How to Form Groups in Virtual Learning Environments? A hybrid approach using genetic algorithms and clustering algorithms

Abstract


According to the ”Censo de Educação Superior de 2022”, there was an increase of 189.1% in enrollments in Distance Education between the years 2018 and 2022. In this context, classes can be larger, as there is no physical limitation imposed by a classroom, and the necessary interactions for teaching are facilitated by computing. This work studies another computational facility that can be inserted into the academic context. Therefore, a methodology that combines techniques, WMH K-means and Genetic Algorithms (GA), is proposed to create solutions that seek to optimize relationships among students. The approach was tested with probabilistically generated data and analyzes the hybrid method in relation to an approach solely using GA. The goal is to enable a more efficient and productive learning environment.

Keywords: Groups, Educational Environments, Education

References

Awal, G. K. and Bharadwaj, K. K. (2014). Team formation in social networks based on collective intelligence–an evolutionary approach. Applied intelligence, 41:627–648.

Borges, R., Sahlgrrens, O., Koivunen, S., Stefanidis, K., Olsson, T., and Laitinen, A. (2023). Computational team assembly with fairness constraints.

Cunha, F. O. M. and Siebra, C. D. A. (2017). Mapeamento sistematico na literatura academico-cientifica sobre abordagens para formacao de grupos em e-learning. Revista Brasileira de Informatica na Educacao, 24:16.

Das, G. S., Altinkaynak, B., Gocken, T., and Turker, A. K. (2022). A set partitioning based goal programming model for the team formation problem. International Transactions in Operational Research, 29:301–322.

Esgario, J. G. M., da Silva, I. E., and Krohling, R. A. (2019). Application of genetic algorithms to the multiple team formation problem.

Gutierrez, J. H., Astudillo, C. A., Ballesteros-Perez, P., Mora-Melia, D., and Candia-Vejar, A. (2016). The multiple team formation problem using sociometry. Computers & Operations Research, 75:150–162.

Hout, M. C., Papesh, M. H., and Goldinger, S. D. (2013). Multidimensional scaling. WIREs Cognitive Science, 4:93–103.

Junior, C. B. and Dorca, F. (2018). Uma abordagem para a criacao e recomendacao de objetos de aprendizagem usando um algoritmo genetico, tecnologias da web semantica e uma ontologia. In Brazilian symposium on computers in education (SBIE), page 1533.

Kalantzi, M., Polyzou, A., and Karypis, G. (2022). Fern: Fair team formation for mutually beneficial collaborative learning. IEEE Transactions on Learning Technologies, 15:757–770.

Katoch, S., Chauhan, S. S., and Kumar, V. (2021). A review on genetic algorithm: past, present, and future. Multimedia Tools and Applications, 80:8091–8126.

Lappas, T., Liu, K., and Terzi, E. (2009). Finding a team of experts in social networks. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 467–476.

Miranda, P. B., Mello, R. F., and Nascimento, A. C. (2020). A multi-objective optimization approach for the group formation problem. Expert Systems with Applications, 162:113828.

Pereira, F., Oliveira, E., Fernandes, D., de Carvalho, L. S. G., and Junior, H. (2019). Otimizacao e automacao da predicao precoce do desempenho de alunos que utilizam juizes online: uma abordagem com algoritmo genetico. In Anais do XXX SBIE 2019, page 1451.

Qureshi, M. A., Khaskheli, A., Qureshi, J. A., Raza, S. A., and Yousufi, S. Q. (2023). Factors affecting students’ learning performance through collaborative learning and engagement. Interactive Learning Environments, 31:2371–2391.

Ramos, J. L. C., Santos, L. F. L., Silva, J. C. S., and Rodrigues, R. L. (2020). Identificacao de perfis de interacao de estudantes de Educacao a distancia por meio de tecnicas de agrupamentos. In Anais do XXXI Simposio Brasileiro de Informatica na Educacao, pages 932–941. Sociedade Brasileira de Computacao.

Rubin, P. A. and Bai, L. (2015). Forming competitively balanced teams. IIE Transactions, 47(6):620–633.

Silveira, P. D. N., Carneiro, S., Moreli, J., de Menezes, C. S., and Cury, D. (2022). Smart learning environments em apoio aos ecossistemas de aprendizagem. In Anais SBIE, pages 175–185. Sociedade Brasileira de Computacao - SBC.

Singh, P., Huynh, P. K., Nguyen, D., Le, T., Moreno, W., and Le, T. Q. (2023). Lever multi-criteria integer programming for effective team formation. IEEE transactions on learning technologie (2024).

Singhbaghel, V. and Bhavani, S. D. (2018). Multiple team formation using an evolutionary approach. 2018 11th International Conference on Contemporary Computing, IC3 2018.

Wang, H., Li, J., Song, Y., Huang, J., Li, J., and Chen, Y. (2022). An improved genetic algorithm for team formation problem. Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022, pages 774–781.

Zhang, L. and Zhang, X. (2013). Multi-objective team formation optimization for new product development. Computers & Industrial Engineering, 64(3):804–811.
Published
2024-11-04
ANDRADE, Milnner Kauan T.; SILVA, Vinícius A.; FERREIRA, Hiran Nonato M.. How to Form Groups in Virtual Learning Environments? A hybrid approach using genetic algorithms and clustering algorithms. In: BRAZILIAN SYMPOSIUM ON COMPUTERS IN EDUCATION (SBIE), 35. , 2024, Rio de Janeiro/RJ. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2024 . p. 1971-1983. DOI: https://doi.org/10.5753/sbie.2024.242721.