Multimodal Affective Computing to Enhance the User Experience of Educational Software Applications
Affective computing is becoming more and more important as it enables to extend the possibilities of computing technologies by incorporating emotions. In fact, the detection of users’ emotions has become one of the most important aspects regarding Affective Computing. In this paper, we present an ed...
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Online Access: | http://dx.doi.org/10.1155/2018/8751426 |
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doaj-71f77b496d0b42749f1c61d1248a410a2021-07-02T14:14:22ZengHindawi LimitedMobile Information Systems1574-017X1875-905X2018-01-01201810.1155/2018/87514268751426Multimodal Affective Computing to Enhance the User Experience of Educational Software ApplicationsJose Maria Garcia-Garcia0Víctor M. R. Penichet1María Dolores Lozano2Juan Enrique Garrido3Effie Lai-Chong Law4Research Institute of Informatics, University of Castilla-La Mancha, Albacete, SpainResearch Institute of Informatics, University of Castilla-La Mancha, Albacete, SpainResearch Institute of Informatics, University of Castilla-La Mancha, Albacete, SpainEscuela Politécnica Superior, University of Lleida, Lleida, SpainDepartment of Informatics, University of Leicester, Leicester, UKAffective computing is becoming more and more important as it enables to extend the possibilities of computing technologies by incorporating emotions. In fact, the detection of users’ emotions has become one of the most important aspects regarding Affective Computing. In this paper, we present an educational software application that incorporates affective computing by detecting the users’ emotional states to adapt its behaviour to the emotions sensed. This way, we aim at increasing users’ engagement to keep them motivated for longer periods of time, thus improving their learning progress. To prove this, the application has been assessed with real users. The performance of a set of users using the proposed system has been compared with a control group that used the same system without implementing emotion detection. The outcomes of this evaluation have shown that our proposed system, incorporating affective computing, produced better results than the one used by the control group.http://dx.doi.org/10.1155/2018/8751426 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jose Maria Garcia-Garcia Víctor M. R. Penichet María Dolores Lozano Juan Enrique Garrido Effie Lai-Chong Law |
spellingShingle |
Jose Maria Garcia-Garcia Víctor M. R. Penichet María Dolores Lozano Juan Enrique Garrido Effie Lai-Chong Law Multimodal Affective Computing to Enhance the User Experience of Educational Software Applications Mobile Information Systems |
author_facet |
Jose Maria Garcia-Garcia Víctor M. R. Penichet María Dolores Lozano Juan Enrique Garrido Effie Lai-Chong Law |
author_sort |
Jose Maria Garcia-Garcia |
title |
Multimodal Affective Computing to Enhance the User Experience of Educational Software Applications |
title_short |
Multimodal Affective Computing to Enhance the User Experience of Educational Software Applications |
title_full |
Multimodal Affective Computing to Enhance the User Experience of Educational Software Applications |
title_fullStr |
Multimodal Affective Computing to Enhance the User Experience of Educational Software Applications |
title_full_unstemmed |
Multimodal Affective Computing to Enhance the User Experience of Educational Software Applications |
title_sort |
multimodal affective computing to enhance the user experience of educational software applications |
publisher |
Hindawi Limited |
series |
Mobile Information Systems |
issn |
1574-017X 1875-905X |
publishDate |
2018-01-01 |
description |
Affective computing is becoming more and more important as it enables to extend the possibilities of computing technologies by incorporating emotions. In fact, the detection of users’ emotions has become one of the most important aspects regarding Affective Computing. In this paper, we present an educational software application that incorporates affective computing by detecting the users’ emotional states to adapt its behaviour to the emotions sensed. This way, we aim at increasing users’ engagement to keep them motivated for longer periods of time, thus improving their learning progress. To prove this, the application has been assessed with real users. The performance of a set of users using the proposed system has been compared with a control group that used the same system without implementing emotion detection. The outcomes of this evaluation have shown that our proposed system, incorporating affective computing, produced better results than the one used by the control group. |
url |
http://dx.doi.org/10.1155/2018/8751426 |
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