From High School to Higher Education: Generative AI Use and Digital Inequalities among Final-Year Students in Romania

Szerzők és előadók

Gergely Orsolya

Szekció és helyszín

AI, Higher Education and the Transformation of Learning
2026. november 25., szerda · 10:35–12:00
Díszterem, 1088 Budapest, Szentkirályi utca 28.

Teljes, beküldött absztrakt

In recent years, generative artificial intelligence (AI) has become part of everyday learning for many young people. Final-year high school students increasingly use AI tools to search for information, complete assignments, prepare for examinations, and support their learning in different ways. As these students move from secondary education to university, their previous experiences with AI are likely to influence both their learning practices and their expectations of higher education. This paper is based on the AI module of the MATURANDUS 2026 survey, a comprehensive study conducted among more than 700 final-year high school students in Harghita and Covasna counties, Romania. The survey explored a wide range of topics related to young people's educational experiences, future plans, values, and social attitudes. This presentation focuses on the findings concerning the use of generative AI, examining students' patterns of use, their attitudes towards AI-assisted learning, and their expectations regarding the role of AI in their future educational and career trajectories. The study is informed by the sociology of youth and the literature on digital inequalities. It starts from the assumption that the educational implications of AI cannot be understood solely in terms of access to technology. While generative AI tools are becoming increasingly available, students differ in how they use them, how confidently they integrate them into their learning, and how critically they reflect on their use. The analysis therefore examines whether patterns of AI use vary according to social background, school type, and place of residence, and considers how these differences may shape students' transition to higher education. The findings show that generative AI has already become a familiar part of everyday learning for many students before they enter university. At the same time, the results suggest that equal access to AI does not necessarily translate into equal educational opportunities. Differences in digital competencies, learning strategies, and critical engagement with AI may contribute to the persistence—or even the widening—of educational inequalities during the transition from secondary to tertiary education. By focusing on students at the point of entry into higher education, the paper offers empirical insights into the experiences and expectations of a generation that has encountered generative AI before starting university. These findings may contribute to current discussions on AI in higher education by providing a better understanding of incoming students' learning practices and by supporting the development of pedagogical approaches that promote AI literacy, responsible use of AI, and more equitable educational opportunities.

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