Exploring the use of generative artificial intelligence by university students: a systematic literature review - Anna E. Korchak; Yevgeny D. Patarakin; Jamie Costley (RUDN Journal of Informatization in Education)
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 GenAI’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.