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Revista Tecnológica-Educativa Docentes 2.0

versión On-line ISSN 2665-0266

Resumen

LOPEZ, Omar Daniel Rosero; LOOR, Génesis Cristina Romo; PILAY, Mercedes Marcela Pincay  y  PISCO, Dimas Geovanny Vera. Mathematics and Science in the Classroom: Exploring the Golden Ratio in the Human Body. Revista Docentes 2.0 [online]. 2026, vol.19, n.1, pp.176-183.  Epub 29-Mayo-2026. ISSN 2665-0266.  https://doi.org/10.37843/rted.v19i1.743.

The golden ratio, a universal mathematical constant, manifests itself in nature, art, and biology, and is a valuable educational resource for integrating science and education. The objective of the research was to empirically analyze the relationship between certain human body dimensions and determine whether these proportions reflected patterns associated with the “Divine Proportion.” The research was framed within the positivist paradigm, applying the hypothetical-deductive method, with a quantitative approach, a non-experimental correlational-explanatory design, and a cross-sectional approach. This allowed for the verification of the hypothesis and the support of conclusions with objective data, increasing the validity and scientific rigor. A non-probability convenience sample of 31 secondary school students was used. Height, lower trunk, and upper trunk were measured. The data were analyzed using multiple linear regression, descriptive statistics, variance tests, and graphical representations, which made it possible to examine associations between variables and generate a predictive model. The results showed a significant proportional relationship between the dimensions studied, with an adjusted R² of 0.994, confirming the robustness of the model applied. As a future research project, it is suggested that the sample size be expanded and nonlinear or comparative models be applied between groups by sex, age, or geographical context, with the aim of further investigating the existence of mathematical proportions in human morphology.

Palabras clave : Golden ratio; body symmetry; predictive models; statistical regression; human morphometry..

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