A Model for Developing Academic Leadership of Teachers in the 21st Century Under the Office of Primary Educational Service Area in Thailand
Bibliographic record
Abstract
This research aimed to present a model for developing the academic leadership of teachers in the 21st century under the Office of Primary Educational Service Area. This study used an integrated research method divided into two phases. Phase One aimed to study the current state of academic leadership of teachers in the 21st century under the Office of the Primary Educational Service Area. The sample group of this phase included 335 educational institution administrators, teachers, and heads of the academic department at schools under the jurisdiction of the Primary Educational Service Area Office Government Inspection Area 14, derived from stratified random sampling and three exemplary educational institutions. Phase Two aimed at creating a model for developing teachers’ academic leadership in the 21st century under the Office of the Primary Educational Service Area. The sample group of this phase consisted of 12 experts for a focus group meeting, obtained from purposive sampling. The research tools used were questionnaires, interviews, and evaluation forms. Data were analyzed to investigate average, standard deviation, and content analysis. The research results showed that the current overall condition in every aspect was practiced at a high level. In addition, there were five academic leadership development models for teachers in the 21st century under the Primary Educational Service Area Office: principles of the model; objectives of the model; methods of operation of the model; evaluation of the model, and conditions for success of the model. The models were appropriate and the overall feasibility was high.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".