Automating the Generation of Study Teams Through Genetic Algorithms Based on Learning Styles in Higher Education

Roberto García-Vélez, Bryam Vega Moreno, Angel Ruiz-Ichazu, David Andres Morales Rivera , Esteban Rosero-Perez

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Both the International Education Organization (OIE) and UNESCO have stated that promoting collaborative activities is a key competence for sustainable development. This postulate focuses on collaboration with local and international networks. In this line, it is important to mention that, in each teamwork, the members are people who interact sharing objectives, rules and deadlines linked to the activity. Under this reality, it is essential to promote study-team activities in higher education, where students can develop skills to solve problems in multidisciplinary groups. To support the process of generating efficient study-teams, in this investigation we present a system capable of exploring the best alternatives to automatically organize homogeneous study-teams that favor the best performance. Our proposal uses a personalized genetic algorithm (GA), based on student learning styles and academic profile. The experimentation phase has yielded positive results compared to the self-organization method or the teacher imposition method.

Idioma originalInglés
Título de la publicación alojadaAdvances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2020 Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing
EditoresTareq Ahram
EditorialSpringer
Páginas270-277
Número de páginas8
ISBN (versión impresa)9783030513276
DOI
EstadoPublicada - 2021
EventoAHFE Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing, 2020 - San Diego, Estados Unidos
Duración: 16 jul 202020 jul 2020

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1213 AISC
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

ConferenciaAHFE Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing, 2020
País/TerritorioEstados Unidos
CiudadSan Diego
Período16/07/2020/07/20

Nota bibliográfica

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

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