Undergraduate nursing students’ perceptions of educational service quality at Alexandria University, Egypt
Bibliographic record
Abstract
This study investigated nursing students’ perceptions towards educational service quality provided by specialty departments at the Faculty of Nursing, Alexandria University. It also identified barriers and offers recommendations for improvement. A cross-sectional descriptive design was carried out utilizing a SERVPERF-based survey developed by Cronin and Taylor (1992) to measure students’ perceptions towards educational service quality. The participants’ responses to the reliability dimension (75.5 ± SD 12.7) were the highest scoring, while participants’ perceptions to the tangibles dimension were the lowest (61.0 ± SD 17.5). Further, students’ opinions regarding barriers to quality services were related to “limited time for study” and “inadequate equipment for clinical training”. Responses to positive factors affecting the quality of services were “accuracy of work”, “effective communication”, and “gaining new knowledge”, as perceived by students. The highest perceived service quality dimension among students was reliability followed by assurance, empathy, responsiveness, and tangibles. Moreover, the majority of students expressed that the Faculty of Nursing gave them prestige in the community, they were happy to study nursing, and they would not study in another higher educational institution even if they had an opportunity to do so.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".