MeL: Modelo de adaptación dinámica del proceso de aprendizaje en eLearning

The use of the Internet has been progressively integrated into our daily lives. This has also been true for all levels of education, where virtual learning environments have been the means by which teachers, students and educational institutions managed and distributed educational experiences. However, the present design of these systems make students have difficulties in deploying their meta-cognitive skills, in addition to producing a cognitive overload due to an inadequate content organization and navigation. Thus, it is necessary to provide learning platforms with a process that allows for the adaptation of these systems to students’ characteristics, needs and context in order to enhance the teaching-learning process. This paper describes an adaptive model for Learning Management Systems (LMSs) that using variables central to the learning process allows for the application of adaptive rules to the different types of contents and knowledge to be transferred and acquired. In practice, the resulting model allows to develop adaptive courses that support and promote learning and self-regulation in virtual learning environmentsEn nuestra vida diaria hemos integrado progresivamente el uso de Internet. Esta incorporación también se ha producido en todos los niveles educativos, donde los entornos virtuales de aprendizaje son el medio utilizado, por profesores, estudiantes e instituciones, para el manejo y la distribución de experiencias educativas. Sin embargo, tal y como están diseñados estos sistemas, hacen que los estudiantes tengan dificultades para desplegar sus habilidades metacognitivas, además de provocar una sobrecarga cognitiva debido a una mala organización de los contenidos y de la navegación. Es necesario, por tanto, incluir en las plataformas de aprendizaje un mecanismo que permita la adaptación de estos sistemas a las características, necesidades y contexto del estudiante con el objetivo de optimizar el proceso de enseñanza-aprendizaje. En este trabajo se describe un modelo de adaptación para Learning Management Systems (LMSs) que utilizando variables centrales en el proceso de aprendizaje permite aplicar reglas adaptativas a los distintos tipos de contenidos y conocimientos que se han de transmitir o adquirir. A nivel aplicado, el modelo obtenido permite desarrollar cursos adaptados que dan soporte y promueven el aprendizaje y la autorregulación dentro de los entornos de aprendizaje virtuales

Educational Robotics Intervention in the Motivation of Students

Nowadays technological developments have been used as educational mediations. An example has been working in the classroom with robots for STEM (Science, Technology, Engineering and Mathematics), however it is important to determine the effects of robots in the classroom, mainly on motivation issues. This article shows a review of related works in educational robotics and their effects, in the same way a methodology is proposed to work in the classroom with effects on student motivation

E-learning como factor de empoderamiento hacia el desarrollo, la autonomía y la autogestión del individuo.

El e-learning es considerada una de las metodologías más eficientes para la masificación de conocimiento en las diferentes poblaciones, permite la inclusión educativa gracias al uso eficiente de las TIC en sus procesos y esto a su vez se ve reflejado en el desarrollo de las comunidades; en las cuales, cada vez es posible llegar a más integrantes, lo que permite trabajar hacia la autogestión del individuo.E-learning is considered one of the most efficient methodologies for the massification of knowledge in different populations, allows educational inclusion thanks to the efficient use of ICT in their processes and this is in turn reflected in the development of communities ; in which, it is increasingly possible to reach more members, which allows working towards self-management of the individual

Adaptation and disability aspects in a virtual learning environment

This paper discusses the main aspects that drive the design of intelligent tutoring system based virtual learning environments. Most of these virtual learning systems focus on tutor activity and use artificial intelligence techniques. Information about the interaction with these systems is used to create a model that, given the preferences and learning styles of a student, performs an information retrieval process to adapt content delivery to the student, according to his/her particular characteristics (learning style, behavior, performance, and whether the student has a disability or not)Este artículo presenta los principales aspectos que se deben tener en cuenta en el diseño de ambientes virtuales de aprendizaje como por ejemplo, los tutores inteligentes. La mayoría de estos sistemas virtuales de aprendizaje se concentran en la actividad del tutor y se utilizan técnicas de inteligencia artificial. Los sistemas que se relacionan a continuación permitieron la generación de un modelo que, dadas las preferencias y estilos de aprendizaje de un estudiante, realiza un proceso de recuperación de información con el fin de adaptar el despliegue y la manera en la que se muestra el contenido a un estudiante dadas las características particulares del mismo (estilos de aprendizaje, comportamiento y desempeño en el sistema y si tiene una discapacidad)

Adaptation and disability aspects in a virtual learning environment

This paper discusses the main aspects that drive the design of intelligent tutoring system based virtual learning environments. Most of these virtual learning systems focus on tutor activity and use artificial intelligence techniques. Information about the interaction with these systems is used to create a model that, given the preferences and learning styles of a student, performs an information retrieval process to adapt content delivery to the student, according to his/her particular characteristics (learning style, behavior, performance, and whether the student has a disability or not).This paper discusses the main aspects that drive the design of intelligent tutoring system based virtual learning environments. Most of these virtual learning systems focus on tutor activity and use artificial intelligence techniques. Information about the interaction with these systems is used to create a model that, given the preferences and learning styles of a student, performs an information retrieval process to adapt content delivery to the student, according to his/her particular characteristics (learning style, behavior, performance, and whether the student has a disability or not)