Assessment of the Quality of Electronic Administrative Services in a Greek Higher Education Institution: Α Case Study
Bibliographic record
Abstract
The basic aim of this paper is to investigate the perceptions, attitudes and experiences of the students of the Department of Primary Education of the University of the Aegean regarding the quality of the provided services to them by the Secretariat of Administrative Electronic Services. The survey was conducted during the second semester of the academic year 2016-2017 with the use of an anonymous written questionnaire which was completed by 128 undergraduate students of the Department of Primary Education of the University of the Aegean. The results of the survey show that students primarily consider as the most important service for them the department’s website and the service Studentsweb. The least important service for them is the communication platform uniway for mobiles. Also, the degree of satisfaction with electronic administrative services is related to the criteria: availability, ease of use, good organization, responsiveness of services to the needs and expectations of students, and the degree of information. Moreover, problems such as "Mistakes about courses’ grades" and "Unsuccessful academic books’ registration" appears to have a negative impact on the degree of satisfaction of students with the corresponding services in which the problems occur. The findings of this research can be useful to the administrative staff and faculty of the University of the Aegean as they reveal the dimensions of electronic administrative services that are important and effective and satisfy or create problems for students.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".