An Unknown World: The Academic Experiences of Korean Immigrant Students at Two Universities in Toronto, Canada
Bibliographic record
Abstract
Although the participation of immigrant students from diverse cultural backgrounds continues to increase in Canadian universities, there is still a lack of a good understanding of their experiences. This study compared the experiences of nine Korean immigrant students in the sciences and social sciences at two Toronto-based universities and the support resources they utilized. Using Reason’s (2009) persistence framework, different aspects of student experiences, including the transition from high school to university and their academic studies, were examined through semi-structured focus groups and interviews. Research participants commonly had difficulties adjusting to Canadian universities and encountered linguistic difficulties throughout their lecture participation and assessment completion that hindered their persistence toward their goal of graduation. The participants varied in the difficulties they encountered with the disciplinary natures of the sciences and social sciences throughout their studies. The participants developedstrategies of audio-recording lectures, reaching out to their peers and teaching staff, and using online resources to overcome the challenges. Differences in participant experiences between the two universities appeared regarding Korean student groups, which they found as the most beneficial source of support. Suggestions are made to better support the experiences of immigrant students inCanadian universities.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.034 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".