59,838 research outputs found

    Digital places: location-based digital practices in higher education using Bluetooth Beacons

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    The physical campus is a shared space that enables staff and students, industry and the public, to collaborate in the acquisition, construction and consolidation of knowledge. However, its position as the primary place for learning is being challenged by blended modes of study that range from learning experiences from fully online to more traditional campus-based approaches. Bluetooth beacons offer the potential to combine the strengths of both the digital world and the traditional university campus by augmenting physical spaces to enhance learning opportunities, and the student experience more generally. This simple technology offers new possibilities to extend and enrich opportunities for learning by exploiting the near-ubiquitous nature of personal technology. This paper provides a high-level overview of Bluetooth beacon technology, along with an indication of some of the ways in which it is developing, and ways that it could be used to support learning in higher education

    Trendswatch 2013: Back to the Future

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    TrendsWatch 2013 highlights six trends that CFM's staff and advisors believe are highly significant to museums and their communities, based on our scanning and analysis over the past year. For each trend, we provide a brief summary, list examples of how the trend is playing out in the world, comment on the trend's significance to society and to museums specifically, and suggest ways that museums might respond. We also provide links to additional readings. TrendsWatch provides valuable background and context for your museum's planning and implementation

    Social networks and performance in distributed learning communities

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    Social networks play an essential role in learning environments as a key channel for knowledge sharing and students' support. In distributed learning communities, knowledge sharing does not occur as spontaneously as when a working group shares the same physical space; knowledge sharing depends even more on student informal connections. In this study we analyse two distributed learning communities' social networks in order to understand how characteristics of the social structure can enhance students' success and performance. We used a monitoring system for social network data gathering. Results from correlation analyses showed that students' social network characteristics are related to their performancePostprint (published version

    ICROFS news 1/2009 - newsletter from ICROFS

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    News and research dissemination from ICROF
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