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Yijun Feng

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#artificial intelligence Open access Sep 2026

Artificial Intelligence and Future-Oriented Aesthetic Education: Design Thinking in Middle School Art Curriculum

Middle school art curricula in many systems still center on skill reproduction, which sits uneasily with the rapid diffusion of generative AI. This study develops a conceptual instructional model that embeds generative AI within the five-stage design thinking process (empathize, define, ideate, prototype, test) for an eighth-grade visual communication course. AI is assigned differentiated functions across the stages—analytical, retrieval, generative, assistive, and evaluative—while students retain responsibility for aesthetic judgment, justification of selections, and iterative revision. Three learning outcomes anchor the design and are operationalized in parallel measurement instruments: aesthetic judgment, creative problem-solving in visual communication, and stylistic self-awareness. Communicative intent is treated as the core sub-dimension of creative problem-solving rather than as a separate outcome, since intent is observable only through the design products and decisions that enact it. A quasi-experimental pretest-posttest pilot was conducted with 68 eighth-grade students (experimental group n = 34, control group n = 34) over a ten-week intervention at a single school, with both classes taught by the same art teacher. ANCOVA indicated that the experimental group outperformed the control group on aesthetic judgment, F(1, 65) = 8.42, p = .005, ηp² = .115, and creative problem-solving, F(1, 65) = 9.17, p = .003, ηp² = .124, with smaller yet significant gains on stylistic self-awareness. Thematic analysis of journals and interviews surfaced three patterns: shifted attention from execution to selection, prompt-based reasoning, and unease about authorship. Findings are presented as encouraging pilot evidence under specific local conditions, pending replication beyond the present site.

Yijun Feng · 0 citations