Empowering ChatGPT adoption in higher education: A comprehensive analysis of university students' intention to adopt artificial intelligence using self-determination and technology-to-performance chain theories

The integration of artificial intelligence (AI), particularly ChatGPT, in higher education is rapidly expanding, offering new avenues for enhancing the learning experience. Despite its potential, the adoption of ChatGPT remains in need of further study, especially in regions like Saudi Arabia. Previous studies have focused on general e-learning tools, but more research needs to examine the specific factors influencing university students' adoption of AI technologies. This study aims to investigate the adoption of ChatGPT among university students in Saudi Arabia, focusing on the mediating role of Technology-to-Performance Chain (TPC) theory between Self-Determination Theory (SDT) constructs (autonomy, competence, and relatedness) and students' intentions to adopt ChatGPT. It also seeks to identify which SDT factors most significantly affect the adoption process. Using a quantitative approach, this study collected data from 253 university students in Saudi Arabia. Structural equation modelling was used to analyze the collected data and determine the relationship between self-determination theory (SDT), technology-to-performance chain theory (TPC) and ChatGPT adoption. Findings reveal that the perceived autonomy and relatedness significantly affect TTF and ChatGPT utilisation, whereas perceived competence has no effect. In addition, TTF and utilisation are the main predictors of intention to adopt ChatGPT. These findings can be useful for educational policy makers and researchers because they indicate that to enhance university students' adoption of AI technologies, focus should be given to their psychological needs. The results also show that enhancing students' self-determination and their perceived connection with technology can significantly affect their decision to adopt such technologies. This research also presents a new model wherein SDT is integrated with TPC with regard to AI in higher education, specifically in the context of Saudi Arabia. This work contributes to the current literature on AI in education with emphasis on cultural specificities of adoption processes.