How a task-blind adaptive VR system can improve users' task performance: an assisted immersive analytics use case
Year: 2025
Type: conference-paper
Abstract: Recently, some works have built adaptive systems providing assistance to the user in virtual reality (VR), with little or no knowledge of the user’s task. These task-blind help systems can influence behaviours and exploration strategies; however, their ability to significantly improve users’ performance on their tasks is still unclear. In this study, we aim to clarify the impact of task-blind help systems on user performance. We also explore two avenues that could provide a better understanding of why these systems can be effective and interesting to study. Our controlled user study involved 56 participants in an immersive analytics environment and compared four VR help-system configurations, including three task-blind systems and a no-assistance baseline. Results showed significant task performance improvements with one task-blind system, highlighting user control as a key factor of efficiency. This work demonstrates the potential of task-blind help systems, offering a flexible framework for adaptive design and raising questions about their broader applications.
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4417025373