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

dc.contributor.authorDOMINGUES, A. M.
dc.date.accessioned2024-01-29T15:45:29Z
dc.date.available2024-01-29T15:45:29Z
dc.date.issued2022
dc.description.abstractThis 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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.urihttp://hdl.handle.net/10400.26/49428
dc.language.isoengpt_PT
dc.subjectComputational Intelligencept_PT
dc.subjectData Miningpt_PT
dc.subjectPattern Recognitionpt_PT
dc.subjectDecision Treept_PT
dc.subjectApriori Algorithmpt_PT
dc.titleComputational Intelligence in Serious Games: a case study to identify patterns in a game for children with learning disabilitiespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleInternational Journal of Computer Applicationspt_PT
person.familyNameDomingues
person.givenNameAndréia Miranda
person.identifier.ciencia-idB611-685E-7C05
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication366362c8-db36-4d8f-91b4-37472af78f5d
relation.isAuthorOfPublication.latestForDiscovery366362c8-db36-4d8f-91b4-37472af78f5d

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