A Study on Elementary English Teachers’ Use of AIDT for Personalized Learning and their Perceptions of Instructional Changes

This study examined how elementary school English teachers utilized AI digital textbooks (AIDT) during the first semester of 2025, focusing on personalized learning support and perceived instructional changes. Sixty-seven teachers with experience using AIDT participated in an online survey addressing diagnostic functions, adaptive learning features, and classroom practices. The results indicated that teachers generally held positive perceptions of AIDT’s assessment and learning analytics functions and frequently used them to monitor whole-class performance and provide feedback. The use of student-specific data for individualized or level-based instruction was also observed, though its extent was somewhat lower than might be expected based on these positive perceptions. Teachers further reported the need for more diverse diagnostic items and expanded instructional content to better support personalized learning. In terms of classroom impact, students were perceived to show higher engagement, and teachers noted a shift in their instructional roles toward facilitators and lesson designers. At the same time, some teachers expressed concerns regarding reduced professional autonomy and weakened instructional expertise. Implications for strengthening data-informed instruction are discussed.