A New Competence-based Approach for Personalizing MOOCs in a Mobile Collaborative and Networked Environment

Massive Open Online Courses (MOOCs) are a new disruptive development in higher education that combines openness and scalability in a most powerful way. They have the potential to widen participation in higher education. Thus, they contribute to social inclusion, the dissemination of knowledge and pedagogical innovation and also the internationalization of higher education institutions. However, one of the critical elements for a massive open language learning experience to be successful is to empower learners and to facilitate networked learning experiences. In fact, MOOCs are designed for an undefined number of participants, thus serving a high heterogeneity of profiles, with diverse learning styles and prior knowledge, and also contexts of participation and diversity of online platforms. Personalization can play a key role in this process. The iMOOC pedagogical model introduced the notion of diversity to MOOC design, allowing for a clear differentiation of learning paths and also virtual environments. In this article, the authors present a proposal based on the iMOOC approach for a new framework for personalizing and adapting MOOCs designed in a collaborative, networked pedagogical approach by identifying each participant's competence profile and prior knowledge, as well as the respective mobile communication device used to generate matching personalized learning. This article also shows the results obtained in a laboratory environment after an experiment has been performed with a prototype of the framework. It can be observed that creating personalized learning paths is possible and the next step is to test this framework with real experimental groups.Los cursos en línea masivos y abiertos (MOOC) son una nueva tendencia rompedora en la educación superior. Estos cursos combinan la propiedad de ser abiertos con la posibilidad de ser escalables de una forma muy potente. Tienen el potencial de permitir la participación en la educación superior para todas las personas, a todos los niveles. Por lo tanto, contribuyen a la inclusión social, la difusión del conocimiento y la innovación pedagógica, así como la internalización de las instituciones de educación superior. Sin embargo, uno de los elementos críticos para que tenga éxito una experiencia de aprendizaje de forma abierta y masiva es potenciar y facilitar una red de aprendizaje. De hecho, los MOOC no están diseñados para un número predefinido de participantes por lo que sirven para un alto número de perfiles heterogéneos, con diversidad de estilos de aprendizaje y conocimientos previos, pero también contextos de participación y diversidad de plataformas online. La personalización puede desempeñar un papel clave en este proceso. El modelo pedagógico iMOOC introdujo el principio de diversidad en el diseño de MOOC, permitiendo una clara diferenciación de caminos de aprendizaje y también entornos virtuales. En este artículo los autores presentan una propuesta basada en el enfoque de iMOOC, sobre un nuevo sistema para la personalización y adaptación de MOOC diseñados en un enfoque colaborativo y en una red pedagógica. El mecanismo es identificar cada competencia del perfil de los participantes, el conocimiento previo que estos tienen así como detectar sus respectivos dispositivos móviles, y se genera un camino de aprendizaje personalizado en base a estos parámetros. Este artículo también muestra los resultados obtenidos en un entorno de laboratorio después de un experimento llevado a cabo con un prototipo del sistema. Se puede observar que es posible crear caminos de aprendizaje personalizados y que el siguiente paso es probar este sistema con grupos experimentales reales

Personalization framework for adaptive robotic feeding assistance

The final publication is available at link.springer.comThe deployment of robots at home must involve robots with pre-defined skills and the capability of personalizing their behavior by non-expert users. A framework to tackle this personalization is presented and applied to an automatic feeding task. The personalization involves the caregiver providing several examples of feeding using Learning-by- Demostration, and a ProMP formalism to compute an overall trajectory and the variance along the path. Experiments show the validity of the approach in generating different feeding motions to adapt to user’s preferences, automatically extracting the relevant task parameters. The importance of the nature of the demonstrations is also assessed, and two training strategies are compared. © Springer International Publishing AG 2016.Peer ReviewedPostprint (author's final draft

Maximizing Competency Education and Blended Learning: Insights from Experts

In May 2014, CompetencyWorks brought together twenty-three technical assistance providers to examine their catalytic role in implementing next generation learning models, share each other's knowledge and expertise about blended learning and competency education, and discuss next steps to move the field forward with a focus on equity and quality. Our strategy maintains that by building the knowledge and networks of technical assistance providers, these groups can play an even more catalytic role in advancing the field. The objective of the convening was to help educate and level set the understanding of competency education and its design elements, as well as to build knowledge about using blended learning modalities within competency-based environments. This paper attempts to draw together the wide-ranging conversations from the convening to provide background knowledge for educators to understand what it will take to transform from traditional to personalized, competency-based systems that take full advantage of blended learning

An E-Learning Investigation into Learning Style Adaptivity

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SARS-CoV-2 Dissemination using a Network of the United States Counties

During 2020 and 2021, severe acute respiratory syndrome coron- avirus 2 (SARS-CoV-2) transmission has been increasing amongst the world’s population at an alarming rate. Reducing the spread of SARS-CoV-2 and other diseases that are spread in similar manners is paramount for public health of- ficials as they seek to effectively manage resources and potential population control measures such as social distancing and quarantines. By analyzing the United States’ county network structure, one can model and interdict poten- tial higher infection areas. County officials can provide targeted information, preparedness training, as well as increase testing in these areas. While these approaches may provide adequate countermeasures for localized areas, they are inadequate for the holistic United States. We solve this problem by col- lecting coronavirus disease 2019 (COVID-19) infections and deaths from the Center for Disease Control and Prevention and a network adjacency structure from the United States Census Bureau. Generalized network autoregressive (GNAR) time series models have been proposed as an efficient learning algorithm for networked datasets. This work fuses network science and operations research techniques to univariately model COVID-19 cases, deaths, and cur- rent survivors across the United States’ county network structure

¿Pueden los MOOC cerrar la brecha de oportunidades?: La contribución del diseño pedagógico social inclusivo

Massive Open Online Courses (MOOCs) are open courses made available online at no cost to the user and designed to scale up, allowing for a large number of participants. As such, they are a disruptive new development which has the potential to widen access to higher education since they contribute to social inclusion, the dissemination of knowledge and pedagogical innovation. However, assuring quality learning opportunities to all cannot be simply reduced to allowing free access to higher education. On the contrary, it implies assuring equitable opportunities for every participant to succeed in their learning experience. This goal depends on the quality of the learning design. To be successful, a massive open online learning experience has to empower learners and to facilitate a networked learning environment. In fact, MOOCs are designed to serve a high heterogeneity of profiles, with many differences regarding learning needs and preferences, prior knowledge, contexts of participation and diversity of online platforms. Personalization can play a key role in this process. In this article, the authors describe the iMOOC pedagogical model and its later derivative, the sMOOC model, and explain how they contributed to the introduction of the principles of diversity and learner equity to MOOC design, allowing for a clear differentiation of learning paths and also of virtual environments, while empowering participants to succeed in their learning experiences. Using a design-based research approach, a comparative analysis of two course iterations each representing each model is also presented and discussed.Los cursos en línea abiertos y masivos (MOOC) son cursos abiertos disponibles en línea sin costo para el usuario y diseñados para ampliarse, permitiendo un gran número de participantes. Como tales, son un nuevo desarrollo disruptivo que tiene el potencial de ampliar el acceso a la educación superior, ya que contribuyen a la inclusión social, la difusión del conocimiento y la innovación pedagógica. Sin embargo, garantizar oportunidades de aprendizaje de calidad para todos no puede reducirse simplemente a permitir el acceso gratuito a la educación superior. Por el contrario, implica asegurar oportunidades equitativas para que cada participante tenga éxito en su experiencia de aprendizaje. Este objetivo depende de la calidad del diseño de aprendizaje. Para tener éxito, una experiencia de aprendizaje en línea abierta y masiva debe empoderar a los alumnos y facilitar un entorno de aprendizaje en red. De hecho, los MOOC están diseñados para servir a una gran heterogeneidad de perfiles, con muchas diferencias con respecto a las necesidades y preferencias de aprendizaje, conocimiento previo, contextos de participación y diversidad de plataformas en línea. La personalización puede jugar un papel clave en este proceso. En este artículo, los autores describen el modelo pedagógico iMOOC y su derivada posterior, el modelo sMOOC, y explican cómo contribuyeron a la introducción de los principios de diversidad y equidad en el diseño MOOC, lo que permite una clara diferenciación de las rutas de aprendizaje y también de entornos virtuales, al tiempo que permite a los participantes tener éxito en sus experiencias de aprendizaje. Usando un enfoque de design-based research, también se presenta y discute un análisis comparativo de dos iteraciones del curso, cada una representando cada modelo