Machine Translation and EFL Writing Development : A Focus on Complexity, Accuracy, and Fluency

Taeyeon Kim^*, Sunmee Chang^**

^*Lecturer, Department of English Language and Literature, College of Humanities & Social Science, Hoseo University
^**Professor, Department of English Language and Literature, College of Humanities & Social Science, Hoseo University

Abstract

This study investigates the effect of machine translation (MT) use on the writing performance of Korean EFL students, focusing on complexity, accuracy, and fluency (CAF). Six participants completed a series of writing tasks in which they first translated their L1 writing into L2 manually and then used MT to revise their L2 drafts. This process was repeated across ten different writing topics. Participants’ drafts were analyzed using CAF measures to assess MT’s impact on their writing performance and observe changes over tasks. The results show that MT significantly improved accuracy and fluency. However, gains in syntactic and lexical complexity were less evident. While group-level analysis showed consistent progress, individual trajectories varied widely, indicating diverse patterns of development. Overall, the findings suggest that MT enhances writing accuracy and fluency among Korean EFL students, although its impact on syntactic and lexical complexity is limited. These results indicate that MT can serve as a valuable tool for self-directed learning, helping students independently improve their writing accuracy and fluency and develop essential self-editing skills. This study highlights the potential of MT as a supplementary tool to support EFL students’ writing development, along with traditional instruction.

초록

Vol. 40 No. 4 (2022.12)

Journal Abbreviation j. Korea Saf. Manag. Sci.
Frequency Published four times annually in March, June, September, and December
Doi Prefix 10.14353/sjk.
Year of Launching 1993
Publisher The Sociolinguistic Society of Korea

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