Gameful Markets for Collaboration and Learning

نویسندگان

  • Stephan Leutenmayr
  • Fabian Kneissl
  • Sven Ziemer
  • François Bry
چکیده

The market metaphor offers a promising form of human computation for gathering and aggregating individual opinions into a collective point of view for groups of people. In this article, we identify different kinds of market forms, their specific goals, and their participants’ behavior. Building on this, we first determine appropriate reward designs for a good functioning of the markets as opinion aggregators. Furthermore, we stress potential possibilities for facilitating participants’ learning. To illustrate and validate the approach proposed, we investigate two different market applications with different kinds of rewards and goals.

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تاریخ انتشار 2013