Publication Date
| In 2025 | 0 |
| Since 2024 | 2 |
Descriptor
| Models | 2 |
| Student Attrition | 2 |
| After School Programs | 1 |
| Algorithms | 1 |
| Apprenticeships | 1 |
| Artificial Intelligence | 1 |
| At Risk Students | 1 |
| Classification | 1 |
| College Students | 1 |
| Dropouts | 1 |
| High School Students | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 2 |
| Journal Articles | 1 |
| Reports -… | 1 |
| Tests/Questionnaires | 1 |
Education Level
| High Schools | 1 |
| Higher Education | 1 |
| Postsecondary Education | 1 |
| Secondary Education | 1 |
Audience
Location
| Delaware | 1 |
| New York (New York) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textChuan 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
Direct linkClare Buckley Flack; John Sludden; James J. Kemple – Research Alliance for New York City Schools, 2024
There is currently a heavy emphasis on career-connected learning for high school students in New York City. ExpandED Schools' science, technology, engineering and mathematics (STEM) Options (ES Options) program predates the newest of these initiatives. Launched in 2019, ES Options combines a credit-bearing STEM apprenticeship in the spring with a…
Descriptors: After School Programs, Work Experience Programs, STEM Education, Student Participation
