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Erratum published on 12 March 2021, see Sustainability 2021, 13(6), 3105.
Article

A Business Intelligence Framework for Analyzing Educational Data

1
Escuela de Ingeniería en Tecnologías de la Información, FICA, Universidad de Las Américas, 170125 Quito, Ecuador
2
Departamento de Sistemas, Universidad Internacional del Ecuador, 170411 Quito, Ecuador
3
Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, 03690 Alicante, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(14), 5745; https://doi.org/10.3390/su12145745
Received: 28 May 2020 / Revised: 12 July 2020 / Accepted: 13 July 2020 / Published: 17 July 2020
(This article belongs to the Special Issue Business Analytics and Data Mining for Business Sustainability)
Currently, universities are being forced to change the paradigms of education, where knowledge is mainly based on the experience of the teacher. This change includes the development of quality education focused on students’ learning. These factors have forced universities to look for a solution that allows them to extract data from different information systems and convert them into the knowledge necessary to make decisions that improve learning outcomes. The information systems administered by the universities store a large volume of data on the socioeconomic and academic variables of the students. In the university field, these data are generally not used to generate knowledge about their students, unlike in the business field, where the data are intensively analyzed in business intelligence to gain a competitive advantage. These success stories in the business field can be replicated by universities through an analysis of educational data. This document presents a method that combines models and techniques of data mining within an architecture of business intelligence to make decisions about variables that can influence the development of learning. In order to test the proposed method, a case study is presented, in which students are identified and classified according to the data they generate in the different information systems of a university. View Full-Text
Keywords: business intelligence (BI); educational data mining (EDM); learning management systems (LMS); learning analytics business intelligence (BI); educational data mining (EDM); learning management systems (LMS); learning analytics
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MDPI and ACS Style

Villegas-Ch, W.; Palacios-Pacheco, X.; Luján-Mora, S. A Business Intelligence Framework for Analyzing Educational Data. Sustainability 2020, 12, 5745. https://doi.org/10.3390/su12145745

AMA Style

Villegas-Ch W, Palacios-Pacheco X, Luján-Mora S. A Business Intelligence Framework for Analyzing Educational Data. Sustainability. 2020; 12(14):5745. https://doi.org/10.3390/su12145745

Chicago/Turabian Style

Villegas-Ch, William; Palacios-Pacheco, Xavier; Luján-Mora, Sergio. 2020. "A Business Intelligence Framework for Analyzing Educational Data" Sustainability 12, no. 14: 5745. https://doi.org/10.3390/su12145745

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