Teaching English Pronunciation to Adult Refugees: A Personal Narrative of a Graduate Student in Newfoundland
Bibliographic record
Abstract
This narrative is based on the Experiential Learning portion of the course ED-6676 "Teaching ESL: Theory and Practice" at Memorial University of Newfoundland (MUN).The practicum consists of imparting 6 hours of ESL lessons to a student appointed by the Association for New Canadians (ANC) in St. John's.Designated students are usually refugees or economic immigrants to Canada and the lessons being provided are pro bono.The topics were chosen according to the level of English proficiency of the student, which in my case was Canadian Language Benchmark (CLB) level 4, and included conversational themes ranging from social conventions, family and friends, nationalities and differences between the home country and the host country.A mix-method approach to ESL teaching was used, including Audio-lingual, Communicative language teaching, Computer-assisted language learning, Direct Method, Grammar-translation method, Language immersion and Task-based language learning.After reflecting on this experience, my conclusions stress the importance of self motivation and student enthusiasm about their learning process, besides the allocation of an enormous amount of study time and dedication, in order to succeed, both economically and personally, in North American Anglophone society.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.032 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.009 |
| 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".