Understanding University Students' Use of Generative AI: The Roles of Demographics and Personality Traits
Newnew Deng, Edward Jiusi Liu, Xiaoming Zhai

TL;DR
This study investigates how university students' demographics and personality traits influence their use and perceptions of generative AI, revealing significant patterns and implications for personalized educational guidance.
Contribution
It provides empirical insights into the roles of demographics and Big Five personality traits in shaping students' GAI usage and attitudes, an area previously underexplored.
Findings
Higher academic year students use GAI more.
Non-native English speakers adopt GAI more readily.
Personality traits significantly predict GAI perceptions and use.
Abstract
The use of generative AI (GAI) among university students is rapidly increasing, yet empirical research on students' GAI use and the factors influencing it remains limited. To address this gap, we surveyed 363 undergraduate and graduate students in the United States, examining their GAI usage and how it relates to demographic variables and personality traits based on the Big Five model (i.e., extraversion, agreeableness, conscientiousness, and emotional stability, and intellect/imagination). Our findings reveal: (a) Students in higher academic years are more inclined to use GAI and prefer it over traditional resources. (b) Non-native English speakers use and adopt GAI more readily than native speakers. (c) Compared to White, Asian students report higher GAI usage, perceive greater academic benefits, and express a stronger preference for it. Similarly, Black students report a more…
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Taxonomy
TopicsEthics and Social Impacts of AI
MethodsADaptive gradient method with the OPTimal convergence rate
