Factors Related to Retention Behaviour of Teachers in Islamic Private Schools in Three Southernmost Provinces in Thailand
Bibliographic record
Abstract
This research aimed to study the factors that affect the persistence of ordinary teachers in private schools in three southernmost provinces of Thailand. The samples were 246 ordinary teachers in Islamic private schools divided into 2 categories: the first group was 131 teachers who remained an instructor in the school and the second group was 115 ex-teachers who had resigned from school. This was a mixed method research, using questionnaire and semi-structured interview. Discriminant analysis was employed for data analysis. It was found that only one discriminant variate differentiated between teachers who remain and those who had resigned; this vairate was the time period they had worked in schools. Results from interviews showed that for teachers to continue to work in Islamic private schools, there is a need to change the welfare system of the school teachers and develop a clear and transparent system for their salary promotion. Also, teachers should have more opportunity to show their full potential. Teachers also recommended that to promote teachers’ morale and motivate them to remain teaching in schools, Ministry of Education should reform rules or regulations of teacher recruiting as government employees. These newly-created rules and regulations should be clear and transparent. Consequently, both religious and ordinary course teachers have opportunity to be recruited equally. They believed that this change could affect the quality of teaching in the schools in positive way. In conclusion, the Thai government should support education in Islamic private schools seriously.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".