MGP: a monitoring-based VR interactive mode to support guided practice

Yu Wang, Hongqiu Luan, Lutong Wang, Shengzun Song, Yulong Bian, Xiyu Bao, Ran Liu, Wei Gai, Gaorong Lv, Chenglei Yang

Abstract: Currently, VR training systems are primarily designed according to the non-directive mode supporting independent practice without a real teacher. Students must complete all system operations resulting in heavy interaction burden and confusion. In this paper, a monitoring-based VR interactive mode is designed to support guided practice in the presence of teacher resources. The mode mainly realizes the separation of teacher–student interaction tasks, environment and equipment, helping the students focus on their own interactions and tasks. It also provides multi-channel information of the students for teachers to better understand students’ training status and make precise guidance. A platform and two applications were developed based on this mode for user study. The results show that the proposed mode can improve learning efficiency and enhance the immersive experience.