Challenges of Educators in the Context of Education Reform and Unrest: A Study of Southern Border Provinces in Thailand
Bibliographic record
Abstract
This qualitative study aimed to identify challenges of educators faced with education reform and violent unrest that has taken place in five Southern provinces of Thailand, as well as leadership characteristics that emerged in this context. Participants were 21 educators from primary schools in Pattani, Yala, Narathiwat, Songkhla and Satun provinces. A purposeful selection was employed for participant recruitment of the study. Data collection methods were semi-structured interviews and related official document analysis. The study revealed that challenges of educators related to education reform were managing curriculum, increasing students’ reading competency, coping with work overloads, and managing limited budgets. Challenges related to social unrest were dealing with instructional management, coping with feelings, and ensuring safety. Leadership characteristics that emerged in response to these challenges were becoming patient, dedicated, and adaptive; guiding changes in instructional methods; and building collaborations with related stakeholders.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".