TY - CONF
T1 - An Intelligent System Based on Genetic Algorithms to Generate Study Groups Using Personality Traits and Academic Profiles in Higher Education
AU - Garcia-Velez, R.
AU - Robles-Bykbaev, V.
AU - Lopez-Notes, M.
AU - Calle-Lopez, D.
AU - Barros-Ponton, M.
AU - Galan-Mena, J.
PY - 2018/12/21
Y1 - 2018/12/21
N2 - © 2018 IEEE. The Higher Education Initiative (HEI) promoted by UNESCO and other international institutions, proposes four fundamental postulates related to the sustainable development. From these postulates, one focuses on the cooperation with local and international networks. In the same way, it is important mentioning that in every group, it members are freely interacting individuals who share accepted norms and goals and have a collective identity. For these reasons, during the university training process, it is fundamental that students learn skills to work in groups as well as to address problems in multidisciplinary teams. In the light of the above, in this paper, we present an intelligent system that determines the best alternatives to automatically generate groups of students to address practice activities and problems. Our proposal uses a genetic algorithm to analyze the personality of the students and their academic profiles. The achieved results are encouraging and show a precision of 87% according to an expert team that evaluated the system.
AB - © 2018 IEEE. The Higher Education Initiative (HEI) promoted by UNESCO and other international institutions, proposes four fundamental postulates related to the sustainable development. From these postulates, one focuses on the cooperation with local and international networks. In the same way, it is important mentioning that in every group, it members are freely interacting individuals who share accepted norms and goals and have a collective identity. For these reasons, during the university training process, it is fundamental that students learn skills to work in groups as well as to address problems in multidisciplinary teams. In the light of the above, in this paper, we present an intelligent system that determines the best alternatives to automatically generate groups of students to address practice activities and problems. Our proposal uses a genetic algorithm to analyze the personality of the students and their academic profiles. The achieved results are encouraging and show a precision of 87% according to an expert team that evaluated the system.
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U2 - 10.1109/CONIITI.2018.8587070
DO - 10.1109/CONIITI.2018.8587070
M3 - Paper
T2 - 2018 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2018 - Proceedings
Y2 - 21 December 2018
ER -