Bridging the Artificial Intelligence Divide in Higher Education: Digital Literacy, Social Influence, and Ethical AI Adoption among University Students

Abstract

This study examines the determinants of ethical artificial intelligence (AI) adoption among university students by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) and Digital Divide Theory. Specifically, this study investigates the effects of digital literacy, social influence, and digital divide on ethical AI adoption, as well as the moderating role of digital divide in the relationships between digital literacy, social influence, and ethical AI adoption. A quantitative survey was conducted involving 408 university students in Indonesia. The data were analyzed using regression analysis, supported by reliability and validity tests, correlation analysis, Gaussian copula endogeneity check, Harman’s single-factor test, non-response bias test, and simple slope analysis. The findings show that digital literacy has a positive and significant effect on ethical AI adoption, indicating that students with stronger digital literacy are more likely to use AI critically, responsibly, and in accordance with academic integrity. Social influence also has a positive and significant effect, suggesting that lecturers, peers, academic norms, and institutional guidance play an important role in encouraging responsible AI use. Digital divide-related conditions are also significantly associated with ethical AI adoption, highlighting the importance of access, capability, and digital support in AI-supported learning. However, the moderating effects of digital divide are not statistically supported. These findings suggest that digital divide functions more as a direct contextual factor than as a moderating variable. This study contributes to the literature on AI adoption in higher education by emphasizing that ethical AI adoption is shaped by individual digital competence, social-academic support, and inclusive digital conditions. The findings also imply that universities need to strengthen digital literacy, develop clear AI-use guidelines, and reduce digital access gaps to promote ethical and inclusive AI adoption.