<jats:p>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 <jats:xref>Mead’s (1946)</jats:xref> 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 <jats:xref>Chi’s (2009)</jats:xref> 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.</jats:p>

<jats:p>Social robots have emerged as a new digital technology that is increasingly being implemented in the educational landscape. While social robots could be deployed to assist young children with their learning in a variety of different ways, the typical approach in educational practices is to supplement the learning process rather than to replace the human caregiver, e.g., the teacher, parent, educator or therapist. When functioning in the role of an educational assistant, social robots will likely constitute a part of a triadic interaction with the child and the human caregiver. Surprisingly, there is little research that systematically investigates the role of the caregiver by examining the ways in which children involve or check in with them during their interaction with another partner<jats:bold>—</jats:bold>a phenomenon that is known as social referencing. In the present study, we investigated social referencing in the context of a dyadic child–robot interaction. Over the course of four sessions within our longitudinal language-learning study, we observed how 20 pre-school children aged 4–5 years checked in with their accompanying caregivers who were not actively involved in the language-learning procedure. The children participating in the study were randomly assigned to either an interaction with a social robot or a human partner. Our results revealed that all children across both conditions utilized social referencing behaviors to address their caregiver. However, we found that the children who interacted with the social robot did so significantly more frequently in each of the four sessions than those who interacted with the human partner. Further analyses showed that no significant change in their behavior over the course of the sessions could be observed. Findings are discussed with regard to the caregiver's role during children's interactions with social robots and the implications for future interaction design.</jats:p>

<jats:title>Abstract</jats:title><jats:p>In child–robot interaction (cHRI) research, many studies pursue the goal to develop interactive systems that can be applied in everyday settings. For early education, increasingly, the setting of a kindergarten is targeted. However, when cHRI and research are brought into a kindergarten, a range of ethical and related procedural aspects have to be considered and dealt with. While ethical models elaborated within other human–robot interaction settings, e.g., assisted living contexts, can provide some important indicators for relevant issues, we argue that it is important to start developing a systematic approach to identify and tackle those ethical issues which rise with cHRI in kindergarten settings on a more global level and address the impact of the technology from a macroperspective beyond the effects on the individual. Based on our experience in conducting studies with children in general and pedagogical considerations on the role of the institution of kindergarten in specific, in this paper, we enfold some relevant aspects that have barely been addressed in an explicit way in current cHRI research. Four areas are analyzed and key ethical issues are identified in each area: (1) the institutional setting of a kindergarten, (2) children as a vulnerable group, (3) the caregivers’ role, and (4) pedagogical concepts. With our considerations, we aim at (i) broadening the methodology of the current studies within the area of cHRI, (ii) revalidate it based on our comprehensive empirical experience with research in kindergarten settings, both laboratory and real-world contexts, and (iii) provide a framework for the development of a more systematic approach to address the ethical issues in cHRI research within kindergarten settings.</jats:p>

<jats:p>Temperamental traits can decisively influence how children enter into social interaction with their environment. Yet, in the field of child–robot interaction, little is known about how individual differences such as shyness impact on how children interact with social robots in educational settings. The present study systematically assessed the temperament of 28 preschool children aged 4–5 years in order to investigate the role of shyness within a dyadic child–robot interaction. Over the course of four consecutive sessions, we observed how shy compared to nonshy children interacted with a social robot during a word-learning educational setting and how shyness influenced children’s learning outcomes. Overall, results suggested that shy children not only interacted differently with a robot compared to nonshy children, but also changed their behavior over the course of the sessions. Critically, shy children interacted less expressively with the robot in general. With regard to children’s language learning outcomes, shy children scored lower on an initial posttest, but were able to close this gap on a later test, resulting in all children retrieving the learned words on a similar level. When intertest learning gain was considered, regression analyses even confirmed a positive predictive role of shyness on language learning gains. Findings are discussed with regard to the role of shyness in educational settings with social robots and the implications for future interaction design.</jats:p>