Telecollaboration and Intercultural Communicative Competence: Revealing Students’ Experiential Insights in Saudi Arabia and the U.S.
Bibliographic record
Abstract
As several intercultural communicative competence studies integrated telecollaboration, this practice has become popular in academia and other relevant disciplines such as bridging cultural differences. Nevertheless, most of such research has been conducted in South Asian countries such as China, Japan and Taiwan, as well as in North America and Europe, with the focus mainly on European languages, specifically English. The driving force of this research was because there has been a rapid increase in the number of learners of English and Arabic as foreign languages, who have rarely interacted together, either because of an existing limited understanding or narrow cultural awareness of each other’s cultures and perhaps languages. Accordingly, the researcher presented a comparative analyses of language learners' insights prior to and after their engagement in a telecollaborative experience. The research indicated that, in the past, there have been limited studies conducting similar investigations of those two settings, due to the tremendous differences in both the languages and cultures. The findings have shown the necessity of participants to understand each other’s needs and interests to result in successful telecollaboration during ICC process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".