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Record W29656031 · doi:10.5206/cie-eci.v38i2.9138

Culturally Responsive Communicative Teaching (CRCLT): A New Alternative for EFL Teachers in China and Other Non-English Speaking Countries

2009· article· en· W29656031 on OpenAlexvenueno aff
Yi-Chun Lin

Bibliographic record

VenueComparative and International Education · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsChinaSociologyPedagogyCultural knowledgeHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

This paper proposes Culturally Responsive Communicative Teaching (CRCLT) as an innovative, alternative approach to meeting the specific cultural contexts and individual students’ needs in non-English-speaking countries. The paper not only contains a comprehensive theoretical framework of the proposed approach, but also offers practical recommendations based on the author’s reading of the literature and professional experience as an EFL teacher in China. The author believes such a study will contribute to EFL teachers’ knowledge of a promising approach which can be adapted to specific cultural contexts and encourage more exploration for new alternatives in teaching EFL in non-English-speaking countries. Cet article propose une approche éducative innovante et alternative appelée « Enseignement Communicatif Sensible au Contexte Culturel » qui cherche à répondre aux besoins contextuels et culturels spécifiques des étudiants de pays non anglophones. Il expose un cadre de référence théorique complet sur l’approche éducative proposée, tout en proposant des recommandations d’ordre pratiques basées sur les lectures et l’expérience professionnelle de l’auteur en tant que professeur d’anglais en Chine. L’auteur pense que cette étude, applicable à des contextes culturels spécifiques, contribuera au monde de l’enseignement de l’anglais et qu’il encouragera de ce fait l’exploration d’autres alternatives pour l’enseignement de l’anglais dans des pays non anglophones.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.057
GPT teacher head0.362
Teacher spread0.304 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2009
Admission routes1
Has abstractyes

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