Computational Intelligence in Serious Games: a case study to identify patterns in a game for children with learning disabilities

This work explores the application of computational intelligence techniques in a serious game (SG) for children with learning disabilities. Specifically, we apply Data Mining (DM) techniques such as Decision Tree and Apriori algorithms aiming to identify the existence of patterns that would allow a better understanding on the profiles of children involved in the game. The data analyzed are related to the interaction of twenty children with the considered SG, which consists of a three dimensional virtual zoo, developed with features that appeal to the preferences of children about nine years old in order to assist and motivate their learning. The results obtained in the conducted experiments revealed patterns in the profiles of the game's players under analysis, allowing to identify some characteristics that can help the psychopedagogical team. These findings can also enable the improvement of the game making it adaptable to different player profiles. ; info:eu-repo/semantics/publishedVersion