Predictors of higher education students' behavioural intention and usage of ChatGPT: the moderating roles of age, gender and experience

The adoption and usage of ChatGPT among students are influenced by various factors, including individual characteristics such as age, gender, and experience with technology use. However, studies on the moderating roles of gender, age, and experience in predicting students' behavioural intention and usage of ChatGPT are limited. This study employed the Unified Theory of Acceptance and Use of Technology (UTAUT2) model to examine the predictors of Higher Education (HE) students' behavioural intention and usage of ChatGPT. The study employed a descriptive cross-sectional survey design with an adapted instrument to collect data from 486 students. Using the Partial Least Squares Structural Equation Modelling approach, the results showed that hedonic motivation, performance expectancy, effort expectancy, and social influence were significant predictors of students' behavioural intention, whereas behavioural intention and facilitating conditions had significant influence on students' actual use of ChatGPT. Age and gender were found to moderate the relationship between facilitating conditions and the use of ChatGPT. Lastly, experience moderated the relationship between habit and the use of ChatGPT, and the relationship between hedonic motivation and behavioural intention. These findings have implications for the design and implementation of ChatGPT in higher education towards enhancing students' engagement and learning outcomes.