Earticle

초록

영어

As machine translation continues to reshape professional and pedagogical practice, translation studies must critically examine how the field has responded. This study maps MT research trends in Korean translation studies and identifies gaps warranting further development. Drawing on an analytical framework synthesized from Choi (2019), Lee (2020), and Shin (2020), this study analyzed 77 articles published between 2021 and 2024 across five Korean translation studies journals. The findings reveal that generative AI has rapidly emerged as a dominant research focus. Alongside this shift, research topics have grown more diverse as MT scholarship matures. Nevertheless, significant gaps remain: producer-oriented perspectives are underrepresented; specialized MT systems receive limited attention; error analysis risks becoming disproportionately foregrounded; classroom findings show inadequate transferability; user perception and acceptance studies address a narrow range of stakeholders; and productivity research seldom accounts for cognitive dimensions or multiple interacting variables. These findings point to the need for greater topic diversification, more rigorous and valid research designs, and sustained interdisciplinary collaboration to advance MT research within Korean translation studies.

목차

1. 서론
2. 기계번역 관련 연구들을 정리한 선행연구
3. 연구 방법
4. 분석 결과 및 논의
4.1 정량 분석
4.2 기존 연구 제안에 대한 대응
4.2.1 연구 주제의 확대 및 심화
4.2.2 생산자 관점의 연구
4.2.3 전문화 및 맞춤화된 기계번역 시스템 연구
4.2.4 지나친 오류 중심의 연구 경계
4.2.5 인식 연구는 인식 주체 범위 확대 필요
4.2.6 다른 교실로의 이전 가능성 확보
4.2.7 생산성 비교 시 다양한 요소 고려 및 인지 연구의 필요
4.2.8 포스트에디팅 교육 및 훈련, 가이드라인
4.2.9 연구 공백 영역
5. 결론
참고문헌

키워드

저자

• 이준호 [ 중앙대학교 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  통번역학연구 [Interpreting and Translation Studies]

• 간기

  계간

• pISSN

  1975-6321

• eISSN

  2713-8372

• 수록기간

  1997~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 717 DDC 400