생성형 AI 기반 확장형 읽기(Extensive Reading) 자료 제작 및 활용 연구

A Study on the Development and Utilization of Extensive Reading Materials Based on Generative AI in Korean Language Education

This study explores the pedagogical potential of developing and utilizing extensive reading materials based on generative artificial intelligence (Generative AI) in Korean language education. Two types of texts—curriculum-linked and independent—were generated and applied in Korean for Academic Purposes (KAP) classes, followed by text difficulty analysis and learner satisfaction surveys. Analysis using the International Standard Model of Korean Language Education (Kim et al., 2017) and the text difficulty prediction formula by Lee (2020) showed that curriculum-linked texts were comparable to textbook levels, while independent texts exhibited relatively higher difficulty. Learner surveys indicated that curriculum-linked texts were rated higher in usability and satisfaction, whereas independent texts, despite higher perceived difficulty, contributed positively to cultural understanding and engagement. These findings suggest that generative AI–based extensive reading materials can be utilized complementarily in both classroom and extracurricular contexts, providing a foundation for future research and pedagogical practice.