A Program to Enhance Teachers’ Instructional Management for Developing Students’ Modern Technology Skills at the College of Agriculture and Technology under the Office of the Vocational Education Commission
Bibliographic record
Abstract
The objectives of this research are to 1. Study the components, indicators, current conditions, desired conditions, essential needs, and guidelines for enhancing teachers' learning management to develop modern technology skills of students at Agricultural and Technology Colleges under the Office of the Vocational Education Commission. 2. Develop a program to enhance teachers' learning management to develop modern technology skills of students at Agricultural and Technology Colleges under the Office of the Vocational Education Commission. 3. Study the outcomes of using the program to enhance teachers' learning management to develop modern technology skills of students at Agricultural and Technology Colleges under the Office of the Vocational Education Commission.The sample group consists of school administrators and teachers. The sample size was determined according to Krejcie and Morgan’s table, totaling 140 participants, selected by multistage random sampling. The key informants include 7 experts, selected by purposive sampling. The instrument used was a questionnaire, with reliability coefficients of 0.91 for the current condition section and 0.95 for the desired condition section. Data were analyzed using percentage, mean, standard deviation, and Priority Need Index (PNI modified). Research findings revealed that: 1.The components of teachers’ learning management to develop modern technology skills of students at Agricultural and Technology Colleges under the Office of the Vocational Education Commission consist of 3 components and 12 indicators, including: 1.Curriculum aspect 2.Learning management aspect 3.Measurement and evaluation aspect The appropriateness evaluation result was at a good level. 2.The current condition of teachers’ learning management to develop modern technology skills of students at Agricultural and Technology Colleges under the Office of the Vocational Education Commission was generally at a good level, while the desired condition was at a very good level overall. When considering the needs by aspect, the highest priority was the learning management aspect, followed by the curriculum aspect, and then the measurement and evaluation aspect. 3.The guidelines for enhancing teachers’ learning management to develop modern technology skills of students at Agricultural and Technology Colleges under the Office of the Vocational Education Commission are based on the following development principles: 1.Learning from experience (70%) 2.Learning from others (20%) 3.Learning from curriculum (10%) The approaches to teacher development include: 1.Learning by doing 2.Self-directed learning 3.Mentoring 4.Knowledge exchange 5.Training workshops Implementing development according to these guidelines helps teachers continuously improve their skills, knowledge, and professional characteristics.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".