Bibliographic citations
Zarate, W., Pando, A. (2021). Aplicación de un modelo de minería de datos para identificación de patrones que influyen en la deserción académica en el instituto superior Leonardo Davinci usando IBM SPSS modeler y la metodología CRISP-DM [Tesis, Universidad Privada Antenor Orrego]. https://hdl.handle.net/20.500.12759/7033
Zarate, W., Pando, A. Aplicación de un modelo de minería de datos para identificación de patrones que influyen en la deserción académica en el instituto superior Leonardo Davinci usando IBM SPSS modeler y la metodología CRISP-DM [Tesis]. PE: Universidad Privada Antenor Orrego; 2021. https://hdl.handle.net/20.500.12759/7033
@misc{sunedu/3587686,
title = "Aplicación de un modelo de minería de datos para identificación de patrones que influyen en la deserción académica en el instituto superior Leonardo Davinci usando IBM SPSS modeler y la metodología CRISP-DM",
author = "Pando Cueva, Aurea Dajana Makarena",
publisher = "Universidad Privada Antenor Orrego",
year = "2021"
}
At present for educational institutions it has become a problem to know the patterns that influence academic dropout and thus try to reduce this number, becoming a headache for decision makers in educational institutions. That is why it is important to know why students decide to abandon their studies and what are the circumstances that lead to it. The tools that allow creating a data mining model and more the analysis of the information of the student data that were provided by the computer systems of the Leonardo Davinci Higher Institute, has led us to create a data mining model that leads to obtain patterns that influence a dropout student. This model was implemented through the analysis of information: personal, academic, and student interaction. To contribute to the solution to the problem of student dropout, it is proposed to develop a ““Data Mining Model to identify patterns that influence Academic Dropout at the Leonardo Davinci Higher Institute““ with the aim of knowing what the possible causes or patterns are that lead a student to abandon their studies, based on the analysis of the characteristics of student data..
This item is licensed under a Creative Commons License