A Case Study of AI-Assisted Sports Injury E-book Development in a Sports Rehabilitation Keystone Design Course

This study examined AI-based sports injury E-books produced in a Sports Rehabilitation Keystone Design course and explored their potential as practice-oriented learning materials.Using a qualitative case study approach and content analysis, 12 E-books created by 31 students during the first semester of 2026 were analyzed.The analysis focused on rehabilitation concepts, functional anatomy, injury assessment and diagnosis, rehabilitation programs, medical and psychological factors, and AIbased content organization.The E-books generally presented sports injuries through definitions, causes, symptoms, diagnosis, treatment, rehabilitation exercises, and prevention strategies.They also incorporated assessment methods, including range of motion, manual muscle testing, history-taking, special tests, and balance tests, as well as return-to-sport criteria and 12-week rehabilitation programs.Some E-books addressed internal medical conditions and psychological factors, reflecting an integrated health management perspective and broader consideration of athlete recovery.However, limitations included inconsistent citation practices, insufficient verification of AI-generated content, and limited detail on exercise intensity, progression criteria, and rehabilitation decision-making.Overall, AI-based E-book production appeared to help students organize disciplinary knowledge, integrate multiple areas of sports rehabilitation, and link theoretical concepts with rehabilitation planning.These findings provide practical implications for designing, implementing, and evaluating similar AI-integrated educational projects in sports rehabilitation education and related practice-based university courses.