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Generative AI tools are increasingly being adopted in education, where they function as collaborators that can provide feedback, suggest alternatives, and scaffold learning. In this paper, I conducted an autoethnographic study by examining my experience as a teacher-researcher integrating generative AI tools as a More Knowledgeable Other (MKO) within the context of game design education. Drawing on Vygotsky’s sociocultural theory, this study documents how generative AI can facilitate creative learning by extending learners’ capacity to ideate, iterate, and reflect on their design processes. This study further reflects on instructional practices and observations of learners engaging with AI-supported creative activities across workshops and training programs. My reflections reveal that generative AI tools enhance feedback loops, accelerate prototyping, and democratize access to mentorship by providing context-aware guidance. However, they also introduce challenges related to illusions of competence, a lack of internalization, and reduced iteration design depth. Future work will explore structured pedagogical models that balance human mentorship with AI-assisted guidance, aiming to establish ethical, adaptive, and creativity-centered frameworks for using generative AI in game design education. Through this lens, this study contributes to an emerging understanding of AI-enabled learning partnerships and their implications for cultivating innovation and talent in the creative industries.
Sultan A. Alharthi (Fri,) studied this question.