Data Mining for Student Outcome Prediction on Moodle: a systematic mapping - Felix, Igor Moreira; Ambrósio, Ana Paula; Lima, Priscila da Silva; Brancher, Jacques Duilio (Anais do Simpósio Brasileiro de Informática na Educação (SBIE); 2018: Anais do XXIX Simpósio Brasileiro de Informática na Educação, 2018)
Virtual learning environments facilitate online learning, generating and storing large amounts of data during the learning/teaching process. This stored data enables extraction of valuable information using data mining. In this article, we present a systematic mapping, containing 42 papers, where data mining techniques are applied to predict students performance using Moodle data. Results show that decision trees are the most used classification approach. Furthermore, students interactions in forums are the main Moodle attribute analyzed by researchers.