JUCS - Journal of Universal Computer Science 25(10): 1301-1322, doi: 10.3217/jucs-025-10-1301

Decision-making Model at Higher Educational Institutions based on Machine Learning

Yuri Vanessa Nieto^‡, Vicente García-Díaz^‡, Carlos Enrique Montenegro^§

‡ University of Oviedo, Oviedo, Spain§ District University Francisco José de Caldas, Bogotá, Colombia

Corresponding author: Yuri Nieto ( uo250052@uniovi.es )

This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-ND 4.0). This license allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.

Citation: Nieto YV, García-Díaz V, Montenegro CE (2019) Decision-making Model at Higher Educational Institutions based on Machine Learning. JUCS - Journal of Universal Computer Science 25(10): 1301-1322. https://doi.org/10.3217/jucs-025-10-1301

Abstract

At Higher Educational Institutions (HEI) the high hierarchical managers and directors face many challenges during the decision-making process, that sometimes are rely on intuition, and past experiences, leading not just to delays but the low impact in the whole academic community. A decision-making model for managers and administrator of HEIs is presented. We propose a detailed methodology when academic prognosis is taking place. The comparison between five robust Machine Learning algorithms is executed accomplishing outperformed results by Support Vector Machine. As a validation experiment, we executed the proposed decision model in a face-to-face public university in Colombia, showing the results in a developed web platform prototype with its correspondent architecture. Moreover, we discuss the social implication of low graduation rates.

Keywords

decision support system, decision-making, machine learning, support vector machine, classification algorithms