Aplicación de la teoría de grafos en el pensamiento computacional

Jorge Hernan Suaza Jimenez

doi:10.24050/reia.v23i46.1955

Application of Graph Theory in Computational Thinking

10.24050/reia.v23i46.1955

Published 2026-09-17

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Application of Graph Theory in Computational Thinking (J. H. Suaza Jimenez, Trans.). (2026). Revista EIA, 23(46), 1-16. https://doi.org/10.24050/reia.v23i46.1955

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Abstract

Graph theory allows for the representation of relationships and modeling of complex problems, which has made it a useful pedagogical resource for strengthening computational thinking in educational contexts. This study analyzes the didactic use of different types of graphs (simple, directed, weighted, multigraphs, and connected) to develop skills such as abstraction, decomposition, pattern recognition, and algorithmic thinking. The research employed a mixed-methods approach with a quasi-experimental design. A total of 200 students from grades 6 to 10 at three educational institutions in the department of Antioquia, Colombia, participated. A sequence of activities based on problem-solving through graphs was implemented, and computational thinking was assessed using an instrument adapted from the Bebras model. The results showed improvements in student performance as the complexity of the activities increased. Statistical analysis revealed a positive correlation between weighted graphs and algorithmic thinking (r = 0.82, p < 0.01), as well as significant differences compared to simple graph activities (t = 12.49; p < 0.001). This suggests that their progressive use favors the development of computational thinking.

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Jorge Hernan Suaza Jimenez

Instituto Tecnológico Metropolitano

https://orcid.org/0000-0002-9669-8145 (unauthenticated)

References

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