Sustainability Mindset Development Model for Secondary School Administrators in Thailand
Bibliographic record
Abstract
The objectives of this research were to create and evaluate a sustainability mindset development model for secondary school administrators in Thailand. The research methodology was mixed-methods research using a multi-phase design, divided into three phases. Phase I involved document analysis, expert interviews, and content analysis. Phase II checked the congruence of sustainability mindset indicators with empirical data. The sample included 400 secondary school administrators and teachers. A questionnaire with a reliability score of 0.915 was utilized. Exploratory factor analysis was performed on a sample of 400 participants, while confirmatory factor analysis was conducted on a sample of 800 participants. Phase III involved creating and evaluating the sustainability mindset development model. A draft model was validated using the connoisseurship technique by 9 experts and evaluated by 11 experts. The findings revealed that 1) the sustainability mindset of secondary school administrators in Thailand consist of 16 indicators, categorized into four factors: ecological worldview (4 indicators), systems perspective (6 indicators), spiritual intelligence (3 indicators), and emotional intelligence (3 indicators); 2) the confirmatory factor analysis indicated that the developed model and its indicators were consistent with empirical data, with χ² = 83.52, df = 65, P-value = 0.0606, CFI = 0.999, TLI = 0.997, RMSEA = 0.027, and SRMR = 0.007, when considering the component weight values, it was found that the component with the highest standardized score was ecological worldview, emotional intelligence, and systems perspective, respectively; and 3) a sustainability mindset development model consists of the model’s name, objectives, principles, concepts, key components, success goals, development methods, and driving mechanisms, and its evaluation in terms of propriety, feasibility, and utility was rated at the highest level.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".