AI chatbots vs. web-based learning in digital health: a randomized trial on improving dry eye syndrome knowledge for nursing students.

Abstract

AI chatbots show promise for delivering interactive, personalized health education but require validation against traditional methods. This study compared effectiveness of artificial intelligence chatbot versus website-based learning for dry eye syndrome knowledge acquisition among undergraduate nursing students. In this randomized controlled study, participants completed baseline dry eye syndrome questionnaires, then were randomized to artificial intelligence chatbot (n = 32) or website groups (n = 31). Over two weeks, artificial intelligence chatbot group received personalized responses via Gemini 2.0, while website groups accessed standardized website content. Post-intervention, both groups completed dry eye syndrome knowledge questionnaire. A comparative analysis evaluated artificial intelligence-generated versus website content for knowledge acquisition, knowledge quality, readability, understandability, and actionability. Both groups showed significant knowledge acquisition, with no significant between-group difference. However, artificial intelligence chatbot responses demonstrated superior knowledge quality in preventive strategies and treatment approaches. AI chatbot showed significantly better readability, understandability, and actionability scores. These results may offer practical strategies for using chatbots not only for knowledge acquisition but also for the digital transformation of nursing education. Artificial intelligence chatbot effectively enhance dry eye syndrome education by improving health promotion through interactive, personalized content.