Vol.5, No.4, November 2016.                                                                                                              ISSN: 2217-8309

                                                                                                                                                           eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

A Cyclic-genetic-algorithm Approach to Composing Heterogeneous Groups of Students


Anon Sukstrienwong


© 2016 Anon Sukstrienwong, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 5, Issue 4, Pages 467-474, ISSN 2217-8309, DOI: 10.18421/TEM54-09, November 2016.




In this paper, the proposed model is described to demonstrate how to mix students in a heterogonous way and equally balance groups in terms of the educational background and assessment of students. A cyclic genetic algorithm (CGA) is employed in the model to mimic the natural process of evolution to achieve the optimized solution. In order to keep population diversity in the CGA, a particular cycle shift operator and self-crossover operator are presented. The model can be used as a starting point for considering both educational background and peer assessments in the formation of heterogeneous groups of students.


Keywords – Cooperative learning, Cyclic genetic algorithm, Group formation, Heterogeneous groups, Peer assessment.



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