Interactions in a Virtual Reality Maritime bridge simulator
Description
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Abstract
Continuous advancements in visualization and display technologies have made simulations in VR more immersive and perceptually realistic. However, relatively less effort has been to put into the user interaction in VR. Most VR training studies have focused on studying educational-related work in different simulators, while emphasizing less on human-computer interaction (HCI) and system usability. In education and training, for a VR simulation to deliver knowledge/skills effectively, user interaction with the system should be seamless and take less effort from the users. To fill this gap, this study aims 1) to identify the interaction techniques and issues involved in a VR bridge simulator used for training, 2) to measure user experience and mental workload in the simulator in relation to the identified interaction techniques, and 3) to propose potential improvements for better simulator training. Based on existing HCI research, this study classifies interaction techniques used in a VR bridge simulator by “objectives” and “metaphors”, which allows the generic techniques required to perform actions in the VR bridge simulator used in this study to be compared with those investigated in other VR HCI studies. Seven (07) nautical students performed a ship handling task in the VR bridge simulator. The System Usability Scale (SUS) was used to measure user experience, NASA-TLX was used to measure task workload, and self-efficacy was measured to reflect participants' learning outcomes. Observation was also performed to quantify the type and number of interactions involved in specific tasks, and interaction issues encountered during the simulation. The observation data reveals that the hand selection technique causes more interaction difficulties than other classified interaction techniques (i.e., head selection; manipulation; screen interaction and teleportation) in the simulator. In addition, participants who encountered more interaction issues in VR showed higher mental workload. To tackle the identified hand selection issue, Go-Go and PRISM techniques could be used to improve the hand interaction technique in the simulator. Continuous advancements in visualization and display technologies have made simulations in VR more immersive and perceptually realistic. However, relatively less effort has been to put into the user interaction in VR. Most VR training studies have focused on studying educational-related work in different simulators, while emphasizing less on human-computer interaction (HCI) and system usability. In education and training, for a VR simulation to deliver knowledge/skills effectively, user interaction with the system should be seamless and take less effort from the users. To fill this gap, this study aims 1) to identify the interaction techniques and issues involved in a VR bridge simulator used for training, 2) to measure user experience and mental workload in the simulator in relation to the identified interaction techniques, and 3) to propose potential improvements for better simulator training. Based on existing HCI research, this study classifies interaction techniques used in a VR bridge simulator by “objectives” and “metaphors”, which allows the generic techniques required to perform actions in the VR bridge simulator used in this study to be compared with those investigated in other VR HCI studies. Seven (07) nautical students performed a ship handling task in the VR bridge simulator. The System Usability Scale (SUS) was used to measure user experience, NASA-TLX was used to measure task workload, and self-efficacy was measured to reflect participants' learning outcomes. Observation was also performed to quantify the type and number of interactions involved in specific tasks, and interaction issues encountered during the simulation. The observation data reveals that the hand selection technique causes more interaction difficulties than other classified interaction techniques (i.e., head selection; manipulation; screen interaction and teleportation) in the simulator. In addition, participants who encountered more interaction issues in VR showed higher mental workload. To tackle the identified hand selection issue, Go-Go and PRISM techniques could be used to improve the hand interaction technique in the simulator.