A characteristic of complex and adaptive systems that display emergent behavior. A structure that self-organizes and gets its smarts from below; agents residing on a scale start producing behavior that lies one scale above them (e.g., ants create colonies, learners create learning communities).
Published in Chapter:
Design Guidelines for Collaboration and Participation with Examples from the LN4LD (Learning Network for Learning Design)
Daniel Burgos (Open University of The Netherlands, The Netherlands), Hans G.K. Hummel (Open University of The Netherlands, The Netherlands), Colin Tattersall (Open University of The Netherlands, The Netherlands), Francis Brouns (Open University of The Netherlands, The Netherlands), and Rob Koper (Open University of The Netherlands, The Netherlands)
Copyright: © 2009
|Pages: 17
DOI: 10.4018/978-1-59904-861-1.ch018
Abstract
This chapter presents some design guidelines for collaboration and participation in blended learning networks. As an exemplary network, we describe LN4LD (Learning Network for Learning Design), which was designed to promote learning and discussion about IMS-Learning Design. ‘Lessons learned’ from pilot implementations of this network over a period of five years are phrased as guidelines for future learning network implementations. The chapter focuses on the positive influence of incentive mechanisms and face-to-face meetings on active participation. These successful interventions are explained from theories about self-organization, social exchange, and social affordances. Repeated measurements show the levels of both passive (accessing and reading information) and active participation (posting, replying, and rating) to significantly increase as a result of both interventions. Both the use of incentive mechanisms and face-to-face meetings can therefore be considered as valuable elements for future models for collaboration in learning networks and for establishing an international community of “learning designers.”