Artificial Neural Network Model to Predict Academic Results in Mathematics II
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Universidad Nacional, Costa Rica
2023
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| Acceso en línea: | https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516 |
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EDUCARE145162023-05-11T15:20:35Z Artificial Neural Network Model to Predict Academic Results in Mathematics II Modelo de red neuronal artificial para predecir resultados académicos en la asignatura Matemática II Modelo de rede neural artificial para prever resultados acadêmicos em Matemática II Incio-Flores, Fernando Alain Capuñay-Sanchez, Dulce Lucero Estela-Urbina, Ronald Omar Red neuronal artificial rendimiento académico predicción Objective. This article shows the design and training of an artificial neural network (ANN) to predict academic results of Civil Engineering students of the Fabiola Salazar Leguía National Intercultural University, from Bagua-Peru, in the subject of Mathematics II. Method. The CRISP-DM methodology was used, surveys were conducted to collect the data, and the RNA model was implemented in the Matlab software using the nnstart command and two learning algorithms: Scaled Conjugate Gradient (SCG) and Levenberg-Marquardt (LM). The performance of the model was evaluated through the mean square error and the correlation coefficient. Conclusions. The LM algorithm achieved better prediction effectiveness. Objetivo. Este artículo muestra el diseño y entrenamiento de una red neuronal artificial (RNA) para predecir resultados académicos de estudiantes de Ingeniería Civil de la Universidad Nacional Intercultural Fabiola Salazar Leguía de Bagua-Perú en la asignatura de Matemática II. Método. Se utilizó la metodología CRISP-DM, para recolectar los datos se emplearon encuestas, el modelo de RNA se implementó en el software Matlab utilizando el comando nnstart y dos algoritmos de aprendizaje: Scaled Conjugate Gradient (SCG) y Levenberg-Marquardt (LM), el rendimiento del modelo se evaluó mediante el error cuadrático medio y el coeficiente de correlación. Conclusiones. El algoritmo LM logró mejor efectividad en la predicción. Objetivo. Este artigo mostra o projeto e o treinamento de uma rede neural artificial (RNA) para predizer resultados acadêmicos de alunos de Engenharia Civil da Universidade Nacional Intercultural Fabiola Salazar Leguía de Bagua-Peru na disciplina de Matemática II. Método. A metodologia CRISP-DM foi utilizada, levantamentos foram utilizados para coletar os dados, o modelo de RNA foi implementado no software Matlab usando o comando nnstart e dois algoritmos de aprendizagem: Scaled Conjugate Gradient (SCG) e Levenberg-Marquardt (LM). O desempenho do modelo foi avaliado por meio do erro quadrático médio e do coeficiente de correlação. Conclusão. O algoritmo LM alcançou melhor eficácia de previsão. Universidad Nacional, Costa Rica 2023-01-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion journal article artículo artigo text/html application/epub+zip application/pdf application/xml audio/mpeg audio/mpeg audio/mpeg https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516 10.15359/ree.27-1.14516 Revista Electrónica Educare; Vol. 27 No. 1 (2023): Revista Electrónica Educare (January-April); 1-19 Revista Electrónica Educare; Vol. 27 Núm. 1 (2023): Revista Electrónica Educare (enero-abril); 1-19 Revista Electrónica Educare; v. 27 n. 1 (2023): Revista Electrónica Educare (janeiro-abril); 1-19 1409-4258 spa eng por https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516/27050 https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516/27051 https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516/27052 https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516/28366 https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516/27053 https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516/27054 https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516/27055 Copyright (c) 2022 Shared by Journal and Authors |
| institution |
Universidad Nacional de Costa Rica |
| collection |
Revista Electrónica Educare |
| language |
spa eng por |
| format |
Online |
| author |
Incio-Flores, Fernando Alain Capuñay-Sanchez, Dulce Lucero Estela-Urbina, Ronald Omar |
| spellingShingle |
Incio-Flores, Fernando Alain Capuñay-Sanchez, Dulce Lucero Estela-Urbina, Ronald Omar Artificial Neural Network Model to Predict Academic Results in Mathematics II |
| author_facet |
Incio-Flores, Fernando Alain Capuñay-Sanchez, Dulce Lucero Estela-Urbina, Ronald Omar |
| author_sort |
Incio-Flores, Fernando Alain |
| title |
Artificial Neural Network Model to Predict Academic Results in Mathematics II |
| title_short |
Artificial Neural Network Model to Predict Academic Results in Mathematics II |
| title_full |
Artificial Neural Network Model to Predict Academic Results in Mathematics II |
| title_fullStr |
Artificial Neural Network Model to Predict Academic Results in Mathematics II |
| title_full_unstemmed |
Artificial Neural Network Model to Predict Academic Results in Mathematics II |
| title_sort |
artificial neural network model to predict academic results in mathematics ii |
| title_alt |
Modelo de red neuronal artificial para predecir resultados académicos en la asignatura Matemática II Modelo de rede neural artificial para prever resultados acadêmicos em Matemática II |
| publisher |
Universidad Nacional, Costa Rica |
| publishDate |
2023 |
| url |
https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516 |
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