University education is at a critical moment due to the pandemic generated by the Coronavirus Disease 2019. Universities, to guarantee the continuity of education, have considered it necessary to modify their educational models, implementing a transition towards a remote education model. This model depends on the use of information and communication technologies for its execution and the establishment of synchronous classes as a means of meeting between teachers and students. However, moving from face-to-face classes to online classes is not enough to meet all the needs of students. By not meeting the needs and expectations of students, problems are generated that directly affect learning. In this work, Big data and artificial intelligence are integrated as a solution in a technological architecture that supports the remote education model. This integration makes it possible to identify the state of learning and recommend immediate actions to its actors. Teachers, knowing the variables that affect academic performance, have the ability to change the components of learning or the method used. Improving learning and validating the capacity of information technologies to generate digital environments suitable for the generation of knowledge. In addition to improving the functionality of educational models and their adaptability to the new normal.
Keywords: Artificial intelligence; Big data; Learning; Remote education.
©2021 Villegas-Ch. et al.