A Learner Corpus Study of Attributive Clauses and Passive Voice in Student Translations

A Learner Corpus Study of Attributive Clauses and Passive Voice in Student Translations

Yvonne Tsai (National Taiwan University, Taiwan)
DOI: 10.4018/978-1-4666-6615-3.ch006
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Abstract

This chapter centers on the nuisance caused by passive voice and attributive clauses in student translations. With the use of learner corpus, calculation, categorization, and annotation functions enable analysis of common linguistic features in student translators. The aim of this study is to correct learners' under-use, over-use, and misuse of terms and linguistic structures. By incorporating technology into teaching and by analyzing passive tense and attributive clauses in student translations with learner corpus, the following study can contribute in designing more effective curricula and teaching materials. The use of objective data to examine student translations provides student translators an autonomous learning environment and translation improvement opportunities.
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Passive Constructions In English And Chinese

To start with, English passives are used more frequently than Chinese passives (R. Xiao, 2007). The passive voice in English is often intentionally used to emphasize the patient; the agent becomes less important and defocused, and as a result, agentless passives are more frequently used than those with agents. Biber et al. (1999) refer to passives with an agent as “long passives” and to those without as “short passives”. Studies show that short passives are more frequently used than long passives in both written and spoken English. Short passives are also significantly more common in spoken than in written English (R. Xiao, 2007).

Key Terms in this Chapter

Learner Corpus: Electronic collections of written texts produced by foreign or second language learners in a variety of language settings.

Text Analysis: The deconstruction of information within a text, such as text structure, text pattern, linguistic features, lexical analysis, and syntactic analysis.

Readability: The quality of written language that makes it easy to read and understand.

Contrastive Analysis: The systematic study of a pair of languages with a view to identifying their structural differences and similarities.

Translation Strategy: A way or method of rendering a certain linguistic unit from one language to another.

Translation Error: A translation error arises from the existence of a relationship between a Target Text and a Source Text during the transfer and movement from the Source Text to the Target Text.

Autonomous Learning: The learner take responsibility for his/her own learning, set goals, choose language learning strategies, monitor progress, and evaluate his/her successful acquisition.

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