Utilization of Language Learning Strategies by Iranian Post Graduate Students and Their Attitude and Motivation Toward English Learning
Why this work is in the frame
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Bibliographic record
Abstract
The current study tries to explore language learning strategies (LLSs) of Iranian postgraduate learners and the effect of motivation and attitude on their strategy use. Oxford’s classification of language learning strategies is the framework of the current study. Her strategy taxonomy includes six categories as memory, cognitive, metacognitive, compensation, social and affective strategies. 156 Iranian post graduate students in Kerman province were selected according to two-step cluster sampling. Then, translated version of Oxford’s strategy inventory for language learning (SILL) was administered to the participants to determine their strategy use. Attitude/motivation test battery (AMTB) was also used to identify the participants’ type of attitude and motivation. After collecting and analyzing data, the following results were found: a) Unlike the findings of the majorities of the studies done so far on foreign language learners, Iranian post graduate students of art and science were found to be high strategy users; b) The participants reported the use of compensation, social, metacognitive, and affective strategies in a high level while memory and cognitive strategies were reported to be used at a medium level; c) No significant difference was found between overall strategy use of students with positive and negative attitude; d) No significant difference was found between overall strategy use of students with integrative and instrumental motivation; e) No significant difference was found between overall strategy use of students of art and science. Key words: Language learning strategies; Iranian post graduate students; Learning attitude; Motivation; English learning
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it