Abstract

MENDOZA JURADO, Helmer Fellman. Data Science an alternative analysis to the pedagogical growth of the student in higher education. Edu. Sup. Rev. Cient. Cepies [online]. 2018, vol.5, n.2, pp.35-46. ISSN 2518-8283.

Abstract This research work intends to present concepts, a newworking model and results generation supported by a scientific method being oriented specifically in the educational and pedagogical area of an institution in higher education. Even though we have always generated and analyzed big volumes of information about each student and their level of progress within the Teaching-Learning Process, the Internet and other new technologies have created different data sources, new ways of processing, analysis and metrics presentation which were very difficult to extract and understand, without the capacity of automation and abstraction that due to inertia gives the Data Science, a component currently entered to the New Technologies of the information and communication, projecting that this volume of information will be duplicated in 2020 and this will increase progressively as we move forward in time, thus the need to give a new approach to the traditional metrics will increase, but in turn it will help in the analysis of new socio-emotional factors o the student, which will help to keep us up-to-date with this new challenge in the age of knowledge.

Keywords : Data Science; Teaching-Learning Process; Educational Data Mining.

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