FOSTERING CREATIVITY IN COMPUTER GRAPHICS EDUCATION THROUGH AN AI-SUPPORTED TEACHING MODULE

Abstract

Creativity is a critical competency in Computer Graphics (CG) education. However, university instruction remains largely technique-oriented and insufficiently supportive of creative thinking. This study develops and evaluates an Artificial Intelligence (AI)-supported teaching module designed to enhance creativity among undergraduate CG students. Grounded in contemporary creativity theory and constructivist instructional design, the module integrates AI as a cognitive scaffold across four stages of the creative process: ideation, exploration, refinement, and reflection. A Design-Based Research (DBR) approach was employed, involving iterative development and implementation in an undergraduate CG course. A mixed-methods design was adopted, with quantitative data collected using a validated self-report creativity scale (pre–post design, n = 96) and qualitative data obtained from student reflections, project artifacts, and instructor observations. Quantitative data were analyzed using paired-samples t-tests, and qualitative data were analyzed using thematic analysis. The findings indicate a statistically significant improvement in students’ creative thinking and originality following the intervention (p < .05). Qualitative results further reveal enhanced ideation fluency, increased willingness to experiment, and deeper reflective engagement. The study demonstrates that AI, when positioned as a supportive cognitive partner rather than a substitute for human creativity, can effectively foster creative learning. This research contributes a process-oriented AI-supported pedagogical model and provides empirical evidence for integrating AI into creative education.