When Creativity Encounters Algorithms: Personality Traits as Predictors of Design Students’ Adoption and Dependence on AI-Assisted Design

Abstract

With the rapid development of generative AI, AI-assisted design tools are increasingly integrated into design education, yet students show marked differences in acceptance, continuance intention, and dependence. Given the creative nature of design learners, personality traits may strongly shape their responses to AI. This study examines how the Big Five influence attitudes toward AI-assisted design and how these attitudes drive continuance intention and AI dependence. Using PLS-SEM with data from 345 design majors, the model “Personality Traits → Attitude → Continuance Intention → AI Dependence” was tested. Conscientiousness positively predicts attitude, while extraversion, neuroticism, and openness negatively predict it; agreeableness shows no effect. These results indicate differing sensitivities to efficiency, uncertainty, and creative constraints in AI-generated outputs. Attitude significantly predicts continuance intention and directly and indirectly contributes to AI dependence. Overall, the study reveals personality’s critical role in AI adoption and provides insights for developing personalized, human–AI collaborative design education.

Keywords: AI-assisted Design, Big Five Personality Traits, Technology Adoption, Continuance Intention, AI Dependency

DOI: 10.54941/ahfe1007634