Questionnaires are among the most common research tools in virtual reality (VR) user studies. Transitioning from virtuality to reality for giving self-reports on VR experiences can lead to systematic biases. VR allows to embed questionnaires into the virtual environment which may ease participation and avoid biases. To provide a cohesive picture of methods and design choices for questionnaires in VR (INVRQ), we discuss 15 INVRQ studies from the literature and present a survey with 67 VR experts from academia and industry. Based on the outcomes, we conducted two user studies in which we tested different presentation and interaction methods of INVRQS and evaluated the usability and practicality of our design. We observed comparable completion times between INVRQS and questionnaires outside VR (OUTVRQS) with higher enjoyment but lower usability for INVRQS. These findings advocate the application of INVRQS and provide an overview of methods and considerations that lay the groundwork for INVRQ design.

Questionnaires are among the most common research tools in virtual reality (VR) evaluations and user studies. However, transitioning from virtual worlds to the physical world to respond to VR experience questionnaires can potentially lead to systematic biases. Administering questionnaires in VR (INVRQS) is becoming more common in contemporary research. This is based on the intuitive notion that INVRQS may ease participation, reduce the Break in Presence (BIP) and avoid biases. In this paper, we perform a systematic investigation into the effects of interrupting the VR experience through questionnaires using physiological data as a continuous and objective measure of presence. In a user study (n=50), we evaluated question-asking procedures using a VR shooter with two different levels of immersion. The users rated their player experience with a questionnaire either inside or outside of VR. Our results indicate a reduced BIP for the employed INVRQ without affecting the self-reported player experience.

In human-computer interaction (HCI), there has been a push towards open science, but to date, this has not happened consistently for HCI research utilizing brain signals due to unclear guidelines to support reuse and reproduction. To understand existing practices in the field, this paper examines 110 publications, exploring domains, applications, modalities, mental states and processes, and more. This analysis reveals variance in how authors report experiments, which creates challenges to understand, reproduce, and build on that research. It then describes an overarching experiment model that provides a formal structure for reporting HCI research with brain signals, including definitions, terminology, categories, and examples for each aspect. Multiple distinct reporting styles were identified through factor analysis and tied to different types of research. The paper concludes with recommendations and discusses future challenges. This creates actionable items from the abstract model and empirical observations to make HCI research with brain signals more reproducible and reusable.

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