Xiaoying Wei

Inter-generational communication enhances mutual understanding and family connections. In China, traditional Chinese opera (Xiqu) serves as a culturally rich topic that provides common ground, fostering meaningful conversations across generations. However, traditional verbal discussion falls short in bridging the cultural and knowledge gaps, thereby failing to convey the full charm of Xiqu and hindering effective inter-generational Xiqu communication. To address this challenge, this study investigates the potential of Virtual Reality (VR) to bridge these generational divides. Using a mixed-methods approach, we developed and evaluated XiquVR to facilitate inter-generational Xiqu communication. Key findings show that XiquVR transforms one-sided storytelling into collaborative activities, visualizes abstract narratives to bridge generational gaps, and facilitates bidirectional exchanges through AI-assisted knowledge sharing. Furthermore, we propose design implications for developing VR applications centered on culturally significant topics to facilitate inter-generational communication.

Inter-generational communication plays a vital role in bridging generational gaps and fostering mutual understanding. However, it remains challenging due to differences in cultural norms, communication styles, and geographical separation. While prior studies have shown Virtual Reality (VR) as a medium that fosters a relaxed atmosphere and companionship, its capacity to address the nuanced dynamics of inter-generational dialogue, such as divergent values and relational intricacies, remains limited. To address this gap, we explored the opportunities of Artificial Intelligence (AI) to support inter-generational communication in VR. We developed three technology probes (e.g., Content Generator, Communication Facilitator, and Info Assistant) in VR and employed them in a probe-based participatory design study with twelve inter-generational pairs. Our results show that AI-powered VR facilitates inter-generational communication by enhancing mutual understanding, fostering conversation fluency, and promoting active participation. We also introduce several challenges when using AI-powered VR in supporting inter-generational communication and derive design implications for future VR platforms, aiming to improve inter-generational communication.

Virtual reality (VR) is increasingly used as a social platform for users to interact and build connections with one another in an immersive virtual environment. Reflecting on the empirical progress in this area of study, a comprehensive review of how VR could be used to support social interaction is required to consolidate existing practices and identify research gaps to inspire future studies. In this work, we conducted a systematic review of 94 publications in the HCI field to examine how VR is designed and evaluated for social purposes. We found that VR influences social interaction through self-representation, interpersonal interactions, and interaction environments. We summarized four positive effects of using VR for socializing, which are relaxation, engagement, intimacy, and accessibility, and showed that it could also negatively affect user social experiences by intensifying harassment experiences and amplifying privacy concerns. We introduce an evaluation framework that outlines the key aspects of social experience: intrapersonal, interpersonal, and interaction experiences. According to the results, we uncover several research gaps and propose future directions for designing and developing VR to enhance social experience.

In recent years, various head-worn virtual reality (VR) techniques have emerged to enhance object selection for occluded or distant targets. However, many approaches focus solely on ray-casting inputs, restricting their use with other input methods, such as bare hands. Additionally, some techniques speed up selection by changing the user's perspective or modifying the scene context, which may complicate interactions when users plan to resume or manipulate the scene afterward. To address these challenges, we present FocalSelect, a heuristic selection technique that builds 3D disambiguation through head-hand coordination and scoring-based functions. Our interaction design adheres to the principle that the intended selection range is a small sector of the headset's viewing frustum, allowing optimal targets to be identified within this scope. We also introduce a density-aware adjustable occlusion plane for effective depth culling of rendered objects. Two experiments are conducted to assess the adaptability of FocalSelect across different input modalities and its performance against five selection techniques. The results indicate that FocalSelect enhances selection experiences in occluded and remote scenarios while preserving the spatial context among objects. This preservation helps maintain users' understanding of the original scene and facilitates further manipulation. We also explore potential applications and enhancements to demonstrate more practical implementations of FocalSelect.