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  1. Regular exercise provides many mental and physical health benefits. However, when exercises are done incorrectly, it can lead to injuries. Because the COVID-19 pandemic made it challenging to exercise in communal spaces, the growth of virtual fitness programs was accelerated, putting people at risk of sustaining exercise-related injuries as they received little to no feedback on their exercising techniques. Colocated robots could be one potential enhancement to virtual training programs as they can cause higher learning gains, more compliance, and more enjoyment than non-co-located robots. In this study, we compare the effects of a physically present robot by having a person exercise either with a robot (robot condition) or a video of a robot displayed on a tablet (tablet condition). Participants (N=25) had an exercise system in their homes for two weeks. Participants who exercised with the colocated robot made fewer mistakes than those who exercised with the video-displayed robot. Furthermore, participants in the robot condition reported a higher fitness increase and more motivation to exercise than participants in the tablet condition. 
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  2. null (Ed.)
    In this paper, we argue in favor of creating robots that both teach and learn. We propose a methodology for building robots that can learn a skill from an expert, perform the skill independently or collaboratively with the expert, and then teach the same skill to a novice. This requires combining insights from learning from demonstration, human-robot collaboration, and intelligent tutoring systems to develop knowledge representations that can be shared across all three components. As a case study for our methodology, we developed a glockenspiel-playing robot. The robot begins as a novice, learns how to play musical harmonies from an expert, collaborates with the expert to complete harmonies, and then teaches the harmonies to novice users. This methodology allows for new evaluation metrics that provide a thorough understanding of how well the robot has learned and enables a robot to act as an efficient facilitator for teaching across temporal and geographic separation. 
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