Applications of artificial intelligence in the personalization of university learning
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Abstract
The increasing integration of artificial intelligence in higher education institutions has transformed how educational processes are designed and developed, fostering approaches that are more adaptable to students' individual characteristics. In this context, personalized learning has become a key strategy that leverages the capabilities of these technologies to respond to different learning paces, interests, and academic needs. This study aimed to analyze the main applications, contributions, and limitations of artificial intelligence in personalized university learning through an integrative review of scientific literature. Sixteen research studies, selected based on predefined criteria, were examined, and their results were organized through a thematic synthesis process. The analysis identified six predominant application areas: adaptive learning, recommendation systems, AI-assisted assessment, virtual assistants, learning analytics, and curriculum personalization strategies. Consequently, artificial intelligence represents a resource with significant potential for strengthening personalized learning in higher education, provided its integration is approached from a pedagogical, ethical, and technological perspective that ensures responsible use and contributes to the continuous improvement of educational quality.
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