A Comprehensive Review of the Major Studies and Theoretical Models of Student Retention in Higher Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>Student retention rate has been a major concern for tertiary institutions around the world since the establishment of formal education. Generally speaking, not every student completes his or her study program. Although students fail to graduate for different reasons, some of them choose to voluntarily withdraw from their study programs. This might affect the image of the tertiary institutions in many different ways including their academic reputation and financial plans. To deal with such critical issue, there is a need for strategies and plans that are based on the findings of scientific research. The literature of student retention in higher education is rich of the theoretical models and empirical studies that gained consideration among researchers and educators over the last four decades. Therefore, some of these studies and theoretical models were comprehensively reviewed and discussed. The purpose of this is to provide researchers, educators and policy makers with a background to this issue and the latest strategies and techniques that help them deal with it as well as to find the common patterns and themes of the mostly reported student attrition factors.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it