On the Relationship between Iranian L2 Teachers’ Pedagogical Beliefs and L2 Learners’ Attitudes
Bibliographic record
Abstract
The present study employed a descriptive survey design to investigate L2 learners’ attitudes towards language learning, and the possible effects of teachers’ beliefs on learners’ attitudes. Participants were chosen from among 2 groups: Twenty EFL teachers were asked to take part in this study and 80 from a pool of 213 learners at 2 language schools who were chosen to fill out the learners’ attitude questionnaire. The teachers were subsequently placed at/in 3 groups of high-opinion group (HOG), moderate group (MG), and low-opinion group (LG), and the attitudes of the learners of these 3 groups of teachers were compared to uncover the possible impact of teacher beliefs on learner attitudes. The relationship between the teachers’ beliefs and the learners’ attitudes was analyzed, and it that showed there was a statistically significant difference in the learners’ attitude scores for HOG, MG, and LOG. Analysis of the data showed that the learners of the HOG teachers gained significantly higher attitude scores than the learners of the MG teachers. Simply put, it was found that EFL teachers’ beliefs can influence their learners’ attitudes about language learning. Language teachers should learn about the effect of their beliefs and experience it and become more aware of practicing them.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".