번역학 내 기계번역 연구 동향 및 발전 방향 - 2021년부터 2024년까지 KCI 번역학 논문을 중심으로

초록

As machine translation continues to reshape professional and pedagogicalpractice, translation studies must critically examine how the field has responded. This study maps MT research trends in Korean translation studies and identifiesgaps warranting further development. Drawing on an analytical frameworksynthesized from Choi (2019), Lee (2020), and Shin (2020), this study analyzed77 articles published between 2021 and 2024 across five Korean translationstudies journals. The findings reveal that generative AI has rapidly emerged as adominant research focus. Alongside this shift, research topics have grown morediverse as MT scholarship matures. Nevertheless, significant gaps remain:producer-oriented perspectives are underrepresented; specialized MT systemsreceive limited attention; error analysis risks becoming disproportionatelyforegrounded; classroom findings show inadequate transferability; userperception and acceptance studies address a narrow range of stakeholders; andproductivity research seldom accounts for cognitive dimensions or multipleinteracting variables. These findings point to the need for greater topicdiversification, more rigorous and valid research designs, and sustainedinterdisciplinary collaboration to advance MT research within Korean translationstudies.

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