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Personalization of resources for the teaching of university mathematics using artificial intelligence
Objective: to present a model for the personalization of learning resources using artificial intelligence (AI) techniques for the teaching of university mathematics. Methodology: The model was built based on the learning styles of Felder and Silverman and on a prior knowledge questionnaire applied to students in algebra, geometry and trigonometry once they enter professional engineering careers. Results: The recommendations of learning resources by learning styles were analyzed and AI techniques were applied, to find patterns in seven different groups of students. Conclusion: With this model, the possibility of making an adequate recommendation of learning resources was evaluated, considering the type and order of presentation of these and, in addition, on the areas that should be prioritized when entering the university.