The Part-Time Student Experience: Its Influence on Student Engagement, Perceptions, and Retention
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
Part-time learners have had a history of campus isolation, fewer opportunities to engage on campus, and much higher attrition rates than their full-time peers (Jacoby, 2015; Rajasekhara & Hirsch, 2000). As a result, this study sought to uncover effective ways of enhancing the academic and social experiences of part-time learners and, in turn, increase retention rates. The attitudes, experiences, perceived needs, and challenges of 41 part-time students at a large Canadian community college during the fall 2015 semester were captured through an anonymous survey. From the data gathered, effective ways to enhance the college experiences of part-time students were identified and a relationship between school affinity and a part-time learner’s motivation to remain in school and persist to graduation were established. Recommendations resulting from this study centre on flexibility, availability, and student choice for post-secondary programs, courses, services, and social events aimed at part-time learners.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.018 | 0.001 |
| Scholarly communication | 0.001 | 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