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RISTI - Revista Ibérica de Sistemas e Tecnologias de Informação

versão impressa ISSN 1646-9895

Resumo

CARRASCAL, Ana Isabel Oviedo  e  JIMENEZ, Gabriel Almendrales. Study on Learning Styles by Data Mining as support for Academic Management in Educational Institutions. RISTI [online]. 2018, n.29, pp.1-13. ISSN 1646-9895.  http://dx.doi.org/10.17013/risti.29.1-13.

Learning styles are the strategies used by a student to acquire knowledge, their analysis allows educational institutions to improve learning environments, which commonly depend on biological, psychological, environmental, school and community conditions. This paper presents a study on learning styles applying data mining techniques to the information derived from the application of two tests called VARK and CHAEA to the students of the Educational Institution “Joaquín Cárdenas Gómez” of the Municipality of San Carlos - Antioquia (Colombia). This work formulates a plan of support for the Management Directive with the list of factors that influence learning. The findings indicate that learning styles alone do not influence school failure, require the combination of other elements such as age and have more than one learning style.

Palavras-chave : Learning styles; Data mining; educational analytic.

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