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La inteligencia artificial (IA) está provocando una transformación significativa en el ámbito educativo al ofrecer nuevas herramientas digitales y metodologías inteligentes para mejorar el proceso de enseñanza – aprendizaje. A nivel mundial la tecnología se ha integrado profundamente a nuestra vida diaria, la IA actualmente se presenta como una herramienta disruptiva que posee un futuro prometedor en relación a la evolución del sistema educativo, donde la globalización y la post pandemia de COVID-19 han resaltado la necesidad de adaptar los métodos educativos a la nueva era digital, pero también han creado brechas considerablemente significativas en el acceso y uso de estas tecnologías. Este artículo de revisión básicamente examina la integración de la IA en el sistema de educación, destacando componentes y usos respecto a la automatización de procesos administrativos, mejora de la investigación y personalización del aprendizaje, con el objetivo principal de determinar cómo comenzar a utilizar la IA en el sector educativo para generar un impacto significativo. Este estudio busca proporcionar una visión y enfoque claro de cómo la Inteligencia Artificial puede ser implementada de manera efectiva para mejorar la calidad del proceso de enseñanza – aprendizaje y prepararse para el futuro disruptivo que presenta, tanto para los educandos como los educadores.

Background: While coverage of long-lasting insecticide-treated nets (LLIN) has steadily increased, a growing number of studies report gaps between net ownership and use. We conducted a mixed-methods social science study assessing the importance of net preference and use after OlysetH LLINs were distributed through a mass campaign in rural communities surrounding Iquitos, the capital city of the Amazonian region of Peru. Methods: The study was conducted in the catchment area of the Paujil and Cahuide Health Centres (San Juan district) between July 2007 and November 2008. During a first qualitative phase, participant observation and in-depth interviews collected information on key determinants for net preference and use. In a second quantitative phase, a survey among recently confirmed malaria patients evaluated the acceptability and use of both LLINs and traditional nets, and a case control study assessed the association between net preference/use and housing structure (open vs. closed houses). Results: A total of 10 communities were selected for the anthropological fieldwork and 228 households participated in the quantitative studies. In the study area, bed nets are considered part of the housing structure and are therefore required to fulfil specific architectural and social functions, such as providing privacy and shelter, which the newly distributed OlysetH LLINs ultimately did not. The LLINs’ failure to meet these criteria could mainly be attributed to their large mesh size, transparency and perceived ineffectiveness to protect against mosquitoes and other insects, resulting in 63.3% of households not using any of the distributed LLINs. Notably, LLIN usage was significantly lower in houses with no interior or exterior walls (35.2%) than in those with walls (73.8%) (OR = 5.2, 95CI [2.2; 12.3], p,0.001). Conclusion: Net preference can interfere with optimal LLIN use. In order to improve the number of effective days of LLIN protection per dollar spent, appropriate