Investigating EFL College Students’ English Writings Produced by AI-Based Machine Translation
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The purpose of this research was to investigate the characteristics of Korean college students’ writings, which have been produced without or with the help of machine translation tool in the classroom. Specifically, this research attempted to investigate the linguistic characteristics of the students’ writings, and types of errors identified in the writings. Twelve pieces of writings from three college students were collected for analysis. Two online word analysis programs, Word Counter (2023) and LIWC-22 (2023), were employed for data analysis. The findings of data analysis found out that 1) The students’ drafts consisted of 22.8 sentences including 303.9 words in 3.6 paragraphs on average. 2) In the students’ drafts, ‘unique’ words (46.8%) were included a lot more than ‘difficult’ words (27%), and students tended to write their essay writings in an unfiltered or impromptu way rather than an analytical way regardless of their English language proficiency levels. 3) The highest frequency of errors was seen in grammatical errors (41.7%) followed by lexical errors (31.6%). Based on the research findings, pedagogical implications and suggestions for the effective use of machine translation in English writing classes were presented.
II. Literature Review
1. How Do Students and Teachers Perceive Machine Translation?
2. How Does Machine Translation Help Learners’ Writing?
3. How has Machine Translation Contributed to Language Teachingand Learning?
III. Methodology
1. Participants and Their Writings
2. Collecting Students’ Writings
3. Analyzing Data
Ⅳ. Results and Discussion
1. Linguistic Features of the Students’ Writings
2. The Word Use of the Students’ Writings
3. Different Error Types in Students’ Writings
Ⅴ. Concluding Remarks
References