Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/87212

TítuloForming suitable groups in MCSCL environments
Autor(es)Amara, Sofiane
Bendella, Fatima
Macedo, Joaquim
Santos, Alexandre
Palavras-chaveCollaborative learning
Group formation
Grouping algorithms
MCSCL
Mobile learning
Data1-Jan-2021
EditoraIGI Global
RevistaInternational Journal of Information and Communication Technology Education
Resumo(s)Given the peculiarities of mobile computer-supported collaborative learning (MCSCL) environments, forming suitable groups in such learning environments represents a hard and time-consuming task. This is because many conditions related to mobile learners, devices, and environment should be considered. Unlike the existing solutions, the present paper shows a grouping approach that allows a customizable formation of (1) homogeneous groups, (2) heterogeneous groups, and (3) mixed groups. The proposed solution does not only help instructors to dynamically form appropriate MCSCL groups, but it also allows to continually control the learners' learning, psychological, and social developments. To assess the effectiveness of the proposed solution, three metrics were used: (1) comparison between the characteristics of the existing group formation tools, (2) average intra-cluster distance of each grouping algorithm, and (3) an experimental evaluation in a real world environment. The obtained results show a great superiority of the proposed solution compared to the existing ones.
TipoArtigo
URIhttps://hdl.handle.net/1822/87212
DOI10.4018/IJICTE.2021010103
ISSN1550-1876
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals

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