Asian Students’ Perceptions of English as a Lingua Franca Arising from Intercultural Communication in the Global Society
Bibliographic record
Abstract
When English as a lingua franca (ELF) arising from intercultural communication emerges in the global society due to the trend toward internationalization in recent decades, whether it is accepted by those who usually consider American English and British English as standard English deserves the attention of researchers and educators across the world. The study of this paper thus targets Asian students speaking English as a foreign language (EFL) and studying at a university in Taiwan and explores how they view such a social language through quantitative research. According to the findings, EFL students in Taiwan commonly hold positive attitudes toward ELF and also have the desire to learn it because of the need for making friends with foreigners online. It is thus concluded that EFL students in Taiwan are likely to feel motivated to learn about new forms and expressions in ELF which can make them understand more about the changing world. As the study also shows that students’ attitudes toward ELF and those toward inner-cirle Englishes are linked to each other, it is also concluded that integrating a comparative analysis of ELF and inner-circle Englishes into the English curriculum of university students in Taiwan can be considered as part of intercultural education which is beneficial for enhancing their knowledge and skills of intercultural communication in the global society. It is further suggested that Asian students living in the global society of the 21st century should not be isolated from the changing world but rather receive intercultural education which enables them to broaden their worldviews and possess certain levels of competence for responding to world affairs.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".