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Autor/inn/enYang, Yanxia; Wei, Xiangqing; Li, Ping; Zhai, Xuesong
TitelAssessing the Effectiveness of Machine Translation in the Chinese EFL Writing Context: A Replication of Lee (2020)
QuelleIn: ReCALL, 35 (2023) 2, S.211-224 (14 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Yang, Yanxia)
ORCID (Wei, Xiangqing)
ORCID (Li, Ping)
ORCID (Zhai, Xuesong)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0958-3440
DOI10.1017/S0958344023000022
SchlagwörterTranslation; Computational Linguistics; English (Second Language); Second Language Learning; Second Language Instruction; Positive Attitudes; Language Proficiency; Student Attitudes; Teaching Methods; Language Processing; Writing (Composition); Writing Instruction; Writing Improvement; Foreign Countries; Language Usage; China
AbstractWith the dramatic improvement in quality, machine translation has emerged as a tool widely adopted by language learners. Its use, however, has been a divisive issue in language education. We conducted an approximate replication of Lee (2020) about the impact of machine translation on EFL writing. This study used a mixed-methods approach with automatic text analyzer Coh-Metrix and human ratings, supplemented with questionnaires, interviews, and screen recordings. The findings obtained support most of the original work, suggesting that machine translation can help language learners improve their EFL writing proficiency, specifically in strengthening lexical expressions. Students generally hold positive attitudes towards machine translation, despite some skeptical views regarding the values of machine translation. Most students express a strong wish to learn how to effectively use machine translation. Machine translation literacy instruction is therefore suggested for incorporation into the curriculum for language students. (As Provided).
AnmerkungenCambridge University Press. 100 Brook Hill Drive, West Nyack, NY 10994. Tel: 800-872-7423; Tel: 845-353-7500; Fax: 845-353-4141; e-mail: subscriptions_newyork@cambridge.org; Web site: https://www.cambridge.org/core/what-we-publish/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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