Model for predicting academic performance in virtual courses through supervised learning
Since virtual courses are asynchronous and non-presential environments, the following of student tasks can be a hard work. Virtual Education and Learning Environments (VELE) often provide tools for this purpose (Zaharia et al. in Commun ACM 59(11):56-65, 2016, [1]). In Moodle, some plugins take info...
- Autores:
-
Silva, Jesús
Garcia Cervantes, Evereldys
Cabrera, Danelys
García, Silvia
Binda, María Alejandra
Pineda Lezama, Omar Bonerge
Lamby Barrios, Juan Guillermo
Vargas Mercado, Carlos
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7710
- Acceso en línea:
- https://hdl.handle.net/11323/7710
https://doi.org/10.1007/978-981-15-7234-0_92
https://repositorio.cuc.edu.co/
- Palabra clave:
- Virtual education environments
Supervised learning
Moodle
Neural networks
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International