Artificial intelligence as a support technique for university learning

Abstract

Currently, universities seek to improve academic methods that come from a traditional model. Traditional models base learning on the experience of teachers and the development of activities. Studies carried out in the educational field consider that not all activities generate knowledge in students. The activities must adapt to the needs of each student to build an efficient model that contributes to learning. To solve this problem, education experts support academic management in the use of information and communication technologies. The inclusion of techniques such as the analysis of educational data and artificial intelligence identify the deficiencies and needs of students. This work proposes the design of an expert system that interacts with students and evaluates their responses with those of data analysis systems to reach a conclusion and recommend activities that align with the needs of each student.