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Cultural Factors in EAP Teaching — Influences of Thought Pattern on English Academic Writing

2012· article· en· W1917020226 on OpenAlexvenueno aff
Xiuyan Xu

Bibliographic record

VenueCross-cultural communication · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyAcademic writingEnglish for academic purposesChinaEnglish studiesMathematics educationPsychologyLinguisticsProduct (mathematics)Political scienceMathematics

Abstract

fetched live from OpenAlex

In the last decade, more and more EFL teachers in the universities of China have been aware of the feasibility and necessity of teaching English for Academic Purpose (EAP), which is identified as one type of English for Specific Purposes, to students of non-English majors. Among the EAP courses, academic writing is considered as the most helpful one. More and more scholars of ESP in China have conducted researches on English academic writing (EAW) including analysis on the syntactic characteristics of English for academic purposes, corpus-based study of English dimension adjectives in academic speaking and writing, and comparative study on Natives’ EAW and Chinese EAW. It was pointed that the EAW research in China focuses on language form and rules, but neglects the correlation of contents and thoughts. Therefore, this research studies the influences of cultural thought patterns on English academic writing by employing product approach to contrast vocabulary and discourse differences in EAW writings produced by Chinese students and native English students. Key Words : English for Academic Purpose (EAP); Cultural factors; Thought pattern; English Academic Writing

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.068
GPT teacher head0.365
Teacher spread0.297 · 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 designObservational
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

Citations5
Published2012
Admission routes1
Has abstractyes

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