Neural Networks to Predict Schooling Failure/Success

Pinninghoff, M.; Salcedo, P.; CONTRERAS, R.

Keywords: prediction, neural networks, schooling performance

Abstract

This paper depicts an already developed experience in search for a predictable mechanism with respect to the future performance of a student considering the numerous factors that influence in its failure/success. The use of different neural networks configurations in conjunction with a large data volume on top of detailed attributes consideration for each student makes for an adequate base for the results obtained to be analyzed. The idea behind this paper is to arrange a mechanism that allows us to estimate before hand taking into consideration data from the student in reference to family, social and wealth surroundings for the student future performance identifying those factors that favors the tendency to failure or success.

Más información

Título de la Revista: BIO-INSPIRED SYSTEMS AND APPLICATIONS: FROM ROBOTICS TO AMBIENT INTELLIGENCE, PT II
Volumen: 4528
Editorial: SPRINGER INTERNATIONAL PUBLISHING AG
Fecha de publicación: 2007
Página de inicio: 571
Página final: 579
Idioma: English
Notas: SCOPUS