Recruitment of international students in Canadian higher education: factors influencing students’ perceptions and experiences
Bibliographic record
Abstract
Working with education agents is common for many Canadian higher education institutions (HEIs) to recruit international students due to the key role education agents play in bridging the international students with foreign HEIs. The purpose of this study was to explore international students' perceptions and experiences with education agents, thus collecting feedback from international students, revealing potential issues, and suggesting improvements in HEIs’ recruitment strategy. An online survey combined with a paper format survey was distributed to current or recent international students across Canada. Two scales were used to measure participants' perceptions and experiences with education agents. A total of 385 participants completed the survey. Findings revealed that nearly half of the participants used education agent services during their application to Canadian HEIs. However, their perceptions and experiences with education agents were not positive. Participants described practices of double-dipping by agents and the more participants paid agents, the less satisfied they tended to be. The outcome of this study highlights issues in the recruitment of international students, identifies strategies to regulate agents’ practices, and strategies to better support international students. These findings can be used by Canadian HEIs to improve their recruitment strategy and create a better working relationship with education agents to support the transition of international students to Canadian HEIs.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".