Determining Factors of Students’ Satisfaction with Malaysian Skills Training Institutes
Bibliographic record
Abstract
The purpose of this study is to examine students’ perception of quality of service offered in Malaysian skills training institutes and how it influences overall satisfaction. This study employed a questionnaire survey involving seven skills training institutes in Klang Valley, Malaysia. From 600 questionnaires distributed, 419 were returned (69.8 percent response rate). Causation relationship was analysed using Partial Least Squares Structural Equation Modelling technique. Results show that campus environment was the most significant predictor of student satisfaction, followed by management of institute and support services. Interestingly, the study found that physical facilities and training delivery were not significant predictors of students’ overall satisfaction. Enriching knowledge in service quality and customer satisfaction is important for skills training institutes to identify priorities for performance improvement. The implication of this finding is deemed valuable and useful for institution management, policymakers and researchers in the training and educational sector.
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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 | 0.000 | 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 | 0.001 |
| 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 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".