인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
Generative AI is rapidly being integrated into English education, marking a new paradigm of innovation. Having experienced the pandemic’s abrupt shift in learning environments without adequate preparation, the present moment calls for proactive readiness. South Korea, where enthusiasm for English learning and an advanced ICT infrastructure create a unique context, could offer valuable insights. This study examines thematic patterns in Korean tertiary-level English education research during the COVID-19 pandemic. Text mining was applied to 190 Korea Citation Index (KCI)-indexed journal articles using three analytic methods: frequency analysis, semantic network analysis, and Latent Dirichlet Allocation (LDA) topic modeling. The findings indicate that learner-centered themes emerged as major areas of focus. Frequency analysis showed “learner” in 98.4% of documents, “online” in 91.6%, and “learning” in 76.8%. Semantic network analysis identified “learner” as the central node, most strongly linked with “online” (91.1%) and “learning” (75.8%) and highlighted low-proficiency learners, as “beginner-level” and “beginner-proficiency” pairs ranked among the top five associations. LDA topic modeling identified eleven thematic clusters, with learner satisfaction, engagement, and autonomy emerging alongside instructional design issues such as delivery formats, digital tools, and blended learning. Overall, the results suggest that the central pedagogical concern was not technology but the learner. In this new paradigm, as generative AI transforms educational practice, learners may become active participants who design, regulate, and critically engage with their own learning. Future research should explore how these evolving roles can be effectively supported through pedagogical design.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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