LEARNING STYLES AND THE CLUSTERING PROCESS: WHAT THEY TELL US TO FORM COOPERATIVE GROUPS IN MATHEMATICS AT EJA-EPT

o que eles nos dizem para a formação de grupos cooperativos em matemática na EJA-EPT

Abstract

This article aims to reflect on the data mining process for the composition of groups of students of Youth and Adult Education, governed by their learning styles. At that time, 25 students were submitted to an Index of Learning Styles (ILS) questionnaire that guided the possibility of groupings for future cooperative work in mathematics classes. From the collection of the style profiles of each student, the clustering algorithm k-means was used as a suggestion for the formation of groups. At the end of the work, specificities were observed in the clusters formed and in the groups of clusters. Thus, we believe that the data mining technique will be useful to the process of forming groups based on learning styles, if there is, on the part of the teacher, the necessary analysis that identifies the homogeneity of each group and the heterogeneity between the groups. groups. Based on these specificities, the teacher will have more elements to direct the pedagogical being.