Different effects of machine translation on L2 revisions across students' L2 writing proficiency levels

被引:0
|
作者
Lee, Sangmin-Michelle [1 ]
机构
[1] Kyung Hee Univ, Global Commun, Seoul, South Korea
来源
LANGUAGE LEARNING & TECHNOLOGY | 2022年 / 26卷 / 01期
关键词
Machine Translation; L2; Revision; L2 Writing Proficiency; GOOGLE TRANSLATE; LANGUAGE; FEEDBACK; ACCURACY; LEARNERS; WRITERS; STRATEGIES; L1;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
In recent years, machine translation (MT) has been gaining popularity, both in academic settings and in everyday life among foreign language students. However, insufficient research has been conducted in this field. Moreover, the findings of extant literature are often contradictory, and there are few empirical studies based on students ' actual outcomes. Therefore, the present study investigates the effectiveness of using MT in English-as-a-Foreign-Language (EFL) writing classes. It particularly examines whether students' L2 writing proficiency levels influence their revisions when using MT. According to the results, using MT helped all levels of students improve their revisions, but to a different extent depending on their L2 writing proficiency levels. Compared to the higher-level students, the lower-level students made fewer changes per error, resulting in less improvement in the revised versions. Furthermore, this study found that the lowest-level students benefited the least from MT, mainly due to their limited L2 knowledge. Conversely, the higher-level students benefited more from MT by critically selecting better options between their own translations and those produced by MT. Overall, this study includes several pedagogical implications for using MT in L2 writing classrooms.
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页数:21
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