A Comparative Analysis of Four Navigation Aids on User Performance in Single User Virtual Environment

In virtual environments (VEs), whether collaborative or single-user, numerous interaction strategies have been developed to facilitate task execution. However, due to the diverse nature of tasks and applications in VEs, these interaction techniques often vary significantly and lack standardization. Consequently, there are no universally accepted or well-organized interaction techniques that can be effectively applied across all VEs. This limitation becomes especially evident in Single User Virtual Environments (SUVEs), where effective communication modalities are essential for task execution. Despite their importance, there has been limited research on systematically comparing communication modalities such as arrows-casting, textual guidance, audio cues, and 3D Map-Liner (3DML) to assess their impact on user performance during task completion in SUVEs.This study aims to address the above gap by evaluating user performance with different communication modalities in SUVEs. Specifically, it compares the effectiveness of arrows-casting, textual guidance, audio cues, and 3DML for task execution in a VE designed for assembly tasks. A virtual environment was developed where the Dijkstra algorithm was implemented to calculate the shortest distance, ensuring optimized navigation. To conduct the study, 20 undergraduate students were selected to test these navigational aids. The results highlight that arrows-casting demonstrated the highest user performance among the tested modalities, while audio navigation aids showed the lowest performance.The findings of this study provide valuable insights into the design and selection of communication modalities in SUVEs. The superior performance of arrows-casting suggests that visual navigation aids are particularly effective in guiding users during task execution. On the other hand, the low performance of audio navigation aids indicates the need for further refinement and integration of audio cues in VEs. These results can inform the development of more efficient and user-friendly navigation aids, contributing to improved task completion and overall user experience in VEs. Additionally, the methodology and findings can serve as a foundation for future research on interaction techniques and task optimization in diverse virtual environments.