The effect of editing techniques on machine translation-informed academic foreing language writing

Abstract

Although the field of machine translation has witnessed huge improvements in recent years, its potentials have not been fully exploited in other interdisciplinary areas such as foreign language teaching. The aim of this paper, therefore, is to report an experiment in which this technology was employed to teach a foreign language to a group of students. This mixed-method study explores the effect of teaching editing techniques in machine translation to a group of Persian EFL university students in an academic writing course. Twenty students took part in a 4-day workshop in which one session was devoted to teaching editing techniques and three remaining sessions to the use of editing techniques, namely, correcting mistakes, removing ambiguities, simplifying structures and combining structures. Each session consisted of a pre-test, a training and a post-test. In addition, in each session, one key writing point, namely, determiners, paraphrasing and collocations were discussed. A questionnaire for candidates’ demographic information and another for learning experiences were administered. The results indicated a statistically significant improvement in the overall gain score. Further analysis showed a significant improvement in the use of determiners in contrast to paraphrasing and collocations. Lack of improvement in data driven learning in paraphrasing and collocation seemed to stem from weakness in vocabulary and grammatical knowledge in both the mother tongue and the target language. Analysis of questionnaire data revealed that the instruction proved to be beneficial since it could be easily implemented in correction and confirmation. On the whole, it can be concluded that providing the correct type of guidance and feedback on how to use machine translation will indeed have a profound effect on foreign language writing skill.

Keywords

• editing
• machine translation
• data driven learning
• writing