머신러닝 활용 초등영어 교과서 텍스트 군집화 및 그림책 텍스트 분류 연구

• 발행기관: 한국초등영어교육학회
• 저자명: 조규희(Jo, Kyuhee) 이동환(Lee, Dong-hwan)
• 간행물 정보: 『초등영어교육』제31권 2호, 37~59쪽, 전체 23쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 2025.06.30

국문 초록

This study explores how machine-learning technique can enhance text selection in primary English education by clustering textbook dialogues according to their communicative functions and by classifying picture-book texts within the same framework. 484 dialogue texts from five publishers’ Grade 3~6 textbooks were vectorized and clustered with an unsupervised algorithm. 13 clusters aligned perfectly with a single communcative functions, while 32 clusters showed high concordance when second-most frequent function was also considered. The validated cluster labels served as training data in a logistic-regression classifier that assigned seven English picture books to curriculum-specified communicative functions. Four picture books were classified with high probability for a single function, confirming that models trained on textbook dialogues can credibly map out-of-textbook reading materials onto the curriculum. Educationally, the approach furnishes an objective tool for teachers to identify picture-book texts that reinforce the communicative goals of a given unit. More broadly, it demonstrates that quantitative text analytics can reveal latent connections between mandated textbooks and external resources, offering a scalable pathway toward more coherent and diversified input in primary English classrooms.

키워드

머신러닝 텍스트 군집화 텍스트 분류 의사소통기능 초등영어교육 machine learning text clustering text classification communicative primary English education functions