A Primer on Data-Driven Gamification Design


Gamification gradually gains more attention. However, gamification and its successful application is still unclear. There is a lack of insights and theory on the relationships between game design elements, motivation, domain context and user behavior. We want to discover the potentials of data-driven optimization of gamification design, e.g. by the application of machine learning techniques on user interaction data. Therefore, we propose data-driven gamification design (DDGD) and conducted a questionnaire with 17 gamification experts. Our results show that respondents regard DDGD as a promising method to improve gamification design and lead to a general definition for DDGD.

  author    = {Michael Meder and
               Till Plumbaum and
               Sahin Albayrak},
  title     = {A Primer on Data-Driven Gamification Design},
  booktitle = {Proceedings of the First International Workshop on Data-Driven Gamification
               Design co-located with 21st International Academic MindTrek Conference
               (AcademicMindtrek 2017), Tampere, Finland, September 20, 2017.},
  pages     = {12--17},
  year      = {2017},
  crossref  = {DBLP:conf/mindtrek/2017ddgd},
  url       = {http://ceur-ws.org/Vol-1978/paper2.pdf},
issn = {1613-0073},
  timestamp = {Wed, 08 Nov 2017 07:29:37 +0100},
  biburl    = {http://dblp.org/rec/bib/conf/mindtrek/MederPA17},
  bibsource = {dblp computer science bibliography, http://dblp.org}
First International Workshop on Data-Driven Gamification Design Workshop (DDGD2017) at Mindtrek17