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An artificial intelligence tool for heterogeneous team formation in the classroom

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An artificial intelligence tool for heterogeneous team formation in the classroom

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dc.contributor.author Alberola Oltra, Juan Miguel es_ES
dc.contributor.author Del Val Noguera, Elena es_ES
dc.contributor.author Sanchez-Anguix, Víctor es_ES
dc.contributor.author Palomares Chust, Alberto es_ES
dc.contributor.author Teruel Serrano, Mª Dolores es_ES
dc.date.accessioned 2016-09-05T14:44:08Z
dc.date.available 2016-09-05T14:44:08Z
dc.date.issued 2016-06-01
dc.identifier.issn 0950-7051
dc.identifier.uri http://hdl.handle.net/10251/68758
dc.description.abstract [EN] Nowadays, there is increasing interest in the development of teamwork skills in the educational context. This growing interest is motivated by its pedagogical effectiveness and the fact that, in labour contexts, enterprises organise their employees in teams to carry out complex projects. Despite its crucial importance in the classroom and industry, there is a lack of support for the team formation process. Not only do many factors influence team performance, but the problem becomes exponentially costly if teams are to be optimised. In this article, we propose a tool whose aim it is to cover such a gap. It combines artificial intelligence techniques such as coalition structure generation, Bayesian learning, and Belbin s role theory to facilitate the generation of working groups in an educational context. This tool improves current state of the art proposals in three ways: i) it takes into account the feedback of other teammates in order to establish the most predominant role of a student instead of self-perception questionnaires; ii) it handles uncertainty with regard to each student s predominant team role; iii) it is iterative since it considers information from several interactions in order to improve the estimation of role assignments. We tested the performance of the proposed tool in an experiment involving students that took part in three different team activities. The experiments suggest that the proposed tool is able to improve different teamwork aspects such as team dynamics and student satisfaction. es_ES
dc.description.sponsorship This work is supported by the following projects: TIN2014-55206-R, TIN2012-36586-C03-01, PROMETEOII/2013/019, TIN2015-65515-C4-1-R, H2020-ICT-2015-688095. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation MICINN/TIN2012-36586-C03-01 es_ES
dc.relation MICINN/TIN2015-65515-C4-1-R es_ES
dc.relation.ispartof Knowledge-Based Systems es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Team formation es_ES
dc.subject Artificial intelligence es_ES
dc.subject Belbin roles es_ES
dc.subject Computational intelligence es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.subject.classification ECONOMIA, SOCIOLOGIA Y POLITICA AGRARIA es_ES
dc.subject.classification BIBLIOTECONOMIA Y DOCUMENTACION es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title An artificial intelligence tool for heterogeneous team formation in the classroom es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.knosys.2016.02.010
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/688095/EU/Large-scale pilots for collaborative OpenCourseWare authoring, multiplatform delivery and Learning Analytics/
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2014-55206-R/ES/PRIVACIDAD EN ENTORNOS SOCIALES EDUCATIVOS DURANTE LA INFANCIA Y LA ADOLESCENCIA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2013%2F019/ES/HUMBACE: HUMAN-LIKE COMPUTATIONAL MODELS FOR AGENT-BASED COMPUTATIONAL ECONOMICS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials es_ES
dc.contributor.affiliation Universitat Politècnica de València. Grupo de Investigación de Tecnología Informática e Inteligencia Artificial es_ES
dc.description.bibliographicCitation Alberola Oltra, JM.; Del Val Noguera, E.; Sanchez-Anguix, V.; Palomares Chust, A.; Teruel Serrano, MD. (2016). An artificial intelligence tool for heterogeneous team formation in the classroom. Knowledge-Based Systems. 101:1-14. https://doi.org/10.1016/j.knosys.2016.02.010 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.knosys.2016.02.010 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 14 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 101 es_ES
dc.relation.senia 309285 es_ES
dc.contributor.funder European Commission
dc.contributor.funder Ministerio de Ciencia e Innovación
dc.contributor.funder Generalitat Valenciana


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