Artificial intelligence in higher education: Benefits and concerns

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Authors: Nitza Davidovitch, Aleksandra Gerkerova
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Abstract

Artificial intelligence (AI) is transforming higher education through applications such as adaptive learning platforms, virtual assistants, and predictive analytics. This study examines AI’s impact on student motivation, academic performance, and ethical considerations, using survey data from 76 students across five universities in Odessa, Ukraine. Participants from STEM, the humanities, and the social sciences offered diverse perspectives on AI use. The findings indicate that more frequent AI use is positively associated with motivation (r = 0.60, p < 0.01), involvement (r = 0.67, p < 0.01), and self-reported academic performance (r = 0.54, p < 0.05). Students also perceived AI as supportive for retention (M = 4.05, SD = 0.79; 78%) and understanding (M = 3.90, SD = 0.85; 74%), and reported higher focus (M = 4.10, SD = 0.77; 80%) and efficiency (M = 4.30, SD = 0.72; 85%). Ethical concerns were prominent, with strong agreement on plagiarism awareness, responsible use, and data privacy (Krippendorff’s α = 0.86–0.91). STEM students showed the most positive attitudes toward AI (78% positive) compared with the humanities (55%) and social sciences (67%). While AI fosters inclusivity by supporting non-native English speakers and students with learning disabilities, gaps in AI literacy and infrastructure limit equitable access. The study underscores the importance of governance frameworks to address ethical challenges and calls for targeted investments in AI training for students and faculty. This research highlights AI’s potential to enhance learning while emphasizing the need for responsible integration. By offering evidence-based recommendations, the study informs future strategies to ensure AI serves as a tool for empowerment rather than inequity.

Fields of Study & Subjects

Artificial Intelligence in Education Artificial Intelligence in Healthcare and Education Educational Technology and Pedagogy

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 January 2026