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Tele-operated collaborative robots are used by many children for academic learning. However, as child-directed play is important for social-emotional learning, it is also important to understand how robots can facilitate play. In this article, we present findings from an analysis of a national, multi-year case study, where we explore how 53 children in grades K–12 (n= 53) used robots for self-directed play activities. The contributions of this article are as follows. First, we present empirical data on novel play scenarios that remote children created using their tele-operated robots. These play scenarios emerged in five categories of play: physical, verbal, visual, extracurricular, and wished-for play. Second, we identify two unique themes that emerged from the data—robot-mediated play as a foundational support of general friendships and as a foundational support of self-expression and identity. Third, our work found that robot-mediated play provided benefits similar to in-person play. Findings from our work will inform novel robot and HRI design for tele-operated and social robots that facilitate self-directed play. Findings will also inform future interdisciplinary studies on robot-mediated play. 

Many robot-delivered health interventions aim to support people longitudinally at home to complement or replace in-clinic treat- ments. However, there is little guidance on how robots can support collaborative goal setting (CGS). CGS is the process in which a person works with a clinician to set and modify their goals for care; it can improve treatment adherence and efficacy. However, for home-deployed robots, clinicians will have limited availability to help set and modify goals over time, which necessitates that robots support CGS on their own. In this work, we explore how robots can facilitate CGS in the context of our robot CARMEN (Cognitively Assistive Robot for Motivation and Neurorehabilitation), which delivers neurorehabilitation to people with mild cognitive impairment (PwMCI). We co-designed robot behaviors for supporting CGS with clinical neuropsychologists and PwMCI, and prototyped them on CARMEN. We present feedback on how PwMCI envision these behaviors supporting goal progress and motivation during an intervention. We report insights on how to support this process with home-deployed robots and propose a framework to support HRI researchers interested in exploring this both in the context of cognitively assistive robots and beyond. This work supports design- ing and implementing CGS on robots, which will ultimately extend the efficacy of robot-delivered health interventions. 

Clinical educators have used robotic and virtual patient simulator systems (RPS) for dozens of years, to help clinical learners (CL) gain key skills to help avoid future patient harm. These systems can simulate human physiological traits; however, they have static faces and lack the realistic depiction of facial cues, which limits CL engagement and immersion. In this article, we provide a detailed review of existing systems in use, as well as describe the possibilities for new technologies from the human–robot interaction and intelligent virtual agents communities to push forward the state of the art. We also discuss our own work in this area, including new approaches for facial recognition and synthesis on RPS systems, including the ability to realistically display patient facial cues such as pain and stroke. Finally, we discuss future research directions for the field.