Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Classification | 1 |
| College Students | 1 |
| Comparative Analysis | 1 |
| Course Selection (Students) | 1 |
| Decision Making | 1 |
| Enrollment | 1 |
| Inferences | 1 |
| Management Systems | 1 |
| Mathematical Models | 1 |
| Models | 1 |
| Private Colleges | 1 |
| More ▼ | |
Source
| International Educational… | 1 |
Publication Type
| Reports - Research | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textGruver, Nate; Malik, Ali; Capoor, Brahm; Piech, Chris; Stevens, Mitchell L.; Paepcke, Andreas – International Educational Data Mining Society, 2019
Understanding large-scale patterns in student course enrollment is a problem of great interest to university administrators and educational researchers. Yet important decisions are often made without a good quantitative framework of the process underlying student choices. We propose a probabilistic approach to modelling course enrollment…
Descriptors: Models, Course Selection (Students), Enrollment, Decision Making
