Cultivation of Chinese Students’ Cultural Awareness in College English Teaching
Bibliographic record
Abstract
Language and culture are always closely mingled together and sophisticatedly interact with each other. Language is a main expression of culture; meanwhile language is a carrier of culture. There is no language without the influence of culture. Therefore, it is imperative to integrate culture education with language teaching, have students understand different culture through the introduction of cultural knowledge, comparison of cultural phenomenon and cultivation of students’ cultural awareness from the aspects of typical cultural difference including value, national psychological characteristics, thought pattern and connotation of vocabulary and idioms. When carrying out language teaching, teachers should provide students more materials and references related to western culture at the same time of exploring cultural points in textbooks, and designing more class activities, such as role-play and mini drama, comparison and contrast, holding parties on western festivals, etc. to widen students’ cultural horizon and thereby develop students’ cross-cultural communicative competence in order to get acclimatized to the new world that is increasingly globalized and internationalized. Key words : Culture; Language; Cultural awareness; Cultural difference; Cross-cultural communicative competence
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".