Current Situation and Improving Method of Teaching and Learning of College English Translation
Bibliographic record
Abstract
One of the objects of college English teaching is to consolidate and foster the language ability of students. The teaching of translation aims at fostering students’ social intercourse ability. In college English teaching, however, the discussion about translation teaching and the fostering and improvement of students' translation ability are not proportionately valued. In this paper, the questionnaires about non-English majors in Jilin Agriculture University are analyzed to find out the current situation of college English translation teaching and, at the same time, bring forward corresponding improvement strategies for main problems in the teaching. Key words: English translation teaching in college, current situation of translation, translation strategies Resume: L’un des objectifs de l’enseignement-apprentissage de l’anglais universitaire est de consolider et developper la capacite linguistique des eleves. Et l’E/A de la traduction vise a former leur aptitude de communication verbale. Neanmoins, dans l’E/A de l’anglais universitaire, l’E/A de la traduction et le developpement de la capacite de traduction des eleves n’ont pas ete assez tenus en compte. A travers l’enquete realisee aupres des etudiants non specialistes d’anglais de l’Universite agricole de Jilin, l’article present analyse la situation actuelle de l’E/A de la traduction de l’anglais universitaire de notre ecole, propose des contre-mesures pour des problemes principaux existants. Mots-cles: E/A de la traduction de l’anglais universitaire, statu quo de la traduction, strategie de traduction 摘要：大學英語的教學目標之一就是鞏固和培養學生的語言能力；翻譯教學旨在培養學生的語言交際能力。然而，在大學英語教學中翻譯教學的探討和學生翻譯能力的培養與提高在一定程度上並沒有得到足夠的重視。本文通過對吉林農業大學部分非英語專業學生的問卷調查剖析了我校大學英語翻譯教學的現狀，並針對其中的主要問題提出了相應的改進策略。 關鍵詞：大學英語翻譯教學；翻譯現狀；翻譯策略
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".