Rules for forming collaborative groups using automatic detection of personality traits
Group formation is a crucial aspect of collaborative learning. Due to lack of interaction among students, this task becomes complex, and tools that determine groups for collaborative work are needed. Proposals for detecting personality traits and forming groups, based on the Big Five model, were dev...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2020 |
| País: | Brasil |
| Institución: | Sociedade Brasileira de Computação (SBC) |
| Repositorio: | Revista Brasileira de Informática na Educação |
| Idioma: | portugués |
| OAI Identifier: | oai:journals-sol.sbc.org.br:article/3939 |
| Acceso en línea: | https://journals-sol.sbc.org.br/index.php/rbie/article/view/3939 |
| Access Level: | acceso abierto |
| Palabra clave: | Modelo Big Five traços de personalidade formação de grupo aprendizagem colaborativa Big Five Model personality traits group formation collaborative learning |
| Sumario: | Group formation is a crucial aspect of collaborative learning. Due to lack of interaction among students, this task becomes complex, and tools that determine groups for collaborative work are needed. Proposals for detecting personality traits and forming groups, based on the Big Five model, were developed. However, these works do not present rules for group formation. Thus, this work verifies the feasibility of automatically detecting personality traits through written texts and demonstrates the influence of these traits on group formation, identifying a set of rules for this purpose. In addition, this article is a joint effort of two research groups to identify suitable algorithms for detecting personality traits from texts. The grouping rules were extracted from the database of the groups built in order to help in the formation of new groups. Therefore, the contributions of this research were tools for automatic detection of personality traits from texts, identification of learning algorithms more suitable for classification of traits, database of groups and a set of rules based on traits and other parameters. |
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