Técnicas de minería de datos con sotware libre para la detección de factores asociados al rendimiento

  1. Fernando Martínez-Abad 1
  2. Juan Pablo Hernández-Ramos 1
  1. 1 Universitad de Salamanca
Revista:
REXE: Revista de estudios y experiencias en educación

ISSN: 0717-6945,  0718-5162

Año de publicación: 2018

Volumen: 2

Número: 3

Páginas: 135-145

Tipo: Artículo

DOI: 10.21703/REXE.ESPECIAL3_201812514512 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: REXE: Revista de estudios y experiencias en educación

Objetivos de desarrollo sostenible

Resumen

he computational capacities allowed by current computer equipment, coupled with the availability of mass data in all areas, including Education Sciences, demand the development and application of statistical techniques and sotware that help in obtaining meaningful information on these mass data and that facilitate the data transformation into useful knowledge for society. he collection of meaningful information in these data universes and its transformation into useful knowledge for society. Based on a research project under development, this paper presents the potential of the Weka statistical sotware to develop statistical analysis from massive large-scale evaluation databases. In this context, Weka allows researchers to apply techniques of Data Mining, considered within the techniques of the so-called Big Data. hus, this work shows a proposal for the use of Weka sotware in the analysis and detection of nontrivial information between the immensity of the available data. In this way, this study presents to the scientiic community a set of statistical procedures and techniques that can be valuable and replicable in multiple educational and social ields. he conclusions relect on the possibilities of the transference of the knowledge generated to the society in general and to the educational agents in particular.

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