The Impact of AI-Driven Personalized Learning on Korean Language Performance
The Mediating Role of Intelligent Recommendation Systems
DOI:
https://doi.org/10.3991/ijet.v21i04.62579Keywords:
‘AI’，, ‘Language Learning’, ‘Intelligent Recommendation System’, ‘Korean Language Learning Performance’Abstract
Artificial intelligence (AI) is transforming foreign language learning from traditional knowledge transmission into a data-driven adaptive learning process. Grounded in Personalized Learning Theory and technology-enhanced learning (TEL), this study examines the impact of AI application on Korean language learning performance (KAP) from the perspective of technological mediation and further explores the mediating role of intelligent recommendation systems (IRSs). Using questionnaire and academic performance data from 850 undergraduate students majoring in the Korean language, the study employs multiple regression and mediation analysis to test the proposed relationships. The results indicate that AI application significantly improves KAP (β = 4.684, p < 0.01) and exerts a significant partial mediating effect through IRSs. Specifically, AI application significantly increases the utilization of IRSs (β = 3.127, p < 0.01), while IRSs further enhance learning performance (β = 2.827, p < 0.01). Marginal effect analysis further reveals that the positive effect of AI is strongest at moderate usage levels, whereas excessive AI use leads to diminishing marginal returns. The findings demonstrate that AI not only directly improves learning outcomes through real-time feedback, speech recognition, and personalized learning support, but also promotes resource allocation optimization and dynamic learning path adjustment through AI-driven adaptive learning mechanisms. This study extends the mechanism-oriented explanation of AI-assisted language learning within the context of Korean language education and provides theoretical and practical implications for the development of intelligent and personalized Korean language learning platforms in higher education.
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