Artificial intelligence (AI), particularly text-to-image generative AI (GenAI), has developed rapidly and is increasingly used in the field of visual arts for its ability to generate images from textual descriptions (Mannuru et al., 2023). While artists such as Jason M. Allen have shown how these tools can enhance design efficiency, inspire creativity, and support early stages of artmaking (Jaruga-Rozdolska, 2022; Marrone et al., 2022), their educational potential remains insufficiently studied, especially among school-age learners (Hutson & Lang, 2023a). This study examines how GenAI influences students’ artistic confidence and creative thinking within a nine-week, project-based art program involving fifty fifth-grade students from a public primary school in Shenzhen, China. Observations and informal interviews were conducted to gather insights into students’ learning experiences and perceptions of the technology. The presentation focuses on the methodological framework designed to elicit, interpret, and triangulate students’ voices regarding GenAI-assisted art creation. It discusses how a mixed-methods approach can capture authentic learning experiences and contribute to developing more student-centred approaches to integrating AI in art education.

Authors:
Yalan Huang, Nanyang Technological University, Singapore

About the Presenter(s)
Huang Yalan is a textile artist and art educator, currently a PhD candidate at Nanyang Technological University, Singapore. Her current research explores how text-to-image AI tools influence students’ creative thinking and artistic confidence.

See this presentation on the full schedule – Sunday Schedule

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