Implications for Developing Korean Language AI Digital Textbooks through Functional Analysis of U.S. Language Art AI Digital Textbooks

Objectives This study aims to analyze AI digital textbooks for national language education in the United States and draw implications for the development of AI digital textbooks for national language education. Methods AI digital textbooks for native language education in the United States were analyzed in terms of ‘student’, ‘teacher’, and ‘common’ based on the main functions of AI digital textbooks. Results The reference cases are Redbird Language art&Writing (McGraw-Hill) and IXL Language arts (IXL Learning), and the following implications were drawn as a result of the analysis. Conclusions At the student level, it was suggested that it is necessary to develop diagnostic questions that evaluate practical language performance and thinking ability, recommend optimal learning paths and contents for each individual considering cognition and emotion, provide social interactive contents, and provide AI instructors for each area of the Korean language department. At the teacher level, it was suggested that AI assistant teacher function that supports class design based on data such as eye tracking, recording, and recording of learners' language performance, the ability to reconstruct content according to the student's level, and the ability to provide teachers with a Korean language learning profile through data-based learning management are necessary. At the common level, it was suggested that there is a need for a dashboard that reveals information on learners' language use and a communication system in which information on learners' Korean learning is effectively exchanged.