Analyzing the Findings of the Saudi Research on Student Attrition in Higher Education
Bibliographic record
Abstract
<p class="apa">This paper presents a comprehensive review of the available literature on student attrition in Saudi higher education context. Despite the reported low student retention rates in Saudi tertiary institutions, student attrition remains an under-researched phenomenon. Thus, this paper aims to trace and collect all the available studies that addressed the issue of low student retention in the Saudi in higher education and to present and analyse their findings. This will help in providing evidence and empirical data that give a clearer view of the problem and pave the way for the future researchers as well as allowing for suggestions towards more effective plans and solutions. The student attrition factors reported in the reviewed Saudi studies were classified under personal, academic, social and institutional categories. However, the students’ low academic abilities and institutional factors were the most common across all of the studies. These factors relate to students’ experiences with the administrative system of their academic institution, including the admission, registration and disciplinary rules and policies and the availability and quality of student services and facilities.</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.
How this classification was reachedexpand
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".