Learning Language and Culture Through Intercultural Online Exchange
Bibliographic record
Abstract
Abstract This chapter presents a study in which native speakers of French in Quebec, Canada interacted through computer-mediated communication (CMC) with non-native speakers in British Columbia, Canada over the course of one university semester. The goal of the study was to describe the value and characteristics of an intercultural exchange as a language practice in regards to language development, intercultural learning, and sociolinguistic development for L2 learners. This chapter presents the results of the first two aspects studied. The data included transcripts of text-based chat discussions and of an online written group forum, pre- and posttest questionnaires, and one-on-one interviews. Drawing on the sociocultural perspective, this study used a qualitative approach to analyze the collected data. The results suggest that this type of exchange fosters the creation of a collective meaning that allowed L2 learners to participate in meaningful interactions and to increase their level of confidence. Finally, the exchange allowed participants to experience the dimension of “culture as individual” (Levy, 2007), an aspect of culture that encouraged them to share their personal views on culture and to connect on a personal level with their native speaker partners.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".