Interlanguage Pragmatics: Iranian EFL Teachers’ Cognition
Bibliographic record
Abstract
In curricula where teachers have agency to make decisions on everyday classroom activities, their cognition exerts strong influences on their pedagogical practices. The present paper reports on a qualitative multiple-case study exploring Iranian English as a Foreign Language (EFL) teachers’ cognition of interlanguage pragmatics. Through triangulation of multiple methods and data sources, the study details descriptions of five Iranian EFL teachers’ classroom practices, the cognitions behind these practices, and the way their cognition and the teaching context interact in shaping their everyday teaching practices. The findings suggest that underrepresentation of pragmatic competence in the EFL classes can be attributed to contextual factors such as deficiency in the EFL teachers’ content and pedagogic content knowledge of interlanguage pragmatics and curricular decisions. The main findings are then discussed against the backdrop of the literature on interlanguage pragmatics. Keywords: Interlanguage pragmatics, language teacher cognition, belief, EFL teacher, EFL teacher knowledge base Dans les programmes où les enseignants ont le pouvoir décisionnel quant aux activités quotidiennes en salle de classe, les connaissances des enseignants exercent une grande influence sur leurs pratiques pédagogiques. Cet article fait état d’une étude qualitative multi-cas portant sur les connaissances en pragmatique interlangue qu’ont des enseignants iraniens d’anglais langue étrangère (ALE). Par une triangulation de nombreuses méthodes et sources de données, l’article décrit en détail les pratiques en salle de classe de cinq enseignants iraniens d’ALE, les connaissances qui sous-tendent ces pratiques et la façon dont leurs connaissances et le contexte d’enseignement interagissent pour façonner les pratiques pédagogiques quotidiennes. Les résultats indiquent que la sous-représentation d’une compétence pragmatique dans les cours d’ALE serait attribuable à des facteurs contextuels tels des lacunes dans les connaissances, chez les enseignants d’ALE, relatives au contenu et à la pédagogie en matière de pragmatique interlangue et aux décisions concernant le programme. Nous discutons des résultats principaux dans le contexte de la documentation sur la pragmatique interlangue. Mots clés : pragmatique interlangue; connaissances des enseignants de langue; croyance; enseignant d’ALE; connaissances fondamentales des enseignants d’ALE
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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 | 0.004 | 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 | 0.003 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".