The Child Factor in Child-Robot Interaction: Discovering the Impact of Developmental Stage and Individual Characteristics

TL;DR

The paper tackles Child-Robot Interaction (CRI) by foregrounding the child factor through child development theories, arguing that both developmental stage and individual differences shape CRI outcomes. It reviews CRI literature in healthcare and education, highlighting widespread short-term studies with mixed cognitive gains and the limited generalizability of results. The authors advocate for a systemic integration of child psychology into CRI design, emphasizing age- and trait-sensitive task content, long-term autonomous robots, and collaborative design with child development experts. This perspective aims to yield more engaging, sustainable CRI scenarios and clearer experimental designs that better support children's developmental goals.

Abstract

Social robots, owing to their embodied physical presence in human spaces and the ability to directly interact with the users and their environment, have a great potential to support children in various activities in education, healthcare and daily life. Child-Robot Interaction (CRI), as any domain involving children, inevitably faces the major challenge of designing generalized strategies to work with unique, turbulent and very diverse individuals. Addressing this challenging endeavor requires to combine the standpoint of the robot-centered perspective, i.e. what robots technically can and are best positioned to do, with that of the child-centered perspective, i.e. what children may gain from the robot and how the robot should act to best support them in reaching the goals of the interaction. This article aims to help researchers bridge the two perspectives and proposes to address the development of CRI scenarios with insights from child psychology and child development theories. To that end, we review the outcomes of the CRI studies, outline common trends and challenges, and identify two key factors from child psychology that impact child-robot interactions, especially in a long-term perspective: developmental stage and individual characteristics. For both of them we discuss prospective experiment designs which support building naturally engaging and sustainable interactions.

Figures (5)

• Figure 1: Age distribution histogram, which shows how often children of a certain age participated in the studies from Table \ref{['tab:survey']}.
• Figure 2: Interaction time with the robot in one session (blue line) and cumulatively over multiple sessions ("Total interaction time", orange dots). This figure illustrates the studies from Table \ref{['tab:survey']}, ordered by how long children interacted with the robot. The last three values in the total interaction time plot (600, 960 and 2250 minutes, indicated by the black arrow) are omitted for better readability. As the graph shows, nearly half of the studies envision a single session, lasting max. 25 minutes, while longer ones envision multiple sessions, each lasting up to 50 minutes.
• Figure 3: Interaction modes in the reviewed studies, shown separately for the single-session and multi-session scenarios.
• Figure 4: Robots used in the reviewed studies.
• Figure 5: Illustrations from some of the child-robot interaction studies reviewed in this work. Top left: Michaud et al. 2005 michaud2005autonomous ("Roball"), top right: Vinoo et al. 2021 vinoo2021design, middle left: Tanaka et al. 2015 tanaka2015pepper, middle right: Yadollahi et al. 2018 yadollahi2018deictic, bottom: Nasir et al. 2020 nasir2020positive.