International students' challenges at an English-language university in Montréal
Bibliographic record
Abstract
The goal of this qualitative research project was to investigate different types of challenges experienced by a group of international students at an English-language university in Montréal, Québec, Canada, along with the factors which these students believed helped or could help them have a better experience. Semi-structured interviews were conducted with each of the participants. Among the experiences reported by the participants are language-related challenges, academic and university-related challenges, personal and social challenges, and cultural challenges. These are also reported in the research literature. While participants talked positively about different student services available to them on campus, they also described sources of additional support which they would consider helpful (e.g. a one-on-one language support program, financial support, etc.). This study also showed that not all international students, at the beginning of their studies, are aware of some key services available to them (i.e. peer-pairing programs, peer-tutoring). Given that post-secondary institutions have seen a considerable increase in international student enrolment over the past decades (The Association of Universities and Colleges of Canada, 2011, 2014; Institute of International Education, 2014), reaching out to international students should be one of universities' priorities, so as to ensure that as many students as possible take advantage of the services they may need.Keywords: international education, higher 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".