Arabic Language Teachers’ Engagement with Published Educational Research in Kuwait’s Secondary Schools
Bibliographic record
Abstract
This study investigates Arabic language teachers’ engagement with published educational research in Kuwait’s secondary schools. The study employs 170 participants across six educational regions in the country by using a quota sampling strategy. It used a questionnaire in eliciting their engagement with published educational research. The data were analysed by using simple percentage to describe the scenarios of their engagement with the published educational research. The results show that there is a lack of encouragement and support by their institutions in relation to teachers’ engagement with published educational research. It also indicates that the findings of the study do not relate to their practical teaching.This study recommends that there should be raising of awareness of the teachers on the importance of published educational research. Researchers should be cognizant of the needs of teachers and important roles that teachers could play in the implementation of the findings of the research. It also suggests the development of teachers’ capacity-building such as teachers’ research literacy. This could assist teachers to develop their reading and writing, as well as engaging with published educational research. Again, the study advocates the development of organisational cultures which could support teachers’ engagement with research. This might help in developing teachers’ professional development in relation to their engagement with published educational research.
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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 | 0.019 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".