Effects of English Language Proficiency on the Choice of Language Learning Strategies by Saudi English-major Undergraduates
Bibliographic record
Abstract
It is reported that language learning is a creative and dynamic process and the learners are active partners in this process. This trend in language teaching motivated the researchers to investigate the learners' individual differences and the identification of language learning strategies (LLS) has become a major area of interest in this regard because it is suggested that language learners consciously or unconsciously employ different LLS. This research study investigated LLS used by Saudi English-major undergraduates by using SILL version7. Paired Samples t-test was applied to see if significant differences exist as a result of their GPA differences. The informants of this study were 240 English-major undergraduates (low GPA, 106 & high GPA, 134) enrolled at foreign languages department Taif university. Results reported that the participants with high English language proficiency use language learning strategies more frequently. The participants ranked the metacognitive strategies the highest as compared to other LLS followed by social and cognitive LLS respectively. Among the remaining three categories of LLS, compensation and affective strategies showed mixed preferences but memory strategies were assigned the least mean values by both sample groups. Considering the fact that frequency of LLS usage and English language proficiency are positively linked to each other, it is concluded that it seems necessary to teach language learning strategies explicitly so that even the weaker students should be able to enhance English language proficiency by exploiting a wide range of suitable strategies that are appropriate to different classroom activities and learners' L2 experience.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".