AI Literacy Scale for Undergraduate Design Students: Development and Validation

Artificial intelligence (AI) is reshaping design education, yet field-specific instruments to assess AI literacy remain scarce. Drawing on UNESCO’s AI Competency Framework together with Design Thinking, Systems Thinking and human–AI co-creativity, this study reconceptualizes AI literacy for undergraduate design students and develops the AI-CIEI Scale as a four-dimensional measurement tool. An initial item pool was generated through literature synthesis and expert review, and then refined via cognitive interviews and pilot testing. A survey of 485 design majors from eight public universities in China (5-point Likert scale) was conducted; exploratory factor analysis and confirmatory factor analysis supported a 25-item structure comprising Cognition & Collaboration, Implementation & Integration, Ethics & Critical Judgment, and Innovation & Systemic Thinking, with excellent model fit, high internal consistency, and satisfactory convergent and discriminant validity. Criterion-related validity was examined using a MIMIC-type structural equation model including gender, academic year, major, AI training frequency, and AI usage duration as predictors: academic year showed small but consistent positive associations with all four dimensions, whereas the other variables displayed weak and non-significant effects. These findings indicate that AI literacy in design education reflects intertwined cognitive, procedural, ethical and systemic competencies shaped more by program-level learning trajectories than by short-term exposure, and position the AI-CIEI Scale as a theoretically grounded tool for diagnostics, curriculum alignment and future intervention studies.