- Lytvynova, S. H. (orcid.org/0000-0002-5450-6635) (2026) Аrtificial intelligence in higher education: personalization of learning, effectiveness, and challenges Zenodo, м. Женева, Швейцарія.
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Abstract
This paper critically examines the potential of artificial intelligence (AI), including generative AI, to personalize learning in higher education, its relationship with learning outcomes and psychological well-being, and the conditions for responsible implementation. Drawing on a narrative review of ten selected scholarly and institutional sources, it distinguishes AI adoption and perceived usefulness from empirically demonstrated educational effectiveness. The discussion considers intelligent tutoring systems, adaptive assessment, learning analytics, natural-language interaction, and the risks of excessive cognitive offloading, unreliable outputs, and data misuse. It emphasizes the role of instructional design, educator oversight, and transparent institutional policies in aligning AI applications with learning objectives. The paper proposes evaluating personalization through knowledge acquisition, transfer, argumentation, and independent performance, including delayed assessments, while identifying the need for comparative and longitudinal research.
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