Analysis of media reports on digital textbooks using keyword networks and topic modeling

Objectives This study analyzed discourses related to digital textbooks in domestic media reports from 2007 to 2024. Methods To this end, data were collected from BIGKINDS, a domestic media report data provision platform, with keywords such as ‘digital textbook’ and ‘AI textbook’, and keyword frequency analysis, co-occurrence network analysis, and topic modeling were performed using the R program. Results Digital textbooks were linked to various issues in terms of policy, education, and technology, and keywords such as ‘education’, ‘digital’, ‘AI’, ‘school’, and ‘content’ appeared mainly in keyword frequency analysis. Topic modeling analysis derived 10 major topics such as digital infrastructure construction, AI-based learning innovation, resolving the education gap, digital content development, and policy support. Conclusions This study systematically analyzes media discourses on digital textbooks to suggest implications for future education policies and textbook development directions.