Model for predicting academic performance through artificial intelligence
During the transit of students in the acquisition of competencies that allow them a good future development of their profession, they face the constant challenge of overcoming academic subjects. According to the learning theory, the probability of success of his studies is a multifactorial problem,...
- Autores:
-
Silva, Jesús
Romero, Ligia
solano, darwin
Fernández, Claudia
Pineda, Omar
Rojas, Karina
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_816b
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7291
- Acceso en línea:
- https://hdl.handle.net/11323/7291
https://repositorio.cuc.edu.co/
- Palabra clave:
- Academic performance
Big data
Neural networks
Learning analytics
- Rights
- closedAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
| Summary: | During the transit of students in the acquisition of competencies that allow them a good future development of their profession, they face the constant challenge of overcoming academic subjects. According to the learning theory, the probability of success of his studies is a multifactorial problem, with learning-teaching interaction being a transcendental element (Muñoz-Repiso and Gómez-Pablos in Edutec. Revista Electrónica de Tecnología Educativa 52: a291–a291 (2015), [1]. This research describes a predicative model of academic performance using neural network techniques on a real data set. |
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