Exploring adolescents' development of intercultural competence through the Canadian interprovincial student exchange
Bibliographic record
Abstract
To help live harmoniously in a multicultural country with two official languages, young Canadians must develop skills to interact with fellow citizens; that is, they need to develop their intercultural competence (IC). To this end, there are many educational initiatives in Canada, such as the Canadian interprovincial student exchange. Through this exchange, secondary students from English-dominant provinces are paired with students from Québec. In turn, each paired participant lives with their host family, and hosts their partner, each for three months. Drawing from Deardorff’s process model of IC, the cultural intelligence model and learning theories, I used a mixed methods design to assess and understand the possible intercultural growth amongst participants in this exchange. Original aspects of this design include the sampling design and methods used (i.e., quasi-experimental design assessing various aspects of the exchange, and the researcher-designed participant ethnographic journal). One hundred study participants were recruited (38 exchange participants, of which 13 completed the journal, and 62 in the control group). Statistical results suggest that the exchange led, on average, to an increase in IC, as measured by the Cultural Intelligence Scale. Through thematic qualitative analysis (of interview and journal data from 14 of the exchange participants), which at times supported or contrasted with the quantitative data, I developed a series of interconnected themes. These themes showed that the ways participants achieved intercultural growth were varied and complex. For example, on the one side, participants who forged strong relationships benefitted from socialisation and developed IC. On the other side, by analysing disorienting incidents, participants were able to decentre from their own perspectives, appreciate perspectives of others, and adjust their behaviour, which helped them develop IC. Drawing on these findings, I developed a framework identifying plausible pathways to IC development for adolescent exchange participants, which can be used in future research for better understanding IC development. The study findings also point to important pedagogical implications; chiefly, the need to offer better intercultural preparation, including hosting preparation, and the value of reflection (e.g., through completion of the ethnographic journal designed for this study) to help optimise exchange participants’ IC development.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".