Understanding differences in student engagement with AI in art education through a cluster analysis approach - Baikulakov, Yerlan; Kozybay , Anarbek; Kenzhebekova , Rabiga; Kulakhmet , Moldabek; Kumisbekova , Moldir (Journal of Interdisciplinary Studies in Education, 2026)
This study explores how university students in Kazakhstan experience and engage with artificial intelligence (AI) tools in their art education. Focusing on students’ creative thinking, digital self-confidence, and attitudes toward AI, we gathered responses from 248 participants studying in design and art-related programs across four universities. Using a self-developed survey, we analysed the data with clustering techniques to identify four different student profiles, each reflecting different levels of creativity and comfort with AI: Practical Technophiles, Creative Traditionalists, Disengaged Learners, and Balanced Creatives. The findings reveal that students vary widely in how they perceive and use AI in their creative processes. While some embrace AI as a helpful and inspiring tool, others remain cautious, preferring traditional artistic approaches. These differences indicate the importance of flexible teaching strategies that respect students' diverse perspectives. By taking these findings into account, educators can create more inclusive and effective art education practices that integrate digital tools without losing sight of artistic identity and student agency.