Many studies have investigated how interpersonal differences between users influence their experience in Virtual Reality (VR) and it is now well recognized that user's subjective experiences and responses to the same VR environment can vary widely. In this study, we focus on player traits, which correspond to users' preferences for game mechanics, arguing that players react differently when experiencing VR scenarios. We developed three scenarios in the same VR environment that rely on different game mechanics, and evaluate the influence of the scenarios, the player traits and the time of practice of the VR environment on users' perceived flow. Our results show that 1) the type of scenario has an impact on specific dimensions of flow; 2) the scenarios have different effects on flow depending on the order they are performed, the flow preconditions being stronger when performed at last; 3) almost all dimensions of flow are influenced by the player traits, these influences depending on the scenario, 4) the Aesthetic trait has the most influences in the three scenarios. We finally discuss the findings and limitations of the present study that we believe have strong implications for the design of scenarios in VR experiences.

With the ever-growing use of extended reality (XR) technologies, researchers seek to understand the factors leading to a higher quality of experience. Measurements of the quality of experience (e.g., presence, immersion, flow) are usually assessed through questionnaires completed after the experience. To cope with shortcomings and limitations of this kind of assessment, some recent studies tend to use physiological measures and interaction traces generated in the virtual world in replacement or in addition to questionnaires. Those physiological and behavioral measurements are still complex to implement, and existing studies difficult to replicate, because of a lack of easy and efficient tools to collect and visualize such data produced during XR experiments. In this paper, we present XRE-cho, a Unity package that allows for the recording, replaying and visualization of user behavior and interactions during XR sessions; recorded data allows to replay the whole experience, as it includes movements of the XR device, controllers and interacted objects, as well as eye tracking data (e.g., gaze position, pupils diameter). The capabilities of this tool are illustrated in a user study, where 12 participants' data have been collected and visualized with XREcho. Source code for XREcho is publicly available on GitHub.1

The impact of olfactory cues on user experience in virtual reality is increasingly studied. However, results are still heterogeneous and existing studies difficult to replicate, mainly due to a lack of standardized olfactory displays. In that context, we present Nebula, a low-cost, open-source, olfactory display capable of diffusing scents at different diffusion rates using a nebulization process. Nebula can be used with PC VR or autonomous head-mounted displays, making it easily transportable without the need for an external computer. The device was calibrated to diffuse at three diffusion rates: no diffusion, low and high. For each level, the quantity of delivered odor was precisely characterized using a repeated weighting method. The corresponding perceived olfactory intensities were evaluated by a psychophysical experiment on sixteen participants. Results demonstrated the device capability to successfully create three significantly different perceived odor intensities (Friedman test p < 10− 6, Wilcoxon tests padj < 10− 3), without noticeable smell persistence and with limited noise and discomfort. For reproducibility and to stimulate further research in the area, 3D printing files, electronic hardware schemes, and firmware/software source-code are made publicly available.