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      Factores que intervienen en el rendimiento académico en la Universidad Translated title: Factors that affect Academic Performance at the University

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          Abstract

          La minería de datos es ampliamente utilizada en el área de negocios, industrial o de servicio al consumidor. En este estudio se pretende darle una aplicación menos comercial y un poco más académica, que apoye en la toma de decisiones a los involucrados en el proceso de enseñanza-aprendizaje en la Universidad. El objetivo de este estudio es identificar factores que afectan el rendimiento académico de los estudiantes, mediante técnicas del aprendizaje supervisado utilizando árboles de decisión, para lograrlo se analizan los datos de las materias cursadas desde el año 2012 al año 2015 en pre grado de la Universidad Católica Boliviana, regional Cochabamba. Los resultados muestran que los factores que más afectaron el rendimiento académico fueron: la inscripción temprana, el mayor espacio libre en aula, repetir las materias, la hora de inicio de clases, el número de alumnos inscritos, la edad del estudiante y la experiencia del docente.

          Translated abstract

          Data mining is widely used in business, industrial or consumer service areas. This study uses a data mining technique in academic scenarios, in order to support in decision-making to whom are involved in the teaching-learning process at the university. The goal of this study is to identify factors that affect the academic performance of students, using supervised learning techniques with decision trees. For this purpose, this study analyzes the undergraduate student records from 2012 to 2015 of the Bolivian Catholic University, regional Cochabamba. The study shows that the factors that most affect students' performance are: early registration, the largest free space in the classroom, repeating the subjects, the start time of classes, the number of students enrolled, the age of the student and the experience of the teacher.

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          Most cited references3

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          Mining Educational Data to Analyze Students Performance

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            Claves en la aplicación del algoritmo CHAID. Un estudio del ocio físico deportivo universitario

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              Data Mining: A prediction for Student's Performance Using Classification Method

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                Author and article information

                Journal
                ran
                Acta Nova
                RevActaNova.
                Universidad Católica Boliviana (Cochabamba, , Bolivia )
                1683-0789
                September 2018
                : 8
                : 4
                : 552-563
                Affiliations
                [01] Cochabamba orgnameUniversidad Católica Boliviana Bolivia arteaga@ 123456ucbcba.edu.bo
                Article
                S1683-07892018000200004 S1683-0789(18)00800400004
                8fd9bce4-e8d1-49cc-8b39-65b576443a31

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

                History
                : August 2018
                : July 2017
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 18, Pages: 12
                Product

                SciELO Bolivia

                Categories
                Artículos científicos

                Data mining,student performance,higher education,Minería de datos,rendimiento académico,educación superior

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