Be(com)ing multilingual listeners: preparing (monolingual) teacher candidates to work with multilingual learners in mainstream classrooms
Bibliographic record
Abstract
Classrooms across the United States today often include students from multiple different cultural and linguistic backgrounds. The teaching force, by contrast, has remained predominantly White and Anglophone with little experience learning additional languages (Athanases & Wong, Citation2018; Deroo & Ponzio, Citation2023; Pettit, Citation2011). When teachers themselves have limited experience with linguistic diversity, how can teacher educators raise teacher candidates’ (TCs) critical multilingual language awareness (CMLA) over the limited duration of the teacher certification process? This article analyzes the implementation of a CMLA project which engaged secondary TCs in becoming language learners themselves to reflect on the experience of being an early language learner. We collected written reflections from 49 TCs about their language learning experiences over 30 h and drew on the five domains of CMLA (Power, Cognitive, Affective, Social and Performance) (Prasad, Citation2022) to code the data set. We focus on the domain of Power to examine how learning a new language even for a short time can engage TCs practically in attending not only to mechanics of teaching and learning with multilingual students but also more critically to recognize the systemic power relations among languages and language users in schools.RÉSUMÉ Aujourd’hui, les salles de classe à travers les États-Unis comprennent souvent des élèves issus de multiples origines culturelles et linguistiques différentes. Le corps enseignant, en revanche, reste majoritairement blanc et anglophone, avec peu d‘expérience dans l‘apprentissage de langues supplémentaires (Athanases & Wong, Citation2018; Deroo & Ponzio, Citation2023; Pettit, Citation2011). Lorsque les enseignants ont eux-mêmes une expérience limitée de la diversité linguistique, comment les formateurs d‘enseignants peuvent-ils élever l’éveil aux langues critiques (CMLA en anglais) des stagiaires pendant la durée limitée du processus de certification des enseignants? Cet article analyse la mise en œuvre d‘un projet de CMLA dans le cadre duquel des stagiaires du secondaire ont été amenés à devenir eux-mêmes des apprenants de langues afin de réfléchir à leur expérience d‘apprenant précoce de langues. Nous avons recueilli les réflexions écrites de 49 stagiaires sur leurs expériences d‘apprentissage des langues pendant 30 heures et nous nous sommes appuyés sur les cinq domaines du CMLA (pouvoir, cognitif, affectif, social et performance) (Prasad, Citation2022) pour coder l‘ensemble des données. Nous nous concentrons sur le domaine du pouvoir pour examiner comment l‘apprentissage d‘une nouvelle langue, même pendant une courte période, peut inciter les stagiaires à s‘intéresser de manière pratique non seulement aux mécanismes de l‘enseignement et de l‘apprentissage avec des étudiants multilingues, mais aussi, de manière plus critique, à reconnaître les relations de pouvoir systémiques entre les langues et les apprenants de langues dans les écoles.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".