Cultural Learning of Canadian Students Participating in the “Teaching Across Borders – National Volunteer Center Program”
Bibliographic record
Abstract
The need to internationalize teacher education programs requires us to attempt to measure the development of intercultural competencies resulting from participation in international teaching programs. From 2007 through 2009, The National Volunteer Center (NVC) of Chile’s Ministry of Education partnered with the Teaching Across Borders (TAB) program of the University of Calgary to create an international teaching program through which student teachers from the University of Calgary completed a 10-week volunteer English teaching program in Chilean public schools. This study attempts of measure the effect of the TAB/NVC program on these students’ intercultural adaptability. During the 2009 TAB/NVC program all ten program participants were administered the Cross-Cultural Adaptability Inventory (CCAI) both before and after the TAB/NVC program. The results of the participants’ CCAI pre- and post-tests reveal that some subjects made significant progress towards improving their cross-cultural adaptability while others made very little progress. There may be various reasons for this discrepancy but one possibly important factor for those subjects that did not make significant progress towards increased cross-cultural adaptability was the lack of a comprehensive intercultural training and orientation at the start of the program. The research question for this paper is: How much development toward intercultural competence and intercultural adaptability is produced by Canadian students’ participation in the National Volunteer Center’s program?
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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 | 0.001 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".