Pronunciation teaching in minority languages: perspectives of elementary school teachers in a Chinese-English bilingual program in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite an increasing interest in pronunciation instruction in English as a majority language or international lingua franca, less is known about pronunciation learning in non-English minority languages, especially among child learners. Bilingual education programs provide a unique context to address this research gap, as they involve immersive education in minority languages. Teachers in these programs thus are insightful informants. The current study focuses on the context of a Mandarin-English bilingual program in Canada and addresses two research questions: What factors do teachers believe influence students’ Mandarin pronunciation learning? What are teachers’ strategies and needs when teaching Mandarin pronunciation? Semi-structured interviews were conducted with twelve Chinese teachers with diverse language backgrounds. The teachers discussed multifaceted factors that influenced bilingual students’ pronunciation learning, including speech targets, individual factors, and language environments at school and in society. Teachers shared a wide array of pronunciation teaching techniques, although they expressed concerns related to policies and resources. This study demonstrates the complexity of teaching the pronunciation of a minority language, whose speech system is distinctly different from English, in a bilingual classroom setting. It shares teaching strategies among bilingual teachers and identifies future directions for policymaking and research.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it