Effects of Attitude towards Language Learning and Risk-taking on EFL Student's Proficiency
Bibliographic record
Abstract
This study was an endeavor to investigate effects of attitude towards language learning and risk-taking on EFL students' proficiency. To achieve the objectives of the study, three data gathering instruments were used: Attitude towards Language Learning Scale, Venturesomeness Subscale of Eysenck IVE Questionnaire, and Oxford Quick Placement Test (2005). The participants were 120 female and male college students majoring in English Translation at Marvdasht University. The results showed that the relationship between proficiency level –high, middle, and low –and attitude towards language learning was not significant and the middle proficient participants were higher risk-takers. The results demonstrated differences in risk-taking between high and intermediate levels. Moreover, there was no significant difference between high and low groups and low and middle groups. Correlational analysis revealed a significant positive relationship between attitude towards language learning and risk-taking (r=.20, p< 0.05). Besides, language proficiency and attitude towards language learning did not have a significant correlation (r= .06, p> 0.05).
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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 | 0.001 | 0.008 |
| 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 | 0.001 | 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 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".