Multiliteracies Pedagogy in Second Language Learning: Examining How Canadian Elementary ESL Classrooms Can Empower Diverse English Language Learners
Bibliographic record
Abstract
Canada's socio-cultural landscape is changing every day due to the transitional migration of demographics from all over the world. The immigrant and refugee populations who enter Canadian society are mostly allophones who do not speak English or French- Canada's two official languages as their mother tongue. The allophone students who belong to this migrator group must learn the official languages to get equal access to the country's social and economic sectors. Thus, Canadian schools are entitled to provide adequate support in teaching English and French to these immigrant students to ensure their merging in broader society. But these immigrant students have diverse linguistic and cultural backgrounds. Therefore, they are essentially various in their second language learning needs. For this reason, it is challenging for educators to support these learners considering their linguistic and cultural diversity. The given research paper conducts a systematic literature review with authentic, peer-reviewed resources to examine how multiliteracies pedagogy can inform second language teaching and learning in elementary classrooms of Ontario, Canada. This study deals with the English language learning of multilingual and multicultural allophone English Language Learners (ELLs) in the English as a Second Language (ESL) programs of Ontario elementary schools. This research paper reflects upon different aspects of multiliteracies approaches. It concludes that multiliteracies pedagogy has numerous potentials to address ELL’s diversity and the educators of Ontario elementary ESL programs can offer a better English language learning environment to the ELLs by ensuring proper implementation of multiliteracies pedagogy in their teaching-learning process.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".