Analysis of the Use of Data Mining Techniques to Detect Low Academic Performance: A Review of the Scientific Literature from 2015-2020 - Crhistian Hilario-Melo; Christian Sanchez-Pantigoso; Michael Cabanillas-Carbonell (Communications of International Proceedings, 2020)
Low academic performance is a problem that affects a large number of Latin American educational institutions, this being the main problem of university dropouts. Educational data mining is an essential part in the detection of low academic performance. The present document is a systematic literature review which obtained 220 documents collected from the BD Dialnet, IEEE_Xplore, IOP Science, ProQuest, Redalyc, Science Direct, Scopus. Managing to systematize 49 documents with the best data mining techniques, reflecting them in tables and illustrations, in which we determine that the impact generated by the use of data mining techniques is positive since more than 80% accuracy is obtained.
Keywords: Academic performance; data mining; student's performance; data mining techniques.