The Practice of Supporting International Students Learning English in Canada: Grounding Decisions in Evidence and Lived Experience
Bibliographic record
Abstract
This paper is a response to the language, learning, and life needs of the increasing number of international students studying in Canada. In addition to introducing two “real-life” international students who chose to live in Canada to learn English and otherwise study, the paper presents what the literature tells us about: international students in general; culture shock and acculturation; the struggle of international students for identity, based on the International Student Identity model; and mental health issues among this learner group. It then juxtaposes key themes found in the literature with the life experiences of the aforementioned students. Implications for students, extracurricular and preparatory program planners, and classroom instructors are shared. Given the role of many continuing education centres in providing ESL instruction and supports, the paper holds particular value for educators and administrators in the continuing education sector.
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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 | 0.026 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.016 | 0.017 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| 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".