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 sphere of knowledge and information could be depicted as a complex mesh of correlated items. By properly exploiting these connections, innovative educational strategies could be defined, possibly leading to more efficient learning processes. In this work we investigate how the topological structure embedding the items to be learned affects the efficiency of a learning dynamics, simulated as an ordered exploration of the network. To this end we introduce a general class of algorithms that, standing on well-established findings on educational scheduling, namely the spacing and lag effects, capture some of the behaviors of an individual moving in a knowledge space, while learning. In exploring this space, learners move along connections, periodically revisiting some concepts, and sometimes jumping on very distant ones. In order to investigate the effect of networked information structures on the dynamics we focused both on synthetic and real-world graphs such as subsections of Wikipedia and word-association graphs. We highlight the existence of optimal topological structures for our learning dynamics whose efficiency is affected by the balance between hubs and the least connected items. Interestingly, the real-world graphs we considered lead naturally to almost optimal learning performances.