Bibliographic record
Abstract
Listening is one of the fundamental language skills which plays a crucial role in facilitating language learning. However, very little research has been conducted on the relationship between EFL learners’ listening strategy use and their individual differences. Listening strategies are the techniques that we use consciously or unconsciously to understand and interpret the text we are listening and they are directly contributed to the comprehension and recall of listening input. Despite the relatively small number of investigation in the realm of listening strategies, there is a lack of research study investigating them in relation to specific traits or skills. This study aimed at investigating the relationship between creativity and the use of listening comprehension strategies by EFL learners. To this end 45 students at the advanced level were chosen out of 88. The adapted version of Listening Strategy Questionnaire was administered to the subjects to identify their listening strategies. Then, Torrance Test of Creative Thinking was administered to measure their creative abilities. The descriptive analysis indicated that these EFL learners employed meta-cognitive listening strategies more than cognitive strategies and they used cognitive strategies more than socio-affective strategies. The Pearson Correlation analysis showed that there was a statistically high, significant and positive association between Iranian EFL learners’ creative abilities and their listening strategies at <0.01 level. The correlation between creativity and meta-cognitive strategies was higher than those of other strategies, followed by the correlation between creativity and cognitive strategies and then the correlation between creativity socio-affective strategies. In the end, pedagogical implications and areas for further research were provided.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".