A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students

Autores
Yannibelli, Virginia Daniela; Armentano, Marcelo Gabriel; Berdun, Franco Daniel; Amandi, Analia Adriana
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Collaborative learning team building is a fundamental, difficult and time-consuming task in educational environments. In this paper, we address a collaborative learning team building problem that considers two valuable grouping criteria usually considered by teachers. One of these criteria considers the understanding levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the understanding levels of their members. The other criterion considers the interest levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the interest levels of their members. The problem addressed has been recognised as an NP-Hard optimization problem. To solve the problem, we propose a steady-state evolutionary algorithm. This algorithm aims to organize the students taking a given course into teams in such a way that the two grouping criteria of the problem are optimized. The performance of the algorithm is evaluated on nine problem instances with different levels of complexity, and is compared with that of the only algorithm previously proposed for solving the addressed problem. The obtained results show that the steady-state evolutionary algorithm significantly outperforms the previous algorithm.
Fil: Yannibelli, Virginia Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Armentano, Marcelo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Berdun, Franco Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Materia
COLLABORATIVE LEARNING
COLLABORATIVE LEARNING TEAM BUILDING
EVOLUTIONARY ALGORITHMS
STEADY-STATE EVOLUTIONARY ALGORITHMS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/58497
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the StudentsYannibelli, Virginia DanielaArmentano, Marcelo GabrielBerdun, Franco DanielAmandi, Analia AdrianaCOLLABORATIVE LEARNINGCOLLABORATIVE LEARNING TEAM BUILDINGEVOLUTIONARY ALGORITHMSSTEADY-STATE EVOLUTIONARY ALGORITHMShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Collaborative learning team building is a fundamental, difficult and time-consuming task in educational environments. In this paper, we address a collaborative learning team building problem that considers two valuable grouping criteria usually considered by teachers. One of these criteria considers the understanding levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the understanding levels of their members. The other criterion considers the interest levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the interest levels of their members. The problem addressed has been recognised as an NP-Hard optimization problem. To solve the problem, we propose a steady-state evolutionary algorithm. This algorithm aims to organize the students taking a given course into teams in such a way that the two grouping criteria of the problem are optimized. The performance of the algorithm is evaluated on nine problem instances with different levels of complexity, and is compared with that of the only algorithm previously proposed for solving the addressed problem. The obtained results show that the steady-state evolutionary algorithm significantly outperforms the previous algorithm.Fil: Yannibelli, Virginia Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Armentano, Marcelo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Berdun, Franco Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaGraz University of Technology2016-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/58497Yannibelli, Virginia Daniela; Armentano, Marcelo Gabriel; Berdun, Franco Daniel; Amandi, Analia Adriana; A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students; Graz University of Technology; Journal of Universal Computer Science; 22; 10; 10-2016; 1298-13180948-695X0948-6968CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3217/jucs-022-10-1298info:eu-repo/semantics/altIdentifier/url/http://www.jucs.org/doi?doi=10.3217/jucs-022-10-1298info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:13:34Zoai:ri.conicet.gov.ar:11336/58497instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:13:35.132CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students
title A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students
spellingShingle A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students
Yannibelli, Virginia Daniela
COLLABORATIVE LEARNING
COLLABORATIVE LEARNING TEAM BUILDING
EVOLUTIONARY ALGORITHMS
STEADY-STATE EVOLUTIONARY ALGORITHMS
title_short A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students
title_full A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students
title_fullStr A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students
title_full_unstemmed A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students
title_sort A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students
dc.creator.none.fl_str_mv Yannibelli, Virginia Daniela
Armentano, Marcelo Gabriel
Berdun, Franco Daniel
Amandi, Analia Adriana
author Yannibelli, Virginia Daniela
author_facet Yannibelli, Virginia Daniela
Armentano, Marcelo Gabriel
Berdun, Franco Daniel
Amandi, Analia Adriana
author_role author
author2 Armentano, Marcelo Gabriel
Berdun, Franco Daniel
Amandi, Analia Adriana
author2_role author
author
author
dc.subject.none.fl_str_mv COLLABORATIVE LEARNING
COLLABORATIVE LEARNING TEAM BUILDING
EVOLUTIONARY ALGORITHMS
STEADY-STATE EVOLUTIONARY ALGORITHMS
topic COLLABORATIVE LEARNING
COLLABORATIVE LEARNING TEAM BUILDING
EVOLUTIONARY ALGORITHMS
STEADY-STATE EVOLUTIONARY ALGORITHMS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Collaborative learning team building is a fundamental, difficult and time-consuming task in educational environments. In this paper, we address a collaborative learning team building problem that considers two valuable grouping criteria usually considered by teachers. One of these criteria considers the understanding levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the understanding levels of their members. The other criterion considers the interest levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the interest levels of their members. The problem addressed has been recognised as an NP-Hard optimization problem. To solve the problem, we propose a steady-state evolutionary algorithm. This algorithm aims to organize the students taking a given course into teams in such a way that the two grouping criteria of the problem are optimized. The performance of the algorithm is evaluated on nine problem instances with different levels of complexity, and is compared with that of the only algorithm previously proposed for solving the addressed problem. The obtained results show that the steady-state evolutionary algorithm significantly outperforms the previous algorithm.
Fil: Yannibelli, Virginia Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Armentano, Marcelo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Berdun, Franco Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
description Collaborative learning team building is a fundamental, difficult and time-consuming task in educational environments. In this paper, we address a collaborative learning team building problem that considers two valuable grouping criteria usually considered by teachers. One of these criteria considers the understanding levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the understanding levels of their members. The other criterion considers the interest levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the interest levels of their members. The problem addressed has been recognised as an NP-Hard optimization problem. To solve the problem, we propose a steady-state evolutionary algorithm. This algorithm aims to organize the students taking a given course into teams in such a way that the two grouping criteria of the problem are optimized. The performance of the algorithm is evaluated on nine problem instances with different levels of complexity, and is compared with that of the only algorithm previously proposed for solving the addressed problem. The obtained results show that the steady-state evolutionary algorithm significantly outperforms the previous algorithm.
publishDate 2016
dc.date.none.fl_str_mv 2016-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/58497
Yannibelli, Virginia Daniela; Armentano, Marcelo Gabriel; Berdun, Franco Daniel; Amandi, Analia Adriana; A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students; Graz University of Technology; Journal of Universal Computer Science; 22; 10; 10-2016; 1298-1318
0948-695X
0948-6968
CONICET Digital
CONICET
url http://hdl.handle.net/11336/58497
identifier_str_mv Yannibelli, Virginia Daniela; Armentano, Marcelo Gabriel; Berdun, Franco Daniel; Amandi, Analia Adriana; A Steady-state Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students; Graz University of Technology; Journal of Universal Computer Science; 22; 10; 10-2016; 1298-1318
0948-695X
0948-6968
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3217/jucs-022-10-1298
info:eu-repo/semantics/altIdentifier/url/http://www.jucs.org/doi?doi=10.3217/jucs-022-10-1298
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Graz University of Technology
publisher.none.fl_str_mv Graz University of Technology
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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