Papers for

product developers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Extended reality better described with two dimensions instead of one

Beyond the 1D Reality-Virtuality Continuum: A 2D Framework for Seven Extended Reality Paradigms

Abstract: The Reality-Virtuality (RV) continuum helps in describing the relationship between physical and computer-generated environments. However, the increasing number of Extended Reality (XR) paradigms introduces new technologies. Their characteristics cannot be completely represented by a single real-virtual dimension. It can be noted that XR systems not only vary in their proportion of real and virtual content but also adds, suppresses, or transforms information available to the user. This work proposes a framework for characterizing seven XR realities, namely Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), Augmented Virtuality (AV), Phenomenal Reality (PR), Annexing Reality (AnR), and Diminished Reality (DR). It uses a two-dimensional extension of the conventional 1D RV continuum. The first dimension helps in identification of the position of an XR technology between real and virtual environments. The second dimension captures information addition and subtraction. The proposed approach gives a qualitative basis for comparing existing and emerging XR paradigms within a unified XR framework.

Tue 27 OctHuman-Computer Interaction
The gist
The traditional way to describe extended reality (XR) is as a line between real and virtual, but this doesn't capture all XR technologies well. The authors propose a new framework with two dimensions: one for how real or virtual the environment is, and another for how information is added or removed. This two-dimensional model helps categorize seven different XR types, including common ones like virtual reality and augmented reality, and newer ones that change or remove information. This framework gives a clearer way to compare and understand diverse XR experiences.
Open → 2610.36674v1

Pairs use AI tools to overcome challenges in shared design work

DuoSketch: How Pairs Navigate Challenges in AI-Supported Collaborative Design Ideation

Abstract: Generative AI offers new resources for collaborative design ideation, yet how designers work with it as a shared concept develops remains underexplored. We developed DuoSketch, integrating a shared canvas and live transcripts with a separate AI for each member of a pair. An exploratory qualitative study with 12 pairs identified three challenges: unresolved fit between AI proposals and shared design purposes, shared meanings not expressed in AI responses, and agreed changes missing from later outputs. We found that pairs navigated these challenges through bridging work in two directions: AI -> Shared Design (reworking features, developing uses, and assessing fit with shared requirements) and Shared Design -> AI (supplying materials, explaining meanings, and communicating decisions). We discuss how future AI systems can support the joint exploration and articulation of design ideas.

Wed 7 OctHuman-Computer Interaction
The gist
Working together on design ideas can be tricky, especially when using AI tools that don’t always understand the team’s shared goals. The authors created DuoSketch, a system where two people each have their own AI assistant helping on a shared design canvas. They found that pairs face challenges like AI suggestions not matching their joint plans or missing agreed changes later on. To deal with this, pairs do extra work to clarify how AI fits into their shared ideas and to teach AI what they mean. This research points to ways AI systems could better support teamwork in creative design.
Open → 2610.10249v1