Intelligent personal learning environments as support for inclusive education at the higher education level

Currently, due to the United Nations (UN) Agenda 2030 specifically goal 4 focused on education, higher education institutions (HEI) are striving to address inclusive education in the best possible way, it is a pending issue that is on the agenda of HEI educational policies. Personal learning environments (PLE) are educational technologies that are ideally suited to support the implementation of inclusive education because they provide a personalized learning space for each student. Machine learning techniques are used to process students' academic information and thus detect patterns of information in the data. This study has as a priority to present at an architectural level a Personal Learning Environment that integrates a Federated Learning model and through the students’ data interaction this way is possible to know the learning needs of each one with the help of Universal Design for Learning (UDL).