Extensive Reading: A Multifaceted Panacea for EFL Students at KKU
Bibliographic record
Abstract
This research aims to assess the importance of Extensive Reading (ER) in developing reading comprehension, vocabulary development, and speaking fluency among English as a Foreign Language (EFL) students at King Khalid University (KKU). Most EFL students appear to be under pressure and confront anxiety while acquiring English language competency in basic language skills. According to MacIntyre and Gardner (1994, p. 284), language anxiety is the "feeling of tension and apprehension" with language learning, including listening, speaking, and language comprehension. One thought of making language learning an enjoyable activity is to make language acquisition a natural process instead of a forced and external one. According to Day & Bamford (2002), the goal of ER is to help students become fluent, independent, and confident readers. ER encourages L2 learners to explore the English language independently, especially in an EFL environment. ER inherently encourages language acquisition by allowing students to read extensively in a relaxed and natural environment, thus developing the basic nuances of the language effortlessly. This approach is also referred as uninterrupted sustained silent reading (USSR). Two distinct groups of students, namely experimental and control groups, will participate in this study. The results will help measure the effect of ER on students’ reading comprehension and speaking fluency. The experimental group will practice effortless ER for almost 12 weeks. Students' performance in the assigned reading task, vocabulary development, and speaking proficiency will be analyzed using SPSS. Finally, the researchers will suggest efficient measures to implement ER as a teaching methodology at the English department, and will also encourage implementation of an ER club at the faculty of languages and translation, KKU.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".