Invasive medical procedures can cause significant anxiety in children, affecting both immediate and long-term healthcare experiences. While social robots have shown promise in reducing anxiety, most interventions rely on short-term distraction. This paper introduces the Dream Robot, a social robot designed to deliver a medical hypnosis intervention to reduce anxiety in pediatric hospitals. We present three design phases of a rigorous interdisciplinary participatory process involving children, healthcare professionals, and roboticists. Through in-situ pilots during blood draws, anesthesia induction, and feeding tube placement, we examined how children, parents, and clinicians engaged with robot-guided medical hypnosis. Our findings indicate that such interventions can support children’s coping, but only when aligned with developmental differences, procedural timing, and social dynamics between child, parent, and healthcare professionals. Parents frequently acted as co-regulators, guiding children’s engagement. These results position robot-guided medical hypnosis as a situated, selective intervention rather than a universal solution for pediatric care.

Healthcare practitioners often use distraction techniques to ease children’s anxiety during blood draws. This study explored the effectiveness of a social robot, Softbank Robotics NAO, in reducing anxiety and pain for children aged 4-12 during blood draws. The robot engaged with children using behaviors tailored to the children’s age. Interestingly, results indicated the robot significantly increased anxiety, but pain levels remained unchanged. We argue that this effect may result from the robot’s novelty and that, over the long term, the robot could have a positive impact on anxiety, consistent with other studies. This research underscores the potential of social robots to alleviate children’s anxiety in medical procedures, enhancing patient experience in pediatric healthcare.

Maintaining the child-robot relationship after a significant break, such as a holiday, is an important step for developing sustainable social robots for education. We ran a four-session user study (n = 113 children) that included a nine-month break between the third and fourth session. During the study, participants practiced math with the help of a social robot math tutor. We found that social personalization is an effective strategy to better sustain the child-robot relationship than the absence of social personalization. To become reacquainted after the long break, the robot summarizes a few pieces of information it had stored about the child. This gives children a feeling of being remembered, which is a key contributor to the effectiveness of social personalization. Enabling the robot to refer to information previously shared by the child is another key contributor to social personalization. Conditional for its effectiveness, however, is that children notice these memory references. Finally, although we found that children's interest in the tutoring content is related to relationship formation, personalizing the topics did not lead to more interest in the content. It seems likely that not all of the memory information that was used to personalize the content was up-to-date or socially relevant.

To benefit from the social capabilities of a robot math tutor, instead of being distracted by them, a novel approach is needed where the math task and the robot's social behaviors are better intertwined. We present concrete design specifications of how children can practice math via a personal conversation with a social robot and how the robot can scaffold instructions. We evaluated the designs with a three-session experimental user study (n = 130, 8-11 y.o.). Participants got better at math over time when the robot scaffolded instructions. Furthermore, the robot felt more as a friend when it personalized the conversation.

Social robots have been introduced in different fields such as retail, health care and education. Primary education in the Netherlands (and elsewhere) recently faced new challenges because of the COVID-19 pandemic, lockdowns and quarantines including students falling behind and teachers burdened with high workloads. Together with two Dutch municipalities and nine primary schools we are exploring the long-term use of social robots to study how social robots might support teachers in primary education, with a focus on mathematics education. This paper presents an explorative study to define requirements for a social robot math tutor. Multiple focus groups were held with the two main stakeholders, namely teachers and students. During the focus groups the aim was 1) to understand the current situation of mathematics education in the upper primary school level, 2) to identify the problems that teachers and students encounter in mathematics education, and 3) to identify opportunities for deploying a social robot math tutor in primary education from the perspective of both the teachers and students. The results inform the development of social robots and opportunities for pedagogical methods used in math teaching, child-robot interaction and potential support for teachers in the classroom.

Research has shown that social robots carry potential to be used in an educational setting. The possibility to have multiple roles carried out by one tool does not only instigate curiosity but also raises concerns. Whereas practical challenges get tackled by rapid technological advances, the moral challenges often get overlooked. In this study, we examined the moral values related to educational robots from a teachers' perspective, by first identifying concerns and opportunities, and subsequently linking them to (moral) values. We conducted focus group sessions with teachers to explore their perceptions regarding concerns and opportunities related to educational robots. Teachers voiced several considerations ranging from having concerns towards privacy to seeing opportunities in adding friendship and attachment a robot could emanate.

Social robots are increasingly studied and applied in the educational domain. Although they hold great potential for education, they also bring new moral challenges. In this study, we explored the moral considerations related to social robots from the perspective of Dutch educational policymakers by first identifying opportunities and concerns and then mapping them onto (moral) values from the literature. To explore their moral considerations, we conducted focus group sessions with Dutch Educational Policymakers (N = 20). Considerations varied from the potential to lower the workload of teachers, to concerns related to the increased influence of commercial enterprises on the educational system. In total, the considerations of the policymakers related to 15 theoretical values. We identified the moral considerations of educational policymakers to gain a better understanding of a governmental attitude towards the use of social robots. This helps to create the necessary moral guidelines towards a responsible implementation of social robots in education.

Ethics by Design concerns the methods, algorithms and tools needed to endow autonomous agents with the capability to reason about the ethical aspects of their decisions, and the methods, tools and formalisms to guarantee that an agent's behavior remains within given moral bounds. In this context some questions arise: How and to what extent can agents understand the social reality in which they operate, and the other intelligences (AI, animals and humans) with which they co-exist? What are the ethical concerns in the emerging new forms of society, and how do we ensure the human dimension is upheld in interactions and decisions by autonomous agents?. But overall, the central question is: "Can we, and should we, build ethically-aware agents?" This paper presents initial conclusions from the thematic day of the same name held at PRIMA2017, on October 2017.