Intelligent systems and their application in the evaluation of university academic performance: A literature review in the South American context

The study aimed to analyze the impact of intelligent systems on improving academic performance and personalized learning, through a review of 29 articles published between 2016 and 2024. It focused on the use of artificial intelligence, machine learning, data mining, and intelligent tutoring systems in education. The results showed that these technologies optimize educational assessment and improve academic performance. Predictive models help identify students at risk of dropping out, enabling early interventions. Adaptive architectures proved effective across various disciplines, and intelligent tutoring systems enhanced interaction and feedback. Despite these advances, challenges remain in accessibility in resource-limited environments and ethical concerns related to data privacy and algorithmic bias. The study highlights the need for an inclusive and ethical approach to ensure these technologies transform education and benefit all students.

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