On Cultivation of Cross-cultural Awareness in College English Teaching:Take Integrated Skills of English as an Example
Bibliographic record
Abstract
Abstract: Language is an indispensable part of culture. To understand language means knowing about culture first. Culture teaching plays an essential role in English language teaching. The cultural orientation in language communication should be highly valued and the relevant cultural background should be led in where necessary. This paper discusses the training of cross-cultural awareness in college English teaching by taking Integrated Skills of English as an example. Besides teaching language, English teaching is to cultivate the students’ cross-cultural awareness and transform their linguistic competence into communicative competence in an effective way.Key words: Culture teaching; Cross-cultural awareness; Communicative competence; Integrated Skills of EnglishResume: La langue est un element indispensable de la culture. Afin de comprendre une langue, il faut connaitre la culture d'abord. L’enseignement de la culture joue un role essentiel dans l'enseignement de la langue anglaise. L'orientation culturelle dans la communication linguistique devrait etre mise en valeur et le fond culturel approprie doit etre introduit dans le cas echeant. Cet article discute la formation de sensibilisation interculturelle dans l'enseignement de l’anglais au college en prenant des competences integrees en anglais comme un exemple. Outre l'enseignement de la langue, l’enseignement de l'anglais est de former la sensibilisation interculturelle des eleves et de transformer leurs competences linguistiques en competence communicative de maniere efficace. Mots cles: Enseignement de la culture; Sensibilisation interculturelle; Competence communicative; Competences integrees en anglais
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".