CRISP-EDM: a proposal to adapt the CRISP-DM model for educational data mining

• Jorge Luis Cavalcanti Ramos Federal University of São Francisco Valley https://orcid.org/0000-0002-6099-6861
• Rodrigo Lins Rodrigues Rural Federal University of Pernambuco https://orcid.org/0000-0002-3598-5204
• João Carlos Sedraz Silva Universidaede Federal do Vale do São Francisco https://orcid.org/0000-0002-4082-9652
• Pamella Letícia Silva de Oliveira UFRPE

DOI: https://doi.org/10.5753/cbie.sbie.2020.1092

Abstract

This theoretical article presents a proposal to adapt the consolidated CRISP-DM data mining model to educational data scenarios, whether they come from online teaching platforms or from sources such as national course exams or even academic management systems. Despite fully following the six steps of the original model, the proposed model, here called CRISP-EDM, presents some particularities due to the types of data and the educational domain. The model has already been used in two approved doctoral theses and is now presented in more detail in this work. This is expected to contribute to research in the field of educational data mining.

Keywords: EDM, Learning Analytics, KDD

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