What They Learned Won’t Go Away: The Impacts of an International Exchange Program on Chinese Teacher Candidates’ Understanding of and Practice in Science Education
Bibliographic record
Abstract
Purpose: The Canadian university where this study took place has established an international exchange program in teacher education with a large Chinese university. This study was designed to examine how the international exchange program influenced Chinese science teacher candidates’ understanding of science education and how such learning impacted their teaching in China. Design/Approach/Methods: The study adopted a qualitative research design with interview and reflective journal as the main approaches for data collection. Findings: Participants greatly appreciated the opportunity of exchange. They reported an improved understanding of Canadian school education and its science curriculum and pedagogy, which changed many aspects of their original values about the relationship between the teacher and students, classroom environment, and so on. Although they faced many constraints to implement what they learned from the exchange in Chinese science classrooms, what they learned had never been forgotten. Participants tried to apply them here and there at the level they could control. Originality/Value: There are many reported studies in the literature about Chinese international students on Western campuses. However, research on Chinese students who participate in international exchange programs is very rare. The findings of this study can inform policymakers and education practitioners about student international exchange programs and benefit future exchange participants.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".