Revisiting the video deficit in technology-saturated environments: Successful imitation from people, screens, and social robots.

The "video deficit" is a well-documented effect whereby children learn less well about information delivered via a screen than the same information delivered in person. Research suggests that increasing social contingency may ameliorate this video deficit. The current study instantiated social contingency to screen-based information by embodying the screen within a socially interactive robot presented to urban Australian children with frequent exposure to screen-based communication. We failed to document differences between 22- to 26-month-old children's (N = 80) imitation of screen-based information embedded in a social robot and in-person humans. Furthermore, we did not replicate the video deficit with children imitating at similar levels regardless of the presentation medium. This failure to replicate supports the findings of a recent meta-analysis of video deficit research whereby there appears to be a steady decrease over time in the magnitude of the video deficit effect. We postulate that, should the video deficit effect be truly dwindling in effect size, the video deficit may soon be a historical artifact as children begin perceiving technology as relevant and meaningful in everyday life more and more. This research finds that observational-based learning material can be successfully delivered in person, via a screen, or via a screen embedded in a social robot.

A social robot-based platform for health behavior change toward prevention of childhood obesity.

Childhood obesity is a major public health challenge which is linked with the occurrence of diseases such as diabetes and cancer. The COVID-19 pandemic has forced changes to the lifestyle behaviors of children, thereby making the risk of developing obesity even greater. Novel preventive tools and approaches are required to fight childhood obesity. We present a social robot-based platform which utilizes an interactive motivational strategy in communication with children, collects self-reports through the touch of tangible objects, and processes behavioral data, aiming to: (a) screen and assess the behaviors of children in the dimensions of physical activity, diet, and education, and (b) recommend individualized goals for health behavior change. The platform was integrated through a microservice architecture within a multi-component system targeting childhood obesity prevention. The platform was evaluated in an experimental study with 30 children aged 9-12 years in a real-life school setting, showing children's acceptance to use it, and an 80% success rate in achieving weekly personal health goals recommended by the social robot-based platform. The results provide preliminary evidence on the implementation feasibility and potential of the social robot-based platform toward the betterment of children's health behaviors in the context of childhood obesity prevention. Further rigorous longer-term studies are required.

The man and the machine: Do children learn from and transmit tool-use knowledge acquired from a robot in ways that are comparable to a human model?

Robots are an increasingly prevalent presence in children's lives. However, little is known about the ways in which children learn from robots and whether they do so in the same way as they learn from humans. To investigate this, we adapted a previously established imitation paradigm centered on inefficient tool use. Children (3- to 6-year-olds; N = 121) were measured on their acquisition and transmission of normative knowledge modeled by a human or a robot. Children were more likely to adopt use of a normative tool and to transmit this knowledge to another when shown how to do so by the human than when shown how to do so by the robot. Older children (5- and 6-year-olds) were less likely than younger children (3- and 4-year-olds) to select the normative tool. Our findings suggest that preschool children are capable of copying and transmitting normative techniques from both human and robot models, albeit at different rates and dependent on age.

Can a robot teach me that? Children's ability to imitate robots.

Commensurate with constant technological advances, social robots are increasingly anticipated to enter homes and classrooms; however, little is known about the efficacy of social robots as teaching tools. To investigate children's learning from robots, 1- to 3-year-olds observed either a human or a robot demonstrate two goal-directed object manipulation tasks and were then given the opportunity to act on the objects. Children exhibited less imitation from robotic models that varied with task complexity and age, a phenomenon we term the "robot deficit." In addition, the more children engaged with the robot prior to administration of the imitation task, the more likely they were to replicate the robot's actions. These findings document how children are able to learn from robots but that ongoing design of robotic platforms needs to be oriented to developing more socially engaging means of interacting.

Integration of a Social Robot in a Pedagogical and Logopedic Intervention with Children: A Case Study.

The effectiveness of social robots such as NAO in pedagogical therapies presents a challenge. There is abundant literature focused on therapies using robots with children with autism, but there is a gap to be filled in other educational different needs. This paper describes an experience of using a NAO as an assistant in a logopedic and pedagogical therapy with children with different needs. Even if the initial robot architecture is based on genericbehaviors, the loading and execution time for each specific requirement and the needs of each child in therapy, made it necessary to develop "Adaptive Behaviors". These evolve into an adaptive architecture, appliedto the engineer-therapist-child interaction, requiring the engineer-programmer to be always present during the sessions. Benefits from the point of view of the therapist and the children and the acceptance of NAO in therapy are shown. A robot in speech-therapy sessions can play a positive role in several logopedic aspectsserving as a motivating factor for the children.Future works should be oriented in developing intelligent algorithms so as to eliminate the presence of the engineer-programmer in the sessions. Additional work proposals should consider deepening the psychological aspects of using humanoid robots in educational therapy.

Children's perceptions of the moral worth of live agents, robots, and inanimate objects.

This study examined children's moral concern for robots relative to living and nonliving entities. Children (4-10 years of age, N = 126) watched videos of six different entities having a box placed over them that was subsequently struck by a human hand. Children were subsequently asked to rate the moral worth of each agent relating to physical harm. Children afforded robotic entities less moral concern than living entities but afforded them more moral concern than nonliving entities, and these effects became more pronounced with age. Children's tendency to ascribe mental life to robotic and nonliving entities (but not living entities) predicted moral concern for these entities. However, when asked to make moral judgments relating to giving the agent away, children did not distinguish between nonliving and robotic agents and no age-related changes were identified. Moreover, the tendency to ascribe mental life was predictive of moral concern only for some agents but not others. Overall, the findings suggest that children consider robotic entities to occupy a middle moral ground between living and nonliving entities and that this effect is partly explained by the tendency to ascribe mental life to such agents. They also demonstrate that moral worth is a complex multifaceted concept that does not demonstrate a clear pattern across different ontological categories.

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 ubiquitous. This review is relevant to researchers, educators, roboticists, and clinicians interested in designing and using social robots with developmental populations.

Utilizing an Emotional Robot Capable of Lip-Syncing in Robot-Assisted Speech Therapy Sessions for Children with Language Disorders.

This study scrutinizes the impacts of utilizing a socially assistive robot, the RASA robot, during speech therapy sessions for children with language disorders. Two capabilities were developed for the robotic platform to enhance children-robot interactions during speech therapy interventions: facial expression communication (containing recognition and expression) and lip-syncing. Facial expression recognition was conducted by training several well-known CNN architectures on one of the most extensive facial expressions databases, the AffectNet database, and then modifying them using the transfer learning strategy performed on the CK+ dataset. The robot's lip-syncing capability was designed in two steps. The first step was concerned with designing precise schemes of the articulatory elements needed during the pronunciation of the Persian phonemes (i.e., consonants and vowels). The second step included developing an algorithm to pronounce words by disassembling them into their components (including consonants and vowels) and then morphing them into each other successively. To pursue the study's primary goal, two comparable groups of children with language disorders were considered, the intervention and control groups. The intervention group attended therapy sessions in which the robot acted as the therapist's assistant, while the control group only communicated with the human therapist. The study's first purpose was to compare the children's engagement while playing a mimic game with the affective robot and the therapist, conducted via video coding. The second objective was to assess the efficacy of the robot's presence in the speech therapy sessions alongside the therapist, accomplished by administering the Persian Test of Language Development, Persian TOLD. According to the first scenario, playing with the affective robot is more engaging than playing with the therapist. Furthermore, the statistical analysis of the study's results indicates that participating in robot-assisted speech therapy (RAST) sessions enhances children with language disorders' achievements in comparison with taking part in conventional speech therapy interventions.

Social robots as effective language tutors for children: empirical evidence from neuroscience.

The aim of the current study was to investigate children's brain responses to robot-assisted language learning. EEG brain signals were collected from 41 Japanese children who learned French vocabularies in two groups; half of the children learned new words from a social robot that narrated a story in French using animations on a computer screen (Robot group) and the other half watched the same animated story on the screen but only with a voiceover narration and without the robot (Display group). To examine brain activation during the learning phase, we extracted EEG functional connectivity (FC) which is defined as the rhythmic synchronization of signals recorded from different brain areas. The results indicated significantly higher global synchronization of brain signals in the theta frequency band in the Robot group during the learning phase. Closer inspection of intra-hemispheric and inter-hemispheric connections revealed that children who learned a new language from the robot experienced a stronger theta-band EEG synchronization in inter-hemispheric connections, which has been previously associated with success in second language learning in the neuroscientific literature. Additionally, using a multiple linear regression analysis, it was found that theta-band FC and group assignment were significant predictors of children's language learning with the Robot group scoring higher in the post-interaction word recognition test. These findings provide novel neuroscientific evidence for the effectiveness of social robots as second language tutors for children.

Co-designing the Embodiment of a Minimalist Social Robot to Encourage Hand Hygiene Practises Among Children in India.

We conducted an empirical study to co-design a social robot with children to bring about long-term behavioural changes. As a case study, we focused our efforts to create a social robot to promote handwashing in community settings while adhering to minimalistic design principles. Since cultural views influence design preferences and technology acceptance, we selected forty children from different socio-economic backgrounds across India as informants for our design study. We asked the children to design paper mock-ups using pre-cut geometrical shapes to understand their mental models of such a robot. The children also shared their feedback on the eight resulting different conceptual designs of minimalistic caricatured social robots. Our findings show that children had varied expectations of the robot's emotional intelligence, interactions, and social roles even though it was being designed for a specific context of use. The children unequivocally liked and trusted anthropomorphized caricatured designs of everyday objects for the robot's morphology. Based on these findings, we present our recommendations for the physical and interaction features of a minimalist social robot assimilating the children's inputs and social robot design principles grounded in prior research. Future studies will examine the children's interactions with a built prototype.

Ethical Considerations from Child-Robot Interactions in Under-Resourced Communities.

Recent advancements in socially assistive robotics (SAR) have shown a significant potential of using social robotics to achieve increasing cognitive and affective outcomes in education. However, the deployments of SAR technologies also bring ethical challenges in tandem, to the fore, especially in under-resourced contexts. While previous research has highlighted various ethical challenges that arise in SAR deployment in real-world settings, most of the research has been centered in resource-rich contexts, mainly in developed countries in the 'Global North,' and the work specifically in the educational setting is limited. This research aims to evaluate and reflect upon the potential ethical and pedagogical challenges of deploying a social robot in an under-resourced context. We base our findings on a 5-week in-the-wild user study conducted with 12 kindergarten students at an under-resourced community school in New Delhi, India. We used interaction analysis with the context of learning, education, and ethics to analyze the user study through video recordings. Our findings highlighted four primary ethical considerations that should be taken into account while deploying social robotics technologies in educational settings; (1) language and accent as barriers in pedagogy, (2) effect of malfunctioning, (un)intended harms, (3) trust and deception, and (4) ecological viability of innovation. Overall, our paper argues for assessing the ethical and pedagogical constraints and bridging the gap between non-existent literature from such a context to evaluate better the potential use of such technologies in under-resourced contexts.

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.

Designing for culturally responsive social robots: An application of a participatory framework.

Integrating cultural responsiveness into the educational setting is essential to the success of multilingual students. As social robots present the potential to support multilingual children, it is imperative that the design of social robot embodiments and interactions are culturally responsive. This paper summarizes the current literature on educational robots in culturally diverse settings. We argue the use of the Culturally Localized User Experience (CLUE) Framework is essential to ensure cultural responsiveness in HRI design. We present three case studies illustrating the CLUE framework as a social robot design approach. The results of these studies suggest co-design provides multicultural learners an accessible, nonverbal context through which to provide design requirements and preferences. Furthermore, we demonstrate the importance of key stakeholders (students, parents, and teachers) as essential to ensure a culturally responsive robot. Finally, we reflect on our own work with culturally and linguistically diverse learners and propose three guiding principles for successfully engaging diverse learners as valuable cultural informants to ensure the future success of educational robots.

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 (N 1 = 30, N 2 = 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.

Comparing a Robot Tutee to a Human Tutee in a Learning-By-Teaching Scenario with Children.

Social robots are increasingly being studied in educational roles, including as tutees in learning-by-teaching applications. To explore the benefits and drawbacks of using robots in this way, it is important to study how robot tutees compare to traditional learning-by-teaching situations. In this paper, we report the results of a within-subjects field experiment that compared a robot tutee to a human tutee in a Swedish primary school. Sixth-grade students participated in the study as tutors in a collaborative mathematics game where they were responsible for teaching a robot tutee as well as a third-grade student in two separate sessions. Their teacher was present to provide support and guidance for both sessions. Participants' perceptions of the interactions were then gathered through a set of quantitative instruments measuring their enjoyment and willingness to interact with the tutees again, communication and collaboration with the tutees, their understanding of the task, sense of autonomy as tutors, and perceived learning gains for tutor and tutee. The results showed that the two scenarios were comparable with respect to enjoyment and willingness to play again, as well as perceptions of learning gains. However, significant differences were found for communication and collaboration, which participants considered easier with a human tutee. They also felt significantly less autonomous in their roles as tutors with the robot tutee as measured by their stated need for their teacher's help. Participants further appeared to perceive the activity as somewhat clearer and working better when playing with the human tutee. These findings suggest that children can enjoy engaging in peer tutoring with a robot tutee. However, the interactive capabilities of robots will need to improve quite substantially before they can potentially engage in autonomous and unsupervised interactions with children.

Social/dialogical roles of social robots in supporting children's learning of language and literacy-A review and analysis of innovative roles.

One of the many purposes for which social robots are designed is education, and there have been many attempts to systematize their potential in this field. What these attempts have in common is the recognition that learning can be supported in a variety of ways because a learner can be engaged in different activities that foster learning. Up to now, three roles have been proposed when designing these activities for robots: as a teacher or tutor, a learning peer, or a novice. Current research proposes that deciding in favor of one role over another depends on the content or preferred pedagogical form. However, the design of activities changes not only the content of learning, but also the nature of a human-robot social relationship. This is particularly important in language acquisition, which has been recognized as a social endeavor. The following review aims to specify the differences in human-robot social relationships when children learn language through interacting with a social robot. After proposing categories for comparing these different relationships, we review established and more specific, innovative roles that a robot can play in language-learning scenarios. This follows Mead's (1946) theoretical approach proposing that social roles are performed in interactive acts. These acts are crucial for learning, because not only can they shape the social environment of learning but also engage the learner to different degrees. We specify the degree of engagement by referring to Chi's (2009) progression of learning activities that range from active, constructive, toward interactive with the latter fostering deeper learning. Taken together, this approach enables us to compare and evaluate different human-robot social relationships that arise when applying a robot in a particular social role.

Children's learning-by-teaching with a social robot versus a younger child: Comparing interactions and tutoring styles.

Human peer tutoring is known to be effective for learning, and social robots are currently being explored for robot-assisted peer tutoring. In peer tutoring, not only the tutee but also the tutor benefit from the activity. Exploiting the learning-by-teaching mechanism, robots as tutees can be a promising approach for tutor learning. This study compares robots and humans by examining children's learning-by-teaching with a social robot and younger children, respectively. The study comprised a small-scale field experiment in a Swedish primary school, following a within-subject design. Ten sixth-grade students (age 12-13) assigned as tutors conducted two 30 min peer tutoring sessions each, one with a robot tutee and one with a third-grade student (age 9-10) as the tutee. The tutoring task consisted of teaching the tutee to play a two-player educational game designed to promote conceptual understanding and mathematical thinking. The tutoring sessions were video recorded, and verbal actions were transcribed and extended with crucial game actions and user gestures, to explore differences in interaction patterns between the two conditions. An extension to the classical initiation-response-feedback framework for classroom interactions, the IRFCE tutoring framework, was modified and used as an analytic lens. Actors, tutoring actions, and teaching interactions were examined and coded as they unfolded in the respective child-robot and child-child interactions during the sessions. Significant differences between the robot tutee and child tutee conditions regarding action frequencies and characteristics were found, concerning tutee initiatives, tutee questions, tutor explanations, tutee involvement, and evaluation feedback. We have identified ample opportunities for the tutor to learn from teaching in both conditions, for different reasons. The child tutee condition provided opportunities to engage in explanations to the tutee, experience smooth collaboration, and gain motivation through social responsibility for the younger child. The robot tutee condition provided opportunities to answer challenging questions from the tutee, receive plenty of feedback, and communicate using mathematical language. Hence, both conditions provide good learning opportunities for a tutor, but in different ways.

The early ontogeny of infants' imitation of on screen humans and robots.

Traditionally, infants have learned how to interact with objects in their environment through direct observations of adults and peers. In recent decades these models have been available over different media, and this has introduced non-human agents to infants' learning environments. Humanoid robots are increasingly portrayed as social agents in on screen, but the degree to which infants are capable of observational learning from screen-based robots is unknown. The current study thus investigated how well 1- to 3-year-olds (N = 230) could imitate on-screen robots relative to on-screen and live humans. Participants exhibited an imitation deficit for robots that varied with age. Furthermore, the well-known video deficit did not replicate as expected, and was weak and transient relative to past research. Together, the findings documented here suggest that infants are learning from media in ways that differ from past generations, but that this new learning is nuanced when novel technologies are involved.

Does agency matter? Neural processing of robotic movements in 4- and 8-year olds.

Despite the increase in interactions between children and robots, our understanding of children's neural processing of robotic movements is limited. The current study theorized that motor resonance hinges on the agency of an actor: its ability to perform actions volitionally. As one of the first studies with a cross-sectional sample of preschoolers and older children and with a specific focus on robotic action (rather than abstract non-human action), the current study investigated whether the perceived agency of a robot moderated children's motor resonance for robotic movements, and whether this changed with age. Motor resonance was measured using electroencephalography (EEG) by assessing mu power while 4 and 8-year-olds observed actions performed by agentic versus non-agentic robots and humans. Results show that older children resonated more strongly with non-agentic than agentic robotic or human movement, while no such differences were found for preschoolers. This outcome is discussed in terms of a predictive coding account of motor resonance. Importantly, these findings contribute to the existing set of studies on this topic by showing that, while keeping all kinematic information constant, there is a clear developmental difference in how children process robotic movement depending on the level of agency of a robot.

Social Robots as Creativity Eliciting Agents.

Can robots help children be more creative? In this work, we posit social robots as creativity support tools for children in collaborative interactions. Children learn creative expressions and behaviors through social interactions with others during playful and collaborative tasks, and socially emulate their peers' and teachers' creativity. Social robots have a unique ability to engage in social and emotional interactions with children that can be leveraged to foster creative expression. We focus on two types of social interactions: creativity demonstration, where the robot exhibits creative behaviors, and creativity scaffolding, where the robot poses challenges, suggests ideas, provides positive reinforcement, and asks questions to scaffold children's creativity. We situate our research in three playful and collaborative tasks - the Droodle Creativity game (that affords verbal creativity), the MagicDraw game (that affords figural creativity), and the WeDo construction task (that affords constructional creativity), that children play with Jibo, a social robot. To evaluate the efficacy of the robot's social behaviors in enhancing creative behavior and expression in children, we ran three randomized controlled trials with 169 children in the 5-10 yr old age group. In the first two tasks, the robot exhibited creativity demonstration behaviors. We found that children who interacted with the robot exhibiting high verbal creativity in the Droodle game and high figural creativity in the MagicDraw game also exhibited significantly higher creativity than a control group of participants who interacted with a robot that did not express creativity (p < 0.05*). In the WeDo construction task, children who interacted with the robot that expressed creative scaffolding behaviors (asking reflective questions, generating ideas and challenges, and providing positive reinforcement) demonstrated higher creativity than participants in the control group by expressing a greater number of ideas, more original ideas, and more varied use of available materials (p < 0.05*). We found that both creativity demonstration and creativity scaffolding can be leveraged as social mechanisms for eliciting creativity in children using a social robot. From our findings, we suggest design guidelines for pedagogical tools and social agent interactions to better support children's creativity.