Evaluating Social Acceptance of eXtended Reality (XR) Agent Technology: A User Study (Extended Version)

Megha Quamara, Viktor Schmuck, Cristina Iani, Axel Primavesi, Alexander Plaum +1 more
7/22/2025
cs.HCcs.AI

No confident code implementation found for this paper. 1 possible match can be shown below.

Abstract

In this paper, we present the findings of a user study that evaluated the social acceptance of eXtended Reality (XR) agent technology, focusing on a remotely accessible, web-based XR training system developed for journalists. This system involves user interaction with a virtual avatar, enabled by a modular toolkit. The interactions are designed to provide tailored training for journalists in digital-remote settings, especially for sensitive or dangerous scenarios, without requiring specialized end-user equipment like headsets. Our research adapts and extends the Almere model, representing social acceptance through existing attributes such as perceived ease of use and perceived usefulness, along with added ones like dependability and security in the user-agent interaction. The XR agent was tested through a controlled experiment in a real-world setting, with data collected on users' perceptions. Our findings, based on quantitative and qualitative measurements involving questionnaires, contribute to the understanding of user perceptions and acceptance of XR agent solutions within a specific social context, while also identifying areas for the improvement of XR systems.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{quamara2025evaluating,
  title  = {Evaluating Social Acceptance of eXtended Reality (XR) Agent Technology: A User Study (Extended Version)},
  author = {Megha Quamara and Viktor Schmuck and Cristina Iani and Axel Primavesi and Alexander Plaum and Luca Vigano},
  year   = {2025},
  eprint = {2507.16562},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.16562v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2507.16562.svg)](https://codeofpaper.com/paper/2507.16562)

Discussion