Economics students’ behavioural intention and usage of ChatGPT in higher education: a hybrid structural equation modelling-artificial neural network approach

Abstract

The Chat Generative Pre-Trained Transformer, popularly referred to as ChatGPT, is an AI-based technology with the potential to revolutionise conventional teaching and learning in higher education institutions (HEIs). However, it remains unclear which factors influence the behavioural intentions and the actual usage of ChatGPT among economics students in Ghanaian HEIs. In pursuit of this goal, we employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) to gain a better understanding of the antecedents influencing the behavioural intentions and actual usage of ChatGPT among economics students. The study surveyed 306 Ghanaian students enrolled in economics at a public university. These students were aware of the existence of ChatGPT applications. We applied a hybrid analytical approach, combining structural equation modelling and artificial neural network (SEM-ANN), to elucidate the causal relationships between variables believed to impact perceived trust, intentions, and actual usage. The results showed that design and interactivity have a significant impact on perceived trust. Similarly, perceived trust, social influence, performance expectancy, hedonic motivation, and habits drive behavioural intentions. Among the various factors influencing behavioural intentions, hedonic motivation emerged as the most dominant. Moreover, behavioural intentions and facilitating conditions significantly drive students’ actual use of the ChatGPT. Nevertheless, ethics is not a significant factor in perceived trust, and effort expectancy does not affect behavioral intention. These findings, however, offer theoretical and practical contributions that can serve as guide for a thoughtful and responsible integration of AI-based tools as a future strategy to enhance education accessibility and inclusivity opportunities.