AI' s Brush on Novice Posters: Unfolding Visual Competence Shifts of Design Students
作者
Yisu Zhao,Chuhan Li,Qianqian Hu,Fang Liu,Renke He
出处
期刊:Proceedings of DRS日期:2026-06-02
标识
DOI:10.21606/drs.2026.1379
摘要
As generative AI tools increasingly permeate design education, questions arise about their impact on novice students’ creative competence. This study addresses two research questions: (RQ1) How does AI participation affect students’ creative outcomes, particularly the visual dimensions of their work? (RQ2) How do evaluators redefine competence amid AI involvement in novice design students’ creative processes? Using a mixed-method approach, Study1 analysed professional evaluations of 88 student projects, showing that AI-assisted works scored higher in creativity and visual elaboration but not in design logic, with greater score divergence.Study2 involved interviews with eight design experts, revealing tensions in evaluators’ attribution of competence and how AI reshapes judgment criteria. Findings indicate that generative AI alters students’ visual outcomes and evaluative norms, underscoring the need for a reflective, transparent integration of AI into design pedagogy. Results also suggest updating frameworks for assessing design competence in AI-augmented learning environments.