KOREASCHOLAR

This study aims to collect and analyze Common European Framework of Reference for Languages (CEFR)-related research in Korean language education to identify emerging trends. It examines 28 academic articles published in Korea from 2020 to 2024, using text mining and language network analysis methods. Term Frequency (TF) and Term Frequency-Inverse Document Frequency (TF-IDF) analyses revealed that studies on curriculum design and application in Korean language education appeared with high frequency. Semantic network analysis identified key research directions, such as comparing proficiency level systems in Korean curricula, proposing “mediation” activities based on CEFR, and evaluating CEFR as an assessment tool. Latent Dirichlet Allocation (LDA) topic modeling categorized the studies into three groups: (1) research directly analyzing CEFR, (2) research applying CEFR to overseas Korean language curriculum design, and (3) research comparing existing Korean curricula with CEFR. This study is significant as the first to analyze CEFR-related research trends in Korean language education. By employing objective data analysis tools such as text mining, it enhances the reliability of findings and provides valuable insights into recent research trends.

I. 서론
II. 연구 방법
    1. 데이터 수집
    2. 데이터 클리닝
    3. 데이터 분석
III. 연구 결과
    1. TF 분석
    2. TF-IDF 분석
    3. 의미연결망 분석
    4. LDA 토픽모델링 분석
IV. 결론 및 제언
참고문헌

• 이윤덕(가톨릭대학교) | Lee Yundeok