Whenever we work, study, play, we constantly move from one piece of information to another. In so doing, we explore what could be defined an information or a knowledge space. Points of this space are components of our knowledge and culture, linked through semantic and logic relations. Whatever the activity we are involved in, while wandering on such networked structures, we describe paths, possibly expanding the space itself and creating novel connections. Still, how the conceptual spaces are structured, how we stand in them and how we shape our trajectories on them are all largely unknown.
Network theory and complex systems analysis can help address these questions, by providing us with a rigorous framework to investigate and model our dynamics as learners and information seekers. By basing on previous findings in cognitive and linguistic research as well as on the actual behaviour of learners in knowledge networks like Wikipedia, we aim at grasping general patterns in learning dynamics. This understanding is indeed key to design novel strategies and tools to make our experiences as knowledge explorers more and more efficient.
New paper on learning dynamics
A new paper about "Optimal learning paths in information networks" just appeared on SciRep. A novel approach to algorithmic education is here proposed, which combines
NetSci2015 - Talk on learning dynamics
Giovanna Chiara Rodi will give a contributed talk during the NetSci2015 Conference on learning dynamics on networks. Abstract Optimal learning paths in information networks Each
Optimal Learning Paths in Information Networks (Journal Article)
Scientific Reports, 5 (10286), 2015.