Bayesian networks for detection of teams roles in learning collaborative supported by computers

Authors

  • José Balmaceda Universidad Nacional del Centro de la Pcia
  • Silvia Schiaffino Universidad Nacional del Centro de la Pcia
  • Daniela Godoy Universidad Nacional del Centro de la Pcia

DOI:

https://doi.org/10.25044/25392190.476

Keywords:

team roles, computer supported collaborative learning, Bayesian networks.

Abstract

Computer-supported collaborative learning allows students who are in different places to work together in the same virtual space, and supports the communication of ideas and information among learners. However, as not all students are identical, it is important to study users' characteristics to build more productive teams. Team Roles Theory allows obtaining very good team performance taking into account individual skills, combining the weaknesses of each role with the strengths of others. Originally, people have to complete extensive questionnaires to determine their team role. In this work we propose an alternative method to make this detection through a collaborative learning system and by using a Bayesian Network.

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Author Biographies

José Balmaceda, Universidad Nacional del Centro de la Pcia

Facultad de Ciencias Exactas, Universidad Nacional del Centro de la Pcia. de Bs. As., Campus Universitario, Paraje Arroyo Seco, Tandil, Argentina.

Silvia Schiaffino, Universidad Nacional del Centro de la Pcia

Instituto de Investigación SISTAN (CONICET – UNCPBA), Campus Universitario, Paraje Arroyo Seco, Tandil, Argentina|

Daniela Godoy, Universidad Nacional del Centro de la Pcia

Instituto de Investigación SISTAN (CONICET – UNCPBA), Campus Universitario, Paraje Arroyo Seco, Tandil, Argentina.

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Published

2015-07-30

How to Cite

Balmaceda, J., Schiaffino, S., & Godoy, D. (2015). Bayesian networks for detection of teams roles in learning collaborative supported by computers. Teknos Revista científica, 15(1), 43–51. https://doi.org/10.25044/25392190.476

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