AI-Assisted Mood Board Development: Enhancing Creative Ideation in Graphic Design Education - Anggarini, Anggi; Pramesti, Rachmadita Dwi (University of Science and Computer Technology, 2026)
This study examines how integrating Artificial Intelligence (AI) into mood board development enhances the ideation process in graphic design education. The research aimed to understand how AI-supported visual exploration influences students’ originality, complexity, and goal alignment during creative concept development. A mixed-method approach was employed, combining quantitative rubric-based evaluation of student mood boards with qualitative thematic analysis of interviews and classroom observations to capture both performance outcomes and design thinking processes. The findings show that AI tools expanded visual exploration and improved conceptual clarity, yet their effectiveness depended on how critically students engaged with prompt iteration and keyword synthesis. Students who refined descriptive keywords and combined AI outputs with digital imaging achieved higher originality and coherence. Complexity increased when students generated multiple AI iterations from different visual angles, whereas goal alignment benefited from structured mind mapping informed by tone and manner. Qualitative results revealed six interrelated themes: idea exploration, AI assistance, visual curation, AI limitations, ethics and reflection, and implementation recommendations, highlighting the interplay between human judgment and computational generation. Overall, the study affirms that mood board development remains essential in guiding conceptual direction and visual storytelling in design education. AI serves as a creative collaborator that supports deeper ideation and expands the boundaries of visual experimentation in contemporary design learning.