A Needs Analysis of Elementary School Teachers on AI-based Digital English Textbooks

This study aimed to analyze elementary school teachers’ needs regarding the functions of AI-based digital English textbooks. Data were collected from a survey of 96 elementary school teachers. First, a paired sample t-test was first used to examine differences between perceived importance and current implementation. Borich’s needs assessment model was then applied to identify priority items, and the Locus for Focus model was followed visualize them. Finally, a comprehensive analysis was conducted to determine the most urgent needs. Results showed that among five categories—Diagnostic and Evaluation Functions, Support for Personalized Instructional Design, Adaptive Learning Support, AI Tutor and Assistant Teacher, and Dashboard and User Interface—the highest need was in Diagnostic and Evaluation Functions. Personalized Instructional Design and Adaptive Learning Support also showed high demand. These findings suggest that AI-based digital textbooks remain in a developmental phase, requiring further discussion on how to implement them effectively according to subject-specific needs.