Résumé
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.