Mapping the behavioral profiles of students in a brazilian MOOC

Authors

DOI:

https://doi.org/10.15536/reducarmais.10.2026.4334

Keywords:

MOOCs, Profile Mapping, Behavioral Profil, K-means

Abstract

Although the peak of MOOC courses was the year 2012, many Educational Institutions are still betting on this educational format, for the dissemination of specialized knowledge at affordable costs, even more so in times when remote teaching has become so important. In this sense, research indicates that in 2018 more than 11 thousand MOOCs were offered in 900 universities, highlighting that there is a great demand for this educational model. However, many questions are still open about MOOCs, such as low engagement and high dropout rates (around 90%). Such factors encourage research in order to customize the environments and contents of MOOCs, for this purpose mapping the profiles of students who take these courses is a significant task. In this context, this study aims to map the profiles of students of a MOOC in the area of chemistry on a Brazilian platform, focusing on the objectives of these students when they take a course in this format. To carry out the mapping, the K-means Clustering algorithm was used and 4 predominant behavioral profiles were identified: Engaged, Strategic, Inactive and Scammers. With the results presented by this study, strategies can be developed to improve the MOOCs offered by the platform, based on knowledge of student profiles, with actions to inhibit bad behavior and encourage desirable behavior.

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Author Biography

Vanessa Faria de Souza, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul- IFRS

Doutora pelo Programa de Pós-Graduação em Informática na Educação (PPGIE) da Universidade Federal do Rio Grande do Sul (UFRGS). Mestre em Informática pelo Programa de Pós-Graduação em Informática (PPGI) da Universidade Tecnológica Federal do Paraná (UTFPR), na área de Computação Aplicada, e com ênfase em Engenharia de Software. Possui Especialização em Educação Especial Inclusiva, com ênfase em Tecnologias Assistivas pela Universidade Estadual do Norte do Paraná (UENP). É graduada em Sistemas de Informação também pela UENP - Bacharel em Sistemas de Informação e Licenciada em Computação. Também Completou a Licenciatura em Matemática no Programa de Formação Pedagógica, pela UTFPR. Atualmente é docente dedicação exclusiva no Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS) no Campus Ibirubá. Ministra aulas nos Cursos de Ciência da Computação, Técnico em Informática Integrado do Ensino Médio, Licenciatura em Matemática e Especialização em Ensino de Linguagens e suas Tecnologias. É membro do Grupo de Pesquisa Computação Interdisciplinar Alto Jacuí. Tem interesse nas áreas de Mineração de Dados Educacionais, Learning Analytics, Inteligência Artificial - Machine Learning e Deep Leaning, Sistemas Digitais e Robótica Educacional.

References

ALRAIMI, K. M.; ZO, H.; CIGANEK, A. P. Understanding the MOOCs continuance: The role of openness and reputation. Computers & Education, v. 80, p. 28-38, 2015. Disponível em: https://doi.org/10.1016/j.compedu.2014.08.006

FELDER, Richard; SILVERMAN, Linda. Learning and Teaching Styles in Engineering Education. Engineering Education, [S. l.], v. 78, n. 7, p. 674–681, 1988.

FERREIRA-SATLER, Mateus et al. Fuzzy ontologies-based user profiles applied to enhance e-learning activities. Soft Computing, [S. l.], v. 16, n. 7, p. 1129–1141, 2012. Disponível em: https://doi.org/10.1007/s00500-011-0788-y

FERREIRA, Hiran Nonato M. et al. An automatic and dynamic student modeling approach for adaptive and intelligent educational systems using ontologies and Bayesian networks. In: 2017, Proceedings - 2016 IEEE 28th International Conference on Tools with Artificial Intelligence, ICTAI 2016. [S. l.: s. n.] p. 738–745. Disponível em: https://doi.org/10.1109/ICTAI.2016.0113

FINNEY, Sara J. et al. Exploring profiles of academic help seeking: A mixture modeling approach. Learning and Individual Differences, [S. l.], v. 61, n. February 2017, p. 158–171, 2018. Disponível em: https://doi.org/10.1016/j.lindif.2017.11.011

HAMIM, Touria; BENABBOU, Faouzia; SAEL, Nawal. Student profile modeling: An overview model. In: 2019, ACM International Conference Proceeding Series. [S. l.: s. n.] p. 1–9. Disponível em: https://doi.org/10.1145/3368756.3369075

HARTIGAN, J. A; WONG, M. A. (1979). Algorithm AS 136: A K-means clustering algorithm. Applied Statistics, v. 28, p. 100–108. Disponível em: https://doi.org/10.2307/2346830

KOLB, D. .. Experiential Learning: Experience as the Source of Learning and Development. New Jersey: Englewood Cliffs, 1984. E-book.

KORCHI, Adil; ABDELLAH, Mohamed Ben; FEZ, Morocco. A modeling learner approach in a computing environment for human learning based on ontology. International Journal of Computer Engineering & Technology International Journal of Computer Engineering and Technology, [S. l.], v. 6, n. 69, p. 21–31, 2015.

MARECA, Pilar; BORDEL, Borja. Students Profiles and their Behavior in MOOC Platforms, MIRIADAX Platform. In: 2019, Coimbra, Portugal. 14th Iberian Conference on Information Systems and Technologies (CISTI). Coimbra, Portugal: [s. n.], 2019. p. 1–6. Disponível em: https://doi.org/10.23919/CISTI.2019.8760696

MUMFORD, A. Honey P. The Manual of Learning Styles. [S. l.]: Maidenhead, 1982. E-book.

REZGUI, Kalthoum; MHIRI, Hédia; GHÉDIRA, Khaled. Ontology-based e-Portfolio modeling for supporting lifelong competency assessment and development. Procedia Computer Science, [S. l.], v. 112, p. 397–406, 2017. Disponível em: https://doi.org/10.1016/j.procs.2017.08.041

RODRIGUES, Rodrigo Lins et al. Discovery engagement patterns MOOCs through cluster analysis. IEEE Latin America Transactions, [S. l.], v. 14, n. 9, p. 4129–4135, 2016. Disponível em: https://doi.org/10.1109/TLA.2016.7785943

SHAH, D. By the Numbers: MOOCS in 2018 Class Central (2018). Disponível em: <https://www.classcentral.com/report/mooc-stats-2018/>. Acesso em: 01 out. 2020.

SHI, Yuling; PENG, Zhiyong; WANG, Hongning. Modeling student learning styles in MOOCs. In: 2017, Singapura. International Conference on Information and Knowledge Management. Singapura: [s. n.], 2017. p. 979–988. Disponível em: https://doi.org/10.1145/3132847.3132965

SNYMAN, Marici; VAN DEN BERG, Geesje. The Significance of the Learner Profile in Recognition of Prior Learning. Adult Education Quarterly, [S. l.], v. 68, n. 1, p. 1–16, 2018. Disponível em: https://doi.org/10.1177/0741713617731809

TAN, Yueying et al. Learning Profiles, Behaviors and Outcomes: Investigating International Students’ Learning Experience in an English MOOC. In: 2018, Proceedings - 2018 International Symposium on Educational Technology, ISET 2018. : IEEE, 2018. p. 214–218. Disponível em: https://doi.org/10.1109/ISET.2018.00055

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Published

2026-03-02

How to Cite

Faria de Souza, V. (2026). Mapping the behavioral profiles of students in a brazilian MOOC. Educar Mais, 10, 1–21. https://doi.org/10.15536/reducarmais.10.2026.4334

Issue

Vol. 10 (2026): January - December

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Articles

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Copyright (c) 2026 Vanessa Faria de Souza

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