Impact of Related Activities on Reading Comprehension of EFL Students
Bibliographic record
Abstract
This experimental study reported in this article is casual research since it aims to improve reading comprehension of EFL students by means of applying pre-related reading activities. The study is quantitative. It used two instruments: (1) Reading Engagement Scale developed by Whitaker (2003) to determine the efficacy of pre-related reading activities and (2) pretest/posttest to measure comprehension level after implementing related reading activities. The subjects, Saudi EFL learners, were students in an English college in Buraidah city. The research used two groups: experimental and control groups. The subjects in the control group (27 students) were receiving a regular reading instruction, whereas those in the experimental group (24 students) did some pre-related reading activities at home and before the class. Multiple statistical tests were used to find out reliability, regression, and pearson correlation. The result of the study showed that the difference between the two groups was statistically significant. The students in the experimental groups far outperformed those in the control group. The study suggests that EFL learners' comprehension level increases with reading engagement that is related to the class reading. Recommendation of this finding for EFL reading environment is discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".