The Relationship between Perceptual Learning Styles and Reading Comprehension Performance of Iranian EFL Learners
Bibliographic record
Abstract
Reading comprehension is one of the most important aspects in the process of language learning. Individual differences in foreign language learning have also been a common theme among L2 researchers and various factors such as gender, aptitude, motivation, and learning styles have been the subject of numerous studies indicating their effect on language learning. Along the same lines, this study focused on the relationship between perceptual learning styles and L2 reading comprehension and how well each perceptual learning style contributes to L2 reading comprehension. The study was carried out on 60 Iranian foreign language learners. The results of statistical analyses indicated that only tactile and kinesthetic learning styles had a significant relationship with L2 reading comprehension performance. Moreover, the findings of the study revealed that the tactile learning style was the best predictor of L2 reading comprehension performance. Based on the findings of the study, it can be concluded that teachers should try to accommodate different learning styles in teaching reading comprehension. If the educational settings become compatible with the learners’ personal orientations, learners may be able to engage in educational activities more and will thus gain an advantage in learning.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".