Examining University Students' Acceptance and Use of Artificial Intelligence Tools Within the Context of UTAUT2: An Analysis With Structural Equation Modeling

Abstract

Artificial Intelligence (AI) has been merged with everyday life activities and educational settings. Therefore, understanding the factors influencing the acceptance and use of generative AI tools has become a critical consideration. This study examined the acceptance and use of generative AI tools by university students under the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). This survey research was carried out on a sample population consisting of 292 students attending a public university located in the Southeastern part of Türkiye during the Spring semester of the Academic year 2024-2025. The research adopted a web survey methodology and used the partial least squares structural equation modeling technique (PLS-SEM). This research indicates the significant impact of performance expectancy, facilitating conditions, hedonic motivation, and habits on behavioral intention. Effort expectancy, social influence and price value were found not to have significant impact on behavioral intention. Behavioral intention and facilitating conditions were found to have a significant impact on use behavior. The multiple-group analysis also confirms the role of gender as a moderator on the relationship between facilitating conditions and behavioral intention. This research helps fill the existing gaps related to the acceptance and use of generative AI tools in educational contexts. Considering the purposes for which students use generative AI tools, it is observed that they use these tools most frequently for creating written content.