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Innovation Path of AIGC-Empowered “Industry-Academia-Research-Creation” Education Model for Cultural and Creative Majors

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  • Kun Fu

    (Guangdong Industry Polytechnic University, China)

Abstract

Online education in creative disciplines often misaligns with industry innovation. This study proposes an artificial intelligence (AI)-generated content-driven closed-loop model that synchronizes classroom creativity with industry demands via a unified digital platform. Codeveloped with three universities and 10 creative enterprises, the framework integrates a dual-mentor mechanism and real-time semantic tuning to establish a dynamic industry–academia ecosystem. Results show a 71% reduction in prototype iteration time, enhanced creative translation, and improved collaboration. Key scaling factors include algorithm compatibility, assessment fairness, and resource sustainability. An “open-incremental-collaborative” optimization strategy and a concrete AI governance framework covering transparency, bias mitigation, privacy, and intellectual property is proposed. This provides an empirically validated blueprint for AI-generated content-enhanced data-driven education.

Suggested Citation

  • Kun Fu, 2026. "Innovation Path of AIGC-Empowered “Industry-Academia-Research-Creation” Education Model for Cultural and Creative Majors," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global Scientific Publishing, vol. 21(1), pages 1-25, January.
    • Handle: RePEc:igg:jwltt0:v:21:y:2026:i:1:p:1-25
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