Child-Robot Relationship Formation: A Narrative Review of Empirical Research

Do preschoolers trust a competent robot pointer?

How young children learn from different informants has been widely studied. However, most studies investigate how children learn verbally conveyed information. Furthermore, most studies investigate how children learn from humans. This study sought to investigate how 3-year-old children learn from, and come to trust, a competent robot versus an incompetent human when competency is established using a pointing paradigm. During an induction phase, a robot informant pointed at a toy inside a transparent box, whereas a human pointed at an empty box. During the test phase, both agents pointed at opaque boxes. We found that young children asked the robot for help to locate a hidden toy more than the human (ask questions) and correctly identified the robot to be accurate (judgment questions). However, children equally endorsed the locations pointed at by both the robot and the human (endorse questions). This suggests that 3-year-olds are sensitive to the epistemic characteristics of the informant even when its displayed social properties are minimal.

The Power of Robot-mediated Play: Forming Friendships and Expressing Identity

Tele-operated collaborative robots are used by many children for academic learning. However, as child-directed play is important for social-emotional learning, it is also important to understand how robots can facilitate play. In this article, we present findings from an analysis of a national, multi-year case study, where we explore how 53 children in grades K-12 (n = 53) used robots for self-directed play activities. The contributions of this article are as follows. First, we present empirical data on novel play scenarios that remote children created using their tele-operated robots. These play scenarios emerged in five categories of play: physical, verbal, visual, extracurricular, and wished-for play. Second, we identify two unique themes that emerged from the data-robot-mediated play as a foundational support of general friendships and as a foundational support of self-expression and identity. Third, our work found that robot-mediated play provided benefits similar to in-person play. Findings from our work will inform novel robot and HRI design for tele-operated and social robots that facilitate self-directed play. Findings will also inform future interdisciplinary studies on robot-mediated play.

Ethical Considerations in Child-Robot Interactions

Social robots hold promise in augmenting education, rehabilitative care, and leisure activities for children. Despite findings suggesting various benefits of social robot use in schools, clinics, and homes, stakeholders have voiced concerns about the potential social and emotional effects of children engaging in long-term interactions with robots. Given the challenges of conducting large long-term studies of child-robot interaction (CRI), little is known about the impact of CRI on children's socio-emotional development. Here we summarize the literature on predictions and expectations of teachers, parents, therapists, and children regarding the effects of CRI on children's socio-emotional functioning and skill building. We then highlight the limited body of empirical research examining how CRI affects children's social behavior and emotional expression, and we provide a summary of available questionnaires for measuring socio-emotional constructs relevant to CRI. We conclude with design recommendations for research studies aimed at better understanding the effects of CRI, before social robots become more ubiquitous. This review is relevant to researchers, educators, roboticists, and clinicians interested in designing and using social robots with developmental populations.

Have You Ever Seen a Robot? An Analysis of Children's Drawings Between Technology and Science Fiction

Technologies have become an essential part of the daily life of our children. Consequently, artifacts that imply the early adoption of abstract thinking affect the imagination of children and young people in relation to the world of technology, now much more than they did in the past. With the emerging importance of robots in many aspects of our everyday lives, the goal of this study is to investigate which mental representations children have about robots. To this end, drawings from 104 children aged between 7 and 12 years old were used as a map of representations, considering the drawings as a proxy capable of evoking learned or emerging mental frameworks. The drawings were analyzed in several steps: they were first labeled using binary descriptors and then classified using clustering methods based on Hamming distances between drawings. Finally, questionnaire items covering children's perceptions about robots were analyzed for each of the resulting cluster separately to identify differences between them. The results show that there are relationships between the way children draw robots and their perception about robots' capabilities as well as their aspirations to pursue a career in science. These findings can provide meaningful insights into how to design educational robots and learning activities for children to learn with and about robots.

Human–Robot Cooperation in Economic Games: People Show Strong Reciprocity but Conditional Prosociality Toward Robots

Understanding how people socially engage with robots is becoming increasingly important as these machines are deployed in social settings. We investigated 70 participants’ situational cooperation tendencies towards a robot using prisoner’s dilemma games, manipulating the incentives for cooperative decisions to be high or low. We predicted that people would cooperate more often with the robot in high-incentive conditions. We also administered subjective measures to explore the relationships between people’s cooperative decisions and their social value orientation, attitudes towards robots, and anthropomorphism tendencies. Our results showed incentive structure did not predict human cooperation overall, but did influence cooperation in early rounds, where participants cooperated significantly more in high-incentive conditions. Exploratory analyses further revealed that participants played a tit-for-tat strategy against the robot (whose decisions were random), and only behaved prosocially toward the robot when they had achieved high scores themselves. These findings highlight how people make social decisions when their individual profit is at odds with collective profit with a robot, and advance understanding on human–robot interactions in collaborative contexts.

Developments in the design and delivery of self-management support for children and young people with diabetes: A narrative synthesis of systematic reviews

AIMS

Facilitated self-management support programmes have become central to the treatment of chronic diseases including diabetes. For many children and young people with diabetes (CYPD), the impact on glycated haemoglobin (HbA_1c ) and a range of self-management behaviours promised by these programmes remain unrealised. This warrants an appraisal of current thinking and the existing evidence to guide the development of programmes better targeted at this age group.

METHODS

Create a narrative review of systematic reviews produced in the last 3 years that have explored the impact on CYPD of the four key elements of self-management support programmes: education, instruction and advice including peer support; psychological counselling via a range of therapies; self-monitoring, including diaries and telemetric devices; and telecare, the technology-enabled follow-up and support by healthcare providers.

RESULTS

Games and gamification appear to offer a promising means of engaging and educating CYPD. Psychological interventions when delivered by trained practitioners, appear to improve HbA_1c and quality of life although effect sizes were small. Technology-enabled interactive diaries can increase the frequency of self-monitoring and reduce levels of HbA_1c . Telecare provided synchronously via telephone produced significant improvements in HbA_1c .

CONCLUSIONS

The cost-effective flexibility of increasing the reliance on technology is an attractive proposition; however, there are resource implications for digital connectivity in underserved populations. The need remains to improve the understanding of which elements of each component are most effective in a particular context, and how to optimise the influence and input of families, caregivers and peers.

Preschoolers' anthropomorphizing of robots: Do human-like properties matter?

Prior work has yielded contradicting evidence regarding the age at which children consistently and correctly categorize things as living or non-living. The present study tested children's animacy judgments about robots with a Naïve Biology task. In the Naïve Biology task, 3- and 5-year-olds were asked if robots, animals, or artifacts possessed mechanical or biological internal parts. To gauge how much children anthropomorphize robots in comparison to animals and artifacts, children also responded to a set of interview questions. To examine the role of morphology, two robots were used: a humanoid robot (Nao) and a non-humanoid robot (Dash). To investigate the role of dynamic characteristics, children saw one robot behave in a goal-directed manner (i.e., moving towards a ball) and one robot exhibit non-goal-directed behavior (i.e., moving away from a ball). Children of both age groups correctly attributed biological insides to the animal and mechanical insides to the artifact. However, 3-year-olds seemed confused about what belonged inside both robots and assigned biological and mechanical insides equally. In contrast, 5-year-olds correctly assigned mechanical insides to both robots, regardless of the robot's morphology or goal-directedness. Regarding the Animacy Interview, 3-year-olds performed at chance level when asked about the animacy of robots, animals, and artifacts. In contrast, 5-year-olds correctly attributed animacy to animals and accurately refrained from anthropomorphizing artifacts and the non-humanoid robot Dash. However, 5-year-olds performed at chance for Nao, suggesting they may be confused about the psychological properties of a human-looking robot. Taken together, these findings reveal a developmental transition during the preschool years in the attribution of biological and psychological properties to social robot.

Bond formation with pet-robots: An integrative approach

The challenge of long-term interaction between humans and robots is still a bottleneck in service robot research. To gain an understanding of sustained relatedness with robots, this study proposes a conceptual framework for bond formation. More specifically, it addresses the dynamics of children bonding with robotic pets as the basis for certain services in healthcare and education. The framework presented herein offers an integrative approach and draws from theoretical models and empirical research in Human Robot Interaction and also from related disciplines that investigate lasting relationships, such as human-animal affiliation and attachment to everyday objects. The research question is how children’s relatedness to personified technologies occurs and evolves and what underpinning processes are involved. The subfield of research is child-robot interaction, within the boundaries of social psychology, where the robot is viewed as a social agent, and human-system interaction, where the robot is regarded as an artificial entity. The proposed framework envisions bonding with pet-robots as a socio-affective process towards lasting connectedness and emotional involvement that evolves through three stages: first encounter, short-term interaction and lasting relationship. The stages are characterized by children’s behaviors, cognitions and feelings that can be identified, measured and, maybe more importantly, managed. This model aims to integrate fragmentary and heterogeneous knowledge into a new perspective on the impact of robots in close and enduring proximity to children.

Getting acquainted: First steps for child-robot relationship formation

In this article we discuss two studies of children getting acquainted with an autonomous socially assistive robot. The success of the first encounter is key for a sustainable long-term supportive relationship. We provide four validated behavior design elements that enable the robot to robustly get acquainted with the child. The first are five conversational patterns that allow children to comfortably self-disclose to the robot. The second is a reciprocation strategy that enables the robot to adequately respond to the children’s self-disclosures. The third is a ‘how to talk to me’ tutorial. The fourth is a personality profile for the robot that creates more rapport and comfort between the child and the robot. The designs were validated with two user studies (N₁ = 30, N₂ = 75, 8–11 years. o. children). The results furthermore showed similarities between how children form relationships with people and how children form relationships with robots. Most importantly, self-disclosure, and specifically how intimate the self-disclosures are, is an important predictor for the success of child-robot relationship formation. Speech recognition errors reduces the intimacy and feeling similar to the robot increases the intimacy of self-disclosures.

The Design and Observed Effects of Robot-Performed Manual Gestures: A Systematic Review

Communication using manual (hand) gestures is considered a defining property of social robots, and their physical embodiment and presence, therefore we see a need for a comprehensive overview of the state of the art in social robots that use gestures. This systematic literature review aims to address this need by (1) describing the gesture production process of a social robot, including the design and planning steps, and (2) providing a survey of the effects of robot-performed gestures on human-robot interactions in a multitude of domains. We identify patterns and themes from the existing body of literature, resulting in nine outstanding questions for research on robot-performed gestures regarding: developments in sensor technology and AI, structuring the gesture design and evaluation process, the relationship between physical appearance and gestures, the effects of planning on the overall interaction, standardizing measurements of gesture ‘quality’, individual differences, gesture mirroring, whether human-likeness is desirable, and universal accessibility of robots. We also reflect on current methodological practices in studies of robot-performed gestures, and suggest improvements regarding replicability, external validity, measurement instruments used, and connections with other disciplines. These outstanding questions and methodological suggestions can guide future work in this field of research.

Lessons Learned About Designing and Conducting Studies From HRI Experts

The field of human-robot interaction (HRI) research is multidisciplinary and requires researchers to understand diverse fields including computer science, engineering, informatics, philosophy, psychology, and more disciplines. However, it is hard to be an expert in everything. To help HRI researchers develop methodological skills, especially in areas that are relatively new to them, we conducted a virtual workshop, Workshop Your Study Design (WYSD), at the 2021 International Conference on HRI. In this workshop, we grouped participants with mentors, who are experts in areas like real-world studies, empirical lab studies, questionnaire design, interview, participatory design, and statistics. During and after the workshop, participants discussed their proposed study methods, obtained feedback, and improved their work accordingly. In this paper, we present 1) Workshop attendees’ feedback about the workshop and 2) Lessons that the participants learned during their discussions with mentors. Participants’ responses about the workshop were positive, and future scholars who wish to run such a workshop can consider implementing their suggestions. The main contribution of this paper is the lessons learned section, where the workshop participants contributed to forming this section based on what participants discovered during the workshop. We organize lessons learned into themes of 1) Improving study design for HRI, 2) How to work with participants - especially children -, 3) Making the most of the study and robot’s limitations, and 4) How to collaborate well across fields as they were the areas of the papers submitted to the workshop. These themes include practical tips and guidelines to assist researchers to learn about fields of HRI research with which they have limited experience. We include specific examples, and researchers can adapt the tips and guidelines to their own areas to avoid some common mistakes and pitfalls in their research.

Do Robotic Tutors Compromise the Social-Emotional Development of Children?

Social robots are reported to hold great potential for education. However, both scholars and key stakeholders worry about children’s social-emotional development being compromised. In aiming to provide new insights into the impact that social robots can have on the social-emotional development of children, the current study interviewed teachers who use social robots in their day-to-day educational practice. The results of our interviews with these experienced teachers indicate that the social robots currently used in education pose little threat to the social-emotional development of children. Children with special needs seem to be more sensitive to social-affective bonding with a robot compared to regular children. This bond seems to have positive effects in enabling them to more easily connect with their human peers and teachers. However, when robots are being introduced more regularly, daily, without the involvement of a human teacher, new issues could arise. For now, given the current state of technology and the way social robots are being applied, other (ethical) issues seem to be more urgent, such as privacy, security and the workload of teachers. Future studies should focus on these issues first, to ensure a safe and effective educational environment for both children and teachers.

Robot-Fish Interaction Helps to Trigger Social Buffering in Neon Tetras: The Potential Role of Social Robotics in Treating Anxiety

The emerging field of social robotics comprises several multidisciplinary applications. Anxiety and stress therapies can greatly benefit by socio-emotional support provided by robots, although the intervention of social robots as effective treatment needs to be fully understood. Herein, Paracheirodon innesi, a social fish species, was used to interact with a robotic fish to understand intrinsic and extrinsic mechanisms causing anxiety, and how social robots can be effectively used as anxiety treatments. In the first experiment we tested the effects of a conspecific-mimicking robot on the fish tendency to swim in the bottom when transferred in a new tank. Here, P. innesi spent a significantly longer time in the upper section of the test tank when the robotic fish was present, clearly indicating a reduction of their state of anxiety due to social stimuli. The second experiment was based on a modification of the dark/light preference test, since many teleost fish are scototactic, preferring dark environments. However, when the robotic fish was placed in the white half of the test tank, P. innesi individuals swam longer in this section otherwise aversive. Social support provided by the robotic fish in both experiments produced a better recovery from anxiety due to social buffering, a phenomenon regulated by specific neural mechanisms. This study provides new insights on the evolution and mechanisms of social buffering to reduce anxiety, as well as on the use of social robots as an alternative to traditional approaches in treating anxiety symptoms.

Connect With Me. Exploring Influencing Factors in a Human-Technology Relationship Based on Regular Chatbot Use

Companion technologies, such as social robots and conversational chatbots, take increasing responsibility for daily tasks and support our physical and mental health. Especially in the domain of healthcare, where technologies are often applied for long-term use, our experience with and relationship to such technologies become ever more relevant. Based on a 2-week interaction period with a conversational chatbot, our study (N = 58) explores the relationship between humans and technology. In particular, our study focuses on felt social connectedness of participants to the technology, possibly related characteristics of technology and users (e.g., individual tendency to anthropomorphize, individual need to belong), as well as possibly affected outcome variables (e.g., desire to socialize with other humans). The participants filled in short daily and 3 weekly questionnaires. Results showed that interaction duration and intensity positively predicted social connectedness to the chatbot. Thereby, perceiving the chatbot as anthropomorphic mediated the interrelation of interaction intensity and social connectedness to the chatbot. Also, the perceived social presence of the chatbot mediated the relationship between interaction duration as well as interaction intensity and social connectedness to the chatbot. Characteristics of the user did not affect the interrelations of chatbot interaction duration or intensity and perceived anthropomorphism or social presence. Furthermore, we did not find a negative correlation between felt social connectedness of users to the technology and their desire to socialize with other humans. In sum, our findings provide both theoretical and practical contributions. Our study suggests that regular interaction with a technology can foster feelings of social connectedness, implying transferability of dynamics known from interpersonal interaction. Moreover, social connectedness could be supported by technology design that facilitates perceptions of anthropomorphism and social presence. While such means could help to establish an intense relationship between users and technology and long-term engagement, the contexts in which anthropomorphic design is, actually, the means of choice should be carefully reflected. Future research should examine individual and societal consequences to foster responsible technology development in healthcare and beyond.

Hurry Up, We Need to Find the Key! How Regulatory Focus Design Affects Children's Trust in a Social Robot

In educational scenarios involving social robots, understanding the way robot behaviors affect children's motivation to achieve their learning goals is of vital importance. It is crucial for the formation of a trust relationship between the child and the robot so that the robot can effectively fulfill its role as a learning companion. In this study, we investigate the effect of a regulatory focus design scenario on the way children interact with a social robot. Regulatory focus theory is a type of self-regulation that involves specific strategies in pursuit of goals. It provides insights into how a person achieves a particular goal, either through a strategy focused on "promotion" that aims to achieve positive outcomes or through one focused on "prevention" that aims to avoid negative outcomes. In a user study, 69 children (7-9 years old) played a regulatory focus design goal-oriented collaborative game with the EMYS robot. We assessed children's perception of likability and competence and their trust in the robot, as well as their willingness to follow the robot's suggestions when pursuing a goal. Results showed that children perceived the prevention-focused robot as being more likable than the promotion-focused robot. We observed that a regulatory focus design did not directly affect trust. However, the perception of likability and competence was positively correlated with children's trust but negatively correlated with children's acceptance of the robot's suggestions.

Children’s Imaginaries of Robots for Playing With

Children with severe motor impairment due to cerebral palsy have difficulties engaging in play, although they want to play games that typically developing children play. The barriers imposed by motor impairments against engaging in play can be addressed through the use of robots. We aim to identify how children, who have extensive experience of play, imagine what a robot is and what features would make a robot good to play with. Using a qualitative description design, 19 children from urban and rural settings participated in focus groups to draw and talk about the robots they would like to exist. The data were coded and analyzed using a summative approach to content analysis. The findings revealed that the children imagined that a good robot to play with is one that has an anthropomorphic appearance, is tough and strong, has controls, and that is able to move, grab, speak, and play popular children’s games. In particular, the girls imagined that robots should be able to express positive emotions towards children. Age, gender, culture, and the physical environment in which the children lived influenced what they expected to find in a robot for playing with and how they imagined child–robot interactions.

The wizard and I: How transparent teleoperation and self-description (do not) affect children’s robot perceptions and child-robot relationship formation

It has been well documented that children perceive robots as social, mental, and moral others. Studies on child-robot interaction may encourage this perception of robots, first, by using a Wizard of Oz (i.e., teleoperation) set-up and, second, by having robots engage in self-description. However, much remains unknown about the effects of transparent teleoperation and self-description on children’s perception of, and relationship formation with a robot. To address this research gap initially, we conducted an experimental study with a 2 × 2 (teleoperation: overt/covert; self-description: yes/no) between-subject design in which 168 children aged 7–10 interacted with a Nao robot once. Transparency about the teleoperation procedure decreased children’s perceptions of the robot’s autonomy and anthropomorphism. Self-description reduced the degree to which children perceived the robot as being similar to themselves. Transparent teleoperation and self-description affected neither children’s perceptions of the robot’s animacy and social presence nor their closeness to and trust in the robot.

A Meta-analysis on Children’s Trust in Social Robots

Although research on children’s trust in social robots is increasingly growing in popularity, a systematic understanding of the factors which influence children’s trust in robots is lacking. In addition, meta-analyses in child–robot-interaction (cHRI) have yet to be popularly adopted as a method for synthesising results. We therefore conducted a meta-analysis aimed at identifying factors influencing children’s trust in robots. We constructed four meta-analytic models based on 20 identified studies, drawn from an initial pool of 414 papers, as a means of investigating the effect of robot embodiment and behaviour on both social and competency trust. Children’s pro-social attitudes towards social robots were also explored. There was tentative evidence to suggest that more human-like attributes lead to less competency trust in robots. In addition, we found a trend towards the type of measure that was used (subjective or objective) influencing the direction of effects for social trust. The meta-analysis also revealed a tendency towards under-powered designs, as well as variation in the methods and measures used to define trust. Nonetheless, we demonstrate that it is still possible to perform rigorous analyses despite these challenges. We also provide concrete methodological recommendations for future research, such as simplifying experimental designs, conducting a priori power analyses and clearer statistical reporting.

Exploring the Role of Trust and Expectations in CRI Using In-the-Wild Studies

Studying interactions of children with humanoid robots in familiar spaces in natural contexts has become a key issue for social robotics. To fill this need, we conducted several Child–Robot Interaction (CRI) events with the Pepper robot in Polish and Japanese kindergartens. In this paper, we explore the role of trust and expectations towards the robot in determining the success of CRI. We present several observations from the video recordings of our CRI events and the transcripts of free-format question-answering sessions with the robot using the Wizard-of-Oz (WOZ) methodology. From these observations, we identify children’s behaviors that indicate trust (or lack thereof) towards the robot, e.g., challenging behavior of a robot or physical interactions with it. We also gather insights into children’s expectations, e.g., verifying expectations as a causal process and an agency or expectations concerning the robot’s relationships, preferences and physical and behavioral capabilities. Based on our experiences, we suggest some guidelines for designing more effective CRI scenarios. Finally, we argue for the effectiveness of in-the-wild methodologies for planning and executing qualitative CRI studies.

Relationship Development with Humanoid Social Robots: Applying Interpersonal Theories to Human-Robot Interaction

Humanoid social robots (HSRs) are human-made technologies that can take physical or digital form, resemble people in form or behavior to some degree, and are designed to interact with people. A common assumption is that social robots can and should mimic humans, such that human-robot interaction (HRI) closely resembles human-human (i.e., interpersonal) interaction. Research is often framed from the assumption that rules and theories that apply to interpersonal interaction should apply to HRI (e.g., the computers are social actors framework). Here, we challenge these assumptions and consider more deeply the relevance and applicability of our knowledge about personal relationships to relationships with social robots. First, we describe the typical characteristics of HSRs available to consumers currently, elaborating characteristics relevant to understanding social interactions with robots such as form anthropomorphism and behavioral anthropomorphism. We also consider common social affordances of modern HSRs (persistence, personalization, responsiveness, contingency, and conversational control) and how these align with human capacities and expectations. Next, we present predominant interpersonal theories whose primary claims are foundational to our understanding of human relationship development (social exchange theories, including resource theory, interdependence theory, equity theory, and social penetration theory). We consider whether interpersonal theories are viable frameworks for studying HRI and human-robot relationships given their theoretical assumptions and claims. We conclude by providing suggestions for researchers and designers, including alternatives to equating human-robot relationships to human-human relationships.

Pragmatics in the False-Belief Task: Let the Robot Ask the Question!

The poor performances of typically developing children younger than 4 in the first-order false-belief task "Maxi and the chocolate" is analyzed from the perspective of conversational pragmatics. An ambiguous question asked by an adult experimenter (perceived as a teacher) can receive different interpretations based on a search for relevance, by which children according to their age attribute different intentions to the questioner, within the limits of their own meta-cognitive knowledge. The adult experimenter tells the child the following story of object-transfer: "Maxi puts his chocolate into the green cupboard before going out to play. In his absence, his mother moves the chocolate from the green cupboard to the blue one." The child must then predict where Maxi will pick up the chocolate when he returns. To the child, the question from an adult (a knowledgeable person) may seem surprising and can be understood as a question of his own knowledge of the world, rather than on Maxi's mental representations. In our study, without any modification of the initial task, we disambiguate the context of the question by (1) replacing the adult experimenter with a humanoid robot presented as "ignorant" and "slow" but trying to learn and (2) placing the child in the role of a "mentor" (the knowledgeable person). Sixty-two typical children of 3 years-old completed the first-order false belief task "Maxi and the chocolate," either with a human or with a robot. Results revealed a significantly higher success rate in the robot condition than in the human condition. Thus, young children seem to fail because of the pragmatic difficulty of the first-order task, which causes a difference of interpretation between the young child and the experimenter.