Learners in a Tight Corner: An Investigation of Figurative Idiomatic Competence and Learner-related Factors
Bibliographic record
Abstract
Idioms play an indispensable role in communication. Knowledge of idioms is considered an indicator of proficiency. This study is aimed at investigating English as a Foreign Language (EFL) students’ knowledge of frequently used idioms and the effect of learner-related factors. The participants were 218 female EFL college students at the College of Basic Education (CBE) in Kuwait. A test was designed and used as the data collection instrument to assess the students’ knowledge of frequent idioms. The test scores reveal a substantially low overall knowledge in this area. The results show that Kuwaiti EFL learners have difficulty comprehending common idiomatic expressions. Additionally, the study is aimed at determining whether students’ knowledge of idioms is linked to age, year of study, and/or Grade Point Average (GPA). A statistically significant difference in knowledge of frequently used idioms is evident when GPA is taken into account.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".