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Maguire, Sue – Journal of Education and Work, 2021
While measures to combat 'Early Leaving' (EL) have been widely adopted internationally, as a means of curbing rates of economic and social exclusion among young people, the term itself is not widely utilised across the UK. That is not to say that measuring and reducing the number of young people who drop out of education (or training) before…
Descriptors: Foreign Countries, Dropouts, Out of School Youth, Compulsory Education
Yeung, Ryan – Journal of School Health, 2020
Background: This study investigates how the Medicaid Expansion of the Affordable Care Act affected state high school dropout rates. Methods: This study relies on a differences-in-differences estimation strategy that is common in program evaluation, especially in education. This method replicates in a regression framework a classic pre-test…
Descriptors: Federal Legislation, Dropouts, Health Insurance, High School Students
Dawson, Rachel Fulcher; Kearney, Melissa S.; Sullivan, James X. – National Bureau of Economic Research, 2020
We describe the challenge of college non-completion in the U.S. and a variety of explanations for the high rate of non-completion. We then provide an overview of the implementation of and evidence from eight specific college completion interventions designed to increase college completion rates through a comprehensive set of services. The eight…
Descriptors: Graduation Rate, College Graduates, Dropouts, Intervention
Stephani L. Wrabel; Jennie W. Wenger; Linda Cottrell – RAND Corporation, 2025
The National Guard Youth ChalleNGe program is a residential, quasi-military program that serves young people ages 16 to 18 who are struggling to complete their high school credential. This is the ninth report in an annual series that RAND researchers have issued. The prior annual reports cover 2015 through 2022. Each annual report documents the…
Descriptors: High School Students, Residential Programs, Military Training, Youth Programs
Tim Baalmann – Research in Higher Education, 2024
One in three students suffers from at least one common mental disorder highlighting the high prevalence of health issues in higher education. At the same time, every third student drops out of university without achieving their degrees. Nevertheless, connections between health and students' dropout behavior have hardly been investigated. Grounding…
Descriptors: Foreign Countries, Mental Disorders, Dropouts, Student Behavior
Meriem Zerkouk; Miloud Mihoubi; Belkacem Chikhaoui; Shengrui Wang – Education and Information Technologies, 2024
School dropout is a significant issue in distance learning, and early detection is crucial for addressing the problem. Our study aims to create a binary classification model that anticipates students' activity levels based on their current achievements and engagement on a Canadian Distance learning Platform. Predicting student dropout, a common…
Descriptors: Artificial Intelligence, Dropouts, Prediction, Distance Education
Brian Johnson; Amy L. Reschly; Roy P. Martin; Christopher Pinzone; James J. Appleton – Journal of Education for Students Placed at Risk, 2024
Theories of student engagement for dropout and school completion are proposed to begin as early as age five. Student engagement in elementary-age students has been linked to school completion, post-secondary education, and achievement. However, there is little research examining patterns and profiles of student engagement in this population. In an…
Descriptors: Elementary School Students, Grade 3, Learner Engagement, Student Characteristics
Jing Chen; Bei Fang; Hao Zhang; Xia Xue – Interactive Learning Environments, 2024
High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…
Descriptors: MOOCs, Potential Dropouts, Prediction, Artificial Intelligence
Barragán, Sandra; González, Leandro; Calderón, Gloria – Interchange: A Quarterly Review of Education, 2022
A combination of mathematical and statistical modelling techniques may be used to analyse student dropout behaviour. The aim of this study is to combine Survival Analysis and Analytic Hierarchy Process methodologies when identifying students at-risk of dropping out. This combination favours the institutional understanding of dropout as a dynamic…
Descriptors: Undergraduate Students, Gender Differences, Age Differences, Decision Making
De Silva, Liyanachchi Mahesha Harshani; Chounta, Irene-Angelica; Rodríguez-Triana, María Jesús; Roa, Eric Roldan; Gramberg, Anna; Valk, Aune – Journal of Learning Analytics, 2022
Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…
Descriptors: College Students, Dropouts, Dropout Prevention, Data Analysis
Buzgar, Ramona; Opre, Dana; Pintea, Sebastian; Opre, Adrian – Journal of Educational Sciences, 2021
Remedial activities are considered by many authors as an effective strategy for preventing and reducing school dropout. In recent years however, numerous studies showed evidence that we cannot point to one factor that influences the decision to leave school and to only one strategy to prevent or reduce it. Meanwhile the results in the field of…
Descriptors: Foreign Countries, Dropouts, Dropout Prevention, Remedial Instruction
Buyruk Genç, Arzu; Amanvermez, Yagmur; Zeren, Serife Gonca; Erus, Seher Merve – Pegem Journal of Education and Instruction, 2019
In this study, dropout from counseling sessions were investigated in order to examine the underlying causes of dropout. Forty-five university students who applied for counseling but dropped out after the preliminary interview or after any of the sessions participated in the study. The data of the research were collected by Counseling Dropout…
Descriptors: Counseling, Dropouts, College Students, Client Characteristics (Human Services)
Jiyun Elizabeth L. Shin – Social Psychology of Education: An International Journal, 2025
Impostorism is a psychological phenomenon characterized by persistent self-doubt and a fear of being exposed as an intellectual fraud, despite objective records of success. This phenomenon was first observed among high achieving women. The current study investigated impostorism among graduate women in science, technology, engineering, and…
Descriptors: Self Concept, Fear, Females, Graduate Students
Ripsimé K. Bledsoe – Community College Review, 2025
Objective: While much research has been conducted on retention, attrition, and college completion among those who voluntarily withdraw from college, few studies have focused on involuntary withdrawal in the form of academic dismissal. Even less scholarship has examined the subsequent restoration of academic momentum for returning students.…
Descriptors: Reentry Students, Withdrawal (Education), Admission (School), Community College Students
Alexander Karl Ferdinand Loder – European Journal of Education, 2025
University students of Business Administration and related fields have high dropout rates, with previous research identifying student profiles of dropouts in business studies. Evidence is lacking for other university systems. Austria (Europe) allows for multiple enrollments and students with multiple enrollments accomplish more workload even after…
Descriptors: Undergraduate Students, Business Education, Business Administration, Bachelors Degrees

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