Measuring E-Learners' Perceptions of Service Quality
Bibliographic record
Abstract
This article examines the factors of e-learners' perceptions of service quality in terms of the physical appearance of the learning management system, students' assurance of personnel's level of knowledge, and the customized attention to students' needs. The authors use a survey to measure the five dimensions of the SERVQUAL scale, adapted to the e-learning context. A total of 325 responses were obtained. To validate their scale, the authors performed exploratory and confirmatory factor analyses. They found that the most important determining factors for e-learning are: ergonomics, corresponding to the attractiveness of the e-learning system; assurance, corresponding to instructors' ability to satisfy students' needs; and empathy, corresponding to the attention given to each individual student. The authors also found that in the context of e-learning, the relative importance of the dimensions of perceived quality is different from what is typically observed in more traditional services. Their findings enable educational institutions to improve their understanding of the expectations and perceptions of e-learners.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".