BeatriXR: Comprehensive and Adaptive Feedforward Support for Guidance in Virtual Reality EICS008

Virtual Reality (VR) environments challenge users with varied input devices, interaction methods, and interface designs, resulting in a steep learning curve. Feedforward "informs the user about what the result of his action will be", and it allows to ease the process of learning of the end user by providing ways to represent the required action to perform, using contextualised previews that show how to complete a given interaction. Yet, creating effective direct feedforward without specialised tools remains a tedious process. We present BeatriXR, a flexible and adaptive toolkit that simplifies the creation of direct-feedforward configurations in VR. It enables users to build, visualise, and customise direct feedforward using virtual avatars, offering both in-world representations and on-screen comparisons of interaction options. Mapped to the recognised design-space by Muresan et al. (including Triggering, Previewing, and Exiting phases), BeatriXR streamlines development and helps ensure effective feedforward integration in VR environments. As additional support for the feedforward design task, BeatriXR features an LLM-powered decision-support layer that suggests possible configuration options. This guidance helps designers select optimal settings during development for adapting the presentation to user needs and the expected configuration of the interaction context. We conducted an exploratory review with XR domain experts who rated the UI for modifying feedforward settings, and assessed four LLM models in the task of suggesting possible configuration options. The participants’ feedback was positive and provided valuable insights for improving both the user interface, which was generally perceived positively, and the quality of the LLM-generated responses.