Adoption of AI-Supported gastronomy education in higher education: A mixed methods study based on the UTAUT model

Abstract

The purpose of this research is to explore the adoption of artificial intelligence use in culinary arts and gastronomy education among academics and students using the framework of the extended UTAUT model and to enhance and expand on the results yielded by this research using primary data and with the use of a mixed research methodology. The methodology adopted for this research is a mixed methodology where primary data is collected using both survey and interview methodologies.Quantitative analysis results showed that performance expectancy, hedonic motivation, and facilitating conditions have a significant and positive effect on the attitude towards the use of artificial intelligence in gastronomy and culinary arts education. Perceived risk and social influence variables were found to have no significant effect on attitude. Qualitative findings revealed that academicians position AI as a complementary tool supporting the teaching process and that pedagogical guidance and institutional support play a critical role in AI integration. Furthermore, it was emphasized that AI can support creative and practice-based learning processes, but ethical boundaries and applied skills must be preserved.