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Tomasz Zajac; Francisco Perales; Wojtek Tomaszewski; Ning Xiang; Stephen R. Zubrick – Higher Education: The International Journal of Higher Education Research, 2024
Understanding the drivers of student dropout from higher education has been a policy concern for several decades. However, the contributing role of certain factors--including student mental health--remains poorly understood. Furthermore, existing studies linking student mental health and university dropout are limited in both methodology and…
Descriptors: Foreign Countries, Mental Health, Dropout Characteristics, Dropout Prevention
Bañeres, David; Rodríguez-González, M. Elena; Guerrero-Roldán, Ana-Elena; Cortadas, Pau – International Journal of Educational Technology in Higher Education, 2023
Dropout is one of the major problems online higher education faces. Early identification of the dropout risk level and an intervention mechanism to revert the potential risk have been proved as the key answers to solving the challenge. Predictive modeling has been extensively studied on course dropout. However, intervention practices are scarce,…
Descriptors: Dropout Characteristics, Dropout Prevention, Identification, Intervention
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
Eegdeman, Irene; Cornelisz, Ilja; Meeter, Martijn; van Klaveren, Chris – Education Economics, 2023
Inefficient targeting of students at risk of dropping out might explain why dropout-reducing efforts often have no or mixed effects. In this study, we present a new method which uses a series of machine learning algorithms to efficiently identify students at risk and makes the sensitivity/precision trade-off inherent in targeting students for…
Descriptors: Foreign Countries, Vocational Schools, Dropout Characteristics, Dropout Prevention
Robin Clausen – AASA Journal of Scholarship & Practice, 2024
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…
Descriptors: Dropout Prevention, High School Students, Graduation, Graduation Rate
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
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
Inna Bentsalo; Krista Loogma; Meril Ümarik; Terje Väljataga – Vocations and Learning, 2024
A concern across many vocational education systems is the high dropout rate from their programs. This problem is likely to be exacerbated at time of low unemployment rates when employers are less demanding about the certification of skills at the time of employment. This qualitative study examines the factors associated with students leaving early…
Descriptors: Vocational Education, Foreign Countries, Dropout Characteristics, At Risk Students
Luis, Ricardo M. Meira Ferrão; Llamas-Nistal, Martin; Iglesias, Manuel J. Fernández – Smart Learning Environments, 2022
E-learning students have a tendency to get demotivated and easily dropout from online courses. Refining the learners' involvement and reducing dropout rates in these e-learning based scenarios is the main drive of this study. This study also shares the results obtained and crafts a comparison with new and emerging commercial solutions. In a…
Descriptors: Artificial Intelligence, Identification, Electronic Learning, Dropout Characteristics
Hillman, Nick – Higher Education Policy Institute, 2021
Non-continuation in higher education is rising up the political agenda. In the vernacular, it is often described negatively as 'dropping out'. But despite any terminological confusion, all such measures describe a gap between learners' original stated intentions and their situation when they leave their course. This policy note looks at the scale…
Descriptors: Foreign Countries, Dropouts, School Holding Power, Universities
Muench, Janice L. – ProQuest LLC, 2023
This research explores who is at risk of dropping out of high school and how collaborative Student Support Teams can contribute to students staying on track to graduate high school. The issue of student success is important because graduation is positively correlated with important life outcomes and ability to earn an adequate income in the labor…
Descriptors: High School Students, At Risk Students, Potential Dropouts, Dropout Characteristics
Ressa, Theodoto; Andrews, Allyson – International Journal of Modern Education Studies, 2022
Dropout happens when a student withdraws themselves from school at any level of education without a certificate to account for their education. It is an educational problem in America because of its negative consequences on society. Three-quarters of the fastest-growing occupations require more than a high school diploma, and yet, just over half…
Descriptors: Dropouts, Dropout Rate, Dropout Characteristics, Influences
Serafin, Melissa; Atella, Julie – Wilder Research, 2020
The purpose of Diploma On! is to re-engage students who have dropped out of school within member districts and ultimately increase the graduation rate in Hennepin County, Minnesota. Program staff obtain student contact information from identified referral sources within each district, normally after a 15-day drop. Next, they contact the student…
Descriptors: Dropouts, Graduation Rate, Dropout Prevention, Dropout Programs
Dorothea Glaesser; Christopher Holl; Julia Malinka; Laura McCullagh; Lydia Meissner; Nicole Syringa Harth; Maya Machunsky; Kristin Mitte – Social Psychology of Education: An International Journal, 2024
Disengagement is a concept that captures the gradual behavioral, affective, and cognitive distancing from school, and is thus an early indicator of students being at risk for dropout. Based on a social identity framework, we predicted that higher social identification with the class and a positive classroom climate would be associated with lower…
Descriptors: Learner Engagement, Social Environment, At Risk Students, Educational Environment
Rodrigo Duran; Silvia Amélia Bim; Itana Gimenes; Leila Ribeiro; Ronaldo Celso Messias Correia – ACM Transactions on Computing Education, 2023
"Motivation": Enrollments in Brazilian computing degrees are at an all-time high, but graduation numbers have not increased at the same rate. Moreover, enrollment growth has mainly attracted male students, steadily expanding the gender gap in Brazilian computing programs. Such high attrition rates have a great economic impact and may…
Descriptors: Foreign Countries, Academic Persistence, Intention, Dropout Characteristics