship renewal threshold, to examine the effect of losing state merit aid eligibility on college student stop-out, transfer, and bachelor's degree…

Despite the robust literature on the effects of financial aid, the effects of financial aid loss remain largely understudied. We employ a regression discontinuity design, leveraging a minimum GPA scholarship renewal threshold, to examine the effect of losing state merit aid eligibility on college student stop-out, transfer, and bachelor's degree…

The tutor's role in enhancing student retention in distance learning is paramount. This study aims to predict retention and not actual retention by investigating how tutoring support predicts student retention in distance learning at the University of Cape Coast in Ghana. Moore Transactional Distance Theory underpinned the theoretical framework of…

Changing majors or dropping out are of great concern to universities worldwide, but the role of learning approaches in terms of students' persistence has not been previously studied. Changing majors, especially in chemistry, is a severe problem in Finland. Here, learning approach data were collected with the ChemApproach questionnaire from 733…

Online education has been experiencing steadily increasing enrollment rates and it is therefore vital to study student and institutional factors related to dropout risk for online students. Currently, prior research examining this rapidly developing field is limited. With online graduate programs experiencing continuous growth in enrollment rates,…

We present an educational data analytics case study aimed at the early detection of potential dropout in Computer Engineering studies in Cuba. We have employed institutional data of 456 students and performed several experiments for predicting their permanency into three (promotion, repetition, and dropout) or two classes (promoting, not…

This study examined graduation and persistence among social and behavioral science students at a regional comprehensive university. Hazard analyses identified predictors of student trajectories, times at which predictors were more or less impactful, and interactions between predictors such that particular risk factors were more detrimental for…

Young adult carers are four times more likely than other students to drop out of higher education and are amongst the under-represented and disadvantaged groups targeted in the National Strategy for Access and Student Success in Higher Education in the UK. Non-completion of studies has implications not just for the individuals themselves, but also…

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…

Support provided by the research advisor is understood to be one of the keys to success in higher-level studies. However, support remains a construct operationalised in many different ways, making it difficult to prescribe those behaviours supervisors should adopt or abandon to optimise support offered to students. This self-report study examines…

Retention of students is a problem faced by institutions of higher education around the world. Higher education institutions are required to report retention data to government agencies and they depend on tuition funding more than ever before. Prior research has identified many characteristics that when present, increase the likelihood of early…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

This exploratory mixed-methods study examines factors contributing to doctoral students' consideration of departure from their graduate programs with comparisons made by sex and affiliation with Science, Technology, Engineering, and Mathematics (STEM) programs. Logistic regression and qualitative analyses point to the importance of strong…

College students experiencing psychological distress are at unique risk for negative academic outcomes. The Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62; Locke et al., 2011) is a multidimensional symptom inventory designed for use in college counseling centers. However, the relationships between the CCAPS-62 and functional…