International Learning Experiences for Teacher Candidates: A Canadian Attempt to Provide an Intensive Study Abroad Program for Chinese Students
Bibliographic record
Abstract
A recent trend in Teacher Education is to encourage teacher candidates to undertake a learning experience located in a different context from their home institution. This paper explores the experiences of 129 teacher candidates from East China Normal University (ECNU) who visited the University of British Columbia (UBC) between 2013 and 2017 for a 3-week Intensive Study Abroad Program (ISAP) as part of their B.Ed. degree. This program required the university to develop a set of learning experiences to meet the Chinese teacher candidates’ needs. By examining their most memorable experiences of the program, this paper is an effort to understand a Canadian attempt to provide an ISAP curriculum for its Chinese guests. Data was gathered via an online survey and analyzed using the Constant Comparative Method (CCM) (Lincoln and Guba, 1985). Our findings from substantive questions can be divided into three core themes: being in the world as a teacher with humanity , being as belonging , and being critical . These findings will assist future international exchange program’s design for those university administrators and curriculum planners.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".