自闭症儿童的可预测机器人——机器人行为的差异、自闭症儿童特征的特质和儿童-机器人的参与

Bob R. Schadenberg, D. Reidsma, V. Evers, Daniel P. Davison, Jamy J. Li, D. Heylen, Carlos Neves, P. Alvito, Jie Shen, M. Pantic, Björn Schuller, N. Cummins, Vlad Olaru, C. Sminchisescu, Snezana Babovic Dimitrijevic, Suncica Petrovic, A. Baranger, Alria Williams, A. Alcorn, E. Pellicano
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引用次数: 6

摘要

可预测性对自闭症患者来说很重要,而机器人被认为可以满足这一需求,因为它们可以被编程为可预测的,并引发社会互动。设计用于社交技能学习的机器人辅助干预的有效性可能取决于机器人的可预测性、学习参与度和不同自闭症儿童之间的个体差异之间的相互作用。为了更好地理解这种相互作用,我们报告了一项研究,其中24名自闭症儿童参加了机器人辅助干预。我们操纵了机器人行为的变化,作为改变可预测性的一种方式,并测量了孩子们的行为参与、视觉注意力以及他们的个人因素。我们发现,孩子们会继续在行为上参与活动,但随着时间的推移,当机器人难以预测时,他们可能会开始减少对活动相关位置的视觉关注。相反,他们开始越来越多地把目光从经济活动上移开。最终,这可能会对学习产生负面影响,特别是对于具有视觉成分的任务。此外,自闭症特征的严重程度和语言表达能力对行为投入有显著影响。我们认为我们的研究结果是初步的证据,证明机器人的可预测性是让孩子们保持学习状态的重要因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictable Robots for Autistic Children—Variance in Robot Behaviour, Idiosyncrasies in Autistic Children’s Characteristics, and Child–Robot Engagement
Predictability is important to autistic individuals, and robots have been suggested to meet this need as they can be programmed to be predictable, as well as elicit social interaction. The effectiveness of robot-assisted interventions designed for social skill learning presumably depends on the interplay between robot predictability, engagement in learning, and the individual differences between different autistic children. To better understand this interplay, we report on a study where 24 autistic children participated in a robot-assisted intervention. We manipulated the variance in the robot’s behaviour as a way to vary predictability, and measured the children’s behavioural engagement, visual attention, as well as their individual factors. We found that the children will continue engaging in the activity behaviourally, but may start to pay less visual attention over time to activity-relevant locations when the robot is less predictable. Instead, they increasingly start to look away from the activity. Ultimately, this could negatively influence learning, in particular for tasks with a visual component. Furthermore, severity of autistic features and expressive language ability had a significant impact on behavioural engagement. We consider our results as preliminary evidence that robot predictability is an important factor for keeping children in a state where learning can occur.
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