Data analytics of mobile serious games: applying Bayesian data analysis methods

Heide Lukosch, Scott Cunningham

Research output: Contribution to journalArticlepeer-review


Traditional teaching methods in the field of resuscitation training show some limitations, while teaching the right actions in critical situations could increase the number of people saved after a cardiac arrest. For our study, we developed a mobile game to support the transfer of theoretical knowledge on resuscitation. The game has been tested at three schools of further education. A number of data has been collected from 171 players. To analyze this large data set from different sources and quality, different types of data modeling and analyses had to be applied. The application of Bayesian methods showed its usefulness in analyzing the large set of data from different sources. It revealed some interesting findings, such as that female players outperformed the male ones, and that the game fostering informal, selfdirected is equally efficient as the traditional formal learning method.
Original languageEnglish
Pages (from-to)19-36
Number of pages18
JournalInternational Journal of Serious Games
Issue number1
Publication statusPublished - 26 Mar 2018


  • data analytics
  • resuscitation
  • serious games
  • mobile games


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