Development of a Strategic Communication Model for School Principals in Basic Education Administration
Bibliographic record
Abstract
This study was aimed to evaluate a strategic communication model for school principals under the Office of Basic Education Commission in Thailand. A purposive sampling technique was employed to select 10 participants consisting of five experts and five practitioners. The 10 participants evaluated the strategic communication model in terms of its propriety, feasibility, and utility, hence providing guidelines for educational administrators while they are applying this Strategic Communication Model. Firstly, educational administrators determine communication objectives by asking and listening to involved individuals without infringing the Personal Data Protection Act. Secondly, educational administrators and teachers scan the environment in terms of its strengths, weaknesses, opportunities, and threats. Thirdly, educational administrators and teachers create a method of communication by considering their target group and the suitability of time. Fourthly, educational administrators and teachers design messages which are clear, easy to understand, attractive, and interesting. Fifthly, educational administrators and teachers select both online and onsite communication channels that are consistent with the messages to match the target group. Finally, educational administrators evaluate communication before, during, and after communication. The end research outcome is a strategic communication model for educational administrators comprising six components and 20 indicators. The six components of the Strategic Communication Model are clarity of message, channel effectiveness, engagement, credibility and trust, measurement and evaluation, and strategic alignment.
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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 | 0.024 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".