A Study on the EFL Teachers’ Awareness of Classroom Observation Criteria
Bibliographic record
Abstract
The aim of the present study was to investigate the Iranian EFL teachers’ awareness of classroom observation criteria. To this end, 123 Iranian EFL teachers at several language institutes and universities participated in this study. The participants were selected through the convenience sampling method. The instrument used for data collection was a questionnaire for evaluating the criteria used for classroom observation. The reliability of the questionnaire was calculated through Cronbach Alpha. The data were collected in person and through email; they were analyzed through descriptive statistics, independent samples t-test, and the analysis of variance (ANOVA). The descriptive statistics indicated that an increase in teaching experience results in an increase in teachers’ awareness of the classroom observation criteria. The independent samples t-test indicated that there was not a significant difference between gender and the teachers’ awareness of classroom observation criteria. The results obtained from the ANOVA test indicated that there was no difference statistically in teachers’ awareness of classroom observation criteria between the fields of study, and level of education. The result of ANOVA test showed that age had a significant impact on teachers’ awareness of observation criteria. The findings of this study showed that a high percentage of Iranian EFL teachers are aware of the classroom observation criteria.
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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 | 0.003 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".