Research on Fostering Intercultural Communication Competence of Foreign Language Learners
Bibliographic record
Abstract
Globalization has made cross-cultural communication a necessity. The mobility of people and the contact between countries have greatly increased cross-cultural communication. Intercultural awareness has become a prerequisite for successful cross-cultural communication. Intercultural awareness is required if a foreign language learner is to achieve the intercultural communication competence, which is now considered to be the major goal of foreign language learning. Intercultural communication competence is multi-dimensional in nature, implicating not only the linguistic competence, but also the power of perceiving and interpreting socio-cultural events, and the behavioral ability of coping independently with cross-cultural encounters. The objective of this paper is to present an overview of how language and culture are dealt with from a cross-cultural perspective, to discuss concerns with defining norms and standards for foreign language learning raised by this perspective, and to consider how to foster the intercultural communication competence by pedagogical approaches that integrate current understandings and researches of language, culture and learning into their curricular and instructional designs. Key words: Intercultural awareness; Intercultural communication competence; Language and culture; Socio-cultural perspective; Curriculum design
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".