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Melisa Diaz Lema; Melvin Vooren; Marta Cannistrà; Chris van Klaveren; Tommaso Agasisti; Ilja Cornelisz – Studies in Higher Education, 2024
Study success in Higher Education is of primary importance in the European policy agenda. Yet, given the diverse educational landscape across countries and institutions, more coordinated action is needed to gain a more solid knowledge of the dropout phenomenon. This study aims to gain a better insight into students' dropout based on an integrated…
Descriptors: Foreign Countries, Dropout Research, College Students, Dropouts
Chiara Masci; Marta Cannistrà; Paola Mussida – Studies in Higher Education, 2024
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…
Descriptors: Foreign Countries, Dropouts, Dropout Prevention, Potential Dropouts
Andrea Zanellati; Stefano Pio Zingaro; Maurizio Gabbrielli – IEEE Transactions on Learning Technologies, 2024
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…
Descriptors: Dropouts, Dropout Characteristics, Potential Dropouts, Artificial Intelligence
Gabriella Pusztai; Anett Hrabéczy; Cintia Csók – Open Education Studies, 2025
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…
Descriptors: College Students, Dropout Prevention, Parent Participation, At Risk Students
Talamás-Carvajal, Juan Andrés; Ceballos, Héctor G. – Education and Information Technologies, 2023
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.…
Descriptors: College Students, Dropout Prevention, At Risk Students, Identification
Mareike Rußmann; Nicolai Netz; Markus Lörz – Higher Education: The International Journal of Higher Education Research, 2024
We examine the mechanisms explaining the dropout intentions of students with disabilities by integrating Tinto's model of student integration, the student attrition model, the composite persistence model, and insights from social stratification research. The resulting theoretical model posits that not only students' academic and social…
Descriptors: Foreign Countries, Students with Disabilities, Higher Education, Dropout Characteristics
Kokila Ranasinghe; T. Lakshini D. Fernando; Nimali Vineeshiya; Aras Bozkurt – International Review of Research in Open and Distributed Learning, 2025
This study examined the reasons for high dropout numbers in programs offered through open and distance education (ODE). A mixed method approach was employed to collect data from a purposive sample of instructors and students at the Open University of Sri Lanka. A total of 38 reasons were revealed, of which aligned with existing dropout models as…
Descriptors: Dropout Rate, Open Universities, Distance Education, College Faculty
Geisler, Sebastian; Rolka, Katrin; Rach, Stefanie – Educational Studies in Mathematics, 2023
The transition from school to university mathematics is a challenging process for many students. This phenomenon is reflected by high dropout rates from mathematics programs especially during the first year at university that may be related to the development of students' mathematical interest and self-concept. Taking a learning psychological…
Descriptors: College Freshmen, Student Interests, Self Concept, College Mathematics
Dahir Abdi Ali; Ali Mohamud Hussein – Journal of Applied Research in Higher Education, 2024
Purpose: The main purpose of this study is to evaluate the extent of dropout students and identify the relationship between risk factors of dropout and the survival time of students. Design/methodology/approach: The Kaplan-Meier estimator (KM), also known as the product-limit technique, is a nonparametric model function that is commonly used in…
Descriptors: Foreign Countries, College Students, At Risk Students, Potential Dropouts
Chuan Cai; Adam Fleischhacker – Journal of Educational Data Mining, 2024
We propose a novel approach to address the issue of college student attrition by developing a hybrid model that combines a structural neural network with a piecewise exponential model. This hybrid model not only shows the potential to robustly identify students who are at high risk of dropout, but also provides insights into which factors are most…
Descriptors: College Students, Student Attrition, Dropouts, Potential Dropouts
Cannistrà, Marta; Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, Anna Maria – Studies in Higher Education, 2022
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…
Descriptors: Dropouts, Potential Dropouts, Dropout Prevention, Dropout Characteristics
Baneres, David; Rodriguez-Gonzalez, M. Elena; Guerrero-Roldan, Ana Elena – IEEE Transactions on Learning Technologies, 2023
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…
Descriptors: Prediction, Models, Identification, Potential Dropouts
Zühlke, Anne; Kugler, Philipp; Hackenberger, Armin; Brändle, Tobias – Education Economics, 2022
We analyse the economic returns in lifetime labour income of various educational paths in Germany. Using recent data, we calculate cumulative labour earnings at different ages and for different educational paths while controlling the parental background of individuals. We find that after the age of 55, lifetime labour income is higher for…
Descriptors: Foreign Countries, College Students, Potential Dropouts, Dropouts
Roberts, Nicola – Journal of Further and Higher Education, 2023
Globally, statistical analyses have found a range of variables that predict the odds of first-year students failing to progress at their Higher Education Institution (HEI). Some of these studies have included students from a range of disciplines. Yet despite the rise in the number of criminology students in HEIs in the UK, little statistical…
Descriptors: Predictor Variables, Academic Achievement, Academic Failure, College Freshmen
Tim Baalmann; Ana Brömmelhaus; Julika Hülsemann; Michael Feldhaus; Karsten Speck – Journal of College Student Retention: Research, Theory & Practice, 2024
The importance of close social contacts in the educational process has been widely documented, but mainly for the school sector. The present article examines the importance of close relationships on university students' dropout tendencies. Using longitudinal panel data collected at a medium-sized German university, students (N = 7,169) were…
Descriptors: Foreign Countries, Parent Influence, Peer Influence, Intention