Task-blind adaptive virtual reality: Is it possible to help users without knowing their assignments?

作     者：Besga, Simon Rodriguez, Nancy Sallaberry, Arnaud Papastergiou, Thomas Poncelet, Pascal 

作者机构：Univ Montpellier LIRMM CNRS Montpellier France Paul Valery Univ Montpellier AMIS Montpellier France Univ Sorbonne Paris Nord LIPN Paris France 

出 版 物：《VIRTUAL REALITY》 (Virtual Reality)

年 卷 期：2025年第29卷第1期

页      面：1-16页

核心收录：

学科分类：1002[医学-临床医学] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The authors wish to thank all the study participants and Carolin Reichherzer for the discussions about her interesting work and for allowing us to use her 3D reconstruction model 

主　　题：Virtual reality Adaptive human-computer interaction Human-centred computing Cognition Environment design Evaluation methods 

摘      要：The exploration of complex environments (reconstructed locations, immersive data visualisation, etc.) is one of the primary applications of virtual reality (VR) because of the feeling of immersion and the natural interactions that it provides. When exploration is completely free, users easily become disoriented and frustrated due to multiple factors such as task difficulty, interaction techniques, spatial understanding, immersion breaches, etc. Adaptive VR systems aim to overcome these difficulties and increase performance by providing clues to help the user and delivering effective feedback. Current adaptive VR systems are mainly task-based, meaning that they have explicit knowledge about what users must achieve. We assess a new task-blind approach, which aims to enhance users attention and recall processes instead of helping directly with their assignment by trying to infer in real time the task a user is performing. We compare three VR help-system configurations (task-based, task-blind, and no-help) through a controlled user study involving 66 participants. The results show that the group assisted by our task-blind system developed a different behavioural pattern while maintaining similar performance scores in comparison to the task-based approach. This paper shows a new way to offer more flexibility in help-system design and opens up the field of task-blind adaptive VR.