Iranian EFL Teachers’ Attitudes towards Critical Pedagogy
Bibliographic record
Abstract
Critical pedagogy (CP) is a new educational approach that aims to remove social and political injustice and tries to help learners question and challenge oppression. This approach that derives its interest from critical theory has entered the field of research in recent years. In line with this trend, the present study aimed at investigating Iranian EFL teachers’ attitudes towards the application of critical pedagogy, taking into account teachers’ teaching experience and academic background. To this end, a Likert scale questionnaire developed by Tabatabaei (2013) was administered to 99 Iranian EFL teachers teaching at different institutes in Shiraz. The reliability and validity of the questionnaire were recalculated. As far as the validity of the scale was concerned, it was established through factor analysis and the reliability of the questionnaire was checked through Cronbach’s alpha. Statistical procedures, namely, descriptive statistics, independent samples t-test, and two-way ANOVA were applied. The findings of the study revealed that the EFL teachers mostly agree with the application of critical pedagogy. No significant difference was found between novice and experienced teachers' attitudes towards the principles of critical pedagogy. Furthermore, the results indicated that there was no significant relationship between teacher's academic experience and their views regarding critical pedagogy. However, as their teaching experience increased, they developed positive attitudes towards CP.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".