Critical Reconstruction of EdTech Discourse and Conceptual Definition in the Context of Korean Language Education

This study critically reconstructs the concept of EdTech (EduTech) in Korean language education amid the recent shift from digital transformation to AI-enabled learning environments. Using a scoping review and literature-based qualitative concept analysis, it maps how EdTech has been defined and operationalized and identifies the limitations of tool-centric definitions that overlook educational value for language learning. Based on the literature, EdTech is reconceptualized as a language-acquisition ecosystem in which interaction is intentionally organized and data-driven feedback continuously informs instructional decisions and learner support. From this perspective, platforms and AI-mediated services function not merely as auxiliary tools but as constitutive mechanisms that shape communicative contexts and learning trajectories. The study proposes three interaction design principles―contextual presence, multi-agent agency (teacher-peer-AI participation), and data-driven feedback loops―and offers an operational diagnostic checklist to clarify conceptual boundaries and implementation conditions. The findings suggest a shift from technology adoption to ecological design to support more personalized, interaction-oriented language acquisition.