ROHCJun 20, 2016

Impact of robot responsiveness and adult involvement on children's social behaviours in human-robot interaction

arXiv:1606.06104v110 citations
Originality Incremental advance
AI Analysis

This research addresses the challenge of designing engaging social robots for children in educational settings, though it appears incremental in exploring specific interaction factors.

The study investigated how robot responsiveness and adult involvement affect children's social behaviors in human-robot interaction, finding that a fully-autonomous robot led to greater physical activity and anticipatory looks, while a less responsive robot with adult assistance resulted in more positive affect and responsive looks.

A key challenge in developing engaging social robots is creating convincing, autonomous and responsive agents, which users perceive, and treat, as social beings. As a part of the collaborative project: Expressive Agents for Symbiotic Education and Learning (EASEL), this study examines the impact of autonomous response to children's speech, by the humanoid robot Zeno, on their interactions with it as a social entity. Results indicate that robot autonomy and adult assistance during HRI can substantially influence children's behaviour during interaction and their affect after. Children working with a fully-autonomous, responsive robot demonstrated greater physical activity following robot instruction than those working with a less responsive robot, which required adult assistance to interact with. During dialogue with the robot, children working with the fully-autonomous robot also looked towards the robot in anticipation of its vocalisations on more occasions. In contrast, a less responsive robot, requiring adult assistance to interact with, led to greater self-report positive affect and more occasions of children looking to the robot in response to its vocalisations. We discuss the broader implications of these findings in terms of anthropomorphism of social robots and in relation to the overall project strategy to further the understanding of how interactions with social robots could lead to task-appropriate symbiotic relationships.

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