Development of Educational Institution Management Model for Educational Quality Enhancement in Primary Educational Service Area Offices in Northeastern Thailand
Bibliographic record
Abstract
This research aimed to (1) investigate current conditions, desirable conditions, and needs assessment of educational institution management for quality enhancement, and (2) develop management approaches and a comprehensive model for educational institutions in Primary Educational Service Area Offices in Northeastern Thailand. The study employed a three-phase mixed-methods design. In Phase 1, institutional management conditions were examined through questionnaires administered to 760 school administrators and department heads selected via multi-stage sampling. Phase 2 developed management approaches based on structured interviews with 10 experts from high-performing institutions. Phase 3 created and validated a management model with input from seven educational experts through connoisseurship evaluation. The findings revealed moderate current implementation levels across all management dimensions, with leadership ranking highest. Desirable conditions were rated at high levels, with leadership achieving the highest rating. The needs assessment identified eight priority areas requiring development: performance focus, outcomes, process management, leadership, knowledge management, strategic planning, student/stakeholder focus, and workforce focus. The resulting educational institution management model comprises five components: principles/concepts, objectives, operational processes, measurement/evaluation, and implementation conditions. The operational framework integrates seven essential dimensions: leadership, strategic planning, process management, knowledge management, workforce focus, student/stakeholder focus, and performance focus. Expert evaluation confirmed the model’s highest-level appropriateness and utility with high feasibility for enhancing educational quality.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| 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".