Learning in Games through Social Networks
Sanne Kosterman

Abstract:
Modern approaches to human learning suggest that the process of
learning is most effective when the environment is active and
social. Digital techniques of serious games and online social networks
are therefore becoming increasingly popular in today’s educational
system. This thesis contributes to the proposition that combining
elements of social networks and games can positively influence the
learning behaviour of players. To underpin this statement, we propose
a computational model that combines features of social network
learning and game-based learning. The focus is on cooperative games,
in which players are collaborating in a grand coalition and are trying
to achieve a common goal. Our learning paradigm combines insights from
game theory, graph theory, and social choice theory, resulting in an
interdisciplinary framework for analysing learning behaviour. We show
that enriching cooperative games with social networks can improve
learning towards the common goal, under specific conditions on the
network structure and existing expertise in the coalition. Based on
the findings from our formal model, we provide a list of
recommendations on how to include network structures in serious games.