Sustaining self-regulation processes in seamless learning scenarios by situation awareness

This paper faces the problem of increasing the awareness of learners, with respect to their whole learning processes, in order to sustain their capabilities to adapt such processes. The idea is to exploit models and approaches for Situation Awareness, previously adopted in other fields, also in the human learning domain by defining a framework that can be instantiated in a wide range of seamless learning scenarios. Being aware of the learning situations in which they are, learners can make decisions to adapt their behaviours and self-regulate their processes. More specifically, the approach is able to identify learning path types by exploiting the metaphor of bubbles, which represent sets of concepts already acquired by learners. It is possible to identify the situations in which learners are involved by taking into account the way in which such bubbles arise, grow and join together. Lastly, this work also provides a description and an early evaluation of the developed software prototype.