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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
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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
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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
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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
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Stephen M. McPherson – SRATE Journal, 2025
This quantitative based applied research study examined data collected fromstudents who have withdrawnfromor completed aneducator preparation program (EPP) ina small rural public community college in WestVirginia. This study compared studentretention rates with Frontier andRemote (FAR) designation by home zip code. These data informedthe research…
Descriptors: Teacher Education, Rural Schools, Public Colleges, Community Colleges
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Oda Charlotte Larsen Saetre; Serap Keles; Thormod Idsoe – Scandinavian Journal of Educational Research, 2024
We investigated changes in youths' intentions to quit school after following a group-based cognitive behaviour therapy (CBT) based intervention for depressed adolescents in upper secondary school: the Adolescent Coping with Depression Course (ACDC). Data were collected from 228 youths, 133 of whom received the 14-week ACDC intervention and 95 who…
Descriptors: Depression (Psychology), Correlation, Intention, Dropouts
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Selim, Kamal Samy; Rezk, Sahar Saeed – Education and Information Technologies, 2023
Compulsory school-dropout is a serious problem affecting not only the education systems, but also the developmental progress of any country as a whole. Identifying the risk of dropping out, and characterizing its main determinants, could help the decision-makers to draw eradicating policies for this persisting problem and reducing its social and…
Descriptors: Foreign Countries, Dropouts, Predictor Variables, At Risk Students
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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
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Pei, Bo; Xing, Wanli – Journal of Educational Computing Research, 2022
This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for…
Descriptors: At Risk Students, Learning Analytics, Information Retrieval, Models
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Sharifah Holder; Munjireen Sifat; Charlene Kuo; Kerry Green – Education and Urban Society, 2024
Racial disparities are evident in both educational outcomes and incarceration rates when comparing African American and white youth. It is essential to understand the school-to-prison pipeline and the ways in which school discipline practices and other factors disproportionately affect African American students, limit educational attainment, and…
Descriptors: Racial Differences, African American Students, White Students, Anxiety
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Baltà-Salvador, Rosó; Olmedo-Torre, Noelia; Peña, Marta – IEEE Transactions on Education, 2022
Contribution: The present research provides new evidence on the predictors of foreign-born (FB) students' dropout and the situations of discrimination that emerge on engineering campuses. Background: Ethnic minority students remain underrepresented in engineering degrees and have higher dropout rates than their White peers. Previous literature…
Descriptors: Racial Discrimination, Dropouts, Intention, Disproportionate Representation
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Varga, Erika B.; Sátán, Ádám – Hungarian Educational Research Journal, 2021
The purpose of this paper is to investigate the pre-enrollment attributes of first-year students at Computer Science BSc programs of the University of Miskolc, Hungary in order to find those that mostly contribute to failure on the Programming Basics first-semester course and, consequently to dropout. Our aim is to detect at-risk students early,…
Descriptors: Identification, At Risk Students, Computer Science Education, Undergraduate Students
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Ortiz-Lozano, José María; Rua-Vieites, Antonio; Bilbao-Calabuig, Paloma; Casadesús-Fa, Martí – Innovations in Education and Teaching International, 2020
Student dropout is a major concern in studies investigating higher education retention strategies. However, studies investigating the optimal time to identify students who are at risk of withdrawal and the type of data to be used are scarce. Our study consists of a withdrawal prediction analysis based on classification trees using both…
Descriptors: At Risk Students, Dropouts, Undergraduate Students, Withdrawal (Education)
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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
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Wagner, Kerstin; Merceron, Agathe; Sauer, Petra; Pinkwart, Niels – International Educational Data Mining Society, 2023
In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design and which is based on the explainable k-nearest neighbor algorithm,…
Descriptors: College Freshmen, At Risk Students, Dropouts, Dropout Programs
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