DOI: 10.58920/edu0202767 ISSN: 3123-6103

Generative AI in Korean Language Learning: A Scoping Review

Weijian Kong, Yundong Wu
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Generative artificial intelligence (GenAI) is increasingly being integrated into language education, yet evidence concerning its use in Korean language learning remains fragmented. This scoping review examines the emerging research on GenAI and related artificial intelligence applications in Korean language learning, with particular attention to pedagogical affordances, language skills, learner agency, and Korean-specific linguistic and pragmatic characteristics. Following a scoping review framework, relevant literature was identified and screened across major international and Korean academic databases. The final corpus comprised 56 sources, including direct studies of GenAI in Korean language learning, earlier Korean AI and chatbot research, broader research on GenAI in second and foreign language education, and conceptual, ethical, and policy-oriented studies. The findings indicate that existing Korean-language research is concentrated primarily on writing, prompt use, learner perceptions, and university-level instruction, while evidence concerning speaking, listening, reading, and sustained classroom implementation remains comparatively limited. The review further identifies Korean-specific challenges involving honorifics, speech-level selection, contextual appropriateness, and discourse management, which may not be adequately addressed by general-purpose GenAI systems. Across the literature, effective use of GenAI appears to depend on instructional design, learner agency, human mediation, and responsible assessment rather than technology alone. The review concludes by identifying research priorities for empirically validating GenAI-supported Korean language pedagogy and developing context-sensitive, ethically responsible approaches to its integration.

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