Reflexivity in the learning experiences of Chinese international students in Canada
Bibliographic record
Abstract
Many studies have found that Chinese international students face numerous challenges while studying in Canada. However, current research on the reasons behind these challenges is not sufficiently in-depth and comprehensive. The perspective of reflexivity can address these shortcomings. Therefore, this study aimed to explore these reasons through the lens of reflexivity. To understand their experiences with reflexivity in education in China and Canada, qualitative research approach was adopted. Six Chinese graduate students at Memorial University of Newfoundland participated in the study. Data was collected through semi-structured interviews and written narratives. Following thematic content analysis, the study yielded the following key findings: (1) The emphasis on reflexivity in Canadian education over Chinese education is widely acknowledged. (2) Participants exhibited varying degrees of depth in explaining this difference. (3) All participants expressed a preference for reflexive education. (4) Participants demonstrating higher reflexivity were more adept at the Canadian environment. Additionally, the study clarified three common misconceptions: obedience is not a principle of genuine Confucianism; regime type is likely to influence education potentially; and Canadian universities are not recommended to adopt a Chinese-style teaching approach to accommodate Chinese international students. These offer insights for future research.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.023 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".