Generative artificial intelligence adoption among Generation Z students in Turkish higher education


Küçük M., Çalışkan H.

EURASIA JOURNAL OF MATHEMATICS, SCIENCE AND TECHNOLOGY EDUCATION, vol.22, no.7, pp.1-16, 2026 (Scopus)

Abstract


 This research examines how Generation Z students at a single large public university in Turkey intend to incorporate generative artificial intelligence (GenAI) into their studies. Drawing on the unified theory of acceptance and use of technology 2 (UTAUT2), a survey of 346 participants tested the seven core predictors of behavioral intention through covariance-based structural equation modeling. Hedonic motivation emerged as the strongest predictor (β = 0.322, p < 0.001), followed by performance expectancy, habit, and facilitating conditions, whereas effort expectancy, social influence, and price value showed no significant effect. Within this institutional context, students appear motivated by enjoyment, perceived usefulness, established habit, and institutional support rather than by peer pressure, affordability, or ease of use. The simultaneous non-significance of effort expectancy, social influence, and price value points to a culturally and contextually distinct adoption profile that warrants replication across institutions and cultures.