RELIANCE ON ARTIFICIAL INTELLIGENCE IN ETHNOBEAUTY AND WELLNESS LEARNING AND ITS CONSEQUENCES FOR STUDENTS’ SELF-REGULATED LEARNING

Abstract

The development of digital technology and generative Artificial Intelligence has transformed students’ access to learning resources, including in cosmetology, ethnobeauty, and wellness education. Although AI can support information retrieval and learning efficiency, excessive reliance on AI may reduce students’ active engagement in planning, monitoring, and evaluating their own learning processes. This study aims to analyze students’ reliance on AI in learning and its consequences for Self-Regulated Learning through the perspectives of cognitivism and constructivism, with specific attention to beauty and wellness education. This study uses a qualitative approach with a secondary data-based case study by reviewing scientific publications related to AI in education, Self-Regulated Learning, learning theory, cosmetology education, ethnobeauty, natural beauty practices, and sustainable wellness. The results indicate that unreflective AI use can weaken students’ cognitive processing, reduce independent knowledge construction, and limit reflective learning activities. In the context of ethnobeauty and wellness learning, this condition may affect students’ ability to critically verify information about traditional beauty practices, natural ingredients, client needs, safety, and sustainability. The findings suggest that AI should be positioned as a learning scaffold rather than a substitute for students’ thinking processes. Learning strategies such as problem-based learning, inquiry, reflection, collaborative practice, and guided AI literacy are needed to strengthen students’ self-regulation while preserving cultural, ethical, and sustainable values in beauty and wellness education.