AUTHOR=Sergeeva Olga V. , Masalimova Alfiya R. , Zheltukhina Marina R. , Chikileva Lyudmila S. , Lutskovskai Larisa Yu. , Luzin Alexey 

TITLE=Impact of digital media literacy on attitude toward generative AI acceptance in higher education

JOURNAL=Frontiers in Education

VOLUME=Volume 10 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2025.1563148

DOI=10.3389/feduc.2025.1563148

ISSN=2504-284X

ABSTRACT=The rapid implementation of generative artificial intelligence (AI) in higher education has emphasized the necessity to comprehend the factors that impact its acceptance among students. This study examines the influence of digital media literacy on attitudes toward generative AI acceptance in higher education. Utilizing a cross-sectional survey design, a quantitative research methodology was implemented. The research sample included 451 undergraduate students from Kazan Federal University. The assessment of digital media literacy encompassed five sub-dimensions: Device Access, Content Access, Technical Understanding, Critical Understanding, and Create. The acceptance of generative AI was assessed using a scale modified from prior studies. The study employed structural equation modeling to analyze the connections between the sub-dimensions of digital media literacy and attitudes toward accepting generative AI. The results indicated that Content Access and Create had a noteworthy positive influence on attitudes toward accepting generative AI, whereas Technical Understanding had a considerable negative effect. The implementation of Device Access yielded a modest yet noteworthy positive effect, while the introduction of Critical Understanding did not result in a substantial impact. This study contributes to the expanding body of literature on digital media literacy and its influence on the acceptability of technology in higher education. The results underscore the significance of cultivating digital media literacy skills, particularly those related to content access and creation, to prepare students for the complexities and opportunities presented by generative AI in higher education. The study offers recommendations for educators, policymakers, and academics while acknowledging its limitations and suggesting directions for future research.