Robots educate in style: The effect of context and non-verbal behaviour on children's perceptions of warmth and competence
Robots educate in style: The effect of context and non-verbal behaviour on children's perceptions of warmth and competence
复制标题
机器人风格教育：情境和非语言行为对儿童温暖和能力感知的影响
DOI：
10.1109/roman.2017.8172341
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Mark Antonius Neerincx
中科院分区：
文献类型：
--
作者：
Rifca Peters;J. Broekens;Mark Antonius Neerincx
社交机器人正在进入私人和公共领域，在那里它们与非技术用户进行社交互动。这就要求机器人具有社交互动性和智能性，包括表现出适当社交行为的能力。在情感建模方面取得了进展。然而，对行为风格的研究还不太彻底;没有全面的，有效的模型存在的非语言行为来表达风格的人机交互。基于文献调查，我们创建了一个模型的非语言行为来表达高/低的温暖和能力-两个维度，有助于教学风格。在感知研究中，我们评估了这个模型应用于NAO机器人在荷兰的小学和糖尿病营地讲课。为此，我们根据专家评级开发了一种测量感知温暖、能力、主导地位和归属感的工具。我们表明，即使是微妙的操纵机器人的行为影响儿童的机器人的温暖和能力的水平的看法。
Social robots are entering the private and public domain where they engage in social interactions with nontechnical users. This requires robots to be socially interactive and intelligent, including the ability to display appropriate social behaviour. Progress has been made in emotion modelling. However, research into behaviour style is less thorough; no comprehensive, validated model exists of non-verbal behaviours to express style in human-robot interactions. Based on a literature survey, we created a model of non-verbal behaviour to express high/low warmth and competence — two dimensions that contribute to teaching style. In a perception study, we evaluated this model applied to a NAO robot giving a lecture at primary schools and a diabetes camp in the Netherlands. For this, we developed, based on expert ratings, an instrument measuring perceived warmth, competence, dominance and affiliation. We show that even subtle manipulations of robot behaviour influence children's perceptions of the robot's level of warmth and competence.