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Genre effect on Google Translate–assisted L2 writing output quality

Published online by Cambridge University Press:  25 July 2022

Assim S. Alrajhi Open the ORCID record for Assim S. Alrajhi [Opens in a new window]
Assim S. Alrajhi*
Affiliation:
Department of English Language and Translation, College of Arabic Language and Social Studies, Qassim University, Qassim, Saudi Arabia (arajhy@qu.edu.sa)
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Abstract

This study investigates and compares the quality of Google-translated texts (GTTs) across writing genres (narrative, descriptive, expository, and persuasive) with EFL student–generated texts (SGTs), and explores students’ attitudes toward Google Translate (GT) output. In a mixed-methods design with a computational approach to text analysis, this study utilizes multiple data sources, including 328 written texts, written reflections, four attitude questionnaires, focus group discussion, and individual interviews. Forty-one Arabic-speaking undergraduate students majoring in English language and translation at a Saudi university participated in this study. They engaged in eight computer-mediated writing sessions by responding to tasks using English, then responding to the same tasks using their first language (L1). Subsequently, they utilized GT to translate L1 texts into English and compared SGTs with GTTs. The findings show that GTTs have higher literacy levels and richer content in the persuasive and expository genres, and higher style levels in the narrative and descriptive genres. Moreover, the comparison between SGTs and GTTs reveals that GTTs have higher literacy levels, better style, and richer content in the descriptive, expository, and persuasive genres. Meanwhile, the students hold positive views on the general quality, grammatical accuracy, and provision of lexical alternatives in GTTs across genres. Pedagogical implications are discussed.

Keywords

L2 writingmachine translationGoogle Translatewriting genresEFL learners
Type
Research Article
Information
ReCALL , Volume 35 , Issue 3 , September 2023 , pp. 305 - 320
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of EUROCALL, the European Association for Computer-Assisted Language Learning

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