Inspired by the concepts of diminishing reality and ad-blocking in browsers, this study investigates the perceived benefits and concerns of blocking physical, real-world content, particularly ads, through Extended Reality (XR). To understand how users perceive this concept, we first conducted a user study (n=18) with an adblocking prototype to gather initial insights. The results revealed a mixed willingness to adopt XR blockers, with participants appreciating aspects such as customizability, convenience, and privacy. Expected benefits included enhanced focus and reduced stress, while concerns centered on missing important information and increased feelings of isolation. Hence, we investigated the user acceptance of different ad-blocking visualizations through a follow-up online survey (n=120), comparing six concepts based on related work. The results indicated that the XR ad-blocker visualizations play a significant role in how and for what kinds of advertisements such a concept might be used, paving the path for future feedback-driven prototyping.

Personas offer an empathetic approach to capturing user requirements, translating user needs into relatable narratives. However, creating personas manually is time-consuming. Large Language Models (LLMs) can generate personas with convincing natural language, challenging traditional methods. Yet, LLM-generated personas may reflect biases from their training data, potentially compromising diversity. Our study explores how diversity is considered in LLM-generated personas through a qualitative user study with 22 participants. Participants generated personas without specific diversity prompts in the first task, revealing how users naturally interact with LLMs. In the second task, participants were explicitly asked to consider diversity aspects when prompting for personas. Analyzing the prompts and outputs showed that users tend to request less diversity unless explicitly instructed. Meanwhile, LLMs can introduce diversity even when not prompted, potentially broadening representation. However, we also found a critical pitfall: LLM-generated personas may appear diverse due to mentioning various aspects, but fail to translate them into meaningful implications for requirements engineering. This shows the need for a more deliberate approach when using LLMs for persona creation to ensure diversity is not just performative but genuinely informative for design and development.

Current research in Mixed Reality (MR) presents a wide range of novel use cases for blending virtual elements with the real world. This yet-to-be-ubiquitous technology challenges how users currently work and interact with digital content. While offering many potential advantages, MR technologies introduce new security, safety, and privacy challenges. Thus, it is relevant to understand users’ apprehensions towards MR technologies, ranging from security concerns to social acceptance. To address this challenge, we present the Mixed Reality Concerns (MRC) Questionnaire, designed to assess users’ concerns towards MR artifacts and applications systematically. The development followed a structured process considering previous work, expert interviews, iterative refinements, and confirmatory tests to analytically validate the questionnaire. The MRC Questionnaire offers a new method of assessing users’ critical opinions to compare and assess novel MR artifacts and applications regarding security, privacy, social implications, and trust.

Figure 1: Mixed Reality devices could potentially warn its users about fall hazards such as staircases.In our explorative prototype study, participants tested three different warning types: A superimposed small line at the stair landing (Left), a bigger warning including a text label (Middle), and a full-scale warning blocking the whole stair entrance including a text label (Right).

Pilots in non-commercial aviation have minimal access to digital support tools. Common 2D maps, displayed on tablets, are often the only digital information source that fails to adequately capture the 3D airspace and its surroundings, challenging the pilot’s workload and awareness. In this work, we developed and tested a Mixed Reality (MR) prototype with twelve General Aviation (GA) pilots using a full-sized flight simulator environment. The prototype’s demonstration showcased the capabilities of contemporary technology and its potential applications. Following the simulation, in-depth interviews were conducted with the participating pilots to discern their perspectives on integrating MR solutions into cockpit environments. The study revealed valuable insights into pilots’ concerns, design prerequisites for future systems, and potential use cases. This work not only highlights the feasibility of MR implementations but also provides a foundation for the development of enhanced digital tools for GA, aiming to alleviate pilot workload and augment situational awareness.

Cyclists' attention is often compromised when interacting with notifications in traffic, hence increasing the likelihood of road accidents. To address this issue, we evaluate three notification interaction modalities and investigate their impact on the interaction performance while cycling: gaze-based Dwell Time, Gestures, and Manual And Gaze Input Cascaded (MAGIC) Pointing. In a user study (N=18), participants confirmed notifications in Augmented Reality (AR) using the three interaction modalities in a simulated biking scenario. We assessed the efficiency regarding reaction times, error rates, and perceived task load. Our results show significantly faster response times for MAGIC Pointing compared to Dwell Time and Gestures, while Dwell Time led to a significantly lower error rate compared to Gestures. Participants favored the MAGIC Pointing approach, supporting cyclists in AR selection tasks. Our research sets the boundaries for more comfortable and easier interaction with notifications and discusses implications for target selections in AR while cycling.