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Procesamiento de bases de datos escolares por medio de redes neuronales artificiales
School database processing from the perspective of artificial neural networks
[journal article]
Abstract El estudio de bases de datos escolares es un área que ha sido poco estudiada y cuestionada desde el punto de vista de la minería de datos o de la inteligencia artificial. Actualmente, existen algunos trabajos que muestran su procesamiento mediante algoritmos de aprendizaje automático o "inteligentes... view more
El estudio de bases de datos escolares es un área que ha sido poco estudiada y cuestionada desde el punto de vista de la minería de datos o de la inteligencia artificial. Actualmente, existen algunos trabajos que muestran su procesamiento mediante algoritmos de aprendizaje automático o "inteligentes"; sin embargo, no se detienen en analizar la pertinencia de procesar datos cualitativos como si fueran cuantitativos. En este artículo se estudia este problema con el uso de tres modelos de red neuronal. Los resultados evidencian la capacidad de estos modelos para clasificar con un porcentaje de acierto superior a 95% las tendencias en los estudiantes utilizando principalmente datos cualitativos.... view less
The analysis of school mentoring databases is a poorly studied area and it is usually questioned from the point of view of data mining or artificial intelligence. Nowadays, there are some works about the processing of such a type of databases through machine learning algorithms, as well as the so ca... view more
The analysis of school mentoring databases is a poorly studied area and it is usually questioned from the point of view of data mining or artificial intelligence. Nowadays, there are some works about the processing of such a type of databases through machine learning algorithms, as well as the so called "smart algorithms". However, the relevance of analyzing and processing qualitative data as if they were quantitative remains still interesting. In this research, the problem of analyzing school mentoring databases by means of three artificial neural network models are thoroughly studied. Results shows the ability of these models to classify the correct trends in students’ statistics using mainly qualitative data with a high degree of certainty (more than 95% of accuracy).... view less
Keywords
data bank; artificial intelligence; data; analysis; school; mentoring; neural network
Classification
Macroanalysis of the Education System, Economics of Education, Educational Policy
Free Keywords
qualitative data
Document language
Spanish
Publication Year
2020
Page/Pages
p. 441-449
Journal
CIENCIA ergo-sum : revista científica multidisciplinaria de la Universidad Autónoma del Estado de México, 27 (2020) 3
DOI
https://doi.org/10.30878/ces.v27n3a11
ISSN
2395-8782
Status
Published Version; peer reviewed
Licence
Creative Commons - Attribution-Noncommercial-No Derivative Works 4.0
With the permission of the rights owner, this publication is under open access due to a (DFG-/German Research Foundation-funded) national or Alliance license.