Generative artificial intelligence (AI) has the potential to expand the visual toolkit available to students in digital media art. However, a visually attractive AI-generated output does not, in itself, demonstrate that students have developed the ability to make design decisions. This paper proposes a theoretical model that identifies when AI functions as a cognitive scaffold and when it functions as a substitute for the work that students should be doing. The model is based on who is responsible for problem framing, the generation of options, the evaluation of those options, and subsequent design revision. AI literacy enables students to interrogate AI outputs, while task design can be used to make these responsibilities significant. Four propositions link responsibility allocation to creative development, critical evaluation, literacy, and assessment. Two tables are provided that offer a means of operationalising the framework in terms of observable task characteristics and potential research designs. The argument is not that working independently is the best option in all cases, or that the use of AI in any form necessarily reduces creativity. Rather, the argument is that the pedagogical value of AI depends on whether it provides students with genuine opportunities to exercise and develop their judgement. The propositions require empirical testing in the context of digital media art education.
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Zheng, C. (2026) Generative AI as Scaffold or Substitute: Cognitive Responsibility in Digital Media Art Education. Global Education Bulletin, 3(6), 1-6. https://doi.org/10.71052/grb2025/YDWU6185