Predicting student drop-out rates using data mining techniques: A case study

The prevention of students dropping out is considered very important in many educational institutions. In this paper we describe the results of an educational data analytics case study focused on detection of dropout of Systems Engineering (SE) undergraduate students after 6 years of enrollment in a...

Full description

Autores:

PEREZ GUTIERREZ, BORIS RAINIERO
Castellanos, Camilo
Correal, Dario

Tipo de recurso:

Article of journal

Fecha de publicación:

2018

Institución:

Universidad Francisco de Paula Santander

Repositorio:

Repositorio Digital UFPS

Idioma:

eng

OAI Identifier:

oai:repositorio.ufps.edu.co:ufps/1650

Acceso en línea:

http://repositorio.ufps.edu.co/handle/ufps/1650
https://doi.org/10.1007/978-3-030-03023-0_10

Palabra clave:

Student drop out
Student desertion prediction
Educational data mining
Prediction models

Rights

openAccess

License

© Springer Nature Switzerland AG 2018