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How to Enhance Cross-cultural Awareness in TEFL

2010· article· en· W1889131188 on OpenAlexvenueno aff
Bao-he Zhao

Bibliographic record

VenueCross-cultural communication · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCultural competenceSociologyHumanitiesPedagogyLanguage educationPsychologyPhilosophy

Abstract

fetched live from OpenAlex

There is close relationship between language and culture. Language reflects culture and it is influenced and shaped by culture at the same time. Consequently, teaching English is inseparable from teaching its culture. Cultural awareness or tolerance is of great importance in English teaching and learning. It contributes to effectiveness and appropriateness of an English discourse. Only with the communication of language competence and cultural awareness can a language learner be successful in communication. To achieve this goal, the article develops closely around how to foster students’ cross-cultural awareness in EFL teaching. Key words: cross-cultural awareness; EFL teaching; cultural differencesResume: Il y a des liens etroits entre la langue et la culture. La langue reflete la culture et elle est influencee et faconnee par la culture en meme temps. Par consequent, l’enseignement de l'anglais est inseparable de l'enseignement de la culture anglaise. La sensibilisation a la culture ou la tolerance est de grande importance dans l’enseignement et dans l'apprentissage de l'anglais. Elle contribue a l'efficacite et a la pertinence d'un discours en anglais. Un apprenant de langue ne peut reussir dans la communication qu’avec des competences linguistiques et la sensibilisation. Pour atteindre cet objectif, l'article se developpe autour de la facon de favoriser la sensibilisation interculturelle des eleves dans l'enseignement EFL.Mots-Cles: sensibilisation interculturelle; enseignement EFL; differences culturelles

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.072
GPT teacher head0.527
Teacher spread0.456 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2010
Admission routes1
Has abstractyes

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