Repairing socioecological relationships: Landguaging the imperial L2 classroom
Notice bibliographique
Résumé
This two-manuscript dissertation explores how two imperial and non-Indigenous languages in Canada (English and French) can resist replicating monolingual and colonial traditions though plurilingual pedagogies and online tools. In Chapter 1, an overview of the ecolinguistic framework that all chapters are rooted in is presented. It explores how multimodal and plurilingual activities build learners’ relationships to their nested macro- to micro-sized socioecosystems. This framework is then extended to a discussion of ecological technologies and pedagogies. Chapter 2 (Manuscript A) focuses on the struggles that language learners experience when engaging with speakers of different language varieties. This difficulty is often explained by a lack of exposure to sociophonetic variability in classroom materials with the emphasis instead on teaching the (usually invariable) standard variety. Focusing on the French second language (FSL) context, our understanding of sociophonetic variation in the classroom comes primarily from textbook studies; little empirical evidence has quantified the amount and kind of social speech markers (e.g., age, race, region, native speaker status) found in FSL audiovisual curriculum. Using a comparative case study, this chapter examines the audiovisual materials of two FSL classroom contexts: the university and the government sponsored francisation course. Interviews and questionnaires elicited FSL instructors’ criteria for selecting materials, and their experiences with and attitude towards including social speech marker variation in their curriculum. Additionally, audiovisual materials from each instructor collected over a semester were categorized and analysed by five social speech markers and clip length. Results showed that instructors held positive viewpoints towards including variation; however, audiovisual materials from both settings were invariant across the markers of age, race, region, native speaker status and sourced mostly from mass media. Specifically, the materials excluded elderly, adolescent, children, racialized, non-native speakers and varieties from regions other than Québec. Suggestions for incorporating more varied materials in the curriculum are highlighted and form the basis of the second manuscript. To address the lack of variation found in the imperial L2 curriculum in Chapter 2, Chapter 3 (Manuscript B) introduces Parlure Games, a computer-assisted language-learning tool that promotes exposure to and interaction with those speakers absent from audiovisual materials (e.g., elderly, racialized) using non-mass media and online mapping. Parlure Games has three teaching goals: exposure to sociophonetic variation, development of plurilingual competencies, and opportunities to visualize and critically discuss imperialism’s territorial expansionism. Following a four-level chronological framework, Manuscript B reports on the first three stages: (1) the development of Parlure Games in alignment with high variability phonetic training (HVPT) methods; (2) an exploration of its pedagogical affordances based on ecolinguistic principles; and (3) its suitability for achieving the three teaching goals, as evaluated through the Technology Assessment Model-2 (TAM2). While the first two levels are conceptual and design-oriented in scope, the third is empirical: Drawing on TAM-2-informed data, seventeen undergraduate TESL teacher candidates rated Parlure Games highly, suggesting strong adoption intentions. Based on these findings and user feedback, we provide a revised model for the tool’s in-classroom implementation, preparing it for deployment for the final stage of the adopted chronological framework. In the final chapter, the main findings of each manuscript are reviewed, and the value of plurilingual ecolinguistic tools for enhancing the teaching and learning of imperial languages ecologically is reaffirmed. The studies’ limitations are outlined, followed by a set of plurilingual ecopedagogical, Landguaging activities that address the entanglement of language and land in imperial language teaching contexts, repairing imperialism’s sociecological relationship with land.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,016 | 0,014 |
| Communication savante | 0,010 | 0,005 |
| Science ouverte | 0,002 | 0,014 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».