A Case Study of the Influence of Cross-Cultural Learning and Teaching Experiences on Pre-Service Teachers’ Perception of Teachers’ Professional Standards
Bibliographic record
Abstract
Under the aegis of a Canadian SSHRC project, The Reciprocal Learning in Teacher Education and School Education between China and Canada (RLTESECC), a group of Chinese pre-service teachers joined a three-month exchange immersion program in Canada, and had opportunities to attend university teacher education courses, work with local secondary teachers, and participant in education-related activities and events. This cross-cultural learning and teaching experience not only enriched these Chinese pre-service teachers’ cultural understanding, strengthen their English expression abilities, enrich their pedagogical knowledge and skills, but also changed their opinions on teachers between eastern and western more or less, leading to their new perspectives regarding teaching profession. This paper aims to explore the impact of this cross-cultural program on pre-service teachers’ perception of teachers’ qualities and teaching professional standards. Through surveys by questionnaire, interview, and participants’ reflections, the study found that some changes happened in pre-service teachers’ perception and understanding of elementary and secondary teachers’ qualities before and after they went abroad. And the causes of these changes are also discussed in this study. Findings of this study have practical implications for construction and implementation of teacher professional standards and pre-service teacher education for both China and Canada.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".