Letting the Cat out of the Bag: EFL College Students’ Attitudes towards Learning English Idioms
Bibliographic record
Abstract
Learning idioms is an uphill battle for many language learners. Thus, this quantitative study aims to shed light on English as Foreign Language (EFL) college students’ attitudes towards idiom learning. Specifically, the study is interested in revealing their attitudes towards (1) the importance of idiom learning, (2) the difficulties of idiom learning and (3) the learning strategies of idioms. Additionally, the study attempts to determine if there is an influence of age and/or year of study on the students’ attitudes towards learning English idioms. Participants were 218 female EFL college students at the College of Basic Education (CBE) in Kuwait. A five-point Likert-scale questionnaire was employed to obtain data for the study. Data analysis of the questionnaire uncovered the learners’ preferred strategies and sources of difficulties when learning idioms. Results showed that students had positive attitudes towards English idiom learning. Significant differences in the results were found when age was taken into account.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".