Effects of using machine translation to mediate the revision process of Korean university students’ academic writing

Abstract

In recent years, marked gains in the accuracy of machine translation (MT) outputs have greatly increased its viability as a tool to support the efforts of English as a foreign language (EFL) students to write in English. This study examines error corrections made by 58 Korean university students by comparing their original L2 texts to that of MT outputs. Based on the results of the error analysis, the error types were categorized into 12 categories. Students were divided into three distinctive groups to determine differences among them according to the frequency of errors in their writing. The t-test results reveal that the numbers of errors significantly decreased in the revised versions for most of the error types among all groups. The results of the regression analysis also reveal a positive correlation relationship between the number of changes and the reduction of errors. However, the results also indicate that although all groups made error corrections at similar rates, students who less frequently committed errors in their L2 texts (higher language proficiency groups) generally tended to correct a higher proportion of errors. Based on the findings, pedagogical implications are discussed regarding how EFL teachers can effectively incorporate MT into the classroom.

Machine Translation in the Language Classroom: Turkish EFL Learners’ and Instructors’ Perceptions and Use

“…In a study with Turkish EFL students, Tuzcu (2021) found that using OMT during writing activities increased creativity and improved students' "fluency, flexibility, originality and elaboration" (p. 48). Similarly, in a study with EFL learners in the Korean context, Lee and Briggs (2021) found that after OMT revisions, student errors in writing decreased significantly. Such innovative efforts to utilise OMT for instructional purposes may yield valuable benefits beyond efforts to limit or ban their use.…”

“…Because of these developments, language learners have started to enjoy the practicality of online dictionaries and user-friendly software applications that support online OMT. Since the 1990s, the pedagogical implications of OMT were studied for FL education, especially in the area of computer-assisted language learning (CALL) (Benda, 2014;Chandra & Yuyun, 2018;Garcia & Pena, 2011) and their practical and ethical uses (Clifford et al, 2013;Correa, 2011;Groves & Mundt, 2015;Jolley & Maimone, 2015;Knowles, 2016;Lee & Briggs, 2021;McCarthy, 2004;Niño, 2009;Tuzcu, 2021). Niño (2009) attempted to group previous research on machine translation (MT) use in FL teaching and learning into four areas: "1.…”

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“…Some studies have tried to describe the use of these tools by learners and teachers (Briggs, 2018;Clifford et al, 2013;Jolley & Maimone, 2015;Niño, 2009;O'Neill, 2019). Some other researchers have looked into possible ways to make use of these tools as Computer Assisted Language Learning (CALL) tools (Benda, 2014;Chandra & Yuyun, 2018;Garcia & Pena, 2011;Knowles, 2016;Lee & Briggs, 2021;Tuzcu, 2021). Others have focused on the issue from the perspective of academic misconduct (Correa, 2011;Groves & Mundt, 2015;Harris, 2010).…”

Lost in Translation? Students and the Hitches of Machine Translation of Academic Texts: Lecturers’ Perspectives

“…Thus, they may resort to machine translation like Google translate and Bing to change their texts from ST to TT. A few scholars (Lee & Briggs, 2021;Stander, 2020;Waddington, 2001) have studied the effects and impact of using machine translation, methods of evaluating, and strategies for helping students successfully use MT. These studies have overwhelming concentrated on the producers of the TT (i.e., the students), while neglecting the consumers of these texts (i.e., teachers or lecturers).…”