Identifying sets of key players and cliques in socio-educational co-creative projects
Evgeny Patarakin, Vasiliy Burov, Roman Parfenov
Electronic Governance and Open Society: Challenges in Eurasia (EGOSE 2015)St. Petersburg, November 24-25, 2015
Introduction
• The paper presents a new form of network collaboration – the socio-educational projects as an activity that aims not only to better management, but also the formation of links between actors and objects of collaboration.
• Our contribution makes agent-based model which help identify key actors and biggest cliques of actors.
SOCIO-EDUCATIONAL PROJECTS
• Governance and society needs co-creative projects with a final document as the end output of the collective activities.
• Education needs in a co-creative projects with a XXI skills as the learning outcomes of the collective activities.
• All these needs lead to the emergence of new type mixed projects: socio-educational co-creative projects.
SOCIAL-LEARNING ANALYTICS
• Learning analytics is a collection of methods that allow to understand what is going on in a learning scenario
• Modern socio-technical systems store the full history of all activities. This history can be presented as a record of a chess or go game, consisting of many moves:
• Agent ID| Object ID| Type of an action|
Identifying sets of key players
• Key players are those elements in the network that are considered important, in regard to betweenness centrality of vertex. Top ten key players are determined in NetLogo as
• sublist reverse sort-on [norm-betweenness] users 0 9
Identifying sets of maximal cliques
• A clique is a subset of a network in which every node has a direct link to every other node. A maximal clique is a clique that is not itself contained in a bigger clique. Cliques containing more than N members are determined in NetLogo as
• nw:maximal-cliques [if (count ?) > N
CONCLUSION
• We used the technique of dynamic agent-based sociograms to:
• • Trace how and based on what objects forming links between participants of collaborative production.
• • Identify key players and stable biggest cliques, which serve as a cores that support the operation of network communities
• • Analyze the effects of remove of the key players from the field of collaborative production