Towards responsible artificial intelligence integration in creative art and design higher education: a mixed-methods study
Yu, Peipei and Muhammad, Zahid Iqbal (2026) Towards responsible artificial intelligence integration in creative art and design higher education: a mixed-methods study. In: Future Facing Learning and AI in Higher Education, 15-17 April 2026, Teesside University, Middlesbrough. (In Press)
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Artificial intelligence tools are transforming creative education in fields such as game design, fine arts, and media production, shifting the established “studio-to-screen” paradigm from hands-on making towards digitally mediated workflows. Although these tools increasingly support ideation, asset creation, rapid prototyping, and collaboration, their curricular integration in higher education remains inconsistent and theoretically underdeveloped, particularly from the viewpoint of studio-based teaching staff. While industry-focused technical research abounds, empirical studies exploring how university educators integrate such tools into creative pedagogies and the challenges they encounter are limited. This study addresses that gap through a mixed-methods survey of 32 instructors mainly from the UK, delivering art, design, and media programmes at universities. Findings highlight the dual character of these tools as both catalysts for creative experimentation and disruptors of traditional notions of authorship and skill acquisition. Participants valued enhanced accessibility and iterative design possibilities, yet raised concerns about student over-reliance, difficulties in authentic assessment, and the potential loss of tactile, material studio practices. Thematic analysis provided evidence-based recommendations on: (1) integrating digital-tool literacy and ethical reflection into curricula; (2) creating hybrid studio-screen workflows that clarify tool use; (3) providing targeted faculty development for critical pedagogical approaches; and (4) redesigning assessment to privilege process, intention, and human-AI collaboration. These guidelines seek to support responsible, creative, and educationally strong adoption of emerging digital technologies in higher education.
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