arXiv subjects

Zhiqing Wu

Publications and source records attributed to Zhiqing Wu.

4 recordsLinked to original sources

arXiv2026

Human Factors in Immersive Analytics

It has been ten years since the term ''Immersive Analytics'' (IA) was coined and research interest in the topic remains strong. Researchers in this field have produced practical and conceptual knowledge concerning the use of emerging immersive spatial display and interaction technologies for sense-making tasks through a number of papers, surveys, and books. However, a lack of truly physically and psychologically ergonomic techniques, as well as standardized human-centric validation protocols for these, remains a significant barrier to wider acceptance of practical IA systems in ubiquitous applications. Building upon a series of workshops on immersive analytics at various conferences, this workshop aims to explore new approaches and establish standard practices for evaluating immersive analytics systems from a human factors perspective. We will gather immersive analytics researchers and practitioners to look closely at these human factors -- including cognitive and physical functions as well as behaviour and performance -- to see how they inform the design and deployment of immersive analytics techniques and applications and to inform future research.

cs.HC↗

arXiv2025

ExplorAR: Assisting Older Adults to Learn Smartphone Apps through AR-powered Trial-and-Error with Interactive Guidance

Older adults tend to encounter challenges when learning to use new smartphone apps due to age-related cognitive and physical changes. Compared to traditional support methods such as video tutorials, trial-and-error allows older adults to learn to use smartphone apps by making and correcting mistakes. However, it remains unknown how trial-and-error should be designed to empower older adults to use smartphone apps and how well it would work for older adults. Informed by the guidelines derived from prior work, we designed and implemented ExplorAR, an AR-based trial-and-error system that offers real-time and situated visual guidance in the augmented space around the smartphone to empower older adults to explore and correct mistakes independently. We conducted a user study with 18 older adults to compare ExplorAR with traditional video tutorials and a simplified version of ExplorAR. Results show that the AR-supported trial-and-error method enhanced older adults' learning experience by fostering deeper cognitive engagement and improving confidence in exploring unknown operations.

cs.HC↗

arXiv2025

RemVerse: Supporting Reminiscence Activities for Older Adults through AI-Assisted Virtual Reality

Reminiscence activities, which involve recalling and sharing past experiences, have proven beneficial for improving cognitive function, mood, and overall well-being. However, urbanization has led to the disappearance of familiar environments, removing visual and audio cues for effective reminiscence. While old photos can serve as visual cues to aid reminiscence, it is challenging for people to reconstruct the reminisced content and environment that are not in the photos. Virtual reality (VR) and artificial intelligence (AI) offer the ability to reconstruct an immersive environment with dynamic content and to converse with people to help them gradually reminisce. We designed RemVerse, an AI-empowered VR prototype aimed to support reminiscence activities. Integrating generative models and AI agent into a VR environment, RemVerse helps older adults reminisce with AI-generated visual cues and interactive dialogues. Our user study with 14 older adults showed that RemVerse effectively supported reminiscence activities by triggering, concretizing, and deepening personal memories, while fostering increased engagement and autonomy among older adults. Based on our findings, we proposed design implications to make reminiscence activities in AI-assisted VR more accessible and engaging for older adults.

cs.HC↗

arXiv2024

SilverCycling: Exploring the Impact of Bike-Based Locomotion on Spatial Orientation for Older Adults in VR

Spatial orientation is essential for people to effectively navigate and interact with the environment in everyday life. With age-related cognitive decline, providing VR locomotion techniques with better spatial orientation performance for older adults becomes important. Such advancements not only make VR more accessible to older adults but also enable them to reap the potential health benefits of VR technology. Natural motion-based locomotion has been shown to be effective in enhancing younger users' performance in VR navigation tasks that require spatial orientation. However, there is a lack of understanding regarding the impact of natural motion-based locomotion on spatial orientation for older adults in VR. To address this gap, we selected the SilverCycling system, a VR bike-based locomotion technique that we developed, as a representative of natural motion-based locomotion, guided by findings from our pilot study. We conducted a user study with 16 older adults to compare SilverCycling with the joystick-based controller. The findings suggest SilverCycling's potential to significantly enhance spatial orientation in the open-road urban environment for older adults, offering a better user experience. Based on our findings, we identify key factors influencing spatial orientation and propose design recommendations to make VR locomotion more accessible and user-friendly for older adults.

cs.HC↗