Publication Date
In 2025 | 0 |
Since 2024 | 3 |
Descriptor
Influences | 3 |
Potential Dropouts | 3 |
Accuracy | 2 |
Artificial Intelligence | 2 |
College Students | 2 |
Prediction | 2 |
Academic Achievement | 1 |
Algorithms | 1 |
At Risk Students | 1 |
Barriers | 1 |
College Athletics | 1 |
More ▼ |
Author
Andrea Zanellati | 1 |
Chelsea Kuehner-Boyer | 1 |
Houssam El Aouifi | 1 |
Maurizio Gabbrielli | 1 |
Mohamed El Hajji | 1 |
Stefano Pio Zingaro | 1 |
Youssef Es-Saady | 1 |
Publication Type
Journal Articles | 2 |
Reports - Research | 2 |
Dissertations/Theses -… | 1 |
Education Level
Higher Education | 2 |
Postsecondary Education | 2 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Chelsea Kuehner-Boyer – ProQuest LLC, 2024
The Institute of Medicine has found that barriers exist that directly contribute to the underrepresentation of racial and ethnic groups in health professional education. Yet, little research has been done to evaluate the barriers that affect athletic training students. An integrative review was conducted to identify barriers that affect students…
Descriptors: Student Athletes, Barriers, College Athletics, Health Sciences
Houssam El Aouifi; Mohamed El Hajji; Youssef Es-Saady – Education and Information Technologies, 2024
Dropout refers to the phenomenon of students leaving school before completing their degree or program of study. Dropout is a major concern for educational institutions, as it affects not only the students themselves but also the institutions' reputation and funding. Dropout can occur for a variety of reasons, including academic, financial,…
Descriptors: At Risk Students, Potential Dropouts, Identification, Influences
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