Aprendizagem colaborativa nas redes

terça-feira, dezembro 20, 2011

Collaborative learning in networks

Winter Mason a,1 and Duncan J. Watts b,1

Author Affiliations

aStevens Institute of Technology, Hoboken, NJ 07030; and
bYahoo! Research, New York, NY 10018

Edited by Kenneth Wachter, University of California, Berkeley, CA, and approved November 3, 2011 (received for review June 27, 2011)


Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions.

collaboration, diffusion, exploration-exploitation trade off


1To whom correspondence may be addressed. E-mail: wmason@stevens.edu or djw@yahoo-inc.com.

Author contributions: W.M. and D.J.W. designed research; W.M. performed research; W.M. analyzed data; and W.M. and D.J.W. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1110069108/-/DCSupplemental.