Less Is More: An Implementation of an Extensive Reading Program in an English Proficiency Course in the Sultanate of Oman
Bibliographic record
Abstract
This paper reports the implementation of an Extensive Reading (ER) program in an English proficiency course at a higher education institution in the Sultanate of Oman. The implemented ER program for this study is titled, “Less is More” utilizing a readily available website, Voice of America (VOA) Learning English. Data was gathered from undergraduate students of Omani nationality enrolled in an English proficiency course for Spring 2020/2021 semester during the Covid-19. The findings of the study were gathered from multiple sources namely reading speed, comparison of pretest and posttest scores, semi-structured interviews, online focus group discussion, and the course instructor’s reflection of the implementation of the ER program. The backgrounds of the students were considered too. The findings revealed that the average students’ reading speed was consistent at 100wpm (word-per-minute) throughout the ER program. There was a positive outcome on the students’ posttest scores and a significant correlation between the number of articles the students read to their posttest scores. The data from the qualitative inquiry provided an insight into the use of modified texts to encourage more reading. Although the research did not investigate the best practices for an ER in the context of an English proficiency classroom in Oman, it showed how an ER can be implemented online given the circumstances of the Covid-19 pandemic.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".