Empowering local bilingual teachers through extending the pedagogy of multiliteracies in Taiwan’s primary education
Bibliographic record
Abstract
In 2018, Taiwan announced a bilingual education policy. Since then, bilingual teacher development has been a national priority, which has created anxiety and concerns among local Taiwanese teachers, who are expected to teach in the English medium. By extending the core values, design principles and inspired practices from New London Group’s (1996) pedagogy of multiliteracies (PoM), we present how a local Taiwanese teacher in a Grade 1 content and language integrated learning mathematics class successfully leveraged translingual and trans-semiotic resources in an English-as-a-foreign-language context, which in turn facilitated learners’ multilingual production. The findings show that trans-semiotizing helps bilingual teachers effectively deliver and support content learning, whereas translanguaging enables bilingual teachers to create a positive environment which encourages learners’ multilingual production. This study provides an opportunity for Taiwan’s educators to productively navigate problems arising from the bilingual education policy and nativespeakerism in Taiwan through creatively adapting the PoM. This study concludes with directions for bilingual teacher education.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".