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Exploring the use of generative artificial intelligence by university students: a systematic literature review

RUDN Journal of Informatization in Education. 2025. Vol. 22. No. 1. P. 37–57.
Anna E. Korchak, Yevgeny D. Patarakin, Costley J.

Problem statement. Artificial intelligence (AI) has become a transformative force across various sectors, including education. The release of ChatGPT marked a pivotal shift in the educational landscape, accompanied by rapid proliferation of other generative AI (Gen-AI). Gen-AI tools have quickly become one of the most prevalent forms of AI in higher education. This research focus highlights a need for a comprehensive examination of Gen-AI’s use. Addressing this gap is essential to developing a holistic understanding of Gen-AI’s role in higher education, particularly from the student perspective. Given the rapid evolution of Gen-AI technology along with its rapidly growing and often uncontrolled adoption among students, a systematic literature review is necessary to synthesise current knowledge. Methodology. This study conducted a tertiary review utilising a systematic approach outlined in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, focusing on three key steps: search strategy and study selection, data analysis, and synthesis of findings. Data for this study was sourced from two databases: Google Scholar and Lens. These databases were chosen for their extensive coverage and accessibility, ensuring a comprehensive collection of relevant literature on AI use in higher education. The data was approached qualitatively: apriori and aposteriori codes were applied to the papers retrieved from Google Scholar. For a deeper analysis of the selected papers, we conducted a thematic analysis to identify recurring themes and patterns. Results. From the initial screening of 620 papers, 42 were selected for the final sample based on the predefined inclusion and exclusion criteria. The main uses of Gen-AI as identified in the analysed papers are summarised in the table. Conclusion. The variance in how AI is used among students –depending on their competence levels – highlights an essential consideration for educators: AI can potentially widen the gap between more and less competent learners. This observation calls for a pedagogical balance where AI supports learning without diminishing the educational rigour necessary for critical thinking and problem-solving skills.

Research target: Education
Language: English
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Keywords: высшее образованиеобразовательные технологииeducational technologysystematic literature reviewсистематический обзор литературывовлеченность студентов higher educationgenerative artificial intelligenceгенеративный искусственный интеллект student engagement
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