Situation Awareness enabling Decision Support in Seamless Learning

Abstract

In order to enable and support lifelong learning, learners need to be aware of their learning processes. This work proposes a framework for supporting Self-regulation in Seamless Learning scenarios. The framework is based on the Endsley's Model for Situation Awareness. Moreover, the framework is contextualised to a specific class of learning scenarios in order to better explain its potentiality. In particular, the framework allows to define a Decision Support System which exploits the recognized situations for supporting learners in self-regulating their learning processes. Situation Theory is adopted to provide a formal model describing the whole learning situation of the learner. Lastly, a set of algorithms and semantic techniques are proposed to support the above mentioned automatic recognition.