Generative AI divide: How College Students’ Backgrounds Affect Their Gen AI Literacy

Abstract

Abstract In the field of education, generative artificial intelligence has a profound impact, mainly reflected in areas such as personalized learning, automated assignment evaluation, content generation, and open educational resources. However, some scholars have begun to discuss whether this technology may lead to new inequalities. Therefore, this study aims to explore how user background affects the performance of generative artificial intelligence technology through empirical research while focusing on the potential educational inequalities that may arise in the era of generative AI. The research found that generative artificial intelligence literacy is correlated with grade level, institutional tier, and academic discipline, with higher-grade students, those from prestigious universities, and those studying Applied Sciences and Natural Sciences demonstrating better performance.

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