Development of a Model for Identification of Learning Standards in Distance Education using Data Mining and Meaningful Learning

Abstract

Educational data mining can be used to understand data from educational systems to provide subsidies to assist teachers, tutors and decision makers. In this context, the objective of this work was to develop a model to identify patterns of learning in distance education using Data Mining techniques and features extracted from the Meaningful Learning Theory. Seven experiments were carried out to validate the proposed model, which consisted of collecting and analyzing data about students in the seven periods of the Pedagogy course. As a result, it was possible to explain the behavior of groups of students and to validate the proposed model as an essential resource in assisting the decision-making of teachers, tutors, and managers.