Genre-Based Language Teaching Approach & University English Teaching for Different Majors
Bibliographic record
Abstract
Through the introduction and comparative analysis on the Grammar Translation Method and Communicative Approach, the present paper proposes that under the current Chinese educational circumstances, the two methods should be localized in order to adjust to the characteristics of Chinese college English classroom teaching. By combination and further perfection, the Grammar Translation Method and Communicative Approach can serve as college English classroom teaching methods with outstanding Chinese characteristics, which enable the students to improve their language competence and communicative competence, thus the transfer from teacher-centeredness and student-centeredness to learning-centeredness can be achieved. Key words: The Grammar Translation Method, The Communicative Approach, College English Classroom Teaching Resume: A travers la presentation et la comparaison de la traduction grammaticale et de la communication, le present article propose qu’il faut contextualiser ces deux methodes pour les adapter a l’E/A de l’anglais universitaire chinois et aux etudiants chinois tout en accentuant la caracteristique chinoise. Ces deux methodes, apres la combinaison, le greffage, l’amelioration, pourraient devenir la methodologie d’E/A de l’anglais universitaire a la chinoise, qui contribuera a elever le niveau linguistique et communicatif des etudiants et a realiser la transition du centrage sur l’enseignant et l’etudiant au centrage sur l’etude. Mots-cles: traduction grammaticale, communication, E/A de l’anglais universitaire 摘要：本文通過對語法翻譯法與交際法介紹及對比研究，提出在中國教育教學環境下應對其進行本土化研究，取其精華，合理嫁接，以便適合中國大學英語課堂教學和學生的特點，突出中國特色。語法翻譯法與交際式教學法經過糅合、嫁接、改良後可成為目前頗具中國特色的大學英語課堂教學方法，使學生語言能力和交際能力同時提高，並實現從教師為中心、學生為中心，向學習為中心的轉變。 關鍵詞：語法翻譯法；交際法；大學英語課堂教學
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".