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Sistema de gestión del aprendizaje inteligente, adaptativo y accesible
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Diaz, Felipe Tomás
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Universidad Siglo 21
Resumen
Las plataformas de aprendizaje disponibles en la actualidad tienen problemas para adaptarse
a las diferentes formas de aprender, así se comprobó a través de las observaciones y las
entrevistas realizadas tanto a docentes como a estudiantes: desorganización del material,
ausencia de mecanismos que ajusten los contenidos y estrategias didácticas a las
características individuales de los estudiantes y falta de recursos accesibles para personas con
discapacidad son algunos de los problemas detectados. A partir de este diagnóstico, se diseñó,
desarrolló e implementó un sistema de gestión del aprendizaje web y multiplataforma,
orientado a personalizar la experiencia educativa. El desarrollo incluyó la integración de
distintos modelos de inteligencia artificial de OpenAI y Google, utilizados para clasificar
estilos de aprendizaje, recomendar y crear contenido educativo y para adaptar la interfaz y
herramientas en función del perfil del usuario. La aplicación fue desarrollada con tecnologías
web, y se desplego en la nube de Azure para garantizar su escalabilidad, disponibilidad y
seguridad. Se validó el sistema a través de pruebas de usabilidad con usuarios y con pruebas
funcionales en dispositivos/navegadores variados. Como resultado, se obtuvo una
herramienta de software operativa que mejora el seguimiento de trayectorias educativas y
permite adaptar tanto los contenidos como la interfaz según el estilo de aprendizaje del
estudiante (visual, auditivo, lector/escritor o kinestésico), facilitando así que cada persona
pueda estudiar de la forma que le resulta más natural y efectiva, y favoreciendo un proceso
de enseñanza-aprendizaje más flexible y eficiente.
Currently available learning platforms struggle to adapt to different learning styles, as evidenced by observations and interviews with both teachers and students: disorganization of materials, a lack of mechanisms to adjust content and teaching strategies to individual student characteristics, and a lack of accessible resources for people with disabilities are some of the problems identified. Based on this diagnosis, a web-based, multi-platform learning management system was designed, developed, and implemented, aimed at personalizing the educational experience. The development included the integration of various artificial intelligence models from OpenAI and Google, used to classify learning styles, recommend and create educational content, and adapt the interface and tools based on the user's profile. The application was developed with web technologies and deployed in Azure cloud to ensure its scalability, availability, and security. The system was validated through usability testing with users and functional testing on various devices/browsers. The result was a functional software tool that improves the tracking of educational trajectories and allows both the content and the interface to be adapted to the student's learning style (visual, auditory, reader/writer, or kinesthetic), thus facilitating each individual to study in the most natural and effective way for them, and promoting a more flexible and efficient teaching-learning process.
Currently available learning platforms struggle to adapt to different learning styles, as evidenced by observations and interviews with both teachers and students: disorganization of materials, a lack of mechanisms to adjust content and teaching strategies to individual student characteristics, and a lack of accessible resources for people with disabilities are some of the problems identified. Based on this diagnosis, a web-based, multi-platform learning management system was designed, developed, and implemented, aimed at personalizing the educational experience. The development included the integration of various artificial intelligence models from OpenAI and Google, used to classify learning styles, recommend and create educational content, and adapt the interface and tools based on the user's profile. The application was developed with web technologies and deployed in Azure cloud to ensure its scalability, availability, and security. The system was validated through usability testing with users and functional testing on various devices/browsers. The result was a functional software tool that improves the tracking of educational trajectories and allows both the content and the interface to be adapted to the student's learning style (visual, auditory, reader/writer, or kinesthetic), thus facilitating each individual to study in the most natural and effective way for them, and promoting a more flexible and efficient teaching-learning process.