Application of clustering techniques on data generated by an Online Educational Network

Juan Francisco Rodríguez Saredo, Regina Motz


The work presented in this paper seeks to identify trends and groupings in the use of an online educational network. This network has an extensive coverage throughout the national territory and provides Internet accessibility to all the students (children and adolescents). The challenge is that the data does not only belong to a particular study platform, but also includes access records to any other type of website through the network, making the selection of appropriate data quite difficult. Clustering techniques are proposed to perform the analysis. The clustering analysis is based on a space defined by the number of connections in a time interval. The knowledge obtained can be used to support educational decision making.

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