Abstract
An element of great importance for university educational institutions, educators and students is the academic performance of them in the transition of their professional training. The mining of educational data develops models and methods to explore the data collected from the educational learning environments through learning analytics in order to detect patterns that allow predicting variables of interest. The present research describes a predictive model of academic performance using neural network techniques on a set of real data of 300 students of the Systems career of the Central University of Ecuador. This registration was provided by the virtual learning environment https://uvirtual.uce.edu.ec/developed in Moodle and used in said University.
| Translated title of the contribution | Model to predict academic performance based on neural networks and learning analytics |
|---|---|
| Original language | Spanish (Ecuador) |
| Pages (from-to) | 258-266 |
| Number of pages | 9 |
| Journal | RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao |
| Issue number | E17 |
| State | Published - 1 Jan 2019 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2019, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.
Funding
Dado la problemática, los resultados predictivos del modelo sirven a la Universidad para evitar casos de deserción de estudiantes, porque en general, la eficiencia y efectividad del sistema educativo en formar profesionales está actualmente poco trabajada por las universidades, y organizaciones gubernamentales competentes, lo que genera efectos negativos importantes para el país, sobre todo si se considera que el gobierno proyecta una fuerte inyección de inversión por la reforma educacional y la intención de utilizar este indicador como parte de las acreditaciones de las instituciones educativas a nivel superior.
| Funders |
|---|
| Universidade Paranaense |
