The Integration of Local Wisdom with Learning Innovations in the ‘Buddhism’ Course for Lower Secondary School Students in Thailand’s Educational Opportunity Expansion Schools
Bibliographic record
Abstract
This research aims to investigate the local wisdom within communities served by educational opportunity expansion schools in Thailand. Specifically, it seeks to identify local wisdom that can be integrated into the ‘Buddhism’ course for lower secondary school students. The study also synthesizes the integration of this local wisdom with learning management and develops an innovative learning model named ‘SAAOL’. Additionally, student satisfaction with this learning approach is evaluated. The study involved religious leaders, local philosophers, community leaders, educational administrators, teachers, and 200 students selected through purposive sampling. Research tools included in-depth interviews, a learning management manual, and a satisfaction assessment form. The results reveal four local wisdoms, namely ‘Sim’, ‘Khalum’, ‘Pha-Wed Cloth’, and ‘Khun Mak Beng,’ which can be integrated into the ‘Buddhism’ course through the ‘SAAOL learning model.’ Student satisfaction with this approach was notably 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".