Peer Group Formation for Learning

  • Johannes KonertEmail author
Part of the Springer Theses book series (Springer Theses)


To improve the effectiveness of group learning in general, and to address in particular opportunities for educational games, this chapter introduces a technique to match users by considering homogeneous and heterogeneous criteria for matching. First, the chapter identifies the requirements for the algorithmic design, based on the findings from related work analysis and the Group Formation Problem (Sect.  2.1.3). Second, the modeling of matching criteria is derived (Sect. 6.1) and metrics for the group formation algorithm are developed (Sect. 6.2). This includes the proposal of three matching algorithms, and the metrics of GPI and CPI, which fulfill the defined requirements. Finally, the approach towards optimization is discussed and algorithms are designed to optimize the cohorts and handle incremental updates. Details about the corresponding conceptualized API methods can be found in Sect. A.1.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Information TechnologyTechnische Universität DarmstadtDarmstadtGermany

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