Implementation of Artificial Intelligence for Personalized Learning in Higher Education

Introduction: The research focuses on the implementation of artificial intelligence to personalize learning in higher education, considering its potential to enhance educational quality, adapt the teaching process, and enable adaptive learning tailored to the individual. Methods: A documentary review methodology was followed to analyze recent academic sources, prioritizing studies that examine the impact of AI on personalized learning. The documentary analysis provided insights into the advancements, limitations, and opportunities of AI in the specific context of higher education. The article includes a total of 45 bibliographic citations obtained from academic databases such as Latindex, Scielo, Scopus, and Google Scholar. Objective: To analyze how the implementation of artificial intelligence (AI) can personalize learning in higher education. Results: The findings demonstrate that AI helps personalize higher education using intelligent tutoring systems and big data analysis combined with self-regulated learning models. These models help tailor content and guidance to everyone. However, the study also emphasizes the importance of addressing ethical challenges such as privacy and equitable access to AI. Conclusions: Artificial intelligence can be considered a valuable tool for personalizing learning in higher education, with the potential to improve students' academic performance and motivation. However, its use must be framed within rigorous policies to ensure ethical practices. Additionally, further empirical research is recommended to better understand the impact of AI in various educational contexts and to guarantee that these innovations benefit all students.