Exploring User Interactions in AR/VR Interfaces: A Simulation-Based Study

Virtual Reality (VR) and Augmented Reality (AR) technologies have gained significant attention in various domains. User interactions and error rates in VR/AR environments are crucial for improving system performance and user experience. In this study, a simulated dataset of 20,000 data points representing interactions of 1,000 users with four actions: “Select,” “Drag,” “Resize,” and “Rotate” is presented. Likelihood analysis is employed to explore error rates and their correlations with user-related factors such as action duration, fatigue, task success, preference, and learning rate. The findings deepen the understanding of error rates in VR/AR environments and provide insights into optimizing user experiences. The methodology of using simulated data and likelihood analysis can serve as a foundation for future studies investigating error modeling and prediction in real-world VR/AR applications.