Rethinking the importance of social norms in generative AI adoption: investigating the acceptance and use of generative AI among higher education students

Abstract

Generative artificial intelligence (GenAI) has the potential to significantly impact educational practices. Despite the apparent increase in the adoption among students, empirical research on understanding AI use and acceptance among university students is scarce. To address this gap, this study employed an extended technology acceptance model (TAM) incorporating subjective norms, perceived enjoyment, self-efficacy, and compatibility with 943 undergraduate students from 140 universities across Turkey. Findings revealed that attitude toward use, perceived usefulness, self-efficacy, and compatibility significantly predicted behavioral intention to use GenAI tools. Notably, subjective norms had a limited influence on students’ intentions to use GenAI tools, challenging traditional assumptions about social pressures in technology adoption. These insights highlight that students prioritize personal perceptions over social influences in adopting GenAI technologies. Theoretically, the study provides insights into the proposed extended TAM, by validating it in a unique socio-cultural context. Practically, the study provides recommendations on how to foster acceptance of GenAI by enhancing the usability, compatibility, and enjoyment of GenAI tools while addressing potential perceived risks and ethical concerns. The study contributes to understanding GenAI’s role in education, providing a foundation for future investigations into additional factors influencing the use and acceptance of GenAI tools in higher education settings.