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Titlebook: Collaboration and Technology; 18th International C Valeria Herskovic,H. Ulrich Hoppe,Jürgen Ziegler Conference proceedings 2012 Springer-Ve

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https://doi.org/10.1007/978-0-387-69757-4, a .cial .oncurrency .onflict .esolution (SoCCR) protocol enables collaborative editing of text nodes in the planning space. We will illustrate this with an example of user interaction in the Metafora system involving the concurrency mechanism.
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R. Engelking,R. W. Heath,E. Michaelch are collected and stored in a central repository for processing, filtering and visualization on a shared display. A set of different learning and teaching scenarios that can be realized with MoCo are described along with first experiences and insights gained from qualitative and quantitative evaluation.
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Reusability of Data Flow Designs in Complex CSCL Scripts: Evaluation Results from a Case Studyrizes the reuse effort of CSCL scripts with and without data flow definition, in different social context settings. The findings illustrate how the data flow representation may affect the particularization of complex CSCL scripts, and pave the path for alternative, higher abstraction level representations of data flows, to reduce the reuse effort.
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SoCCR – Optimistic Concurrency Control for the Web-Based Collaborative Framework Metafora, a .cial .oncurrency .onflict .esolution (SoCCR) protocol enables collaborative editing of text nodes in the planning space. We will illustrate this with an example of user interaction in the Metafora system involving the concurrency mechanism.
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Enabling and Evaluating Mobile Learning Scenarios with Multiple Input Channelsch are collected and stored in a central repository for processing, filtering and visualization on a shared display. A set of different learning and teaching scenarios that can be realized with MoCo are described along with first experiences and insights gained from qualitative and quantitative evaluation.
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Contextual Analysis of the Victims’ Social Network for People Recommendation on the Emergency Scenar provide important and reliable information about them, thus assisting the emergency team in its work. We use this contextual information to improve the recommendation process, identifying people with high degree of closeness.
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