The Scenarios of Educational Administration of Secondary Schools in Thailand During the Next Decade (A.D. 2022-2031)
Bibliographic record
Abstract
This research is the scenarios of educational administration of secondary schools in Thailand during the next decade (A.D. 2022-2031) by using EDFR research techniques, The research objectives were 1) To study the current conditions and problems of educational administration of secondary schools in Thailand 2) To study the scenarios of educational administration of secondary school in Thailand during the next decade (A.D. 2022-2031). The research results can be summarized as follows: I) The current state and problems of educational administration of the secondary school in Thailand overall practice is at a high level when considering each aspect, there are practices at a high level in all 8 aspects: 1) Planning and quality assurance 2) Academic affairs 3) Student affairs 4) Human resources 5) Administrative work 6) Finance and supplies 7) Building and environment services and 8) Community work and affiliate networks. As for the educational administration problems in Thai secondary schools, the overall practice is at a low level, when considering each aspect, there is a low level of practice in all 8 aspects: 1) Planning and quality assurance 2) Academic affairs 3) student affairs, 4) Human resources, 5) Administrative work, 6) Finance and supplies, 7) Building and environment services, and 8) Community and affiliate networks. II) The scenarios of educational administration of the secondary school in Thailand during the next decade (A.D. 2022-2031) have 49 possible trends as follows: 1) Planning and Quality assurance 7 trends 2) Academic affairs 11 trends 3) Student affairs 8 trends 4) Human resources, 9 trends, 5) Administrative, 4 trends, 6) Finance and supplies, 5 trends, 7) Building and environment services, 3 trends, and 8) Community and affiliate network 2 trends.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".