Abstract:
Understanding how social robots interact with chil-dren's learning is a topic that is currently attracting considerable interest. Yet, there is currently only loose agree...Show MoreMetadata
Abstract:
Understanding how social robots interact with chil-dren's learning is a topic that is currently attracting considerable interest. Yet, there is currently only loose agreement on how social behaviours in robots should best be implemented, and recent research suggests that social behaviours in robots may not always be beneficial for children's learning outcomes. There are similarly conflicting findings on the benefits of social behaviours in promoting trust in robots. This interplay between robots' social behaviours, trust, and learning is therefore yet to be fully investigated. Consequently, the goal of this dissertation is twofold; firstly, to establish a consistent definition and operationalisation of social behaviours in robots, and secondly to determine the effects of these social behaviours on children's learning and evaluations of trust. To this end, four studies are proposed. Through the lens of trust formation, breakdown, and recovery, these studies aim to help understand the role of social behaviours in children's learning from social robots.
Published in: 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)
Date of Conference: 03-06 September 2019
Date Added to IEEE Xplore: 08 December 2019
ISBN Information: