Towards the Integration of Business Intelligence Tools Applied to Educational Data Mining
William Villegas-Ch, Sergio Luján-Mora, Diego Buenaño-Fernández
2nd IEEE World Engineering Education Conference (EDUNINE 2018), p. 1-5, Buenos Aires (Argentina), March 11-14 2018. ISBN: 978-1-5386-4889-6. https://doi.org/10.1109/EDUNINE.2018.8450954
(EDUNINE'18b)
Congreso internacional / International conference
Resumen
At present the educational institutions have computer systems that generate information of the educational activity of each student. This large amount of information is often not used to benefit the management of educational processes. Under these conditions the institutions have acquired systems that extract reports general such as student attendance, semester notes or number of students who approve a course. This information is not sufficient to take corrective measures that act in time and avoid actions such as student dropout. This work it is proposed to use the tools of business intelligence in educational data. The aim is to detect groups of students with similar. This behavior will allow to analyze the causes and possible effects on student performance in a given subject. Once the results are obtained, those involved in the educational process will be allowed to make decisions that contribute to the improvement of the educational quality.