In this paper we investigate the impact of a social robot in the context of serious games in which the robot plays the role of a game opponent by challenging and, at the same time, teaching the child to correctly recycle waste materials. To this aim we performed a study in which we investigated the dimensions that are used to evaluate serious games integrated with those that are typical of the interaction with a social robot. To endow the robot with the capability to play as a game opponent in a real-world context, we implemented an image recognition module based on a Convolutional Neural Network so that the robot could detect and classify the waste material as a child would do, by seeing it. After a preliminary evaluation of the approach, we started a formal experiment in which we measured the effectiveness of game design, the robot evaluation and the evaluation of cognitive and affective elements that can form the pro-environmental attitude and then the tendency to recycling. A primary school classroom was involved in the study and, results obtained so far, are encouraging and drew promising possibilities for robotics education in changing recycling attitude for children since Pepper is positively evaluated as trustful and believable and this allowed to be concentrated on the ‘memorization’ task during the game.

Investigating the Social Robots’ Role in Improving Children Attitudes toward Recycling. The case of PeppeRecycle

Berardina De Carolis;Francesca D’Errico;Veronica Rossano
2019

Abstract

In this paper we investigate the impact of a social robot in the context of serious games in which the robot plays the role of a game opponent by challenging and, at the same time, teaching the child to correctly recycle waste materials. To this aim we performed a study in which we investigated the dimensions that are used to evaluate serious games integrated with those that are typical of the interaction with a social robot. To endow the robot with the capability to play as a game opponent in a real-world context, we implemented an image recognition module based on a Convolutional Neural Network so that the robot could detect and classify the waste material as a child would do, by seeing it. After a preliminary evaluation of the approach, we started a formal experiment in which we measured the effectiveness of game design, the robot evaluation and the evaluation of cognitive and affective elements that can form the pro-environmental attitude and then the tendency to recycling. A primary school classroom was involved in the study and, results obtained so far, are encouraging and drew promising possibilities for robotics education in changing recycling attitude for children since Pepper is positively evaluated as trustful and believable and this allowed to be concentrated on the ‘memorization’ task during the game.
978-1-7281-4793-2
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/246214
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
social impact