Integrating the adapted UTAUT model with moral obligation, trust and perceived risk to predict ChatGPT adoption for assessment support: A survey with students

ChatGPT stands out among other AI technology tools to provide assessment support in the higher education context. This exploratory study investigates the motivators and barriers which influence the use intention of ChatGPT for assessment support among undergraduates in Hong Kong. We tested the adapted and extended UTUAT model using the structural equation modeling approach. Through self-report online questionnaire, we received usable responses from 483 undergraduates of eight Hong Kong universities. In a highly competitive Chinese context, assessment results hold immense significance in determining the value and merit of students. The findings reveal that trust acts as the strongest determinant while moral obligation and perceived risk serve as major inhibitors to students’ acceptance of ChatGPT in assessments. Perceived risk does not mediate the relationship between trust and students’ behavioral intention. Both performance expectancy and effort expectancy positively influence behavioral intention to use ChatGPT for assessment support. However, social influence is found to be statistically insignificant. The results contribute to the education literature by extending the adapted UTAUT model with additional variables for ChatGPT adoption in the assessment context. They offer practical insights to promote ethical and optimal use of ChatGPT in the higher education context.