Educational data mining: An holistic view
Oswaldo Moscoso-Zea, Sergio Luján-Mora
11th Iberian Conference on Information Systems and Technologies (CISTI) (CISTI 2016), p. 600-605, Gran Canaria (Spain), June 15-18 2016. ISBN: 978-989-98434-6-2. https://doi.org/10.1109/CISTI.2016.7521411
(CISTI'16)
Congreso internacional / International conference
Resumen
Datamining (DM) brings together a wide range of techniques and algorithms which allow the extraction of knowledge from databases for timely decision making. DM has been applied to different fields of study. One important research field is Education. Applying DM in education is known as educational datamining (EDM). The main purpose of EDM is to analyze data from educational institutions using different techniques such as: prediction, clustering, time-series analysis, classification, among others. This paper presents an holistic view of EDM including classification of algorithms, methods and tools used in DM processes. Furthermore, processes and indicators that could be improved are analyzed in educational institutions. This study covers papers presented from 2005 to 2015.