Artificial Intelligence (AI) is increasingly being integrated into a wide array of Extended Reality (XR) applications, including sophisticated navigation systems, immersive training simulations for educational use-cases and data analysis in medicine, e.g. for MRI scans. Consequently, ensuring the transparency and interpretability of these AI-driven applications has become a major challenge. This paper examines the growing importance of Explainable AI (XAI) in Extended Reality environments and identifies key challenges in developing effective explanation systems. We analyze how these AI-powered XR applications particularly benefit from transparent explanations that build trust, enhance user understanding and improve overall adoption. After summarizing the general challenges in the field of XAI, we investigate how these challenges manifest in the specific context of XR. By synthesizing current research and identifying critical open questions, this work aims to guide future XAI development towards more transparent, trustworthy systems that prioritize human needs across XR applications and beyond.

As AI systems increasingly permeate design education, the dominant interaction paradigm (text-based chat) risks constraining cognitive engagement in complex, iterative design tasks. This work explores whether and how multimodal interaction methods (e.g., visual, auditory, haptic) enhance cognitive performance compared to traditional chat-based AI interfaces within human-centered design (HCD) education. Based on an initial targeted literature analysis, multimodal interfaces have demonstrated benefits such as reduced cognitive load, increased user engagement, improved learning outcomes, and enhanced collaborative processes. The current work is situated within a broader doctoral research project investigating how generative AI reshapes cognitive design processes in novice designers. Building on an earlier case study that demonstrated that chat interfaces often lead to superficial understanding and linear thinking, this article urges a rethinking of AI-assisted design education as a multimodal, situational, and didactically coordinated experience. The current workshop provides a platform to exchange frameworks and strategies for engineering multimodal, cross-device AI experiences that better serve cognitive growth and design literacy in the generative age.

Manufacturing environments show limited telework adoption due to production requirements regarding physical interaction. Existing research addresses isolated remote collaboration aspects but lacks comprehensive integration frameworks with practical implementation pathways. This research focuses on a telework framework for part manufacturing through human-centered design. The framework combines storyboards depicting advanced integration scenarios with a low-effort implementation, meaning no machine control modifications required, utilizing existing infrastructure: camera systems, screen-based parameter acquisition, and VPN-based remote access. Validation through systematic testing with one operator performing ten manufacturing cycles under traditional and remote modes demonstrated 36% reduction in manual on-site time requirements. Three additional experiments validated operational capabilities: multi-machine coordination showed 50% reduction in physical movement, expert assistance demonstrated 50% task completion time reduction, and CNC program modification indicated improved troubleshooting effectiveness through integrated remote access. Results establish that low-effort telework integration provides measurable operational benefits while maintaining production quality. The framework addresses workforce shortages and operational flexibility requirements, providing foundations for advanced capabilities including predictive maintenance and automated monitoring.

The rapid evolution of augmented and mixed reality (AR/MR) technologies, coupled with the integration of multimedia experiences, is reshaping how users interact with their environments. While traditional handheld displays like smartphones and tablets have democratized access to AR/MR applications, new technologies such as Apple's Vision Pro, smart wearables, and tactile interfaces are setting the stage for enhanced multimodal interactions. These advancements come with their own set of challenges, including developing intuitive interaction techniques, creating seamless cross-device user experiences, and ensuring the effective integration of multimedia elements like sound, visuals, and haptics. Addressing these challenges, following our successful first workshop on "Experience 2.0 and Beyond" at EICS 2024, this second version of our workshop "Experience 2.0 and Beyond" provides a platform for researchers, developers, and practitioners to explore innovative solutions for engineering AR/MR applications that span devices and modalities from visuals to multimedia, fostering a future where immersive, interactive, and multimedia experiences are accessible to all.

Virtual Reality (VR) has seen widespread adoption across various fields in recent years. However, VR sickness remains a persistent issue despite advancements in head-mounted display technology. This study examines the effects of two factors: virtual environment size and upper body movement on VR sickness. Thirty-one participants played a game in which they navigated a mine cart through a cave with four different setups, varying the environment size (small vs. large cave) and the movement type (upper body movement vs. no movement). The results provide suggestions on how future computer games can be designed to reduce VR sickness.

Voice interaction is a valuable method for in-vehicle interactions, especially while driving. However, voice user interfaces (UIs) exhibit drawbacks, such as insufficient feedback, which negatively impact user experience. They also lack key usability heuristics, including visibility of system status and user control. Despite the long-standing presence of head-up displays (HUDs) in vehicles, there is still significant potential for such displays to enhance user experience and contribute to the development of next-generation infotainment systems. This paper proposes a multimodal approach to enhance the usability of voice UIs in vehicles by integrating visual interfaces on the HUD. We designed three visual UIs to support voice assistants. Furthermore, we conducted an expert evaluation based on usability heuristics to assess the three UIs effectiveness. The first UI, the Baseline UI, is the simplest. The second, the Flat Fusion UI, is a conventional design that uses a scrolling method to display additional information. The third, the AR Fusion UI, is a novel interface that employs a futuristic approach, leveraging real-world depth. The findings indicate that while usability varies among the three designs, they show promising results for future research. A user study is suggested to validate this paper's findings and to thoroughly evaluate the three UI designs.

In-vehicle voice assistants face usability challenges due to limitations in delivering feedback within the constraints of the driving environment. The presented study explores the potential of Rich Visual Feedback (RVF) on Head-Up Displays (HUDs) as a multimodal solution to enhance system usability. A user study with 32 participants evaluated three HUD User Interface (UI) designs: the AR Fusion UI, which integrates augmented reality elements for layered, dynamic information presentation; the Baseline UI, which displays only essential keywords; and the Flat Fusion UI, which uses conventional vertical scrolling. To explore HUD interface principles and inform future HUD design without relying on specific hardware, a simulated near-field overlay was used. Usability was measured using the System Usability Scale (SUS), and distraction was assessed with a penalty point method. Results show that RVF on the HUD significantly influences usability, with both content quantity and presentation style affecting outcomes. The minimal Baseline UI achieved the highest overall usability. However, among the two Fusion designs, the AR-based layered information mechanism outperformed the flat scrolling method. Distraction effects were not statistically significant, indicating the need for further research. These findings suggest RVF-enabled HUDs can enhance in-vehicle voice assistant usability, potentially contributing to safer, more efficient driving.

Part manufacturing is an important aspect of industrial production where automation allows a range of manufacturing processes to be completed without the need for manual human activities. Still, human tasks are essential to maintain consistent functioning and part quality. Thus, part production is vulnerable to reduced workforce restrictions (e.g., pandemics). Several technologies, like remote assistance and teleoperation, have the potential to enable new forms of collaboration based on interactive systems. We argue that, given the high complexity of the collaborations, high usability must be the primary priority during design. Research is needed to investigate how Human-Centered Design (HCD) might be used to build and implement collaborative systems that allow telework in complex industrial environments to deal with workforce reductions caused by pandemics or personnel shortages. Ultimately, the target should be a system that uses technology (e.g. Augmented Reality, AR) across devices and user types to counteract productivity and quality problems in reduced workforce situations.

This paper addresses the lack of Extended Reality (XR) applications in practice using an example of factory layout planning (FLP). With a comprehensive analysis we provide recommendations for choosing XR technologies (i.e., Mixed and Virtual Reality – MR/VR; handheld and head-mounted displays – HHDs/HMDs) across FLP use cases. For seamless transitions between use cases and recommended technologies, we implemented consistent object translation and rotation methods in a multi-user MR-HHD app for conceptual FLP and a VR-HMD app for detailed FLP. A pilot study demonstrated the spatial interaction technique’s learnability and applicability. While the participants found XR more useful in detailed versus conceptual FLP, both applications as well as the implemented manipulation constraints and visual abstractions were deemed intuitive to use. User feedback was translated into recommendations for collision prevention, training apps, object selection, and collaboration support. Along with the proposed extensions these results apply beyond FLP to various industries.

Robotic systems for several applications from healthcare to space explorations are being developed to handle different levels of autonomy – from working independently to working in collaboration with or under control by human operators. To ensure optimal human-robot cooperation, appropriate UIs are needed. In this context, applying Mixed Reality handheld displays (MR-HHDs), an ubiquitous tool for virtually augmenting reality, seems promising. As existing MR-HHD-UIs for robot control employ fatigue-prone and view-obstructing touch input, we propose controlling a robot arm via an enhanced MR-HHD-UI based on peripheral touch and device movement. Our detailed, comparative user study on usability and cognitive load demonstrates that the proposed MR-HHD-UI is a powerful tool for complementing the strengths of robots and humans. In our experiment, the MR-HHD-UI outperformed a Gamepad- and Desktop-UI in terms of temporal and cognitive demands and was rated as the preferred UI.

Today, augmented and mixed reality (AR/MR) are found very promising. Even current handheld displays, such as smartphones and tablets, can provide a wide and low budget access to such applications. New devices, like Apple's Vision Pro, smart tattoos(1) [8], interactive clothing, and wearables(2) propose an even higher immersion and are opening totally new exciting worlds for researchers, developers, and users. However, current research in this area faces many challenges, e.g., suitable interaction techniques, better user experience, navigation in MR environments, high cross-device UX, etc. These challenges are still limiting the usage of AR/MR application in real world activities. Targeting these challenges, our workshop will provide a platform for researchers, developers, and professionals to discuss issues and define novel methods and approaches suitable for developing the experience 2.0 and beyond: new interaction paradigms, user interfaces, 3D visualizations, and soundscapes, as well as applications for cross-device AR/MR.

A central element of industrial production is the manufacturing of finished parts from raw material. Even in highly automated environments, processes like milling still rely on human intervention. On-site human operators play a crucial role in ensuring the continuous operation and quality of parts through tasks such as setup and maintenance. This reliance on human involvement makes part manufacturing vulnerable to workforce reductions, whether due to unforeseen circumstances like pandemics or staff shortages. However, new modes of telework collaboration based on interactive systems that comprise visualization and communication technologies, collaborative robots, fast internet, and remote control of machine tools bear potential to overcome these challenges. In consequence, a conceptual framework is proposed that investigates how such modes and systems need to be designed to share the respective tasks between teleworking and on-site employees. As the interactions and systems show a high complexity and since reduced workforce situations often occur suddenly, a high degree of usability must be ensured to enable quick ramp-up and reliable operation. Therefore, an interdisciplinary approach between manufacturing engineering, ergonomics/human factors and human–computer interaction investigates how the concept of human-centered design (HCD) needs to be adapted to ensure this usability. While the initial study focuses on how to integrate human workers in the design of such a system, it also highlights the need to examine different collaboration modes and application scenarios.

Part manufacturing is a key element of industrial production, in which a variety of manufacturing processes can be performed without manual human activities due to automation. However, human tasks (e.g., machine setup and monitoring) are still required to ensure continuous operation and part quality. Thus, part manufacturing is susceptible to reduced workforce situations (e.g. pandemics). Several technologies potentially enable new modes of collaboration based on interactive systems (remote assistance, remote maintenance, collaborative robots, and teleoperation) where an on-site worker and/or collaborative robot collaborates with a qualified remote worker. Due to the high complexity of the collaborations, a high usability needs to be the predominant goal during design. The Human-Centered Design (HCD) approach, which has not previously been adapted for this purpose, provides a suitable foundation to overcome existing limitations. Therefore, research needs to investigate how HCD can be adapted to design and realize collaboration systems that enable telework in part manufacturing and similar complex industrial environments to handle workforce reductions due to pandemics or staff shortages.

Extended Reality (XR) technologies are still lacking appropriate interaction methods that enable users to seamlessly switch between different XR devices and degrees of virtuality. Addressing this gap, we present Move'n'Hold Pro - a set of consistent object manipulation techniques that are available for Mixed Reality handheld displays (MR-HHDs) as well as for Mixed and Virtual Reality headmounted displays (MR-/VR-HMDs). Move'n'Hold Pro extends MRand VR-HMDs with a tablet controller that implements object manipulation methods proposed by latest research on MR-HHD-UIs. Thereby, users can combine tablet movement and peripheral touch to translate or rotate virtual objects through direct or continuous manipulations. In our evaluation, comparing Move'n'Hold Pro to a State of the Art system, Move'n'Hold Pro was rated as the preferred system and to be easier to relearn. Furthermore, Move'n'Hold Pro reduced cognitive efforts, improved usability, and provided more cross-device benefits.

The Covid-19 pandemic has strongly increased the relevance of remote collaboration such that online meetings are now well-established in many companies. However, the corresponding tools usually fail to share 3D content. Although Extended Reality (XR) technologies are known to support exactly such purposes, they are rarely applied in practical settings as existing solutions are designed for specific use cases or hardware and hence lack scalability. In this paper, we investigate the scalability of awareness cues such as head- and hand-rays that are typically suggested to support communication in XR meeting spaces. Based on seven heuristics we identify scalability limitations of existing awareness cues such as incorrect representations of user behavior and visual information overload. Addressing these issues, we present four collaboration support features named AWARE S CUES which allow to individually activate awareness cues for nine different co-located and distributed collaboration styles involving head-mounted and handheld displays.

In a typical car-following scenario, target vehicle speed fluctuations act as an external disturbance to the host vehicle and in turn affect its energy consumption. To control a host vehicle in an energy-efficient manner using model predictive control (MPC), and moreover, enhance the performance of an ecological adaptive cruise control (EACC) strategy, forecasting the future velocities of a target vehicle is essential. For this purpose, a deep recurrent neural network-based vehicle speed prediction using long-short term memory (LSTM) and gated recurrent units (GRU) is studied in this work. Besides these, the physics-based constant velocity (CV) and constant acceleration (CA) models are discussed. The sequential time series data for training (e.g. speed trajectories of the target and its preceding vehicles obtained through vehicle-to-vehicle (V2V) communication, road speed limits, traffic light current and future phases collected using vehicle-to-infrastructure (V2I) communication) is gathered from both urban and highway networks created in the microscopic traffic simulator SUMO. The proposed speed prediction models are evaluated for long-term predictions (up to 10 s) of target vehicle future velocities. Moreover, the results revealed that the LSTM-based speed predictor outperformed other models in terms of achieving better prediction accuracy on unseen test datasets, and thereby showcasing better generalization ability. Furthermore, the performance of EACC-equipped host car on the predicted velocities is evaluated, and its energy-saving benefits for different prediction horizons are presented.

While handheld displays provide a widely available, low-budget access to Mixed Reality, developing appropriate interaction techniques remains challenging. For example, one-handed touch- and gestures-based methods are prone to fatigue and occlusion issues and two-handed device-based techniques are constrained to small-range manipulations or their pre-defined thresholds limit user control. In this paper, we introduce Move’n’Hold – a universally applicable interaction paradigm for translating and rotating virtual objects solely through a handheld display’s movement and peripheral touch. Move’n’Hold combines direct mapping between device and object manipulations when only left-thumb-touch is applied with automated repetitions of these initial manipulations that are started or stopped when right-thumb-touch is added or released. Hence, our technique allows switching individually between natural manipulation for small, precise movements and continuous manipulation for large, coarse movements. Our evaluation revealed Move’n’Hold as an intuitive and easy-to-learn input technique for multidimensional object translations and rotations. The technique also provides high scalability in terms of the distance, direction, complexity, and speed of manipulation. At the same time, it supports different user preferences and interaction styles. Our results further show that learning translation prior to rotation enhanced the overall user experience.

This special issue of the Behaviour & Information Technology journal covers six selected papers from the 33rd European Conference of Cognitive Ergonomics or just for short ECCE 2022 which was held October 4–7, 2022, in Kaiserslautern, Germany. The conference is the annual event of the European Association of Cognitive Ergonomics (EACE), and ECCE is the leading conference in human-media interaction and cognitive ergonomics. It provides an opportunity for both researchers and practitioners to exchange new ideas and practical experiences in a variety of domains. The special theme of ECCE 2022, Evaluating the Reality–Virtuality Continuum, is dedicated to a variety of research areas and applications that are encompassed by the so-called Reality-Virtuality continuum (Milgram and Kishino 1994; Milgram et al. 1995). These include systems that are used in real-world settings such as applications scaling from smart devices to large industrial setups, as well as Mixed Reality (MR) applications that integrate real and virtual objects and Virtual Reality (VR) applications that immerse users into purely virtual environments. ECCE 2022 features contributions from researchers and practitioners which address the broad spectrum of Cognitive Ergonomics challenges in the analysis, design, and evaluation of virtual and physical

In der industriellen und akademischen Forschung ist eine Vielzahl verschiedener Konzepte für Fahrsimulatoren zu finden. Das Spektrum reicht dabei von statischen „Low-End-Simulatoren“ bis zu sehr komplexen „High-End- Simulatoren“ mit hoher Dynamik und z.T. mehr als sechs Freiheitsgraden. Im vorliegenden Beitrag wird ein Fahrsimulator mit 6 Freiheitsgraden vorgestellt, der bei kompakter Bauform und hoher Kosteneffizienz, flexibelste Einsatzmöglichkeiten zur Simulation von Personen- und Nutzfahrzeugen sowie von mobile Arbeitsmaschinen eröffnet. Das Konzept des Simulators beinhaltet dabei die Realisierung offener Schnittstellen für möglichst viele Simulationswerkzeuge sowie die Anpassbarkeit des Simulatoraufbaus. Des Weiteren wird ein Virtual-Reality- Setup (VR-Setup) vorgestellt, das in die Simulatorumgebung integriert ist und eine Rundumprojektion des simulierten Szenarios mit begrenztem Hardware- Aufwand ermöglicht. Neben der Charakterisierung des Übertragungsverhaltens der Bewegungsplattform werden im vorliegenden Beitrag zwei Anwendungsfelder des Simulators vorgestellt. Die Themenfelder umfassen dabei einerseits die Betrachtung von Fahrkomfortaspekten und andererseits die Entwicklung energieeffizienzorientierter Fahrassistenzsysteme (EFAS).