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Although previous research has acknowledged the significance of comprehending the initial acceptance and adoption of ChatGPT in educational contexts, there has been relatively little focus on the user’s intention to continue using ChatGPT or its continued usage. Therefore, the current study aims to investigate the students’ continuance intentions to use ChatGPT for learning by adopting the stimulus–organism–response (SOR) model.

This study has employed the SOR model to investigate how UTAUT factors (such as performance expectancy, facilitating conditions, effort expectancy and social influence) influence the cognitive responses of students (e.g. trust in ChatGPT and attitude towards ChatGPT), subsequently shaping their behavioral outcomes (e.g. the intention to continue using ChatGPT for study). A sample of 392 higher students in Vietnam and the PLS-SEM method was employed to investigate students’ continuance intention to use ChatGPT for learning.

This study reveals that students’ continuance intention to use ChatGPT for learning was directly affected by their attitude toward ChatGPT and trust in ChatGPT. Meanwhile, their attitude toward ChatGPT was built on effort expectancy, social influence, and facilitating conditions and trust in ChatGPT was developed from effort expectancy and social influence.

By extending the analysis beyond initial acceptance, this research provides valuable insights into the factors that influence the sustained utilization of ChatGPT in an educational environment.

The emergence of artificial intelligence technologies, like ChatGPT, has taken the world by storm, particularly in the education sector. This study aims to adopt the unified theory of acceptance and use of technology to explore how effort expectancy (EEC) and performance expectancy (PEE) individually, jointly, congruently and incongruently affect higher education students’ intentions and actual uses of ChatGPT for their learning.

An advanced methodology – polynomial regression with response surface analysis – and a sample of 1,461 higher education students recruited in Vietnam through three-phase stratified random sampling approach were adopted to test developed hypotheses.

Both EEC and PEE were found to have a direct positive impact on the likelihood of higher education students’ intention to use ChatGPT, which in turn promotes them actually use this tool for learning purposes. Conversely, a large incongruence between EEC and PEE will lower the level of intentions and actual uses of ChatGPT for learning. However, when there is a growing incongruence between EEC and PEE, either in a positive or negative direction, the likelihood of students’ intentions to use ChatGPT for learning decreases.

Some practical implications are subsequently recommended to obtain advantages and address potential threats arising from the implementation of this novel technology in the education context.

This study shed the new light on the educational setting by testing how higher education students’ intentions to use ChatGPT and subsequent actual uses of ChatGPT are synthesized from the balance between high EEC and PEE.