생성형 AI 시대 국내 통번역 연구의 동향과 과제: 2023-2025년 3대 학술지 메타 분석

초록

This study systematically analyzes Korean scholarship on generative AI in translation and interpreting, examining 77 research articles published between 2023 and 2025 in three major Korean journals. Drawing on Christensen et al.‘s (2017) tripartite classification, the study develops an extended coding framework to map methodological trends and identify research gaps in the field. The findings reveal sharp increase in AI-related publications, rising from 14 articles in 2023 to 37 in 2025. Translation and interpreting education (37.7%) and quality evaluation (27.3%) dominate the research agenda, followed by theoretical and critical discussions (13.0%). Empirical studies constitute the majority (77.9%), with textual analysis and survey methods being the most prevalent. Korean-to-English language pair remains the most studied (70.4% of language-specific studies), while explicit theoretical grounding appears only in 27.2% of the articles. These patterns suggest the Korean translation and interpreting research in the generative AI era is largely practice-driven and pedagogy-centered in the era of AI. The study identifies key gaps — including the underrepresentation of prompt engineering, process-oriented and multilingual research — and calls for a more theoretically grounded and methodologically diversified research agenda.

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