Improving English Teaching Skills: An Online Course for Non-English Major Teachers in Southern Thailand’s Rural Primary Schools
Bibliographic record
Abstract
The mixed-methods study addressed the needs and challenges faced by first-grade English teachers in rural primary schools in Southern Thailand (for example, lack of pedagogical training). The study’s primary objectives were to investigate these teachers’ needs and difficulties, develop a 15-hour online pedadgocial training course, and evaluate its effectiveness after the training was completed. The research involved 33 teachers and 153 students and employed various tools, including questionnaires, an online pedagogical training and language course, pre-and post-tests, and semi-structured interviews about the experience. The findings highlighted the importance of training in speaking, vocabulary, materials, games, and communicative language teaching (CLT) for these teachers. Statistically significant improvements (p < 0.001) were observed in post-test scores for both teachers and students, indicating the positive impact of the customized online training course on teachers’ English skills and teaching performance and improvement in student learning outcomes.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".