Abstract

Under the assumptions that (i) gamification consists of various types of users that experience game design elements differently; and (ii) gamification is deployed in order to achieve some goal in the broadest sense, we pose the gamification problem as that of assigning each user a game design element that maximizes their expected contribution in order to achieve that goal. We show that this problem reduces to a statistical learning problem and suggest matrix factorization as one solution when user interaction data is given. The hypothesis is that predictive models as intelligent tools for supporting users in decision-making may also have potential to support the design process in gamification.

@article{DBLP:journals/corr/MederJ14,
  author    = {Michael Meder and
               Brijnesh-Johannes Jain},
  title     = {The Gamification Design Problem},
  journal   = {CoRR},
  volume    = {abs/1407.0843},
  year      = {2014},
  ee        = {http://arxiv.org/abs/1407.0843},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}