Adoption of Artificial Intelligence (AI) by University Students: Extending Theory of Planned Behaviour (TPB) with Innovativeness and Risk

Abstract

Artificial Intelligence (AI) has seen widespread adoption across various fields, notably among students in higher education, presenting both benefits and risks. Understanding students' behavioral intentions is therefore crucial. This study evaluates Indonesian students' adoption intention (N=112) using an extended Theory of Planned Behaviour (TPB) model. The framework was enhanced by incorporating Personal Innovativeness and Perceived Risk, while also testing the moderating effects of Gender and Region. Data were analyzed using partial least squares-structural equation modeling (PLS-SEM). The model demonstrated substantial predictive power, explaining 68.5% of the variance in behavioral intention. The findings revealed that Attitude and Subjective Norms were strong, significant predictors of adoption intention. Conversely, Perceived Behavioral Control, Personal Innovativeness, and Perceived Risk were found to be non-significant factors. In the moderation analysis, Gender was found to significantly moderate the influence of both Attitude and Subjective Norms on behavioral intention. Region was also a significant moderator, but only for the relationship between Attitude and intention. The researchers recommend that universities should embrace AI technology while establishing clear regulations for its wise and ethical use. Future studies are encouraged to expand the sample size.

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