La constante evolución de los recursos tecnológicos que se han generado en las últimas décadas y en particular las tecnologías emergentes, así como la Inteligencia Artificial (IA), ha tomado relevancia en su uso en la elaboración de recursos didácticos por profesores que imparten asignaturas de ciencias básicas. Desde sus inicios en 1956 la inteligencia artificial ha revolucionado todas las áreas disciplinares, incluyendo la educación, sin embargo, se ha discutido muy poco sobre el impacto de su despliegue en el área de las ciencias básicas. En este estudio se discute el impacto de la IA en la implementación de recursos didácticos en profesores de ciencias básicas que imparten asignaturas de matemáticas, física y química. La metodología utilizada en esta investigación fue transversal descriptiva, se diseñaron 10 preguntas y se tomaron como muestra a 20 profesores. El análisis de los datos obtenidos muestra un patrón interesante que demarca claramente la transición del uso de herramientas de IA, al implementar con juicio una variedad de estas junto a las prácticas convencionales. En conclusión, se observó una aceptación parcial en el uso de IA con tendencia positiva, lo cual implica que el uso de estas herramientas se irá regularizando e incorporando dentro de las estrategias de aprendizaje en las planeaciones didácticas.

In this work we focused on the estimation of the parameters belonging to a mathematical model for the interaction between three species (plant, plague and bio control agent), with the goal to guaranty the survival of all them. A qualitative analysis of the model is carried out to show the dynamic of it. As well, the model is solved by using a numerical scheme based on multi step method. The obtained code is coupled with the Spux framework to estimate, by stochastic simulations, the unknown parameters of the model. Numerical results show that Spux gives a correct approximation of the parameters because the model simulations with the approximated parameters are in good agreement with the data.

In this work, Bayesian estimation is performed for the parameters of a mathematical model, formulated as a system of ordinary differential equations, that describes cannibalism dynamics in larval populations of Atractosteus tropicus reared in a pond. The model divides the population into three subclasses: vulnerable, cannibalistic, and non-vulnerable individuals. Parameter estimation is conducted under two scenarios: a fed population and an unfed population. Correlation matrices are calculated for both cases. For the fed population, the most influential parameters are food quality and the time devoted to managing cannibalistic individuals. In contrast, for the unfed population, the strongest correlation occurs between the mortality rate and the transition rate of cannibalistic individuals to the non-vulnerable class. Therefore, providing larvae with high-quality food substantially reduces cannibalism and the handling time required and, consequently, increases the survival of the species.

In this work, Bayesian estimation is performed for the parameters of a mathematical model, formulated as a system of ordinary differential equations, that describes cannibalism dynamics in a larval populations of Atractosteus tropicus were reared in a pond. The model divides the population into three subclasses: vulnerable, cannibalistic, and non-vulnerable individuals. Parameter estimation is conducted under two scenarios: a fed population and an unfed population. Correlation matrices are calculated for both cases. For the fed population, the most influential parameters are food quality and the time devoted to managing cannibalistic individuals. In contrast, for the unfed population, the strongest correlation occurs between the mortality rate and the transition rate of cannibalistic individuals to the non-vulnerable class. Therefore, providing larvae with high-quality food substantially reduces cannibalism and the handling time required and, consequently, increases the survival of the species.