Measuring E-Learners' Perceptions of Service Quality
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
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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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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