Developing EAL Learners’ Intercultural Sensitivity Through a Digital Literacy Project
Bibliographic record
Abstract
Language and culture are informally integrated in many English as an Additional Language (EAL) programs, but cultural discussions are often regarded from the perspective of a particular dominant culture. Although this integration is crucial for the development of communicative competence, practical applications are still challenging as language teachers tend to know more about linguistic items than cultural aspects (Celce-Murcia, 2007). This article describes a digital literacy project implemented with language learners in an adult EAL program. Using Bennett’s (1993) DMIS model for intercultural sensitivity, the project invited international students and newcomers to Canada to explore and expand on their understanding of intercultural relationships while studying in a multicultural EAL class. The learners engaged in 5 steps to complete the project (reflective discussion, script writing, video recording scenes, editing, and final reflection), with a short movie serving as the digital product. The digital literacy project is proposed as a potential tool for integrating intercultural sensitivity into EAL programs and engaging learners in discussions about diversity in cultural values, beliefs, and behaviours as a way to affirm their cultural and intercultural identities.Alors que plusieurs programmes d’anglais langue additionnelle (ALA) intègrent informellement la langue et la culture, les discussions portant sur la culture adoptent souvent le point de vue d’une culture dominante particulière. Bien que cette intégration soit cruciale pour le développement de la compétence communicative, les applications pratiques demeurent un problème de taille puisque les enseignants de langue ont généralement plus de connaissances relatives à la langue qu’à la culture (Celce-Murcia, 2007). Cet article décrit un projet d’initiation au numérique mis en œuvre auprès d’apprenants adultes dans un programme d’ALA. S’appuyant sur le modèle DMIS de Bennett (1993) de sensibilité interculturelle, le projet visait à encourager des étudiants internationaux et des nouveaux arrivants au Canada à approfondir leurs connaissances des rapports interculturels tout en poursuivant leur apprentissage dans une classe d’ALA multiculturelle. Les étudiants ont suivi les 5 démarches du projet (discussion de réflexion, rédaction de scénarios, enregistrement vidéo de scènes, édition et réflexion finale) pour arriver à la production d’un court-métrage. Nous proposons ce projet d’initiation au numérique comme outil pouvant appuyer l’intégration de la sensibilité interculturelle dans les programmes d’ALA et inciter les étudiants à discuter de diversité en matière de valeurs, croyances et comportements culturels afin d’affirmer leurs identités culturelles et interculturelles.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".