Effects of AI-generated images in visual art education on students' classroom engagement, self-efficacy and cognitive load

Abstract In recent years, Generative Artificial Intelligence (GAI) has demonstrated remarkable potential for producing creative content, including artwork, which has sparked discussions regarding its role in education. Although AI-generated art is gaining recognition in the art world, its application in visual art education remains underexplored. To address this gap, we focused on AI-generated images-a specific category within AI-generated art that emphasizes visual representation. We integrated these images into visual art education and conducted an experiment to evaluate their effects. Seventy-eight fifth-grade students were randomly assigned to a treatment group (n = 39) and a control group (n = 39). Initially, both groups received conventional visual art instruction using classical images. Subsequently, the treatment group was introduced to a GAI-assisted teaching method utilizing AI-generated images, while the control group continued with conventional instruction. The results revealed that students in the treatment group exhibited significantly higher levels of classroom engagement compared to their peers in the control group. Moreover, the treatment group reported a strong sense of self-efficacy with the GAI-assisted method. Importantly, there were no significant differences in cognitive load between the two groups. A comparative analysis of the students’ paintings was conducted, focusing on technical skill, adherence to theme, composition and design, creativity and originality, effort, and improvement, which aligns with the increased classroom engagement and self-efficacy, thereby supporting the effectiveness of AI-generated images. This study is one of the pioneering works to propose and validate the use of AI-generated images to address challenges in developing learning materials within the context of visual art education.