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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
Pedro Ricardo Álvarez-Pérez; David López-Aguilar; María Olga González-Morales; Rocío Peña-Vázquez – Journal of College Student Retention: Research, Theory & Practice, 2024
The relationship between engagement and the intention to drop out was the focus of this research. Following an empirical-analytical approach, a sample of 1,122 university students responded to a questionnaire designed to measure the engagement and the intention to drop out of school. The results confirmed that undergraduates who considered…
Descriptors: Undergraduate Students, Learner Engagement, Dropout Attitudes, Dropout Prevention
Chiara Masci; Marta Cannistrà; Paola Mussida – Studies in Higher Education, 2024
This paper investigates the student dropout phenomenon in a technical Italian university from a time-to-event perspective. Shared frailty Cox time-dependent models are applied to analyse the careers of students enrolled in different engineering programs with the aim of identifying the determinants of student dropout through time, predicting the…
Descriptors: Foreign Countries, Dropouts, Dropout Prevention, Potential Dropouts
Josep Figueroa-Cañas; Teresa Sancho-Vinuesa – Open Learning, 2024
Practitioners of the statistics course embedded in a computer science programme at a fully online university were concerned with the high dropout rate. In the academic year 2018-19, they decided to carry out a two-phase project in order to address this issue. In the first phase, an early classifier to identify students at risk of dropping out of…
Descriptors: Foreign Countries, College Students, Virtual Schools, Online Courses
Steffen Wild; Sebastian Rahn; Thomas Meyer – International Journal of Education in Mathematics, Science and Technology, 2024
Dropout rates in engineering degree programmes at universities are high, and skilled workers are needed. Universities try to prevent dropouts with different offers one of which is attending bridging courses. Research on the effects of these programmes is rare, especially in subject-specific programmes and study formats like cooperative education.…
Descriptors: Foreign Countries, Engineering Education, Undergraduate Students, Dropout Rate
Roger Sheng So – ProQuest LLC, 2024
Understanding student engagement with the institution from the first day of classes to the end of the semester would help inform the institution of the potential risk that a student will drop out of a class or of the school. Learning Management Systems (LMS) record student interactions with the system and might be able to be used to identify…
Descriptors: Learning Management Systems, Data Use, At Risk Students, Learner Engagement
Hillary Webb-Ganaway – ProQuest LLC, 2024
In the United States, doctoral students have a fifty percent chance of graduating from their institutions with a doctoral degree (Berelson, 1960; Bowen & Rudenstein, 1992; Lovitts, 2001; Sowell et al., 2015); however, this percentage decreases when race and ethnicity are included (Lovitts, 2001; Nettles & Millett, 2006). Research indicates…
Descriptors: Doctoral Students, Blacks, African American Students, Academic Persistence
Cem Recai Çirak; Hakan Akilli; Yeliz Ekinci – Higher Education Quarterly, 2024
In this study, an early warning system predicting first-year undergraduate student academic performance is developed for higher education institutions. The significant factors that affect first-year student success are derived and discussed such that they can be used for policy developments by related bodies. The dataset used in experimental…
Descriptors: Program Development, At Risk Students, Identification, College Freshmen
Tanya Washington Bostic – ProQuest LLC, 2024
At a community college in the state of Florida, student retention has become a critical concern because more than half of the first-year first-generation students fail to graduate. That rate is four times higher than for other first-year students. Guided by Tinto's Student Integration Model as the conceptual framework, this intrinsic qualitative…
Descriptors: Community Colleges, First Generation College Students, College Freshmen, Dropout Rate
Javier Borja-Gil; Mario Castellanos Verdugo; M. Ángeles Oviedo-García – European Journal of Education, 2024
Within OECD countries, 20% of university students continue no further than the first year. The objective of this research is to analyse the antecedents of student commitment, so as to design action plans for reducing dropout rates within higher education. Educational engagement, student--university identification and perception of performance were…
Descriptors: Academic Persistence, College Students, Dropouts, Foreign Countries
Kerstin Wagner; Agathe Merceron; Petra Sauer; Niels Pinkwart – Journal of Educational Data Mining, 2024
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, is based on the explainable k-nearest neighbor algorithm and recommends a…
Descriptors: At Risk Students, Algorithms, Foreign Countries, Course Selection (Students)
Jingjing Long; Jiaxin Lin – Education and Information Technologies, 2024
English language learning students in China often feel challenged to learn English due to lack of motivation and confidence, pronunciation and grammar difference, lack of practice and people to communicate with etc., which affects students mental health. Adopting Big data and AI will help in overcoming these limitations as it provides personalized…
Descriptors: Foreign Countries, English Language Learners, College Students, Mental Health
Harsimran Singh; Banipreet Kaur; Arun Sharma; Ajeet Singh – Education and Information Technologies, 2024
Today, the main aim of educational institutes is to provide a high level of education to students, as career selection is one of the most important and quite difficult decisions for learners, so it is essential to examine students' capabilities and interests. Higher education institutions frequently face higher dropout rates, low academic…
Descriptors: College Students, At Risk Students, Academic Achievement, Artificial Intelligence
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
D. V. D. S. Abeysinghe; M. S. D. Fernando – IAFOR Journal of Education, 2024
"Education is the key to success," one of the most heard motivational statements by all of us. People engage in education at different phases of our lives in various forms. Among them, university education plays a vital role in our academic and professional lives. During university education many undergraduates will face several…
Descriptors: Models, At Risk Students, Mentors, Undergraduate Students
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