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Celia Galve-González; Ana Belén Bernardo; Adrián Castro-López – European Journal of Psychology of Education, 2024
University dropout is a phenomenon of growing interest due to its negative consequences. Various variables have been studied in order to understand why this problem occurs. Satisfaction with the degree choice, self-regulation strategies and engagement within the university are some of the variables that have been studied in order to understand why…
Descriptors: College Students, Potential Dropouts, Decision Making, Student Attitudes
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
Andreas Hadjar; Christina Haas; Irina Gewinner – European Journal of Higher Education, 2023
Based on the classic models developed by Spady and Tinto on the link between social and academic integration and dropout, we propose a refined model to explain dropout intentions--relating to dropout from higher education (HE) and dropout from a specific study programme--that more strongly emphasises individual background characteristics (e.g.…
Descriptors: Individual Characteristics, Higher Education, Potential Dropouts, Intention
Katie Ellis; Claire Johnston – Higher Education: The International Journal of Higher Education Research, 2024
Over 80,000 children in England were being looked after in Local Authority care in 2020 and a further 40,000 people were defined as 'care leavers'. Although a significant body of research highlights the prevalence of educational low achievement in the care experienced population, official government figures show that around 13% of care experienced…
Descriptors: Foreign Countries, College Students, Foster Care, Resilience (Psychology)
Chelsea Kuehner-Boyer – ProQuest LLC, 2024
The Institute of Medicine has found that barriers exist that directly contribute to the underrepresentation of racial and ethnic groups in health professional education. Yet, little research has been done to evaluate the barriers that affect athletic training students. An integrative review was conducted to identify barriers that affect students…
Descriptors: Student Athletes, Barriers, College Athletics, Health Sciences
Jialun Pan; Zhanzhan Zhao; Dongkun Han – IEEE Transactions on Learning Technologies, 2025
Properly predicting students' academic performance is crucial for elevating educational outcomes in various disciplines. Through precise performance prediction, schools can quickly pinpoint students facing challenges and provide customized educational materials suited to their specific learning needs. The reliance on teachers' experience to…
Descriptors: Prediction, Academic Achievement, At Risk Students, Artificial Intelligence
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
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
Deho, Oscar Blessed; Joksimovic, Srecko; Li, Jiuyong; Zhan, Chen; Liu, Jixue; Liu, Lin – IEEE Transactions on Learning Technologies, 2023
Many educational institutions are using predictive models to leverage actionable insights using student data and drive student success. A common task has been predicting students at risk of dropping out for the necessary interventions to be made. However, issues of discrimination by these predictive models based on protected attributes of students…
Descriptors: Learning Analytics, Models, Student Records, Prediction
Rosó Baltà-Salvador; Marta Peña; Ana-Inés Renta-Davids; Noelia Olmedo-Torre – European Journal of Engineering Education, 2024
The under-representation of women in male-dominated STEM fields is a worldwide concern. However, there are other academic fields, like some non-STEM degrees, where female students are over-represented. Previous research has identified five critical factors influencing student participation rates: career choice, satisfaction, self-esteem,…
Descriptors: Females, Disproportionate Representation, Career Choice, 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
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
Jonas Koopmann; Lena M. Zimmer; Markus Lörz – European Journal of Higher Education, 2024
Due to the COVID-19 pandemic, contact, education, and employment opportunities have fundamentally changed worldwide. However, various studies have pointed out that not everyone is equally affected by the changed circumstances. This paper focuses on the impact of the pandemic on the study situation in German higher education and explores the…
Descriptors: COVID-19, Pandemics, Equal Education, Foreign Countries
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
Popa Berce, Carmen Alina; Heciu, Iulia; Bochis, Laura – Acta Didactica Napocensia, 2022
The aim of the study is to highlight the efficiency of a program of activities implemented to develop the level of learning metacognitive awareness of students with low academic performance. The study was conducted on a total of 28 students from the Faculty of Social Humanistic Sciences, University of Oradea, Romania, equally divided into two…
Descriptors: Metacognition, Low Achievement, Academic Achievement, Electronic Learning