Factors Related to Student Persistence in Open Universities
Bibliographic record
Abstract
Student persistence has long been a major challenge for open universities. Despite the evolution of open education, an overall high student attrition rate remains. This paper examines the changes and trends in factors related to student persistence in open universities. It reviews the empirical studies from the 1970s to the 2010s which reported factors influencing student persistence. The relevant studies were searched from databases, including Scopus, Web of Science, and Google Scholar. Among the 108 studies collected, a total of 284 factors influencing student persistence were identified. The factors were categorised into student factors, institutional factors, and environmental factors. Their changes and trends over the years were examined. The results show that student factors were the most frequently studied over the years examined, with the major categories being students’ psychological attributes and outcomes. Institutional factors have been increasingly studied in recent decades, with the design and delivery of programmes and courses being the strongest category. Finally, environmental factors have been decreasingly examined, with factors related to students’ family and work being the two main categories. Based on the results, the implications for developing intervention and retention strategies for student persistence in open universities are discussed.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".