A Learner Corpus Study of Attributive Clauses and Passive Voice in Student Translations
Yvonne Tsai · Advances in educational technologies and instructional design book series · 2014
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.