Generative AI as a Low-Cost Enabler of Campus Cultural Entrepreneurship: An Action Research Study on AI-Supported Entrepreneurial Learning among Vocational College Students

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• Semantic Scholar2026-08-09 07:15:27
  Generative AI as a Low-Cost Enabler of Campus Cultural Entrepreneurship: An Action Research Study on AI-Supported Entrepreneurial Learning among Vocational College Students

  Generative artificial intelligence (GenAI) has created new opportunities for entrepreneurship education by lowering technological and financial barriers to innovation. However, limited research has examined how GenAI can support low-cost cultural entrepreneurship practices among vocational college students, particularly through authentic product development and market-oriented learning processes. This study investigates how GenAI enables campus cultural entrepreneurship through an action research approach involving vocational college students engaged in AI-assisted cultural product creation, small-batch production, and market validation. A four-stage action research framework was implemented, including problem identification, AI-supported creative development, entrepreneurial experimentation, and market feedback-based refinement. Data were collected through student project records, product development documentation, reflective reports, client feedback, and production outcomes. The analysis focused on three key dimensions of GenAI-enabled entrepreneurial learning: (1) AI-supported creative capability, referring to students’ ability to generate and refine cultural product concepts; (2) entrepreneurial learning engagement, reflected through iterative design, collaboration, and problem-solving processes; and (3) campus cultural entrepreneurship outcomes, demonstrated through product development, customer validation, and small-batch production viability. The findings indicate that GenAI functioned as a low-cost enabler by reducing creative production costs, accelerating design iteration, and improving students’ access to entrepreneurial experimentation. Six student teams successfully completed small-batch production projects, with four achieving profitability, one reaching break-even, and one experiencing a modest loss due to production adjustment costs. The study proposes a GenAI-enabled cultural entrepreneurship learning framework that integrates AI affordances, experiential learning, and market-oriented innovation. This research contributes to entrepreneurship education by demonstrating how accessible AI technologies can facilitate vocational students’ transition from creative ideation to practical entrepreneurial activities. The findings have implications for educators and institutions seeking to integrate GenAI into vocational innovation and cultural entrepreneurship programmes.