Articles producció científica> Pedagogia

Minimum entropy collaborative groupings: A tool for an automatic heterogeneous learning group formation

  • Datos identificativos

    Identificador: imarina:9293919
    Autores:
    Vallès-Català, TPalau, R
    Resumen:
    For some decades now, theories on learning methodologies have advocated collaborative learning due to its good results in terms of effectiveness and learning types and its promotion of educational and social values. This means that teachers need to be able to apply different criteria when forming heterogeneous groups of students and to use automated techniques to assist them. In this study, we have created an approach based on complex network theory to design an algorithm called Minimum Entropy Collaborative Groupings (MECG) in order to form these heterogeneous groups more effectively. The algorithm was tested firstly under a synthetic framework and secondly in a real situation. In the first case, we generated 30 synthetic classrooms of different sizes and compared our approach with a genetic algorithm and a random grouping. In the latter case, the approach was tested on a group of 200 students on two subjects of a master's degree in teacher training. For each subject there were 4 large groups of 50 students each, in which collaborative groups of 4 students were created. Two of these large groups were used as random groups, another group used the CHAEA test and the fourth group used the LML test. The results showed that the groups created with MECG were more effective, had less uncertainty and were more interrelated and mature. It was observed that the randomized groups did not obtain significantly better LML results and that this cannot be related to any emotional or motivational effect because the students performed the test as a placebo measure. In terms of learning styles, the results were significantly better with LML than with CHAEA, whereas no significant difference was observed in the randomized groups.Copyright: © 2023 Vallès-Català, Palau. This is an open acce
  • Otros:

    Autor según el artículo: Vallès-Català, T; Palau, R
    Departamento: Pedagogia
    Autor/es de la URV: Palau Martin, Ramon Felix
    Palabras clave: Performance prediction teams system networks
    Resumen: For some decades now, theories on learning methodologies have advocated collaborative learning due to its good results in terms of effectiveness and learning types and its promotion of educational and social values. This means that teachers need to be able to apply different criteria when forming heterogeneous groups of students and to use automated techniques to assist them. In this study, we have created an approach based on complex network theory to design an algorithm called Minimum Entropy Collaborative Groupings (MECG) in order to form these heterogeneous groups more effectively. The algorithm was tested firstly under a synthetic framework and secondly in a real situation. In the first case, we generated 30 synthetic classrooms of different sizes and compared our approach with a genetic algorithm and a random grouping. In the latter case, the approach was tested on a group of 200 students on two subjects of a master's degree in teacher training. For each subject there were 4 large groups of 50 students each, in which collaborative groups of 4 students were created. Two of these large groups were used as random groups, another group used the CHAEA test and the fourth group used the LML test. The results showed that the groups created with MECG were more effective, had less uncertainty and were more interrelated and mature. It was observed that the randomized groups did not obtain significantly better LML results and that this cannot be related to any emotional or motivational effect because the students performed the test as a placebo measure. In terms of learning styles, the results were significantly better with LML than with CHAEA, whereas no significant difference was observed in the randomized groups.Copyright: © 2023 Vallès-Català, Palau. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
    Áreas temáticas: Zootecnia / recursos pesqueiros Sociology Sociología Serviço social Saúde coletiva Química Psychology Psicología Planejamento urbano e regional / demografia Odontología Nutrição Multidisciplinary sciences Multidisciplinary Medicine (miscellaneous) Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Linguística e literatura Letras / linguística Interdisciplinary research in the social sciences Interdisciplinar Human geography and urban studies History & philosophy of science Historia Geografía Geociências General medicine General biochemistry,genetics and molecular biology General agricultural and biological sciences Farmacia Environmental studies Ensino Engenharias iv Engenharias iii Engenharias ii Engenharias i Enfermagem Educação física Educação Economia Direito Demography Comunicação e informação Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência política e relações internacionais Ciência de alimentos Ciência da computação Biotecnología Biology Biodiversidade Biochemistry, genetics and molecular biology (miscellaneous) Astronomia / física Arquitetura, urbanismo e design Archaeology Antropologia / arqueologia Anthropology Agricultural and biological sciences (miscellaneous) Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: ramon.palau@urv.cat
    Identificador del autor: 0000-0002-9843-3116
    Fecha de alta del registro: 2024-08-03
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0280604
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Plos One. 18 (3): e0280604-e0280604
    Referencia de l'ítem segons les normes APA: Vallès-Català, T; Palau, R (2023). Minimum entropy collaborative groupings: A tool for an automatic heterogeneous learning group formation. Plos One, 18(3), e0280604-e0280604. DOI: 10.1371/journal.pone.0280604
    DOI del artículo: 10.1371/journal.pone.0280604
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2023
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Agricultural and Biological Sciences (Miscellaneous),Biochemistry, Genetics and Molecular Biology (Miscellaneous),Biology,Medicine (Miscellaneous),Multidisciplinary,Multidisciplinary Sciences
    Performance prediction
    teams
    system
    networks
    Zootecnia / recursos pesqueiros
    Sociology
    Sociología
    Serviço social
    Saúde coletiva
    Química
    Psychology
    Psicología
    Planejamento urbano e regional / demografia
    Odontología
    Nutrição
    Multidisciplinary sciences
    Multidisciplinary
    Medicine (miscellaneous)
    Medicina veterinaria
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Linguística e literatura
    Letras / linguística
    Interdisciplinary research in the social sciences
    Interdisciplinar
    Human geography and urban studies
    History & philosophy of science
    Historia
    Geografía
    Geociências
    General medicine
    General biochemistry,genetics and molecular biology
    General agricultural and biological sciences
    Farmacia
    Environmental studies
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Enfermagem
    Educação física
    Educação
    Economia
    Direito
    Demography
    Comunicação e informação
    Ciências sociais aplicadas i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência política e relações internacionais
    Ciência de alimentos
    Ciência da computação
    Biotecnología
    Biology
    Biodiversidade
    Biochemistry, genetics and molecular biology (miscellaneous)
    Astronomia / física
    Arquitetura, urbanismo e design
    Archaeology
    Antropologia / arqueologia
    Anthropology
    Agricultural and biological sciences (miscellaneous)
    Administração, ciências contábeis e turismo
    Administração pública e de empresas, ciências contábeis e turismo
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