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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
Edwin Buenaño; María José Beletanga; Mónica Mancheno – Journal of Latinos and Education, 2024
University dropout is a serious problem in higher education that is increasingly gaining importance, as it is essential to understand its causes and search for public and institutional policies that can help reduce it. This research uses conventional and extended Cox survival models to analyze the factors behind dropout rates at a co-financed…
Descriptors: Foreign Countries, College Students, Dropouts, Dropout Rate
Xiao Wen; Hu Juan – Interactive Learning Environments, 2024
To address three issues identified in previous research this study proposes a clustering-based MOOC dropout identification method and an early prediction model based on deep learning. The MOOC learning behavior of self-paced students was analyzed, and two well-known MOOC datasets were used for analysis and validation. The findings are as follows:…
Descriptors: MOOCs, Dropouts, Dropout Characteristics, Dropout Research
Xinhong Zhang; Xiangyu Wang; Jiayin Zhao; Boyan Zhang; Fan Zhang – IEEE Transactions on Education, 2024
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…
Descriptors: MOOCs, Dropout Characteristics, Dropout Research, Predictor Variables
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
Thao-Trang Huynh-Cam; Long-Sheng Chen; Tzu-Chuen Lu – Journal of Applied Research in Higher Education, 2025
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…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Dropout Characteristics
Mendes Vieira, Kelmara; Bender Filho, Reisoli; Da Silva Costa Junior, Elizeu; Martins Santos, Gilberto – Turkish Online Journal of Distance Education, 2023
This research seeks to understand the determinants of student dropout in the courses offered at the Open University of Brazil system at the Federal University of Santa Maria. The research used the following methods: survival function, factorial analysis, and logistic function. Results indicated that male students, with higher levels of income, who…
Descriptors: Distance Education, Dropouts, Foreign Countries, College Students
Stefanie Findeisen; Alexander Brodsky; Christian Michaelis; Beatrice Schimmelpenningh; Jürgen Seifried – Empirical Research in Vocational Education and Training, 2024
Evidence on the extent to which dropout intention can serve as a valid predictor of dropout decisions remains scarce. This study first presents the results of a systematic literature review of 14 studies examining the relationship between dropout intention and actual dropout in post-secondary education (vocational education and training [VET] or…
Descriptors: At Risk Students, Intention, Dropouts, Predictor Variables
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
Marcell Nagy; Roland Molontay – International Journal of Artificial Intelligence in Education, 2024
Student drop-out is one of the most burning issues in STEM higher education, which induces considerable social and economic costs. Using machine learning tools for the early identification of students at risk of dropping out has gained a lot of interest recently. However, there has been little discussion on dropout prediction using interpretable…
Descriptors: Dropout Characteristics, Dropout Research, Intervention, At Risk Students
Naaman, Hind – European Educational Researcher, 2021
Higher education dropout has been considered a major concern for several researchers in the field of education around the World. Although different studies were carried out to deal with the topic, they all faced common limitations. This paper explores the twofold research conducted to investigate higher education dropout in Education studies at…
Descriptors: Dropouts, Dropout Research, Foreign Countries, College Students
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
Wild, Steffen; Rahn, Sebastian; Meyer, Thomas – Empirical Research in Vocational Education and Training, 2023
Cooperative education programs are usually based on a partnership between companies and universities. Dropouts have a particular impact here, for example the loss of junior staff in the companies. Most dropouts in cooperative education occur in the first academic year. In this multicausal dropout process, the influence of the cooperation partner…
Descriptors: Foreign Countries, College Freshmen, Dropouts, Dropout Characteristics
Ntema, Ratoeba Piet – Journal of Student Affairs in Africa, 2022
Student dropout is a significant concern for university administrators, students and other stakeholders. Dropout is recognised as highly complex due to its multi-causality, which is expressed in the existing relationship in its explanatory variables associated with students, their socio-economic and academic conditions, and the characteristics of…
Descriptors: College Students, Dropout Characteristics, At Risk Students, Profiles
Kimberly A. Levin – ProQuest LLC, 2022
The true purpose of this study is to contribute to researchers' and practitioners' understanding of the power of Teacher-Student Relationships (TSRs) relative to at-risk students' graduation status. Much of the research surrounding dropouts focuses on root causes like attendance, retention, and families' economic status. However, minimal research…
Descriptors: Teacher Student Relationship, Interaction, At Risk Students, Graduation