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Genetic algorithms as a tool for structuring collaborative groups

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Abstract

Collaborative learning is a process in which two or more individuals interact in order to learn something. The success of the learning process depends on the way in which the individuals are engaged in a community. Within the community, individuals are grouped into small clusters according to their homogeneous properties and the diversity within the group. In this work we focus on the formation of groups of individuals. More specifically, we apply genetic algorithms in the formation process in order to deal with the high level of complexity. We developed a prototype to evaluate the approach and the results are discussed.

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Notes

  1. https://theteamie.com/

  2. http://conformacion.alertate.com

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Acknowledgments

This work is partially supported by the Chilean National Fund for Scientific and Technological Development, FONDECYT, through project number 1140457.

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Authors and Affiliations

  1. Department of Computer Science, University of Concepción, Concepción, Chile

    M. Angélica Pinninghoff J. & Ricardo Contreras A.

  2. Research and Educational Informatics Department, University of Concepción, Concepción, Chile

    Pedro Salcedo L.

  3. School of Natural and Computing Sciences, University of Aberdeen, Aberdeen, UK

    Ricardo Contreras A.

Authors
  1. M. Angélica Pinninghoff J.
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  2. Ricardo Contreras A.
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  3. Pedro Salcedo L.
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  4. Ricardo Contreras A.
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Correspondence to M. Angélica Pinninghoff J..

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Pinninghoff J., M.A., Contreras A., R., Salcedo L., P. et al. Genetic algorithms as a tool for structuring collaborative groups. Nat Comput 16, 231–239 (2017). https://doi.org/10.1007/s11047-016-9574-1

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  • DOI: https://doi.org/10.1007/s11047-016-9574-1

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