LAUSR

Virtual reality (VR) is a promising tool for motor skill learning. Previous studies have indicated that observing and following a teacher's movements from a first-person perspective using VR facilitates motor skill learning. Conversely, it has also been pointed out that this learning method makes the learner so strongly aware of the need to follow that it weakens their sense of agency (SoA) for motor skills and prevents them from updating the body schema, thereby preventing long-term retention of motor skills. To address this problem, we propose applying “virtual co-embodiment” to motor skill learning. Virtual co-embodiment is a system in which a virtual avatar is controlled based on the weighted average of the movements of multiple entities. Because users in virtual co-embodiment overestimate their SoA, we hypothesized that learning using virtual co-embodiment with a teacher would improve motor skill retention. In this study, we focused on learning a dual task to evaluate the automation of movement, which is considered an essential element of motor skills. As a result, learning in virtual co-embodiment with the teacher improves motor skill learning efficiency compared with sharing the teacher's first-person perspective or learning alone.