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Acta Nova

versión On-line ISSN 1683-0789

Resumen

ARTEAGA SABJA, Wendoline  y  SANDOVAL, Juan Pablo. Factors that affect Academic Performance at the University. RevActaNova. [online]. 2018, vol.8, n.4, pp.552-563. ISSN 1683-0789.

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.

Palabras clave : Data mining; student performance; higher education.

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