The effect of system reliability, information sharing and service quality on e-learning net benefit in public sector organizations
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
The purpose of this study was to investigate how public sector workers in Indonesia use e-learning systems and how they can benefit from them. The researchers analyzed five variables that contribute to the effectiveness of e-learning: system reliability, information sharing, service quality, user satisfaction, and net benefit. Structural Equation Model analysis was used to analyze the data collected from 203 respondents who were public sector employees in Indonesia. The findings of this study revealed that information sharing, and service quality significantly impact user satisfaction, which in turn has a significant effect on net benefits. Additionally, system reliability was found to significantly impact user satisfaction. This theoretical implication suggests that there is a direct relationship between the level of information sharing and service quality provided by a public sector organization and the level of user satisfaction experienced by its usage of e-learning. The practical implication of the finding is that public sector organizations must prioritize the reliability of their e-learning systems. This includes investing in regular maintenance and updates, ensuring proper testing and quality control procedures, and addressing any issues or downtime quickly and effectively.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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