Social robots can support children’s emotional skills development through playful interactions, yet skills like emotional self-disclosure remain underexplored. This study investigates the impact of a social robot designed to encourage emotional self-disclosure during an emotion-identification game with children aged 6-10. In a between-subjects design with 28 participants across two local schools, we compared a Reflective condition, where the robot actively encouraged emotional self-disclosure through question-asking and reciprocal sharing, to a Control condition, where the robot did not. Children in the Reflective condition engaged in emotional self-disclosure when prompted, and showed higher engagement than those in Control. Direct question-asking was more effective than reciprocal self-disclosure. Results suggested that children who perceived the robot as kinder disclosed more, whereas those who viewed it as more real disclosed less. These findings highlight the potential of social robots to foster emotional skills in children and inform the design of future child-robot interaction research.

Study design is critical in Human-Robot Interaction (HRI) due to its highly interdisciplinary nature, that spans a wide range of domains and often presents significant hurdles for novice researchers. Building on the success of the previous years, the fourth edition of the “Workshop Your Study Design” addresses this challenge by pairing early-stage researchers with experienced mentors to refine their study designs and offering mentor-led talks on key HRI topics, tailored to this year's conference sustainability theme. Participants are invited to submit a 2–4 page study proposal focusing on methodology and data analysis. Accepted submissions are discussed in small mentor-led groups, where participants receive targeted feedback on their study designs and can also benefit from engaging in discussions about other participants' submissions. Our expert mentors this year bring expertise in areas such as participatory design, qualitative analysis and longitudinal studies. Thus, the workshop aims to foster a collaborative environment where participants can not only strengthen their study designs, but also gain valuable insights and build lasting connections within the HRI community.

Although research often explores how human-robot interaction influences cooperation in social dilemma scenarios such as the Public Goods Game, most research focuses on robots taking active roles in the game i.e. opponents or team-players. Considering the potential of assistant robots to influence human decision-making, this study explores how an assistant robot with prosocial or individualistic goals influences cooperation in a Public Goods Game. In a between-subjects study (N=60), participants interacted with the robot in one of three conditions: Prosocial, where the robot supported cooperative behavior; Individualistic, where it encouraged self-serving actions; and Control, where the robot provided feedback on the game state without expressing individual goals. Results revealed that participants in the Prosocial or Individualistic conditions contributed less to the public good compared to those in the Control condition. The Prosocial and Individualistic robots were perceived as warmer but evoking more discomfort compared to the Control. Notably, participants who played with the Prosocial robot reported increased trust, not only in the robot but also in their fellow players. These findings suggest that alignment between an assistant robot’s goals and expected social norms plays a key role in trust perception and it also shapes group dynamics. We discuss important considerations for designing assistant robots that provide moral recommendations.