텍스트마이닝 기법을 활용한 국내 중국어 발음 교육 연구 동향 분석 = Research Trends in Chinese Pronunciation Education in Korea : A Text Mining Approach

다국어 초록 (Multilingual Abstract)

This study employs comprehensive text mining techniques to analyze research trends in Chinese pronunciation education in Korea from 2000 to 2025, examining 147 academic papers collected from RISS and KCI databases. By applying TF, TF-IDF, N-gram, and network analysis methods, the study objectively identifies core keywords such as “tone”, “syllable”, and “error”, and tracks their evolution over time.
The results reveal that research activities demonstrate cyclical patterns strongly correlating with socio-political changes between Korea and China, with significant decreases during diplomatic tensions and increases during periods of improved relations. The analysis confirms “tone” as the absolute research hub, while recent studies increasingly incorporate advanced technologies such as AI-based pronunciation assessment and smart tutoring systems. Network analysis demonstrates that Chinese pronunciation education research integrates theoretical phonetic analysis with practical educational applications through a multilayered structure.
The study identifies three developmental phases: Initial Development (2000～2005), Maturation (2006～2015), and Technology Integration (2016～2025), while highlighting current limitations including fragmented research focus and insufficient empirical validation of technology-enhanced learning. This meta-analysis offers valuable insights for improving Chinese pronunciation pedagogy and adapting to future educational challenges through interdisciplinary approaches that combine technology with educational practice.