Educational robots are increasingly adopted to support children’s learning through interactive and personalized learning. Social interaction remains a crucial mechanism for effective learning, yet teacher and parental involvement in out-of-class learning activities is minimal or limited to supervisory roles. To support students with socially and intellectually meaningful learning experiences and to augment teachers’ pedagogical strategies outside of a classroom environment, we aim to explore the design of a learning companion robot by building a better understanding of the use cases for robot-assisted homework. In this paper, we report on findings from in-home technology probe studies with 10 students (aged 10–12), which revealed student expectations surrounding what support needs to be delivered by the robot and how it should be delivered. We discuss the themes of our findings and their implications for future design of social robots for homework assistance.

The goal of this workshop is to have interdisciplinary discussions on family-centered interaction design of technology as an extension to child-centered design. The workshop will discuss the potential benefits of a family-centered approach to design, as well as the challenges and open questions that designers may face when adopting this approach. Through discussions and interactive activities, participants will have the opportunity to discuss and share ideas on how to effectively incorporate a family-centered perspective into their own design processes. A family-centered approach to design has the potential to create more meaningful and contextual experiences for children and their families.

Social robots are becoming increasingly prevalent in the real world. Unsupervised user interactions in a natural and familiar setting, such as the home, can reveal novel design insights and opportunities. This paper presents an analysis and key design insights from family-robot interactions, captured via on-robot recordings during an unsupervised four-week in-home deployment of an autonomous reading companion robot for children. We analyzed interviews and 160 interaction videos involving six families who regularly interacted with a robot for four weeks. Throughout these interactions, we observed how the robot's expressions facilitated unique interactions with the child, as well as how family members interacted with the robot. In conclusion, we discuss five design opportunities derived from our analysis of natural interactions in the wild.

Social robots are emerging as learning companions for children, and research shows that they facilitate the development of interest and learning even through brief interactions. However, little is known about how such technologies might support these goals in authentic environments over long-term periods of use and interaction. We designed a learning companion robot capable of supporting children reading popular-science books by expressing social and informational commentaries. We deployed the robot in homes of 14 families with children aged 10–12 for four weeks during the summer. Our analysis revealed critical factors that affected children’s long-term engagement and adoption of the robot, including external factors such as vacations, family visits, and extracurricular activities; family/parental involvement; and children’s individual interests. We present four in-depth cases that illustrate these factors and demonstrate their impact on children’s reading experiences and discuss the implications of our findings for robot design.