An Analysis of University Students’ Artificial Intelligence Literacy and Acceptance Levels of Generative AI Applications Across Various Variables

Abstract

This study investigates the relationship between university students’ levels of Artificial Intelligence Literacy (AIL) and their acceptance of Generative Artificial Intelligence (GAI) applications within the framework of the Technology Acceptance Model (TAM). The research was conducted using a quantitative correlational survey design with a total of 797 students enrolled in associate, undergraduate, and graduate programs at Amasya University. Data was collected through the Artificial Intelligence Literacy Scale and the Generative Artificial Intelligence Acceptance Scale and analyzed using descriptive statistics, correlation and ANOVA analyses. The findings indicated that students’ overall AIL levels were above average with the highest scores observed in the evaluation and ethics dimensions. The level of GAI acceptance was found to be moderate with performance expectancy and effort expectancy dimensions scoring higher than social influence. Small, but significant differences were observed across gender, level of education, internet usage, and school type: female students scored higher on ethical dimensions, while male students showed higher scores on effort expectancy and social influence. Graduate students achieved higher means in their performance expectancy. Correlation analysis revealed a moderate positive relationship between AIL and GAI acceptance. Regression results indicated that AIL explained 34% of the variance in acceptance. The evaluation dimension emerged as the strongest predictor, while awareness and use made limited yet significant contributions. The ethics dimension was not found to be significant. These results highlight the necessity of integrating critical evaluation and ethical awareness components into higher education curricula to foster responsible and informed use of AI technologies.