The Integration of Intercultural Business Communication Training and Business English Teaching
Bibliographic record
Abstract
The cultural information transferred by language is an important part of Business English teaching. Therefore, teachers of Business English should not only improve the language level of the students, but also develop the students' cross-cultural understanding. The cultivation of intercultural business communication (IBC) competence could not be realized by one or several courses, it must be emphasized through the entirety of Business English teaching. For example, elements of intercultural training should be reflected in Business English teaching materials, classroom discourse, teaching activities, and teaching methodology. This paper analyzed the afore-mentioned elements of IBC competence. Utilizing literature reviews and questionnaires, it also revealed problems in teaching and cultivating IBC competence in Business English curriculum and examined what obstacle Chinese students experience in intercultural communication. The author of this paper proposed three principles that should be followed while integrating IBC competence and Business English teaching in order to realize the simultaneous increase of course knowledge and IBC competence, and to further students’ professional knowledge, English language ability, and intercultural business fluency.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".