Artificial intelligence for design education: a conceptual approach to enhance students’ divergent and convergent thinking in ideation processes

Abstract Contemporary creativity support tools (CSTs) primarily support divergent thinking, while often neglecting convergent thinking. Currently, research is limited concerning how these complementary aspects of creative thought could be integrated into a unified approach. This article theoretically conceptualizes the integration of artificial intelligence (AI) as a facilitator within CSTs to enhance design students' divergent and convergent thinking during ideation processes in higher education. The research employed the concept-driven design research methodology and conducted qualitative interviews with ten design students to evaluate and refine a theoretically underpinned design concept. The study identified four key themes that informed the crafting of a revised design concept: clarity and comprehension requirements, visualization of user journeys, the role of AI, and the balance between predictable and unpredictable interactions. Through iterative refinement, the research established a theoretically and empirically underpinned design concept that demonstrates how AI facilitation can support both divergent and convergent thinking while preserving student agency in creative processes. This research contributes to the theoretical grounding of AI-enhanced creativity support and provides practical insights for integrating AI facilitation in CTSs for design education.