Artificial intelligence in the construction of an adaptive pedagogical model for mathematics leveling

Efraín Martínez, Araceli Queiruga Dios, Deolinda M. L. D. Rasteiro

Abstract: There is an enormous disadvantage for students who, due to different situations, have decided to return to higher education after a prolonged period of time, in the face of an educational system designed for optimal conditions for students. The disadvantage deepens when already in their adult stage, the time for academic dedication decreases due to their work occupations. This proposal aims to adapt the pedagogical model to their needs, specific needs in logic and mathematical operability, time, mobility, and location. Achieving this requires the design of a hybrid application based primarily on artificial intelligence and machine learning, seeking to achieve the adaptation to the student through the correct training of neural networks, resulting in the identification of the specific requirements of each user and the selection and application of strategies, teaching techniques and content of the mathematics program to be learned and apprehended by the person who must remedy the shortcomings caused by the cessation and in many cases by a poor academic process. The following is a tour through the different aspects that support the proposal; from the need presented by students with academic cessation to the approach of a technological and specific solution for each individual starting from the generality of the causes to the possibility of giving a unique result thanks to the developments in Artificial Intelligence and Machine Learning.