Developing a Program to Strengthen Academic Leadership of Primary School Administrators in Northeast of Thailand
Bibliographic record
Abstract
This research aimed: 1) to investigate components and indicators of academic leadership of primary school administrators; 2) to explore existing situation and desirable situation, and assessment the needs to enhance academic leadership of primary school administrators; and 3) to develop a program to strengthen academic leadership of primary school administrators. Mixed methods research was employed which divided into three phases. The 1st phase was investigation of components and indicators of academic leadership of primary school administrators and verify by 7 experts. The 2nd ed. phase was exploration of existing situation and desirable situation of academic leadership of primary school administrators. The samples were 750 primary school administrators and teachers in Northeast of Thailand, obtained through stratified random sampling technique. The 3rd ed. phase was developing a program to strengthen academic leadership of primary school administrators and evaluate the program by 9 experts. The research instruments were the components and indicators evaluation form, an existing and desirable situation questionnaire, the structured interview form, and a program evaluation form. Statistics used were mean, standard deviation, and the modified priority needs index. The research results were: 1) The academic leadership of the primary school administrators comprised of 5 components and 26 indicators; 2) The existing situation of academic leadership of primary school administrators was at a high level, desirable situation was at the highest level, and the needs to strengthen academic leadership of primary school administrators were ranked from high to low was visionary, supervision of learning management, teacher professional development, curriculum and learning management, and learning atmosphere and culture development, respectively; and 3) The developed program to strengthen academic leadership of primary school administrators comprised 5 main parts; 1) program rationale, 2) program objectives, 3) content consists of 5 modules and 25 sub-modules, 4) development methods and activities were self-study, training, and knowledge exchanging and practicing, and 5) program evaluation.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".