How immigrant students from Pacific Rim countries perceive science education in Canadian classrooms
Bibliographic record
Abstract
This study documented the opinions and ideas of twelve immigrant students from Pacific Rim countries in a Canadian high school setting. Data was obtained by in-person, individual interviews. It was not very surprising to discover that there are major differences between Pacific Rim and Canadian science classrooms, as perceived and experienced by the students. Many of the stereotypes that educators hold of the Pacific Rim system of education were confirmed by several of the students that were interviewed. What was surprising is that many of the teaching methods used in the Pacific Rim system have been embraced by the students, and have been proven to support student success in science. After the completion of this study, it was difficult to determine which system of science education the students prefer. Most of the students interviewed stated that they generally disliked most of the methods and strategies used in their home countries. However, many of the students contradicted themselves by stating that the Canadian methods did not pose much of a challenge in order facilitate learning. To allow Pacific Rim immigrant students to adapt smoothly to our system of education, a combination of western and Pacific Rim methods should be incorporated. This study has implications for teachers who teach Pacific Rim immigrant students in secondary schools. Canadian science teachers, and all teachers in general, must not be too quick to judge and criticize the strategies and methods used by teachers in Pacific Rim countries. We must accept that some of their methods, regardless of the difference in philosophy, do work for many students. Canadian teachers should continue to use the strategies that they use comfortably, and try to incorporate parts of the Pacific Rim system. Perhaps this will allow Pacific Rim immigrant students to adapt to education system and our culture in a smoother fashion.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".