The use of fractal imagery and the Integral Strategy in cognitive stimulation of 3- to 7-year-old children: preparation for machine learning

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Resumen

The present study demonstrates the connection between fractal images, children's cognitive development, and machine learning by assessing how self-similarity influenced the cognitive development of children aged 3 to 7, especially in their ability to focus and concentrate. Furthermore, the relationship between technological convergence and fractal images was evaluated, highlighting their potential to inspire innovative applications. The methodology included a comprehensive review of relevant scientific literature and a detailed analysis of research on children's cognitive development. Appropriate statistical methods were employed to analyze the data, notably utilizing the Student's t-test, which helped to reveal the connection between machine learning and self-similarity in nature.
The results underscored the significant potential of fractal images to stimulate the cognitive development of young children, with significant implications in fields such as education and preparation for machine learning. This demonstrates the relevance of research in basic sciences, providing the necessary foundations to advance its algorithms. The article emphasized the exciting convergence between fractal vision, technology, and basic science research, opening new perspectives for future research and applications in various fields, from education to artificial intelligence. Additionally, a comprehensive strategy was proposed with the aim of achieving positive results in children's cognitive development.

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Palabras clave

Aprendizaje automáticoautosemejanzadesarrollo cognitivo infantilestrategiaimágenes fractalesMachine learningself-similaritychild cognitive developmentstrategyfractal images