Supporting Seamless Learning with Semantic Technologies and Situation Awareness

The goal of this work is to propose and motivate the usage of Linked Data (realized by means of the Semantic Web Stack) and Situation Awareness techniques in order to support Seamless Learning scenarios. In particular, Linked Data and Semantic Web technologies and methodologies are considered very useful to model and support the continuity of the seamless experience across heterogeneous (in quality, time and space) learning activities. Moreover, Situation Awareness and, in particular, Situation Recognition techniques can be exploited to sustain enhanced forms of ubiquitous access to learning resources and services which enable the improvement of the learning environment by using context-specific elements.