Palma de Mallorca, España
Affective computing is the study and development of systems that can recognize, interpret, process, and simulate human affects [1]. In the educational area, these systems can be used to identify and measure the affective status of the student during the learning process [2]. In this work, we use a Social Robot in a serious game to interact with the students in order to improve their learning and increase their motivation. Serious Games [3] in education are games that are designed to help to students in learning, as well as being entertaining and fun. Robots equipped with affective capabilities can also be a useful tool to get feedback in a serious game, for example, they can assess the degree of satisfaction of the students. Further, they can act as mediators, motivate the student and adapt the game according to the student’s emotions. Regarding students with special needs, emotions play an important role in their personal development. Students with autism spectrum disorder (ASD) struggle to understand how they feel and how others feel [4]. Students with cerebral palsy (CP) need help to understand and manage their emotions [5]. In this work, we present a tool for training/learning emotions, where the social robot acts as a supervisor of the user's level of success regarding the emotion performed. This system allows replicating and learning in a playful way four facial expressions related to basic emotions: happy, sadness, fear and neutral [6]. This kind of experience can be generalized to other learning contexts such as encouraging attention and motivation, especially in the case of students with attention deficit disorder (ADD) syndrome.
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