Program Development for Enhancing Teachers’ Competencies in Teaching Railway Control and Maintenance in Vocational Colleges under the Office of Vocational Education Commission
Bibliographic record
Abstract
Teacher competency is crucial for the quality development of learners. Teachers with high competence in learning management will result in high-quality learners. This research aims 1) to study the components and indicators of teachers’ competency in teaching railway control and maintenance. 2) to study current conditions, desirable conditions, methods of development, and needs for the development of teachers’ competency in teaching railway control and maintenance. 3) to design and develop a teachers’ competency-enhancing program in teaching railway control and maintenance, and 4) to study the results of implementing the teacher competency-enhancing program in teaching railway control and maintenance. The methodology was research and development conducted in 4 Phases as follows according to the objectives. The results showed that 1) Components and indicators of teachers’ competency in teaching railway control and maintenance have 5 components, and 17 indicators, confirmed by experts, are appropriate at the highest level. 2) Current condition, teachers’ competency in teaching railway control and maintenance, overall was moderate level. The desirable condition, overall was at the highest level. Competency development methods consist of (a) Training, (b) Self-learning, (c) Workshops, (d) Study visits, and (e) Work practice in the workplace, and the priorities of the needs for competency development, including (a) Self-development, (b) Ethics and professional ethics of teachers, (c) Measurement and evaluation of learning outcomes, (d) Curriculum administration and learning management, and (d) Building relationships and cooperation with the community for learning management, respectively. 3) Teachers’ Competency Enhancing Program in Teaching Railway Control and Maintenance consists of (a) Principles, (b) Objectives, (c) Model and development methods, (d) Contents and developing activities consisting of 5 Modules, and (e) Measurement and Evaluation. The result of the program evaluation by qualified experts was appropriate, utility, and possibility at the highest level. 4) The results of implementing the teachers’ competency-enhancing program in teaching railway control and maintenance were used. It was found that (a) knowledge of teacher competency in teaching railway control and maintenance before development received an average score of 17.70 out of 30, representing 58.99% after development, receiving an average score of 25.90, representing 86.33%. Knowledge after development was higher than before development. (b) Teachers’ competencies and overall performance before development were at a moderate level. After development was at the highest level, and (c) the results of the program satisfaction assessment by participants overall and all aspects are at the highest level.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".