Digital assistive technologies (ATs) have been widely used to support people with disabilities at work.However, many existing systems, interfaces, and tools remain inaccessible or insufficiently adaptable to the wide range of human abilities, particularly when cognitive, communicative, or sensory differences are involved.This gap is further exacerbated by what scholars and activists refer to as the disability divide: the sociotechnical disparity between people with and without disabilities in terms of access to, use of, and benefits from digital technologies.Despite increasing policy efforts and legal frameworks, vocational inclusion and training remains a significant challenge.By bringing together a diverse community, this workshop seeks to critically examine the role of digital ATs in advancing vocational inclusion for individuals with disabilities. CCS Concepts• Human-

Information disorder — including misinformation, disinformation, and malinformation — continues to undermine public discourse. Large language model (LLM)-based browser extensions show promise as tools for intervention, yet the role of publicly available tools in this space is not well understood. We conducted a scoping review of the Chrome Web Store and Firefox Add-Ons Store (May–July 2025), screening 951 records and including 34 extensions that use LLMs to process webpage content or user input. Through thematic analysis, we identified six interaction design concept categories: Extension Access, Display Mode, User Guidance, Customization, Content Understanding & Manipulation, and Navigation & Utilities. While extensions demonstrated diverse functionality and potential to debunk information disorder, they overwhelmingly operated as reactive tools, requiring explicit user initiation. Moreover, they rarely embedded themselves within webpage context. These findings reveal a “proactive gap” in current designs. Future LLM-powered extensions should move beyond responsiveness toward proactive, context-aware interventions that inoculate users against misinformation and strengthen critical thinking.

We present FallacyCheck, a proactive Large Language Model (LLM)-based browser extension designed to motivate the critical assessment of news articles by questioning logical fallacies. Existing LLM-based extensions are reactive, limiting their ability to inoculate users against information disorder. FallacyCheck overcomes this by proactively identifying logical fallacies, such as "Appeal to Emotion" and "Ad Hominem", and most importantly, motivating users to critically assess the article by posing them a thought-provoking, non-leading question in a contextual tooltip. This design, rooted in inoculation theory, prompts users toward meta-cognitive reflection on the argument’s logical structure. A preliminary evaluation with 16 highschool students showed the tool was perceived to be easy to use, and the questions helped to stimulate critical thinking. Crucially, participants generally would not have posed these critical questions without the tool’s support.

Research on transparency tools for information privacy has largely focused on users' perceptions of their usefulness-showing users prefer aggregated forms of data representation (e.g., interest segments) over hard-to-interpret raw data.However, users still do not understand what to learn from such interest segments.Representing a user's digital footprint as a user persona may serve as an effective way to communicate such information.Large Language Models (LLMs) show promise in dynamically presenting information in a way that can change user perceptions of complex issues-including privacy, personal data disclosure and user persona generation.We present PERSONÆR-a browser extension for LLM-based user persona generation from live website visits. CCS Concepts• Security and privacy → Usability in security and privacy; Social aspects of security and privacy; • Human-centered computing → Empirical studies in HCI.

Shared control in assistive robotics blends human autonomy with computer assistance, thus simplifying complex tasks for individuals with physical impairments. This study assesses an adaptive Degrees of Freedom control method specifically tailored for individuals with upper limb impairments. It employs a between-subjects analysis with 24 participants, conducting 81 trials across three distinct input devices in a realistic everyday-task setting. Given the diverse capabilities of the vulnerable target demographic and the known challenges in statistical comparisons due to individual differences, the study focuses primarily on subjective qualitative data. The results reveal consistently high success rates in trial completions, irrespective of the input device used. Participants appreciated their involvement in the research process, displayed a positive outlook, and quick adaptability to the control system. Notably, each participant effectively managed the given task within a short time frame.

With the ongoing efforts to empower people with mobility impairments and the increase in technological acceptance by the general public, assistive technologies, such as collaborative robotic arms, are gaining popularity. Yet, their widespread success is limited by usability issues, specifically the disparity between user input and software control along the autonomy continuum. To address this, shared control concepts provide opportunities to combine the targeted increase of user autonomy with a certain level of computer assistance. This paper presents the free and open-source AdaptiX XR framework for developing and evaluating shared control applications in a high-resolution simulation environment. The initial framework consists of a simulated robotic arm with an example scenario in Virtual Reality (VR), multiple standard control interfaces, and a specialized recording/replay system. AdaptiX can easily be extended for specific research needs, allowing Human-Robot Interaction (HRI) researchers to rapidly design and test novel interaction methods, intervention strategies, and multi-modal feedback techniques, without requiring an actual physical robotic arm during the early phases of ideation, prototyping, and evaluation. Also, a Robot Operating System (ROS) integration enables the controlling of a real robotic arm in a PhysicalTwin approach without any simulation-reality gap. Here, we review the capabilities and limitations of AdaptiX in detail and present three bodies of research based on the framework. AdaptiX can be accessed at https://adaptix.robot-research.de.

Robots are becoming increasingly omnipresent in our daily lives, supporting us and carrying out autonomous tasks. In Human-Robot Interaction, human actors benefit from understanding the robot’s motion intent to avoid task failures and foster collaboration. Finding effective ways to communicate this intent to users has recently received increased research interest. However, no common language has been established to systematize robot motion intent. This work presents a scoping review aimed at unifying existing knowledge. Based on our analysis, we present an intent communication model that depicts the relationship between robot and human through different intent dimensions (intent type, intent information, intent location). We discuss these different intent dimensions and their interrelationships with different kinds of robots and human roles. Throughout our analysis, we classify the existing research literature along our intent communication model, allowing us to identify key patterns and possible directions for future research.

Robotic solutions, in particular robotic arms, are becoming more frequently deployed for close collaboration with humans, for example in manufacturing or domestic care environments. These robotic arms require the user to control several Degrees-of-Freedom (DoFs) to perform tasks, primarily involving grasping and manipulating objects. Standard input devices predominantly have two DoFs, requiring time-consuming and cognitively demanding mode switches to select individual DoFs. Contemporary Adaptive DoF Mapping Controls (ADMCs) have shown to decrease the necessary number of mode switches but were up to now not able to significantly reduce the perceived workload. Users still bear the mental workload of incorporating abstract mode switching into their workflow. We address this by providing feed-forward multimodal feedback using updated recommendations of ADMC, allowing users to visually compare the current and the suggested mapping in real-time. We contrast the effectiveness of two new approaches that a) continuously recommend updated DoF combinations or b) use discrete thresholds between current robot movements and new recommendations. Both are compared in a Virtual Reality (VR) in-person study against a classic control method. Significant results for lowered task completion time, fewer mode switches, and reduced perceived workload conclusively establish that in combination with feedforward, ADMC methods can indeed outperform classic mode switching. A lack of apparent quantitative differences between Continuous and Threshold reveals the importance of user-centered customization options. Including these implications in the development process will improve usability, which is essential for successfully implementing robotic technologies with high user acceptance.

Nowadays, robots collaborate closely with humans in a growing number of areas. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, supporting people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior. This, however, is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their motion intent and comprehending how they ”think” about their actions. We work on solutions that communicate the cobots AI-generated motion intent to a human collaborator. Effective communication enables users to proceed with the most suitable option. We present a design exploration with different visualization techniques to optimize this user understanding, ideally resulting in increased safety and end-user acceptance.

Teleoperating industrial manipulators in co-located spaces can be challenging. Facilitating robot teleoperation by providing additional visual information about the environment and the robot affordances using augmented reality (AR), can improve task performance in manipulation and grasping. In this paper, we present two designs of augmented visual cues, that aim to enhance the visual space of the robot operator through hints about the position of the robot gripper in the workspace and in relation to the target. These visual cues aim to improve the distance perception and thus, the task performance. We evaluate both designs against a baseline in an experiment where participants teleoperate a robotic arm to perform pick-and-place tasks. Our results show performance improvements in different levels, reflecting in objective and subjective measures with trade-offs in terms of time, accuracy, and participants’ views of teleoperation. These findings show the potential of AR not only in teleoperation, but in understanding the human-robot workspace.

Assistive technologies such as human-robot collaboration, have the potential to ease the life of people with physical mobility impairments in social and economic activities. Currently, this group of people has lower rates of economic participation, due to the lack of adequate environments adapted to their capabilities. We take a closer look at the needs and preferences of people with physical mobility impairments in a human-robot cooperative environment at the workplace. Specifically, we aim to design how to control a robotic arm in manufacturing tasks for people with physical mobility impairments. We present a case study of a sheltered-workshop as a prototype for an institution that employs people with disabilities in manufacturing jobs. Here, we collected data of potential end-users with physical mobility impairments, social workers, and supervisors using a participatory design technique (Future-Workshop). These stakeholders were divided into two groups, primary (end-users) and secondary users (social workers, supervisors), which were run across two separate sessions. The gathered information was analyzed using thematic analysis to reveal underlying themes across stakeholders. We identified concepts that highlight underlying concerns related to the robot fitting in the social and organizational structure, human-robot synergy, and human-robot problem management. In this paper, we present our findings and discuss the implications of each theme when shaping an inclusive human-robot cooperative workstation for people with physical mobility impairments.

Interacting with the physical and digital environment multimodally enhances user flexibility and adaptability to different scenarios. A body of research has focused on comparing the efficiency and effectiveness of different interaction modalities in digital environments. However, little is known about user behavior in an environment that provides freedom to choose from a range of modalities. That is why, we take a closer look at the factors that influence input modality choices. Building on the work by Jameson & Kristensson, our goal is to understand how different factors influence user choices. In this paper, we present a study that aims to explore modality choices in a hands-free interaction environment, wherein participants can choose and combine freely three hands-free modalities (Gaze, Head movements, Speech) to execute point and select actions in a 2D interface. On the one hand, our results show that users avoid switching modalities more often than we expected, particularly, under conditions that should prompt modality switching. On the other hand, when users make a modality switch, user characteristics and consequences of the experienced interaction have a higher impact in the choice, than the changes in environmental conditions. Further, when users switch between modalities, we identified different types of switching behaviors. Users who deliberately try to find and choose an optimal modality (single switcher), users who try to find optimal combinations of modalities (multiple switcher), and a switching behavior triggered by error occurrence (error biased switcher). We believe that these results help to further understand when and how to design for multimodal interaction in real-world systems.

"Mensch ARgere Dich Nicht" is a Mixed Reality (MR) game based on a popular German board game "Mensch Ärgere Dich Nicht", from the early 1900s, similar to Pachisi. Developed to be a test bed for investigating mixed interactions, the application offers real and virtual variations of all core game elements (board, dice, pieces) for a fully modifiable experience. Using the Microsoft HoloLens, players can interact with the virtual game elements and receive additional information about the current game state. The game also recognizes interactions with real game elements and translates them into the virtual world.

The concept of Mixed Reality has existed in research for decades but has experienced rapid growth in recent years, mainly due to technological advances and peripherals such as the Microsoft HoloLens reaching the market. Despite this, certain design aspects of Mixed Reality experiences, such as the different nuances of real and virtual elements, remain largely unexplored.

Our research is concerned with designing support for ubiquitous access, organization, and interpretation of digital assets that users produce and store across multiple devices and computing platforms. Through a co-design study with scientists we identified specific aspects of conceptual maps they wish to create for their projects in order to make sense of diverse collections of digital media related to their individual and collective work. By the use of a technology probe called DeskPiles we observed the mechanisms involved in such a process. We identified the practice of using sub-document elements to compose the views of digital collections and diverse linking strategies to express semantic relations among concepts and ideas and to enable access to supporting digital assets. Our findings reveal the need to expand traditional information architectures and include (1) an extended range of content reference options and (2) transformation services to enable extraction, conversion, and linking of digital content. We advocate a granular and multi-format representation of content as the basis for reuse and ubiquitous access of digital media in diverse multi-device environments.

Recent findings from Embodied Cognition reveal strong effects of arm and hand movement on spatial memory. This suggests that input devices may have a far greater influence on users' cognition and users' ability to master a system than we typically believe -- especially for spatial panning or zooming & panning user interfaces. We conducted two experiments to observe whether multi-touch instead of mouse input improves users' spatial memory and navigation performance for such UIs. We observed increased performances for panning UIs but not for zooming & panning UIs. We present our results, provide initial explanations and discuss opportunities and pitfalls for interaction designers.

“Interactive spaces” are physical environments or rooms for collaborative work that are augmented with ubiquitous computing technology. Their purpose is to enable a computer-supported collaboration between multiple users that is based on a seamless use of different devices for natural “post-WIMP” interaction (e.g., multitouch walls, interactive tabletops, tablet PCs, or digital pen and paper). However, to this day, there are no well-established guidelines or toolkits for designing and implementing such distributed user interfaces (DUIs). Therefore, this article introduces the Zoomable Object-Oriented Information Landscape (ZOIL), a novel design approach and software framework for post-WIMP DUIs in interactive spaces. In the following, the ZOIL design principles are first introduced and illustrated. They provide recommendations and examples of DUI interaction design for interactive spaces. Then the different software patterns and architectures that have been employed for implementing the open-source ZOIL software framework are described. This framework facilitates the implementation of ZOIL's design principles in practice. Lessons learned from ZOIL's implementation are shared, and the implementation is discussed and compared with related work and approaches. The results of an evaluation of ZOIL with designers and developers conclude the article.

Application programming interfaces (APIs) are the interfaces to existing code structures, such as widgets, frameworks, or toolkits. Therefore, they very much do have an impact on the quality of the resulting system. So, ensuring that developers can make the most out of them is an important challenge. However standard usability evaluation methods as known from HCI have limitations in grasping the interaction between developer and API as most IDEs (essentially the GUI) capture only part of it. In this paper we present the Concept Map method to study the usability of an API over time. This allows us to elicit the mental model of a programmer when using an API and thereby identify usability issues and learning barriers and their development over time.

We introduce "Facet-Streams", a hybrid interactive surface for co-located collaborative product search on a tabletop. Facet-Streams combines techniques of information visualization with tangible and multi-touch interaction to materialize collaborative search on a tabletop. It harnesses the expressive power of facets and Boolean logic without exposing users to complex formal notations. Two user studies reveal how Facet-Streams unifies visual and tangible expressivity with simplicity in interaction, supports different strategies and collaboration styles, and turns product search into a fun and social experience.

MedioVis is a visual information seeking system that aims to support users' natural seeking behavior, particularly in complex information spaces. To achieve this goal we introduce multiple complementary visualization techniques together with an easy-to-use and consistent interaction concept. Over the last four years, MedioVis was developed in the context of digital libraries following a user-centered design process. The focus of this paper is the presentation of our interaction model and further to give an overview of the applied visualization techniques.

Previous research has shown that alphasliders are an effective tool for searching an alphabetically sorted list when only limited screen space is available for the graphical user interface. To improve user satisfaction, we propose equipping the widget with a novel text filter to dynamically limit the slider range. In this way, users are supported in locating target items and in identifying records that are missing. The results of a comparative user evaluation run on a personal digital assistant showed that 8 out of 12 participants preferred the filter widget to the classic interface. We further suggest an enhanced alphaslider design to speed up user interaction.

While zoomable user interfaces can improve the usability of applications by easing data access, a drawback is that some users tend to become lost after they have zoomed in. Previous studies indicate that this effect could be related to individual differences in spatial ability. To overcome such orientation problems, many desktop applications feature an additional overview window showing a miniature of the entire information space. Small devices, however, have a very limited screen real estate and incorporating an overview window often means pruning the size of the detail view considerably. Given this context, we report the results of a user study in which 24 participants solved search tasks by using two zoomable scatterplot applications on a PDA - one of the applications featured an overview, the other relied solely on the detail view. In contrast to similar studies for desktop applications, there was no significant difference in user preference between the interfaces. On the other hand, participants solved search tasks faster without the overview. This indicates that, on small screens, a larger detail view can outweigh the benefits gained from an overview window. Individual differences in spatial ability did not have a significant effect on task-completion times although results suggest that participants with higher spatial ability were slowed down by the overview more than low spatial-ability users.

Existing information-visualization techniques that target small screens are usually limited to exploring a few hundred items. In this article we present a scatterplot tool for Personal Digital Assistants that allows the handling of many thousands of items. The application's scalability is achieved by incorporating two alternative interaction techniques: a geometric-semantic zoom that provides smooth transition between overview and detail, and a fisheye distortion that displays the focus and context regions of the scatterplot in a single view. A user study with 24 participants was conducted to compare the usability and efficiency of both techniques when searching a book database containing 7500 items. The study was run on a pen-driven Wacom board simulating a PDA interface. While the results showed no significant difference in task-completion times, a clear majority of 20 users preferred the fisheye view over the zoom interaction. In addition, other dependent variables such as user satisfaction and subjective rating of orientation and navigation support revealed a preference for the fisheye distortion. These findings partly contradict related research and indicate that, when using a small screen, users place higher value on the ability to preserve navigational context than they do on the ease of use of a simplistic, metaphor-based interaction style.