The Use of Personality Traits to Enhance Theory-driven Group Formation

Authors

  • Rachel Carlos Duque Reis Universidade Federal de Viçosa
  • Kamila Takayama Lyra Universidade de São Paulo
  • Clausius Duque Gonçalves Reis Universidade Federal de Viçosa
  • Bruno Elias Penteado Universidade de São Paulo
  • Seiji Isotani Universidade de São Paulo

DOI:

https://doi.org/10.5753/rbie.2020.28.0.796

Keywords:

CSCL, Group Formation, Algorithm, Personality Trait, Learning Theory

Abstract

Group formation is an important and challenging element for designing successful CSCL scenarios. Despite efforts from the scientific community in developing more effective algorithms to support group formation processes, we still face problems related to learners’ resistance and demotivation towards group work. In this sense, diverse studies highlight the importance of considering learners’ personality traits to form groups, since this factor can influence students’ performance and induce diverse actions and behaviors in group work. Therefore, this paper presents G-FusionPT (Group Formation USIng Ontology and Personality Trait), a group formation algorithm that support new learning roles, denominated Affective Collaborative Learning roles, based on relation between collaborative learning theories and students’ personality traits. The algorithm is based on a collaborative ontology to understand the learning theories (e.g., context, learning activities, group structure), and learners profile to understand learners’ needs (e.g., target/current knowledge/skill). To evaluate the algorithm, we used a 300 student simulated sample with varying group size (three, five, and seven members), and compared G-FusionPT results to other group formation algorithms: G-Fusion (based specifically on collaborative learning theories) and Random (no strategy or criterion). The results demonstrated the effectiveness of G-FusionPT against G-Fusion and Random algorithms, as it generated the highest average percentage of learners in well-formed groups and lowest average percentage of learners in unfit groups.

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Published

2020-10-18

Cómo citar

REIS, R. C. D.; LYRA, K. T.; REIS, C. D. G.; PENTEADO, B. E.; ISOTANI, S. The Use of Personality Traits to Enhance Theory-driven Group Formation. Revista Brasileña de Informática en la Educación, [S. l.], v. 28, p. 796–818, 2020. DOI: 10.5753/rbie.2020.28.0.796. Disponível em: https://journals-sol.sbc.org.br/index.php/rbie/article/view/3962. Acesso em: 24 nov. 2024.

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