earticle

영어

This study analyzes academic research trends related to Multicultural Literacy (ML) using topic modeling techniques. In the context of rapid globalization and multicultural changes, ML has emerged as a key competency for enhancing social integration and industrial productivity. The study emphasizes the importance of ML by analyzing 533 domestic academic papers published between 2002 and 2024. It employs text mining techniques such as TF analysis, Word2Vec, and BERTopic to extract key keywords and identify five core topics. The first topic concerns learning strategies centered on culture, Korean language education, and the use of literary narratives. The second topic highlights global citizenship education, emphasizing multicultural values and world citizenship awareness. The third explores the convergence of media and education, while the fourth proposes educational methodologies utilizing film media. The fifth topic addresses social media and digital writing strategies in the digital age. The results show that ML plays a central role in cultural exchange and serves as an educational tool in the context of the development of digital technologies and media environments. The analyzed data connect academic discussions of ML with practical applications, highlighting the need for social integration and global citizenship education. In particular, digital literacy and convergent approaches expand the practical application possibilities in multicultural societies. This study identifies academic trends in ML research and provides future research directions and policy recommendations based on these trends. It suggests that future research should utilize diverse data sources and combine both quantitative and qualitative analysis to further explore the understanding and practical applications of ML.