Bibliographic record
Abstract
This study examined the English extensive reading (ER) programs across the Arabian Gulf region.It investigated the ER models and approaches adopted by different higher education institutions (HEIs) in the region, their ER practices and activities, and the challenges they encountered in implementing their ER programs.Utilizing qualitative research design with seventeen (17) cases from prominent colleges and universities in Saudi Arabia, United Arab Emirates, Qatar, Bahrain, Oman, and Kuwait, the study found that most English ER programs in the region adopted the Graded Readers approach with the Supervised-Modified ER model and course-component integration scheme.The study further discovered that the ER programs varied in terms of duration, number of hours and sessions, target number of words, required number of books read, engagement and enrichment activities, and assessment system.Lastly, the study also found that HEIs in the region experienced challenges in sustaining meaningful, varied, and sufficient resources, changing the negative attitudes of the stakeholders toward extensive reading, providing more sufficient space for ER in English language curriculum, and building a strong culture of reading in the community as a whole.The study concludes with recommendations on how to improve English ER implementation in the Arabian Gulf region.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".