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Computational Intelligence in Serious Games: a case study to identify patterns in a game for children with learning disabilities
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| 1.03 MB | Adobe PDF |
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Resumo(s)
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.
Descrição
Palavras-chave
Computational Intelligence Data Mining Pattern Recognition Decision Tree Apriori Algorithm