Evaluating service quality in the higher education sector in Iran: an examination of students’ perspective
Bibliographic record
Abstract
Purpose Education is a human right and access to high quality education is key to sustainable socioeconomic development. Improving the quality of higher education institutes is essential for generating the productive human resources. Assessing the quality of higher education from the students’ perspective can be considered a crucial factor in the monitoring of service quality in universities. The purpose of this paper is to evaluate the quality of educational services in a higher education institute, the Kermanshah University of Medical Sciences (KUMS), in the west of Iran. Design/methodology/approach A multistage sampling method was used to select 346 students from the KUMS, who were enrolled in the second semester of the academic year 2015-2016. The SERVQUAL questionnaire was used to gather data on students’ perceptions and their expectations about the quality of educational services. The authors used a statistical significance level of 0.05 to examine the gap between the students’ expectations and their perceptions of service quality in five dimensions, namely tangibles, responsiveness, reliability, empathy and assurance. Findings The results showed that there was a negative service quality gap in all five dimensions. The overall mean score of students’ expectations and their perceptions was 3.19±0.44 and 2.4±0.45, respectively. The score gap between the overall mean score of perceptions and expectations of students was −0.79, which was statistically significant ( p <0.0001). The highest and lowest quality gaps were related to the assurance (−0.84) and tangible (−0.70) dimensions, respectively. Originality/value The study indicated that the quality of educational services provided in the KUMS did not meet students’ expectations in five dimensions of service quality. Thus, it warrants further investigations to determine how to improve the quality of educational services in higher education institutes such as the KUMS.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".