Qual Técnica de Learning Analytics Usar para Prever o Desempenho Acadêmico de Estudantes? Uma Análise Comparativa Experimental com Dados de MOOCs

Predicting student academic performance is one of the main research topics in Learning Analytics, for which different techniques have been applied. In order to facilitate the choice of a technique for this research topic, this study presents a comparative analysis among techniques applied in regression and classification, considering different application scenarios. We used data from MITx/HarvardX containing logs of activities and participation of 15 groups of 12 MOOCs offered between 2012 and 2013. Results obtained from the performance evaluation metrics suggest the choice of Decision Trees as a technique to build models for regression and a choice between Decision Trees and Support Vector Machines to build models for classification.