Teachers’ cluster in personalized and ICT-based instruction in Korea and the USA

This study aims to analyze clusters of teachers' personalized and ICT-based instruction in South Korea and the United States and to explore the variables influencing these clusters. The K-means cluster analysis using PISA 2018 data identified four clusters: ‘High Personalization, High ICT Use’ (Korea 10.9%, U.S. 51.0%), ‘Low Personalization, High ICT Use’ (Korea 22.9%, U.S. 27.9%), ‘High Personalization, Low ICT Use’ (Korea 22.8%, U.S. 15.6%), and ‘Low Personalization, Low ICT Use’ (Korea 43.4%, U.S. 5.6%). The multinomial logistic regression analysis revealed that teaching methods encouraging reading participation and strategy, teacher cooperation, and school ICT policies significantly affected teacher clustering in Korea. For U.S. teachers, teaching methods encouraging reading participation, professional development activities related to personalized instruction, and the school's average reading achievement and SES affected teacher clusters.