Review of Research Trends in Personal Color Diagnosis and Nail Art Color Education: Focus on the Educational Application of AI-Based Diagnosis
Soo Yeon KimThis study provides an integrative review of domestic research on personal color diagnosis and nail art color education, focusing on the educational application of AI-based personal color diagnosis. Previous studies are organized into three domains: nail art design, beauty education programs, and AI- and digital-based color diagnosis. The results show that personal color diagnosis is a key criterion for color selection and image expression in nail art, and acts as an educational mediator that links color theory with practice. Practice-based approaches, including blended and project-based learning, enhance learners’ practical competencies and their creative expression. AI-based personal color diagnosis enables objective color analysis and learner-centered feedback, to support a structured learning process integrating diagnosis, application, and feedback, while functioning as a central pedagogical component. From these findings, this study proposes a three-stage instructional model (Diagnosis–Application–Feedback), presenting an integrated educational framework for beauty education in the digital era.