Generative AI for tourism and hospitality education
Jinsheng Zhu, Shuo Yu
Abstract
This study explores the transformative potential of large language models (LLMs), particularly DeepSeek-V3, in reshaping tourism and hospitality education through generative AI (GenAI). By adopting an experimental approach, the research evaluates DeepSeek’s ability to simulate diverse stakeholder perspectives, including government representatives, university administrators, educators, students, internship coordinators, and industry professionals. The study highlights how LLMs facilitate hands-on knowledge development, innovative thinking, and technology-driven scenarios in education. Leveraging multidimensional analytical frameworks, it examines the integration of GenAI in curriculum design, stakeholder engagement, and computational processes. Findings emphasize the rapid advancements in AI and their implications for creating evolving social identities, systems, and structures within educational practices and enhancing educational practices in tourism and hospitality.